Miracle-dz/UniFAR-FTUs huggingface dataset:
Synergistic activities of ethanolic extracts of Jatropha tanjorensis leaves in conventional management of rheumatoid arthritis in the ankles of Wistar Rats

Background Rheumatoid arthritis (RA) is a common cause of chronic inflammatory joint disease. Plant extracts contain several bioactive factors which can re-establish the homeostasis of joints and joint cartilages. Objectives This study aim to evaluate synergism of ethanolic extracts of Jatropha tanjorensis leaves with Ibuprofen and Sulfasalazine as an antirheumatic agent. Methodology 25 adult male Wistar rats were subjected to different types of treatment (110 days); A: Positive control, B: Ibuprofen, Sulfasalazine and Low dose of extract, C: Ibuprofen, Sulfasalazine and Medium dose of extract, D: Ibuprofen, Sulfasalazine and High dose of extract, E: Normal control. Groups A-D were collagen-induced arthritic (CIA) models. One week before sacrifice, anterior-posterior and lateral diameters of both ankles, physical appearance and weight were assessed. After sacrifice, histological analysis of ankles using modified Mankin scoring system was done. Results Groups B, C and D had significant improvements in direct proportion to the dosages of J. tanjorensis extract administered. Increased doses slowed down the progression of cartilage destruction evidenced by prevention of joint swellings and preservation of chondrocytes and its histological features. Group A (positive control) exhibited cartilage destruction but no cartilage changes noted in group E (normal control). Conclusion We demonstrated synergistic effects of J. tanjorensis with Ibuprofen and Sulfasalazine combination therapy on animal model of collagen-induced rheumatoid arthritis. The evaluation of these effects were assessed by several means; physical appearance, assessment of weight, anterior-posterior and lateral diameters, and histological examination of both ankles of the animal that characterizes the originality of the study. Summary What is already known on this topic – The current therapeutic regimen for RA has some disadvantageous side effects. What this study adds – An alternative to the conventional management of RA with lower side effects. How this study might affect research, practice or policy – There is need to standardize dosages of newer herbs identified to be therapeutic.
Mining the human gut microbiome identifies mycobacterial D-arabinan degrading enzymes

Division and degradation of bacterial cell walls requires coordinated action from a myriad of enzymes. This particularly applies to the elaborate cell walls of acid-fast organisms such as Mycobacterium tuberculosis, which consist of a multi-layered cell wall that contains an unusual glycan called arabinogalactan. Enzymes that cleave the D-arabinan core of this structure have not previously been identified in any organism. We have exploited the breadth of carbohydrate active enzymes in the human gut microbiota to identify four families of glycoside hydrolases each with the capability to degrade the D-arabinan or D-galactan components of arabinogalactan. We have discovered novel exo-D-galactofuranosidases from gut bacteria and used them to discover both endo- and exo-acting enzymes that cleave D-arabinan. This includes new members of the DUF2961 family (GH172), and a novel family of glycoside hydrolases (DUF4185) which display endo-ᴅ-arabinofuranase activity. The DUF4185 enzmyes are conserved in mycobacteria and found in many microbes, suggesting that the ability to degrade mycobacterial glycans plays an important role in the biology of diverse organisms. All mycobacteria encode two conserved endo-D-arabinanases that display different preferences for the essential cell wall components arabinogalactan and lipoarabinomannan, suggesting they are important to cell wall modification and/or degradation. Identification of these enzymes will enable isolation and analysis of mycobacterial cell wall components and facilitate the discovery of new therapeutic or diagnostic options for mycobacterial diseases.
Neural Substrates of Body Ownership and Agency during Voluntary Movement

Body ownership and the sense of agency are two central aspects of bodily self-consciousness. While multiple neuroimaging studies have investigated the neural correlates of body ownership and agency separately, few studies have investigated the relationship between these two aspects during voluntary movement when such experiences naturally combine. By eliciting the moving rubber hand illusion with active or passive finger movements during functional magnetic resonance imaging, we isolated activations reflecting the sense of body ownership and agency, respectively, as well as their interaction, and assessed their overlap and anatomic segregation. We found that perceived hand ownership was associated with activity in premotor, posterior parietal, and cerebellar regions, whereas the sense of agency over the movements of the hand was related to activity in the dorsal premotor cortex and superior temporal cortex. Moreover, one section of the dorsal premotor cortex showed overlapping activity for ownership and agency, and somatosensory cortical activity reflected the interaction of ownership and agency with higher activity when both agency and ownership were experienced. We further found that activations previously attributed to agency in the left insular cortex and right temporoparietal junction reflected the synchrony or asynchrony of visuoproprioceptive stimuli rather than agency. Collectively, these results reveal the neural bases of agency and ownership during voluntary movement. Although the neural representations of these two experiences are largely distinct, there are interactions and functional neuroanatomical overlap during their combination, which has bearing on theories on bodily self-consciousness. SIGNIFICANCE STATEMENT How does the brain generate the sense of being in control of bodily movement (agency) and the sense that body parts belong to one's body (body ownership)? Using fMRI and a bodily illusion triggered by movement, we found that agency is associated with activity in premotor cortex and temporal cortex, and body ownership with activity in premotor, posterior parietal, and cerebellar regions. The activations reflecting the two sensations were largely distinct, but there was overlap in premotor cortex and an interaction in somatosensory cortex. These findings advance our understanding of the neural bases of and interplay between agency and body ownership during voluntary movement, which has implications for the development of advanced controllable prosthetic limbs that feel like real limbs.
Assessing the Effectiveness of Instructional Technology Tools in Online Business Programs

An evaluation rubric was developed to assess instructional technology tools used within online business programs to enhance learner engagement and content presentation skills. The evaluation was designed to determine if the instructional technology within the lesson helped to engage the learner, impact the assessment of outcomes, and improve the ability to present the content of the learning material. In this case study example, an instructional lesson was developed to instruct learners in creating a Work Breakdown Structure (WBS) using a project management software tool. This lesson was designed to be completed in 30 minutes or less. Step-by-step guides for obtaining a free copy of the project software application and creation of a WBS, including a visual example of a finished WBS, were built into this lesson. The lesson also included performance objective alignment to support future analysis of student performance across all courses in which this lesson existed within the Learning Management System (LMS). This evaluation rubric was built into the LMS for the evaluation team (n= 69) and yielded highly positive results of the training lesson across five categories of evaluation: (a) Technology Use (24.05/25), (b) Learner Engagement (19.05/20), (c) Goals and Objectives (19/20), (d) Assessment Value (19.05/20, and (e) Content Presentation (14.05/15). The rubric is one form of evaluation to address assessment elements within courseware development and will be validated in future research projects.
Compact fractal antenna circularly polarised radiation for Wi‐Fi and WiMAX communications

A novel antenna design was configured via a five-stage process. At each stage, a new modified square patch with a half size of that used in the previous stage was added to shape the dual fractal-structure antenna. The antenna had measured dual operating bands (2.4-2.65 and 4.8-6.4 GHz) that meet the specifications of the wireless fidelity (Wi-Fi) and worldwide interoperability for microwave access (WiMAX) applications. The structure of the antenna was carefully analysed to achieve an axial ratio bandwidth of 3 dB, which was ~35% of the first operating band and 30% of the second operating band. Right-hand and left-hand circular polarisations were achieved by switching the inputs. The proposed antenna can be used with portable communication devices because of its compact size (18 × 18 × 0.8 mm 3 ) and maximum efficiency (85%) compared with other related antennas.
Estimating Parameters of the Induction Machine by the Polynomial Regression

Parameter identification of an induction machine is of great importance in numerous industrial applications. This paper used time-varied signals of voltage, current, and rotor speed to compute the equivalent circuit parameters, moment of inertia, and friction coefficient of an induction machine. The theoretical impedance-slip rate characteristic curve of the induction machine can be expressed as a polynomial fraction, so that a proper polynomial fraction can obtain complete and accurate parameters. A time-varied impedance can be found by the time-varied voltage and current. From the variation of impedance to the rotor speed, the parameters of the equivalent circuit can be found. According to the equivalent circuit and rotor speed, the torque can be determined via dynamic simulation. On the basis of torque and rotor speed with time, the moment of inertia and friction coefficient of the motor can then be obtained. Advantages of this method include the ability to obtain the optimal value via only one calculation, without the requirement of any initial value, and the avoidance of any local optimal solution. In this paper, the analysis of a practical induction machine was used as an example to illustrate the practical application.
Women perception of shoe cushioning as a function of mechanical properties of footwear using a sensory trained panel method†

Most of the studies investigated footwear cushioning through the quantification of impact load or running-related injuries. Few studies focused on users’ perception of footwear cushioning. Users’ perception is usually investigated in other domains like food and consumer products using the ‘Sensory Trained Panel’ method. The purpose of this study was to assess the relationship between women's perception of shoe cushioning and mechanical properties of running shoes using a sensory trained panel approach. An initial mechanical characterization enabled to select 10 shoes having a wide range of mechanical properties. Ten recreational women runners were trained to become a ‘Sensory Trained Panel. ’ First, simple vocabulary and gestures were highlighted to make shoe feature definition explicit and understood by all participants. Then, participants were trained to become discriminant, repeatable and in consensus for the rating of a given shoe feature. Finally, after running with a shoe model, participants rated the shoe feature intensity on a linear scale. The order of shoe models was balanced to avoid any effect of rank, sequence and fatigue. Each footwear model was available in four copies to limit alterations of shoe properties due to repetitive use. All the shoe models were blinded to avoid any effect of shoe design on the sensory evaluation. ‘Heel penetration’ was the explicit shoe feature understood by all participants to describe shoe cushioning. Panel performances were statistically verified. A significant correlation was highlighted and enabled to predict users’ perception of heel penetration based on shoe absolute maximal compression (r = 0.86, p = 6.9 × 10−4). The sensory trained panel method seemed powerful to quantify the perception of shoe features and could be used for other purposes than correlation between sensory and mechanical data.
Is operational research in UK universities fit-for-purpose for the growing field of analytics?

Over the last decade considerable interest has been generated into the use of analytical methods in organisations. Along with this, many have reported a significant gap between organisational demand for analytical-trained staff, and the number of potential recruits qualified for such roles. This interest is of high relevance to the operational research discipline, both in terms of raising the profile of the field, as well as in the teaching and training of graduates to fill these roles. However, what is less clear, is the extent to which operational research teaching in universities, or indeed teaching on the various courses labelled as analytics , are offering a curriculum that can prepare graduates for these roles. It is within this space that this research is positioned, specifically seeking to analyse the suitability of current provisions, limited to master s education in UK universities, and to make recommendations on how curricula may be developed. To do so, a mixed methods research design, in the pragmatic tradition, is presented. This includes a variety of research instruments. Firstly, a computational literature review is presented on analytics, assessing (amongst other things) the amount of research into analytics from a range of disciplines. Secondly, a historical analysis is performed of the literature regarding elements that can be seen as the pre-cursor of analytics, such as management information systems, decision support systems and business intelligence. Thirdly, an analysis of job adverts is included, utilising an online topic model and correlations analyses. Fourthly, online materials from UK universities concerning relevant degrees are analysed using a bagged support vector classifier and a bespoke module analysis algorithm. Finally, interviews with both potential employers of graduates, and also academics involved in analytics courses, are presented. The results of these separate analyses are synthesised and contrasted. The outcome of this is an assessment of the current state of the market, some reflections on the role operational research make have, and a framework for the development of analytics curricula. The principal contribution of this work is practical; providing tangible recommendations on curricula design and development, as well as to the operational research community in general in respect to how it may react to the growth of analytics. Additional contributions are made in respect to methodology, with a novel, mixed-method approach employed, and to theory, with insights as to the nature of how trends develop in both the jobs market and in academia. It is hoped that the insights here, may be of value to course designers seeking to react to similar trends in a wide range of disciplines and fields.
A new method of sensing matrix optimization for compressive sensing

Compressive sensing (CS) as a new signal acquisition protocol has been applied widely in numerous application areas such as medical imaging, cryptography, biometrics, communications, wireless sensor networks and internet of things. One problem of CS systems is how to design a suitable sensing matrix to improve the signal reconstruction accuracy with the same number of measurements. The recent method to optimize the sensing matrix is by minimizing the mutual coherence of the equivalent dictionary and the amplified sparse representation error (SRE). This paper proposes a new method of sensing matrix optimization by introducing the relative amplified SRE parameter and incorporate it into the optimization problem. The experimental results with test patches and natural images show that the CS system by using the proposed optimized sensing matrix can decrease the mutual coherence and the amplified SRE. The PSNR of reconstructed test patches and natural images for 25% compression ratio are 27.06 dB and 28.32 dB respectively. The results also demonstrate that the proposed method outperforms the previous ones in terms of image reconstruction accuracy.
Optimal design of a compact passive magnetic bearing based on dynamic modelling

Passive magnetic bearings offer significant advantages relative to common active magnetic bearings, such as simple, robust, and efficient structure. Permanent magnet (PM) passive magnetic bearings are composed of opposing magnet rings on rotor and stator. Although their stiffness has been improved using alternating or Halbach magnetisations in many previous studies, they still suffer from lack of damping force. In this study, the optimal design is focused on a combination of PM bearing and eddy current damper by adding a conductive layer along the magnets of the stator or rotor. This will moderate the magnetic material consumptions; thereby, the cost and overall size of the bearing are reduced. A complete analytical method is performed to calculate the stiffness and axial, radial, and rotating damping coefficients. The accuracy of the analytical model is estimated quantitatively using 3D finite element method simulations. Moreover, all of the parameters are normalised and optimised for maximum stiffness and damping.
Simulation of Thermal Behaviour of a Lithium Titanate Oxide Battery

One of the reasonable possibilities to investigate the battery behaviour under various temperature and current conditions is the development of a model of the lithium-ion batteries and then by employing the simulation technique to anticipate their behaviour. This method not only can save time but also they can predict the behaviour of the batteries through simulation. In this investigation, a three-dimensional model is developed to simulate thermal and electrochemical behaviour of a 13Ah lithium-ion battery. In addition, the temperature dependency of the battery cell parameters was considered in the model in order to investigate the influence of temperature on various parameters such as heat generation during battery cell operation. Maccor automated test system and isothermal battery calorimeter were used as experimental setup to validate the thermal model, which was able to predict the heat generation rate and temperature at different positions of the battery. The three-dimensional temperature distributions which were achieved from the modelling and experiment were in well agreement with each other throughout the entire of discharge cycling at different environmental temperatures and discharge rates.
EventHD: Robust and efficient hyperdimensional learning with neuromorphic sensor

Brain-inspired computing models have shown great potential to outperform today's deep learning solutions in terms of robustness and energy efficiency. Particularly, Hyper-Dimensional Computing (HDC) has shown promising results in enabling efficient and robust cognitive learning. In this study, we exploit HDC as an alternative computational model that mimics important brain functionalities toward high-efficiency and noise-tolerant neuromorphic computing. We present EventHD, an end-to-end learning framework based on HDC for robust, efficient learning from neuromorphic sensors. We first introduce a spatial and temporal encoding scheme to map event-based neuromorphic data into high-dimensional space. Then, we leverage HDC mathematics to support learning and cognitive tasks over encoded data, such as information association and memorization. EventHD also provides a notion of confidence for each prediction, thus enabling self-learning from unlabeled data. We evaluate EventHD efficiency over data collected from Dynamic Vision Sensor (DVS) sensors. Our results indicate that EventHD can provide online learning and cognitive support while operating over raw DVS data without using the costly preprocessing step. In terms of efficiency, EventHD provides 14.2× faster and 19.8× higher energy efficiency than state-of-the-art learning algorithms while improving the computational robustness by 5.9×.
Does hand modulate the reshaping of the attentional system during rightward prism adaptation? An fMRI study

Adaptation to right-deviating prisms (R-PA), that is, learning to point with the right hand to targets perceived through prisms, has been shown to change spatial topography within the inferior parietal lobule (IPL) by increasing responses to left, central, and right targets on the left hemisphere and decreasing responses to right and central targets on the right hemisphere. As pointed out previously, this corresponds to a switch of the dominance of the ventral attentional network from the right to the left hemisphere. Since the encoding of hand movements in pointing paradigms is side-dependent, the choice of right vs. left hand for pointing during R-PA may influence the visuomotor adaptation process and hence the reshaping of the attentional system. We have tested this hypothesis in normal subjects by comparing activation patterns to visual targets in left, central, and right fields elicited before and after adaptation to rightward-deviating prisms using the right hand (RWRH) with those in two control groups. The first control group underwent adaptation to rightward-deviating prisms using the left hand, whereas the second control group underwent adaptation to leftward-deviating prisms using the right hand. The present study confirmed the previously described enhancement of left and central visual field representation within left IPL following R-PA. It further showed that the use of right vs. left hand during adaptation modulates this enhancement in some but not all parts of the left IPL. Interestingly, in some clusters identified in this study, L-PA with right hand mimics partially the effect of R-PA by enhancing activation elicited by left stimuli in the left IPL and by decreasing activation elicited by right stimuli in the right IPL. Thus, the use of right vs. left hand modulates the R-PA-induced reshaping of the ventral attentional system. Whether the choice of hand during R-PA affects also the reshaping of the dorsal attentional system remains to be determined as well as possible clinical applications of this approach. Depending on the patients' conditions, using the right or the left hand during PA might potentiate the beneficial effects of this intervention.