Occupational Safety and Health Practices among Farmers in Wadi Al Fara’ Area, Palestine.

Background: Agriculture is considered a vital sector and it is ranked as the fourth cause for occupational non- fatal injury in the Palestinian society. Methods: A quantitative study in Wadi Al Far’a area was implemented in 2017. Four hundred farmers were interviewed and completed a questionnaire. The researcher requested information about the farmers and their work, along with a description of the injury and its seriousness and whether they were injured during the past twelve months. Moreover, information regarding farmer awareness about the preventive measures was taken. A descriptive analysis, χ2 testing and binary logistic regression were conducted using SPSS (version 20). Results: The analysis showed that 71% of the interviewed farmers were injured, of which 51% of the injuries were concentrated in the hands of the farmers, while 36% of the farmers were injured by stab wounds from sharp objects, and 45% of the accidents were caused by hand equipments. The analysis also showed that 4.2% of the farmers reported that the injuries were serious and needed hospital treatment, while 47.6% needed a rest for a day or less and 2% were left with long-term injuries accompanied by medical certificates. Fewer injuries were found among farmers who attended an occupational safety course and who wore protective uniforms. The binary regression results revealed that farmers coming from big families, who own the farms and work as full time farmers in big fields, were at a higher risk to become injured. While elderly farmers were at a lower risk to be injured. Conclusion: Strengthening the National Committee for Occupational Safety combined with safety education; through the use of safety equipment and the improvement of preventive measures that are needed to improve occupational safety for farmers at the Palestinian level

Assessment of rainwater harvesting systems in poor rural communities: A case study from Yatta area, Palestine.

ARTICLEYatta is a town located nine kilometers south of Hebron city in the West Bank of Palestine. The town houses over 100,000 people of which 49% are females and has a population that doubles every 15 years. Yatta has been connected to a water network since 1974 serving nearly 85% of its households. The water network is old and inadequate to meet the needs of the population. Water supply made available to the area is limited, estimated at 20 L/capita/day. Residents are thus forced to rely on water vendors who supply water that is 400% more expensive with a lower quality compared to municipal water. Therefore, rainwater harvesting is a common practice in the area, with the majority of households owning at least one cistern. Rainwater harvesting is of great socio-economic importance in areas where water sources are scarce and/or polluted. In this research, the quality of harvested rainwater used for drinking and domestic purposes in Yatta was assessed throughout one year. A total of 100 samples were collected from cisterns with an average capacity of 69 m3, which are adjacent to cement-roof catchment areas of 145 m2 average surface area. Samples were analyzed for a number of parameters including temperature, pH, alkalinity, hardness, turbidity, total dissolved solids, NO3, NH4, chloride and salinity. Results showed that most of the rainwater samples were withinWorld Health Organization (WHO) and Environment Protection Agency (EPA) guidelines for chemical parameters. Microbiological contents such as total Coliforms and faecal Coliforms bacteria were tested. The research also addressed the impact of rainwater harvesting systems on different socio-economic attributes of the local community through a questionnaire that had been filled out before any sample was collected.This study was funded by the Partnerships for Enhanced Engagement in Research (PEER) program, implemented by the U.S. National Academy of Sciences—Sponsor Grant No.: AID-OAA-A-11-00012 and USAID-USGS Grant No. G17AS00001

Initial Results from Applied Integrated Practices and Technologies for Sustainable Management of Agrofood Industrial Wastewater in Palestine

conference proceedingsIllicit direct discharges of raw agrofood industrial wastewater into wastewater treatment facilities (WWTFs) or seasonal Wadi beds pose serious public health risks and environmental degradation, exacerbated by socio-economic impacts and regional political conflicts. Policy makers in water and environmental authorities face power limitations by enforcing legal and technical regulations pertinent to connection, co-treatment and non-compliance of agrofood industrial discharges into WWTFs. This paper presents initial results on industrial wastewater management (INWA), a PADUCO program funded project. INWA aims at research development (RD) of new treatment approaches, and governance analysis for agrofood industries identified as heavy organic polluters including olive mills (Nablus), dairy industries (Hebron) and slaughterhouses (Gaza).We focused on governance assessment pertinent to institutional aspects of current wastewater management in the study area. RD entails five ongoing master thesis, of which are four at Birzeit University (BZU) covering governance enhancement and diverse treatment technologies applications. A recent defended BZU thesis proved the economic and environmental feasibility of advanced oxidation process using Fenton reaction as a pretreatment stage for mixed organic industrial wastewaters. Installed at BZU campus, an ongoing research study investigates monitoring and performance evaluation of a pilot UASB-nature based units for slaughterhouse wastewater treatment. The Islamic University of Gaza explores at bench scale the feasibility of activated sludge systems for slaughterhouse wastewater treatment. A fifth ongoing study entails using phytoremediation to revitalize Wadi Zaimer, which receives diverse industrial discharges from Nablus West. Compliance of agrofood industries with national guidelines reduces capital and operational costs, public health risks and pollution loads into receiving water bodies in PalestineNRO Ramallah, PADUCO2 progra

The Wall, Bypass Roads And The Dual Transportation System In Palestine

The road network in Palestine is a complex road system where the highway system is classified into main roads and bypass roads. The main roads are usually two-lane highways that connect the Palestinian cities in the West Bank while the Bypass roads is a road system that is constructed by the Israeli occupation to facilitate the movement of the settlers without entering the large Palestinian urban centers. The movement of Palestinians usually occur on the main streets between cities. They can also use segments of the bypass roads which is most of the time has obstructions such as check points, gates and the separation wall. These on ground road facts have create obstacles on road accessibility for Palestinians and at the same time offers an none obstructed accessibility to destinations for Israeli settlers. This paper will illustrate the road conditions in Palestine by explaining the dual transportation system for Palestinian and Israeli settlers. The paper will also elaborate on and explains the obstacles Palestinian face daily on their accessibility to destination. The paper will use Geographic Information Systems as a mapping tool to explain the existing conditions of the roads and the obstacles people face. The paper will also use spatial analysis in vector and raster to quantify the connectivity characteristic of roads such as road density and intersection density and proximity and then compare these parameters between the roads used by Palestinians and the bypass roads used by Israeli settlers. The results of this paper can be used by local authorities in their planning for accessibility in the West Ban

Industrial Solid Waste Management in a Developing Country Governorate and the Opportunities for the Application of Cleaner Production Principles.

Hebron is an industrial governorate south of Palestine where the lack of studies ends up to inexistent evaluation of its environmental status. Understanding the status of industrial solid waste management (SWM) largely contributes to the determination of the opportunities and the appropriate roadmap for the application of cleaner production principles.In this chapter, we report the results of an extended research-constructed survey conducted in Hebron both at municipal level and industrial level. Primarily the municipal level research was aimed at identifying the current SWM practices. Then the industrial level research was aimed to collect data on both the applied SWM practices in local industries and record the generated quantities of ISW. Towards the development, updating and implementation of a legislative framework, which will support an integrated SWM in the local industrial area, the stakeholders are highly encouraged to develop an incentive system for industries to reduce and recycle the generated ISW. This need clearly emerges from the current research results: Only 21 out of 91 factories treat SW before final disposal; 83.33% of them recycle the waste in situ or in collaboration with local recycling stakeholders; 51.65% of the investigated industries produce a mixture of process and nonprocess ISW, the average rate of nonprocess ISW is 23.22 kg/ day; 8.4% of factories always separate process ISW from nonprocess ISW; 85.7% of factories do not separate their ISW into specific components. Only 13.6% of factories reuse and 16.5% recycle ISW; 77.3% of the recyclable materials are used as secondary raw materials, and 22.7% of them use the separated ISW as secondary raw materials in production, both implementing the fundamental 3Rs principle

Household Hazardous Waste Quantification, Characterization, and Management in Developing Countries’ Cities: A Case Study.

The aim of this research is to assess household hazardous waste (HHW) management in Hebron city, Palestine, investigating the HHW types and proportions. In parallel the level of awareness of household heads in regard to knowledge of risks and hazards associated with HHW items is investigated through a comprehensive survey. Also, analysis of the total generated solid waste was carried out during a 14-working-day period to detect different HHW components and their proportions. Home products constitute the largest percentage of HHW (42.3%), followed by automotive products (17.2%) and personal care products (15.4%) and healthcare products (12.3%). Personal care products are the most category of HHW that is thrown randomly (78.7%). Socioeconomic factors were related to attitudes and practices of citizens in regard to HHW. Overall results show the great risk associated with HHW given that under aged are transferring SW from home to container (40.2%) with high involved risk of accident; containers in some cases are more than 150 m away from home (19%) increasing the aforementioned potential risk. In 18.5% of houses, there was an accident related to HHW risks which are, namely, injuries (42%), poisoning (36%), burns (22%), etc

Information extraction from Arabic law documents

Information extraction from Arabic law documents Mar 2017 – Present Project description It's Samah Abu Shamma graduation project. It extracts some useful information from Arabic legal documents for people how are interested in law field. Project brief description : It takes a raw (.txt) file legal file and it extracts from it the name of the judge/s, lawyer/s, parties ( plaintiffs and defendants ) and the case's verdict. Machine Learning techniques and rule based approach are used to build the Extraction system.Information hidden in unstructured or semi-structured documents can be quite useful. To pull this information, an information extraction system is needed. Making extracted information available in structured format enables answering more complex queries of interest to law professionals. In this paper we address the issue of Arabic information extraction from law documents. We describe a system that extracts some important information of interest to potential users of these documents with minimal human intervention. The system employs a hybrid approach that utilizes machine learning and rule based approaches to extract the needed information from the texts

تحليل ديناميكية الفقر في فلسطين بإستخدام بيانات المقاطع العرضية المتكررة

Dynamic relations and transitions over time are important aspects in different fields. Dynamic models require panel data for at least two periods. However, panel data collection requires high costs. So, in many countries there is a lack of panel data. When only cross-sectional data are available, we will not be able to analyze dynamic relations which will lead to lack of knowledge and capability of prediction of important indicators for the development of people's life. In this thesis, we will apply Dang and Lanjouw (2013), in addition to other traditional approaches, to estimate the transition probabilities of getting into and out of poverty. This thesis can initiate this kind of analysis by highlighting methods of repeated cross-sectional data analysis, which is widely available in different Palestinian surveys. The results show that the rate of mobility of refugees in the poverty is greater than that of the non-refugees, but there is no evidence that there is a difference between refugees and non-refugees to get out of poverty. Thus, the migration caused by the Israeli occupation affected the refugees by increase the probability of entering the trap of poverty

Training neural networks using salp swarm algorithm for pattern classification

Pattern classification is one of the popular applications of neural networks. However, training the neural networks is the most essential phase. Traditional training algorithms (e.g. Back-propagation algorithm) have some drawbacks such as falling into the local minima and slow convergence rate. Therefore, optimization algorithms are employed to overcome these issues. Salp Swarm Algorithm (SSA) is a recent and novel nature-inspired optimization algorithm that proved a good performance in solving many optimization problems. This paper proposes the use of SSA to optimize the weights coefficients for the neural networks in order to perform pattern classification. The merits of the proposed method are validated using a set of well-known classification problems and compared against rival optimization algorithms. The obtained results show that the proposed method performs better than or on par with other methods in terms of classification accuracy and sum squared errors