Miracle-dz/UniFAR-FTUs huggingface dataset:
Metabolomic characterization benefits the identification of acute lung injury in patients with type A acute aortic dissection

Introduction: Acute aortic dissection (AAD) often leads to the development of acute lung injury (ALI). However, the early detection and diagnosis of AAD in patients with ALI pose significant challenges. The objective of this study is to investigate distinct metabolic alterations in the plasma samples of AAD patients with ALI, AAD patients without ALI, and healthy individuals. Method: Between September 2019 and September 2022, we retrospectively collected data from 228 AAD patients who were diagnosed with ALI through post-surgery chest X-ray and PaO2/FiO2 assessments. Univariate analysis was employed to identify pre-surgery risk factors for ALI. Additionally, we conducted high-throughput target metabolic analysis on 90 plasma samples, comprising 30 samples from AAD patients with ALI, 30 from patients with AAD only, and 30 from healthy controls. After LC-MS spectral processing and metabolite quantification, the recursive feature elimination with cross-validation (RFECV) analysis based on the random forest was used to select the optimal metabolites as a diagnostic panel for the detection of AAD patients with ALI. The support vector machines (SVM) machine learning model was further applied to validate the diagnostic accuracy of the established biomarker panel. Results: In the univariate analysis, preoperative β-HB and TNF-α exhibited a significant association with lung injury (OR = 0.906, 95% CI 0.852–0.965, p = 0.002; OR = 1.007, 95% CI 1.003–1.011, p < 0.0001). The multiple-reaction monitoring analysis of 417 common metabolites identified significant changes in 145 metabolites (fold change >1.2 or <0.833, p < 0.05) across the three groups. Multivariate statistical analysis revealed notable differences between AAD patients and healthy controls. When compared with the non-ALI group, AAD patients with ALI displayed remarkable upregulation in 19 metabolites and downregulation in 4 metabolites. Particularly, combining citric acid and glucuronic acid as a biomarker panel improved the classification performance for distinguishing between the ALI and non-ALI groups. Discussion: Differentially expressed metabolites in the ALI group were primarily involved in amino acids biosynthesis, carbohydrate metabolism (TCA cycle), arginine and proline metabolism, and glucagon signaling pathway. These findings demonstrate a great potential of the targeted metabolomic approach for screening, routine surveillance, and diagnosis of pulmonary injury in patients with AAD.
MTNA: A deep learning based predictor for identifying multiple types of N-terminal protein acetylated sites

N-terminal acetylation is a specific protein modification that occurs only at the N-terminus but plays a significant role in protein stability, folding, subcellular localization and protein-protein interactions. Computational methods enable finding N-terminal acetylated sites from large-scale proteins efficiently. However, limited by the number of the labeled proteins, existing tools only focus on certain subtypes of N-terminal acetylated sites on frequently detected amino acids. For example, NetAcet focuses on alanine, glycine, serine and threonine only, and N-Ace predicts on alanine, glycine, methionine, serine and threonine. With the growth of experimental N-terminal acetylated site data, it is observed that N-terminal protein acetylation occurs on nearly ten types of amino acids. To facilitate comprehensive analysis, we have developed MTNA (Multiple Types of N-terminal Acetylation), a deep learning network capable of accurately predicting N-terminal protein acetylation sites for various amino acids at the N-terminus. MTNA not only outperforms existing tools but also has the capability to identify rare types of N-terminal protein acetylated sites occurring on less studied amino acids.
The immigrant earnings disadvantage across the earnings and skills distributions : the case of immigrants from the EU ' s new member states in Ireland

The Immigrant Earnings Disadvantage across the Earnings and Skills Distributions: The Case of Immigrants from the EU’s New Member States in Ireland As the movement of population from the New Member States (NMS) of the EU to the older members is a relatively new flow, it is important to build up our knowledge of who is moving within Europe and how they are performing in their destinations. In this paper, we analyse the earnings of immigrants in Ireland from the NMS using a new large-scale dataset on employees in Ireland. In so doing, we add to the emerging strand in the literature on immigrant earnings that looks beyond average earnings differentials and considers variations in such differentials across the earnings and skills distributions. We do this partly by using quantile regressions and also by analyzing earnings differentials within educational categories. We find that the average earnings difference between immigrants from the NMS and natives is between 10 percent and 18 percent, depending on the controls used. However, the difference is found to be either non-existent or low for people with low skill levels and for people at the lower end of the earnings distribution. The difference is higher for those at the upper ends of the skills and earnings distributions. This suggests that the transferability of human capital is a crucial determinant of the immigrant-native earnings gap for NMS immigrants in Ireland. JEL Classification: J31, J61
Lessons from Outstanding County Agents

This article examines outstanding agents, based on a qualitative survey of 10 successful agents from Colorado, Idaho, Wyoming, and Oregon. Interviewees completed a four-question survey about their perceptions about why they are successful, including their own behavior, their clientele, and the resources available to them from the county and state. Extension leadership can make agents more successful if they are mentored by successful agents, are provided resources, including research, and given flexibility. Agents can help their cause if they have a strong work ethic, are knowledgeable, build strong relationships in their territory, and deliver information in a timely manner.
Adaptive Coping Strategies at the Time of COVID-19: The Role of Social and General Trust

Research in the field shows the crucial role of trust in the functioning of many aspects of social life, especially when dealing with emergencies. We report the results of a study (N = 883) carried out in Italy during the first phase of the COVID-19 crisis to assess whether and how social trust (i.e., trust in those who have the authority and responsibility for making decisions, such as the Italian government, the regional government, the Civil Protection, the European Union, the Catholic Church, and the scientific community) and general trust (i.e., trust in the trustworthiness of other individuals, such as Italians and humankind) are associated with the employment of coping strategies in dealing with the challenges of the pandemic. Overall, the results highlight that trust in different authorities and institutions and trust in other human beings are positively associated with the adoption of adaptive coping strategies such as seeking social support, positive reinterpretation and growth, problem-solving orientation, and transcendent orientation. In contrast, they are negatively related to the adoption of maladaptive coping strategies such as avoidance. These findings point out the benefits of various types of trust in helping individuals deal with crises, such as the COVID-19 pandemic.
Hydrologic impacts due to land cover change in the Yellowwood Lake watershed

Stewart, Emily M. M.S.E. , Purdue University, August 2014. Hydrologic Impacts Due to Land Cover Change in Yellowwood Lake Watershed. Major Professor: Keith A. Cherkauer. The Yellowwood Lake watershed in Southern Indiana has experienced land cover change due to forest harvest throughout the last century. A group of local stakeholders have identified sedimentation into the lake and surface erosion as major concerns for the watershed. The main objective of this study is to better understand how forest harvest methods applied within the watershed effect hydrologic and soil erosion processes. Such knowledge is required to develop a more comprehensive plan to protect the watershed. The Distributed Hydrology-Soil-Vegetation Model (DHSVM) was used for this analysis. This is a physically based, distributed hydrology model that simulates the water and energy balance at the scale of the digital elevation model (DEM). The DHSVM sediment model also simulates hillslope erosion by overland flow and raindrop impact. A sensitivity study was conducted on the model to better understand the effect of forest thinning on the hydrology of the watershed, which was simulated by adjusting the user input fractional coverage parameter of the forest vegetation. Updates were made to the calculation of aerodynamic roughness to produce a more continuous change in displacement height with thinning forest density. Current harvest management, as prescribed by the Indiana Department of Natural Resources, was input to the model
Does Decreased Diffusing Capacity of the Lungs for Carbon Monoxide Constitute a Risk of Decompression Sickness in Occupational Divers?

Long-term alterations of pulmonary function (mainly decreased airway conductance and capacity of the lungs to diffuse carbon monoxide (DLCO)) have been described after hyperbaric exposures. However, whether these alterations convey a higher risk for divers’ safety has never been investigated before. The purpose of the present pilot study was to assess whether decreased DLCO is associated with modifications of the physiological response to diving. In this case–control observational study, 15 “fit-to-dive” occupational divers were split into two groups according to their DLCO measurements compared to references values, either normal (control) or reduced (DLCO group). After a standardized 20 m/40 min dive in a sea water pool, the peak-flow, vascular gas emboli (VGE) grade, micro-circulatory reactivity, inflammatory biomarkers, thrombotic factors, and plasmatic aldosterone concentration were assessed at different times post-dive. Although VGE were recorded in all divers, no cases of decompression sickness (DCS) occurred. Compared to the control, the latency to VGE peak was increased in the DLCO group (60 vs. 30 min) along with a higher maximal VGE grade (p < 0.0001). P-selectin was higher in the DLCO group, both pre- and post-dive. The plasmatic aldosterone concentration was significantly decreased in the control group (−30.4 ± 24.6%) but not in the DLCO group. Apart from a state of hypocoagulability in all divers, other measured parameters remained unchanged. Our results suggest that divers with decreased DLCO might have a higher risk of DCS. Further studies are required to confirm these preliminary results.
Notes on Tasmanian Crustacea, with

descriptions of new species

When in Tasmania in January of this year I collected a few specimens of Crustacea in the neighbourhood of Hobart, and also obtained others from Messrs. A. Simson, of Launceston, and L. Rodway, of Hobart. Since my return to New Zealand several specimens have been forwarded to me by Mr. C. Chilton, who obtained them from Mr. R. M. Laing, and a number of others have been received from Mr. Morton. As far as I am aware, no one in Tasmania has devoted special attention to the Crustacea, though a few species have been described in foreign publications from material gathered in the colony.
A literature review of the relationship between governance, funding strategy and sustainability of non-government organizations

The correlation among governance, funding strategy, and sustainability is vital for non-government organizations (NGOs) and is significant to scholars, policymakers, and NGO practitioners. This paper presents an extensive review of existing literature and a thorough analysis of the key factors affecting NGOs' sustainability. The paper defines fundamental concepts, exploring the probable relationship between governance, funding strategy, and NGO sustainability, as well as examining the factors that influence the effectiveness of NGOs. The paper considers the responsibilities of boards of directors, leadership, accountability, and openness in fostering effective NGO governance. Under funding approaches, it investigates various funding sources for NGOs, such as grants, contributions, and social entrepreneurship, along with their associated challenges. Regarding sustainability, the paper scrutinizes financial, programmatic, and organizational sustainability, plus factors that facilitate or impede NGO sustainability. In conclusion, the paper emphasizes the primary discoveries from the literature review and their practical and policy implications. It contends that effective governance, suitable funding methods, and sustainability are vital for NGO success and suggests that NGOs adopt optimal governance practices, diversify funding streams, and emphasize sustainability in their organizational plans. Policymakers can assist NGOs by cultivating an environment that fosters effective governance, grants access to a variety of funding options, and promotes sustainability within the sector. The paper incorporates a wide array of sources and presents an up-to-date examination of the literature concerning the interrelation of governance, funding approaches, and NGO sustainability.
Bouncing back from COVID-19: a Western Australian community perspective

Introduction This study explored the behavioral profiles of residing Western Australians during a COVID-19 lockdown period and transitions in behavior post-lockdown. Methods A total of 313 participants (76% female, age: M = 50.1, SD = 15.7 years) completed behavioral and mental health questionnaire items ~2 months after a 3-month COVID-19 lockdown in October 2020, using a retrospective recall to assess their experience during the lockdown period. Latent transition analysis (LTA) was used to identify behavioral profiles and transitions. Indicators were identified by assessing during–post-lockdown group differences (Kruskal–Wallis, chi-square tests) and profiles described using qualitative open-ended questions. Results Significant indicators included changes in physical activity, leisure screen time, alcohol intake, psychological distress, and loneliness, but not fast food consumption. The significant indicators were used to form LTA models. The five latent class model showed the best model fit (Log-likelihood = −1301.66, AIC = 426.12, BIC = 609.68). Approximately one in four participants reported a change in their behavior profiles after the lockdown ceased. Key differences between the profiles were age, household income, education, resilience, sense of control, existing mental health issues, and social relations. Washing hands and social distancing were the most recalled and effective health campaigns across the classes, with health campaigns encompassing physical activity/alcohol consumption, or domestic violence having the least attention. Discussion Overall, while most participants recovered relatively well after the lockdown period, LTA did identify subgroups such as those who were inactive and lonely experienced more difficulties than other groups, and engagement with public health campaigns differed. The results provide important insights for future public health campaigns on how these campaigns might be diversified to effectively target more people and particular groups to maximize engagement for maintaining people's mental health with additional focus on physical activity, alcohol consumption, and domestic violence.
Programmable Digital-Microfluidic Biochips for SARS-CoV-2 Detection

Biochips, a novel technology in the field of biomolecular analysis, offer a promising alternative to conventional testing equipment. These chips integrate multiple functions within a single system, providing a compact and efficient solution for various testing needs. For biochips, a pattern-control micro-electrode-dot-array (MEDA) is a new, universally viable design that can replace microchannels and other micro-components. In a Micro Electrode Dot Array (MEDA), each electrode can be programmatically controlled or dynamically grouped, allowing a single chip to fulfill the diverse requirements of different tests. This capability not only enhances flexibility, but also contributes to cost reduction by eliminating the need for multiple specialized chips. In this paper, we present a visible biochip testing system for tracking the entire testing process in real time, and describe our application of the system to detect SARS-CoV-2.
Manganese doped cobalt–nickel spinel ferrite via. sol–gel approach: Insight into structural, morphological, magnetic, and dielectric properties

The structural, morphological, magnetic, and dielectric properties of MnxCo0.5-xNi0.5Fe2O4 (x = 0.0, 0.2, and 0.4) synthesized by sol–gel auto-combustion are reported in this paper. X-ray diffraction pattern of the samples confirms the formation of a single-phase spinel ferrite and the crystallite size (D) is in the range of 32.60–33.62 nm. Fourier transform infrared spectra have a vibrational band at 534.20 cm−1 and 420.13 cm−1 which corresponds to the tetrahedral and octahedral sites of the MnxCo0.5-xNi0.5Fe2O4 respectively. Field emission scanning electron microscope reveals the cubic morphology of the synthesized spinel ferrite with inhomogeneous grain size. Vibrating sample magnetometer analysis showed the ferromagnetic nature of all samples. All the samples exhibit a multi-domain because the value of Mr/Ms lies in the range of 0.153–0.336. Dielectric properties reveal the hopping of the charge carrier which has improved the conduction mechanism of the MnxCo0.5-xNi0.5Fe2O4.
A Learning Method to Estimate Multi-compartmental T2 Distributions with low Data Requirements

The estimation of intravoxel distributions of T2 values based on multi-echo MR data is a challenging task. Interestingly, the information above is quite useful to detect damage on brain tissue, e.g. to estimate myelin-water-fraction changes associated with demyelination processes. Currently available methods typically require a long train of echoes, which are not always feasible to acquire. In this work we tackle this problem using state-of-the-art supervised learning convolutional networks to build a robust prediction model on very limited data ( 5 echoes and 4 TR). The methodology identifies myelin abnormalities in a rodent model of a neurological disorder with demyelination.
The Prevalence of Video Game Addiction and Its Relation to Anxiety, Depression, and Attention Deficit Hyperactivity Disorder (ADHD) in Children and Adolescents in Saudi Arabia: A Cross-Sectional Study

Background and objective Video games have become a popular source of entertainment among children and adolescents, not only targeting the young generation but also increasingly popular among older demographics as well. This study aimed to assess the association between video game addiction and depression, anxiety, and attention deficit hyperactivity disorder (ADHD) among children and adolescents in Saudi Arabia. Materials and methods This was a cross-sectional study involving Saudi adolescents aged 12-16 years. A self-administered online survey was distributed on social media (Twitter, WhatsApp, and Snapchat). The survey addressed sociodemographic characteristics (i.e., age, gender, area of residence city, etc.). Arabic versions of the Patient Health Questionnaire-9 (PHQ-9), the seven-item Generalized Anxiety Disorder Scale (PHQ-GAD7), the ADHD Rating Scale-IV (ADHD-RS), and the seven-item Game Addiction Scale (GAS-7) questionnaires were distributed as well, including Arabic terms for depression, anxiety, and ADHD. Results A total of 393 surveys were completed (males: 58.3% vs. females: 41.7%). Of note, 63.1% of the respondents reported playing video games every day with an average of more than five hours of gaming time per day (25.2%). The prevalence of video game addiction was 62.1%. Independent risk factors of video game addiction included being young in age, playing video games every day, playing more than three hours per day, and playing multiplayer games. Furthermore, our findings suggest that a higher video game addiction score is correlated with higher scores in inattention, anxiety, and depression. Conclusion This study found a high prevalence of video game addiction among Saudi children and adolescents. Excessive video game playing negatively influences mental health and leads to issues including anxiety, depression, and ADHD. Also, younger males with an increased rate of regular playtime were more likely to exhibit video game addiction in comparison to the rest of the population. Further research is required to more comprehensively assess the prevalence rate of video game addiction and its effect on the mental health of the younger generation within the region.
An international analysis of career assistance programmes for high-performance athletes

ABSTRACT This study aims to offer a comprehensive analysis of Career Assistance Programmes (CAPs) available for high-performance athletes across the globe, addressing the current state of resources for their career development and transitional periods. The authors examined 23 sport organisations spanning five continents, focusing on aspects such as CAPs’ accessibility, objectives, content, delivery personnel, practitioner training, and self-evaluation methods. Utilising web-based data collection and research tours, the study acquired pertinent information to address the research questions. Deductive content analysis was employed, with the research questions and the Holistic Athlete Career (HAC) model serving as the framework for categorisation. This study offers an in-depth exploration of global CAPs and provide empirical insights into their current practices. The results show resources available to high-performance athletes, while identifying service gaps, necessitating policies to support a wider range of athletes. Notably, advancements have been made in developing training programmes for practitioners; however, the study highlights the need to further investigate the specific competencies that practitioners develop or seek to acquire through such initiatives. It is suggested that sport organisations actively exchange best practices to augment the effectiveness of their CAPs. The study highlights a service gap for athletes not meeting the high-performance threshold for CAP eligibility, limiting access to resources. Consequently, this population faces limited opportunities for career development and may struggle to cope with the challenges stemming from their athletic pursuits. The authors advocate for the expansion of services to address this disparity, ensuring equitable access to resources for athletes at varying performance levels.
A Strengthened Teleconnection of the Quasi‐Biennial Oscillation and Tropical Easterly Jet in the Past Decades in E3SMv1

The Energy Exascale Earth System Model version 1 (E3SMv1) is a new global model that can generate a weakened tropical easterly jet (TEJ) during the easterly quasi‐biennial oscillation (EQBO) and a strengthened TEJ during the westerly QBO (WQBO), which is referred to as the QBO‐TEJ teleconnection. Although the longitudinal structure of the QBO‐TEJ teleconnection is different between reanalysis and simulations, we hypothesize that simulations can still provide insights into the observed long‐term changes in the QBO‐TEJ teleconnection. The Atmospheric Model Intercomparison Project historical simulations (AMIP‐historical) generate a strengthened trend in the correlation between the QBO and TEJ indices in the period of 1950–2014 as in reanalysis. The comparison of the AMIP‐historical and the Coupled Model Intercomparison Project coupled historical simulations (coupled‐historical) shows that the warming of the Indian Ocean has played a vital role in the strengthened QBO‐TEJ teleconnection over the past six decades.