Graduate Student Papers

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Can LLMs Recommend More Responsible Prompts?
Santana, Vagner; Berger, Sara; Machado, Tiago; de Macedo, Maysa Malfiza; Sanctos, Cassia; Williams, Lemara; Wu, Zhaoqing (ACM, 2025-03-24)
Human-Computer Interaction practitioners have been proposing best practices in user interface design for decades. However, generative Artificial Intelligence (GenAI) brings additional design considerations and currently lacks sufficient user guidance regarding affordances, inputs, and outputs. In this context, we developed a recommender system to promote responsible AI (RAI) practices while people prompt GenAI systems, by recommending addition of sentences based on social values and removal of harmful sentences. We detail a lightweight recommender system designed to be used in prompting-time and compare its recommendations to the ones provided by three base large language models (LLMs) and two LLMs fine-tuned for the task, i.e., recommending inclusion of sentences based on social values and removal of harmful sentences from a given prompt. Results indicate that our approach has the best F1-score balance in terms of recommendations for additions and removal of sentences to promote responsible prompts, while a fine-tuned model obtained the best F1-score for additions, and our approach obtained the best F1-score for removals of harmful sentences. In addition, fine-tuned models improved the objectiveness of responses by reducing the verbosity of generated content in 93% when compared to the content generated by base models. Presented findings contribute to RAI by showing the limits and bias of existing LLMs in terms of recommendations on how to create more responsible prompts and how open-source technologies can fill this gap in prompting-time.
Sectoral Contributions to Primary and Secondary PM_2.5 in Regional Airsheds of India
Kumar, Alok; Imam, Fahad; Dixit, Kuldeep; Chaudhary, Ekta; Sharma, Sumit; Singh, Nimish; Katoch, Varun; Agarwal, Shivang; Ganguly, Dilip; Dey, Sagnik (American Chemical Society, 2025-03-18)
The exceedance of annual ambient fine particulate matter (PM2.5) concentrations above the national air quality standard across a large region in India, extending beyond the urban centers, necessitates an airshed approach for effective air quality management. Using over two decades of satellite-derived PM2.5 concentration data, seasonal wind patterns, and topography, we identified 9–11 major regional airsheds in India and further delineated the local airsheds of nonattainment cities. We separated sectoral contributions to primary and secondary PM2.5 in each airshed using outputs from a chemical transport model for the National Clean Air Program (NCAP) baseline year. In most airsheds, secondary PM2.5 constituted a larger share than primary PM2.5 except for the monsoon season. The domestic sector contributed the most to primary PM2.5 in most airsheds, while transboundary transport, industry, power, and other sources were the major contributors to secondary PM2.5. Our results can be used as a reference to assess progress in reducing ambient PM2.5 levels through the implementation of the NCAP action plan. Our study provides a comprehensive analysis of airsheds in India and underscores the need to control precursor gases, along with primary sources, for effective air pollution mitigation in the context of airsheds.
Care cascades of diabetes and hypertension among late adolescents in India
Malik, Bijaya Kumar; Goyal, Amit Kumar; Maiti, Suraj; Mohanty, Sanjay K. (International Society of Global Health, 2025-03-07)
BACKGROUND: Diabetes and hypertension are the most prevalent morbidities in India and are quickly becoming common among the younger age groups. Adolescents aged 10-19 years, accounting for one-fifth of the country's population, are at an increasing risk of developing these conditions. We aim to examine the prevalence, awareness, treatment, and control (ATC) of diabetes and hypertension among late adolescents (15-19 years) in India. METHODS: We used microdata of 204 346 late adolescents from India's fifth round of the National Family and Health Survey, 2019-21. We defined hypertensive adolescents as those diagnosed with hypertension or those with a systolic blood pressure (BP) measurement of ≥130 mm Hg, diastolic BP measurements of levels ≥80 mm Hg, or those who used medication to lower BP at the time of the survey. Diabetic adolescents were those diagnosed as such by health professionals, those with glucose levels above 140 mg/dL, or those taking any medication to control high blood glucose levels at the time of the survey. We estimated the age-sex-adjusted prevalence of both conditions and their ATC rates, referred to as cascade care. We used the Erreygers' Concentration Index to examine the socioeconomic inequality in cascade care. We used multivariable logistic regression to estimate the average marginal effects while controlling for sociodemographic characteristics. RESULTS: Of 204 346 late adolescents, 27.8% (95% confidence interval (CI) = 27.6, 28.2) had either of the two conditions, with 3.5% (95% CI = 3.4, 3.6) being diabetic and 24.3% (95% CI = 24.0, 24.6) having hypertension. The ATC rate of diabetes was 13.5% (95% CI = 12.4, 14.7), 13.1% (95% CI = 11.9, 14.2), and 12.1% (95% CI = 11.0, 13.3), respectively. For hypertension, the ATC rate was extremely low at 6.2% (95% CI = 5.8, 6.5), 3.5% (95% CI = 3.3, 3.7), and 3.3% (95% CI = 3.1, 3.5), respectively. There was a pro-rich socioeconomic inequality in the prevalence of hypertension and a pro-poor inequality in the prevalence of diabetes among late adolescents. We observed significant variations in both conditions across the regions of India. CONCLUSIONS: The high prevalence and low care cascade levels of diabetes and hypertension among late adolescents in India are concerning. A multipronged strategy that includes screening, diagnosis, and timely interventions at school and home can reduce the burden of hypertension and diabetes among the prospective workforce in India. Sensitising adolescents through school curricula under the New Education Policy (2020) is recommended to reduce the burden of these conditions. We also recommend that longitudinal and intervention studies focussed on this age group be undertaken in the future to help reduce the disease burden.
Antimicrobial resistance transmission in the environmental settings through traditional and UV-enabled advanced wastewater treatment plants: a metagenomic insight
Talat, Absar; Bashir, Yasir; Khalil, Nadeem; Brown, Connor L.; Gupta, Dinesh; Khan, Asad U. (2025-03-06)
Background: Municipal wastewater treatment plants (WWTPs) are pivotal reservoirs for antibiotic-resistance genes (ARGs) and antibiotic-resistant bacteria (ARB). Selective pressures from antibiotic residues, co-selection by heavy metals, and conducive environments sustain ARGs, fostering the emergence of ARB. While advancements in WWTP technology have enhanced the removal of inorganic and organic pollutants, assessing ARG and ARB content in treated water remains a gap. This metagenomic study meticulously examines the filtration efficiency of two distinct WWTPs-conventional (WWTPC) and advanced (WWTPA), operating on the same influent characteristics and located at Aligarh, India. Results: The dominance of Proteobacteria or Pseudomonadota, characterized the samples from both WWTPs and carried most ARGs. Acinetobacter johnsonii, a prevailing species, exhibited a diminishing trend with wastewater treatment, yet its persistence and association with antibiotic resistance underscore its adaptive resilience. The total ARG count was reduced in effluents, from 58 ARGs, representing 14 distinct classes of antibiotics in the influent to 46 and 21 in the effluents of WWTPC and WWTPA respectively. However, an overall surge in abundance, particularly influenced by genes such as qacL, blaOXA−900, and rsmA was observed. Numerous clinically significant ARGs, including those against aminoglycosides (AAC(6’)-Ib9, APH(3’’)-Ib, APH(6)-Id), macrolides (EreD, mphE, mphF, mphG, mphN, msrE), lincosamide (lnuG), sulfonamides (sul1, sul2), and beta-lactamases (blaNDM−1), persisted across both conventional and advanced treatment processes. The prevalence of mobile genetic elements and virulence factors in the effluents possess a high risk for ARG dissemination. Conclusions: Advanced technologies are essential for effective ARG and ARB removal. A multidisciplinary approach focused on investigating the intricate association between ARGs, microbiome dynamics, MGEs, and VFs is required to identify robust indicators for filtration efficacy, contributing to optimized WWTP operations and combating ARG proliferation across sectors.
Test Case-Informed Knowledge Tracing for Open-ended Coding Tasks
Duan, Zhangqi; Fernandez, Nigel; Hicks, Alexander; Lan, Andrew (ACM, 2025-03-03)
Open-ended coding tasks, which ask students to construct programs according to certain specifications, are common in computer science education. Student modeling can be challenging since their open-ended nature means that student code can be diverse. Traditional knowledge tracing (KT) models that only analyze response correctness may not fully capture nuances in student knowledge from student code. In this paper, we introduce Test case-Informed Knowledge Tracing for Open-ended Coding (TIKTOC), a framework to simultaneously analyze and predict both open-ended student code and whether the code passes each test case. We augment the existing CodeWorkout dataset with the test cases used for a subset of the open-ended coding questions, and propose a multitask learning KT method to simultaneously analyze and predict 1) whether a student’s code submission passes each test case and 2) the student’s open-ended code, using a large language model as the backbone. We quantitatively show that these methods outperform existing KT methods for coding that only use the overall score a code submission receives. We also qualitatively demonstrate how test case information, combined with open-ended code, helps us gain fine-grained insights into student knowledge.
Optimizing Schools: An Ethical Analysis of AI Integration in Education
Aina, Adeyemi (2025-01-03)
This case highlights the intersection of technology, society, and ethics, where AI offers transformative opportunities to identify struggling students and enhance their well-being through tailored interventions. However, it also presents risks, including algorithmic bias, data misuse, and a shift away from human-centered education. The Minerva High School case underscores broader ethical challenges in integrating AI into public institutions, particularly those serving vulnerable populations, prompting critical questions about balancing innovation with respect for individual rights and whether technological efficiency should outweigh traditional educational values. This analysis explores these dilemmas through ethical frameworks, offering insights into the responsible deployment of technology in society.
Public health insurance coverage in India before and after PM-JAY: Repeated cross-sectional analysis of nationally representative survey data
Mohanty, Sanjay K.; Upadhyay, Ashish Kumar; Maiti, Suraj; Mishra, Radhe Shyam; Kämpfen, Fabrice; Maurer, Jürgen; O'Donnell, Owen (BMJ, 2023-08-28)
Introduction The provision of non-contributory public health insurance (NPHI) to marginalised populations is a critical step along the path to universal health coverage. We aimed to assess the extent to which Ayushman Bharat-Pradhan Mantri Jan Arogya Yojana (PM-JAY) - potentially, the world's largest NPHI programme - has succeeded in raising health insurance coverage of the poorest two-fifths of the population of India. Methods We used nationally representative data from the National Family Health Survey on 633 699 and 601 509 households in 2015-2016 (pre-PM-JAY) and 2019-2021 (mostly, post PM-JAY), respectively. We stratified by urban/rural and estimated NPHI coverage nationally, and by state, district and socioeconomic categories. We decomposed coverage variance between states, districts, and households and measured socioeconomic inequality in coverage. For Uttar Pradesh, we tested whether coverage increased most in districts where PM-JAY had been implemented before the second survey and whether coverage increased most for targeted poorer households in these districts. Results We estimated that NPHI coverage increased by 11.7 percentage points (pp) (95% CI 11.0% to 12.4%) and 8.0 pp (95% CI 7.3% to 8.7%) in rural and urban India, respectively. In rural areas, coverage increased most for targeted households and pro-rich inequality decreased. Geographical inequalities in coverage narrowed. Coverage did not increase more in states that implemented PM-JAY. In Uttar Pradesh, the coverage increase was larger by 3.4 pp (95% CI 0.9% to 6.0%) and 4.2 pp (95% CI 1.2% to 7.1%) in rural and urban areas, respectively, in districts exposed to PM-JAY and the increase was 3.5 pp (95% CI 0.9% to 6.1%) larger for targeted households in these districts. Conclusion The introduction of PM-JAY coincided with increased public health insurance coverage and decreased inequality in coverage. But the gains cannot all be plausibly attributed to PM-JAY, and they are insufficient to reach the goal of universal coverage of the poor.
Healthcare inequity arising from unequal response to need in the older (45+ years) population of India: Analysis of nationally representative data
Mohanty, Sanjay K.; Khan, Junaid; Maiti, Suraj; Kämpfen, Fabrice; Maurer, Jürgen; O'Donnell, Owen (Elsevier, 2024-11-20)
Given the large and growing number of older (45+ years) people in India, inequitable access to healthcare in this population would slow global progress toward universal health coverage. We used a 2017-18 nationally representative sample of this population (n = 53,687) to estimate healthcare inequality and inequity by economic status. We used an extensive battery of indicators in nine health domains, plus age and sex, to adjust for need. We measured economic status by monthly per capita consumption expenditure and used a concentration index to measure inequalities in probabilities of any doctor visit and any hospitalisation within 12 months. We decomposed inequality with a regression method that allowed for economic and urban/rural heterogeneity in partial associations between healthcare and both need and non-need covariates. We used the associations achieved by the richest fifth of urban dwellers to predict a need-justified distribution of healthcare and compared the actual distribution with that benchmark to identify inequity. We found pro-rich inequalities in doctor visits and hospitalisations, which were driven by use of private healthcare. Adjustment for the greater need of poorer individuals revealed pro-rich inequity that exceeded inequality by about 65% and 39% for doctor visits and hospitalisations, respectively. These adjustments would have been substantially smaller, and inequity underestimated, without allowing for use-need heterogeneity, which accounted for 11% of the inequity in doctor visits and was 373% of inequity in hospitalisations. Targeting service coverage on poorer and rural groups, and increasing their access to private providers, would both reduce inequity and raise average coverage in the older population of India.
Out-of-pocket payment and financial risk protection for breast cancer treatment: a prospective study from India
Wadasadawala, Tabassum; Mohanty, Sanjay K.; Sen, Soumendu; Kanala, Tejaswi S.; Maiti, Suraj; Puchali, Namita; Gupta, Sudeep; Sarin, Rajiv; Parmar, Vani (Elsevier, 2024-01-16)
Background: Available data on cost of cancer treatment, out-of-pocket payment and reimbursement are limited in India. We estimated the treatment costs, out-of-pocket payment, and reimbursement in a cohort of breast cancer patients who sought treatment at a publicly funded tertiary cancer care hospital in India. Methods: A prospective longitudinal study was conducted from June 2019 to March 2022 at Tata Memorial Centre (TMC), Mumbai. Data on expenditure during each visit of treatment was collected by a team of trained medical social workers. The primary outcome variables were total cost (TC) of treatment, out-of-pocket payment (OOP), and reimbursement. TC included cost incurred by breast cancer patients during treatment at TMC. OOP was defined as the total cost incurred at TMC less of reimbursement. Reimbursement was any form of financial assistance (cashless or repayment), including social health insurance, private health insurance, employee health schemes, and assistance from charitable trusts, received by the patients for breast cancer treatment. Findings: Of the 500 patients included in the study, 45 discontinued treatment (due to financial or other reasons) and 26 died during treatment. The mean TC of breast cancer treatment was ₹258,095/US$3531 (95% CI: 238,225, 277,934). Direct medical cost (MC) accounted for 56.3% of the TC. Systemic therapy costs (₹50,869/US$696) were higher than radiotherapy (₹33,483/US$458) and surgery costs (₹25,075/US$343). About 74.4% patients availed some form of financial assistance at TMC; 8% patients received full reimbursement. The mean OOP for breast cancer treatment was ₹186,461/US$2551 (95% CI: 167,666, 205,257), accounting for 72.2% of the TC. Social health insurance (SHI) had a reasonable coverage (33.1%), followed by charitable trusts (29.6%), employee health insurance (5.1%), private health insurance (4.4%) and 25.6% had no reimbursement. But SHI covered only 40.1% of the TC of treatment compared to private health insurance that covered as much as 57.1% of it. Both TC and OOP were higher for patients who were younger, belonged to rural areas, had a comorbidity, were diagnosed at an advanced stage, and were from outside Maharashtra. Interpretation: In India, the cost and OOP for breast cancer treatment are high and reimbursement for the treatment flows from multiple sources. Though many of the patients receive some form of reimbursement, it is insufficient to prevent high OOP. Hence both wider insurance coverage as well as higher cap of the insurance packages in the health insurance schemes is suggested. Allowing for the automatic inclusion of cancer treatment in SHI can mitigate the financial burden of cancer patients in India. Funding: This work was funded by an extramural grant from the Women's Cancer Initiative and the Nag Foundation and an intramural grant from the International Institute of Population Sciences, Mumbai.
Catastrophic health expenditure and distress financing of breast cancer treatment in India: evidence from a longitudinal cohort study
Mohanty, Sanjay K.; Wadasadawala, Tabassum; Sen, Soumendu; Maiti, Suraj; E, Jishna (Springer, 2024-07-23)
Objective: To estimate the catastrophic health expenditure and distress financing of breast cancer treatment in India. Methods: The unit data from a longitudinal survey that followed 500 breast cancer patients treated at Tata Memorial Centre (TMC), Mumbai from June 2019 to March 2022 were used. The catastrophic health expenditure (CHE) was estimated using households' capacity to pay and distress financing as selling assets or borrowing loans to meet cost of treatment. Bivariate and logistic regression models were used for analysis. Findings: The CHE of breast cancer was estimated at 84.2% (95% CI: 80.8,87.9%) and distress financing at 72.4% (95% CI: 67.8,76.6%). Higher prevalence of CHE and distress financing was found among rural, poor, agriculture dependent households and among patients from outside of Maharashtra. About 75% of breast cancer patients had some form of reimbursement but it reduced the incidence of catastrophic health expenditure by only 14%. Nearly 80% of the patients utilised multiple financing sources to meet the cost of treatment. The significant predictors of distress financing were catastrophic health expenditure, type of patient, educational attainment, main income source, health insurance, and state of residence. Conclusion: In India, the CHE and distress financing of breast cancer treatment is very high. Most of the patients who had CHE were more likely to incur distress financing. Inclusion of direct non-medical cost such as accommodation, food and travel of patients and accompanying person in the ambit of reimbursement of breast cancer treatment can reduce the CHE. We suggest that city specific cancer care centre need to be strengthened under the aegis of PM-JAY to cater quality cancer care in their own states of residence.
Compressive and Flexural Strength Characteristics of Paving Stones Produced with Concrete Modified with Polypropylene Waste Chair
Olukanni, E. O.; Oyedepo, O. J.; Arowolo, T. R. (Proceedings of the 2021 Annual Conference of the School of Engineering & Engineering Technology, FUTA, 6th – 8th October, 2021, 2021-10)
The demand for a better performing pavement and the need to convert the ever-growing polymer waste into beneficial use necessitated the need to develop and characterize a polypropylene modified concrete for use in pavement construction. This research focuses on characterizing the strength of concrete produced with polypropylene waste as modifiers for pavement construction. The materials used in this research are fine and coarse aggregates, cement and polypropylene waste chairs (PWC). Tests were performed on the aggregate and fresh concrete to determine their suitability and characteristics for use in concrete for pavement. Two concrete grades 1:2:4 and 1:3:6 was produced into 200 mm, 400 mm and 500 mm long paving stones on which compressive and flexural tests were performed. Results obtained showed that 400 mm 1:2:4 grade concrete has the highest compressive strength of 27.36 N/mm2 at 10% polypropylene composition. The 200 mm 1:2:4 concrete grade paving stone with 10% polyprpopylene composition has the highest flexural strength of 12.90 N/mm2 . It was concluded that the 200 mm long 1:2:4 concrete grade paving stone at 10% polypropylene composition is the best length of paving stone that can give an adequate flexural strength which is the most important requirent in concrete pavement requirement.
Evaluation of Rheological Characteristics of Graphite Modified Bitumen
Oladunjoye, O. O.; Oyedepo, O. J.; Olukanni, E. O.; Akande, S. P. (Proceedings of the 2021 Annual Conference of the School of Engineering & Engineering Technology, FUTA, 6th – 8th October, 2021, 2021-03-06)
The level of performance of asphalt concrete has a close relationship with the properties of bitumen used. This research evaluates the rheological parameters of graphite modified bitumen. Index properties tests were conducted on bitumen and graphite to determine their suitability. Dynamic viscosity and dynamic shear rheometer were conducted on bituminous binder modified with four different proportion of graphite ranging from 2% to 10% by bitumen weight. Dynamic viscosity test was conducted on bitumen and graphite modified bitumen at temperature of 1350C and 1650C using Brookfield Viscometer. The rheological properties are centered on phase angle (δ) and complex shear modulus (G*) which were determined on bitumen and graphite modified bitumen at temperature ranging from 520C – 700C at 10 rad/s frequency using Dynamic Shear Rheometer in accordance with ASTM D7175-15. The storage modulus (G ' ), loss modulus (G") and rutting parameters were then evaluated from phase angle and complex shear modulus. The bitumen and graphite modified bitumen showed that graphite modified bitumen has the highest complex shear modulus and rutting parameter of 8984 (kPa) and 33387 (kPa) at 10% graphite content. The results of viscosity helped to determine the mixing and compaction temperatures. Dynamic shear rheometer test results determined the elastic and viscous behaviour at various temperature. The higher the complex shear modulus and rutting parameter the stiffer the binder will resist deformation and rutting.
Global Perspectives Program 2024 Final Report
Dosumu, Fiyinfunjah Adenike (2024)
Implementation and Evaluation of GBDI Memory Compression Algorithm Using C/C++ on a Broader Range of Workloads
Aina, Adeyemi (2023-05-03)
Memory compression is an important approach in computer architecture for decreasing memory footprint and improving system performance. In this paper, we use C/C++ to develop a current memory compression algorithm; the Global Bases Delta Immediate (GBDI) algorithm, which was proposed at HPCA'2022. By using global bases and enabling deltas within the same block to vary in size, the GBDI compression algorithm decreases the size of encoded data. The goal of this research is to assess the effectiveness of the GBDI algorithm by examining its compression ratios under a broader range of workloads. Our research leads to a better knowledge of the GBDI algorithm's effectiveness and the potential benefits of memory compression techniques for various sorts of applications. Furthermore, our C/C++ version of the algorithm gives academics and practitioners a high degree of freedom over customizing the algorithm for individual workloads and optimizing its performance.
How the Climate Change Threat is Shifting Australia's National Counter-Terrorism Strategy
Mortazavigazar, Amir (2023-03-08)
In this paper, we analyse how extremism and acts of terror will manifest themselves in Australia over the upcoming decades. Australia maintains a robust counter-terrorism strategy along with a comprehensive security apparatus to support that strategy. However, it is becoming apparent to the Australian intelligence community and the Australian government that the national security challenges that Australia will be facing due to climate change have been neglected over the past few years. COVID-19 restrictions demonstrated that issue-motivated extremism can fuel acts of terror and assist violent extremist organisations in their recruitment and radicalisations. In this paper, we demonstrate how climate change mitigation policies can result in issue-motivated extremism and empower violent extremist organisations which can result in acts of terror that would jeopardise Australia’s national security, therefore, we recommend that Australia’s National Intelligence apparatus broaden the issue-motivated extremism purview of terrorism by including climate change related grievances. Furthermore, we recommend amending Australia’s social cohesion and value statements to alleviate climate change related grievances and raise awareness about the threats of climate change related extremism.
Integrating health, economic, and environmental trade-offs into decarbonization decision-making in New England
Mortazavigazar, Amir (2024-05-15)
Emerging nuclear energy technologies: An alternative path to Australia's energy security
Mortazavigazar, Amir (Menzies Research Centre, 2023-12-18)
Gender Differences in Farmers' Indigenous Knowledge of Vegetables Disease Management: Implication for Artificial Intelligence-Enabled Farmers' Decision Support System
Deji, Olanike; Adisa, Priscilla; Ogunbona, Philip; Faniyi, Ebunoluwa; Olowoyo, Olamide; Jubril, Abimbola; Omotola, Olajide; Olukayode, Samuel (Rural Sociological Association of Nigeria, 2021)
The study was carried out in Osun State, Nigeria with the aim to analyse male and female vegetable farmers’ indigenous knowledge of disease management. It specifically assessed the indigenous knowledge of male and female farmers on the symptoms, causes, curative, and preventive measures of the vegetable crop diseases. This was done with the aim to provide gender-responsive benchmark data that could enhance the effective adoption of AI-enabled decision support system for crop disease management. Structured interview schedule was used to elicit quantitative data from 106 respondents (59 males and 47 females) for the study. Descriptive statistics was used to analyse the data. Majority of the male and female farmers used indigenous knowledge in identifying the symptoms, causes, curative and preventive measures of most common vegetable crop diseases. Expert/Extension professional-based human intelligence was also a major source of information on crop disease management among the male and female farmers, but the female farmers experienced lower extension contacts than the males. Scientific study and integration of gender responsive and enabling indigenous knowledge on crop disease management into the AI-enabled farmers’ decision support system involving experts and extension professionals is recommended for effectiveness and sustainability
A Camelid-Derived STAT-Specific Nanobody Inhibits Neuroinflammation and Ameliorates Experimental Autoimmune Encephalomyelitis (EAE)
Mbanefo, Evaristus C.; Seifert, Allison; Yadav, Manoj Kumar; Yu, Cheng-Rong; Nagarajan, Vijayaraj; Parihar, Ashutosh; Singh, Sunanda; Egwuagu, Charles E. (MDPI, 2024-06-16)
Proinflammatory T-lymphocytes recruited into the brain and spinal cord mediate multiple sclerosis (MS) and currently there is no cure for MS. IFN-γ-producing Th1 cells induce ascending paralysis in the spinal cord while IL-17-producing Th17 cells mediate cerebellar ataxia. STAT1 and STAT3 are required for Th1 and Th17 development, respectively, and the simultaneous targeting of STAT1 and STAT3 pathways is therefore a potential therapeutic strategy for suppressing disease in the spinal cord and brain. However, the pharmacological targeting of STAT1 and STAT3 presents significant challenges because of their intracellular localization. We have developed a STAT-specific single-domain nanobody (SBT-100) derived from camelids that targets conserved residues in Src homolog 2 (SH2) domains of STAT1 and STAT3. This study investigated whether SBT-100 could suppress experimental autoimmune encephalomyelitis (EAE), a mouse model of MS. We show that SBT-100 ameliorates encephalomyelitis through suppressing the expansion of Th17 and Th1 cells in the brain and spinal cord. Adoptive transfer experiments revealed that lymphocytes from SBT-100-treated EAE mice have reduced capacity to induce EAE, indicating that the immunosuppressive effects derived from the direct suppression of encephalitogenic T-cells. The small size of SBT-100 makes this STAT-specific nanobody a promising immunotherapy for CNS autoimmune diseases, including multiple sclerosis.
Construction Supply Chain Management Practice and Impact on Project Performance: Perspective From Nigerian Construction Firms
Adegoke, Abiola; Dada, Joshua (Nigerian Institute of Quantity Surveyors, 2022-10-27)
This paper investigates the awareness and extent of construction supply chain management (CSCM) practice by construction firms in Nigeria. In addition, the impact of CSCM on project cost and time performance was evaluated. Design/methodology/approach – A well structure questionnaire survey was administered on the ninety-two construction firms registered with the Bureau of Public Procurement of Oyo State in Southwestern Geopolitical Zone of Nigeria. Descriptive and inferential statistics were used to analyse the elicited data. The results show that construction firms in Nigeria are generally aware of CSCM. While the experience of small, medium and large-scale construction firms on CSCM practice differs, information acquisition and sharing (among other ten significant variables) was found to be the most important element. In determining the impact of CSCM practice on project cost, the eleven identified significant elements were used to develop a multi linear regression model equation Y = 3.654-0.053X1 – 0.036X2 – 0.041X3 - 0.065X4- 0.024X5 - 0.013 X6 - 0.021 X7- 0.021X8- 0.013 X9 - 0.035 X10 - 0.011X11. (Where Y is the cost of construction project and X1…X11 are elements of CSCM practice). In the same vein a model equation showing the impact of CSCM practice on project duration was developed as Y = 5.189-0.022X1 – 0.014X2 – 0.034X3 - 0.025X4- 0.060X5 - 0.011X6 - 0.036 X7 - 0.016X8 - 0.034 X9 - 0.014 X10 - 0.023X11. The generated model equations show an inverse relationship between cost and duration of construction projects and elements of CSCM practice. This implies that adequate utilisation of the elements of CSCM practice will lead to an appreciable reduction in project cost and time. Apart from the general impact of CSCM practice; the quantum effect of each of the elements can be evaluated from the model equations.

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