ASSESSMENT OF FARMERS’ KNOWLEDGE REGARDING CHILD LABOR IN AGRICULTURE: A CASE STUDY OF COTTON GROWERS IN DISTRICT BAHAWALPUR

The work which affects the education, dignity and health of a child is known as child labor. It exists in agriculture sector of Pakistan mostly in the form of hazardous work. The main objective of the study was to investigate the degree of knowledge of cotton growers on child labor issue with special reference to Decent Work of International Labor Organization (ILO). The study was conducted in Bahawalpur district where Decent Work has been implemented by World Wide Fund for Nature (WWF)-Pakistan since 2013 as a part of its Sustainable Agriculture Program. Three categories of farmers were identified among a total of 388 selected cotton growers i.e. Farmers having high level of awareness, farmers having basic level of awareness and farmers having no awareness of child labor. Farmers were also categorized into three groups on the basis of their land holding i.e. (Category ‘a’) 1-7 acres, (b) >7-20 acres and (c) >20-50 acres. The data was analyzed through descriptive statistical method. Among category ‘a’ 7.5%, 88.7% and 3.7% of the farmers had advance, basic and no awareness, respectively. Among category ‘b’ 7.2%, 88.5% and4.2% farmers had advance, basic and no awareness, respectively. Among category ‘c’ 5.8%, 90.2% and 3.9% farmers had advance, basic and no awareness, respectively. Since there was a large proportion of those farmers who have only basic level of awareness on child labor among all the three land holding categories, therefore, there is a need to educate farmers on preventing child labor at their farms to promote sustainable cotton

Can sulphur improve the nutrient uptake, partitioning, and seed yield of sesame?

Sulphur (S) is considered to improve the nutrient uptake of plants due to its synergistic relationship with other nutrients. This could ultimately enhance the seed yield of oilseed crops. However, there is limited quantitative information on nutrient uptake, distribution, and its associated impacts on seed yield of sesame under the S application. Thus, a two-year field study (2018 and 2019) was conducted to assess the impacts of different S treatments (S-0 = Control, S-20 = 20, S-40 = 40, and S-60 = 60 kg ha(-1)) on total dry matter production, nitrogen, phosphorus, potassium, S uptake and distribution at the mid-bloom stage and physiological maturity. Furthermore, treatment impacts were studied on the number of capsules per plant, number of seeds per capsule, thousand seed weight, and seed yield at physiological maturity in sesame. Compared to S-0, over the years, treatment S-40 significantly increased the total uptake of nitrogen, phosphorus, potassium, and S (by 13, 22, 11% and 16%, respectively) at physiological maturity, while their distribution by 13, 36, 14, and 24% (in leaves), 12, 15, 11, and 15% (in stems), 15, 42, 18, and 10% (in capsules), and 14, 22, 9, and 15% (in seeds), respectively. Enhanced nutrient uptake and distribution in treatment S-40 improved the total biomass accumulation (by 28%) and distribution in leaves (by 34%), stems (by 27%), capsules (by 26%), and seeds (by 28%), at physiological maturity, as compared to S-0. Treatment S-40 increased the number of capsules per plant (by 13%), number of seeds per capsule (by 11%), and thousand seed weight (by 6%), compared to S-0. Furthermore, over the years, relative to control, sesame under S-40 had a higher seed yield by 28% and enhanced the net economic returns by 44%. Thus, our results suggest that optimum S level at the time of sowing improves the nutrient uptake and distribution during the plant lifecycle, which ultimately enhances total dry matter accumulation, seed yield, and net productivity of sesame

Toxicities, kinetics and degradation pathways investigation of ciprofloxacin degradation using iron-mediated H\u3csub\u3e2\u3c/sub\u3eO\u3csub\u3e2\u3c/sub\u3e based advanced oxidation processes

© 2018 Institution of Chemical Engineers Ciprofloxacin (CIP) is a widespread emerging water pollutant and thus its removal from aquatic environment is vital. The use of Fe3+/H2O2 and Fe2+/H2O2 resulted in 38 and 64% removal of CIP (8.0 ppm), respectively, within 80 min reaction time (pH 5.8, [H2O2]0 = 80 ppm, and [iron]0 = 20 ppm). Low pH, high temperature, high dose of H2O2 and Fe2+, and low CIP concentration facilitated removal of CIP. The radical scavenger studies proved in situ generated [rad]OH to be involved primarily in the removal of CIP. The effect of temperature was used to estimate enthalpy and activation energies of the removal of CIP. At 800 min reaction time, the Fe2+/H2O2 resulted in 54% mineralization of CIP using 16.0 ppm [CIP]0, 320.0 ppm [H2O2]0, and 40.0 ppm [Fe2+]0. The potential degradation pathways of CIP established from the degradation of CIP by [rad]OH and products evolved was found to be initiated at C6 through the loss of fluoride ion. The acute and chronic toxicities of CIP and its degradation products were estimated with the final product found to be non-toxic. The results suggest that Fe2+/H2O2-mediated AOPs have high potential for degradation as well as toxicity elimination of CIP and its degradation products

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 years; 78.2% included were male with a median age of 37 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

Studies on induced mutations in chickpea (Cicer arietinum L.) I. Responses of the mutagenic treatments in M1 biological parameters

The effect of ethylmethane sulphonate (EMS), sodium azide (SA) and hydrazine hydrate (HZ) on seed germination, pollen fertility and survival at maturity were studied in two varieties viz., Avrodhi and BG- 256 of chickpea. A linear and dose dependant decrease on germination, pollen fertility and survival was observed in all the three mutagenic treatments in both the varieties. The maximum reduction in these parameters was observed to be induced by EMS treatments. Variety Avrodhi proved to be more sensitive to the mutagenic treatments than var. BG-256. Estimated values of LD50 for EMS, SA and HZ were observed to be 0.363, 0.045 and 0.052 for Avrodhi and 0.457, 0.058 and 0.070 for BG-256, respectively

Learning Action-oriented grasping for manipulation

Complex manipulation tasks require grasping strategies that simultaneously satisfy the stability and the semantic constraints that have to be satisfied for an action to be feasible, referred as action-oriented semantic grasp strategies. This study develops a framework using machine learning techniques to compute action-oriented semantic grasps. It takes a 3D model of the object and the action to be performed as input and provides a vector of action-oriented semantic grasps. We evaluate the performance of machine learning (particu- larly classification techniques) to determine which approaches perform better for this problem. Using the best approaches, a multi-model classification technique is developed. The proposed approach is evaluated in simulation to grasp different kitchenobjects using a parallel gripper. The results show that multi-model classification approach enhances the prediction accuracy. The implemented system can be used as to automate the data labeling process required for deep learning approaches.Peer Reviewe

Dispersion of Iron Nanoparticles by Polymer-Based Hybrid Material for Reduction of Hexavalent Chromium

A gel type acrylic acid resin, based on ethyl acrylate-co-1,7-octadiene, has been synthesized by suspension polymerization at 20% cross-linking and subsequent hydrolysis by H2SO4. Capacity of the resin was observed to be 8.90 meq/g or 3.28 meq/mL. The iron nanoparticles used in this study were synthesized by ferrous sulphate method by using LiBH4 as a reductant and characterized by SEM, TEM, XRD, surface area, and electrical properties. Later, the resin was applied for the dispersion of iron nanoparticles over its surface for the reduction of Cr(VI) and subsequent adsorption of Fe(III) and Cr(III) as byproducts. In the column studies the reduction of Cr(VI) and the adsorption of Cr(III) and Fe(III) have been observed up to 240 μmole/L

Learning Action-oriented grasping for manipulation

Complex manipulation tasks require grasping strategies that simultaneously satisfy the stability and the semantic constraints that have to be satisfied for an action to be feasible, referred as action-oriented semantic grasp strategies. This study develops a framework using machine learning techniques to compute action-oriented semantic grasps. It takes a 3D model of the object and the action to be performed as input and provides a vector of action-oriented semantic grasps. We evaluate the performance of machine learning (particu- larly classification techniques) to determine which approaches perform better for this problem. Using the best approaches, a multi-model classification technique is developed. The proposed approach is evaluated in simulation to grasp different kitchenobjects using a parallel gripper. The results show that multi-model classification approach enhances the prediction accuracy. The implemented system can be used as to automate the data labeling process required for deep learning approaches.Peer ReviewedPostprint (author's final draft

Learning Action-oriented grasping for manipulation

Complex manipulation tasks require grasping strategies that simultaneously satisfy the stability and the semantic constraints that have to be satisfied for an action to be feasible, referred as action-oriented semantic grasp strategies. This study develops a framework using machine learning techniques to compute action-oriented semantic grasps. It takes a 3D model of the object and the action to be performed as input and provides a vector of action-oriented semantic grasps. We evaluate the performance of machine learning (particu- larly classification techniques) to determine which approaches perform better for this problem. Using the best approaches, a multi-model classification technique is developed. The proposed approach is evaluated in simulation to grasp different kitchenobjects using a parallel gripper. The results show that multi-model classification approach enhances the prediction accuracy. The implemented system can be used as to automate the data labeling process required for deep learning approaches.Peer Reviewe