Family networks and school enrolment: evidence from a randomized social experiment

We present evidence on whether and how a household’s behavior is influenced by the presence and characteristics of its extended family. Using data from the PROGRESA program in Mexico, we exploit information on the paternal and maternal surnames of heads and spouses in conjunction with the Spanish naming convention to identify the inter and intra generational family links of each household to others in the same village. We then exploit the randomized research design of the PROGRESA evaluation data to identify whether the treatment effects of PROGRESA transfers on secondary school enrolment vary according to the characteristics of extended family. We find PROGRESA only raises secondary enrolment among households that are embedded in a family network. Eligible but isolated households do not respond. The mechanism through which the extended family influences household schooling choices is the redistribution of resources within the family network from eligibles that receive de facto unconditional cash transfers from PROGRESA, towards eligibles on the margin of enrolling children into secondary school

New Techniques of Weighted Sum Method for Solving Multi-Objective Geometric Programming Problems

تعد مشكلة البرمجة الهندسية متعددة الأهداف نوعًا من مشاكل التحسين التي تستخدم بشكل كبير في المشاكل الهندسية. حتى الآن لا يوجد الكثير من تقنيات التحسين التي يمكنها حساب هذا النوع من مشاكل التحسين بسهولة. في هذا البحث ، تم تقديم تقنيتين جديدتين مع خوارزميتين لتحسين مشاكل البرمجة الهندسية متعددة الأهداف. التقنية الاولى تم أنشاءها باستخدام طريقة المجموع الموزون والوسط الحسابي والتقنية الثانية باستخدام طريقة المجموع الموزون والمتوسط ​​الهندسي. تم استخدام هاتين الطريقتين لتحويل مشكلة التحسين الهندسي متعدد الأهداف إلى مشكلة التحسين الهندسي ذات الهدف الواحد. تم اخذ بعض الامثلة بالاعتبار لتوضيح النتائج. كذلك تمت مقارنة هذه النتائج مع التقنيات الشائعة الأخرى المستخدمة في حل مشاكل التحسين الهندسي متعدد الأهداف.Multi-objective geometric programming problem is a type of optimization problem that wildly used in engineering problems. Until now there are not many optimization techniques that can easily compute this type of optimization problem. In this paper, we proposed two new techniques with algorithms to optimize multi-objective geometric programming problems. We created the first technique by using the weighted sum method and Arithmetic mean, and by using the weighted sum method and geometric mean we produced the second technique. These two methods are used to convert multi-objective geometric optimization problems to single-objective geometric optimization problems Some examples are considered to illustrate the results. The results were compared with other common techniques used in solving multi-objective engineering optimization problems

Catalytic Activity of Aluminum Impregnated Catalysts for the Degradation of Waste Polystyrene

Abstract— The aluminum impregnated catalysts of Al-alumina (Al-Al₂O₃), Al-montmorillonite (Al-Mmn) and Al-activated charcoal (Al-AC) of various percent loadings were prepared by wet impregnation method and characterized by SEM, XRD and N2 adsorption/desorption (BET). The catalytic properties were investigated in the degradation of waste polystyrene (WPS). The results of catalytic degradation of Al metal, 20% Al-Al₂O₃, 5% Al-Mmn and 20% Al-AC were compared with each other for optimum conditions. Among the catalyst used 20% Al-Al₂O₃ was found the most effective catalyst. The BET surface area of 20% Al-Al₂O₃ determined was 70.2 m2/g. The SEM data revealed the catalyst with porous structure throughout the frame work with small nanosized crystallites. The yield of liquid products with 20% Al-Al₂O₃ (91.53 ± 2.27 wt%) was the same as compared to Al metal (91.20 ± 0.35 wt%) but the selectivity of hydrocarbons and yield of styrene monomer (56.32 wt%) was higher with 20% Al-Al₂O₃ catalyst

Catalytic Activity of Aluminum Impregnated Catalysts for the Degradation of Waste Polystyrene

Abstract— The aluminum impregnated catalysts of Al-alumina (Al-Al₂O₃), Al-montmorillonite (Al-Mmn) and Al-activated charcoal (Al-AC) of various percent loadings were prepared by wet impregnation method and characterized by SEM, XRD and N2 adsorption/desorption (BET). The catalytic properties were investigated in the degradation of waste polystyrene (WPS). The results of catalytic degradation of Al metal, 20% Al-Al₂O₃, 5% Al-Mmn and 20% Al-AC were compared with each other for optimum conditions. Among the catalyst used 20% Al-Al₂O₃ was found the most effective catalyst. The BET surface area of 20% Al-Al₂O₃ determined was 70.2 m2/g. The SEM data revealed the catalyst with porous structure throughout the frame work with small nanosized crystallites. The yield of liquid products with 20% Al-Al₂O₃ (91.53 ± 2.27 wt%) was the same as compared to Al metal (91.20 ± 0.35 wt%) but the selectivity of hydrocarbons and yield of styrene monomer (56.32 wt%) was higher with 20% Al-Al₂O₃ catalyst

A Probabilistic Analysis of The Trading The Line Strategy

We provide analytic models for which the appropriate statistics of the trading the line strategy, N h , can be derived in closed form. In particular, we provide closed-form expressions concerning the average duration of the open position, E(N h ), the variance of the open duration, Var(N h ), the average of the stopped log price, E(S N h ), the variance of the stopped log price, Var(S N h ), the correlation, Corr(N h , S N h ), and the Laplace transform, E(e−s N h ). These results are obtained, in discrete time settings, for binomial and other price scenarios. Furthermore, when analytic results are not possible, such as the case of a normal distribution for log returns, we show by simulation that our general conclusions still hold. Using these statistics we point out some of the subtle features of the trailing stops strategy