Miracle-dz/UniFAR-FTUs huggingface dataset:
Depopulation of rural landscapes exacerbates fire activity in the western Amazon

Destructive fires in Amazonia have occurred in the past decade, leading to forest degradation, carbon emissions, impaired air quality, and property damage. Here, we couple climate, geospatial, and province-level census data, with farmer surveys to examine the climatic, demographic, and land use factors associated with fire frequency in the Peruvian Amazon from 2000 to 2010. Although our results corroborate previous findings elsewhere that drought and proximity to roads increase fire frequency, the province-scale analysis further identifies decreases in rural populations as an additional factor. Farmer survey data suggest that increased burn scar frequency and size reflect increased flammability of emptying rural landscapes and reduced capacity to control fire. With rural populations projected to decline, more frequent drought, and expansion of road infrastructure, fire risk is likely to increase in western Amazonia. Damage from fire can be reduced through warning systems that target high-risk locations, coordinated fire fighting efforts, and initiatives that provide options for people to remain in rural landscapes.
Vivisection of a Non-Executable, Domain-Specific Language - Understanding (the Usage of) the P3P Language

P3P is the policy language with which websites declare the intended use of data that is collected about users of the site. We have systematically collected P3P-based privacy policies from websites listed in the Google directory, and analysed the resulting corpus with regard to different levels of validity, size or complexity metrics, different cloning levels, coverage of language constructs, and the use of the language’s extension mechanism. In this manner, we have found interesting characteristics of P3P in the wild. For instance, cloning is exceptionally common in this domain, and encountered language extensions exceed the base language in terms of grammar complexity. Overall, this effort helps understanding the de-facto usage of the non-executable, domain-specific language P3P. Some elements of our methodology may be useful for other software languages as well.
Compiler support for speculative multithreading architecture with probabilistic points-to analysis

Speculative multithreading (SpMT) architecture can exploit thread-level parallelism that cannot be identified statically. Speedup can be obtained by speculatively executing threads in parallel that are extracted from a sequential program. However, performance degradation might happen if the threads are highly dependent, since a recovery mechanism will be activated when a speculative thread executes incorrectly and such a recovery action usually incurs a very high penalty. Therefore, it is essential for SpMT to quantify the degree of dependences and to turn off speculation if the degree of dependences passes certain thresholds. This paper presents a technique that quantitatively computes dependences between loop iterations and such information can be used to determine if loop iterations can be executed in parallel by speculative threads. This technique can be broken into two steps. First probabilistic points-to analysis is performed to estimate the probabilities of points-to relationships in case there are pointer references in programs, and then the degree of dependences between loop iterations is computed quantitatively. Preliminary experimental results show compiler-directed thread-level speculation based on the information gathered by this technique can achieve significant performance improvement on SpMT.
Sparse Matching of Random Patches for Person Re-Identification

Most of the open challenges in person re-identification are introduced by the large variations of human appearance and from the different camera views deployed to monitor the environment. To tackle these challenges, almost all state-of-the-art methods assume that all image pixels are equally relevant to the task, hence they are used in the feature extraction procedure. However, it is not guaranteed the a pixel sensed by one camera is viewed by a different one, so computing the person signature using such pixel might bring uninformative data in the feature matching phase. We believe that only some portions of the image are relevant to the re-identification task. Inspired by this, we introduce a novel algorithm that: (i) randomly samples a set of image patches to compute the person signature; (ii) uses the correlation matrix computed between such patches as a weighing tool in the signature matching process; (iii) brings sparsity in the correlation matrix so as only relevant patches are used in the matching phase. To validate the proposed approach, we have compared our performance to state-of-the-art methods using two publicly available benchmark datasets. Results show that superior performance to existing approaches are achieved.
Statistical Methods for Environmental Pollution Monitoring

Sampling Environmental Populations. Environmental Sampling Design. Simple Random Sampling. Stratified Random Sampling. Two-Stage Sampling. Compositing and Three-Stage Sampling. Systematic Sampling. Double Sampling. Locating Hot Spots. Quantiles, Proportions, and Means. Skewed Distributions and Goodness-of-Fit Tests. Characterizing Lognormal Populations. Estimating the Mean and Variance from Censored Data Sets. Outlier Detection and Control Charts. Detecting and Estimating Trends. Trends and Seasonality. Comparing Populations. Appendices. Symbols. Glossary. Bibliography. Index.
Metric based efficiency analysis of educational ERP system usability-using fuzzy model

Enterprise Resource Planning (ERF) systems are sophisticated information database that provide an automatic cross-functional business processes. An ERP user, however, often encounters challenges using complex ERP interfaces. Educational ERP implementation has been plagued with failure, but it to be adopted and is expanding in Indian higher education. An AICTE, UGC and others government approving bodies have made ERP system as mandatory software for all technical institutions. Educational ERP system includes almost all related modules. Despite many benefits, ERP users' recognize usability problems and these problems negatively affect the adaptability of the system in large scale. Usability is mainly making systems `easy to use' and usability testing is a process to collect information about the usability of user interfaces. Usability test consist usability related attributes. Each usability attribute influences a specific characteristic associated with the ERP system. The impact of each usability attribute may very during usability evaluation process. These attributes are navigation, presentation, learnability, customizing, and task support. Usability metrics is generally imprecise, vagueness and ambiguous are characterized by fuzzy aspects and linguistic variables. Fuzzy logic is a branch of mathematics that allows a computer to model the real world the same way that people do. It provides a way to reason with vague, ambiguous and imprecise inputs or knowledge. This paper presents a fuzzy model for assessing the usability of ERP system usability by using these metrics. The present model uses the Mamdani fuzzy Inference approach for developing an overall measure of educational ERP system.
The Question of Vascular Hyper‐Responsiveness in Hypertension

After inhibition of spontaneous tone, the contraction of spirally cut strips of aorta in response to norepinephrine was studied quantitatively in normotensive rats and in 4 different types of hypertensive rats. In no instance did the aortas of hypertensive rats show hyper-responsiveness to norepinephrine. The majority of responses were entirely normal; in a few instances there was decreased responsiveness. In vivo studies which fail to consider the critical effect of an altered “base-line” state in hypertension may demonstrate “hyper-responsiveness” which is more apparent than real.
Using tag data to assess behaviour, vocal sounds, boat noise and potential effects on Humpback whales (Megaptera novaeangliae) in response to whale watching boats in Skjálfandi Bay (Húsavík), Iceland

The rapid development of whale watching in Iceland can represent a serious threat to whales during their critical feeding season. Humpback whales (Megaptera novaeangliae) are one of the most desired whales for wildlife encounters. However, little is known concerning potential effects from whale watching. Furthermore, there is little knowledge regarding vocal humpback whales vocalizations in the area. In this study, acoustic tags were attached to seven humpback whales during summers 2013 and 2014 in Skjálfandi Bay, Húsavík, Iceland. Boat noise levels were measured to investigate possible changes in natural behaviour. A customized breath and lunge detector was built and behavioural patterns were described and analysed statistically. Generalized linear models were used to test for changes in mean dive depth, jerk rate, breath rate, vertical speed, dive rate and dive duration before, during and after exposure to boats. Effects of tagging, boat noise intensity and whether boats were just passing or actively approaching were also tested. Whale vocalizations were assessed and described. Upsweep grunts were the most common vocalizations detected and high frequency calls were also registered during the foraging stage.The results included a significant reduction of jerk rate during active boat approaches compared to boat passes, and increase of mean depth during exposure to high noise intensity compared to low noise intensity. No differences were found between the before, during and after phases. Whales responded by diving deeper and performing longer dives when the boat exposure started during the first hour of the record compared to later boat exposures (suggesting a tagging effect). No significant changes were found for breath rate, vertical speed and dive rate. The observed changes in jerk rate and mean depth might indicate a disruption of foraging behaviour. These immediate responses could lead to impacts affecting the energy availability in the long term. Further, the registered levels of boat noise may impair whale communication (masking) for critical functions (e.g., feeding or socializing). “Knowing is not enough; we must apply, Willing is not enough; we must do” Johann Wolfgang von Goethe (1749-1832)
Nonlinear conductivity of ion-complexed polyethylene oxide

The electric polarization in polyethylene oxide com-plexed with LiClO4 has been investigated over the frequency range from 10 mHz to 10 kHz. The exciting electric fields have been chosen so high that nonlinear components in the dielectric response are evident. Nonlinear dielectric and conductive spectra are determined and their temperature dependence is studied. It is found that the nonlinear relaxation shows a temperature dependence similar to the linear relaxation. With rising temperature the phenomena shift to higher frequencies and the relaxation strength increases. To evaluate relaxation frequencies and strengths theoretical functions are fitted to the experimental data. While the linear spectra are reproduced well over the whole frequency range, a reasonable agreement between experimental data and theoretical curves is found in a limited frequency range only for the nonlinear spectra.
Disruption of actin‐binding domain‐containing Dystonin protein causes dystonia musculorum in mice

The Dystonin gene (Dst) is responsible for dystonia musculorum (dt), an inherited mouse model of hereditary neuropathy accompanied by progressive motor symptoms such as dystonia and cerebellar ataxia. Dst‐a isoforms, which contain actin‐binding domains, are predominantly expressed in the nervous system. Although sensory neuron degeneration in the peripheral nervous system during the early postnatal stage is a well‐recognised phenotype in dt, the histological characteristics and neuronal circuits in the central nervous system responsible for motor symptoms remain unclear. To analyse the causative neuronal networks and roles of Dst isoforms, we generated novel multipurpose Dst gene trap mice, in which actin‐binding domain‐containing isoforms are disrupted. Homozygous mice showed typical dt phenotypes with sensory degeneration and progressive motor symptoms. The gene trap allele (DstGt) encodes a mutant Dystonin‐LacZ fusion protein, which is detectable by X‐gal (5‐bromo‐4‐chloro‐3‐indolyl‐β‐D‐galactoside) staining. We observed wide expression of the actin‐binding domain‐containing Dystonin isoforms in the central nervous system (CNS) and peripheral nervous system. This raised the possibility that not only secondary neuronal defects in the CNS subsequent to peripheral sensory degeneration but also cell‐autonomous defects in the CNS contribute to the motor symptoms. Expression analysis of immediate early genes revealed decreased neuronal activity in the cerebellar‐thalamo‐striatal pathway in the homozygous brain, implying the involvement of this pathway in the dt phenotype. These novel DstGt mice showed that a loss‐of‐function mutation in the actin‐binding domain‐containing Dystonin isoforms led to typical dt phenotypes. Furthermore, this novel multipurpose DstGt allele offers a unique tool for analysing the causative neuronal networks involved in the dt phenotype.
Three-dimensional Structure of Acanthamoeba castellanii Myosin-IB (MIB) Determined by Cryoelectron Microscopy of Decorated Actin Filaments

The Acanthamoeba castellanii myosin-Is were the first unconventional myosins to be discovered, and the myosin-I class has since been found to be one of the more diverse and abundant classes of the myosin superfamily. We used two-dimensional (2D) crystallization on phospholipid monolayers and negative stain electron microscopy to calculate a projection map of a “classical” myosin-I, Acanthamoeba myosin-IB (MIB), at ∼18 Å resolution. Interpretation of the projection map suggests that the MIB molecules sit upright on the membrane. We also used cryoelectron microscopy and helical image analysis to determine the three-dimensional structure of actin filaments decorated with unphosphorylated (inactive) MIB. The catalytic domain is similar to that of other myosins, whereas the large carboxy-terminal tail domain differs greatly from brush border myosin-I (BBM-I), another member of the myosin-I class. These differences may be relevant to the distinct cellular functions of these two types of myosin-I. The catalytic domain of MIB also attaches to F-actin at a significantly different angle, ∼10°, than BBM-I. Finally, there is evidence that the tails of adjacent MIB molecules interact in both the 2D crystal and in the decorated actin filaments.
On the application of factor graphs and the sum-product algorithm to ISI channels

In this paper, based on the application of the sum-product (SP) algorithm to factor graphs (FGs) representing the joint a posteriori probability (APP) of the transmitted symbols, we propose new iterative soft-input soft-output (SISO) detection schemes for intersymbol interference (ISI) channels. We have verified by computer simulations that the SP algorithm converges to a good approximation of the exact marginal APPs of the transmitted symbols if the FG has girth at least 6. For ISI channels whose corresponding FG has girth 4, the application of a stretching technique allows us to obtain an equivalent girth-6 graph. For sparse ISI channels, the proposed algorithms have advantages in terms of complexity over optimal detection schemes based on the Bahl-Cocke-Jelinek-Raviv (BCJR) algorithm. They also allow a parallel implementation of the receiver and the possibility of a more efficient complexity reduction. The application to joint detection and decoding of low-density parity-check (LDPC) codes is also considered and results are shown for some partial-response magnetic channels. Also in these cases, we show that the proposed algorithms have a limited performance loss with respect to that can be obtained when the optimal "serial" BCJR algorithm is used for detection. Therefore, for their parallel implementation, they represent a favorable alternative to the modified "parallel" BCJR algorithm proposed in the literature for the application to magnetic channels.
Applicability Results of a Nonlinear Model-Based Robust Blood Glucose Control Algorithm

Introduction: Generating optimal control algorithms for an artificial pancreas is an intensively researched problem. The available models are all nonlinear and rather complex. Model predictive control or run-to-run-based methodologies have proven to be efficient solutions for individualized treatment of type 1 diabetes mellitus (T1DM). However, the controller has to ensure safety and stability under all circumstances. Robust control methods seek to provide this safety and guarantee to handle even the worst-case situations and, hence, to generalize and complement results obtained by individualized control algorithms. Methods: Modern robust (e.g., Hinf) control is a linear model-based methodology that we have combined with the nonlinear model-based linear parameter varying technique. The control algorithm was designed on the high-complexity modified nonlinear glucose-insulin model of Sorensen, and it was compared step-by-step with linear model-based Hinf control results published in the literature. The applicability of the developed algorithm was tested first on a control cohort of 10 healthy persons' oral glucose tolerance test results and then on a large meal absorption profile adapted from the literature. In the latter case, two preliminary virtual patients were generated based on 1–1 week real continuous glucose monitor measurements. Results: We have found that the algorithm avoids hypoglycemia (not caused by physical activity or stress) independently from the considered absorption profiles. Conclusion: Use of hard constraints proved their efficiency in fitting blood glucose level within a defined interval. However, in the future, more data of different T1DM patients will be collected and tested, including dynamic absorption model and in silico tests on validated simulators.
A maximum entropy shallow functional parser for spoken language understanding

In this paper we investigate a maximum entropy approach to spoken language understanding. We compare this approach with a parser based on finite-state transducers. The parsers are evaluated on a corpus of utterances modelling human-computer interactions within a single domain. The corpus was annotated with task-oriented semantic categories to obtain a set of shallow functional parse trees. We focus our investigation on the quality of the structured concepts produced by each approach. A direct comparison shows that the maximum entropy parser achieves better performance than the finite-state parser, even with very limited training data.
Assessment of Cadexomer Iodine against Staphylococcus aureus Biofilm In vivo and In vitro Using Confocal Laser Scanning Microscopy

Cadexomer iodine releases iodine (0.9% weight/weight) slowly from beads of dextrin and epichlorhydrin. This preparation is an effective debridement and antiseptic agent for chronic exdudative wounds. The purpose of the present study is to examine the influence of cadexomer iodine against glycocalyx production of Staphylococcus aureus isolated from furuncle lesions on cut wounds in mice using confocal laser scanning microscope (CLSM), and the increase in and glycocalyx production of S. aureus in vitro. In the present study, distinct S. aureus cells and glycocalyx were not detected in the dermis around the cadexomer iodine beads or within those beads, while S. aureus cells encircled by glycocalyx were soaked up by the cadexomer beads and were detected within them in vivo and in vitro. We suggest that cadexomer iodine soaks up S. aureus cells encircled by glycocalyx, directly destroys biofilm structures, and collapses glycocalyx during dehydration, and further, that iodine can subsequently kill S. aureus cells within biofilm. Cadexomer iodine is a promising treatment to clear S. aureus cells within biofilm from skin lesions of exudative or infectious wounds and to prevent wound exacerbation.
Microglia-Dependent Alteration of Glutamatergic Synaptic Transmission and Plasticity in the Hippocampus during Peripheral Inflammation

Peripheral inflammatory diseases are often associated with behavioral comorbidities including anxiety, depression, and cognitive dysfunction, but the mechanism for these is not well understood. Changes in the neuronal and synaptic functions associated with neuroinflammation may underlie these behavioral abnormalities. We have used a model of colonic inflammation induced by 2,4,6-trinitrobenzenesulfonic acid in Sprague Dawley rats to identify inflammation-induced changes in hippocampal synaptic transmission. Hippocampal slices obtained 4 d after the induction of inflammation revealed enhanced Schaffer collateral-induced excitatory field potentials in CA1 stratum radiatum. This was associated with larger-amplitude mEPSCs, but unchanged mEPSC frequencies and paired-pulse ratios, suggesting altered postsynaptic effects. Both AMPA- and NMDA-mediated synaptic currents were enhanced, and analysis of AMPA-mediated currents revealed increased contributions of GluR2-lacking receptors. In keeping with this, both transcripts and protein levels of the GluR2 subunit were reduced in hippocampus. Both long-term potentiation (LTP) and depression (LTD) were significantly reduced in hippocampal slices taken from inflamed animals. Chronic administration of the microglial/macrophage activation inhibitor minocycline to the inflamed animals both lowered the level of the cytokine tumor necrosis factor α in the hippocampus and completely abolished the effect of peripheral inflammation on the field potentials and synaptic plasticity (LTP and LTD). Our results reveal profound synaptic changes caused by a mirror microglia-mediated inflammatory response in hippocampus during peripheral organ inflammation. These synaptic changes may underlie the behavioral comorbidities seen in patients.
Encounter: based routing in DTNs

Current work in routing protocols for delay and disruption tolerant networks leverage epidemic-style algorithms that trade off injecting many copies of messages into the network for increased probability of message delivery. However, such techniques can cause a large amount of contention in the network, increase overall delays, and drain each mobile node’s limited battery supply. We present a new DTN routing algorithm, called Encounter-Based Routing (EBR), which maximizes delivery ratios while minimizing overhead and delay. Furthermore, we present a means of securing EBR against black hole denialof-service attacks. EBR achieves up to a 40% improvement in message delivery over the current state-of-the-art, as well as achieving up to a 145% increase in goodput. Also, we further show how EBR outperforms other protocols by introduce three new composite metrics that better characterize DTN routing performance.
Mechanical Lysis of Candida Cells for Crude Protein and Enzymatic Activity Estimation: Comparison of Three Methods

Cells of ten Candida strains were subjected to disruption using three methods-glass beads, sonicator and French pressure cell press separately and results compared for efficiency of each method. The French pressure cell press gave the highest protein yield and glass beads, the lowest (mean of means = 5.6, 40.0, 0.6 µg/ml, respectively, for the three methods). Enzymatic activity was also highest for the French pressure cell press and lowest for glass beads (mean of means = 0.94 mg/min/mg protein).