bluuebunny/crossref_metadata_2025 huggingface dataset:
Plasma Myostatin Increases with Age in Male Youth and Negatively Correlates with Vitamin D in Severe Pediatric Obesity
Authors: Baumgartner Margot , Lischka Julia , Schanzer Andrea , de Gier Charlotte , Walleczek Nina-Katharina , Greber-Platzer Susanne , Zeyda Maximilian
Published: May 2022

Obesity already causes non-communicable diseases during childhood, but the mechanisms of disease development are insufficiently understood. Myokines such as myostatin and irisin are muscle-derived factors possibly involved in obesity-associated diseases. This explorative study aims to investigate whether myostatin and irisin are associated with metabolic parameters, including the vitamin D status in pediatric patients with severe obesity. Clinical, anthropometric and laboratory data from 108 patients with severe obesity (>97th percentile) aged between 9 and 19 years were assessed. Myostatin, its antagonist follistatin, and irisin, were measured from plasma by ELISA. Myostatin concentrations, particularly in males, positively correlated with age and pubertal stage, as well as metabolic parameters such as insulin resistance. Irisin concentrations correlated positively with HDL and negatively with LDL cholesterol values. For follistatin, the associations with age and pubertal stage were inverse. Strikingly, a negative correlation of myostatin with serum vitamin D levels was observed that remained significant after adjusting for age and pubertal stage. In conclusion, there is an independent association of low vitamin D and elevated myostatin levels. Further research may focus on investigating means to prevent increased myostatin levels in interventional studies, which might open several venues to putative options to treat and prevent obesity-associated diseases.
Effects of Vitamin D Supplementation on COVID-19 Related Outcomes: A Systematic Review and Meta-Analysis
Authors: Hosseini Banafsheh , El Abd Asmae , Ducharme Francine M.
Published: May 2022

The COVID-19 outbreak has rapidly expanded to a global pandemic; however, our knowledge is limited with regards to the protective factors against this infection. The aim of this systematic literature review and meta-analysis was to evaluate the impact of vitamin D supplementation on COVID-19 related outcomes. A systematic search of relevant papers published until January 2022 was conducted to identify randomized controlled trials (RCTs) and non-randomized studies of intervention (NRISs). The primary outcomes included the risk of COVID-19 infection (primary prevention studies on uninfected individuals), hospital admission (secondary prevention studies on mild COVID-19 cases), and ICU admission and mortality rate (tertiary prevention studies on hospitalized COVID-19 patients). We identified five studies (one RCT, four NRISs) on primary prevention, with five (two RCTs, three NRISs) on secondary prevention, and 13 (six RCTs, seven NRISs) on tertiary prevention. Pooled analysis showed no significant effect on the risk of COVID-19 infection. No meta-analysis was possible on hospitalization risk due to paucity of data. Vitamin D supplementation was significantly associated with a reduced risk of ICU admission (RR = 0.35, 95% CI: 0.20, 0.62) and mortality (RR = 0.46, 95% CI: 0.30, 0.70). Vitamin D supplementation had no significant impact on the risk of COVID-19 infection, whereas it showed protective effects against mortality and ICU admission in COVID-19 patients.
Children and Adolescents Dietary Habits and Lifestyle Changes during COVID-19 Lockdown in Italy
Authors: Farello Giovanni , D’Andrea Marianna , Quarta Alessia , Grossi Armando , Pompili Davide , Altobelli Emma , Stagi Stefano , Balsano Clara
Published: May 2022

Background: We evaluated the changes in lifestyle during the COVID-19 pandemic lockdown in a sample of children and adolescents in order to assess any increase in risk factors for the onset of cardiovascular diseases in later ages. Methods: We conducted a cross-sectional study involving 965 parents who completed an online survey about dietary habits and lifestyle during the first lockdown in Italy (from 9 March 2020 to 18 May 2020) and compared their findings with the period before the pandemic. The inclusion criteria were parents (or caregivers) with Italian residency and with children aged between 5 and 18 years. Results: We identified 563 adolescents and 402 children. The mean age was 12.28 years (SD 3.754). The pandemic was associated with an increase in the consumption of high-calorie snack foods. The total amount of food in homes during lockdown compared with before the pandemic increased 50%. Relating to the parent-perceived child weight status, more parents reported obesity in their children after lockdown (+0.6% in the 5–11 age group and +0.2% in the 12–18 age group). We reported a reduction of physical activity, an increase of sedentary lifestyle and sleep habits changes. Conclusion: The COVID-19 pandemic was associated with changes in the lifestyles of children and adolescents; this could cause an increase in the incidence of obesity and of cardiovascular and metabolic diseases in adulthood.
Update on Nutrition and Food Allergy
Authors: de Jong Nicolette W. , Wichers Harry J.
Published: May 2022

Food-induced anaphylaxis is an immediate adverse reaction, primarily triggered by the cross-linking of allergen-specific immunoglobulin (Ig) E bound to the high-affinity IgE receptor (FcεRI) on mast cells (MCs) after re-exposure to the same food allergen [...]
Towards Development of a Non-Toxigenic Clostridioides difficile Oral Spore Vaccine against Toxigenic C. difficile
Authors: Hughes Jaime , Aston Carl , Kelly Michelle L. , Griffin Ruth
Published: May 2022

Clostridioides difficile is an opportunistic gut pathogen which causes severe colitis, leading to significant morbidity and mortality due to its toxins, TcdA and TcdB. Two intra-muscular toxoid vaccines entered Phase III trials and strongly induced toxin-neutralising antibodies systemically but failed to provide local protection in the colon from primary C. difficile infection (CDI). Alternatively, by immunising orally, the ileum (main immune inductive site) can be directly targeted to confer protection in the large intestine. The gut commensal, non-toxigenic C. difficile (NTCD) was previously tested in animal models as an oral vaccine for natural delivery of an engineered toxin chimera to the small intestine and successfully induced toxin-neutralising antibodies. We investigated whether NTCD could be further exploited to induce antibodies that block the adherence of C. difficile to epithelial cells to target the first stage of pathogenesis. In NTCD strain T7, the colonisation factor, CD0873, and a domain of TcdB were overexpressed. Following oral immunisation of hamsters with spores of recombinant strain, T7-0873 or T7-TcdB, intestinal and systemic responses were investigated. Vaccination with T7-0873 successfully induced intestinal antibodies that significantly reduced adhesion of toxigenic C. difficile to Caco-2 cells, and these responses were mirrored in sera. Additional engineering of NTCD is now warranted to further develop this vaccine.
Leveraging Affinity Interactions to Prolong Drug Delivery of Protein Therapeutics
Authors: Dogan Alan B. , Dabkowski Katherine E. , von Recum Horst A.
Published: May 2022

While peptide and protein therapeutics have made tremendous advances in clinical treatments over the past few decades, they have been largely hindered by their ability to be effectively delivered to patients. While bolus parenteral injections have become standard clinical practice, they are insufficient to treat diseases that require sustained, local release of therapeutics. Cyclodextrin-based polymers (pCD) have been utilized as a platform to extend the local delivery of small-molecule hydrophobic drugs by leveraging hydrophobic-driven thermodynamic interactions between pCD and payload to extend its release, which has seen success both in vitro and in vivo. Herein, we proposed the novel synthesis of protein–polymer conjugates that are capped with a “high affinity” adamantane. Using bovine serum albumin as a model protein, and anti-interleukin 10 monoclonal antibodies as a functional example, we outline the synthesis of novel protein–polymer conjugates that, when coupled with cyclodextrin delivery platforms, can maintain a sustained release of up to 65 days without largely sacrificing protein structure/function which has significant clinical applications in local antibody-based treatments for immune diseases, cancers, and diabetes.
Different Roles for Multiple Perspectives and Rigorous Testing in Scientific Theories and Models: Towards More Open, Context-Appropriate Verificationism
Authors: Cariani Peter
Published: May 2022

A form of context-appropriate verificationism is proposed that distinguishes between scientific theories as evolving systems of ideas and operationally-specified, testable formal-empirical models. Theories undergo three stages (modes): a formative, exploratory, heuristic phase of theory conception, a developmental phase of theory-pruning and refinement, and a mature, rigorous phase of testing specific, explicit models. The first phase depends on Feyerabendian open possibility, the second on theoretical plausibility and internal coherence, and the third on testability (falsifiability, predictive efficacy). Multiple perspectives produce variety necessary for theory formation, whereas explicit agreement on evaluative criteria is essential for testing. Hertzian observer-mechanics of empirical-deductive scientific models are outlined that use semiotic operations of measurement/evaluation, computation, and physical action/construction. If models can be fully operationalized, then they can be intersubjectively verified (tested) irrespective of metaphysical, theoretical, value-, or culture-based disagreements. Verificationism can be expanded beyond simple predictive efficacy to incorporate testing for pragmatic, functional efficacy in engineering, medicine, and design contexts. Such a more open, pragmatist, operationalist, epistemically-constructivist perspective is suggested in which verification is contingent on the type of assertion (e.g., heuristic, analytic, empirical, pragmatic), its intended purpose, degree and reliability of model-based evidence, and existence of alternate, competing predictive models. Suggestions for epistemological hygiene amidst the world-wide pandemic of misinformation and propaganda are offered.
Secondary Succession Altered the Diversity and Co-Occurrence Networks of the Soil Bacterial Communities in Tropical Lowland Rainforests
Authors: Hu Xuan , Shu Qi , Guo Wen , Shang Zean , Qi Lianghua
Published: May 2022

The characteristics of plant and soil bacterial communities in forest ecosystems have been reported, but our understanding of the relationship between plant communities and soil bacteria in different stages of secondary tropical rainforest succession is still poor. In June 2018, three different natural successional stages of tropical lowland rainforests, early (33 years), early-mid (60 years), and mid successional stage (73 years), in Hainan Island, China, were selected for this study. By conducting field investigation and 16S rRNA gene high-throughput sequencing, the composition and diversity of tree communities, the niche overlap of tree species with legumes among tree species, and the diversity and composition of soil bacterial communities and co-occurrence networks within communities across the successional stages were investigated. The results showed that plant richness and species diversity increased significantly during the secondary succession of tropical lowland rainforests. The order of positive correlations between nitrogen-fixing legumes and other species in plant communities was early-mid > mid > early successional stage. Soil nutrient content and soil bacterial richness were highest in the early-mid stages of succession, followed by mid and early stages of succession. Organic matter (OM), total nitrogen (TN), alkali nitrogen (AN), and available phosphorus (AP) had a stronger positive impact on soil bacterial communities. Co-occurrence network analysis showed that with the advancement of rainforests succession, the negative correlation between soil bacterial species decreased, and the community stability increased. Overall, as a result of tropical lowland rainforest secondary natural succession, the richness and diversity of plant communities increased, which altered the living conditions of nitrogen-fixing legumes and the soil properties, and the network complexity of soil bacterial communities increased with the rising of rainforest soil nutrient content.
Screening for Resistance in Selected Tomato Varieties against the Root-Knot Nematode Meloidogyne incognita in the Philippines Using a Molecular Marker and Biochemical Analysis
Authors: Lizardo Roden Carlo M. , Pinili Marita S. , Diaz Maria Genaleen Q. , Cumagun Christian Joseph R.
Published: May 2022

Tomato is a high-value vegetable crop widely cultivated in the Philippines, and its production is threatened by various stresses including infection by the root-knot nematode M. incognita. In this study, we checked for resistance to M. incognita in selected tomato germplasm collections and commercially available varieties using a bioassay method, the molecular marker Mi23 and biochemical analysis. Among the eight varieties tested, none showed a resistant reaction against M. incognita. Use of the molecular marker Mi23 yielded 430 bp in all the tomato varieties screened. Phylogenetic analysis using the neighbor-joining method revealed the clustering of consensus sequence of the varieties tested with the susceptible variety S. lycopersicum cv. M82-1-8 and a wild relative, S. pimpinellifolium isolate LA2184. The biochemical analysis showed varying responses among the varieties when they were inoculated with M. incognita. Increased levels of total antioxidant activity were observed in Diamante Max F1, Ilocos Red and Tm 2016 11-1, while total phenolic content was found to be elevated in Athena, Avatar TY F1 and Rosanna. Increased levels of ascorbic acid were observed in Athena and Avatar TY F1 even at 45 dpi. Even though these varieties showed elevated levels of the abovementioned biochemical parameters related to a resistance reaction, all of them showed highly susceptible reactions. Hence, this study showed that these tomato varieties have no resistance against M. incognita and that there is a need to identify other sources of resistance against M. incongita and produce resistant tomato cultivars adapted to local conditions.
Regulatory Networks of Flowering Genes in Angelica sinensis during Vernalization
Authors: Luo Mimi , Liu Xiaoxia , Su Hongyan , Li Meiling , Li Mengfei , Wei Jianhe
Published: May 2022

Angelica sinensis is a low-temperature and long-day perennial herb that has been widely used for cardio-cerebrovascular diseases in recent years. In commercial cultivation, up to 40% of flowering decreases the officinal yield of roots and accumulation of bioactive compounds. Although the regulatory mechanism of flowering genes during the photoperiod has been revealed, the networks during vernalization have not been mapped. Here, transcriptomics profiles of A. sinensis with uncompleted (T1), completed (T2) and avoided vernalization (T3) were performed using RNA-seq, and genes expression was validated with qRT-PCR. A total of 61,241 isoforms were annotated on KEGG, KOG, Nr and Swiss-Prot databases; 4212 and 5301 differentially expressed genes (DEGs) were observed; and 151 and 155 genes involved in flowering were dug out at T2 vs. T1 and T3 vs. T1, respectively. According to functional annotation, 104 co-expressed genes were classified into six categories: FLC expression (22; e.g., VILs, FCA and FLK), sucrose metabolism (12; e.g., TPSs, SUS3 and SPSs), hormone response (18; e.g., GID1B, RAP2s and IAAs), circadian clock (2; i.e., ELF3 and COR27), downstream floral integrators and meristem identity (15; e.g., SOC1, AGL65 and SPLs) and cold response (35; e.g., PYLs, ERFs and CORs). The expression levels of candidate genes were almost consistent with FPKM values and changes in sugar and hormone contents. Based on their functions, four pathways that regulate flowering during vernalization were mapped, including the vernalization pathway, the autonomic pathway, the age pathway and the GA (hormone) pathway. This transcriptomic analysis provides new insights into the gene-regulatory networks of flowering in A. sinensis.
Effects of a Biocomplex Formed by Two Scaffold Biomaterials, Hydroxyapatite/Tricalcium Phosphate Ceramic and Fibrin Biopolymer, with Photobiomodulation, on Bone Repair
Authors: Reis Carlos Henrique Bertoni , Buchaim Rogerio Leone , Pomini Karina Torres , Hamzé Abdul Latif , Zattiti Isabella Vasconcelos , Duarte Marco Antonio Hungaro , Alcalde Murilo Priori , Barraviera Benedito , Ferreira Júnior Rui Seabra , Pontes Fenelon Martinho Lima , Grandini Carlos Roberto , Ortiz Adriana de Cássia , Fideles Simone Ortiz Moura , Eugênio Renata Maria de Camargo , Rosa Junior Geraldo Marco , Teixeira Daniel de Bortoli , Pereira Eliana de Souza Bastos Mazuqueli , Pilon João Paulo Galletti , Miglino Maria Angelica , Buchaim Daniela Vieira
Published: May 2022

There are several treatment methods available for bone repair, although the effectiveness becomes limited in cases of large defects. The objective of this pre-clinical protocol was to evaluate the grafting of hydroxyapatite/tricalcium phosphate (BCP) ceramic biomaterial (B; QualyBone BCP®, QualyLive, Amadora, Portugal) together with the heterologous fibrin biopolymer (FB; CEVAP/UNESP Botucatu, Brazil) and with photobiomodulation (PBM; Laserpulse®, Ibramed, Amparo, Brazil) in the repair process of bone defects. Fifty-six rats were randomly divided into four groups of seven animals each: the biomaterial group (G1/B), the biomaterial plus FB group (G2/BFB); the biomaterial plus PBM group (G3/B + PBM), and the biomaterial plus FB plus PBM group (G4/BFB + PBM). After anesthesia, a critical defect was performed in the center of the rats’ parietal bones, then filled and treated according to their respective groups. The rats were euthanized at 14 and 42 postoperative days. Histomorphologically, at 42 days, the G4/BFB + PBM group showed a more advanced maturation transition, with more organized and mature bone areas forming concentric lamellae. A birefringence analysis of collagen fibers also showed a more advanced degree of maturation for the G4/BFB + PBM group. In the comparison between the groups, in the two experimental periods (14 and 42 days), in relation to the percentage of formation of new bone tissue, a significant difference was found between all groups (G1/B (5.42 ± 1.12; 21.49 ± 4.74), G2/BFB (5.00 ± 0.94; 21.77 ± 2.83), G3/B + PBM (12.65 ± 1.78; 29.29 ± 2.93), and G4/BFB + PBM (12.65 ± 2.32; 31.38 ± 2.89)). It was concluded that the use of PBM with low-level laser therapy (LLLT) positively interfered in the repair process of bone defects previously filled with the biocomplex formed by the heterologous fibrin biopolymer associated with the synthetic ceramic of hydroxyapatite and tricalcium phosphate.
Preparation of High Mechanical Strength Chitosan Nanofiber/NanoSiO2/PVA Composite Scaffolds for Bone Tissue Engineering Using Sol–Gel Method
Authors: Ma Wei , Zhang Sihan , Xie Chong , Wan Xing , Li Xiaofeng , Chen Kebing , Zhao Guanglei
Published: May 2022

The majority of chitosan-based bone tissue engineering (BTE) scaffolds have the problem of poor mechanical properties. However, modifying chitosan with conventional silane coupling agents to improve the mechanical properties of scaffolds will introduce additional complications, including cytotoxicity and poor biocompatibility. In this study, two types of organic–inorganic composite scaffolds (F-A-T0/T3/T5 and F-B-T5-P0/P0.5/P1.5/P2.5) were prepared using chitosan nanofibers (CSNF) prepared by the beating-homogenization method, combined with the sol–gel method, and further introduced polyvinyl alcohol (PVA). The F-A-T3 and F-B-T5-P1.5 exhibited interconnected pore and surface nanofibers structures, high porosity (>70%), outstanding swelling properties, and a controllable degradation rate. The Young’s modulus of TEOS: 5.0% (w/w), PVA: 1.5% (w/w) chitosan fiber scaffold is 8.53 ± 0.43 MPa in dry conditions, and 237.78 ± 8.86 kPa in wet conditions, which is four times that of F-A-T5 and twice that of F-B-T5-P0. Additionally, cell (MC3T3-E1) experiments confirmed that the two composite scaffolds had great cytocompatibility and were predicted to be used in the future in the field of BTE scaffolds.
Heat Analysis of Thermal Conductive Polymer Composites: Reference Temperature History in Pure Polymer Matrices
Authors: Guesmi Fethi , Elfarhani Makram , Mkaddem Ali , Ghazali Sami , Bin Mahfouz Abdullah S. , Jarraya Abdessalem
Published: May 2022

This attempt aims at assessing heat generation in thermal conductive polymer (TCP) composites widely used in aerospace sectors. Temperature histories were investigated in both nonreinforced and glass-fiber-reinforced TCPs during abrasive milling. Glass/epoxy and glass/polyester composites with 30% unidirectional glass fiber content were prepared according to appropriate curing cycles. Type K thermocouples connected to a data acquisition system ensured the recording of temperature history along the trim plan during milling. Unexpectedly, when milling TCP composites parallel to fibers, peak temperature was found to be slightly lower than that recorded in nonreinforced polymers. The lateral surface of fibers acts to favor sliding friction, which limits heat generation at interfaces, while relatively low specific heat capacity and thermal conductivity of glass fiber disadvantage heat transfer. However, when milling perpendicular to fibers, the contact area between the tool and the transverse failure area of fibers increases drastically, hence involving severe friction at interfaces. This yields peak temperatures sensitively higher than those obtained in nonreinforced polymers. SEM inspections highlighted the failure modes dominating the material removal process in both nonreinforced and glass-fiber-reinforced polymers. The microcracks and debris observed at the trim plan explain, in part, the heat generation detected on temperature rate plots. Thus, heat conduction between phases governs sensitive surface finish integrity and tool lifetime and, hence, has great economic impact on the manufacturing steps.
Design and Simulation of Small-Scale Waste Separation and Sorting Equipment
Authors: Xu Ziheng , Zhang Jiajia , He Yuhui
Published: May 2022

Environmental pollution is currently a major concern globally owing to increase in the world population and advances in industrialization. An automatic waste separation and sorting equipment for small-scale waste sorting systems was constructed in this paper. A two-DoF (two-degree-of-freedom) parallel sorting mechanism as well as a belt waste separation and feeding mechanism were designed, and 3D models of the mechanism were established. Finite element analysis (FEA) was conducted for the sorting mechanism, and kinematic and dynamic analysis and numerical simulation were performed for the waste and sorting mechanism. The simulation results demonstrated that the spherical waste did not roll out of the platform after leaving the slideway. The waste was stabilized at the center of the platform within a short duration with movement of the collecting mechanism of the platform. The system was optimized to reduce waste separation and sorting time. Stability of the waste motion in the equipment as well as efficiency of the system were significantly improved after optimization. The results showed that the designed equipment can complete separation and sorting of waste materials at lower output power.
Dopamine Incorporated Forward Osmosis Membranes with High Structural Stability and Chlorine Resistance
Authors: Wang Yi , Fang Zhendong , Xie Chaoxin , Zhao Shuaifei , Ng Derrick , Xie Zongli
Published: May 2022

The degradation and detachment of the polyamide (PA) layer for the conventional thin-film composite (TFC) membranes due to chemical disinfectants cleaning with chlorine and material difference of PA layer and substrate are two major bottlenecks of forward osmosis (FO) technology. In this study, a new type of FO membranes was first prepared by controlling dopamine (DA) as the sole amine in the aqueous phase and the reaction with trimesoyl chloride (TMC) as the acyl chloride during interfacial polymerization (IP) process. The influence of membrane synthesis parameters such as monomer concentration, pH of the aqueous phase, IP reaction time and IP temperature were systematically investigated. The optimized membrane showed both improved structure stability and chlorine resistance, more so than the conventional TFC membrane. In general, novel DA/TMC TFC membranes could be an effective strategy to synthesize high-performance FO membranes with excellent structural stability and chlorine resistance.
Could Prosthesis Use Provide a Competitive Advantage in Darts?
Authors: DeVillez Jack , Sabato Jenna , Fiedler Goeran
Published: May 2022

Competitive darts has become increasingly popular over the past few decades, and efforts have been made to have the game recognized as an Olympic sport in the future. The raised profile of the sport and the associated rewards bring up new challenges for the integrity of the game, as athletes are incentivized to exploit rule ambiguities in order to gain competitive advantages. In this research, it was hypothesized that uneven leg lengths and weights, which are comparatively easily realizable in prosthetic limbs, allow players to lean closer to the target and thus improve their throwing accuracy. This hypothesis was tested in a sample of 13 able-bodied subjects who participated in the study, with three sets of throwing trials; one to establish the baseline and two with a longer and heavier trailing leg, respectively. The findings suggest that these modifications are indeed beneficial, resulting in significantly shorter throwing distances and average accuracy improvements of up to 11%. The debate about the potential competitive advantages of prosthesis-wearing Paralympic athletes over their able-bodied peers previously focused on short track running events, where rules have been established that govern the allowable geometry and configuration of sprint prostheses. It appears that comparable regulations should be considered for darts competitions, in order to ensure fair conditions for all participants.
A Systematic Literature Review of Volatility and Risk Management on Cryptocurrency Investment: A Methodological Point of View
Authors: Almeida José , Gonçalves Tiago Cruz
Published: May 2022

In this study, we explore the research published from 2009 to 2021 and summarize what extant literature has contributed in the last decade to the analysis of volatility and risk management in cryptocurrency investment. Our samples include papers published in journals ranked across different fields in ABS ranked journals. We conduct a bibliometric analysis using VOSviewer software and perform a literature review. Our findings are presented in terms of methodologies used to model cryptocurrencies’ volatility and also according to their main findings pertaining to volatility and risk management in those assets and using them in portfolio management. Our research indicates that the models that consider the Markov-switching regime seem to be more consensual among the authors, and that the best machine learning technique performances are hybrid models that consider the support vector machines (SVM). We also argue that the predictability of volatility, risk reduction, and level of speculation in the cryptocurrency market are improved by the leverage effects and the volatility persistence.
UAV Remote Sensing for Biodiversity Monitoring: Are Forest Canopy Gaps Good Covariates?
Authors: Bagaram Martin B. , Giuliarelli Diego , Chirici Gherardo , Giannetti Francesca , Barbati Anna
Published: May 2022

Forest canopy gaps are important to ecosystem dynamics. Depending on tree species, small canopy openings may be associated with intra-crown porosity and with space among crowns. Yet, literature on the relationships between very fine-scaled patterns of canopy openings and biodiversity features is limited. This research explores the possibility of: (1) mapping forest canopy gaps from a very high spatial resolution orthomosaic (10 cm), processed from a versatile unmanned aerial vehicle (UAV) imaging platform, and (2) deriving patch metrics that can be tested as covariates of variables of interest for forest biodiversity monitoring. The orthomosaic was imaged from a test area of 240 ha of temperate deciduous forest types in Central Italy, containing 50 forest inventory plots each of 529 m2 in size. Correlation and linear regression techniques were used to explore relationships between patch metrics and understory (density, development, and species diversity) or forest habitat biodiversity variables (density of micro-habitat bearing trees, vertical species profile, and tree species diversity). The results revealed that small openings in the canopy cover (75% smaller than 7 m2) can be faithfully extracted from UAV red, green, and blue bands (RGB) imagery, using the red band and contrast split segmentation. The strongest correlations were observed in the mixed forests (beech and turkey oak) followed by intermediate correlations in turkey oak forests, followed by the weakest correlations in beech forests. Moderate to strong linear relationships were found between gap metrics and understory variables in mixed forest types, with adjusted R2 from linear regression ranging from 0.52 to 0.87. Equally strong correlations in the same forest types were observed for forest habitat biodiversity variables (with adjusted R2 ranging from 0.52 to 0.79), with highest values found for density of trees with microhabitats and vertical species profile. In conclusion, this research highlights that UAV remote sensing can potentially provide covariate surfaces of variables of interest for forest biodiversity monitoring, conventionally collected in forest inventory plots. By integrating the two sources of data, these variables can be mapped over small forest areas with satisfactory levels of accuracy, at a much higher spatial resolution than would be possible by field-based forest inventory solely.
Automated Detection of Koalas with Deep Learning Ensembles
Authors: Winsen Megan , Denman Simon , Corcoran Evangeline , Hamilton Grant
Published: May 2022

Effective management of threatened and invasive species requires regular and reliable population estimates. Drones are increasingly utilised by ecologists for this purpose as they are relatively inexpensive. They enable larger areas to be surveyed than traditional methods for many species, particularly cryptic species such as koalas, with less disturbance. The development of robust and accurate methods for species detection is required to effectively use the large volumes of data generated by this survey method. The enhanced predictive and computational power of deep learning ensembles represents a considerable opportunity to the ecological community. In this study, we investigate the potential of deep learning ensembles built from multiple convolutional neural networks (CNNs) to detect koalas from low-altitude, drone-derived thermal data. The approach uses ensembles of detectors built from combinations of YOLOv5 and models from Detectron2. The ensembles achieved a strong balance between probability of detection and precision when tested on ground-truth data from radio-collared koalas. Our results also showed that greater diversity in ensemble composition can enhance overall performance. We found the main impediment to higher precision was false positives but expect these will continue to reduce as tools for geolocating detections are improved. The ability to construct ensembles of different sizes will allow for improved alignment between the algorithms used and the characteristics of different ecological problems. Ensembles are efficient and accurate and can be scaled to suit different settings, platforms and hardware availability, making them capable of adaption for novel applications.
Source Apportionment of Heavy Metal Contamination in Urban-Agricultural-Aquacultural Soils near the Bohai Bay Coast, Using Land-Use Classification and Google Satellite Tracing
Authors: Zeng Ling , Jiang Shan , Jing Linhai , Xue Yuan
Published: May 2022

Heavy metal concentrations of Cd, As, Pb, Cu, Cr, and Hg were investigated for 86 soil samples in Jinzhou near the Bohai Sea in China, in order to identify what anthropological activities influenced their distribution levels. Ordinary cokriging (OCK) was utilized to map six heavy-metal distributions by incorporating their main environmental influencers. The resultant p values for the six OCK mapping models of 0–2.78% indicated good statistical significance of the models, and the relative mean absolute errors of 4.82–12.53% and relative root mean square errors of 6.23–18.21% indicated allowable predication precision for their concentrations. The contamination distributions by OCK mapping were then graded based on the standards of the China National Environmental Monitoring Center and the Chinese Environmental Protection Administration, which showed that Cu and As contaminations in parts of this area were over the natural level but not polluted, Cr contamination was omnipresent over the natural level in this area and even reached the polluted level in parts of this area. The graded contamination maps that were overlapped with land-use maps and Google satellite maps, as well as the verifications reported in literatures, enabled correlations of the different contamination levels of As, Cu, and Cr with human activities. Resultantly, it indicated that As and Cu contamination over the natural level may be related to agricultural planting and aquacultural activities along the coast of Bohai Bay, with the contaminants transported via watercourses; Cr contamination over the natural level may have been due to vehicle emissions; and, Cr pollution may have been from steel manufacturing and geochemical factories
A Hybrid Polarimetric Target Decomposition Algorithm with Adaptive Volume Scattering Model
Authors: Li Xiujuan , Liu Yongxin , Huang Pingping , Liu Xiaolong , Tan Weixian , Fu Wenxue , Li Chunming
Published: May 2022

Previous studies have shown that scattering mechanism ambiguity and negative power issues still exist in model-based polarization target decomposition algorithms, even though deorientation processing is implemented. One possible reason for this is that the dynamic range of the model itself is limited and cannot fully satisfy the mixed scenario. To address these problems, we propose a hybrid polarimetric target decomposition algorithm (GRH) with a generalized volume scattering model (GVSM) and a random particle cloud volume scattering model (RPCM). The adaptive volume scattering model used in GRH incorporates GVSM and RPCM to model the volume scattering model of the regions dominated by double-bounce scattering and the surface scattering, respectively, to expand the dynamic range of the model. In addition, GRH selects the volume scattering component between GVSM and RPCM adaptively according to the target dominant scattering mechanism of fully polarimetric synthetic aperture radar (PolSAR) data. The effectiveness of the proposed method was demonstrated using AirSAR dataset over San Francisco. Comparison studies were carried out to test the performance of GRH over several target decomposition algorithms. Experimental results show that the GRH outperforms the algorithms we tested in this study in decomposition accuracy and reduces the number of pixels with negative powers, demonstrating that the GRH can significantly avoid mechanism ambiguity and negative power issues.
MBNet: Multi-Branch Network for Extraction of Rural Homesteads Based on Aerial Images
Authors: Wei Ren , Fan Beilei , Wang Yuting , Zhou Ailian , Zhao Zijuan
Published: May 2022

Deep convolution neural network (DCNN) technology has achieved great success in extracting buildings from aerial images. However, the current mainstream algorithms are not satisfactory in feature extraction and classification of homesteads, especially in complex rural scenarios. This study proposes a deep convolutional neural network for rural homestead extraction consisting of a detail branch, a semantic branch, and a boundary branch, namely Multi-Branch Network (MBNet). Meanwhile, a multi-task joint loss function is designed to constrain the consistency of bounds and masks with their respective labels. Specifically, MBNet guarantees the details of prediction through serial 4× down-sampled high-resolution feature maps and adds a mixed-scale spatial attention module at the tail of the semantic branch to obtain multi-scale affinity features. At the same time, the low-resolution semantic feature maps and interaction between high-resolution detail feature maps are maintained. Finally, the result of semantic segmentation is refined by the point-to-point module (PTPM) through the generated boundary. Experiments on UAV high-resolution imagery in rural areas show that our method achieves better performance than other state-of-the-art models, which helps to refine the extraction of rural homesteads. This study demonstrates that MBNet is a potential candidate for building an automatic rural homestead management system.
Prototyping Crop Traits Retrieval Models for CHIME: Dimensionality Reduction Strategies Applied to PRISMA Data
Authors: Pascual-Venteo Ana B. , Portalés Enrique , Berger Katja , Tagliabue Giulia , Garcia Jose L. , Pérez-Suay Adrián , Rivera-Caicedo Juan Pablo , Verrelst Jochem
Published: May 2022

In preparation for new-generation imaging spectrometer missions and the accompanying unprecedented inflow of hyperspectral data, optimized models are needed to generate vegetation traits routinely. Hybrid models, combining radiative transfer models with machine learning algorithms, are preferred, however, dealing with spectral collinearity imposes an additional challenge. In this study, we analyzed two spectral dimensionality reduction methods: principal component analysis (PCA) and band ranking (BR), embedded in a hybrid workflow for the retrieval of specific leaf area (SLA), leaf area index (LAI), canopy water content (CWC), canopy chlorophyll content (CCC), the fraction of absorbed photosynthetic active radiation (FAPAR), and fractional vegetation cover (FVC). The SCOPE model was used to simulate training data sets, which were optimized with active learning. Gaussian process regression (GPR) algorithms were trained over the simulations to obtain trait-specific models. The inclusion of PCA and BR with 20 features led to the so-called GPR-20PCA and GPR-20BR models. The 20PCA models encompassed over 99.95% cumulative variance of the full spectral data, while the GPR-20BR models were based on the 20 most sensitive bands. Validation against in situ data obtained moderate to optimal results with normalized root mean squared error (NRMSE) from 13.9% (CWC) to 22.3% (CCC) for GPR-20PCA models, and NRMSE from 19.6% (CWC) to 29.1% (SLA) for GPR-20BR models. Overall, the GPR-20PCA slightly outperformed the GPR-20BR models for all six variables. To demonstrate mapping capabilities, both models were tested on a PRecursore IperSpettrale della Missione Applicativa (PRISMA) scene, spectrally resampled to Copernicus Hyperspectral Imaging Mission for the Environment (CHIME), over an agricultural test site (Jolanda di Savoia, Italy). The two strategies obtained plausible spatial patterns, and consistency between the two models was highest for FVC and LAI (R2=0.91, R2=0.86) and lowest for SLA mapping (R2=0.53). From these findings, we recommend implementing GPR-20PCA models as the most efficient strategy for the retrieval of multiple crop traits from hyperspectral data streams. Hence, this workflow will support and facilitate the preparations of traits retrieval models from the next-generation operational CHIME.
An ASIP for Neural Network Inference on Embedded Devices with 99% PE Utilization and 100% Memory Hidden under Low Silicon Cost
Authors: Gao Muxuan , Chen He , Liu Dake
Published: May 2022

The computation efficiency and flexibility of the accelerator hinder deep neural network (DNN) implementation in embedded applications. Although there are many publications on deep neural network (DNN) processors, there is still much room for deep optimization to further improve results. Multiple dimensions must be simultaneously considered when designing a DNN processor to reach the performance limit of the architecture, including architecture decision, flexibility, energy efficiency, and silicon cost minimization. Flexibility is defined as the ability to support as many multiple networks as possible and to easily adjust the scale. For energy efficiency, there are huge opportunities for power efficiency optimization, which involves access minimization and memory latency minimization based on on-chip memory minimization. Therefore, this work focused on low-power and low-latency data access with minimized silicon cost. This research was implemented based on an ASIP (application specific instruction set processor) in which an ISA was based on the caffe2 inference operator and the hardware design was based on a single instruction multiple data (SIMD) architecture. The scalability and system performance of our SoC extension scheme were demonstrated. The VLIW was used to execute multiple instructions in parallel. All costs for data access time were thus eliminated for the convolution layer. Finally, the processor was synthesized based on TSMC 65 nm technology with a 200 MHz clock, and the Soc extension scheme was analyzed in an experimental model. Our design was tested on several typical neural networks, achieving 196 GOPS at 200 MHz and 241 GOPS/W on the VGG16Net and AlexNet.
Monitoring Gases Content in Modern Agriculture: A Density Functional Theory Study of the Adsorption Behavior and Sensing Properties of CO2 on MoS2 Doped GeSe Monolayer
Authors: Gao Xin , Li Yunwu
Published: May 2022

The reasonable allocation and control of CO2 concentration in a greenhouse are very important for the optimal growth of crops. In this study, based on density functional theory (DFT), an MoS2–GeSe monolayer was proposed to unravel the issues of the lower selectivity, poorer sensitivity and non-recyclability of traditional nanomaterial gas sensors. The incorporation of MoS2 units greatly enhanced the sensitivity of the pure GeSe monolayer to CO2 and the high binding energy also demonstrated the thermal stability of the doped structures. The ideal adsorption energy, charge transfer and recovery time ensured that the MoS2–GeSe monolayer had a good adsorption and desorption ability. This paper aimed to solve the matter of recycling sensors within agriculture. This research could provide the theoretical basis for the establishment of a potentially new generation of gas sensors for the monitoring of crop growth.
Design of Proactive Interaction for In-Vehicle Robots Based on Transparency
Authors: Wang Jianmin , Yue Tianyang , Liu Yujia , Wang Yuxi , Wang Chengji , Yan Fei , You Fang
Published: May 2022

Based on the transparency theory, this study investigates the appropriate amount of transparency information expressed by the in-vehicle robot under two channels of voice and visual in a proactive interaction scenario. The experiments are to test and evaluate different transparency levels and combinations of information in different channels of the in-vehicle robot, based on a driving simulator to collect subjective and objective data, which focuses on users’ safety, usability, trust, and emotion dimensions under driving conditions. The results show that appropriate transparency expression is able to improve drivers’ driving control and subjective evaluation and that drivers need a different amount of transparency information in different types of tasks.
Recent Advances in the Use of Surface-Enhanced Raman Scattering for Illicit Drug Detection
Authors: Azimi Shamim , Docoslis Aristides
Published: May 2022

The rapid increase in illicit drug use and its adverse health effects and socio-economic consequences have reached alarming proportions in recent years. Surface-enhanced Raman scattering (SERS) has emerged as a highly sensitive analytical tool for the detection of low dosages of drugs in liquid and solid samples. In the present article, we review the state-of-the-art use of SERS for chemical analysis of illicit drugs in aqueous and complex biological samples, including saliva, urine, and blood. We also include a review of the types of SERS substrates used for this purpose, pointing out recent advancements in substrate fabrication towards quantitative and qualitative detection of illicit drugs. Finally, we conclude by providing our perspective on the field of SERS-based drug detection, including presently faced challenges. Overall, our review provides evidence of the strong potential of SERS to establish itself as both a laboratory and in situ analytical method for fast and sensitive drug detection and identification.
A Novel Fault Diagnosis Method of Rolling Bearing Based on Integrated Vision Transformer Model
Authors: Tang Xinyu , Xu Zengbing , Wang Zhigang
Published: May 2022

In order to improve the diagnosis accuracy and generalization of bearing faults, an integrated vision transformer (ViT) model based on wavelet transform and the soft voting method is proposed in this paper. Firstly, the discrete wavelet transform (DWT) was utilized to decompose the vibration signal into the subsignals in the different frequency bands, and then these different subsignals were transformed into a time–frequency representation (TFR) map by the continuous wavelet transform (CWT) method. Secondly, the TFR maps were input with respective to the multiple individual ViT models for preliminary diagnosis analysis. Finally, the final diagnosis decision was obtained by using the soft voting method to fuse all the preliminary diagnosis results. Through multifaceted diagnosis tests of rolling bearings on different datasets, the diagnosis results demonstrate that the proposed integrated ViT model based on the soft voting method can diagnose the different fault categories and fault severities of bearings accurately, and has a higher diagnostic accuracy and generalization ability by comparison analysis with integrated CNN and individual ViT.
An Examination of Relative Age and Athlete Dropout in Female Developmental Soccer
Authors: Smith Kristy L. , Weir Patricia L.
Published: May 2022

Sport dropout rates among children and youth are a concern for researchers and policy makers. The impact of relative age effects (RAEs) on dropout trends has not been adequately examined in female samples. The purpose of this study was to longitudinally examine dropout in a female soccer cohort in Ontario, Canada. Registration entries for a one-year cohort were examined across a seven-year period (n = 9908; age 10–16 years). A chi-square analysis established the presence of RAEs in the initial year of registration. Survival analyses assessed the impact of relative age, competition level, and community size on athlete dropout. A median survival rate of four years was observed for players born in the first quartile, while all remaining quartiles had a median survival of three years. Community size did not predict dropout in this analysis; however, competition level was a significant predictor, with competitive players being more likely to remain engaged vs. recreational players (55.9% vs. 20.7%). The observed trends are likely to have a significant impact from both a healthy development and systems perspective (e.g., economic/market loss). Intervention is needed to mitigate current dropout trends in female athletes. Practical applications are discussed.