Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic differentiation of Alaska Chinook salmon: the missing link for migratory studies

Most information about Chinook salmon genetic diversity and life history originates from studies from the West Coast USA, western Canada and southeast Alaska; less is known about Chinook salmon from western and southcentral Alaska drainages. Populations in this large area are genetically distinct from populations to the south and represent an evolutionary legacy of unique genetic, phenotypic and life history diversity. More genetic information is necessary to advance mixed stock analysis applications for studies involving these populations. We assembled a comprehensive, open‐access baseline of 45 single nucleotide polymorphisms (SNPs) from 172 populations ranging from Russia to California. We compare SNP data from representative populations throughout the range with particular emphasis on western and southcentral Alaska. We grouped populations into major lineages based upon genetic and geographic characteristics, evaluated the resolution for identifying the composition of admixtures and performed mixed stock analysis on Chinook salmon caught incidentally in the walleye pollock fishery in the Bering Sea. SNP data reveal complex genetic structure within Alaska and can be used in applications to address not only regional issues, but also migration pathways, bycatch studies on the high seas, and potential changes in the range of the species in response to climate change.
High bandwidth, variable line-size cache architecture for merged DRAM/Logic LSIs

Merged DRAM/logic LSIs could provide high on-chip memory bandwidth by interconnecting logic portions and DRAM with wider on-chip buses. For merged DRAM/logic LSIs with the memory hierarchy including cache memory, we can exploit such high on-chip memory bandwidth by means of replacing a whole cache line (or cache block) at a time on cache misses. This approach tends to increase the cache-line size if we attempt to improve the attainable memory bandwidth. Larger cache lines, however, might worsen the system performance if programs running on the LSIs do not have enough spatial locality of references and cache misses frequently take place. This paper describes a novel cache architecture suitable for merged DRAM/logic LSIs, called variable line-size cache or VLS cache, for resolving the above-mentioned dilemma. The VLS cache can make good use of the high on-chip memory bandwidth by means of larger cache lines and, at the same time, alleviate the negative e ects of larger cache-line size by partitioning each large cache line into multiple sub-lines and allowing every sub-line to work as an independent cache line. The number of sub-lines involved when a cache replacement occurs can be determined depending on the characteristics of programs. This paper also evaluates the cost/performance improvements attainable by the VLS cache and compares it with those of conventional cache architectures. As a result, it is observed that a VLS cache reduces the average memory-access time by 16:4% while it increases the hardware cost by only 13%, compared to a conventional direct-mapped cache with xed 32-byte lines.
Individual identification by gait vibration data transmitted floor

The establishment of variety methods in the individual identification technology is desirable. In this study, it is considered that the method of individual identification from vibration data generated in gait. In the walking motion, the unique information such as the individual's body type and habit is contained. It is assumed that the unique information is reflected in the gait vibration data transmitted in the floor. The potential for application to individual identification is shown by extracting one step and analyzing the unique information from the gait vibration data. The Adaboost method is applied to the extraction of one step of the walking. In order to represent the characteristics of each individual and analyzed using the Principal Component Analysis.
Estimation of speech embedded in a reverberant and noisy environment by independent component analysis and wavelets

In this paper, we develop a system for enhancement of the speech signal with highest energy from a linear convolutive mixture of n statistically independent sound sources recorded by m microphones, where m<n. In this system we use the concept of independent component analysis (ICA) along with adaptive auditory filter banks and pitch tracking. Computer simulations and real-world experiments carried out in an actual room and measured through objective and subjective measures confirm the validity of the proposed algorithm.
Modeling Chinese Painting Images Based on Ontology

Traditional Chinese painting is a unique form of art and highly regarded for its theory, expression and techniques throughout the world. However, popular image processing techniques have little been used in this specific domain. Especially, how to model traditional Chinese painting images based on ontology is a very important and urgent task. In the paper, the characteristics of traditional Chinese painting are analyzed firstly. Then, the process of constructing ontology for traditional Chinese painting is dissertated in details, including how to select appropriate classes and properties in CRM ontology and how to extend them in specific domain. In addition, the framework of retrieval is introduced. Ontology is a good avenue for knowledge sharing and information integration. The work of the paper is very meaning to information standardization in specific Chinese art image domain.
SCORAM: Oblivious RAM for Secure Computation

Oblivious RAMs (ORAMs) have traditionally been measured by their bandwidth overhead and client storage. We observe that when using ORAMs to build secure computation protocols for RAM programs, the size of the ORAM circuits is more relevant to the performance. We therefore embark on a study of the circuit-complexity of several recently proposed ORAM constructions. Our careful implementation and experiments show that asymptotic analysis is not indicative of the true performance of ORAM in secure computation protocols with practical data sizes. We then present SCORAM, a heuristic compact ORAM design optimized for secure computation protocols. Our new design is almost 10x smaller in circuit size and also faster than all other designs we have tested for realistic settings (i.e., memory sizes between 4MB and 2GB, constrained by 2-80 failure probability). SCORAM makes it feasible to perform secure computations on gigabyte-sized data sets.
Layer‐by‐layer assembled polyelectrolyte blend membranes and their use for ion separation and rejection

Polyelectrolyte blend films and membranes were prepared upon alternating electrostatic adsorption of polyallylamine hydrochloride (PAH) and mixtures of polystyrene sulfonate (PSS) and polyacrylic acid (PAA) in different ratio on solid supports. Infrared studies indicated that the PSS-PAA blend composition of the films always differed from the mixture composition in the dipping solution, PSS being preferentially adsorbed. Films deposited on porous supporting membranes (polyacrylonitrile/polyethylene terephthalate) were studied on their ion permeation under diffusion dialysis conditions, and their flux and salt rejection under nanofiltration and reverse osmosis (RO) conditions. Blend membranes prepared at pH 1.7 exhibit a significantly improved anion separation and salt rejection, the ideal separation factor α(NaCl/Na2SO4) of a membrane prepared from a PSS:PAA mixture of 1:1 (w/w) being 197 ± 10 (pure PAH/PSS: 45). The NaCl and Na2SO4 rejections under RO conditions are 85 and 97% (pure PAH/PSS: 15 and 27%), respectively. POLYM. ENG. SCI., 2011. © 2011 Society of Plastics Engineers
Decentralized Event-Triggering for Control of Nonlinear Systems

This paper considers nonlinear systems with full state feedback, a central controller and distributed sensors not co-located with the central controller. We present a methodology for designing decentralized asynchronous event-triggers, which utilize only locally available information, for determining the time instants of transmission from the sensors to the central controller. The proposed design guarantees a positive lower bound for the inter-transmission times of each sensor, while ensuring asymptotic stability of the origin of the system with an arbitrary, but priorly fixed, compact region of attraction. In the special case of Linear Time Invariant (LTI) systems, global asymptotic stability is guaranteed and scale invariance of inter-transmission times is preserved. A modified design method is also proposed for nonlinear systems, with the addition of event-triggered communication from the controller to the sensors, that promises to significantly increase the average sensor inter-transmission times compared to the case where the controller does not transmit data to the sensors. The proposed designs are illustrated through simulations of a linear and a nonlinear example.
Towards Light-Weight, Real-Time-Capable Singing Voice Detection

We present a study that indicates that singing voice detection – the problem of identifying those parts of a polyphonic audio recording where one or several persons sing(s) – can be realised with substantially fewer (and less expensive) features than used in current state-of-the-art methods. Essentially, we show that MFCCs alone, if appropriately optimised and used with a suitable classifier, are sufficient to achieve detection results that seem on par with the state of the art – at least as far as this can be ascertained by direct, fair comparisons to existing systems. To make this comparison, we select three relevant publications from the literature where publicly accessible training/test data were used, and where the experimental setup is described in enough detail for us to perform fair comparison experiments. The result of the experiments is that with our simple, optimised MFCC-based classifier we achieve at least comparable identification results, but with (in some cases much) less computational effort, and without any need for extensive lookahead, thus paving the way to on-line, real-time voice detection applications.
Proximal and Distal Predictors of the Spider Monkey’s Stress Levels in Fragmented Landscapes

The rapid loss, fragmentation and degradation of tropical forests threaten the survival of many animal species. However, the way in which these phenomena affect animal health has been poorly explored, thus limiting the design of appropriate conservation strategies. To address this, here we identified using linear mixed models the effect of proximal (diet, activity pattern, hunting and logging) and distal (sum of the basal areas of fruiting-tree species [SBAFS], landscape forest cover and degree of forest fragmentation) variables over fecal glucocorticoid metabolite (fGCM) levels–hormones associated with animal health and fitness–of six groups of spider monkeys (Ateles geoffroyi) inhabiting six landscapes with different spatial structures in Mexico. Proximal variables showed a stronger predictive power over fGCMs than distal. In this sense, increases in travel time, the occurrence of hunting, and reductions in rest time and fruit consumption resulted in higher fGCM levels. Regarding distal variables, increases in SBAFS were negatively related to fGCM levels, thus suggesting that food scarcity increases stress hormone levels. Nevertheless, contrary to theoretical expectations, spider monkeys living in smaller tracts of forest spent less time travelling, but the same time feeding on fruit as those in more forested areas. The lower net energy return associated with this combination of factors would explain why, contrary to theoretical expectations, increased forest cover was associated with increased levels of fGCMs in these groups. Our study shows that, at least in the short term, spider monkeys in fragmented landscapes do not always present higher levels of stress hormones compared to those inhabiting continuous forest, and the importance of preserving fruit sources and controlling hunting for reducing the levels of stress hormones in free ranging spider monkeys.
Immunophenotypic characteristics and clinical relevance of CD56+ and CD56− extranodal nasal-type natural killer/T-cell lymphoma

This study aimed to determine whether the phenotypic characteristics of the two subtypes of CD56+ and CD56− lymphoma have relevance for their clinical behavior and prognosis. The immunophenotypes of all patients were confirmed using standard criteria for CD20, CD3ε, CD56, cytotoxic molecules (T-cell intracellular antigen-1 [TIA-1] and granzyme B), and Ki-67, and in situ hybridization for Epstein–Barr virus (EBV)-encoded RNA (EBER). CD56 was expressed in 90 of 118 (76.3%) patients. The majority (83.3%) of patients with nasal natural killer/T-cell lymphoma (NKTCL) presented with CD56+ lymphoma, whereas patients with NKTCL of the extranasal upper aerodigestive tract were more likely to have CD56− lymphoma (53.6%, p < 0.000). A lower percentage of expression of granzyme B and Ki-67 (>50%) was found in patients with CD56− lymphoma compared with those with CD56+ lymphoma (p < 0.05). The clinical characteristics and prognosis were comparable between patients with CD56+ and CD56− lymphomas. The corresponding overall survival and progression-free survival rates were 74.1% and 56.7%, respectively, for patients with CD56+ lymphoma compared with 81.6% and 60.5% for those with CD56− lymphoma (p > 0.05). There was no clinical or prognostic significance in determining the two subtypes of CD56+ and CD56− NKTCL based on their immunophenotypic profiles, which has clinical implications for pathological diagnosis and insight into disease behavior.
Validation of the General Health Questionnaire in a young community sample

SYNOPSIS Validity coefficients of the 30-item, 28-item and 12-item versions of the General Health Questionnaire (GHQ) were determined by comparison with the Present State Examination (PSE) in a sample of 200 17-year-olds. The PSE classified 7 people (3·5%) as cases, although only 47% were identified as free of symptoms. Misclassification rates, sensitivity and specificity values are presented for different cutting scores for the three versions of the GHQ. The GHQ-28 had superior values, especially with a cutting score of 5/6; the GHQ-12 with a 2/3 cutting score also had acceptable values. All versions of the GHQ correlated highly with the PSE Index of Definition and total scores, providing support for the treatment of GHQ scores as a continuous variable in this kind of population. Correlations between sub-scales of the GHQ-28 give further evidence for a general factor and the relative independence of the social dysfunction sub-scale.
Evidence for Invariants in Local Search

It is well known that the performance of a stochastic local search procedure depends upon the setting of its noise parameter, and that the optimal setting varies with the problem distribution. It is therefore desirable to develop general priniciples for tuning the procedures. We present two statistical measures of the local search process that allow one to quickly find the optimal noise settings. These properties are independent of the fine details of the local search strategies, and appear to be relatively independent of the structure of the problem domains. We applied these principles to the problem of evaluating new search heuristics, and discovered two promising new strategies.
A numerical optimal control approach to the design of an optical fibre-based evanescent field sensor

Abstract This paper presents an application of numerical optimization via dynamic programming in the design of a refractive index profile for an optical fibre-based evanescent field sensor. The designed sensor delivers approximately 15% of the total propagating electromagnetic field power to the surrounding environment for sensing purposes, representing a substantial improvement over previous ad-hoc designs delivering at most 9% (Gibson et al. , 2001).
Self-compensating fiber optic flow sensor based on dual fiber Bragg gratings

We present a novel fiber optic flow sensor system by using two fiber Bragg gratings (FBGs) and a cantilever beam structure in this paper. This fiber optic flow sensor uses two FBGs that are bonded on both sides of a cantilever beam to measure the flow rate by monitoring the FBG wavelength changes caused by the bending of the cantilever beam. Cross sensitivity of the temperature dependence of the sensor can be compensated automatically. We fabricate the FBG flow sensor and test it in the laboratory-scaled flow set-up. The testing results demonstrate its high resolution and repeatability for the fluid flow rate measurements. Based on the analysis of test results, the fiber optic flow system will be optimized in the materials of the cantilever beam and the process of sensor fabrication, so as to finally be used in the oil field.
An imaging algorithm for synthetic aperture interferometric radiometers with built-in RFI mitigation

Radio Frequency Interference (RFI) is probably one of the most important limiting factors in the accuracy of the brightness temperatures measured by microwave radiometers. Due to the proximity of the “protected” L-band (1400-1427 MHz) to numerous services (communication, localization, broadcast.), this band is seriously affected by RFI, preventing ESA's SMOS mission or NASA/CONAE Aquarius mission from retrieving soil moisture and ocean salinity over large areas of the world. In this work, a technique is presented as an attempt to mitigate the RFI at its origin, when the synthetic aperture image is being formed. The technique is based on the well-known beam- and null-steering techniques used in today's advanced communication systems, but generalized to the synthetic aperture case, by means of the so-called equivalent array factor, which allows to interpret the “synthetic aperture array” as a “real aperture array” with an antenna in the position of each baseline.
QoE4CLOUD: A QoE-driven multidimensional framework for cloud environments

Cloud Operators, in order to respond effectively to the QoS requirements of cloud applications, are obliged to apply over-provisioning policies. In general, this tactic leads to severe waste of the available cloud computing resources. Similarly, both Service/Platform Providers and End-Users wish to avoid the extra cost of this over-provisioning tactic and pay only per use, without having to statically reserve extra resources in advance. As a consequence, the cloud community urgently asks for flexible and intelligent management solutions, towards enhanced and efficient utilization of the cloud. The ultimate target of any intelligent cloud management scheme should be the provision of a service at an adequate quality level, creating the need to introduce the notion of Quality of Experience (QoE). In this context, this paper proposes a unified QoE-aware management framework, directly targeting to cloud computing environments. The proposed management system suggests the optimization of cloud resources usage and offered services in terms of QoE, satisfying the different service and resource requirements of all the involved cloud entities. In addition, the proposed novel approach merges together various QoS aspects in a multidimensional framework, referred to as QoE4CLOUD, which considers the perceived quality as the key metric for the management and performance optimization of the cloud environment.
Influence of Si-Al-Ge-Sb Matricies on Tm3+ Excitation Levels

Absorption and fluorescence spectra in the range from 350 to 1750 nm of several Tm3+- doped optical performs (rods) for optical fiber drawing were measured. Silica-based matrices of Al2O3-GeO2-P2O5-Sb2O3-SiO2 composition doped with several thousands ppm of Tm3+ were characterized. The preforms were fabricated by the Modified Chemical Vapor Deposition and by the solution doping methods. A new method, Genetic Algorithm SPEctra Decomposition was adopted for processing of the measured absorption spectra. This decomposition made it possible to calculate the oscillator strengths of Tm3+ absorption levels. Fluorescence bands of Tm3+ at 800 nm or 1640 nm were found in fluorescence spectra measured on the preform samples when excited at 1064 nm only.
Slope Stability Analysis with Finite Element Method

A slope is studied with limiting equilibrium method and finite element method comparatively. It is found that the results of the two methods are almost the same. The distribution of principal stress, maximal plastic strain, plastic zone, lateral displacement, vertical settlement and incremental of displacement can be investigated by FEM effectively, which make it easy to expediently choose the method of slope reinforcement and the position of strengthening.
MAC Performance Evaluation of IEEE 802.16j

Being an evolution of IEEE 802.16e, IEEE 802.16j mobile multi-hop relay (MMR) is proposed to gain coverage extension and throughput enhancement. Although the IEEE standard 802.16j-2006 has not been published yet, the second version of 802.16j Draft Standard (802.16j D2) has been released in 2007. In this paper, for the first time, we evaluate the MAC performance of the Draft Standard based on the new relay-based OFDMA frame structure and the new transmission technique-Tunnel. Transmission using tunnel has been defined in 802.16j D2, but our work is to find a way to make use of the tunnel to meet each connectionpsilas QoS requirement as well as gaining a higher MAC efficiency. The impact of different parameters, such as MAC frame size, MAC protocol data unit (MPDU) size, QoS and the number of connections are considered in our analysis. Our results show that, for the sake of 5 kinds of QoS defined in the standard, we suggest 5 tunnel CIDs should be included in each relay station (RS) to aggregate all the connections into 5 different groups. And our results also show that, hop by hop tunnel establishing has a better performance than end to end tunnel establishing. As confirmed by our performance evaluation, we recommend hop by hop tunnel establishing with 5 QoS differentiation which has the best MAC efficiency to apply in 802.16j network.
Learning to Reinforce Search Effectiveness

Session search is an Information Retrieval (IR) task which handles a series of queries issued for a search task. In this paper, we propose a novel reinforcement learning style information retrieval framework and develop a new feedback learning algorithm to model user feedback, including clicks and query reformulations, as reinforcement signals and to generate rewards in the RL framework. From a new perspective, we view session search as a cooperative game played between two agents, the user and the search engine. We study the communications between the two agents; they always exchange opinions on "whether the current stage of search is relevant" and "whether we should explore now. " The algorithm infers user feedback models by an EM algorithm from the query logs. We compare to several state-of-the-art session search algorithms and evaluate our algorithm on the most recent TREC 2012 to 2014 Session Tracks. The experimental results demonstrates that our approach is highly effective for improving session search accuracy.