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The paper deals with assortment optimization when customers purchase products using a nonparametric choice model. Each customer is presented with a preference list and will buy an available highest‐ranked offered product on the preference list. The paper presents a novel bi‐objective integer programming model for assortment optimization following a ranking‐based consumer choice model. The objectives are maximizing the expected revenue and maximizing customer satisfaction. This problem is recognized as an NP‐hard problem. After developing the bi‐objective model, an improved version of the augmented ε$\varepsilon $‐constraint method is proposed to solve the problem and retrieve the Pareto‐optimal solutions. In each iteration, this algorithm solves a single‐objective linear integer programming sub‐problem. Our approach aims to obtain a complete set of Pareto‐optimal solutions. Finally, we present computational experiments on synthetic data. Several numerical illustrations are provided at the end to demonstrate the application of the proposed methodology. The computational results provide the decision‐makers with valuable information regarding the factors that mainly affect the solutions. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to investigate how the enrichment of medical documents' index terms by their comments improves the relevance and novelty of the top-ranked results retrieved by an NLP system. Design/methodology/approach: A semi-experimental pre-test and post-test research was designed to compare NLP-based indexes before and after being expanded by the comment terms. The experiments were conducted on a test collection of 13,957 documents commented by F1000-Prime reviewers. They were indexed at title, abstract, body and full-text levels. In total, 100 seed documents were randomly selected and served as queries. The textual similarity of the documents and queries was calculated using Lucene-more-like-this function and evaluated by the semantic similarity of their MeSH. The results novelty was measured using maximal marginal relevance and evaluated by their MeSH novelties. Normalized discounted cumulative gain was used to compare the basic and expanded indexes' precisions at 10, 20 and 50 top ranks. Findings: The relevance and novelty of the results ranked at the top precision points was improved after expanding the indexes by the comment terms. The finding implies that meta-texts are effective in representing their mother documents, by adding dynamic elements to their rather static contents. It also provides further evidence about the merits of the application of social intelligence and collective wisdom reflected in the actions and reactions of users in tackling the challenges faced by NLP-based systems. Originality/value: This is the first study to confirm that social comments on scientific papers improve the performance of information systems in terms of relevance and novelty. Peer review: The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-05-2022-0283. [ABSTRACT FROM AUTHOR]

Knowing customer types and their purchase behavior helps revenue management experts to estimate the demand and finally devise a better sales strategy to improve the revenue. Inferring customer types from sales transactions and availability data is a challenging topic in RM. In this paper, we proposed an approach to discover customer types using a classic linear ordering problem. Our linear ordering-based market discovery approach (LMD) comprises three steps: generation of an initial solution, evaluation of the solution by a choice-based model, and finally creation and addition of a new customer type. The number of different customer types is factorial in the number of alternatives and should be pruned. Here, the customer types are pruned based on observed sales and offered-sets, instead of business assumptions or applications. To evaluate the proposed method, a real publicly available dataset of five hotels is used. The results show that LMD outperforms the other available approaches in the literature and improves the log-value results of all datasets by approximately 6%. [ABSTRACT FROM AUTHOR]

Purpose: Co-citation frequency, defined as the number of documents co-citing two articles, is considered as a quantitative, and thus, an efficient proxy of subject relatedness or prestige of the co-cited articles. Despite its quantitative nature, it is found effective in retrieving and evaluating documents, signifying its linkage with the related documents' contents. To better understand the dynamism of the citation network, the present study aims to investigate various content features giving rise to the measure. Design/methodology/approach: The present study examined the interaction of different co-citation features in explaining the co-citation frequency. The features include the co-cited works' similarities in their full-texts, Medical Subject Headings (MeSH) terms, co-citation proximity, opinions and co-citances. A test collection is built using the CITREC dataset. The data were analyzed using natural language processing (NLP) and opinion mining techniques. A linear model was developed to regress the objective and subjective content-based co-citation measures against the natural log of the co-citation frequency. Findings: The dimensions of co-citation similarity, either subjective or objective, play significant roles in predicting co-citation frequency. The model can predict about half of the co-citation variance. The interaction of co-opinionatedness and non-co-opinionatedness is the strongest factor in the model. Originality/value: It is the first study in revealing that both the objective and subjective similarities could significantly predict the co-citation frequency. The findings re-confirm the citation analysis assumption claiming the connection between the cognitive layers of cited documents and citation measures in general and the co-citation frequency in particular. Peer review: The peer review history for this article is available at https://publons.com/publon/10.1108/OIR-04-2020-0126. [ABSTRACT FROM AUTHOR]

Introduction: It remains a matter of debate whether traditional concepts regarding the nature of food affect the development and progression of multiple sclerosis (MS).To date, there are limited studies that have investigated the association between MS and dietary patterns based on the categories of food nature (hot, cold, or balanced) defined in traditional medicine.Method: This case-control study was conducted from October 2019 to February 2020. In total, 60 patients diagnosed with MS within the preceding 6 months and referred to our neurology outpatient clinic were included in our case group. The control group included 180 patients who were referred to the same center for general or orthopedic surgery. Dietary intake was assessed in both groups through a reliable and valid semi-quantitative food frequency questionnaire. Data were assessed using principal component analysis.Results: The mean age of the participants was 44.9 ± 17.33 years. The analysis showed that four food patterns were distinguished (eigenvalue > 1), namely "additives and cold-natured foods", "hot and balanced foods and nuts", "dairy and legumes", and "hot and balanced starches". These food patterns explained 57.8% of the total variance. After adjusting all confounding factors, individuals in the highest quartile and medium quartile of "additives and cold-natured foods" had an elevated MS risk compared with the lowest quartile (OR = 7.21, 95%CI = 2.01-12.38 and OR = 3.37, 95%CI = 1.02-11.35, respectively). Furthermore, individuals in the highest quartile of the "hot and balanced foods and nuts" group were protected against MS compared with its lowest quartile (OR = 0.28, 95%CI = 0.08-0.90). Moreover, a protective effect against MS was seen in the highest quartile of the "hot and balanced starches" group relative to its lowest quartile (OR = 0.34, 95%CI = 0.12-0.98). No significant association was found between "dairy and legumes" and the risk of MS.Conclusion: This study revealed that dietary patterns based on the traditional concept of food nature might be associated with the risk of developing MS. This represents the first work in this area, so further research is recommended. [ABSTRACT FROM AUTHOR]

Purpose: Social comments are rich in information and useful in evaluating, ranking or retrieving different kinds of materials. However, their merits in representing or providing added values to scientific articles have not yet been studied. Therefore, the present study investigates the informativeness of open review reports as a kind of social comments in a scholarly setting. Design/methodology/approach: A test collection was built consisting of 100 randomly selected queries, 1,962 reviewed documents and their reviewers' open reports from F1000Research. They were analyzed using natural language techniques. The comments' salient words were compared to the documents' and also to the Medical Subject Headings (MeSH) salient words. The receiver operating characteristic (ROC) curve was used to test the accuracy of the comments in representing their related articles. Findings: The papers' contents and comments have a considerable number of salient words in common. The comments' salient words are also largely found in the MeSH, signifying their consistency with the knowledge tree and their potential to add some complementary features to their related items. The ROC curves confirm the accuracy of the comments in retrieving their related papers. Originality/value: This research is the first to reveal the merits of open review reports on scientific papers, in terms of their relatedness to their mother articles, in specific, and to the knowledge tree, in general. They are found informative in not only representing the reviewed papers but also in adding values to the contents of the papers. [ABSTRACT FROM AUTHOR]

Demand forecasting is an integral part of every revenue management system. Demand raises from customers; therefore, knowing customers and their behavior is essential in this regard. Similar customers are grouped into a customer type. Discovering customer types from sales transactions and product availability data is a challenging topic. The basic idea of this paper is to use metaheuristic's capability in exploring the search space instead of mathematical demand models in the research field of market discovery. In this work, a genetic algorithm is proposed to find efficient customer types. The main challenge of using a genetic algorithm in this field is to choose the proper fitness function. We use a two-phase fitness function for this problem to evaluate feasible and infeasible solutions. To evaluate the proposed method, a real publicly available dataset of five hotels is used. The results indicate that the genetic algorithm improves approximately 10% of the log-likelihood value of other proposed approaches with equal or lower number of customer types. [ABSTRACT FROM AUTHOR]

Purpose: Variations of cerebral blood flow in response to hypoxia and hyperoxia in different disease conditions can provide new insights into disease etiopathogenesis. This study aimed to determine the characteristics of cerebral vasoreactivity for ischemia and demyelination. Materials and methods: This case–control study included: 28 patients with lacunar infarctions verified by history, physical examination, and MRI; 28 age- and sex-matched healthy controls; 28 patients with relapsing–remitting multiple sclerosis (MS), based on McDonald criteria; and 28 age- and sex-matched healthy controls for the MS group. Transcranial Doppler sonography was undertaken in all subjects to calculate the mean flow velocity (MFV) of the right middle cerebral artery (MCA) and, after a breath-holding (BH) maneuver, the breath-holding index (BHI) was determined. Results: There was no significant difference of BHI and changes of MFV of the MCA in MS patients compared to controls (1.02 ± 0.4 vs 1.02 ± 0.3, p = 0.993; and 16.8 ± 8.1 vs 11.3 ± 10.8, p = 0.057). BHI in patients with lacunar infarctions was significantly lower (0.8 ± 0.4 vs 1.2 ± 0.3, p < 0.001) compared to controls. The BHI (p = 0.040) and variations of MFV of MCA (p = 0.007) in MS patients were significantly higher than in patients with lacunar infarctions. The vasoreactivity of demyelinating lesions was higher than that of ischemic ones. Conclusion: Therefore, cerebral vasoreactivity determined by transcranial Doppler could be utilized for differentiating demyelinating from ischemic lesions. [ABSTRACT FROM AUTHOR]

Background: Multiple sclerosis (MS) is the most common neuroinflammatory disease in young adults. Anxiety and depression may predispose individuals to MS and flare-ups. Serotonin transmission is modified in some brain regions of patients with MS, and these changes may contribute to their psychiatric abnormalities. We studied the frequencies of common polymorphisms of the serotonin reuptake transporter (SERT) gene in patients with MS according to their psychological status. Methods: The 5-HTTLPR, rs25531, and STin2VNTR polymorphisms of the SERT gene were genotyped by polymerase chain reaction (PCR)-based methods in 100 patients with MS and 100 healthy controls. Results: There were no remarkable differences in SERT gene polymorphisms between patients with MS and healthy controls. Unlike the control group, 41% of the patients showed some degree of depression based on Beck Depression Inventory (BDI), but no association was observed between SERT gene polymorphisms after the patients were stratified by depression status. Conclusion: In addition to SERT gene polymorphisms, modulation of serotonin at the synapses may also be regulated by genetic variations in tryptophan hydroxylase type 2 and serotonin receptors. Further studies with functional brain imaging of the serotonergic system in patients with MS can provide information on the role of serotonin in this disease. [ABSTRACT FROM AUTHOR]

Semantics and accessibility are naturally part of HTML by design. Therefore, there is a must to significantly leverage the standard markup language and write the cleanest code possible. The purpose of this work is performing HTML validity check in terms of compliance with W3C standards for home pages of Iranian digital and electronic libraries in order to pave way for applying semantic technologies in Iranian Library websites. This is a comparative survey. 82 library software-based digital libraries and 68 electronic libraries were identified via Google search in the domains of .ir, .ac.ir, .org and .com. Data collected via an automatic tool developed by authors in which W3C Markup Validation Service is used for validation tests. Besides, total tags of URLs are counted through it to be able to normalize HTML error frequencies for each home page. Data were analyzed using nonparametric tests via IBM SPSS Statistics 20. Validation test results in about 50 percent failure rate. 38 out of 70 valid libraries are digital libraries and 32 are electronic ones. Mean of HTML error has dramatically decreased in 2017 in comparison with 2015; however Standard Deviation has increased sharply. Moreover, the distribution of HTML error scores is similar across digital and electronic libraries. Regarding conformance to HTML standards, it seems essential to revise the web design of Iranian digital and electronic libraries to fulfill semantic web potentialities. [ABSTRACT FROM AUTHOR]

During the selling time horizon of a product category, a number of products may become unavailable sooner than others and the customers may substitute their desired product with another or leave the system without purchase. So, the recorded sales do not show the actual demand of each product. In this paper, a nonparametric algorithm to estimate true demand using censored data is proposed. A customer choice model is employed to model the demand and then a nonlinear least square method is used to estimate the demand model parameters without assuming any distribution on customer's arrival. A simple heuristic approach is applied to make the objective function convex, making the algorithm perform much faster and guaranteeing the convergence. Simulated dataset of different sizes are used to evaluate the proposed method. The results show a 23% improvement in root mean square error between estimated and simulated true demand, in contrast to alternate methods usually used in practice. [ABSTRACT FROM AUTHOR]

Introduction The purpose of this study was to assess whether demographic, brain anatomical regions and contrast enhancement show differences in multiple sclerosis (MS) patients with increased diffusion lesions (ID group) compared with diffusion restriction (DR group). Method MRI protocol comprised T1- and T2-weighted sequences with and without gadolinium (Gd), and sagittal three-dimensional FLAIR sequence, DWI and ADC maps were prospectively performed in 126 MS patients from January to December 2015. The investigation was conducted to evaluate differences in demographic, cord and brain regional, technical, and positive or negative Gd contrast imaging parameters in two groups of ID and DR. Statistical analysis was performed by using SPSS. Results A total of 9.6% of patients showed DR. In the DR group, 66.6% of the patients showed contrast enhancement of plaques, whereas 29.2% of the IR group showed enhancement of plaques. The most prevalent group was non-enhanced plaques in the ID group, followed by Gd-enhanced plaques in the ID group. Patients in the ID group (90.4%) were significantly more than in the DR group (9.6%). Out of the 40 patients with Gd-enhanced plaques, 80.5% was from the ID group and 19.5% from the DR group.Conclusion MRI of the brain, unlike of the cord, with Gd demonstrates significant difference in enhancement between the two groups (p < 0.05). No significant difference was seen in demographic, cord and brain regional, and technical parameters, EDSS, disease duration, and attack rate as well as demographic and regional parameters between the ID and decrease diffusion groups (p > 0.05). [ABSTRACT FROM AUTHOR]

Multiple sclerosis (MS) is the most common cause of disability after trauma in young adults in Northern Hemisphere; it imposes a major burden on the affected young people. A significant association between MS and demyelinating peripheral neuropathy which might be due to common pathogenesis for the central and peripheral nerves demyelination has been reported in several studies. We aimed to assess if there is any peripheral nervous system involvement in a sample of Iranian MS population. Extensive nerve conduction studies (NCS) were conducted in 20 MS patients according to McDonald criteria, and 20 age and gender matched healthy appearing controls. The F-wave ratio was calculated through placing the minimum amount of F-wave proximal latency after 10 stimuli and median or tibial nerves compound motor action potential (CMAP) proximal latency in the corresponding formula. Data were compared between groups. Finally, we found the significantly lower median and tibial nerves conduction velocities (NCV) in MS patients than healthy controls (P=0.008 and 0.003 respectively, Independent Samples t-test). Also, tibial NCV had a significant statistical correlation with Kurtzke's expanded disability scale score (EDSS) as patients with higher EDSS had lower tibial NCV (Pearson's correlation coefficient, r²=0.8). No statistical relationship was found between MS subtypes and NCS parameters. Although we found some electrodiagnostic abnormalities in Iranian MS patients in comparison to the healthy participants, these differences were small and inconclusive. More extensive well-designed electrodiagnostic studies for evaluation of peripheral nervous system involvement and its probable pattern in these patients seems to be needed. [ABSTRACT FROM AUTHOR]

Background: Multiple Sclerosis (MS) is a chronic demyelinating disease of the central nervous system and its epidemiology has changed in recent years. Previously, Iran was considered to have a low MS prevalence. In this study, we aimed to update the prevalence and incidence of MS in Iran. Patients and Methods: This study was conducted based on the data derived from the new report of Iran's Ministry Of Health and Medical Education (MOHME) regarding the patients who have registered to obtain support for treatment in Iran till the end of 2013. Results: Among the 42,200 registered patients, 32,477 were female and 9,723 were male (sex ratio: 3.34: 1), and 4,545 were diagnosed in 2013. This resulted in a prevalence of 54.51 and an incidence of 5.87 per 100,000. Conclusion: According to our study results, Iran has a medium-to-high prevalence rate of MS. According to the previous epidemiologic studies from Iran, it seems that the prevalence of MS significantly has increased during recent years. This rate is similar to what is seen in many western countries. © 2014 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

The present study was performed to investigate the effects of dimethylfumarate (DMF) and methylhydrogen fumarate (MHF) on the cytokine pattern of peripheral blood mononuclear cells (PBMCs) of multiple sclerosis (MS) patients. The PBMCs from patients and healthy controls were stimulated with myelin basic protein (MBP) or phytohemagglutinin (PHA) and cultured in the presence of DMF and MHF. The percentage of CD4++IL-4++ and CD4++IFN-γγ++ cells was determined by means of intracellular cytokine staining. CD4++IL-4++ cells were significantly increased in the presence of DMF and MHF when PBMCs were stimulated by MBP (P < 0.003). The same significant result was obtained by PHA stimulation (P < 0.049). In terms of CD4++IFN-γγ++ cells, the percentage of cells did not significantly differ between the cultures stimulated with MBP or PHA in the presence and absence of the drugs. Results of MBP stimulation in control group also showed a significant increase in CD4++IL-4++ cells in the presence of DMF and MHF. In comparison between patient and control groups, no statistically significant changes were observed. In conclusion, both DMF and MHF effectively increased IL-4 production, whereas they did not significantly change IFN-γγ level, indicating the role of these drugs in increasing the production of beneficial cytokines such as IL-4. [ABSTRACT FROM AUTHOR]