bluuebunny/crossref_metadata_2025 huggingface dataset:
Cyclodextrins as Multi-Functional Ingredients in Dentistry
Authors: Braga Susana Santos
Published: August 2023

Cyclodextrins are present in a variety of oral hygiene compositions. The present work describes the role of cyclodextrins in several toothpastes and mouthwashes that are already available in the market, as well as their prospective use in other applications as investigated in studies in the literature. Moreover, cyclodextrins are under study for the development of materials used in various techniques of dental repair, such as fillings, cements and binders therein. Their role in each of the innovative materials is presented. Finally, the prospect of the use of cyclodextrin-based delivery systems for the oral cavity is introduced, with a focus on new cyclodextrin molecules with dual action as bone-targeting agents and osteogenic drugs, and on new cross-linked cyclodextrin particles with a high drug loading and sustained drug delivery profile for the treatment of diseases that require prolonged action, such as periodontitis. In conclusion, cyclodextrins are herein demonstrated to act as versatile and multi-action ingredients with a broad range of applications in dentistry.
Antimicrobial Activity of Selenium Nanoparticles (SeNPs) against Potentially Pathogenic Oral Microorganisms: A Scoping Review
Authors: Sans-Serramitjana Eulàlia , Obreque Macarena , Muñoz Fernanda , Zaror Carlos , Mora María de La Luz , Viñas Miguel , Betancourt Pablo
Published: August 2023

Biofilms are responsible for the most prevalent oral infections such as caries, periodontal disease, and pulp and periapical lesions, which affect the quality of life of people. Antibiotics have been widely used to treat these conditions as therapeutic and prophylactic compounds. However, due to the emergence of microbial resistance to antibiotics, there is an urgent need to develop and evaluate new antimicrobial agents. This scoping review offers an extensive and detailed synthesis of the potential role of selenium nanoparticles (SeNPs) in combating oral pathogens responsible for causing infectious diseases. A systematic search was conducted up until May 2022, encompassing the MEDLINE, Embase, Scopus, and Lilacs databases. We included studies focused on evaluating the antimicrobial efficacy of SeNPs on planktonic and biofilm forms and their side effects in in vitro studies. The selection process and data extraction were carried out by two researchers independently. A qualitative synthesis of the results was performed. A total of twenty-two articles were considered eligible for this scoping review. Most of the studies reported relevant antimicrobial efficacy against C. albicans, S. mutans, E. faecalis, and P. gingivalis, as well as effective antioxidant activity and limited toxicity. Further research is mandatory to critically assess the effectiveness of this alternative treatment in ex vivo and in vivo settings, with detailed information about SeNPs concentrations employed, their physicochemical properties, and the experimental conditions to provide enough evidence to address the construction and development of well-designed and safe protocols.
Modulation of Human Dendritic Cell Functions by Phosphodiesterase-4 Inhibitors: Potential Relevance for the Treatment of Respiratory Diseases
Authors: Nguyen Hoang Oanh , Tiberio Laura , Facchinetti Fabrizio , Ripari Giulia , Violi Valentina , Villetti Gino , Salvi Valentina , Bosisio Daniela
Published: August 2023

Inhibitors of phosphodiesterase-4 (PDE4) are small-molecule drugs that, by increasing the intracellular levels of cAMP in immune cells, elicit a broad spectrum of anti-inflammatory effects. As such, PDE4 inhibitors are actively studied as therapeutic options in a variety of human diseases characterized by an underlying inflammatory pathogenesis. Dendritic cells (DCs) are checkpoints of the inflammatory and immune responses, being responsible for both activation and dampening depending on their activation status. This review shows evidence that PDE4 inhibitors modulate inflammatory DC activation by decreasing the secretion of inflammatory and Th1/Th17-polarizing cytokines, although preserving the expression of costimulatory molecules and the CD4+ T cell-activating potential. In addition, DCs activated in the presence of PDE4 inhibitors induce a preferential Th2 skewing of effector T cells, retain the secretion of Th2-attracting chemokines and increase the production of T cell regulatory mediators, such as IDO1, TSP-1, VEGF-A and Amphiregulin. Finally, PDE4 inhibitors selectively induce the expression of the surface molecule CD141/Thrombomodulin/BDCA-3. The result of such fine-tuning is immunomodulatory DCs that are distinct from those induced by classical anti-inflammatory drugs, such as corticosteroids. The possible implications for the treatment of respiratory disorders (such as COPD, asthma and COVID-19) by PDE4 inhibitors will be discussed.
A Drug-Eluting Injectable NanoGel for Localized Delivery of Anticancer Drugs to Solid Tumors
Authors: Godau Brent , Samimi Sadaf , Seyfoori Amir , Samiei Ehsan , Khani Tahereh , Naserzadeh Parvaneh , Najafabadi Alireza Hassani , Lesha Emal , Majidzadeh-A Keivan , Ashtari Behnaz , Charest Gabriel , Morin Christophe , Fortin David , Akbari Mohsen
Published: August 2023

Systemically administered chemotherapy reduces the efficiency of the anticancer agent at the target tumor tissue and results in distributed drug to non-target organs, inducing negative side effects commonly associated with chemotherapy and necessitating repeated administration. Injectable hydrogels present themselves as a potential platform for non-invasive local delivery vehicles that can serve as a slow-releasing drug depot that fills tumor vasculature, tissue, or resection cavities. Herein, we have systematically formulated and tested an injectable shear-thinning hydrogel (STH) with a highly manipulable release profile for delivering doxorubicin, a common chemotherapeutic. By detailed characterization of the STH physical properties and degradation and release dynamics, we selected top candidates for testing in cancer models of increasing biomimicry. Two-dimensional cell culture, tumor-on-a-chip, and small animal models were used to demonstrate the high anticancer potential and reduced systemic toxicity of the STH that exhibits long-term (up to 80 days) doxorubicin release profiles for treatment of breast cancer and glioblastoma. The drug-loaded STH injected into tumor tissue was shown to increase overall survival in breast tumor- and glioblastoma-bearing animal models by 50% for 22 days and 25% for 52 days, respectively, showing high potential for localized, less frequent treatment of oncologic disease with reduced dosage requirements.
Optimization and Production of Aceclofenac-Loaded Microfiber Solid Dispersion by Centrifugal Spinning
Authors: Bitay Enikő , Gergely Attila Levente , Szabó Zoltán-István
Published: August 2023

Aceclofenac-loaded polyvinylpyrrolidone fiber-based amorphous solid dispersion was produced successfully by centrifugal spinning. The solution concentration and rotational speed were optimized to produce the fiber-based drug carrier system, with a determined production rate of 12.7 g/h dry solid fibers. The obtained fibers were bead-free and smooth-surfaced with an average diameter of 7.5 ± 2.5 μm. Gas chromatographic determinations revealed that ethanol, as a residual solvent, was well below the regulatory limit of 0.5%. Differential scanning calorimetric investigation and infrared spectroscopic measurements were used to track the physicochemical changes that intervene during fiber formation in the solid state. The results revealed that the rapid evaporation of the solvent was accompanied by a probable crystalline to amorphous transition of the active substance during centrifugal spinning. In vitro dissolution studies revealed an instantaneous disintegration of the fibrous structure and a rapid release of the active substance, with the microfibrous webs greatly outperforming the crystalline active substance, especially in the early time-points. This implies that centrifugal spinning offers a viable scale-up production process to prepare drug-loaded fiber-based solid dispersions.
Mesoporous Composite Bioactive Compound Delivery System for Wound-Healing Processes
Authors: Purcăreanu Bogdan , Ene Manuela Diana , Moroșan Alina , Mihaiescu Dan Eduard , Florea Mihai Alexandru , Ghica Adelina , Nita Roxana Andreea , Drumea Veronica , Grigoroscuta Mihai Alexandru , Kuncser Andrei , Badica Petre , Olariu Laura
Published: August 2023

Currently, the treatment of wounds is still a challenge for healthcare professionals due to high complication incidences and social impacts, and the development of biocompatible and efficient medicines remains a goal. In this regard, mesoporous materials loaded with bioactive compounds from natural extracts have a high potential for wound treatment due to their nontoxicity, high loading capacity and slow drug release. MCM-41-type mesoporous material was synthesized by using sodium trisilicate as a silica source at room temperature and normal pressure. The synthesized mesoporous silica was characterized by using Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), N2 absorption–desorption (BET), Dynamic Light Scattering (DLS) and Fourier transform infrared spectroscopy (FT-IR), revealing a high surface area (BET, 1244 m2/g); pore diameter of approx. 2 nm; and a homogenous, ordered and hexagonal geometry (TEM images). Qualitative monitoring of the desorption degree of the Salvia officinalis (SO) extract, rich in ursolic acid and oleanolic acid, and Calendula officinalis (CO) extract, rich in polyphenols and flavones, was performed via the continuous recording of the UV-VIS spectra at predetermined intervals. The active ingredients in the new composite MCM-41/sage and marigold (MCM-41/SO&CO) were quantified by using HPLC-DAD and LC-MS-MS techniques. The evaluation of the biological composites’ activity on the wound site was performed on two cell lines, HS27 and HaCaT, naturally involved in tissue-regeneration processes. The experimental results revealed the ability to stimulate collagen biosynthesis, the enzymatic activity of the main metalloproteinases (MMP-2 and MMP-9) involved in tissue remodeling processes and the migration rate in the wound site, thus providing insights into the re-epithelializing properties of mesoporous composites.
Fruit and Vegetable Production
Authors: Abbey Lord , MacDonald Mason , Ampofo Josephine
Published: August 2023

Fruits and vegetables are generally known to contain important vitamins, fiber, essential minerals, and vital bioactive compounds that possess health benefits such as anti-inflammatory, antimicrobial, antioxidant, and anticancer properties [...]
Antimicrobial, Cytotoxic, and Anti-Inflammatory Activities of Tigridia vanhouttei Extracts
Authors: Mejía-Méndez Jorge L. , Lorenzo-Leal Ana C. , Bach Horacio , López-Mena Edgar R. , Navarro-López Diego E. , Hernández Luis R. , Juárez Zaida N. , Sánchez-Arreola Eugenio
Published: August 2023

In this work, bulb extracts of Tigridia vanhouttei were obtained by maceration with solvents of increasing polarity. The extracts were evaluated against a panel of pathogenic bacterial and fungal strains using the minimal inhibitory concentration (MIC) assay. The cytotoxicity of the extracts was tested against two cell lines (THP-1 and A549) using the MTT assay. The anti-inflammatory activity of the extracts was evaluated in THP-1 cells by measuring the secretion of pro-inflammatory (IL-6 and TNF-α) and anti-inflammatory (IL-10) cytokines by ELISA. The chemical composition of the extracts was recorded by FTIR spectroscopy, and their chemical profiles were evaluated using GC-MS. The results revealed that only hexane extract inhibited the growth of the clinical isolate of Pseudomonas aeruginosa at 200 μg/mL. Against THP-1 cells, hexane and chloroform extracts were moderately cytotoxic, as they exhibited LC50 values of 90.16, and 46.42 μg/mL, respectively. Treatment with methanol extract was weakly cytotoxic at LC50 443.12 μg/mL against the same cell line. Against the A549 cell line, hexane, chloroform, and methanol extracts were weakly cytotoxic because of their LC50 values: 294.77, 1472.37, and 843.12 μg/mL. The FTIR analysis suggested the presence of natural products were confirmed by carboxylic acids, ketones, hydroxyl groups, or esters. The GC-MS profile of extracts revealed the presence of phytosterols, tetracyclic triterpenes, multiple fatty acids, and sugars. This report confirms the antimicrobial, cytotoxic, and anti-inflammatory activities of T. vanhouttei.
Development of Indicator Film Based on Cassava Starch–Chitosan Incorporated with Red Dragon Fruit Peel Anthocyanins–Gambier Catechins to Detect Banana Ripeness
Authors: Santoso Valentia Rossely , Pramitasari Rianita , Anugrah Daru Seto Bagus
Published: August 2023

Banana ripeness is generally determined based on physical attributes, such as skin color; however, it is considered subjective because it depends on individual factors and lighting conditions. In addition, improper handling can cause mechanical damage to the fruit. Intelligent packaging in the form of indicator film incorporated with anthocyanins from red dragon fruit peel has been applied for shrimp freshness detection; however, this film has low color stability during storage, necessitating the addition of gambier catechins as a co-pigment to increase anthocyanin stability. Nevertheless, the characteristics of films that contain gambier catechins and their applications to bananas have not been studied yet; therefore, this study aims to develop and characterize indicator films that were incorporated with red dragon fruit peel anthocyanins and gambier catechins to detect banana ripeness. In this study, the indicator films were made via solvent casting. The films were characterized for their structural, mechanical, and physicochemical properties, and then applied to banana packaging. The results show that the film incorporated with anthocyanins and catechins in a ratio of 1:40 (w/w) resulted in better color stability, mechanical properties, light and water vapor barrier ability, and antioxidant activity. The application of the indicator films to banana packaging resulted in a change in color on the third day of storage. It can be concluded that these films could potentially be used as an indicator to monitor banana ripeness.
Monodisperse Fluorescent Polystyrene Microspheres for Staphylococcus aureus Aerosol Simulation
Authors: Lu Siyu , Li Fan , Liu Bo , Yang Kun , Tian Feng , Cheng Zhi , Ding Sheng , Hou Kexin
Published: August 2023

Staphylococcus aureus (SA) is one of the most common causes of hospital-acquired infections and foodborne illnesses and is commonly found in nature in air, dust, and water. The spread and transmission of SA aerosols in the air has the potential to cause epidemic transmission among humans and between humans and animals. To effectively provide the timely warning of SA aerosols in the atmosphere, the identification and detection of SA aerosol concentrations are required. Due to their homogeneous physicochemical properties, highly monodisperse submicron polystyrene (PS) microspheres can be used as one of the simulants of SA aerosols. In this study, 800 nm monodisperse fluorescent PS (f-PS) microspheres with fluorescence spectra and particle size distribution similar to those of SA were prepared. The 800 nm monodisperse f-PS microspheres had a fluorescence characteristic peak at 465 nm; in aerosols, 800 nm monodisperse f-PS microspheres with a similar particle size distribution to that of SA were further verified, mainly in the range of 500 nm–1000 nm; finally, it was found that the f-PS microspheres still possessed similar fluorescence characteristics after 180 days. The f-PS microspheres prepared in this study are very close to SA in terms of particle size and fluorescence properties, providing a new idea for aerosol analogs of SA.
Recent Development of Polymer Nanofibers in the Field of Optical Sensing
Authors: Li Jinze , Liu Xin , Xi Jiawei , Deng Li , Yang Yanxin , Li Xiang , Sun Hao
Published: August 2023

In recent years, owing to the continuous development of polymer nanofiber manufacturing technology, various nanofibers with different structural characteristics have emerged, allowing their application in the field of sensing to continually expand. Integrating polymer nanofibers with optical sensors takes advantage of the high sensitivity, fast response, and strong immunity to electromagnetic interference of optical sensors, enabling widespread use in biomedical science, environmental monitoring, food safety, and other fields. This paper summarizes the research progress of polymer nanofibers in optical sensors, classifies and analyzes polymer nanofiber optical sensors according to different functions (fluorescence, Raman, polarization, surface plasmon resonance, and photoelectrochemistry), and introduces the principles, structures, and properties of each type of sensor and application examples in different fields. This paper also looks forward to the future development directions and challenges of polymer nanofiber optical sensors, and provides a reference for in-depth research of sensors and industrial applications of polymer nanofibers.
A New Approach for Ocean Surface Wind Speed Retrieval Using Sentinel-1 Dual-Polarized Imagery
Authors: Gao Yuan , Wang Yunhua , Wang Weili
Published: August 2023

A synthetic aperture radar (SAR) has the capability to observe ocean surface winds with a high spatial resolution, even under extreme conditions. The purpose of this work was to develop a new method for wind speed retrieval with the combination of SAR dual-polarized signals. In this study, we collected 28 tropical cyclone imageries observed using the Sentinel-1 dual-polarization mode. These imageries were collocated with radiometer wind speed measurements and reanalysis of wind vector products. In the new method, the wind speed was set as the output. VV-polarized (vertical transmitting–vertical receiving polarized) normalized radar cross section (NRCS), incident angle, VH-polarized (vertical transmitting–horizontal receiving polarized) NRCS, and wind direction were set as the inputs. Based on different output combinations, wind retrieval models were developed with multiple linear regression (MLR). According to the validation and comparison, the proposed models performed better than the traditional piecewise VH-polarization geophysical model functions (GMFs). The impact of thermal noise on the retrieval of low wind speeds (<10 m/s) could be partially reduced. The input of wind direction is unnecessary if the combination of VV- and VH-polarized imageries has been utilized. These results suggest that the use of MLR and the dual-polarization combination can improve SAR wind retrieval accuracy. Compared with SMAP measurements, our SAR retrievals can provide fine structures of TC wind fields.
Remote Sensing Parameter Extraction of Artificial Young Forests under the Interference of Undergrowth
Authors: Tao Zefu , Yi Lubei , Wang Zhengyu , Zheng Xueting , Xiong Shimei , Bao Anming , Xu Wenqiang
Published: August 2023

Due to the lower canopy height at the maximum crown width at the bottom of young Picea crassifolia trees, they are mixed with undergrowth. This makes it challenging to accurately determine crown size using CHM data or point cloud data. UAV imagery, on the other hand, incorporates rich color information and, after processing, can effectively distinguish between spruce trees and ground vegetation. In this study, the experimental site was an artificial young forest of Picea crassifolia in Shangshan Village, Qinghai Province, China. UAV images were used to obtain normalized saturation data for the sample plots. A marker-controlled watershed segmentation algorithm was employed to extract tree parameters, and the results were compared with those obtained via point cloud clustering segmentation and the marker-controlled watershed segmentation algorithm based on Canopy Height Model (CHM) images. The research results showed that the single tree recognition capabilities of the three types of data were similar, with F-measures of 0.96, 0.95, and 0.987 for the CHM image, UAV imagery, and point cloud data, respectively. The mean square errors of crown width information extracted from the UAV imagery using the marker-controlled watershed segmentation algorithm were 0.043, 0.125, and 0.046 for the three sample plots, which were better than the values of 0.103, 0.182, and 0.074 obtained from CHM data, as well as the values of 0.36, 0.461, and 0.4 obtained from the point cloud data. The point cloud data exhibited better fitting results for tree height extraction compared to the CHM images. This result indicates that UAV-acquired optical imagery has applicability in extracting individual tree feature parameters and can compensate for the deficiencies of CHM and point cloud data.
Using Deep Learning Methods for Segmenting Polar Mesospheric Summer Echoes
Authors: Domben Erik Seip , Sharma Puneet , Mann Ingrid
Published: August 2023

Polar mesospheric summer echoes (PMSE) are radar echoes that are observed in the mesosphere during the arctic summer months in the polar regions. By studying PMSE, researchers can gain insights into physical and chemical processes that occur in the upper atmosphere—specifically, in the 80 to 90 km altitude range. In this paper, we employ fully convolutional networks such as UNET and UNET++ for the purpose of segmenting PMSE from the EISCAT VHF dataset. First, experiments are performed to find suitable weights and hyperparameters for UNET and UNET++. Second, different loss functions are tested to find one suitable for our task. Third, as the number of PMSE samples used is relatively small, this can lead to poor generalization. To address this, image-level and object-level augmentation methods are employed. Fourth, we briefly explain our findings by employing layerwise relevance propagation.
Sat-Mesh: Learning Neural Implicit Surfaces for Multi-View Satellite Reconstruction
Authors: Qu Yingjie , Deng Fei
Published: August 2023

Automatic reconstruction of surfaces from satellite imagery is a hot topic in computer vision and photogrammetry. State-of-the-art reconstruction methods typically produce 2.5D elevation data. In contrast, we propose a one-stage method directly generating a 3D mesh model from multi-view satellite imagery. We introduce a novel Sat-Mesh approach for satellite implicit surface reconstruction: We represent the scene as a continuous signed distance function (SDF) and leverage a volume rendering framework to learn the SDF values. To address the challenges posed by lighting variations and inconsistent appearances in satellite imagery, we incorporate a latent vector in the network architecture to encode image appearances. Furthermore, we introduce a multi-view stereo constraint to enhance surface quality. This constraint minimizes the similarity between image patches to optimize the position and orientation of the SDF surface. Experimental results demonstrate that our method achieves superior visual quality and quantitative accuracy in generating mesh models. Moreover, our approach can learn seasonal variations in satellite imagery, resulting in texture mesh models with different and consistent seasonal appearances.
A Multi-Correlation Peak Phase Deblurring Algorithm for BeiDou B1C Signals in Urban Environments
Authors: Yang Xu , Feng Wenquan , Zhuang Chen , Wang Qiang , Yang Xu , Yang Zhe
Published: August 2023

With the widespread global application of BeiDou navigation, BeiDou B1C signaling based on Quadrature Multiplexed Binary Offset Carrier (QMBOC) modulation is expected to be extensively used in urban environments due to its wider signal bandwidth, smaller code pseudorange measurement errors, and stronger multipath capabilities. Despite offering higher positioning accuracy and secondary modulation characteristics of the BeiDou, B1C signals introduce the challenge of multiple peaks in the autocorrelation function. This leads to phase ambiguity during signal acquisition and tracking, resulting in positioning deviations of tens or even hundreds of meters. In urban environments, such deviations give rise to significant practical application issues. To address this problem, we have designed a multi-loop structure for the synchronous tracking of B1C signals and proposed a multi-peak phase-deblurring algorithm specifically tailored for the BeiDou B1C signal in urban environments. This algorithm considers the coupling relationship between the code and the carrier loops, and by matching the structural design of multiple loops, it achieves a precise and unambiguous phase estimation of the pseudocode, enabling the stable tracking of the entire loop for the BeiDou B1C signal. Simulation and actual testing demonstrate that the algorithm exhibits an error less than 0.03 for chip intervals when the signal-to-noise ratio is greater than −20 dB. Additionally, the accuracy can be improved by adjusting the set conditions, making it suitable for urban environments.
A Review of Hybrid VLC/RF Networks: Features, Applications, and Future Directions
Authors: Bravo Alvarez Lisandra , Montejo-Sánchez Samuel , Rodríguez-López Lien , Azurdia-Meza Cesar , Saavedra Gabriel
Published: August 2023

The expectation for communication systems beyond 5G/6G is to provide high reliability, high throughput, low latency, and high energy efficiency services. The integration between systems based on radio frequency (RF) and visible light communication (VLC) promises the design of hybrid systems capable of addressing and largely satisfying these requirements. Hybrid network design enables complementary cooperation without interference between the two technologies, thereby increasing the overall system data rate, improving load balancing, and reducing non-coverage areas. VLC/RF hybrid networks can offer reliable and efficient communication solutions for Internet of Things (IoT) applications such as smart lighting, location-based services, home automation, smart healthcare, and industrial IoT. Therefore, hybrid VLC/RF networks are key technologies for next-generation communication systems. In this paper, a comprehensive state-of-the-art study of hybrid VLC/RF networks is carried out, divided into four areas. First, indoor scenarios are studied considering lighting requirements, hybrid channel models, load balancing, resource allocation, and hybrid network topologies. Second, the characteristics and implementation of these hybrid networks in outdoor scenarios with adverse conditions are analyzed. Third, we address the main applications of hybrid VLC/RF networks in technological, economic, and socio-environmental domains. Finally, we outline the main challenges and future research lines of hybrid VLC/RF networks.
A Low Complexity Rolling Bearing Diagnosis Technique Based on Machine Learning and Smart Preprocessing
Authors: Fort Ada , Landi Elia , Mugnaini Marco , Vignoli Valerio
Published: August 2023

In this work, we present a diagnosis system for rolling bearings that leverages simultaneous measurements of vibrations and machine rotation speed. Our approach combines the robustness of simple time domain methods for fault detection with the potential of machine learning techniques for fault location. This research is based on a neural network classifier, which exploits a simple and novel preprocessing algorithm specifically designed for minimizing the dependency of the classifier performance on the machine working conditions, on the bearing model and on the acquisition system set-up. The overall diagnosis system is based on light algorithms with reduced complexity and hardware resource demand and is designed to be deployed in embedded electronics. The fault diagnosis system was trained using emulated data, exploiting an ad-hoc test bench thus avoiding the problem of generating enough data, achieving an overall classifier accuracy larger than 98%. Its noteworthy ability to generalize was proven by using data emulating different working conditions and acquisition set-ups and noise levels, obtaining in all the cases accuracies greater than 97%, thereby proving in this way that the proposed system can be applied in a wide spectrum of different applications. Finally, real data from an on-line database containing vibration signals obtained in a completely different scenario are used to demonstrate the distinctive capability of the proposed system to generalize.
Experimental Investigation of Acoustic Features to Optimize Intelligibility in Cochlear Implants
Authors: Henry Fergal , Parsi Ashkan , Glavin Martin , Jones Edward
Published: August 2023

Although cochlear implants work well for people with hearing impairment in quiet conditions, it is well-known that they are not as effective in noisy environments. Noise reduction algorithms based on machine learning allied with appropriate speech features can be used to address this problem. The purpose of this study is to investigate the importance of acoustic features in such algorithms. Acoustic features are extracted from speech and noise mixtures and used in conjunction with the ideal binary mask to train a deep neural network to estimate masks for speech synthesis to produce enhanced speech. The intelligibility of this speech is objectively measured using metrics such as Short-time Objective Intelligibility (STOI), Hit Rate minus False Alarm Rate (HIT-FA) and Normalized Covariance Measure (NCM) for both simulated normal-hearing and hearing-impaired scenarios. A wide range of existing features is experimentally evaluated, including features that have not been traditionally applied in this application. The results demonstrate that frequency domain features perform best. In particular, Gammatone features performed best for normal hearing over a range of signal-to-noise ratios and noise types (STOI = 0.7826). Mel spectrogram features exhibited the best overall performance for hearing impairment (NCM = 0.7314). There is a stronger correlation between STOI and NCM than HIT-FA and NCM, suggesting that the former is a better predictor of intelligibility for hearing-impaired listeners. The results of this study may be useful in the design of adaptive intelligibility enhancement systems for cochlear implants based on both the noise level and the nature of the noise (stationary or non-stationary).
Detection of Pedestrians in Reverse Camera Using Multimodal Convolutional Neural Networks
Authors: Reveles-Gómez Luis C. , Luna-García Huizilopoztli , Celaya-Padilla José M. , Barría-Huidobro Cristian , Gamboa-Rosales Hamurabi , Solís-Robles Roberto , Arceo-Olague José G. , Galván-Tejada Jorge I. , Galván-Tejada Carlos E. , Rondon David , Villalba-Condori Klinge O.
Published: August 2023

In recent years, the application of artificial intelligence (AI) in the automotive industry has led to the development of intelligent systems focused on road safety, aiming to improve protection for drivers and pedestrians worldwide to reduce the number of accidents yearly. One of the most critical functions of these systems is pedestrian detection, as it is crucial for the safety of everyone involved in road traffic. However, pedestrian detection goes beyond the front of the vehicle; it is also essential to consider the vehicle’s rear since pedestrian collisions occur when the car is in reverse drive. To contribute to the solution of this problem, this research proposes a model based on convolutional neural networks (CNN) using a proposed one-dimensional architecture and the Inception V3 architecture to fuse the information from the backup camera and the distance measured by the ultrasonic sensors, to detect pedestrians when the vehicle is reversing. In addition, specific data collection was performed to build a database for the research. The proposed model showed outstanding results with 99.85% accuracy and 99.86% correct classification performance, demonstrating that it is possible to achieve the goal of pedestrian detection using CNN by fusing two types of data.
Infrared HOT Photodetectors: Status and Outlook
Authors: Rogalski Antoni , Kopytko Małgorzata , Hu Weida , Martyniuk Piotr
Published: August 2023

At the current stage of long-wavelength infrared (LWIR) detector technology development, the only commercially available detectors that operate at room temperature are thermal detectors. However, the efficiency of thermal detectors is modest: they exhibit a slow response time and are not very useful for multispectral detection. On the other hand, in order to reach better performance (higher detectivity, better response speed, and multispectral response), infrared (IR) photon detectors are used, requiring cryogenic cooling. This is a major obstacle to the wider use of IR technology. For this reason, significant efforts have been taken to increase the operating temperature, such as size, weight and power consumption (SWaP) reductions, resulting in lower IR system costs. Currently, efforts are aimed at developing photon-based infrared detectors, with performance being limited by background radiation noise. These requirements are formalized in the Law 19 standard for P-i-N HgCdTe photodiodes. In addition to typical semiconductor materials such as HgCdTe and type-II AIIIBV superlattices, new generations of materials (two-dimensional (2D) materials and colloidal quantum dots (CQDs)) distinguished by the physical properties required for infrared detection are being considered for future high-operating-temperature (HOT) IR devices. Based on the dark current density, responsivity and detectivity considerations, an attempt is made to determine the development of a next-gen IR photodetector in the near future.
Efficient Sigma–Delta Sensor Array Beamforming
Authors: Carbajal Ipenza Sammy Johnatan , Masiero Bruno Sanches
Published: August 2023

Nowadays, sensors with built-in sigma–delta modulators (ΣΔMs) are widely used in consumer, industrial, automotive, and medical applications, as they have become a cost-effective and convenient way to deliver data to digital processors. This is the case for micro-electro-mechanical system (MEMS), digital microphones that convert analog audio to a pulse-density modulated (PDM) bitstream. However, as the ΣΔMs output a PDM signal, sensors require either built-in or external high-order decimation filters to demodulate the PDM signal to a baseband multi-bit pulse-code modulated (PCM) signal. Because of this extra circuit requirement, the implementation of sensor array algorithms, such as beamforming in embedded systems (where the processing resources are critical) or in very large-scale integration (VLSI) circuits (where the power and area are crucial) becomes especially expensive as a large number of parallel decimation filters are required. This article proposes a novel architecture for beamforming algorithm implementation that fuses delay and decimation operations based on maximally flat (MAXFLAT) filters to make array processing more affordable. As proof of concept, we present an implementation example of a delay-and-sum (DAS) beamformer at given spatial and frequency requirements using this novel approach. Under these specifications, the proposed architecture requires 52% lower storage resources and 19% lower computational resources than the most efficient state-of-the-art architecture.
Built Environment in Urban Space Affect Protests: A Cross-Sectional Study in Hong Kong
Authors: Wu Xueying , Lu Yi , Wang Jingjing , Jiang Bin
Published: August 2023

The built environment is indispensable for conducting protests. However, we still know little about the role the built environment plays in either supporting or hindering protests. In this study, we investigated the relationship between built environment characteristics and the spatial distribution of 348 protests that occurred in Hong Kong from June 2019 to January 2020. We innovatively distinguished between peaceful and violent protests as well as legal and illegal (authorized vs. unauthorized) protests. Our study revealed several significant patterns. First, in general, areas with a higher level of building density, government and commerce point-of-interest (POI) density, metro accessibility, park density, and street greenery experienced more protesting activities. Second, illegal and violent protests, those which are less constrained by authorities and thus more likely to reflect the autonomous choices of the protestors, are more likely to occur in regions with more government and commercial buildings, high metro accessibility, and a high level of street greenery. Based on these findings, we also proposed a new framework to illustrate the relationship between certain built environment features and choice of protest locations, which we hope will provide preliminary guidance for future studies.
Toward the Optimization of Mining Operations Using an Automatic Unmineable Inclusions Detection System for Bucket Wheel Excavator Collision Prevention: A Synthetic Study
Authors: Kritikakis George , Galetakis Michael , Vafidis Antonios , Apostolopoulos George , Michalakopoulos Theodore , Triantafyllou Miltiades , Roumpos Christos , Pavloudakis Francis , Deligiorgis Basileios , Economou Nikos , Andronikidis Nikos
Published: August 2023

This work introduces a methodology for the automatic unmineable inclusions detection and Bucket Wheel Excavator (BWE) collision prevention, using electromagnetic (EM) inspection and a fuzzy inference system. EM data are collected continuously ahead from the bucket wheel of a BWE and subjected to processing. Two distinct methodologies for data processing were developed and integrated into the MATLAB programming environment. The first approach, named “Simple Mode”, utilizes statistical process control to generate real-time alerts in the event of a potential collision involving the excavator’s bucket and hard rock inclusions. The advanced processing flow (“Advanced Mode”) requires accurate instrument positioning and data from successive EM scans. It incorporates techniques of local resistivity maxima detection (Position Prominence Index) as well as Neural Network-based Pattern Recognition (NNPR). A decision support process based on a Fuzzy Inference System (FIS) has been developed to assist BWE operators in avoiding collision when digging hard rock inclusions. The proposed methodology was extensively tested using synthetic EM data. Limited real data, acquired with a CMD2 (GF Instruments) EM instrument equipped with GPS, were used to control its efficiency. Increased accuracy in the automatic detection of unmineable inclusions was observed using the Advanced Mode. On the other hand, the Simple Mode processing technique offers the advantage of being independent of instrument positioning as well as it provides real-time inspection of the excavated mine slope. This work introduces a methodology for hard rock inclusion detection and can contribute to the optimization of mine operations by improving resource efficiency, safety, cost savings, and environmental sustainability.
Evaluation of Seismic Performance of Masonry Stone Pagoda: Dynamic Centrifuge Test and Numerical Simulation Analysis
Authors: Lee Gayoon , Park Heon-Joon , Pham Khoa V. A. , Kim Jae-Young , Lee Sung-Min , Lee Kihak
Published: August 2023

This study provides a comparison of results from dynamic centrifuge tests and a finite element analysis model to confirm the behavior of a representative Korean stone pagoda cultural heritage structure against earthquakes. The indirect stiffness or physical state of the structure was estimated by measuring the natural frequency of the masonry stone pagoda. The actual natural frequency of the stone pagoda was measured to be 4.5 Hz. It was determined to have a lower natural frequency than other stone pagodas of similar size. For the experiment, a dynamic centrifugal separator test was performed on a 1/15 model. Data from an actual earthquake record, the Ofunato earthquake, were used, with various maximum acceleration levels ranging from 0.069 g to 0.424 g. In order to confirm the accuracy of the finite element analysis model, the measured natural frequency of the masonry stone pagoda was compared with the modal analysis of the finite element model. When the data obtained from the experiment and the PGA (peak ground acceleration) of the FEM analysis with a complex masonry stone pagoda using a validated model result were compared, it was found to have a low average error rate of 13%. This shows that structural behavior can be predicted for similar masonry stone pagoda structures using finite element method analysis in the future.
Coupling System Dynamics Model of Cross Border Logistics and Ecological Environment Based on the Sustainable Perspective of Global Value Chain
Authors: Zhang Hai-Na
Published: August 2023

International import and export trade, along with cross-border logistics management, plays a pivotal role in the era of globalization, driving the development of the global economy and fostering international trade prosperity. Nevertheless, the continuous growth of the global economy has also brought forth fresh challenges to the ecological environment posed by cross-border logistics activities. Against this backdrop, this paper begins by analysing the correlation between international trade and logistics activities. The study reveals a positive response relationship between the total volume of international import and export trade and cross-border logistics, demonstrating a positive correlation. Subsequently, the impact of international import and export trade, as well as cross-border logistics, on the ecological environment is discussed, underscoring the significance of implementing ecological environment monitoring. Taking into account the environmental impact of cross-border logistics activities, an integrated system is proposed and designed to enhance cross-border logistics efficiency while considering environmental protection and sustainable development. This system encompasses real-time monitoring, data collection, threat, and risk assessment. This study makes a clear contribution to research on green innovation and environmental protection within the context of cross-border logistics. It offers a different perspective on the integration of cross-border logistics management and the ecological environment, deepens understanding of environmental protection innovation strategies and cross-border logistics management from the perspective of sustainable development. Furthermore, it provides valuable management insights for related enterprises to balance development and environmental protection. Additionally, it sheds light on the international impact of import and export trade, offering crucial inspiration and theoretical references for decision-making.
The Composition and Assembly of Soil Microbial Communities Differ across Vegetation Cover Types of Urban Green Spaces
Authors: Zhou Yangyi , Wang Jiangping
Published: August 2023

Soil microorganisms play an important role in urban green spaces by providing ecological functions. However, information on the structure and assembly of microbial communities and the public risk of pathogenic bacteria in urban green spaces remains elusive. Here, we conducted a field survey on soil organisms in different vegetation cover types of urban green spaces (e.g., grasslands, shrublands, and woodlands) based on 16 S rRNA gene amplicon sequencing. We found that soil microbial communities in grasslands were dominated by Pseudomonadota, Acidobacteriota, Actinomycetota, and Chloroflexota. The diversity and niche breadth of the microbial communities in grasslands showed differences compared to shrublands and woodlands. Stochastic processes, which contribute to community assembly in grasslands, were lower compared to shrublands and woodlands, dominating the soil microbial community assembly of urban green spaces. Compared with soil microbial communities in scrublands and woodlands, the network of soil microbial communities in grasslands was simpler and had a weaker stability. Furthermore, the value of the microbial index of pathogenic bacteria in the observed green spaces was 0.01, which means that the risk of potential pathogens in green spaces was low. This study provides crucial information for the sustainable management of urban green spaces by regulating soil microorganisms, offering novel insights into the public health risks associated with potential pathogenic bacteria in these green spaces.
Fostering Urban Destination Prosperity through Post COVID-19 Sustainable Tourism in Craiova, Romania
Authors: Mazilu Mirela , Niță Amalia , Drăguleasa Ionuț-Adrian , Mititelu-Ionuș Oana
Published: August 2023

In accordance with the 2030 Agenda, the prosperity of tourist destinations holds a crucial role in the sustainable development of urban areas. Tourism represents an imperative solution in transitioning from survival to success after the COVID-19 pandemic. The stakeholders in the field should introduce new tourism forms that enable a more comprehensive strategy for managing and developing responsible tourism, bringing into focus new skills, resources, and levels for change to develop resilience, urban community satisfaction, and the unique intrinsic attraction of each tourist destination in Romania. This study develops a model of prosperity for urban tourist destinations, which can be applied to medium-large cities in Romania. We propose for the city of Craiova the use and identification of four spheres of sustainability, which in turn have a set of 17 indicators. The research method used to determine the indicators has two stages: (1) the analysis of the specialized literature to identify the appropriate indicators for an urban destination and (2) statistical analyzes and interviews with internal stakeholders (residents), which present their tourist perspective of the city. This article tackles an innovative concept, called prosperity and innovation in Craiova tourism, which can be implemented in all tourism niches and brings new development perspectives that correspond to the norms of sustainable development and their direction towards sustainability. The article addresses the concept of prosperity in tourism and contains information about: the definition of prosperity, the concept of prosperity (an engine of innovation in tourism and its implications), but also perspectives for a prosperous tourism policy in Craiova tourism.
Narratives on Education for Sustainable Development in Malaysian Universities
Authors: Syed-Abdullah Sharifah Intan Sharina , Kushnir Iryna , Abdrahim Nur Aira
Published: August 2023

Higher education institutions are powerful forces in producing the human capital necessary to drive sustainable development. To support global aspirations to improve our planet, higher education institutions worldwide have been integrating the education for sustainable development agenda within the curriculum of a wide range of disciplines. This study aims to describe how Malaysian public universities have been implementing education for sustainable development. By adopting a qualitative research approach, this study gathered data through in-depth interviews and four focus group discussions with 16 sustainability experts from five public universities in Malaysia, renowned for their education provision and research in the field of sustainable development. Thematic analyses of the data reveal four prevailing approaches to implementing education for sustainable development at Malaysian higher education institutions. They are the organisational adoption approach, the competitive approach, the continuity approach, and the transformative approach. This study also projects the idea that the implementation of education for sustainable development (ESD) requires solid support from the institutions’ senior management to prioritise it in their managerial agenda.