An integrated management systems approach to corporate sustainability

Purpose &ndash; This paper seeks to describe an integrated management systems (IMS) approach for the integration of corporate sustainability into business processes.Design/methodology/approach &ndash; An extensive review of published literature was conducted. Building on existing research, the paper presents an original framework for structuring the integration of corporate sustainability with existing business infrastructure. The framework is supported by a detailed set of diagnostic questions to help guide the process. Both the framework and the diagnostic questions are based on the &ldquo;Plan-Do-Check-Act&rdquo; cycle of continuous improvement.Findings &ndash; The paper highlights the need for a systematic means to integrate sustainability into business processes. Building on that point, the paper illustrates how an IMS approach can be used to structure the entire process of managing, measuring, and assessing progress towards corporate sustainability.Practical implications &ndash; The paper should be of interest to both practitioners and researchers. The framework and diagnostic questions will help guide decision makers through the process of building sustainability into their core business infrastructure. Since the framework and diagnostic questions provide the flexibility to accommodate specific organizational contexts, it is anticipated that they will have wide applicability.Originality/value &ndash; The paper makes several contributions. The framework provides a systematic approach to corporate sustainability that has not been elaborated on in previous publications. The unique set of diagnostic questions provides a means to evaluate the extent to which corporate sustainability has been integrated into an organization.<br /

Prevalence of NAFLD in Healthy and Young Male Individuals

Introduction. Nonalcoholic fatty liver disease (NAFLD) is an important cause of liver disease in adults and the most common cause of liver disease in children (Lavine and Schwimmer 2004). The abnormalities include increased liver fat without inflammation (steatosis) and nonalcoholic steatohepatitis (NASH). NASH may lead to fibrosis, cirrhosis, and ultimately liver failure if it is not treated (Matteoni et al. 1999). The objective of the study is to estimate the magnitude of the problem which will help us to formulate strategies in managing the potentially difficult problem. Materials and Methods. We included 1000 individuals between the ages of 30 and 50 years who came for annual checkup. The patients with other comorbidities like diabetes, ischemic heart disease, chronic liver disease, or renal diseases were excluded from the study. History of alcohol ingestion was also taken; any individual with history of alcohol intake was also excluded. All of them underwent investigations including CBC, LFTs, height and weight. The individuals who were found to have increased ALT (50 to 150 u/L) further underwent investigations including ultrasound of abdomen hepatitis b and c serology RA and ANA antibodies. All the individuals who were found to have viral or autoimmune illness were excluded from the study. The individuals having raised ALT levels and ultrasound evidence of fatty liver were taken. Results. 13.5% of the individuals were found to have NAFLD among those selected for the study. Conclusion. Mass campaign regarding physical and dietary measures needs to be undertaken in general masses regarding the gravity and potential prevention of the disease

Hybrid SPF and KD Operator-Based Active Contour Model for Image Segmentation

Image segmentation is a crucial stage of image analysis systems because it detects and extracts regions of interest for further processing, such as image recognition and the image description. However, segmenting images is not always easy because segmentation accuracy depends significantly on image characteristics, such as color, texture, and intensity. Image inhomogeneity profoundly degrades the segmentation performance of segmentation models. This article contributes to image segmentation literature by presenting a hybrid Active Contour Model (ACM) based on a Signed Pressure Force (SPF) function parameterized with a Kernel Difference (KD) operator. An SPF function includes information from both the local and global regions, making the proposed model independent of the initial contour position. The proposed model uses an optimal KD operator parameterized with weight coefficients to capture weak and blurred boundaries of inhomogeneous objects in images. Combined global and local image statistics were computed and added to the proposed energy function to increase the proposed model's sensitivity. The segmentation time complexity of the proposed model was calculated and compared with previous state-of-the-art active contour methods. The results demonstrated the significant superiority of the proposed model over other methods. Furthermore, a quantitative analysis was performed using the mini-MIAS database. Despite the presence of complex inhomogeneity, the proposed model demonstrated the highest segmentation accuracy when compared to other methods

The Karachi intracranial stenosis study (KISS) Protocol: an urban multicenter case-control investigation reporting the clinical, radiologic and biochemical associations of intracranial stenosis in Pakistan.

Background: Intracranial stenosis is the most common cause of stroke among Asians. It has a poor prognosis with a high rate of recurrence. No effective medical or surgical treatment modality has been developed for the treatment of stroke due to intracranial stenosis. We aim to identify risk factors and biomarkers for intracranial stenosis and to develop techniques such as use of transcranial doppler to help diagnose intracranial stenosis in a cost-effective manner. Methods/Design: The Karachi Intracranial Stenosis Study (KISS) is a prospective, observational, case-control study to describe the clinical features and determine the risk factors of patients with stroke due to intracranial stenosis and compare them to those with stroke due to other etiologies as well as to unaffected individuals. We plan to recruit 200 patients with stroke due to intracranial stenosis and two control groups each of 150 matched individuals. The first set of controls will include patients with ischemic stroke that is due to other atherosclerotic mechanisms specifically lacunar and cardioembolic strokes. The second group will consist of stroke free individuals. Standardized interviews will be conducted to determine demographic, medical, social, and behavioral variables along with baseline medications. Mandatory procedures for inclusion in the study are clinical confirmation of stroke by a healthcare professional within 72 hours of onset, 12 lead electrocardiogram, and neuroimaging. In addition, lipid profile, serum glucose, creatinine and HbA1C will be measured in all participants. Ancillary tests will include carotid ultrasound, transcranial doppler and magnetic resonance or computed tomography angiogram to rule out concurrent carotid disease. Echocardiogram and other additional investigations will be performed at these centers at the discretion of the regional physicians. Discussion: The results of this study will help inform locally relevant clinical guidelines and effective public health and individual interventions

Burnout among surgeons before and during the SARS-CoV-2 pandemic: an international survey

Background: SARS-CoV-2 pandemic has had many significant impacts within the surgical realm, and surgeons have been obligated to reconsider almost every aspect of daily clinical practice. Methods: This is a cross-sectional study reported in compliance with the CHERRIES guidelines and conducted through an online platform from June 14th to July 15th, 2020. The primary outcome was the burden of burnout during the pandemic indicated by the validated Shirom-Melamed Burnout Measure. Results: Nine hundred fifty-four surgeons completed the survey. The median length of practice was 10&nbsp;years; 78.2% included were male with a median age of 37&nbsp;years old, 39.5% were consultants, 68.9% were general surgeons, and 55.7% were affiliated with an academic institution. Overall, there was a significant increase in the mean burnout score during the pandemic; longer years of practice and older age were significantly associated with less burnout. There were significant reductions in the median number of outpatient visits, operated cases, on-call hours, emergency visits, and research work, so, 48.2% of respondents felt that the training resources were insufficient. The majority (81.3%) of respondents reported that their hospitals were included in the management of COVID-19, 66.5% felt their roles had been minimized; 41% were asked to assist in non-surgical medical practices, and 37.6% of respondents were included in COVID-19 management. Conclusions: There was a significant burnout among trainees. Almost all aspects of clinical and research activities were affected with a significant reduction in the volume of research, outpatient clinic visits, surgical procedures, on-call hours, and emergency cases hindering the training. Trial registration: The study was registered on clicaltrials.gov "NCT04433286" on 16/06/2020

Using geographically weighted logistic regression (GWLR) for pedestrian crash severity modeling: Exploring spatially varying relationships with natural and built environment factors

Although a large number of studies have tried to explore the relationship between built environment and pedestrian crash severity in developed countries, there is a lack of similar studies in the context of developing countries. Methodologically, the contributory factors influencing pedestrian crash severity are commonly identified through global logistic regression (GLR) models. However, these models are unable to capture the spatial variation in the relationships between the dependent and independent variables. The local logistic regression model, such as geographically weighted logistic regression (GWLR), can potentially overcome this issue. The application of local logistic regression to model pedestrian crash severity is absent in the literature. Therefore, this study aimed to apply the GWLR technique to explore spatially heterogeneous relationships between natural and built environment-related factors and pedestrian crash severity in Dhaka, the capital city of a developing country: Bangladesh. First, using secondary pedestrian crash data, a GLR model was developed to identify significant contributory factors influencing pedestrian crash severity. Results of the model showed that the probability of fatal pedestrian crash occurrence increased at night, in unlit locations, and during adverse weather conditions. In addition, the likelihood of a fatal crash decreases when medians exist on roads and around institutional land use. Also, the chance of fatal crashes increased on straight and flat roads and at locations with more bus stops. Finally, this study explored spatial variation in the effect intensity of these significant variables across the study area using the GWLR technique. High intensity variation across the study area was found for road geometry and institutional land use factors. On the other hand, low intensity variation was found for light conditions and the presence of median factors. This technique can be applied in any area, and the results would help provide insights into the spatial dimension of traffic safety

Curcuminoids

WOS: 000560757300012[No abstract available

Energy-efficient Harvested-Aware clustering and cooperative Routing Protocol for WBAN (E-HARP)

Wireless Body Area Network (WBAN) is an interconnection of small bio-sensor nodes that are deployed in/on different parts of human body. It is used to sense health-related data such as rate of heart beat, blood pressure, blood glucose level, Electro-cardiogram (ECG), Electro-myography (EMG) etc. of human body and pass these readings to real-time health monitoring systems. WBANs is an important research area and is used in different applications such as medical field, sports, entertainment, social welfare etc. Bio-Sensor Nodes (BSNs) or simply called as Sensor Nodes (SNs) are the main backbone of WBANs. SNs normally have very limited resources due to its smaller size. Therefore, minimum consumption of energy is an essential design requirement of WBAN schemes. In the proposed work, Energy-efficient Harvested-Aware clustering and cooperative Routing Protocol for WBAN (E-HARP) are presented. The presented protocol mainly proposes a novel multi-attribute-based technique for dynamic Cluster Head (CH) selection and cooperative routing. In the first phase of this two-phased technique, optimum CH is selected among the cluster members, based on calculated Cost Factor (CF). The parameters used for calculation of CF are; residual energy of SN, required transmission power, communication link Signal-to-Noise-Ratio (SNR) and total network energy loss. In order to distribute load on one CH, E-HARP selects new CH in each data transmission round. In the second phase of E-HARP, data is routed with cooperative effort of the SN, which saves the node energy by prohibiting the transmission of redundant data packets. To evaluate the performance of the proposed technique, comprehensive experimentations using NS-2 simulation tool has been conducted. The results are compared with some latest techniques named as EH-RCB, ELR-W, Co-LAEEBA, and EECBSR. The acquired results show a significant enhancement of E-HARP in terms of network stability, network life time, throughput, end-to-end delay and packet delivery ratio

Impacts of the COVID-19 Pandemic on Active Travel Mode Choice in Bangladesh: A Study from the Perspective of Sustainability and New Normal Situation

The COVID-19 pandemic has caused incredible impacts on people’s travel behavior. Recent studies suggest that while the demand for public transport has decreased due to passengers’ inability to maintain physical distance inside this mode, the demand for private automobile and active transport modes (walking and cycling) has increased during the pandemic. Policymakers should take this opportunity given by the pandemic and encourage people to use active transport more in the new normal situation to achieve sustainable transportation outcomes. This study explores the expected change in active transport mode usage in the new normal situation in Bangladesh based on the data from a questionnaire survey. The study finds that 56% and 45% of the respondents were expected to increase travel by walking and cycling, respectively, during the new normal situation. On the other hand, 19% of the respondents were expected to do the opposite. The study further identifies the factors influencing the expected change in travel by active transport modes during the new normal situation by developing multinomial logistic regression models. Finally, this study proposes policies to increase active transport use beyond the pandemic and ensure sustainable mobility for city dwellers and their well-being