bluuebunny/crossref_metadata_2025 huggingface dataset:
The Generation of Human iPSC Lines from Three Individuals with Dravet Syndrome and Characterization of Neural Differentiation Markers in iPSC-Derived Ventral Forebrain Organoid Model
Authors: Zayat Valery , Kuczynska Zuzanna , Liput Michal , Metin Erkan , Rzonca-Niewczas Sylwia , Smyk Marta , Mazurczak Tomasz , Goszczanska-Ciuchta Alicja , Leszczynski Pawel , Hoffman-Zacharska Dorota , Buzanska Leonora
Published: January 2023

Dravet syndrome (DRVT) is a rare form of neurodevelopmental disorder with a high risk of sudden unexpected death in epilepsy (SUDEP), caused mainly (>80% cases) by mutations in the SCN1A gene, coding the Nav1.1 protein (alfa-subunit of voltage-sensitive sodium channel). Mutations in SCN1A are linked to heterogenous epileptic phenotypes of various types, severity, and patient prognosis. Here we generated iPSC lines from fibroblasts obtained from three individuals affected with DRVT carrying distinct mutations in the SCN1A gene (nonsense mutation p.Ser1516*, missense mutation p.Arg1596His, and splicing mutation c.2589+2dupT). The iPSC lines, generated with the non-integrative approach, retained the distinct SCN1A gene mutation of the donor fibroblasts and were characterized by confirming the expression of the pluripotency markers, the three-germ layer differentiation potential, the absence of exogenous vector expression, and a normal karyotype. The generated iPSC lines were used to establish ventral forebrain organoids, the most affected type of neurons in the pathology of DRVT. The DRVT organoid model will provide an additional resource for deciphering the pathology behind Nav1.1 haploinsufficiency and drug screening to remediate the functional deficits associated with the disease.
Derivation of the Immortalized Cell Line UM51-PrePodo-hTERT and Its Responsiveness to Angiotensin II and Activation of the RAAS Pathway
Authors: Erichsen Lars , Kloss Lea Doris Friedel , Thimm Chantelle , Bohndorf Martina , Schichel Kira , Wruck Wasco , Adjaye James
Published: January 2023

Recent demographic studies predict there will be a considerable increase in the number of elderly people within the next few decades. Aging has been recognized as one of the main risk factors for the world’s most prevalent diseases such as neurodegenerative disorders, cancer, cardiovascular disease, and metabolic diseases. During the process of aging, a gradual loss of tissue volume and organ function is observed, which is partially caused by replicative senescence. The capacity of cellular proliferation and replicative senescence is tightly regulated by their telomere length. When telomere length is critically shortened with progressive cell division, cells become proliferatively arrested, and DNA damage response and cellular senescence are triggered, whereupon the “Hayflick limit” is attained at this stage. Podocytes are a cell type found in the kidney glomerulus where they have major roles in blood filtration. Mature podocytes are terminal differentiated cells that are unable to undergo cell division in vivo. For this reason, the establishment of primary podocyte cell cultures has been very challenging. In our present study, we present the successful immortalization of a human podocyte progenitor cell line, of which the primary cells were isolated directly from the urine of a 51-year-old male. The immortalized cell line was cultured over the course of one year (~100 passages) with high proliferation capacity, endowed with contact inhibition and P53 expression. Furthermore, by immunofluorescence-based expression and quantitative real-time PCR for the podocyte markers CD2AP, LMX1B, NPHS1, SYNPO and WT1, we confirmed the differentiation capacity of the immortalized cells. Finally, we evaluated and confirmed the responsiveness of the immortalized cells on the main mediator angiotensin II (ANGII) of the renin–angiotensin system (RAAS). In conclusion, we have shown that it is possible to bypass cellular replicative senescence (Hayflick limit) by TERT-driven immortalization of human urine-derived pre-podocyte cells from a 51-year-old African male.
Copper Death Inducer, FDX1, as a Prognostic Biomarker Reshaping Tumor Immunity in Clear Cell Renal Cell Carcinoma
Authors: Jiang Aimin , Ye Juelan , Zhou Ye , Zhu Baohua , Lu Juan , Ge Silun , Qu Le , Xiao Jianru , Wang Linhui , Cai Chen
Published: January 2023

Background: Progress in the diagnosis and treatment of clear cell renal cell carcinoma (ccRCC) has significantly prolonged patient survival. However, ccRCC displays an extreme heterogenous characteristic and metastatic tendency, which limit the benefit of targeted or immune therapy. Thus, identifying novel biomarkers and therapeutic targets for ccRCC is of great importance. Method: Pan cancer datasets, including the expression profile, DNA methylation, copy number variation, and single nucleic variation, were introduced to decode the aberrance of copper death regulators (CDRs). Then, FDX1 was systematically analyzed in ccRCC to evaluate its impact on clinical characteristics, prognosis, biological function, immune infiltration, and therapy response. Finally, in vivo experiments were utilized to decipher FDX1 in ccRCC malignancy and its role in tumor immunity. Result: Copper death regulators were identified at the pancancer level, especially in ccRCC. FDX1 played a protective role in ccRCC, and its expression level was significantly decreased in tumor tissues, which might be regulated via CNV events. At the molecular mechanism level, FDX1 positively regulated fatty acid metabolism and oxidative phosphorylation. In addition, FDX1 overexpression restrained ccRCC cell line malignancy and enhanced tumor immunity by increasing the secretion levels of IL2 and TNFγ. Conclusions: Our research illustrated the role of FDX1 in ccRCC patients’ clinical outcomes and its impact on tumor immunity, which could be treated as a promising target for ccRCC patients.
Renewable Polymers Derived from Limonene
Authors: Lyubushkin Roman Aleksandrovich , Cherkashina Natalia Igorevna , Pushkarskaya Dar’ya Vasil’yevna , Matveenko Dar’ya Sergeyevna , Shcherbakov Alexander Sergeevich , Ryzhkova Yuliya Sergeevna
Published: January 2023

Renewable natural and synthetic basic substances can be used to produce biodegradable polymers. Several methods of the polymerization of terpene limonene have been evaluated. The polymerization methods evaluated are radical polymerization, cationic polymerization and thiol-ene polymerization. The free-radical polymerization of limonene with azobisisobutyronitrile (AIBN) as an initiator was carried out. The cationic polymerization of limonene was carried out using AlCl3 as a catalyst. The copolymerization of limonene with mercaptoethanol, 2-mercaptoethyl ether without an initiator and with an AIBN initiator was studied and it was also shown that polymerization can proceed spontaneously. The resulting compounds were investigated by NMR and FTIR spectroscopy. The values of the molecular weight characteristics of the samples obtained are presented, such as: number-average molecular weight, hydrodynamic radius and characteristic viscosity, depending on the method of production. The coefficients α (molecular shape) in the Mark–Kuhn–Houwink equation are determined according to the established values of the characteristic viscosity. According to the values obtained, the AC molecules in solution have parameters α 0.14 to 0.26, which corresponds to a good solvent and the molecular shape-dense coil.
Applying of C8-BTBT-Based EGOFETs at Different pH Values of the Electrolyte
Authors: Shaposhnik Polina A. , Poimanova Elena Y. , Abramov Anton A. , Trul Askold A. , Anisimov Daniil S. , Kretova Elena A. , Agina Elena V. , Ponomarenko Sergey A.
Published: January 2023

Electrolyte-gated organic field-effect transistors (EGOFETs) is a popular platform for numerous sensing and biosensing applications in aqueous media. In this work, the variation of electrical characteristics of EGOFETs based on small-molecule organic semiconductor C8-BTBT and polystyrene blend in water solutions at different pH values was investigated. A positive shift of the threshold voltage with near-Nernstian pH sensitivity was demonstrated in the pH range from 4.9 to 2.8, while no measurable pH dependence in the range from 4.9 to 8.6 pH was registered. These results indicate chemical doping of the molecules of organic semiconductors by protons from the electrolyte in the acidic region. In order to check the applicability of the EGOFETs in a flow mode, a flow chamber was designed and assembled. The preliminary results obtained in the flow mode measurements showed a fast response to pH variation.
Pregnant Women’s Attitudes and Beliefs towards Sleep and Exercise: A Cross-Sectional Survey
Authors: Cannon Summer , Hayman Melanie , Lastella Michele
Published: January 2023

As many as 80% of women report experiencing poor sleep throughout pregnancy. Exercise is associated with many health benefits during pregnancy and is established as a non-pharmacological method to improve sleep in both pregnant and non-pregnant populations. Given the importance of sleep and exercise during pregnancy, the aim of this cross-sectional study was to (1) examine pregnant women’s attitudes and beliefs towards sleep and exercise during pregnancy, and (2) investigate the barriers women face to achieving good sleep and engaging in healthy levels of exercise. Participants were comprised of 258 pregnant Australian women (31.3 ± 5.1 years) who completed a 51-question online survey. Almost all (98%) participants believed exercise during pregnancy to be safe, whilst over half (67%) believed participating in more exercise will improve their sleep. Over 70% of participants reported experiencing barriers such as physical symptoms related to pregnancy that negatively impacted their ability to exercise. Almost all (95%) participants reported experiencing barriers to sleep in their current pregnancy. Present findings suggest that overcoming intrapersonal barriers should be a priority for any intervention aiming to improve sleep or increase exercise levels in pregnant populations. Findings from the present study highlight the need for a better understanding of women’s sleep experiences during pregnancy, and demonstrate how exercise may improve sleep and health outcomes.
Statistical Study of the Effectiveness of Surface Application of Graphene Oxide as a Coating for Concrete Protection
Authors: Antolín-Rodríguez Andrea , Merino-Maldonado Daniel , Rodríguez-González Álvaro , Fernández-Raga María , González-Domínguez José Miguel , Juan-Valdés Andrés , García-González Julia
Published: January 2023

Improving the protection of concrete by applying graphene oxide (GO) as a surface treatment has become the objective of the present study. This study focuses on performing a statistical analysis to study different levels of GO application as an exterior coating, thus observing the effectiveness of the coating and the optimization of the treatment material for concrete protection. Four tests were performed to define concrete durability, such as pressurized water penetration, capillary absorption, freeze-thaw resistance and carbonation resistance. The results showed an increase in concrete durability with any level of GO application on the surface, considering that the optimum amount of application for water impermeability and freeze-thaw resistance is 26.2 µg/cm2, since it was possible to reduce pressurized water penetration by 45%, capillary water absorption by 57% and freeze-thaw detachment by 25%. However, the optimum application rate for carbonation resistance is 52.4 µg/cm2, reducing carbonation by almost 60%. In conclusion, if the concrete is going to be exposed to less aggressive environments, the application of a mild surface coating of GO is sufficient for its protection, and if the concrete is going to be exposed to more aggressive environments, it is necessary to increase the amount of GO. The performance of GO as a coating significantly increased the degree of protection of the concrete, increasing its service life and proving to be a promising treatment for concrete surface protection.
The Initial Development and Evaluation of Cross-Linked Casein Films for Sustainable Footwear
Authors: Indrie Liliana , McNeil Steven , Mutlu Mehmet Mete , Bota Sanda , Ilieș Dorina Camelia , Karavana Hüseyin Ata
Published: January 2023

To increase the sustainability of footwear and align it with the circular bioeconomy, there is a pressing need to develop novel bio-based materials to replace the synthetic polymers currently used. In this study, casein-based films were prepared by solution casting with a tannic acid cross-linker, and a glycerol plasticizer. The properties important to footwear materials were characterised, including tensile strength and elongation, stitch strength, hardness, grain cracking strength, water vapour permeability, and thermal properties. The tannic acid imparted a brown colour to the films with good resistance to light-induced fading. Their tensile strengths were 4–5 N/mm2, elongation at break 45%–73%, and water vapour permeability 0.2–0.6 mg/(cm2h), depending upon the levels of the cross-linker and plasticiser. The strength of the films was close to those of some non-leather footwear materials such as compact rubbers and insock materials, but below that required for leather shoe vamps/uppers. The casein films were successfully used in sneaker- and ballerina-style shoes as components of the insock and decorative design elements on the vamp. This work has demonstrated the concept of using casein films in footwear. The properties of the films could be improved by further research, particularly with respect to cross-linking, plasticizing, and combining with bio-based fibers and fabrics.
Preparation of Hydrophobic Monolithic Supermacroporous Cryogel Particles for the Separation of Stabilized Oil-in-Water Emulsion
Authors: Takase Hayato , Watanabe Nozomi , Shiomori Koichiro , Okamoto Yukihiro , Ciptawati Endang , Matsune Hideki , Umakoshi Hiroshi
Published: January 2023

Here, we prepared hydrophobic cryogel particles with monolithic supermacropores based on poly-trimethylolpropane trimethacrylate (pTrim) by combining the inverse Leidenfrost effect and cryo-polymerization technique. The hydrophobic cryogel particles prepared by adopting this method demonstrated the separation of the stabilized O/W emulsion with surfactant. The prepared cryogel particles were characterized in terms of macroscopic shape and porous structure. It was found that the cryogel particles had a narrow size distribution and a monolithic supermacroporous structure. The hydrophobicity of the cryogel particles was confirmed by placing aqueous and organic droplets on the particles. Where the organic droplet was immediately adsorbed into the particles, the aqueous droplet remained on the surface of the particle due to repelling force. In addition, after it adsorbed the organic droplet the particle was observed, and the organic solvent was diffused into the entire particle. It was indicated that monolithic pores were distributed from the surface to the interior. Regarding the application of the hydrophobic cryogel particles, we demonstrated the separation of a stabilized oil-in-water emulsion, resulting in the successful removal of the organic solvent from the emulsion.
Impact of Nesting Mode, Diet, and Taxonomy in Structuring the Associated Microbial Communities of Amazonian Ants
Authors: Chanson Anaïs , Moreau Corrie S. , Duplais Christophe
Published: January 2023

Studies of ant biodiversity are important to understand their group better, as well as to extend our knowledge on the evolution of their associated organisms. Host-associated microbial communities, and particularly bacterial communities, are shaped by different host factors such as habitat, diet, and phylogeny. Here, we studied the structures of bacterial and microbial eukaryote communities associated with Amazonian ants collected from two habitats: the rainforest and the city. We collected 38 ant species covering a large taxonomic range, and we used 16S rRNA and 18S rRNA amplicon sequencing to study the impact of the host’s ecological and phylogenetic factors on their microbial communities. Our results show that (1) habitat does not structure ant microbial communities, (2) ant diet and nesting mode impact bacterial communities, while only nesting mode structures microbial eukaryote communities, and (3) microbial diversity is not correlated with host phylogeny, although several ant genera have conserved bacterial communities. As we continue to uncover the diversity and function of insect-associated microbes, this work explores how host ecology and evolutionary history shape ant microbial communities.
The Importance of Including Spatial Autocorrelation When Modelling Species Richness in Archipelagos: A Bayesian Approach
Authors: Barros Diogo Duarte , Mathias Maria da Luz , Borges Paulo A. V. , Borda-de-Água Luís
Published: January 2023

One of the aims of island biogeography theory is to explain the number of species in an archipelago. Traditionally, the variables used to explain the species richness on an island are its area and distance to the mainland. However, increasing evidence suggests that accounting for other variables is essential for better estimates. In particular, the distance between islands should play a role in determining species richness. This work uses a Bayesian framework using Gaussian processes to assess whether distance to neighbouring islands (spatial autocorrelation) can better explain arthropod species richness patterns in the Azores Archipelago and in the Canary Islands. This method is flexible and allows the inclusion of other variables, such as maximum altitude above sea level (elevation). The results show that accounting for spatial autocorrelation provides the best results for both archipelagos, but overall, spatial autocorrelation seems to be more important in the Canary archipelago. Similarly, elevation plays a more important role in determining species richness in the Canary Islands. We recommend that spatial autocorrelation should always be considered when modelling an archipelago’s species richness.
Application of the AT(N) and Other CSF Classification Systems in Behavioral Variant Frontotemporal Dementia
Authors: Constantinides Vasilios C. , Boufidou Fotini , Bourbouli Mara , Pyrgelis Efstratios-Stylianos , Ghika Apostolia , Koros Christos , Liakakis George , Papageorgiou Sokratis , Stefanis Leonidas , Paraskevas George P. , Kapaki Elisabeth
Published: January 2023

Background: Patients with a frontotemporal lobar degeneration (FTLD) usually manifest with behavioral variant frontotemporal dementia (bvFTD). Alzheimer’s disease (AD) may also manifest with a predominant behavioral-dysexecutive syndrome, similar to bvFTD. Cerebrospinal fluid (CSF) biomarkers, such as total tau (τT), phosphorylated tau (τP-181) and amyloid beta with 42 amino-acids (Aβ42), can predict AD pathology in vivo. The aim of this study was to compare the τT/Aβ42 and τP-181/Aβ42 ratios, the BIOMARKAPD/ABSI criteria and the AT(N) classification system in a cohort of bvFTD patients. Methods: A total of 105 bvFTD patients (21 possible bvFTD; 20%) with CSF data, examined from 2008 to 2022, were included. Seventy-eight AD patients and 62 control subjects were included. The CSF biomarkers were measured with Innotest (2008–2017 subcohort) and EUROIMMUN (2017–2022 subcohort) ELISAs. Results: Depending on the classification system, 7.6 to 28.6% of bvFTD had an AD biochemical profile. The τT/Aβ42 and τP-181/Aβ42 ratios classified more patients as AD compared to the BIOMARKAPD/ABSI and AT(N) systems. The patients with possible bvFTD had higher frequencies of AD compared to the probable bvFTD patients. Conclusions: The four classification criteria of CSF AD biomarkers resulted in differences in AD allocation in this bvFTD cohort. A consensus on the optimal classification criteria of CSF AD biomarkers is pivotal.
Serum S100B Levels in Patients with Liver Cirrhosis and Hepatic Encephalopathy
Authors: Kim Mo-Jong , Kim Jung-Hee , Jung Jang-Han , Kim Sung-Eun , Kim Hyoung-Su , Jang Myoung-Kuk , Park Sang-Hoon , Lee Myung-Seok , Suk Ki , Kim Dong , Choi Eun-Kyoung , Park Ji-Won
Published: January 2023

Hepatic encephalopathy (HE) is one of the main complications of liver cirrhosis (LC) and is classified into minimal hepatic encephalopathy (MHE) and overt hepatic encephalopathy (overt HE). S100B is expressed mainly in astrocytes and other glial cells, and S100B has been reported to be associated with various neurological disorders. The present study aimed to investigate the diagnostic ability of serum S100B to discriminate the grade of HE and the parameters correlated with serum S100B levels. Additionally, we investigated whether serum S100B levels can be used to predict 1-year mortality in cirrhotic patients. In total, 95 cirrhotic patients were consecutively enrolled and divided into the following three groups: (i) without any types of HEs; (ii) with MHE; and (iii) with overt HE. The diagnosis of MHE was made by the Mini-Mental State Examination (MMSE) and Psychometric Hepatic Encephalopathy Score (PHES). Among the three groups, there were no significant differences in serum S100B levels regardless of HE severity. The clinical parameters correlated with serum S100B levels were age, serum bilirubin, and creatinine levels. The Model for End-Stage Liver Disease (MELD) score showed a significant positive correlation with serum S100B levels. The relationship between serum S100B levels and MELD score was maintained in 48 patients without any type of HE. Additionally, hyperammonemia, low cholesterol levels, and the combination of serum S100B levels ≥ 35 pg/mL with MELD score ≥ 13 were factors for predicting 1- year mortality. In conclusion, serum S100B level was not useful for differentiating the severity of HE. However, we found that serum S100B levels can be affected by age, serum bilirubin, and creatinine in cirrhotic patients and are associated with MELD scores. Additionally, serum S100B levels showed the possibility of predicting 1-year mortality in cirrhotic patients. These findings suggest that serum S100B levels may reflect liver dysfunction and prognosis in liver disease.
Multimodal Few-Shot Target Detection Based on Uncertainty Analysis in Time-Series Images
Authors: Khoshboresh-Masouleh Mehdi , Shah-Hosseini Reza
Published: January 2023

The ability to interpret multimodal data, and map the targets and anomalies within, is important for an automatic recognition system. Due to the expensive and time-consuming nature of multimodal time-series data annotation in the training stage, multimodal time-series image understanding, from drone and quadruped mobile robot platforms, is a challenging task for remote sensing and photogrammetry. In this regard, robust methods must be computationally low-cost, due to the limited data on aerial and ground-based platforms, yet accurate enough to meet certainty measures. In this study, a few-shot learning architecture, based on a squeeze-and-attention structure, is proposed for multimodal target detection, using time-series images from the drone and quadruped robot platforms with a small training dataset. To build robust algorithms in target detection, a squeeze-and-attention structure has been developed from multimodal time-series images from limited training data as an optimized method. The proposed architecture was validated on three datasets with multiple modalities (e.g., red-green-blue, color-infrared, and thermal), achieving competitive results.
Towards More Efficient Rényi Entropy Estimation
Authors: Skorski Maciej
Published: January 2023

Estimation of Rényi entropy is of fundamental importance to many applications in cryptography, statistical inference, and machine learning. This paper aims to improve the existing estimators with regard to: (a) the sample size, (b) the estimator adaptiveness, and (c) the simplicity of the analyses. The contribution is a novel analysis of the generalized “birthday paradox” collision estimator. The analysis is simpler than in prior works, gives clear formulas, and strengthens existing bounds. The improved bounds are used to develop an adaptive estimation technique that outperforms previous methods, particularly in regimes of low or moderate entropy. Last but not least, to demonstrate that the developed techniques are of broader interest, a number of applications concerning theoretical and practical properties of “birthday estimators” are discussed.
Tracking Control for Output Probability Density Function of Stochastic Systems Using FPD Method
Authors: Yang Yi , Zhang Yong , Zhou Yuyang
Published: January 2023

Output probability density function (PDF) tracking control of stochastic systems has always been a challenging problem in both theoretical development and engineering practice. Focused on this challenge, this work proposes a novel stochastic control framework so that the output PDF can track a given time-varying PDF. Firstly, the output PDF is characterised by the weight dynamics following the B-spline model approximation. As a result, the PDF tracking problem is transferred to a state tracking problem for weight dynamics. In addition, the model error of the weight dynamics is described by the multiplicative noises to more effectively establish its stochastic dynamics. Moreover, to better reflect the practical applications in the real world, the given tracking target is set to be time-varying rather than static. Thus, an extended fully probabilistic design (FPD) is developed based on the conventional FPD to handle multiplicative noises and to track the time-varying references in a superior way. Finally, the proposed control framework is verified by a numerical example, and a comparison simulation with the linear–quadratic regulator (LQR) method is also included to illustrate the superiority of our proposed framework.
A Novel Framework for Classification of Different Alzheimer’s Disease Stages Using CNN Model
Authors: Mohi ud din dar Gowhar , Bhagat Avinash , Ansarullah Syed Immamul , Othman Mohamed Tahar Ben , Hamid Yasir , Alkahtani Hend Khalid , Ullah Inam , Hamam Habib
Published: January 2023

Background: Alzheimer’s, the predominant formof dementia, is a neurodegenerative brain disorder with no known cure. With the lack of innovative findings to diagnose and treat Alzheimer’s, the number of middle-aged people with dementia is estimated to hike nearly to 13 million by the end of 2050. The estimated cost of Alzheimer’s and other related ailments is USD321 billion in 2022 and can rise above USD1 trillion by the end of 2050. Therefore, the early prediction of such diseases using computer-aided systems is a topic of considerable interest and substantial study among scholars. The major objective is to develop a comprehensive framework for the earliest onset and categorization of different phases of Alzheimer’s. Methods: Experimental work of this novel approach is performed by implementing neural networks (CNN) on MRI image datasets. Five classes of Alzheimer’s disease subjects are multi-classified. We used the transfer learning determinant to reap the benefits of pre-trained health data classification models such as the MobileNet. Results: For the evaluation and comparison of the proposed model, various performance metrics are used. The test results reveal that the CNN architectures method has the following characteristics: appropriate simple structures that mitigate computational burden, memory usage, and overfitting, as well as offering maintainable time. The MobileNet pre-trained model has been fine-tuned and has achieved 96.6 percent accuracy for multi-class AD stage classifications. Other models, such as VGG16 and ResNet50 models, are applied tothe same dataset whileconducting this research, and it is revealed that this model yields better results than other models. Conclusion: The study develops a novel framework for the identification of different AD stages. The main advantage of this novel approach is the creation of lightweight neural networks. MobileNet model is mostly used for mobile applications and was rarely used for medical image analysis; hence, we implemented this model for disease detection andyieldedbetter results than existing models.
Detecting Browser Drive-By Exploits in Images Using Deep Learning
Authors: Iglesias Patricia , Sicilia Miguel-Angel , García-Barriocanal Elena
Published: January 2023

Steganography is the set of techniques aiming to hide information in messages as images. Recently, stenographic techniques have been combined with polyglot attacks to deliver exploits in Web browsers. Machine learning approaches have been proposed in previous works as a solution for detecting stenography in images, but the specifics of hiding exploit code have not been systematically addressed to date. This paper proposes the use of deep learning methods for such detection, accounting for the specifics of the situation in which the images and the malicious content are delivered using Spatial and Frequency Domain Steganography algorithms. The methods were evaluated by using benchmark image databases with collections of JavaScript exploits, for different density levels and steganographic techniques in images. A convolutional neural network was built to classify the infected images with a validation accuracy around 98.61% and a validation AUC score of 99.75%.
Research on Laboratory Test Method of Wave Energy Converter Wave-Wire Conversion Ratio in Irregular Waves
Authors: Shangguan Liang , Lu Kuan , Wang Huamei
Published: January 2023

The laboratory test of the wave energy converter model is an important means to evaluate the performance of the device. At present, there are few performance tests for complete specifications under the irregular wave. Referring to the test methods and standards at home and abroad, combined with the actual test work experience in the laboratory, using the irregular wave power calculation formula with the effective wave height and the spectral peak period as parameters, then the wave-wire conversion ratio test method of the wave energy converter physical model under irregular waves in the laboratory is proposed. The method is applied to the basin test experiment of the physical model of the horn-shaped backward bent duct buoy (BBDB) wave energy converter. The research results show that the established test method and process of wave-wire conversion performance have achieved good application results in the irregular waves laboratory test, and can better reflect the device operating characteristics in real sea conditions. The test results provide data support for the model design of the wave energy converter in the next test stage, the demonstration test of the prototype, and the prediction of power generation in real sea conditions.
Investigation of the Splashing Characteristics of Lead Slag in Side-Blown Bath Melting Process
Authors: Zou Quan , Hu Jianhang , Yang Shiliang , Wang Hua , Deng Ge
Published: January 2023

Aiming at the melt splashing behavior in the smelting process of an oxygen-enriched side-blowing furnace, the volume of fluid model and the realizable k−ε turbulence model are coupled and simulated. The effects of different operating parameters (injection velocity, immersion depth, liquid level) on splash height are explored, and the simulation results are verified by water model experiments. The results show that the bubbles with residual kinetic energy escape to the slag surface and cause slag splashing. The slag splashing height gradually increases with the increase in injection velocity, and the time-averaged splashing height reaches 1.01 m when the injection speed is 160 m/s. Increasing the immersion depth of the lance, and the slag splashing height gradually decreases. When the immersion depth is 0.12 m, the time-averaged splashing height is 0.85 m. Increasing the liquid level is beneficial to reduce the splash height, when the liquid level is 2.7 m, the splash height reduces to 0.77 m. With the increase in the liquid level, the slag splashing height gradually decreases, and the time-averaged splashing height is 0.77 m when the initial liquid level is 2.7 m.
A Surrogate-Assisted Adaptive Bat Algorithm for Large-Scale Economic Dispatch
Authors: Pang Aokang , Liang Huijun , Lin Chenhao , Yao Lei
Published: January 2023

Large-scale grids have gradually become the dominant trend in power systems, which has increased the importance of solving the challenges associated with large-scale economic dispatch (LED). An increase in the number of decision variables enlarges the search-space scale in LED. In addition to increasing the difficulty of solving algorithms, huge amounts of computing resources are consumed. To overcome this problem, we proposed a surrogate-assisted adaptive bat algorithm (GARCBA). On the one hand, to reduce the execution time of LED problems, we proposed a generalized regression neural network surrogate model based on a self-adaptive “minimizing the predictor” sampling strategy, which replaces the original fuel cost functions with a shorter computing time. On the other hand, we also proposed an improved hybrid bat algorithm (RCBA) named GARCBA to execute LED optimization problems. Specifically, we developed an evolutionary state evaluation (ESE) method to increase the performance of the original RCBA. Moreover, we introduced the ESE to analyze the population distribution, fitness, and effective radius of the random black hole in the original RCBA. We achieved a substantial improvement in computational time, accuracy, and convergence when using the GARCBA to solve LED problems, and we demonstrated this method’s effectiveness with three sets of simulations.
A Review on Modeling Variable Renewable Energy: Complementarity and Spatial–Temporal Dependence
Authors: Iung Anderson Mitterhofer , Cyrino Oliveira Fernando Luiz , Marcato André Luís Marques
Published: January 2023

The generation from renewable sources has increased significantly worldwide, mainly driven by the need to reduce the global emissions of greenhouse gases, decelerate climate changes, and meet the environmental, social, and governance agenda (ESG). The main characteristics of variable renewable energy (VRE) are the stochastic nature, its seasonal aspects, spatial and time correlations, and the high variability in a short period, increasing the complexity of modeling, planning, operating, and the commercial aspects of the power systems. The research on the complementarity and dependence aspects of VREs is gaining importance, given the development of hybrid generation systems and an array of VREs generators spread over a large region, which could be compounded by different renewable sources, such as hydro, solar, and wind. This review is based on a systematic literature review, providing a comprehensive overview of studies that investigated applied methodologies and methods to address dependence and complementarity. It is a recent field of interest, as 60% of the articles were published in the last five years, a set of methods that have been employed to address this issue, from conventional statistics methods to artificial intelligence. The copulas technique appears as an important approach to modeling renewable energy interdependence. There is a gap in articles comparing the accuracy of the methods employed and the computational efforts.
A Hybrid Oil Production Prediction Model Based on Artificial Intelligence Technology
Authors: Kong Xiangming , Liu Yuetian , Xue Liang , Li Guanlin , Zhu Dongdong
Published: January 2023

Oil production prediction plays a significant role in designing programs for hydrocarbon reservoir development, adjusting production operations and making decisions. The prediction accuracy of oil production based on single methods is limited since more and more unconventional reservoirs are being exploited. Artificial intelligence technology and data decomposition are widely implemented in multi-step forecasting strategies. In this study, a hybrid prediction model was proposed based on two-stage decomposition, sample entropy reconstruction and long short-term memory neural network (LSTM) forecasts. The original oil production data were decomposed into several intrinsic mode functions (IMFs) by complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN); then these IMFs with different sample entropy (SE) values were reconstructed based on subsequence reconstruction rules that determine the appropriate reconstruction numbers and modes. Following that, the highest-frequency reconstructed IMF was preferred to be decomposed again by variational mode decomposition (VMD), and subsequences of the secondary decomposition and the remaining reconstructed IMFs were fed into the corresponding LSTM predictors based on a hybrid architecture for forecasting. Finally, the prediction values of each subseries were integrated to achieve the result. The proposed model makes predictions for the well production rate of the JinLong volcanic reservoir, and comparative experiments show that it has higher forecasting accuracy than other methods, making it recognized as a potential approach for evaluating reservoirs and guiding oilfield management.
The Impact of AI Technologies on E-Business
Authors: Castillo Maria Jimenez , Taherdoost Hamed
Published: January 2023

The outbreak of COVID-19 has entirely changed how consumers behave, due to an over-reliance on online shopping. With the global pandemic demanding people to stay home, multiple companies had to find innovative strategies to remain competitive and adapt to these rapid changes. However, the pandemic has also propelled the development of technologies, such as artificial intelligence (AI). AI concerns the engineering of machines and programs to make them intelligent, make decisions on their own or provide humans with information that will aid them in the decision-making process. Artificial intelligence software can be programmed according to an organization’s needs and performance goals. Although AI offers e-businesses multiple advantages, in order to differentiate themselves from their competitors, it is still a relatively new technology. A lack of understanding of its implementation will hinder organizations from reaping the full benefits of this technology. Moreover, multiple disputes regarding AI’s ethicality and privacy concerns have led to further research focused on making these systems more reliable and ethical.
Effect of Multi-Walled Carbon Nanotubes on the Growth and Expression of Stress Resistance Genes in Birch
Authors: Zhuzhukin Konstantin V. , Evlakov Peter M. , Grodetskaya Tatiana A. , Gusev Alexander A. , Zakharova Olga V. , Shuklinov Aleksey V. , Tomina Elena V.
Published: January 2023

Recent studies have shown that nanomaterials, including carbon nanotubes, are associated with a wide range of effects on living organisms, from stimulation to toxic effects. Plants are an important object of such research, which is associated with the potential use of carbon nanomaterials in agriculture and environmental protection. At the same time, the specific mechanisms of formation of plant resistance to the effects of carbon nanotubes remain not fully understood, especially in woody plants. Therefore, we studied the effect of aqueous colloids of multi-walled carbon nanotubes (MWCNTs) with an outer diameter of 10–30 nm and a length of about 2 μm at a concentration of 1, 10, 50, and 100 mg/L on morphometric parameters and the level of expression of stress resistance genes in Betula pubescens Ehrh. and B. pendula Roth. plants in greenhouse conditions. The results showed an increase in the length and diameter of the shoot in the studied plants. The dry biomass of the leaf increased by 30%, the stem by 42%, and the root by 49% when using MWCNTs at a concentration of 10 mg/L. The expression of the stress resistance genes DREB2 and PR-10 significantly increased under the influence of 1 mg/L MWCNTs on plants of both species. At the same time, the use of 100 mg/L nanoparticles led to a decrease in the studied parameters in Betula pendula, which may be associated with the negative effect of MWCNTs in high concentrations. The revealed positive effects of low concentrations of MWCNTs on morphometric parameters and stimulation of stress resistance genes by nanotubes open up prospects for their use in woody plant biotechnology.
These Boots Are Made for Walking: A Qualitative Study on the Perceived Barriers to Pedestrian Mobility in Madrid
Authors: López-Lambas M. Eugenia , Alonso Andrea , Ramírez-Saiz Alba , Pereira Andrés
Published: January 2023

As an active mode of transportation, walking has proven to be an effective strategy to tackle environmental problems while improving health. The current paper highlights the main factors that either encourage or deter pedestrians in their daily trips by analyzing the arisen discussions in three different Focus Groups (FGs), which were later synthesized into factors ranking according to their positive or negative outcomes. The results help identify these factors and show how a variety of target groups (seniors, young adults, middle-aged adults, divided by male and female perspective) perceive the city in different ways: younger adults prioritize accessibility and quality of the infrastructure, females highlighted the insecurity suffered during nighttime trips, and older adults emphasized the relevance of street maintenance. Finally, the benefits of walking on physical and mental health are viewed positively amongst all target groups, considering walking as a means to help people reduce stress.
Gene Content and Coding Diversity of the Growth Hormone Loci of Apes
Authors: González-Álvarez Rafael , Rodríguez-Sánchez Irám Pablo , Barrera-Saldaña Hugo A.
Published: January 2023

The growth hormone (GH) locus has experienced a dramatic evolution in primates, becoming multigenic and diverse in anthropoids. Despite sequence information from a vast number of primate species, it has remained unclear how the multigene family was favored. We compared the structure and composition of apes’ GH loci as a prerequisite to understanding their origin and possible evolutionary role. These thorough analyses of the GH loci of the chimpanzee, gorilla, and orangutan were done by resorting to previously sequenced bacterial artificial chromosomes (BACs) harboring them, as well as to their respective genome projects data available in GenBank. The GH loci of modern man, Neanderthal, gibbon, and wild boar were retrieved from GenBank. Coding regions, regulatory elements, and repetitive sequences were identified and compared among species. The GH loci of all the analyzed species are flanked by the genes CD79B (5′) and ICAM-1 (3′). In man, Neanderthal, and chimpanzee, the loci were integrated by five almost indistinguishable genes; however, in the former two, they rendered three different hormones, and in the latter, four different proteins were derived. Gorilla exhibited six genes, gibbon seven, and orangutan four. The sequences of the proximal promoters, enhancers, P-elements, and a locus control region (LCR) were highly conserved. The locus evolution might have implicated duplications of the ancestral pituitary gene (GH-N) and subsequent diversification of the copies, leading to the placental single GH-V gene and the multiple CSH genes.
Factors That Influence, Exacerbate, Contribute or Promote Violence in Couples
Authors: Sánchez Claudia , Mota Cecilia , Carreño Jorge , Gómez María
Published: January 2023

Life as a couple, and their ability to solve problems or not, can result in the relationship being satisfactory and functional or unsatisfactory and dysfunctional, which increases the risk of violence with serious implications. For that reason, it is important to isolate the risk factors to prevent and treat unsatisfactory and dysfunctional relationships. The qualitative interpretive exploratory method was used, analysing 50 sessions of group psychotherapy with patients from a reproductive health institution whose relationships faced violent problems. The identified factors were the lack of autonomy in one of the partners, unresolved internal factors, a combination of external factors and factors caused by their interaction; symmetrical and asymmetrical violence, subjugation of one before the other, intergenerational violence, family violence during childhood and normalisation of violence. Isolating factors to understand relationship problems at risk of manifesting violence opens the possibility of effective, specific and preventive treatments of family and intimate partner violence.
Applying Geomatics Techniques for Documenting Heritage Buildings in Aswan Region, Egypt: A Case Study of the Temple of Abu Simbel
Authors: Elbshbeshi AbdElhamid , Gomaa Ahmed , Mohamed Abdelmonem , Othman Amal , Ibraheem Ismael M. , Ghazala Hosni
Published: January 2023

It has recently become more popular to involve 3-D modeling and digital documentation in the conservation and restoration of heritage sites. The main objective of the current study is to develop a digital documentation process using laser scanning for Abu Simbel Temple, which is one of the most famous archaeological sites in Egypt. We focus on these techniques to replace traditional methods of building heritage documentation. To create the 3-D model with geographic coordinates and measure the rate of deformation, a precise geodetic network of five points was established around the temple. Then, 52 scans of the temple facade and its interior parts were taken using a Trimble TX6 laser scanner. This led to the creation of a 3-D digital model of the temple that includes geometric, structural, architectural, historical data, and non-engineering information (such as appearance, inscriptions, and material details). The 3-D point cloud model outputs exhibit a 6 mm spacing between the points with an error of 4 mm and a standard deviation of 5 mm. In addition, the temple’s virtual tour included 61 panoramic images. This virtual tour can help to increase heritage awareness, promote tourism, and aid in the future restoration of any parts vulnerable to damage.
Hormone–Flavonoid Patterns in Two Genotypes of Campanula portenschlagiana with Distinct Adventitious Rooting Competence
Authors: Bergonci Tábata , Fomsgaard Inge S. , Kjaer Katrine H. , Paponov Ivan A.
Published: January 2023

In horticulture and floriculture, plants are predominantly propagated vegetatively from stem cuttings. Consequently, the success of propagation depends on a plant’s capacity to form adventitious roots (AR) at the basal part of the cutting, and AR formation depends on the interaction between flavonoids and plant hormones in the basal part. In ornamental plants, flavonoid accumulation is important for flower color and can interact with plant hormone activity. In this study, we used an aeroponic system to culture two Campanula portenschlagiana genotypes contrasting in flower color to estimate cultivar differences in AR formation, flavonoid concentrations, and hormone composition. We found a greater accumulation of flavonols and flavones in petals in a blue-flowered genotype than in a white-flowered genotype. The blue-flowered genotype also accumulated more flavonols and flavones in the basal part of cuttings and showed better AR formation. The better AR formation in the blue-colored genotype was related to a greater accumulation of auxin and a lower accumulation of ABA in the basal part of the cuttings. In conclusion, higher flavonoid levels in the basal part of cuttings may interact with hormone action to affect excision-induced AR formation during the vegetative propagation of Campanula.