A survey on critical factors influencing organizational commitment

Organizational commitment is an important issue and organization attitude has become an area of study among many researchers in the fields of organizational behavior. In fact, there are many studies on human resource management where the effects of organizational commitment on other issues have been investigated and the purpose of this research is to find critical factors influencing on organizational commitment. Based on an exploration of the literature review and interviews, the proposed study of this paper extracts 24 variables and using factor analysis, we select the most important factors, which are grouped in four categories. The implementation of our factor analysis has revealed Affective commitment, Continuous commitment, Moral commitment and Enduring commitment are the most important factors influencing organizational commitment

BMI1 and TWIST1 Downregulated mRNA Expression in Basal Cell Carcinoma

Background: BMI1, TWIST1 and SNAI2/SLUG have been implicated in aggressive behavior of squamous cell carcinoma (SCC) and melanoma and BMI1 expression could identify subtypes of Merkel cell carcinoma (MCC). However, BMI1, TWIST1 and SNAI2 expression levels in basal cell carcinomas (BCCs) have not been elucidated. We hypothesized BCC could be a good model system to decipher mechanisms which inhibit processes that drive tumor metastasis. The aim of this study was to examine the mRNA expression level of BMI1, TWIST1, and SNAI2 in BCCs. Materials and Methods: Thirty-five fresh non-metastatic BCC tissue samples and seven fresh normal skin tissue samples were evaluated by real-time RT-PCR. Results: BMI1 and TWIST1 demonstrated marked down-regulation (p< 0.00l, p= 0.00l respectively), but SNAI2 showed no significant change (p=0.12). Conclusions: Previous literature has clearly demonstrated a positive association between BMI1 and TWIST1 expression and metastatic BCC, aggressive SCC and melanoma. Here, we demonstrated a negative association between BMI1 and TWIST1 mRNA expression level and BCC

Quantification of Multi-Parametric Magnetic Resonance Imaging Based on Radiomics Analysis for Differentiation of Benign and Malignant Lesions of Prostate

Background: The most common cancer (non-cutaneous) malignancy among men is prostate cancer. Management of prostate cancer, including staging and treatment, playing an important role in decreasing mortality rates. Among all current diagnostic tools, multiparametric MRI (mp-MRI) has shown high potential in localizing and staging prostate cancer. Quantification of mp-MRI helps to decrease the dependency of diagnosis on readers’ opinions. Objective: The aim of this research is to set a method based on quantification of mp-MRI images for discrimination between benign and malignant prostatic lesions with fusion-guided MR imaging/transrectal ultrasonography biopsy as a pathology validation reference. Material and Methods: It is an analytical research that 27 patients underwent the mp-MRI examination, including T1- and T2- weighted and diffusion weighted imaging (DWI). Quantification was done by calculating radiomic features from mp-MRI images. Receiver-operating-characteristic curve was done for each feature to evaluate the discriminatory capacity and linear discriminant analysis (LDA) and leave-one-out cross-validation for feature filtering to estimate the sensitivity, specificity and accuracy of the benign and malignant lesion differentiation process is used. Results: An accuracy, sensitivity and specificity of 92.6%, 95.2% and 83.3%, respectively, were achieved from a subset of radiomics features obtained from T2-weighted images and apparent diffusion coefficient (ADC) maps for distinguishing benign and malignant prostate lesions.  Conclusion: Quantification of mp-MRI (T2-weighted images and ADC-maps) based on radiomics feature has potential to distinguish benign with appropriate accuracy from malignant prostate lesions. This technique is helpful in preventing needless biopsies in patients and provides an assisted diagnosis for classifications of prostate lesions

Radiomic Analysis of Multi-parametric MR Images (MRI) for Classification of Parotid Tumors

Background: Characterization of parotid tumors before surgery using multi-parametric magnetic resonance imaging (MRI) scans can support clinical decision making about the best-suited therapeutic strategy for each patient. Objective: This study aims to differentiate benign from malignant parotid tumors through radiomics analysis of multi-parametric MR images, incorporating T2-w images with ADC-map and parametric maps generated from Dynamic Contrast Enhanced MRI (DCE-MRI).Material and Methods: MRI scans of 31 patients with histopathologically-confirmed parotid gland tumors (23 benign, 8 malignant) were included in this retrospective study. For DCE-MRI, semi-quantitative analysis, Tofts pharmacokinetic (PK) modeling, and five-parameter sigmoid modeling were performed and parametric maps were generated. For each patient, borders of the tumors were delineated on whole tumor slices of T2-w image, ADC-map, and the late-enhancement dynamic series of DCE-MRI, creating regions-of-interest (ROIs). Radiomic analysis was performed for the specified ROIs. Results: Among the DCE-MRI-derived parametric maps, wash-in rate (WIR) and PK-derived Ktrans parameters surpassed the accuracy of other parameters based on support vector machine (SVM) classifier. Radiomics analysis of ADC-map outperformed the T2-w and DCE-MRI techniques using the simpler classifier, suggestive of its inherently high sensitivity and specificity. Radiomics analysis of the combination of T2-w image, ADC-map, and DCE-MRI parametric maps resulted in accuracy of 100% with both classifiers with fewer numbers of selected texture features than individual images.  Conclusion: In conclusion, radiomics analysis is a reliable quantitative approach for discrimination of parotid tumors and can be employed as a computer-aided approach for pre-operative diagnosis and treatment planning of the patients

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

Investigation of rice quality milling in abrasive and blade whiteners in terms of breakage percentage and degree of milling

Reduction of rice losses is very important. In this study, appropriate moisture contents for milling of three common rice cultivars were determined in abrasive and blade whiteners. To this end, a factorial test based on a randomized complete block design with three replications was carried out in two milling systems: abrasive and blade whiteners, on three paddy cultivars: Sorkheh, Sazandegi, and Tarom and at four moisture contents: 8, 10, 12 and 14% (on wet basis). The paddy cultivars were dried and converted into white rice in abrasive and blade systems. In each treatment, the rice-breakage percentage, the DOM, the working capacity and the power consumption of each system were measured. The results showed that cultivar Sorkheh had the lowest rice-breakage rate. In addition, the mean breakage rate and DOM were significantly lower in the abrasive whitener than in the blade whitener. Based on results, most appropriate milling moisture contents for the cultivars Sorkheh, Sazandegi, and Tarom were 10, 12, and 10%, respectively, in the abrasive system, and 10, 12, and 12%, respectively, in the blade system. The working capacity and power consumption in the abrasive system were 1.7 and 3.43 times as much as those in the blade system, respectively

Synthesis and thermal shock evaluation of porous SiC ceramic foams for solar thermal applications

Reticulated porous ceramics with structural features spanning across multiple length scales are emerging as the primary media in a variety of demanding mass and heat transfer applications, most notably solar‐assisted synthetic fuel processing. In this study, we focus on engineering of the open pore silicon carbide (SiC)‐based foams in such catalytic applications. We evaluate the mechanical integrity and thermal stability of these porous structures. X‐ray tomography analyses of the 3D structures reveal the presence of dual pore size distribution different by up to an order of magnitude in length scale. We further study the effect of thermal shock—induced via water quenching—on the SiC structures and we conclude that the mechanical properties of the ceramic foams are significantly reduced after thermal stress. Comparison of SEM micrographs—before and after thermal shock—reveals that needle‐like features appear inside the foam matrix. These elongated defects may be responsible for structural and mechanical weakening