Miracle-dz/UniFAR-FTUs huggingface dataset:
Dormancy release of Norway spruce under climatic warming: testing ecophysiological models of bud burst with a whole-tree chamber experiment.

Ecophysiological models predicting timing of bud burst were tested with data gathered from 40-year-old Norway spruce (Picea abies (L.) Karst. ) trees growing in northern Sweden in whole-tree chambers under climatic conditions predicted to prevail in 2100. Norway spruce trees, with heights between 5 and 7 m, were enclosed in individual chambers that provided a factorial combination of ambient (365 micromol mol-1) or elevated (700 micromol mol-1) atmospheric CO2 concentration, [CO2], and ambient or elevated air temperature. Temperature elevation above ambient ranged from +2.8 degrees C in summer to +5.6 degrees C in winter. Compared with control trees, elevated air temperature hastened bud burst by 2 to 3 weeks, whereas elevated [CO2] had no effect on the timing of bud burst. A simple model based on the assumption that bud rest completion takes place on a fixed calendar day predicted timing of bud burst more accurately than two more complicated models in which bud rest completion is caused by accumulated chilling. Together with some recent studies, the results suggest that, in adult trees, some additional environmental cues besides chilling are required for bud rest completion. Although it appears that these additional factors will protect trees under predicted climatic warming conditions, increased risk of frost damage associated with earlier bud burst cannot be ruled out. Inconsistent and partially anomalous results obtained in the model fitting show that, in addition to phenological data gathered under field conditions, more specific data from growth chamber and greenhouse experiments are needed for further development and testing of the models.
A New Method for Rule Finding Via Bootstrapped Confidence Intervals

Association rule discovery in large data sets is vulnerable to producing excessive false positives, due to the multiple inference eﬀect . Analytical results presented here indicate that Bonferonni-based solutions to this problem may have inherent limitations. Thus the paper proposes a new approach to this problem, based on simultaneous conﬁdence intervals, computed via a novel use of the statistical boot-strap tool. The proposal here diﬀers markedly from previous bootstrap/resampling approaches, not only in function but also in basic goal, which is to enable much more active participation by domain experts. The new method is computationally intensive, but another analytical result presented here has implications for reducing the amount of computation.
Interference-aware geocasting for VANET

With the introduction of standards such as DSRC and WAVE, vehicular ad hoc networks (VANET) are being considered as candidates to improve road safety. Safety applications developed on top of VANET enable vehicle and driver improved awareness of the road situation through vehicles sharing their status and knowledge of the road conditions. In order for these systems to operate, they depend on reliable communication. To overcome fading, shadowing and other effects that cause packet loss, such applications commonly use retransmission schemes to improve packet delivery. However, the wireless channels used for these applications are bandwidth constrained, and retransmission can cause interference which in turn will degrade the reliability of the communication channel. Therefore, it is necessary to find a strategy that balances retransmission with channel occupancy for optimal reliability. In this paper, we present a cooperative retransmission algorithm that overcomes shadowing caused by blocking objects such as heavy vehicles in order to combat the resulting unreliability, whilst controlling the interference caused by retransmissions. The proposed algorithm weighs up the additional area a node can cover, with the amount of interference a retransmission by the same node would cause. We evaluate the performance of the algorithm in urban scenarios using the NS-3 simulator, and find that the proposed algorithm is effective in overcoming the negative effects of shadows caused by blocking objects.
Unstructured volume‐agglomeration MG: Solution of the Poisson equation

We are interested in solving second-order PDEs with multigrid and unstructured meshes. The multigrid strategy we present here is adapted from the generalized finite volume agglomeration multigrid algorithm we have developed recently for the solution of the Euler equations. We now focus on Poisson's equation. A strategy is defined by introducing a correction factor for the diffusive terms, and some illustrating results are given.
An Empirical Investigation of Word Class-Based Features for Natural Language Understanding

There are many studies that show using class-based features improves the performance of natural language processing (NLP) tasks such as syntactic part-of-speech tagging, dependency parsing, sentiment analysis, and slot filling in natural language understanding (NLU), but not much has been reported on the underlying reasons for the performance improvements. In this paper, we investigate the effects of the word class-based features for the exponential family of models specifically focusing on NLU tasks, and demonstrate that the performance improvements could be attributed to the regularization effect of the class-based features on the underlying model. Our hypothesis is based on empirical observation that shrinking the sum of parameter magnitudes in an exponential model tends to improve performance. We show on several semantic tagging tasks that there is a positive correlation between the model size reduction by the addition of the class-based features and the model performance on a held-out dataset. We also demonstrate that class-based features extracted from different data sources using alternate word clustering methods can individually contribute to the performance gain. Since the proposed features are generated in an unsupervised manner without significant computational overhead, the improvements in performance largely come for free and we show that such features provide gains for a wide range of tasks from semantic classification and slot tagging in NLU to named entity recognition (NER).
Measurement Properties and Implementation of a Checklist to Assess Leadership Skills during Interdisciplinary Rounds in the Intensive Care Unit

The implementation of interdisciplinary teams in the intensive care unit (ICU) has focused attention on leadership behavior. A daily recurrent situation in ICUs in which both leadership behavior and interdisciplinary teamwork are integrated concerns the interdisciplinary rounds (IDRs). Although IDRs are recommended to provide optimal interdisciplinary and patient-centered care, there are no checklists available for leading physicians. We tested the measurement properties and implementation of a checklist to assess the quality of leadership skills in interdisciplinary rounds. The measurement properties of the checklist, which included 10 essential quality indicators, were tested for interrater reliability and internal consistency and by factor analysis. The interrater reliability among 3 raters was good (κ, 0.85) and the internal consistency was acceptable (α, 0.74). Factor analysis showed all factor loadings on 1 domain (>0.65). The checklist was further implemented during videotaped IDRs which were led by senior physicians and in which 99 patients were discussed. Implementation of the checklist showed a wide range of "no" and "yes" scores among the senior physicians. These results may underline the need for such a checklist to ensure tasks are synchronized within the team.
Strong converse and Stein's lemma in quantum hypothesis testing

The hypothesis testing problem for two quantum states is treated. We show a new inequality between the errors of the first kind and the second kind, which complements the result of Hiai and Petz (1991) to establish the quantum version of Stein's lemma. The inequality is also used to show a bound on the probability of errors of the first kind when the power exponent for the probability of errors of the second kind exceeds the quantum relative entropy, which yields the strong converse in quantum hypothesis testing. Finally, we discuss the relation between the bound and the power exponent derived by Han and Kobayashi (1989) in classical hypothesis testing.
Simple steps help minimize costs, risks in project contracts

Contrary to prevailing opinion, risks and project financing costs can be higher for lump sum (LS) project contracts than under reimbursable-type contracts. An element-by-element analysis of the risks and costs associated with a project enables investors to develop variations of reimbursable contracts. Project managers can use this three-step procedure, along with other recommendations, to measure the hidden project costs and risks associated with LS contracts. The author bases his conclusions on case studies of recent projects in the petroleum refining and petrochemical industries. The findings, however, are general enough to be applicable in other industrial sectors.
Single-Molecule DNA Sequencing of a Viral Genome

The full promise of human genomics will be realized only when the genomes of thousands of individuals can be sequenced for comparative analysis. A reference sequence enables the use of short read length. We report an amplification-free method for determining the nucleotide sequence of more than 280,000 individual DNA molecules simultaneously. A DNA polymerase adds labeled nucleotides to surface-immobilized primer-template duplexes in stepwise fashion, and the asynchronous growth of individual DNA molecules was monitored by fluorescence imaging. Read lengths of >25 bases and equivalent phred software program quality scores approaching 30 were achieved. We used this method to sequence the M13 virus to an average depth of >150× and with 100% coverage; thus, we resequenced the M13 genome with high-sensitivity mutation detection. This demonstrates a strategy for high-throughput low-cost resequencing.
A Stacked VCO Architecture for Generating Multi-level Synchronous Control Signals

This paper presents a VCO architecture capable of generating multi-level synchronous control signals. It has been implemented by stacking multiple identical VCOs which reuse the current among themselves and thereby reduces the overall power dissipation. Clock frequency of all the voltage levels can be controlled by a single input. This stacked VCO can be used to generate switch control signals having optimum voltage swings, for multi-phase Switched-Capacitor based DC-DC converters. The design has been implemented in 65 nm, triple-well, bulk CMOS process. The design example utilizes 3.3 V supply to generate perfectly synchronous clock phases in three separate voltage levels, namely, 0V-1.1V, 1.1V-2.2V and 2.2V-3.3V. The VCO provides output frequency ranging from 16 MHz to 150 MHz with a gain (KV CO) of 248 KHz/mV. Simulation results are presented to demonstrate the functionality and robustness of the design.
A dual function for Munc‐18 in exocytosis of PC12 cells

Munc‐18 interacts with the SNARE protein syntaxin and is supposed to influence transmitter release by controlling the formation of exocytosis‐relevant SNARE complexes. Here, we used combined biochemical and physiological analyses to study the role of the Munc‐18/syntaxin interaction in large dense core vesicle (LDCV) exocytosis of neuroendocrine PC12 cells. We compared two Munc‐18 mutants carrying mutations in the syntaxin‐binding region and show that Munc‐18's membrane association depends on direct binding to syntaxin. The data suggest that perturbation of syntaxin binding inhibits neurotransmitter release upstream of the individual fusion event implying an essential role of the Munc‐18/syntaxin complex leading to exocytosis. Furthermore, we show that a Munc‐18 mutant lacking any syntaxin binding has a stimulatory effect on secretion, and provide evidence that the Munc‐18/Mint1 interaction may constitute a second pathway for Munc‐18 to regulate exocytosis. We propose that Munc‐18 represents a dynamic link between syntaxin‐related and Mint1‐related mechanisms, both involved in the control of LDCV exocytosis in neuroendocrine cells.
A Boosting-like Online Learning Ensemble

Changes in the data distribution (concept drift) makes online learning a challenge that is progressively attracting more attention. This paper proposes Boosting-like Online Learning Ensemble (BOLE) based on heuristic modifications to Adaptable Diversity-based Online Boosting (ADOB), which is a modified version of Oza and Russell's Online Boosting. More precisely, we empirically investigate the effects of (a) weakening the requirements to allow the experts to vote and (b) changing the concept drift detection method internally used, aiming to improve the ensemble accuracy. BOLE was tested against the original and other modified versions of both boosting methods as well as three renowned ensembles using well-known artificial and real-world datasets and statistically surpassed the accuracies of both boosting methods as well as those of the three ensembles. The accuracy improved in most tested situations but this is more evident in the datasets with more concept drifts, where the accuracy gains were very high.
Applications of nonlinear diffusion in image processing and computer vision

Nonlinear diffusion processes can be found in many recent methods for image processing and computer vision. In this article, four applications are surveyed: nonlinear diffusion filtering, variational image regularization, optic flow estimation, and geodesic active contours. For each of these techniques we explain the main ideas, discuss theoretical properties and present an appropriate numerical scheme. The numerical schemes are based on additive operator splittings (AOS). In contrast to traditional multiplicative splittings such as ADI, LOD or D'yakonov splittings, all axes are treated in the same manner, and additional possibilities for efficient realizations on parallel and distributed architectures appear. Geodesic active contours lead to equations that resemble mean curvature motion. For this application, a novel AOS scheme is presented that uses harmonie averaging and does not require reinitializations of the distance function in each iteration step.
The effect of interaction modality for facial-constrained robots in domestic environment

There is an increase in the number of functional-service robots in a domestic environment. Although most of functional-service robots are lack expressive faces, research that supports social interaction between users and facial-constrained robots are limited. This study investigated what interaction modalities can be effectively used for naturalistic social interaction between users and facial-constrained robots in a domestic environment. We applied non-facial and non-verbal interaction methods for representing robots' state. We conducted a 3 (modalities: motion vs. light vs. sound) within-participants experiment (N=25). Using motion was the most familiar way of interaction between a user and a non-facial robot. Also, robots' perceived sociality was associated with people's preference for robots. This study shows evidence that robots' motion would be helpful for users to understand the robots' mind in a social manner; furthermore, it would enhance users' acceptance of robots.
Righting Software

What tools do we use to develop and debug software? Most of us rely on a full-screen editor to write code, a compiler to translate it, a source-level debugger to correct it, and a source-code control system to archive and share it. These tools originated in the 1970s, when the change from batch to interactive programming stimulated the development of innovative languages, tools, environments, and other utilities we take for granted. Microsoft Research has developed two generations of tools, some of which Microsoft developers already use to find and correct bugs. These correctness tools can improve software development by systematically detecting programming errors.
Automated Translation of a Literary Work: A Pilot Study

Current machine translation (MT) techniques are continuously improving. In specific areas , post-editing (PE) can enable the production of high-quality translations relatively quickly. But is it feasible to translate a literary work (fiction, short story, etc) using such an MT+PE pipeline? This paper offers an initial response to this question. An essay by the American writer Richard Powers, currently not available in French, is automatically translated and post-edited and then revised by non-professional translators. In addition to presenting experimental evaluation results of the MT+PE pipeline (MT system used, automatic evaluation), we also discuss the quality of the translation output from the perspective of a panel of readers (who read the translated short story in French, and answered a survey afterwards). Finally, some remarks of the official French translator of R. Powers, requested on this occasion, are given at the end of this article.
Inertial Proprioceptive Devices: Self-Motion-Sensing Toys and Tools

One of the current goals of technology is to redirect computation and communication capabilities from within the traditional computer and into everyday objects and devices—to make devices. one important function of smart devices is motion sensing. a proprioceptive device has a sense of its own motion and position. this ability can allow pens to remember what they have written, cameras to record their positions along with images, and baseball bats to communicate to batters information about their swing. in this paper, inertial sensing is introduced as the logical choice for unobtrusive, fully general motion sensing. example proprioceptive device applications are presented along with their sensing ranges and sensitivities. finally, the technologies used in implementing inertial sensors are described, and a survey of commercially available accelerometers and gyroscopes is presented.
Routing Metric Based on Node Degree for Load-Balancing in Large-Scale Networks

Traffic Engineering (TE) is required for reducing highly-loaded links/nodes in a part of networks, thereby reducing the traffic concentration in a part of network. For efficient use of network resources, it is important to efficiently map traffic demands to network resources. However, most of the existing TE schemes are not aware of underlying network topology, Indeed, they try to dynamically map traffic demands to network resources in response to traffic trends in a short period of time. The paper addresses the issue of network congestion due to inefficient mapping between traffic demand and network resources. We propose a new routing metric to allocate forwarding route from source node to its destinations for effective use of network resources in scale-free networks. We show that the best routing metric is $p$-norm based on node degrees along a path to destination node. Furthermore, we investigate the impact of the parameter, $p$, on congestion level of each link, and show the best parameter $p$ to minimize the maximum stress centrality in a network.
Energy Efficiency With Proportional Rate Fairness in Multirelay OFDM Networks

This paper investigates the energy efficiency (EE) in multiple relay-aided OFDM systems, where decode-and-forward (DF) relay beamforming is employed to help the information transmission. In order to explore the system performance behavior with user fairness for such a system, an optimization problem is formulated to maximize the EE by jointly considering multiple factors, i.e., the transmission mode selection (DF relay beamforming or direct-link transmission), the helping relay set selection, the subcarrier assignment and the power allocation at the source and relays on subcarriers, under nonlinear proportional rate fairness constraints, where both transmit power consumption and linearly rate-dependent circuit power consumption are taken into account. To solve the nonconvex optimization problem, we propose a low-complexity scheme to approximate it. Simulation results demonstrate its effectiveness. The effects of the circuit power consumption on system performance is also studied and it is observed that with either the constant or the linearly rate-dependent circuit power consumption, system EE grows with the increment of system average channel-to-noise ratio (CNR), but the growth rates show different behaviors. For the constant circuit power consumption, system EE increasing rate is an increasing function of the average CNR, while for the linearly rate-dependent one, system EE increasing rate is a decreasing function of the average CNR. This observation is very important, which indicates that by deducing the circuit dynamic power consumption per unit data rate, system EE can be greatly enhanced. Besides, we also discuss the effects of the number of users and subcarriers on the system EE performance.
Systems Level Dissection of Candida Recognition by Dectins: A Matter of Fungal Morphology and Site of Infection

Candida albicans is an ubiquitous fungal commensal of human skin and mucosal surfaces, and at the same time a major life-threatening human fungal pathogen in immunocompromised individuals. Host defense mechanisms rely on the capacity of professional phagocytes to recognize Candida cell wall antigens. During the past decade, the host immune response to Candida was dissected in depth, highlighting the essential role of C-type lectin receptors, especially regarding the power of the Dectins’ family in discriminating between the tolerated yeast-like form of Candida and its invading counterpart, the hyphae. This review focuses on the immuno-modulatory properties of the Candida morphologies and their specific interactions with the host innate immune system in different body surfaces.
Factors influencing compliance to tactical driver advice: An assessment using a think-aloud protocol

Connected Cruise Control (CCC) is an in-car driver support systems that aims to improve throughput in dense motorway traffic by advising drivers how to drive. The system is currently under development within a HTAS project. It will integrate lane advice, headway advice and speed advice. CCC will not take over vehicle control. This makes its effectiveness dependent on the drivers ability and willingness to comply to the advice. In the present study we used a think-aloud protocol, during the first on-road field-test of the CCC system, to assess drivers' initial reactions to the advice. From the transcripts we extracted factors that can influence compliance to tactical driver advice. These factors can be used to formulate hypotheses about driver compliance to CCC.