bluuebunny/crossref_metadata_2025 huggingface dataset:
Predictors of mental well-being over the first lockdown period due to the COVID-19 pandemic in France. A repeated cross-sectional study
Authors: Barbalat Guillaume , Tanguy Melac Audrey , Zante Elodie , Haesebaert Frédéric , Franck Nicolas
Published: August 2023

Introduction

Numerous studies have investigated the positive and negative effects of potential predictors of well-being during lockdowns due to COVID-19. Yet, little is known on whether these effects significantly changed with time spent in lockdown. In the current study, we described the association of mental well-being with a large number of background characteristics (e.g., socio-demographic or health-related factors), COVID-related factors, and coping strategies, over the duration of the first lockdown due to COVID-19 in France.

Methods

A nationwide online survey was conducted over 7 of the 8 weeks of the 1st lockdown in France, i.e., from 25 March 2020 to 10 May 2020. The level of mental well-being was reported using the Warwick-Edinburgh Mental Well-Being Scale (WEMWBS). We also measured various background characteristics (e.g., age, sex, education, health issues), COVID-related factors (e.g., health and economic risks, agreement with lockdown), and coping strategies. Our analytical strategy enabled us to disentangle effects aggregated over the study period from those that linearly vary with time spent in lockdown.

Results

Our final dataset included 18,957 participants. The level of mental well-being dropped gradually from the third to the eighth week of lockdown [49.7 (sd 7.9) to 45.5 (sd 10.6)]. Time in lockdown was associated with a decrease in well-being (for each additional 10 days of lockdown: B = −0.30, 95%CI: −0.62, −0.15). Factors that showed significantly negative and positive effects on well-being as time in lockdown progressed were (for each additional 10 days of lockdown): having current psychiatric problems (B = −0.37; 95%CI: −0.63, −0.04), worries about having access to personal protective equipment (B = −0.09; 95%CI: −0.18, −0.01), coping by having positive beliefs about the future of the pandemics (B = 0.29; 95%CI: 0.04, 0.62), being supported by neighbors (B = 0.24; 95%CI: 0.04, 0.44), and being involved in collective actions (B = 0.23; 95%CI: 0.04, 0.46).

Discussion

Participants from our sample saw a drop in their mental well-being throughout the first period of COVID-19 lockdown. Policymakers should be mindful of factors contributing to greater deterioration of mental well-being over time, such as having current psychiatric issues. Promoting collective actions and local support from neighbors may alleviate the deterioration of mental well-being over time.
Mysteries of Small Worms and How Their Arch Enemies Save Our Food
Authors: Rueda-Ramírez Diana , Class 2022 HU Scientific Writing
Published: August 2023

To produce enough food, we must protect our crops from pests that attack plants. Some of these pests are mysterious small worms called nematodes, wandering through the soil. While most nematodes are beneficial to plants, others can destroy whole crops. The most common weapons against destructive nematodes are also harmful to nature. We need more environmentally friendly tools to control these worms. Tiny spider-like creatures called mites are the nematodes’ arch enemies. Can mites be used to control nematode populations and protect crops? Scientists did experiments on tomato plants in a greenhouse. They added both harmful and helpful nematodes to check the effect of mites. The experiment showed that mites alone, and in combination with the beneficial nematodes, reduced the damage harmful nematodes caused to the plants. Future studies should determine how we can help mites and friendly nematodes to protect our crops and ensure our food supply!
Global Warming: Plants and Animals on the Move
Authors: Feeley Kenneth J. , Freeman Benjamin G.
Published: August 2023

Global warming is forcing many species to change where they live. As temperatures rise, some places will become too hot for the plants and animals that live there now. Species will migrate out of these hot areas and into other areas that used to be too cold for them. In some cases, species will not be able to move fast enough to escape rising temperatures, or there will not be enough places with suitable climates left for them to live in—increasing the risk that these species will become extinct. As global warming forces many plant and animal species to move around, or causes them to become extinct from certain areas, the types of species that we find around us will change, which will affect our lives.
A system science methodology develops a new composite highly predictable index of magnetospheric activity for the community: the whole-Earth index E(1)
Authors: Borovsky Joseph E. , Lao Christian J.
Published: August 2023

For community use, a new composite whole-Earth index E(1) and its matching composite solar wind driving function S(1) are derived. A system science methodology is used based on a time-dependent magnetospheric state vector and a solar wind state vector, with canonical correlation analysis (CCA) used to reduce the two state vectors to the two time-dependent scalars E(1)(t) and S(1)(t). The whole-Earth index E(1) is based on a diversity of measures via six diverse geomagnetic indices that will be readily available in the future: SML, SMU, Ap60, SYMH, ASYM, and PCC. The CCA-derived composite index has several advantages: 1) the new “canonical” geomagnetic index E(1) will provide a more powerful description of magnetospheric activity, a description of the collective behavior of the magnetosphere–ionosphere system. 2) The new index E(1) is much more accurately predictable from upstream solar wind measurements on Earth. 3) Indications are that the new canonical geomagnetic index E(1) will be accurately predictable even when as-yet-unseen extreme solar wind conditions occur. The composite solar wind driver S(1) can also be used as a universal driver function for individual geomagnetic indices or for magnetospheric particle populations. To familiarize the use of the new index E(1), its behavior is examined in different phases of the solar cycle, in different types of solar wind plasma, during high-speed stream-driven storms, during CME sheath-driven storms, and during superstorms. It is suggested that the definition of storms are the times when E(1) >1.
Seed quality improvement applications in black cumin seeds (Nigella sativa L.)
Authors: Ekren Sidika , Paylan Ismail Can , Gokcol Adem
Published: August 2023

The black cumin plant, which forms the research material, is a plant cultivated in many countries for various purposes. By eliminating the difficulties in seed germination, efficiency can be increased. Applications to improve seed quality include improving harvesting, drying and storage technologies, pre-sowing applications, seed processing and coating technologies. Among these applications, priming applications and seed coating methods occupy an important place. In previous studies on plants from the Ranunculaceae family, various pathogens of plant viruses have been identified. One of the viruses transmitted by seeds of the Ranunculaceae family is Cucumber mosaic virüs (CMV). The aim was to increase germination rates and to achieve early and uniform emergence of black cumin, which has a small seed size and whose embryos also show irregular germination. For this purpose, priming, chemical application and film coating and their combinations were used to determine and recommend the best method. In addition to these studies, black cumin seeds infected with CMV were determined by serological and molecular analysis methods and a series of applications were carried out to eliminate this viral factor from the seeds. As a result of the evaluations, the seeds showed the highest germination rate (91% and 93%, respectively) when priming+polymer+KNO3 and priming+polymer+GA3 were applied. It was found that both polymer application and priming application increased GA3 efficiency. Priming+polymer+GA3 application statistically allowed the seeds to reach the mean germination time (5.87 days) in the shortest time. In contrast, the application of the polymer alone and the applications in combination with the polymer caused the seeds to reach the mean germination time longer than the control. The chemical substances and applications that successfully eliminated the cmv factor in black cumin seeds were determined. It was found that the most successful applications were hot water and ozone applications.
Pharmacokinetics of mebendazole in plasma and cerebrospinal fluid following a single oral dose in healthy dogs
Authors: Yanke Amy B. , Day Kendall E. , Taylor Amanda R. , Cruz-Espindola Crisanta , Boothe Dawn M.
Published: August 2023

Novel therapies are needed for treatment of gliomas. Mebendazole previously demonstrated anti-neoplastic effects on canine glioma cell lines at in vitro mean inhibitory concentrations (IC50) of 10 ng/mL. Our study aimed to titrate the oral dose of mebendazole necessary to achieve concentrations ≥10 ng/mL in cerebrospinal fluid (CSF) of healthy dogs. We hypothesized that an oral dose up to 200 mg/kg would be necessary. Phase one was a dose titration study using a total of 6 mixed breed dogs that described dose vs. plasma concentrations for 72 h after single oral dosing of either 50 mg/kg (n = 2), 100 mg/kg (n = 2), or 200 mg/kg (n = 2). Based on phase one, phase two dogs (total of 9) received 100 mg/kg (n = 4) or 200 mg/kg (n = 5) orally and blood samples were collected intermittently for 60 h with CSF samples collected intermittently for 24 h. Mebendazole was quantitated in plasma and CSF using high performance liquid chromatography. Median peak plasma concentrations (Cmax) were reached at 7 ± 2 h (100 mg/kg) of 220 ng/mL (81, 283) and at 15 ± 4 h (200 mg/kg) of 147 ng/ml (112, 298). The respective area under the curve (AUC: ng/ml/h) reported as a median was 2,119 (1,876, 3,288) vs. 3,115 (1,559, 4,972). Median plasma concentrations (ng/ml) for 100 vs. 200 mg/kg were 47 (32, 52) vs. 65 (35, 104), respectively. For CSF, the median value for Cmax (at 100 mg/kg vs. 200 mg/kg) was 8 (2, 28) vs. 21 (12, 27) and AUC was 87 (22, 157) vs. 345 (92, 372), respectively. Relative bioavailability in CSF vs. plasma was 4 to 10%. Although several animals demonstrated clinical signs indicative of gastrointestinal upset [i.e., vomiting (n = 2), diarrhea (n = 2), or both (n = 1)], these events were not considered serious. The in vitro IC50 for gliomas can be reached in CSF at 100 mg/kg (n = 1), however a 200 mg/kg dose yielded more consistent concentrations.
Generation of Achievable Three-Dimensional Trajectories for Autonomous Wheeled Vehicles via Tracking Differentiators
Authors: Krasnova Svetlana A. , Kokunko Julia G. , Kochetkov Sergey A. , Utkin Victor A.
Published: August 2023

Planning an achievable trajectory for a mobile robot usually consists of two steps: (i) finding a path in the form of a sequence of discrete waypoints and (ii) transforming this sequence into a continuous and smooth curve. To solve the second problem, this paper proposes algorithms for automatic dynamic smoothing of the primary path using a tracking differentiator with sigmoid corrective actions. Algorithms for setting the gains of the differentiator are developed, considering a set of design constraints on velocity, acceleration, and jerk for various mobile robots. When tracking a non-smooth primary path, the output variables of the differentiator generate smooth trajectories implemented by a mechanical plant. It is shown that the tracking differentiator with a different number of blocks also generates derivatives of the smoothed trajectory of any required order, taking into account the given constraints. Unlike standard analytical methods of polynomial smoothing, the proposed algorithm has a low computational load. It is easily implemented in real time on the on-board computer. In addition, simple methods for modeling a safety corridor are proposed, taking into account the dimensions of the vehicle when planning a polygon with stationary obstacles. Confirming results of numerical simulation of the developed algorithms are presented.
Mapping Shrimp Pond Dynamics: A Spatiotemporal Study Using Remote Sensing Data and Machine Learning
Authors: Bellam Pavan Kumar , Gumma Murali Krishna , Panjala Pranay , Mohammed Ismail , Suzuki Aya
Published: August 2023

Shrimp farming and exporting is the main income source for the southern coastal districts of the Mekong Delta. Monitoring these shrimp ponds is helpful in identifying losses incurred due to natural calamities like floods, sources of water pollution by chemicals used in shrimp farming, and changes in the area of cultivation with an increase in demand for shrimp production. Satellite imagery, which is consistent with good spatial resolution and helpful in providing frequent information with temporal imagery, is a better solution for monitoring these shrimp ponds remotely for a larger spatial extent. The shrimp ponds of Cai Doi Vam township, Ca Mau Province, Viet Nam, were mapped using DMC-3 (TripleSat) and Jilin-1 high-resolution satellite imagery for the years 2019 and 2022. The 3 m spatial resolution shrimp pond extent product showed an overall accuracy of 87.5%, with a producer’s accuracy of 90.91% (errors of omission = 11.09%) and a user’s accuracy of 90.91% (errors of commission = 11.09%) for the shrimp pond class. It was noted that 66 ha of shrimp ponds in 2019 were observed to be dry in 2022, and 39 ha of other ponds had been converted into shrimp ponds in 2022. The continuous monitoring of shrimp ponds helps achieve sustainable aquaculture and acts as crucial input for the decision makers for any interventions.
Enhancing Speech Emotions Recognition Using Multivariate Functional Data Analysis
Authors: Saumard Matthieu
Published: August 2023

Speech Emotions Recognition (SER) has gained significant attention in the fields of human–computer interaction and speech processing. In this article, we present a novel approach to improve SER performance by interpreting the Mel Frequency Cepstral Coefficients (MFCC) as a multivariate functional data object, which accelerates learning while maintaining high accuracy. To treat MFCCs as functional data, we preprocess them as images and apply resizing techniques. By representing MFCCs as functional data, we leverage the temporal dynamics of speech, capturing essential emotional cues more effectively. Consequently, this enhancement significantly contributes to the learning process of SER methods without compromising performance. Subsequently, we employ a supervised learning model, specifically a functional Support Vector Machine (SVM), directly on the MFCC represented as functional data. This enables the utilization of the full functional information, allowing for more accurate emotion recognition. The proposed approach is rigorously evaluated on two distinct databases, EMO-DB and IEMOCAP, serving as benchmarks for SER evaluation. Our method demonstrates competitive results in terms of accuracy, showcasing its effectiveness in emotion recognition. Furthermore, our approach significantly reduces the learning time, making it computationally efficient and practical for real-world applications. In conclusion, our novel approach of treating MFCCs as multivariate functional data objects exhibits superior performance in SER tasks, delivering both improved accuracy and substantial time savings during the learning process. This advancement holds great potential for enhancing human–computer interaction and enabling more sophisticated emotion-aware applications.
Triphenylamine-Based Helical Polymer for Flexible Memristors
Authors: Li Jinyong , Gong Minglei , Wang Xiaoyang , Fan Fei , Zhang Bin
Published: August 2023

Flexible nonvolatile memristors have potential applications in wearable devices. In this work, a helical polymer, poly (N, N-diphenylanline isocyanide) (PPIC), was synthesized as the active layer, and flexible electronic devices with an Al/PPIC/ITO architecture were prepared on a polyethylene terephthalate (PET) substrate. The device showed typical nonvolatile rewritable memristor characteristics. The high-molecular-weight helical structure stabilized the active layer under different bending degrees, bending times, and number of bending cycles. The memristor was further employed to simulate the information transmission capability of neural fibers, providing new perspectives for the development of flexible wearable memristors and biomimetic neural synapses. This demonstration highlights the promising possibilities for the advancement of artificial intelligence skin and intelligent flexible robots in the future.
Cognitive Neuroimaging Studies on Poverty and Socioeconomic Status Differences in Children and Families across the World: Translational Insights for Next Decade’s Policy, Health, and Education
Authors: Kamgang Shanine , Lord Meghan , Mishra Aanchal , D’Angiulli Amedeo
Published: August 2023

This systematic review and meta-analysis of global peer-reviewed neuroimaging findings preliminarily assessed the magnitude of effect sizes (ES) of the influences of family poverty/low socioeconomic status (SES) on children’s neurocognition and whether these were consistently detrimental. The literature search (Web of Science; PUBMED; MEDLINE: PSYCNET; GOOGLE SCHOLAR; SCIENCEDIRECT) included 66 studies from 1988 to 2022; 85% of the studies included were conducted in Western, high-income nations. Bayesian models, corrected by study sizes and variances, revealed ESs were heterogeneous across countries and measurements. Bayesian and standard hypothesis testing indicated high and low SES groups showed similar behavioral performances in neuroimaging-concurrent tasks. Except for Magnetic Resonance Imaging studies, ESs were small-to-intermediate with modest reliability. The strongest ESs were found for attention, mathematical performance, language, and cortical volume, followed by intermediate ESs for reading and socioemotional processes. Differentials in resting activity and connectivity, working memory, and executive functions yielded small effects. A bibliometric analysis showed a significant proportion of the literature attributed neurocognitive deficits to low SES, despite overlooking the under-representativity of non-Western and low-income countries, potential influences of racial/ethnic differences, and measurement sensitivity/specificity discrepancies. To reach United Nations Sustainable Development Goals, policies and interventions should consider regional, structural, or environmental ecologies beyond the individual, critically probing implicit deficit attributions.
SLAMF7 as a Promising Immunotherapeutic Target in Multiple Myeloma Treatments
Authors: Chu Emily , Wu Jian , Kang Stacey S. , Kang Yubin
Published: August 2023

Multiple myeloma (MM) is a common hematological malignancy that has fostered several new therapeutic approaches to combat newly diagnosed or relapsed MM. While the field has advanced over the past 2 decades, the majority of patients will develop resistance to these treatments, causing the need for new therapeutic targets. SLAMF7 is an attractive therapeutic target in multiple myeloma, and a monoclonal antibody that targets SLAMF7 has shown consistent beneficial outcomes in clinical trials to date. In this review, we will focus on the structure and regulation of SLAMF7 and its mechanism of action. The most recent clinical trials will be reviewed to further understand the clinical implications and improve the prognosis of MM. Furthermore, the efficacy of anti-SLAMF7 monoclonal antibodies combined with standard therapies and possible resistance mechanisms will be discussed. This review aimed to provide a detailed summary of the role of SLAMF7 in the pathogenesis of patients with MM and the rationale for further investigation into SLAMF7-mediated molecular pathways associated with MM development.
An Overview of Endometrial Cancer with Novel Therapeutic Strategies
Authors: Kuhn Theresa M. , Dhanani Saeeda , Ahmad Sarfraz
Published: August 2023

Endometrial cancer (EC) stands as the most prevalent gynecologic malignancy. In the past, it was classified based on its hormone sensitivity. However, The Cancer Genome Atlas has categorized EC into four groups, which offers a more objective and reproducible classification and has been shown to have prognostic and therapeutic implications. Hormonally driven EC arises from a precursor lesion known as endometrial hyperplasia, resulting from unopposed estrogen. EC is usually diagnosed through biopsy, followed by surgical staging unless advanced disease is expected. The typical staging consists of a hysterectomy with bilateral salpingo-oophorectomy and sentinel lymph node biopsies, with a preference placed on a minimally invasive approach. The stage of the disease is the most significant prognostic marker. However, factors such as age, histology, grade, myometrial invasion, lymphovascular space invasion, tumor size, peritoneal cytology, hormone receptor status, ploidy and markers, body mass index, and the therapy received all contribute to the prognosis. Treatment is tailored based on the stage and the risk of recurrence. Radiotherapy is primarily used in the early stages, and chemotherapy can be added if high-grade histology or advanced-stage disease is present. The risk of EC recurrence increases with advances in stage. Among the recurrences, vaginal cases exhibit the most favorable response to treatment, typically for radiotherapy. Conversely, the treatment of widespread recurrence is currently palliative and is best managed with chemotherapy or hormonal agents. Most recently, immunotherapy has emerged as a promising treatment for advanced and recurrent EC.
Cyberknife Radiosurgery for Prostate Cancer after Abdominoperineal Resection (CYRANO): The Combined Computer Tomography and Electromagnetic Navigation Guided Transperineal Fiducial Markers Implantation Technique
Authors: Vavassori Andrea , Mauri Giovanni , Mazzola Giovanni Carlo , Mastroleo Federico , Bonomo Guido , Durante Stefano , Zerini Dario , Marvaso Giulia , Corrao Giulia , Ferrari Elettra Dorotea , Rondi Elena , Vigorito Sabrina , Cattani Federica , Orsi Franco , Jereczek-Fossa Barbara Alicja
Published: August 2023

In this technical development report, we present the strategic placement of fiducial markers within the prostate under the guidance of computed tomography (CT) and electromagnetic navigation (EMN) for the delivery of ultra-hypofractionated cyberknife (CK) therapy in a patient with localized prostate cancer (PCa) who had previously undergone chemo-radiotherapy for rectal cancer and subsequent abdominoperineal resection due to local recurrence. The patient was positioned in a prone position with a pillow under the pelvis to facilitate access, and an electromagnetic fiducial marker was placed on the patient’s skin to establish a stable position. CT scans were performed to plan the procedure, mark virtual points, and simulate the needle trajectory using the navigation system. Local anesthesia was administered, and a 21G needle was used to place the fiducial markers according to the navigation system information. A confirmatory CT scan was obtained to ensure proper positioning. The implantation procedure was safe, without any acute side effects such as pain, hematuria, dysuria, or hematospermia. Our report highlights the ability to use EMN systems to virtually navigate within a pre-acquired imaging dataset in the interventional room, allowing for non-conventional approaches and potentially revolutionizing fiducial marker positioning, offering new perspectives for PCa treatment in selected cases.
Decoding Hip Muscle Activation: A Comparative Electromyographic Analysis of Turn-Out Bent Knee Pulse and Single-Leg Banded Glute Bridge Exercises in Healthy Female Subjects
Authors: Gasibat Qais , Alexe Cristina Ioana , Raveica Gabriela , Tohănean Dragoș Ioan , Vasilios Koronas , Alexe Dan Iulian
Published: August 2023

Individuals with lower extremity injuries and back pain may exhibit weakness and stiffness in important muscles such as the gluteus maximus and external hip rotators. To aid clinicians in understanding the impact of exercises on factors like stability, endurance, and strength, electromyography (EMG) examination can be employed to monitor muscle activation. In this investigation, the EMG activity of the gluteus maximus and medius were compared between two exercises: the turn-out bent knee pulse and the single-leg banded glute bridge. The study enrolled a group of 64 healthy young women, aged 19 to 24 years. The raw data collected were standardized and represented as a percentage of maximum voluntary isometric contraction (%MVIC). To assess the reliability of the EMG recordings, the test–retest analysis was performed using the intraclass correlation coefficient (ICC3,1). Statistical analysis involved conducting a one-way ANOVA to compare the EMG amplitudes between the two exercises. Remarkably, the results demonstrated a significantly higher EMG signal amplitude during the single-leg banded glute bridge exercise (mean ± SD: 90 ± 28% MVIC) when compared to the turn-out bent knee pulse exercise (mean ± SD: 70 ± 15% MVIC) (F = 16.584, p = 0.001). The study found that the single-leg banded glute bridge exercise had a significantly higher EMG signal amplitude compared to the turn-out bent knee pulse exercise. This suggests that the single-leg banded glute bridge exercise may be more effective in strengthening the gluteus maximus and medius muscles. Overall, this study highlights the importance of targeted muscle training in rehabilitation protocols and the use of EMG examination to monitor muscle activation.
Supplementary Control of Conventional Coordinated Control for 1000 MW Ultra-Supercritical Thermal Power Plant Using One-Step Ahead Control
Authors: Choi Hyuk , Choi Yeongseok , Moon Un-Chul , Lee Kwang Y.
Published: August 2023

The intermittence of renewable energy sources increases the importance of the effective load-tracking ability of power plants. Coordinated control between boiler and turbine systems is the uppermost layer of a thermal power plant control to follow the load demand. In this paper, a supplementary controller is proposed based on the One-Step Ahead strategy for coordinated control of thermal power plants. After a plant model is developed offline from a step response test, the optimized control of the One-Step Ahead strategy is applied to the boiler feed-forward (BFF) signal to control the electric power output and the main steam pressure simultaneously. Simulation with a 1000 MW ultra-supercritical (USC) once-through type power plant is performed. The results show that the error of Mega-Watt Output (MWO) was reduced to 78~95%, and settling time was reduced to 64~79% from conventional coordinated control by adding the proposed supplementary controller.
Impact of Grid Unbalances on Electric Vehicle Chargers
Authors: Alwahaibi Sultan , Wheeler Patrick , Rivera Marco , Ahmed Md Rishad
Published: August 2023

There is a global trend to reduce emissions from cars through the adoption of other alternatives, such as electric vehicles (EVs). The increasing popularity of EVs has led to a growing demand for electric vehicle chargers. EV chargers are essential for charging the batteries of EVs. Since the EV charger stays connected to the grid for long periods of time to charge the EV battery, it must be able to handle disturbances in the power grid. The goal of this paper is to present an overview of the impact of grid events on EV battery chargers. As well as the impact of grid unbalances on EV chargers, this paper also provides an overview of the impact of grid faults on other, similar power electronics interfaced resources such as PV and energy storage systems.
Inter-Zone Optimal Scheduling of Rural Wind–Biomass-Hydrogen Integrated Energy System
Authors: Zhang Mingguang , Yu Shuai , Li Hongyi
Published: August 2023

To solve the problems of low utilization of biomass and uncertainty and intermittency of wind power (WP) in rural winter, an interval optimization model of a rural integrated energy system with biogas fermentation and electrolytic hydrogen production is constructed in this paper. Firstly, a biogas fermentation kinetic model and a biogas hydrogen blending model are developed. Secondly, the interval number is used to describe the uncertainty of WP, and an interval optimization scheduling model is developed to minimize daily operating cost. Finally, a rural integrated energy system in Northeast China is taken as an example, and a sensitivity analysis of electricity price, gas production, and biomass price is conducted. The simulation results show that the proposed strategy can significantly reduce the wind abandonment rate and improve the economy by 3.8–22.3% compared with conventional energy storage under optimal dispatch.
Smart Urban Wind Power Forecasting: Integrating Weibull Distribution, Recurrent Neural Networks, and Numerical Weather Prediction
Authors: Shirzadi Navid , Nasiri Fuzhan , Menon Ramanunni Parakkal , Monsalvete Pilar , Kaifel Anton , Eicker Ursula
Published: August 2023

The design, operational planning, and integration of wind power plants with other renewables and the grid face challenges attributed to the intermittent nature of wind power generation. Addressing this issue necessitates the development of a smart wind power (and in particular wind speed) forecasting approach. This is a complex task due to substantial fluctuations in wind speed. To overcome the inherent stochastic nature of wind speed and mitigate related challenges, traditionally, numerical weather prediction (NWP) models are employed for wind speed forecasting. However, the applicability of NWP models is limited to short-term forecasting due to their computational constraints. In this study, a hybrid AI-based approach is proposed to improve forecast accuracy over a 48 h horizon for the city of Montreal. The results demonstrate that by integrating the probability distribution of wind speed with a deep learning model, the forecasted values align closely with the observed values in terms of seasonality and trend, exhibiting enhanced accuracy. Evaluation metrics reveal a substantial reduction in the root mean squared error (13–31%) across three prediction horizons (summer, fall, and winter) compared to a single long, short-term memory model. Furthermore, integrating the improved model with the numerical weather prediction model yields increased accuracy and decreased error compared to the LSTM–Weibull model.
Characteristics and Key Controlling Factors of the Interbedded-Type Shale-Oil Sweet Spots of Qingshankou Formation in Changling Depression
Authors: Yang Liang , Xing Jilin , Xue Wei , Zheng Lehua , Wang Rui , Xiao Dianshi
Published: August 2023

Different types of shale-oil sweet spots have developed and are vertically stacked in multiple layers of the Qingshankou Formation in the Changling Depression, southern Songliao Basin. Furthermore, this area lacks a classification standard in the optimization of its shale-oil sweet-spot area/layers. Through relevant tests of the region in question’s organic geochemistry, physical properties, oiliness, and pore structure, this paper investigates the formation elements of shale-oil sweet spots. In addition, summaries of its enrichment-controlling factors are given, and the classification standard and evaluation method for understanding the comprehensive sweet spots of the interbedded-type shale oil are then established. The interbedded-type shale oil is enriched in the Qingshankou I Member in the Changling Depression, and it has the features of medium-to-high maturity, the development of inorganic pores and micro-cracks, as well as higher oil saturation and better oil mobility. The sweet-spot enrichment is affected by lamina type, sedimentary facies, maturity, and sand–shale combinations. Both silty-laminated felsic shale and argillaceous-laminated felsic shale, which are developed in semi-deep lakes, are favorable shale lithofacies as they have excellent brittleness and oil mobility. The high maturity and the interbedded combination of sand and shale ensure the efficient production of shale oil, among which the pure-shale section issues a continuous contribution to the production process. Combined with oil testing, sweet-spot classification standards and a comprehensive evaluation of interbedded-type shale oil were established. An area of 639.2 km2 for the interbedded-type shale-oil sweet spots was preferred, among which type I (193 km2) belonged to the combination of “good shale and good siltstone interlayers adjacent”, and type II belonged to “good shale and medium siltstone interlayers adjacent” combination (which have long-term low and stable production prospects). The research provides theoretical guidance on the effective exploration and development of the shale oil of the Qingshankou Formation in the Changling Depression.
Improving Torque Analysis and Design Using the Air-Gap Field Modulation Principle for Permanent-Magnet Hub Machines
Authors: Sun Yuhua , Bianchi Nicola , Ji Jinghua , Zhao Wenxiang
Published: August 2023

The Double Permanent Magnet Vernier (DPMV) machine is well known for its high torque density and magnet utilization ratio. This paper aims to investigate the torque generation mechanism and its improved design in DPMV machines for hub propulsion based on the field modulation principle. Firstly, the topology of the proposed DPMV machine is introduced, and a commercial PM machine is used as a benchmark. Secondly, the rotor PM, stator PM, and armature magnetic fields are derived and analyzed considering the modulation effect, respectively. Meanwhile, the contribution of each harmonic to average torque is pointed out. It can be concluded that the 7th-, 12th-, 19th- and 24th-order flux density harmonics are the main source of average torque. Thanks to the multi-working harmonic characteristics, the average torque of DPMV machines has significantly increased by 31.8% compared to the counterpart commercial PM machine, while also reducing the PM weight by 75%. Thirdly, the auxiliary barrier structure and dual three-phase winding configuration are proposed from the perspective of optimizing the phase and amplitude of working harmonics, respectively. The improvements in average torque are 9.9% and 5.4%, correspondingly.
LCA and C-LCC Indicator as Tools for Sodium-Ion Batteries’ Eco-Design
Authors: Carvalho Maria Leonor , Cusenza Maria Anna , Mela Giulio , Temporelli Andrea , Quinzeni Irene , Girardi Pierpaolo
Published: August 2023

Sodium-ion batteries are considered promising alternatives to lithium-ion technology; however, the diffusion on a commercial scale is hindered by the struggle to identify materials with high electrochemical performances. Studies available in the literature are mainly focused on electrochemical performance and neglect aspects related to the environmental sustainability. In fact, the current state-of-the-art (presented in this study) shows that life cycle assessment (LCA) studies related to the production processes of electrode materials for Na-ion batteries are still very limited. The LCA methodology applied during the development of a technology phase can constitute a valid support for an eco-oriented design and, therefore, to the choice of solutions characterized by a lower environmental impact with the same electrochemical performance. In this context, a life cycle-based environmental–economic assessment was performed to evaluate the environmental impacts of the production process of cathode and anode materials for sodium-ion batteries. The study is focused on the cathodic active material Na0.66MnO2, considering two synthesis paths, and the anodic material consisting of tin (Sn) and Sn-carbon nanofiber (Sn-Cn) active material, binder, and other additives. Results illustrate the environmental performance of the different materials and constitute a useful input for their selection within an eco-design view.
Green Hydrogen: Resources Consumption, Technological Maturity, and Regulatory Framework
Authors: Rey Jesús , Segura Francisca , Andújar José
Published: August 2023

Current climate crisis makes the need for reducing carbon emissions more than evident. For this reason, renewable energy sources are expected to play a fundamental role. However, these sources are not controllable, but depend on the weather conditions. Therefore, green hydrogen (hydrogen produced from water electrolysis using renewable energies) is emerging as the key energy carrier to solve this problem. Although different properties of hydrogen have been widely studied, some key aspects such as the water and energy footprint, as well as the technological development and the regulatory framework of green hydrogen in different parts of the world have not been analysed in depth. This work performs a data-driven analysis of these three pillars: water and energy footprint, technological maturity, and regulatory framework of green hydrogen technology. Results will allow the evaluation of green hydrogen deployment, both the current situation and expectations. Regarding the water footprint, this is lower than that of other fossil fuels and competitive with other types of hydrogen, while the energy footprint is higher than that of other fuels. Additionally, results show that technological and regulatory framework for hydrogen is not fully developed and there is a great inequality in green hydrogen legislation in different regions of the world.
Reactive Transport Modeling of Chemical Stimulation Processes for an Enhanced Geothermal System (EGS)
Authors: Ma Li , Cui Zhenpeng , Feng Bo , Qi Xiaofei , Zhao Yuandong , Zhang Chaoyu
Published: August 2023

An enhanced geothermal system is a kind of artificial geothermal system, which can economically exploit geothermal energy from deep thermal rock mass with low permeability by artificially created geothermal reservoirs. Chemical stimulation refers to a reservoir permeability enhancement method that injects a chemical stimulant into the fractured geothermal reservoir to improve the formation permeability by dissolving minerals. In this study, a reactive solute transport model was established based on TOUGHREACT to find out the effect of chemical stimulation on the reconstruction of a granite-hosted enhanced geothermal system reservoir. The results show that chemical stimulation with mud acid as a stimulant can effectively improve the permeability of fractures near the injection well, the effective penetration distance can reach more than 20 m after 5 days. The improvement of porosity and permeability was mainly caused by the dissolution of feldspar and chlorite. The permeability enhancement increased with the injection flow rate and HF concentration in the stimulant, which was weakly affected by the change in injection temperature. The method of chemical enhancement processes can provide a reference for subsequent enhanced geothermal system engineering designs.
Can a CO2 Tax Be Socially Just? Analysis of the Social Distribution Effects of the German CO2 Taxation
Authors: Venjakob Maike , Wagner Oliver , Schnurr Birte
Published: August 2023

Rising energy costs have led to increased discussion about the social impact of the energy transition in Germany in recent years. In 2021, a gradually increasing CO2 tax was introduced. This paper analyzes the question of whether a CO2 tax can be socially just. Using data analysis and desk research, correlations between income and energy consumption in Germany are shown. In a short analysis, it is investigated which additional burdens different types of private households have to expect in the coming years due to the introduction of CO2 pricing on energy. In particular, the introduction of a per capita flat rate fed by CO2 tax revenues could be a suitable way to reduce the burden on low-income households.
Modeling a Combustion Chamber of a Pulse Detonation Engine
Authors: Smirnov Nickolay , Nikitin Valeriy , Mikhalchenko Elena , Stamov Lyuben
Published: August 2023

This paper presents the results of numerical simulation of a model combustion chamber of a pulse detonation engine using the authors’ developed software package. The main goal of the present study is to numerically investigate the effects of cyclic operation of pulse detonating chambers, as the former studies have been limited to simulating one cycle. To achieve this goal, a new mathematical model for heavy gas was applied simulating condensed fuel phase, which made it possible to accelerate computations and simulate multi-cycle operation of the device. Distributions of such characteristics as temperature, pressure, velocity, concentrations of reagents, intensity of reactions, and thrust force are obtained. A two-stage kinetic model of propellant combustion is proposed. Attention is paid to the main stages of PDE operation: filling of the chamber with reagents, ignition and transition to detonation, products exhaust, purification, and cooling the chamber with a neutral gas. The simulation of the working cycle with the shortest period for the specified system parameters was carried out, the execution time of each stage was obtained, and an assessment was carried out to minimize the main stages of the work cycle. Numerical results demonstrated that the characteristics of the engine cycle are stabilized already in the second cycle: the thrust in the first cycle differs from the thrust in the second by 5%, in the third from the second by 1%. Moreover, details of thrust dynamics in the second and third cycles were studied.
Alteration of Mitochondrial Transcript Expression in Arabidopsis thaliana Using a Custom-Made Library of Pentatricopeptide Repeat Proteins
Authors: Vincis Pereira Sanglard Lilian , Small Ian D. , Colas des Francs-Small Catherine
Published: August 2023

Pentatricopeptide repeat (PPR) proteins are considered a potential tool for manipulating organelle gene expression in plants because they can recognise a wide range of different RNA sequences, and the molecular basis for this sequence recognition is partially known and understood. A library of redesigned PPR proteins related to restorer-of-fertility proteins was created and transformed into plants in order to target mitochondrial transcripts. Ninety different variants tested in vivo showed a wide range of phenotypes. One of these lines, which displayed slow growth and downward curled leaves, showed a clear reduction in complex V. The phenotype was due to a specific cleavage of atp1 transcripts induced by a modified PPR protein from the library, validating the use of this library as a source of mitochondrial ‘mutants’. This study is a step towards developing specific RNA targeting tools using PPR proteins that can be aimed at desired targets.
CBD Inhibits In Vivo Development of Human Breast Cancer Tumors
Authors: García-Morales Lázaro , Mendoza-Rodríguez Mónica G. , Tapia Ramírez José , Meza Isaura
Published: August 2023

Inflammation is a critical component of cancer development. Previously, we showed in vitro that IL-1β treatment of non-invasive human breast cancer MCF-7 cells promoted their transition to a malignant phenotype (6D cells). This epithelial–mesenchymal transition was reverted by exposure to cannabidiol (CBD). We show in a murine model that subcutaneous inoculation of 6D cells induced formation and development of tumors, the cells of which keep traits of malignancy. These processes were interrupted by administration of CBD under two schemes: therapeutic and prophylactic. In the therapeutic scheme, 6D cells inoculated mice developed tumors that reached a mean volume of 540 mm3 at 45 days, while 50% of CBD-treated mice showed gradual resorption of tumors. In the prophylactic scheme, mice were pre-treated for 15 days with CBD before cells inoculation. The tumors formed remained small and were eliminated under continuous CBD treatment in 66% of the animals. Histological and molecular characterization of tumors, from both schemes, revealed that CBD-treated cells decreased the expression of malignancy markers and show traits related with apoptosis. These results confirm that in vivo CBD blocks development of breast cancer tumors formed by cells induced to malignancy by IL-1β, endorsing its therapeutic potential for cancer treatment.
Protective Effects of Pituitary Adenylate-Cyclase-Activating Polypeptide on Retinal Vasculature and Molecular Responses in a Rat Model of Moderate Glaucoma
Authors: Patko Evelin , Szabo Edina , Vaczy Alexandra , Molitor Dorottya , Tari Eniko , Li Lina , Csutak Adrienne , Toth Gabor , Reglodi Dora , Atlasz Tamas
Published: August 2023

Despite the high probability of glaucoma-related blindness, its cause is not fully understood and there is no efficient therapeutic strategy for neuroprotection. Vascular factors have been suggested to play an important role in glaucoma development and progression. Previously, we have proven the neuroprotective effects of pituitary adenylate-cyclase-activating polypeptide (PACAP) eye drops in an inducible, microbeads model in rats that is able to reproduce many clinically relevant features of human glaucoma. In the present study, we examined the potential protective effects of PACAP1-38 on the retinal vasculature and the molecular changes in hypoxia. Ocular hypertension was induced by injection of microbeads into the anterior chamber, while control rats received PBS. PACAP dissolved in vehicle (1 µg/drop) or vehicle treatment was started one day after the injections for four weeks three times a day. Retinal degeneration was assessed with optical coherence tomography (OCT), and vascular and molecular changes were assessed by immunofluorescence labeling. HIF1-α and VEGF-A protein levels were measured by Western blot. OCT images proved severe retinal degeneration in the glaucomatous group, while PACAP1-38 eye drops had a retinoprotective effect. Vascular parameters were deteriorated and molecular analysis suggested hypoxic conditions in glaucoma. PACAP treatment exerted a positive effect against these alterations. In summary, PACAP could prevent the severe damage to the retina and its vasculature induced by ocular hypertension in a microbeads model.
The Role of Toll-like Receptor-4 in Macrophage Imbalance in Lethal COVID-19 Lung Disease, and Its Correlation with Galectin-3
Authors: Pedicillo Maria Carmela , De Stefano Ilenia Sara , Zamparese Rosanna , Barile Raffaele , Meccariello Mario , Agostinone Alessio , Villani Giuliana , Colangelo Tommaso , Serviddio Gaetano , Cassano Tommaso , Ronchi Andrea , Franco Renato , Pannone Paola , Zito Marino Federica , Miele Francesco , Municinò Maurizio , Pannone Giuseppe
Published: August 2023

To the current data, there have been 6,955,141 COVID-19-related deaths worldwide, reported to WHO. Toll-like receptors (TLRs) implicated in bacterial and virus sensing could be a crosstalk between activation of persistent innate-immune inflammation, and macrophage’s sub-population alterations, implicated in cytokine storm, macrophage over-activation syndrome, unresolved Acute Respiratory Disease Syndrome (ARDS), and death. The aim of this study is to demonstrate the association between Toll-like-receptor-4 (TLR-4)-induced inflammation and macrophage imbalance in the lung inflammatory infiltrate of lethal COVID-19 disease. Twenty-five cases of autopsy lung tissues were studied by digital pathology-based immunohistochemistry to evaluate expression levels of TLR-4 (CD 284), pan-macrophage marker CD68 (clone KP1), sub-population marker related to alveolar macrophage Galectin-3 (GAL-3) (clone 9C4), and myeloid derived CD163 (clone MRQ-26), respectively. SARS-CoV-2 viral persistence has been evaluated by in situ hybridation (ISH) method. This study showed TLR-4 up-regulation in a subgroup of patients, increased macrophage infiltration in both Spike-1(+) and Spike-1(−) lungs (p < 0.0001), and a macrophage shift with important down-regulation of GAL-3(+) alveolar macrophages associated with Spike-1 persistence (p < 0.05), in favor of CD163(+) myeloid derived monocyte-macrophages. Data show that TLR-4 expression induces a persistent activation of the inflammation, with inefficient resolution, and pathological macrophage shift, thus explaining one of the mechanisms of lethal COVID-19.