Miracle-dz/UniFAR-FTUs huggingface dataset:
Scanning Probe Microscopy for Energy Research

Introduction: Local Probes in the Next Decade of Energy Research: Bridging Macroscopic and Atomic Worlds (D A Bonnell and S V Kalinin) Scanning Probes for Energy Harvesting Systems: Photovoltaics and Solar Cells: Electrical Scanning Probe Microscopy on Solar Cell Materials (R Giridharagopal, G E Rayermann and D S Ginger) Organic Solar Cell Materials and Devices Characterized by Conductive and Photoconductive Atomic Force Microscopy (X-D Dang, M Guide and T-Q Nguyen) Kelvin Probe Force Microscopy for Solar Cell Applications (T Glatzel) Reversible Rectification in Sub-Monolayer Molecular P-N Junctions: Towards Nanoscale Photovoltaic Studies (J A Smerdon, N C Giebink and J R Guest) Study of Photoinduced Charges with Atomic Force Microscopy (M Dokukin, N Guz and I Sokolov) Imaging of Nanoscale Photogenerated Charge Transport in Organic Photovoltaic Materials (B Hamadani, P M Haney and N B Zhitenev) Photoassisted Kelvin Probe Force Microscopy for Characterization of Solar Cell Materials (T Takahashi) Scanning Probes for Fuel Cells and Local Electrochemistry: Electrochemical Strain Microscopy of Oxygen-Ion Conductors: Fuel Cells and Oxide Electronics (A Kumar, S Jesse, S V Kalinin, F Ciucci and A Morozovska) Ion Dynamics in Nanoscopic Subvolumes of Solid Electrolytes Analysed by Electrostatic Force Spectroscopy (A Schirmeisen and B Roling) Nanoscale Electrochemistry in Energy Related Systems Using Atomic Force Microscopy (W Lee, M H Lee, R P O'Hayre and F B Prinz) Scanning Probe Microscopy of Fuel Cell Materials Under Realistic Operating Conditions (S S Nonnenmann and D A Bonnell) Scanning Probe Microscopy of Energy Storage Materials and Devices: In situ SPM Analysis of Interfacial Phenomena in Lithium-Ion Batteries (M Inaba, S-K Jeong and Z Ogumi) Conducting-Probe Atomic Force Microscopy of Electrochemical Interfaces (P A Veneman and K J Stevenson) Electrochemical Strain Microscopy of Li-ion and Li-air Battery Materials (T M Arruda, N Balke, S Jesse and S V Kalinin) Emerging Scanning Probe Techniques: High Sensitivity Scanning Impedance Microscopy and Spectroscopy (S S Nonnenmann, X Chen and D A Bonnell) Scanning Microwave Microscopy: Advances in Quantitative Capacitance and Carrier Density Measurements at the Nanometer Scale (S Wu, F Kienberger and H Tanbakuchi) Mapping Electrochemistry at the Micro and Nanoscales with Scanning Ion Conductance Microscopy (C Laslau, D E Williams and J Travas-Sejdic) Force Microscopy, Nanochemistry and Nanofabrication (R Garcia, M Chiesa and Y K Ryu) Studying the Mechanism of Piezoelectric Nanogenerators (J Song and Z L Wang).
Efficient unassisted video segmentation using enhanced fast marching

The paper describes a novel unassisted, fully automatic segmentation technique applicable to colour natural video sequences. The algorithm uses the fast marching method for fast extraction of semantic objects from a frame in a video sequence. These objects are extracted by joint motion and colour analysis. The algorithm handles background in the same way as other objects, thus it does not need global motion compensation. The basic disadvantage of the fast marching method is related to unidirectional motion of an active contour. The new technique overcomes this difficulty by use of an enhancement step consisting in colour processing only. This processing step is performed on a small portion a frame only.
Which Is the Best Surgical Approach for the Pancreatic Cancer? A Classification of Pancreatic Cancer to Guide Operative Decisions Is Needed.

Reply: We appreciate the comments by Guerra et al addressing the potential role of robot-assisted surgery in resection of hepatic malignancies located in segment VII. As described in our recent article, a large abdominal incision (with thoracotomy, when necessary) provides the best view of the surgical field and widest working space for resection of hepatic segment VII, although open hepatectomy with such a large incision may result in painful postoperative recovery for patients. We also expect that robot-assisted surgery and other minimally invasive techniques will play a role in improving the short-term outcomes and quality of life of patients undergoing resection for segment VII lesions. The major advantage of robotic surgery lies in the high mobility of the forceps. This enables vertical transection of the hepatic parenchyma even for deeply located regions of the liver, such as segment VII. Fluorescence imaging mounted on the robotic surgery system may also help to identify hepatic malignancies and segmental boundaries during hepatectomy. In contrast, it may be difficult to obtain a sufficient view of the cranial aspects of the hepatic transection planes using the rigid laparoscope of the current robotic system. We have used transthoracic trocars for resection of segment VII lesions, after Gayet’s original technique, to obtain a surgical view vertical to the diaphragmatic surfaces of the liver with a laparoscope. Another concern about robotic hepatectomy for segment VII lesions is whether hemorrhage from the right hepatic vein and vena cava can be quickly addressed; this is important because such hemorrhage can become a critical situation. We have great interest in the application of robot-assisted surgery to resection of the ‘‘difficult’’ liver regions by Guerra et al and look forward to reading about the details of their techniques and operative outcomes.
Immune clone algorithm for mining association rules on dynamic databases

The paper seeks to generate large itemsets in a dynamic transaction database using immune clone algorithm. Intra transactions, inter transactions and distributed transactions are considered for mining association rules. The time of complexity of DMARICA (dynamic mining of association rules using immune clone algorithm) is analyzed, with fast updata (FUP) algorithm for intra transactions and e-apriori for inter transactions. The problem of mining association rules in the distributed environment is explored by distributed DMARICA (DDMARICA). The study shows that DMARICA outperforms both FUP and e-apriori in terms of execution time and scalability, without comprising the quality or completeness of rules generated. DMARICA is also compared with DMARG(dynamic mining of association rules using genetic algorithm). And it has better performance than that of DMARG
Estimation of coupling coefficient and refractive indexfor fused coupled fibers

Fiber couplers are widely used in telecommunication and industry as a passive splitting power device. The effective power coupling and transmitting from one fiber to another is mainly determined by both coupling length and coupling coefficient. Coupling length can be calculated directly but for coupling coefficient it depends upon the refractive index and separation fiber axis. After fusion processes of two SMF-28eÂ® couplers, the refractive index is unknown due to change in the radius of fiber (rcladd<40i�­m and rcore<1.5i�­m). Coupling coefficient range is obtained from a distribution of coupling ratio and compared with the empirical formula which also enables to calculate refractive index. In this experiment, coupling coefficient in the range of 0.6-0.9/mm is calculated as a function of separation fiber axis and refractive index of core and cladding. The result shows a good correlation between experimental results and theoretical calculation.
Nuclear-Chemical Synthesis of 1,4-Diazine Quaternary Salts

Ion-molecular reactions of nucleogenic phenyl cations with the nucleophilic centers of 1,4-diazines have been investigated for the first time. Previously unknown tritium labeled N-phenyl quaternary derivatives of pyrazine and quinoxaline, which are potential radioactive biomarkers, have been obtained by nuclear-chemical method.
A Calculation Method Based on Mode for Available Transmission Capacity of Wind Power Grids Considering Wind Power Output Prediction Errors

Due to the problem of inevitable errors in prediction caused by the randomness and transient nature of the high proportion of wind power output in the new power system has had a certain impact on the accuracy of available transmission capacity of the power system. In order to accurately quantify the impact of wind power prediction errors on the available transmission capacity, this article uses Pearson coefficient to calculate the correlation of historical errors in wind power output prediction. The mode theory is used to calculate the upper and lower limits of wind power output prediction error in the next moment of wind power prediction, and the upper and lower limits of prediction error are brought into the available transmission capacity calculation model of the large power grid considering the wind power prediction error range. The accuracy of the error zones obtained is ensured in data statistics, thus obtaining the available transmission capacity of the large power grid considering the wind power prediction error range. The simulation results of the example show that the proposed algorithm based on mode r has high computational accuracy and obvious advantages in calculating the available transmission capacity of high proportion wind power.
An Efficient Scheme for Secure Message Transmission using Proxy-Signcryption

Previous proxy signature schemes enable a principal to have a trusted proxy agent sign messages on its behalf. We present a proxy signature scheme that combines the functionality of proxy signing and en-cryption. This proxy-signcryption scheme is useful for applications that are based on unreliable datagram style network communication model where messages are individually signed and not serially linked via a session key to provide authenticity and integrity. Use of a proxy agent to perform signature function is desirable for applications that are expected to support computing devices with low computational power and storage capacities. Integration of encryption functionality to provide secrecy at no additional cost to the proxy signature generation is an eecient means by which to support the class of applications targeted by this research work such as e-commerce using mobile computing and communication devices.
Experiments with Spectral Learning of Latent-Variable PCFGs

Latent-variable PCFGs (L-PCFGs) are a highly successful model for natural language parsing. Recent work (Cohen et al., 2012) has introduced a spectral algorithm for parameter estimation of L-PCFGs, which—unlike the EM algorithm—is guaranteed to give consistent parameter estimates (it has PAC-style guarantees of sample complexity). This paper describes experiments using the spectral algorithm. We show that the algorithm provides models with the same accuracy as EM, but is an order of magnitude more efficient. We describe a number of key steps used to obtain this level of performance; these should be relevant to other work on the application of spectral learning algorithms. We view our results as strong empirical evidence for the viability of spectral methods as an alternative to EM.
NCTUns 6.0: A Simulator for Advanced Wireless Vehicular Network Research

NCTUns is a novel network simulator/emulator that has many unique features over traditional network simulators/emulators. It runs on Linux and many papers/projects have used it for wireless vehicular network research. According to the NCTUns website (http://NSL.csie.nctu.edu.tw/nctuns.html), as of December 24, 2009, more than 16,164 people from 137 countries in the world have registered and downloaded this software since its first public release on November 1, 2002. In its 6.0 release, NCTUns adds new supports for large-scale microscopic wireless vehicular network (WVN) simulation. In this paper, we introduce the important capabilities of NCTUns 6.0 for wireless vehicular network research.
MULTI-RESOLUTION CLUSTERING OF TEXTURE IMAGES

This paper describes a new method for analysis/synt hesis of textures using a non-parametric multi-resolution approach. In the an alysis step the new technique clusters together structural features with the sa me visual appearance from an input texture using a standard pyramid-based decompositio n. The synthesis is obtained through a sampling procedure constraining the distr ibution of the spatial characteristics at lower resolution. This is realized through a new data structure called frequency tree . Experimental results show the effectiveness of suc h approach: it is capable to reproduce efficiently the generative stochastic pro cess of a wide class of real texture images. The proposed method achieves a greater comp utational efficiency than other approach known in the literature.
Remodeling muscles with calcineurin

Ca2+ signaling plays a central role in hypertrophic growth of cardiac and skeletal muscle in response to mechanical load and a variety of signals. However, the mechanisms whereby alterations in Ca2+ in the cytoplasm activate the hypertrophic response and result in longterm changes in muscle gene expression are unclear. The Ca2+, calmodulin‐dependent protein phosphatase calcineurin has been proposed to control cardiac and skeletal muscle hypertrophy by acting as a Ca2+ sensor that couples prolonged changes in Ca2+ levels to reprogramming of muscle gene expression. Calcineurin also controls the contractile and metabolic properties of skeletal muscle by activating the slow muscle fiber‐specific gene program, which is dependent on Ca2+ signaling. Transcription factors of the NFAT and MEF2 families serve as endpoints for the signaling pathways whereby calcineurin controls muscle hypertrophy and fiber‐type. We consider these findings in the context of a model for Ca2+‐regulated gene expression in muscle cells and discuss potential implications of these findings for pharmacologic modification of cardiac and skeletal muscle function. BioEssays 22:510–519, 2000. © 2000 John Wiley & Sons, Inc.
Applying an XML Warehouse to Social Network Analysis, Lessons from the WebStand Project

In this paper we present the state of advancement of the French ANR WebStand project. The objective of this project is to construct a customizable XML based warehouse platform to acquire, transform, analyze, store, query and export data from the web, in particular mailing lists, with the final intension of using this data to perform sociological studies focused on social groups of World Wide Web, with a specific emphasis on the temporal aspects of this data. We are currently using this system to analyze the standardization process of the W3C, through its social network of standard setters.
Semantic Composition with Quotient Algebras

We describe an algebraic approach for computing with vector based semantics. The tensor product has been proposed as a method of composition, but has the undesirable property that strings of different length are incomparable. We consider how a quotient algebra of the tensor algebra can allow such comparisons to be made, offering the possibility of data-driven models of semantic composition.
Single Channel Recordings From Human Cardiac Sarcoplasmic Reticulum

Native membrane vesicles of human cardiac sarcoplasmic reticulum have been fused with artificial lipld bilayers to obtain recordings of single chloride and calcium release channels. Tissue was obtained from the explanted hearts of patients with end-stage cardiac failure undergoing heart transplantation. Although previous studies of calcium uptake and release have shown that the function of the sarcoplasmic reticulum is abnormal in end-stage cardiac failure, the basic properties of the channels are similar to those reported for equivalent channels from normal animal tissue.
Does the firm-analyst relationship matter in explaining analysts' earnings forecast errors?

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Does the firm-analyst relationship matter in explaining analysts’ earnings forecast errors? Régis Breton, Sébastien Galanti, Christophe Hurlin, Anne-Gaël Vaubourg
Optimized ML-MAC for energy-efficient Wireless Sensor Network protocol

Energy efficient protocol design for Wireless Sensor Networks (WSNs) is a very challenging task because of limited battery capacity of nodes. This necessity for energy efficient operation of a WSN has prompted the development of new protocols in all layers of the communication stack. Layer-wise utilization of densely deployed nodes to effectively prolong the overall network life is presented in this paper. Simulation is done in QualNet 6.1 network simulator. Effective number of layers as well as effective node density over a terrain is also analyzed to achieve energy efficient design. Layering helps the network to work for a long time as only one layer in the network is in action at a time, rest layers are completely sleeping. Also, sensor nodes in ML-MAC (Multi-Layer MAC) have a very short listening time that reduces the energy consumption during communication. The results are used to create a parameter estimator through MATLAB.
Advancing the Terminological Classification of Semi-structured Documents

Usually, documents are given in textual form, accompanied by a set of terminological classifications (metadata), based on vocabularies of domain ontologies. This paper presents a novel method for advancing the above classification, by extracting more properties of the analyzed documents. We first extract additional roles from the textual part and together with roles extracted from the ontology statements, we construct an extended document vector representation. We then introduce a pruning algorithm that, for a given document collection, merges concepts of the ontology to produce classes with a sufficient number of corresponding instances. We then classify the documents to ontology classes using the Stanford linear Classifier. Finally, we propose an algorithm that assigns additional concept labels to documents, using the output of the classifier. Our system is evaluated in a set of real data and ontological descriptions and its performance is measured in terms of various accuracy and specificity measures indicates that the proposed approach for documents classification produces correct labels for the majority of items.
CARBON DIOXIDE AS A FEEDSTOCK.

This report is an overview on the subject of carbon dioxide as a starting material for organic syntheses of potential commercial interest and the utilization of carbon dioxide as a substrate for fuel production. It draws extensively on literature sources, particularly on the report of a 1999 Workshop on the subject of catalysis in carbon dioxide utilization, but with emphasis on systems of most interest to us. Atmospheric carbon dioxide is an abundant (750 billion tons in atmosphere), but dilute source of carbon (only 0.036 % by volume), so technologies for utilization at the production source are crucial for both sequestration and utilization. Sequestration--such as pumping CO{sub 2} into sea or the earth--is beyond the scope of this report, except where it overlaps utilization, for example in converting CO{sub 2} to polymers. But sequestration dominates current thinking on short term solutions to global warming, as should be clear from reports from this and other workshops. The 3500 million tons estimated to be added to the atmosphere annually at present can be compared to the 110 million tons used to produce chemicals, chiefly urea (75 million tons), salicylic acid, cyclic carbonates and polycarbonates. Increased utilization of CO{sub 2} as a startingmore » material is, however, highly desirable, because it is an inexpensive, non-toxic starting material. There are ongoing efforts to replace phosgene as a starting material. Creation of new materials and markets for them will increase this utilization, producing an increasingly positive, albeit small impact on global CO{sub 2} levels. The other uses of interest are utilization as a solvent and for fuel production and these will be discussed in turn. « less
Design of an instrument to measure alcohol-related psychosocial influences in the development of norms among 13-year-old to 17-year-old adolescents

Introduction Harmful drinking among young people is common in Australia and many other countries. Social norms and their influence on adolescents’ alcohol consumption behaviours have received much research attention in recent years. However, there is limited understanding of how social norms related to alcohol are developed and transmitted across social networks and a specific tool that measures these constructs has yet to be developed. This paper outlines the rationale and protocol for the design and validation of a multidimensional survey instrument which measures the development and transmission pathways of alcohol-related norms among adolescents. A longer term aim is to apply the instrument in a respondent-driven sampling study with a large adolescent cohort. Methods and analysis Social Cognitive Theory (SCT) and relevant literature will guide the design of the online survey instrument. Feedback from a practitioner-based stakeholder committee, academic expert panel reviews, focus groups and interviews with adolescents aged 13–17 years in Perth, Western Australia (WA) will serve to ascertain content and face validity. A test–retest will be conducted using a purposive sample of students (n=400) at secondary schools in Perth. The instrument's psychometric properties will be analysed, including exploratory factor analyses, discriminant validity, internal consistency and test–retest reliability. Ethics and dissemination The results of this research will provide public health researchers and practitioners with a comprehensive standardised instrument to explore the characteristics of individual-level and community-level social influences and norms associated with use of alcohol by adolescents and the routes through which these norms are transmitted. The data collected by the instrument is anticipated to inform the design of youth specific interventions with the potential to reduce alcohol-related harms. The Study findings will be disseminated widely through peer-reviewed publications and conference presentations. The study has received approval from the Curtin University Human Research Ethics Committee.
Optimization of the path planning model through integration of improved RRT* algorithm and ACO algorithm

Path planning is an important part of AUV (Autonomous Underwater Vehicle) exploration system. The path planning of AUV should consider the optimization goal of the path, the path environment, the terrain and obstacles, and the performance constraints of the robot itself. This path planning problem can be solved by various algorithms, but the commonly used algorithms often have many problems. Therefore, aiming at the problems of long sampling time, large amount of calculation and too random path planning results of RRT* algorithm, a multi-strategy improved NTDRRT* algorithm is proposed. Aiming at the problem that ACO algorithm is easy to fall into local optimum and slow convergence speed, a multi-strategy improved HPACO algorithm is proposed. The NTDRRT* algorithm and the HPACO algorithm are combined to form a hybrid improved algorithm, and an AUV path planning model is proposed based on this. Through experimental verification, the hybrid path planning algorithm proposed in this paper has achieved good results in search efficiency, global convergence and solution quality. The research content and results of this paper have certain reference value for improving the efficiency and accuracy of AUV path planning, and have made certain contributions to the development of AUV technology, and can also provide reference and inspiration for research in related fields.