bluuebunny/crossref_metadata_2025 huggingface dataset:
Understanding the potential of sustainability turn in farming: review of sociotechnical adoption factors of agri-environmental cropping practices
Authors: Adamsone-Fiskovica Anda , Grivins Mikelis
Published: May 2024

While farming practices such as intercropping, cover cropping, and green manuring are promoted as contributors to environment-friendly agriculture by balancing agricultural production with environmental sustainability, their uptake by farmers has still been limited. This paper provides a holistic global view of the adoption factors of such agri-environmental cropping practices based on a systematic literature review of 53 international peer-reviewed articles. Qualitative analysis of the reviewed studies shows that adoption factors explored by researchers can be categorized along nine thematic groups (sociodemographic characteristics, socioeconomic/financial conditions, environmental conditions, tangible assets and inventory, pre-existing farm practices, agrotechnical aspects of the practice, public support instruments, information and knowledge resources, community dynamics) and two transversal dimensions (generic and practice-specific attitudes), with an additional differentiation of micro- and macro-levels within the former. While many individual factors across the various groups and dimensions are highly context sensitive in terms of their impact on practice adoption, the analysis also identifies a set of factors that demonstrate common trends across the studies. The offered holistic conceptualization and analysis of the adoption factors of the reviewed set of practices contribute to a more comprehensive understanding of the broader potential impact pathways in the farmer reorientation toward sustainable crop production.
Farmers’ resilience to climate change through the circular economy and sustainable agriculture: a review from developed and developing countries
Authors: Hilmi Yahya Shafiyuddin , Tóth József , Gabnai Zoltán , Király Gábor , Temesi Ágoston
Published: May 2024

Farmers struggle to combat uncertain climate issues while encountering pressure on conventional farming practices that lead to carbon emissions, water and soil pollution, and other environmental harms. A growing body of literature investigated circular economy and sustainable practices to support environmental-friendly agriculture activities while providing opportunities for farmers to improve their farm income. Therefore, a study synthesizing previous literature while identifying actual policy to boost farmers’ implementation of sustainable agriculture is worthwhile. Using the Systematic Literature Review analysis, this paper aims to identify farmers’ views on climate change adaptation and mitigation, challenges in implementing circular economy and sustainable practices, and policies to support farmers’ transition toward sustainable agriculture in developed and developing countries. We found that (1) farmers’ awareness of climate change, knowledge and skills are prominent for adapting and mitigating climate change in both types of countries, (2) farmland size, risks of income loss, and training and extension services influenced farmers’ adaptation and mitigation strategies for climate change in developing countries, (3) farmers in both types of countries experienced uncertainty in economic profits and legislative issues when adopting sustainable practices, while farmers in developing countries issued significant up-front expenses to acquire technology to adopt sustainable practices, (4) financial access and incentives through policy can be valuable to develop sustainable livelihoods, especially for farm households.
TomoNet: A streamlined cryogenic electron tomography software pipeline with automatic particle picking on flexible lattices
Authors: Wang Hui , Liao Shiqing , Yu Xinye , Zhang Jiayan , Zhou Z. Hong
Published: May 2024

Cryogenic electron tomography (cryoET) is capable of determining in situ biological structures of molecular complexes at near-atomic resolution by averaging half a million subtomograms. While abundant complexes/particles are often clustered in arrays, precisely locating and seamlessly averaging such particles across many tomograms present major challenges. Here, we developed TomoNet, a software package with a modern graphical user interface to carry out the entire pipeline of cryoET and subtomogram averaging to achieve high resolution. TomoNet features built-in automatic particle picking and three-dimensional (3D) classification functions and integrates commonly used packages to streamline high-resolution subtomogram averaging for structures in 1D, 2D, or 3D arrays. Automatic particle picking is accomplished in two complementary ways: one based on template matching and the other using deep learning. TomoNet’s hierarchical file organization and visual display facilitate efficient data management as required for large cryoET datasets. Applications of TomoNet to three types of datasets demonstrate its capability of efficient and accurate particle picking on flexible and imperfect lattices to obtain high-resolution 3D biological structures: virus-like particles, bacterial surface layers within cellular lamellae, and membranes decorated with nuclear egress protein complexes. These results demonstrate TomoNet’s potential for broad applications to various cryoET projects targeting high-resolution in situ structures.
Declining Tradeoff Between Resistance and Resilience of Ecosystems to Drought
Authors: Yao Ying , Liu Yanxu , Song Jiaxi , Tao Shengli , Li Yan , Wu Tianjing , Wang Yijia , Wang Shuai , Fu Bojie
Published: May 2024

Resistance and resilience are widely used to characterize ecosystem drought stability. Tradeoff between resistance and resilience have been reported, but its long‐term trends remain uncertain at global scale. Based on remotely sensed vegetation indices, we assessed the spatiotemporal dynamics of drought resistance and resilience. Result revealed that there was a significant decline in the tradeoff between resistance and resilience, corresponding to a substantial increase in the proportion of areas with high resistance‐high resilience or low resistance‐low resilience. In the South Sahel, South Africa and Central China, the increased precipitation and vegetation coverage contribute to enhanced drought stability constructed by resistance and resilience; while rising temperature, decreased water availability and deforestation lead to declined stability in northeastern North America, South America and the Congo region. Increases in the areas with low resistance‐low resilience resulting from declining tradeoffs warn of increased regional ecosystem vulnerability.
AML/T cell interactomics uncover correlates of patient outcomes and the key role of ICAM1 in T cell killing of AML
Authors: Sayitoglu Ece Canan , Luca Bogdan A. , Boss Allison Paige , Thomas Benjamin Craig , Freeborn Robert Arthur , Uyeda Molly Javier , Chen Pauline Ping , Nakauchi Yusuke , Waichler Colin , Lacayo Norman , Bacchetta Rosa , Majeti Ravindra , Gentles Andrew J. , Cepika Alma-Martina , Roncarolo Maria Grazia
Published: May 2024

T cells are important for the control of acute myeloid leukemia (AML), a common and often deadly malignancy. We observed that some AML patient samples are resistant to killing by human-engineered cytotoxic CD4+ T cells. Single-cell RNA-seq of primary AML samples and CD4+ T cells before and after their interaction uncovered transcriptional programs that correlate with AML sensitivity or resistance to CD4+ T cell killing. Resistance-associated AML programs were enriched in AML patients with poor survival, and killing-resistant AML cells did not engage T cells in vitro. Killing-sensitive AML potently activated T cells before being killed, and upregulated ICAM1, a key component of the immune synapse with T cells. Without ICAM1, killing-sensitive AML became resistant to killing by primary ex vivo-isolated CD8+ T cells in vitro, and engineered CD4+ T cells in vitro and in vivo. While AML heterogeneity implies that multiple factors may determine their sensitivity to T cell killing, these data show that ICAM1 acts as an immune trigger, allowing T cell killing, and could play a role in AML patient survival in vivo.
Optimizing differential expression analysis for proteomics data via high-performing rules and ensemble inference
Authors: Peng Hui , Wang He , Kong Weijia , Li Jinyan , Goh Wilson Wen Bin
Published: May 2024

Identification of differentially expressed proteins in a proteomics workflow typically encompasses five key steps: raw data quantification, expression matrix construction, matrix normalization, missing value imputation (MVI), and differential expression analysis. The plethora of options in each step makes it challenging to identify optimal workflows that maximize the identification of differentially expressed proteins. To identify optimal workflows and their common properties, we conduct an extensive study involving 34,576 combinatoric experiments on 24 gold standard spike-in datasets. Applying frequent pattern mining techniques to top-ranked workflows, we uncover high-performing rules that demonstrate optimality has conserved properties. Via machine learning, we confirm optimal workflows are indeed predictable, with average cross-validation F1 scores and Matthew’s correlation coefficients surpassing 0.84. We introduce an ensemble inference to integrate results from individual top-performing workflows for expanding differential proteome coverage and resolve inconsistencies. Ensemble inference provides gains in pAUC (up to 4.61%) and G-mean (up to 11.14%) and facilitates effective aggregation of information across varied quantification approaches such as topN, directLFQ, MaxLFQ intensities, and spectral counts. However, further development and evaluation are needed to establish acceptable frameworks for conducting ensemble inference on multiple proteomics workflows.
Bulk transparent supramolecular glass enabled by host–guest molecular recognition
Authors: Cai Changyong , Wu Shuanggen , Zhang Yunfei , Li Fenfang , Tan Zhijian , Dong Shengyi
Published: May 2024

Supramolecular glass is a non-covalently cross-linked amorphous material that exhibits excellent optical properties and unique intrinsic structural features. Compared with artificial inorganic/organic glass, which has been extensively developed, supramolecular glass is still in the infancy stage, and itself is rarely recognized and studied thus far. Herein, we present the development of the host–guest molecular recognition motifs between methyl-β-cyclodextrin and para-hydroxybenzoic acid as the building blocks of supramolecular glass. Non-covalent polymerization resulting from the host–guest complexation and hydrogen bonding formation enables high transparency and bulk state to supramolecular glass. Various advantages, including recyclability, compatibility, and thermal processability, are associated with dynamic assembly pattern. Short-range order (host–guest complexation) and long-range disorder (three dimensional polymeric network) structures are identified simultaneously, thus demonstrating the typical structural characteristics of glass. This work provides a supramolecular strategy for constructing transparent materials from organic components.
Engineering and evaluation of FXa bypassing agents that restore hemostasis following Apixaban associated bleeding
Authors: Jankowski Wojciech , Surov Stepan S. , Hernandez Nancy E. , Rawal Atul , Battistel Marcos , Freedberg Daron , Ovanesov Mikhail V. , Sauna Zuben E.
Published: May 2024

Direct oral anticoagulants (DOACs) targeting activated factor Xa (FXa) are used to prevent or treat thromboembolic disorders. DOACs reversibly bind to FXa and inhibit its enzymatic activity. However, DOAC treatment carries the risk of anticoagulant-associated bleeding. Currently, only one specific agent, andexanet alfa, is approved to reverse the anticoagulant effects of FXa-targeting DOACs (FXaDOACs) and control life-threatening bleeding. However, because of its mechanism of action, andexanet alfa requires a cumbersome dosing schedule, and its use is associated with the risk of thrombosis. Here, we present the computational design, engineering, and evaluation of FXa-variants that exhibit anticoagulation reversal activity in the presence of FXaDOACs. Our designs demonstrate low DOAC binding affinity, retain FXa-enzymatic activity and reduce the DOAC-associated bleeding by restoring hemostasis in mice treated with apixaban. Importantly, the FXaDOACs reversal agents we designed, unlike andexanet alfa, do not inhibit TFPI, and consequently, may have a safer thrombogenic profile.
Bicontinuous RuO2 nanoreactors for acidic water oxidation
Authors: Chen Ding , Yu Ruohan , Yu Kesong , Lu Ruihu , Zhao Hongyu , Jiao Jixiang , Yao Youtao , Zhu Jiawei , Wu Jinsong , Mu Shichun
Published: May 2024

Improving activity and stability of Ruthenium (Ru)-based catalysts in acidic environments is eager to replace more expensive Iridium (Ir)-based materials as practical anode catalyst for proton-exchange membrane water electrolyzers (PEMWEs). Here, a bicontinuous nanoreactor composed of multiscale defective RuO2 nanomonomers (MD-RuO2-BN) is conceived and confirmed by three-dimensional tomograph reconstruction technology. The unique bicontinuous nanoreactor structure provides abundant active sites and rapid mass transfer capability through a cavity confinement effect. Besides, existing vacancies and grain boundaries endow MD-RuO2-BN with generous low-coordination Ru atoms and weakened Ru-O interaction, inhibiting the oxidation of lattice oxygen and dissolution of high-valence Ru. Consequently, in acidic media, the electron- and micro-structure synchronously optimized MD-RuO2-BN achieves hyper water oxidation activity (196 mV @ 10 mA cm−2) and an ultralow degradation rate of 1.2 mV h−1. A homemade PEMWE using MD-RuO2-BN as anode also conveys high water splitting performance (1.64 V @ 1 A cm−2). Theoretical calculations and in-situ Raman spectra further unveil the electronic structure of MD-RuO2-BN and the mechanism of water oxidation processes, rationalizing the enhanced performance by the synergistic effect of multiscale defects and protected active Ru sites.
Effects of C-reactive protein rapid testing and communication skills training on antibiotic prescribing for acute cough. A cluster factorial randomised controlled trial
Authors: Llor Carl , Trapero-Bertran Marta , Sisó-Almirall Antoni , Monfà Ramon , Abellana Rosa , García-Sangenís Ana , Moragas Ana , Morros Rosa
Published: May 2024

This cluster randomised clinical trial carried out in 20 primary care centres in Barcelona was aimed at assessing the effect of a continuous intervention focused on C-reactive protein (CRP) rapid testing and training in enhanced communication skills (ECS) on antibiotic consumption for adults with acute cough due to lower respiratory tract infection (LRTI). The interventions consisted of general practitioners and nurses’ use of CRP point-of-care and training in ECS separately and combined, and usual care. The primary outcomes were antibiotic consumption and variation of the quality-adjusted life years during a 6-week follow-up. The difference in the overall antibiotic prescribing between the winter seasons before and after the intervention was calculated. The sample size calculated could not be reached due to the COVID-19 outbreak. A total of 233 patients were recruited. Compared to the usual care group (56.7%) antibiotic consumption among patients assigned to professionals in the ECS group was significantly lower (33.9%, adjusted odds ratio [aOR] 0.38, 95% CI 0.15–0.94, p = 0.037), whereas patients assigned to CRP consumed 43.8% of antibiotics (aOR 0.70, 95% CI 0.29–1.68, p = 0.429) and 38.4% in the combined intervention group (aOR 0.45, 95% CI, 0.17–1.21; p = 0.112). The overall antibiotic prescribing rates in the centres receiving training were lower after the intervention compared to those assigned to usual care, with significant reductions in β-lactam rates. Patient recovery was similar in all groups. Despite the limited power due to the low number of patients included, we observed that continuous training achieved reductions in antibiotic consumption.
Scalable and unbiased sequence-informed embedding of single-cell ATAC-seq data with CellSpace
Authors: Tayyebi Zakieh , Pine Allison R. , Leslie Christina S.
Published: May 2024

Standard scATAC sequencing (scATAC-seq) analysis pipelines represent cells as sparse numeric vectors relative to an atlas of peaks or genomic tiles and consequently ignore genomic sequence information at accessible loci. Here we present CellSpace, an efficient and scalable sequence-informed embedding algorithm for scATAC-seq that learns a mapping of DNA k-mers and cells to the same space, to address this limitation. We show that CellSpace captures meaningful latent structure in scATAC-seq datasets, including cell subpopulations and developmental hierarchies, and can score transcription factor activities in single cells based on proximity to binding motifs embedded in the same space. Importantly, CellSpace implicitly mitigates batch effects arising from multiple samples, donors or assays, even when individual datasets are processed relative to different peak atlases. Thus, CellSpace provides a powerful tool for integrating and interpreting large-scale scATAC-seq compendia.
A dataset of 40’000 trees with section-wise measured stem diameter and branch volume from across Switzerland
Authors: Didion Markus , Herold Anne , Thürig Esther , Topuz Serra , Vulovic Zeljka , Abegg Meinrad , Nitzsche Jens , Stillhard Jonas , Glatthorn Jonas
Published: May 2024

Estimating growing stock is one of the main objectives of forest inventories. It refers to the stem volume of individual trees which is typically derived by models as it cannot be easily measured directly. These models are thus based on measurable tree dimensions and their parameterization depends on the available empirical data. Historically, such data were collected by measurements of tree stem sizes, which is very time- and cost-intensive. Here, we present an exceptionally large dataset with section-wise stem measurements on 40’349 felled individual trees collected on plots of the Experimental Forest Management project. It is a revised and expanded version of previously unpublished data and contains the empirically derived coarse (diameter ≥7 cm) and fine branch volume of 27’297 and 18’980, respectively, individual trees. The data were collected between 1888 and 1974 across Switzerland covering a large topographic gradient and a diverse species range and can thus support estimations and verification of volume functions also outside Switzerland including the derivation of whole tree volume in a consistent manner.
CASi: A framework for cross-timepoint analysis of single-cell RNA sequencing data
Authors: Wang Yizhuo , Flowers Christopher R. , Wang Michael , Huang Xuelin , Li Ziyi
Published: May 2024

Single-cell RNA sequencing (scRNA-seq) technology has been widely used to study the differences in gene expression at the single cell level, providing insights into the research of cell development, differentiation, and functional heterogeneity. Various pipelines and workflows of scRNA-seq analysis have been developed but few considered multi-timepoint data specifically. In this study, we develop CASi, a comprehensive framework for analyzing multiple timepoints’ scRNA-seq data, which provides users with: (1) cross-timepoint cell annotation, (2) detection of potentially novel cell types emerged over time, (3) visualization of cell population evolution, and (4) identification of temporal differentially expressed genes (tDEGs). Through comprehensive simulation studies and applications to a real multi-timepoint single cell dataset, we demonstrate the robust and favorable performance of the proposal versus existing methods serving similar purposes.
Experimental study of organic enrichment on meiofaunal diversity
Authors: Mohammad Deyaaedin A. , AL-Farga Ammar , Sami Mahmoud
Published: May 2024

The organic enrichment effects on the meiofauna and nematofauna were assessed for field sediment and other experimental ones enriched with organic matters conducted in the laboratory for 4 weeks. Also, dissolved oxygen (DO) and pH were monitored for each one. The abundance and diversity of meiofaunal groups and nematofauna varied. Strong significant correlations were found between DO and the studied items. Nematoda was the most abundant group in the field sediment and other experimental ones; their counts increased with the increase in organic enrichments and were dominated by deposit feeders. Amphipoda, Ostracoda and predator/omnivore nematodes disappeared in highly organic-enriched sediments. Changes in DO and organic enrichments might be the more attributable reasons for the alteration of the meiobenthic assemblages. The generic compositions of Nematoda provide a good indicator for environmental alterations.
Optimization of ultrasonic pretreatment and analysis of chlorogenic acid in potato leaves
Authors: Wang Xin , Gong Xianyun , Lin Binbin
Published: May 2024

Chlorogenic acid (CA) is an effective ingredient that can strengthen immunity during following the COVID-19 era. The current cost of CA is high owing to its complex purification process and low yield (approximately 2%). In this study, a one-step path orthogonal experiment was designed based on the results from Gauss calculation, which consisted of acidity, coordination, and hydrolysis in molecules. The optimized extraction conditions were 60 ℃, 60 min, 1:20 liquid ratio, and 40% ethanol in a nitrogen atmosphere controlled using a device of our own design, which led to CA yields of up to 6.35% from potato leaves. The purified CA was analyzed using high-performance liquid chromatography, thin-layer chromatography, ultraviolet–visible spectroscopy, and molecular fluorescence. This accurate and reproducible method can not only be used to obtain high yields of CA but can also be used for the quality control of active plant products and their isomers.
Development and evaluation of a lyophilization protocol for colorimetric RT-LAMP diagnostic assay for COVID-19
Authors: Prado Nayra Oliveira , Marin Anelis Maria , Lalli Larissa Araujo , Sanchuki Heloisa Bruna Soligo , Wosniaki Denise Kusma , Nardin Jeanine Marie , Morales Hugo Manoel Paz , Blanes Lucas , Zanette Dalila Luciola , Aoki Mateus Nóbrega
Published: May 2024

Molecular diagnostics involving nucleic acids (DNA and RNA) are regarded as extremely functional tools. During the 2020 global health crisis, efforts intensified to optimize the production and delivery of molecular diagnostic kits for detecting SARS-CoV-2. During this period, RT-LAMP emerged as a significant focus. However, the thermolability of the reagents used in this technique necessitates special low-temperature infrastructure for transport, storage, and conservation. These requirements limit distribution capacity and necessitate cost-increasing adaptations. Consequently, this report details the development of a lyophilization protocol for reagents in a colorimetric RT-LAMP diagnostic kit to detect SARS-CoV-2, facilitating room-temperature transport and storage. We conducted tests to identify the ideal excipients that maintain the molecular integrity of the reagents and ensure their stability during room-temperature storage and transport. The optimal condition identified involved adding 5% PEG 8000 and 75 mM trehalose to the RT-LAMP reaction, which enabled stability at room temperature for up to 28 days and yielded an analytical and diagnostic sensitivity and specificity of 83.33% and 90%, respectively, for detecting SARS-CoV-2. This study presents the results of a lyophilized colorimetric RT-LAMP COVID-19 detection assay with diagnostic sensitivity and specificity comparable to RT-qPCR, particularly in samples with high viral load.
A novel multi-task machine learning classifier for rare disease patterning using cardiac strain imaging data
Authors: Siva Nanda K. , Singh Yashbir , Hathaway Quincy A. , Sengupta Partho P. , Yanamala Naveena
Published: May 2024

To provide accurate predictions, current machine learning-based solutions require large, manually labeled training datasets. We implement persistent homology (PH), a topological tool for studying the pattern of data, to analyze echocardiography-based strain data and differentiate between rare diseases like constrictive pericarditis (CP) and restrictive cardiomyopathy (RCM). Patient population (retrospectively registered) included those presenting with heart failure due to CP (n = 51), RCM (n = 47), and patients without heart failure symptoms (n = 53). Longitudinal, radial, and circumferential strains/strain rates for left ventricular segments were processed into topological feature vectors using Machine learning PH workflow. In differentiating CP and RCM, the PH workflow model had a ROC AUC of 0.94 (Sensitivity = 92%, Specificity = 81%), compared with the GLS model AUC of 0.69 (Sensitivity = 65%, Specificity = 66%). In differentiating between all three conditions, the PH workflow model had an AUC of 0.83 (Sensitivity = 68%, Specificity = 84%), compared with the GLS model AUC of 0.68 (Sensitivity = 52% and Specificity = 76%). By employing persistent homology to differentiate the “pattern” of cardiac deformations, our machine-learning approach provides reasonable accuracy when evaluating small datasets and aids in understanding and visualizing patterns of cardiac imaging data in clinically challenging disease states.
Research on social and economic factors influencing regional mortality patterns in China
Authors: Li Tiantian , Zhang Shuyin , Li Handong
Published: May 2024

Regional population mortality correlates with regional socioeconomic development. This study aimed to identify the key socioeconomic factors influencing mortality patterns in Chinese provinces. Using data from the Seventh Population Census, we analyzed mortality patterns by gender and urban‒rural division in 31 provinces. Using a functional regression model, we assessed the influence of fourteen indicators on mortality patterns. Main findings: (1) China shows notable gender and urban‒rural mortality variations across age groups. Males generally have higher mortality than females, and rural areas experience elevated mortality rates compared to urban areas. Mortality in individuals younger than 40 years is influenced mainly by urban‒rural factors, with gender becoming more noticeable in the 40–84 age group. (2) The substantial marginal impact of socioeconomic factors on mortality patterns generally becomes evident after the age of 45, with less pronounced differences in their impact on early-life mortality patterns. (3) Various factors have age-specific impacts on mortality. Education has a negative effect on mortality in individuals aged 0–29, extending to those aged 30–59 and diminishing in older age groups. Urbanization positively influences the probability of death in individuals aged 45–54 years, while the impact of traffic accidents increases with age. Among elderly people, the effect of socioeconomic variables is smaller, highlighting the intricate and heterogeneous nature of these influences and acknowledging certain limitations.
Computational study of diffraction image formation from XFEL irradiated single ribosome molecule
Authors: Stransky Michal , E Juncheng , Jurek Zoltan , Santra Robin , Bean Richard , Ziaja Beata , Mancuso Adrian P.
Published: May 2024

Single particle imaging at atomic resolution is perhaps one of the most desired goals for ultrafast X-ray science with X-ray free-electron lasers. Such a capability would create great opportunity within the biological sciences, as high-resolution structural information of biosamples that may not crystallize is essential for many research areas therein. In this paper, we report on a comprehensive computational study of diffraction image formation during single particle imaging of a macromolecule, containing over one hundred thousand non-hydrogen atoms. For this study, we use a dedicated simulation framework, SIMEX, available at the European XFEL facility. Our results demonstrate the full feasibility of computational single-particle imaging studies for biological samples of realistic size. This finding is important as it shows that the SIMEX platform can be used for simulations to inform relevant single-particle-imaging experiments and help to establish optimal parameters for these experiments. This will enable more focused and more efficient single-particle-imaging experiments at XFEL facilities, making the best use of the resource-intensive XFEL operation.
Adaptive recognition of machining features in sheet metal parts based on a graph class-incremental learning strategy
Authors: Ma Liuhuan , Yang Jiong
Published: May 2024

The integration of computer-aided design (CAD), computer-aided process planning (CAPP), and computer-aided manufacturing (CAM) systems is significantly enhanced by employing deep learning-based automatic feature recognition (AFR) methods. These methods outperform traditional, rule-based approaches, particularly in handling the complexities of intersecting features. However, existing deep learning-based AFR methods face two major challenges. The initial challenge stems from the frequent utilization of voxelized or point-cloud representations of CAD models, resulting in the unfortunate loss of valuable geometric and topological information inherent in original Boundary representation (B-Rep) models. The second challenge involves the limitation of supervised deep learning methods in identifying machining features that are not present in the predefined dataset. This constraint renders them suboptimal for the continually evolving datasets of real industrial scenarios. To address the first challenge, this study introduces a graph-structured language, Multidimensional Attributed Face-Edge Graph (maFEG), crafted to encapsulate the intricate geometric and topological details of CAD models. Furthermore, a graph neural network, Sheet-metalNet, is proposed for the efficient learning and interpretation of maFEGs. To tackle the second challenge, a three-component incremental learning strategy is proposed: an initial phase of pre-training and fine-tuning, a prototype sampling-based replay, and a stage employing knowledge distillation for parameter regularization. The effectiveness of Sheet-metalNet and its complementary incremental learning strategy is evaluated using the open-source MFCAD++ dataset and the newly created SMCAD dataset. Experimental results show that Sheet-metalNet surpasses state-of-the-art AFR methods in machining feature recognition accuracy. Moreover, Sheet-metalNet demonstrates adaptability to dynamic dataset changes, maintaining high performance when encountering newly introduced features, thanks to its innovative incremental learning strategy.
Impact of blocking layers based on TiO2 and ZnO prepared via direct current reactive magnetron sputtering on DSSC solar cells
Authors: Sibiński Maciej , Sawicka-Chudy Paulina , Wisz Grzegorz , Gnida Paweł , Schab-Balcerzak Ewa , Wal Andrzej , Yavorskyi Rostyslav , Cholewa Marian
Published: May 2024

The optimization of dye-sensitized solar cells (DSSCs) technology towards suppressing charge recombination between the contact and the electron transport layer is a key factor in achieving high conversion efficiency and the successful commercialization of this type of product. An important aspect of the DSSC structure is the front blocking layer (BL): optimizing this component may increase the efficiency of photoelectron transfer from the dye to the semiconductor by reduction charge recombination at the TiO2/electrolyte and FTO/electrolyte interfaces. In this paper, a series of blocking layer variants, based on TiO2 and ZnO:TiO2, were obtained using the reactive magnetron sputtering method. Material composition, structure and layer thickness were referred to each process parameters. Complete DSSCs with structure FTO/BL/m-TiO2@N719/ EL-HSE/Pt/FTO were obtained on such bases. In the final results, verification of opto-electrical parameters of these cells were tested and used for the conclusions on the optimal blocking layer composition. As the conclusion, application of blocking layer consists of neat TiO2 resulted in improvement of device efficiency. It should be noted that for TiO2:ZnO/CuxO and TiO2/CuxO cells, higher efficiencies were also achieved when pure TiO2 was used as window layer. Additionally it was proven that the admixture of ZnO phase inspires Voc and FF growth, but is overall unfavorable compared to pristine TiO2 blocking layer and the reference cell, according to the final cell efficiency.
High fat diet ameliorates mitochondrial cardiomyopathy in CHCHD10 mutant mice
Authors: Southwell Nneka , Manzo Onorina , Bacman Sandra , Zhao Dazhi , Sayles Nicole M , Dash Jalia , Fujita Keigo , D’Aurelio Marilena , Di Lorenzo Annarita , Manfredi Giovanni , Kawamata Hibiki
Published: May 2024

Mutations in CHCHD10, a mitochondrial protein with undefined functions, are associated with autosomal dominant mitochondrial diseases. Chchd10 knock-in mice harboring a heterozygous S55L mutation (equivalent to human pathogenic S59L) develop a fatal mitochondrial cardiomyopathy caused by CHCHD10 aggregation and proteotoxic mitochondrial integrated stress response (mtISR). In mutant hearts, mtISR is accompanied by a metabolic rewiring characterized by increased reliance on glycolysis rather than fatty acid oxidation. To counteract this metabolic rewiring, heterozygous S55L mice were subjected to chronic high-fat diet (HFD) to decrease insulin sensitivity and glucose uptake and enhance fatty acid utilization in the heart. HFD ameliorated the ventricular dysfunction of mutant hearts and significantly extended the survival of mutant female mice affected by severe pregnancy-induced cardiomyopathy. Gene expression profiles confirmed that HFD increased fatty acid utilization and ameliorated cardiomyopathy markers. Importantly, HFD also decreased accumulation of aggregated CHCHD10 in the S55L heart, suggesting activation of quality control mechanisms. Overall, our findings indicate that metabolic therapy can be effective in mitochondrial cardiomyopathies associated with proteotoxic stress.
Electrochemically-driven actuators: from materials to mechanisms and from performance to applications
Authors: Yang Lixue , Zhang Yiyao , Cai Wenting , Tan Junlong , Hansen Heather , Wang Hongzhi , Chen Yan , Zhu Meifang , Mu Jiuke
Published: May 2024

This review aims to capture the current state of electrochemical actuators and set a trajectory for future innovation in this field.
Inoculation of chromium-tolerant bacterium LBA108 to enhance resistance in radish (Raphanus sativus L.) and combined remediation of chromium-contaminated soil
Authors: Zhang Hehe , Wang Hui , Tan Aobo , Zhang Longfei , Yao Hanyue , You Xiaoyan , Chen Zhi
Published: May 2024

Inoculation of chromium-tolerant bacterium LBA108 to enhance resistance in radish (Raphanus sativus L.) and combined remediation of chromium-contaminated soil.
OMEF biochip for evaluating red blood cell deformability using dielectrophoresis as a diagnostic tool for type 2 diabetes mellitus
Authors: Ali Dima Samer , Sofela Samuel O. , Deliorman Muhammedin , Sukumar Pavithra , Abdulhamid Ma-sum , Yakubu Sherifa , Rooney Ciara , Garrod Ryan , Menachery Anoop , Hijazi Rabih , Saadi Hussein , Qasaimeh Mohammad A.
Published: May 2024

OMEF biochip is open-micro-electro-fluidic technology for stretching of single red blood cells (RBCs) based on dielectrophoresis and electrodeformation. The biochip assesses RBCs' deformability in type 2 diabetes mellitus as an effective diagnostic tool.
A bimodal time-gated luminescence–magnetic resonance imaging nanoprobe based on a europium(iii) complex anchored on BSA-coated MnO2 nanosheets for highly selective detection of H2O2
Authors: Song Bo , Wang Ziyao , Yan Huinan , Zhang Xinyue , Liu Qi , Luo Jiawen , Yuan Jingli
Published: May 2024

A novel nanocomposite, [Eu(BTD)3(DPBT)]–BSA@MnO2, is reported to serve as an effective nanoprobe for bimodal time-gated luminescence (TGL) and magnetic resonance (MR) imaging of H2O2in vitro and in vivo.
A hydrolytically stable complexant for minor An separation from Ln in process relevant diluents
Authors: Fletcher Lesta S. , Tedder Mariah L. , Olayiwola Samiat O. , Carrick Jesse D.
Published: May 2024

A complexant for chemoselective separation of 241Am3+ from 154Eu3+ in simulated high-level waste is reported. The data advances complexant-based minor An extractions with excellent solubility in process-relevant diluents, high distribution, and good separation.
Iterative click reactions using trivalent platforms for sequential molecular assembly
Authors: Orimoto Gaku , Yoshida Suguru
Published: May 2024

A facile synthesis of multi(triazole)s by iterative click reactions is disclosed. Diverse multi(triazole)-type mid-molecules can be synthesized easily from readily available modules through good chemoselective click reactions.
Electrochemically enabled (3+2) cycloaddition of unbiased alkenes and β-dicarbonyls
Authors: Suryawanshi Sharad M. , Sahoo Suman , Shaligram Parth S. , Manna Narugopal , Samanta Ramesh C.
Published: May 2024

A fluorinated porous carbon electrode and Co-salen catalyst reveal (3+2) cycloaddition of unbiased alkenes and β-dicarbonyls to get inaccessible dihydrofurans. It requires no stabilizing group and works for both cyclic and acyclic β-dicarbonyls.
Deville rebooted – practical N2O5 synthesis
Authors: Edwards Lee E. , Kariuki Benson M. , Didsbury Matthew , Jones Christopher D. , Wirth Thomas
Published: May 2024

UV irradiation is used for the efficient production of dinitrogen pentoxide.
PtAu alloying-modulated hydroxyl and substrate adsorption for glycerol electrooxidation to C3 products
Authors: Li Yan , Wei Xinfa , Pan Rui , Wang Yue , Luo Juanjuan , Li Lanxin , Chen Lisong , Shi Jianlin
Published: May 2024

A honeycomb-like PtAu alloy catalyst has been developed to modulate the adsorption capacity of OH− species and adsorption configuration of glycerol on the catalyst surface for electrocatalytic glycerol upgrading of C3 chemicals.
Alleviating nanostructural phase impurities enhances the optoelectronic properties, device performance and stability of cesium-formamidinium metal–halide perovskites
Authors: Othman Mostafa , Jeangros Quentin , Jacobs Daniel A. , Futscher Moritz H. , Zeiske Stefan , Armin Ardalan , Jaffrès Anaël , Kuba Austin G. , Chernyshov Dmitry , Jenatsch Sandra , Züfle Simon , Ruhstaller Beat , Tabean Saba , Wirtz Tom , Eswara Santhana , Zhao Jiashang , Savenije Tom J. , Ballif Christophe , Wolff Christian M. , Hessler-Wyser Aïcha
Published: May 2024

The impact of the composition of the A-site cations on the intra-domain defect density in cesium-formamidinium perovskite formulations is modulated via alloying.
Ultrahigh voltage direct current quasi-tribovoltaic nanogenerator by switchable tribo-bias induction and deposited charge extraction
Authors: Zhang Xuemei , Ren Dahu , Wu Huiyuan , Wang Jian , Li Xiaochuan , Yang Huake , Li Qianying , Yang Qianxi , Zhu Jinrong , Xi Yi
Published: May 2024

An inventive semiconductor-free design of insulator-based quasi-TVNG (I-Q-TVNG) ingeniously utilizes the rich tribo-charges on the insulator to construct strong tribo-bias to attain remarkable performance in voltage, power, stability, and durability.
Biological fate, functional properties, and design strategies for oral delivery systems for cinnamaldehyde
Authors: Weng Xiaolan , Ho Chi-Tang , Lu Muwen
Published: May 2024

The bio-efficacy and delivery systems of cinnamaldehyde and the underlying mechanisms are summarized and evaluated.
Protection effect of lutein-loaded Pickering emulsion prepared via ultrasound-assisted Maillard reaction conjugates on dry age-related macular degeneration
Authors: Liu Kangjing , Li Yu , Zhong Xu , Hou Yitong , Fei Siyuan , Chen Entao , Tan Mingqian
Published: May 2024

Age-related macular degeneration (AMD) is a prominent cause of vision loss among the elderly, and the treatment options for dry AMD (dAMD) are severely limited.
Efficient preparation of fluorescent nanomaterials derived from chitin via a modification-first strategy assisted by click chemistry
Authors: Liu Yingyin , Li Bowen , Xu Chaoqun , Shi Zicong , Liu Liang , Fan Yimin , Yu Juan
Published: May 2024

Efficient preparation of FChN by a modification-first strategy based on the amino–alkyne/hydroxyl–alkyne click reaction of basic partially deacetylated chitin.
Laser-induced graphene-based digital microfluidics (gDMF): a versatile platform with sub-one-dollar cost
Authors: Liu Ke , He Yu , Lu Zefan , Xu Qiudi , Wang Lan , Liu Zhongxuan , Khou Jeremy , Ye Jiaming , Liu Chong , Zhang Tao
Published: May 2024

Laser-induced graphene-based digital microfluidics (gDMF) offer an easy-to-access, highly versatile, and low-cost platform for POCT application.
Ion transport induced room-temperature insulator–metal transition in single-crystalline Cu2Se
Authors: Suleiman Abdulsalam Aji , Parsi Amir , Razeghi Mohammadali , Başçı Uğur , Oh Saeyoung , Pehlivanoğlu Doruk , Jeong Hu Young , Kang Kibum , Kasırga T. Serkan
Published: May 2024

Cu2Se single crystals are synthesized to demonstrate that Cu ion vacancies can create an order within the crystals which leads to a metal–insulator transition, accompanied by six-orders of magnitude resistivity and optical contrast change.
Stretchable anti-freeze deep eutectic solvent (DES) gels for low-temperature wearable soft sensors
Authors: Hu Xiaohan , Zhao Yinan , Pu Lisha , Chu Xiaoxiao , Sun Changmei , Liu Huizhong
Published: May 2024

Eutectogels with excellent low-temperature sensing performance were prepared using methacrylic acid and pyrrole as monomers and deep eutectic solvents as solvents, capable of stable motion sensing at −20 °C for a long time.
Circularly polarized luminescence activity in the near infrared spectral region of a water-soluble ytterbium(iii) complex containing a conjugated chromophoric ligand
Authors: Mizzoni Silvia , Sickinger Annika , Ruggieri Silvia , Riobé François , Guy Laure , Maury Olivier , Baguenard Bruno , Bensalah-Ledoux Amina , Guyot Yannick , Guy Stéphan , Sanadar Martina , Melchior Andrea , Piccinelli Fabio
Published: May 2024

A chiral Yb(iii) complex bearing a conjugated chromophoric ligand exhibits potential as NIR-to-NIR chiroptical probe for biological purposes.
Antimicrobial nanocomposite coatings for rapid intervention against catheter-associated urinary tract infections
Authors: Patra Dipanjana , Ghosh Sreyan , Mukherjee Sudip , Acharya Yash , Mukherjee Riya , Haldar Jayanta
Published: May 2024

Catheter-associated urinary tract infections (CAUTIs) pose a significant challenge in hospital settings.
Bridging of poly(acetylene)s and PEG-modified poly(olefin)s through ring-opening metathesis copolymerization (ROMCP)
Authors: Kumar Podiyanachari Santhosh , Barłóg Maciej , Al-Hashimi Mohammed , Bazzi Hassan S.
Published: May 2024

Amphiphilic copolymers of highly conjugated poly(acetylene)s and PEG–PDI-incorporating poly(olefin)s have been synthesized and analyzed to study their amphiphilic properties, H-type aggregation processes and self-assembling behavior.
Extraction of the intrinsic rate constant for a photocyclization reaction in capillary microreactors using a simplified reactor model
Authors: Li Jun , Šimek Tosino Helena , Ladewig Bradley P. , Jung Nicole , Bräse Stefan , Dittmeyer Roland
Published: May 2024

Extraction of the intrinsic rate constants for a photocyclization reaction from a simplified reactor model.
Optimizing testing feedback in introductory chemistry: a multi-treatment study exploring varying levels of assessment feedback and subsequent performance
Authors: Murphy Kristen L. , Schreurs David G. , Teichert Melonie A. , Luxford Cynthia J. , Trate Jaclyn M. , Harshmann Jordan T. , Schneider Jamie L.
Published: May 2024

Providing students with feedback on their performance is a critical part of enhancing student learning in chemistry and is often integrated into homework assignments, quizzes, and exams. However, not all feedback is created equal, and the type of feedback the student receives can dramatically alter the utility of the feedback to reinforce correct processes and assist in correcting incorrect processes. This work seeks to establish a ranking of how eleven different types of testing feedback affected student retention or growth in performance on multiple-choice general chemistry questions. These feedback methods ranged from simple noncorrective feedback to more complex and engaging elaborative feedback. A test-retest model was used with a one-week gap between the initial test and following test in general chemistry I. Data collection took place at multiple institutions over multiple years. Data analysis used four distinct grading schemes to estimate student performance. These grading schemes included dichotomous scoring, two polytomous scoring techniques, and the use of item response theory to estimate students’ true score. Data were modeled using hierarchical linear modeling which was set up to control for any differences in initial abilities and to determine the growth in performance associated with each treatment. Results indicated that when delayed elaborative feedback was paired with students being asked to recall/rework the problem, the largest student growth was observed. To dive deeper into student growth, both the differences in specific content-area improvement and the ability levels of students who improved the most were analyzed.
Surface mobility gradient and emergent facilitation in glassy films
Authors: Zhai Qiang , Gao Xin-Yuan , Lee Chun-Shing , Ong Chin-Yuan , Yan Ke , Deng Hai-Yao , Yang Sen , Lam Chi-Hang
Published: May 2024

A distinguishable-particle lattice model of film geometry is proposed and a crossover from bulk-viscosity dominated flow to surface dominated flow is demonstrated.
Possibilities and limitations of convolutional neural network machine learning architectures in the characterisation of achiral orthogonal smectic liquid crystals
Authors: Betts Rebecca , Dierking Ingo
Published: May 2024

An investigation of the phase sequence isotropic-fluid smectic-hexatic smectic-soft crystal–crystalline reveals the potential and limitations of convolutional neural networks applied to the classification of achiral orthogonal liquid crystal phases.
Upcycling mixed-material waste with elemental sulfur: applications to plant oil, unseparated biomass, and raw post-consumer food waste
Authors: Guinati Bárbara G. S. , Sauceda Oloño Perla Y. , Kapuge Dona Nawoda L. , Derr Katelyn M. , Wijeyatunga Shalini K. , Tennyson Andrew G. , Smith Rhett C.
Published: May 2024

Herein we report the preparation of high sulfur-content materials (HSMs) using food waste and elemental sulfur.
Performance enhancement mechanisms of calcium-based thermochemical energy storage compounds: insights from first-principles and experimental investigations
Authors: Guo S. J. , Tian X. K. , Yan J. , Ju S. H. , Zhao C. Y.
Published: May 2024

This work establishes a structure–performance relationship between the atomic parameters of metals and the performance of modified calcium-based TCES materials.
Semiconductor-cluster-loaded ionic covalent organic nanosheets with enhanced photocatalytic reduction reactivity of nitroarenes
Authors: Zhang Jing-Ni , Liu Jia-Xing , Ma Hao , Luo Xiao , Han Cheng-Kun , Zhou Rui , Yuan Shang-Fu , Li Dong-Sheng , Wu Tao
Published: May 2024

A composite catalyst, developed by electrostatic self-assembly of anionic semiconductor clusters onto 2D cationic CONs, boosts photocatalytic selective nitroarene reduction through a strong internal electric field and the II-scheme mechanism.
Bimetallic metal–organic framework: an efficient electrocatalyst for bromine-based flow batteries
Authors: Naresh Raghupandiyan , Satchidhanandam Kalaiarasi , Ilancheran Kaushek Rahul , Ambrose Bebin , Kathiresan Murugavel , Ragupathy P.
Published: May 2024

A newly designed NiCo-MOF@GF electrocatalyst greatly enhanced the kinetics of a Br2/2Br− redox couple, resulting in a higher voltaic efficiency (85.1%) and an overall improvement in the performance of Zn–Br2 flow cells.