bluuebunny/crossref_metadata_2025 huggingface dataset:
Potential Application of Genomic Technologies in Breeding for Fungal and Oomycete Disease Resistance in Pea
Authors: Jha Ambuj B. , Gali Krishna K. , Alam Zobayer , Lachagari V. B. Reddy , Warkentin Thomas D.
Published: June 2021

Growth and yield of pea crops are severely affected by various fungal diseases, including root rot, Ascochyta blight, powdery mildew, and rust, in different parts of the world. Conventional breeding methods have led to enhancement of host plant resistance against these diseases in adapted cultivars, which is the primary option to minimize the yield losses. To support the breeding programs for marker-assisted selection, several successful attempts have been made to detect the genetic loci associated with disease resistance, based on SSR and SNP markers. In recent years, advances in next-generation sequencing platforms, and resulting improvements in high-throughput and economical genotyping methods, have been used to make rapid progress in identification of these loci. The first reference genome sequence of pea was published in 2019 and provides insights on the distribution and architecture of gene families associated with disease resistance. Furthermore, the genome sequence is a resource for anchoring genetic linkage maps, markers identified in multiple studies, identification of candidate genes, and functional genomics studies. The available pea genomic resources and the potential application of genomic technologies for development of disease-resistant cultivars with improved agronomic profile will be discussed, along with the current status of the arising improved pea germplasm.
Evaluation of Microalgae Antiviral Activity and Their Bioactive Compounds
Authors: Carbone Dora Allegra , Pellone Paola , Lubritto Carmine , Ciniglia Claudia
Published: June 2021

During the last year, science has been focusing on the research of antivirally active compounds overall after the SARS-CoV-2 pandemic, which caused a great amount of deaths and the downfall of the economy in 2020. Photosynthetic organisms such as microalgae are known to be a reservoir of bioactive secondary metabolites; this feature, coupled with the possibility of achieving very high biomass levels without excessive energetic expenses, make microalgae worthy of attention in the search for new molecules with antiviral effects. In this work, the antiviral effects of microalgae against some common human or animal viruses were considered, focusing our attention on some possible effects against SARS-CoV-2. We summed up the data from the literature on microalgae antiviral compounds, from the most common ones, such as lectins, polysaccharides and photosynthetic pigments, to the less known ones, such as unidentified proteins. We have discussed the effects of a microalgae-based genetic engineering approach against some viral diseases. We have illustrated the potential antiviral benefits of a diet enriched in microalgae.
GABA Regulates Phenolics Accumulation in Soybean Sprouts under NaCl Stress
Authors: Zhao Yunyun , Xie Chong , Wang Pei , Gu Zhenxin , Yang Runqiang
Published: June 2021

NaCl stress causes oxidative stress in plants; γ-aminobutyric acid (GABA) could alleviate such abiotic stress by enhancing the synthesis of phenolics, but the underlying mechanism is not clear. We investigated the effects of GABA on phenolics accumulation in soybean sprouts under NaCl stress by measuring changes in the content of physiological biochemicals and phenolic substances, in the activity and gene expression of key enzymes, and in antioxidant capacity. GABA reduced the oxidative damage in soybean sprouts caused by NaCl stress and enhanced the content of total phenolics, phenolic acids, and isoflavones by 16.58%, 22.47%, and 3.75%, respectively. It also increased the activities and expression of phenylalanine ammonia lyase, cinnamic acid 4-hydroxylase, and 4-coumarate coenzyme A ligase. Furthermore, GABA increased the activity of antioxidant enzymes and the antioxidant capacity. These events were inhibited by 3-mercaptopropionate (an inhibitor for GABA synthesis), indicating that GABA mediated phenolics accumulation and antioxidant system enhancement in soybean sprouts under NaCl stress.
Structure-Property Relation of Trimethyl Ammonium Ionic Liquids for Battery Applications
Authors: Rauber Daniel , Hofmann Andreas , Philippi Frederik , Kay Christopher W. M. , Zinkevich Tatiana , Hanemann Thomas , Hempelmann Rolf
Published: June 2021

Ionic liquids are attractive and safe electrolytes for diverse electrochemical applications such as advanced rechargeable batteries with high energy densities. Their properties that are beneficial for energy storage and conversion include negligible vapor-pressure, intrinsic conductivity as well as high stability. To explore the suitability of a series of ionic liquids with small ammonium cations for potential battery applications, we investigated their thermal and transport properties. We studied the influence of the symmetrical imide-type anions bis(trifluoromethanesulfonyl)imide ([TFSI]−) and bis(fluorosulfonyl)imide ([FSI]−), side chain length and functionalization, as well as lithium salt content on the properties of the electrolytes. Many of the samples are liquid at ambient temperature, but their solidification temperatures show disparate behavior. The transport properties showed clear trends: the dynamics are accelerated for samples with the [FSI]− anion, shorter side chains, ether functionalization and lower amounts of lithium salts. Detailed insight was obtained from the diffusion coefficients of the different ions in the electrolytes, which revealed the formation of aggregates of lithium cations coordinated by anions. The ionic liquid electrolytes exhibit sufficient stability in NMC/Li half-cells at elevated temperatures with small current rates without the need of additional liquid electrolytes, although Li-plating was observed. Electrolytes containing [TFSI]− anions showed superior stability compared to those with [FSI]− anions in battery tests.
Automatic Actin Filament Quantification and Cell Shape Modeling of Osteoblasts on Charged Ti Surfaces
Authors: Gruening Martina , Dawson Jonathan E. , Voelkner Christian , Neuber Sven , Fricke Katja , van Rienen Ursula , Speller Sylvia , Helm Christiane A. , Nebe J. Barbara
Published: June 2021

Surface charges at the cell–biomaterial interface are known to determine cellular functions. Previous findings on cell signaling indicate that osteoblastic cells favor certain moderately positive surface charges, whereas highly positive charges are not tolerated. In this study, we aimed to gain deeper insights into the influence exerted by surface charges on the actin cytoskeleton and the cell shape. We analyzed surfaces with a negative, moderately positive, and highly positive zeta (ζ) potential: titanium (Ti), Ti with plasma polymerized allylamine (PPAAm), and Ti with a polydiallyldimethylammonium chloride (PDADMA) multilayer, respectively. We used the software FilaQuant for automatic actin filament quantification of osteoblastic MG-63s, analyzed the cell edge height with scanning ion conductance microscopy (SICM), and described the cellular shape via a mathematical vertex model. A significant enhancement of actin filament formation was achieved on moderately positive (+7 mV) compared with negative ζ-potentials (−87 mV). A hampered cell spreading was reflected in a diminished actin filament number and length on highly positively charged surfaces (+50 mV). Mathematical simulations suggested that in these cells, cortical tension forces dominate the cell–substrate adhesion forces. Our findings present new insights into the impact of surface charges on the overall cell shape and even intracellular structures.
Internal Quality Evolution of Open-Source Software Systems
Authors: Alenezi Mamdouh
Published: June 2021

The evolution of software is necessary for the success of software systems. Studying the evolution of software and understanding it is a vocal topic of study in software engineering. One of the primary concepts of software evolution is that the internal quality of a software system declines when it evolves. In this paper, the method of evolution of the internal quality of object-oriented open-source software systems has been examined by applying a software metric approach. More specifically, we analyze how software systems evolve over versions regarding size and the relationship between size and different internal quality metrics. The results and observations of this research include: (i) there is a significant difference between different systems concerning the LOC variable (ii) there is a significant correlation between all pairwise comparisons of internal quality metrics, and (iii) the effect of complexity and inheritance on the LOC was positive and significant, while the effect of Coupling and Cohesion was not significant.
A Novel Asymmetric Hyperchaotic Image Encryption Scheme Based on Elliptic Curve Cryptography
Authors: Liang Haotian , Zhang Guidong , Hou Wenjin , Huang Pinyi , Liu Bo , Li Shouliang
Published: June 2021

Most of the image encryption schemes based on chaos have so far employed symmetric key cryptography, which leads to a situation where the key cannot be transmitted in public channels, thus limiting their extended application. Based on the elliptic curve cryptography (ECC), we proposed a public key image encryption method where the hash value derived from the plain image was encrypted by ECC. Furthermore, during image permutation, a novel algorithm based on different-sized block was proposed. The plain image was firstly divided into five planes according to the amount of information contained in different bits: the combination of the low 4 bits, and other four planes of high 4 bits respectively. Second, for different planes, the corresponding method of block partition was followed by the rule that the higher the bit plane, the smaller the size of the partitioned block as a basic unit for permutation. In the diffusion phase, the used hyperchaotic sequences in permutation were applied to improve the efficiency. Lots of experimental simulations and cryptanalyses were implemented in which the NPCR and UACI are 99.6124% and 33.4600% respectively, which all suggested that it can effectively resist statistical analysis attacks and chosen plaintext attacks.
Image Retrieval Method Based on Image Feature Fusion and Discrete Cosine Transform
Authors: Jiang DaYou , Kim Jongweon
Published: June 2021

This paper presents a new content-based image retrieval (CBIR) method based on image feature fusion. The deep features are extracted from object-centric and place-centric deep networks. The discrete cosine transform (DCT) solves the strong correlation of deep features and reduces dimensions. The shallow features are extracted from a Quantized Uniform Local Binary Pattern (ULBP), hue-saturation-value (HSV) histogram, and dual-tree complex wavelet transform (DTCWT). Singular value decomposition (SVD) is applied to reduce the dimensions of ULBP and DTCWT features. The experimental results tested on Corel datasets and the Oxford building dataset show that the proposed method based on shallow features fusion can significantly improve performance compared to using a single type of shallow feature. The proposed method based on deep features fusion can slightly improve performance compared to using a single type of deep feature. This paper also tests variable factors that affect image retrieval performance, such as using principal component analysis (PCA) instead of DCT. The DCT can be used for dimensional feature reduction without losing too much performance.
CFD Simulation of Solid Suspension for a Liquid–Solid Industrial Stirred Reactor
Authors: Stuparu Adrian , Susan-Resiga Romeo , Bosioc Alin
Published: June 2021

The present study examines the possibility of using an industrial stirred chemical reactor, originally employed for liquid–liquid mixtures, for operating with two-phase liquid–solid suspensions. It is critical when obtaining a high-quality chemical product that the solid phase remains suspended in the liquid phase long enough that the chemical reaction takes place. The impeller was designed for the preparation of a chemical product with a prescribed composition. The present study aims at finding, using a numerical simulation analysis, if the performance of the original impeller is suitable for obtaining a new chemical product with a different composition. The Eulerian multiphase model was employed along with the renormalization (RNG) k-ε turbulence model to simulate liquid–solid flow with a free surface in a stirred tank. A sliding-mesh approach was used to model the impeller rotation with the commercial CFD code, FLUENT. The results obtained underline that 25% to 40% of the solid phase is sedimented on the lower part of the reactor, depending on the initial conditions. It results that the impeller does not perform as needed; hence, the suspension time of the solid phase is not long enough for the chemical reaction to be properly completed.
Estimation of Optimal Speed Limits for Urban Roads Using Traffic Information Big Data
Authors: Kim Hyungkyu , Jung Doyoung
Published: June 2021

The use of an inconsistent speed limit determination method can cause low speed limit compliance. Therefore, we developed an objective methodology based on engineering judgment considering the traffic accident rate in road sections, the degree of roadside development, and the geometric characteristics of road sections in urban roads. The scope of this study is one-way roads with two or more lanes in cities, and appropriate sections were selected among all roads in Seoul. These roads have speed limits of the statutory maximum speed of 80 km/h or lower and are characterized by various speeds according to the function of the road, the roadside development, and traffic conditions. The optimal speed limits of urban roads were estimated by applying the characteristics of variables as adjustment factors based on the statutory maximum speed limit. As a result of investigating and testing various influence variables, the function of roads, the existence of median, the level of curbside parking, the number of roadside access points, and the number of traffic breaks were selected as optional variables that influence the operating speed. The speed limit of one-way roads with two or more lanes in Seoul was approximately 10 km/h lower than the current speed limit. The existing speed limits of the roads were applied uniformly considering only the functional road class. However, considering the road environment, the speed limit should be applied differently for each road. In the future, if the collection scope and real-time collection of road environment information can be determined, the GIS visualization of traffic safety information will be possible for all road sections and the safety of road users can be ensured.
Synthetic Transformations and Medicinal Significance of 1,2,3-Thiadiazoles Derivatives: An Update
Authors: Irfan Ali , Ullah Sami , Anum Ayesha , Jabeen Nazish , Zahoor Ameer Fawad , Kanwal Hafza , Kotwica-Mojzych Katarzyna , Mojzych Mariusz
Published: June 2021

The 1,2,3-thiadiazole moiety occupies a significant and prominent position among privileged heterocyclic templates in the field of medicine, pharmacology and pharmaceutics due to its broad spectrum of biological activities. The 1,2,3-thiadiazole hybrid structures showed myriad biomedical activities such as antifungal, antiviral, insecticidal, antiamoebic, anticancer and plant activators, etc. In the present review, various synthetic transformations and approaches are highlighted to furnish 1,2,3-thiadiazole scaffolds along with different pharmaceutical and pharmacological activities by virtue of the presence of the 1,2,3-thiadiazole framework on the basis of structure–activity relationship (SAR). The discussion in this review article will attract the attention of synthetic and medicinal researchers to explore 1,2,3-thiadiazole structural motifs for future therapeutic agents.
Cephalometric Changes Following Maxillary Expansion with Ni-Ti Leaf Springs Palatal Expander and Rapid Maxillary Expander: A Retrospective Study
Authors: Lanteri Valentina , Abate Andrea , Cavagnetto Davide , Ugolini Alessandro , Gaffuri Francesca , Gianolio Alessandro , Maspero Cinzia
Published: June 2021

Background: The aim of this study is to evaluate and compare, through bidimensional cephalometry, skeletal and dental changes obtained from a rapid maxillary expander (RME) and a Ni-Ti leaf spring expander (Leaf) and compare them with an untreated control group. Methods: Records consisted of lateral cephalograms obtained before and after maxillary expansion of patients that underwent orthodontic treatment at the Department of Biomedical, Surgical and Dental Sciences. The Leaf expander group consisted of 9 males (mean age = 7.5 ± 0.9 years old) and 11 females (mean age = 8.2 ± 0.6 years old). The RME group of the present study was composed of 11 males (mean age = 7.8 ± 0.6 years old) and 12 females (mean age = 8.1 ± 0.5 years old). Digital cephalograms were traced using Dolphin Imaging software v.11.1 (Dolphin Imaging and Management Solutions; Los Angeles, CA, USA), which calculated all reported measurements. Each subject was assigned a random identification number, and the examiner was blinded to the subject when measuring. The difference between the two experimental times in all groups was evaluated using the Student’s t-test for dependent variables. The difference between the two evaluation times in each group for all the variables was used to perform a one-way ANOVA test between the three groups. Results: No statistically significant difference was noted, apart from the angle between the upper incisor and the SN and PP planes, which showed an average decrease of 3.25 and 2.55, respectively, and the angle between the lower incisors and the mandibular plane, which showed an average increase of 2.85 degrees. The one-way ANOVA showed no statistically significant difference between the three groups. Conclusions: It appears that the leaf expander and the RME present similar effects such as dental and skeletal changes.
Agriculture 4.0: Is Sub-Saharan Africa Ready?
Authors: Jellason Nugun P. , Robinson Elizabeth J. Z. , Ogbaga Chukwuma C.
Published: June 2021

A fourth agricultural revolution, termed agriculture 4.0, is gradually gaining ground around the globe. It encompasses the application of smart technologies such as artificial intelligence, biotechnology, the internet of things (IoT), big data, and robotics to improve agriculture and the sustainability of food production. To date, narratives around agriculture 4.0 associated technologies have generally focused on their application in the context of higher-income countries (HICs). In contrast, in this perspective, we critically assess the place of sub-Saharan Africa (SSA) in this new technology trajectory, a region that has received less attention with respect to the application of such technologies. We examine the continent’s readiness based on a number of dimensions such as scale, finance, technology leapfrogging, institutions and governance, education and skills. We critically reviewed the challenges, opportunities, and prospects of adopting agriculture 4.0 technologies in SSA, particularly with regards to how smallholder farmers in the region can be involved through a robust strategy. We find that whilst potential exist for agriculture 4.0 adoption in SSA, there are gaps in knowledge, skills, finance, and infrastructure to ensure successful adoption.
Development of Scott Transformer Model in Electromagnetic Transients Programs for Real-Time Simulations
Authors: Lee Choongman , Cho Gyu-Jung , Kim Joorak
Published: June 2021

This paper presents a Scott transformer model to be applied in electromagnetic transients (EMT) programs, particularly in the absence of a detailed Scott transformer model for performing real-time simulations (RTS). Regarding a Scott transformer, a common topology for converting a three-phase network into two single-phase networks, the transformer model in EMT programs is essential to simulate large-scale electric railway systems. A code-based model has been developed to simulate the transformer in RTS directly and contain the transformer’s actual impedance characteristics. By establishing a mathematical foundation with the current injection method, we presented a matrix representation in conjunction with a network solution of EMT programs. The proposed model can handle more practical parameters of Scott transformers with a relatively low computational load. Thus, it supports the flexible computation of real-time simulators with a finite number of processor units. The accuracy of the model is verified by simulating it and comparing the simulation results with an industrial transformer’s certified performance. Furthermore, a case study involving a comparison of the results with the field measurement data of an actual Korean railway system demonstrated the efficacy of the model.
An Innovative Grey Approach for Group Multi-Criteria Decision Analysis Based on the Median of Ratings by Using Python
Authors: Stanujkić Dragiša , Karabašević Darjan , Popović Gabrijela , Stanimirović Predrag S. , Smarandache Florentin , Saračević Muzafer , Ulutaş Alptekin , Katsikis Vasilios N.
Published: June 2021

Some decision-making problems, i.e., multi-criteria decision analysis (MCDA) problems, require taking into account the attitudes of a large number of decision-makers and/or respondents. Therefore, an approach to the transformation of crisp ratings, collected from respondents, in grey interval numbers form based on the median of collected scores, i.e., ratings, is considered in this article. In this way, the simplicity of collecting respondents’ attitudes using crisp values, i.e., by applying some form of Likert scale, is combined with the advantages that can be achieved by using grey interval numbers. In this way, a grey extension of MCDA methods is obtained. The application of the proposed approach was considered in the example of evaluating the websites of tourism organizations by using several MCDA methods. Additionally, an analysis of the application of the proposed approach in the case of a large number of respondents, done in Python, is presented. The advantages of the proposed method, as well as its possible limitations, are summarized.
Rheumatic Immune-Related Adverse Events—A Consequence of Immune Checkpoint Inhibitor Therapy
Authors: Bobircă Anca , Bobircă Florin , Ancuta Ioan , Florescu Alesandra , Pădureanu Vlad , Florescu Dan Nicolae , Pădureanu Rodica , Florescu Anca , Mușetescu Anca Emanuela
Published: June 2021

The advent of immunotherapy has changed the management and therapeutic methods for a variety of malignant tumors in the last decade. Unlike traditional cytotoxic chemotherapy, which works by interfering with cancer cell growth via various pathways and stages of the cell cycle, cancer immunotherapy uses the immune system to reduce malignant cells’ ability to escape the immune system and combat cell proliferation. The widespread use of immune checkpoint inhibitors (ICIs) over the past 10 years has presented valuable information on the profiles of toxic adverse effects. The attenuation of T-lymphocyte inhibitory mechanisms by ICIs results in immune system hyperactivation, which, as expected, is associated with various adverse events defined by inflammation. These adverse events, known as immune-related adverse events (ir-AEs), may affect any type of tissue throughout the human body, which includes the digestive tract, endocrine glands, liver and skin, with reports of cardiovascular, pulmonary and rheumatic ir-AEs as well. The adverse events that arise from ICI therapy are both novel and unique compared to those of the conventional treatment options. Thus, they require a multidisciplinary approach and continuous updates on the diagnostic approach and management.
Increased Longevity and Dormancy of Soil-Buried Seeds from Advanced Crop–Wild Rice Hybrids Overexpressing the EPSPS Transgene
Authors: Jiang Xiao-Qi , Yang Xiao , Lu Bao-Rong
Published: June 2021

Estimating the fitness effect conferred by a transgene introgressed into populations of wild relative species from a genetically engineered (GE) crop plays an important role in assessing the potential environmental risks caused by transgene flow. Such estimation has essentially focused on the survival and fecundity-related characteristics measured above the ground, but with little attention to the fate of GE seeds shattered in the soil seed banks after maturation. To explore the survival and longevity of GE seeds in soil, we examined the germination behaviors of crop–wild hybrid seeds (F4–F6) from the lineages of a GE herbicide-tolerant rice (Oryzasativa) line that contains an endogenous EPSPS transgene hybridized with two wild O. rufipogon populations after the seeds were buried in soil. The results showed significantly increased germination of the GE crop–wild hybrid seeds after soil burial, compared with that of the non-GE hybrid seeds. Additionally, the proportion of dormant seeds and the content of the growth hormone auxin (indole-3-acetic acid, IAA) in the GE crop–wild hybrid seeds significantly increased. Evidently, the EPSPS transgene enhances the survival and longevity of GE crop–wild rice seeds in the soil seed banks. The enhanced survival and longevity of the GE hybrid seeds is likely associated with the increases in seed dormancy and auxin (IAA) by overexpressing the rice endogenous EPSPS transgene. Thus, the fate of GE seeds in the soil seed banks should be earnestly considered when assessing the environmental risks caused by transgene flow.
An Integrated Peptidomics and In Silico Approach to Identify Novel Anti-Diabetic Peptides in Parmigiano-Reggiano Cheese
Authors: Martini Serena , Solieri Lisa , Cattivelli Alice , Pizzamiglio Valentina , Tagliazucchi Davide
Published: June 2021

Inhibition of key metabolic enzymes linked to type-2-diabetes (T2D) by food-derived compounds is a preventive emerging strategy in the management of T2D. Here, the impact of Parmigiano-Reggiano (PR) cheese peptide fractions, at four different ripening times (12, 18, 24, and 30 months), on the enzymatic activity of α-glucosidase, α-amylase, and dipeptidyl peptidase-IV (DPP-IV) as well as on the formation of fluorescent advanced glycation end-products (fAGEs) was assessed. The PR peptide fractions were able to inhibit the selected enzymes and fAGEs formation. The 12-month-ripening PR sample was the most active against the three enzymes and fAGEs. Mass spectrometry analysis enabled the identification of 415 unique peptides, 54.9% of them common to the four PR samples. Forty-nine previously identified bioactive peptides were found, mostly characterized as angiotensin-converting enzyme-inhibitors. The application of an integrated approach that combined peptidomics, in silico analysis, and a structure–activity relationship led to an efficient selection of 6 peptides with potential DPP-IV and α-glucosidase inhibitory activities. Peptide APFPE was identified as a potent novel DPP-IV inhibitor (IC50 = 49.5 ± 0.5 μmol/L). In addition, the well-known anti-hypertensive tripeptide, IPP, was the only one able to inhibit the three digestive enzymes, highlighting its possible new and pivotal role in diabetes management.
Paradoxical Roles of Desmosomal Components in Head and Neck Cancer
Authors: Liu Yin-Qiao , Zou Hai-Ying , Xie Jian-Jun , Fang Wang-Kai
Published: June 2021

Desmosomes are intercellular adhesion complexes involved in various aspects of epithelial pathophysiology, including tissue homeostasis, morphogenesis, and disease development. Recent studies have reported that the abnormal expression of various desmosomal components correlates with tumor progression and poor survival. In addition, desmosomes have been shown to act as a signaling platform to regulate the proliferation, invasion, migration, morphogenesis, and apoptosis of cancer cells. The occurrence and progression of head and neck cancer (HNC) is accompanied by abnormal expression of desmosomal components and loss of desmosome structure. However, the role of desmosomal components in the progression of HNC remains controversial. This review aims to provide an overview of recent developments showing the paradoxical roles of desmosomal components in tumor suppression and promotion. It offers valuable insights for HNC diagnosis and therapeutics development.
Solvent Exposure and Ionic Condensation Drive Fuzzy Dimerization of Disordered Heterochromatin Protein Sequence
Authors: Mueterthies Jazelli , Potoyan Davit A.
Published: June 2021

Proteins with low complexity, disordered sequences are receiving increasing attention due to their central roles in the biogenesis and regulation of membraneless organelles. In eukaryotic organisms, a substantial fraction of disordered proteins reside in the nucleus, thereby facilitating the formation of nuclear bodies, nucleolus, and chromatin compartmentalization. The heterochromatin family of proteins (HP1) is an important player in driving the formation of gene silenced mesoscopic heterochromatin B compartments and pericentric regions. Recent experiments have shown that the HP1a sequence of Drosophila melanogaster can undergo liquid-liquid phase separation under both in vitro and in vivo conditions, induced by changes of the monovalent salt concentration. While the phase separation of HP1a is thought to be the mechanism underlying chromatin compartmentalization, the molecular level mechanistic picture of salt-driven phase separation of HP1a has remained poorly understood. The disordered hinge region of HP1a is seen as the driver of salt-induced condensation because of its charge enriched sequence and post-translational modifications. Here, we set out to decipher the mechanisms of salt-induced condensation of HP1a through a systematic study of salt-dependent conformations of single chains and fuzzy dimers of disordered HP1a hinge sequences. Using multiple independent all-atom simulations with and without enhanced sampling, we carry out detailed characterization of conformational ensembles of disordered HP1a chains under different ionic conditions using various polymeric and structural measures. We show that the mobile ion release, enhancement of local transient secondary structural elements, and side-chain exposure to solvent are robust trends that accompany fuzzy dimer formation. Furthermore, we find that salt-induced changes in the ensemble of conformations of HP1a disordered hinge sequence fine-tune the inter-chain vs. self-chain interactions in ways that favor fuzzy dimer formation under low salt conditions in the agreement with condensation trends seen in experiments.
Critical Role of Al Pair Sites in Methane Oxidation to Methanol on Cu-Exchanged Mordenite Zeolites
Authors: Han Peijie , Zhang Zhaoxia , Chen Zheng , Lin Jingdong , Wan Shaolong , Wang Yong , Wang Shuai
Published: June 2021

Cu-exchanged aluminosilicate zeolites have been intensively studied for the selective oxidation of methane to methanol via a chemical looping manner, while the nature of active Cu-oxo species for these catalysts is still under debate. This study inquired into the effects of Al distribution on methane oxidation over Cu-exchanged aluminosilicate zeolites, which provided an effective way to discern the activity difference between mononuclear and polynuclear Cu-oxo species. Specifically, conventional Na+/Co2+ ion-exchange methods were applied to quantify isolated Al and Al pair (i.e., Al−OH−(Si−O)1–3−Al−OH) sites for three mordenite (MOR) zeolites, and a correlation was established between the reactivity of the resultant Cu-MOR catalysts and the portions of the accessible framework Al sites. These results indicated that the Cu-oxo clusters derived from the Al pair sites were more reactive than the CuOH species grafted at the isolated Al sites, which is consistent with in situ ultraviolet-visible spectroscopic characterization and density functional theory calculations. Further theoretical analysis of the first C–H bond cleavage in methane on these Cu-oxo species unveiled that stabilization of the formed methyl group was the predominant factor in determining the reactivity of methane oxidation.
Integrating the Sustainable Development Goals (SDGs) into Urban Climate Plans in the UK and Japan: A Text Analysis
Authors: Ozawa-Meida Leticia , Ortiz-Moya Fernando , Painter Birgit , Hengesbaugh Matthew , Nakano Ryoko , Yoshida Tetsuro , Zusman Eric , Bhattacharyya Subhes
Published: June 2021

Cities are increasingly adopting potentially sustainable climate plans. Integrating the Sustainable Development Goals (SDGs) into these plans could help stabilize the climate while generating jobs, narrowing equity gaps, fostering innovation, and delivering other sustainability benefits. Yet, how much cities are integrating the SDGs into climate plans remains poorly understood. This article shed light on this question with a text analysis of SDG “keywords” in climate plans for two British and two Japanese cities. The results revealed that none of the surveyed cities have connected climate with socioeconomic priorities covered in SDG1 (poverty), SDG8 (employment), SDG5 (gender), and SDG10 (inequalities). Meanwhile, the United Kingdom cities made more connections between climate and responsible consumption and production (SDG12) than the Japanese cities. Further, Kyoto, Japan shares a climate-SDGs linkages profile that resembles the United Kingdom cities more than Kawasaki. Though not without limitations, text analysis can facilitate the city-to-city peer learning needed to make urban climate plans sustainable within and across countries.
Magnetic Resonance Imaging during Proton Therapy Irradiation Allows for the Early Response Assessment of Pediatric Chordoma
Authors: Vennarini Sabina , Amelio Dante , Lorentini Stefano , Colafati Giovanna Stefania , Cacchione Antonella , De Vito Rita , Carai Andrea , Pettorini Benedetta , Amichetti Maurizio , Mastronuzzi Angela
Published: June 2021

Chordoma in pediatric patients is very rare. Proton therapy has become a gold standard in the treatment of these neoplasms, as high dose escalation can be achieved regarding the target while maximizing the sparing of the healthy tissues near the tumor. The aim of the work was to assess the evolution of morphological sequences during treatment using T1/T2-weighted magnetic resonance imaging (MRI) for the early response assessment of a classic chordoma of the skull base in a pediatric patient who had undergone surgical excision. Our results demonstrated a significant quantitative reduction in the residual nodule component adhered to the medullary bulb junction, with an almost complete recovery of normal anatomy at the end of the irradiation treatment. This was mainly shown in the T2-weighted MRI. On the other hand, the classic component of the lesion was predominantly present and located around the tooth of the axis. The occipital condyles were morphologically and dimensionally stable for the entire irradiation period. In conclusion, the application of this type of monitoring methodology, which is unusual during the administration of a proton treatment for chordoma, highlighted the unexpected early response of the disease. At the same time, it allowed the continuous assessment of the reliability of the treatment plan.
Deep Learning for Walking Behaviour Detection in Elderly People Using Smart Footwear
Authors: Aznar-Gimeno Rocío , Labata-Lezaun Gorka , Adell-Lamora Ana , Abadía-Gallego David , del-Hoyo-Alonso Rafael , González-Muñoz Carlos
Published: June 2021

The increase in the proportion of elderly in Europe brings with it certain challenges that society needs to address, such as custodial care. We propose a scalable, easily modulated and live assistive technology system, based on a comfortable smart footwear capable of detecting walking behaviour, in order to prevent possible health problems in the elderly, facilitating their urban life as independently and safety as possible. This brings with it the challenge of handling the large amounts of data generated, transmitting and pre-processing that information and analysing it with the aim of obtaining useful information in real/near-real time. This is the basis of information theory. This work presents a complete system aiming at elderly people that can detect different user behaviours/events (sitting, standing without imbalance, standing with imbalance, walking, running, tripping) through information acquired from 20 types of sensor measurements (16 piezoelectric pressure sensors, one accelerometer returning reading for the 3 axis and one temperature sensor) and warn the relatives about possible risks in near-real time. For the detection of these events, a hierarchical structure of cascading binary models is designed and applied using artificial neural network (ANN) algorithms and deep learning techniques. The best models are achieved with convolutional layered ANN and multilayer perceptrons. The overall event detection performance achieves an average accuracy and area under the ROC curve of 0.84 and 0.96, respectively.
Are Inclusive Education or Special Education Programs More Likely to Result in Inclusion Post-School?
Authors: Hornby Garry
Published: June 2021

The main goal of both special education and inclusive education for young people with learning or behavioral difficulties is their maximum inclusion in the community as adults. The question of which of these two approaches is more likely to achieve this goal is addressed by considering the findings of three outcome studies of young people with moderate to severe levels of learning or behavioral difficulties who experienced either option, or some combination of the two. The overall findings indicate that students who left school from a special education setting had better outcomes than those who completed their education in mainstream schools. This is considered to be due to the vocational curriculum and work experience they gained in their final years of special education, which those in mainstream schools did not receive. This suggests that a policy of full inclusion, with the closure of special classes and special schools, will result in less inclusion in their communities post-school for young people with moderate to severe levels of learning or behavioral difficulties.
Distributed Multistatic Sky-Wave Over-The-Horizon Radar Based on the Doppler Frequency for Marine Target Positioning
Authors: Ren Fangyu , Gao Huotao , Yang Lijuan
Published: June 2021

Maritime safety issues have aroused great attention, and it has become a difficult problem to use the sky-wave over-the-horizon radar system to locate foreign targets or perform emergency rescue quickly and timely. In this paper, a distributed multi-point sky-wave over-the-horizon radar system is used to locate marine targets. A positioning algorithm based on the Doppler frequency is proposed, namely, the two-step weighted least squares (2WLS) method. This algorithm first converts the WGS-48 geodetic coordinates of the transceiver station to spatial rectangular coordinates; then, introduces intermediate variables to convert the nonlinear optimization problem into a linear problem. In the 2WLS method, four mobile transmitters and four mobile receivers are set up, and the Doppler frequency is calculated by transmitting and receiving signals at regular intervals; it is proven that the 2WLS algorithm has always maintained a better positioning accuracy than the WLS algorithm as the error continues to increase with a certain ionospheric height measurement error and the Doppler frequency measurement error. This paper provides an effective method for the sky-wave over-the-horizon radar to locate maritime targets.
8-Port Semi-Circular Arc MIMO Antenna with an Inverted L-Strip Loaded Connected Ground for UWB Applications
Authors: Addepalli Tathababu , Desai Arpan , Elfergani Issa , Anveshkumar N. , Kulkarni Jayshri , Zebiri Chemseddine , Rodriguez Jonathan , Abd-Alhameed Raed
Published: June 2021

Multiple-input multiple-output (MIMO) antennas with four and eight elements having connected grounds are designed for ultra-wideband applications. Careful optimization of the lines connecting the grounds leads to reduced mutual coupling amongst the radiating patches. The proposed antenna has a modified substrate geometry and comprises a circular arc-shaped conductive element on the top with the modified ground plane geometry. Polarization diversity and isolation are achieved by replicating the elements orthogonally forming a plus shape antenna structure. The modified ground plane consists of an inverted L strip and semi ellipse slot over the partial ground that helps the antenna in achieving effective wide bandwidth spanning from (117.91%) 2.84–11 GHz. Both 4/8-port antenna achieves a size of 0.61 λ × 0.61 λ mm2 (lowest frequency) where 4-port antenna is printed on FR4 substrate. The 4-port UWB MIMO antenna attains wide impedance bandwidth, Omni-directional pattern, isolation >15 dB, ECC < 0.015, and average gain >4.5 dB making the MIMO antenna suitable for portable UWB applications. Four element antenna structure is further extended to 8-element configuration with the connected ground where the decent value of IBW, isolation, and ECC is achieved.
Implementing a Gaze Tracking Algorithm for Improving Advanced Driver Assistance Systems
Authors: Ledezma Agapito , Zamora Víctor , Sipele Óscar , Sesmero M. Paz , Sanchis Araceli
Published: June 2021

Car accidents are one of the top ten causes of death and are produced mainly by driver distractions. ADAS (Advanced Driver Assistance Systems) can warn the driver of dangerous scenarios, improving road safety, and reducing the number of traffic accidents. However, having a system that is continuously sounding alarms can be overwhelming or confusing or both, and can be counterproductive. Using the driver’s attention to build an efficient ADAS is the main contribution of this work. To obtain this “attention value” the use of a Gaze tracking is proposed. Driver’s gaze direction is a crucial factor in understanding fatal distractions, as well as discerning when it is necessary to warn the driver about risks on the road. In this paper, a real-time gaze tracking system is proposed as part of the development of an ADAS that obtains and communicates the driver’s gaze information. The developed ADAS uses gaze information to determine if the drivers are looking to the road with their full attention. This work gives a step ahead in the ADAS based on the driver, building an ADAS that warns the driver only in case of distraction. The gaze tracking system was implemented as a model-based system using a Kinect v2.0 sensor and was adjusted on a set-up environment and tested on a suitable-features driving simulation environment. The average obtained results are promising, having hit ratios between 96.37% and 81.84%.
A Sub-6G SP32T Single-Chip Switch with Nanosecond Switching Speed for 5G Applications in 0.25 μm GaAs Technology
Authors: Wu Tianxiang , Wei Jipeng , Liu Hongquan , Ma Shunli , Chen Yong , Ren Junyan
Published: June 2021

This paper presents a single-pole 32-throw (SP32T) switch with an operating frequency of up to 6 GHz for 5G communication applications. Compared to the traditional SP32T module implemented by the waveguide package with large volume and power, the proposed switch can significantly simplify the system with a smaller size and light weight. The proposed SP32T scheme utilizing tree structure can dramatically reduce the dc power and enhance isolation between different output ports, which makes it suitable for low-power 5G communication. A design methodology of a novel transmission (ABCD) matrix is proposed to optimize the switch, which can achieve low insertion loss and high isolation simultaneously. The average insertion loss and the isolations are 1.5 and 35 dB at 6 GHz operating frequency, respectively. The switch exhibits the measured input return loss which is better than 10 dB at 6 GHz. The 1 dB input compression point of SP32T is 15 dBm. The prototype is designed in 5 V 0.25 μm GaAs technology and occupies a small area of 12 mm2.
Virtual to Real-World Transfer Learning: A Systematic Review
Authors: Ranaweera Mahesh , Mahmoud Qusay H.
Published: June 2021

Machine learning has become an important research area in many domains and real-world applications. The prevailing assumption in traditional machine learning techniques, that training and testing data should be of the same domain, is a challenge. In the real world, gathering enough training data to create high-performance learning models is not easy. Sometimes data are not available, very expensive, or dangerous to collect. In this scenario, the concept of machine learning does not hold up to its potential. Transfer learning has recently gained much acclaim in the field of research as it has the capability to create high performance learners through virtual environments or by using data gathered from other domains. This systematic review defines (a) transfer learning; (b) discusses the recent research conducted; (c) the current status of transfer learning and finally, (d) discusses how transfer learning can bridge the gap between the virtual and real-world.
Vulnerability Analysis to Maximize the Resilience of Power Systems Considering Demand Response and Distributed Generation
Authors: Mosquera Palacios Darin Jairo , Trujillo Edwin Rivas , López-Lezama Jesús María
Published: June 2021

Electric power systems are subject to failures, due to both deliberate and fortuitous events. This paper addresses the first case in which a disruptive agent aims at maximizing the damage to the network (expressed through the total cost of operation), while the system operator takes the necessary measures to mitigate the effects of this attack. The interaction between these two agents is modeled by means of a bi-level optimization problem. On one hand, the disruptive agent is positioned in the upper-level optimization problem and must decide which elements to render out of service (lines and generators), given a limited destructive budget. On the other hand, the system operator, located in a lower-level optimization problem, reacts to the attack by deploying mitigation measures in order to minimize cost overruns in system operation. Based on the aforementioned dynamic, this paper proposes a novel approach to maximize the resiliency of the power system under intentional attacks through the implementation of distributed energy resources (DERs), namely, distributed generation (DG) and demand response (DR). Three metrics are proposed to assess resilience by assigning DERs in islands generated by the destruction of lines and generators. The results obtained in a didactic 5-bus test system and the IEEE RTS-24 bus test system demonstrate the applicability and effectiveness of the proposed methodology.
A Mathematical Model for the Analysis of Jet Engine Fuel Consumption during Aircraft Cruise
Authors: Velásquez-SanMartín Francisco , Insausti Xabier , Zárraga-Rodríguez Marta , Gutiérrez-Gutiérrez Jesús
Published: June 2021

In this paper we propose a mathematical model for the fuel consumption analysis during aircraft cruise. A closed-form formula that expresses the aircraft’s weight variation over time, and hence, the fuel flow rate, is obtained as a result. Furthermore, a closed-form expression of the aircraft’s main performance parameters is also obtained. We compare the values of such parameters computed by using the Piano-X software and computed by using our mathematical model. Simulation results confirm that our mathematical model provides results very close to reality. Finally, the closed-form formula of the fuel flow rate provided by our model is used to improve the calculation of the carbon dioxide emissions for four example routes, which, unlike here, are usually obtained under the assumption of a constant value of the fuel flow rate.