bluuebunny/crossref_metadata_2025 huggingface dataset:
Evolution of the Reaction and Alteration of Granite with Ordinary Portland Cement Leachates: Sequential Flow Experiments and Reactive Transport Modelling
Authors: Bateman Keith , Murayama Shota , Hanamachi Yuji , Wilson James , Seta Takamasa , Amano Yuki , Kubota Mitsuru , Ohuchi Yuji , Tachi Yukio
Published: July 2022

The construction of a repository for the geological disposal of radioactive waste will include the use of cement-based materials. Following closure, groundwater will saturate the repository, and the extensive use of cement will result in the development of a highly alkaline porewater, pH > 12.5; this fluid will migrate into and react with the host rock. The chemistry of the fluid will evolve over time, initially with high Na and K concentrations, evolving to a Ca-rich fluid, and finally returning to the natural background groundwater composition. This evolving chemistry will affect the long-term performance of the repository, altering the physical and chemical properties, including radionuclide behaviour. Understanding these changes forms the basis for predicting the long-term evolution of the repository. This study focused on the determination of the nature and extent of the chemical reaction, as well as the formation and persistence of secondary mineral phases within a granite, comparing data from sequential flow experiments with the results of reactive transport modelling. The reaction of the granite with the cement leachates resulted in small changes in pH and the precipitation of calcium aluminium silicate hydrate (C-(A-)S-H) phases of varying compositions, of greatest abundance with the Ca-rich fluid. As the system evolved, secondary C-(A-)S-H phases redissolved, partly replaced by zeolites. This general sequence was successfully simulated using reactive transport modelling.
Design, Synthesis and Antifungal Evaluation of Novel Pyrylium Salt In Vitro and In Vivo
Authors: Zhang Yue , Li Qiuhao , Chao Wen , Qin Yulin , Chen Jiayan , Wang Yingwen , Liu Runhui , Lv Quanzhen , Wang Jinxin
Published: July 2022

Nowadays, discovering new skeleton antifungal drugs is the direct way to address clinical fungal infections. Pyrylium salt SM21 was screened from a library containing 50,240 small molecules. Several studies about the antifungal activity and mechanism of SM21 have been reported, but the structure–activity relationship of pyrylium salts was not clear. To explore the chemical space of antifungal pyrylium salt SM21, a series of pyrylium salt derivatives were designed and synthesized. Their antifungal activity and structure-activity relationships (SAR) were investigated. Compared with SM21, most of the synthesized compounds exhibited equivalent or improved antifungal activities against Candida albicans in vitro. The synthesized compounds, such as XY10, XY13, XY14, XY16 and XY17 exhibited comparable antifungal activities against C. albicans with MIC values ranging from 0.47 to 1.0 μM. Fortunately, a compound numbered XY12 showed stronger antifungal activities and lower cytotoxicity was obtained. The MIC of compound XY12 against C. albicans was 0.24 μM, and the cytotoxicity decreased 20-fold as compared to SM21. In addition, XY12 was effective against fluconazole-resistant C. albicans and other pathogenic Candida species. More importantly, XY12 could significantly increase the survival rate of mice with a systemic C. albicans infection, which suggested the good antifungal activities of XY12 in vitro and in vivo. Our results indicated that structural modification of pyrylium salts could lead to the discovery of new antifungal drugs.
Dimethyl Sulfoxide: A Bio-Friendly or Bio-Hazard Chemical? The Effect of DMSO in Human Fibroblast-like Synoviocytes
Authors: Gallardo-Villagrán Manuel , Paulus Lucie , Leger David Yannick , Therrien Bruno , Liagre Bertrand
Published: July 2022

The effect of dimethyl sulfoxide (DMSO) in rheumatoid arthritis (RA) human fibroblast-like synoviocytes (FLSs) has been studied on five different samples harvested from the joints (fingers, hands and pelvis) of five women with RA. At high concentrations (>5%), the presence of DMSO induces the cleavage of caspase-3 and PARP-1, two phenomena associated with the cell death mechanism. Even at a 0.5% concentration of DMSO, MTT assays show a strong toxicity after 24 h exposure (≈25% cell death). Therefore, to ensure a minimum impact of DMSO on RA FLSs, our study shows that the concentration of DMSO has to be below 0.05% to be considered safe.
Evaluation of Anthelmintic and Anti-Inflammatory Activity of 1,2,4-Triazole Derivatives
Authors: Paprocka Renata , Kołodziej Przemysław , Wiese-Szadkowska Małgorzata , Helmin-Basa Anna , Bogucka-Kocka Anna
Published: July 2022

Parasitic diseases, caused by intestinal helminths, remain a very serious problem in both human and veterinary medicine. While searching for new nematicides we examined a series of 1,2,4-triazole derivatives 9–22, obtained during reactions of N3-substituted amidrazones with itaconic anhydride. Two groups of compounds, 9–16 and 17–22, differed in the position of the double bond on the methacrylic acid moiety. The toxicity of derivatives 9–22 and the anti-inflammatory activity of 12 and 19–22 were studied on peripheral blood mononuclear cells (PBMC). Antiproliferative activity of compounds 12 and 19–22 was tested cytometrically in PBMC cultures stimulated by phytohemagglutinin. The influence of derivatives 12 and 19–22 on the TNF-α, IL-6, IL-10 and IFN-γ production was determined by ELISA in lipopolysaccharide-stimulated PBMC cultures. Anthelmintic activity of compounds 10–22 was studied in the Rhabditis sp. nematodes model. Most compounds (11–22) proved to be non-toxic to human PBMC. Derivatives 19–22 showed anti-inflammatory activity by inhibiting the proliferation of lymphocytes. Moreover, compounds 12 and 19–22 significantly reduced the production of TNF-α and derivatives 19–21 decreased the level of INF-γ. The strongest anti-inflammatory activity was observed for compound 21. Compounds 12 and 14 demonstrated anthelmintic activity higher than albendazole and may become promising candidates for anthelmintic drugs.
Localized Nanopore Fabrication via Controlled Breakdown
Authors: Ying Cuifeng , Ma Tianji , Xu Lei , Rahmani Mohsen
Published: July 2022

Nanopore sensors provide a unique platform to detect individual nucleic acids, proteins, and other biomolecules without the need for fluorescent labeling or chemical modifications. Solid-state nanopores offer the potential to integrate nanopore sensing with other technologies such as field-effect transistors (FETs), optics, plasmonics, and microfluidics, thereby attracting attention to the development of commercial instruments for diagnostics and healthcare applications. Stable nanopores with ideal dimensions are particularly critical for nanopore sensors to be integrated into other sensing devices and provide a high signal-to-noise ratio. Nanopore fabrication, although having benefited largely from the development of sophisticated nanofabrication techniques, remains a challenge in terms of cost, time consumption and accessibility. One of the latest developed methods—controlled breakdown (CBD)—has made the nanopore technique broadly accessible, boosting the use of nanopore sensing in both fundamental research and biomedical applications. Many works have been developed to improve the efficiency and robustness of pore formation by CBD. However, nanopores formed by traditional CBD are randomly positioned in the membrane. To expand nanopore sensing to a wider biomedical application, controlling the localization of nanopores formed by CBD is essential. This article reviews the recent strategies to control the location of nanopores formed by CBD. We discuss the fundamental mechanism and the efforts of different approaches to confine the region of nanopore formation.
Design of Multifunctional Tunable Metasurface Assisted by Elastic Substrate
Authors: Li Jing , Fan Hongjie , Ye Han , Wu Tiesheng , Sun Yuhang , Wang Xueyu , Liu Yumin
Published: July 2022

Metasurfaces with both multifunctionality and tunability hold great application potential in next-generation optical devices. In this paper, we propose a stretchable metasurface composed of arrays of identical dielectric rectangular resonators embedded in the polydimethylsiloxane (PDMS) substrate. It is shown that the metasurface possesses three functions at the operating wavelength of 532 nm. The switching of functions can be implemented by changing the period Px of the metasurface, induced by stretching the PDMS substrate along the x-direction. When the period Px is less than the operating wavelength of 532 nm, the behavior of metasurface can switch between transmissive window and reflective mirror. When the period Px of the metasurface varies from 532 nm to 700 nm, the metasurface act as a dynamic equal-power beam splitter with conversion efficiency higher than 90%, and the corresponding splitting angle can be adjusted from 90° to around 49.5°. Moreover, we achieve the switching of transmissive window/reflective mirror/split-ratio-variable splitter based on the metasurface consisting of arrays of identical L-shaped resonators embedded in the PDMS substrate.
Numerical Study of Lid-Driven Hybrid Nanofluid Flow in a Corrugated Porous Cavity in the Presence of Magnetic Field
Authors: Maneengam Apichit , Bouzennada Tarek , Abderrahmane Aissa , Guedri Kamel , Weera Wajaree , Younis Obai , Bouallegue Belgacem
Published: July 2022

The lid-driven top wall’s influence combined with the side walls’ waviness map induce the mixed convection heat transfer, flow behavior, and entropy generation of a hybrid nanofluid (Fe3O4–MWCNT/water), a process analyzed through the present study. The working fluid occupies a permeable cubic chamber and is subjected to a magnetic field. The governing equations are solved by employing the GFEM method. The results show that the magnetic force significantly affects the working fluid’s thermal and flow behavior, where the magnetic force’s perpendicular direction remarkably improves the thermal distribution at Re = 500. Also, increasing Ha and decreasing Re drops both the irreversibility and the heat transfer rate. In addition, the highest undulation number on the wavy-sided walls gives the best heat transfer rate and the highest irreversibility.
Homeobox 27, a Homeodomain Transcription Factor, Confers Tolerances to CMV by Associating with Cucumber Mosaic Virus 2b Protein
Authors: Rattan Usha Kumari , Kumar Surender , Kumari Reenu , Bharti Monika , Hallan Vipin
Published: July 2022

Transcription factors (TFs) play an important role in plant development; however, their role during viral infection largely remains unknown. The present study was designed to uncover the role transcription factors play in Cucumber mosaic virus (CMV) infection. During the screening of an Arabidopsis thaliana (Col-0) transcription factor library, using the CMV 2b protein as bait in the yeast two-hybrid system, the 2b protein interacted with Homeobox protein 27 (HB27). HB27 belongs to the zinc finger homeodomain family and is known to have a regulatory role in flower development, and responses to biotic and abiotic stress. The interaction between CMV 2b and HB27 proteins was further validated using in planta (bimolecular fluorescence complementation assay) and in vitro far-Western blotting (FWB) methods. In the bimolecular fluorescence complementation assay, these proteins reconstituted YFP fluorescence in the nucleus and the cytoplasmic region as small fluorescent dots. In FWB, positive interaction was detected using bait anti-MYC antibody on the target HB27-HA protein. During CMV infection, upregulation (~3-fold) of the HB27 transcript was observed at 14 days post-infection (dpi) in A. thaliana plants, and expression declined to the same as healthy plants at 21 dpi. To understand the role of the HB27 protein during CMV infection, virus accumulation was determined in HB27-overexpressing (HB27 OE) and knockout mutants. In HB27-overexpressing lines, infected plants developed mild symptoms, accumulating a lower virus titer at 21 dpi compared to wild-type plants. Additionally, knockout HB27 mutants had more severe symptoms and a higher viral accumulation than wild-type plants. These results indicate that HB27 plays an important role in the regulation of plant defense against plant virus infection.
Gurltia paralysans: A Neglected Angio-Neurotropic Parasite of Domestic Cats (Felis catus) and Free-Ranging Wild Felids (Leopardus spp.) in South America
Authors: Rojas-Barón Lisbeth , Taubert Anja , Hermosilla Carlos , Gómez Marcelo , Moroni Manuel , Muñoz Pamela
Published: July 2022

Gurltia paralysans is a neglected and re-emerging metastrongyloid angio-neurotropic nematode causing severe chronic meningomyelitis in domestic cats (Felis catus) as well as in free-ranging small wild felids such as kodkods (Leopardus guigna), margays (Leopardus wiedii) and the northern tiger cat (Leopardus triginus) in South America. Within these definitive hosts (DH), adult males and females of G. paralysans parasitize the leptomeningeal veins of the subarachnoid space and/or the meningeal veins of spinal cord parenchyma, inducing vascular alterations. Feline gurltiosis has been associated with progressive thrombophlebitis of the meningeal veins, resulting in ambulatory paraparesis, paraplegia, ataxia, hindlimb proprioceptive deficit, uni- or bilateral hyperactive patellar reflexes, faecal and urinary incontinence, and tail paralysis. The complete life cycle of G. paralysans has not been elucidated yet, but most probably involves gastropods as obligate intermediate hosts (IH). In terms of epidemiology, G. paralysans infections in domestic and wild felids are scattered around various South American countries, with hyperendemic areas in southern parts of Chile. Etiological diagnosis of G. paralysans still represents a challenge for clinicians due to a lack of evidence of the excretion of either eggs or larvae in faeces or in other body fluids. Diagnosis is based on clinical neurological signs, imaging findings through computed tomography (CT), myelography, magnetic resonance imaging (MRI), and post mortem examination. Nonetheless, novel diagnostic tools have been developed, including semi-nested PCR for detecting circulating G. paralysans DNA in the cerebrospinal fluid, serum and blood samples as well as in serological diagnostic kits detecting parasite-derived antigens, but these need validation for routine usage. The hypothetical life cycle of G. paralysans is addressed in this article, including the exogenous stages (i.e., eggs, and first- (L1), second- (L2) and third-stage (L3) larvae) and obligate gastropod IH and/or paratenic hosts (PH), and we propose possible anatomical migration routes of infective L3 that reach the leptomeningeal veins in vivo. Finally, the pro-inflammatory endothelium- and leukocyte-derived innate immune reactions of the host against G. paralysans, which most likely result in thrombophlebitis and meningomyelitis, are briefly touched on.
Effects of Periodontal Splints on Biomechanical Behaviors in Compromised Periodontal Tissues and Cement Layer: 3D Finite Element Analysis
Authors: Liu Yuchen , Fang Ming , Zhao Ruifeng , Liu Hengyan , Tian Min , Zhong Sheng , Bai Shizhu
Published: July 2022

Background: In this study, we evaluated the effect of periodontal splints made from different materials on the stress distributions in compromised periodontal tissues and cement layers, using a computer simulation of mastication. Methods: Twenty-five 3D models were created for a segment of mandibular teeth with different periodontal splints bilaterally extended to the canines. The models were divided into five groups according to the different materials and thicknesses (mm) of the splints: the non-splinted group, PEEK 0.7 group, PEEK 1.0 group, FRC group, and titanium group. Each group was subdivided based on five bone loss levels. Tooth 41 of each model was subjected to vertical and oblique (θ = 45°) static loads of 100 N, respectively, onto the incisal edge. The von Mises stresses and maximum principal stress were analyzed using Abaqus software. Results: Oblique loading resulted in higher stresses on periodontal tissues, cement layers, and splints than those caused by vertical loading. The lower the supporting bone level, the greater the stress difference between the splinted groups and the non-splinted group. In model 133,331, with severe bone loss, the maximum von Mises stress values on the alveolar bone in tooth 41 under oblique loading dramatically decreased from 406.4 MPa in the non-splinted group to 28.62 MPa in the PEEK group and to 9.59 MPa in the titanium group. The four splinted groups presented similar stress distributions in periodontal tissues. The lowest stress level on the splint was observed in the PEEK 0.7 group, and the highest stress level was transferred to the cement layer in this group. Stress concentrations were primarily exhibited at the connectors near the load-carrying area. Conclusions: The tested splinted groups were all effective in distributing the loads on periodontal tissues around splinted teeth with similar patterns. Using splinting materials with low elastic moduli reduced the stress concentration at the splint connectors, whereas the tensile stress concentration was increased in the cement layer. Thus, the use of adhesive cement with a higher elastic modulus is recommended when applying less rigid PEEK splints.
Study of the Polishing Characteristics by Abrasive Flow Machining with a Rotating Device
Authors: Cheng Ken-Chuan , Wang A-Cheng , Chen Kuan-Yu , Huang Chien-Yao
Published: July 2022

Since only uni-direction motion is produced by traditional abrasive flow machining (AFM), so the polishing effects of the inner hole is not easy to achieve uniform roughness of the whole surface after polishing. Therefore, in this study, a rotating device with a DC servo motor was set up in the AFM to increase the tangential forces on the machining surface, and therefore, improve the uniform surface roughness and polishing efficiency. The rotating device was designed by a group of transmission gear set and a DC servo motor to create a rotational finishing path for the abrasive medium. The rotational motion of an abrasive can create different tangential forces on the working surface, inducing a more complex polishing path than that of traditional AFM. In addition to rotational speed, a servo motor can also change rotation directions in one working process, causing an abrasive medium to create many irregular finishing paths in the AFM. The experimental results showed that the surface roughness of the workpiece was significantly decreased with an increase in the rotational speed. Additionally, the results also showed that the surface roughness (SR) of the inner hole decreased from 0.61 μm Ra to 0.082 μm Ra after 20 machining cycles, the surface roughness improvement rate reached 87% at 15 rpm rotational speed, by applying a 1.5:1 silicone gel/abrasive concentration ratio and #60 abrasive mesh in the experiments. This study created excellent polishing efficiency by using a servo rotational device with AFM to produce good surface quality.
Spray Drying of PEG6000 Suspension: Reaction Engineering Approach (REA) Modeling of Single Droplet Drying Kinetics
Authors: Al Zaitone Belal , Al-Zahrani Abdulrahim , Ahmed Osama , Saeed Usman , Taimoor Aqeel Ahmad
Published: July 2022

The spray drying technique is suitable for different kinds of liquid dispersions and can be easily optimized to produce solid particles with tailored properties. The spray drying technique is a complex process. As an example, it is difficult to track drying kinetics, shape, and morphological changes on the scale of a single droplet. To better understand the effect of drying process variables on dried particle formation, it is useful to observe the drying of single droplets. Fundamental processes, such as mass and heat transfer, can then be easily monitored and compared with theoretical models. Acoustic levitation enables droplet/particle suspension in the air without any mechanical contact. Experiments in the acoustic levitator can be used to mimic the drying process in the spray dryer. The drying kinetics of single droplets of PEG6000 into solid particles was studied. Droplets with an initial polymer concentration (PEG6000 aqueous solution of 5%, 10%, and 15% (w/w)) were investigated at different gas drying temperatures. The size of the droplet, moisture content, and the shape evolution of the droplet/particle during the drying process were studied. The experimental drying curves were compared with the Reaction Engineering Approach (REA). The REA models were shown to provide a very good agreement for drying behavior, with a relative error of about ±3% between the initial and predicted droplet mass. This model can be implemented into the large-scale modeling of spray drying using Computational Fluid Dynamics (CFD).
GNSSseg, a Statistical Method for the Segmentation of Daily GNSS IWV Time Series
Authors: Quarello Annarosa , Bock Olivier , Lebarbier Emilie
Published: July 2022

Homogenization is an important and crucial step to improve the usage of observational data for climate analysis. This work is motivated by the analysis of long series of GNSS Integrated Water Vapour (IWV) data, which have not yet been used in this context. This paper proposes a novel segmentation method called segfunc that integrates a periodic bias and a heterogeneous, monthly varying, variance. The method consists in estimating first the variance using a robust estimator and then estimating the segmentation and periodic bias iteratively. This strategy allows for the use of the dynamic programming algorithm, which is the most efficient exact algorithm to estimate the change point positions. The performance of the method is assessed through numerical simulation experiments. It is implemented in the R package GNSSseg, which is available on the CRAN. This paper presents the application of the method to a real data set from a global network of 120 GNSS stations. A hit rate of 32% is achieved with respect to available metadata. The final segmentation is made in a semi-automatic way, where the change points detected by three different penalty criteria are manually selected. In this case, the hit rate reaches 60% with respect to the metadata.
Assessment of Socket Pressure during Walking in Rapid Fit Prosthetic Sockets
Authors: Sasaki Kazuhiko , Guerra Gary , Lei Phyu Win , Chaisumritchoke Sirarat , Sutdet Prawina , Kaewtip Sirintip
Published: July 2022

(1) Background: A sustainable casting system that combines the use of a polystyrene bag, a prosthetic liner and a vacuum system was developed to reduce fabrication time while maintaining comfort for the trans-tibial prosthesis user. (2) Methods: Eight prosthetists (28.7 ± 8.25 years old) fit ten trans-tibial prosthesis wearers (46 ± 12.4 years old) with two types of total surface bearing (TSB) prostheses; a polystyrene bead (PS) prosthesis and a plaster of paris (POP) prosthesis. Duration of casting and combined mean peak pressure was measured at six locations on the residual limb using Force Sensing Resistors (FSR). A pressure uniformity score (%) was determined. Socket Comfort Scale (SCS) was also measured. (3) Results: Duration of casting for the POP method was 64.8 ± 9.53 min and 7.8 ± 2 min for the PS method, (p = 0.006). Pressure uniformity in the POP prosthesis was 79.3 ± 6.54 and 81.7 ± 5.83 in the PS prosthesis (p = 0.027). SCS in both prosthesis types were equivalent. (4) Conclusion: A rapid fit PS prosthesis was developed, with significantly shorter duration than the traditional POP method. Socket pressure uniformity was confirmed and improved in the PS method. Socket comfort was equal between the two prothesis types.
Research on Random Drift Model Identification and Error Compensation Method of MEMS Sensor Based on EEMD-GRNN
Authors: Shi Yonglei , Fang Liqing , Xue Zhanpu , Qi Ziyuan
Published: July 2022

Random drift error is one of the important factors of MEMS (micro-electro-mechanical-system) sensor output error. Identifying and compensating sensor output error is an important means to improve sensor accuracy. In order to reduce the impact of white noise on neural network modeling, the ensemble empirical mode decomposition (EEMD) method was used to separate white noise from the original signal. The drift signal after noise removal is modeled by GRNN (general regression neural network). In order to achieve a better modeling effect, cross-validation and parameter optimization algorithms were designed to obtain the optimal GRNN model. The algorithm is used to model and compensate errors for the generated random drift signal. The results show that the mean value of original signal decreases from 0.1130 m/s2 to −1.2646 × 10−7 m/s2, while the variance decreases from 0.0133 m/s2 to 1.0975 × 10−5 m/s2. In addition, the displacement test was carried out by MEMS acceleration sensor. Experimental results show that the displacement measurement accuracy is improved from 95.64% to 98.00% by compensating the output error of MEMS sensor. By comparing the GA-BP (genetic algorithm-back propagation) neural network and the polynomial fitting method, the EEMD-GRNN method proposed in this paper can effectively identify and compensate for complex nonlinear drift signals.
Automated Chicago Classification for Esophageal Motility Disorder Diagnosis Using Machine Learning
Authors: Surdea-Blaga Teodora , Sebestyen Gheorghe , Czako Zoltan , Hangan Anca , Dumitrascu Dan Lucian , Ismaiel Abdulrahman , David Liliana , Zsigmond Imre , Chiarioni Giuseppe , Savarino Edoardo , Leucuta Daniel Corneliu , Popa Stefan Lucian
Published: July 2022

The goal of this paper is to provide a Machine Learning-based solution that can be utilized to automate the Chicago Classification algorithm, the state-of-the-art scheme for esophageal motility disease identification. First, the photos were preprocessed by locating the area of interest—the precise instant of swallowing. After resizing and rescaling the photos, they were utilized as input for the Deep Learning models. The InceptionV3 Deep Learning model was used to identify the precise class of the IRP. We used the DenseNet201 CNN architecture to classify the images into 5 different classes of swallowing disorders. Finally, we combined the results of the two trained ML models to automate the Chicago Classification algorithm. With this solution we obtained a top-1 accuracy and f1-score of 86% with no human intervention, automating the whole flow, from image preprocessing until Chicago classification and diagnosis.
SNR Prediction with ANN for UAV Applications in IoT Networks Based on Measurements
Authors: Cardoso Caio M. M. , Barros Fabrício J. B. , Carvalho Joel A. R. , Machado Artur A. , Cruz Hugo A. O. , de Alcântara Neto Miércio C. , Araújo Jasmine P. L.
Published: July 2022

The 5G deployment brings forth the usage of Unmanned Aerial Vehicles (UAV) to assist wireless networks by providing improved signal coverage, acting as relays or base-stations. Another technology that could help achieve 5G massive machine-type communications (mMtc) goals is the Long Range Wide-Area Network (LoRaWAN) communication protocol. This paper studied these complementary technologies, LoRa and UAV, through measurement campaigns in suburban, densely forested environments. Downlink and uplink communication at different heights and spreading factors (SF) demonstrate distinct behavior through our analysis. Moreover, a neural network was trained to predict the measured signal-to-noise ratio (SNR) behavior and results compared with SNR regression models. For the downlink scenario, the neural network results show a root mean square error (RMSE) variation between 1.2322–1.6623 dB, with an error standard deviation (SD) less than 1.6730 dB. For the uplink, the RMSE variation was between 0.8714–1.3891 dB, with an error SD less than 1.1706 dB.
WLAN RSS-Based Fingerprinting for Indoor Localization: A Machine Learning Inspired Bag-of-Features Approach
Authors: Altaf Khattak Sohaib Bin , Fawad  , Nasralla Moustafa M. , Esmail Maged Abdullah , Mostafa Hala , Jia Min
Published: July 2022

Location-based services have permeated Smart academic institutions, enhancing the quality of higher education. Position information of people and objects can predict different potential requirements and provide relevant services to meet those needs. Indoor positioning system (IPS) research has attained robust location-based services in complex indoor structures. Unforeseeable propagation loss in complex indoor environments results in poor localization accuracy of the system. Various IPSs have been developed based on fingerprinting to precisely locate an object even in the presence of indoor artifacts such as multipath and unpredictable radio propagation losses. However, such methods are deleteriously affected by the vulnerability of fingerprint matching frameworks. In this paper, we propose a novel machine learning framework consisting of Bag-of-Features and followed by a k-nearest neighbor classifier to categorize the final features into their respective geographical coordinate data. BoF calculates the vocabulary set using k-mean clustering, where the frequency of the vocabulary in the raw fingerprint data represents the robust final features that improve localization accuracy. Experimental results from simulation-based indoor scenarios and real-time experiments demonstrate that the proposed framework outperforms previously developed models.
Accounting for Viscoelasticity When Interpreting Nano-Composite High-Deflection Strain Gauges
Authors: Baker Spencer A. , McFadden McKay D. , Bowden Emma E. , Bowden Anton E. , Mitchell Ulrike H. , Fullwood David T.
Published: July 2022

High-deflection strain gauges show potential as economical and user-friendly sensors for capturing large deformations. The interpretation of these sensors is much more complex than that of conventional strain gauges due to the viscoelastic nature of strain gauges. This research endeavor developed and tested a model for interpreting sensor outputs that includes the time-dependent nature of strain gauges. A model that captures the effect of quasi-static strains was determined by using a conventional approach of fitting an equation to observed data. The dynamic relationship between the strain and the resistance was incorporated by superimposing dynamic components onto the quasi-static model to account for spikes in resistances that accompany each change in sensor strain and subsequent exponential decays. It was shown that the model can be calibrated for a given sensor by taking two data points at known strains. The resulting sensor-specific model was able to interpret strain-gauge electrical signals during a cyclical load to predict strain with an average mean absolute error (MAE) of 1.4% strain, and to determine the strain rate with an average MAE of 0.036 mm/s. The resulting model and tuning procedure may be used in a wide range of applications, such as biomechanical monitoring and analysis.
Comparison of Three 3D Segmentation Software Tools for Hip Surgical Planning
Authors: Mandolini Marco , Brunzini Agnese , Facco Giulia , Mazzoli Alida , Forcellese Archimede , Gigante Antonio
Published: July 2022

In hip arthroplasty, preoperative planning is fundamental to reaching a successful surgery. Nowadays, several software tools for computed tomography (CT) image processing are available. However, research studies comparing segmentation tools for hip surgery planning for patients affected by osteoarthritic diseases or osteoporotic fractures are still lacking. The present work compares three different software from the geometric, dimensional, and usability perspectives to identify the best three-dimensional (3D) modelling tool for the reconstruction of pathological femoral heads. Syngo.via Frontier (by Siemens Healthcare) is a medical image reading and post-processing software that allows low-skilled operators to produce prototypes. Materialise (by Mimics) is a commercial medical modelling software. 3D Slicer (by slicer.org) is an open-source development platform used in medical and biomedical fields. The 3D models reconstructed starting from the in vivo CT images of the pathological femoral head are compared with the geometries obtained from the laser scan of the in vitro bony specimens. The results show that Mimics and 3D Slicer are better for dimensional and geometric accuracy in the 3D reconstruction, while syngo.via Frontier is the easiest to use in the hospital setting.
Non-Contact Breathing Monitoring Using Sleep Breathing Detection Algorithm (SBDA) Based on UWB Radar Sensors
Authors: Husaini Muhammad , Kamarudin Latifah Munirah , Zakaria Ammar , Kamarudin Intan Kartika , Ibrahim Muhammad Amin , Nishizaki Hiromitsu , Toyoura Masahiro , Mao Xiaoyang
Published: July 2022

Ultra-wideband radar application for sleep breathing monitoring is hampered by the difficulty of obtaining breathing signals for non-stationary subjects. This occurs due to imprecise signal clutter removal and poor body movement removal algorithms for extracting accurate breathing signals. Therefore, this paper proposed a Sleep Breathing Detection Algorithm (SBDA) to address this challenge. First, SBDA introduces the combination of variance feature with Discrete Wavelet Transform (DWT) to tackle the issue of clutter signals. This method used Daubechies wavelets with five levels of decomposition to satisfy the signal-to-noise ratio in the signal. Second, SBDA implements a curve fit based sinusoidal pattern algorithm for detecting periodic motion. The measurement was taken by comparing the R-square value to differentiate between chest and body movements. Last but not least, SBDA applied the Ensemble Empirical Mode Decomposition (EEMD) method for extracting breathing signals before transforming the signal to the frequency domain using Fast Fourier Transform (FFT) to obtain breathing rate. The analysis was conducted on 15 subjects with normal and abnormal ratings for sleep monitoring. All results were compared with two existing methods obtained from previous literature with Polysomnography (PSG) devices. The result found that SBDA effectively monitors breathing using IR-UWB as it has the lowest average percentage error with only 6.12% compared to the other two existing methods from past research implemented in this dataset.
RBF Neural Network Sliding Mode Control for Passification of Nonlinear Time-Varying Delay Systems with Application to Offshore Cranes
Authors: Jiang Baoping , Liu Dongyu , Karimi Hamid Reza , Li Bo
Published: July 2022

This paper is devoted to studying the passivity-based sliding mode control for nonlinear systems and its application to dock cranes through an adaptive neural network approach, where the system suffers from time-varying delay, external disturbance and unknown nonlinearity. First, relying on the generalized Lagrange formula, the mathematical model for the crane system is established. Second, by virtue of an integral-type sliding surface function and the equivalent control theory, a sliding mode dynamic system can be obtained with a satisfactory dynamic property. Third, based on the RBF neural network approach, an adaptive control law is designed to ensure the finite-time existence of sliding motion in the face of unknown nonlinearity. Fourth, feasible easy-checking linear matrix inequality conditions are developed to analyze passification performance of the resulting sliding motion. Finally, a simulation study is provided to confirm the validity of the proposed method.
Gender and Ethnicity: The Role of Successful Women in Promoting Equality and Social Change
Authors: Ferreira Raquel Alexandra , Santos Maria Helena
Published: July 2022

This article analyzes the experiences and strategies of white and black women in positions of some power, in which they are able to strive to reduce inequalities and promote social change. From a qualitative perspective, this seeks to open the discussions around the possible applications of intersectionality between gender and “race”/ethnicity for studying the “tokenism phenomenon”. The results reveal six major themes that demonstrate how, while both white and black women share negative consequences of tokenism, the intersections of gender and “race”/ethnicity create dynamics that make black women’s experiences unique. Overall, we may therefore conclude the interviewees represent “agents of change” and deploy their power to promote equality in a variety of ways.
Sexual and Gender-Based Violence and Vulnerability to HIV Infection in Uganda: Evidence from Multilevel Modelling of Population-Level HIV/AIDS Data
Authors: Igulot Patrick
Published: July 2022

Background: Sexual and gender-based violence (SGBV) is highly prevalent in Uganda and its link with HIV infection and compromising access to HIV/AIDS services is known. However, current evidence is controversial. Most of the studies indicate a positive relationship but a few indicate otherwise. Moreover, there is no research examining the effects of community-level SGBV on HIV infection. Objectives: This research explores the association between SGBV and vulnerability to HIV infection. Methods: Multilevel binary logistic regression is applied to secondary data of Uganda AIDS Indicators Survey conducted in 2011. The survey data comprises 12,153 women and 9588 men. Results: SGBV significantly increases the likelihood of HIV infection, with victims having 34%, 1.34 [1.06–1.70] higher odds than non-victims. At the community level, wealth, and pre-sex alcohol abuse are important determinants. Conclusions: Vulnerability to the risk of HIV infection in Uganda is associated with individual-level and community factors. Effective HIV prevention policies need to pay attention to victims of SGBV using individual- and community-level strategies.
An Exploration of the Impact of COVID-19 on Police Demand, Capacity and Capability
Authors: Halford Eric
Published: July 2022

This project report outlines the findings of an initial exploratory study of the impact of the coronavirus (COVID-19) pandemic on the demand, capacity, and capability of the police within the United Kingdom. Freedom of information requests provide data regarding employees affected by COVID-19, including those working from home. A survey of police employees adds richness by exploring the departments and specialist capabilities affected. Preliminary results indicate a shift in demand away from property-related and violent crime, to online criminality, and disorders such as anti-social behavior and breaches of coronavirus legislation. Combined with high volumes of absent employees throughout 2020, the study postulates a reduction in police satisfaction, trust, and confidence may have occurred in the response to cyber investigation and policing anti-social behavior. Investment in agile technology to increase workforce flexibility and improved contingency planning are identified as requirements to prepare for future pandemics and avoid repetition.
Occurrence of Natural and Synthetic Micro-Fibers in the Mediterranean Sea: A Review
Authors: Santini Saul , De Beni Eleonora , Martellini Tania , Sarti Chiara , Randazzo Demetrio , Ciraolo Roberto , Scopetani Costanza , Cincinelli Alessandra
Published: July 2022

Among microplastics (MPs), fibers are one of the most abundant shapes encountered in the aquatic environment. Growing attention is being focused on this typology of particles since they are considered an important form of marine contamination. Information about microfibers distribution in the Mediterranean Sea is still limited and the increasing evidence of the high amount of fibers in the aquatic environment should lead to a different classification from MPs which, by definition, are composed only of synthetic materials and not natural. In the past, cellulosic fibers (natural and regenerated) have been likely included in the synthetic realm by hundreds of studies, inflating “micro-plastic” counts in both environmental matrices and organisms. Comparisons are often hampered because many of the available studies have explicitly excluded the micro-fibers (MFs) content due, for example, to methodological problems. Considering the abundance of micro-fibers in the environment, a chemical composition analysis is fundamental for toxicological assessments. Overall, the results of this review work provide the basis to monitor and mitigate the impacts of microfiber pollution on the sea ecosystems in the Mediterranean Sea, which can be used to investigate other basins of the world for future risk assessment.
The Resistance Patterns in E. coli Isolates among Apparently Healthy Adults and Local Drivers of Antimicrobial Resistance: A Mixed-Methods Study in a Suburban Area of Nepal
Authors: Shrestha Abha , Shrestha Rajeev , Koju Pramesh , Tamrakar Sudichhya , Rai Anisha , Shrestha Priyanka , Madhup Surendra Kumar , Katuwal Nishan , Shrestha Archana , Shrestha Akina , Shrestha Sunaina , K.C Sandip , Kharel Supriya , Tamang Pooja , Thekkur Pruthu , Shakya Shrestha Sony
Published: July 2022

Evidence-based decision-making to combat antimicrobial resistance (AMR) mandates a well-built community-based surveillance system for assessing resistance patterns among commensals and pathogenic organisms. As there is no such surveillance system in Nepal, we attempted to describe the antimicrobial resistance pattern in E. coli isolated from the fecal samples of apparently healthy individuals in Dhulikhel municipality and also explored the local drivers of AMR. We used a mixed-method design with a cross-sectional quantitative component and a descriptive qualitative component, with focus group discussion and key informant interviews as the data collection method. Fecal samples were collected from 424 individuals randomly selected for the study. E. coli was isolated from 85.9% of human fecal samples, of which 14% were resistant to ≥3 class of antimicrobials (multidrug resistant). Of the 368 isolates, resistance to ampicillin (40.0%), tetracycline (20.7%) and cefotaxime (15.5%) were most prevalent. The major drivers of AMR were: lack of awareness of AMR, weak regulations on sales of antimicrobials, poor adherence to prescribed medications, and incomplete dosage due to financial constraints. These findings indicate the need for strict implementation of a national drug act to limit the over-the-counter sales of antimicrobials. Additionally, awareness campaigns with a multimedia mix are essential for educating people on AMR.
Cosmological Perturbations in Bouncing Cosmologies and the Case of the Pre-Big Bang Scenario
Authors: Bozza Valerio
Published: July 2022

Pre-Big Bang cosmology inspired generations of cosmologists in attempts to cure the initial Big Bang singularity using a fundamental length scale as proposed by string theory. The existence of a phase of collapse/inflation with increasing curvature followed by a cosmic bounce has been proposed as an alternative to standard inflation in the solution of the horizon and curvature problems. However, the generation of a nearly scale-invariant spectrum of perturbations is not an automatic prediction of such scenarios. In this paper, I review some general statements about the evolution of perturbations in bouncing cosmologies and some historically significant attempts to reconcile the predicted spectra with the observations. Bouncing cosmologies and, in particular, the pre-Big Bang scenario stand as viable, although more complicated, alternatives to inflation that may still help solve current theoretical and observational tensions.
Advances in Infectious Disease Vaccine Adjuvants
Authors: Fan Jingyi , Jin Shengbin , Gilmartin Lachlan , Toth Istvan , Hussein Waleed , Stephenson Rachel
Published: July 2022

Vaccines are one of the most significant medical interventions in the fight against infectious diseases. Since their discovery by Edward Jenner in 1796, vaccines have reduced the worldwide transmission to eradication levels of infectious diseases, including smallpox, diphtheria, hepatitis, malaria, and influenza. However, the complexity of developing safe and effective vaccines remains a barrier for combating many more infectious diseases. Immune stimulants (or adjuvants) are an indispensable factor in vaccine development, especially for inactivated and subunit-based vaccines due to their decreased immunogenicity compared to whole pathogen vaccines. Adjuvants are widely diverse in structure; however, their overall function in vaccine constructs is the same: to enhance and/or prolong an immunological response. The potential for adverse effects as a result of adjuvant use, though, must be acknowledged and carefully managed. Understanding the specific mechanisms of adjuvant efficacy and safety is a key prerequisite for adjuvant use in vaccination. Therefore, rigorous pre-clinical and clinical research into adjuvant development is essential. Overall, the incorporation of adjuvants allows for greater opportunities in advancing vaccine development and the importance of immune stimulants drives the emergence of novel and more effective adjuvants. This article highlights recent advances in vaccine adjuvant development and provides detailed data from pre-clinical and clinical studies specific to infectious diseases. Future perspectives into vaccine adjuvant development are also highlighted.
Chitosan/Calcium-Coated Ginsenoside Rb1 Phosphate Flower-like Microparticles as an Adjuvant to Enhance Immune Responses
Authors: Song Xinghui , Li Huijuan , Zhang Liheng , Zhang Xiaozhan , Zhao Li , Zhang Gaiping , Cao Shengbo , Liu Yunchao
Published: July 2022

Infectious bursal disease (IBD) is a highly contagious immunocompromising disorder that caused great economic losses in the poultry industry. The field-level control over IBD is primarily via vaccination. The development of a highly effective IBV vaccine has drawn great attention worldwide. Chitosan/Calcium Phosphate (CS/CaP) nanoparticle was a newly developed effective biological delivery system for drug and antigen. Ginsenoside Rb1 is one of the main bioactive components of ginseng root extract, which has antioxidant, anti-inflammatory and immunological enhancement effects. Until now, the combined effect of CS/CaP and ginsenoside Rb1 on the chicken immune response had remained unknown. In this study, the GRb1 and IL-4 were encapsulated into Calcium phosphate and chitosan core structure nanoparticles microspheres (GRb1/IL-4@CS/CaP), and the effect of a newly developed delivery system on an infectious bursal disease virus (IBDV) attenuated vaccine was further evaluated. The results demonstrated that GRb1/IL-4@CS/CaP treatment could induce the activation of chicken dendritic cells (DCs), with the upregulated expression of MHCII and CD80, and the increased production of IL-1β and TNF-α. Importantly, GRb1/IL-4@CS/CaP could trigger a higher level of IBDV-specific IgG and a higher ratio of IgG2a/IgG1 than the traditional adjuvant groups, promoting the production of cytokine, including IFN-γ, TNF-α, IL-4, IL-6, IL-1α, and IL-1β, in chicken serum after 28 d and 42 d post-vaccine. Taken in all, GRb1/IL-4@CS/CaP could elicit prolonged vigorous immune responses for IBDV attenuated vaccine in chicken, which might provide an effective adjuvant system for avian vaccine development.