Social media platforms provide an easily accessible and time-saving communication approach for individuals with mental disorders compared to face-to-face meetings with medical providers. Recently, machine learning (ML)-based mental health exploration using large-scale social media data has attracted significant attention.We aimed to provide a bibliometric analysis and discussion on research trends of ML for mental health in social media.Publications addressing social media and ML in the field of mental health were retrieved from the Scopus and Web of Science databases. We analyzed the publication distribution to measure productivity on sources, countries, institutions, authors, and research subjects, and visualized the trends in this field using a keyword co-occurrence network. The research methodologies of previous studies with high citations are also thoroughly described.Lecture Notes in Computer Science and Journal of Medical Internet Research as the two most productive sources based on Scopus and Web of Science records. In addition, notable methodological approaches with data resources presented in high-ranking publications were investigated.We obtained a total of 565 relevant papers published from 2015 to 2020. In the last 5 years, the number of publications has demonstrated continuous growth with The results of this study highlight continuous growth in this research area. Moreover, we retrieved three main discussion points from a comprehensive overview of highly cited publications that provide new in-depth directions for both researchers and practitioners. Artificial intelligence (AI) has permeated various daily sectors that are directly related to our lives ,2. With Extensive efforts have been put forward to employ AI technologies in health care services in addressing issues related to physical health, involving several medical centers, researchers, and organizations, as well as for mental health as a rapidly growing social issues. Although mental health is a pervasive and comprehensive issue, its detection and exposure are challenging. The World Health Organization estimates that approximately 1 billion people worldwide have mental disorders . MoreoveConsidering this tendency, social media represents a supportive tool for these individuals , where uHiggins et al  define aa study that is composed of a search for scientific publications related to various topics in accordance with systematic guidelines including the search queries, the scientific databases, and the assessment criteria.With this concept, several prior mental health studies have investigated how to utilize ML in social media datasets. For instance, Seabrook et al  examinedIn addition to a systematic review approach, a scoping review may be performed, which is defined as “a type of research synthesis that aims to map the literature on a particular topic or research area and provide an opportunity to identify key concepts” . This imChancellor et al  also perAs presented in numerous prior studies, ML and mental health in social media have gained exponential attention in both practical and academic fields. Thus, we aimed to perform a bibliometric analysis to provide an overview and recent trends of this field.Bibliometric analysis is an extensive and widely used approach “to shed light on the processes of written communication and of the nature and course of development of a discipline” . A bibliSeveral scholars have performed bibliometric analyses on AI/ML in health care areas, including public and mental health, as well as in areas of specific mental illnesses. For example, dos Santos et al  performeIn the case of depression specifically, Tran et al  used a bWith respect to social media, several bibliometric analyses have closely evaluated relevant publications and their effects on society. As a representative example, Chen et al  adopted Based on this background, the use of ML in medical fields and social media has been extensively explored using bibliometric approaches with notable implications and future directions. Therefore, this is an appropriate time to provide more detailed observations on ML with respect to the relation of specific medical areas with social media. Specifically, we examined the trends of research using ML for mental health in social media by employing (1) a bibliometric analysis to determine the publication distributions on sources , authors, institutions, countries, research subjects, and author keywords; and (2) a trend review analysis to determine the distributions of citation numbers, along with a comprehensive review of highly cited publications.With these approaches, we aimed to identify overall research trends of this area in a quantitative manner, and to qualitatively identify the key methodologies used on diverse social media platforms. These findings can shed light on the recent trends in the field and highlight more detailed directions of future research areas.We collected papers from two citation databases, Scopus and WoS. Scopus is one of the largest citation repositories that covers scientific journals, conference proceedings, and books. WoS stores high-quality publications evaluated by three main indices: Science Citation Index Expanded (SCIE), Social Sciences Citation Index (SSCI), or Art & Humanities Citation Index (A&HCI).Relevant publications were obtained when the terms included in the search query appeared in the title, abstract, or keywords. We defined the search query of each topic based on prior research on ML, social media , and menA bibliometric analysis includes the distribution exploration of publication and research subject, as well as citation quantities. Both the Python programming language and Microsoft Excel were employed to perform statistical analyses of the retrieved papers. We first analyzed the publication distributions of papers with several categories . We also performed a network analysis of frequently used keywords. Moreover, to identify the research trends in this area, we performed trend review analyses with highly cited papers covering the following topics: (i) ML techniques, (ii) specific mental illnesses, and (iii) social media.The continuous growth of publications from 2016 to 2020 (until July 2020) is illustrated in Lecture Notes in Computer Science was the most productive publication source in Scopus, followed by CEUR Workshop Proceedings, Neural Computing and Applications, and Journal of Medical Internet Research with more than 20 publication counts each. Journal of Medical Internet Research was selected as the most productive publication source in WoS with 15 publication counts, followed by IEEE Access.We considered several document types, including not only journal articles but also conference proceedings and book chapters. More than 30 countries were identified as the predominant nations performing research in this field in Scopus (n=59) and WoS (n=39). There were 391 different institutions associated with the 565 publications. The top-ranked institutions are presented in The top 20 researchers contributing to the field are listed in The top 10 research subjects of each citation database are given in Along with research subjects, we investigated the keywords derived by the authors, which represent the main research topics of the publications . The keyNote that the keywords with a high frequency reflect the scope of the research area, which includes social media, ML, natural language processing, and mental health. In particular, in the case of mental health–related words, depression was the most frequently presented keyword, followed by suicide, consumer health information, social support, and stress detection. The main research methodologies of papers included natural language processing, sentiment analysis, classification, text mining, and stress detection in the ML field. Twitter and Reddit were identified as the most widely investigated social media platforms in this area.As there are several approaches of text analysis using natural language processing techniques in this field, we believe that future studies may provide hybrid approaches using both textual- and visual-based data collected from several types of social media data. In addition, validating ML models trained on mental health–related social media data in clinical settings needs to be further investigated.The annual number of citations is presented in We evaluated the overall academic output through bibliometric analysis. Due to the lack of observations in the content of the publications, as mentioned in previous studies ,27, we eAn overview and the research methodologies of the 10 highly cited publications are listed in In the case of Twitter, Budenz et al  analyzedTwitter tweets were also used to predict an association with psychological stressors, as one of the major causes of suicide. To prevent suicidal behaviors , the autr). The content analysis indicated significant differences in language expressions among social media platforms.In addition, stress level, as one of the pervasive causes of mental health conditions, was predicted on social media platforms, including Twitter and Facebook . LinguisShuai et al  collecteOne of the notable approaches in this area is a visual-oriented approach. Reece and Danforth  employedBased on the guidelines of De Choudhury et al , Reece aLin et al  collecteA mental illness is often accompanied by another mental illness as a so-called “comorbidity,” which refers to the simultaneous presence of one or more mental or physical disorders. From this viewpoint, Saha et al  developeP=.04) and severe anxiety  among those who had WSC with leave-one-out cross-validation procedures.Cheng et al  utilizedGkotsis et al  collecteEarly estimation of a person’s suicide risk is also an important issue in our society. In accordance with this point, Coppersmith et al  employedThis study involved a bibliometric analysis on the publications related to ML and mental health in social media from 2015 to 2020 with two citation databases, WoS and Scopus, as well as a trend review analysis. Although several prior studies have investigated mental illness, the majority of these studies employed both clinical and physical health care approaches. Along with these studies, social media is considered as one of the most important spaces for effectively and efficiently addressing individuals’ mental health issues . FurtherLecture Notes in Computer Science (Scopus) and Journal of Medical Internet Research (WoS) were the most productive publication sources in this field. Moreover, Harvard University and Georgia Institute of Technology in the United States, and Tsinghua University and the Chinese Academy of Sciences in China were listed as the most vigorous institutes. For individual researchers, Professor Munmun De Choudhury from Georgia Institute of Technology emerged as the most productive and well-known researcher in this field, with 15 publications to her credit. Regarding publications, using social media data in predicting depression was Prof De Choudhury’s first step in this area [Rapidly and consistently increasing publication and citation numbers indicate that there is growing attention and interest in this research area. Among several publication venues, his area , which aSubsequently, we conducted a trend analysis review on highly cited articles, and notable research trends were identified. The highly cited articles tended to employ user-generated content in diverse forms, including text, images, and other metadata, for specific mental disorders. Because no ground truth labels exist for users who have mental disorders, the majority of studies adopted a crowdsourcing survey with a medical-oriented approach and consideration of the participants’ agreements in using their social media accounts -32,34. MBased on the employed approaches with several highly cited articles, three main implications for discussion can be derived. First, the majority of the articles stated privacy and ethical issues as key considerations in using ML for specific mental illness in social media ,30,32,36Considering these discussion points, a few limitations of this study remain. Although we employed WoS and Scopus as our subjects, which are both widely used academic databases globally, there can be other medical-oriented databases that may provide more significant academic and practical information. Moreover, considering more recent and applicable statistical or natural language processing techniques (such as exploratory factor analysis  or topicWith the increase of AI applications in real-word health care settings , there h


PRNP mutation carriers. Similarly, in Alzheimer’s disease and other NDs, higher NfL concentrations seem to predict a faster disease progression. While increasing evidence indicates a potential clinical value of NfL in monitoring cerebrovascular disease, the association between NfL and prediction of outcome and/or disease activity in autoimmune encephalitis and infectious diseases has only been investigated in few cohorts and deserves confirmatory studies. In the era of precision medicine and evolving therapeutic options, CSF and blood NfL might aid the diagnostic and prognostic assessment of RPDs and the stratification and management of patients according to disease progression in clinical trials.Rapidly progressive dementia (RPD) is an umbrella term referring to several conditions causing a rapid neurological deterioration associated with cognitive decline and short disease duration. They comprise Creutzfeldt–Jakob disease (CJD), the archetypal RPD, rapidly progressive variants of the most common neurodegenerative dementias (NDs), and potentially treatable conditions such as infectious or autoimmune encephalitis and cerebrovascular disease. Given the significant clinical and, sometimes, neuroradiological overlap between these different disorders, biofluid markers also contribute significantly to the differential diagnosis. Among them, the neurofilament light chain protein (NfL) has attracted growing attention in recent years as a biofluid marker of neurodegeneration due to its sensitivity to axonal damage and the reliability of its measurement in both cerebrospinal fluid (CSF) and blood. Here, we summarize current knowledge regarding biological and clinical implications of NfL evaluation in biofluids across RPDs, emphasizing CJD, and other prion diseases. In the latter, NfL demonstrated a good diagnostic and prognostic accuracy and a potential value as a marker of proximity to clinical onset in pre-symptomatic  Rapidly progressive dementia (RPD) is an umbrella term that comprehends several heterogenous diseases characterized by a rapidly progressive cognitive decline and a short disease duration, typically 1–2 years between onset and occurrence of dementia and/or of 2–3 years from onset to death . EvidencSporadic Creutzfeldt–Jakob’s disease (CJD) represents the prototype of RPDs and is often referred to as the “great mimicker” given its wide phenotypic heterogeneity . The extThe assessment of neurofilament light chain protein (NfL) has attracted growing attention in recent years due to its sensitivity to neuronal damage and reliability of its measurement in both CSF and blood . NfL is In the present review, we summarize the current knowledge regarding the biological and clinical implications of CSF and blood NfL across the most prevalent etiologies of RPD.C), encoded by the prion protein (PRNP) gene, into a pathological isoform with abnormal conformation (PrPSc), which shows a tendency to aggregate and forms amyloid fibrils , fatal familial insomnia (FFI), and Gerstmann–Sträussler–Scheinker syndrome (GSS). Finally, a small proportion of cases (1–2%) is acquired (PRNP gene and the type (1 or 2) of PrPSc accumulating in the brain. The subtypes are named and classified according to these two main molecular variables into MM(V)1, MM2 cortical (MM2C), MM2 thalamic (MM2T), MV2 kuru (MV2K), VV1, and VV2 subtypes (Sporadic CJD (sCJD) represents the most common form of human prion disease and accounts for about 85–90% of cases. The second most common variant (10–15% of cases) is genetic prion disease, which is related to pathogenic mutations in acquired . In turnsubtypes .Sc accumulation and microglial activation in subcortical white matter in the former subtypes  . InteresMore recently, blood NfL levels were also found significantly higher in patients with prion disease belonging to all CJD forms and subtypes than both controls and other NDs . HoweverRegarding the diagnostic value of blood NfL, only three studies to date evaluated the marker in clinically and/or neuropathological heterogeneous cohorts of RPDs . They obex adiuvantibus therapy. In contrast, a significant increase of its levels in at least one biofluid should prompt a second more specific test such as the RT-QuIC.In conclusion, the very high negative predictive value of NfL for prion disease, due to its high sensitivity for neural damage, may justify its use as an early screening marker. Indeed, low or normal CSF and/or blood levels of NfL in a patient with RPD might exclude with very high certainty the diagnosis of prion disease and induce clinicians to consider other etiologies and to introduce an Different methods have been adopted to assess the rate of clinical progression in prion disease. The MRC Prion Disease Rating Scale, a validated scale of functional impairment, has been used to model linear slopes of functional decline as a measure of the rate of clinical progression . Despitein vivo PrPSc typing is currently unavailable, codon 129 genotyping allows partial patient stratification since early disease onset. In this regard, multivariate analyses adjusted for age and codon 129 genotype showed that CSF and blood NfL, CSF tau, and CSF 14-3-3 were still predictive of survival  therapy in a prion disease mouse model , where aNDs represent the most common etiology in non-prion RPD patients’ cohorts and a frequent source of CJD misdiagnosis . In thisThe differential diagnosis between CJD and rp-NDs is still challenging, given the partial overlap in clinical features and CSF levels of the surrogate protein markers 14-3-3 and total-tau . For thia priori identification of subjects with faster cognitive decline in AD and FTD cohorts to improve patient stratification for future clinical trials. In this regard, few studies showed an association between high CSF NfL levels and rapid cognitive decline in AD’s mild cognitive impairment stage (Another crucial open issue concerns the nt stage . Similarnt stage  and shornt stage , suggestAE represents an increasingly recognized common cause of RPD .Apart from the relevant diagnostic issue of the exclusion of prion disease , CSF andInterestingly, patients on active disease/progression, those on recovery and/or after disease treatment, and those with a stable clinical picture seem to show increased, decreased, or steady levels, respectively . Given tCSF NfL concentration also predicted long-term outcomes in patients with AE . HoweverOn a significant issue, all the studies mentioned above merged patients with several subtypes of AE, raising concerns about a possible selection bias that may have influenced the results discussed above.In RPDs secondary to infectious etiologies, CSF NfL has been reported to predict long-term neurocognitive status in herpes simplex encephalitis . In contInterestingly, NfL data have also been recently obtained in cerebrovascular disease forms that are occasionally associated with a rapid course, such as small vessel disease. Here, blood NfL concentrations have been associated with disability and neurological symptoms, including future cognitive impairment . MoreovePRNP mutation carriers, which are currently the best candidates for new therapeutic options. While in cerebrovascular disease, the evidence of an association between NfL, disease severity, and/or outcome is growing, the role of the marker in AE and infectious encephalitis is not well-clarified, given that current data sets include small cohorts of heterogeneous etiologies and/or insufficient data. In the era of precision medicine, the imminent application of biofluid markers in the routine flow chart may significantly improve the diagnostic and prognostic assessment of patients with RPD.Here, we have provided an overview of currently available CSF and blood NfL data on RPDs. Evidence suggests the potential value of NfL as a first-step diagnostic test in the assessment of RPD patients to quickly screen for the presence of ongoing neuronal damage before performing more specific and/or expensive investigations such as RT-QuIC and/or MRI. Moreover, NfL measurement in biofluids might be useful to track the disease trajectory in prion disease and other neurodegenerative dementias. In this regard, higher levels of CSF and/or blood protein seemed to predict a faster disease progression, higher grade of functional impairment, and/or shorter survival, which are all relevant variables for the stratification and management of patients in ongoing clinical trials. Furthermore, preliminary evidence suggests that blood NfL may have a role as a marker of proximity to clinical onset and, possibly, as the surrogate endpoint of response to ASOs in pre-symptomatic SA-R and PP assembled all the data and wrote the manuscript. Both authors contributed to the article and approved the submitted version.The reviewer PH declared a past co-authorship with one of the authors PP to the handling editor. The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Umoya omuhle (“good air”), conducted in two provinces of South Africa, that adopts an interdisciplinary, ‘whole systems’ approach to problem analysis and intervention development for reducing nosocomial transmission of Mycobacterium tuberculosis (Mtb) through improved IPC. We suggest that TB IPC represents a complex intervention that is delivered within a dynamic context shaped by policy guidelines, health facility space, infrastructure, organisation of care, and management culture. Methods drawn from epidemiology, anthropology, and health policy and systems research enable rich contextual analysis of how nosocomial Mtb transmission occurs, as well as opportunities to address the problem holistically. A ‘whole systems’ approach can identify leverage points within the health facility infrastructure and organisation of care that can inform the design of interventions to reduce the risk of nosocomial Mtb transmission.Infection prevention and control (IPC) measures to reduce transmission of drug-resistant and drug-sensitive tuberculosis (TB) in health facilities are well described but poorly implemented. The implementation of TB IPC has been assessed primarily through quantitative and structured approaches that treat administrative, environmental, and personal protective measures as discrete entities. We present an on-going project entitled  Two recent opinion pieces in leading public health journals underline the importance of holistic, multisectoral, and person-centred approaches to address challenges raised by antimicrobial resistance (AMR) , 2. HoweMycobacterium tuberculosis  transmission [Mtb in health facilities, such as opening doors and windows, wearing protective respirators, and instituting cough triage, remain poorly implemented [TB remains one of the most critical issues facing global public health and health systems today: the disease is responsible for over one million deaths every year, with DR-TB accounting for 29% of AMR-related deaths . Health smission , due to smission . IPC mealemented –8; therehow long and where patients spend time in clinics, in turn affecting the risk of nosocomial transmission.Recommendations to improve health care worker (HCW) adherence to guidelines tend to focus on training and supportive resources, yet there is limited understanding of which elements work to enable sustained implementation. Little attention has been paid to the complex contextual features of clinics  that underpin HCW understanding and implementation of TB IPC measures. This includes, for example, national and provincial policies governing the delivery of TB services ; the architectural design and routine maintenance of health facilities (are infection control measures included?); occupational health and safety (are measures in place to protect HCWs from and compensate them for work-related infections?), and cross-cutting quality improvement efforts (is IPC part of routine audits and accreditation processes?). Equally critical are facility-based protocols and processes that shape the organisation of care, which affects Mtb transmission in the country [Mtb transmission is more or less likely to occur, impact on HCW and managerial practices in the implementation of TB IPC.These gaps in understanding the health systems context relevant to TB IPC are evident in South Africa: nosocomial transmission featured prominently in the 2005 outbreak of extensively drug-resistant (XDR) TB in a hospital HIV outpatient service in KwaZulu-Natal and is likely to remain a key driver of  country , 10. Sou country , yet num country , 12. Stuunderstand the people practising the behaviour’ and ‘understand the setting in which people are practising the behaviour’ [Rather than viewing TB IPC implementation as largely driven by individual agency and discrete tasks, we suggest that TB IPC represents a ‘complex intervention’ with multiple, interacting components that require tailoring to specific settings , for exahaviour’ .Understanding both human behaviour and the organisation of care within the TB IPC practice environment requires an approach that focuses on the clinic as a dynamic site of interaction between humans, microbes, and materials. On the one hand, clinics are microcosms, i.e., bounded areas that are governed by delineated spaces and timing, as well as codes of conduct. On the other hand, they are permeable units through which people and their ideas about risk, infection, and transmission, flow. Further, local clinic dynamics are influenced by broader changes in the health systems, funding, and policy environments.Umoya omuhle (“good air”) project, we adopt an interdisciplinary approach that 1) contextualises work processes and practices related to TB IPC at the clinic level within the structure and functioning of the whole system, and 2) analyses interactions across components. A whole systems approach addresses the dynamic interactions across macro-, meso-, and micro-levels of the health system (see Fig. In the Mtb transmission occurs, as well as opportunities to address the problem holistically. A community-based social contact survey will provide data on how much person contact time occurs in clinics versus other settings, and a clinic-based TB prevalence survey will provide data on increased rates of clinic visiting in people with undiagnosed TB. This data will be used to parameterise a mathematical model of Mtb transmission. Using this model, we will estimate how much DS- and DR-TB result from transmission in health facilities versus other sites in the community. At the same time, in-depth case studies of TB-IPC practices and processes in six health facilities are shedding light on systems components pertinent to IPC including infrastructure, space, management and organisation of care. Working through provincial and district gatekeepers, and with consent of health facility managers and staff, we spent a few days in each of these facilities conducting observations, informal conversations, formal interviews and group discussions as well as structured assessments of patient flow and ventilation. Data on clinic design and the flow of people and air through clinic spaces will be juxtaposed with health workers’ accounts of risk in the context of their work, to contrast perceived and actual ‘hot spots’ of transmission risk, thus elucidating the ‘know-do’ gaps that exist in implementation of TB-IPC practices. Further, examining IPC policy and guidelines and health workers’ and managers’ perceptions of how ‘gold standards’ translate at lower levels of the health system will elucidate reasons for observed discrepancies between policy and practice. We use a System Dynamics Modelling approach to integrate quantitative and qualitative data gained through visual maps of the dynamic relationships across contextual factors, actors, and processes influencing the implementation of TB-IPC measures. This granular analysis is helping us to identify possible leverage points within the system and inform the design of targeted, data-driven interventions to reduce nosocomial Mtb transmission [Methods drawn from epidemiology, anthropology, and health policy and systems research are enabling rich contextual analysis of how nosocomial smission .Mtb transmission, including estimates of cost-effectiveness. The approach has potential for improving current methods to assess TB IPC implementation at facility level, providing additional criteria against which ‘underperforming’ facilities can be evaluated. For example, hitherto neglected domains of organisational culture, leadership, and patient- and workflow and their interaction in the everyday life of clinics could be usefully integrated into more in-depth assessment of TB IPC.In turn, proposed interventions will be simulated and costed to provide decision-makers with better estimates of the impact of innovative systems approaches to IPC on A whole systems approach draws attention to both the human and the organisational dimensions of health care delivery. Elucidating the system and how it ‘works’ will improve our understanding of health managers and health workers’ motivations, fears, hopes, and capacity to adapt recommended TB-IPC measures to the real-life parameters of the clinics and policy environments they work in. In South Africa, emerging solutions targeting systemic change for improved IPC will need to be embedded within broader national initiatives to ‘re-engineer’ primary health care and improve healthcare facility performance. At the same time, our approach to the ‘problem’ of compromised IPC and identification of new strategies in the South African context holds promise for other initiatives intended to prevent nosocomial transmission of drug-resistant and other infections in a holistic and sustainable manner.


The Accreditation Board for Engineering and Technology (ABET) accredits the tertiary education programs in the areas of applied and natural science, computing, engineering, and engineering technology. ABET offers accreditation in the United States and other regions in the world that lack such entities such as Gulf Cooperative Counties (GCC). Though ABET accreditation is voluntary, graduates of the ABET-accredited programs are considered equivalent in knowledge, behaviors, and attitude with global standards. The process of ABET accreditation takes months or years depending upon the gap with readiness and resources. The objective of this study is to compile and prioritize the list of critical success factors (CSFs) to commit resources optimally for sustained academic quality assurance and ABET accreditation. The triangulation research designed has been employed. Firstly, the observation of the ABET accreditation process of multiple programs at King Khalid University (KKU) helped in identifying 11 CSFs in three categories namely Program design and execution, Quality culture and excellence, and Institutional infrastructure and support. Further, these CSFs have been explored in the literature in the area of ABET accreditation. Finally, the research employs a fuzzy analytical hierarchy process (Fuzzy AHP) and full consistency method (FUCOM) to rank the relative importance of these CSFs and their dimensions for sustained academic quality assurance and ABET accreditation. The incorporation of these CSFs will help institutions in the GCC and other regions to get their academic programs ABET-accredited in an optimal manner. Historically, engineering education has gone through the phases of evolution, regulation, and quality control through accreditation . AccrediABET focuses on outcome-based learning (OBL), a marked shift in engineering education from content-based learning (CBL) in the late 1990s and early 2000s , 5. In oThe ABET accreditation process is generally found to be cumbersome, resource draining and time consuming. Mostly previous studies in the area of ABET have focused on student learning outcome, course design, assessments and CQI in different disciplines of engineering. And some studies have also discussed the issues of program objectives, review from stakeholders, and teaching strategies and research. There are also studies that have surveyed the existing program curriculums and identified the lack of importance to the areas of professional skills development, and systems and sustainability education . The sucThe ABET Accreditation process has been very methodical and disciplined at King Khalid University (KKU). It has helped to benchmark different engineering and computing programs against the global standards and improve the shortcomings therein. The objective of this study is to compile the critical success factors (CSFs) essential to achieve and sustain the academic quality assurance and ABET accreditation in a systematic manner. Further, the research also attempts to identify relative importance of CSFs using fuzzy analytical hierarchy process (Fuzzy AHP) and full consistency method (FUCOM) with the help of decision makers. The study also serves the purpose of educating the faculty staff on the relevant critical issues and required modernization in instruction and assessment to make the graduates ready to face the real challenges of workplaces. The outcome of this research will help institutions to manage and commit their resources effectively to achieve and sustain academic quality assurance and ABET accreditation. The rest of the article is organized into following sections: background of ABET, critical success factors for academic quality assurance and ABET accreditation, Program design and execution, Quality culture and excellence, Institutional infrastructure and support, multi-criteria decision making models: Fuzzy AHP and FUCOM, application of Fuzzy AHP and FUCOM, and discussion and conclusions.Earlier in Europe there were mixed approaches in the engineering education such as formal education based on mathematics and science developed in France, apprenticeship-based system developed in England, and their hybrid system . SimilarABET had initially in 1930s simple guidelines for engineering programs evaluation and by 1990s basis changed to lengthy prescriptive criteria , 12. ThaABET has played significant role in ensuring the quality of engineering programs in the international arena. It had first signed the accord with Canadian Engineering Accreditation Board (CEAB) for mutual recognition agreement (MRA) in the year 1979 . Later sThis study follows the triangulation research design to afford a multiple lines of sight or actions on to the problem being studied . FirstlyWhat are the CSFs for the sustained academic quality assurance and ABET accreditation?What is the relative ranking of CSFs for sustained academic quality assurance and ABET accreditation?Following sub-sections mention different data sources used in this study.King Khalid University (KKU) is a public university in the Kingdom of Saudi Arabia, established in 1998 by the merger of two older universities. It has set its ambitious vision to be among top 200 global universities by 2030. As of 2019 KKU has nearly 50 colleges, 72,000 plus students and around 7,000 faculty and staff . Till daThe articles were searched on web of science database with the keyword “Accreditation Board for Engineering and Technology”. In order to keep sample manageable in the review process articles based on significance and recency meaning more than 10 citations or published in the year 2016 or later were selected. The full-length accessible articles were kept on augmented until 7/7/2020 and updated list contained 72 articles and thereof 70 articles were found to be relevant. All 70 articles provided appropriate evidences to support the identified CSFs as discussed in the corresponding sections.Three key people involved in the Quality and ABET Accreditation process at the senior position agreed to serve as decision makers (DMs) to share their expertise. All the DMs were heading the programs’ quality teams, Accreditation in general may be defined as “a process, based on professional judgment, for evaluating whether or not an educational institution or program meets specified standards of educational quality” . ABET thCritical success factors (CSFs) are defined as ‘‘the limited number of areas in which results, if they are satisfactory, will ensure successful competitive performance for the organization” . CSFs ap◦ Student management◦ Program vision, mission and objectives◦ Student learning management◦ Curriculum design◦ Continuous quality improvementProgram design and execution◦ Quality steering team and leader◦ Document orientation and knowledge sharing culture◦ Academic and research excellenceQuality culture and excellence◦ Top management support◦ Institutional quality compliance◦ State of the art facilitiesInstitutional infrastructure and supportThis area is most studied in the literature, as it represents the core of program offering and execution. There are five CSFs in this category as explained in the following paragraphs: Student management, Program vision, mission and objectives, Student learning management, Curriculum design, and Continuous quality improvement. These factors discuss the opportunities provided to the students in the program to gain knowledge, skills and attitudes necessary for the professional practice. The observance of these factors at the significant levels is mandatory to achieve ABET accreditation.Student management deals with devising rules and regulations of admission, progression and graduation and their efficient implementation. The most important aspect of admission is the quality criteria for prospective students and process of admission. Similarly, post-admission guidance such as advising, to effectively progress the program based on prerequisite structure and students’ interests and potentials, needs to be well evidenced. Criteria for lateral admissions such as transfer cases must also be specified clearly. Finally, students must also be well informed about the program graduation requirements. This information may also be provided in the form of rule book for the students as in the case of KKU. The sample literature doesn’t mention much of this factor, nonetheless it is first criterion in SSR. Moreover, important decisions with respect to students’ intake and intake quality, regulations for progression and graduation, advising culture and support, transferability rules, incorporation of work experience reflects the good starting point of the program. KKU has a well-structured decision making framework through committees at different levels such as department, college, deanships and vice-presidencies. There are no formal credits for experiential education (co-ops or internships) in engineering and computing programs at KKU but students may earn credit through different proficiency exams. This is somewhat consistent with results of the survey published in 2005, for 90 ABET-accredited civil engineering programs in USA, only 4 had the credit-based co-op requirements .Academic institutions are setup in line with the national planning agenda for the growth and development of the country. They nurture and supply the required manpower to the industry and society in order to take country forward in the global arena. Same concerns were addressed by the ABET in 1990s by changing the accreditation philosophy from counting of credit hours and detailed specification to assessment of achievement of educational objectives defined in tandem with faculty and industry partners . TherefoAs the education system has changed from the CBL to OBL. It has become imperative that Student learning management must be guided through SOs. It will ensure the necessary knowledge, skills and attitudes in the graduates to start professional practice. SOs may be defined as “observable and measurable manifestation of applied knowledge” . GeneralTen generic professional profiles or behaviours expected of engineers namely analyst, problem-solver, designer, researcher, communicator, collaborator, leader, self-grower, achiever, practitioner may also help in encapsulating SOs . It is uIn current educational environment of OBL, Curriculum design has become very systematic. It must incorporate the stipulated components from the program’s disciplines and their underlying mathematics and scientific knowledge. It must produce a study plan consisting of hierarchically structured courses with well-defined course learning outcomes showing correspondence with the SOs. Similarly, a curriculum map may be generated defining places for different learnings and associated activities . The opeCurriculum design is always faced with constraints of resources such as total credits, and rationed allocation of different knowledge domains and disciplines. And there is always pressure to incorporate newer disciplines in the study plan to meet the challenges of work places such as process safety in chemical engineering . TherefoAll efforts must be made to take the CLOs at the higher levels of Bloom’s taxonomy   through Continuous quality improvement (CQI), requires identification of important stakeholders and program constituencies. Their structured involvement through assessments, reviews and feedback must be sought to make program demand-oriented. Their input may be incorporated in decision making of significant elements of the program such as PEOs, KPIs, SOs, Curriculum, CLOs and program performance. CQI may only be achieved by periodic updates of these elements through direct (students’ performance) and indirect (stakeholders’ feedback) assessments. For instance, at the Department of Engineering Technology, Texas Tech University, 12 different methods of assessments are used in program assessment portfolio: “alumni survey, capstone project report, employer surveys, fundamental review exam, graduate questionnaire, internship report, competitions performance, focus group exit interview, organization participation, seminar attendance, computer skills self-evaluation, pre/post course assessment” . SimilarOne study mentions the details of department of civil and environmental engineering in Seattle University . There aThese factors are not much discussed in the literature but play a very important role in sustaining the quality assurance efforts and ABET accreditation. Attaining these factors may pave the road to academic excellence and leadership. There are three factors in this category: Quality steering team and leader, Document orientation and knowledge sharing culture, and Academic and research excellence. Permanent quality structures, information sharing, innovative pedagogies and research orientation will create a very efficient environment to motivate students for effective learning.Every program must have a quality steering team responsible for ensuring the sustainable quality adoption as witnessed in the literature . ConstitThe motivation and objectives for documentation should be to facilitate sufficient common understanding among different stakeholders and agencies. Documentation, otherwise can easily exceed the limits and inundate the organization, as pointed in previous reports . One stuThe traditional lecture-based approach leads to problems of knowledge islands and their integrated relevance to the profession. Academic excellence is the most fundamental aspect of the program. It requires efficient synergies between program design and delivery in order to meet OBL. There are numerous effective learning strategies that have originated in behavioural, cognitive and social psychologies, and education and learning sciences. In the context of engineering and computing, literature mentions following approaches active learning , cooperaSimilarly, cooperative and collaborative learning facilitates team-based learning  essentiaMini-projects may also provide advantage of breadth, uniformity and accuracy in its assessment over capstone project due to single faculty . And, foAlthough there is no research specific criterion for the ABET undergraduate degree programs . Still, The high level of institutional maturity will be very conducive for establishing high standards of quality. There are three CFSs in this category: Top management support, Institutional quality compliance, and State of the art facilities. An institution poised for maintaining high quality standards will have positive outlook towards quality, organizational structure to promote quality and develop best resources for the success of the program.Adoption of innovation, quality and sustainability initiatives requires huge amount of efforts and resources. Endorsements and full-hearted support from top management becomes essential to accommodate required organizational changes and commitment of resources. At KKU highest authority President participates in the quality matters through the Vice Presidency for Development and Quality. This level of involvement is maintained by college dean and department head (program head) by appointing vice-dean quality and program quality coordinator. Similar evidences are available in the literature such as University of South Carolina, College of Engineering appointed Director of Assessment to maintain CQI process . This ViInstitutional quality compliance through setting up of a permanent executive division for quality will help in dealing with various agencies such as ABET or NCAAA. The responsibility of this division is to provide a quality related centralised assistance to all the programs offered by different colleges and departments. Northern Border University and King Abdulaziz University mention such unit to manage different ABET requirements , 32. At Facilities to carry out program related activities include classrooms, staffrooms, laboratories and library. These facilities must be well furnished and provided with sufficient equipment, efficient computing infrastructure and comprehensive study resources. Modern and updated facilities provide an excellent ambience to carry out instructional and scholarly activities. At KKU due to generous government funding and well-planned development of academic institutions facilities are up to the global standards. E-Learning facilities are managed under the E-Learning Deanship (ELD), established in the year 2005. ELD maintains a robust learning management system (LMS) that offers services for course material sharing, multiple interaction channels, assessments, virtual classroom, classroom capture, learning object repository to share internationally available learning objects. All the courses’ sections are registered each semester in the LMS system and instructors may blend any of the LMS services as suited. KKU has central library, managed under deanship of library affairs, containing hundreds of thousands of books covering all disciplines, digitally manged processes and perfect ambience for acquiring knowledge. Moreover, the Saudi Digital Library (SDL) available to all Saudi universities boast a collection of more than 310,000 e-books, largest in Arab world. SDL has also contracted with more than 300 global publishers such as Elsevier, Springer, Pearson Wiley, Taylor & Francis, Emeralds etc. to offer many other publications such as journals, conference proceedings etc. through its portal. Similarly, General Directorate of Information Technology maintains world class computing, networking and telecommunication resources, and a large collection of e-services in almost every sphere at KKU.n − 1) pair-wise comparisons for n criteria against n (n − 1)/2 comparisons in case of Fuzzy AHP. FUCOM also has built-in consistency and offers the flexibility of measurement scale. Both techniques have been explained in the subsequent sections and their applications is provided in the following section.The multi-criteria decision making (MCDM) methods help in solving complex problems with conflicting criteria. There are several methods in MCDM that may be applied based on the context of the problem. The analytical hierarchy process (AHP) is one of the subjective MCDM method that has been widely used in resource management problems. The modified Fuzzy AHP method incorporates vagueness in decision making. The Fuzzy AHP has been used due to several advantages such as ease of use, scalability, hierarchical structure adjustable to different size of problems and not data intensive . It has Fuzzy analytic hierarchy process (Fuzzy AHP) is a fuzzified form of AHP developed by Saaty (1980) . It is aZadeh (1965)  defined The five-steps Buckley’s Fuzzy AHP is adapted from , 92 as iStep 1: Establishing structure hierarchy for goal. Firstly, the goal of the Fuzzy AHP needs to clearly defined. Thereafter, domains and their factors are listed that contribute in achieving the goal. This requires theoretical base and opinions of the experts.Step 2: Comparing decision makers score. The linguistic definition to compare dimensions and CSFs is given in Step 3: Consistency in comparison matrix: Saaty (1980) [λmax can be calculated from (12) that is based on Theorem AW = λW [y (1980) , used a y (1980) , CI may y (1980)  and will AW = λW . Now, CI AW = λW .Step 4: Fuzzy geometric mean matrix is defined for attributes using (15). Thereafter Fuzzy weights of each attribute is calculated using (16).lwi, mwi, nwi define the lower, middle and upper value of fuzzy weight of wi.Step 5: De-fuzzy number for FTNs is calculated using center of area method by using (17) and normalized using (18).A relatively newer approach for multi-criteria decision making is full consistency model (FUCOM)  method tStep 1: Firstly, the set of criteria Step 2: Thereafter, the comparative priority Cj{k) rank in comparison to the criterion of the Cj{k+1) rank.Step 3: In this step the values of weights for the criteria is estimated that the ratio of weights is equal to the comparative priority such as follows:and also, weights should satisfy the mathematical transitivity such as follows:χ) should be minimized which leads to the following model to be solved.For the maximization of consistency, the DFC ) of criteria and sub-criteria is estimated. For instance, the comparative priorities (φk/(k+1)) for dimensions and first DM may be estimated as follows: φPDE/IIS = 1 andφIIS/QCE = 2.The same hierarchical structure defined previously in χ). Twelve such models are developed for all four set of variables such as dimensions and their CSFs, and three DMs.χ) are shown in Tables In the third step weights are estimated subject to the conditions mentioned in equations (21) and (22) such that the ratio of weights should be equal to comparative priority and weights should also satisfy the mathematical transitivity. This leads to the model given below for dimensions and first DM to be solved for maximization of consistency such that minimize DFC  methods with the help of expert opinions of decision makers have provided almost similar prioritization of dimensions and their CSFs for sustained academic quality assurance and ABET accreditation. The relative importance of the dimensions is Program design and execution (PDE) > Institutional infrastructure and support (IIS) > Quality culture and excellence (QCE) as the corresponding weights are 0.3900 > 0.3682 > 0.2418 for Fuzzy AHP, Similarly, the overall rankings of CSFs for both Fuzzy AHP and FUCOM have been shown in The sensitivity analysis was performed for both Fuzzy AHP and FUCOM methods by varying the weights of dimensions of CSFs by maintaining their order such that PDE > IIS > QCE. The results are shown in Figs Saudi Arabia, a GCC country, has planned to diversify its economy from hydrocarbons and set ambitious future goals such as Saudi Vision 2030. Educational institutions being the primary sources of manpower are also making significant progress and receive generous funding from the government. To bring in quality in professional education such as computing and engineering, the country has set up an organization NCAAA, that has MOU with ABET to develop a national accreditation system. Currently, MoE encourages institutions to get their programs ABET-accredited. ABET being one of the oldest accrediting agencies with a global presence and constantly addressing the future needs for the professional practice, is a de facto leader for setting quality standards in STEM education. ABET, having roots of almost a century, has witnessed the evolution of engineering discipline from practice orientation to design, scientific and mathematical based discipline. ABET in early 2000s has shifted its emphasis from content-based to outcome-based education. Further, ABET is increasingly making the accreditation process less prescriptive and more objective by focusing on PEOs, SOs, and CQI.This research has identified 11 CSFs for academic quality assurance and ABET accreditation through the observation with the ABET accreditation process of multiple programs at KKU, literature review and opinion of experts. These CSFs are categorized into Program design and execution, Quality culture and excellence, and Institutional infrastructure and support. Program design and execution consists of 5 CSFs namely: Student management, Program vision, mission and objectives, Student learning management, Curriculum design, and Continuous quality improvement. Student management deals with admission, transfer, advising, progression, internship credits, and graduation issues. PEOs the most fundamental accord to justify the program existence is handled under Program vision, mission and objects factor. Student learning management ensures the necessary knowledge, skills, and attitudes to be inculcated in the graduates to start professional practice and defined in SOs. SOs should reflect some of the following skills such as design, generic, professional, leadership, and system thinking. Curriculum design produces an OBL study plan consisting of hierarchically structured courses with well-defined CLOs having correspondence with the SOs. Some of the important considerations are backward design model; module-based, stand-alone and senior design approaches; structured and design guided experiences; live creative environments; extracurricular courses; ethics and entrepreneurship studies; and Bloom’s taxonomy. Continuous quality improvement requires assessment, review, and feedback on PEOs, KPIs, SOs, Curriculum, CLOs, and program performance from stakeholders and program constituencies in a closed-loop fashion.The second dimension, Quality culture and excellence, contains 3 CSFs such as Quality steering team and leader, Document orientation and knowledge sharing culture, and Academic and research excellence. These factors are important to sustain the academic quality assurance efforts and taking the program at the global excellence level. A permanent Quality steering team and leader having requisite traits and motivation, is essential to work consistently. The Document orientation and knowledge sharing culture warrants electronic, structured, and reviewed document repositories. Academic excellence entails efficient synergies between program design and delivery to meet OBL. Different learning strategies such as active learning, collaborative learning, service learning, skill, project, game, team and case-based learning among others must be utilized. Similarly approaches like 4H, CPR, value-sensitive design and mini-project may also be integrated. Funded research projects may also add resources to provide learning opportunities. The third dimension, Institutional infrastructure and support category illustrates three important factors Top management support, Institutional quality compliance, and State of the art facilities. The Top management support shows a positive outlook towards maintaining high-quality standards and commitment of needed resources. organizational structure to promote quality and develop the best resources for the success of the program. Constitution of organization or university level permanent executive division can ensure standardized or Institutional quality compliance across the programs. State of the art facilities are the most visible indicator of the success of an institution and helps to sustain the excellence in programs in multiple ways.Further, the decision makers participating in Fuzzy AHP and FUCOM, agreed with the significance of all of the CSFs. FUCOM is a recent method in subjective MCDM class that offers built-in consistency, reduced pair-wise comparisons and flexibility of measurement scale. The decision makers input in terms of pair-wise comparison of dimensions and CSFs helped in establishing their prioritization and rankings. The application of Fuzzy AHP and FUCOM has prioritized the dimensions of CSFs as Program design and execution, Institutional infrastructure and support and Quality culture and excellence in decreasing order. Similarly, the ranking of CSFs has allowed classifying CSFs into high, moderate, and low influence categories. Top management support, Curriculum design, Quality steering team and leader, and Continuous quality improvement are high influencing factors. And, Institutional quality compliance and Student learning management are categorized into moderate influencing factors. Whereas, State of the art facilities, Academic and research excellence, and Document orientation and sharing culture are grouped into comparatively low influence factors. Program vision, mission and objectives and Student management not considered in ranking have been identified to have lowest influence. This grouping doesn’t undermine the importance of any of the CSFs, rather signifies their associated resource requirements. As the Fuzzy AHP and FUCOM are based on the input of decision makers hence results may have a bias. Future research may statistically validate the results with a survey on multiple organizations. Similarly, systematic literature review may be conducted to expand the list of CSFs. Adoption of these CSFs will provide a systematic approach to sustain academic quality assurance and meet the requirements of ABET accreditation.S1 Appendix(DOCX)Click here for additional data file.


GWEP program goals include transformation of clinical training environments into integrated geriatrics and primary care systems to become Age-Friendly Health Systems. CATCH-ON, the collaborative GWEP led by Rush University Medical Center, is working with primary care health systems in four highly varied geographic and system settings to achieve this goal. Each of these clinic systems has unique successes and challenges in developing and implementing workflow protocols; engaging providers, patients, families, and community-based organizations in the development of Age-Friendly Health Communities; and modifying the electronic health record to document assessing and acting on 4Ms. Clinic team members participate in monthly Learning Community sessions to learn about and reinforce the 4Ms, along with practical recommendations for implementing with patients. This session will focus on CATCH-ON’s process for implementing the 4Ms in various practice settings, lessons learned in implementation across large and small health systems, and opportunities to bridge AFHS with the community.


As a result, the goal of this research was field trial of transgenic and conventional rice genotypes. The experiment was carried out in a randomized complete blocks design (RCBD) with four replications and seven genotypes in three isolated regions under the biosafety standard protocol in north of Iran in 2016. In this study, four transgenic lines with an active 2, number of filled spikelet per panicle, and filled spikelet percentage per panicle were obtained for transgenic lines. Khazar cultivar compared to the transgenic lines showed lower paddy yield. In all the three regions, transgenic lines had lower yield loss than their non-transgenic parent. The lowest number of white heads belonged to transgenic Tarom Molaii and transgenic lines. The most positive direct effect on paddy yield was related to the number of filled spikelet per panicle. Thus, this can be a good trait to achieve higher yield derived from reducing the negative indirect effect of dead heart and white heads.The findings demonstrated that in all three regions, transgenic lines derived from Khazar cultivar, were similar to their parent(s) in terms of growth phenology, agronomical traits, grain amylose content, gel consistency, and gelatinization temperature. In all the three regions, the highest number of panicle per mIt can be concluded that by producing transgenic rice, which is resistant to stem borer with an active promoter in the reproductive stage, farmers can reduce significant part of yield loss resulting from dead heart and white heads directly correlating with the number of filled spikelet per panicle and paddy yield. Oryza sativa L.) is the staple food of more than half of the world’s population and has an obvious effect on feeding, income, and job creation of people in the world, especially in Iran [Chilo suppressalis Walker) in Iran and also most regions in the world has been the chemical inputs [cry1Ab of the bacterium Bt. is the best method to give plants resistance against the invasion of pests and to reduce the environmental damage by chemical pesticides [Rice  per plant, number of grains per panicle, and 1000-grain weight. Yield is a complex quantitative trait; in addition to the three main components, there are also some other traits relevant to rice yield, such as plant height, plant architecture, biomass, and seed-setting rate , 24, 35.Srad_calc program was used. This program uses the sunshine hour data to calculate solar radiation. For counting day length, the PP_calc program was applied. Srad_calc and PP_calc programs can also be downloaded from “https://sites.google.com/site/CropModeling.”Experiments were done in isolated paddy fields in three sites, under the control of Iran Rice Research Institute between Alborz Mountains range and the Caspian Sea in Mazandaran and Guilan provinces in north of Iran Table  in 2016.2, KHT3, and KHT4 (driven from the backcross of Khazar cultivars with the transgenic line of Tarom Molaii) containing the gene cry1Ab from the bacterium Bt. (Bacillus thuringiensis) with the transgenic line of Tarom Molaii (containing the gene for resistance against striped stem borer as the non-restorer parent) along with the non-transgenic cultivars. Three non-transgenic rice cultivars were Tarom Hashemi, Nemat, and Khazar. In fact, in this experiment breeding and transgenic of cultivars were considered to use genetic potential of Tarom Molaii cultivar. Therefore, in backcross, 12.5% of Tarom Molaii background was maintained and in F2. In addition to transgenic selection, selection was made based on superior rice characteristics and morphological traits. The diagram of breeding scheme of backcross lines is shown in Fig. The experiment was carried out in a randomized complete blocks design (RCBD) with four replications. In this experiment, there were three transgenic rice lines including KHTThe isolation conditions were met according to biosafety principles (standard of biosafety protocol) consisting of cultivation with distance from other farmers’ paddy fields. This allowed for putting enough margin space around the field, harvesting the margin separately, and eliminating the plants’ residue after the harvesting. The experiment’s time and space distance were also considered adhering to biosafety principles.2, and planting density was 16 plants per square meter by 25 × 25 cm2 planting arrangement. Nitrogen, phosphorus, and potassium fertilizers were used in each region according to the suggestions of Iran Rice Research Institute and by considering the result of soil analysis  of International Rice Research Institute (IRRI).2 in the middle part of each plot based on 12% of moisture. From the relationship between paddy yield and biological yield, the harvest index was calculated and expressed in percentage.During the growing period, after the removal of marginal effect in each site, all agronomical traits  were randomly measured according to Standard Evaluation System (SES) of International Rice Research Institute (IRRI). Paddy yield, straw yield, and biological yield were measured by harvesting hills from 4 m−2 d−1. According to the difference in growing pattern and cultivars’ maturity, the thermal index of GDD was calculated for grain filling period from pollination to physiological maturity stages according to the formula below:The grain filling period was determined based on the time between pollination and physiological maturity (50% of the panicles turned yellowish green). The average of grain filling rate in the unit of area was obtained by dividing the paddy yield based on the length of grain filling period according to g mTmax + Tmin/Tb × 100GDD = Tmax is maximum daily temperature, Tmin is minimum daily temperature, and Tb is based temperature. The temperatures below 10 and above 30 °C were considered 10 and 30, respectively.Where In order to calculate leaf area index the during pollination stage, the maximum length and width for all leaves in ten hills per plant were measured in centimeters, and it was estimated by the formula LA = 0.75 × LW, where LA is leaf area, and L and W are the leaf’s length and width, respectively.Measuring baking qualitative traits, such as grain amylose content, gelatinization temperature, gel consistency, grain length, grain width, grain elongation, baked grain length, baked grain width, baked grain elongation, conversion efficiency, and healthy and broken grain percentage was done by Standard Evaluation System (SES) of International Rice Research Institute (IRRI).N), the number of fairly healthy panicle (N´), and the number of blank panicle (N´´) were measured. The number of healthy spikelet per panicle (P), the number of fairly healthy spikelet per panicle (P´), and total paddy yield (Y) were measured randomly by 16 plants per plot.For estimating yield loss, Islam and Karim’s  method wSorting of infected percentage of plants for determining sensitive and resistance lines was evaluated by Heinrichs  method. After normalization, data analyzed by the SAS statistical software and averages’ comparison were calculated by LSD tests in a 5% probability level. To determine those traits that had the most effect on yield, after applying regression to eliminate alignment, path analysis was performed by genotype correlation with the Path software.Findings of the compound analysis variance in Table 2, KHT3, and KHT4. In the three sites, the least growth period was obtained for local cultivars, including Tarom Hashemi and Tarom Molaii  and Tarom Molaii (3579 kg ha−1). In terms of straw yield and biological yield, cultivars had a high variation , whose percentage of infection was below 10%. KHT2 and KHT3 lines and Nemat cultivar got placed in group III (medium resistance), where dead heart was below 20%. Tarom Hashemi and Khazar cultivars stood in group V (low resistance), where dead heart was equal to 24% and 17%  and other factors (planting and harvesting dates). Yield components are affected by management practices, genotypes, and environment and are often used to justify the cause of yield reducing or increasing. Also, an ecosystem affects the ability of a plant to exhibit genetic potential. In addition, incorrect crop management, water usage, nutrition, temperature, light, and other inappropriate environmental factors can reduce one or more components of the yield components. Also, the number of spikelet per panicle depends on genetic ability of cultivars, climatic conditions at panicle formation, pollination, size, and activity of photosynthetic system at panicle formation period and photosynthetic material transferring capacity to panicle and competition between individual plants. One thousand-grain weight is a genetic trait and is less affected by environmental conditions. This trait depends on the size and duration of the activation of carbon dioxide fixation in plant shoots, photosynthetic material capacities loading to grain, duration of grain formation, weather conditions, mineral amount in grain filling period, and pests and diseases’ occurrence.In order to overcome the issue of low productive tillers, some researchers have proposed new plant type rice with low-tillering and large panicle size . Among rThe difference between paddy yield and biomass was due to environmental conditions (climate and soil) and pests and diseases variation in each region. In fact, the formation of vegetation that has a high performance depends on controlling components that interfere with plant growth and development. Achieving the highest yield in transgenic cultivars was the result of providing optimal growth conditions. Therefore, yield loss due to damage of stem borer in transgenic cultivars was much lower than non-transgenic cultivars. Paddy yield of Nemat and Khazar cultivars and transgenic lines derived from Khazar was higher than Tarom Hashemi and Tarom Molaii cultivars. Because Nemat and Khazar cultivars are dwarf and there is the small distance between source and sink the majority of photosynthetic materials are transferred to grain. The semi-dwarf characteristic of these cultivars reduces the competition between vegetative and reproductive organs for photosynthetic materials. Their paddy yield was higher in comparison with two tall cultivars Tarom Hashemi and Tarom Molaii. This is because in tall cultivars, distance between source and sink is high, and most energy and nutrition that plays a decisive role in the transfer of photosynthetic materials to grain is used for vegetative growth. Remobilization of photosynthetic materials in rice is such that in the pollination and heading stages, produced photosynthesis material is more than the need for these two processes. The excess of photosynthetic material is transferred to stem and stored as starch, and in grain filling stage, starch materials are converted to sugar and transferred to these grains. Therefore, because of the small distance between source and sink, semi-dwarf cultivars are more likely to transfer nutrition supply to grain and have more success compared to tall cultivars. By field trials of two fertilizer levels and 18 modern cultivars on the paddy yield of rice, Li et al.  revealedRice baking traits are mainly determined by the properties of starch, which comprises up to 90% of endosperm of white rice and consists of two amylose and amylopectin components. The high amylose rice is completely separated after drying and hardened after cooling. Most rice with lower amylose content has spikelet with a minimum amount of blank grain and number of broken grains . MeasureChilo agamemnon) under laboratory condition [In terms of white heads, transgenic lines derived from Khazar cultivar got placed in group 7 (relatively sensitive) which had white heads between 16–25%. Other cultivars stood in group 9 (sensitive); it means that the percentage of white heads of these cultivars was above 25%. By increasing the number of larvae in stem, their survival rate in the stem increases and yield decreases in the same way. Also, the reduction of tillers per hill increases the probability of stem damage. However, if there are several tillers, the tillers are not contaminated will produce the crop, and plants can recover from the damage caused by pests. By comparing three transgenic rice lines, Moghaieb [The correlation of traits can be due to genes’ connection or the existence of a genetic interaction with an environmental component. Ye et al.  also didPath coefficient analysis revealed that direct selection for number of fertile spikelet per panicle and harvest index would likely be effective for increasing grain yield . Direct According to combined variance analysis, there were significant differences among genotypes for all studied traits. According to results of mean comparison, the existence of minimum and maximum values for different traits in the same applied conditions for genotypes in each region indicates genetic variation. This means that by plant breeding, we can improve that trait. Therefore, this issue can provide a basis for determining the best cultivar according to the conditions of the region for cultivation. To determine the direct and indirect effects of the variables entered into the stepwise regression model, path analysis was used. The most positive direct effect on paddy yield was related to number of filled spikelet per panicle. The total direct and indirect effects of this trait on paddy yield (genetic correlation with paddy yield) were 93%. Regarding the direct effect of number of filled panicle per panicle on paddy yield and its indirect effect by day to 50% flowering and number of panicle per square meter, this trait can be a proper one for achieving higher yields, achieved by reducing the negative indirect effect of dead heart and white heads.


Fulminant myocarditis is primarily caused by infection with any number of a variety of viruses. It arises quickly, progresses rapidly, and may lead to severe heart failure or circulatory failure presenting as rapid-onset hypotension and cardiogenic shock, with mortality rates as high as 50%–70%. Most importantly, there are no treatment options, guidelines or an expert consensus statement. Here, we provide the first expert consensus, the Chinese Society of Cardiology Expert Consensus Statement on the Diagnosis and Treatment of Fulminant Myocarditis, based on data from our recent clinical trial (NCT03268642). In this statement, we describe the clinical features and diagnostic criteria of fulminant myocarditis, and importantly, for the first time, we describe a new treatment regimen termed life support-based comprehensive treatment regimen. The core content of this treatment regimen includes (i) mechanical life support  immunological modulation by using sufficient doses of glucocorticoid, immunoglobulin and (iii) antiviral reagents using neuraminidase inhibitor. The proper application of this treatment regimen may and has helped to save the lives of many patients with fulminant myocarditis.


The antimicrobial resistance challenge is compounded by inadequate attention to disease prevention and response, global circulation of people and products, differences in industry and market regulations across countries, and a fragile pipeline of new antibiotics and their alternatives. While the discovery of new antimicrobials will provide temporary solutions, sustainable success requires rigorous social science research that explores the drivers of antimicrobial resistance. These solutions should promote balance between equitable access to, conservation of, and innovation for antimicrobials, adapted to local conditions across the globe.,Effective actions against antimicrobial resistance will need to be informed by insights and evidence from the social sciences, encompassing a broad variety of disciplines. From our perspective, current engagement with the full range of social sciences is inadequate; greater collaboration within and between social science disciplines must be prioritized. Only then can we generate sufficient cross-sectional knowledge to overcome obstacles to addressing antimicrobial resistance, including inequitable access to effective antimicrobials, inadequate sanitation and hygiene infrastructure, disincentives for appropriate use of existing antimicrobials, and insufficient incentive for innovation in developing new antimicrobials.Global action plan on antimicrobial resistance in 2015, more than 120 countries developed national action plans. Despite this progress, challenges remain, such as how to scale-up access to antimicrobials without scaling-up resistance, identifying the clinical practices that can reduce antimicrobial use without risking lives, and how to de-link the price of antimicrobials from the cost of their development.–In the past 15 years, social science research has generated substantial knowledge about the systemic causes of antimicrobial resistance and has identified feasible interventions. After the World Health Assembly adopted the To encourage collaboration and to address this challenge, we have created the International Network for Antimicrobial Resistance Social Science (INAMRSS).As initial steps, INAMRSS strongly recommends several coordinated initiatives to better identify and implement valuable social science insights to support and inform much needed action against antimicrobial resistance. These initiatives include (i) tracking inputs and outputs of social science research, including mapping current research spending, research publications and identifying key gaps; (ii) including social scientists in antimicrobial resistance research teams, panels, and proposals; (iii) exploring social science interventions to address antimicrobial resistance at individual, population and systemic levels; (iv) identifying key requirements for infrastructure support and international coordination, such as the Independent Panel on Evidence for Action Against Antimicrobial Resistance and the Global AMR R&D Hub; and (v) using the data generated above to appropriately fund social science research. Only when we consider the multidisciplinary aspects of the challenge together, will we prevail in addressing antimicrobial resistance.