Miracle-dz/UniFAR-FTUs huggingface dataset:
Viewshed Analysis for Improving the Effectiveness of Watchtowers, in the North of Mexico

The forests in Mexico have been seriously affected by forest fires, and thus detection of fires from watchtowers is essential. The current numbers of watchtowers and effectiveness of their distribution is unknown. The aim of the present study was to determine the current and potential area visible from the watchtowers, and to propose a new network to maximize its effectiveness. Visibility analysis in ArcGis were developed by integrating a digital model of elevation and a vegetation cover map, to determine visibility on a surface from point to point along a given line of sight or across the entire surface in a viewshed. It was found that existing watchtowers provide an overall visibility effectiveness (43%) very low compared with the recommended level. We suggest relocating one of the watchtowers and constructing another, which would increase the overall visibility effectiveness up to 81%.
Increased detection rate of human papillomavirus in cervical scrapes by the polymerase chain reaction as compared to modified FISH and southern‐blot analysi

Cervical scrapes from 80 women with a positive cytology result were tested for the presence of human papillomavirus (HPV) using the polymerase chain reaction (PCR) and compared to the results obtained with the modified filter in situ hybridisation (FISH) and the Southern‐blot techniques.
Strain sensing fabric for hand posture and gesture monitoring

In this paper, we report on a new technology used to implement strain sensors to be integrated in usual garments. A particular conductive mixture based on commercial products is realized and directly spread over a piece of fabric, which shows, after the treatment, piezoresistive properties, i.e., a change in resistance when it is strained. This property is exploited to realize sensorized garments such as gloves, leotards, and seat covers capable of reconstructing and monitoring body shape, posture, and gesture. In general, this technology is a good candidate for adherent wearable systems with excellent mechanical coupling with body surface. Here, we mainly focused on a sensorized glove able to detect posture and movements of the fingers. It could be used in several fields of application. We report on experimental results of a sensorized glove used as movements recorder for rehabilitation therapies and medicine. Furthermore, we describe a dedicated methodology used to read the output sensors which allowed to avoid using metallic wires for the connections. The price to be paid for all these advantages is a nonlinear electric response of the fabric sensor and a too long settling time, that in principle, make these sensors not suitable for real-time applications. Here we propose a hardware and computational solution to overcome this limitation.
Regression Test Selection Techniques for Test-Driven Development

Test-Driven Development (TDD) is characterized by repeated execution of a test suite, enabling developers to change code with confidence. However, running an entire test suite after every small code change is not always cost effective. Therefore, regression test selection (RTS) techniques are important for TDD. Particularly challenging for TDD is the task of selecting a small subset of tests that are most likely to detect a regression fault in a given small and localized code change. We present cost-bounded RTS techniques based on both dynamic program analysis and natural-language analysis. We implemented our techniques in a tool called Test Rank, and evaluated its effectiveness on two open-source projects. We show that using these techniques, developers can accelerate their development cycle, while maintaining a high bug detection rate, whether actually following TDD, or in any methodology that combines testing during development.
An Efficient Markerless Method for Resynthesizing Facial Animation on an Anatomy-Based Model

This paper describes a markerless method for automatically estimating animation parameters of an anatomy-based face model from a video sequence. The method is based upon an efficient tracking procedure which employs a linear subspace model of facial appearance. During the training phase of the tracking algorithm, a set of templates is computed from the subspace basis to alleviate the online computation. The efficient tracking algorithm establishes temporal correspondence of the face region by simultaneously determining both motion and appearance parameters. Using a set of key expressions of the actor together with corresponding animation parameters of the face model, we learn a linear relationship between facial animation parameters and appearance parameters. It allows us to efficiently estimate the animation parameters from appearance parameters provided by the tracker. We present experimental results performed on synthetic and live video sequences to demonstrate the effectiveness and efficiency of our method.
Communication Learning in Social Networks: Finite Population and the Rates

Following the Bayesian communication learning paradigm, we propose a finite population learning concept to capture the level of information aggregation in any given network, where agents are allowed to communicate with neighbors repeatedly before making a single decision. This concept helps determine the occurrence of effective information aggregation in a finite network and reveals explicit interplays among parameters. It also enables meaningful comparative statics regarding the effectiveness of information aggregation in networks. Moreover, it offers a solid foundation to address, with a new perfect learning concept, long run dynamics of learning behavior and the associated learning rates as population diverges. Our conditions for the occurrence of finite population learning and perfect learning in communication networks are very tractable and transparent.
Acute heart inflammation: ultrastructural and functional aspects of macrophages elicited by Trypanosoma cruzi infection

• Introduction • Acute T. cruzi infection induces accentuated mobilization/migration of monocytic lineage cells into heart • Heart inflammatory macrophages show a distinct morphology and are actively involved in parasite phagocytosis • Lipid bodies as structural markers of inflammatory macrophages • Macrophages and the resolution of acute inflammation and heart repair • Concluding remarks
Differential effects of acute and chronic exercise on plasticity‐related genes in the rat hippocampus revealed by microarray

Studies were performed to determine the effects of acute and chronic voluntary periods of exercise on the expression of hippocampal genes. RNAs from rodents exposed to a running wheel for 3, 7 and 28 days were examined using a microarray with 1176 cDNAs expressed primarily in the brain. The expression of selected genes was quantified by Taqman RT‐PCR or RNase protection assay. The largest up‐regulation was observed in genes involved with synaptic trafficking (synapsin I, synaptotagmin and syntaxin); signal transduction pathways (Ca2+/calmodulin‐dependent protein kinase II, CaM‐KII; mitogen‐activated/extracellular signal‐regulated protein kinase, MAP‐K/ERK I and II; protein kinase C, PKC‐δ) or transcription regulators (cyclic AMP response element binding protein, CREB). Genes associated with the glutamatergic system were up‐regulated (N‐methyl‐d‐aspartate receptor, NMDAR‐2A and NMDAR‐2B and excitatory amino acid carrier 1, EAAC1), while genes related to the gamma‐aminobutyric acid (GABA) system were down‐regulated (GABAA receptor, glutamate decarboxylase GAD65). Brain‐derived neurotrophic factor (BDNF) was the only trophic factor whose gene was consistently up‐regulated at all timepoints. These results, together with the fact that most of the genes up‐regulated have a recognized interaction with BDNF, suggest a central role for BDNF on the effects of exercise on brain plasticity. The temporal profile of gene expression seems to delineate a mechanism by which specific molecular pathways are activated after exercise performance. For example, the CaM‐K signal system seems to be active during acute and chronic periods of exercise, while the MAP‐K/ERK system seems more important during long‐term exercise.
Toric Genera

Our primary aim is to develop a theory of equivariant genera for stably complex manifolds equipped with compatible actions of a torus T . In the case of omnioriented quasitoric manifolds, we present computations that depend only on their defining combinatorial data; these draw inspiration from analogous calculations in toric geometry, which seek to express arithmetic, elliptic, and associated genera of toric varieties in terms only of their fans. Our theory focuses on the universal toric genus Φ, which was introduced independently by Krichever and Löffler in 1974, albeit from radically different viewpoints. In fact Φ is a version of tom Dieck’s bundling transformation of 1970, defined on T -equivariant complex cobordism classes and taking values in the complex cobordism algebra Ω U (BT k + ) of the classifying space. We proceed by combining the analytic, the formal group theoretic, and the homotopical approaches to genera, and refer to the index theoretic approach as a recurring source of insight and motivation. The resultant flexibility allows us to identify several distinct genera within our framework, and to introduce parametrised versions that apply to bundles equipped with a stably complex structure on the tangents along their fibres. In the presence of isolated fixed points, we obtain universal localisation formulae, whose applications include the identification of Krichever’s generalised elliptic genus as universal amongst genera that are rigid on SU -manifolds. We follow the traditions of toric geometry by working with a variety of illustrative examples wherever possible. For background and prerequisites we attempt to reconcile the literature of east and west, which developed independently for several decades after the 1960s.
Initialization and Potential Predictability of Soil Moisture in the Canadian Seasonal to Interannual Prediction System

The initialization and potential predictability of soil moisture in CanCM4 hindcasts during 1981–2010 is assessed. CanCM4 is one of the two global climate models employed by the Canadian Seasonal to Interannual Prediction System (CanSIPS) providing operational multiseasonal forecasts for Environment and Climate Change Canada (ECCC). Soil moisture forecast initialization in CanSIPS is determined by the response of the land component to forcing from data-constrained model atmospheric fields. We evaluate hindcast initial conditions for soil moisture and its atmospheric forcings against observation-based datasets. Although model values of soil moisture variability compare relatively well with a blend of two reanalysis products, there is significant disagreement in the tropics and arid regions linked to biases in precipitation, as well as in snow-covered regions, likely the result of biases in the timing of snow onset and melt. The temporal variance of initial soil moisture anomalies is typically larger in regions of considerable precipitation variability and in cold continental areas of shallow soil depth. Appreciable variance of initial conditions, combined with persistence of the initial anomalies and the model’s ability to represent future climate variations, lead to potentially predictable soil moisture variance exceeding 60% of the total variance for up to 3–4 months in the tropics and 6–7 months in the mid- to high latitudes during hemispheric winter. Potential predictability at longer leads is primarily found in the tropics and extratropical areas of ENSO-teleconnected influences. We use lagged partial correlations to show that ENSO-teleconnected precipitation in CanCM4 is a likely source of potential predictability of soil moisture up to 1-yr lead in CanSIPS hindcasts.
Delay Analysis of Enhanced Relay-Enabled Distributed Coordination Function

This paper analyzes the delay performance of Enhanced relay-enabled Distributed Coordination Function (ErDCF) for wireless ad hoc networks under ideal condition and in the presence of transmission errors. Relays are nodes capable of supporting high data rates for other low data rate nodes. In ideal channel ErDCF achieves higher throughput and reduced energy consumption compared to IEEE 802.11 Distributed Coordination Function (DCF). This gain is still maintained in the presence of errors. It is also expected of relays to reduce the delay. However, the impact on the delay behavior of ErDCF under transmission errors is not known. In this work, we have presented the impact of transmission errors on delay. It turns out that under transmission errors of sufficient magnitude to increase dropped packets, packet delay is reduced. This is due to increase in the probability of failure. As a result the packet drop time increases, thus reflecting the throughput degradation.
Sympathetic skin response in Parkinson's disease

Sudomotor function in 83 patients with Parkinson's disease (PD) was evaluated using the sympathetic skin response (SSR) and sweat response to intradermal acetylcholine (ACh) injection. The incidence of abnormal SSRs (36.1%) increased, and the size of the response decrease with the severity of the illness. Neither the incidence of abnormal SSRs nor the amplitudes of the responses were influenced by levodopa or an anticholinergic agent. The SSR therefore can be used to evaluate the sudomotor efferent pathway in PD patients. In all the patients who had no SSR response, the local sweat response to ACh showed a reduced number of excitable sweat glands and low sweat volume. One patient, whose local sweat response to ACh was markedly impaired, had unmyelinated and acetylcholinesterase‐positive fiber densities that were in the normal range in his biopsied sural nerve. The abnormal sweat response to ACh is considered to reflect the dysfunction of postganglionic sympathetic fibers in PD patients.
Streaming High-Quality Mobile Video with Multipath TCP in Heterogeneous Wireless Networks

The proliferating wireless infrastructures with complementary characteristics prompt the bandwidth aggregation for concurrent video transmission in heterogeneous access networks. Multipath TCP (MPTCP) is an important transport-layer protocol recommended by IETF to integrate different access medium (e.g., Cellular and Wi-Fi). This paper investigates the problem of mobile video delivery using MPTCP in heterogeneous wireless networks with multihomed terminals. To achieve the optimal quality of real-time video streaming, we have to seriously consider the path asymmetry in different access networks and the disadvantages of the data retransmission mechanism in MPTCP. Motivated by addressing these critical issues, this study presents a novel quAlity-Driven MultIpath TCP (ADMIT) scheme that integrates the utility maximization based Forward Error Correction (FEC) coding and rate allocation. We develop an analytical framework to model the MPTCP-based video delivery quality over multiple communication paths. ADMIT is able to effectively integrate the most reliable access networks with FEC coding to minimize the end-to-end video distortion. The performance of ADMIT is evaluated through extensive semi-physical emulations in Exata involving H.264 video streaming. Experimental results show that ADMIToutperforms the reference transport protocols in terms of video PSNR (Peak Signal-to-Noise Ratio), end-to-end delay, and goodput. Thus, we recommend ADMIT for streaming high-quality mobile video in heterogeneous wireless networks with multihomed terminals.
Silence is gold: Strategic small cell interference management using tokens

Electronic tokens have been proved as an effective incentive scheme in stimulating self-interested network nodes to transmit other nodes' traffic. In other words, tokens are paid to buy transmission. In this work, we propose a novel token framework in a distributed small cell network and design the token system for improved interference mitigation. Contrary to the traditional role of tokens for buying transmission, they are exchanged between users to buy "silence". We focus on designing the optimal token system that minimizes the system outage probability. We first analyze the optimal strategies of individual users, which only consider their own utility maximization and do not care about the system-wise performance. We show that under some mild conditions the optimal strategy has a simple threshold structure. We then analytically derive the optimal token supply that minimizes the network outage probability. Simulation results show that not only does the proposed token system design greatly improve the network outage probability (by up to 75%), it also improves the overall small cell network QoS, particularly when the deployment density is high.
6.895 Theory of Parallel Systems Fast Serial-append File I/o Mode Support for Cilk

Apart from resources, such as memory and processors, parallel computations also require file I/O. There exist a number of interesting file I/O modes, depending on the specific application. One particularly interesting file I/O mode is serial-append, described in [5]. In this mode the file output of a parallel computation, executed on any number of processors, is “the same” as the output of the sequential, single processor execution. Cheerio, an implementation of serial-append presented in [5], uses a special formated file where ordering metadata about the parallel execution of the computation is saved together with the actual data. This allows for later reconstruction of the output of the sequential execution. The algorithm described in [5] uses a single mutex-ed counter that allows a worker processor to obtain a new node to write to, when a steal operation occurs in Cilk’s scheduler. Additional locking mechanisms are also performed by Cilk’s Runtime System in order to correctly maintain the order of the structure required by Cheerio. Due to the high overhead of the steal operation this method does not scale up with the number of processors.
Magnetic Fluctuations and Turbulence in the Venusian Magnetosheath Downstream of Different Types of Bow Shock

We statistically examine the characteristic scaling features of fluctuations in the dayside Venusian magnetosheath downstream of different types, quasi‐parallel (Q∥) and quasi‐perpendicular (Q⊥), of bow shock based on Venus Express data. We found that magnetic fluctuations have different characteristic scaling features downstream of Q∥ and Q⊥ bow shocks. Although the Venusian dayside magnetosheath is much thinner than the Earth magnetosheath, fully developed turbulence can be still observed downstream of the Q∥ bow shock, while the turbulence is not dominant downstream of Q⊥ bow shock. The type of bow shock plays an important role in the characteristic scaling features of downstream magnetic fluctuations. That means that the Q∥ IMF might be a source of the turbulence in Venusian magnetosheath.
Pacific Asia Conference on Information Systems ( PACIS ) 2009 MANAGING KNOWLEDGE FOR ENTERPRISE SYSTEMS IN INDIAN ORGANIZATIONS : CASE STUDY INSIGHTS

Many Enterprise Systems (ES) projects have reported nil or detrimental impacts despite the substantial investment in the system. Having expected positive outcomes for the organization and its functions through the weighty spend, the effective management of ES-related knowledge has been suggested as a critical success factor for these ES projects in ES implementations. This paper suggests theoretical views purporting the importance of understanding on knowledge management for ES success. To explain the complex, dynamic and multifaceted of knowledge management, we adopt the concepts in Learning Network Theory. We then conceptualized the impact of knowledge management on ES by analyzing five case studies in several industries in India, based on the Knowledge-based Theory of the Firm that captures the performance of the system.
RNA duplex unwinding activity of poliovirus RNA-dependent RNA polymerase 3Dpol

The ability of highly purified preparations of poliovirus RNA-dependent RNA polymerase, 3Dpol, to unwind RNA duplex structures was examined during a chain elongation reaction in vitro. Using an antisense RNA prehybridized to an RNA template, we show that poliovirus polymerase can elongate through a highly stable RNA duplex of over 1,000 bp. Radiolabeled antisense RNA was displaced from the template during the reaction, and product RNAs which were equal in length to the template strand were synthesized. Unwinding did not occur in the absence of chain elongation and did not require hydrolysis of the gamma-phosphate of ATP. The rate of elongation through the duplex region was comparable to the rate of elongation on the single-stranded region of the template. Parallel experiments conducted with avian myeloblastosis virus reverse transcriptase showed that this enzyme was not able to unwind the RNA duplex, suggesting that strand displacement by poliovirus 3Dpol is not a property shared by all polymerases.
Diffuse Imaging: Creating Optical Images With Unfocused Time-Resolved Illumination and Sensing

Conventional imaging uses steady-state illumination and light sensing with focusing optics; variations of the light field with time are not exploited. We develop a signal processing framework for estimating the reflectance of a Lambertian planar surface in a known position using omnidirectional, time-varying illumination and unfocused, time-resolved sensing in place of traditional optical elements such as lenses and mirrors. Our model associates time sampling of the intensity of light incident at each sensor with a linear functional of . The discrete-time samples are processed to obtain -regularized estimates of . Improving on previous work, using nonimpulsive, bandlimited light sources instead of impulsive illumination significantly improves signal-to-noise ratio (SNR) and reconstruction quality. Our simulations suggest that practical diffuse imaging applications may be realized with commercially-available temporal light intensity modulators and sensors used in standard optical communication systems.
Feasibility of using Cost Effective LIDAR for Precision Horticulture

LIDAR (Light Detection and Ranging) sensors are one of the biggest contributors to the cost of a mapping/navigation system in a robot. A good quality LIDAR for a simple autonomous robot may cost 20 – 80% of the robot’s cost. Hence proposed is a minimal setup for proving feasibility of using a very cost-effective LIDAR sensor to be used in advanced applications where high-end LIDAR sensors are normally used. Here the application demonstrated is with low computing resources and low-cost devices for demonstrating 2D mapping of a Horticulture field. The setup proposed has got an overall Error of 1.08% while the sensor itself had 1% error. Hence it can be approximated that the setup error is 0.08%. Keywords— LIDAR; Horticulture; Simultaneous localization and mapping; Robot Operating System; Agricultural Robotics; Mapping