Miracle-dz/UniFAR-FTUs huggingface dataset:
Initial stage of genetic mapping in Ciona intestinalis

The use of classic genetics is emerging in the ascidian Ciona intestinalis; recent advances in genomics and high‐quality developmental and evolutionary studies have made this animal an attractive model for research purposes. Genetic mapping in Ciona will likely make a major contribution to ascidian genomics and developmental biology by providing support for genome assembly and annotation and for the isolation of genes with particular mutations, while construction of genetic maps advances classic genetics in this species. Two major issues must be overcome before fine genetic maps can be constructed: the choice of proper genetic backgrounds and the establishment of laboratory strains. A high degree of polymorphism is useful for genetic mapping if we consider particular combinations of genetic backgrounds and techniques, although it is necessary to pay attention to the confused classification of C. intestinalis. Thus, it is preferred to establish laboratory strains instead of using samples with various genetic backgrounds. As these issues are unresolved, only amplified fragment length polymorphism–based maps have been created, while bulk segregant analysis is expected to isolate markers flanking mutant loci. However, rich genomic resources should facilitate the next stage of genetic map construction based on type I markers using coding sequences. The meiotic events that occur in crossing experiments for mapping purposes should shed light on population genetics and speciation issues. The results of such investigations may provide feedback for comparative genomics and developmental genetics in the near future. Developmental Dynamics 236:1768–1781, 2007. © 2007 Wiley‐Liss, Inc.
FR-4 Embedded Wideband Micro-Balun with Coupled LC Resonators

In this paper, a compact wideband balun has been newly designed and fabricated by using magnetically coupled LC resonators. The proposed balun was comprised of two pairs of magnetic coupled LC resonators which share one resonator with each other. The balun was specially designed in order to obtain precise phase difference, identical magnitude, and DC isolation characteristics between two balanced ports with impedance transformation. It was fabricated by embedding high Q spiral inductors and BTO MIM capacitors into a multi-layered FR-4 packaging substrate. The fabricated balun showed excellent phase and magnitude imbalanced characteristics. The measured results were an maximum insertion loss of 1.4 dB, a minimum return loss of 10 dB, a phase imbalance of 5 degree, and magnitude imbalance of 0.7 dB at wide frequency bandwidth of 1 GHz ranged from 1.6 GHz to 2.6 GHz, respectively. The measured results were well agreed with the simulated ones.
Web Form Page in Mobile Devices - Optimization of Layout with a Simple Genetic Algorithm

Filling out a form on mobile devices is generally harder than on other terminals, due to the reduced keyboard and display size, entailing a higher fatigue and limiting the user experience. A solution to this problem can be based on reducing the input effort required to the user by auto-completion, and re-organizing the fields in order to provide first those with a higher prediction power. In this paper we assume to be able to predict the user input and we optimize the fields layout aiming at reducing on average the input actions.
A novel large-memory neural network as an aid in medical diagnosis applications

Describes the application of a LAMSTAR (LArge Memory STorage And Retrieval) neural network to medical diagnosis and medical information retrieval problems. The network is based on M.L. Minsky's (1980) knowledge lines (k-lines) theory of memory storage and retrieval in the central nervous system. It employs arrays of self-organized map modules, such that the k-lines are implemented via link weights (address correlation) that are updated by learning. The network also employs features of forgetting and of interpolation and extrapolation, and is thus able to handle incomplete data sets. It can deal equally well with exact and fuzzy information, thus making it specifically applicable to medical diagnosis where the diagnosis is based on exact data, fuzzy patient interview information, patient histories, observed images and test records. Furthermore, the network can be operated in a closed loop with search engines to intelligently use data from the Internet in a higher learning hierarchy. All of the above features are shown to make the LAMSTAR network suitable for medical diagnosis problems that concern large data sets of many categories that are often incomplete and fuzzy. Applications of the network to three specific medical diagnosis problems are described: two from nephrology and one related to an emergency-room drug identification problem. It is shown that the LAMSTAR network is hundreds, and even thousands, times faster in its training than backpropagation-based networks when used for the same problem with exactly the same information.
Lossless Compression of Chemical Fingerprints Using Integer Entropy Codes Improves Storage and Retrieval

Many modern chemoinformatics systems for small molecules rely on large fingerprint vector representations, where the components of the vector record the presence or number of occurrences in the molecular graphs of particular combinatorial features, such as labeled paths or labeled trees. These large fingerprint vectors are often compressed to much shorter fingerprint vectors using a lossy compression scheme based on a simple modulo procedure. Here, we combine statistical models of fingerprints with integer entropy codes, such as Golomb and Elias codes, to encode the indices or the run lengths of the fingerprints. After reordering the fingerprint components by decreasing frequency order, the indices are monotone-increasing and the run lengths are quasi-monotone-increasing, and both exhibit power-law distribution trends. We take advantage of these statistical properties to derive new efficient, lossless, compression algorithms for monotone integer sequences: monotone value (MOV) coding and monotone length (MOL) coding. In contrast to lossy systems that use 1024 or more bits of storage per molecule, we can achieve lossless compression of long chemical fingerprints based on circular substructures in slightly over 300 bits per molecule, close to the Shannon entropy limit, using a MOL Elias Gamma code for run lengths. The improvement in storage comes at a modest computational cost. Furthermore, because the compression is lossless, uncompressed similarity (e.g., Tanimoto) between molecules can be computed exactly from their compressed representations, leading to significant improvements in retrival performance, as shown on six benchmark data sets of druglike molecules.
A 30-year journey in hip fracture care. An evaluation of how care process development affect lead-times and outcome.

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Prevalence of dementia subtypes in a developing country: a clinicopathological study

OBJECTIVES: To assess the distribution of dementia subtypes in Brazil using a population-based clinicopathological study. METHOD: Brains from deceased individuals aged ≥50 years old were collected after the next of kin signed an informed consent form and provided information through standardized questionnaires. Post-mortem clinical diagnoses were established in consensus meetings, and only cases with moderate or severe dementia or without cognitive impairment were included in the analysis. Immunohistochemical neuropathological examinations were performed following the universally accepted guidelines. A diagnosis of Alzheimer's disease was made when there were at least both a moderate density of neuritic plaques (Consortium to Establish a Register for Alzheimer's disease B or C) and Braak stage III for neurofibrillary tangle distribution. For the diagnosis of vascular dementia, at least three zones or strategic areas had to be affected by infarcts, lacunae, or microinfarcts. RESULTS: From 1,291 subjects, 113 cases were classified as having moderate or severe dementia, and 972 cases were free of cognitive impairment. The neuropathological diagnoses of the dementia sub-group were Alzheimer's disease (35.4%), vascular dementia (21.2%), Alzheimer's disease plus vascular dementia (13.3%), and other causes of dementia (30.1%). Small-vessel disease, which alone was not considered sufficient for a vascular dementia diagnosis, was present in 38.9% of all of the dementia cases and in 16.8% of the group without cognitive impairment (odds ratio = 2.91; 95% confidence interval, 1.53-5.51), adjusted for age, sex, and education. CONCLUSIONS: The relatively high frequencies of vascular dementia and small-vessel disease in the dementia sub-group constitute relevant findings for public health initiatives because control of vascular risk factors could decrease the prevalence of dementia in developing countries.
An energy-efficient matrix multiplication accelerator by distributed in-memory computing on binary RRAM crossbar

Emerging resistive random-access memory (RRAM) can provide non-volatile memory storage but also intrinsic logic for matrix-vector multiplication, which is ideal for low-power and high-throughput data analytics accelerator performed in memory. However, the existing RRAM-based computing device is mainly assumed on a multi-level analog computing, whose result is sensitive to process non-uniformity as well as additional AD- conversion and I/O overhead. This paper explores the data analytics accelerator on binary RRAM-crossbar. Accordingly, one distributed in-memory computing architecture is proposed with design of according component and control protocol. Both memory array and logic accelerator can be implemented by RRAM-crossbar purely in binary, where logic-memory pairs can be distributed with protocol of control bus. Based on numerical results for fingerprint matching that is mapped on the proposed RRAM-crossbar, the proposed architecture has shown 2.86x faster speed, 154x better energy efficiency, and 100x smaller area when compared to the same design by CMOS-based ASIC.
Mining of Concurrent Text and Time Series

ABSTRACT We present a unique approa h to identifying news stories that in uen e the behavior of nan ial markets. We des ribe the design and implementation of nalyst, a system for predi ting trends in sto k pri es based on the ontent of news stories that pre ede the trends. We identify trends in time series using pie ewise linear tting and then assign labels to the trends a ording to an automated binning pro edure. We use language models to represent patterns of language that are highly asso iated with parti ular labeled trends. nalyst an then identify news stories that are highly indi ative of future trends. We evaluate the system in terms of its ability to predi t forth oming trends in the sto k pri es. We perform a market simulation, demonstrating that nalyst is apable of produ ing pro ts that are signi antly higher than random.
Improving self-organizing map with nguyen-widrow initialization lgorithm

The quality of cluster result and the learning speed of Self-organizing map (SOM) are dependent on the initialization of weights since the initial values for weight vectors affect the performance of SOM training when applied to clustering. In this paper, improvement of SOM was achieved with the application of the Nguyen-Widrow algorithm to initialize weights. Nguyen-Widrow initialization algorithm is a method for initialization of the weights of neural networks to speed up the training process. Performance of the modified SOM was determined in terms of cluster error rate and the number of iterations to achieve convergence using different datasets and results show that the modified SOM algorithm produces better cluster results and improved training speed compared to traditional SOM.
Design and implementation of automatic QoS measure framework for web services

Currently, many research efforts on Web services are made based on QoS attributes. However, user-side QoS data is not easily acquired since it relies heavily on user location and network status, and is dynamically changing from time to time. Aiming at measuring user-side QoS, the architecture of a QoS measure framework (QoS4WS) is introduced in this paper, which measures QoS for world-wide Web services with real invocations from different geographic regions periodically. When user-side QoS is to be acquired, a predication procedure which is based on a network coordination approach is executed to calculate real-time user-side QoS. With this framework, a more accurate user-side QoS can be measured automatically. Experiment results show that our framework can get a near-accurate user-side QoS.
HDRFusion: HDR SLAM Using a Low-Cost Auto-Exposure RGB-D Sensor

Most dense RGB/RGB-D SLAM systems require the brightness of 3-D points observed from different viewpoints to be constant. However, in reality, this assumption is difficult to meet even when the surface is Lambertian and illumination is static. One cause is that most cameras automatically tune exposure to adapt to the wide dynamic range of scene radiance, violating the brightness assumption. We describe a novel system - HDRFusion - which turns this apparent drawback into an advantage by fusing LDR frames into an HDR textured volume using a standard RGB-D sensor with auto-exposure (AE) enabled. The key contribution is the use of a normalised metric for frame alignment which is invariant to changes in exposure time. This enables robust tracking in frame-to-model mode and also compensates the exposure accurately so that HDR texture, free of artefacts, can be generated online. We demonstrate that the tracking robustness and accuracy is greatly improved by the approach and that radiance maps can be generated with far greater dynamic range of scene radiance.
Task-dependent force sharing between muscle synergists during locomotion in turkeys

SUMMARY At most joints, there is a redundancy of muscle function. For any given movement, there are a wide range of possible solutions to the problem of how force is shared among muscle synergists. A better understanding of how force is shared among muscle synergists can provide insight into the mechanics and control of movement. We examined force sharing in the gastrocnemius of wild turkeys (Meleagris gallopavo), using strain gauges bonded to bony tendons. Force was measured separately in the lateral (LG) and medial (MG) heads of the gastrocnemius, to evaluate force sharing. We also used inverse dynamics to determine the total force required during swing phase. To determine whether the pattern of force sharing varied depending on the mechanical task, we used running speed (1 to 3.5 m s–1) and limb loading (30 and 60 g added tarsometatarsal mass) to vary the force required at the intertarsal joint. We found that the distribution of force between these two heads varied depending on the phase of the stride cycle. During stance, force was shared in near equal amounts between the two heads and this distribution was unaffected by changes in running speed or limb load. During swing phase, however, there was no force sharing. Force was produced only in the lateral head, and this force was not significantly different from the total force required, as calculated from inverse dynamics. Thus, the LG produced all of the force required for limb extension during swing. This change in the pattern of force sharing between stance and swing supports the theory that force sharing between muscle synergists is task-dependent.
Racial differences in the association between optic disc topography and early glaucoma.

PURPOSE To determine the structural characteristics of the optic disc that are associated with early glaucoma in African Americans and whites and whether these characteristics differ between the races. METHODS Parameters of optic disc topography from 260 African American eyes and 193 white eyes were included in the analysis. One hundred forty-four eyes of African Americans and 109 eyes of normal white subjects were used as a control group. Logistic regression was used to calculate the association between early glaucoma, defined by the visual field, and cup, rim, and disc margin confocal scanning laser ophthalmoscopic (CSLO) parameters, using odds ratios at binary cut points. The cup, rim, and disc margin parameters identified as being independently associated with glaucoma in these reduced models were then included in a single multivariate model. Optic disc area was included in the analysis at each level of the model. This approach was used for the total study group and then separately for the African American and white groups. RESULTS When accounting for difference in optic disc area, rim area had the highest independent association with early glaucoma in both groups, but this association was lower in African Americans (odds ratio [95% confidence interval]: 1.63 [1.12-2.36]) than in whites (odds ratio: 4.74 [2.18-10.28]). Additional independently associated parameters included cup shape, maximum elevation along the contour line, and the temporal-to-inferior contour line modulation ratio in whites and cup shape and the temporal-to-superior contour line modulation ratio in African Americans. CONCLUSIONS Structural characteristics of the optic disc that are best associated with early glaucoma included cup shape and rim area in both groups, but with a less pronounced association in African Americans. In addition, several other race-specific parameters that were independently associated with early glaucoma differed significantly between African Americans and whites. These race-specific differences were independent from the effect of optic disc area.
Tight lower bounds on the ergodic capacity of Rayleigh fading MIMO channels

We consider Gaussian multiple-input multiple-output (MIMO) fading channels assuming that the channel is unknown at the transmitter and perfectly known at the receiver. Using results from multivariate statistics, we derive a tight closed-form lower-bound for the ergodic capacity of such channels at any signal-to-noise ratio (SNR). Moreover, we provide an accurate closed-form analytical approximation of ergodic capacity in the high SNR regime. Our analysis incorporates the frequency-selective Rayleigh fading case and/or spatial fading correlation, and allows Important Insights Into optimal (ergodic capacity maximizing) MIMO configurations. Finally, we verify our analytical expressions through comparison with numerical results.
Non-Cooperative Inter-Cell Interference Coordination Technique for Increasing Throughput Fairness in LTE Networks

One major concern for operators of Long Term Evolution (LTE) networks is mitigating inter-cell interference problems. Inter-Cell Interference Coordination (ICIC) techniques are proposed to reduce performance degradation and to maximize system capacity. It is a joint resource allocation and power allocation problem that aims at controlling the trade-off between resource efficiency and user fairness. Traditional interference mitigation techniques are Fractional Frequency Reuse (FFR) and Soft Frequency Reuse (SFR). FFR statically divides the available spectrum into reuse-1 and reuse-3 portions in order to protect cell-edge users, while SFR reduces downlink transmission power allocated for cell-center resources to protect vulnerable users in the neighboring cells. However, these static techniques are not adapted to non-uniform user distribution scenarios, and they do not provide guarantees on throughput fairness between user equipments. In this paper, we introduce a non-cooperative dynamic ICIC technique that dynamically adjusts resource block allocation according to user demands in each zone. We investigate the impact of this technique on throughput distribution and user fairness under non-uniform user distributions, using an LTE downlink system level simulator. Simulation results show that the proposed technique improves system capacity, and increases throughput fairness in comparison with reuse-1 model, FFR and SFR. It does not require any cooperation between base stations of the LTE network.
Multipath removal by online blind deconvolution in through-the-wall-imaging

In this paper, we propose an online radar imaging scheme that recovers a sparse scene and removes the multipath ringing induced by the front wall in a Through-the-Wall-Imaging (TWI) system without prior knowledge of the wall parameters. Our approach uses online measurements obtained from individual transmitter-receiver pairs to incrementally build the primary response of targets behind the front wall and find a corresponding delay convolution operator that generates the multi-path reflections available in the received signal. In order to perform online sparse imaging while removing wall clutter reflections, we developed a deconvolution extension of the Sparse Randomized Kaczmarz (SRK) algorithm that finds sparse solutions to under- and over-determined linear systems of equations. Our scheme allows for imaging with nonuniformly spaced antennas by building an explicit delay-and-sum imaging operator for each new measurement. Moreover, the active memory requirements remain small even for large scale MIMO systems since the imaging operators are only constructed for individual transmitter-receiver pairs. We test our approach on a simple FDTD simulated room with internal targets and demonstrate that our method successfully eliminates multipath reflections while correctly locating the targets.
Bijective Deformations in Rn via Integral Curve Coordinates

We introduce Integral Curve Coordinates, which identify each point in a bounded domain with a parameter along an integral curve of the gradient of a function f on that domain; suitable functions have exactly one critical point, a maximum, in the domain, and the gradient of the function on the boundary points inward. Because every integral curve intersects the boundary exactly once, Integral Curve Coordinates provide a natural bijective mapping from one domain to another given a bijection of the boundary. Our approach can be applied to shapes in any dimension, provided that the boundary of the shape (or cage) is topologically equivalent to an n-sphere. We present a simple algorithm for generating a suitable function space for f in any dimension. We demonstrate our approach in 2D and describe a practical (simple and robust) algorithm for tracing integral curves on a (piecewise-linear) triangulated regular grid.