Miracle-dz/UniFAR-FTUs huggingface dataset:
Occupational dose estimates for the National Ignition Facility

The National Ignition Facility (NIF) is currently being constructed at Lawrence Livermore National Laboratory (LLNL). During peak operation, the NIF will attain D-T fusion yields of 20 MJ in a single experiment and 1200 MJ/y. With such high yields, neutron activation will be important within the NIF Target Bay. The total dose equivalent (dose) will be maintained {<=} 10 person-rem/y with individual doses {<=} 500 mrem/y, and all doses will be as low as reasonably achievable (ALARA). This work outlines planned maintenance activities, expected dose rates, and the resulting worker dose. Methods for the reduction of this dose are discussed, and a tool for the rapid calculation of the occupational dose is presented.
Encapsulation Systems for Delivery of Flavonoids: A Review

Encapsulation of bioactive compounds s been considered a promising tool for preserving these compounds. Several studies on dietary sources and health benefits of flavonoids, their chemical and stability properties, and encapsulation methods used for delivery of flavonoids were reviewed. Flavonoids comprise the main group of polyphenols widely found in fruits and vegetables responsible for numerous biological activities. They have a flavan nucleus with 15 carbon atoms organized in three rings and are categorized into six subgroups. The main dietary sources of flavonoids are fruits, vegetables, cereals, tea, and some herbs such as Viola odorata Linn. These compounds can prevent diseases such as cardiovascular, cancers, neurodegenerative, diabetes, and inflammatory bowel disease. Despite these beneficial biological activities, flavonoids are not stable against environmental conditions, have low water solubility and low bioavailability after oral administration, which restricts their application. Accordingly, encapsulation has been utilized in order to improve the stability and solubility of flavonoids. Various approaches such as spray drying, molecular complexes, liposomes, nanoparticles, emulsification, and multilamellar vesicles have been applied in the entrapment of flavonoids. Encapsulation can improve the stability of flavonoids as well as solubility, controlled release, and bioavailability.
RFID-Based Distributed Information System of Aircraft Supply Chain Management

Visualization, accuracy and timeliness are the main trends of the supply chain. How combine the information technology and radio frequency identification technology is the next one of the difficulties of aircraft supply chain development in the world. In view of those problems such as geographical dispersion of the current aircraft manufacturing enterprises, and their supply chain too long and difficult to visualization,based on radio frequency identification (RFID) technology and information technology, a solution of distributed information systems for aircraft supply chain management is proposed, the system architecture and function modules are designed, the key problems for the system development are pointed out.
Load Monitoring System of Electric Appliances Based on Hidden Markov Model

This paper proposes a new load monitoring system of electric appliances based on Hidden Markov Model (HMM). Monitoring of electric appliances under operation is expected to lead to understanding needs of power consumers and forecasting power demands in future. In previous works, the monitoring was carried out by developing some special equipments for measurement and/or by collecting information by means of questionnaires. However, development of special equipments and questionnaire survey need high labor and cost. Moreover, the consumer may feel uncomfortable for these activities. Therefore, it is highly recommended to monitor the running electric appliances without installing any expensive equipments nor invading consumers buildings. When a certain electric appliance runs, the current waveform flowing in it shows specific characteristics. This implies that it is quite reasonable to pay attention to the pattern of current waveforms for recognition of used electric appliances. In this paper, HMM, which is widely used for the analysis of time series data, is introduced as the recognizer for the current waveforms. HMM is characterized by three important parameters as follows: transition probability ai j, output probability bi(x) and initial state probability πi. The scenario of recognition based on HMM is divided into two stages; the training stage and recognition stage. In the training stage, the parameters are updated to maximize the likelihood of measured current waveforms, i.e., maximize P(O|λ) where O represents the measured current waveform. Each HMM is trained by using current waveform flowing in each electric appliance in the same way. In the recognition stage, the likelihood for the unknown measured current waveform Ounknown is calculated for all HMM trained in advance. Then, the electric appliance which corresponds to HMM showing highest likelihood can be recognized as the working appliance. The proposed method was applied to the load monitoring of electric appliances in a household. First of all, some electric appliances which were widely used in the household were specified. Then, the current waveforms flowing in them were measured. Figures 1 and 2 show the current waveforms flowing in a refrigerator and a television, respectively. As shown in these figures, the current waveforms show different characteristics according to the electric appliance. Based on these measurements, each HMM was trained for each electric appliance. Finally, pattern recognitions were carried out for measured current waveforms which were not used for the parameter training. As a result of recognition, all unknown waveforms were recognized successfully, and it has been proven that the load monitoring based on pattern recognition of current waveforms using HMM is quite promising.
Machining Capabilities of Graded Materials by Cutting Processes

Professional paper shows the general characteristics of graded materials, their previous industrial use and potential use of graded materials in the future. In any case, today the use of graded materials is increasing and moving from the laboratory environment into everyday use. However, the subsequent processing of the graded material remains the big unknown, and represents a major challenge for researchers and industry around the world. It could be said that the study of machinability of these materials is in its infancy and in this area are many unanswered questions. Machinability problem of graded materials was undertaken at the Faculty of Mechanical Engineering in Maribor. After a radical study of the literature and potential machining processes of graded materials, we started with the implementation of cutting processes on the workpiece. This professional paper presents the first results of the analysis, which will be used for further research and machinability study of graded materials.
The Innovation Complex

The Innovation Complex shows how the new urban economy is being shaped by digital technology businesses and organizations, city government, and a tech-financial meritocracy. Looking closely at “innovation” in New York from the city’s fall in the dot-com crash of 2000 to its emergence as the second-largest startup ecosystem of the 2010s, the book examines the emergence of new organizational, geographical, and discursive spaces that literally root digital production in place, molding a tech-competent workforce, public-private-nonprofit partnerships, and a hegemonic, entrepreneurial culture. The Innovation Complex begins by exploring the city’s subculture of hackathons and meetups, describes the careers of New York–based startup founders and venture capitalists, and traces the transformation of the Brooklyn waterfront from industrial wasteland to “innovation coastline. ” Analyzing connections between local networks and global capital, it shows how a Silicon Valley model of innovation is urbanized by big cities like New York, where an influential alliance between business, government, and university leaders recalls C. Wright Mills’s potent concept of the power elite. Paradoxically, while the 21st-century economy makes cities more successful, they also become less livable for those who cannot reap tech’s rewards.
Fabrication and characterization of high-Q microresonators using thin plate mechanical mode

The growing place of electronics devices in our society increases the demand of small devices such as RF filters, time references and oscillators. The aim of this work concerns the design and characterization of a new kind of crystalline silicon microresonator fabricated using a DRIE (Deep Reactive Ion Etching) technique. This device can be fabricated by IC compatible techniques. This kind of microresonators is electrostatically actuated and uses a contour or Lamé mode as fundamental mode of vibration. Its size gives the resonant frequency and behavior. The mechanical characterization of one microresonator is carried out using an optical bench set-up. The first results obtained on a device show a high Q factor in air close to 1000 at the resonant frequency of 10.3 MHz.
Protein Secondary Structure Prediction using Recurrent Neural Networks

In bioinformatics the prediction of the secondary structure of the protein from its primary amino acid sequence is very difficult, which has a huge impact on the field of science and medicine. The hardest part is how to learn the most effective and correct protein features to improve prediction. Here, we carry out a deep learning model to enhance structure prediction. The core achievement of this paper is a group of recurrent neural networks (RNNs) that can manage high-level relational features from a pair of input protein sequence and target protein sequences. This paper contrasts the different type of recurrent network in recurrent neural networks (RNNs). In addition, the emphasis is on more advanced systems which incorporate a gating utility is called long short term memory (LSTM) unit and the newly added gated recurrent unit (GRU). This recurrent units has been calculated on the basis of predicting protein secondary structure using an amino acid sequence. The dataset has been taken from a publicly available database server (RCSB), and this study shows that advanced recurrent units LSTM is better than GRU for a long protein sequence.
The Starved Lubrication of Piston Rings in a Diesel Engine

Miniature pressure and film thickness transducers mounted in the cylinder liner of a diesel engine have been used to study the lubrication of piston rings. The method of using the gauges to determine oil starvation in the inlet of the rings is described and results from a working engine are presented. Calculations for both starved and fully flooded rings have been carried out and are compared with the measured results.
Machine Performance Degradation Recognition Using Locality Preserving Projections and Clustering Approach

The sensitivity of various features that are characteristics of machine performance may vary significantly under different working conditions. Thus it is critical to devise a systematic feature extraction (FE) approach that provides a useful and automatic guidance on using the most effective features for machine performance recognition without human intervention. This paper proposes a locality preserving projection (LPP)-based FE approach for machine performance degradation recognition. Different from principal component analysis (PCA) that aims to discover the global structure of the Euclidean space, LPP is capable to discover local structure of the data manifold. This may enable LPP to find more meaningful low-dimensional information hidden in the high-dimensional observations compared with PCA. This experimental result on a bearing test-bed shows that LPP-based FE improves the performance of recognizers for identifying performance degradation of bearings.
Active cooling for downhole instrumentation: design criteria and conceptual design summary

This report summarizes the results of a literature survey that describes successful tests of geophysical instruments and their thermal protection systems. The conditions to which an instrument is subjected are formulated into relevant thermal and mechanical design criteria that have proved useful for improving passive thermal protection systems and selecting the preliminary feasibility of active refrigeration systems. A brief summary of the results of a series of conceptual designs on seven different active refrigeration systems is given. The systems are ranked according to feasibility for use in downhole active cooling applications.
Researches on Thermo-Electric Properties of Seawater and Al2O3 Nanofluids

The article utilizes thermo-electric performance experiments to study four fixed volume kinds of electrolytes (Tap Water, Mineral Water, Sea Water, and Al2O3 Nanofluids) under different operating temperatures, distances and areas of electrodes due to the impact of the output currents. The experimental results showed that the rise in operating temperature will significantly affect the magnitude of the output current because of heat convection inside the fluid. And the output current of the seawater was much larger than those of the nanofluids, tap water and mineral water between 27 °C and 90 °C. Its maximum value was up to 4.2 mA. However, the seawater presented unstable for output current. The Al2O3 nanofluids had the most stable among them and its output current was about 1.08 mA. If seawater combined with Al2O3 nanoparticles, they will be able to achieve a complementary role in the future development.
AIDA and group technology

The paper describes part of ft study made by the author at the Turin International Centre, in which the operations research technique of AIDA was used to plan the major policy decisions for a new production system. AIDA or ‘ Analysis of Interconnected Decision Areas ’ is a technique developed by the Institute for Operational Research in Britain. It is used to find optimum solutions for problems involving many different decision areas and inter related options. It uses network analysis to eliminate illogical solutions and carefully specified criteria to choose between the remaining possible solutions. The aim of the study was to compare the solution found using AIDA with the solution based on group technology. AIDA found exactly the same solution as that advocated by the author and by some other advocates of group technology.
Joint torque-velocity pair based manipulability for manipulators

This paper provides a new approach of manipulability for robotic manipulators. While conventional manipulability is analysis in velocity domain and can not include force effect such as gravity of link and payload, the proposing approach can include the force effect. For the purpose, an operation range is introduced. The operation range is for actuator attached with every joint of robot and provides generable joint torque and velocity and their relation (between generating torque/velocity and addable velocity/torque). Using the operation range, we develop a new manipulability in velocity domain, including force effect.
Comparative investigation of single-point and double-point incremental sheet metal forming processes

Abstract As part of a study of the capabilities of processes suitable for the rapid prototyping of sheet metal parts, two variants of incremental forming have been investigated experimentally and with finite element analysis. By examining the manufacture of similar parts by both processes some important differences between the capabilities of the two methods are highlighted. In particular, significant differences in the patterns of thickness variation and initial fracture sites are observed.
Morphology, Ontogeny and Molecular Phylogeny of a New Urostylid Ciliate, Bakuella (Pseudobakuella) Guangdongica n. sp. (Protista, Ciliophora, Hypotrichia) from Southern China

Background: Spirotrich ciliates are one of the most diverse groupsin the phylum Ciliophora and are widely distributed in marine, freshwater, and terrestrial biotopes. Many nominal species are, however, poorly known and their systematic positions remain uncertain due to the lack of information concerning their infraciliature, morphogenesis, and gene sequences. In this paper, the morphology and morphogenesis of Bakuella (Pseudobakuella) guangdongica n. sp. were studied, in addition, genomic DNA was extracted in order to sequence the small subunit rDNA. Results: Bakuella (Pseudobakuella) guangdongica n. sp. is characterized by 150–225 µm in vivo; 35–42 adoral membranelles; three to five buccal, two frontoterminal and eight to 13 transverse + pretransverse cirri; midventral complex comprised of 10–20 midventral pairs and two midventral rows extending to transverse cirri; posterior part of marginal rows slightly overlapped; colorless cortical granules about 1 μm across, arranged in small groups; soil habitat. Its main ontogenetic features are: (1) in the proter, the parental adoral zone of membranelles is completely renewed by new structures; (2) in the opisthe, the oral primordium originates apokinetally, some old midventral cirri join the formation of frontoventral-transverse cirral anlagen; (3) the anlagen for marginal rows and dorsal kineties develop intrakinetally; and (4) the numerous macronuclear nodules fuse into a single mass before dividing. Phylogenetic analyses based on the SSU rDNA sequence suggests the non-monophyly of the genus Bakuella. Conclusions: The morphology, morphogenesis and molecular phylogeny of the new hypotrichous ciliate, Bakuella (Pseudobakuella) guangdongica n. sp. were studied, the phylogenetic analyses show that the Bakuella is polyphyletic in the SSU rDNA.
Finite-difference Time Domain Analysis of a Printed dipole Antenna

Finite-difference time-domain (FDTD) modelling is now established as an accurate numerical tool for the full-wave analysis of microwave circuits. The technique may be applied to highly complex structures as it requires only the regions and the properties of the dielectric and conductors in the structure to be specified. The present paper presents results for both measurement and the FDTD analysis of a printed dipole antenna element and its associated feed network. The antenna is intended for operation within the band 9-12 GHz. < >
Adaptive exponential smoothing versus conventional approaches for lumpy demand forecasting: case of production planning for a manufacturing line

Production planning in a lumpy demand environment can be tenuous, with potentially costly forecasting errors. This paper addresses the issue of selecting the smoothing factor used in lumpy demand forecasting models. We propose a simple adaptive smoothing approach to replace the conventional industrial practice of choosing a smoothing factor largely based on the analyst or engineer's experience and subjective judgment. The Kalman filter approach developed in this study processes measurements to estimate the state of a linear system and utilises knowledge from states of measurements and system dynamics. Performances of an array of forecasting models that have been shown to work well in lumpy demand environments are compared with respect to the proposed adaptive smoothing factor and the conventional smoothing constant across a spectrum of lumpy demand scenarios. All models using the adaptive smoothing factor based on Kalman filter weighting function generate smaller errors than their conventional counterparts, especially under high lumpiness demand environments. Our proposed approach is particularly useful when production management is concerned about simplicity and transferability of knowledge due to constant personnel turnaround and low retention rate of expertise.
Passive Distributed Clustering Scheme in Wireless Sensor Networks

Energy efficiency is especially important for the cluster of the wireless sensor network (WSN). This paper studies how to increase availability and survivability of WSN by selecting a suitable cluster head. For this purpose, we propose a passive distributed clustering scheme (PDCS), to promote the efficiency of energy utilization. In PDCS, both the relative distance and the residual energy are taken into consideration for cluster head selection. Simulation results present that PDCS has better performance than the well-known LEACH scheme.
An Innovative Data Analysis Strategy For Accurate NGS Detection of Tumor mtDNA Mutations

Background: Next generation sequencing (NGS) technology has been commonly applied to detect mtDNA mutations, which are reported to be strongly associated with cancers. However, several key challenges still exist in the bioinformatic analysis of mtDNA sequencing data, which greatly affect the detection accuracy of mtDNA mutations. Methods: Here, we systematically evaluated several key analysis procedures, including trimming, mapping and filtering, in mtDNA mutation detection of FFPE tissues, fresh tissues and plasma samples from cancer patients. Furthermore, the innovative bioinformatics pipeline integrating a newly-developed filtering algorithm was established.Results: We found that trimming procedure was essential for improving mtDNA mapping performance in plasma but not tissue samples. Mapping with rCRS-hg19 reference was strongly suggested for mtDNA mutation detection in plasma samples due to the extreme abundance of NUMTs. In addition, our results showed that the setting of 3 mismatches was most appropriate for mtDNA mutation calling. More importantly, we revealed the presence of a negative logarithmic relationship between mtDNA site sequencing depth and minimum detectable mutation frequency and thus build up an innovative and efficient filtering strategy to increase the accuracy and sensitivity of mutation detection. Finally, we verified that higher sequencing depth was required for PCR-based than capture-based enrichment strategy.Conclusions: Collectively, we established an innovative data analysis strategy, which is of great significance for improving the accuracy of mtDNA mutation detection for different types of tumor samples.
A Comprehensive Evaluation System of Association Rules Based on AHP

Association rules analysis is an important subject in data mining. At present, association rules mining algorithms frequently generate a large number of association rules, but most of the algorithm evaluations make advances only from an aspect, which makes the users select difficultly. Therefore, the comprehensive evaluation of association rules has become highly necessary. A comprehensive evaluation system of association rules based on the AHP (Analytic Hierarchy Process) was presented, which can evaluate the association rules from multi-angle and multi-dimensional. Many evaluation results are integrated into the system, eventually presenting a unified comprehensive coefficient to users. Practical data make it clear that the comprehensive evaluation system is rational and superior.
Coverage shaping of contoured-beam antennas by aperture field synthesis

A synthesis method for high-gain antennas with beams of elliptical or even more complicated crosssections is developed. The desired beam contour is realised in an offset reflector with circular aperture illuminated by a single feed by optimising the phase of the aperture field. A number of cases are presented in which the desired contour is an ellipse. The results are checked by a reflector antenna analysis program using physical optics.