Miracle-dz/UniFAR-FTUs huggingface dataset:
Study of Left Atrial Appendage Function in Patients of Severe Rheumatic Mitral Stenosis and Effect of Successful PTMC on SEC Grading

Background: Left Atrial Appendage (LAA) dysfunction is common in patients of Mitral stenosis (MS). In the present study we compared the LAA function amongst patients of severe rheumatic MS with particular reference to spontaneous echo contrast (SEC) and evaluated the effect of successful Percutaneous Transvenous Mitral Commissurotomy (PTMC) on SEC grading. Methods: It was a single centre prospective descriptive type of study. Total 75 cases were included during the study period from 2016 to 2020. Symptomatic patients with severe rheumatic mitral stenosis (MVA<1.5cm2) in sinus rhythm fulfilling the elective PTMC intervention criteria and those who had a successful intervention only were included. All the patients underwent Clinical examination, ECG, detailed TTE and TEE before, Immediately after (within 24hrs) & after 6 months of PTMC. Results: In the present study mean LAAAC% and LAA PW Doppler velocities were significantly less in patients of severe rheumatic Mitral Stenosis having SEC than patients without SEC, implying more severe LAA dysfunction in patients with SEC. LAA Tissue Doppler velocities were also less in patients with SEC compared to patients without SEC but it was statistically not significant. There was a significant negative correlation between SEC grading and LAAAC (%) and LAA PW Doppler velocities (LAAEDE Velocity, LAALDE Velocity and LAAF velocity), i.e. greater the degree of SEC lesser was the LAAAC (%), LAAEDE Velocity, LAALDE Velocity and LAAF velocity, suggesting more severe LAA dysfunction in patients with greater degree of SEC. There was also negative correlation between SEC grading and LAA Tissue Doppler velocities (ELAA Velocity, ALAA Velocity, SLAA Velocity) but it was statistically not significant. Successful PTMC resulted in significant decrease in SEC grading. Conclusion: Among the patients of severe rheumatic mitral stenosis, presence of SEC implies severe LAA dysfunction, greater the intensity of SEC, greater would be the severity of LAA dysfunction and successful PTMC results in improvement of SEC grading.
Investigation of the in vitro Anticancer Activity of Sorbus aria Extract on Prostate Cancer

Cancer is one of the common diseases observed in our country and worldwide with a high mortality rate. Although cancer has been treated with different applications such as chemotherapy, radiotherapy and surgical operation, the exact remedy of this disease has still not been found, yet. The fact that current treatment methods have severe side effects on patients has increased the interest in natural anticancer agents that are accepted easily and considered as safer by society. The aim of this study is to investigate the anticancer activity of whitebeam (Sorbus aria) that grows in the Central Anatolia Region in Turkey, extract on PC-3 human prostate cancer cells in vitro. The anticancer activity of the ethanol extract obtained from whitebeam fruits evaluated using MTT cell proliferation assay. Also, Folin-Ciocalteu assay and CUPRAC method were performed to determine total phenol content and antioxidant capacity of whitebeam fruits, respectively. Whitebeam fruit extract showed strong anticancer activity on prostate cancer in vitro. The obtained ethanol extract is found to be a promising natural anticancer agent in vitro, and our findings need to be verified with in vivo studies and clinical trials.
Do Seasonal Changes and Climate Effect
the Prevalence of Antibiotic Resistance
of Acinetobacter calcoaceticus-baumannii
Complex?

The high rate of carbapenem resistant Acinetobacter calcoaceticus-baumannii Complex (ABC) is indicated as a threat to public health. We aimed to determine the ABC isolated from Near East University hospital from 2016 to 2019 based on seasonality and climate changes. A total of 218 patients were examined between 2016 and 2019. All isolates were healthcare-acquired isolates, which are defined as those obtained after 48 hours of admission. All isolates were identified by a Phoenix 100 System. Antibiotic susceptibility analysis was reported based on EUCAST guidelines. Isolates were grouped according to seasons as follows: December through February as Quarter 1 (Q1); March through May as Quarter 2 (Q2); June through August as Quarter 3 (Q3); and September through November as Quarter 4 (Q4). Statistical analysis was performed with SPSS Ver 13.0 (SPSS Inc., Chicago, IL, ABD) program. There were significant differences between the number of patients with ABC infections according to years (p=0.000). The rate of carbapenem resistance of ABC was 86.2 % (n = 188). The resistance rates of the ABC isolates as well as carbapenem resistance peaked in October. The infection increased in the summer and decreased gradually in the autumn, winter and spring (p = 0.009). No significant difference was found between the carbapenem resistance of ABC infection and seasonality (p = 0.202). We have found that ABC infections and the carbapenem resistance of ABC increases in the summer months. However, more studies should focus on the epidemiological aspect of ABC infections.
Features of Distance Education in Ukraine during the Covid-19 Pandemic: Problems and Prospects

Our study reveals the peculiarities of the educational process in Ukraine after the introduction of distance learning related to the Covid-19 pandemic. The study was conducted based on two leading educational institutions in Ukraine. We have established that the introduction of distance education both in the world and in Ukraine has its pros and cons. In particular, it depends primarily on the initiative of the teacher to implement such technologies, as well as on the willingness of students to use them and the technical ability of both parties to use these technologies (because our country has faced the problem of Internet coverage). We found that in the era of information technology, the level of communication, both interpersonal and with students, has not changed among the respondents. It is established that almost all teachers who took the survey believe that distance education does not provide students with practical skills, competencies after graduation. Distance education from the point of view of management and administrative activity is more expedient, it gives educational institutions more decentralization and optimization in work.
Seasonal grassland productivity forecast for the U.S. Great Plains using Grass‐Cast

Every spring, ranchers in the drought-prone U.S. Great Plains face the same dif ﬁ cult challenge — trying to estimate how much forage will be available for livestock to graze during the upcoming summer grazing season. To reduce this uncertainty in predicting forage availability, we developed an innovative new grassland productivity forecast system, named Grass-Cast, to provide science-informed estimates of growing season aboveground net primary production (ANPP). Grass-Cast uses over 30 yr of historical data including weather and the satellite-derived normalized vegetation difference index (NDVI) — combined with ecosystem modeling and seasonal precipitation forecasts — to predict if rangelands in individual counties are likely to produce below-normal, near-normal, or above-normal amounts of grass biomass (lbs / ac). Grass-Cast also provides a view of rangeland productivity in the broader region, to assist in larger-scale decision-making — such as where forage resources for grazing might be more plentiful if a rancher ’ s own region is at risk of drought. Grass-Cast is updated approximately every two weeks from April through July. Each Grass-Cast forecast provides three scenarios of ANPP for the upcoming growing season based on different precipitation outlooks. Near real-time 8-d NDVI can be used to supplement Grass-Cast in predicting cumulative growing season NDVI and ANPP starting in mid-April for the Southern Great Plains and mid-May to early June for the Central and Northern Great Plains. Here, we present the scienti ﬁ c basis and methods for Grass-Cast along with the county-level production forecasts from 2017 and 2018 for ten states in the U.S. Great Plains. The correlation between early growing season forecasts and the end-of-growing season ANPP estimate is > 50% by late May or early June. In a retrospective evaluation, we compared Grass-Cast end-of-growing season ANPP results to an independent dataset and found that the two agreed 69% of the time over a 20-yr period. Although some predictive tools exist for forecasting upcoming growing season conditions, none predict actual productivity for the entire Great Plains. The Grass-Cast system could be adapted to predict grassland ANPP outside of the Great Plains or to predict perennial biofuel grass production.
Information Fusion and Semi-Supervised Deep Learning Scheme for Diagnosing Gear Faults in Induction Machine Systems

There has been an increasing interest in the design of intelligent diagnostic systems for industrial applications. The key requirement in the design of practical diagnostic systems is the ability for decision making in high-dimensional feature spaces, where the prior knowledge about the system states in terms of labels is very limited. Moreover, the problem of diagnosing simultaneous defects is rarely addressed on real industrial applications. This paper aims to develop a semi-supervised deep-learning scheme for diagnosing multiple defects including simultaneous ones in a gearbox directly connected to an induction machine shaft. This scheme consists of two main modules: information fusion and decision making. The former integrates captured multiple sensory streams into a very high dimensional feature space. The latter uses a semi-supervised deep learning procedure to minimize the human interaction during the training and maximize the diagnostic efficiency. This scheme facilitates learning and diagnosing defects under harshest conditions 1) where only a few number of labeled samples are collected together with a large number of unlabeled samples, and 2) in a very high-dimensional feature space. Several state-of-the-art semi-supervised and supervised learners have also been included in the scheme, enabling a comparative experiment for diagnosing simultaneous defects.
Analysis and Implementation of a Single Input Dual Output Boost Derived Hybrid Converter

The hybrid converter which can simultaneously deliver DC and AC outputs by using a single DC input is referred as hybrid converter. This system can be achieved by replacing the switch of a conventional boost converter by a voltage source inverter (VSI) bridge network. The converter is called boost derived hybrid converter (BDHC). This configuration got a very wide range of application in the modern electric vehicle industry. The resulting hybrid converter needed lesser number of switches in respect of conventional methods to generate both dc and ac outputs. For controlling switches, pulse width modulation (PWM) control scheme based on unipolar sine-PWM is introduced. The advantages of this converter are better power processing density and increased reliability. The topology has better shoot through protection compared to conventional voltage source inverter which avoid dead time compensation. The hybrid converter has applications in electric power system, electric and hybrid vehicles.
Laparoscopic liver resection for non-colorectal non-neuroendocrine liver metastases: narrative review of literature

Liver resection for resectable colorectal and neuroendocrine liver metastases is the treatment of choice, and laparoscopic approach is considered safe and viable in these patients, with less postoperative complications compared to open surgery. Liver surgery for non-colorectal non-neuroendocrine liver metastases (NCNNLM) is a controversial issue as well as the role of minimally invasive surgery for this heterogeneous groups of malignancies. Patients with NCNNLM in fact are frequently referred to palliation due to the presence of extra-hepatic disease, and even in case of surgery, they usually undergo laparotomic approach. This article aims to examine and consider some of the most relevant contribution to this issue published in literature, trying to take stock of this still unsolved topic of oncologic surgery. Several studies have stated that liver resection can improve outcome in patients with NCNNLM, after careful selection based on different aspects and characteristics. Several criteria of selection have been identified, trying to select patients who could benefit more of surgery, and they include primary tumor histology, age, type of hepatectomy, presence of extra hepatic disease (EHD), length of disease-free interval. Recent reports not only confirm the pivotal role of selection of patient but also specify the technique of liver surgery (open vs. laparoscopic technique), confirming that laparoscopy has better short-term outcomes such as acceptable operative times, blood losses and conversion rate, whereas long-term survival is comparable to those of open liver resection. In conclusion, careful patient selection is the mainstay of treatment of NCNNLM, based on tumor biology and characteristics, and laparoscopic surgery seems to be an adequate approach. Unfortunately, evidence in literature remain scarse or even contradictory, lacking a sufficient number of patients for each tumor. Not rarely studies take into considerations different criteria of selection, which results in additional variability of cohort of populations among studies, and difficult in comparing them.
An investigation of the formation and growth of oxide-embedded silicon nanocrystals in hydrogen silsesquioxane-derived nanocomposites

We report a detailed investigation into the formation of oxide-embedded Si nanocrystals formed during the thermally induced disproportionation of solid hydrogen silsesquioxane (HSQ) in a reducing atmosphere. Silicon nanodomain size, crystallinity, composition, bonding structure, and photoluminescent response were evaluated as functions of processing temperature and time using X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy, and photoluminescence spectroscopy. Our interpretation of data obtained from these analyses provides a basis for a multistep process that yields oxide-embedded Si nanocrystals of controlled structure, composition, and size.
Real Route Navigation System based Automated Stereo Volume Control in Vehicles

The proposed prototype “Real route navigation system based automated stereo volume control system” controls the stereo volume of a car or any vehicle. The volume control is adaptive and regulates as prescribed by the central pollution control board. The major components of the prototype are single-board computer and Thin film transistor (TFT) display. Further, an android application called GPS logger is used to get the precise Latitude and longitudinal coordinates of the vehicular position using cell Phone. The co-ordinates sent by the GPS logger to the cloud are retrieved by the single board computer using read and write Application programming interface (API) keys. On considering various areas like Silent zone, No-horn zone, City limits, and Highway. Co-Ordinates have been manually set with fixed sound limits for each zone. The designed prototype is simple and cost-effective to provide automated stereo volume control which is the vital requirement as one of the features in Autonomous vehicular Design.
Droop-Controlled Rectifiers That Continuously Take Part in Grid Regulation

In this paper, a generic framework for a rectifier to continuously take part in the regulation of grid voltage and frequency is proposed. It can automatically change the power consumed to support the grid, without affecting the normal operation of the load. Such a rectifier has a built-in storage port, in addition to the normal ac and dc ports. The flexibility required by the ac port to support the grid is provided by the storage port without affecting the dc port. The grid support of the ac port is achieved through the recently proposed universal droop controller (UDC). A dc-bus voltage controller cascaded to the UDC is proposed to regulate the dc-bus voltage of the storage port within a wide range so as to provide the flexibility needed, while the dc-port voltage is maintained constant. An illustrative example is presented with the recently proposed $\theta$-converter, which consists of three ports with only four switches. Experimental results are provided to verify the capability of the rectifier to regulate the grid voltage and frequency without affecting the load.
Do remittances condition the relationship between trade and government consumption?

ABSTRACT This paper used a panel model and 99 developing economies over the 1980–2018 period to investigate the effect that remittances had on the relationship between trade and government consumption. We showed that remittances mediate the relationship between trade and government consumption. We documented that in high remittance recipient countries, trade negatively affected government consumption. In low remittance recipient countries, by contrast, we found that trade positively affected government consumption. Our results suggested that remittances can reduce the fiscal cost on government budget associated with adverse trade shocks. We proposed two policy responses for remittance recipient countries.
Boosting Energy Efficiency and Solar Energy inside the Residential, Commercial, and Public Services Sectors in Mexico

The residential, commercial, and public sectors consume between 20% and 30% of final energy demand worldwide. Due to the intensive use of fossil fuels and conventional electricity, they also have an important participation in the emission of greenhouse gases (GHG). Taking Mexico as a case study, this article develops an alternative scenario that considers that in these sectors, buildings can generate energy for self-consumption or to supply it to the power network—for which four solar energy options are analyzed. In addition, to manage and rationalize the energy demand of these buildings, eight energy efficiency measures are studied. These options were selected on the basis that they are technically and economically feasible to implement in buildings in Mexico. The results reveal that by 2030, in relation to the GHG trend scenario, this mitigation scenario reduces 23.5 million tons of carbon dioxide equivalent (MtCO2e) in the residential (19 MtCO2e), commercial (2.6 MtCO2e), and public services sectors (1.9 MtCO2e), while by 2035 it reaches 45 MtCO2e; which far exceed the avoided emissions goals established in Mexico’s nationally determined contributions (NDC) for 2030 (5 MtCO2e) for the residential and commercial sectors. Therefore, it is possible to increase the ambition for mitigation in these sectors, as well as including the public sector, in a renewed Mexico’s NDC. This mitigation scenario generates a total economic benefit of $7.7 billion, which means that it does not generate an overall incremental cost, but requires an incremental investment of over $9 billion USD, which is a financing challenge to achieve this scenario.
System of systems uncertainty quantification using machine learning techniques with smart grid application

System‐of‐Systems capability is inherently tied to the participation and performance of the constituent systems and the network performance which connects the systems together. It is imperative for the SoS stakeholders to quantify the SoS capability and performance to any uncertain variations in the system participation and network outages so that the system participation is incentivized and network design optimized. However, given the independent operations, management, and objectives of constituent systems, along with an increasing number of systems that collectively become a part of SoS, it becomes difficult to obtain a closed analytical function for SoS performance characterization. In this paper, we investigate and compare two machine learning techniques, Artificial Neural Network and Parametric Bayesian Estimation, to obtain a predictive model of the SoS given the uncertainty in the constituent system participation and the network conditions. We demonstrate our approach on a smart grid SoS application example and describe how the two machine learning techniques enable SoS robustness and resilience analysis by quantifying the uncertainty in the model and SoS operations. The results of smart grid example establish the value of SoS uncertainty quantification (UQ) and show how smart grid operators can utilize UQ models to maintain the desired robustness as operating conditions evolve and how the designers can incorporate low‐cost networks into the SoS while maintaining high performance and resilience.
The concentration of heavy metals in the potato tubers of the basic seed groups examined by the variation of fertilizers and pesticides and the period of cultivation

The compost, insecticides, and fungicides used by potato farmers in Bali contain heavy metals Fe, Pb, Cd, and Cr. The purpose of this study was to analyze the impact of the seed group potato cultivation system on the concentration of several heavy metals in potato tubers. Cultivation was carried out in the rainy and dry season with: (1) NPK fertilization, (2) NPK fertilization, insecticide and fungicide spraying, (3) NPK fertilization and compost, and (4) NPK fertilization, compost, insecticide and fungicide spray. Each experimental unit was carried out by 5 farmers as a replication. The variables observed were concentrations of Fe, Pb, Cd, and Cr in the soil, plant parts, and potato tubers. Soil, plant, and potato tuber samples were taken randomly with 5 repetitions from the experimental unit. The Concentrations of Fe, Pb, Cd, and Cr metals in potato plants which are cultivated in the rainy season are on average greater in the amount of metal Fe = 1-21 ppm, Pb = 0.05-3.65 ppm, Cd = 0.01-0.15 ppm, and Cr = 0.02-0.18 ppm of concentrations in plants cultivated in the dry season. The metal content in the root zone of the potato seeds plants were Fe = 120.5 ± 3.2 ppm, Pb = 0.82 ± 0.17 ppm, Cd = 0.4 ± 0.1 ppm, and Cr = 0.59 ± 0, 2 ppm. Metal content in potato tubers were Fe = 0.1-0.3 ppm, Pb = 0.07-0.21 ppm, Cd = 0.03-0.06 ppm, and Cr = 0.03-0.07 ppm, these values are still below the food safety threshold according to WHO. The potato tuber which cultivated is still within safe limits for human consumption, but the spraying of insecticides and fungicides and the use of compost must begin to be limited because it causes an increase in Fe, Pb, Cd, and Cr metals in potato plants amounting 3.53-4.36 ppm, 0.41-0.5 ppm, 0.12-0.15 ppm, and 0.22-0.27 ppm, respectively. Fertilization using chicken manure compost at a dose of 10-20 tons ha-1 is very effective in supporting potato cultivation with the LEISA system. The ability of microbes in the compost to carry out an in-situ bioremediation process on Fe, Pb, Cd, and Cr metals is 49.61-55.60 ppm, 2.59-5.64 ppm, 35.24-52.44 ppm, and 19.68-54.24 ppm, respectively.