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Full-Text Articles in Engineering

Hitch Cart “Landing Gear”, Rebekah White, Jose Raygoza, Randy Hernandez, Brandon Leon Dec 2024

Hitch Cart “Landing Gear”, Rebekah White, Jose Raygoza, Randy Hernandez, Brandon Leon

Mechanical Engineering

This report aims to allow our sponsor, to review our design process of the Hitch Cart Landing Gear Prototype. In the design overview section of this report, we discuss the primary design modifications we made to the wheel mechanism of the existing hitch cart prototype, including the addition of the ACME screws and the folding brackets. This allows our sponsor to see the intended improvements made to the past prototype and understand the primary goal of our project. Then, in the implementation section, we cover the entire manufacturing process to allow our sponsor to understand what manufacturing steps must be …


Supporting Text And Data Analysis Across Campus From The Academic Library, Amy Kirchhoff, Hejin Shin Phd Apr 2024

Supporting Text And Data Analysis Across Campus From The Academic Library, Amy Kirchhoff, Hejin Shin Phd

Digital Initiatives Symposium

The ability to comprehend and communicate with text-based data is essential to future success in academics and employment, as evidenced in a recent survey from Bloomberg Research Services which shows that nearly 97% of survey respondents now use data analytics in their companies and 58% consider data and text mining a business analytics tool (https://www.sas.com/content/dam/SAS/bp_de/doc/studie/ba-st-the-current-state-of-business-analytics-2317022.pdf). This has fueled a substantial growth in text analysis research (involving the use of technology to analyze un- and semi-structured text data for valuable insights, trends, and patterns) across disciplines and a corresponding demand on academic libraries to support text analysis pedagogy and text analysis …


Microplastics Fouling Mitigation In Forward Osmosis Membranes By The Molecular Assembly Of Sulfobetaine Zwitterion, Javad Farahbakhsh, Mitra Golgoli, Mehdi Khiadani, Amir Razmjou, Masoumeh Zargar Apr 2024

Microplastics Fouling Mitigation In Forward Osmosis Membranes By The Molecular Assembly Of Sulfobetaine Zwitterion, Javad Farahbakhsh, Mitra Golgoli, Mehdi Khiadani, Amir Razmjou, Masoumeh Zargar

Research outputs 2022 to 2026

Forward osmosis (FO) membranes have potential for the efficient water and wastewater treatment applications. However, their development has faced significant challenges due to their fouling propensity. In this study, FO membranes modified with sulfobetaine zwitterions (i.e., [2-(Methacryloyloxy)ethyl]dimethyl-(3-sulfopropyl) ammonium hydroxide) were fabricated and used for the first time to address microplastic (MP) fouling issue. Water flux, reverse salt flux (RSF), fouling, and flux recovery were evaluated for the membranes loaded with different quantities of the zwitterions ranging from 0.25 % to 2 %. The developed membranes were tested over 49 h with feed solutions containing polyethylene MPs and bovine serum albumin …


Environmental Analysis Of Codfish Production And Consumption In Portugal, Ayla Frost, Joana Almeida Dr, Joana Dionisio Msc, Radu Godina Dr, Catia Magro Dr Feb 2024

Environmental Analysis Of Codfish Production And Consumption In Portugal, Ayla Frost, Joana Almeida Dr, Joana Dionisio Msc, Radu Godina Dr, Catia Magro Dr

Journal of Critical Global Issues

Codfish, a typical dish consumed frequently in Portugal, is fished in the cold Northern Atlantic waters far from the Portuguese coast. Thus, regional tensions and the environmental impacts of Portuguese codfish importation and production are significant current issues. The present study uses a life cycle assessment methodology to evaluate the array of environmental impacts of the production of 1 kg of codfish, following a cradle to gate approach. The life cycle inventory was grouped into catch and preprocessing, transit, and curing stages. The data collection of products and processes in each stage was based on scientific peer reviewed documents, technical …


Contribution Of Mine Water And Uranium Ore Rocks To The 222rn-Induced Radiation Dose Received By The Mine Workers In A Low-Ore Grade Underground Uranium Mine, India, Imran Athar Beg, Patitapaban Sahu Feb 2024

Contribution Of Mine Water And Uranium Ore Rocks To The 222rn-Induced Radiation Dose Received By The Mine Workers In A Low-Ore Grade Underground Uranium Mine, India, Imran Athar Beg, Patitapaban Sahu

Journal of Sustainable Mining

More than 50% of the radiation dose received by underground mine workers is mainly due to the inhalation of radon (222Rn) gas and its decay products in an underground mine working space. Monitoring and controlling of 222Rn exhalation in the underground mine working plays a vital role in minimizing the radiation risk hazards to the mine-workers. This study discusses the contribution of mine water and uranium ore to 222Rn activity concentration in mine air and its health risk assessment. The annual effective radiation dose (ERn) due to inhalation of 222Rn for mine workers is estimated 0.10 mSv/y. Furthermore, the estimated …


Development Of An Empirical Ground-Motion Model For Post-Mining Induced Seismicity Near Gardanne, France, Pierre Gehl, Pascal Dominique, Hideo Aochi, Mickael Delatre, Jannes Kinscher, Isabelle Contrucci Feb 2024

Development Of An Empirical Ground-Motion Model For Post-Mining Induced Seismicity Near Gardanne, France, Pierre Gehl, Pascal Dominique, Hideo Aochi, Mickael Delatre, Jannes Kinscher, Isabelle Contrucci

Journal of Sustainable Mining

Since the closure of mining activities in 2003, the coal basin of Gardanne in South-East France has experienced thousands of small-magnitude earthquake events, mostly triggered by the flooding of mine workings. Some of these events have been powerful enough to be strongly felt by the population, generating nuisance and concern about potential damage to buildings. The aim of this study is to improve the characterisation of the level of ground motion at the surface, by developing a ground-motion model for post-mining induced seismicity, based on several years of recorded data. A Bayesian-based method is applied to the data in order …


Hydraulic Borehole Mining (Hbm) Technology Employed In Lignite Mining – Technical, Economic And Market Aspects, Bartłomiej Jura, Piotr Krawczyk, Jacek Skiba, Natalia Howaniec Feb 2024

Hydraulic Borehole Mining (Hbm) Technology Employed In Lignite Mining – Technical, Economic And Market Aspects, Bartłomiej Jura, Piotr Krawczyk, Jacek Skiba, Natalia Howaniec

Journal of Sustainable Mining

The results of a cost-effectiveness and economic efficiency assessment of the Hydraulic Borehole Mining (HBM) technology applied to lignite mining are presented. The Dynamic Generation Cost, the Net Present Value, and the Internal Rate of Return were calculated for the extraction of lignite at a rate of about 3.44 million Mg/year from a mining parcel of 1 2.5 km, taking into account CAPEX and OPEX. The cost of mining 1 Mg of lignite using the HBM technology was reported to be lower than its market prices before the energy crisis in Europe caused by the war in Ukraine. The values …


Predicting Open-Pit Mine Production Using Machine Learning Techniques, Faustin Nartey Kumah, Alex Kwasi Saim, Millicent Nkrumah Oppong, Clement Kweku Arthur Feb 2024

Predicting Open-Pit Mine Production Using Machine Learning Techniques, Faustin Nartey Kumah, Alex Kwasi Saim, Millicent Nkrumah Oppong, Clement Kweku Arthur

Journal of Sustainable Mining

In mining, where production is affected by several factors, including equipment availability, it is necessary to develop reliable models to accurately predict mine production to improve operational efficiency. Hence, in this study, four (4) machine learning algorithms – namely: artificial neural network (ANN), random forest (RF), gradient boosting regression (GBR) and decision tree (DT)) – were implemented to predict mine production. Multiple Linear Regression (MLR) analysis was used as a baseline study for comparison purposes. In that regard, one hundred and twenty-six (126) datasets from an open-pit gold mine were used. The developed models were evaluated and compared using the …


Identification Of Strong Tremor Causes For Appropriate Rock Burst Prevention In A Hard Coal Mine, Rafał Pakosz, Łukasz Wojtecki, Maciej J. Mendecki, Agnieszka Krzyżanowska Feb 2024

Identification Of Strong Tremor Causes For Appropriate Rock Burst Prevention In A Hard Coal Mine, Rafał Pakosz, Łukasz Wojtecki, Maciej J. Mendecki, Agnieszka Krzyżanowska

Journal of Sustainable Mining

The exploitation carried out in the Bielszowice part of the Ruda Hard Coal Mine is mainly accompanied by seismic and rock burst hazards. The occurrence of high-energy tremors may be associated with many factors, e.g., fracturing of thick layers of high-strength rocks or destruction processes of a stressed and/or thick coal seam. These factors are often combined when excavating a single longwall panel. Determining the causes of strong tremors is of fundamental importance for mining and rock burst prevention. The extraction of the 004z longwall panel in the top layer of coal seam No. 504 was designed in complex geological …


Mri Image Regression Cnn For Bone Marrow Lesion Volume Prediction, Kevin Yanagisawa Feb 2024

Mri Image Regression Cnn For Bone Marrow Lesion Volume Prediction, Kevin Yanagisawa

Theses and Dissertations

Bone marrow lesions (BMLs), occurs from fluid build up in the soft tissues inside your bone. This can be seen on magnetic resonance imaging (MRI) scans and is characterized by excess water signals in the bone marrow space. This disease is commonly caused by osteoarthritis (OA), a degenerative join disease where tissues within the joint breakdown over time [1]. These BMLs are an emerging target for OA, as they are commonly related to pain and worsening of the diseased area until surgical intervention is required [2]–[4]. In order to assess the BMLs, MRIs were utilized as input into a regression …


A Quick And Cost-Effective Method For Monitoring Deforestation Of Oil Sands Mining Activities Using Synthetic Aperture Radar And Multispectral Real-Time Satellite Data From Sentinel-1 And Sentinel-2., J Garcia Del Real, M. Alcaraz Feb 2024

A Quick And Cost-Effective Method For Monitoring Deforestation Of Oil Sands Mining Activities Using Synthetic Aperture Radar And Multispectral Real-Time Satellite Data From Sentinel-1 And Sentinel-2., J Garcia Del Real, M. Alcaraz

Journal of Sustainable Mining

Alberta’s oil sands mining operations rank among the largest human-made structures globally. Monitoring through the use of Synthetic Aperture Radar (SAR) and Multispectral satellite imaging is an indispensable strategy in attaining sustainable development and mitigating deforestation in the third-largest verified oil reserves worldwide. This paper introduces a novel approach for cost-effective and reliable monitoring of deforestation caused by oil sands mining, avoiding cumbersome methods. It focuses on observing forest/non-forest areas affected by Suncor Energy Company’s mining assets in Alberta, using a combination of SAR and Multispectral satellite remote sensing. Radar images from Sentinel-1B and Multispectral images from Sentinel-2A were analyzed …


Transfer Learning In The Era Of Foundational Models: Application To Diagnosis In Rheumatology, Prashant Shekhar Feb 2024

Transfer Learning In The Era Of Foundational Models: Application To Diagnosis In Rheumatology, Prashant Shekhar

Math Department Colloquium Series

Problems with current synovitis grading procedures

  • There has been a lack of reliability in grading these images in the medical community due to a lack of universally accepted diagnostic criteria [Momtazmanesh et al., 2022]
  • The human/machine variability creates an additional challenge in an efficient automated scoring system [Ranganath et al., 2022]
  • There is a lack of consistency between doctors in grading these images [Momtazmanesh et al., 2022]


History Of Clover Leaf Syndrome, Isabella Perez Feb 2024

History Of Clover Leaf Syndrome, Isabella Perez

Mako: NSU Undergraduate Student Journal

The purpose of this paper is to summarize the history of clover leaf syndrome and describe the newest advancements made to treat it. Clover leaf syndrome is more formally referred to as Kleeblattschadel syndrome. Information was gathered from several scholarly, peer-reviewed articles, and was condensed down into the key takeaways. This syndrome impacts the formation of the skull due to premature fusion of its sutures, creating a tri-lobar skull that resembles a clover leaf. This premature fusion is referred to as a type of craniosynostosis and has been linked to causing several other health complications ranging in severity. This is …


Extraterrestrial Life: The Possibility Of A Human-Alien Interaction, Ariana M. Piscoya Feb 2024

Extraterrestrial Life: The Possibility Of A Human-Alien Interaction, Ariana M. Piscoya

CAFE Symposium 2024

We all have heard of at least one case where someone assured having seen a flying extraterrestrial object. There are thousands of thousands of videos we can find online that “prove” the existence of aliens. In the hypothetical case where aliens are really out there, why haven't we been able to talk to them and look at them face-to-face? A human-extraterrestrial interaction has not yet been achieved for two reasons. First, alien energy is much more powerful than that of humans, so it would require thousands of thousands of years for the human race to develop a technology able to …


Traffic Signal Optimization Using Multiobjective Linear Programming For Oversaturated Traffic Conditions, Mustafa Murat Coşkun, Cevat Şener, İsmail Hakkı Toroslu Feb 2024

Traffic Signal Optimization Using Multiobjective Linear Programming For Oversaturated Traffic Conditions, Mustafa Murat Coşkun, Cevat Şener, İsmail Hakkı Toroslu

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, we present a framework designed to optimize signals at intersections experiencing oversaturated traffic conditions, utilizing mixed-integer linear programming (MILP) techniques. The proposed MILP solutions were developed with different objective functions, namely a reduction in the total remaining queue and fair distribution of the remaining queue after each signal cycle. Our framework contains two distinct stages. The initial stage applies two distinct MILP methodologies, while the subsequent stage employs a neighborhood search method to further reduce the delays associated with the green signal timings derived from the first stage. Ultimately, to evaluate their effectiveness across various intersections, we …


Error Performance Enhancement And Complexity Reduction In Ofdm Systems Via Coordinate Interleaving Under Practical Impairments, Mustafa Anıl Reşat, Armed Tusha, Seda Doğan Tusha, Serdar Özyurt, Hüseyin Arslan Feb 2024

Error Performance Enhancement And Complexity Reduction In Ofdm Systems Via Coordinate Interleaving Under Practical Impairments, Mustafa Anıl Reşat, Armed Tusha, Seda Doğan Tusha, Serdar Özyurt, Hüseyin Arslan

Turkish Journal of Electrical Engineering and Computer Sciences

In this work, subcarrier coordinate interleaving (CI) is implemented to orthogonal frequency division multiplexing (OFDM) systems with the aim of both enhancing the error performance and reducing the implementation complexity. To this end, the modulated symbols are independently chosen from a modified M-ary amplitude-shift keying signal constellation under a specific CI strategy. In addition to doubling the diversity level of the original OFDM scheme, the adopted CI approach also drastically reduces the inverse fast Fourier transform (IFFT) size at the transmit side by guaranteeing the first half of the input vector to be identical with the second half at the …


Artificial Intelligence-Based Evaluation Of The Factors Affecting The Sales Of An Iron And Steel Company, Mehmet Pekkaya, Zafer Uysal, Aytaç Altan, Seçkin Karasu Feb 2024

Artificial Intelligence-Based Evaluation Of The Factors Affecting The Sales Of An Iron And Steel Company, Mehmet Pekkaya, Zafer Uysal, Aytaç Altan, Seçkin Karasu

Turkish Journal of Electrical Engineering and Computer Sciences

It is important to predict the sales of an iron and steel company and to identify the variables that influence these sales for future planning. The aim in this study was to identify and model the key factors that influence the sales volume of an iron and steel company using artificial neural networks (ANNs). We attempted to obtain an integrated result from the performance/sales levels of 5 models, to use the ANN approach with hybrid algorithms, and also to present an exemplary application in the base metals industry, where there is a limited number of studies. This study contributes to …


Fast Grid Search: A Grid Search-Inspired Algorithm For Optimizing Hyperparameters Of Support Vector Regression, Mustafa Açikkar Feb 2024

Fast Grid Search: A Grid Search-Inspired Algorithm For Optimizing Hyperparameters Of Support Vector Regression, Mustafa Açikkar

Turkish Journal of Electrical Engineering and Computer Sciences

This study presents a fast hyperparameter optimization algorithm based on the benefits and shortcomings of the standard grid search (GS) algorithm for support vector regression (SVR). This presented GS-inspired algorithm, called fast grid search (FGS), was tested on benchmark datasets, and the impact of FGS on prediction accuracy was primarily compared with the GS algorithm on which it is based. To validate the efficacy of the proposed algorithm and conduct a comprehensive comparison, two additional hyperparameter optimization techniques, namely particle swarm optimization and Bayesian optimization, were also employed in the development of models on the given datasets. The evaluation of …


Machine Learning Approaches In Comparative Studies For Alzheimer’S Diagnosis Using 2d Mri Slices, Zhen Zhao, Joon Huang Chuah, Chee-Onn Chow, Kaijian Xia, Yee Kai Tee, Yan Chai Hum, Khin Wee Lai Feb 2024

Machine Learning Approaches In Comparative Studies For Alzheimer’S Diagnosis Using 2d Mri Slices, Zhen Zhao, Joon Huang Chuah, Chee-Onn Chow, Kaijian Xia, Yee Kai Tee, Yan Chai Hum, Khin Wee Lai

Turkish Journal of Electrical Engineering and Computer Sciences

Alzheimer’s disease (AD) is an illness that involves a gradual and irreversible degeneration of the brain. It is crucial to establish a precise diagnosis of AD early on in order to enable prompt therapies and prevent further deterioration. Researchers are currently focusing increasing attention on investigating the potential of machine learning techniques to simplify the automated diagnosis of AD using neuroimaging. The present study involved a comparison of models for the detection of AD through the utilization of 2D image slices obtained from magnetic resonance imaging brain scans. Five models, namely ResNet, ConvNeXt, CaiT, Swin Transformer, and CVT, were implemented …


Fractional Delay-Dependent Load Frequency Controller Design For A Single-Area Power System With Communication Delay, Erhan Yumuk Feb 2024

Fractional Delay-Dependent Load Frequency Controller Design For A Single-Area Power System With Communication Delay, Erhan Yumuk

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes a fractional delay-dependent load frequency control design approach for a single-area power system with communication delay based on gain and phase margin specifications. In this approach, the closed-loop reference transfer function relies on the delayed Bode’s transfer function. The gain and phase margin specifications are established in order to optimize the reference model based on three time-domain performance indices. Here, a category of fractional-order model is employed to describe the single-area power system incorporating communication delay. The controller parameters are determined using the fractional-order system model and optimal closed-loop reference model. Then, a delay-dependent control mechanism is …


Grey Wolf Optimization Algorithm-Based Robust Neural Learning Control Of Passive Torque Simulators With Predetermined Performance, Seyyed Amirhossein Saadat, Mohammad Mehdi Fateh, Javad Keighobadi Feb 2024

Grey Wolf Optimization Algorithm-Based Robust Neural Learning Control Of Passive Torque Simulators With Predetermined Performance, Seyyed Amirhossein Saadat, Mohammad Mehdi Fateh, Javad Keighobadi

Turkish Journal of Electrical Engineering and Computer Sciences

In flight control systems, the actuators need to tolerate aerodynamic torques and continue their operations without interruption. To this end, using the simulators to test the actuators in conditions close to the real flight is efficient. On the other hand, achieving the guaranteed performance encounters some challenges and practical limitations such as unknown dynamics, external disturbances, and state constraints in reality. Thus, this article attempts to present a robust adaptive neural network learning controller equipped with a disturbance observer for passive torque simulators (PTS) with load torque constraints. The radial basis function networks (RBFNs) are employed to identify the unknown …


Differentially Private Online Bayesian Estimation With Adaptive Truncation, Sinan Yildirim Feb 2024

Differentially Private Online Bayesian Estimation With Adaptive Truncation, Sinan Yildirim

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a novel online and adaptive truncation method is proposed for differentially private Bayesian online estimation of a static parameter regarding a population. A local differential privacy setting is assumed where sensitive information from individuals is collected on an individual level and sequentially. The inferential aim is to estimate, on the fly, a static parameter regarding the population to which those individuals belong. We propose sequential Monte Carlo to perform online Bayesian estimation. When individuals provide sensitive information in response to a query, it is necessary to corrupt it with privacy-preserving noise to ensure the privacy of those …


Motion Magnification-Inspired Feature Manipulation For Deepfake Detection, Aydamir Mirzayev, Hamdi Di̇bekli̇oğlu Feb 2024

Motion Magnification-Inspired Feature Manipulation For Deepfake Detection, Aydamir Mirzayev, Hamdi Di̇bekli̇oğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Recent advances in deep learning, increased availability of large-scale datasets, and improvement of accelerated graphics processing units facilitated creation of an unprecedented amount of synthetically generated media content with impressive visual quality. Although such technology is used predominantly for entertainment, there is widespread practice of using deepfake technology for malevolent ends. This potential for malicious use necessitates the creation of detection methods capable of reliably distinguishing manipulated video content. In this work we aim to create a learning-based detection method for synthetically generated videos. To this end, we attempt to detect spatiotemporal inconsistencies by leveraging a learning-based magnification-inspired feature manipulation …


Milp Modeling Of Matrix Multiplication: Cryptanalysis Of Klein And Prince, Murat Burhan İlter, Ali Aydın Selçuk Feb 2024

Milp Modeling Of Matrix Multiplication: Cryptanalysis Of Klein And Prince, Murat Burhan İlter, Ali Aydın Selçuk

Turkish Journal of Electrical Engineering and Computer Sciences

Mixed-integer linear programming (MILP) techniques are widely used in cryptanalysis, aiding in the discovery of optimal linear and differential characteristics. This paper delves into the analysis of block ciphers KLEIN and PRINCE using MILP, specifically calculating the best linear and differential characteristics for reduced-round versions. Both ciphers employ matrix multiplication in their diffusion layers, which we model using multiple XOR operations. To this end, we propose two novel MILP models for multiple XOR operations, which use fewer variables and constraints, proving to be more efficient than standard methods for XOR modeling. For differential cryptanalysis, we identify characteristics with a probability …


Automated Identification Of Vehicles In Very High-Resolution Uav Orthomosaics Using Yolov7 Deep Learning Model, Esra Yildirim, Umut Güneş Seferci̇k, Taşkın Kavzoğlu Feb 2024

Automated Identification Of Vehicles In Very High-Resolution Uav Orthomosaics Using Yolov7 Deep Learning Model, Esra Yildirim, Umut Güneş Seferci̇k, Taşkın Kavzoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

The utilization of remote sensing products for vehicle detection through deep learning has gained immense popularity, especially due to the advancement of unmanned aerial vehicles (UAVs). UAVs offer millimeter-level spatial resolution at low flight altitudes, which surpasses traditional airborne platforms. Detecting vehicles from very high-resolution UAV data is crucial in numerous applications, including parking lot and highway management, traffic monitoring, search and rescue missions, and military operations. Obtaining UAV data at desired periods allows the detection and tracking of target objects even several times during a day. Despite challenges such as diverse vehicle characteristics, traffic congestion, and hardware limitations, the …


Longitudinal Attacks Against Iterative Data Collection With Local Differential Privacy, Mehmet Emre Gürsoy Feb 2024

Longitudinal Attacks Against Iterative Data Collection With Local Differential Privacy, Mehmet Emre Gürsoy

Turkish Journal of Electrical Engineering and Computer Sciences

Local differential privacy (LDP) has recently emerged as an accepted standard for privacy-preserving collection of users’ data from smartphones and IoT devices. In many practical scenarios, users’ data needs to be collected repeatedly across multiple iterations. In such cases, although each collection satisfies LDP individually by itself, a longitudinal collection of multiple responses from the same user degrades that user’s privacy. To demonstrate this claim, in this paper, we propose longitudinal attacks against iterative data collection with LDP. We formulate a general Bayesian adversary model, and then individually show the application of this adversary model on six popular LDP protocols: …


A Novel Extended Reaction Force/Torque Observer With Impedance Control, İlkay Turaç Özçeli̇k, Abdurrahman Eray Baran Feb 2024

A Novel Extended Reaction Force/Torque Observer With Impedance Control, İlkay Turaç Özçeli̇k, Abdurrahman Eray Baran

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes a new extended version of the reaction force observer (RFOB) for high-precision motion control systems. The RFOB has been proven to be useful for many applications in the literature. However, because of the low-pass filter present inside of the RFOB, it has certain limitations. In this study, a new algorithm is proposed to compensate for filtering-based errors in the classical RFOB structure. The algorithm includes the differentiation of the observed force and scaling with a proper value. However, since the force has a noisy nature, differentiation also affects the signal’s stability and performance. To resolve this issue, …


Maximizing Charge Dynamics In Znin2s4/Cn Van Der Waals Heterojunction For Optimal Hydrogen Production From Photoreforming Of Glucose, Jinqiang Zhang, Xinyuan Xu, Lei Shi, Huayang Zhang, Shaobin Wang, Hongqi Sun Feb 2024

Maximizing Charge Dynamics In Znin2s4/Cn Van Der Waals Heterojunction For Optimal Hydrogen Production From Photoreforming Of Glucose, Jinqiang Zhang, Xinyuan Xu, Lei Shi, Huayang Zhang, Shaobin Wang, Hongqi Sun

Research outputs 2022 to 2026

Biomass photoreforming stands out as a promising avenue for green hydrogen, leveraging solar energy for the generation and transformation of clean and renewable energy resources. The pursuit of efficient photocatalysts is motivated by the unsatisfied hydrogen evolution performance arising from the complex and stubborn structure of biomass. Herein, we loaded 2-dimensional (2D) ZnIn2S4 onto 2D carbon nitride nanosheets, resulting in the formation of Van der Waals (VDW) heterojunctions (ZIS/CN). Band structure and morphology of CN were rationally tailored through precursor engineering to effectively magnify interfacial internal electric field and minimize diffusion pathway within the VDW heterostructure, realizing optimal charge dynamics …


Analysis Of The Impact Of Water Treatment By Liming Sedimentation And Dredging On The Content Of Heavy Metals In Fish Intended For Consumption, Asfie Maidie, Ismail Fahmy Almadi, Muchlis Efendi, Rekha Yusdha Nilawardhani, Komsanah Sukarti, Henny Pagoray Feb 2024

Analysis Of The Impact Of Water Treatment By Liming Sedimentation And Dredging On The Content Of Heavy Metals In Fish Intended For Consumption, Asfie Maidie, Ismail Fahmy Almadi, Muchlis Efendi, Rekha Yusdha Nilawardhani, Komsanah Sukarti, Henny Pagoray

Journal of Sustainable Mining

The present study sought to determine the presence of metals and arsenic, a metalloid, among the fish of a coal mine reservoir, where the water was treated regularly through liming sedimentation combined with dredging, and the fish living in an adjoining river. The potential hazard of metals in fish as human food was analyzed. Except for selenium (an important metal to the human body), which was higher among the river fish than in the reservoir fish (P < 0.01), there were no particular patterns of other studied metals found in either habitat (P > 0.05), and apparently not related to the fish family that consumed by local people. Measurements of bioaccumulation factor (BAF) yielded scattered values from …


Containerization Of Seafarers In The International Shipping Industry: Contemporary Seamanship, Maritime Social Infrastructures, And Mobility Politics Of Global Logistics, Liang Wu Feb 2024

Containerization Of Seafarers In The International Shipping Industry: Contemporary Seamanship, Maritime Social Infrastructures, And Mobility Politics Of Global Logistics, Liang Wu

Dissertations, Theses, and Capstone Projects

This dissertation discusses the mobility politics of container shipping and argues that technological development, political-economic order, and social infrastructure co-produce one another. Containerization, the use of standardized containers to carry cargo across modes of transportation that is said to have revolutionized and globalized international trade since the late 1950s, has served to expand and extend the power of international coalitions of states and corporations to control the movements of commodities (shipments) and labor (seafarers). The advent and development of containerization was driven by a sociotechnical imaginary and international social contract of seamless shipping and cargo flows. In practice, this liberal, …