The synthesis and structure of the 4,4′-dipyridyl N,N′-donor ligand with a central thiazolo[5,4-d]thiazole (tztz) unit, named Dptztz is presented. With the linker Dptztz and isophthalate (benzene-1,3-dicarboxylate, 1,3-BDC²⁻) the mixed-linker, two-dimensional coordination network [Zn(1,3-BDC)Dptztz]·DMF could be obtained (DMF = dimethylformamide), which belongs to the class of coordination polymers with interdigitated structures (CIDs). The incorporated DMF solvent molecules can be removed through solvent exchange and evacuation such that the supramolecular 3D packing of the 2D networks retains porosity for CO₂ adsorption in activated [Zn(1,3-BDC)Dptztz]. The first sorption study of a tztz-functionalized porous metal-organic framework material yields a BET surface of 417 m²/g from CO₂ adsorption. The heat of adsorption for CO₂ exhibits a relative maximum with 27.7 kJ/mol at adsorbed CO₂ of about 4 cm³/g STP which is interpreted as a gate-opening effect.

Biomimicry in additive manufacturing often refers to topology optimization and the use of lattice structures, due to the organic shape of the topology-optimized designs, and the lattices often looking similar to many light-weight structures found in nature such as trabecular bone, wood, sponges, coral, to name a few. Real biomimetic design however involves the use of design principles taken in some way from natural systems. In this work we use a methodology whereby high resolution 3D analysis of a natural material with desirable properties is “reverse-engineered” and the design tested for the purpose. This allows more accurate replication of the desired properties, and adaption of the design parameters to the material used for production (which usually differs from the biological material). One such example is the impact-protective natural design of the glyptodont body armour. In this paper we report on the production of body armour models in metal (Ti4Al4V) and analyze the resulting mechanical properties, assessing their potential for impact protective applications. This is the first biomimetic study using metal additive manufacturing to date.

We have proposed a data-driven approach for designing mesoscale porous structures of Li-ion battery electrode with three-dimensional virtual structures and machine learning techniques. Over 2,000 artificial 3D structures assuming positive electrode composed of random packed spheres as active material particles are generated, and charge/discharge resistance has been evaluated using simplified Physico-chemical model. In this model, resistance from Li diffusion in active material particles (diffusion resistance), transfer resistance of Li+ in electrolyte (electrolyte resistance) and reaction resistance on the interface between active material and electrolyte are simulated based on mass balance of Li, Ohm’s law in and linearized Butler-Volmer equation, respectively. Using these simulation results, regression models via Artificial Neural Network (ANN) have been created in order to predict charge/discharge resistance from porous structure features. In this study, porosity, active material particle size and volume fraction, pressure in the compaction process, electrolyte conductivity, and binder volume fraction are adopted as features, associated with controllable process parameters for manufacturing battery electrode. As results, the predicted electrode resistance by ANN regression model is good agreement with the simulated values. Furthermore, sensitivity analysis and optimization of the process parameters have been carried out. The proposed data-driven approach could be a solution as a guiding principle for manufacturing battery electrode.

Legionella pneumophila RpoS (LpRpoS) is an alternative sigma factor of RNA polymerase (RNAP) essential for virulence and stress resistance. To investigate the mechanism of RpoS in the intracellular pathogen L. pneumophila, we determined the high-resolution crystal structure of the LpRpoS (residues 95-194) containing a partial region 1.2 and region 2. The structure of LpRpoS (residues 95-194) reveals that the conserved residues are critical for promoter melting, DNA and core RNAP binding. The differences in regulatory factor binding site between Escherichia coli RpoS and LpRpoS suggest that LpRpoS may employ a distinct mechanism to recruit alternative regulatory factors controlling transcription initiation.

The concept of smart morphing blades, which can control themselves to reduce or eliminate the need for active control systems, is a highly attractive solution in blade technology. In this paper an innovative passive control system based on Shape Memory Alloys (SMAs) is proposed. On the basis of previous thermal and shape characterization of a single morphing blade for a heavy-duty automotive cooling axial fan, this study deals with the numerical analysis of the aerodynamic loads acting on the fan. By coupling CFD and FEM approaches it is possible to analyze the actual blade shape resulting from both the aerodynamic and centrifugal loads. The numerical results indicate that the polymeric blade structure ensures proper resistance and enables shape variation due to the action of the SMA strips.

To enable purposeful design and implementation of automated concrete technologies, precise assessment and prediction of the complex material flow at various stages of the process chain are necessary. This paper investigates the intermediate stage of the extrusion and deposition processes in extrusion-based 3D-concrete-printing, using a numerical model based on the Particle Finite Element Method (PFEM). In PFEM, due to the Lagrangian description of motion, remeshing algorithms and the alpha shape method are used to track the free surface during large deformation scenarios. The Bingham constitutive model was used for describing the rheological behaviour of fresh concrete. This model is validated by comparing the numerically predicted layer geometries with those obtained from laboratory 3D printing experiments. Extensive parametric studies were then conducted using the numerical simulation, delineating the influence of process and material parameters on the layer geometries, the dynamic surface forces generated under the extrusion nozzle and the inter-layer interactions.

The current paper is focused on the rapidly developing field of nano-/micro three-dimensional production of inorganic materials. The fabrication method includes laserlithography of hybrid organic-inorganic materials with subsequent heat treatment lead-ing to a variety of crystalline phases in 3D structures. In this work, it was examineda series of organometallic polymer precursors with different silicon (Si) and zirconium (Zr) molar ratios, ranging from 9:1 to 5:5, prepared via sol-gel method. All mixtureswere examined for perspective used in 3D laser by manufacturing by fabricating nano-and micro-feature sized structures. Their deformation and surface morphology wereevaluated depending on chemical composition and crystallographic phase. The appear-ance of a crystalline phase was proven using single-crystal X-ray diffraction analysis,which revealed a lower crystallization temperature for microstructures compared tobulk materials. Fabricated 3D objects retain a complex geometry without any distortion after heat treatment up to 1400^oC. Under the proper conditions, a zircon phase (ZrSiO₄ - a highly stable material) can be observed. In addition, the highest newrecord of achieved resolution below 60 nm has been reached. The proposed prepara-tion protocol can be used to manufacture micro/nano-devices with high precision andresistance to high temperature and aggressive environment.

The aim of this study was to identify MFIs specific determinants of capital structure of selected micro finance institutions in Ethiopia. The researcher employed quantitative research approach with explanatory research design. The result of regression analysis showed that out that variables like growth, profitability, firm size, age, and asset tangibility have positive and statistically significant effect on leverage ratio. Whereas, profitability has statistically significant and negative effect on capital structure. Based on the findings of the study, the researcher concluded that the firm specific determinants of capital structure of micro finance institutions in Ethiopia were growth, profitability, firm size, age, and asset tangibility.

Most of the phase change materials (PCMs) have been limited to use as functional additions or sealed in containers, and extra auxiliary equipment or supporting matrix is needed. The emergence of 3D printing technique has dramatically advanced the developments of materials and simplified production processes. This study focuses on a novel strategy to model thermal energy storage crystalline gels with three-dimensional architecture directly from liquid resin without supporting materials through light-induced polymerization 3D printing technique. A mask-projection stereolithography printer was used to measure the 3D printing test, and the printable characters of crystalline thermal energy storage P(SA-DMAA) gels with different molar ratios were evaluated. For the P(SA-DMMA) gels with small fraction of SA, the 3D fabrication was realized with higher printing precision both on mili- and micro-meter scales. As a comparison of 3D printed samples, P(SA-DMAA) gels made by other two methods, post-UV curing treatment after 3D printing and UV curing using conventional mold, were prepared. The 3D printed P(SA-DMAA) gels shown high crystallinity. Post–UV curing treatment was beneficial to full curing of 3D printed gels, but did not lead to the further improvement of crystal structure to get higher crystallinity. The P(SA-DMAA) crystalline gel having the highest energy storage enthalpy that reached 69.6 J·g⁻¹ was developed. Its good thermoregulation property in the temperature range from 25 to 40 °C was proved. The P(SA-DMAA) gels are feasible for practical applications as one kind of 3D printing material with thermal energy storage and thermoregulation functionality.

Fabrication of a true-3D inorganic ceramic with resolution down to nanoscale using sol-gel resist precursor is demonstrated. The method has an unrestricted free-form capability, control of the fill-factor, and high fabrication throughput. A systematic study of the proposed approach based on ultrafast laser 3D lithography of organic-inorganic hybrid sol-gel resin followed by a heat treatment enabled formation of inorganic amorphous and crystalline composites guided by the composition of the initial resin. The achieved resolution of 100 nm was obtained for 3D patterns of complex free-form architectures. Fabrication throughput of 50×10³ voxels/s is achieved; voxel - a single volume element was recorded by a single pulse exposure. After a subsequent thermal treatment, ceramic phase was formed depending on the temperature and duration of the heat treatment as validated by Raman micro-spectroscopy. The X-ray diffraction (XRD) revealed a gradual emergence of the crystalline phases at higher temperatures with a signature of cristobalite SiO₂, a high-temperature polymorph. Also, the tetragonal ZrO₂ phase known for its high fracture strength was observed. This 3D nano-sintering technique is scalable from nano- to millimeter dimensions and opens a conceptually novel route for optical 3D nano-printing of various crystalline inorganic materials defined by an initial composition for diverse applications for microdevices in harsh physical and chemical environments and high temperatures.

There is a growing interest in fibers supporting optoelectrical properties for textile and wearable display applications. Solution-processed electroluminescent (EL) material systems can be continuously deposited onto fiber or yarn substrates in a roll-to-roll process, making it easy to scale manufacturing. It is important to have precise control over layer deposition to achieve uniform and reliable light emission from these EL fibers. Slot-die coating offers this control and increases the rate of EL fiber production. Here, we report a highly adaptable, cost-effective 3D printing model for developing slot dies used in automatic coating systems. The resulting slot-die coating system enables rapid, reliable production of alternating current powder-based EL (ACPEL) fibers and can be adapted for many material systems. The benefits of this system over dip-coating for roll-to-roll production of EL fibers are demonstrated in this work.

Many studies discuss carbon-based materials because of the versatility of its element. They include different opinions for scientific problems and discuss fairly at convincing and compelling levels within the scope and application. A gas-state carbon atom converts into various states depending on its conditions of processing. The electron transfer mechanism in the gas-state carbon atom is responsible to convert it into various states, namely, graphite, nanotube, fullerene, diamond, lonsdaleite and graphene. The shape of ‘energy trajectory’ enables transferring electrons from the left- and right-sides of an atom is like a parabola. That ‘energy trajectory’ is linked to states (filled state and suitable nearby unfilled state) where force-exertion along the poles of transferring electrons is remained balance. So, the mechanism of originating different states of a gas-state carbon atom is under the involvement of energy first. This is not the case for atoms executing confined inter-state electron-dynamics as the force is involved first. Graphite-, nanotube- and fullerene-state atoms ‘partially evolve partially develop’ (form) their structures. These possess one-dimensional, two-dimensional and four-dimensional ordering of atoms, respectively. Their structural formation also comprises ‘energy curve’ having a shape-like parabola. Transferring suitable filled state electron to suitable nearby unfilled state is under a balance force exerting along the poles. The graphite structure under only attained-dynamics of atoms can also be formed but in two-dimension. Here, binding energy between graphite-state carbon atoms is for a small difference of exerting forces along their opposite poles. Structural formation in diamond, lonsdaleite and graphene atoms involve energy to gain required infinitesimal displacements of electrons through which they maintain orientationally-controlled exerting forces along dedicated poles. In this study, the growth of diamond is found to be south to east-west (ground) where atoms bound ground to south. Thus, diamond atoms merge for a tetra-electron ground to south topological structure. Lonsdaleite atoms merge for a bi-electron ground to just-south topological structure. The growth of graphene is found to be north to ground where atoms bound ground to north. Thus, graphene atoms merge for a tetra-electron ground to north topological structure. Glassy carbon exhibits layered-topological structure where, tri-layers of gas-, graphite- and lonsdaleite-state atoms successively bind in repetitive order. Nanoscale hardness is also sketched based on different force-energy behaviors of different state carbon atoms. Here, structure evolution in each carbon state atom explores its own science.

This theoretical article reviews the model describing processes in social systems based on the analysis of their resource base. Application of the system theory can help to explain why some systems are aimed at prevention of type I errors, while other seek to decrease quantity of type II errors. Such differences are manifested in investment of resources either into deep interaction or into wide coverage. Some examples of such strategies in economic, market and production systems are provided in the article. The article introduces some provisions of the system theory in the context of the resource flows. The main indicators that are considered in this article are the characteristics of the sources of the exchanging flows of resources. Their relative frequency and quality are investigated, on the basis of which the most effective strategy of the system is derived, as a mechanism for redistributing resources. The rigor of the system's strategy depends on the magnitude of the difference in characteristics. It is explained how exactly it influences the exchange processes, that in reality systems do not interact simultaneously, and one of the opposite resource flows is always delayed. It is shown how the system strategy depends on the risks linked with interactions. Also, there are grounds for the need to accumulate resources, including in the situation of their surplus. The model helps also explain shift of economic centers throughout history. Additionally, there is an analogy between systems strategies and the competitive strategies described by M. Porter, and outsourcing versus integration.

In this paper, a geometric body-centered model to simulate the periodic structure of unidirectional fibrous composites is presented. To this end, three prescribed configurations are introduced to predict in a deterministic manner the arrangement of internal and neighboring fibers inside the matrix. Thus, three different representative volume elements (RVEs) are established. Furthermore, the concept of the interphase has been taken into account, stating that each individual fiber is encircled by a thin layer of variable thermomechanical properties. Next, these three unit cells are transformed in a unified manner to a coaxial multilayer cylinder model. This advanced model includes the influence of fiber contiguity in parallel with the interphase concept on the thermomechanical properties of the overall material. Then, by the use of this model, the authors propose explicit expressions to evaluate the longitudinal and transverse thermal conductivity of this type of composite. The theoretical predictions were compared with experimental results, as well as with theoretical values yielded by some reliable formulae derived from other workers, and a reasonable agreement was found.

This paper presents the systematic development and performance characterization of a non-proprietary 3D-printable ultra-high-performance fiber-reinforced concrete (UHPFRC) for digital construction. Several fresh and hardened properties of the developed 3D-printable UHPFRC matrix (without fiber) and composite (with 2% volume fraction of steel fibers) were evaluated and compared to that of conventionally mold-cast UHPFRC. Additionally, the effects of testing direction on the compressive and flexural strengths of the printed UHPFRC were investigated. The fresh properties of the UHPFRC developed in this study satisfied the criteria for extrudability, buildability, and shape-retention-ability, which are relevant for ensuring printability. The printed UHPFRC exhibited superior flexural performance to the mold-cast UHPFRC due to alignment of the short fibers in the printing direction. The high compressive and flexural strengths, along with the deflection-hardening behavior, of the developed UHPFRC can enable the production of thin 3D-printed components with significant reduction or complete elimination of conventional steel bars.

The powder bed fusion (PBF) metal additive manufacturing (AM) method uses an energy source like a laser to melt the metal powders. The laser can locally melt the metal powders and creates a solid structure as it moves. The complexity of the heat distribution in laser PBF metal AM is one of the main features that need to be accurately addressed and understood to design and manage an optimized printing process. In this research, the dependency of local thermal rates and gradients on print after solidification (in the heat-affected zone) was numerically simulated and studied to provide information for designing the print process. The simulation results were validated by independent experimental results. The simulation shows that the local thermal rates are higher at higher laser power and scan speed. Also, the local thermal gradients increase if the laser power increases. The effect of scan speed on the thermal gradients is opposite during heating versus cooling times. Increasing the scan speed increases the local thermal gradients in the cooling times and decreases the local thermal gradients during the heating. In addition, these simulation results could be used in artificial intelligence (AI) and machine learning for developing digital additive manufacturing.

A position sensing glove, called SmartScan, that creates a 3D virtual model of a real object is presented. The data from the glove is processed by a volume minimization algorithm to validate the position sensor data. This allows only data from the object’s surface to be retained. The data validation algorithm allows the user to progressively improve an image by repeatedly moving their hand over the object. In addition, the user can choose their own balance between feature resolution and invalid data rejection. The SmartScan glove is tested on a foot model and is shown to be robust against motion artifacts, and has a mean accuracy of 2.9 mm (compared to a 3D model generated from optical imaging) without calibration.

This article attempts to formulate a mathematical model for a potential explanation regarding the unavoidable impact of a rigid body's peculiar shape on the seamless flow over it. The solid body completely immersed in a Newtonian fluid and respectively has a relative open circuit flow on it will typically experience various observable phenomena like flow separation, flow transition, down-wash, stalling at the higher angle of attack, stalling velocity and how cambered airfoil can typically generate lift at a zero incidence angle. This article respectively represents an understanding of the laminar flow over a rigid body's external surface with due respect to its distinctive shape and size. This working paper formulates a more realistic and simplified mathematical model for open circuit laminar flow over a body, based on the historical data of aerodynamics and theoretical mechanics. This is intended to properly estimate forces on the continuous surface of the body in a laminar flow, to properly explain, understand and predict mentioned phenomena. Most of all the mechanism of streamline formation and its deformation with due regards to flow, shape and size of the body in an open-circuit laminar are formulated mathematically to enhance better design theory which can reduce experimentation while designing a streamlined body.

Below T_CO=157 K the quasi-one-dimensional charge-transfer salt (TMTTF)_2SbF_6 undergoes a pronounced phase transition to a charge-ordered ground state. We have explored the non-linear and photoconductive behavior as a function of applied voltage, laser pulse energy and temperature. Besides a decay of the photoconductive signal in a double exponential fashion in the millisecond range, we discover current oscillations in the kHz range induced by the application of short laser pulses. While the resonance frequencies do not depend on voltage or laser intensity and vary only slightly with temperature, the amplitude changes linearly with the laser intensity and voltage. The findings are discussed and compared to comparable phenomena in other low-dimensional electron systems.

Titanium dioxide (TiO₂) micro and nano architectures have been intensively studied in the past years because of many varied applications in environmental, energy conversion, and storage fields, such as heterogeneous catalysis, dye-sensitized solar cells, lithium/sodium ion batteries, lithium-sulfur (Li-S) batteries, and bio-nanotechnology, etc. Especially the surface and interface structures in the TiO₂ structures play important roles in those applications. This mini review article focuses on TiO₂ micro and nano architectures with the prevalent crystal structures (anatase, rutile, brookite, and TiO₂(B)), and summarizes major advances in the surface and interface engineering and applications in environmental and electrochemical applications. We present the principles and growth mechanisms of TiO₂ nanostructures via different strategies, with an emphasis on rational control of the surface and interface structures. We further discuss the applications of TiO₂ micro and nano architectures in photocatalysis, lithium/sodium ion batteries, and Li-S batteries. Throughout the discussion, the relationship between the device performance and the surface structures of TiO₂ micro/nano structures will be highlighted. Then we discuss the phase transitions of TiO₂ nanostructures and possible strategies of improving the phase stability. The review concludes with a perspective on the current challenges and future research directions.

Methylsilsesquioxane aerogels with uniform mesopores have been facilely prepared via a sol–gel process followed by microwave drying with methyltrimethoxysilane (MTMS) as precursor, hydrochloric acid (HCl) as catalyst, water and methanol as solvents, hexadecyltrimethylammonium chloride (CTAC) as surfactant and template and propylene oxide (PO) as gelation agent. The microstructure, chemical composition and pore structures of the resultant MSQ aerogels were investigated in detail to achieve controllable preparation of MSQ aerogels, and the thermal stability of MSQ aerogels was also analyzed. The gelation agent, catalyst, solvent and microwave power have important roles on pore structures of MSQ aerogels. Meanwhile, microwave drying method is found to not only have a remarkable effect on improving production efficiency, but also be conducive to avoid the collapse of pore structure especially micropores during drying. The resulting MSQ aerogel microwave-dried at 500 W possesses a specific surface area up to 821 m2/g and a mesopore size of 20 nm, and displays good thermal stability.

This topical review describes the results of recent research into and development of silicon nitride, a ceramic material with unique properties. The outcome of this ongoing research strongly encourages the use of monolithic silicon nitride and coatings as contemporary and future biomaterial for a variety of medical applications. Crystallographic structure, synthesis and processing of monolithic structures and coatings, and examples of their medical applications are covered that relate to spinal, orthopedic and dental implants, bone grafts and scaffolds, platforms for intelligent synthetic neural circuits, antibacterial and antiviral particles and coatings, optical biosensors, and nano-photonic waveguides for sophisticated medical diagnostic devices. The examples provided show convincingly that silicon nitride is destined to become a leader to replace titanium and other entrenched biomaterials in many fields of medicine.

Heat shock transcription factors (HSFs) participate in regulating many environmental stress responses and biological processes in plants. Maize (Zea mays L.) is a major cash crop that is grown worldwide. However, the growth and yield of maize are affected by several adverse environmental inputs. Therefore, investigating the factors that regulate maize growth and development and resistance to abiotic stress is an essential task for developing stress-resilient maize varieties. Thus, a comprehensive genome-wide identification analysis was performed to identify HSFs in the maize genome. The current study identified 25 ZmHSFs, randomly distributed throughout the maize genome. Phylogenetic analysis revealed that ZmHSFs are divided into three classes and 13 sub-classes. Gene structure and protein motif analysis supported the results obtained through the phylogenetic analysis. Domain analysis showed the DNA-binding domain to be the most conserved region of ZmHSFs. Segmental duplication is shown to be responsible for the expansion of ZmHSFs. Most of the ZmHSFs are localized inside the nucleus, and the ZmHSFs which belong to the same group show similar physio-chemical properties. The 3D structures revealed comparable conserved ZmHSFs protein structures. RNA-seq analysis revealed a major role of class A HSFs including, ZmHSFA-1a and ZmHSFA-2a in all the maize growth stages, i.e., seed, vegetative, and reproductive development. Furthermore, ZmHSFs displayed an obvious spatiotemporal expression. Under abiotic stress conditions (heat, drought, cold, UV, and salinity), members of class A and B ZmHSFs are induced. Gene ontology (GO) annotation analysis indicated a major role of ZmHSFs in resistance to environmental stress and regulation of primary metabolism. Further, the protein-protein interaction analysis showed that ZmHSFs interact with several molecular chaperons and major stress-responsive proteins. To summarize, this study provides novel insights for functional studies on the ZmHSFs in maize breeding programs.

This compendium presents new mathematical techniques for modeling Point Absorbers. A combined frequency-time domain framework is developed. It is used to simulate the energy generated by the wave farms. With Matlab and Fortran as a base, this leads to obtain physical variables of primary importance, namely position, velocity and power to energy net balance relationships of absorption. Integration of different degrees of freedom with heave as main executable leads in turn to a single buoy motion focus. Acquisition of the needed hydrodynamic coefficients is provided through application of potential field solvers with Boundary Element Methodology background. Initially, this Wave-to-motion model is validated by comparison with previous experimental results for a floating cone cylinder shape (Buldra-FO3). A single, generic, vertical floating cylinder is contemplated then, that responds to the action of the passing regular waves excitation. Later, two equally sized vertical floating cylinders aligned with the incident wave direction are modeled for a variable distance between the bodies. For both unidirectional regular and irregular waves as an input in deep water, we approximate the convolutive radiation force function term through the Prony method. By changing the spatial disposition of the axisymmetric buoys, using for instance triangular or rectangular shaped arrays of three and four bodies respectively, the study delves into motion characteristics for regular waves. The results highlight efficient layouts for maximizing the energy production whilst providing important insights into their performance, revealing displacement amplification- and capture width-ratios, while deriving in possible interpretations of scenarios related to the known park effect. These terms are encompassed by the novelty of a new conceptual Post-Processing methodology in the field, which leads to obtain an optimal distance for the separated bodies with effective energy absorption in a regular wave regime. The main objective is to generate a tendency within the hydrodynamic field of study, which is the Wave to motion perspective. More generally, this computational excursion envisions and depicts potential fields of study, which will surely enhance new connections and link this renewable energy form. Therefore, this research delves first into the historical and technical background on Ocean Wave Energy. Next, it is in the section regarding Materials and Methods, where boundaries and related equations are introduced step by step, together with latter mentioned case scenarios, and their corresponding configuration parameters. A separate section frames then the scope of results, while finally, there is an ensuing discussion and conclusions for evaluation assessment.

Parts produced by laser or electron-beam powder bed fusion (PBF) additive manufacturing are prone to residual stresses, deformations, and other defects linked to non-uniform temperature distribution during the manufacturing process. Several researchers have highlighted the important role scan sequence plays in achieving uniform temperature distribution in PBF. However, scan sequence continues to be determined offline based on trial-and-error or heuristics, which are neither optimal nor generalizable. To address these weaknesses, we have articulated a vision for an intelligent online scan sequence optimization approach to achieve uniform temperature distribution, hence reduced residual stresses and deformations, in PBF using physics-based and data-driven thermal models. This paper proposes SmartScan, our first attempt towards achieving our vision using a simplified physics-based thermal model. The conduction and convection dynamics of a single layer of the PBF process are modeled using the finite difference method and radial basis functions. Using the model, the next best feature (e.g., stripe or island) that minimizes a thermal uniformity metric is found using control theory. Simulations and experiments involving laser marking of a stainless steel plate are used to demonstrate the effectiveness of SmartScan in comparison to existing heuristic scan sequences for stripe and island scan patterns. In experiments, SmartScan yields up to 43% improvement in average thermal uniformity and 47% reduction in deformations (i.e., warpage) compared to existing heuristic approaches. It is also shown to be robust, and computationally efficient enough for online implementation.

3D meso-scale structures that can reach up to centimeters in overall size but retain micro- or nano-features, proved to be promising in various science fields ranging from micro-mechanical metamaterials to photonics and bio-medical scaffolds. In this work we present synchronization of the linear and galvano scanners for efficient femtosecond 3D optical printing of objects at the meso-scale (from sub-μm to sub-cm spanning five orders of magnitude). In such configuration the linear stages provide stitch-free structuring at nearly limitless (up to tens-of-cm) working area, while galvo-scanners allow to achieve translation velocities in the range of mm/s-cm/s without sacrificing nano-scale positioning accuracy and preserving undistorted shape of the final print. The principle behind this approach is demonstrated, proving its inherent advantages in comparison to separate use of only linear stages or scanners. The printing rate is calculated in terms voxels/s, showcasing the capability to maintain an optimal feature size while increasing throughput. Full capabilities of this approach are demonstrated by fabricating structures that reach millimeters in size but still retain μm-scale features: scaffolds for cell growth, microlenses and photonic crystals. All this is combined into a benchmark structure: a meso-butterfly. Provided results show that synchronization of two scan modes is crucial for the end goal of industrial-scale implementation of this technology and makes the laser printing well aligned with similar approaches in nanofabrication by electron and ion beams.

This work presents datasets that can be used for getting a good understanding of an essential geoscience content knowledge that describe earth’s coordinate systems. This include coordinate system used for spherical/spheroidal earth with latitudes and longitudes and their subsequent transformations to 2d maps on a variety of media (paper as well as digital) using the process of map projections. The datasets include PDF documents that are embedded with 3d models, animations and mathematical equations. The dataset has separate PDF documents for geographic (for spherical earth) and projected (2d) coordinate systems. Additionally, the data set include individual 3d models that can be used in various digital systems (including apps) and the animations in mp4 format that can be watched on most of the modern digital devices.

In this paper we review a proposal to represent the geometric degrees of freedom of the gravitational field as a branched covering space, and introduce a new application of this in which the branch loci are 1- or 2-knots. This allows one to construct arbitrary smooth, closed 3- and 4-manifolds with enough geometric and topological information to write down a partition function and calculate statistical quantities in the thermodynamic limit. Further, we find clear evidence for a dimensional reduction of the spacetime geometry from four to two. As an example, we choose a family of smooth 4-manifolds presented in this way, and calculate the entropy of the system.

The nitrogen-doped amorphous oxide semiconductor (AOS) thin film transistors (TFTs) with double-stacked channel layers (DSCL) were prepared and characterized. The DSCL structure composed of nitrogen-doped amorphous InGaZnO and InZnO films (a-IGZO:N/a-IZO:N or a-IZO:N/a-IGZO:N) made the corresponding TFT devices exhibit quite large field-effect mobility due to the existence of double conduction channels. Especially, the a-IZO:N/a-IGZO:N TFTs showed even better electrical performance (μ_FE = 15.0 cm²·V^-1·s^-1, SS = 0.5 V/dec, V_TH = 1.5 V, I_ON/I_OFF = 1.1×10⁸) and stability (V_TH shift of 1.5, -0.5, and -2.5 V for positive bias-stress, negative bias-stress and thermal stress tests, respectively) than the a-IGZO:N/a-IZO:N TFTs. Based on the X-ray photoemission spectroscopy measurements and energy band analysis, it was assumed that the optimized interface trap states, the less ambient gas adsorption, and the better suppression of oxygen vacancies in the a-IZO:N/a-IGZO:N hetero-structures might be responsible for the better behaviors of the corresponding TFTs.

The study of vegetation community and structural change has been central to ecology for over a century, yet how disturbances reshape the physical structure of forest canopies remains relatively unknown. Moderate severity disturbance including fire, ice storms, insect and pathogen outbreaks, affects different canopy strata and plant species, which may give rise to variable structural outcomes and ecological consequences. Terrestrial lidar (light detection and ranging) offers an unprecedented view of the interior arrangement and distribution of canopy elements, permitting the derivation of multidimensional measures of canopy structure that describe several canopy structural traits with known linkages to ecosystem functioning. We used lidar-derived canopy structural measured within a machine learning framework to detect and differentiate among various disturbance agents, including moderate severity fire, ice storm damage, age-related senescence, hemlock woolly adelgid, beech bark disease, and chronic acidification. We found that disturbance agents such as fire and ice storms primarily affected the amount and position of vegetation within canopies, while acidification, pathogen and insect infestation, and senescence altered canopy arrangement and complexity. Only two of the six disturbance agents significantly reduced leaf area, indicating that this commonly quantified canopy feature is insufficient to characterize many moderate severity disturbances. Rather, measures of canopy structure, including those that describe multidimensional change, are needed to characterize disturbance at moderate severities because structural changes from these events are spatially and quantitatively variable. Our findings suggest that standard disturbance detection methods, such as optical based remote sensing platforms, may currently be limited in their ability to detect, differentiate, and characterize disturbance. Further, we conclude that a more broadly inclusive definition of ecological disturbance that incorporates multiple aspects of canopy structure change will improve the modeling, detection, and prediction of functional implications of moderate severity disturbance.

Graphite nanoplatelets (GNPs) were produced from flake graphite that had been immersed in isopropyl alcohol solution (70%) and converted to powder form in an ultrasonic bath (5 h, room temperature). Scanning and transmission electron microscopy, X-ray diffractometry, and Raman spectroscopy identified 120-nm-thick GNP crystallites and 0.5–21 µm plates with different areas and shapes. Extensive exfoliation was observed by transmission electron microscopy with abundant multilayer and some monolayer GNPs. X-ray diffractometry confirmed 43 GNP layers along the c-axis. Raman spectroscopy indicated well-defined GNPs with few defects and no oxide content. Rietveld analysis indicated a GNP crystal lattice with stacks of parallel two-dimensional graphene layers and tightly bound hybridized carbon atoms stacked in a translational …ABAB… sequence in hexagonal rings.

Automatic methods for constructing navigation routes do not fully meet all requirements. The aim of this study was to modify the methodology for generating indoor navigation models based on the Medial Axis Transformation (MAT) algorithm. The simplified method for generating corridor axes relies on the Node-Relation Structure (NRS) methodology. The axis of the modeled structure (corridor) is determined based the points of the middle lines intersecting the structure (polygon). The proposed solution involves a modified approach to the segmentation of corridor space. Traditional approaches rely on algorithms to construct Triangulated Irregular Networks (TINs) by Delaunay triangulation or algorithms for generating Thiessen polygons known as Voronoi diagrams (VDs). In this study, both algorithms were used in the segmentation process. The edges of TINs intersect structures. Selected midpoints on TIN edges, which are located in the central part of the structure, are used to generate VDs. Polygon VDs segment corridor structures. The identifiers or structure nodes are the midpoints on TIN edges rather than the calculated centroids. The generated routes are not zigzag lines, and they approximate natural paths. The main advantage of the proposed solution is its simplicity which can be attributed to the use of standard tools for processing spatial data in a geographic information system.

Inexpensive piezoelectric diaphragms can be used as sensors to facilitate both nozzle height setting and build platform leveling in FFF (Fused Filament Fabrication) 3D printers. Tests simulating nozzle contact are conducted to establish the available output and an output of greater than 8 Volts found at 20 ºC, a value which is readily detectable by simple electronic circuits. Tests are also conducted at a temperature of 80 ºC and, despite a reduction of greater than 80% in output voltage, this is still detectable. The reliability of piezoelectric diaphragms is investigated by mechanically stressing samples over 100,000 cycles at both 20 ºC and 80 ºC and little loss of output over the test duration is found. The development of a nozzle contact sensor using a single piezoelectric diaphragm is described.

The capacity and the mechanism of the adsorption of aqueous barium (Ba), cobalt (Co), strontium (Sr) and zinc (Zn) by Ecuadorian (NatAllo) and synthetic (SynAllo-1 and SynAllo-2) allophanes were studied as a function of contact time, pH and metal ion concentration using kinetic and equilibrium experiments. The mineralogy, nano-structure and chemical composition of the allophanes were characterized by X-ray diffraction, Fourier transform infrared spectroscopy, transmission electron microscopy and specific surface area analyses. The evolution of adsorption fitted to a pseudo-first-order reaction kinetics, where equilibrium between aqueous metal ions and allophane was reached within < 10 min. The metal ion removal efficiencies varied from 0.7 to 99.7 % at pH 4.0 to 8.5. At equilibrium, the adsorption behavior is better described by the Langmuir model than by the Dubinin-Radushkevich model, yielding sorption capacities of 10.6, 17.2 and 38.6 mg/g for Ba^(2+), 12.4, 19.3 and 29.0 mg/g for HCoO_2^-, 7.2, 15.9 and 34.4 mg/g for Sr^(2+) and 20.9, 26.9 and 36.9 mg/g for Zn^(2+), respectively, by NatAllo, SynAllo-2 and SynAllo-1. The uptake mechanism is based on a physical adsorption process. Allophane holds great potential to remove aqueous metal ions and could be used instead of zeolites, montmorillonite, carbonates and phosphates for wastewater treatment.

Maxillofacial defects, arising from trauma, oncological disease or congenital differences, detrimentally affect everyday life. Prosthetic repair offers the aesthetic and functional reconstruction with the help of materials mimicking natural tissues, among which polymers take unprecedented role. The three-dimensional (3D) printing techniques based on the computer-aided design, where polymers are essential, provide a rapid and cost-effective workflow protocol to perfectly restore patient-specific anatomy for prosthetics. This review discusses the main 3D printing approaches to maxillofacial prostheses fabrication: extrusion and lithography, which are radically preferable to the traditional methods. The main assessment criteria, affording the polymer implementation in 3D printing of prostheses, as well as the characteristics of the key advanced polymers, are considered. The success of the prosthesis is shown to be largely dependent on the retention system, predominantly using polymers in the form of adhesives and osseointegrated implants as a support for the prosthesis. The approaches and technological prospects are also discussed in the context of specific aesthetic restoration on the example of the nasal, auricle and ocular prostheses. 3D printing techniques determine the development of personalized approaches to improve aesthetic and functional effect of prosthetics in patients with maxillofacial defects.

A new framework in quantum chemistry has been proposed recently ("An approach to first principles electronic structure calculation by symbolic-numeric computation'' by A. Kikuchi). It is based on the modern technique of computational algebraic geometry, viz. the symbolic computation of polynomial systems. Although this framework belongs to molecular orbital theory, it fully adopts the symbolic method. The analytic integrals in the secular equations are approximated by the polynomials. The indeterminate variables of polynomials represent the wave-functions and other parameters for the optimization, such as atomic positions and contraction coefficients of atomic orbitals. Then the symbolic computation digests and decomposes the polynomials into a tame form of the set of equations, to which numerical computations are easily applied. The key technique is Grröbner basis theory, by which one can investigate the electronic structure by unraveling the entangled relations of the involved variables. In this article, at first, we demonstrate the featured result of this new theory. Next, we expound the mathematical basics concerning computational algebraic geometry, which are necessitated in our study. We will see how highly abstract ideas of polynomial algebra would be applied to the solution of the definite problems in quantum mechanics. We solve simple problems in "quantum chemistry in algebraic variety'' by means of algebraic approach. Finally, we review several topics related to polynomial computation, whereby we shall have an outlook for the future direction of the research.

Based on panel data of 31 provincial-level administrative units (excluding Hong Kong, Macao and Taiwan) in China from 2015 to 2019, using fixed effect model and mediation effect model, this paper makes an empirical analysis on the interaction among digital economy, industrial structure upgrade and high-quality economic development. The results show that, from the overall effect, the digital economy can significantly promote the high-quality development of the economy, and there are regular regional differences, and the relationship between the promotion intensity and the development level of the digital economy is proportional. From the mediation effect, in the relationship between digital economy and high-quality economic development, the upgrade of industrial structure has played a significant part of the mediation effect, the proportion of mediation effect is 25.17% . In addition, the mediation effect of industrial structure upgrade has obvious regional difference, the western area is the strongest, the eastern area is the second, the central area is the weakest. Based on the above research,the concrete policy suggestions are given to promote the development of digital economy and upgrade the level of industrial structure to promote the high-quality development of economy.

Interest in drone solutions in forestry applications is growing. Using drones, datasets can be captured flexibly and at high spatial and temporal resolutions when needed. In forestry applications, fundamental tasks include the detection of individual trees, tree species classification, bio-mass estimation, etc. Deep Neural Networks (DNN) have shown superior results when comparing with conventional machine learning methods such as Multi-Layer Perceptron (MLP) in cases of huge input data. The objective of this research was to investigate 3D convolutional neural networks (3D-CNN) to classify three major tree species in a boreal forest: pine, spruce, and birch. The proposed 3D-CNN models were employed to classify tree species in a test site in Finland. The classifiers were trained with a dataset of 3039 manually labelled trees. Then the accuracies were assessed by employing independent datasets of 803 records. To find the most efficient set of feature combination, we compare the performances of 3D-CNN models trained with hyperspectral (HS) channels, RGB channels, and canopy height model (CHM), separately and combined. It is demonstrated that the proposed 3D-CNN model with RGB and HS layers produces the highest classification accuracy. The producer accuracy of the best 3D-CNN classifier on the test dataset were 99.6%, 94.8%, and 97.4% for pines, spruces, and birches, respectively. The best 3D-CNN classifier produced ~5% better classification accuracy than the MLP with all layers. Our results suggest that the proposed method provides excellent classification results with acceptable performance metrics for HS datasets. Our results show that pine class was detectable in most layers. Spruce was most detectable in RGB data, while birch was most detectable in the HS layers. Furthermore, the RGB datasets provide acceptable results for many low-accuracy applications.

This article is some review of results that were obtained at 2007-2021 years development of “The Information as Absolute” concept and the informational physical model, which is based on the concept; including a number of fundamental physical problems are briefly considered in framework of the conception and the model. Recently in physics there are several publications, that present lists of the problems. However, those lists are essentially incomplete, for at least two reasons. Firsts of all, a number of phenomena are studied traditionally by philosophy, and so corresponding problems are usually considered to be “metaphysical”. However, they relate also to some concrete physical phenomena. For example, physics evidently studies Matter, and so the metaphysical problems “what is ontology of Matter”, “what is “Space”, “Time” and a few other physical phenomena and notions as well, are really a Meta-physical problems “what does physics study?” There are other fundamental physical problems, which are not considered as such in physics, and are absent in the “fundamental problems lists”. Those include the problems, which really exist, yet are incorporated into standard physical theories, and so are fundamental “implicitly”, which in physics are “solved by default” ‒ and mostly erroneously. Note, though, that a number of “Meta-physical”, and concrete fundamental, problems more in detail are considered in the paper “The Informational Conception and Basic Physics”, https://arxiv.org/abs/0707.4657, v5 (2021), so this paper is, in certain sense, an expanded conclusion of this paper, which includes, correspondingly, more in detail consideration of some more general physical problems; and, besides, in this article, the problem “what are Gravity and Electric Forces” is essentially clarified comparing with the arXiv 2021 paper version above. Besides, the concrete problem “What is Life”, and the rational cosmological model, where a few vague points in standard cosmology rather probably are rationally clarified, while the fundamental problem “matter – antimatter asymmetry” in Matter is solved practically for sure, are considered, and one of recently published rather complete “lists of fundamental problems” is commented in Appendix.

Structure-based design and synthesis of two biphenyl-N-acyl-β-D-glucopyranosylamine derivatives as well as their assessment as inhibitors of human liver glycogen phosphorylase (hlGPa, a pharmaceutical target for type 2 diabetes) is presented. X-ray crystallography revealed the importance of structural water molecules and that the inhibitory efficacy correlates with the degree of disturbance caused by the inhibitor binding to a loop crucial for the catalytic mechanism. The in silico derived models of the binding mode generated during the design process corresponded very well with the crystallographic data.

This thesis completion works it out to deepen into diverse modeling techniques for Point Absorbers. A combined frequency-time domain model is conceived, designed and developed in Matlab with Fortran as a base, leading to obtain physical variables of primary importance, namely position, velocity and power to energy net balance relationships of absorption. Integration of different degrees of freedom with heave as main executable leads in turn to a single buoy motion focus. Acquisition of the needed hydrodynamic coefficients is provided through application of NEMOH \& BEMIO solvers due to the Boundary Element Methodology. Initially, this Wave-to-motion model is validated by comparison with previous experimental results for a floating cone cylinder shape (Buldra-FO3). A single, generic, vertical floating cylinder is contemplated then, that responds to the action of the passing regular waves excitation. Later, two equally sized vertical floating cylinders aligned with the incident wave direction are modeled for a variable distance between the bodies. For both unidirectional regular and irregular waves as an input in deep water, we approximate the convolutive radiation force function term through the Prony method. By changing the spatial disposition of the axisymmetric buoys, using for instance triangular or rectangular shaped arrays of three and four bodies respectively, the study delves into motion characteristics for regular waves. The results highlight efficient layouts for maximizing the energy production whilst providing important insights into their performance, revealing displacement amplification- and capture width-ratios, while deriving in possible interpretations of scenarios related to the the known park effect. These terms are encompassed by the novelty of a new conceptual Post-Processing methodology in the field, which leads to obtain an optimal distance for the separated bodies with effective energy absorption in a regular wave regime. In conclusion, this computational excursion envisions and proposes potential fields of study, which will surely enhance new connections and link this renewable energy form.

Unmanned aerial vehicles (UAV) provide an unprecedented capacity to monitor the development and dynamics of tree growth and structure through time. It is generally thought that the pruning of tree crops encourages new growth, has a positive effect on fruiting, makes fruit-picking easier, and may increase yield, as it increases light interception and tree crown surface area. To establish the response of pruning in an orchard of lychee trees, an assessment of changes in tree structure, i.e. tree crown perimeter, width, height, area and Plant Projective Cover (PPC), was undertaken using multi-spectral UAV imagery collected before and after a pruning event. While tree crown perimeter, width and area could be derived directly from the delineated tree crowns, height was estimated from a produced canopy height model and PPC was most accurately predicted based on the NIR band. Pre- and post-pruning results showed significant differences in all measured tree structural parameters, including an average decrease in tree crown perimeter of 1.94 m, tree crown width of 0.57 m, tree crown height of 0.62 m, tree crown area of 3.5 m², and PPC of 14.8%. In order to provide guidance on data collection protocols for orchard management, the impact of flying height variations was also examined, offering some insight into the influence of scale and the scalability of this UAV based approach for larger orchards. The different flying heights (i.e. 30, 50 and 70 m) produced similar measurements of tree crown width and PPC, while tree crown perimeter, area and height measurements decreased with increasing flying height. Overall, these results illustrate that routine collection of multi-spectral UAV imagery can provide a means of assessing pruning effects on changes in tree structure in commercial orchards, and highlight the importance of collecting imagery with consistent flight configurations, as varying flying heights may cause changes to tree structural measurements.

In 2011 over 1.7 million people were hospitalized because of a fragility fracture, and direct costs associated with osteoporosis treatment exceeded 70 billion dollars in the United States. Failure to reach and maintain optimal peak bone mass during adulthood is a critical factor in determining fragility fracture risk later in life. Physical activity is a widely accessible, low cost, and highly modifiable contributor to bone health. Here, we will review the evidence linking exercise and physical activity to bone health in women. Bone structure and quality will be discussed, especially in the context of clinical diagnosis of osteoporosis. We will review the mechanisms governing bone metabolism in the context of physical activity and exercise. Questions such as, when during life is exercise most effective, and what specific types of exercises improve bone health, will be addressed. Finally, we will discuss some emerging areas of research on this topic, and will summarize areas of need and opportunity.

This paper first explains the theory of the origin of force from a new perspective, explaining that the origin of all forces is caused by the "missing of energy in the time dimension" (non-conservation in a certain period of time), and constructs a unified theory of force on this basis. Then, through the unified theory of force, the following phenomena are reinterpreted: (1) The common origin of the inverse square law of gravitation and electromagnetic force; (2) The origin of the repulsive force of electrons and protons at small distances; (3) The mystery of the rotation curve of galaxies and the new explanation of "dark matter"; (4) explain the origin of the magnetic field; (5) Predict that moving magnets have the same radiation effect as charged particles (electron magnetic moments also have radiation effects); (6) Reinterpret Maxwell's displacement current; (7) Reinterpret synchrotron radiation and bremsstrahlung; (8) Explain that the strong and weak forces are short-range forces; (9) Predict the true structure of black holes and the origin of gravitational waves;(10) Possible explanation for the origin of the speed of light.

Three-dimensional convolutional neural networks (3D CNN) as a type of artificial intelligence (AI) are powerful in image processing and recognition using deep learning to perform generative and descriptive tasks. The advantage of CNN compared to its predecessors is that it automatically detects the important features without any human supervision. 3D CNN are used to extract features in three dimensions where input is a 3D volume or a sequence of 2D pictures e.g., slices in a cone-beam computer tomography scan (CBCT). The main aim of this article was to bridge interdisciplinary cooperation between forensic medical experts and deep learning engineers. With emphasis activating clinical forensic experts in the field with possibly basic knowledge of advanced artificial intelligence techniques with interest in its implementation in their efforts to advance the forensic research further. This paper introduces a novel workflow of 3D CNN analysis of full-head CBCT scans. Authors explore and present 3D CNN method for forensic research design concept in five perspectives: (1) sex determination, (2) biological age estimation, (3) 3D cephalometric landmark annotation, (4) growth vectors prediction, (5) facial soft-tissue estimation from the skull and vice versa. In conclusion, 3D CNN application can be a watershed moment in forensic medicine, leading to unprecedented improvement of forensic analysis workflows based on 3D neural networks.

In this paper, the nanoscale dissipative mechanisms of a Cu pad in a Ball Grid Array (BGA) packaging structure during isothermal ageing and uniaxial tension were investigated by the molecular dynamics (MD) method and experiments. From the result of the isothermal ageing test, a nonuniform consumption of Cu and large amount of Kirkendall voids were observed at the interface of Cu and Cu₃Sn. To study the effect of pressure and orientation on this phenomenon, MD simulations were conducted on four types of Cu-Cu₃Sn interface structures with different orientations of Cu. By comparing the diffusion coefficients of atoms in those cases, it was found that the tensile stress would inhibit the diffusion of atoms, whereas compressive stress would accelerate it, and this would be more significant under a larger magnitude of stress and temperature. Note that, in the model with the (101) surface Cu at the interface, both Cu and Cu₃Sn have a higher diffusion coefficient compared with the model with (001) surface Cu. Thus, the orientation of Cu will also contribute to the uniform consumption of the pad. Uniaxial tension simulation combined with DXA and CSP analyses on those models also shows the model with (001) surface Cu has a greater mechanical reliability in our simulations and related experiments.

The telomerase RNA in yeasts is large, usually >1000 nt, and contains functional elements that have been extensively studied experimentally in several disparate species. Nevertheless, they are very difficult to detect by homology-based methods and so far have escaped annotation in the majority of the genomes of Saccharomycotina. This is a consequence of sequences that evolve rapidly at nucleotide level, are subject to large variations in size, and are highly plastic with respect to their secondary structures. Here we report on a survey that was aimed at closing this gap in RNA annotation. Despite considerable efforts and the combination of a variety of different methods, it was only partially successful. While 27 new telomerase RNAs were identified, we had to restrict our efforts to the subgroup Saccharomycetacea because even this narrow subgroup was diverse enough to require different search models for different phylogenetic subgroups. More distant branches of the Saccharomycotina still remain without annotated telomerase RNA.

3D plotting is an additive manufacturing technology enabling biofabrication, thus the integration of cells or biologically sensitive proteins or growth factors into the manufacturing process. However, most (bio-)inks developed for 3D plotting were not shown to be processed into clinical relevant geometries comprising critical overhangs and cavities, which would collapse without a sufficient support material. Herein, we have developed a support hydrogel ink based on methylcellulose (mc), which is able to act as support as long as the co-plotted main structure is not stable. Therefore, 6 w/v %, 8 w/v % and 10 w/v % mc were allowed to swell in water, resulting in viscous inks, which were characterized for their rheological and extrusion properties. The successful usage of 10 w/v % mc as support ink was proven by multichannel plotting of the support together with a plottable calcium phosphate cement (CPC) acting as main structure. CPC scaffolds displaying critical overhangs or a large central cavity could be plotted accurately with the newly developed mc support ink. The dissolution properties of mc allowed complete removal of the gel without residuals, once CPC setting was finished. Finally, we fabricated a scaphoid bone model by computed tomography data acquisition and co-extrusion of CPC and the mc support hydrogel.

With the pressure of the increasing density of urban areas, some public infrastructures are moving to the underground to free up space above, such as utility lines, rail lines and roads. In the big data era, the three dimensional (3D) data can be beneficial to understand the complex urban area. Comparing to spatial data and information of the above ground, we lack of the precise and detailed information about underground infrastructures, such as the spatial information of underground infrastructure, the ownership of underground objects and the interdependence of infrastructures in the above and below ground. How to map reliable 3D underground utility networks and use it in the land administration? First, to explain the importance of this work and find a possible solution, this paper observes the current issues of the existing underground utility database in Singapore. A framework for utility data governance is proposed to manage the work process from the underground utility data capture to data usage. This is the backbone to support the coordination of different roles in the utility data governance and usage. Then, an initial design of the 3D underground utility data model is introduced to describe the 3D geometric and spatial information about underground utility data and connect it to the cadastral parcel for land administration. In the case study, the newly collected data from mobile Ground Penetrating Radar is integrated with the existing utility data for 3D modelling. It is expected to explore the integration of new collected 3D data, the existing 2D data and cadastral information for land administration of underground utilities.

AbstractWhile the technology is relatively new, low cost 3D printing has impacted many aspects of human life. 3D printers are being used as manufacturing tools for a wide variety of devices in a spectrum of applications ranging from diagnosis to implants to external prostheses. The ease of use and availability of 3D design software and low cost has made 3D printing an accessible manufacturing and fabrication tool in many research laboratories. 3D printers can print materials with varying density, optical character, strength and chemical properties providing platforms for a huge number of strategies that can be chosen for user’s needs. In this review, we focus on applications in biomedical diagnostics and how this revolutionary technique is facilitating development of low cost, sensitive and often geometrically complex tools. 3D printing in fabrication of microfluidics, supporting equipment, optical and electronic components of diagnostic devices is presented. Emerging diagnostic 3D bioprinting as a tool to incorporate living cells or biomaterials into 3D printing is also discussed.

Solar3D is an open-source software application designed to interactively calculate solar irradiation at three-dimensional (3D) surfaces in a virtual environment constructed with combinations of 3D city models, digital elevation models (DEMs), digital surface models (DSMs) and feature layers. The GRASS GIS r.sun solar radiation model computes solar irradiation based on two-dimensional (2D) raster maps for given day, latitude, surface and atmospheric conditions. With the increasing availability of 3D city models and demand for solar energy, there is an urgent need for better tools to computes solar radiation directly with 3D city models. Solar3D extends GRASS GIS r.sun from 2D to 3D by feeding the model with input, including surface slope, aspect and time-resolved shading, that is derived directly from the 3D scene using computer graphics techniques. To summarize, Solar3D offers several new features which, as a whole, distinguish itself from existing 3D solar irradiation tools: (1) the ability to consume massive heterogeneous 3D city models, including massive 3D city models such as oblique airborne photogrammetry-based 3D city models (OAP3Ds or integrated meshes); (2) the ability to perform near real-time pointwise calculation for duration from daily to annual; (3) the ability to integrate and interactively explore large-scale heterogeneous geospatial data. (4) the ability to calculate solar irradiation at arbitrary surface positions including at rooftops, facades and the ground. Solar3D is publicly available at https://github.com/jian9695/Solar3D.

Quantitative structure-activity relationship (QSAR) model is adopted to study the relationship between the chemical and physical properties of various substances and the structure. Through QSAR studies, the internal relationship between the invisible structure and the activity can be obtained. In this paper, a novel chaos-enhanced accelerate particle swarm algorithm (CAPSO) is proposed, which is used to molecular descriptors screening and optimization of the weights of back propagation artificial neural network (BP ANN). Then, the QSAR model based on CAPSO and BP ANN is put forward, hereinafter referred to as CAPSO BP ANN model. The prediction experiment showed that the CAPSO algorithm is a reliable method for screening molecular descriptors and the five molecular descriptors obtained by CAPSO algorithm could well characterize the molecular structure of each compound in pKa prediction. The experimental results also showed the CAPSO BP ANN model has a good performance in predicting the pKa values of various compounds, the absolute mean relative error, root mean square error, and square correlation coefficient are respectively 0.5364, 0.0632, and 0.9438, indicating the higher prediction accuracy and correlation. The proposed hybrid intelligent model can be applied in all kinds of engineering design, prediction of physical and chemical properties and intelligent calculation.

Calcineurin B-like proteins (CBL)-interacting protein kinases (CIPKs) by interacting with CBLs regulate developmental processes, hormone signalling transduction and mediate stress responses in plants. Although the genome of chickpea is available, information of CIPK gene family has been missing in chickpea. Here, a total of 22 CIPK encoding genes were identified in chickpea and characterized by in silico methods. We found a high structural conservation in chickpea CIPK family. Our analysis showed that chickpea CIPKs have evolved with dicots from common ancestors, and extensive gene duplication events have played an important role in evolution and expansion of CIPK family in chickpea. Most chickpea CIPK proteins localize in cytoplasm and nucleus. Promoter analysis revealed various cis-regulatory elements related to plant development, hormone signaling and abiotic stresses. Expression analysis indicated that CIPKs are significantly expressed in a spectrum of developmental stages, tissue/organs that hinted their important role in plant development. Several CIPK genes had specific and overlapping expressions in different abiotic stresses and seed development stages, suggesting the important role of CIPK family in abiotic stress signaling, and seed development in chickpea. Thus, this study provides the avenue for detailed functional characterization of CIPK family in chickpea and other legume crops.

Additive Manufacturing (AM) simplifies the fabrication of complex geometries. Its scope has rapidly expanded from the fabrication of pre-production visualization models to the manufacturing of end use parts driving the need for better part quality assurance in the additively manufactured parts. Machine learning (ML) is one of the promising techniques that can be used to achieve this goal. Current research in this field includes the use of supervised and unsupervised ML algorithms for quality control and prediction of mechanical properties of AM parts. This paper explores the applications of supervised learning algorithms - Support Vector Machines and Random Forests. Support vector machines provide high accuracy in classifying the data and is used to decide whether the final parts have the desired properties. Random Forests consist of an ensemble of decision trees capable of both classification and regression. This paper reviews the implementation of both algorithms and analyzes the research carried out on their applications in AM.

A monocular vision pose estimation and identification algorithm used on a small spacecraft for future orbital servicing is studied in this paper. A tracker spacecraft equipped with a short-range vision system is proposed to recover the 3D structural model of a space target in orbit and automatically identify its solar panels and main body using only visual information from an onboard camera. The proposed reconstruction and identification framework is tested using structure-from-motion and point cloud identification methods. The Efficient Perspective-n-Points (EPnP) descriptor is used for pose estimation. Triangulated points are used for component segmentation by means of orientation histogram descriptors. Experimental results based on laboratory images of a spacecraft model show the effectiveness and robustness of our approach.

This work shows the preliminary description of the origin of a sedimentary - exhalative outcrop of Jurassic Lower Pliensbachian. The location of this deposit was achieved by applying an examination based in the identification of sedimentary transgressions of heterochronies ages and the identification of a Rift – type mega –structure. According with the methodology, it was carried out a study of the discordant relationships between two types of sediments: continental and marine. According the characterization, it was noted the existence of light rare earths, in values that show positive anomalies in comparison with the distribution of elements in upper continental crust according to the Clarke [1], reflecting so a felsic affinity of the mineral deposit. Also, positive anomalies of platinum and Pd, were determined with marginal contents of Au and Ag; and finally the base metals Zn, Pb and Cu were detected in low contents, which could be due to the presence of altered shale. According to the sedimentary lithology found, which was of siliciclastic type; to the exhalative roots observed during the fieldwork; the presence of quartz minerals such as biotite and muscovite; the presence of minerals of hydrothermal remobilization like chalcopyrite with some base metals, altered shale, as well as sulfur deficiency; this mineral reservoir could be defined as a SEDEX – type.

Psoriasis is a chronic immune-mediated skin disease that involves interaction of both immune and skin cells, and is characterized by cytokine-driven epidermal hyperplasia, deviant differentiation, inflammation and angiogenesis. Because available treatments for psoriasis have significant limitations, dietary products are potential natural sources of therapeutic molecules, which can rescind molecular defects associated with psoriasis and could be developed for its management. Fisetin (3,7,3′,4′- tetrahydroxyflavone), a phytochemical naturally found in pigmented fruits and vegetables has demonstrated pro-apoptotic and antioxidant effects in several malignancies. This study utilized biochemical, cellular, pharmacological and tissue-engineering tools to characterize the effects of fisetin on normal human epidermal keratinocytes (NHEKs), peripheral blood mononuclear cells (PBMC) and CD4+ T lymphocytes in 2D and 3D psoriasis-like disease models. Fisetin treatment of NHEKs dose and time-dependently induced differentiation and inhibited interleukin-22-induced proliferation, as well as activation of the PI3K/Akt/mTOR pathway. Fisetin treatment of TNF-α-stimulated NHEKs significantly inhibited the activation of p38 and JNK, but had no effect on ERK1/2. In addition, fisetin treatment significantly decreased the secretion of Th1/Th-17 pro-inflammatory cytokines, particularly IFNγ and IL-17A by 12-O- tetradecanolylphorbol 13-acetate (TPA)-stimulated NHEKs and anti-CD3/CD28-activated human PBMCs. Furthermore, we established the in-vivo relevance of fisetin functions, using a 3D full-thickness human skin model of psoriasis (FTRHSP) that closely mimics in-vivo human psoriatic skin-lesions. Herein, fisetin significantly ameliorated psoriasis-like disease features, and decreased the production of IL-17 by CD4+ T lymphocytes co-cultured with FTRHSP. Collectively, our data identify pro-differentiative, anti-proliferative and anti-inflammatory effects of fisetin, via modulation of PI3K-Akt-mTOR and p38/JNK pathways and the production of cytokines in 2D and 3D human skin model of psoriasis. These results suggest that fisetin has a great potential to be developed as an effective and inexpensive agent for the treatment of psoriasis and other related inflammatory skin disorders.

We investigated the properties of architected materials made from UV-cured urethane elastomers and the use of such materials for insoles. The durability and reliability of various materials currently used in medical insoles were compared with those of architected materials with microlattice. The results show that architected materials made from UV-cured urethane elastomers have high impact resilience and grip, and the hardness can easily be changed by adjusting the column diameter of the unit cell. Compared with the foam materials used for medical insoles today, these architected materials also demonstrate superior UV resistance, suggesting that, after being washed in water, they can be air-dried outdoors.

Comparison of the influence of conditioning temperature of microspheres made of medical grade poly(L-lactide) (PLLA) and polylactide with 4wt.% of D-lactide content (PLA), on its thermal and structural properties is presented. The microspheres were fabricated by solid-in-oil-in-water method for application in additive manufacturing. The microspheres were annealed below glass transition temperature (Tg), above Tg but below onset of cold crystallization, and at two temperatures selected from the range of cold crystallization corresponding to crystallization of α’ and α form of poly(L-lactide) respectively, i.e., at 40°C, 70°C, 90°C and 120°C, in order to verify the influence of conditioning temperatures on sinterability of microspheres set as sintering window (SW). Based on differential scanning calorimetry measurements SW of microspheres were evaluated with consideration of existence of cold crystallization and reorganization of crystal polymorph. The results indicate that the conditioning temperature influence on availability and range of SW that depending on the D-lactide presence. We postulate the need for an individual approach for polylactide powders in determining the SW as a temperature range free of any thermal events. Moreover, other core powder characteristic, such as residual solvent content, morphology, particle size distribution, powder flowability and thermal conductivity, as a key property for successful laser sintering, are characterized. The microspheres are close to sphere and the size of microspheres are below 100 µm. Residual solvents content decreases with the increase of annealing temperature. The thermal conductivity is 0.073 W/mK and 0.064 W/mK for PLA and PLLA microspheres, respectively, and it depends on the spherical shape of the microspheres. Furthermore, the WAXD studies prove that an increase in the conditioning temperature causes a slight increase in crystallinity degree for PLLA microspheres and clear increase in crystallization for PLA microspheres.

By means of X-ray computed microtomography (XCMT) the existence of a developed microporous structure having an average pore diameter of ~3.5 μm and pore content of ~1.1 vol.% has been revealed in unirradiated polytetrafluoroethylene (PTFE). It has been found that the combined action of gamma radiation (absorbed dose per PTFE of ~170 kGy) and high temperatures (327-350 °C) leads to the disappearance of the microporous structure and the formation of several large pores with sizes from 30 to 50 μm in the bulk of thermal-radiation modified PTFE (TRM-PTFE). It has been established by X-ray diffraction (XRD) analysis that the thermal-radiation modification of PTFE leads to an increase in the interplanar spacings, the degree of crystallinity and volume of the unit cell, as well as to a decrease in the size of crystals and the X-ray density of the crystalline phase in comparison with the initial polymer. It is assumed that the previously established effect of improving the deformation-strength and tribological properties of the TRM-PTFE can be due not only to the radiation cross-linking of polymer chains but also to the disappearance of the micropore system and to the ordering of the crystalline phase of PTFE.

Integrated information theory (IIT) was initially proposed to describe human consciousness in terms of intrinsic, causal brain-network structures. This theory has the potential to be useful for conceptualising complex living systems. In a previous study, we analysed collective behaviour in Plecoglossus altivelis and found that IIT 3.0 exhibits qualitative discontinuity between three and four fish. Other measures like mutual information did not have such characteristics. In this study, we followed up on our previous findings and examined timescale effects on integrated information of collective behaviour. We found that a long timescale (1 s) causes Boid-like local interactions to dominate over interactions with the whole, but only when the group size is five at a given time scale (i.e. around 0.2 s). Interestingly, the most suitable time scale is roughly equal to fish reaction time. We used these data to propose a new classification for fish schools, with each size group being a unique and autonomous system, despite small group sizes.

In crystal structure prediction, Newton's second law can always be applied to particles (atoms or ions) in a cell to determine their positions. However the values of the period vectors (crystal cell edge vectors) should be determined as well. Here we applied the dynamical equations of period vectors derived recently based on Newton's laws (doi:/10.1139/cjp-2014-0518) for that purpose, where the period vectors are driven by the imbalance between the internal and external pressures/stresses. For equilibrium states, they became equations of state, which essentially turn out the equilibrium conditions of crystals from mechanical point of view. For external pressure, by ignoring some effects, they reduced to the Mie-Gruneisen equation. Since the internal stress has both a full kinetic energy term and a full interaction term, the influences of both external temperature and stress/pressure on crystal structures can be calculated, then thermodynamical properties and processes were presented. Contrary to usual ideas, the equations show that pure harmonic vibrating phonons can result in thermal expansion in crystals when the external temperature is changed. Finally, crystal system collapse due to temperature and/or stress/pressure change was discussed.

Proteins play a major role in biosensors in which they provide catalytic activity and specificity in molecular recognition. The immobilization process is however far from straightforward as it often affects the protein functionality. An extensive interaction of the protein with the surface or a significant surface crowding can lead to changes in the mobility and conformation of the protein structure. This review will provide an insight of how the analysis of the physico-chemical features of the protein surface features before the immobilization process can help to identify the optimal immobilization approach to preserve the functionality of the protein when on the surface of the biosensor.

Thunderstorm electrification has been studied for hundreds of years. Several mechanisms have been proposed to elucidate the electrification, including convective charging, inductive precipitation charging, and ice crystal-graupel collision charging. Field observations and model studies have demonstrated the vital roles that graupel and ice crystals play in the electrification, but the mechanism of the collision charging is still unclear. The fundamental essence of relative growth rate theory used for explaining the tripole charge structure in thunderclouds also needs a further exploration. We analyze the processes of ice crystal-graupel collision charging from charge migration inside hydrometeors to charge separation between two hydrometeors. The driving effects of temperature gradient and chemical potential gradient in charge migration are clarified, as well as the applicability of the relative growth rate theory, thermoelectric effect and surface tension gradient in different humidities. Based on the understanding from these electrification mechanisms, we propose that the essence of charge separation is driven by non-thermal equilibrium, and future studies on thunderstorm electrification should focus on the dynamical non-thermal equilibrium of cloud particles.

Conservation of natural habitats in human-dominated landscapes is critical for halting biodiversity loss. Maintaining habitat quantity and connectivity requires landscape-level collective action, which results from environmental decisions made by individual land owners. We investigate how individual decision making in a rural collective translates into quantitative differences in landscape-level environmental outcomes. Behavioral science has become a critical domain of knowledge in conservation, but little attention has been paid to how multiple behavioral drivers determine the success of collective environmental action. We developed a social-ecological model for landscape-level conservation using a detailed data set of 600 land owners in New Zealand. With the model, we tested whether the effect of social influence networks on collective conservation action was altered by their interplay with land owners’ personal characteristics, connections to cross-scale actors and local environmental contexts. Interactions between multiple behavioral drivers determined the environmental outcomes of collective action in unexpected ways by modifying, muting or amplifying the effects of single drivers. Importantly, we detected a social-ecological mechanism for rapid change in the extent of protected habitats, which can explain highly successful or failed environmental outcomes of collective conservation. Further, when environmentally desirable and undesirable behaviors spread simultaneously through the social network, homophily and network cohesion hinder desirable environmental outcomes. This effect can be modified by other drivers such as social responses to local environmental change. Thus, understanding how the antagonistic and synergistic effects of behavioral drivers can be best utilized in conservation will benefit biodiversity and ensure benefits that humans obtain from biodiversity.

This article presents description of social structures such as, for example, states, in the context of their consideration as systems. Moreover, it seeks to develop K. Marx’s model in terms of systematic approach, as well as to justify the application of the Fibonacci sequence to systems in general and, in particular, to social systems. The description covers a wide range of issues, ranging from the assertion of the basic principle of living systems as patterns in resources flows to description of functions of various aspects of states and their economics in terms of objective needs of such structures. In addition, this article justifies synergetic effect based on proposed model, and the way this effect is applied to state systems. Moreover, it includes the description of main changes of socio-economic formations throughout the history as a natural development of social systems, including possible modern stages. The fundamental tool of this description is description of essence of the mechanism of property rights and its formation options. The differences of two extreme directions of such development are also described on the basis of the objective factor of resource provision. Special attention is given to the concept of surplus value as a feature of social production systems.

A fast calculation method for the full parallax high-resolution hologram is proposed based on the elemental light field image (EI) rendering. A 3D object located near the holographic plane is firstly rendered as multiple EIs with a pinhole array. Each EI is interpolated and multiplied by a divergent sphere wave and interfered with a reference wave to form a hogel. Parallel acceleration is used to calculate the high-resolution hologram because calculation of each hogel is independent. A high-resolution hologram with the resolution of 20,0000×20,0000 pixels is calculated only within 8 minutes. Full parallax high-resolution 3D displays are realized by optical reconstructions.

Histone Lysine Specific Demethylase 1 (LSD1) is overexpressed in many cancers and become a new target for anticancer drugs. In recent years, the small molecule inhibitors with various structures targeting LSD1 have been reported. Here we report the binding interaction modes of a series of thieno[3,2-b]pyrrole-5-carboxamides LSD1 inhibitors using molecular docking, three dimensional quantitative structure-activity relationship (3D-QSAR). Comparative molecular field analysis (CoMFA q²=0.783, r²=0.944, r²_pred=0.851) and Comparative molecular similarity indices analysis (CoMSIA q²=0.728, r²=0.982, r²_pred=0.814) were used to establish 3D-QSAR models, which had good verification and prediction capabilities. Based on the contour maps and the information of molecular docking, 8 novel small molecules were designed in silico, among which compounds D4, D5 and D8 with high predictive activity were subjected to further molecular dynamics simulations (MD), and their possible binding modes were explored. It was found that Asn535 plays a crucial role in stabilizing the inhibitors. Furthermore, the ADME and bioavailability prediction for D4, D5 and D8 were carried out. The results would provide valuable guidance for designing new reversible LSD1 inhibitors in the future.

Forest canopy structure (CS) controls many ecosystem functions and is highly variable across landscapes, but the magnitude and scale of this variation is not well understood. We used a portable canopy lidar system to characterize variation in five categories of CS along N = 3 transects (140–800 m long) at each of six forested landscapes within the eastern USA. The cumulative coefficient of variation was calculated for subsegments of each transect to determine the point of stability for individual CS metrics. We then quantified the scale at which CS is autocorrelated using Moran’s I in an Incremental Autocorrelation analysis. All CS metrics reached stable values within 300 m but varied substantially within and among forested landscapes. A stable point of 300 m for CS metrics corresponds with the spatial extent that many ecosystem functions are measured and modeled. Additionally, CS metrics were spatially autocorrelated at 40 to 88 m, suggesting that patch scale disturbance or environmental factors drive these patterns. Our study shows CS is heterogeneous across temperate forest landscapes at the scale of 10’s of meters, requiring a resolution of this size for upscaling CS with remote sensing to large spatial scales.

During the 1970s, Tunisian durum wheat landraces were replaced progressively by modern cultivars. These landraces are nowadays maintained by smallholder farmers in some ecological niches and are threatened gradually by extinction resulting on the narrowing of the genetic diversity. This study aims to investigate patterns of phenotypic variability using twelve quantitative traits in a panel of 189 durum wheat landraces and seven checks, based on farmer’s population name attribution and genetic structure. Our results showed high phenotypic variability among and within landraces and checks for the majority of the studied traits. The principal components analysis showed similar grouping using farmers name attribution and genetic structure using K = 6, which confirmed the identification of a new gene pool in the oases of Tunisia, represented by the sub-population Jenah Zarzoura and the robustness and high relationships between phenotypic and genome-wide genetic structure using DArTseq method. These findings will enhance the conservation efforts of these landraces and their use in breeding efforts at national and international levels to adapt to dry conditions.

Hepcidin-25 was identified as the main iron regulator in the human body by binding to the sole iron-exporter ferroportin. Studies showed that the N-terminus of hepcidin is responsible for this interaction, the same N-terminus that encompasses a small copper(II)-binding site known as ATCUN (amino terminal Cu(II)- and Ni(II)- binding) motif. Interestingly, this copper-binding property is largely ignored in most papers dealing with hepcidin-25. In this context, detailed investigations of the formed complex of hepcidin-25 with copper could reveal insights into its biological role. The present work is mainly focused on the study of the metal-bound form of hepcidin-25, which could be considered the biologically active form. The first part is devoted to the reversed-phase chromatographic separation of copper-bound and copper-free hepcidin-25, which was achieved by applying basic mobile phases containing 0.1% ammonia. Further, mass spectrometry (tandem mass spectrometry MS/MS, high resolution mass spectrometry HRMS) and nuclear magnetic resonance (NMR) spectroscopy were employed to characterize the copper-peptide. Lastly, a 3D model of hepcidin-25 with bound copper(II) is presented. The identification of metal complexes and potential isoforms and isomers, from which the latter usually are left undetected by mass spectrometry, led to the conclusion that complementary analytical methods are needed to characterize a peptide calibrant or reference material comprehensively. Quantitative nuclear magnetic resonance (qNMR), inductively-coupled plasma mass spectrometry (ICP-MS), ion-mobility spectrometry (IMS) and chiral amino acid analysis (AAA) should be considered among others.

Purpose: The aim of the present experimental 3D-finite element study was to evaluate the influence of an augmented sinus lift with an additional inserted bone graft block. The bone graft block stabilizes the implant in addition to conventional augmented bone. We placed the block in three different positions. The implants were loaded with axial force and forces secondary to laterotrusion and protrusion. Material and Methods: A simplified U-shaped 3D finite element model of the upper jaw and a more complex anatomical model of the left maxilla were created. The bone graft block was placed in three positions: in the lower third in contact with the sinus floor, the middle, and the upper third of the implant. Van Mises’ stress distribution was calculated and analyzed for the different models. We also compared the complex anatomical model with the simplified one. Results: The position of the bone graft block significantly influences the magnitude of stress distribution. A bone graft block positioned in the upper third or middle of the implant reduces the quantity of stress compared to the reference model without a bone graft block. The low bone graft block position is clearly associated with lower stress distribution in compact bone. We registered no significant differences in stress in compact bone with regard to laterotrusion or protrusion. Conclusions: Maximum values of von Mises stresses in compact bone can be reduced significantly by using a bone graft block. The reduction of stress is nearly the same for positions in the upper third and the middle of the implant. It is much more pronounced when the bone graft block is in the lower third of the implant near the sinus floor, which appeared to be the best position in the present study.

The application of solvent method in the preparation of polypropylene powders was investigated, including the influence of various technological conditions, such as the raw material melt index of polypropylene, processing temperature, dosage of the solvent and the packing pressure. The experimental data show that using solvent method can effectively produce polypropylene powder, and the optimal technological conditions are: melt index of polypropylene being about 17.8 g/10min, processing temperature being about 166.0 ℃, dosage of the solvent being about 0.067g/ml and the packing pressure being about 0.7MPa.Under this technological conditions, polypropylene powder with excellent sphericity could be prepared, the apparent density of powder can reach 0.40 g/cm3 and the prepared powder displayed a narrow size distribution with the mean size of about 42.7 µm.

Development of novel anti-cancer peptides requires a rapid screening process which can be accelerated by using appropriate in vitro tumor models. Breast carcinoma tissue is a three dimensional (3D) microenvironment, which contains a hypoxic center surrounded by dense proliferative tissue. Biochemical clues provided by such 3D cell mass cannot be recapitulated in conventional 2D culture systems. In this experiment, we evaluate the efficacy of the sandalwood peptide, cyclosaplin on established in vitro 3D silk breast cancer model using invasive MDA-MB-231 cell line. The anti-proliferative effect of the peptide on 3D silk tumor model is monitored by alamar blue assay, with conventional 2D culture as control. The proliferation rate, glucose consumed, LDH, and MMP-9 activity of Human breast cancer cells are higher in 3D constructs compared to 2D. A higher concentration of drug is required to achieve 50% cell death in 3D culture than 2D cultures. The cyclosaplin treated MDA-MB-231 cells showed significant decrease in MMP-9 activity in 3D constructs. Microscopic analysis revealed the formation of cell clusters evenly distributed in the scaffolds. The drug treated cells were less in number, smaller and showed unusual morphology. Overall, these findings indicate the role of cyclosaplin as a promising anti-cancer therapeutics.

Modelling errors, robust stabilization/tracking problems under parameter and model uncertainties complicate the control of the flexible underactuated systems. Chattering-free sliding-mode based input-output control law realizes robustness against the structured and unstructured uncertainties in the system dynamics and avoids excitation of unmodeled dynamics. The main purpose is to propose a robust adaptive solution for stabilizing and tracking direct-drive (DD) flexible robot arms under parameter and model uncertainties, as well as external disturbances. A lightweight robot arm subject to external and internal dynamic effects was taken into consideration. The challenges are compensating actuator dynamics with the inverter switching effects and torque ripples, stabilizing the zero dynamics under parameter/model uncertainties and disturbances while precisely track the predefined reference position. The precise control of this kind of system demands an accurate system model and knowledge of all sources that excite unmodeled dynamics. For this purpose, equations of motion for a flexible robot arm were derived and formulated for the large motion via Lagrange’s method. The goals were determined to achieve high-speed, precise position control, and satisfied accuracy by compensating the unwanted torque ripple and friction that degrades performance through an adaptive robust control approach. The actuator dynamics and their effect on the torque output were investigated due to the transmitted torque to the load side. The high-performance goals, precision&robustness issues, and stability concerns were satisfied by using robust-adaptive input-output linearization-based control law combining chattering-free sliding mode control (SMC) while avoiding the excitation of unmodeled dynamics.

The purpose of this research has been to analyze the organizational structures of the different federations and entities representing the modalities of trail-running, skyrunning and mountain running and how they have settled in the current sports landscape. The main task of these entities is to act as hosts of the legally established modalities, both internationally and nationally, applying their respective regulations and statutes unilaterally. Through an in-depth review of the different regulations, statutes and current articles of all the organizations that represent the different disciplines, we can observe how a sport modality that seems to be the same is nevertheless distant in its execution (regulations, championships, classifications, systems of points, ...) and that has led to the international level being established in different sport modalities (trail-running and skyrunning) and at the level of the Spanish territory, it has led to an administrative dispute to know who has the powers to approve the sports competitions.

The disruption of conventional manufacturing, supply, and distribution channels for medical supplies during the COVID-19 pandemic has caused widespread shortages and catalyzed local efforts to use nontraditional, rapid manufacturing to meet urgent healthcare needs. Here we present a crisis-responsive design framework designed to assist with product development under pandemic conditions. The framework utilizes extensive stakeholder engagement, comprehensive and dynamic needs assessment, local manufacturing, and product testing for the accelerated development of healthcare products. We contrast this framework with traditional medical device manufacturing and discuss relevant regulatory policies. We highlight the applicability of the crisis-responsive framework to a successful local program that designed and supplied face shields for a large US academic hospital. Finally, we make recommendations aimed at improving future resilience to healthcare emergencies. These include continued development of open source designs suitable for rapid manufacturing and changes in regulatory policy that strike a balance between rigidity and uncontrolled innovation.

In the work, the nuclei structure was modeled by a system of shells consisting of combinations of spherical and annular vortices. Having connected the spin and the magnetic moments of the nuclei with the dynamics of the outer shell of the nucleus, we determined its type and carried out a semiempirical calculation of the parameters of its structure for stable and unstable nuclear isotopes in the sequence of the order number Z from 1 to 37. Comparison of the obtained nuclear sizes with the radii of the electron shells of atoms made it possible to reveal a definite correlation. On the basis of it, it was concluded that the periodic law of Mendeleyev can determine the patterns in the change in the structure of the atomic nucleus.

We propose a computer-generated hologram method for near-eye virtual reality and augmented reality 3D display. A 3D object located near the holographic plane is projected onto a projection plane to obtain a plurality of projected images with different angles. The hologram is calculated by superposition of projected image convolution with a specific PSF through the interference of reference wave with object wave. Holographic 3D display systems with LED as illumination, 4f optical filtering system and lens as eyepiece for near-eye VR display and HOE as combiner for near-eye AR display are designed. The results show that the proposed method is about 38 times faster than the conventional point cloud method. The proposed method is flexible to produce speckle noise free high-quality VR and AR images with efficient focus and defocus capabilities.

Shear connectors are used in steel beam–concrete slabs of composite frame and bridge structures to transfer shear force according to design loads. The existing Y-type perfobond rib shear connectors are designed for girder slabs of composite bridges. Therefore, the rib and transverse rebars of the conventional Y-type perfobond rib shear connectors are extremely large for the composite frames of building structures. We performed push-out tests of stubby Y-type perfobond rib shear connectors for composite frames. These shear connectors have relatively small ribs than conventional Y-type perfobond rib shear connectors. To confirm the shear resistance of these stubby shear connectors, we performed an experiment by using transverse rebars D13 and D16. The results indicate that these shear connectors have suitable shear strength and ductility for application in composite frame structures. The shear strengths obtained using D13 and D16 were not significantly different. However, the ductility of the shear connectors with D16 was 45.1% higher than that of the shear connectors with D13.

Sterile alpha motif domain-containing protein 9 (SAMD9) is a regulatory protein centrally involved in cell proliferation and apoptosis. Mapped to 7p21.1, variants in SAMD9 have been reported in &lt;50 pediatric cases worldwide, typically with early lethality. Germline gain-of-function SAMD9 variants are associated with MIRAGE Syndrome (myelodysplasia, infection, restricted growth, adrenal hypoplasia, genital anomalies, and enteropathy). Spalt like transcription factor 1 (SALL1) is a zinc finger transcriptional repressor located at 16q12.1 where only two transcript variants in SALL1 are known. RUNX2 (6p21.1) encodes a nuclear protein with a Runt DNA-binding domain critical for osteoblastic differentiation, skeletal morphogenesis, and serves as a scaffold for nucleic acids and regulatory factors involved in skeletal gene expression. RUNX2 and SALL1 are thus both ‘master regulators’ of tissue organization and embryo development. Here, we describe exome sequencing and copy number variants in two previously unknown mutations—R824Q in SAMD9, and Q253H in SALL1. A new multiexon 3’ terminal duplication in RUNX2 is also reported. This is the first known phenotype characterization for the intersection of all three variants in a healthy 46,XX adult. Focusing on developmental progress, ultrastructural renal anatomy, and selected reproductive aspects, we describe this unique genotype diagnosed incidentally during Covid-19 illness. Individual disruption in SAMD9, RUNX2, or SALL1 would be expected to give a bleak prognosis. However, the convergence discovered here appears to dampen severe pathology, perhaps by cross-gene silencing of effects normally deleterious when such changes occur alone.

Designing motion representations for the problem of 3D human action recognition from skeleton sequences is an important yet challenging task. An effective representation should be robust to noise, invariant to viewpoint changes and result in a good performance with low-computational demand. Two main challenges in this task include how to efficiently represent spatio-temporal patterns of skeletal movements and how to learn their discriminative features for classification task. This paper presents a novel skeleton-based representation and a deep learning framework for 3D action recognition using RGB-D sensors. We propose to build an action map called SPMF (Skeleton Posture-Motion Feature), which is a compact image representation built from skeleton poses and their motions. An Adaptive Histogram Equalization (AHE) algorithm is then applied on the SPMF to enhance their local patterns and form an enhanced action map, namely Enhanced-SPMF. For learning and classification tasks, we exploit Deep Convolutional Neural Networks based on the DenseNet architecture to learn directly an end-to-end mapping between input skeleton sequences and their action labels via the Enhanced-SPMFs. The proposed method is evaluated on four challenging benchmark datasets, including both individual actions, interactions, multiview and large-scale datasets. The experimental results demonstrate that the proposed method outperforms previous state-of-the-art approaches on all benchmark tasks, whilst requiring low computational time for training and inference.

The capacity of 3D printing (3DP) technologies to initiate speedy polymerization of solvent free resins accounts for their utility in the manufacturing of medical devices. Nonetheless, independent biological evaluation of 3D printed materials is recommended due to the unique parameters of the manufacturing process, which can influence their physical, chemical, and biological properties. In this study, E-Shell 450 material indicated for 3DP of hearing aid shells and inner ear devices was examined for biological safety using zebrafish bioassays adapted to OECD fish embryo test. In addition, the proprietary material was characterized for composition using headspace gas-chromatography mass spectrometry (GC-MS). To initiate test, newly fertilized zebrafish eggs were cultured on non-treated and ethanol-treated materials in glass petri dishes with ultrapure water, incubated at 28.5°C and assessed for developmental endpoints of toxicity at 24h interval until 96h. Data confirmed non-treated material was extremely toxic in bioassays within 24h whereas ethanol-treated material showed a relative lower toxicity possibly due to ethanoic-aqueous interactions as observed by GC-MS. With the current influx of 3D printing materials, users are urged to exercise caution. Operators must also take cognizance of the potential toxicity of the chemicals used in 3DP and implement safety measures to limit their exposure.

The extrusion-based 3D concrete printing (3DCP) technology allows the fabrication of permanent formwork with intricate shapes, into which fresh concrete is cast to build structural members with complex geometry. This significantly enhances the geometric freedom of concrete structures without the use of expensive temporary formwork. In addition, with proper material choice for the permanent formwork, the load-bearing capacity and durability of the resulting structure can be improved. This paper investigates 3DCP of permanent formwork for reinforced concrete (RC) beam construction. A 3D-printable engineered geopolymer composite (3DP-EGC, or strain-hardening geopolymer composite, 3DP-SHGC) recently developed by the authors was used for fabrication of the permanent formwork. The 3DP-EGC exhibits strain-hardening behaviour under direct tension. Two different printing patterns were used for the soffit of the permanent formwork to investigate the effect of this parameter on the flexural performance of RC beams. A conventionally mould-cast RC beam was also prepared as the control beam for comparison purposes. The results showed that the RC beams constructed using the 3DP-EGC permanent formwork exhibited superior flexural performance to the control beam. Such beams yielded significantly higher cracking load (up to 43%), deflection at ultimate load (up to 60%), ductility index (50%) and absorbed energy (up to 107%) than those of the control beam. The ultimate load was comparable with or slightly higher than that of the control beam. Furthermore, the printing pattern at the soffit of the permanent formwork was found to have a significant influence on the flexural performance of the RC beams.

Purpose: To improve numerical simulation of the non-contact tonometry test by using Arbitrary Eulerian-Lagrangian deforming mesh in the coupling between computational fluid dynamics model of an air jet and finite element model of the human eye. Methods: Computational fluid dynamics model simulated impingement of the air puff and consisted of 25920 wedge6 elements and employed Spallart-Allmaras model to simulate capture turbulence of the air jet. The time span of the jet wais 30 ms and maximum Reynolds number

In this article we review the advances that have been made on the understanding of the high-pressure structural, vibrational, and electronic properties of wolframite-type oxides since the first works in the early 1990s. Mainly tungstates, which are the best known wolframites, but also tantalates and niobates, with an isomorphic ambient-pressure wolframite structure, have been included in this review. Apart from estimating the bulk moduli of all known wolframites; the cation-oxygen bond distances and their change with pressure have been correlated with their compressibility. The composition variations of all wolframites have been employed to understand their different structural phase transitions to post-wolframite structures as a response to high pressure. The number of Raman modes and band gap energy changes have been also analyzed in the basis of these compositional differences. The reviewed results are relevant for both fundamental science and for the development of wolframites as scintillating detectors. The possible next research venues of wolframites have also been evaluated.

Thermal infrared imagery provides temperature information on target objects, and has been widely applied in non-destructive testing. However, thermal infrared imagery is not always able to display detailed textures of inspected objects, which hampers the understanding of geometric entities consisting of temperature information. Although some commercial software has been developed for 3D thermal model displays, the software requires the use of expensive specific thermal infrared sensors. This study proposes a cost-effective method for 3D thermal model reconstruction based on image-based modeling. Two smart phones and a low-cost thermal infrared camera are employed to acquire visible images and thermal images, respectively, that are fused for 3D thermal model reconstruction. The experiment results demonstrate that the proposed method is able to effectively reconstruct a 3D thermal model which extremely approximates its corresponding entity. The total computation time for the 3D thermal model reconstruction is intensive while generating dense points required for the creation of a geometric entity. Future work will improve the efficiency of the proposed method in order to expand its potential applications to in-time monitoring.

The present review paper aims at collecting and discussing the research work, numerical and experimental, carried out in the field of Fluid-Structure Interaction (FSI) in one-dimensional (1D) pressurized transient flow in the time-domain approach. Background theory and basic definitions are provided for the proper understanding of the assessed literature. A novel frame of reference is proposed for the classification of FSI models based on pipe degrees-of-freedom. Numerical research is organized according to this classification, while an extensive review on experimental research is presented by institution. Engineering applications of FSI models are described and historical accidents and post-accident analyses documented.

Diarrhoea caused by enterotoxigenic Escherichia coli is one of the leading causes of mortality in children under five years of age and is a great burden on developing countries. The major virulence factor of the bacterium is the heat-labile enterotoxin (LT), a close homologue of the cholera toxin. The toxins bind to carbohydrate receptors in the gastrointestinal tract, leading to toxin uptake and, ultimately, to severe diarrhoea. Previously, LT from human- and porcine-infecting ETEC (hLT and pLT, respectively) were shown to have different carbohydrate-binding specificities, in particular with respect to N-acetyllactosamine-terminating glycosphingolipids. Here, we probed eleven single-residue variants of the heat-labile enterotoxin with surface plasmon resonance spectroscopy and compared the data to the parent toxins. In addition we present a 1.45 Å crystal structure of pLTB in complex with branched Lacto-N-neohexaose (Galbeta4GlcNAcbeta6[Galbeta4GlcNAcbeta3]Galbeta4Glc). The largest difference in binding specificity is caused by mutation of residue 94, which links the primary and secondary binding sites of the toxins. Residue 95 (and to a smaller extent also residues 7 and 18) also contribute, whereas residue 4 shows no effect on monovalent binding of the ligand and may rather be important for multivalent binding and avidity.

Abies beshanzuensis, an extremely endangered species, attracts serious concerns on genetic diversity recovery and population protection. However, little genetic information was known about it till now. In this study, intra-/intergenomic ITS variation, secondary structure, and molecular phylogeny of A.beshanzuensis were determined by nrDNA-ITS marker, and results indicated that, ITS region featured rich polymorphism in ITS1 and highly conservative in 5.8S/ITS2 among intra-/inter-genome, implying rich genetic diversities and the occurrence of non-concerted evolution in ITS region. Predicated 5.8S structure possessed Helices-Loops with 3 motifs (M1/M2/M3) and 5 helices B4-B8, and ITS2 could form conservative Clover-like structure with 5 ribotypes, manifesting genetically structural generalities and individualities. Thirteen ITS pseudogenes were also identified from 76 samples (or clones). Molecular phylogeny revealed that, A.beshanzuensis shared genetically closer relationships with A.fanjingshanensis, A.chensiensis, A.yuanbaoshanensis among genus Abies. The available original data provided rich genetic information on ITS sequence, structure and molecular phylogeny of A.beshanzuensis, which not only updated the databases of ITS sequences as well as secondary structures essential for phylogenetic reference and DNA barcoding analyses, but also contributed to deep exploration of population diversities, origin and evolution as well theoretical direction for population recovery and protection of A.beshanzuensis.

Predicting the growth response of seedlings from the environmental responses of photosynthesis and metabolism may be improved by considering the dynamics of non-structural carbohydrate, NSC, over a diurnal cycle. Attenuation of growth metabolism when NSC content is low could explain why some NSC is conserved through the night. A dynamic model, incorporating diurnal variation in NSC, was developed to simulate growth of seedlings hour-by-hour. I compared predictions of this model to published growth and NSC data for seedlings that varied according to temperature, light, day length, or CO₂. Prolonged-darkness experiments showed a temperature dependent upper limit on the respiration capacity. Respiration was attenuated as NSC was depleted. Furthermore, when NSC was high at dawn, inhibition of photosynthesis could attenuate the accumulation of NSC under low temperature, or high light, or high CO₂. These concepts were used to simulate plant metabolism and growth rates and diurnal variation of NSC in tomato seedlings under two light levels and various temperatures. Comparison of other results using the same model parameters showed the dynamic model could predict results for starch and starch-less plants, and when growth was affected by CO₂ enrichment and day length.

Pollen analysis as a part of palynology deals with the morphological determination of pollen and spores. Different technologies with different resolutions varying from simple light microscopy to highly elaborate electron microscopy are used for the examination, depending on the area of application (e.g. sedimentology, melissopalynology, forensic palynology, etc.). To answer the question of whether laser scanning microscopy (LSM) can replace scanning electron microscopy (SEM) for the determination of pollen species, 168 species were examined using LSM. It was concluded that LSM is both efficient and easy to handle. After preparing the fresh pollen, a 3D laser scan takes 5-10 minutes and unlike using SEM, the pollen does not have to be sputtered or processed. The 3D scans can be measured quickly and easily with the integrated software and there were no observable artifacts. At magnifications up to 8545x, the image quality is comparable to that of a sputtered SEM sample whereas at higher magnifications, the SEM method is superior. Overall, pollen display by LSM is much less time consuming and more cost effective than with the SEM method.

Ribosome assembly is one of the most fundamental processes in gene expression and has served as a playground to investigate the molecular mechanisms of how protein-RNA complexes (RNPs) assemble. The bacterial ribosome is composed of around 50 ribosomal proteins several of which are co-transcriptionally assembled on a ~4,500 nucleotides long pre-rRNA transcript that is further processed and modified during transcription, the entire process taking around 2 minutes in vivo and assisted by dozens of assembly factors. How this complex molecular process works so efficiently to produce an active ribosome has been investigated over decades and has resulted in the development of a plethora of novel approaches that can also be used to study the assembly of other RNPs. Here we review biochemical, structural and biophysical methods that have been developed and integrated to provide a detailed and quantitative understanding of this complex and intricate molecular process of assembly. We also discuss emerging cutting-edge approaches that could be used in the future to study how transcription, rRNA processing, cellular factors and the native cellular environment shape ribosome assembly and RNP assembly at large.

Colonization of distant organs by tumor cells is a critical step of cancer progression. The initial avascular stage of this process (micrometastasis) remains almost inaccessible to study due to the lack of relevant experimental approaches. Here, we introduce an in vitro/in vivo model of organ-specific micrometastases of triple-negative breast cancer (TNBC) that is fully implemented in a cost-efficient chick embryo (CE) experimental platform. The model is built as three-dimensional (3D) tissue engineering constructs (TECs) combining human MDA-MB-231 cells and decellular-ized CE organ-specific scaffolds. TNBC cells colonized CE organ-specific scaffolds in 2-3 weeks, forming tissue-like structures. The feasibility of this methodology for basic cancer research, drug development and nanomedicine was demonstrated on a model of hepatic micrometastasis of TNBC. We revealed that MDA-MB-231 differentially colonize parenchymal and stromal com-partments of the liver-specific extracellular matrix (LS-ECM) and become more resistant to the treatment with molecular Doxorubicin (Dox) and Dox-loaded mesoporous silica nanoparticles than in monolayer cultures. When grafted on CE chorioallantoic membrane, LS-ECM-based TECs induced angiogenic switch. These findings may have important implications for the diag-nosis and treatment of TNBC. The methodology established here is scalable and adaptable for pharmacological testing and cancer biology research of various metastatic and primary tumors.

Non-destructive testing of metallic objects that may contain embedded defects of different sizes is an important application in many industrial branches for quality control. Most of these techniques allow defect detection and its approximate localization, but very few give enough information for its 3D reconstruction. Here we present a hybrid laser – transducer system that combines remote laser-generated ultrasound excitation and non-contact ultrasonic transducer detection. This fully non-contact method gives access to separating scan areas on different object’s faces and defect details from different angles/perspectives can be analysed. This hybrid system can analyse the whole object’s volume data and allow a 3D reconstruction image of the embedded defects. As a novelty for the signal processing improvement, we use a 2D apodization window filtering technique, applied along with the synthetic aperture focusing algorithm in order to remove the undesired effects of side lobes and wide-angle reflections of propagating ultrasound waves, thus, enhancing the resulting 3D image of the defect. We provide both qualitative and quantitative volumetric results with high accuracy and resolution compared with conventional techniques.

Atomic structure of N-electron atoms is often determined using the Hartree-Fock method, which is an integro-differential equation. The exchange term of the Hartree-Fock equations is usually treated as an inhomogeneous term of a differential equation, or with a local density approximation. This work uses matrix methods to solve for the Hartree-Fock equations, rather than the more commonly-used shooting method to integrate an inhomogeneous differential equation. It is well known that a derivative operator can be expressed as a matrix made of finite-difference coefficients; energy eigenvalues and eigenvectors can be obtained by using computer linear-algebra packages. We extend the same technique to integro-differential equations, where a discretized integral can be written as a sum in matrix form. This method is compared against experiment and standard atomic structure calculations. We also can use this method for free-electron wavefunctions. This technique is important for spectral line broadening in two ways: improving the atomic structure calculations, and improving the motion of the plasma electrons that collide with the atom.

Synthesis and characterization of anhydrous LiZn(IO₃)₃ powders prepared from an aqueous solution are reported. Morphological and compositional analyses were carried out by scanning electron microscopy and energy dispersive X-ray measurements. The synthesized powders exhibit a needle-like morphology after annealing at 400°C. A crystal structure for the synthesized compound has been proposed from powder X-ray diffraction and density-functional theory calculations. Rietveld refinements led to a monoclinic structure, which can be described with space group P21, number 4, and unit-cell parameters a = 21.874(9) Å, b = 5.171(2) Å, c = 5.433(2) Å, and beta = 120.93(4)º. Density-functional theory calculations supported the same crystal structure. Infrared spectra were also collected and the vibrations associated to the different modes discussed. The non-centrosymmetric space group determined for this new polymorph of LiZn(IO₃)₃, the characteristics of its infrared absorption spectrum, and the observed second harmonic generation suggest a promising infrared non-linear optical material.

Beyond semantic segmentation,3D instance segmentation(a process to delineate objects of interest and also classifying the objects into a set of categories) is gaining more and more interest among researchers since numerous computer vision applications need accurate segmentation processes(autonomous driving, indoor navigation, and even virtual or augmented reality systems…) This paper gives an overview and a technical comparison of the existing deep learning architectures in handling unstructured Euclidean data for the rapidly developing 3D instance segmentation. First, the authors divide the 3D point clouds based instance segmentation techniques into two major categories which are proposal based methods and proposal free methods. Then, they also introduce and compare the most used datasets with regard to 3D instance segmentation. Furthermore, they compare and analyze these techniques performance (speed, accuracy, response to noise…). Finally, this paper provides a review of the possible future directions of deep learning for 3D sensor-based information and provides insight into the most promising areas for prospective research.

By manipulating the various physico-chemical properties of amino acids, design of peptides with specific self-assembling properties has been emerging since more than a decade. In this context, short peptides possessing detergent properties (so-called “peptergents”) have been developed to self-assemble into well-ordered nanostructures that can stabilize membrane proteins for crystallization. In this study, the peptide with “peptergency” properties, called ADA8 extensively described by Zhang et al., is studied by molecular dynamics for its self-assembling properties in different conditions. In water, it spontaneously forms beta sheets with a β barrel-like structure. We next simulated the interaction of this peptide with a membrane protein, the bacteriorhodopsin, in the presence or absence of a micelle of dodecylphosphocholine. According to the literature, the peptergent ADA8 is thought to generate a belt of β structures around the hydrophobic helical domain that could help stabilize purified membrane proteins. Molecular dynamics is here used to challenge this view and to provide further molecular details for the replacement of detergent molecules around the protein. To our best knowledge, this is the first molecular mechanism proposed for ''peptergency''. In addition, our calculation approach should serve as a predicting tool for the design of beta peptergent with diverse amphipathic properties.

The development of novel porous composite materials for organic dye degradation and removal has received increasing attention due to water contamination problem. In this paper, hydrothermal synthesized nano zeolite A have been encapsulated with porous periodic mesoporous organosilica (PMO) through a simple modified StÖber method an organosilane-directed growth-induced etching strategy, the obtained yolk-shell structured sample was further functionalized by the impregnation of copper, realizing the composite material with hierarchical porous and catalytic properties. The morphology, porosity and metal content of the zeolite Cu/A and Cu/A@Et-PMO were fully characterized. As compared to the parent material, the composite Cu/A@Et-PMO have an efficient adsorption and catalytic degradation performance on methylene blue (MB), the removal efficiency reached as high as 95% of 60 mg/L MB with 10min. These novel structured porous composites may have great potential for adsorption and degradation application including waste effluents.