Highly labor-intensive public works in Madagascar : issues and policy options

High labor intensive (HIMO) public works programs have been very popular in recent years in Madagascar. They have been one of the most common safety net programs used in Madagascar to address poverty and vulnerability. The objectives of these programs are to provide income support to the poor after natural disasters and during seasonal agricultural employment slack period (soudure), and to improve much needed local infrastructures. This paper assesses the effectiveness of HIMO interventions in addressing the needs of poor and vulnerable households using the data from 15 projects implemented between 2006 and 2008 by several agencies. The main finding of this study is that despite their great potential, HIMO projects have shown the following limitations in the Madagascar context: a) lack of coordination among projects implemented by different agencies; b) ineffective targeting and poor selection of projects; c) lack of monitoring and supervision. The paper identifies four areas for improvement: a) better harmonization and coordination of HIMO projects to ensure consistency of approaches among interventions; b) better geographical targeting and selection of projects; c) setting the wage rate according to the local socio-economic conditions to promote self selection of the poor; and d) better collection of information for monitoring and evaluation of the impact of projects.Housing&Human Habitats,Rural Poverty Reduction,Population Policies,,Poverty Monitoring&Analysis

PERAN KEJAKSAAN DALAM PENGAMANAN DAN PENDAMPINGAN HUKUM PROYEK STRATEGIS SESUAI UNDANG UNDANG NO 16 TAHUN 2004 TENTANG KEJAKSAAN REPUBLIK INDONESIA

Penelitian ini digunakan adalah Metode Penelitian Hukum Normative. Dengan menggunakan beberapa pendekatan, seperti pendekatan peraturan perundang-undangan (statute approach), pendekatan Konseptual (conceptual approach), dan pendekatan kasus (case approach). Penelitian ini menemukan bahwa adanya beberapa proyek strategis yang di proses secara hukum baik  oleh aparat penegak hukum Kejaksaan R.I, Kepolisian dan KPK akibat pengguna anggaran dan PPK (pejabat Pembuat Komitmen) di Instansi Pemerintan baik Pusat/Daerah telah melakukan pembayaran 100 % kepada penyedia jasa/kontraktor yang tidak sesuai ketentuan dalam peraturan perundang-undangan akibatnya proyek tersebut tidak bisa di manfaat/digunakan yang menyebabkan terjadinya kerugian negara.Bahwa menyikapi permasalahan tersebut maka aparat penegak hukum Kejaksaan R.I tidak lagi menggunakan fungsinya sebagai penyelidik/penyidik namun berubah fungsi menjadi pengawal,pengaman dan pendamping hukum terhadap proyek strategis lewat fungsi pencegahan (preventif)  yaitu dengan melakukan penyuluhan hukum terhadap penyelenggara proyek baik berkaitan dengan aturan-aturan hukum yang berkaitan dengan pengadaan barang dan jasa serta aturan-aturan yang berkaitan dengan masalaha keuangan..Kata Kunci: Peran, Kejaksaan, Pengamanan, Proyek Strategi

Biochemical, ECF18R , and RYR1 Gene Polymorphisms and Their Associations with Osteochondral Diseases and Production Traits in Pigs

This study reports the association of five blood types, three enzymes, two proteins, Escherichia coli F18 receptor gene (ECF18R), and the Ryanodin receptor (RYR1) gene with six production traits, four meat quality traits, and two osteochondral diseases in Swiss pig populations. Data on on-farm traits (daily weight gain, percent premium cuts, and backfat) and on station-tested traits (daily weight gain, feed conversion ratio, meat quality, and osteochondral lesions) were available on 3,918 and 303 animals, respectively. A mixed linear model with allele substitution effects was used for each trait by marker analysis (144 analyses). Significant marker-trait associations and allele substitution effects are presented. In general, heritability estimates for production and meat quality traits were higher than those for osteochondral lesions. Blood types lack significant associations with many traits except H and S types. Enzymes (mainly, glucose phosphate isomerase) and protein polymorphisms show significant associations with daily weight gain, premium cuts, and backfat as well as osteochondral lesions. The RYR and ECF18R genes significantly affected all growth, production, and lean meat content traits and osteochondral lesions; RYR also affected pH values. This study reports many novel marker-trait associations, particularly between the incidence of osteochondral lesions and polymorphisms at glucose phosphate isomerase, 6-phosphogluconate dehydrogenase, postalbumin 1A, RYR, and ECF18R loci. These results should be useful in selection and for further functional genomics and proteomics investigation

Inculcating universal values via English language education

The teaching and learning of languages need not necessarily be focused entirely on the acquisition of language skills. While the primary aim of language instruction is enhanced proficiency in a language, we need to inculcate values-moral, spiritual, human, ethical, etc. in our teaching and learning activities. The paper demonstrates how this may be done while acquiring various language skills simultaneously. Such value-based education may be a contributing factor towards global peace

Automated Deep Learning Models for the Analysis of Biological Microscopy Images

Recent advances in artificial intelligence (AI) and deep learning are having a tremendous impact on diverse application domains. It would be surprising if the domain of digital microscopy in biology would not benefit from this. This thesis addresses problems that are encountered when analyzing microscopic images with current methods from artificial intelligence, in particular detecting, segmenting and classifying cells, organelles, etc., in microscopic images. It appears that specialized knowledge is needed to ensure success with AI. For example, current AI only works well with a massive amount of samples, for which the desired answer is given. Individual cells would need to be outlined using the mouse and obtain a label (annotation) in the process, for each new type of biomedical research goal. This is too impractical. We present a method from AI that tries to circumvent this stumbling block: Self-supervised learning (SSL) to learn organoid segmentation. The data consists of microscopy images of organoid images provided by our academic hospital. We compared U-net/ResNet with our SSL and traditional supervised learning on labeled images. Surprisingly, the SSL results were even better than relying on the human-labeled samples only. Other problems addressed in this project concern the detection of overlapping objects in an organoid dataset and the classification of organelles within yeast cells using Mask-RNN and Yolo4. In order to help the biological researchers, an 'e-Science' website was developed where they can submit images for segmentation or classification. This website has been extended with other functions related to biological data analysis, e.g., the classification of FASTA codes for protein molecules

Automated Deep Learning Models for the Analysis of Biological Microscopy Images

Recent advances in artificial intelligence (AI) and deep learning are having a tremendous impact on diverse application domains. It would be surprising if the domain of digital microscopy in biology would not benefit from this. This thesis addresses problems that are encountered when analyzing microscopic images with current methods from artificial intelligence, in particular detecting, segmenting and classifying cells, organelles, etc., in microscopic images. It appears that specialized knowledge is needed to ensure success with AI. For example, current AI only works well with a massive amount of samples, for which the desired answer is given. Individual cells would need to be outlined using the mouse and obtain a label (annotation) in the process, for each new type of biomedical research goal. This is too impractical. We present a method from AI that tries to circumvent this stumbling block: Self-supervised learning (SSL) to learn organoid segmentation. The data consists of microscopy images of organoid images provided by our academic hospital. We compared U-net/ResNet with our SSL and traditional supervised learning on labeled images. Surprisingly, the SSL results were even better than relying on the human-labeled samples only. Other problems addressed in this project concern the detection of overlapping objects in an organoid dataset and the classification of organelles within yeast cells using Mask-RNN and Yolo4. In order to help the biological researchers, an 'e-Science' website was developed where they can submit images for segmentation or classification. This website has been extended with other functions related to biological data analysis, e.g., the classification of FASTA codes for protein molecules

Agricultural statistics and space images in Madagascar : estimation of second rice season acreage in a sub-prefecture

Space images are of great interest, particurlarly for acreages estimation of crops in agricultural statistics. But their use in an operational way can't be done without some problems, mainly those about costs, for developping countries. So must be found a way of reducing these three kinds of costs. It means that the appropriate method must be able to supply results on some area, even if it is not covered by all the images used. The author's approach tends to this, and comprises the following steps : 1) selection of a representative image, 2) selection of a date where most of the crops of a year are present, 3) stratification of the studied area, 4) construction of parameters for patterns (crops) recognition, 5) estimation of crops acreage in some are