bluuebunny/crossref_metadata_2025_split huggingface dataset:
An exact solution for the segment-to-segment multiple sequence alignment problem.
Authors: Lenhof H P , Morgenstern B , Reinert K 
Published: July 2002

Abstract
MOTIVATION: In molecular biology, sequence alignment is a crucial tool in studying the structure and function of molecules, as well as the evolution of species. In the segment-to-segment variation of the multiple alignment problem, the input can be seen as a set of non-gapped segment pairs (diagonals). Given a weight function that assigns a weight score to every possible diagonal, the goal is to choose a consistent set of diagonals of maximum weight. We show that the segment-to-segment multiple alignment problem is equivalent to a novel formulation of the Maximum Trace problem: the Generalized Maximum Trace (GMT) problem. Solving this problem to optimality, therefore, may improve upon the previous greedy strategies that are used for solving the segment-to-segment multiple sequence alignment problem. We show that the GMT can be stated in terms of an integer linear program and then solve the integer linear program using methods from polyhedral combinatorics. This leads to a branch-and-cut algorithm for segment-to-segment multiple sequence alignment. RESULTS: We report on our first computational experiences with this novel method and show that the program is able to find optimal solutions for real-world test examples.
Sequence search algorithm assessment and testing toolkit (SAT)
Authors: Park Jong , Holm Liisa , Chothia Cyrus 
Published: July 2002

Abstract
Motivation: The Sequence Search Algorithm Assessment and Testing Toolkit (SAT) aims to be a complete package for the comparison of different protein homology search algorithms. The structural classification of proteins can provide us with a clear criterion for judgment in homology detection. There have been several assessments based on structural sequences with classifications but a good deal of similar work is now being repeated with locally developed procedures and programs. The SAT will provide developers with a complete package which will save time and produce more comparable performance assessments for search algorithms. The package is complete in the sense that it provides a non-redundant large sequence resource database, a well-characterized query database of proteins domains, all the parsers and some previous results from PSI-BLAST and a hidden markov model algorithm.
Results: An analysis on two different data sets was carried out using the SAT package. It compared the performance of a full protein sequence database (RSDB100) with a non-redundant representative sequence database derived from it (RSDB50). The performance measurement indicated that the full database is sub-optimal for a homology search. This result justifies the use of much smaller and faster RSDB50 than RSDB100 for the SAT.
Availability: A web site is up. The whole package is accessible via www and ftp. ftp://ftp.ebi.ac.uk/pub/contrib/jong/SAThttp://cyrah.ebi.ac.uk:1111/Proj/Bio/SAThttp://www.mrc-lmb.cam.ac.uk/genomes/SATIn the package, some previous assessment results produced by the package can also be found for reference.
Contact: jong@ebi.ac.uk
MEG (Model Extender for Gepasi): a program for the

modelling of complex, heterogeneous, cellular systems
Authors: Mendes Pedro , Kell Douglas B. 
Published: July 2002

Abstract
Summary: We describe a program for the construction of spatially distributed metabolic models, which may then be simulated using the metabolic simulator Gepasi. This is useful for the modelling of heterogeneous systems whether as liquid cultures or as spatially organised systems with specified interconnections.
Availability: MEG runs under Windows 95, 98, 2000 and NT, with either Intel or Alpha processors, and is available from http://gepasi.dbs.aber.ac.uk/softw/meg.html
Contact: mendes@vt.edu
* To whom correspondence should be addressed. Present address: Virginia Bioinformatics Institute, Virginia Polytechnic and State University, 1750 Kraft Drive, Suite 1100, Blacksburg, VA 24061, USA.
Distributed cooperative fault detection and isolation for uncertain multi‐agent systems based on zonotope theory
Authors: Zhang Xiangming , Zhu Fanglai 
Published: March 2022

SummaryIn recent years, multi‐agent system (MAS) have attracted extensive attention, but the study for MAS via zonotope theory is very few. This article considers the distributed cooperative fault detection (FD) and fault isolation (FI) problems for a MAS, in which every agent is assumed to be with disturbances in both the sate equation and output equation, by combining Luenberger‐like observers and zonotope theory. To begin with, a robust observer is constructed for each agent, and zonotope theory is applied on the error dynamic system of the observer such that the boundary estimation of the system state can be computed iteratively when the MAS has no fault. After this, for distributed cooperative FD purpose, a residual is also constructed based on the observer. Because the constructed residual contains disturbance, it cannot be used for FD directly. To overcome this drawback, the interval estimation of the residual is calculated by using zonotope method, and based on the residual interval estimate, a residual‐based distributed cooperative FD strategy is presented. Moreover, the distributed cooperative FI scheme is discussed and an FI strategy is also developed by modifying the distributed cooperative FD scheme. Finally, a simulation example is presented to show the effectiveness and advantages of the proposed method.
A Novel Electrochemiluminescence Janus Emitter for Dual‐Mode Biosensing
Authors: Han Tingting , Ma Cheng , Wang Leyong , Cao Yue , Chen Hong‐Yuan , Zhu Jun‐Jie 
Published: March 2022

AbstractA novel electrochemiluminescence (ECL) Janus emitter realizes dual‐mode biosensing for multiple disease‐related biomarkers from cells. Each Janus emitter consists of ruthenium (II) complex and luminol polymer doped hemispheres that are spatially separated but function simultaneously, generating intense dual‐ECL emissions. This design effectively eliminates optical and electrochemical interferences between different ECL mono‐luminophores in comparison with the homogenous nanostructures, thereby improving ECL efficiency and detection sensitivity. Accordingly, the ECL Janus emitters provide a proof of concept for the construction of the ratiometric ECL sensing of H2O2. Furthermore, this Janus emitter enables simultaneous identification and quantification of the intracellular cancer‐related dual microRNAs. This work not only inspires the development of ECL Janus emitters, but also highlights their potential in bioanalysis and clinical diagnosis in the future.
Interfacial Ion‐Trapping Electrolyte‐Gated Transistors for High‐Fidelity Neuromorphic Computing
Authors: Jin Minho , Lee Haeyeon , Im Changik , Na Hyun‐Jae , Lee Jae Hak , Lee Won Hyung , Han Junghyup , Lee Eungkyu , Park Junwoo , Kim Youn Sang 
Published: March 2022

AbstractLi+ electrolyte‐gated transistors (EGTs) have received much attention as artificial synapses for neuromorphic computing. EGTs, however, have been still challenging to achieve long‐term synaptic plasticity, which should be linearly and symmetrically controlled with the magnitude of electrical potential at the gate electrode. Herein, a fluoroalkylsilane (FAS) self‐assembled monolayer (SAM) is introduced as a channel‐electrolyte interlayer with the function of sequential ion‐trapping in Li+ EGTs. It is demonstrated that the retention of Li+ ions can be enhanced, resulting in stable non‐volatile channel conductance update with high fidelity, linearity, and symmetry in EGTs treated with FAS with 5 fluoroalkyl chains. Through investigating electrical analysis and chemical analysis, it is verified that fluoroalkyl chains enable the sequential ion‐trapping at the channel‐electrolyte interface by coulombic attraction between Li+ ions and fluorocarbons. Simulations of artificial neural networks using 20 × 20 digits show FAS‐treated EGTs are suitable as artificial synapses with an accuracy of 89.71% by identical gate pulses and 91.97% by non‐identical gate pulses. A methodological approach is newly introduced for developing synaptic devices based on EGTs for neuromorphic computing with high fidelity.
Robust Lithium–Sulfur Batteries Enabled by Highly Conductive WSe2‐Based Superlattices with Tunable Interlayer Space
Authors: Zhang Chaoqi , Fei Ban , Yang Dawei , Zhan Hongbing , Wang Jiaao , Diao Jiefeng , Li Junshan , Henkelman Graeme , Cai Daoping , Biendicho Jordi Jacas , Morante Joan Ramon , Cabot Andreu 
Published: March 2022

AbstractSuperlattices are rising stars on the horizon of energy storage and conversion, bringing new functionalities; however, their complex synthesis limits their large‐scale production and application. Herein, a simple solution‐based method is reported to produce organic–inorganic superlattices and demonstrate that the pyrolysis of the organic compound enables tuning their interlayer space. This strategy is exemplified here by combining polyvinyl pyrrolidone (PVP) with WSe2within PVP/WSe2superlattices. The annealing of such heterostructures results in N‐doped graphene/WSe2(NG/WSe2) superlattices with a continuously adjustable interlayer space in the range from 10.4 to 21 Å. Such NG/WSe2superlattices show a metallic electronic character with outstanding electrical conductivities. Both experimental results and theoretical calculations further demonstrate that these superlattices are excellent sulfur hosts at the cathode of lithium–sulfur batteries (LSB), being able to effectively reduce the lithium polysulfide shuttle effect by dual‐adsorption sites and accelerating the sluggish Li–S reaction kinetics. Consequently, S@NG/WSe2electrodes enable LSBs characterized by high sulfur usages, superior rate performance, and outstanding cycling stability, even at high sulfur loadings, lean electrolyte conditions, and at the pouch cell level. Overall, this work not only establishes a cost‐effective strategy to produce artificial superlattice materials but also pioneers their application in the field of LSBs.
MXene‐Enhanced Chitin Composite Sponges with Antibacterial and Hemostatic Activity for Wound Healing
Authors: Li Shanshan , Gu Bin , Li Xiaoyun , Tang Shuwei , Zheng Lu , Ruiz‐Hitzky Eduardo , Sun Zeyu , Xu Changliang , Wang Xiaoying 
Published: March 2022

AbstractThis study shows the effective use of MXene‐based nanomaterials to improve the performance of biocomposite sponges in wound healing. In this way, diverse chitin/MXene composite sponges are fabricated by incorporating MXene‐based nanomaterials with various morphology (accordion‐shaped, intercalated, single‐layer, gold nanoparticles (AuNPs)‐loaded single‐layer) into the network of chitin sponge (CH), which can prevent massive blood losses and promote the healing process of bacterial‐infected wounds. With the addition of MXene‐based nanomaterials, the hemostatic efficacy of CH is enhanced due to the improved hemophilicity and accelerated blood coagulation kinetics. Furthermore, the composite sponges show a predominant antibacterial activity through the synergy between the capture and the photothermal effects. Importantly, the addition of AuNPs to composite sponges further improves hemostatic performance and promotes normal skin cell migration to heal the infected wound, achieving wound closure rates of 84% on day 9. These initial studies expand the applications of MXene‐based nanomaterials in biomedical fields.
Vascularized Lung Cancer Model for Evaluating the Promoted Transport of Anticancer Drugs and Immune Cells in an Engineered Tumor Microenvironment
Authors: Kim Dasom , Hwang Kyeong Seob , Seo Eun U , Seo Suyeong , Lee Byung Chul , Choi Nakwon , Choi Jonghoon , Kim Hong Nam 
Published: March 2022

AbstractThe tumor microenvironment (TME) is the environment around the tumor, including blood vessels, immune cells, fibroblasts, signaling molecules, and the extracellular matrix (ECM). Owing to its component interactions, the TME influences tumor growth and drug delivery in a highly complex manner. Although several vascularized cancer models are developed to mimic the TME in vitro, these models cannot comprehensively reflect blood vessel–tumor spheroid interactions. Here, a method for inducing controlled tumor angiogenesis by engineering the microenvironment is presented. The interstitial flow direction regulates the direction of capillary sprouting, showing that angiogenesis occurs in the opposite direction of flow, while the existence of lung fibroblasts affects the continuity and lumen formation of sprouted capillaries. The vascularized tumor model shows enhanced delivery of anticancer drugs and immune cells to the tumor spheroids because of the perfusable vascular networks. The possibility of capillary embolism using anticancer drug‐conjugated liquid metal nanoparticles is investigated using the vascularized tumor model. This vascularized tumor platform can aid in the development of effective anticancer drugs and cancer immunotherapy.
Ultrahigh‐Speed In‐Memory Electronics Enabled by Proximity‐Oxidation‐Evolved Metal Oxide Redox Transistors
Authors: Kumar Mohit , Kim Unjeong , Lee WangGon , Seo Hyungtak 
Published: March 2022

AbstractThe pursuit of a universal device that combines nonvolatile multilevel storage, ultrafast writing/erasing speed, nondestructive readout, and embedded processing with low power consumption demands the development of innovative architectures. Although thin‐film transistors and redox‐based resistive‐switching devices have independently been proven to be ideal building blocks for data processing and storage, it is still difficult to achieve both well‐controlled multilevel memory and high‐precision ultrafast processing in a single unit, even though this is essential for the large‐scale hardware implementation of in‐memory computing. In this work, an ultrafast (≈42 ns) and programable redox thin‐film transistor (ReTFT) memory made of a proximity‐oxidation‐grown TiO2 layer is developed, which has on/off ratio of 105, nonvolatile multilevel analog storage with a long retention time, strong durability, and high reliability. Utilizing the proof‐of‐concept ReTFTs, circuits capable of performing fundamental NOT, AND, and OR operations with reconfigurable logic‐in‐memory processing are developed. Further, on‐demand signal memory‐processing operations, like multi‐terminal addressable memory, learning, pattern recognition, and classification, are explored for prospective application in neuromorphic hardware. This device, which operates on a fundamentally different mechanism, presents an alternate solution to the problems associated with the creation of high‐performing in‐memory processing technology.
Emerging Biosensing Technologies for the Diagnostics of Viral Infectious Diseases
Authors: Kabay Gözde , DeCastro Jonalyn , Altay Alara , Smith Kasey , Lu Hsiang‐Wei , Capossela Antonia McDonnell , Moarefian Maryam , Aran Kiana , Dincer Can 
Published: March 2022

AbstractSeveral viral infectious diseases appear limitless since the beginning of the 21st century, expanding into pandemic lengths. Thus, there are extensive efforts to provide more efficient means of diagnosis, a better understanding of acquired immunity, and improved monitoring of inflammatory biomarkers, as these are all crucial for controlling the spread of infection while aiding in vaccine development and improving patient outcomes. In this regard, various biosensors have been developed recently to streamline pathogen and immune response detection by addressing the limitations of traditional methods, including isothermal amplification‐based systems and lateral flow assays. This review explores state‐of‐the‐art biosensors for detecting viral pathogens, serological assays, and inflammatory biomarkers from the material perspective, by discussing their advantages, limitations, and further potential regarding their analytical performance, clinical utility, and point‐of‐care adaptability. Additionally, next‐generation biosensing technologies that offer better sensitivity and selectivity, and easy handling for end‐users are highlighted. An emerging example of these next‐generation biosensors are those powered by novel synthetic biology tools, such as clustered regularly interspaced short palindromic repeats (CRISPR) with CRISPR‐associated proteins (Cas), in combination with integrated point‐of‐care devices. Lastly, the current challenges are discussed and a roadmap for furthering these advanced biosensing technologies to manage future pandemics is provided.
An Open‐Ended Ni3S2–Co9S8 Heterostructures Nanocage Anode with Enhanced Reaction Kinetics for Superior Potassium‐Ion Batteries
Authors: Zhang Shipeng , Ling Fangxin , Wang Lifeng , Xu Rui , Ma Mingze , Cheng Xiaolong , Bai Ruilin , Shao Yu , Huang Huijuan , Li Dongjun , Jiang Yu , Rui Xianhong , Bai Jintao , Yao Yu , Yu Yan 
Published: March 2022

AbstractSulfides are perceived as promising anode materials for potassium‐ion batteries (PIBs) due to their high theoretical specific capacity and structural diversity. Nonetheless, the poor structural stability and sluggish kinetics of sulfides lead to unsatisfactory electrochemical performance. Herein, Ni3S2–Co9S8 heterostructures with an open‐ended nanocage structure wrapped by reduced graphene oxide (Ni‐Co‐S@rGO cages) are well designed as the anode for PIBs via a selective etching and one‐step sulfuration approach. The hollow Ni‐Co‐S@rGO nanocages, with large surface area, abundant heterointerfaces, and unique open‐ended nanocage structure, can reduce the K+ diffusion length and promote reaction kinetics. When used as the anode for PIBs, the Ni‐Co‐S@rGO exhibits high reversible capacity and low capacity degradation (0.0089% per cycle over 2000 cycles at 10 A g–1). A potassium‐ion full battery with a Ni‐Co‐S@rGO anode and Prussian blue cathode can display a superior reversible capacity of 400 mAh g–1 after 300 cycles at 2 A g–1. The unique structural advantages and electrochemical reaction mechanisms of the Ni‐Co‐S@rGO are revealed by finite‐element‐simulation in situ characterizations. The universal synthesis technology of bimetallic sulfide anodes for advanced PIBs may provide vital guidance to design high‐performance energy‐storage materials.
Microneedle‐Based Technology: Toward Minimally Invasive Disease Diagnostics
Authors: Xu Na , Xu Wenxin , Zhang Manyue , Yu Jia , Ling Guixia , Zhang Peng 
Published: March 2022

AbstractThe traditional way of disease diagnosis is to detect biomarkers in serum, blood, urine, and saliva, but it often faces wound infection and pain, and usually requires professional medical personnel to operate, which is unacceptable for most people. As a result, minimally invasive detection of biomarkers has attracted wide attention and is expected to become a new method for patient monitoring and disease diagnosis. Interstitial fluid (ISF) acts as a medium between cells and the circulatory system, serving as a reservoir of biomolecules, nutrients, and metabolic products. Microneedles (MNs) are effective carriers for delivering drugs, biomolecules, vaccines, and stem cells. What's more, MNs provide a painless, simple, and minimally invasive method to collect skin ISF. In summary, the structural and functional characteristics of MNs provide incomparable advantages and open the door for future diagnosis and monitoring. MNs techniques are minimally invasive, convenient, and patient compliant for individualized and long‐term treatments, which open up new areas of disease diagnosis. In this review, various MNs techniques for ISF sampling in disease diagnosis are reviewed, and their future challenges and development prospects are discussed.
Acid‐Responsive Dual‐Targeted Nanoparticles Encapsulated Aspirin Rescue the Immune Activation and Phenotype in Autism Spectrum Disorder
Authors: He Xueqin , Xie Jiang , Zhang Jing , Wang Xiaorong , Jia Xufeng , Yin Heng , Qiu Zhongqing , Yang Zhihang , Chen Jiao , Ji Zhiliang , Yu Wenqi , Chen Meiwan , Xu Wenming , Gao Huile 
Published: March 2022

AbstractThe treatment of autism spectrum disorder (ASD) is one of the most difficult challenges in neurodevelopmental diseases, because of the unclear pathogenesis research and low brain‐lesion targeting efficiency. Besides, maternal immune activation has been reported as the most mature and widely used model of ASD and aspirin‐triggered lipoxin A4 is a potent anti‐inflammatory mediator being involved in the resolution of neuroinflammation in ASD. Therefore, an aspirin encapsulated cascade drug delivery system (Asp@TMNPs) is established, which can successively target the blood–brain barrier (BBB) and microglial cells and response to the acid microenvironment in lysosome. As a result, the mitochondrial oxidative stress, DNA damage, and inflammation of microglial cells are prominently alleviated. After the treatment of Asp@TMNPs, the social interaction, stereotype behavior, and anxious condition of ASD mice are notably improved and the activation of microglial cells is inhibited. Overall, this system successively penetrates the BBB and targets microglial cells, therefore, it significantly enhances the intracephalic drug accumulation and improves anti‐neuroinflammatory efficacy of aspirin, providing a promising strategy for ASD treatment.
High Energy and Power Density Peptidoglycan Muscles through Super‐Viscous Nanoconfined Water
Authors: Wang Haozhen , Liu Zhi‐Lun , Lao Jianpei , Zhang Sheng , Abzalimov Rinat , Wang Tong , Chen Xi 
Published: March 2022

AbstractWater‐responsive (WR) materials that reversibly deform in response to humidity changes show great potential for developing muscle‐like actuators for miniature and biomimetic robotics. Here, it is presented that Bacillus (B.) subtilis’ peptidoglycan (PG) exhibits WR actuation energy and power densities reaching 72.6 MJ m−3 and 9.1 MW m−3, respectively, orders of magnitude higher than those of frequently used actuators, such as piezoelectric actuators and dielectric elastomers. PG can deform as much as 27.2% within 110 ms, and its actuation pressure reaches ≈354.6 MPa. Surprisingly, PG exhibits an energy conversion efficiency of ≈66.8%, which can be attributed to its super‐viscous nanoconfined water that efficiently translates the movement of water molecules to PG's mechanical deformation. Using PG, WR composites that can be integrated into a range of engineering structures are developed, including a robotic gripper and linear actuators, which illustrate the possibilities of using PG as building blocks for high‐efficiency WR actuators.
Ultralow‐Power Machine Vision with Self‐Powered Sensor Reservoir
Authors: Lao Jie , Yan Mengge , Tian Bobo , Jiang Chunli , Luo Chunhua , Xie Zhuozhuang , Zhu Qiuxiang , Bao Zhiqiang , Zhong Ni , Tang Xiaodong , Sun Linfeng , Wu Guangjian , Wang Jianlu , Peng Hui , Chu Junhao , Duan Chungang 
Published: March 2022

AbstractA neuromorphic visual system integrating optoelectronic synapses to perform the in‐sensor computing is triggering a revolution due to the reduction of latency and energy consumption. Here it is demonstrated that the dwell time of photon‐generated carriers in the space‐charge region can be effectively extended by embedding a potential well on the shoulder of Schottky energy barrier. It permits the nonlinear interaction of photocurrents stimulated by spatiotemporal optical signals, which is necessary for in‐sensor reservoir computing (RC). The machine vision with the sensor reservoir constituted by designed self‐powered Au/P(VDF‐TrFE)/Cs2AgBiBr6/ITO devices is competent for both static and dynamic vision tasks. It shows an accuracy of 99.97% for face classification and 100% for dynamic vehicle flow recognition. The in‐sensor RC system takes advantage of near‐zero energy consumption in the reservoir, resulting in decades‐time lower training costs than a conventional neural network. This work paves the way for ultralow‐power machine vision using photonic devices.