Miracle-dz/UniFAR-FTUs huggingface dataset:
Cyclic LRC codes with hierarchy and availability

Locally recoverable (LRC) codes and their variants have been extensively studied in recent years. In this paper we focus on cyclic LRC codes, presenting two results regarding codes with hierarchical locality and codes with availability. Regarding hierarchical LRC codes, we observe that the cyclic codes of Tamo et al. (2016) can be generalized to yield optimal families with multiple levels of locality for a broader range of parameters than known previously. We also observe that the general approach to cyclic codes with locality can be extended to multidimensional cyclic codes, yielding new families of LRC codes with availability.
Evaluation of Frequency-Dependent Effects of Deep Brain Stimulation in a Cortex-Basal Ganglia-Thalamus Network Model of Parkinson’s Disease*

Parkinson’s disease (PD) is a chronic neurodegenerative disease whose motor symptoms are accompanied by an exaggerated power in the alpha-beta (7-35Hz) band and an increased synchronization of neurons encompassing the cortex-basal ganglia-thalamus network. Currently, deep brain stimulation (DBS) is used as an effective therapy for reducing the excessive power and synchrony observed in brain circuits, thereby ameliorating the PD symptoms. In the present study, we used a biologically plausible computational model of cortex-basal ganglia-thalamus network, which represents both healthy and PD conditions, to systematically investigate the effects of DBS frequency on the model outputs. DBS was applied to the subthalamic nucleus (STN) at different stimulation frequencies (40Hz to 300Hz). Spike train variability and spectral power in the 7-35Hz band were measured from the several nuclei represented in the model. In addition, the magnitude squared coherence between the nuclei was assessed. An increased DBS frequency tended to produce interspike intervals (ISIs) with higher variability as compared to PD condition. Also, DBS significantly reduced the alpha-beta power for almost all brain nuclei. The median of the magnitude-squared coherence matrix (which is a metric of global network synchronization) decreased significantly with the increase of DBS frequency.
Impact of Encapsulation Tissue Growth on Selective Recording in Nerve Cuff Electrodes: A Simulation Study

Peripheral nerve interfaces (PNIs) allow us to extract motor, sensory and autonomic information from the nervous system and use it as control signals in neuroprosthetic and neuromodulation systems. Recent efforts have aimed to improve the recording selectivity of PNIs, including by using spatiotemporal patterns from multi-contact nerve cuff electrodes as input to a convolutional neural network (CNN). Before such a methodology can be translated to humans, its performance in chronic implantation scenarios must be evaluated. We investigated the performance of a CNN-based selective recording approach in the presence of encapsulation tissue, a common immune response to the implantation of a neural interface. This factor was simulated using anatomically accurate computational models of a rat sciatic nerve and nerve cuff electrode. Performance over time was examined in three conditions: training the CNN at baseline only, supervised retraining with explicitly labeled data at periodic intervals, and a semi-supervised self-learning approach. The periodic recalibration approach demonstrated the best results, with an average F1-score of 0.96 ± 0.04, 0.89 ± 0.08, and 0.80 ± 0.08 for SNRs of -5 dB, -10 dB, and -15 dB, respectively, across all time points. Thus, the periodic recalibration approach may be an effective solution to compensate for changes in signal recordings seen over time as a result of encapsulation tissue. The self-learning approach, in which a network is retrained periodically using predicted labels, generally showed degradation in classification performance over time, even as the frequency of training was increased, attributed to an eventual accumulation of mislabeled training data.
Biomechanical parameters assessment for the classification of Parkinson Disease using Bidirectional Long Short-Term Memory*

Nowadays objective and efficient assessment of Parkinson Disease (PD) with machine learning techniques is a major focus for clinical management. This work presents a novel approach for classification of patients with PD (PwPD) and healthy controls (HC) using Bidirectional Long Short-Term Neural Network (BLSTM). In this paper, the SensHand and the SensFoot inertial wearable sensors for upper and lower limbs motion analysis were used to acquire motion data in thirteen tasks derived from the MDS-UPDRS III. Sixty-four PwPD and fifty HC were involved in this study. One hundred ninety extracted spatiotemporal and frequency parameters were applied as a single input against each subject to develop a recurrent BLSTM to discriminate the two groups. The maximum achieved accuracy was 82.4%, with the sensitivity of 92.3% and specificity of 76.2%. The obtained results suggest that the use of the extracted parameters for the development of the BLSTM contributed significantly to the classification of PwPD and HC.
A Low-Power gm-C Filter for Neural Signal Conditioning

Neural recording interfaces are being developed to record neuronal activities of the brain for several decades. There is a stringent requirement to provide conditioning to the weak neural signals. However, various analog designers come across a major challenge of lowering down the values of power consumption by the neural signal conditioning stage owing to the noise and bandwidth trade-offs to power. As an anticipated solution to the same, the design of low-noise operational-transconductance amplifier (OTA) - Capacitor filter or gm-C filter capable of passing EEG signals has been presented in this paper. The reported gm-C filter which relies on Gate-Capacitive Bulk-Driven and current-division technique has been implemented in Cadence Analog Design Platform using standard 0.18 μm CMOS process with BSIM3V3 models of transistors. The simulation results indicate that the proposed circuit draws a very low power (0.368 μW) from the power supply of ± 0.5 V with the total-integrated input referred noise voltage of 4.6 μVRMS and -3 dB frequency of 56.2 Hz. The suggested architecture design of the demonstrated conditioning stage may be useful in the field of low-power neuroprosthetic applications.
NOMA-based Joint One-Way and Two-Way Relaying Aided Finite Blocklength Communication

This work considers a finite blocklength (FBL) non-orthogonal multiple access (NOMA)-based joint one-way and two-way relaying aided communication scheme wherein two source nodes share a single decode-and-forward (DF) relay to exchange their information as well as transmit it to the respective destination nodes over a finite number of channel uses. Novel closed-form expressions have been obtained for the end-to-end block error rate (BLER) at all the nodes and also the net throughput of the system. Furthermore, an asymptotic end-to-end BLER floor has also been obtained for all the nodes at high transmit signal to noise power ratio (SNR). Simulation results are presented to authenticate the analytical results derived and demonstrate the efficacy of the proposed scheme.
Identification of astrocytic factors that could play a role in myelination

Multiple sclerosis (MS) is generally considered to be an autoimmune disease; it results in areas of focal demyelination known as plaques, where astrocytes are the main constituent and appear hypertrophic and stellate with increased expression of glial fibrillary acidic protein (GFAP). Although these reactive astrocytes can be beneficial for encapsulating areas of tissue necrosis within the glial scar, the pro-inflammatory cytokines and extracellular molecules they secrete are thought to be inhibitors of remyelination. Conversely, astrocytes can secrete anti-inflammatory cytokines in their less activated state and thereby can be beneficial for remyelination; although the mechanisms involved are not clearly understood. We have developed myelinating cultures of embryonic rat mixed spinal cord cells that are plated on neurosphere-derived astrocyte monolayers, which allow us to manipulate their reactive state and determine any effects of these astrocytes on myelination. To identify any differences in gene expression profiles of several purified astrocyte phenotypes we carried out a microarray analysis using myelinating cultures plated on astrocytes on poly-L-lysine (PLL-astrocytes) or on tenascin C (TnC-astrocytes), untreated or treated with ciliary neurotrophic factor (CNTF) since it was previously shown that CNTF could stimulate myelination in these myelinating cultures and that TnC-astrocytes supported myelination less than PLL-astrocytes. The microarray analysis suggested CCL2, CCL7 and SERPINB2 as potential myelination regulators, which were validated by qRT-PCR but failed to affect axonal ensheathment in myelinating cultures. A metabolomics analysis was also carried out using untreated or CNTF-treated PLL- and TnC-astrocytes. A list of metabolites were associated with different astrocyte phenotypes and highlighted the importance of lipid metabolism, which might be crucial for stimulating myelination. These in vitro astrocyte phenotypes were compared with previously identified in vivo astrocyte reactivity markers, which suggested that PLL- and TnC-astrocytes could reflect in vivo astrocytes to some extent and that TnC-astrocytes might not be as “quiescent” as currently considered. It is possible that TnC-astrocytes suppress myelination by creating an extracellular matrix (ECM) rich environment, while CNTF dissolves the ECM and thus creates a more regenerative environment. Despite similar stimulatory effects of CNTF on mixed neural cells on PLL and TnC, CNTF appears to affect them via different mechanisms showing that distinct reactive astrocytes could react to the same stimulus in different ways as also presented in in vivo studies.
A Combination of Frequent Pattern Mining and Graph Traversal Approaches for Aspect Elicitation in Customer Reviews

Due to the remarkable increase in e-commerce transactions, people try to have an appropriate choice of purchase through considering other people’s reflected experience in product’s or service’s reviews. Automatic analysis of such corpus requires enhanced developed algorithms based on natural language processing and opinion mining. Moreover, the linguistic differences make extending existing algorithms from one language to another challenging and in some cases impossible. Opinion mining focuses on different subjects of review analysis such as spam detection, aspect elicitation and polarity allocation. In this article, we focus on detection of explicit aspect and propose a methodology to overcome some difficult and problematic aspect compounds in the form of multi- words format in Persian language. Our approach proposes the construction of a directed weighted graph (ADG structure) based on some yielded information from FP-Growth frequent pattern identification algorithm on our corpus of Persian sentence. Traversing some special paths within the ADG graph according to our developed rules could lead us to the extraction of problematic multi-word aspects. We utilize Neo4j NoSQL graph database environment and its Cypher query language in order to create the ADG graph and access the desired paths that reflects our developed rules on the ADG structure which lead us to extract the multi-word aspects. The evaluation of our methodology with the existing approaches on the issue of aspect derivation in Persian language including ELDA, SAM, an MMI-based and an LRT-based algorithms indicates the robustness of our approach.
In vitro assessment of the role of the nucleus pulposus in the mechanism of vertebral body fracture under dynamic compressive loading using high-speed cineradiography

Traumatic Spinal Cord Injuries (TSCI) have a disastrous effect on the physical and mental health of both the patients and their relatives. Around 15 % of these injuries are caused by burst fractures, a sub-type of compressive fractures of the vertebral body. The transient dynamics of these fracture have been studied through in vitro experiments coupled with numerical simulations, but no direct observation have ever been made of their genesis and evolution and the behaviour of the nucleus pulposus under compressive loading has only been hypothesized. The purpose of this study was to evaluate the interactions between the vertebral body and the nucleus pulposus under dynamic compressive loading using high-speed cineradiography. A radiopaque agent was injected into the nuclei pulposi of 4 young porcine thoraco-lumbar and lumbar cadaveric segments, and a dynamic compressive load was applied to them using a servo-hydraulic bench-test. The compression process was filmed with a custom high-speed fluoroscope. The nucleus pulposus loaded the vertebral endplate up to 14,142 ± 486 N, before fracturing it and diffusing into the vertebral body. Then, internal pressure seemingly built up until an outward projection of the nucleus pulposus, at an antero-posterior velocity up to 2.9 m.s-1, or until retroprojection of bony fragments into the spinal canal. These results directly corroborate the hypotheses previously made by other studies and stress the unprecedented advantages of using high-speed cineradiography for the study of complex fractures genesis and evolution.Clinical Relevance— Methodology and results from this study would provide an unprecedented insight on the genesis and transient evolution of complex spinal fractures.
Thermo-Double Diffusion Radiation Effects on the flow of Casson fluid in the Presence of Porous Media and Magnetic field over a stretching Sheet

The present study aims at investigating numerically the doubly stratified Casson nanofluid past a stretching sheet with convective heating boundary conditions. The nanofluid incorporates the effects of Brownian motion and thermophoresis. Governing equations are incorporated with thermo-diffusion, thermal radiation effects, heat absorption, viscous dissipation, the chemical reaction in the presence of porous media and magnetic field. Suitable similarity transformations are used to convert the nonlinear PDEs into a similar set of non-linear ODEs. Numerical solutions of the reduced governing equations are obtained through the BVP4C code of MATLAB. The effects of various parameters on the flow field namely, velocity, temperature, and spices concentration are depicted in graphs. Further, the skin friction, heat and mass effects against various parameters of the model are calculated and presented in the table. It is worthwhile to mention here that the present study has many engineering and industrial applications such as controlling cooling effects, MHD propulsion, paper production, material processing, etc.
Empirical study of fuzzy quantification models for linguistic descriptions of meteorological data

In this work we present an experimental comparison of six widely used quantification methods (Zadeh’s scalar and fuzzy cardinality, Yager’s OWA, Delgado’s GD, Sugeno integral and Vila’s VQ) when evaluating Type-1 and Type-2 linguistic descriptions of data generated from meteorological data provided by the Galician Meteorological Agency MeteoGalicia. The objective of this study is to evaluate if there are significant differences among these models for the data considered. We ranked the generated descriptions based on their degree of truth for each quantification model and we analyzed those results calculating the Pearson correlation coefficient. Results show that there are not significant differences in the models when evaluating Type-1 descriptions. However, in Type-2 evaluation the methods can be grouped in three clusters with a significantly different behavior among them: i) Zadeh’s scalar cardinality, Delgado’s GD and Zadeh’s fuzzy cardinality, ii) Yager’s method and iii) Vila’s VQ.
Efficient Beamforming Training and Limited Feedback Precoding for Massive MIMO Systems

In cellular communications, deploying a larger number of antennas at the base station, also called massive multiple-input multiple-output (MIMO), can offer a significant improvement in system throughput. In this paper, we exploit the spatial fading correlations in massive MIMO to reduce the downlink training and the corresponding feedback overhead in frequency division duplexing systems. We first study the user clustering, where the users with similar spatial channel correlations are clustered together. In the study, we provide the optimal metric and prove the convergence of the user clustering. Then, we propose an efficient eigenspace training and precoding (EETP) framework, where two different prebeamforming matrices are designed to minimize the channel estimation error and to manage the inter-user interference, respectively. In the results, we show that the channel estimation error for EETP decreases monotonically when either the number of prebeamforming vectors or the number of clusters increases. The spectral efficiency of the new algorithms is evaluated extensively with different user distributions, errors in channel correlations, different numbers of clusters, and different coherence block lengths, as well as with dynamic user scheduling for a large number of users. The new EETP not only achieves significant savings in the downlink training and the corresponding feedback, but also offers significantly higher system throughput compared with the existing schemes in the literature.
A Modular Open Source Health Monitoring Garment*

The ability to monitor physiological parameters in an individual is paramount for the evaluation of physical health and the detection of health ailments. Wearable technologies are being introduced on a widening scale to address the absence of modular, accessible, and non-invasive health monitoring as compared to medical grade technologies. In this work, an open source wearable garment is presented that is capable of addressing the absence of such a device. The garment is currently capable of recording electrocardiography, photoplethysmography, galvanic skin response, skin temperature, and respiration rate. The garment has a modular and scalable interface to allow for reconfiguration or expansion of sensor modalities at a total component cost of $137. In a small scale study, the garment is able to reveal strong correlation between heart rate and self perceived stress (R = 0.75, p < .001), showing promise in its ability to capture clinically-relevant physiological information. Based on these results, continued effort will be made to compile a wearable array of sensors tailored to monitor parameters of specific clinical interest.
Reply

We agree with most of Boylan et al’s points regarding our study: (1) modeling generic–generic formulation differences from bioequivalence (BE) studies introduces variability and may overestimate potential concentration changes during switches between generic antiepileptic drug (AED) formulations; (2) the clinical relevance of pharmacokinetic (PK) differences between generic formulations should be evaluated in clinical PK studies; and (3) individual patient factors such as dosing needs, drug tolerability, and pharmacologic properties of specific drugs may dominate effects of formulation differences. We also would agree that most patients with epilepsy can be treated with relatively inexpensive generic formulations. This is particularly true because of newly available extended-release generic formulations of several AEDs that may improve drug delivery and adherence. These points, however, do not address several potential clinical problems with AED formulation switches:
La morera (Morus spp.) como recurso forrajero: Avances y consideraciones de investigación

The review its related to the taxonomy, ecology, origin and distribution, main species and uses of Mullberry (Morus spp.). Some representative results obtained in recent decades, mainly in the agronomy, phytochemistry and animal production, considering its potential as a forage species are presented. Additionally, issues related to the main investigated topics and some areas of knowledge which should be further studied in the coming years are discussed.
Reply

There is no doubt that the development of diagnostic criteria has contributed greatly to epidemiological research in prion diseases, and Heath and colleagues emphasize this in surveillance studies of variant Creutzfeldt-Jakob disease (vCJD). We caution, however, against a more broad application in clinical practice, particularly in governing decisions about clinical diagnosis, communication with patients/caregivers, and access to experimental therapies. The physician looking after a young patient with an unexplained rapidly progressive neuropsychiatric syndrome, dementia, or ataxia needs to make prompt clinical decisions. There are treatable alternative diagnoses, and an early firm diagnosis is essential. The pulvinar sign on magnetic resonance imaging is often not identified when patients are first imaged, and a requirement for a clinical duration of 6 months or greater makes a probable diagnosis impossible in the early stages of disease. Physicians who have cared for families affected by vCJD are aware of the complicated psychological issues generated by the perceived mismanagement of the bovine spongiform encephalopathy epidemic, which are often exacerbated by a delay or equivocation about diagnosis. Several families also choose experimental intracerebroventricular pentosan polysulfate therapy, which requires neurosurgery. In the context of these issues, the role of tonsillar biopsy is underemphasized by Heath et al and the criteria. In our experience of 60 biopsies, by far the largest series worldwide, tonsillar biopsy has 100% sensitivity and specificity, at any stage of the disease. Prion protein deposition in the tonsil can be patchy, and at least 20 germinal centers need to be examined. The number examined in 1 French case reported by Heath et al may not have been adequate to avoid a false-negative result. It is notable that of the 6 most recent patients suspected clinically of having vCJD in the United Kingdom, 3 did not meet epidemiological criteria for probable vCJD while alive. Two of these patients would have been misdiagnosed as sporadic CJD according to the updated clinical diagnostic criteria for sporadic Creutzfeldt-Jakob Disease criteria; typical vCJD was diagnosed at autopsy in both. In a third patient, with a heterozygous codon 129 genotype reported by Kaski et al, the pulvinar sign was not thought to be present by all neuroradiologists, and no tissue was examined. It is reasonable to expect that tonsillar biopsy may have made the correct diagnosis in each of these cases. Given experience with transfusion-associated secondary vCJD, vCJD prions are likely to be present in significant titer in human blood, a diagnostic blood test based on detection of the infectious agent is clearly possible in principle, and if technologically achieved, will necessitate a complete revision of how we approach diagnosis in this disease.