Sadly, despite the highest per-capita health care spending in the world, our statistical life expectancy in the U.S. is declining for three years running. It's past time to address the issues of chronic disease at the root of this trend. But to do so, health insurance needs to take a few lessons from auto insurance.

Auto insurance companies regularly offer discounts for safe driving. Conversely, traffic accidents and speeding lead to rate increases. In addition, Car Insurance.com reports that a DUI can increase an individual's auto insurance rates anywhere from 80% to 371%.

Without these potential auto insurance policy rate increases, our roads would be less safe while being more expensive for the habitual safe and responsible drivers. Interestingly, nobody ever decries these traffic law and auto insurance policies as "nanny state" techniques.

Auto insurance rewards healthy driving while penalizing poor driving.

On the other hand, health insurance fails this sustainability test.

Via commercial insurance, Medicaid, and Medicare rates and taxes rise for everyone because of the unhealthy behavior of some while offering insignificant rewards for healthy behavior. This is a perfect recipe for financial unsustainability in any health-care system, let alone within the most expensive one on the planet.

So what is the health insurance equivalent of speeding or driving under the influence of drugs or alcohol? More importantly, what happens to an individual's health insurance premium for avoidable and well established behaviorally related health problems? Other than some rate adjustments for smoking nothing happens. Worse yet, as the total cost of care for a population increases from avoidable chronic disease states, health insurance rates for everyone increase. Plus, we pay more in taxes to fund Medicaid and Medicare.

The challenge in health insurance is to find a method to reward healthy behavior without driving up health insurance premiums for the chronically ill and those with unfortunate health-related events of no fault of their own.

We could offer relatively inexpensive health insurance to a healthy cohort of patients. Unfortunately, this policy would drastically increase health insurance rates for the sick and chronically ill. Given the extraordinary cost of health care in the United States, it is necessary to spread the cost of care over the majority of the population.

So how does a community, state, or nation rise to the challenge and find a mechanism to reward healthy behavior while disincentivizing unhealthy behavior? An advanced society with affordable health insurance will boldly address this challenge.

The answer lies in the ability to utilize the health insurance equivalents of speeding or reckless driving. Fortunately for us, the Centers for Disease Control or CDC has already accumulated the necessary data. The CDC has identified the most costly behaviors relevant to health insurance: the use of tobacco, alcohol, and sugar-based beverages. As per the CDC, the United States' health care system spends over $700 billion per year treating acute and chronic disease related to the use of these products.

In effect, the "safe drivers" among us are paying this annual $700 billion tab. It's time for a refund. We must begin rewarding healthy behavior in health insurance. Currently, the cost of public and private health insurance includes the cost of caring for many chronic diseases caused by human behavior. The public can smoke, vape, drink, chew, eat and ingest a well-documented variation of unhealthy products. Correspondingly, the price of health insurance increases for everyone.

This is why the largest physician organization in the state of Colorado has enacted policy that could help Colorado lead the nation in addressing the chronic disease epidemic. In November, the Colorado Medical Society voted to support increased taxes on alcohol, tobacco, and sugar-based beverages as long as those taxes be used to address the high cost of health care by addressing chronic disease where it starts and by rewarding those who choose a healthy lifestyle. The Mesa County Medical Society led the charge.

The policy does not support taxes on these products if the revenue is allowed to go to the general fund. If revenue is used for prevention and reducing premiums, there is a healthy return on investment for a Colorado consumer who chooses a healthy lifestyle. It is a tax that is then returned to the well- deserved healthy consumer of health insurance.

This tax policy works like our traffic laws. Healthy living is rewarded while we simultaneously work to reduce the rate and ill effects of unhealthy behavior. And, at the same time, we preserve the insurance pools such that health insurance rates don't go up for the chronically ill with "no-fault" health problems.

With enough support, Colorado could pilot this innovative health policy design for a nation in desperate need of more value per health care dollar.

To learn more, view Dr. Pramenko's TED Talk: "Marketing Healthy Behavior."

Michael J. Pramenko M.D. is the executive director of Primary Care Partners. He is chairman of the Board of Monument Health and is a past president of the Colorado Medical Society.

See the rest here:
How can the health-care system reward healthy behavior? - The Grand Junction Daily Sentinel

I've been thinking about suicide. Not for myself, mind you, but because it's such an evolutionary puzzle. After all, even though evolutionary biologists know full well that no complex human behavior is rigidly and unilaterally determined by genes alone, it remains a well established article of faith that even complex human behavior has at least some underlying genetic component. (Is it an oxymoron, by the way, to suggest that an "article of faith" can be "well established," given thata reasonable definition of faith is belief without evidence? Oh well, that's another question, for another time!)

The suicide puzzle is simple enough to state: any genetically influenced phenotype including behavior that leads to elimination of the genetic factors themselves should be strongly selected against. And yet, suicide appears to be a cross-culturaluniversal. According to the World Health Organization it is the 10th leading cause of deathworldwide, responsible for nearly 1.5 million annual fatalities.

Freud was convinced that the answer, essentially, was "Thanatos," which was among his most crackpot and biologically ignorant theories. Although the word doesn't appear directly in his writings, "death drive" (Todestrieb) does, and is ostensibly opposed to "Eros," the "life drive." In Beyond the Pleasure Principle, Freud maintained that living things possess"an urge ...to restore an earlier state of things," specifically that inorganic simplicity from which all living things emerged. It is a force"whose function is to assure that the organism shall follow its own path to death." This "explanation" is total BS, reminiscent of Henri Bergson's notion that life is due to an "lan vitale," which Julian Huxley caricatured as being equivalent to explaining the movement of a railroad train by its "lan locomotif."

It is plausible that natural selection could favor suicide if, by doing so, predisposing genes were benefiting identical copies of the same genes residing in other bodies namely, in genetic relatives andthus operating by the well-established phenomenon of kin selection, or inclusive fitness. This process hasalready been demonstrated to be a powerful explanation for "altruism" in many animals, both nonhuman and human. But what about cases where this explanation doesn't apply, namely individuals whose death benefits no one, genetic relative or not?

Emile Durkheim, one of the founders of sociology, made an important contribution in his classicbook, Suicide. In it, he identified five distinct social explanations for self-killing: egoistic, altruistic, anomic, and fatalistic, each worth understanding, but none providing any reconciliation with evolution by natural selection.

Some biological coherence, on the other hand,appears to derivefrompathology. Many people die of heart disease or cancer, not because doing so is adaptive, but becausein various ways, our bodies arevulnerable, just like any organism. Similarly, there arealso mental pathologies,notably depresion, due to biochemical malfunctions, among other things. Powerful evidence for this and for not beingcavalier about suicide comes from the fact that antidepressant medications and/or psychotherapy often abolishsuicidality.

Beyond this, however, are cases in which suicide is not precipitated by depression per se. And that's where my hypothesis comes in. Start with pain,a biological warning signal that something isout of whack. Accordingly,living things, including people, have doubtless been selected to minimize painand to avoid it when possible. (For example, it is pain thathelps prevent us from embracing a hot stove.) Then add two consequences of our big, smart brains: knowledge of death, and of killing.

There is much debate about the evolutionary pressures that made us so clever, but no doubt that our species hasbecomevery, veryintelligent. And furthermore, it seems likely that at least some of ourmental abilities e.g., painting, composing symphonies, programming computers, playing the violin weren't selected for directly but arose as a by-product of a creative intellect that was favored because it conveyed other, more clear-cut benefits, such as social cooperation, complex communication, and so forth.

I suggest that as a byproduct, human beings perhaps alone among living things understand about death.(Shades of Ernest Becker.) We don't simply act in most cases to avoid death; our speciesunderstands that it means the cessation of life, and thus, of all sensation not just the end of pleasure, but also of pain. Finally, due once again to our big brains, we have figured out how to end life: not only the lives of prey or other people, but also, by simple extrapolation, our own.

Put these three observations together: (1) people are strongly predisposed to avoid pain, (2) our speciescomprehends that death meansthe end ofbodily sensation, and (3) we know how to kill, including how to kill ourselves. Couldn't the result then be that when individual Homo sapiens experience unrelenting and untreatable pain (physical or emotional)they, unique among living things, can be inclined to endthat pain? Other animals sometimes behave in a way that results in their death: Honeybees die when they sting an intruder to their hive, Pacific salmon die after spawning, and so forth. But there is no reason to think that they are intentionally killing themselves. We, on occasion, are different.

The above considerations are neither intendedto condone suicidenor to oppose it. Moreover,I am not proposing that myhypothetical triad explains more than a subset of suicide, which is doubtless multi-factorialand differs for different people. In addition, this difficult and complex topic is immense, such that perhaps thethree-part biologically based hypothesis presented here isn't even valid. Or new. But maybe it's at least worth thinking about.

David P. Barash is professor of psychology emeritus at the University of Washington. Among his recent books is Through a Glass Brightly: using science to see our species as we really are (2018, Oxford University Press)

See the rest here:
Thinking About Suicide: A Three-Part Hypothesis - Psychology Today

Humans have both intelligent and "stupid" behavior, should self-driving cars be likewise?

When someone says that another person is intelligent, you pretty much assume that this is a praising of how smart or bright the other person might be.

In contrast, if someone is labeled as being stupid, there is a reflexive notion that the person is essentially unintelligent. Generally, the common definition of being stupid is that stupidity consists of a lack of intelligence.

This brings up a curious aspect.

Suppose we somehow had a bucket filled with intelligence. We are going to pretend that intelligence is akin to something tangible and that we can essentially pour it into and possibly out of a bucket that we happen to have handy.

Upon pouring this bucket filled with intelligence onto say the floor, what do you have left?

One answer is that the bucket is now entirely empty and there is nothing left inside the bucket at all. The bucket has become vacuous and contains absolutely nothing.

Another answer is that the bucket upon being emptied of intelligence has a leftover that consists of stupidity. In other words, once youve removed so-called intelligence, the thing that you have remaining is stupidity.

I realize this is a seemingly esoteric discussion but, in a moment, youll see that the point being made has a rather significant ramification for many important things, including and particularly for the development and rise of Artificial Intelligence (AI).

Ponder these weighty questions:

Can intelligence exist without stupidity, or in a practical sense is there always some amount of stupidity that must exist if there is also the existence of intelligence?

Some assert that intelligence and stupidity are a zen-like yin and yang.

In this perspective, you cannot grasp the nature of intelligence unless you also have a semblance of stupidity as a kind of measuring stick.

It is said that humans become increasingly intelligent over time, and thus are reducing their levels of stupidity. You might suggest that intelligence and stupidity are playing a zero-sum game, namely that as your intelligence rises you are simultaneously reducing your level of stupidity (similarly, if perchance your stupidity rises, this implies that your intelligence lowers).

Can humans arrive at a 100% intelligence and a zero amount of stupidity, or are we fated to always have some amount of stupidity, no matter how hard we might try to become fully intelligent?

Returning to the bucket metaphor, some would claim that there will never be the case that you are completely and exclusively intelligent and have expunged stupidity. There will always be some amount of stupidity thats sitting in that bucket.

If you are clever and try hard, you might be able to narrow down how much stupidity you have, though nonetheless there is still some amount of stupidity in that bucket, albeit perhaps at some kind of minimal state.

Does having stupidity help intelligence or is it harmful to intelligence?

You might be tempted to assume that any amount of stupidity is a bad thing and therefore we must always be striving to keep it caged or otherwise avoid its appearance.

But we need to ask whether that simplistic view of tossing stupidity into the bad category and placing intelligence into the good category is potentially missing something more complex. You could argue that by being stupid, at times, in limited ways, doing so offers a means for intelligence to get even better.

When you were a child, suppose you stupidly tripped over your own feet, and after doing so, you came to the realization that you were not carefully lifting your feet. Henceforth, you became more mindful of how to walk and thus became intelligent at the act of walking. Maybe later in life, while walking on a thin curb, you managed to save yourself from falling off the edge of the curb, partially due to the earlier in life lesson that was sparked by stupidity and became part of your intelligence.

Of course, stupidity can also get us into trouble.

Despite having learned via stupidity to be careful as you walk, one day you decide to strut on the edge of the Grand Canyon. While doing so, oops, you fall off and plunge into the chasm.

Was it an intelligent act to perch yourself on the edge like that?

Apparently not.

As such, we might want to note that stupidity can be a friend or a foe, and it is up to the intelligence portion to figure out which is which in any given circumstance and any given moment.

You might envision that there is an eternal struggle going on between the intelligence side and the stupidity side.

On the other hand, you might equally envision that the intelligence side and stupidity side are pals, each of which tugs at the other, and therefore it is not especially a fight as it is a delicate dance and form of tension about which should prevail (at times) and how they can each moderate or even aid the other.

This preamble provides a foundation to discuss something increasingly becoming worthy of attention, namely the role of Artificial Intelligence and (surprisingly) the role of Artificial Stupidity.

Thinking Seriously About Artificial Stupidity

We hear every day about how our lives are being changed via the advent of Artificial Intelligence.

AI is being infused into our smartphones, and into our refrigerators, and into our cars, and so on.

If we are intending to place AI into the things we use, it begs the question as to whether we need to consider the yang of the yin, specifically do we need to be cognizant of Artificial Stupidity?

Most people snicker upon hearing or seeing the phrase Artificial Stupidity, and they assume it must be some kind of insider joke to refer to such a thing.

Admittedly, the conjoining of the words artificial and stupidity seems, well, perhaps stupid in of itself.

But, by going back to the earlier discussion about the role of intelligence and the role of stupidity as it exists in humans, you can recast your viewpoint and likely see that whenever you carry on a discussion about intelligence, one way or another you inevitably need to also be considering the role of stupidity.

Some suggest that we ought to use another way of expressing Artificial Stupidity to lessen the amount of snickering that happens. Floated phrases include Artificial Unintelligence, Artificial Humanity, Artificial Dumbness, and others, none of which have caught hold as yet.

Please bear with me and accept the phrasing of Artificial Stupidity and also go along with the belief that it isnt stupid to be discussing Artificial Stupidity.

Indeed, you could make the case that the act of not discussing Artificial Stupidity is the stupid approach, since you are unwilling or unaccepting of the realization that stupidity exists in the real world and therefore in the artificial world of computer systems that are we attempting to recreate intelligence, you would be ignoring or blind to what is essentially the other half of the overall equation.

In short, some say that true Artificial Intelligence requires a combining of the smart or good AI that we think of today and the inclusion of Artificial Stupidity (warts and all), though the inclusion must be done in a smart way.

Indeed, lets deal with the immediate knee jerk reaction that many have of this notion by dispelling the argument that by including Artificial Stupidity into Artificial Intelligence you are inherently and irrevocably introducing stupidity and presumably, therefore, aiming to make AI stupid.

Sure, if you stupidly add stupidity, you have a solid chance of undermining the AI and rendering it stupid.

On the other hand, in recognition of how humans operate, the inclusion of stupidity, when done thoughtfully, could ultimately aid the AI (think about the story of tripping over your own feet as a child).

Heres something that might really get your goat.

Perhaps the only means to achieve true and full AI, which is not anywhere near to human intelligence levels to-date, consists of infusing Artificial Stupidity into AI; thus, as long as we keep Artificial Stupidity at arms length or as a pariah, we trap ourselves into never reaching the nirvana of utter and complete AI that is able to seemingly be as intelligent as humans are.

Ouch, by excluding Artificial Stupidity from our thinking, we might be damming ourselves to not arriving at the pinnacle of AI.

Thats a punch to the gut and so counter-intuitive that it often stops people in their tracks.

There are emerging signs that the significance of revealing and harnessing artificial stupidity (or whatever it ought to be called), can be quite useful.

At a recent talk sponsored by the Simons Institute for the Theory of Computing at the University of California Berkeley, I chatted with MIT Professor Andrew Lo and discussed his espoused clever inclusion of artificial stupidity into improving financial models, which he has done in recognition that human foibles need to be appropriately recognized and contended with in the burgeoning field of FinTech.

His fascinating co-authored book A Non-Random Walk Down Wall Street is an elegant look at how human behavior is composed of both rationality and irrationality, giving rise to his theory, coined as the Adaptive Markets Hypothesis. His insightful approach goes beyond the prevailing bounds of how financial trading marketplaces do and can best operate.

Are there other areas or applications in which the significance of artificial stupidity might come to play?

Yes.

One such area, I assert, involves the inclusion of artificial stupidity into the advent of true self-driving cars.

Shocking?

Maybe so.

Lets unpack the matter.

Exploiting Artificial Stupidity For Gain

When referring to true self-driving cars, Im focusing on Level 4 and Level 5 of the standard scale used to gauge autonomous cars. These are self-driving cars that have an AI system doing the driving and there is no need and typically no provision for a human driver.

The AI does all the driving and any and all occupants are considered passengers.

On the topic of Artificial Stupidity, it is worthwhile to quickly review the history of how the terminology came about.

In the 1950s, the famous mathematician and pioneering computer scientist Alan Turing proposed what has become known as the Turing test for AI.

Simply stated, if you were presented with a situation whereby you could interact with a computer system imbued with AI, and at the same time separately interact with a human too, and you werent told beforehand which was which (lets assume they are both hidden from view), upon your making inquiries of each, you are tasked with deciding which one is the AI and which one is the human.

We could then declare the AI a winner as exhibiting intelligence if you could not distinguish between the two contestants. In that sense, the AI is indistinguishable from the human contestant and must ergo be considered equal in intelligent interaction.

There are some holes in this logic, which I provide a detailed analysis of here, in any case, the Turing test is widely used as a barometer for measuring whether or when AI might be truly achieved.

There is a twist to the original Turing test that many dont know about.

One qualm expressed was that you might be smarmy and ask the two contestants to calculate say pi to the thousandth digit.

Presumably, the AI would do so wonderfully and readily tell you the answer in the blink of an eye, doing so precisely and abundantly correctly. Meanwhile, the human would struggle to do so, taking quite a while to answer if using paper and pencil to make the laborious calculation, and ultimately would be likely to introduce errors into the answer.

Turing realized this aspect and acknowledged that the AI could be essentially unmasked by asking such arithmetic questions.

He then took the added step, one that some believe opened a Pandora's box, and suggested that the AI ought to avoid giving the right answers to arithmetic problems.

In short, the AI could try to fool the inquirer by appearing to answer as a human might, including incorporating errors into the answers given and perhaps taking the same length of time that doing the calculations by hand would take.

Starting in the early 1990s, a competition was launched that is akin to the Turing test, offering a modest cash prize and has become known as the Loebner Prize, and in this competition the AI systems are typically infused with human-like errors to aid in fooling the inquirers into believing the AI is the human. There is controversy underlying this, but I wont go into that herein. A now-classic article appeared in 1991 in The Economist about the competition.

Notice that once again we have a bit of irony that the introduction of stupidity is being done to essentially portray that something is intelligent.

This brief history lesson provides a handy launching pad for the next elements of this discussion.

Lets boil down the topic of Artificial Stupidity into two main facets or definitions:

1)Artificial Stupidity is the purposeful incorporation of human-like stupidity into an AI system, doing so to make the AI seem more human-like, and being done not to improve the AI per se but instead to shape the perception of humans about the AI as being seemingly intelligent.

2)Artificial Stupidity is an acknowledgment of the myriad of human foibles and the potential inclusion of such stupidity into or alongside the AI in a conjoined manner that can potentially improve the AI when properly managed.

One common misnomer that Id like to dispel about the first part of the definition involves a somewhat false assumption that the computer potentially is going to purposefully miscalculate something.

There are some that shriek in horror and disdain that there might be a suggestion that the computer would intentionally seek to incorrectly do a calculation, such as figuring out pi but doing so in a manner that is inaccurate.

Thats not what the definition necessarily implies.

It could be that the computer might correctly calculate pi to the thousandth digit, and then opt to tweak some of the digits, which it would say keep track of, and do this in a blink of the eye, and then wait to display the result after an equivalent of human-by-hand amount of time.

In that manner, the computer has the correct answer internally and has only displayed something that seems to have errors.

Now, that certainly could be bad for the humans that are relying upon what the computer has reported but note that this is decidedly not the same as though the computer has in fact miscalculated the number.

Theres more to be said about such nuances, but for now lets continue forward.

Both of those definitional variants of Artificial Stupidity can be applied to true self-driving cars.

Doing so carries a certain amount of angst and will be worthwhile to consider.

Artificial Stupidity And True Self-Driving Cars

Todays self-driving cars that are being tried out on our public roadways have already gotten a somewhat muddled reputation for their stylistic driving prowess. Overall, driverless cars to-date are akin to a novice teenage driver that is timid and somewhat hesitant about the driving task.

For example, when you encounter a self-driving car, it will often try to create a large buffer zone between it and the car ahead, attempting to abide by the car lengths rule-of-thumb that you were taught when first learning to drive.

Human drivers generally dont care about the car lengths safety zone and edge up on other cars, doing so to their own endangerment.

Heres another example of such driving practices.

Upon reaching a stop sign, a driverless car will usually come to a full and complete stop. It will wait to see that the coast is clear, and then cautiously proceed. I dont know about you, but I can say that where I drive, nobody makes complete stops anymore at stop signs. A rolling stop is the norm nowadays.

You could assert that humans are driving in a reckless and somewhat stupid manner.

By not having enough car lengths between your car and the car ahead, you are increasing your chances of a rear-end crash. By not fully stopping at a stop sign, you are increasing your risks of colliding with another car or a pedestrian.

In a Turing test manner, you could stand on the sidewalk and watch cars going past you, and by their driving behavior alone you could likely ascertain which are the self-driving cars and which are the human-driven cars.

Does that sound familiar?

It should, since this is roughly the same as the arithmetic precision issue earlier raised.

How to solve this?

One approach would be to introduce Artificial Stupidity as defined above.

First, you could have the on-board AI purposely shorten the car's buffer distance settings to cause it to drive in a similar manner as humans do (butting up to other cars). Likewise, the AI could be modified to roll through stop signs. This is all rather easily arranged.

Humans watching a driverless car and a human-driven car would no longer be able to discern one such car from the other since they both would be driving in the same error-laden way.

Link:
Artificial Stupidity Could Be The Crux To AI And Achieving True Self-Driving Cars - Forbes

This color-coded map shows global surface temperature anomalies. Higher-than-normal temperatures are shown in red, and lower-than-normal temperatures are shown in blue.

The computer models used over the past five decades to predict the impact of future global warming have turned out to be very accurate so far, a new study has found.

Climate scientists at the University of California, Berkeley, Massachusetts Institute of Technology and NASA evaluated climate models from the early 1970s into the late 2000s to see how well they predicted the actual global mean surface temperature, based on levels of carbon dioxide and other greenhouse gases.

They also looked at how well the models matched the relationship between warming and changes in levels of greenhouse gases.

Of the 17 climate projections examined, 14 effectively matched observations after they were published, according to the study published Wednesday in the journal Geophysical Research Letters.

Estimating how much greenhouse gas will be emitted in the future is difficult because it involves human behavior, how well the economy is doing and government policy. Rolling back emission regulations on new cars, for example, adds more carbon dioxide to the atmosphere.

"We did not focus on how well their crystal ball predicted future emissions of greenhouse gases, because that is a question for economists and energy modelers, not climate scientists," Zeke Hausfather, a UC Berkeley doctoral student and lead author of the study, said in a news release. "It is impossible to know exactly what human emissions will be in the future. Physics we can understand, it is a deterministic system; Future emissions depend on human systems, which are not necessarily deterministic."

So, according to Gizmodo's Earther blog, the researchers put the actual amount of global greenhouse emissions into the models to see if they would accurately predict global temperature rise since the models were created.

That found the models were quite accurate.

"The earliest models were so skillful because the fundamental science behind the greenhouse effect and global warming is well established and fairly straightforward," Henri Drake, a co-author of the study and an MIT doctoral student, told Mashable.

"The real message is that the warming we have experienced is pretty much exactly what climate models predicted it would be as much as 30 years ago," Hausfather said. "This really gives us more confidence that today's models are getting things largely right as well."

The Weather Companys primary journalistic mission is to report on breaking weather news, the environment and the importance of science to our lives. This story does not necessarily represent the position of our parent company, IBM.

Read this article:
Early Climate Models Have Accurately Predicted Effects of Global Warming: Study - The Weather Channel

Heres what happened under the Gold Dome on Thursday (December 5th):

Michael L. Testa, Jr. was sworn in as a member of the Senate for the 1st Legislative District.

SENATE ACTION (QUORUM)

Nominations Received and Referred to SJU:

TO BE A JUDGE OF THE SUPERIOR COURT:

Honorable James P. Wilson, J.S.C., of Plainfield.

Honorable Stephen J. Taylor, J.S.C., of Skillman.

Honorable Daniel R. Lindemann, J.S.C., of Wayne.

Honorable Jeffrey R. Jablonski, J.S.C., of Kearny.

Honorable Mitzy Galis-Menendez, J.S.C., of Cliffside Park.

Honorable Marlene Lynch Ford, J.S.C., of Seaside Park.

Honorable Angela White Dalton, J.S.C., of Howell.

Honorable Bradford M. Bury, J.S.C., of Watchung.

TO BE A MEMBER OF THE DELAWARE RIVER JOINT TOLL BRIDGE COMMISSION:

William E. Mandry, of Phillipsburg, to replace Garret Leonard VanVliet.

Nominations Withdrawn:

TO BE A MEMBER OF THE DELAWARE RIVER JOINT TOLL BRIDGE COMMISSION:

Philip J. Mugavero, of Phillipsburg, to replace Garret Leonard VanVliet.

Nomination Corrected Copy:

TO BE A MEMBER OF THE SITE REMEDIATION PROFESSIONAL LICENSING BOARD:

Michael J. Renzulli, of Upper Freehold Township *NOT* Robbinsville, to replace Constantine Tsentas.

Bills Introduced:

S4264 Pou,N William J Pascrell Jr. Highway-designates State Highway Route 19 REF STR

S4265 Bucco,A/OScanlon,D+1 Autistic person-voluntarily make notation on drivers lic, ID card & MV registry REF STR

S4266 Corrado,K Opioid antidote, administered-require involuntary commitment REF SHH

S4267 Cruz-Perez,N State contract award-bidder ineligible to receive if current contract in dispute REF SSG

S4268 Pou,N Cable television-incl cert fees/charges for svc in advertised price to consumers REF SCM

S4269 Weinberg,L Marriage license application-revises form, permit changes in middle and surname REF SJU

S4270 Gopal,V Energy efficiency standards-adopt for general service incandescent lamps REF SEN

S4271 Gopal,V Community College Opportunity Grant program-extend to volunteer emerg responders REF SHI

S4272 Cruz-Perez,N Municipal Rehabilitation and Economic Recovery Act-extend economic recovery term REF SCU

S4273 Gopal,V Disabled person-DEP required to develop beach accessibility guidelines REF SEN

S4274 Greenstein,L Integrated Case Management Services Program-DHS take certain measures concerning REF SHH

S4275 Smith,B Class I renewable energy-allows BPU to increase cost to customers 2022 thru 2024 REF SEN

S4276 Corrado,K Agriculture Development Committee-farmland preservation purposes;$31.153M REF SEN

S4277 Greenstein,L CBT revenues to St. Agric Devel Committee-mun planning incentive farmland grants REF SEN

S4278 Greenstein,L CBT revenues to St. Agric Devel Committee-co. planning incentive farmland grants REF SEN

S4279 Smith,B CBT rev. to State Agric Devel Committee-non-profit organizations farmland grants REF SEN

S4280 Ruiz,M Domestic violence orders-requires to be issued in other languages REF SJU

S4281 Smith,B Piscataway Regional Day School-requires State to sell land and improvements REF SSG

S4285 Sarlo,P SPRS member, 9/11 WTC-provides death benefits to surviving spouses & children REF SBA

S4287 Pou,N Insurance group-submit Corporate Governance Annual Disclosure to DOBI REF SCM

S4288 Singleton,T Homestead property tax reimbursement-proportionate owner collect entire amount REF SCU

S4289 Sweeney,S/Thompson,S Tax levy cap adjustment 2020-2021 thru 2024-2025-sch. districts losing State aid REF SBA

S4296 Pou,N/Sweeney,S+1 Health service corporation-reorganize into a mutual holding company system REF SCM

S4305 Sweeney,S Lobbyists-disclose professional services and filings w/State regulatory agencies REF SSG

Bills Recommitted:

S4204 ScaSca (2R) Sweeney,S Wages and hour and unemployment status-concerns employment status of individuals RCM SLA

Bills Reported from Committee/Given 2nd Reading:

A268 Kean,S/Egan,J+2 P.I.C.K. Awareness Act-authorize special license plate to support recovery REP

A442 AcaSca (2R) Schaer,G/Freiman,R+4 Revenue Advisory Board-establish, provide consensus revenue forecasting advice REP

A1582 AcaAcsScaSca (ACS/2R) Conaway,H/Moriarty,P+9 Dietetics and Nutrition Licensing Act-establish REP/SCA

A2431 Acs (ACS) Benson,D/Jimenez,A+13 Prescr. drug coverage-health insurers prov plans that limit patient cost-sharing REP

A3979 AcsSca (ACS/1R) Lopez,Y/Vainieri Huttle,V+10 Dignity for Incarcerated Primary Caretaker Parents Act REP/SCA

A4493 Aca (1R) Pinkin,N/Conaway,H Sexually transmitted disease-expedite partner therapy for treatment REP

A4608 Sca (1R) Zwicker,A/Downey,J+3 Behavior Analyst Lic Act-produce socially significant human behavior improvement REP/SCA

A5037 AcaAca (2R) Pintor Marin,E/Speight,S+4 Drugs, counterfeit-enhance penalties REP

A5802 Aca (1R) Greenwald,L/Downey,J+16 Family planning services-makes FY2020;$9.5M REP

S48 Sca (1R) Pou,N/Turner,S+1 Juvenile incarceration and parole-imposes restrictions REP/SCA

S469 Singer,R/Gopal,V+1 P.I.C.K. Awareness Act-authorize special license plate to support recovery REP

S618 Scs (SCS) Gordon,R/Oroho,S+2 State revenue estimating and reporting processes-reforms annual REP/SCS

S974 Singleton,T/Kean,T+3 Spinal muscular atrophy-requires newborn infants be screened REP

S993 Sca (1R) Vitale,J Sexually transmitted disease-expedite partner therapy for treatment REP

S1155 Ruiz,M/Rice,R+1 Property, vacant and abandoned-requires registration with municipalities REP

S1865 Scs (SCS) Weinberg,L/Kean,T+1 Prescr. drug coverage-health insurers prov plans that limit patient cost-sharing REP

S2448 Sca (1R) Diegnan,P/Singleton,T+2 Veterans and their spouses-waives certain prof. and occupational licensing fees REP

S2449 Sca (1R) Diegnan,P+2 Veterans and their spouses-waives commercial driver license fees REP

S2540 ScsSca (SCS/1R) Greenstein,L/Cruz-Perez,N+1 Dignity for Incarcerated Primary Caretaker Parents Act REP/SCA

S2625 ScsSca (SCS/1R) Weinberg,L/Ruiz,M Dietetics and Nutrition Licensing Act-establish REP/SCA

S2776 ScsScs (SCS) Smith,B/Greenstein,L+2 Plastic carryout bags, polystyrene & single-use straws-prohibits use REP/SCS

S2897 Madden,F/Singer,R+1 Mold hazard-DCA required to establish procedures for inspection and abatement REP

S2930 Bucco,A/Beach,J+1 Insurance producer licensing fee-exempts honorable discharged mil veterans REP

S3023 Sca (1R) Greenstein,L+2 Probation officers-union officials who represent participate in union activities REP/SCA

S3099 ScaScs (SCS) Weinberg,L/Kean,T+1 Behavior Analyst Lic Act-produce socially significant human behavior improvement

REP/SCS

S3170 ScaSca (2R) Cryan,J/Pou,N+3 Plant closings, mass layoffs-incr. prenotification time & requires severance pay REP/SCA

S3357 Sca (1R) Cunningham,S/Weinberg,L+3 Liberty St. Park Protection Act; estab. Advisory Committee & DEP related actions

REP/SCA

S3457 Sweeney,S/Andrzejczak,B+5 Hooked on Fishing-Not on Drugs Program;$450K REP

S3471 ScsSca (SCS/1R) Andrzejczak,B/Greenstein,L+2 Drugs, counterfeit-enhance penalties REP/SCA

S3759 Sca (1R) Addiego,D/Corrado,K+1 Special education unit-create within Office of Admin. Law; require annual report REP/SCA

S3870 Sarlo,P Sewerage systems, municipal-authorize alternative procedure for sale to pub util REP

S3920 Sca (1R) Pou,N Manufacturing fac-concern provisions of energy by prov cert energy related taxes REP/SCA

S3954 Oroho,S/Singleton,T+2 Labor Law Enforcement-establishes office REP

S4024 Pou,N William Paterson University;$2M REP

S4035 Pou,N/Singleton,T+1 Thomas Edison State University;$1.7M REP

S4083 Weinberg,L/Lagana,J.A. Bright side Manor, Teaneck-fund capital improvement costs;$1.5M REP

S4103 Sca (1R) Sweeney,S/Weinberg,L+1 Family planning services-makes FY2020;$9.5M REP/SCA

S4200 Ruiz,M/Turner,S Breakfast or lunch, reduced price-State pay difference REP

S4204 ScaSca (2R) Sweeney,S Wages and hour and unemployment status-concerns employment status of individuals REP/SCA

S4219 Sweeney,S Public works projects-revises definition to permit project labor agreements REP

S4225 Sca (1R) Greenstein,L/Madden,F Employer tax law-concerns joint liability for payment REP/SCA

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Here's What Happened Under The Gold Dome On Thursday - InsiderNJ

In a way it seems so obvious: find out what kinds of things people are putting into their bodies by studying what comes out the other end. These do sound like muddy waters, but with some clever science researchers are able to draw some clear insights about the habits of different demographics of the population. And with their methods improving all the time, some see a bright future for this dark corner of science that involves real-time health monitoring, predicting disease outbreaks ahead of time and even tracking the rise of antibiotic resistance.

Just like a professional athletes urine sample can be checked for the presence of certain drugs, so too can ours. We dont all have an anti-doping official waiting at the bathroom door, but as our business makes its way into sewerage systems and pools with that of our neighbors, analysis of its chemical makeup can reveal the types of pharmaceuticals we have running through our bodies.

This field of science is known as wastewater-based epidemiology, and in the space of two decades has established itself as a valuable tool to track certain societal behaviors, but one with plenty more still to give.

In the early 2000s, scientists began to seriously explore the idea of tracking the use of illicit drugs by analyzing wastewater. This was inspired by the discovery of metabolites in lakes and rivers, which chemical analysis traced back to certain pharmaceutical compounds that had broken down in the waterways.

Some scientists saw no reason these same techniques couldnt be leveraged to track illicit drug use in the human population. The idea would be to sample wastewater at treatment plants and measure metabolites derived from illicit drugs, gathering non-incriminating drug usage data on the local population.

This is the first feasible approach to obtaining real-time data that truly reflects community-wide usage of drugs while concurrently assuring the inviolable confidentiality of every individual, wrote the EPAs Christian G. Daughton in the American Chemical Societys 2001 publication Pharmaceuticals and Care Products in the Environment. At the same time, this approach yields environmental data for a class of potential pollutants never before considered as such.

Daughton was onto something, it turns out. These days wastewater-based epidemiology has evolved to become a widely used tool by authorities all around the world. By sampling water from sewage treatment plants and measuring the chemical signals within it, scientists can make estimates on the quantity of drugs the community is using, and track the rise and fall of different drug types.

The SCORE network (Sewage analysis CORe group Europe) started out in 2010 as a collaboration between European scientists using wastewater analysis to track illicit drug use in different locations. At first, it involved 19 cities across the continent and by 2018 had expanded to cover 73 cities in 20 different European countries.

EMCDDA

This data is passed onto the European Monitoring Centre for Drugs and Drug Addiction, who work it into a publicly-available online tool that visualizes drug usage trends across the eight years of monitoring so far. By toggling different options, users can see hotspots for cocaine, amphetamine, methamphetamine and MDMA use across the continent, measured as milligrams consumed per 1,000 people each day.

And now other countries have gotten involved, helping to build a more complete picture of drug use around the world. An October paper published in the journal Addiction laid out the most recent data collected by the SCORE network, working with wastewater samples collected between 2011 and 2017, concerning more than 60 million people in 37 different countries.

It produced some interesting insights. For example, methamphetamine use was far more prevalent in North America and Australasia than in parts of Europe, though some hot spots emerged in Slovakia and the Czech Republic. Cocaine remains the drug of choice in Spanish, Italian, Swiss and French cities, while an overall upsurge was observed between 2011 and 2017. Ecstasy also grew in popularity in the cities sampled over the timeframe.

With this kind of generalized data on illicit drug consumption, the idea is that governments can better understand the role drugs play in the wellbeing of their communities. In turn, that can guide policy to curtail their harmful effects, whether that be through better use of police resources, more targeted awareness campaigns or the legalization of some substances that were seeing sweep through parts of the world.

Tying it all in with human behavior

The Australian government was an early adopter of wastewater-based epidemiology, starting out with a handful of testing sites in 2009 and now with a nationwide drug monitoring program in place. Through sewage samples, this initiative monitors the usage of 13 different substances, including nicotine, cannabis and opioid-based pain relievers, with local trends tracked through the help of chemistry researchers around the country. And some of them harbor grand ambitions for wastewater-based epidemiology.

Philip Choi is a PhD student using mass spectrometry and molecular biology to measure different aspects of population health through human waste. This extends beyond illicit drug use to include things like diet and the use of anti-depressants, making new connections between consumption habits and the lifestyles of the community.

The secret is to tie it all in with census data, which is exactly what Choi and his colleagues did the last time Australia conducted a nationwide census in 2016. The scientists had workers at treatment plants around the country freeze wastewater samples during the week of the census, and then mail them into Choi's lab at the University of Queensland for chemical analysis.

In searching these samples for certain biomarkers and comparing them to the census data, the team carried out the first ever study on the links between wastewater chemicals and social and economic measures of a population.

Prior to this study, some studies used wastewater-based epidemiology to study exposure to potentially harmful chemicals or pollutants such as pesticides, herbicides, flame retardants and so forth, Choi tells New Atlas. However, drug measurement studies made up the bulk of wastewater-based epidemiology studies. Additionally, previous studies measured what people are consuming. Our study is unique in that we show why people might consume different things.

And the results of the study, published in The Proceedings of the National Academy of Sciences in October, reveal some intriguing insights indeed. For example, the scientists found that the opioid-based pain reliever tramadol was used more heavily in areas where more people work as physical laborers. In areas populated by people with lower levels of education, they found higher use of anti-depressants and lower levels of dietary fiber. Some of these results were more surprising than others.

Before we analyzed our data, we expected socio-economically advantaged populations to have a better quality of diet, or take less drugs, and so forth, Choi explains. What was surprising, however, was that our data was able to show how specific aspects of socioeconomic advantage or disadvantage, such as having no home internet connection, lacking high school education, or having a high skilled occupation, were linked to diet or drug consumption. For example, we did not expect to find that lack of high school education was strongly linked to lower dietary fiber intake and higher consumption of amitriptyline, an antidepressant.

Higher caffeine and citrus consumption were other examples of habits tied to a strong socioeconomic status that revealed themselves through the wastewater samples. These new relationships that scientists are uncovering between human behavior and the chemicals in their sewage may prove highly valuable in building long-term pictures of population well-being, but could they also have an immediate impact, or even act as a warning sign of impending disaster?

As it stands, wastewater-based epidemiology is a laborious process that requires scientists to gather samples from different treatment plants and run chemical analyses to find out what's inside. But there could come a time when remote sensors built into treatment plants do most of the heavy lifting, and in much more expedient fashion.

"Some wastewater-treatment plants are already using inline sensors to measure specific chemicals in wastewater, such as online continuous monitoring of ammonium," Dr Jake O'Brien, a member of Choi's research team, explains. "There has been progress on developing more sophisticated biosensors for use in wastewater. Biosensors are small devices with a biological receptor, like DNA, an antibody, or a protein, that generates a signal in the presence of an analytical target, or analyte. They are already used for detection of disease biomarkers for both healthcare and environmental monitoring."

O'Brien points to sensor research being carried out at the UK's Cranfield University as an example of the exciting progress being made. Under the guidance of Dr Zhugen Yang, a research group at the university's Water Science Institute brings together cutting-edge biomedical and chemistry techniques to build next-generation sensors that connect wastewater with environmental science and human well-being. Yang also sees huge potential in using these techniques to offer a complete and immediate picture of population health.

"Wastewater-based epidemiology is very powerful to monitor the health at the community level," he tells us. "Compared to conventional analytical tools, sensors can provide rapid response times, ultra-sensitive detection of biomolecules, and the potential to be miniaturized for portable assays requiring minimal sample processing."

These tiny sensors Yang and his team are developing could be used to track pathogens in sewage that reveal outbreaks of certain diseases earlier on. Furthermore, he says they could also be tuned to track indicators of general health risks like diabetes, high blood pressure, sexually transmitted infections and even obesity.

"A recent report demonstrated that the level of an American citys obesity could be predicted by analyzing the bacterial community structure found in sewage," he explains.

Implementing these kinds of advanced sensors on a scale large enough to track population health sounds like a huge undertaking, and an expensive one. But Yang explains that the costs are something his team is already considering, and mightn't be as prohibitive as you'd think.

"Actually, generally those sensors are not so expensive, and we can really reduce the cost of sensors by using cheap material," he says. "For example, recently I have developed a paper-origami device, using filter paper as material to build up hydrophobic and hydrophilic channel to manipulate the liquid rather than using a pump. So I dont think the cost of sensors will be a main limitation for this kind of application."

The rise of antibiotic resistance bacteria, also known as superbugs, is a growing concern among scientists with many fearful they could return us to the dark ages of medicine and kill tens of millions a year by midway through the century. Wastewater-based epidemiology could emerge as a valuable tool in tracking their evolution, and the communities that are most at risk.

"Our recent work also demonstrated a low-cost later flow assay, which can be performed at the site of sample collection, with minimal user intervention, yielding results within 45 minutes and providing a method to monitor public health from wastewater," says Yang. "This can also be used for the tracking of antibiotic-resistant genes, with my research group currently working on the development for these kinds of sensors. The sensor will enable rapid monitoring of antibiotics and antibiotic resistant genes in wastewater."

There are still technical hurdles involved in building real-time sewage monitors to track human health, however. Yang says there are currently a handful of sensors that can perform real-time monitoring of chemical elements, but building versions to identify the right biological signals in real-time presents some unique challenges.

"As most current state-of-the-art sensor technologies for chemical and biological targets are mostly based on the bio-recognition element, the bio-receptor may become too saturated for a long-term detection during deployment, especially for the detection of the complex wastewater matrix," he says. "This is our opportunity to improve those sensors for wastewater-based epidemiology, which ultimately can be deployed for the real-time monitoring."

If these kinds of problems can be overcome, we could see humankind's excrement become an early warning system for some of its biggest health concerns. And then it might no longer be seen as waste at all.

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The science of sewage: What your wastewater could reveal about you - New Atlas