bluuebunny/crossref_metadata_2025_split huggingface dataset:
ALICE ITS 3: the first truly cylindrical inner tracker
Authors: Colella D. 
Published: September 2022

Abstract
The high integration density of MAPS, with silicon sensor and readout electronics implemented in the same device, allows very thin structures with a greatly reduced material budget. Thicknesses of

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(50 μm), values at which silicon chips become flexible, are readily used in many applications. In addition, MAPS can be produced in sensors of wafer size by a process known as stitching. This in turn allows to build detector elements that are large enough to cover full tracker half-layers with single bent sensors. The ALICE ITS 3 project is planning to build a new vertex tracker based on truly cylindrical wafer-scale sensors, with <0.05% X/X0 per layer and located as close as 18 mm to the interaction point. R&D on all project aspects (including mechanics for bent wafer-scale devices, test beams of bent MAPS, design of stitched sensors) is rapidly progressing with the aim for installation during LHC long shutdown 3 (2025–2027). This contribution summarises the project motivation, its R&D schedule, and will show selected highlights of recently accomplished project milestones, including full-scale engineering prototypes with dummy chips and small-scale, fully functional assemblies of functional, bent MAPS.
Characterization measurements of the TRISTAN multi-pixel silicon drift detector
Authors: Urban K. , Carminati M. , Descher M. , Edzards F. , Fink D. , Fiorini C. , Gugiatti M. , Hinz D. , Houdy T. , King P. , Lechner P. , Mertens S. , Siegmann D. , Steidl M. , Wolf J. 
Published: September 2022

Abstract
Sterile neutrinos are a minimal extension of the standard model of particle physics. A laboratory-based approach to search for this particle is via tritium β-decay, where a sterile neutrino would cause a kink-like spectral distortion. The Karlsruhe Tritium Neutrino (KATRIN) experiment extended by a multi-pixel Silicon Drift Detector system has the potential to reach an unprecedented sensitivity to the keV-scale sterile neutrino in a lab-based experiment. The new detector system combines good spectroscopic performance with a high rate capability. In this work, we report about the characterization of charge-sharing between pixels and the commissioning of a 47-pixel prototype detector in a MAC-E filter.
Allpix2 — silicon detector Monte Carlo simulations for particle physics and beyond
Authors: Spannagel S. , Schütze P. 
Published: September 2022

Abstract
Allpix2 is a versatile, open-source simulation framework for silicon pixel detectors. Its goal is to ease the implementation of detailed simulations for both single sensors and more complex setups with multiple detectors. While originally created for silicon detectors in high-energy physics, it is capable of simulating a wide range of detector types for various application scenarios, through its interface to Geant4 to describe the interaction of particles with matter, and the different algorithms for charge transport and digitization. The simulation chain is arranged with the help of intuitive configuration files and an extensible system of modules, which implement the individual simulation steps. Detailed electric field maps imported from TCAD simulations can be used to precisely model the drift behavior of the charge carriers, bringing a new level of realism to the Monte Carlo simulation of particle detectors.
Recently, Allpix2 has seen major improvements to its core framework to take full advantage of multi- and many-core processor architectures for simulating events fully parallel. Furthermore, new physics models such as charge carrier recombination in silicon have been introduced, further extending the application range. This contribution provides an overview of the framework and its components, highlighting the versatility and recent developments.
Xenogenic induction of adipose tissue and maintenance through pre- and post-conditioning using external volume expansion
Authors: Wu Mengfan , Matar Dany Y , Yu Zhen , Karvar Mehran , Chen Ziyu , Ng Brian , Knoedler Samuel , Darwish Oliver , Agarwal Shailesh , Orgill Dennis P , Panayi Adriana C 
Published: September 2022

Abstract
External volume expansion (EVE) has been shown to improve fat graft survival. In this study, we investigated the xenogenic implantation of human allograft adipose matrix (AAM) in non-immunocompromised mice in combination with pre- and post-conditioning with EVE to assess long-term adipose tissue survival. Sixty-eight recipient sites in thirty-four eight-week-old wild type (C57BL/6J) mice were separated into four groups. Thirty-four sites received no conditioning and either a subcutaneous injection of 300 μl saline (n = 17; PBS group) or AAM (n = 17; AAM group). Thirty-four sites received pre-conditioning with EVE (Day -7–3 pre-grafting) and 300 μl of AAM. Seventeen of these sites received immediate post-conditioning (Day 1–5 post-grafting) and 17 delayed post-conditioning (Day 28–32 post-grafting). Tissue was harvested at week 12 for analysis. At 12 weeks, immediate and delayed post-conditioning enabled higher volume retention (p = 0.02 and p < 0.0001, respectively). Adipose Stem Cells were greater in the AAM+Del-EVE group compared to the AAM (p = 0.01). Microvessel density was lower in the AAM group compared to the AAM+Imm-EVE (p = 0.04) and AAM+Del-EVE group (p = 0.02). Macrophage infiltration was lower in the AAM+Imm-EVE (p = 0.002) and AAM+Del-EVE (p = 0.003) groups compared to the AAM group. PCR analysis and Western blotting identified a significantly higher expression of PPAR-γ, LPL and VEGF with delayed-conditioning. Pre- and post-conditioning, particularly delayed-post-conditioning, of the recipient site optimized the microenvironment allowing significant adipogenesis and survival of neo-adipose tissue through robust angiogenesis. This study supports that xenogenic transplantation of adipose matrix allows adipose tissue formation and survival with EVE as an adjuvant.
A Kronig–Penney model in a quadratic channel with periodic δ-interactions: I. Dynamics
Authors: Guarneri Italo 
Published: September 2022

Abstract
A model of a particle in a line, coupled to a harmonic oscillator via a periodic chain of point interactions, is studied. At a critical value of the coupling strength a transition occurs, from a regime in which the oscillator is localized and the particle propagates arbitrarily far, to a regime in which the oscillator is delocalized, and the particle stays localized in position. In the latter regime the energy of the oscillator exponentially increases, while the particle is captured by the interaction points.
Unsteady edge waves generated by time-harmonic pressure: exact solutions
Authors: Abrashkin A A 
Published: September 2022

Abstract
An analytical description of unsteady edge waves over a uniform slope is proposed. It is assumed that the waves are excited by time-harmonic external pressure with inhomogeneous spatial distribution. The problem is considered in Lagrangian variables. An exact solution of the hydrodynamic equations is obtained. It generalizes the stationary Gerstner–Constantin solution. The proposed model describes the dynamics of coastal splashes of arbitrary initial shape. An important feature of the new solution is that it describes waves both propagating and standing in the longshore direction.
Multiscale engineered human skeletal muscles with perfusable vasculature and microvascular network recapitulating the fluid compartments
Authors: Kim Hyeonyu , Osaki Tatsuya , Kamm Roger D , Asada H Harry 
Published: September 2022

Abstract
Creating a vasculature in engineered human skeletal muscle tissues (ehSMTs) enables us to create thick tissues, increase cell survival in implantation, provide models of blood-organ barriers for drug testing, and enhance muscle differentiation through paracrine signaling. Here, contractile ehSMTs with a central perfusable vascular channel and microvascular networks growing from this central vasculature into the surrounding skeletal muscle tissue were newly demonstrated. Because coculturing muscle cells and endothelial cells requires incompatible media, we recapitulated the in vivo extracellular fluid compartments between blood plasma and interstitial fluid by creating an in vitro perfusable vasculature running through skeletal muscle tissue with a physiologic cell density. By using this model, we constructed large vascularized ehSMTs and showed the potential to be utilized for drug testing platforms. Also, we found that coculturing with two separate media from an early stage of muscle differentiation led to increased contractile force, thicker myotubes, and improved muscle differentiation.
Base Money
Authors: Kim Jeong Min 
Published: September 2022

Abstract
This article discusses how US military payment certificates (MPC) escaped from US military bases during the Korean War to become common currency in local economies. The MPC program was intended to control the mixing of US currency in local economies, yet the worldwide use of MPC on all overseas US bases between 1946 and 1973 facilitated black market circulation of military notes globally by allowing trading differentials among dollars, MPC, and local currencies. As soldiers, goods, and money moved through the US base network across Korea and Japan during the war, MPC were commonly used as a medium of exchange for sexual transactions between US soldiers and local women in both countries. The cross-border sexual markets were central to the everyday economies of Korea and Japan, of which black markets trading US Army supplies and currencies were major components. An analysis of this off-base monetization process of MPC offers a new perspective on the global history of war and occupation by highlighting how the sexual economy of illicit and informal transactions has been integral to US military expansion abroad since the end of World War II.
Deep learning joint models for extracting entities and relations in biomedical: a survey and comparison
Authors: Su Yansen , Wang Minglu , Wang Pengpeng , Zheng Chunhou , Liu Yuansheng , Zeng Xiangxiang 
Published: September 2022

AbstractThe rapid development of biomedicine has produced a large number of biomedical written materials. These unstructured text data create serious challenges for biomedical researchers to find information. Biomedical named entity recognition (BioNER) and biomedical relation extraction (BioRE) are the two most fundamental tasks of biomedical text mining. Accurately and efficiently identifying entities and extracting relations have become very important. Methods that perform two tasks separately are called pipeline models, and they have shortcomings such as insufficient interaction, low extraction quality and easy redundancy. To overcome the above shortcomings, many deep learning-based joint name entity recognition and relation extraction models have been proposed, and they have achieved advanced performance. This paper comprehensively summarize deep learning models for joint name entity recognition and relation extraction for biomedicine. The joint BioNER and BioRE models are discussed in the light of the challenges existing in the BioNER and BioRE tasks. Five joint BioNER and BioRE models and one pipeline model are selected for comparative experiments on four biomedical public datasets, and the experimental results are analyzed. Finally, we discuss the opportunities for future development of deep learning-based joint BioNER and BioRE models.
GNN-SubNet: disease subnetwork detection with explainable graph neural networks
Authors: Pfeifer Bastian , Saranti Anna , Holzinger Andreas 
Published: September 2022

AbstractMotivationThe tremendous success of graphical neural networks (GNNs) already had a major impact on systems biology research. For example, GNNs are currently being used for drug target recognition in protein–drug interaction networks, as well as for cancer gene discovery and more. Important aspects whose practical relevance is often underestimated are comprehensibility, interpretability and explainability.ResultsIn this work, we present a novel graph-based deep learning framework for disease subnetwork detection via explainable GNNs. Each patient is represented by the topology of a protein–protein interaction (PPI) network, and the nodes are enriched with multi-omics features from gene expression and DNA methylation. In addition, we propose a modification of the GNNexplainer that provides model-wide explanations for improved disease subnetwork detection.Availability and implementationThe proposed methods and tools are implemented in the GNN-SubNet Python package, which we have made available on our GitHub for the international research community (https://github.com/pievos101/GNN-SubNet).Supplementary informationSupplementary data are available at Bioinformatics online.
Detecting DNA of novel fungal pathogens using ResNets and a curated fungi-hosts data collection
Authors: Bartoszewicz Jakub M , Nasri Ferdous , Nowicka Melania , Renard Bernhard Y 
Published: September 2022

AbstractBackgroundEmerging pathogens are a growing threat, but large data collections and approaches for predicting the risk associated with novel agents are limited to bacteria and viruses. Pathogenic fungi, which also pose a constant threat to public health, remain understudied. Relevant data remain comparatively scarce and scattered among many different sources, hindering the development of sequencing-based detection workflows for novel fungal pathogens. No prediction method working for agents across all three groups is available, even though the cause of an infection is often difficult to identify from symptoms alone.ResultsWe present a curated collection of fungal host range data, comprising records on human, animal and plant pathogens, as well as other plant-associated fungi, linked to publicly available genomes. We show that it can be used to predict the pathogenic potential of novel fungal species directly from DNA sequences with either sequence homology or deep learning. We develop learned, numerical representations of the collected genomes and visualize the landscape of fungal pathogenicity. Finally, we train multi-class models predicting if next-generation sequencing reads originate from novel fungal, bacterial or viral threats.ConclusionsThe neural networks trained using our data collection enable accurate detection of novel fungal pathogens. A curated set of over 1400 genomes with host and pathogenicity metadata supports training of machine-learning models and sequence comparison, not limited to the pathogen detection task.Availability and implementationThe data, models and code are hosted at https://zenodo.org/record/5846345, https://zenodo.org/record/5711877 and https://gitlab.com/dacs-hpi/deepac.Supplementary informationSupplementary data are available at Bioinformatics online.
CGR-CUSUM: a continuous time generalized rapid response cumulative sum chart
Authors: Gomon Daniel , Putter Hein , Nelissen Rob G H H , Van Der Pas Stéphanie 
Published: September 2022

Summary
Rapidly detecting problems in the quality of care is of utmost importance for the well-being of patients. Without proper inspection schemes, such problems can go undetected for years. Cumulative sum (CUSUM) charts have proven to be useful for quality control, yet available methodology for survival outcomes is limited. The few available continuous time inspection charts usually require the researcher to specify an expected increase in the failure rate in advance, thereby requiring prior knowledge about the problem at hand. Misspecifying parameters can lead to false positive alerts and large detection delays. To solve this problem, we take a more general approach to derive the new Continuous time Generalized Rapid response CUSUM (CGR-CUSUM) chart. We find an expression for the approximate average run length (average time to detection) and illustrate the possible gain in detection speed by using the CGR-CUSUM over other commonly used monitoring schemes on a real-life data set from the Dutch Arthroplasty Register as well as in simulation studies. Besides the inspection of medical procedures, the CGR-CUSUM can also be used for other real-time inspection schemes such as industrial production lines and quality control of services.
Age differences in the functional organization of the prefrontal cortex: analyses of competing hypotheses
Authors: Hsieh Shulan , Yang Meng-Heng , Yao Zai-Fu 
Published: September 2022

AbstractWe employed a mixed design task for block and event-related functional magnetic resonance imaging with manipulations of levels of abstraction and duration in task-relevant cues and probes. Age-related differences between younger and older adults in task-related functional brain activity patterns of the prefrontal cortex (PFC) were reported. The results showed that (1) the low episodic condition evoked more activity in the more anterior PFC than the high episodic control condition for both age groups; (2) the low abstraction condition evoked more activity in the more anterior PFC than the high abstraction condition for both age groups; and (3) the signal change did not vary as a function of activity dynamics (transient and sustained responses) and maintenance duration (single-trial and multiple-trial). The findings showed that baseline conditions evoked more activity in the more anterior PFC for the older group than the younger group across most task contrasts and conditions, where these additional activities in the brain regions overlapped within the default mode network (DMN). We tentatively concluded that deficiency in the anterior DMN deactivation during externally driven tasks might be attributed to less efficiency in modulating local connectivity propagate to surrounding tissue, which may paradoxically increase brain activity.
Patterns of retrieval-related cortico-striatal connectivity are stable across the adult lifespan
Authors: Hill Paul F , de Chastelaine Marianne , Rugg Michael D 
Published: September 2022

AbstractMemory retrieval effects in the striatum are well documented and robust across experimental paradigms. However, the functional significance of these effects, and whether they are moderated by age, remains unclear. We used functional magnetic resonance imaging paired with an associative recognition task to examine retrieval effects in the striatum in a sample of healthy young, middle-aged, and older adults. We identified anatomically segregated patterns of enhanced striatal blood oxygen level-dependent (BOLD) activity during recollection- and familiarity-based memory judgments. Successful recollection was associated with enhanced BOLD activity in bilateral putamen and nucleus accumbens, and neither of these effects were reliably moderated by age. Familiarity effects were evident in the head of the caudate nucleus bilaterally, and these effects were attenuated in middle-aged and older adults. Using psychophysiological interaction analyses, we observed a monitoring-related increase in functional connectivity between the caudate and regions of the frontoparietal control network, and between the putamen and bilateral retrosplenial cortex and intraparietal sulcus. In all instances, monitoring-related increases in cortico-striatal connectivity were unmoderated by age. These results suggest that the striatum, and the caudate in particular, couples with the frontoparietal control network to support top-down retrieval-monitoring operations, and that the strength of these inter-regional interactions is preserved in later life.
Point-of-Care Tenofovir Urine Testing for the Prediction of Treatment Failure and Drug Resistance During Initial Treatment for Human Immunodeficiency Virus Type 1 (HIV-1) Infection
Authors: Hermans Lucas E , Umunnakwe Chijioke N , Lalla-Edward Samanta T , Hebel Shane K , Tempelman Hugo A , Nijhuis Monique , Venter Willem D F , Wensing Annemarie M J 
Published: September 2022

ABSTRACTBackgroundViral rebound during antiretroviral treatment (ART) is most often driven by suboptimal adherence in the absence of drug resistance. We assessed the diagnostic performance of point-of-care (POC) tenofovir (TFV) detection in urine for the prediction of viral rebound and drug resistance during ART.MethodsWe performed a nested case-control study within the ADVANCE randomized clinical trial (NCT03122262) in Johannesburg, South Africa. Adults with human immunodeficiency virus (HIV) and newly initiating ART were randomized to receive either dolutegravir or efavirenz, tenofovir disoproxil fumarate or alafenamide, and emtricitabine. All participants with rebound ≥200 copies/mL between 24 and 96 weeks of follow-up were selected as cases and matched to controls with virological suppression &lt;50 copies/mL. Rapid POC urine-TFV detection was performed retrospectively.ResultsWe included 281 samples from 198 participants. Urine-TFV was detectable in 30.7% (70/228) of cases and in 100% (53/53) of controls. Undetectable urine-TFV predicted rebound with a sensitivity of 69% [95% confidence interval {CI}: 63–75] and specificity of 100% [93–100]. In cases with virological failure and sequencing data (n = 42), NRTI drug resistance was detected in 50% (10/20) of cases with detectable urine-TFV versus in 8.3% (2/24) of cases with undetectable urine-TFV. Detectable urine-TFV predicted NRTI resistance (odds ratio [OR] 10.4 [1.8–114.4] P = .005) with a sensitivity of 83% [52–98] and specificity of 69% [50–84].ConclusionsPOC objective adherence testing using a urine-TFV test predicted viral rebound with high specificity. In participants with rebound, urine-TFV testing predicted the selection of drug resistance. Objective adherence testing may be used to rapidly provide insight into adherence, suppression, and drug resistance during ART.
Effectiveness of Molnupiravir in High-Risk Patients: A Propensity Score Matched Analysis
Authors: Najjar-Debbiny Ronza , Gronich Naomi , Weber Gabriel , Khoury Johad , Amar Maisam , Stein Nili , Goldstein Lee Hilary , Saliba Walid 
Published: September 2022

Abstract

Background
Molnupiravir was granted emergency use authorization for the treatment of mild to moderate coronavirus disease 2019 (COVID-19). In this study, we used population-based real-world data to evaluate the effectiveness of molnupiravir.

Methods
The database of the largest healthcare provider in Israel was used to identify all adults with first-ever positive test for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) performed in the community during January–February 2022, who were at high risk for severe COVID-19, and had no contraindications for molnupiravir use. Patients were included regardless of SARS-CoV-2 vaccination status. A total of 2661 patients who received molnupiravir were propensity score matched with 2661 patients who have not received molnupiravir (control group). Patients were followed through 10 March 2022 for up to 28 days for the first occurrence of the composite severe COVID-19 or COVID-19-specific mortality.

Results
The composite outcome occurred in 50 patients in the molnupiravir group and 60 patients in the control group. Molnupiravir was associated with a nonsignificant reduced risk of the composite outcome: hazard ratio, 0.83 (95% confidence interval, .57–1.21). However, subgroup analyses showed that molnupiravir was associated with a significant decrease in the risk of the composite outcome in older patients 0.54 (0.34–0.86), in females 0.41 (0.22–0.77), and in patients with inadequate COVID-19 vaccination 0.45 (0.25–0.82). The results were similar when each component of the composite outcome was examined separately.

Conclusions
This study suggests that in the era of Omicron and in real-life setting, molnupiravir might be effective in reducing the risk of severe COVID-19 and COVID-19-related mortality, particularly in specific subgroups.