bluuebunny/crossref_metadata_2025 huggingface dataset:
Silver Nanoparticles Selectively Treat Neurofibromatosis Type 1-Associated Plexiform Neurofibroma Cells at Doses That Do Not Affect Patient-Matched Schwann Cells
Authors: Attiah Bashnona , Alewine Garrett , Easter Mary-Kate , Coover Robert A. , Fahrenholtz Cale D.
Published: March 2024

Neurofibromatosis Type 1 (NF1) is a common neurogenic condition characterized by heterozygous loss of function mutations in the neurofibromin gene. NF1 patients are susceptible to the development of neurofibromas, including plexiform neurofibromas (pNFs), which occurs in about half of all cases. Plexiform neurofibroma are benign peripheral nerve sheath tumors originating from Schwann cells after complete loss of neurofibromin; they can be debilitating and also transform into deadly malignant peripheral nerve sheath tumors (MPNSTs). Here, our data indicates that silver nanoparticles (AgNPs) may be useful in the treatment of pNFs. We assessed the cytotoxicity of AgNPs using pNF cells and Schwann cells derived from the same NF1 patient. We found that AgNPs are selectively cytotoxic to pNF cells relative to isogenic Schwann cells. We then examined the role of neurofibromin expression on AgNP-mediated cytotoxicity; restoration of neurofibromin expression in pNF cells decreased sensitivity to AgNP, and knockdown of neurofibromin in isogenic Schwann cells increased sensitivity to AgNP, outlining a correlation between neurofibromin expression and AgNP-mediated cytotoxicity. AgNP was able to selectively remove pNF cells from a co-culture with patient-matched Schwann cells. Therefore, AgNPs represent a new approach for clinical management of NF1-associated pNF to address significant clinical need.
Gelatin-/Alginate-Based Hydrogel Scaffolds Reinforced with TiO2 Nanoparticles for Simultaneous Release of Allantoin, Caffeic Acid, and Quercetin as Multi-Target Wound Therapy Platform
Authors: Babić Radić Marija M. , Vukomanović Marija , Nikodinović-Runić Jasmina , Tomić Simonida
Published: March 2024

This study proposes synthesis and evaluation of gelatin-/alginate-based hydrogel scaffolds reinforced with titanium dioxide (TiO2) nanoparticles which, through their combination with allantoin, quercetin, and caffeic acid, provide multi-target therapy directed on all phases of the wound healing process. These scaffolds provide the simultaneous release of bioactive agents and concurrently support cell/tissue repair through the replicated structure of a native extracellular matrix. The hydrogel scaffolds were synthesized via a crosslinking reaction using EDC as a crosslinker for gelatin. Synthesized hydrogel scaffolds and the effect of TiO2 on their properties were characterized by structural, mechanical, morphological, and swelling properties, and the porosity, wettability, adhesion to skin tissue, and simultaneous release features. The biocompatibility of the scaffolds was tested in vitro on fibroblasts (MRC5 cells) and in vivo (Caenorhabditis elegans) in a survival probe. The scaffolds revealed porous interconnected morphology, porosity of 88.33 to 96.76%, elastic modulus of 1.53 to 4.29 MPa, full hydrophilicity, favorable skin adhesivity, and biocompatibility. The simultaneous release was investigated in vitro indicating dependence on the scaffold’s composition and type of bioactive agents. The novel scaffolds designed as multi-target therapy have significant promise for improved wound healing in a beneficial and non-invasive manner.
Cancer Therapy Resistance: Choosing Kinase Inhibitors
Authors: Dell’Aversana Carmela , Sarno Federica , Benedetti Rosaria , Megchelenbrink Wouter Leonard , Cappetta Donato
Published: March 2024

Recent advances in comprehending the essential molecular mechanisms that govern cancer signaling have revealed the pivotal involvement of kinases in the development and progression of various cancer types [...]
Cellulose Nanofibrils-Reinforced Pectin Membranes for the Adsorption of Cationic Dyes from a Model Solution
Authors: Ojstršek Alenka , Gorgieva Selestina
Published: March 2024

In the presented research, a facile, one-step method for the fabrication of cellulose nanofibrils/pectin (CNFs/PC) membranes is described, which were tested further for their ability to remove cationic dyes from the prepared model solutions. For this purpose, ten membranes were prepared with different quantities of CNFs and PC with/without citric acid (CA) or CaCl2 as mediated crosslinking agents, and they were characterised comprehensively in terms of their physical, chemical, and hydrophilic properties. All the prepared CNFs/PC membranes were hydrophilic with a Water Contact Angle (WCA) from 51.23° (without crosslinker) up to 78.30° (CaCl2) and swelling of up to 485% (without crosslinker), up to 437% (CaCl2) and up to 270% (CA). The stability of membranes was decreased with the increase in PC; thus, only four membranes (M1, M2, M3 and M5) were stable enough in water after 24 h, and these were additionally applied in the adsorption trials, using two structurally different cationic dyes, i.e., C.I. Basic Yellow 28 (BY28) and C.I. Basic Blue 22 (BB22), in four concentrations. The highest total surface charge of M3 (2.83 mmol/g) as compared to the other membranes influenced the maximal removal efficiency of both dyes, up to 37% (BY28) and up to 71% (BB22), depending on the initial dye concentration. The final characteristics of the membranes and, consequently, the dye’s absorption ability could be tuned easily by changing the ratio between the CNFs and PC, as well as the type and amount of crosslinker.
Facile Preparation of Cellulose Beads with Tunable Graded Pores and High Mechanical Strength
Authors: Meng Ranjv , Liu Lin , Su Xiuping , Gong Wenli , Luo Xiaolei , Gao Huiying
Published: March 2024

Cellulose-based hierarchical porous beads exhibit significant application potential in adsorption and separation systems due to their degradation and biocompatibility. However, the current fabrications of cellulose beads show poor mechanical properties and a difficult-to-regulate hierarchical porous structure, reducing their lifespan of use and limiting their application in fine separation. Here, we reported the facile creep–drop method to prepare cellulose beads that enabled systemic regulation of the macro-size, micropore structures, and mechanical properties by optimizing injection nozzle diameter, the composition of the coagulation bath, the temperature of the coagulation bath, and cellulose concentration. Notably, during the molding process, the H2SO4-Na2SO4 composite solidification bath endowed cellulose beads with a dense shell layer and a loose core layer, which achieved the integration of mechanical properties and high porosity. The cellulose beads exhibited high porosity (93.38–96.18%) and high sphericity (86.78–94.44%) by modulating the shell thickness of the cellulose beads. In particular, the cellulose beads exhibited excellent mechanical properties with a high compressive strength of 544.24 kPa at a 5% cellulose concentration. It is expected that these cellulose beads with tunable microstructures can realize their potential for applications in the fields of wastewater treatment, chemical engineering, bioengineering, medicine, and pharmaceuticals.
Anticancer Potential of Antimicrobial Peptides: Focus on Buforins
Authors: Tolos (Vasii) Ana Maria , Moisa Cristian , Dochia Mihaela , Popa Carmen , Copolovici Lucian , Copolovici Dana Maria
Published: March 2024

In seeking alternative cancer treatments, antimicrobial peptides (AMPs), sourced from various life forms, emerge as promising contenders. These endogenous peptides, also known as host defense peptides (HDPs), play crucial roles in immune defenses against infections and exhibit potential in combating cancers. With their diverse defensive functions, plant-derived AMPs, such as thionins and defensins, offer a rich repertoire of antimicrobial properties. Insects, amphibians, and animals contribute unique AMPs like cecropins, temporins, and cathelicidins, showcasing broad-spectrum activities against bacteria, fungi, and viruses. Understanding these natural peptides holds significant potential for developing effective and targeted therapies against cancer and infectious diseases. Antimicrobial peptides (AMPs) exhibit diverse structural characteristics, including α-helical, β-sheet, extended, and loop peptides. Environmental conditions influence their structure, connecting to changes in cell membrane hydrophobicity. AMPs’ actions involve direct killing and immune regulation, with additional activities like membrane depolarization. In this review, we focus on antimicrobial peptides that act as anticancer agents and AMPs that exhibit mechanisms akin to antimicrobial activity. Buforin AMPs, particularly Buforin I and II, derived from histone H2A, demonstrate antibacterial and anticancer potential. Buforin IIb and its analogs show promise, with selectivity for cancer cells. Despite the challenges, AMPs offer a unique approach to combat microbial resistance and potential cancer treatment. In various cancer types, including HeLa, breast, lung, ovarian, prostate, and liver cancers, buforins demonstrate inhibitory effects and apoptosis induction. To address limitations like stability and bioavailability, researchers explore buforin-containing bioconjugates, covalently linked with nanoparticles or liposomes. Bioconjugation enhances specificity-controlled release and combats drug resistance, presenting a promising avenue for targeted cancer treatment. Clinical translation awaits further evaluation through in vivo studies and future clinical trials.
The Influence of Strain Rate Behavior on Laminated Glass Interlayer Types for Cured and Uncured Polymers
Authors: Elkilani Ahmed , EL-Emam Hesham , Elsisi Alaa , Elbelbisi Ahmed , Salim Hani
Published: March 2024

Recent explosions and impact events have highlighted the exposure of civil structures, prompting the need for resilient new constructions and retrofitting of existing ones. Laminated glass panels, particularly in glazed facades, are increasingly used to enhance blast resistance. However, the understanding of glass fragments and their interaction with the interlayer is still incomplete. This paper investigates experimentally the quasi-static and dynamic responses of cured and uncured polymers for seven different materials—two different products of polyvinyl butyral (PVB), two ethylene vinyl acetate products (EVA), one product of thermoplastic polyurethane (TPU), and two SentryGlas products (SG)—that were tested between 21 and 32 °C (69.8 and 89.6 °F), which is the recommended room temperature. In these experiments, the responses of PVB, EVA, TPU, and SG were evaluated under a quasi-static strain rate of 0.033 s−1 and compared to the results under a relatively higher strain rate of 2 s−1. Moreover, the high strain rate loading of the materials was accomplished using a drop-weight testing appliance to evaluate the engineering stress–strain response under strain rates between 20 and 50 s−1. The results demonstrated that with strain rates of 20 s−1, PVB behaved like a material with viscoelastic characteristics, but at 45 s−1 strain rates, PVB became a non-elastic material. SG, on the other hand, offered both a high stiffness and a high level of transparency, making it a very good alternative to PVB in structural applications. In contrast, after the maximum stress point, the response to the failure of the seven materials differed significantly. The tests provided ample information for evaluating alternative approaches to modeling these different materials in blast events.
Highly Thermally Conductive Triple-Level Ordered CNT/PVA Nanofibrous Films
Authors: Wu Yanyan , Chen Anqi , Jiang Wenlong , Tan Zhiye , Fu Tingting , Xie Tingting , Zhu Guimei , Zhu Yuan
Published: March 2024

The escalating thermal power density in electronic devices necessitates advanced thermal management technologies. Polymer-based materials, prized for their electrical insulation, flexibility, light weight, and strength, are extensively used in this field. However, the inherent low thermal conductivity of polymers requires enhancement for effective heat dissipation. This work proposes a novel paradigm, emphasizing ordered structures with functional units, to create triple-level, ordered, low-filler loading of multi-walled carbon nanotube (MWCNT)/poly(vinyl alcohol)(PVA) nanofibrous films. By addressing interfacial thermal resistance through –OH groups, the coupling between polymer and MWCNT is strengthened. The triple-level ordered structure comprises aligned PVA chains, aligned MWCNTs, and aligned MWCNT/PVA composite fibers. Focusing on the filler’s impact on thermal conductivity and chain orientation, the thermal transport mechanisms have been elucidated level by level. Our MWCNT/PVA composite, with lower filler loadings (10 wt.%), achieves a remarkable TC exceeding 35.4 W/(m·K), surpassing other PVA composites with filler loading below 50 wt.%.
Exploring the Potential of 3D-Printable Agar–Urea Hydrogels as an Efficient Method of Delivering Nitrogen in Agricultural Applications
Authors: Dissanayake Wathsala , Najaf Zadeh Hossein , Nazmi Ali , Stevens Campbell , Huber Tim , Abhayawardhana Pramuditha
Published: March 2024

Amidst population growth and challenges with existing fertilizers, the development of smart and environmentally friendly agrochemicals is imperative. While 3D printing is widespread, its potential in slow-release agrochemicals remains unexplored. This proof-of-concept study employed solvent casting and 3D printing to develop agar–urea structures. These structures, comprising 2.5% (w/w) agar, incorporated either 7% (w/w) or 13% (w/w) urea as nitrogen nutrients. Rheological, mechanical, and morphological properties and sorption capabilities were explored. Rheological analysis revealed a substantial impact of urea, enhancing material resistance to deformation. In mechanical tests, inclusion of urea showed no significant impact on compressive strength. SEM analysis confirmed the successful entrapment of urea within the agar matrix. The inclusion of urea resulted in a diminished water sorption capacity, attributed to the urea–water interactions disrupting the hydrogen bonding ability of agar. Agar–urea inks were employed in 3D printing utilizing the direct-ink writing technique, and the nitrogen release behavior was investigated. Results revealed nearly complete urea release in the positive control within 48 h. In contrast, agar–urea formulations with 7% (w/w) and 13% (w/w) achieved nitrogen release rates of 88.8% and 94.4%, respectively, suggesting potential for 3D-printed agar formulations to modify the immediate release behavior seen in conventional urea fertilizers.
Pre-Operative Anxiety Related to Major Urogynecologic Surgery: Insights from Perioperative Survey Data in Maine
Authors: Kaonga Nadi Nina , Courbron Yanghee , Holmgren Emmy , Konzal Eliot , Williams Whitney , Brandes Mary , Foust-Wright Caroline
Published: March 2024

Background: Higher levels of pre-operative anxiety are associated with adverse outcomes according to the cardiothoracic and orthopedic literature on emergent surgeries. There are limited data on pre-operative anxiety levels in the gynecologic setting. This study sought to identify predictive variables for high pre-operative anxiety levels in patients undergoing major urogynecologic surgery. Methods: Pre- and post-operative surveys that included demographic data, a modification of the Amsterdam Pre-Operative Anxiety and Information Scale, and open-ended questions regarding anxiety were administered. Descriptive, univariate and multivariate analyses were used to analyze the quantitative elements of the survey data. The qualitative components of the survey data were coded and analyzed using thematic analyses. Results: A total of 54 participants completed the pre-operative survey. The median age was 62 years old, and the majority were employed (n = 34, 60.7%). Roughly 1/3 had been diagnosed with a mental health condition (n = 19, 33.9%) and nearly all had other health conditions (n = 51, 91%). The baseline APAIS score ranged from 9 to 40, with higher scores reflecting higher levels of pre-operative anxiety. The median APAIS score was 24, with a score equal to or greater than 30 being in the highest tertile. Conclusion: No associations were made between the variables and pre-operative anxiety levels. However, useful insights into our patient population were made.
Scattering-Point-Guided Oriented RepPoints for Ship Detection
Authors: Zhao Weishan , Huang Lijia , Liu Haitian , Yan Chaobao
Published: March 2024

Ship detection finds extensive applications in fisheries management, maritime rescue, and surveillance. However, detecting nearshore targets in SAR images is challenging due to land scattering interference and non-axisymmetric ship shapes. Existing SAR ship detection models struggle to adapt to oriented ship detection in complex nearshore environments. To address this, we propose an oriented-reppoints target detection scheme guided by scattering points in SAR images. Our method deeply integrates SAR image target scattering characteristics and designs an adaptive sample selection scheme guided by target scattering points. This incorporates scattering position features into the sample quality measurement scheme, providing the network with a higher-quality set of proposed reppoints. We also introduce a novel supervised guidance paradigm that uses target scattering points to guide the initialization of reppoints, mitigating the influence of land scattering interference on the initial reppoints quality. This achieves adaptive feature learning, enhancing the quality of the initial reppoints set and the performance of object detection. Our method has been extensively tested on the SSDD and HRSID datasets, where we achieved mAP scores of 89.8% and 80.8%, respectively. These scores represent significant improvements over the baseline methods, demonstrating the effectiveness and robustness of our approach. Additionally, our method exhibits strong anti-interference capabilities in nearshore detection and has achieved state-of-the-art performance.
TAG-Net: Target Attitude Angle-Guided Network for Ship Detection and Classification in SAR Images
Authors: Pan Dece , Wu Youming , Dai Wei , Miao Tian , Zhao Wenchao , Gao Xin , Sun Xian
Published: March 2024

Synthetic aperture radar (SAR) ship detection and classification has gained unprecedented attention due to its important role in maritime transportation. Many deep learning-based detectors and classifiers have been successfully applied and achieved great progress. However, ships in SAR images present discrete and multi-centric features, and their scattering characteristics and edge information are sensitive to variations in target attitude angles (TAAs). These factors pose challenges for existing methods to obtain satisfactory results. To address these challenges, a novel target attitude angle-guided network (TAG-Net) is proposed in this article. The core idea of TAG-Net is to leverage TAA information as guidance and use an adaptive feature-level fusion strategy to dynamically learn more representative features that can handle the target imaging diversity caused by TAA. This is achieved through a TAA-aware feature modulation (TAFM) module. It uses the TAA information and foreground information as prior knowledge and establishes the relationship between the ship scattering characteristics and TAA information. This enables a reduction in the intra-class variability and highlights ship targets. Additionally, considering the different requirements of the detection and classification tasks for the scattering information, we propose a layer-wise attention-based task decoupling detection head (LATD). Unlike general deep learning methods that use shared features for both detection and classification tasks, LATD extracts multi-level features and uses layer attention to achieve feature decoupling and select the most suitable features for each task. Finally, we introduce a novel salient-enhanced feature balance module (SFB) to provide richer semantic information and capture the global context to highlight ships in complex scenes, effectively reducing the impact of background noise. A large-scale ship detection dataset (LSSDD+) is used to verify the effectiveness of TAG-Net, and our method achieves state-of-the-art performance.
The Rise of Passive RFID RTLS Solutions in Industry 5.0
Authors: Bendavid Ygal , Rostampour Samad , Berrabah Yacine , Bagheri Nasour , Safkhani Masoumeh
Published: March 2024

In today’s competitive landscape, manufacturing companies must embrace digital transformation. This study asserts that integrating Internet of Things (IoT) technologies for the deployment of real-time location systems (RTLS) is crucial for better monitoring of critical assets. Despite the challenge of selecting the right technology for specific needs from a wide range of indoor RTLS options, this study provides a solution to assist manufacturing companies in exploring and implementing IoT technologies for their RTLS needs. The current academic literature has not adequately addressed this industrial reality. This paper assesses the potential of Passive UHF RFID-RTLS in Industry 5.0, addressing the confusion caused by the emergence of new ’passive’ RFID solutions that compete with established ’active’ solutions. Our research aims to clarify the real-world performance of passive RTLS solutions and propose an updated classification of RTLS systems in the academic literature. We have thoroughly reviewed both the academic and industry literature to remain up to date with the latest market advancements. Passive UHF RFID has been proven to be a valuable addition to the RTLS domain, capable of addressing certain challenges. This has been demonstrated through the successful implementation in two industrial sites, each with different types of tagged objects.
Comparison of Different NDT Techniques for Evaluation of the Quality of PCBs Produced Using Traditional vs. Additive Manufacturing Technologies
Authors: Jasiūnienė Elena , Raišutis Renaldas , Samaitis Vykintas , Jankauskas Audrius
Published: March 2024

Multilayer printed circuit boards (PCBs) can be produced not only in the traditional way but also additively. Both traditional and additive manufacturing can lead to invisible defects in the internal structure of the electronic component, eventually leading to the spontaneous failure of the device. No matter what kind of technology is used for the production of PCBs, when they are used in important structures, quality control is important to ensure the reliability of the component. The nondestructive testing (NDT) of the structure of manufactured electronic components can help ensure the quality of devices. Investigations of possible changes in the structure of the product can help identify the causes of defects. Different types of manufacturing technologies can lead to diverse types of possible defects. Therefore, employing several nondestructive inspection techniques could be preferable for the inspection of electronic components. In this article, we present a comparison of various NDT techniques for the evaluation of the quality of PCBs produced using traditional and additive manufacturing technologies. The methodology for investigating the internal structure of PCBs is based on several of the most reliable and widely used technologies, namely, acoustic microscopy, active thermography, and radiography. All of the technologies investigated have their advantages and disadvantages, so if high-reliability products are to be produced, it would be advantageous to carry out tests using multiple technologies in order to detect the various types of defects and determine their parameters.
Unveiling Morphine: A Rapid and Selective Fluorescence Sensor for Forensic and Medical Analysis
Authors: Boroujerdi Ramin , Butt Andrew , Paul Richard , Majumder Santanu
Published: March 2024

Opioid use, particularly morphine, is linked to CNS-related disorders, comorbidities, and premature death. Morphine, a widely abused opioid, poses a significant global health threat and serves as a key metabolite in various opioids. Here, we present a turn-off fluorescent sensor capable of detecting morphine with exceptional sensitivity and speed in various samples. The fluorescent sensor was developed through the dimerization process of 7-methoxy-1-tetralone and subsequent demethylation to produce the final product. Despite morphine possessing inherent fluorophoric properties and emitting light in an approximately similar wavelength as the sensor’s fluorescent blue light, the introduction of the target molecule (morphine) in the presence of the sensor caused a reduction in the sensor’s fluorescence intensity, which is attributable to the formation of the sensor–morphine complex. By utilizing this fluorescence quenching sensor, the chemo-selective detection of morphine becomes highly feasible, encompassing a linear range from 0.008 to 40 ppm with an impressive limit of detection of 8 ppb. Consequently, this molecular probe demonstrates a successful application in determining trace amounts of morphine within urine, yielding satisfactory analytical results. The study also explores the effect of several variables on the sensor’s response and optimizes the detection of morphine in urine using a response surface methodology with a central composite design.
Hardware Schemes for Smarter Indoor Robotics to Prevent the Backing Crash Framework Using Field Programmable Gate Array-Based Multi-Robots
Authors: Basha Mudasar , Siva Kumar Munuswamy , Chinnaiah Mangali Chinna , Lam Siew-Kei , Srikanthan Thambipillai , Narambhatla Janardhan , Dodde Hari Krishna , Dubey Sanjay
Published: March 2024

The use of smart indoor robotics services is gradually increasing in real-time scenarios. This paper presents a versatile approach to multi-robot backing crash prevention in indoor environments, using hardware schemes to achieve greater competence. Here, sensor fusion was initially used to analyze the state of multi-robots and their orientation within a static or dynamic scenario. The proposed novel hardware scheme-based framework integrates both static and dynamic scenarios for the execution of backing crash prevention. A round-robin (RR) scheduling algorithm was composed for the static scenario. Dynamic backing crash prevention was deployed by embedding a first come, first served (FCFS) scheduling algorithm. The behavioral control mechanism of the distributed multi-robots was integrated with FCFS and adaptive cruise control (ACC) scheduling algorithms. The integration of multiple algorithms is a challenging task for smarter indoor robotics, and the Xilinx-based partial reconfiguration method was deployed to avoid computational issues with multiple algorithms during the run-time. These methods were coded with Verilog HDL and validated using an FPGA (Zynq)-based multi-robot system.
Crack Detection and Analysis of Concrete Structures Based on Neural Network and Clustering
Authors: Choi Young , Park Hee Won , Mi Yirong , Song Sujeen
Published: March 2024

Concrete is extensively used in the construction of infrastructure such as houses and bridges. However, the appearance of cracks in concrete structures over time can diminish their sealing and load-bearing capability, potentially leading to structural failures and disasters. The timely detection of cracks allows for repairs without the need to replace the entire structure, resulting in cost savings. Currently, manual inspection remains the predominant method for identifying concrete cracks. However, in today’s increasingly complex construction environments, subjective errors may arise due to human vision and perception. The purpose of this work is to investigate and design an autonomous convolutional neural network-based concrete detection system that can identify cracks automatically and use that information to calculate the crack proportion. The experiment’s findings show that the trained model can classify concrete cracks with an accuracy of 99.9%. Moreover, the clustering technique applied to crack images enables the clear identification of the percentage of cracks, which facilitates the development of concrete damage level detection over time.
Enhancing Well-Being: A Comparative Study of Virtual Reality Chromotherapy Rooms with Static, Dynamic, and Empty Environments
Authors: Dastan Mine , Ricci Marina , Vangi Fabio , Fiorentino Michele
Published: March 2024

Chromotherapy rooms (CRs) are physical spaces with colored lights able to enhance an individual’s mood, well-being, and, in the long term, their health. Virtual reality technology can be used to implement CR (VRCRs) and provide higher flexibility at lower costs. However, existing VRCRs are limited to a few use cases, and they do not fully explore the potential and pitfalls of the technology. This work contributes by comparing three VRCR designs: empty, static, and dynamic. Empty is just a void but a blue-colored environment. Static adds static abstract graphics (flowers and sea texture), and dynamic adds dynamic elements (animated star particle systems, fractals, and ocean flow). All conditions include relaxing low-beta and ocean sounds. We conducted a between-subject experiment (n = 30) with the three conditions. Subjects compiled a self-perceived questionnaire and a mathematical stress test before and after the VRCR experience. The results demonstrated that the dynamic condition provided a higher sense of presence, while the self-perceived stress level was insignificant. Dynamic VR conditions are perceived as having a shorter duration, and participants declared that they felt more involved and engaged than in the other conditions. Overall, the study demonstrated that VRCRs have a non-trivial behavior and need further study of their design, especially considering their role in a future where VR will be an everyday working interface.
Autonomous Sensor System for Low-Capacity Wind Turbine Blade Vibration Measurement
Authors: Muxica Diego , Rivera Sebastian , Orchard Marcos E. , Ahumada Constanza , Jaramillo Francisco , Bravo Felipe , Gutiérrez José M. , Astroza Rodrigo
Published: March 2024

This paper presents the design, implementation, and validation of an on-blade sensor system for remote vibration measurement for low-capacity wind turbines. The autonomous sensor system was deployed on three wind turbines, with one of them operating in harsh weather conditions in the far south of Chile. The system recorded the acceleration response of the blades in the flapwise and edgewise directions, data that could be used for extracting the dynamic characteristics of the blades, information useful for damage diagnosis and prognosis. The proposed sensor system demonstrated reliable data acquisition and transmission from wind turbines in remote locations, proving the ability to create a fully autonomous system capable of recording data for monitoring and evaluating the state of health of wind turbine blades for extended periods without human intervention. The data collected by the sensor system presented in this study can serve as a foundation for developing vibration-based strategies for real-time structural health monitoring.
Advanced Data Processing of Pancreatic Cancer Data Integrating Ontologies and Machine Learning Techniques to Create Holistic Health Records
Authors: Manias George , Azqueta-Alzúaz Ainhoa , Dalianis Athanasios , Griffiths Jacob , Kalogerini Maritini , Kostopoulou Konstantina , Kouremenou Eleftheria , Kranas Pavlos , Kyriazakos Sofoklis , Lekka Danae , Melillo Fabio , Patiño-Martinez Marta , Garcia-Perales Oscar , Pnevmatikakis Aristodemos , Torrens Salvador Garcia , Wajid Usman , Kyriazis Dimosthenis
Published: March 2024

The modern healthcare landscape is overwhelmed by data derived from heterogeneous IoT data sources and Electronic Health Record (EHR) systems. Based on the advancements in data science and Machine Learning (ML), an improved ability to integrate and process the so-called primary and secondary data fosters the provision of real-time and personalized decisions. In that direction, an innovative mechanism for processing and integrating health-related data is introduced in this article. It describes the details of the mechanism and its internal subcomponents and workflows, together with the results from its utilization, validation, and evaluation in a real-world scenario. It also highlights the potential derived from the integration of primary and secondary data into Holistic Health Records (HHRs) and from the utilization of advanced ML-based and Semantic Web techniques to improve the quality, reliability, and interoperability of the examined data. The viability of this approach is evaluated through heterogeneous healthcare datasets pertaining to personalized risk identification and monitoring related to pancreatic cancer. The key outcomes and innovations of this mechanism are the introduction of the HHRs, which facilitate the capturing of all health determinants in a harmonized way, and a holistic data ingestion mechanism for advanced data processing and analysis.
Aptamer-Based Sensor for Rapid and Sensitive Detection of Ofloxacin in Meat Products
Authors: Wang Siyuan , Bao Xiuli , Liu Mingwang , Hao Qingfang , Zhang Shuai , Li Siying , Zhang Lei , Kang Xinxin , Lyu Mingsheng , Wang Shujun
Published: March 2024

Ofloxacin (OFL) is widely used in animal husbandry and aquaculture due to its low price and broad spectrum of bacterial inhibition, etc. However, it is difficult to degrade and is retained in animal-derived food products, which are hazardous to human health. In this study, a simple and efficient method was developed for the detection of OFL residues in meat products. OFL coupled with amino magnetic beads by an amination reaction was used as a stationary phase. Aptamer AWO-06, which showed high affinity and specificity for OFL, was screened using the exponential enrichment (SELEX) technique. A fluorescent biosensor was developed by using AWO-06 as a probe and graphene oxide (GO) as a quencher. The OFL detection results could be obtained within 6 min. The linear range was observed in the range of 10–300 nM of the OFL concentration, and the limit of the detection of the sensor was 0.61 nM. Furthermore, the biosensor was stored at room temperature for more than 2 months, and its performance did not change. The developed biosensor in this study is easy to operate and rapid in response, and it is suitable for on-site detection. This study provided a novel method for the detection of OFL residues in meat products.
Optimization of Clustering and Trajectory for Minimizing Age of Information in Unmanned Aerial Vehicle-Assisted Mobile Edge Computing Network
Authors: Shen Huicong , Wang Die , Huang Zhen , Jia Yunjian
Published: March 2024

With the development of the Internet of Things (IoT) technology, massive amounts of sensor data in applications such as fire monitoring need to be transmitted to edge servers for timely processing. However, there is an energy-hole phenomenon in transmitting data only through terrestrial multi-hop networks. In this study, we focus on the data collection task in an unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) network, where a UAV is deployed as the mobile data collector for the ground sensor nodes (SNs) to ensure high information freshness. Meanwhile, the UAV is equipped with an edge server for data caching. We first establish a rigorous mathematical model in which the age of information (AoI) is used as a measure of information freshness, related to both the data collection time and the UAV’s flight time. Then a mixed-integer non-convex optimization problem is formulated to minimize the peak AoI of the collected data. To solve the problem efficiently, we propose an iterative two-step algorithm named the AoI-minimized association and trajectory planning (AoI-MATP) algorithm. In each iteration, the optimal SN–collection point (CP) associations and CP locations for the parameter ε are first obtained by the affinity propagation clustering algorithm. The optimal UAV trajectory is found using an improved elite genetic algorithm. Simulation results show that based on the optimized ε, the AoI-MATP algorithm can achieve a balance between data collection time and flight time, reducing the peak AoI of the collected data.
Temporal and Spatial Evolution of Meteorological Drought in Inner Mongolia Inland River Basin and Its Driving Factors
Authors: Zhang Weijie , Guo Hengzhi , Wu Yingjie , Zhang Zezhong , Yin Hang , Feng Kai , Liu Jian , Fu Bin
Published: March 2024

In order to analyze the temporal and spatial evolution of meteorological drought and explore its driving factors, the inland river basin of Inner Mongolia (IMIRB) was taken as a typical research area, the Standardized Precipitation Evapotranspiration Index (SPEI) of various scales was calculated, and the spatio-temporal trend change characteristics of meteorological drought were analyzed combined with the modified Mann–Kendall trend test (MMK). The typical meteorological drought events were analyzed by using the three-dimensional identification method, and the spatio-temporal evolution characteristics and dynamic evolution law of meteorological drought were analyzed comprehensively and accurately. The driving effects of Pacific Decadal Oscillation (PDO), North Atlantic Multidecadal Oscillation (AMO), Arctic Oscillation (AO), El Niño-Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), and sunspot on meteorological drought were investigated by using the cross wavelet method. The results are as follows: (1) with the increase of SPEI time scale, the frequency of meteorological drought decreased, but the duration and intensity of drought increased; (2) the trend was greatest in spring, with the largest number of areas showing a significant downward trend in SPEI, the strongest persistence in intensity, and significant aridification characteristics; (3) summer meteorological droughts had the largest area of high intensity drought but the smallest area of high frequency areas, and winter droughts had the smallest area of high intensity drought but the largest percentage of high frequency areas; (4) the meteorological drought event that occurred from April 2017 to December 2017 was the most serious, and reached its maximum value in June 2017, which mainly experienced five processes: occurrence—intensification—attenuation—re-intensification—extinction; (5) atmospheric circulation factor, sunspot, and meteorological drought of IMIRB were correlated, and ENSO had the greatest effect on drought. This study provides effective theoretical support for IMIRB drought prevention and disaster reduction.
A Comparison of the Chronologies of Introduced versus Native Coniferous Tree Species Growing in Northwestern Poland during the Period of Global Warming
Authors: Cedro Anna , Nowak Grzegorz
Published: March 2024

The ongoing climatic changes are causing the extinction of numerous species or their withdrawal from previously occupied areas. The environmental and economic significance of introduced species may increase. The aim of the present study was to examine the rate of growth of coniferous species growing in northwestern Poland and to analyze the tree ring width–climate relationships. Six tree species were selected for this study. Two of these species have natural occurrences in Poland: Pinus sylvestris and Larix decidua. The remaining four species were introduced from North America: Chamaecyparis lawsoniana, Thuja plicata, Pseudotsuga menziesii, and Pinus strobus. Samples were collected from 131 trees using a Pressler borer at 1.3 m above ground. Tree ring widths were measured down to 0.01 mm. Climatic data were retrieved from a weather station located 23 km from the study plot. The average tree ring width reaches the lowest value for the P. sylvestris chronology (1.62 mm/year) and for P. strobus (1.69 mm/year), and the highest value is reached for T. plicata (2.80 mm/year) and P. menziesii (2.56 mm/year). The analysis of weather conditions in the designated pointer years and the response function analysis indicate that winter and early spring air temperature is the factor responsible for the formation of wide tree rings in the following species studied: P. sylvestris, C. lawsoniana, P. menziesii, and T. plicata. For L. decidua and P. strobus, the climate–growth relationships are different: weather conditions in the previous growth year are important, and it is the weather in the late spring and summer months. Two of the investigated introduced species (T. plicata and P. menziesii) are characterized by very good acclimatization and are best adapted to the new habitat during the current climate changes. These tree species can constitute a basis for replacing native species, which, due to increasingly severe droughts and higher temperatures, are doing less and less well in their current habitats. Foresters wanting to conduct sustainable forest management will look for replacement species that are well adapted to new habitat conditions in order to maintain the continuity of forest cover.
Solar Landscapes: A Methodology for the Adaptive Integration of Renewable Energy Production into Cultural Landscapes
Authors: Car Chrili , Frohmann Erwin , Grimm-Pretner Dagmar
Published: March 2024

The increasing use of solar energy is an integral step toward carbon neutrality. At the same time, outdoor solar farms are significantly altering existing cultural landscapes. This work examines the possibilities of integrating the use of solar energy into these landscapes in such a way that the unique, regional character of places is preserved and enhanced. The research project that was carried out developed a conceptual design approach that takes as its starting point landscape architectural and aesthetic analyses of existing sites in Styria, Austria, the spatial characteristics of the cultural landscapes in which they are embedded, and their suitability for generating solar energy. The comparison of a site’s characteristics with the technical possibilities evaluated from a literature review enables a responsive design practice using solar modules. The result is a method of landscape architectural design that integrates solar energy on the basis of an adaptive site-specific approach as well as a catalogue of sample cases that illustrate how designing with solar modules can honor and add value to existing places while enhancing their ecological, economic, and social functions.
Patent Protection Policy and Firms’ Green Technology Innovation: Mediating Roles of Open Innovation and Human Capital
Authors: Chen Dong , Chen Shi
Published: March 2024

Green innovations such as renewable energy technologies and cleaner process modifications are important technical routes and critical directions for reducing carbon emissions from industrial production processes. This study examines the impact of intellectual property protection on green technology innovation, constructing a progressive difference-in-differences model using 849 listed manufacturing firms panel data from 2007 to 2019 and taking the Chinese Intellectual Property Rights model cities as a quasi-natural experiment. Our study finds that the pilot policy significantly enhances corporate green innovation. When considering heterogeneity, the policy treatment effect is more remarkable for large firms, state-owned enterprises, and industries where technology can be easily imitated. Moreover, the mediating effect shows that the policy promotes green innovation by encouraging firms’ research and development cooperation and increasing human capital levels. This study proposes that policymakers should reinforce intellectual property protection, encourage companies to be better and bigger, and emphasize the intermediary function of open innovation and human capital in green technology innovation.
The Impact of Environmental Regulation on Collaborative Innovation Efficiency: Is the Porter Hypothesis Valid in Chengdu–Chongqing Urban Agglomeration?
Authors: Wang Zhaohan , Fu Ying , Wu Junqian
Published: March 2024

Under the advocacy of sustainable and innovation-driven development, the potential impact of environmental regulation on collaborative innovation has become a controversial issue. This article uses panel data from 16 cities in the Chengdu–Chongqing urban agglomeration from 2011 to 2021 to analyze the impact of environmental regulation on collaborative innovation efficiency. First, this study uses the two-stage DEA model to analyze each city’s industry–university–research collaborative innovation efficiency. Then, the impact of environmental regulation on collaborative innovation is analyzed using the Tobit model. The results show that in the temporal dimension, the collaborative innovation efficiency of each city shows an upward trend. This demonstrates the outstanding effectiveness of transforming knowledge into technology for economic development. In the spatial dimension, the collaborative innovation efficiency of this urban agglomeration shows a “high in the center and low in the surroundings” pattern. The Tobit regression model shows that environmental regulation significantly impacts collaborative innovation in the Chengdu–Chongqing urban agglomeration. Command-and-control environmental regulation policies have a threshold effect on collaborative innovation, verifying the Porter hypothesis that appropriate environmental regulation promotes innovative activities. The results provide an initial basis for formulating regional environmental policies to achieve a win–win situation for innovation and sustainability in underdeveloped regions.
Spatial Diversity Changes in Land Use and Land Cover Mix in Central European Capitals and Their Commuting Zones from 2006 to 2018
Authors: Kudas Dawid , Wnęk Agnieszka , Hudecová Ľubica , Fencik Robert
Published: March 2024

This article investigates the land use and land cover (LULC) mosaic as a function of distance to the city centre. The research area is four Functional Urban Areas (FUAs) of the capitals of Central European countries: Czechia (Prague), Poland (Warsaw), Slovakia (Bratislava), and Hungary (Budapest). The article presents LULC mix changes in these FUAs in the context of transformations in urban cores and commuting zones of capital city metropolises, which have large populations and prominent positions in the country or region. The study makes use of Urban Atlas LULC data for 2006, 2012, and 2018. LULC change was analysed using a hexagonal tessellation with the hexagon as the basic spatial unit. Spatial entropy (ENT) and Simpson’s Diversity Index (SIDI) were employed. The change in ENT and SIDI were determined as a function of distance to urban cores, as well as changes on the first level of Urban Atlas nomenclature for 2006–2012 and 2012–2018, as well as on the third level of nomenclature for 2012–2018. The research shows that changes from 2006 to 2012 were more considerable than from 2012 to 2018. It also revealed that, if LULC classes are considered on the first level of nomenclature, diversity in urban cores grows and then declines in commuting zones. An analysis of diversity on the third level of nomenclature demonstrated its decline with the growing distance to the urban core. It has also been demonstrated that the mean values of ENT and SIDI are approximately twice as high in urban cores as in commuting zones, indicating a plateau of the mean value of ENT and SIDI over the study period in urban cores compared to an increase in commuting zones around them. The conducted research will be helpful to urban planners and decision-makers in directing the further, inevitable development of metropolitan areas in accordance with sustainable environmental management.