bluuebunny/crossref_metadata_2025 huggingface dataset:
Facts, Concepts and Patterns of Life—Or How to Change Things with Words
Authors: Trächtler Jasmin
Published: July 2023

In his last writings, Wittgenstein repeatedly addresses the question of how our concepts relate to general facts of nature or human nature and how they are embedded in our lives. In doing so, he uses the term “pattern of life”, characterizing the complicated relationship between concepts and our lives and how our concepts “are connected with what interests us, with what matters to us” (LWPP II, 46). But who is this “us”, and whose interests manifest in the concepts we use to designate patterns of life? What if certain concepts—or their absence—are exclusionary, discriminatory, or otherwise unjust to those who are not “us”? In this paper, I want to discuss Wittgenstein’s notion of “pattern of life” in its interweaving with facts, human life, and concepts, as well as its political implications. To this end, I will first outline the relationship between facts and concept formation as Wittgenstein drew it in his last writings. Based on this, I will argue that he uses the concept of pattern of life to capture the complicated relationship between concepts and human nature or “social facts”. Going beyond Wittgenstein and drawing on recent feminist epistemology, I will raise the question of the political implications of our patterns of life and concomitant social “conceptual injustices”. Finally, I will show how imagining facts otherwise and other conceptual worlds can help us to reveal the prejudices and injustices of our concepts and can lead to conceptual change and new patterns of life that may ultimately even change “things”, i.e., our thinking, judging and acting in the world.
Design of Silicon Photonics Integrated Bulk Zigzag and Sinusoidal Structured Mode Conversion Devices Using Genetic Algorithm (GA) Optimization
Authors: Yu Tien-Wei , Chow Chi-Wai , Kuo Pin-Cheng , Lin Yuan-Zeng , Hung Tun-Yao , Jian Yin-He , Yeh Chien-Hung
Published: July 2023

To increase the optical interconnect transmission capacity, different multiplexing technologies, including wavelength division multiplexing (WDM), polarization division multiplexing (PolDM) and mode division multiplexing (MDM), can be utilized. Among them, MDM is a promising technique in silicon photonics (SiPh) integrated optical interconnects since higher order modes can be easily generated and preserved in SiPh waveguides. In this work, we propose and demonstrate the designs of SiPh-based bulk zigzag and sinusoidal structured MDM mode conversion devices using genetic algorithm (GA) optimization. A traditional periodic zigzag structured mode converter design has many sharp zigzag angles in the periodic structure, which are very sensitive to the fabrication error. Here, first of all, we propose and demonstrate a bulk zigzag structure to achieve MDM mode conversion. The proposed bulk zigzag structure can reduce the zigzag angle error as a large number of zigzag angles in the periodic structure are eliminated. Moreover, we further improve our device by proposing a bulk sinusoidal structure to further eliminate the zigzag angle. Results show that both the proposed bulk zigzag and sinusoidal MDM mode converters can still maintain high transmissions of >86%, while the mode conversion lengths of both devices can be significantly reduced by >60% in the C-band wavelength window. In addition, as there are many degrees of freedom (DOFs) during the design of the SiPh mode converter, including the waveguide width, length, period, zigzag angle, etch depth, duty cycle, etc., the GA optimization algorithm is employed. Here, detailed implementation of the GA optimization is discussed.
Elastomer Nanocomposites: Effect of Filler–Matrix and Filler–Filler Interactions
Authors: Bokobza Liliane
Published: July 2023

The reinforcement of elastomers is essential in the rubber industry in order to obtain the properties required for commercial applications. The addition of active fillers in an elastomer usually leads to an improvement in the mechanical properties such as the elastic modulus and the rupture properties. Filled rubbers are also characterized by two specific behaviors related to energy dissipation known as the Payne and the Mullins effects. The Payne effect is related to non-linear viscoelastic behavior of the storage modulus while the Mullins or stress-softening effect is characterized by a lowering in the stress when the vulcanizate is extended a second time. Both effects are shown to strongly depend on the interfacial adhesion and filler dispersion. The basic mechanisms of reinforcement are first discussed in the case of conventional rubber composites filled with carbon black or silica usually present in the host matrix in the form of aggregates and agglomerates. The use of nanoscale fillers with isotropic or anisotropic morphologies is expected to yield much more improvement than that imparted by micron-scale fillers owing to the very large polymer–filler interface. This work reports some results obtained with three types of nanoparticles that can reinforce rubbery matrices: spherical, rod-shaped and layered fillers. Each type of particle is shown to impart to the host medium a specific reinforcement on account of its own structure and geometry. The novelty of this work is to emphasize the particular mechanical behavior of some systems filled with nanospherical particles such as in situ silica-filled poly(dimethylsiloxane) networks that display a strong polymer–filler interface and whose mechanical response is typical of double network elastomers. Additionally, the potential of carbon dots as a reinforcing filler for elastomeric materials is highlighted. Different results are reported on the reinforcement imparted by carbon nanotubes and graphenic materials that is far below their expected capability despite the development of various techniques intended to reduce particle aggregation and improve interfacial bonding with the host matrix.
Bond Performance of CFRP Strands to Grouting Admixture for Prestressed Structure and Development of Their Bond–Slip Constitutive Models
Authors: Wang Ce , Guan Shuai , Sabbrojjaman Md , Tafsirojjaman T.
Published: July 2023

Prestressed concrete structures have witnessed widespread use in building and infrastructure applications during the last two decades due to their high stiffness and strength indices. However, structural failures caused by the corrosion of steel reinforcing bars or strands have proliferated, opening the door for carbon fibre-reinforced polymer (CFRP) strands as an excellent alternative with high corrosion resistance. The bonding interaction between the CFRP strands and concrete is the fundamental parameter in shaping the structural behaviour of CFRP prestressed concrete structures. In this paper, the bonding behaviour between CFRP strands and concrete with grouting admixture is experimentally investigated based on three groups of standard pull-out tests. The bond strength of CFRP strands was systematically studied and compared against steel strands. The untreated CFRP strands exhibited an inefficient bonding strength with the grouting admixture, equivalent to only 5% compared to steel strands of the same diameter. Surface coating with epoxy quartz sand can significantly improve the anchoring efficiency of CFRP strands up to 14 times compared to the untreated strands, which is approximately as efficient as steel strands. Moreover, the bond–slip curves between CFRP strands and concrete were analysed and were found to be different compared to steel strands. Finally, this study proposed bond–slip constitutive models of CFRP strands with better applicability, using an exponentially damped sine function to fit the residual segment of the curve.
Effect of Long-Term Aging on Fatigue and Thermal Cracking Performance of Polyphosphoric Acid and Styrene–Butadiene–Styrene-Modified Bio-Blend Bitumen
Authors: Wang Haitao , Du Zhongming , Liu Guiyong , Luo Xiaofeng , Yang Chunlu
Published: July 2023

Polyphosphoric acid (PPA) and styrene–butadiene–styrene (SBS) were adopted to produce PPA-SBS-modified bio-blend bitumen, which achieved excellent mechanical performance. However, its long-range performance, such as the fatigue and thermal cracking behavior under long-term thermal oxidation, is not well understood. Therefore, a pressure aging vessel (PAV) system was applied to simulate the aging behavior of the bitumen under the action of thermal oxidation. Then, a linear amplitude sweep (LAS) test combined with a viscoelastic continuum damage (VECD) model was applied to investigate the fatigue properties of the bitumen. Moreover, a bending beam rheometer (BBR) test was conducted to evaluate the thermal cracking resistance of the bitumen before and after PAV aging. Meanwhile, an atomic force microscope (AFM) was applied to observe the microscopic topography. The results show that the original compound-modified bitumen can bear more fatigue damage than that of the control bitumen at the failure point, and it also has excellent fatigue resistance at 2.5%, 5%, 7.5%, and 10% applied strain. Moreover, the VECD model can accurately predict the fatigue life of the bitumen under different applied strains. The variation ratio of stiffness modulus for the compound-modified bitumen is below that of the control bitumen after PAV aging, so it shows a better anti-aging performance. Finally, the AFM test shows that PPA and bio-bitumen decrease the heterogeneity of the bitumen, reducing the difference between phases.
The Use of Hot Melt Extrusion to Prepare a Solid Dispersion of Ibuprofen in a Polymer Matrix
Authors: Biedrzycka Kinga , Marcinkowska Agnieszka
Published: July 2023

In this work, we report the use of the hot melt extrusion method in harsh extrusion conditions, i.e., screw rotation speed of 250 rpm, temperature above 100 °C, and two mixing zones, in order to obtain an amorphous dispersion of an active pharmaceutical ingredient (API) that is sparingly soluble in water. As a polymer matrix Eudragit EPO (E-EPO) and as an API ibuprofen (IBU) were used in the research. In addition, the plasticizer Compritol 888 ATO (COM) was tested as a factor potentially improving processing parameters and modifying the IBU release profile. In studies, 25% by weight of IBU, 10% of COM and various extrusion temperatures, i.e., 90, 100, 120, 130, and 140 °C, were used. Hot melt extrusion (HME) temperatures were selected based on the glass transition temperature of the polymer matrix (Tg = 42 °C) and the melting points of IBU (Tm = 76 °C) and COM (Tm = 73 °C), which were tested by differential scanning calorimetry (DSC). The thermal stability of the tested compounds, determined on the basis of measurements carried out by thermogravimetric analysis (TGA), was also taken into account. HME resulted in amorphous E-EPO/IBU solid dispersions and solid dispersions containing a partially crystalline plasticizer in the case of E-EPO/IBU/COM extrudates. Interactions between the components of the extrudate were also studied using infrared spectroscopy (FTIR-ATR). The occurrence of such interactions in the studied system, which improve the stability of the obtained solid polymer dispersions, was confirmed. On the basis of DSC thermograms and XRPD diffractograms, it was found that amorphous solid dispersions were obtained. In addition, their stability was confirmed in accelerated conditions (40 °C, 75% RH) for 28 days and 3 months. The release profiles of prepared tablets showed the release of 40% to 63% of IBU from the tablets within 180 min in artificial gastric juice solution, with the best results obtained for tablets with E-EPO/IBU extrudate prepared at a processing temperature of 140 °C.
Effective Interaction between Homo- and Heteropolymer Block of Poly(n-butyl acrylate)-b-poly(methyl methacrylate-r-styrene) Diblock Copolymers
Authors: Lee Sang-In , Seo Min-Guk , Huh June , Paik Hyun-jong
Published: July 2023

We investigated the segregation behavior of a molten diblock copolymer, poly(n-butyl acrylate)-b-poly(methyl methacrylate-r-styrene) (PBA-b-P(MMA-r-S)), wherein styrene (S) is incorporated as a comonomer in the second block to modulate the effective interaction between homopolymer and a random copolymer block. The temperature dependence of the effective interaction parameter χeff between n-butyl acrylate (BA) and the average monomer of the MMA-r-S random block was evaluated from small-angle X-ray scattering (SAXS) analysis using the random phase approximation (RPA) approach. The calculated χeff, as a function of the styrene fraction in the random copolymer block, shows a good agreement with the mean-field binary interaction model. This consistency indicates that the effective interaction between component BA and the average monomer of the random copolymer block is smaller than the interactions between pure components (χBA,MMA,χBA,S). The present study suggests that the introduction of a random copolymer block to a block copolymer can effectively reduce the degree of incompatibility of the block copolymer system without altering the constituent species, which may serve as a viable methodology in designing novel thermoplastic elastomers based on triblock or multiblock copolymers.
Synthesis and Evaluation of Metal Lipoate Adhesives
Authors: Ghosh Animesh , Kozlowski Konrad , Steele Terry W. J.
Published: July 2023

The development of new bioadhesives with integrated properties remains an unmet clinical need to replace staples or sutures. Current bioadhesives do not allow electronic activation, which would allow expansion into laparoscopic and robotic surgeries. To address this deficiency, voltage-activated adhesives have been developed on both carbene- and catechol-based chemical precursors. Herein, a third platform of voltage-activated adhesive is evaluated based on lipoic acid, a non-toxic dithiolane found in aerobic metabolism and capable of ring-opening polymerization. The electro-rheological and adhesive properties of lithium, sodium, and potassium salts of lipoic acid are applied for wet tissue adhesion. At ambient conditions, potassium lipoate displays higher storage modulus than lithium or sodium salt under similar conditions. Voltage stimulation significantly improves gelation kinetics to Na- and K-lipoates, while Li-lipoate is found to not require voltage stimulation for gelation. Lap shear adhesion strength on wetted collagen substrates reveals that the synthetic metal lipoates have comparable adhesion strength to fibrin sealants without viral or ethical risks.
Influence of Molecular Weight on Thermal and Mechanical Properties of Carbon-Fiber-Reinforced Plastics Based on Thermoplastic Partially Crystalline Polyimide
Authors: Vaganov Gleb , Simonova Maria , Romasheva Margarita , Didenko Andrey , Popova Elena , Ivan’kova Elena , Kamalov Almaz , Elokhovskiy Vladimir , Vaganov Vyacheslav , Filippov Alexander , Yudin Vladimir
Published: July 2023

For the first time, a study of the influence of the molecular weight of the thermoplastic partially crystalline polyimide R-BAPB on the thermophysical and mechanical properties of carbon plastics was presented. The molecular weight of polyimide was determined using the method of light scattering and the study of the intrinsic viscosity of polyamic acid solutions. To obtain CFRPs, the uniform distribution of polyimide powder on continuous carbon fibers via electrostatic spraying and further hot calendering and pressing were applied. The study of the structure of the obtained carbon plastics via scanning electron microscopy has shown that the growth of the molecular weight of polyimide prevents the impregnation of carbon fiber with the introduced polyimide. Moreover, an increase in the molecular weight of polyimide leads to a rise in glass transition and thermal decomposition temperatures up to 590 °C, while the degree of crystallinity of CFRP falls. Nonetheless, raising the molecular weight from 22,000 to 70,000 g/mol of a binder polymer improves the interlayer fracture toughness G1C by more than five times.
Insights into Recent Advances of Biomaterials Based on Microbial Biomass and Natural Polymers for Sustainable Removal of Pharmaceuticals Residues
Authors: Rusu Lăcrămioara , Suceveanu Elena-Mirela , Blaga Alexandra-Cristina , Nedeff Florin Marian , Șuteu Daniela
Published: July 2023

Pharmaceuticals are acknowledged as emerging contaminants in water resources. The concentration of pharmaceutical compounds in the environment has increased due to the rapid development of the pharmaceutical industry, the increasing use of human and veterinary drugs, and the ineffectiveness of conventional technologies to remove pharmaceutical compounds from water. The application of biomaterials derived from renewable resources in emerging pollutant removal techniques constitutes a new research direction in the field. In this context, the article reviews the literature on pharmaceutical removal from water sources using microbial biomass and natural polymers in biosorption or biodegradation processes. Microorganisms, in their active or inactive form, natural polymers and biocomposites based on inorganic materials, as well as microbial biomass immobilized or encapsulated in polymer matrix, were analyzed in this work. The review examines the benefits, limitations, and drawbacks of employing these biomaterials, as well as the prospects for future research and industrial implementation. From these points of view, current trends in the field are clearly reviewed. Finally, this study demonstrated how biocomposites made of natural polymers and microbial biomass suggest a viable adsorbent biomaterial for reducing environmental pollution that is also efficient, inexpensive, and sustainable.
Flexing the Spectrum: Advancements and Prospects of Flexible Electrochromic Materials
Authors: Nuroldayeva Gulzat , Balanay Mannix P.
Published: July 2023

The application potential of flexible electrochromic materials for wearable devices, smart textiles, flexible displays, electronic paper, and implantable biomedical devices is enormous. These materials offer the advantages of conformability and mechanical robustness, making them highly desirable for these applications. In this review, we comprehensively examine the field of flexible electrochromic materials, covering topics such as synthesis methods, structure design, electrochromic mechanisms, and current applications. We also address the challenges associated with achieving flexibility in electrochromic materials and discuss strategies to overcome them. By shedding light on these challenges and proposing solutions, we aim to advance the development of flexible electrochromic materials. We also highlight recent advances in the field and present promising directions for future research. We intend to stimulate further innovation and development in this rapidly evolving field and encourage researchers to explore new opportunities and applications for flexible electrochromic materials. Through this review, readers can gain a comprehensive understanding of the synthesis, design, mechanisms, and applications of flexible electrochromic materials. It serves as a valuable resource for researchers and industry professionals looking to harness the potential of these materials for various technological applications.
Experimental Investigation on Post-Fire Mechanical Properties of Glass Fiber-Reinforced Polymer Rebars
Authors: Thongchom Chanachai , Hu Lili , Sanit-in Penpichcha Khongpermgoson , Kontoni Denise-Penelope N. , Praphaphankul Nitipong , Tiprak Koravith , Kongwat Suphanut
Published: July 2023

Glass fiber-reinforced polymer (GFRP) rebars are commonly used as an alternative to conventional steel reinforcement in a variety of structural applications due to their superior low cost, strength-to-weight ratio, and durability. However, their mechanical properties after exposure to elevated temperatures, particularly in fire-prone environments, remain a significant concern. To address this concern, the present study focuses on investigating the residual tensile behavior, specifically the tensile strength and elastic modulus, of GFRP rebars exposed to high temperatures that are realistically encountered during fire incidents. The temperature range considered in this analysis spans from 100 °C to 400 °C, with a heating rate of 20 °C/min. The fire duration of 1 h is used. This comprehensive analysis is essential for enhancing our understanding of the performance and applicability of GFRP rebars in fire-prone environments. Based on their actual application in the construction industry, five specimens of three different rebar sizes (16, 20, and 25 mm) were examined for the effect of rebar size on tensile behavior after fire exposure. In addition, the effects were investigated of air- and water-cooling methods on residual tensile behavior. The nominal tensile strength, elastic modulus, and ultimate strain of GFRP rebars at ambient temperature are 930 MPa, 50.2 GPa and 1.85%, respectively. The test results indicated that as the temperature increased to 400 °C, the ultimate tensile strength of the GFRP bars decreased by up to 55%, while the ultimate strain increased by up to 44%, regardless of the cooling method. In addition, when rebars of sizes 16–25 mm were subjected to a 400 °C fire treatment, the smaller the rebar, the greater the percentage of ultimate tensile and strain reduction. These findings hold great significance for the utilization of GFRP bars within the construction industry. This study offers valuable insights into the design of fire-resilient structures, emphasizing the importance of considering rebar size and cooling methods due to their impact on the post-fire tensile strength and strain of GFRP rebars.
Chitosan–Collagen Electrospun Nanofibers Loaded with Curcumin as Wound-Healing Patches
Authors: Castellano Maila , Dodero Andrea , Scarfi Sonia , Mirata Serena , Pozzolini Marina , Tassara Eleonora , Sionkowska Alina , Adamiak Katarzyna , Alloisio Marina , Vicini Silvia
Published: July 2023

Composite chitosan–collagen nanofibrous mats embedded with curcumin were prepared via a single-step electrospinning procedure and explored as wound-healing patches with superior biological activity. A mild crosslinking protocol consisting of a short exposure to ammonia vapor and UV radiation was developed to ensure proper stability in physiological-like conditions without affecting the intrinsic biocompatibility of chitosan and collagen. The fabricated composite patches displayed a highly porous, homogeneous nanostructure consisting of fibers with an average diameter of 200 nm, thermal stability up to 200 °C, mechanical features able to ensure protection and support to the new tissues, and water-related properties in the ideal range to allow exudate removal and gas exchange. The release kinetic studies carried out in a simulated physiological environment demonstrated that curcumin release was sustained for 72 h when the mats are crosslinked hence providing prolonged bioactivity reflected by the displayed antioxidant properties. Remarkably, combining chitosan and collagen not only ensures prolonged stability and optimal physical–chemical properties but also allows for better-promoting cell adhesion and proliferation and enhanced anti-bacteriostatic capabilities with the addition of curcumin, owing to its beneficial anti-inflammatory effect, ameliorating the attachment and survival/proliferation rates of keratinocytes and fibroblasts to the fabricated patches.
Study on the Preparation of ZnFeO4 by Roasting Zinc-Containing Gossan Ore
Authors: Yang Jinlin , Li Zongyu , Huo Xingnan , Li Hangyu , Liao Shizhen , Ma Shaojian , Li Hengjun
Published: July 2023

Gossan ore is typically abandoned after mining, which not only increases mining production costs but also wastes mineral resources, and its long-term accumulation can easily lead to environmental pollution hazards. Therefore, this paper takes zinc-containing gossan ore as the research object and, based on the high content of zinc and iron minerals in gossan ore, this study conducts a roasting experiment to prepare ZnFeO4. X-ray diffraction is used to characterize and analyze the ZnFeO4 sample prepared by roasting zinc-containing gossan ore. The experimental results indicate that controlling the particle size of the roasted ore sample to −0.074 mm can effectively remove impurities and facilitate the reaction. The influence of roasting temperature and time on the formation of ZnFeO4 is remarkable. The conditions for roasting zinc-containing gossan ore to maximize the ZnFeO4 content are as follows: −0.074 mm particle size ore sample, reaction zinc/iron molar ratio of 1:2, mechanical activation time of 120 min, roasting temperature of 1050 °C, and roasting time of 120 min. These findings provide new ideas for the utilization of gossan ore and lay a theoretical foundation for the efficient development and utilization of difficult-to-select zinc-containing gossan ore.
Evaluation of Biogas Energy from Co-Digestion of Organic Urban Solid Waste with Lime Mud
Authors: Coelho Ulisses Raad da Silva , Crispim Adriele Maria de Cássia , Martins Maria Auxiliadora de Barros , Barros Regina Mambeli , Reno Maria Luiza Grillo , Tiago Filho Geraldo Lúcio , Santos Ivan Felipe Silva
Published: July 2023

The elevated presence of organic material in Brazilian urban solid waste, along with mismanagement of its disposal, can aggravate environmental problems from greenhouse gas emissions to water and soil pollution. In parallel, the paper and cellulose industries consume considerable resources and produce important solid wastes, including lime mud. These urban and industrial realities present common ground, from which a little-studied alternative arises in using biogas electrical energy from the co-digestion of the organic portion of urban solid waste using lime mud. This intersection can reduce the environmental impacts associated with inadequate management and disposal of solid waste, providing industry financial economy resources and contributing to Brazilian energy grid diversification. The current study used economic–financial indicators to evaluate the proposal’s economic feasibility. The obtained results presented a minimum population of 165,200 inhabitants, generating 39,295.77 m3/year of methane, in order to enable a co-digestion proposal. The sensitivity analysis indicated that a population of 185,500 inhabitants would provide a 10-year payback, an energy rate of USD 0.139, and 44,124.49 m3/year of methane to supply the population with power. The net present value was USD 23,336.94, with an internal return rate of 14.71% and a levelized energy cost of 0.103 USD/kWh.
Transforming Inner Alchemical Vision into Painting: Huang Gongwang’s Clearing after Sudden Snow
Authors: Liu Ziyun
Published: July 2023

This paper argues that the Yuan dynasty Daoist Huang Gongwang’s 黃公望 (1269–1354) painting Clearing after Sudden Snow resonates with the principles of inner alchemy (neidan, 內丹), particularly the stage known as the resurgence of yang force. Within this painting, four prominent visual elements—the sun, the spirit room, the cliff, and the snowy mountains—come together to imbue the painting with a rich tapestry of inner alchemical connotations. They collectively portray the sequential stages of cultivation, refinement, and transformation in the context of inner alchemy. The painting not only captures the moment of transition where the snow-covered terrain is gradually transforming into a fresh and awakened state, but it also embodies a visual metaphor for the inner alchemical transformative journey. Furthermore, each individual who engages with the painting may undergo their own personal transformation through the act of contemplation and reflection.
Enhanced Absence Sampling Technique for Data-Driven Landslide Susceptibility Mapping: A Case Study in Songyang County, China
Authors: Fu Zijin , Wang Fawu , Dou Jie , Nam Kounghoon , Ma Hao
Published: July 2023

Accurate prediction of landslide susceptibility relies on effectively handling absence samples in data-driven models. This study investigates the influence of different absence sampling methods, including buffer control sampling (BCS), controlled target space exteriorization sampling (CTSES), information value (IV), and mini-batch k-medoids (MBKM), on landslide susceptibility mapping in Songyang County, China, using support vector machines and random forest algorithms. Various evaluation metrics are employed to compare the efficacy of these sampling methods for susceptibility zoning. The results demonstrate that CTSES, IV, and MBKM methods exhibit an expansion of the high susceptibility region (maximum susceptibility mean value reaching 0.87) and divergence in the susceptibility index when extreme absence samples are present, with MBKM showing a comparative advantage (lower susceptibility mean value) compared to the IV model. Building on the strengths of different sampling methods, a novel integrative sampling approach that incorporates multiple existing methods is proposed. The integrative sampling can mitigate negative effects caused by extreme absence samples (susceptibility mean value is approximately 0.5 in the same extreme samples and presence-absence ratio) and obtain significantly better prediction results (AUC = 0.92, KC = 0.73, POA = 2.46 in the best model). Additionally, the mean level of susceptibility is heavily influenced by the proportion of absent samples.
Study of the Response of Environmental Factors of the Coastal Area in Zhoushan Fishery to Typhoon In-fa Based on Remote Sensing
Authors: Tang Rong , Cai Lina , Yan Xiaojun , Ye Xiaomin , Xu Yuzhu , Yin Jie
Published: July 2023

The response of typical environmental factors in Zhoushan Fishery, including sea surface temperature (SST), sea surface salinity (SSS), and chlorophyll a (Chl-a), before and after Typhoon In-fa was analyzed using satellite data and reanalysis data in this study. Additionally, this study simultaneously elucidated the mechanism by which the typhoon affected these factors. The results showed that: (1) the strong vertical mixing caused by In-fa provoked a decrease in SST, while the asymmetric typhoon wind stress and vertical difference in temperature structure before the typhoon caused a more robust cooling of SST on the right side of the In-fa track; (2) despite the strong mixing and inflow of hypersaline seawater increasing SSS, the combined effect of intense rainfall and diluted water inflow caused an overall decrease in SSS after In-fa’s landing; (3) In-fa caused the Chl-a concentration to decrease first and then increase. The high cloudiness and low Chl-a seawater inflow inhibited the phytoplankton growth during the typhoon, while the abundant light, rich surface nutrients under the upwelling effect, and transport of rich land-based substances induced rapid phytoplankton reproduction after the typhoon; and (4) the change in Chl-a concentration, current, temperature, and salinity induced by a typhoon are essential factors that affect fish behavior and community composition in fisheries. This study provides a point of reference to reveal the response of environmental factors to typhoons and their effects on fishery resources in fisheries located on nearshore estuarine shallow waters with intensive islands.
Machine-Learning-Enhanced Procedural Modeling for 4D Historical Cities Reconstruction
Authors: Vaienti Beatrice , Petitpierre Rémi , di Lenardo Isabella , Kaplan Frédéric
Published: July 2023

The generation of 3D models depicting cities in the past holds great potential for documentation and educational purposes. However, it is often hindered by incomplete historical data and the specialized expertise required. To address these challenges, we propose a framework for historical city reconstruction. By integrating procedural modeling techniques and machine learning models within a Geographic Information System (GIS) framework, our pipeline allows for effective management of spatial data and the generation of detailed 3D models. We developed an open-source Python module that fills gaps in 2D GIS datasets and directly generates 3D models up to LOD 2.1 from GIS files. The use of the CityJSON format ensures interoperability and accommodates the specific needs of historical models. A practical case study using footprints of the Old City of Jerusalem between 1840 and 1940 demonstrates the creation, completion, and 3D representation of the dataset, highlighting the versatility and effectiveness of our approach. This research contributes to the accessibility and accuracy of historical city models, providing tools for the generation of informative 3D models. By incorporating machine learning models and maintaining the dynamic nature of the models, we ensure the possibility of supporting ongoing updates and refinement based on newly acquired data. Our procedural modeling methodology offers a streamlined and open-source solution for historical city reconstruction, eliminating the need for additional software and increasing the usability and practicality of the process.
Application of Remote Sensing in Detecting and Monitoring Water Stress in Forests
Authors: Le Thai Son , Harper Richard , Dell Bernard
Published: July 2023

In the context of climate change, the occurrence of water stress in forest ecosystems, which are solely dependent on precipitation, has exhibited a rising trend, even among species that are typically regarded as drought-tolerant. Remote sensing techniques offer an efficient, comprehensive, and timely approach for monitoring forests at local and regional scales. These techniques also enable the development of diverse indicators of plant water status, which can play a critical role in evaluating forest water stress. This review aims to provide an overview of remote sensing applications for monitoring water stress in forests and reveal the potential of remote sensing and geographic information system applications in monitoring water stress for effective forest resource management. It examines the principles and significance of utilizing remote sensing technologies to detect forest stress caused by water deficit. In addition, by a quantitative assessment of remote sensing applications of studies in refereed publications, the review highlights the overall trends and the value of the widely used approach of utilizing visible and near-infrared reflectance data from satellite imagery, in conjunction with classical vegetation indices. Promising areas for future research include the utilization of more adaptable platforms and higher-resolution spectral data, the development of novel remote sensing indices with enhanced sensitivity to forest water stress, and the implementation of modelling techniques for early detection and prediction of stress.
A Software-Defined Radar for Low-Altitude Slow-Moving Small Targets Detection Using Transmit Beam Control
Authors: Cai Lingping , Qian Haonan , Xing Linger , Zou Yang , Qiu Linkang , Liu Zihan , Tian Sirui , Li Hongtao
Published: July 2023

Low-altitude slow-moving small (LSS) targets are defined as flying at altitudes less than 1000 m with speeds less than 55 m/s and a radar crossing-section (RCS) less than 2 m2. The detection performance of ground-based radar using the LSS target detection technique can be significantly deteriorated by the diversity of LSS targets, background clutter, and the occurrence of false alarms caused by multipath interference. To address the LSS target detection problem, we have devised a novel two-dimensional electronic scanning active phased array radar system that is implemented in the software-defined radar architecture and propose a transmit beam control algorithm based on the low peak-to-average ratio (PAPR). Meanwhile, we devised a flexible arbitrary radar waveform generator to adapt to complex environmental situations. Field experiment results effectively demonstrate that our radar can be used to detect LSS targets. Moreover, an ablation experiment was conducted to verify the role played by transmit beam control and adaptive waveform optimization and generation in improving the system performance.
A New Approach toward Corner Detection for Use in Point Cloud Registration
Authors: Wang Wei , Zhang Yi , Ge Gengyu , Yang Huan , Wang Yue
Published: July 2023

For this study, a new point cloud alignment method is proposed for extracting corner points and aligning them at the geometric level. It can align point clouds that have low overlap and is more robust to outliers and noise. First, planes are extracted from the raw point cloud, and the corner points are defined as the intersection of three planes. Next, graphs are constructed for subsequent point cloud registration by treating corners as vertices and sharing planes as edges. The graph-matching algorithm is then applied to determine correspondence. Finally, point clouds are registered by aligning the corresponding corner points. The proposed method was investigated by utilizing pertinent metrics on datasets with differing overlap. The results demonstrate that the proposed method can align point clouds that have low overlap, yielding an RMSE of about 0.05 cm for datasets with 90% overlap and about 0.2 cm when there is only about 10% overlap. In this situation, the other methods failed to align point clouds. In terms of time consumption, the proposed method can process a point cloud comprising 104 points in 4 s when there is high overlap. When there is low overlap, it can also process a point cloud comprising 106 points in 10 s. The contributions of this study are the definition and extraction of corner points at the geometric level, followed by the use of these corner points to register point clouds. This approach can be directly used for low-precision applications and, in addition, for coarse registration in high-precision applications.
Field Verification of Vehicle-Mounted All-Fiber Coherent Wind Measurement Lidar Based on Four-Beam Vertical Azimuth Display Scanning
Authors: Zhang Xiaojie , Li Qingsong , Wang Yujie , Fang Jing , Zhao Yuefeng
Published: July 2023

Wind parameters play a vital role in studying atmospheric dynamics and climate change. In this study, a vehicle-mounted coherent wind measurement Lidar (CWML) with a wavelength of 1.55 µm is demonstrated based on a four-beam vertical azimuth display (VAD) scanning mode, and a method to estimate wind vector from power spectrum is proposed. The feasibility of the application of wind profile Lidar in vehicles is verified by calibration tests, comparison experiments, and continuous observation experiments, successively. The effective detection height of Lidar can reach 3 km. In contrasting experiments, the correlation coefficients of the magnitude and direction of horizontal wind speed measured by vehicle-mounted Lidar and fixed Lidar are 0.94 and 0.91, respectively. The experimental results reveal that the accuracies of wind speed and direction measurements with the vehicle-mounted CWML are better than 0.58 m/s and 4.20°, respectively. Furthermore, to understand the role of the wind field in the process of energy and material transport further, a proton-transfer reaction time-of-flight mass spectrometer (PTR-TOF-MS) is utilized to measure the concentration of volatile organic compounds (VOCs). Relevant experimental results indicate that the local meteorological conditions, including wind speed and humidity, influence the VOC concentrations.
A Gated Content-Oriented Residual Dense Network for Hyperspectral Image Super-Resolution
Authors: Hu Jing , Li Tingting , Zhao Minghua , Wang Fei , Ning Jiawei
Published: July 2023

Limited by the existing imagery sensors, a hyperspectral image (HSI) is characterized by its high spectral resolution but low spatial resolution. HSI super-resolution (SR) aims to enhance the spatial resolution of the HSIs without modifying the equipment and has become a hot issue for HSI processing. In this paper, inspired by two important observations, a gated content-oriented residual dense network (GCoRDN) is designed for the HSI SR. To be specific, based on the observation that the structure and texture exhibit different sensitivities to the spatial degradation, a content-oriented network with two branches is designed. Meanwhile, a weight-sharing strategy is merged in the network to preserve the consistency in the structure and the texture. In addition, based on the observation of the super-resolved results, a gating mechanism is applied as a form of post-processing to further enhance the SR performance. Experimental results and data analysis on both ground-based HSIs and airborne HSIs have demonstrated the effectiveness of the proposed method.
Homography Matrix-Based Local Motion Consistent Matching for Remote Sensing Images
Authors: Liu Junyuan , Liang Ao , Zhao Enbo , Pang Mingqi , Zhang Daijun
Published: July 2023

Feature matching is a fundamental task in the field of image processing, aimed at ensuring correct correspondence between two sets of features. Putative matches constructed based on the similarity of descriptors always contain a large number of false matches. To eliminate these false matches, we propose a remote sensing image feature matching method called LMC (local motion consistency), where local motion consistency refers to the property that adjacent correct matches have the same motion. The core idea of LMC is to find neighborhoods with correct motion trends and retain matches with the same motion. To achieve this, we design a local geometric constraint using a homography matrix to represent local motion consistency. This constraint has projective invariance and is applicable to various types of transformations. To avoid outliers affecting the search for neighborhoods with correct motion, we introduce a resampling method to construct neighborhoods. Moreover, we design a jump-out mechanism to exit the loop without searching all possible cases, thereby reducing runtime. LMC can process over 1000 putative matches within 100 ms. Experimental evaluations on diverse image datasets, including SUIRD, RS, and DTU, demonstrate that LMC achieves a higher F-score and superior overall matching performance compared to state-of-the-art methods.
Comprehensive Evaluation of High-Resolution Satellite Precipitation Products over the Qinghai–Tibetan Plateau Using the New Ground Observation Network
Authors: Liu Zhaofei
Published: July 2023

Satellite precipitation products (SPPs) have been widely evaluated at regional scales. However, there have been few quantitative comprehensive evaluations of SPPs using multiple indices. Ten high-resolution SPPs were quantitatively and comprehensively evaluated from precipitation occurrence and series indices using an improved rank score (RS) method in the data-scarce Qinghai–Tibetan Plateau (QTP). The new observation network, along with a number of national basic stations, was applied for SPP evaluation to obtain more reliable results. The results showed that the GPM and MSWEP showed the strongest overall performance, with an RS value of 0.75. CHIRPS and GPM had the strongest performance at measuring precipitation occurrence (RS = 0.92) and series (RS = 0.75), respectively. The optimal SPPs varied in evaluation indices, but also concentrated in the MSWEP, GPM, and CHIRPS. The bias of SPPs was markedly in the QTP, with relative error generally between −80% and 80%. In general, most SPPs showed the ability to detect precipitation occurrence. However, the SPPs showed relatively weak performance at measuring precipitation series. The mean Kling–Gupta efficiency of all stations was <0.50 for each SPP. The SPPs showed better performance in monsoon-affected regions, which mainly include the Yangtze, Yellow, Nu–Salween, Lancang–Mekong, Yarlung Zangbo–Bramaputra, and Ganges river basins. Performance was relatively poor in the westerly circulation areas, which mainly include the Tarim, Indus, and QTP inland river basins. The performance of SPPs showed a seasonal pattern during the year for most occurrence indices. The performance of SPPs in different periods was opposite in different indices. Therefore, multiple indices representing different characteristics are recommended for the evaluation of SPPs to obtain a comprehensive evaluation result. Overall, SPP measurement over the QTP needs further improvement, especially with regard to measuring precipitation series. The proposed improved RS method can also potentially be applied for comprehensive evaluation of other products and models.
Domain Adaptation Based on Semi-Supervised Cross-Domain Mean Discriminative Analysis and Kernel Transfer Extreme Learning Machine
Authors: Li Xinghai , Ma Jianwei
Published: July 2023

Good data feature representation and high precision classifiers are the key steps for pattern recognition. However, when the data distributions between testing samples and training samples do not match, the traditional feature extraction methods and classification models usually degrade. In this paper, we propose a domain adaptation approach to handle this problem. In our method, we first introduce cross-domain mean approximation (CDMA) into semi-supervised discriminative analysis (SDA) and design semi-supervised cross-domain mean discriminative analysis (SCDMDA) to extract shared features across domains. Secondly, a kernel extreme learning machine (KELM) is applied as a subsequent classifier for the classification task. Moreover, we design a cross-domain mean constraint term on the source domain into KELM and construct a kernel transfer extreme learning machine (KTELM) to further promote knowledge transfer. Finally, the experimental results from four real-world cross-domain visual datasets prove that the proposed method is more competitive than many other state-of-the-art methods.
Smart Wireless Sensor Technology for Healthcare Monitoring System Using Cognitive Radio Networks
Authors: Jabeen Tallat , Jabeen Ishrat , Ashraf Humaira , Ullah Ata , Jhanjhi N. Z. , Ghoniem Rania M. , Ray Sayan Kumar
Published: July 2023

Programmable Object Interfaces are increasingly intriguing researchers because of their broader applications, especially in the medical field. In a Wireless Body Area Network (WBAN), for example, patients’ health can be monitored using clinical nano sensors. Exchanging such sensitive data requires a high level of security and protection against attacks. To that end, the literature is rich with security schemes that include the advanced encryption standard, secure hashing algorithm, and digital signatures that aim to secure the data exchange. However, such schemes elevate the time complexity, rendering the data transmission slower. Cognitive radio technology with a medical body area network system involves communication links between WBAN gateways, server and nano sensors, which renders the entire system vulnerable to security attacks. In this paper, a novel DNA-based encryption technique is proposed to secure medical data sharing between sensing devices and central repositories. It has less computational time throughout authentication, encryption, and decryption. Our analysis of experimental attack scenarios shows that our technique is better than its counterparts.
SELID: Selective Event Labeling for Intrusion Detection Datasets
Authors: Jang Woohyuk , Kim Hyunmin , Seo Hyungbin , Kim Minsong , Yoon Myungkeun
Published: July 2023

A large volume of security events, generally collected by distributed monitoring sensors, overwhelms human analysts at security operations centers and raises an alert fatigue problem. Machine learning is expected to mitigate this problem by automatically distinguishing between true alerts, or attacks, and falsely reported ones. Machine learning models should first be trained on datasets having correct labels, but the labeling process itself requires considerable human resources. In this paper, we present a new selective sampling scheme for efficient data labeling via unsupervised clustering. The new scheme transforms the byte sequence of an event into a fixed-size vector through content-defined chunking and feature hashing. Then, a clustering algorithm is applied to the vectors, and only a few samples from each cluster are selected for manual labeling. The experimental results demonstrate that the new scheme can select only 2% of the data for labeling without degrading the F1-score of the machine learning model. Two datasets, a private dataset from a real security operations center and a public dataset from the Internet for experimental reproducibility, are used.