bluuebunny/crossref_metadata_2025 huggingface dataset:
Usance of industrial 4.0 technique to overcome the pandemic situation of COVID-19
Authors: Bhardwaj Vaibhav , Agarwal Pankaj , Nayak Soumya Ranjan , Sisodiya Mangal Singh , Singh Vijander
Published: January 2021

COVID 19 (Coronavirus) pandemic has created surge demand for essential good and other items like medical equipment and industries which were shut and need to revive back themselves again with new strategies and plan to bring the situation back towards normalcy the study also aimed to propose new technique including advantage of Industry 4.0 ethics to reduce the impact and tackle the situation of COVID-19 and post COVID-19. A detailed review of the literature is done on the technologies along with their Industry 4.0 applications during this COVID-19 pandemic, The review holds some basic and advance technologies application to enhance industrial safety and boosting the work culture to normal and efficient. Using appropriate search words on the databases of IEEE papers, Google Scholar and Research Gate. We found several useful applications which can be inculcated along with modern human-machine interfacing which can help for proper control and management of COVID-19 pandemic and these techniques are been discussed in this paper. Available technologies blend along with Industry 4.0 technique and procedure could also help the society to work and understand smartly and get aware of this methodology which can lead them to stay safe and secure along with maintaining working efficiency. Industry 4.0 can fulfil the requirements of society/community during this crisis’s situation. The new technique which firstly make assure that the induvial and belonging health and safety is first priority and their demand are need to be fulfil on time so that no one suffers. These Industry 4.0 technologies could provide a lot of innovative ideas and solution at from base local areas to global platforms. The supply chain partners and government bodies should work along with new technologies wisely for improving the services during COVID-19 and of any similar situations happening anywhere anytime.
Investigation of rheological and performance characteristics of oxidized polyethylene polymer blended with SBS modified bitumen
Authors: Mandrawalia Ajay Kumar , Gaur Arun , Mittal Abhishek
Published: January 2021

This research article investigates the influence of oxidized polyethylene (PE) polymer on rheological and performance properties of SBS modified bitumen at an optimum dose of 0.5 % by weight. To evaluate the impact of PE polymer on SBS modified bitumen different performance testing such as indirect tensile strength and resilient modulus was conducted on PE polymer blended bituminous concrete mixes and rheology of modified bitumen was determined using dynamic shear rheometer. It was concluded that the intrusion of PE polymer in SBS modified bitumen improved elastic recovery and viscosity. The findings of resilient modulus test, indicated that the addition of PE polymer enhanced the response of modified bituminous mixes under repeated loading (Mr value) by 11%, 20% and 16% at 25°C, 35°C and 45°C respectively as compared to SBS bituminous mix.
Overview on Hardfacing Processes, Materials and Applications
Authors: Garbade R. R. , Dhokey N. B.
Published: January 2021

Hardfacing alloys are mainly obtained through atomization of powders and by determining of alloying elements in pure form or ferro alloys. They are widely used materials as weld overlay to improve wear and corrosion resistance in applications such as agricultural, construction, mining, etc. Wear is an important factor that controls life of any component. Different types of wear such as corrosion, impact, abrasion, metallic, etc are responsible for worn out of components. Many researches have been done to either reduce the wear or improve the wear resistant of the existing materials. Among these, hardfacing technique has made many developments since last few years. As in nuclear reactors, hardfacing of the grid plate through Laser cladding and Plasma Transferred arc welding, to improve the life of the components and resistance from wear and corrosion. Hardfacing involves applying a consumable material with desired wear properties over a soft base metal to enhance resistance to different wear mechanism. Using Calphad technique for development of desired composition and application of Schaffler diagram has been attempted successfully. In this paper a review of hardfacing processes and materials, highlighting the use of Laser cladding and Plasma transfer arc for overlaying hardfacing alloys has been attempted.
Industrial Temperature Measurement of Flame and Flue gases using IOT and Image processing
Authors: Sujatha K. , Ponmagal R.S. , SenthilKumar K. , Karthikeyan V. , Ramkumar K.S. , Bhavani N P G
Published: January 2021

This study effort contracts with measuring the flame temperature in the combustion chamber along with a scheme to monitor the temperature of flue gases from the power plants. Presently, the gases from the exhaust are monitore dusing gas analyzers which are positioned at the exit point of the chimney. These gas analyzers are prone to cold end corrosion which will lead to malfunctioning of the equipment causing erroneous results during measurements. Thiskind of indigenous technique facilitates to develop an Industrial IoT (IIoT) temperature monitoring system at power plants. A combination of Principal Component Analysis (PCA) with Cascaded Neural Network (CNN) is used. The features extracted and reduced serve as inputs to CNN. An efficient technology to scrutinize and measure the temperature inside the combustion chamber thereby reducing the amount of flue gas emissions by the partnership of two methods.
An enhanced intelligent classification approach to improve the encryption of big data
Authors: Gupta Gitanjali , Lakhwani Kamlesh
Published: January 2021

Progression in cloud applications have been hindered due to critical issues such as Data security and privacy. The aggravating concern remains the ability and access of cloud operators in acquiring sensitive data. Consequently, usage and excitement of cloud computing has remained lukewarm, with users remaining skeptical of the level of confidentiality promised. Principally, the financial industry and governmental agencies have shown lackluster and inimical enthusiasm of these indications. The paper serves to analyze the aforementioned issue, and present a creative proposal into cryptography, as a means to virtually restrict cloud service operator’s access to sensitive data. The free-will of cloud operators in handling sensitive data will be undermined. Through this method, file is divided with more accuracy using an intelligent classification technique. Alternatively, a different method can be utilized to find out whether data need splitting to obtain lesser operating time and minimize storage space. The results show that the approach can resolve innumerable risks associated with cloud computing, whilst requiring sufficient computing time using a very good intelligent machine learning classification techniques. As such, novel approach has been proposed which is entitled as a model for Sensitive Encrypted Storage (SES). In this model, three proposed algorithms Convolution Neural Network with Logistic Regression, Elliptic-curve Diffie Hellman-Shifted Adaption Homomorphism Encryption and Decryption have been integrated.
Efficiency and Green House Emission Response of Different Vehicles Operating on Various Driving Cycles
Authors: Puri Deepali , Leena G
Published: January 2021

In today’s scenario, energy security and global warming are considered as vital parameters of concern. The use of large number of conventional vehicles on roads has caused serious environmental pollution and they consume considerable amount of energy resources. Thus solution lies in switching to cleaner and greener energy alternatives, such as electrical energy. In this paper, conventional, electric and hybrid electric vehicles are compared on the basis of efficiency and greenhouse gas emissions. For efficient comparison, three different cycles, namely, Manhattan, Urban Dynamometer Driving Schedule and Arterial, are chosen. The simulation and computer modelling is implemented using the Advanced vehicle simulator (ADVISOR) platform. When Electric vehicle is tested on three different types of driving cycles, it exhibits highest efficiency and no tail pipe emission as compared to other vehicles. Thus the use of Pure electric vehicle eliminates both the problem of depleting energy resources and environmental pollution.
Furnace Flame Tracking for Combustion Quality Estimation in Coal Fired Boilers
Authors: Sujatha K. , Sinthia P. , Babu Jada Satish , Ponmagal R.S. , Veerendrakumar J. , Balaji V. , Srividhya V.
Published: January 2021

This research work focus is on optimization of the combustion quality as the combustion quality plays a vital role in minimizing NOx and CO emissions in the flue gas. Power generated is also another important factor under consideration so as to meet the demand. Flame monitoring in boilers using digital imaging provides replacement for the conventional technique of temperature measurement. The indigenous method can be replaced by incorporating an online PC based system by analyzing the flame images.
An Integrated Approach for Flood Prediction by Using Block Chain Network and Machine Learning
Authors: Murugan Kalpana , Seeta Reddy A. , Sivasainath Reddy M. , Raviteja Reddy P.
Published: January 2021

Now a days heavy rainfall becomes the major problem in India because of the changes that occur in global environment and in climatic conditions this problem rises so, To overcome this problem, this proposed method i.e advanced flood alerting system (AFAS) had been introduced by using machine learning and block chain network. This method helps to predict an early occurrence of flood with an efficient output probability of prediction. The output of this project gives an accurate and approximate probability percentage of flood prediction. After predicting the flood it gives an alert or caution to that particular area that has been effected by flood so, it helps them to take necessary precaution steps to follow, If this happened then the victims that effected by flood can be saved and also death loss and property loss can be reduced in an effective manner.
Side-channel Analysis using Deep Learning on Hardware Trojans
Authors: Kokila J. , Chithra S. , Ramasubramanian N.
Published: January 2021

A power side-channel analysis is proposed to nd the correct key in hardware trojan affected AES by evaluating correlation between every sub-key guesses. A deep learning method for side-channel analysis (SCA) is proposed, which consists of two phases-characterization and attack. Multilayer perceptron (MLP) and convolutional neural networks(CNN) are used as the models to determine the SCA and their performances are evaluated. Two kinds of desynchronization were used, where maximum possible value with which the trace can be shifted was 0 in rst and 100 in the second. SCA is performed in these desynchronized traces also.
Modified direct clustering algorithm for group formation in cellular manufacturing
Authors: Potdar G C , Sapkal S U , Shivade A S
Published: January 2021

In cellular manufacturing system formation of machine-part families is an important task. Cellular manufacturing systems deals with various clustering algorithms which are particularly relevant to the problem of machine component group formation. In this paper, case study from well-known gearbox manufacturing company is considered where there is scope for using cellular manufacturing system. Company is manufacturing the gearbox varying from single stage reduction to four stage reduction. A modified direct clustering algorithm is proposed and is applied after the initial incidence matrix derived from direct clustering algorithm. This algorithm overcomes the problem arises during application of direct clustering algorithm and gives the optimum solution. The algorithm is specifically designed to deal with large amount of data during realistic situations. The results of proposed algorithm are compared with well-known existing algorithms and it is found that the proposed algorithm gives the better solution than the existing algorithms under consideration.
Classification of lung infected Corona Virus X Ray Images using Deep Learning CNN Model
Authors: Gupta Yogesh Kumar , Agrawal Saroj , Mittal Aman
Published: January 2021

All Start In this examination as learning, a dataset of COVID-19 lung contaminated X-beam pictures with common infection pneumonia, insisted Covid-19 sickness, and ordinary occurrences were utilized for the programmed acknowledgment of the Corona virus infirmity. The purpose of the investigation is to the comparable portrayal of Covid-19 utilizing Convolution Neural Network and assesses the precision proposed model convolutional neural framework over the progressing years for clinical picture characterization. Corona Virus lung infected X-Ray Images accessible by Kaggle a complete 590 images, which classified in 2 classes: typical and Covid-19. To survey the hypothesis accuracy of the models. The plan models end up being productive appeared differently in relation to made by (Arpan Mangal et al, 2020), (A. A. Saraiva et al.,2020), (Ioannis D. Apostolopoulos et al, 2020), (Ali Narin et al. 2020), which gained accuracy 90.5,95.30, 96.78, 98 independently and the current work had an ordinary precision of 99.54.
Evaluation of compressive and split tensile strength of slag based aluminosilicate geopolymer reinforced by waste polymeric materials using Taguchi method
Authors: Khezrloo Amirreza , Tayebi Morteza , Shafiee Abbas , Aghaie Alireza
Published: January 2021

In this work, slag based aluminosilicate geopolymer was reinforced with polymeric fibers including, polyester (PES) (waste tire cap plies), polymeric particles including polyethylene terephthalate (PET) (waste water bottle), styrene-butadiene rubber (SBR) (waste tire), and polyvinyl chloride (PVC) (waste water hose). The tensile and compressive strength of the material was evaluated. Taguchi method was employed to assess the influence of the effective parameters on the mechanical characteristics of the geopolymer composite. QUALITEK-4 software was used to create the L32 orthogonal array with 192(96+96) geopolymer specimens and 32+32 experiments. Analysis of variance (ANOVA) was utilized to analyze the results of the experiments. The prepared geopolymers were characterized by SEM analysis. The results revealed that the compressive and split tensile strength of the aluminosilicate geopolymer was substantially improved after reinforced by the PES fibers compared with other particles such as SBR, PVC, and PET.
The role of applied strain and volume percentage of components on mechanical properties and fracture toughness in multilayered Al/Mg composite fabricated by the accumulative roll bonding process
Authors: Delshad Gholami M , Rahmatabadi D , Shojaee T , Hashemi R , Mohammadi B.
Published: January 2021

In this study, for the first time, the effect of applied strains and volume percentage of components of layered composite on the mechanical properties and fracture toughness of Al/Mg were investigated experimentally. The multilayered Al/Mg were produced by the accumulative roll bonding (ARB) process. For the investigation, three Al/Mg composites with different volume percentages (25%, 50%, and 66.6%Al) at different applied strains (0.8–3.2) were produced. The experimental evaluation included microscopic examination by optical microscope imaging, uniaxial tensile test, and plane strain fracture toughness. As the applied strain for all three composites increased, plastic instability in the magnesium reinforcement intensified, but due to the low thickness of the Al layers compared to the Mg layer, uniform structure of Mg distribution in Al for all three composite was not achieved. Also, by adding Al layers to the primary composite, a lower shear strain was applied to the magnesium reinforcement, and instability intensity in the reinforcement layer decreased. For this reason, as Al layers increased, plastic instability diminished. By raising the exerted strain, the values of tensile strength increased, and by adding Al layers, the elongation increased. The maximum amount of tensile strength and elongation for each composite was achieved in the same ARB pass (last pass) and the highest values of UTS and elongation were reached to 384.1 MPa and 1.95% for Al25%Mg, respectively. However, the highest amount of fracture toughness for each composite was obtained in the different exerted strains and the maximum value of 41.4 MPa·m1/2 was achieved for Al33.3% in the third pass. The present phenomena indicated that many factors such as higher Mg volume with higher energy absorption, plastic instability, thickness ratio, plastic instability, and value of applied strain affected the fracture toughness. In summary, the relationship between fracture toughness with applied strain and also with volume percent of Al was not always straightforward. It depends on other factors, such as how the reinforcement was distributed, the thickness of the layers, the workability, and the addition of aluminum. Also, the applied strain has a more significant effect on increasing fracture toughness in multilayered composite if they cause a uniform distribution of reinforcement particles in the field or continuity in the reinforcement layer.
Investigation of the fast magnetosonic wave excited by the Alfvén wave phase mixing by using the Hall–MHD model in inhomogeneous plasma
Authors: LI Zhongzheng , HAN Juanfang , WANG Fangping , CHEN Zhengwu , DUAN Wenshan
Published: January 2021

The inhomogeneity is introduced by a nonzero density gradient which separates the plasma into two different regions where plasma density are constant. The Alfvén waves, the phase mixing and the fast magnetosonic wave are excited by the boundary condition in inhomogeneous magnetized plasma. By using the Hall–magnetohydrodynamics (MHD) model, it is found that there are Alfvén waves in the homogeneous regions, while the phase mixing appears in the inhomogeneous region. The interesting result is that a fast magnetosonic wave is excited in a different direction which has a nonzero angle between the wave propagation direction and the direction of the background magnetic field. The dependence of the propagation direction of the excited fast magnetosonic wave and its strength of the magnetic field on the plasma parameters are given numerically. The results show that increasing both the driving frequency and the ratio of magnetic pressure to thermal pressure will increase the acceleration of the electrons. The electron acceleration also depends on the inhomogeneity parameters.
Adaptive pruning-based optimization of parameterized quantum circuits
Authors: Sim Sukin , Romero Jonathan , Gonthier Jérôme F , Kunitsa Alexander A
Published: January 2021

Variational hybrid quantum–classical algorithms are powerful tools to maximize the use of noisy intermediate-scale quantum devices. While past studies have developed powerful and expressive ansatze, their near-term applications have been limited by the difficulty of optimizing in the vast parameter space. In this work, we propose a heuristic optimization strategy for such ansatze used in variational quantum algorithms, which we call ‘parameter-efficient circuit training (PECT)’. Instead of optimizing all of the ansatz parameters at once, PECT launches a sequence of variational algorithms, in which each iteration of the algorithm activates and optimizes a subset of the total parameter set. To update the parameter subset between iterations, we adapt the Dynamic Sparse Reparameterization scheme which was originally proposed for training deep convolutional neural networks. We demonstrate PECT for the Variational Quantum Eigensolver, in which we benchmark unitary coupled-cluster ansatze including UCCSD and k-UpCCGSD, as well as the Low-Depth Circuit Ansatz (LDCA), to estimate ground state energies of molecular systems. We additionally use a layerwise variant of PECT to optimize a hardware-efficient circuit for the Sycamore processor to estimate the ground state energy densities of the one-dimensional Fermi-Hubbard model. From our numerical data, we find that PECT can enable optimizations of certain ansatze that were previously difficult to converge and more generally can improve the performance of variational algorithms by reducing the optimization runtime and/or the depth of circuits that encode the solution candidate(s).
Preparation and water flow velocity measurement of a large diameter single-wall carbon nanotube
Authors: Fan Aoran , Hu Yudong , Zhang Yufeng , Ma Weigang , Zhang Xing
Published: January 2021

To fill the gap in the measurement of large diameter single-wall carbon nanotube (SWCNT) and further predict the variation rule of mass flux versus diameter, this work measured the water flow velocity and mass flux coefficient in an individual SWCNT with a 3.07 nm diameter. A mechanical method is used to obtain the large diameter SWCNT by removing the internal tube of a double-wall carbon nanotube, and then the water flow velocity through this SWCNT was measured by an electrical method. The water flow velocity of large diameter SWCNT can reach to 146.1 ± 32.5 μm s−1, and the enhancement factor compared with no-slip Hagen–Poiseuille relation is about 14.5. A mass flux coefficient is defined to describe the mass flow ability through SWCNT and calculated by the experiment data. Although the enhancement factor decreased to ∼1/4 of the normal size SWCNT (∼1.5 nm), the mass flux coefficient in the large diameter SWCNT increased efficiently, and which is about 5.7 times to the normal size SWCNT. Based on the above measurement result, a reported simulation result can be revised and then verified to describe the enhancement factor versus diameter, and the mass flux coefficient of the SWCNT can be further predicted. According to the prediction result, in the bulk-like liquid region, the mass flux of an individual SWCNT can reach to maximum when the diameter is around 2.9 nm, which would provide a new idea for the design of the SWCNT-based nanodevices in the future.
New twists in actin–microtubule interactions
Authors: Pimm Morgan L. , Henty-Ridilla Jessica L.
Published: January 2021

Actin filaments and microtubules are cytoskeletal polymers that participate in many vital cell functions including division, morphogenesis, phagocytosis, and motility. Despite the persistent dogma that actin filament and microtubule networks are distinct in localization, structure, and function, a growing body of evidence shows that these elements are choreographed through intricate mechanisms sensitive to either polymer. Many proteins and cellular signals that mediate actin–microtubule interactions have already been identified. However, the impact of these regulators is typically assessed with actin filament or microtubule polymers alone, independent of the other system. Further, unconventional modes and regulators coordinating actin–microtubule interactions are still being discovered. Here we examine several methods of actin–microtubule crosstalk with an emphasis on the molecular links between both polymer systems and their higher-order interactions.
Neoliberalism: A Very Short Introduction
Authors: Steger Manfred B. , Roy Ravi K.
Published: January 2021

Neoliberalism: A Very Short Introduction explores the considerable variations of neoliberalism around the world. It also discusses the origins, evolution, and core ideas of neoliberalism. Neoliberalism emerged as the world's dominant economic paradigm in the 1990s. The global financial crash of 2008 and the subsequent emergence of more nationalist ideologies have challenged both neoliberal assumptions and related financial systems—a development most spectacularly reflected in 2016's pro-Brexit referendum in the UK and the Trump election victory in the same year. This new edition asks whether changing versions of neoliberalism might succeed in drowning out the calls for a return to territorial sovereignty and national greatness.
Adverse Childhood Experiences and Rate of Memory Decline From Mid to Later Life: Evidence From the English Longitudinal Study of Ageing
Authors: O’Shea Brendan Q , Demakakos Panayotes , Cadar Dorina , Kobayashi Lindsay C
Published: January 2021

Evidence on the role of early-life adversity in later-life memory decline is conflicting. We investigated the relationships between adverse childhood experiences (ACEs) and memory performance and rate of decline over a 10-year follow-up among middle-aged and older adults in England. Data were from biennial interviews with 5,223 participants aged 54 years or older in the population-representative English Longitudinal Study of Ageing from 2006/2007 to 2016/2017. We examined self-reports of 9 ACEs prior to age 16 years that related to abuse, household dysfunction, and separation from family. Memory was assessed at each time point as immediate and delayed recall of 10 words. Using linear mixed-effects models with person-specific random intercepts and slopes and adjusted for baseline age, participants’ baseline age squared, sex, ethnicity, and childhood socioeconomic factors, we observed that most individual and cumulative ACE exposures had null to weakly negative associations with memory function and rate of decline over the 10-year follow-up. Having lived in residential or foster care was associated with lower baseline memory (adjusted β = −0.124 standard deviation units; 95% confidence interval: −0.273, −0.025) but not memory decline. Our findings suggest potential long-term impacts of residential or foster care on memory and highlight the need for accurate and detailed exposure measures when studying ACEs in relation to later-life cognitive outcomes.
Market Segmentation and Shirley Jackson’s Domestic Humor
Authors: Mangrum Benjamin
Published: January 2021

Shirley Jackson’s essays in popular women’s magazines negotiate the gendered tensions and commercial contradictions of postwar print culture. This essay shows how the women in Jackson’s essays are figures of the fraught convergence of women’s public affiliation and the restrained politics of gender critique. These female figures are also representative of broader issues in US print culture after the Second World War. In particular, Jackson’s essays represent how a certain strain of feminist writing—sometimes known as “domestic humor”—was absorbed within the market forces of print capitalism. To explain this absorption, I draw on mid-century theories of market segmentation.
Insight into the mechanism of thermostabilization of GH10 xylanase from Bacillus sp. strain TAR-1 by the mutation of S92 to E
Authors: Suzuki Manami , Takita Teisuke , Kuwata Kohei , Nakatani Kota , Li Tongyang , Katano Yuta , Kojima Kenji , Mizutani Kimihiko , Mikami Bunzo , Yatsunami Rie , Nakamura Satoshi , Yasukawa Kiyoshi
Published: January 2021

The mechanism of thermostabilization of GH10 xylanase, XynR, from Bacillus sp. strain TAR-1 by the mutation of S92 to E was investigated. Thermodynamic analysis revealed that thermostabilization was driven by the decrease in entropy change of activation for thermal inactivation. Crystallographic analysis suggested that this mutation suppressed the fluctuation of the amino acid residues at position 92-95.
Accurate prediction of inter-protein residue–residue contacts for homo-oligomeric protein complexes
Authors: Yan Yumeng , Huang Sheng-You
Published: January 2021

Protein–protein interactions play a fundamental role in all cellular processes. Therefore, determining the structure of protein–protein complexes is crucial to understand their molecular mechanisms and develop drugs targeting the protein–protein interactions. Recently, deep learning has led to a breakthrough in intra-protein contact prediction, achieving an unusual high accuracy in recent Critical Assessment of protein Structure Prediction (CASP) structure prediction challenges. However, due to the limited number of known homologous protein–protein interactions and the challenge to generate joint multiple sequence alignments of two interacting proteins, the advances in inter-protein contact prediction remain limited. Here, we have proposed a deep learning model to predict inter-protein residue–residue contacts across homo-oligomeric protein interfaces, named as DeepHomo. Unlike previous deep learning approaches, we integrated intra-protein distance map and inter-protein docking pattern, in addition to evolutionary coupling, sequence conservation, and physico-chemical information of monomers. DeepHomo was extensively tested on both experimentally determined structures and realistic CASP-Critical Assessment of Predicted Interaction (CAPRI) targets. It was shown that DeepHomo achieved a high precision of >60% for the top predicted contact and outperformed state-of-the-art direct-coupling analysis and machine learning-based approaches. Integrating predicted inter-chain contacts into protein–protein docking significantly improved the docking accuracy on the benchmark dataset of realistic homo-dimeric targets from CASP-CAPRI experiments. DeepHomo is available at http://huanglab.phys.hust.edu.cn/DeepHomo/
Multi-omic analysis suggests tumor suppressor genes evolved specific promoter features to optimize cancer resistance
Authors: Huang Dan , Wang Xiansong , Liu Yingzhi , Huang Ziheng , Hu Xiaoxu , Hu Wei , Li Qing , Chan Hung , Zou Yidan , Ho Idy H T , Wang Yan , Cheng Alfred S L , Kang Wei , To Ka F , Wang Maggie H T , Wong Sunny H , Yu Jun , Gin Tony , Zhang Qingpeng , Li Zheng , Shen Jianxiong , Zhang Lin , Chan Matthew T V , Liu Xiaodong , Wu William K K
Published: January 2021

Tumor suppressor genes (TSGs) exhibit distinct evolutionary features. We speculated that TSG promoters could have evolved specific features that facilitate their tumor-suppressing functions. We found that the promoter CpG dinucleotide frequencies of TSGs are significantly higher than that of non-cancer genes across vertebrate genomes, and positively correlated with gene expression across tissue types. The promoter CpG dinucleotide frequencies of all genes gradually increase with gene age, for which young TSGs have been subject to a stronger evolutionary pressure. Transcription-related features, namely chromatin accessibility, methylation and ZNF263-, SP1-, E2F4- and SP2-binding elements, are associated with gene expression. Moreover, higher promoter CpG dinucleotide frequencies and chromatin accessibility are positively associated with the ability of TSGs to resist downregulation during tumorigenesis. These results were successfully validated with independent datasets. In conclusion, TSGs evolved specific promoter features that optimized cancer resistance through achieving high expression in normal tissues and resistance to downregulation during tumorigenesis.
essHi-C: essential component analysis of Hi-C matrices
Authors: Franzini Stefano , Di Stefano Marco , Micheletti Cristian
Published: January 2021

Motivation

Hi-C matrices are cornerstones for qualitative and quantitative studies of genome folding, from its territorial organization to compartments and topological domains. The high dynamic range of genomic distances probed in Hi-C assays reflects in an inherent stochastic background of the interactions matrices, which inevitably convolve the features of interest with largely non-specific ones.

Results

Here, we introduce and discuss essHi-C, a method to isolate the specific or essential component of Hi-C matrices from the non-specific portion of the spectrum compatible with random matrices. Systematic comparisons show that essHi-C improves the clarity of the interaction patterns, enhances the robustness against sequencing depth of topologically associating domains identification, allows the unsupervised clustering of experiments in different cell lines and recovers the cell-cycle phasing of single-cells based on Hi-C data. Thus, essHi-C provides means for isolating significant biological and physical features from Hi-C matrices.

Availability and implementation

The essHi-C software package is available at https://github.com/stefanofranzini/essHIC.

Supplementary information

Supplementary data are available at Bioinformatics online.
eHSCPr discriminating the cell identity involved in endothelial to hematopoietic transition
Authors: Wang Hao , Liang Pengfei , Zheng Lei , Long ChunShen , Li HanShuang , Zuo Yongchun
Published: January 2021

Motivation

Hematopoietic stem cells (HSCs) give rise to all blood cells and play a vital role throughout the whole lifespan through their pluripotency and self-renewal properties. Accurately identifying the stages of early HSCs is extremely important, as it may open up new prospects for extracorporeal blood research. Existing experimental techniques for identifying the early stages of HSCs development are time-consuming and expensive. Machine learning has shown its excellence in massive single-cell data processing and it is desirable to develop related computational models as good complements to experimental techniques.

Results

In this study, we presented a novel predictor called eHSCPr specifically for predicting the early stages of HSCs development. To reveal the distinct genes at each developmental stage of HSCs, we compared F-score with three state-of-art differential gene selection methods (limma, DESeq2, edgeR) and evaluated their performance. F-score captured the more critical surface markers of endothelial cells and hematopoietic cells, and the area under receiver operating characteristic curve (ROC) value was 0.987. Based on SVM, the 10-fold cross-validation accuracy of eHSCpr in the independent dataset and the training dataset reached 94.84% and 94.19%, respectively. Importantly, we performed transcription analysis on the F-score gene set, which indeed further enriched the signal markers of HSCs development stages. eHSCPr can be a powerful tool for predicting early stages of HSCs development, facilitating hypothesis-driven experimental design and providing crucial clues for the in vitro blood regeneration studies.

Availability and implementation

http://bioinfor.imu.edu.cn/ehscpr.

Supplementary information

Supplementary data are available at Bioinformatics online.
Motif-Raptor: a cell type-specific and transcription factor centric approach for post-GWAS prioritization of causal regulators
Authors: Yao Qiuming , Ferragina Paolo , Reshef Yakir , Lettre Guillaume , Bauer Daniel E , Pinello Luca
Published: January 2021

Motivation

Genome-wide association studies (GWASs) have identified thousands of common trait-associated genetic variants but interpretation of their function remains challenging. These genetic variants can overlap the binding sites of transcription factors (TFs) and therefore could alter gene expression. However, we currently lack a systematic understanding on how this mechanism contributes to phenotype.

Results

We present Motif-Raptor, a TF-centric computational tool that integrates sequence-based predictive models, chromatin accessibility, gene expression datasets and GWAS summary statistics to systematically investigate how TF function is affected by genetic variants. Given trait-associated non-coding variants, Motif-Raptor can recover relevant cell types and critical TFs to drive hypotheses regarding their mechanism of action. We tested Motif-Raptor on complex traits such as rheumatoid arthritis and red blood cell count and demonstrated its ability to prioritize relevant cell types, potential regulatory TFs and non-coding SNPs which have been previously characterized and validated.

Availability and implementation

Motif-Raptor is freely available as a Python package at: https://github.com/pinellolab/MotifRaptor.

Supplementary information

Supplementary data are available at Bioinformatics online.
RAD: a web application to identify region associated differentially expressed genes
Authors: Guo Yixin , Xue Ziwei , Yuan Ruihong , Li Jingyi Jessica , Pastor William A. , Liu Wanlu
Published: January 2021

With the advance of genomic sequencing techniques, chromatin accessible regions, transcription factor binding sites and epigenetic modifications can be identified at genome-wide scale. Conventional analyses focus on the gene regulation at proximal regions; however, distal regions are usually less focused, largely due to the lack of reliable tools to link these regions to coding genes. In this study, we introduce RAD (Region Associated Differentially expressed genes), a user-friendly web tool to identify both proximal and distal region associated differentially expressed genes (DEGs). With DEGs and genomic regions of interest (gROI) as input, RAD maps the up- and down-regulated genes associated with any gROI and helps researchers to infer the regulatory function of these regions based on the distance of gROI to differentially expressed genes. RAD includes visualization of the results and statistical inference for significance.

Availability and implementation

RAD is implemented with Python 3.7 and run on a Nginx server. RAD is freely available at https://labw.org/rad as online web service.

Supplementary information

Supplementary data are available at Bioinformatics online.
Exact maximal reduction of stochastic reaction networks by species lumping
Authors: Cardelli Luca , Perez-Verona Isabel Cristina , Tribastone Mirco , Tschaikowski Max , Vandin Andrea , Waizmann Tabea
Published: January 2021

Abstrtact

Motivation

Stochastic reaction networks are a widespread model to describe biological systems where the presence of noise is relevant, such as in cell regulatory processes. Unfortunately, in all but simplest models the resulting discrete state-space representation hinders analytical tractability and makes numerical simulations expensive. Reduction methods can lower complexity by computing model projections that preserve dynamics of interest to the user.

Results

We present an exact lumping method for stochastic reaction networks with mass-action kinetics. It hinges on an equivalence relation between the species, resulting in a reduced network where the dynamics of each macro-species is stochastically equivalent to the sum of the original species in each equivalence class, for any choice of the initial state of the system. Furthermore, by an appropriate encoding of kinetic parameters as additional species, the method can establish equivalences that do not depend on specific values of the parameters. The method is supported by an efficient algorithm to compute the largest species equivalence, thus the maximal lumping. The effectiveness and scalability of our lumping technique, as well as the physical interpretability of resulting reductions, is demonstrated in several models of signaling pathways and epidemic processes on complex networks.

Availability and implementation

The algorithms for species equivalence have been implemented in the software tool ERODE, freely available for download from https://www.erode.eu.

Supplementary information

Supplementary data are available at Bioinformatics online.
Transanal total mesorectal excision and low anterior resection syndrome
Authors: van der Heijden J A G , Qaderi S M , Verhoeven R , Custers J A E , Klarenbeek B R , Maaskant-Braat A J G , de Wilt J H W ,   the PLCRC group, Beets G L , Belt E J Th , Berbée M , Beverdam F H , Blankenburgh R , Coene P P L O , de Groot J W B , de Hingh I H J T , de Vos A I , de Wilt J H W , Dekker J W T , Erdkamp F L G , Haringhuizen A W , Helgason H H , Hendriks M P , Hoekstra R , Ijzermans J N M , Jansen J , Kloppenberg F W H , Los M , Meijerink M R , Mekenkamp L J M , Nieboer P , Peeters K C M J , Peters N A J B , Polée M B , Verdaasdonk E G G , Quarles van Ufford-Mannesse P , Rietbroek R C , Schiphorst A H W , Schouten van der Velden A , Schrauwen R W M , Sie M P S , Simkens L , Sommeijer D W , Sonneveld D J A , Spierings L E A , Stockmann H B A C , Talsma K , ten Tije A J , Terheggen F , Tjin-A-Ton M L R , Valkenburg-van Iersel L B J , van Cruijsen H , van der Velden A M T , van Dodewaard-de Jong J M , van Lent A U G , van Voorthuizen T , Vermaas M , Vles W J , Vogelaar J F J , Zimmerman D D E , van Grevenstein H W M U , Vink G R
Published: January 2021

Background

Bowel dysfunction after rectal cancer surgery is common, with some experiencing low anterior resection syndrome (LARS) is common after rectal cancer surgery. This study examined if transanal total mesorectal excision (TaTME) has a similar risk of LARS and altered quality of life (QoL) as patients who undergo low anterior resection (LAR).

Methods

Patients who underwent TaTME or traditionally approached total mesorectal excision in a prospective colorectal cancer cohort study (2014–2019) were propensity score matched in a 1 : 1 ratio. LARS and QoL scores were assessed before and after surgery with a primary endpoint of major LARS at 12 months analysed for possible association between factors by logistic regression.

Results

Of 61 TaTME and 317 LAR patients eligible, 55 from each group were propensity score matched. Higher LARS scores (30.6 versus 25.4, P = 0.010) and more major LARS (65 versus 42 per cent, P = 0.013; OR 2.64, 95 per cent c.i. 1.22 to 5.71) were reported after TaTME. Additionally, QoL score differences (body image, bowel frequency, and embarrassment) were worse in the TaTME group.

Conclusions

TaTME may be associated with more severe bowel dysfunction than traditional approaches to rectal cancer.
Purchasing Power and Self-Determination: Social Worker Perspectives
Authors: Bailey Charlotte , Plath Debbie , Sharma Alankaar
Published: January 2021

The international policy trend towards personalised budgets, which is designed to offer people with disabilities purchasing power to choose services that suit them, is exemplified in the Australian National Disability Insurance Scheme (NDIS). This article examines how the ‘purchasing power’ afforded to service users through individualised budgets impacts on social work practice and the choice and self-determination of NDIS service users. Social workers’ views were sought on the alignment between the NDIS principles of choice and control and social work principles of participation and self-determination and how their social work practice has changed in order to facilitate client access to supports through NDIS budgets and meaningful participation in decision-making. A survey was completed by forty-five social workers, and in-depth semi-structured interviews were conducted with five of these participants. The findings identify how social workers have responded to the shortfalls of the NDIS by the following: interpreting information for clients; assisting service users to navigate complex service provision systems; supporting clients through goal setting, decision-making and implementation of action plans; and adopting case management approaches. The incorporation of social work services into the NDIS service model is proposed in order to facilitate meaningful choice and self-determination associated with purchasing power.
Debt Managers’ Reaction to Sovereign Risk in the Euro Area: Evidence and Policy Implications
Authors: Arnold Ivo J M
Published: January 2021

When sovereign spreads increase, debt managers in the euro area face a funding dilemma. They can either issue more short-term debt, thereby increasing roll-over risk, or issue long-term debt at higher borrowing costs. The latter choice may threaten debt sustainability. Using a sample of monthly data for 10 countries in the euro area, we measure how the share of short-term debt issuance reacts to bond yields, term spreads, default spreads, and money market spreads. We find that sovereign risk is a significant variable in debt reaction functions: higher default spreads increase the reliance on short-term funding, making the euro area more prone to funding crises in individual member states. As a solution to this problem, we discuss a proposal for an interest stabilization mechanism. By providing conditional interest subsidies to distressed countries, such a mechanism can maintain market access and avoid bad bond market equilibria. It will reduce the incentive of debt managers to shorten the maturity structure of public debt and thereby make the euro area less fragile (JEL codes: E43, F45, and H63).
Immuno-metabolic interfaces in cardiac disease and failure
Authors: Bertero Edoardo , Dudek Jan , Cochain Clement , Delgobo Murilo , Ramos Gustavo , Gerull Brenda , Higuchi Takahiro , Vaeth Martin , Zernecke Alma , Frantz Stefan , Hofmann Ulrich , Maack Christoph
Published: January 2021

The interplay between the cardiovascular system, metabolism, and inflammation plays a central role in the pathophysiology of a wide spectrum of cardiovascular diseases, including heart failure. Here, we provide an overview of the fundamental aspects of the interrelation between inflammation and metabolism, ranging from the role of metabolism in immune cell function to the processes how inflammation modulates systemic and cardiac metabolism. Furthermore, we discuss how disruption of this immuno-metabolic interface is involved in the development and progression of cardiovascular disease, with a special focus on heart failure. Finally, we present new technologies and therapeutic approaches that have recently emerged and hold promise for the future of cardiovascular medicine.
Profile shape variation and sexual dimorphism amongst middle-aged Northern Europeans
Authors: Kanavakis Georgios , Silvola Anna-Sofia , Halazonetis Demetrios , Lähdesmäki Raija , Pirttiniemi Pertti
Published: January 2021

Aim

To explore profile shape variation in a large population of middle-aged individuals and investigate features of sexual dimorphism.

Materials and methods

Facial profile photographs of 1776 individuals (964 females and 812 males; 46 years old), members of the Northern Finland Birth Cohort 1966 (NFBC1966), were uploaded and digitized with Viewbox software. Profile shape was defined with 47 landmarks (4 fixed and 43 sliding semi-landmarks). Digitized images were reoriented and scaled with Procrustes Superimposition, and shape variation was determined with a Principal Component Analysis.

Results

More than 90 per cent of profile shape variation was explained by Principal Components (PC) 1–9. PC1, explaining the largest amount of variation (33.1 per cent) described changes in facial convexity, slope of the forehead, lip, and chin protuberance. PC2 (23.1 per cent variation) was more related to vertical changes of the lower facial third and PC3 (11 per cent variation) primarily described changes in lip protrusion and nasal projection. Shape analysis showed a significant difference between the average female and the average male profile shape (P < 0.001); however, this was not evident upon visual observation. The shape variable most associated with sex was PC3 (η 2 = 0.245; P < 0.001), which described changes in lip prominence and in projection of the dorsal nasal surface. An additional discriminant analysis showed that profile shape predicted sex in 76 per cent of males and 79.6 per cent of females.

Conclusions

There is significant sexual dimorphism in facial profile among middle-aged adults. Profile shape variation was associated to changes in lip protrusion, nasal protuberance, and chin projection.