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Abstract The purpose of this research is to design a model to evaluate the level of digitization of the innovation process centered on artificial intelligence in knowledge-based companies, so that the digital maturity of the innovation process in an organization can be measured. The results of 188 indicators were distributed in the form of a 5-point Likert questionnaire and by Delphi method in two times among 18 experts in this field. The result of the work was 5 components as input to the model, which was sent in the form of a questionnaire to 230 knowledge-based companies of Pardis Technology Park. 198 companies completed it and sent it back. From this number of samples, 150 data were separated for training data and 48 data as model test based on a random function. In the last stage, i.e. modeling, the adaptive neural-fuzzy inference method was used for the model. The method of grid separation or lookup table (PG) in MATLAB 2023 software was used to evaluate the performance of the model using root mean square, error (RMSE) and relative error (E). This research was able to provide an intelligent model with a very low error. As a result, it was able to achieve effective indicators in the degree of digitization of the innovation process. Extended Abstract Introduction An innovation process, whether in its general form from the stage of idea formation to the stage of entering the market and commercialization, or in each of the parts separately, must be in such a way that it has the most productivity (efficiency and effectiveness combined during the process). Moving in this direction reduces financial, time and human costs. The relevance of innovation to ensure the competitiveness of companies has been confirmed among researchers and professionals (Schiuma, 2012). Also, innovation is a risky process that requires resources, competence, culture and attitudes that cannot even be promoted and managed easily (D'Este et al., 2012). Due to the mismatch in digital skills and awareness, employees are not able to understand the reasons and potential of implementing new technology and displacement. Therefore, the next challenge in the digital ecosystem is to promote and define conditions, roadmaps and management models for implementing digital innovation strategies, for managing digital knowledge and fostering continuous innovation (Nonaka & Takeuch, 2019). Innovation processes rely on external institutions, i.e. innovation intermediaries, research and development laboratories, or innovation centers (Corre & Mischke, 2005). Global and virtual competition, as well as the rapid development of digital technologies and solutions, raise efficiency standards, increase the speed of market dynamics, and reduce product life cycles (Schiuma, 2012). Each actor involved in innovation must be aware of the organization's vision, goals, and strategies in order to effectively contribute and generate value (Lianto et al., 2018; Nonaka & Takeuchi, 2019). To understand and effectively manage technology, codification and exploitation of generated knowledge, specialized skills and new governance models are required (Joshi et al., 2010). Theoretical framework Digital innovation process Completely rebuilding business around new opportunities and new demands is possible through digital technology. Eyring et al., (2022) in an article, mentioned these processes under the title of digitization. Digitization is a useful and effective necessity. It provides a vision of digital assets that offer opportunities to business or even to industry. Digitization sometimes reconceptualizes their products by serving a business model through their artifacts. Digital transformation describes a sometimes broad process of change that may have multiple goals, while innovation focuses on the moment of invention and the implementation of that invention. Innovation may cause fundamental changes and vice versa, but both are not synonymous. Advancement of digitization and digital changes may be started as an innovation action. This may be catalyzed by new business opportunities, but ultimately must reach beyond the innovation function to reshape the entire organization (Globe, 2018). Businesses need a dynamic tool to support their digital innovation management efforts. Artificial intelligence Artificial intelligence is sometimes called machine intelligence, refers to the intelligence shown by machines in various situations, which is in contrast to the natural intelligence in humans; in other words, artificial intelligence refers to systems that can react similar to human intelligent behavior, including understanding complex situations, simulating human thinking processes and reasoning methods and successfully responding to them, learning and having the ability to acquire knowledge and reason to solve problems (Teece et al., 1997). The scientific study of algorithms and statistical models are used by computer systems that use patterns and inference to perform tasks rather than using clear instructions. Machine learning is the science of making computers learn about a specific subject without the need for an explicit program. As a subset of artificial intelligence, machine learning algorithms create a mathematical model based on sample data or "training data" in order to predict or make decisions without overt planning (Du et al., 2019). Research methodology The sampling method was carried out in the form of theoretical saturation at the stage that no new material was obtained from the articles as a new index, and other indices were common in meaning and concept. In this study, Pardis Technology Park companies and its branches, including Azadi Factory and Hi-Wi centers were considered. Because these companies are active within the innovation ecosystem, they are familiar with the literature in this field, which facilitated the completion of the questionnaires. Questionnaires were sent through the Press Line program and within social network groups, and for some through phone and email. All these companies had the approval of knowledge-based company level 1 to 3 and the completers had educational qualifications of at least bachelor's degree to doctorate. After examining the opinions of the experts, it was determined that a consensus was reached by having an average above 4 for all indicators. In adaptive neural fuzzy inference, the network separation method or lookup table (PG) was used in MATLAB 2023 software. In this method, the number of membership functions is 5 functions representing very low, low, medium, high and very high. Research findings A number of 290 articles were selected among the whole, which had the citation higher than 1. The texts of these 290 articles were studied, and finally 149 articles related to the selected topic and the literature and background of this research were used. In fact, the general goal and main question of this research was to model the innovation process centered on artificial intelligence, was carried out successfully with a very low model error during the test. As a result of reviewing these 149 articles and specialized texts, 189 indicators related to the issue of digital innovation were extracted. As the next goal, 42 main and effective indicators were obtained from this literature Conclusion In addition to the main goal and special goals of the research that were achieved through the presentation of the model, by examining the relationships obtained according to the surface diagrams, the sensitivity and impact of each component can be determined. "Variables" in the output, i.e. the degree of digitalization of the innovation process were analyzed. According to the findings and comparing them with the background and findings of previous researches, it can be stated that the sensitivity rate and impact of input 1, that is, the benefit of digital technologies based on artificial intelligence, is more than the other 4 inputs on the digital level of innovation process, in the sense that having these technologies is the main axis. It is less effective to benefit from the output; and if it is not present in the laboratory, from other components. The lowest sensitivity and impact on the output in the model belonging to the third and fourth components, i.e. network and smart learning, were identified next to the component of benefiting from technologies, and this could mean that in the conditions of benefiting from digital technologies, according to the findings of the research, it is suggested to design the intelligent model of innovation in different industries and for each industry separately for future research. In the literature, researchers encountered a wide range of these digital innovation models such as banking, schools and institutions of higher education, health, etc. The second suggestion is that future researches can design a separate model for each of the input components so that the input component of this research is placed in the output position and the indicators determined in this research are used as their input. It is possible to design 5 other models according to the five components of this research, and connecting these models to develop a final and macro model can bring new achievements.

Abstract Substance Use Disorder (SUD) is a medical condition where an individual compulsively misuses drugs or alcohol despite knowing the negative consequences. The anterior cingulate cortex (ACC) has been implicated in various types of SUDs, including nicotine, heroin, and alcohol use disorders. Our research aimed to investigate the effects of deep brain stimulation (DBS) in the ACC as a potential therapeutic approach for morphine use disorder. Additionally, we measured c-Fos protein expression as an indicator of neural activity in the nucleus accumbens (NAc) and prefrontal cortex (PFC). Our findings indicate that high-frequency (130 Hz) DBS at different amperages, 150 µA and 200 µA in the ACC during the acquisition phase of morphine conditioned place preference (CPP) inhibited the rewarding properties of morphine. Furthermore, DBS at these intensities during the extinction phase facilitated the extinction and mitigated the reinstatement of morphine CPP triggered by drug priming. Morphine conditioning was associated with impaired novel object conditioning (NOR) and locomotor activity. While DBS in the acquisition and extinction phases at both intensities restored NOR memory, only DBS at 200 µA recovered locomotor activity in the open field test. Treatment with DBS at 200 µA decreased c-Fos protein expression in the NAc and PFC (compared to morphine-only group). In conclusion, our data indicate an intensity-dependent effect of ACC DBS on the acquisition, extinction, and reinstatement of morphine-induced CPP in rats. These findings suggest that ACC DBS could be a potential intervention for the treatment of morphine use disorder.

Purpose: This study aims to identify and prioritize the services provided by public libraries during disasters, focusing on their roles before, during, and after such events.Methodology: The research, applied in purpose and descriptive-survey in method, utilized the fuzzy Delphi technique and the Best Worst Method (BWM) to analyze the opinions of 62 public library librarians and 11 library science experts in Iran.Findings: The resulting model outlines 33 services categorized into pre-disaster (14 services), during-disaster (12 services), and post-disaster (7 services). Services during disasters were deemed the most critical, followed by pre-disaster and post-disaster services. Key services include implementing mobile health ambassador libraries, forming voluntary campaigns among librarians, and establishing specialized groups to assess immediate library needs.Conclusion: Public libraries hold a vital role in disaster response and recovery due to their mission of equal access and community support. This study proposes a localized, actionable model of library services to enhance disaster management in Iran.Value: By addressing the unique needs of communities during crises, public libraries can significantly contribute to disaster preparedness and recovery, reinforcing their role as safe havens and resource hubs.

Abstract Background Recent articles have explored the effect of worms on cancer cells. This review focused on various cell cultures employed to understand which cells are more commonly and less utilized. Methods The present review analyzed studies published between 2013 and 2023 to obtain information about different cell cultures used in cancer studies involving helminths. Databases such as PubMed, Google Scholar, HINARI, and the Cochrane Library were searched. Results This search yielded 130 records, but 97 papers were excluded because they were either irrelevant to the research topic (n = 72) or contradicted the research idea (n = 25).The remaining twenty-one articles focused on different types of worms, such as Echinococcus granulosus, Clonorchis sinensis, Opisthorchis felineus, Opisthorchis viverrini, Trichinella spiralis, Toxocara canis, and Heligmosomoides polygyrus. Conclusion Due to the presence of numerous antigens, parasites at different growth stages can impact various cells through unknown mechanisms. Given the high diversity of antigens and their effects, artificial intelligence can assist in predicting initial outcomes for future studies.

Abstract Prediction of the rapid intensification (RI) of tropical cyclones (TCs) is crucial for improving disaster preparedness against storm hazards. These events can cause extensive damage to coastal areas if occurring close to landfall. Available models struggle to provide accurate RI estimates due to the complexity of underlying physical mechanisms. This study provides new insights into the prediction of a subset of rapidly intensifying TCs influenced by prolonged ocean warming events known as marine heatwaves (MHWs). MHWs could provide sufficient energy to supercharge TCs. Preconditioning by MHW led to RI of recent destructive TCs, Otis (2023), Doksuri (2023), and Ian (2022), with economic losses exceeding $150 billion. Here, we analyze the TC best track and sea surface temperature data from 1981 to 2023 to identify hotspot regions for compound events, where MHWs and RI of tropical cyclones occur concurrently or in succession. Building upon this, we propose an ensemble machine learning model for RI forecasting based on storm and MHW characteristics. This approach is particularly valuable as RI forecast errors are typically largest in favorable environments, such as those created by MHWs. Our study offers insight into predicting MHW TCs, which have been shown to be stronger TCs with potentially higher destructive power. Here, we show that using MHW predictors instead of the conventional method of using sea surface temperature reduces the false alarm rate by 30%. Overall, our findings contribute to coastal hazard risk awareness amidst unprecedented climate warming causing more frequent MHWs.

Nanotechnology plays a pivotal role in food science, particularly in the nanoencapsulation of bioactive compounds, to enhance their stability, bioavailability, and therapeutic potential. This review aims to provide a comprehensive analysis of the encapsulation of bioactive compounds, emphasizing the characteristics, food applications, and implications for human health. This work offers a detailed comparison of polymers such as sodium alginate, gum Arabic, chitosan, cellulose, pectin, shellac, and xanthan gum, while also examining both conventional and emerging encapsulation techniques, including freeze-drying, spray-drying, extrusion, coacervation, and supercritical anti-solvent drying. The contribution of this review lies in highlighting the role of encapsulation in improving system stability, controlling release rates, maintaining bioactivity under extreme conditions, and reducing lipid oxidation. Furthermore, it explores recent technological advances aimed at optimizing encapsulation processes for targeted therapies and functional foods. The findings underline the significant potential of encapsulation not only in food supplements and functional foods but also in supportive medical treatments, showcasing its relevance to improving human health in various contexts.

Background: Vitamin D is a steroid hormone that protects against viral infections by influencing innate and adaptive immune responses. The effectiveness of vitamin D3 supplementation in COVID-19 is unknown. The study’s goal was to elucidate the relationship between blood vitamin D levels and COVID-19 clinical outcomes by examining the effect of a single high dose of vitamin D3 on the length of hospital stay in patients. Methods: The descriptive, retrospective study was performed from March to May 2021 at a referral center for patients with COVID-19, in Bam, Iran. A checklist consisting of demographic variables was used to gather data, and laboratory assessments of serum 25(OH) D were evaluated and documented. The connection between serum vitamin D and patient clinical outcomes was investigated after patients were given a single oral dose of 200,000 IU of vitamin D3. Results: 71 COVID-19 patients were treated. Radiological results did not change substantially amongst individuals with various levels of 25(OH)D. After a single dosage of vitamin D3, mean blood levels of xyvitamin D increased considerably and the need for intubation and SpO decreased, and as did the respiratory rate in patients requiring hospitalization due to COVID-19. Conclusion: A single administration of 200,000 IU of vitamin D3 significantly reduced the severity of COVID-19.

Summary: The mechanical properties and forces of the extracellular environment modulate alveolar epithelial cell behavior. To model cancer/fibrosis associated stiffening and dynamic stretch, a biomimetic device was developed that imitates the active forces in the alveolus, while allowing control over the interstitial matrix stiffness. Alveolar epithelial A549 cancer cells were cultured on the devices and their transcriptome was profiled with RNA sequencing. Pathway analysis showed soft materials upregulated the expression of proteoglycans associated with cancer. Consequently, liposomes were modified with peptides targeting heparan sulfate and chondroitin sulfates of the cell surface glycocalyx. Chondroitin sulfate A targeting improved uptake in cells seeded on stiff biomimetic devices, which is attributed to increased chondroitin sulfate proteoglycan localization on cell surfaces in comparison to cells grown on soft devices. These results demonstrate the critical role that mechanical stiffness and stretch play in the alveolus and the importance of including these properties in nanotherapeutic design.

Scientific and technological developments, especially in the field of information and communication technology, have caused significant changes in people's daily lives, and remote work has been promoted as a new approach in managing work and performing activities, especially in the conditions created by the Corona pandemic. This study examines the concept of remote work in a special framework that includes the Corona period and the fifth industrial revolution and emphasizes the need for comprehensive scientific attention and innovative methods. To solve these challenges, this research presents a comprehensive model by applying the soft systems methodology (SSM), which takes into account the perspectives and limitations of different stakeholders and aims to increase the implementation of remote work. Using systematic methods and qualitative data analysis, this study develops the model in a flexible and comprehensive way. In addition, it highlights the role of technology, organizational culture and management strategies in reducing social isolation and increasing telework efficiency. The findings emphasize the dynamic aspect of the remote work ecosystem and emphasize the importance of multifaceted solutions for organizational success in the era of the fifth industrial revolution.

The COVID-19 pandemic has created an unprecedented natural experiment in drug policy, treatment delivery, and harm reduction strategies by exposing wide variation in public health infrastructures and social safety nets around the world. Using qualitative data including ethnographic methods, questionnaires, and semi-structured interviews with people who use drugs (PWUD) and Delphi-method with experts from field sites spanning 13 different countries, this paper compares national responses to substance use during the first wave of the COVID-19 pandemic. Field data was collected by the Substance Use x COVID-19 (SU x COVID) Data Collaborative, an international network of social scientists, public health scientists, and community health practitioners convened to identify and contextualise health service delivery models and social protections that influence the health and wellbeing of PWUD during COVID-19. Findings suggest that countries with stronger social welfare systems pre-COVID introduced durable interventions targeting structural drivers of health. Countries with fragmented social service infrastructures implemented temporary initiatives for PWUD led by non-governmental organisations. The paper summarises the most successful early pandemic responses seen across countries and ends by calling for greater systemic investments in social protections for PWUD, diversion away from criminal-legal systems toward health interventions, and integrated harm reduction, treatment and recovery supports for PWUD.

Sjögrens disease is a complex autoimmune disease with twelve established susceptibility loci. This genome-wide association study (GWAS) identifies ten novel genome-wide significant (GWS) regions in Sjögrens cases of European ancestry: CD247, NAB1, PTTG1-MIR146A, PRDM1-ATG5, TNFAIP3, XKR6, MAPT-CRHR1, RPTOR-CHMP6-BAIAP6, TYK2, SYNGR1. Polygenic risk scores yield predictability (AUROC = 0.71) and relative risk of 12.08. Interrogation of bioinformatics databases refine the associations, define local regulatory networks of GWS SNPs from the 95% credible set, and expand the implicated gene list to >40. Many GWS SNPs are eQTLs for genes within topologically associated domains in immune cells and/or eQTLs in the main target tissue, salivary glands.

Global competition, dynamic markets, and rapidly shrinking innovation and technology cycles, all have imposed significant challenges on the financial, banking, and insurance industries and the need to data analysis for improving decision-making processes in these organizations has become increasingly important. In this regard, the data stored in the databases of these organizations are considered as valuable sources of information and knowledge needed for organizational decisions. In the present research, the researchers focus on the common customers of the bank and insurance industry. The purpose is to provide a methodology to predict the performance of new customers based on the behavior of previous customers. To this end, a hybrid model based on support vector machine and genetic algorithm is used. The support vector machine is responsible for modeling the relationship between customer performance and their identity information and the genetic algorithm is responsible for tuning and optimizing the parameters of the support vector machine. The results obtained from customer classification using the proposed model in this research led to customer classification with a high accuracy of 99%.

While decent work has emerged as the central theme of the psychology of work theory and a global concept and directive for promoting social, political, and economic justice, it has garnered increasing scientific and political attention in the past two decades. However, until now, no defined measurement scale for the pharmaceutical supply chain exists. The present study aims to design and validate key performance indicators (KPIs) for 'decent work' in the pharmaceutical industry supply chain of Iran, using the Decent Work Daffi Scale (2017) as a reliable framework with five sub-scales and 15 items, tested and validated. For the validation of the Decent Work Scale, a quantitative survey study was conducted among selected pharmaceutical industry experts with a sample size of 228 individuals in the year 2023. The current study adopted an exploratory factor analysis approach using SPSS software and a confirmatory factor analysis through AMOS version 24 software. In this context, the factor structure, convergent validity, discriminant validity, and Cronbach's alpha coefficients were examined. The results showed that the five-factor structure outperforms the one-factor model with evidence supporting the convergent, discriminant, and predictive validity of the five-factor scale. Thus, the measurement of decent work in the pharmaceutical industry of Iran comprises five sub-scales: occupational safety conditions, access to healthcare, adequate remuneration, Free time and rest, and alignment of organizational values with family and societal values. This scale can serve as a useful tool for industrial and organizational psychology research, as well as for studies on the sustainability of social supply chains.

Supply chain management (SCM) that is Lean, Agile, Resilient, and Green (LARG) are required for competitiveness in today's complex, high-demand market. SCM must consider LARG paradigms concurrently, a rarely investigated topic. This study provides a comprehensive review of publications that combine all four LARG principles in engineering, business, and management domains. According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach, two Scopus and Google Scholar databases were exhaustively examined. Thirty-two manuscripts were selected for a comprehensive review. The year of publication, document type, countries, authors, journals, keywords, and topics was analyzed from 2000 to 2023. Also, each paper's methodology, central topic, findings, limitations, and future recommendations were outlined. Consequently, the current systematic literature review (SLR) revealed that the proposed topic is in its infancy, with promising prospects. By emphasizing the findings of this study, managers and businesses can increase consumer satisfaction and reduce costs.

ObjectiveAccording to the studies conducted on New Technology-Based Firms (NTBFs), the biggest problem of these companies is their access to financial resources. Studies show that among the indirect intervention policies, credit guarantee schemes have been considered by governments for facilitating the financing of these enterprises due to the need for less budget and a higher leverage effect. The purpose of this article is to present the appropriate credit guarantee model for new technology-based Firms. MethodsIn this study, which used a combination of qualitative and quantitative methods, firstly, by reviewing the literature, credit guarantee models, key components, and main criteria for choosing the appropriate credit guarantee model were identified and validated by the opinion of an expert group. Finally, the most appropriate model was selected using the Multiple Criteria Decision-Making Model and Analytical Network Process (ANP). Also, to form the grounds for policy implications for credit guarantee programs in Iran, an in-depth study of credit guarantee programs in the country and a comparison of the constituent components of credit guarantee programs with the classified models for credit guarantee in the world was carried out. ResultsThe findings of this study indicate a lack of effective policy formulation and a deficiency in the precise and targeted selection of a local credit guarantee model for emerging technology-based firms in Iran. The central outcomes of this study revolve around the identification of credit guarantee models, the delineation of key components, and the establishment of criteria for choosing the most suitable credit guarantee model. Furthermore, the research entails the ranking of both these criteria and the various models under consideration. According to the insights gathered from experts in this domain, the research findings highlight the primary criteria for selecting a credit guarantee model. These criteria, ranked in order of significance include: facilitating the provision of credit services, assessing the consequences of the credit guarantee system, effective risk management, and governance of the credit guarantee system. This ranking reflects the experts' assessment of the most pivotal factors when evaluating credit guarantee programs. The criterion of facilitating the provision of credit services has the most weight (importance). Also, policy implications such as: "Government support policies regarding the development of guarantee tools", " creating a centralized and reliable credit risk database" and "Governance and functional changes in the country's credit guarantee institutions" were proposed to create a local credit guarantee system for NTBFs. ConclusionIn this research, utilizing the ANP methodology, the selection of an apt credit guarantee model for the nation aligns with the specific requirements of emerging technology-based firms, the prevailing economic and institutional landscape, and global best practices and successful models. This approach holds substantial promise for achieving significant success, not only in shaping effective policies but also in their successful implementation within the realm of financing for these companies. Reforming the institutional and functional structure of the country's credit guarantee institutions in the short term, as well as the formation of new credit guarantee institutions according to successful credit guarantee models in the world and their development in the long run can play a significant role in the financing of NTBFs.

The purpose of this research is to compile a model of digital marketing strategies in successful Iranian startups. According to its purpose, the research method is practical, and in terms of its implementation, it is mixed (qualitative-quantitative). The statistical population of the research in the qualitative part includes 13 academic and executive experts in the field of startups in the country, who were selected using the purposeful judgment method and the snowball method, and the statistical population in the quantitative part includes the marketing unit of active successful startups. There are 250 people in the country (5 companies) and marketing professors of 5 top universities in Tehran, and the statistical sample was 148 people, 180 distributed and 163 analytical questionnaires were selected using Morgan's table. A semi-structured interview and a researcher-made questionnaire taken from the qualitative section were used to collect information. In the qualitative part, the data theory method of the foundation was used, and the data obtained from the interviews were coded and analyzed in the three main stages of open coding, central coding, and selective coding, and in the quantitative part, the factor analysis of the indicators was done. The results of the qualitative part indicated that 241 primary codes, 46 central codes and 14 selective codes were identified and extracted. The results of the research showed that the causal conditions with 4 variables of network capability, use of artificial intelligence, marketing capability and customer knowledge have an effect on digital marketing strategies, and the results of confirmatory factor analysis showed that the fit indices of the model were confirmed. Extended Abstract Introduction With the growth of ECT technologies including artificial intelligence, GPS, Bluetooth, QR code and other mobile and Internet connected technologies, marketers can offer micro-experiences/activities/services at an ultra-local level and adjust their messaging to effectively target small consumer segments locally (Singh & Keating, 2018). In this regard, digital marketing activities including mobile marketing, search engine based marketing, institutional marketing, email marketing, social network based marketing, etc. have been proposed. (Dwivedi et al, 2020). On the other hand, social networks have also created new challenges and advantages. It is important for companies to act in the field of specialized social networks so that digital marketing is not used by inexperienced experts and companies are safe from adverse effects by paying special attention to aligning their organizational goals with digital marketing solutions (Aswani et al., 2019). Internet technology and the increase in the number of Internet startups have fundamentally affected the world economy. The Internet provides companies with the opportunity to offer their products and services internationally 24 hours a day (Kohler, 2016). Experience shows that in the future, all organizations must operate online in order to remain competitive. The cost of advertising and marketing products and services on the Internet is very low compared to advertising and distribution costs related to traditional methods. Small and medium businesses are an important part of the economy in all countries, but they are heavily influenced by rapid changes in the external environment, especially demographic and economic. These rapid changes affect the marketing department of these businesses to meet the needs and expectations of customers in order to maintain a competitive position in the market (Sedaghati & Seiedin, 2023). Based on this, the current research is looking for an answer to this question: How is the formulation of digital marketing strategies model in successful Iranian startups? Theoretical Framework Digital marketing The term digital marketing has been referred to as a subset of marketing management and advertising management since two decades ago (Kannan, 2017). Digital marketing includes the set of all tools and activities that are used to market products and services on a digital platform (web, mobile internet or other (digital) tools) (Vaziri Gohar & Abdolhosani, 2020).Digital marketing strategiesIn this changing world, there is an urgent need for a strategic vision and a clear strategy map to sustain business growth. As a result, organizations cannot implement digital marketing without a clear definition of the strategy.Create a good quality customer experience.In defining the digital marketing strategy, management should determine the transition plan to identify the ability of human resources to cope with the change. The company must help, accompany its employees during this transformation, and invest in their retention and competitive advantage (Erdmann & Ponzoa, 2021). Javid et al, (2023) investigated the quality of customer relationship management for the development of digital marketing strategies in Bank-e Shahr. The results of the research showed that the variables of infrastructure, organizational environment, customer orientation, human resources, communication management, service quality, management and planning, strategic management, marketing and performance are in a favorable condition in Bank-e Shahr. The use of up-to-date technologies and the implementation of a suitable organizational structure for managing relationships with customers were identified as reasons for this favorability. Hamdi et al, (2023) investigated the identification of dimensions and components of acceptance of customer relationship management social systems by professional users using Web 2.0 technology. The identified factors were extracted in the form of 40 indicators, 8 components and 3 dimensions. Components and indicators of dimensions and components of acceptance of customer relationship management social systems, including three dimensions; organizational, customer, and technological; which organizational dimension has three components (manpower, organizational culture, organizational structure), customer dimension includes three components (value creation, performance expectation, customer satisfaction), and technological has been identified as having two components (social networks, content production). Research methodology According to its purpose, the research method is applicable, and in terms of its implementation, it is mixed (qualitative-quantitative). The statistical population of the research in the qualitative part includes 13 academic and executive experts in the field of startups in the country, who were selected using the purposeful judgment method and the snowball method; and the statistical population in the quantitative part includes the marketing unit of active successful startups in the country (5 companies) and marketing professors of 5 top universities in Tehran; as many as 250 people, and the statistical sample was 148 people, 180 analytical questionnaires distributed and 163 were selected using Morgan's table. A semi-structured interview and a researcher-made questionnaire taken from the qualitative section were used to collect information. Research findings In the qualitative part, the data-based theory method was used, and the data obtained from the interviews were coded and analyzed in the three main stages of open coding, central coding, and selective coding; and in the quantitative part, factor analysis of the indicators was done. The results of the qualitative part indicated that 241 primary codes, 46 central codes and 14 selective codes were identified and extracted. The results of the research showed that causal conditions with 4 variables of network capability, use of artificial intelligence, marketing capability and customer knowledge have an effect on digital marketing strategies; and the results of confirmatory factor analysis showed that the fit indices of the model were confirmed. Conclusion The current research has been conducted with the aim of developing a model of digital marketing strategies in successful Iranian startups. The results of the present study are in agreement with the results of Javid et al, (2023), Saeidi & Hoseinzadeh Naer (2022), Gholipur (2022), Boban et al, (2020), Bozkut & Gligor (2021), Musavirad & Ahmadi (2022), Dehghan (2018). Malek Akhlagh et al, (2021) showed that electronic customer relationship management means the development of traditional customer relationship management with the help of Internet technologies and an attempt to improve and fill the communication gap in which companies' marketing performance helps through examining the created development. Digitalization blurs the boundaries between technology and management and facilitates new business models based on the concepts, methods and tools of the digital environment. According to the results obtained from the research, it is suggested: Strengthening business practices with the aim of increasing competitiveness based on artificial intelligence should be considered, which leads to a major transformation in business. By using artificial intelligence, startups are able to identify, consider and understand their target buyers, and understand which type of product may be most needed at a specific time. With the evolution of big data and technologies, startups will be able to estimate buyer activity and monitor data-driven companies in any catastrophic situation and will obtain significant results that will improve their marketing decisions. Based on marketing capabilities, startups can meet the needs of current and new customers both through the development of new products and through the development of features and applications of existing products in order to ensure stability and survival, and to avoid shocks caused by new waves of competition based on new technologies.

‎The notion of a (branchwise) commutative $BI$-algebra is presented, and some related properties are investigated. We show that the class of commutative $BH$-algebras is broader than the class of commutative $BI$-algebras. Moreover, we %show that prove every singular $BI$-algebra is a $BH$-algebra. Also, we define the commutative ideals in $BI$-algebras and characterize the commutative $BI$-algebras in terms of commutative ideals.

Background and aims: Shooting plays an important role among the acquired skills of soldiers and is considered one of the main criteria for measuring their capabilities. The aim of this study was to investigate the effect of training interventions on shooting performance in both military and sports fields. Methods: National and international databases from the beginning to April 2022 were searched. In addition, a manual search and a complete review of the sources of the articles were also performed. Results: After reviewing the entire text of the articles, 22 full-text articles were selected that investigated the effect of training interventions on shooting performance in both military and sports fields. The meta-analysis results showed that training interventions have a significant effect on shooting performance both in the military field (p=0.001) and in the sports field (p=0.001). Conclusion: In the current review study, it was found that training interventions have a significant effect on improving the performance of shooters in both military and sports fields. In addition, the results of this review study showed that all interventions can have a positive effect on improving the performance of shooters. Also, the results showed that both physical and mental training interventions are effective in improving shooting performance; Therefore, it is recommended to use them together to improve shooting performance in both military and sports fields.

Background: Appearance quality, which means the perception of each person about their body image and the level of satisfaction with this situation, is one of the important issues in the field of cosmetic surgery, and if it is not fulfilled, it leads to a complaint and a case is raised in the forensic medical commissions of the province. Objectives: This study was aimed to investigate the sociological improvement of appearance quality in cosmetic surgery victims in forensic medical commissions of Tehran province. Materials & Methods: In this cross-sectional study, 276 cosmetic surgery victims whom medical malpractice was confirmed twice in 2018 and 2019 by the Forensic Medical Commissions of Tehran Province were included. A researcher-made questionnaire generated from a qualitative study on 24 individuals was used to assess the appearance quality in terms of satisfaction with appearance and life. Results: The majority of participants were in the 28-37 years age group (43.1%). The mean score of satisfaction with appearance was 11.18±3.60, and the mean score of satisfaction with life was 17.41±6.68. In total, the mean appearance quality was 28.59±8.67. There was a significant relationship between appearance quality and cosmetic surgery complaints (P

The impact of three different pulse durations (100 fs, 1, and 10 ps) on the formation of laser hyperdoped black silicon with respect to surface morphology, sub‐bandgap absorptance, the sulfur concentration profile, and the effective minority carrier lifetime after Al2O3 surface passivation is investigated. The current flow behavior is compared through the hyperdoped layer by I–V measurements after hyperdoping with different pulse durations. For conditions that give the same absolute sub‐bandgap absorptance, an increase in pulse duration from 100 fs to 10 ps results in a shallower sulfur concentration profile. Findings are explained by an increasing ablation threshold from 0.19 J cm−2 for a pulse duration of 100 fs to 0.21 J cm−2 for 1 ps and 0.34 J cm−2 for 10 ps. The formation of an equally absorbing layer with a shallower doping profile results in a reduction in contact and/or sheet resistance. Despite the higher local sulfur concentration, the samples show no decrease in carrier lifetime measured by quasi‐steady‐state photoconductance decay on Al2O3 surface‐passivated samples. The investigation shows that longer pulses of up to 10 ps during laser hyperdoping of silicon result in advanced layer properties that promise to be beneficial in a potential device application.

Abstract Background Cats in Iran are definitive hosts for several zoonotic intestinal helminths, such as Toxocara cati, Dipylidium caninum, Toxascaris leonina, Physaloptera praeputialis and Diplopylidium nolleri. Objective This study aimed to determine the prevalence of intestinal helminth infection in free‐roaming cats in southeast Iran, a region with a high free‐roaming cat population. Methods From January 2018 to December 2021, 153 cadavers of free‐roaming cats from Southeast Iran were necropsied for intestinal helminth infections. The carcasses were dissected, and the digestive systems were removed. The esophagus, stomach, small intestine, caecum and colon were tightly ligated. All adult helminths were collected, preserved and identified. Results The prevalence of gastrointestinal helminth infections was 80.39% (123/153). Of the cats from Kerman, 73% (73/100) were infected with at least one helminth, including D. caninum 70% (70/100), T. leonina 8% (8/100) and P. praeputialis 17% (17/100). Concurrent infection with two helminth species was found in 16% (16/100) and of three species infections was found in 3% (3/100) of the cats. Of the cats from Zabol, 94.33% (50/53) were infected with at least one of the helminths, including D. caninum 69.81% (37/53), T. leonina 11.32% (6/53), P. praeputialis 37.73% (20/53) and T. cati 5.66% (3/53). Concurrent infection with two helminth species was found in 28.3% (15/53), and three species were found in 1.88% (1/53) of the cats. Helminth infections were more prevalent in older cats. There was no association between sex and infection rate. Conclusion Based on the very high prevalence of zoonotic intestinal helminth infections in free‐roaming cats in southeast Iran, the potential public health risk emphasizes the need for intersectoral collaboration, particularly the provision of health and hygiene education to high‐risk populations, such as pre‐school and school‐age children.

Background: Air pollution is one of the most important problems facing people all over the world today, especially in big cities. The ever-increasing population growth, as well as the increase in vehicles and the number of industrial factories in the city of Isfahan, have led to this city being considered one of the largest industrial cities in Iran. Therefore, this city is considered the second most polluted city in Iran after Tehran. The city of Isfahan faces the crisis of air pollution on many days of the year, which directly and indirectly affects all aspects of people's lives in this city. Among these impacts is the quality of rainwater in the area, which joins the surface and groundwater in the region and affects its quality. This cycle will continue and air pollution will affect the quality of drinking water, agriculture, respiratory diseases and, in a word, the health of the people in this region.Materials and methods: In this study, the effects of air pollution in Isfahan on the quality of rainwater in the 10th district of Isfahan city were investigated. The quality of rainwater was studied based on the World Health Organization standard for drinking water, APHA standard for running water, Chinese standard for agricultural use, and Iranian standard for drinking water and agricultural use. To evaluate the air quality of the region, the statistics of the Isfahan Meteorological Organization station were used and the meteorological parameters were analyzed based on the American Environmental Protection Agency standards. Results: The results showed that the EC value of rainwater is more sensitive than pH to determine the suitability of rainwater quality for drinking uses, so when considering pH, many samples have favorable quality, but when considering EC value of the same sample, the quality of rainwater is unfavorable. The results of air quality monitoring based on the amount of PM2.5 on rainy days showed that 5 days were clean, 13 days were acceptable, and 6 days were unsanitary for sensitive groups. Conclusion: Isfahan urban runoff needs to be treated for drinking but it is suitable for agriculture. The results showed that the EC of rainwater is more dependent than pH to the rainfall depth. The results show that rainfall with a relatively small depth caused a significant increase in EC of stormwater. This decrease in the amount of precipitation has led to an increase in the amount of CO and PM2.5 in the atmosphere. The amount of rainfall did not affect the pH of rainwater, while with the increase of rainfall depth, the EC of rainwater has decreased significantly. In general, rainfall depth has a significant effect on EC concentration of rainwater. The results showed that in all the rainy days, the amount of CO, SO2 and O3 pollutants are in a clean state.

IntroductionWheat (Triticum aestivum L.) is one of the most important grains used in the world and its production is reduced in different regions due to drought stress. the plant antioxidant system can scavenge the reactive oxygen species (ROS) produced under drought. Induction of mutation using gamma ray is one of the common methods for genetic modification and identification of tolerant and resistant mutants. Mutant T65-58-8 is one of these drought tolerant genotypes that has been obtained by irradiation to Tabasi wheat genotype. The wheat plant needs irrigation during the flowering stage and drought stress is very important in this stage. In this study, in the flowering stage, the enzymes superoxide dismutase (SOD), catalase (CAT), glutathione reductase (GR) and glutathione peroxidase (GPX) involved in the mechanisms of tolerance to oxidative damage of ROS in the flag leaf were studied and the expression of the genes related to these enzymes was investigated using RNAseq. method.Materials and methodsDrought stress was applied based on field capacity (FC). The experiment was performed as a factorial experiment in a completely randomized design with three replications. Factors studied in this experiment include genotype at two levels (Tabasi parent and Mutant T65-58-8) and drought stress at 5 levels (100% FC or control, 75%, 22%, re-sampling from control pots at 18% FC and sampling after re-irrigation to the pot when had 90% FC). Wheat growth stages can be studied by Zadoks index. SOD activity was measured by Minami and Yoshikawa method, CAT activity by Aebi method, GR activity by Foyer and Halliwell method and GPX activity by Hopkins and Tudhope method. RNA sequencing was performed using Illumina NovaSeq 6000. Gene expression was obtained based on sequencing data by Bowtie2, Tophat2, HTseq-count and Featurecount softwares. After normalization by generating FPKM, Log2FC gene expression was calculated.Results and discussionExamination of superoxide dismutase (SOD), catalase (CAT), glutathione reductase (GR) and glutathione peroxidase (GPX) indices showed a significant difference (p