Miracle-dz/UniFAR-FTUs huggingface dataset:
Metabolic Diseases and Risk of Head and Neck Cancer: A Cohort Study Analyzing Nationwide Population-Based Data

Simple Summary Head and neck cancer has been increasing in recent years, and it seriously deteriorates the quality of life because it directly affects the organs of eating, talking and breathing. Therefore, studies to prevent and treat it are being actively conducted. In the present study, we investigated the effects of metabolic diseases on the development of head and neck cancer as part of research to identify risk factors for head and neck cancer and to prevent it. Obesity lowered the risk of HNC in men. Underweight was a strong risk factor for HNC in both men and women. High LDL cholesterol and TC levels had protective effects on HNC in men, but not in women. Diabetes increased the risk of HNC in both men and women, whereas hypertension increased the risk of HNC only in men. Abstract The aim of the study was to investigate the association between metabolic diseases and the risk of head and neck cancer (HNC) using nationwide population-based big data. This retrospective cohort study was conducted using the Korean National Health Insurance Service health checkup database. A total of 4,575,818 participants aged >40 years who received a health checkup in 2008 were enrolled, and we studied the incidence of HNC until 2019. We analyzed the risk of HNC according to the presence of metabolic diseases, such as obesity, dyslipidemia, hypertension, and diabetes. Although metabolic syndrome itself was not associated with HNC, each component of metabolic syndrome was associated with HNC. Underweight and diabetes were risk factors for HNC (HR: 1.694). High total cholesterol and high low-density lipoprotein cholesterol levels were factors that decreased the risk (HR 0.910 and 0.839). When we analyzed men and women separately, low total cholesterol level, low low-density lipoprotein cholesterol level, and hypertension were risk factors only in men. In addition, pre-obesity, obesity, and central obesity decreased the risk only in men. Each metabolic disease affects HNC in different ways. Underweight and diabetes increased the risk of HNC, whereas high total cholesterol and high low-density lipoprotein cholesterol levels decreased the risk of HNC.
Facility-Level Variation in Hospitalization, Mortality, and Costs in the 30 Days Following Percutaneous Coronary Intervention: Insights on Short-Term Healthcare Value from the VA CART Program

Background — Policies to reduce unnecessary hospitalizations after PCI are intended to improve healthcare value by reducing costs while maintaining patient outcomes. Whether facility-level hospitalization rates after PCI are associated with cost of care is unknown. Methods and Results — We studied 32,080 patients who received PCI at any one of 62 VA hospitals from 2008 to 2011. We identified facility outliers for 30-day risk-standardized hospitalization, mortality and cost. Compared with the risk-standardized average, 2 (3.2%) hospitals had a lower than expected hospitalization rate and 2 (3.2%) hospitals had a higher than expected hospitalization rate. We observed no statistically significant variation in facility-level risk-standardized mortality. The facility-level unadjusted median per patient 30-day total cost was $23,820 (IQR $19,604 to $29,958). Compared with the risk-standardized average, 17 (27.4%) hospitals had lower than expected costs and 14 (22.6%) hospitals had higher than expected costs. At the facility level, the index PCI accounted for 83.1% of total cost (range 60.3-92.2%) while hospitalization after PCI accounted for only 5.8% (range 2.0-12.7%) of 30-day total cost. Facilities with higher hospitalization rates were not more expensive (Spearman (cid:545) =0.16; 95% confidence interval, -0.09 to 0.39; p value=0.21). Conclusions — In this national study, hospitalizations in the 30-days after PCI accounted for only 5.8% of 30-day cost and facility-level cost was not correlated with hospitalization rates. This challenges the focus on reducing hospitalizations after PCI as an effective means of improving healthcare value. Opportunities remain to improve PCI value by reducing variation in total cost of PCI without compromising patient outcomes. PPPatieieentntnt aaaccccccessss ss ananand dd 1-1-1-yeear oooutututcococommmes s ofofof d pepprcccutaneous corrronnaryyy iiintervrvveeention facccillitiesss aaand
Alveolar epithelial ion and fluid transport: β-adrenergic regulation of amiloride-sensitive lung sodium channels

We investigated the mechanism by which cAMP increases sodium transport in lung epithelial cells. Alveolar type II (ATII) cells have two types of amiloride-sensitive, cation channels: a nonselective cation channel (NSC) and a highly selective channel (HSC). Exposure of ATII cells to cAMP, β-adrenergic agonists, or other agents that increase adenylyl cyclase activity increased activity of both channel types, albeit by different mechanisms. NSC open probability (P o ) increased severalfold when exposed to terbutaline, isoproterenol, forskolin, or cAMP analogs without any change in NSC number. In contrast, terbutaline increased HSC number with no significant change in HSC P o . For both channels, the effect of terbutaline was blocked by propranolol and H-89, suggesting a protein kinase A (PKA) requirement for β-adrenergic-induced changes in channel activity. Terbutaline increased cAMP levels in ATII cells, but intracellular calcium also increased. Calcium sequestration with BAPTA blocked β-adrenergic-induced increases in NSC P o but did not alter HSC activity. These observations suggest that β-adrenergic stimulation increases intracellular cAMP and activates PKA. PKA increases HSC number and increases intracellular calcium. The increase in calcium increases NSC P o . Thus increased cAMP levels are likely to increase lung sodium transport regardless of which channel type is present.
Infrastructure-Based Pedestrian Risk Tagging Methodology to Support AV Risk Assessment

Safety is paramount in AV deployment. Traditionally, AV safety is incorporated during development by identifying the failure of vehicular components using risk and scenarios-based validation approaches with risk indicators. The main challenge of having a comprehensive risk assessment for AV safety is to include all potential complex environments that could occur in real-time, which is more critical for higher AV automation levels. Real-world real-time risk assessment research addresses this shortcoming by providing an advanced warning to the AV during deployment either at the vehicle level or at the infrastructure level. This paper proposes a risk tagging methodology to quantitatively risk tag the severity rating of the real-world environment for real-time risk assessment of AV using the existing roadside infrastructure. The proposed methodology - Spatial-Temporal Risk Estimation Ensemble Technique (STREET), provides advanced risk indicators in the form of pedestrian risk tag figure and time to collision value to the AV. This paper includes the evaluation of STREET, tested on four events over a pre-defined uncontrolled traffic scene from the infrastructure and validated using ground truth and heatmap of pedestrian occurrence. This methodology includes three different algorithms developed to emphasize different events depending on the AV risk and safety management strategy. The STREET reduces the bandwidth needed compared to traditional approaches of streaming video images for lightweight integration of AV risk assessment. The outcome of the pedestrian risk tag from STREET can be used as a severity rating for the existing real-time risk assessment of AV via cooperative mode.
Short review on environment and health effect of nanotoxicology

Nanotechnology is a brand-new area of scientific research that has revolutionized the manufacturing sector. The emphasis of this revolution was on the large-scale development of nano-based materials. Materials confinement in small structures, quantum mechanics, the high surface volumes ratio or other unusual properties, phenomena, and processes dominate nanoparticle behavior use of the nanomaterial containing items on the rise, posing a threat to the environment and human health. For the sake of human health and protection in the community, it's important to understand the toxicity of engineered nanomaterials or nano-based products. Nanotoxicology aims to identify potential toxins' toxicological practices in nanomaterials and these products to assess how these materials endanger human health. In this sense, nanoparticles and their fate in the atmosphere have been examined concerning air, water, and soil. Nanomaterials' health effects, such as their impact on various organ systems, have also been mentioned.
Effects of Sous Vide Cooking on Physicochemical, Structural, and Microbiological Characteristics of Cuttlefish, Octopus, and Squid

ABSTRACT This study investigated the physicochemical (pH, moisture, protein, fat, ash, TBA), color (L*, a*, b*), and textural properties (TPA and extended craft knife), mineral content, fatty acid composition, and microbiological properties of raw and sous vide (SV) cooked cuttlefish (at 95°C for 13 min), octopus (at 95°C for 30 min), and squid (at 95°C for 10 min). The pH, protein, and L* values of these samples increased with the cooking. No significant alterations in lipid oxidation were determined in the samples. A gradual decrease in fatty acid with SV cooking was observed. Sulfur was found as the major mineral content in these cephalopods, followed by potassium, sodium, and phosphorus. Thermal treatment influenced the textural properties of the SV cooked samples, in which hardness, gumminess, chewiness, and resilience lower than raw samples was observed. The firmness values of the samples also decreased with the SV cooking. The treatment had significant positive effects on the total mesophilic aerobic bacteria, total coliform, Escherichia coli, and Staphylococcus aureus counts. Vibrio parahaemolyticus (<2 log cfu/g) was not found in the raw and cooked samples. As a result, SV was found to be an effective cooking method for preparing cuttlefish, octopus, and squid.
Choose Your Own Emotion: Predictors of Selective Exposure to Emotion-Inducing Climate Messages

ABSTRACT The contemporary high-choice media landscape offers users considerable latitude to select media content. When it comes to media messaging about science issues like climate change, it is unclear whether audiences gravitate toward different kinds of emotionally evocative messages and what psychosocial factors underlie those preferences. Here, we presented young adults (N = 1,493) with three climate change videos to choose from (“funny,” “scary,” “informational”) and found more participants selected funny content than scary or informational. Contradicting hypotheses derived from mood management theory, negative mood was associated with selecting the scary video. Conservatives preferred the funny and scary video to the informational video, but gender identity was the strongest predictor of selective exposure with women preferring funny and scary videos to informational.
Cuidado ao doente de tuberculose na Estratégia Saúde da Família: percepções de enfermeiras

The objective of this study was to analyze the nurses' perceptions regarding tuberculosis control, according to the theoretical axis of comprehensive healthcare and the concepts of attachment and teamwork. This qualitative study involved 13 nurses from the Family Health Strategy of a priority city in the metropolitan region of Joao Pessoa, Paraiba, Brazil. Data were collected in focal groups and subjected to thematic content analysis. Factors that strengthen tuberculosis control were: supervised treatment, free medication and the provision of supplies. Weakening factors were: worker's turnover, the lack of encouragement for patients and incipient educational actions. The factors that, according to the nurses, weaken tuberculosis patient care should be reviewed by administrators, workers, users and educators with a view to redefining healthcare activities that strengthen attachment, comprehensive healthcare and teamwork.
The Voltage-gated Proton Channel Hv1 Is Required for Insulin Secretion in Pancreatic β Cells

Here, we demonstrate that the voltage-gated proton channel Hv1 represents a regulatory mechanism for insulin secretion of pancreatic islet β cell. In vivo, Hv1-deficient mice display hyperglycemia and glucose intolerance due to reduced insulin secretion, but normal peripheral insulin sensitivity. In vitro, islets of Hv1-deficient and heterozygous mice, INS-1 (832/13) cells and islets with siRNA-mediated knockdown of Hv1 exhibit a marked defect in glucose-, sulfonylurea-, K+-, arginine-induced insulin secretion. Hv1 deficiency decreases both insulin and proinsulin contents, and has an impairment on glucose- and sulfonylurea-induced intracellular Ca2+ homeostasis and membrane depolarization. Furthermore, loss of Hv1 decreases insulin-containing granule pH and increases cytosolic pH in INS-1 (832/13) cells. In addition, histologic studies show a decrease in α and β cell masses in islets of Hv1-deficient mice, and a significant reduction at Hv1 expression levels in pancreatic β cells of streptozotocin (STZ)-induced diabetes mice and high-glucose induced INS-1 (832/13) cell dysfunction. Collectively, our in vitro and in vivo results indicate that Hv1 is required for insulin secretion in the β cell and a major link between β cell dysfunction and diabetes. Our study sheds light on a new biological function of the proton channel.
Paving the Way for Novices: How to Teach AI for K-12 Education in China

In response to the trend that artificial intelligence (AI) is becoming the main driver for social and economic development, enhancing the readiness of learners in AI is significant and important. The state council and the ministry of education of China put AI education for K-12 schools on a high priority in order to foster local AI talents and reduce educational disparities. However, the AI knowledge and technical skills are still limited for not only students but also the school teachers. Furthermore, many local schools in China, especially in the rural areas, are lack of the necessary software and hardware for teaching AI. Hence, we designed and implemented a structured series of AI courses, built on an online block-based visual programming platform. The AI courses are free and easily accessible for all. We have conducted the experimental classes in a local school and collected the results. The results show that the learners in general gained significant learning progress on AI knowledge comprehension, aroused strong interests in AI, and increased the degree of satisfaction towards the course. Especially, our practices significantly increased computational thinking of the students who were initially staying at a lower level.
Toward Predicting Patient’s Satisfaction of Indoor Environmental Quality in Jordanian Hospitals using SVM and K-NN Machine Learning Algorithms

The indoor environment is an essential aspect of hospital design because it impacts patients’ health, well-being, and healing process. Despite that machine learning has been widely employed in various fields, few studies have looked at how machine learning may be used to improve Indoor Environmental Quality (IEQ) in hospitals. As a result, the current study uses a machine learning approach to bridge this gap. To assess the quality of the indoor environment, the researchers used mixed design methodologies. Also, self-reported data and field monitoring of environmental indicators within patients’ rooms were used to collect data from King Abdullah University Hospital (KAUH) as a sample of all Jordanian hospitals. The experiments were carried out with the same dataset for each training and testing after it was split, and the results were evaluated using the same classification metrics. It was revealed that when C equaled 0.01, the Support Vector Machine (SVM) with the linear kernel had higher accuracy in predicting patient satisfaction than other SVM kernels and the K-Nearest Neighbor (K-NN) algorithm.
1-Degree-of-Freedom Robotic Gripper With Infinite Self-Twist Function

This study proposed a novel robotic gripper that can achieve grasping and infinite wrist twisting motions using a single actuator. The gripper is equipped with a differential gear mechanism that allows switching between the grasping and twisting motions according to the magnitude of the tip force applied to the finger. The grasping motion is activated when the tip force is below a set value, and the wrist twisting motion is activated when the tip force exceeds this value. “Twist grasping,” a special grasping mode that allows the wrapping of a flexible thin object around the fingers of the gripper, can be achieved by the twisting motion. Twist grasping is effective for handling objects with flexible thin parts, such as laminated packaging pouches, that are difficult to grasp using conventional antipodal grasping. In this study, the gripper design is presented, and twist grasping is analyzed. The gripper performance is experimentally validated.
A Survey on Field Effect Transistor Based Hydrogen and Nitrogen Gas Sensors

The presented work encircles the survey on different types of Nitrogen and Hydrogen gas sensor with the modified field-effect transistors (FETs) structures. By modifying the structure, through addition of different kind of particles (palladium, platinum, tungsten) or tubes (carbon nanotubes) , the unique sensing device designs are achieved. The structural overview of CNT-based FETs (CNTFETs), Pd-FET, Dual FET, and Tungsten gate FET for Nitrogen and Hydrogen gas detection, their sensing mechanisms, sensitivity are mainly the emphasis of this review work. The COSFET (Chalcogenide-oxide-siliconFET), CNTFET, WO3MOS2 (Tungsten trioxide- Molybdenum disulfide) , are reviewed as nitrogen gas sensor having sensitivity of 100,1.2,45 respectively with-respect-to time and PNINGAA-FET(n+ source pocket doped PIN gate all around tunnel FET), Pd-MOSFET(Palladium-based Trench Gate MOSFET) and Dual-FET used as a hydrogen gas sensor having sensitivity of 105, 10 and 100 with-respect-to pressure in Torr.
Qualidade de vida na perspectiva de pessoas com problemas respiratórios crônicos: a contribuição de um grupo de convivência

This convergent care research was carried out in a social group of persons with chronic respiratory diseases and aimed to identify the elements affecting the quality of life of persons with chronic respiratory problems, and to understand how the educative practice in a social group has contributed to the quality of life of persons with a chronic health condition. Data were collected at group meetings, during which the statements of eleven subjects and two family members were tape-recorded. Data analysis showed that controlling conflicting feelings, continuing to fight for a better life, overcoming one's limitations brought about by disease and treatment and getting family support are factors that affect the quality of life of persons with chronic respiratory problems. The study also made evident that health education acquired through social groups brings effective outcomes in promoting quality of life among the study participants.
Mechanisms of Synaptic Vesicle Exo- and Endocytosis

Within 1 millisecond of action potential arrival at presynaptic terminals voltage–gated Ca2+ channels open. The Ca2+ channels are linked to synaptic vesicles which are tethered by active zone proteins. Ca2+ entrance into the active zone triggers: (1) the fusion of the vesicle and exocytosis, (2) the replenishment of the active zone with vesicles for incoming exocytosis, and (3) various types of endocytosis for vesicle reuse, dependent on the pattern of firing. These time-dependent vesicle dynamics are controlled by presynaptic Ca2+ sensor proteins, regulating active zone scaffold proteins, fusion machinery proteins, motor proteins, endocytic proteins, several enzymes, and even Ca2+ channels, following the decay of Ca2+ concentration after the action potential. Here, I summarize the Ca2+-dependent protein controls of synchronous and asynchronous vesicle release, rapid replenishment of the active zone, endocytosis, and short-term plasticity within 100 msec after the action potential. Furthermore, I discuss the contribution of active zone proteins to presynaptic plasticity and to homeostatic readjustment during and after intense activity, in addition to activity-dependent endocytosis.
Exploring Expressions of Possible Selves with High School and College Students with Learning Disabilities

In this article, we explore a program designed to engage high school and college students with learning disabilities (LD) in conversations about their hopes, expectations, and fears for the future. We explore the mindset of students by focusing on their self-identified passions for life and sense of strengths and limitations. We found that males and females differed in goals related to Academics, Work Ethic, Degree Specific Statements, and Money and Finances. For example, females emphasized “Academic Goals” more frequently than males and focused on topics such as GPA and work ethic in school. However, males made more “Degree Specific Statements” than females, more often emphasizing the desire to be financially stable or have a career with a large income. These differences suggest that college transition staff may want to focus on goals identified by male and female students with LD as a way to be more responsive to student self-identified goals.
A Model for the Prediction of Lifetime Profit Estimate of Dairy Cattle (Student Abstract)

In livestock management, the decision of animal replacement requires an estimation of the lifetime profit of the animal based on multiple factors and operational conditions. In Dairy farms, this can be associated with the profit corresponding to milk production, health condition and herd management costs, which in turn may be a function of other factors including genetics and weather conditions. Estimating the profit of a cow can be expressed as a spatio-temporal problem where knowing the first batch of production (early-profit) can allow to predict the future batch of productions (late-profit). This problem can be addressed either by a univariate or multivariate time series forecasting. Several approaches have been designed for time series forecasting including Auto-Regressive approaches, Recurrent Neural Network including Long Short Term Memory (LSTM) method and a very deep stack of fully-connected layers. In this paper, we proposed a LSTM based approach coupled with attention and linear layers to better capture the dairy features. We compare the model, with three other architectures including NBEATs, ARIMA, MUMU-RNN using dairy production of 292181 dairy cows. The results highlight the performence of the proposed model of the compared architectures. They also show that a univariate NBEATs could perform better than the multi-variate approach there are compared to. We also highlight that such architecture could allow to predict late-profit with an error less than 3$ per month, opening the way of better resource management in the dairy industry.