jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Gilbert S. Omenn | Sandra Orchard | Lydie Lane | Cecilia Lindskog | Charles Pineau | Christopher M. Overall | Bogdan Budnik | Jonathan M. Mudge | Nicolle H. Packer | Susan T. Weintraub | Michael H. A. Roehrl | Edouard C. Nice | Tiannan Guo | Jennifer E. Van Eyk | Uwe Völker | Gong Zhang | Nuno Bandeira | Ruedi Aebersold | Robert L. Moritz | Eric W. Deutsch
Source: Journal of Proteome Research (review, 2024-11-08)
Field: Chemistry — Spectroscopy

The 2024 Report on the Human Proteome from the HUPO Human Proteome Project The Human Proteome Project (HPP), the flagship initiative of the Human Proteome Organization (HUPO), has pursued two goals: (1) to credibly identify at least one isoform of every protein-coding gene and (2) to make proteomics an integral part of multiomics studies of human health and disease. The past year has seen major transitions for the HPP. neXtProt was retired as the official HPP knowledge base, UniProtKB became the reference proteome knowledge base, and Ensembl-GENCODE provides the reference protein target list. A function evidence FE1-5 scoring system has been developed for functional annotation of proteins, parallel to the PE1-5 UniProtKB/neXtProt scheme for evidence of protein expression. This report includes updates from neXtProt (version 2023-09) and UniProtKB release 2024_04, with protein expression detected (PE1) for 18138 of the 19411 GENCODE protein-coding genes (93%). The number of non-PE1 proteins ("missing proteins") is now 1273. The transition to GENCODE is a net reduction of 367 proteins (19,411 PE1-5 instead of 19,778 PE1-4 last year in neXtProt). We include reports from the Biology and Disease-driven HPP, the Human Protein Atlas, and the HPP Grand Challenge Project. We expect the new Functional Evidence FE1-5 scheme to energize the Grand Challenge Project for functional annotation of human proteins throughout the global proteomics community, including π-HuB in China. Human proteome project ; Proteome ; Human proteins ; Computational biology ; Data science ; Proteomics ; Bioinformatics ; Chemistry ; Computer science ; Biology ; Biochemistry ; Gene Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Machine Learning in Bioinformatics
Authors: Zhichao Li | Hongbin Pu | Qingyi Wei
Source: Biosensors (article, 2024-01-29)
Field: Materials Science — Materials Chemistry

Ti3C2Tx MXene-Based Fluorescent Aptasensor for Detection of Dimethoate Pesticide Dimethoate contaminants in food pose a threat to human health. Rapid and sensitive trace detection methods are required to keep food safe. In this study, a novel fluorescent aptasensor was developed for the sensitive detection of dimethoate based on carbon quantum dots labeled with double-stranded DNA (CQDs-apt-cDNA) and Ti<sub>3</sub>C<sub>2</sub>T<sub>x</sub> flakes. Under optimal conditions, the aptasensor showed a good linear range of 1 × 10<sup>-9</sup> to 5 × 10<sup>-5</sup> M for dimethoate with a coefficient of determination (R<sup>2</sup>) of 0.996. Besides, a low detection limit of 2.18 × 10<sup>-10</sup> M was obtained. The aptasensor showed high selectivity in interference samples and good reproducibility with an RSD of 3.06% (<5%) for dimethoate detection. Furthermore, the proposed aptasensor was applied to the detection of dimethoate in apple juice and tap water with satisfactory recoveries from 96.2 to 104.4%. Because of these benefits, this aptasensor has the potential and promise for detecting food contaminants in the food industry. Dimethoate ; Detection limit ; Chemistry ; Chromatography ; Reproducibility ; Pesticide ; Aptamer ; Fluorescence ; Biology ; Molecular biology ; Agronomy MXene and MAX Phase Materials ; Advanced biosensing and bioanalysis techniques ; Carbon and Quantum Dots Applications
Authors: Aysenur Iscen | Kübra Kaygisiz | Christopher V. Synatschke | Tanja Weil | Kurt Kremer
Source: Biomacromolecules (article, 2024-04-23)
Field: Materials Science — Biomaterials

Multiscale Simulations of Self-Assembling Peptides: Surface and Core Hydrophobicity Determine Fibril Stability and Amyloid Aggregation Assemblies of peptides and proteins through specific intermolecular interactions set the basis for macroscopic materials found in nature. Peptides provide easily tunable hydrogen-bonding interactions, which can lead to the formation of ordered structures such as highly stable β-sheets that can form amyloid-like supramolecular peptide nanofibrils (PNFs). PNFs are of special interest, as they could be considered as mimics of various fibrillar structures found in nature. In their ability to serve as supramolecular scaffolds, they could mimic certain features of the extracellular matrix to provide stability, interact with pathogens such as virions, and transduce signals between the outside and inside of cells. Many PNFs have been reported that reveal rich bioactivities. PNFs supporting neuronal cell growth or lentiviral gene transduction have been studied systematically, and their material properties were correlated to bioactivities. However, the impact of the structure of PNFs, their dynamics, and stabilities on their unique functions is still elusive. Herein, we provide a microscopic view of the self-assembled PNFs to unravel how the amino acid sequence of self-assembling peptides affects their secondary structure and dynamic properties of the peptides within supramolecular fibrils. Based on sequence truncation, amino acid substitution, and sequence reordering, we demonstrate that peptide-peptide aggregation propensity is critical to form bioactive β-sheet-rich structures. In contrast to previous studies, a very high peptide aggregation propensity reduces bioactivity due to intermolecular misalignment and instabilities that emerge when fibrils are in close proximity to other fibrils in solution. Our multiscale simulation approach correlates changes in biological activity back to single amino acid modifications. Understanding these relationships could lead to future material discoveries where the molecular sequence predictably determines the macroscopic properties and biological activity. In addition, our studies may provide new insights into naturally occurring amyloid fibrils in neurodegenerative diseases. Fibril ; Peptide ; Supramolecular chemistry ; Chemistry ; Biophysics ; Amyloid (mycology) ; Peptide sequence ; Hydrogen bond ; Sequence (biology) ; Intermolecular force ; Self-assembly ; Amino acid ; Crystallography ; Molecule ; Biochemistry ; Biology ; Organic chemistry Supramolecular Self-Assembly in Materials ; Protein Structure and Dynamics ; Chemical Synthesis and Analysis
Authors: Hongxin Zeng | Xuan Cong | Huifang Zhang | Sen Gong | Tianchi Zhou | Lan Wang | Haoyi Cao | Huajie Liang | Shixiong Liang | Shiqi Wang | Feng Lan | Xun Wang | Ziqiang Yang | Yaxin Zhang | Tie Jun Cui
Source: Science Advances (article, 2024-12-04)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Dynamically logical modulation for THz wave within a dual gate–controlled 2DEG metasurface High-speed logic modulation of terahertz (THz) waves is crucial for future communications, yet a technology gap persists. Here, we report a dual gate–controlled two-dimensional electronic gas logic modulation metasurface that enables symmetric and asymmetric electron distribution states through independent control of the two electron transport channels. The transition between these two states leads to various response modes in the metasurface and notably increases the diversity of the spectrum transformation, resulting in a multivalued relationship in which each output corresponds to more than one input signal, thus establishing the logical modulation. Our results demonstrate the common logical functions of AND, OR, XOR, XNOR, NOR, and NAND at different frequencies with a modulation speed faster than 250 picoseconds. This work offers a unique avenue for the high-speed, free-space logical operation of THz waves and increases the security of secure communication. XNOR gate ; Modulation (music) ; Terahertz radiation ; NAND gate ; Physics ; Logic gate ; Computer science ; Optoelectronics Metamaterials and Metasurfaces Applications ; Terahertz technology and applications ; Molecular Communication and Nanonetworks
Authors: Salah El-Hendawy | Muhammad Usman Tahir | Nasser Al-Suhaibani | Salah Elsayed | Osama Elsherbiny | Hany Elsharawy
Source: Agronomy (article, 2024-06-27)
Field: Chemistry — Analytical Chemistry

Potential of Thermal and RGB Imaging Combined with Artificial Neural Networks for Assessing Salt Tolerance of Wheat Genotypes Grown in Real-Field Conditions Developing new bread wheat varieties that can be successfully grown in saline conditions has become a pressing task for plant breeders. High-throughput phenotyping tools are crucial for this task. Proximal remote sensing is gaining popularity in breeding programs as a quick, cost-effective, and non-invasive tool to assess canopy structure and physiological traits in large genetic pools. Limited research has been conducted on the effectiveness of combining RGB and thermal imaging to assess the salt tolerance of different wheat genotypes. This study aimed to evaluate the effectiveness of combining several indices derived from thermal infrared and RGB images with artificial neural networks (ANNs) for assessing relative water content (RWC), chlorophyll a (Chla), chlorophyll b (Chlb), total chlorophyll (Chlt), and plant dry weight (PDW) of 18 recombinant inbred lines (RILs) and their 3 parents irrigated with saline water (150 mM NaCl). The results showed significant differences in various traits and indices among the tested genotypes. The normalized relative canopy temperature (NRCT) index exhibited strong correlations with RWC, Chla, Chlb, Chlt, and PDW, with R2 values ranging from 0.50 to 0.73, 0.53 to 0.76, 0.68 to 0.84, 0.68 to 0.84, and 0.52 to 0.76, respectively. Additionally, there was a strong relationship between several RGB indices and measured traits, with the highest R2 values reaching up to 0.70. The visible atmospherically resistant index (VARI), a popular index derived from RGB imaging, showed significant correlations with NRCT, RWC, Chla, Chlb, Chlt, and PDW, with R2 values ranging from 0.49 to 0.62 across two seasons. The different ANNs models demonstrated high predictive accuracy for NRCT and other measured traits, with R2 values ranging from 0.62 to 0.90 in the training dataset and from 0.46 to 0.68 in the cross-validation dataset. Thus, our study shows that integrating high-throughput digital image tools with ANN models can efficiently and non-invasively assess the salt tolerance of a large number of wheat genotypes in breeding programs. Genotype ; Salt (chemistry) ; Artificial neural network ; Field (mathematics) ; Biology ; Agronomy ; Biological system ; Botany ; Environmental science ; Artificial intelligence ; Chemistry ; Computer science ; Mathematics ; Biochemistry Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies
Authors: Hanrong Xie | Tiefeng Yang | Manyan Xie | Xijie Liang | Ziliang Fang | Yong Ye | Yue Chen | Yuming Wei | Zhen Wang | Heyuan Guan | Huihui Lu
Source: Laser & Photonics Review (article, 2024-01-10)
Field: Materials Science — Materials Chemistry

Dual‐Crossbar Configurated Bi<sub>2</sub>O<sub>2</sub>Se Device for Multiple Optoelectronic Applications Abstract Two‐dimensional (2D) materials are widely used in numerous optoelectronic devices due to their ultra‐thin dimensions and versatile surfaces. However, less attention is paid to distinguishing the light‐matter interactions along the vertical and horizontal paths within the same 2D lattice, as well as comparatively investigating the optoelectronic behaviors between the sensitive top and bottom surfaces. Here, a dual‐crossbar configured architecture is designed and constructed based on Bi 2 O 2 Se semiconductor, featuring highly compact three‐in‐one assembly, namely bottom surface horizontal (BSH), middle sandwich vertical (MSV) and top surface horizontal (TSH) devices. The MSV with nanoscale channel possesses efficient separation and transportation of the photogenerated electrons and holes, responding faster to the light stimulation and compared favorably to the BSH and TSH devices. The optoelectric behaviors of the BSH device can be regulated by the characteristics of the substrate due to closer contact. Nevertheless, the performance of the TSH device is more sensitive to the environment, such as dopant absorption and heat dispersion, thus enabling the non‐volatile photoresponse and can be employed as an artificial optoelectronic synapse. This work highlights the importance of designing the device architecture based on the intrinsic structural advantages of 2D materials, paving the way toward integrated optoelectronics. Crossbar switch ; Optoelectronics ; Materials science ; Dopant ; Vertical integration ; Computer science ; Doping ; Telecommunications 2D Materials and Applications ; Gas Sensing Nanomaterials and Sensors ; Transition Metal Oxide Nanomaterials
Authors: Wuyu Mao | Ping Dong | Wei Du | Haoxing Wu
Source: Chemical & Biomedical Imaging (article, 2024-12-23)
Field: Chemistry — Organic Chemistry

Fluorogenic Tetrazine Bioorthogonal Probes for Advanced Application in Bioimaging and Biomedicine A variety of bioorthogonal chemical tools have been developed and widely used in the study of biological phenomena in situ. Tetrazine bioorthogonal chemistry exhibits ultrafast reaction kinetics, excellent biocompatibility, and precise optical regulatory capabilities. Fluorogenic tetrazine bioorthogonal probes have achieved particularly diverse applications in bioimaging and disease diagnosis and treatment. This Viewpoint briefly introduces the characteristics and advantages of tetrazine bioorthogonal chemistry, some design strategies of fluorogenic tetrazine probes, and the status of applications of these tools to in vivo imaging, as well as disease diagnosis and treatment. Finally, we discuss challenges and propose future trends in the field of fluorogenic tetrazine probes. This Viewpoint offers insights into the development of new bioorthogonal tools for chemical biology research and for the design of new drugs. Bioorthogonal chemistry ; Tetrazine ; Nanotechnology ; Chemistry ; Combinatorial chemistry ; Computer science ; Click chemistry ; Materials science ; Organic chemistry Click Chemistry and Applications ; Monoclonal and Polyclonal Antibodies Research ; Advanced Biosensing Techniques and Applications
Authors: Stephen Taller | Yiren Chen | Rongjie Song | Wei‐Ying Chen | Andrea Jokisaari
Source: Journal of Nuclear Materials (article, 2024-09-03)
Field: Materials Science — Materials Chemistry

An approach to combine neutron and ion irradiation data to accelerate material qualification for nuclear reactors Next-generation nuclear power plants are generally characterized by higher operating temperatures, increased neutron fluences and energies, and distinct corrosive coolant environments versus the existing light water reactor fleet. Whether using existing materials in new environments, newly developed materials tailored for these environments, or new manufacturing methods, the traditional decades-long approach for materials qualification does not facilitate rapid deployment. Ion irradiation has demonstrated success in reproducing material microstructure and select property evolution resulting from neutron irradiation with three to four orders of magnitude reduction in time and cost, making it an ideal candidate for accelerated irradiation testing. Because microstructure has a large impact on bulk material properties, limited neutron irradiation data at lower damage levels can in principle be combined with accelerated ion testing results and modeling and simulation to form an accurate prediction of microstructure evolution and select properties under different neutron irradiation conditions and at higher damage levels. The objective of this work is to present a conceptual framework of specific steps to fulfill several technical challenges associated with qualifying materials for performance in radiation environments on an accelerated time frame. A brief review of the regulatory landscape for materials in nuclear environments is presented, followed by additional overviews to understand the current state of the art for correlation of materials properties across radiation environments using experimental and computational methodologies. Finally, the roles of academia, national laboratories, and industry in the advancement of this accelerated materials qualification framework are discussed as a path forward, with possible case studies presented. Nuclear engineering ; Neutron ; Irradiation ; Materials science ; Microstructure ; Computer science ; Coolant ; Process engineering ; Environmental science ; Mechanical engineering ; Nuclear physics ; Physics ; Composite material ; Engineering Nuclear Materials and Properties ; Fusion materials and technologies ; Nuclear materials and radiation effects
Authors: Zhengguo Chen | Qingyang Liu | Haoye Liu | Tianyou Wang
Source: Atmosphere (article, 2024-08-20)
Field: Materials Science — Materials Chemistry

Recent Advances in SCR Systems of Heavy-Duty Diesel Vehicles—Low-Temperature NOx Reduction Technology and Combination of SCR with Remote OBD Heavy-duty diesel vehicles are a significant source of nitrogen oxides (NOx) in the atmosphere. The Selective Catalytic Reduction (SCR) system is a primary aftertreatment device for reducing NOx emissions from heavy-duty diesel vehicles. With increasingly stringent NOx emission regulations for heavy-duty vehicles in major countries, there is a growing focus on reducing NOx emissions under low exhaust temperature conditions, as well as monitoring the conversion efficiency of the SCR system over its entire lifecycle. By reviewing relevant literature mainly from the past five years, this paper reviews the development trends and related research results of SCR technology, focusing on two main aspects: low-temperature NOx reduction technology and the combination of SCR systems with remote On-Board Diagnostics (OBD). Regarding low-temperature NOx reduction technology, the results of the review indicate that the combination of multiple catalytic shows potential for achieving high conversion efficiency across a wide temperature range; advanced SCR system arrangement can accelerate the increase in exhaust temperature within the SCR system; solid ammonium and gaseous reductants can effectively address the issue of urea not being able to be injected under low-temperature exhaust conditions. As for the combination of SCR systems with remote OBD, remote OBD can accurately assess NOx emissions from heavy-duty vehicles, but it needs algorithms to correct data and match the emission testing process required by regulations. Remote OBD systems are crucial for detecting SCR tampering, but algorithms must be developed to balance accuracy with computational efficiency. This review provides updated information on the current research status and development directions in SCR technologies, offering valuable insights for future research into advanced SCR systems. NOx ; Environmental science ; Reduction (mathematics) ; Diesel fuel ; Selective catalytic reduction ; Diesel engine ; Automotive engineering ; Chemistry ; Engineering ; Combustion ; Catalysis Catalytic Processes in Materials Science ; Vehicle emissions and performance ; Advanced Combustion Engine Technologies
Authors: Farzin Khodaveisi | Hamidreza Karami | Matin Zarei Karimpour | Marcos Rubinstein | Farhad Rachidi
Source: Scientific Reports (article, 2024-05-23)
Field: Materials Science — Materials Chemistry

Partial discharge localization in power transformer tanks using machine learning methods This paper presents a comparison of machine learning (ML) methods used for three-dimensional localization of partial discharges (PD) in a power transformer tank. The study examines ML and deep learning (DL) methods, ranging from support vector machines (SVM) to more complex approaches like convolutional neural networks (CNN). Multiple case studies are considered, each with different attributes, including sensor position, frequency content of the PD signal, and size of the transformer tank. The paper focuses on predicting the PD location in three-dimensional space using single-sensor electric field measurements. Various aspects of each method are analyzed, such as the input signal, core methodology, correlation coefficient between the predicted location and the actual location, and root mean square error (RMSE). These features are discussed and compared across the different methods. The results indicate that the CNN model exhibits superior performance in terms of location accuracy among the methods considered. Partial discharge ; Support vector machine ; Computer science ; Transformer ; Mean squared error ; Artificial intelligence ; Ranging ; Pattern recognition (psychology) ; Correlation coefficient ; Convolutional neural network ; Machine learning ; Voltage ; Mathematics ; Engineering ; Statistics ; Electrical engineering ; Telecommunications High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; Non-Destructive Testing Techniques
Authors: Michał Markiewicz | Piotr Dziurdzia | T. Skotnicki
Source: Nano Energy (article, 2024-04-01)
Field: Materials Science — Materials Chemistry

Randomly moving thermoelectric energy harvester for wearables and industrial Internet of Things Many machines generate a significant amount of waste heat, which could be used as a steady and plentiful energy source for energy-harvesting Internet of Things devices. The main component in the energy conversion subsystem of such a device is a thermoelectric generator (TEG) placed between a heat source and a heat sink. Once the TEG reaches a steady state, the electromotive force developed across it depends only on the temperature gradient. The aim of this paper is to present a novel approach to boosting power production by making use of another byproduct of working machines – vibrations. Our idea is to add a heat transfer medium with variable thermal conductivity between the TEG and the heat sink; preferably a fluid with a high thermal conductivity coefficient and an air gap. Random motion will cause the fluid to splash, which leads to the creation of ephemeral thermal bridges between the TEG and the heat sink. Taking into account that the thermalisation of a TEG is the main limiting factor of its power production, the ephemeral contacts with the heat source greatly increase its output power. A similar approach can be applied to any energy-harvesting wearable device held by a person or an animal, as the living creature transfers both body heat and random motion during its daily activities. We measured the performance of the randomly moving device for a wide range of angles. The power output of a randomly moving container was significantly greater compared to other setups. The maximum improvement was 49%. The mean improvement was 10% and the median was 17%. Heat sink ; Thermoelectric generator ; Materials science ; Waste heat ; Thermal energy ; Thermal conductivity ; Thermoelectric effect ; Electricity ; Thermal resistance ; Mechanical engineering ; Heat transfer ; Automotive engineering ; Mechanics ; Heat exchanger ; Electrical engineering ; Thermodynamics ; Engineering ; Physics ; Composite material Advanced Thermoelectric Materials and Devices ; Innovative Energy Harvesting Technologies ; Advanced Sensor and Energy Harvesting Materials