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Inverse data envelopment analysis (DEA) approach deals with the input or output estimation preserving relative efficiency score. In many real-world applications, there is more prior information like price information or managerial preferences, etc. that should be considered in the efficiency analysis. Corporation of this sort of information is not dealt with in the inverse DEA literature, not in the input estimation process nor in the output estimation. Thus, the current paper develops a new inverse DEA model capable of dealing with prior information viaweight restrictions. Proposed models are applied in the efficiency and inverse efficiency analysis of a real-world retailer application.

This study introduces a novel approach named the fuzzy Kemeny median indicator ranks accordance (KEMIRA) method tailored for multiattribute decision making (MADM) while capturing and processing the uncertainties inherent in complex problems. We explore preferential voting to enhance MADM models, rewriting it as a linear programming (LP) problem with weight restrictions. Our fuzzy KEMIRA model leverages LP to ascertain optimal priorities and weights for each feature, guided by discrimination intensity functions. To illustrate the effectiveness of our approach, we utilize a well-known numerical example from the literature. We also present a case study describing the location selection of an innovation park constrained by experts’ subjective judgments across various attributes. Through comparative analyses with hesitant fuzzy KEMIRA and stochastic KEMIRA, we demonstrate our proposed fuzzy KEMIRA method's higher flexibility and reduced computational burden. By emphasizing these attributes, we underscore the versatility of our method, which applies to a broad spectrum of MADM problems that go well beyond specific instances.

The use of pesticides to eliminate pests and weeds has raised concerns about water pollution and adverse effects on aquatic organisms, so many efforts have been made to increase the resistance of fish to these pesticides by using a proper nutrition strategy. Therefore, the aim of this study is to investigate the growth performance, antioxidant, and immune responses of fish exposed to Imidacloprid insecticide (C9H10ClN5O2) by different doses of Chlorella vulgarisdry powder to the diet of common carp (Cyprinus carpio). In this study, 600 common carp with a medium weight (18.10±0.2 g; mean ± SE) were prepared and after adaptation and determination of lethal concentration of Imidacloprid, for 56 days in 6 treatments and each with 3 replications were classified and tested (Control (T1), 5% Chlorella vulgarisdry powder and no pollution (T2), 10% Chlorella vulgarisdry powder and no pollution (T3), No Chlorella vulgarisdry powder and 12.5% LC50Imidacloprid (T4), 5% Chlorella vulgarisdry powder plus 12.5% LC50Imidacloprid (T5) and 10% Chlorella vulgarisdry powder plus 12.5% LC50Imidacloprid (T6)). After 96 hours of exposure to distinct concentrations of the insecticide, the total mortality was measured and the Imidacloprid median lethal concentration (LC50) over 96 hours was calculated (266.2 mg/l) using Probit analysis. According to the result, common carp fed T2 had the highest final weight (FW), weight gain (WG), and specific growth rate (SGR), and the lowest feed conversion ratio (FCR) among the groups (P<0.05). Fish in the T2 group had the highest total proteins, albumin and globulin (P<0.05). Fish in the group T4 had the highest cortisol, lactate dehydrogenase (LDH), alanine aminotransferase (ALT), aspartate aminotransferase (AST), and alkaline phosphatase (ALP) levels in the blood, while fish fed T2 and T3 had low values (P<0.05). The alternative complement pathway (ACH50) was significantly higher in T2 and T3 than other groups (P<0.05). Blood total immunoglobulin (Ig) and lysozyme activity were high in T2 and T3 groups, and had the lowest values in the T4 group (P<0.05). The superoxide dismutase (SOD), catalase (CAT) and glutathione peroxidase (GPx) showed the highest activities in T2 (P<0.05). T4 group had the highest malondialdehyde (MDA) level, while T2 and T3 groups had the lowest MDA level (P<0.05). The highest amylase, protease and lipase were in the T2 group, while the lowest values were in the T4 group (P<0.05). In conclusion, dietary Chlorella vulgarisprotects common carp from Imidacloprid insecticide, since it improved growth performance, antioxidant and immune responses of fish.

Oxcarbazepine as an anticonvulsant has been suggested as an effective drug in affective disorders. The present study was designed to compare the efficacy of oxcarbazepine and sodium valproate in the treatment of acute mania in the Iranian population. In a double-blind, randomized clinical trial, hospitalized bipolar patients in the acute manic phase who were admitted to Ibn-e-Sina psychiatric hospital in Mashhad city (north-eastern part of Iran) were enrolled. The diagnosis was confirmed using Structured Clinical Interview for DSM-IV-TR. Patients were then randomly allocated into two groups taking oxcarbazepine (900–2400 mg/day) and sodium valproate (about 20 mg/kg/day) for 6 weeks. Young Mania Rating Scale (YMRS), Clinical Global Impression Scale (CGI-S), and adverse effects of drugs were assessed at baseline and after 3 and 6 weeks. Mania symptoms based on mean scores of YMRS and CGI-S significantly decreased from baseline to endpoint in both treatments (P< 0.01). However, there was no significant difference between the two groups in terms of reduction of symptoms during times (P= 0.715 and P= 0.446, respectively) and adverse events (P> 0.05). This study confirmed the previous findings that indicate the efficacy of oxcarbazepine as same as sodium valproate. Moreover, its adverse effects resemble sodium valproate in the treatment of acutely manic patients.

Multi-attribute decision-making (MADM) methods have always been considered by managers as a tool to support decision making. One of the best methods is to select based on expert opinions. In fact, providing models for aggregating the votes of voters in the group decision making is a subject that has always attracted researchers' attention. We aimed, in this paper, to present a model for aggregating the votes of voters who have been divided by the decision maker (DM) into two groups of desirable and undesirable ones. The proposed model has been explained by presenting its application while a numerical example and case study have also been provided.

The initial issue that must be addressed in teamwork is the manner in which decisions are made by the group and its members. Voting is a procedure to aggregate individual votes to achieve a collective decision. Since individuals have varied opinions and preferences, preferential voting assists in conveying the priorities of the voters to the society or community. In many circumstances, such as voting-based managerial decisions, voters are of a voting preference of unequal voting power. This paper presents a method for the ranking of preferential voting with voters of unequal voting power, which, in addition to the utilization of preference voting models, employs the DEA and assurance region techniques. The deployment of DEA technique causes an increment in the competence of discriminating the ranking of candidates, and in the finale the proposed method is expressed for an empirical example to rank the petrochemical companies in the Tehran Stock Exchange.

The stop signal reaction time (SSRT), a measure of the latency of the stop signal process, has been theoretically formulated using a horse race model of go and stop signal processes by the American scientist Gordon Logan (1994). The SSRT assumes equal impact of the preceding trial type (go/stop) on its measurement. In the case of a violation of this assumption, we consider estimation of SSRT based on the idea of earlier analysis of cluster type go reaction times (GORT) and linear mixed model (LMM) data analysis results. Two clusters of trials were considered including those trials preceded by a go trial and other trials preceded by a stop trial. Given disparities between cluster type SSRTs, we need to consider some new indexes considering the unused cluster type information in the calculations. We introduce mixture SSRT and weighted SSRT as two new distinct indexes of SSRT that address the violated assumption. Mixture SSRT and weighted SSRT are theoretically asymptotically equivalent under special conditions. An example of stop single task (SST) real data is presented to show equivalency of these two new SSRT indexes and their larger magnitude compared to Logan's single 1994 SSRT.Abbreviations:ADHD: attention deficit hyperactivity disorder; ExG: Ex-Gaussiandistribution; GORT: reaction time in a go trial; GORTA: reaction time in a type A gotrial; GORTB: reaction time in a type B go trial; LMM: linear mixed model; SWAN:strengths and weakness of ADHD symptoms and normal behavior rating scale; SSD: stop signal delay; SR: signal respond; SRRT: reaction time in a failedstop trial; SSRT: stop signal reaction times in a stop trial; SST: stop signaltask.

This paper is aimed to make a detailed comparison among international opportunity recognition (IOR) profiles of foreign small and medium enterprises (SMEs) in Iran including four specific countries. After undertaking a literature review, we have conducted 44 semi-structured interviews with SMEs from different industries which focused on Iranian markets in their IOR. Using matrix approach for data display and condensation, this analysis extracted main themes from practitioners' responses by discussion based on literature, and led to a set of IOR profiles divided by each country's practice. The research indicated that most of SMEs commence their OR process by attending fairs or outgoing delegations and continue different routes based on their industrial, cultural and networking components grouped into six factors. The method we have developed for IOR-mapping could help international business scholars to analyse and compare practitioners' situation with others and it also facilitates IOR initiatives locally and globally.

Aim:This research evaluated standard Weibull mixture cure (WMC) network meta-analysis (NMA) with Bayesian hierarchical (BH) WMC NMA to inform long-term survival of therapies. Materials & methods:Four trials in previously treated metastatic non-small-cell lung cancer with PD-L1 >1% were used comparing docetaxel with nivolumab, pembrolizumab and atezolizumab. Cure parameters related to a certain treatment class were assumed to share a common distribution. Results:Standard WMC NMA predicted cure rates were 0.03 (0.01; 0.07), 0.18 (0.12; 0.24), 0.07 (0.02; 0.15) and 0.03 (0.00; 0.09) for docetaxel, nivolumab, pembrolizumab and atezolizumab, respectively, with corresponding incremental life years (LY) of 3.11 (1.65; 4.66), 1.06 (0.41; 2.37) and 0.42 (-0.57; 1.68). The Bayesian hierarchical-WMC-NMA rates were 0.06 (0.03; 0.10), 0.17 (0.11; 0.23), 0.12 (0.05; 0.20) and 0.12 (0.03; 0.23), respectively, with incremental LY of 2.35 (1.04; 3.93), 1.67 (0.68; 2.96) and 1.36 (-0.05; 3.64). Conclusion:BH-WMC-NMA impacts incremental mean LYs and cost–effectiveness ratios, potentially affecting reimbursement decisions.

In this paper we have attempted to provide Iranian business practitioners with a profile on international opportunity recognition (IOR). After undertaking a review on IOR literature we have presented our methodology; thematic analysis on 43 semi-structured-interviews with Iranian companies working in the construction, mining and home appliances industries. This analysis extracted main themes from practitioners' responses by discussion based on literature, and led to a hierarchy and profile among themes. This profile revealed that brand reputation, human capital and trust in home country, and extension of company's FDI are antecedents that affect companies' IOR using a set of sources. The method we have developed for IOR-mapping could help international business scholars in other countries to analyse their practitioners' situation at IOR and facilitate this process at national or regional level.

To compare the effectiveness of inhalation sedation with nitrous oxide/oxygen (N2O/O2) and cognitive behavioural therapy (CBT) in reducing dental anxiety in preschool children. Randomised controlled clinical trial. This study was conducted on 45 preschoolers with moderate to severe dental anxiety (determined by the Children’s Fear Survey Schedule Dental Subscale), who required pulp treatment of at least one primary mandibular molar. Baseline anxiety and cooperation levels were determined using Venham Clinical Anxiety and Cooperation Scales (VCAS and VCCS) and Venham Picture Test (VPT) at the first dental visit (dental prophylaxis and fluoride treatment). Before the second dental visit (pulp treatment), the children were randomly assigned to one of three groups—1: control, 2: N2O/O2and 3: CBT. In group 1, the usual behaviour management techniques were used, in group 2, nitrous oxide/oxygen gas was used and in group 3, unrelated play, Benson’s breathing and positive self-talk and modelling were used. Anxiety and cooperation levels were determined at three periods: injection, rubber dam placement and the application of a high-speed handpiece with VCAS and VCCS and VPT. Finally, anxiety and cooperation differences between the two dental visits were compared within the three groups. Chi square, ANOVA and Kruskal–Wallis and Mann–Whitney Utests were used. N2O/O2and CBT significantly resulted in lower anxiety and higher cooperation in the second visit (at all three periods) compared to the control, although there was no significant difference between these two treatment methods. Both test methods were effective in reducing dental anxiety in preschoolers. Considering the adverse effects and necessity of equipment and trained personnel when using nitrous oxide and oxygen inhalation sedation, cognitive behavioural therapy is preferable because of its better applicability.

In conventional data envelopment analysis, it is assumed that the input versus output status of any particular performance measure is known. In some situations, finding the status of some variables from the input or output point of view is very difficult; these variables are treated as both inputs and outputs and are called flexible measures. In this paper, using the TOPSIS method, and also using a voting model, the status of such a variable will be determined, and the results obtained will be employed to evaluate the efficiency of homogeneous decision making units. Note that all the models used in this paper are linear programming models and there is no need to solve any integer programming model. The approach is illustrated by an example.

Efficiency is a relative measure because it can be measured within different ranges. The traditional voting models measure the efficiencies of candidates within the range of less than or equal to one. The corresponding efficiencies are referred to as the best relative efficiencies, which measure the best performances of candidates. There is another model called ‘inverted voting’ which measures the worse performances of candidates based on mixed integer linear programming. But, there are no relations essentially between voting model and inverted voting model. Thus, we introduce an interval efficiency which consists of efficiencies obtained from the optimistic and pessimistic viewpoints. A minimax regret-based approach (MRA) is used to compare and rank the efficiency intervals of candidates.

In most models of data envelopment analysis (DEA), the best performers have the efficiency score of unity. Usually there are plural decision making units (DMUs) which have this ‘efficient status’ and DEA cannot provide more information about these efficient DMUs. Discrimination between these efficient DMUs is an interesting research subject. In effect, most conventional methods to rank efficient DMUs are based on the concept of common weights analysis (CWA). In this paper, after reviewing the existing common weights models, we propose a new methodology to rank the common weights models for the performance indices of only DEA efficient DMUs based on a voting model. Also, an approach for combining the results obtained from the common weights models is presented. Then, we give an example to illustrate our approach, and finally the new method is employed to rank efficient units in a real world problem.

Linear programming problems with fuzzy variables have been investigated by many researchers in the recent literature. Some methods to solve these problems, such as the primal simplex method and the dual simplex method, are based on the concept of comparison of fuzzy numbers by using ranking functions. In this paper, we give a new primal-dual algorithm for solving linear programming problems with fuzzy variables by using duality results, which was proposed by Mahdavi-Amiri and Nasseri (2007). This algorithm will be useful for sensitivity analysis when the activity vectors change for basic columns. [Received 29 September 2008; Revised 16 March 2009; Accepted 17 April 2009]

There are different ways to allow the voters to express their preferences on a set of candidates. In ranked voting systems, each voter selects a subset of the candidates and ranks them in order of preference. Cook and Kress using a data envelopment analysis/assurance region (DEA/AR) model, proposed to assess each candidate with the most favourable scoring vector for him/her. However, the use of this procedure often causes several candidates to be efficient, i.e., they achieve the maximum score. For this reason, several methods to discriminate among efficient candidates have been proposed. In this research, after reviewing the existing ranking models, we propose a new methodology to rank the ranking models for the performance indices of only DEA efficient candidates based on a voting model. Also, an approach for combining the results obtained from the ranking models is presented.

Background: Obsessive-compulsive disorder (OCD) is a potentially debilitating disease that affects 1-4% of the general population. It is characterized by the presence of obsessions and compulsions which interfere with the individuals life and functioning. Although conventional treatments such as drug therapies and cognitive behavioral therapy exist for OCD, these treatments are not universally successful and can cause side effects, which has created a demand for alternative and complementary therapies. Methods: In this review, we summarize randomized clinical trials on the effectiveness of herbal medicines for the treatment of OCD, and review the possible mechanisms of action for these medicines. A search in PubMed, Scopus, and The Cochrane Library found 1022 studies, of which 7 were included in our review. Results: The studies that we found were conducted over 6 to 12 weeks, and had an average sample size of 37. The plant species studied included Crocus sativus, Echium amoenum, Hypericum perforatum, Silybum marianum, Valeriana officinalis, and Withania somnifera. The trials demonstrated the effectiveness of all plants as treatments for OCD except H. perforatum. The phytochemicals found in these plants produce their effects through a variety of means such as inhibiting the reuptake of monoamines, GABAergic effects, and neuroendocrine modulation. The small number of studies and their small sample sizes, poor methodology, and lack of replication highlight the need for further research into herbal medicines for the treatment of OCD. Conclusion: Overall, herbal medicines can be used as stand-alone therapies for OCD or in conjunction with other methods.

Background: Obsessive-compulsive disorder (OCD) is a severe and debilitating neuropsychiatric condition. Although selective serotonin reuptake inhibitors, tricyclic antidepressants, and cognitive- behavioral therapy are the first-line medication and treatment for OCD, an estimated 30% of patients are treatment-resistant, and complete functional recovery is rare. Natural products as adjuvant or alternative therapies should be examined to find safer and more effective ways to manage OCD. Objectives: To investigate the potential benefits of a combined herbal drug based on Echium amoenum in treating OCD. Methods: Design and Setting: In the psychiatric clinics of Mashhad University of Medical Sciences, 40 patients who met the criteria for the obsessive-compulsive disorder based on DSM-5 were studied in a parallel, double-blind, randomized clinical trial. Intervention: Subjects were randomly assigned to receive Echium amoenum-Melissa officinalis syrup and fluvoxamine or placebo syrup and fluvoxamine for 8 weeks. Outcome Measures: The efficacy of treatment and recurrence of disease were surveyed and compared according to the Yale-Brown Obsessive Compulsive Scale at weeks 0, 4, and 8. Results: Evaluation at the 4th and 8th week showed no significant differences between the two groups (p-value = 0.11, p-value = 0.445, respectively). At the 8th week of treatment, patients in the intervention group showed a remarkable reduction in scores on the Yale-Brown Obsessive-Compulsive Scale questionnaire (p- value= 0.003), and patients in the control group didnt ((p- value= 0.180). This study showed that the E.amoneum-M.officinalis syrup was not significantly more efficacious than the fluvoxamine tablet, but the intervention group showed a significant improving trend (p-value= 0.001). Conclusion: While monotherapy is usually the gold standard methodology, combination or augmentation therapy may also be of merit. Consequently, studies with larger sample sizes and the inclusion of para-clinical assessments such as serologic tests can further shed light on the mechanism of action of the E. amoneum- M. officinalis syrup and deepen our understanding of its effects.

The cleavable pre‐sequences of imported chloroplast and mitochondrial proteins have several features in common. This structural similarity prompted us to test whether a chloroplast pre‐sequence (‘transit peptide’) can also be decoded by the mitochondrial import machinery. In the green alga, Chlamydomonas reinhardtii, the small subunit of ribulose‐1,5‐bisphosphate carboxylase/oxygenase (Rubisco) (a chloroplast protein) is nuclear‐encoded and synthesized in the cytosol with a transient pre‐sequence of 45 residues. The 31 amino‐terminal residues of this chloroplast pre‐sequence were fused to mouse dihydrofolate reductase (a cytosolic protein) and to yeast cytochrome oxidase subunit IV (an imported mitochondrial protein) from which the authentic pre‐sequence had been removed. The chloroplast pre‐sequence transported both attached proteins into the yeast mitochondrial matrix or inner membrane, although it functioned less efficiently than an authentic mitochondrial pre‐sequence. We conclude that mitochondrial and chloroplast pre‐sequences perform their function by a similar mechanism.

The cleavable pre‐sequences of imported chloroplast and mitochondrial proteins have several features in common. This structural similarity prompted us to test whether a chloroplast pre‐sequence (‘transit peptide’) can also be decoded by the mitochondrial import machinery. In the green alga, Chlamydomonas reinhardtii, the small subunit of ribulose‐1,5‐bisphosphate carboxylase/oxygenase (Rubisco) (a chloroplast protein) is nuclear‐encoded and synthesized in the cytosol with a transient pre‐sequence of 45 residues. The 31 amino‐terminal residues of this chloroplast pre‐sequence were fused to mouse dihydrofolate reductase (a cytosolic protein) and to yeast cytochrome oxidase subunit IV (an imported mitochondrial protein) from which the authentic pre‐sequence had been removed. The chloroplast pre‐sequence transported both attached proteins into the yeast mitochondrial matrix or inner membrane, although it functioned less efficiently than an authentic mitochondrial pre‐sequence. We conclude that mitochondrial and chloroplast pre‐sequences perform their function by a similar mechanism.

The commercially important Indica rice cultivar Oryza sativa cv. IR72 has been transformed using direct gene transfer to protoplasts. PEG-mediated transformation was done with two plasmid constructs containing either a CaMV 35S promoter/HPH chimaeric gene conferring resistance to hygromycin (Hg) or a CaMV 35S promoter/BAR chimaeric gene conferring resistance to a commercial herbicide (Basta) containing phosphinothricin (PPT). We have obtained so far 92 Hgr and 170 PPTr IR72 plants from protoplasts through selection. 31 Hgr and 70 PPTr plants are being grown in the greenhouse to maturity. Data from Southern analysis and enzyme assays proved that the transgene was stably integrated into the host genome and expressed. Transgenic plants showed complete resistance to high doses of the commercial formulations of PPT.

In everyday life, many decisions are made, from personal and individual issues to major issues. In most decision-making topics, there are generally several goals and factors for discussion that are analyzed by multi-objective models. Researchers have conducted various studies on multi-objective problem-solving methods and have proposed several approaches to the principles of different theories. Most of these methods face a set of solutions that, based on the structure of the method, suggest one to the Decision Maker (DM), and decision analysis is necessary to arrive at an applicable solution. The process of interacting with the DM in most of these methods is both insufficient or very complex and time consuming. This paper investigates the most common multi-objective optimization methods and in each case proposes suggestions for improving the performance of the method and further interaction with the DM using weight restrictions and discrimination intensity functions; thus providing a more powerful tool for decision support. Each method and its improvement are illustrated with a numerical example.