June 2019 Jobs Report and Industry Update


Economics & Job Creation:


Life Sciences:
“Irregular sleep patterns linked to metabolic disorders”

“Outsmarting deep fakes: AI-driven imaging system protects authenticity'”

“What if you could spot skin cancer before it got too serious?”

The Industrials:
“Bosses who put their followers first can boost their business”

Human Capital Solutions, Inc. (HCS) www.humancs.com is a Retained Executive Search and Professional Recruiting firm focused in Healthcare, Life Sciences, the Industrials, and Technology. Visit our LinkedIn Company Page to learn more about HCS and receive weekly updates.

HCS has created the Prosperity at Work proposition which focuses on creating prosperous relationships between companies and their employees (associates). HCS assists companies in improving bottom line profitability by efficiently planning, organizing and implementing optimized, practical and value-added business solutions.


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Economics & Job Creation:


Total nonfarm payroll employment edged up in May (+75,000), and the
unemployment rate remained at 3.6 percent, the U.S. Bureau of Labor
Statistics reported today. Employment continued to trend up in
professional and business services and in health care.

This news release presents statistics from two monthly surveys. The
household survey measures labor force status, including unemployment,
by demographic characteristics. The establishment survey measures
nonfarm employment, hours, and earnings by industry. For more
information about the concepts and statistical methodology used in
these two surveys, see the Technical Note.

Household Survey Data

The unemployment rate remained at 3.6 percent in May, and the number
of unemployed persons was little changed at 5.9 million. (See table

Among the major worker groups, the unemployment rates for adult men
(3.3 percent), adult women (3.2 percent), teenagers (12.7 percent),
Whites (3.3 percent), Blacks (6.2 percent), Asians (2.5 percent),
and Hispanics (4.2 percent) showed little or no change in May. (See
tables A-1, A-2, and A-3.)

In May, the number of persons unemployed less than 5 weeks increased
by 243,000 to 2.1 million, following a decline in April. The number
of long-term unemployed (those jobless for 27 weeks or more), at 1.3
million, changed little over the month and accounted for 22.4 percent
of the unemployed. (See table A-12.)

Both the labor force participation rate, at 62.8 percent, and the
employment-population ratio, at 60.6 percent, were unchanged in May.
(See table A-1.)

The number of persons employed part time for economic reasons
(sometimes referred to as involuntary part-time workers) declined
by 299,000 in May to 4.4 million. These individuals, who would have
preferred full-time employment, were working part time because their
hours had been reduced or they were unable to find full-time jobs.
Over the past 12 months, the number of involuntary part-time workers
has declined by 565,000. (See table A-8.)

In May, 1.4 million persons were marginally attached to the labor
force, little changed from a year earlier. (Data are not seasonally
adjusted.) These individuals were not in the labor force, wanted and
were available for work, and had looked for a job sometime in the
prior 12 months. They were not counted as unemployed because they had
not searched for work in the 4 weeks preceding the survey. (See table

Among the marginally attached, there were 338,000 discouraged workers
in May, little changed from a year earlier. (Data are not seasonally
adjusted.) Discouraged workers are persons not currently looking for
work because they believe no jobs are available for them. The remaining
1.1 million persons marginally attached to the labor force in May had
not searched for work for reasons such as school attendance or family
responsibilities. (See table A-16.)

Establishment Survey Data

Total nonfarm payroll employment edged up in May (+75,000). Monthly
job gains have averaged 164,000 in 2019, compared with an average gain
of 223,000 per month in 2018. In May, employment continued to trend up
in professional and business services and in health care. (See table

Employment in professional and business services continued to trend up
over the month (+33,000) and has increased by 498,000 over the past 12

Employment in health care continued its upward trend in May (+16,000).
The industry has added 391,000 jobs over the past 12 months.

Construction employment changed little in May (+4,000), following an
increase of 30,000 in April. The industry has added 215,000 jobs over
the past 12 months.

Employment showed little change in May in other major industries,
including mining, manufacturing, wholesale trade, retail trade,
transportation and warehousing, information, financial activities,
leisure and hospitality, and government.

In May, average hourly earnings for all employees on private nonfarm
payrolls increased by 6 cents to $27.83. Over the year, average hourly
earnings have increased by 3.1 percent. Average hourly earnings of
private-sector production and nonsupervisory employees increased by
7 cents to $23.38 in May. (See tables B-3 and B-8.)

The average workweek for all employees on private nonfarm payrolls was
unchanged at 34.4 hours in May. In manufacturing, the average workweek
and overtime hours were unchanged at 40.6 hours and 3.4 hours, respectively.
The average workweek for production and nonsupervisory employees on private
nonfarm payrolls edged down by 0.1 hour to 33.6 hours. (See tables B-2
and B-7.)

The change in total nonfarm payroll employment for March was revised down
from +189,000 to +153,000, and the change for April was revised down from
+263,000 to +224,000. With these revisions, employment gains in March and
April combined were 75,000 less than previously reported. (Monthly revisions
result from additional reports received from businesses and government
agencies since the last published estimates and from the recalculation of
seasonal factors.) After revisions, job gains have averaged 151,000 per
month over the last 3 months.



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Life Sciences:

“Irregular sleep patterns linked to metabolic disorders”

A new study has found that not sticking to a regular bedtime and wakeup schedule — and getting different amounts of sleep each night — can put a person at higher risk for obesity, high cholesterol, hypertension, high blood sugar and other metabolic disorders. In fact, for every hour of variability in time to bed and time asleep, a person may have up to a 27% greater chance of experiencing a metabolic abnormality.

The results of the study, which was funded by the National Heart, Lung, and Blood Institute (NHLBI), part of the National Institutes of Health, appear today in the journal Diabetes Care.

“Many previous studies have shown the link between insufficient sleep and higher risk of obesity, diabetes, and other metabolic disorders,” said study author Tianyi Huang, Sc.D., epidemiologist of the Channing Division of Network Medicine at Brigham and Women’s Hospital, Boston. “But we didn’t know much about the impact of irregular sleep, high day-to-day variability in sleep duration and timing. Our research shows that, even after considering the amount of sleep a person gets and other lifestyle factors, every one-hour night-to-night difference in the time to bed or the duration of a night’s sleep multiplies the adverse metabolic effect.”

For the current study, researchers followed 2,003 men and women, ages 45 to 84, participating in the NHLBI-funded Multi-Ethnic Study of Atherosclerosis (MESA). The participants were studied for a median of six years to find out the associations between sleep regularity and metabolic abnormalities. To ensure objective measurement of sleep duration and quality, participants wore actigraph wrist watches to closely track sleep schedules for seven consecutive days. They also kept a sleep diary and responded to standard questionnaires about sleep habits and other lifestyle and health factors. Participants completed the actigraphy tracking between 2010 and 2013 and were followed until 2016 and 2017.

“Objective metrics and a big and diverse sample size are strengths of this study,” said Michael Twery, Ph.D., director of the NHLBI’s National Center on Sleep Disorders Research. “As is the study’s ability to look not only at current factors, but to conduct a

prospective analysis that allowed us to assess whether patterns of irregular sleep could be linked to future metabolic abnormalities.”

The researchers’ hypothesis that there were, in fact, such associations, proved correct. Individuals with greater variations in their bedtimes and in the hours they slept had a higher prevalence of metabolic problems, and these associations persisted after adjusting for average sleep duration. This was also the case when they looked at the participants who developed metabolic disorders during the 6.3 years of follow up.

The prospective results showed that the variations in sleep duration and bedtimes preceded the development of metabolic dysfunction. According to the authors, this provides some evidence supporting a causal link between irregular sleep and metabolic dysfunction.

Participants whose sleep duration varied more than one hour were more likely to be African-Americans, work non-day shift schedules, smoke, and have shorter sleep duration. They also had higher depressive symptoms, total caloric intake, and index of sleep apnea.

Increasing sleep duration or bedtime variability was strongly associated with multiple metabolic and simultaneous problems such as lower HDL cholesterol and higher waist circumference, blood pressure, total triglycerides, and fasting glucose.

“Our results suggest that maintaining a regular sleep schedule has beneficial metabolic effects,” said study coauthor Susan Redline, M.D., senior physician in the Division of Sleep and Circadian Disorders at Brigham and Women’s Hospital. “This message may enrich current prevention strategies for metabolic disease that primarily focus on promoting sufficient sleep and other healthy lifestyles.”




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“Outsmarting deep fakes: AI-driven imaging system protects authenticity'”

To thwart sophisticated methods of altering photos and video, researchers at the NYU Tandon School of Engineering have demonstrated an experimental technique to authenticate images throughout the entire pipeline, from acquisition to delivery, using artificial intelligence (AI).

In tests, this prototype imaging pipeline increased the chances of detecting manipulation from approximately 45 percent to over 90 percent without sacrificing image quality.

Determining whether a photo or video is authentic is becoming increasingly problematic. Sophisticated techniques for altering photos and videos have become so accessible that so-called “deep fakes” — manipulated photos or videos that are remarkably convincing and often include celebrities or political figures — have become commonplace.

Pawel Korus, a research assistant professor in the Department of Computer Science and Engineering at NYU Tandon, pioneered this approach. It replaces the typical photo development pipeline with a neural network — one form of AI — that introduces carefully crafted artifacts directly into the image at the moment of image acquisition. These artifacts, akin to “digital watermarks,” are extremely sensitive to manipulation.

“Unlike previously used watermarking techniques, these AI-learned artifacts can reveal not only the existence of photo manipulations, but also their character,” Korus said.

The process is optimized for in-camera embedding and can survive image distortion applied by online photo sharing services.

The advantages of integrating such systems into cameras are clear.

“If the camera itself produces an image that is more sensitive to tampering, any adjustments will be detected with high probability,” said Nasir Memon, a professor of computer science and engineering at NYU Tandon and co-author, with Korus, of a paper detailing the technique. “These watermarks can survive post-processing; however, they’re quite fragile when it comes to modification: If you alter the image, the watermark breaks,” Memon said.

Most other attempts to determine image authenticity examine only the end product — a notoriously difficult undertaking.

Korus and Memon, by contrast, reasoned that modern digital imaging already relies on machine learning. Every photo taken on a smartphone undergoes near-instantaneous processing to adjust for low light and to stabilize images, both of which take place courtesy of onboard AI. In the coming years, AI-driven processes are likely to fully replace the traditional digital imaging pipelines. As this transition takes place, Memon said that “we have the opportunity to dramatically change the capabilities of next-generation devices when it comes to image integrity and authentication. Imaging pipelines that are optimized for forensics could help restore an element of trust in areas where the line between real and fake can be difficult to draw with confidence.”

Korus and Memon note that while their approach shows promise in testing, additional work is needed to refine the system. This solution is open-source, and can be accessed at https://github.com/pkorus/neural-imaging. The researchers will present their paper, “Content Authentication for Neural Imaging Pipelines: End-to-end Optimization of Photo Provenance in Complex Distribution Channels,” at the Conference on Computer Vision and Pattern Recognition in Long Beach, California, in June.




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“What if you could spot skin cancer before it got too serious?”

Skin cancer is the most common type of cancer in the United States. If you could visibly see signs of skin cancer on your body, would you be more likely to visit the doctor? A group of professors from BYU and the University of Utah asked that exact question as they looked for the most effective ways to influence people to screen themselves for cancer.

The team found that visual stimulation had a significant impact on those whom they studied, a group of more than 2,200 adults ages 18-89 from across the country. The results demonstrate that UV skin damage visuals can cause viewers to feel fear, which then made these individuals more likely to participate in positive sun-safe behaviors such as wearing sunscreen or protective clothing.

“Just talking about skin cancer, being inundated with facts and mortality rates, all of that is fear-inspiring language, but the images were so powerful that they moved people to intend to take action,” said Kevin John, an assistant professor in BYU’s School of Communications and study co-author.

The group tested a variety of methods including showing people facts, stock photos of other people in the sun, photos where moles have been removed, etc. In total, they used 60 different variations to figure out what method was the most effective.

In addition to sharing facts and figures, John and his colleagues were able to take special UV photos using a VISIA UV complexion analysis system to capture images of skin damage on faces of members from the research team. On the surface, many people may not see signs of skin cancer but with the VISIA UV camera system, UV photographs are capable of revealing existing skin damage caused by UV light exposure which is normally invisible to the naked eye.

“The UV photos, and one particular image of a mole being removed, were the most effective in terms of influencing someone to change their behavior. This tells us these are the types of images we need to use to convince people to screen themselves for cancer. Over time, we hope this will cause mortality rates to drop,” John said.

All comparison group visuals were collected from the educational materials, websites, blogs and social media pages of organizations such as the Skin Cancer Foundation, the American Academy of Dermatology, the Centers for Disease Control and Prevention (CDC), and the American Cancer Society.

The study was funded from a $2.5 million grant from the National Institutes of Health. After reviewing the materials, the researchers asked each person how likely they were to use various sun safety behaviors in the future, such as using sunscreen, wearing protective clothing, staying in the shade and wearing sunglasses.

This study was made available online in the Journal of Behavioral Medicine in December 2018 prior to being published in print this month.




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The Industrials:

“Bosses who put their followers first can boost their business”

Companies would do well to tailor training and recruitment measures to encourage managers who have empathy, integrity and are trustworthy — because they can improve productivity, according to new research from the University of Exeter Business School.

Bosses who are so-called ‘servant leaders’ create a positive culture of trust and fairness in the workplace. In turn, they benefit through creating loyal and positive teams. This type of manager has personal integrity and is also keen to encourage staff development. The new research shows clear evidence of a link between this style of leadership and an increase in productivity.

Researchers examined 130 independent studies which had previously been published and used them to test a number of theories.

“Our work shows that, as we expected, a ‘servant leader’ style of management which is ethical, trustworthy and has a real interest in the well-being and development of staff brings about real positives within the workplace,” said Dr Allan Lee, the lead author of the report and Senior Lecturer in Management.

“Employees are more positive about their work and therefore also often feel empowered to become more creative. The result is a rise in productivity.”

The analysis also found that this style of leadership often creates a positive and valued working relationship between the manager and employee.

“Given the results, we recommend organisations look to put ‘servant leaders’ into influential positions and that training programs and selection processes are aligned to make this happen,” added Dr Lee.

The results also suggest that it would benefit organisations to create, or reinforce a culture that positively promotes trust, fairness, and high-quality working relationships between managers and staff.

The research was carried out by Dr Lee, Dr Joanne Lyubovnikova from Aston Business School, and Drs Amy Wei Tian and Caroline Knight from Curtin University, Perth. It is published in the peer-reviewed academic Journal of Occupational and Organizational Psychology.



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