bluuebunny/crossref_metadata_2025 huggingface dataset:
Direct Synthesis of HKUST-1 onto Cotton Fabrics and Properties
Authors: da Costa Braian Lobo , Rosa Isadora Letícia Aparecida Ataide , Silva Vitória Hipolito , Wu Qiuyue , Samulewski Rafael Block , Scacchetti Fabio Alexandre Pereria , Moisés Murilo Pereira , Lis Manuel J. , Bezerra Fabricio Maestá
Published: October 2022

Metal-organic frameworks are crystalline nanostructures formed by a metal interspersed by an organic binder. These metal-organic materials are examples of nanomaterials applied to textile material in search of new functionalized textiles. Cotton is a cellulosic fiber of great commercial importance, and has good absorption capacity and breathability; however, due to these characteristics, it is susceptible to the development of microorganisms on its surface. This work aims to analyze how the direct synthesis of HKUST-1 in cotton fabric modifies the chemical and physical properties. The material obtained was characterized by scanning electron microscopy to obtain its morphology, by spectrophotometry CIE L*a*b* to verify the color change, by a biological test to verify its resistance to microorganisms and, finally, by a unidirectional traction test to verify the change in its mechanical resistance. Thereby, it was possible to observe the formation of MOFs with the morphology of nanorods, and also, with regard to HKUST-1 in the cotton fabric, when applied, an elimination percentage higher than 99% was observed for both bacteria, E. coli and S. aureus. The presence of MOF was detected even after washing, however, the loss of 75% in the mechanical resistance of the material makes its potential for textile finishing unworkable.
The Problem of Filling a Spherical Cavity in an Aqueous Solution of Polymers
Authors: Frolovskaya Oxana A. , Pukhnachev Vladislav V.
Published: October 2022

The problem of filling a spherical cavity in a liquid has attracted the attention of many authors. The study of bubble behavior in liquid allows to estimate the consequences of cavitation processes, which can lead to the intensive destruction of the material surface. Regarding this connection, it becomes necessary to study the influence of impurities, including polymeric additives on the strengthening or suppression of cavitation. In this paper, this problem is considered in three models of a relaxing fluid. It is shown that for all models, the cavity filling time is finite if the surface tension is not equal to zero. This result was previously established for the cases of ideal and viscous fluids. However, the relaxation factor can significantly change the flow pattern by slowing down the filling process and lowering the level of energy accumulation during the bubble collapse.
Preparation of Core-Shell-Structured RDX@PVDF Microspheres with Improved Thermal Stability and Decreased Mechanical Sensitivity
Authors: Wu Hulin , Jiang Aifeng , Li Mengru , Wang Yanyan , Zhao Fangchao , Li Yanchun
Published: October 2022

Reducing the sensitivity of high-energy simple explosives is the key technology in improving the practical application of high-energy insensitive powder. As the most widely used high-energy explosive, hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) is limited in application due to its high sensitivity. In this work, polyvinylidene fluoride (PVDF) was used as an energetic binder. Core-shell-structured RDX@PVDF microspheres are produced using electrospray assembly technology and fully characterized by thermogravimetric analysis, X-ray diffraction, scanning electron microscopy, transmission electron microscopy, energy dispersive spectroscopy, and mechanical sensitivity. Their thermal stability and mechanical sensitivity are directly related to the weight fraction of the added PVDF. Moreover, core-shell-structured RDX@PVDF microspheres with RDX and PVDF in the proportion three to one possess a spherical-like morphology, the lowest impact sensitivity, the lowest friction sensitivity, and the highest thermal stability. This work provides a facile method for the positive design energetic materials and the prediction of their environmental adaptability.
Effect of Nucleating Agents Addition on Thermal and Mechanical Properties of Natural Fiber-Reinforced Polylactic Acid Composites
Authors: Yang Jae-Yeon , Kim Dong-Kyu , Han Woong , Park Jong-Yeon , Kim Kwan-Woo , Kim Byung-Joo
Published: October 2022

In this study, natural fiber-reinforced polylactic acid (NFRP) composite materials were prepared by adding nucleating agents (NAs) and natural fiber (NF) to compensate for the low thermal stability and brittleness of polylactic acid (PLA). The thermal stability of the fabricated composite material was investigated by differential scanning calorimetry and thermogravimetric analysis. In addition, the tensile modulus of elasticity according to the crystallinity of the composite was measured. The crystallinity of the PLA composite increased to ~700% upon the addition of the NA; thus, the thermal stability also increased. However, the changes in crystallinity and tensile modulus were insignificant when the concentration of the NA added was 4 wt.% or higher. The study demonstrates that the addition of NA and NF is effective in improving the thermal stability and mechanical properties of NFRP.
Chitosan-Hydroxyapatite Bio-Based Composite in Film Form: Synthesis and Application in Wastewater
Authors: Akartasse Noureddine , Azzaoui Khalil , Mejdoubi Elmiloud , Elansari Lhaj Lahcen , Hammouti Belkhir , Siaj Mohamed , Jodeh Shehdeh , Hanbali Ghadir , Hamed Rinad , Rhazi Larbi
Published: October 2022

Water purification from toxic metals was the main objective of this work. A composite in film form was prepared from the biomaterials hydroxyapatite, chitosan and glycerol using the dissolution/recrystallization method. A nanoparticle-based film with a homogenous and smooth surface was produced. The results of total reflectance infrared spectroscopy (ATR-FTIR) and thermal gravimetric analysis (TGA/DTA) demonstrated the presence of a substantial physical force between composite components. The composite was tested for its ability to absorb Cd2+ and Zn2+ ions from aqueous solutions. Cd2+ and Zn2+ adsorption mechanisms are fit using the Langmuir model and the pseudo-second-order model. Thermodynamic parameters indicated that Cd2+ and Zn2+ ion adsorption onto the composite surface is spontaneous and preferred at neutral pH and temperatures somewhat higher than room temperature. The adsorption studies showed that the maximum adsorption capacity of the HAp/CTs bio-composite membrane for Cd2+ and Zn2+ ions was in the order of cadmium (120 mg/g) > Zinc (90 mg/g) at an equilibrium time of 20 min and a temperature of 25 °C. The results obtained on the physico-chemical properties of nanocomposite membranes and their sorption capacities offer promising potential for industrial and biological activities.
Collagen Alignment via Electro-Compaction for Biofabrication Applications: A Review
Authors: Carr Benjamin P. , Chen Zhi , Chung Johnson H. Y. , Wallace Gordon G.
Published: October 2022

As the most prevalent structural protein in the extracellular matrix, collagen has been extensively investigated for biofabrication-based applications. However, its utilisation has been impeded due to a lack of sufficient mechanical toughness and the inability of the scaffold to mimic complex natural tissues. The anisotropic alignment of collagen fibres has been proven to be an effective method to enhance its overall mechanical properties and produce biomimetic scaffolds. This review introduces the complicated scenario of collagen structure, fibril arrangement, type, function, and in addition, distribution within the body for the enhancement of collagen-based scaffolds. We describe and compare existing approaches for the alignment of collagen with a sharper focus on electro-compaction. Additionally, various effective processes to further enhance electro-compacted collagen, such as crosslinking, the addition of filler materials, and post-alignment fabrication techniques, are discussed. Finally, current challenges and future directions for the electro-compaction of collagen are presented, providing guidance for the further development of collagenous scaffolds for bioengineering and nanotechnology.
Novel Approach in Biodegradation of Synthetic Thermoplastic Polymers: An Overview
Authors: Venkatesan Raja , Santhamoorthy Madhappan , Alagumalai Krishnapandi , Haldhar Rajesh , Raorane Chaitany Jayprakash , Raj Vinit , Kim Seong-Cheol
Published: October 2022

Biodegradation is necessary for water-soluble or water-immiscible polymers because they eventually enter streams which can neither be recycled nor incinerated. It is important to consider the microbial degradation of natural and synthetic polymers in order to understand what is necessary for biodegradation and the mechanisms involved. Low/high-density polyethylene is a vital cause of environmental pollution. It occurs by choking the sewer line through mishandling, thus posing an everlasting ecological threat. Environmental pollution due to the unscrupulous consumption of synthetic polymers derived from petroleum has an adverse impact on the environment since the majority of plastics do not degrade, and the further incineration of synthetic plastics generates CO2 and dioxin. This requires understanding the interactions between materials and microorganisms and the biochemical changes involved. Widespread studies on the biodegradation of plastics have been carried out in order to overcome the environmental problems associated with synthetic plastic waste. Awareness of the waste problem and its impact on the environment has awakened new interest in the area of degradable polymers through microbes viz., bacteria, fungi, and actinomycetes. The microbial degradation of plastics is caused by certain enzymatic activities that lead to a chain cleavage of polymers into oligomers and monomers. This review focuses on the biodegradation rate of plastics by fungal and bacterial communities and the mode of action of biodegradation.
Emerging Nurse Manager’s Resilience and Their Empowering Behavior during COVID-19
Authors: Taie Eman Salman , Amine Nessma Nehmedo , Akeel Amira Fathy
Published: October 2022

Background: The COVID-19 pandemic exacerbated tensions and tested the resiliency of many nursing leaders. Resilience enables head nurses to cope with their work environment challenges, and maintain healthy psychological activity. Moreover, their empowering behavior represents the vehicle to transform traumatic events such as the COVID-19 pandemic to create a high-quality work environment. Aim: To explore the relationship between nurse manager resilience and empowering leader behavior during COVID-19. Method: This is a descriptive correlational study. The study subjects consisted of two groups: head nurses (44) and staff nurses (284). The study was conducted at Benisuef University Hospital. Two tools were used for collecting data; nurse managers’ resilience scale, and staff nurses’ perceived empowering behavior during the COVID-19 pandemic via questionnaire. Results: In total, 50% of nurse managers had high resilience skills levels, about one-third of them (34.1%) had moderate levels and only 15.9% had low resilience skills levels. Furthermore, with regard to empowering leadership behavior levels as perceived by staff nurses during COVID-19; 66.9% of them perceived it high, 29.2% reported a moderate level of empowering behavior, and only 3.9% perceived low levels. Finally, there was a highly statistically significant positive correlation between nurse manager’s resilience skills levels and staff nurses’ perception of empowering behavior during COVID-19. Conclusions: Half of the nurse managers had high resilience skills, and only 15.9% had low levels. Two-thirds of staff nurses perceived high levels of their nurse manager’s empowering behavior during COVID-19, in comparison to only 3.9% who perceived low levels. There was a highly statistically significant positive correlation between nurse manager’s resilience skills levels and perceived empowering behavior during COVID-19.
Dramatic Theology: A Hermeneutical Framework for Discerning the Cultural Realities and the Role of Christianity in India
Authors: Kuzhippallil George Thomas
Published: October 2022

This article explains how dramatic theology can discern, evaluate, and interpret critically different cultural institutions and bring forward the uniqueness of Christian revelation in a pluralistic world. It clarifies the concept, methodology, and relevance of dramatic theology, which uses mimetic theory as an auxiliary hypothesis; taking the concrete example of cultural realities in India, it unearths the archaic background of their all-encompassing nature, the multiplicity of gods, and the caste system. It also describes how dramatic theology exposes the unique role of Jesus as the human face of God the Father, and the new gathering—through five acts in the Drama of Salvation—in human history and Christianity in such a complex cultural context.
Indigenous Peoples through the Lens of UNESCO
Authors: Stimac Zrinka
Published: October 2022

The engagement of UNESCO with indigenous peoples and their heritage provides insights into global norms that affect collective cultural rights, religion, and education of indigenous peoples. It also enables insights into structural and organizational challenges and opportunities indigenous peoples experience in the current world. Against this background, this paper analyzes exemplary UNESCO standard-setting documents that explicitly approach indigenous peoples. In doing so, the paper asks first, how these documents situate indigenous peoples in the context of cultural/religious diversity and education. Second, we reconstruct how UNESCO addresses the holistic education of indigenous peoples, and how does it relate to the notion of the holistic approach itself. Methodologically, the paper applies qualitative content analysis with close reading and situates UNESCO’s developments in the theoretical framework of the study of religion. From this perspective, the results address ambiguities around the term “religion”, when concentrated to ritual, and the possibility of convergences between universalist and holistic knowledge.
Medium-Resolution Mapping of Evapotranspiration at the Catchment Scale Based on Thermal Infrared MODIS Data and ERA-Interim Reanalysis over North Africa
Authors: Diarra Alhousseine , Jarlan Lionel , Khabba Saïd , Le Page Michel , Er-Raki Salah , Balaghi Riad , Charafi Soufyane , Chehbouni Abdelghani , El Alami Rafiq
Published: October 2022

Accurate quantification of evapotranspiration (ET) at the watershed scale remains an important research challenge for managing water resources in arid and semiarid areas. In this study, daily latent heat flux (LE) maps at the kilometer scale were derived from the two-source energy budget (TSEB) model fed by the MODIS leaf area index (LAI), land surface temperature (LST) products, and meteorological data from ERA-Interim reanalysis from 2001 to 2015 on the Tensift catchment (center of Morocco). As a preliminary step, both ERA-Interim and predicted LE at the time of the satellite overpass are evaluated in comparison to a large database of in situ meteorological measurements and eddy covariance (EC) observations, respectively. ERA-Interim compared reasonably well to in situ measurements, but a positive bias on air temperature was highlighted because meteorological stations used for the evaluation were mainly installed on irrigated fields while the grid point of ERA-Interim is representative of larger areas including bare (and hot) soil. Likewise, the predicted LE was in good agreement with the EC measurements gathered on the main crops of the region during 15 agricultural seasons with a correlation coefficient r = 0.70 and a reasonable bias of 30 W/m2. After extrapolating the instantaneous LE estimates to ET daily values, monthly ET was then assessed in comparison to monthly irrigation water amounts provided by the local agricultural office added to CRU precipitation dataset with a reasonable agreement; the relative error was more than 89% but the correlation coefficient r reached 0.80. Seasonal and interannual evapotranspiration was analyzed in relation to local climate and land use. Lastly, the potential use for improving the early prediction of grain yield, as well as detecting newly irrigated areas for arboriculture, is also discussed. The proposed method provides a relatively simple way for obtaining spatially distributed daily estimates of ET at the watershed scale, especially for not ungauged catchments.
A Method of Whole-Network Adjustment for Clock Offset Based on Satellite-Ground and Inter-Satellite Link Observations
Authors: Wang Dongxia , Guo Rui , Liu Li , Yuan Hong , Li Xiaojie , Pan Junyang , Tang Chengpan
Published: October 2022

The inter-satellite link is an important technology to improve the accuracy of clock offset measurement and prediction for BeiDou Navigation Satellite System (BDS). At present, BDS measures clock offsets of invisible satellite mainly through the “one-hop” reduction mode based on the satellite-ground clock offset of the node visible satellite and the inter-satellite clock offset between the two satellites. However, there exists a systematic deviation caused by the node satellite reduction, and there is still a large room for improvement in clock offset measurement and prediction. Therefore, this paper firstly proposes a method of whole-network adjustment for clock offset based on the satellite-ground and inter-satellite two-way data. The least square method is used to realize the whole-network adjustment of clock offset based on the observations of two sources, and to obtain optimal estimates of different clock offset reduction. Secondly, the evaluation method combining internal and external symbols are proposed by the fitting residual, prediction error and clock offset closure error. Finally, experimental verification is completed based on BDS measured data. In comparison with the “one-hop” reduction method, the fitting residual and prediction error of the whole-network adjustment method reduces about 45.06% and 52.15%, respectively. In addition, inter-satellite station closure error and three-satellite closure error are reduced from 0.69 ns and 0.23 ns to about 0 ns. It can be seen that the accuracy of BDS time synchronization is significantly improved.
Evaluation of Aerosol Typing with Combination of Remote Sensing Techniques with In Situ Data during the PANACEA Campaigns in Thessaloniki Station, Greece
Authors: Voudouri Kalliopi Artemis , Michailidis Konstantinos , Siomos Nikolaos , Chatzopoulou Anthi , Kouvarakis Georgios , Mihalopoulos Nikolaos , Tzoumaka Paraskevi , Kelessis Apostolos , Balis Dimitrios
Published: October 2022

Two measurement campaigns were conducted at Thessaloniki, an urban station, (40.5°N, 22.9°E; 60 m) in the frame of the PANhellenic infrastructure for Atmospheric Composition and climatEchAnge (PANACEA) project. The first one covers the period from July to August 2019 and the second one from January to February An overview of the aerosol optical properties (columnar and height resolved), acquired with the remote sensing infrastructure of the Laboratory of Atmospheric Physics (LAP) of the Aristotle University of Thessaloniki (AUTH), as well as the additional instrumentation that participated during the PANACEA campaigns is presented. The majority of the detected layers (16 out of 40, ranged between 0.8 and 4.5 km) are classified as biomass burning aerosols, attributed to either city sources or long range transport. Concerning the other aerosol types, the Clean Continental cluster has an occurrence ratio of 23%, while dust layers and mixtures with urban particles transported to Thessaloniki are also identified. Our findings are discussed along with the surface information, i.e., the particulate matter (PM2.5 and PM10) concentrations and the black carbon (BC) concentration, separated into fossil fuel (BCff) and biomass/wood burning (BCwb) fractions. This is the first time that collocated in situ and remote sensing instruments are deployed in Thessaloniki in order to assess the presence of aerosols and the predominant aerosol type both in situ and at elevated heights. Overall, our study showed that the BCwb contribution to the BC values in Thessaloniki is quite low (11%), whilst the majority of the biomass burning layers identified with the lidar system, are also linked with enhanced BC contribution and high Fine Mode Fraction values.
Spatially Non-Stationary Relationships between Changing Environment and Water Yield Services in Watersheds of China’s Climate Transition Zones
Authors: Cao Zhe , Zhu Wei , Luo Pingping , Wang Shuangtao , Tang Zeming , Zhang Yuzhu , Guo Bin
Published: October 2022

Identifying the spatial and temporal heterogeneity of water-related ecosystem services and the mechanisms influencing them is essential for optimizing ecosystem governance and maintaining watershed sustainable development. However, the complex and undiscovered interplay between human activities and natural factors underpins the solutions to the water scarcity and flooding challenges faced by climate transition zone basins. This study used a multiple spatial-scale analysis to: (i) quantify the spatial and temporal variations of the water yield ecosystem service (WYs) of the Wei River Basin (WRB) from 2000 to 2020 using the InVEST model and remote sensing data; and (ii) look at how human activities, climate, topography, and vegetation affect the WYs at the climate transition zone sub-catchment scale using the geographical detector model and multi-scale geographically weighted regression (MGWR). The conclusive research reveals that there would be a gradual increase in WYs between the years 2000 and 2020, as well as a distinct and very different spatial aggregation along the climatic divide. The average yearly precipitation was shown to be particularly linked to the water yield of the WRB. The interplay of human, climatic, plant, and terrain variables has a substantially higher influence than most single factors on the geographical differentiation of WYs. Bivariate enhancement and non-linear enhancement are the most common types of factor interactions. This shows that there are significant interactions between natural and human variables. Our study shows that precipitation and temperature are the main factors that cause WYs in the semi-arid zone. In the semi-humid zone, precipitation and vegetation are the key controlling factors that cause WYs. We provide new perspectives for understanding and optimizing ecosystem management by comparing the drivers of WYS in sub-basins with different climatic conditions. Based on the findings, we recommend that particular attention should be paid to ecosystem restoration practices in watersheds in climatic transition zones.
Parallel Electrical Conductivity at Low and Middle Latitudes in the Topside Ionosphere Derived from CSES-01 Measurements
Authors: Giannattasio Fabio , Pignalberi Alessio , De Michelis Paola , Coco Igino , Pezzopane Michael , Tozzi Roberta , Consolini Giuseppe
Published: October 2022

The study of electrical currents in the topside ionosphere is of great importance, as it may allow a better understanding of the processes involved in the Sun–Earth interaction and magnetosphere–ionosphere–thermosphere coupling, two crucial aspects debated by the Space Weather scientific community. In this context, investigating the electrical conductivity parallel to the geomagnetic field in the topside ionosphere is of primary importance because: (1) it provides information on the capability of the ionosphere to conduct currents; (2) it relates current density and electric field through Ohm’s law; (3) it can help to quantify the dissipation of currents; (4) it is generally modeled and not locally measured by in situ missions. In this work, we used in situ measurements of electron density and temperature recorded between 2019 and 2021 by the China Seismo-Electromagnetic Satellite (CSES-01) flying with an orbital inclination of 97.4° and at an altitude of about 500 km to compute the parallel electrical conductivity in the topside ionosphere at low and middle latitudes at the two fixed local times (LT) characterizing the CSES-01 mission: around 02 and 14 LT. The results, which are discussed in light of previous literature, highlight the dependence of conductivity on latitude and longitude and are compared with those obtained using values both measured by the Swarm B satellite (flying at a similar altitude) and modeled by the International Reference Ionosphere in the same time period. In particular, we found a diurnal variation in parallel electrical conductivity, with a slight hemispheric asymmetry. Daytime features are compatible with Sq and equatorial electrojet current systems, containing “anomalous” low values of conductivity in correspondence with the South Atlantic region that could be physical in nature.
PolSAR Models with Multimodal Intensities
Authors: Ferreira Jodavid A. , Nascimento Abraão D. C. , Frery Alejandro C.
Published: October 2022

Polarimetric synthetic aperture radar (PolSAR) systems are an important remote sensing tool. Such systems can provide high spacial resolution images, but they are contaminated by an interference pattern called multidimensional speckle. This fact requires that PolSAR images receive specialised treatment; particularly, tailored models which are close to PolSAR physical formation are sought. In this paper, we propose two new matrix models which arise from applying the stochastic summation approach to PolSAR, called compound truncated Poisson complex Wishart (CTPCW) and compound geometric complex Wishart (CGCW) distributions. These models offer the unique ability to express multimodal data. Some of their mathematical properties are derived and discussed—characteristic function and Mellin-kind log-cumulants (MLCs). Moreover, maximum likelihood (ML) estimation procedures via expectation maximisation algorithm for CTPCW and CGCW parameters are furnished as well as MLC-based goodness-of-fit graphical tools. Monte Carlo experiment results indicate ML estimates perform at what is asymptotically expected (small bias and mean square error) even for small sample sizes. Finally, our proposals are employed to describe actual PolSAR images, presenting evidence that they can outperform other well-known distributions, such as WmC, Gm0, and Km.
Analysis of Drought Characteristics Projections for the Tibetan Plateau Based on the GFDL-ESM2M Climate Model
Authors: Liu Yu , Jia Zhifeng , Ma Xiaoyi , Wang Yongqiang , Guan Ronghao , Guan Zilong , Gu Yuhui , Zhao Wei
Published: October 2022

Under conditions of continuous global warming, research into the future change trends of regional dry-wet climates is key for coping with and adapting to climate change, and is also an important topic in the field of climate change prediction. In this study, daily precipitation and mean temperature datasets under four representative concentrative pathway (RCP) scenarios in the geophysical fluid dynamics laboratory Earth system model with modular ocean model (GFDL-ESM2M) version 4 were used to calculate the standardized precipitation-evapotranspiration index of the Tibetan Plateau (TP) at different time scales. Using a multi-analytical approach including the Mann–Kendall trend test and run theory, the spatiotemporal variation characteristics of drought in the TP from 2016 to 2099 were studied. The results show that the overall future climate of the TP will develop towards warm and humid, and that the monthly-scale wet–dry changes will develop non-uniformly. As the concentration of carbon dioxide emissions increases in the future, the proportion of extremely significant aridification and humidification areas in the TP will significantly increase, and the possibility of extreme disasters will also increase. Moreover, influenced by the increase of annual TP precipitation, the annual scale of future drought in the region will tend to decrease slightly, and the spatial distributions of the frequency and intensity of droughts at all levels will develop uniformly. Under all four RCP scenarios, the drought duration of the TP was mainly less than 3 months, and the drought cycle in the southern region was longer than that in the northern region. The results of this study provide a new basis for the development of adaptive measures for the TP to cope with climate change.
Machine-Learning-Based Framework for Coding Digital Receiving Array with Few RF Channels
Authors: Xiao Lei , Han Yubing , Weng Zuxin
Published: October 2022

A novel framework for a low-cost coding digital receiving array based on machine learning (ML-CDRA) is proposed in this paper. The received full-array signals are encoded into a few radio frequency (RF) channels, and decoded by an artificial neural network in real-time. The encoding and decoding networks are studied in detail, including the implementation of the encoding network, the loss function and the complexity of the decoding network. A generalized form of loss function is presented by constraint with maximum likelihood, signal sparsity, and noise. Moreover, a feasible loss function is given as an example and the derivations for back propagation are successively derived. In addition, a real-time processing implementation architecture for ML-CDRA is presented based on the commercial chips. It is possible to implement by adding an additional FPGA on the hardware basis of full-channel DRA. ML-CDRA requires fewer RF channels than the traditional full-channel array, while maintaining a similar digital beamforming (DBF) performance. This provides a practical solution to the typical problems in the existing low-cost DBF systems, such as synchronization, moving target compensation, and being disabled at a low signal-to-noise ratio. The performance of ML-CDRA is evaluated in simulations.
An Investigation of Winter Wheat Leaf Area Index Fitting Model Using Spectral and Canopy Height Model Data from Unmanned Aerial Vehicle Imagery
Authors: Zhang Xuewei , Zhang Kefei , Wu Suqin , Shi Hongtao , Sun Yaqin , Zhao Yindi , Fu Erjiang , Chen Shuo , Bian Chaofa , Ban Wei
Published: October 2022

The leaf area index (LAI) is critical for the respiration, transpiration, and photosynthesis of crops. Color indices (CIs) and vegetation indices (VIs) extracted from unmanned aerial vehicle (UAV) imagery have been widely applied to the monitoring of the crop LAI. However, when the coverage of the crop canopy is large and only spectral data are used to monitor the LAI of the crop, the LAI tends to be underestimated. The canopy height model (CHM) data obtained from UAV-based point clouds can represent the height and canopy structure of the plant. However, few studies have been conducted on the use of the CHM data in the LAI modelling. Thus, in this study, the feasibility of combining the CHM data and CIs and VIs, respectively, to establish LAI fitting models for winter wheat in four growth stages was investigated, and the impact of image resolution on the extraction of remote sensing variables (the CHM data, CIs, and VIs) and on the accuracy of the LAI models was evaluated. Experiments for acquiring remote sensing images of wheat canopies during the four growth stages from the RGB and multispectral sensors carried by a UAV were carried out. The partial least squares regression (PLSR), random forest regression (RFR), and support vector machine regression (SVR) were used to develop the LAI fitting models. Results showed that the accuracy of the wheat LAI models can be improved in the entire growth stages by the use of the additional CHM data with the increment of 0.020–0.268 in R2 for three regression methods. In addition, the improvement from the Cis-based models was more noticeable than the Vis-based ones. Furthermore, the higher the spatial resolution of the CHM data, the better the improvement made by the use of the additional CHM data. This result provides valuable insights and references for UAV-based LAI monitoring.
A Bilevel Optimization Model Based on Edge Computing for Microgrid
Authors: Chen Yi , Hayawi Kadhim , Fan Meikai , Chang Shih Yu , Tang Jie , Yang Ling , Zhao Rui , Mao Zhongqi , Wen Hong
Published: October 2022

With the continuous progress of renewable energy technology and the large-scale construction of microgrids, the architecture of power systems is becoming increasingly complex and huge. In order to achieve efficient and low-delay data processing and meet the needs of smart grid users, emerging smart energy systems are often deployed at the edge of the power grid, and edge computing modules are integrated into the microgrids system, so as to realize the cost-optimal control decision of the microgrids under the condition of load balancing. Therefore, this paper presents a bilevel optimization control model, which is divided into an upper-level optimal control module and a lower-level optimal control module. The purpose of the two-layer optimization modules is to optimize the cost of the power distribution of microgrids. The function of the upper-level optimal control module is to set decision variables for the lower-level module, while the function of the lower-level module is to find the optimal solution by mathematical methods on the basis of the upper-level and then feed back the optimal solution to the upper-layer. The upper-level and lower-level modules affect system decisions together. Finally, the feasibility of the bilevel optimization model is demonstrated by experiments.
SenseHunger: Machine Learning Approach to Hunger Detection Using Wearable Sensors
Authors: Irshad Muhammad Tausif , Nisar Muhammad Adeel , Huang Xinyu , Hartz Jana , Flak Olaf , Li Frédéric , Gouverneur Philip , Piet Artur , Oltmanns Kerstin M. , Grzegorzek Marcin
Published: October 2022

The perception of hunger and satiety is of great importance to maintaining a healthy body weight and avoiding chronic diseases such as obesity, underweight, or deficiency syndromes due to malnutrition. There are a number of disease patterns, characterized by a chronic loss of this perception. To our best knowledge, hunger and satiety cannot be classified using non-invasive measurements. Aiming to develop an objective classification system, this paper presents a multimodal sensory system using associated signal processing and pattern recognition methods for hunger and satiety detection based on non-invasive monitoring. We used an Empatica E4 smartwatch, a RespiBan wearable device, and JINS MEME smart glasses to capture physiological signals from five healthy normal weight subjects inactively sitting on a chair in a state of hunger and satiety. After pre-processing the signals, we compared different feature extraction approaches, either based on manual feature engineering or deep feature learning. Comparative experiments were carried out to determine the most appropriate sensor channel, device, and classifier to reliably discriminate between hunger and satiety states. Our experiments showed that the most discriminative features come from three specific sensor modalities: Electrodermal Activity (EDA), infrared Thermopile (Tmp), and Blood Volume Pulse (BVP).
An Adaptive Task-Related Component Analysis Method for SSVEP Recognition
Authors: Oikonomou Vangelis P.
Published: October 2022

Steady-State Visual Evoked Potential (SSVEP) recognition methods use a subject’s calibration data to differentiate between brain responses, hence, providing the SSVEP-based brain–computer interfaces (BCIs) with high performance. However, they require sufficient calibration EEG trials to achieve that. This study develops a new method to learn from limited calibration EEG trials, and it proposes and evaluates a novel adaptive data-driven spatial filtering approach for enhancing SSVEP detection. The spatial filter learned from each stimulus utilizes temporal information from the corresponding EEG trials. To introduce the temporal information into the overall procedure, a multitask learning approach, based on the Bayesian framework, is adopted. The performance of the proposed method was evaluated into two publicly available benchmark datasets, and the results demonstrated that our method outperformed competing methods by a significant margin.
A Novel Background Modeling Algorithm for Hyperspectral Ground-Based Surveillance and Through-Foliage Detection
Authors: Schreiber David , Opitz Andreas
Published: October 2022

Foliage penetration is an unsolved important part of border surveillance of remote areas between regular border crossing points. Detecting penetrating objects (e.g., persons and cars) through dense foliage in various climate conditions using visual sensors is prone to high fault rates. Through-foliage scenarios contain an unprecedented amount of occlusion—in fact, they often contain fragmented occlusion (for example, looking through the branches of a tree). Current state-of-the-art detectors based on deep learning perform inadequately under moderate-to-heavy fragmented occlusion. The FOLDOUT project builds a system that combines various sensors and technologies to tackle this problem. Consequently, a hyperspectral sensor was investigated due to its extended spectral bandwidth, beyond the range of typical RGB sensors, where vegetation exhibits pronounced reflectance. Due to the poor performance of deep learning approaches in through-foliage scenarios, a novel background modeling-based detection approach was developed, dedicated to the characteristics of the hyperspectral sensor, namely strong correlations between adjacent spectral bands and high redundancy. The algorithm is based on local dimensional reduction, where the principal subspace of each pixel is maintained and adapted individually over time. The successful application of the proposed algorithm is demonstrated in a through-foliage scenario comprised of heavy fragmented occlusion and a highly dynamical background, where state-of-the-art deep learning detectors perform poorly.
Photon-Trapping Microstructure for InGaAs/Si Avalanche Photodiodes Operating at 1.31 μm
Authors: Zhang Hewei , Tian Yang , Li Qian , Ding Wenqiang , Yu Xuzhen , Lin Zebiao , Feng Xuyang , Zhao Yanli
Published: October 2022

With the rapid development of photo-communication technologies, avalanche photodiode (APD) will play an increasingly important role in the future due to its high quantum efficiency, low power consumption, and small size. The monolithic integration of optical components and signal processing electronics on silicon substrate chips is crucial to driving cost reduction and performance improvement; thus, the technical research on InGaAs/Si APD is of great significance. This work is the first to demonstrate the use of a photon-trapping (PT) structure to improve the performance of the InGaAs/Si APD based on an SOI substrate, which exhibits very high absorption efficiency at 1310 nm wavelength while the thickness of the absorption layer is kept at 800 nm. Based on the optical and electrical simulations, an optimized InGaAs/Si PT-APD is proposed, which exhibits a better performance and a higher responsivity compared to the original InGaAs/Si APD.
A Hybrid Intelligent Simulation System for Building IoT Networks: Performance Comparison of Different Router Replacement Methods for WMNs Considering Stadium Distribution of IoT Devices
Authors: Barolli Admir , Sakamoto Shinji , Bylykbashi Kevin , Barolli Leonard
Published: October 2022

As the Internet of Things (IoT) devices and applications proliferate, it becomes increasingly important to design robust networks that can continue to meet user demands at a high level. Wireless local area networks (WLANs) can be a good choice as IoT infrastructure when high throughput is required. On the other hand, wireless mesh networks (WMNs), which are WLANs with mesh topology following the IEEE802.11s standard, have many advantages compared to conventional WLANs. Nevertheless, there are some problems that need solutions. One of them is the node placement problem. In this work, we propose and implement a hybrid intelligent system that solves this problem by determining the position of mesh nodes by maximizing the mesh connectivity and the coverage of IoT devices. The system is based on particle swarm optimization (PSO), simulated annealing (SA), and distributed genetic algorithm (DGA). We compare the performance of three router replacement methods: constriction method (CM), random inertia weight method (RIWM), and rational decrement of Vmax method (RDVM). The simulation results show that RIWM achieves better performance compared to CM and RDVM because it achieves the highest connectivity while covering more clients than the other two methods.
The Impact of Global Value Chain Embedding on Corporate Risk Taking of China’s A-Share Market-Listed Companies from 2000–2016
Authors: Wang Junli , Lv Wendong , Zhao Yao , Xu Na
Published: October 2022

Moving towards the high end of the global value chain (GVC) is an inevitable trend of the development of Chinese enterprises, and the level of enterprises’ risk-taking behavior is directly related to their profit acquisition in the global value chain. Based on the matching data of CSMAR and the “General Administration of Customs of the People’s Republic of China”, this paper explores how the embedding of the global value chain affects the risk-taking behavior of enterprises. It is found that (1) R&D investment is an important factor for listed companies to enhance their risk taking by embedding in the global value chain; however, financial constraints will negatively affect this factor. (2) The study’s findings also indicated that improving innovation capacity and increasing R&D investment is crucial for enterprises in developing countries to raise their corporate value. Moreover, it is helpful for enterprises to escape the jaws of danger in the GVC wave. It is advised that the government develop a financial market or enhance the external environment to encourage enterprises’ development. This study reveals the specific impact of global value chain embedding on corporate risk-taking behavior, provides new empirical evidence for understanding the micro mechanism of the relationship between global value chain embedding and economic growth, and has great practical significance for promoting Chinese enterprises to the high-end of the global value chain.
Assessing the Influence of Green Innovation on the Market Performance of Small- and Medium-Sized Enterprises
Authors: Zheng Shiyong , Ye Xinsen , Guan Weili , Yang Yuping , Li Jiaying , Li Biqing
Published: October 2022

Green innovation is a significant component of high-value growth closely linked to China’s 14th five-year plan. This research investigates the influence of green innovation on the market performance of small- and medium-sized enterprises (SMEs). The results are based on the primary data gathered via an online questionnaire survey from 453 respondents working for SMEs in China. The structural equation modeling approach is used for data analysis purposes. The research findings highlight that green innovation positively impacts marketing and products. In turn, marketing innovation positively influences product innovation and market performance, and product innovation also significantly boosts market performance. The study’s findings lead us to suggest that organizations in developing countries should focus on SMEs’ green innovation, which will support them in achieving an effective market performance. The study’s limitations are noted so the findings can be interpreted with caution, and directions for future research are outlined for all stakeholders.
Features of Agrarian Sector Deregulation in the Context of Martial Law: Shocks in Food Security
Authors: Mohylnyi Oleksii , Patyka Nataliia , Kucher Anatolii , Krupin Vitaliy , Siedlecka Agnieszka , Wysokiński Marcin
Published: October 2022

The purpose of this article is to reveal the peculiarities of the agrarian sector deregulation mechanisms in the conditions of the legal regime of martial law and the reasons for the vulnerability of the food security of the country and the world. The process of the agrarian sector deregulation in the period of the legal regime of martial law is clarified with regard to: (a) land matters; (b) taxation; (c) crediting; (d) material and technical support; (e) social and labor relations; and (f) state order. The elements of scientific novelty consist in the introduction of a systematic approach to the generalization of the extraordinary approaches to the process of agrarian sector deregulation during the legal regime of martial law. It is proposed to review the previously adopted documents of a strategic nature regarding the sustainable development of the agrarian sector of Ukraine and to change the mechanisms of the global food crisis fight radically by specially authorized international organizations. The experience of agrarian sector deregulation in the conditions of the legal regime of martial law can be taken into account by the state institutions when reviewing previously adopted documents and during the development of strategic plans for the restoration of the work of commodity producers, guaranteeing the food security of the population and taking into account the internal threats and the long-term external aggression of Russia against Ukraine.
Does Corporate ESG Performance Improve Export Intensity? Evidence from Chinese Listed Firms
Authors: Wu Qinglan , Chen Guifu , Han Jing , Wu Liyan
Published: October 2022

Although there have been numerous studies on environment, society, and governance (ESG), its impact on firm export has not often been examined. In this paper, we use the panel data of Chinese listed firms and a newly constructed ESG index to estimate the impact of ESG on firm export intensity. We further test the likely channels through which ESG can affect firm export intensity, including the innovation channel and financing constraints channel. The findings show that corporate ESG performance imposes a significantly positive impact on firm export intensity. The channel analysis shows that ESG influences export intensity through innovation and financing constraints. Lastly, heterogeneity analysis shows that the boosting effect of ESG on firms’ export intensity mainly originates from large firms and state-owned enterprises (SOEs) in the sample. This paper suggests that policymakers should pay attention to ESG, improve ESG information disclosure and give financial support to small non-SOEs.
Development of an Innovative Attachment Determining Friction Parameters for Quality Assessment in Sustainable Processing
Authors: Mazur Jacek , Różyło Renata , Wójcik Monika , Panasiewicz Marian , Zawiślak Kazimierz , Sobczak Paweł
Published: October 2022

New trends forcing the attractiveness of products in sustainable processing make it necessary to search for innovative methods of measuring their quality. For various biological materials, their physical properties, such as friction parameters in addition to their texture, are very important. Friction determines the course of many technological operations, e.g., transport, cleaning, sorting, fractionation, storage, and dosing of materials. An innovative friction adapter was developed for biological raw materials and tested on samples of self-produced soap. A 3D printing method for the production of this attachment was used. The soap sample loads were 100, 200, and 500 g, and the measurements of frictional resistance were carried out in contact with dry or water moistened synthetic leather, in comparison with sandpaper. For all tested variants (surfaces × loads), the initial friction of soap ranged from 0.853 N to 5.316 N, dynamic friction from 0.123 N to 3.542 N. The static and dynamic friction coefficients ranged from 0.019 to 0.151 and 0.006 to 0.131, respectively. The developed adapter for testing the friction coefficient ensures easy and quick assembly of the analyzed sample, its quick exchange and stable operation in both measurement directions, i.e., pushing and pulling the sample, as well as the possibility of using a lower applied load.