Farmers’ Perceptions of Commercial Insect-Based Feed for Sustainable Livestock Production in Kenya

The utilization of insect-based feeds (IBF) as an alternative protein source is increasingly gaining momentum worldwide owing to recent concerns over the impact of food systems on the environment. However, its large-scale adoption will depend on farmers’ acceptance of its key qualities. This study evaluates farmer’s perceptions of commercial IBF products and assesses the factors that would influence its adoption. It employs principal component analysis (PCA) to develop perception indices that are subsequently used in multiple regression analysis of survey data collected from a sample of 310 farmers. Over 90% of the farmers were ready and willing to use IBF. The PCA identified feed performance, social acceptability of the use of insects in feed formulation, feed versatility and marketability of livestock products reared on IBF as the key attributes that would inform farmers’ purchase decisions. Awareness of IBF attributes, group membership, off-farm income, wealth status and education significantly influenced farmers’ perceptions of IBF. Interventions such as experimental demonstrations that increase farmers’ technical knowledge on the productivity of livestock fed on IBF are crucial to reducing farmers’ uncertainties towards acceptability of IBF. Public partnerships with resource-endowed farmers and farmer groups are recommended to improve knowledge sharing on IBF.

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Large scale similarity search across digital reconstructions of neural morphology

10.1101/2021.12.17.473026 ◽

2021 ◽

Author(s):

Bengt Ljungquist ◽

Masood A Akram ◽

Giorgio A Ascoli

Keyword(s):

Similarity Search ◽

Large Scale ◽

Principal Component ◽

Software Tool ◽

Cell Types ◽

Brain Regions ◽

Morphological Comparison ◽

Data Set ◽

Qualitative Performance ◽

The Impact

Most functions of the nervous system depend on neuronal and glial morphology. Continuous advances in microscopic imaging and tracing software have provided an increasingly abundant availability of 3D reconstructions of arborizing dendrites, axons, and processes, allowing their detailed study. However, efficient, large-scale methods to rank neural morphologies by similarity to an archetype are still lacking. Using the NeuroMorpho.Org database, we present a similarity search software enabling fast morphological comparison of hundreds of thousands of neural reconstructions from any species, brain regions, cell types, and preparation protocols. We compared the performance of different morphological measurements: 1) summary morphometrics calculated by L-Measure, 2) persistence vectors, a vectorized descriptor of branching structure, 3) the combination of the two. In all cases, we also investigated the impact of applying dimensionality reduction using principal component analysis (PCA). We assessed qualitative performance by gauging the ability to rank neurons in order of visual similarity. Moreover, we quantified information content by examining explained variance and benchmarked the ability to identify occasional duplicate reconstructions of the same specimen. The results indicate that combining summary morphometrics and persistence vectors with applied PCA provides an information rich characterization that enables efficient and precise comparison of neural morphology. The execution time scaled linearly with data set size, allowing seamless live searching through the entire NeuroMorpho.Org content in fractions of a second. We have deployed the similarity search function as an open-source online software tool both through a user-friendly graphical interface and as an API for programmatic access.

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A Methodological Approach to Assess the Co-Behavior of Climate Processes over Southern Africa

Journal of Climate ◽

10.1175/jcli-d-18-0689.1 ◽

2019 ◽

Vol 32 (9) ◽

pp. 2483-2495 ◽

Cited By ~ 4

Author(s):

Kwesi A. Quagraine ◽

Bruce Hewitson ◽

Christopher Jack ◽

Izidine Pinto ◽

Christopher Lennard

Keyword(s):

Southern Africa ◽

Large Scale ◽

Southern Oscillation ◽

Methodological Approach ◽

Principal Component ◽

Self Organizing Maps ◽

Circulation Patterns ◽

Climate Forcings ◽

The Impact ◽

Precipitation And Temperature

Abstract The study develops an approach to assess co-behavior of climate processes. The regional response of precipitation and temperature patterns over southern Africa to the combined roles (co-behavior) of El Niño–Southern Oscillation (ENSO), Antarctic Oscillation (AAO), and intertropical convergence zone (ITCZ) is evaluated. Self-organizing maps (SOMs) classify circulation patterns over the subcontinent, and principal component analysis (PCA) is used to identify related patterns across the data. The tropical rain belt index (TRBI), a measure of the ITCZ, is generally in phase with the AAO but mostly out of phase with ENSO. The phases of AAO may enhance or suppress ENSO impact on the location and distribution of regional precipitation and temperature over the region. This understanding of the co-behavior of large-scale processes is important to assess the impact these processes collectively have on precipitation and temperature, especially under future climate forcings.

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Impact of Participation in Contract Farming on Smallholder Farmers’ Income and Food Security in Rural Benin: PSM and LATE Parameter Combined

Sustainability ◽

10.3390/su12030901 ◽

2020 ◽

Vol 12 (3) ◽

pp. 901 ◽

Cited By ~ 4

Author(s):

Odountan Ambaliou Olounlade ◽

Gu-Cheng Li ◽

Sènakpon E. Haroll Kokoye ◽

François Vihôdé Dossouhoui ◽

Kuassi Auxence Aristide Akpa ◽

...

Keyword(s):

Food Security ◽

Food Consumption ◽

Large Scale ◽

Smallholder Farmers ◽

Average Treatment Effect ◽

Farm Income ◽

Security Level ◽

Negative Consequences ◽

Contract Farming ◽

The Impact

Investigated in this work is the impact of contract farming participation on smallholder farmers’ income and food security in rice crop production in Northern Benin using 400 randomly selected rice farmer households. Unlike previous studies, we corrected for both observed and unobserved biases by combining propensity score matching (PSM) and the local average treatment effect parameter (LATE). The results showed significant negative consequences of partaking in rice contract farming. We found evidence of significant negative effects on rice production income at a 1% level. The more the rice farmers join in contract farming, the lower the farm income became. Decreased food consumption was also a result of contract farming participation for potential participants by a score of 60.64, placing their households at the food security status level of poor food consumption because the quantity and nutritional quality of the food consumed were inadequate. Contract farming is, therefore, not a reasonable policy instrument that can help farmers increase their income and improve their food security level in the Alibori Department, Benin if farmers do not diversify their crops. The necessary resources and economic environment are not yet in place to allow contract farming to take full advantage of its potential benefits. To prevent the wasting of scarce public resources, expanding contract farming would not be appropriate in marginal areas with markets and other infrastructure. Additional measures are needed for contract farming to be profitable for contracting actors and to ensure sustainability and the large-scale participation of farmers.

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Fault Localization Analysis for Multiple Fault Diagnosis in Multi-Station Assembly Systems

ASME 2007 International Manufacturing Science and Engineering Conference ◽

10.1115/msec2007-31139 ◽

2007 ◽

Author(s):

Posheng Tsai ◽

Kamal Mannar ◽

Darek Ceglarek

Keyword(s):

Manufacturing Systems ◽

Large Scale ◽

Fault Localization ◽

Principal Component ◽

Component Analysis ◽

Fault Isolation ◽

Data Driven ◽

Multiple Fault ◽

Critical Measure ◽

The Impact

Modern large scale multi-station manufacturing systems require effective variation reduction to improve the final assembly dimensional quality. One critical measure is to diagnose the fault in the process using knowledge-based root cause identification, which can be very challenging due to the complexity of the system. The paper investigates the need of data-driven fault localization to enhance the diagnosability within the context of multiple-fault scenario(s) in multi-station assembly processes where multivariate measurements are used. The paper proposes three types of fault-signal transmission in assembly system and illustrates the nature of structured noise. Moreover, the impact of structured noise on the diagnosability is illustrated on two major fault isolation methods, namely, Principal Component Analysis and Independent Component Analysis. We then propose to use data-driven fault localization to reduce the structured noise effect and enhance the diagnosability. A simulation case study based on automotive panel assembly model is provided to illustrate the impact of structured noise and the need for data-driven localization.

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How do farmland rental markets affect farmers’ income? Evidence from a matched renting-in and renting-out household survey in Northeast China

PLoS ONE ◽

10.1371/journal.pone.0256590 ◽

2021 ◽

Vol 16 (9) ◽

pp. e0256590

Author(s):

Ning Geng ◽

Zhifeng Gao ◽

Chuchu Sun ◽

Mengyao Wang

Keyword(s):

Land Reform ◽

Large Scale ◽

Household Survey ◽

Scale Economy ◽

Farm Income ◽

Agricultural Cooperatives ◽

System Reform ◽

Rental Market ◽

Rental Markets ◽

The Impact

Promoting farmland transfer through the farmland rental market is an essential instrument to achieve the scale economy of agricultural production in China. However, past literature on the land reform in China pays more attention to the renting-in household or the renting-out household, respectively, less to both types of households together. Using a large-scale survey of farm households in China, we examine the determinants of participation in the farmland rental market and quantify the impact of the rental market on farmers’ income. Findings show household off-farm income, family members’ part-time employment, agricultural subsidies, and participation in agricultural cooperatives significantly affect farmers’ participation in the farmland rental market. Participation in the farmland rental market significantly increases the income of renting-in households, while it decreases the income of renting-out households, which might result from the temporary lag effect of the land system reform.

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The Impact of dental wear on the analysis of morphological affinities based on dental non-metric traits

Dental Anthropology Journal ◽

10.26575/daj.v34i2.328 ◽

2021 ◽

Vol 34 (2) ◽

Author(s):

Daniel Fidalgo ◽

Veronica Wesolowski ◽

Mark Hubbe

Keyword(s):

Large Scale ◽

Principal Component ◽

Ordinal Scale ◽

State University ◽

Arizona State University ◽

Dental Wear ◽

Severe Wear ◽

Morphological Studies ◽

Individual Trait ◽

The Impact

Dental wear is described as a limitation to dental morphological studies, as it obscures important crown trait features, resulting in significant differences on trait frequencies, an essential component for estimating biodistances. However, the actual impact of dental wear on biological distances still requires further characterization. We explore the impact of dental wear on morphological affinities for Brazilian pre-colonial series in the context of worldwide reference series. Twenty crown traits were scored using the Arizona State University Dental Anthropological System, and dental wear was quantified as an ordinal scale between 1 (no wear) and 8 (crown eroded). Seven crown trait frequencies are significantly associated with dental wear (p<0.05), demonstrating its impact on their analysis. To explore this impact on biodistances, data was divided by wear categories (all teeth, low-wear, moderate/severe wear) and morphological affinities among series was compared through Euclidean distances, Mean Measure of Divergence, and Principal Component Analysis. Results show the impact of wear is only meaningful when a sample contains many wear-biased traits with only moderate/severe wear. We conclude despite the impact of wear on individual trait frequencies, its impact on morphological affinities can be mitigated by including other variables or when comparisons focus only on large-scale biological differences.

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Predicting social and health vulnerability to floods in Bangladesh

Natural Hazards and Earth System Science ◽

10.5194/nhess-21-1807-2021 ◽

2021 ◽

Vol 21 (6) ◽

pp. 1807-1823

Author(s):

Donghoon Lee ◽

Hassan Ahmadul ◽

Jonathan Patz ◽

Paul Block

Keyword(s):

Disaster Management ◽

Large Scale ◽

Management Practices ◽

Principal Component ◽

Social Health ◽

Equal Weight ◽

Coping Capacity ◽

Health Vulnerability ◽

And Coping ◽

The Impact

Abstract. Floods are the most common and damaging natural disaster in Bangladesh, and the effects of floods on public health have increased significantly in recent decades, particularly among lower socioeconomic populations. Assessments of social vulnerability on flood-induced health outcomes typically focus on local to regional scales; a notable gap remains in comprehensive, large-scale assessments that may foster disaster management practices. In this study, socioeconomic, health, and coping capacity vulnerability and composite social-health vulnerability are assessed using both equal-weight and principal-component approaches using 26 indicators across Bangladesh. Results indicate that vulnerable zones exist in the northwest riverine areas, northeast floodplains, and southwest region, potentially affecting 42 million people (26 % of the total population). Subsequently, the vulnerability measures are linked to flood forecast and satellite inundation information to evaluate their potential for predicting actual flood impact indices (distress, damage, disruption, and health) based on the immense August 2017 flood event. Overall, the forecast-based equally weighted vulnerability measures perform best. Specifically, socioeconomic and coping capacity vulnerability measures strongly align with the distress, disruption, and health impact records observed. Additionally, the forecast-based composite social-health vulnerability index also correlates well with the impact indices, illustrating its utility in identifying predominantly vulnerable regions. These findings suggest the benefits and practicality of this approach to assess both thematic and comprehensive spatial vulnerabilities, with the potential to support targeted and coordinated public disaster management and health practices.

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Sustainable Agricultural Practices, Farm Income and Food Security among Rural Households in Africa

10.21203/rs.3.rs-330019/v1 ◽

2021 ◽

Author(s):

Abdul-Hanan Abdallah ◽

Awal Abdul-Rahman ◽

Gazali Issahaku

Keyword(s):

Food Security ◽

Food Systems ◽

Treatment Effects ◽

Rural Households ◽

Agricultural Practices ◽

Sub Saharan Africa ◽

Farm Income ◽

Welfare Benefits ◽

Sustainable Agricultural Practices ◽

The Impact

Abstract Sustainable agriculture has been recognized in the literature as one of the important pathways to ensuring food systems and livelihoods among rural households in Africa. Using data from the ‘Intensification of Food Crops Agriculture in Sub-Saharan Africa (Afrint)’ project, we examine the impact of adoption of multiple sustainable agricultural practices (SAPs) - zero-tillage, intercropping, residue incorporation and animal manure - on farm incomes and food security (captures as self-sufficiency in food production-SSF) among African rural households. Multinomial endogenous treatment effect (METE) method is applied to control potential selection bias. In addition, the multivalued treatment effects (MTE) model and dose-response-functions (DRFs) are also used to examine the treatment effects heterogeneity associated with SAPs adoption. The study reveals that joint adoption of SAPs is increased farm income and food security relative to the adoption of a single practice. Households obtain significantly higher farm income (FI) and food security (FS) via adoption of at least three practices relative to households adopting less than three practices. These findings reaffirm the benefits of adopting SAPs as a package rather than single practice, to enable farm households to derive significant welfare benefits.

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Tomographic weak lensing bispectrum: a thorough analysis towards the next generation of galaxy surveys

Monthly Notices of the Royal Astronomical Society ◽

10.1093/mnras/stz2862 ◽

2019 ◽

Vol 490 (4) ◽

pp. 4688-4714 ◽

Cited By ~ 7

Author(s):

Matteo Rizzato ◽

Karim Benabed ◽

Francis Bernardeau ◽

Fabien Lacasa

Keyword(s):

Power Spectrum ◽

High Performance ◽

Large Scale ◽

Signal To Noise Ratio ◽

Principal Component ◽

Weak Lensing ◽

Galaxy Surveys ◽

Point Correlation ◽

Non Gaussian ◽

The Impact

ABSTRACT We address key points for an efficient implementation of likelihood codes for modern weak lensing large-scale structure surveys. Specifically, we focus on the joint weak lensing convergence power spectrum–bispectrum probe and we tackle the numerical challenges required by a realistic analysis. Under the assumption of (multivariate) Gaussian likelihoods, we have developed a high performance code that allows highly parallelized prediction of the binned tomographic observables and of their joint non-Gaussian covariance matrix accounting for terms up to the six-point correlation function and supersample effects. This performance allows us to qualitatively address several interesting scientific questions. We find that the bispectrum provides an improvement in terms of signal-to-noise ratio (S/N) of about 10 per cent on top of the power spectrum, making it a non-negligible source of information for future surveys. Furthermore, we are capable to test the impact of theoretical uncertainties in the halo model used to build our observables; with presently allowed variations we conclude that the impact is negligible on the S/N. Finally, we consider data compression possibilities to optimize future analyses of the weak lensing bispectrum. We find that, ignoring systematics, five equipopulated redshift bins are enough to recover the information content of a Euclid-like survey, with negligible improvement when increasing to 10 bins. We also explore principal component analysis and dependence on the triangle shapes as ways to reduce the numerical complexity of the problem.

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Inequalities in Infant Immunization Coverage in Bangladesh

Health Services Insights ◽

10.4137/hsi.s927 ◽

2008 ◽

Vol 1 ◽

pp. HSI.S927 ◽

Cited By ~ 3

Author(s):

Amal K. Halder ◽

M. Kabir

Keyword(s):

Immunization Coverage ◽

Indirect Costs ◽

Principal Component ◽

Wealth Index ◽

Household Wealth ◽

Wealth Status ◽

Proxy Variable ◽

Household Level ◽

Immunization Status ◽

The Impact

Background Although, health status of Bangladeshis has improved, levels of child mortality in Bangladesh remain unacceptably high. This paper reviews household wealth inequalities in immunization coverage in Bangladesh. The objective of the study is to examine how household wealth status and socio-demographic characteristics relate to immunization status of children. Methods Using data from the 2004 Bangladesh Demographic and Health Survey (BDHS), this paper investigated the inequalities and implications of infant immunization coverage in Bangladesh. To prepare the proxy variable of household wealth status we applied principal component analysis (PCA) technique based on variables such as assets, utilities and services available at household level. And then scores of the proxy variable was transferred into quintiles. Results The difference in immunization status between the richest and the poorest quintiles was significant (crude OR 5.2, p < 0.001). The addition of education to the multivariate model lowered the impact of wealth index by almost half. Increasing education levels were positively associated with achieving full vaccination status. Sex of children and age of mothers were not associated with the child's immunization status. Conclusions Despite free immunizations, use is not uniform throughout the population. Access to wealth and education may contribute to disparities in achieving full immunization. Minimizing indirect costs of immunizations may reduce disparities. Health education needs to be intensified for parents with minimal education.

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