bluuebunny/crossref_metadata_2025 huggingface dataset:
Browning Development and Antioxidant Compounds in White Wines after Selenium, Iron, and Peroxide Addition
Authors: Vlahou Eftihia , Christofi Stefania , Roussis Ioannis G. , Kallithraka Stamatina
Published: April 2022

The effect of oxidation on the organoleptic properties of white wines mostly involves increased browning color, loss of the fruity aromas, and appearance of unpleasant odors. Browning, however, is known to be related with polyphenol oxidation and therefore it may be delayed by the presence of antioxidants such as selenium (Se) and SO2. On the other hand, the presence of oxidants such as metal ions and H2O2 can accelerate browning and oxidation phenomena. The browning capacity, the phenolic composition (both total and individual contents of flavanols and hydroxycinnamic acids), the antioxidant activity, and the SO2 content of Assyrtiko white wines were studied after the addition of Fe2+ and H2O2 and Se at two temperatures, employing an accelerated test. Browning was approached from a kinetic point of view, and the study was focused on the implication of oxidants and antioxidants on browning rate, paying particular attention to the content of major redox-active polyphenols, including substances with an o-diphenol feature, such as flavanols and hydroxycinnamic acids. The results showed that after the addition of oxidants it was possible to significantly accelerate the rate of browning development (up to 4.7 and six times) depending on the temperature and the concentration of the added compounds. The presence of Se protected wine color and preserved total SO2 at 35 °C, while at 50 °C, these effects were not observed. Total flavanol content decreased upon heating, while total hydroxycinnamic content showed a slight increase. Similarly, the content of the individual phenolic compounds (with the exception of caffeic acid and (+)-catechin at 35 °C) was decreased with oxidant addition, while Se addition was not adequate to prevent or even promote their oxidation.
Microencapsulation of Natural Food Antimicrobials: Methods and Applications
Authors: Eghbal Noushin , Liao Wei , Dumas Emilie , Azabou Samia , Dantigny Philippe , Gharsallaoui Adem
Published: April 2022

The global demand for safe and healthy food with minimal synthetic preservatives is continuously increasing. Some natural food antimicrobials with strong antimicrobial activity and low toxicity have been considered as alternatives for current commercial food preservatives. Nonetheless, these natural food antimicrobials are hardly applied directly to food products due to issues such as food flavor or bioavailability. Recent advances in microencapsulation technology have the potential to provide stable systems for these natural antibacterials, which can then be used directly in food matrices. In this review, we focus on the application of encapsulated natural antimicrobial agents, such as essential oils, plant extracts, bacteriocins, etc., as potential food preservatives to extend the shelf-life of food products. The advantages and drawbacks of the mainly used encapsulation methods, such as molecular inclusion, spray drying, coacervation, emulsification, supercritical antisolvent precipitation and liposome and alginate microbeads, are discussed. Meanwhile, the main current applications of encapsulated antimicrobials in various food products, such as meat, dairy and cereal products for controlling microbial growth, are presented.
Recovery of Cork Manufacturing Waste within Mortar and Polyurethane: Feasibility of Use and Physical, Mechanical, Thermal Insulating Properties of the Final Green Composite Construction Materials
Authors: Malchiodi Beatrice , Marchetti Roberta , Barbieri Luisa , Pozzi Paolo
Published: April 2022

The valorization of industrial waste is a hot topic toward circular economy and sustainability. Several wastes have been proposed as resources for different production processes; however, others are still disposed to landfill or waste-to-energy plants. For the first time, this work suggests a sustainable alternative to managing cork waste from bottle caps manufacturing; this is generated by a local company at about 220,000 m3/year. The powder waste has a 0.063–1 mm particle size and is mainly composed of cork, polyurethane adhesive, and paraffin. Its valorization is proposed as filler in construction materials such as lime-based mortar (1–4 wt%) and polyurethane (5–15 wt%). Thermal, spectroscopic, and physical characterizations are performed on the cork waste, and mainly result in a low apparent density (340 kg/m3) and high-water absorption (177%). Cork properties allow consideration of extra water in the mortar mix and improve lightness without significantly affecting compressive, bending strength, and thermal insulation. Cork waste in polyurethanes promotes a color change, slightly increases the density (up to 12.5%), and still results in producing a thermally insulating material (<0.06 W/mK). Considering the promising results, this study demonstrates the feasibility of using the manufacturing waste from cork bottle caps to produce green construction materials, thus upgrading it from waste to secondary raw material.
Discomfort Glare Perception by Drivers—Establishing a Link between Subjective and Psychophysiological Assessment
Authors: Stanke Ladislav , Viktorová Lucie , Dominik Tomáš
Published: April 2022

The broad application of LEDs for automotive lighting purposes, together with new discoveries in vision physiology, is creating new challenges in the field of glare perception. The purpose of this study was to link subjective and objective measures of driver-perceived glare following different light sources used in car headlamps. In order to achieve this, a combination of subjective evaluation using an adapted version of the de Boer scale and objective measures based on psychophysiological data was applied. Predominantly, skin conductance response (SCR), heart rate variability (HRV), and eye-blinking frequency (vertical electrooculography, vEOG) were recorded. Though there was some evidence suggesting lower discomfort with glare from light sources with a lower correlated color temperature, the results were generally inconclusive. This illustrates the urgent need to study the linkage between light source properties and subjective and objective glare measures in deeper detail, so that the technical norms governing car headlamps can reflect the needs of human physiology and psychophysiology.
Dispersion of Elastic Waves in Functionally Graded CNTs-Reinforced Composite Beams
Authors: Seyfi Ali , Teimouri Amir , Dimitri Rossana , Tornabene Francesco
Published: April 2022

This work deals with the wave propagation analysis in functionally graded carbon nanotubes (CNTs)-reinforced composite beams lying on an elastic medium. Despite the large amount of experimental and theoretical studies in the literature on the mechanical behavior of composite structures strengthened with CNTs, limited attention has been paid to the effect of an axial graduation of the reinforcing phase on the mechanical response of CNTs-reinforced composite beams. In this paper, CNT fibers are graded across the beam length, according to a power-law function, which expresses a general variation from a linear to parabolic pattern. An Euler-Bernoulli beam theory is considered herein to model the CNTs-reinforced composite structure resting on a Winkler–Pasternak foundation, whose governing equations are derived from the Hamiltonian principle. The theoretical solution of the problem checks for the sensitivity of the mechanical response to different parameters, i.e., the wave number, power index, Winkler and Pasternak coefficients, that could serve for further computational/experimental studies on the same problem, even from a design standpoint.
Exercise for People with Acquired Brain Injury: An ICF Perspective
Authors: Pérez-Rodríguez Marta , García-Hernández Juan José , García-Gómez Saleky , Pérez-Tejero Javier
Published: April 2022

Exercise is an important element in the process of recovery from an acquired brain injury (ABI). However, specific guidance for exercise prescription and interventions in this population are missed. The aim of this study was to establish the key parameters to design and implement exercise programs based on the International Classification of Functioning, Disability, and Health (ICF) domains. A panel of experts that consisted of 13 professionals from neuro-rehabilitation centers evaluated the key parameters of this original proposal. The Heinemann methodology was used for all qualitative analyses. Additionally, Cronbach’s alpha was applied to the statistical analyses. According to the results, Cronbach’s alpha (0.97) indicated excellent internal consistency, and the experts perceptions ratified the proposed criteria to develop exercise programs for people with ABI. The proposed key parameters for the development of exercise programs for people with ABI based in ICF domains (body functions, activity—participation and environmental factors) bring a new, solid, and innovative tool for methodological design of these programs in sub-acute and chronic rehabilitation settings.
Limits of Detection of Mycotoxins by Laminar Flow Strips: A Review
Authors: Zhao Xinyi , Byrne Hugh J. , O’Connor Christine M. , Curtin James , Tian Furong
Published: April 2022

Mycotoxins are secondary metabolic products of fungi. They are poisonous, carcinogenic, and mutagenic in nature and pose a serious health threat to both humans and animals, causing severe illnesses and even death. Rapid, simple and low-cost methods of detection of mycotoxins are of immense importance and in great demand in the food and beverage industry, as well as in agriculture and environmental monitoring, and, for this purpose, lateral flow immunochromatographic strips (ICSTs) have been widely used in food safety and environmental monitoring. The literature to date describing the development of ICSTs for the detection of different types of mycotoxins using different nanomaterials, nanoparticle size, and replicates was reviewed in an attempt to identify the most important determinants of the limit of detection (LOD). It is found that the particle size and type of materials contribute significantly to determining the LOD. The nanoparticle sizes used in most studies have been in the range 15–45 nm and gold nanoparticle-based ICSTs have been shown to exhibit the lowest LOD. Perspectives for potential future development to reduce the LODs of ICSTs are also discussed.
Transcriptome Profiling to Dissect the Role of Genome Duplication on Graft Compatibility Mechanisms in Watermelon
Authors: Kaseb Mohamed Omar , Umer Muhammad Jawad , Anees Muhammad , Zhu Hongju , Zhao Shengjie , Lu Xuqiang , He Nan , El-Remaly Eman , El-Eslamboly Ahmed , Yousef Ahmed F. , Salama Ehab A. A. , Alrefaei Abdulwahed Fahad , Kalaji Hazem M. , Liu Wenge
Published: April 2022

Watermelon (Citrullus lanatus) is a popular crop worldwide. Compared to diploid seeded watermelon, triploid seedless watermelon cultivars are in great demand. Grafting in triploid and tetraploid watermelon produces few seedlings. To learn more about how genome duplication affects graft compatibility, we compared the transcriptomes of tetraploid and diploid watermelons grafted on squash rootstock using a splicing technique. WGCNA was used to compare the expression of differentially expressed genes (DEGs) between diploid and tetraploid watermelon grafted seedlings at 0, 3, and 15 days after grafting (DAG). Only four gene networks/modules correlated significantly with phenotypic characteristics. We found 11 genes implicated in hormone, AOX, and starch metabolism in these modules based on intramodular significance and RT-qPCR. Among these genes, two were linked with IAA (r2 = 0.81), one with ZR (r2 = 0.85) and one with POD (r2 = 0.74). In the MElightsteelblue1 module, Cla97C11G224830 gene was linked with CAT (r2 = 0.81). Two genes from the MEivory module, Cla97C07G139710 and Cla97C04G077300, were highly linked with SOD (r2 = 0.72). Cla97C01G023850 and Cla97C01G006680 from the MEdarkolivegreen module were associated with sugars and starch (r2 = 0.87). Tetraploid grafted seedlings had higher survival rates and hormone, AOX, sugar, and starch levels than diploids. We believe that compatibility is a complicated issue that requires further molecular research. We found that genome duplication dramatically altered gene expression in the grafted plants’ IAA and ZR signal transduction pathways and AOX biosynthesis pathways, regulating hormone levels and improving plant survival.
The Italian Alpine and Subalpine trouts: Taxonomy, Evolution, and Conservation
Authors: Polgar Gianluca , Iaia Mattia , Righi Tommaso , Volta Pietro
Published: April 2022

During the last 150 years, the trout-culture industry focused on enhancing trout populations by stocking, in response to the growing anglers’ demand and the habitat degradation associated to the rapid urbanization and hydropower development. The industrialized north of Italy, home to the Italian Alpine and subalpine trout populations, is the source of most of the revenues of the national trout-culture industry. Its rapid growth, and the massive introduction of non-native interfertile trouts eroded the genetic diversity of native lineages, leading to harsh confrontations between scientists, institutions, and sportfishing associations. We review here the state of the art of the taxonomy and distribution of the northern Italian native trouts, presenting both scientific results and historical documentation. We think the only native trouts in this region are Salmo marmoratus, widespread in this region, plus small and fragmented populations of S. ghigii, present only in the South-western Alps. We strongly recommend the interruption of stocking of domesticated interfertile non-native trouts in this area, and recommend the adoption of Evolutionary Significant Units for salmonid fishery management. We further propose future research directions for a sustainable approach to the conservation and ecosystem management of the fishery resources and inland waters of northern Italy.
Time-Dependent Changes of Laboratory Parameters as Independent Predictors of All-Cause Mortality in COVID-19 Patients
Authors: Limon-de la Rosa Nathaly , Cervantes-Alvarez Eduardo , Méndez-Guerrero Osvely , Gutierrez-Gallardo Miguel A. , Kershenobich David , Navarro-Alvarez Nalu
Published: April 2022

Independent predictors of mortality for COVID-19 patients have been identified upon hospital admission; however, how they behave after hospitalization remains unknown. The aim of this study is to identify clinical and laboratory parameters from admission to discharge or death that distinguish survivors and non-survivors of COVID-19, including those with independent ability to predict mortality. In a cohort of 266 adult patients, clinical and laboratory data were analyzed from admission and throughout hospital stay until discharge or death. Upon admission, non-survivors had significantly increased C reactive protein (CRP), neutrophil count, neutrophil to lymphocyte ratio (NLR) (p < 0.0001, each), ferritin (p < 0.001), and AST (aspartate transaminase) (p = 0.009) compared to survivors. During the hospital stay, deceased patients maintained elevated CRP (21.7 mg/dL [admission] vs. 19.3 [hospitalization], p = 0.060), ferritin, neutrophil count and NLR. Conversely, survivors showed significant reductions in CRP (15.8 mg/dL [admission] vs. 9.3 [hospitalization], p < 0.0001], ferritin, neutrophil count and NLR during hospital stay. Upon admission, elevated CRP, ferritin, and diabetes were independent predictors of mortality, as were persistently high CRP, neutrophilia, and the requirement of invasive mechanical ventilation during hospital stay. Inflammatory and clinical parameters distinguishing survivors from non-survivors upon admission changed significantly during hospital stay. These markers warrant close evaluation to monitor and predict patients’ outcome once hospitalized.
An Artificial Intelligence-Enhanced Blood Pressure Monitor Wristband Based on Piezoelectric Nanogenerator
Authors: Tan Puchuan , Xi Yuan , Chao Shengyu , Jiang Dongjie , Liu Zhuo , Fan Yubo , Li Zhou
Published: April 2022

Hypertensive patients account for about 16% to 37% of the global population, and about 9.4 million people die each year from hypertension and its complications. Blood pressure is an important indicator for diagnosing hypertension. Currently, blood pressure measurement methods are mainly based on mercury sphygmomanometers in hospitals or electronic sphygmomanometers at home. However, people’s blood pressure changes with time, and using only the blood pressure value at the current moment to judge hypertension may cause misdiagnosis. Continuous blood pressure measurement can monitor sudden increases in blood pressure, and can also provide physicians with long-term continuous blood pressure changes as a diagnostic reference. In this article, we design an artificial intelligence-enhanced blood pressure monitoring wristband. The wristband’s sensors are based on piezoelectric nanogenerators, with a high signal-to-noise ratio of 29.7 dB. Through the transformer deep learning model, the wristband can predict blood pressure readings, and the loss value is lower than 4 mmHg. By wearing this blood pressure monitoring wristband, we realized three days of continuous blood pressure monitoring of the subjects. The blood pressure monitoring wristband is lightweight, has profound significance for the prevention and treatment of hypertension, and has wide application prospects in medical, military, aerospace and other fields.
Behavioral Ethics Ecologies of Human-Artificial Intelligence Systems
Authors: Fox Stephen
Published: April 2022

Historically, evolution of behaviors often took place in environments that changed little over millennia. By contrast, today, rapid changes to behaviors and environments come from the introduction of artificial intelligence (AI) and the infrastructures that facilitate its application. Behavioral ethics is concerned with how interactions between individuals and their environments can lead people to questionable decisions and dubious actions. For example, interactions between an individual’s self-regulatory resource depletion and organizational pressure to take non-ethical actions. In this paper, four fundamental questions of behavioral ecology are applied to analyze human behavioral ethics in human–AI systems. These four questions are concerned with assessing the function of behavioral traits, how behavioral traits evolve in populations, what are the mechanisms of behavioral traits, and how they can differ among different individuals. These four fundamental behavioral ecology questions are applied in analysis of human behavioral ethics in human–AI systems. This is achieved through reference to vehicle navigation systems and healthcare diagnostic systems, which are enabled by AI. Overall, the paper provides two main contributions. First, behavioral ecology analysis of behavioral ethics. Second, application of behavioral ecology questions to identify opportunities and challenges for ethical human–AI systems.
Metaheuristic-Based Practical Tool for Optimal Design of Reinforced Concrete Isolated Footings: Development and Application for Parametric Investigation
Authors: Waheed Junaid , Azam Rizwan , Riaz Muhammad Rizwan , Shakeel Mansoor , Mohamed Abdullah , Ali Elimam
Published: April 2022

In the process of designing an economical structure, safety along with total cost must be balanced. This can be attained by design optimization, however the complex nature of the algorithms involved hinders its application. Further, there is a severe lack of research on the optimization of reinforced concrete (RC) isolated footings. Therefore, the main objective of this research is to develop a user-friendly tool for the optimization of RC isolated footings using advanced metaheuristic algorithms to make it more practical and convenient to adopt for design optimization. For this purpose, a spreadsheet-based interface is created in which input parameters from the original design can be entered to find the best option for the minimum cost design. The Evolutionary Algorithm (EA) and the Genetic Algorithm (GA) are used as metaheuristic techniques for optimization. The original design of four examples from the literature is compared with the optimized design obtained from the developed tool to demonstrate its efficiency. For the considered case studies, cost-saving of up to 44% has been obtained. Furthermore, a parametric investigation for the minimum cost objective using the GA has been performed through which a detailed analysis of geometric reinforcement and material strength variables is conducted. The results lead to the derivation of useful thumb rules for the economical design and proportioning of isolated footings.
The Influence of Synthesis Methods and Experimental Conditions on the Photocatalytic Properties of SnO2: A Review
Authors: do Nascimento Jéssica Luisa Alves , Chantelle Lais , dos Santos Iêda Maria Garcia , Menezes de Oliveira André Luiz , Alves Mary Cristina Ferreira
Published: April 2022

Semiconductors based on transition metal oxides represent an important class of materials used in emerging technologies. For this, the performance of these materials strongly depends on the size and morphology of particles, surface charge characteristics, and the presence of bulk and surface defects that are influenced by the synthesis method and the experimental conditions the materials are prepared. In this context, the present review aims to report the importance of choosing the synthesis methods and experimental conditions to modify structural, morphological, and electronic characteristics of semiconductors, more specifically, tin oxide (SnO2), since these parameters may be a determinant for better performance in various applications, including photocatalysis. SnO2 is an n-type semiconductor with a band gap between 3.6 and 4.0 eV, whose intrinsic characteristics are responsible for its electrical conductivity, good optical characteristics, high thermal stability, and other qualities. Such characteristics have provided excellent results in advanced oxidative processes, i.e., heterogeneous photocatalysis applications. This process involves semiconductors in the production of hydroxyl radicals via activation by light absorption, and it is considered as an emerging and promising technology for domestic-industrial wastewater treatment. In our review article, we focused on the photodegradation of different organic dyes and types of persistent organic pollutants using SnO2-based photocatalysts, and how the efficiency of these materials can be impacted by synthesis methods and experimental conditions employed to prepare them.
Synthesis and Application of Egg Shell Biochar for As(V) Removal from Aqueous Solutions
Authors: Akram Asma , Muzammal Shazma , Shakoor Muhammad Bilal , Ahmad Sajid Rashid , Jilani Asim , Iqbal Javed , Al-Sehemi Abdullah G. , Kalam Abul , Aboushoushah Samia Faisal O.
Published: April 2022

Arsenic in water bodies has increased to toxic levels and become a major issue worldwide. Among various treatment methods, the removal of As from polluted water with low-cost and environmental-friendly sorbents such as biochar is considered a promising technique nowadays. In a recent experiment, the treatment of As-contaminated water using egg shell biochar was studied. Various parameters affecting the sorption, such as pH, contact time, sorbent dose, As(V) concentration and the effects of anions, were also examined. The results revealed that at a pH of 4.5, a maximum sorption of 6.3 mg g−1 was observed, and the As(V) removal was 96% with an As concentration of 0.6 mg L−1 and a sorbent dose of 0.9 g L−1. At a contact time of 2 h (120 min), a maximum sorption of 6.3 mg g−1 was noted with a removal percentage of 96%. The sorption of As(V) was obtained at an optimal sorbent dose of 0.9 g L−1. The SEM-EDS data illustrated that biochar consisted of a large number of active sites for As(V) adsorption, and As appeared on the biochar surface after the sorption experiments. Moreover, XPS analyses also confirmed the presence of As(V) on the biochar surface after treatment with As-contaminated water. In a nutshell, the results of this study demonstrate that egg shell biochar has notable efficiency in the removal of As(V) from aqueous solution and that egg shell biochar could be a cost-effective and environmental-friendly sorbent for the treatment of As(V)-contaminated water, specifically in developing countries.
The Increase in Circulating Levels of Pro-Inflammatory Chemokines, Cytokines, and Complement C5 in Canines with Impaired Kidney Function
Authors: Tavener Selena K. , Jewell Dennis E. , Panickar Kiran S.
Published: April 2022

Chronic low-grade inflammation is a key contributor to the progression of kidney disease. The release of cytokines and other pro-inflammatory proteins may further contribute to detrimental kidney health by increasing interstitial edema and renal fibrosis. The aim of the present study was to investigate the inflammatory markers in canines who developed renal disease naturally and were diagnosed with renal disease either during life or following necropsy, as assessed by a veterinarian. RNA was isolated from canine blood obtained at necropsy and stored as bioarchived samples from ten canines with renal disease (9.6–14.7 yr) and ten controls (10.1–14.8 yr). At the time of death, the mean blood creatinine concentration and BUN were elevated in dogs with renal disease compared to control (both p < 0.01). Samples were assessed for changes in gene expression using the Canine cytokine RT2 Profiler PCR Array for inflammation. There was a significant increase in C-C Motif Chemokine Ligand 16 (CCL16), C-X-C Motif Chemokine Ligand 5 (CXCL5), Interleukin 16 (IL-16), and Complement Component 5 (C5) (all p < 0.05 vs. con). In addition, there was also a statistically non-significant increase in 49 genes and a down-regulation in 35 genes from a panel of total 84 genes. Pro-inflammatory genes including CCL16, CXCL5, IL-16, and C5 can all contribute to renal inflammation and fibrosis through different signaling pathways and may lead to a progressive impairment of kidney function. Blockade of their activation may be important in ameliorating the initiation and/or the progression of renal disease.
Respiratory Muscle Training in Patients with Obstructive Sleep Apnoea: A Systematic Review and Meta-Analysis
Authors: Torres-Castro Rodrigo , Solis-Navarro Lilian , Puppo Homero , Alcaraz-Serrano Victoria , Vasconcello-Castillo Luis , Vilaró Jordi , Vera-Uribe Roberto
Published: April 2022

Background: Effective treatments for obstructive sleep apnoea (OSA) include positive pressure, weight loss, oral appliances, surgery, and exercise. Although the involvement of the respiratory muscles in OSA is evident, the effect of training them to improve clinical outcomes is not clear. We aimed to determine the effects of respiratory muscle training in patients with OSA. Methods: A systematic review was conducted in seven databases. Studies that applied respiratory muscle training in OSA patients were reviewed. Two independent reviewers analysed the studies, extracted the data and assessed the quality of evidence. Results: Of the 405 reports returned by the initial search, eight articles reporting on 210 patients were included in the data synthesis. Seven included inspiratory muscle training (IMT), and one included expiratory muscle training (EMT). Regarding IMT, we found significant improvement in Epworth sleepiness scale in −4.45 points (95%CI −7.64 to −1.27 points, p = 0.006), in Pittsburgh sleep quality index of −2.79 points (95%CI −4.19 to −1.39 points, p < 0.0001), and maximum inspiratory pressure of −29.56 cmH2O (95%CI −53.14 to −5.98 cmH2O, p = 0.01). However, the apnoea/hypopnea index and physical capacity did not show changes. We did not perform a meta-analysis of EMT due to insufficient studies. Conclusion: IMT improves sleepiness, sleep quality and inspiratory strength in patients with OSA.
Volatile Organic Compounds in Dactylorhiza Species
Authors: Mecca Marisabel , Racioppi Rocco , Romano Vito Antonio , Viggiani Licia , Lorenz Richard , D’Auria Maurizio
Published: April 2022

HS-SPME-GC–MS analysis of the scent of Dactylorhiza viridis revealed the presence of verbenone (28.86%), caryophyllene (25.67%), β-terpineol (9.48%), and δ-cadinene (6.94%). In the scent of Dactylorhiza romana β-ocimene (18.69%), pentadecane (18.40%), α-farnesene (14.65%), and isopropyl 14-methylpentadecanoate (14.32%) were found. Dactylorhiza incarnata contained tetradecane (11.07%), pentadecane (28.40%), hexadecane (19.53%), heptadecane (17.33%), and α-cubenene (11.48%). Analysis of Dactylorhiza saccifera showed the presence of caryophyllene (17.38%), pentadecane (6.43%), hexadecane (6.13%), and heptadecane (5.08%). Finally, the aroma components found in Dactylorhiza sambucina were caryophyllene (12.90%), β-sesquiphellandrene (32.16%), 4,5-di-epi-aristolochene (10.18%).
Modeling the Territorial Structure Dynamics of the Northern Part of the Volga-Akhtuba Floodplain
Authors: Isaeva Inessa I. , Voronin Alexander A. , Khoperskov Alexander V. , Kharitonov Mikhail A.
Published: April 2022

The subject of our study is the tendency to reduce the floodplain area of regulated rivers and its impact on the degradation of the socio-environmental systems in the floodplain. The aim of the work is to create a new approach to the analysis and forecasting of the multidimensional degradation processes of floodplain territories under the influence of natural and technogenic factors. This approach uses methods of hydrodynamic and geoinformation modeling, statistical analysis of observational data and results of high-performance computational experiments. The basis of our approach is the dynamics model of the complex structure of the floodplain. This structure combines the characteristics of the frequency ranges of flooding and the socio-environmental features of various sites (cadastral data of land use). Modeling of the hydrological regime is based on numerical shallow water models. The regression model of the technogenic dynamics of the riverbed allowed us to calculate corrections to the parameters of real floods that imitate the effect of this factor. This made it possible to use digital maps of the modern topography for hydrodynamic modeling and the construction of floods maps for past and future decades. The technological basis of our study is a set of algorithms and software, consisting of three modules. The data module includes, first of all, the cadastres of the territory of the Volga-Akhtuba floodplain (VAF, this floodplain is the interfluve of the Volga and Akhtuba rivers for the last 400 km before flowing into the Caspian Sea), satellite and natural observation data, spatial distributions of parameters of geoinformation and hydrodynamic models. The second module provides the construction of a multilayer digital model of the floodplain area, digital maps of floods and their aggregated characteristics. The third module calculates a complex territorial structure, criteria for the state of the environmental and socio-economic system (ESES) and a forecast of its changes. We have shown that the degradation of the ESES of the northern part of the VAF is caused by the negative dynamics of the hydrological structure of its territory, due to the technogenic influence the hydroelectric power station on the Volga riverbed. This dynamic manifests itself in a decrease in the stable flooded area and an increase in the unflooded and unstable flooded areas. An important result is the forecast of the complex territorial structure and criteria for the state of the interfluve until 2050.
Envelope Function Analysis of Quasicrystals
Authors: Strzałka Radosław , Chuchra Łukasz , Wolny Janusz
Published: April 2022

Quasicrystals have attracted a growing interest in material science because of their unique properties and applications. Proper determination of the atomic structure is important in designing a useful application of these materials, for which a difficult phase problem of the structure factor must be solved. Diffraction patterns of quasicrystals consist of a periodic series of peaks, which can be reduced to a single envelope. Knowing the distribution of the diffraction image into series, it is possible to recover information about the phase of the structure factor without using time-consuming iterative methods. By the inverse Fourier transform, the structure factor can be obtained (enclosed in the shape of the average unit cell, or atomic surface) directly from the diffraction patterns. The method based on envelope function analysis was discussed in detail for a model 1D (Fibonacci chain) and 2D (Penrose tiling) quasicrystal. First attempts to apply this technique to a real Al-Cu-Rh decagonal quasicrystal were also made.
A Collection of 30 Multidimensional Functions for Global Optimization Benchmarking
Authors: Plevris Vagelis , Solorzano German
Published: April 2022

A collection of thirty mathematical functions that can be used for optimization purposes is presented and investigated in detail. The functions are defined in multiple dimensions, for any number of dimensions, and can be used as benchmark functions for unconstrained multidimensional single-objective optimization problems. The functions feature a wide variability in terms of complexity. We investigate the performance of three optimization algorithms on the functions: two metaheuristic algorithms, namely Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), and one mathematical algorithm, Sequential Quadratic Programming (SQP). All implementations are done in MATLAB, with full source code availability. The focus of the study is both on the objective functions, the optimization algorithms used, and their suitability for solving each problem. We use the three optimization methods to investigate the difficulty and complexity of each problem and to determine whether the problem is better suited for a metaheuristic approach or for a mathematical method, which is based on gradients. We also investigate how increasing the dimensionality affects the difficulty of each problem and the performance of the optimizers. There are functions that are extremely difficult to optimize efficiently, especially for higher dimensions. Such examples are the last two new objective functions, F29 and F30, which are very hard to optimize, although the optimum point is clearly visible, at least in the two-dimensional case.
LumiraDX SARS-CoV-2 Antigen Test for Diagnosing Acute SARS-CoV-2 Infection: Critical Literature Review and Meta-Analysis
Authors: Lippi Giuseppe , Henry Brandon M. , Plebani Mario
Published: April 2022

We present here a critical literature review and meta-analysis on the accuracy of the LumiraDX SARS-CoV-2 Antigen Test for diagnosing acute SARS-CoV-2 infection. An electronic search was conducted in the Scopus and Medline databases using the keywords “LumiraDX” AND “COVID-19” OR “SARS-CoV-2”, without date (i.e., up to 1 February 2022) or language restrictions, for detecting clinical studies where the diagnostic accuracy of the LumiraDX SARS-CoV-2 Antigen Test was compared with reference molecular diagnostic methods. All studies where the rates of true positive, true negative, false positive and false negative cases were available for constructing a 2 × 2 table and providing pooled estimates of diagnostic sensitivity, specificity and accuracy were included in a pooled analysis. The study was conducted in accordance with the PRISMA (preferred reporting items for systematic reviews and meta-analyses) reporting checklist. Eleven studies (n = 8527 samples) could be included in our pooled analysis, while five additional documents provided diagnostic accuracy data but could not be extracted for construction of a 2 × 2 table. The pooled diagnostic sensitivity and specificity were 0.86 (95%CI, 0.84–0.88) and 0.99 (95%CI, 0.98–0.99), respectively, while the area under the summary receiver operating characteristic curve was 0.974 (95%CI, 0.965–0.983) and the agreement was 96.8% (95%CI, 96.4–97.1%), with kappa statistics of 0.87 (95%CI, 0.85–0.88). In conclusion, the diagnostic performance of the LumiraDX SARS-CoV-2 Antigen Test would allow the conclusion that it may be seen as a reliable alternative to molecular testing for the rapid preliminary screening of acute SARS-CoV-2 infections.
Mutation Analysis of Second Primary Tumors in Oral Cancer in Taiwanese Patients through Next-Generation Sequencing
Authors: Liu Ting-Yuan , Lee Chien-Chin , Chen Yu-Chia , Chang Ya-Sian , Huang Hsi-Yuan , Lee Ya-Ting , Yen Ju-Chen , Chao Dysan , Chang Jan-Gowth
Published: April 2022

Head and neck cancer has poor overall survival. Patients with head and neck cancer more frequently develop second primary tumors than do patients with other cancers, leading to a poor prognosis. In this study, we used next-generation sequencing to analyze and compare mutations between first tumors and second tumors in oral cancer. We retrieved tumor tissues collected from 13 patients who were diagnosed twice as having cancer. We used driver gene and trunk mutations to distinguish between recurrent cancer and primary cancer in oral cancer. We observed unique driver gene mutations in three patients with an initial clinical diagnosis of recurrent cancer; hence, we believe that the corresponding patients had primary cancer. Four patients with an initial clinical diagnosis of primary cancer were found to actually have recurrent cancer according to our results. Genetic testing can be used to enhance the accuracy of clinical diagnosis.
Higher-Order Belief Propagation Correction Decoder for Polar Codes
Authors: Zhang Meng , Li Zhuo , Xing Lijuan , Liao Xin
Published: April 2022

Belief propagation (BP) decoding for polar codes has been extensively studied because of its inherent parallelism. However, its performance remains inferior to that of successive cancellation list decoding (SCL) due to the structure of the decoding graph. To improve the block error rate (BLER) performance, the BP correction (BPC) decoding, a post-processing scheme that corrects prior knowledge of the identified code bit, improves convergence by executing additional iterations on the failed BP decoder. Moreover, the BPC decoder demonstrates a better decoding performance than the BP-based bit-flipping decoder. Nevertheless, the additional decoding attempts lead to increased latency. In this article, a modified BPC decoder is proposed to reduce the number of decoding attempts by redefining the correction rules. A new metric is designed to effectively identify the corrected location. Numerical results show that the proposed modified BPC decoder achieves a slight improvement in BLER compared with the original BPC, with a dramatic reduction in average complexity. Furthermore, a higher-order version, named MBPC-Ω, is extended to further improve the performance, where the Ω is the maximum correction order. Numerical results show that the higher-order modified BPC achieves a similar BLER performance to existing multiple bit-flipping BP decoders but has around half the latency overhead. In addition, the proposed MBPC-2 decoder performs better than the cyclic redundancy check-aided SCL (CA-SCL) decoder with list size 4 and is slightly worse than the CA-SCL with list size 8 in high signal-to-noise ratio (SNR) regions but with significant decoding latency reduction.
Entropy-Enhanced Attention Model for Explanation Recommendation
Authors: Yan Yongjie , Yu Guang , Yan Xiangbin
Published: April 2022

Most of the existing recommendation systems using deep learning are based on the method of RNN (Recurrent Neural Network). However, due to some inherent defects of RNN, recommendation systems based on RNN are not only very time consuming but also unable to capture the long-range dependencies between user comments. Through the sentiment analysis of user comments, we can better capture the characteristics of user interest. Information entropy can reduce the adverse impact of noise words on the construction of user interests. Information entropy is used to analyze the user information content and filter out users with low information entropy to achieve the purpose of filtering noise data. A self-attention recommendation model based on entropy regularization is proposed to analyze the emotional polarity of the data set. Specifically, to model the mixed interactions from user comments, a multi-head self-attention network is introduced. The loss function of the model is used to realize the interpretability of recommendation systems. The experiment results show that our model outperforms the baseline methods in terms of MAP (Mean Average Precision) and NDCG (Normalized Discounted Cumulative Gain) on several datasets, and it achieves good interpretability.
A Low-Noise and Monolithic Array Tactile Sensor Based on Incremental Delta-Sigma Analog-to-Digital Converters
Authors: Huang Linqing , Shen Jiulong , Ma Qiyun , Wang Hao , Tsang Wei-Mong , Tang Fang , Wang Miao
Published: April 2022

A low-noise and monolithic array tactile sensor, in which a tactile sensing unit, a low-noise analog front end (AFE), and a high-resolution delta-sigma analog-to-digital converter (ΔΣ ADC) are fully integrated, is presented in this paper. In this proposed system, compared with a discrete-device-based board-level system, the parasitic effect of a long cable connection can be reduced, and results are more accurate. Furthermore, a smaller system area and a lower power consumption can be achieved in this monolithic system. A discrete-continuous mixed mode bandpass AFE is proposed to filter out low-frequency flicker noise and high-frequency white noise. In order to improve the quantization rate of the sensor readout circuit and further suppress the high-frequency noise, a two-way alternate sample-and-hold circuit scheme is adopted in this design. The proposed tactile sensor is designed and fabricated in a 0.5-μm CMOS (Complementary metal oxide semiconductor)mixed-signal process with a 16 × 16 array and a total chip area of 1.9 × 1.9 cm2. This chip consumes 33.5 mW from a 5 V supply. The measurement results showed that the signal-to-noise and distortion rate (SNDR) was 65.2894 dB and that the effective number of bits (ENoB) was 10.553 dB. Moreover, this sensor could achieve a pressure measurement range of 0.002–0.5 N with a resolution of 0.4 mN.
A Novel Fusion Pruning Algorithm Based on Information Entropy Stratification and IoT Application
Authors: Zhao Ming , Hu Min , Li Meng , Peng Sheng-Lung , Tan Junbo
Published: April 2022

To further reduce the size of the neural network model and enable the network to be deployed on mobile devices, a novel fusion pruning algorithm based on information entropy stratification is proposed in this paper. Firstly, the method finds similar filters and removes redundant parts by Affinity Propagation Clustering, then secondly further prunes the channels by using information entropy stratification and batch normalization (BN) layer scaling factor, and finally restores the accuracy training by fine-tuning to achieve a reduced network model size without losing network accuracy. Experiments are conducted on the vgg16 and Resnet56 network using the cifar10 dataset. On vgg16, the results show that, compared with the original model, the parametric amount of the algorithm proposed in this paper is reduced by 90.69% and the computation is reduced to 24.46% of the original one. In ResNet56, we achieve a 63.82%-FLOPs reduction by removing 63.53% parameters. The memory occupation and computation speed of the new model are better than the baseline model while maintaining a high network accuracy. Compared with similar algorithms, the algorithm has obvious advantages in the dimensions of computational speed and model size. The pruned model is also deployed to the Internet of Things (IoT) as a target detection system. In addition, experiments show that the proposed model is able to detect targets accurately with low reasoning time and memory. It takes only 252.84 ms on embedded devices, thus matching the limited resources of IoT.
Design Method for Variable Frequency Brushless Synchronous Generators
Authors: Wang Yongjie , Wang Huizhen , Liu Weifeng , Wang Qin , Zhao Xing
Published: April 2022

Brushless synchronous generators, which have the structure of three-stage generators to realize brushless excitation, are the most commonly used aero-generators. With the development of more electric aircraft technology, the output frequency of aero-generators is changing from constant to variable, and the characteristics of generators are also changed. To make sure that the generators can be adapted to the variable frequency operation, this paper analyzes the effects of different operating conditions on generator performance and proposes corresponding design methods. The design and verification of the electromagnetic field, fluid field, temperature field and stress field are carried out for the variable frequency generator. A prototype generator is manufactured according to the design results. An experimental platform is set up to test the performances of the designed generator. The final experimental results show that the generator can work well in variable frequency generation systems, which proves the design method proposed in this paper is effective and feasible.
Possibilities for Deep Renovation in Multi-Apartment Buildings in Different Economic Conditions in Europe
Authors: Končalović Davor , Nikolic Jelena , Vukasinovic Vladimir , Gordić Dušan , Živković Dubravka
Published: April 2022

This paper analyzes the potential for deep renovation of an apartment building to the level of a passive house in different contexts in the continental part of Europe. The examined variables include different local climatic conditions, levels of economic development, and levels of market development (energy prices, energy footprint, labor prices, etc.) as well as different energy efficiency retrofit scenarios in four different countries. The adequate methodology was developed here in order to obtain an optimal solution for deep renovation in each context. The proposed methodology was based on the interaction of energy simulation and mathematical optimization. In this model, the energy performances of a building are determined with the EnergyPlus package and the optimal solution was obtained by using a mixed-integer non-linear programming model. The results demonstrate that the optimal solution for each analyzed location cannot provide cost-effectiveness over the lifetime of a building, so the introduction of additional subsidies or incentives, such as carbon taxes and upfront subsidies, is necessary.
Periglacial Landforms and Fluid Dynamics in the Permafrost Domain: A Case from the Taz Peninsula, West Siberia
Authors: Misyurkeeva Natalya , Buddo Igor , Kraev Gleb , Smirnov Aleksandr , Nezhdanov Alexey , Shelokhov Ivan , Kurchatova Anna , Belonosov Andrei
Published: April 2022

Most of the developing oil and gas fields in Russia are located in Arctic regions and constructed on permafrost, where recent environmental changes cause multiple hazards for their infrastructure. The blowing-up of pingos, resulting in the formation of gas emission craters, is one of the disastrous processes associated both with these external changes and, likely, with deep sources of hydrocarbons. We traced the channels of fluid migration which link a gas features reservoirs with periglacial phenomena associated with such craters with the set of geophysical methods, including common depth point and shallow transient electromagnetic methods, on an area of a prospected gas field. We found correlated vertical anomalies of acoustic coherence and electrical resistivity associated with gas chimneys in the upper 500–600 m of the section. The thickness of the ice-bonded permafrost acting as a seal for fluids decreased in the chimney zone, forming 25–50 m deep pockets in the permafrost base. Three pingos out of six were located above chimneys in the study area of 200 km2. Two lakes with parapets typical for craters were found. We conclude that the combination of applied methods is efficacious in terms of identifying this type of hazard and locating potentially hazardous objects in the given territory.