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Enterococcus Faecium Septicemia In A Dog: Clinical Features And Molecular Screening Of Virulence Genes Of Enterococcus, Trasida Ployngam, Numfa Fungbun

The Thai Journal of Veterinary Medicine

A one-year-old Golden Retriever male dog manifested multi-systemic inflammation with a marked increment of plasma D-dimer. Enterococcus spp. was identified from hemoculture and it showed multidrug resistance (MDR), including amikacin, cephazolin, ceftriaxone, clindamycin, imipenem, penicillin G and sulfa-trimethoprim. Pure Enterococcus colonies were identified for species-specific DNA by PCR amplification and sequencing. It was 100% identical with the Enterococcus faecium strains in the National Center for Biotechnology Information (NCBI) database. Molecular screening of virulence genes of the isolated E. faecium strain exhibited four of nine genes including gelatinase (gelE), cell wall adhesion (efaAfm), second collagen adhesin (scm) and adhesin of collagen …

Acquired Indirect Unilateral Chronic Reducible Scrotal Hernia In An Arabian Stallion, Mohamed A. Marzok, Adel I. Almubarak, Mahmoud Kandeel, Adel A. Badawy

The Thai Journal of Veterinary Medicine

This case report describes the presentation and surgical management of acquired indirect unilateral chronic reducible scrotal herniation in an 8-year-old Arabian stallion. The horse had a history of moderate unilateral swelling of the scrotum that had been noticed by the owner for 10 months. Upon palpation, the swelling was soft, reducible, painless and not accompanied by an acute abdomen. Ultrasonography, rectal and clinical examination were useful tools for the diagnosis of scrotal hernias in this case. A successful surgical herniorrhaphy was performed with the removal of the testicle at the affected side and the superficial inguinal ring was closed by …

Faculty Affairs Committee Minutes Of The Academic Senate 2022-09-01, University Of Dayton. Faculty Affairs Committee

All Committee Minutes

Approved minutes of a meeting of the Faculty Affairs Committee of the Academic Senate of the University of Dayton.

Student Academic Policies Committee Minutes Of The Academic Senate 2022-09-01, University Of Dayton. Student Academic Policies Committee

All Committee Minutes

Approved minutes of a meeting of the Student Academic Policies Committee of the Academic Senate of the University of Dayton.

Clinico-Laboratory Profile And Outcome Of Covid-19 In Patients With Chronic Immune Thrombocytopenia, Sameer Chhetri Aryal, Sheeren Zia, Harshita Mehrotra, Oluwayomi Oyedeji, Zaher K. Otrock

Pathology Meeting Abstracts

Background/Case Studies: Thrombocytopenia is a well-described complication of COVID-19, with numerous proposed mechanisms among which is immune thrombocytopenia (ITP). There are limited data on the characteristics and impact of COVID-19 on patients with previously diagnosed ITP.

Study Design/Methods: This is a retrospective review of all chronic ITP patients who were diagnosed with COVID-19 between 03/2020 and 01/2022 at a tertiary care center. The study was approved by the IRB. Patients with secondary thrombocytopenia, missing data, and unavailable follow up after COVID-19 diagnosis, were excluded. Demographic data, comorbidities, clinico-laboratory findings before and after COVID-19 diagnosis, management of COVID-19 and outcome were …

Twilytics: A Social Perception Analysis Of Public Transit Systems During The Covid-19 Pandemic, Egbe-Etu Etu, Imokhai Tenebe, Ankur Parma, Likhitha Yelamanchili, Dang Minh Nhu Nguyen, Louis Tran, Ihor Markevych

Mineta Transportation Institute

In the United States, public transit ridership in 2020 declined by 79% compared to 2019 levels. With lockdowns implemented during the early days of the pandemic, direct human-to-human interactions migrated to virtual platforms (e.g., Facebook, Twitter, and Reddit). Social media platforms have aided researchers in answering numerous questions about current societal dilemmas, including COVID-19. This study investigates the public’s perception of transit systems via a social media analysis given the emergence of vaccines and other COVID-19 preventive measures. Findings revealed themes of fear and confusion concerning the use of public transportation during the pandemic. The public had doubts regarding the …

Routes To Lower Greenhouse Gas Emissions From Freight Transportation In The City Of San José, Serena Alexander, Kyle Laveroni, Maxwell Friedman, Janani Thiagrajan

Mineta Transportation Institute

Freight represents approximately 30% of all transportation-related emissions in the U.S., but local climate action plans (CAPs) and freight plans often place limited emphasis on freight emissions reduction strategies. The objective of this report is to examine and present strategies for the City of San José, California to reduce GHG emissions from freight. The authors conducted a geospatial analysis of freight data related to San José, and an analysis of relevant literature and successful freight reduction strategies implemented globally. The report also provides key objectives and generalized strategies to reduce GHG emissions from freight as well as specific recommendations for …

Optimal Standards Of Proof In Antitrust, Murat C. Mungan, Joshua Wright

Faculty Scholarship

Economic analyses of antitrust institutions have thus far focused predominantly on optimal penalties and the design of substantive legal rules, and have largely ignored the standard of proof used in trials as a policy tool in shaping behavior. This neglected tool can play a unique role in the antitrust context, where a given firm may have the choice to engage in exceptional anticompetitive or procompetitive behavior, or simply follow more conventional business practices. The standard of proof used in determining the legality of a firm’s conduct affects not only whether the firm chooses to engage in pro- versus anticompetitive behavior, …

September 1, 2022, The Daily Mississippian

Daily Mississippian (all digitized issues)

No abstract provided.

Towards An Optimal Bus Frequency Scheduling: When The Waiting Time Matters, Songsong Mo, Zhifeng Bao, Baihua Zheng, Zhiyong Peng

Research Collection School Of Computing and Information Systems

Reorganizing bus frequencies to cater for actual travel demands can significantly save the cost of the public transport system. This paper studies the bus frequency optimization problem considering the user satisfaction. Specifically, for the first time to our best knowledge, we study how to schedule the buses such that the total number of passengers who could receive their bus services within the waiting time threshold can be maximized. We propose two variants of the problem, FAST and FASTCO, to cater for different application needs and prove that both are NP-hard. To solve FAST effectively and efficiently, we first present an …

Two-Phase Matheuristic For The Vehicle Routing Problem With Reverse Cross-Docking, Aldy Gunawan, Audrey Tedja Widjaja, Pieter Vansteenwegen, Vincent F. Yu

Research Collection School Of Computing and Information Systems

Cross-dockingis a useful concept used by many companies to control the product flow. It enables the transshipment process of products from suppliers to customers. This research thus extends the benefit of cross-docking with reverse logistics, since return process management has become an important field in various businesses. The vehicle routing problem in a distribution network is considered to be an integrated model, namely the vehicle routing problem with reverse cross-docking (VRP-RCD). This study develops a mathematical model to minimize the costs of moving products in a four-level supply chain network that involves suppliers, cross-dock, customers, and outlets. A matheuristic based …

A Traitor-Resistant And Dynamic Anonymous Communication Service For Cloud-Based Vanets, Huiying Hou, Jianting Ning, Yunlei Zhao, Robert H. Deng

Research Collection School Of Computing and Information Systems

Cloud-based VANETs are designed to enable communication between high-speed vehicles. In such a highly dynamic environment, how to provide secure and anonymous communication service is a challenge. In this article, we affirmatively address the challenge by proposing a traitor-resistant and dynamic anonymous communication framework (TD-ACF) for cloud-based VANETs, which supports several advantageous features. In TD-ACF, each vehicle is represented by a set of attributes instead of its real identity, and the driving data is transmitted in encrypted form. Therefore, the anonymous authentication and the confidentiality of driving data are achieved in this way. Meanwhile, TD-ACF supports two practical requirements in …

Fine-Grained And Controllably Editable Data Sharing With Accountability In Cloud Storage, Huiying Hou, Jianting Ning, Yunlei Zhao, Robert H. Deng

Research Collection School Of Computing and Information Systems

With the increasing cloud storage service, users can enjoy non-interactive data sharing. Nonetheless, the data owner cannot timely update the shared data all the while. To ensure the timeliness and the authoritative source of the data, some users should be allowed to update the data on behalf of an authoritative data owner without changing data source. However, this allows harmful information to be injected into the data unnoticeably. How to efficiently realize editable cloud-based data sharing supporting malicious user tracing has not been fully explored. To address the problem, we propose a fine-grained and controllably editable cloud-based data sharing scheme …

Learning To Solve Multiple-Tsp With Time Window And Rejections Via Deep Reinforcement Learning, Rongkai Zhang, Cong Zhang, Zhiguang Cao, Wen Song, Puay Siew Tan, Jie Zhang, Bihan Wen, Justin Dauwels

Research Collection School Of Computing and Information Systems

We propose a manager-worker framework (the implementation of our model is publically available at: https://github.com/zcaicaros/manager-worker-mtsptwr) based on deep reinforcement learning to tackle a hard yet nontrivial variant of Travelling Salesman Problem (TSP), i.e. multiple-vehicle TSP with time window and rejections (mTSPTWR), where customers who cannot be served before the deadline are subject to rejections. Particularly, in the proposed framework, a manager agent learns to divide mTSPTWR into sub-routing tasks by assigning customers to each vehicle via a Graph Isomorphism Network (GIN) based policy network. A worker agent learns to solve sub-routing tasks by minimizing the cost in terms of both …

Secure Deterministic Wallet And Stealth Address: Key-Insulated And Privacy-Preserving Signature Scheme With Publicly Derived Public Key, Zhen Liu, Guomin Yang, Duncan S. Wong, Khoa Nguyen, Huaxiong Wang, Xiaorong Ke, Yining Liu

Research Collection School Of Computing and Information Systems

Deterministic Wallet (DW) and Stealth Address (SA) mechanisms have been widely adopted in the cryptocurrency community, due to their virtues on functionality and privacy protection, which come from a key derivation mechanism that allows an arbitrary number of derived keys to be generated from a master key. However, these algorithms suffer a vulnerability that, when one derived key is compromised somehow, the damage is not limited to the leaked derived key only, but to the master key and in consequence all derived keys are compromised. In this article, we introduce and formalize a new signature variant, called Key-Insulated and Privacy-Preserving …

Deep Learning-Based Text Recognition Of Agricultural Regulatory Document, Hua Leong Fwa, Farn Haur Chan

Research Collection School Of Computing and Information Systems

In this study, an OCR system based on deep learning techniques was deployed to digitize scanned agricultural regulatory documents comprising of certificates and labels. Recognition of the certificates and labels is challenging as they are scanned images of the hard copy form and the layout and size of the text as well as the languages vary between the various countries (due to diverse regulatory requirements). We evaluated and compared between various state-of-the-art deep learningbased text detection and recognition model as well as a packaged OCR library – Tesseract. We then adopted a two-stage approach comprising of text detection using Character …

Choice-Based Crowdshipping: A Dynamic Task Display Problem, Alp Arslan, Firat Kilci, Shih-Fen Cheng, Archan Misra

Research Collection School Of Computing and Information Systems

This paper studies the integration of the crowd workforce into a generic last-mile delivery setting in which a set of known delivery requests should be fulfilled at a minimum cost. In this setting, the crowd drivers are able to choose to perform a parcel delivery among the available and displayed requests. We specifically investigate the question: what tasks should be displayed to an individual driver, so as to minimize the overall delivery expenses? In contrast to past approaches, where drivers are either (a) given the choice of a single task chosen so as to optimize the platform’s profit, or (b) …

Deep Learning For Coverage-Guided Fuzzing: How Far Are We?, Siqi Li, Xiaofei Xie, Yun Lin, Yuekang Li, Ruitao Feng, Xiaohong Li, Weimin Ge, Jin Song Dong

Research Collection School Of Computing and Information Systems

Fuzzing is a widely-used software vulnerability discovery technology, many of which are optimized using coverage-feedback. Recently, some techniques propose to train deep learning (DL) models to predict the branch coverage of an arbitrary input owing to its always-available gradients etc. as a guide. Those techniques have proved their success in improving coverage and discovering bugs under different experimental settings. However, DL models, usually as a magic black-box, are notoriously lack of explanation. Moreover, their performance can be sensitive to the collected runtime coverage information for training, indicating potentially unstable performance. In this work, we conduct a systematic empirical study on …

Joint Hyperbolic And Euclidean Geometry Contrastive Graph Neural Networks, Xiaoyu Xu, Guansong Pang, Di Wu, Mingsheng Shang

Research Collection School Of Computing and Information Systems

Graph Neural Networks (GNNs) have demonstrated state-of-the-art performance in a wide variety of analytical tasks. Current GNN approaches focus on learning representations in a Euclidean space, which are effective in capturing non-tree-like structural relations, but they fail to model complex relations in many real-world graphs, such as tree-like hierarchical graph structure. This paper instead proposes to learn representations in both Euclidean and hyperbolic spaces to model these two types of graph geometries. To this end, we introduce a novel approach - Joint hyperbolic and Euclidean geometry contrastive graph neural networks (JointGMC). JointGMC is enforced to learn multiple layer-wise optimal combinations …

Eeg-Video Emotion-Based Summarization: Learning With Eeg Auxiliary Signals, Wai-Cheong L. Lew, Di Wang, Kai-Keng Ang, Joo-Hwee Lim, Chai Quek, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Video summarization is the process of selecting a subset of informative keyframes to expedite storytelling with limited loss of information. In this paper, we propose an EEG-Video Emotion-based Summarization (EVES) model based on a multimodal deep reinforcement learning (DRL) architecture that leverages neural signals to learn visual interestingness to produce quantitatively and qualitatively better video summaries. As such, EVES does not learn from the expensive human annotations but the multimodal signals. Furthermore, to ensure the temporal alignment and minimize the modality gap between the visual and EEG modalities, we introduce a Time Synchronization Module (TSM) that uses an attention mechanism …

Constrained Multiagent Reinforcement Learning For Large Agent Population, Jiajing Ling, Arambam James Singh, Duc Thien Nguyen, Akshat Kumar

Research Collection School Of Computing and Information Systems

Learning control policies for a large number of agents in a decentralized setting is challenging due to partial observability, uncertainty in the environment, and scalability challenges. While several scalable multiagent RL (MARL) methods have been proposed, relatively few approaches exist for large scale constrained MARL settings. To address this, we first formulate the constrained MARL problem in a collective multiagent setting where interactions among agents are governed by the aggregate count and types of agents, and do not depend on agents’ specific identities. Second, we show that standard Lagrangian relaxation methods, which are popular for single agent RL, do not …

Toward Intention Discovery For Early Malice Detection In Bitcoin, Ling Cheng, Feida Zhu, Yong Wang, Huiwen Liu

Research Collection School Of Computing and Information Systems

Bitcoin has been subject to illicit activities more often than probably any other financial assets, due to the pseudo-anonymous nature of its transacting entities. An ideal detection model is expected to achieve all the three properties of (I) early detection, (II) good interpretability, and (III) versatility for various illicit activities. However, existing solutions cannot meet all these requirements, as most of them heavily rely on deep learning without satisfying interpretability and are only available for retrospective analysis of a specific illicit type.First, we present asset transfer paths, which aim to describe addresses' early characteristics. Next, with a decision tree based …

2022-09-01 Faculty Senate Meeting Minutes, Morehead State University. Faculty Senate.

Faculty Senate Records

Faculty Senate meeting minutes from September 1, 2022.

Overall Survival In The Simplify-1 And Simplify-2 Phase 3 Trials Of Momelotinib In Patients With Myelofibrosis, Ruben Mesa, Stephen T Oh, Et Al

2020-Current year OA Pubs

Janus kinase inhibitors (JAKi) approved for myelofibrosis provide spleen and symptom improvements but do not address anemia, a negative prognostic factor. Momelotinib, an inhibitor of ACVR1/ALK2, JAK1 and JAK2, demonstrated activity against anemia, symptoms, and splenomegaly in the phase 3 SIMPLIFY trials. Here, we report mature overall survival (OS) and leukemia-free survival (LFS) from both studies, and retrospective analyses of baseline characteristics and efficacy endpoints for OS associations. Survival distributions were similar between JAKi-naïve patients randomized to momelotinib, or ruxolitinib then momelotinib, in SIMPLIFY-1 (OS HR = 1.02 [0.73, 1.43]; LFS HR = 1.08 [0.78, 1.50]). Two-year OS and LFS …

Tactics Ideation Experiment Data, Thomas L. Ashworth, Carl D. Sorensen

ScholarsArchive Data

This data includes the template worksheets, as well as filled worksheets that include ideas written by the participants in a research experiment. This experiment tested the effectiveness of a novel tactics ideation method (i.e., Random Prompts method) to a modified Brainwriting method. Transcribed copies of this data are also included.

Accompanying the data are experiment briefing presentations, Python code for rapid evaluation of the data (the evaluation methods themselves were also developed by the authors), a spreadsheet file with evaluation data (this is a necessary input to the code), and organizational trees (for team idea sets) associated with the evaluation …

Automatic Fairness Testing Of Neural Classifiers Through Adversarial Sampling, Peixin Zhang, Jingyi Wang, Jun Sun, Xinyu Wang, Guoliang Dong, Xinggen Wang, Ting Dai, Jinsong Dong

Research Collection School Of Computing and Information Systems

Although deep learning has demonstrated astonishing performance in many applications, there are still concerns about its dependability. One desirable property of deep learning applications with societal impact is fairness (i.e., non-discrimination). Unfortunately, discrimination might be intrinsically embedded into the models due to the discrimination in the training data. As a countermeasure, fairness testing systemically identifies discriminatory samples, which can be used to retrain the model and improve the model’s fairness. Existing fairness testing approaches however have two major limitations. Firstly, they only work well on traditional machine learning models and have poor performance (e.g., effectiveness and efficiency) on deep learning …

Does Social Media Accelerate Product Recalls? Evidence From The Pharmaceutical Industry, Yang Gao, Wenjing Duan, Huaxia Rui

Research Collection School Of Computing and Information Systems

Social media has become a vital platform for voicing product-related experiences that may not only reveal product defects but also impose pressure on firms to act more promptly than before. This study scrutinizes the rarely-studied relationship between these voices and the speed of product recalls in the context of the pharmaceutical industry where social media pharmacovigilance is becoming increasingly important for the detection of drug safety signals. Using Federal Drug Administration (FDA) drug enforcement reports and social media data crawled from online forums and Twitter, we investigate whether social media can accelerate the product recall process in the context of …

The Molecular Basis Of Diabetic Cardiomyopath, Ahmed Salaheldin Mustafa Ali Sultan

Dissertations

Diabetes mellitus (DM) is a major and worsening global health problem. Type 2 diabetes mellitus (T2DM) accounts for more than 90% of DM and the global epidemic of obesity largely explains the dramatic increase in the incidence and prevalence of T2DM over the past 20 years. Cardiovascular complications are the major cause of morbidity and mortality in diabetic patients. The electrocardiogram (ECG) of diabetic and obese patients is frequently disturbed. The aim of this project was to characterize and clarify the molecular basis of electro-mechanical dysfunction in the hearts of type 2 diabetic and type 2 diabetic/obese rats. Experiments were …

Globalisation And City-Zenship In A Not-So-Networked Society: Looking For Narratives Of Empowerment In The Process Of Seepage Of Techno-Cultural Practices, Atreyee Majumder

Articles

The article seeks to answer questions crucial to the marginalisation debate like - Is commercial globalisation bringing in more than consumer goods into the developing countries? And if so, then what is the consequent impact on the relationship between the state and its citizens. While the city in the developed world acts as a node of contact with the forces of globalisation, sending out the messages of the global ‘fantasy’, the city in the developing world acts as the receptor of such signals from which the 'fantasy’ can be accessed by the rest of the developed world. Persons living in …

Combined Impacts Of Co2 Enrichment And Water Stress On Growth And Physiology Of Plants Inoculated With An Acc Deaminase Producing Rhizobacterium, Shaijal Babu Ppoyil

Dissertations

This study assessed the water stress mitigating effects of elevated CO₂ on Chloris gayana Kunth cv. Katambora (Rhodes grass) and Medicago sativa L. cv. SuperFast (alfalfa) plants, and how the seed inoculation with one of the ACC deaminase producing plant growth promoting rhizobacterium (PGPR) supplemented the stand-alone plant drought stress mitigating effects of elevated CO₂, under different growing conditions in the United Arab Emirates (UAE). Multiple growth and physiology related variables were measured from the plants in response to different treatment combinations made of CO₂, watering treatments (WT), and PGPR, based on the research design …