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Abstract The role of rare non-coding variation in complex human phenotypes is still largely unknown. To elucidate the impact of rare variants in regulatory elements, we performed a whole-genome sequencing association analysis for height using 333,100 individuals from three datasets: UK Biobank (N = 200,003), TOPMed (N = 87,652) and All of Us (N = 45,445). We performed rare (

ABSTRACT The pathogenesis of COVID-19 is associated with a hyperinflammatory immune response. Monocytes and macrophages play a central role in this hyperinflammatory response to SARS-CoV-2. NLRP3 inflammasome activation has been observed in monocytes of patients with COVID-19, but the mechanism and consequences of inflammasome activation require further investigation. In this study, we inoculated a macrophage-like THP-1 cell line, primary differentiated human nasal epithelial cell (hNEC) cultures, and primary monocytes with SARS-CoV-2. We found that the activation of the NLRP3 inflammasome in macrophages does not rely on viral replication, receptor-mediated entry, or actin-dependent entry. SARS-CoV-2 productively infected hNEC cultures without triggering the production of inflammasome cytokines IL-18 and IL-1β. Importantly, these cytokines did not inhibit viral replication in hNEC cultures. SARS-CoV-2 inoculation of primary monocytes led to inflammasome activation and induced a macrophage phenotype in these cells. Monocytic cells from bronchoalveolar lavage (BAL) fluid, but not from peripheral blood, of patients with COVID-19, showed evidence of inflammasome activation, expressed the proinflammatory marker CD11b, and displayed oxidative burst. These findings highlight the central role of activated macrophages, as a result of direct viral sensing, in COVID-19 and support the inhibition of IL-1β and IL-18 as potential therapeutic strategies to reduce immunopathology without increasing viral replication.IMPORTANCEInflammasome activation is associated with severe COVID-19. The impact of inflammasome activation on viral replication and mechanistic details of this activation are not clarified. This study advances our understanding of the role of inflammasome activation in macrophages by identifying TLR2, NLRP3, ASC, and caspase-1 as dependent factors in this activation. Further, it highlights that SARS-CoV-2 inflammasome activation is not a feature of nasal epithelial cells but rather activation of bystander macrophages in the airway. Finally, we demonstrate that two pro inflammatory cytokines produced by inflammasome activation, IL-18 and IL-1β, do not restrict viral replication and are potential targets to ameliorate pathological inflammation in severe COVID-19.

Abstract Background Adults with sickle cell disease (SCD) suffer early mortality and high morbidity. Many are not affiliated with SCD centers, defined as no ambulatory visit with a SCD specialist in 2 years. Negative social determinants of health (SDOH) can impair access to care. Hypothesis: Negative SDOH are more likely to be experienced by unaffiliated adults than adults who regularly receive expert SCD care. Methods Cross-sectional analysis of the SCD Implementation Consortium (SCDIC) Registry, a convenience sample at 8 academic SCD centers in 2017–2019. A Distressed Communities Index (DCI) score was assigned to each registry member’s zip code. Insurance status and other barriers to care were self-reported. Most patients were enrolled in the clinic or hospital setting. Results The SCDIC Registry enrolled 288 Unaffiliated and 2110 Affiliated SCD patients, ages 15-45y. The highest DCI quintile accounted for 39% of both Unaffiliated and Affiliated patients. Lack of health insurance was reported by 19% of Unaffiliated versus 7% of Affiliated patients. The most frequently selected barriers to care for both groups were “previous bad experience with the healthcare system” (40%) and “Worry about Cost” (17%). SCD co-morbidities had no straightforward trend of association with Unaffiliated status. The 8 sites’ results varied. Conclusion The DCI economic measure of SDOH was not associated with Unaffiliated status of patients recruited in the health care delivery setting. SCDIC Registrants reside in more distressed communities than other Americans. Other SDOH themes of affordability and negative experiences might contribute to Unaffiliated status. Recruiting Unaffiliated SCD patients to care might benefit from systems adopting value-based patient-centered solutions.

The public release of ChatGPT and other generative AI chatbot technologies has been accompanied by questions about how academic integrity and student cheating behaviors will be impacted. We analyzed anonymous survey data from three high schools to see if self-reported cheating numbers changed following the introduction of ChatGPT and similar technologies. This survey data set is unique in that data on cheating had been collected with this set of schools both before and after November 2022, when ChatGPT was publicly released and drew attention to these educational concerns. The results suggested that cheating behaviors remained relatively stable after the introduction of this current generation of generative AI chatbot technology. However, some changes in reported behaviors differed depending on the type of cheating (social cheating, AI-related cheating, etc.). Additional survey questions about high school students’ AI chatbot usage and the perceived allowability of such technology revealed mixed opinions on the acceptability of using AI for various academic-related tasks. Most students did not think that using a chatbot to produce an entire paper or complete an entire assignment should be allowable. However, there was support for using AI chatbots to help students to start on assignments and papers and to help explain new concepts to them.

Relationships between peak discharges and catchment size (e.g., flood scaling) in a catchment have the potential to support new river flood forecasting approaches but have not been tested in tropical regions. This study determined flood scaling relationships between peak discharge and nested drainage areas in the La Sierra catchment (Mexico). A statistical power law equation was applied to selected rainfall–runoff events that occurred between 2012 and 2015. Variations in flood scaling parameters were determined in relation to catchment descriptors and processes for peak downstream discharge estimation. Similar to studies in humid temperate regions, the results reveal the existence of log-linear relationships between the intercept (α) and exponent (θ) parameter values and the log–log power–law relationships between (α) and the peak discharge observed from the smallest headwater catchments. The flood parameter values obtained were then factored into the scaling equation (QP = αAθ) and successfully predicted downstream flood peaks, especially highly recurrent flood events. The findings contribute to a better understanding of the nature of flood wave generation and support the development of new flood forecasting approaches in unregulated catchments suitable for non-stationarity in hydrological processes with climate change. HIGHLIGHTS Peak discharge in the La Sierra catchment follows a power–law relationship, similar to humid temperate regions.; Log-linear and log–log relationships can be used to estimate flood parameters and peak downstream discharge especially for frequent events.;

This manuscript proposes and describes an on-chip power meter for photo voltaic power generation aimed at portable systems. The power meter provides the average measure for Maximum PowerPoint Tracking in DC-DC converters. The integrated chip power meter estimates the average current consumption using the DC-DC control system’s discrete-time nature. The power meter synthesis in a 65nm CMOS process explores the implementation with a simple structure and the theoretical considerations for real power measurement. The experimental results with 1.2 Volts in bias conditions consume 5 percent of the overall DC-DC control system with the possible application into systems with alternative energy transducers.

Software quality is critical, as low quality, or “Code smell,” increases technical debt and maintenance costs. There is a timely need for a collaborative model that detects and manages code smells by learning from diverse and distributed data sources while respecting privacy and providing a scalable solution for continuously integrating new patterns and practices in code quality management. However, the current literature is still missing such capabilities. This paper addresses the previous challenges by proposing a Federated Learning Code Smell Detection (FedCSD) approach, specifically targeting “God Class,” to enable organizations to train distributed ML models while safeguarding data privacy collaboratively. We conduct experiments using manually validated datasets to detect and analyze code smell scenarios to validate our approach. Experiment 1, a centralized training experiment, revealed varying accuracies across datasets, with dataset two achieving the lowest accuracy (92.30%) and datasets one and three achieving the highest (98.90% and 99.5%, respectively). Experiment 2, focusing on cross-evaluation, showed a significant drop in accuracy (lowest: 63.80%) when fewer smells were present in the training dataset, reflecting technical debt. Experiment 3 involved splitting the dataset across 10 companies, resulting in a global model accuracy of 98.34%, comparable to the centralized model’s highest accuracy. The application of federated ML techniques demonstrates promising performance improvements in code-smell detection, benefiting both software developers and researchers.

Sketch-based image retrieval (SBIR) utilizes sketches to search for images containing similar objects or scenes. Due to the proliferation of touch-screen devices, sketching has become more accessible and therefore has received increasing attention. Deep learning has emerged as a potential tool for SBIR, allowing models to automatically extract image features and learn from large amounts of data. To the best of our knowledge, there is currently no systematic literature review (SLR) of SBIR with deep learning. Therefore, the aim of this review is to incorporate related works into a systematic study, highlighting the main contributions of individual researchers over the years, with a focus on past, present and future trends. To achieve the purpose of this study, 90 studies from 2016 to June 2023 in 4 databases were collected and analyzed using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) framework. The specific models, datasets, evaluation metrics, and applications of deep learning in SBIR are discussed in detail. This study found that Convolutional Neural Networks (CNN) and Generative Adversarial Networks (GAN) are the most widely used deep learning methods for SBIR. A commonly used dataset is Sketchy, especially in the latest Zero-shot sketch-based image retrieval (ZS-SBIR) task. The results show that Mean Average Precision (mAP) is the most commonly used metric for quantitative evaluation of SBIR. Finally, we provide some future directions and guidance for researchers based on the results of this review.

About 1–2% of people worldwide suffer from epilepsy, which is characterized by unpredictable and intermittent seizure occurrence. Despite the fact that the exact origin of temporal lobe epilepsy is frequently unknown, it is frequently linked to an early triggering insult like brain damage, tumors, or Status Epilepticus (SE). We used an experimental approach consisting of electrical stimulation of the amygdaloid complex to induce two behaviorally and structurally distinct SE states: Type I (fully convulsive), with more severe seizure behaviors and more extensive brain damage, and Type II (partial convulsive), with less severe seizure behaviors and brain damage. Our goal was to better understand how the various types of SE impact the hippocampus leading to the development of epilepsy. Despite clear variations between the two behaviors in terms of neurodegeneration, study of neurogenesis revealed a comparable rise in the number of Ki-67 + cells and an increase in Doublecortin (DCX) in both kinds of SE.

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Brief episodes of low oxygen breathing (therapeutic acute intermittent hypoxia; tAIH) may serve as an effective plasticity-promoting primer to enhance the effects of transcutaneous spinal stimulation-enhanced walking therapy (WALKtSTIM) in persons with chronic (>1 year) spinal cord injury (SCI). Pre-clinical studies in rodents with SCI show that tAIH and WALKtSTIM therapies harness complementary mechanisms of plasticity to maximize walking recovery. Here, we present a multi-site clinical trial protocol designed to examine the influence of tAIH + WALKtSTIM on walking recovery in persons with chronic SCI. We hypothesize that daily (eight sessions, 2 weeks) tAIH + WALKtSTIM will elicit faster, more persistent improvements in walking recovery than either treatment alone. To test our hypothesis, we are conducting a placebo-controlled clinical trial on 60 SCI participants who randomly receive one of three interventions: tAIH + WALKtSTIM; Placebo + WALKtSTIM; and tAIH + WALKtSHAM. Participants receive daily tAIH (fifteen 90-sec episodes at 10% O2 with 60-sec intervals at 21% O2) or daily placebo (fifteen 90-sec episodes at 21% O2 with 60-sec intervals at 21% O2) before a 45-min session of WALKtSTIM or WALKtSHAM. Our primary outcome measures assess walking speed (10-Meter Walk Test), endurance (6-Minute Walk Test), and balance (Timed Up and Go Test). For safety, we also measure pain levels, spasticity, sleep behavior, cognition, and rates of systemic hypertension and autonomic dysreflexia. Assessments occur before, during, and after sessions, as well as at 1, 4, and 8 weeks post-intervention. Results from this study extend our understanding of the functional benefits of tAIH priming by investigating its capacity to boost the neuromodulatory effects of transcutaneous spinal stimulation on restoring walking after SCI. Given that there is no known cure for SCI and no single treatment is sufficient to overcome walking deficits, there is a critical need for combinatorial treatments that accelerate and anchor walking gains in persons with lifelong SCI. Trial Registration: ClinicalTrials.gov, NCT05563103.

Abstract Background Heart rate variability biofeedback (HRV-BF) can be used for stress management. Recent feasibility studies suggest that delivering HRV-BF in virtual reality (VR) is associated with better user experience (UX) and might yield more beneficial changes in HRV than two-dimensional screens. The effectiveness of a VR-supported HRV-BF intervention program has, however, not been investigated yet. Methods In this study, 87 healthy women and men were assigned to a VR-supported HRV-BF intervention (INT; $$n=44$$ n = 44 ) or a wait-list control (WLC; $$n=43$$ n = 43 ) group. The INT came to the lab for four weekly HRV-BF sessions in VR using a head-mounted display. Between lab sessions, participants were asked to perform breathing exercises without biofeedback supported by a mobile application. Stress-related psychological and psychophysiological outcomes were assessed pre- and post-intervention and at a follow-up four weeks after the intervention in both groups. A psychosocial stress test was conducted post-intervention to investigate changes in stress reactivity. UX was assessed after each HRV-BF session in the INT. Results Analysis revealed that LF increased significantly from pre- to post-, whereas pNN50 increased and chronic stress decreased significantly from pre-intervention to follow-up in the INT compared to the WLC. Anxiety and mental fatigue decreased significantly, while mindfulness and health-related quality of life increased significantly from pre- to post- and from pre-intervention to follow-up in the INT compared to the WLC (all small effects). The two groups did not differ in their stress reactivity post-intervention. As for UX in the INT, the degree of feeling autonomous concerning technology adoption significantly decreased over time. Competence, involvement, and immersion, however, increased significantly from the first to the last HRV-BF session, while hedonic motivation significantly peaked in the second session and then gradually returned to first-session levels. Conclusions This HRV-BF intervention program, supported by VR and mobile technology, was able to significantly improve stress indicators and stress-related symptoms and achieved good to very good UX. Future studies should control for potential placebo effects and emphasize higher degrees of personalization and adaptability to increase autonomy and, thereby, long-term health and well-being. These findings may serve as a first step towards future HRV-BF applications of cutting-edge, increasingly accessible technologies, such as wearables, VR, and smartphones, in the service of mental health and healthcare. Trial registration The study was registered retrospectively as a clinical trial on ISRCTN registry (ISRCTN11331226, 26 May 2023).

Abstract Early detection of atrial fibrillation (AF) enables initiation of anticoagulation and early rhythm control therapy to reduce stroke, cardiovascular death, and heart failure. In a cross-sectional, observational study, we aimed to identify a combination of circulating biomolecules reflecting different biological processes to detect prevalent AF in patients with cardiovascular conditions presenting to hospital. Twelve biomarkers identified by reviewing literature and patents were quantified on a high-precision, high-throughput platform in 1485 consecutive patients with cardiovascular conditions (median age 69 years [Q1, Q3 60, 78]; 60% male). Patients had either known AF (45%) or AF ruled out by 7-day ECG-monitoring. Logistic regression with backward elimination and a neural network approach considering 7 key clinical characteristics and 12 biomarker concentrations were applied to a randomly sampled discovery cohort (n = 933) and validated in the remaining patients (n = 552). In addition to age, sex, and body mass index (BMI), BMP10, ANGPT2, and FGF23 identified patients with prevalent AF (AUC 0.743 [95% CI 0.712, 0.775]). These circulating biomolecules represent distinct pathways associated with atrial cardiomyopathy and AF. Neural networks identified the same variables as the regression-based approach. The validation using regression yielded an AUC of 0.719 (95% CI 0.677, 0.762), corroborated using deep neural networks (AUC 0.784 [95% CI 0.745, 0.822]). Age, sex, BMI and three circulating biomolecules (BMP10, ANGPT2, FGF23) are associated with prevalent AF in unselected patients presenting to hospital. Findings should be externally validated. Results suggest that age and different disease processes approximated by these three biomolecules contribute to AF in patients. Our findings have the potential to improve screening programs for AF after external validation.

Abstract Gender differences in navigation performance are a recurrent and controversial topic. Previous research suggests that men outperform women in navigation tasks and that men and women exhibit different navigation strategies. Here, we investigate whether motivation to complete the task moderates the relationship between navigation performance and gender. Participants learned the locations of landmarks in a novel virtual city. During learning, participants could trigger a top-down map that depicted their current position and the locations of the landmarks. During testing, participants were divided into control and treatment groups and were not allowed to consult the map. All participants were given 16 minutes to navigate to the landmarks, but those in the treatment group were monetarily penalized for every second they spent completing the task. Results revealed a negative relationship between physiological arousal and the time required to locate the landmarks. In addition, gender differences in strategy were found during learning, with women spending more time with the map and taking 40% longer than men to locate the landmarks. Interestingly, an interaction between gender and treatment group revealed that women in the control group required more time than men and women in the treatment group to retrieve the landmarks. During testing, women in the control group also took more circuitous routes compared to men in the control group and women in the treatment group. These results suggest that a concurrent and relevant stressor can motivate women to perform similarly to men, helping to diminish pervasive gender differences found in the navigation literature.

This study explores the use of accelerometer signals as the predictors of Rate of Torque Development (RTD) using an artificial neural network (ANN) prediction model. Sixteen physically active men participated (29 ± 5 years), performing explosive isometric contractions while acceleration (ACC) signals were measured. The dataset, comprising ACC signals and corresponding RTD values, was split into training and testing (70–30%) sets for ANN training. The trained model predicted the peak RTD values from the ACC signal inputs. The measured and predicted peak RTD values were compared, with no significant differences observed (p = 0.852). A strong linear fit (R² = 0.81), ICC = 0.94 (p < 0.001), and a mean bias of 30.8 Nm/s demonstrated almost perfect agreement between measures. The study demonstrates the feasibility of using accelerometer data to predict peak RTD, offering a portable and cost-effective method compared to traditional equipment. The ANN prediction model provides a reliable means of estimating RTD from ACC signals, potentially enhancing accessibility to RTD assessment in sports and rehabilitation settings. The findings support the use of ANN models for predicting RTD, highlighting the potential of AI in developing performance analysis tools.

Abstract Transcriptional changes in compensatory erythropoiesis in sickle cell anemia (SCA) and their disease modulation are unclear. We detected 1226 differentially expressed genes in hemoglobin SS reticulocytes compared to non-anemic hemoglobin AA controls. Assessing developmental expression changes in hemoglobin AA erythroblasts for these genes suggests heightened terminal differentiation in early erythroblasts in SCA that diminishes toward the polychromatic to orthochromatic stage transition. Comparison of reticulocyte gene expression changes in SCA with that in Chuvash erythrocytosis, a non-anemic disorder of increased erythropoiesis due to constitutive activation of hypoxia inducible factors, identified 453 SCA-specific changes attributable to compensatory erythropoiesis. Peripheral blood mononuclear cells (PBMCs) in SCA contain elevated proportions of erythroid progenitors due to heightened erythropoiesis. Deconvolution analysis in PBMCs from 131 SCA patients detected 54 genes whose erythroid expression correlated with erythropoiesis efficiency, which were enriched with SCA-specific changes (OR = 2.9, P = 0.00063) and annotation keyword “ubiquitin-dependent protein catabolic process”, “protein ubiquitination”, and “protein polyubiquitination” (OR = 4.2, P = 7.5 × 10–5). An erythroid expression quantitative trait locus of one of these genes, LNX2 encoding an E3 ubiquitin ligase, associated with severe pain episodes in 774 SCA patients (OR = 1.7, P = 3.9 × 10–5). Thus, erythroid gene transcription responds to unique conditions within SCA erythroblasts and these changes potentially correspond to vaso-occlusive manifestations.

Background: Cementless metaphyseal filling stems rely on fixation in the medial-to-lateral and anterior-to-posterior (AP) planes. The purpose of this preclinical study was to develop Insignia, a new metaphyseal filling system to match the anatomy of the proximal femur, and then compare it to clinically successful stems in multiple simulations. Methods: In this preclinical study, the geometry of the proximal femur in the AP plane among 1321 healthy subjects was evaluated using computed tomography. This data was then used to design insignia. Preclinical studies were performed to compare the broaching effort required to prepare a canal using this system, assess the reliability of seating heights for the stem, and compare in vitro micromotion testing of the stem under simulated stair climb activity. Results: The proximal femur decreased approximately 50% in the AP plane spanning 20 mm above the lesser trochanter to 30 mm below the lesser trochanter. Additional bench top testing was performed, and the new stem system was found to demonstrate significantly reduced broaching effort (average 6 vs 29 hits, P-value = .000), reliable seating heights on stem placement, and 70% less proximal micromotion on 10,000-cyclic testing (P < .05) compared to another clinically successful metaphyseal filling stem. Conclusions: The AP dimension of the proximal femur decreases nearly 50% throughout its length. Metaphyseal filling stems that match the AP anatomy of the proximal femur may require fewer hits during broaching, yield reproducible seating heights, and reduce micromotion on cyclic testing.

Abstract Sickle cell anemia (SCA) negatively impacts the ability to achieve educational and occupational goals increasing vulnerability to socioeconomic challenges. In a cross‐sectional analysis of 332 SCA adults, we investigated whether the distressed community index (DCI) was associated with SCA‐related complications and nutritional status. More patients with higher DCI had Medicaid insurance. A higher DCI was independently associated with tobacco use and lower body mass index, serum albumin, and vitamin D 25‐OH levels after adjusting for insurance status but was not associated with SCA‐related complications. Future studies investigating access to healthy foods may help improve health equity in patients with SCA.

Advances in anti-retroviral therapy (ART) have decreased mortality rates and subsequently led to a rise in the number of HIV-positive people living longer. The housing experiences of this new population of interest—older adults (50 years and older) living with HIV—are under-researched. Understanding the housing experiences and unmet needs of older people with HIV can better provide comprehensive care services for them. This study’s systematic review evaluated the peer-reviewed literature reporting housing access/insecurity/assistance/options, housing impact, and unmet needs of older individuals living with HIV in North America from 2012 to 2023. Furthermore, Latent Semantic Analysis (LSA), a text-mining technique, and Singular Value Decomposition (SVD) for text clustering were utilized to examine unstructured data from the abstracts selected from the review. The goal was to allow for a better understanding of the relationships between terms in the articles and the identification of emerging public health key themes affecting older adults living with HIV. The results of text clustering yielded two clusters focusing on (1) improvements to housing and healthcare services access and policies and (2) unmet needs—social support, mental health, finance, food, and sexuality insecurities. Topic modeling demonstrated four topics, which we themed to represent (1) a holistic care approach; (2) insecurities—food, financial, sexuality, and other basic needs; (3) access to housing and treatment/care; and (4) homelessness and HIV-related health outcomes. Stable housing, food, and healthcare services access and availability are critical elements to incorporating comprehensive, holistic healthcare for older adults living with HIV. The aging population requires high-priority policies for accessible and equitable healthcare. Clinicians and policymakers should address individual barriers, adopt a patient-centered approach, increase doctor visits, provide competency training, ensure long-term follow-up, involve families, and improve patient education in care management, contributing to HIV/AIDS geriatric care models.

The objective of this research was the sustainable development of pullulan and its structural and rheological characterization. In addition, the cultivation of the A. pullulans Y2092 strain by submerged fermentation on a laboratory scale was evaluated, valuing the use of industrial waste (residual brewery's yeast), RBY, and a low-cost renewable raw material VHP (very high polarization sugar). A 22 factorial statistical design of experiments was used to analyze the molecular weight of the pullulans produced. The maximum value of 1955 kDa was determined for the pullulan recovered after 96 h of fermentation in the mineral medium added with 70 g/L of VHP and 50 g/L of RBY. The FTIR analysis for the pullulan obtained was similar to the commercial pullulan. The rheological behavior of pullulan solutions is shown, evidencing the relationship between this property and Mw. The results from all analyses indicate that the pullulan obtained is suitable for the future production of biopolymeric films.

Abstract Although a higher prevalence of antiphospholipid autoantibodies (aPL) has been observed in some cohorts of sickle cell disease (SCD) patients, the clinical risk factors for the development of aPL and its associated complications remain unclear. In a retrospective study of 63 SCD patients, a lower hemoglobin concentration and higher white blood cell count were independently associated with an elevated aPL. SCD patients with elevated aPL had increased pregnancy complications (≥3 miscarriages, preterm delivery, pre‐eclampsia) and venous thrombotic events. Our findings suggest that SCD may predispose to the generation of aPL and that aPL itself may contribute to the vasculopathy of SCD. Prospective testing for aPL is warranted in patients with SCD.

The digital market trend is rapidly expanding due to key characteristics like decentralization, accessibility, and market diversity enabled by blockchain technology. This study proposes a Predictive Analytics System to provide simplified reporting for the three most popular cryptocurrencies with varying digits, namely ADA Cardano, Ethereum, and Binance coin, for ten days to contribute to this emerging technology. Thus, this proposed system employs a data science-based framework and six highly advanced data-driven Machine learning and Deep learning algorithms: Support Vector Regressor, Auto-Regressive Integrated Moving Average (ARIMA), Facebook Prophet, Unidirectional LSTM, Bidirectional LSTM, Stacked LSTM. Moreover, the research experiments are repeated several times to achieve the best results by employing hyperparameter tuning of each algorithm. This involves selecting an appropriate kernel and suitable data normalization technique for SVR, determining ARIMA’s (p, d, q) values, and optimizing the loss function values, number of neurons, hidden layers, and epochs in LSTM models. For the model validation, we utilize widely used evaluation techniques: Mean Absolute Error, Root Mean Squared Error, Mean Absolute Percentage Error, and R-squared. Results demonstrate that ARIMA outperforms the other models in all cases, accurately projecting the price variability within the actual price range. Conversely, Facebook Prophet exhibits good performance to some extent. The paper suggests that the ARIMA technique offers practical implications for market analysts, enabling them to make well-informed decisions based on accurate price projections.

Chacha20 is a widely used stream cipher known for using permutation functions to enhance resistance against cryptanalysis. Although the existing literature highlights its strengths, it is worth further exploring its potential susceptibility to differential attacks. This paper proposes an Extended Chacha20 (EChacha20) stream cipher, which offers a slight improvement of Chacha20. It incorporates enhanced Quarter Round Functions $QR-F$ with 32-bit input words and $Add $ , $Rotate $ , and $XOR (ARX)$ operations on 16, 12, 8, 7, 4, and 2 constants. Using these improved $QR-Fs$ , we expect EChacha20 to be more secure and effective against attacks than Chacha20. The threat model leveraged in this paper considers attacker assumptions based on the Bellare-Rogaway Model (B-RM) and the Chosen Plaintext Attack (CPA) to assess the potential security weaknesses. Then, the study analyzes the EChacha20 cipher using the NIST Statistical Test Suite (NSTS) and demonstrates its effectiveness against differential cryptanalysis. A differential attack addresses this challenge, where the study comprehensively analyses the differences between original and flipped bits. The NSTS has been used to statistically analyze the outcome for uniformity and evaluate the randomness of generating sequences of tests considering 1000 tests based on a range of $[{0,1}]$ . Uniformity is evaluated based on the $p-values$ test against a battery of passing sequences, and 100% is achieved from $Runs$ and $Serial (2): Test 1$ , respectively. The performance evaluation metrics leveraged include encryption speed, decryption speed, and memory usage. Based on the test conducted, it has been observed that with increased $QR-F$ , EChacha20 maintains a good balance in speed although slightly higher than Chacha20; however, with also slightly high memory usage compared to Chacha20. Despite that, a comparative study has been conducted against state-of-the-art studies, and the outcome has been reported to show the significance of the current study. Ultimately, the outcome indicates that the EChacha20 cipher has improved $QR-F$ and security properties compared to Chacha20 and may provide a more robust encryption solution for various applications.

Abstract In 1976, NASA's Viking 1 Lander (V1L) was the first spacecraft to operate successfully on the Martian surface. The V1L landed near the terminus of an enormous catastrophic flood channel, Maja Valles. However, instead of the expected megaflood record, its cameras imaged a boulder-strewn surface of elusive origin. We identified a 110-km-diameter impact crater (Pohl) ~ 900 km northeast of the landing site, stratigraphically positioned (a) above catastrophic flood-eroded surfaces formed ~ 3.4 Ga during a period of northern plains oceanic inundation and (b) below the younger of two previously hypothesized megatsunami deposits. These stratigraphic relationships suggest that a marine impact likely formed the crater. Our simulated impact-generated megatsunami run-ups closely match the mapped older megatsunami deposit's margins and predict fronts reaching the V1L site. The site's location along a highland-facing lobe aligned to erosional grooves supports a megatsunami origin. Our mapping also shows that Pohl's knobby rim regionally represents a broader history of megatsunami modification involving circum-oceanic glaciation and sedimentary extrusions extending beyond the recorded megatsunami emplacement in Chryse Planitia. Our findings allow that rocks and soil salts at the landing site are of marine origin, inviting the scientific reconsideration of information gathered from the first in-situ measurements on Mars.

Abstract Background We investigated key risk factors for hospital admission related to powered scooters, which are modes of transportation with increasing accessibility across the United States (US). Methods We queried the National Electronic Injury Surveillance System (NEISS) for injuries related to powered scooters, obtaining US population projections of injuries and hospital admissions. We determined mechanism of injury, characterized injury types, and performed multivariate regression analyses to determine factors associated with hospital admission. Results One thousand one hundred ninety-one patients sustained electric-motorized scooter (e-scooter) injuries and 10.9% (131) required hospitalization from 2013 to 2018. This extrapolated to a US annual total of 862 (95% CI:745–979) scooter injuries requiring hospitalization, with estimated annual mortality of 6.7 patients per year (95% CI:4.8–8.5). The incidence of hospital admissions increased by an average of 13.1% each year of the study period. Fall (79 [60%]) and motor vehicle collision (33 [25%]) were the most common mechanism. Injury locations included head (44 [34%]), lower extremity (22 [17%]), and lower trunk (16 [12%]). On multivariable analysis, significant factors associated with admission included increased age (OR 1.02, 95% CI:1.01–1.02), torso injuries (OR 6.19, 2.93–13.10), concussion (25.45, 5.88–110.18), fractures (21.98, 7.13–67.66), musculoskeletal injury (6.65, 1.20–36.99), and collision with vehicle (3.343, 2.009–5.562). Scooter speed, seasonality, and gender were not associated with risk of hospitalization. Conclusion Our findings show increased hospital admissions and mortality from powered scooter trauma, with fall and motor vehicle collisions as the most common mechanisms resulting in hospitalization. This calls for improved rider safety measures and regulation surrounding vehicular collision scenarios.

This study examines the relationship between vaccination and inflation in battling the COVID-19 pandemic across nations. Data from 85 countries worldwide were collected from the Trading Economics (New York City, USA) website during the COVID-19 pandemic. First, a new theoretical model was proposed based on the economic and healthcare literature; then, a binary variable, inflation/vaccination% was developed according to the proposed theoretical model. The relationship between inflation/vaccination% and macroeconomic factors was examined using logistic regression. After that, the countries were ranked by minimising the inflation/vaccination% rate that measures a country’s efficiency in fighting the COVID-19 pandemic, thereby permitting governments to compare the performance of different countries. The findings show that a country with a higher gross domestic product growth rate and competitiveness index during the COVID-19 pandemic has a lower inflation/vaccination% ratio. The results of this study provide strong evidence that countries should mitigate a pandemic’s economic impact by managing vaccination programmes to control global inflation.

Metabolomics studies in sickle cell disease (SCD) have been so far limited to tens of samples, owing to technical and experimental limitations. To overcome these limitations, we performed plasma metabolomics analyses on 596 samples from patients with SCD enrolled in the WALK-PHaSST study (clinicaltrials gov. Identifier: NCT00492531). Clinical covariates informed the biological interpretation of metabolomics data, including genotypes (hemoglobin [Hb] SS, hemoglobin SC), history of recent transfusion (HbA%), response to hydroxyurea treatment (fetal Hb%). We investigated metabolic correlates to the degree of intravascular hemolysis, cardiorenal function, as determined by tricuspid regurgitation velocity (TRV), estimated glomerular filtration rate (eGFR), and overall hazard ratio (unadjusted or adjusted by age). Recent transfusion events or hydroxyurea treatment were associated with elevation in plasma-free fatty acids and decreases in acyl-carnitines, urate, kynurenine, indoles, carboxylic acids, and glycine- or taurine-conjugated bile acids. High levels of these metabolites, along with low levels of plasma S1P and L-arginine were identified as top markers of hemolysis, cardiorenal function (TRV, eGFR), and overall hazard ratio. We thus uploaded all omics and clinical data on a novel online portal that we used to identify a potential mechanism of dysregulated red cell S1P synthesis and export as a contributor to the more severe clinical manifestations in patients with the SS genotype compared to SC. In conclusion, plasma metabolic signatures - including low S1P, arginine and elevated kynurenine, acyl-carnitines and bile acids - are associated with clinical manifestation and therapeutic efficacy in SCD patients, suggesting new avenues for metabolic interventions in this patient population.

Background Evidence-based parenting programs effectively prevent the onset and escalation of child and adolescent behavioral health problems. When programs have been taken to scale, declines in the quality of implementation diminish intervention effects. Gold-standard methods of implementation monitoring are cost-prohibitive and impractical in resource-scarce delivery systems. Technological developments using computational linguistics and machine learning offer an opportunity to assess fidelity in a low burden, timely, and comprehensive manner. Methods In this study, we test two natural language processing (NLP) methods [i.e., Term Frequency-Inverse Document Frequency (TF-IDF) and Bidirectional Encoder Representations from Transformers (BERT)] to assess the delivery of the Family Check-Up 4 Health (FCU4Health) program in a type 2 hybrid effectiveness-implementation trial conducted in primary care settings that serve primarily Latino families. We trained and evaluated models using 116 English and 81 Spanish-language transcripts from the 113 families who initiated FCU4Health services. We evaluated the concurrent validity of the TF-IDF and BERT models using observer ratings of program sessions using the COACH measure of competent adherence. Following the Implementation Cascade model, we assessed predictive validity using multiple indicators of parent engagement, which have been demonstrated to predict improvements in parenting and child outcomes. Results Both TF-IDF and BERT ratings were significantly associated with observer ratings and engagement outcomes. Using mean squared error, results demonstrated improvement over baseline for observer ratings from a range of 0.83–1.02 to 0.62–0.76, resulting in an average improvement of 24%. Similarly, results demonstrated improvement over baseline for parent engagement indicators from a range of 0.81–27.3 to 0.62–19.50, resulting in an approximate average improvement of 18%. Conclusions These results demonstrate the potential for NLP methods to assess implementation in evidence-based parenting programs delivered at scale. Future directions are presented. Trial registration NCT03013309 ClinicalTrials.gov.

Approximately 40–60% of falls in the elderly lead to injuries, resulting in disability and loss of independence. Despite the higher prevalence of falls and morbidity rates in cognitively impaired individuals, most fall risk assessments fail to account for mental status. In addition, successful fall prevention programmes in cognitively normal adults have generally failed in patients with cognitive impairment. Identifying the role of pathological aging on fall characteristics can improve the sensitivity and specificity of fall prevention approaches. This literature review provides a thorough investigation into fall prevalence and fall risk factors, the accuracy of fall risk assessments, and the efficacy of fall prevention strategies in individuals with diverse cognitive profiles. We show that fall-related characteristics differ between cognitive disorders and fall risk assessment tools as well as fall prevention strategies should critically consider each patient’s cognitive status to facilitate the identification of fallers at an earlier stage and support clinical decision-making.

This study significantly contributes to both theory and practice by providing valuable insights into the role and value of healthcare in the context of online health communities. This study highlights the increasing dependence of patients and their families on online sources for health information and the potential of technology to support individuals with health information needs. This study develops a theoretical framework by analyzing data from a cross-sectional survey using partial least squares structural equation modeling and multi-group and importance–performance map analysis. The findings of this study identify the most beneficial technology-related issues, like ease of site navigation and interaction with other online members, which have important implications for the development and management of online health communities. Healthcare professionals can also use this information to disseminate relevant information to those with chronic illnesses effectively. This study recommends proactive engagement between forum admins and participants to improve technology use and interaction, highlighting the benefits of guidelines for effective technology use to enhance users’ information-seeking processes. Overall, this study’s significant contribution lies in its identification of factors that aid online health community participants in the information-seeking process, providing valuable information to professionals on using technology to disseminate information relevant to chronic illnesses like COPD.

We are currently witnessing an unprecedented era of digital transformation in sports, driven by the revolutions in Artificial Intelligence (AI), Virtual Reality (VR), Augmented Reality (AR), and Data Visualization (DV). These technologies hold the promise of redefining sports performance analysis, automating data collection, creating immersive training environments, and enhancing decision-making processes. Traditionally, performance analysis in sports relied on manual data collection, subjective observations, and standard statistical models. These methods, while effective, had limitations in terms of time and subjectivity. However, recent advances in technology have ushered in a new era of objective and real-time performance analysis. AI has revolutionized sports analysis by streamlining data collection, processing vast datasets, and automating information synthesis. VR introduces highly realistic training environments, allowing athletes to train and refine their skills in controlled settings. AR overlays digital information onto the real sports environment, providing real-time feedback and facilitating tactical planning. DV techniques convert complex data into visual representations, improving the understanding of performance metrics. In this paper, we explore the potential of these emerging technologies to transform sports performance analysis, offering valuable resources to coaches and athletes. We aim to enhance athletes’ performance, optimize training strategies, and inform decision-making processes. Additionally, we identify challenges and propose solutions for integrating these technologies into current sports analysis practices. This narrative review provides a comprehensive analysis of the historical context and evolution of performance analysis in sports science, highlighting current methods’ merits and limitations. It delves into the transformative potential of AI, VR, AR, and DV, offering insights into how these tools can be integrated into a theoretical model.

The authority of user personal health records (PHRs) is usually determined by the owner of a cloud computing system. When a PHR file is accessed, a dynamic access control algorithm must be used to authenticate the users. The proposed dynamic access control algorithm is based on a novel Lagrange interpolation polynomial with timestamps, mainly functioning to authenticate the users with key information. Moreover, the inclusion of timestamps allows user access within an approved time slot to enhance the security of the healthcare cloud system. According to the security analysis results, this healthcare cloud system can effectively resist common attacks, including external attacks, internal attacks, collaborative attacks and equation-based attacks. Furthermore, the overall computational complexity of establishing and updating the polynomials is O(n*m* (log m)2), which is a promising result, where m denotes the degree of $ polynomial~G\left(x, y\right) $ and n denotes the number of secure users in the hierarchy.

Abstract Pulmonary hypertension (PH) is associated with significant morbidity and mortality. RASA3 is a GTPase activating protein integral to angiogenesis and endothelial barrier function. In this study, we explore the association of RASA3 genetic variation with PH risk in patients with sickle cell disease (SCD)‐associated PH and pulmonary arterial hypertension (PAH). Cis‐expression quantitative trait loci (eQTL) were queried for RASA3 using whole genome genotype arrays and gene expression profiles derived from peripheral blood mononuclear cells (PBMC) of three SCD cohorts. Genome‐wide single nucleotide polymorphisms (SNPs) near or in the RASA3 gene that may associate with lung RASA3 expression were identified, reduced to 9 tagging SNPs for RASA3 and associated with markers of PH. Associations between the top RASA3 SNP and PAH severity were corroborated using data from the PAH Biobank and analyzed based on European or African ancestry (EA, AA). We found that PBMC RASA3 expression was lower in patients with SCD‐associated PH as defined by echocardiography and right heart catheterization and was associated with higher mortality. One eQTL for RASA3 (rs9525228) was identified, with the risk allele correlating with PH risk, higher tricuspid regurgitant jet velocity and higher pulmonary vascular resistance in patients with SCD‐associated PH. rs9525228 associated with markers of precapillary PH and decreased survival in individuals of EA but not AA. In conclusion, RASA3 is a novel candidate gene in SCD‐associated PH and PAH, with RASA3 expression appearing to be protective. Further studies are ongoing to delineate the role of RASA3 in PH.

Abstract The control of weeds in agriculture is mainly conducted with the use of synthetic herbicides. However, environmental and human health concerns and increased resistance of weeds to existing herbicides have increased the pressure on researchers to find new active ingredients for weed control which present low toxicity to non-target organisms, are environmentally safe, and can be applied at low concentrations. It is herein described the synthesis of glycerol-fluorinated triazole derivatives and evaluation of their phytotoxic and cytogenotoxic activities. Starting from glycerol, ten fluorinated triazole derivatives were prepared in four steps. The assessment of them on Lactuca sativa revealed that they present effects on phytotoxic and cytogenotoxic parameters with different degrees of efficiency. The compounds 4a, 4b, 4d, 4e, 4i, and 4j have pre-emergent inhibition behavior, while all the investigated compounds showed post emergent effect. Mechanism of action as clastogenic, aneugenic, and epigenetic were observed in the lettuce root meristematic cells, with alterations as stick chromosome, bridge, delay, c-metaphase, and loss. It is believed that glycerol-fluorinated triazole derivatives possess a scaffold that can be explored towards the development of new chemicals for the control of weed species.

Introduction: Exercise intolerance is a common clinical manifestation in patients with sickle cell disease (SCD), though the mechanisms are incompletely understood.Methods: Here we leverage a murine mouse model of sickle cell disease, the Berkeley mouse, to characterize response to exercise via determination of critical speed (CS), a functional measurement of mouse running speed upon exerting to exhaustion.Results: Upon observing a wide distribution in critical speed phenotypes, we systematically determined metabolic aberrations in plasma and organs—including heart, kidney, liver, lung, and spleen—from mice ranked based on critical speed performances (top vs. bottom 25%). Results indicated clear signatures of systemic and organ-specific alterations in carboxylic acids, sphingosine 1-phosphate and acylcarnitine metabolism. Metabolites in these pathways showed significant correlations with critical speed across all matrices. Findings from murine models were thus further validated in 433 sickle cell disease patients (SS genotype). Metabolomics analyses of plasma from 281 subjects in this cohort (with HbA < 10% to decrease confounding effects of recent transfusion events) were used to identify metabolic correlates to sub-maximal exercise test performances, as measure by 6 min walking test in this clinical cohort. Results confirmed strong correlation between test performances and dysregulated levels of circulating carboxylic acids (especially succinate) and sphingosine 1-phosphate.Discussion: We identified novel circulating metabolic markers of exercise intolerance in mouse models of sickle cell disease and sickle cell patients.

This article outlines the specific features of the versatile activities of MSHU sociologicallaboratory. It emphasizes the many-sidedness of research work directions, determined by thelaboratory’s belonging to a higher education institution. The author mentions the laboratory’s advantages in studying the cultural and socio-economic situation in the region, determinedby the opportunity to involve in research the university teachers, specialized in problems under discussion.

Background: To evaluate seroma complications, two techniques were carried out in breast reconstruction: conventional latissimus dorsi flap (CLD) and muscle-sparing latissimus dorsi flap (MSLD) after cancer-related mastectomy. Methods: A total of 108 postmastectomy procedures were performed with autologous tissue reconstruction with latissimus dorsi flaps (LDs) between January 2016 and May 2020. The patients were divided into two groups. The first group was reconstruction with the CLD, and the second group was reconstruction with the MSLD. Forty (40) patients in the first group and 68 patients in the second group were analyzed. Seroma formation was evaluated as the primary outcome. Results: The total number of seromas found in the donor area was 27, of which 45% (n = 18) were found with the CLD and 13.24% (n = 9) with the MSLD, with a difference of 31.76% in favor of the MSLD, with an 95% CI of 14–49 (p

Abstract The reliable assessment of cognitive functioning is critical to the study of brain-behaviour relationships. Yet conditions that are synchronous which ageing, including visual decline, are easily overlooked when interpreting cognitive test scores. The purpose of this study was to demonstrate the negative consequences of visual impairments on cognitive tests performance. Moderate to severe levels of age-related macular degeneration were simulated, with a set of goggles, in a sample of twenty-four normally sighted participants while they completed two cognitive tasks: a vision-dependent reaction time task and a vision-independent verbal fluency test. Performance on the reaction time task significantly decreased (p

Abstract We report long‐term follow‐up of a patient who underwent a tailored laparoscopic procedure for symptomatic cholelithiasis, massive splenomegaly, and a planned pregnancy. There were no complications, and the patient remained symptom‐free at the 5‐year follow‐up. We supplemented our case report with national surgical data demonstrating the safety of laparoscopic splenectomy.

Augmented feedback provided by a coach or augmented reality system can facilitate the acquisition of a motor skill. Verbal instructions and visual aids can be effective in providing feedback about the kinematics of the desired movements. However, many skills require mastering not only kinematic, but also complex kinetic patterns, for which feedback is harder to convey. Here, we propose the electromyography (EMG) space similarity feedback, which may indirectly convey kinematic and kinetic feedback by comparing the muscle activations of the learner and an expert in the task. The EMG space similarity feedback is a score that reflects how well a set of muscle synergies extracted from the expert can reconstruct the learner’s EMG when performing the task. We tested the EMG space similarity feedback in a virtual bimanual polishing task that uses a robotic system to simulate the dynamics of a real polishing operation. We measured the expert’s and learner’s EMG from eight muscles in each arm during the real and virtual polishing tasks, respectively. The goal of the virtual task was to smoothen the surface of a virtual object. Therefore, we defined performance in the task as the smoothness of the object at the end of a trial. We separated learners into real feedback and null feedback groups to assess the effects of the EMG space similarity feedback. The real and null feedback groups received veridic and no EMG space similarity feedback, respectively. Subjects participated in five training sessions on different days, and we evaluated their performance on each day. Subjects in both groups were able to increase smoothness throughout the training sessions, with no significant differences between groups. However, subjects in the real feedback group were able to improve in the EMG space similarity score to a significantly greater extent than the null feedback group. Additionally, subjects in the real feedback group produced muscle activations that became increasingly consistent with an important muscle synergy found in the expert. Our results indicate that the EMG space similarity feedback promotes acquiring expert-like muscle activation patterns, suggesting that it may assist in the acquisition of complex motor skills.

Systemic lupus erythematosus (SLE) affects more severely non-White populations, due to their genetic background and sociodemographic characteristics. Several studies have evaluated Latin American SLE patients to determine their genetic and clinical characteristics as well as prognostic factors; these studies have not only allowed the development of treatment guidelines aimed at the region but also to support regional and global projects. Additionally, educational activities in Spanish and Portuguese have been started to reduce our patients’ health illiteracy. Despite the relatively low research output from Latin American countries, we consider that studies from our region coupled with the networks developed to increase our capabilities, could be a model for other rare autoimmune diseases.

As usual, if many students are attending the lectures, their attendance tracking may become time consuming. Furthermore, there are some possibilities that students could cheat the lecturers of their attendance in the classroom. Therefore, a reliable method to manage the attendance tracking has become a critical issue. This paper aims to propose an attendance tracking system using an Android smartphone equipped with Global Positioning System (GPS) and Near Field Communication (NFC) technologies. Lecturers and students can constantly connect with one another by using smartphones to check and show their attendance automatically if they download and install the software Application (App). Finally, the experimental results have shown that our proposed system can successfully reduce some time for tracking students’ attendance. It also allows users to use their own Android smartphones without purchasing other electronic devices.

Sustaining the release of highly dosed APIs from a matrix tablet is challenging. To address this challenge, this study evaluated the performance of thermoplastic poly (2-alkyl-2-oxazoline)s (PAOx) as matrix excipient to produce sustained-release tablets via three processing routes: (a) hot-melt extrusion (HME) combined with injection molding (IM), (b) HME combined with milling and compression and (c) direct compression (DC). Different PAOx (co-)polymers and polymer mixtures were processed with several active pharmaceutical ingredients having different aqueous solubilities and melting temperatures (metoprolol tartrate (MPT), metformin hydrochloride (MTF) and theophylline anhydrous (THA)). Different PAOx grades were synthesized and purified by the Supramolecular Chemistry Group, and the effect of PAOx grade and processing technique on the in vitro release kinetics was evaluated. Using the hydrophobic poly (2-n-propyl-2-oxazoline) (PnPrOx) as a matrix excipient allowed to sustain the release of different APIs, even at a 70% (w/w) drug load. Whereas complete THA release was not achieved from the PnPrOx matrix over 24 ​h regardless of the processing technique, adding 7.5% w/w of the hydrophilic poly (2-ethyl-2-oxazoline) to the hydrophobic PnPrOx matrix significantly increased THA release, highlighting the relevance of mixing different PAOx grades. In addition, it was demonstrated that the release of THA was similar from co-polymer and polymer mixtures with the same polymer ratios. On the other hand, as the release of MTF from a PnPrOx matrix was fast, the more hydrophobic poly (2-sec-butyl-2-oxazoline) (PsecBuOx) was used to retard MTF release. In addition, a mixture between the hydrophilic PEtOx and the hydrophobic PsecBuOx allowed accurate tuning of the release of MTF formulations. Finally, it was demonstrated that PAOx also showed a high ability to tune the in vivo release. IM tablets containing 70% MTF and 30% PsecBuOx showed a lower in vivo bioavailability compared to IM tablets containing a low PEtOx concentration (7.5%, w/w) in combination with PsecBuOx (22.5%, w/w). Importantly, the in vivo MTF blood level from the sustained release tablets correlated well with the in vitro release profiles. In general, this work demonstrates that PAOx polymers offer a versatile formulation platform to adjust the release rate of different APIs, enabling sustained release from tablets with up to 70% w/w drug loading.

Penelitian ini bertujuan untuk meneliti Pengaruh pembelajaran blended learning menggunakan media pembelajaran Edmodo terhadap hasil belajar siswa kelas VIII SMP Kristen 46 Mapanget Barat. Metode penelitian ini adalah metode eksperimen semu (kuasi eksperimen) dapat mengetahui pengaruh pembelajaran blended learning menggunakan media pembelajaran edmodo terhadap hasil belajar siswa. Data yang digunakan dalam penelitian ini adalah data post-test hasil belajar. Hasil penelitian menunjukkan bahwa terdapat pengaruh pembelajaran blended learning menggunakan media pembelajaran edmodo terhadap hasil belajar siswa kelas VIII pada materi Teorema Phytagoras. Dibuktikan dengan hasil perhitungan thitung = 2,585 > ttabel = 1,672. Hasil penelitian menyimpulkan bahwa skor rata-rata hasil belajar dengan model pembelajaran blended learning menggunakan media pembelajaran Edmodo lebih tinggi dibandingkan dengan pembelajaran blended learning konvensional. Dengan adanya pembelajaran blended learning menggunakan media pembelajaran Edmodo ini melibatkan siswa untuk memecahkan masalah melalui tahap-tahap metode ilmiah sehingga siswa mampu mengembangkan keterampilan matematika baik dari segi kognitif dan afektif

Objectives To investigate factors associated with severe COVID-19 in people with idiopathic inflammatory myopathy (IIM).Methods Demographic data, clinical characteristics and COVID-19 outcome severity of adults with IIM were obtained from the COVID-19 Global Rheumatology Alliance physician-reported registry. A 3-point ordinal COVID-19 severity scale was defined: (1) no hospitalisation, (2) hospitalisation (and no death) and (3) death. ORs were estimated using multivariable ordinal logistic regression. Sensitivity analyses were performed using a 4-point ordinal scale: (1) no hospitalisation, (2) hospitalisation with no oxygen (and no death), (3) hospitalisation with oxygen/ventilation (and no death) and 4) death.Results Of 348 patients, 48% were not hospitalised, 39% were hospitalised (and did not die) and 13% died. Older age (OR=1.59/decade, 95% CI 1.31 to 1.91), high disease activity (OR=3.50, 95% CI 1.25 to 9.83; vs remission), ≥2 comorbidities (OR=2.63, 95% CI 1.39 to 4.98; vs none), prednisolone-equivalent dose >7.5 mg/day (OR=2.40, 95% CI 1.09 to 5.28; vs no intake) and exposure to rituximab (OR=2.71, 95% CI 1.28 to 5.72; vs conventional synthetic disease-modifying antirheumatic drugs only) were independently associated with severe COVID-19. In addition to these variables, in the sensitivity analyses, male sex (OR range: 1.65–1.83; vs female) was also significantly associated with severe outcomes, while COVID-19 diagnosis after 1 October 2020 (OR range: 0.51–0.59; vs on/before 15 June 2020) was significantly associated with less severe outcomes, but these associations were not significant in the main model (OR=1.57, 95% CI 0.95 to 2.59; and OR=0.61, 95% CI 0.37 to 1.00; respectively).Conclusions This is the first large registry data on outcomes of COVID-19 in people with IIM. Older age, male sex, higher comorbidity burden, high disease activity, prednisolone-equivalent dose >7.5 mg/day and rituximab exposure were associated with severe COVID-19. These findings will enable risk stratification and inform management decisions for patients with IIM.

Background People with age-related macular degeneration (AMD) can report reduced mental health. There is also evidence that they struggle with daily tasks because of vision loss. Aims The purpose of this study was to assess the psychological impact of instrumental activities of daily living on people with simulated AMD. Method Twenty-four normally sighted participants completed 12 household tasks, in a simulated home environment, under a moderate-to-severe AMD simulation. Participants’ psychological state was measured through self-report questionnaires and physiological measurements related to anxiety and stress. Tasks were completed twice, under counterbalanced vision conditions (normal and simulated AMD). Results Linear mixed models on vision condition (normal versus simulated AMD) and trial order (trial 1 versus trial 2) revealed a significant large negative effect of the AMD simulation on time to complete tasks, and the anxiety, task engagement and distress self-reports (all P < 0.024, all ω2 > 0.177). There were also significant medium-large effects of trial order on time, task incompletion, task errors, and the anxiety and task engagement self-reports (all P < 0.047, all ω2 > 0.130), whereby the results improved during the second attempt at the tasks. No physiological measures were significant (all P > 0.05). Conclusions Completing instrumental activities of daily living under an AMD simulation had a negative impact on participants’ self-reported mental state. The observed trial order effects also illuminated how practice with tasks could ease anxiety and stress over time.

This study explores a theoretical framework evaluating the antecedents of cyberchondria. In doing so, we not only examined perceived severity as an intervening factor through which online health information seeking (OHIS) may influence cyberchondria but also sought to trace moderators that serve as boundary conditions. To explore the proposed framework, we collected data via a survey. Data were analyzed using conditional process analysis through the regression-centric procedure. We observed that the association between OHIS and cyberchondria is mediated by perceived severity. In addition, neuroticism & beliefs about rituals serve as the first and second stage moderators in influencing the antecedents of cyberchondria. Thus, unlike previous studies which mostly focus on direct effects, in this research, we focus on the mediation, moderation, and moderated mediation effects for hypothesis testing. Therefore, this research broadens our view of the antecedents of cyberchondria from a more systematic standpoint.

In Brazil, sucrose-rich broths (cane juice and/or molasses) are used to produce billions of liters of both fuel ethanol and cachaça per year using selected Saccharomyces cerevisiae industrial strains. Considering the important role of feedstock (sugar) prices in the overall process economics, to improve sucrose fermentation the genetic characteristics of a group of eight fuel-ethanol and five cachaça industrial yeasts that tend to dominate the fermentors during the production season were determined by array comparative genomic hybridization. The widespread presence of genes encoding invertase at multiple telomeres has been shown to be a common feature of both baker’s and distillers’ yeast strains, and is postulated to be an adaptation to sucrose-rich broths. Our results show that only two strains (one fuel-ethanol and one cachaça yeast) have amplification of genes encoding invertase, with high specific activity. The other industrial yeast strains had a single locus (SUC2) in their genome, with different patterns of invertase activity. These results indicate that invertase activity probably does not limit sucrose fermentation during fuel-ethanol and cachaça production by these industrial strains. Using this knowledge, we changed the mode of sucrose metabolism of an industrial strain by avoiding extracellular invertase activity, overexpressing the intracellular invertase, and increasing its transport through the AGT1 permease. This approach allowed the direct consumption of the disaccharide by the cells, without releasing glucose or fructose into the medium, and a 11% higher ethanol production from sucrose by the modified industrial yeast, when compared to its parental strain.