Digital Commons Network^™

Accurate Prediction Of Geometrical Parameters Of An Ultra-Broadband Metamaterial Absorber Using Machine Learning, Md. Rezwan Ahmed, Oishi Jyoti, Pritu P. Sarkar, Mohammod Abdul Motin, Md Selim Habib, Md Samiul Habib

Electrical Engineering and Computer Science Faculty Publications

In this paper, we systematically demonstrate the design and analysis of a new type of ultra-broadband tunable metamaterial perfect absorber (MPA) comprising a top vanadium dioxide (VO2) based patterned resonating patch, a continuous metallic film at the bottom, and an intermediate dielectric substrate having a thickness of only 0.18 at the center working frequency. The simulation results reveal that the absorber achieves a bandwidth of 7.26 THz, ranging from 5.40 THz to 12.66 THz, with more than 90% absorptance and an average absorption of 98.21% under normal incidence of the incoming THz wave. Furthermore, absorptance exceeding 99% is achieved between …

Investigating The Human Face Processing Network: Insights From Acquired Prosopagnosia And Hyperfamiliarity For Faces, Marie-Luise Kieseler

Dartmouth College Ph.D Dissertations

Human faces provide essential social cues that we interpret rapidly, allowing us to recognize identities, interpret emotions, and gauge familiarity. This thesis explores face processing disruptions in four case studies, each offering new insights into the brain’s face recognition mechanisms.

Chapter one presents Annie, a 28-year-old woman who acquired prosopagnosia (face blindness) following COVID-19. After recovering from the severe symptoms of the infection, Annie experienced significant difficulty in recognizing familiar faces and navigating familiar environments. Testing confirmed her impairment in face recognition but showed her preserved cognitive and basic visual processing abilities. Annie was still able to recognize objects and …

A Virus Of The Mind: The Neurological Impact Of Neonatal Herpes Simplex Virus Infection, Abigail Jeanne Dutton

Dartmouth College Ph.D Dissertations

The ability of herpes simplex virus (HSV) to establish lifelong latency in sensory neurons makes it one of the most pervasive viruses worldwide. Although most HSV infections are asymptomatic or cause limited cutaneous symptoms, some give rise to serious central nervous system (CNS) manifestations. Both primary HSV infection and subsequent reactivation events can cause viral replication and spread within the brain, ultimately leading to pathologic inflammation and direct CNS damage. In addition to fulminant presentations of HSV encephalitis, subclinical HSV CNS infections have been implicated in neurodevelopmental, cognitive, and neurodegenerative impairment. To model the lifelong effects of subclinical HSV infection, …

Design And Manufacturing Of Multifunctional Piezoelectric Composites, Huan Zhao

Dartmouth College Ph.D Dissertations

Piezoelectric materials possess a unique ability to convert mechanical energy into electrical signals and have broad industrial applications. However, monolithic piezoelectric materials such as piezoceramics and piezopolymers often suffer from inherent trade-offs among mechanical strength, elasticity, and durability. Piezoelectric composites, typically consisting of a polymer matrix with ceramic reinforcements, offer a solution by combining the advantages of each constituent. Nevertheless, maintaining stable mechanical performance in high-temperature environments remains a significant challenge as conventional polymer matrices usually experience structural degradation.

In this thesis, a novel piezoelectric composite is developed using a preceramic polymer (PCP) matrix with barium titanate (BTO) inclusions. PCPs …

Multimodal Machine Learning To Enhance Patient Prognosis & Management In Cancer Care, Peiying Hua Phd

Dartmouth College Ph.D Dissertations

Precision medicine is a data-driven approach that tailors treatments to individualized need. Emerging in the late twentieth century, it emphasizes customizing therapy based on each person’s unique characteristics and became a major national focus in the US starting in 2015.

Cancer remains a leading cause of death worldwide. With high mortality rates and resource- intensive treatment process, it burdens the healthcare systems. One of the inherent challenges in cancer care is its biological heterogeneity, making diagnosis and treatment planning highly complex and calls for personalized cancer management.

Today, diverse data sources are available to support cancer management and treatment decisions. …

Quality Improvement Of Polycarbonate Medical Device By Moldex3d And Taguchi Doe, Upoma Saha, Wael Mokhtar

Open Access Publishing Support Funded Articles

Incorporating a new design combined with a thermoplastic material without having a prior process database may cause numerous defects in the molded part. Along with the initial setup cost, the scrape due to defects can add additional costs to the production. To address such issues, the numerical analysis tool Moldex3D was used to conduct simulations, and Taguchi Design of Experiment (DOE) was performed to optimize the process parameters. For this study, a classic medical device like the safety goggle model has been chosen as a subject. An amorphous material, polycarbonate, was used because of its transparent and significant thermal properties. …

Erk1/2 Inhibition Alleviates Diabetic Cardiomyopathy By Suppressing Fatty Acid Metabolism, Erin Mclean, Caroline De Roo, Annabel Maag, Megan Coble, Jefferson Cano, Ruijie Liu

Open Access Publishing Support Funded Articles

Background: Diabetes mellitus is associated with morphological and functional impairment of the heart primarily due to lipid toxicity caused by increased fatty acid metabolism. Extracellular signal-regulated protein kinases 1 and 2 (ERK1/2) have been implicated in the metabolism of fatty acids in the liver and skeletal muscles. However, their role in the heart in diabetes remains unclear. In this study, we tested our hypothesis that pharmacological inhibition of ERK1/2 alleviates cardiac remodeling in diabetic mice through a reduction in fatty acid metabolism.   Methods: ERK1/2 phosphorylation in diabetes was determined both in vitro and in vivo. H9C2 cells were subjected …

Deep Learning In Archiving Indus Script And Motif Information, Vaishnavi Dixit, Nushrat Hussain, Shubham Basak, Deva Atturu, Debasis Mitra, Ujjwal Bhattacharya

Electrical Engineering and Computer Science Faculty Publications

This work presents a novel computational system for the automated digitization of image-based data from seals of the ancient Indus Valley Civilization (IVC). The objective of this system’s design is to automatically extract and archive key information from seals or images, including the script and motifs. The system operates as a pipeline comprising three deep learning models integrated with a custom-designed database. Two models form the Ancient Script Recognition network (ASR-net), which digitizes sequences of graphemes from Indus seals, similar to Optical Character Recognition for modern languages. The third model, the Motif Identification network (MI-net), identifies recurring motifs—distinctive symbols or …

Enhancing Electric Vehicle Security And Privacy Through Decentralized Identity Management, Abdullah Aydeger, Engin Zeydan, Josep Mangues-Bafalluy, Suayb S. Arslan, Turk Yekta

Electrical Engineering and Computer Science Faculty Publications

In the next decade, Electric Vehicles (EVs) are expected to contribute to reducing climate change and transforming road mobility significantly. However, the security and privacy of EV charging systems pose considerable challenges that need to be addressed. This article introduces a novel approach by integrating blockchain-based Self-Sovereign Identity (SSI) to enhance the security and privacy of EV charging systems. By leveraging the decentralized and immutable nature of blockchain, the proposed SSI framework can ensure secure and private data exchanges between EVs, charging stations, and backend systems. This three-way integration addresses the vulnerabilities identified in existing EV charging methods, such as …

Quantum Technologies For Beyond 5g And 6g Networks: Applications, Opportunities, And Challenges, Engin Zeydan, Chamitha De Alwis, Rabia Khan, Yekta Turk, Abdullah Aydeger, Thippa Reddy Gadekallu, Madhusanka Liyanage

Electrical Engineering and Computer Science Faculty Publications

As the world prepares for the advent of 6G networks, quantum technologies are becoming critical enablers of the next generation of communication systems. This survey paper investigates the convergence of quantum technologies and 6G networks, focusing on their applications, opportunities and challenges. We begin with an examination of the motivations for integrating quantum technologies into 6G, investigating the potential to overcome the limits of classical computing and cryptography. We then highlight key research gaps, particularly in quantum communication, quantum computing integration and security enhancement. A comprehensive overview of quantum technologies relevant to 6G, including quantum communication devices, quantum computing paradigms, …