bluuebunny/crossref_metadata_2025 huggingface dataset:
Seismic Performance Assessment of Wide Pile-Supported Wharf Considering Soil Slope and Waveform Duration
Authors: Boyke Christino , Nagao Takashi
Published: July 2022

Pile-supported wharf (PSW) is one of the primary port structures and is often damaged by earthquakes. To mitigate the risk of seismic damage to a PSW, its seismic performance should be thoroughly assessed. This study aimed to examine the impact of ground displacement on the seismic performance of PSW with a mild soil slope. We performed soil-structure system finite element analysis targeting a wide PSW. The analysis is divided into two scenarios. In the first scenario, the PSW was modeled without regard for the soil slope, whereas the second scenario considered the soil slope. Two waveforms that matched the target spectral acceleration were used to study the effects of the waveform duration on the seismic response of PSW. The analysis results revealed substantial influences of soil slope displacement as well as differences in waveforms on PSW’s seismic performance.
Numerical Investigation of Plastic Deformation of Flat Plate for Slamming Impact by Coupled Eulerian–Lagrangian Method
Authors: Park Young IL , Park Su-Hyun , Kim Jeong-Hwan
Published: July 2022

Ships and offshore structures are subjected to impact loads, such as slamming and sloshing. High impact pressures can cause permanent hull deformation by a single impact event. In addition, significant fatigue damage can be accumulated via repeated impact pressures. In this study, the plastic deformation behavior of flat plates under slamming impact is numerically investigated using a coupled Eulerian–Lagrangian method. The dynamic impact pressure of the flat plates by weight and drop height is investigated under the assumption of viscous and compressible fluids. To evaluate the plastic deformation of the plate, contact between water and the plate is removed after a certain duration after dropping, and then the remaining deformation is measured. Optimized finite element models for drop simulations are selected via a mesh sensitivity study, and the simulation results are calibrated and compared with experimental data. Results of the simulation and the experiment show good agreement in general in terms of deflection range. However, because the initial condition of the plate is not reflected in the simulation, some discrepancy is observed in maximum deflections. Finally, a discussion is presented for a more accurate fluid impact analysis model based on the comparison results with the experimental data.
The Parameter Design of Nonlinear Energy Sink Installed on the Jacket Pipe by Using the Nonlinear Dynamical Theory
Authors: Yang Lianfeng , Liu Liqin , Luo Chao , Yu Yongjun , Chen Yiqun
Published: July 2022

The aim of this paper is to investigate the vibration suppression effect of a nonlinear energy sink (NES) on the wind-vortex-induced vibration of deep-water jacket pipes. Based on nonlinear dynamical theories, the coupled dynamic equation of a deep-water jacket pipe with NES was established, and the nonlinear response characteristics and motion stability of the system were studied by using the multi-scale mixed harmonic balance method and Routh–Hurwitz criterion. The paper also analyzed the influence of the nonlinear stiffness and damping parameters of an NES on the dynamic response of the pipe. It is concluded that when the nonlinear stiffness of an NES increases to a certain extent, the motion response of the pipe appeared as a saddle-node and Hopf bifurcation, and the vibration amplitude of the pipe is greatly suppressed. For a system with nonlinear motion, NES damping mainly affects the range of the unstable region. For the system without nonlinear motion, the increases in NES damping will reduce the amplitude near the resonance region. Selecting proper parameters of an NES nonlinear stiffness and damping can effectively suppress the vortex-induced vibration of pipes.
Compound Identification from Bromelia karatas Fruit Juice Using Gas Chromatography–Mass Spectrometry and Evaluation of the Bactericidal Activity of the Extract
Authors: Ayil-Gutiérrez Benjamín A. , Amaya-Guardia Karla Cecilia , Alvarado-Segura Arturo A. , Polanco-Hernández Glendy , Uc-Chuc Miguel Angel , Acosta-Viana Karla Y. , Guzmán-Marín Eugenia , Samaniego-Gámez Blancka Yesenia , Poot-Poot Wilberth Alfredo , Lizama-Uc Gabriel , Villanueva-Alonzo Hernán de Jesús
Published: July 2022

Fruits of species of the genus Bromelia contain compounds with health benefits and potential biotechnological applications. For example, Bromelia karatas fruits contain antioxidants and proteins with bactericidal activity, but studies regarding the activity of these metabolites and potential benefits are required. We evaluated the bactericidal activity of the methanolic extract (treated and not treated with activated charcoal) and its fractions (hexane, ethyl acetate, and methanol) from ripe B. karatas fruit (8 °Brix) against Escherichia coli, Enterococcus faecalis, Salmonella enteritidis, and Shigella flexneri. The methanolic extract (ME) minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) were determined at eight concentrations. The methanolic extract MIC was 5 mg/mL for E. faecalis and 10 mg/mL for the other bacteria; the MBC was 20 mg/mL for E. coli and E. faecalis, and 40 mg/mL for S. enteritidis and S. flexneri. Through gas chromatography–mass spectrometry, 131 compounds were identified, some of which had previously been reported to have biological activities, such as bactericidal, fungicide, anticancer, anti-inflammatory, enzyme inhibiting, and anti-allergic properties. The most abundant compounds found in the ME of B. karatas fruits were maleic anhydride, 5-hydroxymethylfurfural, and itaconic anhydride. This study shows that B. karatas fruits contain metabolites that are potentially beneficial for health.
Study on Noise Reduction and Data Generation for sEMG Spectrogram Based User Recognition
Authors: Kim Jae-Myeong , Kim Min-Gu , Pan Sung-Bum
Published: July 2022

With the spread of the modern media industry, harmful genre contents are indiscriminately disseminated to teenagers. The password identification method used to block sensational and violent genre content has become a problem that teenagers can easily steal. Therefore, a user identification method with less risk of theft and hacking is required. The surface EMG (sEMG) signal, which is an electrical signal generated inside the body and has individual features, is being studied as a next-generation user identification method. sEMG involves measuring an individual’s unique muscular strength activated over time as digital signals, thus giving it the advantage of generating different signal patterns. However, it is difficult to constantly and repeatedly acquire each motion signal and the number of repetitions for each motion is insufficient, thus there is a limit to improving user identification accuracy. In this paper, we propose a user identification system that solves the problem of insufficient data by applying the matching pursuit that enables signal generation to the sEMG signal from which the resting signal has been removed and improves classification accuracy by extracting STFT-based time–frequency features. As a result of the experiment, the user identification accuracy of the sEMG spectrogram with the resting state signal removed was 85.4%. In addition, when the training data were increased through data generation, the accuracy was improved, showing a user identification accuracy of 96.1%. Improved user recognition accuracy was confirmed when the training data of the sEMG signal from which the resting signal was removed were increased and multidimensional features including time–frequency were used.
Building Infrastructure to Exploit Evidence from Patient Preference Information (PPI) Studies: A Conceptual Blueprint
Authors: Giordano Luca , Francavilla Andrea , Lanera Corrado , Urru Sara , Berchialla Paola , Baldi Ileana
Published: July 2022

Patients are the most important actors in clinical research. Therefore, patient preference information (PPI) could support the decision-making process, being indisputable for research value, quality, and integrity. However, there is a lack of clear guidance or consensus on the search for preference studies. In this blueprint, an openly available and regularly updated patient preference management system for an integrated database (PPMSDB) that contains the minimal set of data sufficient to provide detailed information for each study (the so-called evidence tables in systematic reviews) and a high-level overview of the findings of a review (summary tables) is described. These tables could help determine which studies, if any, are eligible for quantitative synthesis. Finally, a web platform would provide a graphical and user-friendly interface. On the other hand, a set of APIs (application programming interfaces) would also be developed and provided. The PPMSDB, aims to collect preference measures, characteristics, and meta-data, and allow researchers to obtain a quick overview of a research field, use the latest evidence, and identify research gaps. In conjunction with proper statistical analysis of quantitative preference measures, these aspects can facilitate formal evidence-based decisions and adequate consideration when conducting a structured decision-making process. Our objective is to outline the conceptual infrastructure necessary to build and maintain a successful network that can monitor the currentness and validity of evidence.
Special Issue on Interdisciplinary Artificial Intelligence: Methods and Applications of Nature-Inspired Computing
Authors: Ponce Hiram , Martínez-Villaseñor Lourdes , González-Mendoza Miguel , Fonseca Pablo A.
Published: July 2022

Inspiration in nature has been widely explored, from the macro to micro-scale [...]
Seismic Assessment and Retrofitting of Reinforced Concrete Structures
Authors: Bosco Melina , Rossi Pier Paolo
Published: July 2022

Many constructions are globally built with reinforced or prestressed concrete and a large part of them are designed or expected to resist earthquake actions in addition to gravity loads [...]
Cadence Feedback and Video-Based Engagement Improves Motivation and Performance during Pedalling in Stroke Patients
Authors: Soni Mukesh , Wijeratne Tissa , Ackland David
Published: July 2022

Video and music as a dissociative attention stimulus during exercise is known to distract from the discomfort of physical exertion and improve exercise adherence; however, the influence of video-based feedback and engagement during pedalling on the performance and motivation of pedalling in stroke patients is poorly understood. The aim of this study was to employ a novel video-based engagement paradigm for pedalling in stroke patients and evaluate its capacity to influence the cadence control, physiological output, and perceived motivation and enjoyment. Thirteen stroke patients were recruited with low-to-moderate lower-limb disability (mean age: 64.0 yrs.). A reference group of 18 healthy young adult subjects (mean age: 27.7 yrs.) was also recruited to assess the broad applicability of the techniques to a contrasting non-pathological cohort. The participants pedalled at a slow (60 RPM) and fast (100 RPM) target speed with constant resistance in 15 min pedalling bouts that included (i) baseline pedalling with real-time visual feedback of cadence deviation from the target provided only in the first 20 s (ii) real-time visual feedback of cadence data over the entire pedalling session, and (iii) real-time engagement to maintain the playback rate of a prerecorded video by pedalling at the target speed. During low speed pedalling, stroke patients demonstrated significantly smaller absolute cadence deviation during pedalling with feedback (mean difference: 1.8 RPM, p = 0.014) and video-based engagement (mean difference: 2.4 RPM, p = 0.006) compared to the baseline pedalling. For the healthy adults, feedback and video-based engagement reduced cadence deviation significantly at all speeds (p < 0.05). All but one stroke patient either enjoyed or really enjoyed the video engagement during pedalling and felt motivated to undertake this form of exercise in therapy in the future. This proof-of-concept study showed that feedback and video-based engagement may improve the targeted pedalling performance in stroke patients, and by helping dissociate subjects from physical cues associated with fatigue, may ultimately improve exercise motivation and compliance.
Brain Tumor Analysis Using Deep Learning and VGG-16 Ensembling Learning Approaches
Authors: Younis Ayesha , Qiang Li , Nyatega Charles Okanda , Adamu Mohammed Jajere , Kawuwa Halima Bello
Published: July 2022

A brain tumor is a distorted tissue wherein cells replicate rapidly and indefinitely, with no control over tumor growth. Deep learning has been argued to have the potential to overcome the challenges associated with detecting and intervening in brain tumors. It is well established that the segmentation method can be used to remove abnormal tumor regions from the brain, as this is one of the advanced technological classification and detection tools. In the case of brain tumors, early disease detection can be achieved effectively using reliable advanced A.I. and Neural Network classification algorithms. This study aimed to critically analyze the proposed literature solutions, use the Visual Geometry Group (VGG 16) for discovering brain tumors, implement a convolutional neural network (CNN) model framework, and set parameters to train the model for this challenge. VGG is used as one of the highest-performing CNN models because of its simplicity. Furthermore, the study developed an effective approach to detect brain tumors using MRI to aid in making quick, efficient, and precise decisions. Faster CNN used the VGG 16 architecture as a primary network to generate convolutional feature maps, then classified these to yield tumor region suggestions. The prediction accuracy was used to assess performance. Our suggested methodology was evaluated on a dataset for brain tumor diagnosis using MR images comprising 253 MRI brain images, with 155 showing tumors. Our approach could identify brain tumors in MR images. In the testing data, the algorithm outperformed the current conventional approaches for detecting brain tumors (Precision = 96%, 98.15%, 98.41% and F1-score = 91.78%, 92.6% and 91.29% respectively) and achieved an excellent accuracy of CNN 96%, VGG 16 98.5% and Ensemble Model 98.14%. The study also presents future recommendations regarding the proposed research work.
Application of Virtual Reality Method in Aircraft Maintenance Service—Taking Dornier 228 as an Example
Authors: Wu Wen-Chung , Vu Van-Hoan
Published: July 2022

Flight safety and airlines operation have been at the center of research since aircraft were first invented, as even slight errors in aircraft maintenance may cause serious accidents. Thus, aircraft maintenance is critical to the aviation industry all the time. To prevent maintenance errors, it is important to train for aviation maintenance. Therefore, an aircraft maintenance virtual reality (AMVR) system was developed in this study. For a Dornier-228 aircraft, a walk-around visual inspection of its fuel system was designed and tested in a virtual environment. For the system, CATIA V5 and Unity 3D software were used for designing the 3D model of the aircraft and developing the visual environment, respectively. With the software, the visual environment of the aircraft hangar was created for the system. The developed system was tested by students to validate the effectiveness of using the AMVR system in training. The students acknowledged that the system was beneficial to their learning, which proved that the developed system is highly effective for training students to improve aircraft maintenance skills.
Fabrication of Carbon Aerogels Derived from Metal-Organic Frameworks/Carbon Nanotubes/Cotton Composites as an Efficient Sorbent for Sustainable Oil–Water Separation
Authors: Sun Yinyu , Ke Zhongcheng , Shen Caiyun , Sun Ruikang , Wei Qing , Yin Zihan , Yang Wei
Published: July 2022

Due to the continuous occurrence of water pollution problems, practical separation methods for oil–water mixtures have attracted more and more attention. To date, different kinds of materials have been developed with good hydrophobic properties and strong separation ability. Carbon aerogels, as a promising ideal adsorbent for dealing with oil-spill accidents, have received extensive attention. In this work, zeolitic imidazolate frameworks (ZIFs), nanoparticles, and carbon nanotubes (CNTs) in the three-dimensional (3D) interconnected network structure of cotton balls (CBs) were successfully prepared by a simple and scalable process. The as-prepared carbonized CBs with carbonized ZIF-8 and CNTs (CZIF-8/CNTs/CCBs) were characterized. The oil–water separation performance of the composite was also measured. The results show that the ZIF-8 clusters intercalated with abundant CNTs are fully loaded into the porous structure of the CBs after the in situ synthesis process. Additionally, ZIF-8/CNTs/CBs was carbonized in nitrogen, leading to the formation of CZIF-8/CNTs/CCBs. The prepared material possesses excellent hydrophobicity with a water contact angle of 152.7°, showing good absorption capacities Q1 in the range of 48 to 84 times its original weight for oil and organic liquids. In addition, CZIF-8/CNTs/CCBs exhibits good recyclability in the absorption–distillation test. In summary, this study proposes a novel and simple method for the preparation of a superhydrophobic material that could have wide application in the separation of oil–water mixtures.
The Effect of Molecular Weight on the (Re)-Processability and Material Properties of Bio-Based, Thermoreversibly Cross-Linked Polyesters
Authors: Beljaars Martijn , Kamphuis Arjen J. , Heeres Hero J. , Broekhuis Antonius A. , Picchioni Francesco
Published: July 2022

A (partially) bio-based short-chain polyester is prepared through interfacial polycondensation of furan-functionalized diphenolic acid with terephthalic chloride. The furan groups along the backbone of the obtained polyester are able to form a covalent network (PE-fur/Bism) with various ratios of 1,1′-(methylenedi-4,1-phenylene)bismaleimide via the thermoreversible Diels–Alder (DA) reaction. Several techniques have been employed to characterize the polyester network, including 1H-NMR, gel permeation chromatography (GPC), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), and dynamic mechanical thermal analysis (DMTA). The polyester base polymer displays a glass transition temperature of 115 °C, whereas the temperatures at which the retro-Diels–Alder (rDA) reaction takes place lie above 130 °C for the various polyester/bismaleimide networks. Excellent thermoreversibility and recyclability of the polyester resin have been shown through DSC and DMTA measurements.
Co-Fermentation of Microalgae Biomass and Miscanthus × giganteus Silage—Assessment of the Substrate, Biogas Production and Digestate Characteristics
Authors: Dębowski Marcin , Kazimierowicz Joanna , Zieliński Marcin , Bartkowska Izabela
Published: July 2022

The development of a sustainable bioenergy market is currently largely fueled by energy crops, whose ever-increasing production competes with the global food and feed supply. Consequently, non-food crops need to be considered as alternatives for energy biomass production. Such alternatives include microalgal biomass, as well as energy crops grown on non-agricultural land. The aim of the present study was to evaluate how co-digestion of microalgal biomass with giant miscanthus silage affects feedstock properties, the biogas production process, biogas yields, methane fractions and the digestate profile. Combining giant miscanthus silage with microbial biomass was found to produce better C/N ratios than using either substrate alone. The highest biogas and methane production rates—628.00 ± 20.05 cm3/gVS and 3045.56 ± 274.06 cm3 CH4/d—were obtained with 40% microalgae in the feedstock. In all variants, the bulk of the microbial community consisted of bacteria (EUB338) and archaea (ARC915).
Evaluation of the Influence of Rootstock Type on the Yield Parameters of Vines Using a Mathematical Model in Nontraditional Wine-Growing Conditions
Authors: Klimek Kamila , Postawa Karol , Kapłan Magdalena , Kułażyński Marek
Published: July 2022

Great interest in viticulture in temperate climates results from the introduction of new interspecies hybrids of grapevines which are quite popular due to their high resistance to fungal diseases and lower temperature. However, the impact of rootstocks, common in vine cultivation, is little to not known, which makes setting up vineyards a challenge. This study aimed to evaluate the effect of the following six rootstock types: 101-14 Mgt, SORI, 161-49 C, 5 BB, SO4, 125 AA, and grapevines with their own roots on the yield quantity and berry quality (expressed by Brix extract) of Regent grapevines in temperate climates (southeastern Poland). A five-year experiment alongside a novel numerical model is applied to formulate precise and constructive findings about the rootstock impact in a temperate climate. Both the experimental and numerical part are supported by detailed statistical analysis. The five-year period of study indicates that the vines on rootstock 125 AA yielded the best, significantly. Shrubs grafted on rootstock 161-49 yielded the lowest, while the fruit extract content grafted on rootstock 101-14 was significantly lower among the evaluated ones. The parameters of own-rooted bushes and those grafted on SO4 rootstock did not differ significantly, except for the extract. The model leads to convergent conclusions with statistical analysis of raw experimental data. The 125 AA rootstock was the best for all nine tested case scenarios. On the other hand, 161-49 rootstock was the weakest, justified only in the most challenging conditions.
Fusion Information Multi-View Classification Method for Remote Sensing Cloud Detection
Authors: Hao Qi , Zheng Wenguang , Xiao Yingyuan
Published: July 2022

In recent years, many studies have been carried out to detect clouds on remote sensing images. Due to the complex terrain, the variety of clouds, the density, and content of clouds are various, and the current model has difficulty accurately detecting the cloud in the image. In our strategy, a multi-view data training set based on super pixel is constructed. View A uses multi-level network to extract the boundary, texture, and deep abstract feature of super pixels. View B is the statistical feature of the three channels of the image. Privilege information View P contains the cloud content of super pixels and the tag status of adjacent super pixels. Finally, we propose a cloud detection method for remote sensing image classification based on multi-view support vector machine (SVM). The proposed method is tested on images of different terrain and cloud distribution in GF-1_WHU and Cloud-38 remote sensing datasets. Visual performance and quantitative analysis show that the method has excellent cloud detection performance.
Online and In-Class Evaluation of a Music Theory E-Learning Platform
Authors: Pesek Matevž , Klavž Franc , Šavli Peter , Marolt Matija
Published: July 2022

This paper presents a new version and a three-month evaluation of the Troubadour platform—an open-source music theory ear training platform. Through interviews with teachers, we gathered the most-needed features which would aid their use of the platform. In the new version of the Troubadour platform, we implemented different types of interaction, including class management, re-occurring homework and challenges. Previous research has shown a significant improvement in the students’ performance while using the platform. However, the short time span of the previous experiments has not shown whether these results can be attributed to the novelty bias. To evaluate the efficacy of the platform beyond its novelty bias, we performed a three-month-long evaluation experiment on the students’ interaction through questionnaires and platform-collected data. We collected data on their engagement with the platform. During the experiment, the students attended the school through online courses during the first part of the evaluation, and in-class in the second part. In this paper, we investigate the students’ engagement during the three-month period, explore the influence of the platform’s use in-class versus online learning process, analyze the students’ self-report on their practice habits and compare them with the collected data. The results showed high student engagement during the lockdown period, while the in-class process showed a decrease in the platform’s use, unveiling the students’ need for such platform as a complementary learning channel in remote learning.
Enhanced Anti-Melanogenic Effect of Adlay Bran Fermented with Lactobacillus brevis MJM60390
Authors: Nguyen Huong T. , Gu Mingkun , Choi Chun Whan , Choi Yun-Hyeok , Suh Joo-Won , Cheng Jinhua
Published: July 2022

Fermentation is a traditional technique used to increase nutrients, flavonoids, vitamins, minerals, and the flavor of raw materials. In this study, adlay bran was fermented by Lactobacillus brevis MJM60390 (FAB), and the anti-melanogenic effect was investigated. The results demonstrated that FAB significantly suppressed melanin accumulation in mouse melanogenic B16F10 cells, and the activity was higher than non-fermented adlay bran (NFAB). The molecular mechanism study showed that FAB inhibited melanin synthesis by suppressing the gene expression of melanocortin 1 receptor (Mc1r), melanocyte-inducing transcription factor (Mitf), tyrosinase (Tyr), tyrosinase-related protein-1 (Trp-1), and tyrosinase-related protein-2 (Trp-2) genes. Western blotting analysis showed that FAB strongly decreased the expression of Tyr, Trp-1, and Trp-2 compared to NFAB. Furthermore, phenolic compounds such as gallic acid, p-coumaric acid, ferulic acid, and sinapic acid, which are known for their anti-melanogenic effects, were significantly increased in FAB compared with NFAB. These findings suggest that FAB holds great potential as an anti-melanogenic agent and can be used for the development of whitening cosmetics.
The Memories of Journeys: Spatialization of Time in Wong Kar-wai’s Nostalgic Films
Authors: Lei Chin-Pang
Published: July 2022

There is usually an agenda behind the rewriting of history. As an acclaimed Hong Kong director, Wong Kar-wai has made several nostalgic films set in 1960s Hong Kong, namely, Days of Being Wild (1990), In the Mood for Love (2000), and 2046 (2004). Relating to Hong Kongers’ anxiety over the 1997 handover, Wong’s films are part of a wider symptomatic cultural phenomenon in Hong Kong cinema. In his nostalgic films, time is often spatialized. With his constant interest in mobile space, such as hotels and trains, he creates an alternative perspective to question the grand narrative of history. In his reconstruction of the past, there is never any cultural purity or origin to revisit. Rather, the past is presented with itinerant characters, mobile space, and cultural ambivalence, enabling multiple narratives of history. Focusing on the use of space, this paper analyzes how Wong’s films engender a reflective form of nostalgia, and challenge both official history and the linear concept of time. Wong’s nostalgia, I argue, is not only a response to Hong Kong politics, but also a paradigmatic text illustrating nostalgic writing’s resistance to official historical discourses.
Modification of k-ε Model for Sensible Heat and Momentum Flux Reconstruction from Surface Temperature Data
Authors: Hrebtov Michael , Bobrov Maxim
Published: July 2022

We present a modified k-ε model with a set of wall-functions suitable for reconstruction of sensible heat and momentum fluxes from the observations data (e.g., surface temperature evolution during the diurnal cycle). The modification takes into account stability and buoyancy effects in the Reynolds stress parametrization which affects turbulence production and turbulent heat flux. The single-cell and single-column versions of the model are presented. The model is tested based on CASES-99 observations data for dry ABL. It is shown that the presented modification improves the predictions of sensible heat flux magnitude and leads to a faster onset of a daytime instability, compared to the non-modified k-ε model and its scale-limited modification based on Monin-Obukhov similarity theory.
The Existence of Weak Solutions for the Vorticity Equation Related to the Stratosphere in a Rotating Spherical Coordinate System
Authors: Zhang Wenlin , Fečkan Michal , Wang Jinrong
Published: July 2022

In this paper, based on the Euler equation and mass conservation equation in spherical coordinates, the ratio of the stratospheric average width to the planetary radius and the ratio of the vertical velocity to the horizontal velocity are selected as parameters under appropriate boundary conditions. We establish the approximate system using these two small parameters. In addition, we consider the time dependence of the system and establish the governing equations describing the atmospheric flow. By introducing a flow function to code the system, a nonlinear vorticity equation describing the planetary flow in the stratosphere is obtained. The governing equations describing the atmospheric flow are transformed into a second-order homogeneous linear ordinary differential equation and a Legendre’s differential equation by applying the method of separating variables based on the concepts of spherical harmonic functions and weak solutions. The Gronwall inequality and the Cauchy–Schwartz inequality are applied to priori estimates for the vorticity equation describing the stratospheric planetary flow under the appropriate initial and boundary conditions. The existence and non-uniqueness of weak solutions to the vorticity equation are obtained by using the functional analysis technique.
FAAH rs324420 Polymorphism Is Associated with Performance in Elite Rink-Hockey Players
Authors: Silva Hugo-Henrique , Tavares Valéria , Silva Maria-Raquel G. , Neto Beatriz Vieira , Cerqueira Fátima , Medeiros Rui
Published: July 2022

Genetic factors are among the major contributors to athletic performance. Although more than 150 genetic variants have been correlated with elite athlete status, genetic foundations of competition-facilitating behavior influencing elite performances are still scarce. This is the first study designed to examine the distribution of genetic determinants in the athletic performance of elite rink-hockey players. A total of 116 of the world’s top best rink-hockey players (28.2 ± 8.7 years old; more than 50% are cumulatively from the best four world teams and the best five Portuguese teams), who participated at the elite level in the National Rink-Hockey Championship in Portugal, were evaluated in anthropometric indicators/measurements, training conditions, sport experience and sport injuries history. Seven genetic polymorphisms were analyzed. Polymorphism genotyping was performed using the TaqMan® Allelic Discrimination Methodology. Rink-hockey players demonstrated significantly different characteristics according to sex, namely anthropometrics, training habits, sports injuries and genetic variants, such as Vitamin D Receptor (VDR) rs731236 (p < 0.05). The Fatty Acid Amide Hydrolase (FAAH) rs324420 A allele was significantly associated with improved athletic performance (AA/AC vs. CC, OR = 2.80; 95% Cl, 1.23–6.35; p = 0.014; p = 0.008 after Bootstrap) and confirmed as an independent predictor among elite rink-hockey players (adjusted OR = 2.88; 95% Cl, 1.06–7.80; p = 0.038). Our results open an interesting link from FAAH-related biology to athletic performance.
Kallikrein-Related Peptidase 6 (KLK6) as a Contributor toward an Aggressive Cancer Cell Phenotype: A Potential Role in Colon Cancer Peritoneal Metastasis
Authors: Bouzid Hayet , Soualmia Feryel , Oikonomopoulou Katerina , Soosaipillai Antoninus , Walker Francine , Louati Khaoula , Lo Dico Rea , Pocard Marc , El Amri Chahrazade , Ignatenko Natalia A. , Darmoul Dalila
Published: July 2022

Kallikrein-related peptidases (KLKs) are implicated in many cancer-related processes. KLK6, one of the 15 KLK family members, is a promising biomarker for diagnosis of many cancers and has been associated with poor prognosis of colorectal cancer (CRC) patients. Herein, we evaluated the expression and cellular functions of KLK6 in colon cancer-derived cell lines and in clinical samples from CRC patients. We showed that, although many KLKs transcripts are upregulated in colon cancer-derived cell lines, KLK6, KLK10, and KLK11 are the most highly secreted proteins. KLK6 induced calcium flux in HT29 cells by activation and internalization of protease-activated receptor 2 (PAR2). Furthermore, KLK6 induced extracellular signal–regulated kinases 1 and 2 (ERK1/2) phosphorylation. KLK6 suppression in HCT-116 colon cancer cells decreased the colony formation, increased cell adhesion to extracellular matrix proteins, and reduced spheroid formation and compaction. Immunohistochemistry (IHC) analysis demonstrated ectopic expression of KLK6 in human colon adenocarcinomas but not in normal epithelia. Importantly, high levels of KLK6 protein were detected in the ascites of CRC patients with peritoneal metastasis, but not in benign ascites. These data indicate that KLK6 overexpression is associated with aggressive CRC, and may be applied to differentiate between benign and malignant ascites.
Calpain-Independent Intracellular Protease Activity Is Elevated in Excitotoxic Cortical Neurons Prior to Delayed Calcium Deregulation and Mitochondrial Dysfunction
Authors: Polster Brian M. , Mark Karla A. , Arze Rafael , Hudson Derek
Published: July 2022

Glutamate excitotoxicity contributes to many neurodegenerative diseases. Excessive glutamate receptor-mediated calcium entry causes delayed calcium deregulation (DCD) that coincides with abrupt mitochondrial depolarization. We developed cA-TAT, a live-cell protease activity reporter based on a vimentin calpain cleavage site, to test whether glutamate increases protease activity in neuronal cell bodies prior to DCD. Treatment of rat cortical neurons with excitotoxic (100 µM) glutamate increased the low baseline rate of intracellular cA-TAT proteolysis by approximately three-fold prior to DCD and by approximately seven-fold upon calcium deregulation. The glutamate-induced rate enhancement prior to DCD was suppressed by glutamate receptor antagonists, but not by calpain or proteasome inhibitors, whereas DCD-stimulated proteolysis was partly attenuated by the proteasome inhibitor MG132. Further suggesting that cA-TAT cleavage is calpain-independent, cA-TAT fluorescence was observed in immortalized Capn4 knockout fibroblasts lacking the regulatory calpain subunit. About half of the neurons lost calcium homeostasis within two hours of a transient, 20 min glutamate receptor stimulation. These neurons had a significantly (49%) higher mean baseline cA-TAT proteolysis rate than those maintaining calcium homeostasis, suggesting that the unknown protease(s) cleaving cA-TAT may influence DCD susceptibility. Overall, the results indicate that excitotoxic glutamate triggers the activation of calpain-independent neuronal protease activity prior to the simultaneous loss of calcium homeostasis and mitochondrial bioenergetic function.
Activation and Pharmacological Regulation of Inflammasomes
Authors: Chen Chen , Xu Pinglong
Published: July 2022

Inflammasomes are intracellular signaling complexes of the innate immune system, which is part of the response to exogenous pathogens or physiological aberration. The multiprotein complexes mainly consist of sensor proteins, adaptors, and pro-caspase-1. The assembly of the inflammasome upon extracellular and intracellular cues drives the activation of caspase-1, which processes pro-inflammatory cytokines IL-1β and IL-18 to maturation and gasdermin-D for pore formation, leading to pyroptosis and cytokine release. Inflammasome signaling functions in numerous infectious or sterile inflammatory diseases, including inherited autoinflammatory diseases, metabolic disorders, cardiovascular diseases, cancers, neurodegenerative disorders, and COVID-19. In this review, we summarized current ideas on the organization and activation of inflammasomes, with details on the molecular mechanisms, regulations, and interventions. The recent developments of pharmacological strategies targeting inflammasomes as disease therapeutics were also covered.
Metabolic Syndrome and Obesity-Related Indices Are Associated with Rapid Renal Function Decline in a Large Taiwanese Population Follow-Up Study
Authors: Su Wei-Yu , Chen I-Hua , Gau Yuh-Ching , Wu Pei-Yu , Huang Jiun-Chi , Tsai Yi-Chun , Chen Szu-Chia , Chang Jer-Ming , Hwang Shang-Jyh , Chen Hung-Chun
Published: July 2022

A rapid decline in renal function can cause many complications, and therefore it is important to detect associated risk factors. Few studies have evaluated the associations among obesity-related indices and metabolic syndrome (MetS) with renal function decline. This longitudinal study aimed to explore these relationships in a large cohort of Taiwanese participants. The studied obesity-related indices were waist-to-height ratio (WHtR), A body shape index (ABSI), visceral adiposity index (VAI), lipid accumulation product (LAP), waist-to-hip ratio (WHR), body roundness index (BRI), conicity index (CI), body mass index (BMI), body adiposity index (BAI) and abdominal volume index (AVI). We included 122,068 participants in the baseline study, of whom 27,033 were followed for a median of four years. The baseline prevalence of MetS was 17.7%. Multivariable analysis showed that the participants with MetS and high VAI, WHtR, WHR, LAP, CI, BRI, BMI, BAI, AVI, and ABSI values were significantly associated with a high baseline estimated glomerular filtration rate (eGFR) (all p < 0.001). In addition, the participants with MetS (p < 0.001), high WHtR (p = 0.007), low LAP (p < 0.001), high BRI (p = 0.002), high CI (p = 0.002), high AVI (p = 0.001), high VAI (p = 0.017), and high ABSI (p = 0.013) were significantly associated with a low △eGFR, indicating a rapid decline in renal function. These results showed associations between MetS and high values of obesity-related indices except LAP with high baseline eGFR and rapid decline in kidney function. These findings suggest that screening for MetS and obesity may help to slow the decline in renal function in high-risk populations.
A Point-of-Care Device for Fully Automated, Fast and Sensitive Protein Quantification via qPCR
Authors: Cavallo Francesca Romana , Mirza Khalid Baig , de Mateo Sara , Miglietta Luca , Rodriguez-Manzano  Jesus , Nikolic Konstantin , Toumazou Christofer
Published: July 2022

This paper presents a fully automated point-of-care device for protein quantification using short-DNA aptamers, where no manual sample preparation is needed. The device is based on our novel aptamer-based methodology combined with real-time polymerase chain reaction (qPCR), which we employ for very sensitive protein quantification. DNA amplification through qPCR, sensing and real-time data processing are seamlessly integrated into a point-of-care device equipped with a disposable cartridge for automated sample preparation. The system’s modular nature allows for easy assembly, adjustment and expansion towards a variety of biomarkers for applications in disease diagnostics and personalised medicine. Alongside the device description, we also present a new algorithm, which we named PeakFluo, to perform automated and real-time quantification of proteins. PeakFluo achieves better linearity than proprietary software from a commercially available qPCR machine, and it allows for early detection of the amplification signal. Additionally, we propose an alternative way to use the proposed device beyond the quantitative reading, which can provide clinically relevant advice. We demonstrate how a convolutional neural network algorithm trained on qPCR images can classify samples into high/low concentration classes. This method can help classify obese patients from their leptin values to optimise weight loss therapies in clinical settings.
Development of Nanomaterial-Modified Impedimetric Aptasensor—A Single-Step Strategy for 3,4-Methylenedioxymethylamphetamine Detection
Authors: Soni Shringika , Jain Utkarsh , Burke Donald H. , Chauhan Nidhi
Published: July 2022

Developing rapid, sensitive detection methods for 3,4-Methylenedioxymethylamphetamine (MDMA) is crucial to reduce its current misuse in the world population. With that aim, we developed an aptamer-modified tin nanoparticle (SnNP)-based nanoarchitecture as an electrochemical sensor in this study. This platform exhibited a high electron transfer rate with enhanced conductivity arising from its large surface area in comparison to the bare electrode. This observation was explained by the 40-fold higher electroactive surface area of SnNPs@Au, which provided a large space for 1.0 μM AptMDMA (0.68 ± 0.36 × 1012 molecule/cm2) immobilization and yielded a significant electrochemical response in the presence of MDMA. Furthermore, the AptMDMA-modified SnNPs@Au sensing platform proved to be a simple yet ultrasensitive analytical device for MDMA detection in spiked biological and water samples. This novel electrochemical aptasensor showed good linearity in the range of 0.01–1.0 nM for MDMA (R2 = 0.97) with a limit of detection of 0.33 nM and a sensitivity of 0.54 ohm/nM. In addition, the device showed high accuracy and stability along with signal recoveries in the range of 92–96.7% (Relative Standard Deviation, RSD, 1.1–2.18%). In conclusion, the proposed aptasensor developed here is the first to combine SnNPs and aptamers for illicit compound detection, and it offers a reliable platform for recreational drug detection.
Ultralow Laser Power Three-Dimensional Superresolution Microscopy Based on Digitally Enhanced STED
Authors: Shen Xiaochun , Wang Luwei , Li Wei , Wang He , Zhou Hanqiu , Zhu Yinru , Yan Wei , Qu Junle
Published: July 2022

The resolution of optical microscopes is limited by the optical diffraction limit; in particular, the axial resolution is much lower than the lateral resolution, which hinders the clear distinction of the three-dimensional (3D) structure of cells. Although stimulated emission depletion (STED) superresolution microscopy can break through the optical diffraction limit to achieve 3D superresolution imaging, traditional 3D STED requires high depletion laser power to acquire high-resolution images, which can cause irreversible light damage to biological samples and probes. Therefore, we developed an ultralow laser power 3D STED superresolution imaging method. On the basis of this method, we obtained lateral and axial resolutions of 71 nm and 144 nm, respectively, in fixed cells with 0.65 mW depletion laser power. This method will have broad application prospects in 3D superresolution imaging of living cells.
HCTNet: A Hybrid ConvNet-Transformer Network for Retinal Optical Coherence Tomography Image Classification
Authors: Ma Zongqing , Xie Qiaoxue , Xie Pinxue , Fan Fan , Gao Xinxiao , Zhu Jiang
Published: July 2022

Automatic and accurate optical coherence tomography (OCT) image classification is of great significance to computer-assisted diagnosis of retinal disease. In this study, we propose a hybrid ConvNet-Transformer network (HCTNet) and verify the feasibility of a Transformer-based method for retinal OCT image classification. The HCTNet first utilizes a low-level feature extraction module based on the residual dense block to generate low-level features for facilitating the network training. Then, two parallel branches of the Transformer and the ConvNet are designed to exploit the global and local context of the OCT images. Finally, a feature fusion module based on an adaptive re-weighting mechanism is employed to combine the extracted global and local features for predicting the category of OCT images in the testing datasets. The HCTNet combines the advantage of the convolutional neural network in extracting local features and the advantage of the vision Transformer in establishing long-range dependencies. A verification on two public retinal OCT datasets shows that our HCTNet method achieves an overall accuracy of 91.56% and 86.18%, respectively, outperforming the pure ViT and several ConvNet-based classification methods.
Exploring Gender Differences in the Instructor Presence Effect in Video Lectures: An Eye-Tracking Study
Authors: Zhang Yuyang , Yang Jing
Published: July 2022

The instructor’s presence on the screen has become a popular feature in the video lectures of online learning and has drawn increasing research interest. Studies on the instructor presence effect of video lectures mainly focused on the features of the instructor, and few have taken learners’ differences, such as gender, into consideration. The current study examined whether male and female learners differed in their learning performance and eye movement features when learning video lectures with and without the instructor’s presence. All participants (N = 64) were asked to watch three different types of video lectures: audio-video without instructor presence (AV), picture-video with instructor presence (PV), and video-video with instructor presence (VV). They watched nine videos, three of each condition, and completed a reading comprehension test after each video. Their eye movement data were simultaneously collected when they watched these videos. Results showed that learners gained better outcomes after watching the videos with a talking instructor (VV) than those with the instructor’s picture (PV) or without the instructor (AV). This finding suggests that the dynamic presence of the instructor in video lectures could enhance learning through increased social presence and agency. Gender differences were found in their attention allocation, but not behavioral learning performance. When watching the videos with a talking instructor (VV), female learners dwelt longer on the instructor, while males transited more between the instructor and the text. Our results highlight the value of instructor presence in video lectures and call for more comprehensive explorations of gender differences in online learning outcomes and attention distribution.
Magnetic Resonance Planimetry in the Differential Diagnosis between Parkinson’s Disease and Progressive Supranuclear Palsy
Authors: Quattrone Andrea , Morelli Maurizio , Bianco Maria G. , Buonocore Jolanda , Sarica Alessia , Caligiuri Maria Eugenia , Aracri Federica , Calomino Camilla , De Maria Marida , Vaccaro Maria Grazia , Gramigna Vera , Augimeri Antonio , Vescio Basilio , Quattrone Aldo
Published: July 2022

The clinical differential diagnosis between Parkinson’s disease (PD) and progressive supranuclear palsy (PSP) is often challenging. The description of milder PSP phenotypes strongly resembling PD, such as PSP-Parkinsonism, further increased the diagnostic challenge and the need for reliable neuroimaging biomarkers to enhance the diagnostic certainty. This review aims to summarize the contribution of a relatively simple and widely available imaging technique such as MR planimetry in the differential diagnosis between PD and PSP, focusing on the recent advancements in this field. The development of accurate MR planimetric biomarkers, together with the implementation of automated algorithms, led to robust and objective measures for the differential diagnosis of PSP and PD at the individual level. Evidence from longitudinal studies also suggests a role of MR planimetry in predicting the development of the PSP clinical signs, allowing to identify PSP patients before they meet diagnostic criteria when their clinical phenotype can be indistinguishable from PD. Finally, promising evidence exists on the possible association between MR planimetric measures and the underlying pathology, with important implications for trials with new disease-modifying target therapies.