bluuebunny/crossref_metadata_2025_split huggingface dataset:
Thermodynamic behavior of correlated electron-hole fluids in van der Waals heterostructures
Authors: Qi Ruishi , Joe Andrew Y. , Zhang Zuocheng , Zeng Yongxin , Zheng Tiancheng , Feng Qixin , Xie Jingxu , Regan Emma , Lu Zheyu , Taniguchi Takashi , Watanabe Kenji , Tongay Sefaattin , Crommie Michael F. , MacDonald Allan H. , Wang Feng 
Published: December 2023

AbstractCoupled two-dimensional electron-hole bilayers provide a unique platform to study strongly correlated Bose-Fermi mixtures in condensed matter. Electrons and holes in spatially separated layers can bind to form interlayer excitons, composite Bosons expected to support high-temperature exciton condensates. The interlayer excitons can also interact strongly with excess charge carriers when electron and hole densities are unequal. Here, we use optical spectroscopy to quantitatively probe the local thermodynamic properties of strongly correlated electron-hole fluids in MoSe2/hBN/WSe2 heterostructures. We observe a discontinuity in the electron and hole chemical potentials at matched electron and hole densities, a definitive signature of an excitonic insulator ground state. The excitonic insulator is stable up to a Mott density of ~0.8 × 1012 cm−2 and has a thermal ionization temperature of ~70 K. The density dependence of the electron, hole, and exciton chemical potentials reveals strong correlation effects across the phase diagram. Compared with a non-interacting uniform charge distribution, the correlation effects lead to significant attractive exciton-exciton and exciton-charge interactions in the electron-hole fluid. Our work highlights the unique quantum behavior that can emerge in strongly correlated electron-hole systems.
A resilient battery electric bus transit system configuration
Authors: Foda Ahmed , Mohamed Moataz , Farag Hany , El-Saadany Ehab 
Published: December 2023

AbstractElectric mobility is fundamental to combat climate change and attaining the United Nations Sustainable Development Goals (SDG-11). However, electric mobility necessitates a seamless integration between power and transportation systems, as the resiliency of both systems is becoming far more interdependent. Here, we focus on disruption to Battery Electric Bus (BEB) transit system charging infrastructure and offer a resilient BEB transit system planning model. The proposed model optimizes the BEB system costs while ensuring the system’s robustness against simultaneous charging station failures. In our case study, a single charging station failure would lead to up to 34.03% service reduction, and two simultaneous failures would reduce the service by up to 58.18%. Our proposed two-stage robust model addresses this issue with a relatively small added cost (3.26% and 8.12% higher than the base model). This cost enables uninterrupted BEB system operation during disruption, ensuring personal mobility, social interaction, and economic productivity.
Quantum transport of high-dimensional spatial information with a nonlinear detector
Authors: Sephton Bereneice , Vallés Adam , Nape Isaac , Cox Mitchell A. , Steinlechner Fabian , Konrad Thomas , Torres Juan P. , Roux Filippus S. , Forbes Andrew 
Published: December 2023

AbstractInformation exchange between two distant parties, where information is shared without physically transporting it, is a crucial resource in future quantum networks. Doing so with high-dimensional states offers the promise of higher information capacity and improved resilience to noise, but progress to date has been limited. Here we demonstrate how a nonlinear parametric process allows for arbitrary high-dimensional state projections in the spatial degree of freedom, where a strong coherent field enhances the probability of the process. This allows us to experimentally realise quantum transport of high-dimensional spatial information facilitated by a quantum channel with a single entangled pair and a nonlinear spatial mode detector. Using sum frequency generation we upconvert one of the photons from an entangled pair resulting in high-dimensional spatial information transported to the other. We realise a d = 15 quantum channel for arbitrary photonic spatial modes which we demonstrate by faithfully transferring information encoded into orbital angular momentum, Hermite-Gaussian and arbitrary spatial mode superpositions, without requiring knowledge of the state to be sent. Our demonstration merges the nascent fields of nonlinear control of structured light with quantum processes, offering a new approach to harnessing high-dimensional quantum states, and may be extended to other degrees of freedom too.
Electroreductive hydroxy fluorosulfonylation of alkenes
Authors: Feng Qingyuan , He Tianyu , Qian Shencheng , Xu Peng , Liao Saihu , Huang Shenlin 
Published: December 2023

AbstractAn electroreductive strategy for radical hydroxyl fluorosulfonylation of alkenes with sulfuryl chlorofluoride and molecular oxygen from air is described. This mild protocol displays excellent functional group compatibility, broad scope, and good scalability, providing convenient access to diverse β-hydroxy sulfonyl fluorides. These β-hydroxy sulfonyl fluoride products can be further converted to valuable aliphatic sulfonyl fluorides, β-keto sulfonyl fluorides, and β-alkenyl sulfonyl fluorides. Further, some of these products showed excellent inhibitory activity against Botrytis cinerea or Bursaphelenchus xylophilus, which could be useful for potent agrochemical discovery. Preliminary mechanistic studies indicate that this transformation is achieved through rapid O2 interception by the alkyl radical and subsequent reduction of the peroxy radical, which outcompete other side reactions such as chlorine atom transfer, hydrogen atom transfer, and Russell fragmentation.
Unraveling the intricate connection between dietary factors and the success in long-term space missions
Authors: Pittia Paola , Blanc Stéphane , Heer Martina 
Published: December 2023

AbstractIn recent decades of spaceflight, inadequate caloric intake has posed significant nutritional challenges, contributing to muscle degradation, weakened immune and cardiovascular systems during and after space missions. This challenge becomes more acute on longer exploration missions, where transporting all food for the entire mission becomes a logistical challenge. This places immense pressure on the food system, requiring energy-dense, varied, stable, and palatable food options. Prolonged storage can lead to nutrient degradation, reducing their bioavailability and bioaccessibility to astronauts. Research is essential not only to improve the quality and stability of space food but also to enhance nutrient bioavailability, thereby reducing weight and volume of food. Muscle and bone loss represent major risks during extended spaceflight, prompting extensive efforts to find exercise countermeasures. However, increased exercise requires additional energy intake, and finding the optimal balance between energy needs and the preservation of muscle and bone mass is challenging. Currently, there is no reliable way to measure total energy expenditure and activity-related energy expenditures in real-time. Systematic research is necessary to develop onboard technology for accurate energy expenditure and body composition monitoring. This research should aim to establish an optimal exercise regimen that balances energy requirements while maintaining astronaut strength and minimizing food transport. In summary, this overview outlines key actions needed for future exploration missions to maintain body mass and physical strength of space travellers. It addresses the requirements for food processing and preservation, considerations for space food formulation and production, and the essential measures to be implemented.
Explainable machine learning identifies multi-omics signatures of muscle response to spaceflight in mice
Authors: Li Kevin , Desai Riya , Scott Ryan T. , Steele Joel Ricky , Machado Meera , Demharter Samuel , Hoarfrost Adrienne , Braun Jessica L. , Fajardo Val A. , Sanders Lauren M. , Costes Sylvain V. 
Published: December 2023

AbstractThe adverse effects of microgravity exposure on mammalian physiology during spaceflight necessitate a deep understanding of the underlying mechanisms to develop effective countermeasures. One such concern is muscle atrophy, which is partly attributed to the dysregulation of calcium levels due to abnormalities in SERCA pump functioning. To identify potential biomarkers for this condition, multi-omics data and physiological data available on the NASA Open Science Data Repository (osdr.nasa.gov) were used, and machine learning methods were employed. Specifically, we used multi-omics (transcriptomic, proteomic, and DNA methylation) data and calcium reuptake data collected from C57BL/6 J mouse soleus and tibialis anterior tissues during several 30+ day-long missions on the international space station. The QLattice symbolic regression algorithm was introduced to generate highly explainable models that predict either experimental conditions or calcium reuptake levels based on multi-omics features. The list of candidate models established by QLattice was used to identify key features contributing to the predictive capability of these models, with Acyp1 and Rps7 proteins found to be the most predictive biomarkers related to the resilience of the tibialis anterior muscle in space. These findings could serve as targets for future interventions aiming to reduce the extent of muscle atrophy during space travel.
Mendelian randomization reveals association between retinal thickness and non-motor symptoms of Parkinson’s disease
Authors: Zhou Hang , Shen Bibiao , Huang Zifeng , Zhu Shuzhen , Yang Wanlin , Xie Fen , Luo Yuqi , Yuan Feilan , Zhu Zhaohua , Deng Chao , Zheng Wenhua , Yang Chengwu , Lin Chin-Hsien , Xiao Bin , Tan Eng-King , Wang Qing 
Published: December 2023

AbstractRetinal thickness is related to Parkinson’s disease (PD), but its association with the severity of PD is still unclear. We conducted a Mendelian randomized (MR) study to explore the association between retinal thickness and PD. For the two-sample MR analysis, the summary statistics obtained from genome-wide association studies on the thickness of Retinal nerve fiber layer (RNFL) and ganglion cell inner plexiform layer (GCIPL) were employed as exposure, while the summary statistics associated with PD were used as the outcome. The primary approach utilized was inverse variance weighted. To correct for multiple testing, the false discovery rate (FDR) was employed. For sensitivity analysis, an array of robust MR methods was utilized. We found genetically predicted significant association between reduced RNFL thickness and a reduced risk of constipation in PD (odds ratio [OR] = 0.854, 95% confidence interval [CI] (0.782, 0.933), P < 0.001, FDR-corrected P = 0.018). Genetically predicted reduced RNFL thickness was associated with a reduced Unified Parkinson’s Disease Rating Scale total score (β = −0.042, 95% CI (−0.079, 0.005), P = 0.025), and reduced GCIPL thickness was associated with a lower risk of constipation (OR = 0.901, 95% CI (0.821, 0.988), P = 0.027) but a higher risk of depression (OR = 1.103, 95% CI (1.016, 1.198), P = 0.020), insomnia (OR = 1.090, 95% CI (1.013, 1.172), P = 0.021), and rapid eye movement sleep behaviour disorder (RBD) (OR = 1.198, 95% CI (1.061, 1.352), P = 0.003). In conclusion, we identify an association between retinal thickness and non-motor symptoms (constipation, depression, insomnia and RBD) in PD, highlighting the potential of retinal thickness as a biomarker for PD nonmotor symptoms.
A vertebrate-wide catalogue of T1R receptors reveals diversity in taste perception
Authors: Nishihara Hidenori , Toda Yasuka , Kuramoto Tae , Kamohara Kota , Goto Azusa , Hoshino Kyoko , Okada Shinji , Kuraku Shigehiro , Okabe Masataka , Ishimaru Yoshiro 
Published: December 2023

AbstractTaste is a vital chemical sense for feeding behaviour. In mammals, the umami and sweet taste receptors comprise three members of the taste receptor type 1 (T1R/TAS1R) family: T1R1, T1R2 and T1R3. Because their functional homologues exist in teleosts, only three TAS1R genes generated by gene duplication are believed to have been inherited from the common ancestor of bony vertebrates. Here, we report five previously uncharacterized TAS1R members in vertebrates, TAS1R4, TAS1R5, TAS1R6, TAS1R7 and TAS1R8, based on genome-wide survey of diverse taxa. We show that mammalian and teleost fish TAS1R2 and TAS1R3 genes are paralogues. Our phylogenetic analysis suggests that the bony vertebrate ancestor had nine TAS1Rs resulting from multiple gene duplications. Some TAS1Rs were lost independently in descendent lineages resulting in retention of only three TAS1Rs in mammals and teleosts. Combining functional assays and expression analysis of non-teleost fishes we show that the novel T1Rs form heterodimers in taste-receptor cells and recognize a broad range of ligands such as essential amino acids, including branched-chain amino acids, which have not been previously considered as T1R ligands. This study reveals diversity of taste sensations in both modern vertebrates and their ancestors, which might have enabled vertebrates to adapt to diverse habitats on Earth.
A comprehensive multimodal dataset for contactless lip reading and acoustic analysis
Authors: Ge Yao , Tang Chong , Li Haobo , Chen Zikang , Wang Jingyan , Li Wenda , Cooper Jonathan , Chetty Kevin , Faccio Daniele , Imran Muhammad , Abbasi Qammer H. 
Published: December 2023

AbstractSmall-scale motion detection using non-invasive remote sensing techniques has recently garnered significant interest in the field of speech recognition. Our dataset paper aims to facilitate the enhancement and restoration of speech information from diverse data sources for speakers. In this paper, we introduce a novel multimodal dataset based on Radio Frequency, visual, text, audio, laser and lip landmark information, also called RVTALL. Specifically, the dataset consists of 7.5 GHz Channel Impulse Response (CIR) data from ultra-wideband (UWB) radars, 77 GHz frequency modulated continuous wave (FMCW) data from millimeter wave (mmWave) radar, visual and audio information, lip landmarks and laser data, offering a unique multimodal approach to speech recognition research. Meanwhile, a depth camera is adopted to record the landmarks of the subject’s lip and voice. Approximately 400 minutes of annotated speech profiles are provided, which are collected from 20 participants speaking 5 vowels, 15 words, and 16 sentences. The dataset has been validated and has potential for the investigation of lip reading and multimodal speech recognition.
Chromatic dispersion and thermal coefficients of hygroscopic liquids: 5 glycols and glycerol
Authors: Jakubczyk Daniel , Derkachov Gennadiy , Nyandey Kwasi , Alikhanzadeh-Arani Sima , Derkachova Anastasiya 
Published: December 2023

AbstractChromatic dispersion and thermal coefficients of 6 hygroscopic liquids: ethylene glycol, diethylene glycol, triethylene glycol, tetraethylene glycol, propylene glycol (propane-1, 2-diol), and glycerol were measured in the range from 390 to 1070 nm for temperatures from 1 to 45 °C. A modified Abbe refractometer was utilised. Special care was taken to avoid contaminating the liquids under the test with water and solid particles. The measurement uncertainties were analysed. It was noticed that (in the given range and within the available measurement accuracy) the dependence of the refractive indices on the wavelength and temperature could be considered independently. Thus, thermal coefficients were found for each wavelength used, and their weak dependence on the wavelength was recognised. Then the Sellmeier equation was fitted to the experimental results for each temperature.
Classifying stages in the gonotrophic cycle of mosquitoes from images using computer vision techniques
Authors: Azam Farhat Binte , Carney Ryan M. , Kariev Sherzod , Nallan Krishnamoorthy , Subramanian Muthukumaravel , Sampath Gopalakrishnan , Kumar Ashwani , Chellappan Sriram 
Published: December 2023

AbstractThe ability to distinguish between the abdominal conditions of adult female mosquitoes has important utility for the surveillance and control of mosquito-borne diseases. However, doing so requires entomological training and time-consuming manual effort. Here, we design computer vision techniques to determine stages in the gonotrophic cycle of female mosquitoes from images. Our dataset was collected from 139 adult female mosquitoes across three medically important species—Aedes aegypti, Anopheles stephensi, and Culex quinquefasciatus—and all four gonotrophic stages of the cycle (unfed, fully fed, semi-gravid, and gravid). From these mosquitoes and stages, a total of 1959 images were captured on a plain background via multiple smartphones. Subsequently, we trained four distinct AI model architectures (ResNet50, MobileNetV2, EfficientNet-B0, and ConvNeXtTiny), validated them using unseen data, and compared their overall classification accuracies. Additionally, we analyzed t-SNE plots to visualize the formation of decision boundaries in a lower-dimensional space. Notably, ResNet50 and EfficientNet-B0 demonstrated outstanding performance with an overall accuracy of 97.44% and 93.59%, respectively. EfficientNet-B0 demonstrated the best overall performance considering computational efficiency, model size, training speed, and t-SNE decision boundaries. We also assessed the explainability of this EfficientNet-B0 model, by implementing Grad-CAMs—a technique that highlights pixels in an image that were prioritized for classification. We observed that the highest weight was for those pixels representing the mosquito abdomen, demonstrating that our AI model has indeed learned correctly. Our work has significant practical impact. First, image datasets for gonotrophic stages of mosquitoes are not yet available. Second, our algorithms can be integrated with existing citizen science platforms that enable the public to record and upload biological observations. With such integration, our algorithms will enable the public to contribute to mosquito surveillance and gonotrophic stage identification. Finally, we are aware of work today that uses computer vision techniques for automated mosquito species identification, and our algorithms in this paper can augment these efforts by enabling the automated detection of gonotrophic stages of mosquitoes as well.
Analyzing aberrant DNA methylation in colorectal cancer uncovered intangible heterogeneity of gene effects in the survival time of patients
Authors: Hajebi Khaniki Saeedeh , Shokoohi Farhad , Esmaily Habibollah , Kerachian Mohammad Amin 
Published: December 2023

AbstractColorectal cancer (CRC) involves epigenetic alterations. Irregular gene-methylation alteration causes and advances CRC tumor growth. Detecting differentially methylated genes (DMGs) in CRC and patient survival time paves the way to early cancer detection and prognosis. However, CRC data including survival times are heterogeneous. Almost all studies tend to ignore the heterogeneity of DMG effects on survival. To this end, we utilized a sparse estimation method in the finite mixture of accelerated failure time (AFT) regression models to capture such heterogeneity. We analyzed a dataset of CRC and normal colon tissues and identified 3406 DMGs. Analysis of overlapped DMGs with several Gene Expression Omnibus datasets led to 917 hypo- and 654 hyper-methylated DMGs. CRC pathways were revealed via gene ontology enrichment. Hub genes were selected based on Protein–Protein-Interaction network including SEMA7A, GATA4, LHX2, SOST, and CTLA4, regulating the Wnt signaling pathway. The relationship between identified DMGs/hub genes and patient survival time uncovered a two-component mixture of AFT regression model. The genes NMNAT2, ZFP42, NPAS2, MYLK3, NUDT13, KIRREL3, and FKBP6 and hub genes SOST, NFATC1, and TLE4 were associated with survival time in the most aggressive form of the disease that can serve as potential diagnostic targets for early CRC detection.
Biosynthesis of JC-La2CoO4 magnetic nanoparticles explored in catalytic and SMMs properties
Authors: Satpute Nilesh , Ghosh Mithun Kumar , Kesharwani Aparna , Ghorai Tanmay Kumar 
Published: December 2023

AbstractWe have reported the synthesis of JC-La2CoO4 magnetic nanoparticles from Jatropha Curcas L. leaf extract in aqueous medium and potential application study in catalytic & Single Molecule Magnets (SMMs). Several techniques were used to investigate the structural, morphological, and elemental composition, particle size, optical properties, catalytic and magnetic properties by XRD, FTIR, SEM, EDAX, XPS, UV–visible and squid magnetic measurement. It was found that the crystallite sizes and grain sizes of JC-La2CoO4 NPs were 11.3 ± 1 and 24.1 ± 1 nm respectively and surface morphology of the nanoparticles looks spherical shape with good surface area. The band gap of JC-La2CoO4 was found to be 4.95 eV indicates good semiconductor in nature. XPS studies shows that La and Co present in + 3 and + 2 oxidation state respectively and suggest the composition formula is La2CoO4 with satisfied all the valency of metal ions. The photocatalytic efficiency of La2CoO4 shows good result against methylene blue (MB) compared to other dyes like MO, NO, RhB in presence of sunlight with rate constant 56.73 × 10–3 min-1 and completely degraded within 115 mints. The importance of JC-La2CoO4 has magnetic properties with antiferromagnetic coupling and SMMs properties with nature.
Higher dietary acid load is associated with an increased risk of metabolic syndrome
Authors: Seifi Najmeh , Rahimi Hamidreza , Koochakpoor Glareh , Zarei Amin , Assaran Darban Reza , Ferns Gordon A. , Ghayour-Mobarhan Majid 
Published: December 2023

AbstractThere have been inconsistent reports regarding the association between dietary acid load and Metabolic Syndrome (MetS). We aimed to investigate the association between dietary acid load and MetS in an Iranian adult population. In this cross-sectional study, 1945 participants aged 35–65 years were recruited from MASHAD cohort study. Dietary intakes were assessed using a 24-h dietary recall. Diet-based acidity was assessed as the net endogenous acid production (NEAP), potential renal acid load (PRAL), and dietary acid load (DAL). To define MetS, the International Diabetes Federation (IDF) criteria were used. Multivariable logistic regression models were applied to determine the association between diet-based acid load scores and MetS. Participants' mean age and BMI were 47.13 ± 7.78 years and 27.57 ± 4.48 kg/m2, respectively. Around 57% of the population was female. Overall, 31.9% had MetS. According to the full-adjusted model, there was a significant association between higher quartiles of PRAL, NEAP, and DAL and MetS (Q4 PRAL; OR (95%CI) 1.42(1.05–1.91), Q4 NEAP; OR (95%CI) 1.48(1.11–1.98), Q4 DAL; OR (95%CI) 1.44(1.05–1.91)). This study showed a significant positive association between different dietary acid load indicators (PRAL, NEAP, and DAL) and odds of MetS among Iranian adults.