bluuebunny/crossref_metadata_2025 huggingface dataset:
Complex Nanowrinkling in Chiral Liquid Crystal Surfaces: From Shaping Mechanisms to Geometric Statistics
Authors: Wang Ziheng , Servio Phillip , Rey Alejandro D.
Published: May 2022

Surface wrinkling is closely linked to a significant number of surface functionalities such as wetting, structural colour, tribology, frictions, biological growth and more. Given its ubiquity in nature’s surfaces and that most material formation processes are driven by self-assembly and self-organization and many are formed by fibrous composites or analogues of liquid crystals, in this work, we extend our previous theory and modeling work on in silico biomimicking nanowrinkling using chiral liquid crystal surface physics by including higher-order anisotropic surface tension nonlinearities. The modeling is based on a compact liquid crystal shape equation containing anisotropic capillary pressures, whose solution predicts a superposition of uniaxial, equibiaxial and biaxial egg carton surfaces with amplitudes dictated by material anchoring energy parameters and by the symmetry of the liquid crystal orientation field. The numerical solutions are validated by analytical solutions. The blending and interaction of egg carton surfaces create surface reliefs whose amplitudes depend on the highest nonlinearity and whose morphology depends on the anchoring coefficient ratio. Targeting specific wrinkling patterns is realized by selecting trajectories on an appropriate parametric space. Finally, given its importance in surface functionalities and applications, the geometric statistics of the patterns up to the fourth order are characterized and connected to the parametric anchoring energy space. We show how to minimize and/or maximize skewness and kurtosis by specific changes in the surface energy anisotropy. Taken together, this paper presents a theory and simulation platform for the design of nano-wrinkled surfaces with targeted surface roughness metrics generated by internal capillary pressures, of interest in the development of biomimetic multifunctional surfaces.
Coke-Resistant Ni/CeZrO2 Catalysts for Dry Reforming of Methane to Produce Hydrogen-Rich Syngas
Authors: Sophiana Intan Clarissa , Iskandar Ferry , Devianto Hary , Nishiyama Norikazu , Budhi Yogi Wibisono
Published: May 2022

Dry reforming of methane was studied over high-ratio zirconia in ceria-zirconia-mixed oxide-supported Ni catalysts. The catalyst was synthesized using co-precipitation and impregnation methods. The effects of the catalyst support and Ni composition on the physicochemical characteristics and performance of the catalysts were investigated. Characterization of the physicochemical properties was conducted using X-ray diffraction (XRD), N2-physisorption, H2-TPR, and CO2-TPD. The results of the activity and stability evaluations of the synthesized catalysts over a period of 240 min at a temperature of 700 °C, atmospheric pressure, and WHSV of 60,000 mL g−1 h−1 showed that the 10%Ni/CeZrO2 catalyst exhibited the highest catalytic performance, with conversions of CH4 and CO2 up to 74% and 55%, respectively, being reached. The H2/CO ratio in the product was 1.4, which is higher than the stoichiometric ratio of 1, indicating a higher formation of H2. The spent catalysts showed minimal carbon deposition based on the thermo-gravimetry analysis, which was <0.01 gC/gcat, so carbon deposition could be neglected.
2D/2D Heterojunction of TiO2 Nanoparticles and Ultrathin G-C3N4 Nanosheets for Efficient Photocatalytic Hydrogen Evolution
Authors: Du Ruifeng , Li Baoying , Han Xu , Xiao Ke , Wang Xiang , Zhang Chaoqi , Arbiol Jordi , Cabot Andreu
Published: May 2022

Photocatalytic hydrogen evolution is considered one of the promising routes to solve the energy and environmental crises. However, developing efficient and low-cost photocatalysts remains an unsolved challenge. In this work, ultrathin 2D g-C3N4 nanosheets are coupled with flat TiO2 nanoparticles as face-to-face 2D/2D heterojunction photocatalysts through a simple electrostatic self-assembly method. Compared with g-C3N4 and pure TiO2 nanosheets, 2D/2D TiO2/g-C3N4 heterojunctions exhibit effective charge separation and transport properties that translate into outstanding photocatalytic performances. With the optimized heterostructure composition, stable hydrogen evolution activities are threefold and fourfold higher than those of pure TiO2, and g-C3N4 are consistently obtained. Benefiting from the favorable 2D/2D heterojunction structure, the TiO2/g-C3N4 photocatalyst yields H2 evolution rates up to 3875 μmol·g−1·h−1 with an AQE of 7.16% at 380 nm.
The Effect of Silicon Dioxide Nanoparticles Combined with Entomopathogenic Bacteria or Fungus on the Survival of Colorado Potato Beetle and Cabbage Beetles
Authors: Shatalova Elena I. , Grizanova Ekaterina V. , Dubovskiy Ivan M.
Published: May 2022

Three types of modified silicon dioxide nanoparticles (SiO2, 10–20 nm) with additives of epoxy, silane and amino groups, used independently and in combination with the entomopathogenic bacteria Bacillus thuringiensis subsp. morrisoni and fungus Metarhizium robertsii were tested against Colorado potato beetle (Leptinotarsa decemlineata) and cabbage beetles (Phyllotreta spp.). All three nanoparticles were found to have an entomocidal effect on Colorado potato beetle larvae and crucifer flea beetles when ingested. Increased susceptibility of insects to B. thuringiensis or M. robertsii blastospores and their metabolites was shown after exposure to the modified silicon dioxide nanoparticles. The potential of modified silicon dioxide nanoparticles to enhance the efficiency of biopesticides based on the bacteria B. thuringiensis and fungi M. robertsii is considered in the paper.
Autofluorescence of Model Polyethylene Terephthalate Nanoplastics for Cell Interaction Studies
Authors: Lionetto Francesca , Lionetto Maria Giulia , Mele Claudio , Corcione Carola Esposito , Bagheri Sonia , Udayan Gayatri , Maffezzoli Alfonso
Published: May 2022

This work contributes to fill one of the gaps regarding nanoplastic interactions with biological systems by producing polyethylene terephthalate (PET) model nanoplastics, similar to those found in the marine environment, by means of a fast top-down approach based on mechanical fragmentation. Their size distribution and morphology were characterized by laser diffraction and atomic force microscopy (AFM). Their autofluorescence was studied by spectrofluorimetry and fluorescence imaging, being a key property for the evaluation of their interaction with biota. The emission spectra of label-free nanoplastics were comparable with those of PET nanoplastics labeled with Nile red. Finally, the suitability of label-free nanoplastics for biological studies was assessed by in vitro exposure with Mytilus galloprovincialis hemolymphatic cells in a time interval up to 6 h. The nanoplastic internalization into these cells, known to be provided with phagocytic activity, was assessed by fluorescence microscopy. The obtained results underlined that the autofluorescence of the model PET nanoplastics produced in the laboratory was adequate for biological studies having the potential to overcome the disadvantages commonly associated with several fluorescent dyes, such as the tendency to also stain other organic materials different from plastics, to form aggregates due to intermolecular interactions at high concentrations with a consequent decrease in fluorescence intensity, and to dye desorption from nanoparticles. The results of the autofluorescence study provide an innovative approach for plastic risk assessment.
Role of Chrononutrition in the Antihypertensive Effects of Natural Bioactive Compounds
Authors: Ibarz-Blanch Néstor , Morales Diego , Calvo Enrique , Ros-Medina Laura , Muguerza Begoña , Bravo Francisca Isabel , Suárez Manuel
Published: May 2022

Hypertension (HTN) is one of the main cardiovascular risk factors and is considered a major public health problem. Numerous approaches have been developed to lower blood pressure (BP) in hypertensive patients, most of them involving pharmacological treatments. Within this context, natural bioactive compounds have emerged as a promising alternative to drugs in HTN prevention. This work reviews not only the mechanisms of BP regulation by these antihypertensive compounds, but also their efficacy depending on consumption time. Although a plethora of studies has investigated food-derived compounds, such as phenolic compounds or peptides and their impact on BP, only a few addressed the relevance of time consumption. However, it is known that BP and its main regulatory mechanisms show a 24-h oscillation. Moreover, evidence shows that phenolic compounds can interact with clock genes, which regulate the biological rhythm followed by many physiological processes. Therefore, further research might be carried out to completely elucidate the interactions along the time–nutrition–hypertension axis within the framework of chrononutrition.
The Role of the Microbiome-Brain-Gut Axis in the Pathogenesis of Depressive Disorder
Authors: Młynarska Ewelina , Gadzinowska Joanna , Tokarek Julita , Forycka Joanna , Szuman Aleksandra , Franczyk Beata , Rysz Jacek
Published: May 2022

The role of gut microbiota and its association with the central nervous system via the microbiome-brain-gut axis has been widely discussed in the literature. The aim of this review is to investigate the impact of gut microbiota on the development of depression and underlying molecular mechanisms. There are two possible pathways in which this interaction might occur. The first one suggests that depressive disorder could lead to dysbiosis and one of the causes may be the influence on the hypothalamic-pituitary-adrenal (HPA) axis. The second one considers if changes in the composition of gut microbiota might cause depressive disorder. The mechanisms that could be responsible for this interaction include the secretion of neurotransmitters, gut peptides and the activation of the immune system. However, current knowledge on this topic does not allow for us to state an unambiguous conclusion, and future studies that take into consideration more precise stress-measurement methods are needed to further explore direct mechanisms of the interaction between gut microbiota and mental health.
L-Serine Supplementation Blunts Fasting-Induced Weight Regain by Increasing Brown Fat Thermogenesis
Authors: López-Gonzales Elena , Lehmann Lisa , Ruiz-Ojeda Francisco Javier , Hernández-Bautista René , Altun Irem , Onogi Yasuhiro , Khalil Ahmed Elagamy , Liu Xue , Israel Andreas , Ussar Siegfried
Published: May 2022

Weight regain after fasting, often exceeding the pre-fasting weight, is a common phenomenon and big problem for the treatment of obesity. Thus, novel interventions maintaining reduced body weight are critically important to prevent metabolic disease. Here we investigate the metabolic effects of dietary L-serine supplementation, known to modulate various organ functions. C57BL/6N-Rj male mice were supplemented with or without 1% L-serine in their drinking water and fed with a chow or high-fat diet. Mice were fed either ad libitum or subjected to repeated overnight fasting. Body weight, body composition, glucose tolerance and energy metabolism were assessed. This was combined with a detailed analysis of the liver and adipose tissues, including the use of primary brown adipocytes to study mitochondrial respiration and protein expression. We find that L-serine supplementation has little impact on systemic metabolism in ad libitum-fed mice. Conversely, L-serine supplementation blunted fasting-induced body weight regain, especially in diet-induced obese mice. This reduction in body weight regain is likely due to the increased energy expenditure, based on elevated brown adipose tissue activity. Thus, L-serine supplementation during and after weight-loss could reduce weight regain and thereby help tackle one of the major problems of current obesity therapies.
Variability in the Beneficial Effects of Phenolic Compounds: A Review
Authors: Eseberri Itziar , Trepiana Jenifer , Léniz Asier , Gómez-García Iker , Carr-Ugarte Helen , González Marcela , Portillo María P.
Published: May 2022

When analysing the beneficial effects of phenolic compounds, several factors that exert a clear influence should be taken into account. The content of phenolic compounds in foods is highly variable, directly affecting individual dietary intake. Once ingested, these compounds have a greater or lesser bioaccessibility, defined as the amount available for absorption in the intestine after digestion, and a certain bioavailability, defined as the proportion of the molecule that is available after digestion, absorption and metabolism. Among the external factors that modify the content of phenolic compounds in food are the variety, the cultivation technique and the climate. Regarding functional foods, it is important to take into account the role of the selected food matrix, such as dairy matrices, liquid or solid matrices. It is also essential to consider the interactions between phenolic compounds as well as the interplay that occurs between these and several other components of the diet (macro- and micronutrients) at absorption, metabolism and mechanism of action levels. Furthermore, there is a great inter-individual variability in terms of phase II metabolism of these compounds, composition of the microbiota, and metabolic state or metabotype to which the subject belongs. All these factors introduce variability in the responses observed after ingestion of foods or nutraceuticals containing phenolic compounds.
Substituted Purines as High-Affinity Histamine H3 Receptor Ligands
Authors: Espinosa-Bustos Christian , Leitzbach Luisa , Añazco Tito , Silva María J. , Campo Andrea del , Castro-Alvarez Alejandro , Stark Holger , Salas Cristian O.
Published: May 2022

Continuing with our program to obtain new histamine H3 receptor (H3R) ligands, in this work we present the synthesis, H3R affinity and in silico studies of a series of eight new synthetically accessible purine derivatives. These compounds are designed from the isosteric replacement of the scaffold presented in our previous ligand, pyrrolo[2,3-d]pyrimidine ring, by a purine core. This design also considers maintaining the fragment of bipiperidine at C-4 and aromatic rings with electron-withdrawing groups at N-9, as these fragments are part of the proposed pharmacophore. The in vitro screening results show that two purine derivatives, 3d and 3h, elicit high affinities to the H3R (Ki values of 2.91 and 5.51 nM, respectively). Both compounds are more potent than the reference drug pitolisant (Ki 6.09 nM) and show low toxicity with in vitro models (IC50 > 30 µM on HEK-293, SH-SY5Y and HepG2 cell lines). Subsequently, binding modes of these ligands are obtained using a model of H3R by docking and molecular dynamics studies, thus determining the importance of the purine ring in enhancing affinity due to the hydrogen bonding of Tyr374 to the N-7 of this heterocycle. Finally, in silico ADME properties are predicted, which indicate a promising future for these molecules in terms of their physical–chemical properties, absorption, oral bioavailability and penetration in the CNS.
Activation of Host-NLRP3 Inflammasome in Myeloid Cells Dictates Response to Anti-PD-1 Therapy in Metastatic Breast Cancers
Authors: Tengesdal Isak W. , Li Suzhao , Powers Nicholas E. , May Makenna , Neff Charles P. , Joosten Leo A. B. , Marchetti Carlo , Dinarello Charles A.
Published: May 2022

Tumor-associated inflammation leads to dysregulated cytokine production that promotes tumor immune evasion and anti-tumor immunity dysfunction. In advanced stage breast cancer, the proinflammatory cytokine IL-1β is overexpressed due to large proportions of activated myeloid cells in the tumor microenvironment (TME). Here, we demonstrate the role of the host nucleotide-binding domain, leucine-rich containing family, pyrin domain-containing 3 (NLRP3) inflammasome in metastatic breast cancer. In vitro, we show that stimulation of THP-1 cells with conditioned media collected from MDA-MB-468 cells induced NLRP3 activation and increased Pdcd1l1 expression. In vivo, mice deficient in NLRP3 orthotopically implanted with metastatic breast cancer cell line (E0771) showed significant reduction in tumor growth (p < 0.05) and increased survival (p < 0.01). Inhibition of NLRP3 with the small molecule OLT1177® reduced expression of Pdcd1l1 (p < 0.001), Casp1 (p < 0.01) and Il1b (p < 0.01) in primary tumors. Furthermore, tumor-bearing mice receiving OLT1177® showed reduced infiltration of myeloid-derived suppressor cells (MDSCs) (p < 0.001) and increased CD8+ T cells (p < 0.05) and NK cells (p < 0.05) in the TME. NLRP3 inhibition in addition to anti-PD-1 treatment significantly reduced tumor growth from the monotherapies (p < 0.05). These data define NLRP3 activation as a key driver of immune suppression in metastatic breast cancers. Furthermore, this study suggests NLRP3 as a valid target to increase efficacy of immunotherapy with checkpoint inhibitor in metastatic breast cancers.
Amorphization of Drugs for Transdermal Delivery-a Recent Update
Authors: Chatterjee Bappaditya , Reddy Abhishek , Santra Moushami , Khamanga Sandile
Published: May 2022

Amorphous solid dispersion is a popular formulation approach for orally administered poorly water-soluble drugs, especially for BCS class II. But oral delivery could not be an automatic choice for some drugs with high first-pass metabolism susceptibility. In such cases, transdermal delivery is considered an alternative if the drug is potent and the dose is less than 10 mg. Amorphization of drugs causes supersaturation and enhances the thermodynamic activity of the drugs. Hence, drug transport through the skin could be improved. The stabilization of amorphous system is a persistent challenge that restricts its application. A polymeric system, where amorphous drug is dispersed in a polymeric carrier, helps its stability. However, high excipient load often becomes problematic for the polymeric amorphous system. Coamorphous formulation is another approach, where one drug is mixed with another drug or low molecular weight compound, which stabilizes each other, restricts crystallization, and maintains a single-phase homogenous amorphous system. Prevention of recrystallization along with enhanced skin permeation has been observed by the transdermal coamorphous system. But scalable manufacturing methods, extensive stability study and in-depth in vivo evaluation are lacking. This review has critically studied the mechanistic aspects of amorphization and transdermal permeation by analyzing recent researches in this field to propose a future direction.
Mechanical and Physicochemical Properties of Composite Biopolymer Films Based on Carboxymethyl Cellulose from Young Palmyra Palm Fruit Husk and Rice Flour
Authors: Kaewprachu Pimonpan , Jaisan Chalalai , Klunklin Warinporn , Phongthai Suphat , Rawdkuen Saroat , Tongdeesoontorn Wirongrong
Published: May 2022

Carboxymethyl cellulose from young Palmyra palm fruit husk (CMCy) film has low water barrier properties, which can limit its application. Thus, the combination of CMCy with other polysaccharides, such as rice flour (RF), may solve this problem. The aim of this study is to prepare the CMCy/RF composite films in different proportions (CMCy100, CMCy75/RF25, CMCy50/RF50, CMCy25/RF75, and RF100) and investigate their mechanical and physicochemical properties. The film strength (33.36–12.99 MPa) and flexibility (9.81–3.95%) of the CMCy/RF composite films decreased significantly (p < 0.05) with an increase in the RF proportion. Blending the RF with CMCy could improve the water vapor permeability (9.25–6.18 × 10−8 g m m−2 s−1 Pa−1) and film solubility (82.70–21.64%) of the CMCy/RF composite films. Furthermore, an increased lightness with a coincidental decreased yellowness of the CMCy/RF composite films was pronounced when the RF proportion increased (p < 0.05). However, the addition of RF in different proportions did not influence the film thickness and transparency. Based on SEM micrographs, all film samples had a relatively coarser surface. FTIR spectra showed that some interactions between CMCy and RF blended films had occurred. According to these findings, the CMCy50/RF50 composite film was found to be the best formulation because it has good mechanical and physicochemical properties.
Behavior Study of Commercial Polyurea under Monotonic, Rate Dependent, Cyclic, and Fatigue Tensile Loading for Potential Structural Applications
Authors: Acharya Pawan , Ebrahimian Hamed , Moustafa Mohamed A.
Published: May 2022

Understanding material behavior is key to discovering innovative applications in any field. Regardless of the exciting mechanical properties of polyurea, there has been a limited effort in studying the use of polyurea for structural retrofit and strengthening applications. This study aims to understand the behavior of polyurea under different tensile loading conditions to provide critical information towards enabling the future use of polyurea in structural applications. Several standard coupons are tested under various tensile loading conditions to understand the mechanical behavior of eight different commercial polyureas. The study provides the full stress–strain characteristic curves that can be used for constitutive modeling purposes. The results show that polyurea has a wide range of properties from low strength flexible nature to high strength rigid nature. All tested polyureas displayed some level of rate dependency, i.e., ultimate strength is a function of loading rates. The high-strength polyureas tested only show slight rate dependency and good strength retention under cyclic and fatigue tensile loading, suggesting that polyureas have promising mechanical properties for potential structural applications.
Design and Multiobjective Optimization of Green Closed-Loop Manufacturing-Recycling Network Considering Raw Material Attribute
Authors: Chen Chen , Wang Yue , Lu Shan , Li Xinchao
Published: May 2022

Regarding decision planning in the electronic manufacturing industry, this paper designs a green closed-loop manufacturing-recycling network for multiperiod production planning for multiple products. The network considers the tradeoff between production costs and environmental pollution induced by production scraps. Therefore, a mixed integer programming model with a dual objective is designed to achieve environmental protection and reduce production costs through resource recovery and utilization. At the same time, the recycled materials are considered to be treated, not entirely new, which could affect the manufacturing qualified rate. Thus, material attributes are proposed to distinguish new raw materials from recycled (second-hand) ones through the closed-loop manufacturing-recycling process to enhance the manufacturing qualified rate. In order to solve the dual-objective optimization model and realize optimal decisions, an epsilon constraint is designed to generate a nonextreme solution set by changing the original feasible region. The results show its ability to obtain a more balanced solution in terms of cost and environmental factors compared with the fuzzy-weighted method. Meanwhile, the analysis proves that the dual-objective optimization model with distinguishing material attributes can improve the efficiency of the manufacturing qualified rate and achieve a win-win situation for production and environmental protection during enterprise production.
A Novel Graphical Targeting Technique for Optimal Allocation of Biomass Resources
Authors: Foo Dominic C. Y.
Published: May 2022

Biomass has gained global attention as one of the most important renewable energy resources that reduces greenhouse gas emissions. Various research works have been dedicated to biomass supply chain in the past decade as to continuously support the deployment of biomass resources for regional applications. In this work, a novel graphical method based on process integration is proposed for targeting the amount of biomass resources needed for a power generation problem. Apart from having a good visualized interface, the graphical method provides good insights to stakeholders on the macro-level planning of biomass allocation. Two examples are solved to demonstrate the newly proposed methods.
COSMIC-2 RO Profile Ending at PBL Top with Strong Vertical Gradient of Refractivity
Authors: Xu Xu , Zou Xiaolei
Published: May 2022

The Formosa Satellite-7/Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (Satellite-7/COSMIC-2), which was successfully launched on 25 June 2019, provides dense radio occultation (RO) observations over the tropics and subtropics. This study examines the RO-observed lowest altitude and its possible relationship to refractivity gradients and planetary boundary layer (PBL) heights. COSMIC-2 RO data over the Southeast Pacific region (SEP) and the South-Central Pacific (SCP) from August 2020 are employed to determine their RO-observed lowest altitudes, and the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis data are used to obtain the gradients of refractivity. Results show that there are no ray perigees below the PBL top when the vertical gradient of N−N(r) is strong (<−65 N-unit km−1), where N(r) represents the vertical profile of the spherically symmetric refractivity. Significantly strong local vertical gradients due to atmospheric ducting occur more frequently over the SEP than the SCP areas. For some cases, a strong local horizontal gradient of refractivity in the tangent direction of a ray near its perigee point can also limit the RO profile from going further below even when the vertical gradient of N−N(r) is relatively weak. Fortunately, only about 0.6% COSMIC-2 RO profiles are unaffected by the above factors but cannot observe below 2-km altitude.
Temporal and Spatial Characteristics of the Global Skylight Polarization Vector Field
Authors: Yan Lei , Li Yanfei , Chen Wei , Lin Yi , Zhang Feizhou , Wu Taixia , Peltoniemi Jouni , Zhao Hongying , Liu Siyuan , Zhang Zihan
Published: May 2022

There are two widely recognized global fields in nature: the gravity field and the geomagnetic field. Universal gravitation and Earth rotation are important sources of the Earth’s gravity and geomagnetic fields, which are well known to us. After years of long-term observation, global research, and analysis, it was discovered that we have neglected a direct incident energy of the universe on the Earth. Solar radiation, leading to energy exchange from the atmosphere 100 km above the land surface, is the energy source of the Earth. Polarization is one of the four basic physical properties of solar radiation. After the solar radiation reaches the surface of these media, it reflects, scatters or refracts, and exhibits different degrees of polarization. The polarized solar light forms the Earth–sky polarization vector field. The polarized light dispersion is expected to become a new method for global analysis of the human environment. Polarization detection is the best way to accurately explore the atmospheric effects. Local polarized skylight distribution was found in different sites in the world; however, the global distribution of the polarized sunlight radiation has never been explored. In this paper, we investigate the Global Skylight Polarization Field. This study aimed at providing new insight into the laws of polarization over our Earth. We use a Rayleigh scattering model to obtain the simulation results of the sky polarization field. Rayleigh scattering occurs when the particle size is much smaller than the wavelength of the incident electromagnetic wave. We also use a polarized fisheye camera to collect the sky polarization image and calculate the distribution pattern of the DOLP (degree of linear polarization) and AOLP (azimuth of linear polarization) of the skylight. The stability and gradual change in the degree of polarization in the zenith direction are verified, and the distribution law and daily change law of the degree of polarization in the sky are obtained. With the increase in the solar altitude angle, the degree of polarization will decrease. We also observed the skylight polarization in different weather conditions. Our results demonstrate the physical basis, characteristics, and usability of the polarization field. They show an inevitable trend from optical remote sensing to polarization remote sensing.
Hyperspectral Remote Sensing Image Classification Based on Partitioned Random Projection Algorithm
Authors: Jia Shuhan , Zhao Quanhua , Li Yu
Published: May 2022

Dimensionality reduction based on random projection (RP) includes two problems, namely, the dimensionality is limited by the data size and the class separability of the dimensionality reduction results is unstable due to the randomly generated projection matrix. These problems make the RP algorithm unsuitable for large-size hyperspectral image (HSI) classification. To solve these problems, this paper presents a new partitioned RP (PRP) algorithm and proves its rationality in theory. First, a large-size HSI is evenly divided into multiple small-size sub-HSIs. Afterwards, the projection matrix that maximizes the class separability is selected from multiple samplings in which the class dissimilarity measurement is defined as large inter-class distance and small intra-class variance. By using the same projection matrix, each small-size sub-HSI is projected to generate a low dimensional sub-HSI, thereby generating a low dimensional HSI. Next, the minimum distance (MD) classifier is utilized to classify the low dimensional HSI obtained by the PRP algorithm. Finally, four real HSIs are used for experiments, and three of the most popular classification algorithms based on RP are selected as comparison algorithms to validate the effectiveness of the proposed algorithm. The classification performance is evaluated with the kappa coefficient, overall accuracy (OA), average accuracy (AA), average precision rate (APR), and running time. Experimental results indicate that the proposed algorithm can obtain reliable classification results in a very short time.
Predicting Tree Mortality Using Spectral Indices Derived from Multispectral UAV Imagery
Authors: Bergmüller Kai O. , Vanderwel Mark C.
Published: May 2022

Past research has shown that remotely sensed spectral information can be used to predict tree health and vitality. Recent developments in unmanned aerial vehicles (UAVs) have now made it possible to derive such information at the tree and stand scale from high-resolution imagery. We used visible and multispectral bands from UAV imagery to calculate a set of spectral indices for 52,845 individual tree crowns within 38 forest stands in western Canada. We then used those indices to predict the mortality of these canopy trees over the following year. We evaluated whether including multispectral indices leads to more accurate predictions than indices derived from visible wavelengths alone and how the performance varies among three different tree species (Picea glauca, Pinus contorta, Populus tremuloides). Our results show that spectral information can be effectively used to predict tree mortality, with a random forest model producing a mean area under the receiver operating characteristic curve (AUC) of 89.8% and a balanced accuracy of 83.3%. The exclusion of multispectral indices worsened the model performance, but only slightly (AUC = 87.9%, balanced accuracy = 81.8%). We found variation in model performance among species, with higher accuracy for the broadleaf species (balanced accuracy = 85.2%) than the two conifer species (balanced accuracy = 73.3% and 77.8%). However, all models overpredicted tree mortality by a major degree, which limits the use for tree mortality predictions on an individual level. Further improvements such as long-term monitoring, the use of hyperspectral data and cost-sensitive learning algorithms, and training the model with a larger and more balanced data set are necessary. Nevertheless, our results demonstrate that imagery from UAVs has strong potential for predicting annual mortality for individual canopy trees.
Extraction of Micro-Doppler Feature Using LMD Algorithm Combined Supplement Feature for UAVs and Birds Classification
Authors: Dai Ting , Xu Shiyou , Tian Biao , Hu Jun , Zhang Yue , Chen Zengping
Published: May 2022

In the past few decades, the demand for reliable and robust systems capable of monitoring unmanned aerial vehicles (UAVs) increased significantly due to the security threats from its wide applications. During UAVs surveillance, birds are a typical confuser target. Therefore, discriminating UAVs from birds is critical for successful non-cooperative UAVs surveillance. Micro-Doppler signature (m-DS) reflects the scattering characteristics of micro-motion targets and has been utilized for many radar automatic target recognition (RATR) tasks. In this paper, the authors deploy local mean decomposition (LMD) to separate the m-DS of the micro-motion parts from the body returns of the UAVs and birds. After the separation, rotating parts will be obtained without the interference of the body components, and the m-DS features can also be revealed more clearly, which is conducive to feature extraction. What is more, there are some problems in using m-DS only for target classification. Firstly, extracting only m-DS features makes incomplete use of information in the spectrogram. Secondly, m-DS can be observed only for metal rotor UAVs, or large UAVs when they are closer to the radar. Lastly, m-DS cannot be observed when the size of the birds is small, or when it is gliding. The authors thus propose an algorithm for RATR of UAVs and interfering targets under a new system of L band staring radar. In this algorithm, to make full use of the information in the spectrogram and supplement the information in exceptional situations, m-DS, movement, and energy aggregation features of the target are extracted from the spectrogram. On the benchmark dataset, the proposed algorithm demonstrates a better performance than the state-of-the-art algorithms. More specifically, the equal error rate (EER) proposed is 2.56% lower than the existing methods, which demonstrates the effectiveness of the proposed algorithm.
Wet Paper Coding-Based Deep Neural Network Watermarking
Authors: Wang Xuan , Lu Yuliang , Yan Xuehu , Yu Long
Published: May 2022

In recent years, the wide application of deep neural network models has brought serious risks of intellectual property rights infringement. Embedding a watermark in a network model is an effective solution to protect intellectual property rights. Although researchers have proposed schemes to add watermarks to models, they cannot prevent attackers from adding and overwriting original information, and embedding rates cannot be quantified. Therefore, aiming at these problems, this paper designs a high embedding rate and tamper-proof watermarking scheme. We employ wet paper coding (WPC), in which important parameters are regarded as wet blocks and the remaining unimportant parameters are regarded as dry blocks in the model. To obtain the important parameters more easily, we propose an optimized probabilistic selection strategy (OPSS). OPSS defines the unimportant-level function and sets the importance threshold to select the important parameter positions and to ensure that the original function is not affected after the model parameters are changed. We regard important parameters as an unmodifiable part, and only modify the part that includes the unimportant parameters. We selected the MNIST, CIFAR-10, and ImageNet datasets to test the performance of the model after adding a watermark and to analyze the fidelity, robustness, embedding rate, and comparison schemes of the model. Our experiment shows that the proposed scheme has high fidelity and strong robustness along with a high embedding rate and the ability to prevent malicious tampering.
Raman Natural Gas Analyzer: Effects of Composition on Measurement Precision
Authors: Petrov Dmitry V. , Matrosov Ivan I. , Zaripov Alexey R. , Tanichev Aleksandr S.
Published: May 2022

Raman spectroscopy is a promising method for analyzing natural gas due to its high measurement speed and the potential to monitor all molecular components simultaneously. This paper discusses the features of measurements of samples whose composition varies over a wide range (0.005–100%). Analysis of the concentrations obtained during three weeks of experiments showed that their variation is within the error caused by spectral noise. This result confirms that Raman gas analyzers can operate without frequent calibrations, unlike gas chromatographs. It was found that a variation in the gas composition can change the widths of the spectral lines of methane. As a result, the measurement error of oxygen concentration can reach 200 ppm. It is also shown that neglecting the measurement of pentanes and n-hexane leads to an increase in the calculated concentrations of other alkanes and to errors in the density and heating value of natural gas.
A Dual-Band 47-dB Dynamic Range 0.5-dB/Step DPA with Dual-Path Power-Combining Structure for NB-IoT
Authors: Rad Reza E. , Kim Sungjin , Pu Younggun , Jung Yeongjae , Huh Hyungki , Yoo Joonmo , Kim Seokkee , Lee Kang-Yoon
Published: May 2022

This paper presents a digital power amplifier (DPA) with a 43-dB dynamic range and 0.5-dB/step gain steps for a narrow-band Internet of Things (NBIoT) transceiver application. The proposed DPA is implemented in a dual-band architecture for both the low band and high band of the frequency coverage in an NBIoT application. The proposed DPA is implemented in two individual paths, power amplification, and power attenuation, to provide a wide range when both paths are implemented. To perform the fine control over the gain steps, ten fully differential cascode power amplifier cores, in parallel with a binary sizing, are used to amplify power and enable signals and provide fine gain steps. For the attenuation path, ten steps of attenuated signal level are provided which are controlled with ten power cores, similar to the power amplification path in parallel but with a fixed, small size for the cores. The proposed implementation is finalized with output custom-made baluns at the output. The technique of using parallel controlled cores provides a fine power adjustability by using a small area on the die where the NBIoT is fabricated in a 65-nm CMOS technology. Experimental results show a dynamic range of 47 dB with 0.5-dB fine steps are also available.
Multilevel Structural Components Detection and Segmentation toward Computer Vision-Based Bridge Inspection
Authors: Yu Weilei , Nishio Mayuko
Published: May 2022

Bridge inspection plays a critical role in mitigating the safety risks associated with bridge deterioration and decay. CV (computer vision) technology can facilitate bridge inspection by accurately automating the structural recognition tasks, especially useful in UAV (unmanned aerial vehicles)-assisted bridge inspections. This study proposed a framework for the multilevel inspection of bridges based on CV technology, and provided verification using CNN (convolution neural network) models. Using a long-distance dataset, recognition of the bridge type was performed using the Resnet50 network. The dataset was built using internet image captures of 1200 images of arched bridges, cable-stayed bridges and suspension bridges, and the network was trained and evaluated. A classification accuracy of 96.29% was obtained. The YOLOv3 model was used to recognize bridge components in medium-distance bridge images. A dataset was created from 300 images of girders and piers collected from the internet, and image argumentation techniques and the tuning of model hyperparameters were investigated. A detection accuracy of 93.55% for the girders and 82.64% for the piers was obtained. For close-distance bridge images, segmentation and recognition of bridge components were investigated using the instance segmentation algorithm of the Mask–RCNN model. A dataset containing 800 images of girders and bearings was created, and annotated based on Yokohama City bridge inspection image records data. The trained model showed an accuracy of 90.8% for the bounding box and 87.17% for the segmentation. This study also contributed to research on bridge image acquisition, computer vision model comparison, hyperparameter tuning, and optimization techniques.
“God Helped Us”: Resilience, Religion and Experiences of Gender-Based Violence and Trafficking among African Forced Migrant Women
Authors: Pertek Sandra Iman
Published: May 2022

In this article, I explore how faith and religion shaped the resilience of forced migrant women subjected to intersecting gender-based violence (GBV) and trafficking. Adopting a social constructivist perspective, I draw upon interviews with 11 Christian and 4 Muslim displaced survivors of 10 African nationalities temporarily residing in Tunisia. I first outline the experiences of intersecting violence to understand what displaced survivors were resilient to, and then describe faith pathways to resilience, sometimes with spiritual struggles and unmet religious needs. I delineate ways in which personal prayers and cooperating with God enabled all but one survivor to cope with exploitation and perilous journeys toward imagined refuge. I offer insights for practitioners working with forced migrants on the move and highlight the importance of spiritual support for displaced survivors who are religious. I discuss the findings and offer implications for future research and practice.
Structuring Servitization-Related Capabilities: A Data-Driven Analysis
Authors: Benedettini Ornella
Published: May 2022

The existing literature investigates organizational capabilities for servitization in exploratory studies based predominantly on interviews with managers. This has led to classification frameworks that tend to reflect managerial perceptions regarding key capabilities (rather than actual firm capabilities) and in which associations and connections between capabilities remain anecdotal. This study examines the servitization-related capabilities existing in manufacturing firms that have taken strategic service initiatives and adopts a data-driven approach to explore their underlying structure. A quantitative study based on secondary data from annual report narratives is used to assess the servitization-related capabilities of 79 firms from the aerospace and defense sector and to identify the underlying factors through exploratory factor analysis. The study identifies seventeen capabilities structured into five factors: (i) management of production/delivery operations; (ii) development of valuable and sustainable offerings; (iii) identification of incentives; (iv) planning for uncertainty and change; and (v) relationship management. The study provides evidence of servitization-related capabilities in practice. By examining gaps between existing (current) capabilities and the capabilities identified in our five-factor model, business managers of aerospace and defense firms can assess the status of servitization-related capabilities at their firms and set objectives to develop such capabilities further. The study contributes to the systematic development of a reasonable and parsimonious representation of organizational capabilities for servitization, which is statistically supported and validated through empirical data.
Global Inequalities in the Bioeconomy: Thinking Continuity and Change in View of the Global Soy Complex
Authors: Backhouse Maria , Lühmann Malte , Tittor Anne
Published: May 2022

As a proposed pathway to societal transformation, the bioeconomy is aimed at providing a sustainable alternative to the fossil-based economy, replacing fossil raw materials with renewable biogenic alternatives. In this conceptual contribution, we argue that it is impossible to transform societies into sustainable bioeconomies considering the narrow boundaries of the bioeconomy as a policy. Drawing on approaches including agro-food studies, cheap food, and agrarian extractivism, we show that the bioeconomy is entangled in a broader context of social relations which call its claim to sustainability into question. Our analysis of the global soy complex, which represents the core of the current agro-food system, demonstrates how the bioeconomy perpetuates global inequalities with regard to trade relations, demand, and supply patterns, as well as power relations between the involved actors from the global to the local level. Against this background, we propose a fundamental rethink of the underlying understanding of transformation in bioeconomy policies. Instead of thinking the bioeconomy only along the lines of ecological modernisation, its proponents should consider studies on social-ecological transformation, which would entail radical structural change of the prevailing food regime to cope with the social-ecological crisis.
Social Networking as Leisure: An Attempt to Conceptualize Liquid Leisure
Authors: Olecká Ivana , Trochtová Ludmila , Pospíšil Jiří , Pospíšilová Helena
Published: May 2022

Our research was intended to find out whether social networking is recognized and experienced as leisure or should be considered liquid leisure because its borders are fluid. This aim was connected to the broader question of whether there are still clear borders between work, leisure, and other life aspects. The research was designed as a cross-sectional ex-post-facto study. The survey examined data collected through a structured questionnaire completed and returned by 3451 respondents aged 15+ selected from the general population of the Czech Republic. The statistical significance of hypotheses was tested using χ2 statistics for two-way (C × R) and three-way (C × R × L) contingency tables. Only 752 (21.79%) respondents reported not having or using an online social network account. Even though there is no reason why social networking should not be considered leisure, there was a considerable discrepancy between those who considered social media a leisure activity (8.2%) and those who did not (78.21%). Therefore, this kind of leisure activity is conceptualized in this paper as a specific liquid leisure.
Sustainable Water Management in a Krakow Housing Complex from the Nineteen-Seventies in Comparison with a Model Bio-Morpheme Unit
Authors: Bonenberg Wojciech , Rybicki Stanisław M. , Schneider-Skalska Grażyna , Stochel-Cyunel Jadwiga
Published: May 2022

Cities grow through the addition of new housing structures, but the existing tissue is also modernized. Krakow, like any city with a historical origin, has typologically varied housing tissue. A large area of the city is occupied by multi-family panel-block housing estates which are being revitalised and the scope of this revitalization should include sustainable design elements. This paper determines the potential for implementing integrated water management, that utilizes rainwater in an existing basic urban unit that is a housing estate from the nineteen-seventies, located in Krakow (Poland), in conjunction with the Bio-Morpheme—the fractal reference model unit. The parameters of the Bio-Morpheme were established by earlier research as the optimum for a housing unit with regards to the circular economy and improving water use efficiency. The study covers the need to improve the quality of the housing environment, linked with the presence of natural elements, including a water reservoir, in the direct vicinity of the development. The analyses explored the potential to employ integrated water management with rainwater reuse in a basic urban unit (Krakow-Morpheme) and then compared the findings with the outcomes obtained by the proposed Bio-Morpheme complex. The results indicate that the potential to achieve a lower demand of water from the water supply system and to lower wastewater production were obtained, with a simultaneous opportunity to lay out an open water reservoir into the Krakow-Morpheme urban interior for improvement of the health value and well-being of inhabitants.