Miracle-dz/UniFAR-FTUs huggingface dataset:
Fluid-Structure Interactions in a Tissue during Hyperthermia

A numerical investigation based on fluid-structure interaction analysis was conducted to determine the influence of pulsatile turbulent flow and heating protocol on temperature distribution and heat flux variation in blood vessel and tumor tissues receiving hyperthermia treatment. The arterial wall was modeled using the volume-averaged porous media equations. In addition, a physiological waveform was employed for the inlet velocity and exit pressure. Furthermore, the present numerical model was validated by comparing it with previously published results in the literature. Moreover, discretization of the transport equations was achieved using a finite element scheme based on the Galerkin method of weighted residuals. The results were presented for both flexible and rigid wall models and three different heating schemes were considered in this investigation; constant temperature, constant wall flux and a step-wise heat flux. The first two heating schemes were found to exhibit large temperature variation along the top and bottom surfaces of the tumor, which could influence the surrounding healthy tissues. The results of this investigation illustrate that the local heat flux variation along the bottom surface of the tumor is greater at the beginning of the cycle, where the velocity magnitude is low as compared to the peak flow condition for different heating schemes. The results of this work may enhance the current understanding of the factors that determine the effect of hyperthermia treatment on tumor tissues.
Newton-Based Trainable Learning Rate

Selecting an appropriate learning rate for efficiently training deep neural networks is a difficult process that can be affected by numerous parameters, such as the dataset, the model architecture or even the batch size. In this work, we propose an algorithm for automatically adjusting the learning rate during the training process, assuming a gradient descent formulation. The rationale behind our approach is to train the learning rate along with the model weights. Specifically, we formulate first and second-order gradients w.r. t. the learning rate as functions of consecutive weight gradients, leading to a cost-effective implementation. Our extensive experimental evaluation validates the effectiveness of the proposed method for a plethora of different settings. The proposed method has proven to be robust to both the initial learning rate and the batch size, making it ideal for an off-the-shelf optimizing scheme.
Determining a flow structure in the region of local obstacles of different types taking into account the hydrodynamic conditions for entering the initial section

This paper investigates the influence of hydrodynamic conditions for entering the initial section of the channel located after local obstacles of various types. It is shown that the head losses in the valves and bends of pipelines and in various control elements can be several times higher than those in straight sections of the pipeline. It was established that the assumption about the rectangular shape of the velocity diagram at the entrance to the hydrodynamic initial section does not correspond to the flow pattern in real channels of technological equipment. It is proved that with the manifestation of inertia forces in the flow at the initial section of the channel, hydrodynamic energy losses usually increase, velocity and stress fields are significantly deformed. Given this, it seemed expedient to conduct a study into the processes of flow of viscous liquids in the initial section, located after local obstacles of various types. Experimental and analytical studies have confirmed that there is a significant influence of boundary conditions at the entrance to the initial section on the formation of velocity diagrams and energy loss along its length. The analytical-numerical solution to the system of differential equations describing such flow is given. While solving, the system of equations, by appropriate transformations, takes the form of a nonlinear integral-differential equation. This makes it possible to obtain correct dependences for determining the length of the velocity distribution and energy loss in the investigated section of the channel. The results of calculations of velocity fields in the region of local obstacles agree well with known ideas of the flow pattern, which is observed in physical experiments and the results of analytical solutions. The quantitative difference in results ranges within 12–20 % depending on the Reynolds number. Thus, there is reason to assert that the results of studies reported here could be the basis for devising a procedure of hydrodynamic calculation aimed at structural and operational improvement of existing and designed technological equipment.
The prevalence of sensitization to food allergens in children with atopic dermatitis.

INTRODUCTION Atopic dermatitis (AD) has a complex pathophysiology. The course of the disease is affected by both environmental factors and allergen hypersensitivities. Food and aeroallergens have a significant role in the pathogenesis and disease control. OBJECTIVE In this study, it was aimed to determine the prevalence of food and aeroallergen sensitivity of children with AD. METHODS Children under 18 years with AD who applied to pediatric allergy and immunology outpatient clinics were evaluated. All patients had a skin prick test (SPT) within most common food and aeroallergens. RESULTS One hundred seventy three patients were studied. Most of the moderate and severe AD patients were boys (boys 64% vs. girls 47%). Symptoms started earlier and positive results in SPTs with food allergens were more common in patients with SCORAD (SCORing Atopic Dermatitis) >25 (p < 0.0001). Egg white (39%), egg yolk (31%), cow's milk (13%) and wheat flour (5%), were the most common allergens, respectively. The SCORAD scores were higher in multiple food sensitized patients' groups (p < 0.001). Although, food sensitizations were prevalent in patients who had higher SCORAD scores (p = 0.001), there was no significant difference in sensitization with aeroallergens. (p = 0.392). CONCLUSION Sensitizations to both food and aeroallergens are common in patients with AD. In addition, sensitization to these allergens and SCORAD severity in patients with AD have positive correlation.
Comparison of GPS and IMU systems for total distance, velocity, acceleration and deceleration measurements during small-sided games in soccer

Abstract Physical variables from soccer training are commonly quantified by using global positioning systems (GPS) and/or inertial measurement unit (IMU) systems. More studies are needed to compare both systems, taking into account that both are frequently used to measure physical load. The purpose of this study was to (i) compare IMUs (PlayerMaker™) to ten Hz GPS (Polar Team Pro) units during a square running protocol (SRP) to investigate the accuracy of distance measured and intra-unit reliability of the devices and (ii) compare IMUs and GPS units for measurements of total distance (TD), very high intensity running (VHIR), accelerations and decelerations during small-sided games (SSGs) in semi-professional soccer. Four subjects ran theSRP whilst wearing two IMU units and three GPS units to compare the accuracy of distance measured and examining the intra-unit reliability. Fifteen male soccer players participated in the SSGs where the players’ physical variables were simultaneously captured by a foot-mounted IMU in addition to GPS units. IMU and GPS were respectively 2% and 1% from actual distance, whereof both systems had a coefficient of variation at~1%. In the SSGs, the IMU measured~4% higher TD compared to the GPS. VHIR measured by the IMUs were around 18% lower while the IMUs measured~39% more accelerations and~35% more decelerations compared to the GPS. Both systems measure close to actual distance. In SSGs, IMU measures higher distances below VHIR while the GPS measures higher distance above VHIR. IMUs measure a higher number of accelerations and decelerations during SSGs.
A Variable-Grid Algorithm for Smoothing Clustered Data

SUMMARY An algorithm is described for smoothing data points on the plane. The observation region is divided into cells and each group of four adjoining cells is tested to see whether it can be accepted that the values in the cells come from a distribution with the same underlying value of the parameters. If so, the cells are grouped again in a further round of smoothing. If not, the original values are retained and no further smoothing involving those cells takes place. The method is applied to the following situations: count data assumed to follow a nonhomogeneous Poisson process and count data assumed to follow a negative binomial process with nonhomogeneous rate. This paper had its origins in the attempt to define appropriate smoothing procedures for counts of clustered data in two dimensions, where it could be assumed that there was present both some large-scale spatial variation in the count rate as well as local variation due to clustering. There is of course no method of finally distinguishing between these two types of spatial inhomogeneity, purely on the basis of the data. It is perfectly logically consistent to treat a set of points either as a sample from a Poisson process with rapidly varying density function, or as a sample from a spatially homogeneous clustering process (Bartlett, 1964). Any method for discriminating between the two hypotheses must therefore be based, whether explicitly or otherwise, on some prior assumptions concerning the likely extent of clustering on the one hand or of departures from spatial inhomogeneity on the other. This paper describes a straightforward and computationally rapid algorithm that will allow the user to obtain an impression of the underlying spatial pattern on simple assumptions concerning the nature and extent of local clustering. At the first step in the algorithm, the user nominates a cell size to indicate the dimensions of local spatial clustering. This should be as small as possible while still consistent with the assumption that observations in disjoint cells may be regarded as independently generated. The choice is not very critical, but if chosen too small the procedure will identify as spatial heterogeneity features the user might prefer to regard as clusters. The observation region, supposed to be rectangular, is then divided into cells, the number of divisions along each dimension being equal to some power of 2. Typically, 64 x 64 or 32 x 32 divisions form convenient starting points. For convenience of plotting, the output
Towards a Unified Training for Levenshtein Transformer

Levenshtein Transformer (LevT) is a widely-used text-editing model, which generates a sequence based on editing operations (deletion and insertion) in a non-autoregressive manner. However, it is challenging to train the key refinement components of LevT due to training-inference discrepancy. By carefully designing experiments, our work reveals that the deletion module is under-trained while the insertion module is over-trained due to the imbalance training signals for the two refinement modules. Based on these observations, we further propose a dual learning approach that can remedy the imbalance training by feeding an initial input to both refinement modules, which is consistent with the process in inference. Experimental results on three representative NLP tasks demonstrate the effectiveness and universality of the proposed approach. 1
Binomial Method in Bermudan Option

The Bermudan option allows the contract holders to make and buy a hybrid contract between American and European options. Bermudan option contract can be executed at certain times until the due of the contract. The purpose of this research is to determine the price of the Bermudan option using the binomial method, and then to compare the binomial method result of n steps with the market option price. In determining stock prices at each point, there will be two branches of the binomial method: up and down branches. These branches represent the movement of stock prices in the market. The result shows the price of Bermudan option is convergent at a certain value when the binomial procedure is enlarged. The comparison of the Bermudan option price using a binomial method to the market price shows that the price of Bermudan option is an approach to the market price in certain conditions. Empirically, the price of Bermudan call option is in approach to the market option price or has a minimum error when the exercise price is below the current stock price. The price of Bermudan put option empirically is in approach to the market option price or having a minimum error when the exercise price is above the current stock price.
Udder Hygiene and Mastitis Indicators in Contrasting Environmental Conditions during Half-Time Confinement in Pasture-Based Dairy Systems

Simple Summary Current intensification in pasture-based systems demands periods of part-time confinement or even complete confinement when pastures are limited. Outdoor soil-bedded yards are commonly used in these systems but can predispose cows to dirtier udders and, therefore, a greater risk of mastitis. The aim of the study was to compare the effect of two types of housing, compost barn and outdoor soil-bedded yard, on udder hygiene and mastitis indicators in Holstein dairy cows calved in autumn and spring. In both treatments, the cows were confined during one interval between milking sessions when a supplement was offered and went out to graze in the other interval. The outdoor soil-bedded group presented a greater percentage of dirty cows compared to the compost barn in both calving seasons. Additionally, outdoor soil-bedded autumn calving cows were dirtier after rain than on days without previous rain. However, no differences in somatic cell count or prevalence of mastitis were found between cows in outdoor soil-bedded and compost barn confinement. Abstract This study aimed to compare the association between two types of housing, compost barns (CB) vs. outdoor soil-bedded yard (OD), and udder hygiene and mastitis indicators in Holstein dairy cows calving in autumn (n = 31) and spring (n = 27). After calving, cows were transferred to a pasture-based system with half-time confinement in one of two treatments: CB or OD. The udder hygiene score (UHS) was evaluated monthly and on days after rainfall over the entire lactation period. Individual somatic cell count (SCC) was determined throughout lactation, and the prevalence of intramammary infection (IMI) was estimated. Cows confined in OD presented higher UHS compared to cows in CB (p < 0.05) in both calving seasons. After rains, autumn-calving cows in OD were dirtier than on days without previous rain (OR = 1.85, CI 95%: 1.1–3.1; p < 0.02). However, no differences in IMI and clinical mastitis were found between OD and CB cows in either calving season.
Biochemical, Antioxidant Properties and Antimicrobial Activity of Epiphytic Leafy Liverwort Frullania dilatata (L.) Dumort

In this study, the biochemical, antioxidant properties, and antimicrobial activity of the epiphytic leafy liverwort Frullania dilatata (L.) Dumort were investigated. Due to the scarcity and difficulty in obtaining liverworts, research on their bioactivity is limited; thus, this study aimed to uncover the potential of F. dilatata. The antimicrobial activity was evaluated against various microorganisms, including food isolates, clinical isolates, multidrug-resistant strains, and standard strains, using the disk diffusion method and determining the minimum inhibitory concentration (MIC) values. This study represents the first antioxidant investigation on F. dilatata and an antimicrobial study using ethanol extract and the disk diffusion method. Notably, susceptibility was observed in Enterococcus faecalis ATCC 29212, Enterococcus faecium FI, Listeria monocytogenes ATCC 7644, Providencia rustigianii MDR, and Staphylococcus aureus ATCC 25923. The antioxidant capacity was assessed using the DPPH method, emphasizing the high scavenging performance. Gas chromatography-mass spectrometry (GC-MS) analysis identified the primary compounds as frullanolide (19.08%), 2,3-Dimethylanisole (15.21%), linoleic acid (11.11%), palmitic acid (9.83%), and valerenic acid (5.3%). The results demonstrated the significant antimicrobial activity of F. dilatata against the tested microorganisms and its potent antioxidant properties. These findings emphasize the potential of F. dilatata as a promising source of natural antimicrobial and antioxidant agents, underscoring the importance of further investigation into its bioactive compounds and elucidating the mechanisms of action in future studies.
High contrast amplification at 1053 nm limited by pulse stretching-compressing process

We report on our high-contrast laser based on high-contrast, high-energy seed injection, low-gain optical parametric chirped pulse amplification (OPCPA), and Nd:glass amplifiers, which can be used as the high-contrast front end of a high-power Nd:glass chirped pulse amplification (CPA) laser system. The energy of the stretched 1053 nm high-contrast seed pulse increases to 60 μJ by optimizing the frequency doubling crystal in the pulse cleaning device. After passing through a two-stage low-gain OPCPA, a 2-pass 2-rod Nd:glass amplifier, and a compressor the amplified pulse of 131 mJ∕282 fs is achieved. The third-order correlation scanning measurement shows that the pulse contrast in the tens of ps range is about 10 �7 –10 �8 . With the high-contrast seed passing through the stretcher and compressor only, the contrast measurement indicates that the stretching-compressing process leads mainly to the contrast degradation of the amplified pulse. OCIS codes: 320.7090, 190.4410, 140.3280. doi: 10.3788/COL201614.023201.
DOES SUB-SAHARAN AFRICA'S RAPID POPULATION GROWTH HAVE POSITIVE OR NEGATIVE EFFECTS ON AGGREGATE DOMESTIC INVESTMENT?

This study examines the effect of population growth on aggregate domestic investments in 45 Sub-Saharan African (SSA) countries over the period 2000–2020. It applies the Quantile Method of Moments with fixed effects (i.e., MM-QR), which has the ability to identify both negative and positive effects while controlling for trade, HIV/AIDS prevalence, and economic growth. The findings show that SSA’s rapid population growth has a positive and statistically significant effect on aggregate domestic investments. Findings from this study show that an increase in population growth in the 10th to 60th quantiles is associated with an increase of domestic investment in SSA. This suggests that, as the population grows in SSA, it generates demand for domestic investments such as healthcare services, education, and other social services. Our findings also show that trade is positive and significant across all quantiles (10th to 90th). We find evidence that disease risks, such as the prevalence of HIV/AIDS, slowed the increase in domestic investment in the region across all quantiles (10th to 90th). We conclude by arguing that, since SSA's population growth will double in the near future, the region is bound to become world's next investment hub. In order to enable long-term domestic investments in the region, future policy options should take the challenges of population growth into account.
A Modular Approach to Teaching Mathematical Modeling in Biotechnology in the Undergraduate Curriculum

Abstract Our paper describes a solution we found to a still existing need to develop mathematical modeling courses for undergraduate biology majors. Some challenges of such courses are: (i) relatively limited exposure of biology students to higher-level mathematical and computational concepts; (ii) availability of texts that can give a flavor of how contemporary biological problems are approached with quantitative methods; (iii) expectations to cover specific mathematical (or biological) content rather than teach a problem-solving approach. We solved these challenges by designing a course where several modules were developed, each beginning with a presentation from a campus expert in a biological area of research and concluding with a seminar-style student-led paper presentation of an article that addresses the biological problem using mathematical and computational tools. The aim of the course was to expose students to the vast possibilities and potential in quantitative biology, and to give them a vocabulary to collaborate with mathematicians, statisticians, and computer scientists.
A LIMIT PROPERLY OF RANDOM CONDITIONAL PROBABILITIES AND AN APPROACH OF CONDITIONAL MOMENT GENERATING FUNCTION

Let{(X_n, n ≥0} be a sequence of random variables taking values in S = {1, 2,…, N}, and let pk(xk | xo,…,xk-1) = P(Xk = xk| XO = xo,…, Xk-1 = xk-1). In this paper a theorem on a.e. convergence for the harmonic mean of the random conditional probabilities {ph(Xk | Xo,…, Xk-1), 1≤k≤ n} is obtained. In the proof an approach of applying the differentiation on a net and the tool of conditional moment generating function to the study of strong limit theorem is proposed.
Introduction of Surface Modifiers on the Pt-Based Electrocatalysts to Promote the Oxygen Reduction Reaction Process

The design of Pt-based electrocatalysts with high efficiency towards acid oxygen reduction reactions is the priority to promote the development and application of proton exchange membrane fuel cells. Considering that the Pt atoms on the surfaces of the electrocatalysts face the problems of interference of non-active species (such as OHad, OOHad, CO, etc.), high resistance of mass transfer at the liquid–solid interfaces, and easy corrosion when working in harsh acid. Researchers have modified the surfaces’ local environment of the electrocatalysts by introducing surface modifiers such as silicon or carbon layers, amine molecules, and ionic liquids on the surfaces of electrocatalysts, which show significant performance improvement. In this review, we summarized the research progress of surface modified Pt-based electrocatalysts, focusing on the surface modification strategies and their mechanisms. In addition, the development prospects of surface modification strategies of Pt-based electrocatalysts and the limitations of current research are pointed out.
NET Proteome in Established Type 1 Diabetes Is Enriched in Metabolic Proteins

Background and aims: Type 1 diabetes (T1D) is a chronic autoimmune disease characterized by a T-cell-mediated destruction of the pancreatic insulin-producing beta cells. A growing body of evidence suggests that abnormalities in neutrophils and neutrophil extracellular trap (NET) formation (NETosis) are associated with T1D pathophysiology. However, little information is available on whether these changes are primary neutrophil defects or related to the environmental signals encountered during active disease. Methods: In the present work, the NET proteome (NETome) of phorbol 12-myristate 13-acetate (PMA)- and ionomycin-stimulated neutrophils from people with established T1D compared to healthy controls (HC) was studied by proteomic analysis. Results: Levels of NETosis, in addition to plasma levels of pro-inflammatory cytokines and NET markers, were comparable between T1D and HC subjects. However, the T1D NETome was distinct from that of HC in response to both stimuli. Quantitative analysis revealed that the T1D NETome was enriched in proteins belonging to metabolic pathways (i.e., phosphoglycerate kinase, glyceraldehyde-3-phosphate dehydrogenase, and UTP-glucose-1-phosphate uridylyltransferase). Complementary metabolic profiling revealed that the rate of extracellular acidification, an approximate measure for glycolysis, and mitochondrial respiration were similar between T1D and HC neutrophils in response to both stimuli. Conclusion: The NETome of people with established T1D was enriched in metabolic proteins without an apparent alteration in the bio-energetic profile or dysregulated NETosis. This may reflect an adaptation mechanism employed by activated T1D neutrophils to avoid impaired glycolysis and consequently excessive or suboptimal NETosis, pivotal in innate immune defence and the resolution of inflammation.