Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluations of Inflammatory Status in Chronic Renal Failure Patients Undergoing Hemodialysis and Conservative Treatment

Introduction: - Chronic inflammation is a basic feature of end stage kidney disease and is associated withincreasing risk of mortality and morbidity in patients undergoing dialysis.The aim: - the study amid toevaluate white blood cells and IL-6 in patients undergoing hemodialysis and without hemodialysis. Methodsand Subjects:- The study was designed on 106 patients with chronic renal failure age range (20-69years). The patients divided in two groups according to treatment, 40 patients with conservative treatment and66 patients with hemodialysis treatment. IL-6 were determined by using a commercially available ELISAMicro wells kit. Total white blood cells count and differential count were determined by using an automatedhematology autoanlyzer XT2000i. Results:- showed a significant (p<0.05) decrease of total white bloodcells count, neutrophils, lymphocytes, monocytes, eosinophils and basophils in hemodialytic group whencompared with conservative group. But IL-6 levels was higher significantly (p<0.01) in hemodialytic groupwhen compared with conservative group. Conclusion: - hemodialysis session impaired immune system andactivated anti-inflammatory factors.
Technological, Ethical, Environmental and Legal Aspects of Robotics

Robotics is considered by modern researchers from various positions. The most common technical approach to the study of this concept, which examines the current state and achievements in the field of robotics, as well as the prospects for its development. Also, quite often in recent years, legal experts have begun to address problems related to the development of robotics, focusing on issues related to the legal personality of robots and artificial intelligence, as well as the responsibility of AI for causing harm. A separate direction in the field of robotics research is the analysis of this concept and the relations associated with it, from the standpoint of morality, ethics and technologies.
METHODS OF STANDARDIZATION, WEIGHTING AND AGGREGATION IN THE FORMATION OF SUSTAINABILITY INDEX

A estruturacao de um indice de sustentabilidade necessita de um processo transparente e confiavel, para que seus resultados sejam os mais proximos da realidade e consistentes. Este estudo objetivou uma analise critica do processo da elaboracao estrutural dos (sub)indices de sustentabilidade, comparando suas principais desvantagens e vantagens. A metodologia utilizada centra-se na qualitativa mediante a tecnica de revisao sistematico da literatura e a snowballing. As palavras chave (composite indicators, index, sustainability, aggregation, normalization, advantages e disadvantages) foram inseridas nos diretorios de busca da Google Scholar, Science Direct, Springer Link e Wiley Online Library. Os principais resultados revelam que as tecnicas utilizadas no processo de normalizacao, ponderacao e agregacao de um conjunto de dados em um indice de sustentabilidade apresentam indistintamente fragilidades e limitacoes. Alem disso, as tecnicas multicriterio de agregacao abrangem dados qualitativos, quantitativos e suas incertezas, porem nao eliminam as fragilidades e limitacoes da estruturacao do indice de sustentabilidade. Sendo assim, tendem a ser mais adequados, mas nao garantem que o indice gerados reflitam a complexidade da realidade do sistema que foi reduzido. As contribuicoes teoricas e praticas, deste estudo, relacionam-se com as escolhas dos metodos e tecnicas na estruturacao do (sub)indice de sustentabilidade, pois mesmo com a escolha dos mais adequados na sua elaboracao, nao eliminam suas fragilidades e limitacoes. A originalidade do estudo e a juncao dos principais metodos e tecnicas de elaboracao de um (sub)indice de sustentabilidade em um unico documento, na lingua portuguesa.
Multimaterial Aerosol Jet Printed Magnetic Nanocomposites for Microwave Circuits

This article demonstrates the process and characterization of additively manufactured polymer-matrix magnetic nanocomposites. These nanocomposites are composed of nickel–zinc ferrite (Ni0.5Zn0.5Fe2O4) nanoparticles in a polyimide matrix. These materials are printed using multimaterial aerosol jet printing where aerosols of nickel–zinc ferrite and polyimide inks are mixed in place to fabricate structures with nonunity relative permeability. To characterize these materials, we use energy-dispersive X-ray spectroscopy to estimate the content of ferrite in the composite, fitted simulation models, and ring resonator measurements to estimate the permeability. In fully aerosol jet printed 1-mm2 inductors, we demonstrate an increase in inductance density of 40% in a 4.5-turn microstrip spiral inductor using this printed composite. These fully printed inductors demonstrate an inductance density of 4.2-nH/mm2. EDS analysis shows films with 18 wt. % Ni0.5Zn0. 5Fe2O4. Finally, we show microstrip transmission lines on printed composite compared to the same on polyimide subjected to a dc magnetic bias, displaying a magnetic resonance behavior.
Determination of Evaporative Fluxes Using a Bench-Scale Atmosphere Simulator

An accurate determination of evaporative fluxes is critical for efficient water management in semi-arid climates such as in the Canadian Prairies. The main achievements of this research are the design and operation of a bench-scale atmosphere simulator, performance evaluation using selected weather scenarios pertaining to regional atmospheric conditions, validation using established empirical correlations, and estimation of evaporation rates and the amount for a typical local water body. Results indicate that the measured data achieved the target values for the various parameters and the data were found to be stable during the 3-h test duration. The vapour flux was found to have large variation during summer (0.120 g∙s−1∙m−2 during the day and 0.047 g∙s−1∙m−2 at night), low variation during spring (0.116 g∙s−1∙m−2 during the day and 0.062 g∙s−1∙m−2 at night), and negligible change during fall (0.100 g∙s−1∙m−2 during the day and 0.076 g∙s−1∙m−2 at night). The measured vapour flux was generally within one standard deviation of the equality line when compared with that predicted by both the mass-transfer equations and the combination equations. The average evaporation ranged from 4 mm∙d−1 to 8 mm∙d−1 during the day and decreased to 1 mm∙d−1 to 3 mm∙d−1 at night. The 24-h evaporation was found to be 8 ± 1 mm∙d−1 from late April through late October. Likewise, the cumulative annual evaporation was found to be 1781 mm, of which 82% occurs during the day and 18% at night.
Comparison of ultrasound and histopatological findings breast cancer between women aged below and above 40 years.

Breast cancer is the most common cancer among females, but breast cancer incidence in young women is low. There are limited studies of breast cancer in this age group in Malaysia, while there are conflicting data regarding these women's prognosis compared to older patients. This study describes the common features presented by breast carcinoma on histopathological and ultrasound findings. Objective: To compare the ultrasound findings and histopathological characteristics of breast cancer for women aged below 40 years and those aged 40 years and above. Methodology: This was a retrospective, cross-sectional study using secondary data, in which the data was collected respectively from patient's clinical histories, radiology findings, and histopathology reports of patients with breast cancer in Hospital Serdang from 1 January 2009 until 31 December 2018. Patients were divided into two age groups (ages below 40, ages 40 and above). Results: 205 patients were included in this study. The most common type of breast carcinoma is invasive ductal carcinoma. Common features are grade II breast cancer cells, DCIS high grade, stage 2 (TNM), tumour size of T2 and lymph node invasion. The majority of tumours are positive with oestrogen receptor, progesterone receptor, and HER2 receptor. Conclusion: Younger age group has a similar feature with the older age group, except they have late stage and progesterone negativity. There is no significant association between age group, ultrasound, histological features, and breast carcinoma receptors.
Improvement in performance of solution-processed indium–zinc–tin oxide thin-film transistors by UV/O3 treatment on zirconium oxide gate insulator

We studied solution-processed amorphous indium–zinc–tin oxide (a-IZTO) thin-film transistors (TFTs) with spin-coated zirconium oxide (ZrOx) as the gate insulator. The ZrOx gate insulator was used without and with UV/O3 treatment. The TFTs with an untreated ZrOx gate dielectric showed a saturation mobility (μsat) of 0.91 ± 0.29 cm2 V−1 s−1, a threshold voltage (Vth) of 0.28 ± 0.36 V, a subthreshold swing (SS) of 199 ± 37.17 mV/dec, and a current ratio (ION/IOFF) of ∼107. The TFTs with a UV/O3-treated ZrOx gate insulator exhibited μsat of 2.65 ± 0.43 cm2 V−1 s−1, Vth of 0.44 ± 0.35 V, SS of 133 ± 24.81 mV/dec, and ION/IOFF of ∼108. Hysteresis was 0.32 V in the untreated TFTs and was eliminated by UV/O3 treatment. Also, the leakage current decreased significantly when the IZTO TFT was coated onto a UV/O3-treated ZrOx gate insulator.
Preparation and Characterization of Au/NiPc/Anti-p53/BSA Electrode for Application as a p53 Antigen Sensor

While the tumor suppressor protein p53 regulates the cell cycle to prevent cell damage, it also triggers apoptosis and prevents cancer. These inhibitory functions may disappear once the p53 gene is mutated. Under these circumstances, the detection of p53 protein concentrations can have significant clinical applications. In this study, nickel phthalocyanine (NiPc) was coated on a gold electrode to produce a modified Au/NiPc electrode. p53 antibodies were bonded to the Au/NiPc electrode by the Ni+2 ion in NiPc, which can be self-assembled with the imidazole group of the p53 protein. The Au/NiPc/anti-p53 electrode was subsequently dripped with a buffer solution of bovine serum albumin (BSA) to form the Au/NiPc/anti-p53/BSA electrode, which was used for the detection of p53 antigen under 10 mM potassium ferricyanide/potassium ferrocyanide (K3Fe(CN)6/K4Fe(CN)6) solution by cyclic voltammetry and differential pulse voltammetry analyses. The linear detection range and the sensitivity for the p53 antigen were 0.1–500 pg/mL and 60.65 μA/Log (pg/mL)-cm2, respectively, with a detection time of 90–150 s. In addition, Au/NiPc/anti-p53 (100 ng/mL)/BSA electrodes were tested for specificity using glucose, bovine serum albumin, histidine, ascorbic acid, uric acid, prostate-specific antigen, human serum albumin, and human immunoglobulin G. All p-values were <0.0005, indicating an outstanding specificity.
The Impacts of Hydropower Dams in the Mekong River Basin: A Review

The Mekong River, well known for its aquatic biodiversity, is important to the social, physical, and economic health of millions living in China, Myanmar, Laos, Thailand, Cambodia, and Vietnam. This paper explores the social and environmental impacts of several Mekong basin hydropower dams and groupings of dams and the geographies of their impacts. Specifically, we examined the 3S (Sesan, Sekong Srepok) river system in northeastern Cambodia, the Central Highlands of Vietnam, and southern Laos; the Khone Falls area in southern Laos; the lower Mun River Basin in northeastern Thailand; and the upper Mekong River in Yunnan Province, China, northeastern Myanmar, northern Laos, and northern Thailand. Evidence shows that these dams and groupings of dams are affecting fish migrations, river hydrology, and sediment transfers. Such changes are negatively impacting riparian communities up to 1000 km away. Because many communities depend on the river and its resources for their food and livelihood, changes to the river have impacted, and will continue to negatively impact, food and economic security. While social and environmental impact assessments have been carried out for these projects, greater consideration of the scale and cumulative impacts of dams is necessary.
The Pandemic Holiday Blip in New York City

When it comes to pandemics, such as the one caused by the Coronavirus disease COVID-19, various issues and problems have arisen for the healthcare infrastructure and institutions. With increasing number of patients in need of urgent medical care and hospitalizations, the healthcare systems and regional hospitals may approach their maximum service capacity and may face shortage of various parameters, such as supplies including PPE, medications, therapeutic devices, ventilators, beds, and many more. The article at hand describes the development and framework of a simulation model that enables the modeling and evaluation of the COVID-19 pandemic progress. To achieve this, the model dynamically mimics and simulates the developments and time-dependent behavior of various crucial parameters of the pandemic, among others, the daily infection numbers and death rate. In addition, the model enables the simulation of single events and scenarios that occur outside of the regular pandemic developments as anomalies, such as holidays. Unlike traditional models, the proposed framework is based on factors and parameters closely derived from reality, such as the contact rate of individuals, which allows for a much more realistic representation. In addition, the real connection enables the assessment of effects of various influences regarding the development and progress of the pandemic, such as hospitalization numbers over time. All the aforementioned points are possible within the simulation framework and do not require awaiting the unfolding of the effects in reality. Thus, the model is capable of dynamically predicting how different scenarios turn out. The abilities of the model are demonstrated, illustrated, and proven in a specific case study that shows the impact of holidays, such as Passover and Easter in New York City when quarantine measures might have been ignored, and an increase in extended family gatherings temporarily occurred. As a result, the simulation showed significant impacts and disproportionate number of patients in need of medical care that could be potentially detrimental in reality. For example, compared to the previous trajectory of the pandemic, for a temporary increase of 50% in the contact rate of individuals, the model showed that the total number of cases would increase by 461 090, the maximum number of required hospitalizations would rise to 79 733, and the total number of fatalities would climb by 19 125 over 90 days. In addition to its function and proven capabilities, the model can and is furthermore planned to be adapted to other areas, not necessarily only metropolitan regions in order to expand the utilization of its predictive power. Such predictions could be used to derive regulatory measures and to test various policies for COVID-19 containment.
Study on Development and Quality Evaluation of Chocolate Coated Millet Wafers

Wafer is a small crisp type scrumptious biscuit generally prepared with wheat flour, where the product will undergo a process of heat treatment which reduces the moisture content to a low level i.e. less than 5%. These products are commonly regarded as biscuits by consumers (Nandini et al., 2019). The wafer industry is expected to grow further because the wafers are light in weight and enjoyed as a special treat by the consumer due to their unique sensorial property. Critical parameters for the quality of wafer biscuits are the level of crispness and its retention over shelf life. These two parameters play a major role in maintaining the quality of wafers. Most of the top-selling confectionery products are made up of wafers which are used as top-selling components. Bread or biscuit making literature shows little similarity to the wafers. Coming to characteristics of wafers, these are of crisp, light, and delicate texture. Due to low residual moisture i.e. in the range of 1 to 2% wafers are very crispy in texture. Wafers require high International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 10 Number 01 (2021) Journal homepage: http://www.ijcmas. com
Predictive models for metrological data of engineering systems

Paper is devoted to the predictive models for metrological indicators on the real estate engineering infrastructure. The solution is in demand among many enterprises both in terms of security and economic considerations. The key task is to build a mathematical model performing predictions on the real data samples. We study both classical predictive models (ARIMA, SARIMA) and modern machine learning based approaches (RBF, LSTM), and compare them.
An Adaptive Visual Dynamic-SLAM Method Based on Fusing the Semantic Information

The SLAM problem in dynamic scenes is regarded as a challenge. This article proposes a novel SLAM framework for dynamic environments, which combines neural network and motion information of dynamic objects, making the system more adaptable to dynamic scenes. Specifically, we adopt a fast object detection network, tightly couple the results of the object detection with the geometric information in the SLAM system. Then the feature point extracted from the image is associated with a dynamic probability. By utilizing the feature points which tend to be static, the localization result can be greatly improved in dynamic environments. We perform the experiments both on the public data set and the real environment. The result can demonstrate that the proposed method greatly improves the localization accuracy in a dynamic environment. An open-source version of the source code is available.
Predicting Earnings Management from Qualitative Disclosures

While analysts, customers, and lenders rely on financial disclosures to make decisions regarding a company, executives often manage the disclosed earnings. Detecting such practices is thus a concern for company stakeholders and regulators. Qualitative disclosures are an additional source of information about a company's financial situation, but executives likely attempt to hide their earnings management activity in these disclosures, as well. We use supervised machine learning models to predict earnings management by property and casualty insurers from the Management’s Discussion and Analysis filings. For this, we utilize a new algorithm that interprets textual data conditional on the reported financial situation of the company. We show that the qualitative disclosures can predict earnings management, revealing that executives are unable to remove all subliminal messages from them. The results demonstrate that qualitative disclosures can be useful for learning about the accounting choices of companies.
Indium Tin Oxide Thin Film Deposition by Magnetron Sputtering at Room Temperature for the Manufacturing of Efficient Transparent Heaters

Indium tin oxide (ITO) thin films are widely used as transparent electrodes in electronic devices. Many of those electronic devices are heat sensitive, thus their manufacturing process steps should not exceed 100 °C. Manufacturing competitive high-quality ITO films at low temperature at industrial scale is still a challenge. Magnetron sputtering technology is the most suitable technology fulfilling those requirements. However, ITO layer properties and the reproducibility of the process are extremely sensitive to process parameters. Here, morphological, structural, electrical, and optical characterization of the ITO layers deposited at low temperature has been successfully correlated to magnetron sputtering process parameters. It has been demonstrated that the oxygen flow controls and influences layer properties. For oxygen flow between 3–4 sccm, high quality crystalline layers were obtained with excellent optoelectronic properties (resistivity <8 × 10−4 Ω·cm and visible transmittance >80%). The optimized conditions were applied to successfully manufacture transparent ITO heaters on large area glass and polymeric components. When a low supply voltage (8 V) was applied to transparent heaters (THs), de-icing of the surface was produced in less than 2 min, showing uniform thermal distribution. In addition, both THs (glass and polycarbonate) showed a great stability when exposed to saline solution.
The Relationship of Smoking Habits, Cholesterol Level and Diabetes Mellitus (DM) History With Stroke Incidence in Patients at PKU Muhammadiyah Hospital Sruweng

Stroke is a health problem that attacks the neurological system. It may result in brain damage, paralysis and even death. Hypertension, smoking, Diabetes Mellitus, heart diseases, blood cholesterol levels, alcohol, and drug abuse are some of the risk factors that can be changed. The total outpatient stroke patients were 253 cases. This study is to determine the correlation of smoking habits, cholesterol levels and diabetes mellitus (DM) history with the incidence of stroke. This research is observational research. The samples were taken from 109 respondents using overall sampling technique. To determine the variable’s correlation used Chi Square data analysis. Research resuls have a relationship between smoking habits, cholesterol levels, the history of diabetes mellitus with the incidence of stroke (p value = 0,000) in patients at PKU Muhammadiyah Hospital Sruweng. There was a significant correlation between the variables (smoking habits, cholesterol levels and the history of diabetes mellitus) with the incidence of stroke in patients at PKU Muhammadiyah Hospital Sruweng
Lumbar Instability Induces Ligamentum Flavum Hypertrophy in a Rat Model

Background: The purpose of this study was to establish a novel rat model for ligamentum flavum (LF) hypertrophy using lumbar instability and to elucidate the etiology of LF hypertrophy. Methods: A total number of 30 male rats were used. Lumbar instability was induced by surgical resection of L5/6 posterior elements (n=15). The other rats underwent a sham operation (n=15). After 8 weeks, all rats were taken lateral plain X-rays. The LF from L5/6 in both groups were harvested to investigate histological, immunohistological, and real-time PCR analysis. Results: According to radiological results, the disc height ratio and extension ratio were larger in the rats in the experimental group than that of in the control group. The HE staining showed that the LF thickness in the experimental group significantly increased in comparison to the control group. The Masson trichrome staining showed that the ratio of elastic fibers to collagen fibers in experimental group was lower than that in the control group. The protein and gene expression of TGF-β1, TNF-α, IL-1β, and Col 1 were significantly higher in the experimental group than that in the control group. Conclusion: It is the first time that lumbar instability directly induced LF hypertrophy in a reproducible rat model. Lumbar instability could lead to high expression of inflammatory and fibrotic factors in LF, causing the accumulation of collagen fibers and decreasing of elastic fibers.
Multienzymic Effect with Prebiotics and Probiotics on Carcass Characteristics of Broilers

Poultry industry is one of the fastest growing segments of Indian economy. The Indian poultry market, consisting of broilers and eggs was worth INR 1,750 Billions in 2018 (Source: Internet). India today is the one of the world's largest producer of eggs and broiler meat. The poultry industry in India has undergone a major shift in structure and operation during the last some decades transforming from a mere backyard activity of rural farmers into a major industry with the presence of a large number of integrated players.