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Copyright of Contemporary Accounting Research is the property of Canadian Academic Accounting Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Spawn is DOE's next-generation tool chain for whole building energy control simulation. Spawn couples traditional imperative load-based envelope modelling with new equation-based modelling of HVAC and controls. Spawn uses EnergyPlus for the former and the Modelica Buildings Library for the latter. Because it leverages the Modelica Buildings Library, Spawn can evaluate advanced energy systems at the building and district scale, including new architectures and controls for heat pump systems with storage, and the coupling of such systems to electrical distribution networks. Spawn's Modelica integration likewise enables it to simulate realistic control sequences and therefore to bridge energy simulation and control implementation workflows. From EnergyPlus, Spawn inherits efficient envelope simulation and the ability to use existing envelope model authoring tools. This paper describes the architecture and implementation of Spawn, which automatically couples Modelica and EnergyPlus for run-time data exchange. This paper closes with examples that illustrate Spawn's modelling and simulation processes.

Natural gas combustion to serve space heating hot water systems causes approximately one third of large commercial building energy use in California. This project evaluated an innovative set of non-proprietary, cost-effective methods to reduce energy consumption and associated emissions from these systems. The project demonstrated 70% natural gas savings and substantial electricity savings in two large office buildings, yielding total utility cost savings of approximately $110,000 (or $0.5/ft²) per year. The project also conducted detailed studies on distribution losses and boiler efficiency in several buildings; measured performance of key components in laboratory tests; gathered and analyzed data from hundreds of buildings to evaluate actual performance of these systems; and provided a public dataset to inform future retrofits, research, and code development. The research also highlighted characteristics that make a building a good candidate for retrofit so these results can be scaled. Market transformation activities included 10 journal and conference publications, policy recommendations and a design guide. Based on these findings and other recent work, the opportunity for similarly large emissions reductions appears to be common within the existing large commercial building stock. The resources provided by this project can aid stakeholders in achieving California’s goals to decarbonize buildings.

Background: Pregnancy with raised renal parameters was considered high risk but the degree of this risk is unclear. Hence the present study was done to study the effect of raised renal parameters among women with preeclampsiaon adverse maternal and fetal outcomes. Methodology: A Case -Control study was conducted among 100 patients of Pre-eclampsia,50 patients of Preeclampsia with raised renal parameters were included in the study group as cases and 50 matched preeclamptic patients with normal renal parameters were chosen as controls for the study. Matching was done with respect to certain variables like age group, gestational age, gravida and associated co-morbid condition (Pre-Eclampsia) to avoid bias, for a period of one year to study the effect of altered renal function test sonmaterna land fetal outcome in preeclampsia. Results: Compared to women in the control group, women in the study group had 3.7 times increased odds of preterm delivery (OR, 3.7; 95% CI, 1.0-15.2) and 2.4 times increased odds of delivery via caesarean section (OR, 2.4; 95% CI, 1.09-5.4). Women in the study group was also associated with two-fold increased odds of low birth weight (OR, 2.1; 95% CI, 0.5-9.6). Raised renal parameters among pre-eclamptic women was not associated with increased risk of maternal death in the present study. Conclusion: Raised / abnormal renal parameters in pregnancy is independently associated with adverse maternal and fetal outcomes when other variables and a comorbid condition (Pre-eclampsia)was controlled by matching. [ABSTRACT FROM AUTHOR]

Simple Summary: Validation of plant pathogens' diagnostic assays requires positive and negative controls. High Throughput Sequencing (HTS) has shown capabilities for detecting multiple pathogens simultaneously. However, accurate pathogen identification from HTS data depends on the bioinformatic pipeline used. There is currently no consensus on the best pipeline, leading to inconsistent results. To address this, standardized artificial HTS datasets are proposed as benchmarks to evaluate the performance of bioinformatic pipelines used in detection scenarios using HTS. These datasets will aid in resolving challenges like unknown sensitivity and specificity of the bioinformatic tool, contributing to advancing plant pathogen detection using HTS. The validation of diagnostic assays in plant pathogen detection is a critical area of research. It requires the use of both negative and positive controls containing a known quantity of the target pathogen, which are crucial elements when calculating analytical sensitivity and specificity, among other diagnostic performance metrics. High Throughput Sequencing (HTS) is a method that allows the simultaneous detection of a theoretically unlimited number of plant pathogens. However, accurately identifying the pathogen from HTS data is directly related to the bioinformatic pipeline utilized and its effectiveness at correctly assigning reads to their associated taxa. To this day, there is no consensus about the pipeline that should be used to detect the pathogens in HTS data, and results often undergo review and scientific evaluation. It is, therefore, imperative to establish HTS resources tailored for evaluating the performance of bioinformatic pipelines utilized in plant pathogen detection. Standardized artificial HTS datasets can be used as a benchmark by allowing users to test their pipelines for various pathogen infection scenarios, some of the most prevalent being multiple infections, low titer pathogens, mutations, and new strains, among others. Having these artificial HTS datasets in the hands of HTS diagnostic assay validators can help resolve challenges encountered when implementing bioinformatics pipelines for routine pathogen detection. Offering these purely artificial HTS datasets as benchmarking tools will significantly advance research on plant pathogen detection using HTS and enable a more robust and standardized evaluation of the bioinformatic methods, thereby enhancing the field of plant pathogen detection. [ABSTRACT FROM AUTHOR]

Shotgun metagenomics is an increasingly cost-effective approach for profiling environmental and host-associated microbial communities. However, due to the complexity of both microbiomes and the molecular techniques required to analyze them, the reliability and representativeness of the results are contingent upon the field, laboratory, and bioinformatic procedures employed. Here, we consider 15 field and laboratory issues that critically impact downstream bioinformatic and statistical data processing, as well as result interpretation, in bacterial shotgun metagenomic studies. The issues we consider encompass intrinsic properties of samples, study design, and laboratory-processing strategies. We identify the links of field and laboratory steps with downstream analytical procedures, explain the means for detecting potential pitfalls, and propose mitigation measures to overcome or minimize their impact in metagenomic studies. We anticipate that our guidelines will assist data scientists in appropriately processing and interpreting their data, while aiding field and laboratory researchers to implement strategies for improving the quality of the generated results. [ABSTRACT FROM AUTHOR]

Interest in automated building analytics, including fault detection and diagnostics has been increasing; however, developers of these solutions have lacked access to ground-truth-validated data across a wide range of weather conditions for algorithm development and performance assessment. This study presents the development, and validation of faulted and fault-free models for air handling units (AHUs) – a common HVAC system design. Detailed models for the single-duct AHU (Modelica) and dual-duct AHU (HVACSIM+) were used to conduct annual simulations, for common sensor, mechanical, and control sequence faults. We report lessons learned during the efforts, including challenges and insights regarding how these simulation models, typically used for design applications, can be purposed to accurately reflect real-world system operational behaviours. Finally, we highlight considerations for researchers and FDD developers who may wish to leverage this dataset to assess the performance of their algorithms, and evolving performance of FDD solutions over time. [ABSTRACT FROM AUTHOR]

Quality assurance and quality control (QA/QC) techniques are critical to analytical chemistry, and thus the analysis of microplastics. Procedural blanks are a key component of QA/QC for quantifying and characterizing background contamination. Although procedural blanks are becoming increasingly common in microplastics research, how researchers acquire a blank and report and/or use blank contamination data varies. Here, we use the results of laboratory procedural blanks from a method evaluation study to inform QA/QC procedures for microplastics quantification and characterization. Suspected microplastic contamination in the procedural blanks, collected by 12 participating laboratories, had between 7 and 511 particles, with a mean of 80 particles per sample (±SD 134). The most common color and morphology reported were black fibers, and the most common size fraction reported was 20-212 μm. The lack of even smaller particles is likely due to limits of detection versus lack of contamination, as very few labs reported particles

Background: The prevalence of metabolic syndrome (MetS) in patients infected with Helicobacter pylori, and the factors associated with it are not well understood. This study evaluates MetS and its associated factors among both H pylori-positive and H pylori-negative individuals in Northeast Ethiopia. Methods: A cross-sectional study was conducted between 1 March 2022 to 30 May 2022. A semi-structured questionnaire was used to collect data on sociodemographic, behavioral, and clinical variables. A total of 228 subjects were randomly selected. Blood and stool samples were collected from each subject to measure fasting blood glucose and lipid profiles, and to identify H. pylori infection. Data were entered into Epi. Data 3.1 and analyzed using SPSS version 25. Logistic regression analysis and the Mann--Whitney U-test were performed to determine associated factors and compare median and interquartile ranges. Results: Of the 228 participants, 114 were H. pylori positive, and 114 were H. pylori negative. Participants (50.9% female) ranged in age from 18 years to 63 years, with a median age of 31 (IQR, 22, 40) years. The overall prevalence of MetS among the participants was 23.2%. We found a statistically significant association between MetS and fasting blood glucose level (AOR, 15.965; 95% CI, 7.605-33.515, p<0.001). Furthermore, there was a statistically significant difference in the median serum levels of low-density lipoprotein cholesterol (p<0.001), triglycerides (p=0.036), systolic blood pressure (<0.001), and total cholesterol (p<0.001) between H. pylori-positive and H. pylori-negative participants. Conclusion: MetS was prevalent among study participants. There was also a statistically significant association between fasting blood sugar and MetS. In addition, systolic blood pressure, total cholesterol, triglycerides, and low-density lipoprotein levels were significantly different between H. pylori-positive and H. pylori-negative individuals. [ABSTRACT FROM AUTHOR]

Domestic heating systems across northern Europe are responsible for a substantial fraction of their countries' carbon footprints. In the UK, the vast majority of home space heating is via natural gas boilers with 'wet' hydronic radiator systems. Most of those use TRVs (thermostatic radiator valves) for micro-zoning, to avoid overheating, improve comfort and save energy. To meet Net Zero targets, 20 million such UK gas systems may be retrofitted with heat pumps. Heat pump system designers and installers are cautious about retaining TRVs in such systems in part because of worries that TRV temperature setbacks that lower heat demand may raise heat pump electricity demand in a "bad setback effect", thus wasting energy. This paper presents a new view of heat pump control and provides the first exploration of this issue through the development of a simple physics-based model. The model tests an installation industry claim about the negative effect of TRVs, and finds that though real it should not apply to typical UK retrofits with weather compensation. The energy efficiency benefits of TRVs for older and partly occupied homes, and to keep bedrooms cooler, remain valid. Comfort-seeking householders and installers should know that setting 'stiff' temperature regulation may invoke the bad setback effect and cost dearly in energy and carbon footprint. [ABSTRACT FROM AUTHOR]

Purpose: Obesity is rising among people with HIV (PLWH), sparking interest in bariatric surgery (BS) for this group. Yet, large-scale comparative research on BS outcomes in PLWH is lacking. Methods: We performed a retrospective, matched cohort analysis in PLWH and HIV uninfected controls. Subjects were retrieved from the Dutch Audit for Treatment of Obesity (DATO) registry. Matching (1:7 ratio) included age (± 5-years), sex, body-mass index (BMI) of ± 3 kg/m2, surgery type, and associated health problems (AHPs) at baseline. The primary endpoint was total weight loss percentage (%TWL) ≥ 20% achieved at 1-year post-BS. Secondary endpoints were cumulative %TWL achieved at 2-years post-BS, a reported remission or improvement in AHPs post-BS, and surgical complications, both at 1-year post-BS. Comparisons were performed using conditional logistic regression. Results: Twenty-seven PLWH and 168 controls were included. At 1-year post-BS, 89% PLWH achieved ≥ 20%TWL, compared to 94% of controls (p = 0.4). Cumulative %TWL at 2-years post-BS were 82% and 92% in PLWH and controls, respectively (p = 0.2). Improvement rates in hypertension and type 2 diabetes mellitus were 50% and 86% in PLWH, versus 87% and 87% in controls. Full remission occurred in 20% and 71% of PLHIV, versus 49% and 44% of controls, respectively. No improvement or remission was observed for dyslipidaemia in PLHIV compared to 54% improvement and 29% remission in controls. Surgical complications were 0% in PLHIV and 13% (n = 21) in controls. Conclusion: Efficacy and safety outcomes of BS were similar between PLWH and controls except for the lack of improvement in dyslipidaemia in PLWH. [ABSTRACT FROM AUTHOR]

Effectively teaching scientific reasoning requires an understanding of the challenges students face when learning these skills. We designed an assessment that measures undergraduate student abilities to form hypotheses, design experiments, and interpret data from experiments in cellular and molecular biology. The assessment uses intermediate-constraint free-response questions with a defined rubric to facilitate use with large classes, while identifying common reasoning errors that may prevent students from becoming proficient at designing and interpreting experiments. The assessment measured a statistically significant improvement in a senior-level biochemistry laboratory course, and a larger improvement between the biochemistry lab students and a separate cohort in a first-year introductory biology lab course. Two common errors were identified for forming hypotheses and using experimental controls. Students frequently constructed a hypothesis that was a restatement of the observation it was supposed to explain. They also often made comparisons to control conditions not included in an experiment. Both errors were most frequent among first-year students, and decreased in frequency as students completed the senior-level biochemistry lab. Further investigation of the absent controls error indicated that difficulties with reasoning about experimental controls may be widespread in undergraduate students. The assessment was a useful instrument for measuring improvement in scientific reasoning at different levels of instruction, and identified errors that can be targeted to improve instruction in the process of science.

Abstract Background Physical active lifestyles are essential throughout growth and maturation and may offer potential preventive and therapeutic benefit in patients with juvenile idiopathic arthritis (JIA). Insufficient physical activity (PA), in contrast, can lead to aggravation of disease-related symptoms. This study aimed to i) examine PA levels in children and adolescents with JIA compared to general population controls and ii) investigate correlates of pronounced physical inactivity in order to identify risk groups for sedentary behaviour. Methods Data from children and adolescents with JIA and population controls aged 3 to 17 years documented in the National Pediatric Rheumatologic Database (NPRD) and the German Health Interview and Examination Survey for Children and Adolescents (KiGGS) were used. Self-reported PA was collected from parents/guardians of children up to 11 years of age or adolescents 12 years of age and older. To compare PA-related data, age- and sex-specific pairwise analyses were conducted considering NPRD/KiGGS participants' data from 2017. Correlates of physical inactivity among patients were identified using a linear regression model. Results Data of 6,297 matched-pairs (mean age 11.2 ± 4.2 years, female 67%, patients’ disease duration 4.5 ± 3.7 years, persistent oligoarthritis 43%) were available for evaluation. Almost 36% of patients aged 3–17 years (vs. 20% of controls) achieved the WHO recommended amount of PA, while PA steadily decreased with age (18% of patients aged ≥ 12 years) and varied between JIA categories. Female adolescents and patients with enthesitis-related arthritis were least likely to achieve the minimum recommended level of PA. Physical inactivity was associated with female sex, higher age at disease onset, longer disease duration, more functional disability (C-HAQ) and higher disease activity (cJADAS-10). Conclusions Depending on JIA category, children and adolescents with JIA were similarly or even more likely to achieve the WHO recommended minimum level of PA compared to general population controls. However, since a large proportion of young JIA patients appear to be insufficiently physically active, engagement in targeted efforts to promote PA is urgently needed.

Many commercial buildings have a vast network of sensors as part of their building automation systems (BAS) that allows opportunities for energy consumption and cost savings by deploying advanced control sequences. However, this resource is often underutilized since BAS are typically programmed with simple control sequences with limited potential to deliver on these opportunities. The recent availability of ASHRAE Guideline 36 (G36) with advanced HVAC control sequences supports control retrofits in existing buildings to unlock much of the savings potential. However, barriers such as the lack of standard naming convention of building assets and data points, proprietary equipment and BAS, and the inherent uniqueness of buildings and their systems prevent building stakeholders from adopting any “plug-and-play” implementation of G36. Instead, control vendors must often undertake the manual and labor-intensive point mapping process to identify a data stream’s functional and spatial relationship within the HVAC system along with other relevant contexts and map it to the new control sequences. The vendor must carry out the point mapping process in each individual building since the mapping is unlikely to port over to another building. Even for the same building, the point mapping process can occur multiple times if various control vendors implement different control retrofits and/or multiple control retrofits happen over the lifecycle of the building. Then, there is the likelihood that G36 control sequences are programmed uniquely to the building, preventing the same implementation from being reused in another. Therefore, this paper presents a field demonstration of how we leveraged the Brick ontology with BACnet, OpenBuildingControl’s Control Description Language (CDL), and open-source support tools to implement scalable and portable advanced building controls. These tools provide standardized semantic descriptions and relationships of the building’s assets and data points (Brick), standardized communication protocol to read from and write to the building’s BAS (BACnet), and standardized code implementations (CDL) of standardized advanced control strategies (G36). We implemented G36’s hot water supply temperature setpoint reset in a Berkeley, CA building for this field demonstration. This field demonstration aims to show how integrating these tools may streamline the deployment of advanced control sequences such as G36 in a consistent manner regardless of differences found across buildings.

Safe autonomous vehicle (AV) operations depend on an accurate perception of the driving environment, which necessitates the use of a variety of sensors. Computational algorithms must then process all of this sensor data, which typically results in a high on-vehicle computational load. For example, existing lane markings are designed for human drivers, can fade over time, and can be contradictory in construction zones, which require specialized sensing and computational processing in an AV. But, this standard process can be avoided if the lane information is simply transmitted directly to the AV. High definition maps and road side units (RSUs) can be used for direct data transmission to the AV, but can be prohibitively expensive to establish and maintain. Additionally, to ensure robust and safe AV operations, more redundancy is beneficial. A cost-effective and passive solution is essential to address this need effectively. In this research, we propose a new infrastructure information source (IIS), chip-enabled raised pavement markers (CERPMs), which provide environmental data to the AV while also decreasing the AV compute load and the associated increase in vehicle energy use. CERPMs are installed in place of traditional ubiquitous raised pavement markers along road lane lines to transmit geospatial information along with the speed limit using long range wide area network (LoRaWAN) protocol directly to nearby vehicles. This information is then compared to the Mobileye commercial off-the-shelf traditional system that uses computer vision processing of lane markings. Our perception subsystem processes the raw data from both CEPRMs and Mobileye to generate a viable path required for a lane centering (LC) application. To evaluate the detection performance of both systems, we consider three test routes with varying conditions. Our results show that the Mobileye system failed to detect lane markings when the road curvature exceeded ± 0.016 m−1. For the steep curvature test scenario, it could only detect lane markings on both sides of the road for just 6.7% of the given test route. On the other hand, the CERPMs transmit the programmed geospatial information to the perception subsystem on the vehicle to generate a reference trajectory required for vehicle control. The CERPMs successfully generated the reference trajectory for vehicle control in all test scenarios. Moreover, the CERPMs can be detected up to 340 m from the vehicle's position. Our overall conclusion is that CERPM technology is viable and that it has the potential to address the operational robustness and energy efficiency concerns plaguing the current generation of AVs. [ABSTRACT FROM AUTHOR]

Summary: DNA contamination can critically confound microbiome studies. Here, we take a systematic approach to review the current literature and investigate the prevalence of contamination controls in phyllosphere microbiome research over the past decade. By utilising systematic review principles for this review, we were able to conduct a thorough investigation, screening 450 articles from three databases for eligibility and extracting data in a controlled and methodical manner. Worryingly, we observed a surprisingly low usage of both positive and negative contamination controls in phyllosphere research. As a result, we propose a set of minimum standards to combat the effects of contamination in future phyllosphere research. [ABSTRACT FROM AUTHOR]

Background: Low-level physical activity (LLPA) is crucial for the well-being of adults living with HIV (PLWHs). However, many do not engage in enough physical activity, leading to adverse health outcomes. Identifying the determinants of LLPA can aid in developing effective interventions. Despite this, Ethiopia lacks evidence on this topic. This study aimed to identify predictors of LLPA among PLWHs in the Gedeo zone, located in southern Ethiopia. Methods: An unmatched case-control study was conducted on PLWHs in the Gedeo zone who visited two hospitals and healthcare institutions between December 29th, 2017 and January 22nd, 2019. Respondents were classified into three categories based on their total physical activity levels: high, moderate, and low. Cases were defined as those meeting the criteria for LLPA, while controls were those who did not fall under the cases category. Data was collected using the WHO Stepwise surveillance tool and analyzed using Epidata v3.1 templates and SPSS v22. Predictor variables with a P-value < 0.25 in bivariable analysis and < 0.05 with a 95% confidence interval in multivariable analysis were selected. Results: The study involved 633 HIV-positive adults, with a response rate of 92.41%. Most participants were under 34 years old, with an average age of 36.47±(9.055) for cases and 36.38±(8.389) for controls. The multivariable analysis revealed that educational status (AOR = 4.85, P = 0.02, 95%CI (1.28–18.44)), sex (AOR = 0.24, P = 0.04, 95%CI (0.07–0.90)), duration on ART being exposed for 1–4 Years (AOR = 0.12, P < 0.001, 95%CI (0.03–0.44)) and being exposed for 5–9 Years (AOR = 0.03, P < 0.001, 95%CI (0.01–0.16)), and former alcohol use (AOR = 0.11, P < 0.01, 95%CI (0.02–0.56) were significant predictors of LLPA performance. Conclusions: The study concluded that educational status, sex, ART duration, and past alcohol use are key determinants of LLPA performance among PLWHs in southern Ethiopia. This suggests that policymakers should implement public health campaigns to promote healthy habits, particularly low-level physical activity, among PLWHs. [ABSTRACT FROM AUTHOR]

Copyright of Enfermería Investiga: Investigaciin, Vinculación, Docencia y Gestiin is the property of Revista Enfermeria Investiga and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Soft robotics are attractive to researchers and developers due to their potential for biomimicry applications across a myriad of fields, including biomedicine (e.g., surgery), the film industry (e.g., animatronics), ecology (e.g., physical 'animats'), human–robot interactions (e.g., social robots), and others. In contrast to their rigid counterparts, soft robotics offer obvious actuation benefits, including their many degrees of freedom in motion and their potential to mimic living organisms. Many material systems have been proposed and used for soft robotic applications, involving soft actuators, sensors, and generators. This review focuses on dielectric elastomer (DE)-based actuators, which are more general electro-active polymer (EAP) smart materials. EAP-based soft robots are very attractive for various reasons: (a) energy can be efficiently (and readily) stored in electrical form; (b) both power and information can be transferred rapidly via electrical phenomena; (c) computations using electronic means are readily available. Due to their potential and benefits, DE-based actuators are attractive to researchers and developers from multiple fields. This review aims to (1) provide non-experts with an "easy-to-follow" survey of the most important aspects and challenges to consider when implementing DE-based soft actuators, and (2) emphasize current solutions and challenges related to the materials, controls, and portability of DE-based soft-actuator systems. First, we start with some fundamental functions, applications, and configurations; then, we review the material models and their selection. After, we outline material limitations and challenges along with some thermo-mechano-chemical treatments to overcome some of those limitations. Finally, we outline some of the control schemes, including modern techniques, and suggest using rewritable hardware for faster and more adaptive controls. [ABSTRACT FROM AUTHOR]

Background: Physical active lifestyles are essential throughout growth and maturation and may offer potential preventive and therapeutic benefit in patients with juvenile idiopathic arthritis (JIA). Insufficient physical activity (PA), in contrast, can lead to aggravation of disease-related symptoms. This study aimed to i) examine PA levels in children and adolescents with JIA compared to general population controls and ii) investigate correlates of pronounced physical inactivity in order to identify risk groups for sedentary behaviour. Methods: Data from children and adolescents with JIA and population controls aged 3 to 17 years documented in the National Pediatric Rheumatologic Database (NPRD) and the German Health Interview and Examination Survey for Children and Adolescents (KiGGS) were used. Self-reported PA was collected from parents/guardians of children up to 11 years of age or adolescents 12 years of age and older. To compare PA-related data, age- and sex-specific pairwise analyses were conducted considering NPRD/KiGGS participants' data from 2017. Correlates of physical inactivity among patients were identified using a linear regression model. Results: Data of 6,297 matched-pairs (mean age 11.2 ± 4.2 years, female 67%, patients' disease duration 4.5 ± 3.7 years, persistent oligoarthritis 43%) were available for evaluation. Almost 36% of patients aged 3–17 years (vs. 20% of controls) achieved the WHO recommended amount of PA, while PA steadily decreased with age (18% of patients aged ≥ 12 years) and varied between JIA categories. Female adolescents and patients with enthesitis-related arthritis were least likely to achieve the minimum recommended level of PA. Physical inactivity was associated with female sex, higher age at disease onset, longer disease duration, more functional disability (C-HAQ) and higher disease activity (cJADAS-10). Conclusions: Depending on JIA category, children and adolescents with JIA were similarly or even more likely to achieve the WHO recommended minimum level of PA compared to general population controls. However, since a large proportion of young JIA patients appear to be insufficiently physically active, engagement in targeted efforts to promote PA is urgently needed. [ABSTRACT FROM AUTHOR]

Background: Substance use is prevalent among people with mental health issues, and patients with psychosis are more likely to use and misuse substances than the general population. Despite extensive research on substance abuse among the general public in Kenya, there is a scarcity of data comparing substance use among people with and without psychosis. This study investigates the association between psychosis and various substances in Kenya. Methods: This study utilized data from the Neuro-GAP Psychosis Case-Control Study between April 2018 and December 2022. The KEMRI-Wellcome Trust Research Programme recruited participants from various sites in Kenya, including Kilifi County, Malindi Sub-County, Port Reitz and Coast General Provincial Hospitals, and Moi Teaching and Referral Hospital, as well as affiliated sites in Webuye, Kapenguria, Kitale, Kapsabet, and Iten Kakamega. The collected data included sociodemographic information, substance use, and clinical diagnosis. We used the summary measures of frequency (percentages) and median (interquartile range) to describe the categorical and continuous data, respectively. We examined the association between categorical variables related to psychosis using the chi-square test. Logistic regression models were used to assess the factors associated with the odds of substance use, considering all relevant sociodemographic variables. Results: We assessed a total of 4,415 cases and 3,940 controls. Except for alcohol consumption (p-value=0.41), all forms of substance use showed statistically significant differences between the case and control groups. Cases had 16% higher odds of using any substance than controls (aOR: 1.16, 95%CI: 1.05-1.28, p=0.005). Moreover, males were 3.95 times more likely to use any substance than females (aOR:3.95; 95%CI: 3.43-4.56). All the categories of living arrangements were protective against substance use. Conclusion: The findings of this study suggest that psychotic illnesses are associated with an increased likelihood of using various substances. These findings are consistent with those of previous studies; however, it is crucial to investigate further the potential for reverse causality between psychosis and substance abuse using genetically informed methods. [ABSTRACT FROM AUTHOR]

The study aims to highlight human humanity's controls and purposes by identifying their inherent manifestations from prophetic Sunni sources. It also identifies several controls on human responsibility and purposes through Al-Ahadith Alsahihyn, emphasizing the importance of authentic Sunni sources in their preservation and control. To achieve its objectives, the study followed the collective approach, based on the graduation of the prophetic texts under study collected and selected from the Bukhari and Muslim health as the most important codes of the perceived prophetic year. The study also used the extractive analytical approach: the study of prophetic conversations on human disciplines, purposes, and analysis, to address precise values. The study found several findings, most notably the diversity of human responsibility controls and their multiplicity in the prophetic year. Religious aspects, including social aspects, Islam's desire to form an integrated Islamic personality in all spheres of its life; the study also found the essential purpose of human humanity in the prophetic year, including achieving the goal for which it was created: God's worship is blessed and uplifting, realizing the principle of exclusion in the architecture of the universe and utilizing its treasures. [ABSTRACT FROM AUTHOR]

Triple Entry Accounting (TEA) provides an opportunity for fundamental change in accounting. TEA is a foundational development of Blockchain technology, which is considered a pillar of the Fourth Industrial Revolution. Nevertheless, in order to augment its impact, TEA should be integrated with other systems. This paper aims to examine the relationship of TEA with system integration (SI) and how it can affect integration. This study reviews the SI literature in the context of accounting, examines how the literature on TEA has evolved over the years, and finally contributes to the analysis of how TEA is related to integration. A key theme is the connection of accounting controls and system integration. The methodology of the four design principles of control in system integration is adopted. Transparency is the main perspective of these principles. It was found that TEA promotes transparency, reduces the risk of fraud, and facilitates system integration. [ABSTRACT FROM AUTHOR]

BackgroundThe prevalence of metabolic syndrome (MetS) in patients infected with Helicobacter pylori, and the factors associated with it are not well understood. This study evaluates MetS and its associated factors among both H pylori-positive and H pylori-negative individuals in Northeast Ethiopia.MethodsA cross-sectional study was conducted between 1 March 2022 to 30 May 2022. A semi-structured questionnaire was used to collect data on sociodemographic, behavioral, and clinical variables. A total of 228 subjects were randomly selected. Blood and stool samples were collected from each subject to measure fasting blood glucose and lipid profiles, and to identify H. pylori infection. Data were entered into Epi. Data 3.1 and analyzed using SPSS version 25. Logistic regression analysis and the Mann–Whitney U-test were performed to determine associated factors and compare median and interquartile ranges.ResultsOf the 228 participants, 114 were H. pylori positive, and 114 were H. pylori negative. Participants (50.9% female) ranged in age from 18 years to 63 years, with a median age of 31 (IQR, 22, 40) years. The overall prevalence of MetS among the participants was 23.2%. We found a statistically significant association between MetS and fasting blood glucose level (AOR, 15.965; 95% CI, 7.605–33.515, p

The validation of diagnostic assays in plant pathogen detection is a critical area of research. It requires the use of both negative and positive controls containing a known quantity of the target pathogen, which are crucial elements when calculating analytical sensitivity and specificity, among other diagnostic performance metrics. High Throughput Sequencing (HTS) is a method that allows the simultaneous detection of a theoretically unlimited number of plant pathogens. However, accurately identifying the pathogen from HTS data is directly related to the bioinformatic pipeline utilized and its effectiveness at correctly assigning reads to their associated taxa. To this day, there is no consensus about the pipeline that should be used to detect the pathogens in HTS data, and results often undergo review and scientific evaluation. It is, therefore, imperative to establish HTS resources tailored for evaluating the performance of bioinformatic pipelines utilized in plant pathogen detection. Standardized artificial HTS datasets can be used as a benchmark by allowing users to test their pipelines for various pathogen infection scenarios, some of the most prevalent being multiple infections, low titer pathogens, mutations, and new strains, among others. Having these artificial HTS datasets in the hands of HTS diagnostic assay validators can help resolve challenges encountered when implementing bioinformatics pipelines for routine pathogen detection. Offering these purely artificial HTS datasets as benchmarking tools will significantly advance research on plant pathogen detection using HTS and enable a more robust and standardized evaluation of the bioinformatic methods, thereby enhancing the field of plant pathogen detection.

People typically enhance their online personas by sharing favourable personal information. Nevertheless, sharing of unfavourable information about oneself still occurs and is essential in some online contexts (e.g. allowing negative reviews). It remains unclear why people reveal potentially damaging information. We conducted an online experiment ($N = 462$N=462) to explore the effects of feedback properties and individual characteristics on online information sharing in two contexts (social and socioeconomic) where personal ratings are essential. We allowed users to conceal their personal rating if it dropped below a threshold. The context was the primary determinant of the threshold users chose. Control availability and feedback content triggered additional considerations and caused some users to change their (non)disclosure choices. However, many users relied on their priors (experience, assumptions) rather than on new information. Our findings show how people may fail to identify the impact of nondisclosure, which may signal undesirable information to others. These findings challenge the reliance on holding users solely accountable for their ‘informedness’ vis-à-vis disclosure of their personal information. [ABSTRACT FROM AUTHOR]

Conventional household refrigerators consist of a motor-driven compressor, evaporator, condenser, and expansion valve. To determine the optimal operation strategies of refrigerators, it is essential to investigate the overall system performance, using an appropriate simulator. This study proposed a data-driven simulator based on engineering features and machine learning algorithms for conventional household refrigerators. The most correlated variables for identifying the indoor temperature of refrigerators were identified using variable importance, and these were revealed to be the circulation fan speed, compressor operation status, and refrigerant flow direction. A data-driven simulator was constructed using Bayesian calibration, which considers the important variables, combined with a straightforward heat balance equation. The Markov Chain Monte Carlo approach was used to simultaneously calibrate three coefficients on the critical variables based on the heat balancing equation on each time step, which is consistent with the actual temperature of the container. The results revealed that the proposed approach (equation-based Bayesian calibration outperforms) standard machine learning algorithms, such as linear regression and random forest models, by 38.5%. Additionally, compared to the typical numerical analysis method, it can reduce the delivery time and effort required to develop a reliable simulator for household refrigerators. [ABSTRACT FROM AUTHOR]

In this paper, we study the evasion game of high speed evader involving two pursuers and a single evader with geometric constraints on the control parameters of the players in the plane. The game is described by linear equations. Evasion is said to be possible if the state of the evader doesn’t coincide with the state of any pursuer for all time. We construct an evasion strategy for the evader which ensure completion the evasion game for any initial positions of players. In addition, we introduce a new concept of approach times and demonstrate that the number of approach times does not exceed 3. [ABSTRACT FROM AUTHOR]

Currently, additive manufacturing is utilized to fabricate many different actuators suited for soft robots. However, an effective controller paradigm is essential to benefit from the advantages of soft robots in terms of power consumption, production costs, weight, and safety while operating near living systems. In this work, an artificial muscle is additively manufactured with soft silicone elastomer material capable of demonstrating several levels of stiffness. The 3D‐printed muscle is equipped with carbon fibers to receive a stimulus signal and develop a programmable joint that can present different stiffnesses. A nonlinear controller is developed to autonomously control the variable stiffness joint based on a reinforcement learning algorithm. The controller exhibits a slight increase in settling time; however, it demonstrates a decrease in fluctuation amplitude by 33% and a substantial reduction in power consumption by 41% in comparison to the optimized proportional integral derivative controller. At the same time, it is adaptable to and reliable in new conditions. The variable stiffness muscle is also used as a controllable mechanism to suppress the low frequency vibration. The study shows that the muscle can successfully attenuate the vibration autonomously when it is increased. [ABSTRACT FROM AUTHOR]

Industrial pilot projects often rely on proprietary and expensive electronic hardware to control and monitor experiments. This raises costs and retards innovation. Open-source hardware tools exist for implementing these processes individually; however, they are not easily integrated with other designs. The Broadly Reconfigurable and Expandable Automation Device (BREAD) is a framework that provides many open-source devices which can be connected to create more complex data acquisition and control systems. This article explores the feasibility of using BREAD plug-and-play open hardware to quickly design and test monitoring and control electronics for an industrial materials processing prototype pyrolysis reactor. Generally, pilot-scale pyrolysis plants are expensive custom designed systems. The plug-and-play prototype approach was first tested by connecting it to the pyrolysis reactor and ensuring that it can measure temperature and actuate heaters and a stirring motor. Next, a single circuit board system was created and tested using the designs from the BREAD prototype to reduce the number of microcontrollers required. Both open-source control systems were capable of reliably running the pyrolysis reactor continuously, achieving equivalent performance to a state-of-the-art commercial controller with a ten-fold reduction in the overall cost of control. Open-source, plug-and-play hardware provides a reliable avenue for researchers to quickly develop data acquisition and control electronics for industrial-scale experiments. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Al-Anbar University for Islamic Sciences is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

For brain–computer interfaces, a variety of technologies and applications already exist. However, current approaches use visual evoked potentials (VEP) only as action triggers or in combination with other input technologies. This paper shows that the losing visually evoked potentials after looking away from a stimulus is a reliable temporal parameter. The associated latency can be used to control time-varying variables using the VEP. In this context, we introduced VEP interaction elements (VEP widgets) for a value input of numbers, which can be applied in various ways and is purely based on VEP technology. We carried out a user study in a desktop as well as in a virtual reality setting. The results for both settings showed that the temporal control approach using latency correction could be applied to the input of values using the proposed VEP widgets. Even though value input is not very accurate under untrained conditions, users could input numerical values. Our concept of applying latency correction to VEP widgets is not limited to the input of numbers. [ABSTRACT FROM AUTHOR]

Polymetallic nodules (nodules) are a predominant deep-sea mineral resource due to theirenrichment with critical metals, such as Co, Ni, and Cu, and rare earth elements (REEs). The loose and porous nature of nodules contributes to their adsorption and enrichment in trace metals from seawater and pore water. Consequently, the specific surface area (SSA) of nodules is a key factor requiring further study. However, controls on the SSA of nodules with various genetic types remain poorly characterized. This study aimed to investigate controls on nodule SSA by analyzing the transition metals, REEs, mineralogy, and SSA of nodules recovered from basins in the Atlantic, Indian, and Pacific oceans, including the Northwest Pacific Basin (NPB), Bauer Basin (BB), Tiki Basin (TB), Wharton Basin (WB), Central Indian Basin (CIB), and Angola Basin (AB). Nodule SSAs were compared among the various basins by calculating the BET SSA (based on the equation proposed by Brunauer, Emmett, and Teller, 1938). The results suggest thatnodules from the PNB, WB, CIB, and AB are mainly hydrogenetic, and those nodules have a relatively high SSA, high Co, low Ni and Cu, positive Ce anomalies, and low X-ray diffraction (XRD) intensities at ~10 Å. The nodules from the BB and TB are mainly diagenetic in origin, characterized by a relatively low SSA, low Co, high Ni and Cu, negative Ce anomalies, and high XRD intensities at ~10 Å. The SSAs of nodules were significantly positively correlated with Co, δCe, and light REEs (LREEs), and negatively correlated with the XRD intensity at ~10 Å, Ni, and Cu. The SSAs of nodules from the NPB ranged from 329.440 m2/g to 418.711 m2/g, comparable to the SSAs of Co-rich crusts on seamounts. This study proposes that nodule SAA is regulated by nodule genesis and that hydrogenetic nodules have a higher SSA. [ABSTRACT FROM AUTHOR]

BackgroundSubstance use is prevalent among people with mental health issues, and patients with psychosis are more likely to use and misuse substances than the general population. Despite extensive research on substance abuse among the general public in Kenya, there is a scarcity of data comparing substance use among people with and without psychosis. This study investigates the association between psychosis and various substances in Kenya.MethodsThis study utilized data from the Neuro-GAP Psychosis Case-Control Study between April 2018 and December 2022. The KEMRI-Wellcome Trust Research Programme recruited participants from various sites in Kenya, including Kilifi County, Malindi Sub-County, Port Reitz and Coast General Provincial Hospitals, and Moi Teaching and Referral Hospital, as well as affiliated sites in Webuye, Kapenguria, Kitale, Kapsabet, and Iten Kakamega. The collected data included sociodemographic information, substance use, and clinical diagnosis. We used the summary measures of frequency (percentages) and median (interquartile range) to describe the categorical and continuous data, respectively. We examined the association between categorical variables related to psychosis using the chi-square test. Logistic regression models were used to assess the factors associated with the odds of substance use, considering all relevant sociodemographic variables.ResultsWe assessed a total of 4,415 cases and 3,940 controls. Except for alcohol consumption (p-value=0.41), all forms of substance use showed statistically significant differences between the case and control groups. Cases had 16% higher odds of using any substance than controls (aOR: 1.16, 95%CI: 1.05-1.28, p=0.005). Moreover, males were 3.95 times more likely to use any substance than females (aOR:3.95; 95%CI: 3.43-4.56). All the categories of living arrangements were protective against substance use.ConclusionThe findings of this study suggest that psychotic illnesses are associated with an increased likelihood of using various substances. These findings are consistent with those of previous studies; however, it is crucial to investigate further the potential for reverse causality between psychosis and substance abuse using genetically informed methods.

Development of new building HVAC control algorithms has grown due to needs for energy efficiency and operational flexibility. However, case studies demonstrating new algorithms are largely individualized, making algorithm performance difficult to compare directly. In addition, the effort and expertise required to implement case studies in real or simulated buildings limits rapid prototyping potential. Therefore, this paper presents the Building Optimization Testing Framework (BOPTEST) and associated software for simulation-based benchmarking of building HVAC control algorithms. A containerized run-time environment (RTE) enables rapid, repeatable deployment of common building emulators representing different system types. Emulators use Modelica to represent realistic physical dynamics, embed baseline control, and enable overwriting supervisory and local-loop control signals. Finally, a common set of key performance indicators are calculated within the RTE and reported to the user. This paper details the design and implementation of software and demonstrates its usage to benchmark a Model Predictive Control strategy.

This study examined the use of zoned ventilation systems using a coupled CONTAM/ EnergyPlus model for new California dwellings. Several smart control strategies were developed with a target of halving ventilation-related energy use, largely through reducing dwelling ventilation rates based on zone occupancy. The controls were evaluated based on the annual energy consumption relative to continuously operating non-zoned, code-compliant mechanical ventilation systems. The systems were also evaluated from an indoor air quality perspective using the equivalency approach, where the annual personal concentration of a contaminant for a control strategy is compared to the personal concentration that would have occurred using a continuously operating, non-zoned system. Individual occupant personal concentrations were calculated for the following contaminants of concern: moisture, CO2, particles, and a generic contaminant. Zonal controls that saved energy by reducing outside airflow achieved typical reductions in ventilation-related energy of 10% to 30%, compared to the 7% savings from the unzoned control. However, this was at the expense of increased personal concentrations for some contaminants in most cases. In addition, care is required in the design and evaluation of zonal controls, because control strategies may reduce exposure to some contaminants, while increasing exposure to others.

This study focuses on developing a safe workplace for agricultural tractor drivers and recommending the optimum location for tractor control. Thirteen anthropometric body dimensions of 8,025 Indian male agricultural workers were considered for developing reach envelopes for hand- and foot-operated controls. The optimum reach for hand controls is in the range of 456 to 700 mm forward and 265 to 492 mm above the seat reference point. Similarly, for foot-operated control, the foot could reach within the range 429 to 897 mm forward and 367 mm below, and 30 mm above the seat reference point. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Science & Knowledge Horizons is the property of Journal of Science & Knowledge Horizons and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)