bluuebunny/crossref_metadata_2025 huggingface dataset:
Evolution and Testing of NB-IoT Solutions
Authors: Díaz Zayas Almudena , Rivas Tocado Francisco Javier , Rodríguez Pilar
Published: November 2020

NB-IoT is the first 3GPP technology that has been specifically developed for IoT. In this paper, we will introduce the most important NB-IoT features included in Release 14, Release 15, and Release 16 and the need for testing of NB-IoT solutions. This paper is focused on demonstrating the potential of the new experimentation features included into the TRIANGLE testbed to support testing and benchmarking of Narrowband Internet of Thing (NB-IoT) solutions. TRIANGLE provides an experimentation framework that offers a high level of abstraction using a framework that allows for defining and executing experiments in a very straightforward way. The experimentation framework developed as part of the TRIANGLE project optionally keeps experimenters far from the low level configuration of the infrastructure and provides scenarios which reproduce realistic conditions.
Escaping Local Minima in Path Planning Using a Robust Bacterial Foraging Algorithm
Authors: Abdi Mohammed Isam Ismael , Khan Muhammad Umer , Güneş Ahmet , Mishra Deepti
Published: November 2020

The bacterial foraging optimization (BFO) algorithm successfully searches for an optimal path from start to finish in the presence of obstacles over a flat surface map. However, the algorithm suffers from getting stuck in the local minima whenever non-circular obstacles are encountered. The retrieval from the local minima is crucial, as otherwise, it can cause the failure of the whole task. This research proposes an improved version of BFO called robust bacterial foraging (RBF), which can effectively avoid obstacles, both of circular and non-circular shape, without falling into the local minima. The virtual obstacles are generated in the local minima, causing the robot to retract and regenerate a safe path. The proposed method is easily extendable to multiple robots that can coordinate with each other. The information related to the virtual obstacles is shared with the whole swarm, so that they can escape the same local minima to save time and energy. To test the effectiveness of the proposed algorithm, a comparison is made against the existing BFO algorithm. Through the results, it was witnessed that the proposed approach successfully recovered from the local minima, whereas the BFO got stuck.
Methodology for Dimensioning the Socio-Economic Impact of Power-to-Gas Technologies in a Circular Economy Scenario
Authors: Llera-Sastresa Eva , Romeo Luis M. , Scarpellini Sabina , Portillo-Tarragona Pilar
Published: November 2020

Innovative and sustainable energy technologies are needed in the transition of energy toward a circular economy. Because of the use of renewable energy and carbon utilization, power-to-gas could be a cutting-edge technology that supports the circular model in future sustainable energy markets. However, this technology faces new technical and socio-economic challenges. The use of power-to-gas is limited because of barriers that limit the mobilization of investment capital. In addition, social and economic impacts on the territories in which these facilities are located are under study. In this context, the aims of this paper are: (i) To explore the determinants and barriers for power-to-gas technology to enhance the understanding of investment in innovative energy technologies; and (ii) to support effective policymaking and energy companies’ decision-making processes. This study defines and measures, from a circular economy perspective, the main impacts of the deployment of this technology on a territory in terms of volume of investment, employment generation, and CO2 capture. The study also provides a simplified methodology to contribute to the analysis of the use of power-to-gas. Finally, it improves the knowledge of the socio-economic impact of this cutting-edge technology for the transition of energy to a zero-emission scenario.
Generating Bessel-Gaussian Beams with Controlled Axial Intensity Distribution
Authors: Stsepuro Nikita , Nosov Pavel , Galkin Maxim , Krasin George , Kovalev Michael , Kudryashov Sergey
Published: November 2020

This paper investigated the diffraction of a Gaussian laser beam on a binary mask and a refractive axicon. The principles of the formation of a zero-order Bessel beam with sharp drops of the axial field intensity edges were discussed. A laser optical system based on an axicon for the formation of a Bessel beam with quasi-uniform distribution of axial field intensity was proposed. In the laser optical system, the influence of the axicon apex did not affect the output beam. The results of theoretical and experimental studies are presented. It is expected that the research results will have practical application in optical tweezers, imaging systems, as well as laser technologies using high-power radiation.
A Simple Scheme for Photonic Generation of Microwave Waveforms Using a Dual-drive Mach–Zehnder Modulator
Authors: Hu Jingjing , Li Jian , Zhao Jiayi , Ren Zichen , Gu Yiying , Zhao Mingshan
Published: November 2020

In this paper, a novel photonic scheme for the generation of square and triangular waveforms is proposed and experimentally demonstrated by using a dual-drive Mach–Zehnder modulator (DDMZM) without any optical signal processing. By properly setting the modulation index of the DDMZM, the square and triangular microwave waveforms could be easily achieved in conjunction with a 90° hybrid coupler. Furthermore, the modulation index of the DDMZM could be tuned for a low radio frequency (RF) signal power requirement by tuning the phase difference of the RF signals applied to the two arms of the DDMZM. The proposed scheme for the photonic generation of microwave waveforms is theoretically analyzed and experimentally demonstrated. The periodical triangular and square waveforms with repetition rates of 5 GHz, 8 GHz, and 10 GHz are successfully obtained. The root-mean-square errors between the generated and theoretical triangular and square waveforms with a repetition of 5 GHz are 0.042 and 0.053, respectively.
M2GSNet: Multi-Modal Multi-Task Graph Spatiotemporal Network for Ultra-Short-Term Wind Farm Cluster Power Prediction
Authors: Fan Hang , Zhang Xuemin , Mei Shengwei , Chen Kunjin , Chen Xinyang
Published: November 2020

Ultra-short-term wind power prediction is of great importance for the integration of renewable energy. It is the foundation of probabilistic prediction and even a slight increase in the prediction accuracy can exert significant improvement for the safe and economic operation of power systems. However, due to the complex spatiotemporal relationship and the intrinsic characteristic of nonlinear, randomness and intermittence, the prediction of regional wind farm clusters and each wind farm’s power is still a challenge. In this paper, a framework based on graph neural network and numerical weather prediction (NWP) is proposed for the ultra-short-term wind power prediction. First, the adjacent matrix of wind farms, which are regarded as the vertexes of a graph, is defined based on geographical distance. Second, two graph neural networks are designed to extract the spatiotemporal feature of historical wind power and NWP information separately. Then, these features are fused based on multi-modal learning. Third, to enhance the efficiency of prediction method, a multi-task learning method is adopted to extract the common feature of the regional wind farm cluster and it can output the prediction of each wind farm at the same time. The cases of a wind farm cluster located in Northeast China verified that the accuracy of a regional wind farm cluster power prediction is improved, and the time consumption increases slowly when the number of wind farms grows. The results indicate that this method has great potential to be used in large-scale wind farm clusters.
The Impact of Support Type on the Reliability of Steel Trusses Subjected to the Action of a Fire
Authors: Kubicka Katarzyna , Radoń Urszula
Published: November 2020

The objective of the article involves examining the impact of the type of supporting steel truss on its reliability under the conditions of a fire. The paper uses the system reliability method. Its application was preceded by the identification of kinematically admissible failure mechanisms (KAFMs) and the performance of strength-static calculations for all structural elements for a given moment of fire duration, meaning under the load of current temperature. The KAFMS were identified by the spectral analysis of the stiffness matrix. The criterion of the collapse for a single element was buckling for elements in compression and exceeding the yield strength for elements in tension. A reliability analysis and the calculation of temperature, axial forces, and the bearing capacity of individual elements were performed using original software created in the C++ language. The Cornell reliability index β was adopted as the measure of reliability. A drop in its value along with the fire development was presented for the analyzed structures. The obtained results indicate unambiguously that in the case of a structure subjected to fire action, the selection of a support method is of the utmost importance and determines its safety.
The Effect of Heat Sink Properties on Solar Cell Cooling Systems
Authors: Arifin Zainal , Suyitno Suyitno , Tjahjana Dominicus Danardono Dwi Prija , Juwana Wibawa Endra , Putra Mufti Reza Aulia , Prabowo Aditya Rio
Published: November 2020

High energy demand is leading to the replacement of fossil energy with renewable sources such as solar energy. Solar cells are devices used to generate solar energy. However, when exposed to sunlight with high intensity, a solar cell can suffer a decrease in performance due to overheating. This issue can be addressing by adding a cooling system. This study used a passive cooling system by adding a heat sink with fins to the body panel of the solar cell. The advantage of the passive cooling system is that it does not require additional energy. The number of fins and types of material were varied to obtain the best passive cooling system. The number of fins used was 5, 10, and 15, and the materials used were aluminum and copper. The wind speed vector and the temperature distribution were investigated through simulation. The results showed an increase in the number of fins provided better cooling capacity and increased the photovoltaic performance. The best cooling capability and performance were obtained using 15 fins with a copper base and fin heat sink materials. The decrease in temperature and the increase in efficiency were 10.2 °C and 2.74%, respectively. Therefore, the use of passive cooling system based on heat sinks with fins could provide a potential solution to increase performance and prevent overheating of photovoltaic (PV) panel systems.
“Blurry Touch Finger”: Touch-Based Interaction for Mobile Virtual Reality with Clip-on Lenses
Authors: Kim Youngwon Ryan , Park Suhan , Kim Gerard J.
Published: November 2020

In this paper, we propose and explore a touch screen based interaction technique, called the “Blurry Touch Finger” for EasyVR, a mobile VR platform with non-isolating flip-on glasses that allows the fingers accessible to the screen. We demonstrate that, with the proposed technique, the user is able to accurately select virtual objects, seen under the lenses, directly with the fingers even though they are blurred and physically block the target object. This is possible owing to the binocular rivalry that renders the fingertips semi-transparent. We carried out a first stage basic evaluation assessing the object selection performance and general usability of Blurry Touch Finger. The study has revealed that, for objects with the screen space sizes greater than about 0.5 cm, the selection performance and usability of the Blurry Touch Finger, as applied in the EasyVR configuration, was comparable to or higher than those with both the conventional head-directed and hand/controller based ray-casting selection methods. However, for smaller sized objects, much below the size of the fingertip, the touch based selection was both less performing and usable due to the usual fat finger problem and difficulty in stereoscopic focus.
Assessment of the Highest Stress Concentration Area Generated on the Mandibular Structure Using Meshless Finite Elements Analysis
Authors: Fabra Rivera Andrea , Magalhães Frederico de Castro , Moreno Amalia , Campos Rubio Juan
Published: November 2020

Frequently, the oral cavity area can be affected by different diseases, so the patient needs to be submitted to surgery to remove a specific region of the mandibular. A complete or partial discontinuity of the mandibular bone can cause direct or indirect forces variations during the mastication. The dental prosthesis is an alternative to generate an aesthetic or functional solution for oral cavity lesions. However, they can be wrongly designed, or they can lose the adjustment during their useful life, deteriorating the patient’s condition. In this work, the influence of the fixation components position for a dental prosthesis will be studied based on the finite element method. By means, it is possible to determine the area of the highest stress concentration generated on the mandibular structure. The temporomandibular image obtained by computational tomography was used as a 3D graphic whole model because in the medical area the morphological factors are extremely important. Vertical loads of 50, 100, 150 and 200 N were applied in three different regions: in the whole buccal cavity, simultaneously in the left and right laterals and only in the right lateral, to determine the values of von Mises stress in the mandible. These results were compared between three finite element software packages (Ansys®, SolidWorks® and Inventor®) and a meshless software (SimSolid®). They showed similar behaviors in the highest mechanical stress concentration in the same regions. Regarding the stress values, the percentage error between each software package was less than 10%. The use of SimSolid® software (meshless) proved to be better at identifying the higher stress generated by the dental prosthesis in the facial skeleton, so its computational efficiency, due to its geometric complexity, was highlighted.
The Use of Plant Growth-Promoting Bacteria to Prevent Nematode Damage to Plants
Authors: Gamalero Elisa , Glick Bernard R.
Published: November 2020

Plant-parasitic nematodes have been estimated to annually cause around US $173 billion in damage to plant crops worldwide. Moreover, with global climate change, it has been suggested that the damage to crops from nematodes is likely to increase in the future. Currently, a variety of potentially dangerous and toxic chemical agents are used to limit the damage to crops by plant-parasitic nematodes. As an alternative to chemicals and a more environmentally friendly means of decreasing nematode damage to plants, researchers have begun to examine the possible use of various soil bacteria, including plant growth-promoting bacteria (PGPB). Here, the current literature on some of the major mechanisms employed by these soil bacteria is examined. It is expected that within the next 5–10 years, as scientists continue to elaborate the mechanisms used by these bacteria, biocontrol soil bacteria will gradually replace the use of chemicals as nematicides.
Acute Physiological Responses to High-Intensity Resistance Circuit Training vs. Traditional Strength Training in Soccer Players
Authors: Marín-Pagán Cristian , Blazevich Anthony J. , Chung Linda H. , Romero-Arenas Salvador , Freitas Tomás T. , Alcaraz Pedro E.
Published: November 2020

The aim of this study was to evaluate and compare the cardiorespiratory and metabolic responses induced by high-intensity resistance circuit-based (HRC) and traditional strength (TS) training protocols. Ten amateur soccer players reported to the laboratory on four occasions: (1) protocol familiarization and load determination; (2) maximal oxygen consumption test; (3) and (4) resistance training protocols (HRC and TS), completed in a cross-over randomized order. In both protocols, the same structure was used (two blocks of 3 sets × 3 exercises, separated by a 5-min rest), with only the time between consecutive exercises differing: TS (3 min) and HRC (~35 s, allowing 3 min of local recovery). To test for between-protocol differences, paired t-tests were applied. Results showed that oxygen consumption and heart rate during HRC were 75% and 39% higher than TS, respectively (p < 0.001). After the training sessions, blood lactate concentration at 1.5, 5 and 7 min and excess post-exercise oxygen consumption were higher in HRC. The respiratory exchange ratio was 6.7% greater during HRC, with no between-group differences found post-exercise. The energy cost of HRC was ~66% higher than TS. In conclusion, HRC training induces greater cardiorespiratory and metabolic responses in soccer players and thus may be a time-effective training strategy.
Hyaluronan: Metabolism and Function
Authors: Kobayashi Takashi , Chanmee Theerawut , Itano Naoki
Published: November 2020

As a major polysaccharide component of the extracellular matrix, hyaluronan plays essential roles in the organization of tissue architecture and the regulation of cellular functions, such as cell proliferation and migration, through interactions with cell-surface receptors and binding molecules. Metabolic pathways for biosynthesis and degradation tightly control the turnover rate, concentration, and molecular size of hyaluronan in tissues. Despite the relatively simple chemical composition of this polysaccharide, its wide range of molecular weights mediate diverse functions that depend on molecular size and tissue concentration. Genetic engineering and pharmacological approaches have demonstrated close associations between hyaluronan metabolism and functions in many physiological and pathological events, including morphogenesis, wound healing, and inflammation. Moreover, emerging evidence has suggested that the accumulation of hyaluronan extracellular matrix and fragments due to the altered expression of hyaluronan synthases and hyaluronidases potentiates cancer development and progression by remodeling the tumor microenvironment. In addition to the well-known functions exerted by extracellular hyaluronan, recent metabolomic approaches have also revealed that its synthesis can regulate cellular functions via the reprogramming of cellular metabolism. This review highlights the current advances in knowledge on the biosynthesis and catabolism of hyaluronan and describes the diverse functions associated with hyaluronan metabolism.
Characterization of UVA-Induced Alterations to Transfer RNA Sequences
Authors: Sun Congliang , Limbach Patrick A. , Addepalli Balasubrahmanyam
Published: November 2020

Ultraviolet radiation (UVR) adversely affects the integrity of DNA, RNA, and their nucleoside modifications. By employing liquid chromatography–tandem mass spectrometry (LC–MS/MS)-based RNA modification mapping approaches, we identified the transfer RNA (tRNA) regions most vulnerable to photooxidation. Photooxidative damage to the anticodon and variable loop regions was consistently observed in both modified and unmodified sequences of tRNA upon UVA (λ 370 nm) exposure. The extent of oxidative damage measured in terms of oxidized guanosine, however, was higher in unmodified RNA compared to its modified version, suggesting an auxiliary role for nucleoside modifications. The type of oxidation product formed in the anticodon stem–loop region varied with the modification type, status, and whether the tRNA was inside or outside the cell during exposure. Oligonucleotide-based characterization of tRNA following UVA exposure also revealed the presence of novel photoproducts and stable intermediates not observed by nucleoside analysis alone. This approach provides sequence-specific information revealing potential hotspots for UVA-induced damage in tRNAs.
Evaluation of the Correlation between the rs4918 Polymorphism of AHSG Gene and Coronary Artery Calcification in Patients with Coronary Artery Disease
Authors: Ahmadihosseini Zeynab , Moeinian Morteza , Nazemi Saeed , Elyasi Sepideh , Mohammadpour Amir Hooshang
Published: November 2020

Objectives: Fetuin-A is a circulating calcification inhibitor that prevents coronary artery calcification (CAC) by increasing calcium phosphate solubility and inhibiting VSMC differentiation and apoptosis. In this study, we investigated the correlation between rs4918 and CAC in patients with coronary artery disease (CAD). Methods: Forty-two healthy individuals and eighty-one CAD patients were recruited in the present study. The CAC score (CACS) was measured by CT angiography and the genotype analysis of rs4918 single-nucleotide polymorphism SNP was performed by the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) technique. Results: The CACS was significantly higher in CAD patients compared to healthy individuals (p < 0.001); however, there was no significant difference between the mean CACS in the presence and absence of rs4918 (p = 0.792). The mean calcium score of the left main coronary artery (LMCA) was significantly lower in carriers of the rs4918 allele (p = 0.036). The frequency of rs4918 SNP was almost similar in the control group and CAD patients (p = 0.846). Conclusions: in patients with CAD, we found no significant association between rs4918 SNP and CACS, indicating that carriers of this allele are not at increased risk of developing cardiovascular diseases compared with those without.
New Insights on Molecular Mechanism of Hepatitis B Virus Covalently Closed Circular DNA Formation
Authors: Marchetti Alexander L. , Guo Haitao
Published: November 2020

The chronic factor of the Hepatitis B Virus (HBV), specifically the covalently closed circular DNA (cccDNA), is a highly stable and active viral episomal genome established in the livers of chronic hepatitis B patients as a constant source of disease. Being able to target and eliminate cccDNA is the end goal for a genuine cure for HBV. Yet how HBV cccDNA is formed from the viral genomic relaxed circular DNA (rcDNA) and by what host factors had been long-standing research questions. It is generally acknowledged that HBV hijacks cellular functions to turn the open circular DNA conformation of rcDNA into cccDNA through DNA repair mechanisms. With great efforts from the HBV research community, there have been several recent leaps in our understanding of cccDNA formation. It is our goal in this review to analyze the recent reports showing evidence of cellular factor’s involvement in the molecular pathway of cccDNA biosynthesis.
The Denominator Matters! Lessons from Large Database Research in Neonatology
Authors: Tolia Veeral N. , Clark Reese H.
Published: November 2020

Observational studies from large datasets are becoming more common in neonatology. In this review, we highlight the importance of the denominator in study design and interpretation including examples of bias from source data, weight-based categories, age-related bias, and diagnosis-based denominators.
Developing a POS Tagged Corpus of Urdu Tweets
Authors: Baig Amber , Rahman Mutee U , Kazi Hameedullah , Baloch Ahsanullah
Published: November 2020

Processing of social media text like tweets is challenging for traditional Natural Language Processing (NLP) tools developed for well-edited text due to the noisy nature of such text. However, demand for tools and resources to correctly process such noisy text has increased in recent years due to the usefulness of such text in various applications. Literature reports various efforts made to develop tools and resources to process such noisy text for various languages, notably, part-of-speech (POS) tagging, an NLP task having a direct effect on the performance of other successive text processing activities. Still, no such attempt has been made to develop a POS tagger for Urdu social media content. Thus, the focus of this paper is on POS tagging of Urdu tweets. We introduce a new tagset for POS-tagging of Urdu tweets along with the POS-tagged Urdu tweets corpus. We also investigated bootstrapping as a potential solution for overcoming the shortage of manually annotated data and present a supervised POS tagger with an accuracy of 93.8% precision, 92.9% recall and 93.3% F-measure.
Social Distancing in Indoor Spaces: An Intelligent Guide Based on the Internet of Things: COVID-19 as a Case Study
Authors: Alrashidi Malek
Published: November 2020

Using Internet of Things (IoT) solutions is a promising way to ensure that social distancing is respected, especially in common indoor spaces. This paper proposes a system of placement and relocation of people within an indoor space, using an intelligent method based on two optimizers (ant colony and particle swarm) to find the optimal relocation of a set of people equipped with IoT devices to control their locations and movements. As a real-world test, an amphitheater with students was used, and the algorithms guided students toward correct, safe positions. Two evolutionary algorithms are proposed to resolve the studied problem, ant colony optimization and particle swarm optimization. Then, a comparative analysis was performed between these two algorithms and a genetic algorithm, using different evaluation metrics to assess the behavior of the proposed system. The results show the efficiency of the proposed intelligent IoT system.
The Effect of Catalogue Lead Time on Medium-Term Earthquake Forecasting with Application to New Zealand Data
Authors: Rhoades David A. , J. Rastin Sepideh J. , Christophersen Annemarie
Published: November 2020

‘Every Earthquake a Precursor According to Scale’ (EEPAS) is a catalogue-based model to forecast earthquakes within the coming months, years and decades, depending on magnitude. EEPAS has been shown to perform well in seismically active regions like New Zealand (NZ). It is based on the observation that seismicity increases prior to major earthquakes. This increase follows predictive scaling relations. For larger target earthquakes, the precursor time is longer and precursory seismicity may have occurred prior to the start of the catalogue. Here, we derive a formula for the completeness of precursory earthquake contributions to a target earthquake as a function of its magnitude and lead time, where the lead time is the length of time from the start of the catalogue to its time of occurrence. We develop two new versions of EEPAS and apply them to NZ data. The Fixed Lead time EEPAS (FLEEPAS) model is used to examine the effect of the lead time on forecasting, and the Fixed Lead time Compensated EEPAS (FLCEEPAS) model compensates for incompleteness of precursory earthquake contributions. FLEEPAS reveals a space-time trade-off of precursory seismicity that requires further investigation. Both models improve forecasting performance at short lead times, although the improvement is achieved in different ways.
Deep Semantic-Preserving Reconstruction Hashing for Unsupervised Cross-Modal Retrieval
Authors: Cheng Shuli , Wang Liejun , Du Anyu
Published: November 2020

Deep hashing is the mainstream algorithm for large-scale cross-modal retrieval due to its high retrieval speed and low storage capacity, but the problem of reconstruction of modal semantic information is still very challenging. In order to further solve the problem of unsupervised cross-modal retrieval semantic reconstruction, we propose a novel deep semantic-preserving reconstruction hashing (DSPRH). The algorithm combines spatial and channel semantic information, and mines modal semantic information based on adaptive self-encoding and joint semantic reconstruction loss. The main contributions are as follows: (1) We introduce a new spatial pooling network module based on tensor regular-polymorphic decomposition theory to generate rank-1 tensor to capture high-order context semantics, which can assist the backbone network to capture important contextual modal semantic information. (2) Based on optimization perspective, we use global covariance pooling to capture channel semantic information and accelerate network convergence. In feature reconstruction layer, we use two bottlenecks auto-encoding to achieve visual-text modal interaction. (3) In metric learning, we design a new loss function to optimize model parameters, which can preserve the correlation between image modalities and text modalities. The DSPRH algorithm is tested on MIRFlickr-25K and NUS-WIDE. The experimental results show that DSPRH has achieved better performance on retrieval tasks.
Indoor LOS Propagation Measurements and Modeling at 26, 32, and 39 GHz Millimeter-Wave Frequency Bands
Authors: Pimienta-del-Valle Domingo , Mendo Luis , Riera José Manuel , Garcia-del-Pino Pedro
Published: November 2020

Although the deployment of 5G networks has already started, there are still open questions regarding propagation at millimeter-wave frequency bands. Several propagation campaigns have been carried out at several bands previously identified by regulatory organizations, but due to the wide range of allocated segments of spectrum and the variety of possible propagation scenarios, more measurement campaigns are needed. In this regard, the Universidad Politécnica de Madrid (UPM) has taken millimeter-wave measurements at 26, 32, and 39 GHz bands in an indoor corridor scenario in line-of-sight (LOS) conditions with two antenna configurations (a horn antenna has been used in transmission whereas horn and omnidirectional antennas have been used in reception), and the main results are presented in this paper. The obtained path loss results have been compared with existing millimeter-wave propagation models.
PV Energy Performance in a Sustainable Campus
Authors: Castrillón-Mendoza Rosaura , Manrique-Castillo Paul Andrés , Rey-Hernández Javier M. , Rey-Martínez Francisco J. , González-Palomino Gabriel
Published: November 2020

The challenge of photovoltaic integration as the basis of an energy generation system has been achieved and carried out by the University Autónoma de Cali, Colombia, using an avant-garde energy technology model. This innovative sustainable campus not only fulfills its purpose as an advanced model of a renewable energy integration system, it also aims at environmental research, e-mobility, and energy efficiency. This paper describes how the university implements the technological innovation of integrating the photovoltaic system installation in a university campus, showing its relevant contribution to the electricity generation in the campus buildings by analyzing the different electrical parameters together with the system performance indicators. The implementation of technological solutions has allowed the generation of a quantity of renewable energy within the campus, supplying a sustainable energy response based on energy efficiency and carbon emissions savings. This innovation has been applied following the international standards for the evaluation of the energy performance of photovoltaic systems (IEC 61724), reaching very optimal values for this type of renewable solution. In this paper, the dynamic monitoring of several parameters has been carried out in order to analyze the energy performance, and an energy simulation has been used to achieve optimal solutions and to obtain the perfect modeling of the system. This study shows how to evaluate the performance of an integration of a photovoltaic system in a smart university campus, according to international standards. It achieves complete viability due to its economic savings, energy efficiency and reduction of carbon emission.
Numerical Calculation and Uncertain Optimization of Energy Conversion in Interior Ballistics Stage
Authors: Xin Tong , Yang Guolai , Wang Liqun , Sun Quanzhao
Published: November 2020

Gun firing is a process that converts propellant chemical energy to projectile kinetic energy and other kinds of energies. In order to explore the energy conversion process, firstly, the interior ballistics mathematical model and the barrel-projectile finite element model are built and solved. Then, the related variable values and energy values are obtained and discussed. Finally, for improving energy efficiency, the interval uncertainty optimization problem is modeled, and then solved using the two-layer nested optimization strategy and back-propagation (BP) neural network surrogate model. Calculation results show that, after optimization, the heat efficiency raises from 31.13% to 33.05% and the max rifling stress decreases from 893.68 to 859.76 Mpa, which would improve the firing performance and prolong the lifetime of the gun barrel.
Experimental Study of Three-Bed Adsorption Chiller with Desalination Function
Authors: Sztekler Karol , Kalawa Wojciech , Nowak Wojciech , Mika Lukasz , Gradziel Slawomir , Krzywanski Jaroslaw , Radomska Ewelina
Published: November 2020

Energy efficiency is one of the most important topics nowadays. It is strictly related to energy demand, energy policy, environmental pollution, and economic issues. Energy efficiency can be increased and operating costs reduced by using waste heat from other processes. One of the possibilities is to use sorption chillers to produce chilled water and desalinated water. Low-temperature waste heat is not easy to utilize because of the low energy potential. Using adsorption chillers in low-temperature conditions allows utilizing waste heat and producing useful products in many regions of the world. The paper presents the results of an experimental study carried out on a three-bed adsorption chiller with desalination function, using silica gel and water as a working pair. The laboratory test stand included one evaporator, one condenser, and three separate tanks for water, desalinated water, and brine, respectively. The test stands scheme and description were presented. All results were obtained during several test hours with stable temperature conditions in the range of 57–85 °C for the heating water. It is found that the Coefficient of Performance (COP) increased from 0.20 to 0.58 when the heating water temperature increased from 57 to 85 °C. A similar finding is reported for Specific Cooling Power (SCP), which increased from 27 to 160 W/kg as the heating water temperature increased from 57 to 85 °C. It can be concluded that the heating water temperature strongly impacts the performance of the adsorption chiller.
Effect of Diatomaceous Biosilica and Talc on the Properties of Dielectric Elastomer Based Composites
Authors: Olewnik-Kruszkowska Ewa , Brzozowska Weronika , Adamczyk Arkadiusz , Gierszewska Magdalena , Wojtczak Izabela , Sprynskyy Myroslav
Published: November 2020

Currently, scientists are still looking for new polymeric materials characterized by improved mechanical, thermal as well as dielectric properties. Moreover, it should be stressed that new composites should be environmentally friendly. For this reason, the aim of this work is to establish the influence of natural fillers in the form of diatomaceous biosilica (B) and talc (T) on the properties of dielectric elastomer (DE)-based composites. The dielectric elastomer-based materials have been tested taking into account their morphology, thermal and mechanical properties. Moreover, the dielectric constant of the obtained materials was evaluated. Obtained results revealed that the presence of both diatomaceous biosilica and talc significantly increases dielectric properties while having no significant effect on the mechanical properties of the obtained composites. It should be stressed that the performed analyses constitute a valuable source of knowledge on the effective modification of the thermal and dielectric properties of newly obtained materials.
Assessing the Relationship between Litter + Duff Consumption and Post-Fire Soil Temperature Regimes
Authors: Smith Crystal N. , Hagan Donald L.
Published: November 2020

The immediate effects of wildland fire on soil have been well documented. However, we know much less about the longer-term effects and their implications for plants. Post-fire soil temperature regimes, for example, have received relatively little research attention, despite potential effects on plant phenology and establishment. Using portable temperature datalogger units (iButtons), we conducted an experimental study to assess how fire severity (measured in terms of litter and duff consumption) influences biologically relevant temperature parameters such as diel minimums, maximums, means, and ranges. We also used these data to calculate cumulative soil growing degree days (GDDs). The study was conducted during the early to mid-spring to capture the transition from dormant season to growing season. Results indicate that mean and max soil temperatures increase in the weeks after fire, with the most pronounced effects in the higher severity treatments. By the end of the 40-day study period, soils in the high severity burn treatment had accumulated 72 GDDs, compared to 17.9, 13.6, and 1.4 in moderate, low, and control treatments, respectively. These findings indicate that fire severity has significant and persistent effects on post-fire soil temperature regimes, and this likely has implications for the post-fire vegetation response.
Multiscale Simulation of the Formation of Platinum-Particles on Alumina Nanoparticles in a Spray Flame Experiment
Authors: Wollny Patrick , Angel Steven , Wiggers Hartmut , Kempf Andreas M. , Wlokas Irenaeus
Published: November 2020

Platinum decorated alumina particles have the potential of being a highly (cost-)effective catalyst. The particles are synthesized from platinum(II) acetylacetonate dissolved in a mixture of isopropanol and acetic acid with dispersed alumina carriers. The process is simulated by means of large eddy simulation with reaction kinetics and aerosol dynamics modeling. A two mixture fraction approach for tabulated chemistry with a thickened flame model is used to consider the complex reaction kinetics of the solvent spray combustion. Diffusion is described followings Ficks law with a unity Lewis number for the gas phase species, whereas the particle diffusion coefficients are calculated according to the kinetic theory. An extended model for aerosol dynamics, capable of predicting deposition rate and surface particle growth, is derived from the classical sectional technique. The simulations are compared and validated with product particle characteristics obtained from the experimental observations. Distributions for different locations within the simulation domain show the evolution of particle sizes deposited on the alumina particle surface, and transmission electron microscopy (TEM) images of the composite particles are shown in comparison to 3D particles ballistically reconstructed from simulation data. The ratio of deposited platinum on the alumina carrier particles and the mean diameters of the deposited particles are in good agreement with the experimental observation. Overall, the new method has demonstrated to be suitable for simulating the particle decoration process.
Prediction of the Limiting Flux and Its Correlation with the Reynolds Number during the Microfiltration of Skim Milk Using an Improved Model
Authors: Astudillo-Castro Carolina , Cordova Andrés , Oyanedel-Craver Vinka , Soto-Maldonado Carmen , Valencia Pedro , Henriquez Paola , Jimenez-Flores Rafael
Published: November 2020

Limiting flux (JL) determination is a critical issue for membrane processing. This work presents a modified exponential model for JL calculation, based on a previously published version. Our research focused on skim milk microfiltrations. The processing variables studied were the crossflow velocity (CFV), membrane hydraulic diameter (dh), temperature, and concentration factor, totaling 62 experimental runs. Results showed that, by adding a new parameter called minimum transmembrane pressure, the modified model not only improved the fit of the experimental data compared to the former version (R2 > 97.00%), but also revealed the existence of a minimum transmembrane pressure required to obtain flux (J). This result is observed as a small shift to the right on J versus transmembrane pressure curves, and this shift increases with the flow velocity. This fact was reported in other investigations, but so far has gone uninvestigated. The JL predicted values were correlated with the Reynolds number (Re) for each dh tested. Results showed that for a same Re; JL increased as dh decreased; in a wide range of Re within the turbulent regime. Finally, from dimensionless correlations; a unique expression JL = f (Re, dh) was obtained; predicting satisfactorily JL (R2 = 84.11%) for the whole set of experiments
Machine Learning Approaches Applied to GC-FID Fatty Acid Profiles to Discriminate Wild from Farmed Salmon
Authors: Grazina Liliana , Rodrigues P. J. , Igrejas Getúlio , Nunes Maria A. , Mafra Isabel , Arlorio Marco , Oliveira M. Beatriz P. P. , Amaral Joana S.
Published: November 2020

In the last decade, there has been an increasing demand for wild-captured fish, which attains higher prices compared to farmed species, thus being prone to mislabeling practices. In this work, fatty acid composition coupled to advanced chemometrics was used to discriminate wild from farmed salmon. The lipids extracted from salmon muscles of different production methods and origins (26 wild from Canada, 25 farmed from Canada, 24 farmed from Chile and 25 farmed from Norway) were analyzed by gas chromatography with flame ionization detector (GC-FID). All the tested chemometric approaches, namely principal components analysis (PCA), t-distributed stochastic neighbor embedding (t-SNE) and seven machine learning classifiers, namely k-nearest neighbors (kNN), decision tree, support vector machine (SVM), random forest, artificial neural networks (ANN), naïve Bayes and AdaBoost, allowed for differentiation between farmed and wild salmons using the 17 features obtained from chemical analysis. PCA did not allow clear distinguishing between salmon geographical origin since farmed samples from Canada and Chile overlapped. Nevertheless, using the 17 features in the models, six out of the seven tested machine learning classifiers allowed a classification accuracy of ≥99%, with ANN, naïve Bayes, random forest, SVM and kNN presenting 100% accuracy on the test dataset. The classification models were also assayed using only the best features selected by a reduction algorithm and the best input features mapped by t-SNE. The classifier kNN provided the best discrimination results because it correctly classified all samples according to production method and origin, ultimately using only the three most important features (16:0, 18:2n6c and 20:3n3 + 20:4n6). In general, the classifiers presented good generalization with the herein proposed approach being simple and presenting the advantage of requiring only common equipment existing in most labs.
Innovations in Smart Packaging Concepts for Food: An Extensive Review
Authors: Drago Emanuela , Campardelli Roberta , Pettinato Margherita , Perego Patrizia
Published: November 2020

Innovation in food packaging is mainly represented by the development of active and intelligent packing technologies, which offer to deliver safer and high-quality food products. Active packaging refers to the incorporation of active component into the package with the aim of maintaining or extending the product quality and shelf-life. The intelligent systems are able to monitor the condition of packaged food in order to provide information about the quality of the product during transportation and storage. These packaging technologies can also work synergistically to yield a multipurpose food packaging system. This review is a critical and up-dated analysis of the results reported in the literature about this fascinating and growing field of research. Several aspects are considered and organized going from the definitions and the regulations, to the specific functions and the technological aspects regarding the manufacturing technologies, in order to have a complete overlook on the overall topic.
Spontaneously Fermented Fruiting Bodies of Agaricus bisporus as a Valuable Source of New Isolates of Lactic Acid Bacteria with Functional Potential
Authors: Skrzypczak Katarzyna , Gustaw Klaudia , Jabłońska-Ryś Ewa , Sławińska Aneta , Gustaw Waldemar , Winiarczyk Stanisław
Published: November 2020

The aim of the investigation was the identification and initial study of lactic acid bacteria (LAB) isolated from spontaneously fermented (at 28 °C for 5 days) fruiting bodies of white button mushrooms (Agaricus bisporus). The isolated LAB were preliminarily characterized applying the MALDI-TOF Biotyper. Moreover, further phenotypical, genotypical characteristics as well as some functional and technological properties of the selected microorganisms (including the ability to produce exopolysaccharides, cell hydrophobicity, resistance to low pH, and bile salt) were also analyzed. Among autochthonous LAB (isolated from the tested mushroom raw material), Leuconostoc mesenteroides predominated in spontaneously fermented A. bisporus, while Lactiplantibacillus paraplantarum, Lactiplantibacillus plantarum, and Lactococcus lactis were less abundant. The highest dynamics of acidification of the mushroom material were exhibited by isolates EK55 and EK4 that, after 24 h of incubation, were able to decrease the pH of the raw material up to 5.06 ± 0.021 and 5.17 ± 0.015, respectively. Furthermore, the analysis of bacterial cell hydrophobicity indicated that the highest values of this parameter were noted for L. plantarum isolates EK12 (29.59 ± 0.7%), EK55 (28.75 ± 0.551%), and EK5 (27.33 ± 1.516%). It was revealed some of the analyzed LAB (especially isolates L. plantarum EK55 and L. paraplantarum EK4) exhibited functional and technological potential that might be used in the formulation of novel starter cultures.
The Evidence-Based Practice Silent Enemy: Retracted Articles and Their Use in Systematic Reviews
Authors: Herrera-Peco Ivan , Santillán-García Azucena , Morán José María , Goodman-Casanova Jessica Marian , Cuesta-Lozano Daniel
Published: November 2020

Today, evidence-based nursing practice strives to improve health care, ensure adherence to treatment, improve health outcomes, and guarantee patient safety. The main scientific documents that nurses should consult, to obtain the best possible evidence, are systematic reviews and meta-analyses. However, this type of scientific document has a major issue if it uses retracted articles that could directly affect the consistency of the results shown in the reviews. The aim of this commentary is to present the current issue represented by the use of retracted articles in meta-analyses of systematic reviews and how researchers could detect them, through the use of different instruments, avoiding them, and providing a reliable SR or meta-analysis that could be useful for day-to-day clinical and research activities.