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This study aims to examine the influence of the role of immersive technology on perceived learning's effectiveness by considering the cognitive load of users when using VR-based learning media. This study involved a total of 91 respondents who had attended virtual reality-based learning training. In this research, SmartPLS was used to test the measurement and structural models. This research was conducted through virtual reality-based learning training, to measure the effect of using VR on perceived effectiveness, with cognitive load as the moderator. The research results support all the hypotheses. Ultimately, cognitive overload moderates the relationship between reflective thinking and perceived learning's effectiveness. The lower the cognitive load of the user when using VR, the greater the positive effect reflective thinking has on perceived learning's effectiveness, and vice versa. There are still many contradictions regarding the effectiveness of VR in learning, so this research fills the gap by examining the effect immersive technology has on learning outcomes, by considering the cognitive load of users when using VR-based learning media. This research has several practical implications. First, VR could be proposed as a valuable investment for educational institutions as a learning tool. Second, it is very important to develop VR that is adapted to the context and learning objectives, to optimize its effectiveness. Third, VR developers should focus on creating simplified menus that are easy to use. By reducing the cognitive overload, users will find VR more comfortable and enjoyable to use. [ABSTRACT FROM AUTHOR]

Sensory Over-Responsivity (SOR) is an increasingly recognized challenge among children with neurodevelopmental concerns (NDC). To investigate, we characterized the incidence of auditory and tactile over-responsivity (AOR, TOR) among 82 children with NDC. We found that 70% of caregivers reported concern for their child's sensory reactions. Direct assessment further revealed that 54% of the NDC population expressed AOR, TOR, or both – which persisted regardless of autism spectrum disorder (ASD) diagnosis. These findings support the high prevalence of SOR as well as its lack of specificity to ASD. Additionally, AOR is revealed to be over twice as prevalent as TOR. These conclusions present several avenues for further exploration, including deeper analysis of the neural mechanisms and genetic contributors to sensory processing challenges. [ABSTRACT FROM AUTHOR]

The Dunhuang murals, a significant part of Chinese heritage, have suffered deterioration primarily due to environmental and chemical factors, notably salt damage. This study proposes a sophisticated method that synergizes Fractional Order Differentiation (FOD) and Partial Least Squares Regression (PLSR) to accurately invert the phosphate content in the mural plaster of the Dunhuang paintings. The focal points of the research include: (1) To address the issue of information loss and reduced modeling precision caused by integer-order differentiation algorithms, the FOD method is employed for preprocessing spectral data. This approach ensures the fine spectral differences in the phosphate content of the mural plaster are precisely captured, (2) Utilizing PLSR, the study models the spectral bands identified at a significance level of 0.01 with measured conductivity values, thereby enabling the precise prediction of the phosphate content in the murals. The research outcomes reveal: (1) The FOD method can elucidate the nonlinear characteristics and variation patterns of the mural samples in the spectral data. As the order increases from zero to two, the number of spectral bands meeting the 0.01 significance test initially decreases and then increases. The highest absolute value of the positive correlation coefficient is observed at the 1.9 order, corresponding to the 2077 nm band, (2) For predicting the phosphate content in the murals, the model at the 1.9 order is most suitable for inversion. This model, after cross-validation, achieves a maximum R2 value of 0.861. This study created an efficient FOD-based model for estimating phosphate in mural plaster. [ABSTRACT FROM AUTHOR]

Purpose: The goal of our study was to better characterize new CT diagnoses of peritoneal carcinomatosis (PC) in the ED, and to evaluate how to best identify the primary lesion. Prompt identification of the source of the carcinomatosis may allow for the patient to receive early initial care from the correct clinical service. Methods: All new CT cases of PC-like appearance identified on CT in the ED from January 2017 through July 2020. Each report and corresponding medical record were manually reviewed. Patient demographics, presence/absence of intravenous contrast, source organ predicted by the radiologist in the CT scan report, pathologic diagnosis, and amount of ascites were tabulated. Chi-tests were used to test the statistical significance of differences between groups. Results: Of the 131 CT cases of new PC-like appearance which received workup, 108 cases had pathologically proven PC and 23 cases had no underlying malignancy yielding a positive predictive value for actual PC of 82%. The most common cause of new PC in women was gynecological (66%), and in men was of GI tract origin (57%). Concordance between radiologist prediction and final pathology was higher with intravenous contrast (58%) compared to without contrast (40%); although this difference was not statistically significant (p = 0.19). A moderate or large amount of ascites was found in more than half of GYN primaries and in adenocarcinoma of unknown primary and there was a statistically significant difference in amount of ascites between cancer primaries (p = 0.01). Conclusion: A PC-like appearance on CT in the ED will likely be in patients with known malignancy, but of the new cases, there is a high PPV for it to represent new peritoneal carcinomatosis. Gynecological and GI malignancies are the most common cause in women and men, respectively, and this may help in focusing the radiologist's search pattern. Usage of intravenous contrast may help in identifying a primary lesion, and the presence of high-volume ascites should suggest a GYN primary or adenocarcinoma of unknown primary when there is no other obvious primary lesion. [ABSTRACT FROM AUTHOR]

Children now are facing an increasing risk of early life stress (ELS), which leads to detrimental psychosocial outcomes. Behavior studies suggested that positive parental interactions might moderate the negative impact of ELS, but the related biological alteration remains unclear. This study aims to investigate whether positive parent–child interactions moderate the association between maltreatment (as a severe form of ELS) and hair cortisol concentration (HCC), as well as between HCC and psychosocial outcomes in young children. Participants were 6-year-old Chinese children (N = 257, Mage = 6.2, 121 were male) selected by stratified cluster random sampling from a Shanghai population representative cohort. Proximal 3 cm hair strands were analyzed using liquid chromatography coupled with tandem mass spectrometry for HCC. Children's psychosocial outcome was evaluated using the parental report Strengths and Difficulties Questionnaire (SDQ). Parents also reported the frequency of positive parent–child interactions using the Chinese Parent–Child Interaction Scale (CPCIS) as well as the history of maltreatment. Multi-level logistic regression models adjusting for individual, kindergarten, and district confounders were used to evaluate the associations between maltreatment, HCC, and psychosocial outcomes. Interactions terms tested whether more frequent positive parent–child interactions moderates the association between maltreatment and HCC, as well as between HCC and psychosocial outcomes. Maltreated children exhibited higher levels of HCC (B = 1.20, 95% CI: 0.38,2.02; p = 0.004), and children with higher HCC exhibited poorer psychosocial outcomes (B = 0.34, 95% CI: 0.18,0.51; p < 0.001). Positive parent–child interactions did not have a moderating effect on the association between maltreatment and HCC, but they demonstrated a moderating effect on the association between increased HCC and psychosocial outcomes (interaction term: B = −0.42, 95% CI: −0.75,−0.10; p = 0.01). These findings provide evidence that positive parental interaction may serve as a moderator between chronic cortisol exposure and psychosocial problems. It highlights the importance of frequent parent–child interactions, especially among children under a high risk of ELS. [ABSTRACT FROM AUTHOR]

The identification of anticancer peptides (ACPs) is crucial, especially in the development of peptide-based cancer therapy. The classical models such as Split Amino Acid Composition (SAAC) and Pseudo Amino Acid Composition (PseAAC) lack the incorporation of feature representation. These advancements improve the predictive accuracy and efficiency of ACP identification. Thus, the effort of this research is to propose and develop an advanced framework based on feature extraction. Thus, to achieve this objective herein we propose an Extended Dipeptide Composition (EDPC) framework. The proposed EDPC framework extends the dipeptide composition by considering the local sequence environment information and reforming the CD-HIT framework to remove noise and redundancy. To measure the accuracy, we have performed several experiments. These experiments were employed using four famous machine learning (ML) algorithms named; Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), and K Nearest Neighbor (KNN). For comparisons, we have used accuracy, specificity, sensitivity, precision, recall, and F1-Score as evaluation criteria. The reliability of the proposed framework is further evaluated using statistical significance tests. As a result, the proposed EDPC framework exhibited enhanced performance than SAAC and PseAAC, where the SVM model delivered the highest accuracy of 96. 6% and significant enhancements in specificity, sensitivity, precision, and F1-score over multiple datasets. Due to the incorporation of enhanced feature representation and the incorporation of local and global sequence profiles proposed EDPC achieves higher classification performance. The proposed frameworks can deal with noise and also duplicating features. These are accompanied by a wide range of feature representations. Finally, our proposed framework can be used for clinical applications where ACP identification is essential. Future works will include extending to a larger variety of datasets, incorporating tertiary structural information, and using deep learning techniques to improve the proposed EDPC. [ABSTRACT FROM AUTHOR]

Background: A fistula is an unusual communication between the skin and an inward organ or between the organs. The current study aimed to determine the role of magnetic resonance imaging (MRI) in the diagnosis, description, and classification of fistula-in-ano. Additionally, the study aimed to compare the MRI findings with the operative findings, which is considered the gold standard in our study. Methods: The present study is a prospective study and was carried out on a group of 61 patients: 52 males and 9 females with a mean age of 41 years, who were suspected to have perianal fistulae presented clinically with discharge or localized pain or were asymptomatic. A preoperative MRI was conducted for fistula-in-ano evaluation in these patients from October 2019 till the end of October 2021. A surgeon conducted a physical examination of all patients to document the number and location of cutaneous openings following a full medical history. The MRI images were evaluated and interpreted by multiple expert radiologists who had more than 5 years of experience in analyzing MRI. In the cases (in 3 cases, 4.92%) where there were discrepancies in their interpretations, a senior radiologist's evaluation was considered the final result and was confirmed surgically. Subsequently, the MRI findings were correlated with surgical findings to indicate the specificity, sensitivity, and accuracy of such MRI findings. Results: The MRI technique was the routine (i.e., without contrast administration) technique in 36 (59.02%) patients, with contrast administration in 21 (34.43%) patients and with anesthesia/sedation (uncomfortable, anxious, and claustrophobic patients need to minimize their motion artifact to improve the quality and obtain more detailed images) in 4 (6.56%) patients. The MRI pathology of the studied patients revealed normal findings in 1 (1.64%) patient, anal fissure/early developing tract in 6 (9.84%) patients, and established tract (sinus/fistula) in 54 (88.52%) patients. Park's and St. James's University Hospital classifications were utilized to categorize the patients, with the most common fistula types based on the Park's classification: intersphincteric (44.3%) and transsphincteric (29.5%). Based on the St. James's classification, grade 1 (intersphincteric (34.4%)) and grade 4 (transsphincteric with abscess/side branch (16.4%)) were the most prevalent. A substantial consensus was reached between MRI and surgery findings for classifying tracts, side branches, and abscesses formation with sensitivity, specificity, and accuracy of 100%, 85.71%, and 98.36%, respectively. Conclusions: MRI is a valuable tool in managing patients with perianal fistulas due to its ability to detect hidden areas of infection (such as abscesses) and secondary extensions. These factors contribute to the high recurrence rate after surgery. Additionally, MR imaging can define the anatomical relationships between the fistula and anal sphincters, helping to predict the likelihood of fecal incontinence following surgery. [ABSTRACT FROM AUTHOR]

Web annotation environments are widely used in education based on the premise that student interaction in these environments benefits individual and group learning. However, there is little research on factors driving student interaction in web annotation activities. In this study we asked: What dynamics could explain social interaction among students in web annotation activities in college classrooms? Recognizing the mediated nature of social interaction in web annotation, we hypothesized that student interaction is driven by multiple factors including previous relational events and semantic features of annotation content. Following a novel network analysis method named relational event modeling, we analyzed a rich dataset from four online classes. Results indicated annotation popularity was initially predictive of student replies, meaning popular annotation threads were more likely to attract new replies. However, this effect nearly diminished when adding thread-level semantic cohesion to the model, indicating an significant role played by semantic cohesion in attracting new responses. This paper makes important progress towards modeling social interaction in digital environments as a dynamic, mediated phenomenon. This study contributes empirical insights into web annotation and calls for future work to investigate social interaction as a dynamic network phenomenon. [ABSTRACT FROM AUTHOR]

Maternal characteristics mainly shape attachment security in early childhood and can impact toddler's emotional and social development. Although early determinants of attachment have been widely explored in the West, the studies in non-Western cultures are limited, especially in high-risk groups such as low-SES samples. Therefore, we examined the role of maternal parenting stress, attachment dimensions of anxiety and avoidance in romantic relationships and emotional availability in toddlers' attachment security. The Turkish mothers (N = 63; Mage = 30.17; SD = 4.87) filled out a pack of questionnaires including the Parenting Stress Index-Short Form (PSI-SF; Abidin, 1995) and Experiences in Close Relationships-Revised (ECR-R; Fraley et al., 2000) before video recorded home visits. The toddlers' (Mage = 22.96 months, SD = 7.09) attachment security was coded for Attachment Q-Sort (AQS; Waters, 1995) based on 2.5-h home-visit and 10-min free-play sessions were coded for Emotional Availability Scales (EAS; Biringen, 2008). The results showed that the mother's attachment avoidance and parenting stress were negatively associated with the child's attachment security, while the maternal sensitivity and structuring were positively associated with the child's attachment security. The mothers' behaviours on EAS did not mediate the relationship between maternal attachment dimensions and toddlers' attachment security. We showed that maternal attachment avoidance, parenting stress, lack of sensitivity and structuring behaviours could contribute to insecure attachment in Turkish toddlers. These identified factors warrant attention in the design and implementation of early intervention programs, particularly for mothers from low socio-economic status (SES) backgrounds in Turkey and in non-Western cultures characterised by similar cultural characteristics. Highlights: We examined the role of parenting stress, attachment, and emotional availability on the toddlers' attachment security. The results were obtained through observational data collected in-home visits from a sample of mothers and toddlers from low-SES background. This study represents one of the first attempts to apply Emotional Availability Scales and Attachment Q-Sort in a non-Western cultural context. Maternal attachment avoidance, parenting stress, sensitivity, and structuring emerged as potential early intervention areas. [ABSTRACT FROM AUTHOR]

Purpose: This study investigates baseline patient demographics and predictors of vascular injury, blood transfusion, and compartment syndrome in patients with orthopaedic fractures secondary to GSWs at two high-volume Level I trauma centres. Methods: A retrospective chart review of all GSW-related trauma patients at two Level I trauma centres between July 2019 and September 2021 was conducted. Chi-squared and two-tailed independent t tests were used for data analysis, and logistic regression with odds ratios (OR) determined predictors of primary outcomes. Results: Among 478 GSW patients, 94 (19.7%) sustained 130 orthopaedic fractures, most commonly at the lower extremity (77.7%). Orthopaedic fracture patients showed significantly higher rates of vascular injury (29.8 vs. 4.7%, p < 0.001), transfusion (27.7 vs. 12.8%, p = 0.006), and compartment syndrome (3.2 vs. 0.3%, p = 0.011) compared to non-orthopaedic injury patients. Univariable analysis identified ankle (OR = 47.50, p < 0.001) and hip/femur fractures (OR = 5.31, p < 0.001) as predictors of vascular injury. Multivariable logistic regression revealed lower extremity vascular injury (OR = 54.69, p = 0.006) and anatomic fracture sites of the humerus (OR = 15.17, p = 0.008), clavicle/scapula (OR = 11.30, p = 0.009), and acetabulum/pelvis (OR = 7.17, p = 0.025) as predictors of blood transfusion. Univariable analysis showed lower extremity vascular injury (OR = 30.14, p = 0.007) as a predictor of compartment syndrome. Conclusion: These findings underscore the importance of diagnosing and managing vascular injuries and compartment syndrome in GSW-related orthopaedic fractures, emphasizing the necessity for targeted transfusion strategies in such cases. [ABSTRACT FROM AUTHOR]

This experiment was designed to study the surface defects of 20 % volume fraction SiCp/Al composites after grinding and to provide the necessary experimental results for optimizing grinding parameters. Based on the two-dimensional cutting simulation model of single particle, the main damage of particles in matrix during machining has been investigated. The particles in SiCp/Al composites are randomly distributed and the tool will cut through multiple particles in a single cut and at different locations. A single particle cutting model was developed to study the different states of particle fragmentation by cutting through the upper, middle and lower parts of the particles respectively. Nine groups of parameters were obtained by orthogonal experimental design, and electroplated diamond grinding rod was used as the grinding tool for grinding experiment. In order to get the best surface grinding parameters, a ternary linear regression equation was selected to be established. Significance test could prove the reliability of the linear regression equation, and then, the optimal solution of this equation can be calculated by the MATLAB genetic algorithm toolbox. From the simulation and experimental results, it can be seen that the stress begins to concentrate when the cutting tool is close to the particle, and when the cutting stress exceeds the ultimate compressive strength, the particle is broken and part of it will be pulled out. The breakage of particles is not one-time, but requires many times of large cutting force to break the particles in sections, and the repeated breakage of particles eventually leads to the generation of overall cracks. [ABSTRACT FROM AUTHOR]

Extractive document summary is usually seen as a sequence labeling task, which the summary is formulated by sentences from the original document. However, the selected sentences usually are high redundancy in semantic space, so that the composed summary are high semantic redundancy. To alleviate this problem, we propose a model to reduce the semantic redundancy of summary by introducing the cluster algorithm to select difference sentences in semantic space and we improve the base BERT to score sentences. We evaluate our model and perform significance testing using ROUGE on the CNN/DailyMail datasets compare with six baselines, which include two traditional methods and four state-of-art deep learning model. The results validate the effectiveness of our approach, which leverages K-means algorithm to produce more accurate and less repeat sentences in semantic summaries. [ABSTRACT FROM AUTHOR]

Background: There are few available studies that compare the feasibility, efficacy, and safety of robotic pelvic lateral lymph node dissection compared to laparoscopic pelvic lateral lymph node dissection (LPLND) in advanced rectal cancer. This meta-analysis aims to compare perioperative outcomes between robotic and LPLND. Methods: We performed a systemic literature review of PubMed, Embase, and Web of Science databases. Perioperative parameters were extracted and pooled for analysis. This meta-analysis provided an analysis of heterogeneity and prediction intervals. Results: Five studies were included: 567 patients divided between 266 robotic and 301 LPLND. Overall operation time was longer in the robotic group than laparoscopic group (difference in means = 67.11, 95% CI [30.80, 103.42], p < 0.001) but the difference in the pelvic lateral lymph dissection time was not statistically significant (difference in means = − 1.212, 95% CI [ − 11.594, 9.171], p = 0.819). There were fewer overall complications in the robotic than in the laparoscopic group (OR = 1.589, 95% CI [1.009, 2.503], p = 0.046), especially with respect to urinary retention (OR = 2.23, 95% CI [1.277, 3.894], p = 0.005). More pelvic lateral lymph nodes were harvested by robotic surgery than by laparoscopy (differences in means = − 1.992, 95% CI [ − 2.421, 1.563], p < 0.001). Conclusions: In this meta-analysis, robotic pelvic lateral lymph node dissection was associated with more pelvic lateral lymph nodes harvested and lower overall complications, especially urinary retention when compared to LPLND. Further studies are needed to reinforce these findings. [ABSTRACT FROM AUTHOR]

Purpose: To determine the safety and efficacy associated with drainage volumes greater than 1,500 mL in a single, unilateral thoracentesis without pleural manometry measurements. Materials and Methods: This retrospective, single-institution study included 872 patients (18 years and older) who underwent ultrasound-guided thoracentesis. Patient and procedures data were collected including demographics, number of and laterality of thoracenteses, volume and consistency of fluid removed, and whether clinical or radiologic evidence of re-expansion pulmonary edema (REPE) developed within 24 h of thoracentesis. Fisher's exact test was used to test the significance of the relationship between volume of fluid removed and evidence of REPE. Results: A total of 1376 thoracenteses were performed among the patients included in the study. The mean volume of fluid removed among all procedures was 901.1 mL (SD = 641.7 mL), with 194 (14.1%) procedures involving the removal of ≥ 1,500 mL of fluid. In total, six (0.7%) patients developed signs of REPE following thoracentesis, five of which were a first-time thoracentesis. No statistically significant difference in incidence of REPE was observed between those with ≥ 1,500 mL of fluid removed compared to those with < 1,500 mL of fluid removed (p-value = 0.599). Conclusions: Large-volume thoracentesis may safely improve patients' symptoms while preventing the need for repeat procedures. [ABSTRACT FROM AUTHOR]

Over the last decade, online learning has seen considerable growth, with this being supported by the rapid development of the Internet and other technologies. It is therefore vitally important for academics and practicians to evaluate the effectiveness of e-learning, so they can enhance the learners' acquisition of knowledge and the performance of educational organizations. This study was conducted within this context with the aim of assessing the effectiveness of e-learning and investigating its main predictors, as well as the moderating role of learners' self-efficacy. A conceptual model was developed and used to test the relationships that e-learning effectiveness has with the online interactions between learners and course content, learners and other learners, and learners and the instructor. In addition, self-efficacy with Internet and computer technologies and online communication was also examined as a potential moderator. To test our research hypotheses, we conducted a quantitative empirical study through a web-based survey, with structural equation modeling being used to analyze the data. Online interactions between learners and course content and between learners and the instructor were both found to be significant predictors of e-learning's effectiveness. In addition, self-efficacy was found to play a significant moderating role but only in the dimension of online communication. This paper makes a novel contribution to the existing literature by investigating e-learning's effectiveness as a bi-dimensional concept covering net benefit and e-learner satisfaction. In addition, this study adds to our understanding of online learning by investigating the moderating role that students' self-efficacy can play in terms of both the communicational and technological dimensions. For institutions of higher education, the findings of this study provide some constructive insights and useful recommendations for improving the effectiveness of e-learning systems. [ABSTRACT FROM AUTHOR]

Background: The pre-season preparatory period is considered key for optimizing the physical fitness levels needed to withstand congested match periods and preventing injuries during the regular soccer season. This study contrasted the effects s of neuromuscular training (NMT) versus an endurance-dominated training (ET) program conducted during the preseason on measures of physical fitness and injury occurrence in female soccer players. Methods: Twenty-four female soccer players aged 17.0 ± 1.3 years from a professional soccer club participated in this study. Players were randomly assigned to NMT (n = 12) or ET (n = 12) groups according to their playing position. The preseason intervention program lasted six weeks, with three weekly sessions with a duration of 45–60 min per session. Exercises in the NMT group included muscle strengthening exercises, plyometrics, agility and dynamic stability exercises, while the ET group practiced a traditional pre-season training program consisting of running and sprinting exercises, fartlek, and high-intensity interval training. The training volumes were similar in the two study groups. Anthropometric measurements, physical fitness tests (i.e., linear and change-of-direction speed, muscle strength and power tests) and the overall injury rate per 1000 h of exposure (training, match) were recorded throughout the season. Results: No between group differences were found at pre (T1). Significant group-by-time interactions were observed for the 5, 10, and 30-m linear sprint speed tests (p < 0.001, 2.16 < d < 2.58), the T-test (p = 0.024, d = 1.03), the squat (p < 0.001, d = 4.04), and the countermovement jump test (p < 0.001, d = 2.21), the Loughborough soccer passing test (LSPT) (p = 0.019, d = 1.08), and the 1-RM back squat test (p < 0.001, d = 2.53). Post-hoc tests indicated that NMT provided larger improvements for SJ, CMJ, 1-RM back squat, the 5-m sprint, 10-m sprint, 30-m sprint, T-test and LSPT compared to ET (1.07 > d > 2.77). The injury rate across the season was significantly lower in the NMT (5.1/1000 h exposure) compared to ET (11.8/1000 h exposure) (p = 0.014). Conclusions: The findings support that six-weeks of preseason NMT versus ET induced larger performance improvements, and significantly reduced injury occurrence in elite female soccer players. Key points: • Our results indicate that the integration of 45 to 60 min of preseason neuromuscular training, three times per week, for 6 weeks, can improve physical fitness and prevent injuries in young female soccer players. • The present study demonstrated that the neuromuscular training program can reduce the incidence injury rate by more than 50% and the burden by more than 65% compared to the endurance-dominated training. • Neuromuscular training is an effective approach during the preseason period to improve diverse measures of physical fitness and to reduce injury occurrence. • Preseason neuromuscular training appears to improve the fitness level of female soccer players and as such could allow them to compete at the high level. [ABSTRACT FROM AUTHOR]

Background: Frequency discrimination underlies more complicated auditory activities like speech comprehension and interpretation. However, intensity differences indicate how far apart noises are. This study aimed to evaluate and compare results of frequency modulation and difference limen for intensity in children with cochlear Implants (CI) as well as normal hearing children. Results: This case–control work was performed on 40 children, aged from 5–18 years, divided into two equal groups: a study group with unilateral CI and a control group with normal peripheral hearing. All patients were subjected to otological examination, audiological evaluation, frequency modulation difference limen (FMDL) and difference limen for intensity (DLI) tests. Patients with CI, as compared to normal hearing (NH) subjects, required significantly higher frequencies to discriminate FMDL and DLI respectively (P value = 0.001). At 2000 and 4000 Hz: FMDL had a significant diagnostic power for patients with CI (AUC = 0.980, 0.998 respectively, P < 0.001), at cut off 1.5, with 100% sensitivity and 100% specificity. While, at 4000 Hz: DLI had a significant diagnostic power for patients with CI (AUC = 0.999, P < 0.001), at cut off 1.5, with 100% sensitivity and 100% specificity. Conclusion: A statistically substantial variation was observed among CI and NH children in FMDL and DLI at all frequencies tested. Patients with CI required significantly higher frequencies to discriminate as compared to NH subjects. Frequencies at 2000 Hz and 4000 Hz possess the best specificity and sensitivity of FMDL. While frequency 4000 Hz possess the best specificity and sensitivity of DLI. [ABSTRACT FROM AUTHOR]

The gravity field of the Earth is time-dependent due to several types of mass variations which take place on different time scales. Usually, the time-variability of the gravitational potential of the Earth is expressed by the monthly determination of a static geopotential model based on data from gravity field missions. In this paper, the variability of the potential is parameterized by a functional approach which contains a polynomial trend and periodic contributions. The respective parameters are estimated based on the monthly solutions derived from the GRACE and GRACE-FO gravity field mission up to a maximum degree of expansion n max = 96 . As a preliminary data analysis, a Fourier analysis is performed on selected potential coefficients from the available monthly solutions of the GFZ. The indicated frequency components are then used to formulate a time-dependent analytical approach to describe each Stokes coefficient's temporal behaviour. Different approaches are presented that include both polynomial and periodic components. The respective parameters for modelling the temporal variability of the coefficients are estimated in a Gauss-Markov model and tested for significance by statistical methods. Extensive comparative numerical studies are carried out between the newly generated model variants and the existing monthly GRACE, GRACE-FO and the existing time dependent EIGEN-6S4 solutions. The numerical comparisons make it clear that estimated models based on all available monthly solutions describe the essential periods very well, but such monthly events that deviate strongly from the mean behaviour of the signal show less precision in the space domain. Models that are estimated based on fourteen consecutive monthly solutions, covering one selected year, represent the amplitudes much more precise. The statements made apply to four initial data used, which are filtered to varying degrees. In particular, DDK2, DDK5 and DDK8, as well as unfiltered coefficients were used. For all the model approaches used, it can be seen that the potential coefficients contain up to about n ≈ 40 in case of DDK5 periodically signals with annual, semi-annual or quarterly, as well as Luna nodal periods and do not vary significantly beyond that degree. Only an offset can be estimated significantly for all Stokes coefficients. [ABSTRACT FROM AUTHOR]

The purpose of this project is to assess, for practicing pediatric nurses in the U.S., what is the impact of the Stewards of Children Child Sexual Abuse (CSA) program on their attitudes about reporting suspected CSA. A sample size of 32 nurses completed an online 2-hour continuing education course by Stewards of Children, with a pre/post-test survey. A modified 14-item version of the Teachers Reporting Attitudes Scale for Child Sexual Abuse (TRAS-CSA) was used to measure the nurses' attitudes before and after educational training. The surveys were analyzed to assess changes in attitudes using two-tailed sign tests. Nurses' commitment to reporting CSA is high, even before training. Nurses' confidence in the system of reporting and in the response of authorities related to CSA increased after taking the Stewards of Children online course. While these results are limited in strength by low sample sizes and some null changes, they indicate that trainings like the Stewards of Children course can positively impact nurses' attitudes towards reporting CSA, particularly with regards to confidence in reporting, and therefore warrant further investigation into CSA training for nurses and its effects. [ABSTRACT FROM AUTHOR]

Background: Gastrointestinal Stromal Tumors (GISTs) are the most common mesenchymal tumors of the GI tract. SEER is an extensive cancer database which proves useful in analyzing population trends. This analysis investigated GIST outcomes between geriatric & non‐geriatric patients. Methods: SEER*STAT 8.4.0.1 was used to extract relevant GIST data from 2000 to 2019. Geriatric age was defined as ≥70 years. Variables included age, sex, surgery, cancer‐specific death, and overall survival. Statistical tests included univariate analysis using KM survival estimate (95% confidence interval) to calculate 5‐year survival (5YS). Log‐Rank tests determined statistical significance. Multivariable Cox's PH regression estimated the geriatric hazard death ratio adjusted for sex, stage, and surgery. Results: The number of patients included was 13,579, yielding overall 5YS of 68.6% (95% CI 67.7–69.5). Cancer‐specific death was 39.11% in 2000 & 3.33% in 2019. Non‐geriatric & geriatric patient data yielded 5YS of 77.4% (76.4%–78.3%) and 53.3% (51.7%–54.8%) respectively (p < 0.0001). For no surgery/surgery, younger patient data yielded 5YS of 48.7% (45.8%–51.4%) and 83.7% (82.7%–84.7%) respectively (p < 0.0001); geriatric data yielded 5YS of 29.3% (26.5%–32.1%) and 62.8% (60.8%–64.6%) respectively (p < 0.0001). Multivariable analysis yielded a geriatric hazard death of 2.56 (2.42–2.70) (p < 0.0001). Conclusions: Cancer‐specific death decreased since 2000, indicating an improvement in survival & treatment methods. Observed lower survival rates overall in the geriatric group. Surgery appeared to enhance survival rates in both groups, suggesting that surgery is an important factor in GIST survival regardless of age. Large prospective studies will help define clinical management for geriatric patients. [ABSTRACT FROM AUTHOR]

Recently, there has been increased interest in issues related to functional linear regression models with points of impact. While the estimation of model parameters with a scalar response has been considered in past studies, there has been no attention on the hypothesis testing for these impact points. To test this hypothesis, one needs to determine the asymptotic distribution of the impact points coefficients estimators. In recent literature, the asymptotic distribution has been pointed out in a special case, but the proof has not been provided. Taking into account the necessary conditions, this study establishes the asymptotic distribution for the estimators of impact points coefficients in a general setting. It also offers a method to test the significance of these impact points. To validate the proposed test's asymptotic properties, a simulation study is conducted to assess its performance under various parameter settings. Furthermore, the study analyzes Iranian weather data collected from January 1st to 31st, 2023. [ABSTRACT FROM AUTHOR]

This paper considers the problem of testing statistical hypotheses about the variance components under linear models with crossed random effects. The objective here is two-fold. First, new derivations of exactly distributed F test statistics are presented. Second, an alternative Monte Carlo permutation procedure is proposed to approximate the distribution of the F statistics, which shows its usefulness when the error components distributions depart from normality. Transformations that uniquely decompose the covariance structure of the response vector and do not sacrifice any part of the data, as existing methods do, are presented in matrix form. The suggested transformations highlight the exchangeable covariance structure of the model under the null hypotheses of interest and thus motivate the use of the permutation procedure. Comments on the performance of the proposed procedure compared to existing tests as well as using a real data example are provided. [ABSTRACT FROM AUTHOR]

Edwin Locke's (1969, 1976, 1984) range-of-affect (RoA) hypothesis played a critical role in the literature on job satisfaction. Drawing on the parallel between job facets (e.g., freedom and promotion opportunities) to job and life domains (e.g., health and family) to life, the RoA hypothesis has also been applied to the subjective well-being (SWB) literature. The application of the RoA hypothesis to the SWB literature has focused on the topic of domain importance weighting which refers to the use of weighting of domain importance in aggregating domain-specific satisfaction to obtain overall satisfaction or SWB. The purpose of this study is to examine the applicability of the RoA hypothesis to the SWB literature, particularly concerning the topic of domain importance weighting. Based on the analysis of two survey data sets, this study found that not all empirical evidence supporting the RoA hypothesis from the job satisfaction literature could be replicated in the context of SWB. This study also pointed out that the empirical evidence presented to oppose domain importance weighting in the SWB context was based on an approach that deviated from the conventional approach of the null hypothesis significance test. The applicability of the RoA hypothesis from the job satisfaction context to the SWB context should not be assumed. [ABSTRACT FROM AUTHOR]

We propose Fieller-type methods for inference on generalized entropy inequality indices in the context of the two-sample problem which covers testing the statistical significance of the difference in indices, and the construction of a confidence set for this difference. In addition to irregularities arising from thick distributional tails, standard inference procedures are prone to identification problems because of the ratio transformation that defines the considered indices. Simulation results show that our proposed method outperforms existing counterparts including simulation-based permutation methods and results are robust to different assumptions about the shape of the null distributions. Improvements are most notable for indices that put more weight on the right tail of the distribution and for sample sizes that match macroeconomic type inequality analysis. While irregularities arising from the right tail have long been documented, we find that left tail irregularities are equally important in explaining the failure of standard inference methods. We apply our proposed method to analyze income per-capita inequality across U.S. states and non-OECD countries. Empirical results illustrate how Fieller-based confidence sets can: (i) differ consequentially from available ones leading to conflicts in test decisions, and (ii) reveal prohibitive estimation uncertainty in the form of unbounded outcomes which serve as proper warning against flawed interpretations of statistical tests. [ABSTRACT FROM AUTHOR]

This study is devoted to the study of the digital divide between the developed and frontier regions of China, as a model for solving the problems of the global digital divide. The research is based on a representative sample of 1,520 high school students and 220 teachers. The study included several successive stages; each of them was devoted to finding an answer to one of the formulated research questions or confirming/rejecting the corresponding hypotheses. The first stage was a survey. The researchers then tested for correlations between scores within the same geographic region. The study revealed statistically significant differences in the assessments and the level of proficiency in digital education tools in groups from developed and frontier regions, and using correlation analysis revealed the absence of significant differences in the assessments between genders in all regions and groups and established a strong correlation between the assessment of methods for e-education and the degree of proficiency and familiarity with this tool. The key reason for the digital divide was found to be insufficient access to technology rather than psychological opposition, unpreparedness for e-education, or other reasons. [ABSTRACT FROM AUTHOR]

The analysis of two-way interactions in linear models is common in the fields of ecology and evolution, being often present in allometric, macroevolutionary, and experimental studies, among others. However, the interpretation of significant interactions can be incomplete when limited to the examination of model coefficients and significance tests. The Johnson–Neyman technique represents a step forward in the interpretation of significant two-way interactions, allowing the user to examine how changes in the moderator variable, it being categorical or continuous, affect the significance of the relationship between the dependent variable and the predictor. Despite its implementation in several software since its initial development, the available options to perform the method lack certain functionality aspects, including the visualization of regions of non-significance when the moderator is categorical, the implementation of phylogenetic corrections, and more intuitive graphical outputs. Here I present the R package JNplots, which aims to fill gaps left by previous software regarding the calculation and visualization of regions of non-significance when fitting two-way interaction models. JNplots includes two basic functions which allow the user to investigate different types of interaction models, including cases where the moderator variable is categorical or continuous. The user can also specify whether the model to explore should be phylogenetically informed and choose a particular phylogenetic correlation structure to be used. Finally, the functions of JNplots produce plots that are largely customizable and allow a more intuitive interpretation of the interaction term. Here I provide a walkthrough on the use of JNplots using three different examples based on empirical data, each representing a different common scenario in which the package can be useful. Additionally, I present the different customization options for the graphical outputs of JNplots. [ABSTRACT FROM AUTHOR]

Air pollution is a growing concern in today's urbanized world, necessitating efficient and accurate methods for air quality monitoring. The proliferation of IoT devices has led to a surge in the generation of time-series data. With its high volume and complexity, this surge in time-series data necessitates cloud-based solutions for handling and analyzing this data effectively. However, existing methods for air quality monitoring face challenges in capturing the complex patterns and dynamics of air pollution, which often exhibit both linear and nonlinear characteristics. Air pollution data often exhibit both linear and nonlinear characteristics. Linearity and nonlinearity refer to the nature of the relationships within the data. Some aspects of air quality, such as pollutant concentrations, may follow linear patterns, while other factors, like the interaction of multiple pollutants and environmental conditions, exhibit nonlinear relationships. This complexity arises from the multifaceted nature of air quality dynamics, which various factors and interactions can influence. To address these challenges, this study introduces a novel hybrid time-series approach that combines the proven strengths of two well-established techniques: traditional time-series autoregressive integrated moving average (ARIMA) and soft computing adaptive neuro-fuzzy inference system (ANFIS). The hybrid model is designed to provide a comprehensive solution that accommodates the diverse characteristics of air quality time-series data. To assess the efficacy of our proposed model, we conducted extensive experiments using real-world air pollution datasets obtained from the Ministry of Environment, Forest and Climate Change of India, covering the period from January 2015 to July 2020. Our evaluation includes a range of performance metrics such as root-mean-square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and mean squared logarithmic error (MSLE). Specifically, our model demonstrates exceptional accuracy, with notably low error values for key metrics such as air quality index (AQI) and PM2.5. Furthermore, we subjected our innovative hybrid model to rigorous statistical testing using the Diebold-Mariano test, establishing the significance and superiority of our approach. This research advances our understanding of air quality prediction and offers a valuable solution for mitigating the detrimental effects of air pollution on public health and the environment. [ABSTRACT FROM AUTHOR]

Background: Accurate measurement of polyps size is crucial in predicting malignancy, planning relevant intervention strategies and surveillance schedules. Endoscopists' visual estimations can lack precision. This study builds on our prior research, with the aim to evaluate a recently developed quantitative method to measure the polyp size and location accurately during a simulated endoscopy session. Methods: The quantitative method merges information about endoscopic positions obtained from an electromagnetic tracking sensor, with corresponding points on the images of the segmented polyp border. This yields real-scale 3D coordinates of the border of the polyp. By utilising the sensor, positions of any anatomical landmarks are attainable, enabling the estimation of a polyp's location relative to them. To verify the method's reliability and accuracy, simulated endoscopies were conducted in pig stomachs, where polyps were artificially created and assessed in a test–retest manner. The polyp measurements were subsequently compared against clipper measurements. Results: The average size of the fifteen polyps evaluated was approximately 12 ± 4.3 mm, ranging from 5 to 20 mm. The test–retest reliability, measured by the Intraclass Correlation Coefficient (ICC) for polyp size estimation, demonstrated an absolute agreement of 0.991 (95% CI 0.973–0.997, p < 0.05). Bland & Altman analysis revealed a mean estimation difference of − 0.17 mm (− 2.03%) for polyp size and, a mean difference of − 0.4 mm (− 0.21%) for polyp location. Both differences were statistically non-significant (p > 0.05). When comparing the proposed method with calliper measurements, the Bland & Altman plots showed 95% of size estimation differences between − 1.4 and 1.8 mm (− 13 to 17.4%) which was not significant (p > 0.05). Conclusions: The proposed method of measurements of polyp size and location was found to be highly accurate, offering great potential for clinical implementation to improve polyp assessment. This level of performance represents a notable improvement over visual estimation technique used in clinical practice. [ABSTRACT FROM AUTHOR]

The Self-Exciting Threshold Autoregressive model (SETAR) is non-linear and considers threshold values to model time series affected by regimes. It is extended through the Multivariate SETAR (MSETAR) model, where the threshold variable can also be a multivariate process. The stationary marginal density (smd) of an MSETAR process of order one corresponds to a Unified Skew-Normal density. In this paper, the smd of an MSETAR of order one process was considered to compute explicit expressions of differential entropy and Kullback–Leibler and Jeffrey's divergences between two MSETAR(1) processes. In addition, two asymptotic tests based on divergences were built for statistical significance testing of the disparity between MSETAR(1) processes and the threshold coefficient matrix. Information measures considered involved high-dimensional integrals that likewise depended on multivariate cumulative density normal function. To solve these integrals, Genz's algorithm was considered based on Cholesky decomposition and Monte Carlo approximation. Some numerical experiments and applications to fish condition factor and Chilean economic perception time series illustrate performance. [ABSTRACT FROM AUTHOR]

The.05 boundary within Null Hypothesis Statistical Testing (NHST) "has made a lot of people very angry and been widely regarded as a bad move" (to quote Douglas Adams). Here, we move past meta-scientific arguments and ask an empirical question: What is the psychological standing of the.05 boundary for statistical significance? We find that graduate students in the psychological sciences show a boundary effect when relating p-values across.05. We propose this psychological boundary is learned through statistical training in NHST and reading a scientific literature replete with "statistical significance". Consistent with this proposal, undergraduates do not show the same sensitivity to the.05 boundary. Additionally, the size of a graduate student's boundary effect is not associated with their explicit endorsement of questionable research practices. These findings suggest that training creates distortions in initial processing of p-values, but these might be dampened through scientific processes operating over longer timescales. [ABSTRACT FROM AUTHOR]

The escalating process of urbanization has raised concerns about incidents arising from overcrowding, necessitating a deep understanding of large human crowd behavior and the development of effective crowd management strategies. This study employs computational methods to analyze real-world crowd behaviors, emphasizing self-organizing patterns. Notably, the intersection of two streams of individuals triggers the spontaneous emergence of striped patterns, validated through both simulations and live human experiments. Addressing a gap in computational methods for studying these patterns, previous research utilized the pattern-matching technique, employing the Nelder-Mead Simplex algorithm for fitting a two-dimensional sinusoidal function to pedestrian coordinates. This paper advances the pattern-matching procedure by introducing Simulated Annealing as the optimization algorithm and employing a two-dimensional square wave for data fitting. The amalgamation of Simulated Annealing and the square wave significantly enhances pattern fitting quality, validated through statistical hypothesis tests. The study concludes by outlining potential applications of this method across diverse scenarios. [ABSTRACT FROM AUTHOR]

Randomization tests represent a class of significance tests to assess the statistical significance of treatment effects in randomized single-case experiments. Most applications of single-case randomization tests concern simple treatment effects: immediate, abrupt, and permanent changes in the level of the outcome variable. However, researchers are confronted with delayed, gradual, and temporary treatment effects; in general, with "response functions" that are markedly different from single-step functions. We here introduce a general framework that allows specifying a test statistic for a randomization test based on predicted response functions that is sensitive to a wide variety of data patterns beyond immediate and sustained changes in level: different latencies (degrees of delay) of effect, abrupt versus gradual effects, and different durations of the effect (permanent or temporary). There may be reasonable expectations regarding the kind of effect (abrupt or gradual), entailing a different focal data feature (e.g., level or slope). However, the exact amount of latency and the exact duration of a temporary effect may not be known a priori, justifying an exploratory approach studying the effect of specifying different latencies or delayed effects and different durations for temporary effects. We provide illustrations of the proposal with real data, and we present a user-friendly freely available web application implementing it. [ABSTRACT FROM AUTHOR]

This paper aims to interpret the connotation of high-quality development of tourism economy (HQTE) from the perspective of the new development concepts of innovation, coordination, green, openness and sharing, and then to evaluate the spatial differentiation of China's HQTE based on provincial panel data from 2009 to 2018. Specifically, we employ the spatial convergence model to explore the absolute and conditional β convergence trends of HQTE in the whole country and the eastern, central and western regions of China. Our empirical results reveal that: 1) within the decade, from 2009 to 2018, regions of China with the highest HQTE index is its eastern region followed by the central region and then the western region, but the fastest growing one is the western region of China followed by the central region and then the eastern region. 2) Whether or not the spatial effect is included, there are absolute and conditional β convergence in HQTE in the whole country and aforementioned three regions. 3) The degree of government attention as well as the level of economic development and location accessibility are the positive driving factors for the convergence of HQTE in the whole country and the three regions. The degree of marketization and human capital have not passed the significance test either in the whole country or in the three regions. The above conclusions could deepen the understanding of the regional imbalance and spatial convergence characteristics of HQTE, clarify the primary development objects, and accomplish the goal of China's HQTE. [ABSTRACT FROM AUTHOR]

Background: Endoscopic submucosal dissection (ESD) was widely used for the removal of esophageal tumors, and post-endoscopic submucosal dissection electrocoagulation syndrome (PEECS) was one of the postoperative adverse events. The aim of this research was to develop and validate a model to predict electrocoagulation syndrome after endoscopic submucosal dissection of esophageal tumors. Materials and methods: Patients who underwent esophageal ESD in our hospital were retrospectively included. A predictive nomogram was established based on the results of multivariate logistic regression analysis, and bootstrapping resampling was used for internal validation. Besides, the clinical usefulness of the nomogram was evaluated using decision curve analysis (DCA) and clinical impact curve. Results: A total of 552 patients who underwent esophageal ESD were included in the study, and the incidence of PPECS was 12.5% (69/552). Risk factors associated with PEECS (p < 0.1) were analyzed by multivariate logistic regression analysis, and the final model included four variables, namely gender, diabetes, tumor size and operation time. The predictive nomogram was constructed based on the above four variables, and the area under the ROC curve (AUC) was 0.811 (95% CI 0.767–0.855). The calibration curve of the nomogram presented good agreement between the predicted and actual probabilities. DCA showed that the model improved patient outcomes by helping to assess the risk of PEECS in patients compared to an all-or-no treatment strategy. In addition, the clinical impact curve of the model also indicates that the nomogram has a high clinical net benefit. Conclusion: In conclusion, we have developed a predictive nomogram for PEECS after ESD for esophageal tumors with good predictive accuracy and discrimination. This predictive nomogram can be effectively used to identify high-risk patients with PEECS, which will help clinicians in clinical decision-making and early intervention. [ABSTRACT FROM AUTHOR]

Background: Psychological Clearance level (PCL) for patients undergoing metabolic and bariatric surgery (MBS) is a critical step for successful postoperative outcomes. This study aims to assess the relationship between the level of psychologic fitness and postoperative outcomes in patients undergoing MBS. Methods: We retrospectively analyzed the data of patients who underwent MBS (laparoscopic sleeve gastrectomy [LSG] and laparoscopic Roux-en-Y Gastric Bypass [LRYGB]) and completed two years follow-up, between 2012 and 2019, in a single medical center. The patients were divided into four groups based on PCL, suggesting level of readiness for surgery: Group A (PCL-0: guarded), group B (PCL-1: Fair/reasonable), group C (PCL-2: Good/appropriate), and group D (PCL-3: Strong/excellent). Primary outcome was the percent of total body weight loss (%TWL), and the absolute change in BMI units. Secondary outcomes were missed postoperative visits and patient compliance. Differences between the groups were analyzed using a generalized linear model (GLM), chi-squared and exact Fisher tests, as appropriate. Results: Of 1411 total patients, 607 (43.20%) had complete data at two years follow-up. 512 (84.34%) were females. LSG was performed in 361 (59.5%). No difference was found in %TWL between the four groups (22.14% vs. 28.0% vs. 26.0% vs. 24.8%, p = 0.118). We found a small difference in the mean (SD) of absolute change in BMI between the groups, and on post-hoc analysis it was found between groups B (PCL-1) and D (PCL-3). Overall, no difference between the groups in number of follow-up visits, or compliance issues. However, patients who attended more follow-up visits had less compliance issues (p < 0.001). PCL is inversely correlated with number of psychologic diagnoses (r = − 0.41, p < 0.001) and medical comorbidities (r = − 0.20, p < 0.001). Conclusion: We found no difference in the percent of TWL in patients who underwent MBS based on PCL at two -years follow-up. Medical comorbidities and psychiatric diagnoses impact the PCL. [ABSTRACT FROM AUTHOR]

The present in vitro study aimed to evaluate the influence of various surface treatments on the micro-shear bond strength (μSBS) of calcium silicate–based materials (CSMs) to resin composite. Two hundred and forty cylindrical acrylic molds were filled with Biodentine, NeoMTA Plus, NeoPUTTY MTA, TheraCal LC, and Well-Root PT. The specimens were divided into four groups: control with no surface treatment, acid-etching, tribochemical silica coating (TSC), sandblasting with aluminum oxide (AL). Resin composite was applied and photo-polymerized. The μSBS was measured and surface alterations were evaluated using a SEM. Data were examined using two-way ANOVA and Tukey tests at a significance level of 5%. The lowest bond strength values were detected in the controls. Moreover, the lowest μSBS was demonstrated in the untreated NeoMTA Plus group, whereas the aluminum oxide–treated TheraCal LC group exhibited the highest bond strength (p < 0.05). Cohesive failures were observed dominantly for Biodentine and TheraCal LC, adhesive failures in Well-Root PT, and mixed failures for NeoPUTTY MTA. Surface treatments increased the μSBS values of CSMs and affected the micromorphology of the sample surfaces. The study suggests that surface treatments would be advantageous on CSMs. [ABSTRACT FROM AUTHOR]

On-farm research (OFR) has become popular as a result of precision agriculture technology simplifying the process and farm software capabilities to summarize results collected through the technology. Different OFR designs exists with strip-trials being a simple approach to evaluate different treatments. Common in OFR is the use of yield monitors to collect crop performance data since yield represents a primary response variable in these type studies. The objective was to investigate the ability of grain yield monitoring technologies to accurately inform strip trials when frequent yield variability exists within an experimental unit. A combination of six sub-plot treatment resolutions (TR) that differed in length of imposed yield variation (7.6, 15.2, 30.5, 61.0, 121.9, and 243.8 m) were harvested at combine ground speeds of 3.2, 6.4, 7.2, and 8.1 kph, depending on study site (three study sites total). Intentional yield differences in maize (Zea mays L.) were created for each sub-plot by alternating the amount nitrogen (N) applied: 0 or 202 kg N/ha. Yield was measured by four commercially available yield monitoring (YM) technologies and a weigh wagon. Comparisons were made between the accumulated mass of the YM technology and weigh wagon through percent differences along with testing the significance of the plotted relationship between YM and weigh wagon. Results indicated that yield monitoring technology can be used to evaluate strip trial performance regardless of yield frequency and variability (error < 3%) within an experimental unit when operating within the calibrated range of the mass flow sensor. Operating outside of the calibrated range of the mass flow sensor resulted in > 15% error in estimating accumulated weight and overestimation of yield by 23%. Finally, no significant differences existed in estimating accumulated weight values between grain yield monitor technologies (all p-values ≥ 0.54). [ABSTRACT FROM AUTHOR]

Objectives: More than half of women do not achieve appropriate gestational weight gain. Maternal body image may be an important factor associated with gestational weight gain. However, this association has not been thoroughly evaluated. We aimed to elucidate whether body image parameters before and during pregnancy are associated with gestational weight gain in Japanese women. Methods: This prospective cohort study was conducted at a hospital in Osaka, Japan from March 2020 to March 2021. We recruited women with singleton pregnancies in their second and third trimesters. Body image was assessed using the Pregnancy and Weight Gain Attitude Scale and additional questions. Gestational weight gain was classified as insufficient, appropriate, or excessive based on recommended ranges in Japan. One-way analysis of variance, chi-square tests, and multinomial logistic regression analyses were performed to identify factors associated with insufficient or excessive weight gain. Results: Of 266 enrolled women, 47 had insufficient weight gain and 100 had excessive weight gain during pregnancy. Risk factors for excessive gestational weight gain included a history of dietary restriction before pregnancy, negative attitudes toward gestational weight gain, and perception of body shape as fat and body shape dissatisfaction during pregnancy. Perception of body shape as thin during pregnancy was identified as a risk factor for insufficient gestational weight gain. Conclusions: Body image before and during pregnancy may be an important factor in preventing insufficient or excessive gestational weight gain in Japanese women. Healthcare professionals should consider body image when providing health guidance on weight management to pregnant women. Significance: What is Already Known? Body image is a possible factor in gestational weight gain. Compared to women in other countries, Japanese women of reproductive age tend to have a negative body image. What this Study adds? A history of dietary restriction before pregnancy and negative body image during pregnancy were associated with excessive gestational weight gain among Japanese women. Perception of body shape during pregnancy as thin was associated with insufficient gestational weight gain. Thus, even in a Japanese population, characterized by a majority of women with pre-pregnancy underweight or normal body mass index status, associations between negative body image and gestational weight gain were similar to those in other countries. [ABSTRACT FROM AUTHOR]

The aim of this article is to make a contribution to the Bayesian procedure of testing precise hypotheses for parametric models. For this purpose, we define the Bayesian Discrepancy Measure that allows one to evaluate the suitability of a given hypothesis with respect to the available information (prior law and data). To summarise this information, the posterior median is employed, allowing a simple assessment of the discrepancy with a fixed hypothesis. The Bayesian Discrepancy Measure assesses the compatibility of a single hypothesis with the observed data, as opposed to the more common comparative approach where a hypothesis is rejected in favour of a competing hypothesis. The proposed measure of evidence has properties of consistency and invariance. After presenting the definition of the measure for a parameter of interest, both in the absence and in the presence of nuisance parameters, we illustrate some examples showing its conceptual and interpretative simplicity. Finally, we compare a test procedure based on the Bayesian Discrepancy Measure, with the Full Bayesian Significance Test, a well-known Bayesian testing procedure for sharp hypotheses. [ABSTRACT FROM AUTHOR]

This article proposes to use copulas to characterize the collider bias that concerns the non-substantive change in the causal dependence between variables before and after conditioning on their common effect (collider). This copula-based portrayal allows scholars (1) to capture the sophisticated (e.g., asymmetric or heavy-tail) causal dependence structure that is usually not evidenced by a summative causal effect estimate, such as the regression coefficient based on a well-matched sample; (2) to focus on the causal dependence structure that is insensitive to the influences from the marginal distributions; and (3) to directly and formally test the significance of change in the causal dependence structure using the Cramér–von Mises statistic. Both simulation and real data examples are presented, which suggest that copulas can be a handy tool for practical researchers to describe the collider bias. [ABSTRACT FROM AUTHOR]

This study establishes conditional equivalence between Borda rule and rank sum collective choice. We apply the equivalence condition toward a comparison of the Wilcoxon–Mann–Whitney (WMW) rank sum test and sign test in non-parametric statistics, where the sign test is shown to be procedurally-equivalent to pairwise Borda rule aggregation. We further establish a social choice theoretic robustness check on the WMW test by determining whether a significant WMW rank sum winner could be a raw Borda loser (i.e., could have a p-value greater than 0.5 in a corresponding one-sided sign test). We then test whether a significant sign test winner could be a raw WMW winner. The WMW test is robust against significant victory by a raw Borda loser for almost all small sample cases (specifically, for n < 27 ) at any standard significance level (i.e., for α ≤ 0.10) . The sign test is robust against significant victory by a raw rank sum loser only for n < 14 at any standard significance level. The results provide caution against using the α = 0.10 significance level in some small sample cases of the WMW test. The robustness checks developed herein can be used generally or specifically to check whether a given set of non-parametric data passes the robustness check or whether significance for one test guarantees raw victory in the alternative test (for a given sample size n) in general. These robustness checks present a methodology to test for a weak form of qualitative equivalence across non-parametric tests. We develop a web application (http://avisss.com/visualization/RankSumHistograms.html) for such robustness checks. [ABSTRACT FROM AUTHOR]

Background: Doppler ultrasonography is essential to provide insights into hemodynamic alterations and liver function changes in pre-cirrhotic and cirrhotic patients. Utilizing Doppler examinations, this study aims to explore the correlation between hepatic arterial hemodynamics and Model for end-stage liver disease (MELD) scores in chronic liver disease patients. Methods: A study of 50 chronic liver disease patients included sonographic assessments, measuring liver, portal vein size, and flow. Hepatic artery velocity, resistive index (RI), pulsatility index (PI), and acceleration time (AT) were evaluated. Biochemical parameters (serum bilirubin, creatinine, INR) were used to calculate MELD scores, compared with different Doppler sonographic parameters. Results: The study found a mean peak systolic velocity (PSV) of 107.42 ± 48.10, with end-diastolic velocity (EDV) of 26.40 ± 14.68, RI of 0.74 ± 0.06, and PI of 1.47 ± 0.24. The mean MELD score was 19.28 ± 6.09. Correlations between MELD scores and PSV, EDV, RI, PI, and AT did not yield statistically significant correlations. 80% of subjects displayed high RI (> 0.7) values in the hepatic artery, and a significant correlation was found between portal vein thrombosis and hepatic artery PSV and RI (p < 0.05). Conclusions: Hepatic artery RI and PSV show a significant correlation with portal vein thrombosis. Doppler ultrasonography, while not directly tied to MELD scores, is valuable for non-invasive liver disease monitoring when invasive methods are impractical. Further research is needed to unravel the relationships between hemodynamic changes, MELD scores, and clinical outcomes in a broader patient population. [ABSTRACT FROM AUTHOR]

This study analyzed the impact of educational, perception, and attitudinal factors on the plastic waste behavior of high school students in Vietnam. A cross-sectional research design and questionnaire survey method were used to collect data from 573 high school students. All the statistical analyses and hypothesis tests were performed using SPSS 26 and AmoS 20 software. Research results show that perception does not directly affect students' behavior toward the plastic waste problem (B = 0.051, p = 0.201 > 0.05, CI = [− 0.027; 0.130]) but has an indirect impact through attitude mediation, with an impact coefficient of B = 0.107 (p = 0.016 < 0.05, CI = [0.042; 0.177]). Educational factors positively impact students' behavior toward plastic waste through both direct effects, with an impact coefficient of B = 0.546 (p = 0.00 < 0.05, CI = [0.473; 0.620], and indirect effects, mediated by attitude, with an impact coefficient of B = 0.017 (p = 0.007 < 0.05, CI = [0.003; 0.037]). These findings are new compared to previous studies, contributing to enriching theories related to behavior toward the plastic waste problem and bringing practical significance to Vietnam. The findings of this study provide the basis for proposing measures to improve plastic waste behaviors for Vietnamese high school students. [ABSTRACT FROM AUTHOR]

Previous studies on Bayesian situations, in which probabilistic information is used to update the probability of a hypothesis, have often focused on the calculation of a posterior probability. We argue that for an in-depth understanding of Bayesian situations, it is (apart from mere calculation) also necessary to be able to evaluate the effect of changes of parameters in the Bayesian situation and the consequences, e.g., for the posterior probability. Thus, by understanding Bayes' formula as a function, the concept of covariation is introduced as an extension of conventional Bayesian reasoning, and covariational reasoning in Bayesian situations is studied. Prospective teachers (N=173) for primary (N=112) and secondary (N=61) school from two German universities participated in the study and reasoned about covariation in Bayesian situations. In a mixed-methods approach, firstly, the elaborateness of prospective teachers' covariational reasoning is assessed by analysing the arguments qualitatively, using an adaption of the Structure of Observed Learning Outcome (SOLO) taxonomy. Secondly, the influence of possibly supportive variables on covariational reasoning is analysed quantitatively by checking whether (i) the changed parameter in the Bayesian situation (false-positive rate, true-positive rate or base rate), (ii) the visualisation depicting the Bayesian situation (double-tree vs. unit square) or (iii) the calculation (correct or incorrect) influences the SOLO level. The results show that among these three variables, only the changed parameter seems to influence the covariational reasoning. Implications are discussed. [ABSTRACT FROM AUTHOR]

Manual calculation of the compressive strength of concrete (CSC) is an expensive and time-consuming process. Soft computing methods outperform the statistical methods used to resolve these problems. Nonetheless, complicated prediction models are still incomplete and require more exploration. Artificial neural networks (ANNs) provide a better and faster technique featuring solitary hidden layers and have improved the generalization capacity. The present paper presents three ANN-based (shuffled complex evolution, evaporation rate based water cycle algorithm (ERWCA), and Cuckoo optimization algorithm) prediction models to anticipate the compressive strength of concrete efficiently. An available database from the UCI repository is employed to develop and access the model performance. A comparison is made between the prediction accuracies of the above three techniques. Using all models, a comparative investigation has been conducted to predict the compressive strength of concrete at the curing ages of 91, 56, and 28 days. The experimental findings obtained from the ERWCA-MLP method indicate its capability of robust CSC prediction. On average, this method achieves the minimum RMSE of 0.55314 and 0.43329 and R2 of 0.99803 and 0.99824. The statistical significance test and the comparative analysis of simulation results indicate the superiority of ERWCA-MLP in predicting the compressive strength of concrete. [ABSTRACT FROM AUTHOR]

Payment cards offer a simple and convenient method for making purchases. Owing to the increase in the usage of payment cards, especially in online purchases, fraud cases are on the rise. The rise creates financial risk and uncertainty, as in the commercial sector, it incurs billions of losses each year. However, real transaction records that can facilitate the development of effective predictive models for fraud detection are difficult to obtain, mainly because of issues related to confidentially of customer information. In this paper, we apply a total of 13 statistical and machine learning models for payment card fraud detection using both publicly available and real transaction records. The results from both original features and aggregated features are analyzed and compared. A statistical hypothesis test is conducted to evaluate whether the aggregated features identified by a genetic algorithm can offer a better discriminative power, as compared with the original features, in fraud detection. The outcomes positively ascertain the effectiveness of using aggregated features for undertaking real-world payment card fraud detection problems. [ABSTRACT FROM AUTHOR]

Air pollution is a significant environmental issue affecting public health and ecosystems worldwide, resulting from various sources such as industrial activities, vehicle emissions, and fossil fuel burning. Air pollution contributes to climate change and can cause several health problems, such as respiratory illnesses, cardiovascular disease, and cancer. A potential solution to this problem has been proposed by using different artificial intelligence (AI) and time-series models. These models are implemented in the cloud environment to forecast the Air Quality Index (AQI) utilizing Internet of things (IoT) devices. The recent influx of IoT-enabled time-series air pollution data poses challenges for traditional models. Various approaches have been explored to forecast AQI in the cloud environment using IoT devices. The primary objective of this study is to assess the efficacy of an IoT-Cloud-based model for forecasting the AQI under different meteorological conditions. To achieve this, we proposed a novel BO-HyTS approach that combines seasonal autoregressive integrated moving average (SARIMA) and long short-term memory (LSTM) and fine-tuned it by using Bayesian optimization to predict air pollution levels. The proposed BO-HyTS model can capture both linear and nonlinear characteristics of the time-series data, thus augmenting the accuracy of the forecasting process. Additionally, several AQI forecasting models, including classical time-series, machine learning, and deep learning, are employed to forecast air quality from time-series data. Five statistical evaluation metrics are incorporated to evaluate the effectiveness of models. While comparing the various algorithms among themselves becomes difficult, a non-parametric statistical significance test (Friedman test) is applied to assess the performance of the different machine learning, time-series, and deep learning models. The findings reveal that the proposed BO-HyTS model produced significantly better results than their competitor's, providing the most accurate and efficient forecasting model, with an MSE of 632.200, RMSE of 25.14, Med AE of 19.11, Max Error of 51.52, and MAE of 20.49. The results of this study provide insights into the future patterns of AQI in various Indian states and set a standard for these states as governments develop their healthcare policies accordingly. The proposed BO-HyTS model has the potential to inform policy decisions and enable governments and organizations to protect better and manage the environment beforehand. [ABSTRACT FROM AUTHOR]

We introduce novel null models for assessing the results obtained from observed binary transactional and sequence datasets, using statistical hypothesis testing. Our null models maintain more properties of the observed dataset than existing ones. Specifically, they preserve the Bipartite Joint Degree Matrix of the bipartite (multi-)graph corresponding to the dataset, which ensures that the number of caterpillars, i.e., paths of length three, is preserved, in addition to other properties considered by other models. We describe Alice, a suite of Markov chain Monte Carlo algorithms for sampling datasets from our null models, based on a carefully defined set of states and efficient operations to move between them. The results of our experimental evaluation show that Alice mixes fast and scales well, and that our null model finds different significant results than ones previously considered in the literature. [ABSTRACT FROM AUTHOR]

Load transmission from one element to another is achieved using steel connections, making them an integral part of any structural design. This article examines the differences between the American Codes (AISC) and Eurocode 3 for the design and analysis of steel connections. Moment connections' stiffness, strength, and ductility as expressed in both codes are the core focus of this research. Each tactic's advantages and disadvantages have been detailed, and the effect of seismic load on steel connection design has been investigated. The feasibility of using techniques like haunches and stiffeners to enhance connection design is also explored. The study focuses on moment connections and how they fare under different loads and conditions like stiffness, strength, and ductility. Additionally, the effect of seismic loading on the development of steel connections is analyzed. Finally, the significance of testing and documentation to guarantee the safety and dependability of steel connections has been evaluated. This research can help engineers select a suitable code and connection typology for their projects for improved performance of the overall structural behaviour. [ABSTRACT FROM AUTHOR]

Software in autonomous systems like autonomous cars, robots or drones is often implemented on resource-constrained embedded systems with heterogeneous architectures. At the heart of such software are multiple feedback control loops, whose dynamics not only depend on the control strategy being used, but also on the timing behavior the control software experiences. But performing timing analysis for safety critical control software tasks, particularly on heterogeneous computing platforms, is challenging. Consequently, a number of recent papers have addressed the problem of stability analysis of feedback control loops in the presence of timing uncertainties (cf., deadline misses). In this paper, we address a different class of safety properties, viz., whether the system trajectory with timing uncertainties deviates too much from the nominal trajectory. Verifying such quantitative safety properties involves performing a reachability analysis that is computationally intractable, or is too conservative. To alleviate these problems we propose to provide statistical guarantees over the behavior of control systems with timing uncertainties. More specifically, we present a Bayesian hypothesis testing method that estimates deviations from a nominal or ideal behavior. We show that our analysis can provide, with high confidence, tighter estimates of the deviation from nominal behavior than using known reachability analysis methods. We also illustrate the scalability of our techniques by obtaining bounds in cases where reachability analysis fails, thereby establishing the practicality of our proposed method. [ABSTRACT FROM AUTHOR]