(1) Background: Evidence-based policymaking requires data about the local population's socioeconomic status (SES) at detailed geographical level, however, such information is often not available, or is too expensive to acquire. Researchers have proposed solutions to estimate SES indicators by analyzing Google Street View images, however, these methods are also resource-intensive, since they require large volumes of manually labeled training data. (2) Methods: We propose a methodology for automatically computing surrogate variables of SES indicators using street images of parked cars and deep multiple instance learning. Our approach does not require any manually created labels, apart from data already available by statistical authorities, while the entire pipeline for image acquisition, parked car detection, car classification, and surrogate variable computation is fully automated. The proposed surrogate variables are then used in linear regression models to estimate the target SES indicators. (3) Results: We implement and evaluate a model based on the proposed surrogate variable at 30 municipalities of varying SES in Greece. Our model has $R^2=0.76$ and a correlation coefficient of $0.874$ with the true unemployment rate, while it achieves a mean absolute percentage error of $0.089$ and mean absolute error of $1.87$ on a held-out test set. Similar results are also obtained for other socioeconomic indicators, related to education level and occupational prestige. (4) Conclusions: The proposed methodology can be used to estimate SES indicators at the local level automatically, using images of parked cars detected via Google Street View, without the need for any manual labeling effort.

Multiple sclerosis (MS) is a debilitating disease of the brain and spinal cord (central nervous system). In MS, the immune system attacks the protective sheath (myelin) that covers the nerve fibers, causing communication problems between the brain and the rest of the body. Eventually the disease can cause permanent damage or nerve damage. The signs and symptoms of MS are very different and depend on the extent of the nerve damage and which nerves are affected. Some people with severe MS may lose the ability to walk independently or completely, while others may experience a long recovery period without any new symptoms. Most people with MS have a relapsing-remitting illness. They experience periods of new symptoms or recurrences that occur over days or weeks and usually improve somewhat or completely. Following these recurrences, there are periods of recovery that can last for months or even years. In this Project, we used some methods of machine learning in order to evaluate the precision and accuracy of Methods to Predict and classification of Multiple Sclerosis with different stages. In order to calculate accuracy, precision, recall Fscore we used some different method such as Art Fuzzy, SVM, Decision tree to compare the classes two by two. To improve the results we used the method of Adaptive fuzzy optimization. we used two options Genetic algorithm and particle swarm optimization.

The ASCE-EWRI reference evapotranspiration (ETo) equation is recommended as a standardized method for reference crop ETo estimation. However, various climate data as input variables to the standardized ETo method are considered limiting factors in most cases and restrict the ETo estimation. This paper assessed the potential of different machine learning (ML) models for ETo estimation using limited meteorological data. The ML models used to estimate daily ETo included Gene Expression Programming (GEP), Support Vector Machine (SVM), Multiple Linear Regression (LR), and Random Forest (RF). Three input combinations of daily maximum and minimum temperature (Tmax and Tmin), wind speed (W) with Tmax and Tmin, and solar radiation (Rs) with Tmax and Tmin were considered using meteorological data during 2003–2016 from six weather stations in the Red River Valley. To understand the performance of the applied models with the various combinations, station, and yearly based tests were assessed with local and spatial approaches. Considering the local and spatial approaches analysis, the LR and RF models illustrated the lowest rate of improvement compared to GEP and SVM. The spatial RF and SVM approaches showed the lowest and highest values of the scatter index as 0.333 and 0.457, respectively. As a result, the radiation-based combination and the RF model showed the best performance with higher accuracy for all stations either locally or spatially, and the spatial SVM and GEP illustrated the lowest performance among models and approaches.

Automotive manufacturers and suppliers develop new vehicle systems, such as Advanced Driver Assistance Systems (ADAS), to increase traffic safety and driving comfort. ADAS are technologies that provide drivers with essential information or take over demanding driving tasks. More complex and intelligent vehicle systems are being developed toward fully autonomous and cooperative driving. Apart from the technical development challenges, training of drivers with these complex vehicle systems represents an important concern for automotive manufacturers. This paper highlights the new evolving requirements concerning the training of drivers with future complex vehicle systems. In accordance with these requirements, a new training concept is introduced, and a prototype of a training platform is implemented for utilization in future driving schools. The developed training platform has a scalable and modular architecture so that more than one driving simulator can be networked to a common driving instructor unit. The participating driving simulators provide fully immersive visualization to the drivers by utilizing head-mounted displays instead of conventional display screens and projectors. The driving instructor unit consists of a computer with a developed software tool for training session control, monitoring, and evaluation. Moreover, the driving instructor can use a head-mounted display to participate interactively within the same virtual environment of any selected driver. A simulation model of an autonomous driving system was implemented and integrated in the participating driving simulators. Using this simulation model, training sessions were conducted with the help of a group of test drivers and professional driving instructors to prove the validity of the developed concept and show the usability of the implemented training platform.

Cooperative non-orthogonal multi access communication is a promising paradigm for the future wireless networks because of its advantages in terms of energy efficiency, wider coverage and interference mitigating. In this paper, we study the secrecy performance of a downlink cooperative non-orthogonal multi access (NOMA) communication system under the presence of an eavesdropper node. Smart node selection based on feed forward neural networks (FFNN) is proposed in order to improve the physical layer security (PLS) of a cooperative NOMA network. The selected cooperative relay node is employed to enhance the channel capacity of the legal users, where the selected cooperative jammer is employed to degrade the capacity of the wiretapped channel. Simulations of the secrecy performance metric namely the secrecy capacity ($C_S$) are presented and compared with the conventional technique based on fuzzy logic node selection technique. Based on our simulations and discussions the proposed technique outperforms the existing technique in term the of secrecy performance.

Background: Physical activity has been considered as a promising approach to slow down the disease process in Multiple Sclerosis (MS) patients. While the functional impairments of MS have been studied in detail, but there is limited evidence of the efficacy of exercise interventions on the Multiple Sclerosis functional composite (MSFC) score in these patients. The study aim was to in-vestigate the improvement in MSFC score by multi-function swing suspension training (MFSST) in the women with MS. Methods: The patients were divided into the intervention and control groups. A total of 47 MS patients completed the MSFC components at baseline and after the intervention. Z scores were created for each test based on control means. Results: The MSFC components showed a significant increment in comparison with the baseline levels in the four, six, and eight weeks following the first exercise session (all p<0.05). These dif-ferences in the control group were not significant. The improvement in the MSFC score and the component Z-scores in the intervention groups was found from the fourth week onwards. Conclusions: The study findings highlight that MFSST can be used as an effective treatment method in MS patients due to its positive effects on physical parameters, such as muscles strength, functional impairments, and cognitive problems.

Multiple sclerosis (MS) and necrotizing periodontitis (NP) are two diseases whose aetiology and pathophysiology do not seem to have a common link; however, the treatment of MS with monoclonal antibodies and the decrease in humoral immunity that this entails can be a trigger or an aggravation in patients who present NP. We present a clinical case of NP in which its clinical manifestations, treatment and evolution during therapy with ocrelizumab are reflected. During the evolution of the case, a rapid progression of NP was evidenced. During her evolution, the patient suffered bilateral pneumonia due to COVID requiring treatment with corticosteroids and antibiotics, which led to clinical relief of her NP. Given this important clinical finding, we consider of great interest the regulated dental monitoring of those patients with MS before, during and after the administration of monoclonal antibodies to prevent periodontal deterioration.

In this paper, bikeshare data in Chicago on weather-friendly days in 2019 and 2020 were analyzed to investigate the variation in bikeshare travel before and during the pandemic. Our results show that bikeshare trips during the pandemic were much longer than prior to the pandemic. The increased rate of bikeshare usage was unbalanced spatially and varied significantly for different user types. Specifically, bikeshare was used significantly more by casual users than by subscribers, and the increase occurred much more in the outskirts of the city. The increase in bikeshare travel was associated with a reduction in travel by ride-hailing and public transit, especially in the urban periphery. The correlation of bikeshare use with the bus system was much less significant than with the rail system. Bike lanes/facilities had a mixed effect on bikeshare travel. Weekend bike trips increased in areas where there was no bike lane. Weekday trips, on the contrary, increased in the vicinity of bike greenways.

Multiple Sclerosis (MS) is a progressive neurodegenerative disease that affects more than 2 million people worldwide. Increasing knowledge about MS in different populations has advanced our understanding of disease epidemiology and variation in the natural history of MS among White and minority populations. In addition to differences in incidence, African American (AA) and Hispanic patients have greater disease burden and disability in earlier stages of disease compared to White patients. To further characterize MS in AA and Hispanic populations, we conducted a retrospective chart analysis of 112 patients treated at an MS center in Houston, Texas. Here, we describe differences in clinical presentation, MRI findings, treatment regimens, disability progression, and relapse rate. We found that patients who were evaluated by a neurologist at symptom onset had significantly decreased odds of greater disability [defined as Expanded Disability Status Scale (EDSS) &gt; 4.5] at last presentation compared to patients who were not evaluated by a neurologist (OR: 0.04, 95% CI: 0.16-0.9). We also found that active smokers had significantly increased odds of greater disability both at diagnosis and at last clinical encounter compared to nonsmokers (OR: 2.44, 95% CI: 1.10-7.10, OR= 2.44, 95% CI: 1.35-6.12, p= 0.01, respectively). Assessment of the degree of brain atrophy and progression over time along with enumeration of T1, T2, and gadolinium-enhancing brain lesions did not reveal differences across groups.

While there are many models of epidemic evolution perhaps the basis for such models finds itself in the lumped behavior expressed through the so-called SIR model (Susceptible, Infectious, Recovered) from which spring many related models. This paper discusses multiple analytic solutions to that equation including those that are available in closed analytic form and those for which at least one final integral has to be done numerically, so-called quasi-analytic solutions. The solutions are intrinsically time-dependent of course. The hope is that such an investigation will lead to a better understanding of when and how models can be of use in studying the dynamical evolution of diseases including, perhaps, the great influenza pandemic of 1918 together with later pandemics and epidemics not excluding the Covid-19 pandemic of the present day.

Dengue is one of the life-threatening common neglected tropical diseases of the world, yet to develop any therapeutic for its treatment and prevention. Although there is a licensed vaccine reported, but becomes less efficacious due to the presence of multiple serovars of the dengue virus (DENV). Thus, an efficacious dengue vaccine potent to work against all the serovars is very crucial and time-demanding. Here we used a comprehensive hierarchical reverse vaccinology approach to design an epitope-based vaccine, targeted against multiple serovars of the DENV. Conservancy and population coverage analysis of the promiscuous epitopes revealed the robust immune response against multiple serovars of the DENV and various ethnicities. Final vaccine constructs comprising of B and T-cell epitopes, Universal pan-HLA DR or PADRE (AKFVAAWTLKAAA) sequence, and an adjuvant (β-defensin) at N-terminal of the construct with suitable linkers. Physiochemical properties and secondary structure profiling of the vaccine protein secured its hydrophilic, thermostable, and other structural nature. Molecular docking analysis indicates the deep binding of the proposed vaccine in the binding groove of the human immune TLR4 receptor present on the dendritic cell. In addition, disulfide engineering was coped to extend its stability. Furthermore, molecular dynamics simulation of the modeled vaccine-TLR8 complex showed minimum deformability. Finally, in silico cloning approach of the vaccine construct within an expression vector (pET28a+) assure good expression. Proposed vaccine may give novel insights for treatment of dengue patients.

In recent decades, power consumption has become an essential factor in attracting the attention of integrated circuit (IC) designers. Multiple-valued logic (MVL) and approximate computing are some techniques that could be applied to integrated circuits to make power-efficient systems. By utilizing MVL-based circuits instead of binary logic, the information conveyed by digital signals increases, and this reduces the required interconnections and power consumption. On the other hand, approximate computing is a class of arithmetic computing used in systems where the accuracy of the computation can be traded-off for lower energy consumption. In this paper, we propose novel designs for exact and inexact ternary multipliers based on carbon-nanotube field-effect transistors (CNFETs). The unique characteristics of CNFETs make them a desirable alternative to MOSFETs. The simulations are conducted using Synopsys HSPICE. The proposed design is compared against existing ternary multipliers. The results show that the proposed exact multiplier reduces energy consumption by up to 6X. At the same time, the best inexact design improves energy efficiency by up to 35X compared to the latest state-of-the-art methods. Using the imprecise multipliers for image processing provides evidence that these proposed designs are a low-power system with an acceptable error.

In this paper, a technique of image watermarking using multiple images as watermarks is presented. The technique is based on transform domain functions including discrete wavelet transform (DWT), discrete cosine transform (DCT) and singular value decomposition (SVD) with an image as the host signal i.e. the watermarks will be used as proofs of the authenticity of the host image. The technique is executed by performing multilevel DWT followed by applying DCT and SVD to both the host and watermark. Multiple watermarks are used for the insurance of better security level. The scheme is immune to common image processing operations & some attacks and exhibits PSNR of 108.3781dB, normalized cross correlation (NCC) over 0.99 and normalized correlation (NC) over 0.99.

Assuming the Multiple Point Principle (MPP) as a new law of Nature, we considered the existence of the two degenerate vacua of the Universe: a) the first Electroweak (EW) vacuum at $v_1\approx 246$ GeV—“true vacuum”, and b) the second Planck scale “false vacuum” at $v_2 \sim 10^{18}$ GeV. In these vacua, we investigated different topological defects. The main aim of the paper is an investigation of the black-hole-hedgehogs configurations as defects of the false vacuum. In the framework of the $f(R)$ gravity, described by the Gravi-Weak unification model, we considered a black-hole solution, which corresponds to a “hedgehog”—global monopole, that has been “swallowed” by the black-hole with mass core $M_{BH}\sim 10^{18}$ GeV and radius $\delta\sim 10^{-21}$ GeV$^{-1}$. Considering the results of the hedgehog lattice theory in the framework of the $SU(2)$ Yang-Mills gauge-invariant theory with hedgehogs in the Wilson loops, we have used the critical value of temperature for the hedgehogs’ confinement phase ($T_c\sim 10^{18}$ GeV). This result gave us the possibility to conclude that the SM shows a new physics (with contributions of the $SU(2)$-triplet Higgs bosons) at the scale $\sim 10$ TeV. This theory predicts the stability of the EW-vacuum and the accuracy of the MPP.

We previously reported that in multiple sclerosis (MS) patients with a progressive form of the disease, spinal cord periplaques extend distance away from plaque borders and are characterized by the co-occurrence of partial demyelination, astrocytosis and low-grade inflammation. However, transcriptomic analyses comparing periplaques to adjacent normal-appearing white matter (NAWM) areas did not allow providing a comprehensive view of molecular events in astrocytes vs oligodendrocytes. Here, we re-assessed our transcriptomic data with the aim of identifying functionally-relevant co-expression networks that would reflect astrocyte vs oligodendrocyte molecular signatures in periplaques. We identified an astrocytosis-related gene module comprising GFAP, the hub gene CX43/GJA1 and a set of transcripts forming a TGFB/SMAD1/SMAD2 genomic signature. Partial demyelination was characterized by a co-expression network which, besides myelin genes, comprised a highly significant number of translation/elongation-related genes. Interestingly, the main oligodendrocyte-related hub we identified was NDRG1, a gene previously shown to be specifically silenced in the NAWM of MS patients. This result indicated that NDRG1 down-regulation could be an important event in the process of periplaque partial demyelination. To establish a putative link between NDRG1 down-regulation and a cytokine/chemokine signature, we then sought to identify cytokine/chemokine genes whose mRNA levels inversely correlated with those of NDRG1. Following this approach we found 5 candidate immune-related genes whose up-regulation associated with NDRG1 down-regulation: TGFB1, PDGFC, IL-17D, IL-33, and IL-12A. From these results we propose that in the spinal cord of MS patients with progressive forms of the disease, TGFB1 may limit acute inflammation but concurrently induce astrocytosis and an alteration of oligodendrocytes terminal differentiation.

2,5-Dihydroxyacetophenone (DHAP) is an active compound obtained from Radix Rehmanniae Preparata, which is widely used as a herbal medicine in many Asian countries. DHAP has been found to possess anti-inflammatory, anti-anxiety, and neuroprotective qualities. For the present study, we evaluated the anti-cancer effects of DHAP on multiple myeloma cells. It was discovered that DHAP downregulated the expression of oncogenic gene products like Bcl-xl, Bcl-2, Mcl-1, Survivin, Cyclin D1, IAP-1, Cyclin E, COX-2, and MMP-9, and upregulated the expression of Bax and p21 proteins, consistent with the induction of G2/M phase cell cycle arrest and apoptosis in U266 cells. DHAP inhibited cell proliferation and induced apoptosis, as characterized by the cleavage of PARP and the activation of caspase-3, caspase-8, and caspase-9. Mitogen-activated protein kinase (MAPK) pathways have been linked to the modulation of the angiogenesis, proliferation, metastasis, and invasion of tumors. We therefore attempted to determine the effect of DHAP on MAPK signaling pathways, and discovered that DHAP treatment induced a sustained activation of JNK, ERK1/2, and p38 MAPKs. DHAP also potentiated the pro-apoptotic and anti-proliferative effects of bortezomib in U266 cells. Our results suggest that DHAP can be an effective therapeutic agent to target multiple myeloma.

A progressive and chronic neurological condition called MSA (Multiple System Atrophy) is characterized clinically by varying degrees of dysautonomia, cerebellar ataxia, and parkinsonism. The concept of mitochondrial dysregulation in MSA is one perspective in handling this neurodegenerative disease. Damage to functional mitochondria is driven by the presence of ɑ-Synuclein-induced mitochondrial localization. The goal of MSA treatment up until now has been to reduce symptoms. One of the innovations in the treatment of MSA could be the novel idea based on mitochondrial reprogramming pathways. Mitochondrial reprogramming can be done in various ways in which the use of hydrogen, magnesium and low-dose hydrogen peroxide.

Objective: The purpose of this study was to investigate the effects of Crocin on brain neuroterophins, cognition, sensory and motor dysfunction and compare to fingolimod effects in experimental model of demyelination with Ethidium Bromide EB in female Wistar rats. Methods: Animals were assigned in to 8 groups; Sham, Sham operated (ShOp), EAE, crocin treated (Cr5,10,20 mg/kg), Vehicle, Fingolompd (Fing) and fingolimod + crocin (Cr+Fing). Demyelination was induced by single dose injection of 10 μl of EB 0.1% into the fourth ventricle of the brain. Crocin and fingolimod were applied for 21 days, daily, oral gavage. BDNF, NGF1, nerve conduction velocities, tail flake latency, balance and behavioral variables were sampled and analyzed by paired t-test and ANOVA test with repeated post hoc measurements. Results: The results showed that crocin improves all studied factors, but remarkable imrovments were observed in dosage of 10 mg/kg. Crocin (10mg/kg) and fingolimod (1mg/kg) significantly improved cognition variables in open field test, sensory and motor nerve conduction velocity, tail flick latency and clinical signs (p<005). In addition, applying of crocin co-administered with fingolimod led to significant increases in all assessed factors, greater than crocin or fingolimod intervention alone (α≤0.001). Conclusion: Based on the current findings, crocin can improve the level of brain neurotrophins, exploratory behavior and nerve conduction after demyelination as close as fingolimod results. So, crocins can be considered as a neuro supportive agent in the management of degenerative diseases maybe similar to fingolimod mechanism.

Introduction: This study aimed to validate the psychometric properties of the German eHealth Impact Questionnaire (eHIQ-G), which is divided into two independently administered and scored parts. Methods: 162 people with MS browsed one of two possible websites containing information on MS and completed an online survey. Internal consistency was assessed by Cronbach’s alpha and structural validity by Confirmatory Factor Analysis. Construct validity was examined by assessing correlations with the eHealth Literacy Questionnaire and the General Self-Efficacy Scale. Moreover, the mean difference of the eHIQ-G score between the two websites was investigated. Results: Cronbach’s alpha for the eHIQ-G subscales ranged from .833 to .885. The eHIQ-G part 1 achieved acceptable levels of goodness-of-fit indices, whereas the fit for the eHIQ-G part 2 was poor and likewise for the alternative modified models. The correlations with the reference instruments were 0.08 – 0.62 and as expected. Older age was related with lower eHIQ-G part 1 score, whereas no significant effect was found for education. Although not significant, the website ‘AMSEL’ reached higher mean scores on eHIQ part 2. Conclusion: The eHIQ-G has good internal consistency, and sufficient structural and construct validity. It will facilitate the measurement of the impact of websites providing health information.

Background and Aim: Multiple sclerosis (MS) is known as an autoimmune disease and a chronic inflammatory condition, inducing a wide variety of mood affective disorders, including depression and feelings of hopelessness in many aspects of patients’ quality of life (QoL). In view of the positive side effects of spirituality and spiritual care on finding appropriate strategies for further adaptation, this study aimed to determine the impact of group spiritual care (GSC) on levels of hope in patients suffering from MS. Materials and Methods: This clinical trial was conducted on a total number of 96 patients with MS, referring to the National Multiple Sclerosis Society (NMSS) in the city of Zahedan, Iran. Following sample selection via the convenience sampling technique, the patients meeting the inclusion criteria were randomized into two groups, i.e., intervention and control. The data collection tools for this purpose included a demographic information form and the Adult Hope Scale (AHS, Snyder et al. 1991), completed by the subjects at the pre- and post-intervention stages. As well, the intervention group received five sessions of GSC during three weeks but the control group members only talked over daily issues along with their mental health problems. The data were also analyzed using the SPSS Statistics software (ver. 14). Results: The Kruskal-Wallis test results revealed that the GSC intervention could have a significant positive effect on raising hope in the patients with MS (p<0.001). Moreover, a significant growth was observed in the scores of hope dimensions including agency and pathway (p<0.001). Conclusion: GSC can effectively boost levels of hope in patients suffering from MS in all dimensions. Therefore, it is recommended to utilize this type of care in order to nurture hope in such individuals.

Background: Rituximab is a monoclonal antibody widely used in the treatment of inflammatory and autoimmune disorders. Despite reports of its effectiveness in the treatment of demyelinating diseases of central nervous system (DDCNS), it is not yet approved for use in these disorders. The aim of this study was to investigate the effectiveness and safety of low dose rituximab in three different subgroups of DDCNS including relapsing-remitting multiple sclerosis (RRMS), secondary-progressive multiple sclerosis (SPMS) and neuromyelitis-optica-spectrum disorders (NMOSD).Methods: In a prospective cohort study, we monitored expanded-disability-status-scale (EDSS), relapses (new attacks) and serum-IgG levels to assess effectiveness and drug-adverse-events for safety in patients with RRMS, SPMS and NMOSD. These patients were candidates to receive rituximab according to our common practice protocol. We switched patients to rituximab if there was poor response to first line therapies. We follow a low dose protocol in our center (500 mg twice, two weeks apart, repeating every six months) and these patients treated in a 4-year period were assessed retrospectively for evaluation of our protocol’s safety and effectiveness. Results: 99 patients (42 RRMS, 43 SPMS and 14 NMOSD) received rituximab for a range of 12 to 40 months period. New attacks occurred in 8 RRMS (19%), 10 SPMS (23%) and 1 NMOSD (7%) patients. EDSS decreased in RRMS and NMOSD cases. Serum-IgG levels decremented in SPMS and NMOSD patients. Drug-adverse-events happened in two cases.Conclusion: In this study, low dose rituximab showed substantial effectiveness in preventing disease progression with a considerably good safety profile.

According to the French Agency for Food, Environmental and Occupational Health & Safety, electromagnetic hypersensitivity affects more than 3 million people in France, and headaches are a very frequent cause of complaint in electrohypersensitive patients, to the point of dominating the clinical picture. These headaches share characteristics with migraine pathology, and clinical improvement with anti-migraine therapy has led us to consider that the headache in the electrohypersensitive patient may be a variant of the migraine disease mediated by the TRPA1 receptor, which if confirmed, would offer effective therapeutic possibilities to relieve the electrohypersensitive patient.

Multiple Sclerosis (MS) has a well established link with Epstein-Barr virus (EBV) and a growing association with human endogenous retroviruses (HERVs). In this review, we described how these two pieces may interact in MS pathogenesis

Tuberculosis (TB) is an infectious-contagious disease caused by M. tuberculosis (Koch’s bacillus). About one-quarter of the world’s population is infected with that bacillus and at risk of developing TB disease. Latent tuberculosis corresponds to people who have been infected by TB bacteria but are not (yet) ill. The most vulnerable population to TB activation includes HIV infected, drug abuse and autoimmune disease patients. Multiple Sclerosis (MS) is a chronic and autoimmune neurological disease caused by lymphocytic infiltration. Its prevalence worldwide is 22.2 million cases of MS. There is a relation between TB and MS: due to immunomodulation or immunosuppression treatment of MS (reactivation of latent infection), or due to the intense inflammatory response before the infection of the bacillus (increased susceptibility to the development of autoimmune diseases). Screening for TB includes complete patient history, physical exam, chest radiography, and Tuberculin Skin Test or IGRA (Interferon Gamma Release Assay). This investigation is suggested when MS drugs (immunomodulatory and immunosuppressant medications) are prescribed. If a patient has positive results, the treatment for MS should not be delayed for the finishing TB treatment. In this paper, considering the high prevalence of tuberculosis, we recommend that TB screening should be also done at the moment of Multiple Sclerosis diagnosis.

STAT3 is an oncoprotein which has been shown to contribute to drug resistance in multiple myeloma (MM). Nonetheless, the clinical utility of STAT3 inhibitors in treating MM has been limited, partly related to some of their pharmacologic properties. To overcome these challenges, our group had previously packaged STAT3 inhibitors using a novel formulation of nanoparticles (NP) and found encouraging results. In this study, we aimed to further improve the pharmacologic properties of these NP by decorating them with monoclonal anti-CD38 antibodies. NP loaded with S3I-1757 (a STAT3 inhibitor), labeled as S3I-NP, were generated. S3I-NP decorated with anti-CD38 (labeled as CD38-S3I-NP) were found to have a similar nanoparticular size, drug encapsulation and loading as S3I-NP. The release of S3I-1757 at 24 hours was also similar between the two formulations. Using Cy5.5 labeling of the NP, we found that the decoration of anti-CD38 on these NP significantly increased the cellular uptake by two MM cell lines (p<0.001). Accordingly, CD38-S3I-NP showed a significantly lower inhibitory concentration at 50% (IC50) compared to S3I-NP in two IL6-stimulated MM cell lines (p<0.001). In a xenograft mouse model, CD38-S3I-NP significantly reduced the tumor size by 4 folds compared to S3I-NP on day 12 after drug administration (p=0.006). The efficacy of CD38-S3I-NP in suppressing STAT3 phosphorylation in the xenografts was confirmed by using immunocytochemistry and western blot analysis. In conclusion, our study suggests that the decoration of anti-CD38 on NP loaded with STAT3 inhibitors can further improve their therapeutic effects against MM.

Multiple sclerosis is an autoimmune disorder where both T cells and B cells are implicated in pathology. However, it remains unclear how these two distinct populations cooperate to drive disease. There is ample evidence from studies in both MS patients and mouse models that Th17, B cells, and follicular T helper (TFH) cells contribute to disease. This review article describes the literature that identifies mechanisms by which Th17, TFH, and B cells cooperatively drive disease activity in MS and EAE. The curation of this literature has identified that CNS-infiltrating TFH cells act with TH17 cell to contribute to an inflammatory B cell response in neuroinflammation. This demonstrates that TFH cells and their products are promising targets for therapies in MS.

The role of pregnancy in multiple sclerosis (MS) is of importance because many patients with MS are young women in the childbearing age who require information to inform their reproductive decisions. Pregnancy is now well-known to be associated with fewer relapses of MS and reduced activity of autoimmune encephalomyelitis (EAE). However, in women with multiple sclerosis, this benefit is not always sufficient to protect against a rebound of disease activity if disease modulating therapy is ceased for pregnancy. There is reason to be concerned that use of assisted reproductive therapies can be associated with relapses of MS. It is thought that the beneficial effects of pregnancy are due to the pregnancy-associated changes in the maternal immune system. There is some evidence of this in human studies and studies of EAE. There is also evidence that having been pregnant leads to better long-term outcome of MS. The mechanism for this is not fully understood but it could result from epigenetic changes resulting from pregnancy or parenthood. Further studies of the mechanisms of the beneficial effects of pregnancy could provide information that might be used to produce new therapies.

An increased risk of multiple sclerosis (MS) had been found when individuals had consumed large amounts of processed meat and sausages at young age (Lauer, 2014). Furthermore it was found in many studies that MS patients had acquired a number of common childhood infections at higher ages than controls. Therefore, MS patients from an epidemiological long-term investigation in Germany and different hospital controls, were evaluated for a statistical interaction of these two factors. 324 MS patients and 242 hospital controls were inquired. The study focussed on age 0 - 16. Subjects were tested for additive interaction by multiple linear regression analysis (Knol et al., 2007). There was an additive interaction of the age at any common childhood infection with the consumption of scalded sausages (regression estimate = 0.1370; standard error = 0.0603; p = 0.0239). In contrast, no such interaction could be shown for: animal fats; smoked meat (e.g. ham and bacon); and cold - smoked German salami. Thus there was a synergy of the intake of scalded sausages (e.g. frankfurters, bolognas, etc.) and age at common childhood infections, for the later risk of MS.

This paper presents a new approach to suppress interference between neighbouring radiating elements resulting from surface wave currents. The proposed technique will enable the realization of low-profile implementation of highly dense antenna configuration necessary in SAR and MIMO communication systems. Unlike other conventional techniques of mutual coupling suppression where decoupling slab is located between the radiating antennas the proposed technique is simpler and only requires embedding linear slots near the periphery of the patch. Attributes of this technique are (i) significant improvement in the maximum isolation between the adjacent antennas by 26.7 dB in X-band, & >15 dB in Ku and K-bands; (ii) reduction in edge-to-edge gap between antennas to 10 mm (0.37λ); and (iii) improvement in gain by >40% over certain angular directions, which varies between 4.5 dBi to 8.2 dBi. The proposed technique is simple to implement at low-cost.

Several preclinical and clinical reports have demonstrated that levels of circulating high mobility group box 1 protein (HMGB1) are increased early after trauma and are associated with systemic inflammation and clinical outcomes. However, the mechanisms of the interaction between HMGB1 and inflammatory mediators that lead to the development of remote organ damage after trauma remain obscure. HMGB1 and inflammatory mediators were analyzed in plasma from 54 combat casualties, collected on admission to a military hospital in Iraq, and at 8 and 24 hours after admission. Forty-five (83%) of these patients had traumatic brain injury (TBI). Nine healthy volunteers were enrolled as controls. HMGB1 plasma levels were significantly increased in the first 8 hours after admission, and were found to be associated with systemic inflammatory responses, injury severity score, and presence of TBI. These data provided the rationale for designing experiments in rats subjected to blast injury and hemorrhage, to explore the effect of HMGB1 inhibition by CX-01. Animals were cannulated, then recovered for 5-7 days before blast injury in a shock tube and volume-controlled hemorrhage. Blast injury and hemorrhage induced an early increase in HMGB1 plasma levels that coincided with severity of tissue damage and mortality. CX-01 inhibited systemic HMGB1 release, decreased local and systemic inflammatory responses, significantly reduced tissue and organ damage, and tended to increase survival. These data suggest that CX-01 has potential as an adjuvant treatment for traumatic hemorrhage.

We investigated the response of the Manila clam Venerupis philippinarum to possible temperature and salinity changes in a holding facility. First, clams were exposed to four temperatures for 15 days. Valve closure and survival of clams exposed to seawater at 18℃ were higher than that of those exposed to seawater at 24℃. Second, clams were exposed to six salinities for 15 days. Survival of clams exposed to two salinity fluctuation conditions (24–30 and 27–24 psu) was lower than that of clams exposed to constant 30 psu conditions. Valve closures of clams exposed to constant low salinity conditions (24 psu) and two salinity fluctuation conditions (24–30 and 27–24 psu) were higher than of those exposed to constant 30 psu conditions. Lastly, clams were exposed to two different temperatures and three different salinities conditions for 8 days. Valve closure and survival decreased significantly under the combination of 24℃ and 18 psu. These results suggest that an increase in temperature or a wider range of salinity fluctuations are detrimental to the survival of the Manila clam. The synergistic effect of temperature and salinity stressors may decrease the survival period of clams compared to the effect of a single stressor.

Despite recent advances in immune-modulatory drugs, pharmacological therapies have been proven ineffective in severe presentations of multiple sclerosis (MS), including secondary progressive MS. At present, therapeutic interventions' performance is primarily focused on ameliorating symptoms to improve the patient's quality of life. Among complementary treatments, nutrition has been considered a decisive factor to control symptoms and enhance the wellness of MS patients. Although no special diets are associated with MS, the impact of diet and dietary supplements on the course of progressive forms of the disease have been studied during the last years. Fatigue is among the most common and disabling symptoms reported by MS patients. Fatigue has been defined in the Multiple Sclerosis Council for Clinical Practice Guidelines (MSCCPG, 1998) as a "subjective lack of physical and/or mental energy that the individual perceives as an interference with habitual and desired activities". This study aimed to compare the psychometric functioning of the "Fatigue Severity Scale" (FSS) and the "Modified Fatigue Impact Scale" (MFIS) in our sample of people with MS. Specifically, during chronic treatment, the change in these two parameters with two vitamin-rich dietary supplements (Citozym® and Ergozym®) was evaluated. The impact of these nutritional supplements revealed differences in antioxidant and anti-inflammatory parameters between treatment groups with subsequent improvement in fatigue. In conclusion, the results obtained have confirmed the effectiveness of complementary nutritional therapies, evaluated essentially based on hematological biomarkers, through which it is possible to act on disability to improve the quality of life of MS patients.

Complex models have received significant interest in recent years and are being increasingly used to explain the stochastic phenomenon with upward and downward fluctuation such as the stock market. Different from existing semi-variance methods in traditional integer dimension construction for two variables, this paper proposes a simplified multi-factorized fractional dimension derivation with the exact Excel tool algorithm involving the fractional center moment extension to covariance, which is a complex parameter average that is a multi-factorized extension to Pearson covariance. By examining the peaks and troughs of gold price averages, the proposed algorithm provides more insight into revealing underlying stock market trends to see who is the financial market leader during good economic times. The calculation results demonstrate that the complex covariance is able to distinguish subtle differences among stock market performances and gold prices for the same field that the two variable covariance may overlook. We take the London, Tokyo, Shanghai, Toronto and Nasdaq as the representative examples.

Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system. The interferons (IFNs) were discovered in 1957, and recombinant IFN-β-1b was approved by the US Food and Drug Administration as the first disease-modifying therapy (DMT) for MS in 1993. Since that time, clinical trials and real-world observational studies have demonstrated the effectiveness of IFN therapies. The pivotal intramuscular IFN-β-1a phase 3 trial was the first to demonstrate that a DMT could reduce accumulation of sustained disability in MS. Patient adherence to treatment is higher with intramuscular IFN-β-1a, given once weekly, than with subcutaneous formulations requiring multiple injections per week. Moreover, subcutaneous IFN-β-1a is associated with an increased incidence of injection site reactions and neutralizing antibodies compared with intramuscular administration. In recent years, revisions to MS diagnostic criteria have improved clinicians’ ability to identify patients with MS and have promoted the use of magnetic resonance imaging (MRI) for diagnosis and monitoring. MRI studies show that treatment with IFN-β-1a, relative to placebo, reduces T2 and gadolinium-enhancing lesions and gray matter atrophy. Since the approval of intramuscular IFN-β-1a, several high-efficacy therapies have been approved for MS, though the benefit of these high-efficacy therapies should be balanced against the increased risk of serious adverse events. For some subpopulations of patients, including pregnant women, the safety profile of IFN-β formulations may provide a particular benefit. In addition, the antiviral properties of IFNs may indicate therapeutic opportunities for IFN-β in the treatment of viral infections such as COVID-19.

Abstract: Long noncoding RNAs (lncRNAs) are deregulated in human cancers and are associated with disease progression. Plasmacytoma Variant Translocation 1 (PVT1), an lncRNA, is located adjacent to MYC, linked to multiple myeloma (MM). PVT1 is expressed in MM and is associated with carcinogenesis, however, its role and regulation machinery remain uncertain. We examined PVT1/MYC expression through real time PCR in plasma cells purified from 59 MGUS and 140 MM patients. MM cell lines KMS11, KMS12PE, OPM2, and RPMI8226 were treated with JQ1, a MYC superenhancer inhibitor, or MYC inhibitor 10058-F4. The expression levels of PVT1 and MYC were significantly higher in MM than in MGUS (p &lt; 0.0001), and showed positive correlation with disease progression (r = 0.394, p &lt; 0.0001). JQ1 inhibited cell proliferation and decreased the expression levels of MYC and PVT1. However, 10054-F4 did not alter the expression level of PVT1. The positive correlation between MYC and PVT1 in patients, synchronous downregulation of MYC and PVT1 by JQ1, and no effect of MYC inhibitor on PVT1 expression suggest that the expression of these two genes is coregulated by a superenhancer. Cooperative effects between these two genes may contribute to MM pathogenesis and progression.

Risk attitudes are relevant factors affecting the production and investment decisions at farm level. They are key factors that are related to farmers’ attitudes towards environment and climate change. Several methodological approaches are available to measure the level of stated risk of an economic agent. The Multiple Price List (MPL) method is one of the methods that is gaining relevance. In this study we apply the MPL and relate the risk outcomes with farmers’ characteristics and their perception towards environment and climate change. Data was collected using a face to face survey carried out for a group of 370 agricultural producers of the irrigation district located in northwest of Mexico. Results showed an average risk of about 0.32, locating the agricultural producers of the region in a group with risk aversion, according to the MPL scale. The heterogeneity analysis showed that the socioeconomic factors and the perceptions towards climate change are related to the farmers´ stated risk level. Farmers who are young women with propensity to use public support to invest were shown to be greater risk lovers. Farmers in the region have perceived climate change to a greater extent like floods, hail, diseases and pests, and changing vegetation.

Two sufi women take part in activities related to sufism and create an attraction point in the secular side in Turkey.The most striking point is that both women do not wear headscarves although they are muslim women. This article attempts to show how sufi women Cemalnur Sargut and Hayatnur Artıran have idealized a Muslim woman's identity, the work they are doing to achieve this ideal, their attidue toward Rebublic values, and the effects of these attidues on their followers. This article was created from my doctoral thesis and based on Qualitative research which has been established on the basis of 2-year long participant observation and data obtained from in-depth and focus interviews. 31 women and 20 men were interviewed in depth and focus interviews.The main conclusions of my qualitative research are that the influence of theese sufi women is related with process of modernization by accelerating the establishment of the republic in Turkey. It seems that a perception has established concerning that “public apparency’’ of woman will disappear if the “apparency of body’’ disappears and the woman will return to its role which had relapsed into silence for centuries. Besides not using the headscarf, religious conversation have been created by theese sufi women in the balance of religion, philosophy and science and the fact that they are conducting their works under secular institutions such as foundations and associations have also been observed to have a very important effect on seculer side.

Conyza canadensis is a species invading large agricultural areas throughout the world, mainly to its ability to evolve herbicide resistance. Specifically, in Hungary, extensive areas have been infested by this species due to the difficulty in controlling it with glyphosate. To corroborate this fact as resistance and not as an incorrect herbicide application, eight suspicious glyphosate-resistant C. canadensis populations from different Hungarian regions were studied. In dose-response assays with glyphosate, the LD50 and GR50 values indicated that populations 1 to 5 were resistant to this herbicide (H-5 population the most resistant). Besides, the shikimic acid accumulation tests corroborated the results observed in the dose-response assays. 11 alternative herbicides from 6 different mode of action (MOA) were applied at field doses as control alternatives on populations H-5 and H-6 (both in the same regions). The H-5 population showed an unexpected resistance to flazasulfuron (ALS-inhibitor). The ALS enzyme activity studies indicated that the I50 for H-5 was 63.3 fold higher compared to its correspondent susceptible population (H-6). Therefore, the H-5 population exhibited multiple-resistance to flazasulfuron and glyphosate, being the first case reported in Europe for this two MOA. For that reason, the other herbicides with different MOA have to be tested here.

Malignant cells cultured in three-dimensional (3D) models have been found to be phenotypically and biochemically different from their counterparts cultured conventionally. Since most of these studies employed solid tumor types, how 3D culture affects multiple myeloma (MM) cells is not well understood. Here, we compared MM cells (U266 and RPMI8226) in a 3D culture model with those in conventional culture. While the conventionally cultured cells were present in single cells or small clusters, MM-3D cells grew in large spheroids. We discovered that STAT3 was the pathway that was more activated in 3D in both cell lines. The active form of STAT3 (phospho-STAT3 or pSTAT3), which was absent in MM cells cultured conventionally, became detectable after 1-2 days in 3D culture. This elevated pSTAT3 level was dependent on the 3D environment, since it disappeared after transferring to conventional culture. STAT3 inhibition using a pharmacological agent, Stattic, significantly decreased the cell viability of MM cells and sensitized them to bortezomib in 3D culture. Using an oligonucleotide array, we found that 3D culture significantly increased the expression of several known STAT3 downstream genes implicated in oncogenesis. Since most primary MM tumors are naturally STAT3-active, studies of MM in 3D culture can generate results that are more representative of the disease.

The role of natural factors mainly solar eleven-year cycle variability, and volcanic eruptions on two major modes of climate variability the North Atlantic Oscillation (NAO) and El Niño Southern Oscillation (ENSO) are studied for around last 150 years period. The NAO is the primary factor to regulate Central England Temperature (CET) during winter throughout the period, though NAO is impacted differently by other factors in various time periods. Solar variability indicates a strong positive influence on NAO during 1978-1997, though suggests opposite in earlier period. Solar NAO lag relationship is also shown sensitive to the chosen times of reference and thus points towards the previously proposed mechanism/ relationship related to the sun and NAO. The ENSO is influenced strongly by solar variability and volcanic eruptions in certain periods. This study observes a strong negative association between the sun and ENSO before the 1950s, which is even opposite during the second half of 20th century. The period 1978-1997, when two strong eruptions coincided with active years of strong solar cycles, the ENSO, and volcano suggested a stronger association, and we discussed the important role played by ENSO. That period showed warming in central tropical Pacific while cooling in the North Atlantic with reference to the later period (1999-2017) and also from chosen earlier period. Here we show that the mean atmospheric state is important for understanding the connection between solar variability, the NAO and ENSO and associated mechanism. It presents a critical analysis to improve knowledge about major modes of variability and their role in climate. We also discussed the importance of detecting the robust signal of natural variability, mainly the sun.

A novel configuration for a super-wide impedance planar antenna is presented based on a 2 × 2 microstrip patch antenna (MPA). The antenna comprises a symmetrical arrangement of four-square patches that are interconnected to each other with cross-shaped high impedance microstrip lines. The antenna array is exciting through a single feedline connected to one of the patches. The proposed antenna array configuration overcomes the main drawback of conventional MPA of narrow bandwidth that is typically <5%. The antenna exhibits a super-wide frequency bandwidth from 20 GHz to 120 GHz for S₁₁<−15 dB, which corresponds to a fractional bandwidth of 142.85%. The antenna’s performance of bandwidth, impedance match, and radiation gain were enhanced by etching slots on the patches. The slotted microstrip patch essentially acts like a left-handed capacitance to exhibit metamaterial properties over a given frequency range. With the inclusion of the slot the maximum radiation gain and efficiency of the MPA have increased to 15.11 dBi and 85.79% at 80 GHz, which show an improvement of 2.58 dBi and 12.54%, respectively. The dimension of each patch antenna is 30 × 30 mm². The results show that the proposed MPA is useful for various communications existing and emerging systems such as ultra-wideband (UWB) communications, RFID systems, massive multiple-output multiple-input (MIMO) for 5G, and radar systems.

In this paper, spatial pulse position modulation (SPPM) is used as a case study to investigate the performance of the optical spatial modulation (SM) technique in outdoor atmospheric turbulence (AT). A closed-form expression for the upper bound on the asymptotic symbol error rate (SER) of SPPM in AT is derived and validated by closely-matching simulation results. The error performance is evaluated in weak to strong AT conditions. As the AT strength increases from the weak to strong, the channel fading coefficients become more dispersed and differentiable. Thus, a better error performance is observed under moderate-to-strong AT compared to weak AT. The performance in weak AT can be improved by applying unequal power allocation to make FSO links more distinguishable at the receiver. Receive diversity is considered to mitigate irradiance fluctuation and improve the robustness of the system to turbulence-induced channel fading. The diversity order is computed as half of the number of detectors. Performance comparisons, in terms of energy and spectral efficiencies, are drawn between the SPPM scheme and conventional MIMO schemes such as repetition coding and spatial multiplexing.

Lenalidomide-based regimens are effective treatment options for patients with relapsed/refractory multiple myeloma (RRMM). However, they are associated with an increased risk of infectious complications. This study examines the clinical factors influencing the occurrence of infection in MM patients treated with lenalidomide and dexamethasone (Rd). A retrospective analysis of all patients who received the Rd regimen between 2017-2021 at our institution was performed. The study group consisted of 174 patients and the median age was 65 years. Most patients (n=110, 63.2%) received the Rd treatment in second-line treatment. The majority of patients (64.3%) received bortezomib-based regimens in the first line of treatment. The median progression-free survival was 12.6 (95% CI: 9.5 – 16.2) months, and the median overall survival was 22.3 (95% CI: 15.9 – 28.6) months. The overall response rate was 64.1%, 12.7% of patients achieved complete response and 20.4% had a very good partial response. In multivariate logistic regression analysis, hypoalbuminemia (OR 4.2, 95%CI:1.6-11.2, p= 0.0039), autologous hematopoietic stem cell transplantation (AHSCT) before Rd (OR 2.6, 95% CI:1.0- 6.7, p= 0.048) and anemia grade ≥3 (OR 5.0, 95%CI: 1.8-14.0, p= 0.002) were independent factors related to the occurrence of infections. In conclusion, in this large cohort of RRMM patients, AHSCT before Rd regimen therapy, hypoalbuminemia and anemia during treatment were identified as three independent factors influencing the frequency of infections during Rd therapy. Patients with established risk factors may benefit from optimal supportive therapy.

Human ether-a-go-go-related gene (hERG) potassium channel is well-known contributor to drug-induced cardiotoxicity and therefore an extremely important target when performing safety assessments of drug candidates. Ligand-based approaches in connection with quantitative structure active relationships (QSAR) analyses have been developed to predict hERG toxicity. Availability of the recent published cryogenic electron microscopy (cryo-EM) structure for the hERG channel opened the prospect for using structure-based simulation and docking approaches for hERG drug liability predictions. In recent time, the idea of combining structure- and ligand-based approaches for modeling hERG drug liability has gained momentum offering improvements in predictability when compared to ligand-based QSAR practices alone. The present article demonstrates uniting the structure-based SILCS (site-identification by ligand competitive saturation) approach in conjunction with physicochemical properties to develop predictive models for hERG blockade. This combination leads to improved model predictability based on Pearson’s R and percent correct (represents rank-ordering of ligands) metric for different validation sets of hERG blockers involving diverse chemical scaffold and wide range of pIC50 values. The inclusion of the SILCS structure-based approach allows determination of the hERG region to which compounds bind and the contribution of different chemical moieties in the compounds to blockade, thereby facilitating the rational ligand design to minimize hERG liability.

Obesity has become a rising global health problem affecting adults’ quality of life. The objective of this study was to describe the prevalence of obesity in Indonesian adults based on the cluster of islands. The study was also aimed to identify the risk factors of obesity in each island cluster. This study analysed secondary data of Indonesian Basic Health Research 2018. Our data for analysis comprised 688,638 adults (>=15 years) randomly selected using proportionate to population size throughout Indonesia. We included 20 variables for sociodemographic and obesity-related risk factors for analysis. Obese status was defined using Body Mass Index (BMI) >= 27.5 kg/m2. Our current study defined seven major islands cluster as the unit analysis consisting of 34 provinces in Indonesia. Descriptive analysis was conducted to determine the characteristics of the population and to calculate the prevalence of obesity within provinces in each of the island’s clusters. Multivariate logistic regression analyses to calculate odds ratios (ORs) was performed using R version 3.6.3. The study results showed that all island clusters had at least one province with an obesity prevalence of more than 20%. Six out of twenty variables, comprising four diet factors (consumption of sweet food, high-salt food, meat food, and carbonated drinks) and two other factors (mental health disorders and smoking behaviour), varied across the island clusters. In conclusion, there was a variation of obesity prevalence of the provinces within and between island clusters. Variation of risk factors raised in each cluster island suggested the government rethink and reframe the intervention to address obesity.

This paper will discuss the application of statistic modeling to interpret a health system crisis in Sri Lanka due to COVID- 19.A strong focus on the preventive approach and the contact tracing with the utilization of available resources in a rational manner describes Sri Lanka’s response towards COVID- 19 prevention and mitigation. The early contact tracing, preemptive quarantining, isolation, and treatment were implemented as a concerted effort. This approach, proven efficient during the early phase of the pandemic, was sustainable when there was a rapid increase in the COVID- 19 patients since July 2021, exceeding the health system capacity.The country’s COVID- 19 situation during the period from 01st of August 2021 to 31st of October 2021 was taken into consideration. Variables used for analysis were; total number of cases, recovered cases, comorbid and O₂ dependent patients, ICU patients, and deaths. The regression model was applied to analyze the data by using the EViews 12 (x64) software application.The correlation coefficients of all the independent variables under consideration implies that they have a strong positive relationship with the number of deaths occurred during the said period. According to the computed multiple linear regression model, the number of positive cases and O₂ dependents have a positive relationship with the dependent variable. Further, the Durbin- Watson stat value of the model and multicollinearity test reflect that it is free from serial correlation thereby the model is fit. From the perspective of epidemiological control, these findings highlight the importance of keeping the number of cases within the limits of health system capacity.

Despite extensively investigating the impact of social media on fashion products’ marketing, little evidence is available on how the platforms influence sales prediction. Focusing on Lolita fashion, this study investigates the impact of social media marketing on the sales volume prediction of fashion products. Essentially, we analyzed marketing data, including comments, likes, and shares from the Weibo social platform, to forecast future sales, examine how to enhance profit performance, and make production decisions. Using a quantitative approach, we tested three different prediction models, including multiple regression, decision tree, and XGBoost. The results revealed that increasing comments and decreasing the number of likes could significantly improve the sales volumes of Lolita products. In contrast, shares exerted a less significant impact on sales. Regarding prediction models, XGBoost was found to be the best method. In the fashion industry, social media is a useful tool for forecasting market trend. A limitation of this study is that only one social media platform was used to extract data, which might limit the generalization of the findings.

In this paper we deal with the resolution of a fuzzy multiobjective programming problem using the level sets optimization. We compare it to other optimization strategies studied until now and we propose an algorithm to identify possible Pareto efficient optimal solutions.

Multiple sclerosis (MS) is a chronic autoimmune disease that affects the central nervous system (CNS) characterized by varying degrees of demyelination of uncertain etiology, and is associated with specific environmental and genetic factors. Upon recognition of CNS antigens, the immune cells initiate an inflammatory process which leads to destruction and deterioration of the neurons. Innate immune cells such as macrophages, dendritic cells and natural killer cells are known to play critical roles in the pathogenesis of MS. Also, the activation of peripheral CD4+ T cells by CNS antigens leads to their extravasation into the CNS causing damages that exacerbates the disease. This could be accompanied by dysregulation of T regulatory cells and other cell types functions. Experimental autoimmune encephalomyelitis (EAE) is a mouse model used to study the pathophysiology of MS disease. In this review, we highlight the roles of innate and adaptive immune players in the pathogenesis of MS and EAE.

Paper-based microfluidic analysis devices (μPADs) have attracted attention as a cost-effective platform for point-of-care testing (POCT), food safety, and environmental monitoring. Recently, three-dimensional (3D)-μPADs have been developed to improve the performance of μPADs. For accurate diagnosis of diseases, however, 3D-μPADs need to be developed to simultaneously detect multiple biomarkers. Here, we report a 3D-μPADs platform for the detection of multiple biomarkers that can be analyzed and diagnosed with a smartphone. The 3D-μPADs were fabricated using a 3D digital light processing printer and consisted of a sample reservoir (300 µL) connected to 24 detection zones (of 4 mm in diameter) through 8 microchannels (of 2 mm in width). With the smartphone application, eight different biomarkers related to various diseases were detectable in concentrations ranging from normal to abnormal conditions: glucose (0–20 mmol/L), cholesterol (0–10 mmol/L), albumin (0–7 g/dL), alkaline phosphatase (0–800 U/L), creatinine (0–500 µmol/L), aspartate aminotransferase (0–800 U/L), alanine aminotransferase (0–1000 U/L), and urea nitrogen (0–7.2 mmol/L). These results suggest that 3D-µPADs can be used as a POCT platform for simultaneous detection of multiple biomarkers.

Introduction: Multiple sclerosis (MS) is a demyelinating, chronic, inflammatory and autoimmune disease of the central nervous system (CNS) with axonal degeneration, presenting a progressive and variable course. MS patients usually have complications, such as bladder dysfunction, presence of urinary symptoms and Urinary Tract infection (UTI), which is one of the three most common non-neurological complications in MS patients. Objective: Analyze the most diverse aspects of UTI in MS patients, focusing on risk factors, prevalence, hospitalization and mortality rates of UTIs in this group. Methods: A non-systematic review of articles published on PubMed in the last 10 years with the search terms "Urinary Tract Infection" AND "Multiple Sclerosis". Discussion: MS patients have a high UTI prevalence, mainly due to the occurrence of urinary disorders in these patients. The most common symptoms of UTI in MS patients are urinary urgency, polyuria, nocturia, urinary retention, and incontinence. Escherichia coli, Pseudomonas aeruginosa, and Klebsiella pneumoniae were the most found organisms and treatment is based on antibiotic therapy. Moreover, UTIs can precipitate outbreaks, worsen the disease, causing more damage and a severe neurological condition deterioration. Therefore, UTIs in this group are associated with a high hospitalizations rate and a high mortality rate. Conclusion: UTI represents a great risk and concern in MS patients. The high prevalence, hospitalization rate and mortality rate of UTI in MS is worrying, such as the cause-consequence relationship between UTIs and the use of corticosteroids in outbreaks. Therefore, it is important to be aware of a UTI in this group to make early diagnoses, adequate management, and new infections prevention. Thus, further studies are needed to thoroughly analyze each nuance of this important comorbidity for MS patients.

World Health Organization (WHO) provides the guideline for managing the Particulate Matter (PM) level because when the PM level is higher, it threats the human health. For managing PM level, the procedure for measuring PM value is needed firstly. We use Tapered Element Oscillating Microbalance (TEOM)-based PM measuring sensors because it shows higher cost-effectiveness than Beta Attenuation Monitor (BAM)-based sensor. However, TEOM-based sensor has higher probability of malfunctioning than BAM-based sensor. In this paper, we call the overall malfunction as an anomaly, and we aim to detect anomalies for the maintenance of PM measuring sensors. We propose a novel architecture for solving the above aim that named as Hypothesis Pruning Generative Adversarial Network (HP-GAN). We experimentally compare the several anomaly detection architectures to certify ours performing better.

Background and objectives: Patients with multiple sclerosis (MS) have many potential factors (spasticity, immobilization, glucocorticoids use) which can deteriorate the anthropometrical status and body composition and may have the potential impact on the functional mobility and basic motor skills improvement after physiotherapy. The aim of the study was to assess the functional mobility and basic motor skills in patients with MS and to correlate them with disability and anthropometrical status and body composition parameters. Materials and Methods: Timed Up-and-Go test (TUG), and six-minute walk test (6MWT) were performed in 36 patients with MS before and after 4 weeks of physiotherapy. Body mass index (BMI), waist to height ratio (W/HtR), and waist-to-hip ratio (WHR) were assessed in this group. Body composition was evaluated by bioelectrical impedance analysis (BIA) and fat mass (FAT), fat free mass (FFM), total body water (TBW) and predicted muscle mass (PMM) were expressed as percentage of body mass. Clinical status was assessed by EDSS and AI scales. Results: After physiotherapy, there was a significant improvement in functional mobility and basic motor skills assessed by total distance in 6MWT (p<0.001) and in TUG trials (p<0.001). Positive significant correlations were found between the results obtained in both tests (either before and after physiotherapy) vs. FFM, TBW and PMM, whilst worse results in functional mobility and basic motor skills correlated significantly with higher WHtR, WHR and FAT (p<0.05). Clinical status (EDSS) were significantly related to the WHtR and body composition parameters with the same manner as the results in the either 6MWT and TUG. However, there were no significant relationships between BMI vs. either clinical status (EDSS, AI) and functional mobility tests results in patients with MS. Conclusions: Functional mobility and basic motor skills may be significantly improved during the physiotherapy, but they are related to the anthropometrical status and body composition of MS patients. Moreover, disability status is also significantly related to this parameters. Body composition deterioration seems to be the important target for the therapeutic intervention in MS patients. For proper nutritional status assessment in patients with MS, body composition analysis or WHtR instead BMI should to be used.

In this study, in order to explore the failure mode of ZnO varistors under multiple lightning stroke, a 5-pulse 8/20 μs nominal lightning current with pulse intervals of 50 ms was applied to the ZnO varistors. Scanning electron microscopy (SEM) and X-ray diffractometry (XRD) were used to analyze the microstructure of the material. The failure processes of ZnO varistors caused by multiple lightning impulse current were described. The performance changes of ZnO varistors after multiple lightning impulses were analyzed from macro and micro perspectives. According to the results of this study’s experiments, the macroscopic failure mode of the ZnO varistors after multiple lightning impulse was that the electrical parameters deteriorate rapidly with the increase of the number of impulse groups, and finally destroyed by side-corner cracking. The microstructural examination indicated that after the multiple lightning strokes, the proportion of Bi in the several crystal phases had been converted, the grain size of ZnO varistors became smaller, and the white intergranular phase (Bi-rich grain boundary layer) increased significantly. The failure mechanism was thermal damage and grain boundary structure damage caused by temperature gradient thermal stress generated by multiple lightning current.

Using the sustainable livelihoods analytical framework, adaptability of cattle raising to multiple stressors (e.g. climate change and market conditions) in the dry tropics of Chiapas, Mexico was evaluated. Three case studies located in the Frailesca region of Chiapas were analyzed: (I) peasant cattle raising in a rural village in the Frailesca Valley; (II) peasant cattle raising in a rural village in a natural protected area in the Frailesca Highlands; and (III) holistic cattle raising by farmers with private land ownership in the Frailesca Valley. Adaptability was evaluated using an index on a scale of one to a hundred; average values were: case I = 20.9 ± 1.4; case II = 32.1 ± 1.8; and case III = 63.6 ± 3.5. In order to increase farms adaptability and reduce the vulnerability of cattle raising families, there is a need to modify public policy to take into account the conditions of the most vulnerable farmers (cases I and II). Given the economic, environmental, and social context of Mexico´s dry tropics, establishing ecological or organic cattle raising and silvopastoral systems may reduce the vulnerability of farm families and increase their level of adaptability of their farms to multiple stressors.

The increased deployment of IoT devices in specific areas results in an interference among them and the quality of communications can be severely degraded. To deal with this interference issue, the IEEE 802.11ax standard has been established in hyper-densely wireless networking systems. The 802.11ax adopts a new candidate technology that is called multiple network allocation vector in order to mitigate the interference problem. In this paper, we point out potential problem in multiple network allocation vector which can cause delays to the communication among IoT devices in hyper-dense wireless networks. Furthermore, this paper introduces an adaptive beam alignment algorithm for interference issue resolution. In addition, we analyze potential delays of communications among IoT devices under interference conditions. Lastly, we simulate our proposed algorithm in densely deployed environment and show that the interference issue can be mitigated and the IEEE 802.11ax-based IoT devices can utilize the air interface more fairly compared to conventional IEEE 802.11 distributed coordination function.

Multiple sclerosis (MS) is an immune-mediated, chronic inflammatory disease of the central nervous system (CNS), characterized by demyelination, axonal degeneration, and cognitive impairment. It also has an important impact on the quality of life of patients and their family members. An estimated 2,500,000 people in the world have multiple sclerosis. Neurophysiological parameters, like sensitivity to demyelination and the strength of excitatory and inhibitory synaptic interactions in the cerebral cortex, can be identified through transcranial magnetic stimulation (TMS) in patients affected by multiple sclerosis (MS). These parameters can be valid and objective parameters that can be correlated with the progression of MS, and can provide reliable indices for the severity of illness and the efficacy of drugs used to treat it. The discovery of specific and detailed neurophysiological parameters as surrogate end points for disease activity could represent an important step in clinical trials. Changes in cortical connectivity have already been demonstrated in MS, but in clinical practice, other measures are usually used to evaluate disease activity. We speculate that TMS may be more effective in identifying disease progression that leads to long-term disability, compared to standard surrogate markers, due to the fact that it represents a direct measure of synaptic transmission(s) in MS.

Good data analysis is required for the optimal design of water resources projects. However, data are not regularly collected due to material or technical reasons, which results in incomplete-data problems. Available data and data length are of great importance to solve those problems. Various studies have been conducted on missing data treatment. This study used data from the flow observation stations on Yeşilırmak River in Turkey. In the first part of the study, models were generated and compared in order to complete missing data using ANFIS, multiple regression and Normal Ratio Method. In the second part of the study, the minimum number of data required for ANFIS models was determined using the optimum ANFIS model. Of all methods compared in this study, ANFIS models yielded the most accurate results. A 10-year training set was also found to be sufficient as a data set.

In multi-objective optimization problems, the optimization target is to obtain a set of non-dominated solutions. Comparing solution sets is crucial in evaluating the performances of different optimization algorithms. The use of performance indicators is common in comparing those sets and, subsequently, optimization algorithms. A good solution set must be close to the Pareto-optimal front, well-distributed, maximally extended and fully filled. Therefore, an effective performance indicator must encompass these features as a whole and must be Pareto dominance compliant. Unfortunately, some of the known indicators often fail to properly reflect the quality of a solution set or cost a lot to compute. This paper demonstrates that the Degree of Approximation (DOA) quality indicator, is a weakly Pareto compliant unary indicator that gives a good estimation of the match between the approximated front and the Pareto-optimal front. Moreover, DOA computation is easy and fast.

A novel determination method using flow-through cartridge purification and ultra-high-performance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS) was developed for the identification and quantification of 30 mycotoxins (aflatoxin B1, B2, G1, G2, sterigmatocysin, T-2 toxin, diacetoxyscirpenol, roquefortine C, methylergonovine, ergocornine, lysergol, enniatin A, enniatin A1, enniatin B, enniatin B1, beauvericin, deoxynivalenol, 3-acetylDeoxynivalenol, 15-acetylDeoxynivalenol, patulin, verruculogen, neosolaniol, gliotoxin, HT-2 toxin, wortmannin, zearalenone, α-zearalenol, β-zearalenol, α-zearalanol, and β-zearalanol) in feedstuffs. Mycotoxins were extracted from sample by 0.1% formic acid aqueous solution/acetonitrile (16/84 v/v), then purified by a Cleanert® MC clean-up column. As a result, the pigments and other matrices were efficient removed from the sample extract solution. The purified eluate was collected, then evaporated and redissolved by 0.1% formic acid aqueous solution/acetonitrile (70:30 v/v) for UPLC-MS/MS detection. A BEH Shield RP18 chromatographic column was employed for separation of 30 mycotoxins in a total of 14 min. Multiple-reaction monitoring (MRM) mode was applied for qualitative and quantitative analysis, and matrix calibration curves obtained with the external-standard method was used for quantitation of target analytes. Under optimized conditions, the linearity range was from 2 to 1000 ng/g, and the limit of quantification of the developed method was from 2 to 50 ng/g. The recoveries of 30 mycotoxins spiked in urine samples were from 72.0% to 118.5%, and the relative standard deviation was below 20%. The method was also well approved by certified reference sample, and applied on the real feedstuff samples testing successfully.

The purpose of the study is to empirically analyze the effect of quality of governance on tax revenue in South Africa. This is done by analyzing a time series dataset covering 1996 to 2020. The study used voice and accountability, regulatory quality, government effectiveness, control of corruption, political stability and rule of law as proxies of quality of governance. Multiple regression analysis was performed to test hypotheses. Based on the regression results, all quality of governance variables in South Africa have a negative effect on tax revenue except corruption control. The findings of this study also include policy recommendations. The government of South Africa must design and implement effective ways to combat poor governance, which results in a tax revenue shortfall.

The emerging advancements in separation and classification of various biological matters (e.g., living cells and proteins) using magnetic levitation (MagLev) technology have proven to be effective for improving disease diagnostics. MagLev technique has the capacity to detect and separate useful diagnostic biomarkers from biocomplex environments (e.g., blood and plasma), minimizing the unpleasant daunting task of sample preparations and labeling procedures. Here, we demonstrate the capability of this technique combined with image analysis and machine learning approaches for discriminating the various types of multiple sclerosis (MS) as an important model disease. To arrive at a systematic expert system, we combined robust statistical analysis with machine learning to (1) detect and remove outliers from the raw MagLev image datasets; then (2) process the images and output a low dimensional representation of massive data without losing the main statistical features; and finally (3) predict the MS clinical disease type (Relapsing-Remitting, Primary–Progressive, or Secondary–Progressive) using a classifier. This is expected to improve MS diagnostics since the current practices rely solely on clinical observation and central nervous system imaging, making management approaches are often reactional and inefficient. Thus, there is a need to identify the disease type early on. MagLev is expected to improve MS diagnostics, thereby aiding in prognosis and guiding adequate treatment choices before the patient exhibits signs of permanent neurological deficits.

Introduction: multiple sclerosis (MS) is the most common immune-mediated chronic neurodegenerative disease of the central nervous system (CNS), affecting young people. Due to the permanent disability, cognitive impairment, and the enormous detrimental impact MS can exert on the patients’ health-related quality of life. It is of great importance to recognise it in time and commence adequate treatment at an early stage. The currently used disease-modifying therapies (DMT) aim to reduce disease activity and thus halt disability development, which in current clinical practice are monitored by clinical and imaging parameters but not by biomarkers found in blood and/or the cerebrospinal fluid (CSF). Both clinical and radiological measures routinely used to monitor disease activity lack information on the fundamental pathophysiological features and mechanisms of MS. Furthermore, they lag behind the disease process itself. By the time a clinical relapse becomes evident or a new lesion appears on the MRI scan, potentially irreversible damage has already occurred in the CNS. In recent years several biomarkers that previously have been linked to other neurological and immunological diseases have received increased attention in MS. Additionally, other novel, potential biomarkers with prognostic and diagnostic properties have been detected in the CSF and blood of MS patients. Areas covered: in this review, we summarise the most up to date knowledge and research conducted on the already known and most promising new biomarker candidates found in the CSF and blood of MS patients. Author commentary: the current diagnostic criteria of MS rely on three pillars; MRI imaging, clinical events and the presence of oligoclonal bands in the CSF (which was reinstated into the diagnostic criteria by the most recent revision). Even though the most recent McDonald criteria made the diagnosis of MS faster than the prior iteration, it is still not an infallible diagnostic toolset, especially at the very early stage of clinically isolated syndrome. Together with the gold standard MRI and clinical measures, ancillary blood and CSF biomarkers may not just improve diagnostic accuracy and speed but very well may become agents to monitor therapeutic efficacy and make even more personalised treatment in MS a reality in the near future. The major disadvantage of these biomarkers in the past has been the need to obtain CSF to measure them. However, the recent advances in extremely sensitive immunoassays made their measurement possible from peripheral blood even when present only in minuscule concentrations. This should mark the beginning of a new biomarker research and utilisation era in MS.

The discovery of microRNAs (miRNAs) has fundamentally transformed our understanding of gene regulation. The competing endogenous RNA (ceRNA) hypothesis postulates that not only messenger RNAs but also other RNA transcripts, such as long non-coding RNAs and pseudogenes, can act as natural miRNA sponges. These RNAs influence each other’s expression levels by competing for the same pool of miRNAs through miRNA response elements on their target transcripts, thereby modulating gene expression and protein activity. In recent years, these ceRNA regulatory networks have gained considerable attention in cancer research. Several studies have identified cancer-specific ceRNA networks. Nevertheless, prior bioinformatic analyses have focused on long non-coding RNAs-associated ceRNA networks. Here, we identify an extended-ceRNA network (including both long non-coding RNAs and pseudogenes) shared across a group of four hormone-dependent (HD) cancers, i.e., prostate, breast, colorectal, and endometrial cancers, using data from The Cancer Genome Atlas (TCGA). We performed a functional enrichment analysis for differentially expressed genes in the shared ceRNA network of HD cancers, followed by a survival analysis to determine their prognostic ability. We identified two long non-coding RNAs, nine genes, and seventy-four miRNAs in the shared ceRNA network across four HD cancers. Among them, two genes and forty-one miRNAs were associated with at least one HD cancer survival. This study is the first to investigate pseudogene associated ceRNAs across a group of related cancers and highlights the value of this approach to understanding shared molecular pathogenesis in a group of related diseases.

While multiple myeloma (MM) treatment with proteasome inhibitors and other agents yields encouraging results, primary and secondary resistance remains an emerging problem. An important factor in such treatment resistance is the overexpression of several proteins. The present study comprehensively evaluates the expression of POMP, PSMB5, NRF2, XBP1, cMAF and MAFb proteins in plasma cells isolated from the bone marrow of 39 MM patients treated with bortezomib-based regimens using enzyme-linked immunosorbent assay (ELISA). The proteins were selected on the basis of previous laboratory and clinical studies in bortezomib treated MM patients. It was found that the expression of the investigated proteins did not significantly differ between bortezomib-sensitive and bortezomib-refractory patients. However, the expression of some proteins correlated with overall survival (OS); this was significantly shorter in patients with higher POMP expression (HR 2.8, 95% CI: 1.1-7.0, p = 0.0277) and longer in those with higher MAFB expression (HR 0.32, 95% CI: 0.13-0.80, p = 0.0147). Our results indicate that high expression of POMP and MAFB in MM plasma cells may serve as predictors of OS in MM patients treated with bortezomib-based regimens. However, further studies are needed to determine the role of these factors in effective strategies for improving anti-myeloma therapy.

The development of mobile technology and internet mobile offers new possibilities in both rehabilitation and for patients’ assessment in a longitudinal and MS management perspective. However, because the mobile health applications (mHealth) have only been developed recently, the level of evidence supporting the use of mHealth in patients with multiple sclerosis (pwMS) is currently unclear. Therefore, this study aims to list and describe the different mHealth available for rehabilitation and self-assessment of pwMS and to define the level of evidence supporting these interventions for functioning problems categorized within the International Classification of Functioning, Disability and Health (ICF). 36 studies, performed with 22 different mHealth, were included in this review, 30 about rehabilitation and 6 for self-assessment, representing 3,091 patients. For rehabilitation, most of the studies were focusing on cognitive function and fatigue. Concerning the efficacy we found a small but significant effect of the use of mHealth for cognitive training (SMD = 0.28 [0.12 ; 0.45]) and moderate effect for fatigue (SMD = 0.61 [0.47 ; 0.76]). mHealth is a promising tool in pwMS but more studies are needed to validate these solutions in the others ICF categories. More replications studies are also needed as most of the mHealth have only been assessed in one single study.

Background: The human mind is multimodal. Yet most behavioral studies rely on century-old measures such as task accuracy and latency. To create a better understanding of human behavior and brain functionality, we should introduce other measures and analyze behavior from various aspects. However, it is technically complex and costly to design and implement the experiments that record multiple measures. To address this issue, a platform that allows synchronizing multiple measures from human behavior is needed. Method: This paper introduces an opensource platform named OpenSync, which can be used to synchronize multiple measures in neuroscience experiments. This platform helps to automatically integrate, synchronize and record physiological measures (e.g., electroencephalogram (EEG), galvanic skin response (GSR), eye-tracking, body motion, etc.), user input response (e.g., from mouse, keyboard, joystick, etc.), and task-related information (stimulus markers). In this paper, we explain the structure and details of OpenSync, provide two case studies in PsychoPy and Unity. Comparison with existing tools: Unlike proprietary systems (e.g., iMotions), OpenSync is free and it can be used inside any opensource experiment design software (e.g., PsychoPy, OpenSesame, Unity, etc., https://pypi.org/project/OpenSync/ and https://github.com/moeinrazavi/OpenSync_Unity). Results: Our experimental results show that the OpenSync platform is able to synchronize multiple measures with microsecond resolution.

Non-orthogonal multiple access (NOMA) has been investigated to support massive connectivity for Internet-of-things (IoT) networks. However, since most IoT devices suffer from limited power and decoding capabilities, it is not desirable to pair a large number of devices simultaneously, which encourages two-user NOMA grouping. Additionally, most existing techniques have not considered the diversity in the target QoS of IoT devices, which may lead to spectrum inefficiency. Few investigations have partially considered that issue by using an order-based power allocation (OPA) approach, where the power is allocated according to the order to the user's target throughput within a priority-based NOMA (PNOMA) group. However, this does not fully capture the effects of diversity in the values of the users' target throughputs. In this work, we handle both problems by considering a throughput-based power allocation (TPA) approach, that captures the QoS diversity, within a three-users PNOMA group as a compromise between spectral efficiency and complexity. Specifically, we investigate the performance of a time-division PNOMA (TD-PNOMA) scheme, where the transmission time is divided into two-time slots with two-users per PNOMA group. The performance of such TD-PNOMA is compared with a fully PNOMA (F-PNOMA) scheme, where the three users share the whole transmission time, in terms of the ergodic capacity under imperfect successive interference cancellation (SIC). The results reveal the superiority of TPA compared with OPA approach in both schemes, besides that the throughput of both schemes can outperform each other under imperfect SIC based on the transmit signal-to-noise ratio and the deployment scenarios.

The frame construction of an apartment complex that consists of multiple buildings encounters various uncertainties, owing to the complex relationships among units of work. Currently, the period of such a construction is calculated based on the number of floors of the highest building in the complex. This study quantitatively analyzes an apartment frame construction period using a queue model and evaluates the validity of the estimated period. In this regard, a methodology is proposed for analyzing the construction period by applying the concept of a customer and a server. A case study on the duration of an apartment frame construction is conducted with Korea Land and Housing Corporation, which has supplied the largest number of apartments in South Korea. It was found that the stable state of a queue system was observed when the rate of server utilization was applied to the basement and aboveground floors. However, a stable state was not reached on the ground floor. This study includes non-working days in its calculation and quantitatively analyzes uncertainty factors during construction. Therefore, the findings can be practically utilized to quantitatively plan the durations of work units in an apartment frame construction.

Multiple Myeloma (MM) is the second most common type of hematological disease and, although it is rare among patients under 40 years of age, its incidence rises in elderly subject. MM manifestations are usually known with the abbreviation CRAB (hyperCalcemia, Renal failure, Anaemia, and lytic Bone lesions). In particular, the extent of the bone disease is negatively related to a decreased patients’ quality of life and, in general, bone disease in MM increases both morbidity and mortality. The detection of lytic bone lesions on imaging, especially CT and MRI, is becoming crucial from the clinical viewpoint to separate asymptomatic from symptomatic MM patients and the detection of focal lytic lesion in these imaging data is becoming relevant even when no clinical symptoms are present. Therefore, radiology is pivotal in the staging and accurate management of patients with MM even in early phases of the disease. In this review we describe the opportunities offered by quantitative imaging and radiomics in multiple myeloma. At present time there is still high variability in the choice between various imaging methods to study MM patients and high variability in image interpretation with suboptimal agreement among readers even in tertiary centres. Therefore, the potential of medical imaging for patients affected by MM is still to be completely unveiled. In the next years, new insights to study MM with medical imaging will derive from artificial intelligence (AI) and radiomics usage in different bone lesions and from the wide implementations of quantitative methods to report CT and MRI. Eventually, medical imaging data can be integrated with the patient's outcomes with the purpose to find radiological biomarkers for predicting the disease prognostic flow and its therapeutic response.

Sequence alignment and comparison through pairwise, multiple, global and local techniques are the main principles that underpin comparative genomics. However, most of the algorithms used are alignment-based which imposed some limitations on their use and application. In an attempt to provide an alignment-free alternative approaches, a methodology of comparative optinalysis and statistical mirroring was used and adopted to provide a suitable alternative for multiple genomic sequence comparison. In this article, methods comparison with MUSCLE, MUFFT, Clustal Omega, and T-Coffee was designed to assess the suitability and statistical power of statistical mirroring as an alternative method for multiple genomic sequences comparison using different sets of logically generated biological sequence datasets with different problems and computational complications. The results of the comparisons validate that statistical mirroring is a suitable alignment-free alternative approach for multiple genomic sequence comparison. The applied method (statistical mirroring) distinguishes itself over MUSCLE, MUFFT, Clustal Omega, and T-Coffee in specificity to a position-specific changes, specificity to a base-specific changes, cladogram and phylogenetic linearity, alignment independency, computational simplicity, and limit of input capacity.

Mediterranean catchments are characterized by significant spatial and temporal hydrological variability caused by the interaction of natural as well human-induced abiotic and biotic factors. This study investigates the (non-)linearity rainfall-runoff relationship at multiple temporal scales in representative small Mediterranean catchments (i.e., < 10 km2) to achieve a better understanding of the hydrological response. Rainfall-runoff relationship was evaluated in 44 catchments at annual and event –203 events in 12 of these 44 catchments– scales. A linear rainfall-runoff relation was observed at annual scale with higher scatter in pervious than impervious catchments. Larger scattering was observed at event scale, although pervious lithology and agricultural land use promoted significant rainfall-runoff linear relations in winter and spring. These relationships were particularly analysed during five hydrological years in Es Fangar catchment (3.35 km2; Mallorca, Spain) as a temporal downscaling to assess intra-annual variability in which antecedent wetness conditions played a significant role in runoff generation.

Machine reading comprehension aims to teach machines to understand a text like a human, and is a new challenging direction in Artificial Intelligence. Datasets play an important role while describing or building an algorithm for machine reading comprehension. The type of answers we required from developed algorithm depends on datasets.The datasets are classified into two types, namely datasets with extractive answers and datasets with descriptive answers. This article summarize both datasets with an example of each type to get better insight of datasets in machine reading comprehension and which datasets to use depending the requirements.

Multiple myeloma (MM) is a genetically heterogenous disease that includes a subgroup of 10-15% of patients facing dismal survival despite most intensive treatment. The aim of this review article is to provide an integrated clinical and biological overview on the high-risk MM discussing the novel therapeutic perspectives aimed to target the neoplastic clone and its microenvironment. The dissection of the molecular determinants of the aggressive phenotypes and drug resistance can foster a better tailored clinical management of high-risk profile and refractoriness to therapy. Among the current clinical difficulties in MM, patient’s management manipulating the tumor niche represents a major challenge given the limited knowledge about the MM-milieu interaction. The angiogenesis and bystander infiltrate constitute pivotal mechanisms of mutual collaboration between MM and the non-tumoral counterpart. Immuno-modulatory and anti-angiogenic therapy hold great efficacy but variable and unpredictable responses in high-risk MM. Therefore, it would be worth to better select the population and the MM stage that could profit to a dual immune/vasculogenesis targeting. The comprehensive knowledge of the genetic heterogeneity and MM high-risk ecosystem enforce a systematic bench-to-bedside approach. Despite significant improvements in the biology knowledge, MM is still a chronic and incurable neoplasia and therapeutic options able to overcome the relapsing/refractory behavior represent an unmet clinical need. Here, we corroborate previous biological findings providing a synthetic outlook of novel druggable targets. We also summarize the existing multi-omics-based risk profiling tools, in order to better personalize the patient-oriented clinical management.

Multi-object tracking (MOT) in airborne videos is a challenging problem due to the uncertain airborne vehicle motion, vibrations of the mounted camera, unreliable detections, size, appearance and motion of the moving objects as well as occlusions due to the interaction between the moving objects and with other static objects in the scene.To deal with these problems, this work proposes a four-stage Hierarchical Association framework for multiple object Tracking in Airborne video (HATA). The proposed framework combines data association-based tracking (DAT) methods and target tracking using a Compressive Tracking approach, to robustly track objects in complex airborne surveillance scenes. In each association stage, different sets of tracklets and detections are associated to efficiently handle local tracklet generation, local trajectory construction, global drifting tracklet correction and global fragmented tracklet linking. Experiments with challenging airborne video datasets show significant tracking improvement compared to existing state-of-art methods.

Parallel manipulators with multiple end-effectors bring us interesting advantages over conventional parallel manipulators such as improved manipulability, workspace and avoidance of singularities. In this work the kinematics of a five-bar planar parallel manipulator equipped with two end-effectors is approached by means of the theory of screws. As an intermediate step the displacement analysis of the robot is also investigated. The input-output equations of velocity and acceleration are systematically obtained by resorting to reciprocal-screw theory. In that regard the Klein form of the Lie algebra se(3) of the Euclidean group SE(3) plays a central role. In order to exemplify the method of kinematic analysis, a case study is included. Furthermore, the numerical results obtained by means of the theory of screws are confirmed with the aid of special software like ADAMS.^TM

Chemokine C-C receptor 6 (CCR6) and its exclusive ligand CCL20 is an extremely important chemokine receptor-ligand pair which controls cell migration and immune induction during inflammatory disease. Not many scientific studies have been undertaken to study its immune mechanisms in detail, but its unique contribution to steady state cell chemotaxis in upholding immune tolerance and regulating immune homeostasis during inflammation is evident in multiple organ systems, including lung, liver, kidney, skin, brain, eye, joints, gonads and the gut in the human body. The role of CCR6 is constitutively expressed as a series of much debilitating severe inflammatory and autoimmune diseases, HIV and cancer metastasis. CD4⁺ T cells, the central organizers of adaptive immunity, are stringently mobilized by the CCR6/CCL20 axis also induced by cytokines and a host of other factors in a carefully executed immune modulation scenario, to bring about a delicate balance between pro-inflammatory T_H17 cells and regulatory T_reg cells. Although the exact immune regulatory role is not elucidated yet, CCR6/CCL20 axis is implicated as a front runner which determines the polarization of T_H17 and T_reg cells and consequently the resolution or progression of many debilitating disorders. This review therefore aims at emphasizing the pleiotropic significance of the chemokines CCR6 and CCL20 in immunologic function in multiple organ systems thereby hoping to accentuate its value in future therapeutic modalities.

Multiple sclerosis (MS) is a demyelinating autoimmune disorder of the central nervous system (CNS). Experimental autoimmune encephalomyelitis (EAE) has been widely used to determine the pathogenesis of the disease and evaluate new treatment strategies for MS. Therefore, we investigated the efficacy of oral administration of a Myelin Oligodendrocyte Glycoprotein (MOG) in the treatment of EAE. Female C57BL/6 mice were utilized in three groups (Control group: received PBS orally; prevention group: oral administration of MOG35-55 two weeks before EAE induction; treatment group: oral administration of MOG35-55 after EAE induction. MOG administration, both as prevention and treatment, significantly controlled clinical score, weight loss, CNS inflammation, and demyelination, mainly through the modulation of T cell proliferation, reduction of pro-inflammatory cytokines and transcription factors, including TNF-α, IFN-γ, IL-17, T-bet, and ROR-γt. MOG administration, both as prevention and treatment, also induced anti-inflammatory cytokines and transcription factors, including IL-4, TGF-β, GATA-3, and Foxp3. The results showed that oral administration of MOG, both as prevention and treatment, could efficiently control EAE development. Immunomodulatory mechanisms include the induction of Th2 and Treg cells and the suppression of pro-inflammatory Th1 and Th17 cells.

Fringe projection profilometry(FPP) has been extensively applied in various fields for its superior fast speed, high accuracy and high data density. However, measuring some objects with high reflective surfaces or high dynamic range surfaces remains challenging for FPP. Some multiple exposure image fusion methods have been proposed and successfully improved the measurement performance for these kinds of objects. Normally, these methods have a relatively fixed sequence of exposure settings determined by artificial experience or trial and error experiments, which may decrease the efficiency of the entire measurement process and may have less robustness to various environmental lighting conditions and object reflective properties. In this paper, a novel self-adaptive multiple exposure image fusion method is proposed with two main aspects of improvement on adaptively optimizing the initial exposure and the exposure sequence. By introducing the theory of information entropy, combined with the analysis of the characterization of fringe image entropy, an adaptive initial exposure searching method is first proposed. Then, an exposure sequence generation method based on dichotomy is further described. On the base of these two improvements, a novel self-adaptive multiple exposure image fusion method for FPP as well as its detailed procedures are given. Experimental results validate the performance of the proposed self-adaptivity multiple exposure image fusion method by measuring the objects with different surface reflectivity and in different ambient lighting conditions.

Multiple sclerosis (MS) is a demyelinating autoimmune disorder of the central nervous system (CNS). Experimental autoimmune encephalomyelitis (EAE) has been widely used to determine the pathogenesis of the disease and evaluate new treatment strategies for MS. Therefore, we investigated the efficacy of oral administration of a Myelin Oligodendrocyte Glycoprotein (MOG) in the treatment of EAE. Female C57BL/6 mice were utilized in three groups (Control group: received PBS orally; prevention group: oral administration of MOG35-55 two weeks before EAE induction; treatment group: oral administration of MOG35-55 after EAE induction. MOG administration, both as prevention and treatment, significantly controlled clinical score, weight loss, CNS inflammation, and demyelination, mainly through the modulation of T cell proliferation, reduction of pro-inflammatory cytokines and transcription factors, including TNF-α, IFN-γ, IL-17, T-bet, and ROR-γt. MOG administration, both as prevention and treatment, also induced anti-inflammatory cytokines and transcription factors, including IL-4, TGF-β, GATA-3, and Foxp3. The results showed that oral administration of MOG, both as prevention and treatment, could efficiently control EAE development. Immunomodulatory mechanisms include the induction of Th2 and Treg cells and the suppression of pro-inflammatory Th1 and Th17 cells.

Multiple sclerosis (MS) is a chronic autoimmune inflammatory disease that affects the nervous system. Peripheral blood leukocyte telomere length (LTL) and mitochondrial DNA copy number (mtDNA-CN) are potential biomarkers of disability and neurological damage. The present work evaluated LTL and mtDNA-CN in 75 relapsing-remittent MS (RRMS) patients 50 of whom had an Expanded Disability Status Scale (EDSS) 0 to 3 (mild-moderate disability), and 25 had an EDSS of 3.5 to 7 (severe disability). Absolute LTL and absolute mtDNA-CN were measured via real-time polymerase chain reaction (qPCR). The LTL and mtDNA-CN were significantly lower in RRMS severe disability than in RRMS mild-moderate disability (3.924 ± 0.124 vs 2.854 ± 0.092, p<00001; 75.14 ± 1.77 vs 68.06 ± 1.608, p<0.00001, respectively). The LTL and mtDNA-CN showed a linear correlation in RRMS with mild-moderate disability (r=0.2986, p=0.0351). In addition, in a binary logistic regression model the LTL can predict severe disability (AUC=0.697, p=0.0031, cutoff ≤ 3.0875 Kb, sensitivity= 73.1%, specificity=62.5%), the prediction is improved by including age to the model (AUC=0.765, <0.0001, sensitivity=78.26%, specificity=81.25%). Aging is closely linked to the development of disability in RRMS and can be evaluated through LTL and mtDNA-CN absolute quantification.

Multiple myeloma (MM) is characterized by the malignant proliferation of monoclonal plasma cells in the bone marrow with an elevation in monoclonal paraprotein, renal impairment, hypercalcemia, lytic bony lesions, and anemia. Immune cells and associated cytokines play a significant role in MM growth, progression, and dissemination. While some cytokines and their clinical significance are well described in MM biology, others remain relatively unknown. The aim of the present study was to assess the impact of pretreatment serum levels of 27 selected cytokines on progression-free survival (PFS) and overall survival (OS) in MM patients before first-line therapy with bortezomib-based regimens. Serum cytokine levels were assayed with a Bio-Rad Bio-Plex Pro Human Cytokine 27-Plex Assay on the MAGPIX Multiplex Reader and the Bio-Plex® 200 System (Bio-Rad) including IL-1β, IL-1Ra, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IL-9, IL-10, IL-12, IL-13, IL-15, IL-17, Eotaxin, FGF, G-CSF, GM-CSF, IFN-γ, IP-10, MCP-1, MIP-1α, MIP-1β, PDGF-BB, RANTES, TNF-α, and VEGF. A total of 61 MM patients were examined. Most patients received a bortezomib, cyclophosphamide and dexamethasone (VCD) chemotherapy regimen. In the final multivariate model, IL-13 cytokine level (HR 0.1411, 95% CI: 0.0240-0.8291, p = 0.0302), and ASCT (HR 0.3722, 95% CI: 0.1826-0.7585, p=0.0065) significantly impacted PFS. Furthermore, ASCT (HR 0.142, 95% CI: 0.046-0.438, p=0.0007), presence of bone disease at diagnosis (HR 3.826, 95% CI: 1.471-9.949, p=0.0059) and two cytokine levels- IL-1Ra (HR 1.017, 95% CI: 1.004-1.030, p= 0.0091) and IL-4 (HR 0.161, 95% CI: 0.037-0.698, p = 0.0147) were independent predictors of OS. Three clusters of MM patients were identified with different cytokine profiles. In conclusion, serum pretreatment levels of IL-13 and IL-4 are predictors of better PFS and OS, respectively, whereas IL-1Ra pretreatment levels negatively impact OS in MM patients treated with bortezomib-based chemotherapy. Cytokine signature profile may have a potential influence on the outcome of patients treated with bortezomib.

Multiple myeloma (MM) is a genetically complex disease that results from a multistep transformation of normal to malignant plasma cells in the bone marrow. However, the molecular mechanisms responsible for the initiation and heterogeneous evolution of MM remain largely unknown. A fundamental step needed to understand the oncogenesis of MM and its response to therapy is the identification of driver mutations. The introduction of gene expression profiling (GEP) in MM was an important step in elucidating the molecular heterogeneity of MM and its clinical relevance. Since some mutations in myeloma occur in non-coding regions, studies based on the analysis of mRNA provide more comprehensive information on the oncogenic pathways and mechanisms relevant to MM biology. In this review, we discuss the role of gene expression profiling in understanding the biology of multiple myeloma together with the clinical manifestation of the disease, as well as its impact on treatment decisions and future directions.

Multiple Myeloma (MM) is one of the incurable types of cancer in plasma cells. While immense progress has been made in the treatment of this malignancy, a large percentage of patients were unable to adapt to such therapy. Additionally, these therapies might be associated with significant diseases and are not always tolerated well in all patients. Since cancer in plasma cells has no cure, patients develop resistance to treatments, resulting in R/R MM. BCMA is primarily produced on mature B cells. Its up-regulation and activation are associated with multiple myeloma in both murine and human models, indicating that this might be an effective therapeutic target for this type of malignancy. Additionally, BCMA's predictive value, association with effective clinical trials, and capacity to be utilized in previously difficult to observe patient populations, imply that it might be used as a biomarker for multiple myeloma. Numerous kinds of BCMA-targeting medicines have demonstrated antimyeloma efficacy in individuals with refractory/relapsed MM, including CAR T-cell treatments, ADCs, bispecific antibody constructs. Among these medications, CART cell-mediated BCMA therapy has shown significant outcomes in multiple myeloma clinical trials. This review article outlines CAR T cell mediated BCMA medicines have the efficiency to change the therapeutic pattern for multiple myeloma significantly.

As the number of ships for marine transportation increases with the advancement of global trade, encountering multiple ships in marine traffic becomes common. This situation raises the risk of collision of the ships; hence this paper proposes a novel Fuzzy-logic based intelligent conflict detection and resolution algorithm, where the collision courses and possible avoiding actions are analyzed by considering ship motion dynamics and the input and output fuzzy membership functions are derived. As a conflict detection module, the Collision Risk (CR) is measured for each ship by using a scaled nondimensional Distance to the Closest Point of Approach (DCPA) and Time to the Closest Point of Approach (TCPA) as inputs. Afterwards, the decisions for collision avoidance are made based on the calculated CR, encountering angle and relative angle of each ship measured from others. In this regard, the rules for the Fuzzy interface system are defined in accordance with the COLREGs, and the whole system is implemented on the MATLAB Simulink platform. In addition, to deal with the multiple ship encounters, the paper proposes a unique maximum-course and minimum-speed change approach for decision making, which has been found to be efficient to solve Imazu problems, and other complicated multiple-ship encounters.

Multiple sclerosis (MS) is a chronic inflammatory neurodegenerative autoimmune disease characterized by aberrant infiltration of immune cells into the central nervous system (CNS) and by the loss of myelin. Sclerotic lesions and various inhibitory factors hamper remyelination processes within the CNS. MS patients typically experience gradual cognitive and physical disabilities as the disease progresses. The etiology of MS is still unclear and emerging evidence suggests that microbiome composition could play a much more significant role in disease pathogenesis than was initially thought. Initially believed to be isolated to the gut microenvironment, we now know that the microbiome plays a much broader role in various tissues and is essential in the development of the immune system. Here, we present some of the unexpected roles that the microbiome plays in MS and discuss approaches for the development of next-generation treatment strategies.

This paper proposes a model to evaluate business projects to get into an incubator, allowing to rank them in order of selection priority. The model combines the Momentum method to build prospective scenarios and the Multiple Criteria Decision Making (MCDM) method TOPSIS-2N to rank the alternatives. Six business projects were evaluated to be incubated. The Momentum method made it possible for us to create an initial core of criteria for the evaluation of incubation projects. The TOPSIS-2N method supported the decision to choose the company to be incubated by ranking the alternatives in order of relevance. Our evaluation model has improved the existing models used by incubators. This model can be used and / or adapted by any incubator to evaluate the business projects to be incubated. The set of criteria for the evaluation of incubation projects is original and the use of prospective scenarios with a MCDM method to evaluate companies to be incubated does not exist in the literature.

To assess cognitive impairment and affective symptoms and their association with damage to normal-appearing white matter (NAWM) in patients with clinically isolated syndrome (CIS), we compared neuropsychological test scores between patients with CIS and healthy controls, and examined correlations between these and proton magnetic resonance spectroscopy (1H-MRS) outcomes in patients with CIS. Forty patients with CIS and 40 healthy participants were tested with the set of neuropsychological tests, the Beck Depression Inventory (BDI) and the Hospital Anxiety and Depression Scale (HADS). Single-voxel 1H-MRS was performed on frontal and parietal NAWM of patients with CIS to assess ratios of N-acetyl-aspartate (NAA) to creatine (Cr), myo-inositol (mI), and choline (Cho), as well as mI/Cr and Cho/Cr ratios. Patients with CIS had lower cognitive performance, higher scores for the BDI and anxiety subscale of HADS than healthy controls. There were significant correlations between the following neuropsychological tests and metabolic ratios in the frontal NAWM: Stroop Color-Word Test and Cho/Cr, Symbol Digit Modalities Test and mI/Cr as well as NAA/mI, Go/no-go reaction time and NAA/Cho as well as NAA/mI, Californian Verbal Learning Test and NAA/Cr. BDI scores were related to frontal NAA/mI and parietal NAA/Cr and Cho/Cr ratios, whereas HADS-depression scores were associated with frontal NAA/Cr and NAA/mI, and parietal NAA/Cr and Cho/Cr ratios. HADS-anxiety correlated with parietal NAA/Cr ratio. This study suggests that neurochemical changes in the NAWM assessed with single-voxel 1H-MRS are associated with cognitive performance and affective symptoms in patients with CIS.

Worldwide, over 2.2 million people are suffered from multiple sclerosis (MS), a multifactorial demyelinating disease of the central nervous system. MS is characterized by a wide range of motor, autonomic, and psychobehavioral symptoms including depression, anxiety, and dementia. The blood, cerebrospinal fluid, and postmortem brain samples of MS patients evidenced the disturbance of reduction-oxidation (redox) homeostasis such as the alterations of oxidative and antioxidative enzyme activities and the presence of degradation products. This review article discussed the components of redox homeostasis including reactive chemical species, oxidative enzymes, antioxidative enzymes, and degradation products. The reactive chemical species covered frequently discussed reactive oxygen/nitrogen species, infrequently featured reactive chemicals such as sulfur, carbonyl, halogen, selenium, and nucleophilic species that potentially act as reductive as well as pro-oxidative stressors. The antioxidative enzyme systems covered the nuclear factor erythroid-2-related factor 2 (NRF2)-Kelch-like ECH-associated protein 1 (KEAP1) signaling pathway. The NRF2 and other transcriptional factors potentially become a biomarker sensitive to the initial phase of oxidative stress. Altered components of the redox homeostasis in MS were discussed in search of a diagnostic, prognostic, predictive, and/or therapeutic biomarker. Finally, monitoring a battery of reactive chemical species, oxidative enzymes, antioxidative enzymes and degradation products helps evaluate the redox status of MS patients to expedite building personalized treatment plans for the sake of better quality of life.

The involvement of macular function in its preganglionic elements, during the neurodegenerative process of multiple sclerosis (MS), is controversial. In this case-control observational and retrospective study, we assessed multifocal electroretinogram (mfERG) responses from 41 healthy Controls, 41 relapsing-remitting MS patients without optic neuritis (ON) (MS-noON Group), 47 MS patients with ON: 27 with full recovery of high-contrast best corrected visual acuity (BCVA) (MS-ON-G Group) and 20 with poor recovery of BCVA (MS-ON-P Group). MfERG N1 and P1 implicit times (ITs), and N1-P1 response amplitude densities (RADs) were measured from concentric rings (R) with increasing foveal eccentricity: 0-5° (R1), 5-10° (R2), 10-15° (R3), 15-20° (R4), 20- 25° (R5), and from retinal sectors [superior, nasal, inferior and temporal] between 0-15° and 0- 25°. In MS-ON-P Group, mean mfERG RADs detected from R1 (0-5°) and from the central nasal quadrant (0-15°) were significantly reduced (p<0.01) with respect to those of Control, MS-noON and MS-ON-G Groups. No other significant differences between Groups for any mfERG parameters were found. Our results suggest that in MS, exclusively after ON with poor recovery of BCVA, the neurodegenerative process can induce dysfunctional mechanisms involving photoreceptors and bipolar cells of the fovea and of the more central nasal macular area.

A lightweight image encryption algorithm based on chaos induction via a 5-dimensional hyperjerk oscillator (5DHO) is presented. First, the dynamics of our 5DHO network is investigated and shown to exhibit up to five coexisting hidden attractors in the state space that depend exclusively on the system’s initial values. Further, a simple implementation of the circuit was used to validate its ability to exhibit chaotic dynamical properties. Second, an Arduino UNO platform is used to confirm the usability of our oscillator in digital implementation of the system. Finally, an efficient image encryption application is executed using the proposed chaotic networks based on the use of permutation-substitution sequences. The superior qualities of the proposed strategy are traced to the dynamic set of keys used in the substitution process which heralds the generation of the final ciphered image. Based on the results obtained from the entropy analysis (7.9976), NPCR values (99.62), UACI tests (33.69) and encryption execution time for 512x512 images (0.1179 sec), the proposed algorithm is adjudged to be fast and robust to differential and statistical attacks relative to similar approaches.

In recent years, autonomous robots have proven capable of solving tasks in complex environments. In particular, robot manipulations in activities of daily living (ADL) for service robots have been in wide use. However, manipulations such as loading a dishwasher or folding laundry are difficult to automate robustly. In addition, manipulations of grasping multiple objects in domestic environments present difficulty. To perform those applications better, we developed robotic systems based on shared autonomy by combining the cognitive skills of a human operator with autonomous robot behaviors. In this work, we present techniques for integration of a shared autonomy system for assistive mobile manipulation and new strategies to support users in the domestic environment. We demonstrate that the robot can grasp multiple objects with random size at known and unknown table heights. Specifically, we developed three strategies for manipulation. From experimental results, we observed that the first strategy has the highest success rate (70% for random objects) up to 70 cm table height. Two other strategies perform better for 80 cm to 100 cm table height. The success rate of the second and third strategies shows an average 63.3% and 73.3%, respectively, for grasping random objects. We also demonstrated these strategies using two intuitive interfaces, a visual interface in rviz and a voice user interface with speech recognition, which are suitable for elderly people. In addition, the robot can select strategies automatically in random scenarios, which make the robot intelligent and able to make decisions independently in the environment. We obtained interesting results showing that the robot adapts to the environmental variation automatically. After these experimental demonstrations, our robot shows the capabilities for employment in domestic environments to perform actual tasks.

In this paper, we develop the theory of the multiple q-analogue of the Heine’s binomial formula, chain rule and Leibnitz’s rule. We also derive many useful definitions and results involving multiple q-antiderivative and multiple q-Jackson’s integral. Finally, we list here multiple q-analogue of some elementary functions including trigonometric functions and hyperbolic functions. This may be a good consideration in developing the multiple q-calculus in combinatorics, number theory and other fields of mathematics.

We recently reported that in the spinal cord of PPMS or SPMS patients, large areas of periplaque demyelinating lesions extend distance away from plaque borders. Such lesions are characterized by a progliotic TGF-beta 1 signature accompanied by: i) a low-grade inflammatory reaction, ii) an extensive astrocytosis and iii) a process of incomplete demyelination. It was proposed that, while efficiently dampening inflammation in MS spinal cords, TGF-beta 1 could promote astrocytosis, prevent remyelination and possibly trigger alterations of myelin synthesis. In light of these findings, a re-interpretation of two large neuropathological studies performed on MS brains and spinal cords is provided here. While results from these studies clearly showed that active plaques do not display any region-specific distribution, an important point was apparently overlooked and not discussed by the authors: a significantly higher percentage of inactive plaques was found in MS spinal cords as compared to brains and, conversely, the percentage of slowly-expanding (or smoldering) lesions was significantly lower in the spinal cord as compared to the brain. These data indicate that the spinal cord environment may be more favorable to the resolution of inflammation. Downstream of the autoimmune process leading to plaque formation, region-specific mechanisms may thus drive the outcome of active plaques. While inflammation triggers tissue destruction, inflammation may also be needed for effective tissue repair and an inappropriate dampening of inflammatory events may possibly translate into a poor level of remyelination in MS spinal cords. It is proposed here that TGF-beta 1 is involved in such a brain-spinal cord dissociation of active plaques outcome.

With the great development of intelligent transportation systems (ITS), travel time prediction has attracted the attentions of many researchers and a large number of prediction methods have been developed. However, as an unavoidable topic, the predictability of travel time series is the basic premise for travel time prediction has received less attention than the methodology. Based on the analysis of the complexity of travel time series, this paper defines travel time predictability to express the probability of correct travel time prediction and proposes an entropy-based method to measure the upper bound of travel time predictability. Multiscale entropy is employed to quantify the complexity of travel time series, and the relationships between entropy and the upper bound of travel time predictability are presented. Empirical studies are made with vehicle trajectory data in an express road section. The effectiveness of time scales, tolerance, and series length to entropy and travel time predictability are analysis, and some valuable suggestions about the accuracy of travel time predictability are discussed. Finally, the comparisons between travel time predictability and actual prediction results from two prediction models, ARIMA and BPNN, are conducted. Experimental results demonstrate the validity and reliability of the proposed travel time predictability.

The nature of the interaction between Th17 cells and the blood-brain barrier (BBB) is critical for the development of autoimmune inflammation in the central nervous system (CNS). TNF-a or IL-17 stimulation is known to enhance the adherence of Th17 cells to the brain endothelium. The brain endothelial cells (bEnd.3) express VCAM-1, the receptor responsible for inflammatory cell adhesion, which binds VLA-4 on migrating effector lymphocytes at the early stage of brain inflammation. The present study examines the effect of the pro-inflammatory cytokines TNF-a and IL-17 on the adherence of Th17 cells to bEnd.3 The bEnd.3 cells were found to increase production of CCL2 and CXCL1 after stimulation by pro-inflammatory cytokines, while CCL2, CCL5, CCL20 and IL17 induced Th17 cell migration through a bEnd.3 monolayer. This interaction between Th17 cells and the brain endothelium appears to be mediated by VCAM-1 and some chemotactic cytokines. This observation may suggest potential therapeutic targets for the prevention of autoimmune neuroinflammation development in the CNS.

Guessing effects frequently occur in testing data in educational or psychological applications. Different item response models have been proposed to handle guessing effects in dichotomous test items. However, it has been pointed out in the literature that the oftenemployed three-parameter logistic model poses implausible assumptions regarding the guessing process. The four-parameter guessing model has been proposed as an alternative to circumvent these conceptual issues. In this article, the four-parameter guessing model is compared with alternative item response models for handling guessing effects through a simulation study and an empirical example. It turned out that model selection for item response models should be rather based on the AIC than the BIC. However, the RMSD item fit statistic used with typical cutoff values was found to be ineffective in detecting misspecified item response models. Furthermore, sufficiently large sample sizes are required for sufficiently precise item parameter estimation. Moreover, it is argued that the criterion of statistical model fit should not be the sole criterion of model choice. The item response model used in operational practice should be valid with respect to the meaning of the ability variable and the underlying model assumptions. In this sense, the four-parameter guessing model could be the model of choice in educational large-scale assessment studies.

In recent years, new treatments have been studied for relapsed-refractory multiple myeloma (RRMM), including two CAR-T products and a variety of non CAR-T agents. Since direct comparisons between these innovative treatments are not available, indirect comparisons can be of interest. Reconstruction of individual patient data from Kaplan-Meier graphs (Shiny method) has been employed in numerous reports that have validated its performance. In the present review, we evaluated six treatments proposed for RRMM including two CAR-T products (ciltacabtagene autoleucel and idecabtagene vicleucel) and four treatments not based on a CAR-T (melflufen plus dexamethasone, isatuximab plus dexamethasone, selinexor, and belantamab). The end-point was overall survival (OS); the Shiny method was used to generate reconstructed survival curves. Our results showed statistically significant differences in OS across these treatments. Compared with pharmacological treatments, CAR-T products significantly prolonged OS with an improvement of remarkable clinical relevance. In particular, ciltacabtagene autoleucel showed better OS than idecabtagene vicleucel. As regards non CAR-T treatments, the ranking in OS was headed by isatuximab plus dexamethasone, followed by belantamab, selinexor, and melflufen plus dexamethasone. In conclusion, while the Shiny method has confirmed its validity in reconstructing individual patient data, our indirect comparisons have offered some original clues to better interpret the information on OS published in these studies.

Introduction: Pediatric-Onset Multiple Sclerosis (POMS) is characterized by high inflammatory disease activ-ity. Our aim was to describe the treatment sequencing and report the impact Highly Effective Disease Modifying Treatment (HET) had on disease activity. Materials and Methods: 2/5 consecutive POMS were administered HET as initial therapy after diagnosis. Data on treatment sequencing, relapses and MRIs were collected during the follow-up. Results: Our patients had an average age of 13.8 years (range 9-17) at di-agnosis and 13.4 years (range 9-16) at disease onset, 2/5 (40%) POMS were female. The pre-treatment aver-age annualized relapse rate was 1.6 (range 0.8-2.8) and the average follow-up length was 5 years (range 3-7). A total of 2/5 (40%) patients were stable on HET at initial therapy, 3/5 (60%) required an escalation to more aggressive treatment, even if two of them had been put on HET as initial treatment. Four out of five patients (80%) had No Evidence of Disease Activity-3 status (NEDA-3) at an average follow-up of 3 years (range 2-5). Conclusion: it has been observed that in a recent time period all the cases had prompt diagnosis, early HET or escalation to HET with a good outcome in 80% of the cases.

The importance of statistics in biological research is inevitable. The appliance of statistics is the most powerful tool to support the scientific hypothesis and to give credibility to biological research methodology, to interpret convoluted explanations and conclusions based on the research findings. The evidences from literatures point the persistent statistical errors, selection of non-proper statistical test with the consequence of misinterpretation of the scientific results which are published in international journals. One of the most extensively used statistical tests in the field of biology (preclinical and clinical) is analysis of variance (ANOVA). ANOVA test is in place of multiple T-tests to compare the means of more than two groups at a time; and there are some important points which biologists should be aware of them to avoid possible misinterpretation of results with the consequence of wrong conclusion. Accordingly, the aim of the current review is to help biologists to understand the basic concepts of ANOVA test and reach to a more valid interpretation of achieved results.