Miracle-dz/UniFAR-FTUs huggingface dataset:
SPH simulation of turbulent flow past a high-frequency in-line oscillating cylinder near free-surface

This paper studies a two-dimensional incompressible viscous flow past a circular cylinder with in-line oscillation close to a free-surface. The sub-particle scale (SPS) turbulence model of a Lagrangian particle-based smoothed-particle hydrodynamics (SPH) method has been used to solve the full Navier–Stokes equations together with the continuity equation. The accuracy of numerical code has been verified using two cases consisting of an oscillating cylinder placed in the stationary fluid, and flow over a fixed cylinder close to a free-surface. Simulations are conducted for the Froude number of 0.3, the Reynolds numbers of 40 and 80, various gap ratios for fully-submerged and half-submerge cylinders. The dimensionless frequency and amplitude of oscillating have been chosen as 0.5, 0.8 and 10, 15, respectively. The selection of such a high oscillating frequency causes the flow regime to become turbulent. It is seen that the gap ratio defined as the ratio of cylinder distance from free-surface and its diameter, strongly affects the flow pattern and the magnitude of the drag and lift coefficients. The jet-like flow (the region above the cylinder and beneath the free-surface) creation is discussed in detail and showed that the strength of this jet-like flow is weakened when the gap ratio shrinks. It is seen that by decreasing the gap ratio, the lift and drag coefficients increase and decrease, respectively. It is found that the Reynolds number has an inverse effect on the drag and lift coefficients. Also, it is concluded that by increasing the amplitude of oscillation the drag coefficient increases.
Classification of Vogt-Koyanagi-Harada disease using feature selection and classification based on wide-field swept-source optical coherence tomography angiography

Background: Vogt-Koyanagi-Harada (VKH) disease is a common and easily blinded uveitis entity, with choroid being the main involved site. Classification of VKH disease and its different stages is crucial because they differ in clinical manifestations and therapeutic interventions. Wide-field swept-source optical coherence tomography angiography (WSS-OCTA) provides the advantages of non-invasiveness, large-field-of-view, high resolution, and ease of measuring and calculating choroid, offering the potential feasibility of simplified VKH classification assessment based on WSS-OCTA. Methods: 15 healthy controls (HC), 13 acute-phase and 17 convalescent-phase VKH patients were included, undertaken WSS-OCTA examination with a scanning field of 15 × 9 mm2. 20 WSS-OCTA parameters were then extracted from WSS-OCTA images. To classify HC and VKH patients in acute and convalescent phases, two 2-class VKH datasets (HC and VKH) and two 3-class VKH datasets (HC, acute-phase VKH, and convalescent-phase VKH) were established by the WSS-OCTA parameters alone or in combination with best-corrected visual acuity (logMAR BCVA) and intraocular pressure (IOP), respectively. A new feature selection and classification method that combines an equilibrium optimizer and a support vector machine (called SVM-EO) was adopted to select classification-sensitive parameters among the massive datasets and to achieve outstanding classification performance. The interpretability of the VKH classification models was demonstrated based on SHapley Additive exPlanations (SHAP). Results: Based on pure WSS-OCTA parameters, we achieved classification accuracies of 91.61% ± 12.17% and 86.69% ± 8.30% for 2- and 3-class VKH classification tasks. By combining the WSS-OCTA parameters and logMAR BCVA, we achieved better classification performance of 98.82% ± 2.63% and 96.16% ± 5.88%, respectively. Through SHAP analysis, we found that logMAR BCVA and vascular perfusion density (VPD) calculated from the whole field of view region in the choriocapillaris (whole FOV CC-VPD) were the most important features for VKH classification in our models. Conclusion: We achieved excellent VKH classification performance based on a non-invasive WSS-OCTA examination, which provides the possibility for future clinical VKH classification with high sensitivity and specificity.
Estimating fat, paste and gas in a proving Danish paste by MRI – Method, simulations and experimental results

This paper presents a method to characterize the development of the structures of puff pastries during proving using MRI. Since the resolution is large, each pixel contains an unknown proportion of three components: fat, paste and gas. The signal to noise ratio is low since gas which reaches 80% at the end of proving gives no signal. The signal is the sum of reference signals, corresponding to pixels filled with one component, weighted by the proportions. The reference signals were supposed to be known. We adopted an edge-preserving approach based on the minimization of a penalized least-square criterion. This criterion is the weighted sum of a term accounting for the fidelity to data and a regularization term. The minimization of the criterion is based on a non-linear conjugate gradient algorithm. The settings of the weights of the two terms is based on simulations. Then simulation results are presented. The mean error was similar with or without regularization and depended on the components and their proportion (less that 1% up to 6%). Fat and gas proportions were overestimated, paste proportion was underestimated. The dispersion of the results was lower with regularization (from 0.3% up to 1.5 %). Monte-Carlo simulations showed that these results were not influenced very much by the uncertainty on the reference signals at the end of the proving. Larger uncertainties were found at the beginning of proving. We showed that the regularization of the solutions did improve the visualization of the structures confirming the interest of this approach.We also found that layers down to 40 microns thick and bubbles of which size exceeded 2.5mm could be easily distinguished in fat and gas proportion maps respectively. Experiments on genuine MRI images of Danish paste confirmed the results obtained with the simulation study. We were able to validate the method at the scale of the Danish paste by observing the evolution of the sum of the fat proportion over time, as well as the evolution of the gas content compared with the evolution of the size of the pastry. This confirmed the possibility to use the method to study the proving of a Danish paste.
The influence of COVID-19-related resilience on depression, job stress, sleep quality, and burnout among intensive care unit nurses

The COVID-19 pandemic has placed immense pressure on healthcare workers, in particular, Intensive Care Unit (ICU) nurses, who are at the forefront of managing critically ill COVID-19 patients. This has led to increased stressors and workload, which are associated with negative mental health outcomes such as depression, job stress, sleep disturbances, and burnout. However, COVID-19-related resilience may have mitigated these negative effects. ICU nurses with higher levels of COVID-19-related resilience may be better equipped to manage the stress and job demands during the pandemic, leading to improved mental health outcomes. Therefore, this study aimed to comprehensively explore the factors influencing the resilience of ICU nurses and provide baseline knowledge for future studies to develop interventions that promote COVID-19-related resilience. With shift work and COVID-19 experience with adult patients from hospitals across three regions of South Korea. The questionnaire included scales/measures of nurses’ depression, job stress, sleep quality, and burnout. Results confirmed that resilience was negatively correlated with depression and burnout, and that ICU nurses’ relative levels of resilience strongly influenced their experience of burnout. The findings of this study make a significant contribution to the literature because they focus on resilience, specifically in the context of ICU nursing in South Korea, which has become more challenging and demanding due to the pandemic.
Mild traumatic brain injury increases engagement in criminal behaviour 10 years later: a case–control study

Introduction Sustaining a mild traumatic brain injury (mTBI) has been linked to increased criminal behaviour in later life. However, previous studies have not controlled for the number of injuries, gender, social deprivation, impact of past behaviour, or link to offence type. This study aims to determine if people who experienced a single or multiple mTBI have increased risk of criminal behaviour 10 years post-injury than matched orthopaedic controls. Methods This was a case control study of adults (aged ≥16 years) who experienced a medically diagnosed mTBI and controls who experienced a lower limb fracture (with no TBI) over a 12-month period (01/01/2003–31/12/2003). Participants were identified within Stats New Zealand’s Integrated Data Infrastructure (national database including health and justice records). Participants who experienced a subsequent TBI (post-2003), who were not resident in New Zealand, and who died by 2013 were excluded. Case and controls were matched by age, sex, ethnicity, deprivation index and pre-injury criminal history. Results The study included N = 6,606 mTBI cases and N = 15,771 matched trauma controls. In the 10 years after injury, people experiencing a single mTBI had significantly higher numbers of violent charges (0.26 versus 0.21, p < 0.01) and violent convictions (0.16 versus 0.13, p < 0.05) but not for all court charges and convictions. Analysis of those with a history of prior mTBIs yielded larger effects, with significantly higher numbers of violent charges (0.57 versus 0.24, p < 0.05) and violent convictions (0.34 versus 0.14, p < 0.05). For males, the single mTBI case group had a significantly higher number of violent charges (0.40 versus 0.31, p < 0.05) and violent convictions (0.24 versus 0.20, p < 0.05) but this was not observed for females or all offence types. Discussion Experiencing multiple mTBIs over the lifetime increases the number of subsequent violence-related charges and convictions but not for all offence types in males but not for females. These findings highlight the need for improved recognition and treatment of mTBI to prevent future engagement in antisocial behaviour.
Pathological effects due to metacercariae of Clinostomum piscidium migration in snakeskin gourami (Trichopodus pectoralis) in Thailand

Clinostomum spp. is a fish-borne pathogen and a digenetic trematode with a global range. Despite its zoonotic relevance, the pathogenic impact of the parasite in Thai aquaculture is currently unclear. The present study deals with the pathogenic changes that fluke causes in their host, Trichopodus pectoralis, and the molecular confirmation of the Clinostomum piscidium by targeting 18 s rDNA and ITS gene. The metacercariae of C. piscidium were discovered in the body cavity of infected fish. The gross pathological examination revealed a few white migratory tracks on the surface of the liver and spleen. The migratory track showed histologically as a primary hemorrhage and necrosis of hepatic cells surrounded by a layer of macrophages and epithelioid cells, inflammatory cells, and eosinophilic granular cells in the cytoplasm of liver cells and close to the epithelial cells of the intestine. Also, the migratory track in the spleen appeared as a marked decrease of Red Blood Cell (RBC) count and changes in the necrotic tissue. Infection with this metacercaria produced hepatic tissue injury, which disrupted hepatic metabolism and decreased body weight in the fish hosts. The findings of the study suggest that the pathological effect of C. piscidium on farm T. pectoralis can cause significant economic loss by stunting fish development and predisposing fish to opportunistic pathogens in the environment. Hence, the treatment and control of C. piscidium infections are crucial for the viability of the aquaculture sector since this parasite has been found to cause pathological damage to the vital organs of fish.
Noxious radiant heat evokes bi-component nociceptive withdrawal reflexes in spinal cord injured humans—A clinical tool to study neuroplastic changes of spinal neural circuits

Investigating nocifensive withdrawal reflexes as potential surrogate marker for the spinal excitation level may widen the understanding of maladaptive nociceptive processing after spinal cord injury (SCI). The aim of this prospective, explorative cross-sectional observational study was to investigate the response behavior of individuals with SCI to noxious radiant heat (laser) stimuli and to assess its relation to spasticity and neuropathic pain, two clinical consequences of spinal hyperexcitability/spinal disinhibition. Laser stimuli were applied at the sole and dorsum of the foot and below the fibula head. Corresponding reflexes were electromyography (EMG) recorded ipsilateral. Motor responses to laser stimuli were analyzed and related to clinical readouts (severity of injury/spasticity/pain), using established clinical assessment tools. Twenty-seven participants, 15 with SCI (age 18–63; 6.5 years post-injury; AIS-A through D) and 12 non-disabled controls, [non-disabled controls (NDC); age 19–63] were included. The percentage of individuals with SCI responding to stimuli (70–77%; p < 0.001), their response rates (16–21%; p < 0.05) and their reflex magnitude (p < 0.05) were significantly higher compared to NDC. SCI-related reflexes clustered in two time-windows, indicating involvement of both A-delta- and C-fibers. Spasticity was associated with facilitated reflexes in SCI (Kendall-tau-b p ≤ 0.05) and inversely associated with the occurrence/severity of neuropathic pain (Fisher’s exact p < 0.05; Eta-coefficient p < 0.05). However, neuropathic pain was not related to reflex behavior. Altogether, we found a bi-component motor hyperresponsiveness of SCI to noxious heat, which correlated with spasticity, but not neuropathic pain. Laser-evoked withdrawal reflexes may become a suitable outcome parameter to explore maladaptive spinal circuitries in SCI and to assess the effect of targeted treatment strategies. Registration: https://drks.de/search/de/trial/DRKS00006779.
Arithmetic research based on wavelet transform multi-layer block matching multi-target tracking

Aero-camera on plane and the CCD(Charge Coupled Device) camera on missile are all fitted on moving carrier. They continuously shoot image, which background is moving. Sometimes we need to detect moving targets in the moving background, and track them. An arithmetic based on wavelet transform multi-layer block matching tracking is suggested. It can detect moving targets from the background, and can work out the figure center of the targets, and trace out the movement contrail of the targets. Compared with traditional block matching tracking arithmetic, it overcomes some disadvantages, such as a mass of operation, inaccurate matching in the low SNR(Signal Noise Ratio) image.
Research Tendencies in the Discipline of Distance Education (2015-2022): Examination of Doctoral Theses in Higher Education in Turkey

The discipline of distance education is evolving and becoming mainstream, and this view requires examining research tendencies in the field. Motivated by this justification, it can be argued that understanding distance education to the fullest extent is possible partially through examining changes in theory and practice, as research conducted in the field reflects changes, dynamics, and perspectives. In this regard, the purpose of this paper is to present the research tendencies in doctoral theses in the Turkish higher education context with a specific focus on distance education. In line with this aim, a total of 265 doctoral theses published between 2015 and 2022 were examined through data mining and analytics approaches. The analysis of the titles through t-SNE analysis revealed four broad themes. These are: (1) more emphasis on learning processes; (2) the comparison of online technologies and online learning spaces; (3) a strong focus on educational technologies; and (4) the limitations emerging from comparative studies. The examination of the abstracts through text-mining identified the following themes: (1) the methodological vicious circle, the pursuit of methodological perfection, and lack of critical perspectives; (2) the tendency to use online [educational] technologies; (3) the comparison of distance and face-to-face education; and (4) the design of social interaction and communication in distance education processes. Finally, the analysis of the keywords through word clouds surfaced the following research tendencies: (1) Technology-supported distance education processes; (2) the wide use of educational technologies; (3) focusing on issues related to the learners in distance education. The paper concludes with implications and recommendations for future research directions.
SYSTEM IDENTIFICATION BY A GENERALIZED INTERIOR POINT ALGORITHM AND NONLINEAR OPTIMIZATION METHODS CONSIDERING ARMA MODEL

In this paper, we describe our implementation of an interior point algorithm for large scale systems. First we identify system with small and medium methods convex optimization, then we use interior point method for identification. Finally we offer an interior point method that uses nonlinear cost function and see that we achieve a good trade-off between error and CPU time. Actually, in this paper, we are looking for a method that can identify large scale systems with low model order, error and CPU time of solution of simulation. Previous articles didn’t check the order of the computed model, and the relationship between the error and CPU time. We assume that the model of our simulation is ARMA. We are going to identify a large scale system and compute the error and CPU time and compare the relationships. Examined data in this paper is related to cutaneous potential recordings of a pregnant woman. These data are pendulous and have a large standard deviation; therefore, it can’t be fitted with ordinary curve fittings, so we use the smoothing spline for computing the order of the model. Finally, we checked the influence of the number of data on error and CPU time and order of model.
Dual decomposition and proximal minimization for multi-agent distributed optimization with coupling constraints

We study distributed optimization in a cooperative multi-agent setting, where agents need to agree on the usage of shared resources and can communicate via a time-varying network to this purpose. Each agent has its own decision variables that should be set so as to minimize its individual objective function subject to local constraints. Resource sharing is modeled via coupling constraints that involve the non-negativity of the sum of agents' individual functions, each one depending on the decision variables of one single agent. We propose a novel distributed algorithm to minimize the sum of the agents' objective functions subject to both local and coupling constraints, where dual decomposition and proximal minimization are combined in an iterative scheme. Notably, privacy of information is guaranteed since only the dual optimization variables associated with the coupling constraints are exchanged by the agents. Under convexity assumptions, jointly with suitable connectivity properties of the communication network, we are able to prove that agents reach consensus to some optimal solution of the centralized dual problem counterpart, while primal variables converge to the set of optimizers of the centralized primal problem. A numerical example shows the efficacy of the proposed approach.
A Lazy, Eclectic Derivation of the Black Scholes Formula

The classical Black Scholes option-pricing formula which has been an indispensable tool in the hands of the practitioners of quantitative finance has been derived numerous ways. Some of these derivations have been very theoretical with the full machinery of Girsanov's theorem, some informal and based on practical hedging arguments. We suggest yet another derivation (Actually, we just do certain things while computing the drift in the changed measure very differently), which is based on sound theoretical framework, but does not use much of advanced theory. Instead the derivation suggested here makes repeated use of the technique of measure change that is rather a universal and standard tool in derivative pricing. The approach is lazy, because it defers doing certain things, unless absolutely necessary, while at the same time elegant enough to be pedagogically interesting in its own right.
Estimation of Hurst Parameter in Longitudinal Data with Long Memory

This paper considers the problem of estimation of the Hurst parameter H (1/2, 1) from longitudinal data with the error term of a fractional Brownian motion with Hurst parameter H that gives the amount of the long memory of its increment. We provide a new estimator of Hurst parameter H using a two scale sampling method based on -Sahalia and Jacod (2009). Asymptotic behaviors (consistent and central limit theorem) of the proposed estimator will be investigated. For the proof of a central limit theorem, we use recent results on necessary and sufficient conditions for multi-dimensional vectors of multiple stochastic integrals to converges in distribution to multivariate normal distribution studied by Nourdin et al. (2010), Nualart and Ortiz-Latorre (2008), and Peccati and Tudor (2005).
An in-silico Evaluation of Some Schiff bases for Their Potency Against SARS-CoV-2 Main Protease, PASS Prediction and ADMET Studies

SARS-CoV-2 has created an agonizing pandemic situation all over the world. The inhibition of SARS-CoV-2 main protease (Mpro) by the blockage of viral replication is considered an important drug target to the many researchers working to discover specific drugs for COVID-19 treatment. Schiff bases being documented to possess antimicrobial properties might be investigated as the candidate against COVID-19. Bioactivities of some symmetrical bis-Schiff bases were evaluated using computational studies on the basis of binding affinity, PASS prediction and ADMET study. On the basis of binding affinity, it is concluded that among eighteen tested ligands 2, 5, 8, 16, 17 showed excellent, ligands 4, 6, 18 showed good and the remaining ligands showed moderate inhibition against SARS-CoV-2 Mpro (6LU7) compared to a prescribed anti-Covid-19 drug, hydroxychloroquine (HCQ). PASS prediction revealed some of Schiff bases to have good anti-carcinogenic, anti-tuberculosis, antifungal, and antiviral activities. ADMET study predicted them to be non-toxic and harmless indicating that Schiff bases may act as a promising drug candidate for the treatment of COVID-19.