Miracle-dz/UniFAR-FTUs huggingface dataset:
System Biology Approach to Identify the Hub Genes and Pathways Associated with Human H5N1 Infection

Introduction: H5N1 is a highly pathogenic avian influenza virus that can infect humans and has an estimated fatality rate of 53%. As shown by the current situation of the COVID-19 pandemic, emerging and re-emerging viruses such as H5N1 have the potential to cause another pandemic. Thus, this study outlined the hub genes and pathways associated with H5N1 infection in humans. Methods: The genes associated with H5N1 infection in humans were retrieved from the NCBI Gene database using “H5N1 virus infection” as the keyword. The genes obtained were investigated for protein–protein interaction (PPI) using STRING version 11.5 and studied for functional enrichment analysis using DAVID 2021. Further, the PPI network was visualised and analysed using Cytoscape 3.7. 2, and the hub genes were obtained using the local topological analysis method of the cytoHubba plugin. Results: A total of 39 genes associated with H5N1 infection in humans significantly interacted with each other, forming a PPI network with 38 nodes and 149 edges modulating 74 KEGG pathways, 76 biological processes, 13 cellular components, and 22 molecular functions. Further, the PPI network analysis revealed that 33 nodes interacted, forming 1056 shortest paths at 0.282 network density, along with a 1.947 characteristic path length. The local topological analysis predicted IFNA1, IRF3, CXCL8, CXCL10, IFNB1, and CHUK as the critical hub genes in human H5N1 infection. Conclusion: The hub genes associated with the H5N1 infection and their pathways could serve as diagnostic, prognostic, and therapeutic targets for H5N1 infection among humans.
Image Compression based on Fixed Predictor Multiresolution Thresholding of Linear Polynomial Nearlossless Techniques

Image compression is a serious issue in computer storage and transmission, that simply makes efficient use of redundancy embedded within an image itself; in addition, it may exploit human vision or perception limitations to reduce the imperceivable information Polynomial coding is a modern image compression technique based on modelling concept to remove the spatial redundancy embedded within the image effectively that composed of two parts, the mathematical model and the residual. In this paper, two stages proposed technqies adopted, that starts by utilizing the lossy predictor model along with multiresolution base and thresholding techniques corresponding to first stage. Latter by incorporating the near lossless compression scheme of first stage that corresponding to second stage. The tested results shown are promising in both two stages, that implicilty enhanced the performance of traditional polynomial model in terms of compression ratio , and preresving image quality.
Global Digital Peripheries: The Social Capital Profile of Low‐Adopter Countries

As digital transformations have the potential to reinforce longstanding inequalities and create novel ones within and among societies, it is vital to understand how this process is socially embedded. This article contributes to the study of macro‐level patterns of cross‐country differences in digitalization by providing a global comparative analysis of 76 countries in three different clusters, with a focus on the almost 30 countries with the lowest rates of adoption. Going beyond the “access, use, outcome” perspective of the digital divide approach, this empirical analysis addresses the social embeddedness of digitalization in the framework of the three types of social capital. In contrast to the digitalized and the digitalizing country clusters, the findings on the social capital profile of low‐adopter societies reveal their consistently low status on bridging and linking social capital, as well as their strengths in the trust and ties dimensions of bonding social capital. These results have alarming implications for digital inclusion in low‐adopter societies.
New Augmented Lyapunov‐Krasovskii Functional for Stability Analysis of Systems with Additive Time‐Varying Delays

This paper is concerned with stability analysis for continuous‐time systems with additive time‐varying delays in the Lyapunov‐Krasovskii(L‐K) framework. Firstly, in view of the relationships between the upper bounds of the two time‐varying delays, a new augmented L‐K functional is constructed by using the information of the two upper bounds. Secondly, the free‐matrix‐based integral inequality is used to estimate the derivative of the constructed L‐K functional. Thirdly, a less conservative criterion is derived to assess stability. Finally, a numerical example is presented to demonstrate the effectiveness of the criterion.
Decentralised adaptive control of a class of hidden leader–follower non-linearly parameterised coupled MASs

In this study, decentralised adaptive control is investigated for a class of discrete-time non-linear hidden leader-follower multi-agent systems (MASs). Different from the conventional leader-follower MAS, among all the agents, there exists a hidden leader that knows the desired reference trajectory, while the follower agents know neither the desired reference signal nor which is a leader agent. Each agent is affected from the history information of its own neighbours. The dynamics of each agent is described by the non-linear discrete-time auto-regressive model with unknown parameters. In order to deal with the uncertainties and non-linearity, a projection algorithm is applied to estimate the unknown parameters. Based on the certainty equivalence principle in adaptive control theory, the control for the hidden leader agent is designed by the desired reference signal, and the local control for each follower agent is designed using neighbourhood history information. Under the decentralised adaptive control, rigorous mathematical proofs are provided to show that the hidden leader agent tracks the desired reference signal, all the follower agents follow the hidden leader agent, and the closed-loop system eventually achieves strong synchronisation in the presence of strong couplings. In the end, the simulation results show the validity of this scheme.
Japanese Kanji characters are small-world connected through shared components

We investigate the connectivity within different incre- mental sets of Japanese Kanji characters. Individual characters constitute the vertices in the network, components shared between them provide their edges. We find the resulting networks to have a high clustering coefficient and a low average path length, characterizing them as small worlds. We examine the statistical significance of these findings and the role of the degree distributions. We review the evidence that the small-world topologies of these networks are due to the successive elimination of components in the writing system and discuss the implications of the results for language evolution.
EARLY MANAGEMENT OF SKELETAL CLASS III MALOCCLUSION WITH FACE MASK – A CASE REPORT.

Dr. Abdul Baais Akhoon 1 and Prof. Dr. Mohammad Mushtaq 2 . 1. PG student, Department of Orthodontics and Dentofacial Orthopaedics, Govt. Dental College, Srinagar. 2. Professor and Head, Department of Orthodontics, Govt. Dental College and Hospital, ShereenBagh, Srinagar, University of Kashmir. Manuscript Info Abstract . Manuscript History
Biomarkers of Neonatal Sepsis: Where We Are and Where We Are Going

Neonatal sepsis is a bacterial bloodstream infection leading to severe clinical manifestations frequently associated with death or irreversible long-term deficits. Antibiotics are the drug of choice to treat sepsis, regardless of age. In neonates, the lack of reliable criteria for a definite diagnosis and the supposition that an early antibiotic administration could reduce sepsis development in children at risk have led to a relevant antibiotic overuse for both prevention and therapy. The availability of biomarkers of neonatal sepsis that could alert the physician to an early diagnosis of neonatal sepsis could improve the short and long-term outcomes of true sepsis cases and reduce the indiscriminate and deleterious use of preventive antibiotics. The main aim of this narrative review is to summarize the main results in this regard and to detail the accuracy of currently used biomarkers for the early diagnosis of neonatal sepsis. Literature analysis showed that, despite intense research, the diagnosis of neonatal sepsis and the conduct of antibiotic therapy cannot be at present decided on the basis of a single biomarker. Given the importance of the problem and the need to reduce the abuse of antibiotics, further studies are urgently required. However, instead of looking for new biomarkers, it seems easier and more productive to test combinations of two or more of the presently available biomarkers. Moreover, studies based on omics technologies should be strongly boosted. However, while waiting for new information, the use of the clinical scores prepared by some scientific institutions could be suggested. Based on maternal risk factors and infant clinical indicators, sepsis risk can be calculated, and a significant reduction in antibiotic consumption can be obtained.
Dobrzy rodzice, źli obywatele? Uchylanie się od szczepień ochronnych w badaniach Jennifer A. Reich

good parents, bad citizens? Factors behind Vaccine hesitancy abstract Vaccine hesitancy has recently become a growing challenge for public health in Poland as well as in many other countries in Europe and North America. The paper provides a summary of the main findings concerning the factors behind the phenomenon, as presented in Jennifer A. Reich’s book ‘Calling the Shots. Why Parents Reject Vaccines’, based on her research carried out in the United States. The author demonstrates the multiple ways, in which vaccine hesitancy, particularly prevalent among those with privileged access to education and resources, is linked to broader issues concerning personal choice, bodily integrity, individual responsibility towards community and individual’s relations with the state.
The Evolving Concept of the Multidisciplinary Approach in the Diagnosis and Management of Interstitial Lung Diseases

Background: Interstitial lung diseases (ILDs) are a group of heterogeneous diseases characterized by inflammation and/or fibrosis of the lung interstitium, leading to a wide range of clinical manifestations and outcomes. Over the years, the literature has demonstrated the increased diagnostic accuracy and confidence associated with a multidisciplinary approach (MDA) in assessing diseases involving lung parenchyma. This approach was recently emphasized by the latest guidelines from the American Thoracic Society, European Respiratory Society, Japanese Respiratory Society, and Latin American Thoracic Association for the diagnosis of ILDs. Methods: In this review, we will discuss the role, composition, and timing of multidisciplinary diagnosis (MDD) concerning idiopathic pulmonary fibrosis, connective tissue disease associated with ILDs, hypersensitive pneumonia, and idiopathic pneumonia with autoimmune features, based on the latest recommendations for their diagnosis. Results: The integration of clinical, radiological, histopathological, and, often, serological data is crucial in the early identification and management of ILDs, improving patient outcomes. Based on the recent endorsement of transbronchial cryo-biopsy in idiopathic pulmonary fibrosis guidelines, an MDA helps guide the choice of the sampling technique, obtaining the maximum diagnostic performance, and avoiding the execution of more invasive procedures such as a surgical lung biopsy. A multidisciplinary team should include pulmonologists, radiologists, pathologists, and, often, rheumatologists, being assembled regularly to achieve a consensus diagnosis and to review cases in light of new features. Conclusions: The literature highlighted that an MDA is essential to improve the accuracy and reliability of ILD diagnosis, allowing for the early optimization of therapy and reducing the need for invasive procedures. The multidisciplinary diagnosis of ILDs is an ongoing and dynamic process, often referred to as a “working diagnosis”, involving the progressive integration and re-evaluation of clinical, radiological, and histological features.
Investigation of Free Vibrations of Stepped Nanobeam Embedded In Elastic Foundation

The free vibration of stepped nanobeams embedded in the elastic foundation was investigated using Eringen's nonlocal elasticity theory. It is fixed at the system ends with a simple-simple support. The stepped nanbeam’s equations of motion are obtained by using Hamilton's principle. Multi-time scale, which is the perturbation methods, was used for the analytical solution of the equations. To observe the effects of nano size effect, elastic basis coefficient and step location, natural frequencies of the first three modes of the system were obtained for different non-local parameter values, elastic foundation coefficients, step rates and step positions. In the results, it was seen that the non-local parameter had a negative effect on the natural frequency. The elastic foundation coefficient has been shown to reduce vibration amplitudes.
Koszul A-algebras and free loop space homology

We introduce a notion of Koszul A ∞ -algebra that generalizes Priddy’s notion of a Koszul algebra and we use it to construct small A ∞ algebra models for Hochschild cochains. As an application, this yields new techniques for computing free loop space homology algebras of manifolds that are either formal or coformal (over a ﬁeld or over the integers). We illustrate these techniques in two examples.
An Efficient Adaptive Rescaling Scheme for Computing Moving Interface Problems

In this paper, we present an efﬁcient rescaling scheme for computing the long-time dynamics of expanding interfaces. The idea is to design an adaptive time-space mapping such that in the new time scale, the interfaces evolves logarithmically fast at early growth stage and exponentially fast at later times. The new spatial scale guarantees the conservation of the area/volume enclosed by the interface. Compared with the original rescaling method in [J. Comput. Phys. 225(1) (2007) 554–567], this adaptive scheme dramatically improves the slow evolution at early times when the size of the interface is small. Our results show that the original three-week computation in [J. Comput. Phys. 225(1) (2007) 554–567] can be reproduced in about one day using the adaptive scheme. We then present the largest and most complicated Hele-Shaw simulation up to date.
Karakteristik Tepung Premiks Berbahan Terigu dan Tepung Millet (Panicum miliaceum L.) Kecambah-Fermentasi pada Pembuatan Bolu Kukus

Millet flour produced by germination-fermentation method has been developed as substitute for wheat flour. This study was aimed to find out the characteristics of steamed cake premix flour made from wheat flour and GF millet flour, and to determine the exact ratio between wheat flour and GF millet flour to produce steamed cake with the best sensory characteristics. This research used Complete Randomized Design with a treatment of ratio between wheat flour and millet flour that consisted of 5 levels: 100%:0%, 85%:15%, 70%:30%, 55%:45%, and 40%:60%. The treatment was repeated three times to obtain 15 experimental units. The data obtained were analyzed by analysis of variance, if the treatment had a significant effect, then followed by Duncan Multiple Range Test. The result showed that the ratio between wheat flour and GF millet flour had a significant effect on ash content, fat content, and crude fiber for the premix flour, also had significant effect on swelling power, color intensity (scoring test), softness texture (scoring test), sandy texture (scoring test), texture (hedonic test), and overall acceptance for the steamed cake. The ratio 70:30 of wheat flour and GF millet flour had the best characteristics with moisture content 7.65%, ash content 1.08%, protein content 7.07%, fat content 3.04%, carbohydrate content 81.16%, crude fiber 3.29%, swelling power 153.48%, with sensory characteristics of steamed cake are lighted colors, soft and sandy texture, hedonic for color, aroma, texture, taste, overall acceptance is liked.
Model Predictive Control of a Nonlinear Aeroelastic System Using Volterra Series Representations

The purpose of this study is to investigate the potential effectiveness of using a Volterra-based Model Predictive Control strategy to control a nonlinear aeroelastic system. Model Predictive Control (MPC), also known as Receding Horizon Control (RHC), entails computing optimal control inputs over a finite time horizon, applying a portion of the computed optimal control sequence, and then repeating the process over the next time horizon. The Volterra series provides input-output models of a dynamical system in terms of a series of integral operators of increasing order, where the first-order Volterra operator models the linear dynamics and the higher-order operators model the nonlinear dynamics. In this thesis, Volterra-based Model Predictive Control is applied to simulated linear and nonlinear pitch-plunge aeroelastic systems. A linear MPC controller based on a first-order Volterra model is used to control the linear aeroelastic system, and the results are compared to those obtained using a standard LQR controller and a LQR-based MPC strategy. The controller is implemented for regulator and tracking cases for a free-stream velocity of 6 m/s, a condition for which the open-loop linear system is stable, and a free-stream velocity of 12.5 m/s, which corresponds to an unstable flutter condition. Nonlinear MPC controllers, using second- and third-order Volterra models, are then used to control the nonlinear aeroelastic system for regulator and tracking cases at the stable flight condition. The stability and performance of the linear and nonlinear Volterra-based MPC strategies are discussed, and a detailed analysis of the effect of different parameters such as the optimization horizon, control horizon and control discretization, is provided. The results show that the linear MPC controller is able to successfully track a reference input for the stable condition and stabilizes the system at the unstable flutter condition. It is also shown that the incorporation of the second- and third-order Volterra kernels in the nonlinear MPC controller provides superior performance on the nonlinear aeroelastic system compared to the results obtained using only a linear model.
Effects of Bubble Plumes on Lake Dynamics, Near‐Bottom Turbulence, and Transfer of Dissolved Oxygen at the Sediment‐Water Interface

We quantify the lake dynamics, near‐bottom turbulence, flux of dissolved oxygen (DO) across the sediment‐water interface (SWI) and their interactions during oxygenation in two lakes. Field observations show that the lake dynamics were modified by the bubble plumes, showing enhanced mixing in the near‐field of the plumes. The interaction of the bubble‐induced flow with the internal density structure resulted in downwelling of warm water into the hypolimnion in the far‐field of the plumes. Within the bottom boundary layer (BBL), both lakes show weak oscillating flows primarily induced by seiching. The vertical profile of mean velocity within 0.4 m above the bed follows a logarithmic scaling. One lake shows a larger drag coefficient than those in stationary BBLs, where the classic law‐of‐the‐wall is valid. The injection of oxygen elevated the water column DO and hence, altered the DO flux across the SWI. The gas transfer velocity is driven by turbulence and is correlated with the bottom shear velocity. The thickness of the diffusive boundary layer was found to be consistent with the Batchelor length scale. The dynamics of the surface renewal time follow a log‐normal distribution, and the turbulent integral time scale is comparable to the surface renewal time. The analyses suggest that the effect of bubble plumes on the BBL turbulence is limited and that the canonical scales of turbulence emerge for the time‐average statistics, validating the turbulence scaling of gas transfer velocity in low‐energy lakes.
Antiviral Potential of Specially Selected Bulgarian Propolis Extracts: In Vitro Activity against Structurally Different Viruses

Propolis is a natural mixture of resins, wax, and pollen from plant buds and flowers, enriched with enzymes and bee saliva. It also contains various essential oils, vitamins, mineral salts, trace elements, hormones, and ferments. It has been found that propolis possesses antimicrobial, antiviral, and anti-inflammatory properties. We have studied the antiviral activity of six extracts of Bulgarian propolis collected from six districts of Bulgaria. The study was conducted against structurally different viruses: human coronavirus strain OC-43 (HCoV OC-43) and human respiratory syncytial virus type 2 (HRSV-2) (enveloped RNA viruses), human herpes simplex virus type 1 (HSV-1) (enveloped DNA virus), human rhinovirus type 14 (HRV-14) (non-enveloped RNA virus) and human adenovirus type 5 (HadV-5) (non-enveloped DNA virus). The influence of the extracts on the internal replicative cycle of viruses was determined using the cytopathic effect (CPE) inhibition test. The virucidal activity, its impact on the stage of viral adsorption to the host cell, and its protective effect on healthy cells were evaluated using the final dilution method, making them the focal points of interest. The change in viral infectivity under the action of propolis extracts was compared with untreated controls, and Δlgs were determined. Most propolis samples administered during the viral replicative cycle demonstrated the strongest activity against HCoV OC-43 replication. The influence of propolis extracts on the viability of extracellular virions was expressed to a different degree in the various viruses studied, and the effect was significantly stronger in those with an envelope. Almost all extracts significantly inhibited the adsorption step of the herpes virus and, to a less extent, of the coronavirus to the host cell, and some of them applied before viral infection demonstrated a protective effect on healthy cells. Our results enlarge the knowledge about the action of propolis and could open new perspectives for its application in viral infection treatment.
Effects of DNA Methylation on Gene Expression and Phenotypic Traits in Cattle: A Review

Gene expression in cells is determined by the epigenetic state of chromatin. Therefore, the study of epigenetic changes is very important to understand the regulatory mechanism of genes at the molecular, cellular, tissue and organ levels. DNA methylation is one of the most studied epigenetic modifications, which plays an important role in maintaining genome stability and ensuring normal growth and development. Studies have shown that methylation levels in bovine primordial germ cells, the rearrangement of methylation during embryonic development and abnormal methylation during placental development are all closely related to their reproductive processes. In addition, the application of bovine male sterility and assisted reproductive technology is also related to DNA methylation. This review introduces the principle, development of detection methods and application conditions of DNA methylation, with emphasis on the relationship between DNA methylation dynamics and bovine spermatogenesis, embryonic development, disease resistance and muscle and fat development, in order to provide theoretical basis for the application of DNA methylation in cattle breeding in the future.
Derived representation type and cleaving functors

ABSTRACT We introduce the notation of weakly derived tameness, and establish the equivalence of derived tameness and weakly derived tameness for algebras of finite global dimension. Moreover, we observe the relation between derived representation type and cleaving functors, and obtain a method to judge an algebra to be derived wild. As an application, we determine the derived representation type of self-injective Nakayama algebras.