Miracle-dz/UniFAR-FTUs huggingface dataset:
Digital Identity, Privacy Security and their Legal Safeguards in the Metaverse

The Metaverse is the digitization of the real world, supported by big data, AI, 5G, cloud computing, blockchain, encryption algorithm, perception technology, digital twin, virtual engine and other technologies that interact with human behaviour and thoughts in avatars through digital identity. Cracking the trust problem brought by the avatar depends on the privacy security and authentication technology for individuals using digital identities to enter the Metaverse. To accomplish personal domination of the avatar, metaverse users need privacy data feeding and emotion projection. They must be equipped with proprietary algorithms to process and analyze the complex data generated in adaptive interactions, which challenges the privacy security of user data in the Metaverse. Distinguishing the significance of different identifiers in personal identity generation while imposing different behavioural regulatory requirements on data processing levels may better balance the relationship between personal privacy security and digital identity protection and data utilization in the Metaverse. In response to digital identity issues, there is an objective need to establish a unified digital identity authentication system to gain the general trust of society. Further, the remedies for a right to personality can be applied to the scenario of unlawful infringement of digital identity and privacy security.
Navigating Cultural Diversity in the Selection of Cardiovascular Device Treatments: A Comprehensive Review

In cardiology, patients' cultural beliefs, linguistic differences, lack of knowledge, and socioeconomic status can create barriers to choosing device treatment. To address this issue, we conducted a thorough literature review using online databases such as PubMed, Google Scholar, and Texas Tech University Health Sciences Center's research portal. Our review found that cultural, religious, and linguistic barriers can contribute to patients' apprehension and reservations about device placement. These barriers can also impact patients' adherence to treatment and clinical outcomes. Patients from lower socioeconomic backgrounds may have difficulty accessing and affording device-based treatments. Additionally, fear and inadequate understanding of surgical procedures can deter patients from accepting device treatment in cardiology. To overcome these cultural barriers, healthcare providers must raise awareness about the benefits of device treatment and provide better training to overcome these challenges. It is crucial to address the unique needs of patients from different cultural backgrounds and socioeconomic statuses to ensure they receive the care they need.
Pursuing Educational Partnerships in Diasporic Contexts: Teachers Responding to Pacific Voice in Their Work

In Aotearoa New Zealand, teachers have signaled that they would like to further their development as classroom practitioners, as a way of improving their capabilities as professionals. They want to foster strengths-based authentic partnerships between themselves and their diasporic migrant communities. This article attends to Pacific education, the education in Aotearoa New Zealand of students with migratory links to one or more Pacific Island Nations through a strength-based lens. We report on a Professional Learning Development (PLD) research endeavor, Learning From Each Other, that focused on supporting partnerships between Pacific communities and teachers. We provide a window on the sense making of teachers as they listen to, and are challenged by, diasporic Pacific community voice. Particular emphasis is placed on how teachers explore and transform their approach to partnership by negotiating with habitual practice. The examples given, selected for their apparent ordinariness, relate to new understandings of space and time. The study provides lessons applicable to other situations where access to quality education is problematic for diasporic, migrant communities and where teachers need support for the re-thinking that is required for enhanced partnership arrangements of benefit to all.
Variant Measures and Visualized Statistical Distributions

Using measure model and statistical approches to simulate quantum interaction on binary level systems,multiple interactive conditions are simulated via double path interference measures.From quantum interaction,Einstein,Mach-Zehnder,Stern-Gerlach and CHSH measuring parameters are investigated.Using multiple variable logic functions and variant principle,N bit vectors of 0-1 input/output pairs form variant quaternion to establish variant double path simulation model.Using probability,symmetry/anti-symmetry,sychronous/asychronous conditions,simulation system generates two groups of eight histograms to express their statistical distributions in relevant conditions.
Preclinical Models and Promising Pharmacotherapeutic Strategies in Liver Fibrosis: An Update

Liver fibrosis represents one of the greatest challenges in medicine. The fact that it develops with the progression of numerous diseases with high prevalence (NAFLD, viral hepatitis, etc.) makes liver fibrosis an even greater global health problem. Accordingly, it has received much attention from numerous researchers who have developed various in vitro and in vivo models to better understand the mechanisms underlying fibrosis development. All these efforts led to the discovery of numerous agents with antifibrotic properties, with hepatic stellate cells and the extracellular matrix at the center of these pharmacotherapeutic strategies. This review focuses on the current data on numerous in vivo and in vitro models of liver fibrosis and on various pharmacotherapeutic targets in the treatment of liver fibrosis.
Deep learning modified neural networks with chicken swarm optimization-based lungs disease detection and severity classification

Abstract. Many people around the world are affected by pulmonary disease as well as asthma, pneumonia, lung cancer, and tuberculosis. All of these conditions have one thing in common: airway obstruction. Lung illnesses are a worldwide issue in which chronic obstructive pulmonary disease, pneumonia, asthma, tuberculosis, and fibrosis are few of the most common. An accurate diagnosis of a lung problem is essential, and it has been pursued by many researchers using image processing and machine learning models. Multiple deep learning methods are used to predict lung disease; these include convolutional neural networks, vanilla neural networks, visual geometry group-based neural networks, and the capsule network. Medical data are scarce, so diagnosing pulmonary diseases using chest x-ray pictures from datasets with less than 1000 samples is considered to address the problem. Three deep learning multiple neural networks (DLMNNs) were generated using the chicken swarm optimization (CSO) approach, for which transfer learning was applied to evaluate the performance of each. First, we created an algorithm for segmenting CXR images, and then we compared it with other classification systems. Our results were compared with those of other methods using publicly available data from the Shenzhen and Montgomery lung datasets. However, our technique has a lower number of trainable parameters compared with the best-performing models trained on the Montgomery dataset. The DLMNN-CSO virtually matched the best performance on the Shenzhen dataset, although it was computationally less expensive than the other models. DLMNN-CSO’s validation loss was 0.4, whereas the validation loss for CNN, VDSNet, VGG, and DBN was 0.9, 0.8, 0.6, and 0.5, respectively.
Nonlinear stabilizing control of a rotary double inverted pendulum: a modified backstepping approach

Modified backstepping control is proposed for an under-actuated rotary double inverted pendulum. The system has actuated rotary base joint with which two unactuated links are attached. The proposed control design is a three step process for de-coupled system model. In the first stage, a backstepping controller is designed for each of the active and passive joints. In the second stage, compensation is introduced in the respective control efforts to cater for uncertain terms based on Lyapunov function for each joint. Finally, the controllers obtained in the two stages are combined to form a total control law. The performance of the proposed control scheme is evaluated by convergence analysis and simulations.
Defining the Patient with Lumbar Discogenic Pain: Real-World Implications for Diagnosis and Effective Clinical Management

There is an enormous body of literature that has identified the intervertebral disc as a potent pain generator. However, with regard to lumbar degenerative disc disease, the specific diagnostic criteria lack clarity and fail to capture the primary components which include axial midline low back pain with or without non-radicular/non-sciatic referred leg pain in a sclerotomal distribution. In fact, there is no specific ICD-10-CM diagnostic code to classify and define discogenic pain as a unique source of pain distinct from other recognized sources of chronic low back pain including facetogenic, neurocompressive including herniation and/or stenosis, sacroiliac, vertebrogenic, and psychogenic. All of these other sources have well-defined ICD-10-CM codes. Corresponding codes for discogenic pain remain absent from the diagnostic coding vernacular. The International Society for the Advancement of Spine Surgery (ISASS) has proposed a modernization of ICD-10-CM codes to specifically define pain associated with lumbar and lumbosacral degenerative disc disease. The proposed codes would also allow the pain to be characterized by location: lumbar region only, leg only, or both. Successful implementation of these codes would benefit both physicians and payers in distinguishing, tracking, and improving algorithms and treatments for discogenic pain associated with intervertebral disc degeneration.
Platinum-Based Nanoformulations for Glioblastoma Treatment: The Resurgence of Platinum Drugs?

Current therapies for treating Glioblastoma (GB), and brain tumours in general, are inefficient and represent numerous challenges. In addition to surgical resection, chemotherapy and radiotherapy are presently used as standards of care. However, treated patients still face a dismal prognosis with a median survival below 15–18 months. Temozolomide (TMZ) is the main chemotherapeutic agent administered; however, intrinsic or acquired resistance to TMZ contributes to the limited efficacy of this drug. To circumvent the current drawbacks in GB treatment, a large number of classical and non-classical platinum complexes have been prepared and tested for anticancer activity, especially platinum (IV)-based prodrugs. Platinum complexes, used as alkylating agents in the anticancer chemotherapy of some malignancies, are though often associated with severe systemic toxicity (i.e., neurotoxicity), especially after long-term treatments. The objective of the current developments is to produce novel nanoformulations with improved lipophilicity and passive diffusion, promoting intracellular accumulation, while reducing toxicity and optimizing the concomitant treatment of chemo-/radiotherapy. Moreover, the blood–brain barrier (BBB) prevents the access of the drugs to the brain and accumulation in tumour cells, so it represents a key challenge for GB management. The development of novel nanomedicines with the ability to (i) encapsulate Pt-based drugs and pro-drugs, (ii) cross the BBB, and (iii) specifically target cancer cells represents a promising approach to increase the therapeutic effect of the anticancer drugs and reduce undesired side effects. In this review, a critical discussion is presented concerning different families of nanoparticles able to encapsulate platinum anticancer drugs and their application for GB treatment, emphasizing their potential for increasing the effectiveness of platinum-based drugs.
Chemical imaging of contaminated recycled paper and board: Towards identification of the causality of food contamination

Contamination of recycled paper and board food packaging by mineral oil hydrocarbons caused several crises in the past years. Although the migration from paper and board to foodstuffs has been proved many times, the contamination mechanisms and causalities remain undetermined and face unresolved issues. This study takes part in the collaborative project FoodSafeBioPack, which aims at evaluating the migration of potentially carcinogenic polyaromatic molecules from recycled paper and board packaging to food. New chemical imaging methods are used to follow this contamination at the microscopic scale (fibers and fibrous network). The first images acquired of polyaromatic molecules distribution on fibers were used to develop a methodology that will help to follow their migration. The influence of using different solvents and molecules on the initial chemical potential is discussed. The description of the paper structure and initial conditions of transfer will support the development of a microscopic mass transfer model.
Unconditionally stable operator splitting algorithms for the incompressible magnetohydrodynamics system discretized by a stabilized finite element formulation based on projections

In this article, we propose different splitting procedures for the transient incompressible magnetohydrodynamics (MHD) system that are unconditionally stable. We consider two levels of splitting, on one side we perform the segregation of the fluid pressure and magnetic pseudo‐pressure from the vectorial fields computation. At the second level, the fluid velocity and induction fields are also decoupled. This way, we transform a fully coupled indefinite multi‐physics system into a set of smaller definite ones, clearly reducing the CPU cost. With regard to the finite element approximation, we stick to an unconditionally convergent stabilized finite element formulation because it introduces convection stabilization, allows to circumvent inf‐sup conditions (clearly simplifying implementation issues), and is able to capture non‐smooth solutions of the magnetic subproblem. However, residual‐based finite element formulations are not suitable for segregation, because they lose the skew‐symmetry of the off‐diagonal blocks. Therefore, in this work, we have proposed a novel term‐by‐term stabilization of the MHD system based on projections that is still unconditionally convergent. Copyright © 2012 John Wiley & Sons, Ltd.
Plasmon-mediated circularly polarized luminescence of GaAs in a scanning tunneling microscope

The electroluminescence from p-type GaAs(110) in a scanning tunneling microscope has been investigated at 6 K. Unexpectedly, high degrees of circular polarization have often been observed with ferromagnetic Ni tips and also with paramagnetic W and Ag tips. The data are interpreted in terms of two distinct excitation mechanisms. Electron injection generates intense luminescence with low polarization. Plasmon-mediated generation of electron-hole pairs leads to less intense emission, which, however, is highly polarized for many tips.
How well do forecast models represent observed long‐lived Rossby wave packets during southern hemisphere summer?

Rossby wave packets (RWPs), are atmospheric perturbations linked to the occurrence of extreme weather events such as heatwaves, extratropical cyclone development and other equally destructive phenomena. Under certain circumstances, these packets can last from several days to 2–3 weeks in the atmosphere. Therefore, forecast models should be able to correctly predict their formation and development to enhance extreme weather events prediction from 10 to 30 days in advance. In this study, we assess whether the NCEP and IAP‐CAS sub‐seasonal forecast models can predict the evolution of observed RWPs that last more than 8 days (long‐lived RWPs or LLRWPs) during southern hemisphere summer. Results show that the NCEP (IAP‐CAS) model forecasts LLRWPs that appear eastward (westward) from the observed LLRWPs. Both models forecasted LLRWPs that rapidly lose energy after the 6th–7th lead day of simulation, which could limit LLRWPs prediction to the synoptic time scale. Additionally, both models better forecast LLRWPs when the packets manifest in the eastern Pacific. Southern Annular mode (SAM) and El Niño Southern‐Oscillation (ENSO) do not seem to exert a large influence in the representation of LLRWPs. Nevertheless, during the best LLRWPs forecasts, the observed circulation anomalies signal the manifestation of negative SAM events. In contrast, both forecast models struggle at forecasting LLRWPs when a blocking situation develops to the South of Australia. Lastly, an inactive Madden Julian Oscillation (MJO) seems to favor the development of accurate LLRWPs forecasts, whereas during phases 3, 5 in the NCEP model and 3, 8 for IAP‐CAS, the models struggle at forecasting LLRWPs.
Effects of Piper betle Extracts against Biofilm Formation by Methicillin-Resistant Staphylococcus pseudintermedius Isolated from Dogs

Emergence of methicillin-resistant Staphylococcus pseudintermedius (MRSP) isolated from dogs with cutaneous and wound infections has significantly impacted veterinary medicine. This study aimed to isolate S. pseudintermedius from canine pyoderma and investigate the effects of ethanolic extracts of Piper betle (PB), P. sarmentosum (PS), and P. nigrum (PN) on the bacterial growth and biofilm formation of S. pseudintermedius and MRSP. Of the isolated 152 isolates, 53 were identified as S. pseudintermedius using polymerase chain reaction, and 10 isolates (6.58%) were identified as MRSP based on the presence of mecA. Based on phenotype, 90% of MRSPs were multidrug-resistant. All MRSP had moderate (10%, 1/10) and strong (90%, 9/10) biofilm production ability. PB extracts were the most effective in inhibiting planktonic cells, and the minimum inhibitory concentration at which ≥50% of the isolates were inhibited (MIC50) was 256 µg/mL (256–1024 µg/mL) for S. pseudintermedius isolates and 512 µg/mL (256–1024 µg/mL) for MRSP isolates. The MIC90 for S. pseudintermedius and MRSP was 512 µg/mL. In XTT assay, PB at 4× MIC showed an inhibition rate of 39.66–68.90% and 45.58–59.13% for S. pseudintermedius and MRSP, respectively, in inhibiting biofilm formation. For PB at 8× MIC, the inhibition rates for S. pseudintermedius and MRSP were 50.74–81.66% and 59.57–78.33%, respectively. Further, 18 compounds were identified in PB using gas chromatography–mass spectrometry, and hydroxychavicol (36.02%) was the major constituent. These results indicated that PB could inhibit bacteria growth of and biofilm formation by S. pseudintermedius and MRSP isolated from canine pyoderma in a concentration-dependent manner. Therefore, PB is a potential candidate for the treatment of MRSP infection and biofilm formation in veterinary medicine.
Andrographis paniculata (Burm.f.) Nees Alleviates Methotrexate-Induced Hepatotoxicity in Wistar Albino Rats

Andrographis paniculata is a herbal plant used in traditional medicinal approaches to treat various ailments and diseases. Methotrexate (MTX) is a clinically used immunosuppressant and anticancer drug. One of the increasing concerns with MTX use is liver toxicity. The aim of this study is to investigate the potential effect of aqueous leaf extract of Andrographis paniculata against methotrexate-induced hepatotoxicity. Wistar albino rats were grouped into five groups, and the drugs were administered. MTX (20 mg/kg b.w.) was intraperitoneally injected into rats on the ninth day alone. Aqueous leaf extract of Andrographis paniculata (500 mg/kg b.w./day) was orally administered for 10 days. We confirmed the beneficial effect of aqueous extracts of Andrographis paniculata on restoring the hepatic enzyme markers, lipid profile, antioxidant level, anti-inflammatory marker (IL-10), anti-apoptosis (bcl-2), significant suppression of inflammatory cytokines (TNF-α, and IL-6), apoptosis marker (caspase 3) and cellular tissue damage caused by MTX. Overall, we revealed that Andrographis paniculata reduces critical aspects of oxidative stress, inflammatory processes, and apoptosis, thus protecting against methotrexate-induced hepatotoxicity.
The Moderating Role of Perceived Reward on Leadership Style and Policy Involvement Effects on Job Performance Among Pharmaceutical Managers

Management and behavioral sciences literature has established a direct link between rewards and employee performance. However, limited research exists on the role of perceived reward on the effects of policy strategy involvement and leadership style on the performance of pharmaceutical managers. Intuitively, perceived rewards may have a potential impact on the behavior and attitudes of pharmaceutical managers toward work, and invariably job performance. Based on the incentive theory of motivation framework, the study explored the causal effect of leadership style, and policy involvement on job performance, and the moderating effect of perceived reward among pharmaceutical managers. Comparative differences in perception between operational and strategic managers were evaluated. A cross-sectional web-based questionnaire survey of a random stratified sample of managers (103 strategic and 138 operational) engaged in pharmaceutical marketing. Structural equation modeling was used to evaluate the developed model. Construct validity and fit measures of the hypothetical model were adequate. Policy strategy involvement and leadership style had a positive and significant influence on job performance. Moderation analysis showed that low perceived reward significantly weakened the impact of policy engagement on performance. Integrating improved managers’ involvement with policy and strategy development with commensurate rewards is an incentive strategy to improve managers’ job performance. The study was restricted to only two major managerial groups. More job-related behavioral constructs are required to improve the generalizability of findings, which is suggested for further research.
Mitochondrial Dysfunction: At the Nexus between Alcohol-Associated Immunometabolic Dysregulation and Tissue Injury

Alcohol misuse, directly or indirectly as a result of its metabolism, negatively impacts most tissues, including four with critical roles in energy metabolism regulation: the liver, pancreas, adipose, and skeletal muscle. Mitochondria have long been studied for their biosynthetic roles, such as ATP synthesis and initiation of apoptosis. However, current research has provided evidence that mitochondria participate in myriad cellular processes, including immune activation, nutrient sensing in pancreatic β-cells, and skeletal muscle stem and progenitor cell differentiation. The literature indicates that alcohol impairs mitochondrial respiratory capacity, promoting reactive oxygen species (ROS) generation and disrupting mitochondrial dynamics, leading to dysfunctional mitochondria accumulation. As discussed in this review, mitochondrial dyshomeostasis emerges at a nexus between alcohol-disrupted cellular energy metabolism and tissue injury. Here, we highlight this link and focus on alcohol-mediated disruption of immunometabolism, which refers to two distinct, yet interrelated processes. Extrinsic immunometabolism involves processes whereby immune cells and their products influence cellular and/or tissue metabolism. Intrinsic immunometabolism describes immune cell fuel utilization and bioenergetics that affect intracellular processes. Alcohol-induced mitochondrial dysregulation negatively impacts immunometabolism in immune cells, contributing to tissue injury. This review will present the current state of literature, describing alcohol-mediated metabolic and immunometabolic dysregulation from a mitochondrial perspective.