Comparison Of Standards Research Articles

Abstract 4136023: Eligibility and Barriers of Mavacamten Therapy in Patients with Hypertrophic Cardiomyopathy: A Retrospective Analysis

Background: Hypertrophic Cardiomyopathy (HCM) is a common genetic heart disorder characterized by the thickening of the myocardium. Mavacamten has emerged as a novel medication for targeted therapy in HCM patients, but its adoption faces multiple hurdles. This study aims to evaluate the eligibility of HCM patients for Mavacamten treatment based on certain clinical criteria and to promote consideration of potential barriers patients face in obtaining this medication. Methods: We conducted a retrospective analysis of 115 HCM patients at Truman Medical Center that included demographic data, clinical characteristics, and treatment histories. Patient eligibility for Mavacamten was determined based on ejection fraction (EF) > 55%, symptomatic obstructive HCM, and intolerance to first-line therapy (beta-blockers, calcium channel blockers). Statistical analysis was performed using standard deviation and mean comparisons to estimate the proportion of eligible patients. Results: Out of 115 patients, 96 patients have an EF>55%. 76 patients (66.1%) have a clinical heart failure diagnosis. 94 patients (81.7%) are taking beta-blockers. 49 patients (42.6%) have uncontrolled hypertension indicated by blood pressure >140. Considering these factors, 49 (42.6%) met the clinical criteria for Mavacamten treatment. Of these patients eligible to receive Mavacamten treatment, only one patient was actively taking Mavacamten. The most common obstacles to receiving the drug included lack of insurance coverage, high medication cost, and limited awareness among healthcare providers regarding new treatment options. Conclusion: While a considerable proportion of HCM patients qualify for Mavacamten based on clinical criteria, external factors significantly impede access to this potentially life-altering treatment. Efforts should address this treatment gap through raising awareness to healthcare professionals and improving insurance coverage. This will enhance patient access to Mavacamten, ultimately improving outcomes in HCM management. This study summarizes the eligibility and obstacles to Mavacamten in a sample of HCM patients, emphasizing the need for systemic changes to facilitate access to advanced therapies.

Optimal planning and operation of heterogeneous autonomous and grid-connected microgrids based on multi-criteria techno-economic, environmental, and social indices

Sustainable energy transition involves the execution of recent technologies as a means of ensuring energy access and security. However, the increasing adoption of such technologies, particularly in the presence of diverse constraints, poses significant challenges from a planning perspective. In this context, the multi-objective analysis offers valuable insights for decision-making that balances mutual benefits, as relying solely on a single objective may increase the risk level for stakeholders engaged in coordinated decisions. Based on the real dataset, this study presents a comparative multi-criteria techno-economic, environmental, and social evaluation of site-specific unified standalone and grid-connected hybrid microgrids. The study employs a modified Last Cluster Mean Carried Forward approach for data processing, incorporating the Proprietary Derivative-free Algorithm and Original Grid-Search Algorithm to ensure a standardized comparison. Results reveal the substantial advantages of grid-connected systems over standalone counterparts, with reductions of 12.54 % to 63.73 % and 68.93 % to 89.13 % in terms of Net Present Cost and Levelized Cost of Energy, respectively. Grid-connected systems exhibit superior adaptability, recovering 52.3 % to 98.1 % surplus energy with a Renewable Fraction averaging 77.1 % to 87.9 %. However, these systems were hindered by frequent interruptions and required a minimum capacity shortage of 2.5 % to 3.5 %. Furthermore, grid-connected systems have proved feasible when carbon emissions, forests required to absorb the emissions, and the Social Cost of Carbon Emissions are considered in the range of 4.65–67.13 kiloton (metric), 423.32–6108.53 ha, and $0.24-$3.42 million, respectively. Social analysis and sensitivity analyses are performed to justify the robustness and adaptability. Lastly, the findings are followed by policy recommendations and results validation by comparing prevailing government tariffs and other studies.

Unlocking Heat Transfer Potential in Multi-Sided Porous Geometries: A Study on Magnetothermal Effects and Entropy Generation

This study investigates heat transfer efficiency and irreversibility generation in multi-sided porous thermal systems filled with a Cu-Al2O3-water hybrid nanofluid. The research examines convective heat transfer across various polygonal geometries, ranging from four-sided to infinitely-sided (circular) structures, aiming to maximize thermal system performance intended for scientific and industrial applications. For a standardized comparison, the fluid volume and active heating and cooling lengths are kept constant for all the geometries considered. The analysis includes varying flow-controlling variables like the modified Rayleigh number (Ram), Hartmann number (Ha), and Darcy number (Da) to evaluate how they affect heat transfer efficiency and entropy generation, including total, magnetic, and viscous entropy. The numerical simulations, conducted using the finite element approach, explore Ram values ranging from 10 to 104, Ha from 0 to 70, and Da from 10-4 to 10-2. Streamline and isothermal contours analyze flow behavior, while heatline tools reveal thermal energy transport dynamics. Results show up to a 20% improvement in heat transfer efficiency in optimized configurations. Key findings indicate that hexagonal structures can be viable alternatives to circular tubes in space-constrained applications, offering comparable thermal performance. Interestingly, pentagonal cavities exhibit the highest irreversibility due to symmetry loss. The study offers insightful information for enhancing thermal system design in various industrial settings, particularly for applications requiring efficient heat transfer in limited spaces.

Few-shot Algorithms for Consistent Neural Decoding (FALCON) Benchmark.

Intracortical brain-computer interfaces (iBCIs) can restore movement and communication abilities to individuals with paralysis by decoding their intended behavior from neural activity recorded with an implanted device. While this activity yields high-performance decoding over short timescales, neural data are often nonstationary, which can lead to decoder failure if not accounted for. To maintain performance, users must frequently recalibrate decoders, which requires the arduous collection of new neural and behavioral data. Aiming to reduce this burden, several approaches have been developed that either limit recalibration data requirements (few-shot approaches) or eliminate explicit recalibration entirely (zero-shot approaches). However, progress is limited by a lack of standardized datasets and comparison metrics, causing methods to be compared in an ad hoc manner. Here we introduce the FALCON benchmark suite (Few-shot Algorithms for COnsistent Neural decoding) to standardize evaluation of iBCI robustness. FALCON curates five datasets of neural and behavioral data that span movement and communication tasks to focus on behaviors of interest to modern-day iBCIs. Each dataset includes calibration data, optional few-shot recalibration data, and private evaluation data. We implement a flexible evaluation platform which only requires user-submitted code to return behavioral predictions on unseen data. We also seed the benchmark by applying baseline methods spanning several classes of possible approaches. FALCON aims to provide rigorous selection criteria for robust iBCI decoders, easing their translation to real-world devices.

Initiation response, maximized therapeutic efficacy, and post-treatment effects of biological targeted therapies in myasthenia gravis: a systematic review and network meta-analysis.

As targeted drug development in myasthenia gravis (MG) continues to advance, it is important to compare the efficacy of these drugs for better clinical decision-making. However, due to the varied regimens and dosages used in clinical trials for different drugs, a standardized comparison between them is necessary. This study enrolled participants in phase II and III trials of innovative targeted drugs for MG. The primary outcome was the change in Quantitative Myasthenia Gravis score (MG-QMG) from baseline. The efficacy of all drugs at four time points was separately analyzed at four time points: initiation 1 week, initiation 4 weeks, maximized response, and post last dose 4 weeks. A network meta-analysis was conducted to compare the results of the different drugs. A total of 9 drugs, including Efgartigimod, Rozanolixizumab, Batoclimab, Eculizumab, Belimumab, Zilucoplan, Ravulizumab, Nipocalimab, Rituximab, derived from 12 studies were analyzed. At the initiation 1-week time point, three drugs exhibited significant improvement compared to the placebo effect: Efgartigimod, Zilucoplan, Rozanolixizumab. At the initiation 4-week time point, four drugs showed significant improvement compared to the placebo effect: Efgartigimod, Rozanolixizumab, Batoclimab, Zilucoplan. At the maximized response time point, six drugs achieved significant improvement compared to the placebo effect: Efgartigimod, Rozanolixizumab, Batoclimab, Eculizumab, Zilucoplan, Ravulizumab. At the post last dose 4-week point, all drugs statistically showed no significant difference from the placebo. Although the MG subtypes were not consistent across trials, within the regimen design of each trial, neonatal Fc receptor inhibitors-represented by Efgartigimod, Rozanolixizumab, and Batoclimab-exhibited the most effective response rates when compared to complement and B-cell inhibitor drugs.

Vibration Thresholds Using Conventional Audiometry are Clinically Useful Indicators of Postural Instability in Older Adults.

Falls are a major health concern with potentially dramatic consequences for people over 65 years of age. One crucial determinant in the risk of falls in older adults is postural control, a complex process that requires the contribution of different sensory modalities, namely visual, vestibular, auditory, and somatosensory. While there are well-established methods to screen for age-related vision, hearing, tactile, and vestibular impairments, there are very few widely available methods to screen for somatosensory function, but studies indicate that ankle audiometry (vibration thresholds) using a common B-71 bone vibrator can serve that purpose. To date, unfortunately, this technique has received little attention as a tool to measure postural instability in older adults. The objective of the present study was to examine postural control in older adults with and without degradation of the somatosensory functions, as determined with ankle audiometry. This was standard group comparison. In total, 36 healthy elderly aged between 65 and 80 years old were divided into two groups (low vibration threshold [n = 18] and high vibration threshold [n = 18]). Standard audiometry, video head impulse test, vibration thresholds (big toe, ankle, and tibia), and static postural control task using a force platform were performed. Greater postural instability in participants with higher (worse) vibration thresholds as compared with participants with lower (better) vibration thresholds was observed even though both groups were comparable on hearing threshold and vestibular function. The results indicate that performing a simple vibration threshold evaluation, using a clinically available B-71 with a cut-off value of 42 dB hearing loss, could be an effective, fast, and easy-to-use procedure for detecting people at risk of falls.

X-Shooting ULLYSES: Massive Stars at low metallicity. IX.Empirical constraints on mass-loss rates and clumping parameters for OB supergiants in the Large Magellanic Cloud

Current implementations of mass loss for hot, massive stars in stellar evolution models usually include a sharp increase in mass loss when blue supergiants become cooler than $T_ eff 20-22$ kK. Such a drastic mass-loss jump has traditionally been motivated by the potential presence of a so-called bistability ionisation effect, which may occur for line-driven winds in this temperature region due to recombination of important line-driving ions. We perform quantitative spectroscopy using UV (ULLYSES program) and optical (XShootU collaboration) data for 17 OB-supergiant stars in the LMC (covering the range $T_ eff 14-32$ kK), deriving absolute constraints on global stellar, wind, and clumping parameters. We examine whether there are any empirical signs of a mass-loss jump in the investigated region, and we study the clumped nature of the wind. We used a combination of the model atmosphere code fastwind and the genetic algorithm (GA) code Kiwi-GA to fit synthetic spectra of a multitude of diagnostic spectral lines in the optical and UV. We find an almost monotonic decrease of mass-loss rate with effective temperature, with no signs of any upward mass loss jump anywhere in the examined region. Standard theoretical comparison models, which include a strong bistability jump thus severely overpredict the empirical mass-loss rates on the cool side of the predicted jump. Another key result is that across our sample we find that on average about 40<!PCT!> of the total wind mass seems to reside in the more diluted medium in between dense clumps. Our derived mass-loss rates suggest that for applications such as stellar evolution one should not include a drastic bistability jump in mass loss for stars in the temperature and luminosity region investigated here. The derived high values of interclump density further suggest that the common assumption of an effectively void interclump medium (applied in the vast majority of spectroscopic studies of hot star winds) is not generally valid in this parameter regime.

Estimation of the graft failure by current value joint model, and extension to alternative parameterization structures: Cohort study.

In clinical practice, individuals are followed up to predict the outcome event of interest, and their longitudinal measurements are collected on a regular or irregular basis. We aimed to examine the classical approach, joint model (JM), and alternative parameterization structures using data on the effect of time-varying longitudinal measurements on survival. The motivating cohort dataset included 158 consecutive kidney transplant recipients who had baseline and follow-up data. Although the longitudinal log-transformed estimated glomerular filtration rate (log[eGFR]) measurements and graft failure have an association clinically, the 2 processes are analyzed separately in the classical approach. In addition to the extended Cox model, the current value JM, the weighted cumulative effect JM, and dynamic predictions were performed in the study, by taking advantage of R codes. Of the 158 patients, 34.8% were males. The mean age was 29.8 ± 10.9 years, and the median age was 26 years at the time of transplantation. The hazard ratio for graft failure was 8.80 for a 1-unit decrease in log(eGFR) in the extended Cox model, 10.58 in the current value JM, and 3.65 in the weighted cumulative effect JM. The presence of coronary heart disease was also found to be associated with log(eGFR): 0.199 (P = .03) for the current value JM and 0.197 (P = .03) for the weighted cumulative effect JM. The current value JM was identified as a better model than the extended Cox model and the weighted cumulative effect JM based on parameter and standard error comparison and goodness of fit criteria. JMs should be preferred, as they facilitate better clinical decisions by accounting for the varying slopes and longitudinal variation of estimated glomerular filtration rate among patients. Suitable types of models should be practiced depending on baseline biomarker levels, their trends over time, the distribution of the biomarkers, and the number of longitudinal biomarkers.

Based on Spectrum-Effect Relationship, Network Pharmacology, and Molecular Docking, the Material Basis and Mechanism of Antioxidant Effect of Miao Medicine Indigofera stachyoides Lindl Were Studied.

Indigofera stachyoides Lindl (IS.Lindl, Xuerensen in Chinese) is a traditional medicine frequently utilized by ethnic minorities; nevertheless, the chemicals responsible for these effects have not been identified. Ultraperformance liquid chromatography (UPLC) was utilized to establish the fingerprints of various origins. Free radical scavenging in 1,1-diphenyl-2-trinitrophenylhydrazine (DPPH) and 2,2-biazobis(3-ethyl-phenylpropylthiazole-6-sulfonate) diammonium salt (ABTS) assays was used to evaluate the antioxidant activity. Partial least-squares regression analysis (PLSR) and gray correlation analysis (GRA) were utilized to determine the spectral-effect relationship in order to screen the antioxidant pharmacodynamic components. The corresponding targets were obtained from Traditional Chinese Medicine Systems Pharmacology (TCMSP) and Integrated Traditional Chinese Medicine (ITCM). Disease-related targets for antioxidants were collected from GeneCards and Online Mendelian Inheritance in Man (OMIM) databases. The PPI interaction network analysis, GO enrichment analysis, and KEGG pathway analysis were established using the online analysis platform, and Autodock software assisted in aligning the components with important targets. The fingerprint profile revealed 32 common peaks, and eight standards were identified using standard comparison, with similarity ranging from 0.920 to 0.995. The primary antioxidant components include proanthocyanidin B1, epicatechin, and proanthocyanidin B3. Important targets include EGFR, CASP3, IL6, PTGS2, and TNF. Important signaling pathways include the AGE-RAGE signaling pathways in diabetic complications, the MAPK signaling pathway, the IL-17 signaling pathway, and the pathways in cancer. The results of molecular docking technology showed that the main active ingredients of the drug could bind well to the core target. In this study, we successfully established the spectral-effect relationship of IS.Lindl and clarified the effective substances of IS.Lindl. Through network pharmacology and molecular docking methods, it was clear that IS.Lindl plays an antioxidant role through multicomponent, multitarget, and multipathway synergy.

Augmented and virtual reality imaging for collaborative planning of structural cardiovascular interventions: a proof-of-concept and validation study.

Virtual reality (VR) and augmented reality (AR) have led to significant advancements in cardiac preoperative planning, shaping the world in profound ways. A noticeable gap exists in the availability of a comprehensive multi-user, multi-device mixed reality application that can be used in a multidisciplinary team meeting. A multi-user, multi-device mixed reality application was developed, supporting AR and VR implementations. Technical validation involved a standardized testing protocol and comparison of AR and VR measurements regarding absolute error and time. Preclinical validation engaged experts in interventional cardiology, evaluating the clinical applicability prior to clinical validation. Clinical validation included patient-specific measurements for five patients in VR compared with standard computed tomography (CT) for preoperative planning. Questionnaires were used at all stages for subjective evaluation. Technical validation, including 106 size measurements, demonstrated an absolute median error of 0.69mm (0.25 to 1.18mm) compared with ground truth. The time to complete the entire task was on average, with VR measurements being faster than AR ( versus , ). On clinical validation of five preoperative patients, there was no statistically significant difference between paired CT and VR measurements (0.58 [95% CI, to 2.74], ). Questionnaires showcased unanimous agreement on the user-friendly nature, effectiveness, and clinical value. The mixed reality application, validated through technical, preclinical, and clinical assessments, demonstrates precision and user-friendliness. Further research of our application is needed to validate the generalizability and impact on patient outcomes.

Ethics in sports industry: when does sports autonomy become an excuse for animal abuse?

Abstract Money pushes sports to extremes. As the rewards for success grow, so does the pressure, with sportspeople pushing themselves ever harder. In equestrian sports, this can mean pushing the horse as well, too often to the point of abuse. This article discusses the beautiful side of equestrianism as well as its darker side, which is a bitter reality for many competition horses. It sets out a comparison of legal standards for equine animal welfare (at the level of international law, EU law and national laws) as well as those coming from sports laws. It also examines dependencies between animal protection rules under EU law and animal protection rules under the laws of individual EU Member States concerning equestrian sports. It aims to answer the questions of whether equestrian sports constitute a general exemption to their being considered animal abuse and on what grounds this exemption might be changed in the future.

Masseter and cervical vestibular evoked myogenic potentials in individuals with auditory neuropathy

Objective This study aimed to explore the functional integrity of vestibulo-masseteric and sacculo-collic reflex pathways in individuals with Auditory Neuropathy (AN). The study also aimed at finding the correlation between mVEMP and cVEMP response parameters for AN and healthy individuals. Design Standard group comparison research design Study sample Individuals with AN (n = 20); age-gender matched healthy individuals (n = 20) were recruited. Each participant underwent routine audiological evaluation; mVEMP and cVEMP testing. mVEMP and cVEMP were recorded using 500 Hz tone burst stimulus for all the participants. Results Most of the AN individuals had no mVEMP (ipsilateral & contralateral − 60%; bilateral − 50%) and cVEMP (60%) responses. There was no significant association (p > 0.05) between the duration of AN with mVEMP and cVEMP findings. However, a significant correlation (p < 0.05) was found for EMG rectified amplitude of mVEMP and cVEMP in AN. Conclusion The results of this study suggested an impaired function of the vestibulomassteric and sacculocollic reflex pathways in individuals with AN. Vestibular evaluation should be included as a part of the regular test battery for individuals with AN.

Comparing the impact of conventional and non-conventional processing technologies on water-soluble vitamins and color in strawberry nectar – a pilot scale study

A comprehensive comparison was conducted on the effect of conventional thermal processing (TT), high-pressure processing (HP), pulse electric field (PF), and ohmic heating (OH) on water-soluble vitamins and color retention in strawberry nectar. The ascorbic acid (AA) content increased by 15- and 9-fold after TT and OH treatment, respectively, due to rupturing of cells under heat stress and release of intracellular AA. Dehydroascorbic acid (DHA) content did not change considerably after TT and PF treatment but significantly decreased after HP and OH treatment. TT treatment offered the highest total vitamin C retention. The B vitamins remained largely unchanged after processing, with the highest loss of 34 % for riboflavin in OH-treated samples. All the technologies resulted in similar color retention after processing. The study concludes with a standardized comparison of mainstream preservation technologies using pilot-scale equipment. Such an approach significantly increases the applicability of the results presented in the study.

The Effectiveness, Benefits and Challenges of the Implementation of Flipped Classroom in English Teaching and Learning: A Systematic Review

The aim of doing this systematic review is to fill up the gap on the benefits, challenges, and impacts of flipped classrooms in English language instruction and learning. The research incorporates data from 36 empirical studies that were published between 2017 and 2023. Examining peer-reviewed literature from databases including Web of Science, ERIC, and Scholar Google, the review's content analysis shows the finding are: Flipped classrooms have a positive impact on (1) student learning outcomes, which increased students’ academic achievement; (2) students’ motivation to learn and classroom engagement; (3) enhances social interaction skills and independent learning through group activities. The challenges include that: (1) Some students lack motivation; therefore, they skip watching lectures and materials on video outside of the classroom; (2) there are Issues related to technology, include unreliable internet connections and insufficient technical assistance and so on will set back the outcome. Despite the potential of the flipped classroom model to promote the effectiveness of English language learning, in order to fully realize this potential, improved technological infrastructure, professional development opportunities for teachers, and the cultivation of students' self-directed learning skills are required to address the pedagogical and technological obstacles that arise during implementation. Future studies should concentrate on standardized assessment techniques, cross-cultural and educational environment comparisons, and long-term learning results.

Study and Application of Fine Dissection Methods for Inter-river Sands in Large Shallow River-controlled Delta Plains

Applying the data of coring wells and logging curves of dense well network, identifying the sedimentary sands of different river systems and contemporaneous periods with the methods of standard layer approximation control and comparison of reference layer combinations, establishing a set of logging phase models of inter-river sands, and using the models as a guideline for micro-phase identification, we have studied the distribution and combination characteristics of the micro-phase sands of the inter-river sand bodies, as well as the type of connectivity with the sand bodies of the river and the relationship, and clarified the distribution characteristics and residual oil distribution of the sand bodies of the inter-river sands. The characteristics of different types of sand body movement and residual oil distribution were clarified, effective dredging methods were proposed, and measures such as oil testing and fracturing were taken, which played an important role in guiding the adjustment and dredging of oil fields in the late stage of high water content.

Biometrics of complete human pregnancy recorded by wearable devices

In the United States, normal-risk pregnancies are monitored with the recommended average of 14 prenatal visits. Check-ins every few weeks are the standard of care. This low time resolution and reliance on subjective feedback instead of direct physiological measurement, could be augmented by remote monitoring. To date, continuous physiological measurements have not been characterized across all of pregnancy, so there is little basis of comparison to support the development of the specific monitoring capabilities. Wearables have been shown to enable the detection and prediction of acute illness, often faster than subjective symptom reporting. Wearables have also been used for years to monitor chronic conditions, such as continuous glucose monitors. Here we perform a retrospective analysis on multimodal wearable device data (Oura Ring) generated across pregnancy within 120 individuals. These data reveal clear trajectories of pregnancy from cycling to conception through postpartum recovery. We assessed individuals in whom pregnancy did not progress past the first trimester, and found associated deviations, corroborating that continuous monitoring adds new information that could support decision-making even in the early stages of pregnancy. By contrast, we did not find significant deviations between full-term pregnancies of people younger than 35 and of people with “advanced maternal age”, suggesting that analysis of continuous data within individuals can augment risk assessment beyond standard population comparisons. Our findings demonstrate that low-cost, high-resolution monitoring at all stages of pregnancy in real-world settings is feasible and that many studies into specific demographics, risks, etc., could be carried out using this newer technology.

Deep learning for temporomandibular joint arthropathies: Asystematic review and meta-analysis.

The accurate diagnosis of temporomandibular disorders continues to be a challenge, despite the existence of internationally agreed-upon diagnostic criteria. The purpose of this study is to review applications of deep learning models in the diagnosis of temporomandibular joint arthropathies. An electronic search was conducted on PubMed, Scopus, Embase, Google Scholar, IEEE, arXiv, and medRxiv up to June 2023. Studies that reported the efficacy (outcome) of prediction, object detection or classification of TMJ arthropathies by deep learning models (intervention) of human joint-based or arthrogenous TMDs (population) in comparison to reference standard (comparison) were included. To evaluate the risk of bias, included studies were critically analysed using the quality assessment of diagnostic accuracy studies (QUADAS-2). Diagnostic odds ratios (DOR) were calculated. Forrest plot and funnel plot were created using STATA 17 and MetaDiSc. Full text review was performed on 46 out of the 1056 identified studies and 21 studies met the eligibility criteria and were included in the systematic review. Four studies were graded as having a low risk of bias for all domains of QUADAS-2. The accuracy of all included studies ranged from 74% to 100%. Sensitivity ranged from 54% to 100%, specificity: 85%-100%, Dice coefficient: 85%-98%, and AUC: 77%-99%. The datasets were then pooled based on the sensitivity, specificity, and dataset size of seven studies that qualified for meta-analysis. The pooled sensitivity was 95% (85%-99%), specificity: 92% (86%-96%), and AUC: 97% (96%-98%). DORs were 232 (74-729). According to Deek's funnel plot and statistical evaluation (p =.49), publication bias was not present. Deep learning models can detect TMJ arthropathies high sensitivity and specificity. Clinicians, and especially those not specialized in orofacial pain, may benefit from this methodology for assessing TMD as it facilitates a rigorous and evidence-based framework, objective measurements, and advanced analysis techniques, ultimately enhancing diagnostic accuracy.

Advances in neural architecture search.

Automated machine learning (AutoML) has achieved remarkable success in automating the non-trivial process of designing machine learning models. Among the focal areas of AutoML, neural architecture search (NAS) stands out, aiming to systematically explore the complex architecture space to discover the optimal neural architecture configurations without intensive manual interventions. NAS has demonstrated its capability of dramatic performance improvement across a large number of real-world tasks. The core components in NAS methodologies normally include (i) defining the appropriate search space, (ii) designing the right search strategy and (iii) developing the effective evaluation mechanism. Although early NAS endeavors are characterized via groundbreaking architecture designs, the imposed exorbitant computational demands prompt a shift towards more efficient paradigms such as weight sharing and evaluation estimation, etc. Concurrently, the introduction of specialized benchmarks has paved the way for standardized comparisons of NAS techniques. Notably, the adaptability of NAS is evidenced by its capability of extending to diverse datasets, including graphs, tabular data and videos, etc., each of which requires a tailored configuration. This paper delves into the multifaceted aspects of NAS, elaborating on its recent advances, applications, tools, benchmarks and prospective research directions.

The CentiMarker Project: Standardizing Quantitative Alzheimer's disease Fluid Biomarkers for Biologic Interpretation.

Biomarkers have been essential to understanding Alzheimer's disease (AD) pathogenesis, pathophysiology, progression, and treatment effects. However, each biomarker measure is a representation of the biological target, the assay used to measure it, and the variance of the assay. Thus, biomarker measures are difficult to compare without standardization, and the units and magnitude of effect relative to the disease are difficult to appreciate, even for experts. To facilitate quantitative comparisons of AD biomarkers in the context of biologic and treatment effects, we propose a biomarker standardization approach between normal ranges and maximum abnormal AD ranges, which we refer to as CentiMarker, similar to the Centiloid approach used in PET. We developed a standardization scale that creates percentile values ranging from 0 for a normal population to 100 for the most abnormal measures across disease stages. We applied this scale to CSF and plasma biomarkers in autosomal dominant AD, assessing the distribution by estimated years from symptom onset, between biomarkers, and across cohorts. We then validated this approach in a large national sporadic AD cohort. We found the CentiMarker scale provided an easily interpretable metric of disease abnormality. The biologic changes, range, and distribution of several AD fluid biomarkers including amyloid-β, phospho-tau and other biomarkers, were comparable across disease stages in both early onset autosomal dominant and sporadic late onset AD. The CentiMarker scale offers a robust and versatile framework for the standardized biological comparison of AD biomarkers. Its broader adoption could facilitate biomarker reporting, allowing for more informed cross-study comparisons and contributing to accelerated therapeutic development.

Gas sensor mechanism based on Boltzmann statistics and transport theory: Assessing the impact of gas dynamics

Gas dynamics including gas flow, gas adsorption and desorption largely determine the electrical properties of gas sensors. Observing gas phase behavior through a gas sensor is important not only for the sensor itself, but also for nanofilm epitaxial applications. However, gas dynamics traditionally treated with the equilibrium Langmuir model cannot reflect the dynamic details of the gas phase from electrical observations and must rely on a complete theoretical model connecting gas dynamics and electrical transport. This also leads to the fact that the responsivity of all gas sensors does not consider the complete physical reaction and process and is not a truly standardized comparison parameter, making the responsivity comparison unreliable. In this work, a unified model of gas sensors based on Boltzmann transport and statistical theory is proposed to handle gas dynamics and electron transport connected by Langmuir boundary conditions. Jet flow effects are also considered. The theoretical results are consistent with experimental observations of SnO2 sensors for noble and oxidizing gases. This work extends the electrical response of the gas sensor to the field of gas dynamics, thus realizing the possibility of gas dynamics detection through the gas sensor.