Rounds Of Testing Research Articles

Optimalisasi produktivitas pengupasan biji kopi melalui modifikasi mesin pengupas

The aim of this research is to modify the coffee bean husking machine to enhance the quality and efficiency of the husking process. The modifications include the addition of a spring mechanism in the grinding space, enabling the outer roller to move flexibly in accordance with the size of the entering coffee beans. Furthermore, these changes also consider reducing the percentage of broken coffee beans during the husking process. The machine underwent two rounds of testing, with three samples tested under two different drying conditions. The research results demonstrate the success of the modifications in achieving their objectives. The machine's capability to husk coffee beans up to the parchment layer, not just the husk, indicates an improvement in the quality of the husking process. The quantity of successfully husked coffee beans also increased, while the percentage of broken beans decreased. By enhancing the quality and quantity of coffee beans produced by this machine, the modifications can significantly benefit coffee farmers. Additionally, this study utilized Autodesk Fusion 360 software to enable virtual assembly of machine components before physical production. The outcomes of the virtual assembly aided in understanding the machine's functionality and the interactions among its components. Therefore, the modifications to the coffee bean husking machine have assisted coffee farmers in producing higher-quality beans and expediting the coffee processing process.

Evaluating the Efficacy of AI Chatbots as Tutors in Urology: A Comparative Analysis of Responses to the 2022 In-Service Assessment of the European Board of Urology

Introduction: This study assessed the potential of large language models (LLMs) as educational tools by evaluating their accuracy in answering questions across urological subtopics. Methods: Three LLMs (ChatGPT-3.5, ChatGPT-4, and Bing AI) were examined in two testing rounds, separated by 48 h, using 100 Multiple-Choice Questions (MCQs) from the 2022 European Board of Urology (EBU) In-Service Assessment (ISA), covering five different subtopics. The correct answer was defined as “formal accuracy” (FA) representing the designated single best answer (SBA) among four options. Alternative answers selected from LLMs, which may not necessarily be the SBA but are still deemed correct, were labeled as “extended accuracy” (EA). Their capacity to enhance the overall accuracy rate when combined with FA was examined. Results: In two rounds of testing, the FA scores were achieved as follows: ChatGPT-3.5: 58% and 62%, ChatGPT-4: 63% and 77%, and BING AI: 81% and 73%. The incorporation of EA did not yield a significant enhancement in overall performance. The achieved gains for ChatGPT-3.5, ChatGPT-4, and BING AI were as a result 7% and 5%, 5% and 2%, and 3% and 1%, respectively (p > 0.3). Within urological subtopics, LLMs showcased best performance in Pediatrics/Congenital and comparatively less effectiveness in Functional/BPS/Incontinence. Conclusion: LLMs exhibit suboptimal urology knowledge and unsatisfactory proficiency for educational purposes. The overall accuracy did not significantly improve when combining EA to FA. The error rates remained high ranging from 16 to 35%. Proficiency levels vary substantially across subtopics. Further development of medicine-specific LLMs is required before integration into urological training programs.

Seismic behaviour of Exterior RC beam-column joints repaired and strengthened using post-tensioned metal straps

Exterior beam-column joints are the most vulnerable part of substandard reinforced concrete (RC) buildings and are often the first to be damaged during earthquakes. This article presents an experimental and numerical investigation into the behaviour of exterior RC beam-column joints repaired and strengthened using Post-Tensioned Metal Straps (PTMS) for active confinement. The study focused on full-scale beam-column joints with an inadequate core zone detailing, thus emulating the deficiencies found in existing substandard RC buildings. Initially, four “bare” joints were subjected to cyclic tests to induce substantial damage within the core zone. Subsequently, the damaged core of the joints was repaired and recast with new concrete, and PTMS were applied to strengthen the joints, followed by another round of cyclic testing. The experimental findings were compared with predictions generated through established models from existing literature. The results revealed that ASCE/SEI 41–17 guidelines accurately predict the shear capacity of the bare joints. It is shown that recasting the core with new concrete significantly increased the joint’s shear capacity by up to 42% compared their bare counterparts. The use of PTMS strengthening further enhanced the capacity by up to 25%. A “scissors model” was employed for numerical simulations of both bare and PTMS-strengthened joints using DRAIN-2DX, which proved effective at predicting their nonlinear load-displacement envelope response. This article contributes towards the development of new cost-effective post-earthquake strengthening techniques for beam-column joints, with the potential to reduce the vulnerability of substandard RC buildings in developing countries.

Machine-Guided Discovery of Acrylate Photopolymer Compositions.

Additive manufacturing (AM) can be advanced by the diverse characteristics offered by thermoplastic and thermoset polymers and the further benefits of copolymerization. However, the availability of suitable polymeric materials for AM is limited and may not always be ideal for specific applications. Additionally, the extensive number of potential monomers and their combinations make experimental determination of resin compositions extremely time-consuming and costly. To overcome these challenges, we develop an active learning (AL) approach to effectively choose compositions in a ternary monomer space ranging from rigid to elastomeric. Our AL algorithm dynamically suggests monomer composition ratios for the subsequent round of testing, allowing us to efficiently build a robust machine learning (ML) model capable of predicting polymer properties, including Young's modulus, peak stress, ultimate strain, and Shore A hardness based on composition while minimizing the number of experiments. As a demonstration of the effectiveness of our approach, we use the ML model to drive material selection for a specific property, namely, Young's modulus. The results indicate that the ML model can be used to select material compositions within at least 10% of a targeted value of Young's modulus. We then use the materials designed by the ML model to 3D print a multimaterial "hand" with soft "skin" and rigid "bones". This work presents a promising tool for enabling informed AM material selection tailored to user specifications and accelerating material discovery using a limited monomer space.

Activities of clinical pharmacologists across Europe: A survey by the European association of clinical pharmacology and therapeutics.

In order to explore clinical pharmacology and therapeutics (CPT) teaching and practices across continental Europe, the European Association of Clinical Pharmacology and Therapeutics (EACPT) made a survey in 2022 amongst its 27 affiliated societies. The survey was made available online to EACPT representatives, and 47 filled-in questionnaires were received from 25 countries (one to five per country), representing all geographic areas of Europe. Clinical pharmacologists (CPs) spend 25%, 30%, 15%, and 25% of their time in teaching, hospital activities, committees, and research, respectively, with large variations across and within countries. CPT courses are given at Schools of Medicine in all the countries except one, mostly organized and taught by medical doctors (MDs). In Central, Western, and Southern Europe, the teachers may have medicine or pharmacy training. Therapeutic drug monitoring and pharmacovigilance were the hospital activities most frequently reported, and clinical/forensic toxicology, rounds of visits, and pharmacogenetics the least. Two-thirds of the panel think CPs should be MDs. However, the transversal nature of CPT was underlined, with patients/diseases and drugs as gravity centres, thus calling for the complementary skills of MDs and PharmDs. Besides, most respondents reported that clinical pharmacists in their country are involved in rounds of visits, pharmacovigilance, TDM, and/or pharmacogenetic testing and that collaborations with them would be beneficial. CPT comes with a plurality of backgrounds and activities, all required to embrace the different pathologies and the whole lifecycle of medicinal products, but all of them being rarely performed in any given country. The willingness to use common CPT teaching material and prescribing exams at the European level is a good sign of increasing harmonisation of our discipline Europewide.

Exploring the content validity of Clinical Cultural Competence Questionnaire in diverse cultures

Cultural competence is one component of effective communication between patients, families and healthcare professionals. Tools to assess physicians’ clinical cultural competencies need validity evidence. This paper describes Lawshe’s method for determining the Content Validity Index (CVI) for the Clinical Cultural Competence Questionnaire (CCCQ) for North America (NA), Pakistan (PK) and an international group (IG) using physician simulation educators (PSEs) for diverse cultures. Five simulation educators pilot-tested the CCCQ, and initial changes were made based on their feedback. A total of 10 PSEs experts from NA, 11 PSEs from PK and 10 PSEs from IG completed two rounds of validation testing using Lawshe’s CVI survey for the CCCQ. The PSEs rated each item of the CCCQ as ‘essential’, useful but not essential’ or ‘not useful’. Lawshe’s CVI was calculated for the initial CCCQ; the CCCQ was then modified for individual items, separately for each group, NA, PK and IG. The IG comprised PSEs from Bahrain, Oman, Qatar, KSA, UAE, Australia, Argentina, India and Israel. The survey response rate was 83.33% for NA and IG and 91.6% for PK, respectively. The CVI of the CCCQ in round 1 was 0.689 for NA, 0.545 for PK and 0.691 for IG. In the second round of the CCCQ, with modified items, the CVI was 0.89 for NA, 0.802 for PK and 0.862 for IG. The major modifications suggested by the PSEs were to remove the unnecessary items, e.g. demographic information and last medical school attended, as they were deemed unnecessary or reword them for better understanding and combine related items to reduce the length of the CCCQ survey. We also evaluated the comments of PSEs from NA, PK and IG to explore the similarities and differences in their opinions regarding the CCCQ tool items. Our research emphasizes the need to thoroughly examine questionnaire content in tools like the CCCQ to accurately capture the cultural competence knowledge, attitudes and skills crucial for healthcare providers in diverse settings.

Development of a liver disease-specific large language model chat interface using retrieval-augmented generation.

Large language models (LLMs) have significant capabilities in clinical information processing tasks. Commercially available LLMs, however, are not optimized for clinical uses and are prone to generating hallucinatory information. Retrieval-augmented generation (RAG) is an enterprise architecture that allows the embedding of customized data into LLMs. This approach "specializes" the LLMs and is thought to reduce hallucinations. We developed "LiVersa," a liver disease-specific LLM, by using our institution's protected health information-complaint text embedding and LLM platform, "Versa." We conducted RAG on 30 publicly available American Association for the Study of Liver Diseases guidance documents to be incorporated into LiVersa. We evaluated LiVersa's performance by conducting 2 rounds of testing. First, we compared LiVersa's outputs versus those of trainees from a previously published knowledge assessment. LiVersa answered all 10 questions correctly. Second, we asked 15 hepatologists to evaluate the outputs of 10 hepatology topic questions generated by LiVersa, OpenAI's ChatGPT 4, and Meta's Large Language Model Meta AI 2. LiVersa's outputs were more accurate but were rated less comprehensive and safe compared to those of ChatGPT 4. We evaluated LiVersa's performance by conducting 2 rounds of testing. First, we compared LiVersa's outputs versus those of trainees from a previously published knowledge assessment. LiVersa answered all 10 questions correctly. Second, we asked 15 hepatologists to evaluate the outputs of 10 hepatology topic questions generated by LiVersa, OpenAI's ChatGPT 4, and Meta's Large Language Model Meta AI 2. LiVersa's outputs were more accurate but were rated less comprehensive and safe compared to those of ChatGPT 4. In this demonstration, we built disease-specific and protected health information-compliant LLMs using RAG. While LiVersa demonstrated higher accuracy in answering questions related to hepatology, there were some deficiencies due to limitations set by the number of documents used for RAG. LiVersa will likely require further refinement before potential live deployment. The LiVersa prototype, however, is a proof of concept for utilizing RAG to customize LLMs for clinical use cases.

External quality assessment to support the WHO ProSPeRo study for the evaluation of two dual HIV/syphilis point-of-care tests in seven countries

BackgroundSexually transmitted infections (STIs) such as syphilis and HIV remain to be a significant public health issue worldwide. Dual rapid point-of-care tests (POCTs) have shown promise for detecting antibodies to HIV and syphilis but have not been fully evaluated in the field. Our study supported the WHO ProSPeRo study on Sexually Transmitted Infection Point-of-Care Testing (STI POCT) by providing external quality assessment (EQA) for HIV and syphilis testing in reference laboratories and their associated clinical sites in seven countries.MethodsHIV/syphilis serum liquid and dried tube specimen (DTS) panels were prepared by CDC. Liquid panels were distributed to the reference laboratories for three rounds of testing using commercially and locally available laboratory-based serological tests. DTS panels were sent to the clinical testing sites for 8 rounds of POC testing using the Abbott SD BIOLINE HIV/Syphilis Duo test (hereafter referred to as SD BIOLINE) and the Chembio Dual Path Platform (DPP) HIV-Syphilis assay. EQA panels were tested at CDC using the Rapid Plasma Reagin (RPR) test and the Treponema pallidum Particle Agglutination assay (TP-PA) for syphilis antibodies. Genetic Systems HIV-1/HIV-2 Plus O EIA, Geenius HIV Supplemental Assay and the Oraquick Advance HIV test were used to detect HIV antibodies in the EQA panels. Results from the reference laboratories and POCT sites were compared to those obtained at the CDC and a percentage agreement was calculated.ResultsQualitative RPR and TP-PA performed at the reference laboratories demonstrated 95.4–100% agreement with CDC results while quantitative RPR and TP-PA tests demonstrated 87.7% and 89.2% agreement, respectively. A 93.8% concordance rate was observed for qualitative HIV testing in laboratories. EQA testing at clinical sites using dual tests showed 98.7% and 99.1% agreement for detection of HIV antibodies and eight out of 10 sites had > 95.8% agreement for syphilis testing. However, two clinical sites showed only 65.0–66.7% agreement for SD BIOLINE and 84.0–86.7% for DPP, respectively, for syphilis testing.ConclusionsOverall, laboratories demonstrated high EQA performance in this study. Both HIV/syphilis POCTs gave expected results in the clinic-based evaluations using DTS. However, testing errors were identified in a few testing sites suggesting the necessity for continuous training and monitoring the quality of POC testing.

Iterative Patient Testing of a Stimuli-Responsive Swallowing Activity Sensor to Promote Extended User Engagement During the First Year After Radiation: Multiphase Remote and In-Person Observational Cohort Study.

Frequent sensor-assisted monitoring of changes in swallowing function may help improve detection of radiation-associated dysphagia before it becomes permanent. While our group has prototyped an epidermal strain/surface electromyography sensor that can detect minute changes in swallowing muscle movement, it is unknown whether patients with head and neck cancer would be willing to wear such a device at home after radiation for several months. We iteratively assessed patients' design preferences and perceived barriers to long-term use of the prototype sensor. In study 1 (questionnaire only), survivors of pharyngeal cancer who were 3-5 years post treatment and part of a larger prospective study were asked their design preferences for a hypothetical throat sensor and rated their willingness to use the sensor at home during the first year after radiation. In studies 2 and 3 (iterative user testing), patients with and survivors of head and neck cancer attending visits at MD Anderson's Head and Neck Cancer Center were recruited for two rounds of on-throat testing with prototype sensors while completing a series of swallowing tasks. Afterward, participants were asked about their willingness to use the sensor during the first year post radiation. In study 2, patients also rated the sensor's ease of use and comfort, whereas in study 3, preferences were elicited regarding haptic feedback. The majority of respondents in study 1 (116/138, 84%) were willing to wear the sensor 9 months after radiation, and participant willingness rates were similar in studies 2 (10/14, 71.4%) and 3 (12/14, 85.7%). The most prevalent reasons for participants' unwillingness to wear the sensor were 9 months being excessive, unwanted increase in responsibility, and feeling self-conscious. Across all three studies, the sensor's ability to detect developing dysphagia increased willingness the most compared to its appearance and ability to increase adherence to preventive speech pathology exercises. Direct haptic signaling was also rated highly, especially to indicate correct sensor placement and swallowing exercise performance. Patients and survivors were receptive to the idea of wearing a personalized risk sensor for an extended period during the first year after radiation, although this may have been limited to well-educated non-Hispanic participants. A significant minority of patients expressed concern with various aspects of the sensor's burden and its appearance. ClinicalTrials.gov NCT03010150; https://clinicaltrials.gov/study/NCT03010150.

KovaaK's aim trainer as a reliable metrics platform for assessing shooting proficiency in esports players: a pilot study.

Esports research lacks game-based metrics platforms appropriate for adequately capturing esports performance. The aim of this pilot study was to assess the reliability of the KovaaK's first-person shooter (FPS) aim trainer as a metrics platform for assessing shooting proficiency in esports players. Ten FPS esports players completed two identical experimental trials (T) separated by three to five days. Each trial included four rounds (R) of testing, evaluating four shooting tasks: Micro Flicking, Macro Flicking, Strafe Tracking, and Wall Peeking. Reliability of performance outcomes (e.g., accuracy, headshot accuracy, hits per second, and total shots hit) were assessed using the intraclass correlation coefficient (ICC) and their 95% confidence intervals (CI), and significant differences were identified using repeated-measures analysis of variance (RM-ANOVA). Results indicated excellent, or good to excellent reliability for all outcome variables with the ICC estimates ranging between 0.947-0.995, with lower and upper bound 95% CIs ranging between 0.876-0.988, and 0.984-0.999, respectively. Significant improvements were seen between experimental trials in the Macro Flicking task for accuracy (p = .005) and hits per second (p = .009) only. Significant interactions between trial and round were identified in the Micro Flicking task for accuracy (p = .006), with post hoc analysis showing accuracy was significantly higher in T1R1 compared to T2R1 (87.74 ± 3.13 vs. 85.99 ± 3.05, respectively, p = .02), and in T2R4 compared to T2R2 (87.99 ± 2.89 vs. 84.70 ± 4.25, respectively, p = .049). Significant interactions were also identified in the Strafe Tracking task for headshot accuracy (p = .002), with post hoc analysis showing headshot accuracy was significantly higher in T1R2 compared to T2R2 (78.48 ± 8.15 vs. 76.79 ± 12.16, respectively, p = .003), and in T1R2 compared to T1R1 (78.48 ± 8.15 vs. 73.68 ± 17.94, respectively, p = .023). In summary, this study demonstrates that KovaaK's provides a reliable metrics platform for assessing shooting proficiency in esports, however, some variability in performance was observed.

Developing a tool to optimize research on antioxidants for rooster semen cryopreservation

This study aimed to develop a tool for predicting the potential impact of research studies involving the effect of antioxidants in rooster semen freezing diluent, depending on the variables that have been studied. To achieve this, a comprehensive meta-analysis of fifty-eight research documents was performed. Sixty-two traits were sorted into four major categories: study demographics, study design-related parameters, rooster semen quality-related parameters, and fertility level indicators. The quartile determination of each research document was collected from the Journal Citation Reports database. After twenty-five testing rounds, all variables that showed multicollinearity problems were discarded from further analyses (VIF < 5). HOST, pellet volume, mass motility, light hours, and sperm concentration were the most influential traits for the classification of papers in different quartiles (Wilks’ lambda: 0.797, 0.891, 0.895, 0.896, and 0.904, respectively). The research was validated as reported in the cross-validation analysis, with 93.60% of papers being correctly classified within their group. The present research assists researchers not only in the decision-making process for journals in which to publish the outcomes of their studies, but also to seek for the inclusion of parameters which attract a wider interest for the matter from scientific readers. This leads to the optimisation of resources in studies evaluating the effect of antioxidants in poultry reproduction by identifying the most scientifically relevant variables and those which in trun will lead toa greater impact on research publications.

Large‐scale hybrid test of a curved bridge considering complete boundary condition by a large spatial loading system

AbstractSmall‐radius curved bridges are mostly used for overpass ramps, that are spatially irregular and usually have very complex seismic behavior. It is not easy to reproduce such behavior because of the need for large‐scale shaking tables. The hybrid test is one of the most effective approaches for solving this problem by considering the structural elements of interest as physically tested substructure while the rest is numerically simulated. In this paper, a hybrid test system was first developed based on the OpenFresco framework, where one of the piers was considered as the tested substructure, and the rest was simulated by OpenSees. A novel spatial loading device (SLD), configured as the Stewart pattern, was then developed to achieve the boundary conditions between substructures. The control schemes to perform the force‐displacement mixed control, conduct the geometric transformation while considering the load point offset, and achieve an external displacement control were proposed and validated through several rounds of hybrid testing. The experimental results indicate that the experimental system including loading control subsystem and hybrid control subsystem can realize the loading command accurately.

An Improved Fault Diagnosis Algorithm for Highly Scalable Data Center Networks

Fault detection and localization are vital for ensuring the stability of data center networks (DCNs). Specifically, adaptive fault diagnosis is deemed a fundamental technology in achieving the fault tolerance of systems. The highly scalable data center network (HSDC) is a promising structure of server-centric DCNs, as it exhibits the capacity for incremental scalability, coupled with the assurance of low cost and energy consumption, low diameter, and high bisection width. In this paper, we first determine that both the connectivity and diagnosability of the m-dimensional complete HSDC, denoted by HSDCm(m), are m. Further, we propose an efficient adaptive fault diagnosis algorithm to diagnose an HSDCm(m) within three test rounds, and at most N+4m(m−2) tests with m≥3 (resp. at most nine tests with m=2), where N=m·2m is the total number of nodes in HSDCm(m). Our experimental outcomes demonstrate that this diagnosis scheme of HSDC can achieve complete diagnosis and significantly reduce the number of required tests.

Teacher RePlay and Children ReAct: pilot testing a formative toolkit to support playful learning in the classroom

Playful learning has seen a resurgence of interest in the past decade, particularly in contexts where play is not traditionally part of a teacher’s repertoire. Teachers interested in exploring the integration of play in their classrooms need formative tools and resources that help them to reflect and assess their own practice and their ability to create a playful learning experience for their students. This study presents the results of two rounds of pilot testing in three countries for Teacher RePlay, a new open-source toolkit designed to support teachers interested in reflecting on and deepening their learning through play practice. The toolkit includes the main Teacher RePlay observation protocol for teachers, as well as Children ReAct, a complementary protocol for a photo-elicited focus group discussion with children, intended to directly assess children’s experiences and reflections on learning through play. Upon observation, teachers receive customized coaching suggestions and tips designed to strengthen their learning through play practice. Initial results from the piloting indicate that the toolkit holds strong potential for teachers interested in better understanding and deepening their playful learning practice. This paper discusses the development, validation, successes, and challenges of the Teacher RePlay toolkit, and identifies future directions for its use.

Pengaruh Manajemen Laba, Intellectual Capital dan Related Party Transaction terhadap Integritas Laporan Keuangan: Studi pada Perusahaan Sektor Manufaktur yang Terdaftar di Bursa Efek Indonesia Periode 2018-2021

In order for the information obtained by users of financial statements to be accounted for by the firm, financial statements and statements by corporations must be provided honestly, correctly, and without distortion or concealment. Users use financial reports as a decision-making tool since they provide an overview of the performance and growth of the organization. Conservativeness proxies may be used to evaluate the reliability of the financial accounts. To minimize fraud in financial reports and mistakes in decision-making, conservative accounting is the practice of presenting financial statements that are full of caution against important uncertainties and risks to a commercial business's situation. The goal of this research is to assess the financial reporting accuracy of manufacturing sector businesses listed on the Indonesia Stock Exchange (IDX) from 2018 to 2021 in the areas of intellectual property, related party transactions, and earnings management. This study uses the manufacturing sector of the IDX as its sample population for the years 2018 through 2021. Purposive sampling was employed, and data was collected from 408 samples representing 102 different firms over the course of four years. Panel data regression analysis using the Eviews 10 software is used for this in-depth examination of the data, which involves several rounds of testing. Financial statement accuracy was shown to be impacted by the presence of related party transactions, intellectual property, and earnings management. Earnings management reduces financial statement reliability. On the other hand, related party transactions and intellectual property have no bearing on how accurate the financial records are.

542 - Validation of the skin pain numerical rating scale of the Pruritus and Symptoms Assessment for Atopic Dermatitis for adults and adolescents with moderate-to-severe atopic dermatitis

Abstract Background Skin pain is a common and burdensome symptom of atopic dermatitis (AD), and its severity increases with disease progression. The Pruritus and Symptoms Assessment for Atopic Dermatitis (PSAAD) is a validated 11-item patient-reported instrument developed in accordance with regulatory agency guidance for assessment of the daily symptoms of patients with AD, including skin pain. Objective To establish content validity and evaluate the psychometric properties of the skin pain numerical rating scale (NRS) item of the PSAAD. Methods The skin pain NRS is a single-item measure from the PSAAD and is used to assess skin pain severity over the past 24 hours with the question “How painful was your skin over the past 24 hours?” on a 10-point scale from 0 (not painful) to 10 (extremely painful). A qualitative validation analysis consisting of concept elicitation (CE) interviews; electronic completion of the PSAAD measure, including the skin pain NRS; and cognitive debriefing (CD) interviews was conducted for adults and adolescents with mild-to-severe AD. Evaluation of psychometric properties of the skin pain NRS—including test-retest reliability, estimation of meaningful within-patient change (MWPC), known-group validity, ability to detect change, construct validity, quality of completion, and ceiling and floor effects—was conducted based on a post hoc qualitative and quantitative analysis of pooled data, with skin pain NRS as part of the PSAAD in the abrocitinib monotherapy phase 3 trials JADE MONO-1 (NCT03349060) and JADE MONO-2 (NCT03575871). Data from patients (≥12 years of age) with moderate-to-severe AD were pooled across all treatment arms. Results Among 30 CE interviews (adolescents [12-17 years], n=15; adults [≥18 years], n=15) conducted over 2 rounds of testing, 20 of 30 (67%) patients reported skin pain. During CD interviews (n=30), 100% of patients interpreted the skin pain NRS item as intended, and 73% reported it as relevant. The psychometric validation analysis included 736 patients (JADE MONO-1, N=347; JADE MONO-2, N=389). The test-retest reliability of the skin pain NRS was evidenced by large intraclass correlation coefficients (ICC; 0.76 and 0.72 in JADE MONO-1 and MONO-2, respectively) for a single daily skin pain score, which increased to 0.93 and 0.91 for a measurement averaging at least 4 scores per week. Convergent validity was demonstrated by correlations between skin pain and other clinician- and patient-­reported AD measures (median correlation &amp;gt;0.4 starting at week 4). The skin pain NRS distinguished between “clear” and “severe” disease severity groups, assessed using the Patient Global Assessment (PtGA) and Investigator’s Global Assessment (IGA) as continuous and categorical anchors (P&amp;lt;0.0001); differences were also significant among other disease severity groups using the PtGA and IGA as continuous anchors (P&amp;lt;0.0001). Based on the PtGA and IGA anchor analysis, the estimated MWPC was 1.9 and ranged from 2.7 to 3.9 points using the empirical cumulative distribution function analysis. Ability to detect change was demonstrated by linear relationships between disease severity measures and skin pain scores (correlation of ≥0.5 between the skin pain NRS and the PtGA). More than 90% of patients provided at least 4 daily skin pain scores each week. No floor or ceiling effects were observed. Conclusions The qualitative and quantitative data from initial PSAAD development and psychometric evaluation of the skin pain NRS from the PSAAD support its content validity, reliability, construct validity, and ability to detect change. These findings corroborate the 4-point improvement in skin pain as the adequate and meaningful cut-off to define a skin pain responder in JADE MONO-1 and MONO-2.

Skeletal reconstruction of fossil vertebrates as a process of hypothesis testing and a source of anatomical and palaeobiological inferences

Reconstructions of extinct animals play an important role in vertebrate palaeontology. Such reconstructions represent visual hypotheses regarding the original morphology of the vertebrates they depict, which are amenable to future testing as additional information comes to light through discoveries of new specimens and re-examination of specimens that have already been collected. In this contribution, we argue that the scientific value of reconstructing a fossil vertebrate extends beyond simple presentation of a visual hypothesis, because the process of creating a reconstruction is itself analytical and hypothetico-deductive. Successive drafts of the reconstruction represent provisional visual hypotheses that can be tested on the basis of their internal consistency and their congruence with empirical evidence about the extinct taxon that is the reconstruction’s subject. Iterative refinement of the reconstruction over successive rounds of testing and modification is likely to lead to discoveries about the subject’s anatomy, as certain anatomical possibilities are rejected and others found to be plausible. These anatomical discoveries, here termed first-order inferences, may in turn lead to second-order inferences about functional morphology or other aspects of palaeobiology. Three case studies from dinosaur palaeontology, respectively involving the skull of the hadrosaurid Edmontosaurus Lambe, 1917, the forelimb of the ceratopsid Pachyrhinosaurus Sternberg, 1950, and the hindlimb of an indeterminate ceratopsid, are provided to illustrate how the process of reconstruction can be a fertile source of discoveries.

Incidence of Fit Test Failure During N95 Respirator Reuse and Extended Use

The COVID-19 pandemic resulted in a widespread acute shortage of N95 respirators, prompting the Centers for Disease Control and Prevention to develop guidelines for extended use and limited reuse of N95s for health care workers (HCWs). While HCWs followed these guidelines to conserve N95s, evidence from clinical settings regarding the safety of reuse and extended use is limited. To measure the incidence of fit test failure during N95 reuse and compare the incidence between N95 types. This prospective cohort study, conducted from April 2, 2021, to July 15, 2022, at 6 US emergency departments (EDs), included HCWs who practiced N95 reuse for more than half of their clinical shift. Those who were unwilling to wear an N95 for most of their shift, repeatedly failed baseline fit testing, were pregnant, or had facial hair or jewelry that interfered with the N95 face seal were excluded. Wearing the same N95 for more than half of each clinical shift and for up to 5 consecutive shifts. Participants chose an N95 model available at their institution; models were categorized into 3 types: dome (3M 1860R, 1860S, and 8210), trifold (3M 1870+ and 9205+), and duckbill (Halyard 46727, 46767, and 46827). Participants underwent 2 rounds of testing using a different mask of the same type for each round. The primary outcome was Occupational Safety and Health Administration-approved qualitative fit test failure. Trained coordinators conducted fit tests after clinical shifts and recorded pass or fail based on participants tasting a bitter solution. A total of 412 HCWs and 824 N95s were fit tested at baseline; 21 N95s (2.5%) were withdrawn. Participants' median age was 34.5 years (IQR, 29.5-41.8 years); 252 (61.2%) were female, and 205 (49.8%) were physicians. The overall cumulative incidence of fit failure after 1 shift was 38.7% (95% CI, 35.4%-42.1%), which differed by N95 type: dome, 25.8% (95% CI, 21.2%-30.6%); duckbill, 28.3% (95% CI, 22.2%-34.7%); and trifold, 61.3% (95% CI, 55.3%-67.3%). The risk of fit failure was significantly higher for trifold than dome N95s (adjusted hazard ratio, 1.75; 95% CI, 1.46-2.10). In this cohort study of ED HCWs practicing N95 reuse, fit failure occurred in 38.7% of masks after 1 shift. Trifold N95s had higher incidence of fit failure compared with dome N95s. These results may inform pandemic preparedness, specifically policies related to N95 selection and reuse practices.

Predicting compressive and flexural strength of high-performance concrete using a dynamic Catboost Regression model combined with individual and ensemble optimization techniques

Compressive Strength (CS) and Flexural Strength (FS) cannot be overstated when designing reinforced concrete structures, as industry standards govern these factors. Creating reliable predictive models for these properties offers the potential to enhance cost-effectiveness and efficiency by decreasing the necessity for numerous rounds of lab testing and iterative experiments, which are essential for obtaining valuable design information. In construction, evaluating the characteristics of advanced high-performance concrete (HPC) is crucial. Machine learning techniques are widely recognized as competent tools for forecasting the mechanical characteristics of concrete substances. This research centers on the comparison of different algorithms, including the standalone Catboost Regression model (CAT), hybrid models that incorporate the CAT model along with two distinct optimization algorithms, namely Artificial Rabbits Optimization (ARO) and Honey Badger Algorithm (HBA), as well as an ensemble approach that combines CAT with the ARO-HBA ensemble optimization algorithm. Considering the results indicated by the R2 values, the CAHB model showed significantly better performance in predicting both CS (R2trainCAHB=0.996) and FS (R2trainCAHB=0.994). Furthermore, when examining statistical accuracy metrics such as RMSE and MAE, it became evident that CAHB performed significantly better than CAT in forecasting the mechanical properties of concrete.

Older adults' name-face association learning is facilitated for names with high-frequency first syllables.

Older adults have even greater difficulty learning name-face associations than young adults, although many variables reflecting properties of the names have been shown to affect young and older adults' name learning similarly. Older adults' name-face association learning was compared for names with high-frequency (HF) first syllables versus names with low-frequency (LF) first syllables. Twenty-eight adults ages 65 to 80 learned five names with HF first syllables and five names with LF first syllables in association with 10 new faces over repeated testing rounds with feedback. Participants learned more name-face associations when the names had HF first syllables than LF first syllables. Findings indicate that older adults benefit from increased frequency of phonological segments within a word on a task other than word retrieval and are consistent with a theoretical framework that accounts for learning new name-face associations, the effects of linguistic properties of the names, and ageing.