bluuebunny/crossref_metadata_2025_split huggingface dataset:
Relaxation effects in twisted bilayer molybdenum disulfide: structure, stability, and electronic properties
Authors: Arnold Florian M , Ghasemifard Alireza , Kuc Agnieszka , Kunstmann Jens , Heine Thomas 
Published: July 2023

Abstract
Manipulating the interlayer twist angle is a powerful tool to tailor the properties of layered two-dimensional crystals. The twist angle has a determinant impact on these systems’ atomistic structure and electronic properties. This includes the corrugation of individual layers, formation of stacking domains and other structural elements, and electronic structure changes due to the atomic reconstruction and superlattice effects. However, how these properties change with the twist angle, θ, is not yet well understood. Here, we monitor the change of twisted bilayer (tBL) MoS2 characteristics as a function of θ. We identify distinct structural regimes, each with particular structural and electronic properties. We employ a hierarchical approach ranging from a reactive force field through the density-functional-based tight-binding approach and density-functional theory. To obtain a comprehensive overview, we analyzed a large number of tBLs with twist angles in the range of

θ
=

0.2
∘

…

59.6
∘

. Some systems include up to half a million atoms, making structure optimization and electronic property calculation challenging. For

13

°

≲
θ
≲

47

°

, the structure is well-described by a moiré regime composed of two rigidly twisted monolayers. At small twist angles (

θ
⩽

3
∘

and

57
∘

⩽
θ

), a domain-soliton regime evolves, where the structure contains large triangular stacking domains, separated by a network of strain solitons and short-ranged high-energy nodes. The corrugation of the layers and the emerging superlattice of solitons and stacking domains affects the electronic structure. Emerging predominant characteristic features are Dirac cones at K and kagome bands. These features flatten for θ approaching 0∘ and 60∘. Our results show at which range of θ the characteristic features of the reconstruction, namely extended stacking domains, the soliton network, and superlattice, emerge and give rise to exciting electronics. We expect our findings also to be relevant for other tBL systems.
Faster variational quantum algorithms with quantum kernel-based surrogate models
Authors: Smith Alistair W R , Paige A J , Kim M S 
Published: July 2023

Abstract
We present a new optimization strategy for small-to-intermediate scale variational quantum algorithms (VQAs) on noisy near-term quantum processors which uses a Gaussian process surrogate model equipped with a classically-evaluated quantum kernel. VQAs are typically optimized using gradient-based approaches however these are difficult to implement on current noisy devices, requiring large numbers of objective function evaluations. Our approach shifts this computational burden onto the classical optimizer component of these hybrid algorithms, greatly reducing the number of quantum circuit evaluations required from the quantum processor. We focus on the variational quantum eigensolver (VQE) algorithm and demonstrate numerically that these surrogate models are particularly well suited to the algorithm’s objective function. Next, we apply these models to both noiseless and noisy VQE simulations and show that they exhibit better performance than widely-used classical kernels in terms of final accuracy and convergence speed. Compared to the typically-used stochastic gradient-descent approach to VQAs, our quantum kernel-based approach is found to consistently achieve significantly higher accuracy while requiring less than an order of magnitude fewer quantum circuit executions. We analyze the performance of the quantum kernel-based models in terms of the kernels’ induced feature spaces and explicitly construct their feature maps. Finally, we describe a scheme for approximating the best-performing quantum kernel using a classically-efficient tensor network representation of its input state and so provide a pathway for scaling this strategy to larger systems.
On the devolvement of fractal antenna for IoT applications
Authors: Kumar Ashwini , Dewan Basudha , Khandelwal Arpit , Shrivastava Kapil 
Published: July 2023

Abstract
A fractal patch antenna is designed and fabricated on FR4-epoxy substrate for Internet of Things (IoT) applications. Minkowski fractal has been used in the design of radiating element of antenna and slots are incorporated in the partial ground structure. The proposed antenna is miniaturized by 65% in terms of resonating frequency using Minkowski fractal. The proposed structure of antenna has an overall size of 60× 40 ×1.6 mm3. The antenna resonates at 1.223, 1.58, 2.69, and at 3.54 GHz. It exhibits an impedance bandwidth of 0.11 (1.16–1.27) GHz, 0.23 (1.47–1.70) GHz, and 4.5 (1.99–6.49) GHz. The proposed antenna has a peak gain of 3.4 dBi. The key benefits of the proposed antenna are: simple structure, improved performance characteristics, and its usefulness for applications such as Global Positioning System (GPS), Radar Altimeter, Public Safety Applications, and 5G communications in sub-6 GHz band. The simulated results of the proposed fractal antenna have been verified experimentally. The results are highly convincing.
Introduction: Remixing the Classics
Authors: Sullivan Erin 
Published: July 2023

Abstract
Drawing on the findings of the Remixing the Classics research network, this introduction highlights the importance of both digital culture and classic literature to adaptation studies today. It starts with a historiographical account of digital media’s impact on adaptive creativity and adaptation studies, particularly in light of twenty-first-century franchise culture and transmedia storytelling. It then makes a case for the continued relevance of classic literature to these fields, despite its decreased prominence within adaptation studies and its near-invisibility in transmedia studies. That case is grounded in three arguments: the continued centrality of these texts in compulsory education, the potential for radical adaptations to articulate progressive political engagements through canonical works, and the special ability of repeatedly adapted literature to illuminate cultural change. The introduction finishes with a summary of the issue’s contents and an assertion of the artistic, pedagogical, and political significance of new media to old stories and old stories to new media.
The dualist character of a garden’s aesthetic properties
Authors: Fenner David 
Published: July 2023

Abstract
The attribution of perceptually based aesthetic properties to a garden should be indexed to whether that attribution is (1) to the ever-changing dynamic garden or (2) to some phenomenal capture of the garden in one’s experience, frozen like a photograph. Perceptually based aesthetic properties are used to identify objects, to compare them to others, to evaluate them, and to describe them as we seek to interpret or find meaning in them. This set of activities requires aesthetic properties that do not change, or at least not much, if any degree of normativity is to be maintained. But those aesthetic properties that are derived from our immediate sensations of a garden only describe a garden at a certain time, under certain conditions, in certain states—all of which change constantly. Both descriptions are useful, and perhaps necessary, for appreciating gardens.
Funded hospital discharges to care homes: a cohort study
Authors: Wilson Carol L , Keevil Victoria L , Goodman Claire 
Published: July 2023

Abstract

Background
Optimising timely discharge from hospitals is an international priority. In 2020, the Coronavirus disease 2019 (COVID-19) pandemic resulted in the United Kingdom Government implementing the Discharge to Assess (D2A) model across England. This funded temporary care home placement to allow further recovery and assessment of care needs outside of the hospital.

Objectives
Determine if older adults discharged from hospital to care homes after implementation of D2A differ in their characteristics or outcomes.

Design and methods
Two cohorts of older adults discharged from hospital to care homes pre- and post-implementation of the D2A model (n = 244), with 6 months of follow-up. Data were extracted from routinely collected healthcare records.

Results
The mean duration of the hospital admission was reduced (29 vs. 23 days (P = 0.02)) but discharges to care homes did not increase with implementation of D2A (n = 161 in both cohorts prior to exclusions). In July–December 2020 (post-implementation), 28% of people were living in a private residence 6 months post-discharge, compared with 18% in the same period in 2019 (P = 0.09). When those who died were excluded, this changed to 40 vs. 28% (P = 0.19). There was no change in 6-month mortality (26 vs. 35% (P = 0.17)), and no increase in readmission rate (0.48 vs. 0.63 (P = 0.21) readmissions-per-patient over 6 months). No differences in key characteristics were found. However, patients were placed in care homes further from admission addresses (17.3 vs. 9.8 km (P = 0.00001)).

Conclusions
Implementation of D2A did not result in poorer outcomes but was associated with a reduced length of hospital stay.
The extent of anticholinergic burden across an older Welsh population living with frailty: cross-sectional analysis of general practice records
Authors: Cheong V-Lin , Mehdizadeh David , Todd Oliver M , Gardner Peter , Zaman Hadar , Clegg Andrew , Alldred David P , Faisal Muhammad 
Published: July 2023

Abstract

Background
Anticholinergic medicines are associated with adverse outcomes for older people. However, little is known about their use in frailty. The objectives were to (i) investigate the prevalence of anticholinergic prescribing for older patients, and (ii) examine anticholinergic burden according to frailty status.

Methods
Cross-sectional analysis of Welsh primary care data from the Secure Anonymised Information Linkage databank including patients aged ≥65 at their first GP consultation between 1 January and 31 December 2018. Frailty was identified using the electronic Frailty Index and anticholinergic burden using the Anticholinergic Cognitive Burden (ACB) scale. Descriptive analysis and logistic regression were conducted to (i) describe the type and frequency of anticholinergics prescribed; and (ii) to estimate the association between frailty and cumulative ACB score (ACB-Sum).

Results
In this study of 529,095 patients, 47.4% of patients receiving any prescription medications were prescribed at least one anticholinergic medicine. Adjusted regression analysis showed that patients with increasing frailty had higher odds of having an ACB-Sum of &gt;3 compared with patients who were fit (mild frailty, adj OR 1.062 (95%CI 1.061–1.064), moderate frailty, adj OR 1.134 (95%CI 1.131–1.136), severe frailty, adj OR 1.208 (95%CI 1.203–1.213)).

Conclusions
Anticholinergic prescribing was high in this older population. Older people with advancing frailty are exposed to the highest anticholinergic burden despite being the most vulnerable to the associated adverse effects. Older people with advancing frailty should be considered for medicines review to prevent overaccumulation of anticholinergic medications, given the risks of functional and cognitive decline that frailty presents.
CRISPR/Cas9 genome editing for comparative genetic analysis related to soy sauce brewing in Aspergillus sojae industrial strains
Authors: Igarashi Takayuki , Katayama Takuya , Maruyama Jun-ichi 
Published: July 2023

ABSTRACT
Aspergillus sojae has traditionally been used in soy sauce brewing. Genetic modification techniques have been established in A. sojae, but it is difficult to apply them to various industrial strains. Although we have previously developed a CRISPR/Cpf1 system for genetic modification of A. sojae, another genome editing system was required for versatile modification. In addition, repetitive genetic modification using the CRISPR system has not been established in A. sojae. In this study, we demonstrated mutagenesis, gene deletion/integration, and large deletion of a chromosomal region in A. sojae using the CRISPR/Cas9 system. We also successfully performed repetitive genetic modification using a method that involved forced recycling of genome-editing plasmids. Moreover, we demonstrated that the effects of genetic modification related to soy sauce brewing differed among A. sojae industrial strains. These results showed that our technique of using the CRISPR/Cas9 system is a powerful tool for genetic modification in A. sojae.
Contrastively generative self-expression model for single-cell and spatial multimodal data
Authors: Zhang Chengming , Yang Yiwen , Tang Shijie , Aihara Kazuyuki , Zhang Chuanchao , Chen Luonan 
Published: July 2023

Abstract
Advances in single-cell multi-omics technology provide an unprecedented opportunity to fully understand cellular heterogeneity. However, integrating omics data from multiple modalities is challenging due to the individual characteristics of each measurement. Here, to solve such a problem, we propose a contrastive and generative deep self-expression model, called single-cell multimodal self-expressive integration (scMSI), which integrates the heterogeneous multimodal data into a unified manifold space. Specifically, scMSI first learns each omics-specific latent representation and self-expression relationship to consider the characteristics of different omics data by deep self-expressive generative model. Then, scMSI combines these omics-specific self-expression relations through contrastive learning. In such a way, scMSI provides a paradigm to integrate multiple omics data even with weak relation, which effectively achieves the representation learning and data integration into a unified framework. We demonstrate that scMSI provides a cohesive solution for a variety of analysis tasks, such as integration analysis, data denoising, batch correction and spatial domain detection. We have applied scMSI on various single-cell and spatial multimodal datasets to validate its high effectiveness and robustness in diverse data types and application scenarios.
A comprehensive assessment of hurdle and zero-inflated models for single cell RNA-sequencing analysis
Authors: Cui Tao , Wang Tingting 
Published: July 2023

AbstractSingle cell RNA-sequencing (scRNA-seq) technology has significantly advanced the understanding of transcriptomic signatures. Although various statistical models have been used to describe the distribution of gene expression across cells, a comprehensive assessment of the different models is missing. Moreover, the growing number of features associated with scRNA-seq datasets creates new challenges for analytical accuracy and computing speed. Here, we developed a Python-based package (TensorZINB) to solve the zero-inflated negative binomial (ZINB) model using the TensorFlow deep learning framework. We used a sequential initialization method to solve the numerical stability issues associated with hurdle and zero-inflated models. A recursive feature selection protocol was used to optimize feature selections for data processing and downstream differentially expressed gene (DEG) analysis. We proposed a class of hybrid models combining nested models to further improve the model’s performance. Additionally, we developed a new method to convert a continuous distribution to its equivalent discrete form, so that statistical models can be fairly compared. Finally, we showed that the proposed TensorFlow algorithm (TensorZINB) was numerically stable and that its computing speed and performance were superior to those of existing ZINB solvers. Moreover, we implemented seven hurdle and zero-inflated statistical models in Python and systematically assessed their performance using a real scRNA-seq dataset. We demonstrated that the ZINB model achieved the lowest Akaike information criterion compared with other models tested. Taken together, TensorZINB was accurate, efficient and scalable for the implementation of ZINB and for large-scale scRNA-seq data analysis with DEG identification.
ShinyBioHEAT: an interactive shiny app to identify phenotype driver genes in E.coli and B.subtilis
Authors: Wang Chen , Govindarajan Harikumar , Katsonis Panagiotis , Lichtarge Olivier 
Published: July 2023

Abstract

Summary
In any population under selective pressure, a central challenge is to distinguish the genes that drive adaptation from others which, subject to population variation, harbor many neutral mutations de novo. We recently showed that such genes could be identified by supplementing information on mutational frequency with an evolutionary analysis of the likely functional impact of coding variants. This approach improved the discovery of driver genes in both lab-evolved and environmental Escherichia coli strains. To facilitate general adoption, we now developed ShinyBioHEAT, an R Shiny web-based application that enables identification of phenotype driving gene in two commonly used model bacteria, E.coli and Bacillus subtilis, with no specific computational skill requirements. ShinyBioHEAT not only supports transparent and interactive analysis of lab evolution data in E.coli and B.subtilis, but it also creates dynamic visualizations of mutational impact on protein structures, which add orthogonal checks on predicted drivers.

Availability and implementation
Code for ShinyBioHEAT is available at https://github.com/LichtargeLab/ShinyBioHEAT. The Shiny application is additionally hosted at http://bioheat.lichtargelab.org/.
Exploitation of surrogate variables in random forests for unbiased analysis of mutual impact and importance of features
Authors: Voges Lucas F , Jarren Lukas C , Seifert Stephan 
Published: July 2023

Abstract

Motivation
Random forest is a popular machine learning approach for the analysis of high-dimensional data because it is flexible and provides variable importance measures for the selection of relevant features. However, the complex relationships between the features are usually not considered for the selection and thus also neglected for the characterization of the analysed samples.

Results
Here we propose two novel approaches that focus on the mutual impact of features in random forests. Mutual forest impact (MFI) is a relation parameter that evaluates the mutual association of the features to the outcome and, hence, goes beyond the analysis of correlation coefficients. Mutual impurity reduction (MIR) is an importance measure that combines this relation parameter with the importance of the individual features. MIR and MFI are implemented together with testing procedures that generate P-values for the selection of related and important features. Applications to one experimental and various simulated datasets and the comparison to other methods for feature selection and relation analysis show that MFI and MIR are very promising to shed light on the complex relationships between features and outcome. In addition, they are not affected by common biases, e.g. that features with many possible splits or high minor allele frequencies are preferred.

Availability and implementation
The approaches are implemented in Version 0.3.3 of the R package RFSurrogates that is available at github.com/AGSeifert/RFSurrogates and the data are available at doi.org/10.25592/uhhfdm.12620.
Prophylactic mesh augmentation after laparotomy for elective and emergency surgery: meta-analysis
Authors: Frassini Simone , Calabretto Francesca , Granieri Stefano , Fugazzola Paola , Massaro Matteo , Sargenti Benedetta , Schiavone Luca , Zanghì Simone , Dal Mas Francesca , Ansaloni Luca , Cobianchi Lorenzo 
Published: July 2023

Abstract

Background
Incisional hernia is a common short- and long-term complication of laparotomy and can lead to significant morbidity. The aim of this systematic review and meta-analysis is to provide an up-to-date overview of the laparotomy closure method in elective and emergency settings with the prophylactic mesh augmentation technique.

Methods
The Scopus, PubMed, and Web of Science databases were screened without time restrictions up to 21 June 2022 using the keywords ‘laparotomy closure’, ‘mesh’, ‘mesh positioning’, and ‘prophylactic mesh’, and including medical subject headings terms. Only RCTs reporting the incidence of incisional hernia and other wound complications after elective or emergency midline laparotomy, where patients were treated with prophylactic mesh augmentation or without mesh positioning, were included. The primary endpoint was to explore the risk of incisional hernia at different follow-up time points. The secondary endpoint was the risk of wound complications. The risk of bias for individual studies was assessed according to the Revised Cochrane risk-of-bias tools for randomized trials.

Results
Eighteen RCTs, including 2659 patients, were retrieved. A reduction in the risk of incisional hernia at every time point was highlighted in the prophylactic mesh augmentation group (1 year, risk ratio 0.31, P = 0.0011; 2 years, risk ratio 0.44, P &lt; 0.0001; 3 years, risk ratio 0.38, P = 0.0026; 4 years, risk ratio 0.38, P = 0.0257). An increased risk of wound complications was highlighted for patients undergoing mesh augmentation, although this was not significant.

Conclusions
Midline laparotomy closure with prophylactic mesh augmentation can be considered safe and effective in reducing the incidence of incisional hernia. Further trials are needed to identify the ideal type of mesh and technique for mesh positioning, but surgeons should consider prophylactic mesh augmentation to decrease incisional hernia rate, especially in high-risk patients for fascial dehiscence and even in emergency settings.

PROSPERO registration ID
CRD42022336242 (https://www.crd.york.ac.uk/prospero/record_email.php).
Serum Virome of Southern Beaufort Sea polar bears (Ursus maritimus) during a period of rapid climate change
Authors: Fry Tricia L , Owens Leah A , Ketz Alison C , Atwood Todd C , Dunay Emily , Goldberg Tony L 
Published: July 2023

Abstract
Climate change affects the behavior, physiology and life history of many Arctic wildlife species. It can also influence the distribution and ecology of infectious agents. The southern Beaufort Sea (SB) subpopulation of polar bears (Ursus maritimus) has experienced dramatic behavioral changes due to retreating sea ice and other climate-related factors, but the effects of these changes on physiology and infection remain poorly understood. Using serum from polar bears sampled between 2004 and 2015 and metagenomic DNA sequencing, we identified 48 viruses, all of the family Anelloviridae. Anelloviruses are small, ubiquitous infectious agents with circular single-stranded DNA genomes that are not known to cause disease but, in humans, covary in diversity and load with immunological compromise. We therefore examined the usefulness of anelloviruses as biomarkers of polar bear physiological stress related to climate and habitat use. Polar bear anelloviruses sorted into two distinct clades on a phylogenetic tree, both of which also contained anelloviruses of giant pandas (Ailuropoda melanoleuca), another ursid. Neither anellovirus diversity nor load were associated with any demographic variables, behavioral factors or direct physiological measures. However, pairwise genetic distances between anelloviruses were positively correlated with pairwise differences in sampling date, suggesting that the polar bear “anellome” is evolving over time. These findings suggest that anelloviruses are not a sensitive indicator of polar physiological stress, but they do provide a baseline for evaluating future changes to polar bear viromes.