bluuebunny/crossref_metadata_2025 huggingface dataset:
Seismic Anisotropy Estimation Using a Downhole Microseismic Data Set in a Shale Gas Reservoir
Authors: Yu Changpeng , Zhu Yaling , Shapiro Serge
Published: November 2023

Shale anisotropy has a significant impact on the data processing and interpretation of microseismic monitoring in shale gas reservoirs. A geology- and rock-physics-constrained approach to estimating shale anisotropy using down-hole microseismic data sets is proposed in this study and is applied to the case of Horn River shale. A priori knowledge of shale anisotropy is obtained by integrating geological analyses and rock physics studies. This knowledge serves as an important constraint when building the initial model, minimizing the uncertainties and evaluating the results. The application to Horn River shale shows that the optimized anisotropic velocity model reduces the time misfit by about 65% compared to the originally provided velocity model. As the relocated perforation shot indicates, the event locations are significantly improved. The results also show that a high fraction of clay mineral results in strong fabric anisotropy in the Fort Simpson formation, whereas the quartz-rich shale gas reservoirs (Muskwa and Otter Park formations) show weaker fabric anisotropy. The percentage of velocity anisotropy in Horn River shale can be up to 40%. The fabric anisotropy of shale derived from the downhole microseismic data set is comparable with that of laboratory experiments. This demonstrates that downhole microseismic monitoring, as a quasi in situ experiment, has the potential to contribute to a better understanding of subsurface anisotropy beyond the laboratory. In addition, microseismic measurements of shale anisotropy are conducted in the seismic frequency band and are thus more applicable for further seismic applications.
An Analysis and Global Identification of Smoothless Variable Order of a Fractional Stochastic Differential Equation
Authors: Li Qiao , Zheng Xiangcheng , Wang Hong , Yang Zhiwei , Guo Xu
Published: November 2023

We establish both the uniqueness and the existence of the solutions to a hidden-memory variable-order fractional stochastic partial differential equation, which models, e.g., the stochastic motion of a Brownian particle within a viscous liquid medium varied with fractal dimensions. We also investigate the inverse problem concerning the observations of the solutions, which eliminates the analytic assumptions on the variable orders in the literature of this topic and theoretically guarantees the reliability of the determination and experimental inference.
Climate Change, Extreme Weather, and Intimate Partner Violence in East African Agrarian-Based Economies
Authors: Munala Leso , Allen Elizabeth M. , Frederick Andrew J. , Ngũnjiri Anne
Published: November 2023

Severe weather events can be a catalyst for intimate partner violence, particularly in agricultural settings. This research explores the association between weather and violence in parts of East Africa that rely on subsistence farming. We used IPUMS-DHS data from Uganda in 2006, Zimbabwe in 2010, and Mozambique in 2011 for intimate partner violence frequency and EM-DAT data to identify weather events by region in the year of and year prior to IPUMS-DHS data collection. This work is grounded in a conceptual framework that illustrates the mechanisms through which violence increases. We used logistic regression to estimate the odds of reporting violence in regions with severe weather events. The odds of reporting violence were 25% greater in regions with severe weather compared to regions without in Uganda (OR = 1.25, 95% CI: 1.11–1.41), 38% greater in Zimbabwe (OR = 1.38, 95% CI: 1.13–1.70), and 91% greater in Mozambique (OR = 1.91, 95% CI: 1.64–2.23). Our results add to the growing body of evidence showing that extreme weather can increase women’s and girls’ vulnerability to violence. Moreover, this analysis demonstrates that climate justice and intimate partner violence must be addressed together.
(Poly)phenols: The Missing Piece in the Puzzle of Inflammation
Authors: Figueira Inês , Ávila-Gálvez María Ángeles , Loncarevic-Vasiljkovic Natasa , dos Santos Cláudia Nunes
Published: November 2023

Despite researchers’ and clinicians’ exponential understanding of chronic diseases’ complexity, ranging from cancer, diabetes, and neurodegenerative disorders, we still have a lot of unanswered questions on pathobiology mechanisms, wherein inflammation is central [...]
Impact of Bariatric Surgery on Subtilisin/Kexin Type 9 (PCSK9) Gene Expression and Inflammation in the Adipose Tissue of Obese Diabetic Rats
Authors: Heald Adrian , Fachim Helene , Bashir Bilal , Garside Bethanie , Adam Safwaan , Iqbal Zohaib , Syed Akheel , Donn Rachelle , Le Roux Carel , Abdelaal Mahmoud , White James , Soran Handrean
Published: November 2023

Bariatric surgery improves dyslipidaemia and reduces body weight, but it remains unclear how bariatric surgery modulates gene expression in fat cells to influence the proprotein convertase subtilisin/kexin type 9 (PCSK-9) and low-density lipoprotein receptor (LDLR) gene expression. The expression of the PCSK9/LDLR/tumor necrosis factor-alpha (TNFα) gene in adipose tissue was measured in two groups of Zucker Diabetic Sprague Dawley (ZDSD) rats after Roux-en-Y gastric bypass (RYGB) surgery or ‘SHAM’ operation. There was lower PCSK9 (p = 0.02) and higher LDLR gene expression (p = 0.02) in adipose tissue in rats after RYGB. Weight change did not correlate with PCSK9 gene expression (r = −0.5, p = 0.08) or TNFα gene expression (r = −0.4, p = 0.1). TNFα gene expression was positively correlated with PCSK9 gene expression (r = 0.7, p = 0.001) but not correlated with LDLR expression (r = −0.3, p = 0.3). Circulating triglyceride levels were lower in RYGB compared to the SHAM group (1.1 (0.8–1.4) vs. 1.5 (1.0–4.2), p = 0.038) mmol/L with no difference in cholesterol levels. LDLR gene expression was increased post-bariatric surgery with the potential to reduce the number of circulating LDL particles. PCSK9 gene expression and TNFα gene expression were positively correlated after RYGB in ZDSD rats, suggesting that the modulation of pro-inflammatory pathways in adipose tissue after RYGB may partly relate to PCSK9 and LDLR gene expression.
Proton Compared to X-Irradiation Induces Different Protein Profiles in Oral Cancer Cells and Their Derived Extracellular Vesicles
Authors: Juvkam Inga Solgård , Zlygosteva Olga , Sitarz Mateusz , Thiede Bernd , Sørensen Brita Singers , Malinen Eirik , Edin Nina Jeppesen , Søland Tine Merete , Galtung Hilde Kanli
Published: November 2023

Extracellular vesicles (EVs) are membrane-bound particles released from cells, and their cargo can alter the function of recipient cells. EVs from X-irradiated cells have been shown to play a likely role in non-targeted effects. However, EVs derived from proton irradiated cells have not yet been studied. We aimed to investigate the proteome of EVs and their cell of origin after proton or X-irradiation. The EVs were derived from a human oral squamous cell carcinoma (OSCC) cell line exposed to 0, 4, or 8 Gy from either protons or X-rays. The EVs and irradiated OSCC cells underwent liquid chromatography–mass spectrometry for protein identification. Interestingly, we found different protein profiles both in the EVs and in the OSCC cells after proton irradiation compared to X-irradiation. In the EVs, we found that protons cause a downregulation of proteins involved in cell growth and DNA damage response compared to X-rays. In the OSCC cells, proton and X-irradiation induced dissimilar cell death pathways and distinct DNA damage repair systems. These results are of potential importance for understanding how non-targeted effects in normal tissue can be limited and for future implementation of proton therapy in the clinic.
Attempts to Understand Oral Mucositis in Head and Neck Cancer Patients through Omics Studies: A Narrative Review
Authors: San Valentin Erin Marie D. , Do Kim-Anh , Yeung Sai-Ching J. , Reyes-Gibby Cielito C.
Published: November 2023

Oral mucositis (OM) is a common and clinically impactful side effect of cytotoxic cancer treatment, particularly in patients with head and neck squamous cell carcinoma (HNSCC) who undergo radiotherapy with or without concomitant chemotherapy. The etiology and pathogenic mechanisms of OM are complex, multifaceted and elicit both direct and indirect damage to the mucosa. In this narrative review, we describe studies that use various omics methodologies (genomics, transcriptomics, microbiomics and metabolomics) in attempts to elucidate the biological pathways associated with the development or severity of OM. Integrating different omics into multi-omics approaches carries the potential to discover links among host factors (genomics), host responses (transcriptomics, metabolomics), and the local environment (microbiomics).
VEGFR and DPP-IV as Markers of Severe COVID-19 and Predictors of ICU Admission
Authors: Pius-Sadowska Ewa , Kulig Piotr , Niedźwiedź Anna , Baumert Bartłomiej , Łuczkowska Karolina , Rogińska Dorota , Sobuś Anna , Ulańczyk Zofia , Kawa Miłosz , Paczkowska Edyta , Parczewski Miłosz , Machalińska Anna , Machaliński Bogusław
Published: November 2023

The pathophysiology of the severe course of COVID-19 is multifactorial and not entirely elucidated. However, it is well known that the hyperinflammatory response and cytokine storm are paramount events leading to further complications. In this paper, we investigated the vascular response in the pathophysiology of severe COVID-19 and aimed to identify novel biomarkers predictive of ICU admission. The study group consisted of 210 patients diagnosed with COVID-19 (age range: 18–93; mean ± SD: 57.78 ± 14.16), while the control group consisted of 80 healthy individuals. We assessed the plasma concentrations of various vascular factors using the Luminex technique. Then, we isolated RNA from blood mononuclear cells and performed a bioinformatics analysis investigating various processes related to vascular response, inflammation and angiogenesis. Our results confirmed that severe COVID-19 is associated with vWF/ADAMTS 13 imbalance. High plasma concentrations of VEGFR and low DPP-IV may be potential predictors of ICU admission. SARS-CoV-2 infection impairs angiogenesis, hinders the generation of nitric oxide, and thus impedes vasodilation. The hypercoagulable state develops mainly in the early stages of the disease, which may contribute to the well-established complications of COVID-19.
The Effect of Fat Intake with Increased Omega-6-to-Omega-3 Polyunsaturated Fatty Acid Ratio in Animal Models of Early and Late Alzheimer’s Disease-like Pathogenesis
Authors: Galeano Pablo , de Ceglia Marialuisa , Mastrogiovanni Mauricio , Campanelli Lorenzo , Medina-Vera Dina , Campolo Nicolás , Novack Gisela V. , Rosell-Valle Cristina , Suárez Juan , Aicardo Adrián , Campuzano Karen , Castaño Eduardo M. , Do Carmo Sonia , Cuello A. Claudio , Bartesaghi Silvina , Radi Rafael , Rodríguez de Fonseca Fernando , Morelli Laura
Published: November 2023

This work aims to clarify the effect of dietary polyunsaturated fatty acid (PUFA) intake on the adult brain affected by amyloid pathology. McGill-R-Thy1-APP transgenic (Tg) rat and 5xFAD Tg mouse models that represent earlier or later disease stages were employed. The animals were exposed to a control diet (CD) or an HFD based on corn oil, from young (rats) or adult (mice) ages for 24 or 10 weeks, respectively. In rats and mice, the HFD impaired reference memory in wild-type (WT) animals but did not worsen it in Tg, did not cause obesity, and did not increase triglycerides or glucose levels. Conversely, the HFD promoted stronger microglial activation in Tg vs. WT rats but had no effect on cerebral amyloid deposition. IFN-γ, IL-1β, and IL-6 plasma levels were increased in Tg rats, regardless of diet, while CXCL1 chemokine levels were increased in HFD-fed mice, regardless of genotype. Hippocampal 3-nitrotyrosine levels tended to increase in HFD-fed Tg rats but not in mice. Overall, an HFD with an elevated omega-6-to-omega-3 ratio as compared to the CD (25:1 vs. 8.4:1) did not aggravate the outcome of AD regardless of the stage of amyloid pathology, suggesting that many neurobiological processes relevant to AD are not directly dependent on PUFA intake.
Triboelectric Nanogenerators Based on Nanostructured Layers of Zinc Oxide Deposited on Carbon Fabric
Authors: Petrushenko Sergey I. , Fijalkowski Mateusz , Kopach Volodymyr R. , Shepotko Yevhenii M. , Adach Kinga , Dukarov Sergei V. , Sukhov Volodymyr M. , Fedonenko Alina , Khrypunova Alina L. , Klochko Natalia P.
Published: November 2023

In this work, to obtain textile triboelectric layers for wearable flexible triboelectric nanogenerators (TENGs), we used two modes of growing nanostructured zinc oxide (ZnO) arrays on a carbon fabric (CF) using the automatic Successive Ionic Layer Adsorption and Reaction (SILAR) method. To produce a CF/ZnO_nr triboelectric textile with an array of intergrown short ZnO nanorods, we used a pre-coating of carbon fibers with ZnO seed layers. When the ZnO layer was fabricated by automatic SILAR on bare carbon fabric, we obtained the CF/ZnO_ns textile with an array of interconnected ZnO nanosheets 50–100 nm thick. As a proof of concept, we developed and tested two prototypes of flexible vertical contact–separation mode CF/ZnO_nr/PET/ITO and CF/ZnO_ns/PET/ITO TENGs, in which a gap was involuntarily formed between the smooth PET layer and the woven carbon textile coated with nanostructured ZnO films. In pressing tests with a force of ~5 N (pressure ~33 kPa), the CF/ZnO_ns/PET/ITO TENG created a higher open-circuit voltage up to 30 V and a higher maximum surface charge density of 1.3 μC/m2. In the successive press–release tests, this TENG showed an output voltage of 3.6 V, a current density of 1.47 μA/cm2, and a power density of 1.8 µW/cm2, confirming its effectiveness.
A Novel Composite Pitch Control Scheme for Floating Offshore Wind Turbines with Actuator Fault Consideration
Authors: Liu Shuang , Han Yaozhen , Ma Ronglin , Hou Mingdong , Kang Chao
Published: November 2023

It is of great importance to simultaneously stabilize output power and suppress platform motion and fatigue loads in floating offshore wind turbine control systems. In this paper, a novel composite blade pitch control scheme considering actuator fault is proposed based on an augmented linear quadratic regulator (LQR), a fuzzy proportional integral (PI) and an adaptive second-order sliding-mode observer. Collective pitch control was achieved via the fuzzy PI, while individual pitch control was based on the augmented LQR. In the case of actuator fault, an adaptive second-order sliding-mode observer was constructed to effectively eliminate the need for the upper bound of unknown fault derivatives and suppress the chattering effect. This paper conducted co-simulations based on FAST (Fatigue, Aerodynamics, Structures, and Turbulence) and MATLAB/Simulink to verify the effectiveness and superiority of the proposed scheme under different environmental conditions. It is shown that platform roll was reduced by approximately 54% compared to that under PI control. For the tower fore–aft moment, load reductions of 45% or more were achievable. The proposed scheme can greatly reduce the pitch and roll of the floating platform and loads in the windward direction of the wind turbine.
Fatigue Load Minimization for a Position-Controlled Floating Offshore Wind Turbine
Authors: Saunders Brendan , Nagamune Ryozo
Published: November 2023

Floating offshore wind farm control via real-time turbine repositioning has a potential in significantly enhancing the wind farm efficiency. Although the wind farm power capture increase by moving platforms with aerodynamic force has been verified in a recent study, the investigation and mitigation of the fatigue damage caused by such aerodynamic force manipulated for turbine repositioning is still necessary. To respond to these needs, this paper presents fatigue load controller design for a semisubmersible floating offshore wind turbine, particularly when the turbine position is controlled by the nacelle yaw angle. At various turbine positions determined by nacelle yaw angles and average wind speeds, the designed controller manipulates three blade pitch angles individually and minimizes the fatigue load at the tower base. As the individual blade pitch controller, the linear quadratic regulator is optimized through surrogate optimization by simulating the turbine disturbed by various turbulent wind and irregular wave profiles, and then by searching for a minimum fatigue from these simulations. Fatigue load analysis with the optimized controller leads to the main contribution of this paper, that is, to demonstrate that turbine repositioning can be achieved while allowing for the inclusion of a fatigue reducing controller. In fact, when operating the FOWT with the position controller and fatigue load controller, the fatigue damage at the tower base is reduced by about 40% for different nacelle yaw angles. This result supports the feasibility of position-controlled wind turbines to optimize the wind farm efficiency, thereby drastically reducing the offshore wind energy cost.
Model-Free Control for Doubly Salient Permanent Magnet-Generator-Based Tidal Stream Turbine Considering Flux-Weakening Operation
Authors: Chen Hao , Liu Luming , Amirat Yassine , Zhou Zhibin , Aϊt-Ahmed Nadia , Benbouzid Mohamed
Published: November 2023

Renewable energy generation is increasingly important due to serious energy issues. A Doubly Salient Permanent Magnet Generator (DSPMG) can be an interesting candidate for tidal stream renewable energy systems. However, the special structure makes the system nonlinear and strongly coupled even after Park transformation and involves a larger torque ripple. Previous research mainly focused on model-based control for this machine, which is very sensitive to the parameters. Thus, to control the complex systems stably and accurately, two model-free control algorithms, Active Disturbance Rejection-Based Iterative Learning Control (ADRILC) and Active Disturbance Rejection Control–Iterative Learning Control (ADRC–ILC), are proposed for the current and speed control loops of a DSPMG-based Tidal Stream Turbine (TST), respectively. ADRC–ILC uses ADRC to deal with the external non-periodic speed ripple and adopts ILC to reduce the internal periodic speed ripple. ADRILC employs an iterative method to improve the ESO for the enhancement of the convergence rate of ILC. Considering the variable tidal speed, when the speed is above the rated value, Maximum Power Point Tracking (MPPT) must be changed to a power limitation strategy for limiting the generator power to the rated value and extending the system operating range. Thus, Optimal Tip Speed Ratio (OTSR)-based MPPT (for a low tidal current speed) and Leading Angle Flux-Weakening Control (LAFWC) (for a high tidal current speed) strategies are also proposed. According to the simulation results, the proposed ADRC–ILC + ADRILC has the lowest torque ripple, the highest control accuracy, as well as a good current tracking capability and strong robustness. At the rated speed, the proposed method reduces the torque ripple by more than 20% and the speed error by about 80% compared with PI control: the current difference is limited in 2A. The LAFWC proposed for an excessive tidal current speed is effective in conserving the electromagnetic power and increasing the generator speed.
The Interactions between Two Fungal Endophytes Epicoccum layuense R2-21 and Alternaria alternata XHYN2 and Grapevines (Vitis vinifera) with De Novo Established Symbionts under Aseptic Conditions
Authors: Pan Xiao-Xia , Liu Hui-Zhi , Li Yu , Zhou Ping , Wen Yun , Lu Chun-Xi , Zhu You-Yong , Yang Ming-Zhi
Published: November 2023

In this study, we focused on grapevine–endophyte interactions and reprogrammed secondary metabolism in the host plant due to defense against the colonization of endophytes. Thus, the transcriptional responses of tissue cultured grapevine seedlings (Vitis vinifera L. cv.: Cabernet Sauvignon) to two fungal endophytes Epicoccum layuense R2-21 (Epi R2-21) and Alternaria alternata XHYN2 (Alt XHYN2) at three different time points (6 h, 6 d, 15 d) were analyzed. As expected, a total of 5748 and 5817 differentially expressed genes (DEGs) were separately initiated in Epi R2-21 and Alt XHYN2 symbiotic tissue cultured seedlings compared to no endophyte treatment. The up-regulated DEGs at all time points in Epi R2-21- or Alt XHYN2–treated seedlings were mainly enriched in the flavonoid biosynthesis, phenylpropanoid biosynthesis, phenylalanine metabolism, stilbenoid, diarylheptanoid and gingerol biosynthesis, and circadian rhythm–plant pathways. In addition, the up-regulated DEGs at all sampling times in Alt XHYN2-treated tissue cultured seedlings were enriched in the plant–pathogen interaction pathway, but appeared in Epi R2-21 symbiotic seedlings only after 15 d of treatment. The down-regulated DEGs were not enriched in any KEGG pathways after 6 h inoculation for Epi R2-21 and Alt XHYN2 treatments, but were enriched mainly in photosynthesis–antenna proteins and plant hormone signal transduction pathways at other sampling times. At three different time points, a total of 51 DEGs (all up-regulated, 1.33–10.41-fold) were involved in secondary metabolism, and 22 DEGs (all up-regulated, 1.01–8.40-fold) were involved in defense responses in endophytic fungi symbiotic tissue cultured seedlings. The protein–protein interaction (PPI) network demonstrated that genes encoding CHS (VIT_10s0042g00920, VIT_14s0068g00920, and VIT_16s0100g00910) and the VIT_11s0065g00350 gene encoding CYP73A mediated the defense responses, and might induce more defense-associated metabolites. These results illustrated the activation of stress–associated secondary metabolism in the host grapevine during the establishment of fungi–plant endophytism. This work provides avenues for reshaping the qualities and characteristics of wine grapes utilizing specific endophytes and better understanding plant–microbe interactions.
Optical and Structural Properties of Aluminum Nitride Epi-Films at Room and High Temperature
Authors: Yang Yanlian , Liu Yao , Wang Lianshan , Zhang Shuping , Lu Haixia , Peng Yi , Wei Wenwang , Yang Jia , Feng Zhe Chuan , Wan Lingyu , Klein Benjamin , Ferguson Ian T. , Sun Wenhong
Published: November 2023

The high-quality aluminum nitride (AlN) epilayer is the key factor that directly affects the performance of semiconductor deep-ultraviolet (DUV) photoelectronic devices. In this work, to investigate the influence of thickness on the quality of the AlN epilayer, two AlN-thick epi-film samples were grown on c-plane sapphire substrates. The optical and structural characteristics of AlN films are meticulously examined by using high-resolution X-ray diffraction (HR-XRD), scanning electron microscopy (SEM), a dual-beam ultraviolet-visible spectrophotometer, and spectroscopic ellipsometry (SE). It has been found that the quality of AlN can be controlled by adjusting the AlN film thickness. The phenomenon, in which the thicker AlNn film exhibits lower dislocations than the thinner one, demonstrates that thick AlN epitaxial samples can work as a strain relief layer and, in the meantime, help significantly bend the dislocations and decrease total dislocation density with the thicker epi-film. The Urbach’s binding energy and optical bandgap (Eg) derived by optical transmission (OT) and SE depend on crystallite size, crystalline alignment, and film thickness, which are in good agreement with XRD and SEM results. It is concluded that under the treatment of thickening film, the essence of crystal quality is improved. The bandgap energies of AlN samples obtained from SE possess larger values and higher accuracy than those extracted from OT. The Bose–Einstein relation is used to demonstrate the bandgap variation with temperature, and it is indicated that the thermal stability of bandgap energy can be improved with an increase in film thickness. It is revealed that when the thickness increases to micrometer order, the thickness has little effect on the change of Eg with temperature.
Hydraulic Expansion Joint Contact State of Heat Exchanger Based on New Contact Area Measurement Method
Authors: Zhang Wenze , Liu Jianwei , Ma Jianping , He Yulin , Wu Sunbing
Published: November 2023

The contact state of a seamless internal threaded copper tube and an aluminium foil fin not only affects the heat transfer efficiency of a tube–fin heat exchanger but also seriously affects its service life. In this study, hydraulic expansion technology was used to connect the copper tube with an internal thread with a 7 mm diameter to the fin of the heat exchanger. The influence of the expansion pressure and pressure holding time on the contact state was analysed through experiments and finite element simulation, and the variation law of the two on the contact state was obtained. The contact state was characterised by the contact gap and contact area. In order to obtain the specific contact area value, a new method of measuring the contact area was developed to reveal the variation in contact area between the copper tube and the fin after expansion. The results show that the contact gap decreases with an increase in expansion pressure, while the pressure holding time remains the same. The contact area increases with an increase in expansion pressure, and the rate of increase slows. When the expansion pressure is 18 MPa, the average contact gap is approximately 0.018 mm. When the expansion pressure reaches 16 MPa, the contact area ratio is 91.0%. When the expansion pressure increases to 18 MPa, the contact area ratio only increases by approximately 0.6%. Compared with the influence of the expansion pressure on the increase in contact area, the influence of the pressure holding time on the contact area is lower.
Time-Resolved Structural Measurement of Thermal Resistance across a Buried Semiconductor Heterostructure Interface
Authors: Lee Joohyun , Jo Wonhyuk , Kwon Ji-Hwan , Griffin Bruce , Cho Byeong-Gwan , Landahl Eric C. , Lee Sooheyong
Published: November 2023

The precise control and understanding of heat flow in heterostructures is pivotal for advancements in thermoelectric energy conversion, thermal barrier coatings, and efficient heat management in electronic and optoelectronic devices. In this study, we employ high-angular-resolution time-resolved X-ray diffraction to structurally measure thermal resistance in a laser-excited AlGaAs/GaAs semiconductor heterostructure. Our methodology offers femtometer-scale spatial sensitivity and nanosecond time resolution, enabling us to directly observe heat transport across a buried interface. We corroborate established Thermal Boundary Resistance (TBR) values for AlGaAs/GaAs heterostructures and demonstrate that TBR arises from material property discrepancies on either side of a nearly flawless atomic interface. This work not only sheds light on the fundamental mechanisms governing heat flow across buried interfaces but also presents a robust experimental framework that can be extended to other heterostructure systems, paving the way for optimized thermal management in next-generation devices.
Analyzing the Impact of Financial News Sentiments on Stock Prices—A Wavelet Correlation
Authors: Cristescu Marian Pompiliu , Mara Dumitru Alexandru , Nerișanu Raluca Andreea , Culda Lia Cornelia , Maniu Ionela
Published: November 2023

This study investigates the complex interplay between public sentiment, as captured through news titles and descriptions, and the stock prices of three major tech companies: Microsoft (MSFT), Tesla (TSLA), and Apple (AAPL). Leveraging advanced analytical methods including Pearson correlation, wavelet coherence, and regression analysis, this research probes the degree to which stock-price fluctuations can be attributed to the polarity of media sentiment. The methodology combines statistical techniques to assess sentiment’s predictive power for stock opening and closing prices, while wavelet coherence analysis unveils the temporal dynamics of these relationships. The results demonstrate a significant correlation between sentiment polarity and stock prices, with description polarity affecting Microsoft’s opening prices, title polarity influencing Tesla’s opening prices, and a positive impact of title polarity on Apple’s closing prices. However, Tesla’s stock showed no significant coherence, indicating a potential divergence in how sentiment affects stock behavior across companies. The study highlights the importance of sentiment analysis in forecasting stock-market trends, revealing not only direct correlations but also lagged influences on stock prices. Despite its focus on large-cap tech firms, this research provides a foundational understanding of sentiment’s financial implications, suggesting further investigation into smaller firms and other market sectors.
Coefficient Estimates for Quasi-Subordination Classes Connected with the Combination of q-Convolution and Error Function
Authors: El-Deeb Sheza M. , Cotîrlă Luminita-Ioana
Published: November 2023

We utilize quasi-subordination to analyze and introduce several new classes, and we construct a new operator by combining the error function and q-convolution. Additionally, we obtain estimates for the Fekete Szego functional and the Taylor–Maclaurin coefficients for functions in c2 and c3 new classes. Moreover, we discuss some applications of the operator.
Stochastic Models and Processing Probabilistic Data for Solving the Problem of Improving the Electric Freight Transport Reliability
Authors: Martyushev Nikita V. , Malozyomov Boris V. , Filina Olga A. , Sorokova Svetlana N. , Efremenkov Egor A. , Valuev Denis V. , Qi Mengxu
Published: November 2023

Improving the productivity and reliability of mining infrastructure is an important task contributing to the mining performance enhancement of any enterprise. Open-pit dump trucks that move rock masses from the mining site to unloading points are an important part of the infrastructure of coal mines, and they are the main transport unit used in the technological cycle during open-pit mining. The failure of any of the mining truck systems causes unscheduled downtime and leads to significant economic losses, which are associated with the need to immediately restore the working state and lost profits due to decreased site productivity and a disruption of the production cycle. Therefore, minimizing the number and duration of unscheduled repairs is a necessity. The most time-consuming operations are the replacement of the diesel engine, traction generator, and traction motors, which requires additional disassembly of the dump truck equipment; therefore, special reliability requirements are imposed on these units. In this article, a mathematical model intended for processing the statistical data was developed to determine the reliability indicators of the brush collector assembly and the residual life of brushes of electric motors, which, unlike existing models, allow the determination of the refined life of the brushes based on the limiting height of their wear. A method to predict the residual life of an electric brush of a DC electric motor is presented, containing a list of controlled reliability indicators that are part of the mathematical model. Using the proposed mathematical model, the reliability of the brush-collector assembly, the minimum height of the brush during operation, and the average rate of its wear were studied and calculated.
Microbiomes: A New Open Section in Microorganisms
Authors: Jehmlich Nico
Published: November 2023

As the Editor-in-Chief of Microorganisms, it is my pleasure to introduce a new Section of this journal [...]
Assessing the Probiotic Effects of Pediococcus pentosaceus CACC616 in Weaned Piglets
Authors: Park Soyeon , Song Jeongsup , Park Mi Ae , Jang Hyun-Jun , Son Seoyun , Kim Dae-Hyuk , Kim Yangseon
Published: November 2023

During weaning, piglets experience various stressor events that disrupt their gut microbiota and immune balance, decrease growth parameters, and increase mortality rates. In this study, we assessed the efficacy of Pediococcus pentosaceus CACC616 as a probiotic supplement. We characterized this strain and evaluated its effect on improving growth performance, modulating gut microbiota composition, and reducing noxious odor components in weaned piglets compared to a non-supplementary diet (control). During the 26-day period, 40 crossbred weaned piglets were randomly assigned to pens with 20 animals each in two groups: control and treatment groups with CACC616. On day 26, the treatment group exhibited a lower feed conversion ratio (FCR) and a significant alteration in gut microbial composition, correlating with improved growth parameters and gut health (p < 0.05). The treatment group also exhibited significantly reduced digestibility- and intestinal-environment-related noxious odor components (p < 0.05). The CACC616 strain effectively reduced pathogenic genera numbers, including Campylobacter, Mogibacterium, Escherichia–Shigella, and Desulfovibrio spp., with the treatment group exhibiting lower fecal calprotectin levels than the control group (p < 0.05). Overall, this study revealed that the functional probiotic CACC616 contributes to enhanced FCR and effectively modulates weaned piglets’ inflammation and intestinal microbiota.
Modeling of Subwavelength Gratings: Near-Field Behavior
Authors: Chernyavsky Alexander , Bereza Alexey , Frumin Leonid , Shapiro David
Published: November 2023

Subwavelength gratings have received considerable attention in the fields of photonics, optoelectronics, and image sensing. This paper presents simple analytical expressions for the near-field intensity distribution of radiation scattered by these gratings. Our proposed methodology employs a 2D point dipole model and a specialized version of perturbation theory. By validating our models via numerical techniques including boundary and finite element methods, we demonstrate their effectiveness, even for narrow slits.
Effect of Interaction between Carbon Dioxide and Fluid Phase/Rock Interface on Carbon Dioxide Storage
Authors: Cao Xiaopeng , Feng Qihong , Ji Yanfeng
Published: November 2023

The interaction between CO2, formation water, and rock surfaces after CO2 flooding and the mechanism by which it affects CO2 storage were studied in this paper. The results show that variations in the solubility of CO2 in crude oil under pressure are similar to those observed in formation water. The solubility of CO2 increases as pressure increases under a low-pressure conditions. The solubility of CO2 in crude oil increases significantly when crude oil is in a low-viscosity state, and this makes it easier to diffuse CO2 into the oil phase at high temperatures. More resistance is encountered when CO2 diffuses into the liquid-containing space of an irregular core, making the coefficient of diffusion into the oil–water two-phase flow in the porous medium smaller. After the core is corroded by a CO2-saturated aqueous solution, the quartz content in the mineral component increases and the plagioclase and potassium feldspar content significantly decrease. The dissolution of the feldspar leads to the formation of a large amount of secondary kaolinite, thus increasing the kaolinite content. In the early stage of CO2 erosion during dynamic displacement, the combined effect of particle migration and inorganic precipitation leads to a slow growth in core permeability and porosity. As the erosion progresses, the influence of particle migration and inorganic precipitation on permeability gradually decreases, while the porosity of the core gradually increases. The secondary pores play a role, and the erosion of the CO2–water system makes the permeability and porosity of the core gradually increase. During dynamic displacement, CO2 is mainly stored in the reservoir in free and irreducible states. Under the pressure of the reservoir, some of the CO2 participates in erosion reactions and is stored in the rock or the solution in the form of minerals or ions. In addition, a small portion of the CO2 is dissolved in the residual water and residual oil that remain after the dynamic displacement. The results of this paper can provide some theoretical support for the design of a CO2 storage site.
Technological Innovations in the Application of Constructed Wetlands: A Review
Authors: Fernández Ramírez Luis E. , Zamora-Castro Sergio A. , Sandoval-Herazo Luis Carlos , Herrera-May Agustín L. , Salgado-Estrada Rolando , De La Cruz-Dessavre Dylan A.
Published: November 2023

Constructed wetlands (CWs) are highly effective in wastewater treatment and have generated lines of research with a focus on technological development and implemented innovations. This work concentrates on the most recent technical and scientific advances that have obtained optimal results in the construction of CWs using sustainable materials and the use of ornamental plants and other aquatic plants. Efficiency is also documented through models and simulation with neural networks, the use of the random forest method, and the use of software such as MODFLOW, MODPATH, and COMSOL Multiphysics. The information shown is structured by geographical area and addresses regions of Africa, Asia, Europe, North America, South America, and Oceania. It is important to consider that the optimization and innovation of CW for pollutant removal may benefit developing countries that do not have sufficient infrastructure to meet the demand for municipal and industrial wastewater.
Energy, Exergy, Economic, and Environmental Prospects of Solar Distiller with Three-Vertical Stages and Thermo-Storing Material
Authors: Bacha Habib Ben , Abdullah AbdelKader S. , Essa Fadl A. , Omara Zakaria M.
Published: November 2023

Solar distillation emerges as a viable remedy for addressing water scarcity in both remote and urban locales. However, its operational efficiency remains a limiting factor. Consequently, this study undertakes a comprehensive approach by introducing design modifications to enhance a distiller’s overall productivity. The pivotal adjustment involves configuring the distiller into a three-tiered structure, thus designating it as a multi-stage solar still (MSSS). Notably, the solar stills are crafted entirely from glass to optimize consistent solar tracking, eschewing the conventional sun-tracking rotation mechanism. Furthermore, the three-stage distiller undergoes refinement through the incorporation of a thermo-storing material (PCM) comprising paraffin infused with graphene nanocomposites at the base of the solar still (SS). Subsequent to these design enhancements, a comprehensive evaluation encompassing exergy, economic viability, environmental impact, and thermal considerations is conducted for both the conventional solar still (CSS) and MSSS. The outcomes elucidate that the upper stage of the MSSS outperforms its counterparts, producing superior results. Comparative analysis indicates a remarkable 160% enhancement in productivity for the MSSS over the CSS. Cumulative water productivities for the CSS and MSSS with PCM are recorded at 2840 and 7980 mL/m2 during the daytime, reflecting an improvement of 181%. The energy efficiency metrics reveal values of 31%, 49.8%, and 53% for the CSS, MSSS, and MSSS with PCM, respectively. Moreover, the MSSS with PCM demonstrates an exergy efficiency of 5.8%. The environmental implications are quantified at 12 tons of CO2 emissions per year for the MSSS with PCM. Finally, the cost considerations illustrate a reduction in the cost of freshwater for the MSSS with PCM (0.10 $/L) and the MSSS (0.13 $/L), as compared to the conventional SS (0.24 $/L).
A Study on Wheel Member Condition Recognition Using 1D–CNN
Authors: Lee Jin-Han , Lee Jun-Hee , Lee Chang-Jae , Lee Seung-Lok , Kim Jin-Pyung , Jeong Jae-Hoon
Published: November 2023

The condition of a railway vehicle’s wheels is an essential factor for safe operation. However, the current inspection of railway vehicle wheels is limited to periodic major and minor maintenance, where physical anomalies such as vibrations and noise are visually checked by maintenance personnel and addressed after detection. As a result, there is a need for predictive technology concerning wheel conditions to prevent railway vehicle damage and potential accidents due to wheel defects. Insufficient predictive technology for railway vehicle’s wheel conditions forms the background for this study. In this research, a real-time tire wear classification system for light-rail rubber tires was proposed to reduce operational costs, enhance safety, and prevent service delays. To perform real-time condition classification of rubber tires, operational data from railway vehicles, including temperature, pressure, and acceleration, were collected. These data were processed and analyzed to generate training data. A 1D–CNN model was employed to classify tire conditions, and it demonstrated exceptionally high performance with a 99.4% accuracy rate.
Achieving Robust Compressive Sensing Seismic Acquisition with a Two-Step Sampling Approach
Authors: Titova Anna , Wakin Michael B. , Tura Ali C.
Published: November 2023

The compressive sensing (CS) framework offers a cost-effective alternative to dense alias-free sampling. Designing seismic layouts based on the CS technique imposes the use of specific sampling patterns in addition to the logistical and geophysical requirements. We propose a two-step design process for generating CS-based schemes suitable for seismic applications. During the first step, uniform random sampling is used to generate a random scheme, which is supported theoretically by the restricted isometry property. Following that, designated samples are added to the random scheme to control the maximum distance between adjacent sources (or receivers). The null space property theoretically justifies the additional samples of the second step. Our sampling method generates sampling patterns with a CS theoretical background, controlled distance between adjacent samples, and a flexible number of active and omitted samples. The robustness of two-step sampling schemes for reallocated samples is investigated and CS reconstruction tests are performed. In addition, using this approach, a CS-based 3D seismic survey is designed, and the distributions of traces in fold maps and rose diagrams are analyzed. It is shown that the two-step scheme is suitable for CS-based seismic surveys and field applications.
More Reliable Neighborhood Contrastive Learning for Novel Class Discovery in Sensor-Based Human Activity Recognition
Authors: Zhang Mingcong , Zhu Tao , Nie Mingxing , Liu Zhenyu
Published: November 2023

Human Activity Recognition (HAR) systems have made significant progress in recognizing and classifying human activities using sensor data from a variety of sensors. Nevertheless, they have struggled to automatically discover novel activity classes within massive amounts of unlabeled sensor data without external supervision. This restricts their ability to classify new activities of unlabeled sensor data in real-world deployments where fully supervised settings are not applicable. To address this limitation, this paper presents the Novel Class Discovery (NCD) problem, which aims to classify new class activities of unlabeled sensor data by fully utilizing existing activities of labeled data. To address this problem, we propose a new end-to-end framework called More Reliable Neighborhood Contrastive Learning (MRNCL), which is a variant of the Neighborhood Contrastive Learning (NCL) framework commonly used in visual domain. Compared to NCL, our proposed MRNCL framework is more lightweight and introduces an effective similarity measure that can find more reliable k-nearest neighbors of an unlabeled query sample in the embedding space. These neighbors contribute to contrastive learning to facilitate the model. Extensive experiments on three public sensor datasets demonstrate that the proposed model outperforms existing methods in the NCD task in sensor-based HAR, as indicated by the fact that our model performs better in clustering performance of new activity class instances.
MIC: Microwave Imaging Curtain for Dynamic and Automatic Detection of Weapons and Explosive Belts
Authors: Baqué Rémi , Vignaud Luc , Wasik Valentine , Castet Nicolas , Herschel Reinhold , Cetinkaya Harun , Brandes Thomas
Published: November 2023

DEXTER (detection of explosives and firearms to counter terrorism) is a project funded by NATO’s Science for Peace and Security (SPS) program with the goal of developing an integrated system capable of remotely and accurately detecting explosives and firearms in public places without impeding the flow of pedestrians. While body scanner systems in secure areas of public places are becoming more and more efficient, the attack at Brussels airport on 22 March 2016, upstream of these systems, in the middle of the crowd of passengers, demonstrated the lack of discreet and real-time security against threats of mass terrorism. The NATO-SPS international and multi-year DEXTER project aims to provide new technical and strategic solutions to fill this gap. This project is based on multi-sensor coordination and fusion, from hyperspectral remote laser to smart glasses, artificial algorithms, and suspect identification and tracking. One of these sensors is dedicated to threat detection (large weapon or explosive belt) using the clothing of pedestrians by means of an active microwave component. This project is referred to as MIC (Microwave Imaging Curtain), also supported by the French SGDSN (General Secretariat of Defense and National Security), and utilizes a radar system capable of generating 3D images in real-time to address non-checkpoint detection of explosives and firearms. The project, led by ONERA (France), is based on a radar imaging system developed by the Fraunhofer FHR institute, using a MIMO architecture with an Ultra-Wide Band waveform. Although high-resolution 3D microwave imaging is already being used in expensive body scanners to detect firearms concealed under clothing, MIC’s innovative approach lies in utilizing a high-resolution 3D imaging device that can detect larger dangerous objects carried by moving individuals at a longer range, in addition to providing discrete detection in pedestrian flow. Automatic detection and classification of these dangerous objects is carried out on 3D radar images using a deep-learning network. This paper will outline the project’s objectives and constraints, as well as the design, architecture, and performance of the final system. Additionally, it will present real-time imaging results obtained during a live demonstration in a relevant environment.
Dual-Stream Spatiotemporal Networks with Feature Sharing for Monitoring Animals in the Home Cage
Authors: Nwokedi Ezechukwu Israel , Bains Rasneer Sonia , Bidaut Luc , Ye Xujiong , Wells Sara , Brown James M.
Published: November 2023

This paper presents a spatiotemporal deep learning approach for mouse behavioral classification in the home-cage. Using a series of dual-stream architectures with assorted modifications for optimal performance, we introduce a novel feature sharing approach that jointly processes the streams at regular intervals throughout the network. The dataset in focus is an annotated, publicly available dataset of a singly-housed mouse. We achieved even better classification accuracy by ensembling the best performing models; an Inception-based network and an attention-based network, both of which utilize this feature sharing attribute. Furthermore, we demonstrate through ablation studies that for all models, the feature sharing architectures consistently outperform the conventional dual-stream having standalone streams. In particular, the inception-based architectures showed higher feature sharing gains with their increase in accuracy anywhere between 6.59% and 15.19%. The best-performing models were also further evaluated on other mouse behavioral datasets.