Assessment of Corporate Social Responsibility (CSR) awareness and practices in manufacturing sector of Pakistan

Globalization and mass communication have significantly influenced the socio-economic growth of countries and organizations are under immense pressure to develop their businesses in a more socially responsible way. Consequently, Corporate Social Responsibility (CSR) has emerged as a business development concept. CSR acknowledgement is low in south Asian countries both at state and corporate levels. Pakistan, being a developing country, is no exception and the manufacturing sector, which is the third largest contributing sector to the economy, is facing the challenge of corporate social compliance. This study explores the awareness level amongst employees in the manufacturing sector and also evaluates the practices of CSR activities in these organizations. The study is mainly focused on the textile and automobile sectors and shows greater CSR awareness in the automobile sector than the textile sector; however, there are many organizations where the concept of CSR is unknown. The findings of this research will help organizations in enhancing understanding of CSR amongst employees and will also allow manufacturing industries to improve their implementation against identified weak areas. Increased levels of social compliance will ultimately help organizations in promoting their businesses in the global market

Utility of participatory rural appraisal for health needs assessment and planning.

BACKGROUND: While poverty and lack of life opportunities are root causes of a high burden of disease and infant and maternal mortality, inadequate health care contributes heavily. Often those who are left without care are those who need it most. Existing health services are managed without taking into account acceptance and need perspectives. This further reduces the effectiveness of and equity in health care. In order to guide the planning of reproductive health services by a national NGO, health needs were assessed in a district in Sindh using a combination of participatory rural appraisal (PRA) and qualitative and quantitative research methods. PRA is considered as a better framework to assess, analyse and develop programs with communities. OBJECTIVE: The objective of PRA was to initiate community involvement and to understand the needs of health care from a community perspective. METHODOLOGY: PRA was conducted with groups of men and women from three rural areas in a district of Sindh, Pakistan using a life cycle framework. The community members identified various stages of their life with the associated health issues. RESULTS: This research was empowering to community members as it facilitated community involvement. The respondents took charge of the process of identification of health needs at PRA sessions. PRA helped identify health problems considered prevalent and important by the community. More importantly, it helped potential service providers and the community to initiate community involvement in planning. CONCLUSION: PRA is not only an effective tool for assessment and analysis of health issues but also a vehicle to promote community involvement. Additionally, participatory methods contribute to understand the context of quantitative data generated for planning purposes

Establishment of an efficient callus induction and plant regeneration system in Pakistani wheat ( Triticum aestivum ) cultivars

Four commercially grown wheat varieties of Pakistan, namely Inqilab-91, Chakwal-97, Tatara and Manthar were used for this investigation. For callus induction different concentrations of 2,4-Dichlorophenoxyaceticacid (2,4-D) along with 0.1 mg/L of Kinetin were evaluated. For regeneration initially different concentrations of Indole-3-Acetic Acid (IAA) and 6-BenzylAminoPurine (BAP) were tested. Best hormone combinations were further subjected to Kinetin and 6-\u3b3-\u3b3-dimethylallylaminopurine (2iP). For Inqilab-91, Chakwal-97 and Manthar, 3 mg/L of 2,4-D was found optimum, which induced 83.25%, 77.75% and 95.20% of embryogenic calli, respectively. Maximum callus induction (97.18%) was observed in Tatara when 2 mg/L of 2,4-D was used. As regard to regeneration, Inqilab-91, Chakwal-97 and Manthar showed maximum regeneration on media containing 0.1 mg/L IAA, 0.4 mg/L Kinetin and 0.5 mg/L 2iP, regenerating 87.25%, 81.75% and 68.75% respectively. For Tatara maximum regeneration of 12.25% was obtained on 0.1 mg/L IAA and 2 mg/L of BAP. Presently optimized regeneration method holds promise for facilitating the deployment of agronomical important trait through genetic transformation for the improvement of this important food crop

Fuzzy logic based cluster head election led energy efficiency in history assisted cognitive radio networks

The performance and the network lifetime of cooperative spectrum sensing (CSS) infrastructure-based cognitive radio (CR) networks are hugely affected by the energy consumption of the power-constrained CR nodes during spectrum sensing, followed by data transmission and reception. To overcome this issue and improve the network lifetime, clustering mechanisms with several nodes inside a single cluster can be employed. It is usually the cluster head (CH) in every cluster that is responsible for aggregating the data collected from individual CR nodes before it is being forwarded to the base station (BS). In this article, an energy-efficient fuzzy logic-based clustering (EEFC) algorithm is proposed, which uses a novel set of fuzzy input parameters to elect the most suitable node as CH. Unlike most of the other probabilistic as well as fuzzy logic-based clustering algorithms, EEFC increments the fuzzy input parameters from three to four to obtain improved solutions employing the Mamdani method for fuzzification and the Centroid method for defuzzification. It ensures that the best candidate is selected for the CH role by obtaining the crisp value from the fuzzy logic rule-based system. While compared to other well-known clustering algorithms such as low-energy adaptive clustering hierarchy (LEACH), CH election using fuzzy logic (CHEF), energy-aware unequal clustering using fuzzy logic (EAUCF), and fuzzy logic-based energy-efficient clustering hierarchy (FLECH), our proposed EEFC algorithm demonstrates significantly enhanced network lifetime where the time taken for first node dead (FND) in the network is improved. Moreover, EEFC is implemented in the existing history-assisted energy efficient infrastructure CR network to analyze and demonstrate the overall augmented energy efficiency of the system

APPRAISAL OF CLIMATE CHANGE DISASTER AND FOOD SECURITY IN KHYBER PAKHTUNKHAW PAKISTAN USING GEOSPATIAL TECHNOLOGIES

Drought is one of the most severe natural disasters. It negatively influences the crop output considerably as water resources are inadequate across large geographic areas. Food insecurity, hunger, and poverty are widespread in three Pakistani provinces: Baluchistan, Khyber Pakhtunkhwa, and Sindh. Until March/April 2022, roughly 4.66 million people, or 25% of the population examined, were severely food insecure. Historically, the severity of a drought is evaluated using several different indicators, with the selection of indices depending on the data that is easily accessible. By multiple aspects, including potential evapotranspiration and rainfall data on a standard timescale and computing monthly, seasonal, or annual data, the Reconnaissance Drought Index (RDI) has a significant advantage over the other indices in determining drought severity. When rainfall in a region is significantly lower than the amount of potential evapotranspiration, drought situations can occur on the earth. Rainfall will often occur in locations with an increase in the relative humidity of the air. The reconnaissance drought index (RDI) for Khyber Pakhtaunkhawa province in Pakistan was calculated from 1981 to 2020 for 3-, 6-, and 12-month timeframes. This research employed rainfall, minimum and maximum temperature data from KPK province to describe drought using the DrinC program, the Man Kendall test, and Sen's slope calculator to determine drought patterns and variation. All regions had moderate, severe, and extreme droughts, with RDIs between -1.0 and -3.5. RDI 3-, 6-, and 12-month evaluations highlighted 1991, 1994, 2000, 2010, 2015, and 2017. These results indicate that productivity declines in dry and subsequent years due to seasonal rainfall and soil moisture retention.Wheat production averaged 1.7 tones ha-1 year-1, with significant variations. Between October and December, it is an essential to have favorable growing conditions to increase productivity. If droughts occur in this era, the yield will be substantially more negatively impacted than if they occur later in the growing cycle. The 3-month RDI values offer a more accurate description of this variation than the six-month and twelve-months RDI Values. Geospatial drought analysis indicates a considerable variance in drought patterns across the Kpk province over the last 4 decades. Because long-term droughts sometimes affect water quality, especially groundwater, a rise in the intensity of long-term droughts could pose a risk to the water management in the regions that have been examined. Analysis of the Landsat TM 30 m data took place. At the same time, Landsat imageries were utilized to generate the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) for drought evaluation. The findings of the NDWI indicate an increase in value from 0.58 to 0.7 for the KPK region

Rationale and protocol for estimating the economic value of a multicomponent quality improvement strategy for diabetes care in South Asia

Background: Economic dimensions of implementing quality improvement for diabetes care are understudied worldwide. We describe the economic evaluation protocol within a randomised controlled trial that tested a multi-component quality improvement (QI) strategy for individuals with poorly-controlled type 2 diabetes in South Asia. Methods/Design: This economic evaluation of the Centre for Cardiometabolic Risk Reduction in South Asia (CARRS) randomised trial involved 1146 people with poorly-controlled type 2 diabetes receiving care at 10 diverse diabetes clinics across India and Pakistan. The economic evaluation comprises both a within-trial cost-effectiveness analysis (mean 2.5 years follow up) and a microsimulation model-based cost-utility analysis (life-time horizon). Effectiveness measures include multiple risk factor control (achieving HbA1c \u3c 7% and blood pressure \u3c 130/80 mmHg and/or LDL-cholesterol\u3c 100 mg/dl), and patient reported outcomes including quality adjusted life years (QALYs) measured by EQ-5D-3 L, hospitalizations, and diabetes related complications at the trial end. Cost measures include direct medical and non-medical costs relevant to outpatient care (consultation fee, medicines, laboratory tests, supplies, food, and escort/accompanying person costs, transport) and inpatient care (hospitalization, transport, and accompanying person costs) of the intervention compared to usual diabetes care. Patient, healthcare system, and societal perspectives will be applied for costing. Both cost and health effects will be discounted at 3% per year for within trial cost-effectiveness analysis over 2.5 years and decision modelling analysis over a lifetime horizon. Outcomes will be reported as the incremental cost-effectiveness ratios (ICER) to achieve multiple risk factor control, avoid diabetes-related complications, or QALYs gained against varying levels of willingness to pay threshold values. Sensitivity analyses will be performed to assess uncertainties around ICER estimates by varying costs (95% CIs) across public vs. private settings and using conservative estimates of effect size (95% CIs) for multiple risk factor control. Costs will be reported in US$ 2018. Discussion: We hypothesize that the additional upfront costs of delivering the intervention will be counterbalanced by improvements in clinical outcomes and patient-reported outcomes, thereby rendering this multi-component QI intervention cost-effective in resource constrained South Asian settings

An Efficient Method for Antenna Design Based on a Self-Adaptive Bayesian Neural Network-Assisted Global Optimization Technique

Gaussian process (GP) is a very popular machine learning method for online surrogate-model-assisted antenna design optimization. Despite many successes, two improvements are important for the GP-based antenna global optimization methods, including: 1) the convergence speed (i.e., the number of necessary electromagnetic (EM) simulations to obtain a high-performance design) and 2) the GP model training cost when there are several tens of design variables and/or specifications. In both aspects, the state-of-the-art GP-based methods show practical but not desirable performance. Therefore, a new method, called the self-adaptive Bayesian neural network surrogate-model-assisted differential evolution (DE) for antenna optimization (SB-SADEA), is presented in this article. The key innovations include: 1) the introduction of the Bayesian neural network (BNN)-based antenna surrogate modeling method into this research area, replacing GP modeling, and 2) a bespoke self-adaptive lower confidence bound (LCB) method for antenna design landscape making use of the BNN-based antenna surrogate model. The performance of SB-SADEA is demonstrated by two challenging design cases, showing considerable improvement in terms of both convergence speed and machine learning cost compared with the state-of-the-art GP-based antenna global optimization methods

Health-related quality of life variations by sociodemographic factors and chronic conditions in three metropolitan cities of South Asia: The CARRS study

Objectives: Health-related quality of life (HRQOL) is a key indicator of health. However, HRQOL data from representative populations in South Asia are lacking. This study aims to describe HRQOL overall, by age, gender and socioeconomic status, and examine the associations between selected chronic conditions and HRQOL in adults from three urban cities in South Asia.Methods: We used data from 16 287 adults aged ≥20 years from the baseline survey of the Centre for Cardiometabolic Risk Reduction in South Asia cohort (2010-2011). HRQOL was measured using the European Quality of Life Five Dimension-Visual Analogue Scale (EQ5D-VAS), which measures health status on a scale of 0 (worst health status) to 100 (best possible health status).Results: 16 284 participants completed the EQ5D-VAS. Mean age was 42.4 (±13.3) years and 52.4% were women. 14% of the respondents reported problems in mobility and pain/discomfort domains. Mean VAS score was 74 (95% CI 73.7 to 74.2). Significantly lower health status was found in elderly (64.1), women (71.6), unemployed (68.4), less educated (71.2) and low-income group (73.4). Individualswith chronic conditions reported worse health status than those without (67.4 vs 76.2): prevalence ratio, 1.8 (95% CI 1.61 to 2.04).Conclusions: Our data demonstrate significantly lower HRQOL in key demographic groups and those with chronic conditions, which is consistent with previous studies. These data provide insights on inequalities in population health status, and potentially reveal unmet needs in the community to guide health policies

Prevalence and incidence of hypertension: Results from a representative cohort of over 16,000 adults in three cities of south Asia

Background: Despite high projected burden, hypertension incidence data are lacking in South Asian population. We measured hypertension prevalence and incidence in the Center for cArdio-metabolic Risk Reduction in South Asia (CARRS) adult cohort.Methods: The CARRS Study recruited representative samples of Chennai, Delhi, and Karachi in 2010/11, and socio-demographic and risk factor data were obtained using a standard common protocol. Blood pressure (BP) was measured in the sitting position using electronic sphygmomanometer both at baseline and two year follow-up. Hypertension and control were defined by JNC 7 criteria.Results: In total, 16,287 participants were recruited (response rate=94.3%) and two year follow-up was completed in 12,504 (follow-up rate=79.2%). Hypertension was present in 30.1% men (95% CI: 28.7-31.5) and 26.8% women (25.7-27.9) at baseline. BP was controlled in 1 in 7 subjects with hypertension. At two years, among non-hypertensive adults, average systolic BP increased 2.6mm Hg (95% CI: 2.1-3.1), diastolic BP 0.7mm Hg (95% CI: 0.4-1.0), and 1 in 6 developed hypertension (82.6 per 1000 person years, 95% CI: 80.8-84.4). Risk for developing hypertension was associated with age, low socio-economic status, current alcohol use, overweight, pre-hypertension, and dysglycemia. Risk of incident hypertension was highest (RR=2.95, 95% CI: 2.53-3.45) in individuals with pre-hypertension compared to normal BP. Collectively, 4 modifiable risk factors (pre-hypertension, overweight, dysglycemia, and alcohol use) accounted for 78% of the population attributable risk of incident hypertension.Conclusion: High prevalence and poor control of hypertension, along with high incidence, in South Asian adult population call for urgent preventive measures