bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gut microbiota composition and metabolite profiling in smokers: a comparative study between emphysema and asymptomatic individuals with therapeutic implications
Authors: Lee Se Hee , Kim Jiseon , Kim Na Hyun , Kim Ock-Hwa , Shon Chang-Ho , Kim Su Jung , Jang Youngwon , Yun Sunmi , Lim Se Eun , Jung So Yi , Yoo Hyun Ju , Heo Sun-Hee , Lee Sei Won 
Published: July 2023

BackgroundDiet has a crucial role in the gut microbiota, and dysbiosis in the gut and lungs has been suggested to be associated with chronic obstructive pulmonary disease. We compared the diet, microbiome and metabolome between asymptomatic smokers and those with emphysema.MethodsWe enrolled 10 asymptomatic smokers with preserved lung function and 16 smokers with emphysema with severe airflow limitation. Dietary intake information was gathered by a self-reported questionnaire. Sputum and faecal samples were collected for microbial and metabolomics analysis. A murine model of emphysema was used to determine the effect of metabolite supplementation.ResultsDespite having a similar smoking history with emphysema patients, asymptomatic smokers had higher values of body mass index, fibre intake and faecal acetate level. Linear discriminant analysis identified 17 microbial taxonomic members that were relatively enriched in the faeces of asymptomatic smokers. Analysis of similarity results showed dissimilarity between the two groups (r=0.287, p=0.003). Higher acetate level was positively associated with forced expiratory volume in one second in the emphysema group (r=0.628, p=0.012). Asymptomatic smokers had a greater number of species associated with acetate and propionate (r>0.6) than did those with emphysema (30 vs 19). In an emphysema mouse model, supplementation of acetate and propionate reduced alveolar destruction and the production of proinflammatory cytokines, and propionate decreased the CD3+CD4+IL-17+T-cell population in the lung and spleen.ConclusionSmokers with emphysema showed differences in diet, microbiome and short-chain fatty acids compared with asymptomatic smokers. Acetate and propionate showed therapeutic effects in a smoking-induced murine model of emphysema.
Estimating the attributable fraction of mortality from acute respiratory distress syndrome to inform enrichment in future randomised clinical trials
Authors: Saha Rohit , Pham Tài , Sinha Pratik , Maddali Manoj V , Bellani Giacomo , Fan Eddy , Summers Charlotte , Douiri Abdel , Rubenfeld Gordon D , Calfee Carolyn S , Laffey John Gerard , McAuley Daniel Francis , Shankar-Hari Manu 
Published: July 2023

BackgroundEfficiency of randomised clinical trials of acute respiratory distress syndrome (ARDS) depends on the fraction of deaths attributable to ARDS (AFARDS) to which interventions are targeted. Estimates of AFARDSin subpopulations of ARDS could improve design of ARDS trials.MethodsWe performed a matched case-control study using the Large observational study to UNderstand the Global impact of Severe Acute respiratory FailurE cohort. Primary outcome was intensive care unit mortality. We used nearest neighbour propensity score matching without replacement to match ARDS to non-ARDS populations. We derived two separate AFARDSestimates by matching patients with ARDS to patients with non-acute hypoxaemic respiratory failure (non-AHRF) and to patients with AHRF with unilateral infiltrates only (AHRF-UL). We also estimated AFARDSin subgroups based on severity of hypoxaemia, number of lung quadrants involved and hyperinflammatory versus hypoinflammatory phenotypes. Additionally, we derived AFAHRFestimates by matching patients with AHRF to non-AHRF controls, and AFAHRF-ULestimates by matching patients with AHRF-UL to non-AHRF controls.ResultsEstimated AFARDSwas 20.9% (95% CI 10.5% to 31.4%) when compared with AHRF-UL controls and 38.0% (95% CI 34.4% to 41.6%) compared with non-AHRF controls. Within subgroups, estimates for AFARDScompared with AHRF-UL controls were highest in patients with severe hypoxaemia (41.1% (95% CI 25.2% to 57.1%)), in those with four quadrant involvement on chest radiography (28.9% (95% CI 13.4% to 44.3%)) and in the hyperinflammatory subphenotype (26.8% (95% CI 6.9% to 46.7%)). Estimated AFAHRFwas 33.8% (95% CI 30.5% to 37.1%) compared with non-AHRF controls. Estimated AFAHRF-ULwas 21.3% (95% CI 312.8% to 29.7%) compared with non-AHRF controls.ConclusionsOverall AFARDSmean values were between 20.9% and 38.0%, with higher AFARDSseen with severe hypoxaemia, four quadrant involvement on chest radiography and hyperinflammatory ARDS.
Effects of fine aggregate content on the unsaturated hydraulic characteristics of recycled concrete aggregate
Authors: Chen Rui , Wu Fan , Ng Charles W.W. , Tai Pei , Mei Dong-jie 
Published: July 2023

Recycled concrete aggregate (RCA) can be used in landfill and slope cover systems, where its unsaturated hydraulic properties play an important role. The hydraulic behavior of RCAs can be potentially controlled through mixing coarse and fine aggregates by a pre-determined proportion, which lacks experimental validation. In this study, water retention curve (WRC) and permeability function (PF) of RCAs with different fine aggregate contents ( fc) were investigated. Experiments on 9 RCAs with different gradations reveal that when fc is between 20% and 30%, a second air entry value appears, and the shape of both WRC and PF becomes bimodal, which is probably resulted from an uneven dual-peak pore size distribution. With an increasing fc, the first air entry value and the residual water content increases. The unsaturated coefficient of permeability decreases with the increasing fc for a low suction level (<0.1 kPa), but increases with the raise of fc for high suction (>10 kPa). Overall, adopting a properly mixed RCA with fc value of less than 10% or over 40%, instead of a narrowly graded RCA, is recommended for coarse- and fine-grained layers in a capillary barrier, respectively.
Some observable physical properties of the higher dimensional dS/AdS black holes in Einstein-bumblebee gravity theory
Authors: Uniyal Akhil , Kanzi Sara , Sakallı İzzet 
Published: July 2023

AbstractWe study the greybody factors, quasinormal modes, and shadow of the higher dimensional de-Sitter (dS)/anti de-Sitter (AdS) black hole spacetimes derived from the Einstein-bumblebee gravity theory within the Lorentz symmetry breaking (LSB) framework. We specifically apply the semi-analytical WKB method and the time domain approach to study the scalar and Dirac perturbations of the black hole. In-depth researches are done on the effects of the LSB and dimensionality on the bosonic/fermionic greybody factors, quasinormal modes, and shadow of the higher dimensional bumblebee black hole. The results obtained are discussed, tabulated, and illustrated graphically.
Online Predictions for Online TSP on the Line
Authors: Shao Jian-Xi , Liang Ya-Chun , Liao Chung-Shou 
Published: July 2023

With a rapidly growing attention on the development of learning-augmented algorithms, we revisit the classical online traveling salesman problem (OLTSP) from the perspective of such learning approaches. A learning-augmented online algorithm, or simply an online algorithm with predictions, considers how to improve its competitive performance with theoretical guarantees by forecasting the information of future requests, e.g., their release time or locations in the OLTSP. In this study, we investigate the OLTSP on the real line, motivated by the parcel picking problem in a smart warehouse, which aims at scheduling a route for a server (saying, a Kiva robot), starting at the origin, serving all online requests and returning to the origin such that the completion time is minimized. Each online request is released over time on the real line and the server moves back and forth along the line with unit speed. We mainly focus on zealous algorithms, a special type of online algorithms for the OLTSP which never allow the sever to wait if there are still unserved requests, and exploit a specific forecasting strategy, called online predictions, which makes a sequence of predictions one by one in an online manner. In order to ensure better competitive performance, we particularly explore the worst-case scenarios that restrict the power of such predictions. Based on the discussion, we make an assumption in which online predictions are guaranteed to be useful, and devise a learning-augmented algorithm with [Formula: see text]-robustness and [Formula: see text]-consistency, [Formula: see text], comparing to the previous lower bound of [Formula: see text], where [Formula: see text] and [Formula: see text] which indicate prediction errors are sufficiently small constants. Moreover, we also conduct numerical experiments to demonstrate the practical effectiveness of the proposed algorithm.
PCBend: Light Up Your 3D Shapes With Foldable Circuit Boards
Authors: Freire Marco , Bhargava Manas , Schreck Camille , Hugron Pierre-Alexandre , Bickel Bernd , Lefebvre Sylvain 
Published: July 2023

We propose a computational design approach for covering a surface with individually addressable RGB LEDs, effectively forming a low-resolution surface screen. To achieve a low-cost and scalable approach, we propose creating designs from flat PCB panels bent in-place along the surface of a 3D printed core. Working with standard rigid PCBs enables the use of established PCB manufacturing services, allowing the fabrication of designs with several hundred LEDs.
Our approach optimizes the PCB geometry for folding, and then jointly optimizes the LED packing, circuit and routing, solving a challenging layout problem under strict manufacturing requirements. Unlike paper, PCBs cannot bend beyond a certain point without breaking. Therefore, we introduce parametric cut patterns acting as hinges, designed to allow bending while remaining compact. To tackle the joint optimization of placement, circuit and routing, we propose a specialized algorithm that splits the global problem into one sub-problem per triangle, which is then individually solved.
Our technique generates PCB blueprints in a completely automated way. After being fabricated by a PCB manufacturing service, the boards are bent and glued by the user onto the 3D printed support. We demonstrate our technique on a range of physical models and virtual examples, creating intricate surface light patterns from hundreds of LEDs.
The code and data for this paper are available at https://github.com/mfremer/pcbend.
A Full-Wave Reference Simulator for Computing Surface Reflectance
Authors: Yu Yunchen , Xia Mengqi , Walter Bruce , Michielssen Eric , Marschner Steve 
Published: July 2023

Computing light reflection from rough surfaces is an important topic in computer graphics. Reflection models developed based on geometric optics fail to capture wave effects such as diffraction and interference, while existing models based on physical optics approximations give erroneous predictions under many circumstances (e.g. when multiple scattering from the surface cannot be ignored). We present a scalable 3D full-wave simulator for computing reference solutions to surface scattering problems, which can be used to evaluate and guide the development of approximate models for rendering. We investigate the range of validity for some existing wave optics based reflection models; our results confirm these models for low-roughness surfaces but also show that prior rendering methods do not accurately predict the scattering behavior of some types of surfaces.
Our simulator is based on the boundary element method (BEM) and accelerated using the adaptive integral method (AIM), and is implemented to execute on modern GPUs. We demonstrate the simulator on domains up to 60 × 60 × 10 wavelengths, involving surface samples with significant height variations. Furthermore, we propose a new system for efficiently computing BRDF values for large numbers of incident and outgoing directions at once, by combining small simulations to characterize larger areas. Our simulator will be released as an open-source toolkit for computing surface scattering.
Improved Water Sound Synthesis using Coupled Bubbles
Authors: Xue Kangrui , Aronson Ryan M. , Wang Jui-Hsien , Langlois Timothy R. , James Doug L. 
Published: July 2023

We introduce a practical framework for synthesizing bubble-based water sounds that captures the rich inter-bubble coupling effects responsible for low-frequency acoustic emissions from bubble clouds. We propose coupled-bubble oscillator models with regularized singularities, and techniques to reduce the computational cost of time stepping with dense, time-varying mass matrices. Airborne acoustic emissions are estimated using finite-difference time-domain (FDTD) methods. We propose a simple, analytical surface-acceleration model, and a sample-and-hold GPU wavesolver that is simple and faster than prior CPU wavesolvers.
Sound synthesis results are demonstrated using bubbly flows from incompressible, two-phase simulations, as well as procedurally generated examples using single-phase FLIP fluid animations. Our results demonstrate sound simulations with hundreds of thousands of bubbles, and perceptually significant frequency transformations with fuller low-frequency content.
Generative Design of Sheet Metal Structures
Authors: Barda Amir , Tevet Guy , Schulz Adriana , Bermano Amit Haim 
Published: July 2023

Sheet Metal (SM) fabrication is perhaps one of the most common metalworking technique.
Despite its prevalence, SM design is manual and costly, with rigorous practices that restrict the search space, yielding suboptimal results.
In contrast, we present a framework for the first automatic design of SM parts. Focusing on load bearing applications, our novel system generates a high-performing manufacturable SM that adheres to the numerous constraints that SM design entails:
The resulting part minimizes manufacturing costs while adhering to structural, spatial, and manufacturing constraints. In other words, the part should be strong enough, not disturb the environment, and adhere to the manufacturing process. These desiderata sum up to an elaborate, sparse, and expensive search space.

Our generative approach is a carefully designed exploration process, comprising two steps. In
Segment Discovery
connections from the input load to attachable regions are accumulated, and during
Segment Composition
the most performing valid combination is searched for.

For Discovery, we define a slim grammar, and sample it for parts using a Markov-Chain Monte Carlo (MCMC) approach, ran in intercommunicating instances (i.e, chains) for diversity. This, followed by a short continuous optimization, enables building a diverse and high-quality library of substructures. During Composition, a valid and minimal cost combination of the curated substructures is selected. To improve compliance significantly without additional manufacturing costs, we reinforce candidate parts onto themselves --- a unique SM capability called
self-riveting.
we provide our code and data in https://github.com/amir90/AutoSheetMetal.

We show our generative approach produces viable parts for numerous scenarios. We compare our system against a human expert and observe improvements in both part quality and design time. We further analyze our pipeline's steps with respect to resulting quality, and have fabricated some results for validation.
We hope our system will stretch the field of SM design, replacing costly expert hours with minutes of standard CPU, making this cheap and reliable manufacturing method accessible to anyone.
Use of Payload Binding Selectivity Enhancers to Improve Therapeutic Index of Maytansinoid–Antibody–Drug Conjugates
Authors: Nguyen Toan D. , Bordeau Brandon M. , Balthasar Joseph P. 
Published: July 2023

Abstract
Systemic exposure to released cytotoxic payload contributes to the dose-limiting off-target toxicities of anticancer antibody–drug conjugates (ADC). In this work, we present an “inverse targeting” strategy to optimize the therapeutic selectivity of maytansinoid-conjugated ADCs. Several anti-maytansinoid sdAbs were generated via phage-display technology with binding IC50 values between 10 and 60 nmol/L. Co-incubation of DM4 with the anti-maytansinoid sdAbs shifted the IC50 value of DM4 up to 250-fold. Tolerability and efficacy of 7E7-DM4 ADC, an anti-CD123 DM4-conjugated ADC, were assessed in healthy and in tumor-bearing mice, with and without co-administration of an anti-DM4 sdAb. Co-administration with anti-DM4 sdAb reduced 7E7-DM4–induced weight loss, where the mean values of percentage weight loss at nadir for mice receiving ADC+saline and ADC+sdAb were 7.9% ± 3% and 3.8% ± 1.3% (P &lt; 0.05). In tumor-bearing mice, co-administration of the anti-maytansinoid sdAb did not negatively affect the efficacy of 7E7-DM4 on tumor growth or survival following dosing of the ADC at 1 mg/kg (P = 0.49) or at 10 mg/kg (P = 0.9). Administration of 7E7-DM4 at 100 mg/kg led to dramatic weight loss, with 80% of treated mice succumbing to toxicity before the appearance of mortality relating to tumor growth in control mice. However, all mice receiving co-dosing of 100 mg/kg 7E7-DM4 with anti-DM4 sdAb were able to tolerate the treatment, which enabled reduction in tumor volume to undetectable levels and to dramatic improvements in survival. In summary, we have demonstrated the utility and feasibility of the application of anti-payload antibody fragments for inverse targeting to improve the selectivity and efficacy of anticancer ADC therapy.
impacto da pandemia da COVID-19 nas práticas de biossegurança hospitalar
Authors: Nogueira Rayssa Almeida , Reis Larissa Castro dos , Paiva Miriana Figueiredo Pereira , Moreira Rafaela Sechim , Almeida Lavínia Lages , Percu Breno Silva , Guerrero Lorenzo , Martins Murillo José Silva , Mendonça Vinícius Rodrigues , Pacheco Renato Bittencourt , Resgala Ludmilla Carvalho Rangel 
Published: July 2023

A pandemia de COVID-19 modificou a vida em âmbito global. Prejuízos econômicos, culturais e sociais foram notados em grande escala, junto às incontáveis mortes. Diante disso, mudanças nas práticas hospitalares tornaram-se necessárias para evitar a propagação do vírus entre os profissionais e os pacientes internados. Diante desse contexto, o estudo objetivou discutir os impactos trazidos pela pandemia de COVID-19 ao ambiente hospitalar, incluindo as principais mudanças no intuito de evitar a disseminação do vírus. Para a realização da pesquisa, foram utilizados artigos originais, publicados em plataformas de referência bibliográfica, como SciELO e PubMed, em língua portuguesa, nos últimos 20 anos. Sendo assim, observou-se impactos no ambiente hospitalar, principalmente em relação ao aumento da utilização de Equipamentos de Proteção Individual (EPIs) e Coletiva (EPCs). Além disso, a adoção do álcool 70% mostrou-se de intensa valia como antisséptico, minimizando os riscos de contaminação. Portanto, é possível inferir que apesar das práticas hospitalares anteriores à pandemia apresentarem relevância, a alta transmissibilidade do vírus SARS-CoV 2 obrigou que novas medidas fossem incluídas em contextos de biossegurança, culminando em menores riscos de auto e heterocontaminação no sistema de saúde.
Implementation of an Atrial Fibrillation Decision Aid Care Pathway in the Emergency Department Reduces Atrial Fibrillation Hospitalizations
Authors: Gehi Anil K. , Armbruster Tiffany , Walker Jennifer , Rosman Lindsey , Laux Jeffrey , Becker Ari , Aladesanmi Oludamilola , Mazzella Anthony J. , Deyo Zachariah , Biese Kevin 
Published: July 2023

BACKGROUND:
A straightforward decision aid to guide disposition of atrial fibrillation (AF) patients in the emergency department (ED) was developed for use by ED providers. The implementation of this decision aid in the ED has not been studied.

METHODS:
A pragmatic stepped-wedge cluster approach for analysis of retrospectively collected electronic health record data was used in which 5 hospitals were selected to commence the intervention at periodic intervals following an initial 1-year baseline assessment with 5 additional hospitals included in the comparison group (all in North Carolina). The primary end point of analysis was hospitalization rate. Hierarchical multivariable logistic regression analyses for admission as a function of the intervention while controlling for prespecified patient and hospital predictors were performed with clustering done at the hospital level.

RESULTS:

Between October 2017 and May 2020, a total of 11 458 patients (mean age, 71.4; 50.5% female) presented to 1 of the 10 hospitals with a primary diagnosis of AF. Absolute admission rate was reduced from 60.5% to 48.3% following the intervention (odds ratio, 0.83 [95% CI, 0.71–0.97];
P
=0.016). After adjusting for covariates, the intervention was associated with a small increased rate of return to the ED for AF within 30 days of the initial presentation (1.6% to 2.7%; hazard ratio, 1.70 [95% CI, 1.26–2.31];
P
<0.001).

CONCLUSIONS:
We demonstrate that implementation of a novel decision aid to guide disposition of patients primary diagnosis of AF presenting to the ED was associated with a reduced admission rate independent of patient and hospital factors. Use of the protocol was associated with a small but significant increase in rate of repeat presentations for AF at 30-day follow-up. Use of a decision aid such as the one described here represents an important tool to reduce unnecessary AF hospitalizations.
T-Cell MyD88 Is a Novel Regulator of Cardiac Fibrosis Through Modulation of T-Cell Activation
Authors: Bayer Abraham L. , Smolgovsky Sasha , Ngwenyama Njabulo , Hernández-Martínez Ana , Kaur Kuljeet , Sulka Katherine , Amrute Junedh , Aronovitz Mark , Lavine Kory , Sharma Shruti , Alcaide Pilar 
Published: July 2023

BACKGROUND:
Cardiac inflammation in heart failure is characterized by the presence of damage-associated molecular patterns, myeloid cells, and T cells. Cardiac damage-associated molecular patterns provide continuous proinflammatory signals to myeloid cells through TLRs (toll-like receptors) that converge onto the adaptor protein MyD88 (myeloid differentiation response 88). These induce activation into efficient antigen-presenting cells that activate T cells through their TCR (T-cell receptor). T-cell activation results in cardiotropism, cardiac fibroblast transformation, and maladaptive cardiac remodeling. T cells rely on TCR signaling for effector function and survival, and while they express MyD88 and damage-associated molecular pattern receptors, their role in T-cell activation and cardiac inflammation is unknown.

METHODS:

We performed transverse aortic constriction in mice lacking MyD88 in T cells and analyzed remodeling, systolic function, survival, and T-cell activation. We profiled wild type versus

Myd88
−/−

mouse T cells at the transcript and protein level and performed several functional assays.

RESULTS:

Analysis of single-cell RNA-sequencing data sets revealed that MyD88 is expressed in mouse and human cardiac T cells. MyD88 deletion in T cells resulted in increased levels of cardiac T-cell infiltration and fibrosis in response to transverse aortic constriction. We discovered that TCR-activated

Myd88
−/−

T cells had increased proinflammatory signaling at the transcript and protein level compared with wild type, resulting in increased T-cell effector functions such as adhesion, migration across endothelial cells, and activation of cardiac fibroblast. Mechanistically, we found that MyD88 modulates T-cell activation and survival through TCR-dependent rather than TLR-dependent signaling.

CONCLUSIONS:
Our results outline a novel intrinsic role for MyD88 in limiting T-cell activation that is central to tune down cardiac inflammation during cardiac adaptation to stress.