bluuebunny/crossref_metadata_2025 huggingface dataset:
Optical Fibre Sensor for Capillary Refill Time and Contact Pressure Measurements under the Foot
Authors: Ballaji Hattan K. , Correia Ricardo , Liu Chong , Korposh Serhiy , Hayes-Gill Barrie R. , Musgrove Alison , Morgan Stephen P.
Published: September 2021

Capillary refill time (CRT) refers to the time taken for body tissue to regain its colour after an applied blanching pressure is released. Usually, pressure is manually applied and not measured. Upon release of pressure, simple mental counting is typically used to estimate how long it takes for the skin to regain its colour. However, this method is subjective and can provide inaccurate readings due to human error. CRT is often used to assess shock and hydration but also has the potential to assess peripheral arterial disease which can result in tissue breakdown, foot ulcers and ultimately amputation, especially in people with diabetes. The aim of this study was to design an optical fibre sensor to simultaneously detect blood volume changes and the contact pressure applied to the foot. The CRT probe combines two sensors: a plastic optical fibre (POF) based on photoplethysmography (PPG) to measure blood volume changes and a fibre Bragg grating to measure skin contact pressure. The results from 10 healthy volunteers demonstrate that the blanching pressure on the subject’s first metatarsal head of the foot was 100.8 ± 4.8 kPa (mean and standard deviation), the average CRT was 1.37 ± 0.46 s and the time to achieve a stable blood volume was 4.77 ± 1.57 s. For individual volunteers, the fastest CRT measured was 0.82 ± 0.11 and the slowest 1.94 ± 0.49 s. The combined sensor and curve fitting process has the potential to provide increased reliability and accuracy for CRT measurement of the foot in diabetic foot ulcer clinics and in the community.
Simulation and Optimization Studies of the LHCb Beetle Readout ASIC and Machine Learning Approach for Pulse Shape Reconstruction
Authors: Kopciewicz Pawel , Akiba Kazuyoshi Carvalho , Szumlak Tomasz , Sitko Sebastian , Barter William , Buytaert Jan , Eklund Lars , Hennessy Karol , Koppenburg Patrick , Latham Thomas , Majewski Maciej , Oblakowska-Mucha Agnieszka , Parkes Chris , Qian Wenbin , Velthuis Jaap , Williams Mark
Published: September 2021

The optimization of the Beetle readout ASIC and the performance of the software for the signal processing based on machine learning methods are presented. The Beetle readout chip was developed for the LHCb (Large Hadron Collider beauty) tracking detectors and was used in the VELO (Vertex Locator) during Run 1 and 2 of LHC data taking. The VELO, surrounding the LHC beam crossing region, was a leading part of the LHCb tracking system. The Beetle chip was used to read out the signal from silicon microstrips, integrating and amplifying it. The studies presented in this paper cover the optimization of its electronic configuration to achieve the lower power consumption footprint and the lower operational temperature of the sensors, while maintaining a good condition of the analogue response of the whole chip. The studies have shown that optimizing the operational temperature is possible and can be beneficial when the detector is highly irradiated. Even a single degree drop in silicon temperature can result in a significant reduction in the leakage current. Similar studies are being performed for the future silicon tracker, the Upstream Tracker (UT), which will start operating at LHC in 2021. It is expected that the inner part of the UT detector will suffer radiation damage similar to the most irradiated VELO sensors in Run 2. In the course of analysis we also developed a general approach for the pulse shape reconstruction using an ANN approach. This technique can be reused in case of any type of front-end readout chip.
Area-Efficient Post-Processing Circuits for Physically Unclonable Function with 2-Mpixel CMOS Image Sensor
Authors: Okura Shunsuke , Aoki Masanori , Oyama Tatsuya , Shirahata Masayoshi , Fujino Takeshi , Ishikawa Kenichiro , Takayanagi Isao
Published: September 2021

In order to realize image information security starting from the data source, challenge–response (CR) device authentication, based on a Physically Unclonable Function (PUF) with a 2 Mpixel CMOS image sensor (CIS), is studied, in which variation of the transistor in the pixel array is utilized. As each CR pair can be used only once to make the CIS PUF resistant to the modeling attack, CR authentication with CIS can be carried out 4050 times, with basic post-processing to generate the PUF ID. If a larger number of authentications is required, advanced post-processing using Lehmer encoding can be utilized to carry out authentication 14,858 times. According to the PUF performance evaluation, the authentication error rate is less than 0.001 ppm. Furthermore, the area overhead of the CIS chip for the basic and advanced post-processing is only 1% and 2%, respectively, based on a Verilog HDL model circuit design.
On the Complementarity of Sparse L0 and CEL0 Regularized Loss Landscapes for DOA Estimation
Authors: Delmer Alice , Ferréol Anne , Larzabal Pascal
Published: September 2021

L0 sparse methods are not widespread in Direction-Of-Arrival (DOA) estimation yet, despite their potential superiority over classical methods in difficult scenarios. This comes from the difficulties encountered for global optimization on hill-climbing error surfaces. In this paper, we explore the loss landscapes of L0 and Continuous Exact L0 (CEL0) regularized problems in order to design a new optimization scheme. As expected, we observe that the recently introduced CEL0 penalty leads to an error surface with less local minima than the L0 one. This property explains the good behavior of the CEL0-regularized sparse DOA estimation problem for well-separated sources. Unfortunately, CEL0-regularized landscape enlarges L0-basins in the middle of close sources, and CEL0 methods are thus unable to resolve two close sources. Consequently, we propose to alternate between both error surfaces to increase the probability of reaching the global solution. Experiments show that the proposed approach offers better performance than existing ones, and particularly an enhanced resolution limit.
Attitudes towards Participation in a Passive Data Collection Experiment
Authors: Ságvári Bence , Gulyás Attila , Koltai Júlia
Published: September 2021

In this paper, we present the results of an exploratory study conducted in Hungary using a factorial design-based online survey to explore the willingness to participate in a future research project based on active and passive data collection via smartphones. Recently, the improvement of smart devices has enabled the collection of behavioural data on a previously unimaginable scale. However, the willingness to share this data is a key issue for the social sciences and often proves to be the biggest obstacle to conducting research. In this paper we use vignettes to test different (hypothetical) study settings that involve sensor data collection but differ in the organizer of the research, the purpose of the study and the type of collected data, the duration of data sharing, the number of incentives and the ability to suspend and review the collection of data. Besides the demographic profile of respondents, we also include behavioural and attitudinal variables to the models. Our results show that the content and context of the data collection significantly changes people’s willingness to participate, however their basic demographic characteristics (apart from age) and general level of trust seem to have no significant effect. This study is a first step in a larger project that involves the development of a complex smartphone-based research tool for hybrid (active and passive) data collection. The results presented in this paper help improve our experimental design to encourage participation by minimizing data sharing concerns and maximizing user participation and motivation.
UAV Block Geometry Design and Camera Calibration: A Simulation Study
Authors: Roncella Riccardo , Forlani Gianfranco
Published: September 2021

Acknowledged guidelines and standards such as those formerly governing project planning in analogue aerial photogrammetry are still missing in UAV photogrammetry. The reasons are many, from a great variety of projects goals to the number of parameters involved: camera features, flight plan design, block control and georeferencing options, Structure from Motion settings, etc. Above all, perhaps, stands camera calibration with the alternative between pre- and on-the-job approaches. In this paper we present a Monte Carlo simulation study where the accuracy estimation of camera parameters and tie points’ ground coordinates is evaluated as a function of various project parameters. A set of UAV (Unmanned Aerial Vehicle) synthetic photogrammetric blocks, built by varying terrain shape, surveyed area shape, block control (ground and aerial), strip type (longitudinal, cross and oblique), image observation and control data precision has been synthetically generated, overall considering 144 combinations in on-the-job self-calibration. Bias in ground coordinates (dome effect) due to inaccurate pre-calibration has also been investigated. Under the test scenario, the accuracy gap between different block configurations can be close to an order of magnitude. Oblique imaging is confirmed as key requisite in flat terrain, while ground control density is not. Aerial control by accurate camera station positions is overall more accurate and efficient than GCP in flat terrain.
Use of the Ferroelectric Ceramic Bismuth Titanate as an Ultrasonic Transducer for High Temperatures and Nuclear Radiation
Authors: Reinhardt Brian T. , Tittmann Bernhard R.
Published: September 2021

Ultrasonic transducers are often used in the nuclear industry as sensors to monitor the health and process status of systems or the components. Some of the after-effects of the Fukushima Daiichi earthquake could have been eased if sensors had been in place inside the four reactors and sensed the overheating causing meltdown and steam explosions. The key element of ultrasonic sensors is the piezoelectric wafer, which is usually derived from lead-zirconate-titanate (Pb(Zr, Ti)O3, PZT). This material loses its piezoelectrical properties at a temperature of about 200 °C. It also undergoes nuclear transmutation. Bismuth titanate (Bi4Ti3O12, BiTi) has been considered as a potential candidate for replacing PZT at the middle of this temperature range, with many possible applications, since it has a Curie–Weiss temperature of about 650 °C. The aim of this article is to describe experimental details for operation in gamma and nuclear radiation concomitant with elevated temperatures and details of the performance of a BiTi sensor during and after irradiation testing. In these experiments, bismuth titanate has been demonstrated to operate up to a fast neutron fluence of 5 × 1020 n/cm2 and gamma radiation of 7.23 × 1021 (gamma/cm2). The results offer a perspective on the state-of the-art for a possible sensor for harsh environments of high temperature, Gamma radiation, and nuclear fluence.
Distributed Fiber Optic Shape Sensing of Concrete Structures
Authors: Monsberger Christoph M. , Lienhart Werner
Published: September 2021

Civil structural health monitoring (CSHM) has become significantly more important within the last decades due to rapidly growing construction volume worldwide as well as aging infrastructure and longer service lifetimes of the structures. The utilization of distributed fiber optic sensing (DFOS) allows the assessment of strain and temperature distributions continuously along the installed sensing fiber and is widely used for testing of concrete structures to detect and quantify local deficiencies like cracks. Relations to the curvature and bending behavior are however mostly excluded. This paper presents a comprehensive study of different approaches for distributed fiber optic shape sensing of concrete structures. Different DFOS sensors and installation techniques were tested within load tests of concrete beams as well as real-scale tunnel lining segments, where the installations were interrogated using fully-distributed sensing units as well as by fiber Bragg grating interrogators. The results point out significant deviations between the capabilities of the different sensing systems, but demonstrate that DFOS can enable highly reliable shape sensing of concrete structures, if the system is appropriately designed depending on the CSHM application.
IEEE 802.11ax OFDMA Resource Allocation with Frequency-Selective Fading
Authors: Tutelian Sergei , Bankov Dmitry , Shmelkin Dmitri , Khorov Evgeny
Published: September 2021

This paper studies the usage of orthogonal frequency division multiple access (OFDMA) for uplink transmissions in IEEE 802.11ax networks. OFDMA enables simultaneous multi-user transmissions in Wi-Fi, but its usage requires efficient resource allocation algorithms. These algorithms should be able to adapt to the changing channel conditions, including the frequency-selective fading. This paper presents an OFDMA resource allocation algorithm for channels with frequency-selective fading and proposes an approach to adapt the user transmission power and modulation and coding schemes to the varying channel conditions, which is efficient even in the case when the access point has outdated channel state information. The proposed scheduling algorithm and power allocation approach can double the goodput and halve the data transmission time in Wi-Fi networks even in dense deployments of access points.
Automatic Inside Point Localization with Deep Reinforcement Learning for Interactive Object Segmentation
Authors: Li Guoqing , Zhang Guoping , Qin Chanchan
Published: September 2021

In the task of interactive image segmentation, the Inside-Outside Guidance (IOG) algorithm has demonstrated superior segmentation performance leveraging Inside-Outside Guidance information. Nevertheless, we observe that the inconsistent input between training and testing when selecting the inside point will result in significant performance degradation. In this paper, a deep reinforcement learning framework, named Inside Point Localization Network (IPL-Net), is proposed to infer the suitable position for the inside point to help the IOG algorithm. Concretely, when a user first clicks two outside points at the symmetrical corner locations of the target object, our proposed system automatically generates the sequence of movement to localize the inside point. We then perform the IOG interactive segmentation method for precisely segmenting the target object of interest. The inside point localization problem is difficult to define as a supervised learning framework because it is expensive to collect image and their corresponding inside points. Therefore, we formulate this problem as Markov Decision Process (MDP) and then optimize it with Dueling Double Deep Q-Network (D3QN). We train our network on the PASCAL dataset and demonstrate that the network achieves excellent performance.
BER Performance Analysis of Non-Coherent Q-Ary Pulse Position Modulation Receivers on AWGN Channel
Authors: Shi Xianhua , Sun Yimao , Tian Jie , Chen Maolin , Liu Youjiang , Xie Nan , Zhang Jian
Published: September 2021

This paper introduces the structure of a Q-ary pulse position modulation (PPM) signal and presents a noncoherent suboptimal receiver and a noncoherent optimal receiver. Aiming at addressing the lack of an accurate theoretical formula of the bit error rate (BER) of a Q-ary PPM receiver in the additive white Gaussian noise (AWGN) channel in the existing literature, the theoretical formulas of the BER of a noncoherent suboptimal receiver and noncoherent optimal receiver are derived, respectively. The simulation results verify the correctness of the theoretical formulas. The theoretical formulas can be applied to a Q-ary PPM system including binary PPM. In addition, the analysis shows that the larger the Q, the better the error performance of the receiver and that the error performance of the optimal receiver is about 2 dB better than that of the suboptimal receiver. The relationship between the threshold coefficient of the suboptimal receiver and the error performance is also given.
Mitigating Wireless Channel Impairments in Seismic Data Transmission Using Deep Neural Networks
Authors: Iqbal Naveed , Lawal Abdulmajid , Zerguine Azzedine
Published: September 2021

The traditional cable-based geophone network is an inefficient way of seismic data transmission owing to the related cost and weight. The future of oil and gas exploration technology demands large-scale seismic acquisition, versatility, flexibility, scalability, and automation. On the one hand, a typical seismic survey can pile up a massive amount of raw seismic data per day. On the other hand, the need for wireless seismic data transmission remains immense. Moving from pre-wired to wireless geophones faces major challenges given the enormous amount of data that needs to be transmitted from geophones to the on-site data collection center. The most important factor that has been ignored in the previous studies for the realization of wireless seismic data transmission is wireless channel effects. While transmitting the seismic data wirelessly, impairments like interference, multi-path fading, and channel noise need to be considered. Therefore, in this work, a novel amalgamation of blind channel identification and deep neural networks is proposed. As a geophone already is responsible for transmitting a tremendous amount of data under tight timing constraints, the proposed setup eschews sending any additional training signals for the purpose of mitigating the channel effects. Note that the deep neural network is trained only on synthetic seismic data without the need to use real data in the training process. Experiments show that the proposed method gives promising results when applied to the real/field data set.
Comparing Class-Aware and Pairwise Loss Functions for Deep Metric Learning in Wildlife Re-Identification
Authors: Dlamini Nkosikhona , van Zyl Terence L.
Published: September 2021

Similarity learning using deep convolutional neural networks has been applied extensively in solving computer vision problems. This attraction is supported by its success in one-shot and zero-shot classification applications. The advances in similarity learning are essential for smaller datasets or datasets in which few class labels exist per class such as wildlife re-identification. Improving the performance of similarity learning models comes with developing new sampling techniques and designing loss functions better suited to training similarity in neural networks. However, the impact of these advances is tested on larger datasets, with limited attention given to smaller imbalanced datasets such as those found in unique wildlife re-identification. To this end, we test the advances in loss functions for similarity learning on several animal re-identification tasks. We add two new public datasets, Nyala and Lions, to the challenge of animal re-identification. Our results are state of the art on all public datasets tested except Pandas. The achieved Top-1 Recall is 94.8% on the Zebra dataset, 72.3% on the Nyala dataset, 79.7% on the Chimps dataset and, on the Tiger dataset, it is 88.9%. For the Lion dataset, we set a new benchmark at 94.8%. We find that the best performing loss function across all datasets is generally the triplet loss; however, there is only a marginal improvement compared to the performance achieved by Proxy-NCA models. We demonstrate that no single neural network architecture combined with a loss function is best suited for all datasets, although VGG-11 may be the most robust first choice. Our results highlight the need for broader experimentation and exploration of loss functions and neural network architecture for the more challenging task, over classical benchmarks, of wildlife re-identification.
Precipitation Changes in the Three Gorges Reservoir Area and the Relationship with Water Level Change
Authors: Li Qin , Liu Xiuguo , Zhong Yulong , Wang Mengmeng , Shi Manxing
Published: September 2021

As the largest hydroelectric project worldwide, previous studies indicate that the Three Gorges Dam (TGD) affects the local climate because of the changes of hydrological cycle caused by the impounding and draining of the TGD. However, previous studies do not analyze the long-term precipitation changes before and after the impoundment, and the variation characteristics of local precipitation remain elusive. In this study, we use precipitation anomaly data derived from the CN05.1 precipitation dataset between 1988 and 2017 to trace the changes of precipitation before and after the construction of the TGD (i.e., 1988–2002 and 2003–2017), in the Three Gorges Reservoir Area (TGRA). Results showed that the annual and dry season precipitation anomaly in the TGRA presented an increasing trend, and the precipitation anomaly showed a slight decrease during the flood season. After the impoundment of TGD, the precipitation concentration degree in the TGRA decreased, indicating that the precipitation became increasingly uniform, and the precipitation concentration period insignificantly increased. A resonance phenomenon between the monthly average water level and precipitation anomaly occurred in the TGRA after 2011 and showed a positive correlation. Our findings revealed the change of local precipitation characteristics before and after the impoundment of TGD and showed strong evidence that this change had a close relationship with the water level.
A Review of Heartbeat Detection Systems for Automotive Applications
Authors: Arakawa Toshiya
Published: September 2021

Many accidents are caused by sudden changes in the physical conditions of professional drivers. Therefore, it is quite important that the driver monitoring system must not restrict or interfere with the driver’s action. Applications that can measure a driver’s heartbeat without restricting the driver’s action are currently under development. In this review, examples of heartbeat-monitoring systems are discussed. In particular, methods for measuring the heartbeat through sensing devices of a wearable-type, such as wristwatch-type, ring-type, and shirt-type devices, as well as through devices of a nonwearable type, such as steering-type, seat-type, and other types of devices, are discussed. The emergence of wearable devices such as the Apple Watch is considered a turning point in the application of driver-monitoring systems. The problems associated with current smartwatch- and smartphone-based systems are discussed, as are the barriers to their practical use in vehicles. We conclude that, for the time being, detection methods using in-vehicle devices and in-vehicle cameras are expected to remain dominant, while devices that can detect health conditions and abnormalities simply by driving as usual are expected to emerge as future applications.
Gap Reconstruction in Optical Motion Capture Sequences Using Neural Networks
Authors: Skurowski Przemysław , Pawlyta Magdalena
Published: September 2021

Optical motion capture is a mature contemporary technique for the acquisition of motion data; alas, it is non-error-free. Due to technical limitations and occlusions of markers, gaps might occur in such recordings. The article reviews various neural network architectures applied to the gap-filling problem in motion capture sequences within the FBM framework providing a representation of body kinematic structure. The results are compared with interpolation and matrix completion methods. We found out that, for longer sequences, simple linear feedforward neural networks can outperform the other, sophisticated architectures, but these outcomes might be affected by the small amount of data availabe for training. We were also able to identify that the acceleration and monotonicity of input sequence are the parameters that have a notable impact on the obtained results.
The Validity and Reliability of a Tire Pressure-Based Power Meter for Indoor Cycling
Authors: Fiolo Nicholas J. , Lu Hai-Ying , Chen Chia-Hsiang , Fuchs Philip X. , Chen Wei-Han , Shiang Tzyy-Yuang
Published: September 2021

The purpose of this study was to evaluate the validity and reliability of a tire pressure sensor (TPS) cycling power meter against a gold standard (SRM) during indoor cycling. Twelve recreationally active participants completed eight trials of 90 s of cycling at different pedaling and gearing combinations on an indoor hybrid roller. Power output (PO) was simultaneously calculated via TPS and SRM. The analysis compared the paired 1 s PO and 1 min average PO per trial between devices. Agreement was assessed by correlation, linear regression, inferential statistics, effect size, and Bland–Altman LoA. Reliability was assessed by ICC and CV comparison. TPS showed near-perfect correlation with SRM in 1 s (rs = 0.97, p < 0.001) and 1-min data (rs = 0.99, p < 0.001). Differences in paired 1 s data were statistically significant (p = 0.04), but of a trivial magnitude (d = 0.05). There was no significant main effect for device (F(1,9) = 0.05, p = 0.83, ηp2 = 0.97) in 1 min data and no statistical differences between devices by trial in post hoc analysis (p < 0.01–0.98; d < 0.01–0.93). Bias and LoA were −0.21 ± 16.77 W for the 1 min data. Mean TPS bias ranged from 3.37% to 7.81% of the measured SRM mean PO per trial. Linear regression SEE was 7.55 W for 1 min TPS prediction of SRM. ICC3,1 across trials was 0.96. No statistical difference (p = 0.09–0.11) in TPS CV (3.6–5.0%) and SRM CV (4.3–4.7%). The TPS is a valid and reliable power meter for estimating average indoor PO for time periods equal to or greater than 1 min and may have acceptable sensitivity to detect changes under less stringent criteria (±5%).
Non-Contact Oxygen Saturation Measurement Using YCgCr Color Space with an RGB Camera
Authors: Kim Na Hye , Yu Su-Gyeong , Kim So-Eui , Lee Eui Chul
Published: September 2021

Oxygen saturation (SPO2) is an important indicator of health, and is usually measured by placing a pulse oximeter in contact with a finger or earlobe. However, this method has a problem in that the skin and the sensor must be in contact, and an additional light source is required. To solve these problems, we propose a non-contact oxygen saturation measurement technique that uses a single RGB camera in an ambient light environment. Utilizing the fact that oxygenated and deoxygenated hemoglobin have opposite absorption coefficients at green and red wavelengths, the color space of photoplethysmographic (PPG) signals recorded from the faces of study participants were converted to the YCgCr color space. Substituting the peaks and valleys extracted from the converted Cg and Cr PPG signals into the Beer–Lambert law yields the SPO2 via a linear equation. When the non-contact SPO2 measurement value was evaluated based on the reference SPO2 measured with a pulse oximeter, the mean absolute error was 0.537, the root mean square error was 0.692, the Pearson correlation coefficient was 0.86, the cosine similarity was 0.99, and the intraclass correlation coefficient was 0.922. These results confirm the feasibility of non-contact SPO2 measurements.
Developing a Fast Ultra-High-Performance Liquid Chromatography–Tandem Mass Spectrometry Method for High-Throughput Surface Contamination Monitoring of 26 Antineoplastic Drugs
Authors: Dugheri Stefano , Mucci Nicola , Squillaci Donato , Marrubini Giorgio , Bartolucci Gianluca , Melzi Camillo , Bucaletti Elisabetta , Cappelli Giovanni , Trevisani Lucia , Arcangeli Giulio
Published: September 2021

Growing attention on carcinogenicity and mutagenicity of antineoplastic drugs (ADs) from the International Agencies has led to the present strict safe handling and administration regulations. Accordingly, one of the most common ways to assess occupational exposure to these substances is to identify and quantify possible surface contamination inside hospital preparation and administration units. Thus, it is essential to develop a fast and high-throughput monitoring method capable of identifying a significant number of ADs. The present study reports developing a UHPLC–MS/MS analysis to screen 26 ADs surface contamination through wipe test sampling. A Cortecs UPLC T3 50 × 2.1 mm (1.6 µm) column was selected to perform the analysis, using the evaluations of previous studies and the Product Quality Research Institute (PQRI) database. The design of experiments (DoE) methodological approach was used to optimize the chromatographic conditions concerning the best separation between all ADs. The limits of quantification for the analytes were between the pg/mL and ng/mL orders, and the turnaround time was limited to about 15 min. The obtained accuracy was mostly between 90% and 110% for all the analytes, while the precision was under 10% and a low matrix effect was observed for said analytes. Only vindesine and docetaxel presented lower performances.
Muscle Fiber Type Transitions with Exercise Training: Shifting Perspectives
Authors: Plotkin Daniel L. , Roberts Michael D. , Haun Cody T. , Schoenfeld Brad J.
Published: September 2021

Human muscle fibers are generally classified by myosin heavy chain (MHC) isoforms characterized by slow to fast contractile speeds. Type I, or slow-twitch fibers, are seen in high abundance in elite endurance athletes, such as long-distance runners and cyclists. Alternatively, fast-twitch IIa and IIx fibers are abundant in elite power athletes, such as weightlifters and sprinters. While cross-sectional comparisons have shown marked differences between athletes, longitudinal data have not clearly converged on patterns in fiber type shifts over time, particularly between slow and fast fibers. However, not all fiber type identification techniques are created equal and, thus, may limit interpretation. Hybrid fibers, which express more than one MHC type (I/IIa, IIa/IIx, I/IIa/IIx), may make up a significant proportion of fibers. The measurement of the distribution of fibers would necessitate the ability to identify hybrid fibers, which is best done through single fiber analysis. Current evidence using the most appropriate techniques suggests a clear ability of fibers to shift between hybrid and pure fibers as well as between slow and fast fiber types. The context and extent to which this occurs, along with the limitations of current evidence, are discussed herein.
Influence between COVID-19 Impacts and Project Stakeholders in Chilean Construction Projects
Authors: Araya Felipe , Sierra Leonardo
Published: September 2021

The construction sector has been heavily impacted by COVID-19 due to the restricted conditions required by construction projects to perform physical activities. Given this context, it is of interest for the industry to identify the impacts that COVID-19 has had on the development of construction projects. However, little is known regarding how the impacts of COVID-19 have affected multiple stakeholders in construction projects and whether there is some interaction among such impacts. This study aims to explore the impacts of COVID-19 and their influence among different construction stakeholders (i.e., engineers and managers, workers, suppliers). This study was enabled by 40 semi-structured interviews that were performed with stakeholders in construction projects in Chile. Content analysis from the interviews led to the identification of categories of impacts and stakeholders, to the development of a cognitive map of the impacts, and to the application of correspondence analysis. Fifteen categories of impacts were identified, and six construction stakeholders were identified as having been impacted by COVID-19. Identifying the causes and effects of the impacts felt by multiple stakeholders revealed that these impacts interacted among each other. Understanding the impacts of COVID-19 on construction stakeholders may facilitate the development of effective mitigation strategies to reduce COVID-19 impacts on the construction sector.
How the COVID-19 Pandemic Will Change Workplaces, Healthcare Markets and Healthy Living: An Overview and Assessment
Authors: Kolakowski Heather , Shepley Mardelle McCuskey , Valenzuela-Mendoza Ellie , Ziebarth Nicolas R.
Published: September 2021

The COVID-19 pandemic has disrupted most aspects of our lives: how we work, how we socialize, how we provide health care, and how we take care of our most vulnerable members of society. In this perspectives article, we provide a multidisciplinary overview of existing research covering these fields. Moreover, we enrich this research overview with news reporting and insights from a panel of expert practitioners affiliated with the Cornell Institute for Healthy Futures. We sketch existing evidence, focusing on how the pandemic has transformed our lives since March 2020. Then, for each of the fields covered by this article, we propose optimistic perspectives on what healthy living could look like in the future, given the current challenges and opportunities. In particular, we discuss the needed transformations of our workplaces, the health care market, senior living, healthy eating, and personal wellness.
Methodology and Application of Statistical Techniques to Evaluate the Reliability of Electrical Systems Based on the Use of High Variability Generation Sources
Authors: Berna-Escriche César , Pérez-Navarro Ángel , Escrivá Alberto , Hurtado Elías , Muñoz-Cobo José Luis , Moros María Cristina
Published: September 2021

This study presents a new methodology, based on Monte-Carlo techniques to evaluate the reliability of a carbon-free electricity generation system based on renewable sources; it uses as inputs the variation of the electricity demand and the fluctuations in the renewable supply and provides the renewable system to be installed to guarantee a specific supply reliability level. Additionally, looking for a reduction of this renewable system, the methodology determines the improvements by the incorporation of nuclear power and electricity storage. The methodology is of general application, its implementation being possible under different contexts, such as different time horizons and different future energy scenarios, both for developing, emerging, and developed countries. The only requirement is to have a sufficient database from which to make predictions for future scenarios of electrical generation–demand balances. As an example of practical implementation, the electrical system reliability for the particular case of Spain in 2040 has been forecasted. When considering the fluctuations in solar and wind power contributions, very high values of the installed power from these renewable sources are needed to reach a high reliability of the system. These values decrease substantially if contributions from nuclear and storage technologies are included.
Effects of the COVID-19 Pandemic on Food Security and Agriculture in Iran: A Survey
Authors: Rad Abdullah Kaviani , Shamshiri Redmond R. , Azarm Hassan , Balasundram Siva K. , Sultan Muhammad
Published: September 2021

The consequences of COVID-19 on the economy and agriculture have raised many concerns about global food security, especially in developing countries. Given that food security is a critical component that is affected by global crises, beside the limited studies carried out on the macro-impacts of COVID-19 on food security in Iran, this paper is an attempt to address the dynamic impacts of COVID-19 on food security along with economic and environmental challenges in Iran. For this purpose, a survey was conducted with the hypothesis that COVID-19 has not affected food security in Iran. To address this fundamental hypothesis, we applied the systematic review method to obtain the evidence. Various evidences, including indices and statistics, were collected from national databases, scientific reports, field observations, and interviews. Preliminary results revealed that COVID-19 exerts its effects on the economy, agriculture, and food security of Iran through six major mechanisms, corresponding to a 30% decrease in the purchasing power parity in 2020 beside a significant increase in food prices compared to 2019. On the other hand, the expanding environmental constraints in Iran reduce the capacity of the agricultural sector to play a crucial role in the economy and ensure food security, and in this regard, COVID-19 forces the national programs and budget to combat rising ecological limitations. Accordingly, our study rejects the hypothesis that COVID-19 has not affected food security in Iran.
Residents’ Willingness to Pay for a Carbon Tax
Authors: Goh Ie Zheng , Matthew Nitanan Koshy
Published: September 2021

Addressing environmental issues has been a significant challenge. Malaysia is one of the fastest-growing countries in terms of economic, social, and land use development but high in CO2 emission rates. The introduction of a carbon tax is seen to reduce greenhouse gases emission (GHG), but the uncertain extent of implementation, based on economic theory, remains unknown. Hence, the current study’s objectives are to assess residents’ knowledge and attitude towards GHG. It is also to analyse the factors influencing residents’ Willingness to Pay (WTP). Three hundred and eleven (311) residents from Klang were selected using convenience sampling. The result shows that most of the respondents were willing to pay and had medium knowledge and a high level of attitude towards GHG. Poisson regression analysis results showed that gender, age, income, education, number of households, and marital status variables significantly influenced the maximum WTP. Overall, the residents’ WTP for a carbon tax was estimated at RM36.31 per year for open-ended (CVM): RM36.96 and double bound (CVM): RM35.65. A mechanism such as investment in green technology, eco-transportation, and green energy using the tax can be applied. This study is pivotal towards achieving SDG 13: Climate action.
Changes in Fan Energy Consumption According to Filters Installed in Residential Heat Recovery Ventilators in Korea
Authors: Cho Kyungjoo , Chae Chang-U , Cho Dongwoo , Kim Taeyeon
Published: September 2021

In recent years, because of outdoor ultrafine particles, residential heat recovery ventilators (HRVs) have been used with high efficiency filters by residents in Korea. However, as pre-filters are primarily used in residential HRVs, when a high-efficiency particulate air (HEPA) filter is installed, the filter pressure drop increases, reducing the airflow rate, which requires the fan to draw more power to maintain the airflow rate. Therefore, in this study, the change in power usage of HRVs installed in residential apartments in Korea with various air volumes and filters were analyzed. The results show that HEPA filters consumed 13.5–17.5% (16.1% on an average), 11.8–16.0% (13.8% on an average), and 16.8–41.3% (30.1% on an average) more power at 0.5, 1.0, and 1.5 air changes/h, respectively, than the pre-filter. These results indicate that unexpected power consumption increase could be caused if a pre-filter is replaced with a HEPA filter in residential small air-volume HRVs. This may lead to noise or failure due to fan overload. Thus, it is necessary to operate residential HRVs at the optimum air volume according to the fan performance.
The Effect of Nitrogen Fertilization on the Yield, Quality and Fatty Acid Composition of Opuntia ficus-indica Seed Oil
Authors: Nkoi Vuyelwa , Wit Maryna de , Fouche Herman , Coetzer Gesine , Hugo Arno
Published: September 2021

Cactus pears are nutritious, drought-tolerant plants that flourish in hot and arid regions. All its plant parts can be consumed by humans and animals. Fruit seed oil production is an important emerging industry in South Africa. As part of an initiative to promote cactus pears as multi-functional crops, dual-purpose cultivars should be identified, and their production increased. The aim of this study was to investigate the role of nitrogen (N) fertilizer on the seed oil yield and quality of Opuntia ficus-indica. The project encompassed a trial using N fertilization from three N sources (limestone ammonium nitrate, ammonium sulfate, urea) and four N application levels (0, 60, 120, 240 kg ha−1). Oil was quantitatively extracted from the seed using the Folch method; fatty acids were quantified using a Varian 430-GC. Seed oil content significantly increased (p = 0.035) with increased N fertilization rates; the oil yield ranged between 7.96 and 9.54%. The composition of the main fatty acids (oleic, palmitic, cis-vaccenic and stearic acid) was significantly influenced; oleic and stearic acid were significantly increased by higher fertilization levels whereas a reducing trend was observed in palmitic and cis-vaccenic acid levels. The highest content fatty acid, linoleic acid, was not significantly influenced.
On the Remuneration to Electrical Utilities and Budgetary Allocation for Substation Maintenance Management
Authors: Zarco-Periñán Pedro J. , Martínez-Ramos José L. , Zarco-Soto Fco. Javier
Published: September 2021

The liberalization of electricity markets has produced a great change in electrical utilities. One of these changes has affected the methodology for setting their remuneration. Depending on the country, these are different. Despite the wide range of remuneration methodologies for the electricity market of each country, they all feature one common element: the remuneration of operation and maintenance. One of the messages that this remuneration transmits is the need to extend the useful life of the facilities to allow sustainable development. This article focuses on the remuneration schemes of electrical utilities, the classification of substations for the definition of their maintenance programs, and the budget allocation for the execution of maintenance in these critical infrastructures. The particularity of these facilities, in which it is generally necessary to de-energize some of their parts for maintenance, has also been taken into account. To this end, a simple methodology currently used is presented based on the standardization of the bays of the substations and their classification into levels of importance. This classification into levels enables the facilities to be grouped according to similarities in their maintenance plans, although they differ from each other in terms of the periodicity of the application of maintenance procedures. This methodology guarantees a similar distribution of maintenance activities and financial needs over the years. In addition, the methodology allows one to know the importance of each substation (since the greater the equivalent weight, the greater the importance). Finally, the application of the proposed methodology in a real case is presented. It shows the simplicity, effectiveness, and lamination of the budgetary allocation of the proposed methodology, this being the main contribution of the formulation.
Are Landscape Restoration Interventions Sustainable? A Case for the Upper Tana Basin of Kenya
Authors: Kizito Fred , Gicheha Jane , Nurudeen Abdul Rahman , Tamene Lulseged , Nganga Kennedy , Koech Nicholas
Published: September 2021

Landscape restoration initiatives often have the potential to result in environmental gains, but the question of whether these gains are sustainable and how they are linked to other community needs (social, productivity and economic gains) remains unclear. We use the Sustainable Intensification Assessment Framework (SIAF) to demonstrate how environmental benefits are linked to productivity, environment, social, human, and economic components. Using the SIAF, the standardization of relevant indicators across multiple objectives provided a contextual representation of sustainability. The study assessed the overall gains resulting from the measured indicators of sustainable land management (SLM) practices and their relationship to the multiple domains of the SIAF. We present a unique case for SLM options using a combined-methods approach where biophysical, socio-economic, and citizen science help assess the sustainability of the interventions. Using a participatory approach with farmers, land restoration options were conducted in four target micro-watersheds for 3 years (2015–2017). Co-developed restoration measures at the landscape level within the four micro-watersheds (MW1-MW4) resulted in a substantial increment (50%) for all treatments (grass strips, terraces, and a combination of grass strips and terraces) in soil moisture storage and increased maize and forage production. We demonstrate that SLM practices, when used in combination, greatly reduce soil erosion and are profitable and sustainable while conferring livelihood benefits to smallholder farmers.
Disaster Risk Awareness: The Turkish Migrants Living in Northern Italy
Authors: Atun Funda , Fonio Chiara
Published: September 2021

In this study, we analysed the socio-demographic characteristics and disaster risk awareness of the Turkish migrants living in northern Italy. We initiated the study with an extensive face-to-face questionnaire with 544 individual respondents. With the help of the questionnaire, we gathered information on the socio-demographic structure of the Turkish community living in the area and the immigrants’ disaster experience, their level of disaster preparedness and disaster risk awareness, and their potential behaviour during an emergency. Additionally, we conducted focus group meetings in Milan, Lecco, Como and Varese with 49 migrants living in the region. In the focus group meetings, we discussed the migrants’ awareness of disasters and potential behaviour patterns during emergencies. We collected the informative booklets and past event reports prepared by civil protection centres and municipalities and used them in focus group meetings to collect participants’ opinions. The results show that the migrant communities’ disaster risk awareness is low, but their capacity to adapt to suddenly changing conditions is higher than presumed.
Average Luminance Calculation in Street Lighting Design, Comparison between BS-EN 13201 and RP-08 Standards
Authors: Rusu Alexandru Viorel , Galatanu Catalin Daniel , Livint Gheorghe , Lucache Dorin Dumitru
Published: September 2021

This paper presents a study on the influence of the observer’s position in relation to the calculation surface. This is the initial observation of the research, respectively that the two standards consider the position of the observer differently. For these situations, two types of calculations were performed. For the first set of calculations, the software used was DIALux 4.13 as this software can perform calculations in line with the RP-08 standard. The second set of calculations was performed with a script that offers the possibility to change the observer’s position. The conclusion was that EN-13201 has a better approach, but both standards could be improved. The second case study refers to the influence of the longitudinal observer position in an average luminance calculation. If one considers RP-08 as a guideline for performing the calculations, the conclusions are that changing the distance from the observer to the calculation surface has absolutely no effect on the average luminance value. On the other hand, if European standards are used as a guideline, changing the distance (from the standardized 60 m, either closer to the calculation surface or further away) can influence the overall results in average luminance and uniformity. Taking into account the results of these two case studies, the conclusion is that both RP-08 and BS-EN 13201 should be updated so that the observer’s distance in relation to the calculation surface would be a variable dependent on the stopping distance calculated based on the speed limit of the road.