bluuebunny/crossref_metadata_2025 huggingface dataset:
Diagnostic Advances in Childhood Tuberculosis—Improving Specimen Collection and Yield of Microbiological Diagnosis for Intrathoracic Tuberculosis
Authors: Wobudeya Eric , Bonnet Maryline , Walters Elisabetta Ghimenton , Nabeta Pamela , Song Rinn , Murithi Wilfred , Mchembere Walter , Dim Bunnet , Taguebue Jean-Voisin , Orne-Gliemann Joanna , Nicol Mark P. , Marcy Olivier
Published: March 2022

There is no microbiological gold standard for childhood tuberculosis (TB) diagnosis. The paucibacillary nature of the disease, challenges in sample collection in young children, and the limitations of currently available microbiological tests restrict microbiological confirmation of intrathoracic TB to the minority of children. Recent WHO guidelines recommend the use of novel rapid molecular assays as initial diagnostic tests for TB and endorse alternative sample collection methods for children. However, the uptake of these tools in high-endemic settings remains low. In this review, we appraise historic and new microbiological tests and sample collection techniques that can be used for the diagnosis of intrathoracic TB in children. We explore challenges and possible ways to improve diagnostic yield despite limitations, and identify research gaps to address in order to improve the microbiological diagnosis of intrathoracic TB in children.
Low Drug Loading Hampers the Clinical Translation of Peptide Drugs-Containing Metered-Dose Inhalers
Authors: Huang Zhengwei , Shu Lei , Huang Ying , Wu Chuanbin , Pan Xin
Published: March 2022

Peptide-based drugs have attracted extensive attention from the medical and pharmaceutical industry because of their relatively high safety and efficacy. However, most of the peptide drugs approved are administrated by injection, which can easily cause poor patient compliance. In this circumstance, pulmonary administration as an alternative to injection administration can not only avoid the above issue but also accelerate the absorption rate of peptide drugs and improve bioavailability. Among the pulmonary delivery systems available on the market, metered-dose inhalers (MDIs) have emerged as appealing candidates for pulmonary delivery systems with clinical translational value, owing to their many merits, including portable, easy-to-operate, and cost-effective properties. Nevertheless, the industrialization of peptide drugs-containing MDIs encounters a bottleneck of low drug loading, owing to the incompatibility between the propellant and the peptide drugs, which cannot be effectively overcome by the current carrier particle encapsulation strategy. Herein, we put forward the following strategies: (1) To screen amphiphilic materials with high surface activity and strong interaction with peptide drugs; (2) To construct a chemical connection between peptide drugs and amphiphilic substances; (3) To optimize the cosolvent for dispersing peptide drugs. We suppose these strategies have the potential to defeat the bottleneck problem and provide a new idea for the industrialization of peptide drugs-containing MDIs.
Paeoniflorin Alleviates Skeletal Muscle Atrophy in Ovariectomized Mice through the ERα/NRF1 Mitochondrial Biogenesis Pathway
Authors: Park Ki-Sun , Kim Hyungjun , Kim Hye Jin , Lee Kang-In , Lee Seo-Young , Kim Jieun
Published: March 2022

Muscle atrophy in postmenopausal women is caused by estrogen deficiency and a variety of inflammatory factors, including tumor necrosis factor alpha (TNFα). Paeoniflorin (PNF), a natural compound with anti-inflammatory properties, improves estradiol synthesis. Here, we demonstrate that PNF inhibits the progression of TNFα-induced skeletal muscle atrophy after menopause by restoring mitochondrial biosynthesis. Differentiated myoblasts damaged by TNFα were restored by PNF, as evident by the increase in the expression of myogenin (MyoG) and myosin heavy chain 3 (Myh3)—the markers of muscle differentiation. Moreover, diameter of atrophied myotubes was restored by PNF treatment. TNFα-repressed nuclear respiratory factor 1 (NRF1) and mitochondrial transcription factor A (TFAM) (a major regulator of mitochondrial biosynthesis) were restored by PNF, via regulation by estrogen receptor alpha (ERα), an upregulator of NRF1. This mechanism was confirmed in ovariectomized (OVX) mice with a ~40% reduction in the cross-sectional area of the anterior tibialis muscle. OVX mice administered PNF (100, 300 mg/kg/day) for 12 weeks recovered more than ~20%. Behavioral, rotarod, and inverted screen tests showed that PNF enhances reduced muscle function in OVX mice. ERα restored expression of mitofusin 1 (MFN1) and mitofusin 2 (MFN2) (mitochondrial fusion markers) and dynamin-related protein (DRP1) and fission 1 (FIS1) (mitochondrial fission markers). Therefore, PNF can prevent muscle atrophy in postmenopausal women by inhibiting dysfunctional mitochondrial biogenesis.
Drug Nanocrystals: Focus on Brain Delivery from Therapeutic to Diagnostic Applications
Authors: Zingale Elide , Bonaccorso Angela , Carbone Claudia , Musumeci Teresa , Pignatello Rosario
Published: March 2022

The development of new drugs is often hindered by low solubility in water, a problem common to nearly 90% of natural and/or synthetic molecules in the discovery pipeline. Nanocrystalline drug technology involves the reduction in the bulk particle size down to the nanosize range, thus modifying its physico-chemical properties with beneficial effects on drug bioavailability. Nanocrystals (NCs) are carrier-free drug particles surrounded by a stabilizer and suspended in an aqueous medium. Due to high drug loading, NCs maintain a potent therapeutic concentration to produce desirable pharmacological action, particularly useful in the treatment of central nervous system (CNS) diseases. In addition to the therapeutic purpose, NC technology can be applied for diagnostic scope. This review aims to provide an overview of NC application by different administration routes, especially focusing on brain targeting, and with a particular attention to therapeutic and diagnostic fields. NC therapeutic applications are analyzed for the most common CNS pathologies (i.e., Parkinson’s disease, psychosis, Alzheimer’s disease, etc.). Recently, a growing interest has emerged from the use of colloidal fluorescent NCs for brain diagnostics. Therefore, the use of NCs in the imaging of brain vessels and tumor cells is also discussed. Finally, the clinical effectiveness of NCs is leading to an increasing number of FDA-approved products, among which the NCs approved for neurological disorders have increased.
Comprehensive Analysis of Nivolumab, A Therapeutic Anti-Pd-1 Monoclonal Antibody: Impact of Handling and Stress
Authors: Torrente-López Anabel , Hermosilla Jesús , Salmerón-García Antonio , Cabeza José , Navas Natalia
Published: March 2022

Nivolumab, formulated in the medicine Opdivo® (10 mg/mL), is a therapeutic monoclonal antibody (mAb) used in the treatment of different types of cancer. Currently, there is insufficient knowledge about the behaviour of this protein with regards to the risk associated with its routine handling or unintentional mishandling, or when subjected to stress conditions in hospitals. These conditions can be simulated in forced degradation studies, which provide an in-depth understanding of the biophysical and biochemical properties of mAbs. In this study, we carried out a physicochemical and functional characterisation of nivolumab, which was subjected to various stress conditions: heat, freeze/thaw cycles, agitation, light exposure and high hypertonic solution. We used a wide range of analytical techniques: Far-UV CD, IT-FS, DLS, SE/UHPLC(UV)-[Native]MS, and ELISA. The results show that exposure to light was the stress test with the greatest impact on the samples, revelling the formation of non-natural dimers and a different isoform profile. In addition, nivolumab (Opdivo®) demonstrated stability up to 60 °C (1 h). As regards functionality all the nivolumab (Opdivo®) stressed samples were found to be stable except for those subjected to light and agitation, and to a lesser extent, those subjected to FTC 5 and NaCl stresses.
The Optimization of a Convex Aspheric Lightweight SiC Mirror and Its Optical Metrology
Authors: Jiang Ping , Zhou Pingwei
Published: March 2022

Space telescopes with large diameters or with wide fields require convex secondary mirrors which are mounted at the front of telescope. In this paper, a convex aspheric lightweight SiC mirror and Hindle detection method are presented. A parameter optimization method is utilized in the mirror design process in which the mirror surface accuracy is taken as the objective. As the mirror has a relative high diameter-to-thickness ratio, an S-type flexure support is proposed to maintain the surface figure under gravity, thermal change and assembly error. To minimize the surface figure under these loads, the design principle is studied separately. The optical metrology is performed by the Hindle ball supported by a gravity offloading system. The tested surface had an accuracy of λ/100 root mean square (λ = 632.8 nm). In addition, the mechanical design was validated by dynamic testing.
Pulse Shape Estimation in a DSR Fiber Laser Using the Genetic Algorithm
Authors: Bahloul Faouzi , Boussaidi Mariem , Karar Abdullah S. , Salhi Mohamed
Published: March 2022

Exploiting the computing power of the genetic algorithm, a numerical study of dissipative soliton resonance (DSR) in a ring laser mode-locked by a real saturable absorber (SA) is conducted. A section of photonic crystal fiber (PCF) is inserted into the laser cavity design to facilitate accurate control of both dispersion and nonlinearity. The influence of the cavity parameters on the evolution of the DSR pulses is systematically analyzed. The genetic algorithm demonstrates that the generation of DSR square pulses depends directly on the PCF dispersion, the PCF nonlinearity, the PCF length, and the modulation depth of the SA. Finally, the sensitivity of the DSR pulse width, peak power and energy to perturbations in a few key design parameters are highlighted.
Fungal Pathogenesis-Related Cell Wall Biogenesis, with Emphasis on the Maize Anthracnose Fungus Colletotrichum graminicola
Authors: Oliveira Silva Alan de , Aliyeva-Schnorr Lala , Wirsel Stefan G. R. , Deising Holger B.
Published: March 2022

The genus Colletotrichum harbors many plant pathogenic species, several of which cause significant yield losses in the field and post harvest. Typically, in order to infect their host plants, spores germinate, differentiate a pressurized infection cell, and display a hemibiotrophic lifestyle after plant invasion. Several factors required for virulence or pathogenicity have been identified in different Colletotrichum species, and adaptation of cell wall biogenesis to distinct stages of pathogenesis has been identified as a major pre-requisite for the establishment of a compatible parasitic fungus–plant interaction. Here, we highlight aspects of fungal cell wall biogenesis during plant infection, with emphasis on the maize leaf anthracnose and stalk rot fungus, Colletotrichum graminicola.
Phenotype and Genotype Interaction Underlying Distributive Characteristic for Awn Development in Rice
Authors: Park Jae-Ryoung , Son Ju , Kim Eun-Gyeong , Jang Yoon-Hee , Yun Byoung-Ju , Kim Kyung-Min
Published: March 2022

As a wild ancestor of cultivated rice, Oryza rufipogon is domesticated into cultivated rice Oryza sativa, many agricultural traits are newly created or disappear. In particular, in wild rice, awn protects from predators and is easily blown by the wind and used as a means of propagation. However, awns gradually disappeared as they were breeding from wild rice to cultivated rice. Since awn development is disadvantageous to rice yield, it is important to understand the genetic basis related to awn development. In addition, characterization of the genes associated with awn development is helpful in analyzing the genetic relationships of rice from ancient times to the present for the regulatory mechanisms of awn formation. QTL analysis identified RM14330-RM218 on chromosome 3 using a 120 Cheongcheong/Nagdong double haploid population. Through screening of genes related to awn development in RM-14330-RM218, it is indicated that OsDRPq3 is a causal gene that can be involved in awn development. OsDRPq3 transcription level is maintained high in long awn and less yield populations during the panicle formation stage, the period during awn development. Moreover, the sequence of OsDRPq3 has high homology with the drooping protein leaf. This study provides a new resource for phylogenetic research of rice and exploration of awn development.
Assessing the Invasion Risk of Humulus scandens Using Ensemble Species Distribution Modeling and Habitat Connectivity Analysis
Authors: Urziceanu Mariana Mihaela , Cîșlariu Alina Georgiana , Nagodă Eugenia , Nicolin Alma Lioara , Măntoiu Dragoș Ștefan , Anastasiu Paulina
Published: March 2022

Given the rapid spread of invasive alien plant species in Europe and limited information regarding their distribution and dispersion patterns, we analyzed the invasive risk of Humulus scandens, a species with an increased invasive potential. We collected occurrence records from Romania within an EU funded project and literature data, in order to perform an ensemble distribution model. Environmental variables varied from downscaled topoclimatic continuous entries to categorical ones, such as soil class, texture, or land use. Results showed potential core areas of the species within the study region. By inverting the probability output of the models, we have created a resistance surface which helped us model its dispersion patterns. Further, we assessed the probability of invasion for each resulted corridor using the species dispersion ecology and created an invasion risk map. H. scandens is highly influenced by milder climates and areas with constant flooding events, thus we found that the Tisa basin and its tributaries can be under a high invasion risk, spreading through the entire catchment, in Central, Western, and Northern Romania, towards the Eastern Carpathians. The Danube acted as a dispersion corridor for major river systems in southern Romania, but the dispersion capability of the species dropped in steppe areas with higher aridity and limited water course network. This approach is useful for creating adequate action plans in relation to invasive alien plant species, and should urgently be regarded, as results show a potentially large distribution of H. scandens across entire water catchment areas, with devastating effects on natural ecosystems.
Conductivity Behaviour under Pressure of Copper Micro-Additive/Polyurethane Composites (Experiment and Modelling)
Authors: Mehvari Saeid , Sanchez-Vicente Yolanda , González Sergio , Lafdi Khalid
Published: March 2022

In this study, micro-size copper particles (less than 25 μm) were incorporated into polyurethane (PU) using a solution mixing method and spin-coating technique to fabricate composite films in concentrations from 0.5 to 20 vol.%. The conductivity behaviour of these composites under pressure was studied experimentally and numerically. The conductivity measurements were performed in-plane and through-thickness under pressure. It was found that changes in conductivity only occurred in the z-direction under an applied pressure from 1 to 20 kPa. The results showed that pressure could induce conductivity up to about 7.2 × 10−1 S∙m−1 for composites with a Cu concentration higher than 2.6 vol.%. It seems that applied pressure reduced the thickness of the polymer film, decreasing the distance between copper particles and promoting the formation of a conductive network, thus making the material conductive. A semi-analytical model that can accurately provide the percolation threshold (PT) concentration was used to fit the experimental conductivity. The PT concentrations for PU-Cu composite ranged from 7.1 vol.% to 1.4 vol.% and decreased with the rise in pressure. This is known as a pressure-induced percolation transition phenomenon (PIPT). Finally, the finite element method based on the representative volume element model (FE-RVE) simulation technique was used to predict the conductivity behaviour. This numerical simulation provided a good description of the experimental conductivity after the PT and correctly predicted the PT concentration. This study shows that FE-RVE could be used to effectively simulate the influence of pressure on the electrical properties of a polymer–metal composite, reducing the need for costly and time-consuming experiments.
Fabrication of Conductive, High Strength and Electromagnetic Interference (EMI) Shielded Green Composites Based on Waste Materials
Authors: Ali Azam , Hussain Fiaz , Tahir Muhammad Farrukh , Ali Majid , Zaman Khan Muhammad , Tomková Blanka , Militky Jiri , Noman Muhammad Tayyab , Azeem Musaddaq
Published: March 2022

Conventional conductive homopolymers such as polypyrrole and poly-3,4-ethylenedioxythiophene (PEDOT) have poor mechanical properties, for the solution to this problem, we tried to construct hybrid composites with higher electrical properties coupled with high mechanical strength. For this purpose, Kevlar fibrous waste, conductive carbon particles, and epoxy were used to make the conductive composites. Kevlar waste was used to accomplish the need for economics and to enhance the mechanical properties. At first, Kevlar fibrous waste was converted into a nonwoven web and subjected to different pretreatments (chemical, plasma) to enhance the bonding between fiber-matrix interfaces. Similarly, conductive carbon particles were converted into nanofillers by the action of ball milling to make them homogeneous in size and structure. The size and morphological structures of ball-milled particles were analyzed by Malvern zetasizer and scanning electron microscopy. In the second phase of the study, the conductive paste was made by adding the different concentrations of ball-milled carbon particles into green epoxy. Subsequently, composite samples were fabricated via a combination of prepared conductive pastes and a pretreated Kevlar fibers web. The influence of different concentrations of carbon particles into green epoxy resin for electrical conductivity was studied. Additionally, the electrical conductivity and electromagnetic shielding ability of conductive composites were analyzed. The waveguide method at high frequency (i.e., at 2.45 GHz) was used to investigate the EMI shielding. Furthermore, the joule heating response was studied by measuring the change in temperature at the surface of the conductive composite samples, while applying a different range of voltages. The maximum temperature of 55 °C was observed when the applied voltage was 10 V. Moreover, to estimate the durability and activity in service the ageing performance (mechanical strength and moisture regain) of developed composite samples were also analyzed.
Multiscale Investigation on the Performance of Engineered Cementitious Composites Incorporating PE Fiber and Limstone Calcined Clay Cement (LC3)
Authors: Gong Guoqiang , Guo Menghuan , Zhou Yingwu , Zheng Shuyue , Hu Biao , Zhu Zhongfeng , Huang Zhenyu
Published: March 2022

Limestone calcined clay cement (LC3) is successfully used to fabricate engineered cementitious composites (ECC) exhibiting tensile strength σtu of 9.55 ± 0.59 MPa or tensile strain capacity εtu of 8.53 ± 0.30%. The high tensile strength of the composites is closely related to the improvement of fiber/matrix interfacial bond strength, and the high ductility is attributed to the enhancement of fiber dispersion homogeneity. For the case of ECC incorporating 50% LC3, the reduction of initial cracking stress σtc that favors the growth of the crack in a controlled manner also contributes to the improvement of strain hardening behavior. The composition analysis indicates that carboaluminates and additional hydration products including C-(A)-S-H and ettringite are generated, which contributes to the densification of the microstructure of the ECC matrix. The pore structure is thus remarkably refined. Besides, when ordinary Portland cement (OPC) is partly replaced by LC3, the consumed energy and equivalent CO2 emission decrease, especially the equivalent CO2 emission with the reduction ratio attaining 40.31%. It is found that ECC using 35% LC3 exhibits the highest mechanical resistance and ECC incorporating 50% LC3 shows the highest ductility from the environmental point of view.
Fused-Filament Fabrication of Short Carbon Fiber-Reinforced Polyamide: Parameter Optimization for Improved Performance under Uniaxial Tensile Loading
Authors: Belei Carlos , Joeressen Jana , Amancio-Filho Sergio T.
Published: March 2022

This study intends to contribute to the state of the art of Fused-Filament Fabrication (FFF) of short-fiber-reinforced polyamides by optimizing process parameters to improve the performance of printed parts under uniaxial tensile loading. This was performed using two different approaches: a more traditional 2k full factorial design of experiments (DoE) and multiple polynomial regression using an algorithm implementing machine learning (ML) principles such as train-test split and cross-validation. Evaluated parameters included extrusion and printing bed temperatures, layer height and printing speed. It was concluded that when exposed to new observations, the ML-based model predicted the response with higher accuracy. However, the DoE fared slightly better at predicting observations where higher response values were expected, including the optimal solution, which reached an UTS of 117.1 ± 5.7 MPa. Moreover, there was an important correlation between process parameters and the response. Layer height and printing bed temperatures were considered the most influential parameters, while extrusion temperature and printing speed had a lower influence on the outcome. The general influence of parameters on the response was correlated with the degree of interlayer cohesion, which in turn affected the mechanical performance of the 3D-printed specimens.
Highly Stretchable and Sensitive Multimodal Tactile Sensor Based on Conductive Rubber Composites to Monitor Pressure and Temperature
Authors: Zhu Bing , Ma Chi , Qian Zhihui , Ren Lei , Yuan Hengyi
Published: March 2022

Stretchable and flexible tactile sensors have been extensively investigated for a variety of applications due to their outstanding sensitivity, flexibility, and biocompatibility compared with conventional tactile sensors. However, implementing stretchable multimodal sensors with high performance is still a challenge. In this study, a stretchable multimodal tactile sensor based on conductive rubber composites was fabricated. Because of the pressure-sensitive and temperature-sensitive effects of the conductive rubber composites, the developed sensor can simultaneously measure pressure and temperature, and the sensor presented high sensitivity (0.01171 kPa−1 and 2.46–30.56%/°C) over a wide sensing range (0–110 kPa and 30–90 °C). The sensor also exhibited outstanding performance in terms of processability, stretchability, and repeatability. Furthermore, the fabricated stretchable multimodal tactile sensor did not require complex signal processing or a transmission circuit system. The strategy for stacking and layering conductive rubber composites of this work may supply a new idea for building multifunctional sensor-based electronics.
Influence of HLB Value of Emulsifier on the Properties of Microcapsules and Self-Healing Properties of Waterborne Coatings
Authors: Tao Yu , Yan Xiaoxing
Published: March 2022

In this paper, self-healing microcapsules were prepared by using melamine–formaldehyde (MF) resin as the wall material and shellac as the core material repairing agent. In order to explore the effect of the four factors (i.e., the HLB value of emulsifier, the type of solvent, the mass ratio of shellac to rosin, and the rate of rotating) on the comprehensive performance of microcapsules, and orthogonal experiments with four factors and three levels were carried out. The results showed that the hydrophilic lipophilic balance (HLB) value of the emulsifier was the most important influencing factor. In order to further explore the relationship between the HLB value of the emulsifier and the morphology of the microcapsules and the coating rate as well as to further optimize the performance of the microcapsules, taking the HLB value of the emulsifier as the single factor variable, single-factor tests were carried out. The results showed that when the HLB value was 12.56, the microcapsules of melamine–formaldehyde resin-coated shellac–rosin mixture had a uniform distribution and high coating rate. In order to explore the self-healing properties of waterborne coatings with microcapsules, the microcapsules prepared by single-factor experiments were mixed into the waterborne coatings at mass ratios of 0%, 3.0%, 6.0%, 9.0%, 12.0%, and 15.0%. It showed that the elongation at break of the waterborne coating with the addition of 3.0% microcapsule at mass fraction was improved, and it had a higher repair rate. This study provides a new research idea for the optimization and characterization of the self-healing properties of waterborne coatings.
Biofunctionalization of Endolysins with Oligosacharides: Formulation of Therapeutic Agents to Combat Multi-Resistant Bacteria and Potential Strategies for Their Application
Authors: Camacho-González Carlos E. , Cardona-Félix César S. , Zamora-Gasga Victor , Pérez-Larios Alejandro , Sánchez-Burgos Jorge Alberto
Published: March 2022

In the aquaculture sector, the biofunctionalization of biomaterials is discussed using materials from algae and analyzed as a possible potential strategy to overcome the challenges that hinder the future development of the application of endolysins in this field. Derived from years of analysis, endolysins have recently been considered as potential alternative therapeutic antibacterial agents, due to their attributes and ability to combat multi-resistant bacterial cells when applied externally. On the other hand, although the aquaculture sector has been characterized by its high production rates, serious infectious diseases have led to significant economic losses that persist to this day. Although there are currently interesting data from studies under in vitro conditions on the application of endolysins in this sector, there is little or no information on in vivo studies. This lack of analysis can be attributed to the relatively low stability of endolysins in marine conditions and to the complex gastrointestinal conditions of the organisms. This review provides updated information regarding the application of endolysins against multi-resistant bacteria of clinical and nutritional interest, previously addressing their important characteristics (structure, properties and stability). In addition, regarding the aquaculture sector, the biofunctionalization of biomaterials is discussed using materials from algae and analyzed as a possible potential strategy to overcome the challenges that hinder the future development of the application of endolysins in this field.
Queuing Models for Analyzing the Steady-State Distribution of Stochastic Inventory Systems with Random Lead Time and Impatient Customers
Authors: Alnowibet Khalid A. , Alrasheedi Adel F. , Alqahtani Firdous S.
Published: March 2022

In material management, the inventory systems may have good management aspects in terms of materials; however, this negatively affects the relationship between the facility and customers. In classical inventory models, arriving demands are satisfied immediately if there is enough on-hand inventory. Traditional inventory models consider optimization problems and find the optimal policy of decision variables without computing the stationary distribution of the inventory states for random demand. Hence, a detailed analysis of inventory management systems requires a joint distribution of system stock levels and the number of requests to be investigated thoroughly. This research provides a new stochastic mathematical model for inventory systems with lead times and impatient customers under deterministic and uniform order sizes. The proposed model identifies the performance measures in a stochastic environment, analyzing the properties of the inventory system with stochastic and probabilistic parameters, and finally, validating the model’s accuracy. To analyze the system, balance equations were derived from a mathematical characterization of the underlying queuing model dependent on the Markov chain formalism. The precise performance was achieved by examining the graphical representation of the service process in a steady-state as a function of both arrival distribution and the customer patience coefficient, while it was challenging to derive an optimal curve fit in a three-dimensional space that features two input variables and a single output variable.
Sovereign Credit Ratings Analysis Using the Logistic Regression Model
Authors: Takawira Oliver , Mwamba John W. Muteba
Published: March 2022

This study is an empirical analysis of sovereign credit ratings (SCR) in South Africa (SA) using Logistic Regression (LR) to identify their determinants and forecast SCRs. Data of macroeconomic indicators including SCRs from 1999 to 2020 in quarterly format were classified and analyzed to identify indicators utilized by Credit Rating Agencies (CRAs) and then predict future ratings CRAs take various information from political, infrastructure, financial, economic, regional, local, and other factors pertaining to a country and assess the ability of that country to pay its debt. This information is then presented through a grading scale termed rating, with the highest rating country being highly creditworthy and lowest rating likely to default. There are three major CRAs, namely, Fitch, Moodys and Standard and Poors. The study identified the use of different macroeconomic indicators by CRAs as well as different techniques in assessing and assigning sovereign credit ratings. The study points out that Household Debt to Disposable Income Ratio (HDDIR) was the most influential variable on SCRs. HDDIR, exchange rates and the inflation rate were the most crucial variables for guessing credit ratings. Policymakers should aim to reduce household debt in relation to disposable income, implement policies that strengthen the local currency and stabilize as well as lower inflation. Investors should watch out on nations that have high household debt levels as this may spill over into credit risk.
LSNet: Learned Sampling Network for 3D Object Detection from Point Clouds
Authors: Wang Mingming , Chen Qingkui , Fu Zhibing
Published: March 2022

The3D object detection of LiDAR point cloud data has generated widespread discussion and implementation in recent years. In this paper, we concentrate on exploring the sampling method of point-based 3D object detection in autonomous driving scenarios, a process which attempts to reduce expenditure by reaching sufficient accuracy using fewer selected points. FPS (farthest point sampling), the most used sampling method, works poorly in small sampling size cases, and, limited by the massive points, some newly proposed sampling methods using deep learning are not suitable for autonomous driving scenarios. To address these issues, we propose the learned sampling network (LSNet), a single-stage 3D object detection network containing an LS module that can sample important points through deep learning. This advanced approach can sample points with a task-specific focus while also being differentiable. Additionally, the LS module is streamlined for computational efficiency and transferability to replace more primitive sampling methods in other point-based networks. To reduce the issue of the high repetition rates of sampled points, a sampling loss algorithm was developed. The LS module was validated with the KITTI dataset and outperformed the other sampling methods, such as FPS and F-FPS (FPS based on feature distance). Finally, LSNet achieves acceptable accuracy with only 128 sampled points and shows promising results when the number of sampled points is small, yielding up to a 60% improvement against competing methods with eight sampled points.
QDA-System: A Cloud-Based System for Monitoring Water Quality in Brazilian Hydroelectric Reservoirs from Space
Authors: Curtarelli Marcelo , Neto Edmar , de Siqueira Fanny , Yopan Felipe , Soares Gilmar , Pauli Gilnei , de Souza João , Silva Luana , Sagaz Marcio , Demay Miguel , Bortolas Natália , Yoshimura Ricardo , Guimarães Vitor
Published: March 2022

This article presents the QDA-System (Sistema Qualidade da Água, from Portuguese), a system developed to monitor the quality of surface waters in Brazilian hydroelectric reservoirs using satellite images and cloud computing services. The development requirements of the QDA-System considered its use for operational monitoring purposes, with all processing steps automated, and a user-friendly interface to access and query the data generated automatically by the system. A pilot application of the QDA-System was customized and implemented for monitoring the Foz do Chapecó hydroelectric reservoir located in southern Brazil. For the pilot application, the QDA-System was customized to estimate nine water quality parameters,: five were estimated directly from Sentinel-2 multispectral images and four were estimated indirectly. We expect that in the near future the QDA-System can be replicated to monitor other Brazilian reservoirs, bringing benefits and cost reduction related to water quality monitoring, not only for the sector of hydroelectric generation but for other sectors that also need similar monitoring, such as sanitation and aquaculture production.
Plant Viral Disease Detection: From Molecular Diagnosis to Optical Sensing Technology—A Multidisciplinary Review
Authors: Wang Yeniu Mickey , Ostendorf Bertram , Gautam Deepak , Habili Nuredin , Pagay Vinay
Published: March 2022

Plant viral diseases result in productivity and economic losses to agriculture, necessitating accurate detection for effective control. Lab-based molecular testing is the gold standard for providing reliable and accurate diagnostics; however, these tests are expensive, time-consuming, and labour-intensive, especially at the field-scale with a large number of samples. Recent advances in optical remote sensing offer tremendous potential for non-destructive diagnostics of plant viral diseases at large spatial scales. This review provides an overview of traditional diagnostic methods followed by a comprehensive description of optical sensing technology, including camera systems, platforms, and spectral data analysis to detect plant viral diseases. The paper is organized along six multidisciplinary sections: (1) Impact of plant viral disease on plant physiology and consequent phenotypic changes, (2) direct diagnostic methods, (3) traditional indirect detection methods, (4) optical sensing technologies, (5) data processing techniques and modelling for disease detection, and (6) comparison of the costs. Finally, the current challenges and novel ideas of optical sensing for detecting plant viruses are discussed.
Quantifying Post-Fire Changes in the Aboveground Biomass of an Amazonian Forest Based on Field and Remote Sensing Data
Authors: Pontes-Lopes Aline , Dalagnol Ricardo , Dutra Andeise Cerqueira , de Jesus Silva Camila Valéria , de Alencastro Graça Paulo Maurício Lima , de Oliveira e Cruz de Aragão Luiz Eduardo
Published: March 2022

Fire is a major forest degradation component in the Amazon forests. Therefore, it is important to improve our understanding of how the post-fire canopy structure changes cascade through the spectral signals registered by medium-resolution satellite sensors over time. We contrasted accumulated yearly temporal changes in forest aboveground biomass (AGB), measured in permanent plots, and in traditional spectral indices derived from Landsat-8 images. We tested if the spectral indices can improve Random Forest (RF) models of post-fire AGB losses based on pre-fire AGB, proxied by AGB data from immediately after a fire. The delta normalized burned ratio, non-photosynthetic vegetation, and green vegetation (ΔNBR, ΔNPV, and ΔGV, respectively), relative to pre-fire data, were good proxies of canopy damage through tree mortality, even though small and medium trees were the most affected tree size. Among all tested predictors, pre-fire AGB had the highest RF model importance to predicting AGB within one year after fire. However, spectral indices significantly improved AGB loss estimates by 24% and model accuracy by 16% within two years after a fire, with ΔGV as the most important predictor, followed by ΔNBR and ΔNPV. Up to two years after a fire, this study indicates the potential of structural and spectral-based spatial data for integrating complex post-fire ecological processes and improving carbon emission estimates by forest fires in the Amazon.
Parameter Estimation for Precession Cone-Shaped Targets Based on Range–Frequency–Time Radar Data Cube
Authors: Han Lixun , Feng Cunqian
Published: March 2022

A radar echo signal received from a cone-shaped target with precession contains micro-Doppler (m-D) information from different effective scattering centers. By taking full advantage of the m-D information, this paper proposes a parameter estimation algorithm for precession cone-shaped targets based on the range–frequency–time radar data cube (RDC). We build scattering center models of precession cone-shaped targets with the occlusion effect. The Binary Mask method is first utilized to obtain a high-resolution range-Doppler (RD) sequence. On this basis, the range–frequency–time RDC can be extracted from the RD sequence. In order to approach the actual case, we discuss the parameter estimation algorithm under different radar lines-of-sight (LOS). The most attractive attribute of this algorithm is that it can conduct in-depth research on m-D parameter estimation from a three-dimensional (3D) domain. Finally, the experimental results illustrate the effectiveness of the proposed method.
The Emotion Probe: On the Universality of Cross-Linguistic and Cross-Gender Speech Emotion Recognition via Machine Learning
Authors: Costantini Giovanni , Parada-Cabaleiro Emilia , Casali Daniele , Cesarini Valerio
Published: March 2022

Machine Learning (ML) algorithms within a human–computer framework are the leading force in speech emotion recognition (SER). However, few studies explore cross-corpora aspects of SER; this work aims to explore the feasibility and characteristics of a cross-linguistic, cross-gender SER. Three ML classifiers (SVM, Naïve Bayes and MLP) are applied to acoustic features, obtained through a procedure based on Kononenko’s discretization and correlation-based feature selection. The system encompasses five emotions (disgust, fear, happiness, anger and sadness), using the Emofilm database, comprised of short clips of English movies and the respective Italian and Spanish dubbed versions, for a total of 1115 annotated utterances. The results see MLP as the most effective classifier, with accuracies higher than 90% for single-language approaches, while the cross-language classifier still yields accuracies higher than 80%. The results show cross-gender tasks to be more difficult than those involving two languages, suggesting greater differences between emotions expressed by male versus female subjects than between different languages. Four feature domains, namely, RASTA, F0, MFCC and spectral energy, are algorithmically assessed as the most effective, refining existing literature and approaches based on standard sets. To our knowledge, this is one of the first studies encompassing cross-gender and cross-linguistic assessments on SER.
Cooperative Terrestrial-Underwater Wireless Optical Links by Using an Amplify-and-Forward Strategy
Authors: Jurado-Navas Antonio , Álvarez-Roa Carmen , Álvarez-Roa María , Castillo-Vázquez Miguel
Published: March 2022

In this paper, we analyze a combined terrestrial-underwater optical communication link for providing high-speed optical connectivity between onshore and submerge systems. For this purpose, different transmission signaling schemes were employed to obtain performance results in terms of average bit error rate (ABER). In this sense, from the starting point of a known conditional bit-error-rate (CBER) in the absence of turbulence, the behavior of the entire system is obtained by applying an amplify-and-forward (AF) based dual-hop system: The first link is a terrestrial free-space optical (FSO) system assuming a Málaga distributed turbulence and, the second one, is an underwater FSO system with a Weibull channel model. To obtain performance results, a semi-analytical simulation procedure is applied, using a hyper-exponential fitting technique previously proposed by the authors and leading to BER closed-form expressions and high-accuracy numerical results.
Time-Lag Aware Latent Variable Model for Prediction of Important Scenes Using Baseball Videos and Tweets
Authors: Hirasawa Kaito , Maeda Keisuke , Ogawa Takahiro , Haseyama Miki
Published: March 2022

In this study, a novel prediction method for predicting important scenes in baseball videos using a time-lag aware latent variable model (Tl-LVM) is proposed. Tl-LVM adopts a multimodal variational autoencoder using tweets and videos as the latent variable model. It calculates the latent features from these tweets and videos and predicts important scenes using these latent features. Since time lags exist between posted tweets and events, Tl-LVM introduces the loss considering time lags by correlating the feature into the loss function of the multimodal variational autoencoder. Furthermore, Tl-LVM can train the encoder, decoder, and important scene predictor, simultaneously, using this loss function. This is the novelty of Tl-LVM, and this work is the first end-to-end prediction model of important scenes that considers time lags to the best of our knowledge. It is the contribution of Tl-LVM to realize high-quality prediction using latent features that consider time lags between tweets and multiple corresponding previous events. Experimental results using actual tweets and baseball videos show the effectiveness of Tl-LVM.
Structural Anomalies Detection from Electrocardiogram (ECG) with Spectrogram and Handcrafted Features
Authors: Li Hongzu , Boulanger Pierre
Published: March 2022

Cardiovascular diseases are the leading cause of death globally, causing nearly 17.9 million deaths per year. Therefore, early detection and treatment are critical to help improve this situation. Many manufacturers have developed products to monitor patients’ heart conditions as they perform their daily activities. However, very few can diagnose complex heart anomalies beyond detecting rhythm fluctuation. This paper proposes a new method that combines a Short-Time Fourier Transform (STFT) spectrogram of the ECG signal with handcrafted features to detect heart anomalies beyond commercial product capabilities. Using the proposed Convolutional Neural Network, the algorithm can detect 16 different rhythm anomalies with an accuracy of 99.79% with 0.15% false-alarm rate and 99.74% sensitivity. Additionally, the same algorithm can also detect 13 heartbeat anomalies with 99.18% accuracy with 0.45% false-alarm rate and 98.80% sensitivity.
Evaluating the Accuracy of the Azure Kinect and Kinect v2
Authors: Kurillo Gregorij , Hemingway Evan , Cheng Mu-Lin , Cheng Louis
Published: March 2022

The Azure Kinect represents the latest generation of Microsoft Kinect depth cameras. Of interest in this article is the depth and spatial accuracy of the Azure Kinect and how it compares to its predecessor, the Kinect v2. In one experiment, the two sensors are used to capture a planar whiteboard at 15 locations in a grid pattern with laser scanner data serving as ground truth. A set of histograms reveals the temporal-based random depth error inherent in each Kinect. Additionally, a two-dimensional cone of accuracy illustrates the systematic spatial error. At distances greater than 2.5 m, we find the Azure Kinect to have improved accuracy in both spatial and temporal domains as compared to the Kinect v2, while for distances less than 2.5 m, the spatial and temporal accuracies were found to be comparable. In another experiment, we compare the distribution of random depth error between each Kinect sensor by capturing a flat wall across the field of view in horizontal and vertical directions. We find the Azure Kinect to have improved temporal accuracy over the Kinect v2 in the range of 2.5 to 3.5 m for measurements close to the optical axis. The results indicate that the Azure Kinect is a suitable substitute for Kinect v2 in 3D scanning applications.
A Cognitive Sample Consensus Method for the Stitching of Drone-Based Aerial Images Supported by a Generative Adversarial Network for False Positive Reduction
Authors: Seo Jeong-Kweon
Published: March 2022

When using drone-based aerial images for panoramic image generation, the unstableness of the shooting angle often deteriorates the quality of the resulting image. To prevent these polluting effects from affecting the stitching process, this study proposes deep learning-based outlier rejection schemes that apply the architecture of the generative adversarial network (GAN) to reduce the falsely estimated hypothesis relating to a transform produced by a given baseline method, such as the random sample consensus method (RANSAC). To organize the training dataset, we obtain rigid transforms to resample the images via the operation of RANSAC for the correspondences produced by the scale-invariant feature transform descriptors. In the proposed method, the discriminator of GAN makes a pre-judgment of whether the estimated target hypothesis sample produced by RANSAC is true or false, and it recalls the generator to confirm the authenticity of the discriminator’s inference by comparing the differences between the generated samples and the target sample. We have tested the proposed method for drone-based aerial images and some miscellaneous images. The proposed method has been shown to have relatively stable and good performances even in receiver-operated tough conditions.
Integration of IoT Technologies into the Smart Grid
Authors: Cavalieri Salvatore , Cantali Giulio , Susinna Andrea
Published: March 2022

This paper presents a novel solution in the field of the integration of the Smart Grid and the Internet of Things. The definition of a web platform able to offer a RESTful interface to IEC 61850 Servers to a generic user is proposed. The web platform enables the mapping of information maintained by an IEC 61850 Server into MQTT messages. Suitable mechanisms to introduce interoperable exchange of information were defined. The paper presents the main features offered by the proposed platform. The originality of the proposal is highlighted by comparing it with the current literature. A prototype was realized, and the software implementation choices are described and the main results of its evaluation are presented.