With the breakthrough of modernism, various efforts are undertaken to rationalize architecture and building processes using industrial principles. Few architects explore these as intensively as Walter Gropius, the founder of the Bauhaus. Even before World War One, and increasingly in the interwar years, Gropius and a number of colleagues undertake various experiments which manifest in a series of projects, essays, model houses and Siedlungen. These aim at conceptually different goals, i.e. they follow two different categories of industrial logic: first, a flexible construction kit and, second, an assembly line serial production. This article traces the genesis of these two concepts and analyses their characteristics using these early manifestations. Compared to existing literature, this article takes into account hitherto neglected primary sources as well as technological and construction history aspects—allowing for a distinction based not only on theoretical, but also technological and structural characteristics. This article shows that Gropius succeeds in formulating and exploring the two principles in theory and practice as well as drawing conclusions by the end of the 1920s. With them, he contributed significantly to the rationalization of architecture, and his principles have been picked up and developed further by numerous architects since then.

When the distance between an obstacle and a power line is less than the discharge distance, a discharge arc can be generated, resulting in interruption of power supplies. Therefore, regular safety inspections are necessary to ensure safe operations of power grids. Tall vegetation and buildings are the key factors threatening the safe operation of extra high voltage transmission lines within a power line corridor. Manual or LiDAR based-inspections are time consuming and expensive. To make safety inspections more efficient and flexible, a low-altitude unmanned aerial vehicle remote-sensing platform equipped with optical digital camera was used to inspect power line corridors. We propose a semi-patch matching algorithm based on epipolar constraints using both correlation coefficient and the shape of its curve to extract three dimensional (3D) point clouds for a power line corridor. Virtual photography was used to transform the power line direction from approximately parallel to the epipolar line to approximately perpendicular to epipolar line to improve power line measurement accuracy. The distance between the power lines and the 3D point cloud is taken as a criterion for locating obstacles within the power line corridor automatically. Experimental results show that our proposed method is a reliable, cost effective and applicable way for practical power line inspection, and can locate obstacles within the power line corridor with measurement accuracies better than ±0.5 m.

In the paper, the author discusses and computes bounds of the sine and cosine along straight lines on the complex plane.

Sports video analysis is an interesting and emerging field in the domain of computer vision. It has become a very popular subject among scholars all over the world in the last decade due to the need of automated classification of events such as offsides, in/out situations, goals and so on. The most important problem in sports video analysis is detection and tracking of ball and players. Extraction of court lines is also another important problem since it is necessary in the classification of aforementioned events. In this study, considering some of the previous work on the subject, we develop a method for tracking the ball and players in tennis videos where the camera position and orientation is supposed fixed.

Ever since pharmacy has become a profession, pharmacist's role has been continuously subjected to changes due to specific influences from historical, socio-economic, political, and scientific context. Nowadays the classic perception of pharmaceutical profession in Community Pharmacy is facing worldwide extinction due to many factors. Modern services, such as online, mail-order, and telephone-order pharmacies are increasingly gaining ground thanks to their ability to facilitate customer demand. However, at the same time, they are endangering “face-to-face” contact, affecting the building of customer loyalty based on direct “human” interaction, and consequently reducing pharmacists to mere commercial figures. Communication is in fact emphasized as the essential element to build a solid and appropriate interpersonal relationship with the client, to make the consultancy process effective, and to strengthen pharmacist's professionalism in community pharmacy. The aim of this work is to analyze pharmacist’s role in modern society by pinpointing the factors affecting pharmacy profession practice. Specific purpose will be improving both the academic training of future professionals and their capacity to approach public relations through a deepened study and practice of behavioral, communication, educational, and sociological methodologies and techniques that would allow the development of more effective communication skills useful for providing an efficient consultancy service.

We monitored the water quality and hydrological conditions of a horizontal subsurface constructed wetland (HSSF-CW) in Beijing, China, for 2 years. We simulated the area rate constant and the temperature coefficient with the first-order kinetic model. We examined the relationships between the nitrogen (N) removal rate, N load, seasonal variations in the N removal rate, and environmental factors, such as the area rate constant, temperature, and dissolved oxygen (DO). The effluent ammonia (NH₄⁺-N) and nitrate (NO₃⁻-N) concentrations were significantly lower than the influent concentrations (p<0.01, n=38). The NO₃⁻-N load was significantly correlated with the removal rate (R²=0.9566, p<0.01), but the NH^₄+-N load was not correlated with the removal rate (R²=0.0187, p>0.01). The area rate constants of NO₃⁻-N and NH₄⁺-N at 20 °C were 27.01±26.49 and 16.63±10.58 m∙yr⁻¹, respectively. The temperature coefficients for NO₃⁻-N and NH₄⁺-N were estimated at 1.0042 and 0.9604, respectively. The area rate constants for NO₃⁻-N and NH₄⁺-N were not correlated with temperature (p>0.01). The NO₃⁻-N area rate constant was correlated with the corresponding load (R²=0.9625, p<0.01). The NH₄⁺-N area rate was correlated with DO (R²=0.6922, p<0.01), suggesting that the factors that influenced the N removal rate in this wetland met Liebig's law of the minimum.

The transition from the Peptide/RNA world to the Protein/RNA world in the hydrothermal vent environment was a major event in the history of life. The advent of proteins utterly changed the conditions of emerging life, representing a watershed in its development. During subsequent translation various protein enzymes emerged driving protocells into a more complex and interconnected system. With their astonishing versatility, the protein enzymes catalyzed crucial biochemical reactions within protocells into more complex biomolecules in diverse metabolic pathways, whereas structural proteins provided strength and permeability in the cell membrane. Four major events followed after availability of various kinds of protein molecules during prebiotic synthesis. These are: (1) the modification of the phospholipid membrane into the plasma membrane; (2) the origin of primitive cytoplasm; (3) the beginnings of the virus world; and (4) the advent of DNA. The first innovation mediated by proteins was the improvement of the cell membrane. The phospholipid membrane was initially evolved in a vent environment from the gradual modification of a fatty acid membrane via an intermediate phosphatidate acid by non-enzymatic reactions. The phospholipid is then synthesized from phosphatidate acid by a series of enzymes. To make the phospholipid membrane more permeable, various protein molecules interacted with the cell membrane. Proteins not only stabilized the wall membrane, but also acted as pumps, preventing some molecules from the protocells from crossing the membrane barriers, while permitting other selected molecules and ions to enter and leave the protocell. The second modification led by proteins is the gradual conversion of the interior of the protocell from a water-like medium into a gel-like cytoplasm, which became the storehouse of a wide range of biomolecules including amino acids, proteins, nucleic acids, ribosomes, as well as salt and water. The third innovation utilizing the newly synthesized proteins was the emergence of the ancient virus world. In the milieu of different kinds of mRNAs in the prebiotic soup, jelly-roll capsid genes originated de novo within genomes of nonviral mRNAs by overprinting. These fragile capsid genes were possibly coated by proteins on the mineral substrate for stability and durability, transforming them into ancient viral particles. These protein coats were random and were not encoded by encased genes. Some protocells might have engulfed these viral particles, when the capsid genes utilized the ribosomes of the host to translate into the appropriate capsid proteins. These capsid proteins then coated the viral genes to make new copies of primordial viruses inside the protocell. Since then, viruses became capsid-encoding organisms. These primordial mRNA viruses parasitized RNA-based protocells, manipulating them to make new copies of themselves. This was the beginning of a relentless war between viruses and their protocellular hosts. The next stage in viral evolution was the emergence of a primitive retrovirus (pre-retrovirus) with a new kind of replicative strategy in a sense that it could turn its RNA into DNA using its own reverse transcriptase enzyme. This is the beginning of the Retro world that facilitated the transition from RNA to DNA genomes. The infection of RNA protocells with pre-retroviruses progressively transferred the RNA genome to a viral DNA genome by retro-transcription. The advent of DNA by the pre-retrovirus marks the fourth innovation, when a number of enzymes had already developed and were utilized by pre-retroviruses. With continued infection, DNA viruses slowly transferred not only their core replication enzymes, such as helicase, primase, and DNA polymerase, to RNA protocells, but also to their DNAs as well. Thus, began the DNA world, when DNA replaced RNA as the major genome of the protocells. With the advent of DNA, replication of information was entirely dissociated from its expression. Because DNA is much more stable than mRNA with more storage capacity, it is a superb archive for information systems in the form of base sequences. DNA progressively took over the replicative storage function of mRNA, leaving the latter for protein synthesis. The new protocell with the DNA genome will diversify into large populations of DNA protocells that will outcompete populations of RNA protocells. Genetic information began to flow from DNA to mRNA to protein in a two-step process involving transcription and translation. In the biological stage, DNA replication was central to the binary fission of the first cell, orchestrated by the duplication of genomes and then the division of the parent cell into two identical daughter cells. It was carried out by a set of enzymes that formed a Z-ring at the site of replication. With the onset of binary fission, the population of primitive cells grew rapidly in the hydrothermal vent environment, undergoing Darwinian evolution and diversification. These primordial hyperthermophiles, presumably the first life, obtained food and energy directly from the vent environment. However, such a situation was self-limiting, so the early cells evolved their own mechanisms for generating metabolic energy and synthesizing the molecules necessary for their reproduction. The earliest fossil record (≥ 3.5 Ga) of biotic activity is preserved in the Archean hydrothermal and sedimentary rocks of the Nuvvuagittuq Craton of Canada, the Isua Craton of Greenland, the Pilbara Craton of Australia, the Kaapvaal Craton of South Africa, and the Singhbhum Craton of India in the form of the carbonaceous remains of microbial cells, cellular microfossils, and stromatolites. These microscopic fossils provide crucial evidence of the origin and early evolution of prokaryotic cells, beginning with hyperthermophiles. Molecular phylogenetic analysis suggests that both domains of life ¬– Bacteria and Archaea probably split from the last universal common ancestor (LUCA), a hyperthermophilic organism. In the younger sequences of these Archean cratons, two kinds of photosynthetic bacteria, anoxygenic green sulfur bacteria, and oxygenic cyanobacteria, appeared in quick succession from the thermophilic ancestor, indicating a shift of niche from a benthic to a planktonic, with reduced thermotolerance. The development of anoxygenic and oxygenic photosynthesis would have allowed life to escape the hydrothermal setting and invade a newly evolved habitat—broad continental shelves to tap solar energy. Cyanobacteria invaded the global ocean, turned it into blue and green, produced oxygen for the first time, and left their signatures in the carbonates and stromatolites.

This research aims to identify the role of the Dyson model for strategic development in achieving strategic success, and the starting point of the research was the following main question: What is the role of the Dyson model in achieving success?The research was applied in the field in the departments of the Baghdad Municipality, where the examination list was relied upon, which included a set of questions that the senior and middle leaders in the Baghdad Municipality answered, and it was the main means by which the information related to the field of research was collected, and the checklist included two variables and three dimensions From each variable, as each dimension included four questions that express indicators that revolve around one of the research hypotheses, and the case study methodology was used, which defined its path and steps, collected and analyzed field data, and linked it to its theoretical framework, in order to reach To achieve the goal of completing this research, and through analyzing, interpreting and discussing the results, the most important results were drawn up: It was found that the principle of motivation within the departments of Baghdad Municipality does not exist and this affects the employees who do not receive it from the higher leaders in their departments, and this shows that the leaderships in The Municipality of Baghdad do not have the skills and experience. Baghdad Municipality seeks to work alone and not to involve employees who have experiences and skills and strive to achieve development in their departments, and this is what the community members expressed. Among them and poor business completion in their departments.

A methodology for both accurate and smooth contour line generation from Light Detection and Ranging (LiDAR) point clouds is proposed in this paper. In order to improve the accuracy of contour lines in the area of forests, constrained triangulation networks with break lines are then constructed to generate contour lines. In break line extraction, a bi-threshold method for edge line detection is used to extract both complete and reliable break lines. A point clouds elevation adjustment with constrain of break lines and an interpolator considering a contour interval is proposed to improve the smoothness of contour lines. The proposed interpotator is also can avoid contour line intersection when contour lines are interpolated. Statistical parameters and shape index are then used to evaluate quantitatively the accuracy and smoothness of the resultant contour lines, which fill in the blank of contour lines evaluation in theory. The experiments show that high-quality contours in terms of smoothness and accuracy can be generated from LiDAR point clouds.

This paper presents an approach to the Euler-Bernoulli beam theory (EBBT) using the finite difference method (FDM). The EBBT covers the case of small deflections, and shear deformations are not considered. The FDM is an approximate method for solving problems described with differential equations. The FDM does not involve solving differential equations; equations are formulated with values at selected points of the structure. Generally, the finite difference approximations are derived based on fourth-order polynomial hypothesis (FOPH) and second-order polynomial hypothesis (SOPH) for the deflection curve; the FOPH is made for the fourth and third derivative of the deflection curve while the SOPH is made for its second and first derivative. In addition, the boundary conditions and not the governing equations are applied at the beam’s ends. In this paper, the FOPH was made for all of the derivatives of the deflection curve, and additional points were introduced at the beam’s ends and positions of discontinuity (concentrated loads or moments, supports, hinges, springs, etc.). The introduction of additional points allowed us to apply the governing equations at the beam’s ends and to satisfy the boundary and continuity conditions. Moreover, grid points with variable spacing were also considered, the grid being uniform within beam segments. First-order analysis, second-order analysis, and vibration analysis of structures were conducted with this model. Furthermore, tapered beams were analyzed (element stiffness matrix, second-order analysis). Finally, a direct time integration method (DTIM) was presented. The FDM-based DTIM enabled the analysis of forced vibration of structures, with damping taken into account. The results obtained in this paper showed good agreement with those of other studies, and the accuracy was increased through a grid refinement. Especially in the first-order analysis of uniform beams, the results were exact for uniformly distributed and concentrated loads regardless of the grid. Further research will be needed to investigate polynomial refinements (higher-order polynomials such as fifth-order, sixth-order…) of the deflection curve; the polynomial refinements aimed to increase the accuracy, whereby non-centered finite difference approximations at beam’s ends and positions of discontinuity would be used.

The emergence of proteins in the prebiotic world was a watershed event at the origin of life. With their astonishing versatility, the protein enzymes catalyzed crucial biochemical reactions within protocells into more complex biomolecules in diverse metabolic pathways, whereas structural proteins provided strength and permeability in the cell membrane. Five major biochemical innovations followed in succession after availability of various kinds of protein molecules during decoding and translation of mRNAs. These are: (1) the modification of the phospholipid membrane into the plasma membrane; (2) the origin of primitive cytoplasm; (3) primitive gene regulation; (4) the beginnings of the virus world; and (5) the advent of DNA. The creative role of viruses during prebiotic synthesis led to the origin of the DNA world, when DNA replaced mRNA as the major genome of the protocells. With the advent of DNA, replication of information was entirely dissociated from its expression. Because DNA is much more stable than mRNA with more storage capacity, it is a superb archive for information systems in the form of base sequences. DNA progressively took over the replicative storage function of mRNA, leaving the latter for protein synthesis. Genetic information began to flow from DNA to mRNA to protein in a two-step process involving transcription and translation. In the biological stage, DNA replication was central to the binary fission of the first cell, orchestrated by the duplication of genomes and then the division of the parent cell into two identical daughter cells. With the onset of binary fission, the population of primitive cells grew rapidly in the hydrothermal vent environment, undergoing Darwinian evolution and diversification by mutation. The habitat of the earliest fossil record (≥ 3.5 Ga) from the Archean sedimentary rocks of Canada, Greenland, Australia, South Africa, and India offers a new window on the early radiation of microbial life. The development of anoxygenic and then oxygenic photosynthesis from early hyperthermophiles would have allowed life to escape the hydrothermal setting to the mesophilic global ocean.

Railway has been used as one of the most crucial means of transportation in public mobility and economic development. For efficiently operating railways, the electrification system in railway infrastructure, which supplies electric power to trains, is essential facilities for stable train operation. Due to its important role, the electrification system needs to be rigorously and regularly inspected and managed. This paper presents a supervised learning method to classify Mobile Laser Scanning (MLS) data into ten target classes representing overhead wires, movable brackets and poles, which are recognized key objects in the electrification system. In general, the layout of railway electrification system shows a strong regularity of spatial relations among object classes. The proposed classifier is developed based on Conditional Random Field (CRF), which characterizes not only labeling homogeneity at short range, but also the layout compatibility between different object classes at long range in the probabilistic graphical model. This multi-range CRF model consists of a unary term and three pairwise contextual terms. In order to gain computational efficiency, MLS point clouds is converted into a set of line segments where the labeling process is applied. Support Vector Machine (SVM) is used as a local classifier considering only node features for producing the unary potentials of CRF model. As the short-range pairwise contextual term, Potts model is applied to enforce a local smoothness in short-range graph. While, long-range pairwise potentials are designed to enhance spatial regularities of both horizontal and vertical layouts among railway objects. We formulate two long-range pairwise potentials as the log posterior probability obtained by Naïve Bayes classifier. The directional layout compatibilities are characterized in probability look-up tables which represent co-occurrence rate of spatial relations in horizontal and vertical directions. The likelihood function is formulated by multivariate Gaussian distributions. In the proposed multi-range CRF model, the weight parameters to balance four sub-terms are estimated by applying the Stochastic Gradient Descent (SGD). The results show that the proposed multi-range CRF can effectively classify detailed railway elements, representing the average recall of 97.66% and the average precision of 97.07% for all classes.

World is now experiencing a major health calamity due to the coronavirus disease (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus clade 2 (SARS-CoV- 2). The foremost challenge facing the scientific community is to explore the growth and transmission capability of the virus. Use of artificial intelligence (AI), such as, deep learning, in (i) rapid disease detection from x-ray/computerized tomography (CT)/ high-resolution computed tomography (HRCT) images, (ii) accurate prediction of the epidemic patterns and their saturation throughout the globe, (iii) identification of the epicenter in each country/state and forecasting the disease from social networking data, (iv) prediction of drug-protein interactions for repurposing the drugs, and (v) socio-economic impact and prediction of future relapses, has attracted much attention. In the present manuscript, we describe the role of various AI-based technologies for rapid and efficient detection from CT images complementing quantitative real time polymerase chain reaction (qRT-PCR) and immunodiagnostic assays. AI-based technologies to anticipate the current pandemic pattern, possibility of future relapses and socio-economic impact are also discussed. We inspect how the virus transmits depending on different factors, such as, population density and mobility among others. We depict how AI-based mobile app for contact tracing and surveys can prevent the transmission. A modified deep learning technique can assess affinity of the most probable drugs to treat COVID-19. Here a few effective antiviral drugs, such as, Geneticin, Avermectin B1, and Ancriviroc among others, have been reported with their appropriate validation from previous investigations.

This study presents an exact solution to the free vibration analysis of a uniform Timoshenko beam, with a harmonic vibration being assumed. The Timoshenko beam theory covers cases associated with small deflections based on shear deformation and rotary inertia considerations. In this paper, a moment-shear force-circular frequency-curvature relationship was presented. The complete study was based on this relationship and closed-form expressions of efforts and deformations were derived. The free vibration response of single-span systems and spring-mass systems was analyzed; closed-form formulations of matrices expressing the boundary conditions were presented and the natural frequencies were determined by solving the eigenvalue problem. Systems with intermediate mass, spring, or spring-mass system were also analyzed. Furthermore, first-order dynamic stiffness matrices in local coordinates were derived. Finally, a second-order analysis of beams resting on an elastic Winkler foundation was conducted. The results obtained in this paper were in good agreement with those of other studies.

The human mind is multimodal. Yet most behavioral studies rely on century-old measures of behavior—task accuracy and latency (response time). Multimodal and multisensory analysis of human behavior creates a better understanding of how the mind works. The problem is that designing and implementing these experiments is technically complex and costly. This paper introduces versatile and economical means of developing multimodal-multisensory human experiments. We provide an experimental design framework that automatically integrates and synchronizes measures including electroencephalogram (EEG), galvanic skin response (GSR), eye-tracking, virtual reality (VR), body movement, mouse/cursor motion and response time. Unlike proprietary systems (e.g., iMotions), our system is free and open-source; it integrates PsychoPy, Unity and Lab Streaming Layer (LSL). The system embeds LSL inside PsychoPy/Unity for the synchronization of multiple sensory signals—gaze motion, electroencephalogram (EEG), galvanic skin response (GSR), mouse/cursor movement, and body motion—with low-cost consumer-grade devices in a simple behavioral task designed by PsychoPy and a virtual reality environment designed by Unity. This tutorial shows a step-by-step process by which a complex multimodal-multisensory experiment can be designed and implemented in a few hours. When conducting the experiment, all of the data synchronization and recoding of the data to disk will be done automatically.

In the paper, by virtue of a Lévy–Khintchine representation and an alternative integral representation for the weighted geometric mean, the authors establish a Lévy–Khintchine representation and an alternative integral representation for the Toader–Qi mean. Moreover, the authors also collect an probabilistic interpretation and applications in engineering of the Toader–Qi mean.

The geometry of Poincare disk itself is interpreted without any mapping to dierent spaces. Our approach might be one of the shortest and is intended for educational contribution.

Euler’s product formula over the primes and Euler’s zeta function equate to enshrine the Fundamental Theorem of Arithmetic that every integer > 1 is the product of a unique set of primes. The product formula has no zero, and with a domain ≤1 Euler’s zeta diverges. Dirichlet’s eta function η(s), negates alternate terms of zeta, permitting convergence when s∈C and Re(s) < 1, and its non-trivial zeros {ρ}, have a deep relationship with the distribution of the primes. The Riemann Hypothesis is that all the non-trivial zeros have Re(ρ) = 1/2. This work examines the symmetries in a partial Euler’s zeta series with a complex domain equating it to the difference between two finite vector series whose matched terms have mirror-image arguments, but whose magnitudes differ when Re(s) ≠ 1/2. Analytical continuation generates a modified eta series η_l(s), in which every l^th term is multiplied by (1-l). If the integer l is appropriately determined by the Im(s), similar paired finite vector series have a difference that closely follows η_l (s) and their terminal vectors intersect in a unique way permitting zeros only when Re(s) = 1/2. Furthermore, those vectors tracking the derivatives of the series, have a special relationship permitting zeros of the differential only when Re(s) > 1/2.

All empirical water column correction methods have consistently been reported to require existing depth sounding data for the purpose of calibrating a simple depth retrieval model; they yield poor results over very bright or very dark bottoms. In contrast, we set out to (i) use only the relative radiance data in the image along with published data, and several new assumptions, (ii) in order to specify and operate the simplified radiative transfer equation (RTE), (iii) for the purpose of retrieving both the satellite derived bathymetry (SDB) and the water column corrected spectral reflectance over shallow seabeds. Sea truth regressions show that SDB depths retrieved by the method only need tide correction. Therefore it shall be demonstrated that, under such new assumptions, there is no need (i) for formal atmospheric correction, (ii) nor for conversion of relative radiance into calibrated reflectance , (iii) nor for existing depth sounding data, to specify the simplified RTE and produce both SDB and spectral water column corrected radiance ready for bottom typing. Moreover, the use of the panchromatic band for that purpose is introduced. Altogether, we named this process the Self-Calibrated Supervised Spectral Shallow-sea Modeler (4SM). This approach requires a trained practitioner, though, to produce its results within hours of downloading the raw image. The ideal raw image should be a “near-nadir” view, exhibit homogeneous atmosphere and water column, include some coverage of optically deep waters and bare land, and lend itself to quality removal of haze, atmospheric adjacency effect, and sun/sky glint.

There is growing recognition in research and policy of a mental health crisis among Canada’s paramedics but despite this, epidemiological surveillance of the problem is in its infancy. Just weeks before the emergence of the COVID-19 pandemic, we surveyed paramedics from a single, large, urban paramedic service in Ontario, Canada to assess for symptom clusters consistent with Post-Traumatic Stress Disorder (PTSD), major depressive disorder, and generalized anxiety disorder and to identify potential risk factors for each. In total, we received 589 completed surveys (a 97% completion rate) and found that 11% screened positive for PTSD, 15% for depression, and 15% for anxiety, with 1 in 4 active-duty paramedics screening positive for any of the three as recently as February 2020. In adjusted analyses, the risk of a positive screen varied as a function of employment classification, gender, self-reported resilience, and previous experience as a member of the service’s peer support team. Our findings support the position that paramedics screen positive for mental disorders at high rates – a problem likely to have worsened since the onset of the COVID-19 pandemic. We echo the calls of researchers and policymakers for urgent action to support paramedic mental health in Canada.

In the paper, the authors present an explicit form for a family of inhomogeneous linear ordinary differential equations, find a more significant expression for all derivatives of a function related to the solution to the family of inhomogeneous linear ordinary differential equations in terms of the Lerch transcendent, establish an explicit formula for computing all derivatives of the solution to the family of inhomogeneous linear ordinary differential equations, acquire the absolute monotonicity, complete monotonicity, the Bernstein function property of several functions related to the solution to the family of inhomogeneous linear ordinary differential equations, discover a diagonal recurrence relation of the Stirling numbers of the first kind, and derive an inequality for bounding the logarithmic function.

Computational fluid dynamics is used to study the impact of the support structure of a tidal turbine on performance and the downstream wake characteristics. A high-fidelity computational model of a dual rotor, contra-rotating tidal turbine in a large channel domain is presented, with turbulence modelled using large eddy simulation. Actuator lines represent the turbine blades, permitting the analysis of transient flow features and turbine diagnostics. The following four cases are considered: the flow in an unexploited, empty channel; flow in a channel containing the rotors; flow in a channel containing the support structure; and flow in a channel with both rotors and support structure. The results indicate that the support structure contributes significantly to the behaviour of the turbine and to turbulence levels downstream, even when the rotors are upstream. This implies that inclusion of the turbine structure, or some parametrisation thereof, is a prerequisite for the realistic prediction of turbine performance and reliability, particularly for array layouts where wake effects become significant.

In the paper, by virtue of techniques in combinatorial analysis, the authors simplify two families of nonlinear ordinary differential equations in terms of the Stirling numbers of the first kind.

With the development of higher voltage power grid, the high and low voltage parallel loops are emerging, which lead to energy losses, even threaten the security and stability of power system. The multi-infeed HVDC configurations widely appearing in AC/DC interconnected power system make this situation even worse. Aimed at energy saving and system security, a decision optimization method for power grid operating condition with high and low voltage parallel loops is proposed in this paper. Firstly, considering hub substation distribution and power grid structure, parallel loop opening schemes are generated with GN algorithm. Then, candidate opening schemes are preliminarily selected from all these generated schemes based on a filtering index. Finally, with the influence on power system security, stability and operation economy in consideration, an evaluation model for candidate opening schemes is founded based on analytic hierarchy process (AHP). And a fuzzy evaluation algorithm is used to find the optimal scheme. Simulation results of New England 39-bus system and an actual power system validate the effectiveness and superiority of this proposed method.

Background-The outbreak of COVID-19 pandemic has affected the global economy from its starting. Indian economy is also affected by the pandemic and experienced a lot of economic damages. India has become the global hotspot of COVID-19 during the second wave of the pandemic and recorded the second-highest position in terms of positivity rate after China. The present study attempts to analyze the economic issues that emerged in the first and second waves of the pandemic in India. Method/Approach-There is no econometric tools or analytical models used in the present study. This study attempts to evaluate the two research questions which are formed on the basis of some previous studies by various organizations and researchers. The research questions are as follow, First, what are the sectors those are primarily affected at the time of the first COVID-19 outbreak? Second, which economic issues and impacts emerged in the second wave of the pandemic? Results/ Findings-From the study, it is found that the second wave of COVID-19 is not much affected by the Indian economy. At this time, no nationwide lockdown was announced by the Government. But so, it was much severe in the time of the first wave of COVID-19. Many sectors were affected by the pandemic like agriculture, MSMEs, Tourism, etc., and these resulted in substantial unemployment problems in the economy. The study is trying to analyze these problems and concluding it with a few policy recommendations for the economy of India.

White and three types of black garlic (13, 32 and 45 days of fermentation, named 0C1, 1C2 and 2C1 respectively) were selected in order to check possible differences in their nutraceutic potential. For this purpose, garlic were physico-chemically characterised, and both in vivo and in vitro assays were carried out. Black garlic showed higher polyphenol content and antioxidant capacity than white garlic. The biological studies have shown that only white garlic was not safe showing toxicity effect. Furthermore, none garlic exert protective effects against H₂O₂, except the 0C1 black garlic. Moreover, garlic was non-genotoxic with the exception of the highest concentration of white garlic. On the other hand, 0C1 was the most antigenotoxic substance. The in vivo longevity assays yielded significant extension of lifespan results in some concentrations of white and 0C1and 1C2 black garlic. The in vitro experiments showed that all studied garlic induced a decrease in leukaemia cells growth. However, none type of garlic was able to induce proapoptotic internucleosomal DNA fragmentation. Taking into account the physicochemical and biological data, black garlic could be considered as a potential functional food and used in preventive treatment of age-related diseases. In addition, our findings could be relevant for the black garlic processing agrifood companies as the economical and timing costs are significantly reduced to 13 days aging.

Wind turbine plants are complex dynamic and uncertain processes driven by stochastic inputs and disturbances, as well as different loads represented by gyroscopic, centrifugal, and gravitational forces. Moreover, as their aerodynamic models are nonlinear, both modelling and control become challenging problems. On one hand, high-fidelity simulators should contain different parameters and variables in order to accurately describe the main dynamic system behaviour. Therefore, the development of modelling and control for wind turbine systems should consider these complexity aspects. On the other hand, these control solutions have to include the main wind turbine dynamic characteristics without becoming too complicated. The main point of this paper is thus to provide two practical examples of development of robust control strategies when applied to a simulated wind turbine plant. Experiments with the wind turbine simulator and the Monte–Carlo tools represent the instruments for assessing the robustness and reliability aspects of the developed control methodologies when the model-reality mismatch and measurement errors are also considered. Advantages and drawbacks of these regulation methods are also highlighted with respect to different control strategies via proper performance metrics.

This paper proposes a crack recognition method based on high-resolution line array cameras and adaptive lifting algorithm. By defining the crack rate, this algorithm calculates the ratio of the crack area to the area of the entire collected image to characterize the damage extent of the current section. The algorithm first uses image preprocessing to reduce the image noise, then uses histogram equalization to enhance the feature of the crack region, divides the whole image into multiple sub-blocks, and extracts region features in the sub-block. At the same time, this algorithm defines related feature descriptors, and constructs weak classifiers according to each feature descriptor, and converts the weak classifiers into strong classifiers by using an adaptive lifting algorithm. Finally, this algorithm realizes the division of the crack regions. Experimental results show that the proposed algorithm can meet the actual needs and is better than other classical algorithms.

We present a brief history of the construction of models of the universe, followed by calculations of quantitative characteristics of basic geometric and kinematic properties of the Standard Cosmological Model ($\Lambda$CDM). Using the Friedmann equations of uniform space, we derive equations characterizing a $\Lambda$CDM model that describes a universe corresponding to current observational data. The equations take into account the effects of radiation and ultra-relativistic neutrinos. It is shown that the universe at very early and late stages can be described to sufficient accuracy by simple formulas. Certain important moments of cosmic evolution are determined: the times when densities of the gravitational components of the universe become equal, when they contribute equally to the gravitational force, when the accelerating expansion of space begins, and several others. The dependences of different distances on redshift and the scale factor of space are derived. The distance to the sphere that expands with the speed of light (the Hubble distance), and its current and future acceleration, are found. Concepts of a horizon, second inflation, and second horizon are discussed. We consider the remote future of the universe and the opportunity, in principle, of connection with extraterrestrial civilizations.

In the paper, by virtue of the Faà di Bruno formula, some properties of the Bell polynomials of the second kind, and an inversion formula for the Stirling numbers of the first and second kinds, the authors establish meaningfully and significantly two identities which simplify coefficients in a family of ordinary differential equations associated with higher order Bernoulli numbers of the second kind.

Aerial image classification has become popular and has attracted extensive research efforts in recent decades. The main challenge lies in its very high spatial resolution but relatively insufficient spectral information. To this end, spatial-spectral feature extraction is a popular strategy for classification. However, parameter determination for that feature extraction is usually time-consuming and depends excessively on experience. In this paper, an automatic spatial feature extraction approach based on image raster and segmental vector data cross-analysis is proposed for the classification of very high spatial resolution (VHSR) aerial imagery. First, multi-resolution segmentation is used to generate strongly homogeneous image objects and extract corresponding vectors. Then, to automatically explore the region of a ground target, two rules, which are derived from Tobler’s First Law of Geography (TFL) and a topological relationship of vector data, are integrated to constrain the extension of a region around a central object. Third, the shape and size of the extended region are described. A final classification map is achieved through a supervised classifier using shape, size, and spectral features. Experiments on three real aerial images of VHSR (0.1 to 0.32 m) are done to evaluate effectiveness and robustness of the proposed approach. Comparisons to state-of-the-art methods demonstrate the superiority of the proposed method in VHSR image classification.

Dislocation is one of the major challenges in unmanned aerial vehicle (UAV) image stitching. In this paper, we propose a new dynamic programming for seamlessly stitching UAV images using optical flow. Our solution consists of two steps: Firstly, an image-matching algorithm is used to correct the images so that they are in the same coordinate system. Secondly, a new dynamic programming algorithm is develop based on the concept of a stereo dual-channel energy accumulation using optical flow. A new energy aggregation and traversal strategy is adopted in our solution, which can find a more optimal seam line for adjacent image stitching. Our algorithm overcomes the theoretical limitation of the classical Duplaquet algorithm. Experiments show that the algorithm can effectively solve the dislocation problem in UAV image stitching. Beyond that, our solution is also direction-independent, which has more adaptability and robustness for UAV images.

In this short communication, we conducted first-principles calculations to explore the stability of boron monochalcogenides (BX, X=S, Se or Te), as a new class of two-dimensional (2D) materials. We predicted BX monolayers with two different atomic stacking sequences of ABBA and ABBC, referred in this work to 2H and 1T, respectively. Analysis of phonon dispersions confirm the dynamical stability of BX nanosheets with the both 2H and 1T atomic lattices. Ab-initio molecular dynamics simulations reveal the outstanding thermal stability of all predicted monolayers at high temperatures over 1500 K. BX structures were found to exhibit high elastic modulus and tensile strengths. It was found that BS and BTe nanosheets can show high stretchability, comparable to that of the graphene. It was found that all predicted monolayers exhibit semiconducting electronic character, in which 2H structures present lower band-gaps as compared with 1T lattices. The band-gap values were found to decrease from BS to BTe. According to the HSE06 results, 1T-BS and 2H-BTe show respectively, the maximum (4.0 eV) and minimum (2.06 eV) electronic band-gaps. This investigation introduces boron monochalcogenides as a novel class of 2D semiconductors with remarkable thermal, dynamical and mechanical stability.

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.

Transposable elements (TEs) ubiquitously exist in the human genome, and some have the ability to copy and paste themselves to other locations, resulting in new insertions. Organisms have evolved with mechanisms and machineries to repress such activity. TEs are also co-opted for beneficial functions by the host and are thus maintained in the genome. During the lifetime of humans, aberrant TE activity might cause or contribute towards diseases including neurological conditions such as Alzheimers Disease (AD) and cancer. While inflammatory pathways linked to TEs may be a part of the disease pathology, on the other hand altered TE activity involving inflammatory pathways could be recognised by disease suppression mechanisms. For this reason, TEs could be targeted for therapeutic applications aiming to prevent TE activity or reduce initial inflammatory pathways as well as to activate disease suppression mechanisms. In this review, we describe the contributory and potential preventative roles of TEs in neurological conditions and cancer from a molecular and evolutionary perspective. Evolutionary paradigms both at the unicellular and organismal level aid understanding the role of TEs in disease. These observations could pave the way for the development of novel therapeutic approaches targeting TEs.

Estimation of core and surface temperature is one of the crucial functionalities of the lithium-ion Battery Management System (BMS) towards providing effective thermal management, fault detection and operational safety. While, it is impractical to measure core temperature using physical sensors, implementing a complex estimation strategy in on-board low-cost BMS is challenging due to high computational cost and the cost of implementation. Typically, a temperature estimation scheme consists of a heat generation model and a heat transfer model. Several researchers have already proposed ranges of thermal models having different levels of accuracy and complexity. Broadly, there are first-order and second-order heat capacitor-resistor-based thermal models of lithium-ion batteries (LIBs) for core and surface temperature estimation. This paper deals with a detailed comparative study between these two models using extensive laboratory test data and simulation study to access suitability in online prediction and onboard BMS. The aim is to guide whether it’s worth investing towards developing a second-order model instead of a first-order model with respect to prediction accuracy considering modelling complexity, experiments required and the computational cost. Both the thermal models along with the parameter estimation scheme are modelled and simulated using MATLAB/Simulink environment. Models are validated using laboratory test data of a cylindrical 18650 LIB cell. Further, a Kalman Filter with appropriate process and measurement noise levels are used to estimate the core temperature in terms of measured surface and ambient temperatures. Results from the first-order model and second-order models are analyzed for comparison purposes.

The mitigation of NLOS (non-line-of-sight) propagation conditions is one of main challenges in wireless signals based indoor localization. When RFID localization technology is applied in applications, RSS fluctuates frequently due to the shade and multipath effect of RF signal, which could result in localization inaccuracy. In particularly, when tags carriers are walking in LOS (line-of-sight) and NLOS hybrid environment, great attenuation of RSS will happen, which would result in great location deviation. The paper proposes an IMU-assisted (Inertial Measurement Unit) RFID based indoor localization in LOS/NLOS hybrid environment. The proposed method includes three improvements over previous RSS based positioning methods: IMU aided RSS filtering, IMU aided LOS/NLOS distinguishing and IMU aided LOS/NLOS environment switching. Also, CRLB (Cramér-Rao Low Bound) is calculated to prove theoretically that indoor positioning accuracy for proposed method in LOS/NLOS mixed environment is higher than position precision of only use RSS information. Simulation and experiments are conducted to show that proposed method can reduce the mean positioning error to around 3 meters without site survey.

Document deskewing is a fundamental problem in document image processing. While existing methods have limitations, such as Hough Line Transformation that can deskew images upside down, and Deep Learning models that require huge amounts of human labour and computational resources and still fail to deskew while taking care of orientation, OCR-based methods also struggle to read text when it is tilted. In this paper, we propose a novel, simple, cost-effective deep learning method for fixing the skew and orientation of documents. Our approach reduces the search space for the machine learning model to predict whether an image is upside down or not, avoiding the huge search space of predicting an angle between 0 and 360. We finetuned a MobileNetV2 model, which was pre-trained on imagenet, using only 200 images and achieve good results. This method is useful for automation-based tasks, such as data extraction using OCR technology, and can greatly reduce manual labour.

Cameroon's national vaccination campaign was launched on April 12, 2021, amid a nationwide outbreak of COVID-19 with two types of vaccines. This study provides preliminary evidence of the level of coverage of the population and gives an early overview of the challenges, the achievements and the lessons learned. COVID-19 vaccine administration data were obtained from data of the Cameroon Ministry of Public Health. Descriptive statistical analyses were conducted. Thirty days after the introduction of COVID 19 vaccines, five percent of the target population was vaccinated. Women represented one third of the people vaccinated regardless of age and health conditions. Although AEFI reported were minor and scanty with both vaccines, the majority of the vaccinated did not come back for their second dose. There is a need to build confidence among eligible beneficiaries in order to expand the benefits of vaccination to control the current pandemic. The country is still far below the target which could be worrisome given that the uptake is slow and, the 391 200 doses of the AstraZeneca are going to expire in August 2021. This study offers insights into those early efforts as a contribution to significant discussions about upcoming approach to improve service delivery and uptake.

This study is designed to assess and improve apparel sewing section efficiency and productivity throughout line balancing. Apparel industry is one of the oldest and among the most global industry, being primarily concerned with the design and production of cloth and their supply. The central process in apparel manufacturing is the joining together of components which is known as the sewing process , which is the most labour intensive type of manufacturing process .Proper utilization of resources in garment sewing section is more critical to enhance the performance of the apparel industry by reducing production cost and minimizing wastage. For effective utilization of resources in the sewing section, good line balancing is important to increase productivity and production efficiency. This research was a design to analyse and improve the assembling line in the case of Telaje garment manufacturing and sales plc. The study was first conduct observations in the production floor and start work with the selection of sewing line in the garment production process. Among the nine lines of the factory select one on the production floor and one garment ordered product known as five pocket men’s jeans trousers are selected. For this study, both qualitative and quantitative research approaches were employed. Both primary and secondary data sources are used to detail the collected relevant data to understand the current efficiency scenario of the factory. The main challenges to minimizing line efficiency and productivity with the expected performance measurement are improper utilization of resources and improper implementation of line balancing in sewing section, therefore this thesis work shows that the bottleneck process and consequence solution will be searched, and finally significantly improving the productivity by 418 unit products/ day and, hence the efficiency will increase from 28.83% to 50.04% of the line

Patient-derived xenograft (PDX) models are created by engraftment of patients’ tumor tissues into immunocompetent mice. Since PDX model keep the characteristics of primary patient’s tumor such as gene expression profiles and drug sensitivity, it now becomes most reliable in vivo human cancer model. The engraftment rate are increased with the introduction of NOD/Scid based immunocompromised mice, especially, NK cell defective NOD strains such as NOD/Scid/IL2Rγnu (NOG/ NSG) mice and NOD/Scid/Jak3null (NOJ) mice. Success ratio differs from the origin of tumor: Gastrointestinal tumors tend to higher success rate and breast cancer is lower. Subcutaneous transplantation is most popular method to establish PDX, but some tumor needs orthotropic or renal capsule transplantation, and human hormone treatment is needed to establish hormone dependent cancers such as prostate and breast cancer. PDX library with patient’s clinical data, gene-expression patterns, mutational status, drug responsiveness and tumor architecture will be the powerful tool for developing specific biomarker and novel individualized therapy and establishing precision cancer medicine.

In the paper, the author (1) presents an explicit formula and its inversion formula for higher order derivatives of generating functions of the Bell polynomials, with the help of the Faà di Bruno formula, properties of the Bell polynomials of the second kind, and the inversion theorem for the Stirling numbers of the first and second kinds; (2) recovers an explicit formula and its inversion formula for the Bell polynomials in terms of the Stirling numbers of the first and second kinds, with the aid of the above explicit formula and its inversion formula for higher order derivatives of generating functions of the Bell polynomials; (3) constructs some determinantal and product inequalities and deduces the logarithmic convexity of the Bell polynomials, with the assistance of the complete monotonicity of generating functions of the Bell polynomials. These inequalities are main results of the paper.

Based on the kinematic approach of the limit analysis and slip-line theories, this paper proposes a new 2D analytical model to evaluate the collapse support pressure to ensure the face stability of a circular tunnel in purely cohesive soils driven by a shield. The normality conditions, the yield criterion and the vertical soil arching effect are considered in the analytical model. Two upper bound solutions corresponding to the ratio of the cover to the diameter (C/D) are derived from considering the mechanisms based on the motion of rigid multi-blocks. Comparisons are made with existing upper and lower bound solutions published in previous articles. The results are close to the solutions of practical engineering. The failure mechanisms proposed in this study provide a better explanation for the failure process in the heading of the tunnel face.

Chilli leaf curl virus (ChiLCV) is a severe threat to the successful cultivation of the chilli peppers. Besides, the genetics and heterosis for important traits under the influence of ChiLCV infestation is not well studied. Therefore here, were crossed seven genotypes (lines) with high yield and quality attributes with four highly resistant genotypes (testers) in a line (L) × tester (T) mating design to produce 28 F1 hybrids. Parents and their hybrids were evaluated for yield attributes and ChiLCV resistance. All the four testers were symptomless and among seven lines, two were moderately resistant and five were moderately susceptible to the ChiLCV. Among 28 F1 hybrids, 12 showed a moderate resistant reaction, 11 were moderately susceptible and five susceptible to the ChiLCV disease. Based on per se performance, most promising hybrid combinations were L3 × T2, L6 × T1, and L3 × T1 for yield attributes. Whereas the superior crosses for ChiLCV resistance based on heterobeltosis, standard heterosis and specific combining ability test (SCA) effects were L6 × T1 and L7 × T3. Lines and testers showed significant differences for all the characters except for the plant height. The general combining ability (GCA) effects for testers were significant for all the traits except for days to first harvest. The ratio of σ2GCA/σ2SCA indicated the predominance of non-additive gene effects in the inheritance of traits studied in this experiment. The contribution of lines was more compared to testers for all the characters except for primary branches plant-1. Overall, this study provides valuable information regarding the genetics and heterosis in chilli with respect to ChiLCV infestation

Shipbreaking research has not been in the forefront until the last decade in which environmental and occupational hazards have been highlighted while economic sustainability and contextual conditions were not equally considered. The adoption of a triple bottom line approach across core business issues (environmental impacts, workplace safety ) as well as peripheral stakeholders expectation (environmental sustainability focus) has been retarded due to the less attention on the latter. Based on the findings of the 128 review papers, the study suggests that organizational learning and economic sustainability needs to prioritize through the formation of strange alliance among the stakeholders. The study argues that the dialogue and discussion on the peripheral stakeholders (NGOs, yard managers, national and international policy organizations) would lead to a more sustainable shipbreaking industry in the south Asian regions.

In this paper, we investigate p-adic q-integral (q-Volkenborn integral) on Z_p of p-adic gamma function via their Mahler expansions. We also derived two q-Volkenborn integrals of p-adic gamma function in terms of q-Daehee polynomials and numbers and q-Daehee polynomials and numbers of the second kind. Moreover, we discover q-Volkenborn integral of the derivative of p-adic gamma function. We acquire the relationship between the p-adic gamma function and Stirling numbers of the first kind. We finally develop a novel and interesting representation for the p-adic Euler constant by means of the q-Daehee polynomials and numbers.

Synthesis of new series of 1-phenyl-3-(4-(pyridin-3-yl) phenyl) urea derivatives and its in vitro antiproliferative activities against NCI-60 human cancer cell lines of nine different cancer types are described. Fourteen compounds 5a-n have been synthesized with three different hydrogen bondable moieties (4-hydroxylmethylpiperidinyl and trimethoxyphenyloxy and 4-hydroxyethylpiperazine) attached to the core structure 1-phenyl-3-(4-(pyridin-3-yl) phenyl) urea. Different substituents with different π and σ values were added on the terminal phenyl group. Compounds with 4-hydroxymethylpiperidine moiety showed higher mean percentage inhibition values over the 60-cell line panel at 10-µM concentration. They showed broad-spectrum antiproliferative activity over many cell lines of different cancer types. For instance, compound 5a elicited some lethal rather than inhibition effects on SK-MEL-5 melanoma cell line, 786-0, A498, RXF 393 renal cancer cell lines, and MDA-MB-468 breast cancer cell line by 146.1, 108.7, 136.2, 134.8, 116.6 % at 10 µM, respectively. Compounds 5a-e exhibited superior antiproliferative activity than Paclitaxel and Gefitinib against the most sensitive cell lines. Two compounds, 5a and 5d showed promising mean growth inhibitions and thus were further tested at five-dose testing mode to determine their IC₅₀ values. The data revealed that 5a and 5d urea compounds are the most active derivatives with significant efficacies and superior potencies than Paclitaxel in 21 different cancer cell lines, belonging particularly to renal cancer and melanoma cell lines. Moreover, 5a and 5d had superior potencies than Gefitinib in 38 and 34 cancer cell lines, respectively; belonging particularly to colon cancer, breast cancer and melanoma cell lines.

Flushing tap water is often promoted as a simple and low cost approach to reducing water lead exposures. This study evaluated lead reduction when prevailing flush guidelines (30 seconds-2 minutes) are implemented in a city compliant with lead-associated water regulations (New Orleans, LA). Water samples (n=1,497) collected from a convenience sample of 376 residential sites (2015-2017) were analyzed for lead in samples collected: at 1) first draw (n=375), and after incremental flushes of 2) 30-45 seconds (n=375), 3) 2.5-3 minutes (n=373), and 4) 5.5-6 minutes (n=218). There was no significant reduction when compared to the first draw lead level, until the 6 minute flush (p<0.05); but most sites (52%) still had detectable lead (≥1 ppb) after 6 minutes. Older homes (pre-1950) and low occupancy sites had significantly higher WLLs (p<0.05).Each sample type had health-based standard exceedances at over 50% of sites sampled (max: 58 ppb). While flushing is an effective short-term approach to remediate high lead, prevailing flush recommendations are an inconsistently effective exposure prevention measure that can often inadvertently increase exposures. Public health messages should be modified to ensure appropriate application of flushing for specific cities, while acknowledging its short-comings and practical limitations.

Cancer cell lines are widely used as in vitro models of tumorigenesis, facilitating fundamental discoveries in cancer biology and translational medicine. Currently, there are few options for glioblastoma (GBM) treatment and limited in vitro models with accurate genomic and transcriptomic characterization. Here, a detailed characterization of a new GBM cell line, namely AHOL1, was conducted in order to fully characterize its molecular composition based on its copy number alteration (CNA) and transcriptome profiling, followed by the validation of key elements associated with GBM tumorigenesis. Large numbers of CNAs and differentially expressed genes (DEGs) were identified. CNAs were distributed throughout the genome, including gains at Xq11.1-q28, Xp22.33-p11.1, Xq21.1-q21.33, 4p15.1-p14, 8q23.2-q23.3 and losses at Yq11.21-q12, Yp11.31-p11.2 and 12p13.31 positions. Nine druggable genes were identified, including HCRTR2, ETV1, PTPRD, PRKX, STS, RPS6KA6, ZFY, USP9Y and KDM5D. By integrating DEGs and CNAs, we identified 57 overlapping genes enriched in fourteen pathways. Altered expression of several cancer-related candidates found in the DEGs-CNA dataset was confirmed by RT-qPCR. Taken together, this first comprehensive genomic and transcriptomic landscape of AHOL1 provides unique resources for further studies and identifies several druggable targets that may be useful for therapeutics and biologic and molecular investigation of GBM.

The current study sets out to develop an empirical line method (ELM) radiometric calibration framework for reducing atmospheric contributions in UAS imagery and for producing scaled remote sensing reflectance imagery. Using a MicaSense RedEdge camera flown on a custom-built octocopter, the research reported herein finds that atmospheric contributions have an important impact on UAS imagery. Data collected over the Lower Pearl River Estuary in Mississippi during five week-long missions covering a wide range of environmental conditions was used to develop and test a simplified ELM radiometric calibration framework designed specifically for the reduction of atmospheric contributions to UAS imagery in studies with limited site accessibility or data acquisition time constraints. The framework was effective in reducing atmospheric and other external contributions to UAS imagery. Unique to the proposed radiometric calibration framework is the radiance to reflectance conversion conducted externally from the calibration equations which allows for the normalization of illumination independent from the time of UAS image acquisition and from the time of calibration equations development. This paper presents the simplified ELM radiometric calibration framework that can be used as a time-effective calibration technique to reduce errors in the UAS imagery.

The RAINBOW Phase III study established the efficacy of the combination of paclitaxel and ramucirumab, a monoclonal antibody targeting VEGF receptor-2 (VEGF-R2), as second-line therapy. We retrospectively analyzed the data of patients treated with ramucirumab plus paclitaxel at our Institution to evaluate the impact of clinical heterogeneous figures on the efficacy and safety of this combination paclitaxel/ramucirumab in a real- life cohort of patients. After a median follow-up of 10.74 months, the median progression-free survival (PFS) was 5.8 months (95% CI: 3.04 - 5,63). Disease control rate (DCR) was 61% and the median duration of response (DOR) was 5.8 months. Median overall survival (OS) was 8.3 months. A trend toward better outcome was observed in HER2 positive patients. In multivariate analysis, nutritional status (p = 0.0001) and number of metastatic sites (p = 0.0266) resulted significantly related with longer PFS. Our analysis confirmed the efficacy and safety of the combination of ramucirumab with paclitaxel also in the real-life practice and the median PFS is significantly longer than that reported for Western population in previous studies. Subgroup analysis confirms the key-role of nutritional status as prognostic factor and suggests a possible interaction between EGF and angiogenesis pathways that deserves further investigations.

It is always a difficult task to assign the peaks recorded from vibrational spectrum. Herein we explored a new pathway of density functional theory (DFT) simulation to present three kinds of spectra of ice XIV and can be referenced as inelastic neutron scattering (INS), IR, and Raman experimental spectrum. The INS spectrum is proportional to phonon density of states (PDOS) while the photon scattering signals reflect the normal vibration frequencies near the Brillouin zone (BZ) center. Based on good agreements with experimental data, we identified the relative frequency and made scientific assignments by normal vibration modes analysis. The debating two hydrogen bond (H-bond) peaks among ice phases from INS have been discussed and the dynamic process of H-bond vibrations were found to be classified into two basic modes. we deduce that two H-bond modes are a general rule among ice family and more works are ongoing to investigate this subject.

Local binary pattern is one of the visual descriptors and can be used as a powerful feature extractor for texture classification. In this paper, a novel representation for face recognition is proposed, called it Bilateral Line Local Binary Patterns (BL-LBP). This scheme is an extension of Line Local Binary Patterns descriptors in the statistical learning subspace. The present bilateral descriptors are fused with an ensemble learning of calibrated SVM models. The performance of this scheme is evaluated using 5 standard face databases. It is found that it is robust against illumination variation, diverse facial expressions and head pose variations and its recognition accuracy reaches 98 percent, running on a mobile device with a processing speed of 63 ms per face. Results suggest that our proposed method can be very useful for the vision systems that have limited resources where the computational cost is critical.

Following an initial mechanical insult, traumatic spinal cord injury (SCI) induces a secondary wave of injury, resulting in a toxic lesion environment inhibitory to axonal regeneration. This review focuses on the glial cell line-derived neurotrophic factor (GDNF) and its application, also in combination with other factors and cell transplantations, for repairing the injured spinal cord. As recent decades of studies strongly suggest combinational treatment approaches hold the greatest therapeutic potential for the central nervous system (CNS) trauma, future directions of combinational therapies will also be discussed.

Background: There is lack of data on types of community first aids use and treatment given post injuries from many low-middle income countries, including India. Materials and Methods: A cross-sectional study was conducted among children up-to 18 years of age, in Ujjain district, India to understand types of first aid given and health seeking post injury. Results: A total of 1087 injuries, in 1049 children were identified in last one year, 729 (67%) received, first aid and 758 (72%) sought some healthcare. Children with burns received most (86%) first aid, while most children (84%) with road traffic accidents (RTA) sought health care. Most children (52%) sought healthcare from a private health set-up; most (65%) being transported within the golden hour; motorbikes being the most preferred (50%) mode of transport. Only 1% injured used ambulance services. Commonly reported first aid included: use of coconut oil on wounds from falls (38%) and burns (44%); antiseptic cream on wounds from RTA (31%), turmeric in falls (16%), and rubbing of metal on a bitten site (47%). Potentially harmful substances applied included lime, toothpaste, clay and mud. Conclusion: In most injuries, appropriate locally available substances, were used by the community. Our findings will help design community interventions to increase appropriate first aid in childhood injuries.

Typhonium flagelliforme is an Indonesian herbal plant used and applied traditionally to treat cancer diseases. Gamma rays have irradiated rodent tuber mutant plant at six doses gray to in-crease the chemical compounds of anticancer activity. The effect of isolated compounds from ro-dent tuber mutant plants has never been studied and published yet. Our study unveiled the poten-tial of stigmasterol as a remarkable cytotoxic agent and the significant contribution of NMR spectroscopy, IR, Mass spectra, QTOF MS towards the isolation and identification of this anti-cancer agent. Stigmasterol was isolated from T. flagelliforme mutant plant. Stigmasterol was more effective against MCF-7 cells with an IC50 value of 0.1623 µM than Cisplatin with IC50 value 13.2 µM. It is the most potential and active fraction in the human breast cancer cell line. The mo-lecular docking study analyzed the chemical profile of stigmasterol to confirm the receptor in agonist binding sites. The prediction of the toxicity of stigmasterol compounds using in silico and analysis of its interaction with the receptor can act as a competitive regulator with a high-affinity binding site on FXR. Stigmasterol has potential as a candidate for an anticancer drug that pro-moting further clinical action.

In this study, a matched-mode autoregressive source depth estimation method (MMAR) based on autoregressive (AR) wavenumber estimation is proposed for a moving source in shallow water waveguides. The signal original frequency and the environmental parameters, namely, the sound speed profile and bottom properties are known as a prior knowledge. The mode wavenumbers are estimated by the AR modal wavenumber spectrum. On the basis of the mode wavenumber estimation, the mode amplitudes can be estimated by the wavenumber spectrum that is obtained by generalized Hankel transform. The source depth estimation is determined by the peak of source depth function wherein the data mode best matches the replica mode that is calculated using a propagation model. Compared with other methods of moving source depth estimation, the proposed method exhibits a better performance in source depth estimation under low signal-to-noise ratio or the small range span. The selection of horizontal line array depth is illustrated by simulation and normal mode theory in details.

Many spectroscopic diagnostics are routinely used as a technique to infer the plasma parameters from line emission spectra but their accuracy depends on the numerical model or code used for the fitting process. However, the validation of a line shape code requires some steps : comparison of the line shape code with other similar codes for some academic (simple) cases and then more complex ones, comparison of the fitting parameters obtained from the best fit of the experimental spectra with those obtained with other diagnostic techniques and/or comparison of the fitting parameters obtained by different codes to fit the same experimental data. Here we compare the profiles of the hydrogen Balmer β line in a helium plasma computed by six codes for a selected set of plasma parameters and we report on the plasma parameters inferred by each of them from the fitting to a number of experimental spectra measured in a helium corona discharge where the pressure was in the range 1- 5 bar.

The main goal of the present paper is to construct some families of the Carlitz’s q-Bernoulli polynomials and numbers. We firstly introduce the modified Carlitz’s q-Bernoulli polynomials and numbers with weight (α, β) and investigate their some explicit properties and identities arising from the bosonic q-Volkenborn integral on ℤ_p. We then define the modified degenerate Carlitz’s q-Bernoulli polynomials and numbers with weight (α, β) and obtain some recurrence relations and other identities. Moreover, we derive some correlations with the modified Carlitz’s q-Bernoulli polynomials with weight (α, β), the modified degenerate Carlitz’s q-Bernoulli polynomials with weight (α, β), the Stirling numbers of the first kind and second kind.

Integrating triple bottom line (TBL) goals into supply chains (SCs) is a challenging task which necessitates the careful coordination of numerous stakeholders’ individual interests. Recent technological advancements can impact TBL sustainability by changing the design, structure and management of modern SCs. Blockchain technology enables immutable data records and facilitates a shared data view along the supply chain. The Physical Internet (PI) is an overarching framework that can be applied to create a layered and comprehensive view of the SC. In this conceptual paper I define and combine these technologies and derive several high-level research areas and research questions to investigate adoption, management as well as structural SC issues. I suggest a theory-based research agenda for the years to come that exploits the strengths of rigorous academic research, while remaining relevant for the industry. Furthermore, I suggest various well-established theories to tackle the respective research questions and provide specific directions for future research.

In the search for new 2D materials beyond graphene with similar exemplary properties Stanene the new graphene relative was successfully synthesized and characterized in 2016 [14]. This new material which consists of atomically thin tin (Sn) atoms arranged in a hexagonal lattice has shown great promise in gas sensing applications in its pristine, doped and functionalized forms as evidenced by the recent research outputs following its discovery. Researchers have discovered that with its exotic properties it is highly efficient in the detection of the environmentally harmful gases like SO2, NO2, CO2, NH3 and can serve as a multifunctional gas sensor. In this focused and up-to-date review we aim to group the literature on first principles studies of stanene regards to its application for gas sensing and critically examine the success/failures of its multifunctional gas sensing properties as compared to graphene. We systematically present and discusses how structural deformations, defects and doping effect the gas sensing performance. Despite the impressive progress in the field of gas sensing with stanene shown by first principles calculations, many challenges in large scale synthesis, device fabrication and commercialization need to be addressed. The current review can help understand the current status and drawbacks of stanene and identify future directions in this field.

Sentinel-1A/B radar remote sensing data were applied for the first time to determine the sixth nuclear test, its underground explosion h-bomb location and affected zone in North Korea, on September 3, 2017. Location of epicenters nuclear test were found according to line-of-sight displacement images via its maximum value. Line-of-sight displacement images were obtained by processing in the GMTSAR package in the VirtualBox virtual machine of the Linux Ubuntu 16.04 operation system. In this research, three scenes Sentinel-B data with descending orbits were considered, one after and two before the event (the nuclear test date) scene were used.

Background: Barleria lupulina Lindl. (Hop-headed) is a small shrub, possess potent anti-inflammatory, analgesic, anti-leukemic, antitumor, anti-hyperglycemic, anti-amoebic, virucidal, diuretic, bactericidal and antibiotic properties. Methods: Cytotoxicity, bioactive assay and genetic analysis of B. lupulina were investigated in the present communication. The leaf extract was investigated by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT), Neutral red uptake (NRU), DNA fragment, reactive oxygen species (ROS) generation, mitochondrial membrane potential (MMP) assay, gene expression analysis and cDNA synthesis to evaluate anti-cancerous potency using cancerous THP-1 cell lines in vitro and in vivo. Results: HPTLC analysis reveals four spots and GC-MS analysis displayed the presence of eleven bioactive compounds among which benzofuranon, hexadecanoic acid, ethyl 9,12,15-octadecatrienoate, and 3,7,11,15-tetramethyl-2-hexadecanoic acid were the most prominent compounds. The ethanolic extract showed significant cytotoxicity (P<0.5) against THP-1 cell line at a concentration of 1mg/mL. The cells were also observed for apoptosis through DNA fragmentation in B. lupulina treated cells. Conclusions: It can be concluded that if the dose range was further refined within the range of 100-1000 µg/mL there could be dose at which the entire population of the THP-1 cell line would be apoptosis induced. The extract induced ROS in the cells after 30 minutes of exposure displaying cytotoxic effects and DNA fragmentation assay.

The present work encompasses an application-oriented perspective to the possible employment of gold nanoparticles as nanomedicine in cancer therapeutics. The rationale of the work lies in the growing needs for assessment of advanced alternative treatment of cancer employing functionalized nanoparticles as nanomedicine. Gold nanoparticles fabricated via green chemistry methods by leaves of a time-honored medicinal plant, Piper betle were ascertained for their synthesis and properties under the umbrella of characterization of nanoparticles, through various techniques like UV-vis spectroscopy, FTIR spectroscopy, X-ray diffraction, and scanning electron microscopy. The cytotoxicity assay of well-characterized gold nanoparticles was monitored against lung cancer cell line (A549) by metabolic and imaging assays. MTT assay or the metabolic assay was performed for a range of nanoparticles’ concentrations. The results were promising and proved to be a leading-edge venture, envisaging the possibility of gold nanoparticles for cancer therapeutics.

Smenamides are an intriguing class of peptide/polyketide molecules of marine origin showing antiproliferative activity against lung cancer Calu-1 cells at nanomolar concentrations through a clear pro-apoptotic mechanism. To probe the role of the activity-determining structural features, the 16-epi-analogue of smenamide A and eight simplified analogues in the 16-epi series were prepared using a flexible synthetic route. The synthetic analogues were tested on multiple myeloma (MM) cell lines showing that the configuration at C-16 slightly affects the activity, since the 16-epi-derivative is still active at nanomolar concentrations. Interestingly, it was found that the truncated compound 8, mainly composed of the pyrrolinone terminus, was not active while compound 17, essentially lacking the pyrrolinone moiety, was 1000-fold less active than the intact substance and was the most active among all the synthesized compounds.

Breast cancer treatment mostly revolved around radiation therapy and surgical interventions, these treatments doesn’t provide satisfactory relief to the patients and carry unmanageable side-effects. Nanomaterials show promising results in treating cancer cells and have many advantages such as high biocompatibility, bioavailability and effective therapeutic capabilities. Interestingly, fluorescent magnetic nanoparticles have been used in many biological and diagnostic applications, but there is no report of use of fluorescent magnetic submicronic polymer nanoparticles (FMSP-nanoparticles) in the treatment of human breast cancer cells. In the present study, we have tested the effect FMSP-nanoparticles on human breast cancer cells (MCF-7). We have tested different concentrations (1.25µg/1mL, 12.5µg/mL and 50µg/1mL) of FMSP-nanoparticles in MCF-7 cells and evaluated the nanoparticles response morphometrically. Our results revealed that FMSP-nanoparticles produced a concentration dependent effect on the cancer cells, dose of 1.25µg/mL produced no significant effect on the cancer cell morphology and cell death, whereas dosages of 12.5µg/mL and 50µg/mL respectively showed significant nuclear augmentation, disintegration, chromatic condensation followed by dose dependent cell death. Our results demonstrate FMSP-nanoparticles have ability to induce cell death in MCF-7 cells and may be considered as a potential anti-cancer agent for breast cancer treatments.

Background: Breast cancer is the leading cause of cancer mortality and morbidity among Indonesian women. Identification of biological pathways leading into therapeutic resistance through in vitro model is an important step to develop alternative effective therapy in breast cancer. Loss of PTEN expression has been associated with resistance to chemotherapy by involving PI3K/PTEN- dependent apoptosis pathway. We conducted in vitro experiment to investigate the association of hsa-miR-21 and PTEN expression in Doxorubicin-resistant MCF-7 cell line. Methods: Parental MCF-7 cells were periodically incubated with Doxorubicin to obtain specific Dox-resistant variant determined by IC50 using MTT assay. PTEN protein expression was analyzed using immunocytochemistry. Expression of mature has-miR-21 was measured using qRT-PCR. Results: The IC50 of Doxorubicin in parental MCF-7 and Doxorubicin-resistant MCF-7 cells (MCF-7/Dox) was 0.68 and 5.78 µg/ml, respectively. Hsa-miR-21 was significantly overexpressed in MCF-7/Dox cells compared to parental MCF cells (7.94 fold changes). Conclusion: PTEN and hsa-miR-21 expression levels were negatively correlated in Doxorubicin resistant-MCF cells. Further study to confirm the causal relationship of miR-21 overexpression and PTEN downregulation in MCF-7/Dox is required.

Results from a behavioral economic laboratory experiment are used to enhance our understanding of public health decisions made during the COVID-19 pandemic. The identification of systematic biases from optimal decision theory found in controlled experiments could help inform public policy design for future public health crises. The laboratory and the shelter-in-place decisions made during COVID-19 included elements of risk, uncertainty and ambiguity. The lab findings found individuals adopt different decision rules depending on both personal attributes and on the context and environment in which the decision task is conducted. Key observations to consider in the context of the COVID-19 decision environment include the importance of past experience, the ability to understand and calculate the odds of each action, the size and differences in economic payoffs given the choice, the value of information received, and how past statistical independent outcomes influence future decisions. The academic space encompassing both public health and behavioral economics is small, yet important, particularly in the current crisis. The objective of continued research in this area would be to develop a more representative model of decision-making processes, particularly during crisis, that would serve to enhance future public health policy design.

Background: First episode psychosis (FEP), schizophrenia and affective disorders are accompanied by activation of the immune inflammatory response system (IRS). The compensatory immune-regulatory reflex system (CIRS) is a regulatory immune response that is induced by the IRS but exerts negative feedback through, for example, increased levels of anti-inflammatory cytokines such as IL-4, IL-13 and IL-10. Different phenotypes of schizophrenia may exhibit distinct IRS and CIRS immune profiles.Aims: This study aims to examine the IRS and CIRS components, including macrophagic M1, T-helper (Th)-1, Th-2, Th-17 and T-regulatory (Treg) phenotypes, in antipsychotic-naïve FEP patients before and after risperidone treatment.Methods: We included 31 antipsychotic-naïve FEP patients who had measurements of IRS and CIRS biomarkers before and after treatment with risperidone for 10 weeks, and 22 healthy controls.Results: Antipsychotic-naive FEP patients showed interrelated increments in M1, Th-1, Th-2, Th-17 and Treg phenotypes and a relatively greater IRS response (especially granulocyte-macrophage colony-stimulating factor (GM-CSF), interleukin (IL)-6 and IL-12) as compared with the CIRS response (IL-4, IL-13, IL-5 and IL-10). Inflammatory markers, especially IL-6 and IL-8, were significantly correlated with negative, psychotic, affective and excitation symptom dimensions. Treatment with risperidone significantly suppressed the IRS and CIRS. Baseline levels of CIRS biomarkers, especially higher soluble tumor necrosis factor receptor-1 and IL-10 predicted clinical improvement during treatment.Discussion: Our findings indicate that FEP is characterized by robust IRS (M1 + Th-1 + Th-17) and CIRS responses, suggesting that monocytes, macrophages, Th-1, Th-2, Th-17 and Treg cells are activated. The findings indicate that a) FEP patients are prone to the detrimental effects of M1, Th-1, Th-17 and Th-2 cells, which may contribute to long-lasting abnormalities in brain circuitry; and b) in FEP, the CIRS may contribute to recovery from the acute phase of illness. Enhancing the CIRS is a new drug target to treat FEP.

There have been several cases of large-scale wind generators (WGs) tripping off caused by untimely fault removing in recent years. Currently, the discoordination between the box-type transformer fuse protection (BTFP) and two-section collecting line current protection (CLCP) brings a security risk to wind farm. In order to ensure the selectivity, the first section (Sec-I) CLCP should be set a enough interval that is longer than the fuse melting time, and another interval is set for the Sec-II CLCP, which weakens the speed of the CLCP. When a fault occurs on the collecting line, there is no doubt that WGs cannot work too long in abnormal operation, which may cause WGs to be placed off the grid. For a power system with high penetration of wind power, large-scale WGs tripping off will cause a great power shortage, and affect the stability of the power system. The selectivity and sensitivity of the CLCP is analyzed in detail to make the CLCP speed better. Considering the fault ride-through ability of WGs, the fault clear time is an important factor to lead to large-scale WGs tripping off. Two main works are done in this paper. The first is to accelerate the speed of the Sec-I CLCP though reducing the protection zone. Another one is introduce the risk assessment module into the CLCP, which not only improve the speed of the CLCP but also ensure the safety of the wind farm during faults. According to the deference in trip-off causes of WGs, the matching functions are created to assess the trip-off risk of WGs on the spot. In the case of fault, the trip-off risk indicators of WGs are timely updated to data sharing center and open to the CLCPs. The set of risk indicators is divided into several subsets according to the risk range. The dynamic changes of the subsets during fault help to improved CLCP scheme. This scheme can accelerate protection speed based on the increasing risk of large-scale WGs tripping off in wind farms. Compared with traditional CLCP, this approach can make the CLCP combines selectivity and speed better based on the analysis of the ride- through ability of WGs.

Efficient quality evaluation provides support for the timely and good maintenance of the lane line marking. This paper searches and optimizes the back propagation(BP) network model which referred to the analytic hierarchy process(AHP) model structure, as well as the number of nodes in the middle layer network. Based on this, a comprehensive evaluation method of multi-dimensional lane line quality such as shape, color and contrast is established. The experimental results show that the parameters of the model are more simplified, and the scoring and classification results of lane lines are more accurate.

This article focuses on the current state-of-the-art in the area of cellular and molecular biotechnology for over-production of clinically relevant therapeutic growth factors and how the technology can be used for the treatment of osteoarthritis (OA). Transfected and irradiated protein packaging cell lines may be used as “cellular factories” for large-scale production of therapeutic proteins and pro-anabolic growth factors, particularly in the context of cartilage matrix regeneration. We discuss the potential for new innovations in regenerative medicine for degenerative diseases of synovial joints using mammalian protein production platforms, specifically protein packaging cell lines, for over-producing growth factors for cartilage tissue regeneration and give recent examples. Mammalian protein production platforms that incorporate protein packaging cell lines are superior to bacterial expression systems and are likely to have a significant impact on the development of new biological therapies for treating focal cartilage defects and more generally for the treatment of degenerative joint diseases such as OA.

Disputes on authorships or the order of authors on publications are among the most common conflicts in science, particularly where multi-author papers have become the norm. Here, I propose an adaptable and generalizable method to rationalize and democratize decisions about authorships, which can be applied in diverse scientific areas. In the process, the authors of a manuscript collect, discuss, score, and weight their contributions to the final manuscript. The decision process is assisted by a simple spreadsheet-based “authorship matrix”, which helps to break down the complexity of different contributions and their importance. The matrix generates a score s describing the percentage of the author’s total contributions and can be used to determine authorship and their order. The transparency and simplicity score s can reduce conflicts and thus increase productivity in collaborations.

For a given set of plasma parameters, along a single series (Lyman, Balmer etc) the lines with higher principal quantum number(n) lines get progressively wider, closer to each other, and start merging for a certain critical n. In the present work four different codes(with further options) are used to calculate the entire Balmer series for moderate and high electron densities. Particular attention is paid to the relevant physics, such as the cutoff criteria, strong and penetrating electron collisions.

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.

With the accelerating urbanization process, the population increasingly concentrates in urban areas. In view of the special situation in China and a series of problems in the process of rapid urbanization, there were no reasonable measures for optimizing the population pattern. This study explored the distribution pattern of the Chinese population and proposed an optimization plan for the population distribution using GIS analysis. The main findings were as follows. (1) From 2010 to 2015, the distribution of population density in China presented a pattern of high in the southeast and low in the northwest based on the county-level administrative regions. The population still showed a tendency to migrate to the southeast of the country based on the “Hu Huanyong Line”. (2) There was a great difference in the land use efficiency in terms of population and economic production in China. The economic concentration in China was higher than the population concentration. In the areas where population and economic production were aggregated, GDP per capita and land use efficiency were higher. (3) Based on the land use efficiency in terms of population and economic production, the optimized urbanization plan of “1+4+11” for China’s urbanization was put forward, namely, one national-level aggregated area of population and economic production, 4 regional-level aggregated areas of population and economic production, and 11 local regionally aggregated areas of population and economic production. This optimization plan for urbanization represents an attempt to explore the direction of China’s urbanization, and it can be used to optimize the spatial development pattern and provide scientific guidance for the new urbanization plan.

PPARgamma belongs to the group of nuclear receptors which is expressed in the trophoblast and together with other factors is responsible for the maintenance of pregnancy. Apart from that PPARgamma is also a main factor for macrophage polarization. The aim of this study was to investigate the combined expression pattern and frequency of PPARgamma under physiological circumstances and in spontaneous and recurrent miscarriages in the trophoblast and in maternal macrophages of the decidua. Human placental tissues of the first trimester (15 physiologic pregnancies, 15 spontaneous abortion & 16 recurrent miscarriage placentas) were analyzed for expression of the nuclear receptor PPARgamma. Expression changes were evaluated by immunohistochemistry and RT-PCR in trophoblast and in maternal macrophages of the decidua. Maternal macrophages were identified by double immunofluorescence using CD68 as marker for macrophages. The intermediate villous trophoblast revealed a significantly lower PPARgamma expression in spontaneous and recurrent abortion. Maternal macrophages express PPARgamma. Their number is significantly enhanced in the decidua of spontaneous miscarriages whereas in recurrent miscarriages maternal macrophages seem to express PPARgamma only in very few cases. PPARgamma is associated with an M2 polarization state that is common for decidual macrophages. The lack of PPARgamma in recurrent miscarriage decidual macrophages seems to be associated with a specific inflammatory response against the fetus.

Technological advancements and innovations have profoundly changed the lives of people giving rise to smart environments, cities, and societies. As homes are the building block of cities and societies, smart homes are critical to establishing smart living and are expected to play a key role in enabling smart cities and societies. The current academic literature and commercial advancements on smart homes have mainly focused on developing and providing smart functions for homes to provide security management and facilitate the residents in their various activities such as ambiance management. Homes are much more than physical structures, buildings, appliances, operational machines, and systems. Homes are composed of families and are inherently complex phenomena underlined by humans and their relationships with each other, subject to individual, intragroup, intergroup, and intercommunity goals. There is a clear need to understand, define, consolidate existing research, and actualize the overarching roles of smart homes, the roles of smart homes that would serve the needs of future smart cities and societies. This paper introduces our data-driven parameter discovery methodology and uses it to provide, for the first time, an extensive, rather fairly comprehensive, analysis of the families and homes landscape seen through the eyes of academics and the public using over a hundred thousand research papers and nearly a million tweets. We develop a methodology using deep learning, natural language processing (NLP), and big data analytics methods and apply it to automatically discover parameters that capture a comprehensive knowledge and design space of smart families and homes comprising social, political, economic, environmental, and other dimensions. The 66 discovered parameters and the knowledge space comprising 100s of dimensions are explained by reviewing and referencing over 300 articles from the academic literature and tweets. The knowledge and parameters discovered in this paper can be used to develop a holistic understanding of matters related to families and homes facilitating the development of better, community-specific, policies, technologies, solutions, and industries for families and homes, leading to strengthening families and homes, and in turn, empowering sustainable societies across the globe.

Computational methods are essential to support and advance nuclear technologies due to the hazards of handling and analysing highly radioactive materials such as spent nuclear fuel (SNF). However, many such methods, including those thatcan predict SNF compositions and decay heat parameters, require expensive, proprietary software, alongside significant programming experience and computational power for utilisation, severely limiting availability of data and hampering research throughput. Although some datasets are available, many are incomplete or only cover certain fuel systems for older reactor types. Research investigating new methods for SNF recycling, for example, requires compositional and decay heat data for fuel systems not covered by extant data, though analogous source data may be available. With this in mind, we have developed a simple, accessible, and flexible method for extrapolation of isotopic, elemental, and decayheat compositions for SNF at discharge and following decay storage before recycling, based on an extant dataset. This semi-empirical method uses physical and mathematical first principles and can be performed using software accessible to all researchers. This provides outputs accurate to within 1% of reference values interpolated within the range of available data for isotopic compositions, with sensible extrapolations at higher burnups beyond those reported, withoverall elemental outputs accurate to within 0.1%of expected totals. In this publication, we present the developmental methodology, some sample data, the present limitations, and options for future development and expansion of functionality.

Base on building information modeling(BIM) plus with Robotic process automation (RPA) technology is rapid development in smart building operations and maintenance (O&M). RPA is a workflow-based automated execution tool that is particularly well suited for replacing manual execution of simple and repetitive tasks using computer systems. The use of RPA technology can saves man-hours and increases productivity, which is important for the automation of building operations and maintenance operations.. The BIM technology, as an advanced technology in the construction industry, it can provide new ideas and methods for building operation and maintenance based on its visualization characteristics. That’s integrating RPA with BIM technology which will enhance the digitalization and virtualization of smart building operation and management. In this article will first introduce the features of RPA and BIM technology and then discuss the technical roadmap for remote automated operation and maintenance of smart building equipment room to implemention a low-cost and high efficient building equipment room operation and maintenance solution.

The strictness of the result of an excavation, whether mechanical or by means of explosives, is naturally conditioned by the objective, and therefore by the type of technique applied to achieve it. To attain the best results in terms of rock breakage and respect of the final profile, it’s important to evaluate the excavation specific energy and its optimization. This research focuses on evaluating the effects of different techniques on the quality of final walls in open-pit and underground operations. Different geometries and configurations can be applied to both quarrying and tunnelling blasts. The research is aimed to push contour blasts to their limits, and the main aspects are discussed in order to improve the blast parameters in the daily practice.

Passive plasma spectroscopy is a well-established non-intrusive diagnostic technique. Depending on the emitter and its environment which determine the dominant interactions and effects governing emission line shapes, passive spectroscopy allows the determination of electron densities, emitter and perturber temperatures as well as other quantities like abundances. However, using spectroscopy needs appropriate line shape codes retaining all the physical effects governing the emission line profiles. This requires for line shape code developers to continuously correct or improve them to increase their accuracy when applied for diagnostics. This is exactly the aim expected from code-code and code-data comparisons. In this context, the He I 492 nm emitted in a helium corona discharge at room temperature represents an ideal case since its profile results from several broadening mechanisms: Stark, Doppler, resonance and van der Waals. The importance of each broadening mechanism depends on the plasma parameters. Here the profiles of the He I 492 nm in a helium plasma computed by various codes are compared for a selected set of plasma parameters. In addition, preliminary results related to plasma parameter determination using experimental spectra from a helium corona discharge at low pressure 1- 2 bars, are presented.

Nowadays, the wasting of resources is one of the fundamental challenges of the industrial sector. The rectangle packing problem can be very effective in this context. Practical applications of this issue in the timing and designing of the industries and businesses are very remarkable. The purpose of this issue is to arrange a set of rectangles with specific dimensions in a rectangular page with a specific width and unlimited height without overlapping. The fundamental challenge in this issue is that this is an NP-complete issue. Therefore, it is difficult to achieve the best arrangement, which has the maximum rate of resource utilization and also has a linear running time. Many algorithms have been presented to estimate a practical solution for this issue. In the past decades, the best fit method has been one of the most useful methods for this purpose. This study presents a combinatorial algorithm based on two algorithms, including the lowest front-line strategy and the best-fit algorithm. The running results indicate that the suggested algorithm performs well, despite its simplicity. The time complexity of the suggested algorithm is O(nm), in which n is the number of input rectangles and m is the number of the created front lines.

The Strawberry Line is a linear Local Nature Reserve extending along a dismantled railway corridor in North Somerset, England. The Reserve is cherished as a recreational resource by local communities and I am very fortunate to live beside it. During the COVID-19 lockdown of spring 2020, I decided to make use of my permissible daily exercise to record the distribution of breeding birds along my particular ‘patch’ of the Strawberry Line - the Vale of Winscombe section in the Mendip Hills. In describing the Reserve’s birdlife, I hope that I can provide an added layer of interest for locals and visitors, which might help in these difficult times deliver an enhanced dose of ‘Nature’s Fix’ and perhaps also shine a light towards a greater appreciation and connection with the natural world.

This paper discusses a MEMS switch that can be fabricated using low temperature (<100^oC) deposition and patterning techniques suitable for the back-end-of-the-line integration with CMOS. The resulting cross-bar switches can be used for electrostatic discharge protection, FPGA implementation, chip security assessment and lock-down, and circuit block power management. We discuss platinum and iron switch with turn-on voltages of ~ 1.8 V. In the case of the iron switches, we also show that they can be magnetized to have “memory” and stay on when turned on. Platinum switch cycling of up to 1000 times did not show any changes in their turn-on voltage and their contact resistance was unchanged. The 10-100 nm switch airgaps were formed using low temperature sputtered sacrificial polysilicon and XeF₂ etching. XeF₂ does not attack any of the metals used in CMOS enabling fabrication of cross-bar switches with any of these metals. Once activated, it takes ∿ 6 to mechanically turn on the switch that can be decreased to ~1 ns by optimizing the device structure. Interestingly, the nm-scale gaps can be used as spark gap as a fast plasma switch to discharge first followed by the activation of the MEMS switch.

This article presents a new theory on redshift of light from celestial bodies. Lately it has been found that the Hubble constant calculated from different methods discord so much that calls arise for new physics to explain. Also, in addition to many unsolved puzzles like dark matter and source of expansion force, we shall show in this article that the current theory of redshift implies a few hidden, unreasonale assumptions. By assuming photon has temperature and its thermal energy is fully converted to wave energy, this article shows that photon can have a new redshift called Temperature Redshift, which not only is more significant for remote stars or galaxies, but also better fits the observational data, including those used in Hubble constant calculation. As such, if true, this new theory not only adds to our new understanding of photons, but may totally change our current understanding of the Universe, i.e., the Big Bang theory.

Ice covering on overhead transmission lines would cause damage to transmission system and long-term power outage. Among various de-icing devices, modular multilevel converter (MMC) based DC de-icer (MMC-DDI) is recognized as a promising solution due to its excellent technical performance. Its principle feasibility has been well studied, but few literature discuss its economy or hardware optimization, thus the designed MMC-DDI for high voltage transmission lines is usually too large and too expensive for engineering applications. To fill this gap, this paper presents a quantitative analysis on the converter characteristics of MMC-DDI, and calculates the minimal converter rating and its influencing factors. It reals that, for a given de-icing requirement, the converter rating varies greatly with its AC-side voltage. Then an optimization configuration is proposed to reduce the converter rating and improve its economy. The proposed configuration is verified in a MMC-DDI for a 500kV transmission line as a case study. The result shows, in the case of outputting same de-icing characteristics, the optimized converter rating is reduced from 151 MVA to 68 MVA, and total cost of MMC-DDI is reduced by 48%. This analysis and conclusion are conductive to the optimized design of multilevel DC de-icer, then to its engineering application.

We introduce a modelling framework for the investigation of on-line machine learning processes in non-stationary environments. We exemplify the approach in terms of two specific model situations: In the first, we consider the learning of a classification scheme from clustered data by means of prototype-based Learning Vector Quantization (LVQ). In the second, we study the training of layered neural networks with sigmoidal activations for the purpose of regression. In both cases, the target, i.e. the classification or regression scheme, is considered to change continuously while the system is trained from a stream of labeled data. We extend and apply methods borrowed from statistical physics which have been used frequently for the exact description of training dynamics in stationary environments. Extensions of the approach allow for the computation of typical learning curves in the presence of concept drift in a variety of model situations. First results are presented and discussed for stochastic drift processes in classification and regression problems. They indicate that LVQ is capable of tracking a classification scheme under drift to a non-trivial extent. Furthermore, we show that concept drift can cause the persistence of sub-optimal plateau states in gradient based training of layered neural networks for regression.

Micro channel tube (MCT) is widely employed in industry due to its excellent efficiency in heat transfer. An MCT is commonly produced through extrusion within a porthole die, where severe plastic deformation is inevitably involved. Moreover, the plastic deformation, which dramatically affects the final property of the MCT, varies significantly from location to location. In order to understand the development of the microstructure and its effect on the final property of the MCT, the viscoplastic self-consistent (VPSC) model, together with the finite element analysis and the flow line model, is employed in the current study. The flow line model is used to reproduce the local velocity gradient within the complex porthole die, while VPSC model is employed to predict the evolution of the microstructure accordingly. In addition, electron backscatter diffraction (EBSD) measurement and mechanical tests are used to characterize the evolution of the microstructure and the property of the MCT. The simulation results agree well with the corresponding experimental ones. The influence of the material’s flow line on the evolution of the orientation and morphology of the grains, and the property of the produced MCT are discussed in detail.

The semi-logarithmic plot of the cumulative number of cases of epidemics resembles the response of a first-order systems for a step load. This similarity was utilized to develop a first order model that can be used for extracting information about the dynamics of infectious disease epidemics. The developed model was validated using COVID-19 data of China. It was also heuristically fitted to other 13 countries. Obtained results indicated that the model can reliably forecasts the number of infected person, epidemic growth speed towards steady-state condition (process time constant, T), and time to reach steady-state condition (4T). The developed model will help public health authorities in developing more effective control strategies of epidemics.

The dependence on Unmanned Aerial Vehicles (UAVs) has dramatically increased in many sectors around the globe. UAVs are in high demand, and their technology is developing quickly due to their sophisticated ability to handle various issues. UAVs are capable of replacing labor-intensive tasks with conducive and safe regulation. Additional tools or sensors need to be added to the UAVs system to ensure the implementation of UAVs able to serve into industrial level. The paper aims to consolidate and present a thorough understanding of the various stages of image processing pipelines deployed in UAV applications, including image acquisition, preprocessing, feature extraction, object detection and tracking, and decision-making processes. Throughout this paper, several aspects were deliberate such as strengths, limitations, and performance metrics of existing approaches, this paper seeks to provide researchers, engineers, and practitioners with valuable insights into the challenges and opportunities of image processing systems for UAVs. Ultimately, the synthesis of this knowledge will contribute to enhancing the effective-ness, autonomy, and applicability of UAVs in diverse fields such as surveillance, agriculture, disaster management, and environmental monitoring.

An improved anti-noise morphology vision navigation algorithm is proposed for intelligent tractor tillage in a complex agricultural field environment. Firstly, the two key steps, Guided Filtering and improved anti-noise morphology navigation line extraction, were addressed in detail. Then the experiments were carried out in order to verify the effectiveness and advancement of the presented algorithm. Finally, the optimal template and its application condition were studied for improving the image processing speed. The comparison experiment results show that the YCbCr color space has minimum time consumption, 0.094 s, compared with HSV, HIS and 2R-G-B color spaces. The Guided Filtering method can enhance the new & old soil boundary effectively than any other methods such as Tarel, Multi-scale Retinex, Wavelet-based Retinex and Homomorphic Filtering, meanwhile, has the fastest processing speed of 0.113 s. The extracted soil boundary line of the improved anti-noise morphology algorithm has best precision and speed compared with other operators such as Sobel, Roberts, Prewitt and Log. After comparing different size of image template, the optimal template with the size of 140×260 pixels can meet high precision vision navigation while the course deviation angle is not more than 7.5°. The maximum tractor speed of the optimal template and global template are 51.41 km/h and 27.47 km/h respectively which can meet real-time vision navigation requirement of the smart tractor tillage operation in the field. The experimental vision navigation results demonstrated the feasibility of the autonomous vision navigation for tractor tillage operation in the field using the new & old soil boundary line extracted by the proposed improved anti-noise morphology algorithm which has broad application prospect.

As the era of omics continues to expand, omics-based experiments have become popular in industrial biotechnology. They promise deeper biological understanding, which may be leveraged to develop novel solutions to bioprocess optimization and cell line engineering strategies. Despite this expansion, naivety about what omic data offers and how to best handle such data can challenge the extraction of actionable value. However, the value of omic experiments in biotechnology research and development can be maximized with deliberate application of omic approaches and forethought about analysis techniques. Here we describe important considerations when designing and implementing omic-based experiments, and discuss how systems biology analysis strategies can enhance efforts to obtain actionable insights in biomanufacturing.

The origin of life has not been solved as yet, in spit of the time passage more than thirty years from publication of RNA world hypothesis by W. Gilbert (1986), which is based on the “gene/replicator--first” theory. On the contrary, I have proposed [GADV]-protein world hypothesis (GADV hypothesis), assuming that life emerged from [GADV]-protein world, which is grounded on the “protein/metabolism-first” theory. However, two weak points of protein world hypothesis, (i) protein cannot be produced without gene, and (ii) protein cannot be self-replicated, have been frequently pointed out by supporters of RNA world hypothesis. Then, I examined whether the two weak points could be overcome by GADV hypothesis or not. From the results, it was confirmed that (i) [GADV]-protein could be pseudo-replicated in the absence of gene owing to protein 0^th-order structure or [GADV]-amino acids, and (ii) the replication ability is not always required from the beginning but it is sufficient to acquire it at some time point until the emergence of life. Thus, it was concluded that life emerged as [GADV]-protein world hypothesis, which is grounded on the “protein/metabolism-first” theory, expects.

Two X chromosomes of female mammals randomly inactivate one of paternal or maternal X chromosome in early embryonic development and all the daughter cells produced from these cells retain the same feature of X chromosome inactivation, which is called X chromosome inactivation (XCI). Studying the mechanisms of XCI is important for understanding epigenetic that plays an important role in age-associated diseases. The previous studies have demonstrated that binding of RNAs and DNAs may play a role in activating gene expression. In this paper, our study aims to explore whether the mechanisms of XCI involve the RNA binding strength to X chromosome DNAs. The bioinformatics analyses based on big data were used to analyze the simulated binding strength of RNAs (RNA binding strength) to 23 chromosomes (including X chromosome and 22 human autosomes) and the characteristics of repetitive sequences in the X-inactivation centre. The results revealed that RNA binding strength of the long arm of the X chromosome that is almost entirely inactivated in XCI was significantly lower than that of all autosomes and the short arm of X chromosome, meanwhile the RNA binding strengths of inactivation regions in X chromosome were significantly lower than that of regions escaping from XCI. Different repetitive sequence clusters within the center of XCI presented a cross distribution characteristic. To further prove whether the repetitive sequences in human X chromosome involve in XCI, we cloned long interspersed element (LINE-1, L1) and short interspersed element (Alu) from human Xq13, the center of XCI, and constructed expression vectors carrying sense-antisense combination repetitive sequences (L1s or Alus). Effects of combined L1 or combined Alu sequences on expression of EGFP reporter gene were examined in stably transfected HeLa cells, which simulates the effects of repetitive sequences located on chromosomes. The results of experiments revealed transcribed L1 repetitive sequences activated EGFP reporter gene expression, so did the Alus. The experiment results suggested repetitive sequences activated genes by interaction of transcribed RNAs and DNAs. Since the binding of RNAs and DNAs can activate gene, so the low RNA binding strength of human X chromosome may be one of reasons of XCI. The cross distribution characteristics of different repetitive sequence clusters leading to a cascade of gene activation or gene inactivation may be the reason of transcriptional silencing one of the X chromosomes in female mammals.

Wolbachia are intracellular endosymbionts of several invertebrate taxa, including insects and nematodes. Although Wolbachia DNA has been detected in ticks, its presence is generally associated with parasitism by insects. To determine whether or not Wolbachia can infect and grow in tick cells, cell lines from three tick species, Ixodes scapularis, Ixodes ricinus and Rhipicephalus microplus, were inoculated with Wolbachia strains wStri and wAlbB isolated from mosquito cell lines. Homogenates prepared from fleas collected from cats in Malaysia were inoculated into an I. scapularis cell line. Bacterial growth and identity were monitored by microscopy and PCR amplification and sequencing of fragments of Wolbachia genes. The wStri strain infected Ixodes spp. cells and was maintained through 29 passages. The wAlbB strain successfully infected Ixodes spp. and R. microplus cells and was maintained through 2-5 passages. A novel strain of Wolbachia belonging to the supergroup F, designated wCfeF, was isolated in I. scapularis cells from a pool of Ctenocephalides sp. cat fleas and maintained in vitro through two passages over nine months. This is the first confirmed isolation of a Wolbachia strain from a flea and the first isolation of any Wolbachia strain outside the “pandemic” A and B supergroups. The study demonstrates that tick cells can host multiple Wolbachia strains, and can be added to panels of insect cell lines to improve success rates in isolation of field strains of Wolbachia.

The objective of the present work was to determine the productivity and costs of timber harvesting and skidding during the first commercial thinning of a Scots pine stand. The analyzed harvesting set consisted of a mini-excavator (34 kW) with an stroke harvester head (gripping range: 4–30 cm), and a farm tractor coupled to an logging trailer with a hydraulic crane. Merchantable timber (roundwood with a minimum diameter of 5 cm inside bark) was harvested from a 25-year old planted Scots pine stand growing on a grid of 1.4×1.8 m. The study showed the productivity of the mini-harvester range from 3.09 to 3.47 m3∙PMH15 -1, and that of the forwarding set to be 4.07 m3∙PMH15 -1. The analyzed model of productivity as a function of individual tree volume and thinning intensity was statistically significant, but the intensity parameter was significant only on plots located along wide access trails (3.7 m) and insignificant on plots located along the narrow access trial (2.5m). The intertree distance was not found to be significant. The calculated net machine costs for the forwarding set and mini-harvester were 36.12 Euro∙PMH 1 and 52.47 Euro∙PMH-1, respectively. An increase in the utilization rate of the harvesting set to 80% would reduce the timber harvesting and skidding costs to 22.07 Euro∙m-3.

Recent developments in mid-infrared (MIR) spectroscopic ellipsometry enabled by quantum cascade lasers (QCLs) resulted in a drastic improvement in signal-to-noise ratio compared to conventional thermal emitter based instrumentation. Thus, it was possible to reduce the acquisition time for high-resolution broadband ellipsometric spectra from multiple hours to less than 1 second. This opens up new possibilities for real-time in-situ ellipsometry in polymer processing. To highlight these evolving capabilities we demonstrate the benefits of a QCL based MIR ellipsometer by investigating single and multilayered polymer films. The molecular structure and reorientation of a 2.5m thin biaxially oriented polyethylene terephtalate film is monitored during a stretching process lasting 24.5 s to illustrate the perspective of ellipsometric measurements in dynamic processes. In addition, a polyethylene/ethylene vinyl alcohol/polyethylene multilayer film is investigated at continuously varying angle of incidence ( 0∘ – 50∘) in 17.2 s, highlighting an unprecedented sample throughput for the technique of varying angle spectroscopic ellipsometry in the MIR spectral range. The obtained results underline the superior spectral and temporal resolution of QCL ellipsometry and qualify this technique as suitable method for advanced in-situ monitoring in polymer processing.

Background: Australia’s healthcare system is complex and fragmented which can create challenges in healthcare, particularly in rural and remote areas. Aboriginal people experience inequalities in healthcare treatment and outcomes. This study aimed to investigate barriers and enablers to accessing healthcare services for Aboriginal people living in rural and remote Australia. Methods: Semi-structured interviews were conducted with healthcare delivery staff and stakeholders recruited through snowball sampling. The communities were selected for their high proportion of Aboriginal people and geographical representation (coastal, rural, and border). Thematic analysis identified barriers and enablers. Results: Thirty-one interviews were conducted (n =5 coastal, n=13 remote, and n=13 border) and six themes identified: 1) Improved coordination of healthcare services; 2) Better communication between services and patients; 3) Trust in services and cultural safety; 4) Importance of prioritizing health services by Aboriginal people; 5) Importance of reliable, affordable and sustainable services; 6) Distance and transport availability. These themes were often present as both barriers and enablers to healthcare access for Aboriginal people. They were also present across the healthcare system and within all three communities. Conclusions: This study describes a pathway to better healthcare outcomes for Aboriginal Australians by providing insights into ways to improve access.

The notion of the three-phase (line) tension remains one of the most disputable notions in the surface science. A very broad range of its values has been reported. Experts even do not agree on the sign of the line tension. The polymer-chain-like model of the three-phase (triple) line enables the rough estimation of the entropic input into the value of the line tension, estimated as Γ_en≅(k_B T)/d_m ≅〖10〗^(-11) N, where d_m is the diameter of the liquid molecule. The introducing of the polymer-chain-like model of the triple line is justified by the “water string” model of the liquid state, predicting strong orientation effects for liquid molecules located in the vicinity of hydrophobic moieties. The estimated value of the entropic input into the line tension is close to experimental findings, reported by various groups.