Miracle-dz/UniFAR-FTUs huggingface dataset:
Cytotoxic, Antidiabetic, and Antioxidant Study of Biogenically Improvised Elsholtzia blanda and Chitosan-Assisted Zinc Oxide Nanoparticles

In the present study, we have improvised a biogenic method to fabricate zinc oxide nanoparticles (ZnO NPs) using chitosan and an aqueous extract of the leaves of Elsholtzia blanda. Characterization of the fabricated products was carried out with the help of ultraviolet–visible, Fourier transform infrared, X-ray diffraction, field emission scanning electron microscopy, high-resolution transmission electron microscopy, selected area electron diffraction, and energy-dispersive X-ray analyses. The size of the improvised ZnO NP measured between 20 and 70 nm and had a spherical and hexagonal shape. The ZnO NPs proved to be highly effective in the antidiabetic test as the sample showed the highest percentage of enzyme inhibition at 74% ± 3.7, while in the antioxidant test, 78% was the maximum percentage of 2,2-diphenyl-1-picrylhydrazyl hydrate scavenging activity. The cytotoxic effect was investigated against the human osteosarcoma (MG-63) cell line, and the IC50 value was 62.61 μg/mL. Photocatalytic efficiency was studied by the degradation of Congo red where 91% of dye degradation was observed. From the various analyses, it can be concluded that the as-synthesized NPs may be suitable for various biomedical applications as well as for environmental remediation.
Predicted star counts in selected fields and photometric bands Applications to galactic structure, the disk luminosity function, and the detection of a massive halo

Tables are presented of predicted star counts in 17 selected directions on the sky as a function of apparent B, V, R, and I magnitudes and absolute visual magnitudes calculated from the Bahcall-Soneira Galaxy model. It is noted that eight of the fields were selected ab initio for their usefulness in determining from star counts either parameters of galactic structure, the faint end of the disk luminosity function, or the detection of a massive stellar halo. Star counts in specified fields to m sub I = 19 mag are able to reveal the faint end of the disk luminosity function down to the end of the hydrogen-burning main sequence. It is thought that star counts at high galactic latitudes to m sub I = 22 mag should reveal the stellar constituents of a massive halo if they are massive enough to be on the hydrogen-burning main sequence.
High precision kinematic surveying with laser scanners

Abstract The kinematic survey of roads and railways is becoming a much more common data acquisition method. The development of the Mobile Road Mapping System (MoSES) has reached a level that allows the use of kinematic survey technology for high precision applications. The system is equipped with cameras and laser scanners. For high accuracy requirements, the scanners become the main sensor group because of their geometric precision and reliability. To guarantee reliable survey results, specific calibration procedures have to be applied, which can be divided into the scanner sensor calibration as step 1, and the geometric transformation parameter estimation with respect to the vehicle coordinate system as step 2. Both calibration steps include new methods for sensor behavior modeling and multisensor system integration. To verify laser scanner quality of the MoSES system, the results are regularly checked along different test routes. It can be proved that a standard deviation of 0.004 m for height of the scanner points will be obtained, if the specific calibrations and data processing methods are applied. This level of accuracy opens new possibilities to serve engineering survey applications using kinematic measurement techniques. The key feature of scanner technology is the full digital coverage of the road area. Three application examples illustrate the capabilities. Digital road surface models generated from MoSES data are used, especially for road surface reconstruction tasks along highways. Compared to static surveys, the method offers comparable accuracy at higher speed, lower costs, much higher grid resolution and with greater safety. The system's capability of gaining 360 profiles leads to other complex applications like kinematic tunnel surveys or the precise analysis of bridge clearances.
Bayesian Statistics for Loan Default

Bayesian inference has gained popularity in the last half of the twentieth century thanks to the wider applications in numerous fields such as economics, finance, physics, engineering, life sciences, environmental studies, and so forth. In this paper, we studied some key benefits of Bayesian inference and how they can be used in predicting loan default in the banking sector. Various traditional classification techniques are also presented to draw comparisons primarily in terms of the ease of interpretability and model performance. This paper includes the use of non-informative priors to attempt to arrive to the convergence of posterior distribution. Finally, with the Bayesian techniques proven to be an alternative to the classical approaches, the paper attempted to demonstrate that Bayesian techniques are indeed powerful in financial data analytics and applications.
Cluster Restricted Maximum Weight Clique Problem and Linkages with Satellite Image Acquisition Scheduling

We consider the cluster-restricted maximum weight clique problem (CRCP), a variation of the well-known maximum weight clique problem. While CRCP itself is mathematically interesting, our motivation to study the problem primarily comes from its application in the area of Satellite Image Acquisition Scheduling. Earth observing satellites revolve around the earth in specific orbits and takes images of prescribed areas requested by the clients. Not every region can be fully acquired in a single satellite pass. This necessitates the division of the region into multiple strips. There might be several image acquisition opportunities for each strip as the satellites have agility in their rolling angles. Then the Satellite Image Acquisition Scheduling Problem (SIASP) is to select the opportunities to acquire as many images as possible, without repetition, within a planning horizon while considering the image priorities and energy constraints. SIASP has a piecewise linear objective function to favor the completion of an image acquisition request and try to avoid partial acquisition of many requests. Extensive experimental study is provided on randomly generated instances based on the predicted statistics given by MDA, Richmond, Canada. These experiments are intended as a preliminary investigation on image acquisition scheduling for the Canadian RADARSAT Constellation Mission (RCM), a constellation of three satellites, which is planned to be launched in 2018. SIASP can be modeled as a CRCP with piecewise linear objective function. We provide integer programming (IP) formulations for CRCP with linear and piecewise linear objective function. We also suggest heuristic (metaheuristic) algorithms that exploit the power of modern IP solvers such as CPLEX. Experimental results using the heuristic algorithms on DIMACS and BOSHLIB benchmark instances for the clique problem are reported. Finally, an exact algorithm for CRCP along with some theoretical analysis is presented.
Monte Carlo Simulations of Radio Pulsars and Their Progenitors

Standard models of binary evolution were applied to a model of the main-sequence population to trace the paths by which a massive star may evolve into a neutron star. Using three different models of binary evolution, the relative number of neutron stars formed by each path was calculated. It was found that none of the models were able to reproduce both the observed velocity distribution of radio pulsars and the observed incidence of binary pulsars. 59 references.
An Anti-collision Early Warning and Detection System for Vehicle Visual Blind Area and Its Control Method

: This paper designs a collision prevention warning detection system and proposes a control method based on this system. The system and its control method have the paired photoelectric signal transmitting unit and the photoelectric signal receiving unit around the vehicle to detect and prevent the collision in the the driver's visual blind area. The system and its control method can realize the real-time voice alarm inside and outside the vehicle, so as to improve the driving safety and reduce the crash accident during the vehicle driving.
Accelerating Deep Neural Networks for Efficient Scene Understanding in Multi-Modal Automotive Applications

Environment perception constitutes one of the most critical operations performed by semi- and fully- autonomous vehicles. In recent years, Deep Neural Networks (DNNs) have become the standard tool for perception solutions owing to their impressive capabilities in analyzing and modelling complex and dynamic scenes, from (often multi-modal) sensory inputs. However, the well-established performance of DNNs comes at the cost of increased time and storage complexity, which may become problematic in automotive perception systems due to the requirement for a short prediction horizon (as in many cases inference must be performed in real-time) and the limited computational, storage, and energy resources of mobile systems. A common way of addressing this problem is to transform the original large pre-trained networks into new smaller models, by utilizing Model Compression and Acceleration (MCA) techniques, improving both their storage and execution efficiency. Within the MCA framework, in this paper, we investigate the application of two state-of-the-art weight-sharing MCA techniques, namely a Vector Quantization (VQ) and a Dictionary Learning (DL) one, as well as two novel extensions, towards the acceleration and compression of widely used DNNs for 2D and 3D object-detection in automotive applications. Apart from the individual (uni-modal) networks, we also present and evaluate a multi-modal late-fusion algorithm for combining the detection results of the 2D and 3D detectors. Our evaluation studies are carried out on the KITTI Dataset. The obtained results lend themselves to a twofold interpretation. On the one hand, they showcase the significant acceleration and compression gains that can be achieved via the application of weight sharing on the selected DNN detectors, with limited accuracy loss, as well as highlight the performance differences between the two utilized weight-sharing approaches. On the other, they demonstrate the substantial boost in detection performance obtained by combining the outcome of the two unimodal individual detectors, using the proposed late-fusion-based multi-modal approach. Indeed, as our experiments have shown, pairing the high-performance DL-based MCA technique with the loss-mitigating effect of the multi-modal fusion approach, leads to highly accelerated models (up to approximately $2.5 \times $ and $6\times $ for the 2D and 3D detectors, respectively) with the performance loss of the fused results ranging in most cases within single-digits figures (as low as around 1% for the class “cars”).
New developments in the ergodic theory of nonlinear dynamical systems

The purpose of this paper is to give a survey of recent results on non-uniformly hyperbolic dynamical systems. The emphasis is on the existence of strange attractors and Sinai-Ruelle-Bowen measures for Henon maps, but we also describe results about statistical properties of such dynamical systems and state some of the open questions in this area.
Breaking down the RECIST 1.1 double read variability in lung trials: What do baseline assessments tell us?

Background In clinical trials with imaging, Blinded Independent Central Review (BICR) with double reads ensures data blinding and reduces bias in drug evaluations. As double reads can cause discrepancies, evaluations require close monitoring which substantially increases clinical trial costs. We sought to document the variability of double reads at baseline, and variabilities across individual readers and lung trials. Material and methods We retrospectively analyzed data from five BICR clinical trials evaluating 1720 lung cancer patients treated with immunotherapy or targeted therapy. Fifteen radiologists were involved. The variability was analyzed using a set of 71 features derived from tumor selection, measurements, and disease location. We selected a subset of readers that evaluated ≥50 patients in ≥two trials, to compare individual reader’s selections. Finally, we evaluated inter-trial homogeneity using a subset of patients for whom both readers assessed the exact same disease locations. Significance level was 0.05. Multiple pair-wise comparisons of continuous variables and proportions were performed using one-way ANOVA and Marascuilo procedure, respectively. Results Across trials, on average per patient, target lesion (TL) number ranged 1.9 to 3.0, sum of tumor diameter (SOD) 57.1 to 91.9 mm. MeanSOD=83.7 mm. In four trials, MeanSOD of double reads was significantly different. Less than 10% of patients had TLs selected in completely different organs and 43.5% had at least one selected in different organs. Discrepancies in disease locations happened mainly in lymph nodes (20.1%) and bones (12.2%). Discrepancies in measurable disease happened mainly in lung (19.6%). Between individual readers, the MeanSOD and disease selection were significantly different (p<0.001). In inter-trials comparisons, on average per patient, the number of selected TLs ranged 2.1 to 2.8, MeanSOD 61.0 to 92.4 mm. Trials were significantly different in MeanSOD (p<0.0001) and average number of selected TLs (p=0.007). The proportion of patients having one of the top diseases was significantly different only between two trials for lung. Significant differences were observed for all other disease locations (p<0.05). Conclusions We found significant double read variabilities at baseline, evidence of reading patterns and a means to compare trials. Clinical trial reliability is influenced by the interplay of readers, patients and trial design.
Association between diabetes mellitus, prediabetes and risk, disease progression of Parkinson's disease: A systematic review and meta-analysis

Background Previous studies reported inconsistent results regarding association between diabetes mellitus (DM), prediabetes and risk, disease progression of Parkinson's disease (PD). The meta-analysis was made to investigate association between DM, prediabetes and risk, disease progression of PD. Methods Literatures investigating association between DM, prediabetes and risk, disease progression of PD were searched in these databases: PubMed and Web of Science. Included literatures were published before October 2022. STATA 12.0 software was used to compute odds ratios (ORs)/relative risks (RRs) or standard mean differences (SMDs). Results DM was associated with a higher risk of PD, compared to non-diabetic participants with a random effects model (OR/RR = 1.23, 95% CI 1.12–1.35, I2 = 90.4%, p < 0.001). PD with DM (PD-DM) was associated with a faster motor progression compared to PD without DM (PD-noDM) with a fixed effects model (RR = 1.85, 95% CI 1.47–2.34, I2 = 47.3%, p = 0.091). However, meta-analysis for comparison in change rate of United Rating Scale (UPDRS) III scores from baseline to follow-up time between PD-DM and PD-noDM reported no difference in motor progression between PD-DM and PD-noDM with a random effects model (SMD = 2.58, 95% CI = −3.11 to 8.27, I2 = 99.9%, p < 0.001). PD-DM was associated with a faster cognitive decline compared to PD-noDM with a fixed effects model (OR/RR = 1.92, 95% CI 1.45–2.55, I2 = 50.3%, p = 0.110). Conclusions In conclusion, DM was associated with a higher risk and faster disease decline of PD. More large-scale cohort studies should be adopted to evaluate the association between DM, prediabetes and PD.
Tearing mode formation and radiative edge cooling prior to density limit disruptions in ASDEX Upgrade

Tearing mode formation is investigated for ohmic density limit discharges on the ASDEX Upgrade tokamak at medium and high safety factors (q95=3.8, 4.9, 6.0). Low electron temperatures inside magnetic islands and the observation of localized C III impurity radiation suggest that a thermal instability, as proposed by Rebut and Hugon, destabilizes the (m, n)=(3,1) and (4,1) islands, which grow during the current profile contraction phase. In contrast, the (2,1) islands appear to be thermally stable. Minor disruptions lead to step-wise loss of confinement, first localized at the 4 2 surface, then after a time delay comparable to the resistive time-scale, at the q=3 surface and after a second time delay, at the q=4 surface. It is found that (3,1) islands, unlike (2,1) islands, are quenched by the high heat flux during minor disruptions
Outlier Detection in Logistic Regression

The use of logistic regression, its modelling and decision making from the estimated model and subsequent analysis has been drawn a great deal of attention since its inception. The current use of logistic regression methods includes epidemiology, biomedical research, criminology, ecology, engineering, pattern recognition, machine learning, wildlife biology, linguistics, business and finance, et cetera. Logistic regression diagnostics have attracted both theoreticians and practitioners in recent years. Detection and handling of outliers is considered as an important task in the data modelling domain, because the presence of outliers often misleads the modelling performances. Traditionally logistic regression models were used to fit data obtained under experimental conditions. But in recent years, it is an important issue to measure the outliers scale before putting the data as a logistic model input. It requires a higher mathematical level than most of the other material that steps backward to its study and application in spite of its inevitability. This chapter presents several diagnostic aspects and methods in logistic regression. Like linear regression, estimates of the logistic regression are sensitive to the unusual observations: outliers, high leverage, and influential observations. Numerical examples and analysis are presented to demonstrate the most recent outlier diagnostic methods using data sets from medical domain.
The views of University Students About Civic Involvement Projects

The aim of this study is to reveal the views of university students who conduct civic involvement projects on these projects. Case study research method which is a qualitative research approach and criterion sampling, one of the purposive sampling types, were used in the study. The participants of the study are university students from undergraduate, graduate and doctorate education programs. The data of the study were collected through a questionnaire with five open-ended questions prepared by the researcher. Content analysis method was used for the analysis of the data. At the end of the study, it is revealed that the studies of university students who conduct civic involvement projects are for students, children, animals, elders and environment, the projects provide educational, social, socio-economic, emotional and individual contributions to individuals, the awareness of social sensitivity in individuals can be realized through education, social media, responsibility and family, the projects contribute to individuals such as taking responsibility, being sensitive and thinking broadly, and the definition of social sensitivity has the same meanings although they express the definition in different ways. As a result of the study, some suggestions are offered, such as taking the opinions of the instructors who conduct civic involvement projects and the individuals who are applied civic involvement projects.
Heat transfer phenomenon in a retarded boundary layer over a moving continuous cylinder

The phenomena of flow separation on a surface of finite length is analogous to boundary layer flows caused by retarded motion of continuous surfaces, which ultimately seize at some downstream position and increase drag on aerodynamic vehicles. According to the literature, a stationary surface of finite length will generate a boundary layer that is less energetic than one that is developed over a moving continuous surface. This means that a moving continuous surface is preferred to a stationary surface of finite length for the sustainability of the transport phenomena in such a retarded flow, which must eventually meet the flow separation. Therefore, the goal of this study is to conduct a heat transfer analysis in a delayed laminar boundary layer generated by a moving continuous cylinder with a constant radius. Wall temperature of uniform nature is considered in this investigation. In most of the boundary layer flows the self-similarity of the flow does not persist because of choosing the reference velocity of the desired character. Thus, the problem becomes non-similar. In general, the non-similarity of a flow may appear due to various aspects of the problem such as the retarded nature of the reference velocity, the surface temperature, the curvature of the body, etc. Surface transverse curvature imparts favorable consequences on the separating boundary layer and hence on the seizing flow character. The purpose of this investigation is to determine how TVC k and the wall velocity power index m affect temperature profiles, the local Nusselt number Nux , the thickness of the thermal layer, and the thermal diffusivity of heat in a retarded boundary layer. In addition to this, the influence of Prandtl number Pr and Stanton number St has also been investigated. The numerical solution is computed using an implicit finite difference scheme, commonly known as the Keller-Box scheme in MATLAB scientific computing software Investigations reveal that the TVC assists the thermal transport by enhancing the rate of heat transfer and the length of the convectively heat transferring region (starting from the leading edge to the location where the flow gets seized) by increasing the longitudinal region of flow (starting from the leading edge to the location where the flow gets seized) on the surface. The surface wall velocity power index 1$? > m>1 acts to decrease the temperature distribution and reduces the heat transfer rate at the surface. Further, the Prandtl number Pr reduces the thermal boundary layer thickness and the Stanton number St but enhances the local Nusselt number.