Miracle-dz/UniFAR-FTUs huggingface dataset:
Defining social acceptability in ecosystem management: a workshop proceedings; 1992 June 23-25; Kelso, WA.

by the software have been corrected; however, some mistakes may remain. Papers were provided in camera-ready form for printing by the authors, who are therefore responsible for the content and accuracy. Opinions expressed may not necessarily reflect the position of the U.S. Department of Agriculture. The use of trade, firm or corporation names in this publication is for the information and convenience of the reader. Such use does not constitute an official endorsement or approval by the U.S. Department of Agriculture of any product or service to the exclusion of others that may be suitable. This compendium of papers was developed in response to the assumption that implementing an ecological approach to forest management requires an understanding of socially acceptable forestry-what it is and the implications of doing it. The papers in this collection bring to bear perspectives from a variety of social science disciplines and question whether the focus on social acceptability is an appropriate and useful one. Abstract 1 Introduction: Social Acceptability in Ecosystem Management
Presentation Format and Online Reviews Persuasiveness: The Effect of Computer-Synthesized Speech

Computer-synthesized speech is emerging as a mainstream human-computer interface in post-PC devices. However, there is limited research on its effect on the user experience. We contribute to this emerging stream by focusing on online review persuasiveness. The current presentation standard is the text review accompanied by images and numeric ratings. We review the limited theory on the effect of synthesized speech on users and report preliminary results from a lab experiment. Our findings suggest that varying the message presentation, from text to speech, improves the persuasiveness of online reviews through stronger trust beliefs, attitude toward the subject of the review and purchase intention. However, they don’t support the most intuitive explanation for why: that synthesized speech increases user perceptions of trustworthiness, expertise, credibility and similarity of the source. If confirmed, our results would call for an exciting search for the mechanisms by which speech interfaces increase the persuasiveness of massages.
Bioimaging-based detection of mislocalized proteins in human cancers by semi-supervised learning

MOTIVATION There is a long-term interest in the challenging task of finding translocated and mislocated cancer biomarker proteins. Bioimages of subcellular protein distribution are new data sources which have attracted much attention in recent years because of their intuitive and detailed descriptions of protein distribution. However, automated methods in large-scale biomarker screening suffer significantly from the lack of subcellular location annotations for bioimages from cancer tissues. The transfer prediction idea of applying models trained on normal tissue proteins to predict the subcellular locations of cancerous ones is arbitrary because the protein distribution patterns may differ in normal and cancerous states. RESULTS We developed a new semi-supervised protocol that can use unlabeled cancer protein data in model construction by an iterative and incremental training strategy. Our approach enables us to selectively use the low-quality images in normal states to expand the training sample space and provides a general way for dealing with the small size of annotated images used together with large unannotated ones. Experiments demonstrate that the new semi-supervised protocol can result in improved accuracy and sensitivity of subcellular location difference detection. AVAILABILITY AND IMPLEMENTATION The data and code are available at: www.csbio. sjtu.edu. cn/bioinf/SemiBiomarker/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Distributed Early Worm Detection Based on Payload Histograms

Epidemic worms has become a social problem owing to their potency in paralyzing the Internet, thus affecting our way of life. Recent researches have pointed out that epidemic worms can propagate similar payloads rapidly. It was shown that it is possible to evaluate similarities between these payloads in terms of a 256-dimensional vector based on histograms of the appearance frequencies of 256 character codes. This observation has also been confirmed by our earlier works. However, this method, if applied to flows from only one network, which means a network managed by an independent organization, is prone to a high rate of false positives in cases such as when normal emails are sent through a mailing list. To overcome this problem, we propose a new scheme which checks for any similarity between flows detected at several IDSs in a distributed environment. The proposed scheme is based on the fact that normal payloads propagating from different networks are different, whereas in the case of epidemic worms payloads even propagated through different networks but generated by the same worm exhibit similarity. We have demonstrated the effectiveness of the proposed scheme through extensive experiments using real network traffic that contains worms.
Detecting Stopping Track Muons with the IceCube Neutrino Observatory

Neutrinos have become an important tool in the study of the universe because of their weak interaction with matter, but due to this property it is also difficult to detect them. One way to indirectly detect them is through another particle, the muon. This method is being carried out in the IceCube Neutrino Observatory. Currently the detector has limited information about the interaction of low energy muons and the effect they have on the detectors. It is therefore necessary to study these low energy muons at their minimum ionizing energy to find the probability of them hitting a Digital Optical Module (DOM). This will allow us to calibrate the detector for low energy muons and neutrinos. This was done by using simulated data with the COsmic Ray SImulations for KAscade (CORSIKA) program which runs Monte Carlo
Encoding of Spatio-Temporal Input Characteristics by a CA1 Pyramidal Neuron Model

The in vivo activity of CA1 pyramidal neurons alternates between regular spiking and bursting, but how these changes affect information processing remains unclear. Using a detailed CA1 pyramidal neuron model, we investigate how timing and spatial arrangement variations in synaptic inputs to the distal and proximal dendritic layers influence the information content of model responses. We find that the temporal delay between activation of the two layers acts as a switch between excitability modes: short delays induce bursting while long delays decrease firing. For long delays, the average firing frequency of the model response discriminates spatially clustered from diffused inputs to the distal dendritic tree. For short delays, the onset latency and inter-spike-interval succession of model responses can accurately classify input signals as temporally close or distant and spatially clustered or diffused across different stimulation protocols. These findings suggest that a CA1 pyramidal neuron may be capable of encoding and transmitting presynaptic spatiotemporal information about the activity of the entorhinal cortex-hippocampal network to higher brain regions via the selective use of either a temporal or a rate code.
Evaluation of the appropriate different reference crops to quantify N 2 fixation in soybean ( Glycine max L . ) using the 15 N isotopic method

There are several methods available to assess the amount of biological nitrogen fixation (BNF), among them both the N isotopic method and the nitrogen difference method can estimate BNF. These methods require an appropriate non-N-fixing reference plant which must obtain all its N from the same soil pools as the N-fixing plant, without any nitrogen derived from atmosphere. The present experiment was conducted to evaluate the suitability of various reference plants for determination of BNF in three soybean varieties, which are most cultivated in Iran. For this purpose a factorial experiment was carried out under greenhouse conditions using pots containing a loamy clay soil with a low level of nitrogen (530 and 12.5 mg kg for total-N and mineral-N, respectively) and no indigenous rhizobia. Seeds were pre-germinated in sterile conditions and, at the time of plantation, each seedling was inoculated with one ml of Bradyrhizobium japonicum inoculum grown in Yeast extract Manitol Broth containing about 10cells mL. Soybean cultivars were Clark-63, Williams and Pershing. The reference crops were two wheat cultivars (Omid and Tabas), one local cultivar (Valfajer) of barley, an noninoculated soybean and a non-nodulating isoline of soybean Chippewa. Each treatment was replicated 4 times. For quantifying BNF using the A-value approach, two solutions of N-15 enriched ammonium sulfate (9.616% and 2.086% N-15 atom excess) were applied in amounts equivalent to 20 and 100 kg N ha at plant developmental stage V2 (vegetative 2) to fixing and plant developmental stages V2, R2 (reproductive 2) and R5 to reference pots. Four months after planting (stage R6) the plants were harvested, oven dried (70C) and ground to a fine powder. Total N and N-15 were determined using semi Kjeldhal and emission spectrometry. The percentages of nitrogen drived from air (Ndfa%), soil (Ndfs%) and fertilizer (Ndff%) were calculated. Results showed significant difference between reference crops. The suitability of uninoculated soybean reference plants (except Williams) was significantly similar to non-nodulating soybean Chippewa despite Wheats and Barely. Also, this was the same for all of them for proportions of nitrogen derived from atmosphere and soil sources. Furthermore, according to the Ndfa%, more than 90% of the N required by soybean cultivars were supplied through symbiosis. In view of amount and proportion of nitrogen derived from air Pershing fixed significantly more nitrogen than two another cultivars. BIERANVAND ET AL. 17 WCSS, 14-21 August 2002, Thailand 1651-2
Diffusion framework for geometric and photometric data fusion in non-rigid shape analysis

In this paper, we explore the use of the diffusion geometry framework for the fusion of geometric and photometric information in local and global shape descriptors. Our construction is based on the definition of a diffusion process on the shape manifold embedded into a high-dimensional space where the embedding coordinates represent the photometric information. Experimental results show that such data fusion is useful in coping with different challenges of shape analysis where pure geometric and pure photometric methods fail.
Heme Oxygenase in the Rat Anterior Pituitary: Immunohistochemical Localization and Possible Role in Gonadotropin and Prolactin Secretion

The objectives of this study were to determine if heme oxygenase (HO), which catalyzes the degradation of heme and the formation of carbon monoxide (CO), is localized in the rat anterior pituitary and, if so, to determine if hemin (a substrate for HO) or chromium mesoporphyrin (CrMP) (an inhibitor of HO), alter pituitary gonadotropin and prolactin secretion. For localization of HO, sections of anterior pituitaries obtained from mature Holtzman Sprague-Dawley rats in different stages of the estrous cycle were immunostained for two of the HO isoforms, HO-1 and HO-2. The immunostaining for the inducible HO isoform (HO-1) was limited to discrete populations of pituitary cells, whereas the constitutive isoform (HO-2) had a more widespread distribution. The afternoon surge of leutinizing hormone (LH) in the plasma of ovariectomized, estradiol-treated rats was advanced by 2 hr after 7 days of treatment with CrMP (4 μM/kg), and this effect was reversed when hemin (30 μM/kg) was coadministered with CrMP. The afternoon follicle-stimulating hormone (FSH) surge was not affected by either treatment. In contrast, the afternoon prolactin (PRL) surge was completely blocked or delayed by CrMP treatment, and this effect was not reversed by hemin. In vitro perifusion of pituitary explants with CrMP also significantly reduced PRL release compared with secretion from untreated explants. In vitro gonadotropin-releasing hormone (GnRH)-stimulated FSH secretion was significantly increased from pituitary explants of ovariectomized, estradiol-treated rats treated in vivo with hemin but was unaffected by CrMP treatment, whereas GnRH-stimulated LH release was not affected by hemin but was increased by CrMP treatment. In conclusion, this study demonstrates that HO exists in the rat anterior pituitary gland, and that a substrate and an inhibitor of this enzyme alter the secretion of gonadotropins and PRL.
Short-Term Traffic Flow Prediction Using Neuro-Genetic Algorithms

This paper presents a new short-term traffic flow prediction system based on an advanced Time Delay Neural Network (TDNN) model, the structure of which is synthesized using a Genetic Algorithm (GA). The model predicts flow and occupancy values at a given freeway section based on contributions from their recent temporal profile (over a few minutes) as well the spatial profile (including inputs from neighboring upstream and downstream sections). An in-depth investigation of the variables pertinent to traffic flow prediction was conducted examining the extent of the "look-back" in time interval, the extent of prediction in the future, the extent of spatial contribution, the resolution of the input data, and their effects on prediction accuracy. The model's performance is validated using both simulated and real traffic flow data obtained from the ATMS Testbed in Orange County, California. Both temporal and spatial effects were found to be essential for proper prediction. Results obtained indicate that the prediction errors vary inversely with the extent of the spatial contribution, and that the inclusion of three loop stations in both directions of the subject station is sufficient for practical purposes. Also, the longer the extent of prediction, the more the predicted values tend toward the mean of the actual, for which case the optimal look-back interval also shortens. The results also indicate that the level of data aggregation/resolution should be comparable to the prediction horizon for best accuracy. The model performed acceptably using both simulated and real data. The model also showed potential to be superior to such other well-known neural network models as the Multi layer Feed-forward (MLF) when applied to the same problem.
Detection and Estimation Algorithms in Massive MIMO Systems

This book chapter reviews signal detection and parameter estimation techniques for multiuser multiple-antenna wireless systems with a very large number of antennas, known as massive multi-input multi-output (MIMO) systems. We consider both centralized antenna systems (CAS) and distributed antenna systems (DAS) architectures in which a large number of antenna elements are employed and focus on the uplink of a mobile cellular system. In particular, we focus on receive processing techniques that include signal detection and parameter estimation problems and discuss the specific needs of massive MIMO systems. Simulation results illustrate the performance of detection and estimation algorithms under several scenarios of interest. Key problems are discussed and future trends in massive MIMO systems are pointed out.
Urban change monitoring from multi-temporal TerraSAR-X images

Monitoring urban growth and change is an important issue for urban planning and disaster management. In this study, three temporal TerraSAR-X images are used to monitor the urban changes. The difference and correlation coefficient between two images are calculated with a sliding window. Then a new factor that composites the difference and correlation coefficient is proposed to detect the changes. The Tokyo international airport expansion construction is used as a case study. The urban changes due to the progress of the construction are detected by the proposed approach. Then an aerial photograph taken during the construction and the visually detected results are used to verify the accuracy of the results.
TRACE TRANSFORM AND KLT BASED INVARIANT FEATURES AND IMAGE RECOGNITION SYSTEM

SUMMARY An important problem in invariant image recognition is automatic extraction of invariant features, which are able to describe an object invariant under translation, rotation and scale. Elegant solution of this problem is using Trace transform based on Triple Features. To compute invariant Triple Features a sophisticated combination of three functionals (Trace, Circus and Diametric) is needed. The paper overline the properties of the functionals must have in order to extract invariant features. The problem of high dimensionality and selecting of optimal combinations of functionals is solved using Karhunen - Loeve transform (KLT). The new architecture of invariant image recognition system based on Trace transform and KLT is presented. The system performance was tested in image recognition experiments.
An Arabidopsis Mutant Hypersensitive to Red and Far-Red Light Signals

A new mutant called psi2 (for phytochrome signaling) was isolated by screening for elevated activity of a chlorophyll a/b binding protein–luciferase (CAB2–LUC) transgene in Arabidopsis. This mutant exhibited hypersensitive induction of CAB1, CAB2, and the small subunit of ribulose-1,5-bisphosphate carboxylase (RBCS) promoters in the very low fluence range of red light and a hypersensitive response in hypocotyl growth in continuous red light of higher fluences. In addition, at high-but not low-light fluence rates, the mutant showed light-dependent superinduction of the pathogen-related protein gene PR-1a and developed spontaneous necrotic lesions in the absence of any pathogen. Expression of genes responding to various hormone and environmental stress pathways in the mutant was not significantly different from that of the wild type. Analysis of double mutants demonstrated that the effects of the psi2 mutation are dependent on both phytochromes phyA and phyB. The mutation is recessive and maps to the bottom of chromosome 5. Together, our results suggest that PSI2 specifically and negatively regulates both phyA and phyB phototransduction pathways. The induction of cell death by deregulated signaling pathways observed in psi2 is reminiscent of retinal degenerative diseases in animals and humans.
“One Entity per Discourse” and “One Entity per Collocation” Improve Named-Entity Disambiguation

The “one sense per discourse” (OSPD) and “one sense per collocation” (OSPC) hypotheses have been very influential in Word Sense Disambiguation. The goal of this paper is twofold: (i) to explore whether these hypotheses hold for entities, that is, whether several mentions in the same discourse (or the same collocation) tend to refer to the same entity or not, and (ii) test their impact in Named-Entity Disambiguation (NED). Our experiments show consistent results on different collections and three state-of-the-art NED system. OSPD hypothesis holds in around 96%-98% of documents whereas OSPC hypothesis holds in 91%-98% of collocations. Furthermore, a simple NED post-processing in which the majority entity is promoted, produces a gain in performance in all cases, reaching up to 8 absolute points of improvement in F-measure. These results show that NED systems would benefit of considering these hypotheses into their implementation.
EhADH112 Is a Bro1 Domain-Containing Protein Involved in the Entamoeba histolytica Multivesicular Bodies Pathway

EhADH112 is an Entamoeba histolytica Bro1 domain-containing protein, structurally related to mammalian ALIX and yeast BRO1, both involved in the Endosomal Sorting Complexes Required for Transport (ESCRT)-mediated multivesicular bodies (MVB) biogenesis. Here, we investigated an alternative role for EhADH112 in the MVB protein trafficking pathway by overexpressing 166 amino acids of its N-terminal Bro1 domain in trophozoites. Trophozoites displayed diminished phagocytosis rates and accumulated exogenous Bro1 at cytoplasmic vesicles which aggregated into aberrant complexes at late stages of phagocytosis, probably preventing EhADH112 function. Additionally, the existence of a putative E. histolytica ESCRT-III subunit (EhVps32) presumably interacting with EhADH112, led us to perform pull-down experiments with GST-EhVps32 and [35S]-labeled EhADH112 or EhADH112 derivatives, confirming EhVps32 binding to EhADH112 through its Bro1 domain. Our overall results define EhADH112 as a novel member of ESCRT-accessory proteins transiently present at cellular surface and endosomal compartments, probably contributing to MVB formation during phagocytosis.
Visualizations relevant to the user by multi-view latent variable factorization

A main goal of data visualization is to find, from among all the available alternatives, mappings to the 2D/3D display which are relevant to the user. Assuming user interaction data, or other auxiliary data about the items or their relationships, the goal is to identify which aspects in the primary data support the user's input and, equally importantly, which aspects of the user's potentially noisy input have support in the primary data. For solving the problem, we introduce a multi-view embedding in which a latent factorization identifies which aspects in the two data views (primary data and user data) are related and which are specific to only one of them. The factorization is a generative model in which the display is parameterized as a part of the factorization and the other factors explain away the aspects not expressible in a two-dimensional display. Functioning of the model is demonstrated on several data sets.
Transforming regulations into performance models in the context of reasoning for outcome-based compliance

Recently, interest in performance modeling of out-come-based regulations has grown in the regulatory community. In this context, performance modeling refers to the measuring of important business aspects in a coordinated manner and the use of these measurements for improved decision making. Goal modeling techniques have shown to be beneficial when expressing and analyzing performance models. Since most regulations are still written in natural language, support for the transformation of regulatory text into performance models is needed. This allows regulators and regulated parties to keep working with familiar natural language regulations and to use goal models indirectly while avoiding a potentially significant learning curve for goal-modeling techniques. In this paper, we present such a tool-supported transformation to goal models expressed with the User Requirements Notation that enables reasoning about outcome-based regulations via widely available evaluation mechanism for goal models. The transformation is implemented in the jUCM-Nav goal modeling tool and illustrated with an example from the banking domain.
The Effects of Contextual Strength on Phonetic Identification in Younger and Older Listeners

It has often been reported that older listeners have difficulty discriminating between phonetically similar items, but may rely on contextual cues as a compensatory mechanism. The present study examined the effects of different degrees of semantic bias on speech perception in groups of younger and older listeners. Stimuli from two /g/-/k/ voice onset time (VOT) continua were presented at the end of biasing and neutral sentences. Results indicated that context strongly influenced phonetic identification in older listeners; this was true for younger listeners only in the case of less-than-ideal stimuli. Findings are discussed in relation to theories concerning age-related changes in speech processing.