Miracle-dz/UniFAR-FTUs huggingface dataset:
Is There a Negative Thermal Expansion in Supported Metal Nanoparticles? An in Situ X-ray Absorption Study Coupled with Neural Network Analysis

Interactions with their support, adsorbates, and unique structural motifs are responsible for many intriguing properties and potential applications of supported metal nanoparticles (NPs). At the same time, they complicate the interpretation of experimental data. In fact, the methods and approaches that work well for the ex situ analysis of bulk materials may be inaccurate or introduce artifacts in the in situ analysis of nanomaterials. Here, we revisit the controversial topic of negative thermal expansion and anomalies in the Debye temperature reported for oxide-supported metal NPs. In situ X-ray absorption experimental data collected for Pt NPs in ultrahigh vacuum and an advanced data analysis approach based on an artificial neural network demonstrate that Pt NPs do not exhibit intrinsic negative thermal expansion. Similarly, as for bulk materials, in the absence of adsorbates and strong particle-support interaction, the bond lengths in metal NPs increase with temperature. The previously reported anomali.
A Survey of Low Voltage and Low Power Amplifier Topologies

Reducing voltage supply is one of the most effective way to reduce the power consumption, but, on the other hand it is a challenging choice for the analog designers. In this paper, different topologies, well-suited for low voltage and ultra-low voltage supply, are depicted, investigated, designed in the same standard 180 nm technology and compared, highlighting the benefits and the possible applications.
Cost-sensitive design of error correcting output codes

Many real world applications involve multiclass cost-sensitive learning problems. However, some well-worked binary cost-sensitive learning algorithms cannot be extended into multiclass cost-sensitive learning directly. It is meaningful to decompose the complex multiclass cost-sensitive classification problem into a series of binary cost-sensitive classification problems. So, in this paper we propose an alternative and efficient decomposition framework, using the original error correcting output codes. The main problem in our framework is how to evaluate the binary costs for each binary cost-sensitive base classifier. To solve this problem, we proposed to compute the expected misclassification costs starting from the given multiclass cost matrix. Furthermore, the general formulations to compute the binary costs are given. Experimental results on several synthetic and UCI datasets show that our method can obtain comparable performance in comparison with the state-of-the-art methods.
Cytidine and ribothymidine nucleolipids synthesis, organogelation, and selective anion and metal ion responsiveness

Nucleolipids of 2′,3′-O-diacylatedribothymidine supports the organogelation by utilizing inherent self-base pairing and solvent mediated bifurcated H-bonding and hydrophobic effect. These organogels exhibits unusual Hg2+ mediated base pairing.
An Investigation of the Consciousness Energy Healing Therapy on Physicochemical and Thermal Properties of Silver Sulfadiazine

Silver sulfadiazine is a topical sulfa drug antibiotic that is used by burn patients to prevent the bacterial infection. This study was aimed to analyze the impact of the Trivedi Effect® on the physicochemical and thermal properties of silver sulfadiazine with the help of various analytical techniques. The silver sulfadiazine sample was divided into the control and treated parts; where, no Biofield Treatment was provided to the control part, while the treated part received the Biofield Treatment remotely by a renowned Biofield Energy Healer, Dahryn Trivedi. The PXRD peak intensities and the crystallite sizes were significantly altered ranging from -75.25% to 31.21% and -8.80% to 192.76% respectively, along with 64.06% increase in the average crystallite size of the treated sample than the control sample. The particle sizes were decreased by 1.60% (d10), 2.30% (d50), 2.06% (d90), and 4.40% [D (4,3)]; therefore, the surface area was increased by 2.61% in the treated sample in contrast to the control sample. The latent heat of fusion and decomposition of the treated sample were significantly altered by -21.52% and 32.03%, respectively, compared to the control sample. Additionally, the total weight loss was reduced by 1.86%; however, the residue amount was increased by 2.88% in the treated sample compared with the control sample. Hence, the Biofield Treatment might be considered as a novel approach to generate a new polymorph of silver sulfadiazine that is more soluble, bioavailable, and thermally stable, which could be useful in designing a novel pharmaceutical formulation for better therapeutic response against various type of bacterial disease.
Thermophiles from Deep Subsurface Waters

Thermophiles dominate deep subsurface aquifers and represent the most ancient life on the planet. In this project, the culturable diversity of thermophiles that inhabit the world’s largest freshwater geothermal aquifer, Australia’s Great Artesian Basin (GAB), were explored using culture-dependent techniques. These studies largely focused on four unique microbial mat communities that exist in the runoff channel of the New Lorne Bore (registered number 17263) at temperatures between 52 – 72 °C and mostly targeted the cultivation of iron(III)- reducing bacteria due to their considerable influence on subsurface processes and likely involvement in the corrosion of GAB bores and pipelines. During this project a number of novel and modified screening methods were developed including high-throughput microenrichments of thermophiles using Biolog (Biolog Inc., U.S.A.) and U-bottom deep-well (1 ml) microtiter plates (Sarstedt, Germany) amended with seldom tested energy substrates and varied terminal electron acceptors (TEA) such as iron(III), sulphate, vanadium(V) and molybdenum(VI). Phylogenetic analyses of the isolates recovered in this project detected more than 15 novel phylotypes thereby extending the known culturable diversity of the GAB microflora. Complete phenotypic characterisations were performed on 9 GAB thermoanaerobic isolates, which resulted in the descriptions of 8 novel organisms including 4 novel genera: Thermotalea metallivorans (Ogg & Patel, 2009b), Fervidicola ferrireducens (Ogg & Patel, 2009c), Sporolituus thermophilus (Ogg & Patel, 2009d) and Fervidicella metallireducens (Ogg & Patel, 2010); and 4 novel species: Caloramator australicus (Ogg & Patel, 2009a), Caloramator mitchellensis (Ogg & Patel, 2011a), Thermovenabulum gondwanense (Ogg et al., 2010), and Desulfotomaculum varum (Ogg & Patel, 2011c); and amendments to the genus Caloramator (Ogg & Patel, 2011a) [given in Appendices 1 – 8]. Included in these characterisation studies was a modified method for determining an organisms mol % of G + C content of DNA using TempliPhi (Amersham Biosciences, U.K.) genome amplification kits to prepare the high molecular weight (HMW) genomic DNA prior to thermal denaturation. When the phenotypic data resulting from the strain characterisations was combined with the enrichment results, a complex model of the microbial oxidation of organic matter in the GAB at elevated temperatures (50 – 70 °C) was constructed.
Nuclear and chemical characterization of heavy actinides

Abstract Recent progress in the production of heavy nuclei far from stability and in the studies of nuclear and chemical properties of heavy actinides is briefly reviewed. Exotic nuclear decay properties including nuclear fission of heavy nuclei, measurements of first ionization potentials of heavy actinides, and redox studies of heavy actinides are described. Brief history of discovery of the transuranium elements is also presented.
Preparation and Evaluation of Zwitterionic Polymer Coated Capillary Columns for Analysis of Proteins by Capillary Electrophoresis

Abstract The ability to manipulate and control the inner surface properties of silica capillary is of crucial importance for analysis of proteins by capillary electrophoresis. In this work, surface-initiated atom transfers radical polymerization (ATRP) of zwitterionic 3-dimethyl(methacryloyloxyethyl) ammonium propane sulfonate (DMAPS) is employed to tailor the functionality of silica capillary in a well-controlled manner. The structure of the coating and the protein separation performance were investigated. The results confirmed that the P(DMAPS) grafting can substantially enhance the performance of the capillary columns. With the versatility of surface-initiated ATRP and the excellent performance of zwitterionic polymer chains, the zwitterionic polymer coated capillary columns can be readily tailored for analysis of proteins by capillary electrophoresis.
Path Planning Aware of Robot’s Center of Mass for Steep Slope Vineyards

Summary Steep slope vineyards are a complex scenario for the development of ground robots. Planning a safe robot trajectory is one of the biggest challenges in this scenario, characterized by irregular surfaces and strong slopes (more than 35°). Moving the robot through a pile of stones, spots with high slope or/and with wrong robot yaw may result in an abrupt fall of the robot, damaging the equipment and centenary vines, and sometimes imposing injuries to humans. This paper presents a novel approach for path planning aware of center of mass of the robot for application in sloppy terrains. Agricultural robotic path planning (AgRobPP) is a framework that considers the A* algorithm by expanding inner functions to deal with three main inputs: multi-layer occupation grid map, altitude map and robot’s center of mass. This multi-layer grid map is updated by obstacles taking into account the terrain slope and maximum robot posture. AgRobPP is also extended with algorithms for local trajectory replanning during the execution of a trajectory that is blocked by the presence of an obstacle, always assuring the safety of the re-planned path. AgRobPP has a novel PointCloud translator algorithm called PointCloud to grid map and digital elevation model (PC2GD), which extracts the occupation grid map and digital elevation model from a PointCloud. This can be used in AgRobPP core algorithms and farm management intelligent systems as well. AgRobPP algorithms demonstrate a great performance with the real data acquired from AgRob V16, a robotic platform developed for autonomous navigation in steep slope vineyards.
Robust Sensor Fault Reconstruction via a Bank of Second-Order Sliding Mode Observers for Aircraft Engines

This paper deals with sensor faults of aircraft engines under uncertainties using a bank of second-order sliding mode observers (SMOs). In view of the effect of inevitable uncertainties on the fault reconstruction, a method combining H ∞ concepts and linear matrix inequalities (LMIs) is proposed, in which a scaling matrix is designed to minimize the gain of the transfer function matrix from uncertainty to reconstruction. However, robust design generally requires that engine outputs outnumber faults. In the case where the above-mentioned requirement is not satisfied, a bank of sliding mode observers is proposed to ensure the degrees of freedom available in robust design. In specific, each observer corresponds to a certain sensor with the hypothesis that the corresponding sensor will not have faults, to create one degree of design freedom for each observer. After fault occurrence, a large estimation error is expected in the observers with wrong hypothesis, and then a logic module is designed to detect sensor faults and obtain the optimal robust sensor fault reconstruction at the same time. The proposed approach is applied to a nonlinear engine component-level-model (CLM) simulation platform, and a numerical study is performed to validate the effectiveness.
An Intelligent Event-Sentiment-Based Daily Foreign Exchange Rate Forecasting System

Financial time series analysis is an important research area that can predict various economic indicators such as the foreign currency exchange rate. In this paper, a deep-learning-based model is proposed to forecast the foreign exchange rate. Since the currency market is volatile and susceptible to ongoing social and political events, the proposed model incorporates event sentiments to accurately predict the exchange rate. Moreover, as the currency market is heavily dependent upon highly volatile factors such as gold and crude oil prices, we considered these sensitive factors for exchange rate forecasting. The validity of the model is tested over three currency exchange rates, which are Pak Rupee to US dollar (PKR/USD), British pound sterling to US dollar (GBP/USD), and Hong Kong Dollar to US dollar (HKD/USD). The study also shows the importance of incorporating investor sentiment of local and foreign macro-level events for accurate forecasting of the exchange rate. We processed approximately 5.9 million tweets to extract major events’ sentiment. The results show that this deep-learning-based model is a better predictor of foreign currency exchange rate in comparison with statistical techniques normally employed for prediction. The results present evidence that the exchange rate of all the three countries is more exposed to events happening in the US.
A Computationally Efficient Finite Element Pedestrian Model for Head Safety: Development and Validation

Head injuries are often fatal or of sufficient severity to pedestrians in vehicle crashes. Finite element (FE) simulation provides an effective approach to understand pedestrian head injury mechanisms in vehicle crashes. However, studies of pedestrian head safety considering full human body response and a broad range of impact scenarios are still scarce due to the long computing time of the current FE human body models in expensive simulations. Therefore, the purpose of this study is to develop and validate a computationally efficient FE pedestrian model for future studies of pedestrian head safety. Firstly, a FE pedestrian model with a relatively small number of elements (432,694 elements) was developed in the current study. This pedestrian model was then validated at both segment and full body levels against cadaver test data. The simulation results suggest that the responses of the knee, pelvis, thorax, and shoulder in the pedestrian model are generally within the boundaries of cadaver test corridors under lateral impact loading. The upper body (head, T1, and T8) trajectories show good agreements with the cadaver data in vehicle-to-pedestrian impact configuration. Overall, the FE pedestrian model developed in the current study could be useful as a valuable tool for a pedestrian head safety study.
Theoretical and computational studies on nanofriction: A review

The subject of nanofriction having its origins in the late 19th century has slowly but surely started picking up lately. With rapid advancements in science and technology throughout the last century, understanding nanofriction has been gaining prominence. In this context, and in the current 21st century of nanotechnology, it is expected that nanofriction will play a predominant role, as we try moving forward to solve the most pressing medical and biological problems with the usage of nanobots. It is important to understand the challenges we have to encounter in order to solve these problems for the benefit of the human race. The availability of high speed computers and smart algorithms has made it possible to investigate the problems (as outlined above and many more) without compromising on the complexities involved. The focus of the present review is to bring together major theoretical/mathematical models and computational approaches to study friction at nanoscale. The role of adhesion in the estimation of force of friction at nanoscale has also been clearly outlined. A critical discussion on the significance of single and multiple asperity models towards estimating friction at nanoscale has also been provided. At the end, a short description on scanning probe microscopy in estimating nanofriction has been provided for the completeness of the review.
Mechanical design and testing of the MOMA flight model laser head for the EXOMARS 2020 mission

A hermetically sealed laser head (LH) emitting laser pulses at a wavelength of 266 nm has been developed and tested for the Mars Organic Molecule Analyzer (MOMA) instrument of the ESA/Roscosmos ExoMars 2020 mission. MOMA comprises a gas chromatograph (GC) and a laser desorption mass spectrometer (LDMS). Its primary function is to search for traces of present or past signs of organic molecules in subsurface material probes. The LH is used as an excitation source for the LDMS part of MOMA. Its design fulfils stringent mass and volume requirements and is realized as a hermetically sealed system. It consists of a laser diode pumped Nd:YAG based laser oscillator, a frequency conversion stage for frequency quadrupling of the fundamental laser oscillator wavelength, a compact monitoring stage for internal laser pulse detection, a beam shaping telescope and an adjustable laser beam steering unit with the purpose of guiding the generated UV laser beam to its target position in front of the mass spectrometer (MS) ion inlet. The system has undergone extensive functional and environmental testing including vibration, shock and thermal vacuum chamber tests. After completion of the functional and environmental test campaign, the LH has been integrated on the MOMA mass spectrometer. Here we report on the mechanical design of this LH and its environmental testing. Furthermore, the LH was successfully tested both functionally and environmentally on LDMS level.
A 124 fJ/Bit Cascode Current Mirror Array Based PUF With 1.50% Native Unstable Bit Ratio

In this paper, we present a novel physical unclonable function (PUF) design based on cascode current mirror array. By using a single-stage cascode amplifier for each PUF cell, the output impedance can be significantly elevated. Compared with a traditional single-stage amplifier-based current-mode PUF, the proposed structure is capable of generating more polarized voltage value for the output node. With an additional digital buffer, the temporal noise can be well-suppressed, and a rail-to-rail digital output can be provided with high native reliability. Moreover, through operating the transistors at the subthreshold region, the overall power consumption can be dramatically reduced. Featuring a compact footprint of $3.23~\mu \text{m}^{2}$ (i.e. 764 ${F}^{2}$ ) for each PUF cell, the proposed PUF implementation is validated using 65-nm standard CMOS process. The excellent randomness of the proposed PUF design is verified based on the test results with widely-accepted auto-correlation function and NIST suites. Meanwhile, the PUF’s uniqueness is measured with 10 chip prototypes and reported to be 49.94%. In addition, the fabricated PUF chips were also characterized with various environmental influences. With multiple readout (500 times) under the reference operating temperature of 27 °C and supply voltage of 1.2 V, the native unstable bit ratio is measured to be as low as 1.50%, which can be further improved to 0.79% by adopting the mainstream temporal majority voting (TMV)-based error correction scheme. Besides, we also evaluate the fabricated PUF chips’ reliability under varied operating temperature from −40 °C to 120 °C and supply voltage from 0.95 to 1.3 V. The averaged bit error rate (BER) per 10 °C and BER per 0.1 V are measured to be 0.86% and 1.02%, respectively. Compared with the state-of-the-art implementations, the reliability figure of merit (RFoM) is improved by $1.16\sim 4.29\times $ , with the influences of the temporal noise, the temperature/supply voltage variations and their ranges comprehensively considered.
A survey on data-driven process monitoring and diagnostic methods for variation reduction in multi-station assembly systems

PurposeDriven by the development in sensing techniques and information and communications technology, and their applications in the manufacturing system, data-driven quality control methods play an essential role in the quality improvement of assembly products. This paper aims to review the development of data-driven modeling methods for process monitoring and fault diagnosis in multi-station assembly systems. Furthermore, the authors discuss the applications of the methods proposed and present suggestions for future studies in data mining for quality control in product assembly.Design/methodology/approachThis paper provides an outline of data-driven process monitoring and fault diagnosis methods for reduction in variation. The development of statistical process monitoring techniques and diagnosis methods, such as pattern matching, estimation-based analysis and artificial intelligence-based diagnostics, is introduced.FindingsA classification structure for data-driven process control techniques and the limitations of their applications in multi-station assembly processes are discussed. From the perspective of the engineering requirements of real, dynamic, nonlinear and uncertain assembly systems, future trends in sensing system location, data mining and data fusion techniques for variation reduction are suggested.Originality/valueThis paper reveals the development of process monitoring and fault diagnosis techniques, and their applications in variation reduction in multi-station assembly.
Eye-Sat: A 3U Student CubeSat from CNES Packed with Technology

Eye-Sat will observe the Zodiacal light, the Sun light scattered by interplanetary dust. It is a diffuse and faint white glow. Equipped with its small home-made telescope, this 3U CubeSat will measure the zodiacal light’s intensity and linear polarization ratio. The payload’s optics has a focal length of 50 mm and a diameter of 25 mm for a field of view of +/6.5°. Two rotating wheels bear spectral and polarizing filters. For one year Eye-Sat will produce more than 500 GB of data which will be downloaded to the ground thanks to a high data rate X-band link. Moreover, scientific objectives impose severe requirements on the attitude determination and control system such as a 0.25° 3axis pointing accuracy. To fulfil these requirements, Eye-Sat comprises a star tracker and four reaction wheels. Eye-sat will also welcome new technologies on board to demonstrate their applicability in space environment and to test their in-orbit performances: C&DH module will combine a dual-core ARM9 microprocessor (CPU frequency up to 1GHz) and a FPGA Flight software will be based on Time and Space Partitioning technology S-band TTC transceiver X-band transmitter for scientific data Solar panels will be deployed by self-blocking and self-deployable composite hinges Hold-on and Release Mechanisms based on the thermal knife concept 3DPlus camera with a CMOS detector from CMOSIS Innovative black coating from Cilas Eye-Sat is a Student CubeSat which belongs to JANUS, a CNES’ program that supports French Universities in developing their CubeSat projects. The specificity of Eye-Sat is that it has been developed within the French Space Agency since 2012, with more than 200 students involved. After passing a successful qualification review before a board of CNES agents in October 2018, the project team is now in the Assembling, Integration and Validation phase with the flight model. Launch is due on October/November 2019, on a Soyouz rocket from French Guyana, with COSMOS Sky-Med from the Italian Space Agency and Cheops from the European Space Agency.