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The building sector is a major contributor to the world's energy consumption, exhibiting an ever-increasing trend. Heat losses through the building envelope constitute the most significant factor. Furthermore, the construction process has seen limited technological advancements in recent years, remaining heavily reliant on manual labor. Additive manufacturing emerges as a promising approach, with applications in the building sector on the rise. However, research on the thermal performance of 3D-printed components remains limited. Despite its recent introduction in the construction industry, 3D printing has yet to attain a level of maturity commensurate with other established methods. This paper aims to reduce this gap by analyzing 3D-printed blocks from a heat transfer perspective. The article introduces two key innovations. Firstly, it explores the design of various internal geometries and air gaps aimed at minimizing heat flux exchange between block surfaces. Secondly, it presents an experimental study conducted with a custom-designed setup tailored for testing 3D printed blocks. The blocks are constructed using recyclable plastic material and feature different internal geometries based on hexagonal cells. While the plan size of the cells remains consistent, their vertical structures vary as follows: 1) Block 1: Hexagonal air cavities without horizontal partitions. 2) Block 2: Hexagonal air cavities with three horizontal partitions, dividing the cells vertically into four parts. 3) Block 3: Honeycomb structure characterized by three horizontal partitions and staggering along the vertical axis. Their performance was experimentally evaluated using the Hot Box method, heat flow meter sensors, and infrared thermography. The results demonstrated reductions of up to 11.5 % in terms of thermal transmittance (U-value) with the inclusion of horizontal partitions. Starting from a U-value of 1.22 ± 0.04 W/m2K (Block 1), a transmittance of 1.08 ± 0.04 W/m2K was achieved for the honeycomb structure with horizontal partitions (Block 3).

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The mechanical properties of a coal-rock body were examined through uniaxial compression tests, and the rupture process of the coal-rock body was monitored in real time using a combined acoustic emission (AE) monitoring system and a digital image correlation (DIC) full-field strain measurement system. From a comparison of the mechanical properties of coal and sandstone, clear differences are apparent regarding the uniaxial compressive strength, deformation characteristics, and damage mode; the brittle failure characteristics of the coal samples are also more evident. The change in AE energy reflects the accumulation and release of elastic energy during the rupture process, and the evolution of AE localization points under different stress levels can effectively reflect rupture propagation. Further, the DIC full-field strain measurement method can quantitatively monitor the evolution of the displacement and strain fields at the marking point and surface simultaneously, thereby overcoming the limitations of traditional empirical and qualitative rupture processes. During monitoring, the AE focuses on the internal rupture of the specimen and the DIC focuses on the surface deformation. These complement each other and reflect the rupture process more comprehensively.

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Reliable modeling of oily wastewater emphasizes the paramount importance of sustainable and health-conscious wastewater management practices, which directly aligns with the Sustainable Development Goals (SDG) while also meeting the guidelines of the World Health Organization (WHO). This research explores the efficiency of utilizing polypyrrole-coated ceramic-polymeric membranes to model oily wastewater separation efficiency (SE) and permeate flux (PF) based on established experimental procedures. In this area, computational simulation still needs to be explored. The study developed predictive regression models, including robust linear regression (RLR), stepwise linear regression (SWR) and linear regression (LR) for the ceramic-polymeric porous membrane, aiming to interpret its complex performance across diverse conditions and, thus, develop its utility in oily wastewater treatment applications. Subsequently, a novel, simple average ensemble paradigm was explored to reduce errors and improve prediction skills. Prior to the development of the model, stability and reliability analysis of the data was conducted based on Philip Perron tests with the Bartlett kernel estimation method. The accuracy of the SE exhibited a high consistency, averaging 99.92% with minimal variability (standard deviation of 0.026%), potentially simplifying its prediction compared to PF. The modes were validated and evaluated using metrics like MAE, RMSE, Speed, and MSE, in addition to 2D graphical and cumulative distribution function graphs. The LR model emerged as the best with the lowest RMSE =0.21951, indicating superior prediction accuracy, followed closely by RLR with an RMSE = 0.22359. SWLR, while having the highest RMSE = 0.34573, marked its dominance in prediction speed with 110 observations per second. Notably, the RLR model justified a reduction in error by approximately 35.29% compared to SWLR. Moreover, the training efficiency of the LR model exceeded, demanding a mere 2.9252 s, marking a reduction of about 32.54% compared to SWLR. The improved simple ensemble learning proved merit over the three models regarding error accuracy. This study emphasizes the essential role of soft-computing learning in optimizing the design and performance of ceramic-polymeric membranes.

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The congestion problem has driven many researchers to address it, among other networking issues. In a packet-switched network, congestion is essential; it leads to a high response time to deliver packets due to heavy traffic, which eventually causes packet loss. Hence, congestion control mechanisms are utilized to prevent such cases. Several interesting algorithms are proposed to focus on this dilemma, such as the Self-Clocked Rate Adaptation for Multimedia (SCReAM) designed for interactive real-time video streaming applications. One of the main issues of SCReAM is the high design complexity due to the large size of its documentation and coding. Furthermore, there is a considerable number of parameters that can be adjusted to accomplish the desired performance. This study proposes a guided parameters' tuning approach to assess and optimize the SCReAM algorithm in an emulated 5G environment through a detailed exploration of its parameters. The proposed approach consists of three phases, namely, the initialization phase, the standalone experimentation phase, and the hybrid experimentation phase. In the first phase, we illustrate the method of initializing and implementing the environment, followed by specifying the investigated parameters' settings, testing, and validation. The second phase aims to investigate SCReAM parameters in isolation to identify the effect on the performance in relation to network queue delay, smoothed Round Trip Time (sRTT), and throughput. The final phase discusses the possibility of achieving the optimum performance by combining various sets to provide researchers with clear and explicit guidelines to establish an adequate SCReAM behavior for the desired application. To the best of our knowledge, this is the first study that proposes a preliminary and comprehensive analysis of the SCReAM algorithm. Based on the proposed approach, when L4S/ECN is disabled, we reduced the network queue delay by 63.36% and increased the network throughput by 48.6% as compared to the results generated by the original design. In L4S/ECN-enabled mode, the network queue delay is reduced by 16.17% while the network throughput increased by 93%.

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Due to situational fluidity and intrinsic uncertainty of emergency response, there needs to be a fast vehicle routing algorithm that meets the constraints of the situation, thus the receiving-staging-storing-distributing (RSSD) algorithm was developed. Benchmarking the quality of this satisficing algorithm is important to understand the consequences of not engaging with the NP-Hard task of vehicle routing problem. This benchmarking will inform whether the RSSD algorithm is producing acceptable and consistent solutions to be used in decision support systems for emergency response planning. We devise metrics in the domain space of emergency planning, response, and medical countermeasure dispensing in order to assess the quality of RSSD solutions. We conduct experiments and perform statistical analyses to assess the quality of the RSSD algorithm's solutions compared to the best known solutions for selected capacitated vehicle routing problem (CVRP) benchmark instances. The results of these experiments indicate that even though the RSSD algorithm does not engage with finding the optimal route solutions, it behaves in a consistent manner to the best known solutions across a range of instances and attributes.

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When teachers work with students exhibiting academic failure, they may look to factors outside of instruction such as a student's home life or perceived disability as explanations. Placing the locus of control outside of the instructional context becomes a convenient way to escape culpability for unsatisfactory outcomes. A more functional approach to addressing academic deficits allows educators to determine environmental factors responsible for the lack of progress and then create interventions designed to address these functions of academic failure. Although experimental analyses serve as the gold standard for evaluating functional relations between behavior and environment, educators may not always have the ability to systematically test all behavior-environment relations. Indirect assessments provide one means to develop hypotheses about environment-behavior relations that can then be validated with experimental analyses. In this study, researchers developed an indirect tool (Academic Diagnostic Checklist - Beta; ADC-B) based on the function of academic performance deficits (Daly et al. in School Psychology Review 26:554, 1997) and validated the use of the ADC-B by comparing interventions that were suggested (indicated) and those non-suggested (contraindicated) by the ADC-B. Researchers used the ADC-B with four participants and found that for three of the four participants, the suggested intervention was the most efficacious at improving accuracy with the target skills. One limitation is that we did not evaluate the full technical adequacy of the ADC-B, which should be a focus of future research. Supplementary Information: The online version contains supplementary material available at 10.1007/s10864-023-09511-x.

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Effects of processing and extraction solvents on antioxidant properties and other characteristics were evaluated for ten medicinal plant species originating from two different localities and two production years. A combination of spectroscopic and liquid chromatography techniques possessed data for multivariate statistics. Water, 50% (v/v) ethanol, and dimethyl sulfoxide (DMSO) were compared to select the most suitable solvent for the isolation of functional components from the frozen/dried medicinal plants. DMSO and 50% (v/v) ethanol were evaluated as more efficient for phenolic compounds and colorants extraction, while water was more useful for element extraction. Drying and extraction of herbs with 50% (v/v) ethanol was the most appropriate treatment to ensure a high yield of most compounds. The satisfactory differentiation of herbs (61.8-100%) confirmed the significant effect of the processing, geographical, and seasonal factors on target functional component concentrations. Total phenolic and total flavonoid compounds content, total antioxidant activity expressed as TAA, yellowness, chroma, and browning index were identified as the most important markers for medicinal plant differentiation.

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Polyurethane (PU) has been used in a variety of industries during the past few years due to its exceptional qualities, including strong mechanical strength, good abrasion resistance, toughness, low-temperature flexibility, etc. More specifically, PU is easily "tailored" to satisfy particular requirements. There is a lot of potential for its use in broader applications due to this structure-property link. Ordinary polyurethane items cannot satisfy people's increased demands for comfort, quality, and novelty as living standards rise. The development of functional polyurethane has recently received tremendous commercial and academic attention as a result. In this study, the rheological behavior of a polyurethane elastomer of the PUR (rigid polyurethane) type was examined. The study's specific goal was to examine stress relaxation for various bands of specified strains. We also suggested the use of a modified Kelvin-Voigt model to describe the stress relaxation process from the perspective of the author. For the purpose of verification, materials with two different Shore hardness ratings-80 and 90 ShA, respectively-were chosen. The outcomes made it possible to positively validate the suggested description in a variety of deformations ranging from 50% to 100%.

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The presented scientific study deals with the environmental and energetic aspects concerning application of the experimental fuels in high-powerful engines. This study analyses the most important results from the experimental tests realised on the motorbike engine in the case of two testing regimes: at first using a standardly produced combustion engine and then with the adjusted engine configuration designed in order to improve efficiency of the combustion process. There were tested and compared each other three different engine fuels in framework of the presented research work. The first fuel was the top experimental fuel 4-SGP, which is world-widely applied in the motorbike competitions. The second fuel was the experimental and sustainable fuel, which is called superethanol E-85. This fuel was developed in order to reach the highest power output and the lowest engine gaseous emissions. The third was a standard fuel, which is normally at disposal. Besides that, there were created also the experimental fuel mixtures. Their power output and emissions were tested, too.

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INTRODUCTION: Distracted driving has been linked to multiple driving decrements and is responsible for thousands of motor-vehicle fatalities annually. Most U.S. states have enacted restrictions on cellphone use while driving, the strictest of which prohibit any manual operation of a cellphone while driving. Illinois enacted such a law in 2014. To better understand how this law affected cellphone behaviors while driving, associations between Illinois' handheld phone ban and self-reported talking on handheld, handsfree, and any cellphone (handheld or handsfree) while driving were estimated. METHODS: Data from annual administrations of the Traffic Safety Culture Index from 2012-2017 in Illinois and a set of control states were leveraged. The data were cast into a difference-in-differences (DID) modeling framework, which compared Illinois to control states in terms of pre- to post-intervention changes in the proportion of drivers who self-reported the three outcomes. Separate models for each outcome were fit, and additional models were fit to the subset of drivers who talk on cellphones while driving. RESULTS: In Illinois, the pre- to post-intervention decrease in the drivers' probability of self-reporting talking on a handheld phone was significantly more extreme than that of drivers in control states (DID estimate -0.22; 95% CI -0.31, -0.13). Among drivers who talk on cellphones while driving, those in Illinois exhibited a more extreme increase in the probability of talking on a handsfree phone while driving than those control states (DID estimate 0.13; 95% CI 0.03, 0.23). CONCLUSIONS: These results suggest that Illinois' handheld phone ban reduced talking on handheld phones while driving among study participants. They also corroborate the hypothesis that the ban promoted substitution from handheld to handsfree phones among drivers who talk on the phone while driving. PRACTICAL APPLICATIONS: These findings should encourage other states to enact comprehensive handheld phone bans to improve traffic safety.

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Predicting workload characteristics could help web systems achieve elastic scaling and reliability by optimizing servers' configuration and ensuring Quality of Service, such as increasing or decreasing used resources. However, a successful analysis using a simulation model and recognition and prediction of the behavior of the client presents a challenging task. Furthermore, the network traffic characteristic is a subject of frequent changes in modern web systems and the huge content of system logs makes it a difficult area for data mining research. In this work, we investigate prepared trace contents that are obtained from the benchmark of the web system. The article proposes traffic classification on the web system that is used to find the behavior of client classes. We present a case study involving workload analysis of an online stock trading application that is run in the cloud, and that processes requests from the designed generator. The results show that the proposed analysis could help us better understand the requests scenario and select the values of system and application parameters. Our work is useful for practitioners and researchers of log analysis to enhance service reliability.

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With the outbreak of COVID-19, a large number of medical staffs have invested in the front line of anti-epidemic. Medical protective clothing (MPC) can provide a safe environment for the wearers to block bacteria and viruses. However, nowadays, the thermal performance of MPC on the market is very poor, resulting in the extremely low comfort of the wearer. Some improved MPCs were made of materials, which were not easy to obtain with high cost. Some improved MPCs were lack of thermal comfort experimental data based on real human body. Therefore, this paper proposed a novel MPC with reusable PCM and ventilation. Through simulation and experiment, human comfort of the novel MPC was compared with the other two kinds of MPCs. Five subjects were invited to carried out the comfort tests under three states of motion with three types of MPCs. The results showed the novel MPC with higher cost performance in the effective period had been proved that PPD decreased by 39.5% than the traditional MPC. Besides, the novel MPC could meet the comfort requirements of medical staffs for one shift. Furthermore, the work can provide theoretical methods and basic experimental data for the continuous improvement of the comfort and safety of MPC.

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This study integrates an intersectional framework with data on 15,000 U.S. ninth graders from the High School Longitudinal Study of 2009 to investigate differences in ninth-grade math course placement at the intersection of adolescents' learning disability status, race, and socioeconomic status (SES). Descriptive results support an increased liability perspective, with the negative relationship between a learning disability and math course placement larger for adolescents more privileged in terms of their race and/or SES. Adjusted results suggest that the lower math course placements of youth with learning disabilities are due to cumulative disadvantage rather than disability-related inequities in the transition to high school for youth of diverse racial and socioeconomic backgrounds. In addition to demonstrating the importance of intersectional perspectives, this study provides a roadmap for future studies by introducing the new perspective of increased liability to be used in conjunction with the widely employed perspective of multiple marginalization.

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Though operant learning has been applied to socially significant animal behavior for many years, connections between these practical applications and the basic science that supports them have weakened over time. There is a need for replications and extensions of technologies derived from basic research to applied animal settings, and for practical questions to be taken back to the lab where they can be modeled and studied under controlled conditions before incorporating the results in applied behavior-change research and practice. This special issue highlights ways that behavior analysis can contribute to and support the development of evidence-based applications with animals. Articles in this issue provide context for the relationship between basic research and practice in animal behavior, apply basic principles to animal behavior practice, and investigate practical problems using basic research techniques. Each of these is important for a robust interchange between basic science and practice. Here we comment on the contributions of each article to the literature and identify directions for future research.

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Traditional discussions involving 'basic' and 'applied' behavioral research often focus on the differences, or gaps, between these areas. They take place in different environments, use different methods, ask different questions, and have different objectives. Applied animal behavior is no exception. Focusing on the differences in these areas is to the detriment of a cohesive and complete understanding of animal behavior. This paper instead focuses on the similarities between these two sides, and presents them as a matter of scale. A series of real-life examples experienced by the authors is used to highlight how the skills and knowledge of both the applied and the basic sides are valuable and necessary to not only further both fields independently, but to develop a comprehensive understanding of animal behavior.

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Some of the earliest applications outside the laboratory of principles derived from the experimental analysis of behavior (EAB), such as the pioneering work of Keller and Marian Breland, involved animals. This translational tradition continues to the present as EAB-related behavior principles are applied with increasing frequency to behavior management and training practices with animals in nonlaboratory settings. Such translations, and those populations to which they are applied, benefit from a rigorous experimental analysis of practices that are promulgated in popular outlets. These translations both affirm the generality of those principles and serve as goads for laboratory and field research that can further articulate extant principles, develop new ones, and refine methods of application and assessment. This review considered several areas of basic EAB research and contemporary applied animal behavior (AAB) practices in relation to one another: (1) response establishment and maintenance, (2) response reduction and elimination, (3) chaining and conditioned reinforcement, and (4) discriminative stimulus control. Within each topic, a selection of processes and procedures in both EAB and AAB work were reviewed in relation to one another.

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A novel piezoelectric generator based on soft piezoelectric film consisting of a polyimide (PI) sheet and lead zirconate titanate (PZT) is proposed to generate electric energy under the operating conditions of low-frequency and small-amplitude vibration. The theoretical model and working principle of the piezoelectric generator are discussed in detail. Using ANSYS software, a finite element analysis of the static and modal characteristics of the piezoelectric generator is carried out. Further, the output of the prepared piezoelectric generator is investigated by a home-made experimental platform. Results show that the transient excitation voltage of the generator increases with the increase in load resistance, and the continuous excitation voltage increases first and then remains almost stable. The maximum continuous power produced by the piezoelectric generator is about 4.82 mW. Furthermore, the continuous excitation voltage and power are in accordance with the simulation values when the load resistances are 20 kΩ and 25 kΩ, respectively.

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This is a review of content and method for incorporating the history of the experimental analysis of behavior (EAB) into the EAB course, although the material also could be adapted for any course related to the topics of learning and behavior change, or the history of psychology. Six elements associated with establishing a new discipline are considered as a framework for introducing the history of EAB: the intellectual leader/founding scientist(s), early proponents of the new area who advance and elaborate on the founder's ideas, the cultural context in which the discipline develops, a set of methods, a textbook, and means of communicating with other, similarly inclined scientists. The historical ebb and flow of research and some of the reasons for these shifts are discussed next, with examples of EAB research themes that have shifted over time. Illustrating the history of EAB with specific milestone experiments seems a useful way to both introduce substantive research and its history. To that end, milestone experiments in EAB are discussed. The review ends with considerations about locating historical material within the EAB course.

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Diabetes is a chronic metabolic disorder associated with the accelerated development of macrovascular (atherosclerosis and coronary artery disease) and microvascular complications (nephropathy, retinopathy and neuropathy), which remain the principal cause of mortality and morbidity in this population. Current understanding of cellular and molecular pathways of diabetes-driven vascular complications, as well as therapeutic interventions has arisen from studying disease pathogenesis in animal models. Diabetes-associated vascular complications are multi-faceted, involving the interaction between various cellular and molecular pathways. Thus, the choice of an appropriate animal model to study vascular pathogenesis is important in our quest to identify innovative and mechanism-based targeted therapies to reduce the burden of diabetic complications. Herein, we provide up-to-date information on available mouse models of both Type 1 and Type 2 diabetic vascular complications as well as experimental analysis and research outputs. LINKED ARTICLES: This article is part of a themed issue on Preclinical Models for Cardiovascular disease research (BJP 75th Anniversary). To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v179.5/issuetoc.

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Production of concrete is connected to extensive energy demands, greenhouse gases production or primary sources depletion. Reflecting current economical, social, or environmental trends, there is strong pressure on mitigation these requirements and impacts. The exploitation of secondary- or waste materials in production processes has therefore a great potential which is not related solely to binders but also to fillers. In this light, this paper aims at thorough investigations of concrete mixtures with crushed concrete pavements as partial or full replacement of natural coarse aggregates. The research combines experimental techniques to quantify the influence of the substitution on basic physical, mechanical, and heat/moisture transport/storage parameters. The experimental data obtained are further exploited as input data for computational prediction of coupled heat and moisture transport to assess the influence of the aggregates substitution on hygrothermal performance of the built-in concretes. In the last step, the environmental impacts are assessed. Since the changes in the hygrothermal performance were found to be insignificant (i), the compressive strength were improved by up to 25% (ii) and most of the environmental impact indicators were decreased (iii) at the same time, the findings of the research presented predeterminate such a reuse strategy to wider application and use.