bluuebunny/crossref_metadata_2025_split huggingface dataset:
Contact feedback helps snake robots propel against uneven terrain using vertical bending
Authors: Fu Qiyuan , Li Chen 
Published: July 2023

AbstractSnakes can bend their elongate bodies in various forms to traverse various environments. We understand well how snakes use lateral body bending to push against asperities on flat ground for propulsion, and snake robots can do so effectively. However, snakes can also use vertical bending to push against uneven terrain of large height variation for propulsion, and they can adjust this bending to adapt to novel terrain presumably using mechano-sensing feedback control. Although some snake robots can traverse uneven terrain, few have used vertical bending for propulsion, and how to control this process in novel environments is poorly understood. Here we systematically studied a snake robot with force sensors pushing against large bumps using vertical bending to understand the role of sensory feedback control. We compared a feedforward controller and four feedback controllers that use different sensory information and generate distinct bending patterns and body-terrain interaction. We challenged the robot with increasing backward load and novel terrain geometry that break its contact with the terrain. We further varied how much the feedback control modulated body bending to conform to or push against the terrain to test their effects. Feedforward propagation of vertical bending generated large propulsion when the bending shape matched terrain geometry. However, when perturbations caused loss of contact, the robot easily lost propulsion or had motor overload. Contact feedback control resolved these issues by helping the robot regain contact. Yet excessive conformation interrupted shape propagation and excessive pushing stalled motors frequently. Unlike that using lateral bending, for propulsion generation using vertical bending, body weight that can help maintain contact with the environment but may also overload motors. Our results will help snake robots better traverse uneven terrain with large height variation and can inform how snakes use sensory feedback to control vertical body bending for propulsion.
Multistate transition dynamics by strong time-dependent perturbation in NISQ era
Authors: Wang Yulun , Krstić Predrag S 
Published: July 2023

Abstract
We develop a quantum computing scheme utilizing McLachlan variational principle in a hybrid quantum–classical algorithm to accurately calculate the transition dynamics of a closed quantum system with many excited states subject to a strong time-dependent perturbation. A systematic approach for optimal construction of a general N-state ansatz with unary N-qubit encoding is refined. We also use qubit efficient encoding in McLachlan variational quantum algorithm to reduce the number of qubits to

log

2

N

, simultaneously diminishing depths of the quantum circuits. The significant reduction of the number of time steps is achieved by use of the second order marching method. Instrumental in obtaining high accuracy are adaptations of the circuits to include time-dependent global phase correction. We illustrated, tested and optimized our quantum computing algorithm on a set of 16 bound hydrogenic eigenstates exposed to a strong laser attosecond pulse. Results for transition probabilities are obtained with accuracy better than 1%, as established by comparison to the benchmark data. Use of interaction representation of the Hamiltonian reduces the noise accumulation while the quantum system evolves in time.
Textile electronics for wearable applications
Authors: Pu Junhong , Ma Kitming , Luo Yonghui , Tang Shengyang , Liu Tongyao , Liu Jin , Leung Manyui , Yang Jing , Hui Ruomu , Xiong Ying , Tao Xiaoming 
Published: July 2023

Abstract
Textile electronics have become an indispensable part of wearable applications because of their large flexibility, light-weight, comfort and electronic functionality upon the merge of textiles and microelectronics. As a result, the fabrication of functional fibrous materials and the integration of textile electronic devices have attracted increasing interest in the wearable electronic community. Challenges are encountered in the development of textile electronics in a way that is electrically reliable and durable, without compromising on the deformability and comfort of a garment, including processing multiple materials with great mismatches in mechanical, thermal, and electrical properties and assembling various structures with the disparity in dimensional scales and surface roughness. Equal challenges lie in high-quality and cost-effective processes facilitated by high-level digital technology enabled design and manufacturing methods. This work reviews the manufacturing of textile-shaped electronics via the processing of functional fibrous materials from the perspective of hierarchical architectures, and discusses the heterogeneous integration of microelectronics into normal textiles upon the fabric circuit board and adapted electrical connections, broadly covering both conventional and advanced textile electronic production processes. We summarize the applications and obstacles of textile electronics explored so far in sensors, actuators, thermal management, energy fields, and displays. Finally, the main conclusions and outlook are provided while the remaining challenges of the fabrication and application of textile electronics are emphasized.
A deep neural network approach for parameterized PDEs and Bayesian inverse problems
Authors: Antil Harbir , Elman Howard C , Onwunta Akwum , Verma Deepanshu 
Published: July 2023

Abstract
We consider the simulation of Bayesian statistical inverse problems governed by large-scale linear and nonlinear partial differential equations (PDEs). Markov chain Monte Carlo (MCMC) algorithms are standard techniques to solve such problems. However, MCMC techniques are computationally challenging as they require a prohibitive number of forward PDE solves. The goal of this paper is to introduce a fractional deep neural network (fDNN) based approach for the forward solves within an MCMC routine. Moreover, we discuss some approximation error estimates. We illustrate the efficiency of fDNN on inverse problems governed by nonlinear elliptic PDEs and the unsteady Navier–Stokes equations. In the former case, two examples are discussed, respectively depending on two and 100 parameters, with significant observed savings. The unsteady Navier–Stokes example illustrates that fDNN can outperform existing DNNs, doing a better job of capturing essential features such as vortex shedding.
Antibacterial efficacy of surface aluminum oxide nanostructures produced by hot water treatment
Authors: Smith Quinshell , Burnett Kenneth , Ali Nawab , Bush John , Karabacak Tansel 
Published: July 2023

Abstract
This study utilizes a hot water treatment (HWT) method for introducing antibacterial properties to aluminum (Al) surfaces, which has relevance in several industries ranging from food packaging and ventilation systems to biomedical materials. The HWT process can produce a nanostructured oxide layer on a wide range of metallic materials by simply immersing the metal in water at temperatures ranging from 75 °C to 95 °C. In this work, Al foil was treated in deionized (DI) water for 5 min at various temperatures, including 75 °C, 85 °C, and 95 °C. Concentrations of Gram-negative Escherichia coli (E. coli) and Gram-positive Staphylococcus epidermidis (S. epidermidis) were placed on Al foil for different times, ranging from 30 seconds to 60 min The survival time was measured, and the analysis of the results indicates a direct correlation between when the bacteria was exposed to HWT Al foil and the number of bacteria killed. As the temperature of the HWT increased, there was an increase in antibacterial activity. This finding is consistent with our expectations; at higher HWT temperatures, more prominent nanostructures are produced, causing increased inactivation of bacteria. Our results show the nanostructured HWT Al foil was superior at inactivating Gram-negative (E. coli) and Gram-positive (S. epidermidis) bacteria compared to the untreated control Al foil. HWT Al foil treated at 75 °C, 85 °C, and 95 °C was 58%, 64%, and 73% more effective in killing the Gram-negative bacteria, respectively, after only 30 seconds of contact time compared to untreated control Al foil, while the antibacterial efficacy was enhanced 88%, 92%, and 94% for the Gram-positive bacteria, respectively. The HWT nanostructures synthesized at 95 °C, after 60 min of contact time, were able to inactivate 97% of the gram-negative bacteria and 100% of the gram-positive bacteria, demonstrating the efficacy of its antibacterial properties. This research presents a novel, inexpensive, and environmentally friendly method of producing nanostructures that inhibit bacterial activity.
The association between high ambient temperature and risk of hospitalization: a time-series study in eight ecological regions in Vietnam
Authors: Tran Nu Quy Linh , Ngo Hieu K T , Tuong Vy Nguyen Thi , Dang Tran Ngoc , Nghiem Son , Nguyen Huu Quyen , Phung Dung 
Published: July 2023

Abstract
Viet Nam is among the countries most threatened by and vulnerable to climate change and extreme weather events. However, research on the temperature-morbidity relationship at the national scale has been scarce. This study aimed to assess the impact of high temperatures on the risk of hospital admissions for all causes and heat-sensitive diseases across eight ecological regions in Vietnam. The study utilized a longitudinal dataset that included hospitalization and meteorological data from eight provinces representing eight regions in Vietnam. A time series analysis was applied using the generalized linear and distributed lag models with a quasi-Poisson family to examine the temperature-hospitalization association in each province. A random-effects meta-analysis was used to calculate the pooled estimate of risk for the national scale. The country-level pooled effects (%, [95% CI]) indicated that a 1 °C increase above the threshold temperature (19 °C) increased the hospitalization risk for all causes and infectious diseases by 0.8% [0.4%–1.2%] and 2.4% [1.02%–1.03%], respectively at lag 0–3 d. The effects of heat on respiratory diseases and mental health disorders were not significant. At the regional level, the association varied across eight regions, of which the Northern parts tended to have a higher risk than the Southern. This is among very few national-scale studies assessing hospitalization risk associated with high temperatures across eight ecological regions of Vietnam. These findings would be useful for developing evidence-based heat-health action plans.
Adaptation as Process: A Genetic Edition of Andrew Davies’ Middlemarch (BBC/WGBH, 1994)
Authors: Smith Justin , Hobbs Lucy 
Published: July 2023

Abstract
This article reports on an interdisciplinary project to produce the first genetic edition of a television adaptation, drawing on the papers of screenwriter Andrew Davies who adapted George Eliot’s Middlemarch for the BBC in 1994. Combining methodologies from digital humanities, television history, and archival theory and practice, the digital resource places Xtensible Mark-up Language versions of Eliot’s novel and Davies’ scripts at the centre of an intertextual framework which enables close cross-referencing. Supported by primary sources derived from thorough production history research, the genetic edition opens up a potentially productive approach to adaptation which foregrounds the creative practice of the screenwriter at the heart of the collaborative process of producing television adaptations of classic novels. Following an outline of the case history, the project and the resource, the article then illustrates some preliminary findings based on new editorial commentary. It concludes that this genetic edition will not only be of interest to Eliot scholars, television historians, and adaptations studies, but might have potential beyond the academy in the development of resources for education and heritage sites.
Socioeconomic Inequalities and Molecular Risk for Aging in Young Adulthood
Authors: Potente Cecilia , Chumbley Justin , Xu Wenjia , Levitt Brandt , Cole Steven W , Ravi Sudharshan , Bodelet Julien Stephane , Gaydosh Lauren , Harris Kathleen Mullan , Shanahan Michael J 
Published: July 2023

Abstract
Diverse manifestations of biological aging often reflect disparities in socioeconomic status (SES). In this paper, we examine associations between indicators of SES and an mRNA-based aging signature during young adulthood, before clinical indications of aging are common. We use data from wave V (2016–2018) of the National Longitudinal Study of Adolescent to Adult Health, a nationally representative study of adults aged 33–43 years, with transcriptomic data from a subset of 2,491 participants. Biological aging is measured using 1) a composite transcriptomic aging signature previously identified by Peters et al.’s out-of-sample meta-analysis (Nat Commun. 2015;6:8570) and 2) 9 subsets that represent functional pathways of coexpressed genes. SES refers to income, education, occupation, subjective social status, and a composite measure combining these 4 dimensions. We examine hypothesized mechanisms through which SES could affect aging: body mass index, smoking, health insurance status, difficulty paying bills, and psychosocial stress. We find that SES—especially the composite measure and income—is associated with transcriptomic aging and immune, mitochondrial, ribosomal, lysosomal, and proteomal pathways. Counterfactual mediational models suggest that the mediators partially account for these associations. The results thus reveal that numerous biological pathways associated with aging are already linked to SES in young adulthood.
Impact of enhanced pharmacy services on adherence for patients with hypertension
Authors: Garcia Paloma , Zolekar Ashwini , Donnelly Andrew , Nagelli Anitha 
Published: July 2023

Abstract

Purpose
To evaluate the impact of UI TEAM RX, a pharmacy-based enhanced services and care model, on adherence in patients with hypertension and prescribed a renin-angiotensin system antagonist (RASA).

Methods
A single-center, retrospective, observational cohort study was conducted in an academic health system, University of Illinois Hospital & Health Sciences System (UI Health). The cohort consisted of patients who utilized UI Health’s outpatient pharmacies between May 2016 and December 2018 to fill RASA prescriptions. Patients who were not part of the UI TEAM RX care model served as the control group, while patients enrolled in UI TEAM RX formed the intervention group. The control and intervention groups were matched based on index date, age, gender, and race. The primary outcome was mean change in a rolling 6-month calculation of proportion of days covered (PDC). The secondary outcome was the percentage of patients who had reached their blood pressure goal at follow-up at 12 months.

Results
Patients receiving UI TEAM RX intervention showed significant improvement in mean PDC at 6-month follow-up compared to control patients (P &lt; 0.01). The proportion of patients with a PDC above 0.8 was higher in the intervention group, but this difference was not statistically significant. There was also a 16.4% increase in the proportion of patients who reached their blood pressure goal in the intervention group, although this increase was not statistically significant.

Conclusion
The UI TEAM RX program had a statistically significant impact on patients’ mean PDCs. An increase in the number of patients reaching their blood pressure goal was also seen.
Does the unity of reason imply that epistemic justification is factive?
Authors: Hirvelä Jaakko 
Published: July 2023

Abstract
Some externalists have recently argued that the unity of theoretical and practical reason implies that epistemic justification is factive. It is argued that arguments for the factivity of epistemic justification either (i) equate two actions that are in fact different, or (ii) make the unwarranted assumption that the by-relation transmits justification. The unity of reason does not imply that epistemic justification is factive.
Three-Dimensional Photography and Computer Modeling as a Reconstructive Surgical Training Tool
Authors: Singh Prateush , Chan Kayen , Dhar Shivani , Krumhuber Eva , Mosahebi Afshin , Ponniah Allan 
Published: July 2023

Abstract

Background
Reconstructive surgery operations are often complex, staged, and have a steep learning curve. As a vocational training requiring thorough three-dimensional (3D) understanding of reconstructive techniques, the use of 3D photography and computer modeling can accelerate this learning for surgical trainees.

Objectives
The authors illustrate the benefits of introducing a streamlined reconstructive pathway that integrates 3D photography and computer modeling, to create a learning database for use by trainees and patients alike, to improve learning and comprehension.

Methods
A computer database of 3D photographs and associated computer models was developed for 35 patients undergoing reconstructive facial surgery at the Royal Free Hospital, London, UK. This was used as a training and teaching tool for 20 surgical trainees, with an MCQ questionnaire assessing knowledge and a Likert scale questionnaire assessing satisfaction with the understanding of core reconstructive techniques, given before and after teaching sessions. Data were analyzed using the Mann–Whitney U test for trainee knowledge and Wilcoxon rank sum test for trainee satisfaction.

Results
Trainee (n = 20) knowledge showed a statistically significant improvement, P &lt; .01, as did trainee satisfaction, P &lt; .05, after a teaching session using 3D photography and computer models for facial reconstruction.

Conclusions
Three-dimensional photography and computer modeling are useful teaching and training tools for reconstructive facial surgery. The authors advocate the implementation of an integrated pathway for patients with facial defects to include 3D photography and computer modeling wherever possible, to develop internal databases for training trainees as well as patients. This algorithm can be extrapolated to other aspects of reconstructive surgery.

Level of Evidence: 5
ZooPathWeb: a comprehensive web resource for zoonotic pathogens
Authors: Hu Rui-Si , Zhang Xin , Wei Yanming 
Published: July 2023

Abstract

Motivation
Zoonotic pathogens, such as viruses, bacteria, fungi and parasites, can be transmitted from animals to humans, causing a wide range of diseases that can vary from mild to life-threatening. These pathogens typically exhibit a broad host range, infecting domestic and/or wild animals, which serve as reservoirs of infection. Human infection can occur through direct contact with infected animals or their body fluids, consumption of contaminated food or water, or via bites from infected arthropod vectors. Understanding the epidemiological characteristics and population structure of zoonotic pathogens is of paramount importance for preventing and controlling the spread of zoonotic diseases.

Results
Here, we present ZooPathWeb, a comprehensive online resource for zoonotic pathogens. ZooPathWeb provides essential information on pathogens that are particularly relevant to public health and includes a literature collection organized by pathogen classification, such as lineage, host, country or region and publication year. Moreover, we have developed four web-based utility tools for this release: SeqNHandle, PaPhy-ML, TreeView and BLAST. These tools are specifically designed to facilitate the identification of population structure and adaptive evolution in relation to zoonotic pathogens.

Availability and implementation
The ZooPathWeb website is accessed via http://lab.malab.cn/~hrs/zoopathweb/. The source code for AKINND, which is used for collecting pathogen-related literature, can be found at https://github.com/RuiSiHu/AKINND. Additionally, the source code for PaPhy-ML, utilized for phylogenetic analysis, can be found at https://github.com/RuiSiHu/PaPhy-ML.

Supplementary information
Supplementary data are available at Bioinformatics Advances online.
Counting pseudoalignments to novel splicing events
Authors: Borozan Luka , Rojas Ringeling Francisca , Kao Shao-Yen , Nikonova Elena , Monteagudo-Mesas Pablo , Matijević Domagoj , Spletter Maria L , Canzar Stefan 
Published: July 2023

Abstract

Motivation
Alternative splicing (AS) of introns from pre-mRNA produces diverse sets of transcripts across cell types and tissues, but is also dysregulated in many diseases. Alignment-free computational methods have greatly accelerated the quantification of mRNA transcripts from short RNA-seq reads, but they inherently rely on a catalog of known transcripts and might miss novel, disease-specific splicing events. By contrast, alignment of reads to the genome can effectively identify novel exonic segments and introns. Event-based methods then count how many reads align to predefined features. However, an alignment is more expensive to compute and constitutes a bottleneck in many AS analysis methods.

Results
Here, we propose fortuna, a method that guesses novel combinations of annotated splice sites to create transcript fragments. It then pseudoaligns reads to fragments using kallisto and efficiently derives counts of the most elementary splicing units from kallisto’s equivalence classes. These counts can be directly used for AS analysis or summarized to larger units as used by other widely applied methods. In experiments on synthetic and real data, fortuna was around 7× faster than traditional align and count approaches, and was able to analyze almost 300 million reads in just 15 min when using four threads. It mapped reads containing mismatches more accurately across novel junctions and found more reads supporting aberrant splicing events in patients with autism spectrum disorder than existing methods. We further used fortuna to identify novel, tissue-specific splicing events in Drosophila.

Availability and implementation
fortuna source code is available at https://github.com/canzarlab/fortuna.
Unravelling spatial gene associations with SEAGAL: a Python package for spatial transcriptomics data analysis and visualization
Authors: Wang Linhua , Liu Chaozhong , Gao Yang , Zhang Xiang H -F , Liu Zhandong 
Published: July 2023

AbstractSummaryIn the era where transcriptome profiling moves toward single-cell and spatial resolutions, the traditional co-expression analysis lacks the power to fully utilize such rich information to unravel spatial gene associations. Here, we present a Python package called Spatial Enrichment Analysis of Gene Associations using L-index (SEAGAL) to detect and visualize spatial gene correlations at both single-gene and gene-set levels. Our package takes spatial transcriptomics datasets with gene expression and the aligned spatial coordinates as input. It allows for analyzing and visualizing genes’ spatial correlations and cell types’ colocalization within the precise spatial context. The output could be visualized as volcano plots and heatmaps with a few lines of code, thus providing an easy-yet-comprehensive tool for mining spatial gene associations.Availability and implementationThe Python package SEAGAL can be installed using pip: https://pypi.org/project/seagal/. The source code and step-by-step tutorials are available at: https://github.com/linhuawang/SEAGAL.