bluuebunny/crossref_metadata_2025 huggingface dataset:
The Use of Compost from Post-Consumer Wood Waste Containing Microbiological Inoculums on Growth and Flowering of Chrysanthemum (Chrysanthemum × grandiflorum Ramat./Kitam.)
Authors: Schroeter-Zakrzewska Anita , Komorowicz Magdalena
Published: May 2022

The purpose of the conducted study was to assess the possibility of using composts made from post-consumer wood containing waste of fibre boards and microbiological inoculums in chrysanthemum (Chrysanthemum × grandiflorum Ramat./Kitam.) ‘Jewel Time’ cultivation. Five variants of composts (marked ask, KK, AL, AL + K, EM, EM + K) were prepared, each variant was duplicate. All variants consisted of fibreboard waste (60% of its weight), mixed with mature compost made from fibreboard waste (30%), Protohumovit-biologically active organic fertilizer with the chemical composition of cattle manure (3%), starch, sugar, corn oil (together 7%). A biological inoculum “Activit Las” was added to one half of reactors. “Activit Las” (produced by Atlas Planta S.C, Bydgoszcz) is biological inoculum containing of selected bacteria, actinobacteria and fungi, that is intended to accelerate the composting of lignocellulosic materials, including wood from forest and sawmill. The second part of reactors was implemented by microbiological inoculum (EM) from Greenland Technologia EM (Trzcianki, Poland). A Bio Best (produced by Atlas Planta S.C, Bydgoszcz) formulation of chicken manure was added to some of the reactors containing EM and Activit Las. Compost without any additional microorganisms and microelements was control for experiment. Plant quality depended on the dose of compost used as well as on the type of microbial inoculations used during the composting process. The addition of composts containing the EM microbial inoculation to peat stimulated the formation of inflorescences and inflorescence buds. It also had a positive effect on the size and number of leaves. An additional effect of using compost obtained from wood waste is the reduction in the consumption of natural resources such as peat.
Structure from Linear Motion (SfLM): An On-the-Go Canopy Profiling System Based on Off-the-Shelf RGB Cameras for Effective Sprayers Control
Authors: De Bortoli Luca , Marsi Stefano , Marinello Francesco , Carrato Sergio , Ramponi Giovanni , Gallina Paolo
Published: May 2022

Phytosanitary treatment is one of the most critical operations in vineyard management. Ideally, the spraying system should treat only the canopy, avoiding drift, leakage and wasting of product where leaves are not present: variable rate distribution can be a successful approach, allowing the minimization of losses and improving economic as well as environmental performances. The target of this paper is to realize a smart control system to spray phytosanitary treatment just on the leaves, optimizing the overall costs/benefits ratio. Four different optical-based systems for leaf recognition are analyzed, and their performances are compared using a synthetic vineyard model. In the paper, we consider the usage of three well-established methods (infrared barriers, LIDAR 2-D and stereoscopic cameras), and we compare them with an innovative low-cost real-time solution based on a suitable computer vision algorithm that uses a simple monocular camera as input. The proposed algorithm, analyzing the sequence of input frames and exploiting the parallax property, estimates the depth map and eventually reconstructs the profile of the vineyard’s row to be treated. Finally, the performances obtained by the new method are evaluated and compared with those of the other methods on a well-controlled artificial environment resembling an actual vineyard setup while traveling at standard tractor forward speed.
Oral D-Aspartate Treatment Improves Sperm Fertility in Both Young and Adult B6N Mice
Authors: Raspa Marcello , Paoletti Renata , Peltier Manon , Majjouti Mohamed , Protti Michele , Mercolini Laura , Mahabir Esther , Scavizzi Ferdinando
Published: May 2022

D-Aspartate (D-Asp) treatment improved the fertility of young male C57BL/6N mice in vivo revealing a direct role on capacitation, acrosome reaction, and fertility in vitro in young males only. We investigated whether the positive effect of D-Asp on fertility could be extended to adult males and evaluated the efficacy of a 2- or 4-week-treatment in vivo. Therefore, 20 mM sodium D-Asp was supplied in drinking water to males of different ages so that they were 9 or 16 weeks old at the end of the experiments. After sperm freezing, the in vitro fertilization (IVF) rate, the birth rate, hormone levels (luteinizing hormone (LH), epitestosterone, and testosterone), the sperm quality (morphology, abnormalities, motility, and velocity), the capacitation rate, and the acrosome reaction were investigated. Oral D-Asp treatment improves the fertilizing capability in mice regardless of the age of the animals. Importantly, a short D-Asp treatment of 2 weeks in young males elevates sperm parameters to the levels of untreated adult animals. In vivo, D-Asp treatment highly improves sperm quality but not sperm concentration. Therefore, D-Asp plays a beneficial role in mouse male fertility and may be highly relevant for cryorepositories to improve mouse sperm biobanking.
Adaptability Challenges for Organic Broiler Chickens: A Commentary
Authors: Guarino Amato Monica , Castellini Cesare
Published: May 2022

As organic and conventional poultry production increased in the last decade, so did consumers’ concerns, sustainability requirements, and animal welfare as well as health issues. According to Reg. EU 848/2008 on organic production, poultry must be adapted to organic outdoor systems and cope with all the regulatory constraints in terms of nutrition, health, and welfare. Adaptability must take into account the above challenges, constraints, and concerns. Chicken adaptability should not only mean being able to use pasture and outdoor areas, but also mean being able to overcome, or be resilient to, the challenges of organic farming without compromising welfare, performance, and product quality. This commentary identifies solutions to the new challenges that organic poultry chains must face in future productive scenarios, detects consumer viewpoints to provide a perspective on organic poultry production, and summarizes as well as defines chicken adaptability to organic production, assessing the main factors of chicken adaptability.
No Evidence for Contagious Yawning in Juvenile Ravens (Corvus corax): An Observational Study
Authors: Gallup Andrew C. , Schild Anja B. , Ühlein Markus A. , Bugnyar Thomas , Massen Jorg J. M.
Published: May 2022

The overt and reflexive matching of behaviors among conspecifics has been observed in a growing number of social vertebrates, including avian species. In general, behavioral contagion—such as the spread of yawning—may serve important functions in group synchronization and vigilance behavior. Here, we performed an exploratory study to investigate yawn contagion among 10 captive juvenile ravens (Corvus corax), across two groups. Using observational methods, we also examined the contagiousness of three other distinct behaviors: stretching, scratching, and shaking. A total of 44 20 min observations were made across both groups, including 28 in the morning and 16 in the afternoon. The time and occurrence of all the behaviors from each bird were coded, and the temporal pattern of each behavior across both groups was then analyzed to assess the degree of social contagion. Overall, we found no evidence for contagious yawning, stretching, scratching, or shaking. However, yawns were relatively infrequent per observation (0.052 ± 0.076 yawns/bird) and thus experimental methods should be used to support this finding.
Pathological Findings in African Pygmy Hedgehogs Admitted into a Portuguese Rehabilitation Center
Authors: Silva Gabriela Fernandes , Rêma Alexandra , Teixeira Sílvia , Pires Maria dos Anjos , Taulescu Marian , Amorim Irina
Published: May 2022

Most of the pathologies that affect hedgehogs are diagnosed postmortem; thus, it is essential to share knowledge between clinicians and pathologists in order to recognize predispositions to diseases and to establish adequate diagnostic and therapeutic plans. This study aimed to describe the most relevant postmortem pathological conditions in a group of six rescued African pygmy hedgehogs, performed over a period of four months. Hedgehogs were submitted to necropsy examinations and subsequent histopathological analyses. Microscopically, all the studied hedgehogs revealed alterations in one or more organ systems. Although a significant and diverse number of pathological conditions were obtained, this study focused on less common or more relevant pathologies found in African pygmy hedgehogs—namely, wobbly hedgehog syndrome, squamous cell carcinoma and mast cell tumors. Furthermore, this study constitutes the first report of Mycobacterium spp. in hedgehogs in Portugal, the second report of follicular thyroid carcinoma in an African pygmy hedgehog, the description of a lipoid pneumonia for the first time in this species and a lung adenocarcinoma—a pathology rarely reported in African pygmy hedgehogs.
Morphological Stasis in Time? A Triatoma brasiliensis brasiliensis Study Using Geometric Morphometrics in the Long Run
Authors: Paschoaletto Letícia , Dale Carolina , Lima-Neiva Vanessa , Carbajal-de-la-Fuente Ana Laura , de Oliveira Jader , Benítez Hugo A. , Costa Jane
Published: May 2022

Triatoma brasiliensis brasiliensis Neiva, 1911 is one of the most important vectors of Chagas disease in the Brazilian semiarid regions in the north-east. The risk imposed by T. b. brasiliensis to the human populations, due to frequent invasions and/or colonization of the domiciles, demands constant monitoring and control actions as well as an understanding of its evolutionary process. In this context, the following research studies the pattern of shape adaptation over time using a large dataset from 102 years of specimen collections in order to identify the morphological plasticity of this vector in Brazil. This dataset was analyzed using geometric morphometrics tools and the timescale was divided into eight different groups, containing specimens from 1912 to 2014. Geometric morphometrics analysis showed an interesting morphological stasis in the wing shape of T. b. brasiliensis, which allowed us to understand the high capacity of adaptation to changes in climate condition through time, and the invasive status which Triatoma species have around the world. Moreover, these results showed novel findings as an interesting phenotypic pattern, with no modifications in more than 100 years, leading us to understand the shape evolution in Triatominae as a vector species of diseases.
Sulforaphane Enhanced Proliferation of Porcine Satellite Cells via Epigenetic Augmentation of SMAD7
Authors: Zhang Rui , Neuhoff Christiane , Yang Qin , Cinar Mehmet U. , Uddin Muhammad J. , Tholen Ernst , Schellander Karl , Tesfaye Dawit
Published: May 2022

Satellite cells take an indispensable place in skeletal muscle regeneration, maintenance, and growth. However, only limited works have investigated effects of dietary compounds on the proliferation of porcine satellite cells (PSCs) and related mechanisms. Sulforaphane (SFN) at multiple levels was applied to PSCs. The PSCs’ viability and HDAC activity were measured with a WST-1 cell proliferation kit and Color-de-Lys® HDAC colorimetric activity assay kit. Gene expression and epigenetics modification were tested with qRT-PCR, Western blot, bisulfite sequencing, and ChIP-qPCR. This study found that SFN enhanced PSC proliferation and altered mRNA expression levels of myogenic regulatory factors. In addition, SFN inhibited histone deacetylase (HDAC) activity, disturbed mRNA levels of HDAC family members, and elevated acetylated histone H3 and H4 abundance in PSCs. Furthermore, both mRNA and protein levels of the Smad family member 7 (SMAD7) in PSCs were upregulated after SFN treatment. Finally, it was found that SFN increased the acetylation level of histone H4 in the SMAD7 promoter, decreased the expression of microRNAs, including ssc-miR-15a, ssc-miR-15b, ssc-miR-92a, ssc-miR-17-5p, ssc-miR-20a-5p, and ssc-miR-106a, targeting SMAD7, but did not impact on the SMAD7 promoter’s methylation status in PSCs. In summary, SFN was found to boost PSC proliferation and epigenetically increase porcine SMAD7 expression, which indicates a potential application of SFN in modulation of skeletal muscle growth.
The Potential of α-Mangostin from Garcinia mangostana as an Effective Antimicrobial Agent—A Systematic Review and Meta-Analysis
Authors: Sultan Omer Sheriff , Kantilal Haresh Kumar , Khoo Suan Phaik , Davamani Amalraj Fabian , Eusufzai Sumaiya Zabin , Rashid Farah , Jamayet Nafij Bin , Soh Jue Ann , Tan Yen Yee , Alam Mohammad Khursheed
Published: May 2022

This systematic review aims to evaluate the antimicrobial activity of α-mangostin derived from Garcinia mangostana against different microbes. A literature search was performed using PubMed and Science Direct until March 2022. The research question was developed based on a PICO (Population, Intervention, Control and Outcomes) model. In this study, the population of interest was microbes, α-mangostin extracted from Garcinia mangostana was used as exposure while antibiotics were used as control, followed by the outcome which is determined by the antimicrobial activity of α-mangostin against studied microbes. Two reviewers independently performed the comprehensive literature search following the predetermined inclusion and exclusion criteria. A methodological quality assessment was carried out using a scoring protocol and the risk of bias in the studies was analyzed. Reward screening was performed among the selected articles to perform a meta-analysis based on the pre-determined criteria. Case groups where α-mangostin extracted from Garcinia mangostana was incorporated were compared to groups using different antibiotics or antiseptic agents (control) to evaluate their effectiveness. A total of 30 studies were included; they were heterogeneous in their study design and the risk of bias was moderate. The results showed a reduction in microbial counts after the incorporation of α-mangostin, which resulted in better disinfection and effectiveness against multiple microbes. Additionally, the meta-analysis result revealed no significant difference (p > 0.05) in their effectiveness when α-mangostin was compared to commercially available antibiotics. α-mangostin worked effectively against the tested microbes and was shown to have inhibitory effects on microbes with antibiotic resistance.
Biological Evaluation of Avocado Residues as a Potential Source of Bioactive Compounds
Authors: Rojas-García Alejandro , Fuentes Eduardo , Cádiz-Gurrea María de la Luz , Rodriguez Lyanne , Villegas-Aguilar María del Carmen , Palomo Iván , Arráez-Román David , Segura-Carretero Antonio
Published: May 2022

Avocado seed and peel are the main by-products from avocado industrialisation, and account for nearly 30% of fruit weight. Although they are usually discarded, their high phenolic content has been deeply associated with several nutritional and functional benefits. Thus, for a comprehensive analytical evaluation of both semi-industrial extracts, various steps have been developed: tentative characterisation and quantification of the phenolic composition using HPLC-ESI-qTOF-MS, determination of TPC and antioxidant activity by Folin–Ciocalteu, FRAP, TEAC and ORAC methods, evaluation of scavenging capacity against different ROS and measurement of the enzymatic inhibitory potential against potentially harmful enzymes. Finally, their bioactive potential was tested in a human platelet model where antiaggregatory activity was measured. Hence, 48 different compounds were identified, where flavonoids and procyanidins were the most representative groups. The higher TPC was found in avocado peel extract (190 ± 3 mg/g), which showed more antioxidant power and more capacity to decrease ROS generation than seed extract (60 ± 2 mg/g). In addition, both extracts showed enzymatic inhibition, especially against hyaluronidase, xanthine oxidase and acetylcholinesterase. Lastly, avocado peel was proven to inhibit platelet aggregation with significant results at 1, 0.75 and 0.5 mg/mL, where the extract showed reducing effects on agonists’ expression such as p-selectin or GPIIb/IIIa complex. These results demonstrate that both semi-industrial extracts—above all, avocado peel—have an interesting potential to be exploited as a natural by-product with antioxidant properties with multiple applications for the prevention of different pathologies.
High-Risk HPV with Multiple Infections Promotes CYP2E1, Lipoperoxidation and Pro-Inflammatory Cytokines in Semen of Asymptomatic Infertile Men
Authors: Pérez-Soto Elvia , Medel-Flores María Olivia , Fernández-Martínez Eduardo , Oros-Pantoja Rigoberto , Miranda-Covarrubias José Cruz , Sánchez-Monroy Virginia
Published: May 2022

High-risk human papillomavirus (HR-HPV) infection, followed by chronic inflammation and oxidative stress, is a major risk factor of male infertility. In this study, we explored the potential impact of high-risk (HR) HPV genotypes in single infection (SI) and multiple infections (MI) that promote CYP2E1 expression, oxidative damage and pro-inflammatory cytokines, possibly contributing to sperm damage and male infertility. Semen samples from 101 infertile military men were studied. We analyzed seminal parameters, namely, HPV genotyping, cytochrome P450 2E1 (CYP2E1), oxidative stress biomarkers (total antioxidant capacity (TAC), catalase (CAT) and superoxide dismutase (SOD)), lipid peroxidation (LPO), 8-hydroxiguanosine (8-OHdG) and pro-inflammatory cytokines (IFN-γ, IL-1β, IL-4, IL-6 and IL-8). Eighty-one men (80.2%, 81/101) were positive for HPV infection, and MI-HR-HPV was higher than SI-HR-HPV (63% vs. 37%). HPV-52 was the most frequently detected type (18.5%), followed by HPV-33 (11.1%), and the most frequent combination of genotypes detected was HPV-33,52 (11.1%), followed by HPV-18,31 (6.2%). The group with infected samples presented lower normal morphology and antioxidant levels compared to non-infected samples. In concordance, the infected group showed high levels of LPO, IFN-γ, IL-1β, IL-4 and IL-6 and downregulation of CAT and SOD enzymes. Interestingly, changes in motility B, low levels of TAC, overexpression of CYP2E1, LPO and IL-8 levels were higher in MI-HR-HPV than SI-HR-HPV, suggesting that HPV infection promotes a chronic inflammatory process and a toxic and oxidative microenvironment, which increases with MI-HPV infections.
Phytochemical Screening, Antioxidant and Antifungal Activities of Aconitum chasmanthum Stapf ex Holmes Wild Rhizome Extracts
Authors: Rafiq Shah , Wagay Nasir Aziz , Elansary Hosam O. , Malik Mansoor Ahmad , Bhat Irshad Ahmad , Kaloo Zahoor Ahmad , Hadi Abdul , Alataway Abed , Dewidar Ahmed Z. , El-Sabrout Ahmed M. , Yessoufou Kowiyou , Mahmoud Eman A.
Published: May 2022

Aconitum chasmanthum Stapf ex Holmes, an essential and critically endangered medicinal plant from Kashmir Himalayas, was studied for its antioxidant and antifungal properties. The shade-dried powdered rhizome was extracted sequentially with hexane, ethyl acetate, and methanol. These subsequent fractions were evaluated for total phenolic content (TPC); total flavonoid content (TFC); antioxidant assays, such as 1,1-diphenyl 1-2-picryl-hydrazyl (DPPH); ferric-reducing antioxidant power (FRAP); superoxide radical scavenging (SOR); hydroxyl radical scavenging (OH) and antifungal activity using the poisoned food technique. Highest TPC (5.26 ± 0.01 mg/g) and TFC (2.92 ± 0.04 mg/g) were reported from methanolic extracts. The highest values of radical scavenging activities were also observed in methanolic extracts with IC50 values of 163.71 ± 2.69 μg/mL in DPPH, 173.69 ± 4.91 μg/mL in SOR and 159.64 ± 2.43 μg/mL in OH. The chemical profile of ethyl acetate extract was tested using HR-LCMS. Methanolic extracts also showed a promising inhibition against Aspergillus niger (66.18 ± 1.03), Aspergillus flavus (78.91 ± 1.19) and Penicillium notatum (83.14 ± 0.97) at a 15% culture filtrate concentration with minimum inhibitory concentration (MIC) values of 230 μg/mL, 200 μg/mL and 190 μg/mL, respectively. Overall, the methanolic fractions showed significant biological potential, and its pure isolates might be used to construct a potential new medicinal source.
Reactive Sulfur Compounds in the Fight against COVID-19
Authors: Iciek Małgorzata , Bilska-Wilkosz Anna , Kozdrowicki Michał , Górny Magdalena
Published: May 2022

The SARS-CoV-2 coronavirus pandemic outbreak in 2019 resulted in the need to search for an effective and safe strategy for treating infected patients, relieving symptoms, and preventing severe disease. SARS-CoV-2 is an RNA virus that can cause acute respiratory failure and thrombosis, as well as impair circulatory system function. Permanent damage to the heart muscle or other cardiovascular disorders may occur during or after the infection. The severe course of the disease is associated with the release of large amounts of pro-inflammatory cytokines. Due to their documented anti-inflammatory, antioxidant, and antiviral effects, reactive sulfur compounds, including hydrogen sulfide (H2S), lipoic acid (LA), N-acetylcysteine (NAC), glutathione (GSH), and some other lesser-known sulfur compounds, have attracted the interest of scientists for the treatment and prevention of the adverse effects of diseases caused by SARS-CoV-2. This article reviews current knowledge about various endogenous or exogenous reactive sulfur compounds and discusses the possibility, or in some cases the results, of their use in the treatment or prophylaxis of COVID-19.
Phlorotannins of the Brown Algae Sargassum vulgare from the Mediterranean Sea Coast
Authors: Chouh Amina , Nouadri Tahar , Catarino Marcelo D. , Silva Artur M. S. , Cardoso Susana M.
Published: May 2022

Brown seaweeds are a good source of bioactive compounds, particularly of phlorotannins, which may exert a wide spectrum of pharmacological properties. In the present study, phlorotannins of S. vulgare were extracted using a 70% acetone solution and the crude extract was further purified through liquid–liquid partition, giving rise to n-hexane, ethyl acetate and aqueous residue fractions. The crude extract and the purified fractions were evaluated for potential antioxidant abilities as well as for inhibitory potential towards the digestive enzymes α-amylase and pancreatic lipase, and anti-inflammatory potential through the hindering of albumin denaturation. Overall, the ethyl acetate fraction was the richest in phlorotannins (9.4 ± 0.03 mg PGE/g) and was also the most promising regarding the tested bioactive properties. Of note, its inhibitory potential towards α-amylase was about nine times that of the commercial drug acarbose and its inhibitory activity against high temperature-induced protein denaturation was superior to that of the non-steroidal drug ketoprofen. According to UHPLC-DAD-ESI-MS/MS analysis, this fraction contained a range of phlorotannins with at least six units of phloroglucinol, including dibenzodioxine-1,3,6,8-tetraol, fuhalol, pentaphlorethol, fucopentaphlorethol and dihydroxypentafuhalol, in addition to several less common phlorotannin sulfate derivatives.
A Review of Optical Neural Networks
Authors: Zhang Danni , Tan Zhongwei
Published: May 2022

With the continuous miniaturization of conventional integrated circuits, obstacles such as excessive cost, increased resistance to electronic motion, and increased energy consumption are gradually slowing down the development of electrical computing and constraining the application of deep learning. Optical neuromorphic computing presents various opportunities and challenges compared with the realm of electronics. Algorithms running on optical hardware have the potential to meet the growing computational demands of deep learning and artificial intelligence. Here, we review the development of optical neural networks and compare various research proposals. We focus on fiber-based neural networks. Finally, we describe some new research directions and challenges.
Effects of Hydroxypropyl Methylcellulose (HPMC) on the Reinforcement of Sand by Microbial-Induced Calcium Carbonate Precipitation (MICP)
Authors: Zhu Wanyi , Yuan Mengnan , He Fanmin , Zhao Yang , Xiao Zhiyang , Wang Qian , Meng Fanyou , Tang Qiang
Published: May 2022

Microbial-induced calcium carbonate precipitation (MICP) is a new technology used for reinforcing soils through microbial mineralization. However, the existing MICP treatment technology is more suiTable for deeper soils due to its high permeability. In this study, HPMC, a cohesive material combined with Sporosarcina pasteurii-induced calcium carbonate precipitation was used to improve the surface layer of the soil. It was also tested in different contents of bacterial solutions and cementation solutions and with a different number of MICP treatments, and was analyzed and discussed by measuring the surface layer strength, calcium carbonate content generated in the crust, rainfall erosion resistance, wind erosion resistance, and ammonia retention rate of the specimens. The microstructure of the samples was investigated by XRD and SEM. It was shown that the addition of HPMC and increasing the number of MICP treatments were effective in the increase in the calcium carbonate content in the surface crust, but had no effect on the total amount of induced calcium carbonate. The combination of HPMC addition and MICP technology can effectively reduce rainwater scour loss and wind erosion loss, and increase its rainfall erosion resistance and wind erosion resistance. Rainfall losses were reduced by up to 30% in specimens treated with HPMC for MICP technology. When the wind speed was 12 m/s, the maximum mass loss rate of the specimens treated with HPMC for MICP was only 0.828%. The addition of HPMC can effectively improve the ammonia absorption rate and reduce the release of ammonia in the process of MICP technology, which is of great significance for environmental protection. The microstructure showed that the addition of HPMC and the increase in the number of treatments using MICP technology can make the surface structure of the specimens more compact, and the calcium carbonate can more effectively fill the pores and cement the soil particles, while the addition of HPMC may not change the calcium carbonate crystal type.
Balancing Data through Data Augmentation Improves the Generality of Transfer Learning for Diabetic Retinopathy Classification
Authors: Mungloo-Dilmohamud Zahra , Heenaye-Mamode Khan Maleika , Jhumka Khadiime , Beedassy Balkrish N. , Mungloo Noorshad Z. , Peña-Reyes Carlos
Published: May 2022

The incidence of diabetes in Mauritius is amongst the highest in the world. Diabetic retinopathy (DR), a complication resulting from the disease, can lead to blindness if not detected early. The aim of this work was to investigate the use of transfer learning and data augmentation for the classification of fundus images into five different stages of diabetic retinopathy. The five stages are No DR, Mild nonproliferative DR, Moderate nonproliferative DR, Severe nonproliferative DR and Proliferative. To this end, deep transfer learning and three pre-trained models, VGG16, ResNet50 and DenseNet169, were used to classify the APTOS dataset. The preliminary experiments resulted in low training and validation accuracies, and hence, the APTOS dataset was augmented while ensuring a balance between the five classes. This dataset was then used to train the three models, and the best three models were used to classify a blind Mauritian test datum. We found that the ResNet50 model produced the best results out of the three models and also achieved very good accuracies for the five classes. The classification of class-4 Mauritian fundus images, severe cases, produced some unexpected results, with some images being classified as mild, and therefore needs to be further investigated.
Weak Signal Detection Based on Combination of Sparse Representation and Singular Value Decomposition
Authors: Ma Huijie , Li Shunming , Li Xianglian , Lu Jiantao
Published: May 2022

Due to the inevitable acquisition system noise and strong background noise, it is often difficult to detect the features of weak signals. To solve this problem, sparse representation can effectively extract useful information according to the sparse characteristics of signals. However, sparse representation is less effective against non-Gaussian white noise. Therefore, a novel SRSVD method combining sparse representation and singular value decomposition is proposed to further improve the denoising performance of the algorithm. All the signal components highly matched with the dictionary are extracted by sparse representation, and then each component of singular value decomposition is weighted by the evaluation index, PMI, which can indicate the component with useful information in the signal, so that the signal denoising performance of the algorithm is greatly improved. The performance of the proposed method is verified by the processing of weak signals in the circuit and early fault signals of bearings. The results show that SRSVD can successfully suppress noise interference. Compared with other existing methods, SRSVD has better denoising performance.
Task-Oriented Motion Planning of a Space Manipulator under Multiple Constraints
Authors: Liang Changchun , Pan Dong , Chen Gang , Xin Pengfei , Zhang Xiaodong
Published: May 2022

During task execution by a space manipulator, many factors need to be considered, such as joint motion range, external environment interference, running speed and task time. Studying the motion planning strategy under multi-constraint conditions is important for optimizing the task flow of the manipulator and improving the planning autonomy. Aiming at this, this paper proposes a method based on a hierarchical task network which has the ability to connect non-adjacent nodes of topology when generating the best path; it also carries out the control simulation of traditional path planning of a manipulator for typical tasks and the latter two working conditions using an optimal task planning method. The results show that this method is effective for realizing the Cartesian spatial task planning of a manipulator under multiple constraints and has important on-orbit application significance for improving the continuous autonomy of task completion.
Pedestrian Localization in a Video Sequence Using Motion Detection and Active Shape Models
Authors: Antonio Velázquez Juan Alberto , Romero Huertas Marcelo , Alejo Eleuterio Roberto , Granda Gutiérrez Everardo Efrén , Del Razo López Federico , Rendón Lara Eréndira
Published: May 2022

There is increasing interest in video object detection for many situations, such as industrial processes, surveillance systems, and nature exploration. In this work, we were concerned with the detection of pedestrians in video sequences. The aim was to deal with issues associated with the background, scale, contrast, or resolution of the video frames, which cause inaccurate detection of pedestrians. The proposed method was based on the combination of two techniques: motion detection by background subtraction (MDBS) and active shape models (ASM). The MDBS technique aids in the identification of a moving region of interest in the video sequence, which potentially includes a pedestrian; then, the ASM algorithm actively finds and adjusts the silhouette of the pedestrian. We tested the proposed MDBS + ASM method with video sequences from open repositories, and the results were favorable in scenes where pedestrians were in a well-illuminated environment. The mean fit error was up to 4.5 pixels. In contrast, in scenes where reflections, occlusions, or pronounced movement are present, the identification was slightly affected; the mean fit error was 8.3 pixels in the worst case. The main contribution of this work was exploring the potential of the combination of MDBS and ASM for performance improvements in the contour-based detection of a moving pedestrian walking in a controlled environment. We present a straightforward method based on classical algorithms which have been proven effective for pedestrian detection. In addition, since we were looking for a practical process that could work in real-time applications (for example, closed-circuit television video or surveillance systems), we established our approach with simple techniques.
On the Sum of α-μ/Inverse Gamma Variates with Applications to Diversity Receivers
Authors: Cheng Weijun , Ma Tengfei , Wang Gang
Published: May 2022

How to model shadow fading by applying the inverse gamma (IGA) distribution has recently gained widespread attention in wireless transmissions. However, the sum of α-μ/IGA variates, and its applications under independent and/or correlated scenarios, have yet to be addressed in open research works. Hence, this paper provides a systematic investigation of the α-μ/IGA model. First, we derive the expressions of the fundamental statistics of the univariate and bivariate α-μ/IGA models including the probability density function, cumulative distribution function, and moment generating function, and propose a mixture α-μ model to approximate the α-μ/IGA model. Then, according to the above statistical expressions, the statistical properties of the sum of α-μ/IGA variates are obtained and employed in the maximal ratio combining receivers. Third, the novel exact and approximated expressions of some performance metrics of interest are also derived, for instance, the average bit/symbol error probability, the outage probability, the average channel capacity, and the effective rate. Moreover, to prove the asymptotic properties of the performance metrics at the high signal-to-noise regions, some examples are performed. Finally, we explore numerical analysis and simulations to demonstrate the accuracy of the theoretical expressions under the different channel and system parameters. These results provide some significant insights into the reliability design and deployment of some conventional and emerging wireless communication applications.
Methodology for Phytoplankton Taxonomic Group Identification towards the Development of a Lab-on-a-Chip
Authors: Carvalho Denise A. M. , Pinto Vânia C. , Sousa Paulo J. , Magalhães Vitor H. , Fernández Emilio , Gomes Pedro A. , Minas Graça , Gonçalves Luís M.
Published: May 2022

This paper presents the absorbance and fluorescence optical properties of various phytoplankton species, looking to achieve an accurate method to detect and identify a number of phytoplankton taxonomic groups. The methodology to select the excitation and detection wavelengths that results in superior identification of phytoplankton is reported. The macroscopic analyses and the implemented methodology are the base for designing a lab-on-a-chip device for a phytoplankton group identification, based on cell analysis with multi-wavelength lighting excitation, aiming for a cheap and portable platform. With such methodology in a lab-on-a-chip device, the analysis of the phytoplankton cells’ optical properties, e.g., fluorescence, diffraction, absorption and reflection, will be possible. This device will offer, in the future, a platform for continuous, autonomous and in situ underwater measurements, in opposition to the conventional methodology. A proof-of-concept device with LED light excitation at 450 nm and a detection photodiode at 680 nm was fabricated. This device was able to quantify the concentration of the phytoplankton chlorophyll a. A lock-in amplifier electronic circuit was developed and integrated in a portable and low-cost sensor, featuring continuous, autonomous and in situ underwater measurements. This device has a detection limit of 0.01 µ/L of chlorophyll a, in a range up to 300 µg/L, with a linear voltage output with chlorophyll concentration.
A Novel Method for Generating H2 by Activation of the μAl-Water System Using Aluminum Nanoparticles
Authors: Kader Mohammad S. , Zeng Wenhui , Johnston Elisabeth , Buckner Steven W. , Jelliss Paul A.
Published: May 2022

A method is described for activation of the reaction of room temperature water with micron-scale aluminum particles (μAl) by the addition of poly(epoxyhexane)-capped aluminum nanoparticles (Al NPs). By themselves, Al NPs react vigorously and completely with water at ambient temperatures to produce H2. While pure μAl particles are unreactive toward water, mixtures of the μAl particles comprising 10 to 90% (by mass) of Al NPs, demonstrated appreciable hydrolytic activation. This activation is attributed to the reaction of the Al NPs present with water to produce a basic solution. Speciation modelling, pH studies, and powder X-ray diffraction analysis of the hydrolysis product confirm that the pH change is the key driver for the activation of μAl rather than residual heat from the exothermicity of Al NP hydrolysis. A mechanism is proposed by which the nonreactive aluminum oxide layer of the μAl is eroded under basic conditions. Mixtures 10% by mass of Al NPs can be used to produce the optimal quantity of H2.
Energy-Efficient Driving for Adaptive Traffic Signal Control Environment via Explainable Reinforcement Learning
Authors: Jiang Xia , Zhang Jian , Wang Bo
Published: May 2022

Energy-efficient driving systems can effectively reduce energy consumption during vehicle operation. Most of the existing studies focus on the driving strategies in a fixed signal timing environment, whereas the standardized Signal Phase and Timing (SPaT) data can help the vehicle make the optimal decisions. However, with the development of artificial intelligence and communication techniques, the conventional fixed timing methods are gradually replaced by adaptive traffic signal control (ATSC) approaches. The previous studies utilized SPaT information that cannot be applied directly in the environment with ATSC. Thus, a framework is proposed to implement energy-efficient driving in the ATSC environment, while the ATSC is realized by the value-based reinforcement learning algorithm. After giving the optimal control model, the framework draws upon the Markov Decision Process (MDP) to make an approximation to the optimal control problem. The state sharing mechanism allows the vehicle to obtain the state information of the traffic signal agents. The reward function in MDP considers energy consumption, traffic mobility, and driving comfort. With the support of traffic simulation software SUMO, the vehicle agent is trained by Proximal Policy Optimization (PPO) algorithm, which enables the vehicle to select actions from continuous action space. The simulation results show that the energy consumption of the controlled vehicle can be reduced by 31.73%~45.90% with a different extent of mobility sacrifice compared with the manual driving model. Besides, we developed a module based on SHapley Additive exPlanations (SHAP) to explain the decision process in each timestep of the vehicle. That can make the strategy more reliable and credible.
Multi-Head TrajectoryCNN: A New Multi-Task Framework for Action Prediction
Authors: Liu Xiaoli , Yin Jianqin
Published: May 2022

Action prediction is an important task in human activity analysis, which has many practical applications, such as human–robot interactions and autonomous driving. Action prediction often comprises two subtasks: action semantic prediction and future human motion prediction. Most of the existing works treat these subtasks separately, ignoring the correlations, leading to unsatisfying performance. By contrast, we jointly model these tasks and improve human motion predictions utilizing their action semantics. In terms of methodology, we propose a novel multi-task framework (Multi-head TrajectoryCNN) to simultaneously predict the action semantics and human motion of future human movements. Specifically, we first extract a general spatiotemporal representation of partial observations via two regression blocks. Then, we propose a regression head and a classification head for predicting future human motion and action semantics of human motion, respectively. For the regression head, another two stacked regression blocks and two convolutional layers are applied to predict future poses from the general representation learning. For the classification head, we propose a classification block and stack two regression blocks to predict action semantics from the general representation. In this way, the regression and classification heads are incorporated into a unified framework. During the backward propagation of the network, the human motion prediction and the semantic prediction may be enhanced by each other. NTU RGB+D is a widely used large-scale dataset for action recognition, which was collected by 40 different subjects from three views. Based on the official protocols, we use the skeletal modality and process action sequences with fixed lengths for the evaluation of our action prediction task. Experiments on NTU RGB+D show our model’s state-of-the-art performance. Furthermore, the experimental results also show that semantic information is of great help in predicting future human motion.
A Fast Finite Element Simulation Method of Phased Array Ultrasonic Testing and Its Application in Sleeve Fillet Weld Inspection
Authors: Wu Yuxuan , Pei Cuixiang , Zhang Hongbo , Liu Yan , Jia Pengjun
Published: May 2022

Numerical simulation can provide quantitative information on ultrasonic beam propagation and plays an important role in analyzing its detection ability and in optimizing the corresponding parameters of the phased array ultrasonic testing (PAUT). In this paper, a fast finite element simulation method of PAUT is developed using an improved explicit integration algorithm and a non-zero element compressed storage method. The new method is applied for the simulation of PAUT of a type-B sleeve weld, and compared with the commercial finite element software and experiment results. We found that the computation time and memory consumption of the new method is only about a 15th and a 40th of the commercial finite element software, respectively.
Development of Radiator with Thermoplastic Polymer and Insert-Molded Aluminum Alloy Parts for Light-Emitting Diode Headlights
Authors: Chen Yenlung , Chang Juikun , Huang Chun , Chiu Changche , Lai Wei , Ye Zhiting , Han Pin
Published: May 2022

The increasing popularity of electric vehicles has increased the demand for lightweight auto parts. However, the excessive weight of traditional metal heat sinks has remained a concern. Metal has excellent thermal conductivity but low radiation efficiency. Conversely, thermoplastic polymers have excellent heat radiation efficiency but poor thermal conductivity. In this study, we propose a radiator constructed using thermoplastic polymer and insert-molded aluminum alloy parts to maintain the low junction temperature of light-emitting diodes (LEDs); the radiator’s weight is reduced through a combination of aluminum alloy and a thermally conductive polymer designed for automotive headlights. At an LED thermal load of 11.48 W, the measured temperature on the LED pad is 60.8 °C. The weight of the proposed radiator is 23.37% lighter than that of a pure metal radiator. When the lightweight radiator is used in high-power LED headlights, it effectively dissipates heat within a limited space.
Reportability Tool Design: Assessing Grouping Schemes for Strategic Decision Making in Maintenance Planning from a Stochastic Perspective
Authors: Viveros Pablo , Pantoja Nicolás Cárdenas , Kristjanpoller Fredy , Mena Rodrigo
Published: May 2022

In this article, we report on the design and implementation of a reportability tool using Microsoft Power BI embedded with Python script to assess opportunistic grouping schemes under a preventive maintenance policy. The reportability tool is based on specially developed indicators based on current maintenance standards for better implementation and considers a formerly developed grouping strategy with poor embedded performance indicators as an implementation case for the tool. Performance indicators were carefully developed considering a stochastic perspective when possible; this enables decisions to be influenced by risk assessment under a costs view. Reporting is focused on six maintenance sub-functions, enabling the decision maker to easily assess performance of any maintenance process, thereby improving the quality of decisions. The developed tool is a step forward for grouping (or any scheduling scheme) strategies due to its flexibility to be implemented in almost any case, enabling comparison between different grouping algorithms.
What Are Lake Beaches Made of? An Assessment of Plastic Beach Litter on the Shores of Como Bay (Italy)
Authors: Bellasi Arianna , Binda Gilberto , Boldrocchi Ginevra , Pozzi Andrea , Bettinetti Roberta
Published: May 2022

Plastic waste dispersion is a well-recognized environmental threat, despite continuous efforts towards improving waste disposal management over the last few decades. Plastic litter is known to strongly impact upon water bodies and shorelines, affecting the health of ecosystems and impacting upon the aesthetic value of sites. Moreover, plastic waste that is abandoned on beaches contributes towards different degradation processes that potentially lead to the formation of secondary microplastics (MPs), with likely cascade effects upon the whole ecosystem. In this view, this study aims to characterize the plastic beach litter found on the shores of the western basin of Como Lake (Italy) to better understand the origin of MPs in littoral sediments, including the recognition of object typologies and the chemical characterization of polymers using Fourier-transformed infrared analysis (FTIR). The results highlighted that the most abundant polymers on beaches are polypropylene (PP) and polyethylene (PE), representing 73% of the collected polymers. This confirms that floating, low-density polymers are more likely to accumulate on beaches. Moreover, almost 66% of litter is represented by commonly used manufactured items (disposable objects, packaging, and everyday items). This evidence, combined with the analysis of the main environmental features of the sampling sites (the main winds, distance to urban areas, and the presence of tributaries) indicate that abundance of beached litter is mainly linked to beach accessibility and the local winds. These results highlight that multiple factors affect the environmental fate of plastic litter and give insights into the assessment of secondary microplastics in beach sediments.
Dynamic Uncertainty Quantification and Risk Prediction Based on the Grey Mathematics and Outcrossing Theory
Authors: Wang Lei , Liu Jiaxiang
Published: May 2022

Embarked from the practical conditions of small samples in time-invariant and time-variant uncertainties, a complete non-probabilistic analysis procedure containing uncertainty quantification, uncertainty propagation, and reliability evaluation is presented in this paper. Firstly, the Grey systematic approach is proposed to determine the boundary laws of static intervals and dynamic interval processes. Through a combination of the policies of the second-order Taylor expansion and the smallest parametric interval set, the structural response histories via quantitative uncertainty results are further confirmed. Additionally, according to the first-passage idea from classical random process theory, the study on the time-dependent reliability measurement on the basis of the interval process model is carried out to achieve a more elaborate estimation for structural safety during its whole life cycle. A numerical example and one experimental application are eventually discussed for demonstration of the usage and reasonability of the methodology developed.