System Measures Research Articles

Consultation Content and Techniques for measurement-Based Care Implementation in Youth Community Mental Health Settings.

Measurement-based care (MBC) is an evidence-based practice (EBP) focused on regularly administering outcome measures to clients to inform clinical decision making. While MBC shows promise for improving youth treatment outcomes, therapist adoption remains low. Clinical consultation is one strategy that improves MBC implementation, but our limited understanding of consultation hinders the ability to optimize its impact. This research explored the content of, and techniques used during MBC consultation calls. Therapists (N = 55) in a randomized controlled trial treating adolescents with anxiety and/or depression were trained to utilize MBC with usual treatment using the Youth Outcome Questionnaire (YOQ) through an online measurement feedback system (MFS). Weekly ongoing consultation followed an initial workshop training in MBC. Case discussions (N = 294) during consultation calls were coded using a developed codebook, including 12 content and 10 consultant techniques. Results indicated that content focused predominantly on interpretation of client symptom and alliance report, planning for YOQ administration, and discussion of data with clients in session. Common consultant techniques included modeling and eliciting report viewing and interpretation, making clinical suggestions, and didactics about clinical and technical issues. Notably, role-play/behavioral rehearsal was not used. The prevalence of passive consultation techniques (suggestions, didactics) suggests a focus on teaching rather than active techniques (behavioral rehearsal, modeling), potentially influenced by the novelty of MBC and MFS. Technical aspects of MBC, such as measure administration and system usage, emerged as key consultation content, highlighting an unanticipated emphasis on logistics over clinical implementation. These findings underscore the evolving role of consultation in supporting MBC implementation and suggest that addressing technical challenges early in training might enhance adoption.

A preliminary application and its error estimates of a simple stereo-camera measure system for the far-sea fishery of Pacific saury

Pacific saury is one of the most economically important species in the northwestern Pacific Ocean. The management of this resource relies on precise input of biological data such as body length and is often hindered by a lack of such data on captured fish. This study explores the potential of electronic monitoring (EM) using off-the-shelf stereo cameras to overcome the challenges of collecting and measuring saury body length from the Pacific saury fishery. Using a calibrated WEEVIEW SID WV3000 3D camera, a total of 252 paired images with different shooting angles and distances were obtained for further measurement using Sebastes Stereo Image Analysis Software (SSIAS). The treatments for the measurement distance (MD) were 30 cm, 60 cm, and 100 cm, for the depression angle (DA) were 30°, 60°, and 90°, and for the position angle (PA) were 0°, 45°, and 315° (− 45°). An assistant calibration (AC) in the form of a 16 cm black ruler was also added used. The SSIAS measurement results indicated that the best measurement was obtained with 0° position angle, 90° depression angle, and 30 cm distance from the target fish. The use of AC in the SSIAS + AC measurement was proven to reduce the measurement error from 2.45 to 8.64% to − 1.86 to 0.01%. This study set the baseline for the application of EM on collecting saury body length and the use of AC has been proven to increase the measurement accuracy.

The Experience of Observational Departments’ Functioning for Treatment of Patients with Tuberculosis from COVID-19 Contact and Convalescents after COVID-19

Relevance. To control COVID-19, a net of special infection hospitals and departments was created, a system of medicaments and protective means’ supply was set up, necessary normative and regulatory documentation was developed and overall vaccination of population was performed in Moscow. Within frames of work for prophylaxis of COVID-19 spread in patients with tuberculosis at in-patient units of the State Budgetary Healthcare Institution of Moscow city «The Moscow Research and Clinical Center for Tuberculosis Control of the Moscow Government Department of Health” (hereinafter referred as the Center), observational departments for treatment of patients with tuberculosis from COVID-19 contact and convalescents after COVID-19. Aims. To evaluate specialized observational departments’ work as part of general anti-epidemic control measure system for COVID- 19 at tuberculosis hospitals. Materials and methods. The observational departments’ work within the period of 2020–2022 with 1075 patients treated including 400 patients from COVID-19 contact areas (37.2%) and 675 convalescent patients after COVID-19 (62.8%), was analyzed. The results obtained during the study were statistically treated by means of application program package Microsoft Office 2007. The quantitative parameters with presumably normal distribution were described with mean arithmetic values (M) and standard deviations (SD), and 95% confidence interval (CI 95%). The estimation of significance of differences between outcomes was evaluated with the Pearson χ2 test. The differences were considered to be statistically significant with p < 0,05. Results and discussion. The evaluation data on functioning efficacy of observational departments for patients with tuberculosis from COVID-19 contact and convalescent patients with tuberculosis after COVID-19 within the large medical institution hospital of physiatry profile. Among all patients, 153 of patients who fell ill with COVID-19 (14.2%; 95% CI [12.21–16.38%]) were determined, which lowered the number of COVID-19 areas at in-patient departments of the Center by 11.8%. The mean timeframes of COVID- 19 determination in general were 8.0 days: 5.4 days among contacts from new coronavirus infection areas and 12.4 days among convalescents at the department for the treatment of patients with tuberculosis and new coronavirus infection. The comparative analysis showed that COVID-19 was more frequently determined in tuberculosis patients from the contact with those who fell ill with COVID-19 (p < 0.001) than in convalescents. Conclusions. During medical care for patients of physiatry profile in Moscow city, a wide range of management decisions consisting in the change of routing system in specialized medical care, was taken. Among them, creation and functioning of observational departments for contact persons from COVID-19 areas and convalescents after COVID-19 play a particular role.Creation of such departments within a large medical institution enabled the contemporary isolation of contact persons from COVID- 19 areas and convalescents after COVID-19 and allowed the additional control of nosocomial infection spread

浅析WTO 对《美国对进口晶体硅光伏产品的保障措施》的裁决

This article focuses on the safeguards measure case of “China vs. U.S. Crystalline Silicon Photovoltaic Products” and deeply explores the relevant issues related to safeguard measures in international trade remedies involved in this case. Research on this issue will help China better understand responding to related trade frictions in international trade has enabled China to change its passive position into an active position in dealing with such issues. This article explains the safeguard measure case of “China vs. United States Crystalline Silicon Photovoltaic Products” and then introduces the rules of the WTO safeguard measure system. It then analyzes the five focus points of dispute, focusing on the expert group’s analysis of the causal relationship in this case. Identify the situation, and finally discuss China’s response to such situations.

Optimized scheduling of smart community energy systems considering demand response and shared energy storage

Integrated energy systems within communities play a pivotal role in addressing the diverse energy requirements of the system, emerging as a central focus in contemporary research. This paper contributes to exploring optimal scheduling in a smart community featuring multiple smart buildings equipped with a substantial share of distributed photovoltaic sources, shared energy storage, and controllable loads. The study formulates a two-stage scheduling optimization model incorporating multiple stakeholders, explicitly examining the game dynamics between the smart community operator and the customer load aggregator. The weights assigned to each optimization objective are determined using an analytic hierarchy process-entropy weight method to establish a balanced and nuanced approach. The ensuing optimal scheduling encompasses unit output and energy trading considerations, focusing on enhancing the system's economic viability, safety measures, and environmental sustainability. A comprehensive evaluation is conducted to validate the proposed model by comparing its performance with alternative operational strategies. The results show that the designed strategy can reduce the operating cost by 40.22% and increase the level of PV consumption by 22.57% compared to the traditional heat-based strategy, which is effective in mitigating power fluctuations, smartly responding to dispatch peak demand, enhancing new energy integration, and ensuring the security of grid operation.

Canine Disease Prediction using Multi-Directional Intensity Proportional Pattern with Correlated Textural Neural Network

Data optimization is crucial for enhancing prediction accuracy and similarity identification in texture learning systems, especially for predicting canine diseases. Traditional data retrieval methods often struggle with accuracy and efficiency, particularly when dealing with large datasets. This study presents a novel approach combining Multi-Directional Intensity Proportional Pattern (MDIPP) with a Similarity Measure (SM) system to improve data relevance and similarity estimation. The model organizes data into a paged database structure, which speeds up search operations. A neural network, Correlated Textural Neural Network (CTNN), forecasts the relevance of feature attributes and sorts matching indexes to predict canine diseases based on Test data. The CTNN model incorporates a correlation factor among features to enhance prediction accuracy. The relevance of data is determined using an upgraded neural network that accounts for these correlations. The study evaluates performance based on precision, recall, F1-score, and data retrieval accuracy, comparing the results with state-of-the-art techniques. By improving the organization and indexing of data and refining the prediction process, this approach aims to advance data validation and the prediction of canine diseases in large-scale texture learning systems

A case study of pragmatic measure development of the Treatment Integrity for Elementary Settings self-report measure for teachers.

Due to usability, feasibility, and acceptability concerns, observational treatment fidelity measures are often challenging to deploy in schools. Teacher self-report fidelity measures with specific design features might address some of these barriers. This case study outlines a community-engaged, iterative process to adapt the observational Treatment Integrity for Elementary Settings (TIES-O) to a teacher self-report version designed to assess the use of practices to support children's social-emotional competencies in elementary classrooms. Cognitive walkthrough interviews were conducted with teachers to improve the usability of the teacher self-report measure, called the Treatment Integrity for Elementary Schools-Teacher Report (TIES-T). Qualitative content analysis was used to extract themes from the interviews and inform changes to the measure. Increasing clarity and interactive elements in the measure training were the dominant themes, but suggestions for the measure format and jargon were also suggested. The suggested changes resulted in a brief measure, training, and feedback system designed to support the teacher's use of practices to support children's social-emotional competencies in elementary classrooms. Future research with the TIES-T will examine the score reliability and validity of the measure.

Non-Invasive Assessment of Abdominal/Diaphragmatic and Thoracic/Intercostal Spontaneous Breathing Contributions.

(1) Background: Technically, a simple, inexpensive, and non-invasive method of ascertaining volume changes in thoracic and abdominal cavities are required to expedite the development and validation of pulmonary mechanics models. Clinically, this measure enables the real-time monitoring of muscular recruitment patterns and breathing effort. Thus, it has the potential, for example, to help differentiate between respiratory disease and dysfunctional breathing, which otherwise can present with similar symptoms such as breath rate. Current automatic methods of measuring chest expansion are invasive, intrusive, and/or difficult to conduct in conjunction with pulmonary function testing (spontaneous breathing pressure and flow measurements). (2) Methods: A tape measure and rotary encoder band system developed by the authors was used to directly measure changes in thoracic and abdominal circumferences without the calibration required for analogous strain-gauge-based or image processing solutions. (3) Results: Using scaling factors from the literature allowed for the conversion of thoracic and abdominal motion to lung volume, combining motion measurements correlated to flow-based measured tidal volume (normalised by subject weight) with R2 = 0.79 in data from 29 healthy adult subjects during panting, normal, and deep breathing at 0 cmH2O (ZEEP), 4 cmH2O, and 8 cmH2O PEEP (positive end-expiratory pressure). However, the correlation for individual subjects is substantially higher, indicating size and other physiological differences should be accounted for in scaling. The pattern of abdominal and chest expansion was captured, allowing for the analysis of muscular recruitment patterns over different breathing modes and the differentiation of active and passive modes. (4) Conclusions: The method and measuring device(s) enable the validation of patient-specific lung mechanics models and accurately elucidate diaphragmatic-driven volume changes due to intercostal/chest-wall muscular recruitment and elastic recoil.

JAVANESE MEDICINAL MEASURE LEXICONS (NUMERAL CLASSIFIERS) IN SERAT PRIMBON RERACIKAN JAMPI JAWI

Traditional medicine in a global context has been observed widely in several countries. Research on traditional medicine has not been massively conducted in Indonesia, especially in Java. The present research, in response to the area of this subject, is an initial study to observe and examine the traditional medicine in Java, especially the medicine measurement system recorded in Serat Primbon Racikan Jampi Jawi. The measure system in traditional medicine has various lexicons as has been revealed in the lexicalization of numeral classifiers and the cultural context of the measurement system in traditional medicine recorded in Serat Primbon Racikan Jampi Jawi. The theoretical perspectives are composed of culture, semantics, and lexicography; using note-taking techniques as the data collection, dictionary method as the data analysis, definition and meaning description as the data presentation as well as its meaning relations. Based on the observation, there were 77 (seventy-seven) Javanese measure lexicons consisting of 60 (sixty) base words, 5 (five) affixed words, and 13 (thirteen) word combinations in Serat Primbon Racikan Jampi Jawi. Meaning relations found from the lexicons were abstract meaning relations by using 7 (seven) concepts of retrieval and concrete features with 6 (six) compositional constructions. The measure was obtained from 9 (nine) other fields of lexicon and was used to measure 25 (twenty-five) types of ingredients with one-to-one relations, one-to-two or more relations, and two or more-to-one relations. This research indicated that (1) The form of language adapts to the creativity and references in the measure; (2) The meaning of the measure characterizes the experience and knowledge of the Javanese people on the traditional medicine system in their everyday life; and (3) The measure system is the answer to the needs, specifications, and inheritance of the local wisdom of the Javanese people, particularly in the field of traditional medicine.

Applying rainfall threshold estimates and frequency ratio model for landslide hazard assessment in the coastal mountain setting of South Asia

Landslides pose a serious risk to life and property in the mountainous regions around the globe. Understanding the interplay of landslide conditioning and triggering factors is essential for lessening the impacts caused by the hazard. Cox's Bazar — a coastal mountainous district in Bangladesh is recurrently affected by rainfall-triggered landslides. Based on analysis of 14 experiential landslides and combination of gauged and satellite rainfall estimates for the period from 2003 to 2019, the present study determines three landslide-triggering rainfall thresholds for the Cox's Bazar District (CBD): 1. Intensity-Duration (ID) threshold derived in this study revealed that any rainfall event with an intensity of ≥4.04 ​mm/h if prolonging for ≥12h can cause slope failures; 2. Event-Duration (ED) threshold suggested that a normalized cumulative event rainfall (EMAP) of 0.15 for one day is expected to trigger landslides; and 3. threshold calculated using randomly chosen antecedent rainfall expressed best distinction on 30-day rainfall and the equation of the threshold came out as Rth ​= ​64–0.02 Ra30. The recurrence probability of the derived antecedent rainfall threshold and likely landslides was determined through the Poisson distribution. Moreover, we assess the landslide susceptibility of the district with a coupled use of Frequency Ratio (FR) statistical measure and Geographic Information System (GIS). Considering the combined role of selected conditioning factors, the landslide susceptibility status of the CBD was quantified and classified into probability intervals. The accuracy of the susceptibility maps was assessed through the Relative Landslide Density Index (R-Index) that used a field landslide inventory, comprising well distributed 891 events. Moreover, gridded population data was superimposed on the derived susceptibility maps to understand the risk levels of people. The derivation of landslide-triggering rainfall thresholds and spatial susceptibility assessment has been useful to propose a low-cost Landslide Early Warning System (LEWS) which can contribute in alleviating the adverse effects of landslide hazard in the CBD.

Successful Return to Sport and Daily Activities After Suture Augmentation of Both the Anterior Talofibular Ligament and Calcaneofibular Ligament

To evaluate the return to sport and daily activities in addition to clinical outcomes after modification of the Brostöm repair, specifically using suture augmentation for concomitant fixation of both the anterior talofibular ligament and calcaneofibular ligament. Patients who had grade III ankle sprains and lateral ankle instability, all of whom failed supervised conservative management, were included. Patients underwent a modified Broström procedure consisting of suture augmentation for both the anterior talofibular ligament and calcaneofibular ligament. For clinical outcome evaluation, Foot and Ankle Ability Measure (FAAM) and Karlsson-Peterson Scoring System for Ankle Function questionnaires coupled with questions regarding time of return to sport and level of sports activity were used. Thirty-one patients were included. The differences in preoperative and postoperative FAAM scores for both the Activities of Daily Living subscale and Sports subscale were significant (P < .001). The FAAM Activities of Daily Living score improved from an average of 46.06 preoperatively to 77.49 postoperatively (P < .001, 99% confidence interval, 26.4-36.4). The FAAM Sports score improved from an average of 4 preoperatively to 19.31 postoperatively (P < .001, 99% confidence interval, 11.6-19.0). For the Karlsson-Peterson Scoring System for Ankle Function, the surveyed population reported a mean of 82.74 points out of 100 post-op (standard deviation 20.14). The mean time to return to sport activity was 5.72 months. Mean follow-up time was 24.12 months. This variant Broström procedure with suture anchors and augmentation of both the anterior talofibular ligament and calcaneofibular ligament was effective in helping patients return to their preinjury functionality level in both daily life and sports activity. Level IV, therapeutic case series.

Methods for Electroporation and Transformation Confirmation in &lt;em&gt;Limosilactobacillus reuteri&lt;/em&gt; DSM20016

Lactobacillus were an incredibly large, diverse genus of bacteria comprising 261 species, several of which were commensal strains with the potential for use as a chassis for synthetic biological endeavors within the gastrointestinal tract. The wide phenotypic and genotypic variation observed within the genus led to a recent reclassification and the introduction of 23 novel genera. Due to the breadth of variations within the old genera, protocols demonstrated in one member may not work as advertised with other members. A lack of centralized information on how exactly to manipulate specific strains has led to a range of ad hoc approaches, often adapted from other bacterial families. This can complicate matters for researchers starting in the field, who may not know which information does or does not apply to their chosen strain. In this paper, we aim to centralize a set of protocols with demonstrated success, specifically in the Limosilactobacillus reuteri strain designation F275 (other collection numbers: DSM20016, ATCC23272, CIP109823), along with troubleshooting advice and common issues one may encounter. These protocols should enable a researcher with little to no experience working with L. reuteri DSM20016 to transform a plasmid, confirm transformation, and measure system feedback in a plate reader via a reporter protein.

Physiotherapy Management in Cases of Cerebral Palsy Flaccid Ec Microcephaly

Cerebral Palsy is a disorder of the development of body movement and posture, resulting in movement limitations that can occur starting from the fetus or baby accompanied by disorders of the musculoskeletal system, sensation, perception, awareness, communication, and behavior. the study used a case report study conducted at the Oemah Physiotherapy Clinic in Solo. The cause of cerebral palsy begins during the prenatal period which is caused by infection, anoxia, toxic, genetics, congenital malformations of the brain, the neonatal period occurs due to anoxia, traumatic, and postnatally caused by trauma, infection and toxic. Physiotherapy helps in optimizing children's active movements by using interventions in the form of myofacial release, patterning, and exercise. After being treated for 4 times T1-T4 there was no increase or change in muscle strength by measuring XOTR muscle strength and motor function in children using gross motor function measure (GMFM) and gross motor function classification system (GMFCS) measurements. Keywords: Cerebral Palsy, XOTR, GMFM, GMFCS

Reconsidering the syntactic complexity measures on L2 spoken English: A multi-dimensional perspective

Based on a review of previous measures employed in English syntactic complexity investigation, this article, following Biber's Multi-dimensional approach, re-establishes a comprehensive new measure system which is composed of four dimensions i.e. Subordination, Length of Production, Coordination and Nominals using factor analysis upon a collection of indices in reference. Under the newly established framework, the research examines the effects of grade level and genre factors on second language English learners' syntactic complexity in oral English in terms of the four indices representing the four dimensions. ANOVA results show that all indices except C/T, the one representing the Subordination dimension, which shows stability across grade levels, are positively related with grade level and susceptible to genre. In the argumentative genre, students generally produce more complex sentences than in the narrative genre as regards all the four dimensions.

Generalized picture fuzzy distance and similarity measures on the complete lattice and their applications

Picture fuzzy sets (PFSs) with four dimensions of positive, neutral, negative, and rejection have more advantages in representing and evaluating ambiguous information than intuitionistic fuzzy sets. But, since the PFS’s introduction, its measure theory has not been sufficiently developed. The existing picture fuzzy distance measures (PFDMs) and picture fuzzy similarity measures (PFSMs) are sometimes invalid or irrational, as they were not constructed on a bounded lattice. To get over these restrictions, this paper seeks to develop a picture fuzzy measure system. First, their restrictions are determined by categorizing the PFDMs and PFSMs, the score functions. Second, the probability-based λ−1-precision score function for picture fuzzy numbers and its computational aspects are highlighted. Again, the proposed score function is used to depict the generalized PFDMs/PFSMs on a complete lattice. In comparison study, some numerical examples are provided to confirm the effectiveness of the proposed measures. Then, a framework for making decision is offered to address multi-criteria decision-making problems with uncertainty by combining the proposed generalized PFDM and the concept of the Vlsekriterumska Optimizaca I Kompromisno Resenje (VIKOR) method. Finally, the drug selection problem in medical diagnostics is addressed using the suggested decision-making framework. Sensitivity and comparative studies demonstrate the validity, adaptability, and superiority of the suggested method.

Detection of sarcopenia using deep learning-based artificial intelligence body part measure system (AIBMS).

Background: Sarcopenia is an aging syndrome that increases the risks of various adverse outcomes, including falls, fractures, physical disability, and death. Sarcopenia can be diagnosed through medical images-based body part analysis, which requires laborious and time-consuming outlining of irregular contours of abdominal body parts. Therefore, it is critical to develop an efficient computational method for automatically segmenting body parts and predicting diseases. Methods: In this study, we designed an Artificial Intelligence Body Part Measure System (AIBMS) based on deep learning to automate body parts segmentation from abdominal CT scans and quantification of body part areas and volumes. The system was developed using three network models, including SEG-NET, U-NET, and Attention U-NET, and trained on abdominal CT plain scan data. Results: This segmentation model was evaluated using multi-device developmental and independent test datasets and demonstrated a high level of accuracy with over 0.9 DSC score in segment body parts. Based on the characteristics of the three network models, we gave recommendations for the appropriate model selection in various clinical scenarios. We constructed a sarcopenia classification model based on cutoff values (Auto SMI model), which demonstrated high accuracy in predicting sarcopenia with an AUC of 0.874. We used Youden index to optimize the Auto SMI model and found a better threshold of 40.69. Conclusion: We developed an AI system to segment body parts in abdominal CT images and constructed a model based on cutoff value to achieve the prediction of sarcopenia with high accuracy.

Influence of built environment on building energy consumption: a case study in Nanjing, China.

Built environment plays a significant role in optimizing building energy consumption. However, few studies have explored the comprehensive effect between built environment metrics on building energy consumption. Thus, this study aims to explore interrelationships between built environment on building energy consumption focused on moderating effect. In this study, we established a built environment measure system from the perspective of land use and land cover, landscape structure and building configuration. This study explored the correlation between built environment and building energy consumption and analyzed the moderating effect of building configuration emphatically. Results show that: for integrated grids group, normalized difference vegetation index (NDVI) and modified normalized difference water index (MNDWI) have a positive influence and impervious area (IA) has a negative influence, with NDVI has the greatest impact. Building floor (BF), building coverage ratio (BCR) and aspect ratio can weaken the positive relationship between NDVI and energy use intensity of grid ( ). BCR weakens the positive effect of MNDWI on . The moderating effect of building configuration on EUI varies in the same grid group and among different grid groups. For sample 1, BCR inhibits the negative effect of mean perimeter-area ration (PARA-MN) on . For sample 2, BF promotes the negative effect of number of patches and land use richness index (R) on . And sky view factor inhibits the positive effect of IA on . This study reveals the pathways of built environment on building energy consumption. As a result, the keys of optimizing building energy consumption are the reasonable planning and optimization of the urban built environment of different land cover. The online version contains supplementary material available at 10.1007/s10668-023-02930-w.

Joint angular-frequency distribution estimation via spatial-temporal sparse sampling and low-rank matrix recovery

This paper is committed to the joint angular-frequency distribution (JAFD) estimation for incoherently distributed wideband (IDW) sources by using spatial-temporal sparse sampling (STSS). The STSS increases dramatically the degrees of freedom (DOFs) of the measure system, and can solve the ambiguity problem between angular and frequency parameters. Then, it is observed that the discrete representation of the JAFD gives rise to a helpful low-rank matrix. To estimate the JAFD for IDW sources, a rank minimization problem is further formulated as the modified Schatten-p norm minimization (MSpNM) problem, which can be resolved efficiently by the accelerated iterative singular value thresholding algorithm (AISVTA). Compared with traditional methods based on spatial and temporal Nyquist sampling (STNS), the proposed method based on STSS reduces the sampling rate requirement on hardware and provides better JAFD estimation precision. Experiment simulations indicate its effectiveness and confirm the superior performance of the proposed method based on STSS.

Optimization of M/M/2 Queueing Model with Working Vacations

The paper deals with an M/M/2 Queueing Model with working vacations and reneging of customers due to impatience. The matrix geometric method is used to find the distribution of the number of customers in the system. A cost function is constructed to obtain the optimal value of the service rate to optimize (minimize) the cost function using the Quadratic Fit Search Method (QFSM). Further, the effects on the system's performance measures using numerical analysis and graphical representation are studied.

Methods to assess validity of positioning systems in team sports: can we do better?

ObjectivesThere is previously reported a large variety of criterion measures and reference systems applied to validate position tracking systems in sports. This study aims to investigate the effect of different...