Miracle-dz/UniFAR-FTUs huggingface dataset:
DIFFERENCES IN GENOTYPE OF E. FAECALIS AND E. FAECIUM CLINICAL ISOLATES REGARDING CYTOLYSIN AND GELATINASE PRODUCTION IN BULGARIAN PATIENTS

Purpose - compare the phenotype and genotype correlation of cytolysin and gelatinase production in clinical isolates Enterococcus spp. Materials and methods - 100 Enterococcus strains collected over a period of one year from inpatients of two Bulgarian university hospitals, were tested for phenotype production of cytolysin and gelatinase. Multiplex PCR was performed to screen the presence of gelE and cylA virulence genes. Results – 17% of the enterococcal isolates demonstrated only cytolysin production phenotypically. Gelatinase activity was found in 21% of the isolates. Only E. faecalis showed combined phenotypic production of cytolysin plus gelatinase (21%). Forty-five percent of the tested enterococci were identified negative for both hemolysin and gelatinase activity. GelE was the most prevalent virulent gene (48% of the isolates). CylA gene was present alone only in four non-invasive E. faecalis isolates. Twenty-six percent of the isolates possessed both cylA and gelE genes and 21% did not harbor any of the virulence factors genotypically. Conclusion - our results prove that it is appropriate to perform both phenotypic and genotypic analysis of the enterococci virulence profile in parallel in order to better characterize the strains, which in turn may serve to develop more effective methods to limit the spread of infections caused by these microorganisms.
Retail sales forecasting using LSTM and ARIMA-LSTM: A comparison with traditional econometric models and Artiﬁcial Neural Networks

Aggregate retail sales is an important economic indicator that requires precise understanding and forecasting. This research extends the study of Alon, Qi, and Sadowski (2001), which makes use of three econometric models: Box-Jenkins ARIMA, Winters exponential smoothing, multivariate regression, and an Artiﬁcial Neural Network, to forecast retail sales in the US in two periods of time. The extension considers two additional methods: LSTM and ARIMA-LSTM and an additional extended period. The forecasting performances of the models are hence compared in three diﬀerent scenarios. Overall, the results of the study are mixed with evidence that ARIMA and Winters models are the most consistent, while LSTM and ARIMA-LSTM have high accuracy in certain cases, such as in the extended period. The views stated in this thesis are those of the author and not necessarily those of the supervisor, second assessor, Erasmus School of Economics or Erasmus University Rotterdam.
Diaphragmatic ultrasound as a predictor of successful extubation from mechanical ventilation in elderly patients

Background: Although mechanical ventilation (MV) is life-saving in a patient with acute respiratory distress which is more prevalent in the elderly age group, it is also one of the most important causes of diaphragmatic dysfunction and thus MV weaning failure. Diaphragmatic function assessment has a crucial role in the assessment of the weaning outcome. Bedside diaphragmatic ultrasound (US) has an important role in the assessment of diaphragmatic thickness and function with recently used multifunction indices such as diaphragmatic excursion and velocity. Aim:We aim to evaluate the role of ultrasonographic function indices of the diaphragm in the weaning of mechanically ventilated elderly ICU patients and study the relationship between the ultrasonographic indices, time for mechanical ventilation and weaning time. Results: Bedside diaphragmatic ultrasonographic examination was performed on 60 patients Aged ≥ 70 years old, who were intubated, mechanically ventilated in ICU. The percentage of patients with Diaphragmatic dysfunction (DD) compared to nondiaphragmatic dysfunction (non-DD) was 3:1. The percentage of weaning success was higher in the non-DD group than the DD group (76.9% and 28.9% respectively). Diaphragmatic function indices had statistical significance in differentiating both DD and non-DD groups. The cutoff value for diaphragmatic thickness, excursion and velocity was about (10mm&10mm, 13mm&12mm and 16&15mm/s) with area under the curve (0.891&0.771, 0.794&0.771 and 0.692&0.71) on the right and left sides respectively. Conclusion: Bedside diaphragmatic ultrasound including multifunction indices has an important role in detecting diaphragmatic dysfunction and thus weaning failure as well as the duration of the mechanical ventilation negatively correlated with the sonographic Turkish Journal of Physiotherapy and Rehabilitation; 32(3) ISSN 2651-4451 | e-ISSN 2651-446X www.turkjphysiotherrehabil. org 13639 indices in elderly patients intubated and mechanically ventilated more than 48 hours in ICU.
An agent-based model of strategic adoption of real-time payments

Real-time payments (RTPs) allow consumers to receive funds before the completion of payment clearing and settlement. This early, irrevocable release of funds represents a credit risk to banks in the event there are issues with the payment, such as the consumer's deposit holdings being insufficient to cover the payment they are sending. We investigate the effects such risks may have on the strategic adoption of RTPs by banks. We define a network game in which consumer nodes with deposit holdings are assigned to bank nodes responsible for routing consumer payments within the network. Bank nodes make a strategic decision regarding which consumers may send RTPs in the network by selecting from a set of available strategies based on the initial deposits of the consumers. Using agent-based modeling and empirical game-theoretic analysis, we analyze this strategic decision in various game configurations. Our results show that bank nodes tend to choose strategies that allow many, but not all, consumer nodes to send RTPs. We find that this outcome in strategic equilibrium reduces successful payments and increases the incidence of insufficient funds availability, compared to a setting where RTPs are universally enabled. This manifests in our model because RTP enables receivers of payments to turn around those funds more quickly to make payments of their own. As a result, banks are better off when all payments are realtime, but a strategic bank node is inclined to avoid the liability of allowing its own depositors to use RTPs when the risk is considered high.
Master Computer Science Dynamic Conﬁguration of Operators and Parameters in Diﬀerential Evolution through Combined Fitness and Diversity-Driven Adaptation Methods

The widespread success of metaheuristics can be partially credited to the developments in the realm of hyper-heuristics, where the automation of the otherwise manual, problem-speciﬁc tuning of a metaheuristic is studied. While some hyper-heuristics tune the algorithm prior to its application, they can also be leveraged to adapt the algorithm’s behavior during the optimization process, in response to changes in the environment. The metaheuristic known as Diﬀerential Evolution (DE) has endured many modiﬁcations aiming to adaptively control its parameters, and more recently, to adaptively select the operators employed to generate new candidate solutions. Most such methods greedily select strategies that give the most rapid improvements with regard to the objective function, risking convergence on a local optimum. This thesis sets up a framework for intertwined adaptation of operators and parameters for population-based metaheuristics, where the adaptation process addresses the exploration/exploitation dilemma by explicitly encouraging exploratory behavior. In detail, we devise diversity-based metrics that capture the exploratory or exploitative tendency of a single individual, which can then be used to reward or penalize its associated strategy. Several methods for balancing the ﬁtness-and diversity-based metrics are considered, as well as diﬀerent methods that determine which operators are applied in future iterations. Through an extensive tuning process, seven adaptive DE algorithms are obtained, which are then benchmarked on BBOB/COCO to assess their empirical performances, and analyzed with regard to several aspects of the algorithmic behavior. Further, we perform an elaborate experiment to assess the optimal composition of the conﬁguration space, which holds the operator conﬁgurations available to the hyper-heuristic. The results show the eﬃciency of the joint parameter and operator adaptation, driven by both ﬁtness-and diversity-related metrics, making DE more versatile across diﬀerent problem types. In addition, we provide practical recommendations regarding the composition of the conﬁguration space.
Identification of Alien Chromosome/Chromatin Introgressions in Triticale × Wheat Derived Stable Lines Through Molecular Cytogenetic Analysis

Jeberson, M. S. , Chaudhary, H. K. , Chahota, R. K. , & Ashokkumar, K. (2021). Identification of Alien Chromosome/Chromatin Introgressions in Triticale × Wheat Derived Stable Lines Through Molecular Cytogenetic Analysis. Journal of Current Opinion in Crop Science, 2(1), 1-10. Molecular cytogenetic study was conducted for identifying rye chromosome/chromatin translocation, substitution and addition in 43 triticale x wheat derived stable lines (BC1F7 and F7 generations) six different crosses using FISH (Fluorescence in situ hybridization) and GISH (Genomic in situ hybridization) analyses with different probes. Rye chromosomes/chromatin was identified in 17 BC1F7 and 12 F7 lines by these two analyses. The GISH and FISH techniques worked satisfactorily for identifying the presence of rye chromatin at metaphase. All the lines were associated with alien chromosome translocation, addition or substitution except a few lines. Most of the recombinants present in TW 1, TW 2 and TW 6 crosses were observed to be associated with important alien chromatin translocation like 1BL/1RS, substitutions 1R (1D), 5R (5D) and combination of both i.e., 1BL/1RS + 5R (5D) and in some cases presence of more than 4 rye chromosomes. The crosses TW 3 and TW 5 possessed 8 to 14 rye chromosomes in their chromosome constitution. So, their morphological expression was similar to triticale. These reconstituted lines will be of immense application for the future wheat breeding programmes.
Master Computer Science Predicting Successful Sequences in Soccer using Boosted LSTM Networks

Soccer match data is becoming widely available, and as a result, new methods to quantify team positioning are found. These methods could potentially be used as features in prediction models to rate players or to ﬁnd better tactics. However, most methods have seen limited validation of their eﬀectiveness in prediction models. In this thesis, we use a large library of existing spatial features to identify dangerous ball possessions. Some of these features are sparse, and were previously unusable in our models. We show that using NaN-ﬁlling, we can successfully introduce sparse features to increase performance of diﬀerent classiﬁcation models, including (boosted) LSTMs. We also show that our models are at least capable of comprehending simple indicators for danger. Lastly, we present the best performance of our models, which shows that boosting can improve performance. The LSTMs did not outperform our baseline methods in the current setups, but we show that they could have the potential to become better in the future.
Interpolation and Extrapolation of Subsequent Weather Radar Images

Recent advancement in the communication technologies creates an opportunity for the effective use of nowcasting – predicting the weather over short periods and communicating the predictions to the public in real time. Current nowcasting systems using weather radar images in the Czech Republic are built on traditional algorithms and numerical weather models. The objective of this work is to research the possibilities of using neural networks for processing of weather radar image sequences as an enhancement to the existing nowcasting methods. I propose and test a convolutional neural network as a solution for two tasks – interpolation and extrapolation of a sequence of weather radar images. In both tasks, the proposed network achieves promising results. Quantitative comparison of my network and the currently used method COTREC ended in favour of the proposed network. The qualitative evaluation shows multiple benefits of my solution – the ability to capture the change of the radar echo intensity and shape. The results of this work create space for deeper research in this field.
ANALYSIS OF BACTERIAL DIVERSITY IN RAW FISH CEVICHE

Ceviche is a traditional dish made from raw fish meat marinated in lime juice without any heat cooking step throughout its preparation process. Although the use of organic acids as antibacterial agents is well known; recent research indicates that lime juice actually can reduce the risk of V. parahemolyticus infections but it is ineffective against other potential pathogens. Despite the fact that fresh fish meat is safe; exposed organs including skin, gills and guts represent a potential source of bacterial contamination. In Mexico, diarrheal diseases are caused mainly by contaminated food; it is estimated that almost 67% of infections are due the presence of bacterial agents mainly in frozen and fresh fish. The main objective of this study was to estimate the taxonomic diversity of microbial species present in ready-to-eat ceviche using a metagenomic approach. Six samples of commercially available ceviche were subjected to DNA high throughput sequencing and bioinformatics analyses, we identified between 65,000 and 131,000 reads per sample. The predominant phyla identified through the samples were Proteobacteria, Bacteroidetes and Firmicutes. We discuss the factors involved in the microbiological quality of this kind of raw foods and how they influence the bacterial diversity within the analyzed samples.
Labour Mobility With Vocational Skill: Australian Demand and Pacific Supply

Can new channels for mid‐skill labour mobility simultaneously enhance the welfare of Australia and the Pacific Region? Answering this question requires forecasting Australian demand for vocationally‐skilled migrants over the next generation, and the potential for Pacific supply of those migrants. We project demand for such mid‐skill migrants over the next three decades by combining data on trends in the demand for basic tasks with data on trends in native investment in education commensurate with those tasks. We estimate that the Australian economy growing at historical rates through the year 2050 will demand approximately 1.6–2.1 million foreign workers with Technical and Vocational Education and Training. A large share of these could be supplied from the Pacific Islands with sufficient investment in training, with direct cooperation from Australian employers, and targeted access to the Australian labour market.
Forecasting Residential Electricity Load Demand using Machine Learning

Since the emergence of diﬀerent forms of sophisticated home appliances and smart home devices globally, the demand for residential energy is rapidly growing. This growing demand has led to create energy sustainability issues, which have been identiﬁed as one of the major concerns in the recent times as more consumers need more energy. Therefore, the forecasting of demand for electricity plays a crucial role in maintaining an equilibrium between the consumers demand and energy generated by the energy producing companies. In recent years, numerous machine learning algorithms have been employed to forecast the consumers electricity load demand. This study has been carried out as a comparative analysis of four diﬀer-ent machine learning algorithms, Autoregressive Integrated Moving Average with Explanatory Variable (ARIMAX), Seasonal Autoregressive Integrated Moving Average with Explanatory Variable (SARIMAX), PROPHET and Long-Short Term Memory (LSTM) for a group of residential customer present at London. It is observed that the eﬃciency of the LSTM model is considerably greater than all the other implemented models.
Dynamic Price-Enabled Strategic Energy Management Scheme in Cloud-Enabled Smart Grid

In this work, the problem of high-quality energy service provisioning in the presence of competitive prosumers and micro-grids in cloud-enabled smart grid is studied. Oligopolistic prosumers behave non-cooperatively and store the excess generated energy for future use, which increases the load on the main grid and degrades the performance of the smart grid. To address this issue, we propose a dynamic cloud-based pricing scheme, named SmartPrice, to enforce cooperation among the prosumers for ensuring high quality of service provided by the micro-grids. In SmartPrice, using cloud infrastructure, each micro-grid calculates a reward factor for each prosumer based on his/her behavior to enforce cooperation among them. We model the interaction between each micro-grid and the prosumers using a single-leader-multiple-followers Stackelberg game, where the micro-grids and the prosumers act as the leaders and the followers, respectively. Each micro-grid determines the unit energy price to be charged/paid and each prosumer determines the quantity of excess energy to be supplied for ensuring high revenue. Thus, SmartPrice enforces cooperation among the micro-grids and prosumers. Additionally, using SmartPrice, the price for unit energy charged from the prosumers reduces by 23.37-<inline-formula><tex-math notation="LaTeX">$35.63\%$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>35</mml:mn><mml:mo>. </mml:mo><mml:mn>63</mml:mn><mml:mo>%</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="misra-ieq1-3118637.gif"/></alternatives></inline-formula>, thereby ensuring high revenue and the number of prosumers served by the micro-grids increases by 38.19-<inline-formula><tex-math notation="LaTeX">$53.14\%$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>53</mml:mn><mml:mo>. </mml:mo><mml:mn>14</mml:mn><mml:mo>%</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="misra-ieq2-3118637.gif"/></alternatives></inline-formula>.
Analysis of the Influence of Upper Protective Layer Mining on the Effect of Pressure Relief and Protection of Coal and Rock Masses between the Lower Overburden Layers

Protective seam mining is an effective gas pressure relief method in deep mining. Effective theoretical calculation methods in the current studies on the prediction of pressure relief protection effect of interbed coal and rock masses and their distribution laws are lacking. Thus, the evaluation and research with respect to pressure relief effect in protective seam mining relatively lag behind. This situation restricts the engineering feasibility evaluation and decision making in the protective seam mining. Therefore, the influence of upper protective seam mining on the pressure relief protection effect of coal and rock mass between underlying beds was investigated in this study. On the basis of an analysis of concrete engineering projects, a mechanical model was constructed for the pressure relief protection effect of upper protective seam mining on the coal and rock mass between underlying beds. The distribution equation of pressure relief expansion ratio in the underlying protected seam was also derived. The influence laws of main influencing factors on the pressure relief protection effect of the protected seam were revealed as well. In the end, the pressure relief effect was analyzed and verified for the protected seam before and after mining through numerical simulation and similarity simulation test. The pressure relief effect of upper protective seam mining on the coal and rock mass between underlying beds and the distribution characteristics were deeply explored in this study, which could provide a theoretical reference for the decision making in the gas extraction engineering design and pre-evaluation of extraction effect. Results show that the effective pressure relief zone (expansion rate>0.3%) of the protected seam beneath the goaf is located within the range of approximately 40 m from the coal wall to the rear part. It also presents an approximate “Λ-shaped distribution characteristic,” that is, it experiences migration and evolution with the advancement in the working face. Moreover, the peak pressure relief lags behind the coal wall on the working face by nearly 10–20 m. In the numerical simulation, the expansion ratio in the goaf also presents an approximate “Λ-shaped distribution. ” Its effective pressure relief zone is the 50 m range from the coal wall to the rear part of the goaf, and the peak value lags behind the coal wall by around 15 m. The theoretical results and numerical simulation results are basically consistent with the physical experiment results. The expansion rates are 1.25%, 1.268%, and 1.32%, respectively. The elastic modulus E of coal seam and interbed spacing H are the main influencing factors of the swelling deformation and are negatively correlated with the expansion ratio. In the actual mining process, E and H of the protected layer can be measured to infer the expansion deformation of the protected layer.
Assessing the Relationship among the Land Surface Features: A Geographic Information System (GIS) and Remote Sensing (RS) Based Approach for City Area

Due to climate change and urbanization, it is important to monitor and evaluate the components of the environment. For this reason, ward-22 and ward-27 of the Khulna City Corporation (KCC) area have been selected for the study. This research seeks to identify the existing land use profile and assess the land surface components such as topography, Normalized Difference Buildup Index (NDBI), Normalized Difference Vegetation Index (NDVI), Normalized Difference Moisture Index (NDMI), Normalized Difference Salinity Index (NDSI) and Land Surface Temperature (LST) to measure the relationships among the land surface components. The land use land cover map shows that about 59% of ward-22 and 71.5% area of ward-27 are built-up areas. Both of the wards contain little amount of water body, vegetation and open space. Both of the wards have residential land use types with commercial purposes on the periphery. Accordingly, 63.32% and 65% of structures of ward-22 and 27 are pucca. The land surface components reveal that both areas contain lower slopes, less vegetation, less moisture, severe salinity, highly built-up areas, and high land surface temperature. The relationships among the land surface components show that NDVI has a negative relation with LST and NDBI whereas NDVI represents a positive correlation with NDMI. On the other hand, NDBI shows a positive correlation with LST whereas NDMI negatively correlates with LST. NDSI and topography reflect no meaningful relationship between NDBI, NDVI, LST, and NDMI. However, the research findings may be essential to city planners and decision-makers for incorporating better urban management at the micro level concerning climate change.
Synthesis, Crystal Structure of a New Na (I) Complex with 4-Benzoylbenzoic Acid-p-Aminobenzene Sulfonic Acid

A novel sodium complex, [NaL·(H2O)2]n, was synthesized by reflux reaction of p-amino benzene sulfonic acid, 4-benzoylbenzoic acid and NaOH in ethanol/water solution and structurally characterized by elemental analysis, IR spectrum and X-ray single crystal diffraction analysis. The crystal of the complex belongs to monoclinic, space group P21/c with a = 19.403(4) Å, b = 8.0083(16) Å, c = 10.532(2) Å, β = 103.22(3)°, V = 1593.15(60) Å3, Z = 4, Dc = 1.621 mg·m−3, μ = 1.590 mm−1, F (000) = 1576, and final R1 = 0.1204, ωR2 = 0.2951. The complex molecules form a 1D chain structure by the new ligand. The 1D chains generate a 2D layer structur through the intermolecular hydrogen bonds and the connection of sodium ions. And the 2D layers form 3D supramolecular architecture structure by the hydrogen-bond interaction.