Subjects -> ENGINEERING (Total: 2791 journals)
    - CHEMICAL ENGINEERING (248 journals)
    - CIVIL ENGINEERING (242 journals)
    - ELECTRICAL ENGINEERING (176 journals)
    - ENGINEERING (1402 journals)
    - ENGINEERING MECHANICS AND MATERIALS (452 journals)
    - HYDRAULIC ENGINEERING (56 journals)
    - INDUSTRIAL ENGINEERING (100 journals)
    - MECHANICAL ENGINEERING (115 journals)

ENGINEERING (1402 journals)                  1 2 3 4 5 6 7 8 | Last

Showing 1 - 200 of 1205 Journals sorted alphabetically
3 Biotech     Open Access   (Followers: 2)
3D Research     Hybrid Journal   (Followers: 17)
AAPG Bulletin     Hybrid Journal   (Followers: 9)
Abstract and Applied Analysis     Open Access   (Followers: 1)
Aceh International Journal of Science and Technology     Open Access   (Followers: 3)
ACS Nano     Hybrid Journal   (Followers: 189)
Acta Geotechnica     Hybrid Journal   (Followers: 6)
Acta Metallurgica Sinica (English Letters)     Hybrid Journal   (Followers: 8)
Acta Nova     Open Access  
Acta Polytechnica : Journal of Advanced Engineering     Open Access  
Acta Universitatis Cibiniensis. Technical Series     Open Access   (Followers: 1)
Active and Passive Electronic Components     Open Access   (Followers: 5)
Additive Manufacturing Letters     Open Access   (Followers: 6)
Adsorption     Hybrid Journal   (Followers: 4)
Advanced Energy and Sustainability Research     Open Access   (Followers: 4)
Advanced Engineering Forum     Full-text available via subscription   (Followers: 10)
Advanced Engineering Research     Open Access  
Advanced Journal of Graduate Research     Open Access   (Followers: 1)
Advanced Quantum Technologies     Hybrid Journal   (Followers: 1)
Advanced Science     Open Access   (Followers: 11)
Advanced Science Focus     Free   (Followers: 5)
Advanced Science Letters     Full-text available via subscription   (Followers: 8)
Advanced Science, Engineering and Medicine     Partially Free   (Followers: 3)
Advanced Synthesis & Catalysis     Hybrid Journal   (Followers: 19)
Advanced Theory and Simulations     Hybrid Journal   (Followers: 2)
Advances in Applied Energy     Open Access   (Followers: 5)
Advances in Catalysis     Full-text available via subscription   (Followers: 7)
Advances in Complex Systems     Hybrid Journal   (Followers: 10)
Advances in Engineering Software     Hybrid Journal   (Followers: 25)
Advances in Fuzzy Systems     Open Access   (Followers: 5)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 19)
Advances in Heat Transfer     Full-text available via subscription   (Followers: 27)
Advances in Natural Sciences : Nanoscience and Nanotechnology     Open Access   (Followers: 28)
Advances in Operations Research     Open Access   (Followers: 13)
Advances in OptoElectronics     Open Access   (Followers: 6)
Advances in Physics Theories and Applications     Open Access   (Followers: 12)
Advances in Polymer Science     Hybrid Journal   (Followers: 50)
Advances in Remote Sensing     Open Access   (Followers: 58)
Advances in Science and Research (ASR)     Open Access   (Followers: 8)
Aerobiologia     Hybrid Journal   (Followers: 2)
Aerospace Systems     Hybrid Journal   (Followers: 7)
African Journal of Science, Technology, Innovation and Development     Hybrid Journal   (Followers: 7)
AIChE Journal     Hybrid Journal   (Followers: 31)
Ain Shams Engineering Journal     Open Access   (Followers: 1)
Al-Nahrain Journal for Engineering Sciences     Open Access  
Al-Qadisiya Journal for Engineering Sciences     Open Access  
AL-Rafdain Engineering Journal     Open Access  
Alexandria Engineering Journal     Open Access   (Followers: 1)
AMB Express     Open Access   (Followers: 1)
American Journal of Applied Sciences     Open Access   (Followers: 21)
American Journal of Engineering and Applied Sciences     Open Access   (Followers: 7)
American Journal of Engineering Education     Open Access   (Followers: 13)
American Journal of Environmental Engineering     Open Access   (Followers: 6)
American Journal of Industrial and Business Management     Open Access   (Followers: 23)
Annals of Civil and Environmental Engineering     Open Access   (Followers: 1)
Annals of Combinatorics     Hybrid Journal   (Followers: 3)
Annals of Pure and Applied Logic     Open Access   (Followers: 4)
Annals of Regional Science     Hybrid Journal   (Followers: 7)
Annals of Science     Hybrid Journal   (Followers: 9)
Annual Journal of Technical University of Varna     Open Access  
Antarctic Science     Hybrid Journal   (Followers: 1)
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 3)
Applicable Analysis: An International Journal     Hybrid Journal   (Followers: 1)
Applications in Energy and Combustion Science     Open Access   (Followers: 2)
Applications in Engineering Science     Open Access  
Applied Catalysis A: General     Hybrid Journal   (Followers: 7)
Applied Catalysis B: Environmental     Hybrid Journal   (Followers: 9)
Applied Clay Science     Hybrid Journal   (Followers: 6)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 16)
Applied Energy     Partially Free   (Followers: 25)
Applied Engineering Letters     Open Access  
Applied Magnetic Resonance     Hybrid Journal   (Followers: 3)
Applied Nanoscience     Open Access   (Followers: 7)
Applied Network Science     Open Access   (Followers: 2)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 4)
Applied Physics Research     Open Access   (Followers: 5)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 5)
Arab Journal of Basic and Applied Sciences     Open Access  
Arabian Journal for Science and Engineering     Hybrid Journal   (Followers: 1)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 5)
Archives of Foundry Engineering     Open Access  
Archives of Thermodynamics     Open Access   (Followers: 10)
Arctic     Open Access  
Arid Zone Journal of Engineering, Technology and Environment     Open Access  
ArtefaCToS : Revista de estudios sobre la ciencia y la tecnología     Open Access  
Asian Journal of Applied Science and Engineering     Open Access  
Asian Journal of Applied Sciences     Open Access   (Followers: 2)
Asian Journal of Biotechnology     Open Access   (Followers: 8)
Asian Journal of Control     Hybrid Journal  
Asian Journal of Technology Innovation     Hybrid Journal   (Followers: 5)
Assembly Automation     Hybrid Journal   (Followers: 2)
ATZagenda     Hybrid Journal  
ATZextra worldwide     Hybrid Journal  
AURUM : Mühendislik Sistemleri ve Mimarlık Dergisi = Aurum Journal of Engineering Systems and Architecture     Open Access   (Followers: 1)
Australasian Journal of Engineering Education     Hybrid Journal   (Followers: 3)
Australasian Physical & Engineering Sciences in Medicine     Hybrid Journal   (Followers: 1)
Australian Journal of Multi-Disciplinary Engineering     Hybrid Journal  
Autocracy : Jurnal Otomasi, Kendali, dan Aplikasi Industri     Open Access  
Automotive and Engine Technology     Hybrid Journal  
Automotive Experiences     Open Access  
Automotive Innovation     Hybrid Journal  
Avances en Ciencias e Ingenierías     Open Access  
Avances: Investigación en Ingeniería     Open Access  
Balkan Region Conference on Engineering and Business Education     Open Access   (Followers: 2)
Bangladesh Journal of Scientific and Industrial Research     Open Access  
Basin Research     Hybrid Journal   (Followers: 6)
Batteries     Open Access   (Followers: 8)
Batteries & Supercaps     Hybrid Journal   (Followers: 5)
Bautechnik     Hybrid Journal   (Followers: 1)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 27)
Beni-Suef University Journal of Basic and Applied Sciences     Open Access  
Beyond : Undergraduate Research Journal     Open Access  
Bhakti Persada : Jurnal Aplikasi IPTEKS     Open Access  
Bharatiya Vaigyanik evam Audyogik Anusandhan Patrika (BVAAP)     Open Access  
Bilge International Journal of Science and Technology Research     Open Access   (Followers: 1)
Biointerphases     Open Access   (Followers: 1)
Biomaterials Science     Hybrid Journal   (Followers: 11)
Biomedical Engineering     Hybrid Journal   (Followers: 11)
Biomedical Engineering Letters     Hybrid Journal   (Followers: 3)
Biomedical Engineering: Applications, Basis and Communications     Hybrid Journal   (Followers: 4)
Biomedical Microdevices     Hybrid Journal   (Followers: 8)
Biomedical Science and Engineering     Open Access   (Followers: 4)
Biomicrofluidics     Open Access   (Followers: 7)
Biotechnology Progress     Hybrid Journal   (Followers: 42)
Black Sea Journal of Engineering and Science     Open Access  
Botswana Journal of Technology     Full-text available via subscription   (Followers: 1)
Boundary Value Problems     Open Access  
Bulletin of Canadian Petroleum Geology     Full-text available via subscription   (Followers: 12)
Bulletin of Engineering Geology and the Environment     Hybrid Journal   (Followers: 15)
Cahiers Droit, Sciences & Technologies     Open Access   (Followers: 1)
Calphad     Hybrid Journal  
Canadian Geotechnical Journal     Hybrid Journal   (Followers: 28)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 51)
Carbon Resources Conversion     Open Access   (Followers: 2)
Carpathian Journal of Electronic and Computer Engineering     Open Access  
Case Studies in Thermal Engineering     Open Access   (Followers: 9)
Catalysis Communications     Hybrid Journal   (Followers: 7)
Catalysis Letters     Hybrid Journal   (Followers: 3)
Catalysis Reviews: Science and Engineering     Hybrid Journal   (Followers: 9)
Catalysis Science and Technology     Hybrid Journal   (Followers: 9)
Catalysis Surveys from Asia     Hybrid Journal   (Followers: 4)
Catalysis Today     Hybrid Journal   (Followers: 4)
CEAS Space Journal     Hybrid Journal   (Followers: 6)
Cell Reports Physical Science     Open Access  
Cellular and Molecular Neurobiology     Hybrid Journal   (Followers: 2)
CFD Letters     Open Access   (Followers: 7)
Chaos : An Interdisciplinary Journal of Nonlinear Science     Hybrid Journal   (Followers: 3)
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 1)
Chaos, Solitons & Fractals : X     Open Access   (Followers: 1)
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 2)
Chinese Journal of Engineering     Open Access   (Followers: 1)
Chinese Journal of Population, Resources and Environment     Open Access  
Chinese Science Bulletin     Open Access  
Ciencia e Ingenieria Neogranadina     Open Access  
Ciencia en su PC     Open Access   (Followers: 1)
Ciencia y Tecnología     Open Access  
Ciencias Holguin     Open Access   (Followers: 1)
CienciaUAT     Open Access  
Cientifica     Open Access  
CIRP Annals - Manufacturing Technology     Hybrid Journal   (Followers: 10)
CIRP Journal of Manufacturing Science and Technology     Hybrid Journal   (Followers: 12)
City, Culture and Society     Hybrid Journal   (Followers: 23)
Clay Minerals     Hybrid Journal   (Followers: 7)
Cleaner Engineering and Technology     Open Access   (Followers: 4)
Cleaner Environmental Systems     Open Access   (Followers: 4)
Coastal Engineering     Hybrid Journal   (Followers: 16)
Coastal Engineering Journal     Hybrid Journal   (Followers: 7)
Coastal Engineering Proceedings : Proceedings of the International Conference on Coastal Engineering     Open Access   (Followers: 1)
Coastal Management     Hybrid Journal   (Followers: 29)
Coatings     Open Access   (Followers: 2)
Cogent Engineering     Open Access   (Followers: 1)
Cognitive Computation     Hybrid Journal   (Followers: 2)
Color Research & Application     Hybrid Journal   (Followers: 1)
COMBINATORICA     Hybrid Journal  
Combustion Theory and Modelling     Hybrid Journal   (Followers: 18)
Combustion, Explosion, and Shock Waves     Hybrid Journal   (Followers: 21)
Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering     Open Access  
Communications in Numerical Methods in Engineering     Hybrid Journal   (Followers: 2)
Components, Packaging and Manufacturing Technology, IEEE Transactions on     Hybrid Journal   (Followers: 27)
Composite Interfaces     Hybrid Journal   (Followers: 6)
Composite Structures     Hybrid Journal   (Followers: 244)
Composites Part A : Applied Science and Manufacturing     Hybrid Journal   (Followers: 177)
Composites Part B : Engineering     Hybrid Journal   (Followers: 221)
Composites Part C : Open Access     Open Access   (Followers: 1)
Composites Science and Technology     Hybrid Journal   (Followers: 150)
Comptes Rendus : Mécanique     Open Access   (Followers: 2)
Computation     Open Access   (Followers: 1)
Computational Geosciences     Hybrid Journal   (Followers: 17)
Computational Optimization and Applications     Hybrid Journal   (Followers: 9)
Computer Applications in Engineering Education     Hybrid Journal   (Followers: 6)
Computer Science and Engineering     Open Access   (Followers: 15)
Computers & Geosciences     Hybrid Journal   (Followers: 29)
Computers & Mathematics with Applications     Full-text available via subscription   (Followers: 8)
Computers and Electronics in Agriculture     Hybrid Journal   (Followers: 7)
Computers and Geotechnics     Hybrid Journal   (Followers: 11)
Computing and Visualization in Science     Hybrid Journal   (Followers: 6)
Computing in Science & Engineering     Full-text available via subscription   (Followers: 31)
Conciencia Tecnologica     Open Access  
Continuum Mechanics and Thermodynamics     Hybrid Journal   (Followers: 8)
Control Engineering Practice     Hybrid Journal   (Followers: 46)

        1 2 3 4 5 6 7 8 | Last

Similar Journals
Journal Cover
Biomedical Engineering Letters
Journal Prestige (SJR): 0.332
Citation Impact (citeScore): 1
Number of Followers: 3  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 2093-9868 - ISSN (Online) 2093-985X
Published by Springer-Verlag Homepage  [2469 journals]
  • A time-based single transmission-line readout with position multiplexing

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      Abstract: We developed a time-based single-transmission-line readout method for time-of-flight positron emission tomography (PET) detectors. The 2D position of a silicon photomultiplier (SiPM) array was encoded in the upper and lower widths of a specially prepared L-shaped tag pulse followed by the original scintillation signal. A PET detector setup was configured using a 4 × 4 array of LSO crystals optically coupled one-to-one to a 4 × 4 SiPM array. Two pulse width modulator circuits were employed per SiPM anode signal channel and a total of 32 width-modulated digital pulses were summed and merged with a delayed common-cathode signal. The final output was analyzed using timestamps crossing two-level threshold voltages. All 16 crystals were clearly separated on a positioning map. The average energy and coincidence time resolutions were 15.0 ± 1.1% and 288.7 ± 29.3 ps after proper correction process, respectively. A 3D position decoding capability was also shown by the remarkable discrimination performance in a phoswich PET detector setup (LSO and LGSO), resulting from well-preserved scintillation signals. The proposed method enables a time-based single-channel readout with 3D gamma ray interaction position decoding capability without compromising on detector performance. This method provides gamma ray energy and arrival time information as well as 2D and depthwise interaction positions of the phoswich detectors through one channel readout. Thus, channels can be reduced by at least 4–5 times compared to typically employed charge-sharing-based position multiplexing method; this significantly reduces the burden of data acquisition on the PET system.
      PubDate: 2022-01-17
       
  • Practical review on photoacoustic computed tomography using curved
           ultrasound array transducer

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      Abstract: Photoacoustic computed tomography (PACT) has become a promising imaging modality from laboratory to clinical research. Of many components of PACT system, the ultrasound (US) array transducer is an essential device to simultaneously receive photoacoustic (PA) signals from several directions in a parallel manner. Many research groups and companies have developed various types of US array transducers while accounting the properties of the PA waves to achieve better image quality, deeper imaging depth, faster imaging speed, and a wider field of view. In this review, we present the implementation and application of the state-of-the-art PACT systems using several types of curved US arrays: arc-shaped, ring-shaped, and hemispherical array transducers. Furthermore, we discuss the current limitations of PACT and also potential future directions for enhancing them.
      PubDate: 2021-12-19
       
  • Biomedical Engineering Letters indexed in Science Citation Index Expanded
           (SCIE)

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      PubDate: 2021-12-15
       
  • Developing a control framework for self-adjusting prosthetic sockets
           incorporating tissue injury risk estimation and generalized predictive
           control

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      Abstract: To perform activities of daily living (ADL), people with lower limb amputation depend on the prosthetic socket for stability and proprioceptive feedback. Poorly fitting sockets can cause discomfort, pain, limb tissue injuries, limited device usage, and potential rejection. Semi-passively controlled adjustable socket technologies exist, but these depend upon the user’s perception to determine safe interfacial pressure levels. This paper presents a framework for automatic control of an adjustable transtibial prosthetic socket that enables active adaptation of residuum-socket interfacial loading through localized actuators, based on soft tissue injury risk estimation. Using finite element analysis, local interfacial pressure vs. compressive tissue strain relationships were estimated for three discrete anatomical actuator locations, for tissue injury risk assessment within a control structure. Generalized Predictive Control of multiple actuators was implemented to maintain interfacial pressure within estimated safe and functional limits. Controller simulation predicted satisfactory dynamic performance in several scenarios. Actuation rates of 0.06–1.51 kPa/s with 0.67% maximum overshoot, and 0.75–1.58 kPa/s were estimated for continuous walking, and for a demonstrative loading sequence of ADL, respectively. The developed platform could be useful for extending recent efforts in adjustable lower limb prosthetic socket design, particularly for individuals with residuum sensory impairment.
      PubDate: 2021-12-02
       
  • A digital cardiac disease biomarker from a generative progressive cardiac
           cine-MRI representation

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      Abstract: Cardiac cine-MRI is one of the most important diagnostic tools used to assess the morphology and physiology of the heart during the cardiac cycle. Nonetheless, the analysis on cardiac cine-MRI is poorly exploited and remains highly dependent on the observer's expertise. This work introduces an imaging cardiac disease representation, coded as an embedding vector, that fully exploits hidden mapping between the latent space and a generated cine-MRI data distribution. The resultant representation is progressively learned and conditioned by a set of cardiac conditions. A generative cardiac descriptor is achieved from a progressive generative-adversarial network trained to produce MRI synthetic images, conditioned to several heart conditions. The generator model is then used to recover a digital biomarker, coded as an embedding vector, following a backpropagation scheme. Then, an UMAP strategy is applied to build a topological low dimensional embedding space that discriminates among cardiac pathologies. Evaluation of the approach is carried out by using an embedded representation as a potential disease descriptor in 2296 pathological cine-MRI slices. The proposed strategy yields an average accuracy of 0.8 to discriminate among heart conditions. Furthermore, the low dimensional space shows a remarkable grouping of cardiac classes that may suggest its potential use as a tool to support diagnosis. The learned progressive and generative representation, from cine-MRI slices, allows retrieves and coded complex descriptors that results useful to discriminate among heart conditions. The cardiac disease representation expressed as a hidden embedding vector could potentially be used to support cardiac analysis on cine-MRI sequences.
      PubDate: 2021-11-27
       
  • Photoacoustic imaging aided with deep learning: a review

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      Abstract: Photoacoustic imaging (PAI) is an emerging hybrid imaging modality integrating the benefits of both optical and ultrasound imaging. Although PAI exhibits superior imaging capabilities, its translation into clinics is still hindered by various limitations. In recent years, deeplearning (DL), a new paradigm of machine learning, is gaining a lot of attention due to its ability to improve medical images. Likewise, DL is also widely being used in PAI to overcome some of the limitations of PAI. In this review, we provide a comprehensive overview on the various DL techniques employed in PAI along with its promising advantages.
      PubDate: 2021-11-23
       
  • Adaptive fuzzy deformable fusion and optimized CNN with ensemble
           classification for automated brain tumor diagnosis

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      Abstract: Automatic classification of brain tumor plays a vital role to speed up the treatment procedure, plan and boost the survival rate of patients. Nowadays, Magnetic Resonance Imaging (MRI) is employed for determining brain tumor. However, manual identification of brain tumor is purely based on the sensitivity and experience of medical professionals. Thus, more research works towards brain tumor classification have been implemented for minimizing the human factor. Different imaging approaches are employed for detecting brain tumors. Though, MRI is mainly employed owing to the better quality of images due to the non ionizing radiation of images. One of the major categories of machine learning is called deep learning, which shows an outstanding performance, mainly on solving the segmentation and classification issues. The aim of this paper to introduce a new brain tumor classification model based on the intelligent segmentation and classification approaches. The main phases of the proposed model are (a) Data collection, (b) Pre-processing, (c) Tumor segmentation, and (d) Tumor Classification. Initially, the datasets related to the brain tumor are gathered from several benchmark sources and subjected to the pre-processing step. Here, it is performed by the median filtering and contrast enhancement techniques. The first contribution of this paper is the development of an enhanced segmentation approach termed as Adaptive Fuzzy Deformable Fusion (AFDF)-based Segmentation, which merges the two concepts of Fuzzy C-Means Clustering (FCM) and snake deformable approach. Here, the significant parameters of the AFDF are optimized by the improved Deer Hunting Optimization Algorithm (DHOA) termed Adaptive Coefficient Vector-based DHOA (ACV-DHOA). The classification of images is performed by the Optimized Convolutional Neural Network with Ensemble Classification (OCNN-EC) after segmenting the tumor. In the proposed deep learning classification, the number of convolutional layers and hidden neurons of CNN is optimized by the ACV-DHOA, and the fully connected layer is replaced by the ensemble classifier with Deep Neural Network (DNN), autoencoder, and Support Vector Machine (SVM). The classifier which is getting high rank is considered as the optimal one. The experimentation results are performed on the standard database that shows the high classification accuracy of the developed model by evaluating with other conventional methods.
      PubDate: 2021-11-07
       
  • Bias-generating factors in biofluid amyloid-β measurements for
           Alzheimer’s disease diagnosis

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      Abstract: Alzheimer’s disease (AD) is the most prevalent cause of dementia worldwide, yet the dearth of readily accessible diagnostic biomarkers is a substantial hindrance towards progressing to effective preventive and therapeutic approaches. Due to a long delay between cerebral amyloid-β (Aβ) accumulation and the onset of cognitive impairments, biomarkers that reflect Aβ pathology and enable routine screening for disease progression are of urgent need for application in the clinical diagnosis of AD. According to accumulating evidences, cerebrospinal fluid (CSF) and plasma offer windows to the brain as they allow monitoring of biochemical changes in the brain. Considering the high availability and accuracy in depicting Aβ deposition in the brain, Aβ levels in CSF and plasma are regarded as promising fluid biomarkers for the diagnosis of AD patients at an early stage. However, clinical data with intra- and interindividual variations in the concentrations of CSF and plasma Aβ implicate the need to reevaluate current Aβ detection methods and establish a standardized operating procedure. Therefore, this review introduces three bias-generating factors in biofluid Aβ measurement that may hamper the accurate Aβ quantification and how such complications can be overcome for the widespread implementation of fluid Aβ detection in clinical practice.
      PubDate: 2021-11-01
      DOI: 10.1007/s13534-021-00201-z
       
  • Micro/nanotechnology-inspired rapid diagnosis of respiratory infectious
           diseases

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      Abstract: Humans have suffered from a variety of infectious diseases since a long time ago, and now a new infectious disease called COVID-19 is prevalent worldwide. The ongoing COVID-19 pandemic has led to research of the effective methods of diagnosing respiratory infectious diseases, which are important to reduce infection rate and help the spread of diseases be controlled. The onset of COVID-19 has led to the further development of existing diagnostic methods such as polymerase chain reaction, reverse transcription polymerase chain reaction, and loop-mediated isothermal amplification. Furthermore, this has contributed to the further development of micro/nanotechnology-based diagnostic methods, which have advantages of high-throughput testing, effectiveness in terms of cost and space, and portability compared to conventional diagnosis methods. Micro/nanotechnology-based diagnostic methods can be largely classified into (1) nanomaterials-based, (2) micromaterials-based, and (3) micro/nanodevice-based. This review paper describes how micro/nanotechnologies have been exploited to diagnose respiratory infectious diseases in each section. The research and development of micro/nanotechnology-based diagnostics should be further explored and advanced as new infectious diseases continue to emerge. Only a handful of micro/nanotechnology-based diagnostic methods has been commercialized so far and there still are opportunities to explore.
      PubDate: 2021-11-01
      DOI: 10.1007/s13534-021-00206-8
       
  • Technological advances in electrochemical biosensors for the detection of
           disease biomarkers

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      Abstract: With an increasing focus on health in contemporary society, interest in the diagnosis, treatment, and prevention of diseases has grown rapidly. Accordingly, the demand for biosensors for the early diagnosis of disease is increasing. However, the measurement range of existing electrochemical sensors is relatively high, which is not suitable for early disease diagnosis, requiring the detection of small amounts of biocomponents. Various attempts have been made to overcome this and amplify the signal, including binding with various labeling molecules, such as DNA, enzymes, nanoparticles, and carbon materials. Efforts are also being made to increase the sensitivity of electrochemical sensors, and the combination of nanomaterials, materials, and biotechnology offers the potential to increase sensitivity in a variety of ways. Recent studies suggest that electrochemical sensors can be a powerful tool in providing comprehensive insights into the targeting and detection of disease-associated biomarkers. Significant advances in nanomaterial and biomolecule approaches for improved sensitivity have resulted in the development of electrochemical biosensors capable of detecting multiple biomarkers in real time in clinically relevant samples. In this review, we have discussed the recent studies on electrochemical sensors for detection of diseases such as diabetes, degenerative diseases, and cancer. Further, we have highlighted new technologies to improve sensitivity using various materials, including DNA, enzymes, nanoparticles, and carbon materials.
      PubDate: 2021-11-01
      DOI: 10.1007/s13534-021-00204-w
       
  • Recent advances in magnetic nanoparticle-based microfluidic devices for
           the pretreatment of pathogenic bacteria

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      Abstract: Rapid and sensitive detection of pathogenic bacteria in various samples, including food and drinking water, is important to prevent bacterial diseases. Most bacterial solutions contain only a small number of bacteria in complex matrices with impurities; hence, pretreatment is necessary to separate and concentrate target bacteria before sensing. Among various pretreatment methods, iron oxide magnetic nanoparticle (MNP)-based pretreatment has drawn attention owing to the unique properties of MNP, such as high magnetic susceptibility, superparamagnetism, and biocompatibility. After target bacteria are captured by recognition molecule-functionalized MNPs, bacteria–MNP complexes can be easily separated and enriched by applying an external magnetic field. Various devices, such as optical, electrochemical, and magnetoresistance sensors, can be used to detect target bacteria, and their detection principles have been discussed in numerous review papers. Herein, we focus on recent research advances and challenges in magnetic pretreatment of pathogenic bacteria using microfluidic devices, which offer the advantages of process automation and miniaturization.
      PubDate: 2021-11-01
      DOI: 10.1007/s13534-021-00202-y
       
  • Cellular and biomolecular detection based on suspended microchannel
           resonators

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      Abstract: Suspended microchannel resonators (SMRs) have been developed to measure the buoyant mass of single micro-/nanoparticles and cells suspended in a liquid. They have significantly improved the mass resolution with the aid of vacuum packaging and also increased measurement throughput by fast resonance frequency tracking while target objects travel through the microchannel without stopping or even slowing down. Since their invention, various biological applications have been enabled, including simultaneous measurements of cell growth and cell cycle progression, and measurements of disease associated physicochemical change, to name a few. Extension and advancement towards other promising applications with SMRs are continuously ongoing by adding multiple functionalities or incorporating other complementary analytical metrologies. In this paper, we will thoroughly review the development history, basic and advanced operations, and key applications of SMRs to introduce them to researchers working in biological and biomedical sciences who mostly rely on classical and conventional methodologies. We will also provide future perspectives and projections for SMR technologies.
      PubDate: 2021-11-01
      DOI: 10.1007/s13534-021-00207-7
       
  • Assessment of structural, biological and drug release properties of
           electro-sprayed poly lactic acid-dexamethasone coating for biomedical
           applications

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      Abstract: The efficacy of an implant is highly depends on its coating characteristics mainly determined by polymer properties and coating technique. Electro-spraying is an inexpensive and versatile coating technique with various advantages for biomedical application. In this study, the efficacy of electro-sprayed (ES) poly lactic acid (PLA)-dexamethasone (DEX) coatings for medical implants was evaluated and compared with spin-coated samples as control. Structural properties of coatings were investigated using X-ray diffraction (XRD) and differential scanning calorimetry (DSC). Confocal and scanning electron microscopy (SEM), contact angle measurement and nanoindentation tests were used to study surface properties. Coating degradation rate and drug release profile were studied for 40 days. Cell viability experiments were also performed on human endothelial (HUVEC) and smooth muscle cells (HUASMC) using MTT assay and SEM. XRD and DSC analysis showed electro-spraying significantly reduce PLA and DEX crystallinity. Surface studies showed ES coatings has significantly higher hydrophobicity and roughness with microbead-nanofiber morphology vs. micro-nanoporous structure of spin-coated samples. Initial burst release of DEX was 22% and 10% after 6 h and total release was 71% and 46% after 40 days for ES and spin-coated samples, respectively. HUVEC viability of ES samples was higher than spin-coated ones after 1 and 4 days. However, dexamethasone release profile reduced HUASMC proliferation in ES PLA-DEX samples in comparison to spin-coated after 1 and 3 days. In conclusion, in vitro results showed potential of ES PLA-DEX as a biocompatible and efficient anti-inflammatory coating with suitable drug release profile for future applications such as coronary drug eluting stents.
      PubDate: 2021-11-01
      DOI: 10.1007/s13534-021-00205-9
       
  • Stabilizing breathing pattern using local mechanical vibrations:
           comparison of deterministic and stochastic stimulations in rodent models
           of apnea of prematurity

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      Abstract: Mechanical stimulation has been shown to reduce apnea of prematurity (AOP), a major concern in preterm infants. Previous work suggested that the underlying mechanism is stochastic resonance, amplification of a subthreshold signal by stochastic stimulation. We hypothesized that the mechanism behind the reduction of apnea length may not be a solely stochastic phenomenon, and suggest that a purely deterministic, non-random mechanical stimulation could be equally as effective. Mice and rats were anesthetized, tracheostomized, and mechanically ventilated to halt spontaneous breathing. Two miniature motors controlled by a microcontroller were attached around the abdomen. Ventilation was paused, stimulations were applied, and the time to the rodent’s first spontaneous breath (T) was measured. Six spectrally different signals were compared to one another and the no-stimulation control in mice. The most successful deterministic stimulation (D) at reducing apnea was then compared to a pseudo-random noise (PRN) signal of comparable amplitude and frequency. CO2%, CO2 stabilization time (Ts), O2 saturation (SpO2%), and T were also measured. D significantly reduced T compared to no stimulation for medium and high amplitudes. PRN also reduced T, without  a difference between D and PRN. Furthermore, both stimulations significantly reduced Ts with no significant differences between the respective stimulations. However, there was no effect of D or PRN on SpO2%. The lack of differences between D and PRN led to an additional series of experiment comparing the same D to a band-limited white noise (WN) signal in young rats. Both D and WN were shown to significantly reduce T, with D showing statistical superiority in reduction of apnea. We further speculate that both deterministic and stochastic mechanical stimulations induce some form of mechanotransduction which is responsible for their efficacy, and our findings suggest that mechanical stimulation may be effective in treating AOP.
      PubDate: 2021-11-01
      DOI: 10.1007/s13534-021-00203-x
       
  • Nanostructures in non-invasive prenatal genetic screening

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      Abstract: Prenatal screening is an important issue during pregnancy to ensure fetal and maternal health, as well as preventing the birth of a defective fetus and further problems such as extra costs for the family and society. The methods for the screening have progressed to non-invasive approaches over the recent years. Limitations of common standard screening tests, including invasive sampling, high risk of abortion and a big delay in result preparation have led to the introduction of new rapid and non-invasive approaches for screening. Non-invasive prenatal screening includes a wide range of procedures, including fetal cell-free DNA analysis, proteome, RNAs and other fetal biomarkers in maternal serum. These biomarkers require less invasive sampling than usual methods such as chorionic villus sampling, amniocentesis or cordocentesis. Advanced strategies including the development of nanobiosensors and the use of special nanoparticles have provided optimization and development of NIPS tests, which leads to more accurate, specific and sensitive screening tests, rapid and more reliable results and low cost, as well. This review discusses the specifications and limitations of current non-invasive prenatal screening tests and introduces a novel collection of detection methods reported studies on nanoparticles’ aided detection. It can open a new prospect for further studies and effective investigations in prenatal screening field.
      PubDate: 2021-10-11
      DOI: 10.1007/s13534-021-00208-6
       
  • Challenges in delivery systems for CRISPR-based genome editing and
           opportunities of nanomedicine

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      Abstract: The CRISPR-based genome editing technology has opened extremely useful strategies in biological research and clinical therapeutics, thus attracting great attention with tremendous progress in the past decade. Despite its robust potential in personalized and precision medicine, the CRISPR-based gene editing has been limited by inefficient in vivo delivery to the target cells and by safety concerns of viral vectors for clinical setting. In this review, recent advances in tailored nanoparticles as a means of non-viral delivery vector for CRISPR/Cas systems are thoroughly discussed. Unique characteristics of the nanoparticles including controllable size, surface tunability, and low immune response lead considerable potential of CRISPR-based gene editing as a translational medicine. We will present an overall view on essential elements in CRISPR/Cas systems and the nanoparticle-based delivery carriers including advantages and challenges. Perspectives to advance the current limitations are also discussed toward bench-to-bedside translation in engineering aspects.
      PubDate: 2021-08-01
      DOI: 10.1007/s13534-021-00199-4
       
  • Recent advances in hybrid system of porous silicon nanoparticles and
           biocompatible polymers for biomedical applications

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      Abstract: Hybrid systems of nanoparticles and polymers have emerged as a new material in the biomedical field. To date, various kinds of hybrid systems have been introduced and applied to drug delivery, regenerative medicine, therapeutics, disease diagnosis, and medical implantation. Among them, the hybridization of nanostructured porous silicon nanoparticles (pSiNPs) and biocompatible polymers has been highlighted due to its unique biological and physicochemical properties. This review focuses on the recent advances in the hybrid systems of pSiNPs and biocompatible polymers from an engineering aspect and its biomedical applications. Representative hybrid formulations, (i) Polymer-coated pSiNPs, (ii) pSiNPs-embedded polymeric nanofibers, are outlined along with their preparation methods, biomedical applications, and future perspectives. We believe this review provides insight into a new hybrid system of pSiNPs and biocompatible polymers as a promising nano-platform for further biomedical applications. Graphic abstract Recently developed and representative hybrid systems of porous silicon nanoparticles and biocompatible polymers and their biomedical applications are introduced.
      PubDate: 2021-08-01
      DOI: 10.1007/s13534-021-00194-9
       
  • Hidden Markov model-based heartbeat detector using electrocardiogram and
           arterial pressure signals

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      Abstract: The automatic detection of a heartbeat is commonly performed by detecting the QRS complex in the electrocardiogram (ECG), however, various noise sources and missing data can jeopardize the reliability of the ECG. Therefore, there is a growing interest in combining the information from many physiological signals to accurately detect heartbeats. To this end, hidden Markov models (HMMs) are used in this work to jointly exploit the information from ECG, arterial blood pressure (ABP) and pulmonary arterial pressure (PAP) signals in order to conceive a heartbeat detector. After preprocessing the physiological signals, a sliding window is used to extract an observation sequence to be passed through two HMMs (previously trained on a training dataset) in order to obtain the log-likelihoods of observation and signals a detection if the difference of log-likelihoods exceeds an adaptive threshold. Several HMM-based heartbeat detectors were conceived to exploit the information from the ECG, ABP and PAP signals from the MIT-BIH Arrhythmia, PhysioNet Computing in Cardiology Challenge 2014, and MGH/MF Waveform databases. A grid search methodology was used to optimize the duration of the observation sequence and a multiplicative factor to form the adaptive threshold. Using the optimal parameters found on a training database through 10-fold cross-validation, sensitivity and positive predictivity above 99% were obtained on the MIT-BIH Arrhythmia and PhysioNet Computing in Cardiology Challenge 2014 databases, while they are above 95% in the MGH/MF waveform database using ECG and ABP signals. Our detector approach showed detection performances comparable with the literature in the three databases.
      PubDate: 2021-08-01
      DOI: 10.1007/s13534-021-00192-x
       
  • Engineered immune cells with nanomaterials to improve adoptive cell
           therapy

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      Abstract: Cell-based cancer immunotherapy is mainly performed to re-stimulate or boost the anti-tumor immunity by leveraging the anti-tumoral functions of infused cells. Although conventional adoptive cell therapy with T cells and DC vaccines had potentiated the use of ex vivo engineered cells for cancer immunotherapy, these approaches had a low success rate and some off-target side effects. Recent developments on this intervention are adopting nanoengineering to overcome limitations imposed by the environment the therapeutic cells would be in and the natural characteristics of the cells; thus, enhancing the efficacy of therapies. For this purpose, T cells, NK cells, DCs, and macrophages are engineered to either maintain anti-tumoral phenotypes, target tumor efficiently, or improve the innate functionalities and viability.
      PubDate: 2021-08-01
      DOI: 10.1007/s13534-021-00197-6
       
  • CNN based classification of motor imaginary using variational mode
           decomposed EEG-spectrum image

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      Abstract: A novel approach of preprocessing EEG signals by generating spectrum image for effective Convolutional Neural Network (CNN) based classification for Motor Imaginary (MI) recognition is proposed. The approach involves extracting the Variational Mode Decomposition (VMD) modes of EEG signals, from which the Short Time Fourier Transform (STFT) of all the modes are arranged to form EEG spectrum images. The EEG spectrum images generated are provided as input image to CNN. The two generic CNN architectures for MI classification (EEGNet and DeepConvNet) and the architectures for pattern recognition (AlexNet and LeNet) are used in this study. Among the four architectures, EEGNet provides average accuracies of 91.37%, 94.41%, 85.67% and 90.21% for the four datasets used to validate the proposed approach. Consistently better results in comparison with results in recent literature demonstrate that the EEG spectrum image generation using VMD-STFT is a promising method for the time frequency analysis of EEG signals.
      PubDate: 2021-08-01
      DOI: 10.1007/s13534-021-00190-z
       
 
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