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Assessing Interactions Between Wild Host Plants And Stemborer Species In East Africa, Elie Ntirenganya, Venuste Nsengimana, Bonoukpoè Mawuko Sokame, Simon Boniface Boni, Yoseph Assefa, Janvier Uwayezu, Muluken Goftishu

All Rsif Scholars' Publications

Lepidopteran stemborers are among the most destructive pests of maize, sorghum, and sugarcane in Africa. Yet, data on their species composition and host range in Rwanda remain limited. This study provides the first comprehensive assessment of stemborer diversity, seasonal dynamics, and altitudinal distribution across eastern (low altitude), central (mid-altitude), and northern (high altitude) Rwanda. Surveys were conducted during both the rainy (maize growing) and dry seasons of 2023–2024, targeting infested maize fields and surrounding wild vegetation. A total of 2691 stemborer individuals were recovered from nine host plants, with 1474 (54.8%) from wild and fodder vegetation and 1217 (45.2%) from …

Economic Value Of Agro-Meteorological Services: A Review Of The International Literature, Joseph Manzvera, Kwabena Asomanin Anaman

All Rsif Scholars' Publications

Introduction:

The increasing frequency and intensity of climate-induced extreme weather events, such as droughts, have significantly reduced agricultural productivity worldwide. Enhancing access to agro-meteorological services can mitigate these impacts by improving farmers’ decision-making and adaptive capacity. However, their economic value remains poorly understood, especially in African countries where meteorological services are provided as public goods. Demonstrating their value is critical to stimulate investment and strengthen climate-resilient agriculture.

Methods:

This study reviews and synthesises empirical evidence on the economic value of agro-meteorological services through a systematic literature review and meta-analysis of international studies. Both peer-reviewed and grey literature were analysed to …

Dietary Responses Of Taste Receptor Genes To Plant-Based Diets In Farmed Fish: A Literature Review, Leonildo Dos Anjo Viagem, Jean Nepomuscene Hakizimana, Cyrus Rumisha, Brunno Da Silva Cerozi, Gerald Misinzo

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Taste receptor genes, particularly those in the bitter (tas2r) and umami/sweet (tas1r) families, are critical in regulating chemosensory perception and feeding behavior, influencing fish’s acceptance of plant-based diets. This review synthesizes the current research on how these genes respond to plant-based diets in farmed fish. A comprehensive search of scientific databases, including Web of Science, Scopus, PubMed, and Google Scholar, was conducted to identify relevant studies. Plant-based diets modulate gene expression, receptor activity, and signaling pathways, enabling fish to adapt to alternative feeds. The findings of the studies analyzed in this review show that plant ingredients affect fish taste receptor …

Gut And Blood Microbiota Of Nile Tilapia (Oreochromis Niloticus) Reared With Lettuce (Lactuca Sativa) And Challenged With Escherichia Coli And Vibrio Cholerae In Aquaponic Systems, Ang´Elica Adiaç˜ Ao Jossefa, Leonildo Dos Anjo Viagem, Brunno Da Silva Cerozi, Sebastian Wilson Chenyambuga

All Rsif Scholars' Publications

Aquaponics, a bio-integrated system that combines fish farming and vegetable cultivation, has gained significant attention due to its rapid expansion and potential for sustainable food production. In aquaponics, along with plants and fish, both beneficial and harmful microorganisms are also present. This study was conducted to assess the microbiota diversity of Nile tilapia reared with lettuce in aquaponic systems, with a focus on food safety implications. A total of 144 Nile tilapia juveniles with an average initial weight of 30.7 ± 0.03 g were randomly stocked and allocated to three treatments, each with three replicates. In treatment one, the fish …

Examining The Role Of Agroecology In Food Security Prediction: Evidence From Burkina Faso Using Machine Learning Methods, Theodore Nikiema, Pamela Giselle Katic, Sylvain Kpenavoun Chogou, Eugene C. Ezin

All Rsif Scholars' Publications

Background

Food insecurity affects a large proportion of the world's population, with enormous disparities to the disadvantage of low-income countries, especially those in sub-Saharan Africa. In this context, public decision-makers, funders, and NGOs urgently need streamlined indicators on households in precarious situations to better orient their policies and aid. However, existing food security monitoring tools focus on isolated dimensions of the problem, and some remain static. We aim to fill these gaps by focusing on a composite metric of food security to explore associations and identify variables with predictive relevance for food security outcomes using machine learning techniques.

Methodology

This …

Improving Accuracy Of Wind Speed Forecasted With Power Law And Multiple Layer Perceptron: A Case Study Of Aneho, A Coastal Area Of Togo, Maklewa Agoundedemba, Raphael Nyenge, Nicholas Musila, Kicoun Jean-Yves N’Zi Toure, Chang Ki Kim, Hyun-Goo Kim

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Wind speed forecasting is critical for optimizing wind energy generation, especially in regions with complex and variable weather patterns. This study focuses on improving the accuracy of wind speed forecasting using Multiple Layer Perceptron (MLP) models, with specific application to Aneho, a coastal area in Togo. The Power Law (PL) extrapolation or interpolation method is commonly used to estimate wind speeds at different heights. However, PL tends to show significant performance variability, particularly in periods with complex wind conditions. This study aimed to assess the accuracy of the PL method and enhance it using MLP for bias correction. We used …

Effect Of Diets Containing Soybean Or Seaweed (Kappaphycus Sp.) On Growth, Feed Utilization And Nutrient Digestibility In Nile Tilapia (Oreochromis Niloticus), Leonildo Dos Anjo Viagem, Jean Nepomuscene Hakizimana, Cyrus Rumisha, Gerald Misinzo, Brunno Da Silva Cerozi

All Rsif Scholars' Publications

Aquaculture is rapidly expanding, with Nile tilapia (Oreochromis niloticus) being a key freshwater species. Rising fishmeal (FM) costs and environmental concerns have increased interest in sustainable alternative protein sources. This study evaluated the effects of diets containing soybean (SB) or Kappaphycus sp. on the growth, feed efficiency and nutrient digestibility of Nile tilapia (O. niloticus). Four dietary treatments were tested over a 62-day feeding trial: FM diet, a diet containing SB, Kappaphycus sp. (seaweed [SW]) and a natural meal (NM) serving as a negative control. Diets were formulated to be isoproteic (360 g/kg) and isocaloric (3600 kcal/kg). Growth performance, feed …

Agroclimatic Sensing, Communication, And Computational Systems-Based Methods And Technologies For Precision Irrigation Management: Current State And Prospects, Aminata Sarr, Abhilash K. Chandel, Lamine Diop Lamine Diop, Yrébégnan Moussa Soro, Alain K. Tossa, Smrutilipi Hota, Arunachalam Manimozhian

All Rsif Scholars' Publications

Agriculture uses most of the world’s fresh water. Given that the worldwide population is expanding at an alarming rate, more land cultivation is apparently in demand. As a result, much more water would be required to irrigate cultivable lands. However, fresh water is becoming scarce at a faster rate due to climate uncertainties and over-exploitation. Several controlled irrigation techniques, such as drip and sprinkler irrigation, have been introduced to safeguard water resources. However, these techniques do not readily meet crop water demands and often end up causing overapplication of water. Under these circumstances, smart precision irrigation is the best solution. …

Assessment Of The Life Cycle Of Photovoltaic Solar Technologies For Sustainable Energy Transitions: Implications For Climate Policy And Low-Carbon System Integration, Wakiang Emile Latchiba, Sebastian Waita, Julius M. Mwabora

All Rsif Scholars' Publications

The rapid expansion of photovoltaic (PV) deployment demands integrated environmental and economic evaluation of emerging technologies. This study compares crystalline silicon (c-Si), perovskite, and hybrid perovskitesilicon tandem PV systems using a cradle-to-grave Life Cycle Assessment (LCA) combined with Techno-economic Analysis (TEA) to measure environmental impacts, resource efficiency, and cost performance. Environmental indicators include life cycle greenhouse gas emissions, total energy demand, water use, and overall impact, while economic performance is assessed through levelized cost of electricity (LCOE). Sensitivity analysis explores the effects of energy payback time (EPBT), material efficiency, and perovskite stability. Results show manufacturing as the main hotspot, contributing …

Effects Of Biochar Produced From Different Feedstocks And Organic Fertilizers On Soil Properties And Maize (Zea Mays L.) Production In The Northern Part Of Rwanda, Charles Lwanga Twagiramungu, Bobe Bedadi, Claver Ngaboyisonga, Concorde Nsengumuremyi, David Fangueiro

All Rsif Scholars' Publications

This study applied biochar derived from different local feedstocks and organic fertilizers (OF) on contrasting acidic soils, Andosol and Nitisol, in order to investigate their effects on selected soil properties and maize growth and yield parameters. A split plot design was employed, with treatments being factorial combinations of OF (control without OF (OF0), cow manure (OF1), chicken manure (OF2), and compost (OF3)) as a main plot factor and biochar (no biochar applied (B0), maize straw biochar (B1), eucalyptus biochar (B2), pinus biochar (B3)) as a sub-plot factor. An amelioration in soil properties was observed in treated plots compared to the …

Forecasting Future Adoption Rates Of Agroecological Innovations Using Machine Learning: Perspectives From Burkina Faso’S 45 Provinces From 2010 To 2020, Theodore Nikiema, Pamela Giselle Katic, Issaka Abdou Razakou Kiribou, Sylvain Kpenavoun Chogou, Eugene C. Ezin

All Rsif Scholars' Publications

Implementation of agroecological innovations tends to be long-term processes, withthe practices of one year often linked to those of previous years. However, previousstudies have focused on understanding drivers of adoption at farm level, with adoptionmeasured at a point in time. In this study, we use a decade of panel data from thePermanent Agricultural Survey in Burkina Faso from 2010 to 2020 and machine learningapproaches, to model adoption rates of agroecological innovations at the provinciallevel as an autoregressive process. This modeling approach allows us to exploit the timeseries nature of our dataset to forecast future adoption rates. Our results showcase thepotential …

Autonomous Self-Trained Channel State Predictionmethod For Mmwave Vehicular Communications, Abidemi Orimogunje, Vukan Ninkovic, Evariste Twahirwa, Gaspard Gashema, Dejan Vukobratovic

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Establishing and maintaining 5G mmWave vehicular connectivity poses a significant challenge due to high user mobility that necessitates frequent triggering of beam switching procedures. Departing from reactive beam switching based on the user device channel state feedback, proactive beam switching prepares in advance for upcoming beam switching decisions by exploiting accurate channel state information (CSI) prediction. In this paper, we develop a framework for autonomous self-trained CSI prediction for mmWave vehicular users where a base station (gNB) collects and labels a dataset that it uses for training recurrent neural network (RNN)-based CSI prediction model. The proposed framework exploits the CSI …

Occurrence And Levels Of Multiple Veterinary Antibiotics In Broiler Chicken Processed And Sold In Southern Mozambique, Noemia Andre Mugabe, Jamal Kussaga, Abdulsudi Issa-Zacharia

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Antibiotic residues in chicken meat pose a health risk to the general public, particularly to sensitive consumers. The aim of this study was to determine the level of antibiotic residues in on-the-market dressed chicken in the Southern Region of Mozambique. A total of 160 samples were randomly collected from eight markets located in five districts in the provinces of Maputo, Gaza, and Inhambane. The residues of β-lactams, quinolones, tetracyclines, and sulfonamides in chicken breast muscle were separated, identified, and quantified using high-performance liquid chromatography (HPLC), coupled with ultraviolet light (UV–VIS). Results revealed that 26.9% of the analyzed samples displayed detectable …

Osteogenic Differentiation Properties Of Blgfs/Odex Hydrogel Doped With Collagen Derived From Chambo Tilapia Fish Skin, Bhahat Lawlley Zimba, Xiaohan Yang, Mwemezi Rwiza, Elingarami Sauli, Shenqi Wang

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Background

Bone defects caused by trauma, congenital disorders and degenerative diseases such as osteoporosis remain a major clinical challenge, especially in developing regions. Although bone grafting is the current gold standard for treating bone defects, it faces limitations, including donor site morbidity, limited availability and immune rejection. This study developed and evaluated a novel hybrid biomaterial composed of bovine β-lactoglobulin fibrils (BLGFs), oxidized dextran (ODEX) and collagen (COL) extracted from Chambo tilapia fish skin for bone tissue engineering applications.

Methods

BLGFs were synthesized from whey protein, while ODEX was produced by oxidizing dextran. Three biomaterials–COL, BLGFs/ODEX and BLGFs/ODEX/COL–were synthesized and …

Functionalized Blgfs/Odex Hydrogel Scaffold Incorporating Oreochromis Lidole Skin Collagen For Bone Tissue Regeneration, Bhahat Lawlley Zimba, Xiaohan Yang, Mwemezi Rwiza, Elingarami Sauli, Shenqi Wang

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Background: Bones provide support to the body and protect vital internal organs. Bones have the capacity to repair minor defects, but this ability is substantially impaired in large defects. Mineralization, which is an essential stage of osteogenesis during bone defect repair, occurs through the deposition of calcium phosphate crystals to form the structural framework of bone tissue. In the present study, BLGFs/ODEX/COL hydrogel scaffolds were synthesized and characterized to determine their osteogenic differentiation capabilities. The hydrogel scaffolds were also applied to bone defect in SD rats and the regeneration of bone tissue was assessed. Methods: Whey protein was used to …

Quantifying Power Quality In Stand-Alone Minigrids Using Fuzzy Power Quality Indices: A Case Of Illaut Minigrid In Sub-Saharan Africa, D. E D. E. Nkolokosa, Sebastian Waita, Mutugi Kiruki, Walbermark Marque Dos Santos

All Rsif Scholars' Publications

Recently the concept of power quality in stand-alone minigrids is gaining wide recognition. The inherent uncertainties and dynamic operating conditions of the decentralised energy systems have promoted calls for increased research activities in power quality assessment and improvements. This study proposes an innovative approach for quantifying power quality in stand-alone minigrids. The existing conventional power quality indices have limited operational capacity; hence, they require improvement in terms of accuracy, reliability and versatility. The proposed methodology incorporates a hierarchical evaluation index comprising harmonic distortion, frequency fluctuation, voltage variation, dips and interruptions. Results indicate that interruptions got the lowest power index (0), …

Reliability-Aware Federated Ordinal Learning For Weekly Irrigation Management Zone Prediction On Edge Nodes, Rehema Mwawado, Jimmy Nsenga, Marco Zennaro, Damien Hanyurwimfura, Antonios Morellos, Muhammad Qaswar, Abdul Mounem Mouazen

All Rsif Scholars' Publications

The vision of smart agriculture depends on systems that can autonomously integrate distributed sensor data to support on-farm decisions such as precision irrigation and nutrient management. In variable-rate irrigation (VRI), this requires timely, high-resolution information to generate management zones that adapt to within-field variability throughout the season. However, current practice often relies on static zone maps and centralized processing, both of which are poorly suited to dynamic field conditions where sensors may fail, or drift and internet connectivity is often limited in resource-constrained environments. This study presents a reliability-aware edge-learning pipeline for weekly VRI zone prediction using federated learning (FL). …

The Effect Of Transient Power Ramp-Up On Structural And Optical Properties Of Cuo Thin Films Prepared By Radio Frequency Magnetron Sputtering, Cyril C. F. Kumachang, Daniel I. Amune, Ivy M Asuo, Dahiru Sanni, Yusuf A. Olanrewaju, Nicole Doumit, Richard Koech, Vitalis Anye, Esidor Ntsoenzok, Nutifafa Doumon

All Rsif Scholars' Publications

Transition metal oxides have found application as charge transport materials (CTMs) in perovskite solar cell devices due to their better environmental stability and superior electronic properties compared to organic CTMs. Many researchers have used radio frequency (RF) magnetron sputtering to deposit inorganic CTMs on inorganic layers. However, such efforts on perovskites have been limited by the distortion of high-energy ions of the sputtering gas energized by the RF power and temperature. The ions may also distort the interface between transparent conducting oxides and the charge transport layers, thereby increasing optical scattering. Thus, the effect of ramp power during RF magnetron …

Biomass And Ecosystem Services Valuation In Support Of Urban Climate-Resilience In Dakar, Senegal, Momath Diankha, Moussa Soule, Serigne Modou Sarr, Maharazu A. Yusuf, Kwame Oppong Hackman, Sintayehu Workeneh Dejene, Issaka Abdou Razakou Kiribou

All Rsif Scholars' Publications

Rapid urbanization is a growing global concern that challenges sustainability in cities. Urban trees provide several ecosystem services, such as climate regulation, carbon sequestration, and air-pollution removal. The sustainable benefits of these services imply the preservation of urban forests in developing countries, where trees are frequently removed and replaced by buildings and other infrastructure. Supporting informed decisionmaking requires accurate estimation and valuation of tree biomass and ecosystem services beyond conventional forest-based allometric approaches. This study used a scientific ecosystem services modeling tool to improve the accuracy of biomass estimates for the Mbao Protected Forest in Dakar. It uses the vegetation …

Enhancing Stability And Efficiency In Perovskite Solar Cells: Insights Into Inorganic Htl Deposition And Interface Defect Passivation, Daniel I Amune, W Fidel, R. K Koech, Dahiru Sanni, J Botsoa, V Anye, E Nstoenzok

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The perovskite solar cell (PSC) as an emerging and promising type of solar cell has been extensively studied, but instability is still a major challenge. Replacing the hygroscopic organic hole transport layer (HTL) in PSCs can result in an improvement in the device stability. However, it is still difficult to deposit inorganic HTLs onto the underlying perovskite layer without eroding or distorting it in the regular n–i–p architecture, thereby inducing defects at the interface and reducing the performance of the device. In this study, the performance of PSCs with an inorganic HTL is modelled using SCAPS-1D. The perovskiteHTL interface defect …

Christmas Peace, St. Norbert Music Department

Music Performances

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Look-Ahead Cyber-Threat Forecasting For Connected And Automated Transport: A Spatio-Temporal Graph Learning Approach, Md Al Amin, Mohammad Shafat Ahsan, Jannatul Maua, Arifa Akter Eva, M.F. Mridha, Md. Jakir Hossen

Student Publications [Scholarly]

Modern intelligent transportation systems (ITS) increasingly rely on connected electronic control units (ECUs), exposing in-vehicle networks to cyber-attacks such as message injection on the Controller Area Network (CAN) bus. While prior work has focused on post-factum detection, this paper addresses the underexplored task of forecasting cyber-attacks before they occur. We propose a spatio-temporal graph neural network (STGNN) architecture that models CAN traffic as a dynamic graph sequence, where nodes represent active CAN IDs and edges capture statistical co-activation patterns. Each graph snapshot encodes temporal features such as inter-arrival statistics and entropy, and is processed using graph attention layers followed by …

Time-Varying, Frequency-Domain, And Quantile Spillovers Across Energy And Financial Markets Under Climate Policy Uncertainty: Evidence From Tvp-Var-Sv, Bk, And Qvar Models, Md Qamruzzaman, Abdulrahman Alomair, Mohammed Alomair, Sylvia Kor

Student Publications [Scholarly]

The study explores how much area is influenced by climate policy uncertainty (CPU), which adjusts the dynamics of volatility and cross-market spillovers among European electricity, energy commodities, carbon markets, and financial assets, thereby explaining the mechanisms affected by the existing sustainability transition. Using high-frequency market data, we combine an econometric architecture linking a time-varying parameter VAR to stochastic volatility, Barunik–Krehlik frequency-domain connectedness, and quantile-VAR methods, thereby enabling the capture of horizon-specific and regime-dependent risk transmission. The discussion shows that the CPU is a structural amplifying agent of market interconnectedness, which has its most substantial impacts in long-horizon and downside regimes. …

Evaluating Spatiotemporal Changes And Predicting Land-Use Dynamics Using An Artificial Neural Network In Worcester City, Massachusetts, Mst Sanjida Alam, Mijanur Rahman, Nusrut Sharmin, Md Naim Molla, Hossain Al Mahbub, Mohammad Muniruzzaman, Md Nadim Rahman, Edris Alam

Student Publications [Scholarly]

The land use and land cover (LULC) change has a remarkable impact on the urban ecosystems due to its effect on the environmental processes, natural resources, and urban sustainability. The aim of this study was to conduct the spatiotemporal analysis of LULC in Worcester City, Massachusetts, and to identify the dynamics of forest cover and justify its causes in the given time range of 2003–2023. LULC classification and forest change detection were done with high-resolution datasets provided by the National Land Cover Database (NLCD). The MLP-ANN outperformed logistic regression and achieved higher in overall accuracy percentages and location Kappa values. …

Attention-Based Geo–Textual Fusion Network For Disaster Risk Prediction, Mohammad Shafat Ahsan, Mst Sanjida Alam, Syed Sajjad Ahmed, Md Tanzimul Islam, Hashibul Ahsan Shoaib, M.F. Mridha, Md. Jakir Hossen

Student Publications [Scholarly]

Natural disasters pose recurring threats to human life and infrastructure, demanding intelligent systems that can process heterogeneous data streams and provide actionable insights in real time. Existing approaches often treat textual signals from social media and emergency communications separately from spatial hazard attributes, limiting their effectiveness in capturing the full complexity of evolving crises. This paper proposes an AI-driven geo–textual intelligence framework that integrates disaster-related text with GIS-based hazard features for real-time risk prediction and evacuation planning. The framework employs contextual text encoders and a neural GIS encoder, fused through an attention mechanism that dynamically weights cross-modal signals. Experiments on …

Tree Composition And Carbon Turnover Dynamics Across 22 Years In A Costa Rican Premontane Moist Forest Fragment, Milena Cambronero, Fabián Araya-Yannarella, Lauren Holmes, Jill Cass

Student Publications [Scholarly]

Aim of study: Tropical forests are increasingly threatened by deforestation and fragmentation. In Costa Rica, extensive land-use change has left forest fragments whose long-term ecological dynamics remain poorly understood. This study assessed changes in tree diversity, composition, structure, and aboveground carbon stocks during a 22-year period (2000-2022) in a premontane moist forest fragment in Costa Rica. Area of study: Municipal Forest of Atenas (26.4-ha), Alajuela, Costa Rica. Material and methods: Tree inventories were conducted in 32 plots (10 m radius) in 2000 and 33 plots in 2022. We analysed diversity and composition using Bray-Curtis dissimilarity, Hill numbers, and Importance Value …

Self-Compassion And Sexual Assault Victimization: A Systematic Review, Alexis A. Adams-Clark, Jerin Lee, Lucy W. Naughton, Anna Purcell, Ananya Sharma, Siena Candullo, Kelsey Sawyer, Prachi H. Bhuptani, Lindsay M. Orchowski

Student Publications [Scholarly]

Sexual assault survivors demonstrate substantial resilience, prompting calls for strength-based approaches to understanding recovery. One construct receiving increasing attention is self-compassion (i.e., treating oneself with kindness and understanding in the face of suffering), which may buffer against the negative mental health effects of assault victimization. The current systematic review synthesized data from 31 peer-reviewed studies examining self-compassion, sexual assault exposure, and mental health. Reported in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards and registered in PROSPERO (CRD420250648494), the review included observational and experimental studies assessing sexual assault victimization and self-compassion across the lifespan. Most studies …

Modeling And Performance Evaluation Of Machine Learning For Historical And Future Land Use And Land Cover Dynamics In Chattogram District, Bangladesh, Mst Sanjida Alam

Student Publications [Scholarly]

Introduction – Land use and land cover (LULC) change is rapidly redrawing the environmental landscape of coastal Bangladesh. Methods – This study integrates Landsat-based classification, machine learning-based approaches, and Markov Chain simulation to assess historical and future LULC dynamics in Chattogram District. Results – Random Forest classification achieved overall accuracies of 95.96%, 90.45%, and 94.25% for 2006, 2015, and 2025, respectively. Results reveal substantial cropland expansion (+32, 375 ha) and continued growth of built-up land, accompanied by declines in vegetation, waterbodies, and bare land. Random Forest demonstrated strong predictive performance, achieving an out-of-bag (OOB) accuracy of 92.63% and a skill …

“I Have Already Lost My Kids”: Mothering Experiences Of Women In Jail, Bothwell Piason, Dawn Beichner-Thomas

Faculty Publications - Criminal Justice Sciences

Although women represent a small proportion of the incarcerated population globally, their rate of incarceration in the United States has increased dramatically over the past four decades, outpacing that of men. As carceral trends return to pre-COVID-19 pandemic levels, jail populations continue to rise, with most incarcerated women being mothers of young children. Yet, research on motherhood behind bars has largely focused on prisons rather than jails. This study explores the mothering experiences of women incarcerated in two U.S. Midwestern jails, including both pretrial detainees and sentenced individuals. Using qualitative data from in-depth interviews with jailed mothers, the analysis examines …

Teaching The Sociological Imagination: Creating Community In Tumultuous Times, Marta Ascherio

Faculty Publications - Criminal Justice Sciences

Opening paragraph:

In fall 2022, I began a tenure track position at Illinois State University (ISU), as a joint hire between the Department of Criminal Justice Sciences and the Latin American and Latino Studies Program (LALS). LALS is a multi-disciplinary program with affiliated faculty from multiple colleges and departments across campus. In contrast to affiliated faculty whose main teaching responsibilities are in their home departments, as a joint hire I have teaching responsibilities in Criminal Justice Sciences (two classes) and LALS (one class). I became part of a small cohort of faculty across departments (Languages, Sociology and Anthropology, Communications, and …