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Projects related to Geotechnical Engineering require thorough ground study to know the soil behaviour thus making it necessary to determine the strength and stability parameters of soil. The soils of Assam are primarily of four types viz., Alluvial (old and new), Piedmont, Hill and Lateritic soils with the alluvium abundantly available in the state. The most important soil parameters are the shear strength parameters, namely, cohesion (c) and angle of internal friction (Φ) which can be obtained using triaxial tests with different drainage conditions. But one triaxial test may take weeks to complete and are very expensive. Moreover, for large projects it is practically preposterous to conduct large number of triaxial tests. Hence, an alternate way is to develop a relation between different parameters which enable us to determine others. The main objective of this study is establishing prediction models that allow the shear parameters to be predicted from soil index properties. For this, three prediction models are developed by combining various soil parameters viz., Liquid Limit (LL), Plastic Limit (PL), Specific Gravity (G) and Optimum Moisture Content (OMC) using Multivariate Regression Analysis (MRA) and Artificial Neural Network (ANN). The results show better performance for ANN than MRA. [ABSTRACT FROM AUTHOR]

Background: This research aims to compare the differences in kinematic parameters associated with cross and uppercut punches between Sanda athletes (SA) and Boxing athletes (BA) to analyze their impacts on peak punching speed. Methods: The punches of BA (n = 20) and SA (n = 20) were compared utilizing a three-dimensional (3D) framework and high-speed cameras in terms of 13 key parameters. An independent samples t-test (α = 0.05) was employed to analyze the differences in punching between BA and SA. Meanwhile, a stepwise multiple linear regression equation was developed to analyze the influence of selected parameters on peak punching speed. Results: The results reveal that, among the 13 kinematic parameters, the six cross-related parameters and four uppercut-related parameters are significantly different (both p ≤ 0.05). The results of multivariate regression analysis unveils that the peak punching speed for the cross are influenced by the anteroposterior position of the center of gravity (in BA) and the maximum angular velocity of the shoulder (in SA). In contrast, for both BA and SA, the maximum angular velocity of the shoulder plays a critical impact on uppercut. Conclusions: These findings indicate that trunk and upper limbs significantly influence the peak punching speed, which provides suggestions for daily training regimen of SA and BA as well as their coaches. [ABSTRACT FROM AUTHOR]

This study presents a comprehensive optimization of algal oil extraction and transesterification for sustainable biodiesel production. Freshwater Spirogyra algae underwent Soxhlet extraction using n-hexane. response surface methodology (RSM), principal component analysis (PCA), and multivariate regression analysis (MRA) were employed to investigate the effects of biomass–solvent ratio (BSR), algae particle size (APS), and extraction-contact time (E-CT) on algal oil yield (AOY). The extracted oil was then converted to biodiesel via transesterification, and the impacts of the methanol–oil ratio (MOR) and transesterification-contact time (T-CT) on biodiesel conversion efficiency (BCE) were analyzed. Results demonstrate that optimal BSR, APS, and E-CT for maximal AOY are 1:7, 400 µm, and 3–4 h, respectively. For transesterification, a MOR of 12:1 and a T-CT of 4 h yielded the highest BCE. Predictive models exhibited exceptional accuracy, with R2 values of 0.916 and 0.950 for AOY and BCE, respectively. The produced biodiesel complied with ASTM D6751 and EN 14214, showcasing its potential for renewable energy applications. [ABSTRACT FROM AUTHOR]

Copyright of Journal of International Business Studies is the property of Springer Nature 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.)

Using multivariate regression, we identified situational, personal and contextual variables correlated with business students' self-reported rates of academic misconduct. The most influential predictors of increasing academic misconduct were: higher estimates of peers' academic misconduct, increasingly negative perceptions of the program's academic integrity culture, and rating questionable academic behaviours less seriously. Individual priorities, personal characteristics and social support were less influential. We then analyzed our quantitative results in light of our deep understanding of the broader context to derive richer insights from the interplay of our independent variables. Importantly, our results indicate that program-led proactive messaging designed to foster a culture of academic integrity can effectively buffer tendencies towards academic dishonesty. Absent ongoing messaging, however, increasing academic pressures may erode those initial benefits. Moreover, repercussions of major academic integrity breaches can be long lasting, suggesting an even greater need for fostering a culture of academic integrity a priori. Finally, we recommend a public health practice of identifying positive deviants – individuals who thrive in challenging environments – and then in an effort to change a peer support system that fosters academic misconduct into one that discourages it, engaging with those individuals to understand why and how they resist the status quo. [ABSTRACT FROM AUTHOR]

Abstract Using multivariate regression, we identified situational, personal and contextual variables correlated with business students’ self-reported rates of academic misconduct. The most influential predictors of increasing academic misconduct were: higher estimates of peers’ academic misconduct, increasingly negative perceptions of the program’s academic integrity culture, and rating questionable academic behaviours less seriously. Individual priorities, personal characteristics and social support were less influential. We then analyzed our quantitative results in light of our deep understanding of the broader context to derive richer insights from the interplay of our independent variables. Importantly, our results indicate that program-led proactive messaging designed to foster a culture of academic integrity can effectively buffer tendencies towards academic dishonesty. Absent ongoing messaging, however, increasing academic pressures may erode those initial benefits. Moreover, repercussions of major academic integrity breaches can be long lasting, suggesting an even greater need for fostering a culture of academic integrity a priori. Finally, we recommend a public health practice of identifying positive deviants – individuals who thrive in challenging environments – and then in an effort to change a peer support system that fosters academic misconduct into one that discourages it, engaging with those individuals to understand why and how they resist the status quo.

In our rapidly changing world, understanding how species respond to shifting conditions is of paramount importance. Pharmaceutical pollutants are widespread in aquatic ecosystems globally, yet their impacts on animal behaviour, life‐history and reproductive allocation remain poorly understood, especially in the context of intraspecific variation in ecologically important traits that facilitate species' adaptive capacities. We test whether a widespread pharmaceutical pollutant, fluoxetine (Prozac), disrupts the trade‐off between individual‐level (co)variation in behavioural, life‐history and reproductive traits of freshwater fish. We exposed the progeny of wild‐caught guppies (Poecilia reticulata) to three field‐relevant levels of fluoxetine (mean measured concentrations: 0, 31.5 and 316 ng/L) for 5 years, across multiple generations. We used 12 independent laboratory populations and repeatedly quantified activity and risk‐taking behaviour of male guppies, capturing both mean behaviours and variation within and between individuals across exposure treatments. We also measured key life‐history traits (body condition, coloration and gonopodium size) and assessed post‐copulatory sperm traits (sperm vitality, number and velocity) that are known to be under strong sexual selection in polyandrous species. Intraspecific (co)variation of these traits was analysed using a comprehensive, multivariate statistical approach. Fluoxetine had a dose‐specific (mean) effect on the life‐history and sperm trait of guppies: low pollutant exposure altered male body condition and increased gonopodium size, but reduced sperm velocity. At the individual level, fluoxetine reduced the behavioural plasticity of guppies by eroding their within‐individual variation in both activity and risk‐taking behaviour. Fluoxetine also altered between‐individual correlations in pace‐of‐life syndrome traits: it triggered the emergence of correlations between behavioural and life‐history traits (e.g. activity and body condition) and between life‐history and sperm traits (e.g. gonopodium size and sperm vitality), but collapsed other between‐individual correlations (e.g. activity and gonopodium size). Our results reveal that chronic exposure to global pollutants can affect phenotypic traits at both population and individual levels, and even alter individual‐level correlations among such traits in a dose‐specific manner. We discuss the need to integrate individual‐level analyses and test behaviour in association with life‐history and reproductive traits to fully understand how animals respond to human‐induced environmental change. [ABSTRACT FROM AUTHOR]

Copyright of Coal Geology & Exploration is the property of Xian Research Institute of China Coal Research Institute 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.)

İnşaat sektörüne hammadde sağlayan taş ve kalker ocakları genellikle maliyetleri en aza indirmek amacıyla şehirleşmenin yakın çevrelerinde yer almaktadır. Bu ocaklarda üretim yöntemi olarak yine ekonomik olması nedeniyle delme ve patlatma yöntemi tercih edilmektedir. Delme ve patlatma yöntemindeki teknolojik gelişmelere rağmen, bu yöntem ile kazı bazı çevresel olumsuz etkilere neden olabilmektedir. Bu etkilerden olan titreşimler, jeolojik yapıya da bağlı olarak uzak mesafelerde de etkili olabilmesi nedeniyle oldukça önemlidir. Bu çalışmada, Eskişehir ili sınırları içerisinde yer alan Yörükkaracaören köyü yakınında bulunan bir kalker ocağında yapılan patlatmalar bir adet titreşim ölçer cihazı ile izlenmiş ve toplam 31 adet titreşim olayı kaydedilmiştir. Kaydedilen bu olayların verileri daha sonra ölçekli mesafe ve çok değişkenli regresyon analizi tekniğine dayalı farklı titreşim tahmin modelleri uygulanarak istatistiksel analize tabi tutulmuştur. Yapılan bu istatiksel analizler sonucunda, ölçekli mesafeye dayalı Roy eşitliğinin bu saha için en iyi tahmin modeli olduğu belirlenmiş ve titreşim tahminleri bu eşitlik ile yapılmıştır. Çalışmada ayrıca, çok değişkenli regresyon analizi yönteminin patlatma kaynaklı titreşimlerin tahmininde kullanılabilirliği ortaya konmuştur.

In this article, the performance of a 3.36 kWp grid-connected photovoltaic system (GCPVS) under warm and subhumid weather conditions and the development of a predictive mathematical model is presented. Climate data of the 2021 year were used to evaluate energy generation, different types of performance, and efficiency. The average annual yield, corrected yield, array, and final yields were 6.45 h/day, 6.18 h/day, 5.16 h/day, and 4.97 h/day, respectively. The overall annual mean capacity factor and efficiency ratios were 20.73% and 77.22%, correspondingly. Experimental data were analyzed and correlated by multivariate linear regression (MLR) prediction and simulation to validate models. The MLR analysis showed that the efficiency is highly dependent on the temperature of the PV modules and that climatic parameters significantly affect the efficiency and output electric power. The prediction models for PV module efficiency, system efficiency, and direct current energy exhibit an uncertainty of ±1.04%, ±0.57%, and ±35.38 kWh, one-to-one. The monthly generation was compared with results obtained by Energy3D simulation-free software, showing an absolute error of ±2.33 kWh. This information can be used as a methodological tool for predicting efficiency and power generation in direct current. [ABSTRACT FROM AUTHOR]

Passenger thermal comfort in high-speed train (HST) carriages presents unique challenges due to factors such as extensive operational areas, longer travel durations, larger spaces, and higher passenger capacities. This study aims to propose a new prediction model to better understand and address thermal comfort in HST carriages. The proposed prediction model incorporates skin wettedness, vertical skin temperature difference (ΔTd), and skin temperature as parameters to predict the thermal sensation vote (TSV) of HST passengers. The experiments were conducted with 65 subjects, evenly distributed throughout the HST compartment. Thermal environmental conditions and physiological signals were measured to capture the subjects' thermal responses. The study also investigated regional and overall thermal sensations experienced by the subjects. Results revealed significant regional differences in skin temperature between upper and lower body parts. By analyzing data from 45 subjects, We analyzed the effect of 25 variables on TSV by partial least squares (PLS), from which we singled out 3 key factors. And the optimal multiple regression equation was derived to predict the TSV of HST occupants. Validation with an additional 20 subjects demonstrated a strong linear correlation (0.965) between the actual TSV and the predicted values, confirming the feasibility and accuracy of the developed prediction model. By integrating skin wettedness and ΔTd with skin temperature, the model provides a comprehensive approach to predicting thermal comfort in HST environments. This research contributes to advancing thermal comfort analysis in HST and offers valuable insights for optimizing HST system design and operation to meet passengers' comfort requirements. [ABSTRACT FROM AUTHOR]

Copyright of Arid Zone Research / Ganhanqu Yanjiu is the property of Arid Zone Research Editorial Office 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 is to propose an approach to predicting the risk of progression of chronic tonsillitis in patients based on multivariate regression analysis for timely, convenient, and accurate diagnosis with subsequent selection of effective treatment and preventive measures in ENT departments (otolaryngology departments). A number of 100 patients with various forms of chronic tonsillitis, whose average age was 37 years, and 51 women and 49 men, were examined according to a specially developed questionnaire to predict the risk of ChT progression. The most probable indicators of chronic tonsillitis progression were selected to build a multivariate regression model for predicting the risk of ChT progression, 13 probable factors of the ChT progression were analyzed, and 9 factors were used to build a multivariate regression model. Histogram of the residual deviations is distributed symmetrically, approaching the curve of the normal distribution of the residuals and the absence of systematic deviations from the normal-probability straight line, so we conclude that the statistical hypothesis that their distribution conforms to the normal distribution law is not rejected. The residuals relative to the predicted values are scattered chaotically, which indicates the absence of dependence on the predicted values for the risk of chronic tonsillitis progression. The coefficient of determination was calculated, which is 0.8258, which claims that 82.58% of the factors are considered in the prediction model of the risk of chronic tonsillitis progression. The coefficient of determination indicates how well the obtained observations confirm the mathematical model. The proposed multivariate regression model that considers the risk factors for the ChT progression makes it possible to predict potential meta tonsillar complications and the possibility of timely disease prevention. [ABSTRACT FROM AUTHOR]

The main objective of the present study was to reveal the significance of R&D in order to ensure sustainable economic growth. The present study consists of four main parts. In the first part of the study, the term R&D is defined in detail. The Solow model, which is the theoretical basis of the study, is discussed in the introduction. In the first part of the study, the term 'economic growth' is explained, as well. Different definitions of economic growth are given and then the basic resources of the economy, people, nature, funds, technological change, and innovation are examined. Ensuring economic growth and improving the quality of life is desired by all nations and peoples. Therefore, the policies and measures to be determined for this purpose are socrucial. In this sense, innovation-oriented economic models are examined. In addition, in the second part of the study, the academic literature is examined in terms of the relationship between loans provided by financial institutions to the private sector, R&D investments, and economic growth. In the third and final part of the study, the relationship between R&D, domestic credit provided to private sector, and economic growth are examined using multivariate regression, cointegration, FMOLS, DOLS, CCR, and ARDL analyzes for China, South Korea, and Japan fort he period between 1991 and 2020. In the conclusion part, all the results obtained are interpreted and the relationship between domestic credit provided to private sector, R&D, and economic growth are presented in a concrete way in terms of empirical findings. [ABSTRACT FROM AUTHOR]

In a multi-reservoir system, the stochastic nature of basin data resulting from rainfall introduces risk into water management operations. Effective management that accounts for these risks can obtain maximum benefits from the system. This study presents a description of a multi-reservoir water resources system with hydroelectric power plants, utilizing the energy optimization model developed by OPAN in 2007. The model was applied to reservoirs located successively on the Lower Kızılırmak River in the Kızılırmak Basin, with the objective function being the maximization of firm power by using drought period inflows and total energy by using monthly average inflows. The study considered three scenarios: deterministic, probabilistic, and risky (critical cases), with probabilities of inflows from the basin being determined for the latter. Monthly inflows with determined probabilities were used to obtain data for the risky case. Optimum operating levels were determined based on this data to maximize firm power and total energy. According to the operating levels, the reservoir with the largest useful volume manages the operation. The values obtained from the optimization were then used in multivariate regression analysis using the Statistical Package for Social Scientists (SPSS), a statistical analysis program. The analysis explored the effects of monthly operating levels in the reservoirs, the amount of inflow released from the spillway, the amount of inflow released for energy production, the monthly average inflow to the reservoirs, and firm power values on energy production. [ABSTRACT FROM AUTHOR]

Aims: Psychological status may be an important predictor of outcome after periacetabular osteotomy (PAO). The aim of this study was to investigate the influence of psychological distress on postoperative health-related quality of life, joint function, self-assessed pain, and sports ability in patients undergoing PAO. Methods: In all, 202 consecutive patients who underwent PAO for developmental dysplasia of the hip (DDH) at our institution from 2015 to 2017 were included and followed up at 63 months (SD 10) postoperatively. Of these, 101 with complete data sets entered final analysis. Patients were assessed by questionnaire. Psychological status was measured by Brief Symptom Inventory (BSI-18), health-related quality of life was raised with 36-Item Short Form Survey (SF-36), hip functionality was measured by the short version 0f the International Hip Outcome Tool (iHOT-12), Subjective Hip Value (SHV), and Hip Disability and Outcome Score (HOS). Surgery satisfaction and pain were assessed. Dependent variables (endpoints) were postoperative quality of life (SF-36, HOS quality of life (QoL)), joint function (iHOT-12, SHV, HOS), patient satisfaction, and pain. Psychological distress was assessed by the Global Severity Index (GSI), somatization (BSI Soma), depression (BSI Depr), and anxiety (BSI Anx). Influence of psychological status was assessed by means of univariate and multiple multivariate regression analysis. Results: In multiple multivariate regression, postoperative GSI, BSI Soma, and BSI Depr had a negative effect on postoperative SF-36 (e -2.07, -3.05, and -2.67, respectively; p < 0.001), iHOT-12 (e -1.35 and -4.65, respectively; p < 0.001), SHV (e -1.20 and -2.71, respectively; p < 0.001), HOS QoL (e -2.09 and -4.79, respectively; p < 0.001), HOS Function (e -1.00 and -3.94, respectively; p < 0.001), and HOS Sport (e -1.44 and -5.29, respectively; p < 0.001), and had an effect on postoperative pain (e 0.13 and 0.37, respectively; p < 0.001). Conclusion: Psychological distress, depression, and somatization disorders affect health-related quality of life, perceived joint function, and sports ability. Pain perception is significantly increased by somatization. However, patient satisfaction with surgery is not affected. Cite this article: Bone Jt Open 2023;4(10):758–765.

The water required by the plant is provided through the porous environment of the soil around the root. Therefore, indicators such as soil texture and effective porosity have been defined to measure the amount of water available to the plant. The pore size determines water energy and the plant's ability to absorb moisture, which is evaluated in this article. Multivariate regression analysis between the integral energy of water in different ranges of humidity as the dependent variable and the indices of soil pore size distribution as the independent variable has been investigated. Due to the fact that none of the indices of the pore size distribution curve have a significant relationship with the integral energy value of water in the permanent wilting point, therefore, it was not possible to estimate this index using the indices of the pore size distribution curve. The results showed that the elongation index of soil pore size distribution curve is the only factor determining the amount of integral energy of water in different soil water contents. HIGHLIGHTS The effect of soil porosity size distribution on integral energy content of soil water has been considered.; There is no significant statistical relationship with the values of integral energy of water in different humidity ranges.;

To simulate the consumption of duplicate technological tooling (hereinafter referred to as TT), it is proposed to use the apparatus of multivariate regression analysis, which provides the main patterns formalization of consumption formation value in the form of linear regression dependencies. An important difference of the proposed approach to the development of regression models is an increased degree of detail due to the use of the number of detail operations performed using specific TT sizes as independent variables, which makes it possible to eliminate the calculation error associated with the presence of passing positions in the planning period (batches of parts and assembly units ). As a result, a quantitative assessment of the constructed dependencies based on the calculation of multiple correlation coefficients, the Fisher dispersion ratio, the Theil’s coefficient of irrelevance allowed us to conclude that they are adequate to the conditions of consumption TT at the aviation enterprise. To improve the adequacy of displaying real processes of TT consumption, the developed models are equipped with a parametric adaptation mechanism. The use of the steepest descent method makes it possible to adjust the regression parameters based on incoming data, taking into account the main trends in the development of the simulated process and providing for smoothing its random fluctuations.

To explore the risk factors and nursing measures of early surgical site infection (SSI) after posterior lumbar interbody fusion (PLIF).

Copyright of Food Research & Development is the property of Food Research & Development Editorial Department 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.)

Abstract Background The current German S3 guideline for polytrauma lists five criteria for prehospital intubation: apnea, severe traumatic brain injury (GCS ≤8), severe chest trauma with respiratory failure, hypoxia, and persistent hemodynamic instability. These guideline criteria, used in adults in daily practice, have not been previously studied in a collection of severely injured children. The aim of this study was to assess the extent to which the criteria are implemented in clinical practice using a multivariate risk analysis of severely injured children. Methods Data of 289,698 patients from the TraumaRegister DGU® were analyzed. Children meeting the following criteria were included: Maximum Abbreviated Injury Scale 3+, primary admission, German-speaking countries, years 2008–2017, and declaration of intubation. Since children show age-dependent deviating physiology, four age groups were defined (years old: 0–2; 3–6; 7–11; 12–15). An adult collective served as a control group (age: 20–50). After a descriptive analysis in the first step, factors leading to prehospital intubation in severely injured children were analyzed with a multivariate regression analysis. Results A total of 4489 children met the inclusion criteria. In this cohort, young children up to 2 years old had the significantly highest injury severity (Injury Severity Score: 21; p ≤ 0.001). Falls from both high (> 3 m) and low heights (

Special concentrically braced frames (SCBFs) with in‐plane buckling (IPB) braces are often designed using the provisions applicable for out‐of‐plane buckling (OOPB) brace systems. As a result, the IPB brace systems may fail in the undesirable modes as observed in past experimental studies. In this study, a novel simplified analytical formulation based on the rigid beam spring model (RBSM) has been proposed to prevent the out‐of‐plane buckling of IPB braces. A high‐fidelity finite element model (FEM) is generated and validated with the experimental studies incorporating the influence of the residual stress, imperfection, and strain hardening. The variability, sensitivity, and uncertainties involved in predicting the direction of buckling of braces are examined. A parametric study has been carried out to investigate the influence of thickness and clearance of the gusset and knife plates, geometric imperfections, slenderness ratios, compactness ratios, residual stresses, and frame actions considering the most destabilizing effect in the OOPB mode. The third mode of buckling, termed as the mixed‐mode of buckling, has been observed in this study. A design criterion is proposed to get the desired IPB mode of buckling of braces in SCBFs. Multivariate regression analysis is carried out to incorporate the impact of various parameters as well as uncertainties in the formulation of the design criteria. The validity of the proposed equation is verified by comparing the findings of past experimental studies for various loading scenarios. Finally, a resistance factor of 0.8 in the LRFD approach has been proposed for the IPB brace systems. [ABSTRACT FROM AUTHOR]

Siwei Xing,1,&ast; Xiaohao Ruan,1,&ast; Jingyi Huang,1,&ast; Jiaqi Yan,1 Wenhao Lin,1 Jinlun Huang,1 Jiacheng Liu,1 Da Huang,1 Rong Na,2 Danfeng Xu1 1Department of Urology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China; 2Division of Urology, Department of Surgery, Queen Mary Hospital, The University of Hong Kong, Hong Kong, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Rong Na, Division of Urology, Department of Surgery, Queen Mary Hospital, The University of Hong Kong, 102 Pok Fu Lam Road, Hong Kong, People’s Republic of China, Email narong.hs@gmail.com Da Huang, Department of Urology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, Shanghai, 200025, People’s Republic of China, Email huangdasjtu@gmail.comPurpose: To explore the impact of family history (FH) on renal cell carcinoma (RCC) and its pathological subtype clear cell RCC (ccRCC) in a Chinese population; a significant association has previously been determined not only in familial cancer syndrome but also in sporadic cases in western populations.Methods: Consecutive patients with kidney tumors from October 2017 to May 2021 at a tertiary hospital in Shanghai were enrolled in the study. Demographic and clinical information was collected, including age, gender, FH (positive or negative, types of cancers, degree of relatives, etc.), pathological diagnosis, and Fuhrman grades.Results: A positive FH of any cancer was observed in 26.5% of the RCC patients, while only 16.8% patients with benign kidney tumor were found to have a positive FH. A strong correlation was observed between FH of any cancers in first-degree relatives and RCC (odds ratio [OR]=4.60, 95% confidence interval [CI]: 1.95– 10.85, P=5.50× 10− 5) or ccRCC (OR=4.63, 95% CI: 1.95– 11.02, P=9.63× 10− 5). In subgroup analysis, FH of digestive cancers was significantly associated with RCC (OR=4.42, 95% CI: 1.35– 14.51, P=0.005) or ccRCC (OR=4.14, 95% CI: 1.25– 13.75, P=6.84× 10− 4). Similar results were found in multivariate analyses. However, no significant association was observed between FH and age at onset.Conclusion: FH was an independent risk factor for RCC and ccRCC in this Chinese population. FH of any cancer in first-degree relatives and FH of digestive cancers were found to be the most significant risk factors for kidney cancers.Keywords: Chinese population, family history, renal cell carcinoma, risk factor, multivariate regression analysis

Water-supply network systems are an indispensable social infrastructure in modern society. Therefore, water supply utilities require high system robustness towards both accidents and natural disasters. In this study, we define a work performance indicator (WPI) to quantitatively measure the robustness of water supply utilities (WSU) in Japan. The WPI was defined from three perspectives: reliability, safety, and sustainability. Based on actual data expressing the work performance of Japanese WSU from 1980 to 2018, we illustrate the numerical results of WPIs to determine their regional characteristics. We applied statistical data analysis techniques such as multivariate regression analysis, cluster analysis, and principal component analysis to calculate the WPIs and investigate the historical and regional characteristics and trends of WSU in Japan during the investigated period. These approaches can be applied to the design and improvement of natural disaster mitigation policies, such as those focused on earthquakes in Japan. [ABSTRACT FROM AUTHOR]

Renewable energy policies and adoption of new renewable energy technologies in different states of the USA are not uniform. The factors affecting the trends in adopting electrical energy generation using sustainable resources: wind, solar, hydro, geothermal and biomass as well as registered all electric vehicles in 50 states and district of Columbia in the USA was analyzed using multivariate linear regression analysis. Eight contributing factors: percentages of high school graduates; college graduates; total population; land area; percentage of water covered area; average annual income and registered democrats in the state were selected as predictor variables. Among eight factors considered, percentage of registered democrats was found as the most influencing factor (p = 0.00543) determining the renewable electrical energy adoption. The transition to all electric cars strongly co-related to higher average annual income of the population (p = 0.00141). In conclusion, an aggressive education campaign by environmentalist and pro-sustainability groups may help in de-coupling the energy and environment policies in the USA from political ideologies in order to achieve a more sustainable future. Factors Affecting Sustainable Energy Technology Adoption Policies of 50 States and District of Columbia in the USA [ABSTRACT FROM AUTHOR]

Background: The current German S3 guideline for polytrauma lists five criteria for prehospital intubation: apnea, severe traumatic brain injury (GCS ≤8), severe chest trauma with respiratory failure, hypoxia, and persistent hemodynamic instability. These guideline criteria, used in adults in daily practice, have not been previously studied in a collection of severely injured children. The aim of this study was to assess the extent to which the criteria are implemented in clinical practice using a multivariate risk analysis of severely injured children. Methods: Data of 289,698 patients from the TraumaRegister DGU® were analyzed. Children meeting the following criteria were included: Maximum Abbreviated Injury Scale 3+, primary admission, German-speaking countries, years 2008–2017, and declaration of intubation. Since children show age-dependent deviating physiology, four age groups were defined (years old: 0–2; 3–6; 7–11; 12–15). An adult collective served as a control group (age: 20–50). After a descriptive analysis in the first step, factors leading to prehospital intubation in severely injured children were analyzed with a multivariate regression analysis. Results: A total of 4489 children met the inclusion criteria. In this cohort, young children up to 2 years old had the significantly highest injury severity (Injury Severity Score: 21; p ≤ 0.001). Falls from both high (> 3 m) and low heights (< 3 m) were more common in children than in adults. The same finding applied to the occurrence of severe traumatic brain injury. When at least one intubation criterion was formally present, the group up to 6 years old was least likely to actually be intubated (61.4%; p ≤ 0.001). Multivariate regression analysis showed that Glasgow Coma Scale score ≤ 8 in particular had the greatest influence on intubation (odds ratio: 26.9; p ≤ 0.001). Conclusions: The data presented here show for the first time that the existing criteria in the guideline for prehospital intubation are applied in clinical practice (approximately 70% of cases), compared to adults, in the vast majority of injured children. Although severely injured children still represent a minority of all injured patients, future guidelines should focus more on them and address them in a specialized manner. [ABSTRACT FROM AUTHOR]

Study Design: Retrospective multicenter.Objective: The aim was to investigate the factors involved in, and their relative contributions to, the overall accuracy of robot-assisted pedicle screw placement.Summary Of Background Data: Robot-assisted surgery has reportedly resulted in greater accuracy for placement of pedicle screws than conventional methods. There are many potential factors affecting the accuracy of pedicle screws placed with a robot. No study has investigated these factors in a robust way.Materials and Methods: Radiographic and clinical data of three centers were pooled. Preoperative and postoperative computerized tomographies were obtained by all three centers to assess the accuracy of the placed screws. The primary outcome measured was accuracy of pedicle screws placed with the robot. The authors performed a multivariate regression analysis to determine the significant patient-related and screw-related variables and their relative contribution to the overall accuracy. In addition, an ordinal regression analysis was conducted to investigate the effects of different variables on accuracy of robot-placed screws graded by Gertzbein-Robbins grading system (GRS).Results: The total contribution of all studied variables to overall accuracy variation as measured by offsets between the placed and planned screws was only 18%. Obesity, long constructs, female gender, surgeon, and vertebral levels were among the factors that had small contributions to the different screw offsets. For GRS grades, significant variables were gender (Log odds: 0.62, 95% CI: 0.38-0.85), age (Log odds: 0.02, 95% CI: 0.01-0.03), length of constructs (Log odds: 0.07, 95% CI: 0.02-0.11), screw diameter (Log odds: 0.55, 95% CI: 0.39-0.71), and length of the screws (Log odds: 0.03, 95% CI: 0.01-0.05). However, these variables too, regardless of their significant association with the accuracy of placed screws, had little contribution to overall variability of accuracy itself (only about 7%).Conclusion: The accuracy of screws placed with robotic assistance, as graded by GRS or measured offsets between planned and placed screw trajectories, is minimally affected by different patient-related or screw-related variables due to the robustness of the robotic navigation system used in this study.Level Of Evidence: Level III. [ABSTRACT FROM AUTHOR]

Objective To retrospectively analyze the clinical and pathological data of 48 patients with adenoid cystic carcinoma of the head and neck and screen out related factors that affect the patient's prognosis. Methods The overall survival rate of patients is used as the main indicator for observing prognosis. We selected 11 clinical and pathological factors as observation indicators that may have an impact on the survival and prognosis of patients. The relation between observation factors and the overall survival rate of patients was analyzed by Cox multivariate regression. Results The median follow-up time was 33.5(1-98) months. The 1-, 2- and 5-years overall survival rates were 95%, 91% and 87%. Local recurrence occurred in 14(29.2%) patients. Distant metastasis occurred in 22(45.8%) patients. Cox regression analysis showed that recurrence, distant metastasis and primary site were correlated with the overall survival rate of patients with head and neck adenoid cystic carcinoma (P < 0.05). Conclusion Adenoid cystic carcinoma is a relatively rare tumor of the head and neck with a low degree of malignancy. However, recurrence, distant metastasis and primary site have relatively great impact on the prognosis of patients.

• Hemodynamic alterations due to atrial fibrillation (AF) increase the risk of dementia. • Lenticulostriate arteries (LSAs) are susceptible to vascular dementia development. • We combined MRI-based computational fluid dynamics and multivariate regression analyses. • The role of LSAs morphology on the cerebral hemodynamics during AF is investigated. • Few geometrical features identify LSA morphologies prone to AF-induced vascular damage. Atrial fibrillation (AF) is the most common cardiac arrhythmia, inducing accelerated and irregular beating. Beside well-known disabling symptoms - such as palpitations, reduced exercise tolerance, and chest discomfort - there is growing evidence that an alteration of deep cerebral hemodynamics due to AF increases the risk of vascular dementia and cognitive impairment, even in the absence of clinical strokes. The alteration of deep cerebral circulation in AF represents one of the least investigated among the possible mechanisms. Lenticulostriate arteries (LSAs) are small perforating arteries mainly departing from the middle cerebral artery (MCA) and susceptible to small vessel disease, which is one of the mechanisms of subcortical vascular dementia development. The purpose of this study is to investigate the impact of different LSAs morphologies on the cerebral hemodynamics during AF. By combining a computational fluid dynamics (CFD) analysis of LSAs with 7T high-resolution magnetic resonance imaging (MRI), we performed different CFD-based multivariate regression analyses to detect which geometrical and morphological vessel features mostly affect AF hemodynamics in terms of wall shear stress. We exploited 17 cerebral 7T-MRI derived LSA vascular geometries extracted from 10 subjects and internal carotid artery data from validated 0D cardiovascular-cerebral modeling as inflow conditions. Our results revealed that few geometrical variables - namely the size of the MCA and the bifurcation angles between MCA and LSA - are able to satisfactorily predict the AF impact. In particular, the present study indicates that LSA morphologies exhibiting markedly obtuse LSA-MCA inlet angles and small MCA size downstream of the LSA-MCA bifurcation may be more prone to vascular damage induced by AF. The present MRI-based computational study has been able for the first time to: (i) investigate the net impact of LSAs vascular morphologies on cerebral hemodynamics during AF events; (ii) detect which combination of morphological features worsens the hemodynamic response in the presence of AF. Awaiting necessary clinical confirmation, our analysis suggests that the local hemodynamics of LSAs is affected by their geometrical features and some LSA morphologies undergo greater hemodynamic alterations in the presence of AF. [ABSTRACT FROM AUTHOR]

The quality assessment and grading of agricultural products is one of the post-harvest activities that has received considerable attention due to the growing demand for healthy and better-quality products. Recently, various non-destructive methods have been used to evaluate the quality of agricultural products, which are very desirable and faster and more economical than destructive methods. Optical methods are one of the most important non-destructive methods that use the high speed of light detection and computer data processing and are able to evaluate the quality and classification of products with high accuracy. Among the optical methods, visible–near-infrared (Vis/NIR) spectroscopy is considered one of the most accurate methods. In this research, Vis/NIR spectroscopy technology was used in the spectral range of 350–1150 nm for non-destructive detection of some quality parameters including pH, TA, SSC, and TP of two varieties of Red Delicious and Golden Delicious apples. Various pre-processing models were developed to predict the parameters, which brought the desired results with high accuracy so that pH prediction results were for yellow apples (RMSEC = 0.009, rc = 0.991, SDR = 2.51) and for red apples (RMSEC = 0.005, rc = 0.998, SDR = 2.56). The results for TA were also (RMSEC = 0.003, rc = 0.996, SDR = 2.51) for red apples and (RMSEC = 0.001, rc = 0.998, SDR = 2.81) for yellow apples. The results regarding SSC were for red apples (RMSEC = 0.209, rc = 0.990 and SDR = 2.82) and for yellow apples (RMSEC = 0.054, SDR = 2.67 and rc = 0.999). In addition, regarding TP, the results were for red apples (RMSEC = 0.2, rc = 0.989, SDR = 2.05) and for yellow apples (RMSEC = 1.457, rc = 0.998, SDR = 1.61). The obtained results indicate the detection of the mentioned parameters with high accuracy by visible/infrared spectroscopic technology. [ABSTRACT FROM AUTHOR]

The main objective of this study is to present a methodology to model the microstructure and mechanical properties of ZE41-xCa-ySr alloys for integrated optimization calculation of the heat treatment process of gearbox casting. Firstly, the models of microstructure and mechanical properties of ZE41-xCa-ySr alloys (0 ≤ x ≤ 2, 0 ≤ y ≤ 0.2) are developed using an artificial neural network (ANN) and multivariate regression. The dataset for ANN and regression models is generated by investigating the microstructures and mechanical properties of the ZE41-xCa-ySr alloys. The inputs for ANN and regression models are Ca and Sr contents, aging temperature and aging time. The outputs are grain size, ultimate tensile strength, elongation and microhardness. The optimal ANN model is obtained by testing the performance of different network architectures. In addition, multivariate regression models have been built based on the Least Squares method. Secondly, based on SiPESC software, an Integrated Computing Platform is constructed by combining the scripting language with the command line operation of simulation software, realizing the "process—microstructure—property" optimization calculation. Finally, based on the developed regression model, an Integrated Computing Platform batch called MATLAB achieves the heat treatment process optimization based on mechanical property prediction. The optimum aging temperature of the ZE41-0.17Ca-0.2Sr alloy is 322 °C, and the corresponding aging time is 11 h. Furthermore, the optimized results are validated by the ANN model, suggesting that ANN predicted results are in good agreement with optimized results. As a consequence, this work provides a new strategy for the research and development of Mg alloys, contributing to acceleration in the development of magnesium alloys. [ABSTRACT FROM AUTHOR]

Background: This research aims to compare the differences in kinematic parameters associated with cross and uppercut punches between Sanda athletes (SA) and Boxing athletes (BA) to analyze their impacts on peak punching speed., Methods: The punches of BA ( n  = 20) and SA ( n  = 20) were compared utilizing a three-dimensional (3D) framework and high-speed cameras in terms of 13 key parameters. An independent samples t -test ( α  = 0.05) was employed to analyze the differences in punching between BA and SA. Meanwhile, a stepwise multiple linear regression equation was developed to analyze the influence of selected parameters on peak punching speed., Results: The results reveal that, among the 13 kinematic parameters, the six cross-related parameters and four uppercut-related parameters are significantly different (both p  ≤ 0.05). The results of multivariate regression analysis unveils that the peak punching speed for the cross are influenced by the anteroposterior position of the center of gravity (in BA) and the maximum angular velocity of the shoulder (in SA). In contrast, for both BA and SA, the maximum angular velocity of the shoulder plays a critical impact on uppercut., Conclusions: These findings indicate that trunk and upper limbs significantly influence the peak punching speed, which provides suggestions for daily training regimen of SA and BA as well as their coaches., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2024 Xu, Mao and Xi.)

The natural gas usage as a vehicle fuel in the mining industry is one of the priority tasks of the state. The article pays special attention to the component composition of natural gas from the point of view of its thermal efficiency during combustion in the combustion chamber of a power plant on a heavy-duty vehicle in difficult quarry conditions. For this, domestic and foreign methods for determining the main indicator characterizing the knock resistance of fuel in the combustion process – the methane number – are considered. Improvement of technical and economic indicators will be carried out by changing the composition of the gas mixture based on methane to fit the design features of the gas power plant, the methane number will be the determining indicator. A theoretical analysis of the influence of the methane number on such engine parameters as the compression ratio and the maximum speed of the flame front propagation in the second phase of combustion in the engine cylinder, expressed through the angle of rotation of the crankshaft, is presented. Based on the results of theoretical and experimental studies, the dependences of the influence of the methane number on the efficiency of the working process of the engine and its external speed characteristic were obtained.

This study presents a fast and simple estimation method for dosimetry assessment of a clothed human body exposed to electromagnetic fields in millimeter-wave bands. A multivariate regression algorithm was given instead of conventional numerical methods for the first time, which utilized the exact value of skin surface temperature rise that was computed by the Monte-Carlo method by changing the oblique incidence wave angle, the cross-polarization power ratio, and the air gap spacing from the cloth to the body. The detailed formula for bioheat transfer analysis considering the abovementioned key parameters is first introduced. Then, a polynomial function is derived by multivariate regression analysis using the simulation result to estimate the skin temperature rises under various exposure conditions and scenarios. In comparison with those results obtained by the traditional methods, the proposed regression algorithm significantly reduced the expense of computational resources. The results estimated using the developed function show a maximum error of less than 0.013 °C for the skin tissues of different body parts and different cloth materials, demonstrating that the proposed method is easy and efficient for the estimation of a high degree of skin temperature rise in a relatively complicated radio-wave exposure environment in millimeter-wave bands. [ABSTRACT FROM AUTHOR]

In the present study, experiments were carried out on circular model bridge piers individually as well as with two-piers-in-tandem arrangement under clear water scour conditions predominantly caused by formation of horseshoe vortex. Independent collar plates around bridge piers and a continuous collar plate covering both the piers were installed as countermeasures against scouring. In case of two piers, efficacy of scour-protection devices for front and rear piers was checked for the overall stability. Performance potential was noted to be about 67% and 100% for continuous collar plates of sizes 2.5D and 3.0D around two piers at average bed level with spacing of 2.0D; where D is the diameter of the pier. During degradation of general bed level, a group of three continuous collar plates was employed around both the piers to ensure considerable reduction of scour. A group of three collar plates of sizes 2.5D and 3.0D having an inter-plate spacing Cs equal to D/4 with the middle plate placed at the average bed level reduced scour by 79 and 82%, respectively, in comparison to the scour depth for an unprotected pier. A mathematical model was developed by multivariate regression analysis to prediction the scour depth for both the pier arrangements. [ABSTRACT FROM AUTHOR]

Soil-test crop response (STCR) approach is aiming to precise adjustment of fertilizers under varying soil-test values for targeted-yield, presently gaining recognitions for sustainable nutrient management. The study aimed to envisage the precision scale of STCR targeted-yield models in maize-lentil rotation in alkaline Fluvisol under sole-fertilizer and integrated nutrient management (with farmyard manure). Fertility-gradient, test-crop diagnostic, and validation trials were conducted following STCR technical program. Soil fertility gradient and variable fertilizer doses had caused a large variation in grain yield of maize (0.99–4.94 t ha−1, CV = 30%) and lentil (1.11–2.02 t ha−1, CV = 13%). Lentil had increased potential to utilize soil nutrient pools; in contrast, maize was highly responsive to fertlizer nutrients. Multivariate-regression analysis revealed that fertilizers N, P, and S had a strong and direct influence on maize yield; where fertilizer-P was the primary yield-determining variable for lentil. Both sole-fertilizer and integrated STCR-based treatments attained the targeted-yields in maize. However, STCR treatments could not attain the targeted-yields in lentil (17–29% deviation), but had yield advantage over the blanket recommended fertilizer dose. Hence, in tropical-alkaline soils, integrated STCR targeted-yield approach could be the sustainable nutrient management option(s) for improving the productivity of the maize-lentil system. [ABSTRACT FROM AUTHOR]

Water managers have increasingly shown that demand management solutions are more important than searching for alternative sources to resolve the challenges and shortages of water supply services. This study identifies the impact of climate variables on residential water demand in three geographically and spatially dispersed towns (Arba Minch, Ziway, and Debre Birhan) in Ethiopia. Monthly mean temperature, relative humidity, and precipitation are analyzed using multivariate regression models to identify and evaluate the impacts of the parameters on water consumption. Principal component analysis (PCA) is also used to determine the dominant independent variable affecting the rate of water consumption. Mean temperature is shown to be the dominant variable causing the changes in water consumption in Arba Minch. The water consumption at Debre Birhan is slightly affected by relative humidity. Analyzed climate variables do not affect the water consumption changes at Ziway. The main findings of this paper show that geographical distribution and other determinants are more important determinants of residential water demand. It is concluded that the analyzed climate variables are not the dominant determinants which impact drinking water consumption at the study sites. Thus, it is recommended to include relevant information about the climate variables alongside other determinants in order to enhance the water management system in evaluating and auditing water usage. [ABSTRACT FROM AUTHOR]

This research focuses on the SMEs development evaluation of the impact of founder’s financial behavior, measured by behavioral characteristics of CEOs capacity for self-awareness, planning, and patience, also their knowledge about financial understanding which affect the ability to manage their performance of SMEs. The purpose of this research is to analyze and reduce the rate of failure of SMEs in Indonesia by pursuing the defined determinants from their behavioral traits and self-knowledge on financial understanding in decision making. This study uses a survey conducted across Indonesia, mainly on Java island, with the sample size of 482 SMEs. This research uses multivariate regression analysis as a tool for measuring the impact of founder’s financial behavior variables and financial literacy variable for SMEs performance as a dependent variable. DOI: 10.26905/jkdp.v25i3.5142