bluuebunny/crossref_metadata_2025 huggingface dataset:
Overcoming the Double Empathy Problem Within Pairs of Autistic and Non-autistic Adults Through the Contemplation of Serious Literature
Authors: Chapple Melissa , Davis Philip , Billington Josie , Myrick Joe Anthony , Ruddock Cassie , Corcoran Rhiannon
Published: July 2021

Recent research based on the needs of the autistic community has explored the frequent social misunderstandings that arise between autistic and non-autistic people, known as the double empathy problem. Double empathy understandings require both groups to respect neurodiversity by focussing on individuality across groups. This study aimed to explore how literature, through its ability to uncover nuanced emotional response differences between readers, could facilitate double empathy understandings within pairs of autistic and non-autistic adults. A longitudinal, qualitative design was used, with 4 gender-matched pairs. Participants read Of Mice and Men for 1 week, whilst completing a structured, reflective diary. This was followed by 4 one-hour paired reading sessions, where pairs discussed the book and their reflections in depth. Participants were then invited to a final one-on-one interview to discuss their thoughts and experiences of the paired reading sessions. Thematic and literary analysis of the session and interview data revealed four themes (1) The Book as Social Oil; (2) From a World of Difference to a World of Affinity; (3) Emotional Intelligence: From Thinking About to Feeling with; and (4) From Overwhelming to Overcoming. All participants reported having achieved an individualised view of one another to explore their nuanced differences. The non-autistic group reported a more sensitive understanding of what it means to be autistic, while the autistic group overcame concerns about non-autistic people stereotyping autism, and instead reported feeling valued and accommodated by their non-autistic partners.
The Benefits of Forgiveness at Work: A Longitudinal Investigation of the Time-Lagged Relations Between Forgiveness and Work Outcomes
Authors: Cao Wenrui , van der Wal Reine C. , Taris Toon W.
Published: July 2021

Forgiveness has received increasing attention in the work context. Although recent cross-sectional studies have found a positive link between forgiveness and work outcomes, further research examining the temporal dynamics between these variables is needed to establish causality. This preregistered panel study investigated the time-lagged relations between forgiveness and work outcomes, and specifically addressed the question whether forgiving a coworker benefits work outcomes. Longitudinal survey data were collected at four time points among 139 Chinese employees working at least 20 hours per week. Results from cross-lagged panel models revealed that forgiving an offending coworker with whom one has a relatively good work relationship predicted better work outcomes (i.e., higher job satisfaction, higher work engagement, and lower burnout) over time, while controlling for perceived severity of the offense. Evidence for the reverse effect (with work outcomes predicting forgiveness) was not found. Our findings thus suggest that forgiveness facilitates well-being-related work outcomes. Implications for a better understanding of forgiveness in work relationships are discussed.
Community Violence Exposure and School Functioning in Youth: Cross-Country and Gender Perspectives
Authors: Koposov Roman , Isaksson Johan , Vermeiren Robert , Schwab-Stone Mary , Stickley Andrew , Ruchkin Vladislav
Published: July 2021

Background:Many children and adolescents experience violent events which can be associated with negative consequences for their development, mental health, school, and social functioning. However, findings between settings and on the role of gender have been inconsistent. This study aimed to investigate cross-country and gender differences in the relationship between community violence exposure (CVE) and school functioning in a sample of youths from three countries.

Methods:A self-report survey was conducted among school students (12–17 years old) in Belgium (Antwerp,N= 4,743), Russia (Arkhangelsk,N= 2,823), and the US (New Haven,N= 4,101). Students were recruited from within classes that were randomly selected from within schools that had themselves been randomly selected (excepting New Haven, where all students were included). CVE was assessed with the Screening Survey of Exposure to Community Violence. School functioning was assessed with four measures: the Perceived Teacher Support scale, Negative Classroom Environment scale, and Academic Motivation and Perception of Safety at School scales. Multivariate Analyses of Covariance were performed to assess differences in the levels of school-related problem behaviors in boys and girls, who reported different degrees of CVE.

Results:Participants in all three countries reported a relatively high prevalence of violence exposure (36.2% in Belgium, 39.3% in Russia and 45.2% in the US who witnessed violence), with a higher proportion of girls than boys witnessing violent events (varied from 37.4 to 51.6% between the countries), whereas boys reported more episodes of victimization by violence than girls (varied from 32.3 to 49.9% between the countries). Youths who experienced increased CVE (from no exposure to witnessing to victimization) reported an increase in all school functioning problems in all of the countries and this association was not gender-specific.

Conclusions:Our findings suggest that regardless of differences in the level of CVE by country and gender, violence exposure is negatively associated with school functioning across countries. Nonetheless, even though reactions to community violence among adolescents may be expressed in a similar fashion, cross-country differences in social support systems should also be taken into account in order to provide culturally sensitive treatment modalities.
Pandemic Risk Management for Public Health Care Schemes
Authors: Liu Zhengqiao , Wu Yang-Che , Wang Mei-Chih , Ding Yue , Nguyen Tien-Trung
Published: July 2021

The coronavirus disease 2019 (COVID-19) caused by a novel coronavirus, severe acute respiratory syndrome coronavirus 2, has caused a large death, a range of serious health problems, and significant economic costs in many countries around the world. This study analyzes statistical characteristics of pandemic disasters using historical records since the Middle Ages. Compared to literature which studies the effect of the COVID- 19 pandemic on the financial market, this paper attempts to find two financial instruments in the financial market to hedge pandemic risks. Two instruments could be useful for public health care schemes to increase their assets or decrease their liabilities during the pandemic period, namely, assets in the form of a biotechnology investment portfolio and liabilities in the form of pandemic bonds. Empirical results show the feasibility of such instruments and the informational efficiency of the U.S. stock market.
NDVI Variation and Yield Prediction in Growing Season: A Case Study with Tea in Tanuyen Vietnam
Authors: Phan Phamchimai , Chen Nengcheng , Xu Lei , Dao Duy Minh , Dang Dinhkha
Published: July 2021

Tea is one of the most significant cash crops and plays an important role in economic development and poverty reduction. On the other hand, tea is an optimal choice in the extreme weather conditions of Tanuyen Laichau, Vietnam. In our study, the NDVI variation of tea in the growing season from 2009 to 2018 was showed by calculating NDVI trend and the Mann-Kendall analysis to assess trends in the time series. Support Vector Machine (SVM) and Random Forest (RF) model were used for predicting tea yield. The NDVI of tea showed an increasing trend with a slope from −0.001–0.001 (88.9% of the total area), a slope from 0.001–0.002 (11.1% of the total area) and a growing rate of 0.00075/year. The response of tea NDVI to almost climatic factor in a one-month time lag is higher than the current month. The tea yield was estimated with higher accuracy in the RF model. Among the input variables, we detected that the role of Tmean and NDVI is stronger than other variables when squared with each of the independent variables into input data.
Long Term Monitoring and Connection between Topography and Cloud Cover Distribution in Serbia
Authors: Valjarević Aleksandar , Morar Cezar , Živković Jelena , Niemets Liudmyla , Kićović Dušan , Golijanin Jelena , Gocić Milena , Bursać Nataša Martić , Stričević Ljiljana , Žiberna Igor , Bačević Nikola , Milevski Ivica , Durlević Uroš , Lukić Tin
Published: July 2021

The use of weather satellite recordings has been growing rapidly over the last three decades. Determining the patterns between meteorological and topographical features is an important scientific job. Cloud cover analysis and properties can be of the utmost significance for potential cloud seeding. Here, the analysis of the cloud properties was conducted by means of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite recordings. The resolution of used data was 1 km2 within the period of 30 years (1989–2019). This research showed moderate changing of cloudiness in the territory of Serbia with a high cloudiness in February, followed by cloudiness in January and November. For the past three decades, May has been the month with the highest cloudiness. The regions in the east and south-west, and particularly in the west, have a high absolute cloudiness, which is connected with the high elevation of the country. By means of long term monitoring, the whole territory of Serbia was analyzed for the first time, in terms of cloudiness. Apart from the statistical and numerical results obtained, this research showed a connection between relief and clouds, especially in the winter season. Linear regression MK (Mann-Kendall test) has proven this theory right, connecting high elevation sides with high absolute cloudiness through the year.
“Stay at Home” in Italy during the COVID-19 Outbreak: A Longitudinal Study on Individual Well-Being among Different Age Groups
Authors: Quaglieri Alessandro , Lausi Giulia , Fraschetti Angelo , Burrai Jessica , Barchielli Benedetta , Pizzo Alessandra , Cordellieri Pierluigi , De Gennaro Luigi , Gorgoni Maurizio , Ferlazzo Fabio , Sdoia Stefano , Zivi Pierpaolo , Giannini Anna Maria , Mari Emanuela
Published: July 2021

The restrictions imposed by the Italian government because of the coronavirus outbreak have been shown to be demanding on the Italian population. Data were collected at four different time points from 29 March 2020 to 3 May 2020 and during the final follow-up survey on 12 October 2020. In the present study, we provided longitudinal evidence on the relationship between the lockdown and mental health dimensions, such as emotional state, perceived stress, and time perspective, for three age groups. The results allowed us to observe their psychological status from different perspectives at five different time points. Notably, a negative effect of the lockdown individual well-beings emerged as a trend, and differences in individual adaptation strategies to a prolonged stressful situation were observed at the follow-up. Indeed, pairwise comparisons between age groups showed that the young adult group (18–23 years old) seemed to be the most psychologically affected by the lockdown. The findings are discussed according to the most recent literature on the topic. To the best of our knowledge, this is one of the first longitudinal studies carried out in Italy concerning the general psychological effects of the coronavirus lockdown.
rs10514231 Leads to Breast Cancer Predisposition by Altering ATP6AP1L Gene Expression
Authors: Ma Shumin , Ren Naixia , Huang Qilai
Published: July 2021

Numerous genetic variants located in autophagy-related genes have been identified for association with various cancer risks, but the biological mechanisms underlying these associations remain largely unknown. Here we investigated their regulatory activity with a parallel reporter gene assay system in breast cancer cells and identified multiple regulatory SNP sites, including rs10514231. It was located in the second intron of ATG10 and showed gene regulatory activity in most breast cancer cells we used. Mechanistically, the T allele of rs10514231 led to ATP6AP1L downregulation by decreasing the binding affinity of TCF7L2. Overexpression of the ATP6AP1L gene in cancer cells diminished cell proliferation, migration, and invasion. Notably, ATP6AP1L downregulation correlated with breast cancer risk and with poor prognosis in patients. These results provide a plausible mechanism behind the association of rs10514231 with breast cancer risk and will be important for more effective therapeutic target identification for precision medicine.
Targeting Cancer Metabolism Breaks Radioresistance by Impairing the Stress Response
Authors: Schwab Melissa , Thunborg Katharina , Azimzadeh Omid , von Toerne Christine , Werner Caroline , Shevtsov Maxim , Di Genio Tommaso , Zdralevic Masa , Pouyssegur Jacques , Renner Kathrin , Kreutz Marina , Multhoff Gabriele
Published: July 2021

The heightened energetic demand increases lactate dehydrogenase (LDH) activity, the corresponding oncometabolite lactate, expression of heat shock proteins (HSPs) and thereby promotes therapy resistance in many malignant tumor cell types. Therefore, we assessed the coregulation of LDH and the heat shock response with respect to radiation resistance in different tumor cells (B16F10 murine melanoma and LS174T human colorectal adenocarcinoma). The inhibition of LDH activity by oxamate or GNE-140, glucose deprivation and LDHA/B double knockout (LDH−/−) in B16F10 and LS174T cells significantly diminish tumor growth; ROS production and the cytosolic expression of different HSPs, including Hsp90, Hsp70 and Hsp27 concomitant with a reduction of heat shock factor 1 (HSF1)/pHSF1. An altered lipid metabolism mediated by a LDHA/B double knockout results in a decreased presence of the Hsp70-anchoring glycosphingolipid Gb3 on the cell surface of tumor cells, which, in turn, reduces the membrane Hsp70 density and increases the extracellular Hsp70 levels. Vice versa, elevated extracellular lactate/pyruvate concentrations increase the membrane Hsp70 expression in wildtype tumor cells. Functionally, an inhibition of LDH causes a generalized reduction of cytosolic and membrane-bound HSPs in tumor cells and significantly increases the radiosensitivity, which is associated with a G2/M arrest. We demonstrate that targeting of the lactate/pyruvate metabolism breaks the radioresistance by impairing the stress response.
Nanobiotechnology and Immunotherapy: Two Powerful and Cooperative Allies against Cancer
Authors: Mainini Francesco , De Santis Francesca , Fucà Giovanni , Di Nicola Massimo , Rivoltini Licia , Eccles Michael
Published: July 2021

A number of novel cancer therapies have recently emerged that have rapidly moved from the bench to the clinic. Onco-immunotherapies, such as immune checkpoint blockade inhibitors and adoptive cell therapies, have revolutionized the field, since they provide a way to induce strong anti-tumor immune responses, which are able to fight cancer effectively. However, despite showing great efficacy in hematological and some solid tumors, unresponsiveness, development of therapy resistance and the development of serious adverse effects, limit their capacity to impact the vast majority of tumors. Nanoparticle-based delivery systems are versatile vehicles for a wide variety of molecular cargoes and provide an innovative strategy to improve conventional onco-immunotherapies. They can be finely tuned to release their contents in the tumor microenvironment, or to deliver combinations of adjuvants and antigens in the case of nanovaccines. In this review, we summarize the recent advancements in the field of nanobiotechnology, to remodel the tumor microenvironment and to enhance immunotherapies.
Machine Learning Approaches to Classify Primary and Metastatic Cancers Using Tissue of Origin-Based DNA Methylation Profiles
Authors: Modhukur Vijayachitra , Sharma Shakshi , Mondal Mainak , Lawarde Ankita , Kask Keiu , Sharma Rajesh , Salumets Andres
Published: July 2021

Metastatic cancers account for up to 90% of cancer-related deaths. The clear differentiation of metastatic cancers from primary cancers is crucial for cancer type identification and developing targeted treatment for each cancer type. DNA methylation patterns are suggested to be an intriguing target for cancer prediction and are also considered to be an important mediator for the transition to metastatic cancer. In the present study, we used 24 cancer types and 9303 methylome samples downloaded from publicly available data repositories, including The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). We constructed machine learning classifiers to discriminate metastatic, primary, and non-cancerous methylome samples. We applied support vector machines (SVM), Naive Bayes (NB), extreme gradient boosting (XGBoost), and random forest (RF) machine learning models to classify the cancer types based on their tissue of origin. RF outperformed the other classifiers, with an average accuracy of 99%. Moreover, we applied local interpretable model-agnostic explanations (LIME) to explain important methylation biomarkers to classify cancer types.
Targeting Orphan G Protein-Coupled Receptor 17 with T0 Ligand Impairs Glioblastoma Growth
Authors: Doan Phuong , Nguyen Phung , Murugesan Akshaya , Subramanian Kumar , Konda Mani Saravanan , Kalimuthu Vignesh , Abraham Bobin George , Stringer Brett W. , Balamuthu Kadalmani , Yli-Harja Olli , Kandhavelu Meenakshisundaram
Published: July 2021

Glioblastoma, an invasive high-grade brain cancer, exhibits numerous treatment challenges. Amongst the current therapies, targeting functional receptors and active signaling pathways were found to be a potential approach for treating GBM. We exploited the role of endogenous expression of GPR17, a G protein-coupled receptor (GPCR), with agonist GA-T0 in the survival and treatment of GBM. RNA sequencing was performed to understand the association of GPR17 expression with LGG and GBM. RT-PCR and immunoblotting were performed to confirm the endogenous expression of GPR17 mRNA and its encoded protein. Biological functions of GPR17 in the GBM cells was assessed by in vitro analysis. HPLC and histopathology in wild mice and an acute-toxicity analysis in a patient-derived xenograft model were performed to understand the clinical implication of GA-T0 targeting GPR17. We observed the upregulation of GPR17 in association with improved survival of LGG and GBM, confirming it as a predictive biomarker. GA-T0-stimulated GPR17 leads to the inhibition of cyclic AMP and calcium flux. GPR17 signaling activation enhances cytotoxicity against GBM cells and, in patient tissue-derived mesenchymal subtype GBM cells, induces apoptosis and prevents proliferation by stoppage of the cell cycle at the G1 phase. Modulation of the key genes involved in DNA damage, cell cycle arrest, and in several signaling pathways, including MAPK/ERK, PI3K–Akt, STAT, and NF-κB, prevents tumor regression. In vivo activation of GPR17 by GA-T0 reduces the tumor volume, uncovering the potential of GA-T0–GPR17 as a targeted therapy for GBM treatment. Conclusion: Our analysis suggests that GA-T0 targeting the GPR17 receptor presents a novel therapy for treating glioblastoma.
Transcriptomics-Based Phenotypic Screening Supports Drug Discovery in Human Glioblastoma Cells
Authors: Shapovalov Vladimir , Kopanitsa Liliya , Pruteanu Lavinia-Lorena , Ladds Graham , Bailey David S.
Published: July 2021

We have used three established human glioblastoma (GBM) cell lines—U87MG, A172, and T98G—as cellular systems to examine the plasticity of the drug-induced GBM cell phenotype, focusing on two clinical drugs, the phosphodiesterase PDE10A inhibitor Mardepodect and the multi-kinase inhibitor Regorafenib, using genome-wide drug-induced gene expression (DIGEX) to examine the drug response. Both drugs upregulate genes encoding specific growth factors, transcription factors, cellular signaling molecules, and cell surface proteins, while downregulating a broad range of targetable cell cycle and apoptosis-associated genes. A few upregulated genes encode therapeutic targets already addressed by FDA approved drugs, but the majority encode targets for which there are no approved drugs. Amongst the latter, we identify many novel druggable targets that could qualify for chemistry-led drug discovery campaigns. We also observe several highly upregulated transmembrane proteins suitable for combined drug, immunotherapy, and RNA vaccine approaches. DIGEX is a powerful way of visualizing the complex drug response networks emerging during GBM drug treatment, defining a phenotypic landscape which offers many new diagnostic and therapeutic opportunities. Nevertheless, the extreme heterogeneity we observe within drug-treated cells using this technique suggests that effective pan-GBM drug treatment will remain a significant challenge for many years to come.
Catalysts and Processes for H2S Conversion to Sulfur
Authors: Barba Daniela
Published: July 2021

The hydrogen sulfide (H2S) is one of the main byproducts in natural gas plants, refineries, heavy oil upgraders, and metallurgical processes [...]
Multisystemic Cellular Tropism of SARS-CoV-2 in Autopsies of COVID-19 Patients
Authors: Wong Dickson W. L. , Klinkhammer Barbara M. , Djudjaj Sonja , Villwock Sophia , Timm M. Cherelle , Buhl Eva M. , Wucherpfennig Sophie , Cacchi Claudio , Braunschweig Till , Knüchel-Clarke Ruth , Jonigk Danny , Werlein Christopher , Bülow Roman D. , Dahl Edgar , von Stillfried Saskia , Boor Peter
Published: July 2021

Multiorgan tropism of SARS-CoV-2 has previously been shown for several major organs. We have comprehensively analyzed 25 different formalin-fixed paraffin-embedded (FFPE) tissues/organs from autopsies of fatal COVID-19 cases (n = 8), using histopathological assessment, detection of SARS-CoV-2 RNA using polymerase chain reaction and RNA in situ hybridization, viral protein using immunohistochemistry, and virus particles using transmission electron microscopy. SARS-CoV-2 RNA was mainly localized in epithelial cells across all organs. Next to lung, trachea, kidney, heart, or liver, viral RNA was also found in tonsils, salivary glands, oropharynx, thyroid, adrenal gland, testicles, prostate, ovaries, small bowel, lymph nodes, skin and skeletal muscle. Viral RNA was predominantly found in cells expressing ACE2, TMPRSS2, or both. The SARS-CoV-2 replicating RNA was also detected in these organs. Immunohistochemistry and electron microscopy were not suitable for reliable and specific SARS-CoV-2 detection in autopsies. These findings were validated using in situ hybridization on external COVID-19 autopsy samples (n = 9). Apart from the lung, correlation of viral detection and histopathological assessment did not reveal any specific alterations that could be attributed to SARS-CoV-2. In summary, SARS-CoV-2 and its replication could be observed across all organ systems, which co-localizes with ACE2 and TMPRSS2 mainly in epithelial but also in mesenchymal and endothelial cells. Apart from the respiratory tract, no specific (histo-)morphologic alterations could be assigned to the SARS-CoV-2 infection.
On the Localized Surface Plasmonic Resonances of AgPd Alloy Nanoparticles by Experiment and Theory
Authors: Ntemogiannis Dimitrios , Tsarmpopoulou Maria , Chronis Alexandros G. , Anyfantis Dimitrios I. , Barnasas Alexandros , Grammatikopoulos Spyridon , Sigalas Mihail , Poulopoulos Panagiotis
Published: July 2021

Ag/Pd multilayers and AgPd alloyed ultrathin films were deposited on Corning glass by magnetron sputtering. After being annealed in a furnace in air at 460 °C, self-assembled nanoparticles were formed. Localized surface plasmon resonances were observed only for the Ag-rich samples in the full range of the visible light spectrum. The resonance position was found to depend on the initial film thickness. In order to gain further physical insight, rigorous theoretical calculations were carried out via the rigid coupled-wave analysis method for the entire compositional range between Ag and Pd. Theoretical calculations were proven to be in suitable agreement with the experimental results.
Molecular Dynamics Study on Nano-Friction and Wear Mechanism of Nickel-Based Polycrystalline Superalloy Coating
Authors: Zhu Zongxiao , Wang Hui , Qiang Zixuan , Jiao Shi , Wang Linjun , Zheng Min , Zhu Shengyu , Cheng Jun , Yang Jun
Published: July 2021

In this work, molecular dynamics simulations are employed to study the nanotribological process of nickel-based polycrystalline superalloy coating. A series of simulations were carried out using the method of repeated friction to explore the influence of frictional force, friction coefficient, grinding groove morphology, wear scar depth, debris flow direction, subsurface damage degree and evolution of defects during the nano-friction process. In addition, the change mechanism of different grain sizes on wear scar depth, frictional force, friction coefficient, and internal damage in the repeated friction process is also explored. The results show that the frictional force is related to the direction of the dislocation slip, and that the friction coefficient change is related to the number of repeated frictions. Moreover, it is observed that the grinding ball has a shunting effect on the formed wear debris atoms, and the shunt point is located at the maximum horizontal radius. We reveal that the grain boundary structure has a strengthening effect. When the grinding ball rubs to the grain boundary, the nucleation of dislocation defects inside the workpiece is obviously hindered by it. Simultaneously, we also find that the closer the subsurface is to the bottom of the grinding ball, the greater the degree of damage to the workpiece by friction. Furthermore, with the grain size decreases that the material begins to soften, resulting in a decrease of frictional force, friction coefficient, and smaller defects are formed inside the workpiece. The research of this work can better clarify the microscopic mechanism of the polycrystalline friction process.
Dihedral-Angle Dependence of Intermolecular Transfer Integrals in BEDT-BDT-Based Radical-Cation Salts with θ-Type Molecular Arrangements
Authors: Kadoya Tomofumi , Sugiura Shiori , Higashino Toshiki , Tahara Keishiro , Kubo Kazuya , Sasaki Takahiko , Takimiya Kazuo , Yamada Jun-ichi
Published: July 2021

We report the structural and physical properties of a new organic Mott insulator (BEDT-BDT)AsF6 (BEDT-BDT: benzo[1,2-g:4,5-g′]bis(thieno[2,3-b][1,4dithiin). This AsF6 salt has the same structure as the PF6 salt. Although the anions are disordered, the donor molecules form a θ-type arrangement. The temperature dependence of the resistivity exhibits semiconducting behavior. The static magnetic susceptibility follows Curie–Weiss law over a wide temperature range; however, below 25 K, the magnetic susceptibility is in agreement with a one-dimensional chain model with the exchange coupling J = 7.4 K. No structural phase transition was observed down to 93 K. At 270 K, the Fermi surface calculated by the tight-binding approximation is a two-dimensional cylinder; however, it is significantly distorted at 93 K. This is because the dihedral angles between the BEDT-BDT molecules become larger due to lattice shrinkage at low temperatures, which results in a smaller transfer integral (t1) along the stack direction. This slight change in the dihedral angle gives rise to a significant change in the electronic structure of the AsF6 salt. Radical-cation salts using BEDT-BDT, in which the highest occupied molecular orbital does not have a dominant sign throughout the molecule, are sensitive to slight differences in the overlap between the molecules, and their electronic structures are more variable than those of conventional θ-type conductors.
Fishes of the Lower Lulua River (Kasai Basin, Central Africa): A Continental Hotspot of Ichthyofaunal Diversity under Threat
Authors: Mbimbi Mayi Munene José J. , Stiassny Melanie L. J. , Monsembula Iyaba Raoul J. C. , Liyandja Tobit L. D.
Published: July 2021

The ichthyofauna of the Lulua River, a large right bank tributary of the Kasai River in central Africa, is among the most poorly documented in the Kasai ecoregion. To remedy this lack of knowledge, sampling was carried out between 2007 and 2014 along the main channel and in many tributaries. A total of 201 species distributed in 81 genera, 24 families, and 12 orders are reported from the lower reaches of the Lulua. The species richness reported in this study represents a substantially improved documentation of the Lulua ichthyofauna (historically estimated at only 79 species). Here, 129 species are recorded for the first time, bringing the total number of known species to 208. Among these, five have recently been described: Raiamas brachyrhabdotos Katemo Manda, Snoeks, Choca Manda, and Vreven 2018, Distichodus kasaiensis Moelants, Snoeks, and Vreven, 2018, Distichodus polli Abwe, Snoeks, Choca Manda, and Vreven 2019, Epiplatys atractus Van Der Zee, Mbimbi, and Sonnenberg 2013, and Hypsopanchax stiassnyae Van Der Zee, Sonnenberg, and Mbimbi 2015; numerous additional taxa are currently under investigation. Recognized here as a continental hotspot of ichthyofaunal diversity, the Lulua is under extreme threat from exploitation of forest products for building materials, deforestation for shifting agriculture and charcoal exploitation, destructive fishing practices, and mining, all of which are rapidly increasing in the watershed. The present study provides baseline documentation for use in conservation planning and future developmental projects in the Kasai ecoregion in general and Lulua River basin in particular.
Pairwise Elastic Net Representation-Based Classification for Hyperspectral Image Classification
Authors: Li Hao , Zhang Yuanshu , Ma Yong , Mei Xiaoguang , Zeng Shan , Li Yaqin
Published: July 2021

The representation-based algorithm has raised a great interest in hyperspectral image (HSI) classification. l1-minimization-based sparse representation (SR) attempts to select a few atoms and cannot fully reflect within-class information, while l2-minimization-based collaborative representation (CR) tries to use all of the atoms leading to mixed-class information. Considering the above problems, we propose the pairwise elastic net representation-based classification (PENRC) method. PENRC combines the l1-norm and l2-norm penalties and introduces a new penalty term, including a similar matrix between dictionary atoms. This similar matrix enables the automatic grouping selection of highly correlated data to estimate more robust weight coefficients for better classification performance. To reduce computation cost and further improve classification accuracy, we use part of the atoms as a local adaptive dictionary rather than the entire training atoms. Furthermore, we consider the neighbor information of each pixel and propose a joint pairwise elastic net representation-based classification (J-PENRC) method. Experimental results on chosen hyperspectral data sets confirm that our proposed algorithms outperform the other state-of-the-art algorithms.
Adaptive Fixed-Time Control of Strict-Feedback High-Order Nonlinear Systems
Authors: Li Yang , Zhang Jianhua , Ye Xiaoyun , Chin Cheng Siong
Published: July 2021

This paper examines the adaptive control of high-order nonlinear systems with strict-feedback form. An adaptive fixed-time control scheme is designed for nonlinear systems with unknown uncertainties. In the design process of a backstepping controller, the Lyapunov function, an effective controller, and adaptive law are constructed. Combined with the fixed-time Lyapunov stability criterion, it is proved that the proposed control scheme can ensure the stability of the error system in finite time, and the convergence time is independent of the initial condition. Finally, simulation results verify the effectiveness of the proposed control strategy.
Learning Ordinal Embedding from Sets
Authors: Diallo Aïssatou , Fürnkranz Johannes
Published: July 2021

Ordinal embedding is the task of computing a meaningful multidimensional representation of objects, for which only qualitative constraints on their distance functions are known. In particular, we consider comparisons of the form “Which object from the pair (j,k) is more similar to object i?”. In this paper, we generalize this framework to the case where the ordinal constraints are not given at the level of individual points, but at the level of sets, and propose a distributional triplet embedding approach in a scalable learning framework. We show that the query complexity of our approach is on par with the single-item approach. Without having access to features of the items to be embedded, we show the applicability of our model on toy datasets for the task of reconstruction and demonstrate the validity of the obtained embeddings in experiments on synthetic and real-world datasets.
Thermal Stability and Reliability Test of Some Saturated Fatty Acids for Low and Medium Temperature Thermal Energy Storage
Authors: Anand Abhishek , Kant Karunesh , Shukla Amritanshu , Chen Chang-Ren , Sharma Atul
Published: July 2021

Phase change materials have been overwhelmingly used for thermal energy storage applications. Among organics, fatty acids are an important constituent of latent heat storage. Most of the saturated fatty acid PCMs so far studied are either unary or binary constituents of pure fatty acids. In the present study, ternary blends of saturated fatty acids i.e., capric, lauric, myristic, stearic, and palmitic acids have been developed with different weight proportions. A series of 28 ternary blends viz. CA-LA-MA, CA-LA-PA, CA-LA-SA, CA-MA-PA, CA-MA-SA, and CA-PA-SA were prepared and analyzed with differential scanning calorimetry, thermal gravimetric analysis, and Fourier transform infrared spectroscopy. DSC analysis revealed that the prepared materials lie in the 15–30 °C temperature range. Also, 300 thermal melt/freeze cycles were conducted which showed ±10% variation in terms of the melting peak for most of the PCMs, with the average latent heat of fusion between 130 and 170 kJ/kg. The TGA analysis showed that most of the PCMs are thermally stable up to 100 °C and useful for medium-low storage applications, and FTIR analysis showed that the materials are chemically stable after repeated thermal cycles. Based on cycle test performances, the developed materials were found to be reliable for long-term use in building and photovoltaic applications.
Trichel Pulse Analysis: Physical Calculation and Validation by Using Broadband Measurements
Authors: Friebe Kerstin , Jenau Frank
Published: July 2021

Partial discharge measurement is part of the monitoring of equipment in power engineering systems. It provides important information about the condition of the equipment and in particular the condition of the insulation components. This information serves to take necessary preventive measures at an early stage to avoid failures of the affected energy system and thus ensure a high level of energy supply security. Possible causes of partial discharges in energy technology equipment include high field strengths at edges with small radii or defects within insulation materials itself. Depending on the location and extent of the occurrence, partial discharge events may cause lasting damage to components of equipment. In order to be able to interpret the measurement results of partial discharge monitoring with regard to the exact cause and, if necessary, to evaluate them automatically, a precise understanding of the physical phenomena that occur during a partial discharge is necessary. The physical replication of a partial discharge pulse helps to better understand, evaluate, and interpret measurement results and thus create a synergy between measurement data and model-based results.
Two Current-Based Methods for the Detection of Bearing and Impeller Faults in Variable Speed Pumps
Authors: Becker Vincent , Schwamm Thilo , Urschel Sven , Antonino-Daviu Jose Alfonso
Published: July 2021

The growing number of variable speed drives (VSDs) in industry has an impact on the future development of condition monitoring methods. In research, more and more attention is being paid to condition monitoring based on motor current evaluation. However, there are currently only a few contributions to current-based pump diagnosis. In this paper, two current-based methods for the detection of bearing defects, impeller clogging, and cracked impellers are presented. The first approach, load point-dependent fault indicator analysis (LoPoFIA), is an approach that was derived from motor current signature analysis (MCSA). Compared to MCSA, the novelty of LoPoFIA is that only amplitudes at typical fault frequencies in the current spectrum are considered as a function of the hydraulic load point. The second approach is advanced transient current signature analysis (ATCSA), which represents a time-frequency analysis of a current signal during start-up. According to the literature, ATCSA is mainly used for motor diagnosis. As a test item, a VSD-driven circulation pump was measured in a pump test bench. Compared to MCSA, both LoPoFIA and ATCSA showed improvements in terms of minimizing false alarms. However, LoPoFIA simplifies the separation of bearing defects and impeller defects, as impeller defects especially influence higher flow ranges. Compared to LoPoFIA, ATCSA represents a more efficient method in terms of minimizing measurement effort. In summary, both LoPoFIA and ATCSA provide important insights into the behavior of faulty pumps and can be advantageous compared to MCSA in terms of false alarms and fault separation.
A Novel Optimization Algorithm for Solar Panels Selection towards a Self-Powered EV Parking Lot and Its Impact on the Distribution System
Authors: El-Bayeh Claude Ziad , Zellagui Mohamed , Shirzadi Navid , Eicker Ursula
Published: July 2021

This paper proposes an original multi-criteria decision-making optimization algorithm to select the best solar panels in an existing market and optimally size the photovoltaic (PV) system for an electric vehicle parking lot (EVPL). Our proposed algorithm is called rank-weigh-rank (RWR), and it is compared to the well-known technique for order of preference by similarity to ideal solution (TOPSIS) optimization algorithm under the same conditions for validation purposes. Results show that the speed of our proposed algorithm (RWR) in finding the best solution increases exponentially compared to TOPSIS when the numbers of alternatives and criteria increase. Moreover, 77% is the probability of obtaining results with more than 80% accuracy compared to TOPSIS, which validates the efficiency of our algorithm. In addition, we were able to design an EVPL with a power self-sufficiency ratio of 60.8%, the energy self-sufficiency ratio of 74.7%, and a payback period of 10.58 years. Moreover, the renewable energy-based EVPL was able to reduce the power losses on the network by 95.7% compared to an EVPL without a renewable energy system and improve the voltage deviation.
A Theoretical Study on Reversible Solid Oxide Cells as Key Enablers of Cyclic Conversion between Electrical Energy and Fuel
Authors: Biswas Saheli , Rathore Shambhu , Kulkarni Aniruddha , Giddey Sarbjit , Bhattacharya Sankar
Published: July 2021

Reversible solid oxide cells (rSOC) enable the efficient cyclic conversion between electrical and chemical energy in the form of fuels and chemicals, thereby providing a pathway for long-term and high-capacity energy storage. Amongst the different fuels under investigation, hydrogen, methane, and ammonia have gained immense attention as carbon-neutral energy vectors. Here we have compared the energy efficiency and the energy demand of rSOC based on these three fuels. In the fuel cell mode of operation (energy generation), two different routes have been considered for both methane and ammonia; Routes 1 and 2 involve internal reforming (in the case of methane) or cracking (in the case of ammonia) and external reforming or cracking, respectively. The use of hydrogen as fuel provides the highest round-trip efficiency (62.1%) followed by methane by Route 1 (43.4%), ammonia by Route 2 (41.1%), methane by Route 2 (40.4%), and ammonia by Route 1 (39.2%). The lower efficiency of internal ammonia cracking as opposed to its external counterpart can be attributed to the insufficient catalytic activity and stability of the state-of-the-art fuel electrode materials, which is a major hindrance to the scale-up of this technology. A preliminary cost estimate showed that the price of hydrogen, methane and ammonia produced in SOEC mode would be ~1.91, 3.63, and 0.48 $/kg, respectively. In SOFC mode, the cost of electricity generation using hydrogen, internally reformed methane, and internally cracked ammonia would be ~52.34, 46.30, and 47.11 $/MWh, respectively.
Research on the Correction Method of the Capillary End Effect of the Relative Permeability Curve of the Steady State
Authors: Li Yanyan , Wang Shuoliang , Kang Zhihong , Yuan Qinghong , Xue Xiaoqiang , Yu Chunlei , Zhang Xiaodong
Published: July 2021

Relative permeability curve is a key factor in describing the characteristics of multiphase flow in porous media. The steady-state method is an effective method to measure the relative permeability curve of oil and water. The capillary discontinuity at the end of the samples will cause the capillary end effect. The capillary end effect (CEE) affects the flow and retention of the fluid. If the experimental design and data interpretation fail to eliminate the impact of capillary end effects, the relative permeability curve may be wrong. This paper proposes a new stability factor method, which can quickly and accurately correct the relative permeability measured by the steady-state method. This method requires two steady-state experiments at the same proportion of injected liquid (wetting phase and non-wetting phase), and two groups of flow rates and pressure drop data are obtained. The pressure drop is corrected according to the new relationship between the pressure drop and the core length. This new relationship is summarized as a stability factor. Then the true relative permeability curve that is not affected by the capillary end effect can be obtained. The validity of the proposed method is verified against a wide range of experimental results. The results emphasize that the proposed method is effective, reliable, and accurate. The operation steps of the proposed method are simple and easy to apply.
Method for Sizing of a PV System for Family Home Using Economic Indicators
Authors: Šimić Zvonimir , Topić Danijel , Crnogorac Ilija , Knežević Goran
Published: July 2021

This paper presents a method for finding an optimal photovoltaic (PV) system according to Croatian legislation. The PV sizing model, in which a decision on investment is made according to economic indicators, is made using MATLAB Software. Based on the input data, the monthly PV system production is calculated, and electricity price formed. According to the PV system production and electricity price, economic indicators are calculated and obtained as output data. The model input data are solar irradiation, load diagram, PV system costs and market price of electricity while the model output data are PV system production, savings, profit, incomes, Net Present Value (NPV) and Levelized Cost of Electricity (LCOE). The obtained economic indicators are presented graphically and used for decision making on an optimal PV system size. The presented model is applied and presented in a case study.
Influence of Population Income on Energy Consumption for Heating and Its CO2 Emissions in Cities
Authors: Zarco-Periñán Pedro J. , Zarco-Soto Irene M. , Zarco-Soto Fco. Javier , Sánchez-Durán Rafael
Published: July 2021

As a result of the increase in city populations, and the high energy consumption and emissions of buildings, cities in general, and buildings in particular, are the focus of attention for public organizations and utilities. Heating is among the largest consumers of energy in buildings. This study examined the influence of the income of inhabitants on the consumption of energy for heating and the CO2 emissions in city buildings. The study was carried out using equivalized disposable income as the basis for the analysis and considered the economies of scale of households. The results are shown per inhabitant and household, by independently considering each city. Furthermore, to more clearly identify the influence of the population income, the study was also carried out without considering the influence of the climate. The method was implemented in the case of Spain. For this purpose, Spanish cities with more than 50,000 inhabitants were analyzed. The results show that, both per inhabitant and per household, the higher the income of the inhabitants, the greater the consumption of energy for heating and the greater the emissions in the city. This research aimed to help energy utilities and policy makers make appropriate decisions, namely, planning for the development of facilities that do not produce greenhouse gases, and enacting laws to achieve sustainable economies, respectively. The overall aim is to achieve the objective of mitigating the impact of emissions and the scarcity of energy resources.
Numerical Study of Heat Transfer Intensification in a Circular Tube Using a Thin, Radiation-Absorbing Insert. Part 2: Thermal Performance
Authors: Jasiński Piotr Bogusław
Published: July 2021

This article is the second part of the work under the same title, which is based on the results of the research presented in the previous article: “Numerical study of heat transfer intensification in a circular tube using a thin, radiation-absorbing insert. Part 1: Thermo-hydraulic characteristics”. Part 1 presents an analysis of pressure drops and heat transfer intensification in a round tube with an insert, using the phenomenon of radiation absorption. In this paper, an analysis of the tested insert’s thermal performance (PEC) is presented, taking into account the criterion of equal pumping power. The tests were carried out for the range of Re = 5000–100,000 numbers, for various insert diameters (from 20% to 90% of the pipe diameter) and a constant temperature difference between the wall and the gas ∆T = 100 °C. The highest Nu numbers were observed for inserts with dimensionless diameters of 0.3 and 0.4, while the highest flow resistance was observed for inserts with diameters of 0.6 and 0.7 of the channel diameter. The thermal efficiency was calculated in two ways, as was the associated Nu number. These results significantly differed from each other: the maximum PEC values for method (I) reached 2, and for method (II) to 8. The common feature for both calculation methods was the fact that the maximum values of the Nu number and the thermal efficiency were observed for small Re numbers; however, as the Re number increases, PEC and Nu number decrease strongly.
An Integral Method for Natural Convection of Van Der Waals Gases over a Vertical Plate
Authors: Avramenko A. A. , Shevchuk I. V. , Kovetskaya Yu. Yu. , Dmitrenko N. P.
Published: July 2021

This paper focuses on a study of natural convection in a van der Waals gas over a vertical heated plate. In this paper, for the first time, an approximate analytical solution of the problem was obtained using an integral method for momentum and energy equations. A novel simplified form of the van der Waals equation for real gases enabled estimating the effects of the dimensionless van der Waals parameters on the normalized heat transfer coefficients and Nusselt numbers in an analytical form. Trends in the variation of the Nusselt number depending on the nature of the interaction between gas molecules and the wall were analyzed. The results of computations for a van der Waals gas were compared with the results for an ideal gas.