bluuebunny/crossref_metadata_2025 huggingface dataset:
Crop Nitrogen Fertilization Schedule in Bread Wheat Affects the Mechanical Performances of Thermoplastic Films Obtained by Plasticization of Flours
Authors: Benincasa Paolo , Dominici Franco , Luzi Francesca , Governatori Catia , Gazza Laura , Galassi Elena , Tosti Giacomo , Puglia Debora
Published: February 2023

Recent research has investigated the plasticization of wheat flour as a non-food alternative application. In this work, we analyzed the performances of thermoplastic films obtained using flours of two bread wheat cultivars (Bologna and Bora) grown in fall–spring under four nitrogen (N) fertilization treatments: (1) continuously well-N-fed (N300 = 300 kg N ha−1, split throughout the growth cycle); (2) N-fed only very early (N60-0 = 60 kg N ha−1, just one month after sowing); (3) N-fed only extremely late (N0-120 = 120 kg N ha−1 at pollination); (4) unfertilized control (N0). Flours were characterized for glutenin and gliadin fractions, Chopin’s alveograph parameters, Field Emission Scanning Electron Microscopy (FESEM) images, and thermogravimetric analysis (TGA), while films were evaluated for mechanical properties (tensile strength at break, σb; elongation at break, εb; Young’s modulus, E) and FESEM images. Differences among treatments for absolute and relative abundances of gluten fractions and alveographic parameters were extremely marked and gave rise to differences in tensile properties of thermoplastic films. Within each cultivar, the ranking of treatments for εb values was N0 > N60-0 > N0-120 > N300. Thus, εb was inversely correlated with crop N availability and total gluten content of the flour. The σb was less variable among N treatments; however, in both cultivars, it was high in N0 and N300 and appreciably lower in N0-120. Overall, the best mechanical performances were obtained with flours from crops not subjected to imbalances in N nutrition (N0, N300). Our work demonstrates that bioplastic engineering needs to take into consideration the variability of biological source material like that caused by different crop N availability.
Evaluation of Selected Parameters of Oxidative Stress and Adipokine Levels in Hospitalized Older Patients with Diverse Nutritional Status
Authors: Mądra-Gackowska Katarzyna , Szewczyk-Golec Karolina , Gackowski Marcin , Woźniak Alina , Kędziora-Kornatowska Kornelia
Published: February 2023

Malnutrition is classified as one of the Giant Geriatric Syndromes. It carries serious consequences, such as sarcopenia or depression, which lead to functional disability. The main objective of this study was to identify parameters of oxidative stress and adipokines, which may be potential biomarkers of malnutrition in hospitalized older patients. During the study, selected parameters were determined in 137 senile patients, taking into account their nutritional status determined according to the Mini Nutritional Assessment (MNA), as well as an additional tool, namely the Geriatric Nutritional Risk Index (GNRI). Leptin and resistin were determined as the parameters with statistically significant differences between the patients classified according to the MNA. This phenomenon was confirmed using the GNRI classification. However, additional parameters for which differences were observed include the oxidized low-density lipoprotein level and activity of glutathione peroxidase. In conclusion, the determination of the mentioned markers in hospitalized senile patients as an adjunct to the routine assessment of nutritional status might be suggested to identify the early risk of malnutrition so that a personalized nutritional therapy can be implemented as early as possible.
Rescue of Dopamine Neurons from Iron-Dependent Ferroptosis by Doxycycline and Demeclocycline and Their Non-Antibiotic Derivatives
Authors: Tourville Aurore , Viguier Sarah , González-Lizárraga Florencia , Tomas-Grau Rodrigo Hernán , Ramirez Paola , Brunel Jean-Michel , Dos Santos Pereira Mauricio , Del-Bel Elaine , Chehin Rosana , Ferrié Laurent , Raisman-Vozari Rita , Figadère Bruno , Michel Patrick Pierre
Published: February 2023

Several studies have reported that the tetracycline (TC) class antibiotic doxycycline (DOX) is effective against Parkinson’s disease (PD) pathomechanisms. The aim of the present work was three-fold: (i) Establish a model system to better characterize neuroprotection by DOX; (ii) Compare the rescue effect of DOX to that of other TC antibiotics; (iii) Discover novel neuroprotective TCs having reduced antibiotic activity. For that, we used cultures of mouse midbrain dopamine (DA) neurons and experimental conditions that model iron-mediated oxidative damage, a key mechanism in PD pathobiology. We found that DOX and the other TC antibiotic, demeclocycline (DMC), provided sustained protection to DA neurons enduring iron-mediated insults, whereas chlortetracycline and non-TC class antibiotics did not. Most interestingly, non-antibiotic derivatives of DOX and DMC, i.e., DDOX and DDMC, respectively, were also robustly protective for DA neurons. Interestingly, DOX, DDOX, DMC, and DDMC remained protective for DA neurons until advanced stages of neurodegeneration, and the rescue effects of TCs were observable regardless of the degree of maturity of midbrain cultures. Live imaging studies with the fluorogenic probes DHR-123 and TMRM revealed that protective TCs operated by preventing intracellular oxidative stress and mitochondrial membrane depolarization, i.e., cellular perturbations occurring in this model system as the ultimate consequence of ferroptosis-mediated lipid peroxidation. If oxidative/mitochondrial insults were generated acutely, DOX, DDOX, DMC, and DDMC were no longer neuroprotective, suggesting that these compounds are mostly effective when neuronal damage is chronic and of low-intensity. Overall, our data suggest that TC derivatives, particularly those lacking antibiotic activity, might be of potential therapeutic utility to combat low-level oxidative insults that develop chronically in the course of PD neurodegeneration.
Treatment with PCSK9 Inhibitor Evolocumab Improves Vascular Oxidative Stress and Arterial Stiffness in Hypercholesterolemic Patients with High Cardiovascular Risk
Authors: Silla Alessia , Fogacci Federica , Punzo Angela , Hrelia Silvana , Simoni Patrizia , Caliceti Cristiana , Cicero Arrigo F. G.
Published: February 2023

Atherosclerosis and atherosclerotic-related cardiovascular diseases (ASCVD) are characterized by high serum levels of low-density lipoprotein cholesterol (LDL-C) that can promote the generation of reactive oxygen species (ROS). To answer the need for better LDL-C control in individuals at high and very high risk for CVD, a new injectable innovative family of lipid-lowering (LL) monoclonal antibodies against the protein convertase subtilisin/kexin type 9 (PCSK9) has been approved. However, the effect of these drugs on vascular function, such as ROS generation and arterial stiffness, has not already been extensively described. In this report, we present data from 18 males with high to very high CV risk undergoing LL treatment (LLT) with either statin and ezetimibe or ezetimibe monotherapy, who experienced, after a 2-month treatment with Evolocumab, a significant improvement in blood pressure (BP)-adjusted carotid–femoral pulse wave velocity (cfPWV) (p-value = 0.0005 in the whole cohort, p-value = 0.0046 in the sub-cohort undergoing background LLT with statin and ezetimibe, p-value = 0.015 in the sub-cohort undergoing background LLT with ezetimibe monotherapy), which was significantly associated with a decrease in freshly isolated leukocytes (PBMCS)-derived H2O2 production (p-value = 0.004, p-value = 0.02 and p-value = 0.05, respectively, in the whole cohort, in the statin + ezetimibe sub-cohort, and the ezetimibe sub-cohort). Our observations support the role of systemic oxidative stress in atherosclerosis and give a further rationale for using Evolocumab also for its effect in vascular disorders linked to oxidative processes.
Accelerated AGEing: The Impact of Advanced Glycation End Products on the Prognosis of Chronic Kidney Disease
Authors: Dozio Elena , Caldiroli Lara , Molinari Paolo , Castellano Giuseppe , Delfrate Nicholas Walter , Romanelli Massimiliano Marco Corsi , Vettoretti Simone
Published: February 2023

Advanced glycation end products (AGEs) are aging products. In chronic kidney disease (CKD), AGEs accumulate due to the increased production, reduced excretion, and the imbalance between oxidant/antioxidant capacities. CKD is therefore a model of aging. The aim of this review is to summarize the present knowledge of AGEs in CKD onset and progression, also focusing on CKD-related disorders (cardiovascular diseases, sarcopenia, and nutritional imbalance) and CKD mortality. The role of AGEs as etiopathogenetic molecules, as well as potential markers of disease progression and/or therapeutic targets, will be discussed.
IDH2 Deficiency Promotes Endothelial Senescence by Eliciting miR-34b/c-Mediated Suppression of Mitophagy and Increased ROS Production
Authors: Lee Ikjun , Piao Shuyu , Kim Seonhee , Nagar Harsha , Choi Su-jeong , Kim Minsoo , Vu Giang-Huong , Jeon Byeong-Hwa , Kim Cuk-Seong
Published: February 2023

Endothelial senescence impairs vascular function and thus is a primary event of age-related vasculature diseases. Isocitrate dehydrogenase 2 (IDH2) plays an important role in inducing alpha-ketoglutarate (α-KG) production and preserving mitochondrial function. However, the mechanism and regulation of IDH2 in endothelial senescence have not been elucidated. We demonstrated that downregulation of IDH2 induced accumulation of miR-34b/c, which impaired mitophagy and elevated mitochondrial reactive oxygen species (ROS) levels by inhibiting mitophagy-related markers (PTEN-induced putative kinase 1 (PINK1), Parkin, LC-II/LC3-I, and p62) and attenuating Sirtuin deacetylation 3 (Sirt3) expression. The mitochondrial dysfunction induced by IDH2 deficiency disrupted cell homeostasis and the cell cycle and led to endothelial senescence. However, miR-34b/c inhibition or α-KG supplementation restored Sirt3, PINK1, Parkin, LC-II/LC3-I, p62, and mitochondrial ROS levels, subsequently alleviating endothelial senescence. We showed that IDH2 played a crucial role in regulating endothelial senescence via induction of miR-34b/c in endothelial cells.
A Privacy-Enabled, Blockchain-Based Smart Marketplace
Authors: Yakubu Bello Musa , Khan Majid Iqbal , Khan Abid , Anjum Adeel , Syed Madiha Haider , Rehman Semeen
Published: February 2023

Advancements in sensor-enabled devices led to the emergence of resource trading models for smart communities, such as the smart marketplace (SMP). Most of the proposed SMP architectures are based on blockchain technology, which has a public ledger to achieve transparency. Consequently, safeguarding the participant’s anonymity, untraceability, and transactional data privacy during trading becomes a challenging task. Most of the existing solutions to achieve anonymity are based on multiple account mapping, which is prone to identity-based attacks, and cryptographic techniques are used to achieve transactional data privacy, which often has a high computational overhead. In this work, we propose a lightweight privacy-enabled message exchange mechanism to accomplish our privacy goals in a blockchain-based SMP. Evaluation of the scheme was conducted to measure its resilience toward safeguarding participants’ anonymity, untraceability, and transactional data privacy during trading cycles. Statistical game theory-based security analysis and simulation based performance analysis of the proposed scheme showed that it achieved the desired privacy goals with a low computational overhead compared with existing state-of-the-art schemes.
Numerical Simulation and Experimental Verification of Wind Field Reconstruction Based on PCA and QR Pivoting
Authors: Liu Shi , Zhang Guangchao
Published: February 2023

Short-term wind forecasting is critical for the dispatch, controllability and stability of a power grid. As a challenging but indispensable work, short-term wind forecasting has attracted considerable attention from researchers. In this paper, Principal Component Analysis (PCA) is applied to Computational Fluid Dynamics (CFD) calculation results for feature extraction and then combined with sparse sensing to achieve the rapid reconstruction of a three-dimensional wind speed field and pressure field. Before reconstruction, the relationship between the reconstruction error and the noise level, and a number of the basis vectors is systematically studied. In the simulation, the wind shear effect is introduced into the inlet boundary condition, and the reconstruction errors of the uniform inlet are 0.21% and 6.46%, respectively, while the maximum reconstruction errors including the wind shear effect are 1.21% and 6.41%, respectively, which verifies the feasibility of applying a PCA-based reconstruction algorithm to a 3D wind field reconstruction. In addition, to solve the time-consuming problem of most optimization algorithms based on a brute-force combinatorial search, an innovative optimization algorithm based on the QR pivoting is investigated to determine the sparse sensor placements. Simulation results show that when the number of sensors is equal to the number of basis vectors, the error of random placement is even 20 times of the optimal placement, which illustrates that QR pivoting is a powerful optimization algorithm. Finally, a wind tunnel experiment of velocity field reconstruction is performed, to verify the practicability of the optimized method based on QR pivoting, and the results indicate that a reasonably high accuracy 3D wind field can be obtained with only 10 sensors (the error of most points is less than 5% and the minimum error is only 0.74%). In general, the proposed algorithm incorporating PCA, sparse sensing and QR pivoting can quickly reconstruct the 3D velocity and pressure fields with reduced measurement costs, which is of great significance for the development of short-term wind forecasting methods.
Application of Improved Process Neural Network Based on the Fireworks Algorithm in the Temperature-Rise Predictions of a Large Generator Rotor
Authors: Guo Wu , Guo Jian , Miao Fengjuan
Published: February 2023

Building an effective algorithm model for large key power equipment has very important research significance and application value. Aiming at the typical operating state characteristics of large generators and taking the temperature changes as the main research indicators, the improved fireworks algorithm was used to optimize the process neural network, and the key data characteristics were studied based on the machine experiment and actual operation data of a 300 MW generator so as to find the variation and development trends of the maximum temperature rise caused by negative-sequence current. Furthermore, the effectiveness of the neural network model suitable for large generators established in this paper was verified by test functions and experiments. On this basis, the calculation method was applied to different working conditions, component materials, and heating positions of the generator. Moreover, the temperature-rise prediction results of the structural components for the generator rotor were obtained, and the optimization scheme of the slot wedge material given, which provide a reference for temperature-rise research and the selection of component materials for large generators.
A Sensitive and Practical Evaluation to Detect Lower-Limb Strength Changes in Geriatrics: The Isometric Knee Extension Test
Authors: Buendía-Romero Ángel , Hernández-Belmonte Alejandro , Franco-López Francisco , Romero-Borrego Eduardo , Cava Alejandro M. , Pallarés Jesús G. , Courel-Ibáñez Javier
Published: February 2023

This study aimed to examine the sensitivity of the isometric knee extension (IKE) test to detect changes in the lower-limb strength of institutionalized older adults after exercise and inactivity periods. Thirty-four and fifteen institutionalized older adults completed the training and inactive periods, respectively. At each time point, the participants completed two testing sessions. In the first session, they performed the IKE test. As a complement to this evaluation, the second testing session was used to assess their functional capacity and handgrip strength. The sensitivity of the IKE test was examined by comparing the changes generated in this test against the repeatability of the protocol. A 4-week multicomponent Vivifrail program was implemented. After that, a subsample of the participants was re-evaluated after a 14-week inactivity period. Significant changes (p < 0.01; ES ≥ 0.27) in the IKE strength for both the dominant (+0.27 N/kg) and non-dominant legs (+0.25 N/kg) were produced after the training intervention. Likewise, significant decrements (p < 0.01; ES ≥ 0.31) were detected after the inactive period for the dominant (−0.29 N/kg) and non-dominant legs (−0.32 N/kg). All mean changes were found to be superior to the variability threshold of the IKE test for both legs, with superior sensitivity for the non-dominant leg (≥73%). Thus, the IKE test is a sensitive and practical tool for detecting changes in the lower-limb strength of institutionalized older adults after exercise and inactivity periods. Because of its applicability, it seems pertinent to implement the IKE test in a geriatric context.
Time-Frequency Feature-Based Seismic Response Prediction Neural Network Model for Building Structures
Authors: Zhang Peng , Li Yiming , Lin Yu , Jiang Huiqin
Published: February 2023

Currently, machine learning techniques are widely used in structural seismic response studies. The developed network models for various types of seismic response provide new ways to analyse seismic hazards. However, it is not easy to balance the applicability of the input, accuracy, and computational efficiency for existing network models. In this paper, a neural network model containing an efficient self-adaptive feature extraction module (AFEM) is designed. It can recognize time-frequency features from ground motion (GM) inputs for structural seismic response prediction tasks while considering the model’s computational accuracy and computational cost. The self-adaptive feature extraction module is constructed based on the MFCCs feature extraction process in NLP. AFEM recognizes time-frequency features closely related to structures’ behaviour and response under dynamic loads. Taking the seismic response prediction of a typical building as the target task, the neural network configuration, including a baseline model M0 and three comparison models (M1, M2, and M3) with AFEM, is systematically analysed. The results demonstrate that the proposed M1 model with initial AFEM, the M2 model with combined amplitude and phase features, and the M3 model with a complex-valued network are more adaptable than the baseline model to the target task. The extracted amplitude and phase features by the M3 model’s AFEM significantly improve model validation accuracy by 8.6% while reducing computation time by 11.4%. It could provide the basis for future research on regional earthquake damage intelligence assessment systems.
RBCN-Net: A Data-Driven Inertial Navigation Algorithm for Pedestrians
Authors: Zhu Yiqi , Zhang Jinglin , Zhu Yanping , Zhang Bin , Ma Weize
Published: February 2023

Pedestrian inertial navigation technology plays an important role in indoor positioning technology. However, low-cost inertial sensors in smart devices are affected by bias and noise, resulting in rapidly increasing and accumulating errors when integrating double acceleration to obtain displacement. The data-driven class of pedestrian inertial navigation algorithms can reduce sensor bias and noise in IMU data by learning motion-related features through deep neural networks. Inspired by the RoNIN algorithm, this paper proposes a data-driven class algorithm, RBCN-Net. Firstly, the algorithm adds NAM and CBAM attention modules to the residual network ResNet18 to enhance the learning ability of the network for channel and spatial features. Adding the BiLSTM module can enhance the network’s ability to learn over long distances. Secondly, we construct a dataset VOIMU containing IMU data and ground truth trajectories based on visual inertial odometry (total distance of 18.53 km and total time of 5.65 h). Finally, the present algorithm is compared with CNN, LSTM, ResNet18 and ResNet50 networks in VOIMU dataset for experiments. The experimental results show that the RMSE values of RBCN-Net are reduced by 6.906, 2.726, 1.495 and 0.677, respectively, compared with the above networks, proving that the algorithm effectively improves the accuracy of pedestrian navigation.
Application of Failure Mode Effects Analysis for Maintenance of Turnout System on Serviced Urban Rapid Transit
Authors: Choi Jung-Youl , Kim Sun-Hee , Han Kyung-Sung , Chung Jee-Seung
Published: February 2023

Over the past 25 years, maintenance processes for the wooden sleeper turnouts of sleeper floating tracks (known as STEDEF) have been insufficient, lacking accurate maintenance history and failure cause analyses. Currently, damaged parts are repeatedly replaced without an analysis of the cause of their failure. Therefore, it has been difficult to predict potential damages due to the lack of maintenance history data on the replaced items and the timing of the turnout component. This study proposes a turnout maintenance plan using the failure mode and effects analysis (FMEA) technique to analyze the turnout maintenance history data for a period spanning 10 years. The maintenance damage type of the turnout was classified to confirm the cause of damage and the damage frequency. Additionally, components that could lower the occurrence score were selected based on a risk analysis of the turnover. Therefore, it was possible to reduce the risk occurrence score by improving the size of the turnout top plate and the number of bolts.
An Analysis of the Process of Applying Technical Lubricating Coatings
Authors: Ochowiak Marek , Werowska Klaudia , Krupińska Andżelika , Matuszak Magdalena , Włodarczak Sylwia , Bielecki Zdzisław
Published: February 2023

The results of research on the process of applying lubricating coatings are presented in this work. For this purpose, plastic greases were used, in which the base oil is perfluoropolyether (PFPE) and the thickener is poly(tetrafluoroethylene) (PTFE). Due to their consistency, these materials are classified into different classes according to the National Lubricating Grease Institute (NLGI). The research was carried out using a time-pressure valve at varying atomization pressure values. Based on the obtained results, the width of the obtained material path and the angle of spray atomization were determined. The research indicated linear relationships between the atomization pressure and the degree of uniformity of the obtained spray.
FEAROL: Aging Flow Entries Based on Local Staircase Randomized Response for Secure SDN Flow Tables
Authors: Liao Ling Xia , Ma Xiaohang , Zhao Changqing , Li Zhi , Chao Han-Chieh
Published: February 2023

Software-Defined Networking (SDN) systems are sensitive to the lifespans of flow entries in flow tables as such lifespans affect the overall network-forwarding latency and the flow table space usage, particularly when the systems are under cyber attack. Instead of developing extra approaches to reactively detect the attacks and mitigate the impact of the attacks, this paper views the lifespans of flow entries as the privacy of the SDN systems and proposes a Flow-Entry Aging RandOmization Layer (FEAROL), which applies the staircase randomized response mechanism in the flow-entry-aging process at switches. FEAROL locally perturbs the lifespan of each flow entry in the flow table. Since the true lifespan of each flow entry is different from the lifespan set in the entry by the controller and dynamically perturbed by FEAROL, Low-rate Denial-of-Service (LDoS) attacks based on the sniffed flow-entry timeouts cannot be effectively organized. FEAROL proactively prevents LDoS attacks from overflowing the flow tables and legitimate flow packets from being dropped due to the broken synchronization between attack flows and the network settings. FEAROL can adjust its aging policies and privacy budget based on the real-time monitored network performance. FEAROL is prototyped in an open-source soft switch (OpenVSwitch) and evaluated through simulations on real network traces. The results show that FEAROL increases the overhead of aging a flow entry. However, this overhead can be significantly reduced by adjusting the interval at which the aging process is triggered. FEAROL also effectively defends against flow table overflow LDoS attacks by significantly reducing the table usage of LDoS attack flows. When the aging strategy is carefully chosen, the table space used by attack flow entries can be reduced to 0.
Kefir Enriched with Encapsulated Volatile Oils: Investigation of Antimicrobial Activity and Chemical Composition
Authors: Tița Mihaela Adriana , Constantinescu Maria Adelina , Opruța Tiberius Ilie , Bătuşaru Cristina , Rusu Lăcrămioara , Tița Ovidiu
Published: February 2023

The present study was designed to determine the changes in the chemical composition of kefir enriched with encapsulated volatile oils by enzymatic methods and the antimicrobial activity of volatile oils. Using encapsulated volatile oils (fennel, mint, and lavender) and cow’s milk, we created three different forms of kefir. To highlight the antiseptic capacity of the volatile oils, we performed their antimicrobial analysis on three types of molds (Geotrichum candidum, Penicillium expansum, Aspergillus niger) and one Gram-negative bacterium (Escherichia coli). The technique used to determine antimicrobial activity was Kirby–Bauer. The changes in the chemical composition of kefir samples with encapsulated volatile oils were analyzed using enzymatic methods and were compared with a control sample of kefir. The main analyzed chemical compounds were lactose, D-glucose, D-galactose, acetic acid, ethanol, L-lactic acid, and L-glutamic acid. The kefir samples enriched with volatile oils obtained superior results compared to the control sample during the whole analysis period. The main advantage of using encapsulation is that the bioactive compounds of the volatile oils are gradually released in the kefir sample due to the protection provided by sodium alginate. As a result, products with high nutritional values were obtained that are beneficial to the consumer’s health and have a longer shelf life thanks to the volatile oils’ antimicrobial properties.
Fracture Resistance Evaluation and Failure Modes Rating Agreement for Two Endocrown Designs: An In Vitro Study
Authors: Alzahrani Saeed J. , Hajjaj Maher S. , Yeslam Hanin E. , Marghalani Thamer Y.
Published: February 2023

This in vitro study aimed to evaluate the fracture resistance and mode of failure of endocrowns with proximal extension design compared to the conventional design, and to assess the agreement of evaluators on the failure mode. Twenty mandibular third molars free of caries with approximately similar root lengths and crown dimensions were sectioned parallel to the occlusal plane 2 mm above the cementoenamel junction (CEJ). Then, pulp chambers and canals were accessed, cleaned, and smoothed for the path of insertion. To achieve a symmetrical pulp chamber with an average depth of 3 mm, chambers were filled with flowable resin composite. Then, teeth were randomly divided into two groups (n = 10). The control group has all the walls at the same level. The test group had a box extension on the proximal wall 2 mm apical to the buccal and lingual wall level. Endocrowns (n = 20) of two different designs (conventional and proximal extensions) were fabricated using lithium disilicate (IPS e.max CAD, Ivoclar Vivadent, Schaan, Liechtenstein). After cementation, specimens were loaded with a round-end vertical loading tip at a rate of 0.5 mm per minute until fracture (INSTRON, Norwood, MA, USA). Then, the fractured specimens were collected for evaluation and assessment. Statistical analyses were performed using the Mann-Whitney U-test (α = 0.05) for fracture test analysis and Cohen’s Kappa for inter-rater reliability. The Mann-Whitney U-test showed a non-significant difference between the two groups (p = 0.142). However, the mode of failure of the endocrown with proximal extension showed more catastrophic failures than the conventional design. Adding proximal boxes to the endocrown design did not negatively impact the fracture resistance of the restoration. Visualization of the fracture line and tracing their apical end by direct vision or other diagnostic tools is an essential part of the evaluation of failures of endocrowns. Endodontically treated molar teeth with proximal caries extension might be restored with an endocrown with proximal extension. Clinicians should take extra care when visualizing the fracture lines and tracing their apical end as it might be very misleading.
Analysis of Factors Affecting Purchase of Self-Defense Tools among Women: A Machine Learning Ensemble Approach
Authors: Borres Rianina D. , Ong Ardvin Kester S. , Arceno Tyrone Wyeth O. , Padagdag Allyza R. , Sarsagat Wayne Ralph Lee B. , Zuñiga Hershey Reina Mae S. , German Josephine D.
Published: February 2023

Street crime is one of the world’s top concerns and a surge in cases has alarmed people, particularly women. Related studies and recent news have provided proof that women are the target for crimes and violence at home, outdoors, and even in the workplace. To guarantee protection, self-defense tools have been developed and sales are on the rise in the market. The current study aimed to determine factors influencing women’s intention to purchase self-defense tools by utilizing the Protection Motivation Theory (PMT) and the Theory of Planned Behavior (TPB). The study applied multiple data analyses, Machine Learning Algorithms (MLAs): Decision Tree (DT), Random Forest Classifier (RFC), and Deep Learning Neural Network (DLNN), to predict purchasing and consumer behavior. A total of 553 Filipino female respondents voluntarily completed a 46-item questionnaire which was distributed online, yielding 22,120 data points. The MLAs output showed that attitude, perceived risk, subjective norm, and perceived behavioral control were the most significant factors influencing women’s intention to purchase self-defense tools. Environment, hazardous surroundings, relatives and peers, and thinking and control, all influenced the women’s intention to buy self-defense tools. The RFC and DLNN analyses proved effective, resulting in 96% and 97.70% accuracy rates, respectively. Finally, the MLA analysis in this research can be expanded and applied to predict and assess factors affecting human behavior in the context of safety.
A Free-Space Transmission Setup for Material Parameters Estimation with Affordable and Non-Synchronized Software-Defined Radios in the 0.85–1.55 GHz Band
Authors: Gonçalves Fábio Júlio Fonseca , Brancaccio Adriana , Ferreira Leonardo Augusto , da Silva Elson José
Published: February 2023

This paper describes a prototype of a free-space transmission setup for dielectric parameters estimation. The transmitter and receiver, both configurable by software and working in the range 0.85–1.55 GHz, are not synchronized, as they use different clocks. An estimation of the dielectric permittivity of a planar sample was obtained by comparing our measurements with a numerical model. A parametric study with different variables was conceived in order to find the best fit between measurements and simulations. Customized techniques were applied to deal with noise and inconsistencies found in the measurements. The genetic algorithm was used to adjust the constants that minimized the error between simulated and experimental data. Results for a reference sample of polymethylmethacrylate are presented and discussed. Although the accuracy of the proposed approach in recovering the dielectric parameters of the sample was relatively low, the simplicity and cost-effectiveness of this setup make it interesting for scenarios where a rough characterization of the material is sufficient.
Numerical Investigation on the Influence of Breakwater and the Sediment Transport in Shantou Offshore Area
Authors: Wu Yuxi , Zhu Kui , Qin Hao , Wang Yang , Sun Zhaolong , Jiang Runxiang , Wang Wanhu , Yi Jiaji , Wang Hongbing , Zhao Enjin
Published: February 2023

The coastline of Shantou is tortuous, while the hydrodynamic environment is complicated. In this paper, the hydrodynamic model is established by the FVCOM (Finite Volume Coastal Ocean Model); the open boundary conditions such as water level, river, and wind field are the input; and the model is verified by tidal harmonic function. According to the previous research, the typhoon wind field with a 10-year return period is selected for storm surge simulation. When there is a bank, the accumulated water on the land cannot enter the ocean due to the block of the bank but accumulates on the inner side of the bank, resulting in higher accumulated water, but less than 0.5 m. In the aspect of sediment deposition, a sediment transport model is established to analyze the sediment deposition in Shantou Port and its surrounding waters. Some reasonable suggestions are put forward for the sediment deposition in Shantou. According to the simulation results, the following conclusions can be drawn: (1) In the case of typhoon storm surge in the return period of 10 years, the bank can effectively protect the inland. Still, accumulated water will collect near the bank. (2) The offshore water level will rise by 0.4 m after adding a bank. (3) The sediment in Shantou Bay mainly comes from the ocean sediment caused by tides, and the largest sedimentation occurs in the main channel.
The Effect of Light Availability on Photosynthetic Responses of Four Aglaonema commutatum Cultivars with Contrasting Leaf Pigment
Authors: Hui Junai , Wu Canhang , Li Xiaomei , Huang Leying , Jiang Yongqiang , Zhang Bipei
Published: February 2023

Plants can be grouped into sun- and shade-type owing to their distinct irradiance adaptation. Aglaonema commutatum is a typical shade-tolerant perennial foliage plant native to South Asia with various leaf colorations. ‘Red’ cultivars are widely used for interior decorations and as courtyard ornamental plants, owing to their unique hue and bi-adaptation of both low and high irradiance. However, the underlying source of ‘red’ pigment-dependent irradiance bi-adaptation remains largely unknown. Therefore, four A. commutatum cultivars were comparatively evaluated in terms of pigment composition and photosynthetic rate under full light (sunlight) or 50% full light (shade) to unveil the relationship between pigmentation and irradiance bi-adaptation. Our results showed that the photosynthetic rate of sun leaves generated from light response curves was significantly correlated with anthocyanin content and chlorophyll in red cultivars, suggesting the influence of anthocyanin–light interactions on the high/low irradiance bi-adaptation of red A. commutatum. This study provides a theoretical basis for further cultivating red foliage A. commutatum cultivars under diverse light conditions.
Korean Sign Language Recognition Using Transformer-Based Deep Neural Network
Authors: Shin Jungpil , Musa Miah Abu Saleh , Hasan Md. Al Mehedi , Hirooka Koki , Suzuki Kota , Lee Hyoun-Sup , Jang Si-Woong
Published: February 2023

Sign language recognition (SLR) is one of the crucial applications of the hand gesture recognition and computer vision research domain. There are many researchers who have been working to develop a hand gesture-based SLR application for English, Turkey, Arabic, and other sign languages. However, few studies have been conducted on Korean sign language classification because few KSL datasets are publicly available. In addition, the existing Korean sign language recognition work still faces challenges in being conducted efficiently because light illumination and background complexity are the major problems in this field. In the last decade, researchers successfully applied a vision-based transformer for recognizing sign language by extracting long-range dependency within the image. Moreover, there is a significant gap between the CNN and transformer in terms of the performance and efficiency of the model. In addition, we have not found a combination of CNN and transformer-based Korean sign language recognition models yet. To overcome the challenges, we proposed a convolution and transformer-based multi-branch network aiming to take advantage of the long-range dependencies computation of the transformer and local feature calculation of the CNN for sign language recognition. We extracted initial features with the grained model and then parallelly extracted features from the transformer and CNN. After concatenating the local and long-range dependencies features, a new classification module was applied for the classification. We evaluated the proposed model with a KSL benchmark dataset and our lab dataset, where our model achieved 89.00% accuracy for 77 label KSL dataset and 98.30% accuracy for the lab dataset. The higher performance proves that the proposed model can achieve a generalized property with considerably less computational cost.
Genetic Variation versus Morphological Variability in European Peatland Violets (Viola epipsila—V. palustris Group)
Authors: Żabicka Justyna , Kirschey Tom , Migdałek Grzegorz , Słomka Aneta , Kuta Elżbieta
Published: February 2023

In Europe, the V. epipsila—V. palustris group comprises V. epipsila Ledeb., V. palustris L., V. pubifolia (Kuta) G. H. Loos (=V. palustris subsp. pubifolia Kuta), interspecific hybrids, and putative introgressants. The genetic affinity of V. pubifolia to V. palustris, and their shared origin via hybridization followed by polyploidization, were confirmed using inter simple sequence repeat (ISSR) markers, restriction site-associated DNA sequencing (RAD-Seq), and a low-copy nuclear gene, GPI, which encodes glucose-6-phosphate isomerase. The other taxa of subsect. Stolonosae were not identified as putative parents of V. pubifolia by GPI. Our analyses indicated that V. pubifolia can be included in the morphological and genetic variation of V. palustris. The ISSR, RAD-Seq, and genome size value separated well V. palustris from V. epipsila and hybrids. The results also reopen the discussion on intraspecific variation in the context of taxa ranks and species concepts. The reduced tolerance of V. epipsila in Europe to changing environmental conditions might result from low genetic differentiation and heterozygosity, as well as the increased number of interspecific hybrids (V. epipsila × V. palustris), and eventually can possibly lead to its extinction. The disappearance of populations/individuals of this species may indicate anthropogenic changes occurring in peatlands.
IS481EU Shows a New Connection between Eukaryotic and Prokaryotic DNA Transposons
Authors: Kojima Kenji K. , Bao Weidong
Published: February 2023

DDD/E transposase gene is the most abundant gene in nature and many DNA transposons in all three domains of life use it for their transposition. A substantial number of eukaryotic DNA transposons show similarity to prokaryotic insertion sequences (ISs). The presence of IS481-like DNA transposons was indicated in the genome of Trichomonas vaginalis. Here, we surveyed IS481-like eukaryotic sequences using a bioinformatics approach and report a group of eukaryotic IS481-like DNA transposons, designated IS481EU, from parabasalids including T. vaginalis. The lengths of target site duplications (TSDs) of IS481EU are around 4 bps, around 15 bps, or around 25 bps, and strikingly, these discrete lengths of TSDs can be observed even in a single IS481EU family. Phylogenetic analysis indicated the close relationships of IS481EU with some of the prokaryotic IS481 family members. IS481EU was not well separated from IS3EU/GingerRoot in the phylogenetic analysis, but was distinct from other eukaryotic DNA transposons including Ginger1 and Ginger2. The unique characteristics of IS481EU in protein sequences and the distribution of TSD lengths support its placement as a new superfamily of eukaryotic DNA transposons.
Using Attribution Sequence Alignment to Interpret Deep Learning Models for miRNA Binding Site Prediction
Authors: Grešová Katarína , Vaculík Ondřej , Alexiou Panagiotis
Published: February 2023

MicroRNAs (miRNAs) are small non-coding RNAs that play a central role in the post-transcriptional regulation of biological processes. miRNAs regulate transcripts through direct binding involving the Argonaute protein family. The exact rules of binding are not known, and several in silico miRNA target prediction methods have been developed to date. Deep learning has recently revolutionized miRNA target prediction. However, the higher predictive power comes with a decreased ability to interpret increasingly complex models. Here, we present a novel interpretation technique, called attribution sequence alignment, for miRNA target site prediction models that can interpret such deep learning models on a two-dimensional representation of miRNA and putative target sequence. Our method produces a human readable visual representation of miRNA:target interactions and can be used as a proxy for the further interpretation of biological concepts learned by the neural network. We demonstrate applications of this method in the clustering of experimental data into binding classes, as well as using the method to narrow down predicted miRNA binding sites on long transcript sequences. Importantly, the presented method works with any neural network model trained on a two-dimensional representation of interactions and can be easily extended to further domains such as protein–protein interactions.
Tutorial for Stopped-Flow Water Flux Measurements: Why a Report about “Ultrafast Water Permeation through Nanochannels with a Densely Fluorous Interior Surface” Is Flawed
Authors: Pfeffermann Juergen , Pohl Peter
Published: February 2023

Millions of years of evolution have produced proteinaceous water channels (aquaporins) that combine perfect selectivity with a transport rate at the edge of the diffusion limit. However, Itoh et al. recently claimed in Science that artificial channels are 100 times faster and almost as selective. The published deflation kinetics of vesicles containing channels or channel elements indicate otherwise, since they do not demonstrate the facilitation of water transport. In an illustrated tutorial on the experimental basis of stopped-flow measurements, we point out flaws in data processing. In contrast to the assumption voiced in Science, individual vesicles cannot simultaneously shrink with two different kinetics. Moreover, vesicle deflation within the dead time of the instrument cannot be detected. Since flawed reports of ultrafast water channels in Science are not a one-hit-wonder as evidenced by a 2018 commentary by Horner and Pohl in Science, we further discuss the achievable limits of single-channel water permeability. After analyzing (i) diffusion limits for permeation through narrow channels and (ii) hydrodynamics in the surrounding reservoirs, we conclude that it is unlikely to fundamentally exceed the evolutionarily optimized water-channeling performance of the fastest aquaporins while maintaining near-perfect selectivity.
Machine Learning Model Based on Insulin Resistance Metagenes Underpins Genetic Basis of Type 2 Diabetes
Authors: Saxena Aditya , Mathur Nitish , Pathak Pooja , Tiwari Pradeep , Mathur Sandeep Kumar
Published: February 2023

Insulin resistance (IR) is considered the precursor and the key pathophysiological mechanism of type 2 diabetes (T2D) and metabolic syndrome (MetS). However, the pathways that IR shares with T2D are not clearly understood. Meta-analysis of multiple DNA microarray datasets could provide a robust set of metagenes identified across multiple studies. These metagenes would likely include a subset of genes (key metagenes) shared by both IR and T2D, and possibly responsible for the transition between them. In this study, we attempted to find these key metagenes using a feature selection method, LASSO, and then used the expression profiles of these genes to train five machine learning models: LASSO, SVM, XGBoost, Random Forest, and ANN. Among them, ANN performed well, with an area under the curve (AUC) > 95%. It also demonstrated fairly good performance in differentiating diabetics from normal glucose tolerant (NGT) persons in the test dataset, with 73% accuracy across 64 human adipose tissue samples. Furthermore, these core metagenes were also enriched in diabetes-associated terms and were found in previous genome-wide association studies of T2D and its associated glycemic traits HOMA-IR and HOMA-B. Therefore, this metagenome deserves further investigation with regard to the cardinal molecular pathological defects/pathways underlying both IR and T2D.
Evidence of Nrf2/Keap1 Signaling Regulation by Mitochondria-Generated Reactive Oxygen Species in RGK1 Cells
Authors: Indo Hiroko , Masuda Daisuke , Sriburee Sompong , Ito Hiromu , Nakanishi Ikuo , Matsumoto Ken-ichiro , Mankhetkorn Samlee , Chatatikun Moragot , Surinkaew Sirirat , Udomwech Lunla , Kawakami Fumitaka , Ichikawa Takafumi , Matsui Hirofumi , Tangpong Jitbanjong , Majima Hideyuki
Published: February 2023

It has been known that reactive oxygen species (ROS) are generated from the mitochondrial electron transport chain (ETC). Majima et al. proved that mitochondrial ROS (mtROS) caused apoptosis for the first time in 1998 (Majima et al. J Biol Chem, 1998). It is speculated that mtROS can move out of the mitochondria and initiate cellular signals in the nucleus. This paper aims to prove this phenomenon by assessing the change in the amount of manganese superoxide dismutase (MnSOD) by MnSOD transfection. Two cell lines of the same genetic background, of which generation of mtROS are different, i.e., the mtROS are more produced in RGK1, than in that of RGM1, were compared to analyze the cellular signals. The results of immunocytochemistry staining showed increase of Nrf2, Keap1, HO-1 and 2, MnSOD, GCL, GST, NQO1, GATA1, GATA3, GATA4, and GATA5 in RGK1 compared to those in RGM1. Transfection of human MnSOD in RGK1 cells showed a decrease of those signal proteins, suggesting mtROS play a role in cellular signals in nucleus.
Identification of Prognosis-Related Oxidative Stress Model with Immunosuppression in HCC
Authors: Ren Zhixuan , Zhang Jiakang , Zheng Dayong , Luo Yue , Song Zhenghui , Chen Fengsheng , Li Aimin , Liu Xinhui
Published: February 2023

For hepatocellular carcinoma (HCC) patients, we attempted to establish a new oxidative stress (OS)-related prognostic model for predicting prognosis, exploring immune microenvironment, and predicting the immunotherapy response. Significantly differently expressed oxidative stress-related genes (DEOSGs) between normal and HCC samples from the Cancer Genome Atlas (TCGA) were screened, and then based on weighted gene coexpression network analysis (WGCNA), HCC-related hub genes were discovered. Based on the least absolute shrinkage and selection operator (LASSO) and cox regression analysis, a prognostic model was developed. We validated the prognostic model’s predictive power using an external validation cohort: the International Cancer Genome Consortium (ICGC).Then a nomogram was determined. Furthermore, we also examined the relationship of the risk model and clinical characteristics as well as immune microenvironment. 434 DEOSGs, comprising 62 downregulated and 372 upregulated genes (p < 0.05 and |log2FC| ≥ 1), and 257 HCC-related hub genes were recognized in HCC. Afterward, we built a five-DEOSG (LOX, CYP2C9, EIF2B4, EZH2, and SRXN1) prognostic risk model. Using the nomogram, the risk model was shown to have good prognostic value. Compared to the low risk group, HCC patients with high risk had poorer outcomes, worse pathological grades, and advanced tumor stages (p < 0.05). There were significant increases in LOX, EIF2B4, EZH2, and SRXN1 expression in HCC samples, while CYP2C9 expression was decreased. Finally, Real-time PCR (RT-qPCR) confirmed the mRNA expressions of five genes (CYP2C9, EIF2B4, EZH2, SRXN1, LOX) in HCC cell lines. Our study constructed a prognostic OS-related model with strong predictive power and potential as an immunosuppressive biomarker for HCC leading to improving prediction and providing new insights for HCC immunotherapy.