Miracle-dz/UniFAR-FTUs huggingface dataset:
Preparation and Separation Properties of Electrospinning Modified Membrane with Ionic Liquid Terminating Polyimide/Polyvinylpyrrolidone@Polydopamine

In this paper, superhydrophilic polyimide (PI) membranes were prepared using the electrostatic spinning method, capped with a hydrophilic ionic liquid (IL), and blended with polyvinylpyrrolidone (PVP). Using this preparation, the surface of the fiber membranes was coated in polydopamine (PDA) by means of an in-growth method. Scanning electron micrographs showed prepared blend films can form continuous fibers, for whom the distributions of diameter and pore were uniform. Post-modification (carried out by adding hydrophilic substances), the ability of the membrane surface to adhere to water was also significantly improved. The water contact angle was reduced from 128.97 ± 3.86° in unmodified PI to 30.26 ± 2.16°. In addition, they displayed a good separation effect on emulsified oil/water mixtures. The membrane flux reached a maximum value of 290 L·m−2·h−1, with a maximum separation efficiency reached of more than 99%. After being recycled 10 times, the separation efficiency maintained a level exceeding 95%. The purpose of this study is to demonstrate the simplicity and efficiency of this experiment, thereby providing new ideas for the future application of membrane separation technology in wastewater treatment.
The Next-Generation NIDS Platform: Cloud-Based Snort NIDS Using Containers and Big Data

Snort is a well-known, signature-based network intrusion detection system (NIDS). The Snort sensor must be placed within the same physical network, and the defense centers in the typical NIDS architecture offer limited network coverage, especially for remote networks with a restricted bandwidth and network policy. Additionally, the growing number of sensor instances, followed by a quick increase in log data volume, has caused the present system to face big data challenges. This research paper proposes a novel design for a cloud-based Snort NIDS using containers and implementing big data in the defense center to overcome these problems. Our design consists of Docker as the sensor’s platform, Apache Kafka, as the distributed messaging system, and big data technology orchestrated on lambda architecture. We conducted experiments to measure sensor deployment, optimum message delivery from the sensors to the defense center, aggregation speed, and efficiency in the data-processing performance of the defense center. We successfully developed a cloud-based Snort NIDS and found the optimum method for message-delivery from the sensor to the defense center. We also succeeded in developing the dashboard and attack maps to display the attack statistics and visualize the attacks. Our first design is reported to implement the big data architecture, namely, lambda architecture, as the defense center and utilize rapid deployment of Snort NIDS using Docker technology as the network security monitoring platform.
Ostrom’s Design Principles in Residential Public Open Space Governance: Conceptual Framework and Literature Review

Various measures were undertaken to internalize the state-owned common pool resource (CPR) based public open space’s (POS) externalities which arisen from the perennial commons’ dilemmas, yet, to date, not a single adaptive governance strategy has been discovered. Thus, a review of trans-disciplinary analytic perspectives is required, which thereof, highlights the objective of the paper i.e., to propose Ostrom’s common-property-based self-organizing eight design principles by examining how can they be adaptably applied in governing the residential commons, POS (particularly landed property) in the Malaysian context. Two study areas: states of Sabah and Selangor, of different institutional POS governance, were a priori fleshed out. Succinctly, Ostrom’s principles are basic, insightful, well-defined, organized, and widely-applicable, which have enabled us to consent that there is certainly a void for both states to adapt her oeuvre as a dynamic panacea in POS governance. This paper infers that Ostrom’s principles are a means to improve the status quo of POS’ quality (as POS rejuvenation) which postulates stakeholders to reckon it as a new paradigm in the urban design and planning perspective
Therapeutic Values of Earthworm Species Extract from Azad Kashmir as Anticoagulant, Antibacterial, and Antioxidant Agents

Aims Current research aimed to explore the therapeutic values of different earthworms as antibacterial, anticoagulant, and antioxidant agents. Methods Ten different earthworms, i.e., Amynthas corticis, Amynthas gracilis, Pheretima posthuma, Eisenia fetida, Aporrectodea rosea, Allolobophora chlorotica, Aporrectodea trapezoides, Polypheretima elongata, Aporrectodea caliginosa, and Pheretima hawayana, were collected and screened for biological activities. Antibacterial effect analysis of earthworm species was done against fourteen bacterial pathogens, i.e., Escherichia coli, Serratia marcescens, Streptococcus pyogenes, Staphylococcus epidermidis, Staphylococcus aureus, Klebsiella pneumoniae, Pseudomonas aeruginosa (1), Salmonella typhimurium, Shigella flexneri, Enterobacter amnigenus, Serratia odorifera, Pseudomonas aeruginosa (2), Staphylococcus warneri, and Lactobacillus curvatus, via agar well diffusion, crystal violet, MTT, agar disc diffusion, and direct bioautography assays. Antioxidant potential was evaluated through ABTS and DPPH assays. Lipolytic, proteolytic, and amylolytic assays were done for lipase, protease, and amylase enzymes confirmation. In vitro anticoagulant effects were examined in the blood samples by measuring prothrombin time. Results Results revealed that all earthworm extracts showed the inhibition of all tested bacterial pathogens except P. aeruginosa (1), P. aeruginosa (2), S. warneri, and L. curvatus. The maximum zone of inhibition of E. coli was recorded as 14.66 ± 0.57 mm by A. corticis, 25.0 ± 0.0 mm by P. posthuma, 20.0 ± 0.0 mm by E. fetida, and 20.0 ± 0.0 mm by A. trapezoid. Cell proliferation, biofilm inhibition, the synergistic effect of extracts along with antibiotics, and direct bioautography supported the results of agar well diffusion assay. Similarly, P. hawayana, A. corticis, A. caliginosa, and A. trapezoids increase the prothrombin time more efficiently compared to other earthworms. A. corticis, A. gracilis, A. rosea, A. chlorotica, P. elongata, and A. trapezoides showed maximum DPPH scavenging potential effect. Conclusions The coelomic fluid of earthworms possessed several bioactive compounds/enzymes/antioxidants that play an important role in the bacterial inhibition and act as anticoagulant agents. Therefore, the development of new therapeutic drugs from invertebrates could be effective and potential for the prevention of the emergence of multidrug-resistant bacteria.
Interoperability in the era of digital innovation: An information systems research agenda

Digital innovation enables new forms of cyber-physical innovation based on digital business ecosystems. However, the realization of the opportunities arising from such innovation substantially hinges on interoperability, that is, the ability of two or more systems to exchange information and understand that exchanged information. While interoperability is a long-standing topic in research and practice alike and a valuable knowledge base exists, digital innovation poses novel challenges that might not be covered by conventional wisdom. Accordingly, we review the literature and, first, propose an organizing framework for existing interoperability knowledge involving the contextual conditions of low interoperability, the mechanisms to increase interoperability, and the associated outcomes. Second, we use the framework to identify previous research foci in the scholarly discourse about interoperability and to discuss the potential limitations of this past work in light of digital innovation. Third, we propose a research agenda that enables information systems (IS) research to address the identified limitations—involving conceptual, scoping, and methodological issues—and provide specific recommendations on how to address the identified issues in future IS research. Finally, we propose five major research topics for further inquiry by combining the challenges identified in current knowledge with the current shift toward hyper-connected ecosystems underlying digital innovation.
Preferential Attachment and Pattern Formation in R&D Networks - Plausible explanation or just a widespread myth?

The emergence and solidification of network patterns is typically explained by the preferential attachment rule. The underlying logic is that a small number of actors which are characterized by an above average degree attract links at a higher rate than others. We raise the question as to what extent the wide spread preferential attachment explanation holds true in the context of inventor networks. To shed some light on this issue we investigate co-patenting relationships among inventors in the field of laser technology in West Germany from 1961 to 2005. From a system perspective, the development of the inventor networks is in line with the pattern that is implied by the preferential attachment logic. However, we find high levels of fluidity of micro-level relationships that put the typical transaction cost and trust-based explanation of tie formation processes into question.
Propagation of a p-polarized plane wave across a transparency and chiral interface using a $\overline{k}$-vector approach

Diffraction of a p-polarized electromagnetic (EM) wave across a 1D transparency and subsequent transmission through a planar achiral/chiral (ACC) interface are examined using Fresnel-Kirchhoff (F-K) diffraction formula and an effective $\overline{k}$-vector approach. Following determination of the Fresnel coefficients (FCs) at the boundary, we examine the transmission across the interface and tracking the transmitted amplitudes via a combination of the effective FCs and the $\overline{k}$-vector approach.
Classification method of support vector machine based on error correction coding

In the space radiation environment, there will be many errors in the multi-classification results of support vector machine which caused by single event flipping, the ability to correct classification errors through error correction coding is studied in this paper, results of simulation confirm that error correction coding can increase the accuracy, which is beneficial for anti-single event flip.
Comparison of Different Machine Learning Models in Prediction of Postirradiation Recurrence in Prostate Carcinoma Patients

After primary treatment of localized prostate carcinoma (PC), up to a third of patients have disease recurrence. Different predictive models have already been used either for initial stratification of PC patients or to predict disease recurrence. Recently, artificial intelligence has been introduced in the diagnosis and management of PC with a potential to revolutionize this field. The aim of this study was to analyze machine learning (ML) classifiers in order to predict disease progression in the moment of prostate-specific antigen (PSA) elevation during follow-up. The study cohort consisted of 109 PC patients treated with external beam radiotherapy alone or in combination with androgen deprivation therapy. We developed and evaluated the performance of two ML algorithms based on artificial neural networks (ANN) and naïve Bayes (NB). Of all patients, 72.5% was randomly selected for a training set while the remaining patients were used for testing of the models. The presence/absence of disease progression was defined as the output variable. The input variables for models were conducted from the univariate analysis preformed among two groups of patients in the training set. They included two pretreatment variables (UICC stage and Gleason's score risk group) and five posttreatment variables (nadir PSA, time to nadir PSA, PSA doubling time, PSA velocity, and PSA in the moment of disease reevaluation). The area under the receiver operating characteristic curve, sensitivity, specificity, positive predictive value, negative predictive value, and predictive accuracy was calculated to test the models' performance. The results showed that specificity was similar for both models, while NB achieved better sensitivity then ANN (100.0% versus 94.4%). The ANN showed an accuracy of 93.3%, and the matching for NB model was 96.7%. In this study, ML classifiers have shown potential for application in routine clinical practice during follow-up when disease progression was suspected.
Environmental Factor Accelerate the Deterioration of Tuff Stone Heritage: A Case Study of a Stone House in Southeast China

Water plays an important role in the deterioration of rocks. Often, the condensation cannot be ignored in addition to the rain and seepage, especially for stone relics built with tuff in humid areas. As part of this study, a century-old stone house in southeastern China was investigated alongside the microclimate, including temperature, humidity, and rainfall in the study area. Results showed that the main types of deterioration in this house were detachment, with some areas exhibiting surface hardness decreased by more than 50%. This decay was caused in part by condensation on the inner walls of the stone house during the rainy season. According to statistics, more than two-thirds of the time the rainy season produces condensate on the inner wall, which is primarily found on the north side of the house because there is less solar radiation. Conversely, the stress caused by severe temperature differences on the south side contributes more to the deterioration of rock. Environmental conditions with high humidity and strong temperature differences will accelerate the deterioration process of tuff stone with high porosity. Consequently, it is recommended that stones built by tuff in such a humid environment take rainproof measures and maintain good air circulation to reduce the adverse effects of condensation.
Industry 4.0 Readiness Calculation—Transitional Strategy Definition by Decision Support Systems

The digitization of the manufacturing industry, 10 years after the introduction of the Industry 4.0 concept, is still one of the most demanding tasks for the companies, especially for SMEs. As one of the biggest barriers in new business model implementation, the lack of strategy and workforce skills is frequently mentioned in the literature. The high level of investments it requires and the perception of high risks with unclear future benefits can be avoided with readiness factor calculation. This paper presents a novel model for readiness factor calculation, oriented to process planning and based on decision support systems. The model enables the definition of the optimal strategic plan for the digitization with the use of decision support systems (analytic hierarchy process) and through the use of statistical methods implemented within the model it minimizes the influence of human subjectivity and quantification of qualitative criteria. This innovative approach enables the understanding of the transition process to new technology-enabled business models, in this case oriented towards process planning. The useability and reliability of the model is proven in a case study of a metal machining company.
Adalimumab Decorated Nanoparticles Enhance Antibody Stability and Therapeutic Outcome in Epithelial Colitis Targeting

Inflammatory bowel disease (IBD) is a chronic inflammatory disease of the gastrointestinal tract with increasing incidence worldwide. Although a deeper understanding of the underlying mechanisms of IBD has led to new therapeutic approaches, treatment options are still limited. Severe adverse events in conventional drug therapy and poor drug targeting are the main cause of early therapy failure. Nanoparticle-based targeting approaches can selectively deliver drugs to the site of inflammation and reduce the risk of side effects by decreasing systemic availability. Here, we developed a nanoparticulate platform for the delivery of the anti-TNF-α antibody adalimumab (ADA) by covalent crosslinking to the particle surface. ADA binding to nanoparticles improved the stability of ADA against proteolytic degradation in vitro and led to a significantly better therapeutic outcome in a murine colitis model. Moreover, immobilization of ADA reduced systemic exposure, which can lead to enhanced therapeutic safety. Thus, nanoparticle protein decoration constitutes a platform through which epithelial delivery of any biological of interest to the inflamed gut and hence a local treatment can be achieved.
The 5-HT6R agonist E-6837 and the antagonist SB-271046 reverse the psychotic-like behaviors induced by ketamine

Schizophrenia is a serious mental disorder that affects 1% of the world’s population. Although various therapeutic tools have been developed since the appearance of the first generation of antipsychotics, the effect of these agents does not manage to attenuate a significant part of psychotic symptoms. Ketamine is an anesthetic agent able to produce psychotic-like symptoms through the antagonism of the glutamatergic N-methyl-d-aspartic acid (NMDA) receptors (NMDARs). This drug has been widely used to study new pharmacological tools with potential antipsychotic properties. On the contrary, it is known that the 5-HT6 receptor agonist and antagonist drugs induce procognitive, anxiolytic and antidepressant effects in different preclinical models. Therefore, the aim of this study was to evaluate the behavioral actions of the 5-HT6 receptors’ agonist E-6837 and the antagonist SB-271046, in ICR-CD1 mice previously treated with a subchronic ketamine scheme (10 mg/kg i.p. daily for 5 days). Results showed that repeated administration of ketamine induced recognition memory deficit, anxiogenic effects, obsessive-compulsive behaviors and stereotyped movements. The acute administration of both 5-HT6 agents reversed the memory deficit and induced a decrease in anxiety, whereas SB-271046 administration produced a decrease in climbing behavior. The injection of either of these 5-HT6 drugs had no effect in the light–dark test. Surprisingly, when these drugs were injected together with ketamine, anxiogenic actions were produced. Current findings suggest that both agonist and antagonist 5-HT6 drugs play an important role in modulating psychotic-like symptoms induced by the subchronic blockade of NMDAR.
Design and Implementation of Amharic-based IDE with High-Level Programming Language

INTRODUCTION: Programming languages enable us to communicate with our machines in a human-like way through computer code. Many programming languages have been developed; however, the majority of them do not have an Amharic development environment. This resulted in a Limited capacity of finding our solutions for our problems based on the context of where we are in the world and lack of technological innovation in the Amharic Language . OBJECTIVES: the main goal of this study is to create an easy-to-use high-level Amharic programming language, as well as a special compiler Environment for the language. METHODS: To develop the Amharic-based compiler development environment (IDE), we have used the compiler developments environment principles by modifying existing algorithms for the language. In this study, we conducted a new Amharic programming language environment called SABA, as well as a special Amharic interfaced compiler DAMAT. RESULTS: We discovered that the study support those who wanted to learn programming languages in their local language, and educational institutions found it better to teach and learn. Last, the study contributes to global technological advancement. CONCLUSION: The study illustrates the possibilities of constructing a programming language environment using native language by developing a prototype, further additional keywords, and grammar will enhance the study.
Assessing Technology Innovation of Mobile Health Apps for Medical Care Providers

In recent years, mobile health applications (mHealth apps) have created a new social context in the clinical diagnosis process based on technology innovation. To improve understanding of digital transformation in healthcare and determinants for its implementation, this article examines the available mHealth apps addressed to medical practitioners and explores these apps features’ trustworthiness, quality, and popularity. Based on the normalization process theory, we explain the process from the introduction of mHealth innovation in the clinical practice to the intention of professional engagement. We conduct content analysis of the apps’ descriptions, functions, and user reviews; measured available app features and performance metrics; and applied statistical analysis to understand features intercorrelations and users’ preferences. We observe moderate levels of reliability and quality in the existing mHealth apps, revealing margins for potential improvement. The mHealth app star rating, quality score, and downloads are all highly intercorrelated. The apps with more features score higher in quality, especially those with credible sources, feedback opportunities, and “how to use” instructions. App development from credible sources can increase their trustworthiness. Further, technological advances in these apps can greatly benefit health professionals’ everyday practice and, thus, healthcare for society. This article contributes to the information systems research by using social theories to reveal the importance of app features to the adoption of professional health applications and underline the sets of policies/practices that should apply in the app development process to strengthen clinical efficiency and effectiveness.
Internet Use and Quality of Life: The Multiple Mediating Effects of Risk Perception and Internet Addiction

The impact of internet use on quality of life (QoL) has become an increasing focus of academic research. This paper aims to explore the internal influencing mechanisms of internet use (i.e., leisure-oriented internet use (LIU); work-oriented internet use (WIU)) on QoL, with a focus on the multiple mediating effects of risk perception and internet addiction. We constructed a theoretical framework from a psychological perspective and tested the hypotheses using hierarchical regression analysis with a sample of 1535 participants. The results showed that: (1) LIU had a positive effect on QoL, while WIU did not have a significant impact on QoL; (2) both risk perception and internet addiction had a negative influence on QoL; (3) risk perception positively impacted internet addiction; (4) risk perception and internet addiction had multiple mediating effects on the relationship between internet use and QoL.
Perceptions of Indonesian Nurses Toward the Application of the Internet of Things in the Future

In the healthcare industry, Internet of Things (IoT) based systems are utilized for phone care delivery, smart healthcare, smart health sensors and wearable technology, preventative systems, and distant monitoring. No studies have assessed nurses’ perspectives of IoT applications in Indonesia. The purpose of this study was to identify health professionals’ perspectives on future health and technology trends, to identify their readiness to adopt new health technologies, and to identify the use of IoT technology in healthcare applications. This study was conducted using a descriptive and cross-sectional approach. Nurses with a Diploma III and at least one year of experience were selected from three different departments (medical surgical, pediatrics, maternity). About 76% of 350 nurses had little knowledge of IoT technology and 95% said they do not keep up to date with IoT publications. About 50% of nurses believed that IoT technology will have a large impact on the health and education sectors. These results indicated that IoT technology and informatics should be included in nursing education and further studies should be conducted to integrate technological trends into healthcare and nursing practices. Keywords: perceptions, nurses, internet of things, healthcare