Miracle-dz/UniFAR-FTUs huggingface dataset:
Hormones in experimental autoimmune encephalomyelitis (EAE) animal models

Abstract Multiple sclerosis (MS) is an inflammatory demyelinating disease of the central nervous system (CNS) in which activated immune cells attack the CNS and cause inflammation and demyelination. While the etiology of MS is still largely unknown, the interaction between hormones and the immune system plays a role in disease progression, but the mechanisms by which this occurs are incompletely understood. Several in vitro and in vivo experimental, but also clinical studies, have addressed the possible role of the endocrine system in susceptibility and severity of autoimmune diseases. Although there are several demyelinating models, experimental autoimmune encephalomyelitis (EAE) is the oldest and most commonly used model for MS in laboratory animals which enables researchers to translate their findings from EAE into human. Evidences imply that there is great heterogeneity in the susceptibility to the induction, the method of induction, and the response to various immunological or pharmacological interventions, which led to conflicting results on the role of specific hormones in the EAE model. In this review, we address the role of endocrine system in EAE model to provide a comprehensive view and a better understanding of the interactions between the endocrine and the immune systems in various models of EAE, to open up a ground for further detailed studies in this field by considering and comparing the results and models used in previous studies.
High-dimensional Channel Estimation for Simultaneous Localization and Communications

Simultaneous localization and communication (SLAC) is a desirable feature of 5G and beyond 5G wireless networks. To be able to implement SLAC, efficient high dimensional channel estimation methods are critical. This work presents a low-complexity multidimensional channel parameter estimation via rotational invariance techniques (MD-ESPRIT). We use both the spatial smoothing and forward-backward averaging techniques to further explore data samples to extract multipath components (MPCs). We propose a one-dimensional Fast-Fourier-Transform- (FFT) and inverse-FFT-based approach to obtain the signal subspaces for angular frequency estimation. The geometry relationship between MPCs and positions is utilized for simultaneous positioning and mapping. Numerical results demonstrate the improved identifiability and low complexity performance of the proposed scheme.
Arbuscular mycorrhizal fungi species differentially regulate plant growth, phosphorus uptake and stress tolerance of soybean in lead contaminated soil

Abstract Arbuscular mycorrhizal fungi (AMF) symbiosis can enhance plant growth in unfavorable conditions. However, functional variations among different AMF species for their ability to enhance phosphorus (P) uptake and soybean tolerance in lead (Pb) contaminated soil have rarely been examined. The present study therefore aimed to compare the growth, P uptake and Pb tolerance of soybean plants colonized by different AMF and to test the relationship between P uptake efficiency and Pb uptake in Pb contaminated soil. Soybean inoculated with three different AMF, Funneliformis mosseae, Claroideoglomus etunicatum, and Rhizophagus intraradices and control was grown under three Pb addition levels (0, 100 and 300 mg kg−1) in a pot experiment. The results showed that AMF inoculation significantly promoted the plant growth, P uptake and Pb accumulation in the roots, with less translocation of Pb from roots to the shoots compared to non-inoculated plants. Soybean plants inoculated with R. intraradices were more tolerant to Pb toxicity compared with other two AMF species in terms of higher root colonization, biomass, P uptake and seed yield. Significant linear correlations were observed between biomass, P uptake and Pb uptake of the plant. The findings in this study are essential in using AMF to promote soybean growth and P uptake in heavy metal-contaminated soils. Moreover, symbiotic P uptake and retention of Pb in roots of plants could serve as important criteria for screening of efficient AMF species or isolates for plant growth, P nutrition and metal tolerance in heavy metal contaminated soils.
Orthogonal Time Sequency Multiplexing Modulation

This paper proposes orthogonal time sequency multiplexing (OTSM), a novel single carrier modulation scheme based on the well known Walsh-Hadamard transform (WHT) combined with row-column interleaving, and zero padding (ZP) between blocks in the time-domain. The information symbols in OTSM are multiplexed in the delay and sequency domain using a cascade of time-division and Walsh-Hadamard (sequency) multiplexing. By using the WHT for transmission and reception, the modulation and demodulation steps do not require any complex multiplications. We then propose two low-complexity detectors: (i) a simpler non-iterative detector based on a single tap minimum mean square time-frequency domain equalizer and (ii) an iterative time-domain detector. We demonstrate, via numerical simulations, that the proposed modulation scheme offers high performance gains over orthogonal frequency division multiplexing (OFDM) and exhibits the same performance of orthogonal time frequency space (OTFS) modulation, but with lower complexity. In proposing OTSM, along with simple detection schemes, we offer the lowest complexity solution to achieving reliable communication in high mobility wireless channels, as compared to the available schemes published so far in the literature.
Adversarial, yet Friendly Signal Design for Secured Wireless Communication

Whenever wireless communication link becomes a unique communication means, ensuring security is just as important as achieving fast and reliable communication especially for military and medical systems. A common approach for secure wireless communication is via encryption of the information but this may fail to provide complete security (e.g., vulnerable to side-channel attack) especially when it comes with computation-limited scenarios such as Internet of Things (IoT) case. A simpler, yet powerful alternative technique to improve security is by preventing eavesdroppers from knowing correct modulation and coding (MCS) scheme. In traditional wireless communication systems, this MCS information can be secured based on sophisticate design of mutually cooperative strategies between the transmitter and the receiver. However, for deep learning (DL)-based wireless communication systems, this cooperation can be significantly simplified by just adding a well-designed adversarial signal to the transmitted signal. In this paper, we propose a novel, transferable adversarial signal design that simultaneously prevents non-cooperative eavesdroppers from achieving correct modulation scheme while ensuring the intended, cooperative receiver’s correct acquisition of the modulation scheme. Extensive numerical results validate secrecy of the proposed scheme along with transferability.
Decentralized Reinforcement Learning Based Anti-Jamming Communication for Self-Organizing Networks

This paper investigates the problem of decentralized spectrum sharing in self-organizing networks against a dynamic and unknown jamming environment using reinforcement learning. In the network, the anti-jamming spectrum sharing has to not only coordinate spectrum access of users, but also combat the malicious jamming. However, most existing anti-jamming approaches are centralized and require information exchange, which are not suitable for decentralized self-organizing networks in the jamming environment. We formulate the multiuser anti-jamming channel selection problem as a Markov game, and propose a decentralized deep reinforcement learning based collaborative anti-jamming algorithm to achieve the equilibrium solution. It is shown in the simulation part that without information exchange, the approach enables multiple users to independently explore the spectrum environment and obtain effective (close to optimal) collaborative anti-jamming strategies against unknown and dynamic jamming.
Low-Complexity Precoding for Millimeter Wave MIMO Systems with Finite Alphabet Inputs

This paper considers low-complexity hybrid analog-digital precoding for millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems with finite alphabet inputs. We analyze the mutual information with finite alphabet inputs in the extreme signal-to-noise ratio (SNR) region. At low SNR, we find out that it is optimal to transmit signals through its strongest sub-channel, and thus formulate the analog precoding problem as a single-variable optimization problem. An iterative coordinate descent algorithm is developed to obtain the near-optimal hybrid precoder. At high SNR, the mutual information degrades when the Gaussian scheme is directly applied into the practical systems with finite alphabet inputs. Therefore, a modified fully-digital precoder is proposed to improve the mutual information. Numerical results validate that the proposed schemes achieve a good trade-off between mutual information and computational complexity.
WiLAR: A Location-adapted Action Recognition System based on WiFi

In modern society, wireless signals are ubiquitous in various indoor environments, such as living houses, offices and shop malls, facilitating human living in various aspects. Action recognition is a technique in roaring demand in the field of human-computer interaction. Whereas previous research studies propose various methods to action recognition using wireless signals, action recognition in locations with limited data is still very challengeable. To realize decent action recognition with the help of wireless signals, we propose WiLAR, a location-adapted action recognition system based on WiFi, which enables action detection, segmentation and recognition with commodity WiFi devices in locations with different amounts of data. WiLAR extracts informative features from fine-grained WiFi channel state information (CSI), and then feeds features into elaborately designed deep learning models to realize action recognition in different locations. In our dedicated experiments, WiLAR achieves average 97% accuracy workout recognition in locations with plenty of data, and also outperforms other recognition models in locations with limited training data.
Political discourse of history and action in the political project of José De Alencar during imperial Brazil

ABSTRACT José de Alencar (1829–1877) is one of the most relevant names in Brazilian Romantic literature of the nineteenth century, and an important politician of the Conservative Party. This work attempts to provide a glimpse of major influences from European Romanticism, highlighting the way it brought a Christian notion of a linear and positivist history to Brazilian political arena. A documental research is made on two non-literary publications: Systema Representativo (1868) and A Propriedade (posthumously published in 1883) seeking to pinpoint the notion of iconic linear time as an ideological colonisation of political discourses through the Romantic stylistic approach of Alencar.
Hybrid Mean Variance Mapping Optimization Algorithm for Solving Stochastic Based Dynamic Economic Dispatch Incorporating Wind Power Uncertainty

Abstract This paper presents a model for studying the dynamic economic load dispatch problem in power system including conventional thermal generators and wind turbines. The problem is solved using the hybrid variant Mean Variance Mapping Optimization technique. Due to the stochastic nature of wind speed, the Weibull distribution parameters of wind speed are obtained for different time intervals (24 hours). Consequently, the probability density function for the output wind power is achieved for each hour separately. The constraints for the thermal generators are considered including generation limits, ramp rate limits, valve-point loading and spinning reserve. The optimization problem is solved for different scenarios and total operating cost obtained shows the effect of wind power penetration as well as the overestimate and underestimate power probabilities.
The (Non-)Adoption of Participatory Newsroom Innovations under Authoritarian Rule: How Comment Sections Diffused in Belarus and Azerbaijan (1998–2017)

Abstract Extant research on how innovations diffuse among news organizations over time has largely focussed on democratic contexts. By contrast, this is the first longitudinal study to investigate the spread of a participatory newsroom innovation under authoritarian rule. Adopting a multiple case study design, the article reconstructs the histories of comment sections on the opinion-leading online media in two authoritarian contexts, which varied maximally with regard to the outcome of the diffusion process. In Belarus, the diffusion process followed a classic S-shaped curve of adoption, whereas in Azerbaijan adoption rates remained low during the studied period. The study identified primarily three factors that obstructed the diffusion process in Azerbaijan: (1) the restrictive policy of the authoritarian leadership specifically towards audience participation on news websites (social system), (2) the low intensity of communicative exchange between local and foreign news organizations (communication channels), (3) the advent of the successor technology in 2010 (time).
Factors influencing individual ability to follow physical distancing recommendations in Aotearoa New Zealand during the COVID-19 pandemic: a population survey

ABSTRACT Physical distancing (also commonly known as social distancing) is an important non-pharmaceutical strategy to minimise the risk of transmission of SARS-CoV-2 virus. A range of restrictions to promote physical distancing form a key part of the Aotearoa New Zealand (NZ) all-of-government response to the global COVID-19 pandemic. The effectiveness of physical distancing strategies is highly dependent on buy-in and the actions of individuals, households and communities. This NZ population survey was conducted to identify people’s views on the effectiveness of various strategies, and factors impacting on their capacity to follow physical distancing requirements during Alert Levels 4, 3, and 2 (April 24th–June 8th 2020). The majority of the 2407 participants were supportive of the public health measures implemented to promote physical distancing across Alert Levels. Few substantial differences were observed in relation to demographic characteristics, suggesting high overall levels of understanding and willingness to adhere to distancing requirements. Around half of the participants reported difficulties practicing physical distancing when in public. Reasons included being an essential worker and challenges related to the behaviour of others. These survey findings highlight the willingness of NZ’s population to play their part in eliminating COVID-19 transmission, and the way in which behavioural change was rapidly adopted in line with government requirements.
Biochar as a substitute for inorganic fertilizer: Effects on soil chemical properties and maize growth in Ghana

Abstract Owing to the benefits of biochar in soil sustainability, this study considered the effect of applying rice husk biochar as a substitute for inorganic fertilizer on soil properties and maize growth in Ghana. Six treatments (comprising of five rice husk biochar rates and one rate of NPK inorganic fertilizer as control) with four replicates in a pot experiment and “Obaatanpa” maize variety were used for the study. Results showed that the incorporation of biochar increased soil pH, organic carbon and effective cation exchange capacity for the various treatments which were higher than NPK treatment. Generally, 50 t/ha biochar applied at the time of planting recorded the lowest soil chemical properties which resulted in reduced maize germination count and yield while 50 t/ha biochar applied 2 weeks before planting improved soil chemical properties. Biochar increased all soil chemical properties analyzed more than NPK except for available phosphorus and potassium, which are key nutrients for maize growth. The maize yield in the biochar treatments was significantly lower (by 300%) than the NPK treatment, suggesting that biochar application in the short term, although could increase soil chemical properties, does not translate into essential nutrients available for improving maize yield. Therefore, quantity and incubation time for rice husk biochar before planting has a significant impact on soil nutrient and yield of maize. Future studies should consider the application of biochar at a longer period before planting and in combination with inorganic fertilizer as a top dressing and residual biochar for maize production.
Against Neo-Cartesianism: Neurofunctional Resilience and Animal Pain

ABSTRACT Several influential philosophers and scientists have advanced a framework, often called Neo-Cartesianism (NC), according to which animal suffering is merely apparent. Drawing upon contemporary neuroscience and philosophy of mind, Neo-Cartesians challenge the mainstream position we shall call Evolutionary Continuity (EC), the view that humans are on a nonhierarchical continuum with other species and are thus not likely to be unique in consciously experiencing negative pain affect. We argue that some Neo-Cartesians have misconstrued the underlying science or tendentiously appropriated controversial views in the philosophy of mind. We discuss recent evidence that undermines the simple neuroanatomical structure-function correlation thesis that undergirds many Neo-Cartesian arguments, has an important bearing on the recent controversy over pain in fish, and places the underlying epistemology framing the debate between NC and EC in a new light that strengthens the EC position.
Response of Beta vulgaris L. to nitrogen and micronutrients in dry environment.

Soils in dry environments, including Egypt, have low fertility and poor structure. To enhance soil fertility and crop performance, management technologies such as plant nutrition and suitable cultivars are needed for such environments. To investigate the yield performance under such conditions, two field trials were conducted using two Beta vulgaris cultivars (Amina – V1; BTS 301 – V2), two nitrogen levels (N1 – 200; N2 – 350 kg N/ha) and two micronutrient mixtures (M1 – Fe + Zn + Mn; M2 – tap water). Results indicated that growth and yields and their qualities were positively (P ≤ 0.05 and/or P ≤ 0.01) affected by all factors singly or in various interactions. The best yield performance was obtained with the trilateral interaction application of V2 × N2 × M1. Correlation analysis revealed presence of highly significant r values between white sugar yield and root yield.
Time Distortions: A Systematic Review of Cases Characteristic of Alice in Wonderland Syndrome

Of the perceptual distortions characteristic of Alice in Wonderland syndrome, substantial alterations in the immediate experience of time are probably the least known and the most fascinating. We reviewed original case reports to examine the phenomenology and associated pathology of these time distortions in this syndrome. A systematic search in PubMed, Ovid Medline, and the historical literature yielded 59 publications that described 168 people experiencing time distortions, including 84 detailed individual case reports. We distinguished five different types of time distortion. The most common category comprises slow-motion and quick-motion phenomena. In 39% of all cases, time distortions were unimodal in nature, while in 61% there was additional involvement of the visual (49%), kinaesthetic (18%), and auditory modalities (14%). In all, 40% of all time distortions described were bimodal in nature and 19% trimodal, with 1% involving four modalities. Underlying neurological mechanisms are varied and may be triggered by intoxications, infectious diseases, metabolic disorders, CNS lesions, paroxysmal neurological disorders, and psychiatric disorders. Bizarre sensations of time alteration—such as time going backwards or moving in circles—were mostly associated with psychosis. Pathophysiologically, mainly occipital areas appear to be involved, although the temporal network is widely disseminated, with separate component timing mechanisms not always functioning synchronously, thus occasionally creating temporal mismatches within and across sensory modalities (desynchronization). Based on our findings, we propose a classification of time distortions and formulate implications for research and clinical practice.
A Voronoi-Based User-Centric Cooperation Scheme in Cell-Less Architecture

Along with the dramatic rising of data rate, user-centric network (UCN) is regarded as a promising concept. However, densely deployed same-frequency small base stations (SBSs) in UCN deteriorates the user performance. Coordinated multipoint (CoMP) is an important technique for alleviating inter-cell interference. In this paper, to combat the severe interference, we proposed a user-centric cooperation scheme–Voronoi CoMP in a cell-less architecture. In this scheme, users are assigned their own clusters of SBSs respectively and the clusters for different users are not overlapped. This CoMP structure ensures that each user served by the base stations which are the closest ones of all SBSs to it and this will maximize the useful power of each user and in the meantime minimize the interference. The numerical results and simulations show that the proposed CoMP scheme can indeed promote the performance of dense small cell network (DSCN) corresponding to the designed metrics.
Systematic Review of Psychological and Behavioral Correlates of Recreational Running

Introduction: The aim of this review was to systematically synthesize the published literature describing the psychological and behavioral correlates of recreational running in adults, defined as running for leisure, with or without a competitive component. Methods: Quantitative research published in peer-reviewed journals until January 2021 were included. Studies were identified through MEDLINE, PsycINFO, SPORTDiscus, and Web of Science and were included in this review if they (1) were aimed at recreational running, (2) included general adult samples (18 years or older, without a diagnosed medical condition or metabolic disorder), and (3) assessed psychological or behavioral correlates of recreational running. Results: Fifty-six articles reporting 58 studies met the eligibility criteria and were included. There were 27 cross-sectional studies, 12 longitudinal studies, and 19 trials (8 non-controlled trials, 5 controlled trials, and 6 randomized controlled trials) (n = 37,501, 18–77 years old, 43% women). Twenty-eight studies assessed antecedents of running behavior, and 25 studies used running behavior as treatment or predictor of a given effect or outcome. Four studies examined both predictors and outcomes of running. Thirty-one studies showed poor quality, while 20 had fair and 7 good quality. Motives were the most frequently studied antecedent of running behavior (k = 19), and results suggest that the highest-ranked or more prevalent motives were physical health, psychological motives, and personal achievement. Additionally, perceived control, attitude toward running, intention and subjective norms, self-efficacy, and social support may have also played a role in the adoption of recreational running. Moreover, improvements in mood (k = 10) and well-being (k = 10) were the most frequently reported positive outcomes of running. Reductions in depression, anxiety, and stress were also reported in included studies. Discussion: To our knowledge, this is the first systematic review on this topic. The identification of behavioral and psychological correlates of recreational running across populations can contribute to inform and guide a public policy agenda, focused on helping people sustain regular physical activity, through a modality they have chosen and appear to enjoy. Systematic Review Registration: https://www.crd. york.ac. uk/prospero/display_record. php? RecordID=68954, identifier: CRD42017068954.