bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluating the Color Preferences for Elderly Depression in the United Arab Emirates
Authors: Jung Chuloh , Mahmoud Naglaa Sami Abdelaziz , El Samanoudy Gamal , Al Qassimi Nahla
Published: February 2022

The elderly are more prone to develop depression from physical, psychological, and economic changes, and 25.7% of the United Arab Emirates’ (UAE) elderly population suffer from depression. Color therapy is a widely accepted treatment to solve the depressive symptoms of the elderly. The color preference of the Seniors’ Happiness Centre—in Ajman UAE—a residential space for the elderly, could improve the quality of life, including depression symptoms. This paper explored the relationship between the color preference of the resident bedroom space and the depressive symptoms. As a methodology, using color images as stimuli, the physiological and psychological responses of the 86 elderly participants to the proposed color preference of the resident bedroom interiors—observed through a viewing box to simulate 3D space perception—were compared and analyzed to investigate the relationship between the color preference and depression by a survey with the Geriatric Depression Scale (GDS) and Electroencephalogram (EEG) measurement. The results showed that the elderly’s preference for warm colors is higher than that of cold colors, and each room needs a different color scheme because the elderly, 65 and above, have different visual characteristics. There was no significant difference between the left and right alpha wave values of the prefrontal cortex of the participant group. The main reason is that the brain waves are minute electrical signals and appear different from person to person. The color scheme on one side of the wall with increased saturation seemed to improve depressive symptoms effectively. It was found that psychologically, healthy elderly reacted positively to the single-color scheme of the Blue cool color, but elderly with depression reacted well to the contrast color scheme of the Blue-Yellow/Red cool color. This study will serve as critical data to propose more color preferences for the Seniors’ Happiness Center suitable for the elderly by studying the response to more diverse colors in the UAE.
The Pseudokinase TRIB1 in Immune Cells and Associated Disorders
Authors: Danger Richard , Feseha Yodit , Brouard Sophie
Published: February 2022

Research advances in Tribbles homolog (TRIB) genes have established the consensus that this protein family plays roles in diverse biological conditions and regulates intracellular signaling networks and several human diseases. In this review, we focus on one member of the family, TRIB1, and its role at the crossroads of immune signaling. TRIB1 directly interacts with transcription factors such as FOXP3 and C/EBPα, with several signaling molecules such as MEK1 and MALT1 and directly acts on key cell signaling pathways such as the MAPK and NF-κB pathways. Altogether, these interactions emphasize that TRIB1 is at the center of major cell signaling pathways while TRIB1 has cell-specific roles, potentially depending on the expressing cells and binding partners. In this review, we describe its roles in immune cells and highlight the interacting partners explaining these functions which suggests TRIB1 as a precise mediator of cellular homeostasis as well as in different cancers and immune-related disorders.
A Journey through Time on the Discovery of Cell Cycle Regulation
Authors: Uzbekov Rustem , Prigent Claude
Published: February 2022

All living organisms on Earth are made up of cells, which are the functional unit of life. Eukaryotic organisms can consist of a single cell (unicellular) or a group of either identical or different cells (multicellular). Biologists have always been fascinated by how a single cell, such as an egg, can give rise to an entire organism, such as the human body, composed of billions of cells, including hundreds of different cell types. This is made possible by cell division, whereby a single cell divides to form two cells. During a symmetric cell division, a mother cell produces two daughter cells, while an asymmetric cell division results in a mother and a daughter cell that have different fates (different morphologies, cellular compositions, replicative potentials, and/or capacities to differentiate). In biology, the cell cycle refers to the sequence of events that a cell must go through in order to divide. These events, which always occur in the same order, define the different stages of the cell cycle: G1, S, G2, and M. What is fascinating about the cell cycle is its universality, and the main reason for this is that the genetic information of the cell is encoded by exactly the same molecular entity with exactly the same structure: the DNA double helix. Since both daughter cells always inherit their genetic information from their parent cell, the underlying fundamentals of the cell cycle—DNA replication and chromosome segregation—are shared by all organisms. This review goes back in time to provide a historical summary of the main discoveries that led to the current understanding of how cells divide and how cell division is regulated to remain highly reproducible.
Chemerin Impact on Alternative mRNA Transcription in the Porcine Luteal Cells
Authors: Makowczenko Karol G. , Jastrzebski Jan P. , Paukszto Lukasz , Dobrzyn Kamil , Kiezun Marta , Smolinska Nina , Kaminski Tadeusz
Published: February 2022

Chemerin participates in the regulation of processes related to physiological and disorder mechanisms in mammals, including metabolism, obesity, inflammation, and reproduction. In this study, we have investigated chemerin influence on alternative mRNA transcription within the porcine luteal cell transcriptome, such as differential expression of long non-coding RNAs (DELs) and their interactions with differentially expressed genes (DEGs), differences in alternative splicing of transcripts (DASs), and allele-specific expression (ASEs) related to the single nucleotide variants (SNVs) frequency. Luteal cells were collected from gilts during the mid-luteal phase of the oestrous cycle. After in vitro culture of cells un-/treated with chemerin, the total RNA was isolated and sequenced using the high-throughput method. The in silico analyses revealed 24 DELs cis interacting with 6 DEGs and trans-correlated with 300 DEGs, 137 DASs events, and 18 ASEs. The results enabled us to analyse metabolic and signalling pathways in detail, providing new insights into the effects of chemerin on the corpus luteum functions related to inflammatory response, leukocyte infiltration, the occurrence of luteotropic and luteolytic signals (leading to apoptosis and/or necroptosis). Validation of the results using qPCR confirmed the predicted expression changes. Chemerin at physiological concentrations significantly modifies the transcription processes in the porcine luteal cells.
Automatic Colorectal Cancer Screening Using Deep Learning in Spatial Light Interference Microscopy Data
Authors: Zhang Jingfang K. , Fanous Michael , Sobh Nahil , Kajdacsy-Balla Andre , Popescu Gabriel
Published: February 2022

The surgical pathology workflow currently adopted by clinics uses staining to reveal tissue architecture within thin sections. A trained pathologist then conducts a visual examination of these slices and, since the investigation is based on an empirical assessment, a certain amount of subjectivity is unavoidable. Furthermore, the reliance on external contrast agents such as hematoxylin and eosin (H&E), albeit being well-established methods, makes it difficult to standardize color balance, staining strength, and imaging conditions, hindering automated computational analysis. In response to these challenges, we applied spatial light interference microscopy (SLIM), a label-free method that generates contrast based on intrinsic tissue refractive index signatures. Thus, we reduce human bias and make imaging data comparable across instruments and clinics. We applied a mask R-CNN deep learning algorithm to the SLIM data to achieve an automated colorectal cancer screening procedure, i.e., classifying normal vs. cancerous specimens. Our results, obtained on a tissue microarray consisting of specimens from 132 patients, resulted in 91% accuracy for gland detection, 99.71% accuracy in gland-level classification, and 97% accuracy in core-level classification. A SLIM tissue scanner accompanied by an application-specific deep learning algorithm may become a valuable clinical tool, enabling faster and more accurate assessments by pathologists.
Electronic Nose and Tongue for Assessing Human Microbiota
Authors: Tonacci Alessandro , Scafile Alessandro , Billeci Lucia , Sansone Francesco
Published: February 2022

The technological developments of recent times have allowed the use of innovative approaches to support the diagnosis of various diseases. Many of such clinical conditions are often associated with metabolic unbalance, in turn producing an alteration of the gut microbiota even during asymptomatic stages. As such, studies regarding the microbiota composition in biological fluids obtained by humans are continuously growing, and the methodologies for their investigation are rapidly changing, making it less invasive and more affordable. To this extent, Electronic Nose and Electronic Tongue tools are gaining importance in the relevant field, making them a useful alternative—or support—to traditional analytical methods. In light of this, the present manuscript seeks to investigate the development and use of such tools in the gut microbiota assessment according to the current literature. Significant gaps are still present, particularly concerning the Electronic Tongue systems, however the current evidence highlights the strong potential such tools own to enter the daily clinical practice, with significant advancement concerning the patients’ acceptability and cost saving for healthcare providers.
Progress in Fast and Red Plastic Scintillators
Authors: Hamel Matthieu
Published: February 2022

Radiological detection where Cherenkov residual background can be prominent requires scintillators with increased emission wavelength. Cherenkov residual background precludes the use of UV-emitting sensors such as plastic scintillators. However, the literature is scarce in red-emitting plastic scintillators and only one commercial scintillator is currently available (BC-430, from Saint-Gobain Crystals and Detectors). In addition, X-ray imaging or time-of-flight positron emission tomography (ToF-PET) applications are also demanding on this type (color) of scintillators, but such applications also require that the material displays a fast response, which is not particularly the case for BC-430. We present herein our latest developments in the preparation and characterization of fast and red plastic scintillators for this application. Here, ‘fast’ means nanosecond range decay time and ‘red’ is an emission wavelength shifted towards more than 550 nm. At first, the strategy to the preparation of such material is explained by decomposing the scintillator to fundamental elements. Each stage is then optimized in terms of decay time response, then the elemental bricks are arranged to give plastic scintillator formulations that are compatible with the abovementioned characteristics. The results are compared with the red-emissive BC-430 commercial plastic, and the ultra-fast, violet-emitting BC-422Q 1% plastic. In particular, the first-time use of trans-4-dimethylamino-4′-nitrostilbene in the scintillation field as a red wavelength shifter allowed preparing plastic scintillators with the following properties: λemmax 554 nm, photoluminescence decay time 4.2 ns, and light output ≈ 6100 ph/MeV. This means a scintillator almost as bright as BC-430 but at least three times faster. This new sensor might provide useful properties for nuclear instrumentation.
Impact of the COVID-19 Pandemic on Emergency Care Utilization and Outcomes in Pediatric Patients with Intussusception
Authors: Lee Jin Hee , Ro Young Sun , Kwon Hyuksool , Suh Dongbum , Moon Sungwoo
Published: February 2022

Background: We determined whether a decrease in healthcare utilization patterns during the COVID-19 pandemic affected the treatment process of pediatric patients with intussusception. Methods: Patients with suspected intussusception who had ICD-10 code K561 as their discharge diagnosis from the national database were selected, and those who underwent either radiologic and/or surgical reduction were defined as true intussusception patients. We compared the time periods from patients visiting the ED to ultrasound, radiologic reduction and/or surgical reduction between the study group (first half of 2020, COVID-19 period) and the control groups (control group 1: first half of 2019, control group 2: second half of 2019). Results: The number of suspected intussusception patients in each group was 1223, 1576, and 624, and the incidence rates were 7.85, 11.30, and 4.19 per 100,000 person-half-years (control group 1, control group 2, study group, respectively, p < 0.05). No differences in terms of the time from the ED visit to ultrasound, radiological reduction and/or surgical reduction were noted between the study group and the control groups. Conclusions: In Korea, the COVID-19 pandemic did not significantly affect the ED treatment process or the results of patients with intussusception.
Association between Coagulation Profile and Clinical Outcome in Children with SARS-CoV-2 Infection or MIS-C: A Multicenter Cross-Sectional Study
Authors: Buonsenso Danilo , Mariani Francesco , Pierri Luca , Morello Rosa , Yock-Corrales Adriana , Del Aguila Olguita , Lazzareschi Ilaria , Zampino Giuseppe , Nunziata Francesco , Valentini Piero , Lo Vecchio Andrea
Published: February 2022

Limited data on the coagulation profile in children affected by the SARS-CoV-2 infection are available. We aimed to evaluate the role of d-dimers as predictors of poor outcomes in a pediatric population affected by the SARS-CoV-2 infection or multisystem inflammatory syndrome (MIS-C). We performed a retrospective cross-sectional multicenter study. Data from four different centers were collected. Laboratory tests, when performed, were collected at the time of diagnosis, and 24, 48, 72, 96, 120 and beyond 120 h from diagnosis; blood counts with formula, an international normalized ratio (INR), activated partial thromboplastin time (aPTT), D-dimers and fibrinogen values were collected. Data regarding clinical history, management and outcome of the patients were also collected. Three hundred sixteen patients with a median age of 3.93 years (IQR 0.62–10.7) diagnosed with COVID-19 or MIS-C were enrolled. Fifty-eight patients (18.3%) showed a severe clinical outcome, 13 (4.1%) developed sequelae and 3 (0.9%) died. The univariate analysis showed that age, high D-dimer values, hyperfibrinogenemia, INR and aPTT elongation, and low platelet count were associated with an increased risk of pediatric intensive care unit (PICU) admission (p < 0.01). Three multivariate logistic regressions showed that a d-dimer level increase was associated with a higher risk of PICU admission. This study shows that D-dimer values play an important role in predicting the more severe spectrum of the SARS-CoV-2 infection, and was higher also in those that developed sequelae, including long COVID-19.
Can Intentional Weight Loss Ameliorate Sarcopenia in Individuals with Obesity? A Longitudinal Interventional Study
Authors: Tannir Hana , Itani Leila , Kreidieh Dima , El Masri Dana , El Ghoch Marwan
Published: February 2022

Little remains known regarding the impact of weight loss on sarcopenic obesity (SO), and for this reason we aimed to assess the relationship between the two during a weight management program. Body composition was measured at baseline and six-month follow-up using the Tanita BC-418, and step measurements were obtained daily over a period of six months using an Omron HJ-320 pedometer, in 41 adults of both genders with obesity. The participants were then categorized according to the presence or absence of SO. After a significant weight loss, an improvement in the appendicular skeletal mass (ASM) to weight ratio (24.5 ± 3.5 vs. 26.2 ± 3.6, p < 0.01), indicated a decrease in the prevalence of SO by 12.2%. Moreover, these findings were confirmed by logistic regression analysis revealing a significant WL% ≥ 5% combined with an active lifestyle (i.e., ≥8000 steps/day), decreased the risk of SO by 91% (OR = 0.09; 95% CI: 0.02–0.56), after adjusting for age and gender. In conclusion, in a weight management setting, a personalized program for individuals with SO that incorporates new strategies in terms of weight loss and physical activity targets may be adopted to improve the sarcopenia-related index and reduce the prevalence of SO in this population.
A Proposal for a National Cancer Control Plan for the UAE: 2022–2026
Authors: Al-Shamsi Humaid O. , Abyad Amin M. , Rafii Saeed
Published: February 2022

The United Arab Emirates (UAE) is one of the fastest growing economies with consequent increase in non-communicable diseases including cancer. The number of reported cases and mortality have been increasing in the UAE over the years, despite screening and early detection efforts which appear to be far from target coverage of the intended population. In this work, we highlight key elements of a proposed national cancer control plan for the UAE. The plan is still a work in progress and has not yet been officially adopted. A comprehensive and effective control plan requires accurate data, a reliable cancer registry, and periodic monitoring and evaluation. The UAE cancer control plan is being prepared in line with the WHO and EMRO framework, with defined objectives and goals. The objectives are to combat cancer, reduce incidence, control mortality, and improve outcomes and quality of life for cancer patients. There is also a focus on improving public health education, prevention, early detection, prompt diagnosis, treatment facilitation, continuity of care, performance evaluation, training of workforce, and research.
Re-Examination of the Phylogenetic Relationship among Merulinidae Subclades in Non-Reefal Coral Communities of Northeastern Taiwan
Authors: Chen Chieh-Jhen , Ho Yu-Ying , Chang Ching-Fong
Published: February 2022

Species identification for spawning corals relies heavily on morphology. Recent molecular phylogenetic approaches have demonstrated the limits of traditional coral taxonomy based solely on skeletal morphology. Merulinidae is considered a complex taxonomic group, containing 24 genera and 149 species. This family is one of the most taxonomically challenging and its taxonomy has largely improved in recent studies. However, studies of the phylogeny of Merulinidae are constrained by limited geographic scales. In Taiwan, merulinid corals are dominant in non-reefal communities on northeast coasts and they consistently spawn between summer and fall. This study is a first attempt to establish a molecular database of merulinid corals in this new area, including a volcanic island (Kueishan Island), and provide information about sexual reproduction. We analyzed 65 specimens, including 9 genera and 28 species collected from Taiwan using one mitochondrial marker (COI: cytochrome c oxidase subunit 1 gene) and three nuclear markers (ITS: nuclear ribosomal internal transcribed spacer, 28S rDNA D1 and D2, and histone H3) to re-examine phylogenetic relationships and search for new species. Overall, 58 COI sequences, 59 for ITS, 63 for 28S, and 62 histone sequences were newly obtained from the collected specimens. The reconstructed molecular tree demonstrates that all the specimens and reference sequences we examined are clustered within Merulinidae. Subclades A, B, C, D/E, F, G, H, and I are congruent with previous studies. However, Astrea curta is separated from the other congeneric species, Astrea annuligera (XVII-B), which is a sister to Favites and defined as a new subclade K. In addition, two new species (Paragoniastrea deformis and Paragoniastrea australensis) were discovered for the first time in Taiwan, and we defined them as a new subclade J. In addition, A. curta, P. auastralensis, and P. deformis are all hermaphroditic spawners and released bundles in July. This study greatly improves the accuracy of biodiversity estimates, systematic taxonomy, and reproduction for Taiwan’s coral ecosystem.
Design and Analysis of Current Sensor Fault Detection Mechanisms for PMSM Drives Based on Neural Networks
Authors: Jankowska Kamila , Dybkowski Mateusz
Published: February 2022

This paper describes a vector-controlled Permanent Magnet Synchronous Motor (PMSM) drive system with the current sensor fault detection mechanism. In general, the control structure is based on the well-known Field Oriented Control (FOC) algorithm. The structure is equipped with an additional algorithm for current sensor fault detection based on a neural network. The presented control structure is able to detect typical current sensor faults, such as lack of signal, intermittent signal, variable gain and signal noise. The application of the NN detector guarantees a faster detection of the sensor fault than classical detectors based on algorithmic methods or logical systems. This work focuses on presenting the methodology of designing detectors and their analysis, based solely on simulation analysis. The simulation results, conducted in the Matlab/Simulink environment, are presented for the above-mentioned faults in phase A and phase B for different speed conditions.
Critical Illness Polyneuropathy and Myopathy and Clinical Detection of the Recovery of Consciousness in Severe Acquired Brain Injury Patients with Disorders of Consciousness after Rehabilitation
Authors: Hakiki Bahia , Cecchi Francesca , Pancani Silvia , Romoli Anna , Draghi Francesca , Scarpino Maenia , Sterpu Raisa , Mannini Andrea , Macchi Claudio , Grippo Antonello
Published: February 2022

Background: Disorders of consciousness (DoCs) include unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS). Critical illness polyneuropathy and myopathy (CIPNM) is frequent in severe acquired brain injuries and impacts functional outcomes at discharge from the intensive rehabilitation unit (IRU). We investigated the prevalence of CIPNM in DoCs and its relationship with the consciousness assessment. Methods: Patients with DoCs were retrospectively selected from the database including patients admitted to the IRU of the IRCCS Don Gnocchi Foundation, Florence, from August 2012 to May 2020. Electroneurography/electromyography was performed at admission. Consciousness was assessed using the Coma Recovery Scale-Revised (CRS-R) at admission and discharge. Patients transitioning from a lower consciousness state to a higher one were classified as improved responsiveness (IR). Results: A total of 177 patients were included (UWS: 81 (45.8%); MCS: 96 (54.2%); 78 (44.1%) women; 67 years (IQR: 20). At admission, 108 (61.0%) patients had CIPNM. At discharge, 117 (66.1%) patients presented an IR. In the multivariate analysis, CRS-R at admission (p = 0.006; OR: 1.462) and CIPNM (p = 0.039; OR: −1.252) remained significantly associated with IR only for the UWS patients. Conclusions: CIPNM is frequent in DoCs and needs to be considered during the clinical consciousness assessment, especially in patients with UWS.
Investigation of Eye-Tracking Scan Path as a Biomarker for Autism Screening Using Machine Learning Algorithms
Authors: Kanhirakadavath Mujeeb Rahman , Chandran Monica Subashini Mohan
Published: February 2022

Autism spectrum disorder is a group of disorders marked by difficulties with social skills, repetitive activities, speech, and nonverbal communication. Deficits in paying attention to, and processing, social stimuli are common for children with autism spectrum disorders. It is uncertain whether eye-tracking technologies can assist in establishing an early biomarker of autism based on the children’s atypical visual preference patterns. In this study, we used machine learning methods to test the applicability of eye-tracking data in children to aid in the early screening of autism. We looked into the effectiveness of various machine learning techniques to discover the best model for predicting autism using visualized eye-tracking scan path images. We adopted three traditional machine learning models and a deep neural network classifier to run experimental trials. This study employed a publicly available dataset of 547 graphical eye-tracking scan paths from 328 typically developing and 219 autistic children. We used image augmentation to populate the dataset to prevent the model from overfitting. The deep neural network model outperformed typical machine learning approaches on the populated dataset, with 97% AUC, 93.28% sensitivity, 91.38% specificity, 94.46% NPV, and 90.06% PPV (fivefold cross-validated). The findings strongly suggest that eye-tracking data help clinicians for a quick and reliable autism screening.
Precise Quantification of Land Cover before and after Planned Disturbance Events with UAS-Derived Imagery
Authors: Miller Zachary , Hupy Joseph , Hubbard Sarah , Shao Guofan
Published: February 2022

This paper introduces a detailed procedure to utilize the high temporal and spatial resolution capabilities of an unmanned aerial system (UAS) to document vegetation at regular intervals both before and after a planned disturbance, a key component in natural disturbance-based management (NDBM), which uses treatments such as harvest and prescribed burns toward the removal of vegetation fuel loads. We developed a protocol and applied it to timber harvest and prescribed burn events. Geographic image-based analysis (GEOBIA) was used for the classification of UAS orthomosaics. The land cover classes included (1) bare ground, (2) litter, (3) green vegetation, and (4) burned vegetation for the prairie burn site, and (1) mature canopy, (2) understory vegetation, and (3) bare ground for the timber harvest site. Sample datasets for both kinds of disturbances were used to train a support vector machine (SVM) classifier algorithm, which produced four land cover classifications for each site. Statistical analysis (a two-tailed t-test) indicated there was no significant difference in image classification efficacies between the two disturbance types. This research provides a framework to use UASs to assess land cover, which is valuable for supporting effective land management practices and ensuring the sustainability of land practices along with other planned disturbances, such as construction and mining.
3D Void Handling Geographic P2P-RPL for Indoor Multi-Hop IR-UWB Networks
Authors: Kim Dongwon , Jung Jiwon , Kwon Younggoo
Published: February 2022

IETF has standardized the point-to-point RPL (P2P-RPL) to ensure reliable and optimal P2P route discovery for low-power and lossy networks (LLNs). P2P-RPL propagates route discovery packets to all nodes in the network, which results in high routing communication overheads. Recently, other RPL-based P2P routing algorithms have been proposed to reduce such overheads, but still, quite an amount of overheads occur due to their flooding-based approach. In real life 3D environments, a larger number of nodes should be deployed to guarantee the full network connectivity, and thus the flooding strategy incurs higher overheads. In effort to alleviate high overheads, geographic routing is an attractive solution that exploits the nodes’ geographic locations in its next-hop routing selection. However, geographic routing inherently suffers from the local minimum (void) problem following greedy next-hop selection. Local minima occur more often in 3D space, and therefore, a reliable 3D void handling technique is required. In this paper, we propose greedy forwarding and void handling point-to-point RPL with adaptive trickle timer (GVA-P2P-RPL), which is a novel RPL-based P2P routing protocol that quickly discovers energy-efficient and reliable P2P routes in 3D networks. In GVA-P2P-RPL, P2P-RPL is modified to greedily forward routing packets when it is possible. IR-UWB-based 3D multi-hop self-positioning is conducted in advance to obtain the geographical location of each node. When local minima are encountered, routing packets are temporarily broadcast just like in the traditional P2P-RPL. A new trickle algorithm called adaptive trickle timer (ATT) is also presented to reduce route discovery time and provide better collision avoidance effects. The performance of GVA-P2P-RPL is compared with that of P2P-RPL, partial flooding-based P2P-RPL (PF-P2P-RPL) and ER-RPL. It shows significant improvements in route discovery overheads and route discovery time against these state-of-the-art RPL-based P2P routing methods in 3D environments. Performance evaluation in the special network case where a huge 3D void volume exists in the center is also presented to show the strong void recovery capability of the proposed GVA-P2P-RPL in 3D environments.
Error Compensation Enhanced Day-Ahead Electricity Price Forecasting
Authors: Kontogiannis Dimitrios , Bargiotas Dimitrios , Daskalopulu Aspassia , Arvanitidis Athanasios Ioannis , Tsoukalas Lefteri H.
Published: February 2022

The evolution of electricity markets has led to increasingly complex energy trading dynamics and the integration of renewable energy sources as well as the influence of several external market factors contributed towards price volatility. Therefore, day-ahead electricity price forecasting models, typically using some kind of neural network, play a crucial role in the optimal behavior of market agents. The most prominent models and benchmarks rely on improving the accuracy of predictions and the time for convergence by some sort of a priori processing of the dataset that is used for the training of the neural network, such as hyperparameter tuning and feature selection techniques. What has been overlooked so far is the possible benefit of a posteriori processing, which would consider the effects of parameters that could refine the predictions once they have been made. Such a parameter is the estimation of the residual training error. In this study, we investigate the effect of residual training error estimation for the day-ahead price forecasting task and propose an error compensation deep neural network model (ERC–DNN) that focuses on the minimization of prediction error, while reinforcing error stability through the integration of an autoregression module. The experiments on the Nord Pool power market indicated that this approach yields improved error metrics when compared to the baseline deep learning structure in different training scenarios, and the refined predictions for each hourly sequence shared a more stable error profile. The proposed method contributes towards the development of more flexible hybrid neural network models and the potential integration of the error estimation module in future benchmarks, given a small and interpretable set of hyperparameters.
Levelized Cost of Electricity Generation by Small Hydropower Projects under Clean Development Mechanism in India
Authors: Patro Epari Ritesh , Kishore Teegala Srinivasa , Haghighi Ali Torabi
Published: February 2022

Contrary to conventional fossil fuel-based electricity generation technologies, renewable energy centered technologies, specifically small hydropower, release a lesser amount of anthropogenic greenhouse gases but are normally more expensive. A major segment of the capital investment in the current small hydropower scenario accounts for equipment and construction process costs. The construction and cost administration process are generally limited to analysis of the capital cost of civil constructions, electro-mechanical equipment works, neglecting the costs related to operating and maintaining the plant, replacement or refurbishment, certified emission reductions, among others. Contemporary studies indicate that these costs form a substantial fraction of the total capital investment. Consequently, for cost management and investment decision making, small hydropower plant developers are drawing increased attention in recent years towards conducting life cycle costing studies that take into account the ignored costs. In addition, small hydropower plants in developing nations can become more competitive by trading the emission reductions achieved under the provision of the Clean Development Mechanism, an outcome of the Kyoto Protocol proposed at the United Nations Framework Convention on Climate Change. In this paper, a modest attempt has been made to determine the Levelized cost of electricity generation using life cycle costing methodology, which accounts for all the costs over operating lifetime on a range of small hydropower plants and the results are analyzed.
Wind-Photovoltaic-Energy Storage System Collaborative Planning Strategy Considering the Morphological Evolution of the Transmission and Distribution Network
Authors: Cai Defu , Wang Zuowei , Miao Shihong , Chen Rusi , Zheng Zhong , Zhou Kunpeng
Published: February 2022

The collaborative planning of a wind-photovoltaic (PV)-energy storage system (ESS) is an effective means to reduce the carbon emission of system operation and improve the efficiency of resource collaborative utilization. In this paper, a wind-PV-ESS collaborative planning strategy considering the morphological evolution of the transmission and distribution network is proposed. Firstly, aiming at the optimal economy of transmission and distribution network and considering the constraints of safe and stable operation of the system, the planning model of the transmission network based on DC power flow and the planning model of the distribution network based on AC power flow are constructed. Further, considering the coupling interaction between the transmission and distribution networks, a collaborative planning model of transmission and distribution networks based on second-order cone relaxation (SOCR) is constructed. Secondly, in order to reduce the computational complexity of the model and ensure the global optimality of the model solution, a fast model solution method based on heterogeneous decomposition architecture is proposed. Thirdly, the multiple driving factors of the morphological evolution of transmission and distribution network are analyzed, the morphological evolution path and typical characteristics of transmission and distribution network are determined, and a wind-PV-ESS collaborative planning strategy considering the morphological evolution of a transmission and distribution network is proposed. Finally, the results show that, compared with the sprouting period, the overall economy of the development period and maturity period is improved by 3342 k$ and 5751 k$ respectively, and the effectiveness and necessity of the collaborative planning strategy proposed in this paper is verified.
Performance Degradation of a Shell-and-Tube Heat Exchanger Due to Tar Deposition
Authors: Aldi Nicola , Casari Nicola , Pinelli Michele , Suman Alessio , Vulpio Alessandro
Published: February 2022

Biomass represents a programmable renewable energy source that is useful for reducing issues related to the transfer from fossil fuels to the renewable energy era. The exploitation of biomass is strongly related to the development of power technologies that are designed to improve efficiency; however, at the same time, they have to be designed to improve the life cycle of the entire installation—especially in relation to maintenance operations. In this paper, a numerical analysis is proposed to assess the performance of a heat exchanger used for separating condensing tar from syngas generated by the gasification of lignocellulosic wood chips and pellets. The analysis included clean, fouled, and clogged conditions. Flow maldistribution characterized the inlet section of shell-and-tube configurations and was responsible for clogging phenomena. Starting from field detection, analyses of fouled and clogged conditions showed a reduction in the effectiveness of the heat exchanger, causing dangerous conditions for the internal combustion engine used to exploit the syngas flow.
Assessment of the Impact of the Human Coronavirus (COVID-19) Lockdown on the Energy Sector: A Case Study of Sharjah, UAE
Authors: Samara Fatin , Abu-Nabah Bassam A. , El-Damaty Waleed , Bardan Mayyada Al
Published: February 2022

The recent coronavirus (COVID-19) pandemic has wreaked havoc on the global economy, causing major shifts in energy use and output patterns. For some countries, this has had a significant effect on energy demand and carbon emissions, at least in the short term. Since the United Arab Emirates is currently exerting many efforts towards sustainability, it is important to assess and understand the impacts of the pandemic and the lockdown measurements on the local energy sectors. Data for this analysis were gathered by the Sharjah Electricity Water & Gas Authority (SEWA) for Sharjah City which is the capital of the Emirate of Sharjah. The changes in electricity after the implementation of quarantine and lockdown-like measures were assessed, and the results indicate that the electric power demand in Sharjah City was reduced in the commercial, industrial, and agricultural sectors, whereas the residential and government sectors witnessed a higher power demand. The overall electricity consumption in the year 2020 was reduced by 1.04% in comparison with previous years including 2016 to 2019. The results of this study indicate that the changes in electricity consumption were minimal in Sharjah City as compared to other cities around the world. However, this paper highlights the importance of governmental response during and after a pandemic, and the possible impacts that lockdowns could potentially have in the energy industry worldwide.
Experimental and Numerical Analyses of a Novel Wing-In-Ground Vehicle
Authors: van Sluis Martijn , Nasrollahi Sina , Gangoli Rao Arvind , Eitelberg Georg
Published: February 2022

The AeroCity is a new form of transportation concept that has been developed to provide high-speed ground transportation at a much lower cost than the existing high-speed railway. Utilizing the Wing-in-Ground (WIG) effect, the AeroCity vehicle does not require complex infrastructures like other contemporary concepts, such as the Hyperloop or Maglev trains. In the current work, the aerodynamic characteristics of the AeroCity vehicle are examined through a Computational Fluid Dynamics (CFD) analysis. The results from the CFD analysis qualitatively match with the findings of wind tunnel experiments. Surface streamlines and boundary layer measurements correspond well with the numerical data. However, the force measurements show a discrepancy. It is found that the separation bubble over the side plates is not captured by the CFD, and this is responsible for an under-prediction of the drag at higher free-stream velocities. The Transition SST model improved the matching between the experiments and numerical simulations. The influence of the moving ground is numerically investigated, and the effect of non-moving ground on the vehicle aerodynamics was found not to be significant. Finally, the inclusion of the track wall is examined. It is found that the merging of the wingtip vortices is responsible for a significant drag increase and, therefore, an alternative track geometry should be investigated.
Ash Behaviour during Combustion of Agropellets Produced by an Agro-Industry—Part 2: Chemical Characterization of Sintering and Deposition
Authors: Royo Javier , Canalís Paula , Zapata Sebastián , Gómez Maider , Bartolomé Carmen
Published: February 2022

Eight different pellets (one woody and seven blends of woody and herbaceous biomass) produced by an agro-industry were tested in a fixed-bed reactor to characterize their behaviour during their combustion process. The objective was to analyze the possible problems that could arise and, thus, achieve advances in the greater penetration of these agropellets in the energy market. The blends’ design and tests results are presented in the first part of this article. The results of the bottom ash and fly ash samples obtained from the combustion tests using SEM-EDS and P-XRD techniques were analyzed in order to delve into the sintering and deposition phenomena, respectively. Regarding the sintering, a clear relationship has been found between the results of the SEM-EDS analysis and the initial composition of the ash of the fuels. Additionally, the analysis of the results confirms a different ash behaviour regarding the sintering phenomenon depending on the ratio between the amounts of Si, Ca + Mg and K + Na. With respect to deposition, it has been determined that in woody pellets, showing the lower sintering degree, the predominant deposition mechanism is by inertial impact, while in blend pellets it is by condensation, which increases when the percentage of herbaceous in the mixture increases. It has been proved that, in order to compensate (at least partially) for the negative effect of the herbaceous components in the blends, working with a higher λ value is interesting, as it achieves a decrease in the combustion temperature (with λ >1), which implies both a decrease in the sintering degree and in the deposition, improving therefore the ash behaviour in the combustion of agropellets.
Design, Analysis, and Optimization of Permanent Magnet Vernier Machines Considering Rotor Losses
Authors: Wu Wenjie , Xu Liang , Liu Bin
Published: February 2022

The purpose of this paper is the design, analysis, and optimization of a new structure of a permanent magnet vernier machine (PMVM) with a high torque density and low rotor losses. First, the modulation principle and topology of this PMVM is introduced. Then, its average torque and rotor loss are enhanced and reduced by optimizing the flux modulation poles distribution. For the sake of further reducing the rotor losses on the premise of maintaining the torque density, the contribution of the air gap flux density harmonics to the rotor loss is analyzed. Then, a new topological structure of a rotor with a flux barrier is introduced to reduce the rotor losses due to the decrease of each harmful harmonic. Through the analysis of the structure of the PMVM with the flux barrier, the influence of the parameters on the performance is built. After that, a multi-objective optimization algorithm is used to optimize the PMVM so as to obtain the optimal performance. Moreover, the electromagnetic performance comparison between the newly proposed machine and the original one is presented to indicate that lower rotor losses can be obtained by the proposed machine when the torque is ensured. Finally, a prototype of proposed PMVM is built and further tested to verify the validities of the theoretical and finite-element analyses.
Advanced Exergy Analyses of a Solar Hybrid Food Dehydrator
Authors: Amjad Waseem , Raza Muhammad Ali , Asghar Furqan , Munir Anjum , Mahmood Faisal , Husnain Syed Nabeel , Hussain Muhammad Imtiaz , Kim Jun-Tae
Published: February 2022

In this study, for the first time an advanced exergy analysis was applied to a solar hybrid food dehydrator to find out the causes of the inefficacies and to assess the actual improvement potential. The dryer was integrated with an evacuated solar tube collector and gas burner as a heating sources. Drying experiments were performed using bell pepper at 55 °C under three heating options i.e., gas, solar and dual. The rates of exergy destructions were split into unavoidable (EdUN) and avoidable (EdAV) which further split into four parameters termed unavoidable endogenous (EdUN,EN), unavoidable exogenous (EdUN,EX), avoidable endogenous (EdAV,EX) and avoidable exogenous (EdAV,EN). Conventional exergy analysis revealed that drying chamber possess lower improvement potential rate (IP) than heating components while outcomes of advanced exergy analysis showed that both the design and system components interaction of heating unit imparted a major effect on its efficiency. Optimizing the operating conditions of the heating sources could reduce their higher amount of inefficiencies. The values of exergy efficiency for the overall system were calculated to be 86.66%, 84.18%, 83.74% (conventional) and 97.41%, 95.99%, 96.16% (advanced) under gas, dual and solar heating modes respectively.
Study of Sawing Parameters for Caragana korshinskii (C.K.) Branches
Authors: Gao Yaoyao , Wang Yutong , Qu Aili , Kan Jiangming , Kang Feng , Wang Yutan
Published: February 2022

To solve the problems of poor sawing surface quality, severe blade wear and high power consumption caused by unreasonable working parameters in the process of Caragana korshinskii (C.K.) stumping, this study explored the effects of branch diameter (D), sawing speed (vc), feeding speed (vf), cutting inclination (α), number of circular saw teeth (T) and moisture content (M) on sawing power consumption (P) and sawing surface quality (A) through a single-factor test using a homemade branch sawing bench. Based on the Box–Behnken design principle, a multi-factor test was carried out based on a single-factor test with vc, vf, α and T as influencing factors and with P and A as targets, establishing a regression model. The test results show that the sawing power consumption (P) increases with increasing D, decreases with increasing M, and decreases first and then increases with increasing vc, vf, α and T; the sawing surface quality (A) increases first and then decreases with increasing D, increases with increasing M, and first increases and then decreases with increasing vc, vf, α and T. The optimum combination of parameters for the regression model was obtained with vc of 45.24 m/s, vf of 0.34 m/s, α of 10° and T of 100, which resulted in the P of 177.46 J and A of 85.87%. The errors between the predicted and actual values of P and A are 3.1% and 6%, respectively. The study can provide information to support the development of subsequent C.K. stubble equipment.
In the Shadow of Cormorants: Succession of Avian Colony Affects Selected Groups of Ground Dwelling Predatory Arthropods
Authors: Machač Ondřej , Ivinskis Povilas , Rimšaitė Jolanta , Horňák Ondřej , Tuf Ivan Hadrián
Published: February 2022

(1) Nesting of the great cormorants strongly influences terrestrial ecosystems by physical destruction of vegetation and chemical changes in the soil and around the nesting colonies. (2) We investigated spider, harvestmen, and centipede assemblages in different influenced plots (starting colony, active dense colony, and partly abandoned colony) in the biggest Lithuanian cormorant colony in pine woods on the shore of the Baltic Sea in the Curonian Spit National Park in Lithuania. Selected groups of ground dwelling predatory arthropods were collected by pitfall traps in 2012–2014. (3) We recorded a total of 4299 spider specimens (102 species), 451 harvestmen specimens (9 species), and 1537 centipede specimens (7 species). The coverage of moss and herb vegetation, mean Ellenberg value for light, bare ground without vegetation, and number of nests significantly influenced the abundance, species richness, and ecological groups of arthropod predators. (4) Active ground hunters represented by spider Trochosa terricola and centipede Lithobius forficatus were positively influenced by bare ground without vegetation and a higher density of nests, and negatively influenced by an increasing coverage of moss and herbs. The opposite effect was found for web builder spiders and less movable species, represented by dominant spider species Diplostyla concolor and harvestmen Nemastoma lugubre and Oligolophus tridens. (5) The results show how cormorant influence the forest vegetation structure and affect the abundance and species diversity of ground dwelling predatory arthropods.