Statistical Tools Research Articles

Pattern of E. histolytica infection and its correlates among patients in a general practice clinic: A four-year retrospective evaluation

Background: Overcrowding, poor hygiene and scarcity of portable water are common features of population growth in a resource poor nation especially with rising cost of living from inflation. This is the often the state of many underdeveloped nations such as Nigeria. Such environments encourage the spread of communicable diseases. This study assess the pattern, trend, and at-risk population of Entamoeba histolytica (E. histolytica), implicated in intestinal Amoebiasis in South-South Nigeria. Method: This retrospective study was conducted using hospital data obtained from the laboratory department of a general hospital clinic in Warri and covered a period of four years from January 2015 - December 2018. The record of 4,169 laboratory results of stool samples examined by direct smear and concentration technique, were recovered from a designed computer database. Trend of infection over the period as well as variations in distribution patterns between sex, age and seasons were determined using appropriate statistical tools. Results: Out of the 4,169 stool samples 365 (8.8%) had E. histolytica with decreasing trend of infection from 2015 – 2018 as 135 of 1210 (11%); 118 of 1114 (10.6%); 57 of 792 (7.2%); 55 of 1053 (5.2%) respectively. Prevalence of infections was higher in females, 57.5% (95CI%, 51.7-59.7, n= 210) than males (n=155, 42.5%, 95%CI, 40.3-48.6). The prevalence of infections was highest among Age brackets 1-5years, 6-15 years and 35+ years; but lowest in the 26-35 years with peak season of infections at first and last quarters of each year. Conclusions: Children are more vulnerable to E. histolytica infestation and the dry seasons of the year place them at risk. This information underscores the need for local surveillance to evaluate the effectiveness of control and preventive health measures with a view of reducing the prevalence and morbidity of parasitic infections in our locality.

Is the Existing Hydropower Development Policy, 2001 Investment Friendly?

Nepal is endowed with an abundance of hydro resources. Its gross hydropower potential is estimated to be 83,290 MW technically. Out of which, 42,133 MW is ascertained as economically exploitable. However, in the span of 112 years, only around 2,900 MW is harnessed. It is obvious that the development of hydropower is a public policy-related matter. Previous studies exhibit several complications in hydropower development policy, 2001 such as private sector participation in electricity trade, lack of one window system, term of project, hedging mechanisms, foreign direct investment, and so forth. In this regard, this study aims to investigate its efficiency and effectiveness through quantitative research design. Herein, for the sake of empirical research three independent variables namely, Financial Incentives Sufficiency (FIS), Return on Investment Sufficiency (RoIS), and Market Access Sufficiency (MAS), and one dependent variable namely, Investment Friendliness (IF) was dealt. To collect the opinion of respondents a set of questionnaires comprising 11 questions was developed and approached to 108 informants from 25 diverse sectors of the hydro-industry. Herein, deductive reasoning was persuaded. For analyzing data, statistical tools such as arithmetic mean, standard deviation, factor analysis, Chi-Square tests, Mann Whitney "U" test, and Kruskal-Wallis "H" test were computed. Based on empirical analysis this study concludes that the hydropower development policy, of 2001 is investment-friendly. However, the study manifested a number of rooms that were to be addressed as changing the expectations of investors. On this ground, the findings of this study will be applicable with a view to formulating a more investment-friendly hydropower policy in the future.

Quantitative Research Design and Sample Trends: A Systematic Examination of Emerging Paradigms and Best Practices

Research design and sampling are pivotal in scientific research, shaping methodology and ensuring the credibility and validity of findings, necessitating clear and focused attention from researchers. Based on the above statement the study was focused on underlining the research design's basic terms and sample in order for researchers to be reliable in their research. The study used PRISMA to select the sample of documents. 30 major studies were used to explain the research objectives. The study covers only four types of research design i.e. Descriptive, Developmental, Experimental, and Casual Comparative. Results highlight the four research designs that aim to answer, words to be concerned with during objective setting, statistical tools, data visualization, words to be selected during hypothesis setting based on tools, and the minimum number of samples required depending on various tools. The research concludes that the choice of effective research design terms is pivotal. In statistical analysis, hypothesis wording directs research, with terminology so depending on the tools appropriate words need to be selected. Researchers need to make sure that the minimum sample size is right. However, larger samples improve the stability and accuracy of results. This study contributes by explaining essential research design terminology on sample selection, and their influence on statistical analysis, providing researchers with a clear guide to improve credibility and validity in their work.

Effect of the anode material, applied current and reactor configuration on the atenolol toxicity during an electrooxidation process

Atenolol (ATL) is a beta-blocker pharmaceutical product which is excreted mainly unchanged and may represent a long-term risk for organisms present in the sea and in fresh water. Due to its low biodegradation rate, electrochemical advanced oxidation processes (EAOPs) can be used to remove this compound. In this work, ATL ecotoxicity was analyzed in the presence of sodium sulfate (Na2SO4), which is widely used as supporting electrolyte in EAOPs. Ecotoxicity values were expressed as the pollutant concentration that leads to a 50% inhibition of the root elongation of Lactuca sativa seeds in relation to the control (EC50(5 days)). The obtained values for ATL showed an EC50(5 days) of 1377 mg L−1 towards Lactuca sativa. When Na2SO4 was added, the toxicity of the sample increased but no synergy was detected between both compounds. With 2 g L−1 Na2SO4, ATL showed an EC50(5 days) of 972 mg L−1; and with 4 g L−1 Na2SO4 and higher concentrations, EC50 value for ATL was 0 mg L−1. Statistical tools were used to obtain the zones of the [ATL]-[Na2SO4] plane which are toxic towards Lactuca sativa.Solutions containing ATL and Na2SO4 were treated by electrooxidation. Two anode materials (a boron-doped diamond electrode and a microporous Sb-doped SnO2 ceramic one); three operation currents (0.4, 0.6 and 1 A); and two reactor configurations (one-compartment reactor and two-compartment reactor separated by a cation exchange membrane) were used. Lactuca sativa seeds and Vibrio fischeri bacterium tests were employed to evaluate the toxicity of the solutions before and after applying the electrooxidation process. In all the tests, the ecotoxicity of the treated sample increased. This fact is owing to the persulfate presence in the solution due to the sulfate electrochemical oxidation. Nevertheless, none of the final samples were toxic towards Vibrio fischeri because ecotoxicity values were lower than 10 TU; and, in the case of the one-compartment reactor, practically all of them were also non-toxic towards Lactuca sativa. The toxicity of the treated samples increased when using the two-compartment reactor in the presence of the BDD anode, and when the operation current was increased. This is attributed to the highest formation of persulfates. Amongst all the tests performed in this work, the lowest toxicity value (i.e., 3 TU) together with the complete mineralization and degradation degrees was achieved with the two-compartment reactor using the BDD anode and operating at 0.6 A.

The Influence of Materialism and Store Atmosphere on Compulsive Buying With The Mediating Variable of Fashion Interest (Study on Consumers of Kosshe Boutique Pontianak)

This research aims to examine the relationship between materialism and store atmosphere on compulsive buying where fashion interest is the mediating variable. The approach used in this research is quantitative research. This research is included in descriptive research with a survey method. The type of research used in this research is causal associative research. The population in this research is consumers of Kosshe Boutique Pontianak who have made purchases at least 2 times in the last 6 months and are female, with a sample of 200 respondents. Sampling in this research used a non-probability sampling method in the form of purposive sampling. The collected data was then analyzed using the Structural Equation Model with the SmartPLS statistical application tool version 3.9.3. The results of data analysis show that materialism has a significant effect on compulsive buying, store atmosphere has a significant effect on compulsive buying, materialism has a significant effect on fashion interest, store atmosphere has a significant effect on fashion interest and fashion interest is not significant on compulsive buying. The results of the mediation role test were not significant.
 Keywords : Materialism: Store Atmosphere; Fashion Interest; Compulsive Buying

DEMYSTIFYING LEADERSHIP: A HOLISTIC ANALYSIS OF ITS ROLE, INCLUDING DEMOGRAPHIC FACTORS IN E-COMMERCE IN SMES IN AD DAKHILIYAH GOVERNORATE, OMAN

This quantitative study with a sample of 375 participants from small and medium enterprises (SME) in the Ad Dakhiliyah region of Oman examines the impact of transformational and transactional leadership styles on E-commerce adoption (ECA). A multi-group (MGA) analysis was conducted to investigate the influence of demographic factors on ECA through leadership styles. Using statistical analyses via SPSS and SmartPLS 4, the study shows significant gender differences in the influence of leadership styles on ECA. In addition, comparisons were made with two other demographic factors — age and leadership position. However, caution should be exercised when generalising beyond the study's focus on the Ad Dakhiliyah region. Despite a comprehensive investigation, the age factor shows an insignificant difference in the impact of transformational and transactional leadership on ECA. This study makes an important contribution to the understanding of leadership dynamics in the digital age in Omani SMEs, highlighting the gender nuances. The integration of robust research models and statistical tools enhances methodological rigour and provides practitioners and future researchers with nuanced perspectives on leadership and technology adoption in the Ad Dakhiliyah region and in the broader context of Omani SMEs.
 Keywords: Leadership Style, E-commerce Adoption, Technology Adoption, Gender, SME, Oman, SmartPLS.

Efficient and sustainable tandem annulation-decarboxylation reaction using ecocatalysis

Substituted cyclohexenones are well-known building blocks for the synthesis of numerous natural products and bioactive compounds. Despite their widespread use, they are prepared under conditions that are not compatible with the principles of green chemistry. Here the synthesis of substituted cyclohexenones was revisited using a tandem annulation-decarboxylation strategy, in an eco-friendly process without compromising on efficiency. To meet this challenge, environmental catalysts, named ecocatalysts®, which derived from biomass wastes were used. Under microwave activation, ecocatalysis assisted by statistical tools led to excellent yields, as well as remarkable green metrics for the whole synthetic process, which both exceeded those previously reported. The reaction was scaled-up allowing the recycling assessment of the best ecocatalysts®. The reaction was also extended to other substrates. The catalytically active species within the best ecocatalyst® was identified through extensive characterisation by MP-AES, XRPD, SEM, XPS and solid-state NMR, allowing to depict a mechanism confirmed by DFT calculations.

Combined green analytical principles and quality by design for ultraperformance liquid chromatography analytical method development, the characterization and in-silico toxicity prediction of Ixazomib degradation products using mass spectrometry

Ixazomib citrate (IC) is the first oral selective proteosome inhibitor for treating multiple myeloma. IC is prone to degradation due to its oxidative deboronation and the amide bond, affecting patient health, drug quality, and efficacy. The stability of IC is crucial during drug development as it guides the inherent stability of the molecule, its degradation pathways, packing materials, and formulation development. Following the International Conference on Harmonization (ICH) Q1A (R2) and Q1B, a stability study were performed for both solution and solid-state stress studies. Under oxidative and alkaline conditions, 3 degradation products (DPs) were identified, separated, and method-validated according to ICH Q2 (R1) guidelines. From the Design Expert statistical tool, the Central Composite Design was used to optimize the final analytical method conditions, where the p-values for the model are < 0.05%. Green analytical chemistry has significantly reduced the use of hazardous organic solvents without losing chromatographic performance. The green separation and quantification of DPs and IC on Ultra Performance Liquid Chromatography (UPLC) using an Inert-Sustain C8 (50×3.0) mm 2.0 µm column with gradient elution using 10 mM ammonium acetate buffer (pH 5.0) and ethanol at a flow rate of 0.5 mL/min and detection at 230 nm. The results of green assessment tools like GAPI, AGREE, and Analytical eco-scale found that the method is excellent for the greenness of utilizing ethanol as a solvent, shorter runtime, and lesser waste. The method was validated as per ICH Q2 guidelines, and the results found it is sensitive, precise, accurate, robust, and linear for its intended use. The method is suitable for quantifying IC and its DPs from 2.0 to 150 µg/mL with R2 values of 0.9996 with a detection limit of 1.0 µg/mL. The plausible degradation structures and pathways of DPs were outlined using tandem mass spectra employed on LC-QTOF-MS/MS in both ESI positive and negative modes. The mechanistic explanation for establishing DPs was explained in detail. The ADMET Predictor™ software predicted the physicochemical and ADMET properties. The toxicity profile reveals that DP2 and DP3 are teratogenic, while D1 and D3 show phospholipidosis.

Effects of banditry security risk on livelihood of cattle herders in Katsina State, Nigeria

Livestock enterprise is an important source of livelihood to many people in Nigeria. Vulnerability of livestock business to insecurity risk is a major threat to the livelihood of stakeholders in the livestock value chain (cattle herders and marketers). Insecurity risk among livestock herders has a ripple effect in the economy of Nigeria. Empirical information is scanty for the clarification and development in security risk control model especially with the emergence of banditry in Nigeria. This study broadly examines the effect of insecurity risk on the livelihood of livestock herders in Katsina State, Nigeria. Primary data obtained with the use of structured questionnaire from randomly selected 200 respondents were analyzed by descriptive and inferential statistical tools (mean, frequency distribution table, probability and multiple regression). The result shows that the probability of banditry attack was 20%. The major benefit derivable from livestock business by herders is income generation. The major cause of banditry insecurity was unresolved conflict between farmers and herdsmen (100%), unemployment/deliberate negative tendency of bandits to climb wealth ladder (93.5%) and corruption among government officials (93%). Test of hypothesis indicates that all the insecurity indicators (cattle rustling, theft, kidnapping and tax imposition) negatively and significantly (P &lt; 0.05) affected livelihood capital (asset) (income savings and herd size). There are sufficient evidence to conclude that livelihood capital of cattle herders is worst hit by banditry insecurity risk in Katsina State, Nigeria. It was recommended that government should adopt amnesty policy of disarmament, reintegration and rehabilitation of repentant bandits. This study has expanded the frontier of literature of the ripple effects of banditry insecurity on cattle value chain and implications for policy options.

Estimating phenotypic stability for relevant yield and quality traits in French bean (Phaseolus vulgaris L.) using AMMI analysis

The presence of strong G x E (genotype by environment interaction) is a major hurdle for selecting superior genotypes when genotypes are placed into new and unfamiliar production systems. Genotype or cultivar (s) with high yield potential and having less adaptability and stability to particular environment is never a suitable choice for a breeder and farmer particularly. Purposefully, four successive seasons were chosen to enumerate the phenotypic stability of 27 French bean genotypes for yield and quality traits by involving modern statistical tools like AMMI (Additive Main Effect and Multiplicative Interaction), GGE [G + (G x E)] and cluster analysis. AMMI analysis of variance witnessed magnitude of G, E and G x E was 81.94%, 11.58% and 6.48% of the total variation respectively. The IPCA I (Interaction Principal Component Axes) was contributed with 55.44%, 73.60%, 71.81%, 81.69% and 72.16% G x E variations of days to 50% flowering, pod length, number of pods per plant, average pod weight and pod yield respectively. For qualitative traits i.e., protein content (mg/100g FW), total soluble solids (%) and total phenol content (mg GAE/g FW) the involvement of IPCA I to total genotype by environment interaction variations were 89.55%, 96.07% and 66.52% respectively. The AMMI biplot revealed French bean genotypes viz., IC632961, Arka Sukomal, IIHR-PV-29, IIHR-PV-30 having low AMMI stability value and higher mean value for relevant yield and quality traits in both late kharif and rabi as two mega-environments. Multivariate analysis demonstrated significant higher contribution of pod yield associated traits towards total variations and positive correlation between them. The 27 French bean genotypes formed five groups as per Euclidean distance and the clustering revealed the nature of diversity of French bean genotypes viz., IC 632961, IIHR-B-PV-24, Arka Sukomal, Arka Arjun, Ayoka and Phalguni in response to changing environments and can be utilized in future breeding programme. The study revealed pole type French bean genotypes viz., IC 632961, Arka Sukomal and bush type French bean genotypes viz., IIHR-B-PV-29, IIHR-B-PV-30 could be promising for utilization in future breeding programmes for the concerned traits.

The Business Environment in Slovakia from the Point of View of the Death of Enterprises

Creating favorable conditions in the business sphere is one of the main priorities of the European Union, while each member country implements the objectives of the EU strategy in its national strategic documents. The goal of this paper is modeling respectively quantifying the effect of the death of business entities in Slovakia in 2019 and 2020 from selected factors using logistic regression. We decided to find out which of the selected factors (legal form of the enterprise; size group according to the average registered number of employees; region; economic activity performed by the enterprise) most influenced the death of enterprises in the period before and during the pandemic, which will allow us to determine the most and the least threatened categories of enterprises. The analysis was based on the business demography database, while the processing itself was carried out using the statistical tool SAS Enterprise Guide 7.1. The results of the analysis during the COVID-19 pandemic showed a significant impact of the factor legal form of the enterprise - mainly in the group of enterprises owned by natural persons, then a statistically significant impact of the factor size group of enterprise with an average registered number of employees 0-1 and finally a significant impact of the factor economic activity of the enterprise, mainly in the field of services. The smallest but statistically significant effect was manifested in the region factor, while the region in the east of Slovakia can be considered the most threatened from the point of view of the demise of enterprises. An interesting fact is that the influence of individual categories of factors on the closure of a enterprises in the case of micro-enterprises with one employee is very similar to the situation throughout Slovakia.

Effects of employee engagement on organizational performance: case of public universities in Ethiopia

The objective of this research is to examine the impact of Employee Engagement on Organizational Performance within Public Universities in Ethiopia. It aims to explore the relationship between employee engagement and the overall performance of these institutions, specifically focusing on public universities. By providing significant insights and recommendations, this research will contribute towards the development of strategies that can enhance employee engagement and improve the overall performance of Ethiopian public universities. The study utilized both quantitative and qualitative approaches, employing descriptive and explanatory research designs. To gather data, three Ethiopian universities were selected based on their establishment date, and a random selection technique was used to include 365 personnel in the sample. Descriptive statistical tools like mean and standard deviation were employed, while structural equation models were utilized for confirmatory factor analysis and path analysis. The study's findings indicate that vigor, dedication, and absorption all have a significant and favorable impact on organizational performance in higher education. The study findings also indicate that the performance of study institutions differs based on the extent of employee involvement. This research introduces a fresh perspective of the relationship between employee engagement and organizational performance by concentrating specifically on the context of public universities in Ethiopia. This sheds light on the distinctive dynamics and obstacles encountered by these institutions. Furthermore, the study adds to the current body of knowledge by exploring the relationship between employee engagement and organizational performance, offering valuable insights and suggestions to enhance performance in the setting of Ethiopian public universities.

Evaluating the Adoption of Cleaner Production Technology for Sustainable Green Hotels in the Philippines

With the increasing trend of waste production in the hotel industry, a turn to green waste management would greatly alleviate costs and carbon footprint. Although policies are being updated to accommodate the transition to eco-friendlier management, there is little literature about technologies used to reduce pollution. This study assessed the economic effectiveness and cost improvement of the hotel industry in Western Visayas using cleaner production technology practices. This study utilized a descriptive survey research approach. The 156 participants, which consisted of hotel owners, managers, and employees, were chosen using a stratified random sampling technique using G* power version 3.0. The statistical tools employed were frequency counts, percentages, rankings, averages, standard deviation, and one-way ANOVA. Results revealed that the top five cleaner production technology practices implemented that suggest sustainability were: “modify facilities/equipment”, “adequate proper control operations”, “improves facilities/equipment layout”, “provides training and incentive programs”, and “improves wastes segregation and storage”. The study shows no significant differences observed in the scope of practices for stars 3-5. On the contrary, there is a significant difference seen in the scope of 2-star hotel practices. The use of cleaner production technology and green practices has also decreased the hotel's use of energy, water, and solid waste management. Importantly, the cost of consumption in each hotel unit decreased. The findings of this study will enable hotels to adopt efficient waste sorting techniques, paving the way for a greener transition in the hospitality industry. By doing so, future research, projects, and policy implementations may be directed to a better tomorrow.

Environmentally friendly voltammetric determination of melatonin in river water: Development and validation studies

AbstractMelatonin (MEL) is a hormone that can discharge into aquatic bodies and act as an endocrine disruptor; thus, its determination is important. In this study, a boron‐doped diamond electrode was used to develop an electroanalytical method based on square‐wave voltammetry to determine trace concentrations of MEL in river water. The electroanalytical method was developed and optimized in 0.1 mol L−1 sodium phosphate (pH=4.0) with parameters f=10 s−1, a=50 mV, and ΔES=2 mV. The validation study was carried out in the working range of 1.2–10.8 μmol L−1 using the parameters and statistical tools recommended by the validation guidelines of regulatory agencies. The matrix effect was significant; therefore, an analytical curve was directly constructed in the sample matrix by standard addition method. Results of linear regression indicated that the standard addition curve data presented a good adjust to linear model and have therefore a good linearity. Low limits of detection (0.29 μmol L−1) and quantification (0.86 μmol L−1) were observed. The estimates for precision (RSD (%)&lt;15 %) and accuracy (mean recovery&gt;99.5 %) were suitable according to the limits established in the literature; thus, the method was precise and accurate for the adopted working range. The study findings indicate that square‐wave voltammetry combined with a boron‐doped diamond electrode can be used for reliable and consistent determination of trace concentrations of MEL in river water. Furthermore, it presents interesting features such as lower environmental impact, speed, and low cost.

Application of the Non-Parametric Signals Test to a Company

Objective: The aim of this paper is to show the application of the Non-Parametric Sign Test in problems involving the testing of central tendency values. Theoretical framework: Non-parametric methods are widely used in the study of populations that are taken in rank order (such as a movie that receives one to four star ratings). The use of non-parametric methods may also be necessary when the data has a ranking but no clear numerical interpretation, such as when accessing preferences. In terms of scale, non-parametric methods result in data that is "in order" (Thatcher et al., 2005) Method: Data was taken from a company in the South of Rio de Janeiro and a case study was carried out using the Non-Parametric Sign Test. Final Considerations: Initially it proved unfeasible to use a Parametric Test because the Anderson-Darling Test showed that the Assumption of Normality was not confirmed and finally the Non-Parametric Sign Test showed that the hypothetical Median really is the correct measure of Central Tendency. Implications of the research: The use of Non-Parametric Tests is widespread in scientific literature and has proven to be highly effective in dealing with data where the assumptions of Normality are not confirmed. Originality/value: Despite being well-known statistical tools, Non-Parametric Tests are widely used and can bring innovations to their application, as in the case of the company in question.

Hourglass, a compass navigating global and regional heterogeneity of pancreatic cancer†.

Advances in the digital pathology field have facilitated the characterization of histology samples for both clinical and preclinical research. However, uncovering subtle correlations between bioimaging, clinical and molecular parameters requires extensive statistical analysis. As a user-friendly software, Hourglass, simplifies multiparametric dataset analysis through intuitive data visualization and statistical tools. Systemic analysis of interleukin-6 (IL-6)/pStat3 signaling pathway through Hourglass revealed differences in regional immune cell composition within tumors. Moreover, these regional disparities were partially mediated by sex. Overall, Hourglass simplifies information extraction from complex datasets, resolving overlooked regional and global spatial tumor differences. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Climate Change versus Economic Growth: Case of Greenhouse Apply a Study of European Union Countries and England from 2010 to 2019 Using Linear Regression and Neural Networks

Climate change, encompassing the greenhouse effect, is a scientifically acknowledged fact. Factors such as population increase and limited resources for economic growth warrant consideration. This paper aims to develop a new approach to explore the relationship between the greenhouse effect (including climate change) and economic growth and the social/welfare state and find if the government really focus on the reduction of the greenhouse or is marketing. The objective is to develop a study employing linear regression, neural networks, and other statistical tools to elucidate these relationships. The data comprise figures for the human development index (HDI), the greenhouse effect, the GDP, and environmental indicators. The method used will be a parametric workout about the variables that affect the greenhouse gas emissions, the relationship between it and the HDI, and finally, will apply a prediction of greenhouse effects incorporating a neural network. Since 2020, in European Union countries, and especially in new members, focus has been placed on the HDI rather than on the reduction in the greenhouse effect. On the other hand, neural networks allow advances that enable the European Union to focus on climate change, with large investments planned until 2030 because the reduction in greenhouse gases can be effectively lowered when the countries’ expenditures are focused on environmental protection, including enhancing biodiversity.

Awareness and Perception of Students Toward Execution of Internet of Things in Library Services: A study of Indian Institute Technologies of Northern India

Abstract This study aimed to investigate students’ awareness and perception toward the execution of Internet of Things (IoT) in library services of Indian Institute Technologies (IITs) of Northern India. This study consists of a quantitative research design in which a survey was conducted utilizing a stratified random sampling technique to survey 813 students from five IITs. A total of 780 correctly filled-out surveys were received, yielding a response rate of 95.94%. Statistical tools, including Microsoft Excel and the Statistical Package for the Social Sciences, were used to analyze the data. To assess the significance of the results at the 0.05% level, statistical analysis was carried out utilizing percentages and analysis of variance. This study will communicate the attitude, awareness, and perception of students regarding the implementation of IoT in libraries of IITs. It is conducted to understand the motive behind new technology acceptance in academic libraries. The findings reveal that most of the students got familiar with IoT from browsing on the Web/Internet, social networking sites, research projects, conferences, workshops, webinars and faculty development programs, professional discussions, and meetings, as part of the curriculum. Respondents were in favor of implementing IoT in library services. They believed that IoT will ensure better and more efficient utilization of library resources, followed by real-time information accessibility, recommend IoT-based library services, system content quality will be updated, and will increase the quality of the library; the efficiency of library services will increase with implementation of IoT. It will increase the productivity of library services, be useful in an emergency, and promote information literacy. The study’s findings would be beneficial to libraries and academic institutions interested in implementing IoT applications in their libraries.

Convolution smoothing and non-convex regularization for support vector machine in high dimensions

The support vector machine (SVM) is a well-known statistical learning tool for binary classification. One serious drawback of SVM is that it can be adversely affected by redundant variables, and research has shown that variable selection is crucial and necessary for achieving good classification accuracy. Hence some SVM variable selection studies have been devoted, and they have an unified “empirical hinge loss plus sparse penalty” formulation. However, a noteworthy issue is the computational complexity of existing methods is high especially for large-scale problems, due to the non-smoothness of the hinge loss. To solve this issue, we first propose a convolution smoothing approach, which turns the non-smooth hinge loss into a smooth surrogate one, and they are asymptotically equivalent. Moreover, we construct computationally more efficient SVM variable selection procedure by implementing non-convex penalized convolution smooth hinge loss. In theory, we prove that the resulting variable selection possesses the oracle property when the number of predictors is diverging. Numerical experiments also confirm the good performance of the new method.

Numerical analysis of thermophoretic particle deposition on 3D Casson nanofluid: Artificial neural networks-based Levenberg–Marquardt algorithm

Abstract The aim of this research is to provide a new computer-assisted approach for predicting thermophoresis particle decomposition on three-dimensional Casson nanofluid flow that passed over a stretched surface (thermophoresis particle decomposition on three-dimensional Casson nanofluid flow; TPD-CNF). In order to understand the flow behavior of nanofluid flow model, an optimized Levenberg–Marquardt learning algorithm with backpropagation neural network (LMLA-BPNN) has been designed. The mathematical model of TPD-CNF framed with appropriate assumptions and turned into ordinary differential equations via suitable similarity transformations are used. The bvp4c approach is used to collect the data for the LMLA-BPNN, which is used for parameters related with the TPD-CNF model controlling the velocity, temperature, and nanofluid concentration profiles. The proposed algorithm LMLA-BPNN is used to evaluate the obtained TDP-CNF model performance in various instances, and a correlation of the findings with a reference dataset is performed to check the validity and efficacy of the proposed algorithm for the analysis of nanofluids flow composed of sodium alginate nanoparticles dispersed in base fluid water. Statistical tools such as Mean square error, State transition dynamics, regression analysis, and error dynamic histogram investigations all successfully validate the suggested LMLA-BPNN for solving the TPD-CNF model. LMLA-BPNN networks have been used to numerically study the impact of different parameters of interest, such as Casson parameter, power-law index, thermophoretic parameter, and Schmidt number on flow profiles (axial and transverse), and energy and nanofluid concentration profiles. The range, i.e., 10−4–10−5 of absolute error of the reference and target data demonstrates the optimal accuracy performance of LMLA-BPNN networks.