Miracle-dz/UniFAR-FTUs huggingface dataset:
Revisiting the Characteristics of Stochastic Gradient Noise and Dynamics

In this paper, we characterize the noise of stochastic gradients and analyze the noise-induced dynamics during training deep neural networks by gradient-based optimizers. Specifically, we firstly show that the stochastic gradient noise possesses finite variance, and therefore the classical Central Limit Theorem (CLT) applies; this indicates that the gradient noise is asymptotically Gaussian. Such an asymptotic result validates the wide-accepted assumption of Gaussian noise. We clarify that the recently observed phenomenon of heavy tails within gradient noise may not be intrinsic properties, but the consequence of insufficient mini-batch size; the gradient noise, which is a sum of limited i.i. d. random variables, has not reached the asymptotic regime of CLT, thus deviates from Gaussian. We quantitatively measure the goodness of Gaussian approximation of the noise, which supports our conclusion. Secondly, we analyze the noise-induced dynamics of stochastic gradient descent using the Langevin equation, granting for momentum hyperparameter in the optimizer with a physical interpretation. We then proceed to demonstrate the existence of the steady-state distribution of stochastic gradient descent and approximate the distribution at a small learning rate.
The Past, Present, and Future of the United States Medical Licensing Examination Step 2 Clinical Skills Examination

In January 2021, the United States Medical Licensing Examination (USMLE) announced the permanent suspension of their Step 2 Clinical Skills (CS) examination. Launched in 2004, the Step 2 CS examination was intended to ensure that physicians entering graduate medical education possess the necessary information gathering, clinical reasoning, and communication skills necessary to provide patient care. Although the requirement that doctors pass a clinical skills examination as a condition of licensure likely improved some elements of medical education and physician practice, the Step 2 CS examination was deeply unpopular among many medical students since its inception. The demise of USMLE Step 2 CS provides an opportunity to re-examine the test’s value and incorporate improvements in future iterations. However, doing so requires a clear understanding of why the test was so vigorously challenged. Here, we review the history of clinical skills examinations used for medical licensure in the United States and highlight the persistent concerns regarding Step 2 CS’s cost, value, validity, and lack of examinee feedback before proposing future improvements to address each concern.
Toll-Like Receptors (TLRs): Structure, Functions, Signaling, and Role of Their Polymorphisms in Colorectal Cancer Susceptibility

Toll-like receptors (TLRs) are the important mediators of inflammatory pathways in the gut which play a major role in mediating the immune responses towards a wide variety of pathogen-derived ligands and link adaptive immunity with the innate immunity. Numerous studies in different populations across the continents have reported on the significant roles of TLR gene polymorphisms in modulating the risk of colorectal cancer (CRC). CRC is one of the major malignancies affecting the worldwide population and is currently ranking the third most common cancer in the world. In this review, we have attempted to discuss the structure, functions, and signaling of TLRs in comprehensive detail together with the role played by various TLR gene SNPs in CRC susceptibility.
Efficacy and safety of Qingre-Chushi therapies in active ulcerative colitis: A network meta-analysis

Background Ulcerative colitis (UC) is a chronic inflammatory disease with an increasing incidence in the world. Qingre-Chushi therapies (QC) can alleviate clinical symptoms. Therefore, a network meta-analysis was conducted to systematically evaluate the efficacy and safety of QC in the treatment of active UC patients. Methods 7 databases were screened and relevant randomized controlled trials were selected. The tools of Cochrane Handbook and the GRADE system were conducted to assess the quality of outcomes. Pooled risk ratio or standard mean difference was calculated with 95% credible interval for outcomes measurement using the random-effects model. The surface under the cumulative ranking curve (SUCRA) was performed to rank the treatments. The larger SUCRA scores, the more effective interventions. Results A total of 3560 articles were identified and 21 studies including 1829 participants were included for further analysis. Totally, 9 therapies regimens were compared: oral mesalazine, mesalazine enema, mesalazine suppository, oral mesalazine + mesalazine enema, oral QC, oral QC + oral mesalazine, QC enema, oral QC + QC enema, and oral mesalazine + QC enema. Based on the SUCRA plot, oral QC + oral mesalazine was the best treatment in inducing clinical response; oral QC + QC enema had the best efficacy in the improvement of Mayo scores and alleviating abdominal pain; oral mesalazine + mesalazine enema was the optimal therapy in the endoscopic improvement and reducing diarrhea; QC enema + oral mesalazine was the best option in preventing bloody stool. Conclusion This study confirmed the efficacy and safety of QC in treating active UC and suggested that the combination of oral medications with topical can achieve more benefits.
Evaluation of thrombophilia testing in the inpatient setting: A single institution retrospective review

Background Thrombophilia workup is typically inappropriate in the inpatient setting as testing may be skewed by anticoagulation, acute thrombosis, or acute illness. Objective To determine adherence of inpatient thrombophilia testing with institutional guidelines. Patients and methods A retrospective study to evaluate thrombophilia testing practices of adult patients who were admitted to Lehigh Valley Hospital at Cedar Crest with either venous thromboembolism or ischemic stroke in 2019. Testing included inherited and acquired thrombophilia. Patient charts were individually reviewed for three measured outcomes: 1) the number of appropriate thrombophilia testing in the inpatient setting; 2) the indications used for thrombophilia testing; 3) the proportion of positive thrombophilia tests with change in clinical management. Results 201 patients were included in our study. 26 patients (13%) were tested appropriately in accordance with institution guidelines and 175 (87%) patients were tested inappropriately. The most common reason for the inappropriate testing was testing during acute thrombosis. 28 of the 201 patients had positive thrombophilia tests, but the reviewers only noted 7 patients with change in clinical management—involving anticoagulation change. Conclusion Our study revealed that a majority of inpatient thrombophilia testing did not follow institutional guidelines for appropriate testing and did not change patient management. These thrombophilia tests are often overutilized and have minimal clinical utility in the inpatient setting.
An improved deep forest model for prediction of e-commerce consumers’ repurchase behavior

As the Internet retail industry continues to rise, more and more consumers choose to shop online, especially Chinese consumers. Using consumer behavior data left on the Internet to predict repurchase behavior is of great significance for companies to achieve precision marketing. This paper proposes an improved deep forest model, and the interactive behavior characteristics of users and goods are added into the original feature model to predict the repurchase behavior of e-commerce consumers. Based on the Alibaba mobile e-commerce platform data set, first construct a feature engineering that includes user characteristics, product characteristics, and interactive behavior characteristics. And then use our proposed model to make predictions. Experiments show that the model’s overall performance with increased interactive behavior features is better and has higher accuracy. Compared with the existing prediction models, the improved deep forest model has certain advantages, which not only improves the prediction accuracy but also reduces the cost of training time.
Sugammadex, the Guardian of Deep Muscle Relaxation During Conventional and Robot-Assisted Laparoscopic Surgery: A Narrative Review

Abstract High intra-abdominal pressure induced by artificial pneumoperitoneum can obviously impair respiratory and circulatory functions and has a negative effect on the prognosis of patients undergoing conventional and robot-assisted laparoscopic surgery. The application of deep neuromuscular blockade during the operation is reported to lower the intra-abdominal pressure and improve patients’ outcome. However, concern lies in the risks of postoperative residual muscular paralysis with the use of deep neuromuscular blockade. Sugammadex, a specific antagonist for aminosteroids muscle relaxants, can effectively and rapidly reverse rocuronium and vecuronium induced neuromuscular blockade of different depths. Thus, sugammadex allows the ability to safeguard the application of deep neuromuscular blockade in laparoscopic operations and helps to alleviate the adverse complications associated with pneumoperitoneum. Here, we review the application of deep neuromuscular blockade in different laparoscopic surgeries and discuss the benefits and possible risks of sugammadex administration in the reversal of deep neuromuscular blockade in these operations.
Preferences, trust, and performance in youth business groups

We study how social preferences and norms of reciprocity are related to generalized (outgroup) and particularized (ingroup) trust among members of youth business groups in northern Ethiopia. The Ethiopian government promotes youth employment among land-poor rural youth by allocating them rehabilitated communal lands for the formation of sustainable businesses. The typical sustainable production activities that the groups can invest in include apiculture, forestry, horticulture, and livestock production. Our study used incentivized experiments to elicit social preferences, trust, and trustworthiness. We use data from 2427 group members in 246 functioning business groups collected in 2019. Altruistic and egalitarian preferences were associated with stronger norms to reciprocate, higher outgroup and ingroup trustworthiness and trust while spiteful and selfish preferences had opposite effects. The social preferences had both direct and indirect effects (through the norm to reciprocate) on trustworthiness and trust. Ingroup trust was positively correlated with a number of group performance indicators.
Complete mitochondrial genome of Hypomecis punctinalis Scopoli, 1763 and its phylogenetic position within family Geometridae

Abstract Hypomecis punctinalis Scopoli, 1763 belongs to the Lepidopteran family Geometridae. We sequenced the complete mitochondrial genome (mitogenome) of H. punctinalis. The mitogenome is 15,648 bp long and contains a typical set of genes (13 protein-coding genes (PCGs), 22 tRNA genes, and two rRNA genes) and a 484 bp AT-rich region. All PCGs start with ATN codons and stop at TAA codon except for cox1 using CGA as initiation codon and nad4 and nad5 using incomplete termination codon T. Within the mitogenome, 17 intergenic spacers and seven overlaps are founded. The intergenic nucleotides are 294 bp in total and two longest intervals locate between trnGln and nad2 as well as trnCys and trnTyr . The overlap nucleotides are 47 bp in total and the maximum overlap lies between cox2 and trnLys . The AT-rich region of the mitogenome contains an ‘ATAGA + polyT’ motif, three copies of 30-bp-repeat and a short polyA tail. The phylogenetic tree shows the relationships of four subfamilies of Geometridae are (((Ennominae + Geometrinae)+Larentiinae)+Sterrhinae)) and the relationships within subfamily Ennominae are ((((Erannis+Biston)+(Jankowskia+(Hypomecis+(Apocheima+Milionia))))+Ectropis)+Abraxas)+Phthonandria)+Celenna).
The complete chloroplast genome of Beesia deltophylla (Ranunculaceae)

Abstract Beesia deltophylla is an endemic and rare species only distributed in Xizang, China. The chloroplast genome of B. deltophylla is 157,397 bp in length, with 112 encoded genes including 78 protein-coding genes, 30 tRNA genes and 4 rRNA genes. Phylogenetic reconstruction has confirmed the placement of B. deltophylla as sister to B. calthifolia. These two species formed a clade closely to a Japan endemic species Anemonopsis macrophylla.
Beneficial effects of posttransplant dipeptidyl peptidase-4 inhibitor administration after pancreas transplantation to improve β cell function

Purpose Dipeptidyl peptidase-4 (DPP-4) inhibitors lower blood glucose levels and enhance the function of pancreatic β cells. Yet, it is unknown whether posttransplant administration of DPP4 inhibitors is beneficial for pancreas transplant recipients. Methods We thus retrospectively analyzed the records of 312 patients who underwent pancreas transplantation between 2000 and 2018 at Asan Medical Center (Seoul, Korea) and compared the metabolic and survival outcomes according to DPP-4 inhibitor treatment. Results The patients were divided into the no DPP-4 inhibitor group (n = 165; no treatment with DPP-4 inhibitors or treated for <1 month) and the DPP-4 inhibitor group (n = 147; treated with DPP-4 inhibitors for ≥1 month). There were no significant differences in levels of glucose, hemoglobin A1c, and insulin between the 2 groups during 36 months of follow-up. However, the level of C-peptide was significantly higher in the DPP-4 inhibitor group at 1, 6, and 24 months posttransplant (all P < 0.05). Moreover, the DPP-4 inhibitor group had significantly higher rates of overall (log-rank test, P = 0.009) and death-censored (log-rank test, P = 0.036) graft survival during a 15-year follow-up. Conclusion Posttransplant DPP-4 inhibitor administration may help improve the clinical outcomes including β cell function after pancreas transplantation.
Mental Health, Smartphone Use Type, and Screen Time Among Adolescents in South Korea

Purpose The excessive use of smartphones for social interaction is associated with mental health. However, few studies have considered the purpose of smartphone usage and screen time together. Therefore, we investigated the impact of smartphone purpose and screen time on mental health using data from the 2017 Korea Youth Risk Behavior Web-based Survey (KYRBS). Participants and Methods A total of 54,243 adolescents answered items on purpose and screen time of smartphone use, stress perception, sleep dissatisfaction, depressive symptoms, and suicide-related indicators. The purpose of smartphone usage was categorized as social interaction and non-social interaction, and the daily smartphone screen time was classified into three categories: < 2 hours, ≥ 2 hours but < 4 hours, ≥ 4 hours per day. Results We determined that, on weekdays, stress perception, sleep satisfaction, depressive symptoms, and suicide-related indicators worsened in both groups that used smartphones for ≥4 hours per day. When using smartphone for ≥2 hours but <4 hours per day on weekdays, depending on the smartphone use purpose, mental health outcomes differed between the two groups. On weekends, using smartphones for ≥2 hours but <4 hours per day worsened sleep satisfaction but decreased suicide-related indicators in both groups. Mental health outcomes improved when participants used smartphones for ≥2 hours but <4 hours per day but worsened when smartphones were used for ≥4 hours per day on weekends. Conclusion Recommended screen time of smartphone is different depending on the purpose of smartphone use, and the risk of uncontrolled usage is emphasized, rather than the absolute screen time.
Personalizing Psychological Care for Chronic Cancer-Related Fatigue: A Case Study on Symptom Dynamics

Approximately 25% of cancer patients suffer from chronic cancer-related fatigue (CCRF), which is a complex, multifactorial condition. While there are evidence-based interventions, it remains unclear what treatment works best for the individual patient. Psychological network models can offer a schematic representation of interrelations among fatigue and protective and perpetuating factors for the individual patient. We explored whether feedback based on these individual fatigue networks can help personalize psychological care for CCRF. A 34-year old woman with CCRF was referred to our mental healthcare institute for psycho-oncology. During the waitlist period, she filled out an experience sampling app for 101 days, including five daily assessments of fatigue, pain, mood, activity and fatigue coping. The interplay between items was visualized in network graphs at the moment-level and day-level, which were discussed with the patient. For example, acceptance of fatigue in the past three hours was associated with less hopelessness and less fatigue in the following moment. At the day-level, acceptance was also being associated with less fatigue, less hopelessness, a better mood, and more motivation to do things. The patient recognized these patterns and explained how unexpected waves of fatigue can make her feel hopeless. This started a dialogue on how cultivating acceptance could potentially help her handle the fatigue. The patient would discuss this with her therapist. Feedback based on individual fatigue networks can provide direct insight into how one copes with CCRF and subsequently offer directions for treatment. Further research is needed in order to implement this in clinical practice.
Plant-based Diet and Iron Deficiency Anemia in Sundanese Adolescent Girls at Islamic Boarding Schools in Indonesia

Background Adolescent girls are at risk for iron deficiency anemia (IDA) due to the higher demand of iron for growth and the loss of blood during menstruation. Consumption of foods containing iron that have higher bioavailability can reduce the risk of IDA although diets that are largely plant-based, like those consumed by many Sundanese people, may not contain sufficient bioavailable iron. Here, we investigated the correlation between plant-based diets and IDA in adolescent Sundanese girls who were students at Islamic boarding schools in Indonesia. Methods A total of 176 girls from seven Islamic boarding schools in Tasikmalaya were recruited. Nutritional intake data were obtained using 24-hr dietary recall. Blood samples were analyzed with a Sysmex-XNL instrument to measure several parameters including hemoglobin, mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), and mean corpuscular hemoglobin concentration (MCHC). Results The prevalence of IDA in the study population was 22.2%. Iron intake was 6.59 mg/day, which was lower than the recommended amount. The molar ratio of phytic acid to iron and vitamin C to iron was 8.72 and 0.03, respectively. There was a correlation between heme iron and both hemoglobin (p=0.009) and hematocrit (p=0.018). Iron from meat, fish, and poultry was correlated with hemoglobin (p=0.009) and hematocrit (p=0.011). Conclusion The Sundanese plant-based diet did not affect the IDA status. Instead, IDA was associated with consumption of less animal-based foods that have iron with higher bioavailability. Increased access to an animal-based menu at the school cafeteria could be an approach to prevent IDA in students at Islamic boarding schools in Indonesia.
Comparison of Back-Propagation Neural Network, LACE Index and HOSPITAL Score in Predicting All-Cause Risk of 30-Day Readmission

Background The main purpose of this study is to predict the all-cause risk of 30-day readmission by employing the back-propagation neural network (BPNN) in comparison with traditional risk assessment tools of LACE index and HOSPITAL scores. Methods This was a retrospective cohort study from January 1st, 2018 to December 31st, 2019. A total of 55,688 hospitalizations from a medical center in Taiwan were examined. The LACE index (length of stay, acute admission, Charlson comorbidity index score, emergency department visits in previous 6 months) and HOSPITAL score (hemoglobin level at discharge, discharge from an Oncology service, sodium level at discharge, procedure during hospital stay, Index admission type, number of hospital admissions during the previous year, length of stay) are calculated. We employed variables from LACE index and HOSPITAL score as the input vector of BPNN for comparison purposes. Results The BPNN constructed in the current study has a considerably better ability with a C statistics achieved 0.74 (95% CI 0.73 to 0.75), which is statistically significant larger than that of the other two models using DeLong’s test. Also, it was possible to achieve higher sensitivity (70.32%) without penalizing the specificity (71.76%) and accuracy (71.68%) at its optimal threshold, which is at the 20% of patients with the highest predicted risk. Moreover, it is much more informative than the other two methods because of a considerably higher LR+ and a lower LR-. Conclusion Our findings suggest that more attention should be paid to methods based on non-linear classification systems, as they lead to substantial differences in risk-scores.
InNetGAN: Inception Network-Based Generative Adversarial Network for Denoising Low-Dose Computed Tomography

Low-dose Computed Tomography (LDCT) has gained a great deal of attention in clinical procedures due to its ability to reduce the patient's risk of exposure to the X-ray radiation. However, reducing the X-ray dose increases the quantum noise and artifacts in the acquired LDCT images. As a result, it produces visually low-quality LDCT images that adversely affect the disease diagnosing and treatment planning in clinical procedures. Deep Learning (DL) has recently become the cutting-edge technology of LDCT denoising due to its high performance and data-driven execution compared to conventional denoising approaches. Although the DL-based models perform fairly well in LDCT noise reduction, some noise components are still retained in denoised LDCT images. One reason for this noise retention is the direct transmission of feature maps through the skip connections of contraction and extraction path-based DL modes. Therefore, in this study, we propose a Generative Adversarial Network with Inception network modules (InNetGAN) as a solution for filtering the noise transmission through skip connections and preserving the texture and fine structure of LDCT images. The proposed Generator is modeled based on the U-net architecture. The skip connections in the U-net architecture are modified with three different inception network modules to filter out the noise in the feature maps passing over them. The quantitative and qualitative experimental results have shown the performance of the InNetGAN model in reducing noise and preserving the subtle structures and texture details in LDCT images compared to the other state-of-the-art denoising algorithms.