Miracle-dz/UniFAR-FTUs huggingface dataset:
Density Based Data Clustering

Data clustering is a data analysis technique that groups data based on a measure of similarity. When data is well clustered the similarities between the objects in the same group are high, while the similarities between objects in different groups are low. The data clustering technique is widely applied in a variety of areas such as bioinformatics, image segmentation and market research. This project conducted an in-depth study on data clustering with focus on density-based clustering methods. The latest density-based (CFSFDP) algorithm is based on the idea that cluster centers are characterized by a higher density than their neighbours and by a relatively larger distance from points with higher densities. This method has been examined, experimented, and improved. These methods (KNN-based, Gaussian Kernelbased and Iterative Gaussian Kernel-based) are applied in this project to improve (CFSFDP) density-based clustering. The methods are applied to four milestone datasets and the results are analyzed and compared.
Application of Straw and Biopreparations as a Sustainable Method for Increasing the Organic Carbon Content and Chemical, Physical, and Biological Soil Properties in Spring Barley Culture

Increasing climate change, through its impact on the economy, results in measures to reduce its negative effects. In agriculture, the expected positive effects may come from the implementation of practices with high carbon sequestration potential (e.g., straw incorporation). The idea of using straw as an energy feedstock requires an in-depth analysis of the impact of this practice on the organic carbon content of arable soils. Straw incorporation combined with the use of biopreparations can provide an attractive alternative to conventional fertilization and plant protection systems. This study aimed to assess the effect of straw, effective microorganisms preparation, and biostimulant on the physicochemical and biological soil parameters. The analyses included organic carbon, available P, K, and Mg, total and mineral nitrogen content, pH, bulk density, soil penetration resistance, and the number of soil-culturable heterotrophic bacteria, actinobacteria, and fungi determination. It was found that straw and EM addition resulted in the highest SOC content. Statistically lower values of bulk density and soil penetration resistance were also observed after straw incorporation. The results of our research revealed that, while the addition of straw beneficially affects soil quality, the impact of biopreparations application on soil parameters varies depending on the experimental combination used.
IMMEDIATE SURGICAL TREATMENT IN NEGLECTED OPEN LEFT SUPRACONDYLAR HUMERAL FRACTURE: A CASE REPORT

ABSTRACT Supracondylar humeral fractures are the most common paediatric elbow fractures. However, open supracondylar humeral fractures are rarely found in children. In developing countries, delayed treatment is common, and patient can present to hospital as neglected case. The aim of this article is to report immediate surgical treatment in neglected case of open supracondylar humeral fracture. A case of 16-year-old boy who suffered from neglected open left supracondylar humeral fracture was reported. He had history of traffic accident 10 days before admission, and was treated by traditional bone setter. He has already undergone surgery by debridement and followed by an open reduction with cross K-wire internal fixation, and external support post operatively. The fracture has already reduced and fixated well postoperatively. Immediate surgical treatment of neglected open supracondylar humeral fractures is recommended to achieve the best reduction of the fractures and prevent the infection.Key words: Surgical Treatment; Neglected Case, Open Fracture, Supracondylar Humeral ABSTRAK Fraktur humerus suprakondiler merupakan fraktur yang paling sering pada siku anak-anak. Namun, fraktur terbuka humerus suprakondiler jarang ditemukan pada anak-anak. Di negara berkembang, sering dijumpai penanganan yang tertunda, dan pasien bisa datang ke rumah sakit dalam keadaan sebagai kasus yang terabaikan. Tujuan dari artikel ini adalah untuk melaporkan penanganan pembedahan segera pada kasus fraktur terbuka humerus suprakondiler yang terabaikan.Dilaporkan seorang anak laki-laki berusia 16 tahun yang menderita fraktur humerus suprakondiler kiri yang terabaikan. Dia memiliki riwayat kecelakaan lalu lintas 10 hari sebelum datang ke rumah sakit, dan awalnya ditangani oleh dukun sangkal putung tradisional. Dia telah menjalani operasi dengan debridemen dan diikuti oleh reduksi terbuka dan pemasangan fiksasi internal menggunakan k-wire silang, dan pemasangan slab gips eksternal pasca operasi. Hasil pasca operasi menunjukkan bahwa fraktur tereduksi dan terfiksasi dengan baik. Penanganan pembedahan segera untuk fraktur terbuka humerus suprakondiler yang terabaikan direkomendasikan untuk mendapatkan reduksi terbaik dari fraktur dan mencegah infeksi.Kata kunci: Penanganan Pembedahan; Kasus Terabaikan, Fraktur Terbuka, Humerus Suprakondiler
Change, time and information geometry

Dynamics, the study of change, is normally the subject of mechanics. Whether the chosen mechanics is ``fundamental'' and deterministic or ``phenomenological'' and stochastic, all changes are described relative to an external time. Here we show that once we define what we are talking about, namely, the system, its states and a criterion to distinguish among them, there is a single, unique, and natural dynamical law for irreversible processes that is compatible with the principle of maximum entropy. In this alternative dynamics changes are described relative to an internal, ``intrinsic'' time which is a derived, statistical concept defined and measured by change itself. Time is quantified change.
Song popularity and processing fluency of lyrics

Several studies show that a concept or object is more popular when it is easier to process. The present research applies this notion of processing fluency to the lyrics of all 271 top 5 songs on the United Kingdom chart for each week from 1999 to 2014. The processing fluency of the lyrics was computer scored for readability, presence of rhyme, and complexity, and popularity was assessed in terms of peak chart position and duration of tenure on the chart. After controlling for the energy of the musical component of the song, analyses showed that factors relating to the processing fluency of the lyrics predicted peak popularity but not duration of chart tenure. Significant relationships were observed between peak popularity and both rhyme saturation and basic lyric readability properties.
Unravelling the carbon pools and carbon stocks under different land uses of Conoor region in Western Ghats of India

Land uses are pivotal in global carbon cycles. The native forest lands possess a greater potential to sequester higher carbon, which can directly address soil quality and climate change problems. Unfortunately, the rapid conversion of forests to other land use over the past few decades has significantly declined the concentration of carbon in the soils. Therefore, in order to estimate the impact of land-use change (LUC) on soil carbon status, this present study was attempted under major ecosystems (Forest (FOR), cropland (CRP), tea plantation (TEA)) of Conoor. Results from findings revealed that total organic carbon (TOC) concentration and carbon pools were significantly (p<0.05) higher in FOR than in CRP and TEA. TOC (0-45 cm) recorded in FOR, CRP and TEA was 32.88, 11.87 and 18.84 g kg-1 and it decreased along the depth increment. Carbon stock (t ha-1) in FOR, CRP and TEA (0-45cm) was 68.10, 26.04, 42.42. Microbial biomass carbon (MBC) was higher in FOR (283.08 mg kg-1) followed by TEA (94.64 mg kg-1) and CRP (76.22 mg kg-1). The microbial biomass nitrogen (MBN) followed; FOR > TEA > CRP. These results clearly indicate that the LUC has inflicted a greater impact on soil carbon status and its extent was quantified using the land degradation index (LDI). The LDI (0-45 cm) recorded in CRP (-38.65) and TEA (-61.75) signals the need for immediate implementation of carbon management strategies in the CRP and TEA ecosystem to keep the soils of Conoor alive and prevent land degradation.
Deep Learning Provides Substantial Improvements to County‐Level Fire Weather Forecasting Over the Western United States

The recent wildfires in the western United States during 2018 and 2020 caused record‐breaking fire damage and casualties. Despite remarkable advances in fire modeling and weather forecasting, it remains challenging to anticipate catastrophic wildfire events and associated damage. One key missing component is a fire weather prediction system with sufficiently long lead time capable of providing useful regional details. Here, we develop a hybrid prediction model of wildfire danger called CFS with super resolution (CFS‐SR) as a proof of concept to fill that void. The CFS‐SR model is constructed by integrating the Climate Forecast System version 2 with a deep learning (DL) technique from Single Image Super Resolution, a method widely used in enhancing image resolution. We show that for the 2018–2019 fire season, the CFS‐SR model significantly improves accuracy in forecasting fire weather at lead times of up to 7 days with an enhanced spatial resolution up to 4 km. This level of high resolution provides county‐level fire weather forecast, making it more practical for allocating resources to mitigate wildfire danger. Our study demonstrates that a proper combination of ensemble climate predictions with DL techniques can boost predictability at finer spatial scales, increasing the utility of fire weather forecasts for practical applications.
The component sizes of a critical random graph with pre-described degree sequence

Consider a critical random multigraph $\mathcal{G}_n$ constructed by the configuration model such that its vertex degrees are independent random variables with the same distribution $\nu$ (criticality means that the second moment of $\nu$ is finite and equals twice its first moment). We specify the scaling limits of the ordered sequence of component sizes of $\mathcal{G}_n$ in different cases. When $\nu$ has finite third moment, the components sizes rescaled by $n^{-2/3}$ converge to the excursion lengths of a Brownian motion with parabolic drift, whereas when $\nu$ is a power law distribution with exponent $\gamma \in (3,4)$, the components sizes rescaled by $n^{-(\gamma-2)/(\gamma-1)}$ converge to the excursion lengths of a drifted process with independent increments that will be characterized.
Feasibility of a VR Intervention to Decrease Anxiety in Children with Tumors Undergoing CVC Dressing

Virtual reality (VR) represents a promising digital intervention for managing distress and anxiety in children with tumors undergoing painful medical procedures. In an experimental cross-over study, we administered a VR intervention consisting of relaxing games during central venous catheter (CVC) dressing. The VR sessions were compared with no-VR during CVC medication. We used the distress thermometer and RCMAS-2 scale to assess distress and anxiety levels. We also explored the satisfaction level in patients and families. We enrolled 22 children. The distress levels after medication were lower in the VR group than in those without VR (VR: median 2; IQR 0–2; no-VR: median 4; IQR: 3–5). No variation in anxiety levels was detected by VR intervention. Satisfaction for using VR was very high in children and their families although a total of 12% of children were disappointed by the effect of VR. Most healthcare workers felt that VR would be useful in routine clinical practice. A VR intervention is highly acceptable, may be efficacious in decreasing distress in children with cancer undergoing painful procedures, but it is less likely that it has a measurable impact on anxiety. Evidence from larger studies is needed to assess VR translation into the clinical workflow.
Business Students Have Different Views about Their Performance and Approach to Study in Relation to Exam Formats, Depending on Attitudes Towards Digital Teaching

The aim of this article is to see if there are substantial differences in attitudes towards teaching methods and choice of assessment between the students who are present at campus and to those who prefer the online version. During COVID-19, we got a unique opportunity to compare the students who took the same course and had identical exams. The same questionnaire is distributed to both groups in a compulsory subject in economics at Norwegian University of Science and Technology (NTNU). The choice of method is a pairwise comparison of the mean values using T-test. The findings show a significant difference between these two groups. Those who chose to be on campus had higher Grade Point Average (GPA) at high school, and they preferred the traditional form of exams. Those who chose to follow the lectures digitally favoured multiple choice tests, or home-based ‘open book’ exams. This means that both teaching methods and the choice of exam forms can have a major impact on the ranking of the students.
Does Non-violent Repression Have Stronger Dampening Effects than State Violence? Insight from an Emotion-Based Model of Non-violent Dissent

Abstract The effects of repression on dissent are debated widely. We contribute to the debate by developing an agent-based model grounded in ethnographic interviews with dissidents. Building on new psychology research, the model integrates emotions as a dynamic context of dissent. The model moreover differentiates between four repression types: violence, street blockages, curfews and Facebook cuts. The simulations identify short-term dampening effects of each repression type, with a maximum effect related to non-violent forms of repression. The simulations also show long-term spurring effects, which are most strongly associated with state violence. In addition, the simulations identify nonlinear short-term spurring effects of state violence on early stage dissent. Such effects are not observed for the remaining repressive measures. Contrasting with arguments that violence deters dissent, this suggests that violence may fuel dissent, while non-violent repression might suppress it.
Ractopamine at the Center of Decades-Long Scientific and Legal Disputes: A Lesson on Benefits, Safety Issues, and Conflicts

Ractopamine (RAC) is a synthetic phenethanolamine, β–adrenergic agonist used as a feed additive to develop leanness and increase feed conversion efficiency in different farm animals. While RAC has been authorized as a feed additive for pigs and cattle in a limited number of countries, a great majority of jurisdictions, including the European Union (EU), China, Russia, and Taiwan, have banned its use on safety grounds. RAC has been under long scientific and political discussion as a controversial antibiotic as a feed additive. Here, we will present significant information on RAC regarding its application, detection methods, conflicts, and legal divisions that play a major role in controversial deadlock and why this issue warrants the attention of scientists, agriculturists, environmentalists, and health advocates. In this review, we highlight the potential toxicities of RAC on aquatic animals to emphasize scientific evidence and reports on the potentially harmful effects of RAC on the aquatic environment and human health.
Busy Boards, Entrenched Directors and Corporate Innovation

We provide a comprehensive study of how different corporate governance mechanisms influence corporate innovation. Using panel data regression analysis across a sample of more than 13,600 firm-years for firms based in the United States between 1996–2010, we find that entrenched boards, though commonly associated with lower firm value, actually generate substantial innovation. We find that busy boards hinder innovation unless they also have interlocking relationships. Conversely, interlocked directors enhance innovation, unless they are busy. Directors who are CEOs or Board Chairs at other companies hinder innovation. Interestingly, despite being significant determinants of firm value in other studies, director experience, independence and ownership are not related to innovation. In order to be innovative, firms should appoint directors to leverage their professional relationships and directors must have a long-term perspective.
Grid dispersion analysis of plane square biquadratic serendipity finite elements in transient elastodynamics

The spatial discretisation of a continuum by the FEM introduces dispersion errors to the numerical solution of stress wave propagation. Errors of phase and group velocities and the scatter of wave propagation are induced. When these propagating phenomena are modelled by the FEM, the speed of a single harmonic wave depends on its frequency. Parasitic effects do not exist in an ‘ideal’ unbounded continuum. With higher order finite elements, there are optical modes in the spectrum resulting in spurious oscillations of stress and velocity distributions near the sharp wavefronts. In principle, the dispersion errors and the spurious oscillations cannot be removed from these solutions but can be suppressed to a certain extent. For reliable numerical solutions by the FEM, the dispersion errors should be analysed and determined. The dispersion properties of a plane square biquadratic serendipity finite element are examined and compared with a bilinear one. Dispersion analysis is carried out for the consistent and lumped mass matrices. A dispersive ‘improved’ lumped mass matrix for biquadratic serendipity elements is proposed. The paper closes with the recommendation of a choice of permissible dimensionless wavelengths for bilinear and biquadratic serendipity finite element meshes. Copyright © 2013 John Wiley & Sons, Ltd.
Current Perspectives on Indications for Ileal Pouch-Anal Anastomosis in Older Patients

Abstract The population of older patients with inflammatory bowel disease (IBD) is expected to continue to increase in the coming decades, which necessitates and improved understanding of the critical issues faced by patients in this population. Although restorative proctocolectomy with IPAA remains the surgical procedure of choice for the majority of patients with medically refractory ulcerative colitis (UC) and UC-related dysplasia, the evidence surrounding surgery for older patients UC remains sparse. In particular, comparisons of outcomes among older and younger patients undergoing IPAA and comparisons between older patients undergoing IPAA and those undergoing proctocolectomy with end ileostomy remain an understudied and important issue, as evidence in this area will be used to guide patient-centered surgical choices among older patients who require colectomy for UC. In this narrative review, we review the available literature regarding IPAA for older patients, as well as the pre-, peri-, and postoperative factors that may influence outcomes in this population.
A Comparison of Four Methods for Obtaining Information Functions for Scores From Computerized Adaptive Tests With Normally Distributed Item Difficulties and Discriminations

A simulation study compared four methods of estimating information for maximum-likelihood estimates (MLE) from fixed-length computerized adaptive tests (CAT): those by (1) Lord (1980), (2) Segall, Moreno, and Hetter (1997), (3) Ito, Pommerich, and Segall (2009a), and (4) Ito and Segall (2010), referred to, respectively, as “local,” “quasi-local,” “global-slope,” and “conditional-averaging-on- q ” (CA-theta ). A 900-item bank was constructed using operational three-parameter logistic item parameter estimates [i.e., a (discrimination), b (difficulty), and c (pseudo-guessing)] such that the a and b parameters were as normally distributed as possible. Test length and the number of simulees at each theta point were varied. Generally, information functions for the quasi-local and global-slope methods were very close to those for the reference local method. However, those for the CA-theta method were distinctly different, which might be explained conceptually. These findings were considerably different than those from previous studies that had used a skewed item bank, and illustrated how bank characteristics, including distributions of item difficulties, discriminations, and ability-bank (mis)matches, could influence which methods would yield similar score information functions.
EDF Statistics for Goodness-of-Fit: Part 1

Abstract : The paper deals with EDF statistics, a class of goodness-of-fit statistics. They are based on a comparison of F(x) with the empirical distribution function (F sub n)(x). Recent work has now made it possible to use these statistics very easily when F(x) is continuous and completely specified and also for two very important practical situations - when the distribution tested is normal, or exponential, with parameters to be estimated. Power studies suggest they should be brought into wider use. The report concentrates on a practical guide to the use of EDF statistics; specifically, those usually called D(+), D(-), D, W(2), V, U(2), A.
A Novel Family of Cage-like (CuLi, CuNa, CuK)-phenylsilsesquioxane Complexes with 8-Hydroxyquinoline Ligands: Synthesis, Structure, and Catalytic Activity

The first examples of metallasilsesquioxane complexes, including ligands of the 8-hydroxyquinoline family 1–9, were synthesized, and their structures were established by single crystal X-ray diffraction using synchrotron radiation. Compounds 1–9 tend to form a type of sandwich-like cage of Cu4M2 nuclearity (M = Li, Na, K). Each complex includes two cisoid pentameric silsesquioxane ligands and two 8-hydroxyquinoline ligands. The latter coordinates the copper ions and corresponding alkaline metal ions (via the deprotonated oxygen site). A characteristic (size) of the alkaline metal ion and a variation of characteristics of nitrogen ligands (8-hydroxyquinoline vs. 5-chloro-8-hydroxyquinoline vs. 5,7-dibromo-8-hydroxyquinoline vs. 5,7-diiodo-8-hydroxyquinoline) are highly influential for the formation of the supramolecular structure of the complexes 3a, 5, and 7–9. The Cu6Na2-based compound 2 exhibits high catalytic activity towards the oxidation of (i) hydrocarbons by H2O2 activated with HNO3, and (ii) alcohols by tert-butyl hydroperoxide. Studies of kinetics and their selectivity has led us to conclude that it is the hydroxyl radicals that play a crucial role in this process.
Automatic Detection of Atrial Fibrillation from ECG Signal Using Hybrid Deep Learning Techniques

In cardiac rhythm disorders, atrial fibrillation (AF) is among the most deadly. So, ECG signals play a crucial role in preventing CVD by promptly detecting atrial fibrillation in a patient. Unfortunately, locating trustworthy automatic AF in clinical settings remains difficult. Today, deep learning is a potent tool for complex data analysis since it requires little pre and postprocessing. As a result, several machine learning and deep learning approaches have recently been applied to ECG data to diagnose AF automatically. This study analyses electrocardiogram (ECG) data from the PhysioNet/Computing in Cardiology (CinC) Challenge 2017 to differentiate between atrial fibrillation (AF) and three other rhythms: normal, other, and too noisy for assessment. The ECG data, including AF rhythm, was classified using a novel model based on a combination of traditional machine learning techniques and deep neural networks. To categorize AF rhythms from ECG data, this hybrid model combined a convolutional neural network (Residual Network (ResNet)) with a Bidirectional Long Short Term Memory (BLSTM) network and a Radial Basis Function (RBF) neural network. Both the F1-score and the accuracy of the final hybrid model are relatively high, coming in at 0.80% and 0.85%, respectively.