bluuebunny/crossref_metadata_2025 huggingface dataset:
Impact of Cellulase and Lactic Acid Bacteria Inoculant to Modify Ensiling Characteristics and In Vitro Digestibility of Sweet Corn Stover and Cassava Pulp Silage
Authors: Kaewpila Chatchai , Thip-uten Suwit , Cherdthong Anusorn , Khota Waroon
Published: January 2021

Improving the productive performance of agricultural residue silage has practical relevance to sustaining livestock production. Sweet corn stover (SCS) and cassava pulp (CSVP) are widespread in the tropics as low-cost feed resources. To efficiently prepare SCS and CSVP silage, the impact of adding Acremonium cellulase (AC), Lactobacillus casei strain TH14 inoculant (TH14), and their combination (AC+TH14) on ensiling characteristics, microbial population, chemical compositions, and in vitro digestibility were tested in comparison to control (no additive). After 60 d of ensiling, the pH value and ammonia nitrogen content of silage were lower (p < 0.05) when AC was used as the additive. Compared with other treatments, TH14 provided abundant lactic acid fermentation in silage. All tested additives increased the crude protein (CP) content and decreased the neutral detergent fiber (NDF) content of SCS silage. In CSVP silage, only AC and AC+TH14 altered the CP and NDF content. In addition, AC and AC+TH14 provided greater in vitro dry matter digestibility and a lower in vitro fiber digestibility. Overall, optimized either AC or TH14 can be recommended as an attractive additive to improve the ensiling characteristics of SCS and CSVP silage. AC significantly modifies the in vitro digestibility of silage.
Antiarthritic Potential of Calotropis procera Leaf Fractions in FCA-Induced Arthritic Rats: Involvement of Cellular Inflammatory Mediators and Other Biomarkers
Authors: Singh Vandana S. , Dhawale Shashikant C. , Shakeel Faiyaz , Faiyazuddin Md. , Alshehri Sultan
Published: January 2021

Calotropis procera (commonly known as Swallow wort) is described in the Ayurvedic literature for the treatment of inflammation and arthritic disorders. Therefore, in the present work, the antiarthritic activity of potential fractions of Swallow wort leaf was evaluated and compared with standards (indomethacin and ibuprofen). This study was designed in Wistar rats for the investigation of antiarthritic activity and acute toxicity of Swallow wort. Arthritis was induced in Wistar rats by injecting 0.1 mL of Freund’s complete adjuvant (FCA) on the 1st and 7th days subcutaneously into the subplantar region of the left hind paw. Evaluation of our experimental findings suggested that antiarthritic activity of methanol fraction of Swallow wort (MFCP) was greater than ethyl acetate fraction of Swallow wort (EAFCP), equal to standard ibuprofen, and slightly lower than standard indomethacin. MFCP significantly reduced paw edema on the 17th, 21st, 24th, and 28th days. It also showed significant effect (p < 0.01) on arthritic score, paw withdrawal latency, and body weight. The inhibition of serum lysosomal enzymes and proinflammatory cytokines along with improvement of radiographic features of hind legs was also recorded with MFCP. Finally, it was concluded that MFCP can be a feasible therapeutic candidate for the treatment of inflammatory arthritis.
Mechanical and Acoustic Emission (AE) Characteristics of Rocks under Biaxial Confinements
Authors: Du Kun , Liu Minghui , Yang Chengzhi , Tao Ming , Feng Fukang , Wang Shaofeng
Published: January 2021

The surrounding rocks of underground engineering are generally subjected to a biaxial compressive stress condition. The failure properties of rocks under such a stress condition are worthy of being studied to ensure the stability of surrounding rock. This study aims to investigate the mechanical characteristics and acoustic emission (AE) properties of granite, marble, and sandstone in biaxial compression tests. Under biaxial confinements, it is evident that the elastic moduli of the three types of rocks decrease, and the plasticity increases monotonously with the increase of the intermediate principal stress σ2. As σ2 increases, the biaxial compressive strength σbcs of rock increases initially and subsequently decreases. The lateral strain ε2 of rock under biaxial confinement is controlled by both σ1 and σ2, and the restrain degree in the development of microcracks and the constrain extent in the expansion along the direction of σ2 are both enhanced gradually with increase in σ2. The sharp increase points of AE hit and AE count indicate that the failure will occur soon. The AF-RA distribution of AE signals shows that the increase of σ2 causes more tensile cracks in rock. According to the dip failure angle of macro-cracks in rock under biaxial confinement, the failure modes of granite and marble are slabbing, while failure mode of sandstone is shear. In addition, the σ2 has a positive effect on the mass ratio of large size fragments after rock failure. An exponent relationship between the σbcs and σ2 was found, and the inner apices–inscribed Drucker–Prager criterion can be used to predict the σbcs of rock.
Electron Pumping and Spectral Density Dynamics in Energy-Gapped Topological Chains
Authors: Kurzyna Marcin , Kwapiński Tomasz
Published: January 2021

Electron pumping through energy-gapped systems is restricted for vanishing local density of states at the Fermi level. In this paper, we propose a topological Su–Schrieffer–Heeger (SSH) chain between unbiased leads as an effective electron pump. We analyze the electron transport properties of topologically trivial and nontrivial systems in the presence of external time-dependent forces in the form of one-Gaussian or two-Gaussian perturbations (train impulses). We have found that the topologically trivial chain stands for much better charge pump than other normal or nontrivial chains. It is important that, during the perturbation, electrons are pumped through the mid-gap temporary states or through the induced sidebands states outside the energy gap. We also analyze the local density of states dynamics during the quench transition between different topological phases of the SSH chain. It turns out that after the quench, the edge topological states migrate through other sites and can temporarily exist in a topologically trivial part of the system. The tight-binding Hamiltonian and the evolution operator technique are used in our calculations.
Evaluation of Rice Straw Ash as a Pozzolanic Addition in Cementitious Mixtures
Authors: Hidalgo Samantha , Soriano Lourdes , Monzó José , Payá Jordi , Font Alba , Borrachero Mª Victoria
Published: January 2021

Rice husk ash is one of the most widely studied biomass ashes used in pozzolanic addition. Given its lower silica content, rice straw ash (RSA) has been explored less often, despite the fact that, according to the United Nations Food and Agriculture Organization (FAO), rice straw (RS) production is estimated at 600 million tons/year. In this work, RSA was physically and chemically characterized, and its pozzolanic properties were assessed. A controlled conditioning, burning, homogenization and grinding procedure was carried out to obtain RSA from RS. Chemical composition, insoluble residue, reactive silica, chloride content and particle size distribution were assessed for ash characterization. To determine RSA pozzolanicity, Frattini, electrical conductivity and pH measurements in an aqueous suspension of hydrated CH/RSA mixtures were obtained. Portland cement (PC) mortars with 15% and 30% RSA substitutions evaluated. The mechanical tests showed specimens with a strength activity index up to 90% and 80% with 15% and 30% RSA, respectively, after 3 days, and these values grew to 107–109% after 90 curing days.
The Rotating Liner Engine (RLE) Diesel Prototype: Reducing Internal Engine Friction by about 40% under Idle Conditions
Authors: Dardalis Dimitrios , Basu Amiyo , Hall Matt J. , Mattthews Ronald D.
Published: January 2021

The Rotating Liner Engine (RLE) concept is a design concept for internal combustion engines, where the cylinder liner rotates at a surface speed of 2–4 m/s in order to assist piston ring lubrication. Specifically, we have evidence from prior art and from our own research that the above rotation has the potential to eliminate the metal-to-metal contact/boundary friction that exists close to the piston reversal areas. This frictional source becomes a significant energy loss, especially in the compression/expansion part of the cycle, when the gas pressure that loads the piston rings and skirts is high. This paper describes the Diesel RLE prototype constructed from a Cummins 4BT and the preliminary observations from initial low load testing. The critical technical challenge, namely the rotating liner face seal, appears to be operating with negligible gas leakage and within the hydrodynamic lubrication regime for the loads tested (peak cylinder pressures of the order of 100 bar) and up to about 10 bar BMEP (brake mean effective pressure). Preliminary testing has proven that the metal-to-metal contact in the piston assembly mostly vanished, and a friction reduction at idle conditions of about 40% as extrapolated to a complete engine has taken place. It is expected that as the speed increases, the friction reduction percentage will diminish, but as the load increases, the friction reduction will increase. The fuel economy benefit over the US Heavy-Duty driving cycle will likely be of the order of 10% compared to a standard engine.
Integrating Dilated Convolution into DenseLSTM for Audio Source Separation
Authors: Heo Woon-Haeng , Kim Hyemi , Kwon Oh-Wook
Published: January 2021

Herein, we proposed a multi-scale multi-band dilated time-frequency densely connected convolutional network (DenseNet) with long short-term memory (LSTM) for audio source separation. Because the spectrogram of the acoustic signal can be thought of as images as well as time series data, it is suitable for convolutional recurrent neural network (CRNN) architecture. We improved the audio source separation performance by applying the dilated block with a dilated convolution to CRNN architecture. The dilated block has the role of effectively increasing the receptive field in the spectrogram. In addition, it was designed in consideration of the acoustic characteristics that the frequency axis and the time axis in the spectrogram are changed by independent influences such as speech rate and pitch. In speech enhancement experiments, we estimated the speech signal using various deep learning architectures from a signal in which the music, noise, and speech were mixed. We conducted the subjective evaluation on the estimated speech signal. In addition, speech quality, intelligibility, separation, and speech recognition performance were also measured. In music signal separation, we estimated the music signal using several deep learning architectures from the mixture of the music and speech signal. After that, the separation performance and music identification accuracy were measured using the estimated music signal. Overall, the proposed architecture shows the best performance compared to other deep learning architectures not only in speech experiments but also in music experiments.
Impact of Dataset Size on Classification Performance: An Empirical Evaluation in the Medical Domain
Authors: Althnian Alhanoof , AlSaeed Duaa , Al-Baity Heyam , Samha Amani , Dris Alanoud Bin , Alzakari Najla , Abou Elwafa Afnan , Kurdi Heba
Published: January 2021

Dataset size is considered a major concern in the medical domain, where lack of data is a common occurrence. This study aims to investigate the impact of dataset size on the overall performance of supervised classification models. We examined the performance of six widely-used models in the medical field, including support vector machine (SVM), neural networks (NN), C4.5 decision tree (DT), random forest (RF), adaboost (AB), and naïve Bayes (NB) on eighteen small medical UCI datasets. We further implemented three dataset size reduction scenarios on two large datasets and analyze the performance of the models when trained on each resulting dataset with respect to accuracy, precision, recall, f-score, specificity, and area under the ROC curve (AUC). Our results indicated that the overall performance of classifiers depend on how much a dataset represents the original distribution rather than its size. Moreover, we found that the most robust model for limited medical data is AB and NB, followed by SVM, and then RF and NN, while the least robust model is DT. Furthermore, an interesting observation is that a robust machine learning model to limited dataset does not necessary imply that it provides the best performance compared to other models.
An AIS Data-Driven Approach to Analyze the Pattern of Ship Trajectories in Ports Using the DBSCAN Algorithm
Authors: Lee Hyeong-Tak , Lee Jeong-Seok , Yang Hyun , Cho Ik-Soon
Published: January 2021

As the maritime industry enters the era of maritime autonomous surface ships, research into artificial intelligence based on maritime data is being actively conducted, and the advantages of profitability and the prevention of human error are being emphasized. However, although many studies have been conducted relating to oceanic operations by ships, few have addressed maneuvering in ports. Therefore, in an effort to resolve this issue, this study explores ship trajectories derived from automatic identification systems’ data collected from ships arriving in and departing from the Busan New Port in South Korea. The collected data were analyzed by dividing them into port arrival and departure categories. To analyze ship trajectory patterns, the density-based spatial clustering of applications with noise (DBSCAN) algorithm, a machine learning clustering method, was employed. As a result, in the case of arrival, seven clusters, including the leg and turning section, were derived, and departure was classified into six clusters. The clusters were then divided into four phases and a pattern analysis was conducted for speed over ground, course over ground, and ship position. The results of this study could be used to develop new port maneuvering guidelines for ships and represent a significant contribution to the maneuvering practices of autonomous ships in port.
Performance of Wild Non-Conventional Yeasts in Fermentation of Wort Based on Different Malt Extracts to Select Novel Starters for Low-Alcohol Beers
Authors: Capece Angela , De Fusco Deborah , Pietrafesa Rocchina , Siesto Gabriella , Romano Patrizia
Published: January 2021

Nowadays, the increasing interest in new market demand for alcoholic beverages has stimulated the research on useful strategies to reduce the ethanol content in beer. In this context, the use of non-Saccharomyces yeasts to produce low-alcohol or alcohol-free beer may provide an innovative approach for the beer market. In our study, four wild non-Saccharomyces yeasts, belonging to Torulaspora delbrueckii, Candida zemplinina and Zygosaccharomyces bailii species, were tested in mixed fermentation with a wild selected Saccharomyces cerevisiae strain as starters for fermentation of different commercial substrates used for production of different beer styles (Pilsner, Weizen and Amber) to evaluate the influence of the fermentative medium on starter behaviour. The results obtained showed the influence of non-Saccharomyces strains on the ethanol content and organoleptic quality of the final beers and a significant wort–starter interaction. In particular, each starter showed a different sugar utilization rate in each substrate, in consequence of uptake efficiency correlated to the strain-specific metabolic pathway and substrate composition. The most suitable mixed starter was P4-CZ3 (S. cerevisiae–C. zemplinina), which is a promising starter for the production of low-alcohol beers with pleasant organoleptic characteristics in all the tested fermentation media.
Role of the Binding Motifs in the Energy Level Alignment and Conductance of Amine-Gold Linked Molecular Junctions within DFT and DFT + Σ
Authors: Montes Enrique , Vázquez Héctor
Published: January 2021

We investigate, using density functional theory (DFT), the electronic and conducting properties of benzenediamine connected to gold electrodes via different tip structures. We examine a series of binding motifs to the electrodes and calculate the junction spectral properties. We consider corrections to the position of molecular resonances at the junction and discuss different approaches to the calculation of these shifts. We relate the magnitude of these corrections to resonance energies to the atomistic structure of the tip. Benzenediamine DFT-based transmission spectra can be well approximated by a Lorentzian model involving only the highest occupied molecular orbital (HOMO). We show how benzenediamine calculated conductance values in quantitative agreement with previous experiments can be achieved from the combination of DFT-based spectra and corrections to the DFT-based HOMO energy and an accessible Lorentzian model.
Metabolic Signatures of Cryptosporidium parvum-Infected HCT-8 Cells and Impact of Selected Metabolic Inhibitors on C. parvum Infection under Physioxia and Hyperoxia
Authors: Vélez Juan , Velasquez Zahady , Silva Liliana M. R. , Gärtner Ulrich , Failing Klaus , Daugschies Arwid , Mazurek Sybille , Hermosilla Carlos , Taubert Anja
Published: January 2021

Cryptosporidium parvum is an apicomplexan zoonotic parasite recognized as the second leading-cause of diarrhoea-induced mortality in children. In contrast to other apicomplexans, C.parvum has minimalistic metabolic capacities which are almost exclusively based on glycolysis. Consequently, C. parvum is highly dependent on its host cell metabolism. In vivo (within the intestine) infected epithelial host cells are typically exposed to low oxygen pressure (1–11% O2, termed physioxia). Here, we comparatively analyzed the metabolic signatures of C. parvum-infected HCT-8 cells cultured under both, hyperoxia (21% O2), representing the standard oxygen condition used in most experimental settings, and physioxia (5% O2), to be closer to the in vivo situation. The most pronounced effect of C. parvum infection on host cell metabolism was, on one side, an increase in glucose and glutamine uptake, and on the other side, an increase in lactate release. When cultured in a glutamine-deficient medium, C. parvum infection led to a massive increase in glucose consumption and lactate production. Together, these results point to the important role of both glycolysis and glutaminolysis during C. parvum intracellular replication. Referring to obtained metabolic signatures, we targeted glycolysis as well as glutaminolysis in C. parvum-infected host cells by using the inhibitors lonidamine [inhibitor of hexokinase, mitochondrial carrier protein (MCP) and monocarboxylate transporters (MCT) 1, 2, 4], galloflavin (lactate dehydrogenase inhibitor), syrosingopine (MCT1- and MCT4 inhibitor) and compound 968 (glutaminase inhibitor) under hyperoxic and physioxic conditions. In line with metabolic signatures, all inhibitors significantly reduced parasite replication under both oxygen conditions, thereby proving both energy-related metabolic pathways, glycolysis and glutaminolysis, but also lactate export mechanisms via MCTs as pivotal for C. parvum under in vivo physioxic conditions of mammals.
Catalytic Hydrogenation and Dehydrogenation Reactions of N-alkyl-bis(carbazole)-Based Hydrogen Storage Materials
Authors: Jung Joori , Shin Byeong Soo , Kang Jeong Won , Han Won-Sik
Published: January 2021

Recently, there have been numerous efforts to develop hydrogen-rich organic materials because hydrogen energy is emerging as a renewable energy source. In this regard, we designed and prepared four new materials based on N-alkyl-bis(carbazole), 9,9′-(2-methylpropane-1,3-diyl)bis(9H-carbazole) (MBC), 9,9′-(2-ethylpropane-1,3-diyl)bis(9H-carbazole) (EBC), 9,9′-(2-propylpropane-1,3-diyl)bis(9H-carbazole) (PBC), and 9,9′-(2-butylpropane-1,3-diyl)bis(9H-carbazole) (BBC), to investigate their hydrogen adsorption/hydrogen desorption reactivity depending on the length of the alkyl chain. The gravimetric densities of MBC, EBC, PBC, and BBC were 5.86, 5.76, 5.49, and 5.31 H2 wt %, respectively, again depending on the alkyl chain length. All materials showed complete hydrogenation reactions under ruthenium on an alumina catalyst at 190 °C, and complete reverse reactions and dehydrogenation reactions were observed under palladium on an alumina catalyst at <280 °C. At this temperature, all the prepared compounds were thermally stable, and no decomposition was observed.
Cardiac MRI and Myocardial Injury in COVID-19: Diagnosis, Risk Stratification and Prognosis
Authors: Sanghvi Saagar K. , Schwarzman Logan S. , Nazir Noreen T.
Published: January 2021

Myocardial injury is a common complication of the COVID-19 illness and is associated with a worsened prognosis. Systemic hyperinflammation seen in the advanced stage of COVID-19 likely contributes to myocardial injury. Cardiac magnetic resonance imaging (CMR) is the preferred imaging modality for non-invasive evaluation in acute myocarditis, enabling risk stratification and prognostication. Modified scanning protocols in the pandemic setting reduce risk of exposure while providing critical data regarding cardiac tissue inflammation and fibrosis, chamber remodeling, and contractile function. The growing use of CMR in clinical practice to assess myocardial injury will improve understanding of the acute and chronic sequelae of myocardial inflammation from various pathological etiologies.
Changes in Students’ Achievement Motivation in the Context of the COVID-19 Pandemic: A Function of Extraversion/Introversion?
Authors: Smith Jonathan , Guimond Fanny-Alexandra , Bergeron Julie , St-Amand Jérôme , Fitzpatrick Caroline , Gagnon Mathieu
Published: January 2021

Students’ mental health has been an increased concern since the outbreak of the COVID-19 pandemic. However, academic outcomes have received very little attention. In this study, changes in students’ achievement motivation are investigated using an expectancy–value framework. Participants (n = 90) were high school students (grades 9 and 10) who reported on their expectancy and value perceptions in regard to learning before and during the pandemic (i.e., January and November 2020). Changes over time and as a function of extraversion/introversion were analyzed using repeated measures multivariate analyses of variance (MANOVAs). Most perceptions were found to be stable with the exception of interest in learning, which increased as a function of extraversion. Results are discussed in light of relevant pre-pandemic evidence.
A Fast Lock All-Digital MDLL Using a Cyclic Vernier TDC for Burst-Mode Links
Authors: Park Dongjun , Choi Sungwook , Kim Jongsun
Published: January 2021

An all-digital multiplying delay-locked loop (MDLL)-based clock multiplier featuring a time-to-digital converter (TDC) to achieve fast power-on capability is presented. The proposed MDLL adopts a new offset-free cyclic Vernier TDC to achieve a fast lock time of 15 reference clock cycles while maintaining a wide detection range and high resolution. The proposed offset-free TDC also uses a correlated double sampling technique to remove mismatch and offset issues, resulting in low jitter characteristics. After the MDLL is quickly locked, the TDC is turned off, and it goes into delta-sigma modulator (DSM)-based sequential tracking mode to reduce power consumption and improve jitter performance. Implemented in a 65-nm 1.0-V CMOS process, the proposed MDLL occupies an active area of 0.043 mm2 and generates a 2.4-GHz output clock from a 75-MHz reference clock (multiplication factor N = 32). It achieves an effective peak-to-peak jitter of 9.4 ps and consumes 3.3 mW at 2.4 GHz.
Empirical Analysis of Rank Aggregation-Based Multi-Filter Feature Selection Methods in Software Defect Prediction
Authors: Balogun Abdullateef O. , Basri Shuib , Mahamad Saipunidzam , Abdulkadir Said Jadid , Capretz Luiz Fernando , Imam Abdullahi A. , Almomani Malek A. , Adeyemo Victor E. , Kumar Ganesh
Published: January 2021

Selecting the most suitable filter method that will produce a subset of features with the best performance remains an open problem that is known as filter rank selection problem. A viable solution to this problem is to independently apply a mixture of filter methods and evaluate the results. This study proposes novel rank aggregation-based multi-filter feature selection (FS) methods to address high dimensionality and filter rank selection problem in software defect prediction (SDP). The proposed methods combine rank lists generated by individual filter methods using rank aggregation mechanisms into a single aggregated rank list. The proposed methods aim to resolve the filter selection problem by using multiple filter methods of diverse computational characteristics to produce a dis-joint and complete feature rank list superior to individual filter rank methods. The effectiveness of the proposed method was evaluated with Decision Tree (DT) and Naïve Bayes (NB) models on defect datasets from NASA repository. From the experimental results, the proposed methods had a superior impact (positive) on prediction performances of NB and DT models than other experimented FS methods. This makes the combination of filter rank methods a viable solution to filter rank selection problem and enhancement of prediction models in SDP.
On-Line Learning and Updating Unmanned Tracked Vehicle Dynamics
Authors: Strawa Natalia , Ignatyev Dmitry I. , Zolotas Argyrios C. , Tsourdos Antonios
Published: January 2021

Increasing levels of autonomy impose more pronounced performance requirements for unmanned ground vehicles (UGV). Presence of model uncertainties significantly reduces a ground vehicle performance when the vehicle is traversing an unknown terrain or the vehicle inertial parameters vary due to a mission schedule or external disturbances. A comprehensive mathematical model of a skid steering tracked vehicle is presented in this paper and used to design a control law. Analysis of the controller under model uncertainties in inertial parameters and in the vehicle-terrain interaction revealed undesirable behavior, such as controller divergence and offset from the desired trajectory. A compound identification scheme utilizing an exponential forgetting recursive least square, generalized Newton–Raphson (NR), and Unscented Kalman Filter methods is proposed to estimate the model parameters, such as the vehicle mass and inertia, as well as parameters of the vehicle-terrain interaction, such as slip, resistance coefficients, cohesion, and shear deformation modulus on-line. The proposed identification scheme facilitates adaptive capability for the control system, improves tracking performance and contributes to an adaptive path and trajectory planning framework, which is essential for future autonomous ground vehicle missions.
Design of Multi Standard Near Field Communication Outphasing Transmitter with Modulation Wave Shaping
Authors: Korošak Žiga , Suhadolnik Nejc , Pleteršek Anton
Published: January 2021

The aim of this work is to tackle the problem of modulation wave shaping in the field of near field communication (NFC) radio frequency identification (RFID). For this purpose, a high-efficiency transmitter circuit was developed to comply with the strict requirements of the newest EMVCo and NFC Forum specifications for pulse shapes. The proposed circuit uses an outphasing modulator that is based on a digital-to-time converter (DTC). The DTC based outphasing modulator supports amplitude shift keying (ASK) modulation, operates at four times the 13.56 MHz carrier frequency and is made fully differential in order to remove the parasitic phase modulation components. The accompanying transmitter logic includes lookup tables with programmable modulation pulse wave shapes. The modulator solution uses a 64-cell tapped current controlled fully differential delay locked loop (DLL), which produces a 360° delay at 54.24 MHz, and a glitch-free multiplexor to select the individual taps. The outphased output from the modulator is mixed to create an RF pulse width modulated (PWM) output, which drives the antenna. Additionally, this implementation is fully compatible with D-class amplifiers enabling high efficiency. A test circuit of the proposed differential multi-standard reader’s transmitter was simulated in 40 nm CMOS technology. Stricter pulse shape requirements were easily satisfied, while achieving an output linearity of 0.2 bits and maximum power consumption under 7.5 mW.
Multi-Objective Optimization of Joint Power and Admission Control in Cognitive Radio Networks Using Enhanced Swarm Intelligence
Authors: El-Saleh Ayman A. , Shami Tareq M. , Nordin Rosdiadee , Alias Mohamad Y. , Shayea Ibraheem
Published: January 2021

The problem of joint power and admission control (JPAC) is a critical issue encountered in underlay cognitive radio networks (CRNs). Moving forward towards the realization of Fifth Generation (5G) and beyond, where optimization is envisioned to take place in multiple performance dimensions, it is crucially desirable to achieve high sum throughput with low power consumption. In this work, a multi-objective JPAC optimization problem that jointly maximizes the sum throughput and minimizes power consumption in underlay CRNs is formulated. An enhanced swarm intelligence algorithm has been developed by hybridizing two new enhanced Particle Swarm Optimization (PSO) variants, namely two-phase PSO (TPPSO) and diversity global position binary PSO (DGP-BPSO) variants employed to optimize the multi-objective JPAC problem. The performance of the enhanced swarm intelligence algorithm in terms of convergence speed and stability, while optimizing both the sum throughput and power consumption, is investigated under three different operational scenarios defined by their single objective priorities, which translate to sum throughput and power consumption preferences. Simulation results have proven the effectiveness of the enhanced swarm intelligence algorithm in achieving high sum throughput and low power consumption under the three operational scenarios when the network includes an arbitrary number of primary and secondary users. Comparing the hybrid SPSO approach and the proposed approach, the proposed scheme has shown its effectiveness in increasing the sum throughput to 7%, 16%, and 31% under the multimedia, balanced and power saving operational scenarios, respectively. In addition, the proposed approach is more power efficient as it can provide additional power savings of 3.58 W, 2.48 W, and 1.6741 W under the aforementioned operational scenarios, respectively.
An Efficient Indexing Scheme for Network Traffic Collection and Retrieval System
Authors: Jiang Chao , Wang Jinlin , Li Yang
Published: January 2021

Historical network traffic retrieval, both at the packet and flow level, has been applied in many fields of network security, such as network traffic analysis and network forensics. To retrieve specific packets from a vast number of packet traces, it is an effective solution to build indexes for the query attributes. However, it brings challenges of storage consumption and construction time overhead for packet indexing. To address these challenges, we propose an efficient indexing scheme called IndexWM based on the wavelet matrix data structure for packet indexing. Moreover, we design a packet storage format based on the PcapNG format for our network traffic collection and retrieval system, which can speed up the extraction of index data from packet traces. Offline experiments on randomly generated network traffic and actual network traffic are performed to evaluate the performance of the proposed indexing scheme. We choose an open-source and widely used bitmap indexing scheme, FastBit, for comparison. Apart from the native bitmap compression method Word-Aligned Hybrid (WAH), we implement an efficient bitmap compression method Scope-Extended COMPAX (SECOMPAX) in FastBit for performance evaluation. The comparison results show that our scheme outperforms the selected bitmap indexing schemes in terms of time consumption, storage consumption and retrieval efficiency.
RCVC: RSU-Aided Cluster-Based Vehicular Clouds Architecture for Urban Areas
Authors: Ben bezziane Mohamed , Korichi Ahmed , Kerrache Chaker Abdelaziz , Fekair Mohamed el Amine
Published: January 2021

As a promising topic of research, Vehicular Cloud (VC) incorporates cloud computing and ad-hoc vehicular network (VANET). In VC, supplier vehicles provide their services to consumer vehicles in real-time. These services have a significant impact on the applications of internet access, storage and data. Due to the high-speed mobility of vehicles, users in consumer vehicles need a mechanism to discover services in their vicinity. Besides this, quality of service varies from one supplier vehicle to another; thus, consumer vehicles attempt to pick out the most appropriate services. In this paper, we propose a novel protocol named RSU-aided Cluster-based Vehicular Clouds protocol (RCVC), which constructs the VC using the Road Side Unit (RSU) directory and Cluster Head (CH) directory to make the resources of supplier vehicles more visible. While clusters of vehicles that move on the same road form a mobile cloud, the remaining vehicles form a different cloud on the road side unit. Furthermore, the consumption operation is achieved via the service selection method, which is managed by the CHs and RSUs based on a mathematical model to select the best services. Simulation results prove the effectiveness of our protocol in terms of service discovery and end-to-end delay, where we achieved service discovery and end-to-end delay of 3 × 10−3 s and 13 × 10−2 s, respectively. Moreover, we carried out an experimental comparison, revealing that the proposed method outperformed several states of the art protocols.
Vibration-Based Monitoring of Wind Turbines: Influence of Layout and Noise of Sensors
Authors: Pacheco João , Oliveira Gustavo , Magalhães Filipe , Moutinho Carlos , Cunha Álvaro
Published: January 2021

The reduction in operating and maintenance costs of wind farms is a fundamental element to guarantee the competitiveness and growth of the wind market. Wind turbines are highly dynamic structures prone to wear during their lifetime. Therefore, dynamic monitoring systems represent an excellent option to continuously evaluate their structural conditions. These systems allow early detection of damages, permit a proactive response, minimising downtime, and maximising productivity. In this context, the present paper describes the main results obtained with alternative instrumentation strategies tested in a 2.0 MW onshore wind turbine to reduce the costs of the monitoring equipment and at the same time ensure an adequate accuracy in structural condition evaluation. The data processing strategy encompasses the use of operational modal analysis combined with algorithms that deal with the particularities of operation of the wind turbines to continuously track the main vibration modes. After this automated online identification, the influence of the environmental and operating conditions on the tracked natural frequencies is mitigated, making the detection of abnormal variations of the natural frequencies possible, which might flag the appearance of damage. A database of continuously collected acceleration time series during one year is adopted to test the efficiency of alternative monitoring system layouts in detecting simulated damage scenarios. The tested alternative monitoring layouts present a varying number of sensors, alternative distributions in the wind turbine tower, and different sensor noise levels.
Coupled Thermo–Hydro–Mechanical–Seismic Modeling of EGS Collab Experiment 1
Authors: Lu Jianrong , Ghassemi Ahmad
Published: January 2021

An important technical issue in the enhanced geothermal system (EGS) is the process of fracture shear and dilation, fracture network propagation and induced seismicity. EGS development requires an ability to reliably predict the fracture network’s permeability evolution. Laboratory and field studies such as EGS Collab and Utah FORGE, and modeling simulations provide valuable lessons for successful commercial EGS design. In this work we present a modeling analysis of EGS Collab Testbed Experiment 1 (May 24, Stim-II ≅ 164 Notch) and interpret the stimulation results in relation to the creation of a fracture network. In doing so, we use an improved 3D discrete fracture network model coupled with a 3D thermo-poroelastic finite element model (FEM) which can consider fracture network evolution and induced seismicity. A dual-scale semi-deterministic fracture network is generated by combining data from image logs, foliations/micro-fractures, and core. The natural fracture properties (e.g., length and asperity) follow a stochastic distribution. The fracture network propagation under injection is considered by an ultrafast analytical approach. This coupled method allows for multiple seismic events to occur on and around a natural fracture. The uncertainties of seismic event clouds are better constrained using the energy conservation law. Numerical simulations show that the simulated fracture pressure profiles reasonably follow the trend observed in the field test. The simulations support the concept that a natural fracture was propagated from the injection well connecting with the production well via intersection and coalescence with other natural fractures consistent with plausible flow paths observed on the field. The fracture propagation profiles from numerical modeling generally match the field observation. The distribution of simulated micro-seismicity have good agreement with the field-observed data.
The Importance of Local Investments Co-Financed by the European Union in the Field of Renewable Energy Sources in Rural Areas of Poland
Authors: Standar Aldona , Kozera Agnieszka , Satoła Łukasz
Published: January 2021

Local investments for the development of renewable energy sources (RESs) constitute an important element of sustainable rural development. They are conducive to the social and economic development of the said areas, and improve the environmental values and living conditions of their inhabitants. However, such advancement in rural areas is not possible without adequate financial support, including the funds from the EU budget. Therefore, the main objective of the research is to assess the scale, scope and importance of local investments in renewable energy sources in rural areas of Poland in 2014–2020, cofinanced from EU funds. The study covered 1117 projects, whose beneficiaries were rural and urban–rural municipalities. Evaluation of the municipal investment activities in acquiring EU subsidies in the area of environmentally friendly energy was conducted using selected methods of descriptive statistics and the analysis of variance. Subsequently, with the use of logistic regression, the study identified the main socioeconomic, financial and environmental conditions of the investment activities of the local government entities in RES in rural areas. Empirical studies allowed for the positive verification of the research hypothesis, which assumed that “The highest investment activity in the field of local projects co-financed from EU funds, related to the development of RES in rural areas, may be attributed to municipalities performing primarily agricultural functions, located in Eastern Poland”. The municipalities’ own income potential and investment activity are of major importance for the acquisition of EU funds used in RES financing. Municipalities at a lower development level demonstrated a greater activity in accessing these funds. They view the development of RES as an opportunity for accelerated growth.
Non-Destructive Lumber and Engineered Pine Products Research in the Gulf South U.S. 2005–2020
Authors: Seale R. Dan , Shmulsky Rubin , Jose Nistal Franca Frederico
Published: January 2021

This review primarily describes nondestructive evaluation (NDE) work at Mississippi State University during the 2005–2020 time interval. Overall, NDE is becoming increasingly important as a means of maximizing and optimizing the value (economic, engineering, utilitarian, etc.) of every tree that comes from the forest. For the most part, it focuses on southern pine structural lumber, but other species such as red pine, spruce, Douglas fir, red oak, and white oak and other products such as engineered composites, mass timber, non-structural lumber, and others are included where appropriate. Much of the work has been completed in conjunction with the U.S. Department of Agriculture, Forest Service, Forest Products Laboratory as well as the Agricultural Research Service with the overall intent of improving lumber and wood products standards and valuation. To increase the future impacts and adoption of this NDE-related work, wherever possible graduate students have contributed to the research. As such, a stream of trained professionals is a secondary output of these works though it is not specifically detailed herein.
Evaluating the Anti-Inflammatory and Antioxidant Effects of Broccoli Treated with High Hydrostatic Pressure in Cell Models
Authors: Ke Yi-Yuan , Shyu Yuan-Tay , Wu Sz-Jie
Published: January 2021

Isothiocyanates (ITCs) are important functional components of cruciferous vegetables. The principal isothiocyanate molecule in broccoli is sulforaphane (SFN), followed by erucin (ERN). They are sensitive to changes in temperature, especially high temperature environments where they are prone to degradation. The present study investigates the effects of high hydrostatic pressure on isothiocyanate content, myrosinase activity, and other functional components of broccoli, and evaluates its anti-inflammatory and antioxidant effects. Broccoli samples were treated with different pressures and for varying treatment times; 15 min at 400 MPa generated the highest amounts of isothiocyanates. The content of flavonoids and vitamin C were not affected by the high-pressure processing strategy, whereas total phenolic content (TPC) exhibited an increasing tendency with increasing pressure, indicating that high-pressure processing effectively prevents the loss of the heat-sensitive components and enhances the nutritional content. The activity of myrosinase (MYR) increased after high-pressure processing, indicating that the increase in isothiocyanate content is related to the stimulation of myrosinase activity by high-pressure processing. In other key enzymes, the ascorbate peroxidase (APX) activity was unaffected by high pressure, whereas peroxidase (POD) and polyphenol oxidase (PPO) activity exhibited a 1.54-fold increase after high-pressure processing, indicating that high pressures can effectively destroy oxidases and maintain food quality. With regards to efficacy evaluation, NO production was inhibited and the expression levels of inducible nitric oxide synthase (iNOS) and Cyclooxygenase-2 (COX-2) were decreased in broccoli treated with high pressures, whereas the cell viability remained unaffected. The efficacy was more significant when the concentration of SFN was 60 mg·mL−1. In addition, at 10 mg·mL−1 SFN, the reduced/oxidized glutathione (GSH/GSSG) ratio in inflammatory macrophages increased from 5.99 to 9.41. In conclusion, high-pressure processing can increase the isothiocyanate content in broccoli, and has anti-inflammatory and anti-oxidant effects in cell-based evaluation strategies, providing a potential treatment strategy for raw materials or additives used in healthy foods.
Biochemical and Behavioral Consequences of Ethanol Intake in a Mouse Model of Metabolic Syndrome
Authors: Baliño Pablo , Romero-Cano Ricard , Muriach María
Published: January 2021

Ethanol abuse is a common issue in individuals with sedentary lifestyles, unbalanced diets, and metabolic syndrome. Both ethanol abuse and metabolic syndrome have negative impacts on the central nervous system, with effects including cognitive impairment and brain oxidative status deterioration. The combined effects of ethanol abuse and metabolic syndrome at a central level have not yet been elucidated in detail. Thus, this work aims to determine the effects of ethanol intake on a mouse model of metabolic syndrome at the behavioral and biochemical levels. Seven-week-old male control (B6.V-Lep ob/+JRj) and leptin-deficient (metabolic syndrome) (B6.V-Lep ob/obJRj) mice were used in the study. Animals were divided into four groups: control, ethanol, obese, and obese–ethanol. Ethanol consumption was monitored for 6 weeks. Basal glycemia, insulin, and glucose overload tests were performed. To assess short- and long-term memory, an object recognition test was used. In order to assess oxidative status in mouse brain samples, antioxidant enzyme activity was analyzed with regard to glutathione peroxidase, glutathione reductase, glutathione, glutathione disulfide, lipid peroxidation products, and malondialdehyde. Ethanol intake modulated the insulin response and impaired the oxidative status in the ob mouse brain.
Neuroprotective Effect of Vascular Endothelial Growth Factor on Motoneurons of the Oculomotor System
Authors: Silva-Hucha Silvia , Pastor Angel M. , Morcuende Sara
Published: January 2021

Vascular endothelial growth factor (VEGF) was initially characterized as a potent angiogenic factor based on its activity on the vascular system. However, it is now well established that VEGF also plays a crucial role as a neuroprotective factor in the nervous system. A deficit of VEGF has been related to motoneuronal degeneration, such as that occurring in amyotrophic lateral sclerosis (ALS). Strikingly, motoneurons of the oculomotor system show lesser vulnerability to neurodegeneration in ALS compared to other motoneurons. These motoneurons presented higher amounts of VEGF and its receptor Flk-1 than other brainstem pools. That higher VEGF level could be due to an enhanced retrograde input from their target muscles, but it can also be produced by the motoneurons themselves and act in an autocrine way. By contrast, VEGF’s paracrine supply from the vicinity cells, such as glial cells, seems to represent a minor source of VEGF for brainstem motoneurons. In addition, ocular motoneurons experiment an increase in VEGF and Flk-1 level in response to axotomy, not observed in facial or hypoglossal motoneurons. Therefore, in this review, we summarize the differences in VEGF availability that could contribute to the higher resistance of extraocular motoneurons to injury and neurodegenerative diseases.
Transcriptional Regulation of PIK3CD and PIKFYVE in T-Cell Acute Lymphoblastic Leukemia by IKAROS and Protein Kinase CK2
Authors: Dovat Elanora , Song Chunhua , Hu Tommy , Rahman Mohammad Atiqur , Dhanyamraju Pavan Kumar , Klink Morgann , Bogush Daniel , Soliman Mario , Kane Shriya , McGrath Mary , Ding Yali , Desai Dhimant , Sharma Arati , Gowda Chandrika
Published: January 2021

IKAROS, encoded by the IKZF1 gene, is a DNA-binding protein that functions as a tumor suppressor in T cell acute lymphoblastic leukemia (T-ALL). Recent studies have identified IKAROS’s novel function in the epigenetic regulation of gene expression in T-ALL and uncovered many genes that are likely to be directly regulated by IKAROS. Here, we report the transcriptional regulation of two genes, phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit delta (PIK3CD) and phosphoinositide kinase, FYVE-type zinc finger containing (PIKFYVE), by IKAROS in T-ALL. PIK3CD encodes the protein p110δ subunit of phosphoinositide 3-kinase (PI3K). The PI3K/AKT pathway is frequently dysregulated in cancers, including T-ALL. IKAROS binds to the promoter regions of PIK3CD and PIKFYVE and reduces their transcription in primary T-ALL. Functional analysis demonstrates that IKAROS functions as a transcriptional repressor of both PIK3CD and PIKFYVE. Protein kinase CK2 (CK2) is a pro-oncogenic kinase that is overexpressed in T-ALL. CK2 phosphorylates IKAROS, impairs IKAROS’s DNA-binding ability, and functions as a repressor of PIK3CD and PIKFYVE. CK2 inhibition results in increased IKAROS binding to the promoters of PIK3CD and PIKFYVE and the transcriptional repression of both these genes. Overall, the presented data demonstrate for the first time that in T-ALL, CK2 hyperactivity contributes to PI3K signaling pathway upregulation, at least in part, through impaired IKAROS transcriptional regulation of PIK3CD and PIKFYVE. Targeting CK2 restores IKAROS’s regulatory effects on the PI3K oncogenic signaling pathway.