Many Industrial Internet of Things (IIoT) applications require wireless networks with low power consumption, low latency, and secure communication. The IPv6 over the TSCH mode of IEEE 802.15.4e (IETF ...6TiSCH) standard has been created to fulfill these requirements and provide reliable and efficient communication, specifically in industrial environments. A reliable authentication process is the first step towards the ensuring privacy and security of a wireless IoT network. The IETF Constrained Join Protocol (CoJP) is the standard centralized authentication protocol developed by the IETF 6TiSCH Working Group which is used to manage the node bootstrapping processes through a centralized entity named as Join Registrar/Coordinator (JRC). This process requires the joining nodes to be authenticated via the JRC entity. Centralized authentication within 6TiSCH networks exhibits scalability limitations beyond small-to-medium deployments, necessitating alternative approaches for applications requiring large number of deployed nodes. Using a distributed approach where JRC role is distributed among the nodes within the network can help to mitigate this drawback. In this paper, a node placement method for a decentralized authentication process is introduced to address the scalability challenges of the centralized authentication process in 6TiSCH networks where a heuristic solution that can optimise Proxy-JRC placement has been proposed. Experimental results with 2,3 and 4 number of Proxy-JRC nodes placed by the proposed approach show up to 25% improvement in terms of key update time and up to 22% in terms of power consumption. These results highlight the benefits of employing a distributed key update mechanism to meet low power consumption, low latency, and secure communication requirements in large-scale 6TiSCH networks.
The study aims to explore the effect of the type of higher education institution on students’ engagement. The meta-analyses of multilevel regression coefficients revealed significant relationships ...between the type of higher education institution and student engagement indicators across the years from 2013 to 2019. Comparing different types of higher education institutions with the base category, our findings revealed significant differences in effective teaching practices, discussion with diverse others, and student-faculty interaction consistent throughout the years. These findings are expected to provide insights for institutional administrators, policymakers, and researchers given that student engagement in higher education has become an indicator of quality all around the world.
Education researchers, policy makers, and practitioners have emphasized the role that social-emotional learning and self-regulation play in children’s adjustment and connection to school, ...particularly as they transition from pre-school to kindergarten and the primary grades. A pretest–posttest cluster-randomized efficacy trial of the Social-Emotional Learning Foundations (SELF) curriculum for kindergarten–first-grade students found positive main effects on assessments of self-regulation, social-emotional learning, social-emotional vocabulary, and general behavioral functioning. This study is a secondary analysis using structural equation modeling to explore whether SELF effects on school adjustment were mediated by its effects on language and/or self-regulation–related outcomes. Findings replicated direct effects of treatment but did not support hypothesized mediators. In contrast, direct effects of treatment on measures of competent school functioning and internalizing behavior were mediated by outcome effects on a standardized measure of social-emotional learning competence. Study findings underscore the fundamental importance of social-emotional learning to school success and suggest related measurement issues in social-emotional learning and topics for further research.
Background:
Propensity score analysis (PSA) is a popular method to remove selection bias due to covariates in quasi-experimental designs, but it requires handling of missing data on covariates before ...propensity scores are estimated. Multiple imputation (MI) and single imputation (SI) are approaches to handle missing data in PSA.
Objectives:
The objectives of this study are to review MI-within, MI-across, and SI approaches to handle missing data on covariates prior to PSA, investigate the robustness of MI-across and SI with a Monte Carlo simulation study, and demonstrate the analysis of missing data and PSA with a step-by-step illustrative example.
Research design:
The Monte Carlo simulation study compared strategies to impute missing data in continuous and categorical covariates for estimation of propensity scores. Manipulated conditions included sample size, the number of covariates, the size of the treatment effect, missing data mechanism, and percentage of missing data. Imputation strategies included MI-across and SI by joint modeling or multivariate imputation by chained equations (MICE).
Results:
The results indicated that the MI-across method performed well, and SI also performed adequately with smaller percentages of missing data. The illustrative example demonstrated MI and SI, propensity score estimation, calculation of propensity score weights, covariate balance evaluation, estimation of the average treatment effect on the treated, and sensitivity analysis using data from the National Longitudinal Survey of Youth.
Driving vehicles according to eco-driving principles and techniques have significant impact on decreasing both fuel consumption and carbon dioxide (CO2) emissions. In addition to some kind of ...technical and/or mechanical features brought by today's new generation vehicles, driver behavior is also one of the greatest factors affecting the fuel consumption. Many studies show that the effect of eco-driving education on the drivers loses its impact in long term and there needs some sort of continuous monitoring and/or feedback mechanisms. This kind of driver monitoring becomes very critical especially in fleets composed of heavy-duty vehicles, such as municipality buses, truck fleets, etc. Moreover, in order to adapt behavior to drive more economically, information about instant fuel consumption has to be provided to the driver. Hence, in this paper, we introduce an eco-driving system in which data gathered from the controller area network (CANBus) of public transport vehicles are processed for both comparative and fair evaluation of bus drivers' eco-driving performance. Moreover, in-vehicle components of the system guide the drivers during their trips; provide feedbacks and real-time warnings considering the fuel consumption. Developed system was successfully deployed and evaluated in one of the public metrobus systems used by approximately 250000 passengers every day. Based on the 15-months evaluation period, the results are very promising in the sense that both drivers and operators found the system useful and the system provided fuel saving up to approximately 5% even in the short term of monthly comparisons.
The livestock industry in Türkiye is vital to the country's agricultural sector and economy. In particular, sheep products are an important source of income and livelihood for many Turkish ...smallholder farmers in semi-arid and highland areas. Türkiye is one of the largest sheep producers in the world and its sheep production system is heavily dependent on indigenous breeds. Given the importance of the sheep industry in Türkiye, a systematic literature review on sheep breeding and genetic improvement in the country is needed for the development and optimization of sheep breeding programs using modern approaches, such as genomic selection. Therefore, we conducted a comprehensive literature review on the current characteristics of sheep populations and farms based on the most up-to-date census data and breeding and genetic studies obtained from scientific articles. The number of sheep has increased in recent years, mainly due to the state's policy of supporting livestock farming and the increase in consumer demand for sheep dairy products with high nutritional and health benefits. Most of the genetic studies on indigenous Turkish sheep have been limited to specific traits and breeds. The use of genomics was found to be incipient, with genomic analysis applied to only two major breeds for heritability or genome-wide association studies. The scope of heritability and genome-wide association studies should be expanded to include traits and breeds that have received little or no attention. It is also worth revisiting genetic diversity studies using genome-wide single nucleotide polymorphism markers. Although there was no report of genomic selection in Turkish sheep to date, genomics could contribute to overcoming the difficulties of implementing traditional pedigree-based breeding programs that require accurate pedigree recording. As indigenous sheep breeds are better adapted to the local environmental conditions, the proper use of breeding strategies will contribute to increased income, food security, and reduced environmental footprint in a sustainable manner.
An increasing number of studies have focussed on the neurobiology of schizophrenia (SCH), contributing to a better understanding of this disorder. Prolidase is a metalloprotease found in various ...tissues, which has been associated with the concentrations of proline, a neurotransmitter, in the brain. There is evidence to suggest that elevated proline levels play a role in SCH. The aim of the present study was to compare plasma proline levels in patients with drug-naive first-episode psychosis (FEP) and in those with SCH. Patients diagnosed with FEP (n = 26) and SCH (n = 26) were recruited for this study, in addition to healthy control volunteers (n = 26). Plasma prolidase levels were found to be elevated in the SCH group compared to drug-naive FEP and healthy control groups. This finding indicates that prolidase levels are higher in SCH patients, while levels in patients with drug-naive FEP are similar to those of healthy control. Follow-up studies are needed to provide a better understanding of prolidase in the etiopathogenesis of SCH.
Wireless sensor networks are integral to Industrial Internet of Things applications, enabling efficient data collection and analysis in factories, production facilities, and energy management ...systems. Networks running IETF 6TiSCH protocol enhance these capabilities by offering low power consumption, high reliability, and precise timing. However, ensuring security, data integrity, and authorized access in these networks is critical. This study proposes a lightweight authentication and session key agreement protocol tailored for 6TiSCH networks. This protocol employs XOR operations, personal passwords, and hash functions to authenticate the nodes to the network and secure the link layer communication. The protocol ensures secure network inclusion and user access to nodes while maintaining low power consumption. Quantitative evaluations demonstrate the protocol's effectiveness, achieving a 25% reduction in energy consumption, a 20% reduction in the duration of the authentication process, and a 15% decrease in the total number of bits transmitted compared to existing methods. Tests that are run on Contiki OS using COOJA simulator validate the protocol's performance, confirming its suitability for IIoT applications by ensuring robust security and efficient resource utilization. Furthermore, the proposed scheme's scalability makes it adaptable to a wide range of IIoT scenarios, and its implementation simplicity facilitates easy integration into existing systems. These characteristics underscore the protocol's potential to significantly enhance the security and efficiency of IIoT networks.
Decomposing variables into between and within components are often required in multilevel analysis. This method of decomposition should not ignore possible unreliability of an observed group mean ...(i.e., arithmetic mean) that is due to small cluster sizes and can lead to substantially biased estimates. Adjustment procedures that allow unbiased estimation have been defined and implemented in software for a two-level model. This study shows how to implement a two-stage adjustment procedure in a three-level design. A simulation study showed that the adjustment procedure provides unbiased estimates. To demonstrate how the adjustment procedure can change results in a real data context, an illustration is provided using a set up in which 355 Level-1 units are nested in 93 Level-2 and 19 Level-3 units.
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