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Full-Text Articles in Physical Sciences and Mathematics

Towards Llm-Based Fact Verification On News Claims With A Hierarchical Step-By-Step Prompting Method, Xuan Zhang, Wei Gao Nov 2023

Towards Llm-Based Fact Verification On News Claims With A Hierarchical Step-By-Step Prompting Method, Xuan Zhang, Wei Gao

Research Collection School Of Computing and Information Systems

While large pre-trained language models (LLMs) have shown their impressive capabilities in various NLP tasks, they are still underexplored in the misinformation domain. In this paper, we examine LLMs with in-context learning (ICL) for news claim verification, and find that only with 4-shot demonstration examples, the performance of several prompting methods can be comparable with previous supervised models. To further boost performance, we introduce a Hierarchical Step-by-Step (HiSS) prompting method which directs LLMs to separate a claim into several subclaims and then verify each of them via multiple questionsanswering steps progressively. Experiment results on two public misinformation datasets show that …

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Krover: A Symbolic Execution Engine For Dynamic Kernel Analysis, Pansilu Madhura Bhashana Pitigalaarachchi Pitigala Arachchillage, Xuhua Ding, Haiqing Qiu, Haoxin Tu, Jiaqi Hong, Lingxiao Jiang Nov 2023

Krover: A Symbolic Execution Engine For Dynamic Kernel Analysis, Pansilu Madhura Bhashana Pitigalaarachchi Pitigala Arachchillage, Xuhua Ding, Haiqing Qiu, Haoxin Tu, Jiaqi Hong, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

We present KRover, a novel kernel symbolic execution engine catered for dynamic kernel analysis such as vulnerability analysis and exploit generation. Different from existing symbolic execution engines, KRover operates directly upon a live kernel thread's virtual memory and weaves symbolic execution into the target's native executions. KRover is compact as it neither lifts the target binary to an intermediary representation nor uses QEMU or dynamic binary translation. Benchmarked against S2E, our performance experiments show that KRover is up to 50 times faster but with one tenth to one quarter of S2E memory cost. As shown in our four case studies, …

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Faire: Repairing Fairness Of Neural Networks Via Neuron Condition Synthesis, Tianlin Li, Xiaofei Xie, Jian Wang, Qing Guo, Aishan Liu, Lei Ma, Yang Liu Nov 2023

Faire: Repairing Fairness Of Neural Networks Via Neuron Condition Synthesis, Tianlin Li, Xiaofei Xie, Jian Wang, Qing Guo, Aishan Liu, Lei Ma, Yang Liu

Research Collection School Of Computing and Information Systems

Deep Neural Networks (DNNs) have achieved tremendous success in many applications, while it has been demonstrated that DNNs can exhibit some undesirable behaviors on concerns such as robustness, privacy, and other trustworthiness issues. Among them, fairness (i.e., non-discrimination) is one important property, especially when they are applied to some sensitive applications (e.g., finance and employment). However, DNNs easily learn spurious correlations between protected attributes (e.g., age, gender, race) and the classification task and develop discriminatory behaviors if the training data is imbalanced. Such discriminatory decisions in sensitive applications would introduce severe social impacts. To expose potential discrimination problems in DNNs …

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Laf: Labeling-Free Model Selection For Automated Deep Neural Network Reusing, Qiang Hu, Yuejun Guo, Xiaofei Xie, Maxime Cordy, Mike Papadakis, Yves Le Traon Nov 2023

Laf: Labeling-Free Model Selection For Automated Deep Neural Network Reusing, Qiang Hu, Yuejun Guo, Xiaofei Xie, Maxime Cordy, Mike Papadakis, Yves Le Traon

Research Collection School Of Computing and Information Systems

pplying deep learning (DL) to science is a new trend in recent years, which leads DL engineering to become an important problem. Although training data preparation, model architecture design, and model training are the normal processes to build DL models, all of them are complex and costly. Therefore, reusing the open-sourced pre-trained model is a practical way to bypass this hurdle for developers. Given a specific task, developers can collect massive pre-trained deep neural networks from public sources for reusing. However, testing the performance (e.g., accuracy and robustness) of multiple deep neural networks (DNNs) and recommending which model should be …

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Pro-Cap: Leveraging A Frozen Vision-Language Model For Hateful Meme Detection, Rui Cao, Ming Shan Hee, Adriel Kuek, Wen Haw Chong, Roy Ka-Wei Lee, Jing Jiang Nov 2023

Pro-Cap: Leveraging A Frozen Vision-Language Model For Hateful Meme Detection, Rui Cao, Ming Shan Hee, Adriel Kuek, Wen Haw Chong, Roy Ka-Wei Lee, Jing Jiang

Research Collection School Of Computing and Information Systems

Hateful meme detection is a challenging multimodal task that requires comprehension of both vision and language, as well as cross-modal interactions. Recent studies have tried to fine-tune pre-trained vision-language models (PVLMs) for this task. However, with increasing model sizes, it becomes important to leverage powerful PVLMs more efficiently, rather than simply fine-tuning them. Recently, researchers have attempted to convert meme images into textual captions and prompt language models for predictions. This approach has shown good performance but suffers from non-informative image captions. Considering the two factors mentioned above, we propose a probing-based captioning approach to leverage PVLMs in a zero-shot …

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Matk: The Meme Analytical Tool Kit, Ming Shan Hee, Aditi Kumaresan, Nguyen Khoi Hoang, Nirmalendu Prakash, Rui Cao, Roy Ka-Wei Lee Nov 2023

Matk: The Meme Analytical Tool Kit, Ming Shan Hee, Aditi Kumaresan, Nguyen Khoi Hoang, Nirmalendu Prakash, Rui Cao, Roy Ka-Wei Lee

Research Collection School Of Computing and Information Systems

The rise of social media platforms has brought about a new digital culture called memes. Memes, which combine visuals and text, can strongly influence public opinions on social and cultural issues. As a result, people have become interested in categorizing memes, leading to the development of various datasets and multimodal models that show promising results in this field. However, there is currently a lack of a single library that allows for the reproduction, evaluation, and comparison of these models using fair benchmarks and settings. To fill this gap, we introduce the Meme Analytical Tool Kit (MATK), an open-source toolkit specifically …

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Revisiting Disentanglement And Fusion On Modality And Context In Conversational Multimodal Emotion Recognition, Bobo Li, Hao Fei, Lizi Liao, Yu Zhao, Chong Teng, Tat-Seng Chua, Donghong Ji, Fei Li Nov 2023

Revisiting Disentanglement And Fusion On Modality And Context In Conversational Multimodal Emotion Recognition, Bobo Li, Hao Fei, Lizi Liao, Yu Zhao, Chong Teng, Tat-Seng Chua, Donghong Ji, Fei Li

Research Collection School Of Computing and Information Systems

It has been a hot research topic to enable machines to understand human emotions in multimodal contexts under dialogue scenarios, which is tasked with multimodal emotion analysis in conversation (MM-ERC). MM-ERC has received consistent attention in recent years, where a diverse range of methods has been proposed for securing better task performance. Most existing works treat MM-ERC as a standard multimodal classification problem and perform multimodal feature disentanglement and fusion for maximizing feature utility. Yet after revisiting the characteristic of MM-ERC, we argue that both the feature multimodality and conversational contextualization should be properly modeled simultaneously during the feature disentanglement …

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Partial Annotation-Based Video Moment Retrieval Via Iterative Learning, Wei Ji, Renjie Liang, Lizi Liao, Hao Fei, Fuli Feng Nov 2023

Partial Annotation-Based Video Moment Retrieval Via Iterative Learning, Wei Ji, Renjie Liang, Lizi Liao, Hao Fei, Fuli Feng

Research Collection School Of Computing and Information Systems

Given a descriptive language query, Video Moment Retrieval (VMR) aims to seek the corresponding semantic-consistent moment clip in the video, which is represented as a pair of the start and end timestamps. Although current methods have achieved satisfying performance, training these models heavily relies on the fully-annotated VMR datasets. Nonetheless, precise video temporal annotations are extremely labor-intensive and ambiguous due to the diverse preferences of different annotators.Although there are several works trying to explore weakly supervised VMR tasks with scattered annotated frames as labels, there is still much room to improve in terms of accuracy. Therefore, we design a new …

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Heterogeneous Graph Neural Network With Multi-View Representation Learning, Zezhi Shao, Yongjun Xu, Wei Wei, Fei Wang, Zhao Zhang, Feida Zhu Nov 2023

Heterogeneous Graph Neural Network With Multi-View Representation Learning, Zezhi Shao, Yongjun Xu, Wei Wei, Fei Wang, Zhao Zhang, Feida Zhu

Research Collection School Of Computing and Information Systems

In recent years, graph neural networks (GNNs)-based methods have been widely adopted for heterogeneous graph (HG) embedding, due to their power in effectively encoding rich information from a HG into the low-dimensional node embeddings. However, previous works usually easily fail to fully leverage the inherent heterogeneity and rich semantics contained in the complex local structures of HGs. On the one hand, most of the existing methods either inadequately model the local structure under specific semantics, or neglect the heterogeneity when aggregating information from the local structure. On the other hand, representations from multiple semantics are not comprehensively integrated to obtain …

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Ppdf: A Privacy-Preserving Cloud-Based Data Distribution System With Filtering, Yudi Zhang, Willy Susilo, Fuchun Guo, Guomin Yang Nov 2023

Ppdf: A Privacy-Preserving Cloud-Based Data Distribution System With Filtering, Yudi Zhang, Willy Susilo, Fuchun Guo, Guomin Yang

Research Collection School Of Computing and Information Systems

Cloud computing has emerged as a popular choice for distributing data among both individuals and companies. Ciphertext-policy attribute-based encryption (CP-ABE) has been extensively used to provide data security and enable fine-grained access control. With this encryption technique, only users whose attributes satisfy the access policy can access the plaintext. In order to mitigate the computational overhead on users, particularly on lightweight devices, partial decryption has been introduced, where the cloud assists in performing the decryption computations without revealing sensitive information. However, in this process, the cloud obtains the user's attributes, thus infringing on the user's privacy. To address this issue, …

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Spatial Data Management For Green Mobility, Christophe Claramunt, Christine Bassem, Demetrios Zeinalipour-Yazti, Baihua Zheng, Goce Trajcevski, Kristian Torp Nov 2023

Spatial Data Management For Green Mobility, Christophe Claramunt, Christine Bassem, Demetrios Zeinalipour-Yazti, Baihua Zheng, Goce Trajcevski, Kristian Torp

Research Collection School Of Computing and Information Systems

While many countries are developing appropriate actions towards a greener future and moving towards adopting sustainable mobility activities, the real-time management and planning of innovative transportation facilities and services in urban environments still require the development of advanced mobile data management infrastructures. Novel green mobility solutions, such as electric, hybrid, solar and hydrogen vehicles, as well as public and gig-based transportation resources are very likely to reduce the carbon footprint. However, their successful implementation still needs efficient spatio-temporal data management resources and applications to provide a clear picture and demonstrate their effectiveness. This paper discusses the major data management challenges, …

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Github Actions: The Impact On The Pull Request Process, Mairieli Wessel, Joseph Vargovich, Marco Gerosa, Christoph Treude Nov 2023

Github Actions: The Impact On The Pull Request Process, Mairieli Wessel, Joseph Vargovich, Marco Gerosa, Christoph Treude

Research Collection School Of Computing and Information Systems

Software projects frequently use automation tools to perform repetitive activities in the distributed software development process. Recently, GitHub introduced GitHub Actions, a feature providing automated workflows for software projects. Understanding and anticipating the effects of adopting such technology is important for planning and management. Our research investigates how projects use GitHub Actions, what the developers discuss about them, and how project activity indicators change after their adoption. Our results indicate that 1,489 out of 5,000 most popular repositories (almost 30% of our sample) adopt GitHub Actions and that developers frequently ask for help implementing them. Our findings also suggest that …

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Cgt-Gan: Clip-Guided Text Gan For Image Captioning, Jiarui Yu, Haoran Li, Yanbin Hao, Bin Zhu, Tong Xu, Xiangnan He Nov 2023

Cgt-Gan: Clip-Guided Text Gan For Image Captioning, Jiarui Yu, Haoran Li, Yanbin Hao, Bin Zhu, Tong Xu, Xiangnan He

Research Collection School Of Computing and Information Systems

The large-scale visual-language pre-trained model, Contrastive Language-Image Pre-training (CLIP), has significantly improved image captioning for scenarios without human-annotated image-caption pairs. Recent advanced CLIP-based image captioning without human annotations follows a text-only training paradigm, i.e., reconstructing text from shared embedding space. Nevertheless, these approaches are limited by the training/inference gap or huge storage requirements for text embeddings. Given that it is trivial to obtain images in the real world, we propose CLIP-guided text GAN (CgT-GAN), which incorporates images into the training process to enable the model to "see" real visual modality. Particularly, we use adversarial training to teach CgT-GAN to mimic …

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Metaformer Baselines For Vision, Weihao Yu, Chenyang Si, Pan Zhou, Mi Luo, Yichen Zhou, Jiashi Feng, Shuicheng Yan, Xinchao Wang Nov 2023

Metaformer Baselines For Vision, Weihao Yu, Chenyang Si, Pan Zhou, Mi Luo, Yichen Zhou, Jiashi Feng, Shuicheng Yan, Xinchao Wang

Research Collection School Of Computing and Information Systems

Abstract—MetaFormer, the abstracted architecture of Transformer, has been found to play a significant role in achieving competitive performance. In this paper, we further explore the capacity of MetaFormer, again, by migrating our focus away from the token mixer design: we introduce several baseline models under MetaFormer using the most basic or common mixers, and demonstrate their gratifying performance. We summarize our observations as follows: (1) MetaFormer ensures solid lower bound of performance. By merely adopting identity mapping as the token mixer, the MetaFormer model, termed IdentityFormer, achieves >80% accuracy on ImageNet-1K. (2) MetaFormer works well with arbitrary token mixers. When …

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A Survey On Aspect-Based Sentiment Analysis: Tasks, Methods, And Challenges, Wenxuan Zhang, Xin Li, Yang Deng, Lidong Bing, Wai Lam Nov 2023

A Survey On Aspect-Based Sentiment Analysis: Tasks, Methods, And Challenges, Wenxuan Zhang, Xin Li, Yang Deng, Lidong Bing, Wai Lam

Research Collection School Of Computing and Information Systems

As an important fine-grained sentiment analysis problem, aspect-based sentiment analysis (ABSA), aiming to analyze and understand people's opinions at the aspect level, has been attracting considerable interest in the last decade. To handle ABSA in different scenarios, various tasks are introduced for analyzing different sentiment elements and their relations, including the aspect term, aspect category, opinion term, and sentiment polarity. Unlike early ABSA works focusing on a single sentiment element, many compound ABSA tasks involving multiple elements have been studied in recent years for capturing more complete aspect-level sentiment information. However, a systematic review of various ABSA tasks and their …

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Leveraging Long Short-Term User Preference In Conversational Recommendation Via Multi-Agent Reinforcement Learning, Yang Deng, Yaliang Li, Bolin Ding, Wai Lam Nov 2023

Leveraging Long Short-Term User Preference In Conversational Recommendation Via Multi-Agent Reinforcement Learning, Yang Deng, Yaliang Li, Bolin Ding, Wai Lam

Research Collection School Of Computing and Information Systems

Conversational recommender systems (CRS) endow traditional recommender systems with the capability of dynamically obtaining users’ short-term preferences for items and attributes through interactive dialogues. There are three core challenges for CRS, including the intelligent decisions for what attributes to ask, which items to recommend, and when to askor recommend, at each conversation turn. Previous methods mainly leverage reinforcement learning (RL) to learn conversational recommendation policies for solving one or two of these three decision-making problems in CRS with separated conversation and recommendation components. These approaches restrict the scalability and generality of CRS and fall short of preserving a stable training …

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Rethinking Conversational Agents In The Era Of Large Language Models: Proactivity, Non-Collaborativity, And Beyond, Yang Deng, Wenqiang Lei, Minlie Huang, Tat-Seng Chua Nov 2023

Rethinking Conversational Agents In The Era Of Large Language Models: Proactivity, Non-Collaborativity, And Beyond, Yang Deng, Wenqiang Lei, Minlie Huang, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Conversational systems are designed to offer human users social support or functional services through natural language interactions. Typical conversation researches mainly focus on the response-ability of the system, such as dialogue context understanding and response generation. In the era of large language models (LLMs), LLM-augmented conversational systems showcase exceptional capabilities of responding to user queries for different language tasks. However, as LLMs are trained to follow users' instructions, LLM-augmented conversational systems typically overlook the design of an essential property in intelligent conversations, i.e., goal awareness. In this tutorial, we will introduce the recent advances on the design of agent's awareness …

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Multimodal Fashion Knowledge Extraction As Captioning, Yifei Yuan, Wenxuan Zhang, Yang Deng, Wai Lam Nov 2023

Multimodal Fashion Knowledge Extraction As Captioning, Yifei Yuan, Wenxuan Zhang, Yang Deng, Wai Lam

Research Collection School Of Computing and Information Systems

Social media plays a significant role in boosting the fashion industry, where a massive amount of fashion-related posts are generated every day. In order to obtain the rich fashion information from the posts, we study the task of social media fashion knowledge extraction. Fashion knowledge, which typically consists of the occasion, person attributes, and fashion item information, can be effectively represented as a set of tuples. Most previous studies on fashion knowledge extraction are based on the fashion product images without considering the rich text information in social media posts. Existing work on fashion knowledge extraction in social media is …

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The High Energy X-Ray Probe: Resolved X-Ray Populations In Extragalactic Environments, Bret D. Lehmer, Kristen Garofali, Breanna A. Binder, Francesca Fornasini, Neven Vulic, Andreas Zezas, Ann Hornschemeier, Margaret Lazzarini, Hannah Moon, Toni Venters, Daniel Wik, Mihoko Yukita, Matteo Bachetti, Javier A. Garcia, Brian Grefenstette, Kristin Madsen, Kaya Mori, Daniel Stern Nov 2023

The High Energy X-Ray Probe: Resolved X-Ray Populations In Extragalactic Environments, Bret D. Lehmer, Kristen Garofali, Breanna A. Binder, Francesca Fornasini, Neven Vulic, Andreas Zezas, Ann Hornschemeier, Margaret Lazzarini, Hannah Moon, Toni Venters, Daniel Wik, Mihoko Yukita, Matteo Bachetti, Javier A. Garcia, Brian Grefenstette, Kristin Madsen, Kaya Mori, Daniel Stern

Physics Faculty Publications and Presentations

We construct simulated galaxy data sets based on the High Energy X-ray Probe (HEX-P) mission concept to demonstrate the significant advances in galaxy science that will be yielded by the HEX-P observatory. The combination of high spatial resolution imaging (FWHM), broad spectral coverage (0.2–80 keV), and sensitivity superior to current facilities (e.g., XMM-Newton and NuSTAR) will enable HEX-P to detect hard (4–25 keV) X-ray emission from resolved point-source populations within ∼800 galaxies and integrated emission from ∼6,000 galaxies out to 100 Mpc. These galaxies cover wide ranges of galaxy types (e.g., normal, starburst, and passive galaxies) and properties (e.g., metallicities …

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Editorial: Solutions To Water Crises (Related To Actual Interventions), Jenia Mukherjee, Saket Pande, Melissa Haeffner, Sara Marks, Pieter Van Oel, Matthew Sanderson, Adriana Allen Nov 2023

Editorial: Solutions To Water Crises (Related To Actual Interventions), Jenia Mukherjee, Saket Pande, Melissa Haeffner, Sara Marks, Pieter Van Oel, Matthew Sanderson, Adriana Allen

Environmental Science and Management Faculty Publications and Presentations

Water science has become “pluralistic” (Evers et al., 2017) to collectively (yet differently) understand complex water systems with promising combinations of compatible and complementary disciplines. The contemporary context of water science discusses the more severe water-society challenges of the Anthropocene. Yet, the conversation is not definitive; indeed, there are unending debates between quantitative and qualitative research approaches including methodological choices and accuracies along questions of scales, themes, and politics of funding. Transdisciplinary applications and cross-sectoral engagements offer solution-oriented water just trajectories – scientists, practitioners, and user groups designing and deploying “solutions” related to actual interventions in addressing water …

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University Of Arkansas, Chemistry And Biochemistry Department Research Publications, 2014- November 2023. 107p., Jeremy Smith, Lutishoor Salisbury Nov 2023

University Of Arkansas, Chemistry And Biochemistry Department Research Publications, 2014- November 2023. 107p., Jeremy Smith, Lutishoor Salisbury

University Libraries Faculty Publications and Presentations

This report provides a compilation of the research publications by the Chemistry and Biochemistry faculty for the period: 2014 - November 2023. The information was gathered from major databases in science and technology including Web of Science, SciFinder, Reaxys, PubMed, IEEE Explore and Engineering Index. At least one author in each of the publications has the CHBC department as its affiliation. It includes a table summarizing the research. The listing is organized according to type of publications within specific years.

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Enabling Data Driven Analysis Of Vulnerabilities And Sustainability Challenges In Urban Settings, Shrideep Pallickara Oct 2023

Enabling Data Driven Analysis Of Vulnerabilities And Sustainability Challenges In Urban Settings, Shrideep Pallickara

Sustainability Seminar Series

Can data help us understand and mitigate sustainability and vulnerability challenges? Can these data can spur exploration of new questions and hypotheses, particularly across traditionally disparate disciplines, and offer unprecedented opportunities for discovery and innovation? In this talk, Dr. Pallickara will describe an NSF-funded multi-institution effort that he leads, Sustain. Crucially, analytics capabilities within Sustain are accessible via a browser, allowing researchers to formulate hypotheses and explore multiple dimensions of vulnerability and sustainability that crosscut diverse domains and spatiotemporal scopes.

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The Santa Clara, 2023-10-31, Santa Clara University Oct 2023

The Santa Clara, 2023-10-31, Santa Clara University

The Santa Clara

No abstract provided.

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Water Efficiency & Sustainability In The Mountain West, 2022, Zachary Billot, Caitlin J. Saladino, William E. Brown Jr. Oct 2023

Water Efficiency & Sustainability In The Mountain West, 2022, Zachary Billot, Caitlin J. Saladino, William E. Brown Jr.

Environment

This fact sheet analyzes the effectiveness of state-level policies related to water usage, conservation, and sustainability for the Mountain West states of Arizona, Colorado, Nevada, New Mexico, and Utah in 2022. The original data are published in the “2022 State Policy Scorecard for Water Efficiency and Sustainability” report written by the Alliance for Water Efficiency.

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A Novel Multidimensional Reference Model For Heterogeneous Textual Datasets Using Context, Semantic And Syntactic Clues, Ganesh Kumar, Shuib Basri, Abdullahi Abubakar Imam, Abdullateef Abdullateef Oluwagbemiga Balogun, Hussaini Mamman, Luiz Fernando Capretz Oct 2023

A Novel Multidimensional Reference Model For Heterogeneous Textual Datasets Using Context, Semantic And Syntactic Clues, Ganesh Kumar, Shuib Basri, Abdullahi Abubakar Imam, Abdullateef Abdullateef Oluwagbemiga Balogun, Hussaini Mamman, Luiz Fernando Capretz

Electrical and Computer Engineering Publications

With the advent of technology and use of latest devices, they produces voluminous data. Out of it, 80% of the data are unstructured and remaining 20% are structured and semi-structured. The produced data are in heterogeneous format and without following any standards. Among heterogeneous (structured, semi-structured and unstructured) data, textual data are nowadays used by industries for prediction and visualization of future challenges. Extracting useful information from it is really challenging for stakeholders due to lexical and semantic matching. Few studies have been solving this issue by using ontologies and semantic tools, but the main limitations of proposed work were …

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Phthalocyanines Prepared From 4,5-Dihexylthiophthalonitrile, A Popular Building Block, Derya Topkaya Taşkiran, Zeynel Şahi̇n, Ümi̇t İşci̇, Fabi̇enne Dumouli̇n Oct 2023

Phthalocyanines Prepared From 4,5-Dihexylthiophthalonitrile, A Popular Building Block, Derya Topkaya Taşkiran, Zeynel Şahi̇n, Ümi̇t İşci̇, Fabi̇enne Dumouli̇n

Turkish Journal of Chemistry

Phthalocyanines are tetrapyrrolic artificial porphyrinoids that play major roles in advanced biological and technological applications. Research on this family of dyes is particularly active in Türkiye, with many derivatives being prepared from 4,5-dihexyl-thiophthalonitrile DiSHexPN, which is one of the most popular noncommercially available building blocks for phthalocyanines. This review summarizes the phthalocyanines and their versatile properties and applications that have been published since 1994, when the synthesis of DiSHexPN was first described, to emphasize the importance of this building block in plentiful applications, all with bio-medical or technological impact.

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Water-Soluble Phthalocyanine Photosensitizers For Photodynamic Therapy, İpek Ömeroğlu, Mahmut Durmuş Oct 2023

Water-Soluble Phthalocyanine Photosensitizers For Photodynamic Therapy, İpek Ömeroğlu, Mahmut Durmuş

Turkish Journal of Chemistry

Photodynamic therapy (PDT) is based on a photochemical reaction that is started when a photosensitizing process is activated by the light and results in the death of tumor cells. Solubility is crucial in PDT applications to investigate the physical and chemical characteristics of phthalocyanines, but, unfortunately, most phthalocyanines show limited solubility especially in water. To increase the solubility of phthalocyanines in polar solvents and water, ionic groups such as -SO3 - , -NR3 +, -COO- , and nonionic groups such as poly-oxy chains are frequently added to the peripheral or nonperipheral positions of the phthalocyanine framework. Since water-solubility and NIR-absorbing …

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Electrochemical Dna Biosensors Developed For The Monitoring Of Biointeractions With Drugs: A Review, Kadri̇ye Arzum Erdem Gürsan, Muhammed Hüseyi̇n Şentürk, Esma Yildiz Göz, Meltem Maral, Ayla Yildirim, Ayşen Bozoğlu, Burak Kivrak, Nesli̇han Ceren Ay Oct 2023

Electrochemical Dna Biosensors Developed For The Monitoring Of Biointeractions With Drugs: A Review, Kadri̇ye Arzum Erdem Gürsan, Muhammed Hüseyi̇n Şentürk, Esma Yildiz Göz, Meltem Maral, Ayla Yildirim, Ayşen Bozoğlu, Burak Kivrak, Nesli̇han Ceren Ay

Turkish Journal of Chemistry

The interaction of drugs with DNA is important for the discovery of novel drug molecules and for understanding the therapeutic effects of drugs as well as the monitoring of side effects. For this reason, many studies have been carried out to investigate the interactions of drugs with nucleic acids. In recent years, a large number of studies have been performed to electrochemically detect drug-DNA interactions. The fast, sensitive, and accurate results of electrochemical techniques have resulted in a leading role for their implementation in this field. By means of electrochemical techniques, it is possible not only to demonstrate drug-DNA interactions …

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Heterocyclic Molecules With Esipt Emission: Synthetic Approaches, Molecular Diversities, And Application Strategies, Nuretti̇n Mengeş Oct 2023

Heterocyclic Molecules With Esipt Emission: Synthetic Approaches, Molecular Diversities, And Application Strategies, Nuretti̇n Mengeş

Turkish Journal of Chemistry

Excited-state intramolecular proton transfer (ESIPT) is one of the most essential emission processes in most circumstances because of its dual emission band in most cases and its high Stokes shifts. These distinguishing properties make ESIPT-based probes more suitable for a variety of applications, including analyte sensors, solid-state sensing mechanisms, optical technologies, and biomarkers for endogenous or exogenous compounds in various settings. As a result, researchers around the world are working on ESIPT emissions and developing different scaffolds for various applications or industry demands. This field of study is rapidly expanding and there is a need for an up-to-date review of …

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Cryogelation Reactions And Cryogels: Principles And Challenges, Oğuz Okay Oct 2023

Cryogelation Reactions And Cryogels: Principles And Challenges, Oğuz Okay

Turkish Journal of Chemistry

Cryogelation is a powerful technique for producing macroporous hydrogels called cryogels. Although cryogelation reactions and cryogels were discovered more than 70 years ago, they attracted significant interest only in the last 20 years mainly due to their extraordinary properties compared to the classical hydrogels such as a high toughness, almost complete squeezability, a mechanically stable porous structure with honeycomb arrangement, poroelasticity, and fast responsivity against external stimuli. In this mini review, general properties of cryogelation systems including the cryoconcentration phenomenon responsible for the unique properties of the cryogels are discussed. The squeezability and poroelasticity of cryogels comparable to those seen …

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