Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterisation of P60 surface lipoprotein and its evaluation in a recombinant ELISA

1 This paper reports the identification and characterization of a 60 kDa surface protein 2 antigen (P60) of Mycoplasma capricolum subspecies capricolum ( Mcc ), and describes its 3 diagnostic application. Genomic localization and presence in P60 of conserved functional 4 domains suggested a structural and functional relationship with the immunodominant antigen 5 P48 of Mycoplasma agalactiae, a basic membrane protein. A rP60-ELISA was developed, 6 and it resulted in a high specificity for Mcc infections after evaluation with 125 goat sera. 7 The comparison with an existent ELISA based on whole Mcc cell lysates showed that the two 8 assays have comparable sensitivities, but the rP60-ELISA has the significant advantage of a 9 greater specificity. Results indicate that P60 is a potential marker of Mcc infection, especially 10 useful in areas where the presence of Mycoplasma capricolum subspecies capripenumoniae 11 is also reported. P60, a basic membrane protein (Bmp) sharing structural and genetic similarities with the Ma and Mbo P48 genes. We also report evaluation of its diagnostic potential in a recombinant ELISA (rP60-ELISA). bovine ELISA net absorbances were obtained for each by subtracting the absorbance measured against GST from the absorbance against the protein. Cut-off was evaluated using a subset of well characterized sera in dose titration experiments, and a positive reaction was defined as having a reactivity of >20% of the positive control serum enclosed in each plate. the percentage reactivity group were obtained using software Version 1.7. 1 (Fleiss, A subset of serum samples (n=73) from groups A, C, and the whole ELISA (wc-ELISA) and co-workers
University of Birmingham Computer-based teaching is as good as face to face lecture-based teaching of evidence based medicine

Background: At postgraduate level evidence based medicine (EBM) is currently taught through tutor based lectures. Computer based sessions fit around doctors' workloads, and standardise the quality of educational provision. There have been no randomized controlled trials comparing computer based sessions with traditional lectures at postgraduate level within medicine. Methods: This was a randomised controlled trial involving six postgraduate education centres in the West Midlands, U.K. Fifty five newly qualified foundation year one doctors (U.S internship equivalent) were randomised to either computer based sessions or an equivalent lecture in EBM and systematic reviews. The change from pre to post-intervention score was measured using a validated questionnaire assessing knowledge (primary outcome) and attitudes (secondary outcome). Results: Both groups were similar at baseline. Participants' improvement in knowledge in the computer based group was equivalent to the lecture based group (gain in score: 2.1 [S.D = 2.0] versus 1.9 [S.D = 2.4];
Miivfind: A Command for Identifying Model-Implied Instrumental Variables for Structural Equation Models in Stata

This article presents a new Stata command, miivfind, that implements an algorithm developed by Bollen and Bauer (2004, Sociological Methods and Research 32: 425–452) to find the model-implied instrumental variables (MIIVs) from an identified structural equation model. MIIVs allow researchers to draw on instrumental-variable estimators, such as two-stage least-squares estimators, to obtain estimates for the parameters of a hypothesized structural equation model. It can be difficult to identify MIIVs by inspection of either a diagram of the model or the model equations. Two examples are provided that illustrate the use of miivfind to identify MIIVs and some of the advantages of a MIIV estimator as compared with a maximum likelihood estimator. By assisting in the process of finding MIIVs, miivfind facilitates the use of an alternative class of estimators, instrumental-variable estimators, to the standard maximum-likelihood and asymptotic-distribution free estimators available for structural equation models.
Analysis and optimization of energy efficiency for an electric vehicle with four independent drive in-wheel motors

The independent driving ability of the four-wheel independent drive electric vehicles can be used to improve the energy efficiency of the vehicle. The composition and structure of a prototype were introduced in this article and the rapid prototype was applied to design the upper-level control system. Experimental data obtained from the bench tests and the chassis dynamometer tests were employed to generate the torque response performance and power efficiency map of the in-wheel motor. The control logic of the in-wheel motor was obtained based on the least squares method. Besides, a front and rear axle torque distribution method was proposed to reduce the energy consumption of vehicle, and the simulating test of the prototype was conducted based on the in-wheel motor efficiency map. Simulation analysis of vehicle energy consumption in vehicle driving cycle was carried out in ways of rear axle drive, average torque allocation, and optimized torque energy-saving allocation; the results show that the optimized torque energy-saving allocation strategy can decrease the energy consumption up to approximately 0.117 and 0.426 kJ per unit mileage comparing with the rear axle drive and average torque allocation.
Tools and Methodology for Converting Natural Language into RDF Representations

Recently, there is an increased interest on approaches, methodologies and tools converting natural language into machine readable representations, such as RDF format. Although several steps have been made towards Natural Language Processing (NLP) domain, the machine intelligence for understanding natural language is still a topic of high research interest and its further exploration is going to bring significant benefits to several sub-tasks such as machine translation and questions answering. Natural language processing and natural language understanding are the usual approaches to transform the textual content from being unstructured and ambiguous, into structured and unambiguous. The current article presents the pipeline of linguistic processing and knowledge extraction techniques that are combined together in order to extract structured knowledge from natural language textual content and populate a knowledge base with quality triples. Moreover, it gives an overview of existing knowledge extraction tools found in the literature. Last, a short discussion and comparison of these tools is provided, and the article concludes with a brief summary.
Photovoltaic Integrated Shunt Active Power Filter with Simpler ADALINE Algorithm for Current Harmonic Extraction

This manuscript presents a significant work in improving the current harmonics extraction algorithm and indirectly improving the injection current produced by a single-phase Photovoltaic Shunt Active Power Filter (PV SAPF). Improvement to the existing adaptive linear neuron (ADALINE) technique has been carried out, leading to the formation of a simpler ADALINE; it is expected to perform as fast as the current harmonics extraction algorithm. Further analysis on the DC link capacitor control algorithm, called “self-charging with step size error cancellation”, was also done to inspect the performance of the algorithm in a single-phase photovoltaic shunt active power filter system. Both algorithms, configured in single-phase PV SAPF, were simulated in MATLAB/Simulink (R2012b). A laboratory prototype was developed, and the algorithms were computed on a TMS320F28335 Digital Signal Processing (DSP) board for hardware implementation purposes. From the acquired results, the simpler ADALINE algorithm has effectively performed with lower total harmonic Distortion (THD) and outstanding compensation. The established algorithm of self-charging with step size error cancellation works well with single-phase PV SAPF and has shown less overshoot, a fast response time, and minimal energy losses.
Spat collection of the pearl oyster ( Pinctada margaritifera cumingii ) in French Polynesia: an evaluation of the potential impact on genetic variability of wild and farmed populations after 20 years of commercial exploitation

Pearl production, based on the aquaculture of the blacklipped pearl oyster Pinctada margaritifera is an essential economic activity in French Polynesia. Production relies almost exclusively on the collection of wild spat, which makes the activity very dependent on natural resources. A good knowledge of these resources is thus essential for the rational management of farmed and wild populations. In this study, we analysed the structure of genetic variability, in wild and farmed populations distributed on four atolls from the Tuamotu–Gambier archipelago using four anonymous nuclear loci. No genetic difference was observed among samples from wild populations collected from Northern Tuamotu to Southern Gambier. This suggests that large-scale dispersal, either due to the absence of barriers to natural larval migration, or to the transport of collected spat for pearl production. No significant differences were found between wild and adjacent farmed populations for the number of alleles and observed heterozygosity, which supports the conclusion that current methods used to collect wild spat are unlikely to affect the genetic composition of pearl oyster populations. However, a more accurate picture of the situation might be obtained with more variable markers.
Non-Adherence to Pharmacotherapy: A Prospective Multicentre Study About Its Incidence and Its Causes Perceived by Chronic Pain Patients Patient Preference and Adherence

Objective: Pharmacological interventions remain the cornerstone of chronic pain treatment; however, nearly 40% of the prescription medicines are not taken as prescribed. The present study aims at understanding and describing non-adherence from the perspective of chronic pain patients during a 1-year follow-up study. Methods: A cohort of 950 consecutive patients referred to a ﬁ rst consultation in Multidisciplinary Chronic Pain Clinics was followed with a standardized protocol for 1 year. This included assessment of pain characteristics; prescribed medication; therapeutic adherence; effectiveness of treatment, non-adherence and its perceived reasons; clinical outcomes and quality of life. We used a mixed methods approach, including qualitative and quantitative analyses. Results: Forty-nine percent of the 562 patients who responded to all assessments during follow-up were adherent after 1 year of chronic pain treatment. The core associations between each “ non-adherence reason ” and Anatomical Therapeutic Chemical Code (ATC) group were perceived side effects ( p =0.019) and delayed start ( p =0.022) for narcotic analgesics (opioids); perceived non-ef ﬁ cacy ( p =0.017) and delayed start ( p =0.004) for antiepileptics and anticonvulsants; perceived low necessity ( p =0.041) and delayed start ( p =0.036) for analgesics antipyretics; change in prescriptions because of a new clinical condition for antidepressants ( p =0.024); high concerns ( p =0.045) and change in prescriptions because of a new clinical condition ( p <0.001) for non-steroidal anti-in ﬂ ammatory drugs; delayed start ( p =0.016) and ﬁ nancial constraints ( p =0.018) for other medications. Discussion: This study emphasizes the patient ’ s perspective regarding non-adherence to pharmacological treatment of chronic pain, providing valuable and novel information to be used in future interventions to help patients make an informed choice about their adherence behavior.
Comparison between 3D Printed Auxetic and Non-Auxetic Structures: Simulation and Experimental Validation

:- In this study, five different auxetic structures were designed into dog bone specimens and printed with approximated similar masses, intended as the constant parameter. These specimens were then simulated by Finite Element Analysis before being subjected to tensile testing. In the simulation, yield stress comparisons between auxetic structures and non-auxetic were analyzed. UTS (Ultimate Tensile Stress) and maximum strain from tensile test results were compared with 3D printed non-auxetic with concentric infill. The results showed agreement between simulation and testing in terms of deformations and failure spots. In the end, simulated auxetic structures showed extensions in yielding limit at a range of 5-20% compared to control. Meanwhile, four out of five tested auxetics were proved to gain increment in UTS value at a range of 25.14%-160.9% and additional maximum strain percentage by 4.1-31.49% compared to non-auxetic with 10.1 MPa and 2.48%, UTS and maximum strain Respectively.
Characterization of 3D PET systems for accurate quantification of myocardial blood flow

Research article: Dynamic range is defined as a scanner-specific maximum injected activity/body-weight, below which myocardial blood flow can be quantified accurately using Rb-82 3D-PET imaging. Financial ABSTRACT Three-dimensional (3D) mode imaging is the current standard for positron emission tomography-computed tomography (PET-CT) systems. Dynamic imaging for quantification of myocardial blood flow (MBF) with short-lived tracers, such as Rb-82-chloride (Rb-82), requires accuracy to be maintained over a wide range of isotope activities and scanner count-rates. We propose new performance standard measurements to characterize the dynamic range of PET systems for accurate quantitative imaging. Methods : 1100-3000 MBq of Rb-82 or N-13-ammonia was injected into the heart wall insert of an anthropomorphic torso phantom. A decaying isotope scan was performed over 5 half-lives on 9 different 3D PET-CT systems and 1 3D/two-dimensional (2D) PET-only system. Dynamic images (28x15s) were reconstructed using iterative algorithms with all corrections enabled. Dynamic range was defined as the maximum activity in the myocardial wall with <10% bias, from which corresponding dead-time, count-rates and/or injected activity limits were established for each scanner. Scatter correction residual bias was estimated as the maximum cavity blood-to-myocardium activity ratio. Image quality was assessed via the coefficient of variation measuring non-uniformity of the left ventricle (LV) myocardium activity distribution. Results : Maximum recommended injected activity/body-weight, peak dead-time correction factor, count-rates and residual scatter bias for accurate cardiac MBF imaging were: 3-14 MBq/kg, 1.5-4.0, 22-64 Mcps singles and 4-14 Mcps prompt coincidence count-rates, and 2-10% on the investigated scanners. Non-uniformity of the myocardial activity distribution varied from 3-16%. Conclusion : Accurate dynamic imaging is possible on the 10 3D-PET systems if the maximum injected MBq/kg values are respected to limit peak dead-time losses during the bolus first-pass transit. PET-CT-16 systems to assess reproducibility of injected activity/body-weight values. This study established methods to evaluate the accurate dynamic operating range of 3D PET systems for quantitative cardiac imaging with Rb-82. Decaying isotope phantom scans were performed over 5 half-lives to determine the optimal operating range, defined by the maximum injected activity/body-weight, and corresponding maximum singles, prompt coincidence count-rates and/or peak dead-time factors. Patient scans were performed near the suggested limits on 3 representative scanners and confirmed validity of the phantom scan recommendations. Evaluation of the scatter correction bias confirmed the effectiveness of manufacturer-implemented scatter corrections in 3D-mode. Finally, LV polar-map non-uniformity, and the absence of count-rate dependent pile-up artifacts, was found to be adequate for diagnostic evaluation.
Induction motor temperature monitoring via signal injection enhanced with adaptive neuro-fuzzy inference system

This research work presents a reliable technique to protect the stator winding of asynchronous machine. The protection scheme depends on continuous temperature monitoring of the winding. It utilizes integration between the DC injection method and an artificial intelligence technique. The soft starter coupled to asynchronous machine is used to inject DC signal. It modifies the operation of the reverse-parallel thyristors. The gate control signal of the soft starter produces a short delay in half current cycle for one phase of the machine. Then the DC components are obtained from the current and voltage Fourier analysis. By using the magnitude of the DC signals, the stator winding resistance and temperature are computed. To obtain an accurate temperature of winding; the calculated motor parameters are employed to be an input data for a fuzzy scheme. Therefore, the Adaptive Neuro-Fuzzy Inference System (ANFIS) scheme is utilized to supply an efficient and active temperature display for stator winding. In addition ANFIS decreased the estimation error of the winding temperature without affecting on motor torque at certain delay angle. The obtained results with Matlab simulation are inventively. RÉSUMÉ. Cet article de recherche présente une technique fiable pour protéger l’enroulement de stator d’une machine asynchrone. Le schéma de protection dépend de la surveillance continue de la température de l'enroulement. Il utilise l'intégration de la méthode d'injection de courant continu (CC) et une technique d'intelligence artificielle. Le démarreur accouplé à une machine asynchrone est utilisé pour injecter un signal de CC. Il modifie le fonctionnement des thyristors inversés. Le signal de commande de porte du démarreur produit un court délai dans le demi-cycle de courant pour une phase de la machine. Ensuite, les composantes de CC sont obtenues à partir de l'analyse de Fourier du courant et de la tension. En utilisant la magnitude des signaux de CC, la résistance et la température de l'enroulement du stator sont calculées. Pour obtenir une température d’enroulement précise, les paramètres moteur calculés sont utilisés en tant que donnée d'entrée pour un schéma flou. Par conséquent, le système d'inférence neuro-flou adaptatif (ANFIS en anglais) est utilisé pour fournir un affichage de la température efficace et actif pour l'enroulement du stator. De plus, le système 92 EJEE. Volume 19 – n° 1-2/2017 d'inférence neuro-flou adaptatif a diminué l'erreur d'estimation de la température de l'enroulement sans affecter la torque du moteur à un certain angle de retard. Les résultats obtenus avec la simulation Matlab sont inventifs.
Error-Related Potentials in Reinforcement Learning-Based Brain-Machine Interfaces

The human brain has been an object of extensive investigation in different fields. While several studies have focused on understanding the neural correlates of error processing, advances in brain-machine interface systems using non-invasive techniques further enabled the use of the measured signals in different applications. The possibility of detecting these error-related potentials (ErrPs) under different experimental setups on a single-trial basis has further increased interest in their integration in closed-loop settings to improve system performance, for example, by performing error correction. Fewer works have, however, aimed at reducing future mistakes or learning. We present a review focused on the current literature using non-invasive systems that have combined the ErrPs information specifically in a reinforcement learning framework to go beyond error correction and have used these signals for learning.
Evaluation of Feature Selection for Alzheimer’s Disease Diagnosis

Accurate recognition of patients with Alzheimer’s disease (AD) or mild cognitive impairment (MCI) is important for the subsequent treatment and rehabilitation. Recently, with the fast development of artificial intelligence (AI), AI-assisted diagnosis has been widely used. Feature selection as a key component is very important in AI-assisted diagnosis. So far, many feature selection methods have been developed. However, few studies consider the stability of a feature selection method. Therefore, in this study, we introduce a frequency-based criterion to evaluate the stability of feature selection and design a pipeline to select feature selection methods considering both stability and discriminability. There are two main contributions of this study: (1) It designs a bootstrap sampling-based workflow to simulate real-world scenario of feature selection. (2) It develops a decision graph to determine the optimal combination of supervised and unsupervised feature selection both considering feature stability and discriminability. Experimental results on the ADNI dataset have demonstrated the feasibility of our method.
Rapid Shifts in Visible Carolina Grasshopper (Dissosteira carolina) Coloration During Flights

Some brightly colored structures are only visible when organisms are moving, such as parts of wings that are only visible in flight. For example, the primarily brown Carolina grasshopper (Dissosteira carolina) has contrasting black-and-cream hindwings that appear suddenly when it takes off, then oscillate unpredictably throughout the main flight before disappearing rapidly upon landing. However, the temporal dynamics of hindwing coloration in motion have not previously been investigated, particularly for animals that differ from humans in their temporal vision. To examine how quickly this coloration appears to a variety of non-human observers, we took high-speed videos of D. carolina flights in the field. For each of the best-quality takeoffs and landings, we performed a frame-by-frame analysis on how the relative sizes of the different-colored body parts changed over time. We found that in the first 7.6 ± 1.5 ms of takeoff, the hindwings unfurled to encompass 50% of the visible grasshopper, causing it to roughly double in size. During the main flight, the hindwings transitioned 6.4 ± 0.4 times per second between pauses and periods of active wing-beating (31.4 ± 0.5 Hz), creating an unstable, confusing image. Finally, during landings, the hindwings disappeared in 11.3 ± 3.0 ms, shrinking the grasshopper to 69 ± 9% of its main flight size. Notably, these takeoffs and landings occurred faster than most recorded species are able to sample images, which suggests that they would be near-instantaneous to a variety of different viewers. We therefore suggest that D. carolina uses its hindwings to initially startle predators (deimatic defense) and then confuse them and disrupt their search images (protean defense) before rapidly returning to crypsis.