Socio-economic determinants of child mortality in Pakistan and the moderating role of household’s wealth index

Background Child mortality is an important social indicator that describes the health conditions of a country as well as determines the country’s overall socio-economic development. The Government of Pakistan has been struggling to reduce child mortality (67.2 per thousand live births in 2019). Pakistan could not achieve the target set for Millennium Development Goals to reduce child mortality and still working to meet the target set by the Sustainable Development Goals. This study has investigated the socio-economic determinants of child mortality in Pakistan by using household-level data. Socio-economic characteristics related to women (mothers) and households have been considered as possible determinants of child mortality. The moderating role of a household’s wealth index on the association between woman’s education and child mortality has also been investigated. Methods The comprehensive dataset of the Pakistan Demographic and Health Survey 2017–18 has been used to explore the determinants of child mortality by using multivariable logistic regression. The interaction term of women’s education and household wealth index has been used to investigate the moderating role of the household’s wealth index. Results The results indicate that the likelihood of child mortality decreases with an increase in women’s education, their empowerment, their husband’s education, the wealth status of their households, access to clean drinking water, access to toilet facilities, and exposure to mass media. Whereas, an increase in unmet need for family planning increases the likelihood of child mortality. The study also identified the moderating role of a household’s wealth index on the association between woman’s education and child mortality. Conclusions Household wealth status moderates the association between women’s education and child mortality. The absolute slope of the curve showing the association of women’s education and child mortality is higher (more negative) for richer households than poorer households. It implies that a household’s wealth status strengthens the relationship between women’s education and child mortality. With the increase in the household’s wealth status, the effect of a mother’s education on child mortality becomes more pronounced.

IMPLEMENTASI KEBIJAKAN IZIN MENDIRIKAN BANGUNAN (IMB) DALAM MENINGKATKAN PENDAPATAN ASLI DAERAH (PAD) PADA DINAS PENANAMAN MODAL PELAYANAN TERPADU SATU PINTU (DPMPTSP) KABUPATEN PANGKEP

Penelitian yang dilakukan dengan tujuan agar dapat diketahui proses dan faktor yang mempengaruhi implementasi kebijakan dan adakah pengaruh terhadap peningkatan pendapatan asli daerah (PAD) pada Dinas Penanaman Modal dan Pelayanan Terpadu Satu Pintu (DPMPTSP) Kabupaten Pangkep. Metode penelitian yang dilakukan bersifat kualitatif dengan metode deskriptif kualitatif. Yaitu memberikan pengamatan dan penggambaran terhadap aspek- aspek penelitian, kemudian meneskripsikan aspek tersebut. Untuk menentukan fakta maka peneliti melakukan wawancara, observasi beberapa informan kunci meliputi pelaksana kebijakan IMB, anggota DPRD, dan masyarakat yang bermohon. Hasil penelitian menunjukkan pada Implementasi kebijakan Izin Mendirikan Bangunan di Kabupaten Pangkep belum berjalan dengan efektif dan belum sesuai dengan keinginan pemerintah daerah. Hal ini dikarenakan belum maksimalnya penerapan kebijakan IMB ditandai dengan tidak diterapkannya waji IMB, ketentuan wajib memenuhi syarat tata bangunan. Adapun faktor yang menyebabkan tidak efektifnya implementasi kebijakan adalaah kualitas dan kwantitas staf yang masih kurang, pengawasan dan dukungan politik dari legislatif masih kurang dan komunikasi yang belum efektif yang belum berjalan dengan baik.Penerimaan retribusi IMB terhadap PAD masih sangat rendah, penerimaan retribusi selama tiga tahun terakhir tidak mengalami kenaikan sesuai target yang diharapkan pemerintah. Setiap tahunnya retribusi IMB yang diterrima Rp. 900.000.000 dimana hanya tercapai 60% dari target yang ditentukan pemerintah Kabupaten Pangkep. Nilai kontribusi tersebut belum signifikan terhadap peningkatan PAD di Kabupaten Pangkep. The research was conducted with the aim of knowing the processes and factors that influence policy implementation and whether there is an effect on increasing local revenue (PAD) at the One Stop Integrated Service and Investment Service (DPMPTSP) Pangkep Regency. The research method carried out is qualitative with a qualitative descriptive method. That is to provide observations and descriptions of aspects of the research, then describe these aspects. To determine the facts, the researchers conducted interviews, observed several key informants including IMB policy implementers, DPRD members, and the people who applied. The results showed that the implementation of the building permit policy in Pangkep Regency had not run effectively and had not been in accordance with the wishes of the local government. This is because the implementation of the IMB policy has not been maximized, which is marked by the non-applicability of the mandatory IMB, the provisions of which must meet the building structure requirements. The factors that cause the ineffective implementation of policies are the quality and quantity of staff that are still lacking, political supervision and support from the legislature are still lacking and communication is not yet effective which has not gone well. Receipt of IMB levies on PAD is still very low, retribution receipts for three years The last one did not increase according to the target expected by the government. Each year the IMB levy received is Rp. 900,000,000 where only 60% of the target set by the Pangkep Regency government was achieved. The value of this contribution has not been significant to the increase in PAD in Pangkep Regency.

Efficient Targeted Influence Maximization Based on Multidimensional Selection in Social Networks

The influence maximization problem over social networks has become a popular research problem, since it has many important practical applications such as online advertising, virtual market, and so on. General influence maximization problem is defined over the whole network, whose intuitive aim is to find a seed node set with size at most k in order to affect as many as nodes in the network. However, in real applications, it is commonly required that only special nodes (target) in the network are expected to be influenced, which can use the same cost of placing seed nodes but influence more targeted nodes really needed. Some research efforts have provided solutions for the corresponding targeted influence maximization problem (TIM for short). However, there are two main drawbacks of previous works focusing on the TIM problem. First, some works focusing on the case the targets are given arbitrarily make it hard to achieve efficient performance guarantee required by real applications. Second, some previous works studying the TIM problems by specifying the target set in a probabilistic way is not proper for the case that only exact target set is required. In this paper, we study the Multidimensional Selection based Targeted Influence Maximization problem, MSTIM for short. First, the formal definition of the problem is given based on a brief and expressive fragment of general multi-dimensional queries. Then, a formal theoretical analysis about the computational hardness of the MSTIM problem shows that even for a very simple case that the target set specified is 1 larger than the seed node set, the MSTIM problem is still NP-hard. Then, the basic framework of RIS (short for Reverse Influence Sampling) is extended and shown to have a 1 − 1/e − ϵ approximation ratio when a sampling size is satisfied. To satisfy the efficiency requirements, an index-based method for the MSTIM problem is proposed, which utilizes the ideas of reusing previous results, exploits the covering relationship between queries and achieves an efficient solution for MSTIM. Finally, the experimental results on real datasets show that the proposed method is indeed rather efficient.

On properties of one functional used in software constructions for solving differential games

Nonlinear differential game (DG) is investigated; relaxations of the game problem of guidance are investigated also. The variant of the program iterations method realized in the space of position functions and delivering in limit the value function of the minimax-maximin DG for special functionals of a trajectory is considered. For every game position, this limit function realizes the least size of the target set neighborhood for which, under proportional weakening of phase constraints, the player interested in a guidance yet guarantees its realization. Properties of above-mentioned functionals and limit function are investigated. In particular, sufficient conditions for realization of values of given function under fulfilment of finite iteration number are obtained.

Layer-specific developmentally precise axon targeting of transient suppressed-by-contrast retinal ganglion cells (tSbC RGCs)

The mouse retina encodes diverse visual features in the spike trains of more than 40 retinal ganglion cell (RGC) types. Each RGC type innervates a specific subset of the more than 50 retinorecipient brain areas. Our catalog of RGC types and feature representations is nearing completion. Yet, we know little about where specific RGC types send their information. Furthermore, the developmental strategies by which RGC axons choose their targets and pattern their terminal arbors remain obscure. Here we identify a genetic intersection (Cck-Cre and Brn3cCKOAP) that selectively labels transient Suppressed-by-Contrast (tSbC) RGCs, a member of an evolutionarily conserved functionally mysterious RGC subclass. We find that tSbC RGCs selectively innervate the dorsolateral and ventrolateral geniculate nuclei of the thalamus (dLGN and vLGN), the superior colliculus (SC), and the nucleus of the optic tract (NOT). They binocularly innervate dLGN and vLGN but project only contralaterally to SC and NOT. In each target, tSbC RGC axons occupy a specific sublayer, suggesting that they restrict their input to specific circuits. The tSbC RGC axons span the length of the optic tract by birth and remain poised there until they simultaneously innervate their four targets around postnatal day five. The tSbC RGC axons make no errors in choosing their targets and establish mature stratification patterns from the outset. This precision is maintained in the absence of Brn3c. Our results provide the first map of SbC inputs to the brain, revealing a narrow target set, unexpected laminar organization, target-specific binocularity, and developmental precision.

Repurposing Oil and Gas Reservoirs for Blue Hydrogen Production

Hydrogen is critical to achieving the NetZero Target set by the UK government in 2050. There have been concerted efforts to produce more hydrogen from renewable sources (green hydrogen) to reduce the impact on the environment. The arguments have been that hydrogen produced from hydrocarbon sources contribute largely to CO 2 emission in the atmosphere causing global warming. While this is true, the reality however is that the increasing demand projections for hydrogen have not been met by green hydrogen. At present, nearly all industrial hydrogen are produced from hydrocarbon sources (Muradov 2017). CO 2emission is a major by-product of blue hydrogen production. However, there is a need to reverse engineer the hydrogen process from hydrocarbons, explore hydrogen production directly from the reservoir and retain the accompanying CO 2from being released into the surface. Using a depleted reservoir as feedstock, one method of doing this is by in-situ hydrogen production through thermal combustion of the hydrocarbon reservoirs.

Domain Adaptation for Document Image Binarization via Domain Classification

Binarization represents a key role in many document image analysis workflows. The current state of the art considers the use of supervised learning, and specifically deep neural networks. However, it is very difficult for the same model to work successfully in a number of document styles, since the set of potential domains is very heterogeneous. We study a multi-source domain adaptation strategy for binarization. Within this scenario, we look into a novel hypothesis where a specialized binarization model must be selected to be used over a target domain, instead of a single model that tries to generalize across multiple domains. The problem then boils down to, given several specialized models and a new target set, deciding which model to use. We propose here a simple way to address this question by using a domain classifier, that estimates which of the source models must be considered to binarize the new target domain. Our experiments on several datasets, including different text styles and music scores, show that our initial hypothesis is quite promising, yet the way to deal with the decision of which model to use still shows great room for improvement.

PEMANFAATAN KICK FOOT SENSOR UNTUK MEKANISME BUKA TUTUP BAGASI KENDARAAN

Along with its development, car manufacturers are increasingly improving safety and security features in each of their products. Currently, this element of safety and security has become an important target in the development of the existence of various features that exist in a vehicle. In this study, the power back door feature is implemented by using the kick foot sensor as input data to open and close the trunk of the vehicle through the actuator. This feature uses a foot sensor so you don't have to press any buttons, just point your foot under the rear bumper and the sensor will automatically read and open the trunk door. This feature is very helpful for passengers who want to put their luggage in the trunk but have both hands to carry items such as bags or plastic shopping bags. There are several stages carried out in this research. In the first stage, the specification of the required actuator motor, including force and torque, is carried out by analyzing the free body diagram to be able to open and close the trunk. In the second stage, the trunk door is tested when the condition is open and close. From the test results, the average time to open the trunk is 11.79 seconds, while the average time to close the trunk is 11.56 seconds. The time obtained is faster than the initial design target set, which is 15 seconds both when opening and closing the trunk. While the sensitivity of the motion sensor can range from 20 mm to 400 mm when the foot is directly under the sensor.

The Application of Numbered Heads Together (NHT) in Online Learning

This research is a Classroom Action Research conducted at Public Senior High School 3 Bengkulu City, especially class XI MIPA 4. Online learning in this class reduces student learning activities. Many students are passive in learning. This affects decreasing their learning outcomes. For that, it is necessary to provide the appropriate treatment for solving the problem. This treatment is to apply a learning model that requires students to be more active in learning. One of them is the Numbered Head Together (NHT) learning model. This study aims to increase student activeness in the online learning process and improve student learning outcomes using the NHT model, especially chemical equilibrium material. The subjects of this study were 34 students of class XI MIPA 4. The instruments used were the student activeness observation sheet and the learning outcome test instrument. This research runs in 2 cycles, with each cycle consisting of planning, implementing, observing, and reflecting. The results obtained, overall, there was an increase in student activity in the online learning process and student learning outcomes. The percentage of student activeness in online learning increased from 40.19% in cycle I to 85.29% in cycle II. Meanwhile, the percentage of student learning outcomes completeness was risen from 55.88% in the first cycle to 82.35%. Both have achieved the target set, which is 75%.