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PurposeTo find out what is known from literature about Long COVID until January 30, 2021.MethodsWe undertook a four-step search with no language restriction. A preliminary search was made to identify the keywords. A search strategy of all electronic databases resulted in 66 eligible studies. A forward and backward search of the references and citations resulted in additional 54 publications. Non-English language articles were translated using Google Translate. We conducted our scoping review based on the PRISMA-ScR Checklist.ResultsOf 120 papers, we found only one randomized clinical trial. Of the 67 original studies, 22 were cohort, and 28 were cross-sectional studies. Of the total 120 publications, 49.1% focused on signs and symptoms, 23.3% on management, and 10.8% on pathophysiology. Ten publications focused on imaging studies. The results are also presented extensively in a narrative synthesis in separated sections (nomenclature, diagnosis, pathophysiology, risk factors, signs/symptoms, management).ConclusionsThe controversies in its definition have impaired proper recognition and management. The predominant symptoms were: fatigue, breathlessness, arthralgia, sleep difficulties, and chest pain. Recent reports also point to the risk of long-term sequela with cutaneous, respiratory, cardiovascular, musculoskeletal, mental health, neurologic, and renal involvement in those who survive the acute phase of the illness.

PurposeThe purpose of this paper is to investigate micropolar magnetohydrodynamics (MHD) fluid flow passing over a vertical plate. Three different base fluids have been used that include water, ethylene glycol and ethylene glycol/water (50%–50%). Also, a nanoparticle was used in all of the base fluids. The effects of natural convection heat transfer and magnetic field have been taken into account.Design/methodology/approachThe main purpose of solving the governing equations is to scrutinize the effects of the magnetic parameter, the nanoparticle volume fraction, micropolar parameter and nanoparticles shape factor on velocity, temperature and microrotation profiles, the skin friction coefficient and the Nusselt number. These surveys have been considered for three base fluids simultaneously.FindingsThe results indicate that for water-based fluids, the temperature profile of lamina-shaped nanoparticles is 38.09% higher than brick-shaped nanoparticles.Originality/valueThis paper provides micropolar MHD fluid flow analysis considering natural convection heat transfer and magnetic field in three different base fluids. The aim of assessments is the diagnosis of some parameter effects, such as magnetic parameter and nanoparticle volume fraction, on velocity, temperature and microrotation profiles and components. Also, the use of mixed base fluids presented as a novelty in this paper.

In this study, the interfacial and mechanical properties of cellulose nanocrystals (CNC) coated glass fiber/epoxy composites were investigated as a function of the CNC content on the surface of glass fibers (GF). Chopped GF rovings were coated with CNC by immersing the GF in CNC (0-5 wt%) aqueous suspensions. Single fiber fragmentation (SFF) tests showed that the interfacial shear strength (IFSS) increased by ~69% in composites produced with CNC coated GF as compared to uncoated GF, suggesting an enhancement of stress transfer across the GF/matrix interface. The role of CNC coatings on the tensile, flexural, and thermo-mechanical properties of the CNC-coated GF/epoxy composites was investigated. Incorporation of 0.17 wt% CNC in the composite resulted in increases of ~10% in both elastic modulus and tensile strength, and 40 and 43 % in flexural modulus and strength respectively. In conclusion CNC coatings on GF alter the GF/matrix interface resulting in improvement of the mechanical performance of the corresponding composites.

Objectives We hypothesized that the frequency (in Hertz) of generalized spike–waves (GSWs) in patients with idiopathic generalized epilepsy (IGE) has associations with the syndromic diagnosis as well as with the prognosis of patients (their response to medical treatment). Methods This was a retrospective study of a prospectively developed database. All patients with a diagnosis of IGE were studied at the epilepsy center at Shiraz University of Medical Sciences, Shiraz, Iran, from 2008 until 2022. Patients were classified into four IGE syndromes: childhood absence epilepsy; juvenile absence epilepsy; juvenile myoclonic epilepsy; and generalized tonic–clonic seizures alone. Results Five hundred and eighty‐three patients were studied. GSWs were commonly observed in all four syndromes of IGE. Frequency of GSW (in Hertz) did not have a significant association with the syndromic diagnosis of the patients (p = .179). The presence of GSW did not have a significant association with the seizure outcome (becoming seizure free or not) of the patients (p = .416). Frequency of GSW did not have a significant association with the seizure outcome of the patients either (p = .574). Conclusion GSWs are the hallmark electroencephalographic footprints of idiopathic generalized epilepsies; however, neither their presence nor their frequency has practical associations with the syndromic diagnosis of IGEs or their outcome (response to treatment).

The aim of this study was to evaluate the water quality of Shatt Al-Arab River (SAR) and investigate the influences on the variations of heavy metals levels. The surface water and bed sediments samples at four stations have been collected (4 months) during 2017–2018, and seven heavy metals (Ni2+, Cr3+, Pb2+, As3+, Hg2+, U4+ and Cd2+), as well as 11 parameters including total dissolved solids, the concentration of hydrogen ions, dissolved oxygen, nitrate, chlorides, turbidity, total hardness, electrical conductivity and alkalinity were investigated. The results indicated that the water quality in the SAR depend on the combined effects of natural and anthropogenic factors. The variation of water quality of SAR influenced by the chemical ions inflow from the Tigris River and the marine salt from Arabian Gulf. The highest value of TDS was in S4 it reached to 42,844 mg/l. The results showed that most of the ions increase their concentration by more than 200%, especially in summer season at Fao area due to the effect of the seawater intrusions. In comparison to the sediments, low concentrations and a uniform distribution of most metals were observed in the river water. The river sediments were polluted with heavy metals, while pollution levels in the water were still within permissible limits for drinking, irrigation and aquatic life. These findings indicated that the major sources of river contamination with heavy metals were the atmospheric deposit of gaseous emissions from oil production and electric generators and the surface runoff from agricultural areas after rainfall. Additionally, the tide greatly controls the distribution heavy metals in the river.

The current study aimed to identify the association between COVID-19 vaccination and prolonged post-COVID symptoms (long-COVID) in adults who reported suffering from this condition. This was a retrospective follow-up study of adults with long-COVID syndrome. The data were collected during a phone call to the participants in January-February 2022. We inquired about their current health status and also their vaccination status if they agreed to participate. In total, 1236 people were studied; 543 individuals reported suffering from long long- COVID (43.9%). Chi square test showed that 15 out of 51 people (29.4%) with no vaccination and 528 out of 1185 participants (44.6%) who received at least one dose of any vaccine had long long- COVID symptoms (p = 0.032). In people who have already contracted COVID-19 and now suffer from long-COVID, receiving a COVID vaccination has a significant association with prolonged symptoms of long-COVID for more than one year after the initial infection. However, vaccines reduce the risk of severe COVID-19 (including reinfections) and its catastrophic consequences (e.g., death). Therefore, it is strongly recommended that all people, even those with a history of COVID-19, receive vaccines to protect themselves against this fatal viral infection.

2 Furthermore, after four steps in our study (searching for molecules, molecular docking results, in-silico blood–brain barrier permeability analysis, and drug safety data), we concluded that “In the current in-silico study, we could identify Fluticasone propionate as a good candidate to deliver FKBP5 blockade. [...]a large clinical trial (CODES trial) failed to demonstrate that cognitive behavioral therapy has a statistically significant advantage compared with standardized medical care alone for the reduction of monthly seizures in patients with functional seizures (psychogenic nonepileptic seizures/attacks). 3 Furthermore, a previous meta-analysis that used data from 13 manuscripts on 228 patients with functional seizures (psychogenic nonepileptic seizures/attacks) showed that 47% of patients achieved seizure control after completion of psychological therapeutic intervention. 4 On the other hand, a study of the natural history of 69 patients with functional seizures (psychogenic nonepileptic seizures/attacks), who never received a proper psychological treatment, showed that 52% of these patients were seizure-free in their last follow-up visit. 5 Functional seizures (psychogenic nonepileptic seizures/attacks) have significant and devastating effects on patients' lives 6 and therefore, the scientific community has the obligation to try to discover more efficacious therapeutic options for the treatment of this condition.

This study focuses on the kinematic and dynamic modeling of a wheeled-legged robot (WLR), taking into account kinematic and dynamic slippage. In this regard, the Gibbs–Appell formulation was utilized to derive dynamic equations. Determining the slippage in the wheels for movement equations is a challenging task due to its dependency on factors such as the robot’s postures, velocities, and surface characteristics. To address this challenge, machine vision was used to quantify the slippage of the wheels on the body based on the pose estimation method. This data served as input for movement equations to analyze the robot’s deviation from its path and posture. In the following, the robot’s movement was simulated using Webots and MATLAB, followed by various experimental tests involving acceleration and changes in leg angles on the WLR. The results were then compared to the simulations to demonstrate the accuracy of the developed system modeling. Additionally, an IMU sensor was utilized to measure the robot’s motion and validate against machine vision data. The findings revealed that neglecting the slippage of the wheels in the robot’s motion modeling resulted in errors ranging from 5% to 11.5%. Furthermore, lateral slippage ranging from 1.1 to 5.2 cm was observed in the robot’s accelerated movement. This highlights the importance of including lateral slippage in the equations for a more precise modeling of the robot’s behavior.

The purpose of the current endeavor was to evaluate the feasibility of using easily accessible and applicable clinical information (based on history taking and physical examination) in order to make a reliable differentiation between idiopathic generalized epilepsy (IGE) versus focal epilepsy using machine learning (ML) methods. The first phase of the study was a retrospective study of a prospectively developed and maintained database. All patients with an electro-clinical diagnosis of IGE or focal epilepsy, at the outpatient epilepsy clinic at Shiraz University of Medical Sciences, Shiraz, Iran, from 2008 until 2022, were included. The first author selected a set of clinical features. Using the stratified random portioning method, the dataset was divided into the train (70%) and test (30%) subsets. Different types of classifiers were assessed and the final classification was made based on their best results using the stacking method. A total number of 1445 patients were studied; 964 with focal epilepsy and 481 with IGE. The stacking classifier led to better results than the base classifiers in general. This algorithm has the following characteristics: precision: 0.81, sensitivity: 0.81, and specificity: 0.77. We developed a pragmatic algorithm aimed at facilitating epilepsy classification for individuals whose epilepsy begins at age 10 years and older. Also, in order to enable and facilitate future external validation studies by other peers and professionals, the developed and trained ML model was implemented and published via an online web-based application that is freely available at http://www.epiclass.ir/f-ige.