bluuebunny/crossref_metadata_2025 huggingface dataset:
Fiberless, Multi-Channel fNIRS-EEG System Based on Silicon Photomultipliers: Towards Sensitive and Ecological Mapping of Brain Activity and Neurovascular Coupling
Authors: Chiarelli Antonio Maria , Perpetuini David , Croce Pierpaolo , Greco Giuseppe , Mistretta Leonardo , Rizzo Raimondo , Vinciguerra Vincenzo , Romeo Mario Francesco , Zappasodi Filippo , Merla Arcangelo , Fallica Pier Giorgio , Edlinger Günter , Ortner Rupert , Giaconia Giuseppe Costantino
Published: May 2020

Portable neuroimaging technologies can be employed for long-term monitoring of neurophysiological and neuropathological states. Functional Near-Infrared Spectroscopy (fNIRS) and Electroencephalography (EEG) are highly suited for such a purpose. Their multimodal integration allows the evaluation of hemodynamic and electrical brain activity together with neurovascular coupling. An innovative fNIRS-EEG system is here presented. The system integrated a novel continuous-wave fNIRS component and a modified commercial EEG device. fNIRS probing relied on fiberless technology based on light emitting diodes and silicon photomultipliers (SiPMs). SiPMs are sensitive semiconductor detectors, whose large detection area maximizes photon harvesting from the scalp and overcomes limitations of fiberless technology. To optimize the signal-to-noise ratio and avoid fNIRS-EEG interference, a digital lock-in was implemented for fNIRS signal acquisition. A benchtop characterization of the fNIRS component showed its high performances with a noise equivalent power below 1 pW. Moreover, the fNIRS-EEG device was tested in vivo during tasks stimulating visual, motor and pre-frontal cortices. Finally, the capabilities to perform ecological recordings were assessed in clinical settings on one Alzheimer’s Disease patient during long-lasting cognitive tests. The system can pave the way to portable technologies for accurate evaluation of multimodal brain activity, allowing their extensive employment in ecological environments and clinical practice.
A Novel LSTM for Multivariate Time Series with Massive Missingness
Authors: Fouladgar Nazanin , Främling Kary
Published: May 2020

Multivariate time series with missing data is ubiquitous when the streaming data is collected by sensors or any other recording instruments. For instance, the outdoor sensors gathering different meteorological variables may encounter low material sensitivity to specific situations, leading to incomplete information gathering. This is problematic in time series prediction with massive missingness and different missing rate of variables. Contribution addressing this problem on the regression task of meteorological datasets by employing Long Short-Term Memory (LSTM), capable of controlling the information flow with its memory unit, is still missing. In this paper, we propose a novel model called forward and backward variable-sensitive LSTM (FBVS-LSTM) consisting of two decay mechanisms and some informative data. The model inputs are mainly the missing indicator, time intervals of missingness in both forward and backward direction and missing rate of each variable. We employ this information to address the so-called missing not at random (MNAR) mechanism. Separately learning the features of each parameter, the model becomes adapted to deal with massive missingness. We conduct our experiment on three real-world datasets for the air pollution forecasting. The results demonstrate that our model performed well along with other LSTM-derivation models in terms of prediction accuracy.
Feasibility of a Wearable Reflectometric System for Sensing Skin Hydration
Authors: Schiavoni Raissa , Monti Giuseppina , Piuzzi Emanuele , Tarricone Luciano , Tedesco Annarita , De Benedetto Egidio , Cataldo Andrea
Published: May 2020

One of the major goals of Health 4.0 is to offer personalized care to patients, also through real-time, remote monitoring of their biomedical parameters. In this regard, wearable monitoring systems are crucial to deliver continuous appropriate care. For some biomedical parameters, there are a number of well established systems that offer adequate solutions for real-time, continuous patient monitoring. On the other hand, monitoring skin hydration still remains a challenging task. The continuous monitoring of this physiological parameter is extremely important in several contexts, for example for athletes, sick people, workers in hostile environments or for the elderly. State-of-the-art systems, however, exhibit some limitations, especially related with the possibility of continuous, real-time monitoring. Starting from these considerations, in this work, the feasibility of an innovative time-domain reflectometry (TDR)-based wearable, skin hydration sensing system for real-time, continuous monitoring of skin hydration level was investigated. The applicability of the proposed system was demonstrated, first, through experimental tests on reference substances, then, directly on human skin. The obtained results demonstrate the TDR technique and the proposed system holds unexplored potential for the aforementioned purposes.
Heart Rate Variability and Accelerometry as Classification Tools for Monitoring Perceived Stress Levels—A Pilot Study on Firefighters
Authors: Meina Michał , Ratajczak Ewa , Sadowska Maria , Rykaczewski Krzysztof , Dreszer Joanna , Bałaj Bibianna , Biedugnis Stanisław , Węgrzyński Wojciech , Krasuski Adam
Published: May 2020

Chronic stress is the main cause of health problems in high-risk jobs. Wearable sensors can become an ecologically valid method of stress level assessment in real-life applications. We sought to determine a non-invasive technique for objective stress monitoring. Data were collected from firefighters during 24-h shifts using sensor belts equipped with a dry-lead electrocardiograph (ECG) and a three-axial accelerometer. Levels of stress experienced during fire incidents were evaluated via a brief self-assessment questionnaire. Types of physical activity were distinguished basing on accelerometer readings, and heart rate variability (HRV) time series were segmented accordingly into corresponding fragments. Those segments were classified as stress/no-stress conditions. Receiver Operating Characteristic (ROC) analysis showed true positive classification as stress condition for 15% of incidents (while maintaining almost zero False Positive Rate), which parallels the amount of truly stressful incidents reported in the questionnaires. These results show a firm correspondence between the perceived stress level and physiological data. Psychophysiological measurements are reliable indicators of stress even in ecological settings and appear promising for chronic stress monitoring in high-risk jobs, such as firefighting.
Application and Algorithm of Ground-Penetrating Radar for Plant Root Detection: A Review
Authors: Liang Hao , Xing Linyin , Lin Jianhui
Published: May 2020

Attention to the natural environment is equivalent to observing the space in which we live. Plant roots, which are important organs of plants, require our close attention. The method of detecting root system without damaging plants has gradually become mainstream. At the same time, machine learning has been achieving good results in recent years; it has helped develop many tools to help us detect the underground environment of plants. Therefore, this article will introduce some existing content related to root detection technology and machine detection algorithms for root detection, proving that machine learning root detection technology has good recognition capabilities.
Multi-Level Cross Residual Network for Lung Nodule Classification
Authors: Lyu Juan , Bi Xiaojun , Ling Sai Ho
Published: May 2020

Computer-aided algorithm plays an important role in disease diagnosis through medical images. As one of the major cancers, lung cancer is commonly detected by computer tomography. To increase the survival rate of lung cancer patients, an early-stage diagnosis is necessary. In this paper, we propose a new structure, multi-level cross residual convolutional neural network (ML-xResNet), to classify the different types of lung nodule malignancies. ML-xResNet is constructed by three-level parallel ResNets with different convolution kernel sizes to extract multi-scale features of the inputs. Moreover, the residuals are connected not only with the current level but also with other levels in a crossover manner. To illustrate the performance of ML-xResNet, we apply the model to process ternary classification (benign, indeterminate, and malignant lung nodules) and binary classification (benign and malignant lung nodules) of lung nodules, respectively. Based on the experiment results, the proposed ML-xResNet achieves the best results of 85.88% accuracy for ternary classification and 92.19% accuracy for binary classification, without any additional handcrafted preprocessing algorithm.
An Efficient Interface for the Integration of IoT Devices with Smart Grids
Authors: Viel Felipe , Augusto Silva Luis , Leithardt Valderi Reis Quietinho , De Paz Santana Juan Francisco , Celeste Ghizoni Teive Raimundo , Albenes Zeferino Cesar
Published: May 2020

The evolution of computing devices and ubiquitous computing has led to the development of the Internet of Things (IoT). Smart Grids (SGs) stand out among the many applications of IoT and comprise several embedded intelligent technologies to improve the reliability and the safety of power grids. SGs use communication protocols for information exchange, such as the Open Smart Grid Protocol (OSGP). However, OSGP does not support the integration with devices compliant with the Constrained Application Protocol (CoAP), a communication protocol used in conventional IoT systems. In this sense, this article presents an efficient software interface that provides integration between OSGP and CoAP. The results obtained demonstrate the effectiveness of the proposed solution, which presents low communication overhead and enables the integration between IoT and SG systems.
Efficient Training Procedures for Multi-Spectral Demosaicing
Authors: Shopovska Ivana , Jovanov Ljubomir , Philips Wilfried
Published: May 2020

The simultaneous acquisition of multi-spectral images on a single sensor can be efficiently performed by single shot capture using a mutli-spectral filter array. This paper focused on the demosaicing of color and near-infrared bands and relied on a convolutional neural network (CNN). To train the deep learning model robustly and accurately, it is necessary to provide enough training data, with sufficient variability. We focused on the design of an efficient training procedure by discovering an optimal training dataset. We propose two data selection strategies, motivated by slightly different concepts. The general term that will be used for the proposed models trained using data selection is data selection-based multi-spectral demosaicing (DSMD). The first idea is clustering-based data selection (DSMD-C), with the goal to discover a representative subset with a high variance so as to train a robust model. The second is an adaptive-based data selection (DSMD-A), a self-guided approach that selects new data based on the current model accuracy. We performed a controlled experimental evaluation of the proposed training strategies and the results show that a careful selection of data does benefit the speed and accuracy of training. We are still able to achieve high reconstruction accuracy with a lightweight model.
Moving towards IoT Based Digital Communication: An Efficient Utilization of Power Spectrum Density for Smart Cities
Authors: Ali Tariq , Alwadie Abdullah S. , Rizwan Abdul Rasheed , Sajid Ahthasham , Irfan Muhammad , Awais Muhammad
Published: May 2020

The future of the Internet of Things (IoT) is interlinked with digital communication in smart cities. The digital signal power spectrum of smart IoT devices is greatly needed to provide communication support. The line codes play a significant role in data bit transmission in digital communication. The existing line-coding techniques are designed for traditional computing network technology and power spectrum density to translate data bits into a signal using various line code waveforms. The existing line-code techniques have multiple kinds of issues, such as the utilization of bandwidth, connection synchronization (CS), the direct current (DC) component, and power spectrum density (PSD). These highlighted issues are not adequate in IoT devices in smart cities due to their small size. However, there is a need to design an effective line-code method to deal with these issues in digital IoT-based communication for smart technologies, which enables smart services for smart cities. In this paper, the Shadow Encoding Scheme (SES) is proposed to transmit data bits efficiently by using a physical waveform in the smart cities’ ecosystem. SES provides a reliable transmission over the physical medium without using extra bandwidth and with ideal PSD. In it, the shadow copy of the repeating bitstream is forwarded, rather than repeating the actual stream again and again. The PSD is calculated with the help of mathematical equations to validate SES. MATLAB simulator is used to simulate SES and compared with other well-known digital line-code techniques. The bit error rate is also compared between SES and the chirp spread spectrum (CSS) for the specific data frames. The coordinates of the PSD graph are also shown in tabular form, which shows a vivid picture of the working conditions of various line codes.
Gait Variability Using Waist- and Ankle-Worn Inertial Measurement Units in Healthy Older Adults
Authors: Rantalainen Timo , Karavirta Laura , Pirkola Henrikki , Rantanen Taina , Linnamo Vesa
Published: May 2020

Gait variability observed in step duration is predictive of impending adverse health outcomes among apparently healthy older adults and could potentially be evaluated using wearable sensors (inertial measurement units, IMU). The purpose of the present study was to establish the reliability and concurrent validity of gait variability and complexity evaluated with a waist and an ankle-worn IMU. Seventeen women (age 74.8 (SD 44) years) and 10 men (73.7 (4.1) years) attended two laboratory measurement sessions a week apart. Their stride duration variability was concurrently evaluated based on a continuous 3 min walk using a force plate and a waist- and an ankle-worn IMU. Their gait complexity (multiscale sample entropy) was evaluated from the waist-worn IMU. The force plate indicated excellent stride duration variability reliability (intra-class correlation coefficient, ICC = 0.90), whereas fair to good reliability (ICC = 0.47 to 0.66) was observed from the IMUs. The IMUs exhibited poor to excellent concurrent validity in stride duration variability compared to the force plate (ICC = 0.22 to 0.93). A good to excellent reliability was observed for gait complexity in most coarseness scales (ICC = 0.60 to 0.82). A reasonable congruence with the force plate-measured stride duration variability was observed on many coarseness scales (correlation coefficient = 0.38 to 0.83). In conclusion, waist-worn IMU entropy estimates may provide a feasible indicator of gait variability among community-dwelling ambulatory older adults.
Industry 4.0 Lean Shopfloor Management Characterization Using EEG Sensors and Deep Learning
Authors: Schmidt Daniel , Villalba Diez Javier , Ordieres-Meré Joaquín , Gevers Roman , Schwiep Joerg , Molina Martin
Published: May 2020

Achieving the shift towards Industry 4.0 is only feasible through the active integration of the shopfloor into the transformation process. Several shopfloor management (SM) systems can aid this conversion. They form two major factions. The first includes methodologies such as Balanced Scorecard (BSC). A defining feature is rigid structures to fixate on pre-defined goals. Other SM strategies instead concentrate on continuous improvement by giving directions. An example of this group is the “HOSHIN KANRI TREE” (HKT). One way of analyzing the dissimilarities, the advantages and disadvantages of these groups, is to examine the neurological patterns of workers as they are applying these. This paper aims to achieve this evaluation through non-invasive electroencephalography (EEG) sensors, which capture the electrical activity of the brain. A deep learning (DL) soft sensor is used to classify the recorded data with an accuracy of 96.5%. Through this result and an analysis using the correlations of the EEG signals, it has been possible to detect relevant characteristics and differences in the brain’s activity. In conclusion, these findings are expected to help assess SM systems and give guidance to Industry 4.0 leaders.
Peg-in-Hole Assembly Based on Six-Legged Robots with Visual Detecting and Force Sensing
Authors: Zhao Yinan , Gao Feng , Zhao Yue , Chen Zhijun
Published: May 2020

Manipulators with multi degree-of-freedom (DOF) are widely used for the peg-in-hole task. Compared with manipulators, six-legged robots have better mobility performance apart from completing operational tasks. However, there are nearly no previous studies of six-legged robots performing the peg-in-hole task. In this article, a peg-in-hole approach for six-legged robots is studied and experimented with a six-parallel-legged robot. Firstly, we propose a method whereby a vision sensor and a force/torque (F/T) sensor can be used to explore the relative location between the hole and peg. According to the visual information, the robot can approach the hole. Next, based on the force feedback, the robot plans the trajectory in real time to mate the peg and hole. Then, during the insertion, admittance control is implemented to guarantee the smooth insertion. In addition, during the whole assembly process, the peg is held by the gripper and attached to the robot body. Connected to the body, the peg has sufficient workspace and six DOF to perform the assembly task. Finally, experiments were conducted to prove the suitability of the approach.
Proprioceptive Estimation of Forces Using Underactuated Fingers for Robot-Initiated pHRI
Authors: Ballesteros Joaquin , Pastor Francisco , Gómez-de-Gabriel Jesús M. , Gandarias Juan M. , García-Cerezo Alfonso J. , Urdiales Cristina
Published: May 2020

In physical Human–Robot Interaction (pHRI), forces exerted by humans need to be estimated to accommodate robot commands to human constraints, preferences, and needs. This paper presents a method for the estimation of the interaction forces between a human and a robot using a gripper with proprioceptive sensing. Specifically, we measure forces exerted by a human limb grabbed by an underactuated gripper in a frontal plane using only the gripper’s own sensors. This is achieved via a regression method, trained with experimental data from the values of the phalanx angles and actuator signals. The proposed method is intended for adaptive shared control in limb manipulation. Although adding force sensors provides better performance, the results obtained are accurate enough for this application. This approach requires no additional hardware: it relies uniquely on the gripper motor feedback—current, position and torque—and joint angles. Also, it is computationally cheap, so processing times are low enough to allow continuous human-adapted pHRI for shared control.
Toward Efficient Image Recognition in Sensor-Based IoT: A Weight Initialization Optimizing Method for CNN Based on RGB Influence Proportion
Authors: Deng Zile , Cao Yuanlong , Zhou Xinyu , Yi Yugen , Jiang Yirui , You Ilsun
Published: May 2020

As the Internet of Things (IoT) is predicted to deal with different problems based on big data, its applications have become increasingly dependent on visual data and deep learning technology, and it is a big challenge to find a suitable method for IoT systems to analyze image data. Traditional deep learning methods have never explicitly taken the color differences of data into account, but from the experience of human vision, colors play differently significant roles in recognizing things. This paper proposes a weight initialization method for deep learning in image recognition problems based on RGB influence proportion, aiming to improve the training process of the learning algorithms. In this paper, we try to extract the RGB proportion and utilize it in the weight initialization process. We conduct several experiments on different datasets to evaluate the effectiveness of our proposal, and it is proven to be effective on small datasets. In addition, as for the access to the RGB influence proportion, we also provide an expedient approach to get the early proportion for the following usage. We assume that the proposed method can be used for IoT sensors to securely analyze complex data in the future.
Medication Safety in Intravenous Therapy: A Compatibility Study and Analysis of Reaction Products of Dihydralazine and Metamizole
Authors: Koller Anna Katharina , Fischer Oliver , Krebs Sabine , Heinrich Markus R. , Dörje Frank
Published: May 2020

The pharmacotherapy of critically ill patients is challenging due to the variety of drugs that have to be applied. As the majority of pharmaceuticals must be administered intravenously because of the critical condition of the patients, the compatibility of co-applied intravenous drugs is crucial for a safe and successful infusion therapy. Antihypertensive therapy was reported by health care professionals to be ineffective in association with concomitant application of dihydralazine and metamizole (dipyrone). As both drugs are administered in German intensive care units, we analyzed their compatibility, examined the mechanisms of underlying dihydralazine degradation, and identified reaction products of dihydralazine and metamizole. Binary combinations were prepared at the high and the low end of the nominal administration concentration. Validated high performance liquid chromatography/ultraviolet absorption (HPLC-UV) analysis was conducted to quantify drug amount and high performance liquid chromatography/mass spectrometry (HPLC-MS) was used to analyze degradation products. The combinations of dihydralazine and metamizole proved to be incompatible as dihydralazine concentration decreased immediately and considerably. Metamizole also slightly decreased over time. Specific degradation products of dihydralazine were identified and a degradation pathway was postulated. Our findings demonstrate that the intravenous co-administration of dihydralazine and metamizole should be strictly avoided due to the incompatibility of these two drugs.
Stay or Leave Abusive Dating Relationships: Portuguese Victims’ Reasons and Barriers
Authors: Caridade Sónia , Pinheiro Inês , Dinis Maria Alzira Pimenta
Published: May 2020

The decision to stay or leave an abusive relationship is multifactorial and frequently involves a cyclic process involving several phases. This article presents a qualitative analysis regarding the reasons and barriers to stay or leave an abusive dating relationship, as well as the challenges that it implies. A semi-structured, in-depth interview was used to collect data from thirteen dating victims, aged 17–30 years and mainly female (n = 12). The emotional and affective dependence of the partner and the belief that behaviour may change emerge as the main reasons presented by the victims to remain in an abusive relationship. Shame, fear of losing the partner, and failure to recognize the abusive relationship were reported as the main barriers to leave the abusive relationship, thus making it difficult to seek help. Understanding reasons to stay in, or barriers to leave, an abusive relationship is fundamental to promoting help-seeking behaviours in victims of dating violence (DV), particularly in the case of young people, since it has serious implications in the developmental pathway of this age group.
The Relationship between Isometric Force-Time Characteristics and Dynamic Performance: A Systematic Review
Authors: Lum Danny , Haff G. Gregory , Barbosa Tiago M.
Published: May 2020

The purpose of this article was to review the data on the relationship between multi-joint isometric strength test (IsoTest) force-time characteristics (peak force, rate of force development and impulse) and dynamic performance that is available in the current literature. Four electronic databases were searched using search terms related to IsoTest. Studies were considered eligible if they were original research studies that investigated the relationships between multi-joint IsoTest and performance of dynamic movements; published in peer-reviewed journals; had participants who were athletes or active individuals who participate in recreational sports or resistance training, with no restriction on sex; and had full text available. A total of 47 studies were selected. These studies showed significant small to large correlations between isometric bench press (IBP) force-time variables and upper body dynamic performances (r2 = 0.221 to 0.608, p < 0.05) and significant small to very large correlation between isometric squat (ISqT) (r2 = 0.085 to 0.746, p < 0.05) and isometric mid-thigh pull (IMTP) (r2 = 0.120 to 0.941, p < 0.05) force-time variables with lower body dynamic performances. IsoTest force-time characteristics were shown to have small to very large correlations with dynamic performances of the upper and lower limbs as well as performance of sporting movements (r2 = 0.118 to 0.700, p < 0.05). These data suggest that IsoTest force-time characteristics provide insights into the force production capability of athletes which give insight into dynamic performance capabilities.
Analysis of Combustion Process of Protective Coating Paints
Authors: Polanczyk Andrzej , Majder-Lopatka Malgorzata , Dmochowska Anna , Salamonowicz Zdzislaw
Published: May 2020

Structural elements in buildings exposed to high temperature may lose their original stability. Application of steel structures has several advantages; however, deflection under exposure to high temperatures may be a potential obstacle. Therefore, the aim of the study was to determine how temperature affects decomposition of protective paints applied in the construction. A dedicated installation for the analysis of the combustion process of protective coating paints in a laboratory scale was prepared. The experimental device consisted of the following parts: top-loading furnace connected to the gas conditioner, the LAT MG-2 gas mixer, and portable gas analyzer GASMET DX-4010. The following type of the protective powder coating paints were analyzed: alkyd and polyurethane. The obtained results indicated that during thermal decomposition of paints, formaldehyde, benzene, heptane, and butanol were released, however in different concentrations. Moreover, decomposition temperature affected the type and amount of released gas mixture components. With increasing temperature, increased release of formaldehyde and benzene was noticed, while the concentration of butanol and heptane decreased. Finally, the product of thermal decomposition emitted in the highest concentration was formaldehyde, which can cause irritation and sensitization in humans.
Creative Enough to Become an Entrepreneur: A Multi-Wave Study of Creative Personality, Education, Entrepreneurial Identity, and Innovation
Authors: Zhou Jinyi , Xu Xingzi , Li Yawen , Liu Chengcheng
Published: May 2020

In order to sustain an innovative working style, entrepreneurs need to build unique identities. However, relatively few studies have investigated what types of individuals are more likely to construct an entrepreneurial identity. In the current study, drawing upon identity construction theory, we proposed that an important individual difference, creative personality, would have a positive impact on the construction of an entrepreneurial identity, which in turn would facilitate individuals’ work-related innovations. Education was proposed to moderate this mediating effect, in that individuals with a higher level of education would have a higher possibility of constructing an entrepreneurial identity and producing sustainable innovations. We suggested that with considerable education, creative individuals would become entrepreneurs during their career progression and harvest more work-related innovations. A multi-wave sample of 12,686 participants from the National Longitudinal Survey of Youth (1979) was used to test our hypotheses. The results indicated that creative personality, along with education, interactively predicted an individual’s entrepreneurial identity, which in turn predicted innovation. Education significantly moderated the mediating effect of entrepreneurial identity. The theoretical and practical implications were also discussed.
Powering the Commercial Sector in Nigeria Using Urban Swarm Solar Electrification
Authors: Babajide Abisoye , Brito Miguel Centeno
Published: May 2020

The commercial sector in Nigeria has been greatly hampered due to the poor availability of reliable electricity. In a 2014 World Bank report, nearly half of the firms doing business in Nigeria identified electricity as a major constraint, with over a quarter of them listing electricity as their biggest obstacle. The business losses due to electrical outages have been significant, with losses averaging about 16% of annual sales. The lack of access to reliable electricity is one of the biggest challenges to economic growth in Nigeria. This paper proposes a means of powering the commercial sector in Nigeria using urban swarm electrification. It outlines a conceptual framework for using a distributed network made up of grid-connected home solar PV systems as a viable option for providing the commercial sector with more reliable access to electricity. It further addresses the policy implications for the commercial sector with the enablement of more electrification options, implications that include strong economic impact, as well as the expansion and creation of new industries.
Integrated Software Development and Case Studies for Optimal Operation of Cascade Reservoir within the Environmental Flow Constraints
Authors: Wu Chengjun , Fang Guohua , Liao Tao , Huang Xianfeng , Qu Bo
Published: May 2020

Reservoir optimal operation considering aquatic ecological protection is a hot topic in current research. This paper proposes an improved minimum monthly average runoff method (IMMR) for calculating environmental flow and an improved invasive weed optimization algorithm (IIWO) for optimizing complex problems. An integrated software consists of three modules, which is developed in this paper, i.e., IIWO convergence test module, environmental flow calculation module, and cascade reservoir operation module. Three test functions are included in the IIWO convergence test module. The minimum monthly average runoff method (MMR), IMMR, Tennant Method, Q90, and Q95 are included in the environmental flow calculation module. The IIWO and invasive weed optimization algorithm (IWO) are included in the cascade reservoir operation module. Wujiang River Basin in China is studied as a case in this paper. The results show that the environmental flow of cascade reservoir calculated by IMMR is 1871 m3/s, the maximum and the minimum are calculated by T-O and T-M, respectively. The power generation of cascade reservoir calculated by IWO is less than IIWO. The conclusions that IIWO has better convergence than IWO in solving cascade reservoir model, and the water volume of environmental flow has no obvious influence on cascade reservoir operation are drawn.
Probabilistic Fire Risk Framework for Optimizing Construction Site Layout
Authors: El Meouche Rani , Abunemeh Mohammed , Hijazi Ihab , Mebarki Ahmed , Fatayer Fadi , Issa Amjad
Published: May 2020

Purpose: This paper aims to develop an efficient model able to reduce catastrophic consequences and the significant number of victims resulting from fires at construction sites. The paper proposes probabilistic modeling aimed to minimize the probability of failure of a construction site. Methodology: The developed model in this paper consists of modeling fire hazards, the vulnerability of the potential targets, and the risk within construction sites. The optimization algorithm called “differential evolution” is used in order to determine the optimal site layout, which is characterized by having the smallest overall probability of failure. A numerical simulation is performed to delineate an appropriate probability density function of the failure of the site. In addition, a geographic information system (GIS) is used to display the spatial variability of fire risk on a construction site. Findings: The paper provides an efficient model to enhance site layout planning and assign locations for supporting temporary facilities at appropriate positions within a construction site. The model is examined through applying it on a simple case study containing numerous facilities. All these facilities are considered vulnerable targets and some of them are potential fire hazards, with different intensity values. Value: Most of the previous research focuses on travel cost distance in developing site layout planning models. This paper fulfills the development of a valuable model able to generate an optimized construction site layout by minimizing the probability of failure of the whole site. It will assist the decision makers and the risk managers in identifying the riskiest zones on a construction site.
Anxiety and Bodily Pain in Older Women Participants in a Physical Education Program. A Multiple Moderated Mediation Analysis
Authors: Chiva-Bartoll Óscar , Morente-Oria Honorato , González-Fernández Francisco Tomás , Ruiz-Montero Pedro Jesús
Published: May 2020

(1) Background: Bodily pain is normally associated with the consequences of ageing, whereas anxiety shows a high prevalence in elderly people, decreasing the health-related quality of life (HRQoL). Pain coping strategies are used to reduce the consequences of pain, specifically in older people. This study analyzed if the passive and active pain coping strategies were significant moderators in the link between anxiety and bodily pain with a physical component as a mediator. (2) Methods: This cross-sectional study consisted of older women between 60 and 90 years old from small villages with under 5000 inhabitants, of whom 53.8% of the total were participants of a physical education program. Participants of the present study completed all sociodemographic (living alone/accompanied, marital and educational status, number of illnesses, and level of physical activity (PA)) and clinical (anxiety, HRQoL, and pain coping strategies) questionnaires. Anxiety was assessed by the Hospitality Anxiety and Depression Scale (HAD), passive and active strategies by the Vanderbilt Pain Management Inventory (VPMI), and bodily pain and the physical component by the SF-36 questionnaire. (3) Results: The physical component positively predicted bodily pain (p < 0.001) and passive strategies significantly moderated the effect of anxiety on the physical component (p = 0.034). (4) Conclusions: These outcomes help to understand the link between anxiety and bodily pain in older women and the moderation of pain coping strategies in this relationship. In addition, the physical component should be considered when physical education programs aimed at the reduction of bodily pain through the management of anxiety are designed.
The Bearing Stiffness Effect on In-Wheel Motors
Authors: Biček Matej , Connes Raphaël , Omerović Senad , Gündüz Aydin , Kunc Robert , Zupan Samo
Published: May 2020

In-wheel motors offer a promising solution for novel drivetrain architectures of future electric vehicles that could penetrate into the automotive industry by transferring the drive directly inside the wheels. The available literature mainly deals with the optimization of electromagnetically active parts; however, the mechanical design of electromagnetically passive parts that indirectly influence motor performance also require detailed analysis and extensive validation. To meet the optimal performance of an in-wheel motor, the mechanical design requires optimization of housing elements, thermal management, mechanical tolerancing and hub bearing selection. All of the mentioned factors have an indirect influence on the electromagnetic performance of the IWM and sustainability; therefore, the following paper identifies the hub bearing as a critical component for the in-wheel motor application. Acting loads are reviewed and their effect on component deformation is studied via analytically and numerically determined stiffness as well as later validated by measurements on the component and assembly level to ensure deformation envelope and functionality within a wide range of operations.
Soil Disturbance and Recovery after Coppicing a Mediterranean Oak Stand: The Effects of Silviculture and Technology
Authors: Venanzi Rachele , Picchio Rodolfo , Spinelli Raffaele , Grigolato Stefano
Published: May 2020

Traditional coppice management system is one of the most debated topics in the Mediterranean area, as it is a forest management system that accounts for over 23 million hectares. Coppicing is considered the oldest form of sustainable forest management. Its past and current widespread popularity is mainly due to its capacity to positively contribute to the rural economy and ecosystem services. This research aimed at assessing the effect of coppicing on soil characteristics, understanding a possible treatment return time, and evaluating the implementation of proper sustainable forest operations (SFOs) in order to have a better understanding of the disturbance caused by silvicultural treatment and forest operations with two different harvesting techniques. The results demonstrated that physical, chemical, and biological soil features were partially disturbed by the coppicing. Both silvicultural treatment and forest operations influenced soil disturbance. The least impactful technique was extraction by winch, while forwarding resulted in heavier alterations of soil characteristics. It took about five years for the soil to recover its original pre-harvest conditions when the disturbance was caused by the silvicultural treatment alone (non-trafficked areas) and about eight to nine years when the disturbance was the cumulated effect of silvicultural treatment and logging activity (trafficked areas).
Prognosis of COVID-19 in Patients with Liver and Kidney Diseases: An Early Systematic Review and Meta-Analysis
Authors: Oyelade Tope , Alqahtani Jaber , Canciani Gabriele
Published: May 2020

The mortality and severity in COVID-19 is increased in patients with comorbidities. The aim of this study was to evaluate the severity and mortality in COVID-19 patients with underlying kidney and liver diseases. We retrieved data on the clinical features and primary composite end point of COVID-19 patients from Medline and Embase which had been released from inception by the April 16, 2020. The data on two comorbidities, liver diseases and chronic kidney disease, were pooled and statistically analysed to explain the associated severity and mortality rate. One hundred and forty-two abstracts were screened, and 41 full articles were then read. In total, 22 studies including 5595 COVID-19 patients were included in this study with case fatality rate of 16%. The prevalence of liver diseases and chronic kidney disease (CKD) were 3% (95% CI; 2–3%) and 1% (95% CI; 1–2%), respectively. In patients with COVID-19 and underlying liver diseases, 57.33% (43/75) of cases were severe, with 17.65% mortality, while in CKD patients, 83.93% (47/56) of cases were severe and 53.33% (8/15) mortality was reported. This study found an increased risk of severity and mortality in COVID-19 patients with liver diseases or CKD. This will lead to better clinical management and inform the process of implementing more stringent preventative measures for this group of patients.
Discovery of Three Toxic Proteins of Klebsiella Phage fHe-Kpn01
Authors: Spruit Cindy M. , Wicklund Anu , Wan Xing , Skurnik Mikael , Pajunen Maria I.
Published: May 2020

The lytic phage, fHe-Kpn01 was isolated from sewage water using an extended-spectrum beta-lactamase-producing strain of Klebsiella pneumoniae as a host. The genome is 43,329 bp in size and contains direct terminal repeats of 222 bp. The genome contains 56 predicted genes, of which proteomics analysis detected 29 different proteins in purified phage particles. Comparison of fHe-Kpn01 to other phages, both morphologically and genetically, indicated that the phage belongs to the family Podoviridae and genus Drulisvirus. Because fHe-Kpn01 is strictly lytic and does not carry any known resistance or virulence genes, it is suitable for phage therapy. It has, however, a narrow host range since it infected only three of the 72 tested K. pneumoniae strains, two of which were of capsule type KL62. After annotation of the predicted genes based on the similarity to genes of known function and proteomics results on the virion-associated proteins, 22 gene products remained annotated as hypothetical proteins of unknown function (HPUF). These fHe-Kpn01 HPUFs were screened for their toxicity in Escherichia coli. Three of the HPUFs, encoded by the genes g10, g22, and g38, were confirmed to be toxic.
Modelling Degradation and Replication Kinetics of the Zika Virus In Vitro Infection
Authors: Bernhauerová Veronika , Rezelj Veronica V. , Vignuzzi Marco
Published: May 2020

Mathematical models of in vitro viral kinetics help us understand and quantify the main determinants underlying the virus–host cell interactions. We aimed to provide a numerical characterization of the Zika virus (ZIKV) in vitro infection kinetics, an arthropod-borne emerging virus that has gained public recognition due to its association with microcephaly in newborns. The mathematical model of in vitro viral infection typically assumes that degradation of extracellular infectious virus proceeds in an exponential manner, that is, each viral particle has the same probability of losing infectivity at any given time. We incubated ZIKV stock in the cell culture media and sampled with high frequency for quantification over the course of 96 h. The data showed a delay in the virus degradation in the first 24 h followed by a decline, which could not be captured by the model with exponentially distributed decay time of infectious virus. Thus, we proposed a model, in which inactivation of infectious ZIKV is gamma distributed and fit the model to the temporal measurements of infectious virus remaining in the media. The model was able to reproduce the data well and yielded the decay time of infectious ZIKV to be 40 h. We studied the in vitro ZIKV infection kinetics by conducting cell infection at two distinct multiplicity of infection and measuring viral loads over time. We fit the mathematical model of in vitro viral infection with gamma distributed degradation time of infectious virus to the viral growth data and identified the timespans and rates involved within the ZIKV-host cell interplay. Our mathematical analysis combined with the data provides a well-described example of non-exponential viral decay dynamics and presents numerical characterization of in vitro infection with ZIKV.
Recombinant Costimulatory Fusion Proteins as Functional Immunomodulators Enhance Antitumor Activity in Murine B16F10 Melanoma
Authors: Cai Huaman , Wang Wenfang , Lin Zhibing , Zhang Yan , Wu Bing , Wan Yuhua , Li Rongxiu
Published: May 2020

Blocking inhibitory signaling and engaging stimulatory signaling have emerged as important therapeutic modalities for cancer immunotherapy. This study aimed to investigate immunomodulatory features of three recombinant costimulatory ligand proteins in a mouse model, which are extracellular domains of OX40-ligand (OX40L), 4-1BB-ligand (4-1BBL), or two domains in tandem, fused with the transmembrane domain of diphtheria toxin (DTT), named DTT-COS1, DTT-COS2, and DTT-COS12, respectively. In vitro study showed that DTT-COS1 and DTT-COS12 had immunological activity increasing the ratio of CD8/CD4 T cells. Treatments with DTT-COS1 and DTT-COS12 dramatically generated immune protection against the B16F10 tumor challenge in both prophylactic and therapeutic efficacy. Furthermore, regarding tumor microenvironment (TME) immunomodulation, DTT-COS1 treatment increased the proportion of CD4+ effector T cells (Teff) and decreased the expression of a suppressive cytokine. Meanwhile, DTT-COS12 reduced regulatory T cells (Treg) and improved the level of stimulatory cytokines. In addition, endogenous antibodies against OX40L/4-1BBL were generated, which may help with antitumor responses. Unexpectedly, DTT-COS2 lacked antitumor effects in vitro and in vivo. Importantly, serum analysis of liver-function associated factors and pro-inflammatory cytokines demonstrated that treatments were safe formulations in mice without signs of systemic toxicity. Remarkably, DTT-COS1 and DTT-COS12 are functional immunomodulators for mouse B16F10 melanoma, creating practical preclinical value in cancer immunotherapy.
Pustulan Activates Chicken Bone Marrow-Derived Dendritic Cells In Vitro and Promotes Ex Vivo CD4+ T Cell Recall Response to Infectious Bronchitis Virus
Authors: Larsen Frederik T. , Guldbrandtsen Bernt , Christensen Dennis , Pitcovski Jacob , Kjærup Rikke B. , Dalgaard Tina S.
Published: May 2020

Infectious bronchitis virus (IBV) is a highly contagious avian coronavirus. IBV causes substantial worldwide economic losses in the poultry industry. Vaccination with live-attenuated viral vaccines, therefore, are of critical importance. Live-attenuated viral vaccines, however, exhibit the potential for reversion to virulence and recombination with virulent field strains. Therefore, alternatives such as subunit vaccines are needed together with the identification of suitable adjuvants, as subunit vaccines are less immunogenic than live-attenuated vaccines. Several glycan-based adjuvants directly targeting mammalian C-type lectin receptors were assessed in vitro using chicken bone marrow-derived dendritic cells (BM-DCs). The β-1-6-glucan, pustulan, induced an up-regulation of MHC class II (MHCII) cell surface expression, potentiated a strong proinflammatory cytokine response, and increased endocytosis in a cation-dependent manner. Ex vivo co-culture of peripheral blood monocytes from IBV-immunised chickens, and BM-DCs pulsed with pustulan-adjuvanted recombinant IBV N protein (rN), induced a strong recall response. Pustulan-adjuvanted rN induced a significantly higher CD4+ blast percentage compared to either rN, pustulan or media. However, the CD8+ and TCRγδ+ blast percentage were significantly lower with pustulan-adjuvanted rN compared to pustulan or media. Thus, pustulan enhanced the efficacy of MHCII antigen presentation, but apparently not the cross-presentation on MHCI. In conclusion, we found an immunopotentiating effect of pustulan in vitro using chicken BM-DCs. Thus, future in vivo studies might show pustulan as a promising glycan-based adjuvant for use in the poultry industry to contain the spread of coronaviridiae as well as of other avian viral pathogens.
CFD Modelling of Particle-Driven Gravity Currents in Reservoirs
Authors: Wildt Daniel , Hauer Christoph , Habersack Helmut , Tritthart Michael
Published: May 2020

Reservoir sedimentation results in ongoing loss of storage capacity all around the world. Thus, effective sediment management in reservoirs is becoming an increasingly important task requiring detailed process understanding. Computational fluid dynamics modelling can provide an efficient means to study relevant processes. An existing in-house hydrodynamic code has been extended to model particle-driven gravity currents. This has been realised through a buoyancy term which was added as a source term to the momentum equation. The model was successfully verified and validated using literature data of lock exchange experiments. In addition, the capability of the model to optimize venting of turbidity currents as an efficient sediment management strategy for reservoirs was tested. The results show that the concentration field during venting agrees well with observations from laboratory experiments documented in literature. The relevance of particle-driven gravity currents for the flow field in reservoirs is shown by comparing results of simulations with and without buoyant forces included into the model. The accuracy of the model in the area of the bottom outlet can possibly be improved through the implementation of a non-upwind scheme for the advection of velocity.