Spearman Rank Order Correlation Research Articles

PRELIMINARY ANALYSIS SUGGESTS FRESHWATER INVERTEBRATE ENVIRONMENTAL DNA IS MORE CONCENTRATED IN SURFACE WATER THAN IN BENTHIC SEDIMENTS

Abstract The collection, identification, and census of freshwater invertebrates helps to increase understanding of the ecological function of lakes and streams. However, this work can be time-consuming and laborious because invertebrate identification often requires considerable taxonomic training and expertise. The collection and analysis of environmental DNA (eDNA), the genetic material that organisms shed into their surrounding environment, represents a potentially revolutionary approach for rapid and accurate invertebrate surveillance in freshwater environments. Previous studies have demonstrated that fish eDNA tends to be more abundant in freshwater lake sediments than the water column above, so we conducted an experiment to examine whether this pattern holds true for freshwater invertebrates. We collected paired samples from benthic sediments and the water column at ten sites around an urban playa lake in Lubbock, Texas. Based on cycle threshold values from quantitative PCR (qPCR) amplification with universal invertebrate primers targeting the COI gene, a paired Wilcoxon signed-rank test and Spearman rank-order correlation suggested that invertebrate eDNA quantities were correlated between the sediment and water column but consistently more concentrated in the water compared to the sediment below, directly contrasting with previous studies of fish eDNA. Future work combining eDNA detection and high-throughput sequencing (i.e., metabarcoding) will increase understanding of how eDNA signals relate to local invertebrate pools and increase the utility of eDNA sampling for freshwater invertebrates.

Patient-Reported Outcome Measurement Information System Depression and Anxiety in Elective Knee Surgery Patients.

Mental health has been shown to play an important role in patient-reported outcomes (PRO); however, there is a general lack of literature describing patient-reported outcome measurement information system (PROMIS) depression and anxiety computer adaptive tests in elective knee surgery patients. The purpose of our study was to assess the prevalence of depression and anxiety symptoms before and after elective knee surgery and to determine whether these symptoms influence postoperative functional outcomes. An institutional review board-approved prospective orthopaedic registry was retrospectively queried for patients undergoing elective knee surgery from June 2015 to November 2018. Electronic surveys collecting patient demographic information and PROs were administered pre- and postoperatively. Of the 663 patients that completed baseline questionnaires, 466 completed 2-year follow-up (70.3%). PROs included PROMIS depression, PROMIS anxiety, International Knee Documentation Committee Subjective Knee Form (IKDC), and PROMIS physical function (PF). Wilcoxon rank sum and Spearman's rank order correlation were utilized to determine associations between variables. Multivariable analysis was used to control for confounding variables. Average PROMIS depression and anxiety scores significantly improved 2 years after surgery. PROMIS depression and anxiety scores significantly correlated with each other. PROMIS depression and anxiety scores significantly correlated with PROMIS PF and IKDC scores. After controlling for confounders on multivariable analysis, worse 2-year PROMIS anxiety was predictive of less functional improvement and worse 2-year PF and IKDC, while worse 2-year PROMIS depression was predictive of less improvement in IKDC. This study confirms the important relationship between mental health and functional outcomes. Given that psychiatric comorbidities are potentially modifiable with treatment, proper recognition could potentially lead to better orthopaedic outcomes. In addition, the prevalence of depression and anxiety symptoms postoperatively, as documented by PROMIS computer adaptive tests, may act as a barrier to achieving optimal functional outcomes after elective knee surgery. LEVEL OF EVIDENCE: Level III.

Marketing yourself in social media as a global health organization: lessons to be learned.

To evaluate whether X, formerly known as Twitter, is being used effectively to advance the goals of International Volunteers in Urology (IVUmed). How is X activity associated with end-user engagement? Monthly analytics of the X account @IVUmed were reviewed between September 2014 and November 2022 using https://analytics.twitter.com/ . Outcomes included tweets, mentions, impressions, engagements, interactions, followers, and profile visits. Statistical analysis using Mann-Whitney U test and Spearman's rank-order correlation was performed. Top tweet content between December 2020 and November 2022 was also analyzed and assigned one of seven different categories: research, workshops, mission statement, educational materials, fundraising, individual spotlight, and other. Of @IVUmed's 1668 followers, 1334 (80.0%) were individuals. One thousand one hundred twenty-six (84.4%) individuals listed their locations with the majority (79.8%) residing in high-income countries. Tweet impressions have increased over time; they were significantly higher (p < 0.01) on average after the onset of COVID-19 in March 2020. From December 2020 to November 2022, new followers were positively correlated with tweet impressions (p < 0.01), total mentions (p < 0.01), and profile visits (p < 0.01). Profile visits were positively correlated with total tweets (p < 0.01). The content categories for monthly top tweets that proportionally garnered the most engagements were workshops (50%) and individual spotlight (29%), despite not being the most tweeted about content categories. Non-profit organizations wishing to increase their web-based outreach can benefit from increased primary X activity. While not evaluated in this study, it may also improve fundraising capabilities. Nevertheless, periodic review of account activity is important to ensure engagement of the targeted audience.

P006 The Impact of Growth Hormone Treatment on Cardiovascular Control in Children with Prader-Willi syndrome

Abstract Background Many children with Prader-Willi syndrome (PWS) are treated with growth hormone (GH), which may increase the risk of obstructive sleep apnoea. Children with PWS also have impaired cardiac autonomic control due to reduced parasympathetic activity, which may increase cardiovascular risk, however the impact of GH on autonomic control is yet to be elucidated. Methods Pre- and post-GH polysomnographic data in 38 children (aged 0-18 years) were retrospectively collected. Spectral analysis of heart rate variability (HRV) was used to determine total, low frequency (LF, sympathetic and parasympathetic activity), high frequency (HF, parasympathetic activity) power and LF/HF (sympathovagal balance). Data were compared with Wilcoxon Signed Rank Test and Spearman Rank Order Correlation analysis and are presented as median [interquartile range]. Results HRV data were significantly correlated with age so children were grouped into those &amp;lt;2 years (n=22) and &amp;gt;2 years (n=16). There were no significant differences in the obstructive or central apnoea-hypopnoea indexes between pre- and post-GH studies in either group. In children &amp;lt;2 years, there were no significant differences in total power, LF, HF and LF/HF between studies. In children &amp;gt;2 years, total power (1912.2 ms2, [920.2, 4916.1] vs 1010.2 ms2 [416.0, 2828.7), LF (434.0 ms2 [247.0, 1340.7] vs 278.9 ms2 [83.4, 676.0]) and HF (986.0 ms2 [321.8, 2400.6] vs 414.4 ms2 [146.2, 1152.7]) were lower (p&amp;lt; 0.01 for all) post-GH. Conclusions Our results demonstrate that GH decreases both sympathetic and parasympathetic activity during sleep in children &amp;gt;2 years, which could further increase cardiovascular risk.

Influence of Social Media Marketing Strategies and Best Practices on E-Satisfaction And E-Loyalty

This study investigated hotels' social media marketing strategies in Davao Region. Also, it determined the perceived effectiveness of the social media marketing used by the selected hotels' level of e-satisfaction of tourists using social media marketing by selected hotels. This study used a descriptive research design since it aimed to explain and interpret the findings gathered from the quantitative data. There were 455 respondents for the quantitative data and eight (8) respondents for the qualitative data. Instruments used in the study were an adapted survey questionnaire and an in-depth interview utilizing the research guide questions. The study participants were purposively selected, and the questionnaires were distributed equally. This study analyzed the statistical data using the Frequency, Weighted Median, Kruskal-Wallis, Spearman's Rank-Order Correlation, and Multiple Regression Analysis. Data revealed that social media is one of the most cost-efficient digital marketing methods; Facebook is the most prevalent Social Networking Site (SNS) used by hotels and use third-party booking sites to support the hotel's revenue. Moreover, findings showed that selected hotels implemented a high level of effectiveness of social media, a high level of customers' e-satisfaction on social media, and a high level of e-loyalty of hotels' customers on social media marketing strategies by hotels. Thus, the result clarified that compared to social media marketing, e-satisfaction, as a factor in general, was influential in igniting e-loyalty. Lastly, three (3) best practices were identified from the participants: innovation, customer engagement, and accessibility.

Modeling of daily groundwater level using deep learning neural networks

Groundwater is an essential water source, becoming more vital due to shortages in available surface water resources. Hence, monitoring groundwater levels can show the amount of water available to extract and use for various purposes. However, the groundwater system is naturally complex, and we need models to simulate it. Therefore, we employed a deep learning model called CNN-biLSTM neural networks for modeling groundwater, and the data was obtained from USGS. The data included daily groundwater levels from 2002 to 2021, and the data was divided into 95% for training and 5% for testing. Besides, three deep CNN-biLSTM models were employed using three different algorithms (SGDM, ADAM, and RMSprop(. Also, Bayesian optimization was used to optimize parameters such as the number of biLSTM layers and the number of biLSTM units. The model's performance was based on Spearman's Rank-Order Correlation (r), and the model with SGDM showed the best results compared to other models in this study. Finally, the CNN model with LSTM can simulate time series data effectively.

Landscape of the Radiosensitizing Properties of Targeted Agents from the NCI CTEP Portfolio across Genomically Diverse 3D Tumor Models

Clinical translation of molecular targeted radiosensitizers remains challenging. To improve the robustness of preclinical data, we sought to broadly examine across a wide spectrum of genomic cancer features the radiosensitizing properties of targeted drugs from the NCI Cancer Therapy Evaluation Program (CTEP). As part of a U01 Consortium, we adapted a robotic high-throughput platform for testing ionizing radiation (IR) plus drug combinations in 3D cultures derived from non-small cell lung carcinoma (NSCLC), head/neck (HNSCC), and pancreatic cancers. All cell lines were annotated, mycoplasma free, and re-authenticated. Signal windows were established for all 3D growth formats. CTEP drugs were added in four concentrations 24 hours prior to IR exposure of 384-well plates. Five days after IR, cell viability was assessed, an endpoint previously benchmarked using colony formation. Each data point was based on 4-6 technical replicates with 2 biological repeats. A multistep statistical method combining Wilcoxon signed-rank and Spearman rank-order correlation tests together with adjusted Benjamini-Hochberg corrections for multiple comparisons was used to identify radiosensitization hits. Select validation experiments of hits were carried out. We screened 73 3D tumor models with 34-42 CTEP drugs each plus IR (n = 10,744 cell line/drug concentration combinations). IR/drug patterns were comparable for the three cancer types. DNA damage response (DDR) inhibitors constituted the most active class of radiosensitizers with DNA-PKcs, PARP, and ATR being the top targets. In contrast, the majority of the other agents radiosensitized only a minority of models. Highlighting NSCLC, out of 1,120 cell line/drug combinations, 328 (29.3%) were associated with statistically significant radiosensitization. PARP inhibitors, of particular interest for clinical translation in this space, demonstrated relatively broad radiosensitization for talazoparib (62%) and olaparib (44%) but less so for veliparib (28%), which correlated with differential PARP trapping potentials. Radiosensitization was evident even for tumor genotypes associated with radioresistance such as mutant KRAS, KEAP1, and STK11. Interestingly, single-agent activity of olaparib was more pronounced in 11/30 3D cultures compared to 2D growth conditions but with only 2/11 having known homologous recombination defects. Lastly, for HPV negative HNSCC (735 combinations), there was radiosensitization in subsets of models for IAP, ATR, and AKT targets, which are under clinical investigation. We present a unique resource for examining radiosensitizing drug properties in 3D cultures. The observed radiosensitization patterns strongly argue for the use of larger panels of clinically relevant tumor models rather than a few non-representative cell lines. Our data highlight the urgent need for predictive biomarkers to guide IR/drug combinations, even for some DDR inhibitors.

POLICE RECORD MANAGEMENT: IDENTIFICATION OF THE PROBLEMS ENCOUNTERED BY POLICE PERSONNEL IN THE FIRST CONGRESSIONAL DISTRICT OF ZAMBOANGA DEL NORTE

This paper primarily sought to determine the extent of effectiveness of police records management in the first congressional district of Zamboanga del Norte. This study employed a quantitative method which included descriptive-survey and descriptive-correlational. There were thirty (30) respondents in the study. Frequency count and per cent, weighted mean, Mann-Whitney U Test, Kruskal-Wallis H Test, and Spearman rank-order correlation were the statistical tools used in the study. The study revealed that the level of respondents' perception level on the attributes of records management, specifically in records creation, records retention and disposition, records storage and maintenance, records access and retrieval, and appropriate use of technology and records management programs is “very much effective" rating. However, the level of respondents' perception level on archival records is "much effective." Moreover, the problems encountered by police personnel in managing police records are not serious and the extent of the factors precipitating the police personnel problems encountered in managing police records is to the least extent. Furthermore, there was no relationship between police record management attributes and record management problems. It signifies that the police records officers' highly effective management of police records had nothing to do with their less severe management issues. In other words, police officers who claimed to be highly competent at handling police records did not necessarily have major issues doing so. Keywords: Police personnel records management, recordkeeping

The Effectiveness of Communication on Generasi Pesona Indonesia’s Instagram in Fulfilling Tourism Informationn Needs

The rise of social media platforms has transformed the way individuals access information, with Instagram emerging as a potent medium due to its visual appeal and engaging features. This research, titled "The Effectiveness of Tourism Communication on Generasi Pesona Indonesia’s (GenPI) Instagram in Fulfilling Tourism Information Needs," aims to assess the efficacy of communication on GenPI's Instagram account in meeting the tourism information needs of its followers. The theoretical framework for this research encompasses concepts such as communication, communication effectiveness, new media, Instagram, and information needs. Employing a quantitative approach with a descriptive focus, the study targets the followers of Generasi Pesona Indonesia’s (GenPI) Instagram account(@genpiindonesia), constituting a population of 15,900 individuals. A sample size of 99 respondents is determined using the Taro Yamane formula, selected through purposive sampling. Data is collected through literature review and questionnaires distributed via Google Form. Analysis of the collected data involves single-table and cross-table examinations, and the relationship between variables is assessed using Spearman's Rank Order Correlations formula with SPSS 25 software. The findings indicate that video content on GenPI’s Instagram account effectively fulfills the tourism information needs of followers, providing valuable recommendations and sought-after tourist destinations. Moreover,the research demonstrates a significant relationship between followers' interaction frequency with Generasi Pesona Indonesia (GenPI)'s Instagram account and the extent to which their tourism information needs are satisfied. This study sheds light on the pivotal role of Instagram as a tool for disseminating tourism-related information, exemplified by GenPI's account, in satisfying the informational requirements of its audience.

Sales Force Training and Employee Performance of Insurance Firms in Port Harcourt

This study examined the requirements of sales force training and employee performance of of insurance firms in Port Harcourt. This study adopted a cross-sectional survey and correlation investigation to establish relationship between sales force training and employee performance of of insurance firms in a non-contrived setting. Both primary and secondary methods of data collection were used to obtain relevant data for analysis. The instrument of data collection employed was the questionnaire. The population of the study consists of fourteen (14) registered insurance firms in Port Harcourt as obtained from Port Harcourt Chamber of Commerce, Industry, Mines and Agriculture (PHCCIMA). The sample size of this study consists of one hundred and seventy-seven (177) workers as determined by Taro Yamane formula at 5% significant level. The data was analyzed using the Spearman Rank Order Correlation Coefficient statistic through the aid of statistical packages for social science version 23.0. The result of the findings revealed the existence of significant and positive relationship between sales force training and employee performance of of insurance firms in Port Harcourt. The researchers conclude that sales force training affect employee performance of of insurance firms in Port Harcourt and therefore recommended that management of insurance firms in Port Harcourt should intensify their efforts in sales force training in order to improve the skills of their sales force and overall performance.

Technological Change and Organizational Performance of Commercial Banks in Yenagoa, Bayelsa State

The aim of this study was to examine the relationship between technological change and organizational performance of commercial banks in Bayelsa State. The research adopted survey design method which comprises of 100 respondents drawn from 15 commercial banks in Bayelsa State sampled with questionnaire. The study used Spearman Rank-Order Correlation Coefficient (rs) to analyze the data and test the hypotheses. The study found out that technological adoption has a significant and weak positive relationship with operational performance and financial performance in commercial banks in Bayelsa State. The study concludes that technological adoption contributes significantly to the modeled outcomes of operational performance and financial performance. The study recommended that the commercial banks should be ready to adapt to new technology and modern ways of production that can help facilitate improvement in sales and to maximize profit.

Right heart echocardiography findings in hypoxic pneumonia patients during the COVID-19 pandemic in a South African population.

The right ventricle is affected by Coronavirus disease 19 (COVID-19) via multiple mechanisms, which can result in right ventricular dysfunction (RVD). This study aimed to provide an assessment of right heart function using conventional echocardiography and advanced strain imaging, in patients with hypoxic pneumonia during the COVID-19 pandemic. This study was an observational, prospective, single-centre study, including adults with hypoxic pneumonia, in two groups: COVID-19 pneumonia; and non-COVID-19 pneumonia. Bedside echocardiography was performed according to a pre-specified protocol and all right heart measurements were done as per standard guidelines. Right ventricular free wall strain (RVFWS) was measured using Philips® QLAB 11.0 speckle tracking software. Descriptive and comparative statistics were used to analyse data. Spearman Rank Order Correlations were used to determine the correlation between right ventricular (RV) parameters and clinical parameters. Univariate and multivariate logistic regression analyses were performed to characterize the predictors of in-hospital mortality. We enrolled 48 patients with COVID-19 pneumonia and 24 with non-COVID-19 pneumonia. COVID-19 patients were significantly older with a higher frequency of hypertension and diabetes and a trend towards a lower severity of illness score. Mean RVFWS yielded the highest estimates for the prevalence of RVD (81%), with no difference between the two pneumonia groups. Median Tricuspid Annular Plane Systolic Excursion (TAPSE) and right ventricular systolic excursion velocity (RVS') were not significantly different between COVID-19 (TAPSE 17.2 and RVS' 12), and non-COVID-19 pneumonia (TAPSE 17.8 and RVS' 12.1) with P values of 0.29 and 0.86, respectively. Non-COVID-19 pneumonia patients with moderate to severe hypoxaemia (PF < 150) were at greater risk of an elevated RV Systolic Pressure >30 mmHg respiratory rate = 3.25 (CI 1.35-7.82) on admission. Troponin levels discriminated between COVID-19 survivors (6 ng/L) and non-survivors (13 ng/L), P = 0.04. The mortality rate for COVID-19 was high (27%) compared to non-COVID-19 pneumonia (12%). Patients with COVID-19 pneumonia had a similar admission prevalence of RVD when compared to patients with non-COVID-19 pneumonia. Despite preserved traditional parameters of RV systolic function, RVFWS was diminished in both groups, and we propose that RVFWS serves as an important marker of the subclinical disease of RV.

Global, regional, and national incidence, mortality, and disability-adjusted life years of non-rheumatic valvular heart disease and trend analysis from 1990 to 2019: Results from the Global Burden of Disease study 2019.

In the context of the population growing and aging worldwide, the incidence of non-rheumatic valvular heart disease increased rapidly. This study aimed to describe the burden of non-rheumatic valvular heart disease, providing an up-to-date and comprehensive analysis on the global and regional levels and time trends from 1900 to 2019. The Global Burden of Disease 2019 was used to obtain data for this analysis. Non-rheumatic valvular heart disease in the Global Burden of Disease study includes both non-rheumatic calcific aortic valve disease and non-rheumatic degenerative mitral valve disease. The incidence, mortality, and disability-adjusted life year in 204 countries from 1990 to 2019 were analyzed by location, year, sex, age, and socio-demographic index. Estimated annual percentage change was calculated to represent the temporal trends from 1990 to 2019. Spearman's rank order correlation was used to determine the correlation between socio-demographic index and the incidence and burden of non-rheumatic valvular heart disease. Globally, there were 1.65 million (95% uncertainty interval, 1.56-1.76 million) incident cases, 0.16 million (95% uncertainty interval, 0.14-0.18 million) death cases, and 2.79 million (95% uncertainty interval, 2.52-3.31 million) disability-adjusted life years of non-rheumatic valvular heart disease. Compared with 1990, the number of incident cases, death cases, and disability-adjusted life years in 2019 increased by 104.58%, 210.60%, and 167.62%, respectively, the age-standardized incidence rate (estimated annual percentage change, 0.39; 95% confidence interval, 0.29 to 0.49) increased due to population growth, and the age-standardized death rates (estimated annual percentage change, -0.32; 95% confidence interval, -0.39 to -0.25) and age-standardized disability-adjusted life year rate (estimated annual percentage change, -0.81; 95% confidence interval, -0.87 to -0.74) decreased during this period. Regarding the socio-demographic index, the highest age-standardized incidence, death, and disability-adjusted life year rates of non-rheumatic valvular heart disease were found in high-socio-demographic index countries in 2019. Meantime, the age-standardized incidence rate remained increased from 1990 to 2019, while significant decreases were found in the age-standardized death rate and age-standardized disability-adjusted life year rate. Females have higher age-standardized incidence rate, while higher age-standardized death rate and age-standardized disability-adjusted life year rate belong to males globally during the period of 1990-2019. Increasing trends were observed for both incidence, death, and disability-adjusted life year rates with age. High systolic blood pressure was the leading cause for non-rheumatic valvular heart disease across all ages. From 1990 to 2019, the age-standardized incidence rate of non-rheumatic valvular heart disease remained increased, while age-standardized death rate and age-standardized disability-adjusted life year rate decreased, resulting from the growing population worldwide and improving medical resources. The aged, who has high systolic blood pressure and diet high in sodium, should pay more attention to, especially in high-socio-demographic index regions. With the population aging, the number of patients who require heart valve replacement is estimated to increase significantly in the future. Effective measures are warranted to control and treat the incidence and burden of non-rheumatic valvular heart disease.

FLAME-VQA: A Fuzzy Logic-Based Model for High Frame Rate Video Quality Assessment

In the quest to optimize user experience, network, and service, providers continually seek to deliver high-quality content tailored to individual preferences. However, predicting user perception of quality remains a challenging task, given the subjective nature of human perception and the plethora of technical attributes that contribute to the overall viewing experience. Thus, we introduce a Fuzzy Logic-bAsed ModEl for Video Quality Assessment (FLAME-VQA), leveraging the LIVE-YT-HFR database containing 480 video sequences and subjective ratings of their quality from 85 test subjects. The proposed model addresses the challenges of assessing user perception by capturing the intricacies of individual preferences and video attributes using fuzzy logic. It operates with four input parameters: video frame rate, compression rate, and spatio-temporal information. The Spearman Rank–Order Correlation Coefficient (SROCC) and Pearson Correlation Coefficient (PCC) show a high correlation between the output and the ground truth. For the training, test, and complete dataset, SROCC equals 0.8977, 0.8455, and 0.8961, respectively, while PCC equals 0.9096, 0.8632, and 0.9086, respectively. The model outperforms comparative models tested on the same dataset.

A quantitative study of confidence among paramedics in assessment of the cardiovascular system.

Patients presenting to the ambulance services with cardiovascular complaints are common, and as such, represent a notable proportion of paramedic clinical practice. Numerous texts refer to a system-based approach to cardiovascular assessment, however the application by paramedics is scarcely researched. As such, this article aims to quantify paramedic confidence levels regarding an examination of a patient with a cardiovascular complaint. An online cross-sectional survey was conducted, recruiting paramedics from one ambulance trust within the United Kingdom and analysing their confidence levels of assessing a patient with a cardiovascular complaint. Paramedics were recruited using purposive sampling and asked to complete an online questionnaire exploring their confidence levels among cardiovascular assessments, which were subsequently quantified to summarise confidence levels expressed by these respondents. A total of 331 responses across one ambulance service were received in April 2021. Of these, 90.3% (299/331) reported a high level of confidence with the general cardiovascular assessment. Throughout all individual elements of assessment, over 50% of respondents indicated they feel confident with the examination, except when assessing heaves and thrills where 56.2% (185/329) and 55.1% (182/330) of respondents disagreed with feeling confident, respectively. A strong correlation was seen throughout the results between confidence levels and the reported occurrence of each type of assessment, which was demonstrated using Spearman's rank-order correlation. High confidence levels for a cardiovascular examination were reported among the respondents of this survey. Paramedics have shown good confidence among all areas of a cardiovascular assessment, except with palpating the chest for heaves and thrills. There is an evident link between reported confidence levels and how often these assessments are completed, however there is still room for additional training and research within this area.

The aftermath of war; mental health, substance use and their correlates with social support and resilience among adolescents in a post-conflict region of Sri Lanka

BackgroundArmed conflicts impact on the health and well-being of everyone, but its effect on adolescent mental health is a significant, yet under-explored area in global health. Mental health disorders which develop during adolescence often lead to behavioural problems, risky decision-making, under-age substance use and can adversely impact on educational attainment. This study aimed to estimate the prevalence of common mental disorders, substance use and their correlates with social support and resilience among adolescents (age 12–19 years) in Vavuniya; a post-conflict region of Sri Lanka.MethodsA population-based cross-sectional study was conducted, with a modified cluster sampling method used for participant selection. Eight culturally adapted instruments were used for data collection. A total of 585 adolescents participated in the study. Analyses were performed using SPSS Version 23 statistical software package. All statistical tests were two-sided (p < 0.05) and p-values less than 0.05 were considered significant. Chi-square tests were used to explore associations between variables of interest. Spearman rank order correlation was used to examine correlations among depression, hopelessness, quality of life, social support, and resilience.ResultsThe mean age of participants was 15.02 (± 2.13) years. Ninety-one (15.6%) participants reported being exposed to one or more war-related events, and 85 (93.4%) participants in this group reported being internally displaced due to war. Fifty-two (8.9%) had dropped out of school and the prevalence of depression (3.9%) and substance use (7%) were low. Correlational analyses revealed that depression and hopelessness were significantly negatively correlated with social support, resilience, and quality of life (p < 0.01). Linear regression analysis suggested that 40% of the variance in resilience of the participants can be explained by perceived social support.ConclusionThe low prevalence of hopelessness and depression highlights the resilience of this group in the face of adversity. Furthermore, significant negative correlations between hopelessness and depression with perceived social support and resilience suggest that social support and resilience could be protective factors against mental health issues in these adolescents. However, the prevalence of school dropouts calls for a focus on academic attainment to promote better educational outcomes in the adolescents of this conflict-affected region.

Customer Care Considerations and Business Performance of Small and Medium Scale Enterprises in Rivers State

This study examined the relationship between customer care considerations and business performance of small and medium scale enterprises in Rivers State. The study adopted the descriptive survey research design where data were collected from managers and marketers of ten (10) small and medium scale enterprises in the manufacturing sector. A sample of 233 respondents was used for the study. The sample size was determined using the Taro Yamane’s formula. A structured questionnaire was used to elicit data from the respondents. The data collected were analyzed using percentage and frequency analysis, mean and standard deviation, while the hypotheses were tested using Spearman Rank Order Correlation Coefficient (rho). The SPSS 22.0 version was used to correlate the data on the study variables. The findings revealed that there is significant relationship between customer enquiry consideration and customer satisfaction. The study also found a significant relationship between customer enquiry consideration and customer patronage of SMEs. A significant relationship was found between customer enquiry consideration and customer retention by SMEs. The study also reported a significant relationship between customer support consideration and customer satisfaction. The study equally discovered a significant relationship between customer support consideration and customer patronage of SMEs. A significant relationship was found between customer support consideration and customer retention by SMEs. The study also found a significant relationship between customer complaint consideration and customer satisfaction. A significant relationship was found between customer complaint consideration and customer patronage of SMEs. The study also reported a significant relationship between customer complaint consideration and customer retention by SMEs. Finally it was revealed that organizational size significantly moderates the relationship between customer care consideration

Literasi Media Dalam Menanggulangi Berita Hoax Di Media Sosial Mahasiswa Ilmu Perpustakaan

This study aims to determine the ability of Library Science students to analyze hoax news on social media, the ability of Library Science students to access hoax news on social media, the relationship between the media literacy skills of Library Science students in tackling hoax news on social media, and the ability of Library Science students to evaluate news. hoaxes on social media. This study uses quantitative research using a questionnaire as a means of collecting data obtained from respondents. The population of this study were all Library Science students of UIN North Sumatra from the 2019 stambuk, 2020 and 2021, namely 352 students with a total sample of 79 students determined by the slovin formula. The sampling technique used to determine the sample is Random Sampling/Probability Sampling. To measure the relationship between the media literacy abilities of Library Science students at UIN North Sumatra in tackling hoax news on social media and test hypotheses using the Spearman's Rho Rank-Order Correlations formula and Guilford's calculations. The results showed that media literacy ability had a positive relationship with a value of 0.358 which indicated a strong enough relationship in tackling hoax news.

Employee Evaluation and Organizational Efficiency in the Bayelsa State Ministry of Education

The paper examined the relationship between employee evaluation and organizational efficiency in Ministry of Education, Bayelsa State. Descriptive Survey Design was adopted Amongst300employees of Ministry of Education.291 workers were randomly sampled. A closed- ended questionnaire was used as primary data collection tool and was analyzed via inferential statistics; Spearman Rank Order Correlation Coefficient with the aid of SPSS. The study adopted feedback and reward as the dimensions of employee evaluation. However, the study revealed that feedback and reward are statistically significant with quality service. It was recommended that the Ministry should put in place staff evaluation practices that is void of sentiment and favouritism but be fair, open and strategic.

Prediction of transportation energy demand in Türkiye using stacking ensemble models: Methodology and comparative analysis

The transportation sector accounts for 61.5% of global oil consumption and is responsible for 29% of the world’s total energy demand. Passenger transportation utilizes around 50%–60% of the energy used for transportation-related activities. Accurate prediction of future transportation energy consumption is essential for governments to make well-informed decisions regarding transportation infrastructure development and utilization, which supports the United Nations’ Sustainable Development Goals (SDGs) and advances the shift to a net-zero carbon economy. With the expected increase in population, vehicles, and economic growth, it is essential to predict the energy demand to ensure sustainable urban transportation. This is crucial not only for economic prosperity but also for promoting human health and mitigating carbon emissions. Therefore, transportation energy demand prediction plays a vital role in designing sustainable future urban transportation and making informed energy investment and policy decisions. This study proposes a novel methodology and investigates for the application of machine learning stacking ensemble method with hyperparameter tuning and multicollinearity removal to predict transportation energy demand in Turkey based on historic data from 1975–2019. The dataset includes GDP, year, vehicle miles traveled, population, oil price, passenger miles traveled, and ton-miles traveled as features. A performance evaluation and comparison of 19 machine learning algorithms is first carried out to find the best candidate for the stacking ensemble models, including eXtreme Gradient Boosting algorithm. This performance comparison uses all features and also only two of them during the training phase, and it takes into consideration a 4-fold cross-validation. A combination of permutation importance and hierarchical clustering algorithm on the Spearman rank-order correlations is used for dimensionality reduction of the dataset. Extra Tree Regressor and ADABoost Regressor, which are both placed in the second level of the suggested models, are two meta-regressors that are proposed for stacking ensembles because they perform better compared to single machine learning algorithm. In total, eight stacking ensemble models – four for each of the meta-regressors – were developed and investigated considering all features and only two of them separately. Six metrics – R-squared, MSE, MAE, RMSE, RMSLE, and MAPE – are used to assess all models. The Extra Trees Regressor can be used as a meta-regressor in the best proposed stacking ensemble model to predict the energy demand for transportation. This model achieves an R-squared value of approximately 0.99 when all the features are taken into consideration. When only two features from the dataset are considered the same stacking ensemble model can achieve an accuracy of 0.98. These findings have the potential to contribute to the development of more accurate models and results, which can, in turn, lead to improved strategies for managing future transportation energy demand. Additionally, this research can support the advancement of alternative technologies that promote sustainable urban development, ultimately helping to move towards a net-zero carbon economy.