bluuebunny/crossref_metadata_2025 huggingface dataset:
Estradiol (E2) Improves Glucose-Stimulated Insulin Secretion and Stabilizes GDM Progression in a Prediabetic Mouse Model
Authors: Liebmann Moritz , Asuaje Pfeifer Melissa , Grupe Katharina , Scherneck Stephan
Published: June 2022

Female New Zealand obese (NZO) mice are an established model of preconceptional (pc.) prediabetes that progresses as gestational diabetes mellitus (GDM) during gestation. It is known that NZO mice show improvement in insulin sensitivity and glucose-stimulated insulin secretion (GSIS) during gestation in vivo. The latter is no longer detectable in ex vivo perifusion experiments in isolated islets of Langerhans, suggesting a modulation by extrapancreatic factors. Here, we demonstrated that plasma 17β-estradiol (E2) levels increased markedly in NZO mice during gestation. The aim of this work was to determine whether these increased E2 levels are responsible for the improvement in metabolism during gestation. To achieve this goal, we examined its effects in isolated islets and primary hepatocytes of both NZO and metabolically healthy NMRI mice. E2 increased GSIS in the islets of both strains significantly. Hepatic glucose production (HGP) failed to be decreased by insulin in NZO hepatocytes but was reduced by E2 in both strains. Hepatocytes of pregnant NZO mice showed significantly lower glucose uptake (HGU) compared with NMRI controls, whereby E2 stimulation diminished this difference. Hepatocytes of pregnant NZO showed reduced glycogen content, increased cyclic adenosine monophosphate (cAMP) levels, and reduced AKT activation. These differences were abolished after E2 stimulation. In conclusion, our data indicate that E2 stabilizes and prevents deterioration of the metabolic state of the prediabetic NZO mice. E2 particularly increases GSIS and improves hepatic glucose utilization to a lower extent.
Combined Therapy with a CCR2/CCR5 Antagonist and FGF21 Analogue Synergizes in Ameliorating Steatohepatitis and Fibrosis
Authors: Puengel Tobias , Lefere Sander , Hundertmark Jana , Kohlhepp Marlene , Penners Christian , Van de Velde Frederique , Lapauw Bruno , Hoorens Anne , Devisscher Lindsey , Geerts Anja , Boehm Stephanie , Zhao Qihong , Krupinski John , Charles Edgar D. , Zinker Bradley , Tacke Frank
Published: June 2022

(1) Background: With new potential drug targets emerging, combination therapies appear attractive to treat non-alcoholic steatohepatitis (NASH) and fibrosis. Chemokine receptor CCR2/5 antagonists can improve fibrosis by reducing monocyte infiltration and altering hepatic macrophage subsets. Fibroblast growth factor 21 (FGF21) may improve NASH by modulating lipid and glucose metabolism. We compared effects of single drug to combination treatment as therapeutic strategies against NASH. (2) Methods: We analyzed serum samples and liver biopsies from 85 nonalcoholic fatty liver disease (NAFLD) patients. A CCR2/5 inhibitor (BMS-687681-02-020) and a pegylated FGF21 agonist (BMS-986171) were tested in male C57BL/6J mice subjected to dietary models of NASH and fibrosis (choline-deficient, L-amino acid-defined, high-fat diet (CDAHFD) up to 12 weeks; short- (2w) or long-term (6w) treatment). (3) Results: In NAFLD patients, chemokine CCL2 and FGF21 serum levels correlated with inflammatory serum markers, only CCL2 was significantly associated with advanced liver fibrosis. In rodent NASH, CCR2/5 inhibition significantly reduced circulating Ly6C+ monocytes and hepatic monocyte-derived macrophages, alongside reduced hepatic inflammation and fibrosis. FGF21 agonism decreased body weight, liver triglycerides and histological NASH activity. Combination treatment reflected aspects of both compounds upon short- and long-term application, thereby amplifying beneficial effects on all aspects of steatohepatitis and fibrosis. (4) Conclusions: CCR2/5 inhibition blocks hepatic infiltration of inflammatory monocytes, FGF21 agonism improves obesity-related metabolic disorders. Combined therapy ameliorates steatohepatitis and fibrosis more potently than single drug treatment in rodent NASH, corroborating the therapeutic potential of combining these two approaches in NASH patients.
Cichoric Acid May Play a Role in Protecting Hair Cells from Ototoxic Drugs
Authors: Lai Ting-Wei , Cheng Hsin-Lin , Su Tzu-Rong , Yang Jiann-Jou , Su Ching-Chyuan
Published: June 2022

Ototoxic hearing loss due to antibiotic medication including aminoglycosides and excess free radical production causes irreversible hair cell injury. Cichoric acid, a naturally occurring phenolic acid, has recently been found to exert anti-oxidative and anti-inflammatory properties through its free radical scavenging capacity. The present study aimed to investigate the protective effects of cichoric acid against neomycin-induced ototoxicity using transgenic zebrafish (pvalb3b: TagGFP). Our results indicated that cichoric acid in concentrations up to 5 μM did not affect zebrafish viability during the 2 h treatment period. Therefore, the otoprotective concentration of cichoric acid was identified as 5 μM under 2 h treatment by counting viable hair cells within the neuromasts of the anterior- and posterior-lateral lines in the study. Pretreatment of transgenic zebrafish with 5 μM of cichoric acid for 2 h significantly protected against neomycin-induced hair cell death. Protection mediated by cichoric acid was, however, lost over time. A terminal deoxynucleotidyl transferase dUTP nick-end labeling (TUNEL) assay and FM4-64 staining, respectively, provided in situ evidence that cichoric acid ameliorated apoptotic signals and mechanotransduction machinery impairment caused by neomycin. A fish locomotor test (distance move, velocity, and rotation frequency) assessing behavioral alteration after ototoxic damage revealed rescue due to cichoric acid pretreatment before neomycin exposure. These findings suggest that cichoric acid in 5 μM under 2 h treatment has antioxidant effects and can attenuate neomycin-induced hair cell death in neuromasts. Although cichoric acid offered otoprotection, there is only a small difference between pharmacological and toxic concentrations, and hence cichoric acid can be considered a rather prototypical compound for the development of safer otoprotective compounds.
A Test Method for Obstacle-Avoidance Performance of Unmanned Surface Vehicles Based on Mobile-Buoy–Shore Multisource-Sensing-Data Fusion
Authors: Xiao Guoquan , Zheng Guihong , Ren Bing , Wang Yue , Hong Xiaobin , Zhang Zhigang
Published: June 2022

In order to avoid the influence of the test system itself on the autonomous navigation and performance test accuracy of unmanned surface vehicles (USVs), a test method for the obstacle-avoidance performance of USVs based on mobile-buoy–shore multisource-sensing-data fusion is proposed. In this method, a mobile-buoy-integrated test system is designed (that is, the test instrument is installed on the mobile buoy). The buoy is both the carrier of the test instrument and the obstacle. The software and hardware functions of the test system are realized in modules, and the obstacle-avoidance monitoring function of the USV is realized by the trajectory-tracking method of buoy perception preprocessing and shore adaptive weighted fusion. Then, on the basis of the mobile-buoy–shore sensing-data-fusion method, performance tests and a quantitative evaluation of the obstacle perception, static-obstacle avoidance, and dynamic-obstacle avoidance of the USV were carried out. The results show that: (1) the tested USV can accurately identify the distance between buoys; (2) the three static-obstacle-avoidance performance scores of the single obstacle, continuous obstacle, and inflection-point obstacle are 74.81, 77.14, and 47.61, respectively, and the quantitative evaluation score of the static-obstacle-avoidance comprehensive performance is 66.4; (3) the obstacle-avoidance-performance scores of overtaking, encounter, and cross encounter are about 53.92, 36.51, and 6.48, respectively, and the quantitative evaluation score of the comprehensive performance of the dynamic-obstacle avoidance is 72.36. The above quantitative evaluation results show that the system can: participate in track intervention and obstacle-avoidance monitoring as an obstacle; give the static- and dynamic-obstacle-avoidance quantitative evaluation results in a predetermined way, which verifies the feasibility and effectiveness of the obstacle-avoidance-performance test system of the USV on the basis of mobile-buoy–shore multisource-sensing fusion; and be used for the testing and evaluation of the obstacle-avoidance performance of USVs.
Recent Advances in Directed Yeast Genome Evolution
Authors: Yao Zhen , Wang Qinhong , Dai Zongjie
Published: June 2022

Saccharomyces cerevisiae, as a Generally Recognized as Safe (GRAS) fungus, has become one of the most widely used chassis cells for industrial applications and basic research. However, owing to its complex genetic background and intertwined metabolic networks, there are still many obstacles that need to be overcome in order to improve desired traits and to successfully link genotypes to phenotypes. In this context, genome editing and evolutionary technology have rapidly progressed over the last few decades to facilitate the rapid generation of tailor-made properties as well as for the precise determination of relevant gene targets that regulate physiological functions, including stress resistance, metabolic-pathway optimization and organismal adaptation. Directed genome evolution has emerged as a versatile tool to enable researchers to access desired traits and to study increasingly complicated phenomena. Here, the development of directed genome evolutions in S. cerevisiae is reviewed, with a focus on different techniques driving evolutionary engineering.
The Interactive Effect of Ownership Structure on the Relationship between Annual Board Report Readability and Stock Price Crash Risk
Authors: Shandiz Mohsen , Zadeh Farzaneh , Askarany Davood
Published: June 2022

This study investigates the interactive effect of ownership structure on the relationship between annual board report readability and stock price crash risk in companies listed on the Tehran Stock Exchange (TSE). The negative skewness model was used to measure the crash risk of stock prices and the Fog index was used for determining the readability of the board of directors’ report. The ownership structure is examined in institutional ownership, significant managerial ownership, and family ownership. The data of companies listed on the TSE from 2013 to 2019 have been used. The statistical method of this research is multiple regressions and, to test the research hypotheses, the data panel model and the ordinary least squares method have been employed. Overall, this study provides new evidence to explain the reporting quality and the crash risk of stock prices from the lenses of the agency theory. It further investigates the interactive effect of ownership structure on the relationship between annual board report readability and stock price crash risk. The results show a significant correlation between the readability of the board of directors’ report and the crash risk of stock prices. Furthermore, the relationship between the readability of the board report and stock price crash risk is not affected by the ownership structure, including institutional ownership, significant managerial ownership, and family ownership. It can be inferred that an ownership structure, which includes institutional shareholders, significant shareholders, and family ownership, increases the supervision of managers and their reports, so they cannot keep adverse information from being released. This will ultimately improve the readability of their reports and reduce the risk of stock price crashes.
Slurry Spreading on a Silt Loam Soil: Influence of Tyre Inflation Pressure, Number of Passages, Machinery Choice and Tillage Method on Physical Soil Quality and Sugar Beet Growth
Authors: Vanderhasselt Adriaan , Euben Ronald , D’Hose Tommy , Cornelis Wim
Published: June 2022

Soil compaction forms a major threat to the well-functioning of agricultural soils. This threat is primarily driven by the increasing wheel loads of modern farming machinery and the increased frequency of field operations in periods when the soil is moist to wet and thus more prone to compaction. The application of slurry in early spring can have a highly detrimental impact, certainly for a crop like sugar beet, which is sensitive to soil compaction. A one-year experiment was set up on silt loam soil in the Belgian loess belt to assess the short-term impact of this field operation on soil under conventional ploughing and under non-inversion tillage. Two types of farming machinery were compared: a widely used tractor-trailer combination and a less common self-propelled slurry spreader, with the latter having higher wheel loads. Both machines were operated according to common or standard practice and a practice that aims at preventing soil compaction. For the tractor-trailer, this was with tyre inflation pressure recommended for road traffic and field traffic, respectively, corresponding with high and low tyre inflation pressure. The self-propelled slurry spreader was operated under standard and crab steering, respectively. Lowering the tyre inflation pressure to the recommended level for field traffic limited soil compaction and sugar beet yield loss. Although the effects of crab steering were less pronounced, it lowered the impact on the soil by limiting the number of passages. The overall machinery effect remained limited. The heavier self-propelled slurry spreader did not significantly increase the level of soil compactness and reduce sugar beet yield compared to the more common tractor-trailer combination. Soil under conventional ploughing showed more soil compaction, while the effectiveness of reducing tyre inflation pressure as a prevention strategy was lower compared to non-inversion tillage. The tillage practice, however, did not have any overall influence on sugar beet yield.
Optimization Approaches and Techniques for Automotive Alternators: Review Study
Authors: Mahmood Omar Talal , Wan Hasan Wan Zuha , Ismail Luthffi Idzhar , Shafie Suhaidi , Azis Norhafiz , Norsahperi Nor Mohd Haziq
Published: June 2022

Optimization and improvement of the electrical system are applied to cope with the increased demand for electrical power in the vehicular system; they must be carried out in many ways to ensure that the vehicles are provided with the necessary electricity for their performance work electrical equipment. This paper reviews the various optimization approaches for the alternator used in automotive applications and discusses the advantages and disadvantages of each method. The optimization is achieved to the field excitation current that influences the alternator output voltage, and the other techniques designed a controller to optimize the output power of the alternator using power electronic converters. The most suitable approaches are those approaches that use real-time optimization and self-optimization methods. Combining the above two methods can achieve the best results, higher efficiency, stable performance, and a large amount of power produced by the alternator.
Recent Iris and Ocular Recognition Methods in High- and Low-Resolution Images: A Survey
Authors: Lee Young Won , Park Kang Ryoung
Published: June 2022

Among biometrics, iris and ocular recognition systems are the methods that recognize eye features in an image. Such iris and ocular regions must have a certain image resolution to achieve a high recognition performance; otherwise, the risk of performance degradation arises. This is even more critical in the case of iris recognition where detailed patterns are used. In cases where such low-resolution images are acquired and the acquisition apparatus and environment cannot be improved, recognition performance can be enhanced by obtaining high-resolution images with methods such as super-resolution reconstruction. However, previous survey papers have mainly summarized studies on high-resolution iris and ocular recognition, but do not provide detailed summaries of studies on low-resolution iris and ocular recognition. Therefore, we investigated high-resolution iris and ocular recognition methods and introduced in detail the low-resolution iris and ocular recognition methods and methods of solving the low-resolution problem. Furthermore, since existing survey papers have focused on and summarized studies on traditional handcrafted feature-based iris and ocular recognition, this survey paper also introduced the latest deep learning-based methods in detail.
Benchmarking Cost-Effective Opinion Injection Strategies in Complex Networks
Authors: Topîrceanu Alexandru
Published: June 2022

Inferring the diffusion mechanisms in complex networks is of outstanding interest since it enables better prediction and control over information dissemination, rumors, innovation, and even infectious outbreaks. Designing strategies for influence maximization in real-world networks is an ongoing scientific challenge. Current approaches commonly imply an optimal selection of spreaders used to diffuse and indoctrinate neighboring peers, often overlooking realistic limitations of time, space, and budget. Thus, finding trade-offs between a minimal number of influential nodes and maximizing opinion coverage is a relevant scientific problem. Therefore, we study the relationship between specific parameters that influence the effectiveness of opinion diffusion, such as the underlying topology, the number of active spreaders, the periodicity of spreader activity, and the injection strategy. We introduce an original benchmarking methodology by integrating time and cost into an augmented linear threshold model and measure indoctrination expense as a trade-off between the cost of maintaining spreaders’ active and real-time opinion coverage. Simulations show that indoctrination expense increases polynomially with the number of spreaders and linearly with the activity periodicity. In addition, keeping spreaders continuously active instead of periodically activating them can increase expenses by 69–84% in our simulation scenarios. Lastly, we outline a set of general rules for cost-effective opinion injection strategies.
Optimal Control with Partially Observed Regime Switching: Discounted and Average Payoffs
Authors: Escobedo-Trujillo Beatris Adriana , Garrido-Meléndez Javier , Alcalá Gerardo , Revuelta-Acosta J. D.
Published: June 2022

We consider an optimal control problem with the discounted and average payoff. The reward rate (or cost rate) can be unbounded from above and below, and a Markovian switching stochastic differential equation gives the state variable dynamic. Markovian switching is represented by a hidden continuous-time Markov chain that can only be observed in Gaussian white noise. Our general aim is to give conditions for the existence of optimal Markov stationary controls. This fact generalizes the conditions that ensure the existence of optimal control policies for optimal control problems completely observed. We use standard dynamic programming techniques and the method of hidden Markov model filtering to achieve our goals. As applications of our results, we study the discounted linear quadratic regulator (LQR) problem, the ergodic LQR problem for the modeled quarter-car suspension, the average LQR problem for the modeled quarter-car suspension with damp, and an explicit application for an optimal pollution control.
Development and Applications of Augmented Whale Optimization Algorithm
Authors: Alnowibet Khalid Abdulaziz , Shekhawat Shalini , Saxena Akash , Sallam Karam M. , Mohamed Ali Wagdy
Published: June 2022

Metaheuristics are proven solutions for complex optimization problems. Recently, bio-inspired metaheuristics have shown their capabilities for solving complex engineering problems. The Whale Optimization Algorithm is a popular metaheuristic, which is based on the hunting behavior of whale. For some problems, this algorithm suffers from local minima entrapment. To make WOA compatible with a number of challenging problems, two major modifications are proposed in this paper: the first one is opposition-based learning in the initialization phase, while the second is inculcation of Cauchy mutation operator in the position updating phase. The proposed variant is named the Augmented Whale Optimization Algorithm (AWOA) and tested over two benchmark suits, i.e., classical benchmark functions and the latest CEC-2017 benchmark functions for 10 dimension and 30 dimension problems. Various analyses, including convergence property analysis, boxplot analysis and Wilcoxon rank sum test analysis, show that the proposed variant possesses better exploration and exploitation capabilities. Along with this, the application of AWOA has been reported for three real-world problems of various disciplines. The results revealed that the proposed variant exhibits better optimization performance.
An Alternative Approach for Identifying Nonlinear Dynamics of the Cascade Logistic-Cubic System
Authors: Liao Yanan , Yang Kai , Wang Hua , Xiao Qingtai
Published: June 2022

The 0-1 test for chaos, which is a simple binary method, has been widely used to detect the nonlinear behaviors of the non-cascade chaotic dynamics. In this paper, the validity checks of the 0-1 test for chaos to the popular cascade Logistic-Cubic (L-C) system is conducted through exploring the effects of sensitivity parameters. Results show that the periodic, weak-chaotic, and strong-chaotic states of the cascade L-C system can be effectively identified by the introduced simple method for detecting chaos. Nevertheless, the two sensitivity parameters, including the frequency ω and the amplitude α, are critical for the chaos indicator (i.e., the median of asymptotic growth rate, Km) when the cascade dynamic is detected by the method. It is found that the effect of α is more sensitive than that of ω on Km regarding the three dynamical states of the cascade L-C system. Meanwhile, it is recommended that the three states are identified according to the change of K with α from zero to ten since the periodic and weak-chaotic states cannot be identified when the α is greater than a certain constant. In addition, the modified mean square displacement Dc*(n) fails to distinguish its periodic and weak-chaotic states, whereas it can obviously distinguish the above two and strong-chaotic states. This work is therefore invaluable to gaining insight into the understanding of the complex nonlinearity of other different cascade dynamical systems with indicator comparison.
Decomposition of Finitely Additive Markov Chains in Discrete Space
Authors: Zhdanok Alexander , Khuruma Anna
Published: June 2022

In this study, we consider general Markov chains (MC) defined by a transition probability (kernel) that is finitely additive. These Markov chains were constructed by S. Ramakrishnan within the concepts and symbolism of game theory. Here, we study these MCs by using the operator approach. In our work, the state space (phase space) of the MC has any cardinality and the sigma-algebra is discrete. The construction of a phase space allows us to decompose the Markov kernel (and the Markov operators that it generates) into the sum of two components: countably additive and purely finitely additive kernels. We show that the countably additive kernel is atomic. Some properties of Markov operators with a purely finitely additive kernel and their invariant measures are also studied. A class of combined finitely additive MC and two of its subclasses are introduced, and the properties of their invariant measures are proven. Some asymptotic regularities of such MCs were revealed.
Marine Cyclic Peptides: Antimicrobial Activity and Synthetic Strategies
Authors: Ribeiro Ricardo , Pinto Eugénia , Fernandes Carla , Sousa Emília
Published: June 2022

Oceans are a rich source of structurally unique bioactive compounds from the perspective of potential therapeutic agents. Marine peptides are a particularly interesting group of secondary metabolites because of their chemistry and wide range of biological activities. Among them, cyclic peptides exhibit a broad spectrum of antimicrobial activities, including against bacteria, protozoa, fungi, and viruses. Moreover, there are several examples of marine cyclic peptides revealing interesting antimicrobial activities against numerous drug-resistant bacteria and fungi, making these compounds a very promising resource in the search for novel antimicrobial agents to revert multidrug-resistance. This review summarizes 174 marine cyclic peptides with antibacterial, antifungal, antiparasitic, or antiviral properties. These natural products were categorized according to their sources—sponges, mollusks, crustaceans, crabs, marine bacteria, and fungi—and chemical structure—cyclic peptides and depsipeptides. The antimicrobial activities, including against drug-resistant microorganisms, unusual structural characteristics, and hits more advanced in (pre)clinical studies, are highlighted. Nocathiacins I–III (91–93), unnarmicins A (114) and C (115), sclerotides A (160) and B (161), and plitidepsin (174) can be highlighted considering not only their high antimicrobial potency in vitro, but also for their promising in vivo results. Marine cyclic peptides are also interesting models for molecular modifications and/or total synthesis to obtain more potent compounds, with improved properties and in higher quantity. Solid-phase Fmoc- and Boc-protection chemistry is the major synthetic strategy to obtain marine cyclic peptides with antimicrobial properties, and key examples are presented guiding microbiologist and medicinal chemists to the discovery of new antimicrobial drug candidates from marine sources.
Hybrid Pd-Nanoparticles within Polymeric Network in Selective Hydrogenation of Alkynols: Influence of Support Porosity
Authors: Nikoshvili Linda Z. , Popov Alexander Y. , Bykov Alexey V. , Sidorov Alexander I. , Kiwi-Minsker Lioubov
Published: June 2022

This work is addressing the selective hydrogenation of alkynols over hybrid catalysts containing Pd-nanoparticles, within newly synthesized hyper-cross-linked polystyrenes (HPS). Alkynols containing C5, C10, and C20 with a terminal triple bond, which are structural analogues or direct semi-products of fragrant substances and fat-soluble vitamins, have been studied. Selective hydrogenation was carried out in a batch mode (ambient hydrogen pressure, at 90 °C, in toluene solvent), using hybrid Pd catalysts with low metal content (less than 0.2 wt.%). The microporous and mesoporous HPS were both synthesized and used as supports in order to address the influence of porosity. Synthesized catalysts were shown to be active and selective: in the case of C5, hydrogenation selectivity to the target product was more than 95%, at close to complete alkynol conversion. Mesoporous catalysts have shown some advantages in hydrogenation of long-chain alkynols.
Characterizations of Six Pomegranate (Punica granatum L.) Varieties of Global Commercial Interest in Morocco: Pomological, Organoleptic, Chemical and Biochemical Studies
Authors: El Moujahed Sara , Dinica Rodica-Mihaela , Cudalbeanu Mihaela , Avramescu Sorin Marius , Msegued Ayam Iman , Ouazzani Chahdi Fouad , Kandri Rodi Youssef , Errachidi Faouzi
Published: June 2022

Pomegranate variety properties are important not only to demonstrate their diversity but also to satisfy the current market need for high-quality fruits. This study aims to characterize pomological and physico-chemical features as well as the antioxidant capacity of Moroccan local cultivars (Djeibi, Mersi, Sefri 1 and Sefri 2) compared to the imported ones (Mollar de Elche and Hicaz). The pomological characteristics of varieties were relatively diverse. The juice varieties (PJ) displayed a marketed variability in organoleptic and quality properties, such as the flavor, juice yield, and micro/macronutrients contents. Interrelationships among the analyzed properties and PJ varieties were investigated by principal component analysis (PCA). Dimension of the data set was reduced to two components by PCA accounting for 64.53% of the variability observed. The rinds varieties (PR) were studied for their total phenolics, flavonoids, and condensed tannins quantifications. PR varieties extracts exhibited different levels of free radical scavenging activity and local varieties revealed a greater potential with stability over time. The HPLC-DAD analyses of PR extracts revealed (+) catechin as the major compound, where the highest content was found for the local varieties. The SEC analysis showed the molecular weight distribution of phenolic compounds with a high size of condensed tannins formed by the polymerization of the catechin monomer. Given these properties, this research provides an easy selection of high-quality fruits as potential candidates for local market needs.
Indoxyl Sulfate Induces Oxidative Changes in Plasma and Hemolysate
Authors: Pieniazek Anna , Kopera Michal , Gwozdzinski Lukasz , Gwozdzinski Krzysztof
Published: June 2022

The deteriorating function of the kidneys in chronic kidney disease (CKD) is associated, among other things, with the retention of many unnecessary metabolic products in the body. Indoxyl sulfate (IS) belongs to the group of uremic toxins with a high protein binding affinity. Moreover, this compound can generate oxidative stress. We hypothesized that a high concentration of IS might induce oxidative changes in erythrocytes and plasma components, and could therefore contribute to CKD progression. In this study, we evaluated the influence of IS on the oxidative stress parameters in plasma and hemolysate. Moreover, as a result of the action of IS, we observed a decrease in the total antioxidant capacity and a change in the activity of catalase and superoxide dismutase in hemolysate and plasma. The obtained results indicate that IS induces oxidative damage to hemolysate and plasma components. Greater changes in the parameters of oxidative stress were observed in hemolysate than in plasma treated with indoxyl sulfate. The obtained results suggest that the increased concentration of IS in patients with chronic kidney disease may lead to a decrease in the lifespan of erythrocytes in their bloodstream.
On the Traceability of the Hazelnut Production Chain by Means of Trace Elements
Authors: Calà Elisa , Fracchia Andrea , Robotti Elisa , Gulino Federica , Gullo Francesca , Oddone Matteo , Massacane Marco , Cordone Gianluigi , Aceto Maurizio
Published: June 2022

The production chain of hazelnuts has been studied by analyzing three sets of samples produced in purity from three different pools of hazelnuts of cultivar “Tonda Gentile Trilobata”, “Tonda Gentile Romana” and “Mortarella”, all cultivated in Italy. From each pool, five processed products were obtained: roasted hazelnuts, hazelnut paste, hazelnut cream, Gianduja paste and Gianduiotto paste. After pre-treatment by means of dry ashing, all samples from each cultivar, including raw hazelnuts, were then analyzed by means of Inductively Coupled Plasma–Optical Emission Spectroscopy (ICP-OES) and Inductively Coupled Plasma–Mass Spectrometry (ICP-MS). A good discrimination was obtained among the different chain stages according to the distribution of the trace elements, as expected. More interesting was the discrimination among the different cultivars: it was possible to distinguish the samples produced from the respective cultivar by means of specific chemical markers, particularly Mo and Ni.
Elimination of Scintillation Noise Caused by External Environment Disturbances in Open Space
Authors: Tang Qi-Xing , Gao Hua , Zhang Yu-Jun , Chen Dong
Published: June 2022

External environment disturbances in open space cause scintillation noise in tunable diode laser absorption spectroscopy (TDLAS), which is used to detect the concentration of gases in air. However, most gases analyzed by TDLAS are present in trace amounts in air. Thus, useful information is typically submerged in strong noise, thereby reducing the detection accuracy. Herein, a method is proposed to eliminate the scintillation noise caused by external environment disturbances in open space. First, the submerged signal is detected via fast coarse-tuning filtering. Then, scintillation noise is eliminated through the extraction and reconstruction of the main feature information. Thereafter, the background signal is obtained by unequal precision. Furthermore, adaptive iterative fitting is performed. Finally, an experimental setup is established for atmospheric detection in an open optical path. The experimental results show that the COD and RSS fitted using the traditional method are 0.87859 and 1.5772 × 10−5, respectively, and those fitted using the proposed method are 0.91448 and 8.81639 × 10−6, respectively. The field results imply that the proposed method has improved accuracy for detecting trace gases in open space and can be employed for practical engineering applications.
Community- and Data-Driven Services for Multi-Policy Pedestrian Routing
Authors: Damian Ioan , Ionita Anca Daniela , Anton Silvia Oana
Published: June 2022

Pedestrian routing is important in a multitude of public spaces, especially those characterized by a large number of newcomers. Their needs may be diverse, with priority for the shortest path, the less crowded or the less polluted one, the accessibility for reduced mobility, or the sheltering from unfavorable weather conditions. Hence, typical graph-based routing must be enriched to support multiple policies, at the choice of each person. The paper proposes a systemic approach and a set of services for orientation and accessibility, which are both community-driven and data-driven, for correctly perceiving the routing necessities and the surrounding situation. The response time to a pathfinding query depends on the types of policies applied and not only on their number, because each of them contributes to the customization of the weighted graph, although it refers to the same physical space traversed by pedestrians. The paper also presents results of loading tests for up to 5000 Virtual Users, inspired from real-life requirements and executed on a graph that models a real building in our university; different policies are applied to assess performance metrics, with simulated community feedback and sensor data.
Secrecy Capacity Maximization of UAV-Enabled Relaying Systems with 3D Trajectory Design and Resource Allocation
Authors: An Qi , Pan Yu , Han Huizhu , Hu Hang
Published: June 2022

Unmanned aerial vehicles (UAVs) have attracted considerable attention, thanks to their high flexibility, on-demand deployment and the freedom in trajectory design. The communication channel quality can be effectively improved by using UAV to build a line-of-sight communication link between the transmitter and the receiver. Furthermore, there is increasing demand for communication security improvement, as the openness of a wireless channel brings serious threat. This paper formulates a secrecy capacity optimization problem of a UAV-enabled relay communication system in the presence of malicious eavesdroppers, in which the secrecy capacity is maximized by jointly optimizing the UAV relay’s location, power allocation, and bandwidth allocation under the communication quality and information causality constraints. A successive convex approximation–alternative iterative optimization (SCA-AIO) algorithm is proposed to solve this highly coupled nonconvex problem. Simulation results demonstrate the superiority of the proposed secrecy transmission strategy with optimal trajectory design and resource allocation compared with the benchmark schemes and reveal the impacts of communication resources on system performance.
Path Loss Model for 3.5 GHz and 5.6 GHz Bands in Cascaded Tunnel Environments
Authors: Qian Jingyuan , Wu Yating , Saleem Asad , Zheng Guoxin
Published: June 2022

An important and typical scenario of radio propagation in a railway or subway tunnel environment is the cascaded straight and curved tunnel. In this paper, we propose a joint path loss model for cascaded tunnels at 3.5 GHz and 5.6 GHz frequency bands. By combining the waveguide mode theory and the method of shooting and bouncing ray (SBR), it is found that the curvature of tunnels introduces an extra loss in the far-field region, which can be modeled as a linear function of the propagation distance of the signal in the curved tunnel. The channel of the cascaded straight and curved tunnel is thus characterized using the extra loss coefficient (ELC). Based on the ray-tracing (RT) method, an empirical formula between ELC and the radius of the curvature is provided for 3.5 GHz and 5.6 GHz, respectively. Finally, the accuracy of the proposed model is verified by measurement and simulation results. It is shown that the proposed model can predict path loss in cascaded tunnels with desirable accuracy and low complexity.
A Secure Blockchain-Based Authentication and Key Agreement Scheme for 3GPP 5G Networks
Authors: Chow Man Chun , Ma Maode
Published: June 2022

The futuristic fifth-generation cellular network (5G) not only supports high-speed internet, but must also connect a multitude of devices simultaneously without compromising network security. To ensure the security of the network, the Third Generation Partnership Project (3GPP) has standardized the 5G Authentication and Key Agreement (AKA) protocol for mutually authenticating user equipment (UE), base stations, and the core network. However, it has been found that 5G-AKA is vulnerable to many attacks, including linkability attacks, denial-of-service (DoS) attacks, and distributed denial-of-service (DDoS) attacks. To address these security issues and improve the robustness of the 5G network, in this paper, we introduce the Secure Blockchain-based Authentication and Key Agreement for 5G Networks (5GSBA). Using blockchain as a distributed database, our 5GSBA decentralizes authentication functions from a centralized server to all base stations. It can prevent single-point-of-failure and increase the difficulty of DDoS attacks. Moreover, to ensure the data in the blockchain cannot be used for device impersonation, our scheme employs the one-time secret hash function as the device secret key. Furthermore, our 5GSBA can protect device anonymity by mandating the encryption of device identities with Subscription Concealed Identifiers (SUCI). Linkability attacks are also prevented by deprecating the sequence number with Elliptic Curve Diffie–Hellman (ECDH). We use Burrows–Abadi–Needham (BAN) logic and the Scyther tool to formally verify our protocol. The security analysis shows that 5GSBA is superior to 5G-AKA in terms of perfect forward secrecy, device anonymity, and mutual Authentication and Key Agreement (AKA). Additionally, it effectively deters linkability attacks, replay attacks, and most importantly, DoS and DDoS attacks. Finally, the performance evaluation shows that 5GSBA is efficient for both UEs and base stations with reasonably low computational costs and energy consumption.
Wheel Slip Control Applied to an Electric Tractor for Improving Tractive Efficiency and Reducing Energy Consumption
Authors: de Melo Rodnei Regis , Tofoli Fernando Lessa , Daher Sérgio , Antunes Fernando Luiz Marcelo
Published: June 2022

This work presents an automatic slip control solution applied to a two-wheel-drive (2WD) electric tractor. Considering that the slip can be maintained within a specific range that depends on the type of soil, it is possible to increase the tractive efficiency of the electric vehicle (EV). The control system can be easily designed considering only the longitudinal dynamics of the tractor while using simple proportional-integral (PI) controllers to drive the inverters associated with the rear wheels. The introduced solution is tested on an experimental electric tractor prototype traveling on firm soil considering case studies in which the slip control is enabled and disabled. The acquired results demonstrate that the slip control allows for obtaining a more stable performance and reduced energy consumption.
A Combined Near-Infrared and Mid-Infrared Spectroscopic Approach for the Detection and Quantification of Glycine in Human Serum
Authors: Veettil Thulya Chakkumpulakkal Puthan , Wood Bayden R.
Published: June 2022

Serum is an important candidate in proteomics analysis as it potentially carries key markers on health status and disease progression. However, several important diagnostic markers found in the circulatory proteome and the low-molecular-weight (LMW) peptidome have become analytically challenging due to the high dynamic concentration range of the constituent protein/peptide species in serum. Herein, we propose a novel approach to improve the limit of detection (LoD) of LMW amino acids by combining mid-IR (MIR) and near-IR spectroscopic data using glycine as a model LMW analyte. This is the first example of near-IR spectroscopy applied to elucidate the detection limit of LMW components in serum; moreover, it is the first study of its kind to combine mid-infrared (25–2.5 μm) and near-infrared (2500–800 nm) to detect an analyte in serum. First, we evaluated the prediction model performance individually with MIR (ATR-FTIR) and NIR spectroscopic methods using partial least squares regression (PLS-R) analysis. The LoD was found to be 0.26 mg/mL with ATR spectroscopy and 0.22 mg/mL with NIR spectroscopy. Secondly, we examined the ability of combined spectral regions to enhance the detection limit of serum-based LMW amino acids. Supervised extended wavelength PLS-R resulted in a root mean square error of prediction (RMSEP) value of 0.303 mg/mL and R2 value of 0.999 over a concentration range of 0–50 mg/mL for glycine spiked in whole serum. The LoD improved to 0.17 mg/mL from 0.26 mg/mL. Thus, the combination of NIR and mid-IR spectroscopy can improve the limit of detection for an LMW compound in a complex serum matrix.
A New Side-Looking Scheme for Speed Estimation and Detection of Tangential Slow-Moving Targets
Authors: Qi Ziyi , Huang Xiaohong , He Lanpu
Published: June 2022

A single-beam radar system cannot adopt a side-looking installation scheme, which is completely perpendicular to the moving direction of the target in an intelligent transportation system (ITS), because of its own limitations. In this paper, a side-looking radar velocity measurement system that utilizes a new signal processing method and multi-channel radar scheme is proposed. Constant false alarm rate (CFAR) and generalized likelihood ratio test (GLRT) detectors are used to detect the data processing results in different stages in order to reduce the false alarm rate of targets. At the same time, a deconvolution-based clutter map algorithm is proposed to solve the problem of clutter interference in the test environment, and its theoretical performance is verified by simulation. Finally, 77 G commercial radar is used to test the system, and the results show that this algorithm can effectively detect and accurately estimate the speed of tangential low-speed targets under clutter interference.
Analysis of changes in PPP legislation: what consequences are possible for construction?
Authors:   ", Vasilyeva E. Yu. ,   Budget-and-contracted work in construction",   Journal
Published: June 2022

The novelties, proposed for the development of the legislation in the field of pablic-and-private partnership are considered in the article. The most essential novelties as well as the opinions and assumptions of experts in the occasion of their influence on the development of the construction industry are analysed. Some revealed offers on the adjustment and improvement of these amendments are systematized.
Development of green construction in the Russian Federation
Authors:   Moscow State University of Civil Engineering, Bakrunov Yu . O . , Mikhaylova E. A. ,   Moscow State University of Civil Engineering
Published: June 2022

The existing systems of ecological certification are considered in the article. The situation with the implementation of ecological certification of buildings in the Russian Federation is analysed. Special attention is paid to the creation of a domestic system of certification by NOSTROY as the alternative to foreign systems which can become inaccessible because of the geopolitical causes.
Arabic Quran Verses Authentication Using Deep Learning and Word Embeddings
Authors: Touati-Hamad Zineb , Ridda Laouar Mohamed , Bendib Issam , Hakak Saqib
Published: June 2022

Nowadays, with the developments witnessed by the Internet, algorithms have come to control all aspects of digital content. Due to its Arabic roots, it is ironic to find that Arabic Quranic content is still thirsty to benefit from computer linguistics, especially with the advent of artificial intelligence algorithms. The massive spread of Islamic-typed websites and applications has led to a widespread of digital Quranic content. Unfortunately, such content lacks censorship and can rarely match resourcefulness. It is quite difficult, especially for a non-native speaker of the Arabic language, to distinguish and authenticate the provided Quranic verses from the non-Quranic Arabic texts. Text processing techniques classified outside the field of Natural Language Processing (NLP) give less qualified results, especially with Arabic texts. To address this problem, we propose to explore Word Embeddings (WE) with Deep Learning (DL) techniques to identify Quranic verses in Arabic textual content. The proposed work is evaluated using twelve different word embeddings models with two popular classifiers for binary classification, namely: Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM). The experimental results showed the superiority of the proposed approach over traditional methods in distinguishing between the Quranic verses and the Arabic text with an accuracy of 98.33%.
Deux millénaires d’occupations mésolithiques au bord de l’Escaut à Kerkhove (Belgique) : première approche palethnographique
Authors: Vandendriessche Hans , Guéret Colas , Aluwé Kim , Messiaen Liesbeth , Cruz Frédéric , Storme Annelies , Allemeersch Luc , Van Neer Wim , Sergant Joris , Crombe Philippe
Published: June 2022

La fouille récente du gisement alluvial de Kerkhove (Belgique), situé dans la vallée de l’Escaut, à une vingtaine de kilomètres de la frontière française, a permis de mettre au jour 17 locus mésolithiques. D’après les données typochronologiques et les datations absolues, ces locus datent non seulement du Mésolithique ancien, mais aussi du Mésolithique moyen et récent. La première phase d’occupation de la levée alluviale, datée du 11e et 10e millénaire avant le présent (cal BP), a clairement été la plus intensive. Elle correspond à un Mésolithique ancien caractérisé par des assemblages du « groupe de Chinru », dominés par les triangles et les pointes à base retouchée. La deuxième phase d’occupation, celle du Mésolithique moyen, compte trois locus et est caractérisée par de nombreuses lamelles étroites à bord abattu, et des pointes à retouche couvrante d’une part, et par une exploitation de matières premières siliceuses différentes d’autre part. La dernière phase d’occupation date du Mésolithique récent. Elle est représentée par un seul locus qui a livré de nombreux artefacts en grès-quartzite de Wommersom, quelques trapèzes et des lamelles plus régulières. Le principal intérêt du site de Kerkhove est la possibilité d’étudier tous les aspects de l’industrie lithique, mais également l’exploitation des matières premières siliceuses et des autres ressources naturelles dans une large perspective diachronique. En effet, hors vestiges lithiques, des quantités considérables de coquilles de noisettes carbonisées et de restes fauniques ont été récupérées. En plus de la présence d’ossements brûlés, des restes fauniques non brûlés sont également conservés, situation inédite pour le Mésolithique ancien, moyen et récent du nord de la Belgique. Ainsi, les ossements de sanglier et de chevreuil dominent les assemblages du Mésolithique ancien et sont associés à des restes d’animaux à fourrures, tandis que les contextes du Mésolithique moyen livrent des indices fréquents de consommation de poissons sur le site.