Miracle-dz/UniFAR-FTUs huggingface dataset:
Usefulness of the estimation of physiologic ability and surgical stress (E-PASS) system for prediction of complication and prognosis in hepatocellular carcinoma patients after hepatectomy

Background Estimation of physiologic ability and surgical stress (E-PASS) system was verified in predicting postoperative complications or mortality in many surgical operations. This research aimed to investigate whether the E-PASS system could predict postoperative complications and was related with long-term prognosis in primary hepatocellular carcinoma (HCC) patients. Methods A total of 236 HCC patients who underwent liver resection were collected in this study. We performed univariate analyses to determine the potential risk factors for complications after hepatectomy. The potential independent risk factors were then included in the logistic regression for multivariable analysis. The optimal cutoff value of Comprehensive Risk Score (CRS) was identified by a receiver operating characteristic (ROC) curve. Based on this value, the patients were divided into two groups to investigate the relation between CRS with postoperative complications. The relation between CRS and overall survival (OS) or recurrence-free survival (RFS) was analyzed further in these two groups. Results Postoperative complications occurred in 79 patients. Multivariable analysis suggested that CRS was independent factor for predicting postoperative complications (P<0.001). The optimal CRS cutoff value in our study was 0.126. Patients with high Preoperative Risk Score (PRS) had a higher rate of postoperative complications occurrence, both major and mild complications (P<0.001). Our study showed that HCC patients with higher CRS had poorer survival prognosis [hazard ratio (HR): 3.735, 95% confidence interval (CI): 1.200–11.631, P=0.023]. The 3-year OS rate of high CRS group (CRS ≥0.126) and low CRS group (CRS <0.126) were 66.2% vs. 84.8% (P<0.001), respectively. Conclusions For HCC patients after liver resection, E-PASS was an effective predictive system for evaluating the risks of postoperative complications and may can predict prognosis in long term.
A New Magnetic Coupler With High Rotational Misalignment Tolerance for Unmanned Aerial Vehicles Wireless Charging

In this letter, a novel magnetic coupler with high rotational misalignment tolerance is proposed for unmanned aerial vehicles (UAVs) wireless charging. The transmitting coil consists of an inner coil and an outer circular coil connected in series, which generates a horizontal magnetic field from the center to all periphery directions within the charging range. Then, to receive the flux effectively and to adapt to UAV's structure, a vertical square air-core coil is designed and attached to the landing gear. The proposed magnetic coupler can reduce significantly the magnetic fluxes penetrating through the body of the UAV, therefore mitigating electromagnetic interference with onboard devices. Simulation based on ANSYS Maxwell and experiments based on a laboratory prototype are carried out to validate the proposal. The results show that, the proposed magnetic coupler can transmit power in all 360° of rotational misalignments, and the output voltage of the wireless charging system fluctuates only 2% around the 48 V reference.
Scoring Functions for Protein-Ligand Binding Affinity Prediction Using Structure-based Deep Learning: A Review

The rapid and accurate in silico prediction of protein-ligand binding free energies or binding affinities has the potential to transform drug discovery. In recent years, there has been a rapid growth of interest in deep learning methods for the prediction of protein-ligand binding affinities based on the structural information of protein-ligand complexes. These structure-based scoring functions often obtain better results than classical scoring functions when applied within their applicability domain. Here we review structure-based scoring functions for binding affinity prediction based on deep learning, focussing on different types of architectures, featurization strategies, data sets, methods for training and evaluation, and the role of explainable artificial intelligence in building useful models for real drug-discovery applications.
The Antarctic Moss Pohlia nutans Genome Provides Insights Into the Evolution of Bryophytes and the Adaptation to Extreme Terrestrial Habitats

The Antarctic continent has extreme natural environment and fragile ecosystem. Mosses are one of the dominant floras in the Antarctic continent. However, their genomic features and adaptation processes to extreme environments remain poorly understood. Here, we assembled the high-quality genome sequence of the Antarctic moss (Pohlia nutans) with 698.20 Mb and 22 chromosomes. We found that the high proportion of repeat sequences and a recent whole-genome duplication (WGD) contribute to the large size genome of P. nutans when compared to other bryophytes. The genome of P. nutans harbors the signatures of massive segmental gene duplications and large expansions of gene families, likely facilitating neofunctionalization. Genomic characteristics that may support the Antarctic lifestyle of this moss comprise expanded gene families involved in phenylpropanoid biosynthesis, unsaturated fatty acid biosynthesis, and plant hormone signal transduction. Additional contributions include the significant expansion and upregulation of several genes encoding DNA photolyase, antioxidant enzymes, flavonoid biosynthesis enzymes, possibly reflecting diverse adaptive strategies. Notably, integrated multi-omic analyses elucidate flavonoid biosynthesis may function as the reactive oxygen species detoxification under UV-B radiation. Our studies provide insight into the unique features of the Antarctic moss genome and their molecular responses to extreme terrestrial environments.
Exploration and Visualization of Learning Behavior Patterns from the Perspective of Educational Process Mining

The data in modern educational information systems are not given enough attention and are not fully utilized. Therefore, the motivations of our study are to preliminarily explore learning behavior patterns by applying process mining to educational datasets, and construct prediction models based on previous learning behavior. The data in modern educational information systems can be used by teaching managers to analyze various aspects of the educational process from different perspectives. We prepare to choose three datasets randomly which include student number, courses and grades attributes from a university’s educational information systems. This paper firstly applies system clustering to give an overview of students’ academic performance, and roughly determines clustering number. In order to ensure the accuracy which is relevant to the analysis of students’ learning behavior patterns, a semi-biased statistic is proposed to quantitatively determine clustering number. Then, the data are clustered by fast clustering algorithm, and the clustering effect is cross-validated which is aimed at accurately analyzing the behavior patterns of student groups and using data visualization technology to visualize different student groups. Finally, the support vector machine is used to construct a classifier for predicting the learning behavior pattern, and the parameters in the support vector machine are optimized by Bayesian optimization, genetic algorithm optimization and whale optimization respectively. The research found that: 1) In the equal test of the group mean, when the significance of most courses is less than 0.05, it means that there is a significant difference among different categories. In this case, using the semi-biased statistic proposed in the paper is helpful to improve clustering effect. 2) The better the students learn, the better the clustering effect of the category which they belong to is. 3) Whale optimization algorithm works best.
Sex and Body Colour Affect the Variation in Internal Body Temperature of Oedaleus decorus asiaticus in Natural Habitats in Inner Mongolia, China

Oedaleus decorus asiaticus is one of the most harmful locusts in agricultural and pastoral areas in China. Plagues of this grasshopper can aggravate grassland degradation and cause huge damage to the livestock industry. Fungal biopesticides are seen as a suitable means of controlling grasshoppers and locusts. However, the efficiency of fungal biopesticides is dependent on temperature. Currently, there is limited knowledge on the thermal biology of this grasshopper in natural habitats. In this study, ground temperature measurements were made in conjunction with measurements of internal body temperatures using thermocouples and hand-held thermometers. The grasshoppers were randomly caught during the daytime in 2017 and 2018 in eight different locations in Inner Mongolia Autonomous Region, China. Our results indicated that the average internal body temperature of nymphs as well as adults of O. d. asiaticusis was higher than the ground temperature and that it increases/decreases with increases/decreases in ground temperature, respectively, during the daytime. Moreover, the adult internal body temperature is significantly higher than that of the nymphs at different times of the day, specifically around 6:00, 10:00, 13:00, and 18:00. Female internal body temperatures were significantly higher than those of the males by an average of 0.90 °C. Additionally, the average internal body temperature of the brown morphs was higher than that of the green morphs by approximately 1.17 °C. These findings demonstrate that brown morph insects might be more tolerant of fungal biopesticides and hence the biopesticides may take longer to kill them. Hence, ecophysiological adaptations to climate change may affect how fungal biopesticides could be used in the future.
Synergistic Anti-Inflammatory Activity of Ginger and Turmeric Extracts in Inhibiting Lipopolysaccharide and Interferon-γ-Induced Proinflammatory Mediators

This study aims to investigate the combined anti-inflammatory activity of ginger and turmeric extracts. By comparing the activities of individual and combined extracts in lipopolysaccharide and interferon-γ-induced murine RAW 264.7 cells, we demonstrated that ginger-turmeric combination was optimal at a specific ratio (5:2, w/w) in inhibiting nitric oxide, tumour necrosis factor and interleukin 6 with synergistic interaction (combination index < 1). The synergistic inhibitory effect on TNF was confirmed in human monocyte THP-1 cells. Ginger-turmeric combination (5:2, w/w) also upregulated nuclear factor erythroid 2–related factor 2 activity and heme oxygenase-1 protein expression. Additionally, 6-shogaol, 8-shogaol, 10-shogaol and curcumin were the leading compounds in reducing major proinflammatory mediators and cytokines, and a simplified compound combination of 6-s, 10-s and curcumin showed the greatest potency in reducing LPS-induced NO production. Our study provides scientific evidence in support of the combined use of ginger and turmeric to alleviate inflammatory processes.
Strategies for Instilling Muhammadiyah Values within the Faculty of Islamic Religion, University of Muhammadiyah Palu

In instilling the values ​​of kemuhammadiyahan to others, it is certainly not an easy process, in creating a society that recognizes and also practices the values ​​of kemuhammadiyahn requires a good way or strategy so that what is given to the community can be understood or understood properly. This article discusses strategies for instilling muhammadiyahan values ​​within the Faculty of Islamic Religion, University of Muhammadiyah Palu. which, as the results of our research, found several strategies, such as the inclusion of AIK courses in learning, also holding monthly recitations that discussed kemuhammadiyahan, as well as incorporating kemuhammadiyahan materials into the cadre of organizations of the Faculty of Islamic Religion. And briefly, we convey that the strategy being pursued is very effective and also successful. This can be seen from the quality and insight of the Muhammadiyah in each element within the Faculty of Islamic Religion, as well as the birth of many new Muhammadiyah cadres from the cadre process carried out by organizations within the Faculty of Islamic Religion. In this study, the author uses a naturalistic paradigm, with a qualitative type of research, and with a case study approach.
HIPEC after Interval Debulking Surgery as Best Clinical Practice in Ovarian Cancer Patients: Case Series and Literature Review

Background: Hyperthermic intraperitoneal chemotherapy (HIPEC) combined with interval debulking surgery (IDS) constitutes an adjunctive treatment strategy in advanced ovarian cancer (AOC). This approach is based on the concept of perfusing chemotherapy targeting directly the site of residual tumor after optimal surgical debulking. It improves patients’ outcome in terms of overall survival (OS) and disease free survival (DFS). The correct selection of patients eligible for IDS + HIPEC is crucial: in particular, they must have shown a good response to neoadjuvant chemotherapy (NACT) and have a good performance status (PS). The application of HIPEC at the end of debulking does not seem to increase neither the rate of intra/postoperative complications nor the time of hospitalization. Clinical Cases: After approving an internal protocol for the application of HIPEC in our hospital, we have submitted four patients to IDS + HIPEC in the past 12 months. One of these patients underwent a minimally invasive procedure. No intraor postoperative complications were observed. Results: All patients underwent IDS + HIPEC after being assessed as eligible and after showing a good response to NACT. In the course of IDS in all cases complete debulking was achieved. No patient developed intraor postoperative complications. Conclusions: The addition of HIPEC to interval debulking surgery should be offered to all eligible patients, considering that the association of HIPEC to IDS seems to improve patients’ outcomes in terms of OS and DFS, without increasing post-operative morbidity .
Self-Adaptive Multilingual ASR Rescoring with Language Identification and Unified Language Model

Language Models (LM) can be used in automatic speech recognition (ASR) rescoring to select the hypothesis with the fewest errors. While in multilingual ASR, multiple LMs might be used based on language identification (LID) given by the multilingual ASR outputs. However, in the traditional shallow fusion method, a static LM weight is determined by a development set. This static weight might not fulfill the situations of all languages in test data. And for multiple LMs, different weight needs to be searched for each LM. Instead, A unified multilingual LM will receive a LID token at the beginning of its auto-regressive predicting to decide which language to decode, so that merely one weight is necessary for LM rescoring. Then, we propose a multilingual ASR rescoring method which dynamically tunes the LM weight during decoding to optimize the balance between the end-to-end (E2E) multilingual ASR model and the LM according to the LM’s entropy and logits score as model confidence metrics. With this method, resources for search the best hyperparameter LM weight can also be saved. The experiments are mainly conducted on Common voice and Voxforge corpora. The results show that this method can reach the performance of the best static LM weight and even defeat it in several languages with no hyperparameter to be tuned and nearly zero overhead.
Big Data Clustering Mining Based on Swarm Intelligence Algorithm in Cloud Environment

As science and technology progress and develop rapidly in this day and age, various industry applications have changed the data in a new way, and the explosive growth of data has made traditional data mining unable to perform the current data mining work. The aim of this paper is to study the aggregation digging of big data based around flocking automation algorithms under circumstances of cloud. There is a fuzzy-mean aggregation arrangement with mixed frog leaping in this paper. Through simulation analysis of different clustering algorithms, hybrid frog-hopping and as well as the merging arrangement introduced in this paper, it is concluded that the merging algorithm achieves an improvement of up to 90% accuracy on the iritual membrane dataset. It was demonstrated that the arrangement provides effective agglomerations. When the number of iterations is 500, the fitness value of the algorithm on Dataset 1 is 1.59 × 104, and its convergence speed is faster than the other algorithms.
Students’ Use of Internet Technologies for Interactions in Students’ Use of Internet Technologies for Interactions in Learning Practices: A Study from Saudi Arabia’s Higher Education Learning Practices: A Study from Saudi Arabia’s Higher Education

Internet technologies provide support for students’ learning practices. Some Internet technologies are supported on an organisational level such as learning management systems (LMS) while others are adopted voluntarily by academics and students such as social networking sites (SNSs). Given the unique culture of Saudi Arabia where communication and interaction norms are strictly defined by strong traditions, little is known about the use patterns of these diverse technologies to support student interactions with peers and academics within tertiary learning practices. This qualitative study was conducted in two Saudi universities where seventeen students and twelve academics from both genders were interviewed. The study showed how students tend to communicate with academics in a formal way, create their own online community and interact with external tutors through online paid websites. These interaction patterns are discussed considering the national culture, learning styles and organisational regulations.
Faith-based Communities Affecting Breeding Sites of Mosquito Larvae at Samui Island, Thailand Mosquito using Drone imagery and GLOBE Observer: Habitat Mapping App Students: Switt Kitkumchonskul, Thanawin Khomwongthep, Warissara Kiattiyoscharoen,

This study investigated (1) how faith-based communities (Buddhist and muslim communities) affect the key breeding sites of mosquito larvae at Samui Island, southern Thailand and (2) comparing the number of containers from drone imageries with conventional ground survey. We examined how the number of Aedes aegypti, Ae. albopictus, Culex and Anopheles larvae differed in various types of water containers. Water containers were categorised into the following groups: indoor/outdoor containers, artificial/natural containers, earthen/plastic containers, and containers with/without lids. Samples were collected from a total of 100 households from 50 buddhist and 50 muslim houses using GLOBE Observer: Mosquito Habitat Mapper App. Our results showed that Aedes larvae were found in 57 out of 197 water containers in buddhist and muslim houses. Aedes females laid eggs in different container types depending on faith based communities. Aedes larvae were found in highest numbers in plastic buckets in both communities. The number of positive containers was higher in outdoor containers than indoor containers, artificial containers than natural containers, plastic containers than earthen containers, container without lid than container with lid, and muslim community than Buddhist community. Our results showed that conventional ground survey using MHM App gave higher numbers of containers in both communities (Drone:Ground survey at Plailaem Buddhist community = 22:77; at Hua Thanon Muslim community = 37:80).
Journal of Chemical and process enggineering (

Kitolod (Hippobroma longiflora) plants are plants that are rarely studied, but this plant has many useful contents. One useful kitolod content is flavonoids. Flavonoids is secondary metabolite found in all green plants so it could be found in every plant extract. This compound can dissolve in polar solvents, but is easily degraded at high temperatures. In this case, it is necessary to test the characteristics of flavonoids based on the level of the solvent and the extraction temperature. In addition, coating of flavonoid compounds was carried out with the encapsulation method to keep the compounds from being contaminated or damaged.The extraction was carried out using ethanol solvents with levels of 50%, 60%, 70%, 80% and 90% and the extraction temperatures were30°C, 40°C, 50°C, 60°C and 70C. The coating used in the encapsulation process is sugar (sucrose). The results were, the best extraction and encapsulation is at temperature of 70°C with 90% ethanol solvent and the amount of flavonoids obtained from encapsulation results is 39.5277 mg / 10 gram .
COPD_A_366911 1403..1408

1LungenClinic Grosshansdorf, Airway Research Center North (ARCN), German Center for Lung Research (DZL), Grosshansdorf, Germany; 2Pulmonary Research Institute at LungenClinic Grosshansdorf, Airway Research Center North (ARCN), German Center for Lung Research (DZL), Grosshansdorf, Germany; 3Pneumology and Critical Care Medicine, Thoraxklinik at University Hospital Heidelberg, Translational Lung Research Center Heidelberg (TLRC), Member of German Center for Lung Research (DZL), Heidelberg, Germany; 4Department of Biomedical Informatics (DBMI) at the Center for Preventive Medicine and Digital Health Baden-Württemberg (CPD-BW), University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
Platelet Count and Mean Platelet Value of Rabbit Implanted Bali Cattle Bone Graft (JUMLAH PLATELET DAN MEAN PLATELET VALUE KELINCI PASCA IMPLANTASI BAHAN CANGKOK TULANG ASAL SAPI BALI)

Platelets have an important role in fracture healing. However, its role is still under appreciated. Therefore, this study investigated the values of mean platelet volume and platelet count as the parameters in fracture healing. This study used 10 male local rabbits which were divided into 2 groups randomly, KI (control group) and KII (treatment group). Each femur of both groups was drilled a hole with a diameter of 5 mm, where KI without any substitutes and KII was implanted by demineralized bali cattle bone graft. Each animal was evaluated by collecting its blood from the central auricular vein into an EDTA tube at 24 hours, week 2, 4, and 6 postoperative determining the values of MPV and PC. Results show that treatment shows no differences to MPV and PC, yet time observation does. Overall, MPV and PC were increased in number during observation and are correlated positively.
ARBITRAGE OPPORTUNITIES ON DERIVATIVES: A LINEAR PROGRAMMING APPROACH

I propose a simple tool to determine the existence of arbitrage opportunities on derivatives with the same underlying asset and maturity, when only minimal assumptions on the stochastic behavior of the underlying are made. The case of transaction costs is also considered. The use of linear programming theory makes the approach very easily implementable. Necessary and sucient conditions for no arbitrage, as well as an application on options written on the S&P500 index are given.
Coding for Optical Channels With Photon-Counting

The problem of coding for Pierce's recent model for optical communications is studied. It was concluded that for any positive rate rho (measured in nats per photon), the best code of length n has an error probability bounded by an exponentially decaying function of n. Explicit practical schemes are shown for rho less than or = to 1; and evidence is given that rho approximating 1 may be the practical limit for optical communication.