Miracle-dz/UniFAR-FTUs huggingface dataset:
Pancreatic cancer progression and mortality predicted by depression and anxiety: a systematic review and meta-analysis protocol

Although the relationship between psychological factors and pancreatic cancer outcomes has been widely discussed, controversy remains. We will for the first time systematically summarize the literature to explore the correlation of anxiety and depression to the prognosis of patients with pancreatic cancer. The findings will fill existing research gaps, informing healthcare providers about better psychological care and medical treatment. The following databases will be retrieved from their inception to July 2023: Cochrane Library, MEDLINE (PubMed), Web of Science, EMBASE, and four Chinese databases (Chinese National Knowledge Infrastructure, Wanfang Database, Chinese Biomedical Literature Database, and Chongqing VIP Chinese Science and Technology Periodical Database). The World Health Organization Clinical Trials Registry, Chinese Clinical Registry, and ClinicalTrials.gov will be searched to identify other related studies. A manual search will be performed to identify missing eligible studies based on the reference list of selected articles. The search will focus on studies published in Chinese or English. To assess the risk of bias in the selected articles, Newcastle-Ottawa Quality Assessment Scale (NOS) will be used for the cohort study. Funnel plots and Egger's test will be used to assess whether publication bias exists. Moreover, the Grading of Recommendations Assessment Development and Evaluation (GRADE) will be utilized to analyze the credibility of the results from selected articles. Two independent evaluators will implement the study selection and data extraction, as well as evaluate the risk of bias and evidence quality. Data will be analyzed using Stata 16.0. Trial registration: PROSPERO registration number is CRD42022366232.
Facies architecture of submarine channel deposits on the western Niger Delta slope: Implications for grain‐size and density stratification in turbidity currents

High‐resolution bathymetry, seismic reflection, and piston core data from a submarine channel on the western Niger Delta slope demonstrate that thick, coarse‐grained, amalgamated sands in the channel thalweg/axis transition to thin, fine‐grained, bedded sands and muds in the channel margin. Radiocarbon ages indicate that axis and margin deposits are coeval. Core data show that bed thickness, grain size, and deposition rate strongly decrease with increasing height above channel thalweg and/or distance from channel centerline. A 5 times decrease in bed thickness and 1–2 ψ decrease in grain size are evident over a 20 m elevation change (approximately the elevation difference between axis and margin). A simplified in‐channel sedimentation model that solves vertical concentration and velocity profiles of turbidity currents accurately reproduces the vertical trends in grain size and bed thickness shown in the core data set. The close match between data and model suggests that the vertical distribution of grain size and bed thickness shown in this study is widely applicable and can be used to predict grain size and facies variation in data‐poor areas (e.g., subsurface cores). This study emphasizes that facies models for submarine channel deposits should recognize that grain‐size and thickness trends within contemporaneous axis‐margin packages require a change in elevation above the thalweg. The transition from thick‐bedded, amalgamated, coarser‐grained sands to thin‐bedded, nonamalgamated, finer‐grained successions is primarily a reflection of a change in elevation. Even a relatively small elevation change (e.g., 1 m) is enough to result in a significant change in grain size, bed thickness, and facies.
Real-Life Multicenter Experience of Venetoclax in Combination with Hypomethylating Agents in Previously Untreated Adult Patients with Acute Myeloid Leukemia in Greece

Background: The landscape of first-line treatment for acute myeloid leukemia (AML) patients ineligible for intensive chemotherapy has changed remarkably after venetoclax approval. Accumulating real-world data further apprises us with more knowledgeable use. To assess the efficacy and safety challenges in the real-life setting of the combination of hypomethylated agent (HMA) and venetoclax, we conducted a multi-center retrospective study. Methods: Forty adult AML patients treated with the combination of HMA and venetoclax as a first-line treatment after full approval (2020) were included. To confirm VIALE-A results, this group was compared to a historical cohort of 17 chemotherapy-ineligible AML patients treated with HMA monotherapy before 2020. Results: The combination of HMA-venetoclax achieved a composite complete response rate of 86.8% (p < 0.001), median overall survival, and event-free survival of 33.8 and 19.7 months, respectively, in a median follow-up of 17.8 months (pos < 0.001, HR = 0.276, CI: 0.132–0.575, pEFS = 0.004, HR = 0.367, CI: 0.174–0.773). High rates of neutropenia (90%) and consequent infection rates (57.5%) were noted. Only 55% of our patients received antifungal prophylaxis, as its use remains controversial, and invasive fungal infections were presented in 7.5%. Conclusions: Evidently, venetoclax-HMA yields high response rates and profound survival benefits in real life and has changed our approach to alternative chemotherapy options.
Improving conversion rate prediction via self-supervised pre-training in online advertising

The task of predicting conversion rates (CVR) lies at the heart of online advertising systems aiming to optimize bids to meet advertiser performance requirements. Even with the recent rise of deep neural networks, these predictions are often made by factorization machines (FM), especially in commercial settings where inference latency is key. These models are trained using the logistic regression framework on labeled tabular data formed from past user activity that is relevant to the task at hand.Many advertisers only care about click-attributed conversions, which are conversions that occurred after a user has clicked on an ad. A major challenge in training models that predict conversions-given-clicks comes from data sparsity - clicks are rare, conversions attributed to clicks are even rarer. However, mitigating sparsity by adding conversions that are not click-attributed to the training set impairs model calibration, causing the mean prediction to no longer converge to the actual CVR. Since calibration is critical to achieving advertiser goals, this is infeasible.In this work we use the well-known idea of self-supervised pre-training, and use an auxiliary auto-encoder model trained on all conversion events, both click-attributed and not, as a feature extractor to enrich the main CVR prediction model. Since the main model does not train on non click-attributed conversions, this does not impair calibration. We adapt the basic self-supervised pre-training idea to our online advertising setup by using a loss function designed for tabular data, facilitating continual learning by ensuring auto-encoder stability, and incorporating a neural network into a large-scale real-time ad auction that ranks tens of thousands of ads, while conforming to the strict latency constraints, and without incurring a major engineering cost. We evaluate our approach and show improvements both offline, during training, and in an online A/B test. Following its success in A/B tests, our solution is now fully deployed to the Yahoo native advertising system, and its impact is measured in millions of dollars annually.
Nutrient Harvest Index and Soil Available Nutrients of Rice (Oryza Sativa) as Influenced by System of Rice Intensification (Sri) Practices

A field study was conducted in sandy loam soil during kharif to evaluate the different SRI practices in lowland rice ecosystem. The treatments viz . , YOSC, NOSC, YMSC, YOSH, NMSC, NOSH, YMSH, YORH, NMSH, YMRH, NORH and NMRH were replicated thrice in a Randomised Block Design in which Y refers to young seedlings of 14 days old; N refers to normal seedlings of 21 days old; O refers to one seedling hill -1 ; M refers to multiple seedlings (3 seedlings hill -1 ); S refers to square planting (22.5 cm x 22.5 cm); R refers to rectangular planting (12.5 cm x 10.0 cm); C refers to conoweeding and H refers to hand weeding. The results revealed that the combination ofYoung seedling, One seedling, Square planting and Conoweeding (YOSC) recorded higher nutrient uptake, nitrogen harvest index, soil available nitrogen, yield and grain harvest index.
Overexpression of EPAC2 reduces the invasion of glioma cells via MMP-2

Exchange proteins directly activated by cAMP (EPACs) are crucial cyclic adenosine 3′,5′-monophosphate- determined signaling pathway intercessors, which are associated with the pathogenesis of neurological disorders and numerous human diseases. To the best of our knowledge, the role of EPAC2 signaling via matrix metalloproteinase 2 (MMP-2) in the pathogenesis of glioma has not been studied. Therefore, the present study focused on the role of EPAC2 in glioma, and assessed the invasiveness of human glioma cell lines following EPAC2 overexpression. Expression levels of EPAC2 in normal brain tissues and clinical glioma specimens were detected by western blotting. An EPAC2 overexpression vector was transfected into U251 and U87 cell lines to increase the expression levels of EPAC2. Expression levels of MMP-2 were detected by western blotting, and the invasive abilities of glioma cells were detected by a Transwell assay. EPAC2 was relatively highly expressed in normal brain tissue, while EPAC2 expression was significantly decreased in clinical glioma specimens (P<0.01). In vitro transfection of EPAC2 overexpression vector significantly reduced the MMP-2 protein levels of glioma cells, and, at the same time, the invasive cell number was significantly decreased in a Transwell assay. The present study demonstrated that MMP-2 regulation via EPAC2 overexpression is a novel promising therapeutic route in malignant types of glioma.
Implementation and Use of Clinical Decision Support System in Malawi National ART EMR System

The introduction of Malawi national antiretroviral therapy (NART) electronic medical record (EMR) system has improved the management and reporting of ART patient data. Designed to aid in decision-making by providers for individual patients in their care, the system has been integrated with a Clinical Decision Support System (CDSS). NART EMR system was introduced in 2006, and by 2021, it had been extended to over 206 healthcare facilities in the country. Despite several evaluations conducted on the NART EMR, there has been limited attention given to evaluating the implementation and usage of the CDSS within the NART EMR system. Hence, the study sought to establish how CDSS in the NART EMR system has been implemented and used by healthcare providers in Malawi to improve decision making on an individual patient on antiretroviral therapy (ART) at any point in time. The study employed a qualitative methodology, gathering data through observations, interviews, and an in-depth analysis of the system. The study establishes that smooth integration of CDSS in EMR system into regular and normal clinical workflow contributes to the success of CDSS use. Despite the successes of CDSS in EMR system, issues of system quality and information quality must be addressed during design and implementation of the CDSS to enhance efficiency and effectiveness of the system. The study suggests that those responsible for implementation should prioritize improving the underlying logic of the clinical decision support intervention in order to address existing concerns and improve the accuracy of the provided information. Additionally, the study recommends active consultation with the system's real users during the implementation process.
Uveal melanoma: Recent advances in immunotherapy

Uveal melanoma (UM) is the most common primary intraocular cancer in adults. The incidence in Europe and the United States is 6-7 per million population per year. Although most primary UMs can be successfully treated and locally controlled by irradiation therapy or local tumor resection, up to 50% of UM patients develop metastases that usually involve the liver and are fatal within 1 year. To date, chemotherapy and targeted treatments only obtain minimal responses in patients with metastatic UM, which is still characterized by poor prognosis. No standard therapeutic approaches for its prevention or treatment have been established. The application of immunotherapy agents, such as immune checkpoint inhibitors that are effective in cutaneous melanoma, has shown limited effects in the treatment of ocular disease. This is due to UM’s distinct genetics, natural history, and complex interaction with the immune system. Unlike cutaneous melanomas characterized mainly by BRAF or NRAS mutations, UMs are usually triggered by a mutation in GNAQ or GNA11. As a result, more effective immunotherapeutic approaches, such as cancer vaccines, adoptive cell transfer, and other new molecules are currently being studied. In this review, we examine novel immunotherapeutic strategies in clinical and preclinical studies and highlight the latest insight in immunotherapy and the development of tailored treatment of UM.
Decline of coral reefs during late Paleocene to early Eocene global warming

Introduction Conclusions References Tables Figures Back Close Full Screen / Esc Abstract Introduction Conclusions References Tables Figures Back Close Full Screen / Esc Abstract Since the 1980s the frequency of warming events has intensified and simultaneously widespread coral bleaching, and enhanced coral mortality have been observed. Yet, it remains unpredictable how tropical coral reef communities will react to prolonged adverse conditions. Possibly, coral reef systems are sufficiently robust to withstand 5 continued environmental pressures. But if coral mortality increases, what will platform communities of the future look like? The co-evolution of early Paleogene carbonate platforms and palaeoclimate may provide insight. Here we document the impact of early Paleogene global warming on shallow-water carbonate platforms in the Tethys. Between 59 and 55 Ma, three discrete stages in platform development can be identified 10 Tethys-wide: during the first stage carbonate platforms mainly consisted of coralgal reefs; during the second – transitional – stage coralgal reefs thrived only at middle latitudes and gave way to larger foraminifera as dominant carbonate producer in low latitudes; finally, during the third stage, newly developing larger foraminifera lineages completely took over the role as main carbonate-producing organisms in low to middle 15 latitudes. We postulate that rising temperatures led to a stepwise demise of Paleocene coral reefs, giving way to an unprecedented expansion of larger foraminifera, dominating Tethyan platforms during the early Eocene.
Determining the extent of declining pasture productivity with nitrogen fertiliser

Declining productivity of sown pastures due to a reduction in plant available soil nitrogen has typically reduced grass and beef production by 50% since initial land development within the Brigalow bioregion of southern and central Queensland. As this decline continues, it’s estimated it will cost the northern beef industry more than $17 billion over the next 30 years. To assist landholders determine the extent of declining pasture productivity on their own properties, and assess the magnitude of response if more nitrogen is made available, nitrogen fertiliser was applied to approximately 70 replicated and non-replicated sites across southern and central Queensland between 2012 and 2014. Nitrogen (N) fertiliser as Green Urea NV® (Incitec Fertilisers) was broadcast onto existing grass-pastures in the lead up to a forecast rainfall event in summer. A range of rates were applied, from 25 – 200 kg N/ha, and dry matter yields and protein levels were measured. At all sites the grass pasture responded to the added nitrogen, with the magnitude of response dependant on the amount of nitrogen applied. As the production from sown pastures continues to decline, options that improve nitrogen supply and address this decline will be required to improve beef production across the northern region.
Benchmarking of Wind Turbine Wake Models in Large Offshore Windfarms

Quantifying accurately wind turbine wakes is a key aspect of wind farm economics in large wind farms. This research compares three engineering wake models with power production data from the Horns Rev and Lillgrund offshore wind farms. Single and multiple wake cases are investigated to verify the performance of the models in different conditions. The simulations reveal that the three wake models have similar behaviours for both wind farms although the turbine spacing and the turbulence intensity are different. The results prove the robustness of the models to provide accurate power predictions when the simulations are averaged over wind direction sectors of 30◦. However, all models significantly underpredict the power production of a single row of wind turbines using narrow sectors of 3◦ or 5◦. This discrepancy is discussed and justified by the wind direction uncertainty included in the datasets.
Multiobjective Hyperparameter Optimization of Artificial Neural Networks for Optimal Feedforward Torque Control of Synchronous Machines

Multiobjective hyperparameter optimization is applied to find optimal artificial neural network (ANN) architectures used for optimal feedforward torque control (OFTC) of synchronous machines. The proposed framework allows to systematically identify Pareto optimal ANNs with respect to multiple (partly) contradictory objectives, such as approximation accuracy and computational burden of the considered ANNs. The obtained Pareto optimal ANNs are trained and implemented on a realtime system and tested experimentally for a nonlinear reluctance synchronous machine against non-Pareto optimal ANN designs and a state-of-the-art OFTC approach. Finally, based on the most recent results from ANN approximation theory, guidelines for Pareto optimal ANN-based OFTC design and implementation are provided.
Health Education Initiatives for People Who Have Experienced Prison: A Narrative Review

Due to the selectiveness of criminal systems and the context of social vulnerability, there is a high prevalence of health problems among individuals with a history of incarceration. When there is an insufficient level of health care, prior clinical conditions can worsen, and health education can be a response to this problem. Health education is a process of building health knowledge that is intended to facilitate thematic appropriation by the population that enables people to access, understand, and use health-related information for health improvement. In the context of criminal justice, health education can contribute to the successful transition of people who have experienced prison from their custody to the community setting. This study aimed to identify, synthesize, and critically evaluate peer-reviewed evidence concerning health education initiatives developed during or after incarceration aimed at people released from prison. A narrative review methodology was used to analyze 19 studies about health education interventions for prisoners or people who were arrested. Initiatives were identified in five countries, which showed differences in approaches, with motivational interviewing and group sessions standing out in the studies. All of them were grouped into the following themes: HIV and other sexually transmitted infections, alcohol, opioids and other substances, tuberculosis, and women’s health. We have not performed a quality assessment of the studies included (using checklists such as PRISMA, AMSTAR, or SANRA) as this study is a narrative review and was not intended to be a systematic review or meta-analysis. This review has the potential impact of informing future health education initiatives and policies for individuals transitioning from prison.
Learning analytics for enhanced professional capital development: a systematic review

Background/Motivation This article presents a systematic review aimed at examining the utilization of learning analytics (LA) to enhance teachers’ professional capital. Aim The study focuses on three primary research questions: (1) exploring the characteristics and approaches of LA in professional capital, (2) investigating suggestions from LA for assessing and improving professional capital, and (3) examining variables studied in enhancing the most intricate dimension of professional capital using LA. Methodology To address the research objectives, a systematic review was conducted focusing on the key concepts “learning analytics” and “professional capital. ” Following the procedures outlined encompassed in four stages: identification, screening, inclusion, and adequacy. The PRISMA 2009 protocol guided the systematic review process. Principal findings The findings of the study underscore the efficacy of LA as a catalyst for improving professional capital, particularly through collaborative learning and the utilization of tools like forums and online learning platforms. Social capital emerges as a pivotal component in integrating diverse types of professional capital, fostering opportunities for knowledge creation and social networking. Conclusion/Significance In conclusion, the study highlights the paramount significance of addressing teachers’ professional capital development through collaborative approaches and leveraging technology, particularly in primary education. The article concludes by emphasizing the imperative for more research and knowledge dissemination in this field, aiming to ensure equity in learning and address the challenges posed by the COVID−19 pandemic.
Effect of short video addiction on the sleep quality of college students: chain intermediary effects of physical activity and procrastination behavior

Introduction The purpose of this study was to examine the impact of short video addiction on college students' sleep quality and to elucidate the mechanism underlying this relationship. Thus, we examined the correlation between short video addiction and sleep quality and analyzed the roles of physical activity and procrastination. Methods The Short Video Addiction Scale, Pittsburgh Sleep Quality Index, Aitken Procrastination Inventory, and Physical Activity Rating Scale were administered to 337 college students. Data were analyzed using SPSS 27.0. Pearson's correlation analysis and mediation analysis using the bootstrapping test were performed for the standard method bias test. Results (1) Overall, 25.2% of college students had problems with sleep quality (indicated by a PSQI score ≥ 8). (2) Short video addiction score is positively correlated with college students' sleep quality score; procrastination score was positively associated with both short video addiction score and sleep quality score, and physical activity score was negatively associated with them. (3) Short video addiction significantly positive predicted sleep quality (β = 0.458, P < 0.001), a significant negative predictive effect on physical exercise (β = −0.183, P < 0.001), and a significant positive effect on procrastination behavior (β = 0.246, P < 0.001). After physical exercise and procrastination behavior were entered into the regression equation, short video addiction and procrastination were significantly positive predictors of sleep quality, and physical activity was significantly negative predictor of sleep quality. (4) After accounting for the variables of age, gender, and grade, physical activity and procrastination behaviors independently mediated the association between short-video addiction and sleep quality. Physical activity and procrastination behavior acted as chain mediators in the association between short video addiction and sleep quality, with a chain mediation effect percentage of 1.04%. Short video addiction directly affects college students' sleep quality, indirectly through physical activity and procrastination behavior.