Proxy Indicators Research Articles

Relationships of Magnetic Properties and Heavy Metals Content of Guano in Bat Cave, South Sulawesi, Indonesia

Bat Cave is one of the caves with guano deposits in the Rammang-Rammang karst area, South Sulawesi, Indonesia. The guano deposits can indicate environmental changes in the cave. This study aims to analyze the magnetic properties and correlation between magnetic susceptibility and heavy metal content in guano. Sampling was carried out in Bat Cave, South Sulawesi, Indonesia, and magnetic susceptibility, XRD (mineralogy analysis), and XRF (heavy metal content analysis) were measured. The results showed that the guano sample contained superparamagnetic grains and stable single domain (SP-SSD) measuring -8m3/kg. The location of caves in karst areas and climate change affect the magnetic grains. The Pearson correlation coefficient analysis results showed that magnetic susceptibility had a negative correlation with the heavy metal content of Fe. Meanwhile, Fe has a positive correlation with the content of other heavy metals such as Cu, Zr, and Nb. Thus, magnetic susceptibility has the potential as a proxy indicator to detect the presence of heavy metals.

Localizing Hydrological Drought Early Warning Using In Situ Groundwater Sensors

AbstractDrought early warning systems (DEWSs) aim to spatially monitor and forecast risk of water shortage to inform early, risk‐mitigating interventions. However, due to the scarcity of in situ monitoring in groundwater‐dependent arid zones, spatial drought exposure is inferred using maps of satellite‐based indicators such as rainfall anomalies, soil moisture, and vegetation indices. On the local scale, these coarse‐resolution proxy indicators provide a poor inference of groundwater availability. The improving affordability and technical capability of modern sensors significantly increases the feasibility of taking direct groundwater level measurements in data‐scarce, arid regions on a larger scale. Here, we assess the potential of in situ monitoring to provide a localized index of hydrological drought in Somaliland. We find that calibrating a lumped groundwater model with a short time series of groundwater level observations substantially improves the quantification of local water availability when compared to satellite‐based indices. By varying the calibration length, we find that a 5‐week period capturing both wet and dry season conditions provides most of the calibration capacity. This suggests that short monitoring campaigns are suitable for improving estimations of local water availabilities during drought. Short calibration periods have practical advantages, as the relocation of sensors enables rapid characterization of a large number of wells. These well simulations can supplement continuous in situ monitoring of strategic point sources to setup large‐scale monitoring systems with contextualized and localized information on water availability. This information can be used as early warning evidence for the financing and targeting of early actions to mitigate impacts of hydrological drought.

Leveraging genetic discoveries for sleep to determine causal relationships with common complex traits.

Sleep occurs universally and is a biological necessity for human functioning. The consequences of diminished sleep quality impact physical and physiological systems such as neurological, cardiovascular, and metabolic processes. In fact, people impacted by common complex diseases experience a wide range of sleep disturbances. It is challenging to uncover the underlying molecular mechanisms responsible for decreased sleep quality in many disease systems owing to the lack of suitable sleep biomarkers. However, the discovery of a genetic component to sleep patterns has opened a new opportunity to examine and understand the involvement of sleep in many disease states. It is now possible to use major genomic resources and technologies to uncover genetic contributions to many common diseases. Large scale prospective studies such as the genome wide association studies (GWAS) have successfully revealed many robust genetic signals associated with sleep-related traits. With the discovery of these genetic variants, a major objective of the community has been to investigate whether sleep-related traits are associated with disease pathogenesis and other health complications. Mendelian Randomization (MR) represents an analytical method that leverages genetic loci as proxy indicators to establish causal effect between sleep traits and disease outcomes. Given such variants are randomly inherited at birth, confounding bias is eliminated with MR analysis, thus demonstrating evidence of causal relationships that can be used for drug development and to prioritize clinical trials. In this review, we outline the results of MR analyses performed to date on sleep traits in relation to a multitude of common complex diseases.

The role of social activity in the association between socioeconomic status and physical health in Tehran University of Medical Sciences employees` cohort study: a structural equation modeling

ABSTRACT Socioeconomic status (SES) is often considered a major predictor of health outcomes. This study aimed to determine the role of social activity in the association between SES and physical health among Tehran University of Medical Sciences Employees’ Cohort (TEC) study. In this cross-sectional design, we used the data of the enrolment phase of the Tehran University of Medical Sciences (TUMS) cohort study on 4461 employees. The latent variable of this study was the composite SES-index, which is a combination of assets, social activities, and education. A self-reporting questionnaire was used to measure the physical health conditions of the respondents. The relationship between variables was examined using the structural equation modeling (SEM) in STATA-14. The results showed that 2706 respondents (60.65%) were female and the mean age of all participants was 42.29 years (SD = 8.71, range: 19 to 74). The SEM results showed that the composite SES-index had a significant effect on physical health (β = −0.21, SE = 0.017, p < 0.001, 95٪ CI = [−0.25 to −0.18]). Physical health also exhibited the greatest association with the social activity index (β = −0.18, SE = 0.014, p < 0.001, 95٪ CI = [−0.21 to −0.15]). In addition, the social activities, assets, and education explained 53%, 50%, and 43% of the estimated variance of the composite SES-index, respectively. This study demonstrated that the social activity index could be one of the best proxy indicators of objective SES when we intend to assess the association between SES and physical health.

Trend analysis and Applicability of Fuzzy Time Series Models to Night-time Luminosity Data of Uttarakhand state, India

Objectives: Application of trend detection and fuzzy time series models to predict the growth of Uttarakhand state using night-Time Lights (NTL) dataset (Visible Infrared Imaging Radiometer Suite (VIIRS) night-time lights). Methods: In this work, we propose a methodology to analyze trends and estimate different fuzzy time series models for prediction in the context of forecasting the economic growth of a low-earning income Uttarakhand state. Mann- Kendall tests are used for performing trend analysis of Uttarakhand (India) using night-time luminosity data sets. Forecasting methods based on fuzzy time series models have been presented to deal with uncertainties induced by ambiguities, vagueness, and some other non-probabilistic factors, and have widely been employed in many problems domains. The simulation is done on the Jupyter Notebook platform using night-time luminosity datasets. Findings: We conclude that Uttarakhand and Himachal Pradesh show positive growth in trends for their night-time lights monthly average intensity with magnitude of 0.002182 and 0.002558 respectively. Night time luminosity database can be used as a proxy indicator for the economic growth of the Uttarakhand state as the correlation between NTL time series data of Uttarakhand and its Gross Development Product (GDP) is 0.795641021. Fuzzy time series models can also be used to predict the growth of the Uttarakhand state and the High Order Fuzzy Time Series model gives the accuracy metrics of root mean square (RMSE) as 0.11. Novelty: No previous research work is performed on trend analysis and prediction of growth of a Uttarakhand state using night-time luminosity data sets. Keywords: Fuzzy Systems; Fuzzy Time Series; Prediction; Night time luminosity; Satellite image

Self-Admitted Technical Debt and comments’ polarity: an empirical study

Self-Admitted Technical Debt (SATD) consists of annotations—typically, but not only, source code comments—pointing out incomplete features, maintainability problems, or, in general, portions of a program not-ready yet. The way a SATD comment is written, and specifically its polarity, may be a proxy indicator of the severity of the problem and, to some extent, of the priority with which it should be addressed. In this paper, we study the relationship between different types of SATD comments in source code and their polarity, to understand in which circumstances (and why) developers use negative or rather neutral comments to highlight an SATD. To address this goal, we combine a manual analysis of 1038 SATD comments from a curated dataset with a survey involving 46 professional developers. First of all, we categorize SATD content into its types. Then, we study the extent to which developers express negative sentiment in different types of SATD as a proxy for priority, and whether they believe this can be considered as an acceptable practice. Finally, we look at whether such annotations contain additional details such as bug references and developers’ names/initials. Results of the study indicate that SATD comments are mainly used for annotating poor implementation choices (simeq 41%) and partially implemented functionality (simeq 22%). The latter may depend from “waiting” for other features being implemented, and this makes SATD comments more negatives than in other cases. Around 30% of the survey respondents agree on using/interpreting negative sentiment as a proxy for priority, while 50% of them indicate that it would be better to discuss SATD on issue trackers and not in the source code. However, while our study indicates that open-source developers use links to external systems, such as bug identifiers, to annotate high-priority SATD, better tool support is required for SATD management.

Do renewable energies contribute to enhancing environmental quality in Eastern Africa?

East Africa has enormous renewable energy potential, but only a small portion of it has been exploited, and little is known on its role in improving environmental quality. Thus, this study empirically examines the impact of renewable energy on the environment using ecological footprint (EF; positive indicator) and CO2 emissions (negative indicator) as proxy indicators for environmental quality in a panel of ten East African countries from 1990 to 2015. These indicators were chosen due to their potential impact in the environment. The work used the pooled mean group (PMG) as the main panel estimator to determine the impact while controlling non-renewable energy consumption, GDP per capita, and foreign direct investment (FDI). PMG has been used as it forces the long-run coefficients to be equal across all panel groups. The findings show that in the long run, there is a significant negative relationship between CO2 emissions and renewable energy consumption, as well as a significant positive relationship (with a low impact) between EF and renewable energy consumption, suggesting that renewable energy use enhances the area's environmental quality. Also, results indicate that non-renewable energy use degrades environmental quality in both metrics, whereas GDP degrades environmental quality through CO2 emissions and improves environmental quality through EF. This requires East African countries to focus a higher emphasis on accessible renewable energy sources to achieve quick and sustainable economic growth and minimize environmental effects. To accomplish this, strategic policies and legislation, as well as the promotion of green technology, are required.

Early developmental vulnerabilities following exposure to domestic violence and abuse: Findings from an Australian population cohort record linkage study

Early life exposure to Domestic Violence and Abuse (DVA) is associated with poor psychosocial and cognitive development in childhood. However, most prior research uses mother-reported involvement in DVA as a proxy indicator of child exposure; studies using direct measures of child exposure to DVA are scarce, especially among representative population-based samples. We address this gap by using longitudinal, population-based data from an Australian record linkage study of children to examine the associations between early life exposure to DVA and early childhood developmental vulnerability. Exposure to DVA was measured using police contact records for children involved in a DVA incident either as a victim or witness. Developmental vulnerability at school entry was measured using the Australian Early Development Census, providing indices of five broad domains of function and person-centred classes of developmental risk (referred to as ‘mild generalized risk’, ‘misconduct risk’, and ‘pervasive risk’, each compared to a group showing ‘no risk’). Children exposed to DVA showed significantly greater odds of developmental vulnerability on all five domains and were more likely to be members of the three developmental risk classes. Girls who were victims of DVA (OR = 1.65) had significantly poorer developmental outcomes than boys who were victims (OR = 1.26) within the domain of communication skills and general knowledge (d = 0.29 [SE = 0.16], p = .04). No other sex differences were found. These preliminary findings hold important implications for policy regarding the early intervention and implementation of support services for young children exposed to DVA.

A quantitative analysis of the localized administrative importance rating system and the selection of officials in Qing China

ABSTRACT Administrative districts during the Qing dynasty were rated according to the “Chong Fan Pi Nan” system, imposed on each province, prefecture, sub-prefecture, department and county. The classification distinguished between the need for appointment to “most important” posts (zuiyaoque), “important” posts (yaoque), “medium” posts (zhongque), and “simple” posts (jianque). In accordance with the importance rating system, the Qing court subsequently determined the sequence of officials necessary in each administrative unit as the appointments by the Emperor (qingzhique), the appointments by the Governor-General (tidiaoque), and the appointments by the Board of the Personnel (buxuanque), with the Emperor, Governors-General, and the Board of Personnel having the authority to select officials. In tracing and quantifying the “Chong Fan Pi Nan” system as well as the division into “most important” posts, “important” posts, “medium” posts, and “simple” posts, we can see how the Qing government used geographical information to target the deployment of limited bureaucratic resources based on locally-specific difficulties in governance. In addition, according to the statistics, it appears that “Chong Fan Pi Nan” as a proxy indicator reflects the spatial differences in terms of the disposition of local transportation, administrative affairs, tax collection, and local security. We can also observe that the Qing state intentionally promoted the weighting of frontier provinces to attract officials with better administrative abilities. This article examines how the administrative importance rating system influenced the origin, selection, and promotion of Qing officials by tracking the data of millions of officials in the newly established quantitative database of the Jingshenlu (Records of the Gentry). This study will provide a longue-term perspective for understanding the contemporary Chinese government’s official selection system.

Gender Prediction of Indonesian Twitter Users Using Tweet and Profile Features

The increasing use of social media generates huge amounts of data which in turn triggers research into social media analytics. Social media contents can be analyzed to explore public opinion on an issue or provide the insights reflecting proxy indicators towards real-world events. Understanding the demographics of social media users can increase the potential for applications of sentiment analysis, topic modeling, and other analytical tasks. To map demographics, we need to know the latent attributes of users, such as age, gender, occupation and location of residence. Since this attribute is not directly available, we need to do some inference from the social media data. This study aims to predict the gender attribute given a Twitter user account. We conducted experiments with several supervised classifiers with feature extraction, including the use of word embedding representations. The results of this study indicate that the combination of features extracted from Tweet contents and user profile structured data can predict the gender of Twitter users in Indonesia with accuracy above 80%.

Could mid-upper arm circumference be a valid proxy to the body mass index for elderly persons?

Introduction: In elderly persons, due to physiological, anatomical, and functional changes, body mass index (BMI) may not be suitable for the assessment of nutritional status. Mid-upper arm circumference (MUAC) can be a proxy indicator to identify underweight and overweight/obesity among elderly persons. This study aimed to estimate the correlation between MUAC and BMI, and the cutoffs for MUAC using receiver operating characteristic (ROC) analysis. Material and Methods: This survey was carried out in a resettlement colony of Delhi. The participants were residents of the area who were aged 60 years or older, and selected by a simple random sampling technique. The arm span, weight, and MUAC of the participants were measured. The correlation between MUAC and BMI for gender and age group was calculated. The ROC curve was also constructed. Results: A total of 946 eligible participants were enrolled. The correlation between MUAC and BMI was 0.67 (P &lt; 0.001) and 0.76 (P &lt; 0.001) among men and women, respectively. The MUAC cutoff for underweight was &lt;25 cm with a sensitivity of 68.8% and specificity of 84.9%. The area under the curve (AUC) was 0.84 (0.80–0.88). The MUAC cutoff for overweight/obesity was ≥27 cm with a sensitivity of 83.9% and specificity of 64.9%, and AUC was 0.78 (0.75–0.82). Conclusion: The MUAC of the participants increased as the BMI of the participants increased. MUAC cutoff was determined using the ROC curve for underweight and overweight/obesity among elderly persons.

Network Connectivity Under a Probabilistic Node Failure Model

Centrality metrics have been widely applied to identify the nodes in a graph whose removal is effective in decomposing the graph into smaller sub-components. The node--removal process is generally used to test network robustness against failures. Most of the available studies assume that the node removal task is always successful. Yet, we argue that this assumption is unrealistic. Indeed, the removal process should take into account also the strength of the targeted node itself, to simulate the failure scenarios in a more effective and realistic fashion. Unlike previous literature, herein a {\em probabilistic node failure model} is proposed, in which nodes may fail with a particular probability, considering two variants, namely: {\em Uniform} (in which the nodes survival-to-failure probability is fixed) and {\em Best Connected} (BC) (where the nodes survival probability is proportional to their degree). To evaluate our method, we consider five popular centrality metrics carrying out an experimental, comparative analysis to evaluate them in terms of {\em effectiveness} and {\em coverage}, on four real-world graphs. By effectiveness and coverage we mean the ability of selecting nodes whose removal decreases graph connectivity the most. Specifically, the graph spectral radius reduction works as a proxy indicator of effectiveness, and the reduction of the largest connected component (LCC) size is a parameter to assess coverage. The metric that caused the biggest drop has been then compared with the Benchmark analysis (i.e, the non-probabilistic degree centrality node removal process) to compare the two approaches. The main finding has been that significant differences emerged through this comparison with a deviation range that varies from 2\% up to 80\% regardless of the dataset used that highlight the existence of a gap between the common practice with a more realistic approach.

Grain Size and Sedimentary Sorting Characteristics of Atmospheric Dust in the Cele Oasis, Southern Margin of Taklimakan Desert

Grain size is a proxy indicator of airflow intensity and also provides a scientific basis for the prevention of dust hazards. However, the variations in grain size characteristics that occur during transport and deposition processes are seldom discussed. Here, atmospheric dust samples were collected before and after deposition in a sand–dust storm for grain size analysis. The results showed that the grain size distributions of the atmospheric dust were unimodal during transportation but always became bimodal after deposition. This indicates that the bimodal grain size distribution of the aeolian deposits was caused by sedimentary sorting. The coarse-grained component, which was between 20 and 200 μm, was mainly deposited during the sand–dust storm. Grain size may indicate the strength of the airflow field. The fine-grained component, which ranged in size from 0.4 to 20 μm, was mainly deposited after the sand–dust storm. This component can remain suspended in the atmosphere for a long period of time. Oasis shelterbelts can be used to reduce the fine-grained component of the dust aerosol through the interception of particles by foliage. The grain size variation found in this study from before to after sand–dust storm deposition deepens our understanding of the sediment sorting process.

Forecasting the Volume of Tourism Services in Uzbekistan

The aim of the present research is to assess the impact of factors such as welfare, infrastructure, security, and the environment on inbound tourism as well as to develop its forecast. Six proxy indicators of the above-mentioned factors were selected as variables, namely, welfare (real GDP per capita, life expectancy, consumer price index), infrastructure (passenger transportation volume), security (total recorded crimes), and the environment (CO2 emissions). We used a time series-univariate ARIMA model to forecast the inbound tourism in the Republic of Uzbekistan, and applied the ARDL model to assess the impact of lagged real GDP per capita on inbound tourism in both the short and long terms. The results of our research show that security and welfare significantly affect the inflow of foreign tourists in the country, along with the impact of the COVID-19 pandemic crisis, the effects of which are expected to persist beyond 2026.

Caring for Service Members Who Have Been Sexually Assaulted: The Military Health System.

ABSTRACTIntroductionReports of sexual assault (SA) in the U.S. Military have increased in recent years. Given the deleterious effects of military SA, there remains a need for large-scale studies to assess SA-related health care utilization among active duty service members (ADSMs). The present study, therefore, utilized Military Health System (MHS) data to determine the prevalence of SA-related care, sociodemographic characteristics of ADSMs receiving said care, and the type of provider seen during the initial SA-related health encounter.Materials and MethodsUtilizing the MHS Data Repository and Defense Enrollment Eligibility Reporting System, all ADSMs from the Air Force, Army, Navy, and Marine Corps during fiscal years (FY) 2016-2018 were identified. Those with an International Classification of Diseases diagnostic code related to SA during the study period were isolated. Descriptive statistics and multivariable logistic regression analyses were conducted. The study was exempt from human subjects review.ResultsA total of 1,728,433 ADSMs during FY 2016-2018 were identified, of whom 4,113 (0.24%) had an SA-related health encounter. Rates of SA-related health care encounters decreased each FY. Women (odds ratio [OR] = 12.02, P < .0001), those in the Army (reference group), and enlisted personnel (OR = 2.65, P < .0001) were most likely to receive SA-related health care, whereas ADSMs aged 18-25 years had lower odds (OR = 0.70, P < .0001). In addition, higher odds of SA-related care were observed among those identifying as American Indian/Alaskan Native (OR = 1.37, P = .02) and “Other” race (e.g., multiracial) (OR = 4.60, P < .0001). Initial SA-related health encounters were most likely to occur with behavioral health providers (41.4%).ConclusionsThe current study is the first large-scale examination of health care usage by ADSMs in the MHS who have experienced SA. Results indicated that rates of SA-related care decreased throughout the study period, despite the increasing rates of SA documented by the DoD. Inconsistent with previous research and DoD reports indicating that younger ADSMs are at the highest risk for SA, our study observed lower rates of SA-related care among those aged 18-25 years; additional research is warranted to determine if there are barriers preventing younger ADSMs from seeking SA-related health care. Behavioral health providers were most frequently seen for the initial SA-related encounter, suggesting that they may be in a unique position to provide care and/or relevant referrals to ADSMs who have experienced SA. The present study provides key insights about the prevalence of SA-related care within the MHS, not yet reported in previous literature, which could help inform MHS screening practices. The strengths of the study are the inclusion of the entire active duty population without the need for research recruitment given the utilization of de-identified TRICARE claims data. The study is limited by its use of health care claims data, general SA International Classification of Diseases codes as a proxy indicator for military SA, and lack of data on ethnicity. Future research utilizing MHS data should examine mental health outcomes following the documentation of SA and disruptions in SA-related care due to SARS-CoV-2.

Assessment of Nutritional Status and Anthropometry of Pre-School Children

Child growth is internationally recognized as an important indicator of nutritional status and health in populations. Nutritional status of children is a proxy indicator for assessing the entire population health status and one of the major predictors of child survival. Anthropometry is the scientific study of body measurements and in expensive and non-invasive methods for assessing children’s developing patterns. The literature found relationship between the age, gender, and anthropometric measures of young children. The present study was conducted to understand the relationship among the age, gender, and anthropometric indices across age and gender of pre-school children. The study sample was pre-school children attending Anganwadi in Tirupati town of Chittor district of Andhra Pradesh who were selected randomly. The results revealed that there was association between age, gender, and anthropometric data of pre-school children.

Japan’s pursuit of meritocracy, cosmopolitanism, and global rankings in higher education: a Bourdieusian interpretation

ABSTRACT Through the market-based conception of neoliberal performativity, an interlocking set of socio-economic agendas integrate higher education (HE) in state-level systems of production and accumulation. Within the scope of globalism, the capacity to develop competitive human capital emerges as a proxy indicator of achievement amongst institutions of higher learning. Through this elaborate symbolic structure, Japanese reforms aimed at bolstering “global” soft skills, including English, cosmopolitanism, and interculturality, function alongside an ideological arms race to enhance university rankings and individual investment in education. Invoking a Bourdieusian perspective, this conceptual inquiry suggests that stakeholders consider the secondary effects of asymmetrical efforts towards “élite” education, globalism, and world-class attainment, whereby accompanying policy reform propagates hegemony both locally and internationally. Additionally, the emergence of global soft skills as essential cultural capital challenges the supposed meritocracy of Japan’s HE system. Indeed, the “effort-based-reward” symbolic contract permeating much of the neoliberal discourse fails to account for the functional reality of class-distinguished taste. From this perspective, valuable cultural resources orientate towards a globally conscious, highly-credentialed middle-class privileged in social, economic, and cultural capital, thereby disadvantaging the majority of learners inevitably excluded from study at prestigious, brand-name universities.

Insights regarding mitochondrial DNA copy number alterations in human cancer (Review).

Mitochondria are the critical organelles involved in various cellular functions. Mitochondrial biogenesis is activated by multiple cellular mechanisms which require a synchronous regulation between mitochondrial DNA (mtDNA) and nuclear DNA (nDNA). The mitochondrial DNA copy number (mtDNA-CN) is a proxy indicator for mitochondrial activity, and its alteration reflects mitochondrial biogenesis and function. Despite the precise mechanisms that modulate the amount and composition of mtDNA, which have not been fully elucidated, mtDNA-CN is known to influence numerous cellular pathways that are associated with cancer and as well as multiple other diseases. In addition, the utility of current technology in measuring mtDNA-CN contributes to its extensive assessment of diverse traits and tumorigenesis. The present review provides an overview of mtDNA-CN variations across human cancers and an extensive summary of the existing knowledge on the regulation and machinery of mtDNA-CN. The current information on the advanced methods used for mtDNA-CN assessment is also presented.

Dominance hierarchy in groups of pregnant sows: Characteristics and identification of related indicators

Pig groups are known to be organised along dominance hierarchies. Little is known about the characteristics of the hierarchy in groups of sows and there are various methods to calculate dominance ranks within the hierarchy. Assessing dominance through recording agonistic interactions requires time-consuming observations. In order to compare the ranking methods, to investigate the sociometric characteristics of pig hierarchy such as stability, linearity and steepness, and to identify easy-to-record proxy indicators of hierarchy, four groups of 18 (± 2) gestating sows were studied. The sows were followed from 71 to 106 days of gestation. Starting from day 79, the access to the self-locking automatic feeders was limited to 6 h a day from to stimulate agonistic interactions. Each week, agonistic interactions were recorded during six continuous hours allowing the calculation of several dominance scores and sociometric variables. The restriction of feeding time increased the number of agonistic interactions but did not impact the proportion of agonistic behaviours with physical contact. The Dominance index, the David score and the Elo-score, used to rank the sow according to their dominance position, were highly inter-correlated (R > 0.92). The hierarchy was stable (stability index Stab = 0.996 ± 0.081), transitive (proportion of transitive triads Pt = 0.967 ± 0.035), quasi linear (Improved Landau index of linearity h’ = 0.701 ± 0.068) and moderately steep (real steepness Steep = 0.545 ± 0.085). The rankings obtained through Elo-score were highly correlated with the mean order feeding order (RS = 0.76), weakly correlated with the total number of feeder visits (RS = −0.21, P < 0.001) and not correlated with the daily mean time spent in the feeder (RS = 0.09, P = 0.10), or the total daily spent time in the feeder (RS = 0.10, P = 0.07). The rank was also highly negatively correlated to parity (RS = −0.83, P < 0.001) and to the weight at the end of gestation (RS = −0.75, P < 0.001). The results suggest that dominance hierarchies in stable groups of pregnant sows are stable and strong. Dominance rank of an individual can be estimated according to the feeding order, body weight or parity if there is enough variability in the group.

Rural Market Food Diversity and Farm Production Diversity: Do They Complement or Substitute Each Other in Contributing to a Farm Household's Dietary Diversity?

Majority of undernourished people live in rural Asia and Africa, and many of them are smallholder farmers and consume a significant amount of what they produce. This is specifically true in India. However, in the context of increasing commercial production systems, it is not well-known how much food is consumed from a particular food group that was purchased, what proportion of food is from the production of farm households, and how their diets change seasonally. Furthermore, whether the rural market food diversity complements or substitutes farm production diversity in household's diets is unknown. We employed a mixed-methods research design to answer these questions. The research was conducted in three villages in Telengana State. The results reveal that crop diversity has significantly declined from a highly-diverse production system to a less diverse one. The Food Consumption Score results show that on average own-farm production contributes 23% of food (mainly starchy staples), while market purchases contribute 77% of calories consumed (from more diverse and nutritious foods). Therefore, in the study, villages' market food diversity is more important, and it is complementary to own-farm production. However, our study shows that mere market access (the most widely used proxy indicator in the literature) does not guarantee the availability of diverse nutritious foods to households who use that specific market. This is because market food diversity varies from market to market and across seasons. Therefore, we proposed that in commercial production systems improving crop diversity, and strengthening rural markets, are needed. Moreover, incentivizing retail business and subsidizing nutritious and/or biofortified food in rural areas must be part of strategies to improve nutrition in rural India.