bluuebunny/crossref_metadata_2025 huggingface dataset:
Cross-Validation of a Multiplex LC-MS/MS Method for Assaying mAbs Plasma Levels in Patients with Cancer: A GPCO-UNICANCER Study
Authors: Marin Clémence , Khoudour Nihel , Millet Aurélien , Lebert Dorothée , Bros Pauline , Thomas Fabienne , Ternant David , Lacarelle Bruno , Guitton Jérôme , Ciccolini Joseph , Blanchet Benoit
Published: August 2021

Background: Different liquid chromatography tandem mass spectrometry (LC–MS/MS) methods have been published for quantification of monoclonal antibodies (mAbs) in plasma but thus far none allowed the simultaneous quantification of several mAbs, including immune checkpoint inhibitors. We developed and validated an original multiplex LC–MS/MS method using a ready-to-use kit to simultaneously assay 7 mAbs (i.e., bevacizumab, cetuximab, ipilimumab, nivolumab, pembrolizumab, rituximab and trastuzumab) in plasma. This method was next cross-validated with respective reference methods (ELISA or LC–MS/MS). Methods: The mAbXmise kit was used for mAb extraction and full-length stable-isotope-labeled antibodies as internal standards. The LC–MS/MS method was fully validated following current EMA guidelines. Each cross validation between reference methods and ours included 16–28 plasma samples from cancer patients. Results: The method was linear from 2 to 100 µg/mL for all mAbs. Inter- and intra-assay precision was <14.6% and accuracy was 90.1–111.1%. The mean absolute bias of measured concentrations between multiplex and reference methods was 10.6% (range 3.0–19.9%). Conclusions: We developed and cross-validated a simple, accurate and precise method that allows the assay of up to 7 mAbs. Furthermore, the present method is the first to offer a simultaneous quantification of three immune checkpoint inhibitors likely to be associated in patients.
Achyrocline satureioides (Lam.) DC (Asteraceae) Extract-Loaded Nanoemulsions as a Promising Topical Wound Healing Delivery System: In Vitro Assessments in Human Keratinocytes (HaCaT) and HET-CAM Irritant Potential
Authors: Balestrin Lucélia Albarello , Kreutz Tainá , Fachel Flávia Nathiely Silveira , Bidone Juliana , Gelsleichter Nicolly Espindola , Koester Letícia Scherer , Bassani Valquiria Linck , Braganhol Elizandra , Dora Cristiana Lima , Teixeira Helder Ferreira
Published: August 2021

Achyrocline satureioides (Lam.) DC Asteraceae extracts (ASEs) have been investigated for the treatment of various skin disorders. This study reports the effects of ASE-loaded nanoemulsions (NEASE) on the cellular viability, death by necrosis, and migration of immortalized human keratinocytes (HaCaT cell line), as well as the irritant potential through the hen’s egg chorioallantoic membrane test (HET-CAM). NEASE exhibited a polydispersity index above 0.12, with a droplet size of 300 nm, ζ-potential of −40 mV, and content of flavonoids close to 1 mg/mL. No cytotoxicity of the ASE was observed on HaCaT by MTT assay (up to 10 µg/mL). A significant increase of HaCaT viability was observed to NEASE (up to 5 μg/mL of flavonoids), compared to treatment with the ASE. The necrosis death evaluation demonstrated that only NEASE did not lead to cell death at all the tested concentrations. The scratch assay demonstrated that NEASE was able to increase the cell migration at low flavonoid concentrations. Finally, the HET-CAM test proved the non-irritative potential of NEASE. Overall, the results indicate the potential of the proposed formulations for topical use in wound healing, in view of their promising effects on proliferation and migration in keratinocytes, combined with an indication of the absence of cytotoxicity and non-irritating potential.
Chemical Treatment of Bio-Derived Industrial Waste Filled Recycled Low-Density Polyethylene: A Comparative Evaluation
Authors: Sider Ishaq , Nassar Mahmoud M. A.
Published: August 2021

The search for renewable alternatives for petroleum products that can be used in industrial applications is increasing. Each year, several tons of bio-derived industrial waste is produced and most of it is burned or placed in landfills. Olive pits (OP) have unique characteristics such as abundance, renewability, and biodegradability, which can be utilized to develop new types of biocomposites. One of the most promising uses of OP is that they can reinforce the mechanical properties of polymeric biocomposites. This study describes the preparation of recycled low-density polyethylene (rLDPE) that is filled with OP flour (10, 20, 30, and 40 wt.%) using a twin-screw extruder. The effects of the chemical treatment of the OP surface (sodium hydroxide (NaOH) and dimethyl sulfoxide (DMSO)) on the bio-filler/polymer compatibility along with the produced composite’s chemical, physical, mechanical, and thermal properties have been explored. Overall, the reinforced composites that were obtained with alkali-treated OP have better biocomposite properties. This indicates an improved compatibility between the bio-filler and matrix. The results are promising in terms of using OP flour in developing green composites.
Unravelling Main- and Side-Chain Motions in Polymers with NMR Spectroscopy and Relaxometry: The Case of Polyvinyl Butyral
Authors: Calucci Lucia , Pizzanelli Silvia , Mandoli Alessandro , Birczyński Artur , Lalowicz Zdzisław T. , De Monte Cristina , Ricci Lucia , Bronco Simona
Published: August 2021

Polyvinyl butyral (PVB) is an amorphous polymer employed in many technological applications. In order to highlight the relationships between macroscopic properties and dynamics at a microscopic level, motions of the main-chain and of the propyl side-chains were investigated between Tg − 288 °C and Tg + 55 °C, with Tg indicating the glass transition temperature. To this aim, a combination of solid state Nuclear Magnetic Resonance (NMR) methods was applied to two purposely synthesized PVB isotopomers: one fully protonated and the other perdeuterated on the side-chains. 1H time domain NMR and 1H field cycling NMR relaxometry experiments, performed across and above Tg, revealed that the dynamics of the main-chain corresponds to the α-relaxation associated to the glass transition, which was previously characterized by dielectric spectroscopy. A faster secondary relaxation was observed for the first time and ascribed to side-chains. The geometry and rate of motions of the different groups in the side-chains were characterized below Tg by 2H NMR spectroscopy.
Can Accelerated Aging Procedures Predict the Long Term Behavior of Polymers Exposed to Different Environments?
Authors: Frigione Mariaenrica , Rodríguez-Prieto Alvaro
Published: August 2021

During their useful life, polymers are subject to degradation processes due to exposure to specific environmental conditions over long times. These processes generally lead to changes, almost always irreversible, of properties and performances of polymers, changes which would be useful to be able to predict in advance. To meet this need, numerous investigations have been focused on the possibility to predict the long-term performance of polymers, if exposed to specific environments, by the so called “accelerated aging” tests. In such procedures, the long-term behavior of polymeric materials is typically predicted by subjecting them to cycles of radiations, temperatures, vapor condensation, and other external agents, at levels well above those found in true conditions in order to accelerate the degradation of polymers: this can produce effects that substantially deviate from those observable under natural exposure. Even following the standard codes, different environmental parameters are often used in the diverse studies, making it difficult to compare different investigations. The correlation of results from accelerated procedures with data collected after natural exposure is still a debated matter. Furthermore, since the environmental conditions are a function of the season and the geographical position, and are also characteristic of the type of exposure area, the environmental parameters to be used in accelerated aging tests should also consider these variables. These and other issues concerning accelerated aging tests applied to polymers are analyzed in the present work. However, bearing in mind the limitations of these practices, they can find useful applications for rating the durability of polymeric materials.
Wood-Mimicking Bio-Based Biporous Polymeric Materials with Anisotropic Tubular Macropores
Authors: Srikanthan Vierajitha , Pitois Olivier , Coussot Philippe , Le Droumaguet Benjamin , Grande Daniel
Published: August 2021

Understanding physical phenomena related to fluid flow transport in plants and especially through wood is still a major challenge for the scientific community. To this end, we have focused our attention on the design of wood-mimicking polymeric architectures through a strategy based on the double porogen templating approach which relies on the use of two distinct types of porogens, namely aligned nylon threads and a porogenic solvent, to produce macro- and nanoporosity levels, respectively. A bio-based phenolic functional monomer, i.e., vanillin methacrylate, was employed to mimic either hard wood or soft wood. Upon free-radical polymerization with a crosslinking agent in the presence of both types of porogenic agents, followed by their removal, biporous materials with anistotropic tubular macropores surrounded by a nanoporous matrix were obtained. They were further fully characterized in terms of porosity and chemical composition via mercury intrusion porosimetry, scanning electron microscopy and X-ray microtomography. It was demonstrated that the two porosity levels could be independently tuned by varying structural parameters. Further, the possibility to chemically modify the pore surface and thus to vary the material surface properties was successfully demonstrated by reductive amination with model compounds via Raman spectroscopy and water contact angle measurements.
Modeling the Optical Properties of a Polyvinyl Alcohol-Based Composite Using a Particle Swarm Optimized Support Vector Regression Algorithm
Authors: Owolabi Taoreed O. , Abd Rahman Mohd Amiruddin
Published: August 2021

We developed particle swarm optimization-based support vector regression (PSVR) and ordinary linear regression (OLR) models for estimating the refractive index (n) and energy gap (E) of a polyvinyl alcohol composite. The n-PSVR model, which can estimate the refractive index of a polyvinyl alcohol composite using the energy gap as a descriptor, performed better than the n-OLR model in terms of root mean square error (RMSE) and mean absolute error (MAE) metrics. The E-PSVR model, which can predict the energy gap of a polyvinyl alcohol composite using its refractive index descriptor, outperformed the E-OLR model, which uses similar descriptor based on several performance measuring metrics. The n-PSVR and E-PSVR models were used to investigate the influences of sodium-based dysprosium oxide and benzoxazinone derivatives on the energy gaps of a polyvinyl alcohol polymer composite. The results agreed well with the measured values. The models had low mean absolute percentage errors after validation with external data. The precision demonstrated by these predictive models will enhance the tailoring of the optical properties of polyvinyl alcohol composites for the desired applications. Costs and experimental difficulties will be reduced.
Synthesis and Physicochemical Characteristics of Chitosan-Based Polyurethane Flexible Foams
Authors: Piotrowska-Kirschling Agnieszka , Olszewski Adam , Karczewski Jakub , Piszczyk Łukasz , Brzeska Joanna
Published: August 2021

The use of shrimp waste to obtain chitosan (Ch) is an essential issue, considering a circular economy, waste management, and its application to environmentally friendly materials. In this study, northern prawn shells were utilized to obtain Ch, which could then be used for synthesizing chitosan-based polyurethane (PUR+Ch) foams with different Ch concentration. The chemical structure, morphology, hardness, thermal properties, viscoelastic properties, and sorption properties in relation to oil and water of these materials were determined. The results present that the addition of Ch into PUR influences the physicochemical characteristics and properties of the tested materials. PUR+Ch foams with 1–3 wt% Ch had more open cells and were softer than neat PUR. PUR+Ch1 had the best thermal properties. PUR+Ch2 foam with 2 wt% Ch as a whole was characterized as having the highest water sorption. The PUR+Ch1 foam with 1 wt% Ch had the best oil sorption. This paper shows that the modification of PUR by Ch is a very promising solution, and PUR+Ch foams can be applied in the water treatment of oil spills, which can be dangerous to the water environment.
Risk Propagation of Concentralized Distribution Logistics Plan Change in Cruise Construction
Authors: Zheng Yahong , Ke Jiangcen , Wang Haiyan
Published: August 2021

Compared with the ordinary merchant ship building, the concentralized distribution in cruise building is more complex. Plan change is a common phenomenon in cruise building, and it is easy to lead to mismatch between production and logistics, resulting in risks such as production schedule delay and inventory backlog. In order to reduce the adverse effects of plan change on the shipyard, it is necessary to conduct an in-depth study on the risks of a centralized distribution logistics plan. Based on the analysis of the composition of the centralized distribution logistics planning system, risk factors in different plan links are identified in this paper. A system dynamic model is constructed to simulate the propagation of five basic types of planning risk, including procurement plan, warehousing plan, pallet concentralization plan, distribution plan and production plan. In the case study of HVAC (heating, ventilation and air conditioning) materials, the values of risk factors are estimated though consulting experts with questionnaire. The weight of each risk factor in each subsystem is calculated by a method combined with analytic hierarchy process and coefficient of variation method. Through the simulation experiments carried out in Vensim, it is found that both inventory backlog risk and cruise construction schedule delay risk increase with the increasement of estimated values of risk factors, which is an effective proof of the rationality of the model, and that the most sensitive risk factor for both the two kinds of risk is production planning risk.
Extraction of Areas of Rice False Smut Infection Using UAV Hyperspectral Data
Authors: An Gangqiang , Xing Minfeng , He Binbin , Kang Haiqi , Shang Jiali , Liao Chunhua , Huang Xiaodong , Zhang Hongguo
Published: August 2021

Rice false smut (RFS), caused by Ustilaginoidea virens, is a significant grain disease in rice that can lead to reduced yield and quality. In order to obtain spatiotemporal change information, multitemporal hyperspectral UAV data were used in this study to determine the sensitive wavebands for RFS identification, 665–685 and 705–880 nm. Then, two methods were used for the extraction of rice false smut-infected areas, one based on spectral similarity analysis and one based on spectral and temporal characteristics. The final overall accuracy of the two methods was 74.23 and 85.19%, respectively, showing that the second method had better prediction accuracy. In addition, the classification results of the two methods show that the areas of rice false smut infection had an expanding trend over time, which is consistent with the natural development law of rice false smut, and also shows the scientific nature of the two methods.
EAAU-Net: Enhanced Asymmetric Attention U-Net for Infrared Small Target Detection
Authors: Tong Xiaozhong , Sun Bei , Wei Junyu , Zuo Zhen , Su Shaojing
Published: August 2021

Detecting infrared small targets lacking texture and shape information in cluttered environments is extremely challenging. With the development of deep learning, convolutional neural network (CNN)-based methods have achieved promising results in generic object detection. However, existing CNN-based methods with pooling layers may lose the targets in the deep layers and, thus, cannot be directly applied for infrared small target detection. To overcome this problem, we propose an enhanced asymmetric attention (EAA) U-Net. Specifically, we present an efficient and powerful EAA module that uses both same-layer feature information exchange and cross-layer feature fusion to improve feature representation. In the proposed approach, spatial and channel information exchanges occur between the same layers to reinforce the primitive features of small targets, and a bottom-up global attention module focuses on cross-layer feature fusion to enable the dynamic weighted modulation of high-level features under the guidance of low-level features. The results of detailed ablation studies empirically validate the effectiveness of each component in the network architecture. Compared to state-of-the-art methods, the proposed method achieved superior performance, with an intersection-over-union (IoU) of 0.771, normalised IoU (nIoU) of 0.746, and F-area of 0.681 on the publicly available SIRST dataset.
An Investigation of NEXRAD-Based Quantitative Precipitation Estimates in Alaska
Authors: Nelson Brian R. , Prat Olivier P. , Leeper Ronald D.
Published: August 2021

Precipitation estimation by weather radars in Alaska is challenging. In this study, we investigate National Weather Service (NWS) precipitation products that are produced from the seven NEXRAD radar sites in Alaska. The NWS precipitation processing subsystem generates stages of data at each NEXRAD site which are then input to the weather forecast office to generate a regionwide precipitation product. Data from the NEXRAD sites and the operational rain gauges in the weather forecast region are used to produce this regionwide product that is then sent to the National Centers for Environmental Prediction (NCEP) to be included in the NCEP Stage IV distribution. The NCEP Stage IV product for Alaska has been available since 2017. We use the United States Climate Reference Network (USCRN) data from Alaska to compare to the NCEP Stage IV data. Given that the USCRN can be used in the production of the NCEP Stage IV data for Alaska, we also used the NEXRAD Digital Precipitation Array (DPA) that is generated at the site for comparison of the radar-only products. Comparing the NEXRAD-based data from Alaska to the USCRN gauge estimates using the USCRN site information on air temperature, we are able to condition the analysis based on the hourly or 6-hourly average air temperature. The estimates in the frozen phase of precipitation largely underestimate as compared to the gauge, and the correlation is low with larger errors as compared to other phases of precipitation. In the mixed phase the underestimation of precipitation improves, but the correlation is still low with relatively large errors as compared to the rain phases of precipitation. The difficulties in precipitation estimation in cold temperatures are well known and we show the evaluation for the NCEP Stage IV regional data for Alaska and the NEXRAD site specific Digital Precipitation Array (DPA) data. Results show the challenges of estimating mixed-phase and frozen precipitation. However, the DPA data shows somewhat better performance in the mixed precipitation phase, which suggests that the NWS Precipitation Processing Subsystem (PPS) is tuned to the climatology as it relates to precipitation in Alaska.
A Scheduling Mechanism Based on Optimization Using IoT-Tasks Orchestration for Efficient Patient Health Monitoring
Authors: Iqbal Naeem , Imran  , Ahmad Shabir , Ahmad Rashid , Kim Do-Hyeun
Published: August 2021

Over the past years, numerous Internet of Things (IoT)-based healthcare systems have been developed to monitor patient health conditions, but these traditional systems do not adapt to constraints imposed by revolutionized IoT technology. IoT-based healthcare systems are considered mission-critical applications whose missing deadlines cause critical situations. For example, in patients with chronic diseases or other fatal diseases, a missed task could lead to fatalities. This study presents a smart patient health monitoring system (PHMS) based on an optimized scheduling mechanism using IoT-tasks orchestration architecture to monitor vital signs data of remote patients. The proposed smart PHMS consists of two core modules: a healthcare task scheduling based on optimization and optimization of healthcare services using a real-time IoT-based task orchestration architecture. First, an optimized time-constraint-aware scheduling mechanism using a real-time IoT-based task orchestration architecture is developed to generate autonomous healthcare tasks and effectively handle the deployment of emergent healthcare tasks. Second, an optimization module is developed to optimize the services of the e-Health industry based on objective functions. Furthermore, our study uses Libelium e-Health toolkit to monitors the physiological data of remote patients continuously. The experimental results reveal that an optimized scheduling mechanism reduces the tasks starvation by 14% and tasks failure by 17% compared to a conventional fair emergency first (FEF) scheduling mechanism. The performance analysis results demonstrate the effectiveness of the proposed system, and it suggests that the proposed solution can be an effective and sustainable solution towards monitoring patient’s vital signs data in the IoT-based e-Health domain.
A Smartphone-Based Chemosensor to Evaluate Antioxidants in Agri-Food Matrices by In Situ AuNP Formation
Authors: Calabria Donato , Guardigli Massimo , Severi Paolo , Trozzi Ilaria , Pace Andrea , Cinti Stefano , Zangheri Martina , Mirasoli Mara
Published: August 2021

In recent years, there has been a continuously growing interest in antioxidants by both customers and food industry. The beneficial health effects of antioxidants led to their widespread use in fortified functional foods, as dietary supplements and as preservatives. A variety of analytical methods are available to evaluate the total antioxidant capacity (TAC) of food extracts and beverages. However, most of them are expensive, time-consuming, and require laboratory instrumentation. Therefore, simple, cheap, and fast portable sensors for point-of-need measurement of antioxidants in food samples are needed. Here, we describe a smartphone-based chemosensor for on-site assessment of TAC of aqueous matrices, relying on the antioxidant-induced formation of gold nanoparticles. The reaction takes place in ready-to-use analytical cartridges containing an hydrogel reaction medium preloaded with Au(III) and is monitored by using the smartphone’s CMOS camera. An analytical device including an LED-based lighting system was developed to ensure uniform and reproducible illumination of the analytical cartridge. The chemosensor permitted rapid TAC measurements of aqueous samples, including teas, herbal infusions, beverages, and extra virgin olive oil extracts, providing results that correlated with those of the reference methods for TAC assessment, e.g., oxygen radical absorbance capacity (ORAC).
Selective Subject Pooling Strategy to Improve Model Generalization for a Motor Imagery BCI
Authors: Won Kyungho , Kwon Moonyoung , Ahn Minkyu , Jun Sung Chan
Published: August 2021

Brain–computer interfaces (BCIs) facilitate communication for people who cannot move their own body. A BCI system requires a lengthy calibration phase to produce a reasonable classifier. To reduce the duration of the calibration phase, it is natural to attempt to create a subject-independent classifier with all subject datasets that are available; however, electroencephalogram (EEG) data have notable inter-subject variability. Thus, it is very challenging to achieve subject-independent BCI performance comparable to subject-specific BCI performance. In this study, we investigate the potential for achieving better subject-independent motor imagery BCI performance by conducting comparative performance tests with several selective subject pooling strategies (i.e., choosing subjects who yield reasonable performance selectively and using them for training) rather than using all subjects available. We observed that the selective subject pooling strategy worked reasonably well with public MI BCI datasets. Finally, based upon the findings, criteria to select subjects for subject-independent BCIs are proposed here.
Non-Invasive Detection and Staging of Colorectal Cancer Using a Portable Electronic Nose
Authors: Tyagi Heena , Daulton Emma , Bannaga Ayman S. , Arasaradnam Ramesh P. , Covington James A.
Published: August 2021

Electronic noses (e-nose) offer potential for the detection of cancer in its early stages. The ability to analyse samples in real time, at a low cost, applying easy–to-use and portable equipment, gives e-noses advantages over other technologies, such as Gas Chromatography-Mass Spectrometry (GC-MS). For diseases such as cancer with a high mortality, a technology that can provide fast results for use in routine clinical applications is important. Colorectal cancer (CRC) is among the highest occurring cancers and has high mortality rates, if diagnosed late. In our study, we investigated the use of portable electronic nose (PEN3), with further analysis using GC-TOF-MS, for the analysis of gases and volatile organic compounds (VOCs) to profile the urinary metabolome of colorectal cancer. We also compared the different cancer stages with non-cancers using the PEN3 and GC-TOF-MS. Results obtained from PEN3, and GC-TOF-MS demonstrated high accuracy for the separation of CRC and non-cancer. PEN3 separated CRC from non-cancerous group with 0.81 AUC (Area Under the Curve). We used data from GC-TOF-MS to obtain a VOC profile for CRC, which identified 23 potential biomarker VOCs for CRC. Thus, the PEN3 and GC-TOF-MS were found to successfully separate the cancer group from the non-cancer group.
Virtual Namesake Point Multi-Source Point Cloud Data Fusion Based on FPFH Feature Difference
Authors: Zheng Li , Li Zhukun
Published: August 2021

There are many sources of point cloud data, such as the point cloud model obtained after a bundle adjustment of aerial images, the point cloud acquired by scanning a vehicle-borne light detection and ranging (LiDAR), the point cloud acquired by terrestrial laser scanning, etc. Different sensors use different processing methods. They have their own advantages and disadvantages in terms of accuracy, range and point cloud magnitude. Point cloud fusion can combine the advantages of each point cloud to generate a point cloud with higher accuracy. Following the classic Iterative Closest Point (ICP), a virtual namesake point multi-source point cloud data fusion based on Fast Point Feature Histograms (FPFH) feature difference is proposed. For the multi-source point cloud with noise, different sampling resolution and local distortion, it can acquire better registration effect and improve the accuracy of low precision point cloud. To find the corresponding point pairs in the ICP algorithm, we use the FPFH feature difference, which can combine surrounding neighborhood information and have strong robustness to noise, to generate virtual points with the same name to obtain corresponding point pairs for registration. Specifically, through the establishment of voxels, according to the F2 distance of the FPFH of the target point cloud and the source point cloud, the convolutional neural network is used to output a virtual and more realistic and theoretical corresponding point to achieve multi-source Point cloud data registration. Compared with the ICP algorithm for finding corresponding points in existing points, this method is more reasonable and more accurate, and can accurately correct low-precision point cloud in detail. The experimental results show that the accuracy of our method and the best algorithm is equivalent under the clean point cloud and point cloud of different resolutions. In the case of noise and distortion in the point cloud, our method is better than other algorithms. For low-precision point cloud, it can better match the target point cloud in detail, with better stability and robustness.
Thermal Image Restoration Based on LWIR Sensor Statistics
Authors: Han Jaeduk , Lee Haegeun , Kang Moon Gi
Published: August 2021

An imaging system has natural statistics that reflect its intrinsic characteristics. For example, the gradient histogram of a visible light image generally obeys a heavy-tailed distribution, and its restoration considers natural statistics. Thermal imaging cameras detect infrared radiation, and their signal processors are specialized according to the optical and sensor systems. Thermal images, also known as long wavelength infrared (LWIR) images, suffer from distinct degradations of LWIR sensors and residual nonuniformity (RNU). However, despite the existence of various studies on the statistics of thermal images, thermal image processing has seldom attempted to incorporate natural statistics. In this study, natural statistics of thermal imaging sensors are derived, and an optimization method for restoring thermal images is proposed. To verify our hypothesis about the thermal images, high-frequency components of thermal images from various datasets are analyzed with various measures (correlation coefficient, histogram intersection, chi-squared test, Bhattacharyya distance, and Kullback–Leibler divergence), and generalized properties are derived. Furthermore, cost functions accommodating the validated natural statistics are designed and minimized by a pixel-wise optimization method. The proposed algorithm has a specialized structure for thermal images and outperforms the conventional methods. Several image quality assessments are employed for quantitatively demonstrating the performance of the proposed method. Experiments with synthesized images and real-world images are conducted, and the results are quantified by reference image assessments (peak signal-to-noise ratio and structural similarity index measure) and no-reference image assessments (Roughness (Ro) and Effective Roughness (ERo) indices).
Forward-Looking Ultrasound Wearable Scanner System for Estimation of Urinary Bladder Volume
Authors: Jo Hyeong Geun , Park Beom Hoon , Joung Do Yeong , Jo Jung Ki , Hoh Jeong-Kyu , Choi Won Young , Park Kwan Kyu
Published: August 2021

Accurate measurement of bladder volume is an important tool for evaluating bladder function. In this study, we propose a wearable bladder scanner system that can continuously measure bladder volume in daily life for urinary patients who need urodynamic studies. The system consisted of a 2-D array, which included integrated forward-looking piezoelectric transducers with thin substrates. This study aims to estimate the volume of the bladder using a small number of piezoelectric transducers. A least-squares method was implemented to optimize an ellipsoid in a quadratic surface equation for bladder volume estimation. Ex-vivo experiments of a pig bladder were conducted to validate the proposed system. This work presents the potential of the approach for wearable bladder monitoring, which has similar measurement accuracy compared to the commercial bladder imaging system. The wearable bladder scanner can be improved further as electronic voiding diaries by adding a few more features to the current function.
A High Power-Conversion-Efficiency Voltage Boost Converter with MPPT for Wireless Sensor Nodes
Authors: Zhu Xiwen , Fu Qiang , Yang Ruimo , Zhang Yufeng
Published: August 2021

A high power-conversion-efficiency voltage boost converter with MPPT for wireless sensor nodes (WSNs) is proposed in this paper. Since tiny wireless sensor nodes are all over complex environments, an efficient power management system (PMS) must be equipped to achieve long-term self-power supply and maintain regular operation. It is common to use Photovoltaic cells (PV) to harvest sunlight in the environment. However, most existing interface boost integrated circuits for the PV cell have low efficiency. This paper presents a voltage boost converter (VBC) with high power conversion efficiency (PCE) for WSNs. The integrated circuit (IC) designed in this paper includes a novel four-phase high-efficiency charge pump module, an ultra-low-power perturbation observation (P&O) MPPT control circuit module, a feedback control module, a nano-ampere current reference, etc. Manufactured in a standard 0.35 um complementary metal-oxide-semiconductor (CMOS) technology, the chip area is 3.15 mm × 2.43 mm. Test results demonstrate that when the output voltage of the PV cell is more than 0.5 V, VBC can improve the voltage to 3Vin, and the calculated voltage conversion efficiency can reach 99.4%. P&O MPPT algorithm makes output power improving 8.53%. Furthermore, when the output load current is 297uA, the output PCE achieves 85.1%.
Analysis of Propagation and Distribution Characteristics of Leakage Acoustic Waves in Water Supply Pipelines
Authors: Li Yunfei , Zhou Yang , Fu Ming , Zhou Fan , Chi Zhaozhao , Wang Weihao
Published: August 2021

Leakage detection methods based on the analysis of leakage acoustic signals provide an effective technical approach for detecting small leaks in water supply pipelines. From a technical perspective, the study of the propagation characteristics of acoustic waves generated by the leakage in the water supply pipeline is necessary for detecting the leak location on the basis of acoustic signals. In this study, a 3D transient leakage acoustic wave propagation equation was derived by combining the principles of fluid dynamics and Lighthill acoustic analogy theory. The propagation of the leakage-induced noise in water supply pipeline was modelled theoretically. We simulated the propagation of a leakage acoustic wave under different conditions for different target scenarios encountered in actual pipeline inspections. Specifically, we analysed the effect of different factors, such as the pipe size and acoustic source characteristics, on acoustic propagation. Finally, the simulated experiments were practically performed using a self-designed simulated water supply pipeline and self-developed spherical water supply pipeline detector to validate the simulation analysis. The results of this study provide a theoretical guidance and basis for the analysis of characteristics of leakage acoustic wave signals and the recognition of leakage conditions in water supply pipelines.
“Mexicans Built This Neighborhood!” Gentrification, Organizations, and the Role of Place-Based Identity in Latinx Chicago
Authors: Orta David
Published: August 2021

This exploratory study draws on qualitative interviews to investigate respondents’ perspectives about gentrification in their Chicago neighborhood. Prior research has demonstrated that place-based networks are crucial for the well-being of low-income and immigrant urban residents. A parallel though a previously disparate thread of research discusses the negative impacts of gentrification on long-term residents. I find that residents underscore concerns about their neighborhood’s decreasing affordability, as well as the impending loss of their neighborhood’s local Latinx immigrant identity, as central issues for their community. For residents, “place”, vis-á-vis the neighborhood identity, was central to their own construction of ethnic identity. Concurrently, I find that community organizers viewed place-based changes associated with gentrification as nonstrategic for their organization, whose operations have evolved “beyond the neighborhood”, and endeavor to meet the needs of low-income ethnic Latinx populations across the metropolitan region. I conclude that scholars of both ethnic identity and those studying urban inequalities may benefit from taking a place-centered approach in addressing the gentrification, community organizing, and residential displacement occurring within Latinx communities.
Federated Digital Platforms: Value Chain Integration for Sustainable Infrastructure Planning and Delivery
Authors: Nübel Konrad , Bühler Michael Max , Jelinek Thorsten
Published: August 2021

Twenty-first century infrastructure needs to respond to changing demographics, becoming climate neutral, resilient, and economically affordable, while remaining a driver for development and shared prosperity. However, the infrastructure sector remains one of the least innovative and digitalized, plagued by delays, cost overruns, and benefit shortfalls. The authors assessed trends and barriers in the planning and delivery of infrastructure based on secondary research, qualitative interviews with internationally leading experts, and expert workshops. The analysis concludes that the root-cause of the industry’s problems is the prevailing fragmentation of the infrastructure value chain and a lacking long-term vision for infrastructure. To help overcome these challenges, an integration of the value chain is needed. The authors propose that this could be achieved through a use-case-based, as well as vision and governance-driven creation of federated digital platforms applied to infrastructure projects and outline a concept. Digital platforms enable full-lifecycle participation and responsible governance guided by a shared infrastructure vision. This paper has contributed as policy recommendation to the Group of Twenty (G20) in 2021.
Mitigating Dust Pollution from Construction Activities: A Behavioural Control Perspective
Authors: Kaluarachchi Mekhala , Waidyasekara Anuradha , Rameezdeen Raufdeen , Chileshe Nicholas
Published: August 2021

Construction sites constitute major sources of pollutants creating negative impacts on the environment. Sustainable construction aims at mitigating these negative externalities while promoting economic and social outcomes. Dust pollution in construction sites is an invisible hazard, which is often ignored as little more than a nuisance. Although behavioral control is a popular way of preventing dust generation, past research has paid little attention to worker behavior regarding dust mitigation. This study aims to test a model that predicts intentions to alter the conduct of workers towards dust control in construction activities. This study adopted a questionnaire survey design with construction participants in Sri Lanka, using structural equation modelling to test several hypotheses based on the Norm Activation Model. The results proved that awareness of consequences and ascription of responsibility could have a positive impact on personal norms, which in turn could influence the behavior of site employees. The study also provided new insights on employees’ awareness of dust hazards, their sense of responsibility for its control, and the importance of their company. Policymakers and practitioners are recommended to pay more attention to how to harness worker’s support to mitigate dust pollution, and construction companies should initiate educational campaigns to raise awareness about environmental impacts, to influence personal norms of the workers in building sites. This research contributes to the body of knowledge by enhancing our understanding of factors influencing employees’ dust control behavior.
The Environmental Impact Assessment in Aquaculture Projects in Chile: A Retrospective and Prospective Review Considering Cultural Aspects
Authors: Rodríguez-Luna Dante , Vela Nuria , Alcalá Francisco Javier , Encina-Montoya Francisco
Published: August 2021

In recent years, social and environmental conflicts concerning the aquaculture sector have increased. These conflicts arise from the different perception that individuals, collectives, private companies and the State have about the potential impacts of aquaculture on the environment and quality of life. The Environmental Impact Assessment (EIA) of aquaculture projects in Chile is the main administrative tool for decision-making, allowing identify, predict, and propose preventive measures to mitigate negative consequences of this growing sector. This article analyzes the performance of the EIA in Chile concerning aquaculture projects between 1994 and 2019. Of the 5323 projects entering the Chilean EIA during this period, the EIA system-performance analysis selected the 71 most representative. For a reliable comparative analysis, the selected projects were first classified in accordance with the active regulation within the period. Subsequently, 14 performance indicators were selected and similarities—by means of a principal coordinate analysis—were explored. Significant differences between the third (SD40) and the first two (SD30 and SD95) regulations were observed. Based on these results and considering demands of local communities and social leaders (who request continuous articulations among technical areas, administrative tools, and policies to increase the sustainability standards of aquaculture), four opportunities for improving the EIA in aquaculture projects are proposed: incorporation of synergistic and cumulative effects, adaptation to climate change, development of a general methodology, and incorporation of early citizen participation (in projects having environmental charge) increasing the performance and confidence of the EIA. The introduced methodology enables comparisons of the EIA process in different regulatory periods using indicators, serving as guidance to evaluate the performance of the EIA in aquaculture. This methodology can also be used by other aquaculture producing countries around the world.
Toward Blockchain Technology in the Energy Environment
Authors: Baashar Yahia , Alkawsi Gamal , Alkahtani Ammar Ahmed , Hashim Wahidah , Razali Rina Azlin , Tiong Sieh Kiong
Published: August 2021

Energy management and exchange have increasingly shifted from concentrated to hierarchical modes. Numerous issues have arisen in the decentralized energy sector, including the storage of customer data and the need to ensure data integrity, fairness, and accountability in the transaction phase. The problem is that in the field of the innovative technology of blockchain and its applications, with the energy sector still in the developmental stages, there is still a need for more research to understand the full capacity of the technology in the field. The main aim of this work was to investigate the state of the current research of blockchain technologies as well as their application within the field of energy. This work also set out to identify certain research gaps and provide a set of recommendations for future directions. Among these research gaps is the application of blockchain in decentralized storage, the integration of blockchain with artificial intelligence, and security and privacy concerns, which have not received much attention despite their importance. An analysis of fifty-seven carefully reviewed studies revealed that the emerging blockchain which provides privacy-protection technologies in cryptography and other areas that can be integrated to address users’ privacy concerns is another aspect that needs further investigation. Grid operations, economies, and customers will all learn from blockchain technology as it provides disintermediation, confidentiality, and tamper-proof transfers. Moreover, it provides innovative ways for customers and small solar generators to participate more actively in the electricity sector and to benefit from their properties. Blockchains are a rapidly evolving field of research and growth. A study of this emerging technology is necessary to increase comprehension, to educate the body of expertise on blockchains, and to realize its potential. This study recommends that future work investigates the potential application of blockchain in the energy sector as well as the challenges that face its implementation from the perspective of policy makers. This future approach will enable researchers to direct their focus to the case studies approach, which will facilitate and ease the application of blockchain technology.
The Urban Water Cycle as a Planning Tool to Monitor SARS-CoV-2: A Review of the Literature
Authors: Peña-Guzmán Carlos , Domínguez-Sánchez María Andrea , Rodríguez Manuel , Pulicharla Rama , Mora-Cabrera Karen
Published: August 2021

COVID-19 is a terrible virus that has impacted human health and the economy on a global scale. The detection and control of the pandemic have become necessities that require appropriate monitoring strategies. One of these strategies involves measuring and quantifying the virus in water at different stages of the Urban Water Cycle (UWC). This article presents a comprehensive literature review of the analyses and quantifications of SARS-CoV-2 in multiple UWC components from 2020 to June 2021. More than 140 studies worldwide with a focus on industrialized nations were identified, mainly in the USA, Australia, and Asia and the European Union. Wastewater treatment plants were the focus of most of these studies, followed by city sewerage systems and hospital effluents. The fewest studies examined the presence of this virus in bodies of water. Most of the studies were conducted for epidemiological purposes. However, a few focused on viral load and its removal using various treatment strategies or modelling and developing strategies to control the disease. Others compared methodologies for determining if SARS-CoV-2 was present or included risk assessments. This is the first study to emphasize the importance of the various individual components of the UWC and their potential impacts on viral transmission from the source to the public.
Carbon Productivity and Mitigation: Evidence from Industrial Development and Urbanization in the Central and Western Regions of China
Authors: Wu Yongjiao , Zheng Huazhu , Li Yu , Delang Claudio O. , Qian Jiao
Published: August 2021

This paper investigates carbon productivity (CP) from the perspectives of industrial development and urbanization to mitigate carbon emissions. We propose a hybrid model that includes a spatial lag model (SLM) and a fixed regional panel model using data from the 17 provinces in the central and western regions of China from 2000 to 2018. The results show that the slowly increasing CP has significant spatial spillover effects, with High–High (H–H) and Low–Low (L–L) spatial distributions in the central and western regions of China. In addition, industrial development and urbanization in the study area play different roles in CP, while economic urbanization and industrial fixed investment negatively affect CP, and population urbanization affects CP along a U-shape curve. Importantly, the results show that the patterns of industrial development and urbanization that influence CP are homogenous and mutually imitated in the 17 studied provinces. Furthermore, disparities in CP between regions are due to industrial workforce allocation (TL), but TL has been inefficient; industrial structure upgrades are slowly improving conditions. Therefore, the findings suggest that, in the short term, policymakers in China should implement industrial development policies that reduce carbon emissions in the western and central regions by focusing on improving industrial workforce allocation.
Early-Career Challenges of Youth Development Extension Educators and Effective Strategies
Authors: Jayaratne Koralalage S. U. , Collins Daniel P. , McCollum Shannon B.
Published: August 2021

The purpose of this research study was to determine the challenges faced by early-career youth development extension educators and strategies helpful in managing those challenges. This study used the modified Delphi method of three rounds with a specifically selected expert panel of 24 members to build consensus on the challenges that early-career youth development extension educators faced and managing strategies of those challenges. The expert panel of this Delphi study was selected from two south-eastern states in the U.S. based on their proven success and effectiveness in youth development extension programming in their respective counties. The three-round Delphi study led to building the consensus on 16 challenges faced by early-career youth development extension educators and 14 strategies helpful in managing those challenges. The findings of this study have implications for planning onboarding training programs for early-career youth development extension educators. Future research is needed to understand how identified strategies contribute to managing early-career challenges faced by youth development extension educators.