bluuebunny/crossref_metadata_2025 huggingface dataset:
Oral perception of the textural and flavor characteristics of soy‐cow blended emulsions
Authors: Wan Jie , Ningtyas Dian W. , Bhandari Bhesh , Liu Chengmei , Prakash Sangeeta
Published: October 2021

Soy‐cow blended milk is a potential nutritional beverage and raw material for dairy products. This study determined the particle size, flow, lubrication, flavor and sensory properties of cow milk, soy milk and their blends. Twenty‐one major volatile compounds were identified using solid‐phase microextraction gas chromatography (SPME‐GCMS) in cow milk and soy milk. Among all the compounds detected in the milk samples, hexanal, associated with off flavor was found highest in soymilk followed by cow milk and blended milk. From confocal images, soy‐cow blended milk at a ratio of 1:1 showed a homogenous distribution of small fat globules and protein compared to the soy milk and cow milk. The addition of soy milk to cow milk lowers the particle size although not significantly (p > .05) and decreases the viscosity of blended milk. Cow milk was the most viscous (2.66 mPa·s at 50 s−1) with large particles (0.48 μm) observed from confocal images. However, soymilk was found to have better lubrication properties (boundary regime) with a lower friction coefficient (~0.30) compared to cow milk (~0.40) and blended milk (~0.50) at low entrainment speed (0.1–2 mm/s). The sensory panel ranked cow milk as creamier and more viscous while soymilk was perceived as more astringent with beany flavor. Overall, a proportion of 3:7 soy‐cow blended milk was more acceptable than the other two blended milks with less beany flavor, as confirmed by the lower amount of hexanal from gas chromatography mass spectrometer.
Symbiont shuffling induces differential DNA methylation responses to thermal stress in the coral Montastraea cavernosa
Authors: Rodriguez‐Casariego Javier A. , Cunning Ross , Baker Andrew C. , Eirin‐Lopez Jose M.
Published: October 2021

Algal symbiont shuffling in favour of more thermotolerant species has been shown to enhance coral resistance to heat‐stress. Yet, the mechanistic underpinnings and long‐term implications of these changes are poorly understood. This work studied the modifications in coral DNA methylation, an epigenetic mechanism involved in coral acclimatization, in response to symbiont manipulation and subsequent heat stress exposure. Symbiont composition was manipulated in the great star coral Montastraea cavernosa through controlled thermal bleaching and recovery, producing paired ramets of three genets dominated by either their native symbionts (genus Cladocopium) or the thermotolerant species (Durusdinium trenchi). Single‐base genome‐wide analyses showed significant modifications in DNA methylation concentrated in intergenic regions, introns and transposable elements. Remarkably, DNA methylation changes in response to heat stress were dependent on the dominant symbiont, with twice as many differentially methylated regions found in heat‐stressed corals hosting different symbionts (Cladocopium vs. D. trenchii) compared to all other comparisons. Interestingly, while differential gene body methylation was not correlated with gene expression, an enrichment in differentially methylated regions was evident in repetitive genome regions. Overall, these results suggest that changes in algal symbionts favouring heat tolerant associations are accompanied by changes in DNA methylation in the coral host. The implications of these results for coral adaptation, along with future avenues of research based on current knowledge gaps, are discussed in the present work.
Challenges of persons with multiple sclerosis on ocrelizumab treatment during COVID‐19 pandemic
Authors: Baba Cavid , Yigit Pinar , Dastan Seda , Hancer Pelin , Sagici Ozge , Ozakbas Serkan , Abasiyanik Zuhal
Published: October 2021

Background

Coronavirus disease of the 2019 pandemic caused much fear among people with chronic diseases and those on immunosuppressant treatment because of spreading knowledge that the infection has a fatal course in these populations. People with Multiple Sclerosis on ocrelizumab treatment share this fear too. We aimed to investigate treatment and lifestyle changes of people with multiple sclerosis on ocrelizumab treatment during the lockdown.

Methods

We surveyed 199 of our registered multiple sclerosis patients on ocrelizumab treatment by phone.

Results

In this survey, delays in treating 22 (11%) patients were not caused by fear of immunosuppressive drug use but rather by the general fear of contracting a fatal disease, which is the case during traveling and hospital visits. There was a positive correlation between living alone and treatment delay (P = .029), emphasizing the role of family support or just the presence of another person during the pandemic.

Conclusion

Vaccines might soon solve the pandemic's issue, which is not the case with multiple sclerosis progression, so we should think twice before discontinuing the treatment.
A concept analysis of role ambiguity experienced by hospital nurses providing bedside nursing care
Authors: Cengiz Adem , Yoder Linda H. , Danesh Valerie
Published: October 2021

The concept of role ambiguity, despite its wide application in nursing research, lacks a clear definition and conceptualization, resulting in inconsistencies about how it is defined, operationalized, and applied in research. The purpose of this paper was to analyze and define the concept of role ambiguity among hospital nurses providing nursing care, using the concept analysis method developed by Walker and Avant. The three defining attributes of role ambiguity were lack of information (information deficiency), lack of clarity, and unpredictability. Antecedents included lack of clear role definitions, lack of education/training, communication problems, supervisory behaviors and support, organizational culture, practice environment conditions, experience, group cohesiveness, and preferred work setting. The consequences of role ambiguity included increased stress, lack of organizational commitment, job dissatisfaction, burnout, and increased intent to leave. This concept analysis provides a clear conceptual definition to better understand role ambiguity among hospital nurses along with implications for nurse leaders, educators, clinicians, and researchers to support nurses and guide future research. This paper further emphasizes the importance of nurse‐manager relationships in reducing the experience of role ambiguity among hospital nurses.
Motor sequence learning in a goal‐directed stepping task in persons with multiple sclerosis: a pilot study
Authors: Veldkamp Renee , Moumdjian Lousin , van Dun Kim , Six Joren , Vanbeylen Antoine , Kos Daphne , Feys Peter
Published: October 2021

Motor sequence learning in persons with multiple sclerosis (pwMS) and healthy controls (HC) under implicit or explicit learning conditions has not yet been investigated in a stepping task. Given the prevalent cognitive and mobility impairments in pwMS, this is important in order to understand motor learning processes and optimize rehabilitation strategies. Nineteen pwMS (the Expanded Disability Status Scale = 3.4 ± 1.2) and 18 HC performed a modified serial reaction time task by stepping as fast as possible on a stepping tile when it lit up, either with (explicit) or without (implicit) knowledge of the presence of a sequence beforehand. Motor sequence learning was studied by examining response time changes and differences between sequence and random blocks during the learning session (acquisition), 24 h later (retention), and in three dual‐task (DT) conditions at baseline and retention (automaticity) using subtracting sevens, verbal fluency, and vigilance as concurrent cognitive DTs. Response times improved and were lower for the sequenced compared with the random blocks at the post‐ and retention tests (P's <0.001). Response times during DT conditions improved after learning, but DT cost improved only for the subtracting sevens DT condition. No differences in learning were observed between learning conditions or groups. This study showed motor sequence learning, by acquisition and retention, in a stepping task in pwMS with motor impairments, to a similar degree as HC and regardless of learning conditions. Whether automaticity increased remains unclear.
Changing pattern of pediatric anaphylaxis in Hong Kong, 2010–2019
Authors: Leung Agnes S. Y. , Li Rebecca M. Y. , Au Ann W. S. , Rosa Duque Jaime Sou , Ho Po Ki , Chua Gilbert T. , Wong Chi Hang , Luk David C. K. , Kwan Mike Y. W. , Yau Yat Sun , Wong Gary W. K. , Leung Ting Fan
Published: October 2021

Background

Anaphylaxis is a significant health burden in most Western countries, but there are little published data on the incidence and pattern of anaphylaxis in Asia. We aim to determine the incidence rate and pattern of anaphylaxis over the past decade among the pediatric population in Hong Kong.

Methods

Medical records of patients presenting with allergy‐related symptoms during the period 2010 to 2019 were examined. Pediatric patients aged below 18 years who fulfilled the diagnostic criteria for anaphylaxis laid out by the NIAID/FAAN were analyzed. Incidence rates were calculated using population statistics as the denominator. All information pertaining to the anaphylaxis events and patients’ characteristics was retrieved using standardized data collection forms.

Results

The overall 10‐year estimated incidence of anaphylaxis was 9.76 per 100,000 person‐years, with a rising trend of anaphylaxis incidence across time. Food‐induced anaphylaxis accounted for the majority of hospital presentations, of which peanut and shellfish were the top food triggers in our population. Majority of anaphylaxis episodes were of Grade 4 severity, and young age was a significant predictor of severe allergic reactions. Half of the anaphylaxis episodes were misdiagnosed and adrenaline was only utilized in 42.2% of cases, of which 9.4% were administered adrenaline prior to hospital arrival.

Conclusions

An increasing trend of anaphylaxis incidence over the past decade is evident in Hong Kong children, with a discrepantly low accuracy in diagnosis and suboptimal management of anaphylaxis. There is a pressing need to heighten public and physicians’ awareness of the distinctive features of anaphylaxis in the pediatric age‐group.
Modelling extreme wide‐angle lens cameras
Authors: Lichti Derek D. , Tredoux Wynand , Maalek Reza , Helmholz Petra , Radovanovic Robert
Published: October 2021

The use of consumer cameras fitted with extreme wide‐angle (EWA) lenses for photogrammetric measurement is increasing. Conventional modelling of EWA systems relies on the pinhole camera model and up to five radial lens distortion terms. Aiming to reduce model complexity, this paper reports on an investigation into an alternate approach using fisheye lens models for EWA systems, despite them not falling strictly into the fisheye category. Four fisheye models were tested on four different cameras under laboratory conditions. The self‐calibration results show superior model fit for all fisheye models over the pinhole‐plus‐radial model in terms of residual RMS. The number of radial distortion terms required for the fisheye models was lower in all cases, so model complexity was reduced. Independent assessment revealed very similar 3D reconstruction accuracy for all models. The results suggest that fisheye modelling is an advantageous alternative for EWA lens systems.
Nutrient loading Artemisia cana seedlings in greenhouse increases nitrogen tissue content and post‐outplanting survival
Authors: Watkinson Autumn D. , Naeth M. Anne , Pruss Shelley D.
Published: October 2021

Sagebrush (Artemisia) is a vital habitat component for many grassland species and continued loss, fragmentation, and degradation of sagebrush habitats has increased the need for their restoration. Conventional revegetation methods have resulted in extremely low plant establishment and survival inhibiting the success of sagebrush restoration efforts. During greenhouse production, we sought to improve Artemisia cana seedling quality and post‐planting growth and survival by increasing tissue nutrient content. We conducted a preliminary 12‐week greenhouse study and a subsequent 26‐week greenhouse + 2‐season field study, investigating 12 nutrient loading treatments (application of 70, 105, 175, and 245 mg nitrogen [N] plant−1 at single, constant, exponential, and modified exponential rates). Nitrogen content of seedling leaves and roots at 26 weeks indicated that application of 175 and 245 mg N plant−1 on exponential or modified exponential dosing schedules resulted in nutrient‐loaded seedlings. Seedlings were planted into a cleared plot in Grasslands National Park, SK. After 60 weeks in the field, nutrient‐loaded seedlings had significantly greater survival (75%) than non‐loaded seedlings (65%) and greater crown area (1,351 vs. 1,004 cm2). Rhizomatous reproduction (sprouting) occurred within 4 weeks of planting. New sprouts had disproportionately larger crown areas (2,237 cm2) and greater survival (86%) than planted seedlings. Nutrient loading was an effective method to overcome high mortality that has inhibited restoration outcomes. Where plant materials and resources are limited, nutrient loading could be especially useful by improving seedling survival and crown area without increasing planting densities.
Analysis of make-to-stock queues with general processing times and start-up and lost sales costs
Authors: Sinem Özkan  , Önder Bulut
Published: October 2021

We consider a make-to-stock environment with a single production unit that corresponds to a single machine or a line. Production and hence inventory are controlled by the two-critical-number policy. Production times are independent and identically distributed general random variables and demands are generated according to a stationary Poisson process. We model this production-inventory system as an M/G/1 make-to-stock queue. The main contribution of the study is to extend the control of make-to-stock literature by considering general production times, lost sales and fixed production costs at the same time. We characterize the long-run behaviour of the system and also propose a simple but very effective approximation to calculate the control parameters of the two-critical-number policy. An extensive numerical study exhibits the effects of the production time distribution and the system parameters on the policy control levels and average system cost.
Child access prevention legislative language and pediatric firearm injury rates
Authors: James Bradford , Khallouq Bertha Ben , Swana Hubert
Published: October 2021

Backgroud

Firearm injuries are a significant public health problem facing young people in the USA. In 2015, a total of 16 878 people under 19 years old were injured or killed by firearms. To reduce firearm injuries, 29 states and Washington, DC have enacted child access prevention (CAP) legislation. CAP legislation is intended to reduce the likelihood of a minor obtaining a weapon and subsequent injury or death. This study evaluates the impact of CAP legislation based on language of the legislation, specifically it evaluates a relationship of the legal threshold of liability and the number of firearm injuries per capita of minors.

Methods

Data were collected from the Web-based Injury Statistics Query and Reporting System for patients less than 19 years of age who presented to emergency departments with firearm injuries in 2016. The Giffords Law Center classification was used to group states into three categories (strong/weak/no CAP) based on CAP language. Differences of firearm-related injury rates per capita were assessed.

Results

When controlling for population, states with CAP legislation had a 22% decrease in firearm injuries per capita compared with states without CAP legislation. States with ‘strong’ CAP legislation had a 41% decrease in firearm injuries per capita compared with states with ‘weak’ or no CAP legislation when controlling for population.

Conclusions

States with ‘strong’ CAP legislation had lower pediatric firearm injury rates per capita, but more complete data and further studies are needed to evaluate this relationship as well as other factors that may impact firearm injury rates.
Motor Intention Decoding from the Upper Limb by Graph Convolutional Network Based on Functional Connectivity
Authors: Feng Naishi , Hu Fo , Wang Hong , Zhou Bin
Published: October 2021

Decoding brain intention from noninvasively measured neural signals has recently been a hot topic in brain-computer interface (BCI). The motor commands about the movements of fine parts can increase the degrees of freedom under control and be applied to external equipment without stimulus. In the decoding process, the classifier is one of the key factors, and the graph information of the EEG was ignored by most researchers. In this paper, a graph convolutional network (GCN) based on functional connectivity was proposed to decode the motor intention of four fine parts movements (shoulder, elbow, wrist, hand). First, event-related desynchronization was analyzed to reveal the differences between the four classes. Second, functional connectivity was constructed by using synchronization likelihood (SL), phase-locking value (PLV), H index (H), mutual information (MI), and weighted phase-lag index (WPLI) to acquire the electrode pairs with a difference. Subsequently, a GCN and convolutional neural networks (CNN) were performed based on functional topological structures and time points, respectively. The results demonstrated that the proposed method achieved a decoding accuracy of up to 92.81% in the four-class task. Besides, the combination of GCN and functional connectivity can promote the development of BCI.
Cascade events in geographical space
Authors: Ordoñez Dylan Marcus T. , Batac Rene C.
Published: October 2021

In this paper, we present a simple discrete model of cascade behavior in an actual geographical space with built environments. By simultaneously triggering and relaxing random locations in a network of Voronoi cells interacting via the gravity model, we observe nontrivial statistics with heavy-tailed distributions of cells and actual area extents involved in the cascade. The distributions of these affected areas follow unimodal statistics, unlike the other externally-driven models operating over uniform neighborhoods that exhibit power-laws. Majority of the cascades are limited within the immediate neighborhoods of adjacent Voronoi cells, even for sufficiently large triggering magnitudes. The results are viewed from the perspective of inhomogeneous driving in sandpile-based models, and benchmarked with distributions obtained in other geographic datasets. The method offers a complexity perspective into the generation of large-scale events in physical and intangible flows, and explains their origins from cascaded accumulations of slow, random, and intermittent processes.
First-principles studies of the elastic and magnetic properties of monolayer CrN
Authors: Ma Tai , Wang Jia , Li Xu , Pu Min
Published: October 2021

Two-dimensional (2D) materials with robust ferromagnetism properties have high potentials for application in the field of spintronics. However, extensively pursued 2D sheets, including pure graphene, monolayer BN, and layered transition metal dichalcogenides, are either nonmagnetic or weakly magnetic. The elastic, electronic and magnetic properties of monolayer CrN are calculated using the plane wave pseudo potential method based on first-principles density function theory. Upon determining through calculation that the structure of the monolayer CrN nanosheet is stable, its layer modulus [Formula: see text] shows that its strain resistance is stronger than that of graphene. Through strain analysis, materials with a monolayer CrN type of structure can be obtained. It is determined that 10% of the change in equilibrium area is still applicable to the 2D EOS, showing that this structure is quite stable. The spin-polarized electronic band structure is also calculated under different plane symmetry strains. The plane strain can be used to effectively adjust the metallic and magnetic properties of the material. Analyses of the band structure and density of states reveal that this material is half-metallic, where the origin of the ferromagnetism is related to [Formula: see text]–[Formula: see text] exchange interactions between the Cr and N atoms. Monolayer CrN has semimetallic properties and strong ferromagnetic (FM) properties. The FM effect can enhance the stability of the material. The results show that monolayer CrN is a semimetallic material with good elastic properties and a strong FM property. This material is therefore expected to have good application rospects in the field of spin electronics.
Velocity of transverse sound oscillations in the metals
Authors: Stupka Anton , Kovalchuk Olena
Published: October 2021

The Bohm–Staver description of sound waves in metals in the jellium model is generalized by taking into account not only the self-consistent electric field but also the second correlation moment of internal electric field that provides shear elasticity. The system of linearized equations that contains the second correlation moment of the field as a new variable is built. The wave equation is worked out and the velocities of longitudinal and transverse sound are found. The estimation of the field correlation value through the sublimation heat and the electronic Fermi-gas energy is offered for the metals. The velocities of transverse sound are found, which matches well the velocity obtained from the shear modules.
A bound for the class of nilpotent symplectic alternating algebras
Authors: Sorkatti Layla
Published: October 2021

We continue developing the theory of nilpotent symplectic alternating algebras. The algebras of upper bound nilpotent class, that we call maximal algebras, have been introduced and well studied. In this paper, we continue with the external case problem of algebras of minimal nilpotent class. We show the existence of a subclass of algebras over a field [Formula: see text] that is of certain lower bound class that depends on the dimension only. This suggests a minimal bound for the class of nilpotent algebras of dimension [Formula: see text] of rank [Formula: see text] over any field.
Analysis of fully discrete, quasi non-conforming approximations of evolution equations and applications
Authors: Berselli Luigi C. , Kaltenbach Alex , Růžička Michael
Published: October 2021

In this paper, we consider fully discrete approximations of abstract evolution equations, by means of a quasi non-conforming spatial approximation and finite differences in time (Rothe–Galerkin method). The main result is the convergence of the discrete solutions to a weak solution of the continuous problem. Hence, the result can be interpreted either as a justification of the numerical method or as an alternative way of constructing weak solutions. We set the problem in the very general and abstract setting of pseudo-monotone operators, which allows for a unified treatment of several evolution problems. The examples — which fit into our setting and which motivated our research — are problems describing the motion of incompressible fluids, since the quasi non-conforming approximation allows to handle problems with prescribed divergence. Our abstract results for pseudo-monotone operators allow to show convergence just by verifying a few natural assumptions on the operator time-by-time and on the discretization spaces. Hence, applications and extensions to several other evolution problems can be easily performed. The results of some numerical experiments are reported in the final section.
Hyperbolic compartmental models for epidemic spread on networks with uncertain data: Application to the emergence of COVID-19 in Italy
Authors: Bertaglia Giulia , Pareschi Lorenzo
Published: October 2021

The importance of spatial networks in the spread of an epidemic is an essential aspect in modeling the dynamics of an infectious disease. Additionally, any realistic data-driven model must take into account the large uncertainty in the values reported by official sources such as the amount of infectious individuals. In this paper, we address the above aspects through a hyperbolic compartmental model on networks, in which nodes identify locations of interest such as cities or regions, and arcs represent the ensemble of main mobility paths. The model describes the spatial movement and interactions of a population partitioned, from an epidemiological point of view, on the basis of an extended compartmental structure and divided into commuters, moving on a suburban scale, and non-commuters, acting on an urban scale. Through a diffusive rescaling, the model allows us to recover classical diffusion equations related to commuting dynamics. The numerical solution of the resulting multiscale hyperbolic system with uncertainty is then tackled using a stochastic collocation approach in combination with a finite volume Implicit–Explicit (IMEX) method. The ability of the model to correctly describe the spatial heterogeneity underlying the spread of an epidemic in a realistic city network is confirmed with a study of the outbreak of COVID-19 in Italy and its spread in the Lombardy Region.
Black hole cannibalism
Authors: Bao Ning , Wildenhain Elizabeth
Published: October 2021

In this paper, we consider a version of the Hayden–Preskill thought experiment in which the message thrown into the black hole is itself a smaller black hole. We then discuss the implications of the existence of a recovery channel for this black hole message at asymptotic infinity, resulting in a sharpening of the black hole information paradox for observers who never need to approach a horizon. We suggest decoherence mechanisms as a way of resolving this sharpened paradox.
Explicit values of the oscillation bounds for linear delay differential equations with monotone argument
Authors: Pituk Mihály , Stavroulakis Ioannis P. , Stavroulakis John Ioannis
Published: October 2021

The problem of finding the oscillation bounds for first-order linear delay differential equations has been in the focus of the oscillation theory for a long time. Although numerous estimates for the oscillation bounds are available in the literature, their explicit values were not known. In this paper, we give the oscillation bounds explicitly in terms of the real branches of the Lambert [Formula: see text] function.
Optimization of Nonlinear Unbalanced Flexible Rotating Shaft Passing Through Critical Speeds
Authors: Amirzadegan Sadegh , Rokn-Abadi Mohammad , Firouz-Abadi R. D.
Published: October 2021

This work studies the nonlinear oscillations of an elastic rotating shaft with acceleration to pass through the critical speeds. A mathematical model incorporating the Von-Karman higher-order deformations in bending is developed to investigate the nonlinear dynamics of rotors. A flexible shaft on flexible bearings with springs and dampers is considered as rotor system for this work. The shaft is modeled as a beam and the Euler–Bernoulli beam theory is applied. The kinetic and strain energies of the rotor system are derived and Lagrange method is then applied to obtain the coupled nonlinear differential equations of motion for 6 degrees of freedom. In order to solve these equations numerically, the finite element method (FEM) is used. Furthermore, for different bearing properties, rotor responses are examined and curves of passing through critical speeds with angular acceleration due to applied torque are plotted. Then the optimal values of bearing stiffness and damping are calculated to achieve the minimum vibration amplitude, which causes to pass easier through critical speeds. It is concluded that the value of damping and stiffness of bearing change the rotor critical speeds and also significantly affect the dynamic behavior of the rotor system. These effects are also presented graphically and discussed.
Mechanical Modeling and General Analytical Solution for the Dynamic Buckling of Plane Structures Using a Beam-Column Element with Varying End Restraints
Authors: Beldjazia Aissam , Adman Redouane , Slimani Adel , Saidani Messaoud , Belaid Toufik , Ammari Fatiha
Published: October 2021

The stability of structures is an important aspect that the designer must pay particular attention to in order to ensure safety against collapse. This investigation is concerned with analytical and numerical analyses of the dynamic buckling of plane structures. A rigorous mechanical model is proposed, consisting of a beam-column element with nodal ends possessing two rotational springs of rigidities acting in parallel with the bending stiffness of the beam-column. The model is first analyzed with respect to the dynamic behavior by investigating the influence of the variation in the stiffness of the nodal springs on the fundamental frequency of the proposed mechanical model. Compression axial loading is applied to the beam-column in order to study the nonlinear dynamic behavior by introducing buckling. This novel approach is used to highlight the interaction between the fundamental frequency and the critical buckling load. Simple examples are treated using the approach and the results are compared with those obtained from a global analysis. The results revealed that it is possible to reproduce the stability analysis of a global structure by simply analyzing a target element, taking into account all elements adjacent to it with less than 1% error on the results.
Comparative Analysis of Different Data Replication Strategies in Cloud Environment
Authors: Sasikumar K. , Vijayakumar B.
Published: October 2021

In this paper, we performed a comparative study of the different data replication strategies such as Adaptive Data Replication Strategy (ADRS), Dynamic Cost Aware Re-Replication and Rebalancing Strategy (DCR2S) and Efficient Placement Algorithm (EPA) in the cloud environment. The implementation of these three techniques is done in JAVA and the performance analysis is conducted to study the performance of those replication techniques by various parameters. The parameters used for the performance analysis of these three techniques are Load Variance, Response Time, Probability of File Availability, System Byte Effective Rate (SBER), Latency, and Fault Ratio. From the analysis, it is evaluated that by varying the number of file replicas, it shows deviations in the outcomes of these parameters. The comparative results were also analyzed.
Noncatastrophic convolutional codes over a finite ring
Authors: Napp Diego , Pinto Raquel , Rocha Conceição
Published: October 2021

Noncatastrophic encoders are an important class of polynomial generator matrices of convolutional codes. When these polynomials have coefficients in a finite field, these encoders have been characterized as polynomial left prime matrices. In this paper, we study the notion of noncatastrophicity in the context of convolutional codes when the polynomial matrices have entries in the finite ring [Formula: see text]. In particular, we study the notion of zero left prime in order to fully characterize noncatastrophic encoders over the finite ring [Formula: see text]. The second part of the paper is devoted to investigate free and column distance of convolutional codes that are free finitely generated [Formula: see text]-modules. We introduce the notion of [Formula: see text]-degree and provide new bounds on the free distances and column distance. We show that this class of convolutional codes is optimal with respect to the column distance and to the free distance if and only if its projection on [Formula: see text] is.
Support vector machine-based prediction of pore-forming toxins (PFT) using distributed representation of reduced alphabets
Authors: Bhosale Hrushikesh , Ramakrishnan Vigneshwar , Jayaraman Valadi K.
Published: October 2021

Bacterial virulence can be attributed to a wide variety of factors including toxins that harm the host. Pore-forming toxins are one class of toxins that confer virulence to the bacteria and are one of the promising targets for therapeutic intervention. In this work, we develop a sequence-based machine learning framework for the prediction of pore-forming toxins. For this, we have used distributed representation of the protein sequence encoded by reduced alphabet schemes based on conformational similarity and hydropathy index as input features to Support Vector Machines (SVMs). The choice of conformational similarity and hydropathy indices is based on the functional mechanism of pore-forming toxins. Our methodology achieves about 81% accuracy indicating that conformational similarity, an indicator of the flexibility of amino acids, along with hydrophobic index can capture the intrinsic features of pore-forming toxins that distinguish it from other types of transporter proteins. Increased understanding of the mechanisms of pore-forming toxins can further contribute to the use of such “mechanism-informed” features that may increase the prediction accuracy further.
Quantum information distance
Authors: Dai Songsong
Published: October 2021

In this paper, we give a definition for quantum information distance. In the classical setting, information distance between two classical strings is developed based on classical Kolmogorov complexity. It is defined as the length of a shortest transition program between these two strings in a universal Turing machine. We define the quantum information distance based on Berthiaume et al.’s quantum Kolmogorov complexity. The quantum information distance between qubit strings is defined as the length of the shortest quantum transition program between these two qubit strings in a universal quantum Turing machine. We show that our definition of quantum information distance is invariant under the choice of the underlying quantum Turing machine.
Divide and Conquer: A Quick Scheme for Symbolic Regression
Authors: Luo Changtong , Chen Chen , Jiang Zonglin
Published: October 2021

Symbolic regression (SR), as a special machine learning method, can produce mathematical models with explicit expressions. It has received increasing attention in recent years. However, finding a concise, accurate expression is still challenging because of its huge search space. In this work, a divide and conquer (D&C) scheme is proposed. It tries to divide the search space into a number of orthogonal sub-spaces based on the separability feature inferred from the sample data (dividing process). For each sub-space, a sub-function is learned (conquering process). The target model function is then reconstructed with the sub-functions according to their separability patterns. To this end, a separability pattern detecting technique, bi-correlation test (Bi-CT), is also proposed. Note that the sub-functions could be determined by any of the existing SR methods, which makes D&C easy to use. The D&C powered SR has been tested on many symbolic regression problems, and the study shows that D&C can help SR to get the target function more quickly and reliably.
The mean value of the generalized Dirichlet L-functions with the weight of the Gauss sums
Authors: Niu Yana , Ma Rong , Zhang Yulong , Jiang Peilin
Published: October 2021

Let [Formula: see text] be an integer, and let [Formula: see text] denote a Dirichlet character modulo [Formula: see text]. For any real number [Formula: see text], we define the generalized Dirichlet [Formula: see text]-function as [Formula: see text] where [Formula: see text] with [Formula: see text] and [Formula: see text] both real. It can be extended to all [Formula: see text] using analytic continuation. For any integer [Formula: see text], the famous Gauss sum [Formula: see text] is defined as [Formula: see text] where [Formula: see text]. This paper uses analytic methods to study the mean value properties of the generalized Dirichlet [Formula: see text]-functions with the weight of the Gauss sums, and a sharp asymptotic formula is obtained.
Periodic solutions of Hilbert’s fourth problem
Authors: Álvarez Paiva J. C. , Barbosa Gomes J.
Published: October 2021

It is shown that a possibly irreversible [Formula: see text] Finsler metric on the torus, or on any other compact Euclidean space form, whose geodesics are straight lines is the sum of a flat metric and a closed [Formula: see text]-form. This is used to prove that if [Formula: see text] is a compact Riemannian symmetric space of rank greater than one and [Formula: see text] is a reversible [Formula: see text] Finsler metric on [Formula: see text] whose unparametrized geodesics coincide with those of [Formula: see text], then [Formula: see text] is a Finsler symmetric space.
Review on bimetallic catalysts for electrocatalytic denitrification
Authors: Bai Zehui , Tang Zixuan , Zhang Bin , Jin Shengming , Xu Jianlong , Chang Xinghua , Zhang Yi
Published: October 2021

Accelerated industrialization disrupts the global nitrogen cycle, resulting in alarmingly increased nitrate in groundwater and other water bodies. Electrocatalytic nitrate reduction (NO3RR) with high automation can effectively remove nitrate from polluted water, thus avoiding nitrate accumulation. However, the sluggish cathode reaction kinetics severely hampered the efficiency of NO3RR. Developing high-performance cathode catalysts is of great significance for boosting NO3RR. Compared with pure metal catalysts, bimetal catalysts can further improve the cathode activity and selectivity to nitrogen or ammonia in the electrocatalytic process, attracting extensive research interest. In this review, we discussed the background of denitrification requirements and the development status of bimetallic denitrification catalyst. Metallic cathode catalysts, such as noble-metal, 3d transition metal, main group metal, are described emphatically. Finally, present challenges and future outlook on bimetallic denitrification catalysts are depicted.
Transformation of Schwertmannite to erdite nanorod via an alkaline dissolution–recrystallization process for the effective adsorption of oxytetracycline
Authors: Liu Jiancong , Liu Yanwen , Zhang Zhonglei , Wang Xiaoshu , Wang Ying , Zhu Jia , Chang Ming , Wang Lei
Published: October 2021

Schwertmannite (schw) is a common Fe-bearing mineral in the precipitation of mine wastewater and/or steel pickling wastewater. It could be easily converted to goethite and hematite via heating or hydrothermal treatment and could be used as adsorbent to remove contaminants from wastewater. Herein, the spherical schw was converted into erdite nanorod by a simple hydrothermal method with the addition of Na2S. Schw was spherical particle with a size of 0.4–1.5 [Formula: see text]m. After treatment, it was converted to erdite nanorod particles with 100 nm diameter and 200 nm length. By adding MnO2 at the [Formula: see text] ratio of 1, erdite nanorod grew radially to 1–1.5 [Formula: see text]m, whereas MnO2 was reductively dissolved and recrystallized to rambergite. In the absence of Fe, MnO2 was directly transformed to octahedral alabandite. The product EN-0, prepared without MnO2, showed the optimal [Formula: see text] of oxytetracycline (OTC, 7479.6 mg/g), which was 12 times that of schw. In OTC-bearing solution, erdite was unstable and automatically hydrolyzed to generate Fe–SH/Fe–OH-bearing flocs, and it exhibited abundant surface functional groups for OTC adsorption. Subsequently, the hydroxyl and amino groups on the side chain of OTC would also be complexed with the Fe–SH group to generate an OTC–Fe–S ligand, in the form of flake-like particles with a smooth surface. The formed Mn-bearing minerals, for example, rambergite and alabandite, also complexed with OTC as OTC–Mn–S ligands to form quadrangular prism with shoulder and length of 10 [Formula: see text]m and 20–100 [Formula: see text]m, respectively. Spherical schw was converted into a well-crystallized erdite nanorod with the addition of MnO2, and the product showed potential applications in OTC-bearing wastewater treatment.
Enhanced water durability of phosphor-in-glass (PiG) basing on SnCl2–P2O5 glass matrix induced by adding ZnO
Authors: Xu Da , Wang Wei , Zhang Zhiwei , Mao Zhiyong , Wang Dajian
Published: October 2021

Phosphor-in-glass (PiG) composed of glass matrix and the embedded phosphor particles has been intensively developed to meet the requirement of high-power LED lighting sources. P2O5-based glass matrices are the promising candidates to fabricate high luminescence PiG in view of their low-melting temperature to avoid the erosion of phosphor by glass melting, however, their poor chemical durability limited the practical application. In this work, the water durability of PiG basing on SnCl2–P2O5–ZnO glass matrix embedded with YAG: Ce[Formula: see text] phosphor is demonstrated. With the addition of ZnO, the water durability of SnCl2–P2O5- based PiG is enhanced significantly without obvious loss of light output. The influence of ZnO addition with variable contents on the microstructure, photoluminescent properties and the water durability of the obtained PiG is investigated through a series of characterizations. The obvious improvement of the water erosion resistance induced by adding ZnO provides an optional route to develop higher stability, lead-free, cost-effective low-melting point P2O5-based glass matrix for fabrication of high performance PiG materials.
Transitivity of trees
Authors: Samuel Libin Chacko , Joseph Mayamma
Published: October 2021

For a graph [Formula: see text], a partition [Formula: see text] of the vertex set [Formula: see text] is a transitive partition if [Formula: see text] dominates [Formula: see text] whenever [Formula: see text]. The transitivity [Formula: see text] of a graph [Formula: see text] is the maximum order of a transitive partition of [Formula: see text]. For any positive integer [Formula: see text], we characterize the smallest tree with transitivity [Formula: see text] and obtain an algorithm to determine the transitivity of any tree of finite order.
Structural, Electronic, Magnetic and Mechanical Properties and Magnetocaloric Effect of the Full-Heusler Co2MnGa
Authors: Labidi S. , Masrour R. , Jabar A.
Published: October 2021

Structural, electronic, magnetic and mechanical properties of the Co2MnGa have been calculated with functional density theory using full potential linear augmented plane wave method as implemented in the Wien2k code. Exchange correlation effects for these properties are treated by generalized gradient approximation while for electronic and magnetic properties, in addition to (WC-GGA) correction, mBJ-GGA scheme was also applied. The stiffness constant of the spin wave and the Curie temperature are calculated. Moreover, mechanical parameters included three elastic constants, compression modulus, Young’s modulus and shear modulus are also investigated. This theoretical study provides detailed information on the compound Co2MnGa, in different aspects and can also provide information on the application of this material. Obtained data from ab initio calculations are used as input for Monte Carlo simulations to study the magnetic properties and magnetocaloric effect. Transition temperature, magnetic entropy change, adiabatic temperature change and relative cooling power were found.
On the asymptotic behavior of the eigenvalue distribution of block correlation matrices of high-dimensional time series
Authors: Loubaton Philippe , Mestre Xavier
Published: October 2021

We consider linear spectral statistics built from the block-normalized correlation matrix of a set of M mutually independent scalar time series. This matrix is composed of [Formula: see text] blocks. Each block has size [Formula: see text] and contains the sample cross-correlation measured at L consecutive time lags between each pair of time series. Let N denote the total number of consecutively observed windows that are used to estimate these correlation matrices. We analyze the asymptotic regime where [Formula: see text] while [Formula: see text], [Formula: see text]. We study the behavior of linear statistics of the eigenvalues of this block correlation matrix under these asymptotic conditions and show that the empirical eigenvalue distribution converges to a Marcenko–Pastur distribution. Our results are potentially useful in order to address the problem of testing whether a large number of time series are uncorrelated or not.
Random Toeplitz matrices: The condition number under high stochastic dependence
Authors: Manrique-Mirón Paulo
Published: October 2021

In this paper, we study the condition number of a random Toeplitz matrix. As a Toeplitz matrix is a diagonal constant matrix, its rows or columns cannot be stochastically independent. This situation does not permit us to use the classic strategies to analyze its minimum singular value when all the entries of a random matrix are stochastically independent. Using a circulant embedding as a decoupling technique, we break the stochastic dependence of the structure of the Toeplitz matrix and reduce the problem to analyze the extreme singular values of a random circulant matrix. A circulant matrix is, in fact, a particular case of a Toeplitz matrix, but with a more specific structure, where it is possible to obtain explicit formulas for its eigenvalues and also for its singular values. Among our results, we show the condition number of a non-symmetric random circulant matrix [Formula: see text] of dimension [Formula: see text] under the existence of the moment generating function of the random entries is [Formula: see text] with probability [Formula: see text] for any [Formula: see text], [Formula: see text]. Moreover, if the random entries only have the second moment, the condition number satisfies [Formula: see text] with probability [Formula: see text]. Also, we analyze the condition number of a random symmetric circulant matrix [Formula: see text]. For the condition number of a random (non-symmetric or symmetric) Toeplitz matrix [Formula: see text] we establish [Formula: see text], where [Formula: see text] is the minimum singular value of the matrix [Formula: see text]. The matrix [Formula: see text] is a random circulant matrix and [Formula: see text], where [Formula: see text] are deterministic matrices, [Formula: see text] indicates the conjugate transpose of [Formula: see text] and [Formula: see text] are random diagonal matrices. From random experiments, we conjecture that [Formula: see text] is well-conditioned if the moment generating function of the random entries of [Formula: see text] exists.
Classification of Low-Grade and High-Grade Glioma from MR Brain Images Using Multiple-Instance Learning with Combined Feature Set
Authors: Benson C. C. , Lajish V. L. , Rajamani Kumar
Published: October 2021

Fully automatic brain image classification of MR brain images is of great importance for research and clinical studies, since the precise detection may lead to a better treatment. In this work, an efficient method based on Multiple-Instance Learning (MIL) is proposed for the automatic classification of low-grade and high-grade MR brain tumor images. The main advantage of MIL-based approach over other classification methods is that MIL considers an image as a group of instances rather than a single instance, thus facilitating an effective learning process. The mi-Graph-based MIL approach is proposed for this classification. Two different implementations of MIL-based classification, viz. Patch-based MIL (PBMIL) and Superpixel-based MIL (SPBMIL), are made in this study. The combined feature set of LBP, SIFT and FD is used for the classification. The accuracies of low-grade–high-grade tumor image classification algorithm using SPBMIL method performed on [Formula: see text], [Formula: see text] and FLAIR images read 99.2765%, 99.4195% and 99.2265%, respectively. The error rate of the proposed classification system was noted to be insignificant and hence this automated classification system could be used for the classification of images with different pathological conditions, types and disease statuses.