bluuebunny/crossref_metadata_2025 huggingface dataset:
Improved Multi-Model Classification Technique for Sound Event Detection in Urban Environments
Authors: Khan Muhammad Salman , Shah Mohsin , Khan Asfandyar , Aldweesh Amjad , Ali Mushtaq , Tag Eldin Elsayed , Ishaq Waqar , Hussain Lal
Published: October 2022

Sound event detection (SED) plays an important role in understanding the sounds in different environments. Recent studies on standardized datasets have shown the growing interest of the scientific community in the SED problem, however, these did not pay sufficient attention to the detection of artificial and natural sound. In order to tackle this issue, the present article uses different features in combination for detection of machine-generated and natural sounds. In this article, we trained and compared a Stacked Convolutional Recurrent Neural Network (S-CRNN), a Convolutional Recurrent Neural Network (CRNN), and an Artificial Neural Network Classifier (ANN) using the DCASE 2017 Task-3 dataset. Relative spectral–perceptual linear prediction (RASTA-PLP) and Mel-frequency cepstrum (MFCC) features are used as input to the proposed multi-model. The performance of monaural and binaural approaches provided to the classifier as an input is compared. In our proposed S-CRNN model, we classified the sound events in the dataset into two sub-classes. When compared with the baseline model, our obtained results show that the PLP-based ANN classifier improves the individual error rate (ER) for each sound event, e.g., the error rate (ER) is improved to 0.23 for heavy vehicle events and 0.32 for people walking, and minor gains are shown in other events as compared to the baseline. Our proposed CRNN performs well when compare to the baseline and to our proposed ANN model. Moreover, in cross-validation trials, the results in the evaluation stage demonstrate a significant improvement compared to the best performance of DCASE 2017 Task-3, reducing the ER to 0.11 and increasing the F1-score by 10% in the evaluation dataset. Erosion and dilation were used during post-processing.
Artificial Intelligence-Assisted RT-PCR Detection Model for Rapid and Reliable Diagnosis of COVID-19
Authors: Özbilge Emre , Sanlidag Tamer , Ozbilge Ebru , Baddal Buket
Published: October 2022

With the spread of SARS-CoV-2 variants with higher transmissibility and disease severity, rapid detection and isolation of patients remains a critical step in the control of the pandemic. RT-PCR is the recommended diagnostic test for the diagnosis of COVID-19. The current study aims to develop an artificial intelligence (AI)-driven COVID-19 RT-PCR detection system for rapid and reliable diagnosis, facilitating the heavy burden of healthcare workers. A multi-input deep convolutional neural network (DCNN) is proposed. A MobileNetV2 DCNN architecture was used to predict the possible diagnostic result of RT-PCR fluorescence data from patient nasopharyngeal sample analyses. Amplification curves in FAM (ORF1ab and N genes, SARS-CoV-2) and HEX (human RNAse P gene, internal control) channels of 400 samples were categorized as positive, weak-positive, negative or re-run (unspecific fluorescence). During the network training, HEX and FAM channel images for each sample were simultaneously presented to the DCNN. The obtained DCNN model was verified using another 160 new test samples. The proposed DCNN classified RT-PCR amplification curves correctly for all COVID-19 diagnostic categories with an accuracy, sensitivity, specificity, F1-score, and AUC of the model reported to be 1. Furthermore, the performance of other pre-trained well-known DCNN models was also compared with the MobileNetV2 model using 5-fold cross-validation, and the results showed that there were no significant differences between the other models at the 5% significance level; however, the MobileNetV2 model outperformed others dramatically in terms of the training speed and fast convergence. The developed model can help rapidly diagnose COVID-19 patients and would be beneficial in tackling future pandemics.
Synthesis of Biodiesel by Interesterification of Triglycerides with Methyl Formate
Authors: Sendzikiene Egle , Makareviciene Violeta
Published: October 2022

In the conventional synthesis of biodiesel, not only fatty acid esters (biodiesel) are formed, but also the by-product is the glycerol phase, which amounts to about 10 wt.%. Recently, the studies on the interesterification of oil using carboxylate esters have been launched. In this case, no glycerol is formed, and esters of glycerol and short-chain organic acids soluble in biodiesel are produced. The biodiesel yield is increased, and the biodiesel production process is more economically viable. The process of interesterification with methyl formate yields a mixture of biodiesel and triformylglycerol, which is not inferior in quality to biodiesel, but also has better low-temperature properties. The paper analyzes the application of chemical and enzymatic catalysis methods for the interesterification of triglycerides with methyl formate. The influence of catalyst amount, reagent molar ratio, temperature, and process time on the product yield is presented. The quality indicators of the obtained fuel and their compliance with the requirements of the biodiesel fuel standard are discussed.
Bidirectional Acoustic Negative Refraction Based on a Pair of Identical Purely Imaginary Metamaterials Slabs
Authors: Zhang Ling-Ling , Ji Yang , Chen Peng , Dai Qian , Liu Xiao-Jun
Published: October 2022

Acoustic purely imaginary metamaterials (PIMs) slabs can support the coexistence of coherent perfect absorption and laser modes and are used to achieve negative refraction. Previous works have focused on a pair of different PIM slabs, one operating in CPA mode and the other in laser mode. However, this structure has restrictions on the incident wave direction, specifically the wave can only be incident from the CPA side. In this paper, we derive the analytical expressions for the parameters required for the coexistence of CPA and laser modes in acoustic PIM slabs. Numerical simulation results show that such PIM slab can freely switch states between the coherent complete absorber and the laser depending on the incidence direction. On this basis, by using a pair of identical PIM slabs, bidirectional negative refraction and planar focusing can be achieved. In addition, the parameters in the appropriate range can be found by adjusting the mode order, which facilitates the experimental verification. So far, the required acoustic purely imaginary metamaterials (PIMs) have not been experimentally demonstrated, and the results presented in the manuscript are theoretical speculations on their existence, so practical applications may require more sophisticated design and engineering.
Investigation of the Mechanical Properties of Additively Manufactured Metal Parts with Different Relative Densities
Authors: Thawon Itthidet , Fongsamootr Thongchai , Mona Yuttana , Suttakul Pana
Published: October 2022

Currently, metal additive manufacturing (MAM) has been receiving more attention in many sectors for its production of metal parts because MAM effortlessly enables the fabrication of complex metal parts and provides faster and more sustainable manufacturing than conventional processes. Recently, a MAM-using bound metal deposition (BMD) has been proposed as a user-friendly manufacturing method that can provide low-volume production, economical metal parts, and operation safety. Since the BMD technique is new, information on the mechanical properties of MAM parts using this technique has not been sufficiently provided. This paper aims to study the mechanical properties of MAM parts manufactured by the BMD technique, examining the elastic modulus, yield strength, ultimate strength, and fatigue behavior of the parts with different relative densities. The MAM parts made from 316L and 17-4PH stainless steel were investigated using tensile and fatigue tests. Some mechanical properties of the infill parts in this study were validated with formulas from the literature. The weight efficiency is used as an index to assess the efficiency of the infill parts with different densities by examining the relationship between the mechanical properties and the weight of the MAM parts. The experimental results and a discussion of the weight efficiency assessment are presented as a novel information report on MAM products fabricated by BMD technology.
Using Diffused Essential Oils to Remove Airborne Pine and Pecan Pollen: A Pilot Study
Authors: Davis James T. , Lorenzen Kyle , Poulson Ariel , Carlson Richard E.
Published: October 2022

Pollen is a major source of allergies, and its prevalence is rising. Essential oils, primarily composed of terpenes, are easy to diffuse and are becoming more common to use in the home. To test the effect of diffusing essential oils on indoor pollen, pollen was introduced into an enclosed environment containing an ultrasonic diffuser. Lavender, Citrus Fresh™, and Thieves® were tested against lodgepole pine pollen. Lavender was also tested against pecan pollen. An ultrasonic diffuser, containing either 100 mL of reverse osmosis (RO) water or 100 mL of RO water and 10 drops of an essential oil, was diffused in the environment to see how they would influence the amount of pollen that was deposited on the collection slides, compared to when the diffuser was off. The results show that diffusing RO water and lavender, Citrus Fresh™, or Thieves® essential oil increased the amount of lodgepole pine pollen deposited on the floor of an enclosed environment. Diffusing either RO water alone or RO water and lavender essential oil increased the amount of pecan pollen found on the floor of an enclosed environment. This suggests that a diffuser may help remove pollen from the air and potentially aid in alleviating allergies.
Trigeminal Schwannoma Presenting with Masticatory Muscle Atrophy: A Rare Case Report
Authors: Yoshino Tona , Shinozuka Keiji , Yokoyama Kana , Yamakawa Ayana , Tonogi Morio
Published: October 2022

Trigeminal schwannoma (TS) presenting with masticatory muscle atrophy is very rare. Here, we report the case of an 80 year-old male patient with TS presenting with masticatory muscle atrophy in October 2014. The patient had been diagnosed with hypertrophic pachymeningitis and right intracranial TS in 2013 by his neurologist, for which he was treated with steroids. However, his symptoms in the trigeminal innervation region persisted. He visited our department due to difficulty in opening his mouth as well as eating. Surgery was not performed owing to his advanced age and general condition. His trismus was improved by mouth opening training via manual manipulation for three years. We suggest that TS should be considered in the differential diagnosis of patients with masticatory muscle atrophy. Consultation with a neurologist is also essential. Manual manipulation may be an effective non-surgical treatment option for patients with difficulty in mouth opening owing to TS.
Improving Very High Plastic Clays with the Combined Effect of Sand, Lime, and Polypropylene Fibers
Authors: Meddah Abdelaziz , Goufi Abd Elmalik , Pantelidis Lysandros
Published: October 2022

Improving the mechanical properties of low-strength soils (e.g., high plasticity clays) is one of the main branches of geotechnical engineering. The adoption of stabilization techniques for ensuring that structures will be founded on an adequately strong soil base is a common practice. Stabilization techniques for clay soils may include inert materials (cohesionless soils), chemical substances (cement, lime, or industrial additives), or the use of randomly distributed fibers. While all of these additives are added to low-strength soils by mixing, the question remains whether an optimal combination of stabilization techniques can be achieved for maximizing soil strength. Besides, each one of these additives contributes to an increase in soil strength in a different manner (soil replacement, chemical bonding of soil particles, and soil reinforcement respectively), while, according to the literature, each technique has its limitations. The latter refers to a limited effect on strength improvement and a maximum possible percentage, beyond which an additive has an adverse effect on strength; it also refers to other factors, such as brittleness failure, material availability, overall cost, and environment-related issues. Hence, in the present study, the efficiency of improving the basic geotechnical properties of a very high plasticity clay (liquid limit ωl = 86%) with a coupled effect between dune sand, lime, and polypropylene (PP) fibers has been investigated. The samples prepared by combining the three aforementioned soil improvement techniques were compared in terms of plasticity, compaction characteristics, unconfined compressive strength (UCS), and California Bearing Ratio (CBR) index. The experimental results show that the combination of these additives may lead to a considerable improvement in the strength and ductility of soils, even with a small amount of lime additive. Also, it was observed that 20% of sand, 3.4% of lime and 0.9% of fibers (by wt%) offers the best performance in terms of strength improvement for the clay tested (i.e., 12.75 times improvement compared to the untreated clay).
Therapeutic Potential of Tamarix aphylla in the Prevention of Lung Injury through the Regulation of Inflammation, Oxidative Stress and Cell-Signaling Molecules
Authors: Almatroodi Saleh A. , Khan Amjad Ali , Aloliqi Abdulaziz A. , Syed Mansoor Ali , Rahmani Arshad Husain
Published: October 2022

Tamarix aphylla is a commonly grown plant in Saudi Arabia and its therapeutic potential is widely recognized. Here, in this study, the aim was to explore the role of T. aphylla leaf extract (TAE) on lipopolysaccharide (LPS)-induced acute lung injury (ALI) in mice and LPS-stimulated RAW 264.7 cells. The antioxidant and anti-inflammatory parameters of TAE were performed through in vitro assays by measuring H2O2 free radical scavenging and protein denaturation inhibition. After LPS administration, broncho alveolar lavage fluid (BALF) and lung tissue were obtained to evaluate the pro-inflammatory cytokine levels, histopathological alterations, immunohistochemistry and TUNEL staining. The results designate that TAE shows anti-inflammatory activity through a decrease in pro-inflammatory cytokines, TNF-α and IL-6 in LPS-stimulated RAW 264.7 cells and BALF. The antioxidant enzyme level (SOD) decreased and MDA content was increased in the LPS-induced mice. However, TAE pretreatment markedly reversed these parameters compared to the group administered LPS only (p < 0.05). The histopathological analysis demonstrated that TAE maintained the lung tissue architecture by reducing LPS-induced inflammation and congestion. The expression pattern of the Cox-2 protein and apoptosis was high in the group administered LPS only, whereas TAE pretreatment showed a reduction in the expression pattern and apoptosis. Moreover, the in vitro assay of TAE demonstrated a concentration-dependent free radical scavenging and anti-inflammatory activity. In conclusion, our results advocate the health-promoting effects of T. aphylla on LPS-induced acute lung injury, which might be due to its antioxidative and anti-inflammatory potential.
Three-Dimensional Analytical Calculation and Optimization of Plate-Type Permanent Magnet Electrodynamic Suspension System
Authors: Liu Mingxin , Tan Yiqiu , Yang Qing , Chen Qiang , Zhou Danfeng , Li Jie
Published: October 2022

With the development of rare earth permanent magnet (PM) materials, more and more attention has been paid to the permanent magnet electrodynamic suspension (PM-EDS) structure. In this paper, the plate-type PM-EDS structure with an adjustable deflection angle of PM is researched, and the size of the PM is optimized. First, the second-order vector potential (SOVP) equation is established, and the analytical solutions of the electromagnetic forces and magnetic fields of the PM-EDS structure are obtained by analytical calculation. Secondly, the accuracy and reliability of the analytical model are verified by comparing the analytical calculation results with the finite element analysis (FEA) calculation results. Finally, the multi-objective particle swarm optimization (MOPSO) algorithm is used to optimize the size of the PM. The optimization results prove that the lift-to-drag ratio and lift-to-weight ratio of the suspension system are improved. The research results can provide a theoretical basis for the design of a PM-EDS train.
Dynamic Response and Geogrid Strain Analysis of GRS Retaining Wall
Authors: Wang Jiaquan , Zhong Wentao , Lin Zhinan , Tang Yi
Published: October 2022

Modular Geogrid Reinforced Soil (GRS) retaining walls, as flexible structures, usually have a certain deformation capacity. However, the deformation damage of the facing panels will directly affect the durability performance of the retaining wall and pose a threat to the safety and operation of the road and related facilities. In order to study the influence of different load factors on the deformation mode and failure characteristics of the retaining wall, an indoor large-scale model test was carried out. The test load considers the average load, peak value, amplitude and frequency of load under traffic load. The changes in settlement and horizontal deformation, geogrid strain and acceleration response of the GRS retaining wall are compared and analyzed. The results show that in the dynamic test, the two wall damage modes are “wall facing outward tilt” and “wall facing outward curved”. The maximum strain of the geogrid was 4.5% and 3.6%, respectively, which did not reach the damage strain. The peak load is the largest mechanical response of all load factors, followed by the load magnitude and average value, and finally the load frequency. In addition, combining the existing GRS retaining wall deformation and earth pressure calculation theory, a set of calculation methods for the strain of tendons under external load is proposed.
Recent Development of Heavy Atom-Free Triplet Photosensitizers for Photodynamic Therapy
Authors: Xiao Xiao , Ye Kaiyue , Imran Muhammad , Zhao Jianzhang
Published: October 2022

Photodynamic therapy (PDT) is an attractive method for cancer treatment. Triplet photosensitizers (PSs) are critical for this method; upon photoexcitation, efficient intersystem crossing (ISC) occurs for triplet PSs, the triplet-excited state of the triplet PSs is populated, then via intermolecular triplet energy transfer, the O2, in triplet-spin multiplicity at ground state, is sensitized to the singlet-excited state, i.e., singlet oxygen (1O2) is produced. This strong reactive oxygen species (ROS) will oxidize the biomolecules in the tumor tissue. Thus, the design of novel triplet PSs as efficient PDT agents is vital. In this review article, we will introduce the recent development of the heavy atom-free triplet PSs used for PDT, including those based on spin-orbit charge transfer ISC (SOCT-ISC), twisting of the π-conjugation framework-induced ISC, radical enhanced ISC, and thionated carbonyl-induced ISC. The ISC mechanisms and molecular structure design rationales are discussed. The less studied electron spin selectivity of the ISC of the triplet PSs is also introduced. This information is helpful for the future design of new efficient triplet PSs for PDT.
Design Requirements for a Monitoring System for a Mobile Hemodialysis Device: Patients’ and Care Partners’ Perspectives
Authors: Jónsdóttir Auður Anna , Kessler Larry G. , Kim Ji-Eun
Published: October 2022

Although mobile hemodialysis treatments have been found to be an effective alternative to current in-center and home-based hemodialysis treatments, many barriers to its successful implementation remain. These barriers include the lack of considering user-centered monitoring protocols. This study investigates 24 patients’ and 12 care partners’ expectations for monitoring procedures for a mobile hemodialysis device. Individual semi-structured interviews were conducted at three locations within the Veterans Affairs Health Care System: Seattle, WA; Nashville, TN; and Louisville, KY. All interviews were transcribed and analyzed using inductive or deductive content analysis approaches. We identified 10 categories of indicators suggesting patients’ needs to receive dialysis treatment and 11 categories of indicators suggesting patients’ successful dialysis treatment. Furthermore, we identified six categories of patients’ and care partners’ design expectations for monitoring procedures. The findings from this study have the potential to guide the development of a monitoring system to help ensure users’ acceptance of future mobile hemodialysis devices.
Phased Array Ultrasonic Sector Scan Imaging of Helicopter Damper Bolts Based on Vector Coherence Factor
Authors: Huang Jingxing , Chen Ming , Kong Qingru , Xiao Liangzhong , Lu Chao , Chen Yao
Published: October 2022

Non-destructive testing of the cracks on the in-service bolt’s shank with size M18 is a challenging technical problem. Due to the weak echo energy of cracks with large buried depths, the conventional phased array ultrasonic sector scan imaging has a low signal-to-noise ratio, resulting in the effective defect echo submerged in the structural wave of bolts. This work proposes a method of phased array ultrasonic sector scan imaging based on vector coherence factors to detect the microcracks on the surface of the bolt shank. This is achieved by weighting the phased array sector scan imaging with the vector coherence factor to detect the microcracks of the in-service helicopter damper bolt. Experimental work is also carried out to contrast the SNR value of cracks at buried depths of 70 mm and 90 mm with traditional phased array ultrasonic sector scanning images. This demonstrates that the proposed phased array ultrasonic sector scan imaging based on vector coherence factors detected the cracks with a depth of 0.1 mm at the buried depth of 90 mm. The SNR value of the cracks at the buried depth 70 mm in DAS_VCF images is improved by 11.67 dB, compared with the traditional DAS images, in the case of the focus depth at 60 mm.
Effect of Compressed Sensing Rates and Video Resolutions on a PoseNet Model in an AIoT System
Authors: Kwon Hye-Min , Seo Jeongwook
Published: October 2022

To provide an artificial intelligence service such as pose estimation with a PoseNet model in an Artificial Intelligence of Things (AIoT) system, an Internet of Things (IoT) sensing device sends a large amount of data such as images or videos to an AIoT edge server. This causes serious data traffic problems in IoT networks. To mitigate these problems, we can apply compressed sensing (CS) to the IoT sensing device. However, the AIoT edge server may have poor pose estimation accuracy (i.e., pose score), because it has to recover the CS data received from the IoT sensing device and estimate human pose from the imperfectly recovered data according to CS rates. Therefore, in this paper, we analyze the effect of CS rates (from 100% to 10%) and video resolutions (1280×720, 640×480, 480×360) in the IoT sensing device on the pose score of the PoseNet model in the AIoT edge server. When only considering the meaningful range of CS rates from 100% to 50%, we found that the higher the video resolution, the lower the pose score. At the CS rate of 80%, we could reduce data traffic by 20% despite the degradation in pose score of less than about 0.03 for all video resolutions.
Using Artificial Intelligence Techniques to Predict Intrinsic Compressibility Characteristic of Clay
Authors: Abbey Samuel J. , Eyo Eyo U. , Booth Colin A.
Published: October 2022

Reconstituted clays have often provided the basis for the interpretation and modelling of the properties of natural clays. The term “intrinsic” was introduced to describe a clay remoulded or reconstituted at moisture content up to 1.5 times its liquid limit and consolidated one-dimensionally. In order to circumvent the difficulties of measuring an intrinsic constant called “intrinsic compressibility index” (C*c), a machine learning (ML) approach using traditional non-parametric tree-based and meta-heuristic ensembles was adopted in this study. Results indicated that tree-ensembles namely random decision forest (RDF) and boosted decision tree (BDT) performed better in C*c prediction (average R2 of 0.84 and root mean square error, RMSE of 0.51) compared to stand-alone models. However, models’ hyper parameters combined meta-heuristically, produced the highest accuracy (average R2 of 0.90 and root mean square error, RMSE of 0.34). The greatest capacity to distinguish between positive and negative soil classes (average accuracy of 0.95, precision and recall of 0.86) were demonstrated by meta-ensembles in multinomial classification.
Mitigating Sensor and Acquisition Method-Dependence of Fingerprint Presentation Attack Detection Systems by Exploiting Data from Multiple Devices
Authors: Micheletto Marco , Orrù Giulia , Casula Roberto , Marcialis Gian Luca
Published: October 2022

The problem of interoperability is still open in fingerprint presentation attack detection (PAD) systems. This involves costs for designers and manufacturers who intend to change sensors of personal recognition systems or design multi-sensor systems, because they need to obtain sensor-specific spoofs and retrain the system. The solutions proposed in the state of the art to mitigate the problem still require data from the target sensor and are therefore not exempt from the problem of obtaining new data. In this paper, we provide insights for the design of PAD systems thanks to an overview of an interoperability analysis on modern systems: hand-crafted, deep-learning-based, and hybrid. We investigated realistic use cases to determine the pros and cons of training with data from multiple sensors compared to training with single sensor data, and drafted the main guidelines to follow for deciding the most convenient PAD design technique depending on the intended use of the fingerprint identification/authentication system.
Evidence of Volatility Metals and Metalloids at Environment Conditions
Authors: Bortnikova Svetlana , Yurkevich Nataliya , Volynkin Sergey , Kozlov Aleksander , Makas Alexey
Published: October 2022

Tailings represent a significant risk to the environment globally, but very little is known about the composition of the near-surface air. We conducted laboratory experiments to determine the sizes of the particles and the chemical composition of the flow above the mine waste. A condensate of vapor–gas flow was collected in parallel with particle control by an aerosol diffusion spectrometer (ADS). We reveal that there were no aerosol particles bigger than 3 nm in the flow. The collected condensate contained chemical elements, ions of sulfates, chlorides, phosphates, and formates and a wide range of sulfur-, selenium-, and carbon-containing gases. The main findings of the study are the presence of the metals Zn, Cu, Fe, Al, Cd, Ni, and Ba and the metalloids As, Sb, Se, Ag, Co, Ti, and V in the true-gas phase or in the form of particles smaller than 3 nm in the air above the mine tailings. The surprising fact is that the migration of metals and metalloids in a true-gas form or in ultrafine particles (<3 nm) is possible, which opens up a new research direction on the volatile forms of chemical elements in various climatic conditions and their bioavailability and toxicity.
Comparisons Where It Matters: Using Layer-Wise Regularization to Improve Federated Learning on Heterogeneous Data
Authors: Son Ha Min , Kim Moon Hyun , Chung Tai-Myoung
Published: October 2022

Federated Learning is a widely adopted method for training neural networks over distributed data. One main limitation is the performance degradation that occurs when data are heterogeneously distributed. While many studies have attempted to address this problem, a more recent understanding of neural networks provides insight to an alternative approach. In this study, we show that only certain important layers in a neural network require regularization for effective training. We additionally verify that Centered Kernel Alignment (CKA) most accurately calculates similarities between layers of neural networks trained on different data. By applying CKA-based regularization to important layers during training, we significantly improved performances in heterogeneous settings. We present FedCKA, a simple framework that outperforms previous state-of-the-art methods on various deep learning tasks while also improving efficiency and scalability.
The Use of Carbon-Containing Compounds to Prepare Functional and Structural Composite Materials: A Review
Authors: Zemtsova Elena G. , Arbenin Andrey Yu. , Sidorov Yuri V. , Morozov Nikita F. , Korusenko Petr M. , Semenov Boris N. , Smirnov Vladimir M.
Published: October 2022

The review presents data on the synthesis, properties of carbon-containing compounds, and their application in the technology of obtaining functional and structural composites. Such materials are widely used in recent years due to their good physical and mechanical properties. The review discusses in detail the influence of the chemical composition of various carbon-containing substances and the size of the dispersed phase on the mechanical and physical properties of produced metal matrix composite. The review also concerns methods for the modern synthesis of graphene, carbon nanotubes, and metallic functional and structural composites with reinforcing carbon-containing compounds. Additionally, the results of metal matrix composite modeling are presented. They show that the improved mechanical properties of CNT–Al composites can be attributed to three factors: CNT hardening, matrix grain refinement, and layered architecture.
Reverse Guided Bone Regeneration (R-GBR) Digital Workflow for Atrophic Jaws Rehabilitation
Authors: Felice Pietro , Lizio Giuseppe , Barausse Carlo , Roccoli Lorenzo , Bonifazi Lorenzo , Pistilli Roberto , Simion Massimo , Pellegrino Gerardo
Published: October 2022

Background: Treating extended alveolar defects is challenging for their irregular shape and lack of hard and soft tissues. Virtual planned guided bone regeneration (GBR) with customized meshes aims to optimize the treatment by reducing the risk of dehiscence. The mucosa characteristics are crucial in preserving the bone graft covering and vitality. Methods: Two three-dimensional and extended defects, a mandibular posterior and anterior maxillary atrophy were reconstructed with a particulate graft and a digitally customized scaffold. The workflow entailed merging the pre-operatory clinical related data from intra-oral scanning with the radiologic ones from cone beam-CT. A final ideal prediction of the soft tissue relationship with the implant-borne prosthesis was virtually elaborated, conditioning the design of the titanium membrane fitting the bone defects. Results: A good matching between the scaffold and the bone surface was intra-operatory noted; no complications were registered in the first months of healing with complete integrity of the soft tissues above the graft. Conclusions: A careful evaluation of the soft tissues and a forecast of their final relationship with the implant and prosthesis can improve digital mesh/membrane manufacturing with a suitable healing process up to implant placement and loading, favoring peri-implant tissue stability over time.
A CBCT Evaluation of Nasal Septal Deviation and Related Nasofacial Structures after Maxillary Skeletal Expansion
Authors: Lee Hye-Jeong , Park Jae Hyun , Seo Hye Young , Choi Sung-Kwon , Chang Na-Young , Kang Kyung-Hwa , Chae Jong-Moon
Published: October 2022

Background: The aim of this study was to evaluate three-dimensional (3D) changes in nasal septal deviation (NSD) and related nasofacial structures after maxillary skeletal expansion (MSE). Methods: This retrospective study evaluated 28 patients aged 12.0–48.4 years (mean age, 20.4 ± 7.3 years; 12 males, 16 females) diagnosed with transverse maxillary deficiency and treated with MSE. Cone-beam computed tomography (CBCT) images were taken at pre-expansion (T1), post-expansion (T2), and 6-months after MSE (T3) and were reoriented. Three-dimensional coordinates (x,y,z) were constructed using nasion (N) as the reference point (0,0,0). A paired-sample t-test and an independent sample t-test were performed to investigate and compare the 3D changes of the NSD and nasofacial structures after MSE, depending on the direction and amount of NSD and the amount of midpalatal expansion (MPE). Results: NSD was alleviated at T3–T1 in the coronal plane; nasal septal length increased significantly. The absolute nasal floor (NF) angle (2.06° at T1) decreased at T2–T1 (p > 0.05) and increased at T3–T2 (p < 0.05). The midface moved forward and downward, and pogonion (Pog) and menton (Me) moved downward and backward. There were no significant differences between the higher and lower NSD groups and greater and lesser MPE groups. Conclusions: Consequently, NSD was alleviated with variable positive nasofacial changes after MSE in both the short and long term. Therefore, MSE can be used to improve or camouflage facial deformities.
Study on the Evolution and Resilience of Rail Transit Time Networks—Evidence from China
Authors: Ding Rui , Du Linyu , Du Yiming , Fu Jun , Zhu Yuqi , Zhang Yilin , Peng Lina
Published: October 2022

In the network operation and management of rail transit systems, the occurrence of unexpected events causes damage to the network structure, further hindering regional accessibility performance and the function of the system. This study is based on the rail transit operation schedules in 2009, 2013, 2016, 2019 and 2022. We construct a directional weighted rail transit time network (RNNT) with train operation time as the weight, compare the betweenness centrality, sum of the shortest time path and entropy importance, etc., and quantitatively measure the network accessibility, connectivity and its resilience evolution. The results show that the current rail transportation network in China has a “small-world” effect, and there are a few stations with strong connections. The most densely distributed intervals of travel times between pairs of nodes changes from [440, 445] to [207, 210]. The fastest and best-performing disturbance to network connectivity and accessibility performance are both caused by the betweenness disturbance strategy. When the network connectivity remains 80% effective, the ratio of failed nodes under the static betweenness centrality strategy decreases from 3.96% in 2009 to 2.31% in 2022, with weaker connections between node pairs, and their network resilience diminishes. When the network accessibility remains 80% effective, the ratio of failed nodes under the static (dynamic) betweenness centrality strategy increases from 0.13% (0.13%) in 2009 to 0.20% (0.23%) in 2022. Therefore, the rail transit network can protect the corresponding rail stations based on the station ranking of the above strategies, and this research is beneficial to rail transit network protection and structure optimization.
Double-Facet Effect of Artificial Mechanical Stress on Red Blood Cell Deformability: Implications for Blood Salvage
Authors: Tsohar Tamir , Beyth Shaul , Gural Alexander , Arbell Dan , Yedgar Saul , Barshtein Gregory
Published: October 2022

The use of intra-operative blood salvage, dialysis, and artificial organs are associated with the application of non-physiological mechanical stress on red blood cells (RBCs). To explore the effect of these procedures on red cell deformability, we determined it before and after the mechanical stress application both in an in vitro system and following a blood-saving procedure. RBC from eight healthy donors and fifteen packed RBC units were subjected to mechanical stress. RBCs from five patients undergoing orthopedic surgery were also collected. We measured the percent of undeformable cells (%UDFC) in the red cell samples using our cell flow properties image analyzer, which provides the distribution of RBC deformability in a large cell population. Mechanical stress systematically reduced the cell deformability and increased the %UDFC, while simultaneously causing hemolysis of rigid, undeformable RBCs. Ultimately, the overall result depended on the initial level of the undeformable cells; the stress-induced change in the proportion of rigid cells (Δ%UDFC) increased (Δ%UDFC > 0) when its initial value was low, and decreased (Δ%UDFC < 0) when its initial value was high. This suggests that the final impact of mechanical stress on the percent of rigid cells in the RBC population is primarily determined by their initial concentration in the sample.
Design, Implementation, and Analysis of a Block Cipher Based on a Secure Chaotic Generator
Authors: Dridi Fethi , El Assad Safwan , El Hadj Youssef Wajih , Machhout Mohsen , Lozi René
Published: October 2022

This work proposes a new secure chaos-based encryption/decryption system, operating in cipher block chaining (CBC) mode, and analyze its performance. The cryptosystem includes a robust pseudorandom number generator of chaotic sequences (PRNG-CS). A strong chaos-based S-box is proposed to perform a circular substitution operation (confusion process). This PRNG-CS consists of four discrete 1-D chaotic maps, weakly coupled by a predefined coupling matrix M, to avoid, on the one hand, the divide-and-conquer attack and, on the other hand, to improve the generated sequence’s randomness and lengths. The noun is also used in the construction of the S-box. Moreover, a 2-D modified cat map and a horizontal addition diffusion (HAD) preceded by a vertical addition diffusion (VAD) are introduced to perform the diffusion process. The security analysis and numerous simulation results of the main components (PRNG-CS and S-box) as well as the whole cryptosystem reveal that the proposed chaos-based cryptosystem holds up against various types of statistical and cryptographic attacks.
Automatic Classification of Eyewitness Messages for Disaster Events Using Linguistic Rules and ML/AI Approaches
Authors: Haider Sajjad , Mahmood Azhar , Khatoon Shaheen , Alshamari Majed , Afzal Muhammad Tanvir
Published: October 2022

Emergency response systems require precise and accurate information about an incident to respond accordingly. An eyewitness report is one of the sources of such information. The research community has proposed diverse techniques to identify eyewitness messages from social media platforms. In our previous work, we created grammar rules by exploiting the language structure, linguistics, and word relations to automatically extract feature words to classify eyewitness messages for different disaster types. Our previous work adopted a manual classification technique and secured the maximum F-Score of 0.81, far less than the static dictionary-based approach with an F-Score of 0.92. In this work, we enhanced our work by adding more features and fine-tuning the Linguistic Rules to identify feature words related to Twitter Eyewitness messages for Disaster events, named as LR-TED approach. We used linguistic characteristics and labeled datasets to train several machine learning and deep learning classifiers for classifying eyewitness messages and secured a maximum F-score of 0.93. The proposed LR-TED can process millions of tweets in real-time and is scalable to diverse events and unseen content. In contrast, the static dictionary-based approaches require domain experts to create dictionaries of related words for all the identified features and disaster types. Additionally, LR-TED can be evaluated on different social media platforms to identify eyewitness reports for various disaster types in the future.
A Systematic Review and Meta-Analysis of the Grey Matter Volumetric Changes in Mild Traumatic Brain Injuries
Authors: Mavroudis Ioannis , Chatzikonstantinou Symela , Ciobica Alin , Balmus Ioana-Miruna , Iordache Alin , Kazis Dimitrios , Chowdhury Rumana , Luca Alina-Costina
Published: October 2022

Traumatic brain injury (TBI) is currently a problematic issue of public health due to its frequency, and many of the mild cases often remain undiagnosed despite the possible predisposition to prolonged or persistent post-concussive symptomatology. It was shown here that the severity and persistence of grey matter (GM) changes following TBI could predict disease outcomes. Our aim was to conduct a voxel-wise meta-analysis to detect significant GM changes following mild TBI (mTBI) and to investigate whether these changes are associated with the duration and severity of post-concussion syndrome (PCS). A voxel-wise meta-analysis was conducted regarding the GM and white matter (WM) changes in mTBI adult patients versus healthy controls, and Seed-based d Mapping was used to correlate the data. Standard meta-analysis statistical processing was used to assess heterogeneity and publication bias. Our analysis showed significant GM volume increases in the left medial cingulate/paracingulate gyri, the middle frontal gyrus, and the right caudate nucleus of the mTBI patients and significant volume loss in the thalamus, the frontal lobe, and the temporal lobe. These changes could potentially be associated with PCS that some mTBI later patients develop as a result to the injury or other compensatory changes. Additional studies considering long-term GM changes in mTBI patients and their potential relationship to PCS could provide further insight into the pathophysiological similarities and correlations between mTBI and PCS.
Diagnostics in Tire Retreading Based on Classification with Fuzzy Inference System
Authors: Angles Medina Gian Carlo , Rosas Paredes Karina , Zúñiga Carnero Manuel , Sulla-Torres José
Published: October 2022

Currently, there are tire retreading companies whose evaluations are not wholly accurate; due to various factors, sometimes customers are forced to agree to what is decided, and this means that the customer can sometimes pay for services that do not necessarily guarantee the correct operation of the tire or, failing that, shorten its life. This work aims to develop a tire diagnostic system that allows for evaluating a tire’s faults and can thus be more precise when determining if it needs retreading or a change process. The diagnostic system is focused on demonstrating that fuzzy logic can be applied in diagnosing the condition of tires. The methodology consisted of determining the variables to be considered in the evaluation of tires, such as blowing out, flange breakage, band failure, and patching, then applying fuzzy logic. Subsequently, the execution tests of the built diagnostic software were carried out for its validation in a case study of a tire retreading company. The result was a margin of error of 1.6% accuracy versus 5.6% from the operator experience. The conclusion was that fuzzy logic could be applied correctly in the field of tire retreading, providing substantial savings in time and resources for related companies, as well as giving customers confidence since, by using more accurate results, the diagnostic system will make the tire evaluation efficient.
Sound Source Localization Indoors Based on Two-Level Reference Points Matching
Authors: Wang Shuopeng , Yang Peng , Sun Hao
Published: October 2022

A dense sample point layout is the conventional approach to ensure the positioning accuracy for fingerprint-based sound source localization (SSL) indoors. However, mass reference point (RPs) matching of online phases may greatly reduce positioning efficiency. In response to this compelling problem, a two-level matching strategy is adopted to shrink the adjacent RPs searching scope. In the first-level matching process, two different methods are adopted to shrink the search scope of the online phase in a simple scene and a complex scene. According to the global range of high similarity between adjacent samples in a simple scene, a greedy search method is adopted for fast searching of the sub-database that contains the adjacent RPs. Simultaneously, in accordance with the specific local areas’ range of high similarity between adjacent samples in a complex scene, the clustering method is used for database partitioning, and the RPs search scope can be compressed by sub-database matching. Experimental results show that the two-level RPs matching strategy can effectively improve the RPs matching efficiency for the two different typical indoor scenes on the premise of ensuring the positioning accuracy.
Removal Behavior of Heavy Metals from Aqueous Solutions via Microbially Induced Carbonate Precipitation Driven by Acclimatized Sporosarcina pasteurii
Authors: Li Xinxin , Wang Yan , Tang Jiajie , Li Keke
Published: October 2022

Microbially induced carbonate precipitation (MICP) driven by Sporosarcina pasteurii was highly efficient for heavy metal (i.e., Cd2+, Cu2+ and Pb2+) removal in the range of 50 to 800 mg/L. Sporosarcina pasteurii bacteria were sequentially inoculated in nutrient broths amended with increased concentrations of heavy metals separately to improve the resistance to heavy metal environments. In the absence of Ca2+, the increasing urea concentration was conducive to Cd2+ removal with the best removal ratio 89.9–99.7% at a urea concentration of 2.0 mol/L, but had little positive effect on Cu2+ and Pb2+ removal, with a removal ratio of 62.6–64.4% and 71.4–97.6%, respectively, at a urea concentration of 0.5 mol/L. The heavy metal coprecipitated with Ca2+, leading to much more effective heavy metal removal, and the removal efficiency of Cd2+, Cu2+ and Pb2+ could reach 98.0–99.0, 78.1–82.1 and 98.0–100.0%, respectively. The Cu2+ deposit aggregated and cemented to form clusters, different from Cd2+ and Pb2+ deposits with comparatively dispersed microstructure. For all the three heavy metal precipitates, the predominant mineral was identified as calcite, the most thermodynamically stable polymorph of CaCO3.
Comparison between Different Re-Entry Technologies for Debris Mitigation in LEO
Authors: Barato Francesco
Published: October 2022

The population of satellites in Low Earth Orbit is predicted to growth exponentially in the next decade due to the proliferation of small-sat constellations. Consequently, the probability of collision is expected to increase dramatically, possibly leading to a potential Kessler syndrome situation. It is therefore necessary to strengthen all the technologies required for collision avoidance and end-of-life disposal of new satellites, together with active debris removal of current and potential future dead satellites. Both situations require the lowering of the altitude of a satellite up to re-entry. In this paper several de-orbiting technologies are evaluated: natural decay, chemical propulsion (solid and liquid), electric propulsion, drag sail, electrodynamic tether, and combinations of the previous ones. The comparison considers the initial altitude, system mass, de-orbiting time, collision probability during descent, reliability, and technological limits. Differences between active debris removal and satellite end-of-life self-disposal are taken into account. Moreover, the different types of re-entry, controlled vs. non-controlled, expendable vs. reusable system, demisable vs. non-demisable system are also discussed. Finally, the possibility to operate the satellite in Very Low Earth Orbits with a propulsion system for drag compensation and passive re-entry at end of life is investigated.