Miracle-dz/UniFAR-FTUs huggingface dataset:
ANTIMICROBIAL SUSCEPTIBILITY PATTERN OF STAPHYLOCOCCUS AUREUS STRAINS IN ISLAMABAD, PAKISTAN

Objective: To investigate the prevalence of S. aureus in hospitalized patients of Islamabad. Study Design: Cross-sectional study. Study Duration: Pakistan Institute of Medical Science, Applied Microbiology and Biotechnology Lab, COMSATS Institute of Information Technology, Islamabad, from Sep 2017 to Sep 2018. Methodology: A total of 500 samples were collected. The isolates were divided into four study groups according to their source of origin i.e. group 1 (dermal group), group 2 (nasal group), group 3 (blood group) and group 4 (urine group). Gram staining, catalase test and DNA se media analysis were done for validation of S. aureus. Disc diffusion test (for antibiotic susceptibility), Oxacillin disc test (to differentiate between methicillin-resistant Staphylococcus aureus and methicillin-susceptible staphylococcus aureus) and minimal inhibitory concentration (for susceptibility to vancomycin), were performed. Results: Degree of the prevalence of staphylococcus aureus was 21%, 17%, 9% and 8% in group 1, 2, 3 & 4 respectively. The overall prevalence of staphylococcus aureus was 19.5% in all isolates. The disc diffusion test showed the descending resistance pattern of isolates i.e. 100, 94, 94, 76, 58, 55, 47, 43, 40 and 37% for penicillin, ciprofloxacin, Kanamycin, erythromycin, tetracycline, oxazolidinone, sulfamethoxazole, doxycycline, clindamycin, and cipoxin respectively. Minimal inhibitory concentration found only one sample resistant at 2ug/l concentration of Vancomycin. Moreover, Oxacillin disc test showed 52% methicillin-susceptibleStaphylococcus aureus while 48.2% methicillin-resistant staphylococcus aureus among all isolates. Conclusion: There is an increase in the frequency of methicillin-resistant staphylococcus aureus. Single vancomycin resistant staphylococcus aureus strain was also isolated.
VARIATIONAL ENSEMBLE KALMAN FILTERING USING LIMITED MEMORY BFGS

The extended Kalman ﬁlter (EKF) is one of the most used nonlinear state estimation methods. However, in large-scale problems, the CPU and memory requirements of EKF are prohibitively large. Recently, Auvinen et al. proposed a promising approximation to EKF called the variational Kalman ﬁlter (VKF). The implementation of VKF requires the tangent linear and adjoint codes for propagating error covariances in time. However, the trouble of building the codes can be circumvented by using ensemble ﬁltering techniques, where an ensemble of states is propagated in time using the full nonlinear model, and the statistical information needed in EKF formulas is estimated from the ensemble. In this paper, we show how the VKF ideas can be used in the ensemble ﬁltering context. Following VKF, we obtain the state estimate and its covariance by solving a minimization problem using the limited memory Broyden-Fletcher-Goldfarb-Shanno (LBFGS) method, which provides low-storage approximations to the state covariances. The resulting hybrid method, the variational ensemble Kalman ﬁlter (VEnKF), has several attractive features compared to existing ensemble methods. The model error and observation error covariances can be inserted directly into the minimization problem instead of randomly perturbing model states and observations as in the standard ensemble Kalman ﬁlter. New ensembles can be directly generated from the LBFGS covariance approximation without the need of a square root (Cholesky) matrix decomposition. The frequent resampling from the full state space circumvents the problem of ensemble in-breeding frequently associated with ensemble ﬁlters. Numerical examples are used to show that the proposed approach performs better than the standard ensemble Kalman ﬁlter, especially when the ensemble size is small.
Prevalence of Eimeria spp in buffaloes in Mosul city

لصوملا ةنيدم يف سوماجلا يف ايريميلاا عاونأ راشتنا ةسارد ةصلاخلا يليفط راشتنا ىدم ريدقتل ةيلاحلا ةساردلا تيرجأ Eimeria spp. لك تلمش لصوملا ةنيدم نم ةفلتخم قطانم يف سوماجلا يف حف حف مينث ةينامنرلا ،ا ،اب، ت،لالالالاشلا، تاباغلا نم 150 نم ةرتفلل زارب ةنيع 2019 ةياغل 2020 ث ة لالالا ن ا ةلالالاساردلا تفلالالاشك ف الالايريمي،ا انجب ةلالايلكلا جمخلاا لب سومالالاجلا ي 38 ي الالايريمي،ا نم واونا ةلالالالالالالالا من يخلالالالالالاشف حف % E.zuerni 18.7% , E.ellipsoidalis 16.7% E.uburnensi 6.7% E.bovis 32% ,E.subspherical 22.7% ة لالا ن نلعا ا ةلالاساردلا ترهظا امك وونلاب تناك جمخلل E.bovis طمن ا , جمخلا لب ذا نلع،ا اك طلتخملا 49.1 % دق لا ة لالالالالا ن تناك خ جم ا يف نيبام ةريغلالالالالاصلا رامع،ا تاذ تاناويحل 1-2 تغلب اذا نلعا ةنلالالالالاس 89.3 يف جمخلا ة لالالالالا نب ةنراقم حفلا ج اتن تنيب امكث نان،ا روك. لا نيب جمخلا ة لالالالالالا ن يف مونيم يرف ما ليجلالالالالالا ف حتي حل نين يف ،ةري كلا رامع،ا تاذ تاناويحلا م ةيلالالالامرم تاريغف ،وج نع يجيلالالالا نلا ،وج نلا ةفالالالالاما اايم،ا ةراهظ يف جلالالالا نف طرف طم ةيللالالالاضيلا فايل،ا نيب همذولا ،وجوب ةلثمت ثةيباهتل،ا ايلاخلا يف حاشفرا يليفطلل ةيروطتلا لنارملا
E LEPHANT HERDING ALGORITHM TO CONFINE THE DISCIPLINE COST OF AIRCRAFT LANDING SCHEDULE

: Flights landing engineering issue are a NP-troublesome issue; this article demonstrates an innate figuring and particle swarm advance mean multi-runway flights landing booking issue. The characteristic count relies on a single chromosome coding and dynamic way flights runway dispersing by then picks the center quality by the information entropy of each quality and usage an accumulation of the zone hunting down a framework to comprehend the move back blending and easy to fall into the close to impeccable of the genetic figuring. Elephant gathering computation is moreover used to smash the stop up occur in the runway what's more this structure is used to reduce the control cost.
Derivation of Patient-specific Alveolar Type II Cells from Surfactant Protein-B Deficient Induced Pluripotent Stem Cells

Surfactant protein B (SFTPB) deficiency is a fatal disease affecting newborn babies. A mutation in the surfactant protein B gene results in the inability to reduce surface tension and ultimately, death. This thesis shows that induced pluripotent stem (iPS) cells derived from patient specific SFTPB deficient fibroblasts can be differentiated into alveolar type II cells using a variety of methods including 2D and 3D culture. The iPS cells are also a target for gene therapy with a lentivirus vector containing the wild type sequence of the SFTPB gene, inserted into both wild type and SFTPB deficient iPS cells. These cells were differentiated into lamellar body containing, surfactant expressing alveolar type II cells and the transfected SFTPB deficient cells showed gene and protein expression of surfactant protein B. These findings suggest that a lethal disease can be targeted and reversed, the first step towards a potential cure for a vulnerable population.
Growth Response of Edamame Soybean (Glycine max (L.) Merr.) with Application of Urea and Rhizobium Biofertilizer on Peat Soil Media

Edamame is a type of soybean that is consumed in an immature period. High demand for market exports, especially to Japan, must be balanced by maximizing production by using marginal lands. One of marginal lands is peatland which might be used as growth media for edamame with Urea and Rhizobium biofertilizer application to support its growth. The recent study aimed to analyze the combination of Urea and Rhizobium biofertilizer on the growth of edamame on peat soil media. The experiment was conducted in Completely Randomized Design (CDR) with two factors. First factor was Urea dosage: p1 = 50 kg ha-1, p2 = 150 kg ha-1, p3 = 100 kg ha-1, and p4 = 200 kg ha-1. The second factor was Rhizobium biofertilizer treatment: r0 = without biofertilizer and r1 = with biofertilizer at 8 g kg-1 edamame seeds. All combination was repeated three times with three polybags of them, so that there were 72 plants in total. The results showed that there was a response between application of Urea and Rhizobium biofertilizer have a significant effect on the observed parameters, that is plant height (cm), number of trifoliate leaves (strand), shoot dry weight (g) and root dry weight (g). The result showed that the application of Urea 50 kg ha-1 with Rhizobium biofertilizer increased plant growth of edamame on peat soil.
Effect of Water Stress on Yield and Seed Quality of Coriander (Coriandrum sativum L.)

Coriander ( Coriandrum sativum L.) is an annual herbaceous plant commonly known as Cilantro or Dhania, belonging to family Apiaceae (Umbelliferae), it is a powerful herb with many health benefits.It is a dual purpose crop grown for its aromatic leaves and cremocarpic seeds, which are extensively used as a spice and food flavouring agent. Plant growth is seriously affected by abiotic stresses and drought is one of the most important limiting factors. Drought stress during earlyreproductive growth stage usually reduces the seed yield and seed quality. To assess the effect of drought stress on seed yield and seed quality of coriander, the experiment was conducted in green house in plastic pots at Dr. Y.S. Parmar University of Horticulture and Forestry, Nauni, Solan (H.P.) during the Rabi season of 2012–13. Coriander cv. Solan Selection was used as a test crop. There were four treatments of Water stress i.e. T 1 -Control,T 2 -25%, T 3 -50%, and T4-75% Water deficit imposed at flower forming phase for 15 days. The treatment s were arranged in a design CRD (Completely Randomized Design) with fourreplications. Data were recorded and results indicated th e significant reduction in plant height stress index, dry matter index, biological yield, number of seeds per plant, harvest index (HI) and yield stability ratio and also observed per cent reduction in 1000- seed we ight ,seed moisture content and germination percentage. On other hand there where per cent increase in solute leakage, mean germination time.
Nocturnal and diurnal pollination in Copaifera coriacea, a dominant species in sand dunes of the Middle São Francisco River Basin, Northeastern Brazil

Background and aims – Copaifera coriacea, a species in the resin-producing clade Detarioideae (Leguminosae), is an endemic and abundant species found in sand dunes in Brazilian Caatinga domain vegetation – a Quaternary paleodesert. We investigated floral traits and aspects of pollination biology, focusing on the pollination system of C. coriacea. Material and methods – Anthesis duration, stigma receptivity, pollen viability, nectar concentration, and the presence of osmophores and pigments reflecting UV light were assessed. Floral visitors were classified as potential pollinators, occasional pollinators or thieves, based on the time and foraging behaviour and resource collected. Pollination effectiveness were assessed for potential pollinators by the detection of pollen tubes on the stigma or stylar canal by epifluorescence microscopy.Key results – The species has white and small flowers, with anthesis beginning in the dark (ca 00:30) and the flowers are completely opened approximately 3 h later, when a sweet odour is perceptible. The onset of stigma receptivity and pollen grain viability occurs only after the completion of flower opening, and a concentrated nectar is available during the day. The presence of pollen tubes confirmed the efficiency of the main insects in the transfer of pollen. Conclusion – Our result demonstrates that C. coriacea has a generalist pollination system mediated mainly by two distinct guilds of insect pollinators: moths (nocturnal, searching for nectar) and bees (diurnal, pollen collectors). This finding can provide more information about diversification in the genus Copaifera.
Advances in Conceptual Ship Design Accounting for the Risk of Environmental Pollution

The present paper provides a thorough analysis of the prerequisites in adopting a new paradigm in the conceptual ship design accounting for the environmental pollution driven by maritime transportations. A survey of presently issued IMO environmental requirements outlines the framework within ship design solutions. Identified and carefully examined are several competing optimal design solutions, based on the energy efficiency design index introduced for shipbuilding, operation cost, and the resale costs at the end of the service life, which are used as input variables in a risk-based analysis. Reviewed are the immediate steps taken in the risk-based conceptual ship design to minimise the risk of environmental pollution while considering the life cycle assessment and energy efficiency of the ship propulsion system. Brought forth in the current paper are the results of a study into the concept design of series of containerships operating in the Black Sea for transporting 20, 40 and 45-foot containers aimed at identifying the main dimensions, capacity, visibility, freeboard, stability, bow, and stern design, propulsion complex and propeller design, control and manoeuvrability, seakeeping, energy efficiency design index, capital, and operational expenditures, that leads to the required fright rate for the ships in the range of 4,000 to 14,000 DWT. Accordingly, a bulk carrier’s risk-based concept ship design methodology is employed for the ship life cycle assessment and energy efficiency in pursuance of the optimal design solution in reference to the energy efficiency design index as most applicable to shipbuilding, operation, and resale costs at the end of the service life, and used as input variables in the risk estimate.
STOCK PRICE PREDICTION USING LSTM AND MARKETS SENTIMENT ANALYSIS

- One of the most important challenges in the world of computation is predicting the stock price. Rational and irrational behavior, the sentiment of investors, market rumors, physical, physiological, and other factors all play a role in the forecast. Many of these factors contribute to making stock markets very unpredictable and impossible to forecast accurately. We investigate data analysis as a game changer in this domain. According to efficient market theory, as all knowledge about a company and stock market practices is automatically available to all stakeholders/market participants, the ramifications of those developments are now rooted in the stock price. As a consequence, it is believed that only the previous spot price accurately represents all other market practices and can be used to predict potential movement. As a result, we use Machine Learning (ML) techniques on historical stock market data to infer future patterns, taking the past stock price as the final manifestation of all impacting variables. Deep learning for forecasting stock market prices and patterns has been much more common than ever in the age of big data. In this paper, we introduced a system that predicts the stock prices using LSTM (Long Short-Term Memory) neural network and sentiment analysis using twitter's data. Then, through an in-depth study on how to predict the stock price by the LSTM neural network optimized by ADAM optimizer, the feasibility of the method and the applicability of the model are analyzed, and finally, the conclusion is drawn.
EXPLOITATION OF SPECTRAL AND TEMPORAL INFORMATION FOR MAPPING PLANT SPECIES IN A FORMER INDUSTRIAL SITE

Abstract. Characterization and seasonal (periodic) monitoring of plant species distribution in the context of former industrial activity is crucial to assess long-term anthropogenic footprint on vegetated area. Species discrimination has shown promising results using both HyperSpectral (HS) and MultiSpectral (MS) images. Airborne HS instruments enable high spatial and spectral resolution imagery while time series of satellite MS images provide high temporal resolution and phenological information. This paper aims to compare supervised classification results obtained with non-parametric (Random Forest, RF, Support Vector Machine, SVM) and parametric methods (Regularized Logistic Regression, RLR) applied on both kinds of images acquired on an industrial brownfield. The studied site is a complex vegetated environment due to species diversity: 8 dominant species are retained. The performance obtained by preliminary feature selection based on principal component analysis and vegetation indices, to improve separability of spectral or temporal information according to species, is analysed. The best performance is obtained by RLR method applied on HS data without feature selection (global accuracy of 93 %). Feature selection is found to be a necessary step to perform classification with time series of MS images. Species that are difficult to distinguish from the HS image, namely Salix and Populus, are well separated using Sentinel-2 images (precision around 70%).
UNSUPERVISED OBJECT-BASED CLUSTERING IN SUPPORT OF SUPERVISED POINT-BASED 3D POINT CLOUD CLASSIFICATION

Abstract. The number of approaches available for semantic segmentation of point clouds has grown exponentially in recent years. The availability of numerous annotated datasets has resulted in the emergence of deep learning approaches with increasingly promising outcomes. Even if successful, the implementation of such algorithms requires operators with a high level of expertise, large quantities of annotated data and high-performance computers. On the contrary, the purpose of this study is to develop a fast, light and user-friendly classification approach valid from urban to indoor or heritage scenarios. To this aim, an unsupervised object-based clustering approach is used to assist and improve a feature-based classification approach based on a standard machine learning predictive model. Results achieved over four different large scenarios demonstrate the possibility to develop a reliable, accurate and flexible approach based on a limited number of features and very few annotated data.
What is the Nature And Extent of the Influence of Educational Leadership on Staff Morale, Job Satisfaction, and Motivation?

In a time where retaining qualified teachers is crucial, one cannot ignore the importance of teacher job satisfaction, morale, and motivation in shaping teachers’ intentions to remain in the profession. This is where educational leadership comes into play. This paper looks at the nature and extent of the impact of educational leadership on three important aspects of the job, namely staff morale, job satisfaction, and motivation. The latter constructs are each redefined and reconceptualized as the lack of consensus and the ambiguity in their respective meanings can greatly affect how they are applied as well as their results. When applied to the teaching context, Herzberg’s motivation hygiene theory was found to be unapplicable in relation to theory transferability and the separate categorization of job satisfaction and dissatisfaction. The latter are greatly affected by not only leadership style per se, but more precisely by the teacher’s perception of a certain leadership style. This individuality dimension also affects the ideological compatibility between teachers and work contexts, having a direct impact on job satisfaction. Nonetheless, although educational leadership has proven not to be the sole factor in teacher job satisfaction, morale and motivation, leaders must possess the right knowledge and understanding about the needs, expectations, attitudinal responses, and characteristics of their staff as individual members of a group in order to be able to positively affect their perceptions.
How did Covid-19 Affect Logistics Job Vacancy
 Postings?

Human resources can differentiate firms from their competitors or directly affect the success or failure of firms. As in many sectors, there is a need for qualified employees in the logistics sector, which is of great importance for the national economies. Qualified employees in this sector contribute to the success of the companies and the development of the industry. In this study, it is aimed to reveal the qualifications and characteristics of the labour force needed by logistics companies. It was also aimed to show the impact of COVID-19 on logistics job ads. For this purpose, a total of 1,410 job vacancy postings (before COVID-19) and a total of 1,700 job vacancy postings (during COVID-19) were searched on the kariyer.net website with the word “logistics” and analysed by content analysis method. As a result, it was found that the most advertised province was Istanbul in both periods, the most looked up experience requirement in the candidates was 1-5 years in both periods, the opportunities provided to the candidates (transportation, food and beverage, career, social activity) were not mentioned much in both periods. This study reveals the status of logistics job postings in the period before COVID-19 and during COVID-19. It was also aimed to show the impact of COVID-19 on logistics job ads. We investigated whether the logistics employee demand has changed and whether the pandemic is affecting workforce characteristics. This is the first empirical analysis of the impact of COVID-19 on logistics vacancy postings. © 2021 Innovations in Cardiac Rhythm Management
FINITE ELEMENT APPROXIMATION OF VISCOELASTIC FLOW IN A MOVING DOMAIN

In this work the problem of a viscoelastic fluid flow in a movable domain is considered. A numerical approximation scheme is developed based on the Arbitrary Lagr angian-Eulerian (ALE) formulation of the flow equations. The spatial discretization is accomplished by th e finite element method, and the discontinuous Galerkin method is used for stress approximation. Both first and second o rder time-stepping schemes satisfying the geometric conservation law (GCL) are derived and analyzed, and numeric al experiments that support the theoretical results are presented.
ACCURACY INVESTIGATION ON IMAGE-BASED CHANGE DETECTION FOR BIM COMPLIANT INDOOR MODELS

Abstract. Construction progress documentation is currently of great interest for the AEC (Architecture, Engineering and Construction) branch and BIM (Building Information Modeling). Subject of this work is the geometric accuracy assessment of image-based change detection in indoor environments based on a BIM. Line features usually serve well as geodetic references in indoor scenes in order to solve for camera orientation. However, building edges are never perfectly built as planned and often geometrically generalized for BIM compliant representation. As a result, in this approach, line correspondences for image-to-model co-registration are considered as statistically uncertain entities as this is essential for dealing with metric confidences in the field of civil engineering and BIM. We present an estimation model for camera pose refinement which is based on the incidence condition between model edges and corresponding image lines. Geometric accuracies are assigned to the model edges according to the Level of Accuracy (LOA) specification for BIM. The approach is demonstrated in a series of tests using a synthetic image of an indoor BIM. The effects of varying edge detection accuracies on the estimation are investigated as well as the effects of using model edges with different geometric quality by adding Gaussian noise to the synthetic observations, each within 100 simulation runs. The results show that the camera orientation can be improved with the presented estimation model as long as the BIM compliant references meet the conditions of LOA 30 or higher (σ < 7.5 mm).