bluuebunny/crossref_metadata_2025 huggingface dataset:
Knowledge sharing and self-efficacy role in growing managers’ innovation: Does job satisfaction matter?
Authors: AlQudah Nidal Fawwaz , Mathani Belal , Aldiabat Khaled , Alshakary Kadri , Alqudah Hamza M.
Published: March 2022

BACKGROUND: Innovation is important for companies in order to function and evolve within the competitiveness and uncertainty of economies based on knowledge. Meanwhile, the sources of knowledge and Managers’ self-efficacy are basic building blocks promoting the innovation of managers in organizations, which cannot be neglected especially under different level of Managers’ job satisfaction. OBJECTIVE: This study aims at analysing the influence of both self-efficacy and knowledge sharing on managers’ innovation moderated by job satisfaction. METHODS: The study was conducted at Jordanian public sector, involving 112 managerial managers (respondents) of public institutions and the collected data were proceed using Partial Least Square (PLS) analysis. RESULTS: The finding shows that self-efficacy and knowledge sharing have a positive direct influence on managers’ innovation. Meanwhile, job satisfaction was able to moderate the influence of self-efficacy on the managers’ innovation, but not the relationship between the knowledge sharing and managers’ innovation. IMPLICATIONS: These research findings provide empirical evidence of the role of self-efficacy and knowledge sharing in enhancing managers’ innovation, as well as, the result confirms on the interaction influence of job satisfaction on the relationship between self-efficacy and managers’ innovation in the Jordanian public sector as one of the developing countries. Finally, considering the importance of the public sector within the economy of Jordanian, the findings are valuable for decision-makers and regulators in suggesting new regulations and legislation to better manage the public sector.
Investigating Casual Associations Among Gut Microbiota, Metabolites, and Neurodegenerative Diseases: A Mendelian Randomization Study
Authors: Ning Jing , Huang Shu-Yi , Chen Shi-Dong , Zhang Ya-Ru , Huang Yu-Yuan , Yu Jin-Tai
Published: March 2022

Background: Recent studies had explored that gut microbiota was associated with neurodegenerative diseases (including Alzheimer’s disease (AD), Parkinson’s disease (PD), and amyotrophic lateral sclerosis (ALS)) through the gut-brain axis, among which metabolic pathways played an important role. However, the underlying causality remained unclear. Objective: Our study aimed to evaluate potential causal relationships between gut microbiota, metabolites, and neurodegenerative diseases through Mendelian randomization (MR) approach. Methods: We selected genetic variants associated with gut microbiota traits (N = 18,340) and gut microbiota-derived metabolites (N = 7,824) from genome-wide association studies. Summary statistics of neurodegenerative diseases were obtained from IGAP (AD, 17,008 cases; 37,154 controls), IPDGC (PD, 37,688 cases; 141,779 controls), and IALSC (ALS, 20,806 cases; 59,804 controls) respectively. Results: Greater abundance of Ruminococcus (OR, 1.245; 95% CI, 1.103–1.405; p = 0.0004) was found significantly related to higher risk of ALS. Besides, our study found suggestive associations of Actinobacteria, Lactobacillaceae, Faecalibacterium, Ruminiclostridium, and Lachnoclostridium with AD, of Lentisphaerae, Lentisphaeria, Oxalobacteraceae, Victivallales, Bacillales, Eubacteriumhalliigroup, Anaerostipes, and Clostridiumsensustricto1 with PD, and of Lachnospira, Fusicatenibacter, Catenibacterium, and Ruminococcusgnavusgroup with ALS. Our study also revealed suggestive associations between 12 gut microbiome-dependent metabolites and neurodegenerative diseases. Glutamine was related to lower risk of AD. For the serotonin pathway, serotonin was found as a protective factor of PD, while kynurenine as a risk factor for ALS. Conclusion: Our study firstly applied a two-sample MR approach to detect causal relationships among gut microbiota, gut metabolites, and neurodegenerative diseases. Our findings may provide new targets for treatments and may offer valuable insights for further studies on the underlying mechanisms.
Research on fake online review recognition method based on feature engineering
Authors: Hou Jiani , Zhu Aimin
Published: March 2022

In the context of the explosive growth of online reviews in e-commerce, some merchants began to hire consumers to make fake purchases to increase sales, which caused the difficulty in identifying fake reviews. Therefore, from the perspective of consumers’ shopping behavior, a feature recognition method based on comment text, reviewer attribute and reviewer’s shopping behavior (referred to as TAB) is proposed to solve the problem of fake reviews caused by fake shopping behavior. Compared with BOW, TF-IDF, N-gram, FSP and other traditional feature extraction methods, experiments were carried out on Naive Bayes, SVM, Logistic Regression, Random Forest, CNN and other classification models. By changing the data dimension, the stability of each false comment recognition model was analyzed. The experimental results show that the TAB feature recognition method has better classification performance on logistic regression and support vector machine models, and the model is relatively stable, and the classification effect is not easily affected by dimension change.
Node topology location method of SDN social network based on ant colony algorithm
Authors: He Lichun , Li Jing
Published: March 2022

Due to the convergence defect of the existing SDN social network node topology location methods, there is a large node topology location error problem. In order to solve the above problems, this paper proposes a topology location method of SDN social network nodes based on ant colony algorithm. Firstly, the ant colony algorithm is introduced, and then the biological principle of ant colony algorithm is analyzed to determine the basic steps of ant colony algorithm. According to the number of mobile beacon launch positions and specific launch coordinates in ROI, ant colony algorithm is introduced into the mobile beacon path acquisition program to realize SDN node topology location based on ant colony algorithm. The experimental results show that under the background of node communication radius of 2.0 and 5.0, the node topology positioning errors of this method are small, and the minimum errors are 9.10% and 5.15% respectively. It is fully proved that this method has good node topology positioning effect.
Accounting information quality detection method of listed companies based on mobile social network interaction model
Authors: Wang Tian , Lun Xi
Published: March 2022

The existing quality of accounting information detection methods have large errors and cannot meet the needs of listed companies. Therefore, this paper presents a study on the accounting information quality detection methods of listed companies based on the mobile social network interaction model. The interactive model to obtain accounting information of listed companies based on mobile social network, select accounting information quality detection index, construct the accounting information quality detection index system; Determine the weight of accounting information quality detection index by hierarchical analysis method; construct a panel model based on detection index weight to realize the quality detection of accounting information of listed companies. The experimental results show that the accounting information quality detection error of this method is 0.10%–0.31%. It reduces detection error, improves detection accuracy, has good application performance, and is suitable for the promotion and application of accounting information quality detection.
Frequency division and optimizing capacity technology for hybrid energy storage system considering load smoothing
Authors: Bian Haihong , Zhao Xiu , Fu Yun , Peng Shan
Published: March 2022

There is a problem that how to optimize the allocation of hybrid energy storage system (HESS) economically on user-side. To solve this, a planning and scheduling method of HESS considering load smoothing is proposed. Firstly, an optimization model of energy storage system (ESS) considering energy storage life and peak-shaving rate is established, which is used to determine the rated power, rated capacity of ESS, and the charge and discharge power at each moment of the day. Then, this paper constructs a HESS consisting of lead-carbon battery (Pb-C) and supercapacitor. Variational mode decomposition (VMD) algorithm was used to extract peak load. The peak load is smoothed by super capacitor, and the composite load after peak load optimization is smoothed by Pb-C. Finally, solving the optimization model of HESS by mixed integer linear programming (MILP). And the results of the calculation examples show that the optimization method of HESS proposed in this paper not only reduces peak load effectively, but also improves benefits of HESS under the background of time-of-use electricity price.
A two-stage diversity enhancement differential evolution algorithm for multi-objective optimization problem
Authors: Wei Lixin , Wang Yexian , Fan Rui , Hu Ziyu
Published: March 2022

In order to solve the premature convergence of multi-objective evolutionary algorithm, a two-stage diversity enhancement differential evolution algorithm for multi-objective optimization problem(TSDE) is proposed. The offspring with better performance needs the generation of high-quality parent generation. In this paper, an improved cell density method is used to screen for the high quality parents by estimating the global distribution of the objective space. Moreover, Principal Component Analysis operator is introduced to the external archive to perturb the non-dominated solution, which not only ensures the convergence but also improves the diversity. In order to verify the effectiveness of the algorithm, TSDE and other advanced methods are run on 19 test functions. The results show that TSDE performs better than other algorithms.
RETRACTED: Intelligent color matching model for wood dyeing using Genetic Algorithm and Extreme learning machine
Authors: Guan Xuemei , Li Wenfeng , Huang Qinglong , Huang Jingyi
Published: March 2022

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.
Enhanced slime mould algorithm with multiple mutation strategy and restart mechanism for global optimization
Authors: Zheng Rong , Jia Heming , Wang Shuang , Liu Qingxin
Published: March 2022

Slime mould algorithm (SMA) is a new metaheuristic algorithm proposed in 2020, which has attracted extensive attention from scholars. Similar to other optimization algorithms, SMA also has the drawbacks of slow convergence rate and being trapped in local optimum at times. Therefore, the enhanced SMA named as ESMA is presented in this paper for solving global optimization problems. Two effective methods composed of multiple mutation strategy (MMS) and restart mechanism (RM) are embedded into the original SMA. MMS is utilized to increase the population diversity, and the RM is used to avoid the local optimum. To verify the ESMA’s performance, twenty-three classical benchmark functions are employed, as well as three well-known engineering design problems, including welded beam design, pressure vessel design and speed reducer design. Several famous optimization algorithms are also chosen for comparison. Experimental results show that the ESMA outperforms other optimization algorithms in most of the test functions with faster convergence speed and higher solution accuracy, which indicates the merits of proposed ESMA. The results of Wilcoxon signed-rank test also reveal that ESMA is significant superior to other comparative optimization algorithms. Moreover, the results of three constrained engineering design problems demonstrate that ESMA is better than comparative algorithms.
ESD-SLAM: An efficient semantic visual SLAM towards dynamic environments
Authors: Xu Yan , Wang Yanyun , Huang Jiani , Qin Hong
Published: March 2022

Traditional visual SLAM algorithms run robustly under the assumption of a static environment, but always fail in dynamic scenes, since moving objects will impair camera pose tracking. Given this, this paper presents an efficient semantic dynamic SLAM (ESD-SLAM), which is suitable for dynamic scenarios. Based on the ORB-SLAM2 framework, the ESD-SLAM we proposed employs lightweight semantic segmentation network FcHarDNet to extract semantic information, and uses the region growing algorithm to optimize the semantic segmentation boundary. Then dynamic objects are removed by combining semantic information with multi-view geometry, and it further improves the localization accuracy. Combining semantic information and depth information, a dense point cloud map of static scene is constructed to serve the planning task of mobile robot. We conduct the experiments on the public TUM RGB-D dataset and in the real-world environment. Experimental results show that the proposed algorithm can improve the performance of the ORB-SLAM2 system in dynamic scenes, and significantly improve the real-time performance compared with other same type dynamic SLAM algorithms.
RETRACTED: Multi-script handwritten digit recognition using multi-task learning
Authors: Gondere Mesay Samuel , Schmidt-Thieme Lars , Sharma Durga Prasad , Scholz Randolf
Published: March 2022

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.
RETRACTED: Using patching asymmetric regions to assess ischemic stroke lesion in neuro imaging
Authors: Sreejith S. , Subramanian R. , Karthik S.
Published: March 2022

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.
A novel transmuted lomax exponential distribution: Properties and applications
Authors: Khalil Alamgir , Arshad Kainat , Ijaz Muhammad , Khan Sajjad Ahmad , Manzoor Sadaf , El-Morshedy Mahmoud
Published: March 2022

Statistical lifetime distributions play a very important role in modeling data sets in various fields. Extending the existing distributions is of great interest in statistical research. The modification of the distributions provides more flexible model as compared to existing one. In this article, we propose a new probability model using Quadratic Rank Transmutation Map technique, named as Transmuted Lomax Exponential Distribution (TLED). The new distribution can model data sets with increasing, decreasing and bathtub shape hazard rates. Various statistical properties of the proposed distribution such as moments, order statistics, quantile function, mean residual life function and characteristic function are derived. Further, the parameter estimates are obtained through Maximum Likelihood method along with asymptotic confidence intervals. The utility of the new model is evaluated by analyzing two real data sets. In order to access the performance of the new model, several goodness of fit measures is used. The results indicate that the new model best fits the data as compared to the other extensions of the Lomax distribution.
Interval type-2 fuzzy logic controller based grid-tied solar PV inverter with active and reactive power control
Authors: Venkatasamy B. , Kalaivani L.
Published: March 2022

Solar photovoltaic industry is continuously thriving to improve the performance of power management systems with technology advancement. In the power system, balancing active and reactive power injection and absorption plays a pivotal role in maintaining Grid regulation and power factor and thus improving the efficiency and power handling capability. The Grid-tied solar PV inverters can be the cost-effective solution for reactive power compensation. Solar photovoltaic (SPV) system with the Grid-tied inverter is to produce active and reactive power in various ecological conditions. The Grid-tied PV inverter injects active and reactive power into the grid according to the desired value by the Grid requirements. The Proposed system uses decoupled P-Q theory with Interval type-2 Fuzzy Logic Controller (IT2-FLC). Also, the proposed controller minimizes the Total Harmonic Distortion (THD) and produces regulated output power compared to the other control techniques. The proposed IT2-FLC is compared with a Type-1 Fuzzy Logic Controller (T1-FLC) and conventional mathematical PI controller for performance analysis using simulation. A 75 kW Grid-tied inverter is designed in simulation to prove the effectiveness of the system through Matlab/Simulink. A smaller rating prototype model is developed to verify the simulation results.
RETRACTED: Analysis and prediction of uncertain responses using regression and fuzzy logic for friction stir welding of AA2014 under n-MQL
Authors: Mystica A. , Senthil kumar V.S. , Sakthi abirami B.
Published: March 2022

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.
L2 regularized deep convolutional neural networks for fire detection
Authors: Roy Sanjiban Sekhar , Goti Vatsal , Sood Aditya , Roy Harsh , Gavrila Tania , Floroian Dan , Paraschiv Nicolae , Mohammadi-Ivatloo Behnam
Published: March 2022

Fire calamity is one of the worst adversarial events that can happen to the human race. Fire disaster can happen as a manmade disaster or even naturally, and it may cause environmental, social, and financial damages as well. In order to minimalize the unwanted fire calamity, early detection of fire eruptions coupled with immediate and effective response is extremely vital to disaster management systems. The classification of forest fire and non fire images using deep learning techniques has recently received popularity. Detection and prevention of forest fire have lot of significance from the perspective of the forest fire department, specially for the fire and arson investigators. There are shortcomings in the current mechanisms of forest fire detection in terms of accuracy. Hence, we propose a fire detection model using LeNet5 convolutional neural networks (CNN), which can spot fire in outdoor environments by classifying fire and non fire images. L2 regularization is critical technique that manipulates the complexity of the convolutional neural network model. In our work fire images have certain features that decide if the image is fire or non fire.A weight is assigned to every feature. Regularization used to help to reduce the over fitting that used to caused by plenty of weights. Our proposed provides the directiontowards developing a system that detects the early stages of forest fire.This model can further be utilized to prevent the damage caused by the fire. A CNN is a deep learning method, which has been adopted in order to detect the images of fire and non-fire. With the non sparse solution of L2 regularization we have obtained around 87% of train accuracy, 71% of validation accuracy and 70% of test accuracy after running 10 epochs.
The predictive validity of the Hessisch Oldendorf Risk of Falling Scale (HOSS) decreases during the course of rehabilitation
Authors: Schmidt Simone B. , Boltzmann Melanie , Rollnik Jens D.
Published: March 2022

BACKGROUND: Falls are highly frequent among neurological patients during rehabilitation and subsequent risk assessments are crucial to prevent falls. OBJECTIVE: This study aims to determine the predictive values of the Hessisch Oldendorf Risk of Falling Scale (HOSS, “Hessisch Oldendorfer Sturzrisiko Skala”) for two timeframes: the first month of rehabilitation and from the second month to the end of rehabilitation. METHODS: Scale performances were assessed for 512 patients during inpatient neurological rehabilitation by calculating the sensitivity and the specificity. HOSS items were entered into a binary logistic regression model. Fall rates were calculated and used for correlation analyses and group comparisons. RESULTS: Initial HOSS assessment showed a sensitivity of 80.4% and a specificity of 60.7%. The HOSS re-assessment resulted in a sensitivity of 67.3% and a specificity of 69.5%. Only a non-somnolent state was identified to increase the risk of falling in both timeframes. Patients with a moderate impaired functional status (Barthel-Index between 20 and 50 points) showed the highest fall rates. CONCLUSION: The predictive validity of the HOSS decreases during the rehabilitation course. This might be caused by an altered relevance of the HOSS items during the re-assessment compared to the initial assessment for which the HOSS was developed for.
Are implementation interventions effective in promoting the adoption of evidence-based practices in stroke rehabilitation? A Cochrane Review summary with commentary
Authors: Oral Aydan
Published: March 2022

BACKGROUND: Stroke is the leading cause of disability among neurological disorders. Evidence-based practices to reduce disability are presumed to be associated with more favorable outcomes. OBJECTIVE: To assess whether implementation interventions are effective at increasing uptake of evidence-based practices in stroke rehabilitation. METHODS: The Cochrane Review by Cahill et al. (2020) is summarized. RESULTS: The effectiveness of implementation interventions on health professionals’ use of evidence- based practices is uncertain. CONCLUSIONS: There is an urgent need for future research investigating the utility of implementation interventions to ensure the uptake of evidence by health professionals for the benefit of stroke survivors.
GMFCS level improvement in children with cerebral palsy treated with repeat botulinum toxin injections and intensive rehabilitation: A retrospective study
Authors: Dursun Nigar , Akyuz Merve , Gokbel Tugba , Akarsu Melike , Yilmaz Esin , Karacan Cagla , Dursun Erbil
Published: March 2022

PURPOSE: The Gross Motor Functional Classification System (GMFCS) provides a standardized classification of motor disability in children with cerebral palsy (CP) that is typically considered longitudinally stable. Here, changes in GMFCS levels of children with CP who received repeated botulinum toxin A (BoNT-A) injections within an intensive rehabilitation approach were evaluated. METHODS: This retrospective, observational study included 503 children with CP (GMFCS I-V) treated in a single university rehabilitation clinic. Individualized treatment plans and a variety of rehabilitation techniques were incorporated within an integrated model of care. Each child received≥2 repeated BoNT-A injections as well as an intensive rehabilitation program. RESULTS: GMFCS level following repeat treatment improved in 42.1% of the patients and worsened in 3 patients; 14.9% of children showed improvement after 1 treatment cycle, 12.3% after 2 cycles, 7.6% after 3 cycles, 3.6% after 4 cycles, and 3.8% after≥5 cycles. Type of involvement (p < 0.001), baseline GMFCS (p = 0.001), number of treatment cycles (p < 0.001) and presence of severe dystonia (p = 0.032) were significant predictors of GMFCS improvement, but age and gender were not. CONCLUSION: Children with CP may change GMFCS level when intensive rehabilitation programs are combined with repeated BoNT-A injections.
The value of whole-brain CT perfusion imaging combined with dynamic CT angiography in the evaluation of pial collateral circulation with middle cerebral artery occlusion
Authors: Ma Yi-Chuan , Chen Ai-Qi , Guo Fei , Yu Juan , Xu Min , Shan Dan-Dan , Zhang Shun-Hua
Published: March 2022

BACKGROUND: Middle cerebral artery (MCA) occlusion is extremely common, especially unilateral artery, which can result in a significant incidence of cerebral infarction. OBJECTIVE: To assess the value of whole-brain computed tomography perfusion (CTP) imaging combined with dynamic CT angiography (dCTA) in the evaluation of pial collateral circulation in patients with MCA occlusion. METHODS: Whole-brain CTP and dCTA images were acquired in 58 patients with unilateral MCA occlusion. All patients were divided into three groups according to the American Society of Interventional and Therapeutic Neuroradiology/Society of Interventional Radiology (ASITN/SIR) collateral score (by CTA). The CTP parameters were analysed, including relative cerebral blood flow (rCBF), relative cerebral blood volume (rCBV), relative mean transit time (rMTT), and relative time to peak (rTTP). Patients were followed up with the modified Rankin scale (mRS). All cases in this study were confirmed by DSA. RESULTS: The CTP parameters of the MCA blood supply area on the affected side of patients with different degrees of stenosis were significantly different from those on the unaffected side. There are significant differences in the CTP parameters and openings of the Willis circle in patients with different degrees of stenosis. Significant differences were found in the number of patients with good prognosis. CONCLUSIONS: Whole-brain CT perfusion combined with dynamic CTA can structurally and functionally evaluate the establishment of pial collateral circulation and its effect on cerebral hemodynamic changes.
Does vestibular loss result in cognitive deficits in children with cochlear implants?
Authors: Janky Kristen L. , Thomas Megan , Al-Salim Sarah , Robinson Sara
Published: March 2022

BACKGROUND: In adults, vestibular loss is associated with cognitive deficits; however, similar relationships have not been studied in children. OBJECTIVE: Evaluate the effect of vestibular loss on working memory and executive function in children with a cochlear implant (CCI) compared to children with normal hearing (CNH). METHODS: Vestibular evoked myogenic potential, video head impulse, rotary chair, and balance testing; and the following clinical measures: vision, hearing, speech perception, language, executive function, and working memory. RESULTS: Thirty-eight CNH and 37 CCI participated (26 with normal vestibular function, 5 with unilateral vestibular loss, 6 with bilateral vestibular loss). Children with vestibular loss demonstrated the poorest balance performance. There was no significant reduction in working memory or executive function performance for either CCI group with vestibular loss; however, multivariate regression analysis suggested balance performance was a significant predictor for several working memory subtests and video head impulse gain was a significant predictor for one executive function outcome. CONCLUSIONS: CCI with vestibular loss did not have significantly reduced working memory or executive function; however, balance performance was a significant predictor for several working memory subtests. Degree of hearing loss should be considered, and larger sample sizes are needed.
Etiology Models of Antibody Triggered Histamine Intolerance Inducing Kawasaki Disease and Multisystem Inflammatory Syndromes Diseases
Authors: Ricke Darrell
Published: March 2022

The SARS-CoV-2 virus induces multisystem inflammatory syndrome in children (MIS-C) and adults (MIS-A) in a small subset of individuals. MIS-C and MIS-A symptoms overlap with Kawasaki Disease (KD). While many viruses and a few bacterial pathogens have been proposed as likely causative agents, the pathogenesis of KD remains unknown. The pathogenesis of MIS-C, MIS-A, and KD remain unknown. Herein, this article proposes that antibodies to pathogens, with levels higher than primary immune response level, are activating granulocytes and mast cells resulting in release of inflammatory molecules including histamine. Further, this article proposes that KD, MIS-C, and MIS-A are caused when elevated histamine levels exceed an individual’s histamine tolerance level (i.e., Histamine Intolerance following elevated pathogen antibody levels). This model establishes a framework for why only a small subset of individuals develop KD, MIS-C, and MIS-A following much larger pathogen outbreaks and accounts for the delayed onsets observed.
Population estimates of biomarkers of exposure to carbon monoxide, nicotine, and NNK in smokers and non-smokers
Authors: Ayala-Fierro Felix , Verron Thomas , Lizhnyak Pavel , Freeland Robert , Frost-Pineda Kimberly , Elamin Ashraf , Sarkar Mohamadi
Published: March 2022

Assessment of potentially reduced risk tobacco products (PRRPs) can be facilitated with availability of a single baseline population estimate for biomarkers of exposure (BOEs) for select constituents in cigarette smoke. The purpose of this analysis is to establish such a population estimate for BOEs to carbon monoxide (carboxyhemoglobin - COHb), nicotine (Nicotine Equivalents - NEQ), and nicotine-derived nitrosamine ketone (NNK; total urinary 4-[methylnitrosamino]-1-[3-pyridyl]-1-butanol [NNAL] - NNAL) based on pooled weighted average from published literature. 

Four databases - PubMed®, ScienceDirect®, TOXNET®, and Google Scholar™ – were systematically searched for published literature between 2008-2020 based on a protocol for literature assessment to identify and select studies. A total of 217 scientific articles were identified and reviewed for potential inclusion, 87 studies met the pre-set criteria (reported clinical studies and/or observational studies with reportable original values), and 53 studies met the inclusion criteria for each BOE. We determined the pooled weighted average based on Epanechnikov kernel density curves. The NNAL levels were normalized to a unit (pmol/mg creatinine) commonly used in research studies and reported as geometric means.  

Smokers had significantly (p<0.05) higher levels of NNAL (1.112 pmol/mg creatinine; 95% confidence interval [CI] 0.161, 2.047), COHb (5.21 % saturation; 95% CI 3.91, 6.00), and NEQ (13.81 mg/24 h; 95% CI 9.08, 21.19) compared to non-smokers (0.008 pmol/mg creatinine, 95% CI 0.001, 0.017 for NNAL; 1.05% saturation, 95% CI 0.04, 2.07 for COHb; and 0.058 mg/24 h, 95% CI 0.016, 0.112 for NEQ) This research addresses the existing gap in lack of population level estimates for BOEs by establishing population level estimates for COHb, NEQ, and NNAL that can be used to determine changes in exposure for smokers switching to PRRPs.
Pemilihan Material Rangka Kendaraan Pemanen Jagung Kombinasi dengan Metode CRITIC, Digital Logic dan TOPSIS
Authors: Doloksaribu Martin , Khairi Agus Juniawan , Fathurrohman Muhammad , Supriadi Sugeng
Published: March 2022

Desain rangka kendaraan pemanen jagung kombinasi menuntut rangka kendaraan yang memiliki berat dan kekuatan yang efisien selain kriteria sifat lain yang perlu dipertimbangkan. Pemilihan material dengan banyak kriteria merupakan hal rumit dan memerlukan metode yang tepat untuk meningkatkan probabilitas keberhasilan produk. Pemilihan material rangka kendaraan pemanen jagung kombinasi dilakukan dengan metode CRITIC, Digital Logic dan TOPSIS. Bobot kriteria dihitung dengan metode CRITIC dan Digital Logic. Kandidat material diurutkan dengan metode TOPSIS. Kandidat material terdiri dari dua golongan material yaitu aluminium dan baja struktur. Urutan pertama dengan bobot kriteria metode CRITIC dan metode DL adalah A7075-T6. Urutan kedua dengan metode CRITIC adalah A6061-T6 dan dengan metode DL adalah SSA710. Metode pemilihan material yang tepat dapat memberikan urutan material yang handal.Desain rangka kendaraan pemanen jagung kombinasi menuntut rangka kendaraan yangmemiliki berat dan kekuatan yang efisien selain kriteria sifat lain yang perlu dipertimbangkan.Pemilihan material dengan banyak kriteria merupakan hal rumit dan memerlukan metode yang tepatuntuk meningkatkan probabilitas keberhasilan produk. Pemilihan material rangka kendaraanpemanenjagung kombinasi dilakukan dengan metode CRITIC, Digital Logic dan TOPSIS. Bobot kriteriadihitung dengan metode CRITIC dan Digital Logic. Kandidat material diurutkan dengan metodeTOPSIS. Kandidat material terdiri dari dua golongan material yaitu aluminium dan baja struktur.Urutan pertama dengan bobot kriteria metode CRITIC dan metode DL adalah A7075-T6. Urutankedua dengan metode CRITIC adalah A6061-T6 dan dengan metode DL adalah SSA710. Metodepemilihan material yang tepat dapat memberikan urutan material yang handal.
Lean Construction: como os princípios da manufatura enxuta podem contribuir na gestão dos processos construtivos da construção civil
Authors: Perdigão Leandro , Reinert Junior Adival José
Published: March 2022

A construção civil, atualmente, apresenta um cenário altamente competitivo, o mercado exige a cada dia que as empresas entreguem maior qualidade em seus produtos. Com isso, para que as construtoras possam se destacar elas devem buscar diferenciais, não somente em relação a qualidade dos produtos que produzem, mas também apresentando melhores condições de trabalho para seus colaboradores. Diante deste contexto, esta pesquisa tem como principal questionamento: Os princípios e fundamentos da manufatura enxuta adaptados para a construção civil podem contribuir para melhorias na gestão dos processos construtivos? A realização deste artigo tem como objetivo geral apresentar e analisar os princípios e fundamentos da Manufatura Enxuta na prática da construção civil e o seu uso para otimizar a gestão dos processos. A concretização dеѕtе trаbаlhо será realizada por meio de uma rеvіѕãо bіblіоgráfіса a rеѕреіtо da tеmátіса central, Construção Enxuta (lean construction), rеѕѕаltаndо ѕuaѕ рrіnсіраіѕ práticas fundamentais. A partir da pesquisa feita é possível concluir que o conceito da Construção Enxuta surge como um diferencial para que as empresas do setor da construção civil possam se destacar das demais, contribuindo para melhorias na gestão dos processos, possibilitando assim, gerar maior valor do produto para os clientes, aumentar a qualidade do produto final, aumentar a eficiência das etapas e minimizar os desperdícios.
Attitudes of Primary School Teachers Towards Inclusion of Children with Special Needs in Mainstream Educational Programs in Primary School
Authors: Valenčić Štembergar Anja
Published: March 2022

The
article explores the attitudes of primary school teachers towards the inclusion
of children with special needs in mainstream educational programs in primary
schools. The theoretical part discusses the requirements of the new school
system imposed on teachers. The empirical part presents a study on the
attitudes of primary school teachers towards the inclusion of children with
special needs in mainstream primary schools and on whether there are
differences in attitudes between younger and older teachers. Descriptive and
inferential methods of empirical pedagogical research were used in this paper.
The data was collected through an online questionnaire filled out by primary
school teachers across Slovenia. The study results showed that all teachers,
regardless of age, feel that they are not sufficiently trained to work with
children with special educational needs and disabilities (SEND). At the same
time, they agree that they did not acquire enough skills during their
undergraduate studies to work with these children. Furthermore, the teachers
feel they do not have enough experience working with these children. At the
same time, they agree that the children with SEND should be included in
programs specifically tailored to their needs and not in mainstream primary
school programs. Additionally, the results have shown that teachers think it is
necessary to set different educational goals for children with SEND than for
other students. The teachers feel that working with children with SEND means
additional work. However, they think that the inclusion of children with SEND
in mainstream educational programs is not assessed as problematic. They feel
that other students are also specifically addressed in the class with children
with SEND. However, older teachers than younger ones believe they did not
acquire enough knowledge during their undergraduate studies.
Parental Involvement in Their Children's Education
Authors: Gregorović Belaić Zlatka
Published: March 2022

Parental
involvement in the children's education in our area is still an insufficiently
researched construct. It can be implicitly concluded that parental involvement
is something that happens by itself. However, referring to previous scientific
research, the importance of this topic is also noticed through the positive
relationship between desirable child outcomes, such as better school performance
and parental involvement in their education. The family certainly plays a vital
role in the student's school achievement, i.e., parents contribute to the
child's cognitive development and academic achievement in various ways -
preparing the child for school, transmitting educational values, modeling the
child's self-confidence, establishing learning habits, and participating in
school (Reić Ercegovac & Koludrović, 2010). Various scientific papers
emphasize that the active participation of parents in the education of the
child implies their physical presence and active participation (Sušanj
Gregorović, 2018). There is still no unambiguous, generally accepted definition
despite considerable research about parental involvement in the child's
education. However, there is a consensus that it is a complex, multidimensional
construct involving many parenting activities and behaviors related to the
child's entire education and learning process (Epstein, 1990; Sušanj
Gregorović, 2018). Parental involvement in the child's education is manifested
in two ways: involvement in school activities and parental involvement in home
activities. For the purposes of this paper, the second type of parental
involvement is particularly important. According to the available literature,
it is divided into two domains (Sušanj Gregorović, 2018), the first of which is
parental participation in activities related to knowledge/skills development
(Epstein, 2001; Henderson and Mapp, 2002; Ljubetić, 2014), while the other
refers to participation in learning promotion activities that are not directly
related to schoolwork (creating a cognitively stimulating family environment,
providing educational materials, etc.) (Henderson and Mapp, 2002;
Hoover-Dempsey and Sandler, 1997). This paper aims to contribute to the
theoretical knowledge of the construct through a review of previous scientific
knowledge and research.
A REVIEW OF THE TECHNO – ECONOMIC POTENTIALS OF BALANITES AEGYPTIACA OIL
Authors: Usman Abdulyakin , Ibrahim Ahmad Rufai
Published: March 2022

Plants oil are becoming important in commerce and nutrition worldwide as they are good source of dietary energy and raw material for the manufacture of industrial products. Despite this fact little attention has been given to Balanites aegyptiaca oil.  Therefore there is growing interest in understanding the potential of Balanites aegyptiaca oil as feedstock for improving livelihoods of communities in dryland areas. Balanites aegyptiaca is a multipurpose tree species in dry land of Africa. The plant seed kernel produces high quality oil that amounts for 9-10 % by weight of the whole fruit. Its seed kernel has high oil content (50 %) whose extraction is economically worthwhile. The oil parameters revealed that the oil composed of long chain fatty acids with high degree of unsaturation, making it a good feedstock for biodiesel production. It also has biologically active properties which contribute in its medicinal application. The oil is fulfilling in saturated fatty acids, as such are accustomed as cooking oil. Balanites aegyptiaca oil may be useful for industrialists that produce eco-friendly soap. Therefore, conversion of the oil to different products will help in domestication of this neglected and underuse dryland tree species. This may advocate wise use of renewable natural resources and not protection without possible economic benefit. Thus, Balanites aegyptiaca oil is a multipurpose feedstock with high economic potential and industrial applications if richly exploited. Furthermore, many prospective exploitation possibilities will emerge when further researches are made on this multipurpose oil.
PHYTOCHEMICAL, ANTIOXIDANT AND ANTIMICROBIAL STUDIES OF THE CRUDE EXTRACT OF Curvulariasp. ISOLATED FROM THE LEAVES OF THE MEDICINAL PLANT Piliostigma thonningii (Fabaceae)
Authors: Ogbiko Cyril , Eboka C. J. , Okezie U. M. , Okoye F. B. C.
Published: March 2022

Recently, there is biotechnological interest in secondary metabolites of endophytes since they have been shown to be capable of producing substances of pharmacological importance. Piliostigmathonningii is a tree whose parts are widely employed in Nigeria for diverse medicinal applications. The aim of this study is to investigate the phytochemical composition, the antiradical and in vitro antimicrobial potentials of the crude ethyl acetate extract of Curvularia sp isolated from the leaves of the plant. The endophytic fungus was isolated, purified, and identified using conventional methods. While standard procedures was employed in the determination of the phytochemical constituents, quantitative estimation of the total phenol and flavonoid were done by spectrophotometric method using gallic acid and quercetin as standards respectively. While the antioxidant activity was determined by DPPH scavenging assay, the agar well diffusion method was employed to screen for its antimicrobial capabilities. Results showed the presence ofimportant phytoconstituents notably alkaloid, flavonoid, phenolics, tannin, saponins among others. While the antioxidant assay showed the total phenolic and flavonoid contents to be 212.55 ± 1.2 mgGAE/g extract and 143.16 ± 0.8 mgQE/g extract respectively, a 74.45 ± 0.11% free radical scavenging activity was observed compared to ascorbic acid standard that exhibited a 87.92 ± 0.17% inhibition. At the highest investigated concentration of 1 mg/mL, the extract produced antibacterial activity only against Escherichia coliandPseudomonas aeruginosa. The results showed that the extract exhibits marked antioxidant and selected antibacterial effects thus justifying the assertion that endophytic bioactive compounds have promising applications in the field of medicine.
CHARACTERIZATION OF HYBRID-FORMAMIDINIUM BISMUTH BROMIDE PEROVSKITE MATERIAL (FABi2Br9) SYNTHESIZED VIA GROWTH ASSISTED TECHNIQUE FOR SOLAR CELLS APPLICATION
Authors: Salisu Bashir
Published: March 2022

ABSTRACT

In the last decade, organic-inorganic perovskite solar cells (PSCs) have had tremendous success, raising their power conversion efficiency from 3.8% in 2009(T, A, K, & Y, 2009) to >25.6% (Li et al., 2021). Perovskite material is newly emergent, third-generation solar cells, it generally refers to any composite that has structure like that of calcium titanium oxide (CaTiO2). It has a general formula ABX­3, where A refers to an organic compound, B is an inorganic and X represents the halides. In this research, a Hybrid-Formamidinium Bismuth Bromide Perovskite solar cell (FABi2Br9) was synthesized via a novel crystal growth process and subjected to characterization for determining its optoelectronic properties for solar cells application. The x-ray diffraction (XDR) results revealed the crystal hexagonal structure of FABi2Br9, the crystal sizes were obtained and it gives an excellent size (74nm) for light absorption material. The bandgap was determined using ultraviolet-visible spectroscopy (U.V vis) which was found to be 1.80eV which is within the required range for an absorbing layer in a solar cell architecture. Nuclear magnetic resonance (NMR) and was used to identify the organic content purity of the composite. In conclusion, FABi2Br9 was found to be pure with excellent optoelectronics properties that can readily be used as an absorbent layer in perovskite solar cells architecture
HYDROLOGICAL MODELLING FOR EVALUATING CLIMATE CHANGE IMPACTS ON STREAMFLOW REGIME IN THE BERNAM RIVER BASIN MALAYSIA
Authors: Ismail Habibu , M. K. Rowshon  , N.J. Shanono  , N.M. Nasidi  , Umar D.A.
Published: March 2022

The complexity of hydrological models has been a setback in their evaluation particularly for long-term simulations. Deficit and constant loss (DCL) method has been introduced in Hydrologic Engineering Center's Hydraulic Modeling System (HEC-HMS) model for continuous based simulations. However, studies on climate change impacts using the method are still very few. This study used the method to evaluate potential impacts of climate change on streamflow at Bernam Basin, Malaysia for 2010-2039, 2040-2069 and 2070-2099 to the baseline period (1976-2005) under two RCP scenarios (RCPs 4.5 and 8.5). The model efficiency during evaluation is found satisfactory. Compared with the baseline period, the predicted streamflow   decreased in all future periods during main and off-seasons. However, the changes have become more pronounced during the off-season with a significant decrease of 9.14% under the worst-case scenario (RCP8.5). Therefore, the Basin would likely experience tremendous pressure in the late century due to low streamflow, particularly in off-season months.
A A TYPE II HALF LOGISTIC EXPONENTIATED-G FAMILY OF DISTRIBUTIONS WITH APPLICATIONS TO SURVIVAL ANALYSIS
Authors: BELLO OLALEKAN AKANJI , Sani Ibrahim Doguwa  , Abubakar Yahaya  , Haruna Mohammed Jibril
Published: March 2022

Statisticians have created and proposed new families of distribution by extending or generalizing existing distributions. These families of distributions are made more flexible in fitting different types of data by adding one or more parameters to the baseline distributions. In this article, we present a new family of distributions called Type II half-logistic exponentiated-G family of distributions. We discuss some of the statistical properties of the proposed family such as explicit expressions for the quantile function, probability weighted moments, moments, generating function, survival and order statistics.  The new family’s sub-models were discussed.  We discuss the estimation of the model parameters by maximum likelihood.  Two real data sets were employed to show the usefulness and flexibility of the new family
APPLICATION OF AGRICULTURAL WASTES FOR THE AQUEOUS REMOVAL OF HEAVY METALS FROM WASTE WATER
Authors: Jibril Hafsat Bala , Salga Saleh Muhammad , Ahmed Salisu , Saddiq Maryam
Published: March 2022

Heavy metals were found to have hazardous impact on man and ecosystem. The efficacy of Rice, Millet and Guinea corn husks was tested for the removal of Cu(II) and Fe(II) ions from aqueous solution. The husks were soaked in the metal ion solutions removed, dried, digested and analyzed by MP-AES. The husks were found to be effective for the removal of the targeted metal ions. The results showed the pattern of removal in the order; RH >GCH > MH and GCH > MH > RH for Cu(II) and Fe(II) respectively. The samples were also analyzed for X-ray Fluorescence (XRF) and Fourier Transform Infrared Spectrometer (FTIR). The XRF result showed oxides like SiO2, MnO, MgO and Fe2O3, etc. with SiO2 having the highest percentage. The results of the FTIR analysis showed the presence of OH, C-H, NH and C=O groups, which indicates tendencies for metal binding. Moreover, the MP-AES results showed that RH had the highest removal capacity of Cu(II) with 95% (76 mg/g), followed by GCH 92.5 % (74 mg/g), and MH has the least removal capacity of 84.5 % (67.6 mg/g). The amount of Fe(II) was found to be high in GCH with 95% (76mg/g) followed by MH, 91.5 % (73.2 mg/g) and RH having the least capacity of 60 % (48 mg/g). Generally, the results indicates that all the agricultural wastes have the capacity to remove the heavy metals significantly. This showed that, the husks can be used to remove heavy metals from wastewater without polluting the environment.