Miracle-dz/UniFAR-FTUs huggingface dataset:
IDENTIFICATION OF MYCOBACTERIUM STRAINS BY PCR AND PCR-REA

The presented study aimed isolation of Mycobacterium strains from cases of bovine tuberculosis in Turke y, and identification of these isolates by PCR and restricti on endonuclease analysis (REA). Mycobacteria were isolated from bronchial, mesenteric, and prescapular lymph nodes and tubercl e samples from slaughtered cattle, which were eithe r skin-test reactors or showed tuberculous suspected lesions during meat in spection. The samples were cultured in Lowenstein-Jensen medium. Colonies suspected of being Mycobacterium sp. were analysed by the PCR method using the MTUB_c-gyrBf and MTUB_c-gyrBr primers, which amplify the 1,020-bp region of the gyr B gene, that encodes the B subunit of the DNA gyrase (topois omerase) enzyme in strains of the Mycobacterium tuberculosis complex (MTBC). The REA of MTBC-PCR positive amplified products was performed using the Sac II and Rsa I enzymes, in order to identify specific strains. T he MTBC-PCR analysis of 117 bacterial strains demonstrated that all isolates belonged to the MTBC. All isolates were identified as M. bovis /M. bovis subsp. caprae by Rsa I-REA, whilst 93 (79.5%) of the bacterial strains were ide ntified as M. bovis and 24 (20.4%) as M. bovis subsp. caprae by Sac II-REA. M. bovis subsp. caprae was isolated and identified for the first time in Turkey from bovine tuberculosis cases.
Erwinia amylovora bacteriophage resistance

It has been proposed that phages can be used commercially as a biopesticide for the control of fire blight caused by the phytopathogen Erwinia amylovora. The aim of these studies was to investigate two common bacterial resistance mechanisms, lysogeny and exopolysaccharide production and their influence on phage pathogenesis. A multiplex real-time PCR protocol was designed to monitor and quantify Podoviridae and Myoviridae phages. This protocol is compatible with known E. amylovora and Pantoea agglomerans rtPCR primers/probes which allowed simultaneous study of both phage and bacterial targets. Using in vitro positive phage selection, bacteriophage insensitive derivatives were isolated within sensitive populations of E. amylovora. Prophage screening with real-time PCR and mitomycin C induction determined that the insensitive derivatives harboured the temperate Podoviridae phage ΦEaTlOO. Lysogenic conversion resulted in resistance to secondary homologous phage infections. Prophage screening of environmental samples of E. amylovora and P. agglomerans collected from various locations in Canada, United States and Europe did not demonstrate lysogeny. Therefore, lysogeny is rare or absent while these bacterial species reside on the plant. Recombineering was used to construct exopolysaccharide deficient E. amylovora mutants. The EPS amylovoran mutants became resistant to Podoviridae and certain Siphoviridae phages. Increasing amylovoran production increased phage population growth, presumably by increasing the total number of bacterial cell surface receptors which promoted increased phage infections. In contrast, amylovoran did not playa role in Myoviridae infections, nor did production of the EPS levan for any phage pathogenesis.
Effect of land configuration on water economy, crop yield and profitability under rice (Oryza sativa)-based cropping systems in north-east India.

A field experiment was conducted during the winter (rabi) season of 2006 and 2007 to evaluate the water economy and performance of different crop combinations under standard raised and sunken bed system of cultivation in mid-hills of Meghalaya, north-eastern part of India. The treatment consisted of various winter vegetables crops like tomato (Lycopersicon esculentum L. Mill. nom. cons.), potato (Solanum tuberosum L.) grown on sunken beds and gardenpea (Pisum sativum L.) and Frenchbean (Phaseolus vulgaris L.) grown on raised beds under organic mulched and without mulched condition. Periodical observations on soil moisture content and yield attributes of various crops were recorded for further analysis on water economy and profitability of cropping systems. Organic mulching significantly increased the soil moisture content in all the crop combinations. The profile soil moisture content was significantly higher in rice (Oryza sativa L.)–tomato/gardenpea cropping system (29.3%), lowest being in rice-fallow system (22.5%). Results showed that organic mulch decreased soil temperature by 3–5°C compared to that in the plots without mulch. Among the various crop combinations, rice–tomato/gardenpea gave the highest rice equivalent yield and production efficiency (18 138 kg/ha and 77.18 kg/ha/day, respectively), followed by rice–potato/gardenpea system (16 982 kg/ha and 76.50 kg/ha/day, respectively), lowest being in rice monocropping (4 420 kg/ha and 36.23 kg/ha/day, respectively). Highest net returns (Rs 56 730/ha) was recorded in rice–tomato/gardenpea, followed by rice–potato/ gardenpea (Rs 51 465/ha).
Psoriasis pathophysiology and impact on life

Psoriasis is a chronic skin disorder with various morphology, distribution, severity, and course of disease. The goal of the management is to control disease activity to a level that allows a sufficient quality of life with minimal toxicity from the treatment itself. Unfortunately, 25% of patients suffering from psoriasis experience major psychological distress. Its chronic nature with associated comorbidities has a negative impact on quality of life. We conducted this review using a comprehensive search of MEDLINE, PubMed and EMBASE from January 1996 to March 2017. The following search terms were used: psoriasis, pathogenesis of psoriasis, psoriasis management, quality of life in psoriasis patients. We tried to study the pathogenesis, and management of psoriasis, and understand its effect on the quality of life of patients. Due to the chronic nature and its obvious visibility on skin, many patients suffer from major psychological adverse effects. In majority of the time the health care providers fail to recognize or treat such comorbidities. Healthcare providers must be educated to provide patients with ways to tackle issues with multiple aspects, including psychological, in the management plan for better results.
An Integrated Approach of Best-Worst Method (BWM) and Triangular Fuzzy Sets for Evaluating Driver Behavior Factors Related to Road Safety

Driver behavior plays a major role in road safety because it is considered as a significant argument in traffic accident avoidance. Drivers mostly face various risky driving factors which lead to fatal accidents or serious injury. This study aims to evaluate and prioritize the significant driver behavior factors related to road safety. In this regard, we integrated a decision-making model of the Best-Worst Method (BWM) with the triangular fuzzy sets as a solution for optimizing our complex decision-making problem, which is associated with uncertainty and ambiguity. Driving characteristics are different in different driving situations which indicate the ambiguous and complex attitude of individuals, and decision-makers (DMs) need to improve the reliability of the decision. Since the crisp values of factors may be inadequate to model the real-world problem considering the vagueness and the ambiguity, and providing the pairwise comparisons with the requirement of less compared data, the BWM integrated with triangular fuzzy sets is used in the study to evaluate risky driver behavior factors for a designed three-level hierarchical structure. The model results provide the most significant driver behavior factors that influence road safety for each level based on evaluator responses on the Driver Behavior Questionnaire (DBQ). Moreover, the model generates a more consistent decision process by the new consistency ratio of F-BWM. An adaptable application process from the model is also generated for future attempts.
Density-Aware Multi-Task Learning for Crowd Counting

In this paper, we present a method called density-aware convolutional neural network (DensityCNN) to perform the crowd counting task in various crowded scenes. The key idea of the DensityCNN is to utilize high-level semantic information to provide guidance and constraint when generating density maps. To this end, we implement the DensityCNN by adopting a multi-task CNN structure to jointly learn density-level classification and density map estimation. The density-level classification task learns multi-channel semantic features that are aware of the density distributions of the input image. This task is accomplished via our specially designed group-based convolutional structure in a supervised learning manner. In the density map estimation task, these semantic features are deployed together with high-dimension convolutional features to generate density maps with lower count errors. Extensive experiments on four challenging crowd datasets (ShanghaiTech, UCF_CC_50, UCF-QNCF, and WorldExpo’10) and one vehicle dataset TRANCOS demonstrate the effectiveness of the proposed method.
Development and Evaluation of an AI System for COVID-19

Early detection of COVID-19 based on chest CT will enable timely treatment of patients and help control the spread of the disease. With rapid spreading of COVID-19 in many countries, however, CT volumes of suspicious patients are increasing at a speed much faster than the availability of human experts. Here, we propose an artificial intelligence (AI) system for fast COVID-19 diagnosis with an accuracy comparable to experienced radiologists. A large dataset was constructed by collecting 970 CT volumes of 496 patients with confirmed COVID-19 and 260 negative cases from three hospitals in Wuhan, China, and 1,125 negative cases from two publicly available chest CT datasets. Trained using only 312 cases, our diagnosis system, which is based on deep convolutional neural network, is able to achieve an accuracy of 94.98%, an area under the receiver operating characteristic curve (AUC) of 97.91%, a sensitivity of 94.06%, and a specificity of 95.47% on an independent external verification dataset of 1,255 cases. In a reader study involving five radiologists, only one radiologist is slightly more accurate than the AI system. The AI system is two orders of magnitude faster than radiologists and the code is available at https://github.com/ChenWWWeixiang/diagnosis_covid19.
How using comics can assist in determining the students’ learning of distance-time graphs

The art of teaching mathematics at all levels requires a lot of creativity and innovation from a teacher for the students to effectively grasp what they are taught. Teachers tend to devise various means always ensure that they understand the attention of a learner in mathematics lessons bearing in mind that some learners easily switch off in mathematics lessons. In this study, we explored how a teacher can effectively use comics while teaching upper secondary students the topic of Distance-Time Graphs. The research entails that problems exists among the mathematics areas where the students face a challenge in grasping the concepts they are taught and even lose concentration more quickly while the teacher is teaching thereby falsely conceptualising that mathematics is a difficult subject. The concepts involved in this paper are in concurrent to the existing literature that the use of comics is one of the ways to draw the attention of students while teaching them. An action research approach was adopted to determine whether students’ understanding of mathematics concepts in Brunei schools could be improved using comics. The problems that 38 Year 10 students encountered while learning Distance-Time Graphs have also been elaborated in this paper, and the methodology through which comics can be incorporated into the teaching and learning process in this area has also be shown for practical application in the Brunei secondary school. There is also an elaboration on how the research concerning the use of comics in teaching was conducted and how the hypothesis was analyzed and evaluated to have a positive outcome in the teaching and learning process.
Dual Learning for Explainable Recommendation: Towards Unifying User Preference Prediction and Review Generation

In many recommender systems, users express item opinions through two kinds of behaviors: giving preferences and writing detailed reviews. As both kinds of behaviors reflect users’ assessment of items, review enhanced recommender systems leverage these two kinds of user behaviors to boost recommendation performance. On the one hand, researchers proposed to better model the user and item embeddings with additional review information for enhancing preference prediction accuracy. On the other hand, some recent works focused on automatically generating item reviews for recommendation explanations with related user and item embeddings. We argue that, while the task of preference prediction with the accuracy goal is well recognized in the community, the task of generating reviews for explainable recommendation is also important to gain user trust and increase conversion rate. Some preliminary attempts have considered jointly modeling these two tasks, with the user and item embeddings are shared. These studies empirically showed that these two tasks are correlated, and jointly modeling them would benefit the performance of both tasks. In this paper, we make a further study of unifying these two tasks for explainable recommendation. Instead of simply correlating these two tasks with shared user and item embeddings, we argue that these two tasks are presented in dual forms. In other words, the input of the primal preference prediction task is exactly the output of the dual review generation task , with and denote the preference value space and review space. Therefore, we could explicitly model the probabilistic correlation between these two dual tasks with . We design a unified dual framework of how to inject the probabilistic duality of the two tasks in the training stage. Furthermore, as the detailed preference and review information are not available for each user-item pair in the test stage, we propose a transfer learning based model for preference prediction and review generation. Finally, extensive experimental results on two real-world datasets clearly show the effectiveness of our proposed model for both user preference prediction and review generation.
Design of Criticality-Based Haptic Steering Guidance for Human Like Adaptation to Different Lane Keeping Tasks

Haptic steering guidance is an advanced driving assistance system which provides guidance torques on the steering wheel to assist a human driver. Improvements in performance, safety margins and workload have been reported for lane-keeping and curve negotiation tasks. On the other hand, the guidance system instigates increased driver torques, indicating the occurrence of a mismatch between driver and automation intention. A novel, criticality-based control structure was developed, capable of adapting to different driving conditions by using safety margins (operationalized as time-to-line crossing, TLC) as input. Twenty-four participants drove through a single-lane, 10.8 km long road, with as independent variables the road width (normal road width of 3 m, wide road width of 5 m) and the type of guidance received: no guidance (manual), haptic steering guidance based on lateral deviation from the center-line (performance-based guidance, PBG) and criticality-based guidance (CBG). On the normal road, results show similar benefits for both guidance systems compared to manual control, in terms of performance and safety margins. Workload was reduced by PBG, but both guidance systems yielded increased driver torques. On the wide road, participants drove closer to the center-line with PBG, but at the cost of significantly more guidance torques than CBG. Interestingly, this reduction in lateral deviation did not result in a significant improvement for lowest safety margins encountered. No subjective preference was found for either feedback condition. It can be concluded that criticality-based guidance is capable of adjusting to different driving conditions, without compromising safety margins, whilst greatly reducing guidance torques in situations where they are unneeded.
Diversity for malting quality in barley (Hordeum vulgare) varieties released in India

A study was conducted during 2005 to study the genetic diversity among 72 Indian barley (Hordeum vulgare L.) varieties released during last 60 years for different grain and malt quality traits. Most of these varieties were not originally bred as malt barley and there are only few varieties released as malt barley. The present study was taken up to analyze the extent of variability for malting quality in these released varieties. Observations were recorded on 7 grain and 7 malt traits. The study revealed that lot of variability exists among these varieties for individual malting quality traits. The data were subjected to clustering analysis for grouping of genotypes based on genetic diversity between groups. The hierarchical cluster analysis based on Euclidean distance and agglomerative linkage function indicated that genotypes with good malting quality were mostly grouped in cluster I and II.
The pleiotropic effects of LC8 on the anchoring protein in flagellar radial spoke complex

THE PLEIOTROPIC EFFECTS OF LC8 ON THE ANCHORING PROTEIN IN FLAGELLAR RADIAL SPOKE COMPLEX Anjali Gupta, M.S. Marquette University, 2011 The goal of this thesis is to elucidate the assembly mechanism of macromolecular complexes in the microtubule-based axoneme in flagella. The axoneme is comprised of more than 400 distinct polypeptides. While all axonemal proteins are synthesized in the cell body, they need to be imported to the tip of the growing flagella for the final assembly. They are then assembled into distinctive structural complexes and integrated into precise positions relative to each other. The assembled macromolecular complexes operate in concert enabling the axoneme to beat rhythmically as a biological machine. This arduous process involves multiple reactions and meticulous regulation. However, the assembly process in the cell body and at the tip of flagella remains largely unknown. This thesis took advantage of a flagella model organism Chlamydomonas and a rather simple and a well-characterized axonemal complex, the radial spoke, to identify the key assembly mechanisms. Genetic studies have revealed two spoke components, RSP3 and LC8, that are particularly important for the assembly of the entire complex. Mutants defective in either gene generate paralyzed flagella devoid of the RS. Using a variety of approaches that are possible for this model organism, this study revealed that a stack of LC8 dimers directly binds to RSP3 at the tip of the flagella to promote a series of events, including phosphorylation of RSP3, formation of the base of the RS and docking of the spoke to the axoneme. These findings have shed light on the series of events that occur between transport and assembly. These findings also have broad implications, as LC8 is a promiscuous molecule that interacts with many flagellar and non-flagellar proteins in the cell body. Many of them play vital roles in the normal functioning of cells or in the pathogenesis of microorganisms. Some LC8 target proteins exist in the molecular complexes, as the radial spoke. However, the LC8-involved reactions remain poorly defined. The findings from this thesis show that LC8 bindings can trigger pleiotropic effects on a single target protein. Together, these conclusions shed critical insight on the biology of flagella and LC8.
Angiotensin converting enzyme and mitochondria – molecular and genetic mechanisms involving bradykinin receptors and uncoupling proteins

Low angiotensin converting enzyme (ACE) activity is associated with various cardiovascular phenotypes including reduced left ventricular (LV) hypertrophy, reduced cardiovascular events and enhanced metabolic efficiency, but precise mechanisms are unclear and direct genetic associations remain controversial. ACE degrades kinins and promotes formation of angiotensin II. Combined genetic and in vitro studies were used to test the hypothesis that the previously observed effects may be through alterations in kinins or mitochondrial function via novel uncoupling proteins (UCPs). The -9 allele of the bradykinin β2 receptor BDKRB2+9/-9 gene variant is correlated with low kinin activity and was associated with lower prospective LV growth during strenuous physical exercise and lower prospective hypertensive cardiovascular risk, as well as increased efficiency of skeletal muscle contraction (delta efficiency) in healthy volunteers (P = 0.003, accounting for 11% of the inter-individual variability). Addition of angiotensin II to skeletal myocytes resulted in a 3.5 fold increase in oxygen consumption (P = 0.03). Incubation of isolated myocytes with an ACE inhibitor lead to mitochondrial membrane hyperpolarisation, suggesting mitochondrial coupling may be an important mediator of the cellular actions of ACE. A common promoter variant in the UCP2 gene was associated with a two-fold increase in prospective cardiovascular risk (P < 0.0001). Variation in the UCP3/2 gene cluster accounted for 15% of the inter-individual endurance training related changes in delta efficiency and there was a surprising, but consistent, association with serum ACE activity. Finally, in vitro assays confirmed physiological downregulation of UCP2 in endothelial cells was associated with increased oxidative stress and reduced ACE mRNA. In conclusion, BDKRB2 may mediate some of the beneficial metabolic and cardiovascular effects associated with low ACE activity, possibly through changes in mitochondrial function. Mitochondrial coupling appears pivotal in cardiovascular (patho)physiology, possibly via oxidative stress or a novel ACE metabolic regulatory pathway. UCPs may be a target for future cardiovascular interventions.
Physics of Planetary Ionospheres

I Neutral Atmospheres. - I.1 Nomenclature. - I.2 Barosphere: Distribution Laws. - I.3 Thermosphere-Thermal Structure. - I.4 Exosphere-Atmospheric Escape (Evaporation). - I.5 Physical Properties of Planetary Atmospheres. - II Sources of Ionization. - II.1 Solar EUV Radiation and X-Rays. - 1I.2 Corpuscular Radiation. - II.3 Meteor Ionization. - III Thermal Structure of Planetary Ionospheres. - III.1 Departures from Thermal Equilibrium. - I1I.2 Electron and Ion Temperatures. - III.3 Heat Sources not Related to Photoionization. - IV Chemical Processes. - IV.1 General Comments. - IV.2 Recombination. - IV.3 Charge Exchange Reactions. - IV.4 Negative Ion Reactions. - IV.5 Chemical Reactions and Airglow. - V Plasma Transport Processes. - V.1 Plasma (Ambipolar) Diffusion. - V.2 Plasma Drift and Winds. - V.3 Plasma Escape. - VI Models of Planetary Ionospheres. - VI.1 Equilibrium Models. - VI.2 Observables and Derived Parameters. - VI.3 Ionospheric Regions. - VI.4 Realistic Models of Planetary Ionospheres. - VI.5 The Extent of Planetary Ionospheres. - VII The Ionosphere as a Plasma. - VII.1 General Plasma Properties. - VII.2 The Ionosphere as a Dispersive Medium. - VII.3 Ionospheric Plasma Instabilities. - VIII Experimental Techniques. - VIII.1 Remote Sensing Radio Techniques. - VIII.2 Direct Measurement Techniques. - IX Observed Properties of Planetary Ionospheres. - IX.1 The Terrestrial Ionosphere. - IX.2 The Ionosphere of Mars. - IX.3 The Ionosphere of Venus. - IX.4 The Ionosphere of Jupiter. - Appendix. Physical Data for the Planets and their Atmospheres. - References. - List of Symbols.