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Badges are commonly used in online platforms as incentives for promoting contributions. It is widely accepted that badges "steer" people's behavior toward increasing their rate of contributions before obtaining the badge. This paper provides a new probabilistic model of user behavior in the presence of badges. By applying the model to data from thousands of users on the Q&A site Stack Overflow, we find that steering is not as widely applicable as was previously understood. Rather, the majority of users remain apathetic toward badges, while still providing a substantial number of contributions to the site. An interesting statistical phenomenon, termed "Phantom Steering," accounts for the interaction data of these users and this may have contributed to some previous conclusions about steering. Our results suggest that a small population, approximately 20%, of users respond to the badge incentives. Moreover, we conduct a qualitative survey of the users on Stack Overflow which provides further evidence that the insights from the model reflect the true behavior of the community. We argue that while badges might contribute toward a suite of effective rewards in an online system, research into other aspects of reward systems such as Stack Overflow reputation points should become a focus of the community., To appear in IEEE ICDM2020

Imaging evanescent waves is of crucial importance for sub-wavelength-scale investigation of various phenomena. However, frequently used techniques for near-field imaging require either a strong perturbation of the field, long acquisition times or complex electron-based tools. Here, we introduce nonlinear near-field optical microscopy (NNOM), which is capable of real-time evanescent wave imaging by nonlinear wave mixing while using only standard optical components. As a proof-of-concept, we present non-perturbative, single-shot mapping of evanescent plasmonic patterns, utilizing the nonlinearity of the host metal, and monitor in real time the externally controlled changes to the patterns. We further demonstrate the ability to extract the full field information—the amplitude and phase of all electric-field components—in a polarization-sensitive, spin-selective manner. This simple and highly tunable technique could be extended to deep sub-wavelength imaging of polaritons in two-dimensional materials or other nanophotonic guided modes, for swift photonic device characterization and optimized light−matter interactions. A near-field imaging approach based on nonlinear wave mixing that can provide a detailed picture of evanescent waves in real time and with a single shot is demonstrated. Using only standard optical components, this approach will make near-field imaging much more affordable and accessible.

Epigastric pain can have multiple etiologies including myocardial infarction, pancreatitis, acute aortic syndromes, gastroesophageal reflux disease, esophagitis, peptic ulcer disease, gastritis, duodenal ulcer disease, gastric cancer, and hiatal hernia. This document focuses on the scenarios in which epigastric pain is accompanied by symptoms such as heartburn, regurgitation, dysphagia, nausea, vomiting, and hematemesis, which raise suspicion for gastroesophageal reflux disease, esophagitis, peptic ulcer disease, gastritis, duodenal ulcer disease, gastric cancer, or hiatal hernia. Although endoscopy may be the test of choice for diagnosing these entities, patients may present with nonspecific or overlapping symptoms, necessitating the use of imaging prior to or instead of endoscopy. The utility of fluoroscopic imaging, CT, MRI, and FDG-PET for these indications are discussed. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

Contraceptive use is deemed one of the 10 greatest public health achievements of the 20th century because its benefits are universally acknowledged as a cornerstone for reducing global maternal morbidity and mortality. However, although the adoption of the Affordable Care Act in the United States (US) enhanced access to preventive health services, as well as increased contraceptive use, a considerable proportion of reproductive-aged women still have unmet reproductive health needs. Current data indicates gaps in contraceptive use patterns in the US, particularly among low-income women and those from racial/ethnic and gender minority subgroups, necessitating further investigation using an ecological approach. This narrative literature review aims to investigate the current perspective of contraceptive use in the US using the social-ecological model (SEM). Based on SEM levels, barriers to contraceptive use entail the following levels: individual (e.g., misbelief about the side effects of contraceptives), interpersonal (e.g., influence of family and friends), institutional (e.g., lack of training on how to use different types of contraceptives), community (e.g., societal stigma and shame), and policy (e.g., restrictive federal and states policies). Access to contraceptives for women is a system-level issue that necessitates consideration for multilevel strategies by key stakeholders to improve contraceptive uptake among vulnerable populations.

The aim of this study is to explore the current characteristics of people with chronic lower back (CLB) pain, and the sociodemographic and work-related predictors of this pain.The study design used in the study is a cross-sectional study.The 2018 National Health Interview Survey data were used. Chi-squared analysis was used to assess the sociodemographic characteristics, and logistic regression was used to analyze the risk factors after multiple imputation.Of the 72,831 respondents, 25,397 had provided data on CLB pain and were eligible for this study. People with CLB pain were more likely to be obese, white, female, older than 40 years, and did not have a college degree. They were more likely to carry out less than 150 min of moderate aerobic exercise per week. Age was the sociodemographic predictor of CLB pain (P-value0.001). After imputation and adjusting for covariates, construction and extraction and military-specific occupational groups were associated with an increased risk of CLB pain [odds ratios (OR): 1.32, confidence interval (CI): 1.10-1.59, P-value = 0.004; OR: 2.20, CI: 1.36-3.55, P-value = 0.001]. Working between 41 and 60 h/week significantly also had an increased risk of developing CLB pain (OR: 1.13, CI: 1.01-1.27, P-value 0.043; OR: 1.23, CI: 1.10-1.37, P-value0.001).Low socio-economic status, poor physical fitness, work-life imbalance, and the type of occupation contribute to the development of CLB pain. An improvement in preventive measures is needed to address this morbidity. More studies should be carried out to analyze the type of workplace movements that increase the risk of developing CLB.

Social resilience and trust are two major components of the mitigation of the spread of contagious diseases. Although measures such as the imposition of national lockdowns and self-quarantines have been proven to be effective in reducing morbidity, their efficacy is dependent on public trust and compliance. The purpose of this study was to assess public attitudes toward the COVID-19 outbreak over the course of a year. A cohort study of the adult population in Israel was conducted during three waves of COVID-19 morbidity in that country, with February 2020 as the baseline, March 2020 for the first wave, August 2020 for the second, and January 2021 for the third. The results suggest that there is a relationship between risk perception and compliance with health regulations. Moreover, trust is a major component in public compliance. Fluctuations in risk perception and trust were found to affect compliance with regulations. The failure of decision makers to appropriately address the economic constraints imposed on the public during prolonged disasters, such as the COVID-19 outbreak, is likely to lead to a reduction in public trust in the government and to a decrease in societal resilience.

The coronavirus (COVID-19) pandemic is the deadliest public health emergency in the twenty-first century. To mitigate the rapid spread of the virus, institutions around the globe, including higher education, instituted infection control measures such as social distancing and restricted movements with virtual/remote work and learning environments. These changes, including the pandemic-related stressors, are associated with poor mental health among college students. However, student-mothers may encounter an aggravated psychological impact of the pandemic because of their competing and challenging intersecting roles. Multipronged strategies and targeted-mental health services that consider the needs of student-mothers, their children, and families are encouraged to mitigate the pandemic’s impact. Doing so has important implications for public health, policy, and research.

Purpose: The COVID-19 pandemic has disrupted health care delivery and services around the world causing rapid changes to maternity care protocols and pregnant women to give birth with tight restrictions and significant uncertainties. There is a gap in evidence about expectant and new mothers' experiences with birthing during the pandemic. We sought to describe and understand pregnant and new mothers' lived experiences during the COVID-19 pandemic using authentic birth stories. Study Design and Methods: Using a narrative analysis framework, we extracted relevant YouTube birth stories using predetermined search terms and inclusion criteria. Mothers' birth stories were narrated in their second or third trimester or those who had recently given birth during the pandemic. Birth stories were analyzed using an inductive and deductive approach to capture different and salient aspects of the birthing experience. Results: N = 83 birth stories were analyzed. Within these birth stories, four broad themes and 13 subthemes were identified. Key themes included a sense of loss, hospital experiences, experiences with health care providers, and unique experiences during birth and postpartum. The birth stories revealed that the COVID-19 pandemic brought unexpected circumstances, both positive and negative, that had an impact on mothers' overall birthing experience. Clinical Implications: Results provided a detailed description of women's lived experience with giving birth during the COVID-19 pandemic. Maternity nurses should try to provide clear communication and compassionate patient-centered care to relieve women's anxieties about uncertain and unpredictable policy changes on COVID-19 as the pandemic continues to evolve., The COVID-19 pandemic has disrupted health care delivery and services around the world causing rapid and constant changes to maternity care protocols and pregnant women to give birth with restrictions and significant uncertainties. In this study, mothers' birth stories during the pandemic that were posted to YouTube were analyzed. Rich detailed description of women's lived experience with giving birth during the COVID-19 pandemic are presented along with suggestions for nurses to minimize the stress of the vagueness and ambiguity of hospital restrictive practices during the childbirth process in the context of the pandemic.

Background We tested whether CHA2DS2-VASc and/or HAS-BLED scores better predict ischemic stroke and major bleeding, respectively, than their individual components in maintenance hemodialysis (MHD) patients with atrial fibrillation (AF). Methods A retrospective cohort study of a clinical database containing the medical records of 268 MHD patients with non-valvular AF (167 women, mean age 73.4 ± 10.2 years). During the median follow-up of 21.0 (interquartile range, 5.0–44.0) months, 46 (17.2%) ischemic strokes and 24 (9.0%) major bleeding events were reported. Results Although CHA2DS2-VASc predicted ischemic stroke risk in the study population (adjusted HR 1.74 with 95% CI 1.23–2.46 for each unit of increase in CHA2DS2-VASc score, and HR of 5.57 with 95% CI 1.88–16.49 for CHA2DS2-VASc score ≥ 6), prior ischemic strokes/transient ischemic attacks (TIAs) were non-inferior in both univariate and multivariate analyses (adjusted HR 8.65 with 95% CI 2.82–26.49). The ROC AUC was larger for the prior ischemic stroke/TIA than for CHA2DS2-VASc. Furthermore, the CHA2DS2-VASc score did not predict future ischemic stroke risks in study participants who did not previously experience ischemic strokes/TIAs (adjusted HR 1.41, 95% CI: 0.84–2.36). The HAS-BLED score and its components did not have predictive abilities in discriminating bleeding risk in the study population. Conclusions Previous ischemic strokes are non-inferior for predicting of future ischemic strokes than the complete CHA2DS2-VASc score in MHD patients. CHA2DS2VASc scores are less predictive in MHD patients without histories of CVA/TIA. HAS-BLED scores do not predict major bleeding in MHD patients. These findings should redesign approaches to ischemic stroke risk stratification in MHD patients if future large-scale epidemiological studies confirm them.

Objective To estimate the potential influence of pre-operative patient condition on the benefit of earlier hip fracture surgery for elderly patients. Background Many studies emphasize the benefit of earlier hip fracture surgery for patient survival. However less is known regarding how this relationship is influenced by clinical factors which could serve as potential contra-indicators for earlier surgery. Rushed surgery of patients with contra-indications may even compromise their survival. Methods A retrospective study of patients aged 65 and above with an isolated hip fracture following trauma, based on data from 19 hospitals of the national trauma registry available for the years 2015–2016. Registry data was crossed with data on co-morbidities and medication intake from the biggest health insurance agency in the country, serving more than 50% of the country's population. Mediation analysis was performed on a wide list of co-morbidities, medications and clinical test results in order to establish the mediation of their relationship with inhospital mortality by earlier hip fracture surgery. Factors found significant in the mediation analysis were utilized to adjust a logistic regression for predicting inhospital mortality by function of waiting time to surgery and patient's sex and age. Results Anti-coagulant and anti-platelet intake; test results pointing to decreased kidney function and being diagnosed with diabetes or Ischemic Heart Disease were found to be significantly mediated in their influence on inhospital mortality by hip fracture surgery. Despite anti-platelet intake and kidney function having a significant impact on mortality in the multi-variate analysis, the positive effect of earlier hip surgery on survival remained unchanged after adjustment. Conclusions Earlier hip fracture surgery was found to be beneficial for elderly patients even when their co-morbidities and medication intake are taken into account.

CT colonography (CTC) is growing in its utilization and availability as a screening or diagnostic test for colorectal cancer detection. Its performance stands up to optical colonoscopy and it has become a growing alternative in many situations. This leaves a rising need for training and proficiency in how to perform and interpret CTC. Optimization of exam technique and colonic preparation raises the detection rate of colorectal lesions and renders interpretation easier. Since colorectal cancer remains the second most common cause of cancer death in the United States in men and women combined, the role for CTC is further fortified.

Pelvic floor dysfunction is prevalent, with multifactorial causes and variable clinical presentations. Accurate diagnosis and assessment of the involved structures commonly requires a multidisciplinary approach. Imaging is often complementary to clinical assessment, and the most commonly used modalities for pelvic floor imaging include fluoroscopic defecography, magnetic resonance defecography, and pelvic floor ultrasound. This collaboration opinion paper was developed by representatives from multiple specialties involved in care of patients with pelvic floor dysfunction (radiologists, urogynecologists, urologists, and colorectal surgeons). Here, we discuss the utility of imaging techniques in various clinical scenarios, highlighting the perspectives of referring physicians. The final draft was endorsed by the Society of Abdominal Radiology (SAR), American Urogynecologic Society (AUGS), and the American Urological Association (AUA).

Purpose::There is a common opinion that spinal fractures usually reflect the substantial impact of injuries and therefore may be used as a marker of significant associated injuries, specifically for intra-abdominal injury (IAI). The impact of concomitant spinal cord injury (SCI) with the risk of associated IAI has not been well clarified. The aim of this study was to evaluate the incidence and severity of IAIs in patients suffering from spinal fractures with or without SCI.Methods::A retrospective cohort study using the Israeli National Trauma Registry was conducted. Patients with thoracic, lumbar and thoracolumbar fractures resulting from blunt mechanisms of injury from January 1, 1997 to December 31, 2018 were examined, comparing the incidence, severity and mortality of IAIs in patients with or without SCI. The collected variables included age, gender, mechanism of injury, incidence and severity of the concomitant IAIs and pelvic fractures, abbreviated injury scale, injury severity score, and mortality. Statistical analysis was performed using GraphPad InStat ? Version 3.10, with Chi-square test for independence and two sided Fisher’s exact probability test.Results::Review of the Israeli National Trauma Database revealed a total of 16,878 patients with spinal fractures. Combined thoracic and lumbar fractures were observed in 1272 patients (7.5%), isolated thoracic fractures in 4967 patients (29.4%) and isolated lumbar fractures in 10,639 patients (63.0%). The incidence of concomitant SCI was found in 4.95% (63/1272), 7.65% (380/4967) and 2.50% (266/10639) of these patients, respectively. The overall mortality was 2.5%, proving higher among isolated thoracic fracture patient than among isolated lumbar fracture counterparts (11.3% vs. 4.6%, p < 0.001). Isolated thoracic fractures with SCI were significantly more likely to die than non-SCI counterparts (8.2% vs. 3.1%, p < 0.001). There were no differences in the incidence of IAIs between patients with or without SCI following thoracolumbar fractures overall or in isolated thoracic fractures; although isolated lumbar fractures patients with SCI were more likely to have renal (3.4% vs. 1.6%, p = 0.02) or bowel injuries (2.3% vs. 1.0%, p = 0.04) than the non-SCI counterparts. Conclusion::SCI in the setting of thoracolumbar fracture does not appear to be a marker for associated IAI. However, in a subset of isolated lumbar fractures, SCI patient is associated with increased risks for renal and bowel injury.

The aims of the study is to find out the leading sectors in increasing economic growth in the province of east nusa tenggara. This study uses secondary data in the form of PDRB data for the 2014-2018 period obtained through literature books, readings related to the problem under study. Sources of data were obtained from government agencies such as the East Nusa Tenggara Province Central Statistics Agency (BPS), as well as related agencies. The result in this study. 1. Based on the results of the Klassen Typology analysis, the sector which is included in the advanced sector and growing rapidly or the leading sector is the sector Mandatory Government Administration, Defense and Social Security. Meanwhile, sectors that are included in the advanced but depressed sector are the Agriculture, Forestry and Fisheries sector, the Construction sector, the Transportation and Warehousing sector, the Information and Communication sector, the Education Services sector, the Health Services sector and Social Activities and the Other Services sector. Sectors classified as potential or still developing sectors are mining and quarrying sector, processing industry sector, electricity and gas supply sector, wholesale and retail trade: car and motorcycle repair and accommodation and food and drink provision sector. Meanwhile, sectors that are relatively lagging behind are the water supply sector, waste management, waste and recycling, the financial services and insurance sector, the real estate sector and the corporate services sector.

In the fine chemicals industry, reaction screening and optimisation are essential to development of new products. However, this screening can be extremely time and labor intensive, especially when intuition is used. Machine learning offers a solution through iterative suggestions of new experiments based on past experimental data, but knowing which machine learning strategy to apply in a particular case is still difficult. Here, we develop chemically-motivated virtual benchmarks for reaction optimisation and compare several strategies on these benchmarks. The benchmarks and strategies are encompassed in an open source framework named Summit. The results of our tests show that Bayesian optimisation strategies perform very well across the types of problems faced in chemical reaction optimisation, while many strategies commonly used in reaction optimisation fail to find optimal solutions.

We consider the problem of anomaly detection among a large number of processes, where the probabilistic models of anomalies are unknown. At each time, aggregated noisy observations can be taken from a chosen subset of processes, where the chosen subset conforms to a tree structure. The observation distribution depends on the chosen subset and the absence/presence of anomalies. We develop a sequential search strategy using a hierarchical Kolmogorov-Smirnov (KS) statistics. Referred to as Tree-based Anomaly Search using KS statistics (TASKS), the proposed strategy is order-optimal with respect to the size of the search space and the detection accuracy.

Aim To measure sound exposure in an Australian single-room configured, neonatal unit and compare findings to current sound level recommendations. Methods Sound meters were placed inside 51 internal environments (incubators or open cots), and within the surrounding environment of each occupied single room between September 15 and October 28, 2015. One-second incremental monitoring of decibels on an A-weighted scale (dBA), occurred over a minimum of 48 h. Results All equivalent continuous sound pressure levels (Leq) were significantly higher than the recommended 45 dBA for both incubators and open cots. Maximum sound levels (Lmax) were significantly higher than the recommended 65 dBA, peaking at 126.7 dBA inside the incubator and 124.7 dBA inside the open cot. Incubators were observed to have a higher total percentage of time above 45 dBA than open cots for both day (99.84% vs. 75.59%) and night (98.66% vs. 59.56%). Conclusion Sound levels exceeded the recommended maximum exposure levels outlined by the American Academy of Pediatrics (AAP). The long-term sequelae of adverse sensory exposure on preterm neurodevelopment remains unclear. Renewed attention on factors contributing to increased sound levels in neonatal units needs to be a clinical priority.

Bladder outlet obstruction (BOO) in women might be associated with significant lower urinary tract storage symptoms such as increased frequency, urgency, and incontinence. This prospective study was designed to assess whether there is an objective association between BOO and abnormal parameters during filling cystometry in women. A total of 169 consecutive women (mean age 56 ± 14 years) who were referred for urodynamic investigation were prospectively recruited. Comprehensive medical, obstetric, and gynecological histories were recorded. All patients underwent physical examination, renal and bladder ultrasound, and filled out the International Prostate Symptoms Score (IPSS) questionnaire. The cohort was divided into obstructed and un-obstructed groups based on pressure flow results (Obstruction: Qmax 25 cmH2O). There was no significant difference in the frequency of detrusor overactivity between the obstructed and non-obstructed group (37% vs 32%, p = 0.71). All bladder sensation volumes were significantly lower in obstructed women than non-obstructed women in univariate and multivariate logistic regression analyses. Of the sensation parameters, first desire to void (FDV) had the highest area under the curve (AUC = 0.75, 95% CI = 0.672–0.837, p

BackgroundThe outbreak of a new Coronavirus disease (COVID-19) poses dramatic challenges to public health authorities worldwide. One measure put in place to contain the spread of the disease is self-quarantine of individuals who may have been exposed to the disease. While officials expect the public to comply with such regulation, studies suggest that a major obstacle to compliance for self-quarantine is concern over loss of income or employment due to the prolonged absence from work.MethodsA cohort study of the adult population of Israel was conducted in two time points during the COVID-19 outbreak, the last week of February and the third week of March 2020, in order to assess public attitudes. In particular, public compliance rates to self-quarantine with and without State-sponsored compensation for lost wages were assessed.ResultsThe results suggest that public attitudes changed as the threat increased, making people more compliant with regulations. In February 2020, compliance rate for self-quarantine dropped from 94% to less than 57% when monetary compensation for lost wages was removed; however, in March 2020 this drop became more moderate (from 96 to 71%). The multivariate logistic regression revealed that older, non-Jewish, worried over COVID-19, and trusting the Ministry of Health were more likely than their counterparts to comply with self-isolation, even when monetary compensation was not assumed.ConclusionsDespite the effects of threat on people’s obedience with regulations, this study demonstrates that providing people with assurances about their livelihood during absence from work remains an important component in compliance with public health regulations.

With over 7 million patients worldwide, Parkinson’s disease (PD) is becoming more prevalent as life span and industrialization increase. While the majority of cases are sporadic and present in individuals over 65, inherited mutations in Parkin can manifest in individuals as young as teenagers. The involvement of Parkin in neurodegeneration has been widely investigated and its role in mitophagy is undeniable. In the recent years, however, additional functions of the protein are beginning to come to light, which in turn may influence the way patients harboring Parkin mutations are treated. In the present article, we discuss the clinical and genetic aspects of Parkin-linked PD. For this purpose, we consulted the MDSGene database, which comprises the literature of more than 1000 patients with Parkin mutations. In addition, we provide insight into Parkin’s multifaceted role in mitochondrial clearance and maintenance. Finally, we discuss treatment strategies such as brain stimulation, small molecule drugs and dopaminergic cell replacement that could be tailored to improve the clinical phenotypes in Parkin-linked PD.

Badges are endemic to online interaction sites, from Question and Answer (Q&A) websites to ride sharing, as systems for rewarding participants for their contributions. This paper studies how badge design affects people's contributions and behavior over time. Past work has shown that badges "steer" people's behavior toward substantially increasing the amount of contributions before obtaining the badge, and immediately decreasing their contributions thereafter, returning to their baseline contribution levels. In contrast, we find that the steering effect depends on the type of user, as modeled by the rate and intensity of the user's contributions. We use these measures to distinguish between different groups of user activity, including users who are not affected by the badge system despite being significant contributors to the site. We provide a predictive model of how users change their activity group over the course of their lifetime in the system. We demonstrate our approach empirically in three different Q\&A sites on Stack Exchange with hundreds of thousands of users, for two types of activities (editing and voting on posts).

Objective Higher serum alkaline phosphatase (sALP) levels associate with a poor prognosis in maintenance hemodialysis patients. However, little is known about the meaning of lower sALP in this population. We hypothesized that lower sALP concentrations may express nutritional status and survival accordingly. Methods A retrospective, longitudinal cohort study of a clinical database containing the medical records of 554 patients (367 men and 187 women, mean age 67.6 ± 14.2 years) receiving maintenance hemodialysis from November 2007 to July 2018 in a single center was conducted. sALP, nutritional, bone turnover, and inflammatory marker levels were recorded at 0, 6, 12, 18, 24, 30,and 36 months followed by 58 additional months of clinical observations. Results The median sALP level was 90.0 (71.0-125.8) U/L. In a linear mixed effects model adjusted for baseline demographics and clinical parameters, each 1.0 U/L increase above the mean sALP at baseline was associated with 0.7% slower rate of decline in geriatric nutritional risk index per 3 years (P = .02 for sALP × time interaction). sALP remained associated with the rate of change in geriatric nutritional risk index, even after controlling for C-reactive protein and intact parathyroid hormone levels. For each 1.0 U/L increase in sALP over time, the fully adjusted all-cause mortality hazard ratio using Cox models with the time-varying risk effect was 0.996 (95% confidence interval 0.993-1.000, P = .04). Conclusions Increasing longitudinal levels of sALP associate with improved nutritional status and lower mortality rates. sALP can be used as an integrated marker, combining the properties of the nutritional marker, the marker of mineral-bone disease and inflammation, according to its levels.

CT colonography (CTC), also known as “virtual colonoscopy,” is a minimally invasive complementary screening method to optical colonoscopy (OC) that is growing in its availability and utilization. As a screening test, it is typically performed in outpatient radiology sites. Examinations are monitored by a radiologist trained in its performance. CTC is selectively performed in a hospital setting for patients with comorbidities that render them at a high risk for OC, such as cardiac disease or screening before organ transplantation. In cases where OC is unsuccessful for at complete colonic inspection, CTC can be performed the same day after OC or planned at a later date to evaluate the remainder of the colon. Candidates for CTC must be able to follow instructions and tolerate colonic insufflation. Patients who have fecal incontinence or significant rectal prolapse are not candidates for CTC because of limited ability to maintain colonic distension. Finally, strict adherence to the recommended colonic preparation before CTC is critical to the examination's success.

Cross-layer Aloha protocols that exploit the channel diversity when accessing the spectrum became popular in recent years, due to their capability to increase the user rates as compared to classic Aloha-type protocols. Existing algorithms, however, suffer from significant performance degradation in terms of queue load balancing, which makes them inefficient in practical systems. In this letter, we develop a novel queue and channel based Aloha (QCA) algorithm to solve this issue. In QCA, each user trades off between the channel state and the queue state to increase the rate while keeping the queue load small. Strong performance of the algorithm is demonstrated theoretically and numerically.

This study was primarily aimed at establishing the incidence and impact of hypotension in patients with blunt traumatic brain injury based on National Trauma Registry Database.A retrospective cohort study using the National Trauma Registry was conducted. Patients with TBI following blunt mechanisms of injury were examined, comparing those with and without hypotension (SBP90 mm Hg) on arrival.During the period from 1998 to 2017, the registry included 437.354 blunt trauma patients. Of them, 7818 patients were hemodynamically unstable (SBP90 mm Hg) on admission. 513 met the inclusion criteria. Significant percentages of patients with high grade injures (ISS≥16) and low admission's GCS 3-12 (46% vs 16.4%), were found in the group of hypotensive TBI patients (p0.0001). 323 (62.9%) patients had head AIS score 3-4 and only 190 (37.1%) patients AIS 5-6 (p0.0001). Mortality in the hypotensive TBI group was 32.3%, whereas 6.1% patients died in the TBI hemodynamically stable group (p0.0001).TBI patients presenting with hypotension represent an appreciable portion blunt trauma patients. Prompt brain CT, expedient efforts at optimal resuscitation and possibly early inotropic and vasopressors agents use may have an impact on final outcome in these patients.

Purpose: Pelvic fracture evaluation with abdominopelvic computed tomography (CT) and formal CT cystography for rule out of urine bladder injury have been commonly employed in pediatric trauma patients. The additional delayed imaging required to obtain optimal CT cystography is, however, associated with increased doses of ionizing radiation to pelvic organs and represent a significant risk in the pediatric population for future carcinogenic risk. We hypothesized that avoidance of routine CT cystography among pediatric pelvic fracture victims would not result in an appreciable rate of missed bladder injuries and would aid in mitigating the radiation exposure risk associated with these additional images. Methods: A retrospective cohort study involving blunt trauma pelvic fractures among pediatric trauma patients (age

To contain the novel coronavirus disease (COVID-19) pandemic, health and government authorities have imposed sweeping self-quarantine orders for communities worldwide. Health officials assume that the public will have high rates of compliance. However, studies suggest that a major obstacle to compliance for household quarantine is concern about loss of income. A cross-sectional study of the adult population of Israel was conducted in the last week of February 2020 to assess public attitudes toward the COVID-19 outbreak. In particular, public compliance rates with self-quarantine were assessed, depending on whether lost wages would be compensated for. When compensation was assumed, the compliance rate was 94 percent. When compensation was removed, the compliance rate dropped to less than 57 percent. This study demonstrated that providing people with assurances about their livelihoods during self-quarantine is an important component of compliance with public health regulations.

Early application of tourniquets has reduced injury death rates. At the end of 2013, the Israel Defense Forces Medical Corps completed a military-wide introduction of the Combat Application Tourniquet as the standard-issued tourniquet. The accompanying clinical practice guideline encouraged combat soldiers and medical teams towards a liberal use of tourniquets for extremity injuries, even when in doubt.This study aimed to assess the effects of the wide introduction of advanced tourniquets on the rate of tourniquet applications, the type of tourniquet applied, and the differences in hospitalisation outcomes following the introduction.The study population was composed of hospitalised military casualties with an extremity injury treated by military medical teams between 2006 and 2015. Prehospital data were extracted from the Israel Defense Forces Trauma Registry and matched to corresponding hospital data from the Israeli National Trauma Registry. Two periods were compared: 2006-2013 "pre-intervention period" and 2014-2015 "post-intervention period".A total of 1,578 casualties were recorded during the study period. Of these, 320 (20.3%) occurred between 2014-2015. Characteristics of casualties in the post-intervention period were similar to those in the pre-intervention period including the rate of traumatic amputations (2.5% vs 2.2%, p = 0.93) and Injury Severity Score of 16 or above (12.8% vs 14.9%, p = 0.40). The rate of tourniquet application was more than four-fold in the post-intervention period compared to the pre-intervention period (22.8% vs 5.5%, p 0.001). Nevertheless, rates of in-hospital amputations (1.6% vs 1.6%, p = 1.00) and death (0.9% vs 1.3%, p = 0.53) were similar in the two periods.Following the IDF military-wide introduction of advanced tourniquets, the tourniquet application rate rose sharply, the use of old tourniquets ceased over time, and in-hospital amputation rate did not increase. These findings suggest that the awareness for haemorrhage control using advanced tourniquets rose.

The recent success of deep neural networks (DNNs) for function approximation in reinforcement learning has triggered the development of Deep Reinforcement Learning (DRL) algorithms in various fields, such as robotics, computer games, natural language processing, computer vision, sensing systems, and wireless networking. Unfortunately, DNNs suffer from high computational cost and memory consumption, which limits the use of DRL algorithms in systems with limited hardware resources. In recent years, pruning algorithms have demonstrated considerable success in reducing the redundancy of DNNs in classification tasks. However, existing algorithms suffer from a significant performance reduction in the DRL domain. In this paper, we develop the first effective solution to the performance reduction problem of pruning in the DRL domain, and establish a working algorithm, named Policy Pruning and Shrinking (PoPS), to train DRL models with strong performance while achieving a compact representation of the DNN. The framework is based on a novel iterative policy pruning and shrinking method that leverages the power of transfer learning when training the DRL model. We present an extensive experimental study that demonstrates the strong performance of PoPS using the popular Cartpole, Lunar Lander, Pong, and Pacman environments. Finally, we develop an open source software for the benefit of researchers and developers in related fields., Comment: This paper has been accepted for publication in the IEEE Journal of Selected Topics in Signal Processing

Privacy protection legislation and policy is heavily dependent on the notion of de-identification. Repeated examples of its failure in real-world use have had little impact on the popularity of its usage in policy and legislation. In this paper we will examine some of the misconceptions that have occurred to attempt to explain why, in spite of all the evidence, we continue to rely on a technique that has been shown not to work, and further, which is purported to protect privacy when it clearly does not. With a particular focus on Australia, we shall look at how misconceptions regarding de-identification are perpetuated. We highlight that continuing to discuss the fiction of de-identified data as a form of privacy actively undermines privacy and privacy norms. Further, we note that ‘de-identification of data’ should not be presented as a form of privacy protection by policy makers, and that greater legislative protections of privacy are urgently needed given the volumes of data being collected, connected and mined.

Architectural research often considers buildings and settlement practices as local material adaptations to climate, particularly when it comes to the analysis of architecture in rural and small-scale settlements. Based on ethnographic data from the rapidly urbanizing oasis metropolis Ürümchi in China’s northwestern borderlands, this paper goes beyond such a localized view of climate responsiveness. It analyzes how individual practices of residents for the purpose of creating comfortable spaces in urban settings are linked to the interests of the state and to socio-cultural notions of thermal comfort. Through the classification of Xinjiang as part of China’s northern “Heating Zone,” the keeping warm of individual bodies becomes part of a territorializing strategy, because investments in urban thermal infrastructures and the inclusion in a national heating grid have anchored these regions within the state. There are, however, clear seasonal differences in how indoor residential spaces are regulated to maintain bodily comfort. In winter, apartment owners and residents enjoy the amenities of the state-financed heating infrastructure. In summer, cooling strategies depend on more neoliberalized, individual, social, and architectural ways to lower indoor temperatures. This paper unfolds the diversity of thermal discourses and practices that characterize Ürümchi citizens’ creation of comfortable residential spaces throughout the seasons. The data outlines that houses as infrastructures are far from being simple containers that keep residents’ bodies warm. Instead, the socio-technical organization of thermal spaces interferes with territorial strategies and ethnic place-making.

Today, cyber attacks are constantly evolving and changing, which makes them harder to detect. In particular, detecting attacks in large-scale networks is very challenging because they require high detection rates under real-time resource constraints. In this paper, we focus on detecting infected Internet of Things (IoT) hosts from domain name system (DNS) traffic data. IoT hosts, such as streaming cameras, printers, air conditioners, are hard to protect, unlike PCs and servers. Enterprises are often unaware of the devices which are connected to the network, their types, makes, and vulnerabilities. Since IoT hosts make use of the DNS protocol, analyzing DNS data can give a broad view of malicious activities, because they abuse the DNS protocol and leave fingerprints as part of their attack vector. In this collaborative research between Ben-Gurion University, and IBM, we establish a novel algorithm to detect infected IoT hosts in large-scale DNS traffic, named Anomaly and Reputation Based Algorithm (ARBA). Its novelty resides in developing a framework that combines host classification and domain reputation in a real-time production environment. ARBA is highly computational efficient and meets real-time requirements in terms of run time and computational complexity. By contrast to existing algorithms, it does not require a massive traffic volume for training, which is of significant interest in detecting infected hosts in real-time. The research was conducted on real live streaming data from IBM internal network traffic, and confirm the algorithm's strong performance in a real-time production environment.

Detecting malicious activities in cyber systems is a major challenge of cybersecurity service providers. Due to the large amount of network traffic, it is often likened to finding a needle in a haystack. Domain name system (DNS) is one of the fundamental protocols of the internet, and therefore it can give a broad view of those malicious activities, which abuse it and leave fingerprints as part of their attack vector. In this collaborative research between Ben-Gurion University, and IBM, a significant performance improvement was achieved in detecting malicious domains as compared to the state-of-the-art software solutions. Specifically, we establish a novel algorithm to detect malicious domains in large-scale DNS traffic, named Resource-Efficient Malicious Domain Detector (REMaDD), with the following desired properties. First, the algorithm does not require prior knowledge on historical malicious activities in its real-time operations. Second, the development used real live streaming data from The Inter-University Computation Center (IUCC), and operated on real-time IBM system. The algorithm is highly computational efficient and satisfies real-time requirements in terms of running time and computational complexity. REMaDD demonstrated strong performance in terms of both detection accuracy and computational efficiency as compared to existing algorithms. Specifically, experimental results on IBM production environment demonstrated that REMaDD achieved 89.4% Precision score, and 82.9% Recall score. By contrast, the DomainObserver, and LSTM.MI algorithms achieved only 76.7%, 67.2% Precision score, and 81.7%, 75.3% Recall score, respectively.

This paper studies students engagement in e-learning environments in which students work independently and solve problems without external supervision. We propose a new method to infer engagement patterns of users in such self-directed environments. We view engagement as a continuous process in time, measured along chosen axes that are derived from student data in the system using unsupervised learning (Principal Component Analysis). We construct a trajectory of user activity by projecting the user's scores along the selected PCs at regular time intervals. This approach is applied to a popular e-learning software for K12 math education that is used by thousands of students worldwide. We identify cohorts of users according to the way their trajectory changes over time (e.g., monotone up, monotone down, and constant). Each of the cohorts exhibits distinct behavioral dynamics and differed substantially in the amount of time users spent in the e-learning system. Specifically, one cohort included students that dropped out of the system after choosing very difficult problems that they were not able to complete, while another cohort included students users that chose more diverse problems and stayed longer in the system. In future work, these results can be used by teachers or intelligent tutors to track students’ engagement in the system and decide whether and how to intervene.

This chapter focuses on online learning algorithms that were developed for dynamic spectrum access (DSA), in which a cognitive user aims to learn the occupancy of the spectrum in the presence of external users to improve the spectral usage. The focus is thus on how quickly the cognitive user can learn the external process, and not on the interaction between cognitive users. The chapter discusses the more general model where multiple cognitive users share the spectrum, and the goal is to effectively allocate channels to cognitive users in a distributed manner in order to maximize a certain global objective. It then provides an overview of model‐dependent solutions and discusses the very recent developments of artificial intelligence algorithms based on deep learning for DSA that can effectively self‐adapt to complex real‐world settings.

Real-time strategy (RTS) games are a challenging application for artificial intelligence (AI) methods. This is because they involve simultaneous play and adversarial reasoning that is conducted in real time in large state spaces. Many AI methods for playing RTS games rely on hard-coded strategies designed by human experts. The drawback of using such strategies is that they are often unable to adapt to new scenarios during gameplay. The contribution of this paper is a new approach, called strategy creation via voting (SCV), that uses a voting method to generate a large set of novel strategies from existing expert-based ones. Then, SCV uses an opponent modeling scheme during the game to choose which strategy from the generated pool of possibilities to use. By repeatedly choosing which strategy to use, SCV is able to adapt to different scenarios that might arise during the game. We implemented SCV as a bot for $\mu$ RTS, a recognized RTS testbed. The results of a detailed empirical study show that SCV outperforms all approaches tested in matches played on large maps and is competitive in matches played on smaller maps.

Study objective The latest wave of terrorism worldwide has seen significant use by terrorists of mundane, "low-technology" weapons, such as utility knives and civilian vehicles. How do the injuries they produce compare with that of more conventional terrorism mechanisms, such as use of firearms and explosives? We compare injury patterns of the most frequent terrorism-related injury mechanisms in an Israeli data set. Methods This was a retrospective study of 1,858 patients hospitalized because of terrorism events, which were recorded in the Israeli National Trauma Registry between January 1997 and December 2016. The events were divided into 4 groups based on weapon used: explosions, shootings, stabbings, and vehicular attacks. The groups were compared in terms of injuries sustained, use of hospital resources, and clinical outcomes. Results Explosion-related and vehicular terrorism resulted in a higher proportion of multiple injuries, whereas stabbings and shootings mostly led to isolated injuries. Victims of vehicular attacks had a high proportion of severe head injuries, whereas stabbing victims had a high volume of vascular injuries. All mechanisms involved significant damage to extremities; however, among stabbing victims injury was mainly to the upper extremities, whereas among vehicular attack victims it was mostly to the lower extremities. The overall injury severity of the compared groups was similar, leading to comparable levels of intensive care use and inhospital mortality. Certain similarities in victims' characteristics were observed between the shootings and stabbings and between explosions and vehicular attacks. Conclusion Despite differences between various terrorist attack mechanisms, the resulting injury severity and inhospital mortality are very similar, with stabbings and vehicular attacks causing injuries as serious as those caused by conventional weapons.

We introduce nonlinear near-field optical microscopy (NNOM), capable of real-time evanescent wave imaging by nonlinear wave mixing. Using NNOM, we exhibit phase-resolved polarization- and spin-sensitive near-field mappings of plasmonic patterns using only standard optical components.

BACKGROUND Pain management is important to post-acute functional recovery, yet older persons with Alzheimer's disease and related dementias (ADRD) are often undertreated for pain. The main objectives were (1) to examine the relationship between ADRD and analgesic use among Medicare home health care (HHC) recipients with daily interfering pain, and (2) to examine the impact of analgesic use on functional outcome in patients with and without ADRD. METHODS We analyzed longitudinal data from the Outcome and Assessment Information Set, Medicare HHC claims, and HHC electronic medical records during a 60-day HHC episode. The sample included 6048 Medicare beneficiaries ≥65 years receiving care from an HHC agency in New York in 2019 who reported daily interfering pain. Analgesic use was assessed during HHC medication reconciliation and included any analgesic, non-opioid analgesic, and opioid. ADRD was identified from ICD-10 codes (HHC claims) and cognitive impairment symptoms (Outcome and Assessment Information Set [OASIS]). Functional outcome was measured as change in the composite Activity of Daily Living (ADL) limitation score in the HHC episode. RESULTS ADRD was related to a lower likelihood of using any analgesic (odds ratio [OR] = 0.66, 95% confidence interval [CI]: 0.49, 0.90, p = 0.008) and opioids (OR = 0.54, 95% CI: 0.47, 0.62, p

We consider the adaptive routing problem in multihop wireless networks. The link states are assumed to be random variables drawn from unknown distributions, independent and identically distributed across links and time. This model has attracted a growing interest recently in cognitive radio networks and adaptive communication systems. In such networks, devices are cognitive in the sense of learning the link states and updating the transmission parameters to allow efficient resource utilization. This model contrasts sharply with the vast literature on routing algorithms that assumed complete knowledge about the link state means. The goal is to design an algorithm that learns online optimal paths for data transmissions to maximize the network throughput while attaining low path cost over flows in the network. We develop a novel Online Learning for Shortest path and Backpressure (OLSB) algorithm to achieve this goal. We show theoretically that OLSB achieves a logarithmic regret, defined as the loss of an algorithm as compared to a genie that has complete information about the link state means. Simulation results support the theoretical findings and demonstrate strong performance of the OLSB algorithm.

Aim Penicillin allergy labels are frequently encountered in children and are associated with significant harms. Most children are falsely labelled and can safely tolerate a penicillin but delabelling strategies are underutilised and paediatric-specific resources are lacking. The aim of this study was to evaluate an allergy assessment tool for children in hospital. Methods We evaluated a paediatric-adapted penicillin allergy assessment tool, using an online survey of clinicians in a tertiary paediatric hospital, with 10 hypothetical potential penicillin allergy or adverse reaction cases (including non-allergy reactions). For each case, respondents were asked to use the tool to assign a reaction phenotype and recommend management. We determined the tool's sensitivity, specificity and acceptability to end users. Results We evaluated 30 complete survey responses from senior and junior medical staff, nurses and pharmacists. The tool's overall sensitivity was 80.7% (95% confidence interval (CI) 74.2-87.1%) for assigning the correct reaction phenotype and 85.3% (95% CI 79.4-91.3%) for appropriate management. The tool had high sensitivity for identifying immediate hypersensitivity reactions at 95.6% (95% CI 90.2-100%). Most respondents agreed or strongly agreed that they would use the tool in their practice (22/30, 73.3%). Conclusion This survey evaluated a paediatric-adapted penicillin allergy assessment tool in a tertiary paediatric hospital among multidisciplinary clinician groups. The tool performed well overall and had high safety in identifying immediate hypersensitivity reactions. Further research to support implementation of allergy assessment and delabelling programmes among children is required.

The Corona virus disease 2019 (COVID-19) has significantly affected lives of people around the world. Today, isolation policy is mostly enforced by identifying infected individuals based on symptoms when these appear or by testing people and quarantining those who have been in close contact with infected people. In addition, many countries have imposed complete or partial lock-downs to control the spread of the disease. While lock-downs have succeeded to slow down the spread of the virus, they have devastating effects on the economy and social life. We argue that controlling the spread of the virus can be done by using active feedback to control testing for infection by actively testing individuals with a high probability of being infected. We develop an active testing strategy to achieve this goal, and demonstrate that it would have tremendous success in controlling the spread of the virus. Our results show up to a 50% reduction in quarantine rate and morbidity rate in typical settings as compared to existing methods.

In this chapter, we show that a bayesian network can be an efficient way to diagnose a fault in multivariate processes. We have selected two statistical fault detection techniques (the T 2 chart and the MEWMA chart) and we have demonstrated that these charts can be viewed as a discriminant analysis and so can be implemented in a simple bayesian network. As the efficiency of bayesian network for the diagnosis of systems has already been demonstrated (Verron et al., 2006; Verron et al., 2007), the evident outlook of this work is the full study of the use of bayesian network in order to monitor and control a multivariate process (detection and diagnosis in the same network).

Objectives To analyse the impact of hospital quality indicators on hip fracture mortality in Israel. Study design A retrospective observational study. Methods Data were collected on all patients aged ≥65 years with an isolated hip fracture in the years 2010–2016 from the Israel's National Trauma Registry. These data were then cross checked with information on co-morbidities and medication intake from the Clalit medical fund. All successfully matched patients constituted the study population. The main outcome measures were in-hospital and 1-year mortality. Trend analysis of surgery on hip fractures within 48 h of hospitalisation (referred to as early hip fracture surgeries) and mortality was performed. The introduction of the proportion of early hip fracture surgeries as an official quality parameter in 2013 was considered an intervention. Results The proportion of early hip fracture surgeries continuously increased during the study period and, after the introduction of the quality measure, a significant increase in the uniformity of practice among hospitals was observed. The mortality trend was not related to the early surgeries trend, with a sharp upward spike detected in 2014, followed by a gradual return to previous levels in the subsequent years. The analysis has shown that when adjusting for demographic factors and co-morbidity, both in 2010–2013 and in 2015–2016, a clear benefit in survival existed for patients who were operated on within the first 48 h. In 2014, which was the first year of open publication of achieved quality measures reported in the media, no such benefit was found. Conclusions Even when an improvement in a promoted practice is achieved, its positive impact on clinical outcomes may be delayed, possibly indicating the need for a learning period.

Xenobots have been called “novel living machines” and “living robots” (Brown 2020). A coauthor of the paper (Kriegman et al. 2020) that recently introduced xenobots said, “They’re neither a traditi...