Miracle-dz/UniFAR-FTUs huggingface dataset:
Rational Homotopy Theory II

Sullivan’s seminal paper, Infinitesimal Computations in Topology, includes the application of his techniques to non-simply connected spaces, and these ideas have been used frequently by other authors. Our objective in this sequel to our “Rational Homotopy Theory I, published by Springer-Verlag in 2001, is to provide a complete description with detailed proofs of this material. This then provides the basis for new results, also included, and which we complement with recent advances for simply-connected spaces. There do remain many interesting unanswered questions in the field, which hopefully this text will make it easier for others to resolve.
The Relationship between Service Delivery and Work Engagement on Nurse Performance at Bali Mandara Hospital 2022

Nursing services are the center of attention in every hospital because this service is a main activity that can be used as a benchmark for evaluating health services, especially in inpatient rooms. Performance measurement is carried out to improve the quality of providing nursing care, reduce costs, protect nurses from negligence in carrying out their duties, and protect patients from negligence in health services. Achievement of Indicators based on the Work Plan at Bali Mandara Hospital in 2021 with the performance indicator of the Percentage of Services program that meets Standard Operating Procedures is targeted to reach 100% and the realization reached 85.45%. In 2021, the target of providing salaries and benefits for health workers is 90%, and 87.07% is achieved. The research objective was to determine the relationship between service delivery and work engagement on the performance of inpatient nurses. This study used an observational design with a cross sectional. The number of samples selected was 241 people. Data analysis used multiple logistic regression test. The results showed that there was a significant relationship between service delivery and work engagement on nurse performance. Variable work engagement is the most dominant variable influencing the performance of inpatient nurses at Bali Mandara Hospital.
Sur le problème de Cauchy pour les équations de Davey-Stewartson

The Davey-Stewartson system models the evolution of certain surface waves. Its type depends on the various physical parameters which occur. We give existence and uniqueness results for the Cauchy problem and a result of blow up in finite time Le systeme de Davey-Stewartson modelise l'evolution de certaines ondes de surface. Son type depend de divers parametres, fonctions du contexte physique. On donne des resultats d'existence et d'unicite pour le probleme de Cauchy, ainsi qu'un resultat d'explosion en temps fini
Controlled generation of optical rogue waves in dispersion oscillating fiber

Generation of high-intensity pulses through inelastic soliton collisions in dispersion oscillating fibre is discussed. The inelastic collisions leads to the change amplitudes of solitons, group velocities and even of number of solitons. The generation of giant pulse can be controlled by variation of the modulation period and temporal separation between colliding fundamental solitons. Stimulated Raman scattering and third-order dispersion disimprove the formation of high-intensity pulses. The proposed approach allows to generate rogue waves as result of the inelastic collision of optical solitons.
Multimodal Exercise in Older Patients with Advanced Pancreatic Cancer Undergoing First-Line Chemotherapy: A Case Series Examining Feasibility and Preliminary Efficacy

Purpose. Exercise is emerging as an adjunct therapy to cancer treatment; however, its role in older patients with advanced pancreatic cancer undergoing first-line chemotherapy is unclear. The aim of this study was to primarily provide evidence on feasibility with an exploratory examination of the initial efficacy of exercise in this clinical setting. Materials and Methods. Six patients aged 60–75 years with de novo or recurrent advanced pancreatic cancer undergoing first-line chemotherapy consented to participate in twice-weekly exercise that included resistance and aerobic training and boxing-related activities for up to 12 weeks. Patients were monitored for attendance, adherence, and adverse events. Body composition, muscle strength, functional ability, patient-reported outcome measures, and patient-reported experience measures were assessed at baseline and/or postintervention. Results. Of the 6 patients, 1 withdrew after baseline testing and 5 attended 42%–95% of planned sessions and adhered to 28%–83% of the prescribed exercise. There were no serious exercise-emergent adverse events. All 5 patients increased or maintained lean mass (0.1%–4.4%) and 4 reduced fat mass (−0.4%–−8.6%). Improvements were observed in 4 or all 5 patients for muscle strength (7.1%–75%), 5 times sit-to-stand (1.3%–21.4%), 6-m backward walk (16.5%–35.8%), and patient-reported outcomes. Furthermore, all patients perceived exercise as very helpful in managing their cancer and expressed a strong willingness to continue exercise in the future. Conclusion. A multimodal exercise program appears feasible with potential physical and psychological benefits for older patients with advanced pancreatic cancer undergoing first-line chemotherapy. Further research including a larger sample size is warranted.
Stroke Risk Prediction Using Artificial Intelligence Techniques Through Electronic Health Records

Nowadays, Electronic Health Records (EHR) include critical information in the text format. In order to make medical decisions more efficient, the text should be processed and code deliberated. In this report, we applied Artificial Intelligence (AI) techniques to improve stroke risk prediction based on the EHR text. The system based on Natural Language Processing (NLP) generates structured text from EHR, followed by applying Machine Learning (ML) techniques to classify the text as a "good" or "bad" indicator, which is used for prediction. The ML models here we used include logistic regression and Support Vector Machine (SVM). Our results show that both models can classify the text precisely and make predictions accurately.
Is Oral Vaccination against Escherichia coli Influenced by Zinc Oxide?

Simple Summary Zinc oxide remains a widely used compound for the control and prevention of post-weaning Escherichia coli (E. coli) diarrhoea in piglets. It is sometimes administered concomitantly with oral E. coli vaccines. In this research, we assessed the influence of the administration of zinc oxide in piglet feed in combination with a bivalent vaccine against E. coli. We studied the immune activation, intestinal integrity, production of secretory IgA, and excretion of E. coli via faecal samples at different times post-vaccination. Although the main difference observed was the excretion of the E. coli vaccine strain, the immune response determined in both vaccine groups was similar, irrespective of the presence of ZnO in the feed. Abstract Background: Although zinc oxide has been banned at therapeutic doses in the EU, its use is still legal in most countries with industrial pig farming. This compound has been shown to be very effective in preventing E. coli-related diseases. However, another strategy used to control this pathogen is vaccination, administered parenterally or orally. Oral vaccines contain live strains, with F4 and F18 binding factors. Since zinc oxide prevents E. coli adhesion, it is hypothesised that its presence at therapeutic doses (2500 ppm) may alter the immune response and the protection of intestinal integrity derived from the vaccination of animals. Methods: A group of piglets were orally vaccinated at weaning and divided into two subgroups; one group was fed a feed containing 2500 ppm zinc oxide (V + ZnO) for the first 15 days post-vaccination (dpv) and the other was not (V). Faeces were sampled from the animals at 6, 8, 11, 13, and 15 dpv. Unvaccinated animals without ZnO in their feed (Neg) were sampled simultaneously and, on day 15 post-vaccination, were also compared with a group of unvaccinated animals with ZnO in their feed (ZnO). Results: Differences were found in E. coli excretion, with less quantification in the V + ZnO group, and a significant increase in secretory IgA in the V group at 8 dpv, which later equalised with that of the V + ZnO group. There was also some difference in IFNα, IFNγ, IL1α, ILβ, and TNFα gene expression when comparing both vaccinated groups (p < 0.05). However, there was no difference in gene expression for the tight junction (TJ) proteins responsible for intestinal integrity. Conclusions: Although some differences in the excretion of the vaccine strain were found when comparing both vaccinated groups, there are no remarkable differences in immune stimulation or soluble IgA production when comparing animals orally vaccinated against E. coli in combination with the presence or absence of ZnO in their feed. We can conclude that the immune response produced is very similar in both groups.
Fault Diagnosis in Wind Turbines Based on Weighted Joint Domain Adversarial Network Under Various Working Conditions

In recent years, the practical cross-domain wind turbine fault diagnosis is constrained by label space and distribution differences of fault data under different working conditions. Due to the difference in feature distribution, the generalizability of traditional transfer learning models can be affected. Moreover, the difference in label space, which refers to the target domain (supervisory control and data acquisition (SCADA) data of another wind turbine), covers only a subset of the source domain (SCADA data of one wind turbine) fault categories, it reduces the accuracy of recognition by the diagnostic model for the target domain failure. Therefore, a weighted joint domain adversarial network (WJDAN) is proposed in this article to overcome the above problems. In this method, a weighting function is introduced to identify and remove irrelevant source domain fault categories, with the contribution of source domain data to the domain discriminator, maximum mean discrepancy (MMD), and classifier measured. Besides, the domain adversarial network with the intraclass MMD loss is introduced to minimize the marginal and conditional distributional discrepancies between the source domain and target domain simultaneously. As revealed by the experiments on SCADA data of different wind turbines, the proposed WJDAN outperforms other traditional transfer learning methods on wind turbine fault diagnosis.
Effect of a Co-Feed Liquid Whey-Integrated Diet on Crossbred Pigs’ Fecal Microbiota

Simple Summary The use of low-cost by-products originating from agri- and dairy-chain production in animal nutrition represents an alternative strategy to feed and improve animal performance and reduce the environmental impact. In swine production, liquid-feeding products can positively contribute to the equilibrium of animal guts, thus supporting the reduction of feed medication. The liquid whey by-product of the cheese-making process is considered a palatable alternative feed and a promptly available source to provide functional ingredients without further costly transformation. In the last decade, increased knowledge of the gut microbiome has contributed to expanding our insights on host health, well-being, growth, and feed efficiency. Based on this perspective, this research investigated the fecal microbiota of crossbred pigs that underwent a co-feed liquid whey-integrated diet with a metagenomics approach. Abstract This study assessed the potential effect of a co-feed liquid whey-integrated diet on the fecal microbiota of 14 crossbred pigs. The experimental design was as follows: seven pigs were in the control group, fed with a control feed, and seven were in the experimental group, fed with the same control feed supplemented daily with liquid whey. The collection of fecal samples was conducted on each animal before the dietary treatment (T0) and one (T1), and two (T2) months after the beginning of the co-feed integration. In addition, blood samples were collected from each pig at the same time points in order to evaluate the physiological parameters. Taxonomic analysis showed a bacterial community dominated by Firmicutes, Bacteroidetes, Spirochaetes, and Proteobacteria phyla that populated the crossbred pig feces. The diversity metrics suggested that the co-feed supplementation affected some alpha diversity indexes of the fecal microbiota. In addition, the differential abundance analysis at the genus level revealed significant differences for various genera, suggesting that the liquid whey supplementation potentially influenced a part of the bacterial community over time. Spearman’s correlations revealed that the differential abundant genera identified are positively or negatively correlated with the physiological parameters.
Study and Comparison of Face Recognition Techniques: EIGEN faces and EBGM

In today’s life, the technique of face recognition becomes very popular and found successful application in real life. In this paper, we will have a comparative study of two proposed methods for face recognition. ¬¬ One approach is Eigen Faces and other approach is Elastic Bunch Graph Matching (EBGM). After reviewing and implementation of above said methods, we conclude that EBGM approach is better than Eigen Faces approach in various aspects.
Investigation of Vortex-Induced Vibration of Double-Deck Truss Girder with Aerodynamic Mitigation Measures

The long-span double-deck truss girder bridge has become a recommend structural form because of its good performance on traffic capacity. However, the vortex-induced vibration (VIV) characteristics for double-deck truss girders are more complicated and there is a lack of related research. In this research, wind tunnel tests were utilized to investigate the VIV characteristics of a large-span double-deck truss girder bridge. Meanwhile, the VIV suppression effect of the aerodynamic mitigation measures was measured. Furthermore, the VIV suppression mechanism was studied from the perspective of vortex shedding characteristics. The results indicated that the double-deck truss girder had a significant VIV when the wind attack angles were +3° and +5°. The aerodynamic mitigation measures had an influence on the VIV response of the double-deck truss girder. The upper chord fairing and lower chord inverted L-shaped deflector plate played a crucial role in suppressing VIV. Numerical analysis indicated that vortex shedding above the upper deck or in the wake region may dominate vertical VIV, while vortex shedding in the wake region of the lower deck may dominate torsional VIV. The upper chord fairing and lower chord inverted L-shaped deflector plate disrupted the original vortex shedding pattern in both regions, thereby suppressing VIV. This research can provide a foundation for bridge design and vibration suppression measures for large-span double-deck truss girder bridges.
Advances in 3D printing techniques for cartilage regeneration of temporomandibular joint disc and mandibular condyle

Temporomandibular joint (TMJ) osteoarthritis causes fibrocartilage damage to the TMJ disc and mandibular condyle, resulting in local pain and functional impairment that further reduces patients’ quality of life. Tissue engineering offers a potential treatment for fibrocartilage regeneration of the TMJ disc and mandibular condyle. However, the heterogeneous structure of TMJ fibrocartilage tissue poses significant challenges for the fabrication of biomimetic scaffolds. Over the past two decades, some researchers have attempted to adopt three-dimensional (3D) printing techniques to fabricate biomimetic scaffolds for TMJ fibrocartilage regeneration, but publications on such attempts are limited and rarely report satisfactory results, indicating an urgent need for further development. This review outlines several popular 3D printing techniques and the significant elements of tissue-engineered scaffolds: seed cells, scaffold materials, and bioactive factors. Current research progress on 3D-printed scaffolds for fibrocartilage regeneration of the TMJ disc and mandibular condyle is reviewed. The current challenges in TMJ tissue engineering are mentioned along with some emerging tissue-engineering strategies, such as machine learning, stimuli-responsive delivery systems, and extracellular vesicles, which are considered as potential approaches to improve the performance of 3D-printed scaffolds for TMJ fibrocartilage regeneration. This review is expected to inspire the further development of 3D printing techniques for TMJ fibrocartilage regeneration.
Exhaustive Diagnosis of Discrete Event Systems through Exploration of the Hypothesis Space

We formulate DES diagnosis as the problem of finding preferred candidates in a space of hypotheses. This formulation allows us to compute an exhaustive diagnosis by solving a series of simple problems, called “diagnosis tests”, which consist in finding a candidate in a set of hypotheses. In this way, we can avoid enumerating all explanations of the observation. Experiments on alarm data generated by power networks show that this approach is promising to monitor large
On the Hosoya Z Index of General Graphs

Motivation. The Z index, proposed by Haruo Hosoya in 1971, has initially been applied only to simple graphs representing saturated hydrocarbons. Our aim in this report was to extend the Z index to general graphs that may be used to represent unsaturated systems and heterosystems and to investigate the behavior of the Z index in regard to their structural characteristics such as size, branching, cyclicity, multiple edges and loops. Method. Chemical graph–theoretical concepts were used. The Z index was calculated by means of the Z counting polynomial and the matching polynomial. These polynomials were constructed using the appropriate recurrence relations. The structural behavior of the Z index was tested against the total walk count (twc) index. Results. The Z index was obtained for a number of simple graphs and general graphs. It is shown that the Z index of these graphs follows their structural changes, that is, the Z index increases with the size, loops, multiple edges, cycles and is sensitive to branching. The twc index supports in most cases the structural behavior of the Z index. The relationship between the Z counting polynomial and the matching polynomial is discussed. The edge decomposition of the Z index is also commented. Conclusions. The range of applicability of the Hosoya Z index is extended to general graphs. It is shown that this index accounts well for their structural characteristics.
Correction for Two-Group Sample Size Calculation with Uncertain Group Membership

Sample size and power calculations are often based on a two-group comparison. However, in some instances the group membership cannot be ascertained until after the sample has been collected. In this situation, the respective sizes of each group may not be the same as those prespecified due to binomial variability, which results in a difference in power from that expected. Here we suggest that investigators calculate an ”expected power” taking into account the binomial variability of the group membership, and adjust the sample size accordingly when planning such studies. We explore different scenarios where such an adjustment may or may not be necessary for both continuous and binary responses. In general, the number of additional subjects required depends only slightly on the values of the (standardized) difference in the two group means or proportions, but more importantly on the respective sizes of the group membership. We present tables with adjusted sample sizes for a variety of scenarios that can be readily used by investigators at the study design stage. The proposed approach is motivated by a genetic study of cerebral malaria and a sleep apnea study.
Machine Learning for Network Security: An Analysis of Intrusion Detection Systems

Due to the increasing importance of data and communication over computer networks, securing the network has become a critical issue. One of the most common factors that attackers use to bypass security measures is the availability of Intrusion Detection System (IDS) techniques. This paper aims to introduce machine learning to help improve the capabilities of IDS. The paper explores the potential of machine learning to enhance the security of networks. It starts by introducing network security and IDS, and then it reviews the current limitations of IDS techniques. It then delves into the world of machine learning and its applications in IDS. The paper presents an overview of the various aspects of machine learning-based IDS, including the datasets used for analysis, the models used, and the evaluation metrics that were utilized to measure their effectiveness. It then compares the results with traditional IDS techniques, and it explores the potential of this technology for future research. According to the findings of the study, machine learning-based intrusion detection systems can provide an efficient and accurate method of detecting unauthorized access to a computer network. The paper concludes by discussing the technology's potential for securing networks.
Learning Entirely Unknown Classes in Time-Series Data Using Convolutional Neural Networks for Insulation Status Assessment of Partial Discharges in Power Cable Joints

In this study, a method for supervised learning comprising a convolutional neural network (CNN) and sliding-window threshold is proposed for data with completely unknown categories. The governing principle is that the sliding-window threshold has the effect of local smoothing on the continuous prediction of CNN, and the data label can be updated after a new change point is generated based on simple rules. The partial discharge (PD) data obtained from the accelerated deterioration tests conducted on nine underground cable straight joints were used for verification. Subsequently, two different initial change points were set at 30% and 70%. The change points of the two cases were found to converge relatively closely. Furthermore, the unsupervised learning method was employed to determine a set of change points, which were similar to the results of the proposed method. Therefore, the rationality of the proposed method was verified using several methods.
Extra-Special Groups of Order 32 as Galois Groups

Abstract In this article we examine conditions for the appearance or nonappearance of the two extra-special 2-groups of order 32 as Galois groups over a field F of characteristic not 2. The groups in question are the central products DD of two dihedral groups of order 8, and DQ of a dihedral group with the quaternion group, obtained by identifying the central elements of order 2 in each factor group. It is shown that the realizability of each of these groups as Galois groups over F implies the realizability of other 2-groups (which are not their quotient groups), and in turn that realizability of certain other 2-groups implies the realizability of DD and DQ. We conclude by providing an explicit construction of field extensions with Galois group DD.