Miracle-dz/UniFAR-FTUs huggingface dataset:
Health and Health Behaviors During the Worst of Times

Previous studies have shown that recessions are typically associated with better health and health behaviors. However, majority of these studies use data from the periods of relatively milder economic downturns that predate the “Great Recession. ” In this paper, we examine the relationship between measures of macroeconomic conditions and a large set of outcomes of health and health behaviors using data from BRFSS between 1990 and 2014 with an emphasis on the period enveloping the Great Recession. Our results provide some support for the notion that weaker macroeconomic conditions are positively associated with health related outcomes, although the evidence is stronger for some of the outcomes (e.g., smoking and physical exercise) than others and is not present for some of the other outcomes (e.g., experiencing poor mental health) at all. But overall, the estimates are too small and imprecisely estimated to have any meaningful implications. Furthermore, the estimates become weaker over time and largely disappear in years prior to the period of the Great Recession and continues to remain small during periods enveloping the recession and the afterwards. Overall, we found no evidence that the Great Recession had a significant influence on the existing trends in health and health behaviors.
AoI-Aware Energy-Efficient SFC in UAV-Aided Smart Agriculture Using Asynchronous Federated Learning

In the midst of rising global population and environmental challenges, smart agriculture emerges as a vital solution by integrating advanced technologies to optimize agricultural practices. Through data-driven insights and automation, it tackles the necessity for sustainable resource management, enhancing productivity and resilience in the face of complex food security and ecological concerns. The prospects of utilizing the Internet of Things (IoT) for smart agriculture are tremendous, where many IoT devices can be deployed for local environment monitoring, precision farming, autonomous irrigation, and, soil management. In some use cases like smart monitoring and agrochemical applications, UAV-enabled mobile-edge computing (MEC) is proposed as an enabler to provide IoT nodes with additional resources by hosting their computation functions. From the implementation perspective, to flexibly manage the computation functions in UAVs and/or MEC server, the emerging network function virtualization (NFV) can be utilized. However, efficient orchestration of the virtualized functions would be a challenge. In this paper, we consider a decentralized UAV-aided MEC system for smart agricultural applications in which the processing nodes benefit from the NFV technology. We aim to propose a method for efficiently orchestrating the NFVs while some important metrics are minimized, i.e., the age of information (AoI) and total network energy consumption. Especially, we consider the case in which the network state is not fully observable to the orchestrator or the observations are exposed to uncertainties. Consequently, the problem is formulated as a decentralized partially observable Markov decision process (DEC-POMDP). As the formulated problem is NP-complete, we exploit some structural features of the proposed scheme to introduce the concept of symmetry and simplify the problem. Then, a novel decentralized federated learning-based solution is proposed to solve the problem. Simulation results show the effectiveness of the proposed approach in minimizing the total network energy consumption and achieving $AoI$ values less than $200\:msec$ to support demanding real-time applications.
Unveiling the Probiotic Potential of Streptococcus thermophilus MCC0200: Insights from In Vitro Studies Corroborated with Genome Analysis

Streptococcus thermophilus is widely used as a starter culture in the dairy industry and has garnered attention as a beneficial bacterium owing to its health-promoting functionalities in humans. In this study, the probiotic potential of S. thermophilus MCC0200 isolated from a dairy product was investigated through a combinatorial approach of in vitro and in silico studies. MCC0200 demonstrated the ability to survive harsh gastrointestinal (GI) transit, adhere to intestinal mucosa and exert health-promoting traits in in vitro studies. These findings were corroborated with in silico evidence, wherein, MCC0200 genome harboured genes associated with tolerance to GI conditions, intestinal adhesion and colonization. Genome mapping also highlighted the ability of MCC0200 to produce compounds advantageous for the host (folate, bacteriocins), to release antioxidant enzymes that can quench the free radicals (superoxide dismutase, NADH peroxidase), and to metabolize food components that can be harmful to sensitive people (lactose). MCC0200 also demonstrated a positive effect on reducing cholesterol levels, proving to be a potential candidate for food and pharmaceutical applications. The absence of transmissible antibiotic resistance genes and virulence genes underscored the generally regarded as safe (GRAS) nature of MCC0200. This study explored the potential of Streptococcus thermophilus for its probable applications as a probiotic beyond the dairy industry.
Empathy Levels Among Healthcare Professionals: An Asian Multi-professional Cross-Sectional Study

Background: The aim of the study was to measure empathy in healthcare professionals in Singapore and to compare the scores between the different professions: doctors, nurses, and allied health professionals. Methods: An online survey questionnaire was conducted using the Jefferson Scale of Empathy (JSE) from July 2019 to January 2020. The total JSE score was calculated and compared among the different groups. Multiple linear regression was performed to assess predictors of total empathy scores for groups with statistically lower scores. Results: The survey was completed by 4,188 healthcare professionals (doctors (n=569, 13.6%), nurses (n=3032, 72.4%), and allied health professionals (n=587, 14.0%)) out of the 9,348-strong survey population, with a response rate of 44.8%. The study revealed a mean empathy score (SD) of 103.6 (15.6) for the cohort. The mean empathy score (SD) was 112.3 (14.7), 101.3 (15.2), and 107.0 (15.0), respectively for doctors, nurses, and allied health professionals. These were statistically significantly different among the groups (p< 0.0001), with nurses scoring significantly lower than either doctors (p< 0.0001) or allied health professionals (p< 0.0001). Multiple linear regression showed that age < 30 years old, male gender, Malay ethnicity, and working in a hospital setting were associated with significantly lower empathy scores in the nursing group. Conclusion: Nurses in Singapore had significantly lower empathy scores compared to doctors and allied health professionals. Further research on the underlying causes should be undertaken and measures to improve empathy among Singapore nursing staff should be explored and implemented.
Interdecadal Changes in the Relationship between Interannual Variations of Spring North Atlantic SST and Eurasian Surface Air Temperature

AbstractThis study investigates interdecadal changes in the relationship between interannual variations of boreal spring sea surface temperature (SST) in the North Atlantic and surface air temperature (SAT) over the mid-to-high latitudes of Eurasia during 1948–2014. Analyses show that the connection between the spring North Atlantic tripole SST anomaly pattern and the Eurasian SAT anomalies has experienced marked interdecadal shifts around the early 1970s and mid-1990s. The connection is strong during 1954–72 and 1996–2014 but weak during 1973–91. A diagnosis indicates that interdecadal changes in the connection between the North Atlantic SST and Eurasian SAT variations are associated with changes in atmospheric circulation anomalies over Eurasia induced by the North Atlantic tripole SST anomaly pattern. Further analyses suggest that changes in atmospheric circulation anomalies over Eurasia are related to changes in the position of atmospheric heating anomalies over the North Atlantic, which may be due to.
Application of Machine Learning Techniques to Assess Alpha-Fetoprotein at Diagnosis of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the most common primary liver tumor and is associated with high mortality rates. Approximately 80% of cases occur in cirrhotic livers, posing a significant challenge for appropriate therapeutic management. Adequate screening programs in high-risk groups are essential for early-stage detection. The extent of extrahepatic tumor spread and hepatic functional reserve are recognized as two of the most influential prognostic factors. In this retrospective multicenter study, we utilized machine learning (ML) methods to analyze predictors of mortality at the time of diagnosis in a total of 208 patients. The eXtreme gradient boosting (XGB) method achieved the highest values in identifying key prognostic factors for HCC at diagnosis. The etiology of HCC was found to be the variable most strongly associated with a poorer prognosis. The widely used Barcelona Clinic Liver Cancer (BCLC) classification in our setting demonstrated superiority over the TNM classification. Although alpha-fetoprotein (AFP) remains the most commonly used biological marker, elevated levels did not correlate with reduced survival. Our findings suggest the need to explore new prognostic biomarkers for individualized management of these patients.
ENGage LSU 2.0: Transitioning a Field Trip Experience to a Virtual Format and Its Impact on Middle School Students (Evaluation)

ENGage LSU is a yearly event designed to expose middle school students to different fields and research areas of engineering to spark an interest in possible future careers. This single-day field trip experience invited students to tour several labs and facilities in the College of Engineering and to participate in hands-on activities conducted by university faculty, graduate students, and undergraduates. Students were split into groups of 10-20 and rotated through five different demonstrations and activities with a heavy focus on basic and applied research associated with biomedical, chemical, and environmental engineering, such as designing a scale model of microscale technologies to capture cancer cells, examining the properties of polymers, and observing water filtration methods. There were three iterations of this event starting in 2017 with an average participation of 100 middle school students per year. Results from pre-and post-surveys showed that 22% of participating students increased their interest in engineering and over half increased confidence in their ability to become engineers and their desire to pursue a career in engineering. The 2020 offering was slated to be the largest ENGage LSU event up to then, but unfortunately, the event had to be canceled due to the COVID-19 pandemic. Not wanting to lose momentum and knowing that ENGage LSU was having a positive impact on local students, the authors decided to host a virtual event in 2021 due to continued limitations on in-person gatherings and began planning how to make this transition. Sixteen faculty members volunteered to participate—half of them opted to develop and lead a hands-on activity and the other half performed a demonstration live or asynchronously. 308 students were registered to participate from seven middle schools in four different school districts. Classroom sets of materials for the hands-on activities were distributed to the participating schools prior to the event so that the students could perform the activities while following along virtually. Pre-and post-survey analyses revealed that 19% of these students increased their interest in engineering, 27% increased their confidence in becoming an engineer, and 28% increased their desire to pursue an engineering career. While these trends matched what was observed in the previous in-person events, the amount of increase in some categories was lower. Lessons learned from this virtual transition included the need for better communication between the university and middle schools regarding
Latanoprostene Bunod 0.024% in Patients with Open-Angle Glaucoma Switched from Prior Pharmacotherapy: A Retrospective Chart Review

Introduction Latanoprostene bunod 0.024% (LBN, Vyzulta®) is a nitric oxide-donating prostaglandin analog (PGA). We investigated the real-world efficacy and safety of LBN in patients with open-angle glaucoma (OAG) or ocular hypertension (OHT) who switched their existing intraocular pressure (IOP)-lowering treatment(s) to LBN. Methods This non-interventional, multicenter (United States), retrospective chart review included patients aged ≥18 years with OHT and/or mild-to-moderate OAG diagnoses taking 1–2 IOP-lowering treatments at the time of switch to LBN (index visit). Chart-extracted data included demographics, diagnoses, IOP and ocular assessments, other IOP-lowering treatments, adverse events (AEs), and reasons for discontinuation. The main study outcome was IOP change from the index visit to each of the next 2 chart-recorded follow-up visits. Analysis groups included the overall dataset and 2 subgroups of patients switched from PGA therapy to LBN: “PGA-all” subgroup [all patients previously on a PGA with/without another IOP-lowering product] and “PGA-monotherapy” subgroup [patients previously on a PGA alone]). Additional ocular outcomes (eg, visual acuity) were examined, if available. Results The overall dataset included 49 patients (46 had OAD alone, 2 had OHT alone, and 1 had both). The PGA-all subgroup and PGA-monotherapy subgroups had 41 and 32 patients, respectively. Switching to LBN led to a ~25% IOP reduction from the index visit to Visit 1 that was sustained at Visit 2. IOP findings in the PGA-all and PGA-monotherapy subgroups were consistent with the overall dataset. No meaningful changes in other ocular outcomes were found. Of 14 ocular AEs, 3 were recorded as such (mild in severity, considered unrelated to treatment), and 11 were identified through review of interval ocular histories (no severity/relatedness information); none led to discontinuation. Conclusion In this short-term retrospective chart review of mild-to-moderate OAG/OHT, switching prior IOP-lowering therapy to LBN produced an additional ~25% IOP reduction and appeared to be well tolerated.
Untreated Classic Galactosemia: A Rare Cause of Adult-Onset Progressive Cerebellar Ataxia – A Case Report

Abstract Introduction Identifying the underlying etiology of nonfamilial adult-onset progressive cerebellar ataxia is often challenging because neurologists must consider almost all nongenetic and genetic causes of ataxia. Case Presentation A 39-year-old woman was hospitalized for progressive ataxia with pyramidal and cognitive dysfunction after a right arm shaking and coordination problem deteriorated progressively over 1.5 years. The patient’s medical history included amenorrhea, cataracts, developmental delays, consanguinity of the parents, motor coordination issues, and diarrhea and vomiting in infancy. An important finding that enabled us to solve the diagnostic conundrum was the elevated carbohydrate-deficient transferrin levels in the lack of alcohol-related symptoms, which also occur in untreated carbohydrate metabolism disorders, sometimes with ataxia as a leading symptom. The decreased erythrocyte galactose-1-phosphate uridyltransferase (GALT) enzyme activity and the elevated erythrocyte galactose-1-phosphate (Gal-1P) concentration led to the final diagnosis of galactosemia, a rare metabolic disorder. The patient’s condition stayed stable with strict adherence to lactose-free and galactose-restricted diets, regular physiotherapy, and speech therapy, despite attempts to control the crippling tremor. Conclusion This case highlights the importance of considering rare diseases based on unexplained clinical and laboratory findings. Newborn screening does not change the long-term complications of early-treated classical galactosemia. A small percentage of these patients develop ataxia tremor syndrome.
The Influence of Vertical Wind Shear on Moist Thermals

Although it is well established that vertical wind shear helps to organize and maintain convective systems, there is a longstanding colloquial notion that it inhibits the development of deep convection. To investigate this idea, the vertical momentum budgets of sheared and unsheared moist thermals were compared in idealized cloud model simulations. Consistent with the idea of vertical wind shear inhibiting convective development, convection generally deepened at a slower rate in sheared simulations than in unsheared simulations, and the termination heights of thermals in sheared runs were correspondingly lower. These differences in deepening rates resulted from weaker vertical acceleration of thermals in the sheared compared to the unsheared runs. Downward-oriented dynamic pressure acceleration was enhanced by vertical wind shear, which was the primary reason for relatively weak upward acceleration of sheared thermals. This result contrasts with previous ideas that entrainment or buoyant perturbation pressure accelerations are the primary factors inhibiting the growth of sheared convection. A composite thermal analysis indicates that enhancement of dynamic pressure acceleration in the sheared runs is caused by asymmetric aerodynamic lift forces associated with shear-driven cross flow perpendicular to the direction of the thermals’ ascent. These results provide a plausible explanation for why convection is slower to deepen in sheared environments and why slanted convection tends to be weaker than upright convection in squall lines.
The Role of Peace Attitudes on Sustainable Behaviors: An Exploratory Study

This study delves into the intricate relationship among peace attitudes, personality traits, and sustainable behaviors in a diverse sample of 279 adults from different regions of Italy. Building upon the existing literature, this research affirms the influence of agreeableness, openness, and conscientiousness as primary personality traits associated with sustainable behaviors. Additionally, this study scrutinizes the unique predictive power of peace attitudes. The Peace Attitude Scale (PAS), the Big Five Questionnaire (BFQ), and the Sustainable Behaviors Scale (SBS) were utilized to evaluate peace attitudes, personality traits, and sustainable behaviors. The analysis reveals that peace attitudes significantly predict sustainable behaviors, accounting for 31% of the variance. This predictability is attributed to intrinsic motivation and value alignment. Importantly, peace attitudes extend beyond environmental concerns to embrace social justice and equity, integral components of sustainability. The findings underscore the unique and substantial contribution of peace attitudes to understanding sustainable behavior. This study not only confirms the role of personality traits but also emphasizes the importance of intrinsic values in propelling pro-environmental actions.
The Minimisation of Cardiovascular Disease Screening for Kidney Transplant Candidates

Background: There is increasing evidence that cardiac screening prior to kidney transplantation does not improve its outcomes. However, risk aversion to perioperative events means that, in practice, testing remains common, limiting the availability of ‘real-world’ data to support any change. Our objective was to assess perioperative and 1-year post-transplant cardiovascular events in a kidney transplant candidate cohort who received minimal cardiovascular screening. Methods: The retrospective cohort study included all adult kidney-only transplant recipients in a single UK region between January 2015 and December 2021. Kidney transplant recipients asymptomatic of cardiac disease, even those with established risk factors, did not receive cardiac stress testing. The perioperative and 1-year post-transplant cardiovascular event incidences were examined. Logistic regression was used to identify variables of statistical significance that predicted cardiovascular or cerebrovascular events. Results: A total of 895 recipients fulfilled the inclusion criteria. Prior to transplantation, 209 (23%) recipients had an established cardiac diagnosis, and 193 (22%) individuals had a diagnosis of diabetes. A total of 18 (2%) patients had a perioperative event, and there was a 5.7% incidence of cardiovascular events 1 year post-transplantation. The cardiovascular mortality rate was 0.0% perioperatively, 0.2% at 3 months post-transplant, and 0.2% at 1 year post-transplant. Conclusions: This study demonstrates comparable rates of cardiovascular events despite reduced screening in asymptomatic recipients. It included higher risk individuals who may, on the basis of screening results, have been excluded from transplantation in other programmes. It provides further evidence that extensive cardiac screening prior to kidney transplantation is unlikely to be offset by reduced rates of cardiovascular events.
Early Detection of Ovarian Cancer Using Cells Sourced from a Local Microenvironment

Background Sampling a local microenvironment represents a potentially informative method for monitoring disease progression due to proximity between the sample and diseased tissue. Mass spectrometry (MS) offers high levels of specificity and sensitivity in clinical applications, and we have previously been able to demonstrate that matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS is capable of distinguishing cell mixtures (two-component) at low limits of detection. Methods IVIS imaging of a murine xenograft model of high grade serous ovarian cancer (HGSOC) was performed on a weekly basis to track tumor burden. Vaginal lavages were also obtained weekly through disease progression and samples were subjected to our MALDI-TOF MS workflow followed by statistical analyses of the resulting protein fingerprints over the course of the study. Results Over the course of disease progression, the presence and absence of proteins were compiled to generate a unique protein fingerprint. These fingerprints were found to be largely stable across all mice and converge towards the end point of the study. Our MS limit of detection was found to be more sensitive than microscopy-based methods for the RFP-tagged cells. Conclusion MALDI-TOF MS serves as a unique analytical technique for sampling the vaginal microenvironment in a specific and sensitive manner for the detection of HGSOC in a murine model. Highlights Vaginal lavages represent a unique microenvironment to monitor high grade serous ovarian cancer disease progression in a murine model. MALDI-TOF mass spectrometry is capable of distinguishing disease progression in vivo. Small proteins in the 4-20 kDa region represent a unique diagnostic mass spectrometry-based fingerprint.