Miracle-dz/UniFAR-FTUs huggingface dataset:
Usefulness and Accuracy of Arthrography in Management of Lateral Humeral Condyle Fractures in Children

Summary: The value of arthrography in children's fractures is well established, but the accuracy of this technique has not been reported. We assessed the usefulness of arthrography by performing this test on a series of lateral humeral condyle fractures and, when possible, compared the arthrographic findings with the findings at operation to assess the accuracy of the test. Twenty-four consecutive patients were evaluated, and 13 patients underwent both arthrography and open reduction. We conclude that arthrography is a useful and accurate test when performed on children with lateral humeral condyle fractures and have provided guidelines for its use in managing this problem.
D-dimer for prediction of long-term outcome in cryptogenic stroke patients with patent foramen ovale

Summary Patent foramen ovale (PFO) is a potential cause of cryptogenic stroke, given the possibility of paradoxical embolism from venous to systemic circulation. D-dimer level is used to screen venous thrombosis. We investigated the risk of embolism and mortality according to the presence of PFO and D-dimer levels in cryptogenic stroke patients. A total of 570 first-ever cryptogenic stroke patients who underwent transesophageal echocardiography were included in this study. D-dimer was assessed using latex agglutination assay during admission. The association of long-term outcomes with the presence of PFO and D-dimer levels was investigated. PFO was detected in 241 patients (42.3 %). During a mean 34.0 ± 22.8 months of follow-up, all-cause death occurred in 58 (10.2 %) patients, ischaemic stroke in 33 (5.8 %), and pulmonary thromboembolism in 6 (1.1 %). Multivariate Cox regression analysis showed that a D-dimer level of > 1,000 ng/ml was an independent predictor for recurrent ischaemic stroke in patients with PFO (hazard ratio 5.341, 95 % confidence interval 1.648–17.309, p=0.005), but not in those without PFO. However, in patients without PFO, a D-dimer level of > 1,000 ng/ml was independently related with all-cause mortality. The risk of pulmonary thromboembolism tended to be high in patients with high D-dimer levels, regardless of PFO. Elevated D-dimer levels in cryptogenic stroke were predictive of the long-term outcome, which differed according to the presence of PFO. The coexistence of PFO and a high D-dimer level increased the risk of recurrent ischaemic stroke. The D-dimer test in cryptogenic stroke patients may be useful for predicting outcomes and deciding treatment strategy.
A VCF Loss-Control Tuning Loop for$Q$-Enhanced LC Filters

A loss-control tuning loop for Q-enhanced LC filters based on a voltage-controlled filter (VCF) is presented. The main factors affecting the tuning accuracy in this tuning scheme, including mismatches and frequency tuning errors, are discussed. The tuning scheme was implemented for a 1.5-V, 6-GHz Q-enhanced LC filter on a UMC 0.18-mum standard CMOS process. The design and measurement results are given. Effective loss control of the filter over process tolerances is demonstrated
Simulation of automobile airbag ignition based on BP neural network

For the control of automobile airbag ignition, this paper focused on algorithms based on BP neural network. First, some common airbag ignition algorithms and their deficiencies were introduced, and then algorithms based on BP neural network were discussed. The main design and simulation were introduced, and the results show that the algorithm based on BP neural network is a good solution.
Expression of Sucrose Transporter cDNAs Specifically in Companion Cells Enhances Phloem Loading and Long-Distance Transport of Sucrose but Leads to an Inhibition of Growth and the Perception of a Phosphate Limitation1[W][OPEN]

Increased expression of selected sucrose/proton symporters above wild-type levels in phloem companion cells enhanced phloem loading and long-distant transport but unexpectedly resulted in an inhibition of growth that is associated with perception of a phosphate limitation. Sucrose (Suc) is the predominant form of carbon transported through the phloem from source to sink organs and is also a prominent sugar for short-distance transport. In all streptophytes analyzed, Suc transporter genes (SUTs or SUCs) form small families, with different subgroups evolving distinct functions. To gain insight into their capacity for moving Suc in planta, representative members of each clade were first expressed specifically in companion cells of Arabidopsis (Arabidopsis thaliana) and tested for their ability to rescue the phloem-loading defect caused by the Suc transporter mutation, Atsuc2-4. Sequence similarity was a poor indicator of ability: Several genes with high homology to AtSUC2, some of which have phloem-loading functions in other eudicot species, did not rescue the Atsuc2-4 mutation, whereas a more distantly related gene, ZmSUT1 from the monocot Zea mays, did restore phloem loading. Transporter complementary DNAs were also expressed in the companion cells of wild-type Arabidopsis, with the aim of increasing productivity by enhancing Suc transport to growing sink organs and reducing Suc-mediated feedback inhibition on photosynthesis. Although enhanced Suc loading and long-distance transport was achieved, growth was diminished. This growth inhibition was accompanied by increased expression of phosphate (P) starvation-induced genes and was reversed by providing a higher supply of external P. These experiments suggest that efforts to increase productivity by enhancing sugar transport may disrupt the carbon-to-P homeostasis. A model for how the plant perceives and responds to changes in the carbon-to-P balance is presented.
Isolation and Identification of Kroppenstedtia eburnea Isolates from Multiple Patient Samples

ABSTRACT No clinical isolates have been reported for the recently described thermoactinomycete Kroppenstedtia eburnea. Between 2006 and 2011, we obtained 14 clinical isolates from patients in 9 U.S. states. Here we report growth characteristics, 16S rRNA gene sequencing, matrix-assisted laser desorption ionization–time of flight (MALDI-TOF) mass spectrometry-based identification, and antimicrobial susceptibility profiles of this recently described organism.
IoT based smart energy meter monitoring and controlling system

In recent scenario, energy saving holds prime significance because of inequality between demand and power generation. Using Wi-Fi module entire system will be controlled. Internet of Thing (IoT) is internally related to computing tricks transferring the data under the network with no any help of a human to human or human to computer interrelation. The load to the consumer is to consume regularly with regular monthly payment of the bill. When the electricity bill is paid then the supply will continuously flow or provides.
Plantlet Regeneration from Taro (Colocasia esculenta Schott) Callus

Taro (Colocasia esculenta) callus was induced from shoot tip explants on a modified Nitsch medium supplemented with 2, 4-dichlorophenoxyacetic acid (2, 4-D) and 6-benzyladenine (BA) at 1 mg•liter-1 each. The effect of agar concentration (0, 0.2, 0.4, 0.6, 0.8%, W/V) in a modified Murashige and Skoog (MS) medium on the regeneration of shoots from taro callus was investigated. Shoot differentiation was observed only in 0.2, 0.4 and 0.6% agar concentrations. A high level of shoot differentiation at 64% was measured on 0.6% agar medium. However, root differentiation was observed regardless of agar concentrations.Shoot differentiation was observed on the medium supplemented with 1 mg•liter-1 BA as early as 10 weeks of culture.Addition of 0.1% (W/V) charcoal did not directly induce the regeneration of shoots from the callus, but lengthened the longetivity of the calli since no necrosis was observed after 20 weeks of culture.Proliferation of regenerated shoots was enhanced with the addition of naphthalene acetic acid (NAA) and BA at 1 mg•liter-1 each. The plantlets can be readily potted in a vermiculite medium for acclimatization before planting in the field.
Influence of long‐range‐transported pollution on the annual and diurnal cycles of carbon monoxide and ozone at Cheeka Peak Observatory

[1] We assess the importance of distant pollution sources on the marine background by combining measurements of carbon monoxide (CO) and ozone (O3) with model simulations from the GEOS-CHEM chemical transport model and two types of back trajectories. Measurements were made over a complete annual cycle from March 2001 to May 2002 at Cheeka Peak Observatory (CPO) in Washington State. Data from an earlier campaign (March–April 1997 and 1998) were also incorporated. The seasonal cycles of CO and O3 show a spring maximum and a summer minimum, consistent with other remote sites in the marine boundary layer. European and Asian pollution emission sources of CO, parameterized by GEOS-CHEM, were grouped into one category called “LRT,” representing “long-range transport. ” LRT values produced good correlations with measured CO (monthly averaged r = 0.60, 6-hour averages) and were found to comprise between 15 and 60% of total CO, with higher values in winter/spring and lower values in the summer/fall. CO and O3 observations were classified on the basis of these LRT values, creating two general categories: “more polluted” (LRT > 75th percentile from monthly distribution) and “less polluted” (LRT 75% percentile) were observed throughout the year. Ozone behavior was quite complicated during these events, producing no consistent enhancements. Classification of the measurements with LRT values from GEOS-CHEM is compared to back trajectories, both isentropic and kinematic. Isentropic trajectories agree reasonably well with GEOS-CHEM between February and May in capturing the CO enhancements in air masses influenced by recent emissions but were found to be less useful from June to January. HYSPLIT kinematic trajectories were slightly better at capturing the Asian pollution events than isentropic trajectories but still missed an event during the summer completely that was verified by GEOS-CHEM. Possible reasons for poor trajectory performance in the summer and fall are discussed. Long-range transport appears not to affect the magnitude of the diurnal variability of O3 measurements at CPO, which reflect daytime production of 2–4 ppbv/d. Rather, ship traffic in the vicinity of CPO, which supplies NOx through combustion, likely plays a dominant role.
INCREMENTAL NEURAL LEARNING BY DYNAMIC AND SPATIAL CHANGING WEIGHTS

Abstract In this paper a new neural network model is presented for incremental learning tasks where networks are required to learn new knowledge without forgetting the old one. An essential core of the proposed neural network structure is their dynamic and spatial changing connection weights (DSCWs). A learning scheme is developed for the formulation of the dynamic changing weights, while a structural adaptation is formulated by the spatial changing (growing) connecting weights. To avoid disturbing the past knowledge by the creation of new connections, a restoration mechanism is introduced by using the DSCWs. Usefulness of the proposed model is demonstrated by using a system identification task.
Primary amine coding as a path to comparative proteomics

Various isotope coding strategies are being used today in the field of comparative proteomics. This article specifically reviews the strengths and limitations of various N‐termini‐directing strategies. N‐termini‐directed coding strategy allows for use of different chromatographic enrichment techniques. Since N‐termini‐directed coding strategies are global in nature, they can be utilized in studying PTMs as well as protein expression. Using different N‐termini‐directed coding strategies, both relative and absolute quantification of proteins can be achieved either in the MS mode or in the MS/MS mode. The review ends with the conclusion that significant improvements have been made in the last decade. Among various issues, a need still exists for a better understanding of the kinetic issues in proteomics, relative protein pool sizes for different proteins and the issue of stimulus‐induced changes in protein aggregation. Another critical issue that needs to be addressed in great detail is the role of PTMs in regulation.
Development of a hall-effect based skin sensor

In this paper we introduce a prototype of a novel hall-effect based skin sensor for robotic applications. It uses a small sized chip that provides 3-axis digital output in a compact package. Our purpose was to evaluate the feasibility of measuring 3-axis force while maintain a soft exterior for safe interactions. Silicone was used to produce the soft skin layer with about 8 mm thickness. An MLX90393 chip was installed at the bottom of layer, with a small magnet approximately 5mm above it to measure 3-axial magnetic field data. To evaluate the sensor's performance, an experiment was conducted by measuring normal and shear force when applying total forces of 0.7-14N in the normal and tangential directions of the sensor. The test revealed that the sensor prototype was able to differentiate the components of the force vector, with limited crosstalk. A calibration was performed to convert the measurements of the magnetic field to force values.
MPR-based hybrid routing for mobile ad-hoc networks

This paper describes the design and performance of a routing protocol for mobile ad-hoc networks. Our routing protocol is named "hybrid routing" in that it attempts to take advantage of both proactive and reactive approaches. The protocol is based on the concept of multipoint relaying (MPR) to minimize flooding traffic. For most applications over mobile ad-hoc networks, it is expected that a major portion of communication will be done in the two-hop region. Therefore, when a node needs a route to a destination in the two-hop region, it consults with the routing table as the proactive approach to find the route directly. Outside this region, on the other hand, it discovers a route on demand as the reactive approach through the use of MPR flooding. The proposed protocol has been validated using the ns network simulator with wireless and mobility extensions. The simulation results show that our MPR-HR protocol provides higher efficiency in terms of routing overhead compared to AODV one of the most efficient routing protocols released for mobile ad-hoc networks.
A log-structured buffer for database systems using non-volatile memory

Emerging next-generation non-volatile memory (NVM) technologies, including PCM and STT-MRAM, provide low latency, high bandwidth, non-volatility, and high capacity. Recently, NVM has drawn much attention from the database community to improve transaction processing (e.g., write-ahead logging). As a complement to existing work, we investigate NVM for atomic page updates in database systems. Atomic page update is required for consistent recovery, and database systems generally use redundant writes to support atomic page update (e.g., doublewrite buffer in MySQL/InnoDB). However, redundant writes negatively affect the database and lifetime of storage devices (e.g., flash-based SSD). In this paper, we present LSBM, a log-structured buffer manager which updates pages atomically and efficiently using NVM. LSBM updates pages in an out-of-place manner to achieve atomicity and performs page buffering to improve performance. LSBM also reclaims the buffered pages on the fly to reduce the write traffic to storage. We implement LSBM using an NVDIMM as NVM and ported it to MySQL/InnoDB. The experimental results demonstrate that LSBM improves database performance and reduces write traffic on OLTP workloads.
Ambient Occlusion and Real-time Shadows for Particle Data

Datasets of molecules or particles are commonly visualized by rendering a sphere for every present particle. It is necessary to aid the human perception when such a dataset is to be examined, since depth perception is lost without providing effects such as ambient occlusion or shadows. In this work, we present mechanisms that attempt to provide such effects with high quality without compromising interactive frame rates even in large datasets. Additionally, to reduce noise caused by heavily varying surface normals, normal approximation is deployed.
Resource management in differentiated services: a prototype implementation

The wide deployment of IP technologies has driven the development of IP-based solutions for wireless networks, like the IP-based radio access networks (RAN). Such wireless networks have different characteristics than traditional IP networks, imposing very strict requirements on quality of service (QoS) solutions. Current QoS solutions are not able to satisfy these requirements. This paper describes the prototype implementation of a QoS-framework, called resource management in differentiated services (RMD), which aims to correct this situation. RMD is a framework offering scalable fine-grained QoS guarantees in differentiated services (DiffServ) networks. It extends the DiffServ architecture with new admission control and resource reservation concepts in a scalable way.
Periodicity analysis of charging behavior of electric car drivers : latent class hazard models

The importance of public charging infrastructure has been recognised recently as it represents a key factor in the promotion of plug-in electric vehicles (PEV). Given that a large initial investment from the public sector is essential for its widespread adoption, many studies have focused on the issue how the charging infrastructure should be planned and located. Although it is of critical importance to understand PEV users' charging behavior for improving public charging infrastructure, relatively few number of PEVs makes it difficult to analyze charging behavior of large sample of PEV users. This study uses a Dutch four-year comprehensive charging transaction dataset. Given that electric vehicle users likely exhibit heterogeneous charging behavior in terms of both charging frequency (time interval between successive charging events) and charging regularity (regular charging versus ad-hoc charging), this study applies a heterogeneous hazard-based duration model to examine how often PEV users charge their car at public charging stations and to distinguish the difference characteristics of random (erratic) users and regular (routine) users. The results show that 67 per cent of PEV users charge their car at irregular intervals, while 33 per cent charge regularly. It is also shown that regular users charge their PEV more often and are more likely to have a battery electric vehicle (BEV) compared to random users. Moreover, clear differences exist between the two groups in terms of vehicle and charging characteristics.
Detecting and Grouping Identical Objects for Region Proposal and Classification

Often multiple instances of an object occur in the same scene, for example in a warehouse. Unsupervised multi-instance object discovery algorithms are able to detect and identify such objects. We use such an algorithm to provide object proposals to a convolutional neural network (CNN) based classifier. This results in fewer regions to evaluate, compared to traditional region proposal algorithms. Additionally, it enables using the joint probability of multiple instances of an object, resulting in improved classification accuracy. The proposed technique can also split a single class into multiple sub-classes corresponding to the different object types, enabling hierarchical classification.
Sentiment diffusion in large scale social networks

Popularity of online social networks provides the chance to make sentiment analysis on every user instead of every document or sentence. And relations between users on social media sites often indicate correlation (negation) between users' opinions. In this work, we study how user's opinion spread in social networks. We employ the data from Tencent.com, the largest social network of China to empirically study the problem. Our work focuses on six different topics including policy, products, brand, sports, movie and politician. We study the distributions of peoples' opinions on different topics and how users' opinions are influenced by those he is following. We propose a graphical model to capture the essence of social network as well as an algorithm to perform semi-supervised learning. The learning algorithm can be used to accurately predict users' sentiment in the social network.
Assessment of housing quality in Ibeju-Lekki peri-urban settlement, Lagos State, Nigeria

This article assesses housing quality in Ibeju-Lekki, a peripheral settlement outside Lagos metropolitan region. Using purposive sampling, 370 housing units from clusters of 16 periurban settlements constituted the sample size. Primary data was sourced through structured questionnaires, interview (with local planning personnel) and observation schedules administered through a field survey. Using Statistical Package for Social Sciences, data analysis was done using descriptive analysis to generate frequencies and percentages on socio-economic profile, neighbourhood quality, locational quality, dwelling quality, and building materials used. Tests of correlation were conducted on the mean of variables of neighbourhood quality, locational quality and building materials, derived through recoding of variables by means of Transform statistical tool, to establish the factors influencing housing quality in the study area. The findings show a significant positive correlation between household income and housing quality. The latter is found to be influenced by respondents’ socio-economic attributes, building materials, neighbourhood quality, and locational quality in the study area. It can be concluded that socio-economic characteristics, predominantly income of households, play a major role in the level of housing quality that can be accessed in the study area. It is, therefore, recommended that the state government and private developers should promote alternative building materials, in order to enhance housing affordability by the low-income group. This will reduce the spread of informal housing development. In addition, the state government should align urban policy to eliminate disparity in infrastructural development which has impacted on poor neighbourhood and locational quality in Lagos peri-urban settlements. Keywords: Dwelling quality, housing quality, locational quality, neighbourhood quality, peri-urban settlements
SINGLE-SEQUENCE PROTEIN SECONDARY STRUCTURE PREDICTION BY NEAREST-NEIGHBOR CLASSIFICATION OF PROTEIN WORDS

Predicting protein secondary structure is the process by which, given a sequence of amino acids as input, the secondary structure class of each position in the sequence is predicted. Our approach is built on the extraction of protein words of a fixed length from protein sequences, followed by nearest-neighbor classification in order to predict the secondary structure class of the middle position in each word. We present a new formulation for learning a distance function on protein words based on position-dependent substitution scores on amino acids. These substitution scores are learned by solving a large linear programming problem on examples of words with known secondary structures. We evaluated this approach by using a database of 5519 proteins with a total amino acid length of approximately 3000000. Presently, a test scheme using words of length 23 achieved a uniform average over word position of 65.2%. The average accuracy for alpha-classified words in the test was 63.1%, for beta-classified words was 56.6%, and for coil classified words was 71.6%.