bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mechanism for Extracting Features Using Particle Swarm Optimization for Intrusion Detection Systems
Authors: Sivagaminathan Vaishnavi , Sharma Manmohan , Henge Santosh Kumar 
Published: January 2023

Abstract
The task of ensuring cyber-security has grown increasingly challenging given the concerning expansion of Computing connection and furthermore, there are a large number of computer-related applications available. It also needs a strong defense mechanism towards various cyber-attacks. Identifying irregularities and dangers in such a computer Security measures (IDS) have been established to aid with information security. Particularly, ML approaches are a subset of artificial intelligence (ai). (AI), a useful data-driven anti - malware system was developed. Two alternative intrusion detection (ID) classification reaches were compared in this study, each with its own set of use cases. Before using the two classifiers for classification, the Particle Swarm Optimization (PSO) approach ware used for reduce dimensionality. The classification meets used to characterize network anomalies were studied in this study. PSO + ANN (Artificial neural network), PSO plus Decision Tree and PSO plus K-Nearest Neighbor are the three classifiers used. The Knowledge discovery in databases 99 datasets was used to corroborate the identification techniques' findings. On the result of the implementation, successful metrics like as the following metrics were used to analyze cyber-security databases for various kinds of cyber-attacks: specific, recall, f1-score, correctness, accuracy, and constancy. The two's respective precision, detection rate (DR), and totally bogus rate were also compared to see which one outperforms the other (FPR). The solution was then contrasted with the IDS that was already in place. In terms of detecting network anomalies, The outcomes show that PSO + ANN outperforms the PSO + KNN and PSO + DT classifier algorithms.
Vortex Dynamics of a Separated Wing in a Time-Varying Freestream
Authors: Gloutak Dasha , Jansen Kenneth , Farnsworth John 
Published: January 2023

Abstract
Unsteady flows threaten the performance and efficiency of systems operating in gusty environments. The impact of an unsteady freestream, generated in a closed test-section unsteady wind tunnel, on the flow separation and aerodynamic performance of a wing at a post-stall angle of attack is examined within the current study. Synchronized two-dimensional, high-speed particle image velocimetry and integrated surface pressure measurements were collected for a finite-span wing in a time-varying, spatially uniform freestream. Freestream accelerations impose additional unsteady pressure gradients within the wind tunnel that alter the behavior of shed vortical structures within the separated flow above the wing. Freestream acceleration and conservation of circulation determine the orientation and interaction of shed vortical structures, which alter the magnitude of the fluctuations in the lift force and pitching moment experienced by the wing. Specifically, fluctuations in the sectional lift and pitching moment coefficients are amplified during deceleration and attenuated during acceleration.
Loss of MuRF1 in Duroc Pigs Promotes Skeletal Muscle Hypertrophy
Authors: Li Jiaping , Hu Yiqing , Li Jiajia , Wang Haitao , Wu Hanyu , Zhao Chengcheng , Tan Tan , Zhang Li , Zhu Di , Liu Xu , Li Ning , Hu Xiaoxiang 
Published: January 2023

Abstract
Background
Muscle mass development depends on increased protein synthesis and reduced degradation of muscle proteins. Muscle ring-finger protein-1 (MuRF1) plays a key role in controlling muscle atrophy. Its E3 ubiquitin ligase activity recognizes and degrades skeletal muscle proteins through the ubiquitin-proteasome system. The loss of Murf1 (the gene encoding MuRF1) in mice leads to the accumulation of skeletal muscle proteins and alleviation of muscle atrophy. However, the function of Murf1 in agricultural animals remains unclear. In this study, we bred F1 generation Murf1+/− and F2 generation Murf1−/− Duroc pigs from F0 Murf1−/− pigs to investigate the effect of Murf1 knockout on skeletal muscle development.
Results
The Murf1+/− pigs retained normal muscle growth and reproduction levels, and their lean meat percentage increased by 6% compared to that of the wild-type (WT) pigs. Furthermore, the meat color, pH, water-holding capacity, and tenderness of the Murf1+/− pigs were similar to those of the WT pigs. The drip loss rate and intramuscular fat decreased slightly in the Murf1+/− pigs. However, the cross-sectional area of the myofibers in the longissimus dorsi increased in adult Murf1+/− pigs. The skeletal muscle proteins MYBPC3 and actin, targeted by MuRF1, accumulated in the Murf1+/− and Murf1−/− pigs.
Conclusions
Our findings show that inhibiting muscle protein degradation in MuRF1-deficient Duroc pigs increases the size of their myofibers and percentage of lean meat without influencing their growth or pork quality. Our study demonstrates that Murf1 is a target gene for promoting skeletal muscle hypertrophy in pig breeding.
On quasidifferentiable mathematical programs with equilibrium constraints
Authors: Laha Vivek , Singh Harsh Narayan 
Published: January 2023

Abstract
The aim of this article is to study mathematical programs with equilibrium constraints involving quasidifferentiable functions, denoted by QMPEC, and to synthesize suitable optimality conditions. We first derive Fritz-John (FJ) necessary optimality conditions with Lagrange multipliers depending upon the choice of superdifferentials. We introduce a suitable variant of no nonzero abnormal multiplier constraint qualification for the QMPEC, denoted by NNAMCQ-QMPEC, and derive Karush-Kuhn-Tucker (KKT) necessary optimality conditions. We also propose some conditions under which the Lagrange multipliers do not depend upon the choice of superdifferentials. Further, we prove several sufficient optimality conditions for a weak stationary point to be optimal for the QMPEC under suitable choice of generalized convex functions.
Surgical treatment of left ventricular aneurysm in patients with prior myocardial infarction in the absence of obstructive coronary artery disease (MINOCA): a cohort study
Authors: Song Yangwu , Xu Fei , Feng Wei 
Published: January 2023

Abstract
Background
There is a paucity of studies examining the treatment of patients with prior myocardial infarction in the absence of obstructive coronary arteries (MINOCA) and with a concomitant left ventricular aneurysm. Our study aims to illustrate the clinical characteristics and report the mid-term surgical outcomes in this distinct entity.
Methods
Ten patients with MINOCA and left ventricular aneurysm were investigated. The MINOCA was diagnosed according to Scientific Statement from the American Heart Association. The indication for left ventricular reconstruction was as follows: clear evidence of both an aneurysmal and akinetic left ventricle with a history of myocardial infarction accompanied by heart failure symptoms, angina, or ventricular arrhythmias. Major adverse cardiovascular and cerebrovascular events (MACCE), including death, myocardial infarction, stroke was considered the primary endpoints.
Results
The median follow-up for the whole study population was 64.5 months. Seven MINOCA patients developed a left ventricular aneurysm within 4 years and three MINOCA patients were found to have a concomitant left aneurysm at the first admission. Before surgery, no patients were prescribed angiotensin-converting enzyme inhibitors. Statins, dual antiplatelet therapy, and β-blockers were prescribed in 2, 5, and 5 patients, respectively. After surgery, no MACCE occurred in the follow-up. There was a significant increase in ejection fraction (EF) in the follow-up (p = 0.0009).
Conclusions
Close monitoring and standard medical treatment are required before a left ventricular aneurysm occurs in MINOCA patients. Left ventricular reconstruction remains a viable option for MINOCA patients with left ventricular aneurysms and mid-term outcomes were satisfying in this distinct entity.
Inner Riesz pseudo-balayage and its applications to minimum energy problems with external fields
Authors: Zorii Natalia 
Published: January 2023

Abstract
Note: Please see pdf for full abstract with equations.
For the Riesz kernel κα(x, y) := |x − y|α−n of order 0 < α < n on Rn, n ⩾ 2, we introduce the so-called inner pseudo-balayage ˆωA of a (Radon) measure ω on Rn to a set A ⊂ Rn as the (unique) measure minimizing the Gauss functional
∫ κα(x, y) d(μ ⊗ μ)(x, y) − 2 ∫ κα(x, y) d(ω ⊗ μ)(x, y)
over the class ε+(A) of all positive measures μ of finite energy, concentrated on A. For quite general signed ω (not necessarily of finite energy) and A (not necessarily closed), such ˆωA does exist, and it maintains the basic features of inner balayage for positive measures (defined when α ⩽ 2), except for those implied by the domination principle. (To illustrate the latter, we point out that, in contrast to what occurs for the balayage, the inner pseudo-balayage of a positive measure may increase its total mass.) The inner pseudo-balayage ˆωA is further shown to be a powerful tool in the problem of minimizing the Gauss functional over all μ ∈ ε+(A) with μ(Rn) = 1, which enables us to improve substantially many recent results on this topic, by strengthening their formulations and/or by extending the areas of their applications. For instance, if A is a quasiclosed set of nonzero inner capacity c∗(A), and if ω is a signed measure, compactly supported in Rn \ ClRnA, then the problem in question is solvable if and only if either c∗(A) < ∞, or ˆωA(Rn) ⩾ 1. In particular, if c∗(A) = ∞, then the problem has no solution whenever ω+(Rn) < 1/Cn,α, where Cn,α := 1 if α ⩽ 2, and Cn,α := 2n−α otherwise; whereas ω−(Rn), the total amount of the negative charge, has no influence on this phenomenon. The results obtained are illustrated by some examples.
2010 Mathematics Subject Classification: Primary 31C15.
Assessing the Relationship between Serum levels of vitamin D, CD34, CD133, Iron, and Zinc with Nephropathy in type 2 diabetes
Authors: Pouresmaeil Vahid , Jasem Moslem , Maktoof Mostafa , nia Tayebeh Rabani , Tabrizi Masoud Homayouni 
Published: January 2023

Abstract
One of the most important complications of diabetes is nephropathy. This study was designed to determine the relationship between serum levels of vitamin D, CD34, CD133, Iron, and Zinc in patients with diabetic nephropathy. This case-control study was performed on 37 diabetic patients with nephropathy (DNP) and 30 diabetic patients without nephropathy referred to Mashhad hospitals. Blood pressure, Creatinine, Uric acid, lipid profile, and all the diabetic parameters were measured. Also, Serum levels of insulin, vitamin D, CD34, and CD133 were measured by ELISA. Serum levels of Zinc and Iron were measured by atomic absorption spectrometry. The SPSS v.24 was used for data analysis, and the significance level was less than 5%. In body mass index (p = 0.006), diastolic pressure (p = 0.018), Insulin level (p = 0.028), Creatinine (p = 0.013), as well as the duration of diabetes, Uric acid, and Glomerular filtration rate (GFR) were significantly different between the two groups (each p = 0.0001). The vitamin D (p = 0.034), CD34 (p = 0.0001), CD133 (p = 0.025) levels decrease, and Iron (p = 0.0001) increase in case group; But the Zinc level was not different significantly between the two groups (p = 0.127). The increase in the level of Iron and the decrease in the level of vitamin D, CD34, and CD133 are linked to the severity of DNP. The results show that DNP can directly reduce the CD34 and CD133 markers in the body and increase the rate of secondary complications in these patients. Therefore, controlling these cases can improve the complications of type 2 diabetes.
GT-NRSM: efficient and scalable sharding consensus mechanism for consortium blockchain
Authors: Shen Tao , Li Tianyu , Yu Zhuo , Bai FenHua , Zhang Chi 
Published: January 2023

Abstract
Blockchain is an innovative application of distributed storage, consensus mechanism, cryptographic algorithm and other computer technologies. As the underlying architecture of blockchain, consensus mechanism is the key to realize service-oriented applications of blockchain in terms of its security, efficiency and scalability optimization. In some high complexity consensus mechanism such as Practical Byzantine Fault Tolerance (PBFT), throughput is severely reduced as the number of nodes increases, and even in low complexity algorithms such as Raft, the load on leader is severely affected as the network size increases, which affecting consensus efficiency. To solve these problems, in this paper, we propose a node reliable shard model based on guarantee tree (GT-NRSM) that achieves high scalability while ensuring a certain degree of decentralization and security based on consortium blockchain. Firstly, we design a guarantee mechanism to represent the trust relationship between nodes, and then we design a reliable node selection strategy based on the guarantee mechanism to evaluate the node guarantee results and consensus behavior, determine the node trust status, and identify malicious nodes and select a list of trusted leaders. Secondly, we propose a Dual-Leaders supervision mechanism, where deputy detects the heartbeat of leader while the deputy activity is detected by consensus nodes. Finally, we use guarantee mechanism and reliable node selection strategy to design a network partitioning method to achieve high concurrent consensus for multiple partitions and greatly improve the consensus efficiency. Subsequent experiments show that the throughput of the proposed algorithm improves by 48% over Raft and is much higher than PBFT, which has higher throughput and lower consensus latency.
Generating Insight from Indoor Positioning Data in Manufacturing Assembly Line
Authors: Rahman Ashfaqur , Rana Md Mashud , Baumgartner Peter 
Published: January 2023

Abstract
Indoor positioning systems provide a platform to track multiple objects concurrently in an indoor environment. The primary purpose of these systems is to locate objects. However, the tracks generated by moving objects leave characteristic footprints and can be used to infer valuable information for informed decision making. In this paper, we demonstrate how insightful information can be inferred from indoor tracking data of workers in a manufacturing assembly line setup. We utilise two indoor tracking data sets: (i) a real world (and publicly) available data set which contains the tracking data of multiple workers working together on a tricycle assembly line, and (ii) a synthetic data set of a computer assembly line. We aim to develop a set of data analytics methods to infer several Key Performance Indicators (KPIs) or metrices from the tracking data of the workers that include: resource utilization, worker interaction, deviation from ideal workflow and state of the assembly line. While the methods are developed for analysing data from tricycle and synthetic computer assembly line, they can be generalised to any manufacturing assembly line.
Sequence Stratigraphic Analysis of Well BB-3, Deep Offshore, Niger Delta Basin, Nigeria: Insight from Palynological Studies
Authors: Usman H.O. , Unuevho C.I. , Chukwuma-Orji J. N. , Alkali Y. B. 
Published: January 2023

Abstract
Sequence stratigraphic analysis was carried out on well BB-3, deep offshore, Niger Delta Basin, Nigeria. This is done in order to delineate sequence stratigraphic surfaces using vertical sequence of depositional environment. Palynological analysis was carried out on 82 ditch cutting samples from well BB-3 using the standard acid technique in order to zone the well. Open hole geophysical log data was also provided for the studied interval 10700–15600 ft belonging to the Agbada Formation. Lithologically, the section varies from alternation of sand and shale units with carbonaceous debris, mica flakes, ferruginised materials and glauconite at some interval as accessory minerals. Biozonation included three taxon range biozones in BB-3 well, the proposed palynological biozones are Belskipollis elegans, Crassoretitriletes vanraadshooveni, Pachydermites diederixi biozones which are correlatable with the pantropical zones. Samples from the section are dated early Miocene to middle Miocene age based on the independent palynological evidences. The deduced paleoenvironments of the strata penetrated by the well range from outer neritic through bathyal to abyssal. The successions were broken into Highstand Systems Tracts (HST), Lowstand Systems Tracts (LST) and Transgressive Systems Tracts (TST) and chronostratigraphic surfaces such as Maximum Flooding Surface (MFS), Sequence Boundary (SB) and Transgressive Surface (TS). Three HST, three LST, three TST, two MFS and three SB were recognised. The MFS and SB were dated 15.9 Ma, 15.0 Ma and 16.7 Ma, 15.5 Ma, 13.1 Ma respectively by correlation of the established pollen zones with the Niger delta Cenozoic chronostratigraphic chart. The sandstone and shale units of the Systems Tracts are potential hydrocarbon reservoirs and seal rocks respectively.
EasyReg: A ready-to-use deep learning tool for symmetric affine and nonlinear brain MRI registration
Authors: Iglesias Juan Eugenio 
Published: January 2023

Abstract
Volumetric registration of brain MRI is routinely used in human neuroimaging, e.g., to align different MRI modalities, to measure change in longitudinal analysis, to map an individual to a template, or in registration-based segmentation. Classical registration techniques based on numerical optimization have been very successful in this domain, and are implemented in widespread software suites like ANTs, Elastix, NiftyReg, or DARTEL. Over the last 7-8 years, learning-based techniques have emerged, which have a number of advantages like high computational efficiency, potential for higher accuracy, easy integration of supervision, and the ability to be part of a meta-architectures. However, their adoption in neuroimaging pipelines has so far been almost inexistent. Reasons include: lack of robustness to changes in MRI modality and resolution; lack of robust affine registration modules; lack of (guaranteed) symmetry; and, at a more practical level, the requirement of deep learning expertise that may be lacking at neuroimaging research sites. Here, we present EasyReg, an open-source, learning-based registration tool that can be easily used from the command line without any deep learning expertise or specific hardware. EasyReg combines the features of classical registration tools, the capabilities of modern deep learning methods, and the robustness to changes in MRI modality and resolution provided by our recent work in domain randomization. As a result, EasyReg is: fast; symmetric; diffeomorphic (and thus invertible); agnostic to MRI modality and resolution; compatible with affine and nonlinear registration; and does not require any preprocessing or parameter tuning. We present results on challenging registration tasks, showing that EasyReg is as accurate as classical methods when registering 1mm isotropic scans within MRI modality, but much more accurate across modalities and resolutions. EasyReg is publicly available as part of FreeSurfer; see https://surfer.nmr.mgh.harvard.edu/fswiki/EasyReg.
Burden and outcomes of chronic kidney disease in patients presenting with hypertensive crisis
Authors: Viswanathan Stalin , Yalavarthy Yeshwanth Mohan 
Published: January 2023

Abstract
Objectives
To determine prevalence of chronic kidney disease (CKD) in patients presenting with hypertensive crises and to determine their 30-day outcomes with respect to blood pressure (BP), creatinine level, and mortality.
Methods
Patients admitted to the HTN-C were prospectively enrolled. Demographics, examinations, target organ damage (TOD), and investigations were recorded. Patients were classified as hypertensive emergency(HTN-E) or hypertensive urgent(HTN-U). TODs included cardiovascular (acute coronary syndromes and pulmonary edema), neurological (stroke, encephalopathy), ocular (retinal hemorrhage, papilledema), renal (acute kidney injury-AKI), and hematological (microangiopathic hemolytic anemia). The CKD burden was determined. BP, creatinine, and mortality were assessed at discharge and after 30 days. AKI was confirmed at follow-up, with a reduction in creatinine level of > 25%.
Results
235/262 patients had HTN-E; patients were mostly male and middle-aged. The TOD with decreasing frequency was cardiovascular(53%), ocular(29%), neurological(26%), and AKI(24%). Patients with CKD were significantly younger, had hypertension with ≥ 2 drugs, and had a higher proportion of TOD. Patients with CKD had significantly higher BP and creatinine levels at discharge and at 30 days; the non-CKD group had a higher inpatient mortality rate and lower mortality at 30 days.
Conclusions
Specific markers of AKI in patients with underlying CKD are needed to prioritize care during hypertensive crises. Better community-level support in the form of physicians, nephrologists, and dialysis centers is required for timely assessment of the diagnosis and progression of CKD, recognition and treatment of AKI, control of blood pressure, and regular dialysis, which may reduce the load on emergency departments for hypertensive crises.
PROTOCOLO DE ATENDIMENTO FISIOTERAPÊUTICOPARA INDIVÍDUOS COM DOENÇA DE PARKINSON EM NATAL/RN:
Authors: Lopes Dantas Lígia Pablícia , Araujo Gomes Larissa , De Queiroz Aquino Letícia Maria , Neres Aires Diogo , Santos de Vasconcellos Liliane , Souza Ribeiro Tatiana 
Published: January 2023

A Doença de Parkinson (DP) tem como fisiopatologia a disfunção de neurotransmissores, principalmente a perda progressiva dos neurônios dopaminérgicos da porção compacta da substância negra, que exerce importante função no controle motor do indivíduo. O projeto de extensão “Assistência Fisioterapêutica em Grupo para Indivíduos com Doença de Parkinson” (AGruPar) tem como propósito realizar atendimentos em grupo de indivíduos diagnosticados com a DP, de forma presencial e remota, acontecendo uma vez na semana durante 60 minutos. Os atendimentos são divididos por três temáticas, sendo cada dia uma temática: fortalecimento muscular; cognição; marcha, coordenação e equilíbrio. Os atendimentos são realizados por discentes do curso de Fisioterapia da UFRN campus Natal Central, supervisionados por uma preceptora de Pós-Graduação e coordenados por uma docente.

Palavras-chave: extensão; universidade; Parkinson.
Analisa Harmonisa Tegangan Pada Sistem Kelistrikan Kapal Latih Bung Tomo Dengan Simulasi
Authors: Sibuea Andhika Daniel Hartim Pradana 
Published: January 2023

Harmonisa merupakan suatu kejadian yang timbul akibat pengoperasian beban listrik non linier atau motor listrik, yang merupakan sumber terbentuknya gelombang frekuensi tinggi kelipatan dari frekuensi fundamental. Frekuensi tinggi ini mengganggu sistem kelistrikan, sehingga bentuk gelombang arus maupun tegangan menjadi cacat. Dampak dari tegangan dan arus ini dapat menimbulkan panas yang berlebihan pada sistem distribusi kelistrikan,Â rugi-rugi energi dan menurunnya faktor daya sehingga pada akhirnya penggunaan energi listrik menjadi tidak efisien. Harmonisa dapat membuat motor listrik menjadi overheat, terbakarnya kabel, dan rusaknya peralatan listrik. Penelitian ini bertujuan untuk mengetahui dari peralatan listrik apa saja harmonisa itu muncul dan untuk mencegah hubungan arus pendek pada kapal. Untuk itu penulis telah melakukan analisa terhadap sistem distribusi listrik pada kapal yang memiliki gejala drop voltage yang cukup besar, dengan metode pengukuran harmonisa menggunakan simulasi wiring diagram Kapal latih Bung Tomo pada software ETAP dengan standar parameter dari IEC dan BKI. Data kelistrikan kapal diinput dan dijalankan pada software setelah hasil didapat maka dilakukan perhitungan untuk menentukan filter harmonisa. Hasil dari penelitian ini telah dapat mengurangi nilai harmonisa yang melebihi standar THD 5% menjadi THD 1,77% yang dapat mengurangi kerugian pada sistem kelistrikan kapal yang ditimbulkan dari harmonisa.