bluuebunny/crossref_metadata_2025_split huggingface dataset:
Implementing psychological interventions delivered by respiratory professionals for people with COPD. A stakeholder interview study
Authors: Wileman V. , Rowland V. , Kelly M. , Steed L. , Sohanpal R. , Pinnock H. , Taylor S. J. C. 
Published: October 2023

AbstractImplementing psychological interventions in healthcare services requires an understanding of the organisational context. We conducted an interview study with UK National Health Service stakeholders to understand the barriers and facilitators for implementing psychological interventions for people with chronic obstructive pulmonary disorder (COPD). We used TANDEM as an exemplar intervention; a psychological intervention recently evaluated in a randomised controlled trial. Twenty participants providing care and/or services to people with COPD were purposively sampled from NHS primary/secondary care, and commissioning organisations. Participants were recruited via professional networks and referrals. Verbatim transcripts of semi-structured interviews were analysed using thematic analysis. Four themes were identified: (1) Living with COPD and emotional distress affects engagement with physical and psychological services; (2) Resource limitations affects service provision in COPD; (3) Provision of integrated care is important for patient well-being; and (4) Healthcare communication can be an enabler or a barrier to patient engagement. People need support with physical and psychological symptoms inherent with COPD and healthcare should be provided holistically. Respiratory healthcare professionals are considered able to provide psychologically informed approaches, but resources must be available for training, staff supervision and service integration. Communication between professionals is vital for clear understanding of an intervention’s aims and content, to facilitate referrals and uptake. There was widespread commitment to integrating psychological and physical care, and support of respiratory healthcare professionals’ role in delivering psychological interventions but significant barriers to implementation due to concerns around resources and cost efficiency. The current study informs future intervention development and implementation.
Quantum logic gate synthesis as a Markov decision process
Authors: Alam M. Sohaib , Berthusen Noah F. , Orth Peter P. 
Published: October 2023

AbstractReinforcement learning has witnessed recent applications to a variety of tasks in quantum programming. The underlying assumption is that those tasks could be modeled as Markov decision processes (MDPs). Here, we investigate the feasibility of this assumption by exploring its consequences for single-qubit quantum state preparation and gate compilation. By forming discrete MDPs, we solve for the optimal policy exactly through policy iteration. We find optimal paths that correspond to the shortest possible sequence of gates to prepare a state or compile a gate, up to some target accuracy. Our method works in both the absence and presence of noise and compares favorably to other quantum compilation methods, such as the Ross–Selinger algorithm. This work provides theoretical insight into why reinforcement learning may be successfully used to find optimally short gate sequences in quantum programming.
All-analog photoelectronic chip for high-speed vision tasks
Authors: Chen Yitong , Nazhamaiti Maimaiti , Xu Han , Meng Yao , Zhou Tiankuang , Li Guangpu , Fan Jingtao , Wei Qi , Wu Jiamin , Qiao Fei , Fang Lu , Dai Qionghai 
Published: October 2023

AbstractPhotonic computing enables faster and more energy-efficient processing of vision data1–5. However, experimental superiority of deployable systems remains a challenge because of complicated optical nonlinearities, considerable power consumption of analog-to-digital converters (ADCs) for downstream digital processing and vulnerability to noises and system errors1,6–8. Here we propose an all-analog chip combining electronic and light computing (ACCEL). It has a systemic energy efficiency of 74.8 peta-operations per second per watt and a computing speed of 4.6 peta-operations per second (more than 99% implemented by optics), corresponding to more than three and one order of magnitude higher than state-of-the-art computing processors, respectively. After applying diffractive optical computing as an optical encoder for feature extraction, the light-induced photocurrents are directly used for further calculation in an integrated analog computing chip without the requirement of analog-to-digital converters, leading to a low computing latency of 72 ns for each frame. With joint optimizations of optoelectronic computing and adaptive training, ACCEL achieves competitive classification accuracies of 85.5%, 82.0% and 92.6%, respectively, for Fashion-MNIST, 3-class ImageNet classification and time-lapse video recognition task experimentally, while showing superior system robustness in low-light conditions (0.14 fJ μm−2 each frame). ACCEL can be used across a broad range of applications such as wearable devices, autonomous driving and industrial inspections.
Evidence for a liquid silicate layer atop the Martian core
Authors: Khan A. , Huang D. , Durán C. , Sossi P. A. , Giardini D. , Murakami M. 
Published: October 2023

AbstractSeismic recordings made during the InSight mission1 suggested that Mars’s liquid core would need to be approximately 27% lighter than pure liquid iron2,3, implying a considerable complement of light elements. Core compositions based on seismic and bulk geophysical constraints, however, require larger quantities of the volatile elements hydrogen, carbon and sulfur than those that were cosmochemically available in the likely building blocks of Mars4. Here we show that multiply diffracted P waves along a stratified core–mantle boundary region of Mars in combination with first-principles computations of the thermoelastic properties of liquid iron-rich alloys3 require the presence of a fully molten silicate layer overlying a smaller, denser liquid core. Inverting differential body wave travel time data with particular sensitivity to the core–mantle boundary region suggests a decreased core radius of 1,675 ± 30 km associated with an increased density of 6.65 ± 0.1 g cm−3, relative to previous models2,4–8, while the thickness and density of the molten silicate layer are 150 ± 15 km and 4.05 ± 0.05 g cm−3, respectively. The core properties inferred here reconcile bulk geophysical and cosmochemical requirements, consistent with a core containing 85–91 wt% iron–nickel and 9–15 wt% light elements, chiefly sulfur, carbon, oxygen and hydrogen. The chemical characteristics of a molten silicate layer above the core may be revealed by products of Martian magmatism.
A single photoreceptor splits perception and entrainment by cotransmission
Authors: Xiao Na , Xu Shuang , Li Ze-Kai , Tang Min , Mao Renbo , Yang Tian , Ma Si-Xing , Wang Peng-Hao , Li Meng-Tong , Sunilkumar Ajay , Rouyer François , Cao Li-Hui , Luo Dong-Gen 
Published: October 2023

AbstractVision enables both image-forming perception, driven by a contrast-based pathway, and unconscious non-image-forming circadian photoentrainment, driven by an irradiance-based pathway1,2. Although two distinct photoreceptor populations are specialized for each visual task3–6, image-forming photoreceptors can additionally contribute to photoentrainment of the circadian clock in different species7–15. However, it is unknown how the image-forming photoreceptor pathway can functionally implement the segregation of irradiance signals required for circadian photoentrainment from contrast signals required for image perception. Here we report that the Drosophila R8 photoreceptor separates image-forming and irradiance signals by co-transmitting two neurotransmitters, histamine and acetylcholine. This segregation is further established postsynaptically by histamine-receptor-expressing unicolumnar retinotopic neurons and acetylcholine-receptor-expressing multicolumnar integration neurons. The acetylcholine transmission from R8 photoreceptors is sustained by an autocrine negative feedback of the cotransmitted histamine during the light phase of light–dark cycles. At the behavioural level, elimination of histamine and acetylcholine transmission impairs R8-driven motion detection and circadian photoentrainment, respectively. Thus, a single type of photoreceptor can achieve the dichotomy of visual perception and circadian photoentrainment as early as the first visual synapses, revealing a simple yet robust mechanism to segregate and translate distinct sensory features into different animal behaviours.
Land cover and forest health indicator datasets for central India using very-high resolution satellite data
Authors: Khanwilkar Sarika , Galletti Chris , Mondal Pinki , Urpelainen Johannes , Nagendra Harini , Jhala Yadvendradev , Qureshi Qamar , DeFries Ruth 
Published: October 2023

AbstractSatellite imagery has been used to provide global and regional estimates of forest cover. Despite increased availability and accessibility of satellite data, approaches for detecting forest degradation have been limited. We produce a very-high resolution 3-meter (m) land cover dataset and develop a normalized index, the Bare Ground Index (BGI), to detect and map exposed bare ground within forests at 90 m resolution in central India. Tree cover and bare ground was identified from Planet Labs Very High-Resolution satellite data using a Random Forest classifier, resulting in a thematic land cover map with 83.00% overall accuracy (95% confidence interval: 61.25%–90.29%). The BGI is a ratio of bare ground to tree cover and was derived by aggregating the land cover. Results from field data indicate that the BGI serves as a proxy for intensity of forest use although open areas occur naturally. The BGI is an indicator of forest health and a baseline to monitor future changes to a tropical dry forest landscape at an unprecedented spatial scale.
Chromosome-scale assembly of the wild wheat relative Aegilops umbellulata
Authors: Abrouk Michael , Wang Yajun , Cavalet-Giorsa Emile , Troukhan Maxim , Kravchuk Maksym , Krattinger Simon G. 
Published: October 2023

AbstractWild wheat relatives have been explored in plant breeding to increase the genetic diversity of bread wheat, one of the most important food crops. Aegilops umbellulata is a diploid U genome-containing grass species that serves as a genetic reservoir for wheat improvement. In this study, we report the construction of a chromosome-scale reference assembly of Ae. umbellulata accession TA1851 based on corrected PacBio HiFi reads and chromosome conformation capture. The total assembly size was 4.25 Gb with a contig N50 of 17.7 Mb. In total, 36,268 gene models were predicted. We benchmarked the performance of hifiasm and LJA, two of the most widely used assemblers using standard and corrected HiFi reads, revealing a positive effect of corrected input reads. Comparative genome analysis confirmed substantial chromosome rearrangements in Ae. umbellulata compared to bread wheat. In summary, the Ae. umbellulata assembly provides a resource for comparative genomics in Triticeae and for the discovery of agriculturally important genes.
Pair barracuda swarm optimization algorithm: a natural-inspired metaheuristic method for high dimensional optimization problems
Authors: Guo Jia , Zhou Guoyuan , Yan Ke , Sato Yuji , Di Yi 
Published: October 2023

AbstractHigh-dimensional optimization presents a novel challenge within the realm of intelligent computing, necessitating innovative approaches. When tackling high-dimensional spaces, traditional evolutionary tools often encounter pitfalls, including dimensional catastrophes and a propensity to become trapped in local optima, ultimately compromising result accuracy. To address this issue, we introduce the Pair Barracuda Swarm Optimization (PBSO) algorithm in this paper. PBSO employs a unique strategy for constructing barracuda pairs, effectively mitigating the challenges posed by high dimensionality. Furthermore, we enhance global search capabilities by incorporating a support barracuda alongside the leading barracuda pair. To assess the algorithm’s performance, we conduct experiments utilizing the CEC2017 standard function and compare PBSO against five state-of-the-art natural-inspired optimizers in the control group. Across 29 test functions, PBSO consistently secures top rankings with 9 first-place, 13 second-place, 5 third-place, 1 fourth-place, and 1 fifth-place finishes, yielding an average rank of 2.0345. These empirical findings affirm that PBSO stands as the superior choice among all test algorithms, offering a dependable solution for high-dimensional optimization challenges.
KDM5 family of demethylases promotes CD44-mediated chemoresistance in pancreatic adenocarcinomas
Authors: Wang Dan , Zhang Yingjun , Liao Zhouning , Ge Heming , Güngör Cenap , Li Yuqiang 
Published: October 2023

AbstractA growing body of evidence suggests that the histone demethylase-lysine demethylase 5 (KDM5) family is associated with drug resistance in cancer cells. However, it is still not clear whether KDM5 family members promote chemotherapy resistance in pancreatic ductal adenocarcinomas (PDAC). Comprehensive bioinformatics analysis was performed to investigate the prognostic value, and functional mechanisms of KDM5 family members in PDAC. The effects of KDM5 family members on drug resistance in PDAC cells and the relationship with CD44, as a stem cell marker, were explored by gene knockout and overexpression strategies. Finally, our findings were validated by functional experiments such as cell viability, colony formation and invasion assays. We found that the expression of KDM5A/C was significantly higher in gemcitabine-resistant cells than in sensitive cells, consistent with the analysis of the GSCALite database. The knockdown of KDM5A/C in PDAC cells resulted in diminished drug resistance, less cell colonies and reduced invasiveness, while KDM5A/C overexpression showed the opposite effect. Of note, the expression of KDM5A/C changed accordingly with the knockdown of CD44. In addition, members of the KDM5 family function in a variety of oncogenic pathways, including PI3K/AKT and Epithelial-Mesenchymal Transition. In conclusion, KDM5 family members play an important role in drug resistance and may serve as new biomarkers or potential therapeutic targets in PDAC patients.
Real-time driver monitoring system with facial landmark-based eye closure detection and head pose recognition
Authors: Kim Dohun , Park Hyukjin , Kim Tonghyun , Kim Wonjong , Paik Joonki 
Published: October 2023

AbstractThis paper introduces a real-time Driver Monitoring System (DMS) designed to monitor driver behavior while driving, employing facial landmark estimation-based behavior recognition. The system utilizes an infrared (IR) camera to capture and analyze video data. Through facial landmark estimation, crucial information about the driver’s head posture and eye area is extracted from the detected facial region, obtained via face detection. The proposed method consists of two distinct modules, each focused on recognizing specific behaviors. The first module employs head pose analysis to detect instances of inattention. By monitoring the driver’s head movements along the horizontal and vertical axes, this module assesses the driver’s attention level. The second module implements an eye-closure recognition filter to identify instances of drowsiness. Depending on the continuity of eye closures, the system categorizes them as either occasional drowsiness or sustained drowsiness. The advantages of the proposed method lie in its efficiency and real-time capabilities, as it solely relies on IR camera video for computation and analysis. To assess its performance, the system underwent evaluation using IR-Datasets, demonstrating its effectiveness in monitoring and recognizing driver behavior accurately. The presented real-time Driver Monitoring System with facial landmark-based behavior recognition offers a practical and robust approach to enhance driver safety and alertness during their journeys.
SLC7A11, a potential immunotherapeutic target in lung adenocarcinoma
Authors: Shan Qingqing , Zhang Chi , Li Yangke , Li Qunying , Zhang Yifan , Li Xue , Shi Junqing , Hu Fengying 
Published: October 2023

AbstractSLC7A11 has significant translational value in cancer treatment. However, there are few studies on whether SLC7A11 affects the immune status of lung adenocarcinoma (LUAD). Information on SLC7A11 expression and its impact on prognosis was obtained from the cancer genome atlas and gene expression omnibus databases. The differentially expressed genes (DEGs) were analysed by GO and KEGG. GSEA enrichment analysis was performed in the SLC7A11-high and SLC7A11-low groups. The relationship between SLC7A11 and tumour immunity, immune checkpoints, and immune cell infiltration was studied using R language. We analysed the correlation between SLC7A11 and chemotactic factors (CFs) and chemokine receptors using the TISIDB database. SLC7A11 is overexpressed in many tumours, including LUAD. The 5-year overall survival of patients in the SLC7A11-high group was lower than in the SLC7A11-low group. KEGG analysis found that the DEGs were enriched in ferroptosis signaling pathways. GSEA analysis found that the survival-related signaling pathways were enriched in the SLC7A11-low group. The SLC7A11-low group had higher immune scores and immune checkpoint expression. SLC7A11 was negatively correlated with many immune cells (CD8+ T cells, immature dendritic cells), CFs, chemokine receptors (such as CCL17/19/22/23, CXCL9/10/11/14, CCR4/6, CX3CR1, CXCR3) and MHCs (major histocompatibility complex). SLC7A11 may regulate tumour immunity and could be a potential therapeutic target for LUAD.
Comparative analysis of batch correction methods for FDG PET/CT using metabolic radiogenomic data of lung cancer patients
Authors: Lee Hyunjong , Seo Sujin , Won Sungho , Park Woong-Yang , Choi Joon Young , Lee Kyung-Han , Lee Se-Hoon , Moon Seung Hwan 
Published: October 2023

AbstractIn radiomics research, the issue of different instruments being used is significant. In this study, we compared three correction methods to reduce the batch effects in radiogenomic data from fluorodeoxyglucose (FDG) PET/CT images of lung cancer patients. Texture features of the FDG PET/CT images and genomic data were retrospectively obtained. The features were corrected with different methods: phantom correction, ComBat method, and Limma method. Batch effects were estimated using three analytic tools: principal component analysis (PCA), the k-nearest neighbor batch effect test (kBET), and the silhouette score. Finally, the associations of features and gene mutations were compared between each correction method. Although the kBET rejection rate and silhouette score were lower in the phantom-corrected data than in the uncorrected data, a PCA plot showed a similar variance. ComBat and Limma methods provided correction with low batch effects, and there was no significant difference in the results of the two methods. In ComBat- and Limma-corrected data, more texture features exhibited a significant association with the TP53 mutation than in those in the phantom-corrected data. This study suggests that correction with ComBat or Limma methods can be more effective or equally as effective as the phantom method in reducing batch effects.
Augmentation strategies for an imbalanced learning problem on a novel COVID-19 severity dataset
Authors: Schaudt Daniel , von Schwerin Reinhold , Hafner Alexander , Riedel Pascal , Reichert Manfred , von Schwerin Marianne , Beer Meinrad , Kloth Christopher 
Published: October 2023

AbstractSince the beginning of the COVID-19 pandemic, many different machine learning models have been developed to detect and verify COVID-19 pneumonia based on chest X-ray images. Although promising, binary models have only limited implications for medical treatment, whereas the prediction of disease severity suggests more suitable and specific treatment options. In this study, we publish severity scores for the 2358 COVID-19 positive images in the COVIDx8B dataset, creating one of the largest collections of publicly available COVID-19 severity data. Furthermore, we train and evaluate deep learning models on the newly created dataset to provide a first benchmark for the severity classification task. One of the main challenges of this dataset is the skewed class distribution, resulting in undesirable model performance for the most severe cases. We therefore propose and examine different augmentation strategies, specifically targeting majority and minority classes. Our augmentation strategies show significant improvements in precision and recall values for the rare and most severe cases. While the models might not yet fulfill medical requirements, they serve as an appropriate starting point for further research with the proposed dataset to optimize clinical resource allocation and treatment.
Age and severity-dependent gut microbiota alterations in Tunisian children with autism spectrum disorder
Authors: Chamtouri Mariem , Gaddour Naoufel , Merghni Abderrahmen , Mastouri Maha , Arboleya Silvia , de los Reyes-Gavilán Clara G. 
Published: October 2023

AbstractAlterations in gut microbiota and short chain fatty acids (SCFA) have been reported in autism spectrum disorder (ASD). We analysed the gut microbiota and fecal SCFA in Tunisian autistic children from 4 to 10 years, and results were compared to those obtained from a group of siblings (SIB) and children from the general population (GP). ASD patients presented different gut microbiota profiles compared to SIB and GP, with differences in the levels ofBifidobacteriumandCollinsellaoccurring in younger children (4–7 years) and that tend to be attenuated at older ages (8–10 years). The lower abundance ofBifidobacteriumis the key feature of the microbiota composition associated with severe autism. ASD patients presented significantly higher levels of propionic and valeric acids than GP at 4–7 years, but these differences disappeared at 8–10 years. To the best of our knowledge, this is the first study on the gut microbiota profile of Tunisian autistic children using a metataxonomic approach. This exploratory study reveals more pronounced gut microbiota alterations at early than at advanced ages in ASD. Although we did not account for multiple testing, our findings suggest that early interventions might mitigate gut disorders and cognitive and neurodevelopment impairment associated to ASD.