bluuebunny/crossref_metadata_2025_split huggingface dataset:
Microbial invasion of a toxic medium is facilitated by a resident community but inhibited as the community co-evolves
Authors: Piccardi Philippe , Alberti Géraldine , Alexander Jake M , Mitri Sara 
Published: September 2022

Abstract
Predicting whether microbial invaders will colonize an environment is critical for managing natural and engineered ecosystems, and controlling infectious disease. Invaders often face competition by resident microbes. But how invasions play out in communities dominated by facilitative interactions is less clear. We previously showed that growth medium toxicity can promote facilitation between four bacterial species, as species that cannot grow alone rely on others to survive. Following the same logic, here we allowed other bacterial species to invade the four-species community and found that invaders could more easily colonize a toxic medium when the community was present. In a more benign environment instead, invasive species that could survive alone colonized more successfully when the residents were absent. Next, we asked whether early colonists could exclude future ones through a priority effect, by inoculating the invaders into the resident community only after its members had co-evolved for 44 weeks. Compared to the ancestral community, the co-evolved resident community was more competitive toward invaders and less affected by them. Our experiments show how communities may assemble by facilitating one another in harsh, sterile environments, but that arriving after community members have co-evolved can limit invasion success.
Structure of the membrane-bound formate hydrogenlyase complex from Escherichia coli
Authors: Steinhilper Ralf , Höff Gabriele , Heider Johann , Murphy Bonnie J. 
Published: September 2022

AbstractThe prototypical hydrogen-producing enzyme, the membrane-bound formate hydrogenlyase (FHL) complex from Escherichia coli, links formate oxidation at a molybdopterin-containing formate dehydrogenase to proton reduction at a [NiFe] hydrogenase. It is of intense interest due to its ability to efficiently produce H2 during fermentation, its reversibility, allowing H2-dependent CO2 reduction, and its evolutionary link to respiratory complex I. FHL has been studied for over a century, but its atomic structure remains unknown. Here we report cryo-EM structures of FHL in its aerobically and anaerobically isolated forms at resolutions reaching 2.6 Å. This includes well-resolved density for conserved loops linking the soluble and membrane arms believed to be essential in coupling enzymatic turnover to ion translocation across the membrane in the complex I superfamily. We evaluate possible structural determinants of the bias toward hydrogen production over its oxidation and describe an unpredicted metal-binding site near the interface of FdhF and HycF subunits that may play a role in redox-dependent regulation of FdhF interaction with the complex.
Understanding Braess’ Paradox in power grids
Authors: Schäfer Benjamin , Pesch Thiemo , Manik Debsankha , Gollenstede Julian , Lin Guosong , Beck Hans-Peter , Witthaut Dirk , Timme Marc 
Published: September 2022

AbstractThe ongoing energy transition requires power grid extensions to connect renewable generators to consumers and to transfer power among distant areas. The process of grid extension requires a large investment of resources and is supposed to make grid operation more robust. Yet, counter-intuitively, increasing the capacity of existing lines or adding new lines may also reduce the overall system performance and even promote blackouts due to Braess’ paradox. Braess’ paradox was theoretically modeled but not yet proven in realistically scaled power grids. Here, we present an experimental setup demonstrating Braess’ paradox in an AC power grid and show how it constrains ongoing large-scale grid extension projects. We present a topological theory that reveals the key mechanism and predicts Braessian grid extensions from the network structure. These results offer a theoretical method to understand and practical guidelines in support of preventing unsuitable infrastructures and the systemic planning of grid extensions.
Mesoscopic sliding ferroelectricity enabled photovoltaic random access memory for material-level artificial vision system
Authors: Sun Yan , Xu Shuting , Xu Zheqi , Tian Jiamin , Bai Mengmeng , Qi Zhiying , Niu Yue , Aung Hein Htet , Xiong Xiaolu , Han Junfeng , Lu Cuicui , Yin Jianbo , Wang Sheng , Chen Qing , Tenne Reshef , Zak Alla , Guo Yao 
Published: September 2022

AbstractIntelligent materials with adaptive response to external stimulation lay foundation to integrate functional systems at the material level. Here, with experimental observation and numerical simulation, we report a delicate nano-electro-mechanical-opto-system naturally embedded in individual multiwall tungsten disulfide nanotubes, which generates a distinct form of in-plane van der Waals sliding ferroelectricity from the unique combination of superlubricity and piezoelectricity. The sliding ferroelectricity enables programmable photovoltaic effect using the multiwall tungsten disulfide nanotube as photovoltaic random-access memory. A complete “four-in-one” artificial vision system that synchronously achieves full functions of detecting, processing, memorizing, and powering is integrated into the nanotube devices. Both labeled supervised learning and unlabeled reinforcement learning algorithms are executable in the artificial vision system to achieve self-driven image recognition. This work provides a distinct strategy to create ferroelectricity in van der Waals materials, and demonstrates how intelligent materials can push electronic system integration at the material level.
Energy comparison of sequential and integrated CO2 capture and electrochemical conversion
Authors: Li Mengran , Irtem Erdem , Iglesias van Montfort Hugo-Pieter , Abdinejad Maryam , Burdyny Thomas 
Published: September 2022

AbstractIntegrating carbon dioxide (CO2) electrolysis with CO2 capture provides exciting new opportunities for energy reductions by simultaneously removing the energy-demanding regeneration step in CO2 capture and avoiding critical issues faced by CO2 gas-fed electrolysers. However, understanding the potential energy advantages of an integrated process is not straightforward due to the interconnected processes which require knowledge of both capture and electrochemical conversion processes. Here, we identify the upper limits of the integrated process from an energy perspective by comparing the working principles and performance of integrated and sequential approaches. Our high-level energy analyses unveil that an integrated electrolyser must show similar performance to the gas-fed electrolyser to ensure an energy benefit of up to 44% versus the sequential route. However, such energy benefits diminish if future gas-fed electrolysers resolve the CO2 utilisation issue and if an integrated electrolyser shows lower conversion efficiencies than the gas-fed system.
Exploiting degeneracy in belief propagation decoding of quantum codes
Authors: Kuo Kao-Yueh , Lai Ching-Yi 
Published: September 2022

AbstractQuantum information needs to be protected by quantum error-correcting codes due to imperfect physical devices and operations. One would like to have an efficient and high-performance decoding procedure for the class of quantum stabilizer codes. A potential candidate is Gallager’s sum-product algorithm, also known as Pearl’s belief propagation (BP), but its performance suffers from the many short cycles inherent in a quantum stabilizer code, especially highly-degenerate codes. A general impression exists that BP is not effective for topological codes. In this paper, we propose a decoding algorithm for quantum codes based on quaternary BP with additional memory effects (called MBP). This MBP is like a recursive neural network with inhibitions between neurons (edges with negative weights), which enhance the perception capability of a network. Moreover, MBP exploits the degeneracy of a quantum code so that the most probable error or its degenerate errors can be found with high probability. The decoding performance is significantly improved over the conventional BP for various quantum codes, including quantum bicycle, hypergraph-product, surface and toric codes. For MBP on the surface and toric codes over depolarizing errors, we observe error thresholds of 16% and 17.5%, respectively.
Delayed fluorescence from inverted singlet and triplet excited states
Authors: Aizawa Naoya , Pu Yong-Jin , Harabuchi Yu , Nihonyanagi Atsuko , Ibuka Ryotaro , Inuzuka Hiroyuki , Dhara Barun , Koyama Yuki , Nakayama Ken-ichi , Maeda Satoshi , Araoka Fumito , Miyajima Daigo 
Published: September 2022

AbstractHund’s multiplicity rule states that a higher spin state has a lower energy for a given electronic configuration1. Rephrasing this rule for molecular excited states predicts a positive energy gap between spin-singlet and spin-triplet excited states, as has been consistent with numerous experimental observations over almost a century. Here we report a fluorescent molecule that disobeys Hund’s rule and has a negative singlet–triplet energy gap of −11 ± 2 meV. The energy inversion of the singlet and triplet excited states results in delayed fluorescence with short time constants of 0.2 μs, which anomalously decrease with decreasing temperature owing to the emissive singlet character of the lowest-energy excited state. Organic light-emitting diodes (OLEDs) using this molecule exhibited a fast transient electroluminescence decay with a peak external quantum efficiency of 17%, demonstrating its potential implications for optoelectronic devices, including displays, lighting and lasers.
TOPSIS aided ensemble of CNN models for screening COVID-19 in chest X-ray images
Authors: Pramanik Rishav , Dey Subhrajit , Malakar Samir , Mirjalili Seyedali , Sarkar Ram 
Published: September 2022

AbstractThe novel coronavirus (COVID-19), has undoubtedly imprinted our lives with its deadly impact. Early testing with isolation of the individual is the best possible way to curb the spread of this deadly virus. Computer aided diagnosis (CAD) provides an alternative and cheap option for screening of the said virus. In this paper, we propose a convolution neural network (CNN)-based CAD method for COVID-19 and pneumonia detection from chest X-ray images. We consider three input types for three identical base classifiers. To capture maximum possible complementary features, we consider the original RGB image, Red channel image and the original image stacked with Robert's edge information. After that we develop an ensemble strategy based on the technique for order preference by similarity to an ideal solution (TOPSIS) to aggregate the outcomes of base classifiers. The overall framework, called TOPCONet, is very light in comparison with standard CNN models in terms of the number of trainable parameters required. TOPCONet achieves state-of-the-art results when evaluated on the three publicly available datasets: (1) IEEE COVID-19 dataset + Kaggle Pneumonia Dataset, (2) Kaggle Radiography dataset and (3) COVIDx.
Overcoming the strength–formability trade-off in high strength steels via cryogenic treatment
Authors: Park Gyeongbae , Zargaran A. , Oh J. K. , Trang T. T. T. , Kim N. J. 
Published: September 2022

AbstractHigh strength steels are becoming more important than ever before for automotive applications to reduce the weight of automobiles and to ensure the safety of passengers. Since increased strength usually results in degraded formability, however, cold forming of high strength steels into final shapes remains a challenge to both automotive manufacturers and suppliers. Here we report novel alloy and processing design concepts that can impart high strength to cold-formable steels, which deviates from the traditional approach of improving the formability of high strength steels. Such designed steel subjected to a designed processing route shows an excellent combination of formability and strength as well as crashworthiness, which is crucial for the safety of passengers in the automobiles. The alloy and processing design concepts used in the present study are based on the utilization of thermally induced austenite to martensite transformation, which imparts high strength to cold-formable austenite by cryogenic treatment.
Novel tricyclic small molecule inhibitors of Nicotinamide N-methyltransferase for the treatment of metabolic disorders
Authors: Ruf Sven , Rajagopal Sridharan , Kadnur Sanjay Venkatachalapathi , Hallur Mahanandeesha S. , Rani Shilpa , Kristam Rajendra , Swaminathan Srinivasan , Zope Bharat Ravindra , Gondrala Pavan Kumar , Swamy Indu , Putta V. P. Rama Kishore , Kandan Saravanan , Zech Gernot , Schreuder Herman , Rudolph Christine , Elvert Ralf , Czech Joerg , Birudukota Swarnakumari , Siddiqui M. Amir , Anand Niranjan Naranapura , Mane Vishal Subhash , Dittakavi Sreekanth , Suresh Juluri , Gosu Ramachandraiah , Ramesh Mullangi , Yura Takeshi , Dhakshinamoorthy Saravanakumar , Kannt Aimo 
Published: September 2022

AbstractNicotinamide N-methyltransferase (NNMT) is a metabolic regulator that catalyzes the methylation of nicotinamide (Nam) using the co-factor S-adenosyl-L-methionine to form 1-methyl-nicotinamide (MNA). Overexpression of NNMT and the presence of the active metabolite MNA is associated with a number of diseases including metabolic disorders. We conducted a high-throughput screening campaign that led to the identification of a tricyclic core as a potential NNMT small molecule inhibitor series. Elaborate medicinal chemistry efforts were undertaken and hundreds of analogs were synthesized to understand the structure activity relationship and structure property relationship of this tricyclic series. A lead molecule, JBSNF-000028, was identified that inhibits human and mouse NNMT activity, reduces MNA levels in mouse plasma, liver and adipose tissue, and drives insulin sensitization, glucose modulation and body weight reduction in a diet-induced obese mouse model of diabetes. The co-crystal structure showed that JBSNF-000028 binds below a hairpin structural motif at the nicotinamide pocket and stacks between Tyr-204 (from Hairpin) and Leu-164 (from central domain). JBSNF-000028 was inactive against a broad panel of targets related to metabolism and safety. Interestingly, the improvement in glucose tolerance upon treatment with JBSNF-000028 was also observed in NNMT knockout mice with diet-induced obesity, pointing towards the glucose-normalizing effect that may go beyond NNMT inhibition. JBSNF-000028 can be a potential therapeutic option for metabolic disorders and developmental studies are warranted.
Determination of pharmacokinetics and tissue distribution of a novel lutetium-labeled PSMA-targeted ligand, 177Lu-DOTA-PSMA-GUL, in rats by using LC–MS/MS
Authors: Song Chang Ho , Kim Kweon , Kang Eunhee , Jeong Bora , Lee Myung-Su , Jung Jiyoon , Kim Tae Hwan , Shin Soyoung , Shin Beom Soo 
Published: September 2022

AbstractProstate specific membrane antigen (PSMA) is known to be overexpressed in prostate cancer cells, providing as a diagnostic and therapeutic target for prostate cancer. A lutetium-labeled PSMA targeted ligand, 177Lu-DOTA-PSMA-GUL is a novel radiopharmaceutical, which has been developed for the treatment of prostate cancer. While the GUL domain of 177Lu-DOTA-PSMA-GUL binds to the antigen, the beta-emitting radioisotope, 177Lu-labeled DOTA, interacts with prostate cancer cells. However, the in vivo pharmacokinetics of intact 177Lu-DOTA-PSMA-GUL has never been characterized. This study aimed to evaluate the pharmacokinetics and tissue distribution of the radiopharmaceutical in rats by using its stable isotope-labeled analog, 175Lu-DOTA-PSMA-GUL. A sensitive liquid chromatography-tandem mass spectrometry (LC–MS/MS) analysis of 175Lu-DOTA-PSMA-GUL was developed and validated. Following intravenous injection, the plasma concentration–time profiles of 175Lu-DOTA-PSMA-GUL showed a multi-exponential decline with the average elimination half-life of 0.30 to 0.33 h. Systemic exposure increased with the dose and renal excretion is the major elimination route. Tissue distribution of 175Lu-DOTA-PSMA-GUL was most substantial in kidneys, followed by the prostate. The developed LC–MS/MS assay and the in vivo pharmacokinetic data of 175Lu-DOTA-PSMA-GUL would provide helpful information for further clinical studies to be developed as a novel therapeutic agent for prostate cancer.
Transformer based on channel-spatial attention for accurate classification of scenes in remote sensing image
Authors: Guo Jingxia , Jia Nan , Bai Jinniu 
Published: September 2022

AbstractRecently, the scenes in large high-resolution remote sensing (HRRS) datasets have been classified using convolutional neural network (CNN)-based methods. Such methods are well-suited for spatial feature extraction and can classify images with relatively high accuracy. However, CNNs do not adequately learn the long-distance dependencies between images and features in image processing, despite this being necessary for HRRS image processing as the semantic content of the scenes in these images is closely related to their spatial relationship. CNNs also have limitations in solving problems related to large intra-class differences and high inter-class similarity. To overcome these challenges, in this study we combine the channel-spatial attention (CSA) mechanism with the Vision Transformer method to propose an effective HRRS image scene classification framework using Channel-Spatial Attention Transformers (CSAT). The proposed model extracts the channel and spatial features of HRRS images using CSA and the Multi-head Self-Attention (MSA) mechanism in the transformer module. First, the HRRS image is mapped into a series of multiple planar 2D patch vectors after passing to the CSA. Second, the ordered vector is obtained via the linear transformation of each vector, and the position and learnable embedding vectors are added to the sequence vector to capture the inter-feature dependencies at a distance from the generated image. Next, we use MSA to extract image features and the residual network structure to complete the encoder construction to solve the gradient disappearance problem and avoid overfitting. Finally, a multi-layer perceptron is used to classify the scenes in the HRRS images. The CSAT network is evaluated using three public remote sensing scene image datasets: UC-Merced, AID, and NWPU-RESISC45. The experimental results show that the proposed CSAT network outperforms a selection of state-of-the-art methods in terms of scene classification.
A (GCC) repeat in SBF1 reveals a novel biological phenomenon in human and links to late onset neurocognitive disorder
Authors: Khamse Safoura , Alizadeh Samira , Bernhart Stephan H. , Afshar Hossein , Delbari Ahmad , Ohadi Mina 
Published: September 2022

AbstractThe humanSBF1(SET binding factor 1) gene, alternatively known asMTMR5, is predominantly expressed in the brain, and its epigenetic dysregulation is linked to late-onset neurocognitive disorders (NCDs), such as Alzheimer’s disease. This gene contains a (GCC)-repeat at the interval between + 1 and + 60 of the transcription start site (SBF1-202 ENST00000380817.8). We sequenced theSBF1(GCC)-repeat in a sample of 542 Iranian individuals, consisting of late-onset NCDs (N = 260) and controls (N = 282). While multiple alleles were detected at this locus, the 8 and 9 repeats were predominantly abundant, forming > 95% of the allele pool across the two groups. Among a number of anomalies, the allele distribution was significantly different in the NCD group versus controls (Fisher’s exactp = 0.006), primarily as a result of enrichment of the 8-repeat in the former. The genotype distribution departed from the Hardy–Weinberg principle in both groups (p < 0.001), and was significantly different between the two groups (Fisher’s exactp = 0.001). We detected significantly low frequency of the 8/9 genotype in both groups, higher frequency of this genotype in the NCD group, and reverse order of 8/8 versus 9/9 genotypes in the NCD group versus controls. Biased heterozygous/heterozygous ratios were also detected for the 6/8 versus 6/9 genotypes (in favor of 6/8) across the human samples studied (Fisher’s exactp = 0.0001). Bioinformatics studies revealed that the number of (GCC)-repeats may change the RNA secondary structure and interaction sites at least across human exon 1. This STR was specifically expanded beyond 2-repeats in primates. In conclusion, we report indication of a novel biological phenomenon, in which there is selection against certain heterozygous genotypes at a STR locus in human. We also report different allele and genotype distribution at this STR locus in late-onset NCD versus controls. In view of the location of this STR in the 5′ untranslated region, RNA/RNA or RNA/DNA heterodimer formation of the involved genotypes and alternative RNA processing and/or translation should be considered.
Layer-dependent Schottky contact at van der Waals interfaces: V-doped WSe2 on graphene
Authors: Stolz Samuel , Kozhakhmetov Azimkhan , Dong Chengye , Gröning Oliver , Robinson Joshua A. , Schuler Bruno 
Published: September 2022

AbstractContacting two-dimensional (2D) semiconductors with van der Waals semimetals significantly reduces the contact resistance and Fermi level pinning due to defect-free interfaces. However, depending on the band alignment, a Schottky barrier remains. Here we study the evolution of the valence and conduction band edges in pristine and heavily vanadium (0.44%), i.e., p-type, doped epitaxial WSe2 on quasi-freestanding graphene (QFEG) on silicon carbide as a function of thickness. We find that with increasing number of layers the Fermi level of the doped WSe2 gets pinned at the highest dopant level for three or more monolayers. This implies a charge depletion region of about 1.6 nm. Consequently, V dopants in the first and second WSe2 layer on QFEG/SiC are ionized (negatively charged) whereas they are charge neutral beyond the second layer.