Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploiting electronic health records for research on atrial fibrillation : risk factors, subtypes, and outcomes

BACKGROUND: Electronic health records (EHRs), collected on large populations in routine clinical care, may hold novel insights into the heart rhythm disorder atrial fibrillation (AF). AIM: To exploit EHRs to investigate, validate and extend evidence for AF risk factors, subtypes, and outcomes. METHODS: The CALIBER dataset (1997–2010) linking primary care, secondary care, and mortality records for a representative subset of the UK population was used (i) to model associations between cardiovascular disease (CVD) risk factors and incident AF, including AF with (AF+) and AF without (AF–) intercurrent CVD, (ii) to create EHR definitions for eight AF subtypes (structural, focal, polygenic, postoperative, valvular, monogenic, respiratory and AF in athletes) and (iii) to investigate stroke outcomes by CHA2DS2-VASc, sex, and warfarin use. RESULTS: Among 1,949,052 individuals, 50,097 developed incident AF: 12,652 (25.3%) with AF+ and 37,445 (74.7%) with AF–. Smoking (HR [95%CI] for AF+ vs. AF–: 1.66 [1.56,1.77] vs. 1.21 [1.16,1.25]), hypertension (2.19 [2.11,2.27] vs. 1.65 [1.62,1.69]), and diabetes (2.03 [1.94,2.12] vs. 1.45 [1.41,1.49]) showed consistent direct associations with AF+ and AF–, while heavy drinking (1.17 [0.81,1.67] vs. 1.99 [1.68,2.34]) and total cholesterol levels (0.99 [0.96,1.02] vs. 0.85 [0.84,0.87]) showed inconsistent associations with AF+ and AF–. EHR definitions for AF subtypes were created by combining 2813 diagnosis, medication, and procedure codes. There were 12,751 individuals with AF and valvular heart disease. Prosthetic replacements, mitral stenosis and aortic stenosis showed higher HR [95%CI] for stroke, thromboembolism and mortality (1.13 [1.02,1.24], 1.20 [1.05,1.36], and 1.27 [1.19,1.37] respectively). The net-clinical benefit (NCB [95%CI] per 100 person-years) of warfarin was shown from CHA2DS2-VASc≥2 in men (0.5 [0.1,0.9]) and CHA2DS2-VASc≥3 in women (1.5 [1.1,1.9]). CONCLUSION: AF is a heterogeneous condition associated with diverse disease mechanisms. EHRs can help refine understanding of risk factors, subtypes, and outcomes with relevance for clinical practice.
Effect of hydrogenation on thermal conductivity of 2D Gallium Nitride

The indirect property of two-dimensional GaN bandgap hinders its application in optical field. Hydrogenation can convert the bandgap of GaN monolayer from an indirect to direct one and also tune the bandgap size. The thermal transport, an important property in the application of two-dimensional material, is also influenced by hydrogenation. By performing first-principle calculation and solving phonon Boltzmann equation, we investigate the effect of hydrogenation on thermal conductivity of GaN monolayer. The results show that hydrogenation will slightly increase the thermal conductivity of GaN monolayer from 70.62Wm -1 K -1 to 76.23 Wm -1 K -1 at 300K. The little effect of hydrogenation on thermal conductivity is mainly dominated by two competing factors: (1) the reduction of ZA mode lifetime due to the breaking of reflection symmetry after hydrogenation, and (2) the increased contribution from TA and LA modes due to the reduction of anharmonic scattering caused by the enlarged phonon bandgap after hydrogenation. The results are compared with other two-dimensional materials with hexagonal monolayer structures.
Aggregately Diversiﬁed Bundle Recommendation via Popularity Debiasing and Conﬁguration-aware Reranking

How can we expose diverse items across all users while satisfying their needs in bundle recommendations? Diversiﬁed bundle recommendation is a crucial task since it leads to great beneﬁts for both sellers and users. However, there have been no studies on aggregate diversity in bundle recommendation, while they have been intensively studied in item recommendation. Moreover, existing methods of aggregately diver-siﬁed item recommendation are not fully suitable for bundle recommendation. In this paper, we propose PopCon (Popularity Debiasing and Conﬁguration-aware Reranking), an accurate method for aggregately di-versiﬁed bundle recommendation. PopCon mitigates the popularity bias of a recommendation model by a popularity-based negative sampling in training process, and maximizes accuracy and aggregate diversity by a conﬁguration-aware reranking algorithm. We show that PopCon provides state-of-the-art performance on real-world datasets, achieving up to 60 . 5% higher Entropy@5 and 3 . 92 × higher Coverage@5 with comparable accuracies compared to the best competitor.
Cyber Security Testbed: Keyloggers and Data Visualization on Keyloggers - A Case Study

A Cyber Security Testbed (CST) is used to simulate cyber-attacks, test and evaluate existing and new strategies. It is a safe space to fix vulnerabilities and enhance security. Keyloggers are malicious tools that record keystrokes. Proposed work implemented a case study on the cybersecurity testbeds available, their significance and aims to describe the essential features of an effective cybersecurity testbed. And also contracts with a study on keyloggers, a simulation and analysis of its working. Further entails a data visualization report on two distinct keylogger datasets to gain a meaningful understanding of keyloggers.
International Symposium on Managing Soils for Food Security and Climate Change Adaptation and Mitigation

Synthetic nitrogen (N) fertilizers differ markedly from organic N fertilizer sources in relative isotopic composition at natural abundance levels (δ15N). The objective of this paper is to provide an overview of the applications of δ15N techniques to study the dynamics of synthetic fertilizers, animal excreta and composts in the soil-plant-atmosphere continuum. However, isotopic fractionation processes often complicate the interpretation of results. These fractionation processes and the factors affecting the δ15N signatures of organic N fertilizers are reviewed. Published data from short-, mediumand long-term experiments with annual crop rotations and in pastures subject to organic N inputs are also examined and analyzed with respect to changes in delta nitrogen-15 (δ15N) signatures of the soil, the crop or pasture, the soil biota and leachates. The use of δ15N to differentiate organic and conventional plant products is briefly covered. There are few data on the dynamics of N during the storage of animal excreta or the composting of agricultural wastes as shown by δ15N values in the organic, inorganic or gaseous N phases. The major N loss process is ammonia (NH3) volatilization. Reviewed data show significant relationships between bulk δ15N signatures of stored manure and cumulative NH3 loss or bulk δ15N of livestock manure composts and N concentration. These significant relationships suggest that δ15N may have wider applications in estimating the efficiency of N conservation during storage or composting. In addition, the combined use of bulk δ15N and delta oxygen-18 (δ18O) signatures of nitrous oxide (N2O) evolved during storage and composting, together with the isotopomer-derived site preference of N2O, are emerging technologies for identifying N2O production pathways. δ15N in combination with appropriate statistical analysis is a promising diagnostic tool for differentiating organic and conventional plant products.
Feasibility-Aware Plan Adaptation in Humanoid Gait Generation

Most available schemes used for humanoid walking rely on the separation into a planning phase, typically offline, and a Model Predictive Controller (MPC). Moreover, in order for the MPC to work in real time, simplifying assumptions are made both on the template model and on the constraints so that the underlying optimization problem is a Quadratic Programming (QP). The planner is unaware of the underlying humanoid dynamics and of any disturbance acting on the robot. We present an online Feasibility-Aware Plan Adaptation (FAPA) module which can locally adapt footsteps (positions, timings and orientation) in such a way that it guarantees feasibility of the subsequent Intrinsically Stable MPC (IS-MPC) stage. We present two versions of the proposed scheme: one with a fixed regions assignment for placing the footstep and another one where the regions are selected automatically through mixed-integer programming. Simulation results show the effectiveness of the FAPA scheme.
Convolutional Neural Networks for Nail Disease Detection: A Promising Approach in Dermatology

The aim of this study is to use Deep Learning (DL) techniques to classify and detect human nail diseases. Early and reliable detection is crucial in aiding timely interventions and suitable treatment for nail diseases and their profound impact on a person's well-being. Using a diverse dataset of nail images, a CNN model was developed and trained to achieve the study's objectives. For the model to be able to accurately detect and classify different diseases, the dataset was carefully collected to include various types of nail diseases. In order to improve the model's performance and robustness, the nail images were preprocessed, and data augmentation techniques were applied. The model's assessment encompassed 8 distinct nail diseases, resulting in an impressive accuracy rate of 98.44%. Additional evaluation metrics such as precision, recall, and F1-score were also computed, yielding values of 99.22%, 98.44%, and 99.02% respectively. The achieved outcomes were compared with state-of-the-art (SOTA) techniques, affirming the superiority of the proposed model. This study emphasizes the potential benefits of DL techniques in enhancing healthcare practices, enhancing dermatological diagnostics, and improving the overall well-being of patients suffering from nail diseases.
Towards Data-Driven Material Removal Rate Estimation in Bonnet Polishing

Ultra-precision polishing is a complex process that involves polishing surfaces with nanometre-level accuracy. Even though much of the process is performed using computer numerically controlled (CNC) machines, fully autonomous manufacturing of such fine parts is currently not feasible. The complexity of the process, lack of perfect determinism, surface inaccessibility during the polishing process, and the need for extensive expert knowledge all present significant challenges in ultra-precision manufacturing. In this work, we present a system design for monitoring parameters in the ultra-precision bonnet polishing process, such as the chemical properties of the polishing slurry or tool forces during the process. We also share some initial findings and challenges encountered during the validation stage of the system, which require further consideration. Additionally, we outline our plan for implementing machine learning in material removal rate estimation for bonnet polishing.
Genomic and Functional Evaluation of Two Lacticaseibacillus paracasei and Two Lactiplantibacillus plantarum Strains, Isolated from a Rearing Tank of Rotifers (Brachionus plicatilis), as Probiotics for Aquaculture

Aquaculture plays a crucial role in meeting the increasing global demand for food and protein sources. However, its expansion is followed by increasing challenges, such as infectious disease outbreaks and antibiotic misuse. The present study focuses on the genetic and functional analyses of two Lacticaseibacillus paracasei (BF3 and RT4) and two Lactiplantibacillus plantarum (BF12 and WT12) strains isolated from a rotifer cultivation tank used for turbot larviculture. Whole-genome sequencing (WGS) and bioinformatics analyses confirmed their probiotic potential, the absence of transferable antibiotic resistance genes, and the absence of virulence and pathogenicity factors. Bacteriocin mining identified a gene cluster encoding six plantaricins, suggesting their role in the antimicrobial activity exerted by these strains. In vitro cell-free protein synthesis (IV-CFPS) analyses was used to evaluate the expression of the plantaricin genes. The in vitro-synthesized class IIb (two-peptide bacteriocins) plantaricin E/F (PlnE/F) exerted antimicrobial activity against three indicator microorganisms, including the well-known ichthyopathogen Lactococcus garvieae. Furthermore, MALDI-TOF MS on colonies detected the presence of a major peptide that matches the dimeric form of plantaricins E (PlnE) and F (PlnF). This study emphasizes the importance of genome sequencing and bioinformatic analysis for evaluating aquaculture probiotic candidates. Moreover, it provides valuable insights into their genetic features and antimicrobial mechanisms, paving the way for their application as probiotics in larviculture, which is a major bottleneck in aquaculture.
XF-OPT/META: A Hyperparameter Optimization Framework Applied to the H -SPPBO Metaheuristic for the Dynamic TSP

This paper has two objectives. Firstly, to introduce a new framework XF -OPTIMETA for testing and comparing Hyperparameter Optimization (HPO) methods. The framework supports model-free methods, e.g., Random Search (RS), as well as model-based methods, such as Bayesian Optimization (BO), with various surrogate models. Due to the generalized and modular structure of the XF-OPTIMETA framework, it can be easily extended to other optimization methods for dif-ferent optimization problems. The second objective is to empir-ically compare the performance of various HPO methods for population-based metaheuristics. For that the XF -OPTIMETA framework is used to apply HPO methods to the Hierarchical Simple Probabilistic Population-Based Optimization (H-SPPBO) metaheuristic for the Dynamic Traveling Salesperson Problem (DTSP) and to calculate high-performing parameter values for H-SPPBO. Promising results are obtained using the parameter values found by BO. In particular, a parameter set obtained with Gradient-Boosted Regression Trees (GBRT) outperforms a reference parameter set for H-SPPBO from an existing study.
Signal Space Diversity Based Non-Orthogonal Multiple Access System Employing $M$-Ary PSK

The power domain non-orthogonal multiple access (PD-NOMA) performs reasonably well under perfect successive interference cancellation (SIC) conditions. However, under imperfect SIC, the average sum rate (ASR) and outage performance of PD-NOMA diminish drastically. This work introduces a new signal space diversity (SSD) based PD-NOMA system to mitigate this sudden decrease in performance. In the proposed system, users' information will be multiplexed in the in-phase and quadrature parts of the rotated constellation points of the $M$-ary phase-shift keying (PSK) modulation symbol. The proposed system is capable of circumventing the necessity of SICs, leading to no power allocation constraints and reducing the complexity and delay at the receiver. The ASR and outage probability (OP) analytical expressions are evaluated under the Nakagami-m fading channel. It is noticed from the analysis that the proposed system is superior to the PD-NOMA system under imperfect SIC and exhibits comparable performance with that under perfect SIC. Furthermore, the analytical expressions for symbol error rate (SER) and average SER (ASER) are determined for $M$-ary PSK modulation scheme, and the optimal angle that minimizes the SER is determined for any value of $M$.
Fast and High-Robustness Adaptive Digital Back-Propagation for Fiber Nonlinearity Compensation

RMSProp-based digital back-propagation is proposed for blind nonlinearity compensation. Compared with conventional method, 69.8% reduction in complexity and at least 46.1% improvement in robustness are demonstrated in a simulation of 2000-km 69-GBd DP-16QAM transmission.
Cost Optimizing Cloud based Docker Application Deployment with Cloudfront and Global Accelerator in AWS Cloud

Achieving low latency in application deployment is essential in today's digital environment for guaranteeing the best user experience. This research study examines Elastic Beanstalk, EC2, CI/CD, and Docker & Kubernetes, four popular AWS deployment techniques. This thorough comparison provides organizations and developers with useful information that will help them make wise choices when deploying apps on AWS. In order to guarantee smooth user experiences in developing digital ecosystems, understanding these strategies is essential. The research not only delves into the technical nuances of each method but also offers practical insights, empowering businesses to optimize their application deployments and deliver unparalleled user satisfaction in the rapidly evolving digital landscape. The goal of the study is to determine the most efficient deployment technique for multiple applications that must have minimal latency.
Parameter Tuning of Coronavirus Herd Immunity Optimizer for Detection of Communities in Social Networks

Community detection is an NP-Hard problem that concerns itself with partitioning a network into groups such that nodes within a partition enjoy denser network connections compared to nodes in different partitions. The capacity to locate and examine these groups can offer invaluable assistance in comprehending and illustrating the framework of networks. Since the community detection problem is inherently complex, metaheuristic optimization algorithms are extensively employed to address this problem. A recently proposed metaheuristic population-based algorithm, Coronavirus Herd Immunity Optimizer (CHIO), draws inspiration from the COVID-19 herd immunity treatment strategy. We adapt the CHIO algorithm for the problem of community detection in social networks. In this proposal, the Network Modularity value is computed to assess the quality of a community structure. Tuning the parameters of a metaheuristic algorithm to a given problem at hand is essential for good algorithm performance and is the focus of our proposal. The parameter tuning method developed by Genichi Taguchi is utilized to fine-tune the parameters of the CHIO algorithm in the context of community detection. Experiments on real-world benchmark networks were conducted. The adapted CHIO algorithm is run with parameter values obtained after tuning. It is noticed that the proposed approach is successful in detecting community structures with a high modularity value.
Changing Architecture and Construction Practices in the Gilgit Baltistan Region, Pakistan: Case of Hotel and Tourism Industry

The tourism and hotel industry is rapidly causing the alteration of the architectural and construction practices in the Gilgit-Baltistan region as more and more people have become associated with the industry including both the locals as well as outsiders. This paper presents an overview of the changing scenario of architecture and construction practices in the Gilgit-Baltistan region and the preferences of the local population. It aims to do so by highlighting the architectural and construction practices of the past and present specifically in the hotel and tourism industry of the region, outlining the type of construction and their techniques while also inquiring the locals regarding their preferences pertaining to architecture and construction. The secondary data giving an overview of the region, and the architectural and construction practices; is gathered from the relevant newspaper articles, reports, websites and, journal articles while the primary data is gathered from the site visits to the region along with questionnaire surveys conducted from the local population. An assessment of hotels developed during different timelines presenting case studies employing either vernacular or modern or even a combination of both techniques is carried out in terms of their use of materials, architectural features, and structure/construction typology. Conclusively, the research tries to put forth the trends in architecture and construction practices especially in the case of hotel buildings in the region as while an increase in tourism has caused a boost in the construction of hotels in the region, it has raised many other concerns such as disconnect from local culture, use of alienated building materials making the buildings poor in terms of thermal comfort, dying cultural heritage.
In Vitro and In Silico Studies of Bis-furyl-pyrrolo[3,4-b]pyridin-5-ones on Dengue Virus

A series of six bis-furyl-pyrrolo[3,4-b]pyridin-5-ones synthesized via an Ugi-Zhu reaction coupled to a cascade process [aza Diels-Alder cycloaddition/N-acylation/aromatization] were evaluated in vitro against Dengue virus serotype 4 infection, and the Dengue virus replicon system encoding a Renilla luciferase gen reporter. Also, in silico studies on the non-structural protein 3 (NS3), a flavivirus protease comprising an attractive target for development of therapeutic antivirals bound to non-structural protein 2B (NS3-NS2B) were performed. The in vitro results showed that compounds 1a and 1b reduced the expression of Renilla luciferase in 44.2 and 31.6%, respectively. Additionally, the same compounds decreased viral load, thus revealing their potential activity against Dengue virus serotype 4. From in silico simulations, it was developed a NS3-NS2B model, which was used as a target for the studied molecules. Computational results agree with experimental data, showing that 1a is the best ligand. Finally, a pharmacophoric model was computed for NS3-NS2B, which shows that the ligands need two hydrophobic and one hydrophilic fragment. Such results suggest that two out of the six synthesized bis-furyl-pyrrolo[3,4-b]pyridin-5-ones derivatives presents potential antiviral activity against Dengue virus in vitro. Resumen. Una serie de seis bis-furil-pirrolo[3,4-b]piridin-5-onas sintetizadas vía una reacción Ugi-Zhu acoplada a un proceso en cascada [cicloadición aza Diels-Alder/N-acilación/aromatización] fueron evaluadas in vitro contra infección por el serotipo 4 del virus del dengue y el sistema de replicón del virus del Dengue que codifica un gen reportero de la luciferasa de la Renilla. Además, se realizaron estudios in silico sobre la proteína no estructural 3 (NS3), una proteasa de flavivirus que comprende un blanco atractivo para el desarrollo de antivirales terapéuticos unidos a la proteína no estructural 2B (NS3-NS2B). Los estudios in vitro revelaron que los compuestos 1a y 1b reducen la expresión de Renilla luciferasa en un 44.2 y 31.6%, respectivamente. Adicionalmente, estos compuestos redujeron la carga viral, revelando así su actividad potencial contra el virus del Dengue serotipo 4. Derivado de las simulaciones in silico, se obtuvo un modelo homólogo para NS3-NS2B, el cual fue considerado como blanco de las moléculas estudiadas. Los resultados computacionales correlacionan con los experimentales, mostrando que 1a es el mejor ligando. Finalmente, se generó un modelo farmacofórico para NS3-NS2B, el cual muestra que los ligandos necesitan dos fragmentos hidrofóbicos y uno hidrofílico. Estos resultados demuestran que dos de los seis compuestos que se estudiaron presentan actividad antiviral in vitro.
Implementing OpenFlow, Exploring the Present and Future Software-Defined Networks Ecosystem

Software-defined networking (SDN) has become a paradigm change in network architecture due to its enhanced flexibility, agility, and control over network resources. The OpenFlow protocol, a core component of SDN that enables centralized and programmable network administration, is at the heart of the progress. The existing and future state of software-defined networks using OpenFlow is thoroughly examined. It examines the historical development of SDN, clarifies the core ideas behind OpenFlow, and evaluates the influence of all three on modern networking. In-depth examinations of current developments, market leaders, and enduring difficulties are presented in this research study. It also takes a forward-looking look at the coming years, seeing new trends, chances, and potential challenges. The article also looks into the various ways that SDN is being used in different industries and highlights the numerous benefits that these applications offer. It provides helpful insights into securing SDN and OpenFlow environments while addressing a crucial security issue. With its insightful analysis of the constantly changing world of software-defined networks and OpenFlow technology, it is an essential tool for network specialists, researchers, and decision-makers.