Miracle-dz/UniFAR-FTUs huggingface dataset:
SSARS 2011-Bris,Praks,Janurowa,Marlinek

Medical survival censored data of about 850 patient s are evaluated to compare two basic surgery techni ques. Data comes from patients who underwent colectomy in the University Hospital of Ostrava. The data has b een screened into three general groups: all patients (d ata from both rectum and colon operations), data fr om rectum operations, data from colon operations. Two basic s urgery techniques are used for the colectomy: eithe r classical (open) or laparoscopic operation. Basic q uestion which arises at the colectomy operation is which type of operation to choose to guarantee longer ove all survival time. Two methodological approaches h ave been used to answer this relevant question. First i s the non-parametric approach which results from Ka planMeier estimates of the survival function. For each data group two survival curves are constructed, i.e . for both open and laparoscopic type of operation. Final surv ival curves are compared and evaluated using advanc ed methods of statistical inference (e.g. log-rank tes t). Second is parametric approach which results fro m modelling of survival time. It is based on Maximum Likelihood Estimation method to estimate parameters of probability distribution of overall survival time. Moreover, two Weibull models are used to compare th e two surgery techniques. Mean survival times assigned to particular types of operation are compared. Briš Radim,Praks Pavel, Janurova Katerina, Martinek Lubomir Survival analysis on data of different surgery tech niques to evaluate risk of postoperative complicati ons 34 operative course of treatment. Laparoscopic colectomy for cancer is minimally equivalent alternative to open operation in the treatment of cancer of colon. Concerning the cancer of rectum cancer much less information is available. Meta-analyses comparing laparoscopic versus open surgery for rectal cancer are very rare and in fact they are mostly connected with short term results. Laparoscopic surgery for rectal cancer is still open problem in recent time and especially analysis of long term outcomes are eager ly awaited. 2. Non-parametric approach 2.1. Life distribution, basic relations If failure (lifetime or survival time in medical applications [3]) distribution function F has a density f, the failure rate function (hazard function) λ(t) is defined for those values of t or which F(t) < 1 by: ) ( ) ( ) ( 1 ) ( ) ( t R t f t F t f t = − = λ , (1) where R(t) = 1F(t) is survival function. Knowing failure rate λ(t), the survival function R(t) can be easy derived as: ( )     ∫ − = t dx x t R 0 exp ) ( λ (2) and, knowing survival function R(t), the mean survival time MST (or mean life) and standard error SE of the survival time can be derived as follows:
Translating telecinematic texts Linguistic and Cultural Representation in Audiovisual Translation Voicing difference? The role of voice-over in negotiating identity in non-fiction BBC broadcasting across Italian/English lingua-cultures

Introduction Gieve and Norton (2007, 2010) have argued that the linguistic representation of “foreigners” in non-fiction British broadcasting has considerable “ideological impact on the discursive construction of identity, and cross-cultural relationships” (2010, p. 208). According to the authors, linguistic difference in documentary, travel and lifestyle television genres is flattened or even erased. Consequently, communication between speakers of different languages is routinely portrayed as "smooth, unproblematic, and everyday” (Gieve and Norton, 2010, p. 206). The reconstructed reality (Orero, 2006, p. 2) inherent in these genres is achieved through transfer modes such as voice-over translation, revoicing, narration, and simultaneous interpreting, which in turn give rise to "the peculiar situation of two people apparently speaking to each other in different languages” (Gieve and Norton, 2007, p. 200). Voice-over is also used to convey meaning in translation-mediated audiovisual news products; in particular, foreign politician's speeches, and interviews (Darwish, 2003, 2006; Darwich and Orero, 2014). These are discursive fields in which the translation process is susceptible to ideological manipulation (Diaz-Cintas 2012) that could provoke wide-ranging and possibly disastrous consequences. Despite such potential to create or subvert meaning, voice-over techniques remain mainly unchartered forms of audiovisual translation (Orero 2004, p 76; Franco et al 2010, p. 14). However, as an increasingly widespread mode of disseminating information on cultural and linguistic otherness in non-fiction TV genres and in relaying information regarding overseas news, a systematic investigation into voice-over translation in all its guises is long overdue.
The Influence of the Proctoring System on the Results of Online Tests in the Conditions of Distance Learning

Covid-19 has made significant adjustments to all spheres of Kazalchstan's society, the education sector was no exception, and therefore all educational organizations were forced to urgently activate distance learning. Of course, organizations of higher and postgraduate education used a distance learning format before the pandemic. Kazakh schools experienced difficulties with the distance learning format. One of the problems of distance education is that academic honesty in relation to online tests is dangerous because of deception, which artificially gives a high score. To solve these problems, an online proctoring system was used, designed to eliminate and prevent academic dishonesty. The purpose of this study was to compare the results of online tests with proctoring and online tests without proctoring. The test results of 220 students studying in different groups of the online course were compared using linear models of mixed effects, some students did not use a proctoring system, and the rest were forced to use online proctoring software. Students scored an average of 11 points less and spent less time on online tests that used proctoring software compared to tests without a proctoring system. A significant difference in grades and different use of time was in different exams, both for sections of the same course, and in the fact that some students used software for testing, while others were absent. The necessity of introducing the use of a proctoring program for online learning and distance education is justified. The necessity of using innovative tools in the field of education, in particular in online learning, is actualized. The introduction of proctoring systems increases the reliability of the assessment of educational results in the online mode. It is necessary to further develop the capabilities of proctoring technology and its wide implementation in all universities of the country. The use of this software system will allow educational organizations to improve the quality of the results of distance education provided.
Deep-DFT: A Physics-ML Hybrid Approach to Predict Molecular Energy using Transformer

Computing the energy of molecules plays a critical role for molecule design. Classical ab-initio methods using Density Functional Theory (DFT) often suffers from scalability issues due to its extreme computing cost. A growing number of data-driven neural-net-based DFT surrogate models have been proposed to address this challenge. After trained on the ab-initio reference data, these models signiﬁcantly accelerate the energy prediction of molecular systems, circumventing numerically solving the Schrödinger equation. However, the performance of these models is often limited to the scope within the training data distribution. It is also challenging to discover physical insights from their prediction due to the lack of interpretability of neural networks. In this paper, we aim to design a physics-ML hybrid DFT surrogate model, which is physically interpretable as well as generalizable to beyond the training data distribution. To achieve these goals, we propose a physics-driven approach to ﬁt the energy to an equation combining Coulomb and Lennard-Jones potentials by ﬁrst predicting their sub-parameters, then computing the energy product by the equation. Our experimental results show the effectiveness of the proposed approach in its performance, generalizability, and interpretability.
ALZHEIMER’S DISEASE CLASSIFICATION

When using deep neural networks to separate Alzheimer’s disease patients (n=119) from normal controls (n=131) by using MR images, heat mapping revealed that the image preprocessing is introducing misleading features used by the classifier. Therefore we systematically investigated the influence of registration and brain extraction on the learned features by heat mapping. Results were compared to a novel relevance-guided training method, focusing on brain tissue. The relevance-guided configurations yielded highest classification accuracies and also confirmed histopathologically relevant regional iron deposition. KeywordsDeep convolutional neural networks, heat mapping, relevance guidance, Alzheimer’s disease
Biosorption Analysis and Penoxsulam Herbicide Removal Efficiency by Transgenic Chlamydomonas reinhardtii Overexpression the Cyanobacterial Enzyme Glutathione-s- transferase

Penoxsulam, a new post-emergent rice herbicide, is widely used in rice fields in Egypt. Penoxsulam has been shown to have adverse effects on plant growth; hence, it prevents plants from producing an important enzyme, acetolactate synthase. Glutathione-s-transferase (GST) plays a vital role in the detoxification of xenobiotics including Herbicides. Geneticallyengineered algae can provide feasible and environmentally safe approaches for the phycoremediation of herbicides. In the current study, Cyanobacterial GST was transferred to Chlamydomonas reinhardtii, a model unicellular alga, via the Agrobacterium tumefaciens-mediated transformation method. The GST enzyme activity was confirmed in three transgenic C. reinhardtii lines. To evaluate the removal capacity of penoxsulam by transgenic C. reinhardtii, the microalgae were treated with penoxsulam at 5, 10, and 20 μg ml-1 for twenty-four hours. The percentage of the herbicide removal from 5 and 20 μg ml-1 reached maximally 93.6 % and 54 % in the case of transgenic alga, whereas in the case of the wild type, the percentage of removal reached 52 % and 21 %, respectively. Langmuir and Freundlich adsorption isotherm models and the sorption kinetics have been applied to the experimental data to check the effectiveness of the removal process. The equilibrium data were well-fitted with the Langmuir isotherm model. The results showed that GST transgenic microalgae are effective in the removal of penoxsulam from aqueous solutions and it can be used in phycoremediation systems of herbicides.
Determination of cytotoxicity of germicides and disinfectants on the culture of kidney cells of a calf

Goal. To study the cytotoxicity of certain antibacterial preparations used in the treatment of infectious diseases of the urinary system, as well as some disinfectants for calf kidney cell culture. Methods. Cytological, toxic effects test on primary calf kidney cell culture. Determination of the maximum permissible concentrations of antibiotics, antiseptics, and disinfectants that do not yet lead to degeneration of the cell monolayer of calf kidney cells. Results. Tests of some drugs that are often used in veterinary medicine show that the least toxic to calf kidney cells of all tested antibacterial agents are Oxymicol 20 (active substance — oxytetracycline base), Norsulfazole sodium, and Farmazin 50 (active substance — tylosin). Conclusions. These drugs or similar with the same active substances should be used in the treatment of infectious diseases of the kidney and urinary system of cattle and other animals. The possibility of using the method of cultivation and use as test objects of primary cultures of eukaryotic cells in the selection of the optimal composition of therapeutic and prophylactic drugs or disinfectants for veterinary medicine. The obtained results of cytotoxicity can help veterinarians in choosing antimicrobials and disinfectants in terms of their wide range on the market.
BI/ANALYTICS STRATEGY CONCEPTUAL FRAMEWORK: DEVELOPING AN ENTERPRISE-WIDE BI/ANALYTICS STRATEGY

Industry 4.0 is a term that defines changes in society, industry and technology that are related to the digitization of industry, automation, processing and exchange of unlimited data and modern production techniques. This concept in literature is often used alternately with terms such as The Fourth Industrial Revolution or Industry 4.0. and is largely based on a greater involvement of intelligent systems and robots in all sorts of sectors that are able to work longer and more efficiently than humans. The current pace of change and its impact on society is a challenge that humanity has not yet had the opportunity to face. It is precisely this pace of change, and the large-scale digitization, automation and robotization of all aspects of economic and social life, that imposes the obligation to constantly seek and develop the necessary competences during revolutionary changes.
Improving Hospitality Education Quality with the Concept of Stakeholder Management

Education and business should no longer be seen as two distinct worlds. In fact, the education service can be viewed as a network of exchanges built up by inter-relations and interdependence between a number of stakeholders. Take the newly launched hospitality education in Taiwan as an example; it is a subject for educating professional knowledge and skills to work in the hospitality industry. The quality of hospitality education is affected by students' learning motivations, teachers' teaching competency and the industry's supports such as offering internship and employment opportunities and assisting the curriculum design and so on. Therefore, the concepts learned from the business sector in regard to satisfying needs and wants of stakeholders can be of use in the improvement of education quality. To improve quality in hospitality education strategically, this paper introduces the key elements of quality management: identifying stakeholders; analyzing the 'gaps' between stakeholders' perceptions and expectations; managing the relationships with stakeholders. It is believed that the driving force behind quality in hospitality education lies in the commitment of those who have influence on the curriculum design and curriculum delivery. Therefore, the hospitality institution should aim to improve the quality of its own relationships with the stakeholders. In regard to ways to establish positive relationships between stakeholders, this paper also proposes some suggestions in the end of the paper. Although hospitality education has been selected as the focal point in this study, the ideas that emerge in this paper can also be applied to stimulate research on tourism education and other related sectors and education fields.
Precision Agriculture Based on Bayesian Neural Network

Precision agriculture, utilizing various information to manage crop production, has become the important approach to imitate the food supply problem around the world. Accurate prediction of crop yield is the main task of precision agri-culture. With the help of neural networks, precision agriculture has progressed rapidly in past decades. However, neural networks are notoriously data-hungry and data collection in agriculture is expensive and time-consuming. Bayesian neural network, extending the neural network with Bayes inference, is useful under such circumstance. Moreover, Bayesian allows to estimate uncertainty associated with prediction which makes the result more reliable. In this paper, a Bayesian neural network was applied a small dataset and the result shows Bayesian neural network is more reliable under such circumstance.
RELATIONSHIP BETWEEN TYPE III SECRETION TOXINS, BIOFILM FORMATION, AND ANTIBIOTIC RESISTANCE IN CLINICAL PSEUDOMONAS AERUGINOSA ISOLATES

Background and aim. Pseudomonas aeruginosa is considered as a notorious pathogen due to its multidrug resistance and life threatening infections. We investigated the relationship between type III secretion toxins, biofilm formation, and antibiotic resistance among clinical P. aeruginosa isolates. Methods. A total of 70 genetically distinct clinical P. aeruginosa isolates were characterized for antibiotic resistance by disk diffusion assay. Biofilm formation was evaluated by microtiter plate method and presence of four exo genes (exoS, exoU, exoT and exoY) was investigated by PCR. A p-value < 0.05 was regarded statistically significant. Results. The most effective antibiotics were Meropenem and Piperacillin. Multidrug resistance was more prevalent in the ciprofloxacin-resistant isolates than in the susceptible isolates. The most frequently identified exo was exoS (37.1%). Genotype exoS/exoT was found in 4 isolates, while genotype exoU/exoT was not found. Prevalence of exoS was generally higher in the susceptible isolates than in the resistant isolates. A significant association was found between the formation of strong biofilm and resistance to antibiotics (p < 0.05). Prevalence of exoY and exoU was higher in the non-strong biofilm producers compared to the strong biofilm producers. Conclusion. Our study revealed formation of strong biofilm along with antibiotic resistance and the presence of exo genes in P. aeruginosa isolates. Knowledge of virulence gene profiles and biofilm formation may be useful in deciding appropriate treatment.
Classification of Waste for Efficient Disposal & Recycling using Deep Learning

- Garbage waste generation and accumulation are increasing at a very fast rate. Treating this waste for proper disposal and recycling has become an important topic. The recycling of waste must be done in a very efficient manner. The aim of this paper is to automate the recyclable waste classification just from their images. The recyclable categories are – metal, paper, plastic and glass. The algorithm for classification of waste used is Faster R-CNN with tensor flow. For classification, it takes the image of the trash objects and provides valid boundaries over the objects based on the recyclable waste categories used. The boundaries comprise of various color boundaries based on the categories for recycling process. The hardware implementation includes real time images being taken and given as an input to the trained model. However, in this paper our focus will be to make multiple types of trash getting recognized through the deep learning process.
SOLAR PV AND BATTERY STORAGE INTEGRATION USING THREE-LEVEL NPC INVERTER

In this paper, a configuration of a three-level neutral point clamped (NPC) inverter that can integrate solar PV with battery storage in a gridconnected system is proposed. This paper illustrates the design of three-port dc–dc converter for stand-alone PV systems based on an improved Flyback-Forward topology. It provides a compact single-unit solution with a combined feature of optimized maximum power point tracking (MPPT), high step-up ratio, galvanic isolation, and multiple operating modes for domestic and aerospace applications.
Sea ice trends in climate models only accurate in runs with biased global warming

Observations indicate that the Arctic sea ice cover is rapidly retreating while the Antarctic sea ice cover is steadily expanding. State-of-the-art climate models, by contrast, typically simulate a moderate decrease in both the Arctic and Antarctic sea ice covers. However, in each hemisphere there is a small subset of model simulations that have sea ice trends similar to the observations. Based on this, a number of recent studies have suggested that the models are consistent with the observations in each hemisphere when simulated internal climate variability is taken into account. Here we examine sea ice changes during 1979-2013 in simulations from the most recent Coupled Model Intercomparison Project (CMIP5) as well as the Community Earth System Model Large Ensemble (CESM-LE), drawing on previous work that found a close relationship in climate models between global-mean surface temperature and sea ice extent. We find that all of the simulations with 1979-2013 Arctic sea ice retreat as fast as observed have considerably more global warming than observations during this time period. Using two separate methods to estimate the sea ice retreat that would occur under the observed level of global warming in each simulation in both ensembles, we find that simulated Arctic sea ice retreat as fast as observed would occur less than 1% of the time. This implies that the models are not consistent with the observations. In the Antarctic, we find that simulated sea ice expansion as fast as observed typically corresponds with too little global warming, although these results are more equivocal. We show that because of this, the simulations do not capture the observed asymmetry between Arctic and Antarctic sea ice trends. This suggests that the models may be getting the right sea ice trends for the wrong reasons in both polar regions.
Antioxidant and LC-QToF-MS / MS analysis of polyphenols in polar and non-polar extracts from Strobilanthes crispus and Clinacanthus nutans

Strobilanthes crispus and Clinacanthus nutans are popular herbal plants in the Southeast Asian region. The present work was aimed at determining the antioxidant activities and the associated components in the leaf extracts of both species using polar and non-polar solvents namely water, methanol, ethyl acetate, and hexane. The total phenolic content (TPC) and total flavonoid content (TFC) were higher in the leaf extracts of S. crispus as compared to C. nutans. Among the solvents, methanol was the best solvent in extracting the antioxidant components for S. crispus (TPC: 159.85 ± 0.89 mg GAE/g extract and TFC: 955.47 ± 2.66 mg RE/g extract). However, for C. nutans, its methanolic extract yielded the highest TPC (36.39 ± 0.17 mg GAE/g extract), whereas ethyl acetate yielded the highest TFC (229.61 ± 7.81 mg RE/g extract). The high levels of both TPC and TFC contributed to the antioxidant activities of S. crispus extract as reflected in the methanolic extract attaining the highest level of antioxidant activities, measured by ferric reducing antioxidant power (FRAP) (6.84 ± 1.12 mmol Fe2+/g extract), DPPH radical scavenging (IC50: 203.60 ± 7.28 μg/mL), and Trolox equivalent antioxidant capacity (TEAC) (1.01 ± 0.01 mmol TE/g extract) assays. This contrasted with C. nutans which showed lower antioxidant activities owing to its lower TPC and TFC. Correlation analysis revealed significant correlations (p < 0.05, r = 0.915 0.985) between both TPC and TFC in S. crispus and antioxidant activities. However, only TPC of C. nutans showed a significant correlation with FRAP values (r = 0.934). Further tentative identification of the constituents in the extracts using HPLC-ESI-QToF-MS/MS revealed the existence of 20 polyphenolic compounds in both S. crispus and C. nutans, which were likely responsible for their antioxidant activities. In addition, 15 polyphenolic compounds classified as chalcones, isoflavanoids, flavones, and flavonols have not been previously reported in both species. The methanolic extracts of both species yielded a higher content of antioxidants, with S. crispus offering a richer source of dietary antioxidants as compared to C. nutans. However, further study is needed to identify their bioactivities in relation to their bioactive components.