Miracle-dz/UniFAR-FTUs huggingface dataset:
Seasonality of Ichthyophthirius multifiliis in the Trout (Oncorhynchus mykiss) Farms of the Eastern Black Sea Region of Turkey

Rainbow trout (Oncorhynchus mykiss) ranging from fry to marketing size were sampled monthly in 2002 from three farms to determine prevalence, abundance, and intensity of Ichthyophthirius multifiliis, the causative agent of ichthyophthiriasis. I. multifiliis was present and active in the farms from June to August. However, outbreaks of ichthyophthiriasis occurred only late in summer. Persistent presence of the ciliated parasitic protozoan in the farms suggests that I. multifiliis is endemic in the region. Thus, effective measures such as decreasing of host densities and routine prophylactic treatments should be applied to decrease or eliminate the impact of the parasite on growth of the host. This is the first extensive study providing seasonal data on the presence of I. multifiliis in the Eastern Black Sea Region of Turkey.
Four-compartment muscle fatigue model to predict metabolic inhibition and long-lasting nonmetabolic components

Introduction: Computational muscle force models aim to mathematically represent the mechanics of movement and the factors influencing force generation. These tools allow the prediction of the nonlinear and task-related muscle behavior, aiding biomechanics, sports science, and rehabilitation. Despite often overlooking muscle fatigue in low-force scenarios, these simulations are crucial for high-intensity activities where fatigue and force loss play a significant role. Applications include functional electrical stimulation, motor control, and ergonomic considerations in diverse contexts, encompassing rehabilitation and the prevention of injuries in sports and workplaces. Methods: In this work, the authors enhance the pre-existing 3CCr muscle fatigue model by introducing an additional component of force decay associated with central fatigue and a long-term fatigue state. The innovative four-compartment model distinguishes between the short-term fatigued state (related to metabolic inhibition) and the long-term fatigued state (emulating central fatigue and potential microtraumas). Results: Its validation process involved experimental measurements during both short- and long-duration exercises, shedding light on the limitations of the traditional 3CCr in addressing dynamic force profiles.
Linking Semantic and Knowledge Representations in a Multi-Domain Dialogue System

We describe a two-layer architecture for supporting semantic interpretation and domain reasoning in dialogue systems. Building system that supports both semantic interpretation and domain reasoning in a transparent and well-integrated manner is an unresolved problem because of the diverging requirements of the semantic representations used in contextual interpretation versus the knowledge representations used in domain reasoning. We propose an architecture that provides both portability and efficiency in natural language interpretation by maintaining separate semantic and domain knowledge representations, and integrating them via an ontology mapping procedure. The ontology mapping is used to obtain representations of utterances in a form most suitable for domain reasoners and to automatically specialize the lexicon. The use of a linguistically motivated parser for producing semantic representations for complex natural language sentences facilitates building portable semantic interpretation components as well as connections with domain reasoners. Two evaluations demonstrate the effectiveness of our approach: we show that a small number of mapping rules are sufficient for customizing the generic semantic representation to a new domain, and that our automatic lexicon specialization technique improves parser speed and accuracy.
Context Helps Determine Spatial Knowledge from Tweets

This paper introduces the problem of determining whether people are located in the locations they mention in their Twitter streams. In particular, we investigate the role of context—tweets published before and after a tweet mentioning a location—in this challenging problem. We present a new corpus of Twitter streams with spatial information. Our analyses show that context is key to define the ground truth, as human judgments depend on whether annotators have access to context. Experimental results show that a neural architecture that takes into account context in addition to the tweet mentioning a location yields better results. We also conduct an error analysis to provide insights into the errors made by our best model.
Fundamental study on relaxation processes of water tree in aged power cables aimed for diagnosis with spatial resolution

The "water tree" is a degradation mode of power cable with polymer insulation. A water tree is composed of small droplets filled with water. As the conductivity in water tree is very high, it leads to dielectric breakdown when it grows up. Inside the water tree is filled with trap sites. Therefore, a water tree can be recognized as an electret.
Journal of Graph Algorithms and Applications More Canonical Ordering

Canonical ordering is an important tool in planar graph drawing and other applications. Although a linear-time algorithm to determine canon-ical orderings has been known for a while, it is rather complicated to understand and implement, and the output is not uniquely determined. We present a new approach that is simpler and more intuitive, and that computes a newly defined leftist canonical ordering of a triconnected graph which is a uniquely determined leftmost canonical ordering. Further, we discuss duality aspects and relations to Schnyder woods.
Question Utility: A Novel Static Ranking of Question Search

In this paper, we propose a notion of 'question utility' for studying usefulness of questions and show how question utility can be integrated into question search as static ranking. To measure question utility, we examine three methods: (a) a method of employing the language model to estimate the probability that a question is generated from a question collection and then using the probability as question utility; (b) a method of using the LexRank algorithm to evaluate centrality of questions and then using the centrality as question utility; and (c) the combination of (a) and (b). To use question utility in question search, we employ a log linear model for combining relevance score in question search and utility score regarding question utility. Our experimental results with the questions about 'travel' from Yahoo! Answers show that question utility can be effective in boosting up ranks of generally useful questions.
Fenretinide: A Novel Treatment for Endometrial Cancer

Resistance to progestin treatment is a major hurdle in the treatment of advanced and reoccurring endometrial cancer. Fenretinide is a synthetic retinoid that has been evaluated in clinical trials as a cancer therapeutic and chemo-preventive agent. Fenretinide has been established to be cytotoxic to many kinds of cancer cells. In the present study, we demonstrate that fenretinide decreased cell viability and induced apoptosis in Ishikawa cells, which are an endometrial cancer cell line, in dose dependent manner in-vitro. This effect was found to be independent of retinoic acid nuclear receptor signaling pathway. Further, we have shown that this induction of apoptosis by fenretinide may be caused by increased retinol uptake via STRA6. Silencing of STRA6 was shown to decrease apoptosis which was inhibited by knockdown of STRA6 expression in Ishikawa cells. Results of an in-vivo study demonstrated that intraperitoneal injections of fenretinide in endometrial cancer tumors (created using Ishikawa cells) in mice inhibited tumor growth effectively. Immunohistochemistry of mice tumors showed a decrease in Ki67 expression and an increase in cleaved caspase-3 staining after fenretinide treatment when compared to vehicle treated mice. Collectively, our results are the first to establish the efficacy of fenretinide as an antitumor agent for endometrial cancer both in-vitro and in-vivo, providing a valuable rationale for initiating more preclinical studies and clinical trials using fenretinide for the treatment of endometrial cancer.
Role of reactive oxygen species on the formation of the novel diagnostic marker ischaemia modified albumin

Ischaemia modified albumin (IMA) is a recently developed biomarker of transient myocardial ischaemia.1 Circulating IMA is increased in patients with myocardial ischaemia, after percutaneous coronary intervention,2,3 or in acute coronary syndromes.4 The test has recently been licensed by the US Food and Drug Administration for diagnostic use in suspected myocardial ischaemia. IMA is serum albumin in which the N-terminus has been chemically modified. The diagnostic albumin Co2+ binding (ACB) test is based for IMA on the observation that the affinity of serum albumin for Co2+ is reduced after N-terminus modifications. It has been proposed that reactive oxygen species (ROS) such as superoxide (•O2−) and hydroxyl (•OH) radicals generated during myocardial ischaemia–reperfusion modify the N-terminus of serum albumin resulting in IMA formation but, so far, direct evidence to support this is scarce. We hypothesised that ROS generation causes the formation of IMA. Our objective was to model the formation of IMA in vitro by using chemically generated ROS and the •OH radical scavenger mercaptopropionylglycine (MPG). All reagents were obtained from Sigma-Aldrich (Poole, Dorset, UK) and normal human serum from the North London Transfusion Service (London, UK). Serum pH was 7.35–7.45 at 37°C and was unaltered by any of the reactants during the 15 minute experimental time course. Five millilitre serum aliquots (eight replicate experiments per group) were randomly selected for the following incubations for 15 minutes at 37°C. Group 1, peroxide treated (H2O2): serum was incubated with H2O2 100 μM. Group 2, superoxide treated (•O2−): serum was incubated with a xanthine-xanthine oxidase •O2− generating system consisting of 100 μM xanthine plus 0.05 U/ml xanthine …
Quality of life of women who underwent breast cancer treatment relative to sociodemographic, behavioral, and clinical factors

ABSTRACT Objective Patients with cancer often undergo multiple extended treatments that decrease their quality of life. However, the quality of life of women with breast cancer after they undergo treatment remains underexplored in Brazil. Therefore, this study determined sociodemographic, behavioral, and clinical factors related to the post-treatment quality of life of women with breast cancer. Methods This cross-sectional study involved 101 women diagnosed with breast cancer between 2014 and 2016 and treated at a Brazilian Oncology Reference Service. Data were collected from them using face-to-face surveys. Quality of life was evaluated using the European Organization for the Research and Treatment of Cancer Core Quality of Life questionnaire (EORTC QLQ-C30) and EORTC Breast Cancer-specific Quality of Life questionnaire (EORTC QLQ-BR23). The data collected were analyzed using Student’s t-test and Mann-Whitney U test. Results The median score on the global health, functional, and symptom scales of the EORTC QLQ-C30 was 75.00 (Interquartile range=33.33), 75.99 (Standard deviation [SD]=19.26), and 19.67 (SD=16.91), respectively. The mean score on the functional and symptom scales of the EORTC QLQ-BR23 was 61.89 (SD=17.21) and 20.12 (SD=16.94), respectively. Furthermore, higher post-treatment quality of life was found to be associated with being aged 50 or more, being Black, having eight or more years of education, having a partner, having a paying job, receiving treatment from the private healthcare system, having a higher income, living in the municipality where healthcare services are availed, engaging in physical activity, not smoking, being more religious, having more social support, not being overweight, having no comorbidities, and undergoing lumpectomy. Conclusion Sociodemographic, behavioral, and clinical factors significantly impact the quality of life of women who undergo breast cancer treatment. Implementing interventions that improve health and reducing inequalities in the access to healthcare services can improve the quality of life of these patients.
Representing Stastical Network-Based Anomaly Detection by Using Trust

A large number of systems that rely on the Internet pervasively launched into our daily lives during the last decades. The openness and scalability of the Internet have provided a flexible platform for private customers, professionals, and academics with non-commercial or commercial interests. Therefore, there has been growing interest in network security. Network or computer systems may employ anti-virus, firewall, intrusion prevention system, or intrusion detection system to maintain the safe environment. Among the systems, the intrusion detection system plays a very important role in minimizing the damage caused by different attacks. The system attempts to learn the features of behaviors and events of system and/or users over a period time to build a profile of normal behaviors, then looks for malicious behaviors that deviate from the normal profile. Thus, it is able to detect attacks even when detailed information of the attack does not exist. A wide variety of techniques were proposed to approach the system including machine learning, data mining, hidden Markov models, and statistical analysis. This research mainly considers the statistical analysis-based method due to the simplicity and effectiveness. However, the method has a few disadvantages. First, the results are not intuitive because it requires the related statistical background. Second, it is difficult to integrate the results of different statistical analyses due to the different ranges. Last, the methods provide only two states; normal or malicious behaviors. This research proposes a trust management scheme as a solution to these problems. A trust management scheme is able to scale the results of statistical analyses between 0 (unreliable) and 1 (reliable), so the results would not only be intuitive but also be able to integrate the various results into one. Moreover, the trust values can provide more than normal and malicious behaviors, such as a-little-suspicious, suspicious, or highly-suspicious states. We will show how well the trust management scheme can represent the results of various statistical analyses, how the system can find the appropriate thresholds for classifying the malicious behaviors in this dissertation. The proposed trust management scheme will be applied to two real-world datasets, and we will discuss the experiments results.
PREPARATION OF FATTY ACID METHYL ESTERS AND DIMETHYLACETALS FROM LIPIDS WITH BORON FLUORIDE--METHANOL.

Fatty acid methyl esters and dimethylacetals suitable for gas chromatographic analysis were prepared by treatment of lipids with boron fluoride-methanol (140 g BFI per liter of methanol). This reagent is stable and easy to handle. Reaction conditions were investigated for triglycerides, diglycerides, monoglycerides, free fatty acids, sterol esters, phosphatidyl ethanolamines, phosphatidyl serines, phosphatidyl 'cholines, monophosphoinositides, monogalactosyl glycerides, phosphatidal cholines (choline plasmalogens), digalactosyl glycerides, and sphingomyelins. The methyl esters and dimethylacetals were readily purified by thin-layer chromatography, and yields were quantitative. There were few undesirable side reactions, and they did not affect the validity of the method. The procedure developed is simple, rapid, and generally applicable t o lipids.
Preventing Cross Site Request Forgery Attacks

The Web has become an indispensable part of our lives. Unfortunately, as our dependency on the Web increases, so does the interest of attackers in exploiting Web applications and Web-based information systems. Previous work in the field of Web application security has mainly focused on the mitigation of cross site scripting (XSS) and SQL injection attacks. In contrast, cross site request forgery (XSRF) attacks have not received much attention. In an XSRF attack, the trust of a Web application in its authenticated users is exploited by letting the attacker make arbitrary HTTP requests on behalf of a victim user. The problem is that Web applications typically act upon such requests without verifying that the performed actions are indeed intentional. Because XSRF is a relatively new security problem, it is largely unknown by Web application developers. As a result, there exist many Web applications that are vulnerable to XSRF. Unfortunately, existing mitigation approaches are time-consuming and error-prone, as they require manual effort to integrate defense techniques into existing systems. In this paper, we present a solution that provides a completely automatic protection from XSRF attacks. More precisely, our approach is based on a server-side proxy that detects and prevents XSRF attacks in a way that is transparent to users as well as to the Web application itself. We provide experimental results that demonstrate that we can use our prototype to secure a number of popular open-source Web applications, without negatively affecting their behavior
Relationship between field walking tests and incremental cycle ergometry in COPD

Background and objective: Cycle ergometer training is an important component of pulmonary rehabilitation for patients with COPD. However, incremental cycle tests from which individualized cycle training intensity can be prescribed may not be readily available to clinicians. The aims of the study were to (i) investigate the physiological and psychophysical responses to the 6‐min walk test (6MWT), incremental shuttle walk test (ISWT) and cycle ergometer test (CET); and (ii) determine whether the distance walked in either the 6MWT or the ISWT could be used to estimate peak work rate on a cycle ergometer.
Resource Optimization and Energy Saving in Clusters Using Virtualization

This work proposes a reusable architecture that enables the management of a supporting infrastructure for Web server clusters using virtual machines. The goal of the architecture is to ensure service quality, evaluating how broadly it complies with the operating restrictions (maximum response time) and proportionally acting on physical servers (hosts) or manipulating the virtual machines. In addition, through the rational use of resources, the proposal aims at saving energy. A prototype of the architecture was developed and a performance evaluation carried out. This evaluation shows that the proposal is fully functional and how advantageous it can be in terms of using resources, avoiding waste, yet maintaining the application's service within acceptable quality failure levels.
Heterogeneous Price Setting Behavior and Monetary Non-neutrality : Some General Results

We analyze the effects of heterogeneity in price setting behavior in time-dependent sticky price and sticky information models characterized by quite general adjustment hazard functions. In a large class of models that includes the most commonly used price setting specifications, heterogeneity leads monetary shocks to have larger real effects than in one-sector economies with the same frequency of adjustments. Quantitatively, the effects of heterogeneity in models calibrated to match the recent empirical evidence on pricing behavior are large, even in the absence of strategic complementarity in price setting. We find that the degree of monetary non-neutrality in the calibrated heterogeneous economies can be as large as in an otherwise identical one-sector economy with roughly three times more nominal rigidity. JEL classification codes: E1, E3
Religiousness and Longitudinal Trajectories in Elders' Functional Status

The purpose of this study was to examine the effects of religiousness on the trajectories of difficulties with activities of daily living (ADLs) and instrumental ADLs (IADLs) in community-dwelling older adults over a three-year period. Seven waves of data from the University of Alabama at Birmingham Study of Aging were analyzed using a hierarchical linear modeling method. The study was based on the 784 participants who completed interviews every six months between December 1999 and February 2004. Frequent religious service attendance was associated with fewer ADL difficulties and IADL difficulties at baseline. Furthermore, religious service attendance predicted slower increases for frequent churchgoers and steeper increases for less frequent churchgoers in IADL difficulties, controlling for variables related to demographics and resources. Religious service attendance was independently associated with ADL and IADL difficulties cross-sectionally. However, significant protective effects of religious service attendance were identified longitudinally only for the IADL trajectory.
Human Brain Distinctiveness Based on EEG Spectral Coherence Connectivity

The use of EEG biometrics, for the purpose of automatic people recognition, has received increasing attention in the recent years. Most of the current analyses rely on the extraction of features characterizing the activity of single brain regions, like power spectrum estimation, thus neglecting possible temporal dependencies between the generated EEG signals. However, important physiological information can be extracted from the way different brain regions are functionally coupled. In this study, we propose a novel approach that fuses spectral coherence-based connectivity between different brain regions as a possibly viable biometric feature. The proposed approach is tested on a large dataset of subjects (N = 108) during eyes-closed (EC) and eyes-open (EO) resting state conditions. The obtained recognition performance shows that using brain connectivity leads to higher distinctiveness with respect to power-spectrum measurements, in both the experimental conditions. Notably, a 100% recognition accuracy is obtained in EC and EO when integrating functional connectivity between regions in the frontal lobe, while a lower 97.5% is obtained in EC (96.26% in EO) when fusing power spectrum information from parieto-occipital (centro-parietal in EO) regions. Taken together, these results suggest that the functional connectivity patterns represent effective features for improving EEG-based biometric systems.
Mapping the trajectory of organizational leadership development: A bibliometric analysis

This research analyzes scholarly literature on the topic of leadership development as it relates to the fields of business and management. The researchers conducted a comprehensive search of the Web of Science database covering a 15-year time frame using the PRISMA methodology, ultimately yielding 1017 documents for analysis. Biblioshiny, and VOSviewer were used for quantitative analysis and data visualization, respectively. The study provides valuable information, such as the most influential authors and their nations, the most important keywords, and the most cited scholarly works in the topic. In addition, it reveals active research areas and literature gaps that point to potential new lines of inquiry. In highlighting the managerial and structural consequences of enhancing leadership within companies, the findings provide a useful basis for policymakers and practitioners.