Miracle-dz/UniFAR-FTUs huggingface dataset:
Functionalization of chitosan polymer and their applications

Abstract The deacetylated derivative of chitin i.e. chitosan is an advantageous and interesting bioactive polymer. Despite its biodegradability, it consists of many reactive primary and secondary hydroxyl (–OH) and amino (–NH2) functional groups which allow the possibilities of chemical modifications. The several chemical modifications such as alkylation, acylation, quaternization, phthaloylation, sulfation, thiolation, carboxymethylation, graft copolymerization etc. carried out. The chemical modification results various types of derivatives with modified properties for specific applications in varied area mainly of pharmaceutical, biomedical, biotechnological, cosmetic, agricultural, food and non-food industries as well as in water treatment, paper, and textile industry. The ability of chitosan to undergo versatile modifications and applications presents a great opportunity to scientific community and to industry. GRAPHICAL ABSTRACT
Sensor for high-air-humidity measurement

The humidity sensor using the sensitive capacitive-dependent crystal is described. Presented is the probe sensitivity (dependence of df on the dCx). In addition the new idea of excitation of the entire humidity sensor with stochastic test signals is described, and the humidity surface-measuring method is given. It includes the influence of test signals of the weighting function uncertainty and of the A/D-D/A conversion. The results of humidity measurement with the excitation signals are shown experimentally. The uncertainty of the surface humidity measurement is less than 0.2% (T=15 to 25/spl deg/C and humidity=50 to 98%).
An Influence Maximization Algorithm Based on Community-Topic Features for Dynamic Social Networks

Real social networks are huge and continueto expand rapidly. Most existing dynamic influence maximization (IM) algorithms are based on the node-to-node propagation model; hence, they have high time complexity and large storage space consumption. They usually reduce computational complexity using a sampling method while sacrificing the influence spread. In this paper, we propose a topic-aware community independent cascade (IC) model to reduce the complexity of dynamic IM without losing accuracy. The proposed model reduces the problem domain through community-level propagation, and then enhances the global features by integrating community structural features, community topic features, and time information into an IC model. We construct the data structure of the dynamic community index to avoid recalculation when the network grows. Based on the dynamic community index, we design a dynamic IM algorithm to quickly approximate the solution with the $(1-\frac{1}{e})$-approximation guarantee. The experimental results on real social networks demonstrated that, compared with existing IM algorithms, the proposed algorithm had better stability and dynamic adaptability, higher computational efficiency, and less space consumption without reducing the approximation ratio and influence spread.
Genetic admixture patterns in Argentinian Patagonia

As for other Latin American populations, Argentinians are the result of the admixture amongst different continental groups, mainly from America and Europe, and to a lesser extent from Sub-Saharan Africa. However, it is known that the admixture processes did not occur homogeneously throughout the country. Therefore, considering the importance for anthropological, medical and forensic researches, this study aimed to investigate the population genetic structure of the Argentinian Patagonia, through the analysis of 46 ancestry informative markers, in 433 individuals from five different localities. Overall, in the Patagonian sample, the average individual ancestry was estimated as 35.8% Native American (95% CI: 32.2-39.4%), 62.1% European (58.5-65.7%) and 2.1% African (1.7-2.4%). Comparing the five localities studied, statistically significant differences were observed for the Native American and European contributions, but not for the African ancestry. The admixture results combined with the genealogical information revealed intra-regional variations that are consistent with the different geographic origin of the participants and their ancestors. As expected, a high European ancestry was observed for donors with four grandparents born in Europe (96.8%) or in the Central region of Argentina (85%). In contrast, the Native American ancestry increased when the four grandparents were born in the North (71%) or in the South (61.9%) regions of the country, or even in Chile (60.5%). In summary, our results showed that differences on continental ancestry contribution have different origins in each region in Patagonia, and even in each locality, highlighting the importance of knowing the origin of the participants and their ancestors for the correct interpretation and contextualization of the genetic information.
Development of a dye with broadband absorbance in visible spectrum for an efficient dye-sensitized solar cell

A blended dye composed of five organic dyes, namely, Rose Bengal, Eosin-Y, Rhodamine-B, Fast Green, and Acridine Orange, was developed and tested for various solar cell parameters of ZnO based dye-sensitized solar cell (DSSC). A comparison of the absorption spectra of dyes adsorbed on ZnO electrode revealed that the blended dye efficiently absorbs light in the entire visible region as compared with the individual dye. Six DSSCs were fabricated using the five individual dyes and one developed blended dye. The photovoltaic performance of the cells was examined by determining the various parameters such as open-circuit voltage, short-circuit current, energy conversion efficiency, fill factor, series resistance, and shunt resistance. Incident photon to current conversion efficiency was also measured to correlate the effect of the blended dye on the significant improvement of the solar cell parameters. The sensitization of ZnO electrode with blended dye has resulted in a maximum energy conversion efficiency of.
Trajectory Planning and Realizing of an Exoskeleton Device for Hand Rehabilitation Based on sEMG Control

This paper presents a novel exoskeleton training system for hand rehabilitation with the surface electromyography signals (sEMG) feedback to meet the kinematics characteristics of finger joints. In this system, the sEMG is obtained by means of the surface electrodes loaded the forearm antagonistic muscle. The sEMG is amplified about 100 times again after it was preliminarily amplified about 200 times and filter,. Through threshold and the equivalent calculation, the control signal was input into the driving circuit of DC micro motor to control the hand Exoskeleton. The experimental results show that the processed sEMG can drive the hand exoskeleton for rehabilitation training, and the bending angular of joints agree well with bionics laws. The results possess guideline value for bionics motion control of hand rehabilitation with function damage.
Antenna integration with a waveguide photodetector for high capacity wireless communications

This paper proposes the integration of an antenna with a photodetector for high capacity wireless communications. A waveguide photodetector (WGPD), illuminated on the side, is used to convert the RF‐modulated optical power into a microwave signal. That microwave signal is used to feed an antenna built on the same plane as the photodetector. The WGPD is a standard p‐i‐n device grown on a semi‐insulating InP. The performance of this RF/photonic antenna in the frequency range 17–20 GHz is studied theoretically and experimentally. An equivalent circuit model for the WGPD is developed to predict the photodetector impedance as a function of frequency. The photodetector is matched to the input impedance of the antenna. The agreement between measurement and the circuit model results for the WGPD impedance is very good. It is envisioned that a large number of such RF/Photonic antenna elements could be networked together into a star configuration, feeding in and out of a radio hub. © 2002 Wiley Periodicals, Inc. Microwave Opt Technol Lett 35: 179–184, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.10550
From compliance to control: off-roadmap metrology for low-k1 lithography

The need for high-resolution metrology to verify lithography compliance with shrinking CD and overlay specifications has resulted in a variety of roadmap sanctioned approaches; notably, SEM, AFM and scatterometry. The application of optical microscopy has been relegated to overlay metrology. While high-resolution metrology is essential to the setup and qualification of lithographic processes, it is often ill suited to the demands of dynamic lithography control. The path to improved CD compliance is through improved on- produce dose and focus control. In control applications, enhanced sensitivity to what we are trying to control becomes a new handle on precision-to-tolerance. Sensitivity must be accompanied by ease of setup, speed and sampling. Modeling for correctable components of variation becomes an integral part of the metrology function. We show that the old dog optical microscopy can learn new tricks to encompass the control of dose and focus. In doing so it becomes the lead candidate for an integrated metrology solution.
Experimental thermal and hydraulic study of super hydrophobic wavy mini channel heat sink using aqueous nanofluids

Abstract Super hydrophobic wavy mini channel heat sink is analyzed experimentally for thermal and hydraulic analysis using SiO2 and TiO2 aqueous nanofluids with volumetric concentration of 0.01% and 0.02%. The test rig is validated by comparing the data obtained for water (distilled) using simple wavy mini channel heat sink (without super hydrophobic coating) with the theoretical model of Peng and Peterson. Three cartridge heaters were used to supply uniform heat flux to the base of mini channel heat sink. Results were obtained at steady state in laminar regime of flow at Reynolds number ranging from 400 to 1230. Data were acquired at heating powers of 40, 55, and 70 W. Augmentation of 31.37% in heat transfer was recorded for super hydrophobic mini channel heat sink as compared to conventional heat sink with a reduction of 39.02% in pressure drop. The results can be summarized as enhancement of heat transfer with a noticeable diminution in pressure drop and hence reduced power consumption.
Regenerative Effects of CDP-Choline: A Dose-Dependent Study in the Toxic Cuprizone Model of De- and Remyelination

Inflammatory attacks and demyelination in the central nervous system (CNS) are the key factors responsible for the damage of neurons in multiple sclerosis (MS). Remyelination is the natural regenerating process after demyelination that also provides neuroprotection but is often incomplete or fails in MS. Currently available therapeutics are affecting the immune system, but there is no substance that might enhance remyelination. Cytidine-S-diphosphate choline (CDP-choline), a precursor of the biomembrane component phospholipid phosphatidylcholine was shown to improve remyelination in two animal models of demyelination. However, the doses used in previous animal studies were high (500 mg/kg), and it is not clear if lower doses, which could be applied in human trials, might exert the same beneficial effect on remyelination. The aim of this study was to confirm previous results and to determine the potential regenerative effects of lower doses of CDP-choline (100 and 50 mg/kg). The effects of CDP-choline were investigated in the toxic cuprizone-induced mouse model of de- and remyelination. We found that even low doses of CDP-choline effectively enhanced early remyelination. The beneficial effects on myelin regeneration were accompanied by higher numbers of oligodendrocytes. In conclusion, CDP-choline could become a promising regenerative substance for patients with multiple sclerosis and should be tested in a clinical trial.
Robust Approach for Concurrent Aircraft Design and Airline Network Design

Conceptual aircraft design directly impacts the structure of an airline’s route network and ability to service demand for various ticket itineraries between origin and destination city pairs. The decisions made in allocating new aircraft to serve predicted future demand of various ticket itineraries affects an airline’s risk and profit potential. Therefore, choices on the selection of target market travel itineraries to be served and design requirements of new, yet-to-be-introduced aircraft directly govern the tradeoff of risk against potential profit. This paper presents a concurrent engineering strategy for an airline that wishes to investigate the impact that aircraft design choices and target market capture decisions have on tradeoffs between expected profit and risk in serving particular demand itineraries. The approach considers the integrated domains of aircraft design, airline operations, and passenger demand within the context of a mathematical programming problem. More specifically, innovations .
New Physical Hydrogels Based on Co-Assembling of FMOC–Amino Acids

In the last years, physical hydrogels have been widely studied due to the characteristics of these structures, respectively the non-covalent interactions and the absence of other necessary components for the cross-linking processes. Low molecular weight gelators are a class of small molecules which form higher ordered structures through hydrogen bonding and π–π interactions. In this context it is known that the formation of hydrogels based on FMOC–amino acids is determined by the primary structures of amino acids and the secondary structure arrangement (alpha–helix or beta–sheet motifs). The present study aimed to obtain supramolecular gels through co-assembly phenomenon using FMOC–amino acids as low molecular weight gelators. The stability of the new structures was evaluated by the vial inversion test, while FTIR spectra put into evidence the interaction between the compounds. The gel-like structure is evidenced by viscoelastic parameters in oscillatory shear conditions. SEM microscopy was used to obtain the visual insight into the morphology of the physical hydrogel network while DLS measurements highlighted the sol-gel transition. The molecular arrangement of gels was determined by circular dichroism, fluorescence and UV-Vis spectroscopy.
Aerodynamic Drag Prediction of Helicopter Fuselage

is investigated for one test case using different computational grids. The results are compared with wind-tunnel measurements and show good agreement with the reference data when the ine uence of the wind-tunnel strut is taken into account. Thecomputational e uid dynamics model developed consists ofa parallel multiblock, multigrid Reynolds-averaged Navier ‐Stokes codeand a three-dimensionalhyperbolic grid generator. Block-structured grids are generated from a CAD base. From a numerical point of view, convergence was achieved quickly in all of the cases computed, thus showing efe ciency and low CPU cost.
Strengthening, Retrofitting and Upgrading of Timber Structures with High-Strength Fibres

Around 1990, a project was launched to investigate the possibilities of fabricating efficient wooden joints reinforced with high-strength fibres (HSF). The main considerations of the work were strength, stiffness and practical feasibility. Extensive experimental work was required to optimise the quality of the polymer and of the resulting bond, as well as the flow of forces within the joints for various arrangements of the splice plates. The results have subsequently been applied during reinforcement of existing timber structures. Practical recommendations are given for the execution of such work.
Bayesian approach to proof loading of quasi-identical multi-components structural systems

The present article considers a special class of structural systems for which condition control has proven to constitute a real problem, namely attachments such as e.g., fasteners of façade systems, anchors of retaining walls, rivets in riveted connections, riser attachments of offshore platforms, and many other similar types of structures. Such structural systems are comprised of a large number of quasi-identical components under relatively homogeneous conditions for what concerns both resistances and loads. The problem of condition control is addressed in the context of Bayesian reliability updating; utilizing proof-load tests of a few individual components for the purpose of gaining knowledge about all components. The optimization of proof-load test strategies in regard to the number of components to be tested and the load intensity to be applied is discussed. Two examples are given to illustrate the use and the benefits of the proposed methodology.
Gaudí and Reinforced Concrete in Construction

The first two decades of the 20th century witnessed the introduction and expansion of reinforced concrete as a building material in Spain. Few years passed between the introduction of the first patents in the most industrialized areas of the Iberian Peninsula and the subsequent generalization of the technique through scientific knowledge obtained in universities. This period coincides almost completely with the professional career of Antoni Gaudi, one of the most famous Catalan architects. This study reports that Gaudi had contact with this new material and discusses the transition he made from the traditional construction methods to the use of reinforced concrete in his later works. Placing the starting point in the relationship between Antonio Gaudi and the industrialists who built the first cement factories in Catalonia (especially Eusebi Guell), the research on the patents to which he had access are presented and the characteristics of his works with reinforced structures and materials are described.
Computer Simulations of Galvanic Corrosion Behaviour of Zinc –Aluminium Based Composites Reinforced with Red Mud by Potentiodynamic Polarization Techniques Leading to Corrosion Control

The present investigation aims to evaluate the corrosion control properties of metal matrix composites in comparison with matrix alloy using different concentration of Sodium chloride solutions and potentiodynamic polarization techniques. Matrix alloy used in ZA-27 and the reinforcement used was red mud particulates of size 50-80 microns. Composites are prepared by liquid melt metallurgy technique using vortex method. Red mud particulates reinforced varying from two to six percent by weight in steps of two percent under dry conditions. Specimens are prepared according to ASTM standards. Both composites and corresponding base alloys were subjected to identical test conditions to understand the influence of the reinforcement on alloy corrosion behaviour and effective corrosion control. Composites became less prone to corrosion and pit formation than the matrix alloy, which may be due to chemically inert red mud particles present in the metal matrix composites. On the other hand the test also reveals that corrosion resistance of both alloy and composites in crease with increase in normality of the sodium chloride solution, which may be due to increasing concentration of hydrogen ions in the solution. Corrosion of alloys can be effectively controlled by converting them in to composites by the addition of inert materials like silica particulates. If any automobile parts like bearing are made using these composites corrosion control properties can be tailored so that they can be used effectively in wide area of application.
ANALYSIS AND DESIGN OF RPM AND OTHER COMPOSITE UNDERGROUND PIPELINES

Glass‐fiber‐reinforced plastic mortal' pipes had been in use for pressure and nonpressure underground applications since 1965. Although this material had been used on many projects, the loads imposed on these piplines had not been well understood by most design engineers and manufacturers. In addition, the individual laminate behavior of the composite pipe wall was never modeled in any of the calculations performed by the manufacturers. Also, the effects of soil‐pipe interaction were never properly addressed in the design procedures used. These practices had led to numerous premature failures of reinforced plastic mortar (RPM) pipelines in the United States and other countries and as a consequence, this product disappeared from the market in 1984. In an attempt to inform the design engineers who might be considering similar underground pipeline projects, the loadings applied on these pipelines are reviewed in this paper. A new design procedure was developed based on a composite pipe‐soil interaction finit.
Automatic Classification of Wheat Rust Diseases Using Deep Convolutional Neural Networks

Wheat is the staple food for Indians and it is one of the most common grain crops all over the world. The wheat diseases cause a huge amount of yield losses. The wheat yield losses are due to fungi, bacterial and insect-based diseases. Due to fungal diseases, yield loss has a great effect on wheat grain. Based on the type of fungus, the fungal diseases are categorized into four types namely as rust, leaf spot, spike infection, and virus-based diseases. Hence, these rust diseases affect the whole wheat plant and lead to very heavy yield quality loss. To overcome these quality yield issues, a deep learning-based approach known as a deep convolutional neural network (DCNN) is proposed which can easily classify the wheat rust diseases automatically without human investigation. Additionally, this DCNN training and testing process produces wheat rust diseases determination and high classification results. A total of 1486 wheat plant images have been accessed through the CGIAR dataset and 514 wheat stem rust images have been collected from secondary sources. A total of 2000 wheat plant images have been used for training and testing purposes in DCNN. During training, a stochastic gradient descent method achieves high classification results. Therefore, our proposed approach achieves high classification accuracy of 97.16% for wheat rust diseases.
Hierarchical generative modelling for autonomous robots

Humans can produce complex movements when interacting with their surroundings. This relies on the planning of various movements and subsequent execution. In this paper, we investigated this fundamental aspect of motor control in the setting of autonomous robotic operations. We consider hierarchical generative modelling—for autonomous task completion—that mimics the deep temporal architecture of human motor control. Here, temporal depth refers to the nested time scales at which successive levels of a forward or generative model unfold: for example, the apprehension and delivery of an object requires both a global plan that contextualises the fast coordination of multiple local limb movements. This separation of temporal scales can also be motivated from a robotics and control perspective. Specifically, to ensure versatile sensorimotor control, it is necessary to hierarchically structure high-level planning and low-level motor control of individual limbs. We use numerical experiments to establish the efficacy of this formulation and demonstrate how a humanoid robot can autonomously solve a complex task requiring locomotion, manipulation, and grasping, using a hierarchical generative model. In particular, the humanoid robot can retrieve and deliver a box, open and walk through a door to reach the final destination. Our approach, and experiments, illustrate the effectiveness of using human-inspired motor control algorithms, which provide a scalable hierarchical architecture for autonomous performance of complex goal-directed tasks.