Miracle-dz/UniFAR-FTUs huggingface dataset:
Application Analysis of English Personalized Learning Based on Large-scale Open Network Courses

In the context of Big data, large-scale open online courses increase learning paths for learners, but in the face of countless high-quality curriculum resources, it is easy for derivative learners to face the dilemma of rich curriculum resources but difficult to choose resources, which leads to information maze for learners. How to help learners quickly and accurately find their own learning resources in the explosive growth of MOOC resources is an urgent problem in the field of education Big data. However, the traditional Collaborative filtering recommendation technology does not perform well when dealing with sparse data and cold start. The recommendation content is repeated and can not effectively deal with high-dimensional and nonlinear data of online learning users, resulting in low efficiency of resource recommendation. Therefore, the study adopts a deep belief network (DBN) to construct a personalized resource recommendation model. The model combines the learner behavior characteristics with the curriculum resource content attribute characteristics to form the learner feature vector. The parameters of the model are adjusted according to the characteristics of learners. Through experiments, the proposed model has shown good performance. The experiment explored the effects of training set size, learner characteristics, and GPU on model performance. The experimental results show that when the training set proportion is 100%, the RMSE, Accuracy, Recall, and F1 values of the model are 0.76, 0.946, 0.957, and 0.951, respectively. When the model is trained using a training set containing learner features, the RMSE, Accuracy, Recall, and F1 values of the model are 0.75, 0.962, 0.908, and 0.958, respectively. After using GPU to accelerate the model, the running time of the model decreased from 360 minutes to 90 minutes. The results indicate that the model cannot effectively mine data information when the degree of correlation between sample information is low. The richer the relationships between samples, the better the performance of the model. Simultaneously learning hunger feature vectors and learner behavior feature vectors for training can significantly improve the recommendation accuracy of the model. The main contribution of this study is to propose a recommendation method based on DBN classification to replace traditional similarity calculation methods, using DBN's efficient feature abstraction and feature extraction capabilities to fully explore learners' interest and preference for course resources. In addition, in view of the common problems of cold start and data sparsity in traditional Collaborative filtering recommendation methods, the research deeply mines the characteristics of learners' Demographics and curriculum resources' content attributes, and constructs a learner interest model based on DBN combined with learners' behavior characteristics, which effectively solves the problems of cold start and data sparsity, as well as the inaccurate expression of learners' interest preferences for curriculum resources.
New land-cover maps of Ghana for 2015 using Landsat 8 and three popular classifiers for biodiversity assessment

ABSTRACT Remote-sensing products provide opportunities to monitor complex phenomena on the Earth from space for good decision-making. An example is land-cover maps, which are useful for monitoring both human- and naturally induced environmental changes to enhance environmental management for the benefit of the society. Yet there are numerous critical areas of the world such as biodiversity hotspots where the inaccessibility of quality satellite images has hindered progress in our understanding and management of the natural environment. The West African biodiversity hotspot is one such area where persistent thick clouds in freely available satellite images has been a great discouragement to the production of local land-cover maps to monitor the ongoing deforestation and rapid environmental change. Ghana is a country in West Africa where no land-cover map (except global ones) has been published for over a decade although large tracts of land have been converted from their natural states to agricultural land. In this article, we present 30 m land-cover maps of the country using Landsat 8 images and three popular classifiers – Maximum Likelihood Classifier (MLC), Support Vector Machines (SVMs), and random forest (RF) – for the year 2015. We produced these maps for use in our future biodiversity assessment in the region. An overall accuracy (OA) of 85.5% (kappa = 0.77) was achieved for MLC, with similar but slightly lower accuracies for RF and SVM, which indicates that advanced classification algorithms may not have many advantages when applied to process only multispectral optical data. We observe that shrublands, croplands, and orchards are the dominant classes occupying 35.6%, 31.9%, and 18.4% of the country’s land area, respectively. This further indicates that 50.0% of the country’s land area is under agriculture. Thick forests occupy only 8.0% of the land and are almost entirely confined to forest reserves, highlighting the usefulness of these nature reserves. Our maps will provide input for research advancement, policy formulation, and environmental management at both national and subnational levels.
Urban subcentres in German city regions: Identification, understanding, comparison

Whereas many studies exist regarding urban subcentre identification, systematic analyses of these methods' characteristics are scarce. This paper addresses and reflects these issues for one selected method, the locally weighted regression (LWR) approach. Methodologically the study concludes that no ‘one size fits all’ method exists, but that the LWR is a sensitive means to identify urban subcentres. Content‐wise the study finds that German city regions are fairly monocentric, as all identified subcentres are of local relevance only. Comparisons to the urban spatial structure in US metro areas, to which the same LWR is applied, however, prove to be fairly complicated. Mientras que existen muchos estudios sobre la identificacion de subcentros urbanos, los analisis sistematicos de las caracteristicas de estos metodos son escasos. Este articulo aborda estas cuestiones y reflexiona sobre ellas para un metodo seleccionado: el enfoque de regresion ponderada localmente (LWR, por sus siglas en ingles). Metodologicamente, el estudio concluye que no existe un metodo de ‘talla unica’, sino que el LWR es una forma rigurosa para identificar subcentros urbanos. En lo que respecta al contenido, el estudio encontro que las regiones ciudad alemanas son bastante monocentricas, ya que todos los subcentros identificados tienen solo relevancia local. Sin embargo, las comparaciones con la estructura espacial urbana en las areas metropolitanas de los EE.UU. a las que se aplica el mismo LWR, resultan ser bastante complicadas. 都市部におけるサブセンターの特定に関する研究は多数存在するが、その研究方法の特色に関するシステマティック分析はほとんど行われていない。 本稿では、ある一つの方法、すなわち局所重み付き回帰(locally weighted regression:LWR)アプローチを選択して、この問題を検討する。 方法論的な結論として、万能型の方法は存在しないが、LWRはサブセンターの特定には感度が高い方法であるといえる。 内容的には、ドイツの都市部の地域は単心型(monocentric)が多く、特定されたサブセンターはすべて地域重視(local relevance)であることが分かる。 これと同じLWR法を応用して、米国の大都市圏の都市空間構造と比較すると、米国の都市はかなり複雑であることが分かる。
Mesoscale structure of tropical cyclones in the northwestern part of the Pacific ocean according to the data of the WWLLN

The paper investigates lightning activity in the region of tropical cyclones (TC), its structure and changeability during the process of TC development and attenuation according to the data of the World Wide Lightning Location Network (WWLLN) as well as the relation with ocean surface wind fields according to the ASCAT scatterometer data. Distribution of lightning discharges in TC regions and discharge density fields drawn up from them allowed us to detect TC structure elements, such as mesovortexes, eyewalls, cloud bands and spirals, and to trace their change in space and time.
Descriptive and Functional Genomics in Neonatal Respiratory Distress Syndrome: From Lung Development to Targeted Therapies

In this up-to-date study, we first aimed to highlight the genetic and non-genetic factors associated with respiratory distress syndrome (RDS) while also focusing on the genomic aspect of this condition. Secondly, we discuss the treatment options and the progressing therapies based on RNAs or gene therapy. To fulfill this, our study commences with lung organogenesis, a highly orchestrated procedure guided by an intricate network of conserved signaling pathways that ultimately oversee the processes of patterning, growth, and differentiation. Then, our review focuses on the molecular mechanisms contributing to both normal and abnormal lung growth and development and underscores the connections between genetic and non-genetic factors linked to neonatal RDS, with a particular emphasis on the genomic aspects of this condition and their implications for treatment choices and the advancing therapeutic approaches centered around RNAs or gene therapy.
Microvascular Complications and Associated Risk Factors in Patients with Type 2 Diabetes Mellitus in Al-Madinah Al-Munawara, Saudi Arabia

Background/ aim: Chronic hyperglycemia is a hallmark of the metabolic disorder diabetes mellitus, which also causes microvascular problems that cause morbidity, recurrent hospital stays, and death. Our study's objective is to determine the relationships between microvascular issues and risk factors in people with type 2 diabetes in Al-Madinah Al-Munawara. Subjects and Methods: In Al-Madinah Al-Munawara, 275 patients with type 2 diabetes participated in this descriptive cross-sectional study; 86 of them had microvascular complications. An online questionnaire was used to collect the data. The study covered all participants aged 20 to 65 years old. Incomplete data, patients suffering from COVID-19, chest infections, cancer, and pregnant women were excluded. Results: Microvascular complications affect 37.3% of the elderly (41–65 years old) and 63% of the young (20–40 years old). There is a significant association (p <0.05) between the age of the patients and various types of microvascular complications. Retinopathy and peripheral neuropathy were more common in males than females. There was a positive correlation between HbA1c levels and other variables such as serum cholesterol, hemoglobin, high blood pressure, and the number of hospitalizations. Age, gender, hypertension, and type of treatment have a significant positive effect on the appearance of microvascular complications (p <0.05). Conclusion: In our study, the age, gender, and type of treatment of participants were independent predictors of microvascular complications among type 2 diabetic patients. The risk of complications from DM in this country will be decreased by health education and raising awareness.
Self-purification of Aquatic Media from Hexachlorocyclohexane in a Radical Process

It is known, that highly toxic pesticide hexachlorocyclohexane (HCH) is resistant to decomposition and has a long-term accumulating capacity. Nevertheless, it undergoes complete degradation in reactions with hydroxyl radicals in Fenton-like systems. The goal of this work was to study the influence of HCH on the processes of radical self-purification of water bodies and to explain the mechanisms of chemical transformation of substances occurring in natural waters, as well as to reveal the kinetic characteristics of the processes of radical self-purification of water bodies. It was found, that HCH plays a dual role for aquatic ecosystems – it is not only a scavenger of free radicals, but also an additional initiator. Under the influence of light in the surface layer of water, HCH generates radicals, thus contributing to the self-purification processes.
The Methylene Blue adsorption test applied to geomaterials

Review of the application of the Methylene Blue adsorption test (titration spot method) applied to geomaterials (soils and rocks). With this method the Cation Exchange Capacity (CEC) of fine soils or fine grounded rock powder can be determined. Swelling clays have a high CEC and even small quantities (less than 1 mass % can be detected by this method. Applications of the method are discussed including assessment of the durability of armourstone.
Amelioration of a calcareous saline-sodic soil by gypsum application and different crop rotations

A lysimeter study was conducted to assess the impact of some crop rotations and gypsum on amelioration of a calcareous saline-sodic soil (pHs = 8.4, ECe = 8.6 dS m, SAR = 37.7, CaCO3 = 81.1 g kg) irrigated with marginal-quality water (EC = 1.0 dS m, SAR = 4.2, RSC = 3.1 mmolc L). There were five treatments: (1) control (no crop or chemical amendment), (2) cropping with wheat (Triticum aestivm L.) and rice (Oryza sativa L.) without gypsum application (WR), (3) cropping with wheat and rice with soil application of gypsum (GWR), (4) cultivation of berseem (Trifolium alaxandrinum L.) and Kallar grass {Leptochloa fusca (L.) Kunth} without gypsum application (BK), and (5) cultivation of alfalfa (Medicago sativa L.) and sesbania (Sesbania aculeata L.) without gypsum application (AS). It has been observed that the GWR treatment removed greater amounts of sodium (Na) from the root zone leaving behind minimum level of sodium adsorption ratio (SAR) and the greatest ECe: SAR ratio in post-amelioration soil. Cropping treatments alone had little effect on calcite dissolution and removed less Na during one year period. This evidence suggests that application of a chemical amendment like gypsum could only be advantageous while irrigating saline-sodic soils with marginal-quality waters during reclamation.
The Evolution of Platform Science

Abstract:Although we have been living through an era of the commercialization of science since the 1980s, something has dramatically changed over the last decade. Whereas commercialization used to subject research outputs to market considerations, a new development seeks to monetize nearly all aspects of the research process. This has become manifest under the rubric of “open science” as the purported solution to what is perceived to ail modern science. The commercial interests behind top journal publishers are pursuing control over “open science” by imposing the structures of “platform capitalism” upon the research process. The release of ChatGPT is best understood as the latest act in this drama, with Silicon Valley AI platforms threatening to displace the Big Five publishers as the primary protagonists of the commercialization of science.
Discrete-time Receivers, from N-Path to Charge Sharing Band-pass Filters: a Comparison

Technology scaling greatly benefits discrete-time and N-path filters, making them perfect for Software-Defined Radio and wireless Standards designs. Both strategies enable wide-band and narrowband solutions, high selectivity and easy programmability with low power and high linearity. This paper presents a review of discrete-time and N-path based receivers. Their architecture similarities are examined, focusing on discrete-time receiver building blocks whose features and advances are detailed. An extensive literature review of the State-of-the-Art on these strategies is conducted.
A Survey of Text Classification With Transformers: How Wide? How Large? How Long? How Accurate? How Expensive? How Safe?

Text classification in natural language processing (NLP) is evolving rapidly, particularly with the surge in transformer-based models, including large language models (LLM). This paper presents an in-depth survey of text classification techniques across diverse benchmarks, addressing applications from sentiment analysis to chatbot-driven question-answering. Methodologically, it utilizes NLP-facilitated approaches such as co-citation and bibliographic coupling alongside traditional research techniques. Because new use cases continue to emerge in this dynamic field, the study proposes an expanded taxonomy of text classification applications, extending the focus beyond unimodal (text-only) inputs to explore the emerging field of multimodal classification. While offering a comprehensive review of text classification with LLMs, this review highlights novel questions that arise when approaching the task with transformers: It evaluates the use of multimodal data, including text, numeric, and columnar data, and discusses the evolution of text input lengths (tokens) for long text classification; it covers the historical development of transformer-based models, emphasizing recent advancements in LLMs; it evaluates model accuracy on 358 datasets across 20 applications, with results challenging the assumption that LLMs are universally superior, revealing unexpected findings related to accuracy, cost, and safety; and it explores issues related to cost and access as models become increasingly expensive. Finally, the survey discusses new social and ethical implications raised when using LLMs for text classification, including bias and copyright. Throughout, the review emphasizes the importance of a nuanced understanding of model performance and a holistic approach to deploying transformer-based models in real-world applications.
Development of A Validity and Reliability Taekwondo Technical Skill Test Instrument

Objective: This research aims to compile and develop valid and reliable Taekwondo skill test instruments that meet the competition and to develop test tools with standard norms and conversion values. The participants in this study are the athletes Puslatda Taekwondo Indonesia East Java and the region of Surabaya, 28 senior kyourugi male. The data collection method in this study uses quantitative descriptive, a research procedure using Research and Development (R&D) by Borg & Gall (2007:590). Data analysis used in this research uses Statistical Product and Service Solutions (IBM SPSS V.26), a data analysis technique used as a single correlation of Pearson’s Moment Product. Results: The results of the Standard Operational Procedures (SOP) guidelines for implementing tests and measurement of Taekwondo skills, the Peta Chagi, Pyojeuk, and Jireugi maps, which are valid and reliable. Novelty: The innovation in this research is the creation of the Standard Operational Procedures (SOP) test and measurement techniques skills kicking and kicking that trainers can use to know the best kick of each athlete.
Effects of psychodrama and cognitive behavioral therapy on assertiveness skills of women with marital conflicts

Background and aims: A lack of assertiveness can worsen marital conflicts and cause psychological symptoms. The present study aimed to investigate the effects of psychodrama and cognitive behavioral therapy (CBT) on the assertiveness skills of women with marital conflicts. Methods: This quasi-experimental study was conducted on all married women with marital conflicts visiting the counseling departments of cultural centers at the Municipality of Isfahan (Iran) in 2021. Cluster sampling was employed to select 60 women, who were then assigned to three 20-member groups called CBT, psychodrama, and control using a simple random method. The participants completed the Assertion Inventory before and after the intervention and 60 days after the post-test. The repeated measures ANOVA via SPSS-22 was then used for data analysis. Results: The mean (±SD) of the post-test score of assertiveness skills in the psychodrama and CBT groups was 123.40 (±23.83) and 111.25 (±22.77), respectively, which was different from the control group (83.20 (±21.24)). According to the results, CBT and psychodrama affected the assertiveness components of women with marital conflicts instead of control cases (P<0.001). Furthermore, there were no significant differences between CBT and psychodrama regarding effects on women’s assertiveness components. Conclusion: Considering the positive effects of CBT and psychodrama on improving assertiveness, it is recommended that counseling and psychotherapy centers help women with marital conflict improve their assertiveness skills by providing suitable conditions for conducting CBT and psychodrama sessions.
An Assessment of the Influence of Earthquake Duration in Inducing Landslides

Earthquake duration is a complex natural phenomenon associated with the sudden energy release induced by fault rupture. The shaking during an earthquake is a result of the primary, secondary and surface waves. This study is aimed at establishing the relationship between earthquake duration and other seismic parameters: magnitude, peak ground acceleration, focal distance, fault length in relation to landslides generated by the major earthquakes. To achieve this objective, we made an intensive review of published data on major earthquakes (Mw ≥ 6.6) that generated landslides between 1998 and 2015 in the world. The results reveal that magnitude, focal length and focal depth times fault length are strong determinants of earthquake duration. However, it is noted that peak ground acceleration (PGA) and focal depth do not necessarily determine the duration of earthquake shaking. It is also observed that duration of an earthquake is moderately correlated to area affected by earthquake induced landslides. Additionally, much as the number of landslides produced during and/or after an earthquake does not necessarily augment with increasing duration majority of the investigated major earthquakes that produced great damage, with respect to landslides, were noticed to have lasted for not more than 60 seconds.
Coffee cherry processing waste to produce value-added products through clean production biorefineries

Indonesia is the 4th largest coffee-producing country in the world. Coffee cherry can produce 60% CCPW, more than the core product of coffee beans as the main product produced. CCPW contains lignocellulosic material that can be converted into value-added products. This research optimizes the production of xylose and xylanase enzymes as an integrated process with a biorefinery model to increase the added value of CCPW using the Research Surface Methodology (RSM). Enzyme production is carried out using a bioprocess using Trichoderma viride. Xylose production is carried out using the dregs of xylanase production as raw material and xylanase enzymes which are produced in the integrated process. The xylanase and xylose produced are in the liquid phase. The treatment design for xylanase production is substrate concentration and incubation time, while for xylose production it is substrate concentration and xylanase concentration. Based on the optimization conducted, the optimum condition of xylanase production was 75% substrate concentration with an incubation time of 72 hours, which will result in xylanase an enzyme with an activity of 29.275 U/ml with desirability of 99.55%. On the other hand, the optimum condition of xylose production was 12.54% substrate concentration with a xylanase concentration of 4.01%, which will result in 0.53 g/L xylose content with desirability of 94.06%. These findings show that xylose production efficiency can be achieved through integrated two-stage biorefinery production for efficient and sustainable utilization of CCPW.