Miracle-dz/UniFAR-FTUs huggingface dataset:
Students' Perceptions and Attitudes Towards the Importance of Soft Skills Development in Learning and Career Development

This study aims to understand students' perceptions and attitudes in Vietnam about the importance of developing soft skills in their academic and professional life. Through in-depth interviews with 15 students from 9 universities in Hanoi. The research results show that university students in Vietnam generally understand and appreciate the importance of soft skills for personal development, career advancement and meeting society's expectations. Students recognize the competitive advantage that soft skills bring to the job market and express motivation to develop these skills, including career aspirations and personal development goals. However, the study also identifies various barriers and challenges that prevent them from acquiring and applying soft skills. Based on the results of the study, a number of recommendations are made to support the holistic development of students, equipping them with the necessary soft skills for academic and career success.
May 10, 2020 Experimental Investigation of the Evolution of Gaussian Quantum Discord in

Gaussian quantum discord is a measure of quantum correlations in Gaussian systems. Using Gaussian discord, we quantify the quantum correlations of a bipartite entangled state and a separable two-mode mixture of coherent states. We experimentally analyze the effect of noise addition and dissipation on Gaussian discord and show that the former noise degrades the discord, while the latter noise for some states leads to an increase of the discord. In particular, we experimentally demonstrate the near death of discord by noisy evolution and its revival through dissipation.
Spatial pattern and temporal dynamics of limnological variables in Liuxihe Reservoir,Guangdong

Liuxihe Reservoir, located at the tropic of Cancer, is a large valley-type reservoir. In order to understand its limonological features, main limnological variables including hydrological and environmental factors were observed monthly in 2006. Surface water temperature ranged from 14.9 ℃ to 31.6 ℃ . The thermal stratification was monomictic, initiating in the early March when the water temperature reached 20 ℃, and lasting until December. The total precipitation in 2006 was 2960mm, but mainly distributed in wet season (from April to September). The mean water residence time was about 170 days, being more short in the flooding season (65 days). The mean concentrations of TN, TP, chlorophyll-a and SD were 0.66mg/L, 0.016mg/L, 2.2mg/m3 and 3.1m, respectively, indicating that the reservoir was oligo-mesotrophic. Mass ratio of TN/TP is around 41, 78 for DIN/DIP. Both ratios were much higher than the Redfield ratio, and mean that growth of phytoplankton was strongly limited by phosphorus. The high N/P ratio was attributed to the tropical red soil containing rich iron. A distinct longitudinal pattern and seasonal variability in limnological variables were observed in this reservoir. At the beginning of wet season (April and May), all nutrient concentrations were significantly higher than other period. It confirmed that surface runoff was the main path for nutrient loading into the reservoir. The longitudinal pattern of nutrient and chlorophyll-a concentrations was typical as follows as riverine zonetransition zonelacustrine zone, and the water transparency correspondingly showed an opposite one. High inflow with monsoon was the main driving force in seasonality of limnological variables, and resulted finally in a significantly longitudinal gradient of these variables by interacting with the reservoir own morphology.
Evaluation of naïve and covariance algorithms in variable selection methods

One of the essential aspects of modeling is the model's simplicity. Several methods can simplify the model, including Ridge regression, LASSO, and Elastic Net. We developed an algorithm for selecting the variables in these models, namely Naïve and Covariance. Previous research revealed that the Covariance algorithm is superior in terms of time compared to the Naïve algorithm. It is evaluated by applying models and algorithms to male sex behavior data with the criteria of goodness, namely the simplicity of the model and the minimum AIC value. Based on the study's results, it found that the Covariance algorithm still outperformed the Naïve algorithm in all three models.
Perbandingan Teknik Klasifikasi Catatan Medis untuk Indeks Antropometri Status Gizi Balita

Menilai status gizi balita sangat penting untuk mengawasi perkembangan gizi balita. Penelitian ini mencoba membandingkan dua cara untuk mengklasifikasikan status gizi balita, yaitu dengan menggunakan metode K-Nearest Neighbors (K-NN) dan Support Vector Machine (SVM) berdasarkan Indeks Antropometri. Penelitian ini dilakukan untuk mengetahui teknik mana yang paling baik untuk mengelompokkan balita dalam dataset gizi balita. Data yang digunakan untuk proses ini mencakup informasi seperti jenis kelamin, usia, berat badan, tinggi badan, dan indeks massa tubuh. Kami juga menghitung status gizi balita berdasarkan indeks antropometri, berat badan untuk usia (WFA), tinggi badan untuk usia (HFA), berat badan untuk tinggi badan (WFH), dan indeks massa tubuh untuk usia (BMIFA). Dalam mengukur seberapa baik teknik ini bekerja, kami menggunakan 827 data balita sebagai data latihan dan 207 data balita sebagai data uji. Hasilnya menunjukkan bahwa model K-Nearest Neighbors (K-NN) memiliki akurasi sekitar 93,01%, sementara model SVM memiliki akurasi sekitar 91,8%. Ini berarti model K-NN sedikit lebih baik daripada model SVM dalam mengklasifikasikan status gizi balita berdasarkan indeks antropometri.
Aquatic Insects as Bioindicators of Water Quality in the Achenkovil River, Kerala, India.

The origin of the Achenkovil River, the Devarmalai of Western Ghats, is within the Konni reserve forest of Pathanamthitta district, flowing through Pathanamthitta, Kollam, and merging with the Pamba river in the Alappuzha district. This study included the spatial variation of aquatic insect fauna with respect to water quality. The bottom water samples and insect fauna were collected bimonthly using a Niskin sampler and D-frame nets for a period of one year (February 2019 to January 2020). The study yielded 10736 insect fauna under 8 orders, 21 families, 35 genera, and 36 species. How the quality of the water affects biodiversity of aquatic insects was examined using multivariate statistical techniques (PCA and CCA) and Pearson's correlation coefficient. The findings showed that the upstream portion of the river has a remarkable diversity and quantity of aquatic insect species. The major insect group in the collected sample was ephemeroptera. There were no pollution-sensitive taxa in the middle stream or downstream portions of the river, which suggests that the water quality was declining. The middle stream and downstream sections of the river did not contain any pollution-sensitive taxa, indicating deteriorating water quality. Human-caused factors like washing, cleaning cars, and washing cattle and disposal of garbage are common in these regions. Because most aquatic insects are sensitive to environmental fluctuations, they can be used as an efficient tool in biomonitoring studies.
An Improved Artificial Potential Field UAV Path Planning Algorithm Guided by RRT Under Environment-Aware Modeling: Theory and Simulation

Unmanned Aerial Vehicles (UAVs) have been extensively researched and used in civil and military applications due to their effectiveness and flexibility. However, when identifying obstacles and avoiding them, most of the existing path planning methods fail to accurately perceive the environment, such as without considering the differences between obstacles, which leads to low timeliness and easy fall into a local minimum. In this work, an improved artificial potential field UAV path planning algorithm (G-APF) guided by the rapidly-exploring random tree (RRT) based on an environment-aware model is designed to overcome the limitations of traditional methods. The model can perceive different objects in the environment through the addition of supervised environment modeling to traditional unsupervised path planning. Specifically, an environment-aware model based on YOLOv8 is used to establish the UAV flight environment model, and an adaptive optimal threat distance calculation module is used to construct the repulsive potential field. Secondly, to improve the timeliness of path planning and the global awareness of the model, we first use the G-APF algorithm to plan the rough flight path based on the UAV flight environment. Then, the initially generated trajectory is replanned by building an attractive potential field and combining it with a repulsive potential field. Finally, the problems of local minimum and target unreachability and local trajectory oscillation generated by the artificial potential field (APF) algorithm are solved by G-APF. Experiments with generated regions are performed to demonstrate the efficiency and effectiveness of the proposed approach.
Element Content is a Highly Reliable Marker for Niche Vegetable Oils

The content of twelve elements encountered in four different vegetable oils, each coming from a specific geographical location was precisely determined by ICP-AES over three consecutive years (2015–2017). For each oil type, results were remarkably reproducible indicating that element composition is a powerful fingerprint to depict an oil. Our results allow us to suggest that, once the vegetable origin of any niche oil has been certified (using its element content or not), element content determination can sign its geographical origin.
Autologous blood transfusion in a neurosurgical patient with multiple alloantibodies

There are many challenges to obtain antigen-negative, crossmatch compatible blood for a patient with multiple alloantibodies. We present a case report of a 31-year-old female patient with a recurrent pontine cavernoma who was to undergo a neurosurgical procedure. We identified alloantibodies anti-Fya and anti-c in her blood sample. To meet her intraoperative blood requirement, we attempted with autologous blood transfusion using both predeposit autologous donation and acute normovolemic hemodilution. Autologous blood alone was sufficient despite anticipating surgical blood loss and a postoperative surgical site infection.
Predictive value of ApoB/ApoA-I for recurrence within 1 year after first incident stroke

Background ApoB/ApoA-I ratio is a reliable indicator of cholesterol balance, particularly in the prediction of ischemic events risk. The aim of this study was to investigate the prognostic value of ApoB/ApoA-I for stroke recurrence within 1 year after the first incident. Methods We retrospectively included patients who were first diagnosed with acute (<7 days after onset) ischemic stroke. Blood samples were collected on admission, and serum ApoB and ApoA-I concentrations were measured. We analyzed the relationship between ApoB/ApoA-I ratio and ischemic stroke recurrence within 1 year. Results A total of 722 patients with acute ischemic stroke were included, of whom 102 experienced stroke recurrence within 1 year, with a recurrence rate of 14.1%. Serum ApoB/ApoA-I concentrations on admission were higher in patients with stroke recurrence at 1 year compared with those with a good prognosis (P < 0.001). The Kaplan-Meier survival curve revealed a significant difference in cumulative stroke recurrence rates across ApoB/ApoA-I tertiles (log-rank P-value < 0.001). A positive correlation between the ApoB/ApoA-I ratio and the risk of stroke recurrence within 1 year was demonstrated using Cox regression analysis, which remained significant after adjusting for traditional risk factors [hazard ratio (HR) 4.007, 95% confidence interval (CI) 1.661–9.666]. This relationship was particularly strong in patients with LAA stroke (HR 4.955, 95% CI 1.591–15.434). Subgroup analysis further revealed that a high ApoB/ApoA-I ratio was strongly associated with stroke recurrence regardless of whether patients had high or low LDL-C levels. Discussion ApoB/ApoA-I ratio, measured during the acute phase of the first stroke, was positively correlated with the risk of stroke recurrence within 1 year.
The impact of accounting on business decision-making a case study of the hotel industry in Kosovo

This academic study examines the evolving hospitality sector in Kosovo to identify the significant impact of accounting on complex business decisions. By adopting a multifaceted approach that includes financial analysis, evaluation of financial reports and extensive interviews, it reveals how accounting serves not only as a regulatory tool but also as a strategic partner in pricing, investment and long-term planning. The report highlights the importance of accounting and reporting systems in increasing transparency, building investor confidence and managing risk in the hospitality sector in Kosovo. The findings contribute to improvements in accounting practices and a better understanding of the role of accounting in a dynamic business environment.
Navigating The Metaverse: Exploring Its Pedagogical Affordances in Language Learning

In the digital transformation era with abundant technological advancement, the Metaverse emerged in education, providing opportunities for language learning like never before. This study aims to navigate the potential of the Metaverse by exploring its pedagogical affordances in facilitating language learners, looking into the educators’ strategies in designing lessons for immersive language learning experiences and describing the perceived benefits and challenges of learning language within the Metaverse space fro m the students’ perspectives. Using qualitative research design, this study dives into the pedagogical affordances of the Metaverse, examining the extent to which Metaverse engages and motivates learners, enhances language acquisition, fosters collaboration, and immerses students in a culturally relevant context. Furthermore, this study intends to illustrate the learning environment created by educators in facilitating language learning through Metaverse. Finally, students’ voices were generated to examine the practical implications of Metaverse-based language learning. This study contributes to the broader discourse on digital education by synthesizing the findings related to these research questions. It offers insights that can inform the future of language learning, aligning pedagogy with the possibilities of the Metaverse.
Biophotovoltaics: Green Power Generation From Sunlight and Water

Biophotovoltaics is a relatively new discipline in microbial fuel cell research. The basic idea is the conversion of light energy into electrical energy using photosynthetic microorganisms. The microbes will use their photosynthetic apparatus and the incoming light to split the water molecule. The generated protons and electrons are harvested using a bioelectrochemical system. The key challenge is the extraction of electrons from the microbial electron transport chains into a solid-state anode. On the cathode, a corresponding electrochemical counter reaction will consume the protons and electrons, e.g., through the oxygen reduction to water, or hydrogen formation. In this review, we are aiming to summarize the current state of the art and point out some limitations. We put a specific emphasis on cyanobacteria, as these microbes are considered future workhorses for photobiotechnology and are currently the most widely applied microbes in biophotovoltaics research. Current progress in biophotovoltaics is limited by very low current outputs of the devices while a lack of comparability and standardization of the experimental set-up hinders a systematic optimization of the systems. Nevertheless, the fundamental questions of redox homeostasis in photoautotrophs and the potential to directly harvest light energy from a highly efficient photosystem, rather than through oxidation of inefficiently produced biomass are highly relevant aspects of biophotovoltaics.
Two-Dimensional Ferroelectrics: A Review on Applications and Devices

Over the last few years, research activities have seen two-dimensional (2D) materials become protagonists in the field of nanotechnology. In particular, 2D materials characterized by ferroelectric properties are extremely interesting, as they are better suited for the development of miniaturized and high-performing devices. Here, we summarize the recent advances in this field, reviewing the realization of devices based on 2D ferroelectric materials, like FeFET, FTJ, and optoelectronics. The devices are realized with a wide range of material systems, from oxide materials at low dimensions to 2D materials exhibiting van der Waals interactions. We conclude by presenting how these materials could be useful in the field of devices based on magnons or surface acoustic waves.
Design and Implementation of Automatic Generation Algorithm for Advertising Artistic Design Based on Neural Networks

With the growth of AI, especially breakthroughs in artificial intelligence technology, designers can use machine learning algorithms to generate advertising artistic designs automatically. Traditional grid search and random search methods require a large amount of computational resources and time costs, while particle swarm optimization (PSO) algorithms can find better combinations of hyperparameters in a shorter period of time. This article proposes a current neural network (RNN) algorithm based on PSO, combined with computer-aided design (CAD) tools, to be applied to the automation generation and optimization of advertising artistic design in order to improve design efficiency. By combining the RNN algorithm with CAD tools, designers can automatically generate advertising designs through the algorithm and then adjust and output them through CAD tools. The results show that the PSO-based RNN algorithm can generate more diverse shapes, colours, and textures, demonstrating high novelty and innovation. Moreover, the correlation and overall coordination between various design elements have also been significantly enhanced.
El estrés oxidativo en el perioperatorio: implicaciones clínicas

The trauma of surgery induces systemic stress that alters homeostasis and develops postoperative complications, particularly in high-risk patients. Surgical stress is produced by an acute inflammatory process and by the imbalance between the levels of pro-oxidant molecules and the activity of antioxidant systems. This imbalance is known as oxidative stress (OS). These two mechanisms underlie perioperative complications are reduced with anaesthetic management since some anaesthetics have antioxidant capacity. OS could negatively impact all forms of major surgery, particularly in elderly patients and patients with comorbidities. This review aims to present the concept and cellular bases of OS and its relationship with the most common complications in the perioperative period of cardiac and non-cardiac surgery, as well as the quantitative determination of the level of OS through serum biomarkers. Furthermore, the effect of anaesthetics on OS and the use of antioxidant therapies
Compression therapy in a patient with Klippel-Trénaunay syndrome

Background Klippel-Trénaunay syndrome (KTS) is a rare congenital vascular malformation syndrome defined as capillary and venous malformations, and hypertrophy of the limb with or without lymphatic malformation. Currently there is no cure for KTS but the majority of patients are advised to wear compression garments on the affected limb to control swelling and discomfort. Aim To describe used compression therapy methods and their results in a paediatric patient with KTS. Methods The patient records were assessed for the used treatment methods for KTS. Our patient was treated with multimodal treatments to alleviate symptoms, and compression therapy was used specially to control lymphoedema and venous insufficiency. Results A 13-year-old boy with KTS had lymphoedema and venous insufficiency of the right lower extremity since birth. Compression therapy was started at the age of 2 months with a custom-made, single-leg compression pantyhose with gradual compression from distal to proximal regions. Furthermore, a manual lymphatic drainage and intermittent pneumatic compression were added on the regimen respectively. Other treatment methods included sclerotherapy, surgery and medication. None of treatment methods was sufficient alone to reduce limb oedema but the patient reported improved performance when using compression garments and a positive impact after enhanced compression therapy. Conclusion This report shows the importance of continuous and individualised compression therapy in the treatment of lymphoedema associated to KTS.
The TEI Program for Peer Tutoring and the Prevention of Bullying: Its Influence on Social Skills and Empathy among Secondary School Students

Bullying is a phenomenon that afflicts millions of students around the world, severely harming their emotional and psychological well-being. In response to this challenge, the TEI program (Tutoría Entre Iguales or Peer Tutoring) has been developed as a bullying prevention strategy, aiding students in acquiring social skills and emotional strategies for conflict resolution. The purpose of this research is to examine social skills and empathy among different actors involved in bullying (non-involved, victim, bully, and bully-victim) among secondary school students and to evaluate the impact of the TEI program on the development of relational competencies. A comparative, ex post facto study was conducted in three schools where the TEI program has been implemented (TEI schools) and three where it has not (non-TEI schools). A total of 738 secondary school students (ESO) participated in the study, using a standardized questionnaire to evaluate their perception of bullying. The results of this study demonstrate higher levels of assertiveness and empathy in the non-involved and victim groups. However, lower levels of conflict resolution skills were found in the bully-victim group. In TEI schools, a higher percentage of students not involved in bullying and a lower percentage of bully-victims were observed. Additionally, students in TEI schools scored higher in assertiveness, conflict resolution skills, social skills, and empathy. These findings highlight the importance of developing students’ relational competencies and implementing strategies for bullying prevention to create a safe, healthy, and positive learning environment in schools.