bluuebunny/crossref_metadata_2025_split huggingface dataset:
Larval microbiota primes the Drosophila adult gustatory response
Authors: Montanari Martina , Manière Gérard , Berthelot-Grosjean Martine , Dusabyinema Yves , Gillet Benjamin , Grosjean Yaël , Kurz C. Léopold , Royet Julien 
Published: February 2024

AbstractThe survival of animals depends, among other things, on their ability to identify threats in their surrounding environment. Senses such as olfaction, vision and taste play an essential role in sampling their living environment, including microorganisms, some of which are potentially pathogenic. This study focuses on the mechanisms of detection of bacteria by the Drosophila gustatory system. We demonstrate that the peptidoglycan (PGN) that forms the cell wall of bacteria triggers an immediate feeding aversive response when detected by the gustatory system of adult flies. Although we identify ppk23+ and Gr66a+ gustatory neurons as necessary to transduce fly response to PGN, we demonstrate that they play very different roles in the process. Time-controlled functional inactivation and in vivo calcium imaging demonstrate that while ppk23+ neurons are required in the adult flies to directly transduce PGN signal, Gr66a+ neurons must be functional in larvae to allow future adults to become PGN sensitive. Furthermore, the ability of adult flies to respond to bacterial PGN is lost when they hatch from larvae reared under axenic conditions. Recolonization of germ-free larvae, but not adults, with a single bacterial species, Lactobacillus brevis, is sufficient to restore the ability of adults to respond to PGN. Our data demonstrate that the genetic and environmental characteristics of the larvae are essential to make the future adults competent to respond to certain sensory stimuli such as PGN.
Real-time tracking of coherent oscillations of electrons in a nanodevice by photo-assisted tunnelling
Authors: Luo Yang , Neubrech Frank , Martin-Jimenez Alberto , Liu Na , Kern Klaus , Garg Manish 
Published: February 2024

AbstractCoherent collective oscillations of electrons excited in metallic nanostructures (localized surface plasmons) can confine incident light to atomic scales and enable strong light-matter interactions, which depend nonlinearly on the local field. Direct sampling of such collective electron oscillations in real-time is crucial to performing petahertz scale optical modulation, control, and readout in a quantum nanodevice. Here, we demonstrate real-time tracking of collective electron oscillations in an Au bowtie nanoantenna, by recording photo-assisted tunnelling currents generated by such oscillations in this quantum nanodevice. The collective electron oscillations show a noninstantaneous response to the driving laser fields with a T2 decay time of nearly 8 femtoseconds. The contributions of linear and nonlinear electron oscillations in the generated tunnelling currents were precisely determined. A phase control of electron oscillations in the nanodevice is illustrated. Functioning in ambient conditions, the excitation, phase control, and read-out of coherent electron oscillations pave the way toward on-chip light-wave electronics in quantum nanodevices.
Spin-EPR-pair separation by conveyor-mode single electron shuttling in Si/SiGe
Authors: Struck Tom , Volmer Mats , Visser Lino , Offermann Tobias , Xue Ran , Tu Jhih-Sian , Trellenkamp Stefan , Cywiński Łukasz , Bluhm Hendrik , Schreiber Lars R. 
Published: February 2024

AbstractLong-ranged coherent qubit coupling is a missing function block for scaling up spin qubit based quantum computing solutions. Spin-coherent conveyor-mode electron-shuttling could enable spin quantum-chips with scalable and sparse qubit-architecture. Its key feature is the operation by only few easily tuneable input terminals and compatibility with industrial gate-fabrication. Single electron shuttling in conveyor-mode in a 420 nm long quantum bus has been demonstrated previously. Here we investigate the spin coherence during conveyor-mode shuttling by separation and rejoining an Einstein-Podolsky-Rosen (EPR) spin-pair. Compared to previous work we boost the shuttle velocity by a factor of 10000. We observe a rising spin-qubit dephasing time with the longer shuttle distances due to motional narrowing and estimate the spin-shuttle infidelity due to dephasing to be 0.7% for a total shuttle distance of nominal 560 nm. Shuttling several loops up to an accumulated distance of 3.36 μm, spin-entanglement of the EPR pair is still detectable, giving good perspective for our approach of a shuttle-based scalable quantum computing architecture in silicon.
In-situ formatting donor-acceptor polymer with giant dipole moment and ultrafast exciton separation
Authors: Cheng Chang , Yu Jiaguo , Xu Difa , Wang Lei , Liang Guijie , Zhang Liuyang , Jaroniec Mietek 
Published: February 2024

AbstractDonor-acceptor semiconducting polymers present countless opportunities for application in photocatalysis. Previous studies have showcased their advantages through direct bottom-up methods. Unfortunately, these approaches often involve harsh reaction conditions, overlooking the impact of uncontrolled polymerization degrees on photocatalysis. Besides, the mechanism behind the separation of electron-hole pairs (excitons) in donor-acceptor polymers remains elusive. This study presents a post-synthetic method involving the light-induced transformation of the building blocks of hyper-cross-linked polymers from donor-carbon-donor to donor-carbon-acceptor states, resulting in a polymer with a substantial intramolecular dipole moment. Thus, excitons are efficiently separated in the transformed polymer. The utility of this strategy is exemplified by the enhanced photocatalytic hydrogen peroxide synthesis. Encouragingly, our observations reveal the formation of intramolecular charge transfer states using time-resolved techniques, confirming transient exciton behavior involving separation and relaxation. This light-induced method not only guides the development of highly efficient donor-acceptor polymer photocatalysts but also applies to various fields, including organic solar cells, light-emitting diodes, and sensors.
Coordination-induced O-H/N-H bond weakening by a redox non-innocent, aluminum-containing radical
Authors: Sinhababu Soumen , Singh Roushan Prakash , Radzhabov Maxim R. , Kumawat Jugal , Ess Daniel H. , Mankad Neal P. 
Published: February 2024

AbstractSeveral renewable energy schemes aim to use the chemical bonds in abundant molecules like water and ammonia as energy reservoirs. Because the O-H and N-H bonds are quite strong (>100 kcal/mol), it is necessary to identify substances that dramatically weaken these bonds to facilitate proton-coupled electron transfer processes required for energy conversion. Usually this is accomplished through coordination-induced bond weakening by redox-active metals. However, coordination-induced bond weakening is difficult with earth’s most abundant metal, aluminum, because of its redox inertness under mild conditions. Here, we report a system that uses aluminum with a redox non-innocent ligand to achieve significant levels of coordination-induced bond weakening of O-H and N-H bonds. The multisite proton-coupled electron transfer manifold described here points to redox non-innocent ligands as a design element to open coordination-induced bond weakening chemistry to more elements in the periodic table.
A 10-m national-scale map of ground-mounted photovoltaic power stations in China of 2020
Authors: Feng Quanlong , Niu Bowen , Ren Yan , Su Shuai , Wang Jiudong , Shi Hongda , Yang Jianyu , Han Mengyao 
Published: February 2024

AbstractWe provide a remote sensing derived dataset for large-scale ground-mounted photovoltaic (PV) power stations in China of 2020, which has high spatial resolution of 10 meters. The dataset is based on the Google Earth Engine (GEE) cloud computing platform via random forest classifier and active learning strategy. Specifically, ground samples are carefully collected across China via both field survey and visual interpretation. Afterwards, spectral and texture features are calculated from publicly available Sentinel-2 imagery. Meanwhile, topographic features consisting of slope and aspect that are sensitive to PV locations are also included, aiming to construct a multi-dimensional and discriminative feature space. Finally, the trained random forest model is adopted to predict PV power stations of China parallelly on GEE. Technical validation has been carefully performed across China which achieved a satisfactory accuracy over 89%. Above all, as the first publicly released 10-m national-scale distribution dataset of China’s ground-mounted PV power stations, it can provide data references for relevant researchers in fields such as energy, land, remote sensing and environmental sciences.
From MS/MS library implementation to molecular networks: Exploring oxylipin diversity with NEO-MSMS
Authors: Elloumi Anis , Mas-Normand Lindsay , Bride Jamie , Reversat Guillaume , Bultel-Poncé Valérie , Guy Alexandre , Oger Camille , Demion Marie , Le Guennec Jean-Yves , Durand Thierry , Vigor Claire , Sánchez-Illana Ángel , Galano Jean-Marie 
Published: February 2024

AbstractOxylipins, small polar molecules derived from the peroxidation of polyunsaturated fatty acids (PUFAs), serve as biomarkers for many diseases and play crucial roles in human physiology and inflammation. Despite their significance, many non-enzymatic oxygenated metabolites of PUFAs (NEO-PUFAs) remain poorly reported, resulting in a lack of public datasets of experimental data and limiting their dereplication in further studies. To overcome this limitation, we constructed a high-resolution tandem mass spectrometry (MS/MS) dataset comprising pure NEO-PUFAs (both commercial and self-synthesized) and in vitro free radical-induced oxidation of diverse PUFAs. By employing molecular networking techniques with this dataset and the existent ones in public repositories, we successfully mapped a wide range of NEO-PUFAs, expanding the strategies for annotating oxylipins, and NEO-PUFAs and offering a novel workflow for profiling these molecules in biological samples.
Recovery of 1887 metagenome-assembled genomes from the South China Sea
Authors: Xu Shuaishuai , Huang Hailong , Chen Songze , Muhammad Zain Ul Arifeen , Wei Wenya , Xie Wei , Jiang Haibo , Hou Shengwei 
Published: February 2024

AbstractThe South China Sea (SCS) is a marginal sea characterized by strong land-sea biogeochemical interactions. SCS has a distinctive landscape with a multitude of seamounts in its basin. Seamounts create “seamount effects” that influence the diversity and distribution of planktonic microorganisms in the surrounding oligotrophic waters. Although the vertical distribution and community structure of marine microorganisms have been explored in certain regions of the global ocean, there is a lack of comprehensive microbial genomic surveys for uncultured microorganisms in SCS, particularly in the seamount regions. Here, we employed a metagenomic approach to study the uncultured microbial communities sampled from the Xianbei seamount region to the North Coast waters of SCS. A total of 1887 non-redundant prokaryotic metagenome-assembled genomes (MAGs) were reconstructed, of which, 153 MAGs were classified as high-quality MAGs based on the MIMAG standards. The community structure and genomic information provided by this dataset could be used to analyze microbial distribution and metabolism in the SCS.
Migration mechanism of grouting slurry and permeability reduction in mining fractured rock mass
Authors: Zhengzheng Cao , Pengshuai Wang , Zhenhua Li , Feng Du 
Published: February 2024

AbstractIn order to solve the water and gas discharge hazard caused by gob water and harmful gases (such as CO), the method of grouting overburden fractures is adopted to achieve the purpose of safe and efficient mining production in coal mines. This paper carries out the experimental research on the permeability reduction effect of grouting in fractured rock mass, expounds the relationship between gas flow rate and pressure gradient, seepage pressure and permeability, confining pressure and permeability, and analyzes the permeability change law of fractured rock mass before and after grouting. Besides, the grouting migration and permeability reduction model of fractured fine-grained sandstone is constructed by combining grouting test and numerical simulation, which reveals the dynamic evolution law of rock mass permeability in the grouting process. The results show that the permeability of the grouting rock sample decreases from 700–13,000 to 15–300 mD than that of the ungrouting rock sample, and the decrease is more than 95%, which indicates that the sealing performance of grouting slurry is better. Besides, numerical simulations show that the initial permeability of rock samples is 971.9 mD, and the permeability decreases to 45.79 mD after 1800s, and the permeability decreases to 95.3%, which is basically consistent with the experimental results after grouting. The greater the grouting pressure is, the better the grouting effect is. With the increase of the grouting pressure, the increase of the grouting effect is no longer obvious.
Addressing quantum’s “fine print” with efficient state preparation and information extraction for quantum algorithms and geologic fracture networks
Authors: Henderson Jessie M. , Kath John , Golden John K. , Percus Allon G. , O’Malley Daniel 
Published: February 2024

AbstractQuantum algorithms provide an exponential speedup for solving certain classes of linear systems, including those that model geologic fracture flow. However, this revolutionary gain in efficiency does not come without difficulty. Quantum algorithms require that problems satisfy not only algorithm-specific constraints, but also application-specific ones. Otherwise, the quantum advantage carefully attained through algorithmic ingenuity can be entirely negated. Previous work addressing quantum algorithms for geologic fracture flow has illustrated core algorithmic approaches while incrementally removing assumptions. This work addresses two further requirements for solving geologic fracture flow systems with quantum algorithms: efficient system state preparation and efficient information extraction. Our approach to addressing each is consistent with an overall exponential speed-up.
A new framework for assessment of park management in smart cities: a study based on social media data and deep learning
Authors: Liu Sijia , Tan Chuandong , Deng Feiyang , Zhang Wei , Wu Xuefei 
Published: February 2024

AbstractUrban park management assessment is critical to park operation and service quality. Traditional assessment methods cannot comprehensively assess park use and environmental conditions. Besides, although social media and big data have shown significant advantages in understanding public behavior or preference and park features or values, there has been little relevant research on park management assessment. This study proposes a deep learning-based framework for assessing urban park intelligent management from macro to micro levels with comment data from social media. By taking seven parks in Wuhan City as the objects, this study quantitatively assesses their overall state and performance in facilities, safety, environment, activities, and services, and reveals their main problems in management. The results demonstrate the impacts of various factors, including park type, season, and specific events such as remodeling and refurbishment, on visitor satisfaction and the characteristics of individual parks and their management. Compared with traditional methods, this framework enables real-time intelligent assessment of park management, which can accurately reflect park use and visitor feedback, and improve park service quality and management efficiency. Overall, this study provides important reference for intelligent park management assessment based on big data and artificial intelligence, which can facilitate the future development of smart cities.
Whole transcriptome screening for novel genes involved in meiosis and fertility in Drosophila melanogaster
Authors: Sun Siqi , Defosse Tyler , Boyd Ayla , Sop Joel , Verderose Faith , Surray Diya , Aziz Mark , Howland Margaret , Wu Siwen , Changela Neha , Jang Janet , Schindler Karen , Xing Jinchuan , McKim Kim S. 
Published: February 2024

AbstractReproductive success requires the development of viable oocytes and the accurate segregation of chromosomes during meiosis. Failure to segregate chromosomes properly can lead to infertility, miscarriages, or developmental disorders. A variety of factors contribute to accurate chromosome segregation and oocyte development, such as spindle assembly and sister chromatid cohesion. However, many proteins required for meiosis remain unknown. In this study, we aimed to develop a screening pipeline for identifying novel meiotic and fertility genes using the genome of Drosophila melanogaster. To accomplish this goal, genes upregulated within meiotically active tissues were identified. More than 240 genes with no known function were silenced using RNA interference (RNAi) and the effects on meiosis and fertility were assessed. We identified 94 genes that when silenced caused infertility and/or high levels of chromosomal nondisjunction. The vast majority of these genes have human and mouse homologs that are also poorly studied. Through this screening process, we identified novel genes that are crucial for meiosis and oocyte development but have not been extensively studied in human or model organisms. Understanding the function of these genes will be an important step towards the understanding of their biological significance during reproduction.
Classification and identification of agricultural products based on improved MobileNetV2
Authors: Chen Haiwei , Zhou Guohui , He Wei , Duan Xiping , Jiang Huixin 
Published: February 2024

AbstractWith the advancement of technology, the demand for increased production efficiency has gradually risen, leading to the emergence of new trends in agricultural automation and intelligence. Precision classification models play a crucial role in helping farmers accurately identify, classify, and process various agricultural products, thereby enhancing production efficiency and maximizing the economic value of agricultural products. The current MobileNetV2 network model is capable of performing the aforementioned tasks. However, it tends to exhibit recognition biases when identifying different subcategories within agricultural product varieties. To address this challenge, this paper introduces an improved MobileNetV2 convolutional neural network model. Firstly, inspired by the Inception module in GoogLeNet, we combine the improved Inception module with the original residual module, innovatively proposing a new Res-Inception module. Additionally, to further enhance the model's accuracy in detection tasks, we introduce an efficient multi-scale cross-space learning module (EMA) and embed it into the backbone structure of the network. Experimental results on the Fruit-360 dataset demonstrate that the improved MobileNetV2 outperforms the original MobileNetV2 in agricultural product classification tasks, with an accuracy increase of 1.86%.
Integrative analysis of epilepsy-associated genes reveals expression-phenotype correlations
Authors: Chi Wanhao , Kiskinis Evangelos 
Published: February 2024

AbstractEpilepsy is a highly prevalent neurological disorder characterized by recurrent seizures. Patients exhibit broad genetic, molecular, and clinical diversity involving mild to severe comorbidities. The factors that contribute to this phenotypic diversity remain unclear. Here we used publicly available datasets to systematically interrogate the expression pattern of 230 epilepsy-associated genes across human tissues, developmental stages, and central nervous system (CNS) cellular subtypes. We grouped genes based on their curated phenotypes into 3 broad classes: core epilepsy genes (CEG), where seizures are the dominant phenotype, developmental and epileptic encephalopathy genes (DEEG) that are associated with developmental and epileptic encephalopathy, and seizure-related genes (SRG), which are characterized by the presence of seizures and gross brain malformations. We find that compared to the other two groups of genes, DEEGs are highly expressed within the adult CNS, exhibit the highest and most dynamic expression in various brain regions across development, and are significantly enriched in GABAergic neurons. Our analysis provides an overview of the expression pattern of epilepsy-associated genes with spatiotemporal resolution and establishes a broad expression-phenotype correlation in epilepsy.
Prevalence and associated factors for asymptomatic microscopic hematuria in adults in the PERSIAN Guilan cohort study (PGCS)
Authors: Joukar Farahnaz , Hassanipour Soheil , Atefi Amirhomayoun , Maroufizadeh Saman , Akhavan Ardalan , Naghipour Mohammadreza , Falahatkar Siavash , Khosousi Mohammad-Javad , Asgharnezhad Mehrnaz , Mansour-Ghanaei Fariborz 
Published: February 2024

AbstractAlthough hematuria is not life-threatening, some could be the result of a more severe condition. Our objectives are to report on the prevalence and risk factors of asymptomatic microscopic hematuria (AMH) in the prospective epidemiological research studies of the Iranian adults (PERSIAN) Guilan cohort study (PGCS) population. This cross-sectional study was conducted from 2014 to 2017 and consisted of 10,520 individuals aged 35–70. Data collection was conducted using a questionnaire during a face-to-face interview. The urine analyses (UA) were done up to 2 h after sample collection. Based on a urine microscopy evaluation, AMH is defined as 3 or more red blood cells per high power field (HPF). Simple and multiple logistic regression analysis was conducted to explore factors associated with AMH. The prevalence of AMH in this study was 34.1% and was more prevalent in participants of older ages and female gender as well as those with low educational level, underweight-body mass index (BMI), high physical activity, smoking, alcohol consumption, and kidney stone disease. On the other hand, obesity, opium, and diabetes decreased the likelihood of AMH. The results of the present study shed light on the prevalence and risk factors of AMH and suggested that a significant portion of the study population is affected by AMH. Considering the lack of consensus on a definite clinical guideline for AMH in our country, the results of the present study could be used to design a unit algorithm for screening and therapy of AMH.
Commodity-specific triads in the Dutch inter-industry production network
Authors: Di Vece Marzio , Pijpers Frank P. , Garlaschelli Diego 
Published: February 2024

AbstractTriadic motifs are the smallest building blocks of higher-order interactions in complex networks and can be detected as over-occurrences with respect to null models with only pair-wise interactions. Recently, the motif structure of production networks has attracted attention in light of its possible role in the propagation of economic shocks. However, its characterization at the level of individual commodities is still poorly understood. Here we analyze both binary and weighted triadic motifs in the Dutch inter-industry production network disaggregated at the level of 187 commodity groups, which Statistics Netherlands reconstructed from National Accounts registers, surveys and known empirical data. We introduce appropriate null models that filter out node heterogeneity and the strong effects of link reciprocity and find that, while the aggregate network that overlays all products is characterized by a multitude of triadic motifs, most single-product layers feature no significant motif, and roughly 85% of the layers feature only two motifs or less. This result paves the way for identifying a simple ‘triadic fingerprint’ of each commodity and for reconstructing most product-specific networks from partial information in a pairwise fashion by controlling for their reciprocity structure. We discuss how these results can help statistical bureaus identify fine-grained information in structural analyses of interest for policymakers.