bluuebunny/crossref_metadata_2025 huggingface dataset:
Common Bean Productivity and Micronutrients in the Soil–Plant System under Residual Applications of Composted Sewage Sludge
Authors: Oliveira Gabriela Souza de , Jalal Arshad , Prates Adrielle Rodrigues , Teixeira Filho Marcelo Carvalho Minhoto , Alves Rodrigo Silva , Silva Luana Corrêa , Nascimento Raimunda Eliane Nascimento do , Silva Philippe Solano Toledo , Arf Orivaldo , Galindo Fernando Shintate , Oliveira Fernando Carvalho , Abreu-Junior Cassio Hamilton , Jani Arun Dilipkumar , Capra Gian Franco , Nogueira Thiago Assis Rodrigues
Published: May 2023

Composted sewage sludge (CSS) is an organic fertilizer that can be used as a source of micronutrients in agriculture. However, there are few studies with CSS to supply micronutrients for the bean crop. We aimed to evaluate micronutrient concentrations in the soil and their effects on nutrition, extraction, export, and grain yield in response to CSS residual application. The experiment was carried out in the field at Selvíria-MS, Brazil. The common bean cv. BRS Estilo was cultivated in two agricultural years (2017/18 and 2018/19). The experiment was designed in randomized blocks with four replications. Six different treatments were compared: (i) four increasing CSS rates, i.e., CSS5.0 (5.0 t ha−1 of applied CSS, wet basis), CSS7.5, CSS10.0, CSS12.5; (ii) a conventional mineral fertilizer (CF); (iii) a control (CT) without CSS and CF application. The available levels of B, Cu, Fe, Mn, and Zn were evaluated in soil samples collected in the 0–0.2 and 0.2–0.4 m soil surface horizons. The concentration, extraction, and export of micronutrients in the leaf and productivity of common beans were evaluated. The concentration of Cu, Fe, and Mn ranged from medium to high in soil. The available levels of B and Zn in the soil increased with the residual rates of CSS, which were statistically not different from the treatments with CF. The nutritional status of the common bean remained adequate. The common bean showed a higher requirement for micronutrients in the second year. The leaf concentration of B and Zn increased in the CSS7.5 and CSS10.0 treatments. There was a greater extraction of micronutrients in the second year. Productivity was not influenced by the treatments; however, it was higher than the Brazilian national average. Micronutrients exported to grains varied between growing years but were not influenced by treatments. We conclude that CSS can be used as an alternative source of micronutrients for common beans grown in winter.
Genome-Wide Identification and Abiotic-Stress-Responsive Expression of CKX Gene Family in Liriodendron chinense
Authors: Sun Xiao , Zhu Liming , Hao Zhaodong , Wu Weihuang , Xu Lin , Yang Yun , Zhang Jiaji , Lu Ye , Shi Jisen , Chen Jinhui
Published: May 2023

Liriodendron chinense is a tree species of the Magnoliaceae family, an ancient relict plant mainly used for landscaping and timber production due to its excellent material properties and ornamental value. The cytokinin oxidase/dehydrogenase (CKX) enzyme regulates cytokinin levels and plays an important role in plant growth, development, and resistance. However, too-high or too-low temperatures or soil drought can limit the growth of L. chinense, representing a key issue for research. Here, we identified the CKX gene family in the L. chinense genome and examined its transcriptional responses to cold, drought, and heat stresses. A total of five LcCKX genes, distributed on four chromosomes and divided into three phylogenetic groups, were identified across the whole L. chinense genome. Further analysis showed that multiple hormone- and stress-responsive cis-acting elements are located in the promoter regions of LcCKXs, indicating a potential role of these LcCKXs in plant growth, development, and response to environmental stresses. Based on existing transcriptome data, LcCKXs, especially LcCKX5, were found to transcriptionally respond to cold, heat, and drought stresses. Furthermore, quantitative reverse-transcription PCR (qRT-PCR) showed that LcCKX5 responds to drought stress in an ABA-dependent manner in stems and leaves and in an ABA-independent manner in roots. These results lay a foundation for functional research on LcCKX genes in the resistance breeding of the rare and endangered tree species of L. chinense.
A New Continuous Flow Microwave Radiation Process Design for Non-Isocyanate Polyurethane (NIPU)
Authors: Yang Ping-Lin , Tsai Sung-Han , Chen Kan-Nan , Wong David Shan-Hill
Published: May 2023

Non-isocyanate Polyurethane (NIPU) has been known to result from a thermal-ring-opening reaction between bis-cyclic carbonate (BCC) compounds and polyamines. BCC can be obtained from carbon dioxide capture using an epoxidized compound. Microwave radiation has been found to be an alternative process to conventional heating for synthesizing NIPU on a laboratory scale. The microwave radiation process is far more efficient (>1000 times faster) than using a conventional heating reactor. Now, a flow tube reactor has been designed for a continuous and recirculating microwave radiation system for scaling up NIPU. Furthermore, the TOE (Turn Over Energy) of the microwave for a lab batch (24.61 g) reactor was 24.38 kJ/g. This decreased to 8.89 kJ/g with an increase in reaction size of up to 300 times with this new continuous microwave radiation system. This proves that synthesizing NIPU with this newly-designed continuous and recirculating microwave radiation process is not only a reliable energy-saving method, but is also convenient for scale-up, making it a green process.
Facile UV-Induced Surface Covalent Modification to Fabricate Durable Superhydrophobic Fabric for Efficient Oil–Water Separation
Authors: Zhou Mengmeng , Liu Xiaohui , Xu Fengjiao , Pei Yongbing , Wu Lianbin , Tang Long-Cheng
Published: May 2023

In this work, a durable superhydrophobic fabric was fabricated by using a facile UV-induced surface covalent modification strategy. 2-isocyanatoethylmethacrylate (IEM) containing isocyanate groups can react with the pre-treated hydroxylated fabric, producing IEM molecules covalently grafted onto the fabric’s surface, and the double bonds of IEM and dodecafluoroheptyl methacrylate (DFMA) underwent a photo-initiated coupling reaction under UV light radiation, resulting in the DFMA molecules further grafting onto the fabric’s surface. The Fourier transform infrared, X-ray photoelectron spectroscopy and scanning electron microscopy results revealed that both IEM and DFMA were covalently grafted onto the fabric’s surface. The formed rough structure and grafted low-surface-energy substance contributed to the excellent superhydrophobicity (water contact angle of ~162°) of the resultant modified fabric. Notably, such a superhydrophobic fabric can be used for efficient oil–water separation, for example a high separation efficiency of over 98%. More importantly, the modified fabric exhibited excellent durable superhydrophobicity in harsh conditions such as immersion in organic solvents for 72 h, an acidic or alkali solution (pH = 1–12) for 48 h, undergoing laundry washing for 3 h, exposure to extreme temperatures (from −196° to 120°), as well as damage such as 100 cycles of tape-peeling and a 100-cycle abrasion test; the water contact angle only slightly decreased from ~162° to 155°. This was attributed to the IEM and DFMA molecules grated onto the fabric through stable covalent interactions, which could be accomplished using the facile strategy, where the alcoholysis of isocyanate and the grafting of DFMA via click coupling chemistry were integrated into one-step. Therefore, this work provides a facile one-step surface modification strategy for preparing durable superhydrophobic fabric, which is promising for efficient oil–water separation.
Calcium Carbonate Coating of 3D-Printed PLA ScaffoldsIntended for Biomedical Applications
Authors: Donate Ricardo , Paz Rubén , Quintana Álvaro , Bordón Pablo , Monzón Mario
Published: May 2023

The incorporation of ceramic additives is the most commonly used strategy to improve the biofunctionality of polymer-based scaffolds intended for bone regeneration. By embedding ceramic particles as a coating, the functionality improvement in the polymeric scaffolds can be concentrated on the cell–surface interface, thus creating a more favourable environment for the adhesion and proliferation of osteoblastic cells. In this work, a pressure-assisted and heat-induced method to coat polylactic acid (PLA) scaffolds with calcium carbonate (CaCO3) particles is presented for the first time. The coated scaffolds were evaluated by optical microscopy observations, a scanning electron microscopy analysis, water contact angle measurements, compression testing, and an enzymatic degradation study. The ceramic particles were evenly distributed, covered more than 60% of the surface, and represented around 7% of the coated scaffold weight. A strong bonding interface was achieved, and the thin layer of CaCO3 (~20 µm) provided a significant increase in the mechanical properties (with a compression modulus improvement up to 14%) while also enhancing the surface roughness and hydrophilicity. The results of the degradation study confirmed that the coated scaffolds were able to maintain the pH of the media during the test (~7.6±0.1), in contrast to the pure PLA scaffolds, for which a value of 5.07±0.1 was obtained. The ceramic-coated scaffolds developed showed potential for further evaluations in bone tissue engineering applications.
A New Method to Prepare Stable Polyaniline Dispersions for Highly Loaded Cathodes of All-Polymer Li-Ion Batteries
Authors: Tomšík Elena , Nosov Daniil R. , Ivanko Iryna , Pokorný Václav , Konefał Magdalena , Černochová Zulfiya , Tadyszak Krzysztof , Schmidt Daniel F. , Shaplov Alexander S.
Published: May 2023

A new method for the preparation of polyaniline (PANI) films that have a 2D structure and can record high active mass loading (up to 30 mg cm−2) via acid-assisted polymerization in the presence of concentrated formic acid was developed. This new approach represents a simple reaction pathway that proceeds quickly at room temperature in quantitative isolated yield with the absence of any byproducts and leads to the formation of a stable suspension that can be stored for a prolonged time without sedimentation. The observed stability was explained by two factors: (a) the small size of the obtained rod-like particles (50 nm) and (b) the change of the surface of colloidal PANI particles to a positively charged form by protonation with concentrated formic acid. The films cast from the concentrated suspension were composed of amorphous PANI chains assembled into 2D structures with nanofibrillar morphology. Such PANI films demonstrated fast and efficient diffusion of the ions in liquid electrolyte and showed a pair of revisable oxidation and reduction peaks in cyclic voltammetry. Furthermore, owing to the high mass loading, specific morphology, and porosity, the synthesized polyaniline film was impregnated by a single-ion conducting polyelectrolyte-poly(LiMn-r-PEGMm) and characterized as a novel lightweight all-polymeric cathode material for solid-state Li batteries by cyclic voltammetry and electrochemical impedance spectroscopy techniques.
Preparation and Properties of Medium-Density Fiberboards Bonded with Vanillin Crosslinked Chitosan
Authors: Cao Yanwei , Qin Chen , Zhao Zhengbo , Wang Zhe , Jin Chunde
Published: May 2023

An eco-friendly medium-density fiberboard (MDF) was prepared using vanillin (V) crosslinked chitosan (CS) adhesive through a hot-pressing process. The cross-linking mechanism and the effect of different proportions of added chitosan/vanillin on the mechanical properties and dimensional stability of MDF were investigated. The results showed that vanillin and chitosan are crosslinked to form a three-dimensional network structure due to the Schiff base reaction between the aldehyde group of vanillin and the amino group of chitosan. At the same time, when the mass ratio between vanillin/chitosan was 2:1, MDF obtained the best mechanical properties, the maximum modulus of rupture (MOR) of 20.64 MPa, the mean modulus of elasticity (MOE) of 3005 MPa, the mean internal bonding (IB) of 0.86 MPa, and the mean thickness swelling (TS) of 14.7%. Therefore, the MDF bonded with V-crosslinked CS can be a promising candidate for environmentally-friendly wood-based panels.
Numerical Simulation Study on the Influence of Twist Tape Parameters on Hydrate Particle Deposition
Authors: Wang Shuli , Rao Yongchao , Hao Chengming , Yao Jing , Zhou Shidong
Published: May 2023

Numerical simulation is used to carry out research on the swirl flow transportation of a hydrate in the pipeline under the condition of the whole rotation of the twist tape using DPM (discrete phase modeling) and RNG (renormalization group) k-ε. The influence of different twist tape parameters on the swirl number and concentration distribution of hydrate particles is analyzed. The structure parameters of the twist tape are optimized, based on the swirl efficiency evaluation parameters of a gas-solid two-phase pipeline. Finally, the twist tape is compared with different working conditions: the local rotation of twist tape and an ordinary pipeline. The results show that the areas of a high concentration of particles are near the twist tapes, and the concentration of particles on the leeward side of the twist tapes is higher than that on the windward side. The minimum concentration area at the axial position gradually increases with the increase of the flow distance, and the hydrate particles do not deposit at the bottom of the whole pipe section. The placement angle of the twist tape is greater, and the particle concentration area near the twist tape is also larger. The best placement angle is 25°. Under the condition of constant swirl strength, the range of the high particle concentration area will not increase indefinitely, and it is constant when the height of the twist tape is D/6 and the optimal height is D/6. There should not be too many twist tapes, as this will affect the carrying effect. The optimal number of twist tapes is three. The particle carrying distance of the local swirl flow generation is about double that of the ordinary pipe. The particle carrying distance of the four twist tape pipes is 3.5 times greater than that of the ordinary pipe. The particle carrying distance of the whole swirl flow generation is 6.6 times higher than that of the ordinary pipe. The particle carrying effect is 89% higher than that of the four twist tape pipes. The particle carrying effect is 230% higher than that of the local swirl flow generation. The particle carrying effect is 560% higher than that of the ordinary pipe.
Scanning Three-Dimensional X-ray Diffraction Microscopy with a Spiral Slit
Authors: Hayashi Yujiro , Setoyama Daigo , Fukuda Kunio , Okuda Katsuharu , Katayama Naoki , Kimura Hidehiko
Published: May 2023

Recently, nondestructive evaluation of the stresses localized in grains was achieved for plastically deformed low-carbon steel using scanning three-dimensional X-ray diffraction (S3DXRD) microscopy with a conical slit. However, applicable metals and alloys were restricted to a single phase and evaluated stress was underestimated due to the fixed Bragg angles of the conical slit optimized to αFe. We herein propose S3DXRD with a rotating spiral slit adaptable to various metals and alloys and accurate stress evaluation with sweeping Bragg angles. Validation experiments with a 50-keV X-ray microbeam were conducted for low-carbon steel as a body-centered cubic (BCC) phase and pure Cu as a face-centered cubic (FCC) phase. As a result of orientation mapping, polygonal grain shapes and clear grain boundaries were observed for both BCC and FCC metals. Thus, it was demonstrated that S3DXRD with a rotating spiral slit will be applicable to various metals and alloys, multiphase alloys, and accurate stress evaluation using a X-ray microbeam with a higher photon energy within an energy range determined by X-ray focusing optics. In principle, this implies that S3DXRD becomes applicable to larger and thicker metal and alloy samples instead of current miniature test or wire-shaped samples if a higher-energy X-ray microbeam is available.
Cloaked “Pagods”: Portuguese and “Heathen” Churches in Sixteenth-Century Malabar
Authors: Menon Arathi
Published: May 2023

Vasco da Gama’s arrival in Malabar on 21 May 1498, would hasten an epoch of social and cultural transformation in Malabar’s history. This article examines one development of this transformative period. Namely, it seeks to understand how the arrival of a people who came in search of “Christians and spices” would result in lasting changes to the form and the style of Christian architecture in Malabar, in present-day Kerala (southwest India). It highlights the efforts of the Estado da Índia (Portuguese State of India) to reconcile concomitant political, religious, and economic ambitions in the region by broadly sketching interventions to the practice of Christianity and the architectural style of churches in sixteenth-century Malabar. The article further proposes the reading of Portuguese-style façades in churches that, to the Portuguese, recalled Hindu temples or “pagods” as an interventional program to hide or cloak the political, religious, and historical portent of the traditional Malabar church.
A Review of Critical Element Concentrations in High Enthalpy Geothermal Fluids in New Zealand
Authors: Sajkowski Lucjan , Turnbull Rose , Rogers Karyne
Published: May 2023

This review compiles publicly available datasets describing the chemical composition of geothermal fluids from eight wells in the Taupo Volcanic Zone (TVZ) and Ngāwhā, New Zealand. Our review allows previously reported geothermal reservoir water compositions at various locations around the TVZ (and Ngāwhā) to be assessed and compared for the first time. The combined data present a new perspective on potential critical elements of geothermal resources and will be a valuable tool for future research projects and investment opportunities. Composition data were used to estimate the annual flux of different elements in New Zealand geothermal systems. Several elements found in New Zealand geothermal fluids are currently considered ‘critical’ for the transition to a carbon-neutral economy and are present in economically extractable quantities. We estimate that each year, approximately 1100 tons of lithium pass as heat exchange fluids through Wairakei geothermal power station. An overview of the critical elemental capture and extractive potential from New Zealand’s geothermal fields is provided.
Quality Assessment and Classification of Feedstock for Bioenergy Applications Considering ISO 17225 Standard on Solid Biofuels
Authors: Toscano Giuseppe , De Francesco Carmine , Gasperini Thomas , Fabrizi Sara , Duca Daniele , Ilari Alessio
Published: May 2023

Biomass materials play a key role in the renewable energy market as they can serve as a suitable alternative to fossil fuels. However, the quality of the material entering bioenergy plants is often a cause of technical concern. Biomass quality assessment is crucial not only for energy characterization but also for environmental and operational aspects. The goal of this study is to characterize and classify the biomasses used by Italian power plants with reference to the quality classes stated by the ISO standard 17225:2021. A further objective is to verify the ability of the standard to classify heterogeneous and specific biomasses. In this study, more than 900 biomass samples were analyzed. The samples were collected from several Italian power plants with >5 MWe between 2010 and 2020, and the most important physical and chemical parameters were analyzed according to the international standards of reference. The results of the analyses were collected in a large dataset used for subsequent statistical analyses. Statistical analyses applied are Principal Component Analysis and Pearson correlation maps, which showed that the ash content is a fundamental and ideal parameter to assess the biomass quality. Results obtained demonstrate that herbaceous biomasses are of low quality mainly due to the high ash content; a relatively low ash content was found for woody biomasses.
Does the Rational Function Model’s Accuracy for GF1 and GF6 WFV Images Satisfy Practical Requirements?
Authors: Shan Xiaojun , Zhang Jingyi
Published: May 2023

The Gaofen-1 (GF-1) and Gaofen-6 (GF-6) satellites have acquired many GF-1 and GF-6 wide-field-view (WFV) images. These images have been made available for free use globally. The GF-1 WFV (GF-1) and GF-6 WFV (GF-6) images have rational polynomial coefficients (RPCs). In practical applications, RPC corrections of GF-1 and GF-6 images need to be completed using the rational function model (RFM). However, can the accuracy of the rational function model satisfy practical application requirements? To address this issue, a geometric accuracy method was proposed in this paper to evaluate the accuracy of the RFM of GF-1 and GF-6 images. First, RPC corrections were completed using the RFM and refined RFM, respectively. The RFM was constructed using the RPCs and Shuttle Radar Topography Mission (SRTM) 90 m DEM. The RFM was refined via affine transformation based on control points (CPs), which resulted in a refined RFM. Then, an automatic matching method was proposed to complete the automatic matching of GF-1/GF-6 images and reference images, which enabled us to obtain many uniformly distributed CPs. Finally, these CPs were used to evaluate the geometric accuracy of the RFM and refined RFM. The 14th-layer Google images of the corresponding area were used as reference images. In the experiments, the advantages and disadvantages of BRIEF, SIFT, and the proposed method were first compared. Then, the values of the root mean square error (RSME) of 10,561 Chinese, French, and Brazilian GF-1 and GF-6 images were calculated and statistically analyzed, and the local geometric distortions of the GF-1 and GF-6 images were evaluated; these were used to evaluate the accuracy of the RFM. Last, the accuracy of the refined RFM was evaluated using the eight GF-1 and GF-6 images. The experimental results indicate that the accuracy of the RFM for most GF-1 and GF-6 images cannot meet the actual use requirement of being better than 1.0 pixel, the accuracy of the refined RFM for GF-1 images cannot meet practical requirement of being better than 1.0 pixel, and the accuracy of the refined RFM for most GF-6 images meets the practical requirement of being better than 1.0 pixel. However, the RMSE values that meet the requirements are between 0.9 and 1.0, and the geometric accuracy can be further improved.
Texture Features Derived from Sentinel-2 Vegetation Indices for Estimating and Mapping Forest Growing Stock Volume
Authors: Fang Gengsheng , He Xiaobing , Weng Yuhui , Fang Luming
Published: May 2023

Forest growing stock volume (GSV, m3/ha) is an indispensable variable for forest resources supervision. Precise measurement of GSV is conducive to monitoring forest dynamics. Nevertheless, little research has explored the pattern pixel values and the function of texture features derived from a vegetation index (VI) for GSV prediction. In this study, we investigated combining linear regression or Random Forest with Sentinel-2 spectral predictors and image textures derived from spectral bands and vegetation indices, which were based on standard deviation values or mean values at the plot level, for predicting GSV of Masson pine, theropencedrymion and all the survey plots in Anji County, China. Specifically, ten groups of experiments encompassing combinations of spectral parameters and texture measures were established for detecting the potential of image textures based on two different image pixel statistics. The results showed that texture measures derived from VI were superior to spectral parameters or texture measures derived from spectral bands for estimating the GSV of single tree species. Moreover, texture features based on shortwave infrared bands or their related VI and the standard deviation at pixel level for spectral bands/indices were emphasized. Finally, the mean value at the plot level exhibited slightly stronger potential than the standard deviation in general.
A Two-Stage Aerial Target Localization Method Using Time-Difference-of-Arrival Measurements with the Minimum Number of Radars
Authors: Chen Jinming , Li Yu , Yang Xiaochao , Li Qi , Liu Fei , Wang Weiwei , Li Caipin , Duan Chongdi
Published: May 2023

Distributed radar systems promise to significantly enhance target localization by virtue of the superiority of multi-view observations from widely separated radars, compared to their monostatic counterparts. Nevertheless, when the radar number is limited, performing target localization bears the brunt of the parameter identifiability requirement that the parameter number must be no less than the number of independent measurements. In this way, the canonical two-stage target localization method, as well as its developments, is no longer appropriate for direct application. Hence, in this paper, we propose a novel target localization method using time-difference-of-arrival (TDOA) measurements with the minimum number of radars under platform position uncertainties. The referred distributed system is a bistatic multi-receiver system, where the primary signal is transmitted by a geostationary Earth orbit (GEO) satellite while receivers are equipped on several unmanned aerial vehicles (UAVs). In the first stage, the reference range from the reference radar to the target is estimated by a quadratic function, and then the weighted least squares (WLS) solution of the target location is updated by substituting the range estimate back into it. In the second stage, we invoke the Taylor series approximation to further refine the target localization obtained by the first stage. It can be foreseen that the developed method is beneficial for scenarios with a limited number of radars, including engineering projects such as fire control, surveillance, and guidance, to support high-accuracy target localization. The simulation results show the superiority of the localization performance of the proposed method over other existing methods.
Estimation of Winter Wheat Plant Nitrogen Concentration from UAV Hyperspectral Remote Sensing Combined with Machine Learning Methods
Authors: Chen Xiaokai , Li Fenling , Shi Botai , Chang Qingrui
Published: May 2023

Nitrogen is one of the most important macronutrients and plays an essential role in the growth and development of winter wheat. It is very crucial to diagnose the nitrogen status timely and accurately for applying a precision nitrogen management (PNM) strategy to the guidance of nitrogen fertilizer in the field. The main purpose of this study was to use three different prediction methods to evaluate winter wheat plant nitrogen concentration (PNC) at booting, heading, flowering, filling, and the whole growth stage in the Guanzhong area from unmanned aerial vehicle (UAV) hyperspectral imagery. These methods include (1) the parametric regression method; (2) linear nonparametric regression methods (stepwise multiple linear regression (SMLR) and partial least squares regression (PLSR)); and (3) machine learning methods (random forest regression (RFR), support vector machine regression (SVMR), and extreme learning machine regression (ELMR)). The purpose of this study was also to pay attention to the impact of different growth stages on the accuracy of the model. The results showed that compared with parametric regression and linear nonparametric regression, the machine learning regression method could evidently improve the estimation accuracy of winter wheat PNC, especially using SVMR and RFR, the training set of the model at flowering and filling stage explained 93% and 92% of the PNC variability respectively. The testing set of the model at flowering and filling stages explained 88% and 91% of the PNC variability, the root mean square error of the validation set (RMSEtesting) was 0.82 and 1.23, and the relative prediction deviation (RPD) was 2.58 and 2.40, respectively. Therefore, a conclusion was drawn that it was the best choice to estimate winter wheat PNC at the flowering and filling stage from UAV hyperspectral imagery. Using machine learning methods, SVMR and RFR, respectively, could achieve the most outstanding estimation performance, which could provide a theoretical basis for putting forward the PNM strategy.
From Model-Based Optimization Algorithms to Deep Learning Models for Clustering Hyperspectral Images
Authors: Huang Shaoguang , Zhang Hongyan , Zeng Haijin , Pižurica Aleksandra
Published: May 2023

Hyperspectral images (HSIs), captured by different Earth observation airborne and space-borne systems, provide rich spectral information in hundreds of bands, enabling far better discrimination between ground materials that are often indistinguishable in visible and multi-spectral images. Clustering of HSIs, which aims to unveil class patterns in an unsupervised way, is highly important in the interpretation of HSI, especially when labelled data are not available. A number of HSI clustering methods have been proposed. Among them, model-based optimization algorithms, which learn the cluster structure of data by solving convex/non-convex optimization problems, have achieved the current state-of-the-art performance. Recent works extend the model-based algorithms to deep versions with deep neural networks, obtaining huge breakthroughs in clustering performance. However, a systematic survey on the topic is absent. This article provides a comprehensive overview of clustering methods of HSI and tracked the latest techniques and breakthroughs in the domain, including the traditional model-based optimization algorithms and the emerging deep learning based clustering methods. With a new taxonomy, we elaborated on the main ideas, technical details, advantages, and disadvantages of different types of clustering methods of HSIs. We provided a systematic performance comparison between different clustering methods by conducting extensive experiments on real HSIs. Unsolved problems and future research trends in the domain are pointed out. Moreover, we provided a toolbox that contains implementations of representative clustering algorithms to help researchers to develop their own models.
Designing a Private and Secure Personal Health Records Access Management System: A Solution Based on IOTA Distributed Ledger Technology
Authors: Akbulut Serkan , Semantha Farida Habib , Azam Sami , Pilares Iris Cathrina Abacan , Jonkman Mirjam , Yeo Kheng Cher , Shanmugam Bharanidharan
Published: May 2023

The privacy and security of patients’ health records have been an ongoing issue, and researchers are in a race against technology to design a system that can help stop the compromising of patient data. Many researchers have proposed solutions; however, most solutions have not incorporated potential parameters that can ensure private and secure personal health records management, which is the focus of this study. To design and develop a solution, this research thoroughly investigated existing solutions and identified potential key contexts. These include IOTA Tangle, Distributed Ledger Technology (DLT), IPFS protocols, Application Programming Interface (API), Proxy Re-encryption (PRE), and access control, which are analysed and integrated to secure patient medical records, and Internet of Things (IoT) medical devices, to develop a patient-based access management system that gives patients full control of their health records. This research developed four prototype applications to demonstrate the proposed solution: the web appointment application, the patient application, the doctor application, and the remote medical IoT device application. The results indicate that the proposed framework can improve healthcare services by providing immutable, secure, scalable, trusted, self-managed, and traceable patient health records while giving patients full control of their own medical records.
Energy Aware Software Defined Network Model for Communication of Sensors Deployed in Precision Agriculture
Authors: Ahmed Shakeel
Published: May 2023

A significant technological transformation has recently occurred in the agriculture sector. Precision agriculture is one among those transformations that largely focus on the acquisition of the sensor data, identifying the insights, and summarizing the information for better decision-making that would enhance the resource usage efficiency, crop yield, and substantial quality of the yield resulting in better profitability, and sustainability of agricultural output. For continuous crop monitoring, the farmlands are connected with various sensors that must be robust in data acquisition and processing. The legibility of such sensors is an exceptionally challenging task, which needs energy-efficient models for handling the lifetime of the sensors. In the current study, the energy-aware software-defined network for precisely selecting the cluster head for communication with the base station and the neighboring low-energy sensors. The cluster head is initially chosen according to energy consumption, data transmission consumption, proximity measures, and latency measures. In the subsequent rounds, the node indexes are updated to select the optimal cluster head. The cluster fitness is assessed in each round to retain the cluster in the subsequent rounds. The network model’s performance is assessed against network lifetime, throughput, and network processing latency. The experimental findings presented here show that the model outperforms the alternatives presented in this study.
The Role of the Specific Strength Test in Handball Performance: Exploring Differences across Competitive Levels and Age Groups
Authors: Chirosa-Ríos Luis J. , Chirosa-Ríos Ignacio J. , Martínez-Marín Isidoro , Román-Montoya Yolanda , Vera-Vera José Fernando
Published: May 2023

The aim of this study was to determine if specific physical tests are sufficiently discriminant to differentiate players of similar anthropometric characteristics, but of different playing levels. Physical tests were conducted analyzing specific strength, throwing velocity, and running speed tests. Thirty-six male junior handball players (n = 36; age 19.7 ± 1.8 years; 185.6 ± 6.9 cm; 83.1 ± 10.3 kg; 10.6 ± 3.2 years of experience) from two different levels of competition participated in the study: NT = 18 were world top-level elite players, belonging to the Spanish junior men’s national team (National Team = NT) and A = 18 players of the same age and anthropometric conditions, who were selected from Spanish third league men’s teams (Amateur = A). The results showed significant differences (p < 0.05) between the two groups in all physical tests, except for two-step-test velocity and shoulder internal rotation. We conclude that a battery combining the Specific Performance Test and the Force Development Standing Test is useful in identifying talent and differentiating between elite and sub-elite players. The current findings suggest that running speed tests and throwing tests are essential in selecting players, regardless of age, sex, or type of competition. The results shed light on the factors that differentiate players of different levels and can help coaches in selecting players.
Human Behavior Recognition via Hierarchical Patches Descriptor and Approximate Locality-Constrained Linear Coding
Authors: Liu Lina , Wang Kevin I-Kai , Tian Biao , Abdulla Waleed H. , Gao Mingliang , Jeon Gwanggil
Published: May 2023

Human behavior recognition technology is widely adopted in intelligent surveillance, human–machine interaction, video retrieval, and ambient intelligence applications. To achieve efficient and accurate human behavior recognition, a unique approach based on the hierarchical patches descriptor (HPD) and approximate locality-constrained linear coding (ALLC) algorithm is proposed. The HPD is a detailed local feature description, and ALLC is a fast coding method, which makes it more computationally efficient than some competitive feature-coding methods. Firstly, energy image species were calculated to describe human behavior in a global manner. Secondly, an HPD was constructed to describe human behaviors in detail through the spatial pyramid matching method. Finally, ALLC was employed to encode the patches of each level, and a feature coding with good structural characteristics and local sparsity smoothness was obtained for recognition. The recognition experimental results on both Weizmann and DHA datasets demonstrated that the accuracy of five energy image species combined with HPD and ALLC was relatively high, scoring 100% in motion history image (MHI), 98.77% in motion energy image (MEI), 93.28% in average motion energy image (AMEI), 94.68% in enhanced motion energy image (EMEI), and 95.62% in motion entropy image (MEnI).
Fast-Convergence Reinforcement Learning for Routing in LEO Satellite Networks
Authors: Ding Zhaolong , Liu Huijie , Tian Feng , Yang Zijian , Wang Nan
Published: May 2023

Fast convergence routing is a critical issue for Low Earth Orbit (LEO) constellation networks because these networks have dynamic topology changes, and transmission requirements can vary over time. However, most of the previous research has focused on the Open Shortest Path First (OSPF) routing algorithm, which is not well-suited to handle the frequent changes in the link state of the LEO satellite network. In this regard, we propose a Fast-Convergence Reinforcement Learning Satellite Routing Algorithm (FRL–SR) for LEO satellite networks, where the satellite can quickly obtain the network link status and adjust its routing strategy accordingly. In FRL–SR, each satellite node is considered an agent, and the agent selects the appropriate port for packet forwarding based on its routing policy. Whenever the satellite network state changes, the agent sends “hello” packets to the neighboring nodes to update their routing policy. Compared to traditional reinforcement learning algorithms, FRL–SR can perceive network information faster and converge faster. Additionally, FRL–SR can mask the dynamics of the satellite network topology and adaptively adjust the forwarding strategy based on the link state. The experimental results demonstrate that the proposed FRL–SR algorithm outperforms the Dijkstra algorithm in the performance of average delay, packet arriving ratio, and network load balance.
Enhanced Neural Network Method-Based Multiscale PCA for Fault Diagnosis: Application to Grid-Connected PV Systems
Authors: Attouri Khadija , Mansouri Majdi , Hajji Mansour , Kouadri Abdelmalek , Bouzrara Kais , Nounou Hazem
Published: May 2023

In this work, an effective Fault Detection and Diagnosis (FDD) strategy designed to increase the performance and accuracy of fault diagnosis in grid-connected photovoltaic (GCPV) systems is developed. The evolved approach is threefold: first, a pre-processing of the training dataset is applied using a multiscale scheme that decomposes the data at multiple scales using high-pass/low-pass filters to separate the noise from the informative attributes and prevent the stochastic samples. Second, a principal component analysis (PCA) technique is applied to the newly obtained data to select, extract, and preserve only the more relevant, informative, and uncorrelated attributes; and finally, to distinguish between the diverse conditions, the extracted attributes are utilized to train the NNs classifiers. In this study, an effort is made to take into consideration all potential and frequent faults that might occur in PV systems. Thus, twenty-one faulty scenarios (line-to-line, line-to-ground, connectivity faults, and faults that can affect the normal operation of the bay-pass diodes) have been introduced and treated at different levels and locations; each scenario comprises various and diverse conditions, including the occurrence of simple faults in the PV1 array, simple faults in the PV2 array, multiple faults in PV1, multiple faults in PV2, and mixed faults in both PV arrays, in order to ensure a complete and global analysis, thereby reducing the loss of generated energy and maintaining the reliability and efficiency of such systems. The obtained outcomes demonstrate that the proposed approach not only achieves good accuracies but also reduces runtimes during the diagnosis process by avoiding noisy and stochastic data, thereby removing irrelevant and correlated samples from the original dataset.
How Design Is Appropriated: Understanding Habitation through the Observation of Situated Behavior
Authors: Chiesi Leonardo , Costa Paolo
Published: May 2023

The relationship between people and designed space is often approached exclusively with text-based research techniques (e.g., interviews and questionnaires). After proposing a theoretical framework for design from a sociological perspective, this paper first illustrates the limitations of those techniques when investigating appropriation of designed space, i.e., situated behaviors and perceptions. Then, the observation of socio-environmental indicators is proposed as a research technique, illustrating how this unobtrusive approach overcomes some of those limitations, allowing the study of habitation through the observation of effects of behaviors rather than the behavior itself. A taxonomy of socio-environmental indicators is introduced, showing how five categories can be construed (i.e., traces, alterations, adaptations, signs, and routines) for the analysis of habitation of designed spaces at various level of scales, from the proxemic space around the body to the larger designed environment. Certain specific examples are discussed, showing how indicators can be analyzed, generating insights and the formulation of hypotheses that may be further investigated triangulating with other research techniques. After discussing the limitations of this technique, the paper reflects on how its application contributes to a dialogical appreciation of design.
Exercise-Induced Fatigue Impairs Change of Direction Performance and Serve Precision among Young Male Tennis Players
Authors: Bilić Zlatan , Sinković Filip , Barbaros Petar , Novak Dario , Zemkova Erika
Published: May 2023

This study investigates the effect of exercise-induced fatigue on change of direction performance and serve precision among young tennis players. A group of 21 players (age 12.90 ± 0.76 years), ranked among the top 50 players on the national tennis federation scale and the top 300 on the “Tennis Europe” scale, participated in the study. They underwent a standardized physiological load protocol using the “300-m running test” which consists of consecutive runs for 15 shares of 20 m (15 × 20). Its intensity was determined using the Borg Rating of Perceived Exertion (RPE) scale where subjects evaluated their level of experienced load on a scale from 0 to 10. Prior to and after the protocol, they performed a pre-planned change of direction T-test and serve precision test. Results showed significant increase of time in the T-test (from 11.75 ± 0.45 s to 12.99 ± 0.4 s, p = 0.00) and decrease in serve precision parameter from (6.00 ± 1.04 to 4.00 ± 1.26, p = 0.00) after the fatigue test protocol. The RPE increased from 5 to 9, after the fatigue protocol, indicating the desired fatigue effect. These findings indicate that exercise-induced fatigue impairs change of direction performance and serve precision among young tennis players.
A New Approach to Extracting Tourism Focus Points from Chinese Inbound Tourist Reviews after COVID-19
Authors: Liu Zhenzhen , Masui Fumito , Eronen Juuso , Terashita Shun , Ptaszynski Michal
Published: May 2023

The number of inbound tourists in Japan has been increasing steadily in recent years. However, due to the COVID-19 pandemic, the number of inbound tourists decreased in 2020. This is particularly worrisome for Japan, as the number of inbound tourists is expected to reach 60 million per year by 2030. In order to help Japan’s tourism industry to recover from the pandemic, we propose a method of identifying elements that attract the attention of inbound tourists (focus points) by analyzing reviews on tourist sites. We focus on Hokkaido, a popular area in Japan for tourists from China. Our proposed method extracts high-frequency n-gram patterns from reviews written by Chinese inbound tourists, showing which aspects are mentioned most often. We then use seven types of motivational factors for tourists and principal component analysis to quantify the focus points of each tourist destination. Finally, we estimate the focus points by clustering the n-gram patterns extracted from the tourists’ reviews. The results show that our method successfully identifies the features and focus points of each tourist spot.
A Realistic and Practical Guide for Creating Intelligent Integrated Solutions in Higher Education Using Enterprise Architecture
Authors: Lamey Ahmed , Abdelkader Hatem , Keshk Arabi , Eletriby Sherif
Published: May 2023

Enterprise architecture (EA) plays a crucial role in organizations by providing a clear strategy for digital transformation and seamless information flow across boundaries. It is a tool for achieving current and future objectives effectively. By providing a comprehensive view, EA helps organizations build suitable and sustainable software solutions while avoiding complex challenges caused by unmanageable information flow blockages. Moreover, EA provides a standard framework for implementing enterprise resource planning (ERP) systems. Although EA and ERP systems have different concepts, they possess complementary characteristics that support decision-makers in the ERP selection process, which can be quite risky due to cost feasibility, time consumption, and team effort. This study proposes using the EA concept as a reference module for selecting the most suitable integrated solution for the higher education sector. The aim is to provide high-impact criteria for choosing the most appropriate ERP system as a core solution. Additionally, EA supports other related solutions integrated with the ERP system under the EA umbrella to run a fully automated smart entity. To determine the most suitable ERP solution for higher education entities in the study country, a set of critical criteria for ERP selection as a core solution in the education sector is generated through brainstorming, which is based on an EA reference module specifically designed for higher education entities that seek to operate smartly. A comparison technique is employed to evaluate the highlighted criteria, including a case study for ABC University. The study’s results reveal that fully integrated and sustainable solutions can be envisioned for higher education entities, which can support the digital transformation of the higher education sector based on a smart EA reference module along with a set of critical main ERP selection criteria. This can mitigate the risk associated with ERP selection as a core solution and support decision-makers in selecting the most suitable ERP package for educational entities.