Miracle-dz/UniFAR-FTUs huggingface dataset:
Contour extraction of artificial ski runs based on composite supervoxels

Increasing numbers of people have taken up skiing in recent years due to the strong promotion of the Beijing Winter Olympics in 2022 by We Media. Nowadays, the establishment of three-dimensional digital twin snow fields has become an important way to effectively manage and maintain snow fields. However, due to the large altitude difference and the presence of many trees and rocks in ski resorts, traditional methods face difficulties such as low segmentation accuracy and low merging efficiency of segmentation blocks when performing semantic segmentation of ski runs. Consequently, this paper proposes a contour extraction method of artificial ski runs using composite supervoxels based on the characteristics of artificial ski resorts. To begin with, the point cloud data set of ski resort is segmented to get supervoxels; secondly, the difference in elevation between the seed supervoxel and the adjacent connecting block is calculated to determine whether the merging plane is the ground or another plane; then, according to the normal vector angle threshold and the orthogonal distance threshold, the similarity between the current clustering region and adjacent blocks is evaluated; and finally, the region growth algorithm is optimized based on the point cloud supervoxels of ski resorts, in order to reap the benefits of ski track semantic segmentation. And experiments have shown that the proposed method is superior to the other two in terms of segmentation accuracy, efficiency, and robustness, and is suitable for the segmentation and extraction of ski tracks in complex scenes, such as artificial snow fields.
Predicting Cell Cleavage Timings from Time-Lapse Videos of Human Embryos

Assisted reproductive technology is used for treating infertility, and its success relies on the quality and viability of embryos chosen for uterine transfer. Currently, embryologists manually assess embryo development, including the time duration between the cell cleavages. This paper introduces a machine learning methodology for automating the computations for the start of cell cleavage stages, in hours post insemination, in time-lapse videos. The methodology detects embryo cells in video frames and predicts the frame with the onset of the cell cleavage stage. Next, the methodology reads hours post insemination from the frame using optical character recognition. Unlike traditional embryo cell detection techniques, our suggested approach eliminates the need for extra image processing tasks such as locating embryos or removing extracellular material (fragmentation). The methodology accurately predicts cell cleavage stages up to five cells. The methodology was also able to detect the morphological structures of later cell cleavage stages, such as morula and blastocyst. It takes about one minute for the methodology to annotate the times of all the cell cleavages in a time-lapse video.
I nternational J ournal of V eterinary S cience

Light has been used as a management tool during incubation, but with varying results. The study was to evaluate the effect of egg exposure to LED light at different phases and for different durations on embryo development, hatching and hematological parameters. Five hundred Sasso broiler eggs were assigned to 4 treatments: eggs incubated in the dark throughout incubation (TA), eggs exposed to light from days 1-21 (TB), days 7-21 (TC) and days 14-21 (TD) of incubation. The eggs were photo-exposed using a 6,500k cool LED at 788 clux intensity. The result shows that TB, TC and TD had decreased (P<0.05) average hatch time, internal piping duration, external piping and hatch duration compared to TA. TA eggs recorded a wider hatch window compared to other treatments and the narrowest was TB, comparable to TC and TD. Hematological parameters were not affected at hatch, but the heterophil/lymphocyte ratio was significantly lower (P<0.05) in all photo-incubation treatments when compared to TA. Hatching events in slow-growing broiler birds can be accelerated by pre-hatch light stimulation, moreover, photo-incubation from the first day of incubation narrowed the spread of hatch. Photo-incubating eggs from days 1-21 will enhance hatch synchronization.
ALGEBRAIC SEMANTICS OF PROGRAMS WITH DYNAMIC STRUCTURE

In order to describe algebraic semantics of programs, which do not necessarily terminate, the operations of Σ algebra have been generalized to the case of partial functions on carrier sets. The coweak initial model and the weak terminal model have been proved to exist under certain conditions. However, the prevailing approach fails in the case where the static-structure of the program does not coincide with its dynamic structure. In this paper, a new approach is proposed, which can be used to describe algebraic semantics of programs with dynamic structures as goto statement and nested block. Thus the application of algebraic semantics is extended.
Efficacies of artificial neural networks ushering improvement in the prediction of extant credit risk models

Abstract The study’s objective is to check whether the predictive power of Machine Learning Techniques is better than Logistic Regression in predicting the bankruptcy of firms and that the same predictive power of ascertaining bankruptcy improves when a proxy for uncertainty is added to the model as a default driver. We considered the covid pandemic a black swan event that had caused ambiguity. A significant factor that has increased the probability of bankruptcy in recent times has been the large-scale supply chain disruptions and crippling lockdowns. Firms are trying to get back to pre-Covid utilization of plant capacity or pivot their business models differently to seize newer opportunities amidst the crisis. We considered the change in operating expenditure (primarily decrease) as our proxy for uncertainty as firms were forced to cut down majorly on their operations and thus incurred lesser variable costs. In an economy showing inflationary trends, the operating expenses will generally increase. But we found that the operational costs had shown a dip in the case of many of the firms during FY 20–21, and we attributed it to Covid disruptions. Results show that Machine Learning Techniques are better than Logistic Regression in predicting the bankruptcy of firms and that the same predictive power of ascertaining bankruptcy improves when a proxy for uncertainty is added to the model.
High-sensitivity single molecule fluorescence detection using scanning single-molecule counting

A new, simple technique for single molecule fluorescence detection has been developed and detection limit of less than 100 aM fluorophores has been demonstrated. The technique, similarly to Fluorescence Correlation Spectroscopy (FCS) and other related techniques, uses confocal optics, but differs in that it detects individual molecules crossing the inside of a scanning confocal volume without using statistical techniques as applied in FCS or similar methods. The scanning speed of the confocal volume is higher than the Brownian motion speed of the molecules. Thus, the time evolution of the light intensity data reflects the confocal volume intensity profile, which clearly shows the crossing of single molecules. The estimated total scanning volume enables the concentration or the density of molecules to be obtained. In addition, information related to the rotational and translational diffusion of the molecule was obtained for the purpose of identifying different molecules. It was shown that utilizing the plural characteristic properties of molecules passing through a confocal volume makes possible the discrimination of different molecules. The proposed technique is based on the simple principle of counting molecules one by one using a scanning confocal volume, and is hereafter referred to as Scanning Single-Molecule Counting (SSMC).
Quantitative determination and antibacterial properties of TiO2 nanoparticle-doped glass ionomer cement: an in vitro study

Purpose: The aim of the present study is to determine the amount of titanium ions released into the artificial salivary medium by modified glass ionomer cement (GIC) doped with 3% and 5% (w/w) titanium dioxide nanoparticles (TiO2-NPs), and to evaluate their antibacterial properties. Materials and methods: 120 cylindrical discs with a diameter of 4 mm and a height of 6 mm were made with 3% and 5% w/w modified GIC containing TiO2 NPs, divided into two groups of 60, and immersed in a chemically synthesized salivary medium. The samples were quantified over four-time periods: 24 hours, two months, four months, and six months, using inductively coupled plasma mass spectroscopy (ICP-MS), antibacterial properties were evaluated by means of colony forming count (CFU) method. Results: The amount of titanium ions released from the discs that received 3%(w/w) TiO2 was highest in the first two months, with no significant release at successive intervals. Also, the second group, which included 5% (w/w) TiO2, saw a considerable ion release at every interval, with the second month seeing the maximum release. The levels in the 5% (w/w) group were consistently higher when the two concentrations were compared at each of the four time points, indicating a considerable increase in titanium release and antibacterial property with a concentration increase from 3% to 5%. Conclusion: 3% and 5% (w/w) concentrations may be considered safe and exhibit significant antimicrobial effect, titanium ions were discharged at higher rates in 5% (w/w) modified GIC containing TiO2-NPs than in 3% (w/w) modified GIC containing TiO2-NPs.
Transcriptome Analysis and Identification of Sesquiterpene Synthases in Liverwort Jungermannia exsertifolia

The liverwort Jungermannia exsertifolia is one of the oldest terrestrial plants and rich in structurally specific sesquiterpenes. There are several sesquiterpene synthases (STSs) with non-classical conserved motifs that have been discovered in recent studies on liverworts; these motifs are rich in aspartate and bind with cofactors. However, more detailed sequence information is needed to clarify the biochemical diversity of these atypical STSs. This study mined J. exsertifolia sesquiterpene synthases (JeSTSs) through transcriptome analysis using BGISEQ-500 sequencing technology. A total of 257,133 unigenes was obtained, and the average length was 933 bp. Among them, a total of 36 unigenes participated in the biosynthesis of sesquiterpenes. In addition, the in vitro enzymatic characterization and heterologous expression in Saccharomyces cerevisiae showed that JeSTS1 and JeSTS2 produced nerolidol as the major product, while JeSTS4 could produce bicyclogermacrene and viridiflorol, suggesting a specificity of J. exsertifolia sesquiterpene profiles. Furthermore, the identified JeSTSs had a phylogenetic relationship with a new branch of plant terpene synthases, the microbial terpene synthase-like (MTPSL) STSs. This work contributes to the understanding of the metabolic mechanism for MTPSL-STSs in J. exsertifolia and could provide an efficient alternative to microbial synthesis of these bioactive sesquiterpenes.
In search of ways to improve the properties of a laser-accelerated heavy ion beam relevant for fusion fast ignition

Ion fast ignition (IFI) is one of the proposed options for inertial fusion in which the ignition of nuclear fuel is initiated by an intense ion beam. In this paper, the properties of a laser-accelerated heavy ion beam are investigated for the possible use of such a beam as a fuel igniter in the IFI scenario. Using a two-dimensional particle-in-cell code, detailed studies of laser-driven heavy ion acceleration were carried out to determine the possibility of improving the properties of the heavy ion beam relevant for IFI by the appropriate selection of certain laser and target parameters. In simulations, a 1-ps laser with an energy of 150–250 kJ irradiated targets with a variety of atomic mass numbers, areal densities, thicknesses, and densities. For each of the sets of laser and target parameters considered in the paper, the parameters of the heavy ion beam relevant for IFI were determined and discussed. It was found that for realistic laser driver parameters, the IFI requirements are best met by ion beams with moderate ion mass numbers (A ∼ 50–100), such as the beam of Cu ions. It was shown that by optimizing the laser focal spot, as well as by properly matching the energy and power of the laser to the target areal mass density, it is possible to significantly improve the properties of the heavy ion beam relevant for IFI and, in particular, bring a many-fold increase in the intensity, fluence, and energy of the beam.
Bäcklund transformations from painlevé analysis

Since its elaboration in 1983 by Weiss, Tabor and Carnevale, the method to explicitly build the Bäcklund transformation of a partial differential equation (PDE) from singularity analysis only has been improved in several complementary directions, and at the present time it succeeds for practically all PDEs in 1+1-dimensions. The current state of the art is presented, and the emphasis is put on understanding the method. There are two important stages: first, the definition (identified with a Darboux transformation) of a resummation variable to make the Laurent series a finite one as requested by the definition of the word integrability; second, the link (identified with a linearizing formula to be taken from the classification of Painlevé and Gambier) between this resummation variable and the Lax pair to be found.
Risk Analysis and Mitigation in Supply Chain with House of Risk (HOR) Approach in Bag Manufacturing Industry at XYZ Ltd.

XYZ Ltd. is a company engaged in the bag-making manufacturing industry. The products produced include various types of bags such as backpacks, messengers, triangles, body bags, waist bags, and wheeled suitcases. The problems currently faced by XYZ Ltd. in its business processes, namely requests that are not the same as forecasts, delays in raw materials sent by suppliers, damage to raw materials during storage in warehouses due to the absence of routine checks, machine breakdowns that affect production process delays, and returns of finished products from consumers due to defect at the time of delivery. This causes the company to lose in terms of time and cost. This study uses the House Of Risk method. The House Of Risk method is a modification of the Failure Modes and Effects of Analysis (FMEA) method and the Quality Function Deployment (QFD) method. The purpose of this study is to identify potential risks that may arise in the supply chain at XYZ Ltd, find out the causes of these risks, and design effective risk mitigation strategies for the company. In the House Of Risk (HOR) stage 1, namely the risk identification stage, there are 33 risk events and 42 risk agents. Then after being analyzed using a Pareto diagram, 13 dominant risk causes were found based on the Aggregate Risk Potential (ARP) value. In the House Of Risk (HOR) phase 2, 14 mitigation actions (preventive actions) are proposed to overcome the probability of the emergence of risk agents in the supply chain of XYZ Ltd.
The Clinical Pharmacology and Therapeutic Evaluation of Non-Steroidal Anti-Inflammatory Drugs in Adult Horses

Simple Summary Non-steroidal anti-inflammatory drugs (NSAIDs) are commonly prescribed in equine practice for a variety of painful or inflammatory conditions. This review discusses the clinical pharmacology of NSAIDs in adult horses and methods of evaluating the therapeutic effect of these drugs in equine research. Abstract This review firstly examines the underlying pathophysiology of pain and inflammation associated with orthopedic disease and endotoxemia. Then, it reviews the clinical pharmacology (pharmacokinetics and pharmacodynamics) of both conventional and non-conventional NSAIDs in the adult horse, and finally provides an overview of different modalities to evaluate the therapeutic efficacy of NSAIDs in research.
The Burden of Human Parechoviruses Among Children in Oman

Objectives This study aimed to evaluate the burden, clinical and laboratory features and outcomes of human parechoviruses (HPeVs) infection among children in Oman. Methods This retrospective study included children (aged <18 years) with molecularly proven HPeV infection who were managed at Sultan Qaboos University Hospital, Muscat, Oman, between January 2017 and December 2019. Data were obtained from the patients’ medical records and analysed to describe their demographics, clinical and laboratory features, management and outcomes. Results HPeV was detected in 61 patients, 44 (72%) of whom were males. The median age of these patients was nine months (interquartile range [IQR]: 6–15 months). HPeV was detected throughout the year without any significant peaks. Majority of the patients (n = 51, 84%) had co-infection with other viruses. Forty-eight (79%) children with HPeV infection required hospitalisation, and their median length of hospital stay was five days (IQR: 3–8 days). Ex-prematurity (n = 10, 16%) was the commonest comorbidity among this group. Fever (n = 41, 67%) and cough (n = 41, 67%) were the commonest presenting symptoms among the children. Two-thirds of the HPeV-infected children in this cohort were managed for lower respiratory tract infection; none was managed for meningitis. Gastroenteritis was not common in this cohort; only eight children had diarrhoea. All children made a full recovery. Conclusion HPeVs infection does not show a clear seasonality in Oman. Most of the children were aged <2 years and had a viral co-infection. The outcomes of HPeV infection were favourable, with no mortalities, but a thorough follow-up for neurological outcomes was lacking.
Optical Phase Distortion due to Compressible Flow over Laser Turrets

'. : Compressible flow' over a laser turret causes'variation in density and the index of refraction. As a result, a laser beam develops a phase distortion. Phase distortion has been calculated for both blunt and small perturbation turrets. For the blunt turret,the Janzen-Rayleigh technique was used to determine the flow field. Phase distortions of 2.2 wavelengths at 3.8 microns were calculated for the blunt turret. For small perturbation turrets a versatile analytical model was developed for a turret on a fuselage with circular cross section. With a two-dimensional Fourier series representation of the turret, any shape can be considered. Both subsonic and supersonic flows can be calculated. Phase distortions of 1.2 wavelengths at 3.8 microns were calculated for one turret at high subsonic Mach number. In addition to being of value for laser turrets, the methods are applicable to reconnaissance aircraft using photographic equipment and :. , cruise missiles using celestial navigation.
INTERNAL DIFFUSION-LIMITED AGGREGATION ON NON-AMENABLE GRAPHS

The stochastic growth model Internal Diffusion Limited Aggregation was defined in 1991 by Diaconis and Fulton. Several shape results are known when the underlying state space is the d-dimensional lattice, or a discrete group with exponential growth. We prove an extension of the shape result of Blachere and Brofferio for Internal Diffusion Limited Aggregation on a wide class of Markov chains on non-amenable graphs.
Gray-level Morphological Operations for Image Segmentation and Tracking Edges on Medical Applications

Summary In this paper we mainly focused on grayscale images and how these images can be decomposed into number of peaks. This decomposition is called the peak analysis of grayscale images. Due its sensitive definition, there is a wide range of applications for peak analysis. The detection criterion expresses the fact that important edges should not be missed. It is of paramount important to preserve, uncover or detect the geometric structure of image objects. Thus morphological filters, which are more suitable than linear filters for shape analysis, play a major role for geometry based enhancement and detection. A new method for image segmentation and tracking edges based on morphological transformation is proposed. This algorithm uses the morphological transformations dilation and erosion. A gradient determined grey level morphological procedure for edge increase and decrease is present. First, the maximum gradient, in the local neighborhood, forms the contribution to the erosion of the center pixel of that neighborhood. The gradients of the transformed image are then used as contributions to subsequent dilation of eroded image. The edge sharpening algorithm is applied on various sample images. Proposed algorithm segments the image by preserving important edges.
A PIV comparison of the flow field and wall shear stress in rigid and compliant models of healthy carotid arteries

Certain systems relevant to circulatory disease have walls which are neither rigid nor static, for example, the coronary arteries, the carotid artery and the heart chambers. In vitro modeling allows the fluid mechanics of the circulatory system to be studied without the ethical and safety issues associated with animal and human experiments. Computational methods in which the equations are coupled governing the flow and the elastic walls are maturing. Currently there is a lack of experimental data in compliant arterial systems to validate the numerical predictions. Previous experimental work has commonly used rigid wall boundaries, ignoring the effect of wall compliance. Particle Image Velocimetry is used to provide a direct comparison of both the flow field and wall shear stress (WSS) observed in experimental phantoms of rigid and compliant geometries representing an idealized common carotid artery. The input flow waveform and the mechanical response of the phantom are physiologically realistic. The results show that compliance affects the velocity profile within the artery. A rigid boundary causes severe overestimation of the peak WSS with a maximum relative difference of 61% occurring; showing compliance protects the artery from exposure to high magnitude WSS. This is important when trying to understand the development of diseases like atherosclerosis. The maximum, minimum and time averaged WSS in the rigid geometry was 2.3, 0.51 and 1.03Pa and in the compliant geometry 1.4, 0.58 and 0.84Pa, respectively.
Recognition of short-term changes in physiological signals with the wavelet-based multifractal formalism

In this paper we address the problem of revealing and recognition transitions between distinct physiological states using quite short fragments of experimental recordings. With the wavelet-based multifractal analysis we characterize changes of complexity and correlation properties in the stress-induced dynamics of arterial blood pressure in rats. We propose an approach for association revealed changes with distinct physiological regulatory mechanisms and for quantifying the influence of each mechanism.