Miracle-dz/UniFAR-FTUs huggingface dataset:
Neurorehabilitation Algorithm in Multiple Sclerosis: Traditions and Challenges

Multiple sclerosis (MS) is an autoimmune demyelinating disease of the central nervous system, usually beginning between 20 and 40 years (predominantly in females). Motor weakness, spasticity, balance and coordination dysfunctions provoke severe difficulty in everyday activities of MS patients. MS is a socially important disease, with a high level of acquired disability in a relatively young population. Our purpose is to emphasize the potential of some contemporary physical modalities for MS-neurorehabilitation, based on practice and research. Principal clinical and instrumental assessment and treatment methods are stated: electrical stimulations (with low and middle frequency electric currents); low frequency low intensity magnetic field; proprioceptive neuro-muscular facilitation (PNF) methods; analytic exercises, device-assisted mechano-therapy (passive, active or combined), robotic rehabilitation, etc. We insist on the importance of technical aids (wheelchair, canes, or walking sticks). Authors propose a structured Neurorehabilitation algorithm for MS-patients, with elements of physiotherapy, cryotherapy, electrotherapy, magnetotherapy, ergotherapy, diet, patient’s education. We present the application of this algorithm on a typical MS-patient, treated with cryophysiotherapy, ergotherapy, electrostimulations, Locomat-rehabilitation.
Analysis of Microplastic Intake by Human through Red Kurisi Fish (Nemiptus Japonicas) and Mackerel (Rastrelliger Sp) Consumption in the Coastal Area Community of Tamasaju Village, North Galesong, Takalar Regency

Plastic waste has become one of the most serious threats to the marine environment. Among the plastic waste that is of particular concern are microplastics because of their small size. The purpose of this study was to analyze the level of microplastic intake through fish consumption in the coastal area of Tamasaju Village, North Galesong, Takalar Regency. This research is a type of qualitative research with a descriptive approach. The samples in this study were 30 respondents and 20 fish with the types of mackerel and red kurisi fish. Data obtained by interview using questionnaires, identification of microplastics in fish in the laboratory, and identification of polymer types using FTIR spectroscopy. The results showed that the total number of microplastics found was 18 particles. The type of microplastic found was a line shape with different color and size variations, with the blue line dominating, namely 77.77%. The average concentration of microplastics found in fish was 3.1 mg/kg, with polystyrene polymer content. It is known that the average intake of non-carcinogenic microplastics by the community is 0.04 mg/kg/day (non-carcinogenic) and as much as 0.02 mg/ kg/day (carcinogenic). This shows that the intake of microplastics by humans through fish consumption is still categorized as safe.
Regulatory Developments in the Gig Economy: A Literature Review

The emergence of the gig economy and its rapid growth was anticipated to play a big part in its economy. Despite the enormous benefits, the gig economy business model had also attracted numerous issues in many countries and regions. The research utilized a Systematic Literature Review (SLR) methodology by Snyder for analyzing regulation issues in the gig economy, which was divided into six steps, those were defining the central question, determining databases, using search string to find relevant keywords, extracting data, filtering data, and analyzing the findings to answer to the main question. The SLR results show licensing and misclassifications are the most dominant factors in gig economy, while regulatory issues such as safety, tax, externalities, wage, benefit, privacy, and discrimination area are other factors in it. The most popular platform types that attract regulators are work on demand, asset rental, and crowd-work.
Document Representations to Improve Topic Modelling

Each and every day we are collecting lots of information from web applications. So it is difficult to understand or detect what the whole information is all about. To detect, understand and summarise the whole information we need some specific tools and techniques like topic modelling which helps to analyze and identify the crisp of the data. This paper implements the sparsity based document representation to improve Topic Modeling, it organizes the data with meaningful structure by using machine learning algorithms like LDA(Latent Dirichlet Allocation) and OMP(Orthogonal Matching Pursuit) algorithms. It identifies a documents belongs to which topic as well as similarity between documents in an existing dictionary. The OMP(Orthogonal Matching Pursuit) algorithm is the best algorithm for sparse approximation With better accuracy. OMP(Orthogonal Matching Pursuit) algorithm can identify the topics to which the input document[Y] is mostly related to across a large collection of text documents present in a dictionary.
Effect of Sr, Zn, and Ce Substitution on the Properties of Bioactive Glasses

As well as improving the life of people of all ages, a rise in the life expectancy of people has led to an increased demand for new restoring and augmentation materials that have applications in therapies for bone pathologies. Bioactive Glasses (BGs) have revolutionized the field of biomaterials as they have been generally accepted to be able to promote both hard and soft living tissues regeneration and self-repair. This brief review will discuss the effect of metallic ions substitution on the properties of bioactive glasses for tissue engineering and regenerative medicine applications.
Propriedades Psicométricas da Comprehensive Assessment of Sadistic Tendencies (CAST) no Brasil

Resumo Objetivou-se reunir evidências psicométricas da Comprehensive Assessment of Sadistic Tendencies (CAST) no Brasil. Os resultados da análise fatorial exploratória indicaram uma solução unifatorial, com adequada precisão, tendo itens com discriminação entre moderada e muito alta, cobrindo uma ampla faixa do traço latente. As correlações da CAST com a Tríade Sombria, amabilidade e conscienciosidade e com os fatores da escala de agressão são evidências de validade convergente, além do sadismo ter um incremento significativo na explicação do comportamento agressivo. Pensando no avanço dos estudos sobre a Tétrade Sombria, selecionaram-se os quatro itens mais informativos da CAST, acoplando-os aos 12 da Dirty Dozen, testados por meio de uma análise fatorial confirmatória, apresentaram indicadores de ajuste aceitáveis. No conjunto, os resultados reúnem evidências da adequação psicométrica da CAST, oferecendo uma versão curta e eficaz para avaliação da Tétrade Sombria.
De Novo Design and Bioactivity Prediction of SARS-CoV-2 Main Protease Inhibitors Using ULMFit

The global pandemic of coronavirus disease (COVID-19) caused by SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) created a rush to discover drug candidates. Despite the efforts, so far no vaccine or drug has been approved for treatment. Artificial intelligence offers solutions that could accelerate the discovery and optimization of new antivirals, especially in the current scenario dominated by the scarcity of compounds active against SARS-CoV-2. The main protease (Mpro) of SARS-CoV-2 is an attractive target for drug discovery due to the absence in humans and the essential role in viral replication. In this work, we developed a deep learning platform for de novo design of putative inhibitors of SARS-CoV-2 main protease (M pro ). Our methodology consists of 3 main steps: 1) training and validation of general chemistry-based generative model; 2) fine-tuning of the generative model for the chemical space of SARS-CoV- M pro inhibitors and 3) training of a classifier for bioactivity prediction using transfer learning. The fine-tuned chemical model generated >90% valid, diverse and novel (not present on the training set) structures. The generated molecules showed a good overlap with M pro chemical space, displaying similar physicochemical properties and chemical structures. In addition, novel scaffolds were also generated, showing the potential to explore new chemical series. The classification model outperformed the baseline area under the precision-recall curve, showing it can be used for prediction. In addition, the model also outperformed the freely available model Chemprop on an external test set of fragments screened against SARS-CoV-2 Mpro, showing its potential to identify putative antivirals to tackle the COVID-19 pandemic. Finally, among the top-20 predicted hits, we identified nine hits via molecular docking displaying binding poses and interactions similar to experimentally validated inhibitors.
The Effect of Regular Hemodialysis on the Nutritional Status of Children with End-stage Renal Disease

Original Research Article Background: Children with end-stage renal disease (ESRD) have rates of mortality estimated to be 30-times higher than expected for age compared with those of healthy children. Physical manifestations of under-nutrition, such as body mass index (BMI) have been associated with increased risk of mortality. Traditional measures, such as height, weight and serum albumin concentration, may not be accurate indicators to assess the nutritional status of children receiving maintenance hemodialysis. Meeting the special nutritional needs of these children often requires nutritional supplementation, by either the enteral or the parenteral route. Recently, in children receiving maintenance hemodialysis that is malnourished, intradialytic parenteral nutrition (IDPN) has been utilized as a means to provide additional protein and calories. Objectives: The present study was carried out to identify the malnutrition in children receiving maintenance hemodialysis, with special focus on outcome. Method: This was A cross-sectional observational study was conducted in the Department of Pediatrics of a Pediatric hospital of Benghazi from January 2019 to June 2019. 81 children aged from five to eighteen years on regular hemodialysis. Outcome measures: Measurements included questionnaire that elicited information on social demographic characteristics, Patient’s medical history, and duration of hemodialysis. Anthropometry, biochemical parameters were measured. Anthropometric measurements were expressed as z scores. Data were analyzed using descriptive statistics. The ChiSquare test was applied to examine the study data. Results: Data shows that 49. 4% of children had BMI between 5th percentile up to the 85th percentile were considered normal weight, while, 30. 9% of children had BMI less than the 5th percentile, were categorized as underweight. With regard to biochemical parameters, children had significantly higher serum phosphate, creatinine, and Blood urea nitrogen. However, study population had lower of hemoglobin and serum albumin. In addition, results show that a significant positive correlation between children who were on dialysis for 33-36months with underweight and high serum creatinine and parathyroid hormone. Conclusions: Nutritional assessment is essential to the management of children with CRF. Anthropometry is a sensitive indicator of the nutritional status.
Combined Trajectory Planning and Tracking for Autonomous Vehicles on Deformable Terrains

In this work, a novel combined trajectory planner and tracking controller is developed for autonomous vehicles operating on off-road deformable terrains. Common approaches to trajectory planning and tracking often rely on model-dependent schemes, which utilize a simplified model to predict the impact of control inputs to future vehicle response. However, in an off-road context and especially on deformable terrains, accurately modeling the vehicle response for predictive purposes can be challenging due to the complexity of the tire-terrain interaction and limitations of state-of-the-art terramechanics models in terms of operating conditions, computation time, and continuous differentiability. To address this challenge and improve vehicle safety and performance through more accurate prediction of the plant response, in this paper, a nonlinear model predictive control framework is presented that accounts for terrain deformability explicitly using a neural network terramechanics model for deformable terrains. The utility of the proposed scheme is demonstrated on high fidelity simulations for a notional lightweight military vehicle on soft soil. It is shown that the neural network based controller can outperform a baseline Pacejka model based scheme by improving on performance metrics associated with the cost function. In more severe maneuvers, the neural network based controller can achieve sufficient fidelity as compared to the plant to complete maneuvers that lead to failure for the Pacejka based controller. Finally, it is demonstrated that the proposed framework is conducive to real-time implementability.
“Permanent Revolution” to Effect an Ever-Evasive (Ecological) Utopia in Ursula K. Le Guin’s The Dispossessed: An Ambiguous Utopia

This article aims to analyse Ursula Le Guin’s The Dispossessed: An Ambiguous Utopia from an ecological perspective. In her ecologically conscious story, Le Guin explores the (ironic) manifestation and repercussions of humanity’s environmental fear, the virtues and ills of an ever-evasive ecological utopian society that is paradoxically informed by eco-friendly and ecophobic propensities in its pursuit of freedom through the vigorous practice of the art of dispossession, and the possibility of transcending the hyper-separated categories of difference that include the human/non-human dichotomy. What Le Guin seeks in her fictional effort above all is a permanent revolution advocating a never-ending diligent and earnest endeavour to effect an improved, preferable society with a revised awareness of its relations to its human and non-human Others, free from the ethic of exploitation rather than a promotion of an already achieved perfect state.
Somatic Self-Compassion Training Reduces Perceived Stress, Internalized Shame, and Bodily Shame while Increasing Coping Self-efficacy and Self-compassion

Somatic Self-Compassion® training is a newly developed trauma-informed self-compassion training that was designed to combine interoception and sensory modulation in order to teach individuals to more effectively cope with current and past stress. Thirty-two non-clinical adults across five cohorts participated in this pre-post design feasibility study. Participation in Somatic Self-Compassion® Online resulted in significant reductions in perceived stress, internalized shame, and bodily shame and significant improvements in coping self-efficacy and self-compassion. Of particular importance for moving the field of self-compassion research forward is the strengthened case for inclusion of shame as a dependent variable in order to understand the relationship between self-compassion, shame, and stress.
Studies on the chemical constituents in Chrozophora sabulosa Kar.

OBJECTIVE To study the chemical constituents of Chrozophora sabulosa Kar. (Xinjiang origin). METHODS The chemical constituents were isolated by using repeated silical gel column chromatography,preparative thin layer chromatography,Sephadex chromatography,and their structures were elucidated on the basis of spectral analysis and physical-chemical properties.RESULTS Eight compounds were isolated and identified as luteolin(Ⅰ),amentoflavone(Ⅱ),brevifolin(Ⅲ),ethyl brevifolin carboxylate(Ⅳ),apigenin-7-O-(6″-(E)-p-cinnamoyl)-β-D-galactopyran oside(Ⅴ),luteolin-7-O-β-D-rutinoside(Ⅵ),gallic acid(Ⅶ) and ethyl gallate(Ⅷ). CONCLUSION All of these eight compounds were obtained from this genus for the first time.
Excreción de Derivados de Purinas en Función de la Relación Fibra/Proteína en la Dieta de Alpacas (Vicugna pacos)

The aim of this study was to evaluate the relationship of the neutral detergent fibre/ crude protein on urinary excretion of purine derivatives (PD) in alpacas. The experimental design was a 3x3 Latin Square. Three male Huacaya alpacas, 2.5 years old, confined in individual pens were used. Feed was provided once daily and water ad libitum. Three treatments based on oat hay were used where the ratios of fibre/protein was obtained according to the proportions of stems and leaves. The treatments were: T1, leaves oat hay, 58.24% neutral detergent fiber (NDF) and 6.80% crude protein (CP); T2, leaves and stems of oats, 66.31% FDN and 6.36% PC; T3, stems of oats, 70.22% FDN and 5.75% PC. Each experimental period lasted 14 days, 10 days of adaptation and 4 days of evaluation. The levels of DP urine were analyzed by High Performance Liquid Chromatography (HPLC). The total daily excretion of DP was 25.51 (T1), 28.07 (T2) and 14.21 (T3) mg/d. The daily excretion of allantoin, hypoxanthine, xanthine and the total excretion of DP were similar among treatments. The results showed that the NDF/PC ratio at the levels used does not influence DP excretion in the urine of alpacas.
Strengthening Impacts on the Auxiliary and Morphological Changes of TiO2 Degussa

Titanium dioxide (TiO\(_2\)) is an uncommon class of metal oxides that are generally utilized in an assortment of photograph catalysis applications and items in the natural and vitality, including selfcleaning surfaces, hydrogen development and sun(solar energy) oriented vitality conversion. Herein, impact of strengthening treatment on the structure and morphology of TiO\(_2\) (P25) was evaluated. Powder X-ray diffraction, examining electron microscopy, transmission electron microscopy (TEM) and X-ray photoelectron spectroscopy investigation were led to assign the development and portrayal of the auxiliary, substance piece and morphology of TiO\(_2\). The strengthening temperature influences the crystalline measurements, structure and the morphology of the samples. Strengthening temperature of 500\(^\circ\)C is an ideal vale to keep up an exceptionally steady crystalline morphology and all around characterized particles of TiO\(_2\) (P25).
The accuracy of ultrasound study in the diagnosis of carpal tunnel syndrome in comparison with nerve conduction study

Back ground: Carpal tunnel syndrome (CTS) is one of the most common upper limb compression neuropathies. CTS accounts for approximately 90% of all entrapment neuropathies. The diagnosis of carpal tunnel syndrome (CTS) is mainly based on clinical findings and nerve conduction study. It has been recently suggested that ultrasonography (U/S) can be used to diagnose CTS. Aim of study: The aim of this study is to determine the accuracy of Ultrasound (U/S) in diagnosis of (CTS) in comparison with nerve conduction study (NCS) of median nerve. Patient and Methods: The study was a comparative cross sectional study, which done in ALshaheed Gazi AL-Hariri Hospital for specialized surgery/Baghdad – Iraq, From June 2011 to May 2012. sample included 40 patients who met the inclusion criteria they were 37 (92.5%) females, with a mean age was 38.74 ± 6.7 years range (22-52 years), in addition, 3 (7.5%) males with a mean age was 38.83 ± 6.35years range (39-47), the mean age for all patients (40) was 38.76 ± 6.6. , and 80 Asymptomatic healthy comparison group. 72 of them (90%) were females with a mean age 37.8 ± 7.43 years range (25 – 53 years), and the remaining 8 comparision group 10% were males with a mean age 38.4 ± 6.3 ranges (23-52), and the mean age of all comparision group was 38.1 ± 6.5. All subjects in both groups were underwent and U/S and NCS, then the Statistical analysis for the results were done. Results: The Ultrasound signs show the following results: AP diameter of median nerve: show accuracy rate, sensitivity, specificity, as 80%, 78%, 81% respectively. Cross sectional area of median nerve: show accuracy rate, sensitivity, and specificity, as 85%, 85%, 85 respectively. Conclusions: 1. CTS is mainly affect middle age females. 2. We can concluded that sonography can be adds a benefit in diagnosis of CTS. 3. U/S has potential advantages to other diagnostic tools as availability, shorter Examination time and non-invasive.
The Effect of Manganese(Mn) Substitutional Doping on Structural, Electronic and Magnetic Properties of Pristine Hexagonal Graphene: Using Spin Polarized Density Functional Theory

Graphene, a monolayer of carbon atoms packed in a hexagonal structure, has become one of the most remarkable materials available to condensed matter physics and material science(engineering) today due to its nobel structural and electronic properties. In this paper, the structural, electronic, and magnetic properties of Mn-doped monolayer pristine graphene is studied using spin-polarized density functional theory (DFT). The results show that the substitution of Mn dopant atom at the C sites is energetically favorable and the dopants are strongly hybridized with neighboring C-atoms of graphene. The total density of state (TDOS), partial density of state (PDOS), and energy band structure calculations results revel that the electronic and magnetic properties of pristine graphene is being affected in the presence of Mn dopants. Thus, in the presence of Mn dopants nonmagnetic(paramagnetic) and metallic state of pristine graphene is turned to half-metallic with the ferromagnetic ground state. Based on result, we recommend that Mn doped graphene is Nobel material for spintronics and magnetic information storage applications.
De-risking of Green Investments through a Green Bond Market: Empirics and a Dynamic Model

A substantial increase of green investments is still required to reach the Paris Agreement’s emission targets. Yet, capital markets to expedite green invest-ments are generically constrained. Literature has shown that governments could de-risk such investments. Empirical beta pricing and yield estimates reveal some public involvement in the green bonds market, especially for long ma-turity bonds. We provide empirical evidence that Governments and Multilateral organizations can de-risk green investments by supporting the issuance of green bonds in contrast to private green bonds - that show higher yields, volatility and beta prices - and conventional energy bonds, that are more volatile due to oil price variations. Since lower betas also mean lower capital costs, we use those empirical results and run a dynamic model with two types of ﬁrms, modeling the economic behavior of innovators (renewable energy ﬁrms) and incumbents (fos-sil fuel ﬁrms). The simulations of our model show that de-risked interest rates help to phase in renewable energy ﬁrms in the market and avoid a sharp debt increase. However, when the new entrants carry negative pay-oﬀs for a longer time, it might not be suﬃcient to keep the debt low and to avoid a shake-out in the market. Subsidies and carbon taxation can complement the role of the de-risked interest rates and expedite the energy transition. Beside deterministic model variants, we also explore a stochastic version of the model.