Search

Each year, researchers publish an immense number of scientific papers. While some receive many citations, others receive none. Here we investigate whether any of this variance can be explained by the choice of words in a paper's abstract. We find that doubling the word frequency of an average abstract increases citations by 0.70%. We also find that journals which publish papers whose abstracts are shorter and contain more frequently used words receive slightly more citations per paper. Specifically, adding a 5 letter word to an abstract decreases the number of citations by 0.02%. These results are consistent with the hypothesis that the style in which a paper's abstract is written bears some relation to its scientific impact. [ABSTRACT FROM AUTHOR]

Unimodal biometric systems are susceptible to a variety of problems such as noisy data, intra-class variations, limited degrees of freedom, non-universality, spoof attacks and unacceptable error rates. Some of these limitations can be addressed by deploy multimodal biometric systems that integrates the evidence presented by multiple sources of information The proposed system provides effective fusion scheme that combines information presented by the multiple domain experts based on the Rank level fusion integration method, thereby increasing the efficiency of the system which is not possible by the unimodal biometric system. The proposed multimodal biometric system has a number of unique qualities, including principal component analysis and fisher's linear discriminate methods for individual matchers authentication. The novel rank level fusion method is used in order to consolidate the results obtained from different biometric matchers. [ABSTRACT FROM AUTHOR]

Abstract: The purpose of this study was to evaluate the potential of inorganic analysis techniques for the discrimination of document (multipurpose office) paper. A set of 25 different multipurpose office papers from the European market was used for comparison. It appeared that for the single techniques LA–ICP–MS had the highest overall discriminating power. Despite its lower sensitivity, XRF also showed good discriminating power but the correlation with LA–ICP–MS is high. The combination of LA–ICP–MS and IRMS provides a powerful and strongly discriminating set of techniques. [Copyright &y& Elsevier]

Abstract: With a sample of Grade 4 Chinese students, the present study examined whether the electronic version was comparable to the paper-and-pencil version of the Wallach–Kogan Creativity Tests (WKCT). It was found that the two versions generated similar patterns of reliability coefficients and inter-correlation coefficients for the eight creativity measures (verbal and figural fluency, flexibility, uniqueness, and unusualness). Results of MANOVA and subsequent ANOVA revealed that there were no significant differences in the means of all the eight creativity measures assessed by the two versions. These results provided some preliminary evidences for the comparability of the two versions of the WKCT. The availability of the electronic version of the WKCT is in step with the rapid advances in test computerization and it will definitely facilitate creativity research and theorization. [ABSTRACT FROM AUTHOR]

Background: Traumatic injury survivors often experience negative health consequences, impacting recovery. No studies have assessed the feasibility of evaluating the resiliency of hospitalized trauma patients using the 10-item Connor-Davidson Resilience Scale (CD-RISC-10). Purpose: The purpose of this study was to determine the most efficient method to collect survey responses on the CD-RISC-10. Methods: This cross-sectional study used a convenience sample of admitted patients with traumatic injury. Patients were randomized to complete the CD-RISC-10 using pen and paper, tablet, or workstation on wheels. Results: Of the 161 patient surveys, the tablet-based survey took the shortest time to complete (2 minutes, 21 seconds), and the paper survey resulted in the lowest percentage of missed questions (0.5%). Trauma patients reported high levels of resiliency. Conclusion: The CD-RISC-10 can be easily administered to trauma patients. Clinicians should balance efficiency and patient preferences when deciding on a survey collection method. [ABSTRACT FROM AUTHOR]

The prediction of final semester grades is a crucial undertaking in education, offering insights into student performance and enabling timely interventions to support their academic journey. This paper employs a deep learning approach, specifically gated recurrent unit (GRU), in conjunction with feature optimization using analysis of variance (ANOVA), to forecast final semester grades. The predictive model is trained and evaluated on a handcrafted grade prediction dataset, which contains the academic performance of the students during Plus 2 and from Semester 1 to Semester 4 of a group of Computer science and Engineering majors in Kerala. By processing historical academic records and contextual information, the GRU model learns to predict future performance accurately. To enhance the model's efficacy and interpretability, ANOVA is applied to optimize the feature selection process. This statistical technique identifies the most influential factors contributing to final grades, refining the model's predictive power while reducing dimensionality. The experimental results showcase the model's effectiveness in predicting final semester grades, demonstrating superior accuracy and performance compared to grade prediction using CNN with Bayesian optimization and LSTM with L1-Norm optimization. [ABSTRACT FROM AUTHOR]

Obtaining the required surface finish and geometric accuracy together with attaining high production rate is a challenge in finishing of the inner surfaces of steel pipes and bushes. One of the promising techniques for finishing the surface of metal parts is electrochemical machining. In this paper, the surface roughness and dimensional inaccuracy of the inner surface of a CK45 steel bush were controlled electrochemically. For this, a special electrochemical finishing machine was constructed. The effect of electric potential difference along with temperature, flow rate and concentration of electrolyte on the material removal rate, surface roughness and dimensional accuracy were investigated. Box Behnken design (BBD) was used for designing the experiments. Analysis of variance (ANOVA) was performed for validating the experimental models. Also, multi-objective optimization was performed using response surface methodology (RSM) to achieve a predetermined level of surface roughness and dimensional accuracy along with maximizing the material removal rate. [ABSTRACT FROM AUTHOR]

The objective of this paper was to investigate the Cutting Speed, Feed Rate and Depth of Cut to predict Tool wear during Turning of AISI 1040 Medium Carbon Steel Blanks using Artificial Neural Network Approach. The significance of the cutting parameters was investigated using the Analysis of Variance and results revealed the feed rate as the most influential factor, followed by the interaction of cutting speed and depth of cut. The Artificial Neural Network model exhibited notable correlation coefficients (R) in training (0.81301), validation (0.99932), and test (0.99922) datasets, with an overall coefficient of 0.86662, affirming the model's efficacy in predicting tool wear. The minimum predicted tool wear (0.1007mm) was observed at a 0.50mm depth of cut, cutting speed of 200m/min, and feed rate of 0.15mm/rev, demonstrating a close alignment with the observed data. The ANN predictions effectively capture the intricate relationship between tool wear and process parameters, substantiated by high correlation coefficients. [ABSTRACT FROM AUTHOR]

Purpose This study aimed to clarify the relationship between foot and postural changes and low back pain during preg- nancy. Methods The study consisted of a questionnaire about low back pain during pregnancy and measurement surveys. The first survey was conducted at 14--16 weeks of gestation, the second at 24--26 weeks, and the third at 34--36 weeks. The participants were 14 pregnant women. We attached a spherical marker to the anterior superior iliac spine and posterior superior iliac spine. Using a digital camera, we photographed their standing postures from the sagittal plane and calculated the pelvic tilt angle. We applied a free curve ruler to measure the spinal curve, which was then traced on paper to calculate the thoracic kyphosis and lumbar lordosis angles. Participants were asked to adopt a natural standing posture barefoot on the flat glass plate of the pedoscope, and the state of the plantar surface touching the ground was photographed using a digital camera. The lower end of the navicular tuberosity was marked in the standing position, after which we measured the foot length and navicular height, divided the navicular height by the foot length, and multiplied by 100 to calculate the arch height. Statistical analysis was performed for each measurement item and a value of less than 5% was set as the significance level. Results The participants were nine primiparous women and five multiparous women, and 10 women developed low back pain during pregnancy; there was a tendency for the pelvis to tilt forward, the foot arch to flatten, and lordosis of the lumbar spine changed from decreased to increased as the pregnancy progressed, but the differences were not sig- nificant. The left ground contact plantar surface area ratio decreased significantly over time, and the ground contact area decreased as the pregnancy progressed (p<0.01). There were no significant differences over time in the pelvic tilt, thoracic kyphosis, and lumbar lordosis angles, arch height ratios, and ground contact plantar surface area ratios between those with and without low back pain during pregnancy, and between childbirth experiences. Conclusions Pregnant women tended to exhibit an increased pelvic tilt angle and decreased lumbar lordosis from the first to the second trimester of gestation, and increased values from the third trimester. Although the foot tended to flatten owing to the increasing load of the uterus, the ground contact area of the foot did not necessarily increase, and the toes were considered in a floating state because of the weight support by the heel. The anatomical characteristics of the uterus showed that pregnant women were more likely to bear weight on the right side during the third trimester of gestation. The onset of low back pain during pregnancy was associated with multiparous women, flattening of the foot arch, and lumbar spine alignment, which addressed the protrusion of the abdomen associated with uterine enlarge- ment. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of stochastic modeling of atomic ensembles under multi-source noise and makes the model interpretable. First, based on Itô's lemma and Allan variance analysis (ITÔ-AVAR), an approach is proposed to model nonstationary stochastic submodels of atomic ensembles. On this basis, the variance decomposition and nonlinear optimization algorithms are utilized to hybridize modeling atomic ensembles with nonlinear and nonstationary properties. Second, an Itô's lemma dynamic allan variance analysis (ITÔ-DAVAR) approach is developed for online modeling of atomic ensembles. Further, an atomic ensembles sensitivity enhancement scheme based on the proposed approach is given, which effectively promotes the progress of quantum instrument engineering. Finally, the proposed scheme are deployed in the optical pumping magnetometer and spin-exchange relaxation-free comagnetometer, respectively, while experimentally verifying the sensitivity of the spin-exchange relaxation-free comagnetometer reaches 5. 36 × 1 0 − 6 deg s − 1 Hz − 1 / 2 . • An approach is proposed for modeling nonstationary stochastic submodels of atomic ensembles using Itô's lemma and Allan variance analysis. • Combining the variance decomposition and the nonlinear optimization algorithm to hybrid model the atomic ensembles. • A sliding-window technique is employed to realize real-time online modeling of the atomic ensembles, ensuring adaptability and practicality. • An atomic ensembles sensitivity improvement scheme is proposed to promote its engineering progress. • The effectiveness of the proposed approach is verified through numerical simulations and practical experiments. [ABSTRACT FROM AUTHOR]

Copyright of Facta Universitatis: Series Physical Education & Sport is the property of Facta Universitatis, Series Physical Education & Sport and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The Kingdom of Saudi Arabia has developed rigorous strategies to control and prevent the spread of COVID-19. However, the effectiveness of these measures in containing and mitigating the epidemic has yet to be studied. This paper aims to assess the efficiency of preventive policy initiatives that Saudi Arabia has taken to reduce the spread of COVID-19, which was rapid and progressive in nature. Information on the effectiveness of measures applies to help the Saudi government adjust policy responses when considering which measures to relax once the epidemic is controlled. Data for this study were retrieved via publicly available data sources such as the Saudi Arabia Ministry of Health and the government's official news agency—Saudi Press Agency (SPA) websites. Other datasets, such as prevention measures, were gathered from the Country Policy Tracker website. Our dataset's time component extends over 590 consecutive days from 20 January 2020–31 August 2021. Moreover, a mixed-method approach combining COVID-19 data and prevention measures was adopted to assess preventative measures practice. We compiled the dataset used in this study in a Microsoft Excel database. The significance of observed differences among implementing effective strategies was determined using ANOVA and Mixed methods approach. Noticeably, the statistical analysis was performed using the open-source statistical system R version 4.2 (available at http://cran.r-project.org). Our analysis showed that only three out of the 32 (9.4%) measures significantly reduced the spread of COVID-19. Our results also show substantial variations in the spread of COVID-19 associated with preventive measures in Saudi Arabia. There was a significant positive correlation between activating and massive testing in communities and cases of COVID-19 (measure effect = 923.086 and p < 0.05). A similar result was found for complete curfew across the Kingdom and cases of COVID-19 (measure effect = 621.389 and p < 0.10). Removing slum areas interrupted the spread of Covid-19 (measure effect = 305.689 and p < 0.01). The other preventive measures did not significantly affect the COVID-19 pandemic distribution. These findings consistently concluded that activating and massive testing in communities, complete curfew across the Kingdom, and removal of slum areas were the most effective measures for reducing the impact of the COVID-19 pandemic. Only by understanding these correlations will it be possible to control and reduce the rate of COVID-19 spread and, therefore, suggest a possible exit strategy once the epidemic is controlled. [ABSTRACT FROM AUTHOR]

The use of statistics to derive insights from the data has provided researchers with empirical tools to describe, diagnose, predict, and prescribe actions, interventions and generate knowledge from varied data sets. Depending on the types of data (structured, semi-structured, and unstructured), different statistical models and tests can be performed to generate the said insights and new knowledge. Correctly identifying the data types (whether the data is discrete or continuous) aids researchers in identifying the applicable statistical tests. The distribution of the data also has an implication for determining the relevant statistical test. When continuous data are said to be normally distributed, the types of tests that can be used to compare groups differ to when the data are found to be not normally distributed. The same is true for discrete data, in that there are certain assumptions that need to be satisfied to identify the correct statistical tests to use in comparing the data groups. In this paper, the discussion will be focused on nine commonly used statistical tests. These common tests include the t-test, paired t-test, analysis of variance (ANOVA) test, Wilcoxon rank-sum test (WRST), Wilcoxon signed-rank test (WSRT), nonparametric ANOVA, chi-square (X2) test, Fisher's exact test, and McNemar's test. The conditions for the use of these tests will be described, and the applications thereof will be discussed. Therefore, the purpose of this paper is not to describe the mathematical theories behind different statistical tests but to introduce the tests and their applications. [ABSTRACT FROM AUTHOR]

Objectives: Nausea is one of the most important symptoms of patients undergoing chemotherapy. This study aims to determine the effects of aromatherapy with sour lemon on nausea in patients undergoing chemotherapy. Methods: A total of 50 patients undergoing chemotherapy were randomly assigned to experimental and placebo (control) groups. The two groups completed the visual analogue scale for nausea before and the first to the fourth week after starting the intervention. The intervention was performed during chemotherapy. Using a dropper, a paper towel was saturated with 3 drops of sour lemon essential oil; however, for the control group, 3 mL of water as a placebo was spread on a paper towel. The intervention in the experimental and control groups was performed once a week for 4 weeks during weekly chemotherapy sessions. Results: At the beginning of the study, no significant difference was observed between the mean score of nausea in the two groups (P>0.05). The first to the fourth week after starting the intervention, significant differences were observed between the mean score of nausea in the two groups (P<0.05). The results of the repeated measures analysis of variance indicated that the mean score of nausea changed over time in the experimental group, indicating a gradual decrease in the mean score of nausea (P<0.05). Discussion: Our findings indicated that aromatherapy with sour lemon can be effective in reducing nausea in patients undergoing chemotherapy. [ABSTRACT FROM AUTHOR]

In this paper, we aim to find answer to a single question: what are the characteristics of firms with superior use of alliance learning practices? Consequently, we aim to discover the characteristics of firms which are more preoccupied to learn from their strategic alliances. We investigate this research question through a statistical analysis of the answers provided by 46 best performing medium and large-sized companies operating in Romania. By means of several multilinear regressions and an analysis of variance, we found that the companies with superior use of alliance learning practices – thus, more preoccupied to learn – are more proactive, build an alliance culture favouring the use of alliances, develop relational attributes in their alliances (e.g., trust), respectively monitor and control their alliance activity to a higher degree. Contrary to expectations, the companies with superior use of alliance learning practices do not collaborate to a higher degree horizontally, with their competitors and complementors. In terms of the dispersion of companies depending on their use of alliance learning practices, to a high degree (34.1%), the differences between companies can be explained by the proposed set of characteristics developed in this paper. Our findings contribute to the existent literature in the field of alliances, bringing empirical evidence on the characteristics that companies need to develop to better learn from their strategic alliances. In addition, executives of medium and large-sized companies find in this paper valuable information regarding the nurturing of alliance knowledge acquisition and transfer from their strategic allies and partners. [ABSTRACT FROM AUTHOR]

Yarn wickability achieves high thermo-physiological comfort. Therefore, this paper aimed to investigate yarn wickability and analyze statistically factors affecting yarn wicking performance. Methodology consists of testing wicking height for ring spun yarn produced from three levels of fibre types and twist factors at two levels of doubling. Statistical tools such as ANOVA, T-test and Post-hoc tests analyzed the impacts on wicking heights. Findings showed that the Post-hoc test represented the variation between groups more accurately than ANOVA. Furthermore, a comparison of Bonferroni Alpha with T-test p-values revealed that yarn wicking was significantly affected by interactions of fibre type, doubling, and twist level. [ABSTRACT FROM AUTHOR]

Yarn wickability achieves high thermo-physiological comfort. Therefore, this paper aimed to investigate yarn wickability and analyze statistically factors affecting yarn wicking performance. Methodology consists of testing wicking height for ring spun yarn produced from three levels of fibre types and twist factors at two levels of doubling. Statistical tools such as ANOVA, T-test and Post-hoc tests analyzed the impacts on wicking heights. Findings showed that the Post-hoc test represented the variation between groups more accurately than ANOVA. Furthermore, a comparison of Bonferroni Alpha with T-test p-values revealed that yarn wicking was significantly affected by interactions of fibre type, doubling, and twist level. [ABSTRACT FROM AUTHOR]

Cyber security has been drawing massive attention in recent years due to human reliance on new technology, and systems. Therefore, securing these systems against cyber-attacks has become an essential task nowadays. The advanced persistent threat is one of the most sophisticated cyber-attacks in which malicious actors gain unauthorized access to a network and remain undiscovered for a lengthy period of time. The number of recorded advanced persistent threat attacks and threats to organizations intensifies. One method used in detecting advanced persistent threat attacks is machine learning. However, this method has not been covered in many previous kinds of research due to the lack of datasets covering an entire advanced persistent threat attack lifecycle. Thus, this paper aims to build a new dataset that covers the complete life cycle of an advanced persistent threat attack to detect them in different stages such as normal, reconnaissance, initial compromise, lateral movement, and data exfiltration activities. The newly collected dataset is based on advanced persistent threat attacks using tactics, techniques, procedures, and indicators of compromise. Then, it is applied to a proposed machine learning model employing eXtreme gradient boosting and analysis of variance feature selection method. The model was compared to other traditional classifiers: random forest, decision tree, and K-nearest neighbor. Based on the accuracy score of the proposed model 99.89% using only 12 features, it proved to be more powerful and efficient than the other classifiers in detecting advanced persistent threat attacks. The dataset used in this research is newly built based on advanced persistent threat attack behaviors, which will aid organizations in detecting advanced persistent threat attack activity efficiently. The experimental evaluation proved that the proposed method effectively detects advanced persistent threat attacks at different stages. [ABSTRACT FROM AUTHOR]

Globally, aluminium alloys are used in many industries. Application of aluminium alloys is realized by many manufacturing processes in which joining processes are inevitable. Joining of aluminium alloys is achieved by various welding processes. One of the appropriate welding processes used to join aluminium alloy is Gas Metal Arc Welding (GMAW). This paper investigates the effect of process parameters of the GMAW process while welding AA 6351 aluminium alloy weldment with the help of an integrated Taguchi-grey-Fuzzy approach. Taguchi L-16 array was designed by using an orthogonal method to conduct the experiments. From the experimental results, Signal-to-Noise ratios (S=N ratio) were calculated from which Grey Relational Grades (GRG) were computed. These computed GRG were used as input for the fuzzy controller to find the Grey Fuzzy Relational Grades (GFRG), by which optimized process parameters were found and validated. Furthermore, Analysis of Variance (ANOVA) was used to identify the contributions of the GMAW process parameters over the responses. Subsequently, the effects of process parameters on the weldments were also discussed in detail. By identifying the optimized process parameters and contributing process parameters, the quality of weld joints is improved. [ABSTRACT FROM AUTHOR]

This paper included research on the performance of basketball teams, which compete at three different levels of competition, the ABA, the ABA 2, and the BiH Championship. The research was conducted on a sample of 35 teams that played the BiH Championship (11 teams), ABA 2 (12 teams), and ABA (12 teams) in the 2018/2019 season. A total of 64 matches were played (20 matches of the BiH Championship, 22 matches of the ABA 2, and 22 matches of the ABA). Matches were analyzed using a standard form (FIBA) to monitor situation indicators with 22 variables, of which 19 were used in this paper. The main goal of this research was to find out whether it is possible to distinguish successful from unsuccessful teams at three different levels of competition based on 19 standard indicators of situational efficiency in basketball. Based on the results obtained by applied statistical methods, ie analysis of variance, the obtained information can be used as a starting point for analyzing the basketball game of one's team and determining future criteria for selection and programming of basketball teams. The obtained results showed that there are statistically significant differences between the winners at all three levels of competition in those statistical parameters that have a defensive character. So success, to a large extent depends on the realization of the phase of the game in transition, which can be the product of good defense and a jump in defense. [ABSTRACT FROM AUTHOR]

BACKGROUND: The use of accessory devices with pressurized metered-dose inhalers (pMDIs) enhances aerosol delivery and helps overcome any lack of patient coordination when using the pMDI. The use of accessory devices could be influenced by the efficacy, availability, and cost of these devices. The aim of this study was to compare drug delivery with the pMDI alone and with non-antistatic and antistatic accessory devices. METHODS: The total emitted dose and aerodynamic characterization of salbutamol particles were measured for the pMDI alone and for the pMDI combined with 4 different accessory devices: a homemade spacer, the Dolphin spacer, the DispozABLE paper spacer, and the AeroChamber Plus valved holding chamber. Aerodynamic characterization was analyzed with an Andersen cascade impactor at an inhalation flow of 28.3 L/min, and drug deposition was measured with high-performance liquid chromatography. RESULTS: The mean ± SD total emitted dose from the pMDI alone, 155.2 ± 20.5 µg, was the greatest of all modalities, and the difference was significant (P < .001). The homemade and Dolphin spacers had the highest mean ± SD deposited amounts of salbutamol remaining on their walls (ie, 124.1 ± 11.1 µg and 131.5 ± 11.8 µg, respectively). The mean ± SD total emitted doses with the AeroChamber Plus valved holding chamber (61.9 ± 8.9 µg) and the DispozABLE paper spacer (76.4 ± 8.6 µg) were significantly higher than the emitted doses with the other devices. The mean ± SD fine-particle doses emitted with the AeroChamber plus valved holding chamber (51.4 ± 4.7 µg) and the DispozABLE paper spacer (39.7 ± 5.6 µg) were significantly higher than those with the other devices. The AeroChamber Plus valved holding chamber had the lowest mass median aerodynamic diameter (MMAD) values, but there were no statistically significant differences in MMAD between any of the combinations of pMDI and accessory device. CONCLUSIONS: The valved holding chamber and the paper spacer had better aerodynamic characteristics than the other devices tested. We consider the antistatic devices to be the optimum devices for aerosol delivery due to their high efficacy compared to non-antistatic devices. [ABSTRACT FROM AUTHOR]

The area of digital transformation is attracting considerable interest due to the current trend of digital transformation being deployed around industries in the world. Many researchers have addressed the issue of technology acceptance in various industries; however, the area of digital transformation along with the demographic characteristics of creative services has not been explored, especially in the context of Vietnam. This study aims to clarify the influence on the determinants of adoption of digital transformation based on gender and region and is the first experiment to survey in creative services in Vietnam. The methodology is primarily derived from the technology, organization, and environment framework, and uses analysis of variance, independent sample t-test, and multivariate linear regression for investigation; further details on the adopted methodology can be found in this paper. The results reported here provide further evidence for the value of gender and region in the decision of digital transformation adoption and their impact on the determinants of digital transformation. This work has presented a background method for the investigation of creative companies in the context of creative services in Vietnam. However, the findings might be only representative of the characteristics of selected demographics and creative services in Vietnam, so additional studies are needed on other demographic factors and areas. [ABSTRACT FROM AUTHOR]

Background: Burnout has been a chronic problem in theworkplace, especially in health care. Although the literature has examined many antecedents to burnout, specificworkplace practices to reduce burnout remain elusive.Nascent research has begun to examine how health care work places can becomemore caring for workers. Although psychological safety has been proposed as an important predictor of burnout, relations have not yet been comprehensively examined. Purpose: Underpinned by conservation of resources theory,we argue that a caringwork environment, inwhich compassion and interpersonal support are key priorities, provides resources for workers, which should increase psychological safety and in turn help reduce emotional exhaustion. Method: To explore our proposed model, we conducted a paper-and-pencil survey of clinical health care providers working in medical units of a large acute care hospital. Response rate was 44% (n = 631). Results: Analysis found support for a moderated-mediation model in which psychological safety partially mediated relations between caring climate and emotional exhaustion, and this effect was stronger for those who were less empowered in their jobs. Conclusion: Our findings suggest that a caring work environment holds psychological resources that may help buffer against resource losses through increased psychological safety. Practical Implications: Although health care work environments will continue to experience constraints on key resources, worker emotional exhaustion may be mitigated through a focus on systematically increasing caring and compassion in the work environment, as opposed to relying on individual workers to support one another in an uncaring workplace. [ABSTRACT FROM AUTHOR]

Objective: Conversion disorder has a significant impact on families and the healthcare system. A recent review suggests there is little uniformity in treating this population. This paper describes an inpatient treatment program emphasizing physical conditioning and less time uncovering the psychological underpinnings of the presentation. Design: This study included 100 pediatric patients admitted to an inpatient rehabilitation setting with lower extremity weakness/dysfunction not explained by a medical cause. Patients followed a 16-step goal hierarchy to increase physical function. Patients participated in three hours of therapy and met with a psychologist and teacher daily. Patient functioning was assessed at three time periods using the mobility items of the Functional Independence Measure for Children (WeeFIM). Results: Ninety-four patients completed the program. The average length of stay was 10 days. There were no significant differences between gender, length of stay, or insurance. Data was collected from 73 participants at a two-month follow-up. A repeated measures analysis of variance (ANOVA), using time points at admission, discharge, and follow-up, revealed significant improvements over time. Post-hoc contrasts showed differences with admission and discharge but no differences between discharge and follow-up, suggesting gains in mobility remained. Conclusion: This paper describes an inpatient program that effectively treats patients with conversion disorder in a relatively short period. The physical gains made during hospitalization persisted over time and suggest inpatient rehabilitation focusing on physical mobility could be a more financially beneficial approach than outpatient treatment. Future considerations include identifying a more robust assessment process for patients to determine other psychological characteristics that might impact successful, more short-term treatment. [ABSTRACT FROM AUTHOR]

Traditional approaches to portfolio management and optimization often rely on the certain statistical properties, such as expected return and price variance. But these properties generally represent the local behavior of the stocks and are thus not able to represent the stock characteristics in terms of the whole stock market. This paper considers the stock market as a complex system, where stocks affect one another due to unknown forces. It may not possible to measure the actual magnitudes and directions of these forces, but it is possible to observe their effects using the external observations such as the correlation between stocks. To forecast the dynamics, this paper proposes a seminal measure, the cohesion of the stock market network induced by the correlation of stocks. The important observations we obtained from the analyses of the real market (S&P500 and KOSPI200) in the past thirteen years are two folds: (1) the cohesion tends to increase more in a bear market than in a bull market, and (2) the cohesion of the stock market Granger causes the stock returns. Based on these observations, we implemented a stock portfolio recommending system, namely StoPoR. To evaluate the effectiveness of StoPoR system, we conducted the simulated investment based on the portfolio recommended by the StoPoR. The result shows that the monthly returns of StoPoR portfolio (1.44%) is bigger than that of Markowitz efficient portfolio (1.07%) and further bigger than that of the S&P500 index (0.50%). The similar result also holds for the Korean stock market; the monthly return of the StoPoR suggested portfolio (1.83%) gets far bigger than that of Markowitz efficient portfolio (1.61%) and further bigger than that of the KOSPI200 index (0.81%). This result indicates that the characteristics of the stock network are related to the stock returns and its dynamics can be used for constructing a stock portfolio and the prediction of the changes in the stock markets. [ABSTRACT FROM AUTHOR]

Abstract The importance, benefits, and impact of integration of decisions within supply chains have long been investigated by many researchers. Order acceptance and supplier selection are two of the most critical decisions for supply chain managers. Throughout the process of order acceptance, a manufacturer has to decide which orders to be accepted and processed and based on the accepted orders, the volume of required raw material is determined. On the other hand, a manufacturer aims to choose one or several suppliers among all possible choices to provide sufficient raw material for the accepted orders, subject to different criteria such as list price, transportation cost, etc. This paper addresses an integrated framework for profit maximization in an integrated supplier selection, order acceptance and scheduling problem in a single-machine environment with multiple customers. There is substantial literature on the problems of supplier selection and order acceptance; however, to the best of our knowledge, this paper is the first research that integrates these essential decisions in the form of a mathematical model to maximize the total profit. The problem is NP-hard in nature; therefore, solving to optimality is not practically possible for problems with medium and large size. For that purpose, we developed a Heuristic Algorithm (HA) to solve the problem above in a reasonable time, with proper accuracy. Results from this heuristic algorithm are compared with that of a commercial solver (GAMS) and the well-known Genetic Algorithm (GA) and Variable Neighborhood Search (VNS). Computational experiments demonstrate that the developed heuristic algorithm is more efficient in comparison with other tested methods. Highlights • A model is developed to integrate order acceptance, order scheduling, due date assignment, and supplier selection decisions. • A heuristic algorithm is developed to solve the problem promptly with great accuracy. • Extensive computational experiments and analysis demonstrate the outperformance of the developed heuristic algorithm. [ABSTRACT FROM AUTHOR]

Copyright of Ciencia e Ingenieria Neogranadina is the property of Ciencia e Ingenieria Neogranadina and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper is an analysis of media habits of students for defining educational patterns. The media has been in the important role in various fields like education, infotainment, entertainment, planning, development, etc. In this paper, the study of media habits of students has been carried out to explore the methodologies in education and teaching learning process. The students learning at secondary level are competent to express their opinions and habits about media. Categories of media, nature of questions, statements and ranking scale has been defined. This paper presents the values of significant differences between media habits among students. The ANOVA statistical tool has been implemented for estimating the significant differences. [ABSTRACT FROM AUTHOR]

Prediction of tool wear plays a key role in machining world due to its considerable impact on total costs in terms of fabricated part quality and disposal of cutting insert before reaching the tool life limit. In addition, comprehensive evaluation of machining characteristics provides a perspective for improved quality. In this study, during turning of AISI 5140 steel, on-line measurements of cutting tool tip temperature and acoustic emission (AE) and off-line measurement of flank wear (V B) of the cutting tool were performed. Very limited study has been published on the machinability characteristics of AISI 5140, while no research has been published on flank wear characteristics in addition to AE and temperature sensors before. Therefore, in this context, AE and tool tip temperature were measured with adapted sensor systems while V B measurement was performed with microscope when the machining was stopped. Three levels of cutting speed, feed rate, depth of cut and cutting-edge angle, experimental design was composed based on Taguchi's L 27 orthogonal array. The main aim of the paper is to predict the flank wear i.e., main criteria for tool life, cutting temperature and AE with the help of fuzzy inference model. In addition, for providing a holistic approach and comprehensive point of view to the machinability, statistical analysis and optimization of the input parameters were given in detail for temperature, AE and V B. According to results, the combined effect of depth of cut and cutting-edge angle having effect (40%) on V B while cutting edge angle and cutting speed have dominance on temperature (45.4%) and AE (46.23%) respectively. Considering the complexity of turning operations, obtained findings reveal the superiority of the fuzzy inference model which was found the estimations highly close to the test results (90–97%) for each machining characteristic. The applicability of fuzzy rule system for different types of variables in turning is promising for the new generation of materials utilized in manufacturing sector. [ABSTRACT FROM AUTHOR]

Copyright of Cuadernos de Psicología del Deporte is the property of Cuadernos de Psicologia del Deporte and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The aim of this study was to evaluate the effects of different polishing techniques on the surface roughness and gloss of various composites. A total of 360 composite cylinders (6 mm in diameter and 2 mm in thickness) were made using a silicone matrix and 1 of the following 6 restorative materials (n = 60): Admira Fusion, GrandioSO, Filtek Supreme, Filtek Z250, TPH Spectra ST, and Herculite Classic. The composite specimens were cured and then immersed in water for 24 hours. The baseline roughness was standardized with 600-grit silicon carbide paper used in a polishing device for 30 seconds. The specimens were divided into 6 subgroups (n = 10) according to the polishing technique: abrasive discs (Sof-Lex); abrasive discs (Sof-Lex) and diamond paste (Diamond Excel); abrasive rubber point (Dimanto); silicon carbide polishing brush (OptiShine); rubber spiral wheels (Sof-Lex Spiral Wheels - Diamond Polishing System); or sequential application of polishing pastes (Diamond ACI and ACM). After polishing was completed, the surface roughness and gloss were measured, and the data underwent 2-way analysis of variance and the Tukey test (P < 0.05). Statistically significant differences were observed for roughness (P < 0.001) and gloss (P < 0.001) for both factors analyzed (composite material and polishing technique). Admira Fusion exhibited the highest roughness and lowest gloss values of all of the composites, and Filtek Supreme exhibited the lowest roughness and highest gloss values. Sof-Lex Spiral Wheels and OptiShine polishing brush exhibited lower roughness and higher gloss than the other polishing techniques. The effects of different polishing techniques were material dependent, but all systems tested provided clinically acceptable results. The use of a single polishing technique for all types of composite materials might result in undesirable clinical outcomes. [ABSTRACT FROM AUTHOR]

This paper presents the volumetric and Marshall Stability characteristics of irradiated waste polyethylene terephthalate fiber-reinforced asphalt mix utilizing the analysis of variance. Exposing polymers to gamma radiation boosts its mechanical and thermal properties which have a direct impact on improving its strength. The influences of irradiated fiber and binder contents on the volumetric and strength properties have been identified via response surface methods (RSM). The RSM was used to determine the optimized contents of irradiated fiber and binder through central composite design (CCD). The results indicate that the interactions between the two independent variables are both influential. The high values of the coefficient of determination (R2) show a good agreement between the actual and predicted values. The numerical optimization elucidates that the optimal irradiated fiber and binder contents were 0.53% and 5.25% respectively. The absolute percent errors between the actual and predicted values were observed to be less than 7% for all the responses. [ABSTRACT FROM AUTHOR]

This paper aims to assess the current knowledge, attitudes, and behaviors of nursing staff regarding sarcopenia and explore associating factors that influence them. Sarcopenia has an insidious onset and is easily overlooked. However, it is has become very common in older people, seriously jeopardizing the quality of life in patients. The present situation of nurses in China is inadequate, even though they are the primary professionals tasked with screening for sarcopenia, the ability to recognize and effectively manage the disease, and the critical role they play in preventing and controlling sarcopenia in patients. We conducted a cross-sectional design of nurses. Facilitated sampling was used in seven hospitals in Jiangsu Province, China. A total of 409 hospital nursing staff participated in the survey from December 2022 to March 2023. The main survey instruments were the nursing staff about the knowledge of sarcopenia, beliefs, a behavior questionnaire, and a self-designed general information questionnaire. Descriptive of general data, t-test, and ANOVA for influencing factors of three dimensions, whereas multiple linear regression analyses were performed using SPSS23.0 software. Questionnaires were distributed to 460 nurses, and of the 426 (92.6%) questionnaires returned, 409 (96.0%) were valid. The total mean score of nurses' knowledge, beliefs, and behavior about sarcopenia was 125.42 (SD 18.97), the mean score of knowledge latitude was 29.09 (SD 7.80), the mean score of attitude dimension was 57.53 (SD 7.63), and the mean score of behavior latitude was 38.80 (SD 10.71). Multiple linear regression analysis revealed that the nurse's position, Knowledge of sarcopenia, whether or not they were specialist nurses and years of experience in the workplace were the most significant factors correlated with the level of knowledge, belief, and practice (P < 0.05). In China, nurses have little knowledge about sarcopenia, but their attitude towards sarcopenia care is positive. However, there is potential for improvement in nursing behavior toward sarcopenia management. Managers are advised to develop targeted training programs for nurses. Further, it improves their screening and diagnosing abilities, allowing them to prevent and control sarcopenia more effectively. [ABSTRACT FROM AUTHOR]

Data-acquisition programs, such as surveillance and pilots, play an important role in minimizing subsurface risks and improving decision quality for reservoir management. For design optimization and investment justification of these programs, it is crucial to be able to quantify the expected uncertainty reduction and the value of information (VOI) attainable from a given design. This problem is challenging because the data from the acquisition program are uncertain at the time of the analysis. In this paper, a method called ensemblevariance analysis (EVA) is proposed. Derived from a multivariate Gaussian assumption between the observation data and the objective function, the EVA method quantifies the expected uncertainty reduction from covariance information that is estimated from an ensemble of simulations. The result of EVA can then be used with a decision tree to quantify the VOI of a given data-acquisition program. The proposed method has several novel features compared with existing methods. First, the EVA method directly considers the data/objective-function relationship. Therefore, it can handle nonlinear forward models and an arbitrary number of parameters. Second, for cases when the multivariate Gaussian assumption between the data and objective function does not hold, the EVA method still provides a lower bound on expected uncertainty reduction, which can be useful in providing a conservative estimate of the surveillance/pilot performance. Finally, EVA also provides an estimate of the shift in the mean of the objective-function distribution, which is crucial for VOI calculation. In this paper, the EVA work flow for expected-uncertainty-reduction quantification is described. The result from EVA is benchmarked with recently proposed rigorous sampling methods, and the capacity of the method for VOI quantification is demonstrated for a pilot-analysis problem using a field-scale reservoir model. [ABSTRACT FROM AUTHOR]

In this in vitro study, 3 experiments were conducted to evaluate the influence of customizing the apical portion on the characteristics of fiber posts. In the first experiment, 4 fiber posts were submitted to different custom adaptations (no customization, industrial shaping tool, diamond bur, or paper disc) and were observed with a scanning electron microscope to evaluate the micromorphologic changes. In the second experiment, 60 posts of different sizes were divided into 6 groups (n = 10): 0 (No. 0.5), 1 (No. 1), 2 (No. 2), 3 (No. 3), 4 (No. 4), and 5 (paper disc--remodeled No. 4). The posts were submitted to a 3-point bending test. In the third experiment, the crowns of 20 extracted, healthy permanent human canines were removed, and the teeth were endodontically treated, embedded in acrylic resin, and divided into 2 groups (n = 10): I (control), No. 4 posts cemented into post spaces prepared with a No. 4 drill; and II (test), remodeled No. 4 posts cemented into root spaces prepared with No. 2 and 4 drills. The posts were cemented with self-adhesive dual resin cement, and the specimens received direct resin crowns. Fracture strength was measured with a universal testing machine at 45 degrees until fracture. Results were submitted to analysis of variance (P ≤ 0.05). Customization of fiber posts with diamond burs or paper discs produced acceptable micromorphologic changes. Custom adaptation of fiber posts reduced their flexural strength, which remained at acceptable values. Teeth restored with customized fiber posts had greater fracture strength than those restored with intact posts. The results of this study indicated that post remodeling is a safe means to facilitate adaptation to root walls and preserve tooth structure. [ABSTRACT FROM AUTHOR]

The distributed permutation flowshop scheduling problem (DPFSP) has attracted a lot of attentions in recent years. Furthermore, sequence-dependent setup time (SDST) often occurs in the job's production, and total flowtime becomes a more important and meaningful objective for the modern dynamic productive environment. Therefore, the DPFSP with SDST under minimization of total flowtime is investigated in this paper, and the mathematical model is established. To solve the problem, this paper presents three constructive heuristics and an effective discrete artificial bee colony (EDABC) method based on the acceleration. In the EDABC, the constructive heuristics are used to initialize population. Moreover, based on the problem-specific of sequence-dependent, the employed bees stage, onlooker bees stage and scout bees stage are improved by exploring the acceleration methods to evaluate the neighboring solutions. Further, to strengthen the performance of the proposed algorithm, three effective problem-oriented local search methods are developed, including referenced local search (RLS), improved local search 1 (ILS1) and improved local search 2 (ILS2). RLS is used to the best solution after the initialization, and ILS1 and ILS2 are designed in the framework of improved variable neighborhood descent. The extensive computational experiences are carried out, and the results show that the proposed methods, including three heuristics and EDABC, have outstanding performance for the SDST/DPFSP to minimize the total flowtime. • The DPFSP with SDST under minimization of total flowtime is investigated, and 3 heuristics are presented. • An effective discrete artificial bee colony (EDABC) method based on acceleration is proposed. • Experimental design and analysis of variance (ANOVA) are carried out to verify the proposed EDABC. • The experimental evaluation is used to verify the validity of constructive heuristics and EDABC. [ABSTRACT FROM AUTHOR]

This paper summarizes the results of a faculty internationalization perception survey completed by 74 computing faculty. Building on the results of an earlier part of the project (Phase 1), this phase sought to determine whether the hypotheses generated in during data exploration phase would be replicated. For each hypothesis generated in Phase 1 an ANOVA was conducted that determined no statistically significant difference existed at 0.5 alpha level. The lack of a statistically significant difference was not anticipated. Nevertheless, this is an important finding as it is counter to what was discovered in initial research. The concluding section offers some explanation for the unanticipated findings. [ABSTRACT FROM AUTHOR]

Ear infection or otitis media (OM) occurs in many Aboriginal and Torres Strait Islander children at a young age and tends to persist over a long period of time. Chronic OM is associated with conductive hearing loss that reduces a child's access to sounds. This can have a negative impact on development of listening and communication skills. Primary health and early childhood workers are best positioned to detect children with hearing and listening problems. However, they lack appropriate tools to screen and triage young children for early referral. By using a co-design approach with Aboriginal primary health workers and early childhood teachers, we have developed the Parents' Evaluation of Listening and Understanding Measure (PLUM) listening skills questionnaire. The PLUM provides a systematic framework for front-line workers to explore a parent's observations of their child's listening behaviour in everyday situations to detect hearing and listening problems in young Aboriginal children. This paper reports the development of the scale. PLUM scores for 438 children from urban, regional and remote communities in Australia were collected. The internal consistency reliability was 0.87. Normative data from 235 children with normal hearing (hearing thresholds averaged between 0.5 and 4 kHz in the better ear to be no greater than 20 dB HL) were used to define the relationship between PLUM scores and age. The functions allow performance of individual children to be related to their normal-hearing peers. [ABSTRACT FROM AUTHOR]

Background: Healthcare provider (HCP) interactions with pediatric patients and their parents requires methods of communication differing from the HCP/adult patient experience. Gaps remain in understanding strategies and tactics that HCPs might use during pediatric patient interactions. For instance, research is needed to differentiate HCP/pediatric patient interactions among distinct groups such as infants, young children, pre-adolescents, and adolescents. Similarly, HCP beliefs about how an interaction should flow may not match those of parents – with possible consequences regarding compliance with treatment. Methods: This paper reviews research into HCP/pediatric patient interactions and presents survey results that show where expectations align or differ between HCPs and parents. Results: HCPs and parents generally approach the pediatric encounter with similar expectations. However, differences in specific situations are informative. HCPs are more focused on patients than parents. They are more sensitive than parents to situations involving difficult topics and change their approach for different age groups or developmental statuses. HCPs are more responsive to patients than parents for scenarios that involve delicate content, more so for scenarios that require being forthright with their patients. Parents prefer more thorough explanations when reasonable, and want to take part in discussions even when HCPs are more focused on their pediatric patients, especially for adolescents. Conclusion: Having a fuller understanding of the expectations that HCPs and parents hold implies changes in how students in healthcare fields are trained; having better insight into this relationship will prepare them for interacting with pediatric patients while still addressing the needs of parents. [ABSTRACT FROM AUTHOR]

This study explored women snow-sport tourists' destination attribute preferences in relation to their participation level (e.g. skill; sport career stage) through a complementary sequential mixed-methods approach. Initially, a model illustrating a trajectory of snow-sport participation, travel behavior and preferences was created through qualitative methods. This paper presents the quantitative testing of this proposed trajectory model and the associated destination attribute preferences. Enduring Involvement was used to quantitatively assess proposed stages of the snow-sport participation trajectory. Exploratory Factor Analysis revealed two dimensions in women's enduring involvement in snow-sports: 'identity/centrality' and 'hedonism'. Additionally, three dimensions were found for destination attributes: 'resort amenities and activities', 'snow-sport conditions and quality', and 'price'. A Multivariate Analysis of Variance showed that stages of the trajectory could be quantitatively verified. Analysis of Variance indicated that the importance placed on 'resort amenities and activities' decreased as women progressed along the trajectory. 'Snow-sport conditions and quality' was rated higher by more advanced skiers/snowboarders. 'Price' was rated highly along the trajectory stages. [ABSTRACT FROM AUTHOR]

Aims and objectives: To investigate the impact of workplace factors on burnout in New Zealand registered nurses (RNs). Background: Nursing is characterised by chronic workplace stress. Research examining the role of workplace factors (ie practice environment and bullying) in shaping burnout is scarce. Methods: A cross-sectional survey was conducted among 480 New Zealand RNs. Burnout was self-reported using the CBI, while practice environment and negative acts in the workplace were selfreported using PES-NWI, and NAQ-R respectively. The STROBE checklist was used for this paper. Results: For every point increase in PES-NWI, there was a decrease of 6.82, 12.62, and 9.86 points in personal burnout (PB), work-related burnout (WRB), and client-related burnout (CRB) respectively after controlling for demographic and job-related characteristics. For every point increase in NAQ-R, there was an increase of 0.47, 0.50, and 0.20 points in PB, WRB, and CRB respectively after controlling for sample characteristics. These two factors explained for 18.4 percent, 27.6 percent and 12.4 percent of the variation in PB, WRB and CRB respectively. The prevalence of high PB, WRB and CRB was 50.8 percent, 46.5 percent and 16.0 percent respectively. Conclusion: Workplace factors are associated with burnout in RNs. Health-care organisations and nurse leaders have a duty to provide safe and healthy workplaces that cultivate positive outcomes for nurses and patients. Future efforts to reduce workplace stress and burnout in nurses will need to include initiatives that reduce high workloads, provide greater job flexibility and autonomy, increase collaboration and reduce bullying and harassment. [ABSTRACT FROM AUTHOR]