Miracle-dz/UniFAR-FTUs huggingface dataset:
Fragmentation and Drought Legacy Correlate with Distribution of Burrhead Chub in Subtropical Streams of North America

Abstract Burrhead Chub Macrhybopsis marconis is a species of special concern endemic to subtropical streams in south Texas. We documented life history attributes and historical patterns in abundance and distribution to aid in understanding range-wide declines of the species among the Colorado and Guadalupe-San Antonio River systems. Life history results suggest Burrhead Chub lives for 2 years, reaches sexual maturity at age-1, and spawns multiple clutches during March–September. Review of museum vouchers revealed Burrhead Chub is now missing from 26% of its historical range, including most impounded stream segments. There was a significant difference in the size of stream fragments for which Burrhead Chub is missing or still persists. Timing of many extirpations occurred after fragmentation and coincided with a record drought (1949–1959) when range-wide stream flows were exceedingly low during the Burrhead Chub reproductive season. Furthermore, extensive historical collections taken during 1950–1961 in th.
Using RFID in localization for indoor navigation of mobile robots

This paper concerns the issue of indoor navigation of mobile robots. Instead of computer vision, the use of RFID is explored in localization for Circular Navigation Guidance(CNG) law, which aims at fulfilling the navigation tasks of target tracking with the specified approaching configurations. Experimental results validate the effectiveness of the proposed method. In comparison to the computer vision based navigation paradigm, our proposed approach has considerable advantages in sensing efficiency and robustness to illumination and environment changes.
Routing Strategies to Enhance Traffic Capacity for Scale-Free Networks

In order to increase the value of the phrase transition on the regular network, which can be used to measure the capacity of network to process traffic flow, in this paper, we propose a simple traffic flow model for scale-free network based on randomly choosing the shortest path and further discuss the two different routing strategies to enhance the traffic capacity of scale-free networks. The simulation results show new routing strategies can improve the traffic capacity and obtain relatively less traffic flows delivery time without changing the structure of networks; therefore, itpsilas beneficial for decision-making in modern traffic networks.
A phase transition in the first passage of a Brownian process through a fluctuating boundary with implications for neural coding

Finding the first time a fluctuating quantity reaches a given boundary is a deceptively simple-looking problem of vast practical importance in physics, biology, chemistry, neuroscience, economics, and industrial engineering. Problems in which the bound to be traversed is itself a fluctuating function of time include widely studied problems in neural coding, such as neuronal integrators with irregular inputs and internal noise. We show that the probability p(t) that a Gauss–Markov process will first exceed the boundary at time t suffers a phase transition as a function of the roughness of the boundary, as measured by its Hölder exponent H. The critical value occurs when the roughness of the boundary equals the roughness of the process, so for diffusive processes the critical value is Hc = 1/2. For smoother boundaries, H > 1/2, the probability density is a continuous function of time. For rougher boundaries, H < 1/2, the probability is concentrated on a Cantor-like set of zero measure: the probability density becomes divergent, almost everywhere either zero or infinity. The critical point Hc = 1/2 corresponds to a widely studied case in the theory of neural coding, in which the external input integrated by a model neuron is a white-noise process, as in the case of uncorrelated but precisely balanced excitatory and inhibitory inputs. We argue that this transition corresponds to a sharp boundary between rate codes, in which the neural firing probability varies smoothly, and temporal codes, in which the neuron fires at sharply defined times regardless of the intensity of internal noise.
DC Characteristics and Variability on 90nm CMOS Transistor Array-Style Analog Layout

In the MOS analog layout, variability suppression is becoming a major issue, as is layout efficiency. Introducing a transistor array (TA) style to analog layout, this article addresses the layout-dependent variability based on the measurement results of test chips on 90nm CMOS process. In TA style, a large transistor is decomposed into a set of unified subtransistors, which are connected in series or parallel. Focusing on one row layout of diffusion sharing for the multiple gates, we analyze the current direction-dependent variability and the leakage current via off-gates for the electrical isolation. Furthermore, we present several analog design cases on TA including analysis of the impact on the DC characteristics caused by the transistor channel decomposition.
Methylation Profiles of CpG Island Loci in Major Types of Human Cancers

Several reports have described aberrant methylation in various types of human cancers. However, the interpretation of methylation frequency in various human cancers has some limitations because of the different materials and methods used for methylation analysis. To gain an insight into the role of DNA hypermethylation in human cancers and allow direct comparison of tissue specific methylation, we generated methylation profiles in 328 human cancers, including 24 breast, 48 colon, 61 stomach, 48 liver, 37 larynx, 24 lung, 40 prostate, and 46 uterine cervical cancer samples by analyzing CpG island hypermethylation of 13 genes using methylation-specific PCR. The mean numbers of methylated genes were 6.5, 4.4, 3.6, 3.4, 3.1, 3.1, 3.1, and 2.1 in gastric, liver, prostate, larynx, colon, lung, uterine cervix, and in breast cancer samples, respectively. The number of genes that were methylated at a frequency of more than 40% in each tumor type ranged from nine (stomach) to one (breast). Generally genes frequently methylated in a specific cancer type differed from those methylated in other cancer types. The findings indicate that aberrant CpG island hypermethylation is a frequent finding in human cancers of various tissue types, and each tissue type has its own distinct methylation pattern.
QoS routing mechanism using mobility prediction of node in ad-hoc network

MANET(Mobile Ad hoc NETwork) consists of movable only wireless nodes, except fixed station in the wired network. Not only hosts, but also routers for data packet forwarding in network topology changes. It is hard for routing algorithm using previous wired network to be applied to this ad hoc network. In the beginning, table-driven algorithm such as DSDV was shown in MANET, which resulted researches of On-demand routing protocols such as DSR, supporting mobility for mobile terminals. Recently, a routing protocol was developed, combined advantages of the former and the latter, called AODV(Ad hoc On-demand Distance Vector). However, despite advantages of AODV, it makes overall network performance weak due to nodes that move frequently, resulting considerable routing control traffic. In this paper, we propose efficient routing mechanism with route prediction of nodes for link reliability in MANET. Our work collects routes from source to destination with AOMDV. In this process, each node with GPS (Global Positioning System) predicts to move expected location by calculating node's location and velocity. With this mechanism, it makes source node can decide the route which has the longest connection time. And due to the reason why the node can choose appropriate route to data property among multiple routes collected to AOMDV, it also can reduce unnecessary control messages in MANET. By NS2 simulation, we analyze the former routing protocols to demonstrate the superiority of our work.
Fuzzy Peer Groups for Reducing Mixed Gaussian-Impulse Noise From Color Images

The <i>peer</i> <i>group</i> of an image pixel is a pixel similarity-based concept which has been successfully used to devise image denoising methods. However, since it is difficult to define the pixel similarity in a crisp way, we propose to represent this similarity in fuzzy terms. In this paper, we introduce the <i>fuzzy</i> <i>peer</i> <i>group</i> concept, which extends the <i>peer</i> <i>group</i> concept in the fuzzy setting. A <i>fuzzy</i> <i>peer</i> <i>group</i> will be defined as a fuzzy set that takes a <i>peer</i> <i>group</i> as support set and where the membership degree of each <i>peer</i> <i>group</i> member will be given by its fuzzy similarity with respect to the pixel under processing. The <i>fuzzy</i> <i>peer</i> <i>group</i> of each image pixel will be determined by means of a novel fuzzy logic-based procedure. We use the <i>fuzzy</i> <i>peer</i> <i>group</i> concept to design a two-step color image filter cascading a fuzzy rule-based switching impulse noise filter by a fuzzy average filtering over the <i>fuzzy</i> <i>peer</i> <i>group</i>. Both steps use the same <i>fuzzy</i> <i>peer</i> <i>group</i>, which leads to computational savings. The proposed filter is able to efficiently suppress both Gaussian noise and impulse noise, as well as mixed Gaussian-impulse noise. Experimental results are provided to show that the proposed filter achieves a promising performance.
CoParsing of RDF & XML

parsing, coroutines, XML, RDF, inversion RDF/XML is defined using two grammars, that for XML over text, and that for RDF over XML nodes. Conway's classic pipeline compiler architecture is extended to have two coparsers one for each grammar. A direct implementation of this architecture using Java threads for coroutines is presented. An alternate implementation, with the second parser inverted is discussed. Implications for other XML dialects are suggested.
Detection and removal of Salt and Pepper noise in images by improved median filter

A methodology based on median filters for the removal of Salt and Pepper noise by its detection followed by filtering in both binary and gray level images has been proposed in this paper. Linear and nonlinear filters have been proposed earlier for the removal of impulse noise; however the removal of impulse noise often brings about blurring which results in edges being distorted and poor quality. Therefore the necessity to preserve the edges and fine details during filtering is the challenge faced by researchers today. The proposed method consists of noise detection followed by the removal of detected noise by median filter using selective pixels that are not noise themselves. The noise detection is based on simple thresholding of pixels. Computer simulations were carried out to analyse the performance of the proposed method and the results obtained were compared to that of conventional median filter and center weighted median (CWM) filter.
New service development in high tech sectors: a decision making perspective

Many service companies active in high tech sectors have implemented largely decentralized decision architectures in their innovation processes. This is done to improve responsiveness under extremely dynamic and uncertain business conditions. As a consequence of the empowerment of decision-makers at the product management level, the success of the New Service Development (NSD) process will increasingly depend on individual product managersâ€™ information processing and decision-making performance. The present study investigates antecedents of decision-making effectiveness in the high tech NSD process, and reports on a case study performed in the mobile telecommunication services industry. NSD project managersâ€™ unique task conditions are articulated, and some antecedents and moderators of effective decision-making are identified in a study of four innovation projects. Findings are integrated in a theoretical framework. The study reveals the crucial role of decision-makersâ€™ flexible use of various cognitive styles, their proactive attitude, and their capability to mentally represent innovation interfaces with the customer, the technology and the firm. Managerial implications and suggestions for further research are provided.
Computational Strategies for Model-Based Scene Interpretation

Scene interpretation, in the sense of detecting and localizing instances from multiple object classes, is formulated as a two-step process in which non-contextual detection primes global interpretation. During detection a list of instantiations (object identities and poses) is compiled constrained only by invariance no missed detections at the expense of false positives. Contextual information, such as expected relationships among poses, is incorporated afterwards to remove ambiguities. This division is motivated by computational efficiency. In addition, detection itself is organized as a coarse-to-fine search simultaneously in class and pose. This search can be interpreted as successive approximations to likelihood ratio tests arising from a simple (“naive Bayes”) statistical model for the edge maps extracted from the original images. The key to constructing efficient “hypothesis tests” for multiple classes and poses is local ORing; in particular, spread edges provide imprecise but common and locally invariant features. Natural tradeoffs then emerge between discrimination and the shape and extent of spreading. These are analyzed mathematically within the model-based framework and the whole procedure is illustrated by experiments in reading license plates.
Summarization For Termination : No Return ! ( DRAFT )

We propose a program analysis method for proving termination of recursive programs. The analysis is based on a reduction of termination to two separate problems: reachability of recursive programs, and termination of non-recursive programs. Our reduction works through a program transformation that modifies the call sites and removes return edges. In the new, non-recursive program, a procedure call may nondeterministically enter the procedure body (which means that it will never return) or apply a summary statement.
Monetary Policy in Oil-Producing Economies

Most oil-producing economies have a strong dependence on oil revenues for their economic performance and stability. This paper develops a general equilibrium model of an oil-producing economy that takes into account a new transmission channel for oil price shocks. This transmission channel can be described as an income effect generated by oil revenues, and the model shows that its role is important to fully understand monetary policy in these economies. I first present a static model that illustrates that a tension is present in such economies when faced with increases in oil prices. This tension arises, on the one hand, from the contractionary effects of higher oil prices and, on the other hand, from the income effect generated by the increased oil revenues. I then present and solve a dynamic model with price rigidities in a two-sector economy with an oil sector. I find that the Phillips curve includes a measure of oil income that is responsible for additional inflationary pressures. Impulse response functions show that, in terms of consumption and inflation stabilization, the economy responds better to a Taylor rule that reacts to both final goods production and oil production than to a Taylor rule that reacts to final goods production only, although in the former the volatility implied for non-oil output is higher. I also explore welfare-based optimal monetary policy in this framework and conclude that a central bank can stabilize both inflation and output without trade-oÂ§ by reacting optimally to inflation and the output gap. Additionally, among Taylor-type rules, a rule that reacts to consumption and not only to final goods production is welfare superior.
"Towards more readable web: measuring readability of web pages based on link structure" by Adam Jatowt, Kouichi Akamatsu, Nimit Pattanasri, and Katsumi Tanaka with Ching-man Au Yeung as coordinator

Although Web search engines have become information gateways to the Internet, search results often contain pages that are difficult to understand for non-expert users, especially when queries contain technical or rare terms. Readability indexes are well-known measures for estimating text comprehensibility. However, readability indexes are not sufficient for evaluating the comprehensibility of Web pages, as they are designed for general purpose texts. In this research, we investigate the relationship between links and readability of text extracted from Web pages for two datasets, namely English and Japanese pages. We then describe a link analysis algorithm for measuring comprehensibility of Web pages based on the TrustRank algorithm originally used for combating Web spam. Lastly, we report results of preliminary studies to measure the correlation between search rank and readability of Web search results.
A novel prosody adaptation method for Mandarin concatenation-based text-to-speech system

The paper presents a prosody adaptation method which is able to adapt the prosody model of text to speech (TTS) to a new style with a small training corpus. Unlike the conventional prosody mapping between two parallel prosody features, the paper tries to integrate the prosody conversion into the prosody generation model of TTS. In the paper, we use a template-based prosody model which consists of two major parts: the prosody template library and the template parameter prediction trees for TTS system. With this model, the prosody adaptation is realized by the following two steps: converting the prosody template library to the target speaker’s prosody based on the mapping methods, re-training prosody prediction trees with the small target training set. In the model, some transformation algorithms, including linear regression, Gaussian Mixture Model (GMM) and Classification and Regression Tree (CART) are involved. Experimental results show that the prosody adaptation system can generate synthesized speech which is much similar with the target speaker.
Integrating robotics and neuroscience: brains for robots, bodies for brains

Researchers in robotics and artificial intelligence have often looked at biology as a source of inspiration for solving their problems. From the opposite perspective, neuroscientists have recently turned their attention to the use of robotic systems as a way to quantitatively test and analyze theories that would otherwise remain at a speculative stage. Computational models of neurons and networks of neurons are often activated with simplified artificial patterns that bear little resemblance to natural stimuli. The use of robotic systems has the advantage of introducing phenotypic and environmental constraints similar to those that brains of animals have to face during development and in everyday life. Consideration of these constraints is particularly important in light of modern brain theories, which emphasize the importance of closing the perception/action loop between the agent and the environment. To provide concrete examples of the use of robotic systems in neuroscience, this paper reviews our work in the areas of sensory perception and motor learning. The interdisciplinary approach followed by this research establishes a direct link between natural sciences and engineering. This research can lead to the understanding of basic biological problems while producing robust and flexible systems that operate in the real world.
Entrepreneurship and Regional Development

Entrepreneurship and regional development can be addressed from many different angles: clusters, creativity and human capital. Professor Acs, a distinguished researcher in this field, approaches this debate through technology. Technological change can be regarded as the most important factor in long-run macroeconomic growth. It has been argued in new growth theory that the technological element of the growth process results from the profit-motivated choices of economic agents. This important volume makes an essential contribution to this debate by presenting an authoritative selection of the most significant published work on entrepreneurship and regional economic growth.
The Origins of Composition Studies in the American College

Apparatus for facilitating the collection of debris comprises a ramp having a receiving end and a discharging end, a support for the ramp positions the receiving end adjacent the debris and elevates the discharge end, and a container for the debris is supported by the ramp support adjacent the discharge end for receiving debris, such as leaves, therewithin. The ramp and its support may comprise a unitary structure in one embodiment. In another embodiment, the debris container may comprise a cart, one or more walls of which may serve to support the ramp and the ramp may be detached therefrom or it may be pivotally supported thereby for rotation into position as a cover on the cart. The ramp, its support, and the debris container are constructed for portability and facile assembly and disassembly.
Constraint based optimization of stationary fields

In many scenarios a field holds a value that is constant beyond a certain point in the execution of the program. However, Java only allows it to be marked as being final in relation to the control-flow of the program. We present a language extension whereby the programmer can express that a field will have an unchanging value once it satisfies a given constraint. That is the constraint is the guarantee of finality as opposed to the particular code region. A field holding an unchanging value is said to be stationary. The resulting change of the language has similar pitfalls to keywords that express immutability in a dynamic system. However, it provides a number of advantages: ability for improved partial evaluation and specialisation in dynamic compilation, simple inspection to show thread safety and richer information to the runtime environment. We present an implementation of our proposed language extension to Java in the Jikes Research Virtual Machine (RVM). We use class loading as a case study of where lazy initialisation occurs. In code that is frequently executed the probability of a referenced class being uninitialised is less than 1% for method accesses and for fields typically 0%. We create an optimization framework that uses this information to perform specialisation and partial evaluation. We demonstrate that on average 61.32% of accesses occur to fields in their stationary state. We demonstrate that stationary information allows optimizations achieving a best case 3.90% speedup of benchmark applications, and 1.67% speedup on average.
Bile Acids Stimulate cFLIP Phosphorylation Enhancing TRAIL-mediated Apoptosis*

Bile acids induce hepatocyte injury by enhancing death receptor-mediated apoptosis. In this study, bile acid effects on TRAIL-mediated apoptosis were examined to gain insight into bile acid potentiation of death receptor signaling. TRAIL-induced apoptosis of HuH-7 cells, stably transfected with a bile acid transporter, was enhanced by bile acids. Caspase 8 and 10 activation, bid cleavage, cytosolic cytochrome c, and caspase 3 activation by TRAIL were all increased by the bile acid glycochenodeoxycholate (GCDCA). GCDCA (100 μm) did not alter expression of TRAIL-R1/DR4, TRAIL-R2/DR5, procaspase 8, cFLIP-L, cFLIP-s, Bax, Bcl-xL, or Bax. However, both caspase 8 and caspase 10 recruitment and processing within the TRAIL death-inducing signaling complex (DISC) were greater in GCDCA-treated cells whereas recruitment of cFLIP long and short was reduced. GCDCA stimulated phosphorylation of both cFLIP isoforms, which was associated with decreased binding to GST-FADD. The protein kinase C antagonist chelerythrine prevented bile acid-stimulated cFLIP-L and -s phosphorylation, restored cFLIP binding to GST-FADD, and attenuated bile acid potentiation of TRAIL-induced apoptosis. These results provide new insights into the mechanisms of bile acid cytotoxicity and the proapoptotic effects of cFLIP phosphorylation in TRAIL signaling.