bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reliable wafer-scale integration of two-dimensional materials and metal electrodes with van der Waals contacts
Authors: Zhang Xiaodong , Huang Chenxi , Li Zeyu , Fu Jun , Tian Jiaran , Ouyang Zhuping , Yang Yuliang , Shao Xiang , Han Yulei , Qiao Zhenhua , Zeng Hualing 
Published: May 2024

AbstractSince the first report on single-layer MoS2 based transistor, rapid progress has been achieved in two-dimensional (2D) material-based atomically thin electronics, providing an alternative approach to solve the bottleneck in silicon device miniaturization. In this scenario, reliable contact between the metal electrodes and the subnanometer-thick 2D materials becomes crucial in determining the device performance. Here, utilizing the quasi-van der Waals (vdW) epitaxy of metals on fluorophlogopite mica, we demonstrate an all-stacking method for the fabrication of 2D devices with high-quality vdW contacts by mechanically transferring pre-deposited metal electrodes. This technique is applicable for complex device integration with sizes up to the wafer scale and is also capable of tuning the electric characteristics of the interfacial junctions by transferring selective metals. Our results provide an efficient, scalable, and low-cost technique for 2D electronics, allowing high-density device integration as well as a handy tool for fundamental research in vdW materials.
The chromosome-level genomes of the herbal magnoliids Warburgia ugandensis and Saururus chinensis
Authors: Luo Liuming , Fang Dongming , Wang Fang , Lin Qiongqiong , Sahu Sunil Kumar , Song Yali , Kang Jingmin , Guang Xuanmin , Liu Min , Luo Shixiao , Hao Gang , Liu Huan , Guo Xing 
Published: May 2024

Warburgia ugandensis and Saururus chinensis are two of the most important medicinal plants in magnoliids and are widely utilized in traditional Kenya and Chinese medicine, respectively. The absence of higher-quality reference genomes has hindered research on the medicinal compound biosynthesis mechanisms of these plants. We report the chromosome-level genome assemblies of W. ugandensis and S. chinensis, and generated 1.13 Gb and 0.53 Gb genomes from 74 and 27 scaffolds, respectively, using BGI-DIPSEQ, Nanopore, and Hi-C sequencing. The scaffold N50 lengths were 82.97 Mb and 48.53 Mb, and the assemblies were anchored to 14 and 11 chromosomes of W. ugandensis and S. chinensis, respectively. In total, 24,739 and 20,561 genes were annotated, and 98.5% and 98% of the BUSCO genes were fully represented, respectively. The chromosome-level genomes of W. ugandensis and S. chinensis will be valuable resources for understanding the genetics of these medicinal plants, studying the evolution of magnoliids and angiosperms and conserving plant genetic resources.
Scrutinizing transport phenomena and recombination mechanisms in thin film Sb2S3 solar cells
Authors: Younsi Z. , Meddour F. , Bencherif H. , Hossain M. Khalid , Marasamy Latha , Sasikumar P. , Revathy M. S. , Ghotekar Suresh , Karim Mohammad R. , Ayyar Manikandan , Haldhar Rajesh , Rubel Mirza H. K. 
Published: May 2024

AbstractThe Schockley–Quisser (SQ) limit of 28.64% is distant from the Sb2S3 solar cells’ record power conversion efficiency (PCE), which is 8.00%. Such poor efficiency is mostly owing to substantial interface-induced recombination losses caused by defects at the interfaces and misaligned energy levels. The endeavor of this study is to investigate an efficient Sb2S3 solar cell structure via accurate analytical modeling. The proposed model considers different recombination mechanisms such as non-radiative recombination, Sb2S3/CdS interface recombination, Auger, SRH, tunneling-enhanced recombination, and their combined impact on solar cell performance. This model is verified against experimental work (Glass/ITO/CdS/Sb2S3/Au) where a good coincidence is achieved. Several parameters effects such as thickness, doping, electronic affinity, and bandgap are scrutinized. The effect of both bulk traps located in CdS and Sb2S3 on the electrical outputs of the solar cell is analyzed thoroughly. Besides, a deep insight into the effect of interfacial traps on solar cell figures of merits is gained through shedding light into their relation with carriers’ minority lifetime, diffusion length, and surface recombination velocity. Our research findings illuminate that the primary contributors to Sb2S3 degradation are interfacial traps and series resistance. Furthermore, achieving optimal band alignment by fine-tuning the electron affinity of CdS to create a Spike-like conformation is crucial for enhancing the immunity of the device versus the interfacial traps. In our study, the optimized solar cell configuration (Glass/ITO/CdS/Sb2S3/Au) demonstrates remarkable performance, including a high short-circuit current (JSC) of 47.9 mA/cm2, an open-circuit voltage (VOC) of 1.16 V, a fill factor (FF) of 54%, and a notable improvement in conversion efficiency by approximately 30% compared to conventional solar cells. Beyond its superior performance, the optimized Sb2S3 solar cell also exhibits enhanced reliability in mitigating interfacial traps at the CdS/Sb2S3 junction. This improved reliability can be attributed to our precise control of band alignment and the fine-tuning of influencing parameters.
Performance evaluation of different empirical models for reference evapotranspiration estimation over Udhagamandalm, The Nilgiris, India
Authors: Raja P. , Sona Fathima , Surendran U. , Srinivas C. V. , Kannan K. , Madhu M. , Mahesh P. , Annepu S. K. , Ahmed M. , Chandrasekar K. , Suguna A. R. , Kumar V. , Jagadesh M. 
Published: May 2024

AbstractEvapotranspiration (ETo) is an important component of the hydrological cycle and reliable estimates of ETo are essential for assessing crop water requirements and irrigation management. Direct measurement of evapotranspiration is both costly and involves complex and intricate procedures. Hence, empirical models are commonly utilized to estimate ETo using accessible meteorological data. Given that empirical methods operate on various assumptions, it is essential to assess their performance to pinpoint the most suitable methods for ETo calculation based on the availability of input data and the specific climatic conditions of a region. This study aims to evaluate different empirical methods of ETo in the tropical highland Udhagamandalam region of Tamil Nadu, India, utilizing sixty years of meteorological data from 1960–2020. In this study, 8 temperature-based and 10 radiation-based empirical models are evaluated against ETo estimates derived from pan evaporation observation and the FAO Penman–Monteith method (FAO-PM), respectively. Statistical error metrics indicate that both temperature and radiation-based models perform better for the Udhagamandalam region. However, radiation-based models performed better than the temperature based models. This is possibly due to the high humidity of the study region throughout the year. The results suggest that simple temperature and radiation-based models using minimum meteorological information are adequate to estimate ETo and thus find potential application in agricultural water practices, hydrological processes, and irrigation management.
Interdisciplinary approach to identify language markers for post-traumatic stress disorder using machine learning and deep learning
Authors: Quillivic Robin , Gayraud Frédérique , Auxéméry Yann , Vanni Laurent , Peschanski Denis , Eustache Francis , Dayan Jacques , Mesmoudi Salma 
Published: May 2024

AbstractPost-traumatic stress disorder (PTSD) lacks clear biomarkers in clinical practice. Language as a potential diagnostic biomarker for PTSD is investigated in this study. We analyze an original cohort of 148 individuals exposed to the November 13, 2015, terrorist attacks in Paris. The interviews, conducted 5–11 months after the event, include individuals from similar socioeconomic backgrounds exposed to the same incident, responding to identical questions and using uniform PTSD measures. Using this dataset to collect nuanced insights that might be clinically relevant, we propose a three-step interdisciplinary methodology that integrates expertise from psychiatry, linguistics, and the Natural Language Processing (NLP) community to examine the relationship between language and PTSD. The first step assesses a clinical psychiatrist's ability to diagnose PTSD using interview transcription alone. The second step uses statistical analysis and machine learning models to create language features based on psycholinguistic hypotheses and evaluate their predictive strength. The third step is the application of a hypothesis-free deep learning approach to the classification of PTSD in our cohort. Results show that the clinical psychiatrist achieved a diagnosis of PTSD with an AUC of 0.72. This is comparable to a gold standard questionnaire (Area Under Curve (AUC) ≈ 0.80). The machine learning model achieved a diagnostic AUC of 0.69. The deep learning approach achieved an AUC of 0.64. An examination of model error informs our discussion. Importantly, the study controls for confounding factors, establishes associations between language and DSM-5 subsymptoms, and integrates automated methods with qualitative analysis. This study provides a direct and methodologically robust description of the relationship between PTSD and language. Our work lays the groundwork for advancing early and accurate diagnosis and using linguistic markers to assess the effectiveness of pharmacological treatments and psychotherapies.
Advancing state estimation for lithium-ion batteries with hysteresis through systematic extended Kalman filter tuning
Authors: Knox J. , Blyth M. , Hales A. 
Published: May 2024

AbstractKnowledge of remaining battery charge is fundamental to electric vehicle deployment. Accurate measurements of state-of-charge (SOC) cannot be obtained directly and estimation methods must be used instead. This requires both a good model of a battery and a well-designed state estimator. Here, hysteretic reduced-order battery models and adaptive extended Kalman filter estimators are shown to be highly effective, accurate predictors of SOC. A battery model parameterisation framework is proposed, which enhances standardised methods to capture hysteresis effects. The hysteretic model is parameterised for three independent NMC811 lithium-ion cells and is shown to reduce voltage RMS error by 50% across 18 h automotive drive-cycles. Parameterised models are used alongside an extended Kalman filter, which demonstrates the value of adaptive filter parameterisation schemes. When used alongside an extended Kalman filter, adaptive covariance matrices yield highly accurate SOC estimates, reducing SOC estimation error by 85%, compared to the industry standard battery model.
Biological hypoxia in pre-transplant human pancreatic islets induces transplant failure in diabetic mice
Authors: Kato Hiroyuki , Salgado Mayra , Mendez Daniel , Gonzalez Nelson , Rawson Jeffrey , Ligot Doreen , Balandran Bennie , Orr Chris , Quijano Janine C. , Omori Keiko , Qi Meirigeng , Al-Abdullah Ismail H. , Mullen Yoko , Ku Hsun Teresa , Kandeel Fouad , Komatsu Hirotake 
Published: May 2024

AbstractEvaluating the quality of isolated human islets before transplantation is crucial for predicting the success in treating Type 1 diabetes. The current gold standard involves time-intensive in vivo transplantation into diabetic immunodeficient mice. Given the susceptibility of isolated islets to hypoxia, we hypothesized that hypoxia present in islets before transplantation could indicate compromised islet quality, potentially leading to unfavorable outcomes. To test this hypothesis, we analyzed expression of 39 hypoxia-related genes in human islets from 85 deceased donors. We correlated gene expression profiles with transplantation outcomes in 327 diabetic mice, each receiving 1200 islet equivalents grafted into the kidney capsule. Transplantation outcome was post-transplant glycemic control based on area under the curve of blood glucose over 4 weeks. In linear regression analysis, DDIT4 (R = 0.4971, P < 0.0001), SLC2A8 (R = 0.3531, P = 0.0009) and HK1 (R = 0.3444, P = 0.0012) had the highest correlation with transplantation outcome. A multiple regression model of 11 genes increased the correlation (R = 0.6117, P < 0.0001). We conclude that assessing pre-transplant hypoxia in human islets via gene expression analysis is a rapid, viable alternative to conventional in vivo assessments. This approach also underscores the importance of mitigating pre-transplant hypoxia in isolated islets to improve the success rate of islet transplantation.
Mutational landscape of HSP family on human breast cancer
Authors: Fernandez-Muñoz Juan Manuel , Guerrero-Gimenez Martin Eduardo , Ciocca Leonardo Andrés , Germanó María José , Zoppino Felipe Carlos Martin 
Published: May 2024

AbstractBreast cancer (BRCA) is a prevalent malignancy with the highest incidence among females. BRCA can be categorized into five intrinsic molecular subtypes (LumA, LumB, HER2, Basal, and Normal), each characterized by varying molecular and clinical features determined by the expression of intrinsic genes (PAM50). The Heat Shock Protein (HSP) family is composed of 95 genes evolutionary conservated, they have critical roles in proteostasis in both normal and cancerous processes. Many studies have linked HSP to the development and spread of cancer. They modulate the activity of multiple proteins expressed by oncogenes and anti-oncogenes through a range of interactions. In this study, we evaluate the mutational changes that HSP undergoes in BRCA mainly from the TCGA database. We observe that Copy Number Variations (CNV) are the more frequent events analyzed surpassing the occurrence of point mutations, indels, and translation start site mutations. The Basal subtype showcased the highest count of amplified CNV, including subtype-specific changes, whereas the Luminals tumors accumulated the greatest number of deletion CNV. Meanwhile, the HER2 subtype exhibited a comparatively lower frequency of CNV alterations when compared to the other subtypes. This study integrates CNV and expression data, finding associations between these two variables and the influence of CNV on the deregulation of HSP expression. To enhance the role of HSP as a risk predictor in BRCA, we succeeded in identifying CNV profiles as a prognostic marker. We included Artificial Intelligence to improve the clustering of patients, and we achieved a molecular CNV signature as a significant risk factor independent of known classic markers, including molecular subtypes PAM50. This research enhances the comprehension of HSP DNA alterations in BRCA and its relation with predicting the risk of affected individuals providing insights to develop guide personalized treatment strategies.
A strategy for differential abundance analysis of sparse microbiome data with group-wise structured zeros
Authors: Abegaz Fentaw , Abedini Davar , White Fred , Guerrieri Alessandra , Zancarini Anouk , Dong Lemeng , Westerhuis Johan A. , van Eeuwijk Fred , Bouwmeester Harro , Smilde Age K. 
Published: May 2024

AbstractComparing the abundance of microbial communities between different groups or obtained under different experimental conditions using count sequence data is a challenging task due to various issues such as inflated zero counts, overdispersion, and non-normality. Several methods and procedures based on counts, their transformation and compositionality have been proposed in the literature to detect differentially abundant species in datasets containing hundreds to thousands of microbial species. Despite efforts to address the large numbers of zeros present in microbiome datasets, even after careful data preprocessing, the performance of existing methods is impaired by the presence of inflated zero counts and group-wise structured zeros (i.e. all zero counts in a group). We propose and validate using extensive simulations an approach combining two differential abundance testing methods, namely DESeq2-ZINBWaVE and DESeq2, to address the issues of zero-inflation and group-wise structured zeros, respectively. This combined approach was subsequently successfully applied to two plant microbiome datasets that revealed a number of taxa as interesting candidates for further experimental validation.
Unveiling the underlying structure of awe in virtual reality and in autobiographical recall: an exploratory study
Authors: Chirico Alice , Borghesi Francesca , Yaden David B. , Pizzolante Marta , Sarcinella Eleonora Diletta , Cipresso Pietro , Gaggioli Andrea 
Published: May 2024

AbstractOver the last two decades, awe has attracted the attention of an increasing number of researchers. The use of virtual reality has been identified as one of the most effective techniques for eliciting awe, in addition to more personalized methods for inducing emotion, such as autobiographical recall. However, previous measures of awe were unable to uncover the hidden structure of this experience. Awe experience scale (AWE-S) has been validated as a comprehensive measure of contingent awe in English, providing new opportunities for analysis. In this two-phases study, we investigated whether the latent structure of the experience of awe evoked by the autobiographical recall technique (Study 1) overlapped with that induced by exposing participants to a validated virtual reality awe-eliciting training (Study 2). The original English AWE-S structure held both in autobiographical recall induction and virtual reality-based elicitation. Despite evidence of overlap between English and Italian structures, low correlations were found between Italian trait measures used to test the concurrent validity of the AWE-S in the Italian sample and AWE-S state dimensions. This study highlights cultural differences in awe experience, trait, and state variations, and provides new insights into the standardized induction of this emotion through simulated environments.
Spirituality is associated with immune parameters and disease activity in primary Sjögren’s syndrome: a cross-sectional study
Authors: Módis László V. , Aradi Zsófia , Horváth Ildikó Fanny , Pikó Péter , Papp Gábor , Osváth Mátyás , Szántó Antónia , Bugán Antal 
Published: May 2024

AbstractThe role of spirituality in health and disease is a complex and emerging area of research. Incorporating spirituality into the bio-psycho-social model of health and disease leading to the bio-psycho-social-spiritual model provides a more comprehensive framework. In this context, chronic disorders like primary Sjögren’s syndrome (pSS) are of interest due to their intricate interactions between biological, psychological, and spiritual factors. This study explored the relationship between spirituality, immune parameters, and disease activity in pSS patients. Data from 108 patients were analyzed, including self-assessed spirituality (answering to direct questions and completing the Spiritual Transcendence Scale), immunological parameters and disease activity scores. The findings revealed several associations. Individuals with spiritual attitudes or engaged in regular prayer/meditation showed lower serum levels of autoantibodies specific to pSS and lower disease activity scores. Spiritual engagement was also linked to decreased perceived skin and tracheal dryness, suggesting potential benefits for physical symptoms. These findings suggest that spirituality may play a significant role in modulating immune responses and disease activity in pSS patients. The study underscores the importance of considering spirituality as an integral part of the holistic approach to health and disease, further expanding the understanding of the interconnectedness of biological, psychological, and spiritual dimensions.
Reduced precipitation can induce ecosystem regime shifts in lakes by increasing internal nutrient recycling
Authors: Catalan Jordi , Monteoliva Agustín P. , Vega José Carlos , Domínguez Almudena , Negro Ana I. , Alonso Rocío , Garcés Blas Valero , Batalla Meritxell , García-Gómez Héctor , Leira Manel , Nuño Carlos , Pahissa José , Peg María , Pla-Rabés Sergi , Roblas Neftalí , Vargas José Luis , Toro Manuel 
Published: May 2024

AbstractEutrophication is a main threat to continental aquatic ecosystems. Prevention and amelioration actions have been taken under the assumption of a stable climate, which needs reconsideration. Here, we show that reduced precipitation can bring a lake ecosystem to a more productive regime even with a decline in nutrient external load. By analyzing time series of several decades in the largest lake of the Iberian Peninsula, we found autocorrelated changes in the variance of state variables (i.e., chlorophyll and oxygen) indicative of a transient situation towards a new ecosystem regime. Indeed, exceptional planktonic diatom blooms have occurred during the last few years, and the sediment record shows a shift in phytoplankton composition and an increase in nutrient retention. Reduced precipitation almost doubled the water residence time in the lake, enhancing the relevance of internal processes. This study demonstrates that ecological quality targets for aquatic ecosystems must be tailored to the changing climatic conditions for appropriate stewardship.
Comparison of diagnostic performance between Oncomine Dx target test and AmoyDx panel for detecting actionable mutations in lung cancer
Authors: Nagakubo Yuki , Hirotsu Yosuke , Yoshino Mona , Amemiya Kenji , Saito Ryota , Kakizaki Yumiko , Tsutsui Toshiharu , Miyashita Yoshihiro , Goto Taichiro , Omata Masao 
Published: May 2024

AbstractCompanion diagnostic (CDx) tests play important roles in identifying oncogenic driver genes and tailoring effective molecularly targeted therapies for lung cancer patients. In Japan, the Oncomine Dx target test (ODxTT) and the AmoyDx pan lung cancer PCR panel (AmoyDx) are prominent CDx tests and only one of these tests is covered by the domestic insurance system. However, these CDx tests cover different target regions and apply different technologies (ODxTT is amplicon-based next-generation sequencing and AmoyDx is multiplex PCR-based assay), which may lead to missing of actionable mutations affecting patient prognosis. Here, we performed a direct comparison analysis of 1059 genetic alterations of eight driver genes from 131 samples and evaluated the concordance between two CDx tests for detecting actionable variants and fusions. When excluding the eight uncovered variants (ODxTT: two variants, AmoyDx: six variants), the overall percent agreement was 97.6% (1026/1051) with 89.0% of overall positive percent agreement (89/100) and 98.5% of overall negative percent agreement (937/951). Of the 25 discordant genetic alterations, two were undetected despite being covered in the AmoyDx (one EGFR variant and one ROS1 fusion). Furthermore, there were potential false positives in the ODxTT (nine MET exon 14 skippings) and in the AmoyDx (five variants, six ROS1 and three RET fusions). These potential false positives in the AmoyDx likely due to non-specific amplification, which was validated by the unique molecular barcoding sequencing. The ODxTT missed two uncovered EGFR rare variants, which was visually confirmed in the raw sequencing data. Our study provides insights into real-world performance of CDx tests for lung cancer and ensures reliability to advance precision medicine.