bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prediction of Distributed River Sediment Respiration Rates Using Community‐Generated Data and Machine Learning
Authors: Gary Stefan F. , Scheibe Timothy D. , Rexer Em , Torreira Alvaro Vidal , Garayburu‐Caruso Vanessa A. , Goldman Amy , Stegen James C. 
Published: July 2024

AbstractRiver sediment microbial respiration is a key indicator of ecosystem functioning and the biogeochemical fluxes across this critical zone link surface and subsurface waters. As such, there is tremendous interest in measuring and mapping these respiration rates. Respiration observations are expensive and labor intensive; there is limited data available to the community. An open science, collaborative initiative is collecting samples for respiration rate analysis and multi‐scale metadata; this evolving data set is being used for making machine learning (ML) predictions at unsampled sites to help inform continued community engagement. However, it is a challenge to find an optimum configuration for ML models to work with this feature‐rich (i.e., 100+ possible input variables) data set. Here, we present results from a two‐tiered approach to managing the analysis of this complex data set: (a) a stacked ensemble of models that automatically optimizes hyperparameters and manages the training of many models and (b) feature permutation importance to detect the most important features in the models. The major elements of this workflow are modular, portable, open, and cloud‐based thus making this implementation a potential template for other applications. The models developed here predict that sediment organic matter chemistry is one of the most important features for predicting sediment respiration rate. Other larger‐scale, important features fall into the categories of climatic, ecological, geological, and fluvial settings. Leveraging these larger‐scale features to generate data‐driven estimates of river sediment respiration rates reveals spatially consistent but heterogeneous patterns across the river network of the Columbia River Basin.
Maternal, neonatal, and nutritional risk factors for medical and surgical necrotizing enterocolitis
Authors: Essex Clare , Hegedus Clifford , Vincent Katherine , Shiflett Alanna , Rohrer Allison , Chetta Katherine E. 
Published: July 2024

Abstract
Objective
To identify maternal and neonatal risk factors associated with progression to surgery or death after diagnosis of NEC.

Study design
Forty-seven demographic and clinical factors were evaluated across 216 validated cases of NEC occurring between 2010–2020. Nutrition at NEC onset was evaluated in 149 cases. The binary outcome of surgical NEC (progressing to surgery or death) vs. medical NEC (resolved with antibiotic/bowel rest) was compared across variables.

Results
Elevated CRP, rapidly decreasing platelet counts, inotropic medication, intubation, and positive blood cultures within 24 h of diagnosis were associated with progression to surgery/death. Infants with surgical NEC had higher abdominal circumferences at birth. Maternal milk intake and receipt of human milk fortifiers were associated with medical NEC, and infants receiving fortified, maternal milk showed the lowest progression to surgery/death.

Conclusion
The index of suspicion should be heightened for surgical NEC when these risk factors are present.
Learning from models: high-dimensional analyses on the performance of machine learning interatomic potentials
Authors: Liu Yunsheng , Mo Yifei 
Published: July 2024

AbstractMachine learning interatomic potential (MLIP) has been widely adopted for atomistic simulations. While errors and discrepancies for MLIPs have been reported, a comprehensive examination of the MLIPs’ performance over a broad spectrum of material properties has been lacking. This study introduces an analysis process comprising model sampling, benchmarking, error evaluations, and multi-dimensional statistical analyses on an ensemble of MLIPs for prediction errors over a diverse range of properties. By carrying out this analysis on 2300 MLIP models based on six different MLIP types, several properties that pose challenges for the MLIPs to achieve small errors are identified. The Pareto front analyses on two or more properties reveal the trade-offs in different properties of MLIPs, underscoring the difficulties of achieving low errors for a large number of properties simultaneously. Furthermore, we propose correlation graph analyses to characterize the error performances of MLIPs and to select the representative properties for predicting other property errors. This analysis process on a large dataset of MLIP models sheds light on the underlying complexities of MLIP performance, offering crucial guidance for the future development of MLIPs with improved predictive accuracy across an array of material properties.
CRISPRi–TnSeq maps genome-wide interactions between essential and non-essential genes in bacteria
Authors: Jana Bimal , Liu Xue , Dénéréaz Julien , Park Hongshik , Leshchiner Dmitry , Liu Bruce , Gallay Clément , Zhu Junhao , Veening Jan-Willem , van Opijnen Tim 
Published: July 2024

AbstractGenetic interactions identify functional connections between genes and pathways, establishing gene functions or druggable targets. Here we use CRISPRi–TnSeq, CRISPRi-mediated knockdown of essential genes alongside TnSeq-mediated knockout of non-essential genes, to map genome-wide interactions between essential and non-essential genes in Streptococcus pneumoniae. Transposon-mutant libraries constructed in 13 CRISPRi strains enabled screening of ~24,000 gene pairs. This identified 1,334 genetic interactions, including 754 negative and 580 positive interactions. Network analyses show that 17 non-essential genes pleiotropically interact with more than half the essential genes tested. Validation experiments confirmed that a 7-gene subset protects against perturbations. Furthermore, we reveal hidden redundancies that compensate for essential gene loss, relationships between cell wall synthesis, integrity and cell division, and show that CRISPRi–TnSeq identifies synthetic and suppressor-type relationships between both functionally linked and disparate genes and pathways. Importantly, in species where CRISPRi and Tn-Seq are established, CRISPRi–TnSeq should be straightforward to implement.
FHIR-standardized data collection on the clinical rehabilitation pathway of trans-femoral amputation patients
Authors: Arcobelli Valerio Antonio , Moscato Serena , Palumbo Pierpaolo , Marfoglia Alberto , Nardini Filippo , Randi Pericle , Davalli Angelo , Carbonaro Antonella , Chiari Lorenzo , Mellone Sabato 
Published: July 2024

AbstractLower limb amputation is a medical intervention which causes motor disability and may compromise quality of life. Several factors determine patients’ health outcomes, including an appropriate prosthetic provision and an effective rehabilitation program, necessitating a thorough quantitative observation through different data sources. In this context, the role of interoperability becomes essential, facilitating the reuse of real-world data through the provision of structured and easily accessible databases. This study introduces a comprehensive 10-year dataset encompassing clinical features, mobility measurements, and prosthetic knees of 1006 trans-femoral amputees during 1962 hospital stays for rehabilitation. The dataset is made available in both comma-separated values (CSV) format and HL7 Fast Healthcare Interoperability Resources (FHIR)-based representation, ensuring broad utility and compatibility for researchers and healthcare practitioners. This initiative contributes to advancing community understanding of post-amputation rehabilitation and underscores the significance of interoperability in promoting seamless data sharing for meaningful insights into healthcare outcomes.
Two chromosome-level genome assemblies of galling aphids Slavum lentiscoides and Chaetogeoica ovagalla
Authors: Xu Shifen , Jiang Liyun , Zou Zhengting , Zou Ming , Qiao Gexia , Chen Jing 
Published: July 2024

AbstractSlavum lentiscoides and Chaetogeoica ovagalla are two aphid species from the subtribe Fordina of Fordini within the subfamily Eriosomatinae, and they produce galls on their primary host plants Pistacia. We assembled chromosome-level genomes of these two species using Nanopore long-read sequencing and Hi-C technology. A 332 Mb genome assembly of S. lentiscoides with a scaffold N50 of 19.77 Mb, including 11,747 genes, and a 289 Mb genome assembly of C. ovagalla with a scaffold N50 of 11.85 Mb, containing 14,492 genes, were obtained. The Benchmarking Universal Single-Copy Orthologs (BUSCO) benchmark of the two genome assemblies reached 93.7% (91.9% single-copy) and 97.0% (95.3% single-copy), respectively. The high-quality genome assemblies in our study provide valuable resources for future genomic research of galling aphids.
Avoidance of specific calibration sessions in motor intention recognition for exoskeleton-supported rehabilitation through transfer learning on EEG data
Authors: Kueper Niklas , Kim Su Kyoung , Kirchner Elsa Andrea 
Published: July 2024

AbstractExoskeleton-based support for patients requires the learning of individual machine-learning models to recognize movement intentions of patients based on the electroencephalogram (EEG). A major issue in EEG-based movement intention recognition is the long calibration time required to train a model. In this paper, we propose a transfer learning approach that eliminates the need for a calibration session. This approach is validated on healthy subjects in this study. We will use the proposed approach in our future rehabilitation application, where the movement intention of the affected arm of a patient can be inferred from the EEG data recorded during bilateral arm movements enabled by the exoskeleton mirroring arm movements from the unaffected to the affected arm. For the initial evaluation, we compared two trained models for predicting unilateral and bilateral movement intentions without applying a classifier transfer. For the main evaluation, we predicted unilateral movement intentions without a calibration session by transferring the classifier trained on data from bilateral movement intentions. Our results showed that the classification performance for the transfer case was comparable to that in the non-transfer case, even with only 4 or 8 EEG channels. Our results contribute to robotic rehabilitation by eliminating the need for a calibration session, since EEG data for training is recorded during the rehabilitation session, and only a small number of EEG channels are required for model training.
ChaQra: a cellular unit of the Indian quantum network
Authors: Gupta Shashank , Agarwal Iteash , Mogiligidda Vijayalaxmi , Kumar Krishnan Rajesh , Chennuri Sruthi , Aggarwal Deepika , Hoodati Anwesha , Cooper Sheroy , Ranjan  , Bilal Sheik Mohammad , Bhavya K. M. , Hegde Manasa , Krishna M. Naveen , Chauhan Amit Kumar , Korrapati Mallikarjun , Singh Sumit , Singh J. B. , Sud Sunil , Gupta Sunil , Pant Sidhartha , Sankar  , Agrawal Neha , Ranjan Ashish , Mohapatra Piyush , Roopak T. , Ahmad Arsh , Nanjunda M. , Singh Dilip 
Published: July 2024

AbstractMajor research interests on quantum key distribution (QKD) are primarily focused on increasing 1. Point-to-point transmission distance (1000 km). 2. Secure key rate (Mbps). 3. Security of quantum layer (device-independence). It is great to push the boundaries in these fronts but these isolated approaches are neither scalable nor cost-effective due to requirements of specialised hardware and different infrastructure. Current and future QKD network requires addressing different set of challenges apart from distance, key rate and quantum security. In this regard, we present ChaQra—a sub quantum network with core features as 1. Crypto agility (integration in the already deployed telecommunication fibres). 2. Software defined networking (SDN paradigm for routing different nodes). 3. reliability (addressing denial-of-service with hybrid quantum safe cryptography). 4. upgradability (modules upgradation based on scientific and technological advancements). 5. Beyond QKD (using QKD network for distributed computing, multi-party computation etc). Our results demonstrate a clear path to create and accelerate quantum secure Indian subcontinent under national quantum mission.
Diel transcriptional responses of coral-Symbiodiniaceae holobiont to elevated temperature
Authors: Gong Sanqiang , Liang Jiayuan , Xu Lijia , Wang Yongzhi , Li Jun , Jin Xuejie , Yu Kefu , Zhang Yuehuan 
Published: July 2024

AbstractCoral exhibits diel rhythms in behavior and gene transcription. However, the influence of elevated temperature, a key factor causing coral bleaching, on these rhythms remains poorly understood. To address this, we examined physiological, metabolic, and gene transcription oscillations in the Acropora tenuis-Cladocopium sp. holobiont under constant darkness (DD), light-dark cycle (LD), and LD with elevated temperature (HLD). Under LD, the values of photosystem II efficiency, reactive oxygen species leakage, and lipid peroxidation exhibited significant diel oscillations. These oscillations were further amplified during coral bleaching under HLD. Gene transcription analysis identified 24-hour rhythms for specific genes in both coral and Symbiodiniaceae under LD. Notably, these rhythms were disrupted in coral and shifted in Symbiodiniaceae under HLD. Importantly, we identified over 20 clock or clock-controlled genes in this holobiont. Specifically, we suggested CIPC (CLOCK-interacting pacemaker-like) gene as a core clock gene in coral. We observed that the transcription of two abundant rhythmic genes encoding glycoside hydrolases (CBM21) and heme-binding protein (SOUL) were dysregulated by elevated temperature. These findings indicate that elevated temperatures disrupt diel gene transcription rhythms in the coral-Symbiodiniaceae holobiont, affecting essential symbiosis processes, such as carbohydrate utilization and redox homeostasis. These disruptions may contribute to the thermal bleaching of coral.
Performance of quantum annealing inspired algorithms for combinatorial optimization problems
Authors: Zeng Qing-Guo , Cui Xiao-Peng , Liu Bowen , Wang Yao , Mosharev Pavel , Yung Man-Hong 
Published: July 2024

AbstractTwo classes of quantum-annealing-inspired-algorithms (QAIA), namely different variants of simulated coherent Ising machine and simulated bifurcation, have been proposed for efficiently solving combinatorial optimization problems recently. In order to certify the superiority of these algorithms, standardized comparisons among them and against other physics-based algorithms are necessary. In this work, for Max-Cut problems up to 20,000 nodes, we benchmark QAIA against quantum annealing and other physics-based algorithms. We found that ballistic simulated bifurcation excelled for chimera and small-scale graphs, achieving nearly a 50-fold reduction in time-to-solution compared to quantum annealing. For large-scale graphs, discrete simulated bifurcation achieves the lowest time-to-target and outperforms D-Wave Advantage system when tasked with finding the maximum cut value in pegasus graphs. Our results suggest that QAIA represents a promising means for solving combinatorial optimization problems in practice, and can act as a natural baseline for competing quantum algorithms.
Metal-organic framework single crystal for in-memory neuromorphic computing with a light control
Authors: Bachinin Semyon V. , Marunchenko Alexandr , Matchenya Ivan , Zhestkij Nikolai , Shirobokov Vladimir , Gunina Ekaterina , Novikov Alexander , Timofeeva Maria , Povarov Svyatoslav A. , Li Fengting , Milichko Valentin A. 
Published: July 2024

AbstractNeuromorphic architectures, expanding the limits of computing from conventional data processing and storage to advanced cognition, learning, and in-memory computing, impose restrictions on materials that should operate fast, energy efficiently, and highly endurant. Here we report on in-memory computing architecture based on metal-organic framework (MOF) single crystal with a light control. We demonstrate that the MOF with inherent memristive behavior (for data storage) changes nonlinearly its electric response when irradiated by light. This leads to three and more electronic states (spikes) with 81 ms duration and 1 s refractory time, allowing to implement 40 bits s−1 optoelectronic data processing. Next, the architecture is switched to the neuromorphic state upon the action of a set of laser pulses, providing the text recognition over 50 times with app. 100% accuracy. Thereby, simultaneous data storage, processing, and neuromorphic computing on MOF, driven by light, pave the way for multifunctional in-memory computing architectures.
Fast in-line failure analysis of sub-micron-sized cracks in 3D interconnect technologies utilizing acoustic interferometry
Authors: Paulachan Priya , Hammer René , Siegert Joerg , Wiesler Ingo , Brunner Roland 
Published: July 2024

AbstractMore than Moore technology is driving semiconductor devices towards higher complexity and further miniaturization. Device miniaturization strongly impacts failure analysis (FA), since it triggers the need for non-destructive approaches with high resolution in combination with cost and time efficient execution. Conventional scanning acoustic microscopy (SAM) is an indispensable tool for failure analysis in the semiconductor industry, however resolution and penetration capabilities are strongly limited by the transducer frequency. In this work, we conduct an acoustic interferometry approach, based on a SAM-setup utilizing 100 MHz lenses and enabling not only sufficient penetration depth but also high resolution for efficient in-line FA of Through Silicon Vias (TSVs). Accompanied elastodynamic finite integration technique-based simulations, provide an in-depth understanding concerning the acoustic wave excitation and propagation. We show that the controlled excitation of surface acoustic waves extends the contingency towards the detection of nm-sized cracks, an essential accomplishment for modern FA of 3D-integration technologies.
LILRB1-HLA-G axis defines a checkpoint driving natural killer cell exhaustion in tuberculosis
Authors: Wang Jing , Chai Qiyao , Lei Zehui , Wang Yiru , He Jiehua , Ge Pupu , Lu Zhe , Qiang Lihua , Zhao Dongdong , Yu Shanshan , Qiu Changgen , Zhong Yanzhao , Li Bing-Xi , Zhang Lingqiang , Pang Yu , Gao George Fu , Liu Cui Hua 
Published: July 2024

AbstractChronic infections, including Mycobacterium tuberculosis (Mtb)-caused tuberculosis (TB), can induce host immune exhaustion. However, the key checkpoint molecules involved in this process and the underlying regulatory mechanisms remain largely undefined, which impede the application of checkpoint-based immunotherapy in infectious diseases. Here, through adopting time-of-flight mass cytometry and transcriptional profiling to systematically analyze natural killer (NK) cell surface receptors, we identify leukocyte immunoglobulin like receptor B1 (LILRB1) as a critical checkpoint receptor that defines a TB-associated cell subset (LILRB1+ NK cells) and drives NK cell exhaustion in TB. Mechanistically, Mtb-infected macrophages display high expression of human leukocyte antigen-G (HLA-G), which upregulates and activates LILRB1 on NK cells to impair their functions by inhibiting mitogen-activated protein kinase (MAPK) signaling via tyrosine phosphatases SHP1/2. Furthermore, LILRB1 blockade restores NK cell-dependent anti-Mtb immunity in immuno-humanized mice. Thus, LILRB1-HLA-G axis constitutes a NK cell immune checkpoint in TB and serves as a promising immunotherapy target.
Video Modeling to Support Social Communication Goals of Autistic Adults: A Tutorial
Authors: Wilson Kaitlyn P. , Valazza Emily , Price Carrie 
Published: July 2024

Purpose:
Decades of research have shown video modeling to be an effective tool for teaching and supporting a variety of skills in autistic children. More recently, video modeling has emerged as an effective support for autistic adults, with much of the literature focused on vocational success through support of language skills. The purpose of this tutorial is to provide speech-language pathologists, autistic adults, and other team members with evidence-based guidelines for use of video modeling to support success with social communication across settings.

Method:
This evidence-based tutorial draws from the literature on video modeling for autistic adults in the area of social communication, presenting empirically supported guidelines for speech-language pathologists considering video modeling as a tool to support social communication within this population and their interaction partners. This tutorial presents an evidence-based, step-by-step guide to the planning, creation, and use of video models with and by autistic adults, along with important additional considerations based on relevant literature.

Conclusions:
Video modeling is a social communication support that is backed by the scientific literature as an efficacious tool for use by autistic adults. This tutorial will guide speech-language pathologists' use of this evidence-based tool as they work alongside autistic adults and others to help meet social communication goals across settings.
Comparison of Characteristics and Outcomes of Multisystem Inflammatory Syndrome and Prepandemic Kawasaki's Disease
Authors: Ünlü Neşe , Özel Abdulrahman , Büke Övgü , Onan Sertaç Hanedan , Tenekecigil Aslıhan , Erol Meltem , Gayret Özlem Bostan 
Published: July 2024

Abstract
Objective In this study, our objective is to compare the demographic, clinical, laboratory, and echocardiographic findings of patients with multisystem inflammatory syndrome in children (MIS-C) and Kawasaki's disease (KD) diagnosed in the prepandemic period.
Methods We retrospectively collected data from all pediatric patients who met the Centers for Disease Control and Prevention's MIS-C case definition and who met the American Heart Association's definition of complete KD before the coronavirus disease 2019 pandemic.
Results A total of 37 patients diagnosed with MIS-C and 40 patients diagnosed with complete KD were included. Gastrointestinal findings were significantly higher in the MIS-C group than in the KD group (vomiting [p = 0.009], diarrhea [p = 0.009]). The incidence of thrombocytopenia (48.6%) was significantly higher in the MIS-C group. Regarding inflammatory markers, procalcitonin and ferritin were significantly higher in the MIS-C group (p = 0.032 and p = 0.006) and the erythrocyte sedimentation rate was higher in the KD group (p < 0.001). Pericardial effusion and mitral valve regurgitation were significantly more frequent in the MIS-C group (p = 0.024 and p = 0.001).
Conclusion Although they have similar findings, our current study findings show that MIS-C and KD differ from each other with different clinical and laboratory features. We think that these differences will help clinicians in diagnosis and patient management.