Crash risk in morbidly obese drivers before and after bariatric surgery: A population-based cohort study by Junaid Ahmad Bhatti (366799)

“…Morbid obesity may be associated with increased crash risk. These findings favor crash risk assessment in morbidly obese drivers.…”

Driving and dementia: What factors influence how physicians address the issue? Data from the Swedish Dementia Registry (SveDem) by Dorota Religa (402059)

“…Male gender (OR 2.97, p<0.001) and living alone was associated with an increased likelihood of being reported to the STA. …”

How do drivers choose a travel speed? Implications for speed management strategies in Australia by Jennifer Oxley (10057811)

“…</p><h2 dir="ltr">Other Information</h2><p dir="ltr">Published in: Journal of Local and Global Health Science, title discontinued as of (2017)<br>License: <a href="https://creativecommons.org/licenses/by/4.0/deed.en" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.5339/jlghs.2015.itma.23" target="_blank">https://dx.doi.org/10.5339/jlghs.2015.itma.23</a></p>…”

Enhancing Healthcare Systems With Deep Reinforcement Learning: Insights Into D2D Communications and Remote Monitoring by Zina Chkirbene (16869987)

“…<p dir="ltr">The traditional healthcare system is increasingly challenged by its dependence on inperson consultations and manual monitoring, struggling with issues of scalability, the immediacy of care, and efficient resource allocation. …”

BTRAC – Bangalore traffic improvement project – A case study by Sanjeev Kumar (279609)

“…<p dir="ltr">From 3 lakh vehicles in 1985, to about 53 lakh now, vehicle population in Bangalore has increased more than five fold during the last two decades. …”

Soft Computing-Based Damping Controllers With Online Parameters Tuning for Stability Enhancement of Power Systems by Farman Ullah Jan (22278835)

“…</p><h2 dir="ltr">Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/deed.en" rel="noreferrer noopener" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2025.3612288" target="_blank">https://dx.doi.org/10.1109/access.2025.3612288</a></p>…”

Deep Learning for Dynamic Wildlife Monitoring: A Real-Time Approach by Abdul Basit Mughal (22929001)

“…<p dir="ltr">With the rapid amount of deforestation around the world, wild animals lose their habitat and move closer to human settlements, leading to increased human-wildlife conflict and the loss of important human lives, livestock, and rare wild animal species. …”

An End-to-End Concatenated CNN Attention Model for the Classification of Lung Cancer With XAI Techniques by Fariha Haque (21485518)

“…However, manual diagnosis is labor-intensive, requiring the specialized expertise of radiologists, and the increasing number of cancer cases presents challenges in processing large volumes of image data efficiently. …”

An Optimal Approach for Assessing Weibull Parameters and Wind Power Potential for Six Coastal Cities in Pakistan by Ghulam Abbas (764241)

“…The numerical results reveal that NEPFM-SSA outshined NEPFM for all the cases under consideration, authenticating its workability. This increased accuracy results in improving the reliability of assessments of wind energy and the wider operation of wind energy installations. …”

Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms by Marwan Dhuheir (19170898)

“…<p dir="ltr">The integration of unmanned aerial vehicles (UAVs) in the Industrial Internet of Things (IIoT) for smart city applications has been gaining significant attention. UAV swarms are increasingly employed to monitor ground-based IIoT devices in smart cities, offering valuable support to situation-awareness IoT applications, such as surveillance, traffic management, and emergency response. …”

Introducing a Novel Figure of Merit for Evaluating Stability of Perovskite Solar Cells: Utilizing Long Short-Term Memory Neural Networks by Zahraa Ismail (22457644)

“…The comparative analysis of model complexity confirmed that increasing the sophistication of the LSTM model significantly enhances predictive accuracy and generalization capabilities. …”

THz-Enabled UAV Communications Under Pointing Errors: Tractable Statistical Channel Modeling and Security Analysis by Mohammad Javad Saber (4334227)

“…<p dir="ltr">Unmanned aerial vehicles (UAVs) are increasingly being utilized as mobile base stations for rapidly establishing temporary wireless coverage in emergency situations and remote locations. …”

A Novel Partitioned Random Forest Method-Based Facial Emotion Recognition by Hanif Heidari (22467148)

“…Most improved RF versions modify attribute selection processes or combine them with other machine learning algorithms, increasing their complexity. Identifying an appropriate training dataset and determining its size remain open questions. …”

Secrecy Performance of a RIS-Assisted Wireless Network: A Comprehensive Analysis Under Outdated CSI by Tasneem Alshamaseen (22392382)

“…</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Open Journal of the Communications Society<br>License: <a href="https://creativecommons.org/licenses/by/4.0/deed.en" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/ojcoms.2025.3547960" target="_blank">https://dx.doi.org/10.1109/ojcoms.2025.3547960</a></p>…”

Lead exposure of Bangladeshi women at childbearing age: Does mother's education reduce fetal risk factors? by Sharmind Neelotpol (19732277)

“…Depending on its concentration in the body, lead may cause lower IQ level, autism, abnormal pregnancy outcome, abortion, and increased involvement in crime. As lead can cross the placental barrier and affect the fetus, pregnant women, fetuses, and children are more vulnerable to lead poisoning because of rapid bone mobilization and neurodevelopment. …”

Reducing injuries among young drivers: what kind of measures are needed? by Hans-Yngve Berg (19794540)

“…For example, communication campaigns and increased enforcement may be used simultaneously and in particular target young males. …”

Sunitinib induces PTEN expression and inhibits PDGFR signaling and migration of medulloblastoma cells by Castellino, R.C.

“…However, sunitinib did not induce apoptosis in either cell line at any time point, indicating that the anti-migratory effects of sunitinib were not due to impeding cell survival. …”
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The Economic Impact of Optimizing a COVID-19 Management Protocol in Pre-Existing Cardiovascular Disease Patients by Dina Abushanab (10696501)

“…Overall, regardless of critical care status, the optimization of the initial COVID-19 protocols in patients with preexisting CVD did not reduce overall health care costs, but increased it by QAR80,529 (USD 22,117) per patient.…”

Application of Low-Fermenting Yeast Lachancea thermotolerans for the Control of Toxigenic Fungi Aspergillus parasiticus, Penicillium verrucosum and Fusarium graminearum and Their M... by Randa Zeidan (14778388)

“…Very interestingly, it was shown that even 7 yeast colonies reduced <i>Fusarium’s</i> growth and the synthesis of its mycotoxin, deoxynivalenol (DON). Moreover, decreasing yeast nutrient concentrations did not affect the inhibition of fungal growth, but reduced DON synthesis. …”

Associations between Bone Mineral Density and WOMAC Scores in Healthy Individuals: Insights from the Qatar Biobank by Al-Hamdani, Mohammed

“…Multiple linear regression was used to examine associations between sociodemographic factors, total body BMD and BMD related to specific skeletal sites (including femoral (femoral neck and trochanter), trunk, pelvis and total spine), and the three WOMAC subscales (pain, stiffness, and physical function).Results: After controlling for sociodemographic variables, total body and specific BMD measures did not predict pain. However, BMD measures significantly contributed to predicting stiffness after controlling for sociodemographic variables (R2 = 0.065, ΔF(7, 1724) = 3.34, p = 0.002), with a higher total body BMD associated with increased stiffness and a higher trunk BMD associated with decreased stiffness. …”
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