Mycotoxins are fungal secondary metabolites, which can cause acute and chronic toxic effects in animals and humans. The present study aimed to determine multi-mycotoxin levels in Algerian workers using urine as target. A method based on a QuEChERS (quick, easy, cheap, effective, rugged, and safe) extraction procedure followed by LC-MS/MS (liquid-chromatography tandem mass spectrometry) was optimized and validated for determination of 11 mycotoxins in 96 urine samples. Different sorbents were tested to be used in the dispersive solid-phase extraction (d-SPE) cleanup step of QuEChERS. The final method was fit-for-purpose and showed good analytical performance in terms of specificity, linearity and precision. All samples contained at least 2 mycotoxins, being toxin-2 (T-2) the most common, which was found in 92.7% of the samples, followed by zearalenone (ZEN) with 90.6% of positive samples, and ochratoxin A (OTA) with 86.4%. T-2 levels ranged from 0.3 μg/L to 36.3 μg/L, while OTA ranged from 0.3 μg/L to 3.5 μg/L and ZEN ranged from 7.6 μg/L to 126.8 μg/L. This was the first mycotoxin biomonitoring study carried out in the Algerian population. The findings highlight the need of accurate data for better risk assessment and the development of better regulation to manage mycotoxin contamination in this country.

Despite the recent approval of novel immunotherapies, as immunomodulatory drug, proteasome inhibitors and anti-CD38 monoclonal antibodies, Multiple Myeloma (MM) remains incurable and the acquisition of triple-refractoriness leads to really dismal outcomes, in even earlier lines of therapy. More recently, innovative therapeutic strategies targeting B cell maturation antigen (BCMA), highly expressed on the plasma cell surface, are drawing different future landscapes in terms of effectiveness and outcomes. Belantamab Mafodotin, a first-in-class anti-BCMA antibody drug conjugates, demonstrated good efficacy and safety profile in triple-refractory patients in the phase 2 DREAMM-2 trial and it was approved for the treatment of MM triple-exposed patients with >4 prior lines of therapy. Here, starting from Belantamab Mafodotin clinical trials also exploring combination studies and different schedules in order to improve its efficacy and toxicity, we focused on real life experiences all over the world, which have confirmed clinical trial data and encourage further Belantamab Mafodotin investigations

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.

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.

This study investigates the factors influencing consumers' intentions to purchase overseas travel packages via social media in Thailand, with a focus on consumer trust and perceived risks. A mixed-methods approach was employed, combining qualitative and quantitative research techniques. In the qualitative phase, the Fuzzy Set Delphi Method was applied to gather expert consensus from 19 participants. For the quantitative phase, a survey was conducted among 600 individuals who had experience purchasing overseas travel packages on social media in Thailand. First-order and second-order confirmatory factor analyses were used to examine the relationships between eight identified factors: social media influencer, e-WOM, trust, perceived risk, brand image, rating review, personal attitude, and destination image. The results indicate that trust and perceived risk are the most significant factors affecting purchase intention. Trust plays a crucial role in customers' decision-making processes, while perceived risk influences their tendency to avoid purchasing packages if the risk is perceived as high. The insights gained from this study contribute to the understanding of factors influencing purchase intentions for overseas travel packages through social media in Thailand, providing valuable information for travel agencies to develop effective marketing strategies.

Private Set Intersection Cardinality(PSI-CA) is a cryptographic method in secure multi-party computation that allows entities to identify cardinality of the intersection without revealing their private data.Traditional approaches assume similar-sized datasets and equal computational power, overlooking practical imbalances.In real-world applications, dataset sizes and computational capacities often vary, particularly in the Internet of Things and mobile scenarios where device limitations restrict computational types. Traditional PSI-CA protocols are inefficient here, as computational and communication complexities correlate with the size of larger datasets. Thus, adapting PSI-CA protocols to these imbalances is crucial.This paper explores unbalanced scenarios where one party (the receiver) has a relatively small dataset and limited computational power, while the other party (the sender) has a large amount of data and strong computational capabilities.This paper, based on the concept of commutative encryption, introduces Cuckoo filter, cloud computing technology, homomorphic encryption, among other technologies, to construct three novel solutions for unbalanced Private Set Intersection Cardinality (PSI-CA): an unbalanced PSI-CA protocol based on Cuckoo filter, an unbalanced PSI-CA protocol based on single cloud assistance, and an unbalanced PSI-CA protocol based on dual cloud assistance. Depending on performance and security requirements, different protocols can be employed for various applications.

Private Set Intersection (PSI) is a cryptographic method in secure multi-party computation that allows entities to identify common elements in their datasets without revealing their private data. Traditional approaches assume similar-sized datasets and equal computational power, overlooking practical imbalances. In real-world applications, dataset sizes and computational capacities often vary, particularly in the Internet of Things and mobile scenarios where device limitations restrict computational types. Traditional PSI protocols are inefficient here, as computational and communication complexities correlate with the size of larger datasets. Thus, adapting PSI protocols to these imbalances is crucial. This paper explores unbalanced PSI scenarios where one party (the receiver) has a relatively small dataset and limited computational power, while the other party (the sender) has a large amount of data and strong computational capabilities. It introduces three innovative solutions for unbalanced PSI: unbalanced PSI protocol based on Cuckoo filters, unbalanced PSI protocol based on single cloud assistance, and unbalanced PSI protocol based on dual cloud assistance, each addressing the shortcomings of the previous solution. These protocols primarily optimize database computational load, storage capacity, protocol execution time, and security. Depending on performance and security needs, different protocols can be employed for applications such as private contact discovery.

This paper investigates reachable set estimation and state-feedback controller design for linear time-delay control system with bounded disturbances. First, by constructing an appropriate Lyapunov-Krasovskii functional, we obtained a delay-dependent condition, which determed the admissible bounding ellipsoid for the reachable set of the system we considered. Then, a sufficient condition in form of liner matrix inequalities is given to solve the problem of controller design with reachable set estimation. Finally, by minimizing the volume of the ellipsoid and solving the liner matrix inequality, we obtain the desired ellipsoid and controller gain. A comparative numerical example is given to verify the usefulness of our result.

With advances in information technology, big data, mobile communications, and robotics, digital technologies are increasingly being used in factories around the world. This digital transformation is named industry 4.0. Today, industrial companies are looking at how to adopt this era and implement these technologies 4.0 while improving their performance and generating more profits. The objective of this paper is to help companies to better choose the appropriate digital technologies according to their activities using a multi-experts-multi-criteria decision-making approach under hesitant fuzzy information. The proposed model is a generic model based on Multi-Agent Systems allowing to have an idea of the parameters necessary to apply the adopted approach. The adopted approach allows a better representation of uncertainty and subjectivity of experts’ judgments. It would be of great interest, especially, when exact quantitative data are not available. A real case company example is exposed (automotive company) towards putting into practice the proposed approach.

A construction for the systems of natural and real numbers is presented in Zermelo-Fraenkel Set Thoery, that allows for simple proofs of the properties of these systems, and practical and mathematical applications. A practical application is discussed, in the form of a Simple and Linear Fast Adder (Patent Pending). Applications to finite group theory and analysis are also presented. A method is illustrated for finding the automorphisms of any finite group $G$, which consists of defining a canonical block form for finite groups. Examples are given, to illustrate the procedure for finding all groups of $n$ elements along with their automorphisms. The canonical block form of the symmetry group $\Delta_4$ is provided along with its automorphisms. The construction of natural numbers is naturally generalized to provide a simple and sound construction of the continuum with order and addition properties, and where a real number is an infinite set of natural numbers. A basic outline of analysis is proposed with a fast derivative algorithm. Under this representation, a countable sequence of real numbers is represented by a single real number. Furthermore, an infinite $\infty\times\infty$ real-valued matrix is represented with a single real number. A real function is represented by a set of real numbers, and a countable sequence of real functions is also represented by a set of real numbers. In general, mathematical objects can be represented using the smallest possible data type and these representations are calculable. In the last section, mathematical objects of all types are well assigned to tree structures in a proposed type hierarchy.

Ramsey’s theory (RAM) from combinatorics and network theory goes looking for regularities and repeated patterns inside structures equipped with nodes and edges. RAM represents the outcome of a dual methodological commitment: by one side a top-down approach evaluates the possible arrangement of specific subgraphs when the number of graph’s vertices is already known, by another side a bottom-up approach calculates the possible number of graph’s vertices when the arrangement of specific subgraphs is already known. Since natural neural networks are often represented in terms of graphs, we suggest to utilize RAM for the analytical and computational assessment of a peculiar structure supplied with neuronal vertices and axonal edges, i.e., the human brain connectome. We discuss how a RAM approach in neuroscientific issues might be able to locate and trace unexplored motifs shared between different cortical and subcortical subareas. Furthermore, we will describe how notable RAM outcomes, such as the Ramsey’s theorem and the Ramsey’s number, could contribute to uncover still unknown anatomical connexions endowed in neuronal networks and unexpected functional interactions among grey zones of the human brain.

The report details out programming approach for automating warehouse using Answer Set Programming.

Background: Although National Licensing Examinations (NLEs) may be a costly process, they can predict better performance for many following years. The current licensing requirements will not entail and new requirements will be requested. Therefore, this study suggests a framework for the development of the Medical Licensing Exam by exploring the opinions of Egyptian medical practitioners and educators regarding the exam format and criteria. Objective and methods: to describe the needed steps to develop the EMLE through a two-phase exploratory mixed-method study that had been conducted among the Egyptian medical sectors: medical practitioners and educators. Results: There were 50 clinical and academic educators shared in the online discussion about EMLE development. Then, a survey was carried out on 266 participants with various working places in which 198 of the participants were staff in the Higher Education Ministry and 68 physicians in the Ministry of Health. The input from both had contributed to the development of the following framework that is divided into two main sections; the Exam Logistics and the Exam Set up. The exam Logistics included the exam committee, prerequisites for the exam, the admission criteria and fees, and the validity of the license. While the Exam Set up included exam setting, structure, standard-setting, pass marks and reset policy. Conclusion: A Multidisciplinary team resources for the exam setting. Fairness and objectivity were highlighted through several factors; development of the exam blueprint, types of assessment methods, post-exam analysis, and standard-setting. Finally, the reset policy, fees, and validity of the license were recommended with a student-centered perspective that was suggested for the exam committee.

We provide an axiomatic base for the set of natural numbers, that has been proposed as a canonical construction, and use this definition of $\mathbb N$ to find several results on finite group theory. Every finite group $G$, is well represented with a natural number $N_G$; if $N_G=N_H$ then $H,G$ are in the same isomorphism class. We have a linear order, on the quotient space of isomorphism classes of finite groups, that is well behaved with respect to cardinality. If $H,G$ are two finite groups such that $|H|=m<n=|G|$, then $H<\mathbb Z_n\leq G\leq\mathbb Z_{p_1}^{n_1}\oplus\mathbb Z_{p_2}^{n_2}\oplus\cdots\oplus\mathbb Z_{p_k}^{n_k}$ where $n=p_1^{n_1}p_2^{n_2}\cdots p_{k}^{n_k}$ is the prime factorization of $n$. We find a canonical order for the objects of $G$ and define equivalent objects of $G$, thus finding the automorphisms of $G$. The Cayley table of $G$ takes canonical block form, and we are provided with a minimal set of independent equations that define the group. We show how to find all groups of order $n$, and order them. We give examples using all groups with order smaller than $10$, and we find the canonical block form of the symmetry group $\Delta_4$. In the next section, we extend our results to the infinite case, which defines a real number as an infinite set of natural numbers. A real function is a set of real numbers, and a sequence of real functions $f_1,f_2,\ldots$ is well represented by a set of real numbers, as well. In general, we represent mathematical objects using the smallest possible data-type. In the last section, mathematical objects are well assigned to tree structures. We conclude with brief comments on type theory and future work on computational aspects of these representations.

A new approach is presented to defining the amount of information, in which information is understood as the data about a finite set as a whole, whereas the average length of an integrative code of elements serves as a measure of information. We obtain a formula for the syntropy of reflection, that is, the information that two intersecting finite sets reflect about each other. The specificities of reflection of discrete systems through the combination of their parts are considered, and it is shown that the additive syntropy and entropy of reflection are measures of structural order and chaos. Three information laws have been established: the law of conservation of the sum of chaos and order; information law of reflection; the law of conservation and transformation of information. An assessment of the structural organization and the level of development of discrete systems is presented. It is shown that various measures of information are structural characteristics of integrative codes of elements of discrete systems. The conclusion is made that, from the informational-genetic positions, the synergetic theory of information is primary in relation to the Hartley-Shannon information theory. In the appendix we consider the asymmetry of the mutual reflection of finite sets and the proportionality of arbitrary quantities.

We consider Pisot family substitution tilings in $\R^d$ whose dynamical spectrum is pure point. There are two cut-and-project schemes(CPS) which arise naturally: one from the Pisot family property and the other from the pure point spectrum respectively. The first CPS has an internal space $\R^m$ for some integer $m \in \N$ defined from the Pisot family property, and the second CPS has an internal space $H$ which is an abstract space defined from the property of the pure point spectrum. However it is not known how these two CPS's are related. Here we provide a sufficient condition to make a connection between the two CPS's. In the case of Pisot unimodular substitution tiling in $\R$, the two CPS's turn out to be same due to [5, Remark 18.5].

Various factors and constraints should be considered when developing a manufacturing production schedule, and such a schedule is often based on rules. This paper develops a composite dispatching rule based on heuristic rules that comprehensively consider various factors in a semiconductor production line. The composite rule is obtained by exploring various states of a semiconductor production line (machine status, queue size, etc.), where such indicators as makespan and equipment efficiency are used to judge performance. A model of the response surface, as a function of key variables, is then developed to find the optimized parameters of a composite rule for various production states. Further, dynamic scheduling of semiconductor manufacturing is studied based on support vector regression (SVR). This approach dynamically obtains a composite dispatching rule (i.e. parameters of the composite dispatching rule) that can be used to optimize production performance according to real-time production line state. Following optimization, the proposed dynamic scheduling approach is tested in a real semiconductor production line to validate the effectiveness of the proposed composite rule set.

Background: To evaluate the effectiveness of Defocus Incorporated Multiple Segments (DIMS) in slowing myopia progression in pediatric patients as a function of age. Methods: This was a non-randomized experimenter-masked retrospective controlled observational study of European individuals aged 6 -16 years with progressive myopia but no ocular pathology. We retrospectively reviewed the charts of the participants allocated to receive DIMS spectacles (Hoya® MiyoSmart®) or single vision spectacle lenses (control group). Cycloplegic spherical equivalent (SE) and axial length (AL), were measured at baseline and at 36 month follow up. The results were stratified by age into four groups: patients that wore DIMS spectacles oldest or youngest than 10 years of age (respectively, group A, 20 patients mean age 13.6±2.2 and group C, 20 patients mean age 9.0±1.2) and age-matched control groups (group B, 18 patients mean age 13.2±2.5 and group D, 22 patients mean age 8.5±0.9). Results: At 36 months, SE and AL increase resulted significantly reduced in groups A and C, respectively compared to groups B and D (p<0.05). Linear regression analysis showed a significant correlation (P<0.05) between patient age and myopia progression for SE in groups A and C, but only in group A also for AL. Groups B and D did not show any significant correlation (P>0.05). Conclusion: DIMS spectacles seem to slow myopia increase in pediatric patients, however their effectiveness results greatest in children oldest than 10 years of age. Morover our findings suggest that AL may be the more reliable parameter for evaluating myopia progression.

Introduction. Anesthesia is widely used in various fields of dentistry to reduce patient discomfort when the treatment would be painful. The dentist may need to infiltrate the anesthetic into multiple locations and this is usually done with the same needle which passes through the soft tissues several times to distribute the anesthetic solution over a larger area. The present study aims to evaluate, through a morphological analysis under a scanning electron microscope (SEM), how the beveled tip of a 30G needle, used to inject anesthetic several times into different areas of the vestibular mucosa, changes. Materials and methods. 30G needles with two different brands were tested, in vivo used for a variable number of sequential injections from 1 to 6 on 192 patients. The specimens were analyzed under SEM observation to evaluate any deformations induced by contact with the vestibular soft tissues. Results. The amount of deformation, measured along the axis parallel to the needle, was proportional to the number of injections. The protrusion of deformations, measured on an axis perpendicular to the needle, were maximum on the needles used 3 times. For the needles used 4,5 and 6 injections, no further increase in deformations was noted. Conclusion. From the data it seems that the tested needles are not produced to withstand multiple injections consequently after the first injection on soft tissues, they undergo a deformation which could increase the risk of injury to the mucosa itself or to nerves and vessels with which they come into contact. It would be advisable to use the single needle for a reduced number of injections.

For the first time to optimize the creation of new neuroprotective agents based on bioflavonoids, we applied information technologies - docking analysis to calculate the binding of candidate molecules to the pharmacological target protein transthyretin, as well as the program of virtual screening of NO scavengers. As a result of this approach, the substance catechin was isolated from candidate molecules - quercetin, catechin, Epicatechin gallate, Epicatechin, Procyanidin B1, Procyanidin B2, Procyanidin B3, Catechin-3-gallate according to docking analysis. As a result of virtual screening, catechin was identified as a potential NO scavenger (55.15% prediction). The results of the prediction were confirmed by in vitro experiments. Course administration of catechin to animals with experimental multiple sclerosis (MS) against the background of methylprednisolone administration completely eliminated lethal cases, reduced the number of diseased animals by 20%, as well as prevented the development of severe neurological symptoms by 20% (compared to the methylprednisolone group) and by 60% compared to the control group. Course administration of catechin with methylprednisolone leads to decrease of neurodegradation markers in the cytosol of rats with EAE: NSE by 37%, and S-100 - by 54.8%. The combined administration of methylprednisolone significantly exceeds the combination of methylprednisolone with the reference drug mexidol by the degree of NSE reduction. The obtained results indicate a significant neuroprotective effect of ocular combinations of methylprednisolone and catechin. The above-mentioned confirms the correctness of bioflavonoid selection with the help of virtual screening program.

Objective: Daratumumab (Dara) is the first-in-class human-specific anti-CD38 mAb approved for treating multiple myeloma (MM). However, DARA-induced depletion of CD38high natural killer (NK) cells results in crippled antibody-dependent cellular cytotoxicity (ADCC), which limits its clinical detection and prediction for Dara efficacy. Therefore, we aimed to explore new NK subsets that could predict Dara efficacy and the underlying mechanism in Dara development. Methods: Multicolour spectral flow cytometry monitored changes in the immune cells of 13 paired RRMM patients. We used machine learning-driven clustering, FlowSOM (Flow Self-Organizing Maps), and dimensional reduction with tSNE (t-distributed Stochastic Neighbour Embedding) to identify unique cell populations pre- and posttreatment. Then, in vitro, fratricide and proliferation assays were performed to explore the function of new NK subsets against MM under Dara treatment. Results: The NK cells were divided into 25 subsets, among which we found that the percentages of KIR-NKP46+ NK cells decreased in paired RRMM patients compared to healthy controls but increased significantly post-Dara treatment. The fold change in KIR-NKP46+ after one dose of Dara treatment can predict whether the best response could be achieved within one month (ROC=0.86, p=0.011). Further in vitro experiments showed that KIR-NKP46+ NK cells are superior to KIR+ NK cells, cooperatively acting with daratumumab to sustainably eradicate MM cells. Meanwhile, apoptosis was significantly decreased, and the proliferation ability was relatively increased post-Dara treatment. Conclusion: In conclusion, the fold change in KIR-NKP46+ NK cell subsets after one dose of Dara treatment can predict the outcome of the curative effect, indicating a putative role of KIR-NKP46+ subsets against MM cells. The mechanism attributed to a relative expansion of the subset due to decreased apoptosis and increased proliferation ability.

Patients with Multiple Myeloma have an increased susceptibility to severe infections due to several various factors, especially the high tumor burden. The use of the anti-CD38 monoclonal antibodies-based therapies has changed the frequency and epidemiology of infections. We report herein the safety profile of the pivotal clinical trials conducted with anti-CD38 mAbs (daratumumab and isatuximab) and anti-SLAMF7 mAbs (elotuzumab) that led to the approval of regimens employed today in NDMM and RRMM patients.

Gender has been a rarely addressed aspect in digital game-based learning (DGBL). Likewise, mixed results have been presented regarding the effects according to gender and the conditions that generate these effects. The present work studies the effects of a drill-and-practice mathe-matical game on primary students. The study focused on an analysis by gender, measuring learning performance, and motivation in the practice activity. Also, two instructional mechanics were considered regarding the question answering, a multiple-try (MTF) and a single-try (STF) condition, to search for possible differences. A total of 81 students from 4 courses and 2 schools participated in the experiment. The study's main findings were that: (a) the girls outperformed boys in terms of students' learning gains, (b) girls presented lower levels of competence and autonomy than boys, (c) in the MTF, girls presented lower levels of autonomy but no differences in competence contrasted to boys, (d) in the STF, girls presented lower levels of competence but no differences in autonomy against boys, and (e) no differences existed in interest, effort and value among gender overall o per instructional condition. This study enhances the knowledge of gender differences under diverse instructional settings, in particular providing insights into possible differences by gender when varying the number of attempts provided to students.

As the adoption of renewable energy sources grows, ensuring a stable power balance across various time frames has become a central challenge for modern power systems. In line with the "dual carbon" objectives and the seamless integration of renewable energy sources, harnessing the advantages of various energy storage resources and coordinating the operation of long-term and short-term storage have become pivotal directions for future energy storage deployment. To address the complexities arising from the coupling of different time scales in optimizing energy storage capacity, this paper proposes a method for energy storage planning that accounts for power imbalance risks across multiple time scales. Initially, the Seasonal and Trend decomposition using the Loess (STL) decomposition method is utilized to temporally decouple actual operational data. Subsequently, power balance computations are performed based on the obtained data at various time scales to optimize the allocation of different types of energy storage capacities and assess the associated imbalance risks. Finally, the effectiveness of the proposed approach is validated through hourly applications using real-world data from a province in China over recent years.

23-Hydroxy ursolic acid (23-OH UA) is a potent atheroprotective and anti-obesogenic phytochemical, with anti-inflammatory and inflammation resolving properties. In this study, we examined whether dietary 23-OH UA protects mice against the acute onset and progression of experimental autoimmune encephalomyelitis (EAE), a mouse model of multiple sclerosis (MS). Female C57BL/6 mice were fed either a defined low-calorie maintenance diet (MD) or an MD supplemented with 0.2 % wgt/wgt 23-OH UA for 5 weeks prior to actively inducing EAE and during the 30 days post-immunization. We observed no difference in the onset of EAE between both groups of mice, but ataxia and EAE disease severity were suppressed by 52% and 48%, respectively, and disease incidence was reduced by over 49% in mice that received 23-OH UA in their diet. Furthermore, disease-associated weight loss was strikingly ameliorated in 23-OH UA-fed mice. ELISPOT analysis showed no significant differences in frequencies of T cells producing IL-17 or IFN- between 23-OH UA fed mice and control mice, suggesting that 23-OH UA does not appear to regulate peripheral T-cell responses. In summary, our findings demonstrate that dietary 23-OH UA may represent an effective oral adjunct therapy for the prevention and treatment of relapsing-remitting MS.

Steroid hormones have diverse roles in pregnancy; some, such as progesterone and its metabolites, help stabilise pregnancy and can very likely influence the stability of pregnancy and the onset of labour. Changes and disorders in steroidogenesis may be involved in several pregnancy pathologies, such as premature delivery, preeclampsia, and intrahepatic cholestasis. To date, only a few studies have performed steroid analysis in multiple pregnancies. However, these studies offered a limited analysis of the steroidome in children and mothers with multiple pregnancies. Our team and a team from the Department of Steroids and Proteofactors of the Institute of Endocrinology in Prague investigated multiple pregnancies regarding the biosynthesis, transport, and effects of steroids. We recruited two groups of patients: pregnant women with multiple pregnancies as the study group and singleton pregnancies as the control group. Blood samples were drawn from the participants and analysed. Information about the mother, foetus, delivery, and newborn was extracted from medical records. The data were then analysed. The gestational age of twin pregnancies during delivery ranged from 35+3 to 39+3 weeks, while it was 38+1 to 41+1 weeks for the controls. Our findings provide answers to questions regarding the steroidome in multiple pregnancies.

Background. The purpose of the study was to evaluate the intensity and frequency of low back pain (LBP) in people with multiple sclerosis (PwMS) and the patient's knowledge of physiotherapeutic methods of combating. Methods. In this study, patients with confirmed multiple sclerosis were selected. The study was carried out using an original survey questionnaire and a numerical pain intensity scale (Visual Analogue Scale). PwMS were divided into 3 age groups: 18-30 years, 31-50 years, and over 50 years. Results. Ninety PwMS (68 women and 22 men) aged 18 to 60 years were included in the study. The mean duration of the disease was 9.5±4.9 years, and the mean EDSS was 3.5±1.6. Most of the patients had a relapse-remitting form. 68.9% of PwMS felt lower back pain (n = 62). The relationship tested was statistically significant (p=0.0000012), and the strength of the relationship was high (rc=0.695). The average level of low back pain among PwMS was 4.7 out of 10 on the VAS scale. The prevalence of LBP was higher in female patients (p<0.001), with a secondary progressive form (p<0.001) and with a longer duration of the disease (p=0.023). The most widely used methods of LBP therapy were kinesitherapy and manual therapy. Conclusions. LBP is common in multiple sclerosis. A female sex, a secondary progressive form of MS, and a longer duration of the disease increased the risk of LBP. It is important to implement properly planned physiotherapy activities and educate patients on how to combat LBP.

Multiple sclerosis (MS) is a chronic inflammatory autoimmune disease of the central nervous system. According to recent studies, cellular senescence caused by telomere shortening may contribute to the development of MS. Aim of the study: to determine the associations of TEP1 rs1760904, rs1713418, TERC rs12696304, rs35073794 gene polymorphisms with the occurrence of MS. Methods: The study included 200 patients with MS and 230 healthy controls. Genotyping of TEP1 rs1760904, rs1713418 and TERC rs12696304, rs35073794 was performed using RT-PCR. Statistical analysis of the obtained data was performed using the program "IBM SPSS Statistics 29.0". Haplotype analysis was performed using the online program "SNPStats". Results: The TERC rs12696304 G allele of this SNP is associated with a 1.4-fold lower odds of developing MS (p=0.035). TERC rs35073794 is associated with an approximately 2.4-fold reduced odds of MS occurrence in the codominant, dominant, overdominant, and additive models (p < 0.001; p < 0.001; p < 0.001; p < 0.001, respectively). Haplotype analysis shows that the rs1760904-G - rs1713418-A haplotype is statistically significantly associated with a 1.75-fold increased odds of developing MS (p=0.006). The rs12696304-C - rs35073794-A haplotype is statistically significantly associated with a 2-fold decreased odds of developing MS (p=0.008). In addition, the rs12696304-G - rs35073794-A haplotype was found to be statistically significantly associated with a 5.3-fold decreased odds of developing MS (p&lt;0.001). Conclusion: Current evidence may suggest a protective role of TERC SNP in the occurrence of MS, while TEP1 has the opposite effect.

Interferon-beta is one of the most widely prescribed disease-modifying therapies for multiple sclerosis patients. However, this treatment is only partially effective, and a significant proportion of patients do not respond to this drug. This paper proposes an alternative fuzzy logic system based on the opinion of a neurology expert to classify relapsing-remitting multiple sclerosis patients: high, medium, and low responder to interferon-beta. Also, a pipeline prediction model trained with biomarkers associated to interferon-beta response is proposed for predicting whether patients are potential candidates to be treated with this drug, in order to avoid ineffective therapies. The classification results shows that the fuzzy system presents a 100% efficiency compared with an unsupervised hierarchical clustering method (52%). So, the performance of the prediction model is evaluated, and a 0.8 testing accuracy is achieved. Hence, a pipeline model including data standardization, data compression, and a learning algorithm, can be a useful tool for getting reliable predictions about the response to interferon-beta.

Introduction: Unlike cigarette smoking, secondhand smoke (SHS) has not been as well described as an environmental risk for Multiple sclerosis (MS) nor as a risk factor for disease progression. We systematically reviewed the association between SHS and the risk of onset and/or progression of MS.Methods: We systematically screened MEDLINE/PUBMED, Science Direct, LILACs, and SCIELO searching for publications between January 1st , 2010, and July 5, 2021 with the following keywords: “multiple sclerosis and smoking”; “multiple sclerosis and passive smoking”; “multiple sclerosis and secondhand smoking”. An 11-year filter was applied from 2010 to 2021. Results: Fifteen articles were included in this review, which consisted of systematic reviews with meta-analysis (N = 2), systematic reviews (N = 2), and observational studies (N = 11). Both meta-analyses reported an impact of SHS on MS onset among secondhand smokers. One of the systematic reviews selected two observational studies showing the association between SHS and MS development, and one study that did not find a significant association between SHS and the risk of MS development. The other systematic review identified selected eight articles showing a relationship between SHS and MS. Seven observational studies reported higher odds of MS onset when associated with SHS. Four observational studies did not show a relationship between SHS and MS onset or progression.Discussion: Most articles showed a positive association between SHS exposure and the risk of developing MS. On the other hand, an association between SHS and a higher risk for MS progression could not be established.

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.

A presentation is provided of a structural approach for the concurrent teaching of introductory propositional calculus and set theory. The existence of isomorphism is shown between each law (or tautology) of propositional calculus and the form of a corresponding set which is equal to the universal set U considered.

This paper addresses a mode-dependent state-feedback H∞ control for descriptor hybrid systems, considering both the absence and presence of actuator saturation. Firstly, the necessary and sufficient conditions for the stochastic admissibility criterion with H∞ performance ? of the closed-loop system is proposed. Given the proposed non-convex condition, the author reformulates it into linear matrix inequalities (LMIs). Then, to extend the result to the systems with actuator saturation, the actuator saturated control input is expressed as a linear combination of given state-feedback control input and a virtual control input that remains under the saturation level. To verify this expression, the set invariant condition is also suggested by using the singular mode-dependent Lyapunov function candidate. Therefore, the LMI conditions for the existence of the mode-dependent state-feedback H∞ control and the ellipsoidal shape of invariant set are successfully derived. Two numerical examples demonstrate the effectiveness of the proposed approach in optimizing H∞ performance $\gamma$ and identifying the largest invariant set.

Multi-Object Tracking (MOT) is a key technology for Unmanned Aerial Vehicles (UAVs). Traditional tracking-by-detection methods firstly employ an object detector to retrieve targets in each image and then track them based on a matching algorithm. Recently, the popular multi-task learning methods has been dominating this area since they can detect targets and extract Re-Identification (Re-ID) features in a computationally efficient way. However, the detection task and the tracking task have conflicting requirements on image features, leading to the poor performance of the joint learning model compared to separate detection and tracking methods. The problem is more severe when it comes to UAV images due to the presence of irregular motion of large number of small targets. In this paper, we propose a balanced Joint Detection and Re-ID learning (JDR) network to address the MOT problem in UAV vision. To better handle the non-uniform motion of objects in UAV videos, the Set-Member Filter is applied which describes object state as a bounded set. An appearance matching cascade is then proposed based on target state set. Furthermore, a Motion-Mutation module is designed to address the challenges posed by the abrupt motion of UAV. Extensive experiments on the VisDrone-MOT2019 dataset demonstrate that our proposed model, termed as SMFMOT, outperforms state-of-the-arts by a large margin and achieves superior performance on the MOT tasks in UAV videos.

Soil quality is related to food security and human survival and development. In recent years, due to the acceleration of urbanization and the increase of abandoned land, land degradation occurs, poor topsoil quality. In this study, the minimum data set (MDS) was constructed through principal component analysis (PCA) to determine the indicator data set for evaluating topsoil quality in Tieling County, China. In addition, the soil quality index (SQI) was calculated to analyze the spatial distribution characteristics and influencing reasons of topsoil quality in Tieling County. The re-sults showed that MDS included total potassium (TK), Clay, zinc (Zn), soil organic matter (SOM), soil water content (SWC), cation exchange capacity (CEC), pH, and copper (Cu). The MDS indicators can well replace all indicators to evaluate the topsoil quality in the study area. The overall soil quality of Tieling County showed a trend of low in the east and high in the west, and gradually increased from the hilly area to the plain area. The evaluation results are consistent with field research, which can provide reference for other topsoil quality evaluation, and it also provide a basis for the formulation of soil quality improvement measures.

In this paper we prove that if the product $X^{n}$ of a space $X$ has some tightness-type properties, then the space of permutation degree ${\sf SP^{n}}X$ also has these properties. It is proved that the set tightness (resp. $T$-tightness) of the space of permutation degree ${\sf SP^{n}}X$ is equal to the set tightness (resp. $T$-tightness) of the product $X^{n}$.

One of matrix equalities composed of multiple products of matrices and their generalized inverses is given by $A_1B_1^{-}A_2B_2^{-} \cdots A_kB_k^{-}A_{k+1}= A$ where $A_1$, $B_1$, $A_2$, $B_2$, $\ldots$, $A_k$, $B_k$, $A_{k+1}$, and $A$ are given matrices of appropriate sizes, and $B_1^{-}$, $B_2^{-}$, $\cdots$, $B_k^{-}$ are generalized inverses of matrices. The cases for $k = 1, 2$ and their special forms were properly approached in the theory of generalized inverses of matrices. In this note, the author presents an algebraic procedure to derive explicit necessary and sufficient conditions for the equality with $k = 3$ to always hold using certain rank equalities for the block matrices constructed by the given matrices, and then mention a key step of extending the previous work to a general situation.

Most of the existing influence maximization algorithms are not suitable for large-scale social networks due to their high time complexity or limited influence propagation range. Therefore, a D-RIS influence maximization algorithm is proposed based on the independent cascade model and combined with the reverse reachable set sampling. Under the premise that the influence propagation function satisfies monotonicity and submodularity, the D-RIS algorithm uses automatic debugging method to determine the critical value of the number of reverse reachable sets, which not only obtains a better influence propagation range, and greatly reduce the time complexity. The experimental results on the two real data sets of Slashdot and Epinions show that D-RIS algorithm is close to the CELF algorithm and higher than RIS algorithm, HighDegree algorithm, LIR algorithm and pBmH algorithm in influence propagation range. At the same time, it is significantly better than the CELF algorithm and RIS algorithm in running time, which indicates that D-RIS algorithm is more suitable for large scale social network.

We examined how combinations of corporate social responsibility (CSR) activities lead to high performance in Korean companies. This study addressed two related questions to expand our limited knowledge in this area. The first was what combinations of CSR activities achieve high performance. The second was to identify how CSR activities form an interdependent system, depending on different corporate situations. Korean Economic Justice Institute index data, from 2012 to 2018, were used with fuzzy set qualitative comparative analysis, and the results revealed several effective CSR activity factor combinations under given strategies and management environments. Companies with high performance exhibit complementarity between social contribution, environmental management, fairness, and employee satisfaction. By contrast, companies with low corporate performance show no complementarity between relatively unrelated activity factors. For companies whose CSR activities lead to low financial performance, most of the causal pathways focused only on activities at the primary stakeholder level, with weak diversity of CSR activities’ combinations at the primary and secondary stakeholder levels. These results indicate not only the appropriateness of CSR activity factor combinations for companies’ strategy and management environment contexts, but also their effectiveness, and are expected to provide companies with significant implications for CSR activities.

Maximally similar sets (MSS) are sets of elements that share a neighborhood in a high-dimensional space defined by symmetric, reflexive similarity relation. Each element of the universe is employed as the kernel of a neighborhood of a given size (number of members), and elements are added to the neighborhood in order of similarity to the current members of the set until the desired neighborhood size is achieved. The set of neighborhoods is then reduced to the set of unique maximally similar sets by eliminating all sets that are permutations of an existing set. Subsequently, the within-MSS variability of attributes associated with the elements is compared to random sets of the same size to estimate the probability of obtaining variability as low as observed. Individual attributes can be compared for effect size by the ratio of within-MSS variability to random set variability, correcting for statistical power as necessary. The analyses performed identify constraints, as opposed to determinants, in the triangular distribution of pair-wise element similarity. In the example given here, the variability in spring temperature, summer temperature, and growing degree days of forest vegetation samples shows the greatest constraint on forest composition of a large set of candidate environmental variables

In this paper, the set-membership affine projection (SM-AP) algorithm is utilized to censor non-informative data in big data applications. To this end, the probability distribution of the additive noise signal and the excess of mean-squared error (EMSE) in steady-state are employed in order to estimate the threshold parameter of the single threshold SM-AP (ST-SM-AP) algorithm aiming at attaining the desired update rate. Furthermore, by defining an acceptable range for the error signal, the double threshold SM-AP (DT-SM-AP) algorithm is proposed to detect very large errors due to the irrelevant data such as outliers. The DT-SM-AP algorithm can censor non-informative and irrelevant data in big data applications, and it can improve misalignment and convergence rate of the learning process with high computational efficiency. The simulation and numerical results corroborate the superiority of the proposed algorithms over traditional algorithms.

A new formulation for a proposed solution to the 3D Navier-Stokes Equations in cylindrical co-ordinates coupled to the continuity and level set convection equation is presented in terms of an additive solution of the three principle directions in the radial, azimuthal and z directions of flow and a connection between the level set function and composite velocity vector for the additive solution is shown. For the case of a vertical tube configuration with small inclination angle, results are obtained for the level set function defining the interface in both the radial and azimuthal directions. It is found that the curvature dependent part of the problem alone induces sinusoidal azimuthal interfacial waves wheras when the curvature together with the equation for the composite velocity is considered oscillating radial interfacial waves occur. The implications of two extremes indicate the importance of looking at the full equations including curvature.

Using insights from cybernetics and an information-based understanding of biological systems, a precise, scientifically inspired, definition of free-will is offered and the essential requirements for an agent to possess it in principle are set out. These are: a) there must be a self to self-determine; b) there must be a non-zero probability of more than one option being enacted; c) there must be an internal means of choosing among options (which is not merely random, since randomness is not a choice). For (a) to be fulfilled, the agent of self-determination must be organisationally closed (a `Kantian whole'). For (c) to be fulfilled: d) options must be generated from an internal model of the self which can calculate future states contingent on possible responses; e) choosing among these options requires their evaluation using an internally generated goal defined on an objective function representing the overall `master function' of the agent and f) for `deep free-will', at least two nested levels of choice and goal (d-e) must be enacted by the agent. The agent must also be able to enact its choice in physical reality. The only systems known to meet all these criteria are living organisms, not just humans, but a wide range of organisms. The main impediment to free-will in present-day artificial robots, is their lack of being a Kantian whole. Consciousness does not seem to be a requirement and the minimum complexity for a free-will system may be quite low and include relatively simple life-forms that are at least able to learn.

In order to quickly develop a multi ship collaborative collision avoidance plan in multi ship encounter scenarios, a multi ship collision avoidance decision model is proposed in accordance with the requirements of the International Maritime Collision Avoidance Regulations, taking into account the collision avoidance operations in multi ship encounter scenarios. Firstly, the collision risk between ships is determined by the closest encounter distance (DCPA) and closest encounter time (TCPA). Secondly, a decision objective function is established based on rules, degree of ship deviation, and ship risk. Finally, the prediction mechanism is used to calculate the minimum value of the objective function and complete the collision avoidance decision. The simulation results show that in the scenario of multiple ship encounters, the collision avoidance model can achieve safe collision avoidance with a smaller steering frequency and a shorter col-lision avoidance time. The proposed multi ship collision avoidance model can provide reference for collision avoidance decision-making in multi ship encounter scenarios, which helps to im-prove the collision avoidance efficiency in multi ship collision avoidance

Acute coronary syndrome (ACS) is a life-threatening condition that requires a prompt diagnosis and therapeutic intervention. Although serum troponin T and creatinine kinase-MB (CK-MB) are established biomarkers for ACS, it may take several hours to reach diagnostic values for ACS. In this study, we attempted to explore novel biomarkers for ACS with higher sensitivity than that of troponin T and CK-MB. The metabolomic profiles of 18 patients with ACS upon hospital arrival and those of the age-matched control (HC) group consisted of 24 healthy volunteers were analyzed using liquid chromatography-time-of-flight mass spectrometry. Volcano plots showed 24 metabolites whose concentrations differed significantly between the ACS and HC groups. Using these data, we developed a multiple logistic regression model for the ACS diagnosis, in which lysine, isocitrate, and tryptophan were selected as minimum-independent metabolites. The area under the receiver operating characteristic curve value for discriminating ACS from HC was 1.00 (95% confidence interval [CI]: 1.00-1.00). In contrast, those for troponin T and CK-MB were 0.917 (95% confidence interval [CI]: 0.812-1.00) and 0.988 (95% CI: 0.966-1.00), respectively. This study showed the potential of combining three plasma metabolites to discriminate ACS from HC with a higher sensitivity than that of troponin T and CK-MB.

An increased demand for natural products nowadays most specifically probiotics (PRO) is evident since it comes in conjunction with beneficial health effects for the consumers. In this regard, it is well known that encapsulation could affect positively the PRO's viability throughout food manufacturing and long-term storage. This paper aims to analyze and review various multilayer strategies for encapsulation of PRO. Double-layer encapsulation of PRO by electro-hydrodynamic atomization or electrospray technology has been reported along with layer-by-layer assembly and water-in-oil-in-water (W1/O/W2) double emulsions to produce multilayer PRO-loaded carriers. Finally, their applications in food products are presented. The resistance (cover material) and viability of (PRO) to mechanical damage, during gastrointestinal transit and shelf life of these trapping systems are also described. The PRO encapsulation in double and multiple-layer coatings combined with other technologies can be examined to increase the opportunities for new functional products with amended functionalities opening a novel horizon in food technology.

Objective: The goal of this review is to provide a succinct, yet comprehensive, guide to the an-tepartum management of multiple gestations. Methods: This narrative review on twins and multiple gestation provides a concise guide for providers with this ever-growing patient population. PubMED was utilized for literature search. Each reference was evaluated and graded for quality of evidence by US Preventative Services Task Force and Cochrane Review guidelines. Screening, surveillance, and management strategies are delineated succinctly and organized by type of multiple gestation being managed from the lowest risk dichorionic twin pair to the increasingly escalating risks of twins and higher order multiples sharing a placenta and/or amniotic sac. Results: The incidence of twin pregnancies has grown over the past several years, due in large part to delayed reproductive timing and surge in assisted reproductive technologies. Twin pregnancies are associated with higher morbidity for both gravidas and offspring, warranting evidence-based approach in counseling and management. Conclusions: We note the important differences among multiples in chorionicity and amnionicity, in the importance of close surveillance and early delivery. Graded clinical pearls and evi-dence-based recommendations are presented to guide obstetric providers.

Balo’s concentric sclerosis is a rare disease and a subtype of multiple sclerosis. A 38-year-old male patient presented to the hospital with the complaint of numbness in the left-sided upper and lower limb, slurring of speech and left-sided headache for 15 days. Further investigation was done and in ECG ‘Delta wave’ was identified along with tachycardia. Diagnosis of Wolff Parkinson White syndrome was made. The patient’s MRI Brain has shown a non-enhancing intra-axial altered signal intensity lesion at the callose-septal interface adjacent to both lateral ventricles, which was identified as Balo’s concentric sclerosis.

The flow field around a straight chain of multiple slip spherical particles rotating steadily in an incompressible Newtonian fluid about their line of centers is analyzed at low Reynolds numbers. The particles may vary in radius, slip coefficient, and angular velocity, and they are permitted to be unevenly spaced. Through the use of a boundary collocation method, the Stokes equation governing the fluid flow is solved semi-analytically. The interaction effects among the particles are found to be noteworthy under appropriate conditions. For the rotation of two spheres, our collocation results for their hydrodynamic torques are in good agreement with the analytical asymptotic solution in the literature obtained by using a method of twin multipole expansions. For the rotation of three spheres, the particle interaction effect indicates that the existence of the third particle can influence the torques exerted on the other two particles noticeably. The interaction effect is stronger on the smaller or less slippery particles than on the larger or more slippery ones. Torque results for the rotation of chains of many particles visibly show the shielding effect among the particles.

A text obtained by a Large Language Model (LLM) such as GPT4 usually has issues in terms of incorrectness and hallucinations. We build a fact-checking system 'Truth-O-Meter' which identifies wrong facts, comparing the generation results with the web and other sources of information, and suggests corrections. Text mining and web mining techniques are leveraged to identify correct corresponding sentences; also, the syntactic and semantic generalization procedure adopted to the content improvement task. To handle inconsistent sources while fact-checking, we rely on an argumentation analysis in the form of defeasible logic programming. We compare our fact checking engine with competitive approach based on reinforcement learning on top of LLM or token-based hallucination detection. It is observed that LLM content can be substantially improved for factual correctness and meaningfulness.

This paper explores the integration of multiple intelligences and artificial intelligence (AI) in language learning, focusing on its potential to enhance personalization and engagement. Drawing from existing research and studies conducted in various contexts, including the Philippines, this study aims to contribute to the understanding of the benefits, challenges, and effectiveness of this integration. The paper begins with an introduction that highlights the background and significance of integrating multiple intelligences and AI in language learning, identifying research gaps, objectives, research questions, and the theoretical framework. A literature review provides an overview of multiple intelligences theory by Howard Gardner, the role of AI in language learning, and identifies gaps in the existing literature. The methodology section outlines the research design and approach, participant selection, data collection methods, validity and reliability measures, and ethical considerations. Findings and results are presented through the analysis of qualitative data, exploring emergent themes and patterns. The discussion section critically examines the identified research gaps, discusses the validity and reliability of the study, addresses the scope and limitations, and explores the implications of the findings for theory, practice, and future research. The conclusion summarizes the key findings and contributions of the study, reflects on the achievement of research objectives, offers recommendations for further research, and provides final remarks tying together the main points of the study. This paper contributes to the existing body of knowledge by providing insights into the integration of multiple intelligences and AI in language learning and its impact on personalization, engagement, and language learning outcomes.

As required by the EU legislation and the national risk management duties, the pesticide residues were determined by four specialized laboratories in 9,924 samples taken from 119 crops of economic importance and imported foodstuffs during 2017-2021 in Hungary. The screening method applied covered 622 pesticide residues as defined for enforcement purposes. The limit of detection ranged between 0.002-0.008 mg/kg. The 1.0% violation rate was lower than in the European Union for all commodities. No residue was detectable in 45.9% of the samples. For detailed analyses of the results, eight commodities (apple, cherry, grape, nectarine/peach, sweet peppers, and strawberry) were selected as they were analyzed over 195 samples and contained most frequently residues. Besides testing their conformity with national MRLs, applying 0.3MRL action limits for pre-export control, we found that 73% of the sampled lots would be compliant with ≥90% probability based on second independent sampling. Multiple residues (2-23) in one sample were detected in 36-50% of the tested lots. Noting the provisions of integrated pest management and the major pests and diseases of selected crops, normally 3-4, exceptionally 7-9 active ingredients of different mode of actions should be sufficient for their effective and economic protection.

Bi-clonal gammopathy is distinguished by the presence of two different or distinct monoclonal proteins, due to a proliferation of two distinct monoclonal plasma cell clones. A single monoclonal clone can give rise to two different monoclonal proteins. In this report, we present three cases of biclonal multiple myeloma and one case of Waldenstrom's disease that exhibits two biclonal peaks. Serum protein electrophoresis showed two M bands on serum protein electrophoresis.

Traditional grain vinegar is fermented using multiple acetic acid bacteria (AAB) at various temperatures. A single AAB showed high acid–producing ability at 30 °C with a 5% alcohol concentration and an initial pH adjusted to 4.0. Multiple AAB were similar to single AAB, but the optimal initial pH was 3.0. Acid production ability according to the type of AAB was higher in multiple AAB than that for single AAB. That is, using multiple AAB helped to increase the titratable acidity of traditional grain vinegar. In addition, increasing the titratable acidity and content of volatile flavor compounds was advantageous when two, rather than four, AAB types were mixed and used. Titratable acidity was high at medium temperatures (30 °C), but volatile flavor compounds increased at low temperatures (20 °C) under multiple AAB. A 16S rDNA–based microbiome taxonomic profiling analysis identified differences in beta diversity due to multiple AAB and fermentation temperatures. In particular, beta diversity analysis revealed a specific pattern when a mixture of Acetobacter ascedens GV–8 and Acetobacter pasteurianus GV–22 were fermented at low temperature (20 °C). Therefore, we propose the application of multiple AAB with acidic and flavor–producing properties in traditional grain vinegar.

The paper portrays a linear model for synchronous prediction of the dissolved oxygen (DO) level in a protected urban lake by using independent variables in real-time monitoring of the water quality parameters. Multi-linear regression and machine learning techniques were applied to the Dissolved Oxygen (DO) using the basic four parameters of Water Quality Index (WQI). Three real-time industry standard sensors PHEHT, CTZN, OPTOD were used for sampling, data was then interpolated through ArcGIS kriging method. 25 correlations were checked through the ML algorithm, a correlation heat map was produced and the top five relations were taken under consideration and validated by r-score and root mean squared error (RMSE) to develop the linear regression model. The performance of the model was validated through the RMSE, mean squared error (MSE), and mean absolute error (MAE) the r2 accuracy came to 0.983 when it is checked against the sample data. The suggested model can be used as a technique for unknown or malfunctioned sensor’s null DO data prediction.

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.

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.

In this work is proposed a new unsupervised method to evaluate the behavior of urban green areas in presence of heatwave scenarios analyzing the NDVI, NDMI and LST satellite data. To evaluate how these three indices characterize urban green areas during periods of heat waves, a reclassification of the data raster of each index is carried out. Rather than using standard classifications of the three indices, an unsupervised classification approach is proposed that uses the Elbow method to determine the optimal number of classes and the Jenks thematic classification method. Each class is assigned a Gaussian fuzzy set with means and standard deviations equal to that of the associated thematic class. The green urban areas are classified using zonal statistics operators and the degree of membership in the corresponding fuzzy set is used to assess the reliability of the classification. Finally, for each type of greenery the frequencies of belonging to the NDVI, NDMI and LST classes are analyzed to evaluate the behavior of the type of urban greenery during heatwaves. The framework was tested in an urban area consisting of the city of Naples (Italy). The results show that some types of greenery, such as deciduous forests and olive groves, are not very vulnerable to heatwave scenarios, unlike uncultivated areas which, instead, show critical behaviors during heatwaves.

Considering the unquestionable role of education in economic development, it has an impact at a macroeconomic level—contributing to enhancing productivity and innovation, reducing poverty and promoting social cohesion—and at a personal level—ensuring the improvement of knowledge, skills and individual capabilities and promoting social values like empowerment and equality. Notably, quality education is recognized as one of the Sustainable Development Goals (SDGs), which, jointly with other behaviors and attitudes, could impact the development of societies in other fields like health and well-being, cultural preservation, environmental sustainability and even peace and stability—all of them also listed as SDGs. However, the capacity, or not, to reach higher levels of compliance with quality in education (SDG 4) varies from country to country, according to the 2023 Sustainable Development Report results. Thus, the present study used a fuzzy set qualitative comparative analysis to assess the conditions for attaining higher levels of quality education based on the different indicators used to measure SDG 4. The analysis will allow comparisons of results among different countries and provide information about the initiatives that could be relevant to increasing quality education worldwide and for policymakers.

Scheduling and optimization have a central place in the research area of computing because it is increasingly important to achieve fully automated production processes to adjust manufacturing systems to the requirements of Industry 4.0. In this paper, we demonstrate how an automated wet-etch scheduling problem for a semiconductor industry can be solved by constraint answer set programming (CASP) and, its solver called clingcon. The considered scheduling problem includes a robot for lot transfers between the baths. CASP is a hybrid approach in automated reasoning that combines different research areas such as answer set programming, Constraint Processing and Satisfiability Modulo Theories. For a long time, exact methods such as constraint programming have displayed difficulties in solving real large-scale problem instances. Currently, the performance of state-of-the-art constrains solvers is comparatively better than a decade ago, and some complex combinatorial problems can be optimally solved. These theoretical and technical achievements open new horizons for declarative programming applications such as logistics. A successful solution to this problem is achieved and we found that in most cases tested, CASP is faster and obtains in most cases similar makespan values than solutions based on mixed integer linear programming and constraint paradigms.

The identification of fetal cells in the blood and tissues of healthy mothers raised questions about the potential alloreactive origins of various diseases, such as autoimmunity, diabetes, arteriosclerosis, and cancer. However, the extent to which alloreactivity contributes to these diseases remains unverified. This study presents a basic mathematical disease model based on the genes’ origin and immunological interactions. This model, grounded in set theory, classifies these immunological interactions based on their intrinsic, extrinsic, and allogeneic nature. Therefore, this model offers an unexpected common theoretical foundation for understanding alloreactivity, genetic diseases, and infections. Furthermore, this model provides a valuable framework for scrutinizing the role of alloreactivity in health and disease.

This study derives space travel pricing by Walrasian Equilibrium, which is logical reasoning from the general relativity theory (GRT), the accounting equation, and economic supply and demand functions. The Cobb-Douglas functions embed the endogenous space factor as new capital to form the space travel firm's production function, which is also transformed into the consumer's utility function. Thus, the market equilibrium occurs at the equivalence of supply and demand functions, like the GRT presents the equivalence between the spatial geometric tensor and the energy-momentum tensor, which explains the principles of gravity and the motion of space matter in the spacetime framework. The mathematical axiomatic set theory of the accounting equation explains the equity premium effect that causes a short-term accounting equation inequality, then reaches the equivalence by suppliers' incremental equity through the closing accounts process of the accounting cycle. On the demand side, the consumption of space travel can be assumed as a value at risk (VaR) investment to attain the specific spacetime curvature in an expected orbit. Spacetime market equilibrium is then achieved to construct the space travel pricing model. The methodology of econophysics and analogy method was applied to infer the space travel pricing by the model of profit maximization, single-minded, and envy-free pricing in unit-demand markets. A case study with simulation was conducted for empirical verification of the math models and algorithm. Results show that space travel pricing remains the principle of market equilibrium but needs to be extended to the spacetime tensor of GRT.

The multiobjective optimization problem is a key research direction in the field of optimization. Based on the multivariant optimization algorithm (MOA), this paper puts forward a multiobjective multivariant optimization algorithm (MMOA). A good point set is adopted for population initialization and to ensure the homogeneity of the initial solution set and avoid prematurity; global atoms are acquired by non-dominated sorting and an external archiving strategy; a nonlinear search radius is designed to balance global and local searches and enhance the convergence precision of the algorithm. Levy Flight and Sine chaotic mapping are introduced to redesign the update formula for local atoms, increase the convergence rate of the algorithm, and boost the optimization efficiency. Comparative experiments are conducted between MMOA and NSGA-II, MOEA/D, NSWOA, MOGWO, NSMFO on multiobjective test functions and an engineering example. The simulation results show that MMOA has superior convergence and diversity to the other five algorithms.