Miracle-dz/UniFAR-FTUs huggingface dataset:
POSTOPERATIVE EVALUATION AND EXPECTED COMPLICATIONS OF PERORAL ENDOSCOPIC MYOTOMY FOR ACHALASIA CARDIA - USING LOW DOSE MULTI DETECTOR COMPUTED TOMOGRAPHY WITH ORAL CONTRAST

INTRODUCTION Achalasia is an oesophageal motility disorder characterized by a combination of impaired lower oesophageal sphincter (LES) opening and absent peristalsis in the oesophagus in response to deglutition. The most widely used treatment options include endoscopic balloon dilation and laparoscopic or open Heller myotomy [1,2]. Peroral endoscopic myotomy (POEM) was recently introduced novel method which is less invasive as it is carried out through orice naturalis. This procedure has shown promising short-term results reported by few smaller studies, though it is too early to predict long term results for such a recently introduced procedure [3,4]. The procedure includes four steps, the incision of lower oesophageal mucosa, creating a submucosal tunnel, myotomy and closure of the mucosal incision. This procedure is associated with few post procedure adverse events such as pneumothorax, pneumomediastinum, pneumoperitoneum, pleural effusion, subcutaneous emphysema, and submucosal and extraluminal mucosal leaks. These adverse events can be identied by crosssectional imaging, and shows the necessity of postPOEM CT study [5,6,7]. Our study aims to study the post procedural adverse events of POEM procedure, using postoperative low dose multi detector CT chest with oral contrast.
Heat capacities of liquid hydrocarbons. Estimation of heat capacities at constant pressure as a temperature function, using additivity rules

(1) d'Avila, S. G. , Silva R. S. F. , J. Chem. Eng. Data, 15, 421 (1970). (2) Barker, J. A. , Aust. J. Chem., 6, 207 (1953). (3) Jose, J., Philippe R. , Clechet, P., Bull. Soc. Chim. f r . , 8, 2860 (1971). (4) Kay, W. B. , Ind. Eng. Chem., 28, 1014(1936). (5) Loffler. H. J., Kaltetechnik, 20, 72 (1968). (6) Matsunaga, I. , Katayama, T. , J. Chem. Eng. Jpn. , 6, 397 (1973). (7) Morell, C. E. Carlson, C. S. , Mc Ateer, J. H. , Robey, R. F. Smith, P. V. , lnd.
Learning from the Best: Rationalizing Prediction by Adversarial Information Calibration

Explaining the predictions of AI models is paramount in safety-critical applications, such as in legal or medical domains. One form of explanation for a prediction is an extractive rationale, i.e., a subset of features of an instance that lead the model to give its prediction on the instance. Previous works on generating extractive rationales usually employ a two-phase model: a selector that selects the most important features (i.e., the rationale) followed by a predictor that makes the prediction based exclusively on the selected features. One disadvantage of these works is that the main signal for learning to select features comes from the comparison of the final answers given by the predictor and the ground-truth answers. In this work, we propose to squeeze more information from the predictor via an information calibration method. More precisely, we train two models jointly: one is a typical neural model that solves the task at hand in an accurate but black-box manner, and the other is a selector-predictor model that additionally produces a rationale for its prediction. The first model is used as a guide to the second model. We use an adversarial-based technique to calibrate the information extracted by the two models such that the difference between them is an indicator of the missed or over-selected features. In addition, for natural language tasks, we propose to use a language-model-based regularizer to encourage the extraction of fluent rationales. Experimental results on a sentiment analysis task as well as on three tasks from the legal domain show the effectiveness of our approach to rationale extraction.
Incentive Mechanism Design for Distributed Coded Machine Learning

A distributed machine learning platform needs to recruit many heterogeneous worker nodes to finish computation simultaneously. As a result, the overall performance may be degraded due to straggling workers. By introducing redundancy into computation, coded machine learning can effectively improve the runtime performance by recovering the final computation result through the first k (out of the total n) workers who finish computation. While existing studies focus on designing efficient coding schemes, the issue of designing proper incentives to encourage worker participation is still under-explored. This paper studies the platform’s optimal incentive mechanism for motivating proper workers’ participation in coded machine learning, despite the incomplete information about heterogeneous workers’ computation performances and costs. A key contribution of this work is to summarize workers’ multi-dimensional heterogeneity as a one-dimensional metric, which guides the platform’s efficient selection of workers under incomplete information with a linear computation complexity. Moreover, we prove that the optimal recovery threshold k is linearly proportional to the participator number n if we use the widely adopted MDS codes for data encoding. We also show that the platform’s increased cost due to incomplete information disappears when worker number is sufficiently large, but it does not monotonically decrease in worker number.
Verteilung von Eisen in Blättern von Weinreben mit HCO3− induzierter Fe-Chlorose

Es wurde bei der Weinrebe die Verteilung von Fe in gesunden Blattern und in Blattern, die Fe-Chlorose hatten, untersucht. Bicarbonate hemmte den Transport von markiertem Fe aus den Leitbundeln in die Zellen der Interkostalfelder. Auf den Langstreckentransport von markiertem Fe hatte HCO3− keinen signifikanten Einflus. Blatter mit Fe-Chlorose, die von 3 verschiedenen Freilandstandorten gesammelt worden waren, wiesen in den meisten Fallen hohere Fe-Gehalte auf als gesunde Blatter derselben Standorte. Die Gehalte an HCl loslichem Fe waren dagegen in den chlorotischen Blattern signifikant niedriger als in den grunen Blattern. Eine enzymatische Auftrennung der Blatter in Blattadern, Zellen der Interkostalfelder und Chloroplasten zeigte, das die Fe-Gehalte in den Interkostalzellen gruner Blattgewebe signifikant hoher waren als in den Interkostalzellen von chlorotischen Blattern. Weiterhin wiesen die Interkostalzellen von chlorotischen Blattern uberhohte Ca- und P-Gehalte auf. Die P-Gehalte chlorotischer und gruner Blatter standen in keiner Beziehung zum CAL-loslichen Phosphat des Bodens. Die erhohten P-Gehalte in den chlorotischen Blattern werden deshalb als Folge und nicht als Ursache der Fe-Chlorose angesehen. Auf jeweils denselben Standorten wurden unter chlorotischen Rebstocken hohere Tongehalte gefunden als unter gesunden Rebstocken. Es wird vermutet, das aufgrund dieser hoheren Tongehalte Bodenverdichtungen auftreten konnen, die einen CO2-Stau auslosen und damit zu hoheren HCO3−-Konzentrationen in der Bodenlosung fuhren. Distribution of iron in vine leaves with HCO3− induced chlorosis The distribution of Fe in chlorotic and healthy leaves of grapevine has been studied. Application of HCO3− had no significant influence on the long distance transport of labelled Fe, the translocation of Fe from the vascular tissue to the intercostal cells (cells between leaf veins), however, was much affected by HCO3−. Leaf samples collected from three different sites showed in most cases higher Fe contents in the chlorotic leaves as compared with healthy leaves. The solubility of leaf Fe in diluted HCl, however, was lower in chlorotic leaves than in green leaves. Enzymatic dissolution of leaves into vascular tissue, intercostal cells and chloroplasts revealed that the Fe-content in the intercostal cells of green leaves was significantly higher than in the intercostal cells of chlorotic leaves. In addition the intercostal cells of chlorotic leaves had extremly high Ca and P-contents. The P content of green and chlorotic leaves was not related to the level of available P in the soil. It is therefore concluded that the high P content in chlorotic leaves is the sequence and not the cause of Fe-chlorosis. On each of the three sites investigated, higher clay contents were found under chlorotic grapevine plants than under healthy ones. It is assumed that because of this higher clay content, soil compaction may occur, resulting in an accumulation of CO2 and in an increase of the HCO3− concentration in the soil solution.
Generative Adversarial Network for Desert Seismic Data Denoising

Seismic exploration is a kind of exploration method for oil and gas resources. However, the disturbance of numerous random noise will decrease the quality and signal-to-noise ratio (SNR) of real seismic records, which brings difficulties to the following works of processing and interpretation. The seismic records of desert region pose a particular problem because of the strong energy noise and the spectrum overlapping between effective signals and random noise. Recent research works demonstrate that a convolutional neural network (CNN) can increase the SNR of seismic records. The optimization of denoising methods based on CNN is principally driven by the loss functions that largely focus on minimizing the mean-squared reconstruction error between denoising records and theoretical pure records. The denoising results estimated by the CNN model are often lacking the perfection of the signal structure. Therefore, when processing seismic records with low SNR, the denoising results often have a lack of effective signal in some traces, which leads to the poor continuity of events. In order to solve this problem, we adopt the strategy of generative adversarial network (GAN) to construct a GAN for denoising. It is divided into two parts: the generator (the denoising network based on CNN) is used to remove noise, while the discriminator is used to guide the generator to restore the structure information of effective signals. The generator and discriminator enhance the performance of each other through adversarial training, and the generator after adversarial training can greatly recover events and suppress random noise in synthetic and real desert seismic data.
Technology Acceptance Model of Financial Technology in Micro, Small, and Medium Enterprises (MSME) in Indonesia

Seeing the existence of MSME needs that have still not been met although this sector is undeniably important in Indonesian economy, changes in community behaviour and the intensity of the use of technology in the community, financial technology (fintech) has a lot of potentials to become a part of the solution of the problem commonly faced by MSMEs. Therefore this research needs to be done to observe the potential of fintech in integrating MSMEs in terms of the application of technology and knowledge from the community related to fintech. By using Technology Acceptance Model, this research tries to understand the determinant factors of the fintech application used by MSME. Based on the research framework and model, path analysis method used in this research. This research uses primary data gathered by the questioner, which was distributed to MSME. From the analysis conducted, we can conclude that the external factors tested in this research could have an effect on the behaviour intention through perceived usefulness in MSME practice of financial technology. Large variation in MSME educational background, busineess age and size would become a challenge in promoting fintech application, therefore this finding suggests that fintech should be promoted by highlighting what benefits can be obtained by using fintech application.
Adverse Effects of Leader Family-to-Work Conflict on Team Innovation

Drawing from resource drain theory, this article intends to investigate how and when leader family-to-work conflict (FWC) influences team innovation. We conduct two studies to test our model. In Study 1, we collect cross-sectional data from 107 research and development (R&D) team leaders from an electronic information company in China. In Study 2, we collect multisource and time-lagged data from 112 R&D team leaders and 371 members of a biopharmaceutical firm in China. Our research findings showed that leader FWC negatively affects team innovation via leader creative process engagement. Leader perceived organizational support (POS) alleviates the negative effect of leader FWC on leader creative process engagement. Leader POS also weakens the negative effect of leader FWC on team innovation via leader creative process engagement. We discuss the theoretical and practical implications of these results for team innovation, FWC, and POS.
Correlation between EPR, Raman and colorimetric characteristics of the blue ultramarine pigments

Samples of blue ultramarine pigments have been investigated by EPR and Raman spectroscopies, as well as by colorimetry. For the first time, correlations between EPR, Raman and colorimetric parameters of these pigments have been established. It is now established that there is not only one blue ultramarine, but different shades of blue depending on the relative concentrations of the blue and the yellow chromophores. The greenish and the reddish shades of blue are characterised by EPR, Raman and colorimetric parameters.
Evaluación del perfil de estados de ánimo en bailarines de danza española y flamenco

espanolLa danza espanola y el flamenco constituyen disciplinas artisticas onde los factores psicologicos y el dominio y control de los estados de animo se presentan como aspectos clave para un rendimiento experto. Asi, el objetivo de esta investigacion fue evaluar los estados de animo en bailarines y pertenecientes a diferentes companias, asi como en funcion de las distintas posiciones que ocupaban dentro del grupo. Para ello se aplico a 143 bailarines (96 mujeres y 47 hombres) con una edad entre los 18 y 51 anos (30.52±7.86) la version espanola para deportistas adolescentes del Profile Mood State Questionnaire (POMS) (McNair, Lorr & Droppleman, 1971). Se realizaron una prueba t-student y un MANCOVA. Los resultados mostraron diferencias en algunos factores entre los distintos grupos, siendo los bailarines pertenecientes al Ballet Nacional quienes presentabanvalores mas altos en los factores de depresion, colera y fatiga, mientras que aquellos que no pertenecian a dicha compania presentaban mejores valores en tension, vigor y amistad. Igualmente, los resultados en base a la posicion del bailarin dentro del grupo, manifestaron tambien diferencias. Por tanto, se puede concluir, como pertenecer a diferentes companias o la posicion que se ocupa dentro del grupo influye en los estados de animo EnglishSpanish dance and flamenco are artistic disciplines where psychological factors, mastery and control of moods are presented as key factors for expert performance. Therefore, the main aim of this research was to evaluate the moods in dancers belonging to different companies, as well asbdepending on the different positions they occupied within the group. For this, the Spanish version for teenage athletes of the Profile Mood State Questionnaire (POMS) (McNair, Lorr & Droppleman, 1971) was applied to 143 dancers (96 women and 47 men). The age of all subjects was between 18 and 51 years (30.52 ± 7.86). A t-student and MANCOVA was carried out. The results of this study showed differences in some factors between the different groups studied, being the dancers belonging to the National Ballet who presented higher values in the factors of depression, anger and fatigue, while those who did not belong to that company had better values in tension, vigour and friendliness. Likewise, the results based on the position of the dancer within the group, also showed differences Therefore, it can be concluded, how to belong to different companies and even the position within the group influence moods.
Sonochemically synthesized ferromagnetic Fe3O4 nanoparticles as a recyclable catalyst for the preparation of pyrrolo[3,4-c]quinoline-1,3-dione derivatives

This paper reports the green, rapid synthesis of Fe3O4 nanoparticles by the ultrasonic irradiation of Fe2O3 solution and Perilla frutescens (P. frutescens) leaf extract, which was used as both reducing and capping agent. The synthesized Fe3O4 nanoparticles were characterized by Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), transmission electron microscopy (TEM), scanning electron microscopy (SEM), energy dispersive X-ray analysis, vibrating sample magnetometry, thermogravimetric analysis (TGA) and X-ray photoelectron spectroscopy (XPS). The FT-IR spectra indicated that the bioactive molecules present in the plant extract contain polyols, which act as a reducing as well as capping agent, as confirmed by TGA. TEM and SEM showed that the Fe3O4 nanoparticles were approximately spherical in shape with a mean size of 50 nm. The synthesized Fe3O4 nanoparticles exhibited ferromagnetic behavior with a saturation magnetization of 25.15 emu g−1. The Fe3O4 nanoparticles, with their easy recovery by an external magnetic field, exhibited strong catalytic activity towards pyrrolo[3,4-c]quinoline-1,3-dione derivatives. These results suggest that the Fe3O4 nanoparticles produced can be applied as a catalyst in organic synthesis and recycled at least five times without significant loss in its activity.
A Comparison of COVID-19 Epidemiology, Pathophysiology, and Impact on Vulnerable Populations in Two States within the USA

Since late 2019, SARS-CoV-2 has differentially impacted geographies and population demographics as it spread. As of June 30, 2020, two hotspots within the United States of America—the states of Georgia and Michigan—exhibited similar numbers of cases while Michigan had over twice the case fatality rate (CFR) of Georgia. Given the similar populations, land areas, and pandemic timelines of these states, such a large difference is unexpected. The primary goal of this paper is to examine why Michigan experienced much higher COVID-19 mortality than Georgia, which may point to at-risk comorbidities and vulnerable populations. We examined publicly available data on demographics, rates of comorbidities, environmental factors, and other population differences at the state and local levels (the cities of Detroit, Michigan; Atlanta, Georgia; and Albany, Georgia) that have known or identified associations with health outcomes. We also outlined the timeline of the pandemic in each state to determine if the actions of state governments may have contributed to the observed difference in CFR. While the difference in state CFR may imply that Michigan handled the pandemic poorly, the data show that inherent characteristics of Detroit may have led to the higher statewide CFR. Notable differences between the states include elderly populations, agricultural statistics, and drinking habits. Notable differences between the cities included population density, health system quality, per capita income, race, education, media access, and air pollution. Hypertension (among blacks), diabetes (at the city level), chronic kidney disease, asthma, heart disease, and cancer differed in prevalence by location and were associated with increased severity and/or mortality of COVID-19. There were more deaths due to COVID-19 in African American communities and nursing homes in Michigan. A combination of these factors likely explains the differential impact between these two states.
Growth and Nutrient Uptake of Wheat in Clinoptilolite‐Phosphate Rock Substrates

Mixtures of zeolite and phosphate rock react to release cations and anions into soil solution through dissolution and ion exchange. These mixtures have the potential to serve as slow-release sources of nutrients in synthetic soils. The term zeoponics has been used to describe such systems. Research was conducted to monitor dry matter production and nutrient uptake of wheat (Triticum aestivum L.) in a zeoponic system containing phosphate rock and NH 4- and K-saturated zeolite. The objective was to evaluate the ability of zeolite and phosphate rock to provide a balanced supply of N, P, K, and Ca for plant growth. Two zeolite samples (San Miguel and Wyoming clinoptilolite) and two phosphate rock samples (North Carolina and Tennessee phosphate rock) were combined factorially to form four zeoponic mixtures. A series of synthetic soils was formed by combining selected rates of each zeoponic mixture with acid-washed quartz sand. Zeoponic rates (ZR) were 1, 5, 10, 25, 50, 75, and 100% (v/v) of the synthetic soil. Pots were placed in a growth chamber after planting, and plants were harvested every 45 d for a 225-d period. Foliar spray supplied essential nutrients other than N, P, K, and Ca. High yields of wheat dry matter were produced through several cuttings when at least 25% of the synthetic soil was comprised of the zeoponic mixture and when the zeoponic mixture contained a high-reactivity phosphate rock (North Carolina). Tissue analyses suggested that K, and to a lesser extent N, limited wheat growth when ZR ≤10%. Calcium limited wheat growth at ZR > 10% when a low-reactivity phosphate rock (Tennessee) was used, but not when a high-reactivity phosphate rock (North Carolina) was used. Properly formulated zeoponic mixtures of San Miguel or Wyoming clinoptilolite and North Carolina phosphate rock are capable of supplying sufficient levels of N, P, K, and Ca for intensive growth of wheat.
The Impact of External Integration and Internal Integration to Product Innovation and Competitive Advantage on Small and Medium Enterprises (SMEs)

This study aims to analyze the influence of external integration and internal integration to product innovation and competitive advantage. The research was conducted on a sample of 180 manager small and medium enterprises (SMEs) in East Java clothing taken with stratified cluster sampling technique. Selection of sample areas based on areas that have the potential development of the industry. Data collection was done by using questionnaire that has been tested for its validity and reliability. Data analysis used Structural Equation Modeling (SEM) analysis with help of AMOS version 21 program. Based on the analysis of SEM, it was found that the first, external integration influence on product innovation SMEs and affect the competitive advantage of SMEs. Second, the internal integration effect on product innovation SMEs and affect the competitive advantage of SMEs. Third, product innovation SMEs effect on the competitive advantage of SMEs. In this respect, the company needs to build a collaboration of external integration and internal integration in order to improve product innovation and competitive advantage of SMEs.
CHARACTERIZATION OF CHICKEN NUGGETS WITH THE ADDITION OF FLOUR FROM PEACH PALM BY-PRODUCT / CARACTERIZAÇÃO DE NUGGETS DE FRANGO COM ADIÇÃO DE FARINHA DE SUBPRODUTO DE PALMITO PUPUNHA

The aim of this study was to evaluate the potential of using the peach palm by-product (FPP), fiberrich flour, to promote the nutritional enrichment of chicken nuggets. The formulations were produced by replacing chicken skin by FPP, at levels of 0 (control), 4, 8 and 12%. Texture, physicochemical and sensorial properties were evaluated. The contents of dietary fiber and ashes increased due to the addition of FPP (p<0.05), while the protein content was similar among the tested formulations (p>0.05). With the addition of FPP to nuggets there was a decrease in fat content and weight loss, while the values of yield and emulsion stability increased. The formulations with FPP addition had higher values of luminosity (L*) and chromacity b* and lower value of a* than the control sample. The texture profile analysis indicated that hardness, gumminess and chewiness increased due to the addition of FPP, not interfering in springiness. Nugget formulations containing 4% and 8% FPP were well accepted by the tasters, with a sensorial acceptance index ≥ 70%. According to principal component analysis the formulation containing 4% of FPP addition in replacement of chicken skin can be considered more viable than the other tested formulations. Brazilian Journal of Development Braz. J. of Develop. , Curitiba, v. 6, n. 10, p. 75259-75273, oct. 2020. ISSN 2525-8761 75260