Open Access. Powered by Scholars. Published by Universities.®

Digital Commons Network™

Open Access. Powered by Scholars. Published by Universities.®

Discipline
Institution
Keyword
Publication Year
Publication
Publication Type
File Type

Articles 112561 - 112590 of 1113951

Full-Text Articles in Entire DC Network

Vision Paper: Advancing Of Ai Explainability For The Use Of Chatgpt In Government Agencies: Proposal Of A 4-Step Framework, Hui Shan Lee, Shankararaman, Venky, Eng Lieh Ouh Dec 2023

Vision Paper: Advancing Of Ai Explainability For The Use Of Chatgpt In Government Agencies: Proposal Of A 4-Step Framework, Hui Shan Lee, Shankararaman, Venky, Eng Lieh Ouh

Research Collection School Of Computing and Information Systems

This paper explores ChatGPT’s potential in aiding government agencies, drawing from a case study based on a government agency in Singapore. While ChatGPT’s text generation abilities offer promise, it brings inherent challenges, including data opacity, potential misinformation, and occasional errors. These issues are especially critical in government decision-making.Public administration’s core values of transparency and accountability magnify these concerns. Ensuring AI alignment with these principles is imperative, given the potential repercussions on policy outcomes and citizen trust.AI explainability plays a central role in ChatGPT’s adoption within government agencies. To address these concerns, we propose strategies like prompt engineering, data governance, and …

Go to article

Do Contributing Files Provide Information About Oss Newcomers' Onboarding Barriers?, Felipe Fronchetti, David Shepherd, Igor Wiese, Christoph Treude, Marco Gerosa, Igor Steinmacher Dec 2023

Do Contributing Files Provide Information About Oss Newcomers' Onboarding Barriers?, Felipe Fronchetti, David Shepherd, Igor Wiese, Christoph Treude, Marco Gerosa, Igor Steinmacher

Research Collection School Of Computing and Information Systems

Effectively onboarding newcomers is essential for the success of open source projects. These projects often provide onboarding guidelines in their ‘CONTRIBUTING’ files (e.g., CONTRIBUTING.md on GitHub). These files explain, for example, how to find open tasks, implement solutions, and submit code for review. However, these files often do not follow a standard structure, can be too large, and miss barriers commonly found by newcomers. In this paper, we propose an automated approach to parse these CONTRIBUTING files and assess how they address onboarding barriers. We manually classified a sample of files according to a model of onboarding barriers from the …

Go to article

Evaluating Transfer Learning For Simplifying Github Readmes, Haoyu Gao, Christoph Treude, Mansooreh Zahedi Dec 2023

Evaluating Transfer Learning For Simplifying Github Readmes, Haoyu Gao, Christoph Treude, Mansooreh Zahedi

Research Collection School Of Computing and Information Systems

Software documentation captures detailed knowledge about a software product, e.g., code, technologies, and design. It plays an important role in the coordination of development teams and in conveying ideas to various stakeholders. However, software documentation can be hard to comprehend if it is written with jargon and complicated sentence structure. In this study, we explored the potential of text simplification techniques in the domain of software engineering to automatically simplify GitHub README files. We collected software-related pairs of GitHub README files consisting of 14,588 entries, aligned difficult sentences with their simplified counterparts, and trained a Transformer-based model to automatically simplify …

Go to article

Lessons From The Long Tail: Analysing Unsafe Dependency Updates Across Software Ecosystems, Supatsara Wattanakriengkrai, Raula Kula, Christoph Treude, Kenichi Matsumoto Dec 2023

Lessons From The Long Tail: Analysing Unsafe Dependency Updates Across Software Ecosystems, Supatsara Wattanakriengkrai, Raula Kula, Christoph Treude, Kenichi Matsumoto

Research Collection School Of Computing and Information Systems

A risk in adopting third-party dependencies into an application is their potential to serve as a doorway for malicious code to be injected (most often unknowingly). While many initiatives from both industry and research communities focus on the most critical dependencies (i.e., those most depended upon within the ecosystem), little is known about whether the rest of the ecosystem suffers the same fate. Our vision is to promote and establish safer practises throughout the ecosystem. To motivate our vision, in this paper, we present preliminary data based on three representative samples from a population of 88,416 pull requests (PRs) and …

Go to article

Offline Rl With Discrete Proxy Representations For Generalizability In Pomdps, Pengjie Gu, Xinyu Cai, Dong Xing, Xinrun Wang, Mengchen Zhao, Bo An Dec 2023

Offline Rl With Discrete Proxy Representations For Generalizability In Pomdps, Pengjie Gu, Xinyu Cai, Dong Xing, Xinrun Wang, Mengchen Zhao, Bo An

Research Collection School Of Computing and Information Systems

Offline Reinforcement Learning (RL) has demonstrated promising results in various applications by learning policies from previously collected datasets, reducing the need for online exploration and interactions. However, real-world scenarios usually involve partial observability, which brings crucial challenges of the deployment of offline RL methods: i) the policy trained on data with full observability is not robust against the masked observations during execution, and ii) the information of which parts of observations are masked is usually unknown during training. In order to address these challenges, we present Offline RL with DiscrEte pRoxy representations (ORDER), a probabilistic framework which leverages novel state …

Go to article

Kape: Knn-Based Performance Testing For Deep Code Search, Yuejun Guo, Qiang Hu, Xiaofei Xie, Cordy Maxime, Mike Papadakis, Yves Le Traon Dec 2023

Kape: Knn-Based Performance Testing For Deep Code Search, Yuejun Guo, Qiang Hu, Xiaofei Xie, Cordy Maxime, Mike Papadakis, Yves Le Traon

Research Collection School Of Computing and Information Systems

Code search is a common yet important activity of software developers. An efficient code search model can largely facilitate the development process and improve the programming quality. Given the superb performance of learning the contextual representations, deep learning models, especially pre-trained language models, have been widely explored for the code search task. However, studies mainly focus on proposing new architectures for ever-better performance on designed test sets but ignore the performance on unseen test data where only natural language queries are available. The same problem in other domains, e.g., CV and NLP, is usually solved by test input selection that …

Go to article

Prompting And Evaluating Large Language Models For Proactive Dialogues: Clarification, Target-Guided, And Non-Collaboration, Yang Deng, Lizi Liao, Liang Chen, Hongru Wang, Wenqiang Lei, Tat-Seng Chua Dec 2023

Prompting And Evaluating Large Language Models For Proactive Dialogues: Clarification, Target-Guided, And Non-Collaboration, Yang Deng, Lizi Liao, Liang Chen, Hongru Wang, Wenqiang Lei, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Conversational systems based on Large Language Models (LLMs), such as ChatGPT, show exceptional proficiency in context understanding and response generation. However, they still possess limitations, such as failing to ask clarifying questions to ambiguous queries or refuse users' unreasonable requests, both of which are considered as key aspects of a conversational agent's proactivity. This raises the question of whether LLM-based conversational systems are equipped to handle proactive dialogue problems. In this work, we conduct a comprehensive analysis of LLM-based conversational systems, specifically focusing on three key aspects of proactive dialogues: clarification, target-guided, and non-collaborative dialogues. To trigger the proactivity of …

Go to article

Attack Prompt Generation For Red Teaming And Defending Large Language Models, Boyi Deng, Wenjie Wang, Fuli Feng, Yang Deng, Qifan Wang, Xiangnan He Dec 2023

Attack Prompt Generation For Red Teaming And Defending Large Language Models, Boyi Deng, Wenjie Wang, Fuli Feng, Yang Deng, Qifan Wang, Xiangnan He

Research Collection School Of Computing and Information Systems

Large language models (LLMs) are susceptible to red teaming attacks, which can induce LLMs to generate harmful content. Previous research constructs attack prompts via manual or automatic methods, which have their own limitations on construction cost and quality. To address these issues, we propose an integrated approach that combines manual and automatic methods to economically generate high-quality attack prompts. Specifically, considering the impressive capabilities of newly emerged LLMs, we propose an attack framework to instruct LLMs to mimic human-generated prompts through in-context learning. Furthermore, we propose a defense framework that fine-tunes victim LLMs through iterative interactions with the attack framework …

Go to article

Depwignn: A Depth-Wise Graph Neural Network For Multi-Hop Spatial Reasoning In Text, Shuaiyi Li, Yang Deng, Wai Lam Dec 2023

Depwignn: A Depth-Wise Graph Neural Network For Multi-Hop Spatial Reasoning In Text, Shuaiyi Li, Yang Deng, Wai Lam

Research Collection School Of Computing and Information Systems

Spatial reasoning in text plays a crucial role in various real-world applications. Existing approaches for spatial reasoning typically infer spatial relations from pure text, which overlook the gap between natural language and symbolic structures. Graph neural networks (GNNs) have showcased exceptional proficiency in inducing and aggregating symbolic structures. However, classical GNNs face challenges in handling multi-hop spatial reasoning due to the over-smoothing issue, i.e., the performance decreases substantially as the number of graph layers increases. To cope with these challenges, we propose a novel Depth-Wise Graph Neural Network (DepWiGNN). Specifically, we design a novel node memory scheme and aggregate the …

Go to article

Unifying Text, Tables, And Images For Multimodal Question Answering, Haohao Luo, Ying Shen, Yang Deng Dec 2023

Unifying Text, Tables, And Images For Multimodal Question Answering, Haohao Luo, Ying Shen, Yang Deng

Research Collection School Of Computing and Information Systems

Multimodal question answering (MMQA), which aims to derive the answer from multiple knowledge modalities (e.g., text, tables, and images), has received increasing attention due to its board applications. Current approaches to MMQA often rely on single-modal or bi-modal QA models, which limits their ability to effectively integrate information across all modalities and leverage the power of pre-trained language models. To address these limitations, we propose a novel framework called UniMMQA, which unifies three different input modalities into a text-to-text format by employing position-enhanced table linearization and diversified image captioning techniques. Additionally, we enhance cross-modal reasoning by incorporating a multimodal rationale …

Go to article

Large Language Models As Source Planner For Personalized Knowledge-Grounded Dialogues, Hongru Wang, Minda Hu, Yang Deng, Rui Wang, Fei Mi, Weichao Wang, Yasheng Wang, Wai-Chung Kwan, Irwin King, Kam-Fai Wong Dec 2023

Large Language Models As Source Planner For Personalized Knowledge-Grounded Dialogues, Hongru Wang, Minda Hu, Yang Deng, Rui Wang, Fei Mi, Weichao Wang, Yasheng Wang, Wai-Chung Kwan, Irwin King, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

Open-domain dialogue system usually requires different sources of knowledge to generate more informative and evidential responses. However, existing knowledge-grounded dialogue systems either focus on a single knowledge source or overlook the dependency between multiple sources of knowledge, which may result in generating inconsistent or even paradoxical responses. To incorporate multiple knowledge sources and dependencies between them, we propose SAFARI, a novel framework that leverages the exceptional capabilities of large language models (LLMs) in planning, understanding, and incorporating under both supervised and unsupervised settings. Specifically, SAFARI decouples the knowledge grounding into multiple sources and response generation, which allows easy extension to …

Go to article

Controlling Type Confounding In Ad Hoc Teamwork With Instance-Wise Teammate Feedback Rectification, Dong Xing, Pengjie Gu, Qian Zheng, Xinrun Wang, Shanqi Liu, Longtao Zheng, Bo An, Gang Pan Dec 2023

Controlling Type Confounding In Ad Hoc Teamwork With Instance-Wise Teammate Feedback Rectification, Dong Xing, Pengjie Gu, Qian Zheng, Xinrun Wang, Shanqi Liu, Longtao Zheng, Bo An, Gang Pan

Research Collection School Of Computing and Information Systems

Ad hoc teamwork requires an agent to cooperate with unknown teammates without prior coordination. Many works propose to abstract teammate instances into high-level representation of types and then pre-train the best response for each type. However, most of them do not consider the distribution of teammate instances within a type. This could expose the agent to the hidden risk of type confounding. In the worst case, the best response for an abstract teammate type could be the worst response for all specific instances of that type. This work addresses the issue from the lens of causal inference. We first theoretically …

Go to article

Ethical Considerations For Artificial Intelligence In Educational Assessments, Lim Ming Soon Tristan, Gottipati Swapna, Michelle L. F. Cheong Dec 2023

Ethical Considerations For Artificial Intelligence In Educational Assessments, Lim Ming Soon Tristan, Gottipati Swapna, Michelle L. F. Cheong

Research Collection School Of Computing and Information Systems

In the vital context of education, the application of artificial intelligence (AI) to assessments necessitates a nuanced examination of the boundaries between ethically permissible and impermissible practices. In this chapter, the authors applied a systematic literature mapping methodology to scour extant research, so as to holistically structure the landscape into explicit topical research clusters. Through topic modelling and network analyses, research mapped key ethical principles to different assessment phases in a triadic ontological framework. The chapter looks to provide researchers and practitioners the insights into the ethical challenges that exist across an end-to-end assessment pipeline.

Go to article

Deeparc: Modularizing Neural Networks For The Model Maintenance, Xiaoning Ren, Yun Lin, Yinxing Xue, Ruofan Liu, Jun Sun, Zhiyong Feng, Jinsong Dong Dec 2023

Deeparc: Modularizing Neural Networks For The Model Maintenance, Xiaoning Ren, Yun Lin, Yinxing Xue, Ruofan Liu, Jun Sun, Zhiyong Feng, Jinsong Dong

Research Collection School Of Computing and Information Systems

Neural networks are an emerging data-driven programming paradigm widely used in many areas. Unlike traditional software systems consisting of decomposable modules, a neural network is usually delivered as a monolithic package, raising challenges for some maintenance tasks such as model restructure and re-adaption. In this work, we propose DeepArc, a novel modularization method for neural networks, to reduce the cost of model maintenance tasks. Specifically, DeepArc decomposes a neural network into several consecutive modules, each of which encapsulates consecutive layers with similar semantics. The network modularization facilitates practical tasks such as refactoring the model to preserve existing features (e.g., model …

Go to article

Software Composition Analysis For Vulnerability Detection: An Empirical Study On Java Projects, Lida Zhao, Sen Chen, Zhengzi Xu, Lyuye Zhang, Jiahui Wu, Jun Sun, Yang Liu Dec 2023

Software Composition Analysis For Vulnerability Detection: An Empirical Study On Java Projects, Lida Zhao, Sen Chen, Zhengzi Xu, Lyuye Zhang, Jiahui Wu, Jun Sun, Yang Liu

Research Collection School Of Computing and Information Systems

Software composition analysis (SCA) tools are proposed to detect potential vulnerabilities introduced by open-source software (OSS) imported as third-party libraries (TPL). With the increasing complexity of software functionality, SCA tools may encounter various scenarios during the dependency resolution process, such as diverse formats of artifacts, diverse dependency imports, and diverse dependency specifications. However, there still lacks a comprehensive evaluation of SCA tools for Java that takes into account the above scenarios. This could lead to a confined interpretation of comparisons, improper use of tools, and hinder further improvements of the tools. To fill this gap, we proposed an Evaluation Model …

Go to article

An "Off-The-Shelf" Cd2 Universal Car-T Therapy For T-Cell Malignancies, Jingyu Xiang, Jessica M Devenport, Alun J Carter, Karl W Staser, Miriam Y Kim, Julie O' Neal, Julie K Ritchey, Michael P Rettig, Feng Gao, Garrett Rettig, Rolf Turk, Byung Ha Lee, Matthew L Cooper, John F Dipersio Dec 2023

An "Off-The-Shelf" Cd2 Universal Car-T Therapy For T-Cell Malignancies, Jingyu Xiang, Jessica M Devenport, Alun J Carter, Karl W Staser, Miriam Y Kim, Julie O' Neal, Julie K Ritchey, Michael P Rettig, Feng Gao, Garrett Rettig, Rolf Turk, Byung Ha Lee, Matthew L Cooper, John F Dipersio

2020-Current year OA Pubs

T-cell malignancies are associated with frequent relapse and high morbidity, which is partly due to the lack of effective or targeted treatment options. To broaden the use of CAR-T cells in pan T-cell malignancies, we developed an allogeneic "universal" CD2-targeting CAR-T cell (UCART2), in which the CD2 antigen is deleted to prevent fratricide, and the T-cell receptor is removed to prevent GvHD. UCART2 demonstrated efficacy against T-ALL and CTCL and prolonged the survival of tumor-engrafted NSG mice in vivo. To evaluate the impact of CD2 on CAR-T function, we generated CD19 CAR-T cells (UCART19) with or without CD2 deletion, single-cell …

Go to article

Single-Cell Analysis Of Chromatin Accessibility In The Adult Mouse Brain, Songpeng Zu, Yang Eric Li, Et Al. Dec 2023

Single-Cell Analysis Of Chromatin Accessibility In The Adult Mouse Brain, Songpeng Zu, Yang Eric Li, Et Al.

2020-Current year OA Pubs

Recent advances in single-cell technologies have led to the discovery of thousands of brain cell types; however, our understanding of the gene regulatory programs in these cell types is far from complete

Go to article

The Impact Of Aces On College Students And Their Major Choice, Britten Harrison Dec 2023

The Impact Of Aces On College Students And Their Major Choice, Britten Harrison

Electronic Theses and Dissertations

Research examining Adverse Childhood Experiences (ACEs) has mostly focused on the long-term effects of these experiences on adult mental and physical health. Less attention has been focused on the impact of ACEs on college student satisfaction, dropout rates, and major choice. The overarching questions for the current study sought to further research by (1) assessing if there is a relationship between the ACE scores of college students and their mental and physical health, (2) if ACEs play a role in student satisfaction or desire to drop out, and (3) determining if there is a connection between students with high ACE …

Go to article

The Relationship Between Job Challenge And Leadership Aspiration From The Perspective Of The Entry Level Nurse Leader, Rose M. Johnson Dec 2023

The Relationship Between Job Challenge And Leadership Aspiration From The Perspective Of The Entry Level Nurse Leader, Rose M. Johnson

Electronic Theses and Dissertations

While the nurse leader plays an important and integral role in the success of healthcare organizations, the nurse leader pipeline has experienced a troubling and downward trajectory for several years. The lack of leadership aspiration among direct care nurses has been noted as one of several reasons for the downward trajectory. In addition, researchers identified the lack of understanding of perspectives of the various nurse leader roles and the lack of understanding of the effectiveness of experiential learning in the nurse leader role as potential contributions to the problem. The purpose of this quantitative, correlational research was to examine the …

Go to article

Substantial Blue Carbon Sequestration In The World’S Largest Seagrass Meadow, Chuancheng Fu, Sofia Frappi, Michelle N. Havlik, Wells Howe, S. David Harris, Elisa Laiolo, Austin J. Gallagher, Pere Masqué, Carlos M. Duarte Dec 2023

Substantial Blue Carbon Sequestration In The World’S Largest Seagrass Meadow, Chuancheng Fu, Sofia Frappi, Michelle N. Havlik, Wells Howe, S. David Harris, Elisa Laiolo, Austin J. Gallagher, Pere Masqué, Carlos M. Duarte

Research outputs 2022 to 2026

Seagrass meadows are important sinks for organic carbon and provide co-benefits. However, data on the organic carbon stock in seagrass sediments are scarce for many regions, particularly The Bahamas, which accounts for up to 40.7% of the documented global seagrass area, limiting formulation of blue carbon strategies. Here, we sampled 10 seagrass meadows across an extensive island chain in The Bahamas. We estimate that Bahamas seagrass meadows store 0.42–0.59 Pg organic carbon in the top-meter sediments with an accumulation rate of 2.1–2.9 Tg annually, representing a substantial global blue carbon hotspot. Autochthonous organic carbon in sediments decreased from ~1980 onwards, …

Go to article

Time Reduction For Slm Ofdm Papr Based On Adaptive Genetic Algorithm In 5g Iot Networks, Esam A. A. Hagras, Sameh F. Desouky, Saad Aldosary, Haitham Khaled, Tarek M. Hassan Dec 2023

Time Reduction For Slm Ofdm Papr Based On Adaptive Genetic Algorithm In 5g Iot Networks, Esam A. A. Hagras, Sameh F. Desouky, Saad Aldosary, Haitham Khaled, Tarek M. Hassan

Research outputs 2022 to 2026

In this paper, a new peak average power and time reduction (PAPTR) based on the adaptive genetic algorithm (AGA) strategy is used in order to improve both the time reduction and PAPR value reduction for the SLM OFDM and the conventional genetic algorithm (GA) SLM-OFDM. The simulation results demonstrate that the recommended AGA technique reduces PAPR by about 3.87 dB in comparison to SLM-OFDM. Comparing the suggested AGA SLM-OFDM to the traditional GA SLM-OFDM using the same settings, a significant learning time reduction of roughly 95.56% is achieved. The PAPR of the proposed AGA SLM-OFDM is enhanced by around 3.87 …

Go to article

Wastewater Treatment Plants: The Missing Link In Global One-Health Surveillance And Management Of Antibiotic Resistance, Abdolmajid Gholizadeh, Mehdi Khiadani, Maryam Foroughi, Hadi Alizade Siuki, Hadi Mehrfar Dec 2023

Wastewater Treatment Plants: The Missing Link In Global One-Health Surveillance And Management Of Antibiotic Resistance, Abdolmajid Gholizadeh, Mehdi Khiadani, Maryam Foroughi, Hadi Alizade Siuki, Hadi Mehrfar

Research outputs 2022 to 2026

Introduction: As a global public health crisis, antibiotic resistance (AR) should be monitored and managed under the One-Health concept according to the World Health Organization (WHO), considering the interconnection between humans, animals, and the environment. But this approach often remains focused on human health and rarely on the environment and its compartments, especially wastewater as the main AR receptor. Wastewater treatment plants (WWTPs) not only are not designed for reliving AR but also provide appropriate conditions for enhancing AR through different mechanisms. Methods: By reviewing the research-based statistics on the inclusion of WWTPs in the One-Health/AR program crisis, this paper …

Go to article

Duties For Datasets, Jerrold Tsin Howe Soh Dec 2023

Duties For Datasets, Jerrold Tsin Howe Soh

Research Collection Yong Pung How School Of Law

Machine learning (ML) systems are increasingly being deployed in contexts, such as law, medicine and finance, where system errors present serious and foreseeable risks. As ML system behaviour is largely determined by their training inputs, should dataset providers owe duties of care to victims? Using the ImageNet dataset and the Generative Pre-trained Transformer (GPT) models as case studies, this chapter argues that the conventional approach of centralising duties on system providers alone yields insufficient safeguards. Dataset-specific duties should also be considered to incentivise precaution in the preparation of crucial ML input. The chapter analyses how dataset duties may be encompassed …

Go to article

Through The Lens Of A Naturalist: How Learning About Nature Promotes Nature Connectedness Via Awe, Shu Tian Ng, Angela K. Y. Leung, Sarah Hian May Chan Dec 2023

Through The Lens Of A Naturalist: How Learning About Nature Promotes Nature Connectedness Via Awe, Shu Tian Ng, Angela K. Y. Leung, Sarah Hian May Chan

Research Collection School of Social Sciences

Environmental educators stress the importance of engaging with the wonders of the Earth in promoting nature connectedness. However, it remains unclear if learning about nature has an incremental effect beyond mere exposure to nature and what psychological mechanism can explain such a learning effect if it exists. To fill this gap, we propose a mediation model in which learning about nature promotes a sense of awe—a self-transcendent emotion associated with the recognition of vastness in nature. A sense of awe, in turn, promotes nature connectedness. Study 1 employed a cross-sectional survey and offered preliminary support for the proposed model, with …

Go to article

The Economics Of Financial Scams: Evidence From Initial Coin Offerings, Kenny Phua, Bo Sang, Chi Shen Wei, Gloria Yang Yu Dec 2023

The Economics Of Financial Scams: Evidence From Initial Coin Offerings, Kenny Phua, Bo Sang, Chi Shen Wei, Gloria Yang Yu

Research Collection Lee Kong Chian School Of Business

We examine the economics of financial scams by analyzing the market for initial coin offerings (ICOs). Using data snapshots of 5,873 ICOs, we find that irregularities in ICO characteristics across listing websites predict higher scam risk and are likely intentional. These patterns are consistent with a model where malicious issuers maximize profits by using irregularities to screen for naïve investors. Almost half of the ICOs in our sample may be scams, amounting to more than U.S. $6 billion in losses. Our results draw attention to the frequent use of screening mechanisms in financial scams.

Go to article

Small Scale Desalination Technologies: A Comprehensive Review, Hamed Kariman, Abdellah Shafieian, Mehdi Khiadani Dec 2023

Small Scale Desalination Technologies: A Comprehensive Review, Hamed Kariman, Abdellah Shafieian, Mehdi Khiadani

Research outputs 2022 to 2026

In recent decades, problems related to fresh water has become a very important issue for humans. Small-scale desalination (SSD) systems, besides large-scale desalination (LSD) systems, fulfil an important role in meeting freshwater demand by eliminating the cost of transmission and have the advantage of treating water on-site. In this study, for the first time, a comprehensive review of previous studies has been carried out on SSD systems (less than 25 m3/d water production). These systems are powered using renewable, non-renewable or hybrid sources of energy, incorporating different treatment technologies such as: reverse osmosis (RO); electro dialysis (ED); capacitive deionization (CDI); …

Go to article

Thermo-Hydraulic Performance Evaluation Of A Naca 63-015 Heat Exchanger With Shark Denticles As Surface Textures, Aakash S. Hurry, Kevin Hayward, Ferdinando Guzzomi, Kanishk Rauthan, Ana Vafadar Dec 2023

Thermo-Hydraulic Performance Evaluation Of A Naca 63-015 Heat Exchanger With Shark Denticles As Surface Textures, Aakash S. Hurry, Kevin Hayward, Ferdinando Guzzomi, Kanishk Rauthan, Ana Vafadar

Research outputs 2022 to 2026

In this study, the effect of using bio-inspired surface texturing as a technique to further enhance the efficiency of a single Plate Fin Heat Exchanger (PFHX) was investigated experimentally. By using biomimicry across disciplines, the denticle, which is a body adaptation from shark skin for enhanced hydrodynamics, was identified as a surface texture to be used on the fin of a PFHX. A smooth NACA 63-015 PFHX (HX0) was used as baseline for thermo-hydraulic performance comparisons. Initially, three PFHXs (HX1, HX2 and HX3), consisting of arrays of denticles upscaled to different scale factors, were designed and printed in ABS plastic …

Go to article

Metal Organic Frameworks With Carbon Black For The Enhanced Electrochemical Detection Of 2,4,6-Trinitrotoluene, Shaghraf Javaid, Muhammad R. Azhar, Xinyu Li, Juliette I. Phillips, Tanveer Hussain, Hussein Abid, Jun Chen, Xiaobo Ji, Debbie S. Silvester Dec 2023

Metal Organic Frameworks With Carbon Black For The Enhanced Electrochemical Detection Of 2,4,6-Trinitrotoluene, Shaghraf Javaid, Muhammad R. Azhar, Xinyu Li, Juliette I. Phillips, Tanveer Hussain, Hussein Abid, Jun Chen, Xiaobo Ji, Debbie S. Silvester

Research outputs 2022 to 2026

The sensing of explosives such as 2,4,6-trinitrotoluene (TNT) directly at an explosion site requires a fast, simple and sensitive detection method, to which electrochemical techniques are well suited. Herein, we report an electrochemical sensor material for TNT based on an ammonium hydroxide (NH4OH) sensitized zinc-1,4–benzenedicarboxylate Zn(BDC) metal organic framework (MOF) mixed with carbon black on a glassy carbon electrode. In the solvent modulation mechanism, by merely changing the concentration of NH4OH during synthesis, two Zn(BDC) MOFs with novel morphologies were fabricated via a hydrothermal approach. The as-prepared MOFs were characterized using X-ray powder diffraction (XRD), scanning electron microscopy (SEM), Fourier …

Go to article

Fatigue Behaviour Of Load-Bearing Polymeric Bone Scaffolds: A Review, Hamed Bakhtiari, Alireza Nouri, Mehrdad Khakbiz, Majid Tolouei-Rad Dec 2023

Fatigue Behaviour Of Load-Bearing Polymeric Bone Scaffolds: A Review, Hamed Bakhtiari, Alireza Nouri, Mehrdad Khakbiz, Majid Tolouei-Rad

Research outputs 2022 to 2026

Bone scaffolds play a crucial role in bone tissue engineering by providing mechanical support for the growth of new tissue while enduring static and fatigue loads. Although polymers possess favourable characteristics such as adjustable degradation rate, tissue-compatible stiffness, ease of fabrication, and low toxicity, their relatively low mechanical strength has limited their use in load-bearing applications. While numerous studies have focused on assessing the static strength of polymeric scaffolds, little research has been conducted on their fatigue properties. The current review presents a comprehensive study on the fatigue behaviour of polymeric bone scaffolds. The fatigue failure in polymeric scaffolds is …

Go to article

Global Dataset Of Soil Organic Carbon In Tidal Marshes, Tania L. Maxwell, André S. Rovai, Maria F. Adame, Janine B. Adams, José Álvarez-Rogel, William E. N. Austin, Kim Beasy, Francesco Boscutti, Michael E. Böttcher, Tjeerd J. Bouma, Richard H. Bulmer, Annette Burden, Shannon A. Burke, Saritta Camacho, Doongar R. Chaudhary, Gail L. Chmura, Margareth Copertino, Grace M. Cott, Christopher Craft, John Day, Carmen B. De Los Santos, Lionel Denis, Weixin Ding, Joanna C. Ellison, Carolyn J. E. Lewis, Luise Giani, Maria Gispert, Swanne Gontharet, José A. González-Pérez, M. Nazaret González-Alcaraz, Connor Gorham, Anna E. L. Graversen, Anthony Grey, Roberta Guerra, Qiang He, James R. Holmquist, Alice R. Jones, José A. Juanes, Brian P. Kelleher, Karen E. Kohfeld, Dorte Krause-Jensen, Anna Lafratta, Paul S. Lavery, Edward A. Laws, Carmen Leiva-Dueñas, Pei S. Loh, Catherine E. Lovelock, Carolyn J. Lundquist, Peter I. Macreadie, Inés Mazarrasa, J. Patrick Megonigal, Joao M. Neto, Juliana Nogueira, Michael J. Osland, Jordi F. Pagès, Nipuni Perera, Eva-Maria Pfeiffer, Thomas Pollmann, Jacqueline L. Raw, María Recio, Ana C. Ruiz-Fernández, Sophie K. Russell, John M. Rybczyk, Marek Sammul, Christian Sanders, Rui Santos, Oscar Serrano, Matthias Siewert, Craig Smeaton, Zhaoliang Song, Carmen Trasar-Cepeda, Robert R. Twilley, Marijn Van De Broek, Stefano Vitti, Livia V. Antisari, Baptiste Voltz, Christy N. Wails, Raymond D. Ward, Melissa Ward, Jaxine Wolfe, Renmin Yang, Sebastian Zubrzycki, Emily Landis, Lindsey Smart, Mark Spalding, Thomas A. Worthington Dec 2023

Global Dataset Of Soil Organic Carbon In Tidal Marshes, Tania L. Maxwell, André S. Rovai, Maria F. Adame, Janine B. Adams, José Álvarez-Rogel, William E. N. Austin, Kim Beasy, Francesco Boscutti, Michael E. Böttcher, Tjeerd J. Bouma, Richard H. Bulmer, Annette Burden, Shannon A. Burke, Saritta Camacho, Doongar R. Chaudhary, Gail L. Chmura, Margareth Copertino, Grace M. Cott, Christopher Craft, John Day, Carmen B. De Los Santos, Lionel Denis, Weixin Ding, Joanna C. Ellison, Carolyn J. E. Lewis, Luise Giani, Maria Gispert, Swanne Gontharet, José A. González-Pérez, M. Nazaret González-Alcaraz, Connor Gorham, Anna E. L. Graversen, Anthony Grey, Roberta Guerra, Qiang He, James R. Holmquist, Alice R. Jones, José A. Juanes, Brian P. Kelleher, Karen E. Kohfeld, Dorte Krause-Jensen, Anna Lafratta, Paul S. Lavery, Edward A. Laws, Carmen Leiva-Dueñas, Pei S. Loh, Catherine E. Lovelock, Carolyn J. Lundquist, Peter I. Macreadie, Inés Mazarrasa, J. Patrick Megonigal, Joao M. Neto, Juliana Nogueira, Michael J. Osland, Jordi F. Pagès, Nipuni Perera, Eva-Maria Pfeiffer, Thomas Pollmann, Jacqueline L. Raw, María Recio, Ana C. Ruiz-Fernández, Sophie K. Russell, John M. Rybczyk, Marek Sammul, Christian Sanders, Rui Santos, Oscar Serrano, Matthias Siewert, Craig Smeaton, Zhaoliang Song, Carmen Trasar-Cepeda, Robert R. Twilley, Marijn Van De Broek, Stefano Vitti, Livia V. Antisari, Baptiste Voltz, Christy N. Wails, Raymond D. Ward, Melissa Ward, Jaxine Wolfe, Renmin Yang, Sebastian Zubrzycki, Emily Landis, Lindsey Smart, Mark Spalding, Thomas A. Worthington

Research outputs 2022 to 2026

Tidal marshes store large amounts of organic carbon in their soils. Field data quantifying soil organic carbon (SOC) stocks provide an important resource for researchers, natural resource managers, and policy-makers working towards the protection, restoration, and valuation of these ecosystems. We collated a global dataset of tidal marsh soil organic carbon (MarSOC) from 99 studies that includes location, soil depth, site name, dry bulk density, SOC, and/or soil organic matter (SOM). The MarSOC dataset includes 17,454 data points from 2,329 unique locations, and 29 countries. We generated a general transfer function for the conversion of SOM to SOC. Using this …

Go to article

First Prev Next Last