Showing papers by "Southwest University published in 2021"

Image-Based 3D Object Reconstruction: State-of-the-Art and Trends in the Deep Learning Era

Abstract: 3D reconstruction is a longstanding ill-posed problem, which has been explored for decades by the computer vision, computer graphics, and machine learning communities. Since 2015, image-based 3D reconstruction using convolutional neural networks (CNN) has attracted increasing interest and demonstrated an impressive performance. Given this new era of rapid evolution, this article provides a comprehensive survey of the recent developments in this field. We focus on the works which use deep learning techniques to estimate the 3D shape of generic objects either from a single or multiple RGB images. We organize the literature based on the shape representations, the network architectures, and the training mechanisms they use. While this survey is intended for methods which reconstruct generic objects, we also review some of the recent works which focus on specific object classes such as human body shapes and faces. We provide an analysis and comparison of the performance of some key papers, summarize some of the open problems in this field, and discuss promising directions for future research.

Technologies and perspectives for achieving carbon neutrality

Abstract: Global development has been heavily reliant on the overexploitation of natural resources since the Industrial Revolution. With the extensive use of fossil fuels, deforestation, and other forms of land-use change, anthropogenic activities have contributed to the ever-increasing concentrations of greenhouse gases (GHGs) in the atmosphere, causing global climate change. In response to the worsening global climate change, achieving carbon neutrality by 2050 is the most pressing task on the planet. To this end, it is of utmost importance and a significant challenge to reform the current production systems to reduce GHG emissions and promote the capture of CO2 from the atmosphere. Herein, we review innovative technologies that offer solutions achieving carbon (C) neutrality and sustainable development, including those for renewable energy production, food system transformation, waste valorization, C sink conservation, and C-negative manufacturing. The wealth of knowledge disseminated in this review could inspire the global community and drive the further development of innovative technologies to mitigate climate change and sustainably support human activities.

2020 taxonomic update for phylum Negarnaviricota (Riboviria: Orthornavirae), including the large orders Bunyavirales and Mononegavirales

Abstract: In March 2020, following the annual International Committee on Taxonomy of Viruses (ICTV) ratification vote on newly proposed taxa, the phylum Negarnaviricota was amended and emended. At the genus rank, 20 new genera were added, two were deleted, one was moved, and three were renamed. At the species rank, 160 species were added, four were deleted, ten were moved and renamed, and 30 species were renamed. This article presents the updated taxonomy of Negarnaviricota as now accepted by the ICTV.

A Distance Measure for Intuitionistic Fuzzy Sets and Its Application to Pattern Classification Problems

Abstract: As a generation of fuzzy sets, intuitionistic fuzzy sets (IFSs) have a more powerful ability to represent and address the uncertainty of information. Therefore, IFSs have been used in many areas. However, the distance measure between the IFSs indicating the difference or discrepancy grade is still an open question that has attracted considerable attention over the past few decades. Although various measurement methods have been developed, some problems still exist regarding the unsatisfactory axioms of distance measure or that lack discernment and cause counterintuitive cases. To address the above issues, in this article, we propose a new distance measure between IFSs based on the Jensen–Shannon divergence. This new IFS distance measure can not only satisfy the axiomatic definition of distance measure but also has nonlinear characteristics. As a result, it can better discriminate the discrepancies between IFSs, and it generates more reasonable results than do other existing measure methods; these advantages are illustrated by several numerical examples. Based on these qualities, an algorithm for pattern classification is designed that provides a promising solution for addressing inference problems.

"I'm not against online teaching, but what about us?": ICT in Ghana post Covid-19.

Abstract: Globally, Information and Communication Technology (ICT) is regarded as a dependable vehicle for facilitating educational reform and development, a platform for communication, and as a means to achieve the Sustainable Development Goal Four (SDG 4). Since the enactment of the No Child Left Behind Act (NCLB) and declaration of the SDG 4, many countries have opted to embrace the lifelong education for all by integrating ICT in teaching and learning at all school levels. The Ghanaian Government's initiative to ensure "education anytime anywhere for everyone" by revolutionizing teaching and learning through ICT has faced a lot of challenges and criticisms. The main mission of the Ghana ICT for Accelerated Development (ICT4AD) in 2003 was to transform Ghana into an information and technology-driven high-income economy through education, but this goal is yet to be realized. In the wake of the COVID-19 which has forced many countries and educational sectors to adopt online learning, there is a need to discuss the effectiveness of online learning and barriers to online learning in the developing contexts, and how to successfully integrate ICT in schools for online learning, especially rural schools where students' educational careers are in jeopardy because they benefit less from online learning. The paper identifies critical factors that affect online learning, recommends post COVID-19 strategies to promote e-learning for policymakers in education and the government, and concludes with a conceptual model for emergency transition to e-learning.

Plant flavones enrich rhizosphere Oxalobacteraceae to improve maize performance under nitrogen deprivation

Abstract: Beneficial interactions between plant roots and rhizosphere microorganisms are pivotal for plant fitness. Nevertheless, the molecular mechanisms controlling the feedback between root architecture and microbial community structure remain elusive in maize. Here, we demonstrate that transcriptomic gradients along the longitudinal root axis associate with specific shifts in rhizosphere microbial diversity. Moreover, we have established that root-derived flavones predominantly promote the enrichment of bacteria of the taxa Oxalobacteraceae in the rhizosphere, which in turn promote maize growth and nitrogen acquisition. Genetic experiments demonstrate that LRT1-mediated lateral root development coordinates the interactions of the root system with flavone-dependent Oxalobacteraceae under nitrogen deprivation. In summary, these experiments reveal the genetic basis of the reciprocal interactions between root architecture and the composition and diversity of specific microbial taxa in the rhizosphere resulting in improved plant performance. These findings may open new avenues towards the breeding of high-yielding and nutrient-efficient crops by exploiting their interaction with beneficial soil microorganisms.

Power generation for wearable systems

Abstract: Wearable devices are drawing increasing attention in both academia and industry in that they can offer unprecedented information related to human health in real-time and human–machine interactions, which is expected to enable a paradigm shift in the digital world. For this shift to occur, green and sustainable energy technology for powering flexible wearable devices is a roadblock. This paper is dedicated to reviewing cutting-edge wearable power generation methodologies, for which we discuss their pros and cons, underlying physics, and general design/evaluation criteria. Sensor types, materials, processing technology, power consumption, and methods of testing the stretchability and flexibility of wearable devices are also summarized. Based on application scenarios in healthcare, industrial inspection, structural monitoring, armed forces and consumer electronics, an integrated system architecture of wearable, flexible systems is presented. Finally, future perspectives of wearable technologies are outlined by covering the aspects of all-in-one printable wearable electronics, fiber and textile electronics, self-powered self-awareness wearable systems, hybrid-integrated Systems on a Chip (SoC) for flexible electronics, and Internet of Things (IoT)-enabled self-contained systems towards full life cycle monitoring.

Depression and anxiety symptoms associated with internet gaming disorder before and during the COVID-19 pandemic: A longitudinal study.

Abstract: Background: The coronavirus disease-2019 (COVID-19) pandemic has profoundly impacted aspects of human life globally. Playing videogames has been encouraged by several organizations to help individuals cope with the COVID-19 pandemic and associated restrictive measures. This longitudinal study was the first to examine gaming in the context of the pandemic and its association with depressive and anxiety symptoms. Methods: The sample comprised 1,778 children and adolescents (50.7% male) who were part of the Project of School Mental Health in Southwest China. Data were collected at two-time intervals: before the COVID-19 pandemic (October to November 2019 – [T1]) and during the COVID-19 pandemic (April to May 2020 – [T2]). Data were collected on perceived COVID-19 impacts, videogame use, Internet Gaming Disorder (IGD), and depressive and anxiety symptoms. Cross-lagged panel models were computed to examine longitudinal relationships. Results: The results indicated that both videogame use and IGD increased significantly for adolescents at T2. The cross-lagged panel model results suggested that depressive and anxiety symptoms at T1 positively predicted IGD and videogame use at T2 (especially for boys), but not inversely. Perceived COVID-19 impacts mediated the relationship between depressive and anxiety symptoms at T1 and IGD at T2. Conclusion: Children and adolescents both increased videogame use at T2, but only adolescents significantly increased IGD severity at T2. The findings supported the compensatory hypothesis, and are consistent with the Interaction of Person-Affect-Cognition-Execution model as individual responses to COVID-19 may function as a mediator between personal predisposing variables and IGD.

Carbon loss from forest degradation exceeds that from deforestation in the Brazilian Amazon

Abstract: Spatial–temporal dynamics of aboveground biomass (AGB) and forest area affect the carbon cycle, climate and biodiversity in the Brazilian Amazon. Here we investigate interannual changes in AGB and forest area by analysing satellite-based annual AGB and forest area datasets. We found that the gross forest area loss was larger in 2019 than in 2015, possibly due to recent loosening of forest protection policies. However, the net AGB loss was three times smaller in 2019 than in 2015. During 2010–2019, the Brazilian Amazon had a cumulative gross loss of 4.45 Pg C against a gross gain of 3.78 Pg C, resulting in a net AGB loss of 0.67 Pg C. Forest degradation (73%) contributed three times more to the gross AGB loss than deforestation (27%), given that the areal extent of degradation exceeds that of deforestation. This indicates that forest degradation has become the largest process driving carbon loss and should become a higher policy priority. Carbon loss from forests occurs through deforestation or the degradation of existing forest. The loss of forest area in the Brazilian Amazon was higher in 2019 than following drought and an El Nino event in 2015, yet degradation drove three times more biomass loss than deforestation from 2010 to 2019.

Multifunctional organic ammonium salt-modified SnO2 nanoparticles toward efficient and stable planar perovskite solar cells

Abstract: Bulk and interfacial nonradiative recombination hinder the further enhancement of the power conversion efficiency (PCE) and stability of SnO2-based planar perovskite solar cells (PSCs) To date, it is still a huge challenge to minimize the bulk and interfacial nonradiative recombination losses, and thus maximize the potentials of PCE and stability Herein, a novel and effective multifunctional modification strategy through incorporating Girard's Reagent T (GRT) molecules with multiple functional groups to modify SnO2 nanoparticles (NPs), which significantly reduces the bulk and interfacial nonradiative recombination losses through the simultaneous achievement of suppressing nanoparticle agglomeration, improving the electronic property of SnO2 films, facilitating the vertical growth and enlarging the grain size of perovskite crystals, and passivating interfacial defects is reported As a result, the device based on GRT modification delivers a much higher PCE of 2163%, along with significantly suppressed hysteresis, as compared to the control device (1977%) The device stability is ameliorated after GRT modification The unencapsulated device with GRT maintains 995% of its initial PCE after aging at 60 °C for 720 h and 585% after illumination for 672 h under one sun, respectively The present work provides guidance for the design of multifunctional modification molecules toward efficient and stable PSCs

Isolated Single-Atom Ni-N5 Catalytic Site in Hollow Porous Carbon Capsules for Efficient Lithium-Sulfur Batteries.

Abstract: Lithium-sulfur (Li-S) batteries suffer from multiple complex and often interwoven issues, such as the low electronic conductivity of sulfur and Li2S/Li2S2, shuttle effect, and sluggish electrochemical kinetics of lithium polysulfides (LiPSs). Guided by theoretical calculations, a multifunctional catalyst of isolated single-atom nickel in an optimal Ni-N5 active moiety incorporated in hollow nitrogen-doped porous carbon (Ni-N5/HNPC) is constructed and acts as an ideal host for a sulfur cathode. The host improved electrical conductivity, enhanced physical-chemical dual restricting capability toward LiPSs, and, more importantly, boosted the redox reaction kinetics by the Ni-N5 active moiety. Therefore, the Ni-N5/HNPC/S cathode exhibits superior rate performance, long-term cycling stability, and good areal capacity at high sulfur loading. This work highlights the important role of the coordination number of active centers in single-atom catalysts and provides a strategy to design a hollow nanoarchitecture with single-atom active sites for high-performance Li-S batteries.

A Novel Conflict Measurement in Decision-Making and Its Application in Fault Diagnosis

Abstract: Dempster–Shafer evidence (DSE) theory, which allows combining pieces of evidence from different data sources to derive a degree of belief function that is a type of fuzzy measure, is a general framework for reasoning with uncertainty. In this framework, how to optimally manage the conflicts of multiple pieces of evidence in DSE remains an open issue to support decision making. The existing conflict measurement approaches can achieve acceptable outcomes but do not fully consider the optimization at the decision-making level using the novel measurement of conflicts. In this article, we propose a novel evidential correlation coefficient (ECC) for belief functions by measuring the conflict between two pieces of evidence in decision making. Then, we investigate the properties of our proposed evidential correlation and conflict coefficients, which are all proven to satisfy the desirable properties for conflict measurement, including nonnegativity, symmetry, boundedness, extreme consistency, and insensitivity to refinement. We also present several examples and comparisons to demonstrate the superiority of our proposed ECC method. Finally, we apply the proposed ECC in a decision-making application of motor rotor fault diagnosis, which verifies the practicability and effectiveness of our proposed novel measurement.

A chromosome-level genome of the spider Trichonephila antipodiana reveals the genetic basis of its polyphagy and evidence of an ancient whole-genome duplication event.

Abstract: Background The spider Trichonephila antipodiana (Araneidae), commonly known as the batik golden web spider, preys on arthropods with body sizes ranging from ∼2 mm in length to insects larger than itself (>20‒50 mm), indicating its polyphagy and strong dietary detoxification abilities. Although it has been reported that an ancient whole-genome duplication event occurred in spiders, lack of a high-quality genome has limited characterization of this event. Results We present a chromosome-level T. antipodiana genome constructed on the basis of PacBio and Hi-C sequencing. The assembled genome is 2.29 Gb in size with a scaffold N50 of 172.89 Mb. Hi-C scaffolding assigned 98.5% of the bases to 13 pseudo-chromosomes, and BUSCO completeness analysis revealed that the assembly included 94.8% of the complete arthropod universal single-copy orthologs (n = 1,066). Repetitive elements account for 59.21% of the genome. We predicted 19,001 protein-coding genes, of which 96.78% were supported by transcriptome-based evidence and 96.32% matched protein records in the UniProt database. The genome also shows substantial expansions in several detoxification-associated gene families, including cytochrome P450 mono-oxygenases, carboxyl/cholinesterases, glutathione-S-transferases, and ATP-binding cassette transporters, reflecting the possible genomic basis of polyphagy. Further analysis of the T. antipodiana genome architecture reveals an ancient whole-genome duplication event, based on 2 lines of evidence: (i) large-scale duplications from inter-chromosome synteny analysis and (ii) duplicated clusters of Hox genes. Conclusions The high-quality T. antipodiana genome represents a valuable resource for spider research and provides insights into this species' adaptation to the environment.

Edible films from chitosan-gelatin: Physical properties and food packaging application

Abstract: Environmental pollution problems caused by plastic-based packaging promote alternative sustainable solutions to be imminent. Chitosan and gelatin are attracting great attentions in food packaging applications and representing interesting biomaterials for developing edible packaging film due to their excellent inherent properties including degradability, edibility, film-forming property and compatible nature. With the development of technology and economy, food-grade chitosan and food-grade gelatin are emerging and produced under legislation or standards proposed by the government or organization. These chitosan and gelatin could form uniform film-forming solutions and fabricate edible films by strategies including casting, electrospinning and thermoplastic method. The emerging chitosan-gelatin composite films with excellent physical properties including mechanical property, surface hydrophobic property, color property, barrier property and thermal property have achieved great developments. This article comprehensively reviews recent advances in legislation of raw materials, fabrication strategies and physical properties of chitosan-gelatin based edible films.

Microenvironment-Responsive Prodrug-Induced Pyroptosis Boosts Cancer Immunotherapy

Abstract: The absence of tumor antigens leads to a low response rate, which represents a major challenge in immune checkpoint blockade (ICB) therapy. Pyroptosis, which releases tumor antigens and damage-associated molecular patterns (DAMPs) that induce antitumor immunity and boost ICB efficiency, potentially leads to injury when occurring in normal tissues. Therefore, a strategy and highly efficient agent to induce tumor-specific pyroptosis but reduce pyroptosis in normal tissues is urgently required. Here, a smart tumor microenvironmental reactive oxygen species (ROS)/glutathione (GSH) dual-responsive nano-prodrug (denoted as MCPP) with high paclitaxel (PTX) and photosensitizer purpurin 18 (P18) loading is rationally designed. The ROS/GSH dual-responsive system facilitates the nano-prodrug response to high ROS/GSH in the tumor microenvironment and achieves optimal drug release in tumors. ROS generated by P18 after laser irradiation achieves controlled release and induces tumor cell pyroptosis with PTX by chemo-photodynamic therapy. Pyroptotic tumor cells release DAMPs, thus initiating adaptive immunity, boosting ICB efficiency, achieving tumor regression, generating immunological memory, and preventing tumor recurrence. Mechanistically, chemo-photodynamic therapy and control-release PTX synergistically induce gasdermin E (GSDME)-related pyroptosis. It is speculated that inspired chemo-photodynamic therapy using the presented nano-prodrug strategy can be a smart strategy to trigger pyroptosis and augment ICB efficiency.