bluuebunny/crossref_metadata_2025 huggingface dataset:
An Evaluation of the Impact of Increasing the Awareness of the WHO Access, Watch, and Reserve (AWaRe) Antibiotics Classification on Knowledge, Attitudes, and Hospital Antibiotic Prescribing Practices
Authors: Abu-Ajaleh Salam , Darwish Elhajji Feras , Al-Bsoul Shatha , Abu Farha Rana , Al-Hammouri Fawzi , Amer Amer , Al Rusasi Ahmed , Al-Azzam Sayer , Araydah Mohammad , Aldeyab Mamoon A.
Published: May 2023

: The study aims to determine the effect of enhancing knowledge and awareness of the WHO Access, Watch, and Reserve (AWaRe) antibiotics classification on hospital clinical staff’s knowledge, attitudes and antibiotic prescribing practices. A pre-post-intervention study design was employed. The intervention was an educational activity that involved teaching physicians and pharmacists about the AWaRe classification and the risk of antibiotic resistance. A questionnaire was administered to clinical staff pre-and post-intervention. In the pre-interventional stage, 78.5% of participants stated they had not heard about the AWaRe classification of antibiotics. After receiving the intervention: the knowledge regarding the meaning and purpose of AWaRe classification of antibiotics increased from 39.1% to 75.4%; the percentage of participants who agreed with following the AWaRe classification of antibiotics in their practice increased from 21.7% to 58.5%; and the percentage of participants who agreed that AWaRe classification of antibiotics can suggest safe choices of antibiotics increased from 56.5% to 90.8%. Hospital antibiotic use of the Access group increased by 6.6% from pre- to post-intervention. The use of the Watch group and Reserve group decreased post-intervention by 1.7%, and 43.1%, respectively. This study showed important gaps in knowledge and attitudes towards AWaRe, highlighting the need for increasing the awareness of the AWaRe tool amongst healthcare practitioners to ensure rational use of antibiotics.
In Vitro Activity of Omadacycline and Comparator Antibiotics against Extended-Spectrum Beta-Lactamase-Producing Escherichia coli and Klebsiella pneumoniae Urinary Isolates
Authors: Stone Tyler J. , Kilic Abdullah , Williamson John C. , Palavecino Elizabeth L.
Published: May 2023

Limited oral antibiotic options exist for urinary tract infections (UTI) caused by ESBL-producing Enterobacterales. The aim of the study was to evaluate in vitro activity of omadacycline and comparator antibiotics against clinical ESBL-producing and non-ESBL-producing E. coli and K. pneumoniae urinary isolates. 102 isolates each of E. coli and K. pneumoniae were collected from clinical urine specimens in 2019. By design, an equal number of each species were included that tested positive and negative for ESBL production. Omadacycline MICs were determined using gradient test strips and compared to MICs of comparator antibiotics as determined by an automated broth microdilution system. Isolates were considered susceptible to omadacycline if the MIC was ≤4 µg/mL for each species. 54.9% of all ESBL-producing isolates were susceptible to omadacycline, but better susceptibility was observed for ESBL-producing E. coli (74.5%). Omadacycline MICs were 2–4 fold lower for E. coli and K. pneumoniae strains not producing ESBL. The omadacycline MIC 50 and 90 values were 4 and 16 µg/mL, respectively, for all isolates studied. 74.5% of all isolates were considered susceptible to omadacycline. MICs were generally lower for E. coli strains with MIC 50 and 90 values of 4 and 8 µg/mL, respectively (87.3% susceptible), compared with K. pneumoniae. Overall, the most active agents were omadacycline and nitrofurantoin, while other comparator antibiotics were less active. Omadacycline represents a promising oral antibiotic for treating UTI caused by ESBL-producing E. coli, particularly when resistance limits other oral options. Prospective, controlled clinical trials are needed to validate these in vitro results.
Research on Red Jujubes Recognition Based on a Convolutional Neural Network
Authors: Wu Jingming , Wu Cuiyun , Guo Huaying , Bai Tiecheng , He Yufeng , Li Xu
Published: May 2023

Red jujube is one of the most important crops in China. In order to meet the needs of the scientific and technological development of the jujube industry, solve the problem of poverty, realize the backward advantage, and promote economic development, smart agriculture is essential. The main objective of this study was to conduct an online detection study of unpicked red jujubes in order to detect as many red jujubes in the picture as possible while minimizing the occurrence of overfitting and underfitting. Experiments were conducted using the Histogram of Oriented Gradients + Support Vector Machine (HOG+SVM) traditional detection method and the You Only Look Once version 5 (YOLOV5) and Faster R-CNN modern deep learning detection methods. The precision, recall, and F1 score were compared to obtain a better algorithm. The study also introduced the AlexNet model with the main objective of attempting to combine it with other traditional algorithms to maximize accuracy. Labeling was used to label the training images in YOLOV5 and Faster Regions with CNN Features (Faster R-CNN) to train the machine model so that the computer recognized these features when it saw new unlabeled data in subsequent experiments. The experimental results show that in the online recognition detection of red jujubes, the YOLOV5 and Faster R-CNN algorithms performed better than the HOG + SVM algorithm, which presents precision, recall, and F1 score values of 93.55%, 82.79%, and 87.84% respectively; although the HOG + SVM algorithm was relatively quicker to perform. The precision of detection was obviously more important than the efficiency of detection in this study, so the YOLOV5 and Faster R-CNN algorithms were better than the HOG + SVM algorithm. In the experiments, the Faster R-CNN algorithm had 100% precision, 99.65% recall, an F1 score of 99.82%, and 83% non-underfitting images for the recognized images, all of which were higher than YOLOV5′s values, with 97.17% recall, an F1 score of 98.56%, and 64.42% non-underfitting. In this study, therefore, the Faster R-CNN algorithm works best.
Deep TDEM Study for Structural and Mining Purposes: A Case Study of the Barbastro Saline-Evaporitic Formation, Spain
Authors: Porras Daniel , Carrasco Javier , Carrasco Pedro , Herrero-Pacheco José Luis
Published: May 2023

The objective of this study was to obtain the deep subsurface structure of a saline-evaporitic formation affected by an anticlinal structure, defining the position and thickness for its future exploitation (potassium salts). To improve this knowledge, geophysical methods can be applied to establish detailed information on geological structures at depth. This work analyzes the results of a deep time domain electromagnetic (TDEM) survey acquired over the southern flank of the Barbastro-Balaguer Anticline present in the Ebro Basin in the vicinity of Graus (Huesca, Spain), that controls the geometry of the Barbastro saline-evaporitic formation, of interest from the mining point of view. A deep time domain electromagnetic system (TDEM) is used, providing a penetration capability down to 3.0 km depth. A parametric constrained inversion over a lithological known borehole (Monzón-1) is used to obtain a resistivity model and then applied to the rest of the survey points. The applied methodology contributes to improving the geological knowledge, revealing a new detailed geological structure of the Barbastro saline-evaporitic formation affected by the Barbastro-Balaguer Anticline. The survey shows that the Barbastro saline-evaporitic formation presents a structure with a ramp hanging wall and close to flat footwall, generally dipping to the SW, with a decreasing thickness from 1103 m to 601 m, in concordance with the previous accepted geological structural model. The new geophysical study provides essential data, allowing design and drilling optimization in future mining exploitations.
Removing Rain Streaks from Visual Image Using a Combination of Bilateral Filter and Generative Adversarial Network
Authors: Yang Yue , Xu Minglong , Chen Chuang , Xue Fan
Published: May 2023

Images acquired using vision sensors are easily affected by environmental limitations, especially rain streaks. These streaks will seriously reduce image quality, which, in turn, reduces the accuracy of the algorithms that use the resulting images in vision sensor systems. In this paper, we proposed a method that combined the bilateral filter with the generative adversarial network to eliminate the interference of rain streaks. Unlike other methods that use all the information in an image as the input to the generative adversarial network, we used a bilateral filter to preprocess and separate the high frequency part of the original image. The generator for the high-frequency layer of the image was designed to generate an image with no rain streaks. The high-frequency information of the image was used in a high-frequency global discriminator designed to measure the authenticity of the generated image from multiple perspectives. We also designed a loss function based on the structural similarity index to further improve the effect of removal of the rain streaks. An ablation experiment proved the validity of the method. We also compared images in synthetic and real-world datasets. Our method could retain more image information, and the generated image was clearer.
Preliminary Flutter Stability Assessment of the Double-Deck George Washington Bridge
Authors: Russo Sebastiano , Piana Gianfranco , Patruno Luca , Carpinteri Alberto
Published: May 2023

We deal with the flutter analysis of the George Washington bridge, in both the single- and double-deck configurations of 1931 and 1962, respectively. The influence of the additional lower deck on the aerodynamic behavior is investigated. To overcome the lack of aerodynamic data, a simplified approach is followed based on Fung’s formulation, in which the flutter derivatives are expressed in terms of the real and imaginary parts of the Theodorsen function and of the steady-state aerodynamic coefficients of the deck cross-section. The latter are obtained by Computational Fluid Dynamics simulations conducted in ANSYS FLUENT, whereas the ANSYS Mechanical APDL finite element package is used to perform the flutter analyses. Two different methods for the application of the aeroelastic forces are employed for the double-deck configuration: (i) self-excited forces, based on flutter derivatives related to the whole cross-section, acting on the upper deck; and (ii) self-excited forces, based on flutter derivatives related to the single deck, simultaneously applied to the upper and lower decks. The obtained results are critically compared with theoretical predictions of simple formulas available from the literature; it is suggested that laboratory tests are needed since no experimental results seem to be available.
Effect of Slide Diamond Burnishing on the Surface Layer of Valve Stems and the Durability of the Stem-Graphite Seal Friction Pair
Authors: Korzynski Mieczyslaw , Dudek Kazimiera , Korzynska Katarzyna
Published: May 2023

This study analysed the condition of the surface layer of valve stems made of 317Ti steel after polishing and burnishing. Surface roughness, microhardness, and residual stress tests were carried out. The tests were carried out to determine the effect of the condition of the surface layer (especially non-standard parameters of surface roughness) of the stems on the durability of valves and to determine the possibility of obtaining a favourable state by means of sliding burnishing. Significant differences were observed in the values of the roughness parameters that determine the tribological properties of the surface, and higher surface microhardness and residual compressive stresses were obtained after burnishing. The durability of the stem-graphite seal in a reciprocating movement was tested, and the failure-free operation time of valves with burnished stems was approximately four times longer, which is the premise for recommending sliding diamond burnishing as a finishing treatment for valve stems.
Emotional State Detection Using Electroencephalogram Signals: A Genetic Algorithm Approach
Authors: García-Hernández Rosa A. , Celaya-Padilla José M. , Luna-García Huizilopoztli , García-Hernández Alejandra , Galván-Tejada Carlos E. , Galván-Tejada Jorge I. , Gamboa-Rosales Hamurabi , Rondon David , Villalba-Condori Klinge O.
Published: May 2023

Emotion recognition based on electroencephalogram signals (EEG) has been analyzed extensively in different applications, most of them using medical-grade equipment in laboratories. The trend in human-centered artificial intelligence applications is toward using portable sensors with reduced size and improved portability that can be taken to real life scenarios, which requires systems that efficiently analyze information in real time. Currently, there is no specific set of features or specific number of electrodes defined to classify specific emotions using EEG signals, and performance may be improved with the combination of all available features but could result in high dimensionality and even worse performance; to solve the problem of high dimensionality, this paper proposes the use of genetic algorithms (GA) to automatically search the optimal subset of EEG data for emotion classification. Publicly available EEG data with 2548 features describing the waves related to different emotional states are analyzed, and then reduced to 49 features with genetic algorithms. The results show that only 49 features out of the 2548 can be sufficient to create machine learning (ML) classification models with, using algorithms such as k-nearest neighbor (KNN), random forests (RF) and artificial neural networks (ANN), obtaining results with 90.06%, 93.62% and 95.87% accuracy, respectively, which are higher than the 87.16% and 89.38% accuracy of previous works.
A Feasibility Study on Textile Sludge as a Raw Material for Sintering Lightweight Aggregates and Its Application in Concrete
Authors: Chen How-Ji , Chang Wen-Tse , Tang Chao-Wei , Peng Ching-Fang
Published: May 2023

This study aimed to investigate the feasibility of textile sludge as a raw material for sintering lightweight aggregates (LWAs) and its application in concrete. Three samples of different components were taken from the textile sludge, which came from different textile factories in Taiwan. The analysis of the chemical composition of the sludge shows that the total content of SiO2, Al2O3, and Fe2O3 in the textile sludge was far lower than the recommended value in the literature, and that glassy melt could not be produced and sintered into LWAs alone. Therefore, the water purification sludge obtained from a water purification plant owned by the Taiwan Water Supply Company was used as the main raw material, and the textile sludge was used as the auxiliary raw material in addition amounts of 7.5%, 15.0%, and 22.5%. The test results showed that the LWAs sintered by adding textile sludge to water purification sludge could reach the particle density that is generally required for LWAs (between 0.2 and 1.8 g/cm3). The 14-day compressive strength of the lightweight aggregate concrete made from textile-sludge-based LWAs was between 20 and 25 MPa. This means that textile-sludge-based LWAs can be used in secondary structural concrete.
Radiomics for the Prediction of Pathological Complete Response to Neoadjuvant Chemoradiation in Locally Advanced Rectal Cancer: A Prospective Observational Trial
Authors: Shi Liming , Zhang Yang , Hu Jiamiao , Zhou Weiwen , Hu Xi , Cui Taoran , Yue Ning , Sun Xiaonan , Nie Ke
Published: May 2023

(1) Background: An increasing amount of research has supported the role of radiomics for predicting pathological complete response (pCR) to neoadjuvant chemoradiation treatment (nCRT) in order to provide better management of locally advanced rectal cancer (LARC) patients. However, the lack of validation from prospective trials has hindered the clinical adoption of such studies. The purpose of this study is to validate a radiomics model for pCR assessment in a prospective trial to provide informative insight into radiomics validation. (2) Methods: This study involved a retrospective cohort of 147 consecutive patients for the development/validation of a radiomics model, and a prospective cohort of 77 patients from two institutions to test its generalization. The model was constructed using T2-weighted, diffusion-weighted, and dynamic contrast-enhanced MRI to understand the associations with pCR. The consistency of physicians’ evaluations and agreement on pathological complete response prediction were also evaluated, with and without the aid of the radiomics model. (3) Results: The radiomics model outperformed both physicians’ visual assessments in the prospective test cohort, with an area under the curve (AUC) of 0.84 (95% confidence interval of 0.70–0.94). With the aid of the radiomics model, a junior physician could achieve comparable performance as a senior oncologist. (4) Conclusion: We have built and validated a radiomics model with pretreatment MRI for pCR prediction of LARC patients undergoing nCRT.
Invasive Fish and Sea Urchins Drive the Status of Canopy Forming Macroalgae in the Eastern Mediterranean
Authors: Nikolaou Athanasios , Tsirintanis Konstantinos , Rilov Gil , Katsanevakis Stelios
Published: May 2023

Canopy-forming macroalgae, such as Cystoseira sensu lato, increase the three-dimensional complexity and spatial heterogeneity of rocky reefs, enhancing biodiversity and productivity in coastal areas. Extensive loss of canopy algae has been recorded in recent decades throughout the Mediterranean Sea due to various anthropogenic pressures. In this study, we assessed the biomass of fish assemblages, sea urchin density, and the vertical distribution of macroalgal communities in the Aegean and Levantine Seas. The herbivore fish biomass was significantly higher in the South Aegean and Levantine compared to the North Aegean. Very low sea urchin densities suggest local collapses in the South Aegean and the Levantine. In most sites in the South Aegean and the Levantine, the ecological status of macroalgal communities was low or very low at depths deeper than 2 m, with limited or no canopy algae. In many sites, canopy algae were restricted to a very narrow, shallow zone, where grazing pressure may be limited due to harsh hydrodynamic conditions. Using Generalized Linear Mixed Models, we demonstrated that the presence of canopy algae is negatively correlated with the biomass of the invasive Siganus spp. and sea urchins. The loss of Cystoseira s.l. forests is alarming, and urgent conservation actions are needed.
Void Nucleation and Growth from Heterophases and the Exploitation of New Toughening Mechanisms in Metals
Authors: Guo Yi , Paramatmuni Chaitanya , Avcu Egemen
Published: May 2023

Heterophases, such as precipitates, inclusions, second phases, or reinforcement particles, often drive void nucleation due to local incompatibilities in stresses/strains. This results in a significant life-limiting condition, as voids or their coalescence can lead to microcracks that reduce the ductility and fatigue life of engineering components. Continuum-mechanics-based analytical models have historically gained momentum due to their relative ease in predicting failure strain. The momentum of such treatment has far outpaced the development of theories at the atomic and micron scales, resulting in an insufficient understanding of the physical processes of void nucleation and growth. Evidence from the recent developments in void growth theories indicates that the evolution of voids is intrinsically linked to dislocation activity at the void–matrix interface. This physical growth mechanism opens up a new methodology for improving mechanical properties using hydrostatic pressurization. According to the limited literature, with a hydrostatic pressure close to 1 GPa, aluminium matrix composites can be made 70 times more ductile. This significant ductility enhancement arises from the formation of dislocation shells that encapsulate the heterophases and inhibit the void growth and coalescence. With further investigations into the underlying theories and developments of methods for industrial implementations, hydrostatic pressurization has the potential to evolve into an effective new method for improving the ductility and fatigue life of engineering components with further development.
SCDet: A Robust Approach for the Detection of Skin Lesions
Authors: Sikandar Shahbaz , Mahum Rabbia , Ragab Adham E. , Yayilgan Sule Yildirim , Shaikh Sarang
Published: May 2023

Red, blue, white, pink, or black spots with irregular borders and small lesions on the skin are known as skin cancer that is categorized into two types: benign and malignant. Skin cancer can lead to death in advanced stages, however, early detection can increase the chances of survival of skin cancer patients. There exist several approaches developed by researchers to identify skin cancer at an early stage, however, they may fail to detect the tiniest tumours. Therefore, we propose a robust method for the diagnosis of skin cancer, namely SCDet, based on a convolutional neural network (CNN) having 32 layers for the detection of skin lesions. The images, having a size of 227 × 227, are fed to the image input layer, and then pair of convolution layers is utilized to withdraw the hidden patterns of the skin lesions for training. After that, batch normalization and ReLU layers are used. The performance of our proposed SCDet is computed using the evaluation matrices: precision 99.2%; recall 100%; sensitivity 100%; specificity 99.20%; and accuracy 99.6%. Moreover, the proposed technique is compared with the pre-trained models, i.e., VGG16, AlexNet, and SqueezeNet and it is observed that SCDet provides higher accuracy than these pre-trained models and identifies the tiniest skin tumours with maximum precision. Furthermore, our proposed model is faster than the pre-trained model as the depth of its architecture is not too high as compared to pre-trained models such as ResNet50. Additionally, our proposed model consumes fewer resources during training; therefore, it is better in terms of computational cost than the pre-trained models for the detection of skin lesions.
Chemo-Free Treatment Using Anti-PD-1 Antibodies with Lenvatinib in Unresectable Gallbladder Cancer: PD-L1 May Be a Potential Biomarker for a Better Outcome
Authors: Wu Tiantian , Pu Changsheng , Wu Xianjia , Wang Qiang , Zhang Keming
Published: May 2023

Background: Recently, anti-PD-1 antibodies plus lenvatinib has been administered in a series of solid tumors. Yet, the efficacy of chemo-free treatment of this combined therapy has seldom been reported in gallbladder cancer (GBC). The aim of our study was to initially evaluate the efficacy of the chemo-free treatment in unresectable GBCs. Methods: We retrospectively collected the clinical data of unresectable GBCs treated using chemo-free anti-PD-1 antibodies plus lenvatinib in our hospital from March 2019 to August 2022. The clinical responses were assessed, and PD-1 expression was evaluated. Results: Our study enrolled 52 patients, with the median progression-free survival being 7.0 months and the median overall survival being 12.0 months. The objective response rate was 46.2% and the disease control rate was 65.4%. The expression of PD-L1 in patients with objective response was significantly higher than those with progression of disease. Conclusions: For patients with unresectable GBC, when not eligible for systemic chemotherapy, chemo-free treatment using anti-PD-1 antibodies with lenvatinib may become a safe and rational choice. The expression of PD-L1 in tumor tissues may be correlated to the objective response, and thus is expected to be a predictor of efficacy, and further clinical studies are certainly needed.
Using Machine Learning to Predict Abnormal Carotid Intima-Media Thickness in Type 2 Diabetes
Authors: Wu Chung-Ze , Huang Li-Ying , Chen Fang-Yu , Kuo Chun-Heng , Yeih Dong-Feng
Published: May 2023

Carotid intima-media thickness (c-IMT) is a reliable risk factor for cardiovascular disease risk in type 2 diabetes (T2D) patients. The present study aimed to compare the effectiveness of different machine learning methods and traditional multiple logistic regression in predicting c-IMT using baseline features and to establish the most significant risk factors in a T2D cohort. We followed up with 924 patients with T2D for four years, with 75% of the participants used for model development. Machine learning methods, including classification and regression tree, random forest, eXtreme gradient boosting, and Naïve Bayes classifier, were used to predict c-IMT. The results showed that all machine learning methods, except for classification and regression tree, were not inferior to multiple logistic regression in predicting c-IMT in terms of higher area under receiver operation curve. The most significant risk factors for c-IMT were age, sex, creatinine, body mass index, diastolic blood pressure, and duration of diabetes, sequentially. Conclusively, machine learning methods could improve the prediction of c-IMT in T2D patients compared to conventional logistic regression models. This could have crucial implications for the early identification and management of cardiovascular disease in T2D patients.
A Novel Coherent Integration Algorithm for Maneuvering Target Detection Based on Symmetric Instantaneous Autocorrelation Function
Authors: Mi Yunpeng , Zhang Yunhua , Yang Jiefang
Published: May 2023

Detection and parameter estimation of maneuvering targets having a jerking motion are some of the challenging problems for modern radar systems. Such targets usually introduce range migration (RM) and Doppler frequency migration (DFM) problems leading to serious performance degradation in detection. To address these problems, a novel coherent integration (CI) algorithm is proposed based on a new symmetric instantaneous autocorrelation function (NSIAF), which can be utilized to reduce the order on the slow time and to eliminate the linear range migration (LRM) first. Then, the jerk and acceleration of the target are estimated after applying the keystone transform (KT) and the scaled Fourier transform (SFT); both of these are then used to construct the reference function for matched filtering. Finally, CI and target detection can be accomplished by the scaled inverse Fourier transform (SCIFT) after matched filtering. Both simulation data (this work) and practical radar experiment data (data set of others) were processed to validate the proposed algorithm. Compared with other representative algorithms, our algorithm can achieve a good balance between computational complexity and detection performance.
Contingency Planning of Visual Contamination for Wheeled Mobile Robots with Chameleon-Inspired Visual System
Authors: Xu Yan , Yu Hongpeng , Wu Liyan , Song Yuqiu , Liu Cuihong
Published: May 2023

To enable mobile robots to effectively deal with the emergency of visual contamination, contingency planning based on case-based reasoning (CBR) was performed in this paper. First, for a wheeled mobile robot (WMR) equipped with a chameleon-inspired visual system, a target search model in chameleon-inspired binocular negative correlation movement (CIBNCM) mode was established. Second, a CBR-based contingency planning model of visual contamination for WMRs was established, where the reasoning process using CBR for visual contamination was analyzed in detail. Third, through the analysis of environment perception when visual contamination occurs, a perception model in chameleon-inspired visual contamination for WMRs was built. Finally, to validate the proposed approach, a contingency planning experiment scheme for visual contamination was designed based on the robot’s general planning of target tracking, and the experimental result is discussed. The proposed CBR-based contingency planning approach for visual contamination can reason out effective solutions corresponding to the contamination situations. The rationality of the approach was verified by experiments with satisfactory results. Moreover, compared with the contingency planning method based on rule-based reasoning, the accuracy of target retracking after the robot visual system is contaminated is significantly higher for the CBR-based contingent planning method used in this paper.
Impact of the COVID-19 Pandemic on Cryptocurrency Markets: A DCCA Analysis
Authors: Almeida Dora , Dionísio Andreia , Ferreira Paulo , Vieira Isabel
Published: May 2023

Extraordinary events, regardless of their financial or non-financial nature, are a great challenge for financial stability. This study examines the impact of one such occurrence—the COVID-19 pandemic—on cryptocurrency markets. A detrended cross-correlation analysis was performed to evaluate how the links between 16 cryptocurrencies were changed by this event. Cross-correlation coefficients that were calculated before and after the onset of the pandemic were compared, and the statistical significance of their variation was assessed. The analysis results show that the markets of the assessed cryptocurrencies became more integrated. There is also evidence to suggest that the pandemic crisis promoted contagion, mainly across short timescales (with a few exceptions of non-contagion across long timescales). We conclude that, in spite of the distinct characteristics of cryptocurrencies, those in our sample offered no protection against the financial turbulence provoked by the COVID-19 pandemic, and thus, our study provided yet another example of ‘correlations breakdown’ in times of crisis.
Application of Central Composite Design and Superimposition Approach for Optimization of Drying Parameters of Pretreated Cassava Flour
Authors: Nainggolan Ellyas Alga , Banout Jan , Urbanova Klara
Published: May 2023

The primary goals of this study were to identify the influence of temperature and drying time on pretreated cassava flour, as well as the optimal settings for the factors and to analyze the microstructure of cassava flour. The experiment was designed using the response surface methodology with central composite design and the superimposition approach in order to assess the effect of drying temperature (45.85–74.14 °C) and drying time (3.96–11.03 h) and the optimal drying conditions of the cassava flour investigated. Soaking and blanching were applied as pretreatments to freshly sliced cassava tubers. The value moisture content of cassava flour was between 6.22% and 11.07%, whereas the observed whiteness index in cassava flour ranged from 72.62 to 92.67 in all pretreated cassava flour samples. Through analysis of variance, each drying factor, their interaction, and all squared terms had a substantial impact on moisture content and whiteness index. The optimized values for drying temperature and drying time for each pretreated cassava flour were 70 °C and 10 h, respectively. The microstructure showed a non-gelatinized, relatively homogeneous in size and shape sample with pretreatment soaked in distilled water at room temperature. These study results are relevant to the development of more sustainable cassava flour production.
Advanced Glycation End Products: A Comprehensive Review of Their Detection and Occurrence in Food
Authors: Li Lixian , Zhuang Yingjun , Zou Xiuzhi , Chen Maolong , Cui Bo , Jiao Ye , Cheng Yunhui
Published: May 2023

The Maillard reaction (MR) is a complicated chemical process that has been extensively studied. Harmful chemicals known as advanced glycation end products (AGEs), with complex structures and stable chemical characteristics, are created during the final stage of the MR. AGEs can be formed both during the thermal processing of food and in the human body. The number of AGEs formed in food is much higher compared to endogenous AGEs. A direct connection exists between human health and the build-up of AGEs in the body, which can result in diseases. Therefore, it is essential to understand the content of AGEs in the food we consume. The detection methods of AGEs in food are expounded upon in this review, and the advantages, disadvantages, and application fields of these detection methods are discussed in depth. Additionally, the production of AGEs in food, their content in typical foods, and the mechanisms influencing their formation are summarized. Since AGEs are closely related to the food industry and human health, it is hoped that this review will further the detection of AGEs in food so that their content can be evaluated more conveniently and accurately.
Dairy-Protein-Based Aggregates as Additives Enriched with Tart Cherry Polyphenols and Flavor Compounds
Authors: Kopjar Mirela , Buljeta Ivana , Ćorković Ina , Kelemen Vanja , Pichler Anita , Ivić Ivana , Šimunović Josip
Published: May 2023

Nowadays, the development of innovative food products with positive health effects is on the rise. Consequently, the aim of this study was a formulation of aggregates based on tart cherry juice and dairy protein matrix to investigate whether different amounts (2% and 6%) of protein matrix have an impact on the adsorption of polyphenols as well as on the adsorption of flavor compounds. Formulated aggregates were investigated through high-performance liquid chromatography, spectrophotometric methods, gas chromatography and Fourier transform infrared spectrometry. The obtained results revealed that with an increase in the amount of protein matrix used for the formulation of aggregates, a decrease in the adsorption of polyphenols occurred, and, consequently, the antioxidant activity of the formulated aggregates was lower. The amount of protein matrix additionally affected the adsorption of flavor compounds; thus the formulated aggregates differed in their flavor profiles in comparison with tart cherry juice. Adsorption of both phenolic and flavor compounds caused changes in the protein structure, as proven by recording IR spectra. Formulated dairy-protein-based aggregates could be used as additives which are enriched with tart cherry polyphenols and flavor compounds.
State-of-the-Art Insights and Potential Applications of Cellulose-Based Hydrogels in Food Packaging: Advances towards Sustainable Trends
Authors: Singh Ajit Kumar , Itkor Pontree , Lee Youn Suk
Published: May 2023

Leveraging sustainable packaging resources in the circular economy framework has gained significant attention in recent years as a means of minimizing waste and mitigating the negative environmental impact of packaging materials. In line with this progression, bio-based hydrogels are being explored for their potential application in a variety of fields including food packaging. Hydrogels are three-dimensional, hydrophilic networks composed of a variety of polymeric materials linked by chemical (covalent bonds) or physical (non-covalent interactions) cross-linking. The unique hydrophilic nature of hydrogels provides a promising solution for food packaging systems, specifically in regulating moisture levels and serving as carriers for bioactive substances, which can greatly affect the shelf life of food products. In essence, the synthesis of cellulose-based hydrogels (CBHs) from cellulose and its derivatives has resulted in hydrogels with several appealing features such as flexibility, water absorption, swelling capacity, biocompatibility, biodegradability, stimuli sensitivity, and cost-effectiveness. Therefore, this review provides an overview of the most recent trends and applications of CBHs in the food packaging sector including CBH sources, processing methods, and crosslinking methods for developing hydrogels through physical, chemical, and polymerization. Finally, the recent advancements in CBHs, which are being utilized as hydrogel films, coatings, and indicators for food packaging applications, are discussed in detail. These developments have great potential in creating sustainable packaging systems.
Physiotherapy Screening for Referral of a Patient with Peripheral Arterial Disease Masquerading as Sciatica: A Case Report
Authors: Feller Daniel , Giudice Andrea , Maritati Giorgio , Maselli Filippo , Rossettini Giacomo , Meroni Roberto , Lullo Graziana , Hutting Nathan , Mourad Firas
Published: May 2023

Many causes potentially underline pain in the lower extremities, presenting a real challenge for primary care clinicians in the recognition of the source of the patient’s complaints. Peripheral arterial disease (PAD) is defined as a total or partial blockage of the vessels that supply blood from the heart to the periphery. PAD of the lower extremities may masquerade as lumbosacral radiculopathy (LSR)—a common source of leg pain. Physiotherapists should be able to screen for PAD in people presenting with pain in the lower extremities. Failure to correctly screen for PAD could put the patient at risk of severe disability and possible permanent sequelae. This case report outlines the relevant concepts relating to the pathophysiology, screening, and differential diagnosis of PAD, and then further describes the relevant findings from the history and physical examination from the physiotherapist’s perspective in a patient with an unusual symptom presentation. Although the patient was referred by a physician with a diagnosis of LSR, our case highlights the pivotal role of skilled physiotherapists in triaging a severe lower-limb PAD in need of referral. Therefore, this case report aims to increase clinicians’ awareness of the clinical features of a complex case of PAD.
Endodontic Management of Three-Rooted Mandibular Second Molar with Three Separate Orifices and Three Independent Portals of Exit: A Case Report
Authors: Jadhav Kapil R. , VanPutte Cinnamon L. , Tsotsis Polymnia
Published: May 2023

Most mandibular second molars are usually found to have either one or two roots. However, mandibular second molars can also present with variations in the number of roots as well as differences in the morphology of their root canals. An 18-year-old male presented to the Department of Graduate Endodontics clinic with a morphologically variable mandibular second molar with three roots—two mesial and one distal. Two periapical radiographs were taken at different angles, revealing that there were three different canals in separate roots, each with independent portals of exit. This is a rare anatomical configuration. The success of endodontic treatment depends on accurate diagnosis, careful examination, identification of additional roots and canals, as well as detection of variations in root canal morphology. Failing to recognize these variations may lead to failures of root canal treatments and thus unsuccessful endodontic treatment.
Adverse Pregnancy Outcomes and Maternal Periodontal Disease: An Overview on Meta-Analytic and Methodological Quality
Authors: Machado Vanessa , Ferreira Madalena , Lopes Luísa , Mendes José João , Botelho João
Published: May 2023

This umbrella review aims to appraise the methodological quality and strength of evidence on the association between maternal periodontitis and adverse pregnancy outcomes (APOs). PubMed, CENTRAL, Web-of-Science, LILACS, and Clinical Trials were searched until February 2023, without date or language restrictions. Two authors independently screened studies, extracted data, performed the risk-of-bias analysis, and estimated the meta-analytic strengths and validity and the fail-safe number (FSN). A total of 43 SRs were identified, of which 34 conducted meta-analyses. Of the 28 APOs, periodontitis had a strong association with preterm birth (PTB), low birth weight (LBW), and gestational diabetes mellitus (GDM), PTB and LBW showed all levels of strength, and pre-eclampsia showed only suggestive and weak strength. Regarding the consistency of the significant estimates, only 8.7% were likely to change in the future. The impact of periodontal treatment on APOs was examined in 15 SRs, 11 of which conducted meta-analyses. Forty-one meta-analyses were included and showed that periodontal treatment did not have a strong association with APOs, although PTB revealed all levels of strength and LBW showed only suggestive and weak evidence. Strong and highly suggestive evidence from observational studies supports an association of periodontitis with a higher risk of PTB, LBW, GDM, and pre-eclampsia. The effect of periodontal treatment on the prevention of APOs is still uncertain and requires future studies to draw definitive and robust conclusions.
The Folded Radial Forearm Flap in Lip and Nose Reconstruction—Still a Unique Choice
Authors: Ettl Tobias , Gottsauner Maximilian , Kühnel Thomas , Maurer Michael , Schuderer Johannes G. , Spörl Steffen , Taxis Jürgen , Reichert Torsten E. , Fiedler Mathias , Meier Johannes K.
Published: May 2023

(1) Background: The radial forearm flap (RFF) has evolved as the flap of choice for intraoral mucosal reconstructions, providing thin and pliable skin with a safe blood supply. Perforator flaps such as the anterolateral thigh (ALT) flap are increasingly being discussed for the same applications. (2) Methods: Patient history, treatment details, and outcome of 12 patents with moderate to extended defects of the lip and/or nose area that were reconstructed by a folded radial forearm flap were retrospectively evaluated for oncologic and functional outcomes. (3) Results: The mean oncologic and functional follow-up were 21.1 (min. 3.8; max. 83.3) and 31.2 (min. 6; max. 96) months, respectively. All flaps survived without revision. In eight cases, major lip defects were reconstructed by an RFF; in six patients, the palmaris longus tendon was included for lip suspension. The functional results in terms of eating, drinking, and mouth opening were good in five cases, while three patients were graded as fair due to moderate drooling. In seven cases, the major parts of the nose were reconstructed with two good and five fair (nostril constriction in three cases) functional results. (4) Conclusions: The folded RFF remains a unique free flap option for complex three-dimensional lip and nose reconstructions in terms of flexibility, versatility, and robustness.
Short and Middle Functional Outcome in the Static vs. Dynamic Fixation of Syndesmotic Injuries in Ankle Fractures: A Retrospective Case Series Study
Authors: Pavone Vito , Papotto Giacomo , Vescio Andrea , Longo Gianfranco , D’Amato Salvatore , Ganci Marco , Marchese Emanuele , Testa Gianluca
Published: May 2023

Background: Syndesmotic injuries are common lesions associated with ankle fractures. Static and dynamic fixation are frequently used in syndesmotic injury-associated ankle fractures. The purpose of this study is to compare short- and mid-term quality of life, clinical outcomes, and gait after static stabilization with a trans-syndesmotic screw or dynamic stabilization with a suture button device. Methods: Here, 230 patients were enrolled in a retrospective observational study. They were divided in two groups according to the fixation procedure (Arthrex TightRope®, Munich, Germany) synthesis vs. osteosynthesis with a 3.5 mm trans-syndesmotic tricortical screw). They then underwent clinical assessment using the American Foot and Ankle Score (AOFAS) at 1, 2, 6, 12, and 24 months after surgery. Quality of life was assessed according to the EuroQol-5 Dimension (EQ-5D) at 2 and 24 months after surgery in the follow-up; gait analysis was performed 2 and 24 months postoperatively. Results: Significant differences were found at a two-month follow-up according to the AOFAS (p = 0.0001) and EQ-5D (p = 0.0208) scores. No differences were noted in the other follow-ups (p > 0.05) or gait analysis. Conclusion: The dynamic and static fixation of syndesmotic injuries in ankle fracture are both efficacious and valid procedures for avoiding ankle instability. The suture button device was comparable to the screw fixation according to functional outcomes and gait analysis.
MDM2 Implications for Potential Molecular Pathogenic Therapies of Soft-Tissue Tumors
Authors: Sun Sylvia Yao , Crago Aimee
Published: May 2023

Murine double minute 2 (MDM2, gene name MDM2) is an oncogene that mainly codes for a protein that acts as an E3 ubiquitin ligase, which targets the tumor suppressor protein p53 for degradation. Overexpression of MDM2 regulates the p53 protein levels by binding to it and promoting its degradation by the 26S proteasome. This leads to the inhibition of p53’s ability to regulate cell cycle progression and apoptosis, allowing for uncontrolled cell growth, and can contribute to the development of soft-tissue tumors. The application of cellular stress leads to changes in the binding of MDM2 to p53, which prevents MDM2 from degrading p53. This results in an increase in p53 levels, which triggers either cell cycle arrest or apoptosis. Inhibiting the function of MDM2 has been identified as a potential therapeutic strategy for treating these types of tumors. By blocking the activity of MDM2, p53 function can be restored, potentially leading to tumor cell death and inhibiting the growth of tumors. However, further research is needed to fully understand the implications of MDM2 inhibition for the treatment of soft-tissue tumors and to determine the safety and efficacy of these therapies in clinical trials. An overview of key milestones and potential uses of MDM2 research is presented in this review.
Ultra-Low Power Programmable Bandwidth Capacitively-Coupled Chopper Instrumentation Amplifier Using 0.2 V Supply for Biomedical Applications
Authors: Pham Xuan Thanh , Kieu Xuan Thuc , Hoang Manh Kha
Published: May 2023

This paper presents a capacitively coupled chopper instrumentation amplifier (CCIA) with ultra-low power consumption and programmable bandwidth for biomedical applications. To achieve a flexible bandwidth from 0.2 to 10 kHz without additional power consumption, a programmable Miller compensation technique was proposed and used in the CCIA. By using a Squeezed inverter amplifier (SQI) that employs a 0.2-V supply, the proposed CCIA addresses the primary noise source in the first stage, resulting in high noise power efficiency. The proposed CCIA is designed using a 0.18 µm CMOS technology process and has a chip area of 0.083 mm2. With a power consumption of 0.47 µW at 0.2 and 0.8 V supply, the proposed amplifier architecture achieves a thermal noise of 28 nV/√Hz, an input-related noise (IRN) of 0.9 µVrms, a closed-loop gain (AV) of 40 dB, a power supply rejection ratio (PSRR) of 87.6 dB, and a common-mode rejection ratio (CMRR) of 117.7 dB according to post-simulation data. The proposed CCIA achieves a noise efficiency factor (NEF) of 1.47 and a power efficiency factor (PEF) of 0.56, which allows comparison with the latest research results.
GIT: A Transformer-Based Deep Learning Model for Geoacoustic Inversion
Authors: Feng Sheng , Zhu Xiaoqian , Ma Shuqing , Lan Qiang
Published: May 2023

Geoacoustic inversion is a challenging task in marine research due to the complex environment and acoustic propagation mechanisms. With the rapid development of deep learning, various designs of neural networks have been proposed to solve this issue with satisfactory results. As a data-driven method, deep learning networks aim to approximate the inverse function of acoustic propagation by extracting knowledge from multiple replicas, outperforming conventional inversion methods. However, existing deep learning networks, mainly incorporating stacked convolution and fully connected neural networks, are simple and may neglect some meaningful information. To extend the network backbone for geoacoustic inversion, this paper proposes a transformer-based geoacoustic inversion model with additional frequency and sensor 2-D positional embedding to perceive more information from the acoustic input. The simulation experimental results indicate that our proposed model achieves comparable inversion results with the existing inversion networks, demonstrating its effectiveness in marine research.