Miracle-dz/UniFAR-FTUs huggingface dataset:
Leprosy transmission in endemic and non-endemic areas based on the profile of antibody response of PGL-1 and PCR detection of Mycobacterium leprae DNA from nasal swab among healthy children of East Java, Indonesia

Background East Java has become one of the provinces that have higher prevalence of leprosy, especially in the coastal region. Environment has also influenced for leprosy transmission and early detection could reduce the incidence rate of new leprosy cases. Epidemiological studies of leprosy in children can give an illustration of the important aspects of the environment. Presence of Mycobacterium leprae (M. leprae) DNA in nasal swabs and seropositivity level among them can describe M. leprae exposure in that area. Objective Analyzing PCR from nasal swab and seropositivity level among elementary school children between northern coast and southern coast of East Java province. Methods Five hundred and thirty children in Pacitan and Lamongan were involved. Both areas are representation of northern and southern coastal region in East Java Province. After clinical examination, nasal swab and blood samples were obtained. ELISA test was performed to measure the titer of IgM anti Phenolic Glicolipid-1 (PGL-1) antibody then continued by PCR to detect M. leprae DNA. Results From 301 students in Pacitan, 25 students (8.3%) are sero-positives and 9 students (2.9%) are PCR positives. from 229 students in Lamongan, 110 (48,3%) students are sero-positives and 49 students (21.4%) are PCR positives. Both are analyzed by Chi-Square, and from the PCR and ELISA, it concluded that there are statistically significant differences between the two regions. Conclusion From study above shows that in the northern coast of East Java, incidence of subclinical leprosy is still high, it means that in this area still has a high risk of new cases of leprosy in the future and early detection tools need to performed as a preventative measure.
Safety assessment of the process RE‐PET, based on EREMA Basic technology, used to recycle post‐consumer PET into food contact materials

Abstract The EFSA Panel on Food Contact Materials, Enzymes and Processing Aids (CEP) assessed the safety of the recycling process RE‐PET (EU register number RECYC178) which uses the EREMA Basic technology. The input material is hot caustic washed and dried poly(ethylene terephthalate) (PET) flakes originating from collected post‐consumer PET containers including no more than 5% PET from non‐food consumer applications. The flakes are heated in a continuous reactor under vacuum before being extruded. The Panel concluded that the continuous reactor (step 2, for which a challenge test was provided) is critical in determining the decontamination efficiency of the process. The operating parameters to control the performance of this step are temperature, pressure and residence time. It was demonstrated that this recycling process is able to ensure a level of migration of potential unknown contaminants into food below the conservatively modelled migration of 0.1 μg/kg food derived from the exposure scenario for infants when such recycled PET is used at up to 70% in mixtures with virgin PET and of 0.15 μg/kg food derived from the exposure scenario for toddlers when used at up to 100%. Therefore, the Panel concluded that the recycled PET obtained from this process is not of safety concern when used at up to 70% in mixtures with virgin PET for manufacturing bottles for drinking water and at up to 100% for the manufacture of other materials and articles for contact with all types of foodstuffs, for long‐term storage at room temperature, with or without hotfill. Articles made of this recycled PET are not intended to be used in microwave and conventional ovens and such uses are not covered by this evaluation.
Biocontrol of Monochamus alternatus by Beauveria bassiana and Scleroderma guani

By the infection experiment of Beauveria bassiana to the overwintering larvae of Monochamus alternatus under different temperatures and dosages,the results showed:20～25 ℃ was the fittest temperature range for B.bassiana to M.alternatus. Under 20 ℃,parasitic rates of B.bassiana to M.alternatus by three kinds of concentration of B.bassiana spore suspension were 58%、95% and 100% respectively.By comparing mortality of M.alternatus at 4 th instars after inoculation of B.bassiana,Scleroderma guani and S.guani with B.bassiana,on the 7 th day,the highest mortality of M.alternatus only inoculating B.bassiana was 26.3%;the highest mortality of M.alternatus only inoculating S.guani was 55.0%;and the highest montality of M.alternatus inoculating and S.guani with B.bassiana was 94.4%. The field experiment showed that the mortality of the M.alternatus larvae treated by S.guani with B.bassiana was 61.1%,by S.guani was 40.8%,and by B.bassiana was 0.0%. So S.guani with B.bassiana might have better effect to the larvae of M.alternatus.
Design of 33 Level Asymmetrical Multilevel Inverter with Reduced Value of THD

This paper presents a simplified and reduced cascaded H Bridge asymmetrical multilevel inverter in order to generate any number of output voltage levels with reduced number of switching components. In this paper, a 33 level asymmetrical MLI is introduced with different switching angle calculation technique, particularly equal phase method and half height methods are analyzed presented and compared. The main benefits of the proposed 33 level inverter are less number of switching components, lower loss, reduced size and with reduced value of THD using half height switching angle calculation technique. Simulation works are carried out through MATLAB software to demonstrate the performance of the presented 33 level asymmetrical MLI with equal angle and half height switching angle calculation techniques.
Fourier-Based Universal Learning

We develop a Fourier-based approach for classiﬁcation. We use the approach for the feature selection problem, which we study and analyze from a PAC learning perspective for non-uniform (product) probability distributions in deterministic and stochastic settings. In this problem, given the training instances and a parameter k , the objective is to select the best k out of d features along with a k -variable predictor that yield the minimum misclassiﬁcation probability. We formulate this problem as an optimization in the Fourier domain to characterize the optimal features and the predictor. Our algorithm can be viewed as a Fourier-based implementation of L 1 polynomial regression — an L 1 counterpart of the well-known low-degree algorithm. We show that, under statistical independence of the features, our algorithm agnostically learns with respect to the class of k -variable predictors (a.k.a k -juntas) and outperforms other PAC learning approaches in terms of sample complexity and computational complexity. In addition, our results can be used in other fundamental problems under non-uniform distributions, such as learning Boolean k -junta and linear-threshold functions.
Real Time Hand Tracking Method for an Immersive Application

This paper presents a real time ﬁngertip tracking method used for immersive application. The ﬁrst step of the method consists of segmenting the input image captured by a video camera and detects the area representing the human hand. The latter one is identiﬁed by means of skin color detection method. The output of the ﬁrst step is a black and white image where the hand area is coloured in black while the background is in white. In the second step, the hand shape is analysed and the ﬁngertips are detected using convex-hull method. The barycen-tre of the ﬁngertips is then calculated and to estimate the position of the hand. Using the estimated position in each frame, many applications belonging to human computer interaction and immersive domains could be proposed. In this paper, we propose an immersive application which consists of moving virtual objects according to the estimated hand position.
Italy in the Eurozone 1

Using a DSGE model with nominal wage rigidity, we investigate two scenarios for the Italian economy. The first considers sustained policy commitment to reform. The results indicate the possibility of `growing out of bad initial conditions', if fiscal consolidation is combined with a program for bank recovery and for competitiveness and growth. The second scenario involves a strong asymmetric recession. It is likely to be very severe under the restrictions of the currency union. A benign exit from the Eurozone with stable investor expectations could substantially dampen the short-run impact. Stabilization is achieved by monetary expansion, combined with exchange rate depreciation. However, investor panic may lead to escalation. Capital market reactions would offset the benefits of monetary autonomy and much delay the recovery.
Effects of food abundance on growth, survival, and use of space by nymphs of Coenagrion resolutum (Zygoptera)

In the laboratory, nymphs of Coenagrion resolutum that were fed large and frequent meals grew faster, emerged earlier and had higher survivorship than nymphs that were fed smaller, less frequent meals. When given a choice of feeding areas, nymphs tended to remain near areas of food concentration that resulted in high growth rates; however, nymphs did not always remain at those areas of high food concentration that resulted in maximum growth rate.
Domestic Water Pollution among Local Communities in Nigeria ----Causes and Consequences

The paper focuses primarily on the causes, consequences and ways of mitigating the ongoing fresh water pollution problems among Nigerian communities. Adequate supply of safe and sanitised fresh water is an inevitable factor for human and economic development. Although the recent global attention focuses on how the current and foreseeable water crisis and associated consequences would be addressed, lack of education, low budgetary funding, inefficient government policies, corruption, drought and other anthropogenic factors are increasingly contributing to the pollution of domestic water in Nigeria. The homes, local markets, abattoirs, oil and agricultural activities are consistently severing the limited fresh water sources through disposal of harmful wastes. This led to the emergence of several diseases and heavy metals poisoning across the country. The only ways forward are the proper sanitary, awareness and waste management education, adequate funding of water resources and health sectors, effective implementation of judicial measures and adoption of lessons from key developed countries like United Kingdom. A “collective” approach is required for successful implementations.
Molecular evidence on evolutionary switching from particle-feeding to sophisticated carnivory in the calanoid copepod family Heterorhabdidae: drastic and rapid changes in functions of homologues

ABSTRACT The oceanic calanoid copepod family Heterorhabdidae is unique in that it comprises both particle-feeding and carnivorous genera with some intermediate taxa. Both morphological and molecular (nuclear 18S and 28S rRNA) phylogenetic analyses of the family suggest that an evolutionary switch in feeding strategy, from transitions of typical particle-feeding through some intermediate modes to sophisticated carnivory, might have occurred with the development of a specially designed ‘poison’ injection system. In view of the small amount of genetic differentiation among genera in this family, the switching of feeding modes and re-colonization from deep to shallow waters might have occurred over a short geological period since the Middle to Late Miocene.
Physics-based modeling of Antarctic snow and firn density

Abstract. Estimates of snow and firn density are required for satellite altimetry based retrievals of ice sheet mass balance that rely on volume to mass conversions. Therefore, biases and errors in presently used density models confound assessments of ice sheet mass balance, and by extension, ice sheet contribution to sea level rise. Despite this importance, most contemporary firn densification models rely on simplified semi-empirical methods, which are partially reflected by significant modeled density errors when compared to observations. In this study, we present a new, wind-driven, drifting snow compaction scheme that we have implemented into SNOWPACK, a physics-based land surface snow model. We demonstrate high-quality simulation of near-surface Antarctic snow firn density at 122 observed density profiles across the Antarctic ice sheet, as indicated by reduced model biases throughout most of the near-surface firn column when compared to two semi-empirical firn densification models. Because SNOWPACK is physics-based, its performance does not degrade when applied to sites without observations used in the calibration of semi-empirical models, and could therefore better represent firn properties in locations without extensive observations and under future climate scenarios, in which firn properties are expected to diverge from their present state.
On Modeling the Psychological Foundations of Support for Donald Trump

Scholars have identified many psychological factors correlated with support for Donald Trump; however, attempts at modeling Trump support tend to suffer from omitted variable bias on the one hand, or multicollinearity on the other. Both issues obscure inferences. Using two nationallyrepresentative surveys, we demonstrate the perils of including or failing to include many of these factors in models of Trump support. We then reconceptualize the psychological sources of Trump support as components of a broader “profile” of factors that explains Trump support in 2018 and vote choice in 2016, as well as attitudes about issues connected to Trump. Moreover, this profile – an amalgamation of attitudes about, for example, racial groups, immigrants, and political correctness – outperforms partisanship and ideology as predictors of Trump support and is negatively related to support for mainstream Republican candidates. Our analyses suggest that Trump benefitted from activating dimensions of public opinion that transcend traditional party cleavages.
Predicting malignancy: subsolid nodules detected on LDCT in a surgical cohort of East Asian patients

Background Due to widespread use of low-dose computed tomography (LDCT) screening, increasing number of patients are found to have subsolid nodules (SSNs). The management of SSNs is a clinical challenge and primarily depends on CT imaging. We seek to identify risk factors that may help clinicians determine an optimal course of management. Methods We retrospectively reviewed the characteristics of 83 SSN lesions, including 48 pure ground-glass nodules and 35 part-solid nodules, collected from 83 patients who underwent surgical resection. Results Of the 83 SSNs, 16 (19.28%) were benign and 67 (80.72%) were malignant, including 23 adenocarcinomas in situ (AIS), 16 minimally invasive adenocarcinomas (MIA), and 28 invasive adenocarcinomas (IA). Malignant lesions were found to have significantly larger diameters (P<0.05) with an optimal cut-off point of 9.24 mm. Significant indicators of malignancy include female sex (P<0.05), air bronchograms (P<0.001), spiculation (P<0.05), pleural tail sign (P<0.05), and lobulation (P<0.05). When compared with AIS/MIA combined, IA lesions were found to be larger (P<0.05) with an optimal cut-off of 12 mm, and have a higher percentage of part-solid nodules (P<0.001), pleural tail sign (P<0.001), air bronchograms (P<0.05), and lobulation (P<0.05). Further multivariate analysis found that lesion size and spiculation were independent factors for malignancy while part-solid nodules were associated with IA histology. Conclusions East Asian females are at risk of presenting with a malignant lesion even without history of heavy smoking or old age. Nodule features associated with malignancy include larger size, air bronchograms, lobulation, pleural tail sign, spiculation, and solid components. A combination of patient characteristic and LDCT features can be effectively used to guide management of patients with SSNs.
Inventory control model based on multi-attribute material classification: An integrated grey-rough set and probabilistic neural network approach

Efficient and reasonable inventory control can help enterprises improve in‐ ventory management efficiency, reduce inventory cost, and ensure the full utilization of resources. Considering that there are many attributes of materi‐ al, different materials have different effects on enterprises. A multi‐attribute material classification model based on grey rough set and probabilistic neural network is proposed, and an inventory control strategy model based on mate‐ rial classification is constructed according to the characteristics of different types of material. Based on the construction of the relevant models, taking the inventory materials of sample Enterprise A as an example, the grey rough set algorithm is used to reduce the redundant material attributes, and the sample data of normalized reduction attributes are used to classify and discriminate the materials by probabilistic neural network. The results are simulated by MATLAB to obtain the efficient and reasonable classification of the materials of enterprises. Finally, with the sample data of different types of representa‐ tive materials, a matching model of inventory control strategy based on mate‐ rial classification is applied in practice, and the applicability and feasibility of the model are illustrated, providing a scientific basis for enterprises to make decisions on material management and inventory control. © 2019 CPE, University of Maribor. All rights reserved.
A linear model to derive melt pond depth on Arctic sea ice from hyperspectral data

Abstract. Melt ponds are key elements in the energy balance of Arctic sea ice. Observing their temporal evolution is crucial for understanding melt processes and predicting sea ice evolution. Remote sensing is the only technique that enables large-scale observations of Arctic sea ice. However, monitoring melt pond deepening in this way is challenging because most of the optical signal reflected by a pond is defined by the scattering characteristics of the underlying ice. Without knowing the influence of meltwater on the reflected signal, the water depth cannot be determined. To solve the problem, we simulated the way meltwater changes the reflected spectra of bare ice. We developed a model based on the slope of the log-scaled remote sensing reflectance at 710 nm as a function of depth that is widely independent from the bottom albedo and accounts for the influence of varying solar zenith angles. We validated the model using 49 in situ melt pond spectra and corresponding depths from shallow ponds on dark and bright ice. Retrieved pond depths are accurate (root mean square error, RMSE=2.81 cm ; nRMSE=16 %) and highly correlated with in situ measurements ( r=0.89 ; p = 4.34 × 10 - 17 ). The model further explains a large portion of the variation in pond depth ( R2=0.74 ). Our results indicate that our model enables the accurate retrieval of pond depth on Arctic sea ice from optical data under clear sky conditions without having to consider pond bottom albedo. This technique is potentially transferrable to hyperspectral remote sensors on unmanned aerial vehicles, aircraft and satellites.
A IPARALLEL IMPLICIT INCOMPRESSIBLE FLOW SOLVER USING UNSTRUCTURED MESHES

-An incompressible flow solver based on unstructured grids is implemented on a parallel distributed memory computer architecture. An important phase in the flow solver is the solution of the elliptic equations for the velocities and pressure. This elliptic solver is parallelized and incorporated into both the explicit and implicit versions of the incompressible flow solver. Performance and scalability studies are carried out on both Intel iPSC 860 and the Intel Delta prototype, and these studies show that the code is scalable. A parallelizable load balancing algorithm is developed to be used in conjunction with the incompressible flow solver. Steady and unsteady flows over a t&element airfoil and NACAO012 airfoil are computed using the parallel incompressible flow solver.
Beneficial Role of Diazepam in the Histological Alterations of Colon Post Immobilization Stress- Induced in Adult Albino Rats

The present work was planned to study the histological changes that may occur in the colon of the immobilized-stressed albino rats and the ameliorative role of diazepam injected intraperitoneally with therapeutic dose (0.1 mg/ kg b.w.). Sixty adult male albino rats weighing 110 ± 5g were used and divided equally into 6 groups, group(I) served as control rats; group(II) rats treated with diazepam; group (III) and (IV) served as stressed rats (10 animals / each): in which the rats were immobilized individually for 2 hrs. daily for different durations (5 and 30 days, respectively); groups (V) and (VI) served as immobilizedstressed rats (10 animals /each) for 2 hrs daily for 5and 30 days and treated with diazepam for 30 days, respectively. The results recorded a significant increase in sera cortisol of the stressed-rats for 5 and 30 days. Histological results of colon demonstrated epithelial damage in the form of cytoplasmic vacuolation, pyknotic nuclei and some others were karyolitic. Desquamation of the absorptive columnar cells, detachment of cells from the basement membrane, reduction in number of superficial goblet cells containing mucus and distortion of the crypt architecture were observed. Moreover, fibrosis between crypts and marked leucocytic infiltration in lamina propria were elucidated as well as congestion and dilatation of the blood vessels. Additionally, the increment of collagen fibres in the lamina propria of mucosa and muscularis mucosa of the stressed rats was obviously demonstrated. These alterations were time-depended. Treatment with diazepam resulted in decreased cortisol levels, marked improvement and restoration of the histological changes. The results indicated that diazepam is recommended to be used as a curative drug to improve the disturbances in the colon caused under the effect of stress Keywords— Colon, Histology, Stress, Benzodiazepines, Rat ——————————  ——————————
The Impact of Perforation Geometry on Oil Well Productivity

The increase in demand for oil and gas today requires oil operators to maximize productivity. In order to produce more fluid from the reservoir into the wellbore, perforations must penetrate considerably beyond invaded zone with impaired permeability. The production engineers must take advantage of the perforation controllable parameters to maximize the well productivity. In this study, a simple analytical model incorporating perforation length, radius, and shot density was used to analyze oil well productivity. The results shows that the production rate can be increased by the perforation length, radius, and shot density. The drawdown pressure was reduced with increase in the perforation length and shot density. Higher fluid velocity was controlled with increase in the shot density, length and radius of perforation. The length of perforation and shot density are better in optimizing well productivity. Optimum perforation parameters are required as further increase result in increase in cost relative to the productivity.