Miracle-dz/UniFAR-FTUs huggingface dataset:
Association of Psychological Readiness to Return to Sports With Subjective Level of Return at 12 Months After ACL Reconstruction

Background: Return-to-sports (RTS) rates after anterior cruciate ligament (ACL) reconstruction (ACLR) differ according to the level at which patients return. It is unclear whether the level of RTS is affected by psychological readiness to return. Purpose: To examine the association between psychological readiness to RTS and subjective RTS level 12 months after ACLR. Study Design: Case-control study; Level of evidence, 3. Methods: A total of 47 patients who underwent unilateral primary ACLR surgery were enrolled. Assessments at 6 and 12 months postoperatively consisted of knee strength testing (isokinetic quadriceps and hamstring strength), the International Knee Documentation Committee Subjective Knee Evaluation Form (IKDC-SKF), and the Anterior Cruciate Ligament-Return to Sport after Injury (ACL-RSI) scale to measure psychological readiness to RTS. Patients were assigned to 1 of 3 subgroups based on their subjective assessment of RTS level at 12 months postoperatively: RTS at or above preinjury level (RTS≥Pre; n = 19), RTS below preinjury level (RTS<Pre; n = 24), or no RTS (n = 4). Two-way mixed-model analysis of variance was used to examine the effects of RTS subgroup, postoperative time point, and group × time interaction with patient characteristics, knee strength, and IKDC-SKF and ACL-RSI scores. Multivariate logistic regression analysis was performed to determine which factors were associated with RTS subgroupings. Results: Significant differences were found among the RTS≥Pre, RTS<Pre, and no-RTS groups in age, ACL-RSI score at 6 and 12 months, quadriceps strength at 6 and 12 months, and IKDC-SKF score at 6 and 12 months (P < .001 for all). Multivariate logistic regression analysis revealed that RTS at or above preinjury level was associated with higher ACL-RSI score at 12 months postoperatively (odds ratio [OR], 1.11; 95% CI, 1.05-1.20; P = .003) and younger age (OR, 0.80; 95% CI, 0.61-0.92; P = .012). Conclusion: The ACL-RSI score was significantly different among the study groups, and the ACL-RSI score at 12 months postoperatively and younger age were associated with RTS at or above preinjury level.
Real-World Presentation and Prognostic Effect of Allogeneic Blood Transfusion during the Intensive Induction Phase in Pediatric Acute Lymphoblastic Leukemia

Simple Summary In China, approximately 15,000 cases of childhood acute lymphoblastic leukemia (ALL) are diagnosed each year, and it is also the most common hematological cancer and the leading cause of tumor death under the age of 18. At present, ALL remains one of the major indications for allogeneic blood (ABT). This study aims to determine associations between ABT during the intensive induction phase of therapy and prognostic effect in a real-world cohort of pediatric patients with ALL. We found that among the blood products, only fresh frozen plasma (FFP) infusion is closely related to the prognosis of childhood ALL. During the intensive induction phase, the indications of FFP transfusion should be strictly grasped, and the total amount of FFP should be controlled and kept below 25 mL/kg. Abstract Purpose: To determine associations between allogeneic blood transfusion (ABT) during the intensive induction phase of therapy and prognostic effect in a real-world cohort of pediatric patients with acute lymphoblastic leukemia (ALL). Methods: A total of 749 pediatric patients who were diagnosed with ALL were enrolled in this study by using a single-center retrospective cohort study method from February 2008 to May 2022. Results: Among the ABT patients, 711 (94.9%) children were transfused with packed red blood cells (PRBCs), 434 (57.9%) with single-donor platelets (SDPs), and 196 (26.2%) with fresh frozen plasma (FFP). Our multivariate analysis demonstrated that FFP transfusion was the unique independent factor that affected both relapse-free survival (RFS) and overall survival (OS). The transfusion of FFP was significantly associated with higher age (p < 0.001), being more likely to receive SCCLG-ALL-2016 protocol (p < 0.001), higher proportion of more than 25 blood product transfusions, more PRBC transfusion (p < 0.001), and higher D33-MRD-positive rates (p = 0.013). Generalized additive models and threshold effect analysis using piece-wise linear regression were applied to identify the cut-off value of 25 mL/kg for average FFP transfusion. K-M survival analysis further confirmed that average FFP transfusion > 25 mL/kg was an independent adverse indicator of inferior outcome in terms of RFS (p = 0.027) and OS (p = 0.033). Conclusions: In blood products, only FFP supplement is closely related to the prognosis of childhood ALL. During the intensive induction phase, the indications of FFP transfusion should be strictly grasped, and the total amount of FFP should be controlled and kept below 25 mL/kg.
The Challenges on The Work Stress of Young College Teachers in L University

This study investigates the challenges encountered by young college teachers at L University and proposes coping mechanisms to address these challenges. The challenges identified in this study include workload, lack of experience, high expectations, work-life balance, and interpersonal dynamics. Through a comprehensive review of relevant literature and interview of key informants, this research examines the specific context of L University. Based on the findings, coping mechanisms are suggested, such as effective time management, professional development opportunities, clear communication of expectations, setting boundaries, prioritizing self-care, building support networks, and developing conflict resolution skills. Implementing these coping strategies can help young college teachers effectively manage their work stress, improve job satisfaction, and maintain a healthy work-life balance. By addressing these challenges, L University can foster a supportive and conducive environment for young teachers, promoting their professional growth and well-being.
Analysis of TRMM 3-Hourly Multi-Satellite Precipitation Estimates Computed in Both Real and Post-Real Time

Satellite data form the core of the information available for estimating precipitation on a global basis. While it is possible to create such estimates solely from one sensor, researchers have increasingly moved to using combinations of sensors in an attempt to improve accuracy, coverage, and resolution. This poster updates a long-term project in which the authors are working to provide routine combined-sensor estimates of precipitation over the entire globe at relatively fine time and space intervals. The goal is to produce these globally complete precipitation estimates on a 25-km grid every 3 hours. Since late January 2002 we have been estimating precipitation for the latitude band 50 degrees N-S within about 6 hours of observation time. This work is 1 of only 2 or 3 such efforts in the world. Now we are preparing to provide similar estimates for the last 5 years. All of this work is being carried out as part of the Tropical Rainfall Measuring Mission (TRMM). Initially, TRMM was focused on providing excellent long-term averages of precipitation in tropical regions, but since its launch in November 1997 continued research has allowed the same satellite and data system to be used for addressing weather-scale problems as well.
Large Scale Variability of Phytoplankton Blooms in the Arctic and Peripheral Seas: Relationships with Sea Ice, Temperature, Clouds, and Wind

Spatially detailed satellite data of mean color, sea ice concentration, surface temperature, clouds, and wind have been analyzed to quantify and study the large scale regional and temporal variability of phytoplankton blooms in the Arctic and peripheral seas from 1998 to 2002. In the Arctic basin, phytoplankton chlorophyll displays a large symmetry with the Eastern Arctic having about fivefold higher concentrations than those of the Western Arctic. Large monthly and yearly variability is also observed in the peripheral seas with the largest blooms occurring in the Bering Sea, Sea of Okhotsk, and the Barents Sea during spring. There is large interannual and seasonal variability in biomass with average chlorophyll concentrations in 2002 and 2001 being higher than earlier years in spring and summer. The seasonality in the latitudinal distribution of blooms is also very different such that the North Atlantic is usually most expansive in spring while the North Pacific is more extensive in autumn. Environmental factors that influence phytoplankton growth were examined, and results show relatively high negative correlation with sea ice retreat and strong positive correlation with temperature in early spring. Plankton growth, as indicated by biomass accumulation, in the Arctic and subarctic increases up to a threshold surface temperature of about 276-277 degree K (3-4 degree C) beyond which the concentrations start to decrease suggesting an optimal temperature or nutrient depletion. The correlation with clouds is significant in some areas but negligible in other areas, while the correlations with wind speed and its components are generally weak. The effects of clouds and winds are less predictable with weekly climatologies because of unknown effects of averaging variable and intermittent physical forcing (e.g. over storm event scales with mixing and upwelling of nutrients) and the time scales of acclimation by the phytoplankton.
α-Mangostin Effectively Inhibits Chikungunya Virus Replication in HepG2 Cells

Chikungunya virus (CHIKV) is an arthropod-transmitted Alphavirus endemic to countries in Africa and Asia, including Indonesia, which causes debilitating arthralgia which can last several years. The rapid spread of CHIKV to new areas makes the discovery of antiviral agents a high priority. α-mangostin is a xanthone from mangosteen (Garcinia mangostana) pericarp and has antiviral activity against Hepatitis C and Dengue viruses. We investigated the antiviral activity of α-mangostin against CHIKV in HepG2 cells in pre-, post- and combination treatments compared to the common antiviral medicine ribavirin, as well their cytotoxicity. Our results show dose-responsive reductions in viral titer in all treatment regimes, with post- and combination treatments being more effective than pre-treatment only (IC50 = 7.79, 5.99 and 6.39 µM, respectively), but with poor specificity (SI = 1.39, 1.81 and 1.70, respectively) compared to ribavirin. Neither compound showed a direct virucidal effect. These results suggest α-mangostin effectively inhibits CHIKV replication in this cell line.
Designing contests for data science competitions: Number of stages and the prize structures

Firms have been proactively holding data science competitions via online contest platforms to look for innovative solutions from the crowd. When firms are designing such competitions, a key question is “What should be a better contest design to motivate contestants to exert more effort? ” We model two commonly observed contest structures (one stage and two stage) and two widely adopted prize structures (high spread and low spread). We employ economic experiments to examine how contest design affects contestants’ effort level. The results reject the base model with rationality assumption. We find that contestants exert significantly more effort in both the first stage and the second stage of the two‐stage contest. Moreover, it is better to assign most prizes to the winner in the two‐stage contest while it does not matter in one stage. To explain the empirical regularities, we develop a behavioral economics model that captures contestants’ psychological aversion to falling behind and continuous exertion of effort. Our findings demonstrate that it is important for contest organizers to account for the nonpecuniary factors that can influence contestants’ behavior in designing a competition.
Discrepancy Analysis between Histology and Molecular Diagnoses in Kidney Allograft Biopsies: A Single-Center Experience

Histology diagnosis is essential for the monitoring and management of kidney transplant patients. Nowadays, the accuracy and reproducibility of histology have been criticized when compared with molecular microscopy diagnostic system (MMDx). Our cohort included 95 renal allograft biopsies with both histology and molecular diagnoses. Discrepancies between histology and molecular diagnosis were assessed for each biopsy. Among the 95 kidney allograft biopsies, a total of 6 cases (6%) showed clear (n = 4) or borderline (n = 2) discrepancies between histology and molecular diagnoses. Four out of the six (67%) were cases with pathologically and clinically confirmed active infections that were diagnosed as mild to moderate T-cell-mediated rejection (TCMR) with MMDx. Two cases showed pathological changes that were not sufficient to make a definitive diagnosis of active rejection via histology, while MMDx results showed antibody-mediated rejection (ABMR). In addition, there were six cases with recurrent or de novo glomerular diseases diagnosed only via histology. All other biopsy results were in an agreement. Our results indicate that histology diagnosis of kidney allograft biopsy is superior to molecular diagnosis in the setting of infections and glomerular diseases; however, MMDx can provide helpful information to confirm the diagnosis of active ABMR.
The use of intravenous immunoglobulin in the treatment of Hashimoto’s encephalopathy: case based review

Background Hashimoto’s encephalopathy (HE) is a controversial immunological neuropsychiatric disease, with a poorly understood pathogenesis. It is characterized by symptoms of acute or subacute encephalopathy which usually occur in the presence of elevated levels of antithyroid antibodies. Even though it is also known as steroid responsive encephalopathy associated with autoimmune thyroiditis (SREAT), some cases appear to be steroid-resistant. This review examined whether treatment of Hashimoto’s encephalopathy with intravenous immunoglobulin (IVIG) is associated with better clinical outcomes than the standard therapy. Additionally, we presented a case of a 59-year-old man who presented with severe neurological manifestations and was successfully treated with intravenous immunoglobulin. Methods The online databases PubMed and EMBASE were searched. Results A total of 1,365 articles were identified. After the deletion of 112 duplicates, 1,253 studies were screened by evaluating the title and abstract, focusing on Hashimoto’s encephalopathy cases where IVIG were used. 846 studies were excluded because they were not relevant to the topic or included pediatric population. Therefore, 407 full-text articles were assessed for eligibility. The final analysis included 14 eligible articles after 393 were excluded (irrelevant texts, not written in English, full-text not available). In the majority of the selected case-reports, IVIG was associated with a good outcome, sometimes even with dramatic improvements in patient’s status. Conclusion In last years, intravenous immunoglobulin therapy proved its utility in Hashimoto’s encephalopathy’s treatment, being a well tolerated therapy associated with remarkable improvement in patient’s status. Further research is still needed in order to define the optimal treatment protocol for Hashimoto’s encephalopathy and to establish if intravenous immunoglobulin can also be used as a first-line therapy, alone or in combination with steroids.
Reducing partner risk: the effect of feedback timing and incentives

Firms’ partners often face a wide range of risks and may experience detrimental effects when these firms do not meet certain targets. In this study, we examine how timing of feedback about target outcomes and the presence of incentives for managers to meet these targets influence managers’ effort and their partners’ willingness to collaborate. We test our hypotheses in a representative ESG setting using a multi-period investment game with a 2 × 2 design where a collaborating partner only realises a return on her investment if the manager of the firm with whom she contracts meets an ESG norm. The risk of not meeting this norm decreases when managers provide costly effort. While results show no significant effect of feedback timing on managers’ effort in the absence of incentives, providing incentives to the manager may be detrimental for effort provision when target outcomes become available after a short time period. We also find that in the absence of incentives, firms’ partners invest more when outcomes become available after a short time period than after a longer time period. Further, when outcomes become available after a short time period, partners invest less when managers receive incentives compared to when managers receive no incentives.
Drug induced liver disease

Drug-induced liver disease can result from dosage-dependent hepatotoxicity or from adverse reactions to drugs used in therapeutic dosage. The latter idiosyncratic hepatotoxins can cause clinical syndromes that mimic all known liver diseases, so that drugs must be considered as the possible causal agent for all unexplained cases of liver disease. The only specific antidote for dosage-dependent hepatotoxicity is N-acetylcysteine (and some other sulfhydryl donors), which is highly effective for the prevention of significant hepatotoxicity after acetaminophen overdose. Early diagnosis and prompt withdrawal of the offending drug is the key to successful management of most drug-induced liver diseases. The mainstay of treatment is supportive care, with careful monitoring for signs of acute liver failure or progression to chronic liver disease. In cases of liver failure, close liaison with a liver transplant center is crucial; referral for liver transplantation should be considered if standard transplant criteria are fulfilled. Pruritus is a major symptom of drug-induced cholestasis; protracted cases may respond to ursodeoxycholic acid. Corticosteroids can be considered for cases of drug-induced hepatitis, especially those with evidence of immune hypersensitivity, if no improvement is seen in 8 to 12 weeks. Although there are no controlled trials, some patients may respond favorably.
Maternal Healthcare Services in a Rural Area of Haryana during the COVID-19 Pandemic: A Community-Based Study

Background: It is well documented that the utilization of maternal healthcare services during pregnancy and childbirth plays a significant role in reducing maternal morbidity and mortality. Disruptions in maternal healthcare services during the coronavirus disease 2019 (COVID-19) pandemic have been reported. However, there is a paucity of literature from rural areas, as most of the previous studies are either record-based or conducted in tertiary care centers. This study aimed to determine the proportion of women who received the recommended maternal healthcare services during the COVID-19 pandemic and to study various factors associated with the utilization of services. Material and Methods: In this community-based study, we assessed the utilization of maternal healthcare services among 520 women residing in the Ballabgarh Block of District Faridabad, Haryana, whose antenatal, intrapartum, and postnatal period coincided with the first wave of COVID-19 pandemic. Domiciliary visits were made, and women were interviewed retrospectively regarding maternal healthcare services utilized by them. The antenatal care (ANC) cards were reviewed, and details were corroborated. Results: Full ANC was received by 15.3% of women, and 45% of women had less than four antenatal visits. 30.9% of participants had cesarean delivery. The proportion of cesarean delivery in private facilities was significantly higher than in government facilities [Odds Ratio (OR) (95% Confidence intervals (CI)) =10.04 (5.87–17.19); P < 0.001]. In multivariate logistic regression, gravidity was negatively associated with full ANC [OR (95% CI) =0.43 (0.25–0.74); P = 0.002]. Conclusion: Fewer women received the recommended maternal healthcare services during the COVID-19 pandemic. Detailed assessment of health systems and factors affecting routine healthcare services, during the pandemic, can help improve the readiness and response in the future.
TCUNet: A Lightweight Dual-Branch Parallel Network for Sea-Land Segmentation in Remote Sensing Images

Remote sensing techniques for shoreline extraction are crucial for monitoring changes in erosion rates, surface hydrology, and ecosystem structure. In recent years, Convolutional neural networks (CNNs) have developed as a cutting-edge deep learning technique that has been extensively used in shoreline extraction from remote sensing images, owing to their exceptional feature extraction capabilities. They are progressively replacing traditional methods in this field. However, most CNN models only focus on the features in local receptive fields, and overlook the consideration of global contextual information, which will hamper the model’s ability to perform a precise segmentation of boundaries and small objects, consequently leading to unsatisfactory segmentation results. To solve this problem, we propose a parallel semantic segmentation network (TCU-Net) combining CNN and Transformer, to extract shorelines from multispectral remote sensing images, and improve the extraction accuracy. Firstly, TCU-Net imports the Pyramid Vision Transformer V2 (PVT V2) network and ResNet, which serve as backbones for the Transformer branch and CNN branch, respectively, forming a parallel dual-encoder structure for the extraction of both global and local features. Furthermore, a feature interaction module is designed to achieve information exchange, and complementary advantages of features, between the two branches. Secondly, for the decoder part, we propose a cross-scale multi-source feature fusion module to replace the original UNet decoder block, to aggregate multi-scale semantic features more effectively. In addition, a sea–land segmentation dataset covering the Yellow Sea region (GF Dataset) is constructed through the processing of three scenes from Gaofen-6 remote sensing images. We perform a comprehensive experiment with the GF dataset to compare the proposed method with mainstream semantic segmentation models, and the results demonstrate that TCU-Net outperforms the competing models in all three evaluation indices: the PA (pixel accuracy), F1-score, and MIoU (mean intersection over union), while requiring significantly fewer parameters and computational resources compared to other models. These results indicate that the TCU-Net model proposed in this article can extract the shoreline from remote sensing images more effectively, with a shorter time, and lower computational overhead.