Serologic evidence of previous Campylobacter jejuni infection in patients with the Guillain-Barré syndrome

OBJECTIVE: To determine if patients with the Guillain-Barré syndrome are likely to have had Campylobacter jejuni infection before onset of neurologic symptoms. DESIGN: A case-control study. SETTING: Several university medical centers. PATIENTS: Case patients met clinical criteria for the Guillain-Barré syndrome between 1983 and 1990 and had a serum sample collected and frozen within 3 weeks after onset of neurologic symptoms (n = 118). Disease controls were patients with other neurologic illnesses (n = 56); healthy controls were hospital employees or healthy family members of patients (n = 47). MEASUREMENTS: Serum IgA, IgG, and IgM antibodies to C. jejuni were determined by enzyme-linked immunosorbent assays. Assays were done in a blinded manner. RESULTS: Optical density ratios > or = 2 in two or more immunoglobulin classes were seen in 43 (36%) of patients with the Guillain-Barré syndrome and in 10 (10%) of controls (odds ratio, 5.3; 95% CI, 2.4 to 12.5; P < 0.001). Increasing the optical density ratio or the number of immunoglobulin classes necessary to yield a positive result increased the strength of the association. The number of patients with the Guillain-Barré syndrome who had positive serologic responses was greatest from September to November (P = 0.02). Male patients were three times more likely to have serologic evidence of C. jejuni infection (P = 0.009); the proportion of patients with the syndrome who had a positive serologic response increased with age. CONCLUSIONS: Patients with the Guillain-Barré syndrome are more likely than controls to have serologic evidence of C. jejuni infection in the weeks before onset of neurologic symptoms. Campylobacter jejuni may play a role in the initiation of the Guillain-Barré syndrome in many patients.     

Automatic Channel Detection Using DNN on 2D Seismic Data

Geologists interpret seismic data to understand subsurface properties and subsequently to locate underground hydrocarbon resources. Channels are among the most important geological features interpreters analyze to locate petroleum reservoirs. However, manual channel picking is both time consuming and tedious. Moreover, similar to any other process dependent on human intervention, manual channel picking is error prone and inconsistent. To address these issues, automatic channel detection is both necessary and important for efficient and accurate seismic interpretation. Modern systems make use of real-time image processing techniques for different tasks. Automatic channel detection is a combination of different mathematical methods in digital image processing that can identify streaks within the images called channels that are important to the oil companies. In this paper, we propose an innovative automatic channel detection algorithm based on machine learning techniques. The new algorithm can identify channels in seismic data/images fully automatically and tremendously increases the efficiency and accuracy of the interpretation process. The algorithm uses deep neural network to train the classifier with both the channel and non-channel patches. We provide a field data example to demonstrate the performance of the new algorithm. The training phase gave a maximum accuracy of 84.6% for the classifier and it performed even better in the testing phase, giving a maximum accuracy of 90%.     

DeepClassRooms: a deep learning based digital twin framework for on-campus class rooms

Neural Computing and Applications - A lot of different methods are being opted for improving the educational standards through monitoring of the classrooms. The developed world uses Smart...     

Coordinated controller tuning of a boiler turbine unit with new binary particle swarm optimization algorithm

Coordinated controller tuning of the boiler turbine unit is a challenging task due to the nonlinear and coupling characteristics of the system. In this paper, a new variant of binary particle swarm optimization (PSO) algorithm, called probability based binary PSO (PBPSO), is presented to tune the parameters of a coordinated controller. The simulation results show that PBPSO can effectively optimize the control parameters and achieves better control performance than those based on standard discrete binary PSO, modified binary PSO, and standard continuous PSO.     

Light microscopy of Pakistani Berberis leaf cuticles and its taxonomic implications

Taxonomy of the genus Berberis is quite complex, due to overlapping morphological characters, making it very difficult to differentiate the species within the genus. In order to resolve this taxonomic complexity, the foliar anatomy of 10 Berberis L. species was carried out, for the first time from Pakistan, using light microscopy (LM). Significant variation in terms of epidermal cells shape, size, cell wall pattern, and stomata type was observed. B. baluchistanica has the largest epidermal cells, Adaxial: length = 45–(53.9 ± 3.6)–62.5 μm; and width = 22.5–(26.3 ± 1.3)–30 μm; Abaxial: length = 37.5–(43.25 ± 2.5)–50 μm; and width = 20–(22.6 ± 0.8)–25. The highest number of stomata was observed in B. glaucocarpa as 62 on the abaxial surface while the lowest number of stomata was recorded in B. baluchistanica as 8 on the adaxial surface. Of 10 investigated species, 6 possess anomocytic type stomata, while 2 species that is, B. aitchisonii and B. parkeriana have both anomocytic and anisocytic stomata while B. baluchistanica and B. calliobotrys have only paracytic type stomata. The highest number of cells per unit area was present on the adaxial surface of B. calliobotrys ranging from 245–(252.4)–260 followed by B. parkeriana with 209–(227.8)–250 on the abaxial surface. Stomatal index (SI) also varied considerably and was the lowest (2.6) percentage in B. baluchistanica and highest (31.9) percentage in B. kunawurensis. A taxonomic key based on micro‐morphological characters is provided for species identification.     

Molecular dynamics simulation of compressible hot/cold moving lid-driven microcavity flow

Hard-sphere molecular dynamics simulations of lid-driven microcavity gas flow with various subsonic speeds and lid temperatures are conducted. Simulations with faster and colder lids show streamlines of stronger primary vortices. Variations of mass and energy centers with respect to lid speed and temperature are examined. Center of energy is less sensitive to employed lid conditions than center of gravity is. Although moving lid imparts energy into fluid, due to change of impingement rates on the walls of fixed temperature, average energy within the cavity seems quite insensitive to the subsonic lid speed. Behavior of compressibility at both top corners is observed even at low Mach numbers widely considered within incompressible flow region. While high Knudsen number causes considerable property slips near the lid, two-dimensional pressure, density, and temperature plots of excellent quality are generated. Results are promising in use of molecular dynamics simulations for compressible vortex flow analyses while providing insights for understanding microfluidics and nanofluidics in context of molecular mass, momentum and heat transfer in microscale and nanoscale systems.     

Glyceride studies. Part IV. The component glycerides of ten seed oils containing linoleic acid

The component glycerides of ten seed oils (safflower, tobacco, sunflower,Argemone mexicana, maize, cotton, groundnut,Macadamia ternifolia, Gmelina asiatica, andMadhuca latifolia) have been estimated by chromatographic procedures. The results agree with those obtained by lipolysis or calculated directly from the component acids on the basis of the theory of positional distribution.     

Header Detection to Improve Multimedia Quality Over Wireless Networks

Wireless multimedia studies have revealed that forward error correction (FEC) on corrupted packets yields better bandwidth utilization and lower delay than retransmissions. To facilitate FEC-based recovery, corrupted packets should not be dropped so that maximum number of packets is relayed to a wireless receiver's FEC decoder. Previous studies proposed to mitigate wireless packet drops by a partial checksum that ignored payload errors. Such schemes require modifications to both transmitters and receivers, and incur packet-losses due to header errors. In this paper, we introduce a receiver-based scheme which uses the history of active multimedia sessions to detect transmitted values of corrupted packet headers, thereby improving wireless multimedia throughput. Header detection is posed as the decision-theoretic problem of multihypothesis detection of known parameters in noise. Performance of the proposed scheme is evaluated using trace-driven video simulations on an 802.11b local area network. We show that header detection with application layer FEC provides significant throughput and video quality improvements over the conventional UDP/IP/802.11 protocol stack     

A recursive algorithm for solving “a secret sharing” problem

Abstract

This paper presents a recursive algorithm for solving “a secret sharing” problem. This problem is one of the unsolved problems in the Second International Students Olympiad in Cryptography (NSUCRYPTO2015). Recently, Geut et al. solved the problem in a special case. We show that our algorithm is able to solve it in general.