Entire DC Network | Open Access Articles | Digital Commons Network™

Three Classes Of Propofol Binding Sites On Gabaa Receptors, Zi-Wei Chen, Satyanarayana M Chintala, John Bracamontes, Yusuke Sugasawa, Spencer R Pierce, Balazs R Varga, Edward H Smith, Christopher J Edge, Nicholas P Franks, Wayland W L Cheng, Gustav Akk, Alex S Evers

2020-Current year OA Pubs

Propofol is a widely used anesthetic and sedative that acts as a positive allosteric modulator of gamma-aminobutyric acid type A (GABA

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New Insights Into Innate Immunity In Alzheimer's Disease: From Apoe Protective Variants To Therapies, Yun Chen, David M Holtzman

2020-Current year OA Pubs

Recent discoveries of rare variants of human APOE may shed light on novel therapeutic strategies for Alzheimer's disease (AD). Here, we highlight the newly identified protective variant [APOE3 Christchurch (APOE3ch, R136S)] as an example. We summarize human AD and mouse amyloidosis and tauopathy studies from the past 5 years that have been associated with this R136S variant. We also propose a potential mechanism for how this point mutation might lead to protection against AD pathology, from the molecular level, to cells, to mouse models, and potentially, to humans. Lastly, we extend our discussion of the recent insights gained regarding different …

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A Content Analysis Of Counseling Psychology Literature: Resilience Against Oppression Among People Of Color, David C. Stanley Jr., Rawan H. Atari-Khan

Psychology Faculty Research and Publications

The researchers analyzed articles from two flagship counseling psychology journals (i.e., Journal of Counseling Psychology and The Counseling Psychologist) to examine current understandings of resilience. There were 54 articles included in the final analysis that spanned the years 1997–2022. The researchers conducted a content analysis to identify, analyze, and report patterns across counseling psychology journals with regard to how resilience has been defined, the racial/ethnic groups that were of focus, and the forms of oppression that were studied or addressed. Five themes were generated that are a direct representation of the topics within previous literature on resilience in the field …

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Prophylactic Antibiotics For Excision Of Premalignant Vulvar Lesions: A Pilot Randomized Controlled Trial, Mary M Mullen, Whitney R Grither, Hannah Millimet, David G Mutch, Andrea R Hagemann, Carolyn K Mccourt, Matthew A Powell, Premal H Thaker, Dineo Khabele, Lindsay M Kuroki

2020-Current year OA Pubs

No prospective data have been described to inform guidelines on antibiotic prophylaxis for partial vulvectomies. Thus, we conducted a single-center, pilot, double-blind randomized controlled trial to assess the effectiveness of prophylactic antibiotics to prevent wound complications after partial vulvectomies. Patients were randomly assigned 1:1 to preoperative antibiotics or no preoperative antibiotics. The primary outcome of 30-day postoperative wound complications occurred in 31 (62 %) of all patients, with no differences between groups. The most common wound complications were superficial separation (54.2 % antibiotic prophylaxis vs. 65.3 % no prophylaxis, p = 0.37) and surgical site infection (0 % antibiotic prophylaxis …

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The Dallas Donation After Circulatory Death Transplantation Summit: Expanding Donation After Circulatory Death Procedures Through Process Improvement, Broader Utilization, And Innovation, Michele Finotti, William C. Chapman, Et Al.

2020-Current year OA Pubs

Despite a significant increase in utilization over the past decade, the number of donation after circulatory death (DCD) organs that are procured and transplanted in the United States (US) remains well below its potential. There is still room for expansion, as utilizing DCD organs to the fullest extent is currently the most viable solution to the persistent mismatch between supply and demand in transplantation. We convened a multidisciplinary transplantation summit to examine various aspects of DCD, with faculty members from around the world with clinical and academic interest in DCD donation and transplantation, including abdominal and cardiothoracic surgeons, organ procurement …

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Teacher Self Efficacy And The Work Environment, Marium Carpen

Seton Hall University Dissertations and Theses (ETDs)

In a time of uncertainty, teachers have been the backbone of the educational world. They provide a sense of consistency to many students who may need positive role models in their life. Teachers take on roles as caregivers, educators, friends, and are often a “safe place” for students. Yet, how have teachers been supported during times of crisis? With the recent COVID-19 pandemic shifting the world of education, elementary school teachers have had to adapt to new changes within their daily work environment. From transitioning to immediate virtual learning and returning to in-person learning with safety protocols, understanding teacher self-efficacy …

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Proteomic Analysis Reveals Major Proteins And Pathways That Mediate The Effect Of 17-Β-Estradiol In Cell Division And Apoptosis In Breast Cancer Mcf7 Cells, Zhenqi Zhou, Brihget Sicairos, Jianhong Zhou, Yuchun Du

Biological Sciences Faculty Publications and Presentations

Despite extensive research, the genes/proteins and pathways responsible for the physiological effects of estrogen remain elusive. In this study, we determined the effect of estrogen on global protein expression in breast cancer MCF7 cells using a proteomic method. The expression of 77 cytosolic, 74 nuclear, and 81 membrane/organelle proteins was significantly altered by 17-β-estradiol (E2). Protein enrichment analyses suggest that E2 may stimulate cell division primarily by promoting the G1 to S phase transition and advancing the G2/M checkpoint. The effect of E2 on cell survival was complex, as it could simultaneously enhance and inhibit apoptosis. Bioinformatics analysis suggests that …

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Discovery Of Genomic And Transcriptomic Pleiotropy Between Kidney Function And Soluble Receptor For Advanced Glycation End Products Using Correlated Meta-Analyses: The Long Life Family Study, Mary F Feitosa, Shiow J Lin, Sandeep Acharya, Bharat Thyagarajan, Mary K Wojczynski, Allison L Kuipers, Alexander Kulminski, Kaare Christensen, Joseph M Zmuda, Michael R Brent, Michael A Province

2020-Current year OA Pubs

Patients with chronic kidney disease (CKD) have increased oxidative stress and chronic inflammation, which may escalate the production of advanced glycation end-products (AGEs). High soluble receptor for AGE (sRAGE) and low estimated glomerular filtration rate (eGFR) levels are associated with CKD and aging. We evaluated whether eGFR calculated from creatinine and cystatin C share pleiotropic genetic factors with sRAGE. We employed whole-genome sequencing and correlated meta-analyses on combined genome-wide association study (GWAS) p-values in 4182 individuals (age range: 24-110) from the Long Life Family Study (LLFS). We also conducted transcriptome-wide association studies (TWAS) on whole blood in a subset of …

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A Modular Chemigenetic Calcium Indicator For Multiplexed In Vivo Functional Imaging, Helen Farrants, Christian Monroy Hernandez, Yao Chen, Et Al.

2020-Current year OA Pubs

Genetically encoded fluorescent calcium indicators allow cellular-resolution recording of physiology. However, bright, genetically targetable indicators that can be multiplexed with existing tools in vivo are needed for simultaneous imaging of multiple signals. Here we describe WHaloCaMP, a modular chemigenetic calcium indicator built from bright dye-ligands and protein sensor domains. Fluorescence change in WHaloCaMP results from reversible quenching of the bound dye via a strategically placed tryptophan. WHaloCaMP is compatible with rhodamine dye-ligands that fluoresce from green to near-infrared, including several that efficiently label the brain in animals. When bound to a near-infrared dye-ligand, WHaloCaMP shows a 7× increase in fluorescence …

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D2sr: Decentralized Detection, De-Synchronization, And Recovery Of Lidar Interference, Darshana Rathnayake, Hemanth Sabbella, Meera Radhakrishnan, Archan Misra

Research Collection School Of Computing and Information Systems

We address the challenge of multi-LiDAR interference, an issue of growing importance as LiDAR sensors are embedded in a growing set of pervasive devices. We introduce a novel approach named D2SR, enabling decentralized interference detection, mitigation, and recovery without explicit coordination among nearby LiDAR devices. D2SR comprises three stages: (a) Detection, which identifies interfered frames, (b) Mitigation, which performs time-shifting of a LiDAR’s active period to reduce interference, and (c) Recovery, which corrects or reconstructs the depth values in interfered regions of a depth frame. Key contributions include a lightweight interference detection algorithm achieving an F1-score of 92%, a simple …

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Fabrication And Evaluation Of Multicomponent Biomimetic Scaffolds For Bone Tissue Engineering, Mozan Osman Hassan

Dissertations

Bones have an inherent ability to remodel, but critical-size defects can hinder regeneration, leading to delayed healing or non-union fractures. Traditional bone grafts have limitations, such as donor site morbidity and immune rejection, driving the need for synthetic bone substitutes. Bone tissue engineering (BTE) addresses this by developing biomimetic scaffolds that replicate bone properties. This research aimed to fabricate composite scaffolds from strontium (Sr) and zinc (Zn) doped nano-hydroxyapatite (nHAp), collagen, and poly(lactide-co-glycolide) (PLGA). Different doping percentages of Sr/Zn (1%, 2.5%, 4%) were used to fabricate the scaffolds using supercritical CO2 (ScCO2) and electrospinning techniques. Scaffolds were then analyzed for …

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Ms Treatment De-Escalation: Review And Commentary, Krzysztof Selmaj, Hans-Peter Hartung, Marcin P Mycko, Igor Selmaj, Anne H Cross

2020-Current year OA Pubs

Almost all currently licensed disease-modifying therapies (DMTs) for MS treatment require prolonged if not lifelong administration. Yet, as people age, the immune system has increasingly reduced responsiveness, known as immunosenescence. Many MS DMTs reduce the responsiveness of the immune system, increasing the risks for infections and possibly cancers. As people with MS (pwMS) age, it is recognized that inflammatory MS activity declines. Several studies have addressed de-escalation of DMTs for relapsing MS under special circumstances. Here, we review evidence for de-escalating DMTs as a strategy that is particularly relevant to pwMS of older age. Treatment de-escalation can involve various strategies, …

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Interactive Example-Based Explanations To Improve Health Professionals’ Onboarding With Ai For Human-Ai Collaborative Decision Making, Min Hun Lee, Renee Bao Xuan Ng, Silvana Xinyi Choo, Shamala Thilarajah

Research Collection School Of Computing and Information Systems

A growing research explores the usage of AI explanations on user’s decision phases for human-AI collaborative decision-making. However, previous studies found the issues of overreliance on ‘wrong’ AI outputs. In this paper, we propose interactive example-based explanations to improve health professionals’ onboarding with AI for their better reliance on AI during AI-assisted decision-making. We implemented an AI-based decision support system that utilizes a neural network to assess the quality of post-stroke survivors’ exercises and interactive example-based explanations that systematically surface the nearest neighborhoods of a test/task sample from the training set of the AI model to assist users’ onboarding with …

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Self-Adaptive Fine-Grained Multi-Modal Data Augmentation For Semi-Supervised Muti-Modal Coreference Resolution, Li Zheng, Boyu Chen, Hao Fei, Fei Li, Shengqiong Wu, Lizi Liao, Donghong Ji

Research Collection School Of Computing and Information Systems

Coreference resolution, an essential task in natural language processing, is particularly challenging in multi-modal scenarios where data comes in various forms and modalities. Despite advancements, limitations due to scarce labeled data and underleveraged unlabeled data persist. We address these issues with a self-adaptive fine-grained multi-modal data augmentation framework for semi-supervised MCR, focusing on enriching training data from labeled datasets and tapping into the untapped potential of unlabeled data. Regarding the former issue, we first leverage text coreference resolution datasets and diffusion models,to perform fine-grained text-to-image generation with aligned text entities and image bounding boxes. We then introduce a self-adaptive selection …

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Brushbuds: Toothbrushing Tracking Using Earphone Imus, Qiang Yang, Yang Liu, Jake Stuchbury-Wass, Kayla-Jade Butkow, Dong Ma, Cecilia Mascolo

Research Collection School Of Computing and Information Systems

Inadequate toothbrushing habits are a leading cause of oral health problems such as tooth decay. Many individuals are uncertain if they are brushing effectively or over-focusing on specific areas. While high-end electric toothbrushes can address these concerns, manual toothbrushes remain widely used due to their simplicity and affordability. In this paper, we introduce BrushBuds, an earphone-based toothbrushing monitoring system aimed at tracking brushing areas, which leverages the ubiquitous presence of earphones to enhance manual toothbrushing. BrushBuds utilizes Inertial Measurement Units (IMUs) in earphones to detect subtle head movements incurred by toothbrushing. By capturing distinct motion patterns specific to brushing for …

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An Empirical Study To Evaluate Aigc Detectors On Code Content, Jian Wang, Shangqing Liu, Xiaofei Xie, Yi Li

Research Collection School Of Computing and Information Systems

Artificial Intelligence Generated Content (AIGC) has garnered considerable attention for its impressive performance, with Large Language Models (LLMs), like ChatGPT, emerging as a leading AIGC model that produces high-quality responses across various applications, including software development and maintenance. Despite its potential, the misuse of LLMs, especially in security and safetycritical domains, such as academic integrity and answering questions on Stack Overflow, poses significant concerns. Numerous AIGC detectors have been developed and evaluated on natural language data. However, their performance on code-related content generated by LLMs remains unexplored. To fill this gap, in this paper, we present an empirical study evaluating …

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Enhancing Recipe Retrieval With Foundation Models: A Data Augmentation Perspective, Fangzhou Song, Bin Zhu, Yanbin Hao, Shuo Wang

Research Collection School Of Computing and Information Systems

Learning recipe and food image representation in common embedding space is non-trivial but crucial for cross-modal recipe retrieval. In this paper, we propose a new perspective for this problem by utilizing foundation models for data augmentation. Leveraging on the remarkable capabilities of foundation models (i.e., Llama2 and SAM), we propose to augment recipe and food image by extracting alignable information related to the counterpart. Specifically, Llama2 is employed to generate a textual description from the recipe, aiming to capture the visual cues of a food image, and SAM is used to produce image segments that correspond to key ingredients in …

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Risurconv : Rotation Invariant Surface Attention-Augmented Convolutions For 3d Point Cloud Classification And Segmentation, Zhiyuan Zhang, Licheng Yang, Xiang Zhiyu

Research Collection School Of Computing and Information Systems

Despite the progress on 3D point cloud deep learning, most prior works focus on learning features that are invariant to translation and point permutation, and very limited efforts have been devoted for rotation invariant property. Several recent studies achieve rotation invariance at the cost of lower accuracies. In this work, we close this gap by proposing a novel yet effective rotation invariant architecture for 3D point cloud classification and segmentation. Instead of traditional pointwise operations, we construct local triangle surfaces to capture more detailed surface structure, based on which we can extract highly expressive rotation invariant surface properties which are …

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Audio Description Customization, Rosiana Natalie, Ruei-Che Chang, Sheshadri Smitha, Anhong Guo, Kotaro Hara

Research Collection School Of Computing and Information Systems

Blind and low-vision (BLV) people use audio descriptions (ADs) to access videos. However, current ADs are unalterable by end users, thus are incapable of supporting BLV individuals’ potentially diverse needs and preferences. This research investigates if customizing AD could improve how BLV individuals consume videos. We conducted an interview study (Study 1) with fifteen BLV participants, which revealed desires for customizing properties like length, emphasis, speed, voice, format, tone, and language. At the same time, concerns like interruptions and increased interaction load due to customization emerged. To examine AD customization’s effectiveness and tradeoffs, we designed CustomAD, a prototype that enables …

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Desk2desk : Optimization-Based Mixed Reality Workspace Integration For Remote Side-By-Side Collaboration, Ludwig Sidenmark, Tianyu Zhang, Leen Al Lababidi, Jiannan Li, Tovi Grossman

Research Collection School Of Computing and Information Systems

Mixed Reality enables hybrid workspaces where physical and virtual monitors are adaptively created and moved to suit the current environment and needs. However, in shared settings, individual users’ workspaces are rarely aligned and can vary significantly in the number of monitors, available physical space, and workspace layout, creating inconsistencies between workspaces which may cause confusion and reduce collaboration. We present Desk2Desk, an optimization-based approach for remote collaboration in which the hybrid workspaces of two collaborators are fully integrated to enable immersive side-by-side collaboration. The optimization adjusts each user’s workspace in layout and number of shared monitors and creates a mapping …

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Direct Range Proofs For Paillier Cryptosystem And Their Applications, Zhikang Xie, Mengling Liu, Haiyang Xue, Man Ho Au, Robert H. Deng, Siu-Ming Yiu

Research Collection School Of Computing and Information Systems

The Paillier cryptosystem is renowned for its applications in electronic voting, threshold ECDSA, multi-party computation, and more, largely due to its additive homomorphism. In these applications, range proofs for the Paillier cryptosystem are crucial for maintaining security, because of the mismatch between the message space in the Paillier system and the operation space in application scenarios. In this paper, we present novel range proofs for the Paillier cryptosystem, specifically aimed at optimizing those for both Paillier plaintext and affine operation. We interpret encryptions and affine operations as commitments over integers, as opposed to solely over ZN. Consequently, we propose direct …

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Collaborative Cross-Modal Fusion With Large Language Model For Recommendation, Zhongzhou Liu, Hao Zhang, Kuicai Dong, Yuan Fang

Research Collection School Of Computing and Information Systems

Despite the success of conventional collaborative filtering (CF) approaches for recommendation systems, they exhibit limitations in leveraging semantic knowledge within the textual attributes of users and items. Recent focus on the application of large language models for recommendation (LLM4Rec) has highlighted their capability for effective semantic knowledge capture. However, these methods often overlook the collaborative signals in user behaviors. Some simply instruct-tune a language model, while others directly inject the embeddings of a CF-based model, lacking a synergistic fusion of different modalities. To address these issues, we propose a framework of Collaborative Cross-modal Fusion with Large Language Models, termed CCF-LLM, …

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Improving Out-Of-Distribution Detection With Disentangled Foreground And Background Features, Choubo Ding, Guansong Pang

Research Collection School Of Computing and Information Systems

Detecting out-of-distribution (OOD) inputs is a principal task for ensuring the safety of deploying deep-neural-network classifiers in open-set scenarios. OOD samples can be drawn from arbitrary distributions and exhibit deviations from in-distribution (ID) data in various dimensions, such as foreground features (e.g., objects in CIFAR100 images vs. those in CIFAR10 images) and background features (e.g., textural images vs. objects in CIFAR10). Existing methods can confound foreground and background features in training, failing to utilize the background features for OOD detection. This paper considers the importance of feature disentanglement in out-of-distribution detection and proposes the simultaneous exploitation of both foreground and …

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Densetrack : Drone-Based Crowd Tracking Via Density-Aware Motion-Appearance Synergy, Yi Lei, Huilin Zhu, Jingling Yuan, Guangli Xiang, Xian Zhong, Shengfeng He

Research Collection School Of Computing and Information Systems

Drone-based crowd tracking faces difficulties in accurately identifying and monitoring objects from an aerial perspective, largely due to their small size and close proximity to each other, which complicates both localization and tracking. To address these challenges, we present the Density-aware Tracking (DenseTrack) framework. DenseTrack capitalizes on crowd counting to precisely determine object locations, blending visual and motion cues to improve the tracking of small-scale objects. It specifically addresses the problem of cross-frame motion to enhance tracking accuracy and dependability. DenseTrack employs crowd density estimates as anchors for exact object localization within video frames. These estimates are merged with motion …

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Zero-Shot Object Counting With Good Exemplars, Huilin Zhu, Jingling Yuan, Zhengwei Yang, Yu Guo, Zheng Wang, Xian Zhong, Shengfeng He

Research Collection School Of Computing and Information Systems

Zero-shot object counting (ZOC) aims to enumerate objects in images using only the names of object classes during testing, without the need for manual annotations. However, a critical challenge in current ZOC methods lies in their inability to identify high-quality exemplars effectively. This deficiency hampers scalability across diverse classes and undermines the development of strong visual associations between the identified classes and image content. To this end, we propose the Visual Association-based Zero-shot Object Counting (VA-Count) framework. VACount consists of an Exemplar Enhancement Module (EEM) and a Noise Suppression Module (NSM) that synergistically refine the process of class exemplar identification …

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Beat-It : Beat-Synchronized Multi-Condition 3d Dance Generation, Zikai Huang, Xuemiao Xu, Cheng Xu, Huaidong Zhang, Chenxi Zheng, Jing Qin, Shengfeng He

Research Collection School Of Computing and Information Systems

Dance, as an art form, fundamentally hinges on the precise synchronization with musical beats. However, achieving aesthetically pleasing dance sequences from music is challenging, with existing methods often falling short in controllability and beat alignment. To address these shortcomings, this paper introduces Beat-It, a novel framework for beat-specific, key pose-guided dance generation. Unlike prior approaches, Beat-It uniquely integrates explicit beat awareness and key pose guidance, effectively resolving two main issues: the misalignment of generated dance motions with musical beats, and the inability to map key poses to specific beats, critical for practical choreography. Our approach disentangles beat conditions from music …

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Onerestore : A Universal Restoration Framework For Composite Degradation, Yu Guo, Yuan Gao, Yuxu Lu, Huilin Zhu, Ryan Wen Liu, Shengfeng He

Research Collection School Of Computing and Information Systems

In real-world scenarios, image impairments often manifest as composite degradations, presenting a complex interplay of elements such as low light, haze, rain, and snow. Despite this reality, existing restoration methods typically target isolated degradation types, thereby falling short in environments where multiple degrading factors coexist. To bridge this gap, our study proposes a versatile imaging model that consolidates four physical corruption paradigms to accurately represent complex, composite degradation scenarios. In this context, we propose OneRestore, a novel transformer-based framework designed for adaptive, controllable scene restoration. The proposed framework leverages a unique cross-attention mechanism, merging degraded scene descriptors with image features, …

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Documenting Ethical Considerations In Open Source Ai Models, Haoyu Gao, Mansooreh Zahedi, Christoph Treude, Sarita Rosenstock, Marc Cheong

Research Collection School Of Computing and Information Systems

Background: The development of AI-enabled software heavily depends on AI model documentation, such as model cards, due to different domain expertise between software engineers and model developers. From an ethical standpoint, AI model documentation conveys critical information on ethical considerations along with mitigation strategies for downstream developers to ensure the delivery of ethically compliant software. However, knowledge on such documentation practice remains scarce. Aims: The objective of our study is to investigate how developers document ethical aspects of open source AI models in practice, aiming at providing recommendations for future documentation endeavours. Method: We selected three sources of documentation on …

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An Empirical Study Of Api Misuses Of Data-Centric Libraries, Akalanda Galappaththi, Sarah Nadi, Christoph Treude

Research Collection School Of Computing and Information Systems

Developers rely on third-party library Application Programming Interfaces (APIs) when developing software. However, libraries typically come with assumptions and API usage constraints, whose violation results in API misuse. API misuses may result in crashes or incorrect behavior. Even though API misuse is a well-studied area, a recent study of API misuse of deep learning libraries showed that the nature of these misuses and their symptoms are different from misuses of traditional libraries, and as a result highlighted potential shortcomings of current misuse detection tools. We speculate that these observations may not be limited to deep learning API misuses but may …

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A Survey Of Protocol Fuzzing, Xiaohan Zhang, Cen Zhang, Xinghua Li, Zhengjie Du, Bing Mao, Yeting Li, Pan Li

Research Collection School Of Computing and Information Systems

Communication protocols form the bedrock of our interconnected world, yet vulnerabilities within their implementations pose significant security threats. Recent developments have seen a surge in fuzzing-based research dedicated to uncovering these vulnerabilities within protocol implementations. However, there still lacks a systematic overview of protocol fuzzing for answering the essential questions such as what the unique challenges are, how existing works solve them, and so on. To bridge this gap, we conducted a comprehensive investigation of related works from both academia and industry. Our study includes a detailed summary of the specific challenges in protocol fuzzing and provides a systematic categorization …

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Full-Text Articles in Entire DC Network

Three Classes Of Propofol Binding Sites On Gabaa Receptors, Zi-Wei Chen, Satyanarayana M Chintala, John Bracamontes, Yusuke Sugasawa, Spencer R Pierce, Balazs R Varga, Edward H Smith, Christopher J Edge, Nicholas P Franks, Wayland W L Cheng, Gustav Akk, Alex S Evers

2020-Current year OA Pubs

New Insights Into Innate Immunity In Alzheimer's Disease: From Apoe Protective Variants To Therapies, Yun Chen, David M Holtzman

2020-Current year OA Pubs

A Content Analysis Of Counseling Psychology Literature: Resilience Against Oppression Among People Of Color, David C. Stanley Jr., Rawan H. Atari-Khan

Psychology Faculty Research and Publications

Prophylactic Antibiotics For Excision Of Premalignant Vulvar Lesions: A Pilot Randomized Controlled Trial, Mary M Mullen, Whitney R Grither, Hannah Millimet, David G Mutch, Andrea R Hagemann, Carolyn K Mccourt, Matthew A Powell, Premal H Thaker, Dineo Khabele, Lindsay M Kuroki

2020-Current year OA Pubs

The Dallas Donation After Circulatory Death Transplantation Summit: Expanding Donation After Circulatory Death Procedures Through Process Improvement, Broader Utilization, And Innovation, Michele Finotti, William C. Chapman, Et Al.

2020-Current year OA Pubs

Teacher Self Efficacy And The Work Environment, Marium Carpen

Seton Hall University Dissertations and Theses (ETDs)

Proteomic Analysis Reveals Major Proteins And Pathways That Mediate The Effect Of 17-Β-Estradiol In Cell Division And Apoptosis In Breast Cancer Mcf7 Cells, Zhenqi Zhou, Brihget Sicairos, Jianhong Zhou, Yuchun Du

Biological Sciences Faculty Publications and Presentations

2020-Current year OA Pubs

A Modular Chemigenetic Calcium Indicator For Multiplexed In Vivo Functional Imaging, Helen Farrants, Christian Monroy Hernandez, Yao Chen, Et Al.

2020-Current year OA Pubs

D2sr: Decentralized Detection, De-Synchronization, And Recovery Of Lidar Interference, Darshana Rathnayake, Hemanth Sabbella, Meera Radhakrishnan, Archan Misra

Research Collection School Of Computing and Information Systems

Fabrication And Evaluation Of Multicomponent Biomimetic Scaffolds For Bone Tissue Engineering, Mozan Osman Hassan

Dissertations

Ms Treatment De-Escalation: Review And Commentary, Krzysztof Selmaj, Hans-Peter Hartung, Marcin P Mycko, Igor Selmaj, Anne H Cross

2020-Current year OA Pubs

Interactive Example-Based Explanations To Improve Health Professionals’ Onboarding With Ai For Human-Ai Collaborative Decision Making, Min Hun Lee, Renee Bao Xuan Ng, Silvana Xinyi Choo, Shamala Thilarajah

Research Collection School Of Computing and Information Systems

Self-Adaptive Fine-Grained Multi-Modal Data Augmentation For Semi-Supervised Muti-Modal Coreference Resolution, Li Zheng, Boyu Chen, Hao Fei, Fei Li, Shengqiong Wu, Lizi Liao, Donghong Ji

Research Collection School Of Computing and Information Systems

Brushbuds: Toothbrushing Tracking Using Earphone Imus, Qiang Yang, Yang Liu, Jake Stuchbury-Wass, Kayla-Jade Butkow, Dong Ma, Cecilia Mascolo

Research Collection School Of Computing and Information Systems

An Empirical Study To Evaluate Aigc Detectors On Code Content, Jian Wang, Shangqing Liu, Xiaofei Xie, Yi Li

Research Collection School Of Computing and Information Systems

Enhancing Recipe Retrieval With Foundation Models: A Data Augmentation Perspective, Fangzhou Song, Bin Zhu, Yanbin Hao, Shuo Wang

Research Collection School Of Computing and Information Systems

Risurconv : Rotation Invariant Surface Attention-Augmented Convolutions For 3d Point Cloud Classification And Segmentation, Zhiyuan Zhang, Licheng Yang, Xiang Zhiyu

Research Collection School Of Computing and Information Systems

Audio Description Customization, Rosiana Natalie, Ruei-Che Chang, Sheshadri Smitha, Anhong Guo, Kotaro Hara

Research Collection School Of Computing and Information Systems

Desk2desk : Optimization-Based Mixed Reality Workspace Integration For Remote Side-By-Side Collaboration, Ludwig Sidenmark, Tianyu Zhang, Leen Al Lababidi, Jiannan Li, Tovi Grossman

Research Collection School Of Computing and Information Systems

Direct Range Proofs For Paillier Cryptosystem And Their Applications, Zhikang Xie, Mengling Liu, Haiyang Xue, Man Ho Au, Robert H. Deng, Siu-Ming Yiu

Research Collection School Of Computing and Information Systems

Collaborative Cross-Modal Fusion With Large Language Model For Recommendation, Zhongzhou Liu, Hao Zhang, Kuicai Dong, Yuan Fang

Research Collection School Of Computing and Information Systems

Improving Out-Of-Distribution Detection With Disentangled Foreground And Background Features, Choubo Ding, Guansong Pang

Research Collection School Of Computing and Information Systems

Densetrack : Drone-Based Crowd Tracking Via Density-Aware Motion-Appearance Synergy, Yi Lei, Huilin Zhu, Jingling Yuan, Guangli Xiang, Xian Zhong, Shengfeng He

Research Collection School Of Computing and Information Systems

Zero-Shot Object Counting With Good Exemplars, Huilin Zhu, Jingling Yuan, Zhengwei Yang, Yu Guo, Zheng Wang, Xian Zhong, Shengfeng He

Research Collection School Of Computing and Information Systems

Beat-It : Beat-Synchronized Multi-Condition 3d Dance Generation, Zikai Huang, Xuemiao Xu, Cheng Xu, Huaidong Zhang, Chenxi Zheng, Jing Qin, Shengfeng He

Research Collection School Of Computing and Information Systems

Onerestore : A Universal Restoration Framework For Composite Degradation, Yu Guo, Yuan Gao, Yuxu Lu, Huilin Zhu, Ryan Wen Liu, Shengfeng He

Research Collection School Of Computing and Information Systems

Documenting Ethical Considerations In Open Source Ai Models, Haoyu Gao, Mansooreh Zahedi, Christoph Treude, Sarita Rosenstock, Marc Cheong

Research Collection School Of Computing and Information Systems

An Empirical Study Of Api Misuses Of Data-Centric Libraries, Akalanda Galappaththi, Sarah Nadi, Christoph Treude

Research Collection School Of Computing and Information Systems

A Survey Of Protocol Fuzzing, Xiaohan Zhang, Cen Zhang, Xinghua Li, Zhengjie Du, Bing Mao, Yeting Li, Pan Li

Research Collection School Of Computing and Information Systems