Miracle-dz/UniFAR-FTUs huggingface dataset:
Socioeconomic risk factors for fatal opioid overdoses in the United States: Findings from the Mortality Disparities in American Communities Study (MDAC)

Background Understanding relationships between individual-level demographic, socioeconomic status (SES) and U.S. opioid fatalities can inform interventions in response to this crisis. Methods The Mortality Disparities in American Community Study (MDAC) links nearly 4 million 2008 American Community Survey responses to the 2008–2015 National Death Index. Univariate and multivariable models were used to estimate opioid overdose fatality hazard ratios (HR) and 95% confidence intervals (CI). Results Opioid overdose was an overrepresented cause of death among people 10 to 59 years of age. In multivariable analysis, compared to Hispanics, Whites and American Indians/Alaska Natives had elevated risk (HR = 2.52, CI:2.21–2.88) and (HR = 1.88, CI:1.35–2.62), respectively. Compared to women, men were at-risk (HR = 1.61, CI:1.50–1.72). People who were disabled were at higher risk than those who were not (HR = 2.80, CI:2.59–3.03). Risk was higher among widowed than married (HR = 2.44, CI:2.03–2.95) and unemployed than employed individuals (HR = 2.46, CI:2.17–2.79). Compared to adults with graduate degrees, those with high school only were at-risk (HR = 2.48, CI:2.00–3.06). Citizens were more likely than noncitizens to die from this cause (HR = 4.62, CI:3.48–6.14). Compared to people who owned homes with mortgages, those who rented had higher HRs (HR = 1.36, CI:1.25–1.48). Non-rural residents had higher risk than rural residents (HR = 1.46, CI:1.34, 1.59). Compared to respective referent groups, people without health insurance (HR = 1.30, CI:1.20–1.41) and people who were incarcerated were more likely to die from opioid overdoses (HR = 2.70, CI:1.91–3.81). Compared to people living in households at least five-times above the poverty line, people who lived in poverty were more likely to die from this cause (HR = 1.36, CI:1.20–1.54). Compared to people living in West North Central states, HRs were highest among those in South Atlantic (HR = 1.29, CI:1.11, 1.50) and Mountain states (HR = 1.58, CI:1.33, 1.88). Discussion Opioid fatality was associated with indicators of low SES. The findings may help to target prevention, treatment and rehabilitation efforts to vulnerable groups.
Mass Spectrometry-Based Metabolomics Analysis of Obese Patients’ Blood Plasma

Scientists currently use only a small portion of the information contained in the blood metabolome. The identification of metabolites is a huge challenge because only highly abundant and well-separated compounds can be easily identified in complex samples. However, new approaches that enhance the identification of compounds have emerged; among them, the identification of compounds based on their involvement in a particular biological context is a recent development. In this work, this approach was first applied to identify metabolites in complex samples and, together with metabolite set enrichment analysis, was used for the evaluation of blood plasma from obese patients. The proposed approach was found to provide a statistically sound overview of the biochemical pathways, thus presenting additional information on obesity. Obesity progression was demonstrated to be accompanied by marked alterations in steroidogenesis, androstenedione metabolism, and androgen and estrogen metabolism. The findings of this study suggest that the workflow used for blood analysis is sufficient to demonstrate obesity at the biochemical pathway level as well as to monitor the response to treatment. This workflow is also expected to be suitable for studying other metabolic diseases.
Using applied machine learning to predict healthcare utilization based on socioeconomic determinants of care.

OBJECTIVES To determine if it is possible to risk-stratify avoidable utilization without clinical data and with limited patient-level data. STUDY DESIGN The aim of this study was to demonstrate the influences of socioeconomic determinants of health (SDH) with regard to avoidable patient-level healthcare utilization. The study investigated the ability of machine learning models to predict risk using only publicly available and purchasable SDH data. A total of 138,115 patients were analyzed from a deidentified database representing 3 health systems in the United States. METHODS A hold-out methodology was used to ensure that the model's performance could be tested on a completely independent set of subjects. A proprietary decision tree methodology was used to make the predictions. Only the socioeconomic features-age group, gender, and race-were used in the prediction of a patient's risk of admission. RESULTS The decision tree-based machine learning approach analyzed in this study was able to predict inpatient and emergency department utilization with a high degree of discrimination using only purchasable and publicly available data on SDH. CONCLUSIONS This study indicates that it is possible to risk-stratify patients' risk of utilization without interacting with the patient or collecting information beyond the patient's age, gender, race, and address. The implications of this application are wide and have the potential to positively affect health systems by facilitating targeted patient outreach with specific, individualized interventions to tackle detrimental SDH at not only the individual level but also the neighborhood level.
Functional consequences of phenotypic variation between locally adapted populations: Swimming performance and ventilation in extremophile fish

Natural selection drives the evolution of traits to optimize organismal performance, but optimization of one aspect of performance can influence other aspects of performance. Here, we asked how phenotypic variation between locally adapted fish populations affects locomotion and ventilation, testing for functional trade‐offs and trait–performance correlations. Specifically, we investigated two populations of livebearing fish (Poecilia mexicana) that inhabit distinct habitat types (hydrogen‐sulphide‐rich springs and adjacent nonsulphidic streams). For each individual, we quantified different metrics of burst swimming during simulated predator attacks, steady swimming and gill ventilation. Coinciding with predictions, we documented significant population differences in all aspects of performance, with fish from sulphidic habitats exhibiting higher steady swimming performance and higher ventilation capacity, but slower burst swimming. There was a significant functional trade‐off between steady and burst swimming, but not between different aspects of locomotion and ventilation. Although our findings about population differences in locomotion performance largely parallel the results from previous studies, we provide novel insights about how morphological variation might impact ventilation and ultimately oxygen acquisition. Overall, our analyses provided insights into the functional consequences of previously documented phenotypic variation, which will help to disentangle the effects of different sources of selection that may coincide along complex environmental gradients.
Revenue generating in the NHL: Multiple regression analysis on generating revenue in the National Hockey League

This thesis aims to explain the differences between different National Hockey League teams generated revenues. This is done by analyzing the previous researches on different major sports leagues in the Northern America and comparing them with the findings from the NHL. By the data available, different regression models are constructed and further evaluated to analyze the different factors affecting revenue generating in the NHL. Scope of this research is from season 2005/2006 to season 2014/2015. From recent seasons, only a relatively small amount of data was available, thus the season 2014/2015 is the latest season of interest in this research. The data used to build the regression models was first collected in Excel, and then imported to Stata, which was used to build the models. After testing and analysis, a fixed effects model proved out to be the preferred model. Further analysis of the results pointed out the importance of competitive balance in the league to maximize the profitability between teams. In addition, the geographical features of a team, such as population in the area a team is located, proved out to be important when analyzing the generated revenues. Compared with the previous researches, the results had similarities, but as expected, some differences appeared as well. The most noticeable difference from the previous researches was that the regular season success of a team did not appear as a significant factor in any of the models presented. In addition, some earlier studies suggested that pricing of the tickets would be a significant factor in generating revenue, but surprisingly models used in this research did not provoke similar results. Overall, the results indicate that modeling the revenue generating of a NHL team is complicated, but definitely achievable. Further research on the topic should be done, as the financial side of the NHL still remains underexplored.
The Promising Role of Let-7 Microrna in Colorectal Cancer: Practical Points for Clinicians

Colorectal cancer, one of the most common cancers, displays disproportionally high mortality, taking into consideration the enormous amount of data collected over the recent decades and the broad use of preventive colonoscopy worldwide. MicroRNAs, small, non coding RNA molecules, regulate many critical steps of the entire stages of colorectal tumorigenesis process and shed light to the in depth comprehension of the complex genetic environment that governs the process. Let-7 is the largest microRNA family studied and consists of ten mature members, which exhibit redundancy in colorectum. Its main role is to promote differentiation and depress stemness, both in normal and neoplastic colon. It represses or abrogates translation of other genes, by complementary binding to their mRNAs. It is mostly considered a tumor-suppressor, as it targets mainly oncogenes; among them K-ras is the dominant. Let-7 establishes feedback loops with the majority of its targets. Its expression levels increase over fetus development, are higher on the top vs the bottom of the colonic crypt and are downregulated, as normal colorectal epithelium progress to neoplasia. Although let7’s tumor-suppressive effect is dependent on the primitive or advanced stage of colorectal neoplasia, colorectal cancer tissues’ let-7 levels are proportionate to cancer stage. High let-7 levels may prove a favorable prognostic and predictive biomarker. In case scientists overcome multiple limitations, the administration of mature let-7 inside colorectal cancer tissues (directly, delivering synthetic let-7 or indirectly, using a viral vector), may improve future management of CRC, since underexpressed let-7 levels favor every single stage of colonic oncogenic transformation.
Tracking Sustainability Targets with Quantitative Indicator Systems for Performance Measurement of Industrial Symbiosis in Industrial Parks

Industrial Symbiosis (IS) is a systematic and collective (business) approach to optimizing the use of materials and energy among cross-sectoral industries in order to initiate and exhaust extended cascading systems; it is associated with (synergistic) environmental, technical, social, and economic benefits. For monitoring and controlling the development and progress of an IS system, an indicator system must be set up to standardize and assess the IS (sustainability) performance. This study aims to present a quantitative indicator system to enable the tracking of set sustainability targets of an IS system in Industrial Parks (IPs) for goal-directed IS management. The presented guiding framework encourages IP members in IS systems to set sustainability objectives and to evaluate and track their performance over time with a quantitative indicator system. In particular, established and (partly) internationally standardized methods—such as Material Flow Analysis (MFA), Material Flow Cost Accounting (MFCA), Social Network Analysis (SNA), and Life Cycle Assessment (LCA)—are used in order to place the indicator system on a solid and robust foundation and to adequately meet the multi-faceted sustainability perspectives in the form of a combinatorial application for deriving suitable quantitative indicators for all three (environmental, economic, social) dimensions of sustainability. The indicator system, once embedded in an Information Technology (IT)-supported IS tool, contributes crucially to the technology-enabled environment of IS systems, driving sustainability trajectories.
Hand Gesture Recognition for 3D Interfaces

The recent introduction of many new three dimensional applications and display technologies has created the need for new human-computer interfaces in order to interact with them in a simpler and more natural way compared to what is possible with traditional devices such as the keyboard and mouse. In this work we describe a novel interface for interactive 3D browsing that relies only on the direct acquisition of hand gestures exploiting data from depth cameras such as the Microsoft KinectTM. We do not aim at introducing a complete working system for this task, but instead all the various building blocks and available techniques will be presented in order to construct a framework inside which the various components can be fitted.
Psychosocial disaster preparedness : a comparison between the literature and the psychiatric units at the hospital district of Helsinki and Uusimaa

AIM: The aim of the study is to examine how the psychosocial disaster preparedness plans of the Hospital District of Helsinki and Uusimaa (HUS) relate to current literature. BACKGROUND: There is a tendency to prioritize medical preparedness considerably more than psychosocial preparedness. This is unwise, because the psychosocial consequences can be greater than the physical. HUS has a responsibility to prepare for both national and international disasters. The response is guided by preparedness plans. METHOD: The method is a descriptive literature review. Systematic database searches in PubMed, Cinahl and ProQuest Hospital Collection resulted in 327 articles. Finally 17 articles and 2 policy documents were chosen and analysed. The analysis resulted in 5 key components that were compared with the preparedness plans and documents of HUS. FINDINGS: The five key components were preparedness planning, teaching and training, psychosocial interventions, mental health triage, and community outreach. Comparison showed that HUS preparedness plans and documents are to a large extent up-to-date and in harmony with the literature. CONCLUSION: In order to improve its preparedness, HUS could develop further the following 8 areas: the teaching and training plan; relations with other response organisations; tailored plans to specific disasters; policlinic preparedness; inpatient department preparedness; national/international preparedness; IT preparedness and disaster mental health research. The limitation in this study is the low standard of evidence of the articles.
Role of Transient Receptor Potential Canonical Channel 6 (TRPC6) in Diabetic Kidney Disease by Regulating Podocyte Actin Cytoskeleton Rearrangement

Podocyte injury is an important pathogenesis step causing proteinuric kidney diseases such as diabetic kidney disease (DKD). Actin cytoskeleton rearrangement in podocyte induced by multiple pathogenic factors is believed to be the key process resulting in glomerular injury. Many studies have recently shown that transient receptor potential canonical channel 6 (TRPC6) in podocyte plays a critical role in the development and progression of proteinuric kidney disease by regulating its actin cytoskeleton rearrangement. This review is aimed at summarizing the role of TRPC6 on DKD by regulating the podocyte actin cytoskeleton rearrangement, thereby help further broaden our views and understanding on the mechanism of DKD and provide a theoretic basis for exploring new therapeutic targets for DKD patients.
Dynamic Gesture Recognition based on Kernel Density Estimation of Fingertip Angle Set

A fast and table recognition algorithm combining gesture trajectory and gesture types was proposed for the lack of robustness and real-time ability of dynamic gesture recognition in the complex environment. Gesture region was obtained using Kinect sensor in experiment space and accurate gesture region was obtained by a method of variable parameter quickly. Gesture 3D trajectory extraction and recognition was based on the depth data stream. Real-time gesture types recognition based on kernel density estimation sequence of fingertip angle set template matching algorithm was implemented. Experiments demonstrate that the method of gesture segmentation is fast and accurate. Robustness and real-time ability of gesture trajectory recognition and type recognition is better.
FactorNet: Learning to Factorize Intractable and Multi-Modal Posterior Distributions for Energy Disaggregation

Factorial Hidden Markov Models (FHMM) have emerged as a prominent modeling approach for energy disaggregation. However, because latent variables become dependent conditioned on the observation, reasoning about the posterior is usually intractable which is required for inference as well as learning. Recent approaches try to deal with these intractable posterior distributions by applying Variational Inference with an auxiliary distribution that assumes independence between latent states of the posterior. However, because posterior distributions in the context of energy disaggregation are often multi-modal, independent auxiliary distributions fail to capture either-or relationships between appliance states. In this paper, we introduce an auxiliary distribution over posterior states that, in principle, can approximate any multivariate Bernoulli distribution arbitrarily well, while at the same time offering a functional form that allows obtaining independent samples as well as the mode required for inference in O(N) where N is the number of parallel Hidden Markov chains. On top of that, training the distribution requires solely samples of the joint distribution which are typically easy to acquire. We conduct experiments in the context of waveform disaggregation illustrating the superior capacity of the proposed distribution in comparison to independent auxiliary distributions trained on minimizing the forward or backward KL-divergence.
Non-modal stability of variable-density round jets

The current energy market evolution encourages investigations for new forms of energy for land and aircraft propulsion. Gaseous fuels like methane and hydrogen are good candidates. Mixing promotion downstream of jet injectors is a key point of energetic and environmental performance of future engines such as turbojets and ramjets. Indeed, an efficient and fast mixing improves the compactness and efficiency of the combustion chamber. To this end, the understanding and control of transitional mechanisms downstream the injector is an essential prerequisite to the conception of an innovative injector. In this context, the round jet is the good prototype is of central interest to study theoretically the transitional dynamics of such flows. In addition to the shear effects, local variations of the density field due to the binary mixing between density contrasted fuel and oxidiser
Security of Multithreaded Programs by Compilation

Protecting the confidentiality of information that is processed by a modern computer is challenging and important, since more and more sensitive information is fed to them. Access control and encryption are not enough to ensure this confidentiality, because the usage of the information after the access or decryption is not restricted. It is necessary to control the information flow to protect the sensitive information. On modern mobile devices sensitive information is processed and programs are executed multithreaded (e.g. to prevent lock ups when establishing a network connection). Through the timing difference of the scheduled threads it is likely that sensitive information is leaked and an attacker may obtain sensitive data. The idea Barthe, Rezk, Russo and Sabelfeld phrased in [BRRS07] was to close this leak (formally called covert channel) by annotating the byte-code of the program with security labels according to the confidentiality of the information, which causes the scheduler to hide threads that leak information from the attacker. Their formal model allows to formulate this idea as a framework, which can be instantiated with many programming languages, schedulers and types of byte-code.
Improving the Properties of Cornstarch Based Green Composites Reinforced With Banana Fibers by Incorporating Polycaprolactone for Maxillofacial Bone Plates Fabrication

Great attention has been drawn towards the potential application of starch based biodegradable composites in the biomaterial field. The overarching goal of this study is to explore developing green cornstarch composites for the future usage in the fabrication of maxillofacial bone plates. Our previously developed materials using thermoplastic cornstarch matrix reinforced with banana fibers proved to provide reasonable strength (30 MPa). However, the biodegradability characteristics were not as good as the strength. It has been suggested in the literature that the poly (ε-caprolcatone) can improve the biodegradability of the developed material due to its hydrophobic characteristics. Therefore, in this study blends of glycerin plasticized cornstarch and poly (ε-caprolcatone) at different weight fractions were used as a matrix. Composites of this matrix reinforced with 50 wt. % pseudo stem banana fibers were prepared through compression molding at 5 MPa and 160 °C for 30 minutes. Several experiments have been conducted in order to investigate morphological, thermal and mechanical properties. Experimental results revealed that proper selection of the poly (ε-caprolcatone) weight fraction incorporated into the thermoplastic cornstarch matrix has significantly improved the biodegradability of these materials while maintaining the desired mechanical characteristics. Such improvement in the material characteristics qualifies the new formulated cornstarch composites to satisfy the requirements to use this material in making maxillofacial bone plates. Key-Words: Biodegradable maxillofacial bone plates, Green materials, Poly (ε-caprolcatone), Pseudostem Banana Fibers, Thermoplastic Cornstarch