In the financial year 2022, around 1.27 million self-help groups (SHGs) were digitized under Project EShakti. This was a slight increase from the previous year. Project EShakti was conceptualized with the aim of digitizing financial and non-financial data of self-help groups. The SHG-BLP was developed by National Bank for Agriculture and Rural Development (NABARD) to provide financial services to the unattended and undeserved. Under this program, banks were allowed to open savings accounts for self-help groups (SHGs). Self-help groups are registered or unregistered entities comprising 15 to 20 members from low-income families, usually women.

Under the Self Help Group-Bank Linkage Program in India, commercial banks account for 58 percent of the Self-Help Groups' linked savings, as of the financial year 2022. In comparison, the regional rural banks account for 30 percent of the linked savings.

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Under the Self Help Group-Bank Linkage Program in India, commercial banks accounted for 62 percent of the loans outstanding for Self-Help Groups, as of financial year 2022. In contrast, the regional rural banks accounted for 30 percent of loans outstanding.

Open access data set for the manuscript "High Average Power Second-harmonic Generation of a CW Erbium Fiber MOPA" to be published in Photonics Technology Letters.

This line chart displays lowest price by date and is filtered where the stock is SHG.F. The data is about stocks per day.

This study was designed to investigate the mediation effects of social empowerment (SE) in the relationship between perceived social support (PSS) and life satisfaction (LS) in women self-help group members. Also, this research attempted to understand the moderating effect of decision making (DM) and external communication (EC) on the relationship between the constructs. To achieve the above objective, the primary data were collected from the self-help group women members by using an existing scale. In this survey, 333 participants who are members of self-help group completed the questionnaire and considered for the study. The study is non-experimental and survey-based, with no interventions or manipulations involved. In line with ethical guidelines, we obtained informed consent directly from each respondent before their participation. The path coefficient values, t-statistics and P-Values confirmed the positive relationship between PSS->LS; PSS->SE & SE->LS in women self-group members. PLS structural equation modelling estimated by the bootstrap method revealed that SE partially mediates the relationship between PSS & LS. With regard to the interaction effect, the slope analysis and f2 effect size confirmed the moderating effect of EC in the relationship between PSS -> LS & SE -> LS. Methods For the analyses, we used a sample of self-help group (SHG) women members (N=333). Women self-help group members of three major self-help groups such as Navodaya, Sthri Shakthi, and Shri Kshetra Dharmasthala Rural Development (SKDRD), were considered in the study. The respondents were selected using judgemental non-probability sampling. The sampling unit was the SHG in the Southern Karnataka, India. Data were collected through a survey questionnaire, and the survey sessions were arranged at SHG's regular weekly meetings. The investigator personally monitored the completion of the questionnaire. Informed consent was obtained from the SHG members individually. Participation in the survey was voluntary. Each member was allowed 15 minutes to complete the survey. After completing the survey, the investigator collected the questionnaire individually. The datasheet contains two sections. Demographic variables were captured through categorical scales and study variables were based on 5-item Likert scales where 5 =strongly agree, 4= agree, 3= neutral, 2= disagree, 1= strongly disagree. Items with negative intentions were coded reversely. There was no missing data, outliers and data transformations happened.

Data in table tells us about the physical and financial progress under NRLM. it provides details like Progress up to 31st March, 2014 since inception of NRLM, Progress during the year 2014-15 to 2017-18(up to june'17). Table has categorised information under financial progress, physical progress, SHGs promoted, disbursal of revolving fund to SHGs, disbursal of community invested fund to SHGs.

Note: Data up to March, 2013.

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Abstract

Poverty reduction via formation of community based organizations is a popular approach in regions of high socio-economic marginalization, especially in South Asia. The shortage of evidence on the impacts of such an approach is an outcome of the complexity of these projects, which almost always have a multi-sectoral design to achieve a comprehensive basket of aims. In the current research, we consider results from a rural livelihoods program in Bihar, one of India’s poorest states. Adopting a model prevalent in several Indian states, the Bihar Rural Livelihoods Project, known locally as JEEViKA, relies on mobilizing women from impoverished, socially marginalized households into Self Help Groups. Simultaneously, activities such as micro-finance and technical assistance for agricultural livelihoods are taken up by the project and routed to the beneficiaries via these institutions; these institutions also serve as a platform for women to come together and discuss a multitude of the socio-economic problems that they face. We use a retrospective survey instrument, coupled with PSM techniques to find that JEEViKA, has engendered some significant results in restructuring the debt portfolio of these households; additionally, JEEViKA has been instrumental in providing women with higher levels of empowerment, as measured by various dimensions.

In the current research, we consider a multi-sectoral approach which closely resembles the APDPIP design. We take a close look at the impacts of a rural poverty reduction program in Bihar, one of India’s poorest states. This program JEEViKA, focusses on building Self Help Groups (SHGs) of marginalized women; these groups are then federated into higher order institutions of such women at the village and local level. Cheap credit for a variety of purposes, technical assistance for various livelihood activities and encouraging awareness about various public services are the key agendas of this program. However, due to the very nature of JEEViKA’s target population, and given Bihar’s vicious income and gender inequality, the potential for impacts on women’s empowerment exists. A retrospective survey instrument, coupled with ‘Propensity Score Matching’ methods are used to estimate the impacts.

The results from the survey point out that JEEViKA has played an instrumental role in restructuring the debt portfolio of beneficiary households; households that have SHG members have a significantly lower high cost debt burden, are able to access smaller loans repeatedly and borrow more often for productive purposes, when compared to households without SHG members. Since JEEViKA works by mobilizing marginalized women into institutional platforms, such women demonstrate higher levels of empowerment, when empowerment is measured by mobility, decision making and collective action. Finally, we see some effects on the asset positions, food security and sanitation preferences of beneficiary households. It is worth pointing out here that the extent and significance of the results on debt portfolio and empowerment are robust to various matching modules and various specifications of the matched sample. The results on the other dimensions are subject to specifications or matching modules.

This brings out to the point about the timeline of these interventions and the materialization of impacts. In the context of such iterative, multi-sectoral poverty reduction approach, a well_x0002_designed research question must be able to identify the goals that a project should have achieved, given the time-line of that evaluation; the extent of such achievements are only a part of the evaluation agenda. The short review provided above provides some clues that a regular evaluation horizon of 2/3 years may be insufficient time to observe higher order effects, especially since actual benefits happen only after poor are mobilized into institutions and institutions are federated into higher-order institutions; indeed, the village-level institution, the Village Organization, which is made of 15 SHGs on an average, becomes functional 8-10 months after JEEViKA enters a village for the first time. The retrospective nature of the survey instrument also rules out any meaningful comparison of consumption or income levels between treatment and control areas.

Analysis unit

Household

Sampling procedure

The survey was administered to 10 randomly selected households from the target hamlets in all 200 project and 200 non-project villages; we can assume that had caste compositions changed significantly since 2001 in either the selected project or non-project villages, this should be reflected in the sample statistics. It is to be noted that the survey team did not have a beneficiary list for the treatment villages; thus the selection of interviewed HHs were truly random, and not a sample of beneficiary HHs only. The details on the questionnaire and selection of villages to survey are discussed at greater lengths in the Section 3 of the survey report - Data & Identification Strategy. The report is available for download under the Downloads section.

Mode of data collection

Face-to-face [f2f]

Research instrument

An identical survey instrument covering several broad areas on socio-economic indicators was administered to each of the 4000 households. The instrument had two broad modules; the general module was administered to a responsible adult (preferably HH head), and the women’s module was administered to an ever married adult woman. The general module collected economic information focused on asset ownership, debt portfolio, land holdings, savings habit and food security condition; social indicators attempting to capture changes in women’s empowerment focused on women’s mobility, decision making and networks were part of the women’s module. The demographic profile of each household was captured by an appropriate household roster and caste-religion profile; in addition, a livelihood roster was also administered. Given the retrospective nature of the study, questions on certain indicators were designed to capture the levels at end 2007, along with the current level. However for other indicators, like debt portfolio, questions for end 2007 levels were not asked since the chances for incorrect responses are considerable.

Raw data files used in the "Synthesis and functionalisation of biodegradable Second Harmonic Generation nanoprobes for cell targeting" manuscript.

The spatiotemporal assessment of tissue dynamics after the introduction of disruptive factors is crucial for evaluating their impact and for developing effective countermeasures. Here, we report a 4D-spatiotemporal imaging approach using second harmonic generation (SHG) imaging microscopy, enabling an advanced time-resolved analysis of three-dimensional tissue features. This is of particular interest as topical administration of drugs during spinal surgeries is a standard practice for preventing and treating postoperative complications like infections. Local drug concentrations on tissue are high in these scenarios, and given the dura’s role as a protective barrier for the brain and spinal cord, potential drug-induced damage should be evaluated critically. By employing 4D-SHG imaging, we gained detailed insights into changes in dimensional properties of thin section samples, namely, width, height, and volume, as well as into alterations within the hierarchic structure of collagen. The latter thereby allowed us to postulate a mode of action, which we attributed for the herein investigated samples to the pH of the formulation.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Shinhan Financial Group (SHG): Riding the Korean Wave

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

The Figure 1c,d, 2b-f, 3b-g, 4b,c data generated in this study have been deposited.

Grading is as follows: N/A: not available, −: absence of fibrillar collagen, +: few fibrillar collagen, ++: great concentration of fibrillar collagen, +++: fibrillar collagen over the whole field of view.

Abstract

What do we know about incentives and norms in health bureaucracies and service delivery points at various levels of a state in India? For example, the logic of economic theory suggests that governments should be direct providers of services when there is a role for attracting intrinsically motivated agents (Francois, 2000), but we have no empirical evidence on integrity and public service motivation among state personnel across different cadres of service delivery. The available research has focused on documenting evidence of weak incentives and low accountability for service delivery in the public sector, and thence on evaluating interventions targeted at strengthening incentives, such as making some part of pay conditional on performance indicators (for example, Singh and Masters, 2017). But what is available is barely scratching the surface of knowledge needed to help reform leaders think about how to structure government bureaucracies and assign tasks to leverage intrinsic motivation and to reduce reliance on high-powered incentives. Even when increasing the power of incentives has been shown to “work”, the authors of those findings concede that implementing optimal incentive contracts at scale can place significant demands on state capacity (Muralidharan and Sundararaman, 2011). There is even less evidence available about the incentives and motivation of mid-level bureaucrats within the health system, compared to a growing body of research on frontline providers such as doctors and community health workers. Finally, the logic of economic theory, and growing international evidence in support of it, further suggests that politics casts a long shadow on culture in the bureaucracy, but we have no rigorous evidence for this claim for India.

To address these knowledge gaps we designed and implemented a complex survey of multiple types of respondents across districts, blocks (administrative sub-units within districts) and village governments (Gram Panchayats or GPs) in Bihar, one of the poorest states of India and with some of the worst statistics of child malnourishment.

Geographic coverage

16 study districts, from among the 38 of Bihar, selected to represent the 9 administrative divisions of Bihar: Patna, Tirhut, Darbhanga, Kosi, Purnia, Saran, Bhagalpur, Munger, Magadh

Analysis unit

Households Health Staff Politicians Bureaucrats

Universe

Citizens, Within the category of citizens, the survey additionally targeted office-bearing members of women’s Self Help Groups (SHG) under a rural livelihoods program in Bihar known as Jeevika. Politicians Bureaucrats Public Providers of Health Services

Kind of data

Sample survey data [ssd]

Sampling procedure

Budget and implementation constraints required us to select a sample of districts rather than covering all 38 districts of Bihar. At the same time, we needed a large sample to be representative of the diversity within the state, and allow us to capture some variation across district-level institutional characteristics. These constraints led us to determine 16 as the number of districts in which to undertake the survey. The purposive selection of which 16 study districts, from among the 38 of Bihar, was made using the following criteria:

• represent the 9 administrative divisions of Bihar: Patna, Tirhut, Darbhanga, Kosi, Purnia, Saran, Bhagalpur, Munger, Magadh • represent both border and interior districts • select "old" and "new" districts (those which were created after 1991) because district age might matter in interesting ways for their capacity to deliver (to be discussed further) • select districts which might vary in historical institutions that shape norms.

We first explored an established literature in India which finds that there are persistent effects on current service delivery of the long-gone historical institution of the Zamindari system of land revenue (Pandey, 2010; Banerjee and Iyer, 2005). However, since all of the districts of Bihar are classified as belonging to the Zamindari system, we could not use this established measure of historical institutions in selecting the study districts. We then turned to a newer literature which examines the early construction of railway lines in the late 1800s in the United States and India as a potential source of institutional variation (Donaldson, 2018; Donaldson and Hornbeck, 2016; Atack, Haines and Margo, various). The 16 districts in our study include those through which passed the first railway lines in Bihar, and those that received railway lines a decade or so later.

Within each of the 16 districts, 4 blocks were selected using a random number generator,after stratifying by proximity to the main railway line. Within each block, 4 Gram Panchayats (GPs) were selected using a random number generator. However, in one block each in the districts of Lakhisarai and Buxar, 3 GPs instead of 4 were selected because the sampling protocol required a sufficient number of replacement respondents to be available, and these districts only had 3 GPs fulfilling the replacement requirement (more details in section on Respondents below). This yields a sample of respondents drawn from 16 districts, 64 blocks from within those districts, and 254 Gram Panchayats (GPs) from within those blocks.

Citizen Survey: The citizen survey was aimed at respondents from 16 households residing in each GP area. The survey firm was provided with a list of respondents (with replacements) drawn randomly from the electoral rolls available of all voting-age adults in Bihar's population. The target sample size is thus 4064 citizens (16 each from 254 GPs). Within the category of citizens, the survey additionally targeted office-bearing members of women's Self Help Groups (SHG) under a rural livelihoods program in Bihar known as Jeevika. However, we had no lists available with names of SHG leaders of the village-level organziations across GPs. In the absence of these lists, we relied on the survey firm to ensure that enumerator teams would identify SHG leaders during their field-work. The data from SHG leaders that has been provided to us is thus subject to a greater than usual caveat: the risk of whether the enumerator teams accuratelyidentified and obtained interviews with the targeted SHG respondents. The instructions provided to the survey teams was to ask the GP Mukhiya and other GPlevel respondents (such as the ANM, ASHA and AWW) about the GP-level federated organzation of all the SHGs across the GP's communities to identify its President,Secretary and Treasurer. That is, 3 SHG leaders were targeted for each GP, for a total sample of 762 (3 each from 254 GPs) SHG leaders.

Politician Survey: Lists were provided to the survey teams of all incumbent Mukhiyas to be interveiwed, and a random selection (with replacement) of 3 Ward members and 3 candidates from among those who contested the previous GP elections of 2016. The targeted sample size of GP politicians is thus 1778 (7 each from 254 GPs)

Bureaucrats: The survey firm was responsible for identifying and interviewing the respondents holding these positions. The final data submitted by the survey firm contains 293 respondents in supervisory or management positions, including: 13 Civil Surgeons,11 Chief Medical Officers (including 4 who were in Acting capacity), 23 Superintendents (including 13 in Deputy or Acting capacity), 9 District Programme Officers- NHM, 4 District RCH and Immunization In-charge, 7 District Community Mobilizers, 58 MOICs, 58 Acting Facility Incharge, 43 Block Program Managers-NHM, 29 Block RCH Programme officers, and 35 Block Community Mobilizers.

Public Providers of Health Services: The survey team was provided a list (with replacements) of 3 AWW workers to interveiw per GP, for a targeted sample of 762 AWW respondents. The survey team was provided with a list of randomly selected candidates for the categories of respondents for all the PHCs and higher-level health facilities (such as District Hospitals) across the 64 blocks of the study area.

Sampling deviation

Block Level: The survey firm was responsible for identifying the block-level politicians targeted to be interviewed. The targeted sample size of Block-Panchayat (Panchayat Samiti) elected members’ is 128 respondents (2 each from 64 blocks). The 57 MLAs across the 64 blocks of the study area were also identified by the survey firm. However, because of problems of reaching politicians at a time that was close to the 2019 elections in India, the survey firm was able to complete interviews with only 39 MLAs (of the targeted 57) , and with 119 Panchayat Samiti members (of the targeted 128).

District Level: The survey firm was responsible for identifying the MPs from constituencies within the 16 study districts, and the 32 respondents of the District-Panchayat (Zilla Parishad). Again, because of problems reaching political leaders at election time, the survey firm was able to interviewonly 9 MPs, and 28 Zilla Parishad members.

Public Providers of Health Care Services: The survey team was provided with a list of randomly selected candidates for the categories of respondents for all the PHCs and higher-level health facilities (such as District Hospitals) across the 64 blocks of the study area. However, the survey team reports substantial difficulty in adhering to this list because the personnel were not found at the health facilities. The survey team was not able to reach a random sample of providers appointed at these positions.

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Abstract

This Impact Evaluation (IE), a randomized controlled trial, tested the effectiveness of using the women’s self-help group platform of Bihar’s JEEViKA program to address the immediate and underlying determinants of undernutrition among women and children andimprove nutrition outcomes. JEEViKA is a rural livelihoods project, supported by the World Bank in Bihar that supports self-helpgroups (SHGs) – savings and credit-based groups of about 15-20 women, mostly targeted towards those from poor households –with the aim of improving their livelihoods and enhancing household incomes. The JEEViKA Multisectoral Convergence (JEEViKA-MC)pilot, developed by the Bihar Rural Livelihoods Promotion Society with technical support from the World Bank, was designed to leverage these SHGs to provide two complementary sets of interventions—health and nutrition behavior change communication (BCC) to improve women’s knowledge and household practices, and efforts to improve service access through convergence —alongside the existing core package of JEEViKA. The core JEEViKA interventions include: the organization of rural women into SHGs,training and strengthening the SHGs, federation of the SHGs into Village Organizations (VOs) and Cluster-Level Federations (CLFs),bank linkages for the SHGs and their federations, and improvement of livelihoods and women’s empowerment through extensionservices and related interventions. Within this target population, households with young children, mothers of young children, andpregnant women were the primary focus of the JEEViKA-MC pilot.

The IE assessed changes household knowledge and behaviours, as well as in nutrition outcomes of women and children in the pilot areas as compared to areas that did not receive the two additional interventions. Two rounds of panel data - at baseline conducted in April–May 2016, and at endline conducted in October - November2018, of women with children 6 - 23 months of age at baseline, were used to assess the following outcomes of the JEEViKA MC pilotas compared to non-intervention areas, i.e., areas with only the core JEEViKA interventions. - The primary outcomes assessed werewomen’s body mass index (BMI) and reported dietary diversity for children aged 6 -23 months. - Secondary outcomes for womenincluded reported dietary diversity, and health, hygiene, and nutrition knowledge and practices. For children, secondary outcomesincluded anthropometric outcomes, infant and young child feeding practices, and morbidity among children. For households,outcomes included household food security, use of government programs as well as JEEViKA food security-related services, and adoption of hygiene and sanitation practices (including handwashing and use of latrines).

The International Food Policy ResearchInstitute (IFPRI) was contracted to conduct the IE.

Geographic coverage

While the JEEViKA program covers the majority of districts in Bihar, the JEEViKA-MC pilot interventions were introduced in 12 village administrative units, called Gram Panchayats (GPs) of Saur Bazaar, Sonbarsa Raj, and Pattarghat blocks of Saharsa district of Bihar.

Sampling procedure

The impact evaluation used a cluster-randomized controlled trial design. It was conducted across three pilot implementation blocks that had mature self-help groups (i.e. groups formed in 2011). Of the 24 available comparable village administrative clusters, called gram panchayats (GPs), allocated 12 to receive the JEEViKA-MC pilot treatment interventions and another 12 as a comparison group. Cluster randomization was done through simple random sampling. The total number of 120 villages were selected, 60 in each arm. Complete listing of all households in each of these 120 villages was obtained. From this household listing, 25 households were selected as per village that had a woman who: • belonged to a household where at least one woman was a member of a JEEViKA SHG. • had at least one child age 6–23 months. The sampling of 25 households allowed for oversampling of 5 households per village, to ensure that 20 households per village responded to the survey. Thus, the total sample was 20 (HHs per village) * 5 (villages per Gram Panchayat) * 24 (Gram Panchayats) = 2,400 respondents in total: 1,200 in the control and 1,200 in the treatment arm of the study.

For the baseline survey, 5 villages were chosen at random from each of the 24 Gram Panchayats. In cases where there were fewer than 5 villages per Gram Panchayat all villages in the Gram Panchayat were included in the survey and the number of households per Gram Panchayat was increased.

The same households were surveyed during the endline as well.

Mode of data collection

Face-to-face [f2f]

Research instrument

The full set of questionnaires are available for download under the downloads tab.

Response rate

The baseline survey was carried out in 131 villages. 2,246 households were interviewed with respondent women who met the sampling criteria—1,164 in the treatment areas and 1,082 in the comparison areas. At endline, 2,246 baseline households were revisited and 2119 could be re-interviewed (those with baseline respondent women available), for an attrition rate of only 5.65 percent. The most common reasons for attrition among the respondents were migration for work, permanent relocation, temporary absence from the village, and death.

Anthropometric data was collected for 2,116 respondent women from the baseline, re-interviewed the mothers of 2,084 index children (35 were not alive), and anthropometric data for 2,006 index children from the baseline was collected. In addition to the index child, if the mother had given birth to one or more children since the baseline, at endline information on the youngest of those children between the ages of 6 and 23 months was collected. There were 805 such youngest children, and anthropometric data were available for all of them, with no dates of birth missing.

See associated journal article and supplementary information.

The fitting parameters pertaining to specific regions highlighted in Fig. 3 of a red aplanospore were found. R2 values for SHG fits were at least 0.94 and R2 values for THG fits were at least 0.92.aRTHG1 was fixed between -2 and 2, and RTHG2 was set as a free fitting parameter.PIPO SHG and PIPO THG fitting parameters of a red aplanospore of Haematococcus pluvialis.