bluuebunny/crossref_metadata_2025 huggingface dataset:
Leaf Gas Exchange and Growth Responses of Tomato Plants to External Flavonoids Application as Biostimulators under Normal and Salt-Stressed Conditions
Authors: Martinez-Alonso Alberto , Garcia-Ibañez Paula , Bárzana Gloria , Carvajal Micaela
Published: December 2022

The exogenous application of natural metabolites, such as phenolic compounds, is a useful strategy to stimulate growth and reduce the adverse effects of abiotic stress on crops, such as salinity. Salinity stress is one of the most damaging abiotic stresses to plants, causing reductions in growth by changes in the physiology, biochemistry, and gene expression. In this work, we investigated the effect of the foliar application of flavonoids (CropBioLife, CBL) on control and salt-stressed (NaCl 60 mM) tomato plants grown in controlled conditions. The results showed that CBL mainly influenced the stimulation of photosynthesis, increasing CO2 fixation and promoting growth. Furthermore, a higher stomata number in an open state was found in CBL-treated plants in relation to the higher CO2 fixation, which also resulted in a higher H2O uptake due to increasing stomatal conductance and nutrient uptake that plants need for growth. The results were due to the increase of phenolic metabolism and the expression of most of the aquaporins, which could be the triggering signal for the rest to the changes observed. The effect of the biostimulation of CBL under salinity was related to higher levels of photosynthesis, the increase of some mineral nutrients, and the increase of some PIP aquaporins expression, although no effect on growth was observed. The results of this work showing the mechanism of action of flavonoids in tomato plants open a new line of investigation with great importance for the future of agronomy.
Transposable Element Tissue-Specific Response to Temperature Stress in the Stenothermal Fish Puntius tetrazona
Authors: Carotti Elisa , Carducci Federica , Canapa Adriana , Barucca Marco , Biscotti Maria Assunta
Published: December 2022

Ray-finned fish represent a very interesting group of vertebrates comprising a variety of organisms living in different aquatic environments worldwide. In the case of stenothermal fish, thermal fluctuations are poorly tolerated, thus ambient temperature represents a critical factor. In this paper, we considered the tiger barb Puntius tetrazona, a freshwater fish belonging to the family Cyprinidae, living at 21–28 °C. We analyzed the available RNA-Seq data obtained from specimens exposed at 27 °C and 13 °C to investigate the transcriptional activity of transposable elements (TEs) and genes encoding for proteins involved in their silencing in the brain, gill, and liver. TEs are one of the tools generating genetic variability that underlies biological evolution, useful for organisms to adapt to environmental changes. Our findings highlighted a different response of TEs in the three analyzed tissues. While in the brain and gill, no variation in TE transcriptional activity was observed, a remarkable increase at 13 °C was recorded in the liver. Moreover, the transcriptional analysis of genes encoding proteins involved in TE silencing such as heterochromatin formation, the NuRD complex, and the RISC complex (e.g., AGO and GW182 proteins) highlighted their activity in the hepatic tissue. Overall, our findings suggested that this tissue is a target organ for this kind of stress, since TE activation might regulate the expression of stress-induced genes, leading to a better response of the organism to temperature changes. Therefore, this view corroborates once again the idea of a potential role of TEs in organism rapid adaptation, hence representing a promising molecular tool for species resilience.
Trialling Locally Made, Low-Cost Bits to Improve Bit-Related Welfare Problems in Cart Horses: Findings from a Study in Senegal
Authors: Seck Mactar , Jobling Ruth , Brown Ashleigh F.
Published: December 2022

Bits used for cart horses in Senegal are typically made of recovered construction iron and often have defects related to design, shape, fit and metal quality. Consequently, there is widespread presence of bit-related oral injury amongst these equids. It was hypothesised that improving bit design would ameliorate bit-related welfare issues for working cart horses. This study aimed to develop locally made alternative bit prototypes and test their efficacy as less harmful to working horses, and their acceptability to their drivers. Eight animal-based welfare indicators (four physical and four behavioural) were designed to measure positive or negative effects of the new bits. Following a testing phase to appraise and mitigate potential animal welfare risk associated with the alternative bit designs, a total of 540 driver/horse combinations were opportunistically selected across five municipalities in Senegal. Welfare indicators were observed when new bits were introduced and again after 21 weeks of daily use. The results indicated statistically significant improvements in all welfare indicators measured (i.e., lesions on lip commissures, tongue, buccal mucosa and bars; and open mouth, tongue loll, head toss/shake, and head tilt/turn behaviours). None of the drivers reported any difficulty with horse control, nor chose to revert back to their original bits. Whilst acknowledging the limitation of inability to control all potential confounding variables, these preliminary findings suggest the bit itself as an important contributor to oral injury, and the possibility to improve this through alternative bit design that is low-cost, locally produced and acceptable to drivers.
Gene Expression Profiles of the Immuno-Transcriptome in Equine Asthma
Authors: Padoan Elisa , Ferraresso Serena , Pegolo Sara , Barnini Carlo , Castagnaro Massimo , Bargelloni Luca
Published: December 2022

Background: Mild equine asthma (MEA) and severe equine asthma (SEA) are two of the most frequent equine airway inflammatory diseases, but knowledge about their pathogenesis is limited. The goal of this study was to investigate gene expression differences in the respiratory tract of MEA- and SEA-affected horses and their relationship with clinical signs. Methods: Clinical examination and endoscopy were performed in 8 SEA- and 10 MEA-affected horses and 7 healthy controls. Cytological and microbiological analyses of bronchoalveolar lavage (BAL) fluid were performed. Gene expression profiling of BAL fluid was performed by means of a custom oligo-DNA microarray. Results: In both MEA and SEA, genes involved in the genesis, length, and motility of respiratory epithelium cilia were downregulated. In MEA, a significant overexpression for genes encoding inflammatory mediators was observed. In SEA, transcripts involved in bronchoconstriction, apoptosis, and hypoxia pathways were significantly upregulated, while genes involved in the formation of the protective muco-protein film were underexpressed. The SEA group also showed enrichment of gene networks activated during human asthma. Conclusions: The present study provides new insight into equine asthma pathogenesis, representing the first step in transcriptomic analysis to improve diagnostic and therapeutic approaches for this respiratory disease.
In Vitro Probiotic Characterization and Safety Assessment of Lactic Acid Bacteria Isolated from Raw Milk of Japanese-Saanen Goat (Capra hircus)
Authors: Tanaka Yukimune , Aryantini Ni Putu Desy , Yamasaki Eiki , Saito Makoto , Tsukigase Yui , Nakatsuka Hirotaka , Urashima Tadasu , Horiuchi Risa , Fukuda Kenji
Published: December 2022

Two novel probiotic strains of lactic acid bacteria were successfully isolated from the raw milk of dairy Japanese-Saanen goats. Selection criteria for positive candidates were grown on de Man–Rogosa–Sharpe or M17 selective medium at 30, 35, or 42 °C anaerobically, and characterized based on Gram reaction, catalase test, and tolerance to low pH and bile salts. Among the 101 isolated positive candidates, two strains, YM2-1 and YM2-3, were selected and identified as Lacticaseibacillus rhamnosus using 16S rDNA sequence similarity. Culture supernatants of the two strains exhibited antipathogenic activity against Salmonella enterica subsp. enterica serovar. Typhimurium, Shigella sonnei, methicillin-resistant Staphylococcus aureus, methicillin-sensitive Staphylococcus aureus, Listeria monocytogenes, and Escherichia coli O157. The antipathogenic activities were retained to some extent after neutralization, indicating the presence of antipathogenic substances other than organic acids in the culture supernatants. The two strains were sensitive with coincidental minimum inhibition concentrations (indicated in the parentheses hereafter) to ampicillin (0.25 μg/mL), chloramphenicol (4 μg/mL), gentamycin (4 μg/mL), kanamycin (64 μg/mL), streptomycin (16 μg/mL), and tetracycline (4 μg/mL). Furthermore, the two strains were resistant to clindamycin (16 μg/mL) and erythromycin (4 μg/mL). In addition, both YM2-1 and YM2-3 strains showed less unfavorable activities, including bile acid bioconversion, carcinogenic-related enzymes, mucin degradation, plasminogen activation, and hemolysis, than the detection limits of in vitro evaluation methods used in this study. In summary, L. rhamnosus YM2-1 and YM2-3 are highly safe and promising probiotic strains applicable in the dairy industry, and were first isolated from the raw milk of Japanese-Saanen goats.
NMR-Based Characterization of Citrus Tacle Juice and Low-Level NMR and UV—Vis Data Fusion for Monitoring Its Fractions from Membrane-Based Operations
Authors: Gaglianò Martina , De Luca Giuseppina , Conidi Carmela , Cassano Alfredo
Published: December 2022

Tacle is a citrus variety which recently gained further interest due to its antioxidant and biological properties. This study suggests using Nuclear Magnetic Resonance (NMR) imaging to characterize Tacle juice’s metabolic composition as it is intimately linked to its quality. First, polar and apolar solvent systems were used to identify a significant fraction of the Tacle metabolome. Furthermore, the antioxidant capacity and the total content of flavonoids, polyphenols and β-carotene in the juice were investigated with UV—Visible spectroscopy. Tacle juice was clarified and fractionated by ultrafiltration (UF) and nanofiltration (NF) membranes in order to recover and purify its bioactive principles. Finally, the second part of this work sheds light on the spectrophotometric assays and 1H-NMR spectra of fractions coming from membrane operations coupled with a multivariate data analysis technique, PCA, to explore the impact of UF and NF processes on the metabolic profile of the juice.
Optimization of the Cutting Parameters Affecting the Turning of AISI 52100 Bearing Steel Using the Box-Behnken Experimental Design Method
Authors: Yıldız Aytaç , Uğur Levent , Parlak İsmail Enes
Published: December 2022

In this study, we aimed to optimize the cutting parameters that affect the minimum temperature and power consumption in the turning of AISI 52100 bearing steel. For this, the Box-Behnken experimental design method, which was used for the lowest number of experiments in the experimental systems created using the response surface method (RSM), was used. The cutting parameters affecting the turning of the AISI 52100 bearing steel were determined as the cutting speed, depth of cut, and feed rate based on a literature research. The temperature and power consumption values were obtained via analyses according to the experimental design method determined by the finite element analysis (FEM) method. The results obtained were analyzed in Design Expert 13 software. According to the analysis results, the parameter values were determined for the minimum temperature and power consumption. The temperature and power consumption variables were affected by all three parameters, namely the cutting speed, depth of cut, and feed rate. For the minimum temperature and power consumption, a cutting speed of 162.427 m/min, depth of cut of 1.395 mm, and feed rate of 0.247 mm/rev, as well as the feed rate parameters, affected both the temperature and power consumption the most. In addition, it was determined that the cutting speed parameter had the least effect on both the temperature and power consumption variables. In addition, validation experiments were carried out in a real experimental environment with optimum values for the cutting parameters. The results showed that the output values obtained within the limits of the study with the obtained equation were quite close (3.3% error for temperature, 6.6% error for power consumption) to the real experimental outputs.
M-Healthcare Model: An Architecture for a Type 2 Diabetes Mellitus Mobile Application
Authors: Joshua Salaki Reynaldo , Abbas Wasim , Lee Je-Hoon
Published: December 2022

Type 2 diabetes mellitus (T2DM) is a metabolic disorder wherein the patients require DM management to keep their blood glucose under proper and regular control. Diabetes mellitus can be managed with the help of technologies, one of which is mobile health. Mobile health is an innovation in telemedicine that utilizes gadgets as a medium to access digitally based health information and services by utilizing electronic devices connected to the Internet. Mobile health services are distinguished based on interactions between users and medical personnel; namely, interactive and non-interactive services. The developed application can integrate Android mobile application software with supporting hardware, such as a glucometer, a wearable band, a heart rate sensor, a treadmill, and an exercise bike. The provided features in this mobile application include the monitoring of medication, food intake, exercise, and sleep. This study’s goal was to create a mobile application architecture for type 2 diabetes mellitus mobile applications. This research focused on developing an architecture for mobile diabetes applications, a hardware block diagram design, and an architecture of sensors for a type 2 diabetes mellitus mobile application.
Energy Retrofit Optimization by Means of Genetic Algorithms as an Answer to Fuel Poverty Mitigation in Social Housing Buildings
Authors: Ciardiello Adriana , Dell’Olmo Jacopo , Ferrero Marco , Pastore Lorenzo Mario , Rosso Federica , Salata Ferdinando
Published: December 2022

In accordance with national regulations, the renovation of the residential sector is an urgent task for achieving significant reductions in energy consumption and CO2 emissions of the existing building stock. Social housing is particularly in need of such interventions, given the higher vulnerability of its inhabitants and its crucial role in furthering social welfare and environmental sustainability objectives. Both passive and active strategies have proved their efficacy in advancing towards these goals and also in mitigating increasing fuel poverty in low-income families. However, to optimize the best combination of such retrofit strategies, advanced optimization methodologies can be applied. Here, a multi-objective optimization methodology is implemented by a genetic algorithm (aNSGA-II) coupled to EnergyPlus dynamic energy simulations. Then, the energy consumption of the optimal solution is considered by means of EnergyPLAN simulations for the further application of active strategies. The two-step method is tested on a relevant case study, a social housing building in Rome, Italy. Results show that the applied method reduced the energy demand by 51% with passive strategies only. Active strategy implementation allowed for a further reduction of 69% in CO2 emissions and 51% in energy costs. The two-step method proved effective in mitigating fuel poverty and decarbonizing the residential sector.
Can We Structure Biomaterials to Spray Well Whilst Maintaining Functionality?
Authors: Moakes Richard J. A. , Grover Liam M. , Robinson Thomas E.
Published: December 2022

Structured fluid biomaterials, including gels, creams, emulsions and particle suspensions, are used extensively across many industries, including great interest within the medical field as controlled release vehicles to improve the therapeutic benefit of delivered drugs and cells. Colloidal forces within these materials create multiscale cohesive interactions, giving rise to intricate microstructures and physical properties, exemplified by increasingly complex mathematical descriptions. Yield stresses and viscoelasticity, typically arising through the material microstructure, vastly improve site-specific retention, and protect valuable therapeutics during application. One powerful application route is spraying, a convenient delivery method capable of applying a thin layer of material over geometrically uneven surfaces and hard-to-reach anatomical locations. The process of spraying is inherently disruptive, breaking a bulk fluid in successive steps into smaller elements, applying multiple forces over several length scales. Historically, spray research has focused on simple, inviscid solutions and dispersions, far from the complex microstructures and highly viscoelastic properties of concentrated colloidal biomaterials. The cohesive forces in colloidal biomaterials appear to conflict with the disruptive forces that occur during spraying. This review explores the physical bass and mathematical models of both the multifarious material properties engineered into structured fluid biomaterials and the disruptive forces imparted during the spray process, in order to elucidate the challenges and identify opportunities for rational design of sprayable, structured fluid biomaterials.
Inactivation of Yes-Associated Protein Mediates Trophoblast Dysfunction: A New Mechanism of Pregnancy Loss Associated with Anti-Phospholipid Antibodies?
Authors: Huang Zengshu , Tang Zhijing , Guan Haiyun , Leung Wingting , Wang Lu , Xia Hexia , Zhang Wei
Published: December 2022

Pregnancy morbidity induced by anti-phospholipid antibodies (aPL+/PM+) is mainly thought to arise from placental abnormalities. We attempted to investigate the effect of aPL on the activity of Yes-associated protein (YAP) in the trophoblast and how YAP regulated human trophoblasts function. Thus, HTR-8 cells were treated with IgG purified from aPL+/PM+ women or normal controls. We found that aPL+/PM+ IgG impacted YAP activity via abrogating YAP expression. Further investigation of the anti-β2GPI-IgG/β2GPI complex showed an inhibition of nuclear YAP level and translocation in a dose-dependent manner, which might be rescued by progesterone in HTR-8 cells. YAP overexpression or knockdown HTR-8 cells were established for the evaluation of cell function and related gene expression in vitro. Loss of YAP arrested cell cycles in the G2/M phase, accelerated cell apoptosis by increasing the ratio of Bax/Bcl2, and disrupted MMP2/9-mediated cell migration and angiogenesis tube formation by VEGF. These findings support a new mechanism of PM associated with aPL through which YAP inactivation induced by aPL perturbs the trophoblast cell cycle, apoptosis, migration, and angiogenesis, finally developing into pregnancy failure.
Cognition and Neuropsychological Changes at Altitude—A Systematic Review of Literature
Authors: Bliemsrieder Kathrin , Weiss Elisabeth Margarete , Fischer Rainald , Brugger Hermann , Sperner-Unterweger Barbara , Hüfner Katharina
Published: December 2022

High-altitude (HA) exposure affects cognitive functions, but studies have found inconsistent results. The aim of this systematic review was to evaluate the effects of HA exposure on cognitive functions in healthy subjects. A structural overview of the applied neuropsychological tests was provided with a classification of superordinate cognitive domains. A literature search was performed using PubMed up to October 2021 according to PRISMA guidelines. Eligibility criteria included a healthy human cohort exposed to altitude in the field (at minimum 2440 m [8000 ft]) or in a hypoxic environment in a laboratory, and an assessment of cognitive domains. The literature search identified 52 studies (29 of these were field studies; altitude range: 2440 m–8848 m [8000–29,029 ft]). Researchers applied 112 different neuropsychological tests. Attentional capacity, concentration, and executive functions were the most frequently studied. In the laboratory, the ratio of altitude-induced impairments (64.7%) was twice as high compared to results showing no change or improved results (35.3%), but altitudes studied were similar in the chamber compared to field studies. In the field, the opposite results were found (66.4 % no change or improvements, 33.6% impairments). Since better acclimatization can be assumed in the field studies, the findings support the hypothesis that sufficient acclimatization has beneficial effects on cognitive functions at HA. However, it also becomes apparent that research in this area would benefit most if a consensus could be reached on a standardized framework of freely available neurocognitive tests.
Smart Polymeric Micelles for Anticancer Hydrophobic Drugs
Authors: Guzmán Rodríguez Andy , Sablón Carrazana Marquiza , Rodríguez Tanty Chrislayne , Malessy Martijn J. A. , Fuentes Gastón , Cruz Luis J.
Published: December 2022

Cancer has become one of the deadliest diseases in our society. Surgery accompanied by subsequent chemotherapy is the treatment most used to prolong or save the patient’s life. Still, it carries secondary risks such as infections and thrombosis and causes cytotoxic effects in healthy tissues. Using nanocarriers such as smart polymer micelles is a promising alternative to avoid or minimize these problems. These nanostructured systems will be able to encapsulate hydrophilic and hydrophobic drugs through modified copolymers with various functional groups such as carboxyls, amines, hydroxyls, etc. The release of the drug occurs due to the structural degradation of these copolymers when they are subjected to endogenous (pH, redox reactions, and enzymatic activity) and exogenous (temperature, ultrasound, light, magnetic and electric field) stimuli. We did a systematic review of the efficacy of smart polymeric micelles as nanocarriers for anticancer drugs (doxorubicin, paclitaxel, docetaxel, lapatinib, cisplatin, adriamycin, and curcumin). For this reason, we evaluate the influence of the synthesis methods and the physicochemical properties of these systems that subsequently allow an effective encapsulation and release of the drug. On the other hand, we demonstrate how computational chemistry will enable us to guide and optimize the design of these micelles to carry out better experimental work.
Family-, School-, and Neighborhood-Level Predictors of Resilience for Adolescents with a History of Maltreatment
Authors: Chang Yujeong , Yoon Susan , Maguire-Jack Kathryn , Lee Jihye
Published: December 2022

Child maltreatment is a well-known risk factor that threatens the well-being and positive development of adolescents, yet protective factors can help promote resilience amid adversity. The current study sought to identify factors at the family, school, and neighborhood levels associated with resilience outcomes including positive functioning and social skills, among adolescents who have experienced maltreatment. Using longitudinal data from the Fragile Families and Child Wellbeing Study, the analytic sample was limited to 1729 adolescents who experienced maltreatment before age 9. Family-, school-, and neighborhood-level predictors were assessed at age 9, and youth resilience was measured at age 15. We conducted a series of multiple regression analyses to examine multi-level protective factors at age 9 as predictors of positive adolescent functioning and social skills at age 15. The study found that mothers’ involvement was significantly and positively associated with positive adolescent functioning and social skills. Additionally, school connectedness and neighborhood social cohesion were significantly associated with higher levels of adolescent social skills. Our findings suggest that positive environmental contexts such as maternal involvement in parenting, school connectedness, and socially cohesive neighborhoods can serve as important protective factors that promote resilient development among adolescents who have experienced maltreatment as children.
Growth of Pentacene-Doped p-Terphenyl Crystals Using SSVBT and Doping Effects in p-Terphenyl Molecular Crystals
Authors: Ai Qing , Chen Peifeng , Xu Yebin , Zhang Lei
Published: December 2022

High-quality pentacene-doped p-terphenyl bulk crystals were grown by the selective self-seeding vertical Bridgman technique (SSVBT). The lattice structure and crystal properties of the samples of different doping concentrations and their relations with p-terphenyl single crystals were tested and analyzed. The doping effects of pentacene doping at different concentrations in p-terphenyl molecular crystals are discussed. The powder X-ray diffraction, FTIR, and 1H NMR studies show that no additional peaks (except for p-terphenyl) are observed in the spectra of two doped crystals. The results indicate that guest molecules appear as defects in the form of irregularly oriented molecules which do not significantly change the crystal structures. As the doping concentration increases, the average crystallite size decreases, and the crystallinity declines. The ultraviolet–visible absorption and fluorescence spectra show that with added pentacene molecules, the characteristic peak intensities decrease in the spectra owing to the p-terphenyl molecular transition. Meanwhile, characteristic peaks appear due to the pentacene molecular transition. Moreover, with the increase of doping concentration, the intensities of characteristic peaks of host molecules decrease continuously, and those of guest molecules increase accordingly.
Machine Learning Predictive Model as Clinical Decision Support System in Orthodontic Treatment Planning
Authors: Prasad Jahnavi , Mallikarjunaiah Dharma , Shetty Akshai , Gandedkar Narayan , Chikkamuniswamy Amarnath , Shivashankar Prashanth
Published: December 2022

Diagnosis and treatment planning forms the crux of orthodontics, which orthodontists gain with years of expertise. Machine Learning (ML), having the ability to learn by pattern recognition, can gain this expertise in a very short duration, ensuring reduced error, inter–intra clinician variability and good accuracy. Thus, the aim of this study was to construct an ML predictive model to predict a broader outline of the orthodontic diagnosis and treatment plan. The sample consisted of 700 case records of orthodontically treated patients in the past ten years. The data were split into a training and a test set. There were 33 input variables and 11 output variables. Four ML predictive model layers with seven algorithms were created. The test set was used to check the efficacy of the ML-predicted treatment plan and compared with that of the decision made by the expert orthodontists. The model showed an overall average accuracy of 84%, with the Decision Tree, Random Forest and XGB classifier algorithms showing the highest accuracy ranging from 87–93%. Yet in their infancy stages, Machine Learning models could become a valuable Clinical Decision Support System in orthodontic diagnosis and treatment planning in the future.
Zhongshan HF Radar Elevation Calibration Based on Ground Backscatter Echoes
Authors: Jiang Weijie , Liu Erxiao , Kong Xing , Shi Shengsheng , Liu Jianjun
Published: December 2022

The super dual auroral radar network (SuperDARN) is an important tool in the remote sensing of ionospheric potential convection in middle and high latitudes, and also a major source of elevation data detection. A reliable elevation angle helps estimate the propagation paths of high-frequency radio signals between scattering spots and radars, which is crucial for determining high-frequency radar target geolocation. The SuperDARN radar uses interferometry to estimate the elevation of the returned signal. However, elevation data are still underutilized owing to the difficulties of phase difference calibration induced by the propagation time delay between two arrays. This paper statistically analyzes the distribution features of the group range-elevation angle and group range-virtual height before and after calibration using elevation data from the ground backscatter echoes of the Zhongshan SuperDARN radar, calculating the root mean square error (RMSE) of the virtual height; the results show that the RMSE after calibration is mostly reduced to within 54% of that before calibration. Furthermore, we validate the calibration factor based on the primary phase data. The data from 2013 to 2015 indicate that this technique can be efficiently used to estimate the daily calibration factor. Finally, we present the statistical distribution of the calibration factor, which provides technical support for the calibration of elevation data in the future.
Spectral Efficiency of Precoded 5G-NR in Single and Multi-User Scenarios under Imperfect Channel Knowledge: A Comprehensive Guide for Implementation
Authors: Urquiza Villalonga David Alejandro , OdetAlla Hatem , Fernández-Getino García M. Julia , Flizikowski Adam
Published: December 2022

Digital precoding techniques have been widely applied in multiple-input multiple-output (MIMO) systems to enhance spectral efficiency (SE) which is crucial in 5G New Radio (NR). Therefore, the 3rd Generation Partnership Project (3GPP) has developed codebook-based MIMO precoding strategies to achieve a good trade-off between performance, complexity, and signal overhead. This paper aims to evaluate the performance bounds in SE achieved by the 5G-NR precoding matrices in single-user (SU) and multi-user (MU) MIMO systems, namely Type I and Type II, respectively. The implementation of these codebooks is covered providing a comprehensive guide with a detailed analysis. The performance of the 5G-NR precoder is compared with theoretical precoding techniques such as singular value decomposition (SVD) and block-diagonalization to quantify the margin of improvement of the standardized methods. Several configurations of antenna arrays, number of antenna ports, and parallel data streams are considered for simulations. Moreover, the effect of channel estimation errors on the system performance is analyzed in both SU and MU-MIMO cases. For a realistic framework, the SE values are obtained for a practical deployment based on a clustered delay line (CDL) channel model. These results provide valuable insights for system designers about the implementation and performance of the 5G-NR precoding matrices.
A Multilayered Audio Signal Encryption Approach for Secure Voice Communication
Authors: Abdallah Hanaa A. , Meshoul Souham
Published: December 2022

In this paper, multilayer cryptosystems for encrypting audio communications are proposed. These cryptosystems combine audio signals with other active concealing signals, such as speech signals, by continuously fusing the audio signal with a speech signal without silent periods. The goal of these cryptosystems is to prevent unauthorized parties from listening to encrypted audio communications. Preprocessing is performed on both the speech signal and the audio signal before they are combined, as this is necessary to get the signals ready for fusion. Instead of encoding and decoding methods, the cryptosystems rely on the values of audio samples, which allows for saving time while increasing their resistance to hackers and environments with a noisy background. The main feature of the proposed approach is to consider three levels of encryption namely fusion, substitution, and permutation where various combinations are considered. The resulting cryptosystems are compared to the one-dimensional logistic map-based encryption techniques and other state-of-the-art methods. The performance of the suggested cryptosystems is evaluated by the use of the histogram, structural similarity index, signal-to-noise ratio (SNR), log-likelihood ratio, spectrum distortion, and correlation coefficient in simulated testing. A comparative analysis in relation to the encryption of logistic maps is given. This research demonstrates that increasing the level of encryption results in increased security. It is obvious that the proposed salting-based encryption method and the multilayer DCT/DST cryptosystem offer better levels of security as they attain the lowest SNR values, −25 dB and −2.5 dB, respectively. In terms of the used evaluation metrics, the proposed multilayer cryptosystem achieved the best results in discrete cosine transform and discrete sine transform, demonstrating a very promising performance.
Accurate State of Charge Estimation for Real-World Battery Systems Using a Novel Grid Search and Cross Validated Optimised LSTM Neural Network
Authors: Hong Jichao , Liang Fengwei , Gong Xun , Xu Xiaoming , Yu Quanqing
Published: December 2022

State of charge (SOC) is one of the most important parameters in battery management systems, and the accurate and stable estimation of battery SOC for real-world electric vehicles remains a great challenge. This paper proposes a long short-term memory network based on grid search and cross-validation optimisation to estimate the SOC of real-world battery systems. The real-world electric vehicle data are divided into parking charging, travel charging, and finish charging cases. Meanwhile, the parameters associated with the SOC estimation under each operating condition are extracted by the Pearson correlation analysis. Moreover, the hyperparameters of the long short-term memory network are optimised by grid search and cross-validation to improve the accuracy of the model estimation. Moreover, the gaussian noise algorithm is used for data augmentation to improve the accuracy and robustness of SOC estimation under the working conditions of the small dataset. The results indicate that the absolute error of SOC estimation is within 4% for the small dataset and within 2% for the large dataset. More importantly, the robustness and effectiveness of the proposed method are validated based on operational data from three different real-world electric vehicles, and the mean square error of SOC estimation does not exceed 0.006. This paper aims to provide guidance for the SOC estimation of real-world electric vehicles.
Floating Offshore Wind Turbines: Current Status and Future Prospects
Authors: Barooni Mohammad , Ashuri Turaj , Velioglu Sogut Deniz , Wood Stephen , Ghaderpour Taleghani Shiva
Published: December 2022

Offshore wind energy is a sustainable renewable energy source that is acquired by harnessing the force of the wind offshore, where the absence of obstructions allows the wind to travel at higher and more steady speeds. Offshore wind has recently grown in popularity because wind energy is more powerful offshore than on land. Prior to the development of floating structures, wind turbines could not be deployed in particularly deep or complicated seabed locations since they were dependent on fixed structures. With the advent of floating structures, which are moored to the seabed using flexible anchors, chains, or steel cables, wind turbines can now be placed far offshore. The deployment of floating wind turbines in deep waters is encouraged by several benefits, including steadier winds, less visual impact, and flexible acoustic noise requirements. A thorough understanding of the physics underlying the dynamic response of the floating offshore wind turbines, as well as various design principles and analysis methods, is necessary to fully compete with traditional energy sources such as fossil fuels. The present work offers a comprehensive review of the most recent state-of-the-art developments in the offshore wind turbine technology, including aerodynamics, hydromechanics, mooring, ice, and inertial loads. The existing design concepts and numerical models used to simulate the complex wind turbine dynamics are also presented, and their capabilities and limitations are discussed in detail.
Embedding-Graph-Neural-Network for Transient NOx Emissions Prediction
Authors: Chen Yun , Liang Chengwei , Liu Dengcheng , Niu Qingren , Miao Xinke , Dong Guangyu , Li Liguang , Liao Shanbin , Ni Xiaoci , Huang Xiaobo
Published: December 2022

Recently, Acritical Intelligent (AI) methodologies such as Long and Short-term Memory (LSTM) have been widely considered promising tools for engine performance calibration, especially for engine emission performance prediction and optimization, and Transformer is also gradually applied to sequence prediction. To carry out high-precision engine control and calibration, predicting long time step emission sequences is required. However, LSTM has the problem of gradient disappearance on too long input and output sequences, and Transformer cannot reflect the dynamic features of historic emission information which derives from cycle-by-cycle engine combustion events, which leads to low accuracy and weak algorithm adaptability due to the inherent limitations of the encoder-decoder structure. In this paper, considering the highly nonlinear relation between the multi-dimensional engine operating parameters the engine emission data outputs, an Embedding-Graph-Neural-Network (EGNN) model was developed combined with self-attention mechanism for the adaptive graph generation part of the GNN to capture the relationship between the sequences, improve the ability of predicting long time step sequences, and reduce the number of parameters to simplify network structure. Then, a sensor embedding method was adopted to make the model adapt to the data characteristics of different sensors, so as to reduce the impact of experimental hardware on prediction accuracy. The experimental results show that under the condition of long-time step forecasting, the prediction error of our model decreased by 31.04% on average compared with five other baseline models, which demonstrates the EGNN model can potentially be used in future engine calibration procedures.
Categorisation of Biogas Plant Operators in Germany with Regards to Their Intention to Use Straw Pellets as Innovative and Sustainable Substrate Alternative
Authors: Mohrmann Sören , Otter Verena
Published: December 2022

The cultivation of renewable raw materials on arable land is challenged by the ongoing fuel-versus-food debate resulting from increases in maize cultivation, shorter crop rotations and land competition. Accordingly, the current legal framework for biogas production in Germany focuses on limiting cultivation of traditional biogas substrates, such as silage maize, and promoting the use of various alternatives, such as waste materials and by-products. One new sustainable substrate alternative is the use of cereal straw compacted to pellets. Although straw pellets generally have good fermentation properties, they are still rarely used in German biogas production. Since earlier research on agricultural production practices in general has shown that farmers can be divided into groups regarding their acceptance behaviour and the speed to successfully adopt innovative practices and technologies on their farm, this study addresses the research question: How can biogas plant operators in Germany be categorised with regards to their intention to use straw pellets as innovative and sustainable substrate alternatives? In order to answer this question an exploratory factor analysis and subsequent hierarchical cluster analysis was conducted with survey data obtained from German biogas plant operators (n = 309) in early 2021. Based on variables indicating the intention to use and use behaviour regarding straw pellets in biogas plants, four clusters are identified. Plant operator’s innovativeness, perceived risk and the influence of social environment show differences between the clusters. Additionally, the characteristics of the innovation “straw pellets”, such as economic performance and sustainability, were assessed differently by the four clusters of German biogas plant operators. While the clusters do not show significant differences in the socio-demographic characteristics, they do so in the farm characteristics (farm activities besides biogas production, size of the plant, the proportion of slurry/dung and silage maize). According to the results two of the four clusters have a higher acceptance of straw pellets, which also means that they are earlier in considering the actual use. The initiation of regional working groups, information campaigns and financial incentives can support plant operators, especially in the two clusters of potential early adopters, in accepting straw pellets. This should ultimately result in a faster and wider use of straw pellets as substrates in the whole biogas sector.
Improved Secure Encryption with Energy Optimization Using Random Permutation Pseudo Algorithm Based on Internet of Thing in Wireless Sensor Networks
Authors: Nagaraj S. , Kathole Atul B. , Arya Leena , Tyagi Neha , Goyal S. B. , Rajawat Anand Singh , Raboaca Maria Simona , Mihaltan Traian Candin , Verma Chaman , Suciu George
Published: December 2022

The use of wireless and Internet of Things (IoT) devices is growing rapidly. Because of this expansion, nowadays, mobile apps are integrated into low-cost, low-power platforms. Low-power, inexpensive sensor nodes are used to facilitate this integration. Given that they self-organize, these systems qualify as IoT-based wireless sensor networks. WSNs have gained tremendous popularity in recent years, but they are also subject to security breaches from multiple entities. WSNs pose various challenges, such as the possibility of numerous attacks, their innate power, and their unfeasibility for use in standard security solutions. In this paper, to overcome these issues, we propose the secure encryption random permutation pseudo algorithm (SERPPA) for achieving network security and energy consumption. SERPPA contains a major entity known as a cluster head responsible for backing up and monitoring the activities of the nodes in the network. The proposed work performance is compared with other work based on secure IoT devices. The calculation metrics taken for consideration are energy, overheads, computation cost, and time consumption. The obtained results show that the proposed SERPPA is very significant in comparison to the existing works, such as GKA (Group Key Agreement) and MPKE (Multipath Key Establishment), in terms of data transfer rate, energy consumption and throughput.
A Comprehensive Review of Variability in the Thermal Resistance (D-Values) of Food-Borne Pathogens—A Challenge for Thermal Validation Trials
Authors: Soni Aswathi , Bremer Phil , Brightwell Gale
Published: December 2022

The thermal processing of food relies heavily on determining the right time and temperature regime required to inactivate bacterial contaminants to an acceptable limit. To design a thermal processing regime with an accurate time and temperature combination, the D-values of targeted microorganisms are either referred to or estimated. The D-value is the time required at a given temperature to reduce the bacterial population by 90%. The D-value can vary depending on various factors such as the food matrix, the bacterial strain, and the conditions it has previously been exposed to; the intrinsic properties of the food (moisture, water activity, fat content, and pH); the method used to expose the microorganism to the thermal treatment either at the laboratory or commercial scale; the approach used to estimate the number of survivors; and the statistical model used for the analysis of the data. This review focused on Bacillus cereus, Cronobacter sakazakii, Escherichia coli, Listeria monocytogenes, and Clostridium perfringens owing to their pathogenicity and the availability of publications on their thermal resistance. The literature indicates a significant variation in D-values reported for the same strain, and it is concluded that when designing thermal processing regimes, the impact of multiple factors on the D-values of a specific microorganism needs to be considered. Further, owing to the complexity of the interactions involved, the effectiveness of regimes derived laboratory data must be confirmed within industrial food processing settings.
Microbiome-Metabolomics Insights into the Milk of Lactating Dairy Cows to Reveal the Health-Promoting Effects of Dietary Citrus Peel Extracts on the Mammary Metabolism
Authors: Zhao Yuchao , Yu Shiqiang , Zhang Shuyue , Li Yuqin , Tu Yan , Liu Ming , Jiang Linshu
Published: December 2022

The effects of dietary supplementation with citrus peel extract (CPE) on milk biochemical parameters, milk bacterial community, and milk metabolites were evaluated. Eight lactating cows were allocated to a replicated 4 × 4 Latin square. Experimental treatments included the control diet (CON), and CON supplemented with CPE at 50 g/d (CPE50), 100 g/d (CPE100), and 150 g/d (CPE150). Supplementing with CPE linearly decreased milk interleukin-6 and malondialdehyde concentrations and linearly increased lysozyme activity and 1,1-diphenyl-2-picrylhydrazyl radical scavenging activity. Compared with CON, the milk of CPE150 cows had fewer abundances of several opportunistic pathogens and psychrotrophic bacteria, such as Escherichia-Shigella, Sphingobacterium, Alcaligenes, Stenotrophomonas, and Ochrobactrum. Supplementing with CPE significantly altered the metabolic profiling in the milk. The metabolites of flavonoids were enriched in the milk of cows fed CPE150, while some proinflammation compounds were decreased compared with CON. Correlation analysis showed that the change in the bacterial community might partly contribute to the alteration in the expression of milk cytokines. In conclusion, CPE exerts health-promoting effects (e.g., antioxidant, anti-microbial, and anti-inflammatory) in the mammary metabolism of cows due to its flavonoid compounds, which also provide additional value in terms of milk quality improvement.
Consumer Attitudes and Acceptability of Wheat Pancakes with the Addition of Edible Insects: Mealworm (Tenebrio molitor), Buffalo Worm (Alphitobius diaperinus), and Cricket (Acheta domesticus)
Authors: Mazurek Aleksandra , Palka Agnieszka , Skotnicka Magdalena , Kowalski Stanisław
Published: December 2022

The aim of this study was to determine the degree of acceptability of wheat pancakes with the addition of 10%, 20%, and 30% meal from three edible insect species (Alphitobius diaperinus, Tenebrio molitor, Acheta domesticus, respectively). Both consumer attitudes and the acceptability of the test samples were analysed. The study results show that the amount of additive had a statistically significant effect on all of the organoleptic evaluation’s distinguishing features, while the type of additive did not have such a significant effect on the level of consumer acceptability. Both the type and amount of the additive only had a statistically significant effect on the structure of the pancakes. Of all the variants, the sample with the addition of 30% crickets (Pref-2.51) was given the lowest score. An increase in the insect meal content of the products resulted in decreased scores for all the parameters under assessment. The key element that influenced the overall preference was the flavour. Even though the respondents declared positive attitudes towards the idea of consuming pancakes with the addition of insects and entomophagy in general, they were still reluctant to include insects in their diets.
Choosing the Best Members of the Optimal Eighth-Order Petković’s Family by Its Fractal Behavior
Authors: Wang Xiaofeng , Li Wenshuo
Published: December 2022

In this paper, by applying Petković’s iterative method to the Möbius conjugate mapping of a quadratic polynomial function, we attain an optimal eighth-order rational operator with a single parameter r and research the stability of this method by using complex dynamics tools on the basis of fractal theory. Through analyzing the stability of the fixed point and drawing the parameter space related to the critical point, the parameter family which can make the behavior of the corresponding iterative method stable or unstable is obtained. Lastly, the consequence is verified by showing their corresponding dynamical planes.