Symmetry, Volume 13, Issue 3 (March 2021) – 161 articles

Immobilized multi-enzyme cascades are increasingly used in microfluidic devices. In particular, their application in continuous flow reactors shows great potential, utilizing the benefits of reusability and control of the reaction conditions. However, capitalizing on this potential is challenging and requires detailed knowledge of the investigated system. Here, we show the application of computational methods for optimization with multi-level reactor design (MLRD) methodology based on the underlying physical and chemical processes. We optimize a stereoselective reduction of a diketone catalyzed by ketoreductase (Gre2) and Nicotinamidadenindinukleotidphosphat (NADPH) cofactor regeneration with glucose dehydrogenase (GDH). Both enzymes are separately immobilized on magnetic beads forming a packed bed within the microreactor. We derive optimal reactor feed concentrations and enzyme ratios for enhanced performance and a basic economic model in order to maximize the techno-economic performance (TEP) for the first reduction of 5-nitrononane-2,8-dione. Full article

Current research on the cascading failure of coupling networks is mostly based on hierarchical network models and is limited to a single relationship. In reality, many relationships exist in a network system, and these relationships collectively affect the process and scale of the network cascading failure. In this paper, a composite network is constructed based on the multisubnet composite complex network model, and its cascading failure is proposed combined with multiple relationships. The effect of intranetwork relationships and coupling relationships on network robustness under different influencing factors is studied. It is shown that cascading failure in composite networks is different from coupling networks, and increasing the strength of the coupling relationship can significantly improve the robustness of the network. Full article

In this paper, we argue in favor of first-order homogeneous Lagrangians in the velocities. The relevant form of such Lagrangians is discussed and justified physically and geometrically. Such Lagrangian systems possess Reparametrization Invariance (RI) and explain the observed common Arrow of Time as related to the non-negative mass for physical particles. The extended Hamiltonian formulation, which is generally covariant and applicable to reparametrization-invariant systems, is emphasized. The connection between the explicit form of the extended Hamiltonian $\mathit{H}$ and the meaning of the process parameter $\lambda$ is illustrated. The corresponding extended Hamiltonian $\mathit{H}$ defines the classical phase space-time of the system via the Hamiltonian constraint $\mathit{H}=0$ and guarantees that the Classical Hamiltonian H corresponds to $p_0$—the energy of the particle when the coordinate time parametrization is chosen. The Schrödinger’s equation and the principle of superposition of quantum states emerge naturally. A connection is demonstrated between the positivity of the energy $E=c{p}_0>0$ and the normalizability of the wave function by using the extended Hamiltonian that is relevant for the proper-time parametrization. Full article

In this work, anchoring of cinchona derivatives to trifunctional cores (hub approach) was demonstrated to obtain size-enlarged organocatalysts. By modifying the cinchona skeleton in different positions, we prepared four C₃-symmetric size-enlarged cinchona derivatives (hub-cinchonas), which were tested as organocatalysts and their catalytic activities were compared with the parent cinchona (hydroquinine) catalyst. We showed that in the hydroxyalkylation reaction of indole, hydroquinine provides good enantioselectivities (up to 73% ee), while the four new size-enlarged derivatives resulted in significantly lower values (up to 29% ee) in this reaction. Anchoring cinchonas to trifunctional cores was found to facilitate nanofiltration-supported catalyst recovery using the PolarClean alternative solvent. The C₃-symmetric size-enlarged organocatalysts were completely rejected by all the applied membranes, whereas the separation of hydroquinine was found to be insufficient when using organic solvent nanofiltration. Furthermore, the asymmetric catalysis was successfully demonstrated in the case of the Michael reaction of 1,3-diketones and trans-β-nitrostyrene using Hub³-cinchona (up to 96% ee) as a result of the positive effect of the C₃-symmetric structure using a bulkier substrate. This equates to an increased selectivity of the catalyst in comparison to hydroquinine in the latter Michael reaction. Full article

Atomic cascades are ubiquitous in nature and they have been explored within very different scenarios, from precision measurements to the modeling of astrophysical spectra, and up to the radiation damage in biological matter. However, up to the present, a quantitative analysis of these cascades often failed because of their inherent complexity. Apart from utilizing the rotational symmetry of atoms and a proper distinction of different physical schemes, a hierarchy of useful approaches is therefore needed in order to keep cascade computations feasible. We here suggest a classification of atomic cascades and demonstrate how they can be modeled within the framework of the Jena Atomic Calculator. As an example, we shall compute within a configuration-average approach the stepwise decay cascade of atomic magnesium, following a $1s$ inner-shell ionization, and simulate the corresponding (final) ion distribution. Our classification of physical scenarios (schemes) and the hierarchy of computational approaches are both flexible to further refinements as well as to complex shell structures of the atoms and ions, for which the excitation and decay dynamics need to be modeled in good detail. Full article

Industrial Control Systems are an essential part of our daily lives and can be found in industries such as oil, utilities, and manufacturing. Rapid growth in technology has introduced industrial components with network capabilities that allow them to communicate with traditional computer networks, thus increasing their exposure to cyber-attacks. Current research on Industrial Control Systems suffer from lack of technical information as these systems are part of critical infrastructures. To overcome this, researchers have employed different types of testbeds to develop their mechanisms of cyber-attack detection and prevention. This manuscript describes, implements, and evaluates physical, hybrid, and virtual application of a clean water supply system developed for cybersecurity research. The results show that physical testbeds allow an understanding of the behaviour and dynamics of control components like sensors and actuators, which might be affected by external influences such as noise, vibration, temperature, and non-ideal device behaviour. Although, hybrid testbeds reduce the cost of implementation, they ignore the physical dynamics of the system as explained above. Virtual testbeds are the cheapest option in comparison with physical and hybrid testbeds; however, they provide a limited view of the control system operation that could have negative consequences when developing a detection/prevention system. Full article

Objective image quality assessment (IQA) measures are playing an increasingly important role in the evaluation of digital image quality. New IQA indices are expected to be strongly correlated with subjective observer evaluations expressed by Mean Opinion Score (MOS) or Difference Mean Opinion Score (DMOS). One such recently proposed index is the SuperPixel-based SIMilarity (SPSIM) index, which uses superpixel patches instead of a rectangular pixel grid. The authors of this paper have proposed three modifications to the SPSIM index. For this purpose, the color space used by SPSIM was changed and the way SPSIM determines similarity maps was modified using methods derived from an algorithm for computing the Mean Deviation Similarity Index (MDSI). The third modification was a combination of the first two. These three new quality indices were used in the assessment process. The experimental results obtained for many color images from five image databases demonstrated the advantages of the proposed SPSIM modifications. Full article

The formation of a submicron optical cavity on one side of a metal–insulator–metal (MIM) tunneling device induces a measurable electrical current between the two metal layers with no applied voltage. Reducing the cavity thickness increases the measured current. Eight types of tests were carried out to determine whether the output could be due to experimental artifacts. All gave negative results, supporting the conclusion that the observed electrical output is genuinely produced by the device. We interpret the results as being due to the suppression of vacuum optical modes by the optical cavity on one side of the MIM device, which upsets a balance in the injection of electrons excited by zero-point fluctuations. This interpretation is in accord with observed changes in the electrical output as other device parameters are varied. A feature of the MIM devices is their femtosecond-fast transport and scattering times for hot charge carriers. The fast capture in these devices is consistent with a model in which an energy ∆E may be accessed from zero-point fluctuations for a time ∆t, following a ∆E∆t uncertainty-principle-like relation governing the process. Full article

In this work, we outline a general method for calculating Auger spectra in molecules, which accounts for the underlying symmetry of the system. This theory starts from Fano’s formulation of the interaction between discrete and continuum states, and it generalizes this formalism to deal with the simultaneous presence of several intermediate quasi-bound states and several non-interacting decay channels. Our theoretical description is specifically tailored to resonant autoionization and Auger processes, and it explicitly includes the incoming wave boundary conditions for the continuum states and an accurate treatment of the Coulomb repulsion. This approach is implemented and applied to the calculation of the $K-LL$ Auger and autoionization spectra of ozone, which is a $C_{2v}$ symmetric molecule, whose importance in our atmosphere to filter out radiation has been widely confirmed. We also show the effect that the molecular point group and, in particular, the localization of the core-hole in the oxygen atoms related by symmetry operations, has on the electronic structure of the Auger states and on the spectral lineshape by comparing our results with the experimental data. Full article

The median-type filter is an effective technique to remove salt and pepper (SAP) noise; however, such a mechanism cannot always effectively remove noise and preserve details due to the local diversity singularity and local non-stationarity. In this paper, a two-step SAP removal method was proposed based on the analysis of the median-type filter errors. In the first step, a median-type filter was used to process the image corrupted by SAP noise. Then, in the second step, a novel-designed adaptive nonlocal bilateral filter is used to weaken the error of the median-type filter. By building histograms of median-type filter errors, we found that the error almost obeys Gaussian–Laplacian mixture distribution statistically. Following this, an improved bilateral filter was proposed to utilize the nonlocal feature and bilateral filter to weaken the median-type filter errors. In the proposed filter, (1) the nonlocal strategy is introduced to improve the bilateral filter, and the intensity similarity is measured between image patches instead pixels; (2) a novel norm based on half-quadratic estimation is used to measure the image patch- spatial proximity and intensity similarity, instead of fixed L₁ and L₂ norms; (3) besides, the scale parameters, which were used to control the behavior of the half-quadratic norm, were updated based on the local image feature. Experimental results showed that the proposed method performed better compared with the state-of-the-art methods. Full article

In this work, we present a unified approach to the thermodynamics of hadron–quark–gluon matter at finite temperatures on the basis of a quark cluster expansion in the form of a generalized Beth–Uhlenbeck approach with a generic ansatz for the hadronic phase shifts that fulfills the Levinson theorem. The change in the composition of the system from a hadron resonance gas to a quark–gluon plasma takes place in the narrow temperature interval of 150–190 MeV, where the Mott dissociation of hadrons is triggered by the dropping quark mass as a result of the restoration of chiral symmetry. The deconfinement of quark and gluon degrees of freedom is regulated by the Polyakov loop variable that signals the breaking of the $Z\left(3\right)$ center symmetry of the color $SU\left(3\right)$ group of QCD. We suggest a Polyakov-loop quark–gluon plasma model with $\mathcal{O}\left({\alpha }_s\right)$ virial correction and solve the stationarity condition of the thermodynamic potential (gap equation) for the Polyakov loop. The resulting pressure is in excellent agreement with lattice QCD simulations up to high temperatures. Full article

For any graph G of order p, a bijection $f:V\left(G\right)\to \{1,2,\dots ,p\}$ is called a numbering of G. The strength $st{r}_f\left(G\right)$ of a numbering f of G is defined by $st{r}_f\left(G\right)=max\{f\left(u\right)+f\left(v\right)|uv\in E\left(G\right)\},$ and the strength $str\left(G\right)$ of a graph G is $str\left(G\right)=min\left\{st{r}_f\left(G\right)\right|f\mathrm{is}a\mathrm{numbering}\mathrm{of}G\}.$ In this paper, many open problems are solved, and the strengths of new families of graphs are determined. Full article

This paper aims to explore nonlocal complex reverse-spacetime modified Korteweg-de Vries (mKdV) hierarchies via nonlocal symmetry reductions of matrix spectral problems and to construct their soliton solutions by the inverse scattering transforms. The corresponding inverse scattering problems are formulated by building the associated Riemann-Hilbert problems. A formulation of solutions to specific Riemann-Hilbert problems, with the jump matrix being the identity matrix, is established, where eigenvalues could equal adjoint eigenvalues, and thus N-soliton solutions to the nonlocal complex reverse-spacetime mKdV hierarchies are obtained from the reflectionless transforms. Full article

Proper plant leaf disease (PLD) detection is challenging in complex backgrounds and under different capture conditions. For this reason, initially, modified adaptive centroid-based segmentation (ACS) is used to trace the proper region of interest (ROI). Automatic initialization of the number of clusters (K) using modified ACS before recognition increases tracing ROI’s scalability even for symmetrical features in various plants. Besides, convolutional neural network (CNN)-based PLD recognition models achieve adequate accuracy to some extent. However, memory requirements (large-scaled parameters) and the high computational cost of CNN-based PLD models are burning issues for the memory restricted mobile and IoT-based devices. Therefore, after tracing ROIs, three proposed depth-wise separable convolutional PLD (DSCPLD) models, such as segmented modified DSCPLD (S-modified MobileNet), segmented reduced DSCPLD (S-reduced MobileNet), and segmented extended DSCPLD (S-extended MobileNet), are utilized to represent the constructive trade-off among accuracy, model size, and computational latency. Moreover, we have compared our proposed DSCPLD recognition models with state-of-the-art models, such as MobileNet, VGG16, VGG19, and AlexNet. Among segmented-based DSCPLD models, S-modified MobileNet achieves the best accuracy of 99.55% and F1-sore of 97.07%. Besides, we have simulated our DSCPLD models using both full plant leaf images and segmented plant leaf images and conclude that, after using modified ACS, all models increase their accuracy and F1-score. Furthermore, a new plant leaf dataset containing 6580 images of eight plants was used to experiment with several depth-wise separable convolution models. Full article

The first macroscopic object observed to have come from outside the solar system slipped back out of sight in early 2018. 1I/2017 U1 ‘Oumuamua offered a unique opportunity to test understanding of gravity, planetary formation and galactic structure against a true outlier, and astronomical teams from around the globe rushed to study it. Observations lasted several months and generated a tsunami of scientific (and popular) literature. The brief window available to study ‘Oumuamua created crisis-like conditions, and this paper makes a comparative study of techniques used by cosmologists against those used by financial economists in qualitatively similar situations where data conflict with the current paradigm. Analyses of ‘Oumuamua were marked by adherence to existing paradigms and techniques and by confidence in results from self and others. Some, though, over-reached by turning uncertain findings into graphic, detailed depictions of ‘Oumuamua and making unsubstantiated suggestions, including that it was an alien investigator. Using a specific instance to test cosmology’s research strategy against approaches used by economics researchers in comparable circumstances is an example of reverse econophysics that highlights the benefits of an extra-disciplinary lens. Full article

In this paper, we present a new Fuzzy Implication Generator via Fuzzy Negations which was generated via conical sections, in combination with the well-known Fuzzy Conjunction. The new Fuzzy Implication Generator takes its final forms after being configured by the fuzzy strong negations and combined with the most well-known fuzzy conjunctions $T_M$, $T_P$, $T_{LK}$, $T_D$, and $T_{nM}$. The final implications that emerge, given that they are configured with the appropriate code, select the best value of the parameter and the best combination of the fuzzy conjunctions. This choice is made after comparing them with the Empiristic implication, which was created with the help of real temperature and humidity data from the Hellenic Meteorological Service. The use of the Empiristic implication is based on real data, and it also reduces the volume of the data without canceling them. Finally, the MATLAB code, which was used in the programming part of the paper, uses the new Fuzzy Implication Generator and approaches the Empiristic implication satisfactorily which is our final goal. Full article

In remote procedure call (RPC)-based graphic processing unit (GPU) virtualization environments, GPU tasks requested by multiple-user virtual machines (VMs) are delivered to the VM owning the GPU and are processed in a multi-process form. However, because the thread executing the computing on general GPUs cannot arbitrarily stop the task or trigger context switching, GPU monopoly may be prolonged owing to a long-running general-purpose computing on graphics processing unit (GPGPU) task. Furthermore, when scheduling tasks on the GPU, the time for which each user VM uses the GPU is not considered. Thus, in cloud environments that must provide fair use of computing resources, equal use of GPUs between each user VM cannot be guaranteed. We propose a GPGPU task scheduling scheme based on thread division processing that supports GPU use evenly by multiple VMs that process GPGPU tasks in an RPC-based GPU virtualization environment. Our method divides the threads of the GPGPU task into several groups and controls the execution time of each thread group to prevent a specific GPGPU task from a long time monopolizing the GPU. The efficiency of the proposed technique is verified through an experiment in an environment where multiple VMs simultaneously perform GPGPU tasks. Full article

Dense bulk matter is formed during heavy-ion collision and expands towards a vacuum. It behaves as a perfect fluid, described by relativistic hydrodynamics. In order to study initial condition fluctuation and properties of jet propagation in dense hot matter, we assume a Cartesian laboratory frame with several million cells in a stencil with high-accuracy data volume grids. Employing numerical algorithms to solve hydrodynamic equations in such an assumption requires a lot of computing power. Hydrodynamic simulations of nucleus + nucleus interactions in the range of energies of the Large Hadron Collider (LHC) are carried out using our program, which uses Graphics Processing Units (GPUs) and Compute Unified Device Architecture (CUDA). In this work, we focused on transforming hydrodynamic quantities into kinetic descriptions. We implemented the hypersurface freeze-out conditions using marching cubes techniques. We developed freeze-out procedures to obtain the momentum distributions of particles on the hypersurface. The final particle distributions, elliptic flow, and higher harmonics are comparable to the experimental LHC data. Full article

An interesting anomaly in the diffusion process with an apparently negative diffusion coefficient defined through the mean-square displacement in a one-dimensional quantum molecular chain model is shown. Nevertheless, the system satisfies the H-theorem so that the second law of thermodynamics is satisfied. The reason why the “diffusion constant” becomes negative is due to the effect of the phase mixing process, which is a characteristic result of the one-dimensionality of the system. We illustrate the situation where this negative “diffusion constant” appears. Full article

The aim of the study was the application of high-tech wind tunnel device to identify the changes in the biokinetic parameters of running performed on the specially designed treadmill. The research was carried out in the “Planica Nordic Centre—PNC” in the wind tunnel system, where the AirRunner Assault treadmill, which was equipped with four sensors measuring the vertical and horizontal ground reaction forces, was installed. To obtain biokinetic data, the runners performed the treadmill’s run under conditions of airflow directed at each participant’s back (backwind speeds +3 m/s and +5 m/s) and the chest (headwind speeds −5 m/s and −7 m/s). The runner’s speed was measured via image analysis using a DSLR camera and markers on the belt of the treadmill. Additionally, a high-speed camera synchronised to the force acquisition system was used to analyse the contact phase via comparison of foot placement and time series of the ground reaction forces. The contact phases of the running step were found to be longer than the flight phases, with their duration ranging from 0.15 to 0.20 s and the maximum forces at take-off were found to be greater than when running with the backwind. It should be noted that the application of high-tech devices wind tunnel and treadmill were found to be sufficiently accurate to perform kinetic measurements of running parameters in changing conditions, such as resistance and assistance (facilitating). Full article

Fractional q-calculus has been investigated and applied in a variety of fields in mathematical areas including fractional q-integral inequalities. In this paper, we study fractional $(p,q)$-calculus on finite intervals and give some basic properties. In particular, some fractional $(p,q)$-integral inequalities on finite intervals are proven. Full article

In this paper, we obtain a new equivalent fixed-point form of the linear complementarity problem by introducing a relaxed matrix and establish a class of relaxed modulus-based matrix splitting iteration methods for solving the linear complementarity problem. Some sufficient conditions for guaranteeing the convergence of relaxed modulus-based matrix splitting iteration methods are presented. Numerical examples are offered to show the efficacy of the proposed methods. Full article

A series of new bidentate N,S-ligands—aziridines containing a para-substituted phenyl sulfide group—was synthesized and evaluated in the Pd-catalyzed Tsuji–Trost reaction and addition of diethylzinc and phenylethynylzinc to benzaldehyde. A high enantiomeric ratio for the addition reactions (up to 94.2:5.8) was obtained using the aziridine ligand bearing a p-nitro phenyl sulfide group. Collected results reveal a specific electronic effect that, by the presence of particular electron-donating or electron-withdrawing groups in the PhS- moiety, influences the σ-donor–metal binding and the enantioselectivity of the catalyzed reactions. Full article

In this article, we employ the notion of coupled fixed points on a complete b-metric space endowed with a graph to give sufficient conditions to guarantee a solution of system of differential equations with impulse effects. We derive recisely some new coupled fixed point theorems under some conditions and then apply our results to achieve our goal. Full article

The algebraic as well as geometric topological constructions of manifold embeddings and homotopy offer interesting insights about spaces and symmetry. This paper proposes the construction of 2-quasinormed variants of locally dense p-normed 2-spheres within a non-uniformly scalable quasinormed topological (C, R) space. The fibered space is dense and the 2-spheres are equivalent to the category of 3-dimensional manifolds or three-manifolds with simply connected boundary surfaces. However, the disjoint and proper embeddings of covering three-manifolds within the convex subspaces generates separations of p-normed 2-spheres. The 2-quasinormed variants of p-normed 2-spheres are compact and path-connected varieties within the dense space. The path-connection is further extended by introducing the concept of bi-connectedness, preserving Urysohn separation of closed subspaces. The local fundamental groups are constructed from the discrete variety of path-homotopies, which are interior to the respective 2-spheres. The simple connected boundaries of p-normed 2-spheres generate finite and countable sets of homotopy contacts of the fundamental groups. Interestingly, a compact fibre can prepare a homotopy loop in the fundamental group within the fibered topological (C, R) space. It is shown that the holomorphic condition is a requirement in the topological (C, R) space to preserve a convex path-component. However, the topological projections of p-normed 2-spheres on the disjoint holomorphic complex subspaces retain the path-connection property irrespective of the projective points on real subspace. The local fundamental groups of discrete-loop variety support the formation of a homotopically Hausdorff (C, R) space. Full article

Shape classification and matching is an important branch of computer vision. It is widely used in image retrieval and target tracking. Shape context method, curvature scale space (CSS) operator and its improvement have been the main algorithms of shape matching and classification. The shape classification network (SCN) algorithm is proposed inspired by LeNet5 basic network structure. Then, the network structure of SCN is introduced and analyzed in detail, and the specific parameters of the network structure are explained. In the experimental part, SCN is used to perform classification tasks on three shape datasets, and the advantages and limitations of our algorithm are analyzed in detail according to the experimental results. SCN performs better than many traditional shape classification algorithms. Accordingly, a practical example is given to show that SCN can save computing resources. Full article

We obtain existence and uniqueness fixed point theorems as well as approximation results for some classes of mappings defined by symmetric contractive type conditions in a convex metric space in the sense of Takahashi. By using a new approach, i.e., the technique of enrichment of contractive type mappings, we obtain general results which extend the well known Banach contraction mapping principle from metric spaces as well as other corresponding results for enriched mappings defined on Banach spaces. To indicate the relevance of our new results, we present some important particular cases and future directions of research. Full article

Keto-enol prototropic conversions for carbonyl compounds and phenols have been extensively studied, and many interesting review articles and even books appeared in the last 50 years. Quite a different situation takes place for derivatives of biologically active azulene, for which only scanty information on this phenomenon can be found in the literature. In this work, quantum-chemical studies have been undertaken for symmetrically and unsymmetrically substituted azulenols (constitutional isomers of naphthols). Stabilities of two enol (OH) rotamers and all possible keto (CH) tautomers have been analyzed in the gas phase {DFT(B3LYP)/6-311+G(d,p)} and also in aqueous solution {PCM(water)//DFT(B3LYP)/6-311+G(d,p)}. Contrary to naphthols, for which the keto forms can be neglected, at least one keto isomer (C1H, C2H, and/or C3H) contributes significantly to the tautomeric mixture of each azulenol to a higher degree in vacuo (non-polar environment) than in water (polar amphoteric solvent). The highest amounts of the CH forms have been found for 2- and 5-hydroxyazulenes, and the smallest ones for 1- and 6-hydroxy derivatives. The keto tautomer(s), together with the enol rotamers, can also participate in deprotonation reaction leading to a common anion and influence its acid-base properties. The strongest acidity in vacuo exhibits 6-hydroxyazulene, and the weakest one displays 1-hydroxyazulene, but all azulenols are stronger acids than phenol and naphthols. Bond length alternation in all DFT-optimized structures has been measured using the harmonic oscillator model of electron delocalization (HOMED) index. Generally, the HOMED values decrease for the keto tautomers, particularly for the ring containing the labile proton. Even for the keto tautomers possessing energetic parameters close to those of the enol isomers, the HOMED indices are low. However, some kind of parallelism exists for the keto forms between their relative energies and HOMEDs estimated for the entire molecules. Full article

Milling cutters belong to a widely used category of cutting tools. In this category, modular milling cutters are a narrow niche, less studied, and developed. Usually, they are symmetrical cutting tools. A milling cutting tool that can be reconfigured due to its modularity and still keeps its symmetry becomes more interesting and useful for machining. The paper presents such a new concept in a computer aided design (CAD) model of a cutting tool based on some novel features. The tool itself is designed as a modular complex. The way the torque is transmitted from the shaft to the elementary cutters is an original one, as they are joined together based on a profiled assembling. The profile is one formed of filleted circular sectors and segments. The reaming of the elementary cutters has two sections each of them assuming a task: transmitting the torque, and precisely centring, respectively. The cooling system, which is a component of the tool, provides the cutting area with coolant both on the front and side face of the cutting tool. Some nozzles placed around the cutting tool send jets or curtains of coolant towards the side surface of the cutter, instead of parallel, as some existing solutions do. The source of the coolant supply is the inner cooling system of the machine tool. This provides the tool with coolant having proper features: high enough flow and pressure. The output of the research is a CAD-based model of the modular milling cutter with a high performance cooling system. All of this model’s elements were designed taking into account the design for manufacturing principles, so it will be possible to easily manufacture this tool. Several variants of milling cutters obtained by reconfiguring the complex tool are presented. Even if the tool is usually a symmetric complex, it can process asymmetric parts. Symmetry is intensively used to add some advantages to the modular cutting tool: balanced forces in the cutting process, the possibility of controlling the direction of the axial cutting force, and a good machinability of the grooves used to assemble the main parts of the cutting tool. Full article

Compared with ordinary images, each of the remote sensing images contains many kinds of objects with large scale changes, providing more details. As a typical object of remote sensing image, ship detection has been playing an essential role in the field of remote sensing. With the rapid development of deep learning, remote sensing image detection method based on convolutional neural network (CNN) has occupied a key position. In remote sensing images, the objects of which small scale objects account for a large proportion are closely arranged. In addition, the convolution layer in CNN lacks ample context information, leading to low detection accuracy for remote sensing image detection. To improve detection accuracy and keep the speed of real-time detection, this paper proposed an efficient object detection algorithm for ship detection of remote sensing image based on improved SSD. Firstly, we add a feature fusion module to shallow feature layers to refine feature extraction ability of small object. Then, we add Squeeze-and-Excitation Network (SE) module to each feature layers, introducing attention mechanism to network. The experimental results based on Synthetic Aperture Radar ship detection dataset (SSDD) show that the mAP reaches 94.41%, and the average detection speed is 31FPS. Compared with SSD and other representative object detection algorithms, this improved algorithm has a better performance in detection accuracy and can realize real-time detection. Full article