bluuebunny/crossref_metadata_2025_split huggingface dataset:
Collaborative Planning Model of PV-Battery Storage System for Microgrid Considering Demand Response
Authors: Shen Weijie , Zeng Ming 
Published: March 2023

Abstract
The configuration of energy storage with reasonable capacity in the photovoltaic microgrid is a powerful way to promote the local consumption of distributed photovoltaic and improve the efficiency of photovoltaic system. DSM can effectively reduce grid investment and become an important regulation means for efficient operation of power system. The main innovation of this research is to consider the utilization of demand side resources in microgrid planning, which is rarely deployed in previous studies. Firstly, the models of renewable energy output characteristics and energy storage SOC characteristics are established, and the demand response mechanism is analysed; Secondly, taking the minimization of the comprehensive cost of the system as the objective function and the energy balance, equipment characteristics as constraints, a collaborative planning model of PV-Battery storage system for microgrid considering demand response is constructed. Finally, the rationality and effectiveness of the proposed optimization model are verified by the actual data of a microgrid in Fuzhou.
Metric Mutation Anomaly Detection Method of the Power Grid Dispatching Automatic System Based on Machine Learning and Statistics
Authors: Huang Xinjian , Zhai Mingyu , Gao Shang , Ji Kun , Li Hao , Zhang Pan 
Published: March 2023

Abstract
With the increase of the scale, function and complexity of power grid dispatching automatic system, the difficulty of system operation and maintenance increases significantly. This paper presents a metric mutation anomaly detection method based on the combination of machine learning and statistical algorithm. First, the system data is smoothed by machine learning algorithm, and the difference between the smoothed value and the real value is calculated. Then, the difference was used to detect data anomaly by ensemble of statistical method. The effectiveness and accuracy of the method is verified by the test data of the power grid dispatching automatic system. The method can quickly locate the anomaly components of the system and assist the system maintenance personnel in making decisions.
Design of Flexible Drilling and Milling Tool for Composite Wing Beam of Aircraft
Authors: Lai Qingji , Zhao Gangyao , Zhang Ranyang , Guo Zhenghua , Chen Qi , Zhang Pi 
Published: March 2023

Abstract
To solve the disadvantages of traditional processing tooling, such as long processing cycle, low production efficiency, and easy deformation during the processing of large-size composite wing beams, a drilling and milling tooling for flexible positioning of composite wing beams of multiple types of aircraft is proposed based on the structural characteristics and manufacturing technology requirements of a certain type of aircraft wing spar combined with flexible tooling design technology. And a modular mobile clamping unit with automatic control is designed. Then the practical problems such as the difficult clamping and positioning of large-size wing beams, the deformation and vibration during processing are solved by the flexible drilling and milling tool. The results of the current design are helpful to improve the processing efficiency and shorten the manufacturing period of the wing beams.
Pulse shape discrimination using a convolutional neural network for organic liquid scintillator signals
Authors: Jung K.Y. , Han B.Y. , Jeon E.J. , Jeong Y. , Jo H.S. , Kim J.Y. , Kim J.G. , Kim Y.D. , Ko Y.J. , Lee M.H. , Lee J. , Moon C.S. , Oh Y.M. , Park H.K. , Seo S.H. , Seol D.W. , Siyeon K. , Sun G.M. , Yoon Y.S. , Yu I. 
Published: March 2023

Abstract
A convolutional neural network (CNN) architecture is
developed to improve the pulse shape discrimination (PSD) power of
the gadolinium-loaded organic liquid scintillation detector to
reduce the fast neutron background in the inverse beta decay
candidate events of the NEOS-II data. A power spectrum of an event
is constructed using a fast Fourier transform of the time domain raw
waveforms and put into CNN. An early data set is evaluated by CNN
after it is trained using low energy β and α events.
The signal-to-background ratio averaged over 1–10 MeV visible
energy range is enhanced by more than 20% in the result of the CNN
method compared to that of an existing conventional PSD method, and
the improvement is even higher in the low energy region.
Generation of vortex beams with nonuniform phase jumps in azimuthal locations
Authors: Ghavami Sabouri Saeed 
Published: March 2023

Abstract
The phase angle of the vortex beam along a closed loop centered on the optical singularity changes by 2πℓ, where ℓ is the number of phase jumps (PJs) from 0 to 2π and indicates the topological charge of the vortex beam. In this paper, the generation and specification of a new type of vortex beam, in which their PJs are asymmetrically embedded in the phase pattern, are reported. In contrast to Laguerre–Gaussian vortex beams, where PJs are equally spaced azimuthally around the optical singularity, the presented vortex beams have PJs embedded at arbitrary azimuthal angles. By designing a particular forked grating and displaying it on a spatial light modulator, this type of vortex beam is experimentally generated. As with conventional forked grating, the designed grating produces vortex beams with the opposite orbital angular momentum (OAM) sign in the first diffraction order. By measuring the relative orientation of the intensity profile of these OAM beams in the first diffraction order, the position of the PJs on the wavefront of a vortex beam with ℓ = 2 can be determined. This type of vortex beam could have potential applications in various fields of photonics, especially in optical communications based on optical vortices.
Hydrogen permeability of nickel capillaries: mathematical modeling and experimental verification
Authors: Shubnikova Е V , Tropin Е S , Lapushkina Е Y , Bychkov S F , Nemudry А P 
Published: March 2023

Abstract
The present article focuses on the study of the transport characteristics of nickel hydrogen selective membranes (nickel industrial capillaries of various wall thicknesses). The experimental data on hydrogen fluxes through nickel capillaries depending on the membrane wall thickness, temperature, and hydrogen partial pressure were obtained. The highest value of the specific hydrogen flux is ∼0.09 ml·min−1·cm−2 is achieved at 750 °C, pH2.1 = 0.5 atm and the wall thickness of 84 μm. To accurately determine the kinetic parameters of the process of hydrogen transport (the effective activation energy and the pre-exponential factor) in nickel capillaries with a wall thickness of 147 ≤ h ≤ 84 μm, a previously developed mathematical model was used, which takes into account the geometric characteristics of tubular membranes. The results of computer simulation are compared with experimental data.
Comparison of Clinical and Molecular Features Between Patients With Essential Thrombocythemia and Early/Prefibrotic Primary Myelofibrosis Presenting With Thrombocytosis in Taiwan
Authors: Kuo Ming-Chung , Chuang Wen-Yu , Chang Hung , Lin Tung-Huei , Wu Jin-Hou , Lin Tung-Liang , Ou Che-Wei , Hung Yu-Shin , Huang Ting-Yu , Huang Ying-Jung , Wang Po-Nan , Shih Lee-Yung 
Published: March 2023

AbstractObjectivesThe clinical presentations of essential thrombocythemia (ET) may be quite similar to early/prefibrotic primary myelofibrosis (pre-PMF), especially in pre-PMF presenting with thrombocytosis (pre–PMF-T), but may be associated with a different outcome. It is very important to distinguish these two entities. The aim of this study was to address the clinical and prognostic relevance of distinguishing pre–PMF-T from ET.MethodsAll patients, including 258 with ET and 105 with pre–PMF-T, received JAK2V617F, MPL (exon 10), and CALR (exon 9) mutation analysis and allele burden measurement for JAK2V617F and CALR mutants.ResultsPatients with pre–PMF-T had an older age and higher leukocyte and platelet counts but lower hemoglobin levels than patients with ET. Patients with pre–PMF-T had a shorter overall, leukemia-free, and thrombosis-free survival compared with patients with ET. Patients with ET had a higher rate of cerebral ischemic stroke, whereas patients with pre–PMF-T tended to have splanchnic vein thrombosis. The frequencies of JAK2V617F, CALR, and MPL mutations and CALR allele burden were no different, but JAK2V617F allele burden was significantly higher in pre–PMF-T. Patients with pre–PMF-T with the JAK2V617F mutation had an inferior overall survival and thrombosis-free survival, whereas the status of driver gene mutations did not influence the outcomes of patients with ET.ConclusionsET and pre–PMF-T were two distinct disease entities and exhibited different clinical phenotype, genotype, and outcomes.
Designing antimicrobial peptides using deep learning and molecular dynamic simulations
Authors: Cao Qiushi , Ge Cheng , Wang Xuejie , Harvey Peta J , Zhang Zixuan , Ma Yuan , Wang Xianghong , Jia Xinying , Mobli Mehdi , Craik David J , Jiang Tao , Yang Jinbo , Wei Zhiqiang , Wang Yan , Chang Shan , Yu Rilei 
Published: March 2023

AbstractWith the emergence of multidrug-resistant bacteria, antimicrobial peptides (AMPs) offer promising options for replacing traditional antibiotics to treat bacterial infections, but discovering and designing AMPs using traditional methods is a time-consuming and costly process. Deep learning has been applied to the de novo design of AMPs and address AMP classification with high efficiency. In this study, several natural language processing models were combined to design and identify AMPs, i.e. sequence generative adversarial nets, bidirectional encoder representations from transformers and multilayer perceptron. Then, six candidate AMPs were screened by AlphaFold2 structure prediction and molecular dynamic simulations. These peptides show low homology with known AMPs and belong to a novel class of AMPs. After initial bioactivity testing, one of the peptides, A-222, showed inhibition against gram-positive and gram-negative bacteria. The structural analysis of this novel peptide A-222 obtained by nuclear magnetic resonance confirmed the presence of an alpha-helix, which was consistent with the results predicted by AlphaFold2. We then performed a structure–activity relationship study to design a new series of peptide analogs and found that the activities of these analogs could be increased by 4–8-fold against Stenotrophomonas maltophilia WH 006 and Pseudomonas aeruginosa PAO1. Overall, deep learning shows great potential in accelerating the discovery of novel AMPs and holds promise as an important tool for developing novel AMPs.
bvnGPS: a generalizable diagnostic model for acute bacterial and viral infection using integrative host transcriptomics and pretrained neural networks
Authors: Li Qizhi , Zheng Xubin , Xie Jize , Wang Ran , Li Mengyao , Wong Man-Hon , Leung Kwong-Sak , Li Shuai , Geng Qingshan , Cheng Lixin 
Published: March 2023

AbstractMotivationThe confusion of acute inflammation infected by virus and bacteria or noninfectious inflammation will lead to missing the best therapy occasion resulting in poor prognoses. The diagnostic model based on host gene expression has been widely used to diagnose acute infections, but the clinical usage was hindered by the capability across different samples and cohorts due to the small sample size for signature training and discovery.ResultsHere, we construct a large-scale dataset integrating multiple host transcriptomic data and analyze it using a sophisticated strategy which removes batch effect and extracts the common information from different cohorts based on the relative expression alteration of gene pairs. We assemble 2680 samples across 16 cohorts and separately build gene pair signature (GPS) for bacterial, viral, and noninfected patients. The three GPSs are further assembled into an antibiotic decision model (bacterial–viral–noninfected GPS, bvnGPS) using multiclass neural networks, which is able to determine whether a patient is bacterial infected, viral infected, or noninfected. bvnGPS can distinguish bacterial infection with area under the receiver operating characteristic curve (AUC) of 0.953 (95% confidence interval, 0.948–0.958) and viral infection with AUC of 0.956 (0.951–0.961) in the test set (N = 760). In the validation set (N = 147), bvnGPS also shows strong performance by attaining an AUC of 0.988 (0.978–0.998) on bacterial-versus-other and an AUC of 0.994 (0.984–1.000) on viral-versus-other. bvnGPS has the potential to be used in clinical practice and the proposed procedure provides insight into data integration, feature selection and multiclass classification for host transcriptomics data.Availability and implementationThe codes implementing bvnGPS are available at https://github.com/Ritchiegit/bvnGPS. The construction of iPAGE algorithm and the training of neural network was conducted on Python 3.7 with Scikit-learn 0.24.1 and PyTorch 1.7. The visualization of the results was implemented on R 4.2, Python 3.7, and Matplotlib 3.3.4.
On the Challenges of Identifying Benthic Dominance on Anthropocene Coral Reefs
Authors: Tebbett Sterling B , Crisp Samantha K , Evans Richard D , Fulton Christopher J , Pessarrodona Albert , Wernberg Thomas , Wilson Shaun K , Bellwood David R 
Published: March 2023

AbstractThe concept of dominance is frequently used to describe changes in rapidly reconfiguring ecosystems, but the definition of dominance can vary widely among studies. Using coral reefs as a model, we use extensive benthic composition data to explore how variability in applying dominance concepts can shape perceptions. We reveal that coral dominance is sensitive to the exclusion of key algal groups and the categorization of other benthic groups, with ramifications for detecting an ecosystem phase shift. For example, ignoring algal turf inflates the dominance of hard and soft corals in the benthic habitats underpinning reef ecosystems. We need a consensus on how dominance concepts are applied so that we can build a more comprehensive understanding of ecosystem shifts across a broad range of aquatic and terrestrial settings. For reefs, we highlight the benefits of comprehensive and inclusive surveys for evaluating and managing the altered ecosystem states that are emerging in the Anthropocene.
Moving, fast and slow: behavioural insights into bradykinesia in Parkinson’s disease
Authors: Herz Damian M , Brown Peter 
Published: March 2023

Abstract
The debilitating symptoms of Parkinson’s disease, including the hallmark slowness of movement, termed bradykinesia, were described more than 100 years ago. Despite significant advances in elucidating the genetic, molecular and neurobiological changes in Parkinson’s disease, it remains conceptually unclear exactly why patients with Parkinson’s disease move slowly. To address this, we summarize behavioural observations of movement slowness in Parkinson’s disease and discuss these findings in a behavioural framework of optimal control. In this framework, agents optimize the time it takes to gather and harvest rewards by adapting their movement vigour according to the reward that is at stake and the effort that needs to be expended. Thus, slow movements can be favourable when the reward is deemed unappealing or the movement very costly. While reduced reward sensitivity, which makes patients less inclined to work for reward, has been reported in Parkinson’s disease, this appears to be related mainly to motivational deficits (apathy) rather than bradykinesia. Increased effort sensitivity has been proposed to underlie movement slowness in Parkinson’s disease. However, careful behavioural observations of bradykinesia are inconsistent with abnormal computations of effort costs due to accuracy constraints or movement energetic expenditure. These inconsistencies can be resolved when considering that a general disability to switch between stable and dynamic movement states can contribute to an abnormal composite effort cost related to movement in Parkinson’s disease. This can account for paradoxical observations such as the abnormally slow relaxation of isometric contractions or difficulties in halting a movement in Parkinson’s disease, both of which increase movement energy expenditure. A sound understanding of the abnormal behavioural computations mediating motor impairment in Parkinson’s disease will be vital for linking them to their underlying neural dynamics in distributed brain networks and for grounding future experimental studies in well-defined behavioural frameworks.
The radiologically isolated syndrome: revised diagnostic criteria
Authors: Lebrun-Frénay Christine , Okuda Darin T , Siva Aksel , Landes-Chateau Cassandre , Azevedo Christina J , Mondot Lydiane , Carra-Dallière Clarisse , Zephir Helene , Louapre Celine , Durand-Dubief Françoise , Le Page Emmanuelle , Bensa Caroline , Ruet Aurélie , Ciron Jonathan , Laplaud David A , Casez Olivier , Mathey Guillaume , de Seze Jerome , Zeydan Burcu , Makhani Naila , Tutuncu Melih , Levraut Michael , Cohen Mikael , Thouvenot Eric , Pelletier Daniel , Kantarci Orhun H 
Published: March 2023

Abstract
The radiologically isolated syndrome (RIS) was defined in 2009 as the presence of asymptomatic, incidentally identified demyelinating-appearing white matter lesions in the CNS within individuals lacking symptoms typical of multiple sclerosis (MS). The RIS criteria have been validated and predict the transition to symptomatic MS reliably. The performance of RIS criteria that require fewer MRI lesions is unknown.
2009-RIS subjects, by definition, fulfil three to four of four criteria for 2005 dissemination in space (DIS) and subjects fulfilling only one or two lesions in at least one 2017 DIS location were identified within 37 prospective databases. Univariate and multivariate Cox regression models were used to identify predictors of a first clinical event. Performances of different groups were calculated.
Seven hundred and forty-seven subjects (72.2% female, mean age 37.7 ± 12.3 years at the index MRI) were included. The mean clinical follow-up time was 46.8 ± 45.4 months. All subjects had focal T2 hyperintensities suggestive of inflammatory demyelination on MRI; 251 (33.6%) fulfilled one or two 2017 DIS criteria (designated as Groups 1 and 2, respectively), and 496 (66.4%) fulfilled three or four 2005 DIS criteria representing 2009-RIS subjects. Group 1 and 2 subjects were younger than the 2009-RIS group and were more likely to develop new T2 lesions over time (P &lt; 0.001). Groups 1 and 2 were similar regarding survival distribution and risk factors for transition to MS.
At 5 years, the cumulative probability for a clinical event was 29.0% for Groups 1 and 2 compared to 38.7% for 2009-RIS (P = 0.0241). The presence of spinal cord lesions on the index scan and CSF-restricted oligoclonal bands in Groups 1–2 increased the risk of symptomatic MS evolution at 5 years to 38%, comparable to the risk of development in the 2009-RIS group. The presence of new T2 or gadolinium-enhancing lesions on follow-up scans independently increased the risk of presenting with a clinical event (P &lt; 0.001). The 2009-RIS subjects or Groups 1 and 2 with at least two of the risk factors for a clinical event demonstrated better sensitivity (86.0%), negative predictive value (73.1%), accuracy (59.8%) and area under the curve (60.7%) compared to other criteria studied.
This large prospective cohort brings Class I evidence that subjects with fewer lesions than required in the 2009 RIS criteria evolve directly to a first clinical event at a similar rate when additional risk factors are present. Our results provide a rationale for revisions to existing RIS diagnostic criteria.
Spinal disinhibition: evidence for a hyperpathia phenotype in painful diabetic neuropathy
Authors: Marshall Anne , Kalteniece Alise , Ferdousi Maryam , Azmi Shazli , Jude Edward B , Adamson Clare , D’Onofrio Luca , Dhage Shaishav , Soran Handrean , Campbell Jackie , Lee-Kubli Corinne A , Hamdy Shaheen , Malik Rayaz A , Calcutt Nigel A , Marshall Andrew G 
Published: March 2023

AbstractThe dominant sensory phenotype in patients with diabetic polyneuropathy and neuropathic pain is a loss of function. This raises questions as to which mechanisms underlie pain generation in the face of potentially reduced afferent input. One potential mechanism is spinal disinhibition, whereby a loss of spinal inhibition leads to increased ascending nociceptive drive due to amplification of, or a failure to suppress, incoming signals from the periphery. We aimed to explore whether a putative biomarker of spinal disinhibition, impaired rate-dependent depression of the Hoffmann reflex, is associated with a mechanistically appropriate and distinct pain phenotype in patients with painful diabetic neuropathy. In this cross-sectional study, 93 patients with diabetic neuropathy underwent testing of Hoffmann reflex rate-dependent depression and detailed clinical and sensory phenotyping, including quantitative sensory testing. Compared to neuropathic patients without pain, patients with painful diabetic neuropathy had impaired Hoffmann reflex rate-dependent depression at 1, 2 and 3 Hz (P ≤ 0.001). Patients with painful diabetic neuropathy exhibited an overall loss of function profile on quantitative sensory testing. However, within the painful diabetic neuropathy group, cluster analysis showed evidence of greater spinal disinhibition associated with greater mechanical pain sensitivity, relative heat hyperalgesia and higher ratings of spontaneous burning pain. These findings support spinal disinhibition as an important centrally mediated pain amplification mechanism in painful diabetic neuropathy. Furthermore, our analysis indicates an association between spinal disinhibition and a distinct phenotype, arguably akin to hyperpathia, with combined loss and relative gain of function leading to increasing nociceptive drive.