Digital Commons Network^™

Characterizing Dopaminergic Innervation To The Central Amygdala Across Brain Development, Eman Harrison

Summer Research Internship Program

No abstract provided.

Impact Of Chronic Binge Alcohol On Hepatic Immune Infiltration In Siv-Infected Rhesus Macaques, Balseba Tewelde

Summer Research Internship Program

No abstract provided.

Maresin-1 Protects Dopaminergic Neurons In The Sustantia Nigra In A Rat Model Using Misfolded Alpha-Synuclein Seeding, Yasmine Ferrell

Summer Research Internship Program

No abstract provided.

Selected Writings Of Frances Bacon, Frances Bacon

Hannah Arendt Marginalia - All

New York : Modern Library, c 1955 Call #: B1155 .S35

Contains moderate underlinings and marginal linings

https://bardcollege.on.worldcat.org/oclc/722271PDF Information: 112 pages – 8 MB

Abstract Book (Pdf), School Of Medicine

Summer Research Internship Program

Abstract Book for the 2025 Summer Research Internship Program. Participants are listed alphabetically by last name.

Detection Of Oil Pollution On The Tigris River In Iraq Using Fluorescence And Reflecting Techniques, Ahmad K. Ahmad, Thamer M. Mohammed

Karbala International Journal of Modern Science

In this study, a broadband light source (visible and ultraviolet) was used to name minerals via fluorescence spectra and estimate slick oil thickness, ranging from sub-millimetres, using the reflecting spectrum technique. Using a fluorescent technique, we obtained fluorescence spectra of the samples, converting and processing the signals to produce high-resolution data, which enabled the identification of the types of dissolved elements and oil slicks in the Tigris River, highlighting pollution sources and potential control measures. This system aims to show the faint signal in fluorescence samples collected from the cooling system outlet water throughout the refining process from AL-Dora (Baghdad) …

Multilingual Cyber Threat Intelligence Feeds Preprocessing For Threat Intelligence Event Extraction: A Systematic Literature Review, Jamal H. Al-Yasiri, Mohamad Fadli Bin Zolkipli, Nik Fatinah N. Mohd Farid

Karbala International Journal of Modern Science

In cyber threat intelligence (CTI), information security specialists face overwhelming data flows from multiple sources, including hacker forums, dark web markets, and social media. These diverse and multilingual information streams require extensive analysis and processing. However, the current state of CTI faces several challenges, such as reliance on manual annotation and evaluation, as well as limited support for non-English languages, which hinders advanced threat detection and comprehensive analysis. This systematic literature review proposes a conceptual framework designed to overcome existing state-of-the-art limitations. It evaluates recent advancements in CTI methodologies by following PRISMA guidelines and analyzing selected studies from reputable sources, …

A New Species Of Viscachataenia (Cestoda: Anoplocephalidae) From The Southern Mountain Viscacha, Lagidium Viscacia (Hystricomorpha: Chinchillidae), In Bolivia, Terry R. Haverkost, Scott L. Gardner

MANTER: Journal of Parasite Biodiversity

Anoplocephalid cestodes collected from the southern mountain viscacha, Lagidium viscacia, in Boliva in 1986 are here examined, and a new species of Viscachataenia is described. The new species has numerous body measurements that are larger than the existing species, V. quadrata, but the eggs and corresponding structures of the new species are all smaller than those of V. quadrata.

The Nicene Creed And The Question Of The Filioque In Conversations Between Lutherans And Orthodox Christians In North America: 1993–2003, Thomas R. Lee

Consensus

No abstract provided.

The Triune God Spills Into Creation, Calling Us To Love One Another, Kyle Schiefelbein-Guerrero

Consensus

No abstract provided.

More Everything Forever: Ai Overlords, Space Empires, And Silicon Valley’S Crusade To Control The Fate Of Humanity, Joseph Kirby

Consensus

Becker, A. (2025). More everything forever : AI overlords, space empires, and Silicon Valley’s crusade to control the fate of humanity. Basic Books. ISBN: 9781541619593

Autism Spectrum Disorder: A Review Of Genomic Risk Factors, Diagnostic And Pharmacotherapeutic Strategies, Zohor Azher

Saudi Toxicology Journal

Autism Spectrum Disorder (ASD) is a multifactorial neurodevelopmental condition characterized by impairments in social communication and delayed language development, repetitive behaviors, and sensory processing abnormalities. The genetic background of ASD remains incompletely understood due to significant genetic heterogeneity and complexity. This review aims to present current insights into the genetic landscape of ASD, focusing on both common and rare genomic variations. We describe candidate genes associated with ASD, as they are involved in synaptic function and neuronal signaling, making these findings potential therapeutic targets. This review emphasizes the importance of integrating comprehensive clinical assessments with advanced genetic investigations to enhance …

Dual Action Dynamics: Assessing Hypopharyngeal Cancer Cell Survival Using Combination Chemotherapy, Luke Nieman

Biology Summer Fellows

Targeting glucose metabolism is an attractive strategy for cancer treatment, as cancer cells rely more heavily on glycolysis than oxidative phosphorylation, a phenomenon known as the Warburg Effect (Wang et al 2015). Reversing this metabolic reprogramming can impair cancer cell proliferation. NG52, a small-molecule inhibitor of PGK1, has been shown to effectively reverse the Warburg Effect and reduce cancer cell viability (Wycliffe et al. 2007). Paclitaxel, commonly Taxol, is a chemotherapeutic agent that disrupts mitotic spindle function, causing mitotic arrest and apoptosis (Markman et al 2005). In this study, we aimed to evaluate the individual and combined effects of NG52 …

Classroom Enrichment-Based Energy-Exhaustion Games And Their Impact On Developing Selected Social Skills And Physical Attributes And Reducing Hyperactivity And Attention Deficit In Gifted Students, Nihad Mohammed Alwan, Ali Sadiq Dhiyab, Doaa Muhib Al-Din Ahmed, Farah Alaa Jafar

Modern Sport

The significance of this research lies in exploring the impact of energy-exhausting games through enrichment classroom activities on the development of specific social skills and physical attributes, as well as reducing hyperactivity and attention deficit among gifted students aged 13. The research problem emerged from the question: To what extent can energy-exhausting games, when implemented through enrichment classroom programs, contribute to enhancing selected social and physical traits and minimizing hyperactivity and attention deficit? This study aimed to (a) identify the levels of specific social skills in the sample, (b) identify the values of specific physical attributes in the sample, (c) …

Phase 1b/2 Study Evaluating Safety, Efficacy And Immune Effects Of Tlr9 Agonist Cavrotolimod With Anti-Pd-1 Antibodies Among Patients With Advanced Solid Tumors, Mohammed M Milhem, George Ansstas, Et Al.

2020-Current year OA Pubs

BACKGROUND: There is an unmet need for novel immunotherapies to overcome immune evasion in patients with advanced skin cancers resistant to programmed death (PD)-1 / PD-ligand 1 (PD-L1) blockade. Cavrotolimod is a novel spherical nucleic acid configuration of a toll-like receptor 9 agonist oligonucleotide, designed to trigger innate and adaptive immune responses to tumors.

PATIENTS AND METHODS: The safety, pharmacokinetics, pharmacodynamics and preliminary efficacy of intratumoral cavrotolimod, first dosed alone and then in combination with anti-PD-1 antibodies (pembrolizumab or cemiplimab), were assessed in a combined Phase 1b/2 dose escalation/dose expansion study in patients with advanced skin cancers, including melanoma, Merkel …

Can We Train Bots To Negotiate Like Lawyers? And What Do We Learn About Bargaining As We Do?, Dwight Golann

Suffolk University Law School Faculty Works

Forthcoming in 79 Wash. U. J. of Law and Policy ____ (2025)

AI “bots” like ChatGPT can negotiate without training, but they are overly cooperative, making concessions that weaken their bargaining position—unlike skilled legal negotiators, who adapt their tactics to individual situations as well as what occurs in the process and move as needed between cooperative and competitive tactics.

The article explores how to train bots to “negotiate like lawyers” by giving them role instructions, knowledge about bargaining, and iterative practice, including step-by-step instructions to create a bargaining bot in ChatGPT.

The author notes that texts on negotiation, and his …

Patterns And Processes Behind Secretive Marshbird Movement, Abundance, And Distribution Across Southeastern Louisiana, Leah Moran

LSU Doctoral Dissertations

Restoration and conservation of coastal Louisiana hinges on understanding the patterns and processes underlying habitat heterogeneity on the landscape and therefore the species that inhabits this region, including secretive marshbirds. Elusive in nature, this guild of birds has evolved under dynamic hydroperiods, and myriad plant communities present within wetlands. Only recently, however, has research focused on the role of hydrologic dynamics and vegetative structure and distribution on abundance, movement and detection of marshbirds, specifically within southeastern Louisiana. This study aimed to quantify the ecological patterns and processes, particularly hydrologic processes and landscape structure, driving breeding secretive marshbird movement, abundance and …

(Arise) Achievements In Research, Inquiry And Scholarship Exhibition 2025, Office Of Undergraduate Research

(ARISE) Achievements in Research, Inquiry and Scholarship Exhibition

Conference held at John A. Delaney Student Union on July 25, 2025

Comparative Analysis Of Seasonal Mixed Integrated Autoregressive Moving Average And Feed-Forward Neural Networks Models In Predicting United State Natural Hazard Casualties, Mohammed Q. Ibrahim, Azhar A. Mohammed, Alaa A. Khalaf, Nooruldeen A. Noori

Baghdad Science Journal

Improving the statistical and predictive accuracy, especially of the data on natural hazards, is important in addressing these issues. Therefore, policymakers urgently need a reliable forecasting methodology that provides decision-makers with early estimates of future and resulting healthcare expenditures based on historical time series data, so that they can assess potential risks. Researchers in the field of time series face the problem of choosing the best model for analysis from among several available models. Hence, this study compares the most effective model between a time series structure and a neural network model. Therefore, this research compares the predictive performance of …

The Effect Of Qber Estimation On The Efficiency And Security Of Quantum Key Distribution, Sufyan Al-Janabi

Baghdad Science Journal

Quantum Key Distribution (QKD) is a prominent solution to achieve proven secure data transmission between legitimate users despite any assumptions about the eavesdropper's computational power (given that the laws of quantum mechanics are correct). This remains true even under attacks by quantum computers. In recent years, there has been a great research interest in developing enhanced security constructions based on QKD. This is mainly driven by the envisioned threats of quantum computers to the traditional information security infrastructure based on public key cryptography. This research lies under the wide umbrella of the so-called post-quantum cryptography. However, for any QKD protocol, …

Performance Of Cnn And Lstm Model On Covid-19 News Headline Data Classification, Dian Kurniasari, Luthfia Nur Azizah, Purnomo Husnul Khotimah, Warsono

Baghdad Science Journal

During the COVID-19 pandemic, mass media, especially online news portals, have been essential in disseminating health information and governmental policies, serving as the primary reference for the general public. Unfortunately, not all news articles are relevant to COVID-19 case monitoring. Some sources provide information that is less useful for tracking the pandemic's progression. Thus, it is crucial to develop a methodology that allows news articles to effectively aid stakeholders in monitoring COVID-19 developments. This study proposes using Deep Learning (DL) models to classify news headlines for this purpose. The aim is to identify suitable and reliable DL models for classifying …

A Study On Machine Learning Based Parkinson Disease Prediction, Suparna Dasgupta, Soumyabrata Saha, Pronay Pal, Shilarchana Maiti, Sudarshan Nath

Baghdad Science Journal

Parkinson's Disease, a neurodegenerative disorder, is one of the major chronic health issues in the world. It causes a severe disorder that affects majorly muscle control but it can also be the reason of affecting senses, cognitive ability and cognitive health. Approximately, 90% of the Parkinson affected people face speech difficulty. Conventional diagnosis methods may be biased which may result in wrong diagnosis of Parkinson's Disease because symptoms are usually elusive. This study aims to assess how well different machine learning algorithms can predict Parkinson's disease using vowel phonation data, with the goal of early detection and more accurate patient …

Enhancing Fetal Health Assessment Using Machine Learning And Xai Techniques, Niaz Ashraf Khan, A. M. Saadman Rafat

Baghdad Science Journal

Fetal health assessment is crucial for ensuring the well-being of both mother and fetus during pregnancy. Accurate monitoring can reduce child and maternal mortality rates, particularly in low- and middle-income countries where these rates are higher. This research aims to enhance fetal health classification using advanced machine learning techniques and Explainable Artificial Intelligence (XAI) to address the gaps in predictive accuracy and model transparency. A dataset of 2,126 records with 22 features from Cardiotocography (CTG) readings. The dataset was balanced using Synthetic Minority Over-sampling Technique (SMOTE) to handle class imbalances. Various machine learning algorithms, including LightGBM, XGBoost, and Random Forest, …

Twist And Snout: Head And Body Morphologies Determine Feeding Kinematics In Substrate-Biting Fishes, Tal Perevolotsky, Jacob M. Brotman-Krass, Yarden Ratner, Yael Avigad, Adam P. Summers, Cassandra M. Donatelli, Roi Holzman

Engineering Faculty Articles and Research

Synopsis

Across teleosts, feeding by biting substrate-attached prey has evolved multiple times and is associated with convergent morphologies that include a deep body and an elongated, tapered head. However, the functional role of these morphologies in substrate-biting fish is not established. Here, we tested the hypothesis that these morphologies function as control surfaces that affect feeding kinematics during biting. To test this hypothesis, we used simplified physical models of substrate-biting reef fish and examined the role of head, body, and fin morphology in determining feeding kinematics that facilitate the removal of substrate-attached prey. Models simulated the swift lateral movement of …

Long Term Outcomes Of Dermal Substrate Treated Burns And Wounds, Sarvesh Senguttunvan, Sigrid A. Blome-Eberwein Md

Research Scholars

No abstract provided.

Human Ipsc-Based Breast Cancer Model Identifies S100p-Dependent Cancer Stemness Induced By Brca1 Mutation, Jingxin Liu, Cai Zhao, Jiahao Chen, Pengguihang Zeng, Qingjian Li, Ranran Dai, Xingqiang Lai, Wenqian Song, Jianing Chen, Xixi Zhu, Xinyi Liu, Jun Sun, Jia Wang, Peihang Fang, Tengfei Wang, Wenjie Chen, Diana Guallar, Nan Cao, Jianli Zhao, Shicheng Su, Andy Peng Xiang, Yi Arial Zeng, Jie Li, Junchao Cai, Dung-Fang Lee, Jinxin Bei, Yongliang Huo, Hai Hu, Shengbao Suo, Dong-Feng Huang, Jin Bai, Junjun Ding

Faculty, Staff and Student Publications

Breast cancer is the most common malignancy in females and remains the leading cause of cancer-related deaths for women worldwide. The cellular and molecular basis of breast tumorigenesis is not completely understood partly due to the lack of human research models which simulate the development of breast cancer. Here, we developed a method for generating functional mammary-like cells (MCs) from human-induced pluripotent stem cells (iPSCs). The iPSC-MCs closely resemble human primary MCs at cellular, transcriptional, and functional levels. Using this method, a breast cancer model was generated using patient-derived iPSCs harboring germline

Mixed Galerkin- Implicit Differences Methods For Solving Couple Nonlinear Parabolic System With Constant Coefficients, Wafaa Abd Ibrahim, Jamil A. Ali Al-Hawasy

Baghdad Science Journal

In this paper, the mixed Galerkin- implicit difference method (MGIFDM) is used to solve a couple of nonlinear systems of parabolic partial differential equations with constant coefficients which are abbreviated by (CNPSCC). At first the weak form of the CNPSCC is formulated and then it is discretized using the proposed method, the method mixes the Galerkin finite element method (GFEM) in space variables with the implicit finite difference method (IFDM) in time variables, so the method was named by MGIFDM. At any discrete time tj the method transforms the CNPSCC into a couple Galerkin nonlinear algebraic system (CGNAS), which is …

A Study Of The Atangana Baleanu Fractional Differential Equation With An Application In Gas Dynamic Problem, Amjad Shaikh, Shashikant Waghule, Dinkar Patil, Kottakkaran Sooppy Nisar

Baghdad Science Journal

This article presents an analytical approximation for the nonlinearity of the fractional order gas dynamics equation in both homogeneous and nonhomogeneous cases, with a particular emphasis on shock fronts. The approach utilizes the fractional differentiation operator proposed by Atangana and Baleanu. By employing this operator, an approximate solution for the fractional order gas dynamic equations in scenarios involving shock fronts is derived. The solution process primarily involves an iterative procedure that leverages the Laplace transform for numerical computations. The use of the Laplace transform minimizes round-off errors, resulting in a solution that is both precise and straightforward to implement. The …

Enhancing Feature Selection In Network Intrusion Detection Systems Using A Novel Hybrid Binary Swarm Algorithms, Maher Khalaf Hussein, Asmaa Alqassab, Lubna Thanoon Alkahla

Baghdad Science Journal

An intrusion detection system (IDS) is a system that monitors network traffic for any mistrustful activity and issues alerts when it is detected. The selection of feature stage is important in effective intrusion detection systems, as it determines the features that are most influential in detecting normal traffic and malicious traffic. In this study, new proposed hybrid method for selecting features in intrusion detection systems based on the hybrid binary Salp Swarm algorithm (SSA) and the binary Pigeon Inspired Optimizer (PIO), inspired by the collective behavior of animals. The proposed method removes unnecessary features and increases the number of features …

Creation Of Bacteria In Tongue Diagnosis Based On Fractal Methods, S. Pavithra, G. Jayalalitha

Baghdad Science Journal

Bacteria play a vital role in helping with digestion and protecting against harmful infections. However, the Gram-negative bacteria in Tongue will have some disadvantages in the human body. These can be diagnosed by employing the fractal concept. Bacteria's irregular shape and Complex nature can be quantified using fractal dimensions that exhibit self-similarity at different scales. The fractal measurement procedure deliberates the dissimilarity and surface complexity of the tongue-inclusive spot on the tongue. An image of the tongue is analyzed by the HarFa Fractal Method. The Sobel improved Box counting Method is employed to enumerate the outgrowth of Bacteria in Tongue. …