Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigation of a channeling high-intensity laser beam in underdense plasmas

The interaction of an intense short pulse laser (>5/spl times/10/sup 18/ Wcm/sup -2/) with underdense plasma was extensively studied. The beam is found to be highly susceptible to the forward Raman scattering instability. At sufficiently high growth rates, this can lead to wavebreaking with the resultant production of a high flux of accelerated electrons (>10/sup 11/ for E>2 MeV). Some electrons are found to be accelerated well above the dephasing energy, up to 94 MeV. Self-scattered images intimate the presence of high-intensity channels that extend more than 3.5 mm or 12 Rayleigh lengths. These filaments do not follow the axis of laser propagation, but are seen to be emitted within an f4 cone centered around this axis. Spectra of the self-scattered light show that the main contribution of the scattering is not from light captured within these filaments. But there is evidence for self-phase modulation from effects such as ionization and relativistic self-focusing. However, no clear correlation is observed between channel length and the number or energies of accelerated electrons. Evidence for high intensities within the channels is given by small-angle Thomson scattering of the plasma wave generated therein, with this method, the intensity is found to be of the order of 10/sup 18/ Wcm/sup -2/ greater than 12 Rayleigh lengths from focus.
Modeling environments from a route perspective

Environment attributes are perceived or remembered differently according to the perspective used. In this study, two different perspectives, a survey perspective and a route perspective, are explained and discussed. This paper proposes an approach for modeling human environments from a route perspective, which is the perspective used when a human navigates through the environment. The process for route perspective semi-autonomous data extraction and modeling by a mobile robot equipped with a laser sensor and a camera is detailed. Finally, as an example of a route perspective application, a route direction robot was developed and tested in a real mall environment. Experimental results show the advantages of the proposed route perspective model compared with a survey perspective approach. Moreover, the route model is comparable to the performance of an expert person giving route guidance in the mall.
Innovative Convolutional Neural Networks Applied in Dynamometer Cards Generation

There are nearly 200,000 oil wells producing in PetroChina and 94% are sucker-rod pumping wells. Dynamometer card is essential for well diagnosis and optimization, which cost huge investment on sensor installations and maintenance. This paper present an innovative artificial intelligence method to get the card data directly from electrical parameters. With the development of artificial intelligent technology, many challenges in oil and gas industry have the potential to be addressed by developing artificial intelligent and Big Data analytic tools. This paper presents a method to get the dynamometer card using the electrical data collected during production. In our method, we start with building our training datasets consist of dynamometer card and corresponding electrical data with various well performance conditions. We using the state of art artificial intelligent deep learning algorithm to training the data and make a general model to generate the dynamometer card from electrical data. This method is based on image processing and deep learning, which eliminates the disadvantage of conventional physical-mechanism based model. After tested training datasets in several oilfields in PetroChina, the model demonstrates very high accuracy with almost 90% similarity to corresponding dynamometer card. The calculated dynamometer card from our model are good consistent with the field data too. In addition, this method has been testing on hundreds of wells newly produced well utilizing sucker-rod pumping system, which would reduce millions of investment on the sensors and equipment on average 5000 newly producing wells in PetroChina each year. As a result, with the fast development of artificial intelligence technology and expanding training datasets, the deep learning method will be fully utilized in more sucker-rod pump wells to generate the dynamometer card, which is also part of the intelligent well strategy. In the low oil price trend, artificial intelligence is a good choice to lower the investment and maintenance cost for mature fields and newly produced fields.
Regeneration of periodontal bone defects with dental pulp stem cells grafting: Systematic Review

Background The main objective is to evaluate the way to graft the dental pulp stem cells (DPSC) in periodontal defects that best regenerate periodontal tissues. Numerous procedures have been done to promote periodontal regeneration. Bone grafts show good gains clinically and radiographically but histologically seem to have minimal osteoinductive capacity. Another option that exceeds conventional surgery in reducing probing depth and increasing insertion is guided tissue regeneration and tissue engineering that could be an alternative approach to help in the regeneration of living functional bone and peri-dental structures. Material and Methods A search was carried out in Cochrane, PubMed-MEDLINE and Scopus databases with keywords: “dental pulp stem cells”, “periodontal regeneration”, “guided tissue regeneration, periodontal”, “tissue regeneration”, “periodontal bone defects”, “periodontal tissue engineering” and “periodontal defect”. Inclusion criteria were articles in English, maximum 10 years old, in which DPSC were used to regenerate a periodontal defect. Exclusion criteria were studies not published in English, case reports, case series, literature reviews, and studies in which periodontal defect was caused by dental extraction. Results Out of the 185 articles identified, 101 after excluding duplicates, of which 94 were discarded when reading the title and abstract. 7 articles were obtained for the full text reading: a case report and a case series were eliminated. The systematic review is performed with 5 animal testing studies in vivo. The DPSC sheets regenerate a greater amount of bone than the injection. If HGF (hepatocyte growth factor) is added, the maximum bone volume regenerated (69.3 ± 3.9 mm3; p<0.01) is achieved. Similar results were obtained in all carriers tested except in the controls. The periodontal ligament stem cells (PDLSC) formed more new bone, compared to DPSC (p<0.001). The presence of new cementum and periodontal ligament induced by CMLPs, was detected histologically but DPSC cannot achieve it alone. Conclusions Cementum or PDL regeneration does not depend only on DPSC but on other unknown factors. PDLSC has better periodontal regeneration than DPSC. DPSC significantly favours the regeneration of periodontal bone tissue but has few advantages over other grafts. It is necessary to study which growth factors or matrices can enhance their capacity for periodontal regeneration. Key words:Dental pulp, stem cells, periodontal guided tissue regeneration, periodontal bone loss.
Does Colonization with Methicillin-Susceptible Staphylococcus aureus Protect against Nosocomial Acquisition of Methicillin-Resistant S. aureus?

Objective. To test the hypothesis that methicillin-susceptible Staphylococcus aureus (MSSA) carriage may protect against nosocomial methicillin-resistant S. aureus (MRSA) acquisition by competing for colonization of the anterior nares. Design. Prospective cohort and nested case-control study. Setting. Swiss university hospital. Patients. All adult patients admitted to 14 wards of the general medicine division between April 1 and October 31, 2007. Methods. Patients were screened for MRSA and MSSA carriage at admission to and discharge from the division. Associations between nosocomial MRSA acquisition and MSSA colonization at admission and other confounders were analyzed by univariable and multivariable analysis. Results. Of 898 patients included, 183 (20%) were treated with antibiotics. Nosocomial MRSA acquisition occurred in 70 (8%) of the patients (case patients); 828 (92%) of the patients (control subjects) were free of MRSA colonization at discharge. MSSA carriage at admission was 20% and 21% for case patients and control subjects, respectively. After adjustment by multivariate logistic regression, no association was observed between MSSA colonization at admission and nosocomial MRSA acquisition (adjusted odds ratio [aOR], 1.2 [95% confidence interval (CI), 0.6–2.3]). By contrast, 4 independent predictors of nosocomial MRSA acquisition were identified: older age (aOR per 1-year increment, 1.05 [95% CI, 1.02–1.08]); increased length of stay (aOR per 1-day increment, 1.05 [95% CI, 1.02–1.09]); increased nursing workload index (aOR per 1-point increment, 1.02 [95% CI, 1.01–1.04]); and previous treatment with macrolides (aOR, 5.6 [95% CI, 1.8–17.7]). Conclusions. Endogenous MSSA colonization does not appear to protect against nosocomial MRSA acquisition in a population of medical patients without frequent antibiotic exposure.
Mercury exposure and periodontitis among a Korean population: the Shiwha-Banwol environmental health study.

BACKGROUND The oral effect of chronic low-level mercury exposure is not completely understood. This study examined whether mercury exposure is associated with periodontitis. METHODS This study cross-sectionally surveyed 1,328 residents (598 males and 730 females) from the prospective Shiwha and Banwol cohort in Korea from July 2005 to August 2006 at baseline. Two dentists assessed periodontitis, an outcome, using the Community Periodontal Index (CPI): CPI 3 or 4 and CPI 0 to 2 were classified as periodontitis and non-periodontitis, respectively. The hair mercury level, the predictor, was analyzed. The mercury level was categorized according to the reference dose of the Environmental Protection Agency of the United States: normal = <1 ppm and high = > or =1 ppm. Age, gender, economic status, smoking, frequency of daily toothbrushing, diabetes mellitus, hyperlipidemia, and obesity were assessed as confounders. Logistic regression analysis was used to evaluate the adjusted association. Subgroup analyses for gender were also performed. RESULTS Mercury exposure was independently associated with periodontitis (odds ratio = 3.17). Males with high mercury levels had a 50.0% higher probability of having periodontitis than females with normal mercury levels. Of them, the interaction effect between the body burden of mercury and gender was 39.0%. The odds ratio between periodontitis and high mercury levels was higher for males than females (95% confidence interval: 0.99 to 2.23 versus 0.59 to 1.26, respectively). CONCLUSIONS These results suggest that mercury exposure had an independent association with periodontitis. High body-burden mercury in males might be a contributory factor linked with periodontitis.
Modeling service discovery in ad-hoc networks

A protocol for service discovery using attenuated Bloom filters has been proposed for ad-hoc networks. Based on our study, it can well save network bandwidth compared to conventional approaches. We have built both an analytical model and a simulation model to evaluate the performance of our novel discovery mechanism. A comparison of these two models shows that the analytical model yields very accurate results. Further, an extension to the discovery protocol is introduced, and shown to yield significant performance gains. Finally, the impact of node mobility on the performance of our discovery mechanism is evaluated, and shown to be moderate.
Locality sensitive dictionary learning for image classification

In this paper, motivated by the superior performance of sparse representation based dictionary learning for application of image classification and the usage of nonlinearity property in improving performance of image representation, we propose a locality sensitive dictionary learning algorithm with global consistency and smoothness constraint to overcome the restriction of linearity at relatively low cost. Specifically, the image features are partitioned into several groups in a locality sensitive way and a global consistency regularizer is embedded into locality sensitive dictionary learning algorithm. The proposed algorithm is efficient to capture complex nonlinear structure. Experimental results on several benchmark data sets demonstrate the efficiency of our proposed locality sensitive dictionary learning algorithm.
Finding documents and reading them: Semantic metadata extraction, topic browsing and realistic books

What would it take to provide a congenial and comfortable environment for finding and reading books in a digital library? To locate information we need algorithms that extract semantic metadata in forms such as keyphrases, with accuracy and consistency comparable to human indexers. To support this we need comprehensive, detailed thesauri, automatically created, that embody contemporary language and usage. To emulate and enjoy the serendipitous adventures found in real libraries and bookstores we need browsing environments that provide readers with multiple clues in parallel: keyphrases, text excerpts, and supplementary knowledge structures—as well as the documents themselves. For readers to cherish and enjoy individual works we need to transcend the bland reading environment provided by the web by recreating the subjective impact and pleasurable experience of interacting with real books. This paper describes research that aims to achieve these goals.
HIP-KNEE control for gait assistance with Powered Knee Orthosis

A Powered Knee Orthosis (PKO) was developed for the elderly and patients with disordered gait to regain normal walking. In order to enhance the PKO performance and reduce system complexity especially for people with muscle weakness in their knee joints, an algorithm named HIP-KNEE control is proposed. This algorithm is based on the analysis of kinematic gait model, and the desired knee joint angle (KNEE) is estimated from the measurements of hip joint angle (HIP). The relationship between HIP and KNEE is modeled as a polynomial, which can be easily implemented to an embedded controller for real-time control. This control method is suitable to subjects with good function in hip joint, and it can provide help in walking without special training. An Inertia Measurement Units (IMU) is used for obtaining HIP input, and integrated with a footswitch for checking the heel condition; the gait assistance performance can be further improved.
A high‐performance IoT solution to reduce frost damages in stone fruits

Agriculture is one of the key sectors where technology is opening new opportunities to break up the market. The Internet of Things (IoT) could reduce the production costs and increase the product quality by providing intelligence services via IoT analytics. However, the hard weather conditions and the lack of connectivity in this field limit the successful deployment of such services as they require both, ie, fully connected infrastructures and highly computational resources. Edge computing has emerged as a solution to bring computing power in close proximity to the sensors, providing energy savings, highly responsive web services, and the ability to mask transient cloud outages. In this paper, we propose an IoT monitoring system to activate anti‐frost techniques to avoid crop loss, by defining two intelligent services to detect outliers caused by the sensor errors. The former is a nearest neighbor technique and the latter is the k‐means algorithm, which provides better quality results but it increases the computational cost. Cloud versus edge computing approaches are analyzed by targeting two different low‐power GPUs. Our experimental results show that cloud‐based approaches provides highest performance in general but edge computing is a compelling alternative to mask transient cloud outages and provide highly responsive data analytic services in technologically hostile environments.
Diabetes therapy‐focus on Asia: second‐line therapy debate: insulin/secretagogues

The following review is based on the second part of a debate entitled ‘Diabetes therapy‐ focus on Asia: 2nd line therapy: GLP1/DPP4 inhibitors versus Secretagogue/insulin therapy’, which was held during the ‘1st Asia Pacific Congress on Controversies to Consensus in Diabetes, Obesity and Hypertension (CODHy)’, in Shanghai, China, 2011. As such we reviewed only insulin and secretagogue therapy despite the existence of other therapeutic options. The article aims to shed light on the circumstances most adequate for use of these as second‐line agents, despite possible drawbacks. It is important to emphasize that regardless of it being a review of published evidence, it primarily represents the professional opinion of the writers.
Assembly of AUF1 Oligomers on U-rich RNA Targets by Sequential Dimer Association*

Many labile mammalian mRNAs are targeted for rapid cytoplasmic turnover by the presence of A + U-rich elements (AREs) within their 3′-untranslated regions. These elements are selectively recognized by AUF1, a component of a multisubunit complex that may participate in the initiation of mRNA decay. In this study, we have investigated the recognition of AREs by AUF1 in vitro using oligoribonucleotide substrates. Gel mobility shift assays demonstrated that U-rich RNA targets were specifically bound by AUF1, generating two distinct RNA-protein complexes in a concentration-dependent manner. Chemical cross-linking revealed the interaction of AUF1 dimers to form tetrameric structures involving protein-protein interactions in the presence of high affinity RNA targets. From these data, a model of AUF1 association with AREs involving sequential dimer binding was developed. Using fluorescent RNA substrates, binding parameters of AUF1 dimer-ARE and tetramer-ARE equilibria were evaluated in solution by fluorescence anisotropy measurements. Using two AUF1 deletion mutants, sequences C-terminal to the RNA recognition motifs are shown to contribute to the formation of the AUF1 tetramer·ARE complex but are not obligate for RNA binding activity. Kinetic studies demonstrated rapid turnover of AUF1·ARE complexes in solution, suggesting that these interactions are very dynamic in character. Taken together, these data support a model where ARE-dependent oligomerization of AUF1 may function to nucleate the formation of a trans-acting, RNA-destabilizing complex in vivo.
Electromagnetic vibration of saturable reactor considering magnetostriction and damping effect

Vibration and noise is an important factor to restrict the development and application of reactor. A weak 3D magneto-elastic model including magnetostriction and damping effects is developed in this paper. The magnetic field is analyzed based on field-circuit coupling, and then the vibration due to electromagnetic forces is analyzed of dry type reactor under different control currents. The electromagnetic forces include Laplace, Maxwell and magnetostrictive force, which can be calculated through magnetic field analysis. In order to determine the damping coefficient, the modal analysis of the reactor is also carried out. Meanwhile, an experiment platform of a 4.4kVar/220V single-phase controllable saturable reactor(CSR) is built. The vibration of CSR cores and windings were measured and analyzed. The results showed that both magnetostriction and damping have contribution to the vibration and the influence of saturation state of cores on vibration is also great. So, these factors should be considered when analyzing electromagnetic vibration of controllable reactor.
A Suitable Threshold for Speckle Reduction in Ultrasound Images

This paper presents a novel parametric thresholding procedure to reduce the effect of speckle noise in ultrasound (US) medical images. The method comprises the use of an adaptive data-driven exponential operator that operates on wavelet coefficients of the US image to suppress undesired effects of disturbances, preserving signal details. The obtained results demonstrate that the proposed denoising method increases the medical image quality and, therefore, it can be a useful tool in medical diagnosis.
Organizational Culture and IT Business Value: A Resource-Based View

This research studies information technology (IT) business value by examining complementarity effects between organizational culture and dynamic IT capability on firm performance. Using the Competing Values Framework, we study the external/internal focus and flexibility/stability dimensions of organizational culture. Here dynamic IT capability refers to the ability to integrate, build, and reconfigure IT-based resources and competences to adjust to rapidly changing environments. Drawing on the Resource-Based View of the firm (RBV), Dynamic Capabilities theory, and Complementarity theory, we argue that there exists complementarity between organizational culture and dynamic IT capability in influencing firm performance. We plan to use survey method to collect data and test the model. This study is especially important for IT managers and leaders in their decision-making on IS projects and complementary investments in organizations.
Explicit Rate-based Congestion Control for Multimedia Streaming over Mobile Ad hoc Networks

Design of congestion control mechanism for multi-media streaming over the Mobile Ad-hoc Networks (MANET) is challenging. Streaming applications require a smooth transmission rate which the Internet is unable to provide whenever there is congestion in the network. The standard TCP congestion control mechanism is not able to handle the special properties of a shared wireless multi hop channel well. In particular, the frequent changes of the network topology and the shared nature of the wireless channel pose significant challenges. In this paper, we propose a router assisted approach, where routers provide explicit feedback which allows quick increase of throughput. Index Term— Congestion, MANET, multimedia streaming,
Characterizing the performance effect of trials and rotations in applications that use Quantum Phase Estimation

Quantum Phase Estimation (QPE) is one of the key techniques used in quantum computation to design quantum algorithms which can be exponentially faster than classical algorithms. Intuitively, QPE allows quantum algorithms to find the hidden structure in certain kinds of problems. In particular, Shor's well-known algorithm for factoring the product of two primes uses QPE. Simulation algorithms, such as Ground State Estimation (GSE) for quantum chemistry, also use QPE. Unfortunately, QPE can be computationally expensive, either requiring many trials of the computation (repetitions) or many small rotation operations on quantum bits. Selecting an efficient QPE approach requires detailed characterizations of the tradeoffs and overheads of these options. In this paper, we explore three different algorithms that trade off trials versus rotations. We perform a detailed characterization of their behavior on two important quantum algorithms (Shor's and GSE). We also develop an analytical model that characterizes the behavior of a range of algorithms in this tradeoff space.