bluuebunny/crossref_metadata_2025 huggingface dataset:
Amniotic Fluid Mesenchymal Stromal Cells Derived from Fetuses with Isolated Cardiac Defects Exhibit Decreased Proliferation and Cardiomyogenic Potential
Authors: Jain Manali , Singh Neeta , Fatima Raunaq , Nachanekar Aditya , Pradhan Mandakini , Nityanand Soniya , Chaturvedi Chandra Prakash
Published: April 2023

Amniotic fluid mesenchymal stromal cells (AF-MSCs) represent an autologous cell source to ameliorate congenital heart defects (CHDs) in children. The AF-MSCs, having cardiomyogenic potential and being of fetal origin, may reflect the physiological and pathological changes in the fetal heart during embryogenesis. Hence, the study of defects in the functional properties of these stem cells during fetal heart development will help obtain a better understanding of the cause of neonatal CHDs. Therefore, in the present study, we compared the proliferative and cardiomyogenic potential of AF-MSCs derived from ICHD fetuses (ICHD AF-MSCs) with AF-MSCs from structurally normal fetuses (normal AF-MSCs). Compared to normal AF-MSCs, the ICHD AF-MSCs showed comparable immunophenotypic MSC marker expression and adipogenic and chondrogenic differentiation potential, with decreased proliferation, higher senescence, increased expression of DNA-damaged genes, and osteogenic differentiation potential. Furthermore, the expression of cardiac progenitor markers (PDGFR-α, VEGFR-2, and SSEA-1), cardiac transcription factors (GATA-4, NKx 2-5, ISL-1, TBX-5, TBX-18, and MeF-2C), and cardiovascular markers (cTNT, CD31, and α-SMA) were significantly reduced in ICHD AF-MSCs. Overall, these results suggest that the AF-MSCs of ICHD fetuses have proliferation defects with significantly decreased cardiomyogenic differentiation potential. Thus, these defects in ICHD AF-MSCs highlight that the impaired heart development in ICHD fetuses may be due to defects in the stem cells associated with heart development during embryogenesis.
The Expression of Affective Temperaments in Cystic Fibrosis Patients: Psychopathological Associations and Possible Neurobiological Mechanisms
Authors: Amerio Andrea , Magnani Luca , Castellani Carlo , Schiavetti Irene , Sapia Gabriele , Sibilla Francesca , Pescini Rita , Casciaro Rosaria , Cresta Federico , Escelsior Andrea , Costanza Alessandra , Aguglia Andrea , Serafini Gianluca , Amore Mario , Ciprandi Riccardo
Published: April 2023

The aim of this study was to investigate the association between Cystic Fibrosis (CF) and affective temperaments, considering the relevance of ionic balances in neural excitability, as a possible neurobiological basis for temperamental expression. A cross-sectional study involving 55 adult CF patients was conducted. Sociodemographic, clinical and therapeutic characteristics, temperamental and personality dispositions and depressive and anxiety symptoms were evaluated through standardized semi-structured and structured interviews. The majority of the enrolled CF patients were receiving Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) therapy (72.7%), and most of them had hyperthymic temperament predominance (29.1%). Different TEMPS-A (Temperament Evaluation of Memphis, Pisa, Paris, and San Diego Autoquestionnaire) dimensions were not associated with the type of CF phenotype-related mutation or with the use of CFTR-modulator therapy. However, a tendency towards irritability was noted in patients not undergoing CFTR modulator therapy (6.7 ± 4.72 vs. 4.7 ± 4.33; p = 0.13). In light of the limitations imposed by the cross-sectional nature of the study, a hyperthymic temperament was found to be protective against current or lifetime psychopathologic events, whereas the other temperaments were associated with positive psychopathological anamnesis. Based on the measurement of temperament profiles and the study of their associations with clinically relevant variables, we argue that subjecting CF patients to such a temperament assessment could prove beneficial in the transition towards integrated and personalized care.
Adolescent Aggressive Riding Behavior: An Application of the Theory of Planned Behavior and the Prototype Willingness Model
Authors: Zhao Sheng , Chen Xinyu , Liu Jianrong , Liu Weiming
Published: April 2023

Cycling has always been popular in China, especially during the years when the government encouraged green travel. Many people participate in rides to ease traffic congestion and increase transfer convenience. Due to the disorganized and tidal nature of cycling, cyclists create many conflicts with other groups. Adolescents are vulnerable road users with a strong curiosity and risk-taking mindset. Identifying the factors influencing adolescents’ aggressive riding behavior can assist in developing strategies to prevent this behavior. An online questionnaire was used to collect data on bicycling among students in a middle school in Guangzhou, China. The theory of planned behavior (TPB) and prototype willingness model (PWM) have been applied to study travel behavior and adolescent risk behavior. To investigate the impact of psychological variables on adolescent aggressive behavior, we used TPB, PWM, TPB + PWM, and an integrated model. Behavioral intentions are greatly influenced by attitudes, subjective norms, and perceived behavioral control. Both descriptive and moral norms played a role in behavioral willingness. The integrated model explained 18.3% more behavioral variance than the TPB model. The social reactive pathway explained more variance in behavior than the rational path.
Fabrication-Aware Joint Clustering in Freeform Space-Frames
Authors: Koronaki Antiopi , Shepherd Paul , Evernden Mark
Published: April 2023

The geometrical variability in the joints of large-scale, doubly-curved space-frame structures can have a substantial impact on the time and cost of their construction. This paper proposes a novel framework to assess the construction complexity of space-frame structures as a factor of the geometrical variability and fabrication of their joints, to promote the informed design of the fabrication process. The k-means algorithm was used to cluster space-frame joints into fabrication batches, providing an overview of the variability distribution. A novel initialisation method was developed that allows the algorithm to adapt to project-specific inputs, substantially improving cluster compactness. Overlaying the clustering results with the properties of different fabrication processes provides an accurate estimation of the construction complexity of alternative fabrication options. The method was applied to a large-scale case study to demonstrate the benefits in practice. Alternative fabrication scenarios were assessed in the early stages of the design development, leading to the informed design of the fabrication process and hence to the efficient construction of large-scale, complex structures.
Civil Engineering Standard Measurement Method Adoption Using a Structural Equation Modelling Approach
Authors: Muzafar Siti Asmiza , Ali Kherun Nita , Kassem Mukhtar A. , Khoiry Muhamad Azry
Published: April 2023

The adoption of a standardized technique of measuring in civil construction projects is influenced both by the drivers and the strategies used, particularly in emerging nations such as Malaysia. So, the authors of this study used structural equation modeling and the PLS-SEM technique to inquire into the connection between the driver and strategy elements of the adoption. Quantity surveyors at quantity surveying consultancy companies using the standard measurement technique were polled using a questionnaire. Using the PLS-SEM technique provided by the SmartPLS 3 software, a hierarchical model was created to determine the components and their impacts on the adoption of the measuring method. The results indicated that all classes considerably influence the adoption of the standard technique of assessment, but the barrier factors had the most impact. The adoption of a standardized technique of measuring was significantly impacted by the driver and strategy elements. The coefficient of determination (R-squared value) of 0.400 indicates that the dependent variable(s) can be explained by the predictor variable(s) in the model. Moreover, Q2 is significantly different from zero, suggesting that endogenous latent components may be predicted by the conceptual model. Because of its high explanatory power, the created model has given a goodness-of-fit (GoF) index of 0.214. This means that the model adequately represents the link between the variables that affect measuring technique adoption and the effects of these factors. The first stage in determining what motivates people to utilize the most up-to-date standardized measurement approach in civil engineering construction projects is to develop a research model of the variables and to explain the connection between the driver and strategy factors on standard adoption.
Accurate and Fast Deep Learning Dose Prediction for a Preclinical Microbeam Radiation Therapy Study Using Low-Statistics Monte Carlo Simulations
Authors: Mentzel Florian , Paino Jason , Barnes Micah , Cameron Matthew , Corde Stéphanie , Engels Elette , Kröninger Kevin , Lerch Michael , Nackenhorst Olaf , Rosenfeld Anatoly , Tehei Moeava , Tsoi Ah Chung , Vogel Sarah , Weingarten Jens , Hagenbuchner Markus , Guatelli Susanna
Published: April 2023

Microbeam radiation therapy (MRT) utilizes coplanar synchrotron radiation beamlets and is a proposed treatment approach for several tumor diagnoses that currently have poor clinical treatment outcomes, such as gliosarcomas. Monte Carlo (MC) simulations are one of the most used methods at the Imaging and Medical Beamline, Australian Synchrotron to calculate the dose in MRT preclinical studies. The steep dose gradients associated with the 50μm-wide coplanar beamlets present a significant challenge for precise MC simulation of the dose deposition of an MRT irradiation treatment field in a short time frame. The long computation times inhibit the ability to perform dose optimization in treatment planning or apply online image-adaptive radiotherapy techniques to MRT. Much research has been conducted on fast dose estimation methods for clinically available treatments. However, such methods, including GPU Monte Carlo implementations and machine learning (ML) models, are unavailable for novel and emerging cancer radiotherapy options such as MRT. In this work, the successful application of a fast and accurate ML dose prediction model for a preclinical MRT rodent study is presented for the first time. The ML model predicts the peak doses in the path of the microbeams and the valley doses between them, delivered to the tumor target in rat patients. A CT imaging dataset is used to generate digital phantoms for each patient. Augmented variations of the digital phantoms are used to simulate with Geant4 the energy depositions of an MRT beam inside the phantoms with 15% (high-noise) and 2% (low-noise) statistical uncertainty. The high-noise MC simulation data are used to train the ML model to predict the energy depositions in the digital phantoms. The low-noise MC simulations data are used to test the predictive power of the ML model. The predictions of the ML model show an agreement within 3% with low-noise MC simulations for at least 77.6% of all predicted voxels (at least 95.9% of voxels containing tumor) in the case of the valley dose prediction and for at least 93.9% of all predicted voxels (100.0% of voxels containing tumor) in the case of the peak dose prediction. The successful use of high-noise MC simulations for the training, which are much faster to produce, accelerates the production of the training data of the ML model and encourages transfer of the ML model to different treatment modalities for other future applications in novel radiation cancer therapies.
Temporal Machine Learning Analysis of Prior Mammograms for Breast Cancer Risk Prediction
Authors: Li Hui , Robinson Kayla , Lan Li , Baughan Natalie , Chan Chun-Wai , Embury Matthew , Whitman Gary J. , El-Zein Randa , Bedrosian Isabelle , Giger Maryellen L.
Published: April 2023

The identification of women at risk for sporadic breast cancer remains a clinical challenge. We hypothesize that the temporal analysis of annual screening mammograms, using a long short-term memory (LSTM) network, could accurately identify women at risk of future breast cancer. Women with an imaging abnormality, which had been biopsy-confirmed to be cancer or benign, who also had antecedent imaging available were included in this case–control study. Sequences of antecedent mammograms were retrospectively collected under HIPAA-approved guidelines. Radiomic and deep-learning-based features were extracted on regions of interest placed posterior to the nipple in antecedent images. These features were input to LSTM recurrent networks to classify whether the future lesion would be malignant or benign. Classification performance was assessed using all available antecedent time-points and using a single antecedent time-point in the task of lesion classification. Classifiers incorporating multiple time-points with LSTM, based either on deep-learning-extracted features or on radiomic features, tended to perform statistically better than chance, whereas those using only a single time-point failed to show improved performance compared to chance, as judged by area under the receiver operating characteristic curves (AUC: 0.63 ± 0.05, 0.65 ± 0.05, 0.52 ± 0.06 and 0.54 ± 0.06, respectively). Lastly, similar classification performance was observed when using features extracted from the affected versus the contralateral breast in predicting future unilateral malignancy (AUC: 0.63 ± 0.05 vs. 0.59 ± 0.06 for deep-learning-extracted features; 0.65 ± 0.05 vs. 0.62 ± 0.06 for radiomic features). The results of this study suggest that the incorporation of temporal information into radiomic analyses may improve the overall classification performance through LSTM, as demonstrated by the improved discrimination of future lesions as malignant or benign. Further, our data suggest that a potential field effect, changes in the breast extending beyond the lesion itself, is present in both the affected and contralateral breasts in antecedent imaging, and, thus, the evaluation of either breast might inform on the future risk of breast cancer.
Epigenetic Rewiring of Metastatic Cancer to the Brain: Focus on Lung and Colon Cancers
Authors: Morotti Annamaria , Gentile Francesco , Lopez Gianluca , Passignani Giulia , Valenti Luca , Locatelli Marco , Caroli Manuela , Fanizzi Claudia , Ferrero Stefano , Vaira Valentina
Published: April 2023

Distant metastasis occurs when cancer cells adapt to a tissue microenvironment that is different from the primary organ. This process requires genetic and epigenetic changes in cancer cells and the concomitant modification of the tumor stroma to facilitate invasion by metastatic cells. In this study, we analyzed differences in the epigenome of brain metastasis from the colon (n = 4) and lung (n = 14) cancer and we compared these signatures with those found in primary tumors. Results show that CRC tumors showed a high degree of genome-wide methylation compared to lung cancers. Further, brain metastasis from lung cancer deeply activates neural signatures able to modify the brain microenvironment favoring tumor cells adaptation. At the protein level, brain metastases from lung cancer show expression of the neural/glial marker Nestin. On the other hand, colon brain metastases show activation of metabolic signaling. These signatures are specific for metastatic tumors since primary cancers did not show such epigenetic derangements. In conclusion, our data shed light on the epi/molecular mechanisms that colon and lung cancers adopt to thrive in the brain environment.
Intercalated-Laurate-Enhanced Photocatalytic Activities of Ni/Cr-Layered Double Hydroxides
Authors: Zhang Xuehua , Jiang Zili , Sun Fengting , Chen Yuhan , Shi Changrong , Zhang Zhanying , Qian Guangren , Ruan Xiuxiu
Published: April 2023

Laurate (LA−)-intercalated nickel–chromium-layered double hydroxides (LDHs) were synthesized using the co-precipitation method and investigated as a potential photocatalyst for methylene orange (MO) degradation. For comparison, a series of LDHs with various molar ratios of Ni2+(or Mg2+)/Cr3+(or Fe3+)/LA−(or CO32−) were prepared. X−ray diffraction (XRD) and element analysis showed that Ni/Cr(2/1)−1.0 LA LDH had the most ordered crystal structure, and showed the same photocatalytic decolorization performance as Mg/Cr(2/1)−1.0LA LDH towards MO, which was significantly superior to Ni/Cr−CO3 LDH, Ni/Fe(2/1)−1.0LA LDH, and Ni/Cr−CO3 LDH with LA−, and Cr3+ with LA−. The photocatalytic removal rate of MO with the initial concentration of 100 mg/L by Ni/Cr(2/1)−1.0LA LDH (0.5 g/L) could be up to 80% with UV light irradiation for 3 h, which was almost twice higher than that of the sorption test. The photocatalytic reaction was in accordance with the pseudo-first-order kinetics, which implied that the catalytic process took place on the surface of the catalyst. All the results indicate the photodegradation of MO by Ni/Cr−LA LDHs was enhanced by the sorption of MO onto the intercalated LA− in the interlayer. The free radical capture experiments suggest that the main role of the photocatalytic mechanism of Ni/Cr−LA LDHs could be the •O2− with high oxidation activity produced by the electron-hole pairs of LDH, as excited by UV light. Additionally, the •O2− further reacted with the adjacent MO molecule pre-sorbed on the intercalated LA.
Editorial: Special Issue on “Advances on Catalysts Based on Copper”
Authors: Bossola Filippo , Scotti Nicola
Published: April 2023

Copper-based catalysts are very active in a wide range of different reactions, such as methanol synthesis, steam reforming/WGS, hydrogenation/dehydrogenation/transfer hydrogenation, oxidation, dehydrogenative coupling, acid-base reactions, etc [...]
New Trends in Catalytic Conversion of Glycerol
Authors: Lu Tianliang , Xu Chunbao Charles
Published: April 2023

Glycerol is the core byproduct in the production of biodiesel [...]
Nickel-Doped ZnO Porous Sea Urchin Nanostructures with Various Amounts of Oxygen Defects for Volatile Organic Compound Detection
Authors: Ren Haibo , Weng Huaipeng , Dong Xumeng , Huang Jiarui , Joo Sang Woo
Published: April 2023

Porous sea urchin-like nickel-doped ZnO with various nickel contents and high specific surface area were synthesized using a solution method followed by calcination. The nickel-doped ZnO products consisted of numerous porous nanoleaves. The Ni content in these products ranged from 5% to 20%. The Ni dopants in the ZnO lattice were verified by X-ray diffraction and X-ray photoelectron spectroscopy. The sensors based on nickel-doped ZnO sea urchins showed superior sensing performance for some volatile organic compounds (VOCs). ZnO sea urchins with 10% nickel doping exhibited the best gas-sensing performance, including a low working temperature, short response/recovery time, and high sensor response. In particular, the 10% Ni-doped ZnO sea urchin sensor exhibited a response of 84.4 with response/recovery times of 17/20 s towards 100 ppm formaldehyde vapor. These superior sensing behaviors were attributed mainly to a suitable Ni content with high content of oxygen defects, small nanocrystals, and a porous hierarchical structure with a high specific surface area.
Flexible Miniaturized Electrochemical Sensors Based on Multiwalled Carbon Nanotube-Chitosan Nanomaterial for Determination of Nitrite in Soil Solutions
Authors: Gurban Ana-Maria , Zamfir Lucian-Gabriel , Epure Petru , Șuică-Bunghez Ioana-Raluca , Senin Raluca Mădălina , Jecu Maria-Luiza , Jinga Maria Lorena , Doni Mihaela
Published: April 2023

Flexible screen-printed electrodes (SPE) were modified in a simple manner with different composite nanomaterials based on carbon allotropes, polymers, and metallic nanoparticles, for amperometric detection of nitrites in soil. Multiwalled carbon nanotubes (MWCNT), chitosan (CS), silver nanoparticles (AgNPs), 1,8-diaminonaphthalene (1,8-DAN), and a sol-gel (SG) matrix were used for modification of the carbon paste working electrodes. Sensitive and selective detection of nitrite was achieved by using a MWCNT-CS-modified sensor, in acetate buffer at pH 5, at an applied potential of 0.58 V vs. Ag/AgCl. The MWCNT-CS-based sensor displayed a specific sensitivity of 204.4 mA·M−1·cm−2, with a detection limit of 2.3 µM (S/N = 3) in a linear range up to 1.7 mM, showing good stability, reproducibility, and selectivity towards other interfering species. A miniaturized portable system using the developed flexible electrochemical MWCNT-CS-based sensors was dedicated for the detection of nitrite in different samples of soil solutions extracted by using suction lysimeters.
Crystal Structure and Functional Characterization of an S-Formylglutathione Hydrolase (BuSFGH) from Burkholderiaceae sp.
Authors: Hwang Jisub , Do Hackwon , Shim Youn-Soo , Lee Jun Hyuck
Published: April 2023

S-formylglutathione hydrolases (SFGHs) catalyze the hydrolysis of S-formylglutathione to formate and glutathione using the conserved serine hydrolase catalytic triad residues (Ser-His-Asp). SFGHs have broad substrate specificity, including, for example, ester bond-containing substrates. Here, we report the crystal structure of Burkholderiaceae sp. SFGH (BuSFGH) at 1.73 Å resolution. Structural analysis showed that the overall structure of BuSFGH has a typical α/β hydrolase fold, with a central β-sheet surrounded by α-helices. Analytical ultracentrifugation analysis showed that BuSFGH formed a stable dimer in solution. The enzyme activity assay indicated that BuSFGH has a high preference for short-chain p-nitrophenyl esters, such as p-nitrophenyl acetate. The activity of BuSFGH toward p-nitrophenyl acetate was five times higher than that of p-nitrophenyl butylate. Molecular modeling studies on the p-nitrophenyl acetate-bound BuSFGH structure indicate that Gly52, Leu53, Trp96, His147, Ser148, Trp182, Phe228, and His259 residues may be crucial for substrate binding. Collectively, these results are useful for understanding the substrate-binding mechanism and substrate specificity of BuSFGH. They can also provide useful insights for designing modified BuSFGHs with different substrate specificities.
Enhanced Ferromagnetism Induced by Chemical Doping and Epitaxial Strain in La0.8Sr0.2CoO3 Films
Authors: Xie Changzheng , Chen Zhijie , Wang Xinghua , Meng Ying , Wang Yihao
Published: April 2023

The perovskite LaCoO3 and La0.8Sr0.2CoO3 thin films were synthesized successfully by a polymer-assisted deposition method. The structural characterization and thermal decomposition measurements indicate that appropriately increasing the annealing temperature is helpful in improving the film crystallinity. Compared with LaCoO3 films, the Curie temperature is enhanced to a higher temperature in La0.8Sr0.2CoO3 films, which is attributed to the changes in both the valence state and spin state induced by the chemical doping. In addition, a broad transition temperature region is observed in La0.8Sr0.2CoO3 films, revealing the existence of inhomogeneous ground states in this system.
Structural Peculiarities of Natural Ballas—Spheroidal Variety of Polycrystalline Diamond
Authors: Shiryaev Andrei A. , Kaminsky Felix V. , Pavlushin Anton D. , Yapaskurt Vasily O. , Zolotov Denis A. , Averin Alexei A. , Zhilicheva Olga M. , Nickolsky Maximilian S. , Kuznetsova Olga V.
Published: April 2023

Ballas is a rare polycrystalline diamond variety characterized by a radially oriented internal structure and spheroidal outer shape. The origin of natural ballases remains poorly constrained. We present the results of a comprehensive investigation of two classic ballas diamonds from Brazil. External morphology was studied using SEM, high-resolution 3D optical microscopy, and X-ray tomography. Point and extended defects were examined on polished central plates using infra-red, photo- and cathodoluminescence spectroscopies, and electron back-scattering diffraction; information about nanosized inclusions was inferred from Transmission Electron Microscopy. The results suggest that fibrous diamond crystallites comprising ballas are split with pronounced rotation, causing concentric zoning of the samples. Pervasive feather-like luminescing structural features envelop single crystalline domains and most likely represent fibers with non-crystallographic branching. These features are enriched in N3 point defects. Twinning is not common. The nitrogen content of the studied samples reaches 700 at.ppm; its concentration gradually increases from the center to the rim. Annealing of the ballases took place at relatively high temperatures of 1125–1250 °C; the annealing continued even when the samples were fully grown, as suggested by the presence of the H4 nitrogen-related defects in the outer rim. Presumably, the ballas diamond variety was formed at high supersaturation but in conditions favoring a small growth kinetic coefficient. The carbon isotopic composition of the studied ballases (δ13C = −5.42, −7.11‰) belongs to the main mode of mantle-derived diamonds.
Identification of Pseudo-nitzschia Cryptic Species Collected in the Gulf of Naples Using Whole-Cell Fluorescent In Situ Hybridization: From Cultured Sample to Field Test
Authors: Ferrari Michele , Barra Lucia , Ruffolo Luisa , Muto Antonella , Galasso Christian , Percopo Isabella , Greco Silvestro , Cozza Radiana
Published: April 2023

The planktonic diatom genus Pseudo-nitzschia contains several genetically closely related species that can produce domoic acid, a potent neurotoxin known to cause amnesic shellfish poisoning (ASP). An early identification and an adequate monitoring of the potential toxic Pseudo-nitzschia spp. are necessary. However, effective monitoring programs are time consuming due, in some cases, to the cell morphology similarities among species, determined with light microscopy, that can result in insufficient data to give a definitive species and toxins attribution. In this paper, Whole-Cell Fluorescent In Situ Hybridization (WC-FISH) has been evaluated as a powerful tool to detect and enumerate harmful cryptic and/or pseudo-cryptic Pseudo-nitzschia spp. collected in the Gulf of Naples. Fluorescently labelled probes directed against the ribosomal RNA (rRNA) of the 28S large subunit (LSU) were used. In particular, five probes detecting four cryptic species of Pseudo-nitzschia delicatissima complex and one specific for Pseudo-nitzschia multistriata gave good results for the molecular identification of potentially toxic target species in natural samples. Finally, we can state that the WC-FISH method, to identify Pseudo-nitzschia species, is faster and more cost-effective if compared with other rDNA-based methods.
The Fate of Guzmania monostachia in Florida Rests with Humans
Authors: Krupar Shelby , Naranjo Andre A. , Godden Grant , Cellinese Nico
Published: April 2023

Land use changes by humans have eliminated more than half of the wetlands in Florida over the last 200 years, and additional losses are anticipated as a consequence of climate change and ongoing development activities that will accommodate a rapidly growing human population. Both spell danger for the biodiversity and ecosystem services in Florida, and data are needed to inform conservation priorities and actions concerning threatened or endangered wetland species. We modeled the projected distribution of an endangered epiphyte native to the forested wetlands in South Florida, Guzmania monostachia (Bromeliaceae), in response to changing climate and sea level conditions. We constructed ecological niche models (ENMs) under the present framework by using georeferenced occurrence points and projected them into the past and future under different scenarios. Our future climate-based ENMs predicted small losses in suitable habitat for G. monostachia in South Florida, with expansions into higher latitudes due to the warmer climate. In contrast, the models predicted a considerable, although non-detrimental, loss of suitable habitat due to rising sea levels. The combined results suggest that human activity is and will remain the largest threat to G. monostachia in Florida, and conservation efforts should focus on preserving existing habitats that will remain above sea level and explore possibilities for assisted migration.
Causes and Measures of Poverty, Inequality, and Social Exclusion: A Review
Authors: Halkos George E. , Aslanidis Panagiotis-Stavros C.
Published: April 2023

Prevailing measures on the topics of monetary and non-monetary poverty—as well as economic and carbon inequality—are being critically assessed under sustainable development goals (SDGs) with a worldwide perspective. On the one hand, the poverty headcount ratio and the indices poverty gap, poverty severity, and Watts are assessed as core poverty indices. On the other hand, important inequality measures such as the Gini index and the Palma ratio are evaluated in order to find their potentials for policymaking. Furthermore, social exclusion (with the extreme forms of aporophobia and homelessness) has detrimental ramifications on human wellbeing and disturbs public provision policies. Thus, poverty, inequality, and social exclusion are integral parts of SDGs (1, 6 and 10), emphasizing the multidisciplinary nature of the above issues. Additionally, intrinsic elements of Agenda 2030 and the measuring of poverty, inequality, and polarization would significantly improve integrated policy pathways in the national and international fora.
Study of Channel-Type Dynamic Weighing System for Goat Herds
Authors: He Zhiwen , Wang Kun , Chen Jingjing , Xin Jile , Du Hongwei , Han Ding , Guo Ying
Published: April 2023

This paper proposes a design method for a channel-type sheep dynamic weighing system to address the current problems encountered by pastoralists at home and abroad, such as time-consuming sheep weighing, difficulties with data collection, and management of the stress response in sheep. The complete system includes a hardware structure, dynamic characteristics, and a Kalman-aggregate empirical modal decomposition algorithm (Kalman-EEMD algorithm) model for dynamic data processing. The noise suppression effects of the Kalman filter, the empirical modal decomposition (EMD), and the ensemble empirical modal decomposition (EEMD) algorithms are discussed for practical applications. Field tests showed that the Kalman-EEMD algorithm model has the advantages of high accuracy, efficiency, and reliability. The maximum error between the actual weight of the goats and the measured value in the experiments was 1.0%, with an average error as low as 0.40% and a maximum pass time of 2 s for a single goat. This meets the needs for weighing accuracy and goat flock weighing rates.
Machine Translation Systems Based on Classical-Statistical-Deep-Learning Approaches
Authors: Sharma Sonali , Diwakar Manoj , Singh Prabhishek , Singh Vijendra , Kadry Seifedine , Kim Jungeun
Published: April 2023

Over recent years, machine translation has achieved astounding accomplishments. Machine translation has become more evident with the need to understand the information available on the internet in different languages and due to the up-scaled exchange in international trade. The enhanced computing speed due to advancements in the hardware components and easy accessibility of the monolingual and bilingual data are the significant factors that have added up to boost the success of machine translation. This paper investigates the machine translation models developed so far to the current state-of-the-art providing a solid understanding of different architectures with the comparative evaluation and future directions for the translation task. Because hybrid models, neural machine translation, and statistical machine translation are the types of machine translation that are utilized the most frequently, it is essential to have an understanding of how each one functions. A comprehensive comprehension of the several approaches to machine translation would be made possible as a result of this. In order to understand the advantages and disadvantages of the various approaches, it is necessary to conduct an in-depth comparison of several models on a variety of benchmark datasets. The accuracy of translations from multiple models is compared using metrics such as the BLEU score, TER score, and METEOR score.
A Novel Fuzzy-Logic-Based Control Strategy for Power Smoothing in High-Wind Penetrated Power Systems and Its Validation in a Microgrid Lab
Authors: Ochoa Danny , Martinez Sergio , Arévalo Paul
Published: April 2023

Wind power generation has undergone significant development in recent decades due to its environmental advantages and its economic competitiveness. However, its increasing level of penetration is not exempt from drawbacks, such as those derived from the fluctuating nature of the wind. To reduce its negative incidence on grid power quality and stability, different techniques have been developed, such as those based on power smoothing. In these techniques, there is a research gap on the adjustment of the time constant that adapts to the needs of the smoothing, avoiding uncertain results, computational efforts and delays in the response of the control. This paper addresses the problem, proposing a novel method for power smoothing in a wind turbine by using a fuzzy-logic-based supercapacitor storage system and time-constant fitting, with a first-order adaptive transfer function. The method considers as input variables the active power generated by the wind turbine and the state of charge of the supercapacitor, both sampled simultaneously. After a computation process, the proposal generates active power set-point values that the supercapacitor must produce to compensate for the intermittency of the wind, seen from the point of connection to the grid. The results were validated experimentally with comprehensive laboratory tests.
An Instruction-Driven Batch-Based High-Performance Resource-Efficient LSTM Accelerator on FPGA
Authors: Mao Ning , Yang Haigang , Huang Zhihong
Published: April 2023

In recent years, long short-term memory (LSTM) has been used in many speech recognition tasks, due to its excellent performance. Due to a large amount of calculation and complex data dependencies of LSTM, it is often not so efficient to deploy on the field-programmable gate array (FPGA) platform. This paper proposes an LSTM accelerator, driven by a specific instruction set. The accelerator consists of a matrix multiplication unit and a post-processing unit. The matrix multiplication unit uses staggered timing of read data to reduce register usage. The post-processing unit can complete various calculations with only a small amount of digital signal processing (DSP) slices, through resource sharing, and at the same time, the memory footprint is reduced, through the well-designed data flow design. The accelerator is batch-based and capable of computing data from multiple users simultaneously. Since the calculation process of LSTM is divided into a sequence of instructions, it is feasible to execute multi-layer LSTM networks as well as large-scale LSTM networks. Experimental results show that our accelerator can achieve a performance of 2036 GOPS at 16-bit data precision, while having higher hardware utilization compared to previous work.
Kinetics and Structural Optimization of Cobalt-Oxide Honeycomb Structures Based on Thermochemical Heat Storage
Authors: Xiao Gang , Wang Zhide , Ni Dong , Zhu Peiwang
Published: April 2023

Thermochemical heat storage is an important solar-heat-storage technology with a high temperature and high energy density, which has attracted increasing attention and research in recent years. The mono-metallic redox pair Co3O4/CoO realizes heat storage and exothermic process through a reversible redox reaction. Its basic principle is to store energy by heat absorption through a reduction reaction during high-irradiation hours (high temperature) and then release heat through an exothermic-oxidation reaction during low-irradiation hours (low temperature). This paper presents the design of a cobalt-oxide honeycomb structure, which is extruded from pure Co3O4, a porous media with a high heat-storage density and a high conversion rate. Based on the experimental data, a three-dimensional axisymmetric multi-physics numerical model was developed to simulate the flow, heat transfer, mass transfer, and chemical reaction in the thermochemical heat-storage reactor. Unlike the previous treatment approach of equating chemical reactions with surface reactions, the model in this paper considers the consumption and generation of solids and the diffusion and transfer of oxygen in the porous medium during the reaction process, which brings the simulation results closer to the real values. Finally, the influence of the physical parameters of the honeycomb-structured body on the storage and exothermic process is explored in a wide range. The simulation results show that the physical-parameter settings and structural design of the cobalt-oxide honeycomb structure used in this paper are reasonable, and are conducive to improving its charging/discharging performance.
Virtual Development of Advanced Thermal Management Functions Using Model-in-the-Loop Applications
Authors: Müller Jonas , Besser Nico , Hermsen Philipp , Pischinger Stefan , Knauf Jürgen , Bagherzade Pooya , Fryjan Johannes , Balazs Andreas , Gottorf Simon
Published: April 2023

Development challenges in the automotive industry are constantly increasing due to the high number of vehicle variants, the growing complexity of powertrains, and future legal requirements. In order to reduce development times while maintaining a high level of product quality and financial feasibility, the application of new model-based methods for virtual powertrain calibration is a particularly suitable approach. In this context, TME and FEV combine advanced thermal management models with electronic control unit (ECU) models for model-in-the-loop applications. This paper presents a development process for ECU and on-board diagnostics (OBD) functions of thermal management systems in hybrid electric vehicles. Thanks to the highly accurate 1D/3D-models, optimal control strategies for electrically actuated components can be developed in early development phases. Virtual sensors for local temperatures are developed for the ECU software to enable a cost-effective use of dedicated control functions. Furthermore, an application for OBD cooling system leakage detection is shown. Finally, the transferability of the methodology to a battery cooling system is demonstrated.
Analysis of the Thermo-Aeraulic Behavior of a Heated Supply Air Window in Forced Convection: Numerical and Experimental Approaches
Authors: Zeiny Salem , Cherif Yassine , Lassue Stephane
Published: April 2023

This paper presents work intended to characterize air flow and convective heat transfers within a ventilated window. This window is a device that allows for the entry of fresh air into a building while simultaneously preheating it in order to satisfy requirements in terms of air quality and thermal comfort in inhabited spaces. Therefore, this essential component of the building envelope functions herein as a heat exchanger with its own geometric characteristics and exchange conditions. In this research, a dual numerical and experimental approach has been implemented in order to highlight the temperatures, velocities and heat flux fields both at the glazing surfaces and in the ventilated air gaps. Several turbulence models were tested using CFD software (ANSYS-FLUENT®); their results were compared with each other as well as with the experimental results. This study shows that the air gap geometry in the window induces flow disturbances, recirculation phenomena and non-uniform heat exchanges, all of which prove to be important in terms of overall component performance. With regard to modeling and, in particular, at the level of turbulence models, the results obtained indicate that the model GEKO is best suited to the configuration under study when the phenomena of turbulent forced convection dominate the dynamics of the transfers. The k-ε models reveal a tremendous weakness in precisely estimating the problem’s characteristic quantities. From an experimental point of view, local measurements of thermal fluxes and temperatures demonstrate high efficiency with regard to experimental technique, which in turn could be extended to many different configurations for the local evaluation of convection heat transfer.
LVRT and Reactive Power/Voltage Support of Utility-Scale PV Power Plants during Disturbance Conditions
Authors: Alrumayh Omar , Sayed Khairy , Almutairi Abdulaziz
Published: April 2023

This paper proposes a control technique for a large-scale grid-connected photovoltaic (PV) plant that maintains the connection of an inverter to the grid voltage under different types of faults, while injecting a reactive power to accommodate the required grid connection. This control strategy is suggested to improve the low-voltage ride-through (LVRT) capability of grid-connected PV power generation plants. A 20 MW solar PV power plant is modeled and simulated using Matlab/Simulink. The power plant is composed of 10 parallel groups of arrays with a power rating of 2 MWp. The solar PV arrays are connected to a medium-voltage side-rated 22 KV to the utility grid. A dynamic analysis of the grid-connected large-scale solar PV power plant is introduced. This analysis is accomplished in order to determine the impact of three-phase short-circuits at the point of common-coupling (PCC), where the solar PV power station is connected to ensure a practical voltage level by injecting active and reactive power. The reactive power support allows for faster restoration of voltage values at the PCC. When subjected to transient disturbances, the stability of the studied system relies on both the type of the disturbance and the initial operating situation. The disturbance may be either small, resulting from electrical load changes, or large, such as from a transmission line short-circuit (fault) and significant generator loss.
Graph-Based Computational Methods for Efficient Management and Energy Conservation in Smart Cities
Authors: Ernst Sebastian , Kotulski Leszek , Sędziwy Adam , Wojnicki Igor
Published: April 2023

Computational methods play a significant role in reducing energy consumption in cities. Many different sensor networks (e.g., traffic intensity sensors, intelligent cameras, air quality monitoring systems) generate data that can be useful for both efficient management (including planning) and reducing energy usage. Street lighting is one of the most significant contributors to urban power consumption. This paper presents a summary of recent attempts to use computational methods to reduce energy usage by lighting systems, with special focus on graph-based methods. Such algorithms require all the necessary data to be integrated, in order to function properly: this task is not trivial, and is very time-consuming; therefore, the second part of the paper proposes a novel approach to integrating urban datasets and automating the optimisation process. In two practical examples, we show how spatially triggered graph transformations (STGT) can be used to build a model based on the road network map, sensor locations and street lighting data, and to introduce semantic relations between the objects, including utilisation of existing infrastructure, and planning of development to maximise efficiency.
Short-Term Effects of Anthropogenic Disturbances on Stand Structure, Soil Properties, and Vegetation Diversity in a Former Virgin Mixed Forest
Authors: Braga Cosmin Ion , Crisan Vlad Emil , Petritan Ion Catalin , Scarlatescu Virgil , Vasile Diana , Lazar Gabriel , Petritan Any Mary
Published: April 2023

Despite the sharply growing interest in the disturbances occurring in primary forests, little is known about the response of European virgin forests to anthropogenic disturbance. The present study investigated the effect of the first silvicultural interventions that took place nine years earlier in a former virgin forest (FVF). Changes in the stand structure, environmental characteristics, and diversity of ground vegetation were studied in comparison with a nearby virgin forest (VF), both consisting of a mixture of European beech and silver fir. While the tree density did not differ significantly between the two forests, the number of large trees, the basal area, and the stand volume were significantly reduced in the FVF. The deadwood volume was twice as great in the VF as in the FVF and was found in both forests, particularly from silver fir. Despite significantly better light conditions in the FVF, natural regeneration was not significantly higher than in the VF. However, a slight improvement in the proportion of silver fir and other tree species into total regeneration was reported. The soil temperature was significantly higher in the FVF, independent of the measurement season, while the soil moisture showed a higher value in the VF only in spring. The FVF is characterized by a greater soil CO2 emission, which is especially significant in summer and fall. The diversity of the ground vegetation did not yet react significantly to the silvicultural intervention. These preliminary findings are important in drawing suitable forest management practices that need to be applied in mixed beech–silver fir stands, especially in terms of maintaining species diversity. However, the short time frame since the intervention obliges further research on this VF–FVF pair over the next 10–20 years, at least regarding silver fir dynamics.
Adult Trees Cryptomeria japonica (Thunb. ex L.f.) D. Don Micropropagation: Factors Involved in the Success of the Process
Authors: Rojas-Vargas Alejandra , Montalbán Itziar A. , Moncaleán Paloma
Published: April 2023

Cryptomeria japonica (Thunb. ex L.f.) D. Don is a commercial tree native to Japan and is one of the most important forest species in that country and the Azores (Portugal). Because of the quality of C. japonica timber, several genetic improvement programs have been performed. Recently, some studies focusing on C. japonica somatic embryogenesis have been carried out. However, in this species, this process uses immature seeds as initial explants, and for this reason, it is not possible to achieve the maximum genetic gain (100% genetic of the donor plant). Although some studies have been made applying organogenesis to this species, the success of the process in adult trees is low. For this reason, our main goal was to optimize the micropropagation method by using trees older than 30 years as a source of plant material. In this sense, in a first experiment, we studied the effect of different types of initial explants and three basal culture media on shoot induction; then, two sucrose concentrations and two light treatments (LEDs versus fluorescent lights) were tested for the improvement of rooting. In a second experiment, the effects of different plant growth regulators (6-benzylaminopurine, meta-topolin, and thidiazuron) on shoot induction and the subsequent phases of the organogenesis process were analyzed. The cultures produced the highest number of shoots when QL medium (Quoirin and Lepoivre, 1977) and long basal explants (>1.5 cm) were used; the shoots obtained produced a higher number of roots when they were grown under red LED lights. Moreover, root induction was significantly higher in shoots previously induced with meta-topolin.