Miracle-dz/UniFAR-FTUs huggingface dataset:
Coffee and Tea Intake and Risk of Head and Neck Cancer: Pooled Analysis in the International Head and Neck Cancer Epidemiology Consortium

Background: Only a few studies have explored the relation between coffee and tea intake and head and neck cancers, with inconsistent results. Methods: We pooled individual-level data from nine case-control studies of head and neck cancers, including 5,139 cases and 9,028 controls. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (95% CI), adjusting for potential confounders. Results: Caffeinated coffee intake was inversely related with the risk of cancer of the oral cavity and pharynx: the ORs were 0.96 (95% CI, 0.94–0.98) for an increment of 1 cup per day and 0.61 (95% CI, 0.47–0.80) in drinkers of >4 cups per day versus nondrinkers. This latter estimate was consistent for different anatomic sites (OR, 0.46; 95% CI, 0.30–0.71 for oral cavity; OR, 0.58; 95% CI, 0.41–0.82 for oropharynx/hypopharynx; and OR, 0.61; 95% CI, 0.37–1.01 for oral cavity/pharynx not otherwise specified) and across strata of selected covariates. No association of caffeinated coffee drinking was found with laryngeal cancer (OR, 0.96; 95% CI, 0.64–1.45 in drinkers of >4 cups per day versus nondrinkers). Data on decaffeinated coffee were too sparse for detailed analysis, but indicated no increased risk. Tea intake was not associated with head and neck cancer risk (OR, 0.99; 95% CI, 0.89–1.11 for drinkers versus nondrinkers). Conclusions: This pooled analysis of case-control studies supports the hypothesis of an inverse association between caffeinated coffee drinking and risk of cancer of the oral cavity and pharynx. Impact: Given widespread use of coffee and the relatively high incidence and low survival of head and neck cancers, the observed inverse association may have appreciable public health relevance. Cancer Epidemiol Biomarkers Prev; 19(7); 1723–36. ©2010 AACR.
Driver rostering for bus transit companies

Staff scheduling has become increasingly important for both the public sector and private companies. Good rosters have many benefits for an organization, such as lower costs, more effective utilization of resources and fairer workloads and distribution of shifts. The process of constructing optimized work timetables for the personnel is an extremely demanding task. Driver rostering, preceded by vehicle scheduling and driver scheduling, is the last phase in the bus transit scheduling process. This paper presents a successful way to schedule days-off on a yearly basis and shifts on a monthly basis in one of the Finnish bus transportation companies. The days-off and shifts are scheduled using an algorithm that includes features from population-based methods, simulated annealing, tabu search and ejection-chains. The generated software has been integrated into a third-party vendor product.
A Context-Aware Model to Provide Positioning in Disaster Relief Scenarios

The effectiveness of the work performed during disaster relief efforts is highly dependent on the coordination of activities conducted by the first responders deployed in the affected area. Such coordination, in turn, depends on an appropriate management of geo-referenced information. Therefore, enabling first responders to count on positioning capabilities during these activities is vital to increase the effectiveness of the response process. The positioning methods used in this scenario must assume a lack of infrastructure-based communication and electrical energy, which usually characterizes affected areas. Although positioning systems such as the Global Positioning System (GPS) have been shown to be useful, we cannot assume that all devices deployed in the area (or most of them) will have positioning capabilities by themselves. Typically, many first responders carry devices that are not capable of performing positioning on their own, but that require such a service. In order to help increase the positioning capability of first responders in disaster-affected areas, this paper presents a context-aware positioning model that allows mobile devices to estimate their position based on information gathered from their surroundings. The performance of the proposed model was evaluated using simulations, and the obtained results show that mobile devices without positioning capabilities were able to use the model to estimate their position. Moreover, the accuracy of the positioning model has been shown to be suitable for conducting most first response activities.
Decision Support System for Optimizing Reservoir Operations Using Ensemble Streamflow Predictions

This paper investigates the value of ensemble streamflow predictions and energy price forecasts as aid to decision makers in scheduling the quantity and timing of reservoir releases for daily, weekly, and seasonal operations while meeting regulatory constraints. A decision support system DSS is described as it incorporates two integrated models of system operation: a simulation model that replicates general operating rules for the hydropower system and an optimization model that refines operations based upon forecasts of state variables. The DSS provides a series of recommendations for the quantity and timing of reservoir releases to optimize the economic value of the electrical energy produced, while balancing requirements and concerns related to flood control, environmental flows, and water supply. The DSS generates a range of optimal reservoir releases using an ensemble streamflow forecast and identifies robust operational solutions. The results indicate the value of the forecasts in improving system operation.
The Nature of Innovation and the Origin of Technological Spillovers

The aim of this paper is to show that innovations are the result of complex interactions between different private and public agents. For that, we identify the nature of the information sources that firms use to produce their innovations and assess the impact of these different sources on the results of the innovation process. We develop an econometric sequential model dealing successively with the innovation decision and the nature of innovation and use recent French data coming from the 1997 Community Innovation Survey. The main results are that innovation is not the result of isolated agents and that firms use very differently information sources according to the novelty degree of their innovation.
Microsatellite loci from the endemic Southern Ocean octopus Adelieledone polymorpha (Robson, 1930)

To determine the pattern of spatial genetic structure in the endemic Southern Ocean octopus Adelieledone polymorpha, microsatellite loci were isolated from partial genomic libraries enriched for repetitive DNA motifs. Seven dinucleotide and two trinucleotide microsatellite loci were isolated successfully and levels of polymorphism were quantified in 34 individuals sampled from the Southern Ocean near South Georgia. No pairs of microsatellite loci were linked significantly; however, one locus deviated (P < 0.05) from Hardy–Weinberg equilibrium. Overall, the nine loci produced between five and 16 alleles, with observed and expected heterozygosities varying between 0.22 and 0.86 and between 0.21 and 0.94 respectively. This is the first description of microsatellite loci from an octopus endemic to the Southern Ocean, and these genetic markers are being used to quantify spatial structure within A. polymorpha.
Networks with Group Counterproposals

We study two n-player sequential network formation games with externalities. Link formation is tied to simultaneous transfer selection in a Nash demand like game in each period. Players in groups can counterpropose. We give necessary and sufficient conditions for efficiency in terms of cyclical monotonicity. The n-player group version always yields efficiency.
Understanding Behaviours and Roles for Social and Adaptive Robots In Education: Teacher's Perspective

In order to establish a long-term relationship between a robot and a child, robots need to learn from the environment, adapt to specific user needs and display behaviours and roles accordingly. Literature shows that certain robot behaviours could negatively impact child's learning and performance. Therefore, the purpose of the present study is to not only understand teacher's opinion on the existing effective social behaviours and roles but also to understand novel behaviours that can positively influence children performance in a language learning setting. In this paper, we present our results based on interviews conducted with 8 language teachers to get their opinion on how a robot can efficiently perform behaviour adaptation to influence learning and achieve long-term engagement. We also present results on future directions extracted from the interviews with teachers.
Assessment Matters in Higher Education: Choosing and Using Diverse Approaches.

Part 1 Systems approaches to assessment: institutional strategies for assessment innovations in student assessment - a system-wide perspective assessment and evaluation - a systems approach for their utilization using assessment strategically to change the way students learn. Part 2 Exploring the effectiveness of innovative assessment: why assess innovatively? the experience of innovative assessment - student perspectives biases in marking students' written work - quality? Part 3 Assessing practice: assessing practice assessment of key skills using portfolios for assessment in teacher preparation and health sciences group-based assessment - an evaluation of the use of assessed tasks as a method of fostering higher quality learning dimensions of oral assessment and student approaches to learning. Part 4 Towards autonomous assessment towards autonomous assessment - using self and peer assessment self and peer assessment peer assessment of undergraduate seminar presentations - motivations, reflection and future directions using peer and self assessment for the first time.
Microarrays of cells expressing de ® ned cDNAs

NATURE | VOL 411 | 3 MAY 2001 | www.nature. com 107 21. Blasina, A. et al. A human homologue of the checkpoint kinase Cds1 directly inhibits Cdc25 phosphatase. Curr. Biol. 9, 1±10 (1999). 22. Liu, F. , Rothblum-Oviatt, C. , Ryan, C. E. & Piwnica-Worms, H. Overproduction of human Myt1 kinase induces a G2 cell cycle delay by interfering with the intracellular traf®cking of Cdc2-cyclin B1 complexes. Mol. Cell. Biol. 19, 5113±5123 (1999). 23. Alexander, M. R. et al. Regulation of cell cycle progression by swe1p and hog1p following hypertonic stress. Mol. Biol. Cell 12, 53±62 (2001).
An Efficient Program for Many-Body Simulation

The simulation of N particles interacting in a gravitational force field is useful in astrophysics, but such simulations become costly for large N. Representing the universe as a tree structure with the particles at the leaves and internal nodes labeled with the centers of mass of their descendants allows several simultaneous attacks on the computation time required by the problem. These approaches range from algorithmic changes (replacing an $O(N^2 )$ algorithm with an algorithm whose time-complexity is believed to be $O(N\log N)$) to data structure modifications, code-tuning, and hardware modifications. The changes reduced the running time of a large problem $(N = 10,000)$ by a factor of four hundred. This paper describes both the particular program and the methodology underlying such speedups.
Bloom Filters — A Tutorial , Analysis , and Survey

Bloom filters use superimposed hash transforms to provide a probabilistic membership test. The only types of errors are false positives (non-members being reported as members). Non-members are typically detected quickly (requiring only two probes in the optimal case). This article surveys modern applications of this technique (e.g., in spell checking and Web caching software) and provides a detailed analysis of their performance, in theory and practice. The article concludes with practical advice about implementing this useful and intriguing technique.
An Analysis of State–Local Government Capital Expenditure During the 2000s

Capital expenditure by subnational governments in the United States represents about two percent of GDP and 12 percent of state–local spending. Persistent differences among states exist in the amount and composition of this capital expenditure. This regression‐based research examines for the decade of the 2000s: (1) the factors affecting capital spending and interstate differences; (2) the effect of recessions; (3) the response to American Recovery and Reinvestment Act (ARRA) stimulus funds; (4) state and year fixed effects; and (5) investment for highways and K‐12 education. Aggregate capital expenditure is relatively stable, although it increased around recessions, with ARRA grants especially important and substantial state‐specific influences.
AN EMPIRICAL INVESTIGATION OF THE JAPANESE CORPORATE DEMAND FOR INSURANCE

Although numerous theoretical articles investigate factors affecting corporate demand for insurance, empirical tests of the theories are very limited. This article is one of the first attempts to empirically investigate the demand for general insurance of non-financial corporations by using data on Japanese corporations. Regarding insurance demand of Japanese corporations, size, leverage, and regiulation are important factors in determining insurance purchases by large Japanese firms, whereas ownership structure and tax consideration are not.
Granulocyte Colony Stimulating Factor and Physiotherapy after Stroke: Results of a Feasibility Randomised Controlled Trial: Stem Cell Trial of Recovery EnhanceMent after Stroke-3 (STEMS-3 ISRCTN16714730)

Background Granulocyte-colony stimulating factor (G-CSF) mobilises endogenous haematopoietic stem cells and enhances recovery in experimental stroke. Recovery may also be dependent on an enriched environment and physical activity. G-CSF may have the potential to enhance recovery when used in combination with physiotherapy, in patients with disability late after stroke. Methods A pilot 2 x 2 factorial randomised (1:1) placebo-controlled trial of G-CSF (double-blind), and/or a 6 week course of physiotherapy, in 60 participants with disability (mRS >1), at least 3 months after stroke. Primary outcome was feasibility, acceptability and tolerability. Secondary outcomes included death, dependency, motor function and quality of life measured 90 and 365 days after enrolment. Results Recruitment to the trial was feasible and acceptable; of 118 screened patients, 92 were eligible and 32 declined to participate. 60 patients were recruited between November 2011 and July 2013. All participants received some allocated treatment. Although 29 out of 30 participants received all 5 G-CSF/placebo injections, only 7 of 30 participants received all 18 therapy sessions. G-CSF was well tolerated but associated with a tendency to more adverse events than placebo (16 vs 10 patients, p = 0.12) and serious adverse events (SAE) (9 vs 3, p = 0.10). On average, patients received 14 (out of 18 planned) therapy sessions, interquartile range [12, 17]. Only a minority (23%) of participants completed all physiotherapy sessions, a large proportion of sessions (114 of 540, 21%) were cancelled due to patient (94, 17%) and therapist factors (20, 4%). No significant differences in functional outcomes were detected in either the G-CSF or physiotherapy group at day 90 or 365. Conclusions Delivery of G-CSF is feasible in chronic stroke. However, the study failed to demonstrate feasibility for delivering additional physiotherapy sessions late after stroke therefore a definitive study using this trial design is not supported. Future work should occur earlier after stroke, alongside on-going clinical rehabilitation. Trial Registration ISRCTN.com ISRCTN16714730
Neural Multigrid

We propose a multigrid extension of convolutional neural networks (CNNs). Rather than manipulating representations living on a single spatial grid, our network layers operate across scale space, on a pyramid of tensors. They consume multigrid inputs and produce multigrid outputs; convolutional filters themselves have both within-scale and cross-scale extent. This aspect is distinct from simple multiscale designs, which only process the input at different scales. Viewed in terms of information flow, a multigrid network passes messages across a spatial pyramid. As a consequence, receptive field size grows exponentially with depth, facilitating rapid integration of context. Most critically, multigrid structure enables networks to learn internal attention and dynamic routing mechanisms, and use them to accomplish tasks on which modern CNNs fail. Experiments demonstrate wide-ranging performance advantages of multigrid. On CIFAR image classification, flipping from single to multigrid within standard CNN architectures improves accuracy at modest compute and parameter increase. Multigrid is independent of other architectural choices; we show synergistic results in combination with residual connections. On tasks demanding per-pixel output, gains can be substantial. We show dramatic improvement on a synthetic semantic segmentation dataset. Strikingly, we show that relatively shallow multigrid networks can learn to directly perform spatial transformation tasks, where, in contrast, current CNNs fail. Together, our results suggest that continuous evolution of features on a multigrid pyramid could replace virtually all existing CNN designs.
Decisional states

The computational mechanics de nition of a process internal states considers optimal prediction as the criterion for clustering: the process states consist of the histories that lead to the same distribution of future events. Knowledge of the current cluster for a given past, and its associated distribution of possible futures, is the minimal information necessary for making optimal predictions. However when given a practical problem for which a unique prediction is sought, this view o ers no distinction between futures with rather di erent consequences, incurred costs or expected utility. When each future is ponderated by its would-be e ect then decision theory must be used. This article explores the consequences of grouping histories into states with equivalent optimal decisions in terms of utility, rather than equivalent full distributions of futures. The transitions between these decisional states correspond to events that lead to a change of decision. The utility function encodes the a priori knowledge on a system, the decisional states represents the underlying structure matching both the intrinsic system causal states and the external information. An algorithm is provided so as to estimate the states and their transitions from data. Application examples are given for discrete process hidden state reconstruction, cellular automata ltering, and edge detection in images.
Description of KYOTO EBMT System in PatentMT at NTCIR-10

This paper describes“KYOTO”EBMT system that attended PatentMT at NTCIR-10. When translating very different language pairs such as Japanese-English, it is very important to handle sentences in tree structures to overcome the difference. Many of recent studies incorporate tree structures in some parts of translation process, but not all the way from model training (parallel sentence alignment) to decoding. “KYOTO” system is a fully tree-based translation system where we use the treelet alignment model by bilingual generation and monolingual derivation on dependency trees. and example-based translation.
Annotation schemes in North Sámi dependency parsing

In this paper we describe a comparison of two annotation schemes for dependency parsing of North Sámi, a Finno-Ugric language spoken in the north of Scandinavia and Finland. The two annotation schemes are the Giellatekno (GT) scheme which has been used in research and applications for the Sámi languages and Universal Dependencies (UD) which is a cross-lingual scheme aiming to unify annotation stations across languages. We show that we are able to deterministi-cally convert from the Giellatekno scheme to the Universal Dependencies scheme without a loss of parsing performance. While we do not claim that either scheme is a priori a more adequate model of North Sámi syntax, we do argue that the choice of annotation scheme is dependent on the intended application.
Vibration and Position Control of a Flexible Manipulator using a PD-tuned Controller with Modified Genetic Algorithm

Flexible manipulators have received wide attention being more realistic than their rigid counterparts in many practical conditions. The control of the motion and vibration of an elastic model has inspired many studies in the past decades. A modified genetic algorithm (MGA) is proposed to optimize the feedback gains of a proportional derivative (PD) controller used for the control of the position and vibration of a flexible arm. It has been shown that the new algorithm results in faster convergence and higher accuracy over the simple genetic algorithm (SGA). Also, MGA solves the problem of premature convergence and stagnation that is caused by SGA. Three different objective functions based on minimizing the error function were tested and compared. Multi-objective error fitness function combined with the proposed GA has given the best system response which encourages for further research into various control applications. Index Terms — Modified genetic algorithm, multi-objective optimization, PD controller, single-link flexible manipulator, simple genetic algorithm.
Polarimetric SAR model for soil moisture estimation over vineyards at C-band

In this paper we propose a two-component polarimetric model for soil moisture estimation on vineyards suited for C-band radar data. According to a polarimetric analysis carried out here, this scenario is made up of one dominant direct return from the soil and a multiple scattering component accounting for disturbing and non- modeled signal ∞uctuations from soil and short vegetation. We propose a combined X-Bragg/Fresnel approach to characterize the polarized direct response from soil. A validation of this polarimetric model has been performed in terms of its consistency with respect to the available data both from RADARSAT-2 and from indoor measurements. High inversion rates are reported for difierent phenological stages of vines, and the model gives a consistent interpretation of the data as long as the volume component power remains about or below 50% of the surface contribution power. However, the scarcity of soil moisture measurements in this study prevents the validation of the algorithm in terms of the accuracy of soil moisture retrieval and an extensive campaign is required to fully demonstrate the validity of the model. Difierent sources of mismatches between the model and the data have been also discussed and analyzed.