bluuebunny/crossref_metadata_2025 huggingface dataset:
Signal Transduction by VIP and PACAP Receptors
Authors: Langer Ingrid , Jeandriens Jérôme , Couvineau Alain , Sanmukh Swapnil , Latek Dorota
Published: February 2022

Homeostasis of the human immune system is regulated by many cellular components, including two neuropeptides, VIP and PACAP, primary stimuli for three class B G protein-coupled receptors, VPAC1, VPAC2, and PAC1. Vasoactive intestinal peptide (VIP) and pituitary adenylate cyclase-activating polypeptide (PACAP) regulate intestinal motility and secretion and influence the functioning of the endocrine and immune systems. Inhibition of VIP and PACAP receptors is an emerging concept for new pharmacotherapies for chronic inflammation and cancer, while activation of their receptors provides neuroprotection. A small number of known active compounds for these receptors still impose limitations on their use in therapeutics. Recent cryo-EM structures of VPAC1 and PAC1 receptors in their agonist-bound active state have provided insights regarding their mechanism of activation. Here, we describe major molecular switches of VPAC1, VPAC2, and PAC1 that may act as triggers for receptor activation and compare them with similar non-covalent interactions changing upon activation that were observed for other GPCRs. Interhelical interactions in VIP and PACAP receptors that are important for agonist binding and/or activation provide a molecular basis for the design of novel selective drugs demonstrating anti-inflammatory, anti-cancer, and neuroprotective effects. The impact of genetic variants of VIP, PACAP, and their receptors on signalling mediated by endogenous agonists is also described. This sequence diversity resulting from gene splicing has a significant impact on agonist selectivity and potency as well as on the signalling properties of VIP and PACAP receptors.
Immune-Checkpoint Inhibitors in Advanced Bladder Cancer: Seize the Day
Authors: Maiorano Brigida Anna , De Giorgi Ugo , Ciardiello Davide , Schinzari Giovanni , Cisternino Antonio , Tortora Giampaolo , Maiello Evaristo
Published: February 2022

Background: In advanced bladder cancer (BCa), platinum-based chemotherapy represents the first-choice treatment. In the last ten years, immune checkpoint inhibitors (ICIs) have changed the therapeutic landscape of many solid tumors. Our review aims to summarize the main findings regarding the clinical use of ICIs in advanced BCa. Methods: We searched PubMed, Embase, and Cochrane databases, and conference abstracts from international congresses (ASCO, ESMO, ASCO GU) for clinical trials, focusing on ICIs as monotherapy and combinations in metastatic BCa. Results: 18 studies were identified. ICIs targeting PD1 (nivolumab, pembrolizumab), PD-L1 (avelumab, atezolizumab, durvalumab), and CTLA4 (ipilimumab, tremelimumab) were used. Survival outcomes have been improved by second-line ICIs, whereas first-line results are dismal. Avelumab maintenance in patients obtaining disease control with chemotherapy has achieved the highest survival rates. Conclusions: ICIs improve survival after platinum-based chemotherapy. Avelumab maintenance represents a new practice-changing treatment. The combinations of ICIs and other compounds, such as FGFR-inhibitors, antibody-drug conjugates, and anti-angiogenic drugs, represent promising therapeutic approaches. Biomarkers with predictive roles and sequencing strategies are warranted for best patient selection.
A Detailed Hydrodynamic Study of the Split-Plate Airlift Reactor by Using Non-Invasive Gamma-Ray Techniques
Authors: Sabri Laith S. , Sultan Abbas J. , Majdi Hasan Shakir , Jebur Shadha K. , Al-Dahhan Muthanna H.
Published: February 2022

This study focused on detailed investigations of selected local hydrodynamics in split airlift reactor by using an unconventional measurements facility: computed tomography (CT) and radioactive particle tracking (RPT). The local distribution in a cross-sectional manner with its radial’s profiles for gas holdup, liquid velocity flow field, shear stresses, and turbulent kinetic energy were studied under various gas velocity 1, 2 and 3 cm/s with various six axial level z = 12, 20, 40, 60, 90 and 112 cm. The distribution in gas–liquid phases in the whole split reactor column, the riser and downcomer sides, including their behavior at the top and bottom sections of the split plate was also described. The outcomes of this study displayed an exemplary gas–liquid phases dispersion approximately in all reactor’s zones and had large magnitude over the ring of the sparger as well as upper the split plate. Furthermore, the outcomes pointed out that the distribution of this flow may significantly impacts the performance of the split reactor, which may have essential influence on its performance particularly for microorganisms culturing applications. These outcomes are dependable as benchmark information to validate computational fluid dynamics (CFD) simulations and other models.
Evaluation of Pediatric Immediate Life Support Courses by the Students
Authors: Manrique Ignacio , Calvo Custodio , Carrillo Angel , Sebastián Valero , Manrique Gema , López-Herce Jesús
Published: February 2022

A retrospective analysis was performed of 1637 questionnaires among students of immediate pediatric life support (IPLS) courses. All theory and practice classes and organization and methods received an average score higher than 8.5 except for the schedule and time devoted to developing contents. All parameters evaluating instructors’ skills received a score higher than 9. Participants requested more time to practice and for course adaptation to their specific professionals needs. IPLS courses are highly valued by students. The duration of IPLS practice sessions should be increased and the course should be adapted to the specific professional needs of participants.
Modeling Soil Organic Carbon Changes under Alternative Climatic Scenarios and Soil Properties Using DNDC Model at a Semi-Arid Mediterranean Environment
Authors: Lembaid Ibtissame , Moussadek Rachid , Mrabet Rachid , Bouhaouss Ahmed
Published: February 2022

Soil organic carbon (SOC) is one of the central issues in dealing with soil fertility as well as environmental and food safety. Due to the lack of relevant data sources and methodologies, analyzing SOC dynamics has been a challenge in Morocco. During the last two decades, process-based models have been adopted as alternative and powerful tools for modeling SOC dynamics; whereas, information and knowledge on the most sensitive model inputs under different climate, and soil conditions are still very limited. For this purpose, a sensitivity analysis was conducted in the present work, using the DeNitrification-DeComposition (DNDC) model based on the data collected at a semi-arid region (Merchouch station, Morocco). The objective is to identify the most influential factors affecting the DNDC-modeled SOC dynamics in a semi-arid region across different climatic and soil conditions. The results of sensitivity analysis highlighted air temperature as the main determinant of SOC. A decrease in air temperature of 4 °C results in an almost 161 kg C ha−1 yr−1 increase in C sequestration rate. Initial SOC was also confirmed to be one of the most sensitive parameters for SOC. There was a 96 kg C ha−1 yr−1 increase in C sequestration rate under low initial SOC (0.005 kg C ha−1). In the DNDC, air temperature in climatic factors and initial SOC in variable soil properties had the largest impacts on SOC accumulation in Merchouch station. We can conclude that the sensitivity analysis conducted in this study within the DNDC can contribute to provide a scientific evidence of uncertainties of the selected inputs variables who can lead to uncertainties on the SOC in the study site. The information in this paper can be helpful for scientists and policy makers, who are dealing with regions of similar environmental conditions as Merchouch Station, by identifying alternative scenarios of soil carbon sequestration.
Seahorse Predation by Octopuses in the Caribbean and the West Pacific
Authors: Muller Ellen , Harasti David , Hoeksema Bert W.
Published: February 2022

There is much documentation about seahorses (Hippocampus spp.) being threatened by habitat degradation and overfishing, but relatively few published studies mention their natural predators. The present study documents three cases in which seahorses are being caught by octopuses. In one case, the seahorse was partly consumed. These observations made at Bonaire (Caribbean Netherlands) and New South Wales (Australia) suggest that predation on seahorses by octopuses may be more widespread and common than previously thought.
Drone Technology for Monitoring Protected Areas in Remote and Fragile Environments
Authors: Bollard Barbara , Doshi Ashray , Gilbert Neil , Poirot Ceisha , Gillman Len
Published: February 2022

Protected Areas are established to protect significant ecosystems and historical artefacts. However, many are subject to little structured monitoring to assess whether the attributes for which they have been protected are being maintained or degraded. Monitoring sensitive areas using ground surveys risks causing damage to the values for which they are being protected, are usually based on limited sampling, and often convey insufficient detail for understanding ecosystem change. Therefore, there is a need to undertake quick and accurate vegetation surveys that are low impact, cost effective and repeatable with high precision. Here we use drone technology to map protected areas in Antarctica to ultra-high resolution and provide baseline data for future monitoring. Our methods can measure micro-scale changes, are less expensive than ground-based sampling and can be applied to any protected area where fine scale monitoring is desirable. Drone-based surveys should therefore become standard practice for protected areas in remote fragile environments.
Resilience and Posttraumatic Growth after Burn: A Review of Barriers, Enablers, and Interventions to Improve Psychological Recovery
Authors: Woolard Alix , Bullman Indijah , Allahham Amira , Long Treya , Milroy Helen , Wood Fiona , Martin Lisa
Published: February 2022

Burn injuries are traumatic experiences that can detrimentally impact an individual’s psychological and emotional wellbeing. Despite this, some survivors adapt to psychosocial challenges better than others despite similar characteristics relating to the burn. Positive adaptation is known as resilience or posttraumatic growth, depending on the trajectory and process. This review aimed to describe the constructs of resiliency and growth within the burn injury context, examine the risk factors that inhibit resilience or growth after burn (barriers), the factors that promote resilience or growth after burn (enablers), and finally to assess the impact of interventions that have been tested that may facilitate resilience or growth after burn. This review was performed according to the recently updated Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Guidelines. An electronic search was conducted in November 2021 on the databases PubMed, Medline (1966-present), Embase (1974-present), PsycINFO for English-language peer-reviewed academic articles. There were 33 studies included in the review. Findings were mixed for most studies; however, there were factors related to demographic information (age, gender), burn-specific characteristics (TBSA, time since burn), person-specific factors (personality, coping style), psychopathology (depression, PTSD), and psychosocial factors (social support, spirituality/religion, life purpose) that were evidenced to be related to resilience and growth. One qualitative study evaluated an intervention, and this study showed that a social camp for burn patients can promote resilience. This study has presented a variety of factors that inhibit or encourage resilience and growth, such as demographic, individual, and social factors. We also present suggestions on interventions that may be used to promote growth following this adverse event, such as improving social support, coping styles and deliberate positive introspection.
Optimization of Intrusion Detection Systems Determined by Ameliorated HNADAM-SGD Algorithm
Authors: Shyla Shyla , Bhatnagar Vishal , Bali Vikram , Bali Shivani
Published: February 2022

Information security is of pivotal concern for consistently streaming information over the widespread internetwork. The bottleneck flow of incoming and outgoing data traffic introduces the issues of malicious activities taken place by intruders, hackers and attackers in the form of authenticity obstruction, gridlocking data traffic, vandalizing data and crashing the established network. The issue of emerging suspicious activities is managed by the domain of Intrusion Detection Systems (IDS). The IDS consistently monitors the network for the identification of suspicious activities, and generates alarm and indication in the presence of malicious threats and worms. The performance of IDS is improved by using different machine learning algorithms. In this paper, the Nesterov-Accelerated Adaptive Moment Estimation–Stochastic Gradient Descent (HNADAM-SDG) algorithm is proposed to determine the performance of Intrusion Detection Systems IDS. The algorithm is used to optimize IDS systems by hybridization and tuning of hyperparameters. The performance of algorithm is compared with other classification algorithms such as logistic regression, ridge classifier and ensemble algorithms where the experimental analysis and computations show the improved accuracy with 99.8%, sensitivity with 99.7%, and specificity with 99.5%.
A Method for Evaluating the Maximum Capacity of Grid-Connected Wind Farms Considering Multiple Stability Constraints
Authors: Wu Xingyang , Xue Feng , Tang Yi , Dai Jianfeng
Published: February 2022

Boosting the capacity of grid-connected wind farms will greatly contribute to increasing the share of sustainable energy in the global generation mix. It is imperative to study the way to quantitatively assess the maximum capacity of grid-connected wind farms in combination with power system stability characteristics. In this work, a method to evaluate the maximum capacity of grid-connected wind farms considering the joint constraints of frequency and voltage stability is proposed based on the global intrinsic property of frequency stability and the local characteristic of voltage stability. Firstly, the maximum capacity of grid-connected wind farms in the power grid with high wind power penetration is assessed globally based on the frequency stability constraints, and then locally considering the voltage stability constraints of each local power grid. Further on, a quantitative method to evaluate the capacity of grid-connected wind farms is proposed based on the correlation between the local static voltage stability margin and the local capacity of grid-connected wind farms, as well as the global constraint of the maximum capacity of grid-connected wind farms. Finally, the effectiveness of the proposed method is verified by the simulation results of an actual regional power grid.
Research on Multi-Scene Electronic Component Detection Algorithm with Anchor Assignment Based on K-Means
Authors: Xia Zilin , Gu Jinan , Zhang Ke , Wang Wenbo , Li Jing
Published: February 2022

Achieving multi-scene electronic component detection is the key to automatic electronic component assembly. The study of a deep-learning-based multi-scene electronic component object detection method is an important research focus. There are many anchors in the current object detection methods, which often leads to extremely unbalanced positive and negative samples during training and requires manual adjustment of thresholds to divide positive and negative samples. Besides, the existing methods often bring a complex model with many parameters and large computation complexity. To meet these issues, a new method was proposed for the detection of electronic components in multiple scenes. Firstly, a new dataset was constructed to describe the multi-scene electronic component scene. Secondly, a K-Means-based two-stage adaptive division strategy was used to solve the imbalance of positive and negative samples. Thirdly, the EfficientNetV2 was selected as the backbone feature extraction network to make the method simpler and more efficient. Finally, the proposed algorithm was evaluated on both the public dataset and the constructed multi-scene electronic component dataset. The performance was outstanding compared to the current mainstream object detection algorithms, and the proposed method achieved the highest mAP (83.20% and 98.59%), lower FLOPs (44.26GMAC) and smaller Params (29.3 M).
Performance Evaluation of Deep Learning Based Network Intrusion Detection System across Multiple Balanced and Imbalanced Datasets
Authors: Meliboev Azizjon , Alikhanov Jumabek , Kim Wooseong
Published: February 2022

In the modern era of active network throughput and communication, the study of Intrusion Detection Systems (IDS) is a crucial role to ensure safe network resources and information from outside invasion. Recently, IDS has become a needful tool for improving flexibility and efficiency for unexpected and unpredictable invasions of the network. Deep learning (DL) is an essential and well-known tool to solve complex system problems and can learn rich features of enormous data. In this work, we aimed at a DL method for applying the effective and adaptive IDS by applying the architectures such as Convolutional Neural Network (CNN) and Long-Short Term Memory (LSTM), Recurrent Neural Network (RNN), Gated Recurrent Unit (GRU). CNN models have already proved an incredible performance in computer vision tasks. Moreover, the CNN can be applied to time-sequence data. We implement the DL models such as CNN, LSTM, RNN, GRU by using sequential data in a prearranged time range as a malicious traffic record for developing the IDS. The benign and attack records of network activities are classified, and a label is given for the supervised-learning method. We applied our approaches to three different benchmark data sets which are UNSW NB15, KDDCup ’99, NSL-KDD to show the efficiency of DL approaches. For contrast in performance, we applied CNN and LSTM combination models with varied parameters and architectures. In each implementation, we trained the models until 100 epochs accompanied by a learning rate of 0.0001 for both balanced and imbalanced train data scenarios. The single CNN and combination of LSTM models have overcome compared to others. This is essentially because the CNN model can learn high-level features that characterize the abstract patterns from network traffic records data.
Simulated Hough Transform Model Optimized for Straight-Line Recognition Using Frontier FPGA Devices
Authors: Gabrielli Alessandro , Alfonsi Fabrizio , Del Corso Francesca
Published: February 2022

The use of the Hough transforms to identify shapes or images has been extensively studied in the past using software for artificial intelligence applications. In this article, we present a generalization of the goal of shape recognition using the Hough transform, applied to a broader range of real problems. A software simulator was developed to generate input patterns (straight-lines) and test the ability of a generic low-latency system to identify these lines: first in a clean environment with no other inputs and then looking for the same lines as ambient background noise increases. In particular, the paper presents a study to optimize the implementation of the Hough transform algorithm in programmable digital devices, such as FPGAs. We investigated the ability of the Hough transform to discriminate straight-lines within a vast bundle of random lines, emulating a noisy environment. In more detail, the study follows an extensive investigation we recently conducted to recognize tracks of ionizing particles in high-energy physics. In this field, the lines can represent the trajectories of particles that must be immediately recognized as they are created in a particle detector. The main advantage of using FPGAs over any other component is their speed and low latency to investigate pattern recognition problems in a noisy environment. In fact, FPGAs guarantee a latency that increases linearly with the incoming data, while other solutions increase latency times more quickly. Furthermore, HT inherently adapts to incomplete input data sets, especially if resolutions are limited. Hence, an FPGA system that implements HT is inefficient for small sets of input data but becomes more cost-effective as the size of the input data increases. The document first presents an example that uses a large Accumulator consisting of 1100 × 600 Bins and several sets of input data to validate the Hough transform algorithm as random noise increases to 80% of input data. Then, a more specifically dedicated input set was chosen to emulate a real situation where a Xilinx UltraScale+ was to be used as the final target device. Thus, we have reduced the Accumulator to 280 × 280 Bins using a clock signal at 250 MHz and a few tens input points. Under these conditions, the behavior of the firmware matched the software simulations, confirming the feasibility of the HT implementation on FPGA.
An Online Data-Driven LPV Modeling Method for Turbo-Shaft Engines
Authors: Gu Ziyu , Pang Shuwei , Zhou Wenxiang , Li Yuchen , Li Qiuhong
Published: February 2022

The linear parameter-varying (LPV) model is widely used in aero engine control system design. The conventional local modeling method is inaccurate and inefficient in the full flying envelope. Hence, a novel online data-driven LPV modeling method based on the online sequential extreme learning machine (OS-ELM) with an additional multiplying layer (MLOS-ELM) was proposed. An extra multiplying layer was inserted between the hidden layer and the output layer, where the hidden layer outputs were multiplied by the input variables and state variables of the LPV model. Additionally, the input layer was set to the LPV model’s scheduling parameter. With the multiplying layer added, the state space equation matrices of the LPV model could be easily calculated using online gathered data. Simulation results showed that the outputs of the MLOS-ELM matched that of the component level model of a turbo-shaft engine precisely. The maximum approximation error was less than 0.18%. The predictive outputs of the proposed online data-driven LPV model after five samples also matched that of the component level model well, and the maximum predictive error within a large flight envelope was less than 1.1% with measurement noise considered. Thus, the efficiency and accuracy of the proposed method were validated.
Extended Residential Power Management Interface for Flexibility Communication and Uncertainty Reduction for Flexibility System Operators
Authors: Heider Felix , Jahic Amra , Plenz Maik , Schulz Detlef
Published: February 2022

The high importance of demand-side management for the stability of future smart grids came into focus years ago and is today undisputed among a wide spectrum of energy market participants, and within the research community. The increasing development of communication infrastructure, in tandem with the rising transparency of power grids, supports the efforts for deploying demand-side management applications. While it is then accepted that demand-side management will yield positive contributions, it remains challenging to identify, communicate, and access available flexibility to the flexibility managers. The knowledge about the system potential is essential to determine impacts of control and adjustment signals, and employ temporarily required demand-side flexibility to ensure power grid stability. The aim of this article is to introduce a methodology to determine and communicate local flexibility potential of end-user energy systems to flexibility managers for short-term access. The presented approach achieves a reliable calculation of flexibility, a standardized data aggregation, and a secure communication. With integration into an existing system architecture, the general applicability is outlined with a use case scenario for one end-user energy system. The approach yields a transparent short-term flexibility potential within the flexibility operator system.
Appropriate Technology-Based AMI Deployment in Multi-Dwelling Units
Authors: Oh Eunsung , Son Sung-Yong
Published: February 2022

Digital technologies, especially information and communication technologies, paved the way for social welfare by providing efficient and effective means for services. In the energy sector, advanced metering infrastructures (AMIs) are essential for providing various services through information measurement. In this article, we focus on the deployment of an AMI in multi-dwelling units where automated meter reading (AMR) infrastructures are installed. In particular, we explore whether the AMR should substitute the AMI with few alterations, while ensuring desirable accuracy. To determine the adequacy of technology, information measurement performance, service performance, and implementation cost are used as the indicators. Through a case study using real data recorded in Korea, we quantitatively estimate that AMR-based information measurement can exhibit adequate performance and performance degradation of less than 1% in a service environment utilizing AMI with a low-cost investment. We also discuss several technologies and implementation issues in the upcycling of AMR for more reliable service. This study provides a guide for when configuring an information measurement system for a new energy service.
Energy-Based Approaches in Estimating Actual Evapotranspiration Focusing on Land Surface Temperature: A Review of Methods, Concepts, and Challenges
Authors: Taheri Mercedeh , Mohammadian Abdolmajid , Ganji Fatemeh , Bigdeli Mostafa , Nasseri Mohsen
Published: February 2022

The surface energy balance (SEB) model is a physically based approach in which aerodynamic principles and bulk transfer theory are used to estimate actual evapotranspiration. A wide range of different methods have been developed to parameterize the SEB equation; however, few studies addressed solutions to the SEB considering the land surface temperature (LST). Therefore, in the current review, a clear and comprehensive classification is provided for energy-based approaches considering the key role of LST in solving the energy budget. In this regard, three general approaches are presented using LSTs derived by climate and land surface models (LSMs), satellite-based data, and energy balance closure. In addition, this review surveys the concepts, required inputs, and assumptions of energy-based LSMs and SEB algorithms in detail. The limitations and challenges of aforementioned approaches including land surface temperature, surface energy imbalance, and calculation of surface and aerodynamic resistance network are also assessed. According to the results, since the accuracy of resulting LSTs are affected by weather conditions, surface energy closure, and use of vegetation/meteorological information, all approaches are faced with uncertainties in determining ET. In addition, for further study, an interactive evaluation of water and energy conservation laws is recommended to improve the ET estimation accuracy.
Relationship Analysis and Optimisation of Space Layout to Improve the Energy Performance of Office Buildings
Authors: Du Tiantian , Turrin Michela , Jansen Sabine , van den Dobbelsteen Andy , De Luca Francesco
Published: February 2022

Architectural space layout has proven to be influential on building energy performance. However, the relationship between different space layouts and their consequent energy demands has not yet been systematically studied. This study thoroughly investigates such a relationship. In order to do so, a computational method was developed, which includes a method to generate space layouts featuring energy-related variables and an assessment method for energy demand. Additionally, a design of experiments was performed, and its results were used to analyse the relationship between space layouts and energy demands. In order to identify their relationship, four types of design indicators of space layout were proposed, both for the overall layout and for each function. Finally, several optimisations were performed to minimise heating, cooling and lighting demands. The optimisation results showed that the maximum reduction between different layouts was up to 54% for lighting demand, 51% for heating demand and 38% for cooling demand. The relationship analysis shows that when comparing the four types of design indicators, the façade area-to-floor area ratio showed a stronger correlation with energy demands than the façade area ratio, floor area ratio and height-to-depth ratio. Overall, this study shows that designing a space layout helps to reduce energy demands for heating, cooling and lighting, and also provides a reference for other researchers and designers to optimise space layout with improved energy performance.
Benchmarking Approaches for Assessing the Performance of Building Control Strategies: A Review
Authors: Ceccolini Clara , Sangi Roozbeh
Published: February 2022

In the last few decades, researchers have shown that advanced building controllers can reduce energy consumption without negatively impacting occupants’ wellbeing and help to manage building systems, which are becoming increasingly complex. Nevertheless, the lack of benefit awareness and demonstration projects undermines stakeholders’ trust, justifying the reluctance to approve new controls in the industry. Therefore, it is necessary to support the development of controls through solid arguments testifying to the performance gain that can be achieved. However, the absence of standardized and systematic testing methods limits the generalization of results and the ability to make fair cross-study comparisons. This study presents an overview of the different benchmarking approaches used to assess control performance. Our goal is to highlight trends, limitations, and controversies through analytics to support the definition of best practices, which remains a widely discussed topic in this research area. We aim to focus on simulation-based benchmarking, which is regarded as a promising solution to overcome the time and cost requirements related to field or hardware-in-the-loop testing. We identify and investigate four key steps relating to virtual benchmarking: defining the key performance indicators, specifying the reference control, characterizing the test scenarios, and post-processing the results. This work confirmed the expected heterogeneity, underlined recurrent features with the help of analytics, and recognized limits and open challenges.
A Comprehensive Assessment of Fundamental Overcurrent Relay Operation Optimization Function and Its Constraints
Authors: Rojnić Michele , Prenc Rene , Bulat Hrvoje , Franković Dubravko
Published: February 2022

The optimization of overcurrent relays’ operation is a topic associated with protection coordination of distribution networks. Usually, this refers to medium-voltage networks, since they are protected by numerical relay devices, as opposed to low-voltage networks, where utility operators allocate fuses. Correct setting of relays and optimal coordination is becoming a serious challenge to Distribution Network Operators around the world, since their networks’ passive operation has been greatly altered in the past two decades. Distributed generation units, a growing liberalized electricity market and more stringent legislation for distribution network planning and operation by state regulatory bodies have all indirectly affected the evolving of protection philosophy for distribution networks. In this paper the traditional optimization problem of overcurrent relay operation will be addressed and critically examined from both a theoretical and practical point of view. Optimization function, constraints and relay parameters will all be observed and compared with solutions used in distribution networks, and their modifications and improvements will be proposed and elaborated in detail.
HPC Geophysical Electromagnetics: A Synthetic VTI Model with Complex Bathymetry
Authors: Castillo-Reyes Octavio , de la Puente Josep , Cela José María
Published: February 2022

We introduce a new synthetic marine model for 3D controlled-source electromagnetic method (CSEM) surveys. The proposed model includes relevant features for the electromagnetic geophysical community such as large conductivity contrast with vertical transverse isotropy and a complex bathymetry profile. In this paper, we present the experimental setup and several 3D CSEM simulations in the presence of a resistivity unit denoting a hydrocarbon reservoir. We employ a parallel and high-order vector finite element routine to perform the CSEM simulations. By using tailored meshes, several scenarios are simulated to assess the influence of the reservoir unit presence on the electromagnetic responses. Our numerical assessment confirms that resistivity unit strongly influences the amplitude and phase of the electromagnetic measurements. We investigate the code performance for the solution of fundamental frequencies on high-performance computing architectures. Here, excellent performance ratios are obtained. Our benchmark model and its modeling results are developed under an open-source scheme that promotes easy access to data and reproducible solutions.
Microwave-Assisted Pyrolysis of Leather Waste
Authors: González-Lucas María , Peinado Manuel , Vaquero Juan J. , Nozal Leonor , Aguirre Juan Luis , González-Egido Sergio
Published: February 2022

The processing of leather into leather is one of the oldest known manufacturing practices. The subsequent refinement of this technique over recent centuries has led to an increase in production, which in turn has led to an increase in waste production. Today, many of the by-products and waste streams from the leather industry have applications in industries such as petfood and in the production of collagen and derivatives, while others, such as waste from trimming and scraping the material, are disposed of in landfills, causing a detrimental environmental impact. For this reason, new alternatives for the treatment of these wastes, such as pyrolysis, are being investigated. The aim of this work is to assess the feasibility of recovering non-recyclable waste from the leather industry by pyrolysis. Waste from the tanning of cowhides with vegetable tannins and tanning with chrome salts, without pre-treatment, were used as raw materials. The operating conditions of the microwave-assisted pyrolysis were analysed by varying the time (15–30 min), the power (600–1000 W) and the dopant (carbon from the pyrolysis itself) in a batch reactor that allows to treat about 30 g of a sample. Three fractions (liquid, solid and gaseous) were obtained from the waste treatment, and the liquid and gaseous fractions were characterised using different analytical techniques. The solid fraction can be used as fuel due to its high calorific value of more than 20 MJ/kg and its low ash content, with the residue containing vegetable tannins giving the best results with a calorific value of up to 28 MJ kg−1. In addition, the solid fraction can be used as activated carbon after activation treatment, which allows for a more technical use, e.g., in the chemical industry. The liquid fraction contains significant amounts of phenolic groups, such as pyrrole and phenol, as well as other derivatives. Pyridine, aniline, cresol and succinimide, among others, were also found. This makes it a valid source of chemical compounds of high added value in the chemical industry. In addition, the heavy liquid fraction has a good heat capacity of more than 21 MJ/kg, which makes it suitable for use as a fuel. The microwave-assisted pyrolysis process results in the possibility of obtaining products from waste that would otherwise be destined for landfill, thereby obtaining a large number of products and bioproducts with the ability to be reintroduced into the value chain quickly and easily.
A Strategy-Based Formal Approach for Fog Systems Analysis
Authors: Marir Souad , Belala Faiza , Hameurlain Nabil
Published: February 2022

Fog systems are a new emergent technology having a wide range of architectures and pronounced needs making their design complex. Consequently, the design of fog systems is crucial, including service portability and interoperability between the various elements of a system being the most essential aspects of fog computing. This article presents a fog system cross-layer architecture as a first step of such a design to provide a graphical and conceptual description. Then, a BiAgents* (Bigraphical Agents) formal model is defined to provide a rigorous description of physical, virtual, and behavioural aspects of Fog systems. Besides, this formalisation is implemented and executed under a Maude strategy system. The proposed approach is illustrated through a case study: an airport terminal Luggage Inspection System (LIS) while checking the correctness of its relevant properties: the portability of data and their interoperability. The integration of the Maude strategies in the rewriting of Fog system states made it possible to guide the execution of the model and its analysis.
Chemical Imaging of the Polylactic Acid − Wood Adhesion Interface of Bonded Veneer Products
Authors: Grigsby Warren , Torayno Desiree , Gaugler Marc , Luedtke Jan , Krause Andreas
Published: February 2022

The increasing use and potential of polylactic acid (PLA) in wood-based composite materials due to its greater performance over common polyolefins provides the justification for a closer examination of the PLA−wood adhesion performance. In PLA-bonded laminates and composites, the optical differentiation between PLA polymer and wood is not possible and necessitates complex techniques such as fluorescence microscopy to characterize the PLA adhesion interface. In this study, spatial chemical imaging via FTIR analysis has been successfully applied to directly identify PLA bondlines within PLA-bonded veneer laminates and to determine the migration of semi-crystalline and amorphous PLAs from the bondline into the wood structure. This method uses involved point contouring line spectra over the bondline area to distinguish the PLA polymer from the wood. From this quantitative analysis, it is revealed that bondline thickness and PLA penetration values depend on pressing temperature, and this has implications for the reinforcement of the adhesion interface and the bondline performance. Furthermore, in developing a methodology for this assessment, this spatial chemical imaging approach can equally be applied to other polyester, amide, and urethane systems used to bond wood laminates.
Stock Structure Analysis of the Endangered Queen Loach, Botia dario (Hamilton 1822) from Five Rivers of Northern Bangladesh by Using Morphometrics: Implications for Conservation
Authors: Mahfuj Md Sarower , Ahmed Fee Faysal , Hossain Md Firoj , Islam Sk Injamamul , Islam Md Jakiul , Alam Md Ashraful , Hoshan Imran , Nadia Zubyda Mushtari
Published: February 2022

Identifying stock is key to sustainable fisheries management and conservation. Using traditional morphometrics (TMR) and image-based truss network analysis (ITNA), we evaluated the stock structure of the endangered queen loach, Botia dario. The study was carried out in the following five stocks in Bangladesh’s northern rivers: the Atrai, Dhorala, Danu, Jamuna, and Padma. The inventory regarding stock structure was investigated using a total of nine traditional morphometrics, 11 ratios, and 23 truss measurements for each individual. To generate 23 ITNA, 12 landmarks were used. To assess variations among the stocks, a principal component analysis (PCA), factor analysis (FA), canonical variate analysis (CVA), and cluster analysis (CA) were performed. Six principal components explained 91.50% of the variation in TMR, while seven principal components explained 73.425% of the variation in ITNA. CVA, using traditional methods and ratios were correctly classified as 65.0%, 42.0%, 64.2%, 89.3%, and 77.5% for Danu, Padma, Jamuna, Dhorala, and Atrai River stocks, respectively, based on original grouped classes. CVA using ITNA was correctly classified as 90.0%, 80.0%, 77.4%, 94.6%, and 98.6% for Danu, Padma, Jamuna, Dhorala, and Atrai River stocks, respectively, based on original grouped classes. CVA analysis based on TMR and ITNA showed that cannonical variates (CV1 to CV3) are related to the whole-body shape. Both TMR and ITNA formed two clusters. In the first cluster, the Jamuna and Atrai River stocks combinedly formed a separate stock based on (TMR). In ITNA, the Dhorala and Atrai River formed as separate stocks from the other four stocks. According to this study, combining TMR and ITNA analysis aids in the differentiation of various B. dario stocks. The stock separation of this species was supposed to be geographic disconnection, waterway nature, and temperature variations. The B. dario stocks are heavily exploited and the species is an ideal nominee for species variation to boost the aquaculture yield. Within-stock distinctions were revealed in this study, necessitating the identification of gene pools and molecular studies to achieve a deeper understanding of the stocks. Through a more scientific approach, this stock structure study may aid in the development of conservation programs for this endangered species.
Investigating the Impact of Extruded Dehulled Adlay with Specific In Vitro Digestion Properties on Blood Lipids in Subjects with Mild to Moderate Dyslipidemia
Authors: Chung Chieh , Chao Ting-Yu , Chen Hong-Jhang , Xie Gui-Ru , Chiang Wenchang , Hsieh Shu-Chen
Published: February 2022

Dyslipidemia, a major risk factor for cardiovascular diseases (CVDs), is modifiable by diet and lifestyle changes. A large population with mild to moderate dyslipidemia is at risk of developing CVDs, and early initiation of preventive measures can avert advancing into severe medical conditions. Studies suggest increasing slowly digestible starch (SDS) in diets can help lower blood lipids. We processed dehulled adlay, a cereal rich in bioactive compounds, such as polyphenols and phytosterols, into an instant meal by extrusion and milling and then assessed its starch composition and in vitro digestibility. The dehulled adlay was found to consist of 32% SDS and resistant starch combined. Then, eligible subjects with dyslipidemia were recruited to explore the adlay’s hypolipidemic potential, safety, and acceptability. Subjects consumed the dehulled adlay as the sole carbohydrate source in their breakfast, without changing other components in the diet or lifestyle, for 12 weeks. After intervention, serum total cholesterol (TC) decreased significantly in subjects with hypercholesterolemia. In addition, both TC and triglyceride levels decreased significantly in those above 50 years old. In conclusion, the extruded dehulled adlay displays potential for favorably modulating blood lipids, and the effect is more pronounced in the middle-aged population.
Characterization of the Key Aroma Constituents in Fried Tilapia through the Sensorics Concept
Authors: Liu Mingyuan , Zhao Xiaoying , Zhao Mouming , Liu Xiaoling , Pang Yiyang , Zhang Meishuo
Published: February 2022

The object of this study was tilapia fish that were fried in soybean oil. Volatile compounds were extracted from the fish by ASE-HVE and were studied by GC-O-MS and the AEDA analysis method. A total of 30 aroma compounds were initially determined, and these compounds contribute to the aroma of fried tilapias. The key volatile compounds in fried tilapia were quantitatively analyzed by GC-MS, and the volatile compounds in soybean-fried tilapia were studied by flavor recombination and deletion experiments. Trimethylamine, hexanal, 2,3-dimethylpyrazine, dimethyl trisulfide, trans-2-octenal, 2,3-dimethyl-5-ethylpyrazine, (E)-2-nonenal, 2-propyl-pyridine, and (E,E)-2,4-decadienal were finally determined to be the key volatile compounds in soybean-fried tilapia.
QbD Supported Optimization of the Alginate-Chitosan Nanoparticles of Simvastatin in Enhancing the Anti-Proliferative Activity against Tongue Carcinoma
Authors: Rizg Waleed Y. , Naveen N. Raghavendra , Kurakula Mallesh , Bukhary Haitham A. , Safhi Awaji Y. , Alfayez Eman , Sindi Amal M. , Ali Sarah , Murshid Samar S. , Hosny Khaled M.
Published: February 2022

The goal of the current study is to develop a chitosan alginate nanoparticle system encapsulating the model drug, simvastatin (SIM-CA-NP) using a novel polyelectrolytic complexation method. The formulation was optimized using the central composite design by considering the concentrations of chitosan and alginate at five different levels (coded as +1.414, +1, 0, −1, and −1.414) in achieving minimum particle size (PS-Y1) and maximum entrapment efficiency (EE-Y2). A total of 13 runs were formulated (as projected by the Design-Expert software) and evaluated accordingly for the selected responses. On basis of the desirability approach (D = 0.880), a formulation containing 0.258 g of chitosan and 0.353 g of alginate could fulfill the prerequisites of optimum formulation in achieving 142.56 nm of PS and 75.18% EE. Optimized formulation (O-SIM-CAN) was further evaluated for PS and EE to compare with the theoretical results, and relative error was found to be within the acceptable limits, thus confirming the accuracy of the selected design. SIM release from O-SIM-CAN was retarded significantly even beyond 96 h, due to the encapsulation in chitosan alginate carriers. The cell viability study and Caspase-3 enzyme assay showed a notable difference in contrast to that of plain SIM and control group. All these stated results confirm that the alginate-chitosan nanoparticulate system enhanced the anti-proliferative activity of SIM.
Low-Content Pre-Emulsified Safflower Seed Oil Enhances the Quality and Flavor of the Nemipterus Virgatus Surimi Gel
Authors: Song Chunyong , Lin Yufeng , Hong Pengzhi , Liu Huanming , Zhou Chunxia
Published: February 2022

Surimi-based products occupy an important position in the aquatic product processing industry. To enhance the quality and flavor of surimi-based products, the effects of pre-emulsified safflower seed oil on the texture, water-holding capacity (WHC), microstructure, and flavor of Nemipterus virgatus surimi gel was evaluated. The texture and whiteness of the gel were improved, and the WHC increased (p < 0.05) as the content of safflower seed oil increased up to 2 mL per 100 g surimi. Furthermore, the drops of pre-emulsified safflower seed oils with an average diameter of less than 0.10 μm were evenly distributed in gel matrix. Microstructure and infrared spectroscopy analyses indicated that low-content pre-emulsified safflower seed oil acted as filler particles to occupy void spaces, resulting in gel exhibiting a dense network structure. Volatile analysis showed the gel containing pre-emulsified oil enriched volatile compounds, mainly resulting from the oxidation and decomposition of oils by the activation of lipoxygenase, which synergistically contributes to unique flavors of gel. Consequently, low-content pre-emulsified safflower seed oil can used to enhance the quality and flavor of N. virgatus surimi-based products. These findings are especially relevant to the current growing interest in low-fat and high-protein diets.