bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ground-state electron transfer in all-polymer donor:acceptor blends enables aqueous processing of water-insoluble conjugated polymers
Authors: Liu Tiefeng , Heimonen Johanna , Zhang Qilun , Yang Chi-Yuan , Huang Jun-Da , Wu Han-Yan , Stoeckel Marc-Antoine , van der Pol Tom P. A. , Li Yuxuan , Jeong Sang Young , Marks Adam , Wang Xin-Yi , Puttisong Yuttapoom , Shimolo Asaminew Y. , Liu Xianjie , Zhang Silan , Li Qifan , Massetti Matteo , Chen Weimin M. , Woo Han Young , Pei Jian , McCulloch Iain , Gao Feng , Fahlman Mats , Kroon Renee , Fabiano Simone 
Published: December 2023

AbstractWater-based conductive inks are vital for the sustainable manufacturing and widespread adoption of organic electronic devices. Traditional methods to produce waterborne conductive polymers involve modifying their backbone with hydrophilic side chains or using surfactants to form and stabilize aqueous nanoparticle dispersions. However, these chemical approaches are not always feasible and can lead to poor material/device performance. Here, we demonstrate that ground-state electron transfer (GSET) between donor and acceptor polymers allows the processing of water-insoluble polymers from water. This approach enables macromolecular charge-transfer salts with 10,000× higher electrical conductivities than pristine polymers, low work function, and excellent thermal/solvent stability. These waterborne conductive films have technological implications for realizing high-performance organic solar cells, with efficiency and stability superior to conventional metal oxide electron transport layers, and organic electrochemical neurons with biorealistic firing frequency. Our findings demonstrate that GSET offers a promising avenue to develop water-based conductive inks for various applications in organic electronics.
High quality factor metasurfaces for two-dimensional wavefront manipulation
Authors: Hail Claudio U. , Foley Morgan , Sokhoyan Ruzan , Michaeli Lior , Atwater Harry A. 
Published: December 2023

AbstractThe strong interaction of light with micro- and nanostructures plays a critical role in optical sensing, nonlinear optics, active optical devices, and quantum optics. However, for wavefront shaping, the required local control over light at a subwavelength scale limits this interaction, typically leading to low-quality-factor optical devices. Here, we demonstrate an avenue towards high-quality-factor wavefront shaping in two spatial dimensions based on all-dielectric higher-order Mie-resonant metasurfaces. We design and experimentally realize transmissive band stop filters, beam deflectors and high numerical aperture radial lenses with measured quality factors in the range of 202–1475 at near-infrared wavelengths. The excited optical mode and resulting wavefront control are both local, allowing versatile operation with finite apertures and oblique illumination. Our results represent an improvement in quality factor by nearly two orders of magnitude over previous localized mode designs, and provide a design approach for a new class of compact optical devices.
Engineering a synthetic energy-efficient formaldehyde assimilation cycle in Escherichia coli
Authors: Wu Tong , Gómez-Coronado Paul A. , Kubis Armin , Lindner Steffen N. , Marlière Philippe , Erb Tobias J. , Bar-Even Arren , He Hai 
Published: December 2023

AbstractOne-carbon (C1) substrates, such as methanol or formate, are attractive feedstocks for circular bioeconomy. These substrates are typically converted into formaldehyde, serving as the entry point into metabolism. Here, we design an erythrulose monophosphate (EuMP) cycle for formaldehyde assimilation, leveraging a promiscuous dihydroxyacetone phosphate dependent aldolase as key enzyme. In silico modeling reveals that the cycle is highly energy-efficient, holding the potential for high bioproduct yields. Dissecting the EuMP into four modules, we use a stepwise strategy to demonstrate in vivo feasibility of the modules in E. coli sensor strains with sarcosine as formaldehyde source. From adaptive laboratory evolution for module integration, we identify key mutations enabling the accommodation of the EuMP reactions with endogenous metabolism. Overall, our study demonstrates the proof-of-concept for a highly efficient, new-to-nature formaldehyde assimilation pathway, opening a way for the development of a methylotrophic platform for a C1-fueled bioeconomy in the future.
Extendable piezo/ferroelectricity in nonstoichiometric 2D transition metal dichalcogenides
Authors: Hu Yi , Rogée Lukas , Wang Weizhen , Zhuang Lyuchao , Shi Fangyi , Dong Hui , Cai Songhua , Tay Beng Kang , Lau Shu Ping 
Published: December 2023

AbstractEngineering piezo/ferroelectricity in two-dimensional materials holds significant implications for advancing the manufacture of state-of-the-art multifunctional materials. The inborn nonstoichiometric propensity of two-dimensional transition metal dichalcogenides provides a spiffy ready-available solution for breaking inversion centrosymmetry, thereby conducing to circumvent size effect challenges in conventional perovskite oxide ferroelectrics. Here, we show the extendable and ubiquitous piezo/ferroelectricity within nonstoichiometric two-dimensional transition metal dichalcogenides that are predominantly centrosymmetric during standard stoichiometric cases. The emerged piezo/ferroelectric traits are aroused from the sliding of van der Waals layers and displacement of interlayer metal atoms triggered by the Frankel defects of heterogeneous interlayer native metal atom intercalation. We demonstrate two-dimensional chromium selenides nanogenerator and iron tellurides ferroelectric multilevel memristors as two representative applications. This innovative approach to engineering piezo/ferroelectricity in ultrathin transition metal dichalcogenides may provide a potential avenue to consolidate piezo/ferroelectricity with featured two-dimensional materials to fabricate multifunctional materials and distinguished multiferroic.
Wearable, epidermal devices for assessment of swallowing function
Authors: Rafeedi Tarek , Abdal Abdulhameed , Polat Beril , Hutcheson Katherine A. , Shinn Eileen H. , Lipomi Darren J. 
Published: December 2023

AbstractSwallowing is an ensemble of voluntary and autonomic processes key to maintaining our body’s homeostatic balance. Abnormal swallowing (dysphagia) can cause dehydration, malnutrition, aspiration pneumonia, weight loss, anxiety, or even mortality—especially in older adults—by airway obstruction. To prevent or mitigate these outcomes, it is imperative to regularly assess swallowing ability in those who are at risk of developing dysphagia and those already diagnosed with it. However, current diagnostic tools such as endoscopy, manometry, and videofluoroscopy require access to clinical experts to interpret the results. These results are often sampled from a limited examination timeframe of swallowing activity in a controlled environment. Additionally, there is some risk of periprocedural complications associated with these methods. In contrast, the field of epidermal sensors is finding non-invasive and minimally obtrusive ways to examine swallowing function and dysfunction. In this review, we summarize the current state of wearable devices that are aimed at monitoring swallowing function and detecting its abnormalities. We pay particular attention to the materials and design parameters that enable their operation. We examine a compilation of both proof-of-concept studies (which focus mainly on the engineering of the device) and studies whose aims are biomedical (which may involve larger cohorts of subjects, including patients). Furthermore, we briefly discuss the methods of signal acquisition and device assessment in relevant wearable sensors. Finally, we examine the need to increase adherence and engagement of patients with such devices and discuss enhancements to the design of such epidermal sensors that may encourage greater enthusiasm for at-home and long-term monitoring.
Superconductivity in a ferroelectric-like topological semimetal SrAuBi
Authors: Takahashi Hidefumi , Sasaki Tomohiro , Nakano Akitoshi , Akiba Kazuto , Takahashi Masayuki , Mayo Alex H. , Onose Masaho , Kobayashi Tatsuo C. , Ishiwata Shintaro 
Published: December 2023

AbstractGiven the rarity of metallic systems that exhibit ferroelectric-like transitions, it is apparently challenging to find a system that simultaneously possesses superconductivity and ferroelectric-like structural instability. Here, we report the observation of superconductivity at 2.4 K in a layered semimetal SrAuBi characterized by strong spin–orbit coupling (SOC) and ferroelectric-like lattice distortion. Single crystals of SrAuBi have been successfully synthesized and found to show a polar-nonpolar structure transition at 214 K, which is associated with the buckling of Au-Bi honeycomb lattice. On the basis of the band calculations considering SOC, we found significant Rashba-type spin splitting and symmetry-protected multiple Dirac points near the Fermi level. We believe that this discovery opens up new possibilities of pursuing exotic superconducting states associated with the semimetallic band structure without space inversion symmetry and the topological surface state with the strong SOC.
Chemoselective umpolung of thiols to episulfoniums for cysteine bioconjugation
Authors: Hartmann Philipp , Bohdan Kostiantyn , Hommrich Moritz , Juliá Fabio , Vogelsang Lara , Eirich Jürgen , Zangl Rene , Farès Christophe , Jacobs Julia Beatrice , Mukhopadhyay Dwaipayan , Mengeler Johanna Marie , Vetere Alessandro , Sterling Marie Sophie , Hinrichs Heike , Becker Stefan , Morgner Nina , Schrader Wolfgang , Finkemeier Iris , Dietz Karl-Josef , Griesinger Christian , Ritter Tobias 
Published: December 2023

AbstractCysteine conjugation is an important tool in protein research and relies on fast, mild and chemoselective reactions. Cysteinyl thiols can either be modified with prefunctionalized electrophiles, or converted into electrophiles themselves for functionalization with selected nucleophiles in an independent step. Here we report a bioconjugation strategy that uses a vinyl thianthrenium salt to transform cysteine into a highly reactive electrophilic episulfonium intermediate in situ, to enable conjugation with a diverse set of bioorthogonal nucleophiles in a single step. The reactivity profile can connect several nucleophiles to biomolecules through a short and stable ethylene linker, ideal for introduction of infrared labels, post-translational modifications or NMR probes. In the absence of reactive exogenous nucleophiles, nucleophilic amino acids can react with the episulfonium intermediate for native peptide stapling and protein–protein ligation. Ready synthetic access to isotopologues of vinyl thianthrenium salts enables applications in quantitative proteomics. Such diverse applications demonstrate the utility of vinyl-thianthrenium-based bioconjugation as a fast, selective and broadly applicable tool for chemical biology.
T1DiabetesGranada: a longitudinal multi-modal dataset of type 1 diabetes mellitus
Authors: Rodriguez-Leon Ciro , Aviles-Perez Maria Dolores , Banos Oresti , Quesada-Charneco Miguel , Lopez-Ibarra Lozano Pablo J. , Villalonga Claudia , Munoz-Torres Manuel 
Published: December 2023

AbstractType 1 diabetes mellitus (T1D) patients face daily difficulties in keeping their blood glucose levels within appropriate ranges. Several techniques and devices, such as flash glucose meters, have been developed to help T1D patients improve their quality of life. Most recently, the data collected via these devices is being used to train advanced artificial intelligence models to characterize the evolution of the disease and support its management. Data scarcity is the main challenge for generating these models, as most works use private or artificially generated datasets. For this reason, this work presents T1DiabetesGranada, an open under specific permission longitudinal dataset that not only provides continuous glucose levels, but also patient demographic and clinical information. The dataset includes 257 780 days of measurements spanning four years from 736 T1D patients from the province of Granada, Spain. This dataset advances beyond the state of the art as one the longest and largest open datasets of continuous glucose measurements, thus boosting the development of new artificial intelligence models for glucose level characterization and prediction.
RescueNet: A High Resolution UAV Semantic Segmentation Dataset for Natural Disaster Damage Assessment
Authors: Rahnemoonfar Maryam , Chowdhury Tashnim , Murphy Robin 
Published: December 2023

AbstractRecent advancements in computer vision and deep learning techniques have facilitated notable progress in scene understanding, thereby assisting rescue teams in achieving precise damage assessment. In this paper, we present RescueNet, a meticulously curated high-resolution post-disaster dataset that includes detailed classification and semantic segmentation annotations. This dataset aims to facilitate comprehensive scene understanding in the aftermath of natural disasters. RescueNet comprises post-disaster images collected after Hurricane Michael, obtained using Unmanned Aerial Vehicles (UAVs) from multiple impacted regions. The uniqueness of RescueNet lies in its provision of high-resolution post-disaster imagery, accompanied by comprehensive annotations for each image. Unlike existing datasets that offer annotations limited to specific scene elements such as buildings, RescueNet provides pixel-level annotations for all classes, including buildings, roads, pools, trees, and more. Furthermore, we evaluate the utility of the dataset by implementing state-of-the-art segmentation models on RescueNet, demonstrating its value in enhancing existing methodologies for natural disaster damage assessment.
Gridded material stocks in China based on geographical and geometric configurations of the built-environment
Authors: Sun Jian , Wang Tao , Jiang Nanxi , Liu Zezhuang , Gao Xiaofeng 
Published: December 2023

AbstractMaterial stocks have created alternative perspectives in many environmental and climate studies. Their significance nonetheless may be under-explored, partially due to scarcity of more precise, timely and higher-resolution information. To address this limitation, our present study developed a gridded material stocks dataset for China in Year 2000 and 2020, by examining the geographical distribution and geometric configurations of the human-made stock-containing environment. The stocks of twelve materials embodied in five end-use sectors and 104 products and constructions were assessed at a resolution of 1 × 1 km grid. Material intensity in each product or construction component was carefully evaluated and tagged with its geometric conformation. The gridded stocks aggregately are consistent with the stock estimation across 337 prefectures and municipalities. The reliability of our assessment was also validated by previous studies from national, regional, to grid levels. This gridded mapping of material stocks may offer insights for urban-rural disparities, urban mining opportunity, and climate and natural disaster resilience.
SARS-CoV-2 specific sIgA in saliva increases after disease-related video stimulation
Authors: Keller Judith K. , Dulovic Alex , Gruber Jens , Griesbaum Johanna , Schneiderhan-Marra Nicole , Wülfing Clemens , Kruse Jana , Hartmann Annika , Diekhof Esther K. 
Published: December 2023

AbstractSecretory immunoglobulin A (sIgA) in saliva is the most important immunoglobulin fighting pathogens in the respiratory tract and may thus play a role in preventing SARS-CoV-2 infections. To gain a better understanding of the plasticity in the mucosal antibody, we investigated the proactive change in secretion of salivary SARS-CoV-2-specific sIgA in 45 vaccinated and/or previously infected, generally healthy persons (18 to 35 years, 22 women). Participants were exposed to a disease video displaying humans with several respiratory symptoms typical for COVID-19 in realistic situations of increased contagion risk. The disease video triggered an increase in spike-specific sIgA, which was absent after a similar control video with healthy people. The increase further correlated inversely with revulsion and aversive feelings while watching sick people. In contrast, the receptor binding domain-specific sIgA did not increase after the disease video. This may indicate differential roles of the two salivary antibodies in response to predictors of airborne contagion. The observed plasticity of spike-specific salivary antibody release after visual simulation of enhanced contagion risk suggests a role in immune exclusion.
Three-way group decisions using evidence theory under hesitant fuzzy linguistic environment
Authors: Ding Wenke , Li Xingchen , Shen Xiajiong 
Published: December 2023

AbstractIn the actual decision-making process, there will be situations where decision-makers with hesitant attitudes have difficulties in evaluating alternatives numerically, and hesitant fuzzy linguistic term sets can provide decision-makers with an effective way to describe hesitancy in linguistic terms. In multi-attribute group decision-making, each decision maker typically holds different preferences. If the variation in decision makers’ assessment weights across evaluations of each attribute for every alternative is not adequately accounted for, it can result in a problem of coarse-grained calculations, leading to information loss. Additionally, the three-way decision model faces significant challenges in information fusion within the context of the hesitant fuzzy linguistic environment. Therefore, we propose a new three-way decision-making model under the hesitant fuzzy linguistic environment. The model obtains the confidence of different decision makers in attribute evaluations through the fusion of D-S evidence theory, and can perform more fine-grained fusion calculations on the evaluation information of different decision makers. In addition, the model considers the cost function of each alternative in different decision-making actions under hesitant fuzzy linguistic environment, calculates the two thresholds of each alternative in the three-way decision model, and derives the decision rules. The effectiveness of the model is verified through a numerical example and two comparative experiments, therefore, the model can be applied in intelligent classification or recommendation systems of hesitant fuzzy linguistic information systems.
Neural effects of TMS trains on the human prefrontal cortex
Authors: Ross Jessica M. , Cline Christopher C. , Sarkar Manjima , Truong Jade , Keller Corey J. 
Published: December 2023

AbstractHow does a train of TMS pulses modify neural activity in humans? Despite adoption of repetitive TMS (rTMS) for the treatment of neuropsychiatric disorders, we still do not understand how rTMS changes the human brain. This limited understanding stems in part from a lack of methods for noninvasively measuring the neural effects of a single TMS train—a fundamental building block of treatment—as well as the cumulative effects of consecutive TMS trains. Gaining this understanding would provide foundational knowledge to guide the next generation of treatments. Here, to overcome this limitation, we developed methods to noninvasively measure causal and acute changes in cortical excitability and evaluated this neural response to single and sequential TMS trains. In 16 healthy adults, standard 10 Hz trains were applied to the dorsolateral prefrontal cortex in a randomized, sham-controlled, event-related design and changes were assessed based on the TMS-evoked potential (TEP), a measure of cortical excitability. We hypothesized that single TMS trains would induce changes in the local TEP amplitude and that those changes would accumulate across sequential trains, but primary analyses did not indicate evidence in support of either of these hypotheses. Exploratory analyses demonstrated non-local neural changes in sensor and source space and local neural changes in phase and source space. Together these results suggest that single and sequential TMS trains may not be sufficient to modulate local cortical excitability indexed by typical TEP amplitude metrics but may cause neural changes that can be detected outside the stimulation area or using phase or source space metrics. This work should be contextualized as methods development for the monitoring of transient noninvasive neural changes during rTMS and contributes to a growing understanding of the neural effects of rTMS.
Understanding the value of biobank attributes to researchers using a conjoint experiment
Authors: Batheja Deepshikha , Goel Srishti , Fransman Warren , Mantsoki Anna , Ongarello Stefano , Laxminarayan Ramanan 
Published: December 2023

AbstractBiobanks are important in biomedical and public health research, and future healthcare research relies on their strength and capacity. However, there are financial challenges related to the operation of commercial biobanks and concerns around the commercialization of biobanks. Non-commercial biobanks depend on grant funding to operate and could be valuable to researchers if they can enable access to quality specimens at lower costs. The objective of this study is to estimate the value of specific biobank attributes. We used a rating-based conjoint experiment approach to study how researchers valued handling fee, access, quality, characterization, breadth of consent, access to key endemics, and time taken to fulfil requests. We found that researchers placed the greatest relative importance on the quality of specimens (26%), followed by the characterization of specimens (21%). Researchers with prior experience purchasing biological samples also valued access to key endemic in-country sites (11.6%) and low handling fees (5.5%) in biobanks.
Ecosystem service evaluation based on local knowledge of residents using spatial text-mining
Authors: Lee Jae-hyuck , Ahn SoEun 
Published: December 2023

AbstractThis study aims to evaluate the ecosystem services of Upo wetland, one of the best-known Ramsar sites in Korea, reflecting the characteristics of the ecological assets and local knowledges in the area. Application of spatial text-mining begins with collecting local perceptions and knowledge of residents on the 17 ecological assets of Upo site and surrounding area. Our results identified five important ecosystem services: flood control during heavy rainfall, water purification by aquatic plants, cultural and natural heritages, agricultural products and water provision for crop cultivation. GIS created a map where these ecosystem services were linked to the locations of 17 ecological assets. This map showed which ecosystem service is associated with particular ecological assets and their characteristics from residents’ perspectives. Mapping local knowledge using the spatial text-mining is able to identify multi-functional bases which provide various ecosystem services in the same location simultaneously. Identification of multi-functional bases can provide information for local government to design an effective and comprehensive management plan considering physical-cultural geography of ecosystem services.