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The Effect of NaCl on the Stability of Ab3 Lipase from Sphingobacterium sp. that Co-Expressed with LEA K Using In silico Approach

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American Journal of Biochemistry and Biotechnology 2025年第1期21卷 60-67页

作者： Muhammad, Ibrahim Ning, Ng Siau Ismail, Nurul Izza Arsad, Hasni Ikeno, Shinya Rahim, Rashidah Abdul School of Biological Sciences University Sains Malaysia Penang Malaysia Persiaran Bukit Jambul Bayan Lepas Penang Malaysia Advanced Medical and Dental Institute University Sains Malaysia Bandar Putra Bertam Kepala Batas Penang Malaysia Central Business District Garki Abuja900001 Nigeria Department of Science Lab. Technology Ramat Polytechnic Maiduguri Borno 600211 Nigeria Department of Biological Functions and Engineering Graduate School of Life Science and System Engineering Kyushu Institute of Technology Japan

This study explores how sodium chloride (NaCl) influences the binding affinity and stability of the Ab3 lipase-LEA K complex when interacting with olive oil, using molecular docking techniques. The docking simulations, conducted with Auto Dock Vina, reveal that the presence of NaCl significantly enhances the binding affinity of the enzyme-substrate complex, increasing it from-6.55 kcal/moL in the absence of salt to-7.81 kcal/moL with salt. This improvement in binding affinity is accompanied by the formation of additional hydrogen bonds and hydrophobic interactions, indicating that NaCl induces a favourable conformational change in the enzyme complex. Notably, NaCl facilitates interaction with His287, a key residue in the catalytic triad, suggesting improved accessibility and orientation of the active site, which is crucial for catalytic efficiency. These findings underscore the role of NaCl in stabilizing the enzyme complex and enhancing its structural integrity and activity, which has significant implications for industrial applications. Specifically, in industries where processes occur under high-salt conditions, such as food processing and biofuel production, the ability of NaCl to enhance lipase stability and performance could lead to more efficient and cost-effective operations, reducing the need for frequent enzyme replacement and improving overall process efficiency. © 2025 Ibrahim Muhammad, Ng Siau Ning, Nurul Izza Ismail, Hasni Arsad, Shinya Ikeno and Rashidah Abdul Rahim.

关键词： Olive oil

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Implementation of Brushless DC Motor Control Chip Based on PWM Technique 9

Implementation of Brushless DC Motor Control Chip Based on P...

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9th International Conference on Integrated Circuits and Microsystems, ICICM 2024

作者： Xi, Wei Liu, Siyang Sun, Weifeng Southeast University National ASIC System Engineering Research Center Nanjing China Shanghai JARI Zhaoxin Information Technology Company Limited Innovation and Research Department Nanjing China

ISBN: (纸本)9798331509453

In this paper, a brushless DC motor control chip based on PWM technique is proposed. It integrates the rotor position decoder and includes functions for forward and reverse rotation as well as angle selection. The chip integrates the functions of under-voltage protection, over-current protection, and over-temperature protection. This integration enhances the functionality of the chip. The width of the PWM signals is controlled by an external modulation input voltage. Motor speed is controlled by generating a PWM signal with a variable pulse width. The chip outputs six control signals that can be used to control a three-phase brushless motor. The chip design is completed using a 0.25μm BCD process, and the simulation and test results are consistent. The chip is easy to control, occupies a small area, and can reliably drive and control the motor. © 2024 IEEE.

关键词： Brushless DC motors

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Tensor-Based Multi-Scale Correlation Anomaly Detection for AIoT-Enabled Consumer Applications

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IEEE Transactions on Consumer Electronics 2024年第1期71卷 2061-2071页

作者： Zeng, Jiuzhen Yang, Laurence T. Wang, Chao Deng, Xianjun Yang, Xiangli Huazhong University of Science and Technology Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Wuhan430074 China Huazhong University of Science and Technology School of Cyber Science and Engineering Wuhan430074 China Zhengzhou University School of Computer and Artificial Intelligence Zhengzhou450001 China St. Francis Xavier University Department of Computer Science AntigonishNSB2G 2W5 Canada University of South China School of Electrical Engineering Hengyang421001 China

Artificial Intelligence of Things (AIoT) is an innovative paradigm expected to enable various consumer applications that is transforming our lives. While enjoying benefits and services from these applications, we also face serious security issues due to malicious cyber attacks on the massive growth of AIoT consumer devices. Accurate anomaly detection is one of the critical tasks for the trustworthy AIoT removing those obstacles. However, limited by the vector-based data pattern and ill-considered factors for anomalous samples analysis, existing methods suffer from the low detection performance. In this paper, a multi-scale correlation tensor convolutional Gaussian mixture network (named as MTCGM) is presented for ameliorating this actuality. Specifically, MTCGM suggests to construct the multi-scale correlation tensor by stacking one self-correlation matrix and multiple surrounding-correlations of different scales, which well characterizes the network status of AIoT. Subsequently, a 3D-convolutional autoencoder (3DCA) is designed for capturing inter-feature correlations, and followed with a Gaussian mixture probability (GMP) network for the observations likelihood estimation. Moreover, low-dimensional space features, relative Euclidean distance and tensor cosine similarity (TCS) are adopted in MTCGM as the multi-factor to boost the likelihood estimation. Extensive experiments on public benchmark datasets verify the validity of MTCGM, and demonstrate its superiority over the state-of-the-art baselines even in presence of contaminated training samples and input noise. © 1975-2011 IEEE.

关键词： Tensors

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Automated Grading of Breast Cancer Histopathology Images Using Multilayered Autoencoder

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Computers, Materials & Continua 2022年第5期71卷 3407-3423页

作者： Shakra Mehak M.Usman Ashraf Rabia Zafar Ahmed M.Alghamdi Ahmed S.Alfakeeh Fawaz Alassery Habib Hamam Muhammad Shafiq Knowledge Unit of System and Technology University of Management&TechnologySialkot Campus51310Pakistan Department of Computer Science University of Management and TechnologySialkot Campus51310Pakistan Faculty of Computing and Technology University of Engineering&TechnologyNarowal51610Pakistan College of Computer Science and Engineering University of Jeddah21493Saudi Arabia Faculty of Computing and Information Technology King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaifSaudi Arabia Faculty of Engineering Moncton UniversityNBE1A3E9Canada Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

Breast cancer(BC)is the most widely recognized cancer in women *** 2018,627,000 women had died of breast cancer(World Health Organization Report 2018).To diagnose BC,the evaluation of tumours is achieved by analysis of histological *** present,the Nottingham Bloom Richardson framework is the least expensive approach used to grade BC *** contemplate three elements,*** count,*** formation,and *** atypia,which is a laborious process that witness’s variations in expert’s ***,some algorithms have been proposed for the detection of mitotic cells,but nuclear atypia in breast cancer histopathology has not received much *** atypia analysis is performed not only to grade BC but also to provide critical information in the discrimination of normal breast,non-invasive breast(usual ductal hyperplasia,atypical ductal hyperplasia)and pre-invasive breast(ductal carcinoma in situ)and invasive breast *** proposed a deep-stacked multi-layer autoencoder ensemble with a softmax layer for the feature extraction and classification *** classification results show the value of the multilayer autoencoder model in the evaluation of nuclear *** proposed method has indicated promising results,making them more fit in breast cancer grading.

关键词： Breast cancer nuclear atypia autoencoder

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Performance Analysis of Magnetic Nanoparticles during Targeted Drug Delivery:Application of OHAM

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Computer Modeling in engineering & Sciences 2022年第2期130卷 723-749页

作者： Muhammad Zafar Muhammad Saif Ullah Tareq Manzoor Muddassir Ali Kashif Nazar Shaukat Iqbal HabibUllah Manzoor Rizwan Haider Woo Young Kim Institute of Energy and Environmental Engineering University of the PunjabQuaid-e-Azam CampusLahore54590Pakistan Energy Research Centre COMSATS University IslamabadLahore54000Pakistan Department of Energy Engineering Faculty of Mechanical and Aeronautical EngineeringUniversity of Engineering and TechnologyTaxila47080Pakistan Department of Mathematics COMSATS University IslamabadLahore54000Pakistan School of Systems and Technology University of Management Sciences and TechnologyLahore54770Pakistan Department of Electrical Electronics and TelecommunicationEngineeringUniversity of Engineering and TechnologyLahore(FSD Campus)Faisalabad38000Pakistan Department of Electronic Engineering Faculty of Applied Energy SystemJeju National UniversityJeju Special Self-Governing ProvinceJeju-si63243Korea

In recent years,the emergence of nanotechnology experienced incredible development in the field of medical *** the past decade,investigating the characteristics of nanoparticles during fluid flow has been one of the intriguing *** distribution and uniformity have emerged as substantial criteria in both medical and engineering *** effects of chemotherapy on healthy tissues are known to be a significant concern during cancer therapy.A novel treatment method of magnetic drug targeting(MDT)has emerged as a promising topical cancer treatment along with some attractive advantages of improving efficacy,fewer side effects,and reduce drug *** magnetic drug targeting,the appropriate movement of nanoparticles(magnetic)as carriers is essential for the therapeutic process in the blood clot removal,infection treatment,and tumor cell *** this study,we have numerically investigated the behavior of an unsteady blood flowinfused with magnetic nanoparticles during MDT under the influence of a uniform external magnetic field in a *** optimal homotopy asymptotic method(OHAM)is employed to compute the governing equation for unsteady electromagnetohydrodynamics *** influence of Hartmann number(Ha),particle mass parameter(G),particle concentration parameter(R),and electro-osmotic parameter(k)is investigated on the velocity of magnetic nanoparticles and blood *** obtained show that the electro-osmotic parameter,along with Hartmann’s number,dramatically affects the velocity of magnetic nanoparticles,blood flow velocity,and flow ***,results also reveal that at a higher Hartman number,homogeneity in nanoparticles distribution improved *** particle concentration andmass parameters effectively influence the capturing effect on nanoparticles in the blood flow using a micro-tube for magnetic drug ***,investigation also indicates that the OHAM analysis is efficient and quick to h

关键词： Hartmann number magnetic nanoparticles nonlinear analysis targeted drug delivery optimal homotopy asymptotic method(OHAM)

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Granular Ionogel Particle Inks for 3D Printed Tough and Stretchable Ionotronics

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Research 2024年第1期2023卷 429-442页

作者： Yuan Yao Yue Hui Zhenhua Wang Hehao Chen Heng Zhu Nanjia Zhou Key Laboratory of 3D Micro/Nano Fabrication and Characterization of Zhejiang Province School of EngineeringWestlake UniversityHangzhou 310024Zhejiang ProvinceChina Institute of Advanced Technology Westlake Institute for Advanced StudyHangzhou 310024Zhejiang ProvinceChina School of Chemical Engineering and Advanced Materials the University of AdelaideAdelaide 5005South AustraliaAustralia State Key Laboratory of Fluid Power&Mechatronic System Key Laboratory of Soft Machines and Smart Devices of Zhejiang ProvinceCenter for X-MechanicsDepartment of Engineering MechanicsZhejiang UniversityHangzhou 310027China

Ionogels have garnered great attention as promising soft conducting materials for the fabrication of flexible energy storage devices,soft actuators,and ***,the leakage of the ionic liquids,weak mechanical strength,and poor manufacturability have greatly limited their reliability and ***,we propose a new ionogel synthesis strategy by utilizing granular zwitterionic microparticles to stabilize ionic *** ionic liquids swell the microparticles and physically crosslink microparticles via either electronic interaction or hydrogen *** introducing a photocurable acrylic monomer enables the fabrication of double-network(DN)ionogels with high stretchability(>600%)and ultrahigh toughness(fracture energy>10 kJ/m^(2)).The synthesized ionogels exhibit a wide working temperature of−60 to 90℃.By tuning the crosslinking density of microparticles and physical crosslinking strength of ionogels,we synthesize DN ionogel inks and print them into three-dimensional(3D)*** ionogelbased ionotronics are 3D printed as demonstrations,including strain gauges,humidity sensors,and ionic skins made of capacitive touch sensor *** covalently linking ionogels with silicone elastomers,we integrate the ionogel sensors onto pneumatic soft actuators and demonstrate their capacities in sensing large *** our last demonstration,multimaterial direct ink writing is harnessed to fabricate highly stretchable and durable alternating-current electroluminescent devices with arbitrary *** printable granular ionogel ink represents a versatile platform for the future manufacturing of ionotronics.

关键词： crosslinking utilizing gauge

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VMAP: Matching-based Efficient Offloading in IoT-Fog Environments with Variable Resources 17

VMAP: Matching-based Efficient Offloading in IoT-Fog Environ...

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17th IEEE International Conference on Advanced Networks and Telecommunications systems, ANTS 2023

作者： Morey, Jui Satpathy, Anurag Addya, Sourav Kanti Cloud and Smart System Services Lab Department of Computer Science and Engineering National Institute of Technology Karnataka Surathkal India Missouri University of Science and Technology United States

ISBN: (纸本)9798350307672

Fog computing is a promising technology for critical, resource-intensive, and time-sensitive applications. In this regard, a significant challenge is generating an offloading solution that minimizes the latency, energy, and number of outages for a dense IoT-Fog environment. However, the existing solutions either focus on a single objective or mainly dedicate fixed-sized resources as virtual resource units (VRUs). Moreover, these solutions are restrictive and not comprehensive, resulting in poor performance. To overcome these challenges, this paper proposes a VMAP model addressing the lacunas above. Offloading problem is abstracted as a one-to-many matching game between two sets of entities - tasks and fog nodes (FNs) by considering both preferences. Moreover, the preferences and weights of the parameters are generated using the Analytic Hierarchy Process (AHP). Exhaustive simulations indicate that the proposed strategy outperforms the baseline algorithms, considering average task latency and energy consumption by 35% and 22.2%, respectively. Additionally, resource utilization also experiences a boost by 28.57%, and 97.98% of tasks complete their execution within the deadlines. © 2023 IEEE.

关键词： Fog

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De novo engineering of nanoformulation from traditional Chinese medicine mixtures for psoriasis

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Nano Research 2023年第4期16卷 5279-5291页

作者： Yang Li Dan Zhang Tianzi Shi Yulin Yu Yinmei Tian Qi Xie Jingyu Shi Li Kong Conglian Yang Zhiping Zhang Tongji School of Pharmacy Huazhong University of Science and TechnologyWuhan 430030China Department of Pharmacy Wuhan No.1 HospitalTongji Medical SchoolHuazhong University of Science and TechnologyWuhan 430022China Department of Pharmacy Liyuan HospitalTongji Medical SchoolHuazhong University of Science and TechnologyWuhan 430077China Hubei Engineering Research Centre for Novel Drug Delivery System Wuhan 430030China

Nanotechnology has been widely applied in the development of traditional Chinese medicine(TCM).Interestingly,we found that nanostructures intrinsically existed in 12 clinically applied TCM mixtures(TCMMs).However,the role of these nanostructures in TCMMs and their potential value in improving the development of TCMMs remain *** Qingxuechushi mixture as an example,we demonstrated that nanoparticles could be the most efficient part through the pharmacodynamics study on psoriasis *** imitating the physical properties and chemical composition of isolated nanoparticles in Qingxuechushi mixture,a novel nanoformulation with definite components and good therapeutic effect was developed,which not only mimicked the prescription composition rules in the original TCMMs but also possessed the advantage of *** novel nanoformulation could notably alleviate the psoriasis-like manifestations and reduce the levels of pro-inflammatory factors in serum in the psoriasis mouse *** work organically integrates the advantages of TCMMs and nanotechnology,which may provide a new approach and inspiration for the development of TCM.

关键词： traditional Chinese medicine nanotechnology psoriasis nanostructures glycyrrhiza protein

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An innovation prediction of DNA damage of melanoma skin cancer patients using deep learning 14

An innovation prediction of DNA damage of melanoma skin canc...

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14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Ramakrishnan, Rakesh Mohammed, Mehmood Ali Mohammed, Murtuza Ali Mohammed, Vazeer Ali Logeshwaran, J. Maheswaran, S. University of the Cumberlands Department of Information Technology Union CityCA United States University of the Cumberlands Department of Information Technology WilliamsburgKY United States Lewis University Department of Computer & Information System IL United States Sri Eshwar College of Engineering Department of Electronics and Communication Engineering Tamil Nadu Coimbatore India Kongu Engineering College Department of Electronics and Communication Engineering Tamil Nadu Erode India

ISBN: (纸本)9798350335095

There are now a variety of intriguing options for the study of genetic data thanks to recent developments in artificial neural networks and deep learning. In this study, we use a deep learning-based prediction model to find possible DNA damage in individuals with melanoma skin cancer. We create a convolutional neural network (CNN) model to forecast the DNA damage susceptibility of melanoma cancer cells using a publically available genome sequencing dataset. This model preprocesses the genomic data, extracts features, and categorises them. Comparing the results of our CNN model with those of a traditional logistic regression model, we find that our CNN reported superior performance in identifying differences between healthy and cancerous samples with an accuracy of nearly 96%. The model can be used to augment the standard clinical diagnosis of melanoma, which only uses visual assessment and histology. By intervening sooner, clinicians can put forward more personalized and informed plans of care and surveillance for each melanoma patient, reducing medical costs and improving the quality of patient diagnosis. © 2023 IEEE.

关键词： Neural network models

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Integrated operating room planning and scheduling: an ILP-Based off-line approach for emergency responsiveness at a local hospital in Naples

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Soft Computing 2024年第20期28卷 11987-12003页

作者： Boccia, Maurizio Mancuso, Andrea Masone, Adriano Sterle, Claudio Department of Electrical Engineering and Information Technology University of Naples "Federico II" Via Claudio 21 Naples80125 Italy Institute for System Analysis and Computer Science "Antonio Ruberti" National Research Council of Italy via dei Taurini 19 Rome00185 Italy

This paper addresses a real-world Integrated Operating Room Planning and Scheduling (IORPS) problem encountered by a local hospital in Naples, characterized by stringent emergency management constraints, requiring treatment initiation within a 20-minute time-window. We tackle this problem by an original Integer Linear Programming formulation, capable of dealing with different operating room management strategies (open, block and block-modified). Our work differs from conventional cost-focused models by adopting a patient-oriented objective function, aligning with public hospitals obligations. The proposed method has been validated using real-world data provided by the hospital. The performed experimentation demonstrates the efficiency of the approach, capable of determining the optimal solution within an acceptable computation time that aligns with hospital requirements. Moreover, it also highlights the relevance of using our optimization approach to reduce delays in emergency responsiveness. This confirms its practical usage as a substitute for the current manual procedure. © The Author(s) 2024.

关键词： Operating rooms

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