bluuebunny/crossref_metadata_2025 huggingface dataset:
Epithelial Mesenchymal Transition and Immune Response in Metaplastic Breast Carcinoma
Authors: González-Martínez Silvia , Pérez-Mies Belén , Pizarro David , Caniego-Casas Tamara , Cortés Javier , Palacios José
Published: July 2021

Metaplastic breast carcinoma (MBC) is a heterogeneous group of infrequent triple negative (TN) invasive carcinomas with poor prognosis. MBCs have a different clinical behavior from other types of triple negative breast cancer (TNBC), being more resistant to standard chemotherapy. MBCs are an example of tumors with activation of epithelial–mesenchymal transition (EMT). The mechanisms involved in EMT could be responsible for the increase in the infiltrative and metastatic capacity of MBCs and resistance to treatments. In addition, a relationship between EMT and the immune response has been seen in these tumors. In this sense, MBC differ from other TN tumors showing a lower number of tumor-infiltrating lymphocytes (TILS) and a higher percentage of tumor cells expressing programmed death-ligand 1 (PD-L1). A better understanding of the relationship between the immune system and EMT could provide new therapeutic approaches in MBC.
Filtering-Based Instance Selection Method for Overlapping Problem in Imbalanced Datasets
Authors: Rubbo Marcio , Silva Leandro A.
Published: July 2021

The overlapping problem occurs when a region of the dimensional data space is shared in a similar proportion by different classes. It has an impact on a classifier’s performance due to the difficulty in correctly separating the classes. Further, an imbalanced dataset consists of a situation in which one class has more instances than another, and this is another aspect that impacts a classifier’s performance. In general, these two problems are treated separately. On the other hand, Prototype Selection (PS) approaches are employed as strategies for selecting appropriate instances from a dataset by filtering redundant and noise data, which can cause misclassification performance. In this paper, we introduce Filtering-based Instance Selection (FIS), using as a base the Self-Organizing Maps Neural Network (SOM) and information entropy. In this sense, SOM is trained with a dataset, and, then, the instances of the training set are mapped to the nearest prototype (SOM neurons). An analysis with entropy is conducted in each prototype region. From a threshold, we propose three decision methods: filtering the majority class (H-FIS (High Filter IS)), the minority class (L-FIS (Low Filter IS)), and both classes (B-FIS). The experiments using artificial and real dataset showed that the methods proposed in combination with 1NN improved the accuracy, F-Score, and G-mean values when compared with the 1NN classifier without the filter methods. The FIS approach is also compatible with the approaches mentioned in the relevant literature.
An Empirical Assessment of Endpoint Detection and Response Systems against Advanced Persistent Threats Attack Vectors
Authors: Karantzas George , Patsakis Constantinos
Published: July 2021

Advanced persistent threats pose a significant challenge for blue teams as they apply various attacks over prolonged periods, impeding event correlation and their detection. In this work, we leverage various diverse attack scenarios to assess the efficacy of EDRs against detecting and preventing APTs. Our results indicate that there is still a lot of room for improvement as state-of-the-art EDRs fail to prevent and log the bulk of the attacks that are reported in this work. Additionally, we discuss methods to tamper with the telemetry providers of EDRs, allowing an adversary to perform a more stealth attack.
Risk Factors for Fungal Co-Infections in Critically Ill COVID-19 Patients, with a Focus on Immunosuppressants
Authors: Ezeokoli Obinna T. , Gcilitshana Onele , Pohl Carolina H.
Published: July 2021

Severe cases of coronavirus disease 2019 (COVID-19) managed in the intensive care unit are prone to complications, including secondary infections with opportunistic fungal pathogens. Systemic fungal co-infections in hospitalized COVID-19 patients may exacerbate COVID-19 disease severity, hamper treatment effectiveness and increase mortality. Here, we reiterate the role of fungal co-infections in exacerbating COVID-19 disease severity as well as highlight emerging trends related to fungal disease burden in COVID-19 patients. Furthermore, we provide perspectives on the risk factors for fungal co-infections in hospitalized COVID-19 patients and highlight the potential role of prolonged immunomodulatory treatments in driving fungal co-infections, including COVID-19-associated pulmonary aspergillosis (CAPA), COVID-19-associated candidiasis (CAC) and mucormycosis. We reiterate the need for early diagnosis of suspected COVID-19-associated systemic mycoses in the hospital setting.
RETRACTED: The Relationship between CEO Psychological Biases, Corporate Governance and Corporate Social Responsibility
Authors: Salhi Bassem
Published: July 2021

Despite that the relationship between corporate social responsibility activities and real estate operations seems relevant, only some studies have been conducted to explore the reasons that drive these activities in real estate companies. This work presents the relationship between CEO personality traits and corporate social responsibility (CSR) and shows whether corporate governance (CG) practices mitigate or enhance this relationship. This study uses a sample of 420 firm-year-observations using a sample of European real estate firms indexed on Stoxx Europe 600 Index from 2010 to 2019. To test the developed hypotheses, feasible generalized least square (FGLS) regression is applied. The results show that increased confidence in CEOs is an important factor in determining corporate incentives to undertake social responsibility activities. In addition, it has been shown that effective corporate governance practices lead significantly to moderate CEO behavior with regard to corporate social responsibility sharing. Since corporate governance can have a significant impact on CEOs’ behavior in relation to corporate social responsibility, the author recommends firms to improve corporate governance in listed European real estate companies.
Phosphate Cements Based on Calcined Dolomite: Influence of Calcination Temperature and Silica Addition
Authors: Vijan Cristina Andreea , Badanoiu Alina , Voicu Georgeta , Nicoara Adrian Ionut
Published: July 2021

The aim of this study is to assess the possibility of obtaining phosphate cements based on dolomite calcined at various temperatures with/without quartz sand addition. A lower calcination temperature of dolomite (1200 °C) determines a high increase in the system temperature when calcined dolomite is mixed with KH2PO4 (MKP) solution and also a rapid expansion of the paste. The increase in calcination temperature up to 1400 °C reduces the oxides reactivity; however, for lower dosages of MKP, the expansion phenomenon is still recorded. The increase in MKP dosage increases the compressive strength due to the formation of K-struvite. The mixing of dolomite with sand, followed by thermal treatment at 1200 °C, modifies its composition and reactivity; the compressive strength of phosphate cements obtained by mixing this solid precursor with MKP increases up to 28 days of curing. We assessed the nature of hydrates formed in the phosphate systems studied by X-ray diffraction in order to explain the hardening processes and the mechanical properties of these systems. The microstructure and elemental composition of hardened cement pastes were assessed by scanning electronic microscopy with energy-dispersive spectroscopy. The phosphate cements based on calcined magnesite or dolomite were used to immobilize an industrial hazardous waste with high chromium content. The partial substitution of calcined magnesite/dolomite with this waste determines an important decrease in compressive strengths. Nevertheless, the leaching tests confirm an adequate immobilization of chromium in some of the matrices studied (for a waste dosage corresponding to 0.5 wt % Cr).
A Critical Review for an Accurate Electrochemical Stability Window Measurement of Solid Polymer and Composite Electrolytes
Authors: Méry Adrien , Rousselot Steeve , Lepage David , Dollé Mickaël
Published: July 2021

All-solid-state lithium batteries (ASSLB) are very promising for the future development of next generation lithium battery systems due to their increased energy density and improved safety. ASSLB employing Solid Polymer Electrolytes (SPE) and Solid Composite Electrolytes (SCE) in particular have attracted significant attention. Among the several expected requirements for a battery system (high ionic conductivity, safety, mechanical stability), increasing the energy density and the cycle life relies on the electrochemical stability window of the SPE or SCE. Most published works target the importance of ionic conductivity (undoubtedly a crucial parameter) and often identify the Electrochemical Stability Window (ESW) of the electrolyte as a secondary parameter. In this review, we first present a summary of recent publications on SPE and SCE with a particular focus on the analysis of their electrochemical stability. The goal of the second part is to propose a review of optimized and improved electrochemical methods, leading to a better understanding and a better evaluation of the ESW of the SPE and the SCE which is, once again, a critical parameter for high stability and high performance ASSLB applications.
The Influence of the Cooling Bores on Crystal Orientation and Lattice Parameter in Single-Crystalline Cored Turbine Blades
Authors: Krawczyk Jacek , Bogdanowicz Włodzimierz , Sieniawski Jan
Published: July 2021

The areas located near the cooling bores of single-crystalline cored turbine blades made of nickel-based CMSX-4 superalloy were studied. The blades were solidified by the vertical Bridgman technique in the industrial ALD furnace. Longitudinal sections of the blades were studied by Scanning Electron Microscopy, X-ray diffraction topography, X-ray diffraction measurements of the γ′-phase lattice parameter a, and the α angle of the primary crystal orientation. The local changes in α were analyzed in relation to the changes of the dendrite’s growth direction near the cooling bores. It was found that in the area approximately 3 ÷ 4 mm wide around the cooling bores, changes of α and a, both in the blade root and in the airfoil occurred. The local temperature distribution near the cooling bores formed a curved macroscopic solidification front, which caused changes in the chemical composition and, consequently, changes in the a value in a range of 0.002 Å to 0.014 Å. The mechanism of alloying elements segregation by tips of the dendrites on the bent solidification front was proposed. The multi-scale analysis that allows determining a relation between processes proceed both on a millimeter-scale and a micrometric and nanometric scale, was applied in the studies.
Effect of Gold Nanoparticles and Silicon on the Bioactivity and Antibacterial Properties of Hydroxyapatite/Chitosan/Tricalcium Phosphate-Based Biomicroconcretes
Authors: Czechowska Joanna , Cichoń Ewelina , Belcarz Anna , Ślósarczyk Anna , Zima Aneta
Published: July 2021

Bioactive, chemically bonded bone substitutes with antibacterial properties are highly recommended for medical applications. In this study, biomicroconcretes, composed of silicon modified (Si-αTCP) or non-modified α-tricalcium phosphate (αTCP), as well as hybrid hydroxyapatite/chitosan granules non-modified and modified with gold nanoparticles (AuNPs), were designed. The developed biomicroconcretes were supposed to combine the dual functions of antibacterial activity and bone defect repair. The chemical and phase composition, microstructure, setting times, mechanical strength, and in vitro bioactive potential of the composites were examined. Furthermore, on the basis of the American Association of Textile Chemists and Colorists test (AATCC 100), adapted for chemically bonded materials, the antibacterial activity of the biomicroconcretes against S. epidermidis, E. coli, and S. aureus was evaluated. All biomicroconcretes were surgically handy and revealed good adhesion between the hybrid granules and calcium phosphate-based matrix. Furthermore, they possessed acceptable setting times and mechanical properties. It has been stated that materials containing AuNPs set faster and possess a slightly higher compressive strength (3.4 ± 0.7 MPa). The modification of αTCP with silicon led to a favorable decrease of the final setting time to 10 min. Furthermore, it has been shown that materials modified with AuNPs and silicon possessed an enhanced bioactivity. The antibacterial properties of all of the developed biomicroconcretes against the tested bacterial strains due to the presence of both chitosan and Au were confirmed. The material modified simultaneously with AuNPs and silicon seems to be the most promising candidate for further biological studies.
Topology Optimization of Passive Cell Traps
Authors: Wang Zhiqi , Guo Yuchen , Wadbro Eddie , Liu Zhenyu
Published: July 2021

This paper discusses a flexible design method of cell traps based on the topology optimization of fluidic flows. Being different from the traditional method, this method obtains the periodic layout of the cell traps according to the cell trapping requirements by proposing a topology optimization model. Additionally, it satisfies the cell trapping function by restricting the flow distribution while taking into account the overall energy dissipation of the flow field. The dependence on the experience of the designer is reduced when this method is used to design a cell trap with acceptable trapping performance. By comparing the influence of the changes of various parameters on the optimization results, the flexibility of the topology optimization method for cell trap structure optimization is verified. The capability of this design method is validated by several performed comparisons between the obtained layouts and optimized designs in the published literature.
Assessment of Foods Associated with Sodium and Potassium Intake in Japanese Youths Using the Brief-Type Self-Administered Diet History Questionnaire
Authors: Okuda Masayuki , Sasaki Satoshi
Published: July 2021

The identification of sodium and potassium intake in youths is an important step to preventing the increase of blood pressure in childhood. We examined food intake and estimated mineral intake using a brief-type self-administered diet history questionnaire (BDHQ) to test its validity as a comparison with urinary excretion in Japanese youths. The subjects were 5th and 8th graders (n = 2377), who completed the BDHQ and permitted the use of their overnight urine specimens. Sodium intake was poorly associated with sodium excretion (Rho = 0.048), and the coefficients of dietary potassium and a sodium-to-potassium molar ratio were 0.091–0.130. Higher soybean paste (miso) intake and pickles were significantly associated with higher sodium excretion (p ≤ 0.005). However, these foods were positively associated with potassium excretion (p = 0.002–0.012), and not associated with an excreted sodium-to-potassium ratio. Fruits and dairy products were positively associated (p ≤ 0.048), whereas beverages were negatively associated with potassium excretion (p ≤ 0.004). The association of the sodium-to-potassium ratio was opposite to that of potassium (p ≤ 0.001). The choice of foods, potassium, and the sodium-to-potassium ratio assessed using the BDHQ are available as part of health education for youths, but the assessment of sodium intake in population levels should be carefully conducted.
Design and Synthesis of Novel Thiazolo[5,4-d]pyrimidine Derivatives with High Affinity for Both the Adenosine A1 and A2A Receptors, and Efficacy in Animal Models of Depression
Authors: Varano Flavia , Catarzi Daniela , Vigiani Erica , Dal Ben Diego , Buccioni Michela , Marucci Gabriella , Di Cesare Mannelli Lorenzo , Lucarini Elena , Ghelardini Carla , Volpini Rosaria , Colotta Vittoria
Published: July 2021

New compounds with a 7-amino-2-arylmethyl-thiazolo[5,4-d]pyrimidine structure were synthesized and evaluated in vitro for their affinity and/or potency at the human (h) A1, hA2A, hA2B, and hA3 adenosine receptors (ARs). Several compounds (5, 8–10, 13, 18, 19) were characterized by nanomolar and subnanomolar binding affinities for the hA1 and the hA2A AR, respectively. Results of molecular docking studies supported the in vitro results. The 2-(2-fluorobenzyl)-5-(furan-2yl)-thiazolo[5,4-d]pyrimidin-7-amine derivative 18 (hA1 Ki = 1.9 nM; hA2A Ki = 0.06 nM) was evaluated for its antidepressant-like activity in in vivo studies, the forced swimming test (FST), the tail suspension test (TST), and the sucrose preference test (SPT) in mice, showing an effect comparable to that of the reference amitriptyline.
Immunopharmacology in Vernal Keratoconjunctivitis: Current and Future Perspectives
Authors: Chigbu DeGaulle I. , Labib Bisant A.
Published: July 2021

Vernal keratoconjunctivitis (VKC) is a complex and chronic, multifactorial Th2 cell-mediated chronic ocular surface inflammatory condition that typically affects predominantly male children in hot or warm climates. The primary symptom is intense ocular pruritus, often significant enough to affect activities of daily living. Clinical features differ from simple forms of allergic conjunctivitis in that they are more-or-less confined to the superior tarsus and limbus. There is also a risk of corneal involvement, which leads to irreversible vision loss in approximately 6% of patients. Right now, there is no standardized treatment protocol, and many of the currently available options are not effective in severe and recurrent cases. As such, it is imperative to understand this complex allergic immune response in order to identify future therapeutic targets. This review will focus on potential drug targets in VKC, with particular emphasis on immunomodulators and immunobiologic agents.
Innovating on Inhaled Bioequivalence: A Critical Analysis of the Current Limitations, Potential Solutions and Stakeholders of the Process
Authors: Gallegos-Catalán Jonattan , Warnken Zachary , Bahamondez-Canas Tania F. , Moraga-Espinoza Daniel
Published: July 2021

Orally inhaled drug products (OIDPs) are an important group of medicines traditionally used to treat pulmonary diseases. Over the past decade, this trend has broadened, increasing their use in other conditions such as diabetes, expanding the interest in this administration route. Thus, the bioequivalence of OIDPs is more important than ever, aiming to increase access to affordable, safe and effective medicines, which translates into better public health policies. However, regulatory agencies leading the bioequivalence process are still deciding the best approach for ensuring a proposed inhalable product is bioequivalent. This lack of agreement translates into less cost-effective strategies to determine bioequivalence, discouraging innovation in this field. The Next-Generation Impactor (NGI) is an example of the slow pace at which the inhalation field evolves. The NGI was officially implemented in 2003, being the last equipment innovation for OIDP characterization. Even though it was a breakthrough in the field, it did not solve other deficiencies of the BE process such as dissolution rate analysis on physiologically relevant conditions, being the last attempt of transferring technology into the field. This review aims to reveal the steps required for innovation in the regulations defining the bioequivalence of OIDPs, elucidating the pitfalls of implementing new technologies in the current standards. To do so, we collected the opinion of experts from the literature to explain these trends, showing, for the first time, the stakeholders of the OIDP market. This review analyzes the stakeholders involved in the development, improvement and implementation of methodologies that can help assess bioequivalence between OIDPs. Additionally, it presents a list of methods potentially useful to overcome some of the current limitations of the bioequivalence standard methodologies. Finally, we review one of the most revolutionary approaches, the inhaled Biopharmaceutical Classification System (IBCs), which can help establish priorities and order in both the innovation process and in regulations for OIDPs.
Lyophilization Preserves the Intrinsic Cardioprotective Activity of Bioinspired Cell-Derived Nanovesicles
Authors: Neupane Yub Raj , Huang Chenyuan , Wang Xiaoyuan , Chng Wei Heng , Venkatesan Gopalakrishnan , Zharkova Olga , Wacker Matthias Gerhard , Czarny Bertrand , Storm Gerrit , Wang Jiong-Wei , Pastorin Giorgia
Published: July 2021

Recently, bioinspired cell-derived nanovesicles (CDNs) have gained much interest in the field of nanomedicine due to the preservation of biomolecular structure characteristics derived from their parent cells, which impart CDNs with unique properties in terms of binding and uptake by target cells and intrinsic biological activities. Although the production of CDNs can be easily and reproducibly achieved with any kind of cell culture, application of CDNs for therapeutic purposes has been greatly hampered by their physical and chemical instability during long-term storage in aqueous dispersion. In the present study, we conceived a lyophilization approach that would preserve critical characteristics regarding stability (vesicles’ size and protein content), structural integrity, and biological activity of CDNs for enabling long-term storage in freeze-dried form. Compared to the lyoprotectant sucrose, trehalose-lyoprotected CDNs showed significantly higher glass transition temperature and lower residual moisture content. As assessed by ATR-FTIR and far-UV circular dichroism, lyophilization in the presence of the lyoprotectant effectively maintained the secondary structure of cellular proteins. After reconstitution, lyoprotected CDNs were efficiently associated with HeLa cells, CT26 cells, and bone marrow-derived macrophages at a rate comparable to the freshly prepared CDNs. In vivo, both lyoprotected and freshly prepared CDNs, for the first time ever reported, targeted the injured heart, and exerted intrinsic cardioprotective effects within 24 h, attributable to the antioxidant capacity of CDNs in a myocardial ischemia/reperfusion injury animal model. Taken together, these results pave the way for further development of CDNs as cell-based therapeutics stabilized by lyophilization that enabled long-term storage while preserving their activity.
Modulation of Temoporfin Distribution in Blood by β-Cyclodextrin Nanoshuttles
Authors: Yakavets Ilya , Yankovsky Igor , Zorina Tatyana , Belevtsev Mikhail , Bezdetnaya Lina , Zorin Vladimir
Published: July 2021

Photodynamic therapy represents a more targeted and less invasive alternative cancer treatment to traditional modalities. Temoporfin, as with many photosensitizers, is given by injection into a vein, and its subsequent fate is largely determined by the binding to plasma proteins and interaction with endothelial and blood cells. Thus, it is essential to be able to control and to alter the biodistribution of temoporfin in blood. In the present study, we evaluated the effect of co-administration of temoporfin with randomly methylated β-CD (Me-β-CD) on the distribution of temoporfin in the main subpopulations of blood cells of healthy donors using absorbance spectrophotometry and flow cytometry. We showed that cell-bound temoporfin fraction in blood strongly depends on the concentration of Me-β-CD. In fact, the accumulation of temoporfin in white blood cells was more sensitive than that in red blood cells, due to the higher volume of membranous organelles in white blood cells. Finally, we demonstrated that Me-β-CD significantly increases cellular uptake of temoporfin cancer human Burkitt′s lymphoma Raji cells. The presence of Me-β-CD resulted in a spotted pattern of temoporfin distribution in the plasma membrane compartment. Our results clearly demonstrated that β-CDs derivatives provide new options to modulate temoporfin biodistribution in blood.
Polyelectrolyte Multilayer Films Based on Natural Polymers: From Fundamentals to Bio-Applications
Authors: Criado-Gonzalez Miryam , Mijangos Carmen , Hernández Rebeca
Published: July 2021

Natural polymers are of great interest in the biomedical field due to their intrinsic properties such as biodegradability, biocompatibility, and non-toxicity. Layer-by-layer (LbL) assembly of natural polymers is a versatile, simple, efficient, reproducible, and flexible bottom-up technique for the development of nanostructured materials in a controlled manner. The multiple morphological and structural advantages of LbL compared to traditional coating methods (i.e., precise control over the thickness and compositions at the nanoscale, simplicity, versatility, suitability, and flexibility to coat surfaces with irregular shapes and sizes), make LbL one of the most useful techniques for building up advanced multilayer polymer structures for application in several fields, e.g., biomedicine, energy, and optics. This review article collects the main advances concerning multilayer assembly of natural polymers employing the most used LbL techniques (i.e., dipping, spray, and spin coating) leading to multilayer polymer structures and the influence of several variables (i.e., pH, molar mass, and method of preparation) in this LbL assembly process. Finally, the employment of these multilayer biopolymer films as platforms for tissue engineering, drug delivery, and thermal therapies will be discussed.
Analysis of Agronomic Drought in a Highly Anthropogenic Context Based on Satellite Monitoring of Vegetation and Soil Moisture
Authors: Zribi Mehrez , Nativel Simon , Le Page Michel
Published: July 2021

This paper aims to analyze agronomic drought in a highly anthropogenic, semiarid region, the western Mediterranean region. The proposed study is based on Moderate-Resolution Imaging Spectroradiometer (MODIS) and Advanced SCATterometer (ASCAT) satellite data describing the dynamics of vegetation cover and soil water content through the Normalized Difference Vegetation Index (NDVI) and Soil Water Index (SWI). Two drought indices were analyzed: the Vegetation Anomaly Index (VAI) and the Moisture Anomaly Index (MAI). The dynamics of the VAI were analyzed as a function of land cover deduced from the Copernicus land cover map. The effect of land cover and anthropogenic agricultural activities such as irrigation on the estimation of the drought index VAI was analyzed. The VAI dynamics were very similar for the shrub and forest classes. The contribution of vegetation cover (VAI) was combined with the effect of soil water content (MAI) through a new drought index called the global drought index (GDI) to conduct a global analysis of drought conditions. The implementation of this combination on different test areas in the study region is discussed.
Analysis of Salt Lake Volume Dynamics Using Sentinel-1 Based SBAS Measurements: A Case Study of Lake Tuz, Turkey
Authors: Bilgilioğlu Burhan Baha , Erten Esra , Musaoğlu Nebiye
Published: July 2021

As one of the largest hypersaline lakes, Lake Tuz, located in the middle of Turkey, is a key waterbird habitat and is classified as a Special Environmental Protection Area in the country. It is a dynamic lake, highly affected by evaporation due to its wide expanse and shallowness (water depth <40 cm), in addition to being externally exploited by salt companies. Monitoring the dynamics of its changes in volume, which cause ecological problems, is required to protect its saline lake functions. In this context, a spatially homogeneous distributed gauge could be critical for monitoring and rapid response; however, the number of gauge stations and their vicinity is insufficient for the entire lake. The present study focuses on assessing the feasibility of a time-series interferometric technique, namely the small baseline subset (SBAS), for monitoring volume dynamics, based on freely available Sentinel-1 data. A levelling observation was also performed to quantify the accuracy of the SBAS results. Regression analysis between water levels, which is one of the most important volume dynamics, derived by SBAS and levelling in February, April, July and October was 67%, 80%, 84%, and 95% respectively, for correlation in the range of 10–40 cm in water level, and was in line with levelling. Salt lake components such as water, vegetation, moist soil, dry soil, and salt, were also classified with Sentinel-2 multispectral images over time to understand the reliability of the SBAS measurements based on interferometric coherence over different surface types. The findings indicate that the SBAS method with Sentinel-1 is a good alternative for measuring lake volume dynamics, including the monitoring of water level and salt movement, especially for the dry season. Even though the number of coherent, measurable, samples (excluding water) decrease during the wet season, there are always sufficient coherent samples (>0.45) over the lake.
Passive MIMO Radar Detection with Unknown Colored Gaussian Noise
Authors: Liu Yongjun , Liao Guisheng , Li Haichuan , Zhu Shengqi , Li Yachao , Yin Yingzeng
Published: July 2021

The target detection of the passive multiple-input multiple-output (MIMO) radar that is comprised of multiple illuminators of opportunity and multiple receivers is investigated in this paper. In the passive MIMO radar, the transmitted signals of illuminators of opportunity are totally unknown, and the received signals are contaminated by the colored Gaussian noise with an unknown covariance matrix. The generalized likelihood ratio test (GLRT) is explored for the passive MIMO radar when the channel coefficients are also unknown, and the closed-form GLRT is derived. Compared with the GLRT with unknown transmitted signals and channel coefficients but a known covariance matrix, the proposed method is applicable for a more practical case whenthe covariance matrix of colored noise is unknown, although it has higher computational complexity. Moreover, the proposed GLRT can achieve similar performance as the GLRT with the known covariance matrix when the number of training samples is large enough. Finally, the effectiveness of the proposed GLRT is verified by several numerical examples.
An Automatic Method to Detect Lake Ice Phenology Using MODIS Daily Temperature Imagery
Authors: Zhang Xin , Wang Kaicun , Kirillin Georgiy
Published: July 2021

Lake ice phenology is a climate-sensitive indicator. However, ground-based monitoring suffers from the limitations of human vision and the difficulty of its implementation in harsh environments. Remote sensing provides great potential to detect lake ice phenology. In this study, a new automated method was developed to extract lake ice phenology parameters by capturing the temporal pattern of the transitional water/ice phase using a parameterized time function. The method is based on Moderate-Resolution Imaging Spectroradiometer (MODIS) daily temperature products, which have unique potential for monitoring lake ice cover as a result of providing four observations per day at 1 km spatial resolution from 2002 to 2016. Three seasonally ice-covered lakes with different characteristics in different climate regions were selected to test the method during the period of 2002–2016. The temporal pattern of water/ice transition phase was determined on the basis of unfrozen water cover fraction extracted from the MODIS daily temperature data, and was compared with the MODIS snow and reflectance products and Landsat images. A good agreement with an R2 of above 0.8 was found when compared with the MODIS snow product. The annual variation of extracted ice phenology dates showed good consistency with the MODIS reflectance and AMSR-E/2 products. The approach was then applied to nine seasonally ice-covered lakes in northern China from 2002 to 2016. The strongest tendency towards a later freeze-up start date was revealed in Lake Qinghai (6.31 days/10 yr) among the lakes in Tibetan plateau, and the break-up start and end dates rapidly shifted towards earlier dates in Lake Hulun (−3.73 days/10 yr; −5.02 days/10 yr). The method is suitable for estimating and monitoring ice phenology on different types of lakes over large scales and has a strong potential to provide valuable information on the responses of ice processes to climate change.
Mapping Threats of Spring Frost Damage to Tea Plants Using Satellite-Based Minimum Temperature Estimation in China
Authors: Wang Peijuan , Tang Junxian , Ma Yuping , Wu Dingrong , Yang Jianying , Jin Zhifeng , Huo Zhiguo
Published: July 2021

Spring frost damage (SFD), defined as the disaster during the period of newly formed tea buds in spring caused by lower temperature and frost damage, is a particular challenge for tea plants (Camellia sinensis), whose capacity to adapt to extreme weather and climate impacts is limited. In this paper, the region of the Middle and Lower Reaches of the Yangtze River (MLRYR) in China was selected as the major tea plantation study area, and the study period was focused on the concentrated occurrence of SFD, i.e., from March to April. By employing the standard lapse rate of air temperature with elevation, a minimum temperature (Tmin) estimation model that had been previously established was used based on reconstructed MYD11A1 nighttime LST values for 3 × 3 pixel windows and digital elevation model data. Combined with satellite-based Tmin estimates and ground-based Tmin observations, the spatiotemporal characteristics of SFD for tea plants were systematically analyzed from 2003 to 2020 in the MLRYR. The SFD risks at three scales (temporal, spatial, and terrain) were then evaluated for tea plants over the MLRYR. The results show that both SFD days at the annual scale and SFD areas at the daily scale exhibited a decreasing trend at a rate of 2.7 days/decade and 2.45 × 104 ha/day, respectively (significant rates at the 0.05 and 0.01 levels, respectively). The period with the highest SFD risk appeared mainly in the first twenty days of March. However, more attention should be given to the mid-to-late April time period due to the occurrence of late SFD from time to time. Spatially, areas with relatively higher SFD days and SFD risks were predominantly concentrated in the higher altitude areas of northwestern parts of MLRYR for both multi-year averages and individual years. Fortunately, in regions with a higher risk of SFD, the distribution of tea plants was relatively scattered and the area was small. These findings will provide helpful guidance for all kinds of people, including government agencies, agricultural insurance agencies, and tea farmers, in order that reasonable and effective strategies to reduce losses caused by spring frost damage to tea plants may be recommended and implemented.
A Method to Accelerate the Convergence of Satellite Clock Offset Estimation Considering the Time-Varying Code Biases
Authors: Liu Shuai , Yuan Yunbin
Published: July 2021

Continuous and stable precision satellite clock offsets are an important guarantee for real-time precise point positioning (PPP). However, in real-time PPP, the estimation of a satellite clock is often interrupted for various reasons such as network fluctuations, which leads to a long time for clocks to converge again. Typically, code biases are assumed to stay constant over time in clock estimation according to the current literature. In this contribution, it is shown that this assumption reduces the convergence speed of estimation, and the satellite clocks are still unstable for several hours after convergence. For this reason, we study the influence of different code bias extraction schemes, that is, taking code biases as constants, extracting satellite code biases (SCBs), extracting receiver code biases (RCBs) and simultaneously extracting SCBs and RCBs, on satellite clock estimation. Results show that, the time-varying SCBs are the main factors leading to the instability of satellite clocks, and considering SCBs in the estimation can significantly accelerate the filter convergence and improve the stability of clocks. Then, the products generated by introducing SCBs in the clock estimation based on undifferenced observations are applied to PPP experiments. Compared with the original undifferenced model, clocks estimated using the new method can significantly accelerate the convergence speed of PPP and improve the positioning accuracy, which illustrates that our estimated clocks are effective and superior.
Privacy–Accuracy Consideration in Devices That Collect Sensor-Based Information
Authors: Dery Lihi , Jelnov Artyom
Published: July 2021

Accurately tailored support such as advice or assistance can increase user satisfaction from interactions with smart devices; however, in order to achieve high accuracy, the device must obtain and exploit private user data and thus confidential user information might be jeopardized. We provide an analysis of this privacy–accuracy trade-off. We assume two positive correlations: a user’s utility from a device is positively correlated with the user’s privacy risk and also with the quality of the advice or assistance offered by the device. The extent of the privacy risk is unknown to the user. Thus, privacy concerned users might choose not to interact with devices they deem as unsafe. We suggest that at the first period of usage, the device should choose not to employ the full capability of its advice or assistance capabilities, since this may intimidate users from adopting it. Using three analytical propositions, we further offer an optimal policy for smart device exploitation of private data for the purpose of interactions with users.
Automated Multistep Parameter Identification of SPMSMs in Large-Scale Applications Using Cloud Computing Resources
Authors: Brescia Elia , Costantino Donatello , Marzo Federico , Massenio Paolo Roberto , Cascella Giuseppe Leonardo , Naso David
Published: July 2021

Parameter identification of permanent magnet synchronous machines (PMSMs) represents a well-established research area. However, parameter estimation of multiple running machines in large-scale applications has not yet been investigated. In this context, a flexible and automated approach is required to minimize complexity, costs, and human interventions without requiring machine information. This paper proposes a novel identification strategy for surface PMSMs (SPMSMs), highly suitable for large-scale systems. A novel multistep approach using measurement data at different operating conditions of the SPMSM is proposed to perform the parameter identification without requiring signal injection, extra sensors, machine information, and human interventions. Thus, the proposed method overcomes numerous issues of the existing parameter identification schemes. An IoT/cloud architecture is designed to implement the proposed multistep procedure and massively perform SPMSM parameter identifications. Finally, hardware-in-the-loop results show the effectiveness of the proposed approach.
An Integrated Compensation Method for the Force Disturbance of a Six-Axis Force Sensor in Complex Manufacturing Scenarios
Authors: Yao Lei , Gao Qingguang , Zhang Dailin , Zhang Wanpeng , Chen Youping
Published: July 2021

As one of the key components for active compliance control and human–robot collaboration, a six-axis force sensor is often used for a robot to obtain contact forces. However, a significant problem is the distortion between the contact forces and the data conveyed by the six-axis force sensor because of its zero drift, system error, and gravity of robot end-effector. To eliminate the above disturbances, an integrated compensation method is proposed, which uses a deep learning network and the least squares method to realize the zero-point prediction and tool load identification, respectively. After that, the proposed method can automatically complete compensation for the six-axis force sensor in complex manufacturing scenarios. Additionally, the experimental results demonstrate that the proposed method can provide effective and robust compensation for force disturbance and achieve high measurement accuracy.
Research on Design, Calibration and Real-Time Image Expansion Technology of Unmanned System Variable-Scale Panoramic Vision System
Authors: Guo Xiaodong , Wang Zhoubo , Zhou Wei , Zhang Zhenhai
Published: July 2021

This paper summarized the research status, imaging model, systems calibration, distortion correction, and panoramic expansion of panoramic vision systems, pointed out the existing problems and put forward the prospect of future research. According to the research status of panoramic vision systems, a panoramic vision system with single viewpoint of refraction and reflection is designed. The systems had the characteristics of fast acquisition, low manufacturing cost, fixed single-view imaging, integrated imaging, and automatic switching depth of field. Based on these systems, an improved nonlinear optimization polynomial fitting method is proposed to calibrate the monocular HOVS, and the binocular HOVS is calibrated with the Aruco label. This method not only improves the robustness of the calibration results, but also simplifies the calibration process. Finally, a real-time method of panoramic map of multi-function vehicle based on vcam is proposed.
A Hierarchy-Based System for Recognizing Customer Activity in Retail Environments
Authors: Wen Jiahao , Guillen Luis , Abe Toru , Suganuma Takuo
Published: July 2021

Customer activity (CA) in retail environments, which ranges over various shopper situations in store spaces, provides valuable information for store management and marketing planning. Several systems have been proposed for customer activity recognition (CAR) from in-store camera videos, and most of them use machine learning based end-to-end (E2E) CAR models, due to their remarkable performance. Usually, such E2E models are trained for target conditions (i.e., particular CA types in specific store spaces). Accordingly, the existing systems are not malleable to fit the changes in target conditions because they require entire retraining of their specialized E2E models and concurrent use of additional E2E models for new target conditions. This paper proposes a novel CAR system based on a hierarchy that organizes CA types into different levels of abstraction from lowest to highest. The proposed system consists of multiple CAR models, each of which performs CAR tasks that belong to a certain level of the hierarchy on the lower level’s output, and thus conducts CAR for videos through the models level by level. Since these models are separated, this system can deal efficiently with the changes in target conditions by modifying some models individually. Experimental results show the effectiveness of the proposed system in adapting to different target conditions.
Physical Activity Recognition Based on a Parallel Approach for an Ensemble of Machine Learning and Deep Learning Classifiers
Authors: Abid Mariem , Khabou Amal , Ouakrim Youssef , Watel Hugo , Chemcki Safouene , Mitiche Amar , Benazza-Benyahia Amel , Mezghani Neila
Published: July 2021

Human activity recognition (HAR) by wearable sensor devices embedded in the Internet of things (IOT) can play a significant role in remote health monitoring and emergency notification to provide healthcare of higher standards. The purpose of this study is to investigate a human activity recognition method of accrued decision accuracy and speed of execution to be applicable in healthcare. This method classifies wearable sensor acceleration time series data of human movement using an efficient classifier combination of feature engineering-based and feature learning-based data representation. Leave-one-subject-out cross-validation of the method with data acquired from 44 subjects wearing a single waist-worn accelerometer on a smart textile, and engaged in a variety of 10 activities, yielded an average recognition rate of 90%, performing significantly better than individual classifiers. The method easily accommodates functional and computational parallelization to bring execution time significantly down.
Silver Spoon and Green Lifestyle: A National Study of the Association between Childhood Subjective Socioeconomic Status and Adulthood Pro-Environmental Behavior in China
Authors: Liu Meiting , Koivula Aki
Published: July 2021

Based on the life history theory, this study is aimed at examining the associations among childhood subjective socioeconomic status, adulthood pro-environmental behavior, and commercial insurance purchase. We used the data from the 2013 Chinese General Social Survey (CGSS2013) and obtained a sample of 11,172 respondents, with ages ranging from 18 to 97 years old. The respondents were selected using multistage stratified sampling. Correlational, mediational and moderational analyses were conducted using SPSS. The results show that the childhood subjective socioeconomic status is positively associated with adulthood pro-environmental behavior, independent of the current subjective socioeconomic status. In addition, commercial insurance purchase acts as a mediator of the association between childhood subjective socioeconomic status and adulthood pro-environmental behavior. Using conditional process analysis, we demonstrated that age moderated both the path where childhood subjective socioeconomic status influenced adulthood pro-environmental behavior and the path where childhood subjective socioeconomic status influenced commercial insurance purchase. Theoretically, the results provide empirical support for evolutionary perspective on sustainable behavior and demonstrate that childhood environment can constrain individual consumer choices and lifestyle. Practically, positioning target customers to commercial insurance clients may be an effective marketing strategy to increase consumers’ actual purchase of ethical products. Moreover, to realize environmental goals, social policy makers can make efforts to publicize the importance of insurance and expand the coverage of insurance by increasing the corresponding financial subsidies for low socioeconomic status families.
Moving from Niche to Norm: Lessons from Food Waste Initiatives
Authors: Aramyan Lusine H. , Beekman Gonne , Galama Joris , van der Haar Sandra , Visscher Maarten , Zeinstra Gertrude G.
Published: July 2021

For a transition to a circular economy to take place, behavioural change from people who are part of the transition is a key requirement. However, this change often does not occur by itself. For systemic behavioural change, policy instruments that incentivise behaviour supporting circular food systems play a key role. These instruments need to be aligned with the environment in which the behaviour takes place. In this study, we scrutinise a case study with five initiatives on the reduction of food loss and waste (FLW) contributing to a circular food system, to understand how specific, well-targeted combinations of instruments as well as other contextual and personal factors can fuel the transition to a circular economy and the reduction of FLW. All the initiatives are taking place under the umbrella of the Dutch initiative “United against food waste” (STV). We use a behavioural change perspective to assess how initiatives that support circular food systems arise and how they can be further supported. Based on the case-study analysis, we arrive at five common success traits and barriers, and five key needs for upscaling. We conclude that motivated, inspiring frontrunners are of key importance in the initial phase of a transition process. However, once a niche initiative is ready to be scaled up, the enabling environment becomes increasingly important.