Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of Molecular Subtypes in Head and Neck Squamous Cell Carcinoma Based on Dysregulated Immune LncRNAs

Long noncoding RNAs (lncRNAs) perform indispensable functions in cancer pathologies and are involved in the onset and progression of multiple cancers. Multiple platforms were performed to comprehensively analyze the head and neck squamous cell carcinoma (HNSCC) for determining molecular subtypes. Molecular subtypes were clustered and analyzed by the “ConsensusClusterPlus” R package. The Limma software was utilized to screen for differentially expressed genes (DEGs). Functional enrichment analyses, including Gene Set Enrichment Analysis (GSEA), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Ontology (GO), were performed on the three database resources. Seventeen lncRNAs were determined as HNSCC-specific immune lncRNAs that were dysregulated. Our research identified and redefined two distinct molecular subtypes, C1 (230 samples) and C2 (269 samples). Moreover, the C1 subtype had a higher survival rate than the C2 subtype in HNSCC samples, as well as a prolonged median survival duration with activated immune response. 1531 DEGs, including 529 upmodulated genes and 1002 downmodulated genes, were identified in the above two subtypes. Functional enrichment analysis revealed that upmodulated genes in C2 were associated with tumorigenesis and development, while downregulated genes in C2 were associated with immune response. By comparing with the existing immunophenotyping group, it found that C1 had more overlaps with the existing Atypical and Basal, and C2 and Classical and Mesenchymal had a high degree of coincidence. On the basis of lncRNA, there were significant differences in the aspect of prognostic and immunological characteristics in the two identified molecular subtypes of HNSCC.
Pervasive Systems Development: A Stepwise Rule-centric Rigorous Service-Oriented Architectural Approach

To stay competitive in today’s high market volatility and globalization, cross-organizational business information systems and processes are deemed to be knowledge-intensive (e.g. rulecentric), highly adaptive and context-aware, that is explicitly responding to their surrounding environment, user’s preferences and sensing devices. Towards achieving these objectives in developing such applications, we put forwards in this paper a stepwise service-oriented approach that exhibits an explicit separation of concerns, that is, we first conceptualize the mandatory functionalities and then separately and explicitly consider the added-values of contextual concerns, which we then integrate at both the fine-grained activity-level and the coarse-grained process-level to reflect their intuitive business semantics. Secondly, the proposed approach is based on business rule-centric architectural techniques, with emphasis on Event-Conditions-Actions (ECA)-driven transient tailored and adaptive architectural connectors. As third benefit, for formal underpinnings towards rapid-prototyping and validation, we semantically interpret the approach into rewriting logic and its true-concurrent and reflective operational semantics governed by the intrinsic practical Maude language.
ÇOK KRİTERLİ KARAR VERME TEKNİKLERİ İLE ELEKTRONİK BELGE YÖNETİM SİSTEMİ SEÇİMİ ELECTRONIC DOCUMENT MANAGEMENT SYSTEM SELECTION WITH MULTI-CRITERIA DECISION MAKING TECHNIQUES

Universiteler gibi kamu kurumlarinda yazisma surecleri genellikle zaman alici, is yukunu ve burokrasiyi arttirici faaliyetlerdir. Bu nedenle kurumlar, is sureclerinde urettikleri belgeleri sistematik bir sekilde yonetmelerine destek saglayan bilgi sistemlerine ihtiyac duyarlar. Elektronik Belge Yonetim Sistemi (e-BYS), calisma ortamindan bagimsiz olarak belgelerin istenen zaman ve standartta hizli ve hatasiz sekilde uretilmesini, kaydedilmesini, dagitilmasini, arsivlenmesini ve istenen kriterlere gore arama yapilarak belgeye erisilmesini saglayan bilgi sistemidir. Bu ozelliklerinden dolayi, ilgili mevzuat, yonetmelik ve standartlar geregince kamu kurumlarinda son yillarda e-BYS uygulamalarina gecis yapilmasi bir zorunluluk haline gelmistir. Dolayisiyla, universitelerde de alternatifler arasindan guvenli, hizli, kullanici dostu, esnek, etkin ve surdurulebilir e-BYS yazilimlarinin secilmesi ve kullanilmasi onem kazanmaya baslamistir. Ancak ilgili literatur incelendiginde, uygun yazilim secim surecinin yeterli duzeyde ele alinmadigi gorulmektedir. Bu calisma kapsaminda, universitelerin beklenti ve ihtiyaclarina yonelik en uygun yazilim secimi icin kriterler belirlenmis ve bu kriterler Analitik Hiyerarsi Prosesi (AHP) ve Bulanik AHP yontemleri ile agirliklandirilmistir. Alternatif yazilimlar iki farkli yontem ile agirliklandirilan kriterlere gore cok kriterli karar verme tekniklerinden AHP, Bulanik AHP ve TOPSIS yontemleri kullanilarak siralanmistir. Cok kriterli karar verme teknikleri ile sonuclar karsilastirilmis ve yoneticilere karar vermelerinde yol gosterici olmak amaclanmistir.
Intensification of Knowledge Management System within the Framework of Adult Learning for Effective Regional Development

The article analyzes the possibilities of use of innovative methods of instruction for adult learning in the regions with the purpose to intensify the knowledge management system and ensure the principle of equal opportunity for the inhabitants of the regions. The data were acquired in the course of implementation of the national programme Support for Vocational Education with the Aim to Develop Professional Skills and Competences of People Involved in Agriculture and Forestry within the project Vocational Education 2005–2006. The project was being implemented in the time period from 2006 to 2008 inclusive. In the course of project implementation, trainings in 21 regions of the Republic of Latvia had been carried out. All in all, 2,562 people in 119 groups had been trained.
Active-Type Continuously Variable Transmission system based on a Twisted String Actuator

This paper presents an active-type twisted string actuator (TSA)-based continuously variable transmission (CVT). The proposed mechanism improves the advantage of the intrinsic CVT nature of TSA by compensating its non- linear transmission ratio (TR) with the active and continuous conversion of the TR during contraction at a constant load as well as variable load. To change the TR, the proposed CVT adjusts the ratio of rotation between individual twists and overlap twists, which are two different types of string- twisting patterns. The performance of the TSA-based active CVT was experimentally assessed with the fabricated prototype and compared with a mathematical model. This adjustment in the rotation ratio between individual and overlap twists is realized using a planetary gear. By adjusting the rotating speed ratio between the sun and ring gear, the ratio of rotation between individual and overlap twists can be adjusted. Unlike the conventional TSA-based CVT, the proposed CVT can actively and continuously change the TR independent of the external load, even during operation. Consequently, it allows an increase in the operating range of the TSA while maintaining a high contraction speed.
Application of Fishery-independent Data as an Alternative Source for Determining Relative Abundance Indices of Blue Marlin, Makaira nigricans (Actinopterygii: Perciformes: Istiophoridae) in the North-eastern Indian Ocean

The present study aimed to determine the abundance index of blue marlin, Makaira nigricans (Lacepède, 1802) utilizing fishery-independent data, i.e., scientific observer, and attempted to bridge the research's gap for low coverage information in the north eastern Indian Ocean. A total of 2,984 set-by-set observer data from 2006-2018, spatially disaggregated by one-degree blocks, were obtained from the Indonesian scientific observer program following commercial longline fleets. A delta-lognormal model was chosen to fit the dataset, using catch as the response variable with seven covariates. A backward procedure based on AIC, BIC and R2 were used to select the best model. Overall, the delta-Gamma performs better when modelling data with a high proportion of zeros than other traditional models. The blue marlin CPUE trend is relatively stable over time, despite the inter-annual fluctuations, which are likely a result of natural variation in the population as opposed to operational changes or inter-annual environmental variation. Given the low spatial coverage compared to logbook data, scientific observer data performed well and produced a robust abundance index of blue marlin in the northeastern Indian Ocean.
Dissecting mutational allosteric effects in alkaline phosphatases associated with different Hypophosphatasia phenotypes: An integrative computational investigation

Hypophosphatasia (HPP) is a rare inherited disorder characterized by defective bone mineralization, is highly variable in its clinical phenotype. The disease occurs due to various loss-of-function mutations in ALPL, the gene encoding tissue-nonspecific alkaline phosphatase (TNSALP). In this work, a data-driven and biophysics-based approach for large-scale analysis of ALPL mutations – from nonpathogenic to severe HPPs is proposed. Allosteric molecular signatures of ALPL mutations were determined using an integrated pipeline of synergistic approaches including sequence and energetic-based analysis, structural topology network modeling and elastic network models. Statistical analysis of molecular features computed for the ALPL mutations showed a significant difference between the control and mild and severe HPP phenotypes, and the developed machine learning model suggested that the topological network parameters could serve as is a robust indicator for severe mutations. Molecular dynamics simulations coupled with protein structure network was employed to analyze the effect of single-residue variation on conformational dynamics of TNSALP dimers, and we found that severe disease-associated mutations have a significantly greater effect on allosteric communications. The results of this study suggested that ALPL mutations associated with mild and severe HPPs tend to have different effects on protein stability on local scale and long-range communications caused by network rewiring. By linking disease phenotypes with allosteric molecular signatures, the proposed integrative computational approach elucidates the complex sequence-structure-allostery relationships of ALPL mutations and dissects the role of allosteric effects in the pathogenesis of HPPs. Author Summary The understanding of mutational genotype- disease phenotype relationship is a fundamental step for enabling precision medicine. It remains a challenging task to assess the molecular principle of the genotype- phenotype relationship. By focusing on Hypophosphatasia, a rare inherited disorder, as an example, we performed comprehensive analysis of single-amino-acid mutations in the encoded protein of Tissue Nonspecific Alkaline Phosphatase associated in terms of their sequence, structure, and dynamics properties. We further developed a machine learning -based method to classify different disease phenotypes, and the interpretability of the classification model was addressed by the structural-functional analysis of network topological important mutations. Our results highlighted the allosteric propensity of severe mutations, and show the potential allosteric principle of genotype- phenotype relationship.
Characterization of blood mimicking fluid with ultrafast ultrasonic and optical image velocimeters

A blood mimicking fluid (BMF) is imperative for the evaluation of Doppler ultrasound. Doppler ultrasound still causes errors due to some artifacts such as aliasing and presence of grating lobes. One of the other velocimeters is the optical particle image velocimeter (PIV). This study initially developed an in vitro measurement system for analyzing flowing BMF with ultrasonic and optical PIVs. The acoustic properties such as speed of sound, attenuation, and backscatter coefficient of BMF equivalent to the human blood, used for both ultrasonic and optical PIVs were analyzed in a frequency range of 4–12 MHz. The velocity profiles were estimated by ultrasonic and optical PIVs using a block matching method. A difference between velocities obtained by ultrasonic and optical data was within 4.0% using BMF with 20 μm polyamide particle at 0.2% concentration that realized the acoustic properties and speckle patterns similar to those in ultrafast ultrasound blood flow imaging.
Shelterin is a dimeric complex with extensive structural heterogeneity

Human shelterin is a six-subunit complex – comprised of TRF1, TRF2, Rap1, TIN2, TPP1, and POT1 – that binds telomeres, protects them from the DNA-damage response, and regulates the maintenance of telomeric DNA. Although high-resolution structures have been generated of the individual structured domains within shelterin, the architecture and stoichiometry of the full complex are currently unknown. Here we report the purification of shelterin subcomplexes and reconstitution of the entire complex using full-length, recombinantly produced components. By combining negative-stain electron microscopy (EM), crosslinking mass spectrometry (XLMS), mass photometry, and native mass spectrometry (MS), we obtain stoichiometries as well as domain-scale architectures of shelterin subcomplexes and determine that they are extensively conformationally heterogenous. For POT1/TPP1 and POT1/TPP1/TIN2, we observe high variability in the positioning of the POT1 DNA-binding domain, the TPP1 OB fold, and the TIN2 TRFH domain with respect to the C-terminal domains of POT1. Truncation of unstructured linker regions in TIN2, TPP1, and POT1 did not reduce the conformational variability of the heterotrimer. Both shelterin and the TRF1/TIN2/TPP1/POT1 subcomplex primarily adopt fully dimeric complexes, even in the absence of DNA substrates. TRF1/TIN2/TPP1/POT1 and shelterin complex showed extensive conformational variability, regardless of the presence of DNA substrates. We conclude that shelterin adopts a multitude of conformations and argue that its unusual architectural variability is beneficial for its many functions at telomeres.
Dynamic Beam Pattern and Bandwidth Allocation Based on Multi-Agent Deep Reinforcement Learning for Beam Hopping Satellite Systems

Due to the non-uniform geographic distribution and time-varying characteristics of the ground traffic request, how to make full use of the limited beam resources to serve users flexibly and efficiently is a brand-new challenge for beam hopping satellite systems. The conventional greedy-based beam hopping methods do not consider the long-term reward, which is difficult to deal with the time-varying traffic demand. Meanwhile, the heuristic algorithms such as genetic algorithm have a slow convergence time, which can not achieve real-time scheduling. Furthermore, existing methods based on deep reinforcement learning (DRL) only make decisions on beam patterns, lack of the freedom of bandwidth. This paper proposes a dynamic beam pattern and bandwidth allocation scheme based on DRL, which flexibly uses three degrees of freedom of time, space and frequency. Considering that the joint allocation of bandwidth and beam pattern will lead to an explosion of action space, a cooperative multi-agents deep reinforcement learning (MADRL) framework is presented in this paper, where each agent is only responsible for the illumination allocation or bandwidth allocation of one beam. The agents can learn to collaborate by sharing the same reward to achieve the common goal, which refers to maximize the throughput and minimize the delay fairness between cells. Simulation results demonstrate that the offline trained MADRL model can achieve real-time beam pattern and bandwidth allocation to match the non-uniform and time-varying traffic request. Furthermore, when the traffic demand increases, our model has a good generalization ability.
CURRENT DEVELOPMENTS AND TECHNICAL ISSUES OF UNDERWATER TRAFFIC TUNNEL—DISCUSSION ON CONSTRUCTION SCHEME OF TAIWAN STRAIT UNDERSEA RAILWAY TUNNEL

Compared with other means of transportations,underwater tunnel has its own advantagess,o it has been developed quickly at home and abroad in recent years.However,unlike mountain tunnel,underwater tunnel has its own characteristics and technical challenges.After in-depth analysis of the huge advantage of underwater tunnel compared with bridget,he current development stage of underwater tunnel at home and broad is introduced.The construction types of underwater tunnels including drill and blast method,shield method,immerged tube method and submerged floating tunnel are particularly illuminated.The scopes include their characteristics,technical difficulties,application conditions and some related problems;and their advantages and disadvantages are also discussed.The difficulties and key technologies in design and construction of underwater tunnel are summarized.Based on above-mentioned construction outlines,the construction scheme of Taiwan Strait subsea railway tunnel is thoroughly discussedi,ncluding the rationality of underwater railway tunnel,cross-section design and construction key points.Finally,some new concepts of underground projects construction such as underwater tunnel are put forward;and their key major technologies are summarized.These above-mentioned key technical points and suggestions will provide valuable references to the construction of underwater tunnel,especially for the construction of large subsea tunnel in China.
Role of lidocaine and its effect on postoperative outcomes in abdominal cholecystectomy.

OBJECTIVE To investigate the role of pre- and intra-operative lidocaine infusion on post-operative pain management. METHODS The interventional, prospective study was conducted from September 2019 to June 2020 at the Pakistan Ordnance Factories Hospital, Wah Cantt, Pakistan, and comprised patients aged 18-60 years undergoing elective cholecystectomy who were randomised into intervention group A and control group B. Group A was given a bolus dose of lidocaine hydrochloride 2 mg/kg in addition to the standard anaesthesia protocol, while group B was given continuous intravenous infusion of 0.9% normal saline along with the standard protocol. Blood samples for interleukins 6 and 8 were taken at baseline, and then at 2, 6 and 8 hours Post-operatively. Data was analysed using SPSS 23. RESULTS Of the 40 patients, 20(50%) were in each of the two groups. There was a marked decrease in interleukins 6 and 8 levels group A compared to group B (p<0.05). Interleukin 8 level showed a marked decline compared to that of interleukin 6 (p<0.05). CONCLUSIONS A decrease in interleukins 6 and 8 levels highlighted the anti-inflammatory role of lidocaine and resulted in a decrease in post-operative opioid consumption.
Mate choice errors may contribute to slow spread of an invasive Eurasian longhorn beetle in North America

Tetropium fuscum (Coleoptera: Cerambycidae) is a Eurasian longhorn beetle and forest pest that first became invasive to Nova Scotia, Canada around 1990. In the time since its introduction, T. fuscum has spread only about 150 km from its point of introduction. In its invasive range, T. fuscum co-exists with its congener Tetropium cinnamopterum. Although they are ecologically similar species, T. fuscum tends to infest healthier trees and has a smaller host range than T. cinnamopterum. If they successfully interbreed, this could lead to hybrid individuals that are more problematic than either parent species. On the other hand, if T. fuscum can make mating errors in the field, but is not producing hybrid offspring, then this waste of mating resources could help explain the slow spread of T. fuscum in North America. We conducted no-choice and choice mating experiments between T. fuscum and T. cinnamopterum males and females and determined that both T. fuscum and T. cinnamopterum males make mate-choice errors with heterospecific females in a laboratory setting. Our results suggest that mating errors may play a role in the slow spread of T. fuscum in North America.
Learning Automated Essay Scoring Models Using Item-Response-Theory-Based Scores to Decrease Effects of Rater Biases

In automated essay scoring (AES), scores are automatically assigned to essays as an alternative to grading by humans. Traditional AES typically relies on handcrafted features, whereas recent studies have proposed AES models based on deep neural networks to obviate the need for feature engineering. Those AES models generally require training on a large dataset of graded essays. However, assigned grades in such a training dataset are known to be biased owing to effects of rater characteristics when grading is conducted by assigning a few raters in a rater set to each essay. Performance of AES models drops when such biased data are used for model training. Researchers in the fields of educational and psychological measurement have recently proposed item response theory (IRT) models that can estimate essay scores while considering effects of rater biases. This study, therefore, proposes a new method that trains AES models using IRT-based scores for dealing with rater bias within training data.
Using online student interactions to predict performance in a first-year computing science course

ABSTRACT Student performance is a critical factor in determining a university’s reputation because it has a negative effect on student retention. Students who do not perform well in a course are more likely to drop out from their programmes before graduating. Many students who enrol in Computing Science programmes struggle to find success because it is considered a difficult discipline. In this study, a sample of 918 observations were selected containing demographic and academic information about students enrolled in a first-year undergraduate Computing Science course at a university. Classification algorithms such as Decision Tree, Random Forest, Naïve Bayes and Support Vector Machine were used to build predictive models to determine whether a student will pass or fail the course. The results showed the Random Forest algorithms are capable of producing better predictive performance compared with traditional Decision Tree algorithms.
OPTIMAL PATH IDENTIFICATION USING ANT COLONY OPTIMISATION IN WIRELESS SENSOR NETWORK

Wireless Sensor Network WSN is tightly constrained for resources like energy, computational power and memory. Many applications of WSN require to communicate sensitive information at sensor nodes SN to Base station BS. The basic performance of WSN depends upon the path length and numbers of nodes in the path by which data is forwarded to BS. In this paper we present bio-inspired Ant Colony Optimisation ACO algorithm for Optimal Path Identification OPI for packet transmission to communicate between SN to BS. Our modified algorithm OPI using ACO is base-station driven which considers the path length and the number of hops in path for data packet transmission. This modified algorithm finds optimal path OP as well as several suboptimal paths between SN & BS which are useful for effective communication.