bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of the Effectiveness of the Process of Undergraduate Health and Physical Education Program by the CIPP Model
Authors: Iqbal Zafar , Khan Rahim , Wadood Abdul
Published: September 2022

This study aimed to evaluate the process (instruction, activities, and assessment methods) of undergraduate health and physical education (HPE) programs in different colleges of the Khyber Pakhtunkhwa province by employing the CIPP model. A quantitative research technique was used to record the students' responses about the effectiveness of the process through questionnaires. Respondents showed mixed views about different parameters of the process. Students were satisfied with the use of audiovisual aids during instruction, promotion of critical thinking, social and moral values by instruction methods, class discussion, participation of teachers and students in physical activities, and instructions before a specific activity. A significant proportion of the respondents, however, believed that teachers did not use diverse teaching strategies and effective mediums of instruction. Similarly, negative responses were observed about rehabilitation techniques, the role of mentor ship in stimulating students' interest, and the regular arrangement of physical activities. Evaluation of the HPE program by the CIPP model identified some demerits in the process which need improvement to make the program more effective.
States obligations on Terrorism and Anti-Terrorism laws in Pakistan: An Overview
Authors: Arif Sardar M.A. Waqar Khan , Shahbaz Saqib , Bannian Bushra
Published: September 2022

The growing debate on terrorism is sensitive, and its effects are dreadful. States are under international legal obligations to respect, protect and fulfill people's basic human rights without discrimination and distinction.States are required to remove the effects of terrorism, which are outrageous and alarming. In this context, this article focuses on terrorism and International law. It aims to analyze provisions of international law pertaining to terrorism and to present ways to establish universal peace. It analyses the relevant United Nations (UN) resolution sand international legal documents to evaluate the States' obligations. It also analyses the legislation of Pakistan on terrorism as a case study for identifying the lacuna's and loopholes in the existing legal framework. Based on the legal framework, the paper elaborates on the obligations of states in relation to terrorism. It argues that laws on terrorism in Pakistan are sufficient. However, there is needed to implement laws effectively in order to meet growing challenges. There is still a need for improvement in the implementation mechanism pertaining to counter-terrorism measures taken by Pakistan. The line of argument is that states must conform to norms of international law in practical terms, and universal peace can only be established if social justice is guaranteed and human rights protection at every level is ensured.
Linguistic Analysis of the Gender Representation in Jane Austen's Novel, Persuasion, Using Systemic Functional Grammar
Authors: Ishtiaq Muhammad , Gul Nasim , Hayat Qaisar
Published: September 2022

This work explores the relationship between linguistic structures and socially constructed meanings in a text. It employs the transitivity framework of Halliday in order to expose the ideological position and power relations in a classic literary work, especially from a systemic functional perspective. It also tries to find common ground between systemic functional grammar and a narrative. The presence of certain recurring linguistic features in a literary text gives insights into how such linguistic features create meanings and effects. The grammatical structures in a literary work are suggestive of some special meanings and effects. Consequently, in-depth analyses of these grammatical structures in this classic literary work lead to a more realistic understanding of the conventional gender role assigned to the two main characters (the heroin and the protagonist) of Jane Austen's last finished novel Persuasion.
Potential of Islamic Tourism in District Mansehra, Khyber Pakhtunkhwa Pakistan: A Case Study of Naukot Monument Attributed to Sayyid Ali Hamadani
Authors: Hameed Abdul , Arif Anas Mahmud , Anwar Adnan
Published: September 2022

Mansehra, one of the most important districts of Hazara Division, is generally known for its natural landscape and pleasant weather that attract thousands of visitors from across the country and abroad every year.Its geographic location adds more value to its potential as a tourist destination. Located on the ancient and modern trade routes, Mansehra has been receiving and transmitting cultural flow from muti directions since early historical times. With the results, the region has witnessed the emergence, development and fall of various religious moments, including Buddhism, Hinduism, Islam, Sikhism and Christianity. Material evidence of these religious practices can still be noticed in the form of stupas, temples, mosques, shrines, Gurudu waras and churches. The present paper is an attempt to highlight the historical and religious significance of the Muslim period sites with special reference to the Naukot monument and its potential for pilgrimage tourism.
Cyber Stalking: Sociological and Psychological Perspective
Authors: Bibi Zainab , Abbasi Ambreen
Published: September 2022

Cyber stalking is the intimidation or threat to cause distress by blackmailing through internet.Cyber stalking is considered to be a threat to the right to privacy while abusing freedom of information. To discuss the subject issue author has used empirical study methodology. The first part provides an explanation of cyber-stalking in detail while discussing its factors, classification and impacts. In the second part, while discussing the impacts of cyber-stalking, then further discussion provides glimpses of sociological and psychological perspectives and causes of cyber-stalking. Finally, the discussion concluded with recommendations intended to provide a way forward for future research.
Construction of Femininity and Consumer Culture in American Women's Magazines: A Qualitative Study about Good Housekeeping
Authors: Liu Guifang , Malik Muhammad Abid
Published: September 2022

Good housekeeping is one of the mainstream American women's magazines. Targeting primarily the middle-class married women, it gives guidance and suggestions on beautifying appearance, latest fashions,housekeeping, cooking, and child-rearing. Using 24 issues of Good Housekeeping published in 2016-2017, this study explores what kind of femininity is constructed in this magazine. The study uses thematic analysis and interpretive textual analysis as the key methodologies. Furthermore, it explores the overlapping relationships between the magazine, femininity, and consumer culture. The article finds that femininity constructed in those two years of Good Housekeeping tends to be conservative, which is idealized and perfected in the magazine.The magazine has maintained its long-established and conservative style. It is established on a commercialized base and advocates that ideal femininity is to be gained through "purchasing." The conservative femininity constructed by the magazine is under the manipulation of modern patriarchy and consumerism.
Coverage of Health News in the English-Language Newspapers of Pakistan: A Case Study of Dawn and The News
Authors: Adnan Muhammad , Marwan Amir Hamza , Anwar Mussarat
Published: September 2022

This research study investigates health news coverage in the two mainstream English-language newspapers of Pakistan – Dawn and The News – to understand how they covered it. The researchers have focused on the frequency of published news stories, contributors of the news items; nature of coverage;contextualization and use of jargon in the published stories. The researchers applied the Quantitative Content Analysis to answer all the outstanding inquiries of this research project. Based on the data collected in February2019, the researchers found that both the newspapers played down the health-related coverage in their pages –besides relying on the same contributors to report it. The findings revealed that The News needs to bring more diversity in its coverage of different issues related to health, while Dawn needs to work on the language – by avoiding jargon. The Gatekeeping Theory guides the findings.
Citizenship Characteristics and its Education at University Campuses: A Viewpoint of University Students
Authors: Rehman Zia Ur , Naz Sadia
Published: September 2022

Civic education is an imperative as well as a fundamental tool for developing human and social capital around the world. Many institutes are offering civic education, and numerous studies have been conducted in the international context. Still, citizenship education in higher education in Pakistan has been the least researched area, and henceforth it has not been explored how university students rate themselves regarding knowledge and preparation of nationality; and in what way universities propose programs to inculcate civic attributes among graduates. Therefore, to investigate this problem, the current study was conducted with the objectives; of exploring students' views about the characteristics of good citizenship; to examine the role of universities in developing citizenship. Four focus groups from four universities, i.e. one focus group from each university/each focus group consisting of 9 respondents, were taken as the sample of the study. Data was collected by using a semi-structured interview protocol (i.e. a focus group questionnaire) and analyzed by thematic analysis. Findings exposed that the respondents were significantly in favor of improving social responsibility, civic skills,morality/honesty/courtesy, broad mindedness, civic participation, accountability/critical thinking,patriotism/obedience, and reliability (promise-keeping). The group's discussion indicated mixed ideas about the role of universities in developing and maintaining citizenship services at university campuses.
Structural, Morphological and Optical Study of Manganese Doped FeS (Mackinawite) Nanostructures by Chemical Bath Deposition (CBD) Technique
Authors: Yaqoob Sufian , Hasan Noor ul , Khalid Sadia , Akhtar Muhammad Saeed
Published: September 2022

Abstract: Fe1-xMnxS thin films with concentration x=0.02, 0.04, 0.06, 0.08, 0.1 have been deposited on glass substrates by a simple Chemical Bath Deposition (CBD) method at 90 oC. The X-ray Diffraction analysis of deposited thin films revealed the growth of mono-phasic mackinawite (FeS) structure with crystallite size in the range from 4.06 to 5.95 nm as a function of manganese concentrations. The other structural parameters like stacking faults, dislocation density and lattice strain affirmed the improvement in crystal structure and phase stability in manganese doped FeS thin films. Scanning Electron Micrographs depicted the growth of nano-flakes and nano-flowers in case of pure FeS thin films while for manganese doped iron sulfide thin films, homogeneity of the deposited material was observed to improve with distinct boundaries of almost spherical nanostructures. The direct energy band gap of FeS mono-phasic thin films was observed to decrease from 2.23 to 1.89 eV as the concentration of manganese increases in host lattice. The prepared thin films with tunable optical properties would have potential applications in energy conversion and optoelectronic devices.
Developing, evaluating and scaling learning agents in multi-agent environments
Authors: Gemp Ian , Anthony Thomas , Bachrach Yoram , Bhoopchand Avishkar , Bullard Kalesha , Connor Jerome , Dasagi Vibhavari , De Vylder Bart , Duéñez-Guzmán Edgar A. , Elie Romuald , Everett Richard , Hennes Daniel , Hughes Edward , Khan Mina , Lanctot Marc , Larson Kate , Lever Guy , Liu Siqi , Marris Luke , McKee Kevin R. , Muller Paul , Pérolat Julien , Strub Florian , Tacchetti Andrea , Tarassov Eugene , Wang Zhe , Tuyls Karl
Published: September 2022

The Game Theory & Multi-Agent team at DeepMind studies several aspects of multi-agent learning ranging from computing approximations to fundamental concepts in game theory to simulating social dilemmas in rich spatial environments and training 3-d humanoids in difficult team coordination tasks. A signature aim of our group is to use the resources and expertise made available to us at DeepMind in deep reinforcement learning to explore multi-agent systems in complex environments and use these benchmarks to advance our understanding. Here, we summarise the recent work of our team and present a taxonomy that we feel highlights many important open challenges in multi-agent research.
A Multicenter Study of 2-year Outcomes Following Hyperthermia Therapy with Mitomycin C in Treating Non-Muscle Invasive Bladder Cancer: HIVEC-E
Authors: Tan Wei Phin , Plata Bello Ana , Garcia Alvarez Carlos , Guerrero-Ramos Félix , González-Padilla Daniel A. , Nzeh Cajetan , Manuel de la Morena Jose , de Torres Ignacio Gonzalez Valcarcel , Hendricksen Kees , Díaz Goizueta Francisco Javier , Del Álamo Julio Fernandez , Chiancone Francesco , Fedelini Paolo , Poggio Massimiliano , Porpiglia Francesco , Gonzalo Rodríguez Victoria C. , Torres Javier Montero , Wilby Daniel , Robinson Richard , Sousa-Escandón Alejandro , Mata Juan León , Pontones Moreno Jose L. , Molina Francisco Delgados , Adriazola Semino Miguel A. , Stemberger Andrew T. , Escudero Jesús Calleja , Redorta Joan Palou , Tan Wei Shen
Published: September 2022

INTRODUCTION:

High grade, non-muscle invasive bladder cancer (NMIBC) is usually treated with intravesical Bacillus Calmette–Guérin. Chemohyperthermia therapy (CHT) may be a novel alternative therapy for the treatment of NMIBC.

OBJECTIVE:

To evaluate the recurrence-free survival (RFS) of patients treated with CHT using the Combat bladder recirculation system (BRS) for NMIBC.

METHODS:

This was a prospective multi-institutional study of 1,028 consecutive patients with NMIBC undergoing CHT between 2012 and 2020. A total of 835 patients were treated with CHT with Mitomycin C (MMC). Disease was confirmed on transurethral resection of bladder tumor (TURBT) prior to starting CHT. Follow-up included cystoscopy and subsequent TURBT if recurrence/progression was suspected. The primary endpoint was RFS. Secondary endpoints were progression-free survival (PFS) and adverse events from CHT.

RESULTS AND LIMITATIONS:

Median follow up was 22.4 months (Interquartile range (IQR): 12.8 –35.8). Median age was 70.4 years (IQR: 62.1 –78.6). A total of 557 (66.7%), 172 (20.6) and 74 (8.9%) of patients were classified to BCG naïve, BCG unresponsive and BCG failure, respectively. The RFS at 12 months and 24 months for BCG naïve was 87.6% (95% CI 85.0% - 90.4%) and 75.0% (95% CI 71.3% - 78.8%), respectively. The RFS at 12 months and 24 months for BCG unresponsive cohort was 78.1% (95% CI 72.0% - 84.7%) and 57.4% (95% CI 49.7% - 66.3%), respectively. The RFS at 24 months for the BCG unresponsive cohort for CIS with/without papillary disease and papillary only disease were 43.6% (95% CI 31.4% –60.4%) and 64.5% (95% CI 55.4% - 75.1%), respectively. Minor adverse events occurred in 216 (25.6%) patients and severe events occurred in 17 (2.0%) patients.

CONCLUSIONS:

CHT with MMC using the Combat BRS is effective in the medium term and has a favorable adverse event profile.
Adjuvant Chemotherapy Plus Radiotherapy versus Chemotherapy Alone for Locally Advanced Bladder Cancer after Radical Cystectomy
Authors: Ernandez John , Kaul Sumedh , Fleishman Aaron , Korets Ruslan , Chang Peter , Wagner Andrew , Kim Simon , Bellmunt Joaquim , Kaplan Irving , Olumi Aria F. , Gershman Boris
Published: September 2022

BACKGROUND:

Survival with locally advanced bladder cancer (LABC) following radical cystectomy (RC) remains poor. Although adjuvant chemotherapy (AC) is standard of care, one small, randomized trial has suggested a potential survival benefit when combined with post-operative radiotherapy (PORT).

OBJECTIVE:

We examined the association of AC + PORT with overall survival (OS) in patients with LABC after RC.

METHODS:

Using a prior phase 2 trial to inform design, we conducted observational analyses to emulate a hypothetical target trial of patients aged 18–79 years with pT3-4 Nany M0 or pTany N1-3 M0 urothelial bladder carcinoma following RC who were treated with AC (multiagent chemotherapy within 3 months of RC) with or without PORT (≥45 Gy to the pelvis) from 2006–2015 in the NCDB. Patients who received preoperative chemotherapy or radiotherapy were excluded. The associations of treatment with OS were evaluated using multivariable Cox regression.

RESULTS:

1,684 patients were included, with 66 receiving AC + PORT and 1,618 AC alone. Compared to patients treated with AC alone, those treated with AC + PORT were more likely to have pT4 disease (52% vs 26%; p < 0.01), positive surgical margins (44% vs 17%; p < 0.01), and be treated at a non-academic facility (75% vs 53%; p < 0.01). Crude 5-year OS was 19% for AC + PORT versus 36% for AC alone ( p = 0.01). Adjusted 5-year OS was 33% for AC + PORT versus 36% for AC alone ( p = 0.49). After adjusting for baseline characteristics including pathologic features, AC + PORT was not associated with improved OS compared to AC alone (HR 1.11; 95% CI 0.82–1.51).

CONCLUSIONS:

Although infrequently utilized, the addition of radiotherapy to AC is not associated with improved OS in LABC. These results highlight the need for prospective trials to better define the potential benefits from PORT with regard to symptomatic progression and oncologic outcomes.
Randomness extraction in computability theory
Authors: Cenzer Douglas , Porter Christopher P.
Published: September 2022

In this article, we study a notion of the extraction rate of Turing functionals that translate between notions of randomness with respect to different underlying probability measures. We analyze several classes of extraction procedures: (1) a class that generalizes von Neumann’s trick for extracting unbiased randomness from the tosses of a biased coin, (2) a class based on work of by Knuth and Yao (which more properly can be characterized as extracting biased randomness from unbiased randomness), and (3) a class independently developed by Levin and Kautz that generalizes the data compression technique of arithmetic coding. For the first two classes of extraction procedures, we identify a level of algorithmic randomness for an input that guarantees that we attain the extraction rate along that input, while for the third class, we calculate the rate attained along sufficiently random input sequences.
Identification of informational and probabilistic independence by adaptive thresholding
Authors: Li Kuo , Wang Aimin , Wang Limin , Fan Hangqi , Zhang Shuai
Published: September 2022

The independence assumptions help Bayesian network classifier (BNC), e.g., Naive Bayes (NB), reduce structure complexity and perform surprisingly well in many real-world applications. Semi-naive Bayesian techniques seek to improve the classification performance by relaxing the attribute independence assumption. However, the study of dependence rather than independence has received more attention during the past decade and the validity of independence assumptions needs to be further explored. In this paper, a novel learning technique, called Adaptive Independence Thresholding (AIT), is proposed to automatically identify the informational independence and probabilistic independence. AIT can respectively tune the network topologies of BNC learned from training data and testing instance under the framework of target learning. Zero-one loss, bias, variance and conditional log likelihood are introduced to compare the classification performance in the experimental study. The extensive experimental results on a collection of 36 benchmark datasets from the UCI machine learning repository show that AIT is more effective than other learning techniques (such as structure extension, attribute weighting) and helps make the final BNCs achieve remarkable classification improvements.
LAMB: A novel algorithm of label collaboration based multi-label learning
Authors: Zhang Yi , Zhang Zhecheng , Chen Mingyuan , Lu Hengyang , Zhang Lei , Wang Chongjun
Published: September 2022

Exploiting label correlation is crucially important in multi-label learning, where each instance is associated with multiple labels simultaneously. Multi-label learning is more complex than single-label learning for that the labels tend to be correlated. Traditional multi-label learning algorithms learn independent classifiers for each label and employ ranking or threshold on the classification results. Most existing methods take label correlation as prior knowledge, which have worked well, but they failed to make full use of label dependency. As a result, the real relationship among labels may not be correctly characterized and the final prediction is not explicitly correlated. To address these problems, we propose a novel high-order multi-label learning algorithm of Label collAboration based Multi-laBel learning (LAMB). With regard to each label, LAMB utilizes collaboration between its own prediction and the prediction of other labels. Extensive experiments on various datasets demonstrate that our proposed LAMB algorithm achieves superior performance over existing state-of-the-art algorithms. In addition, one real-world dataset of channelrhodopsins chimeras is assessed, which would be of great value as pre-screen for membrane proteins function.
A multiple hierarchical clustering ensemble algorithm to recognize clusters arbitrarily shaped
Authors: Sun Yuqin , Wang Songlei , Huang Dongmei , Sun Yuan , Hu Anduo , Sun Jinzhong
Published: September 2022

As a research hotspot in ensemble learning, clustering ensemble obtains robust and highly accurate algorithms by integrating multiple basic clustering algorithms. Most of the existing clustering ensemble algorithms take the linear clustering algorithms as the base clusterings. As a typical unsupervised learning technique, clustering algorithms have difficulties properly defining the accuracy of the findings, making it difficult to significantly enhance the performance of the final algorithm. AGglomerative NESting method is used to build base clusters in this article, and an integration strategy for integrating multiple AGglomerative NESting clusterings is proposed. The algorithm has three main steps: evaluating the credibility of labels, producing multiple base clusters, and constructing the relation among clusters. The proposed algorithm builds on the original advantages of AGglomerative NESting and further compensates for the inability to identify arbitrarily shaped clusters. It can establish the proposed algorithm’s superiority in terms of clustering performance by comparing the proposed algorithm’s clustering performance to that of existing clustering algorithms on different datasets.
An improvement of FDR for edge detection by applying EM method
Authors: Kim Eun-Gyoung , Kim Sung-Ho
Published: September 2022

In building a graphical model, accuracy in edge detection for the model structure is crucial for the quality of the model. We explored methods for improvement of false discovery rate(FDR) by devising an estimation procedure which is more data sensitive under some condition. The estimation is made by applying an EM method where the parameters include the density function under the null hypothesis (no edge) and the location parameters of the density functions under the alternative hypothesis (presence of edge). Our method is compared favorably with a most popular FDR tool in numerical experiments. We applied our method for analysing gene data of 800 genes and built a network of vector autoregressive model for the data.
Decision analysis of rationalizable strategies in non-zero-sum multi-payoff games
Authors: Eisenstadt-Matalon Erella , Moshaiov Amiram
Published: September 2022

This paper concerns multi-criteria decision-making in a non-cooperative situation between two Decision Makers (DMs), where each of the DMs (players) has self-conflicting objectives. This situation is modeled as a non-zero-sum Multi-Objective Game (nzs-MOG). In the considered case, selecting a strategy depends on the objective preferences of the DM and the inherent uncertainty about the preferences of the other player. In contrast to traditional studies on such a situation, which fail to consider the strategies’ performance trade-offs, here a set of rationalizable strategies is revealed for each of the players and their associated performance trade-offs are exposed and analyzed. Obtaining these strategies is done by an extension of the (worst-case) rationalizability solution concept from zero-sum MOGs to the considered general case of nzs-MOGs. In view of the aforementioned uncertainty about the other player, evaluating the rationalizable strategies involves comparisons between sets of payoff vectors. This causes a difficulty, when trying to analyze the alternative strategies by traditionalmulti-criteria decision-analysis techniques in which each alternative solution is commonly associated with only one payoff vector. To circumvent this difficulty, a technique is suggested, which transforms the set of payoff vectors of each strategy into a representative vector. To demonstrate the proposed technique, a nzs-MOG is devised and strategy analysis and selection is demonstrated, for each of the players, using the Analytical Hierarchy Process (AHP).
Magnetic force prediction of hybrid magnet with Halbach array using generalized regression neural network optimized by a modified aquila optimizer
Authors: Hu Kun , Jiang Hao , Wang Shuang , Li Fei
Published: September 2022

This paper addresses the balancing of global and local searches in the recently proposed AO (Aquila Optimizer) algorithm. The original random algorithm is modified using normal-distribution parameters, and an adaptive function represented by a Weibull function is added to the motion law of the predator. Sixteen benchmark functions are used to test the improved algorithm against several recently developed algorithms. The results show that the accuracy and convergence speed of the modified algorithm are improved while the advantages of the original algorithm are retained. In solving the problems of a complex calculation and limited solution in the design of a hybrid electromagnetic structure based on a Halbach array, a prediction model based on the improved algorithm and generalized regression neural network (GRNN) is designed for improved prediction accuracy of the GRNN. Thirty groups of data are obtained using Ansoft, and the prediction accuracy of the improved GRNN is verified using the data. The mean squared error (MSE) of normalized prediction results reaches 0.1404. The improved prediction model has the prediction error less than 10% and its performance is better than the RBF and the KCV-GRNN.
Lifetime evaluation and extension of wind turbines based on big data
Authors: Su Jun , Fang Chao , Zhu Xinglong , Li Zhi , Sun Meng , Chen Jiaying
Published: September 2022

Although the global wind energy industry has made considerable progress in recent years, wind turbines suffer from frequent failures since the systems are complicated and the working conditions are far from being satisfactory. For the wind turbines to function well, it is imperative to study the overall status of the wind turbine unit, evaluate the performance of the wind farm, apply intelligent operation and maintenance technology, and improve operation and maintenance strategies on an on-going basis, all of which are based on the operation data of the unit. This paper focuses on the evaluation and extension of the lifetime of wind turbines. Based on relevant knowledge and theories from previous studies, an evaluation method based on big data was designed to do the evaluation, and the results of which were verified by real cases. With the duration of catastrophic failures taken into account, the proposed life prediction algorithm was proved to be effective. If the bearing runs for 34 days, the actual remaining life of wind turbines is 0.2 days. The number predicted for LRM is 0.8 days and that predicted for ILRM is 0.31 days. Compared with LRM, the prediction for ILRM is much more accurate.
Characteristic sets profile features: Estimation and application to SPARQL query planning
Authors: Heling Lars , Acosta Maribel
Published: September 2022

RDF dataset profiling is the task of extracting a formal representation of a dataset’s features. Such features may cover various aspects of the RDF dataset ranging from information on licensing and provenance to statistical descriptors of the data distribution and its semantics. In this work, we focus on the characteristics sets profile features that capture both structural and semantic information of an RDF dataset, making them a valuable resource for different downstream applications. While previous research demonstrated the benefits of characteristic sets in centralized and federated query processing, access to these fine-grained statistics is taken for granted. However, especially in federated query processing, computing this profile feature is challenging as it can be difficult and/or costly to access and process the entire data from all federation members. We address this shortcoming by introducing the concept of a profile feature estimation and propose a sampling-based approach to generate estimations for the characteristic sets profile feature. In addition, we showcase the applicability of these feature estimations in federated querying by proposing a query planning approach that is specifically designed to leverage these feature estimations. In our first experimental study, we intrinsically evaluate our approach on the representativeness of the feature estimation. The results show that even small samples of just 0.5 % of the original graph’s entities allow for estimating both structural and statistical properties of the characteristic sets profile features. Our second experimental study extrinsically evaluates the estimations by investigating their applicability in our query planner using the well-known FedBench benchmark. The results of the experiments show that the estimated profile features allow for obtaining efficient query plans.
12-lead ECG signal processing and atrial fibrillation prediction in clinical practice
Authors: Hsieh Jui-Chien , Shih Hsing , Xin Ling-Lin , Yang Chung-Chi , Han Chih-Lu
Published: September 2022

BACKGROUND: Because clinically used 12-lead electrocardiography (ECG) devices have high falsepositive errors in automatic interpretations of atrial fibrillation (AF), they require substantial improvements before use. OBJECTIVE: A clinical 12-lead ECG pre-processing method with a parallel convolutional neural network (CNN) model for 12-lead ECG automatic AF recognition is introduced. METHODS: Raw AF diagnosis data from a 12-lead ECG device were collected and analyzed by two cardiologists to differentiate between true- and false-positives. Using a stationary wavelet transform (SWT) and independent component analysis (ICA) noise reduction was conducted and baseline wandering was corrected for the raw signals. AF patterns were learned and predicted using a parallel CNN deep learning (DL) model. (1) The proposed method alleviates the decreased ECG QRS amplitude enhances the signal-to-noise ratio and clearly shows atrial and ventricular activities. (2) After training, the CNNbased AF detector significantly reduced false-positive errors. The precision of AF diagnosis increased from 77.3% to 94.0 ± 1.5% as compared to ECG device interpretation. For AF screening, the model showed an average sensitivity of 96.8 ± 2.2%, specificity of 79.0 ± 5.8%, precision of 94.0 ± 1.5%, F1-measure of 95.2 ± 1.0%, and overall accuracy of 92.7 ± 1.5%. CONCLUSIONS: The method can bridge the gap between the research and clinical practice The ECG signal pre-processing and DL-based AF interpretation can be rapidly implemented clinically.
A deep learning-based method for cervical transformation zone classification in colposcopy images
Authors: Cao Yuzhen , Ma Huizhan , Fan Yinuo , Liu Yuzhen , Zhang Haifeng , Cao Chengcheng , Yu Hui
Published: September 2022

BACKGROUND: Colposcopy is one of the common methods of cervical cancer screening. The type of cervical transformation zone is considered one of the important factors for grading colposcopic findings and choosing treatment. OBJECTIVE: This study aims to develop a deep learning-based method for automatic classification of cervical transformation zone from colposcopy images. METHODS: We proposed a multiscale feature fusion classification network to classify cervical transformation zone, which can extract features from images and fuse them at multiple scales. Cervical regions were first detected from original colposcopy images and then fed into our multiscale feature fusion classification network. RESULTS: The results on the test dataset showed that, compared with the state-of-the-art image classification models, the proposed classification network had the highest classification accuracy, reaching 88.49%, and the sensitivity to type 1, type 2 and type 3 were 90.12%, 85.95% and 89.45%, respectively, higher than the comparison methods. CONCLUSIONS: The proposed method can automatically classify cervical transformation zone in colposcopy images, and can be used as an auxiliary tool in cervical cancer screening.
The role of resilience in the work-life interface: A systematic review
Authors: Bernuzzi Chiara , Sommovigo Valentina , Setti Ilaria
Published: September 2022

BACKGROUND: In an increasingly competitive marketplace, workers struggle to find a good balance between work and personal life. Difficulties in fulfilling the demands arising from these different domains may undermine employees’ well-being and job-related outcomes, thereby, impairing organizational productivity. OBJECTIVE: Does resilience play a relevant role in relation to work-life interface? And, if so, how is resilience related to its three facets (i.e., work-life conflict, enrichment, and balance)? To answer these questions, the current paper systematically reviews studies analysing the role of resilience in the work-life interface. METHODS: A key terms literature search was performed using multiple electronic databases (i.e., Scopus, PsycINFO, Web of Science, PubMed) without setting any publication date limitation. The review process followed the international PRISMA statement guidelines. A quality assessment was conducted using the Mixed Methods Appraisal Tool. RESULTS: A total of 26 eligible papers published between 2009 and 2020 were included. Among these, 6 employed a qualitative design, while 20 studies adopted a quantitative design mostly examining resilience as antecedent. Data were predominantly collected in the healthcare sector. Resilience was mainly analysed in relation to work-life conflict. The most commonly used theoretical framework was Conservation of Resources theory. CONCLUSIONS: Overall, resilience was negatively associated with work-life conflict and positively related to both work-life balance and enrichment. A positive work-life balance can promote resilience, but resilience can also help workers to balance work and life. Additionally, resilience can protect from the negative effects of both work-life imbalance and work-life conflict on workers’ health and job-related outcomes.
The effects of a 6-month mandatory military police academy training on recruits’ physical fitness
Authors: Barbosa Wélere G. , Saint Martin Daniel R. , Soares Edgard de Melo Keene von Koenig Soares , Fontana Keila Elizabeth , Lan Fan-Yun , Kales Stefanos N. , Molina Guilherme E. , Porto Luiz Guilherme G.
Published: September 2022

BACKGROUND: Physical fitness for health and professional performance play important roles in police workforce considering that policing is a dangerous job, associated with high physical demands. OBJECTIVES: (1) To evaluate the effects of a 6-month course of police academy training on health-related physical fitness (HRPF) of military police recruits. (2) To investigate whether recruits’ HRPF still met the academy entry standards after an unsupervised 7-month period prior to academy. METHODS: We conducted an observational and longitudinal study with 219 male police recruits (aged 25.5±3.6 years; BMI of 24.4±2.5 kg/m2). HRPF parameters included the Cooper 12-min running test for cardiorespiratory fitness (CRF), curl-ups, pull-ups and push-ups for muscle strength/endurance which were evaluated 3 times: 7 months prior to academy course and pre- and post-academy training period. RESULTS: Participants maintained optimal age-related HRPF during the unsupervised period prior to academy. After academy training upon graduation, all HRPF parameters further increased an average of 7.7 to 69.0% (p < 0.001; calculated Cohen’s d effect size ≥0.95). CRF was the only HRPF that improved less than 10% after the academy course. CONCLUSIONS: Police recruits that had passed the application fitness standards maintained their HRPF prior to academy, and all their HRPF parameters increased after a 6-month academy training period which was not primarily focused on exercise training. Among all components of HRPF, CRF appears to be the most challenging one to improve among police recruits. Our findings suggest that regular training with minimum physical standards could be potentially beneficial to police officers’ health and career longevity.
Frequency of working at home, body mass index, and productivity in Japanese office workers: A cohort study
Authors: Nakatsuka Kiyomasa , Murata Shunsuke , Oka Tomohiro , Tsuboi Yamato , Saeki Kenta , Tezuka Masato , Ono Rei
Published: September 2022

BACKGROUND: Since the start of the COVID-19 pandemic, the number of people working at home has grown significantly. OBJECTIVE: This cohort study aimed to investigate whether the frequency of working at home was associated with changes in body mass index (BMI) and productivity from 2018 to 2020. METHOD: Frequency of working at home was self-reported. Participants were classified into three groups based on mean frequency of working at home per week (no working at home: ≦ 0.5 days, low frequency: 0.5 to 2.5 days, and high frequency: >2.5 days). Productivity was measured using a numerical rating scale, and BMI was calculated using height and weight. Changes in BMI and productivity were calculated by subtracting 2018 data from 2020 data. Linear regression analysis was performed by considering BMI and productivity change as outcomes and frequency of working at home as explanatory variable. RESULTS: BMI change in the high frequency group was significantly smaller than in the group that did not work at home (crude; coefficient: –0.27; 95% CI: –0.55––0.01, adjusted; coefficient: –0.30; 95% CI: –0.60––0.01). Frequency of working at home was not associated with productivity change. CONCLUSION: Working at home may be a solution for preventing BMI from increasing significantly.
What affects musculoskeletal risk in nursing assistants and orderlies?
Authors: Oliver-Hernández Coral , Li Shimeng , Astudillo Raúl Jiménez , Rodríguez Inmaculada Mateo
Published: September 2022

BACKGROUND: There are many musculoskeletal disorders in staff members at health centres, given the specific characteristics of their work. OBJECTIVE: The objective was to analyse the postural risk of patient handling tasks performed by nursing assistants and orderlies, as well as task factors, individual or organisational, that may be associated with increased postural risk. METHOD: This is a cross-sectional observational study. Analysis was done on 170 postures in five different tasks performed by 39 participants at three hospitals in Andalusia (Spain). The questionnaires collected sociodemographic variables, the task done, and REBA were used for assessment of postural risk. RESULTS: Overall the average REBA score was 9.0±2.4. Moving the patient to the head of the bed was the task with the highest risk (9.8). Handling involving more than two participants at once increased postural risk. Using mechanical aids were associated with high risk in the legs. Logistic regression analyses showed that age, stature, and not having adjustable beds available were associated with postural risk (p < 0.05). CONCLUSION: Health centre staff perform many tasks with high musculoskeletal disorder risk. Age, stature of the participants, and adjustment of bed height were associated with postural risk.
Healing the wounds of workplace bullying: Evaluating mental health and workplace participation among victims seeking treatment for common mental disorders
Authors: Aarestad Sarah Helene , Harris Anette , Hjemdal Odin , Gjengedal Ragne G. H. , Osnes Kåre , Sandin Kenneth , Reme Silje E. , Hannisdal Marit , Einarsen Ståle Valvatne
Published: September 2022

BACKGROUND: Victims of workplace bullying represent a group characterised by severe negative health complaints at risk of losing their foothold in working life. To date, very few studies have investigated the effect of psychological treatment of the health-related problems often facing victims of bullying. OBJECTIVE: The aim was to investigate if victims of workplace bullying suffering from common mental disorders (CMD) benefit from clinical treatment for their mental health problems at an outpatient clinic treating patients using Metacognitive or Cognitive Behavioural Therapy with work-focus. Criteria were symptom reduction and change in workplace participation. Comparisons were made between the victims of workplace bullying with CMD, a wait-list control group consisting of patients who had also been exposed to bullying yet now awaiting treatment, and other patients not exposed to bullying. METHODS: The sample comprised of 405 patients from an outpatient clinic in Norway. The study used a naturalistic observational design and data was collected pre-treatment and post-treatment. RESULTS: The results showed the treatment to be effective in symptom reduction for victims of bullying to a similar degree as patients otherwise not exposed to bullying. Even more, victims receiving treatment had a larger improvement compared to the wait-list control group (p < 0.001). Yet, among patients on sick leave pre-treatment, fewer victims of bullying were fully working by the end of treatment compared to the patients not exposed to workplace bullying. CONCLUSION: The findings provide ground for optimism for this treatment as an efficient way of dealing with the aftermath of workplace bullying.
Pengaruh ukuran perusahaan, struktur aset, dan return on assets terhadap struktur modal
Authors: Astuty Risma Widya
Published: September 2022

Tujuan dari penelitian untuk mengetahui pengaruh ukuran perusahaan, struktur aset, dan return on assets terhadap struktur modal perusahaan subsektor hotel, restoran, dan pariwisata yang rutin listing di Bursa Efek Indonesia. Jenis penelitian adalah penelitian kuantitatif. Teknik pengambilan sampel dalam penelitian ini adalah teknik purposive  sampling. Sampel dalam penelitian ini adalah laporan keuangan  perusahaan  hotel, restoran, dan pariwisata  yang rutin listing di Bursa Efek Indonesia  tahun 2013-2018. Penelitian ini menggunakan data sekunder yaitu laporan keuangan tahunan. Teknik analisis menggunakan analisis regresi linier berganda. Hasil penelitian  menunjukkan bahwa struktur perusahaan berpengaruh positif signifikan terhadap struktur modal, struktur aset berpengaruh negatif signifikan terhadap struktur modal, dan return on assets berpengaruh negatif tidak signifikan terhadap struktur modal.
A prototipagem rápida na engenharia de manutenção
Authors: Lima Leandro Jose Barbosa
Published: September 2022

Dentro da indústria, a manutenção é um dos departamentos com maior complexidade, sendo considerado um setor que possui grande impacto nos resultados organizacionais e na competitividade da empresa. Nesse contexto, sabe-se que a quebra de uma peça, pode gerar grandes problemas ao processo produtivo, uma vez que a parada na linha de produção, gera atrasos, aumento dos custos e faz com que a organização perca clientes e posição perante o mercado. Por este motivo, empregam-se várias técnicas de manutenção, visando a prevenção e redução destas paradas. Ante ao exposto, o presente artigo tem como questão norteadora: como a prototipagem rápida pode ser aplicada à engenharia de manutenção? Desta forma, adotou-se como objetivo investigar sobre a prototipagem rápida, a fim de verificar de que forma a manutenção, no contexto discutido aqui, pode se beneficiar dessa tecnologia. Para isso, adotou-se como metodologia a revisão bibliográfica. Como resultados, verificou-se que, dentre os diversos tipos de manutenção, a prototipagem rápida pode ser uma alternativa, pois ela possibilita a produção de peças dentro da própria empresa, o que diminui os custos de compra e de estocagem, bem como otimiza o espaço da fábrica, empresa ou indústria. Ela, ainda, pode ser utilizada na recuperação de partes desgastadas. Por fim, verifica-se que a aplicação da prototipagem rápida na manutenção já é possível em casos específicos de negócio, entretanto, deve-se levar em consideração alguns fatores, como: o custo da máquina; treinamento de um operador; matéria prima; e disponibilidade de uma biblioteca dos desenhos em STL (Standard Triangle Language).
Exploration behaviour and foraging strategies in Mediterranean blue tits
Authors: Velasco A. C. , Ferrer E. S. , Sanz J. J.
Published: September 2022

Animal behaviour is potentially a mechanism of individual diet specialization. To explore this possibility we assessed exploratory behaviour (EB) and foraging data for a population of blue tits Cyanistes caeruleus. Our results suggest that: 1) foraging differs between sexes; 2) the prey type selected by females depends on the provisioning rates of their mate, and adjustment of this prey-choice differs between EB phenotypes; and 3) foraging behaviour in males shows a trend towards linkage to their EB phenotype, with faster-exploring males obtaining marginally larger caterpillars but provisioning less frequently than slower-exploring males. Lastly, environmental variables contributed substantially to the diet composition of offspring. For this reason, we cannot suggest that EB dominates, but it may contribute to a diet specialization process in our study population.
The effects of price, brand image, and product quality on customer loyalty and repurchase (a study case on customers of Walls products)
Authors: Harisandi Prasetyo , Purwanto Purwanto
Published: September 2022

Intense industry competition, as well as rapid changes and efforts to retain customers, are competitive goals and scarce resources for the ice cream industry. Price, brand image, and product quality implementation increases customer loyalty and is taken into account in the subsequent purchasing process. The goal of this study was to look at how price, brand image, and product quality affect customer loyalty and repurchase intent. A sample of 130 people who buy Walls brand ice cream products were surveyed. SEM (Structural Aquation Model) is the data analysis method used in this study to test the hypothesis. The results of this study conclude that price, brand image, and product quality have a positive effect on customer loyalty, and customer loyalty also has a positive effect on repurchase intentions. If the loyalty of the majority of customers has the strongest impact on repurchase intention.