Level Of Usage Research Articles

Open Source Plagiarism Checking Software: An Assessment of Awareness and Utility Among Social Science Research Scholars of Lalit Narayan Mithila University, Darbhanga, Bihar: A Study

This study investigates the awareness and usage of open-source plagiarism checking software among research scholars in the Social Sciences discipline at Lalit Narayan Mithila University (LNMU), Darbhanga, Bihar. Given the increasing importance of academic integrity, this study aims to identify the level of knowledge, usage patterns, and perceived benefits of these tools among researchers. A structured questionnaire was administered to 60 participants, revealing a moderate level of awareness but limited usage. The findings suggest the need for enhanced training and institutional support to promote the effective use of open source plagiarism detection software. Although there is a notable intention to use plagiarism detection resources, various barriers remain that must be addressed to optimize their utilization and reinforce academic integrity in research practices.

Exploring the Link Between Social Media Engagement, Social Anxiety, and Environmental Preferences in University Students

As mental health issues become increasingly prominent, social anxiety is prevalent among university students and significantly affects their social behaviors and environmental preferences. With the increasing reliance on social media, understanding how these behaviors shape preferences for physical social environments is crucial for designing supportive campus spaces. This study investigates the relationship between social anxiety, social media usage, and environmental preferences in campus settings. We aim to identify the key environmental factors that can promote healthier social interactions for students with varying levels of social anxiety and social media use. Data were collected from university students through a structured questionnaire assessing demographic characteristics, online and offline behavior, social media usage intensity, social anxiety level, and environmental preferences. Using K-means clustering, participants were grouped into four clusters based on their social media usage and social anxiety levels. ANOVA and Multivariate Multiple Regression (MMR) were conducted to examine differences in environmental preferences across these clusters. Significant differences in environmental preferences were observed across the four clusters. Gender and grade influenced social anxiety levels, with females and undergraduate students reporting greater anxiety. Individuals with high social media use, regardless of their anxiety levels, generally exhibited stronger preferences for various environmental dimensions, including openness, convenience, facility provision, safety/comfort, and cultural landscape. However, individuals with higher social anxiety tended to prefer enclosed, facility-rich, and more controlled environments. The relationship between social anxiety and preferences for convenience, safety/comfort, and cultural landscape was minimal or non-significant. This study highlights the importance of considering both behavioral and psychological factors when designing university social environments. By identifying specific environmental preferences of students with high social anxiety, the findings offer evidence-based recommendations for creating more inclusive and supportive campus spaces that promote positive social interactions and well-being.

PELATIHAN SISTEM MANAJEMEN ARSIP DI KANTOR DESA JAYA MULYA

Outgoing and incoming letters are active dynamic archives whose usage levels are still high. The birth of the e-Government concept makes it easier to administer government by utilizing technology. Dynamic archive management which is still manual causes many shortcomings such as damaged archives, lost archives, difficult to find etc. Therefore, a digital archive management system is needed so that dynamic archive management is more effective. Service activities related to archive management system training were carried out in Jayamulya Village, Serang Baru, Bekasi. The method used is by providing materials, training and practice in managing records of outgoing and incoming letters using an records management system. As a result of this service activity, village officials know, understand, practice and use the archive management system so that outgoing and incoming mail management is more effective. Although the archives management system still needs to be developed to make it easier and more effective in managing archives at the Jayamulya Village Office.

How Climate Change Will Shape Pesticide Application in Quebec’s Golf Courses: Insights with Deep Learning Based on Assessing CMIP5 and CMIP6

The accelerating impact of climate change on golf course conditions has led to a significant increase in pesticide dependency, underscoring the importance of innovative management strategies. The shift from Coupled Model Intercomparison Project Phase 5 (CMIP5) to the latest CMIP6 phase has drawn the attention of professionals, including engineers, decision makers, and golf course managers. This study evaluates how climate projections from CMIP6, using Canadian Earth System Models (CanESM2 and CanESM5), impact pesticide application trends on Quebec’s golf courses. Through the comparison of temperature and precipitation projections, it was found that a more substantial decline in precipitation is exhibited by CanESM2 compared to CanESM5, while the latter projects higher temperature increases. A comparison between historical and projected pesticide use revealed that, in most scenarios and projected periods, the projected pesticide use was substantially higher, surpassing past usage levels. Additionally, in comparing the two climate change models, CanESM2 consistently projected higher pesticide use across various scenarios and projected periods, except for RCP2.6, which was 27% lower than SSP1-2.6 in the second projected period (PP2). For all commonly used pesticides, the projected usage levels in every projected period, according to climate change models, surpass historical levels. When comparing the two climate models, CanESM5 consistently forecasted greater pesticide use for fungicides, with a difference ranging from 65% to 222%, and for herbicides, with a difference ranging from 114% to 247%, across all projected periods. In contrast, insecticides, growth regulators, and rodenticides displayed higher AAIR values in CanESM2 during PP1 and PP3, showing a difference of 28% to 35.6%. However, CanESM5 again projected higher values in PP2, with a difference of 1.5% to 14%.

Design of an Improved Model for Spectrum Sharing and Resource Management Using Deep Q-Network, Federated Averaging, and Ant Colony Optimization

Indeed, the ever-evolving wireless communication requires DSS and resource management for effectiveness. The old methods of spectrum allocation have a strategic shortfall since they are static and thus not adapted to real-time network conditions. Besides, more important challenges include issues over privacy and inefficiency of resource utilization. In the light of such problems, this paper proposes a new method by bringing together three deep-learning techniques, which are Deep Q-Networks, Federated Averaging, and Ant Colony Optimisation. Each is chosen because of its various competencies and complementary capabilities. First, DQN is chosen because it has the capability to handle high-dimensional action space. DQN applies deep learning to approximate the Q Value function, which provides the optimal decision of spectrum allocation based on real-time network states, such as spectrum usage and interference levels. With this scheme, up to a 20% gain in network throughput and up to a 15% cut in wasted spectrum compared to traditional methods are achievable. The second component FedAvg tackles the model training collaboration issue with privacy. It enables FedAvg for privacy-preserving resource management, where multiple devices update the global model collaboratively by communicating model updates without exchanging raw data samples. For this approach, the resulting method leads to a further increase in data privacy by reducing data leakage as high as 40%, with an improvement in resource management accuracy of up to 15%. ACO was employed to optimize resource allocation and improve spectrum efficiency. ACO emulates the natural foraging behavior of ants to solve combinatorial optimization problems. Consequently, it has led to up to 25% increase in spectral efficiency and up to 20% improvement in resource allocation balance sets. All these methods put together will provide a wholesome solution that not only optimizes spectrum and resource management but also promises privacy and adaptability. This represents severe improvement in overcoming the weaknesses of the existing approaches and will provide a strong foundation for next-generation wireless networks.

Lifestyle Patterns among Adolescents in Selected Schools of District Rohtak, Haryana: A Cross Sectional Study

Introduction: - Adolescence is a period in which an individual undergoes major physical and psychological changes. There is convincing evidence between lifestyle diseases and unhealthy habits which are acquired during adolescence and persist in adulthood. An early investigation of the lifestyles of adolescents will probably prevent their progression into serious diseases. Methods: - The present cross-sectional study recruited 600 adolescents studying 9th to 12th in the selected schools of Rohtak, Haryana, India. The lifestyle-related behavior and practices were assessed based on a structured proforma with the following domains: - home & environment, education, eating habits, and sexuality. Ethical permission was obtained from the concerned authorities. Results: - The mean age of the study subjects was 15.9 (SD-1.4) and most of them were males (61%). More than half of the study subjects (52.7%) were having BMI of 18 to 25 Kg/m2 and 39.8% of them belonged to lower middle socio-economic status. A major proportion of the students felt happy to go to school (64%) and were regular in attending school (90%). The majority of them reported having some spiritual beliefs (88%). A major proportion of the students reported that they own smartphones (83%) and were using various social networking sites (83%). Around 63% of the subjects reported eating fast food on monthly basis. About 11% of the subjects reported the usage of alcohol in the current 3 months. Around 20% of the subjects reported knowledge regarding HIV/STD. Conclusion: - The study documents the presence of unhealthy dietary practices, higher levels of usage of mobile phones along with alcohol use in the school children in this setting. The current study provides some preliminary data for policymakers so that they can modify the current policies and interventions according to the needs of adolescents.

Digital twin technology (DTT) in a developing construction industry: evaluation of the awareness and usage among professionals in Nigeria

Technological innovations play a crucial role in project delivery across all sectors of the economy. This research seeks to assess the awareness of digital twin technology (DTT) among construction industry professionals to promote the sustainable completion of construction projects. A quantitative approach was adopted by using a survey questionnaire with convenience sampling. Questionnaires were self-administered to gather information about the industry professionals’ awareness and utilization of DTT in construction projects. Mean Item Score (MIS), Standard Deviation (SD), Spearman, and Kruskal-Wallis tests were used to analyze the collected data. Professionals within the construction industry have demonstrated a high level of familiarity with various technological advancements with computer systems, Wi-Fi, 2D Graphics, Vertex Digital twin platform, and GPS identified as the most commonly utilized tools in the field. Spearman correlation analysis revealed a significant relationship between DTT awareness and usage levels. The study provided valuable information on the present awareness and DTT utilization within the construction sector. It proposed methods through which professionals can familiarize themselves with empowering tools to enhance productivity and performance within the industry.

A copula-based approach for multi-modal demand dependence modeling: Temporal correlation between demand of subway and bike-sharing

As a representative mode of shared mobility, bike-sharing serves not only as a convenient way to conduct short-distance trips in urban areas, but also as a feeder mode to public transit, forming the Bike and Ride (BnR) system. Conducting management for such a hybrid multi-modal system faces various challenges, including the complex interactions between bike-sharing and other modes, highly dynamic passenger demand, and the difficulty of accessing direct transfer data. To overcome such difficulties, our study proposes a framework for assessing the dependency between the two usage modes. Firstly, a Dynamic-Time-Warping-based (DTW) method is utilized to determine the catchment area (CA) between the two modes, allowing the BnR-related tendency similarity under a given time scale to be considered. Then, the patterns of probabilistic dependence between travel demand of the two modes are obtained by a copula-based approach, which separates correlations under specific usage levels from single modal demands. A case study on the multi-modal system formed by docked bike-sharing and subway in New York is conducted to validate the proposed framework. The tendency similarity is found to be most pronounced within 500 m on average under a 4-hour interval. For each formed station group (SG), the best-fitted copula type is selected, capturing the strong tail correlations present only at specific usage levels. The results show a variety of different correlation patterns within SGs, despite the close geographic locations they may share. Areas of potential transfer resistance between the two modes are identified, which is more evident in first-mile-related (FMR) activities. In contrast, the two modes display more weak connections in last-mile-related (LMR) activities. The obtained results can be utilized by bike-sharing service providers to analyze demand distributions and conduct efficient station-level rebalancing. Compared to previous methods, our proposed framework is computationally inexpensive since no direct transfer of data or complex inference network is required. It incorporates statistically significant spatial–temporal information, allowing for a more accurate determination of the bi-modal assessment range. Moreover, considering that single-mode influences are mathematically removed, the resulting correlation in principle links to the strength of the connections between the two modes. Therefore, it can be assessed as an indicator of the reliability of the multi-modal system.

Comparative Analysis of the Codon Usage Pattern in the Chloroplast Genomes of Gnetales Species

Codon usage bias refers to the preferential use of synonymous codons, a widespread phenomenon found in bacteria, plants, and animals. Codon bias varies among species, families, and groups within kingdoms and between genes within an organism. Codon usage bias (CUB) analysis sheds light on the evolutionary dynamics of various species and optimizes targeted gene expression in heterologous host plants. As a significant order of gymnosperms, species within Gnetales possess extremely high ecological and pharmaceutical values. However, comprehensive analyses of CUB within the chloroplast genomes of Gnetales species remain unexplored. A systematic analysis was conducted to elucidate the codon usage patterns in 13 diverse Gnetales species based on the chloroplast genomes. Our results revealed that chloroplast coding sequences (cp CDSs) in 13 Gnetales species display a marked preference for AT bases and A/T-ending codons. A total of 20 predominantly high-frequency codons and between 2 and 7 optimal codons were identified across these species. The findings from the ENC-plot, PR2-plot, and neutrality analyses suggested that both mutation pressure and natural selection exert influence on the codon bias in these 13 Gnetales species, with natural selection emerging as the predominant influence. Correspondence analysis (COA) demonstrated variation in the codon usage patterns among the Gnetales species and indicated mutation pressure is another factor that could impact CUB. Additionally, our research identified a positive correlation between the measure of idiosyncratic codon usage level of conservatism (MILC) and synonymous codon usage order (SCUO) values, indicative of CUB’s potential influence on gene expression. The comparative analysis concerning codon usage frequencies among the 13 Gnetales species and 4 model organisms revealed that Saccharomyces cerevisiae and Nicotiana tabacum were the optimal exogenous expression hosts. Furthermore, the cluster and phylogenetic analyses illustrated distinct patterns of differentiation, implying that codons, even with weak or neutral preferences, could affect the evolutionary trajectories of these species. Our results reveal the characteristics of codon usage patterns and contribute to an enhanced comprehension of evolutionary mechanisms in Gnetales species.

Comparing the trends of MBS telepsychiatry and consultant physician telehealth services from 2017 to 2022: A retrospective study.

The Medicare Benefit Schedule (MBS) telehealth items were expanded in March 2020 during the COVID-19 pandemic. We measured the use of MBS telepsychiatry items compared to consultant physician telehealth items within the context of these item changes, to understand differences in telepsychiatry and physician telehealth utilisation. Monthly counts of face-to-face and telehealth (videoconferencing and telephone) MBS items for psychiatrists and physicians from January 2017 to December 2022 were compiled from Services Australia MBS Item Reports. Usage levels were compared before and after telehealth item expansion. Usage trends for MBS telepsychiatry and physician telehealth items were compared in time-series plots. Telehealth item expansion resulted in a greater rise of telepsychiatry services from 3.8% beforehand to 43.8% of total services subsequently, compared with physician telehealth services (from 0.6% to 20.0%). More physician telehealth services were by telephone compared with telepsychiatry services. Time-series of both telehealth services displayed similar patterns until mid-2022, when physician telehealth services declined as telephone items were restricted. Telepsychiatry services consistently comprised a greater proportion of total services than physician telehealth services. MBS psychiatrist services showed a more substantial and persistent shift to telehealth than physician services, suggesting a greater preference and use of telepsychiatry.

Lifelong Learning Center Trainers: What Are Their Perceived Curriculum Literacy and Digital Technology Usage Levels?

Education and training are crucial components of society's ever-changing nature, and having a strong understanding of curriculum literacy is necessary for trainers in adult education to successfully execute curriculum. Similarly, effective use and integration of digital technologies into educational settings is a necessary skill for trainers. These competencies are critical for K-12 and higher education educators, as well as for adult education trainers who guide the learning process in line with their assigned program. In this study, we have investigated the relationship between trainers' perceived competence in curricular literacy (CL) and their use of digital technologies in education (DTUE). This study employed a descriptive survey methodology to gather data from a total of 628 individuals. The average age of the participants was 41.7 years, and they were all employed at a lifelong learning institution in Türkiye. MANOVA and correlation analysis were executed. We examined whether there were any differences in the trainers' perceived CL and DTUE levels based on the specified variables. The results revealed a positive and weak correlation between trainers' perceived curriculum literacy levels and their use of digital technology. Also, the trainers without prior formal pedagogical training had significantly lower scores in CL and DTUE compared to the trainers who had either graduated from the Faculty of Education or earned a pedagogical formation certificate.

ENHANCED SELECTIVITY OF OXYGEN DELIGNIFICATION BY CHERRY AND GUAR GUM ADDITIVES

Natural polysaccharide-based gums produced by plants in response to biotic or abiotic factors are used in various industries due to their biodegradability, renewability, biocompatibility, and non-toxic properties. This study examined the use of these gums in a new application, such as adding them to the delignification liquor to decrease the negative effects of radicals formed during the oxygen delignification of stone pine kraft pulps. For this purpose, the effects of sweet cherry gum, both with and without hydrogen peroxide reinforcement, and guar gum on oxygen delignification were examined in this study. The addition of both gums, up to a certain usage level, increased the selectivity of the reaction and protected the viscosity from oxidative damage, while causing only a limited reduction in the kappa number during the delignification process. However, it was determined that cherry gum, in hydrogen peroxide-reinforced oxygen delignification, showed no effect on selectivity, but increased pulp strength properties and better bleached pulp could be produced.

Examining the Effectiveness of Teaching Vietnamese Language among Ethnic Minority Primary Students in Son La Province

The Vietnamese language is the common language of different ethnic groups and also it is the official language used in the education sector. The development of the language skills of ethnic minority children is a fundamental issue in the development of education in ethnic regions. The main research question is; how effective are the current strategies in teaching the Vietnamese language to the ethnic minority primary students in Son La province? The methods used are collecting secondary documents, analyzing, and evaluating the situation. Data from the 2020-2021 and 2021-2022 school years show that ethnic minority students in primary schools in Son La province still face certain limitations in language proficiency when learning Vietnamese. The level of Vietnamese usage among ethnic minority students outside the classroom is 45%, and at home is only 5%. Based on the current situation, this article aims to propose some solutions to help ethnic minority primary school students in Son La province overcome language barriers, especially in light of the new requirements of the 2025 General Education Program, and to provide educators and teachers with guidance on building and selecting content as well as teaching methods that are more suitable for learners. Keywords: Ethnic Minorities, Primary Students, Language Barrier, General Education Program, Vietnamese Language, Son La Province.

Assessing the Impact of Artificial Intelligence Tools on Employee Productivity: Insights from a Comprehensive Survey Analysis

This study provides a nuanced understanding of AI’s impact on productivity and employment using machine learning models and Bayesian Network Analysis. Data from 233 employees across various industries were analyzed using logistic regression, Random Forest, and XGBoost, with 5-fold cross-validation. The findings reveal that high levels of AI tool usage and integration within organizational workflows significantly enhance productivity, particularly among younger employees. A significant interaction between AI tools usage and integration (β = 0.4319, p < 0.001) further emphasizes the importance of comprehensive AI adoption. Bayesian Network Analysis highlights complex interdependencies between AI usage, innovation, and employee characteristics. This study confirms that strategic AI integration, along with targeted training programs and ethical frameworks, is essential for maximizing AI’s economic potential.

The Influence of Discount Cuts and Buzz Marketing Strategies on Live Sales Through E-commerce on Impulsive Buying Behavior

The level of internet usage in Indonesia is considered very high, encouraging the community to continuously adapt to using technology as a medium for business creation. The utilization of technology in the business field requires business actors to enhance creativity and strategies to influence and attract consumer purchasing interest. This research will explain the influence of discounts and buzz marketing strategies on live sales through e-commerce on impulsive buying behavior, with respondents aged 15-29 who reside in Jakarta. The technique used in the research for sample selection is non-probability sampling with purposive sampling. Data collection in this research was conducted by distributing questionnaires. The research analysis technique used is Smart PLS. Ultimately, the results of this study show that discounts on live sales through e-commerce have a positive but insignificant effect on impulsive buying behavior. Meanwhile, buzz marketing in live sales through e-commerce has a significant positive effect on impulsive buying behavior.

A randomized, placebo-controlled trial of purified anthocyanins on cognitive function in individuals at elevated risk for dementia: Analysis of inflammatory biomarkers toward personalized interventions

BackgroundDementia poses a significant global health challenge. Anthocyanins neutralize free radicals, modulate signaling pathways, inhibit pro-inflammatory genes, and suppress cytokine production and may thus have positive cognitive effects in people at increased risk of dementia. We aim to investigate the effects of purified anthocyanins on cognitive function in people at increased risk of dementia according to their inflammation status based on blood-based inflammatory biomarkers. MethodsThis is a secondary analysis of a 24-week randomized, double-blind, placebo-controlled trial. Cluster analysis was performed to categorize two groups based on their individual inflammatory biomarker profile using multiplex sandwich ELISA for the quantitative measurement of cytokines. Descriptive statistics and longitudinal models assessed cognitive outcomes. The primary comparison was the group difference at week 24 based on a modified intention-to-treat analysis. ResultsCluster analysis revealed two distinct inflammatory biomarker profiles. In Cluster 1 (high levels of inflammation biomarkers), anthocyanin treatment showed a statistically significant improvement on cognitive function compared to placebo at 24 weeks. No significant differences were observed in Cluster 2 (low levels of inflammation biomarkers). The demographic characteristics, cognitive scores, and biomarker distributions were similar between treatment groups at baseline. However, cluster 1 exhibited higher BMI, diabetes prevalence, medication usage, and lower HDL cholesterol levels. ConclusionIndividuals with elevated levels of inflammation markers benefited from anthocyanin treatment to enhance cognitive performance, whereas those with lower levels did not. The anti-inflammatory and antioxidant properties of anthocyanins make them a promising intervention, and future prospective trials in people with increased inflammation are warranted.

Integrated Biomarker Response Emphasizing Neuronal Oxidative Stress and Genotoxicity Induced by Oxamyl in Sprague Dawley Rats: Ameliorative Effect of Ginseng as a Neuroprotective Agent.

Climate change has led to increased and varying pest infestation patterns, triggering a rise in pesticide usage and exposure. The effects of oxamyl, a widely used nematicide in Egypt, encompasses typical signs of carbamate intoxication; nevertheless, long-term effects of oxamyl exposure, particularly on the nervous system, require further elucidation. This study systematically investigated the mechanism and manifestations of repeated subacute exposure to sublethal doses of oxamyl in male SD rats. Data showed a dose-dependent genotoxic effect, manifested as increased bone marrow micronuclei and decreased brain expression of key genes involved in neurogenesis and neuronal development. Coincidently, brain histopathology showed dose-dependent neurodegeneration in various regions, associated with a significant increase in GFAP immunoreactivity, indicative of neuroinflammation. Biochemical examination revealed a typical pattern of cholinesterase inhibition by carbamates in serum and brain tissue, as well as increased oxidative stress markers in the brain such as SOD activity reduction, alongside an increase in NO and MDA. The ability of Ginseng at a 100 mg/Kg dose to ameliorate the effects of oxamyl exposure was investigated. Ginseng use, either as a protective or therapeutic regimen, attenuated the observed genotoxic, neuroinflammatory, and biochemical alterations. Our results indicate that repeated exposure to oxamyl triggers an integrative neurotoxic response, driven by genotoxicity, oxidative stress, and neuroinflammation, that could trigger an increase in neurological and cognitive disorders. These findings emphasize the urgent need for confirmatory translational studies in human subjects to assess these changes and inform policy decisions regarding safe levels of usage and appropriate agricultural and public health practices.

A new insight on efficient ammonia borane dehydrogenation withRu-Imine@Al2O3 catalyst

Ammonia borane is widely recognized as a reliable source of hydrogen. However, for efficiently generate hydrogen from ammonia borane, the use of appropriate catalysts is necessary. Transition metal catalysts, significantly enhance the hydrogen production. In our study, we focused on synthesizing a catalyst, Ru-Imine@Al2O3, by incorporating ruthenium-imine onto the surface of alumina in an ethanoic solution. We conducted this synthesis under ambient conditions. We employed advanced analytical techniques to characterize it. To better understand the structure and composition of catalyst. Notably, this is the first time that Ru-Imine and Ru-Imine@Al2O3 have been used for dehydrogenation of ammonia borane. During our experiments, we found that the Ru-Imine@Al2O3 catalyst exhibited excellent activity in the dehydrogenation process of ammonia borane, releasing hydrogen. We tested different levels of Ru-Imine usage and observed the best performance with 10 % Ru-Imine complex in a 10 mg catalyst. Under these conditions, the catalyst produced 19531 mL H2gcat.−1min−1, at 30.0 ± 1 °C. the catalytic activity of 100 % Ru-Imine was also tested under the specified conditions and produced 14183 mL H2gcat.−1min−1. To gain further insights into the reaction, we thoroughly determined the kinetics and proposed a mechanism for the dehydrogenation process. Our findings revealed that Ru-Imine@Al2O3 catalyzed dehydrogenation of ammonia borane exhibited a lower activation energy (Ea) of 21.9 kJ mol−1. This implies that the reaction can proceed more easily and efficiently with the presence of the catalyst. Furthermore, we assessed the reusability of the catalyst and found that it demonstrated excellent performance even after eight cycles with 100 % conversion of ammonia borane. This highlights the potential of the Ru-Imine@Al2O3 catalyst for repeated use without significant degradation in its activity. These findings contribute to the advancing of hydrogen generation technologies and offer promising prospects for utilizing ammonia borane as a hydrogen source.

Assessing post-Covid-19 Lebanese teachers’ attitudes towards ICT and their level of integration in the classroom in relation to their years of experience

In this technological era, the implementation of Information and Communication Technology (ICT) into the learning environment is impacted by many factors, chief among them are those related to the teachers whose experience and attitude play a key role in the proper integration of technology. This study purports to investigate the effect of teachers’ experience on their attitude towards ICT integration and their level of usage in the classroom. It used a quantitative descriptive method by adopting two surveys (Hernández-Ramos et al., 2014 and Sánchez et al., 2012) as the main instrument for data collection. The survey was administered in four English language private urban schools in Lebanon. This study shows that the teachers hold an overall positive attitude towards ICT integration in the classroom. However, no significant relationship between their attitude and years of experience is identified. While teachers demonstrate a moderate to low ICT usage, a significant negative correlation between their use of ICT in the classroom and their years of experience is evident. These findings are not consistent with the prevalent literature that tends to associate positive attitudes towards technology with higher usage of ICT in different educational settings around the world. Limitations of the study and recommendations for sustainable implementation of ICT in the classroom are provided.

A MILP-based approach to address the production and distribution planning of large industrial gas supply chains

This paper focuses on addressing the Production Routing Problem (PRP) of industrial gas supply chains (SC). The work introduces a Mixed-Integer Linear Programming (MILP) based approach to effectively tackle this challenging problem. The proposed framework aims to increase company profits by optimizing both production and distribution activities simultaneously. For the distribution part, a route generation algorithm is employed to initially generate a set of feasible routes, ensuring that only routes with practical significance are considered. Subsequently, the mathematical model is developed considering only the set of routes generated. The formulation includes decisions associated with plants production levels, plant selection to supply the different consumers, clients to be visited per trip and day, quantity to be delivered and routes to be used. As part of the problem, it is considered that trucks can make several trips per day, as well as trips of several days. To take into account the last feature, the approach accounts for the explicit effect of the lead time on production and distribution decisions. In this way, the work allows for different delivery times for customers included in the same route, according to their inventories and usage levels. The model considers fleet unavailability until they return to the plants after finishing a trip. Finally, two case studies, one motivating and the other industrial size, are presented and solved. The results obtained demonstrate the effectiveness of the proposed approach to solve the case studies in reasonable CPU times.