Miracle-dz/UniFAR-FTUs huggingface dataset:
Sensitivity characteristics of LPFGs inscribed in FMF

Few mode fiber (FMF) has been studied a lot in recent years. It is told that the co-propagating coupling between different modes in few mode long-period fiber gratings (FM-LPFGs) can get a large sensitivity in sensing measurement. In this paper, we present a comprehensive simulation about the sensing sensitivity of long-period fiber gratings (LPFGs) inscribed in few mode fiber (FMF). We recognize a sensitivity factor which contributes a lot to the sensing sensitivity, and calculate the value in FMF. Our analysis reveals a high sensitivity factor at the resonance wavelength of 1550nm when the resonant cladding mode order equals to 20. Our simulation proves that LPFGs inscribed in FMF, comparing with sing mode fiber (SMF), have a much better sensing performance in the temperature, strain and surrounding refractive index (RI) when the cladding mode order is closed to 20. Particularly, the maximum value of RI sensitivity can reach 1512 nm/10−3 in FMF when the surrounding RI equals to 1.43, five times as much as the value in SMF.
Sleep Influences the Severity of Memory Disruption in Amnestic Mild Cognitive Impairment: Results From Sleep Self-assessment and Continuous Activity Monitoring

Sleep is important for declarative memory consolidation in healthy adults. Sleep disruptions are typical in Alzheimer disease, but whether they contribute to memory impairment is unknown. Sleep has not been formally examined in amnestic mild cognitive impairment (aMCI), which is characterized by declarative-memory deficits without dementia and can signify prodromal Alzheimer disease. We studied 10 aMCI patients and 10 controls over 2 weeks using daily sleep surveys, wrist-worn activity sensors, and daily recognition tests. Recognition was impaired and more variable in aMCI patients, whereas sleep was similar across groups. However, lower recognition of items learned the previous day was associated with lower subjective sleep quality in aMCI patients. This correlation was not present for information learned the same day and thus did not reflect nonspecific effects of poor sleep on memory. These results indicate that inadequate memory consolidation in aMCI patients is related to declines in subjective sleep indices. Furthermore, participants with greater across-night sleep variability exhibited lower scores on a standardized recall test taken prior to the 2-week protocol, suggesting that consistent sleep across nights also contributes to successful memory. Physiological analyses are needed to further specify which aspects of sleep in neurological disorders impact memory function and consolidation.
Planning by Rewriting: Eeciently Generating High-quality Plans

Domain-independent planning is a hard combinatorial problem. Taking into account plan quality makes the task even more diicult. We introduce a new paradigm for eecient high-quality planning that exploits plan rewriting rules and eecient local search techniques to transform an easy-to-generate, but possibly sub-optimal, initial plan into a low-cost plan. In addition to addressing the issues of eeciency and quality, this framework yields a new anytime planning algorithm. We have implemented this planner and applied it to several existing domains. The results show that this approach provides signiicant savings in planning effort while generating high-quality plans.
Forecasting inflation with dynamic factor model – the case of Poland

The purpose of the article is to evaluate the forecasting performance of dynamic factor models in forecasting inflation in the Polish economy. The factor models are based on the assumption that the behavior of most macroeconomic variables can be well described by several unobservable factors, which are often interpreted as the driving factors in the economy. Such models are very often successfully used for forecasting. Employing several factors instead of a large number of explanatory variables may increase the number of degrees of freedom with the same information content. In the article we compare forecast accuracy of dynamic factor models with the forecast accuracy of three competitive models: univariate autoregressive model, VAR model and the model with leading indicator from the business survey. We have used 92 monthly time series from the Polish and world economy to conduct the out-of-sample real time forecasts of inflation (consumer price index). The results are encouraging. The dynamic factor model outperforms other models for both 1-step ahead and 3-step ahead forecast. The advantage of factor models is more straightforward for 1-month than for 3-month horizon.
Identifying Cardiac Syncope Based on Clinical History: A Literature-Based Model Tested in Four Independent Datasets

Background We aimed to develop and test a literature-based model for symptoms that associate with cardiac causes of syncope. Methods and Results Seven studies (the derivation sample) reporting ≥2 predictors of cardiac syncope were identified (4 Italian, 1 Swiss, 1 Canadian, and 1 from the United States). From these, 10 criteria were identified as diagnostic predictors. The conditional probability of each predictor was calculated by summation of the reported frequencies. A model of conditional probabilities and a priori probabilities of cardiac syncope was constructed. The model was tested in four datasets of patients with syncope (the test sample) from Calgary (n=670; 21% had cardiac syncope), Amsterdam (n=503; 9%), Milan (n=689; 5%) and Rochester (3877; 11%). In the derivation sample ten variables were significantly associated with cardiac syncope: age, gender, structural heart disease, low number of spells, brief or absent prodrome, supine syncope, effort syncope, and absence of nausea, diaphoresis and blurred vision. Fitting the test datasets to the full model gave C-statistics of 0.87 (Calgary), 0.84 (Amsterdam), 0.72 (Milan) and 0.71 (Rochester). Model sensitivity and specificity were 92% and 68% for Calgary, 86% and 67% for Amsterdam, 76% and 59% for Milan, and 73% and 52% for Rochester. A model with 5 variables (age, gender, structural heart disease, low number of spells, and lack of prodromal symptoms) was as accurate as the total set. Conclusion A simple literature-based Bayesian model of historical criteria can distinguish patients with cardiac syncope from other patients with syncope with moderate accuracy.
Enforcing structure on textual use cases via annotation models

Textual use cases are commonly used to represent software requirements at initial stages. However in most of the cases, these documents are unstructured. In this paper, we present a linguistic engine for processing textual use cases and extract a structured model in terms of an annotation model out of these use cases. An annotation model of a use case can further be used to generate various UML requirements models, Business Process Models and ontology. The implementation details of Natural Language Processing (NLP) technique employed by us for the linguistic engine is described in this paper in detail. Also, we consider a corpus containing 123 use cases from real-life industrial projects within our company, and translate them into annotation models using our NLP technique. For evaluating the performance of conversion we use a few metrics and report some promising results for our linguistic engine.
One tone, two ears, three dimensions: a robotic investigation of pinnae movements used by rhinolophid and hipposiderid bats.

Bats, which echolocate using broadband calls, are believed to employ the passive acoustic filtering properties of the head and pinnae to provide spectral cues which encode 3-D target angle. Microchiropteran species whose calls consist of a single, constant frequency harmonic (i.e., some species in the families Rhinolophidae and Hipposideridae) may create additional acoustic localization cues via vigorous pinna movements. In this work, two types of echolocation cues generated by moving a pair of receivers aboard a model sensor head are investigated. In the first case, it is supposed that a common 3-D echolocation principle employed by all bats is the creation of alternative viewing perspectives, and that constant frequency (CF) echolocators use pinna movement rather than morphology to alter the acoustic axes of their perceptual systems. Alternatively, it is possible rhinolophids and hipposiderids move their ears to create dynamic cues--in the form of frequency and amplitude modulations--which vary systematically with target elevation. Here the use of binaural and monaural timing cues derived from amplitude modulated echo envelopes are investigated. In this case, pinna mobility provides an echolocator with a mechanism for creating dramatic temporal cues for directional sensing which, unlike interaural timing differences, do not degrade with head size.
Favored gyral sites of supratentorial astrocytic tumors

It is well known that the predilective sites of extrinsic tumors (meningiomas, chordomas, etc) are at the skull base and along the calvarium. Although intrinsic tumors or glial tumors have also been seen to have anatomic and functional predilective sites within the central nervous system, these have not been well documented. We conducted this study to investigate if supratentorial astrocytic tumors have a predilection for specifi c gyri. We investigated the clinical and radiological records of 60 successive patients who had been operated on at our institution and had had histologically confi rmed supratentorial astrocytic tumors (36 males, 24 females, mean age: 52 years). Coronal sections were selected from the pre-operative contrast enhanced T1-weighted magnetic resonance imaging (MRI). The labeling of gyral areas for analysis of MRI was done using Yasargil’s method. Additional information obtained from 3-dimensional MRI and surgical fi ndings was taken into account when it was diffi cult to distinguish the specifi c gyrus in which the tumor was located. The middle portions of the frontal gyri, insular gyri and the supramarginal gyrus and its surroundings were among the most common locations for the development of tumors. Interestingly, with the exception of one case, none of the tumors was situated in the precentral or postcentral gyri. It seems that supratentorial astrocytic tumors have a predilection for specifi c gyri and disfavor some other gyri. This cannot be explained simply by the different sizes of the cerebral lobes. A classical lobar concept of cerebral anatomy may lead to a misunderstanding of cerebral pathophysiology.
INVASIVE SPECIES SPREAD MAPPING USING MULTI-RESOLUTION REMOTE SENSING DATA

The invasions of non-native species of vegetation pose significant threats to natural environments at all geographical scales. Saltcedar has been commonly treated as one of the several most threatening invasive species in U.S. in the next ten years. The spatial extent and density of infestation by saltcedar in the Rio Grande floodplain has been poorly understood in the past. Remote sensing provides a unique tool to map and monitor invasive species and provides a mean to detect major land cover changes and quantify the rate of change. To date, remote sensing has been mainly applied for mapping some canopy dominant invasive species. Accurate mapping of saltcedar distribution and abundance in a timely manner plays a central role to assist the undertaking of an effective control. Current studies have largely concentrated on the large-area detection with coarse resolution remote sensing data. Nevertheless, it is lacking of studies that systematically evaluate the respective potential of high spatial resolution satellite imagery, airborne hyperspectral imagery, as well as moderate resolution imagery for mapping saltcedar’s extents, distribution and monitoring its spread over time. Such cost and benefit analysis will be particularly invaluable to the regional or national scale study, in which selection of an appropriate image type to maximize the outcome plays an important part. In this study, a comprehensive test was designed and carried out to examine the ability to integrate multi-temporal and multi-resolution imagery: including very-high spatial resolution (QuickBird), hyperspectral resolution imagery (AISA), and moderate resolution satellite imagery (Landsat TM), in differentiating saltcedar from other riparian vegetation types in the Rio Grande river basin. Two types of analyses were fulfilled: first, five pixel-based classification methods were adopted for assessing effectiveness of QuickBird and AISA, respectively, i.e., the Maximum Likelihood Classifier (MLC), Neural Network Classifier (NNC), Support Vector Machine (SVM), Spectral Angle Mapper (SAM), and Maximum Matching Feature (MMF); Second, Landsat TM imagery was synthesized from AISA and tested for mapping abundance of saltcedar with four linear spectral unmixing methods and three back-propagation neural network methods. Results indicated that AISA outperformed QuickBird imagery in differentiating saltcedar from other riparian vegetation species. SVM achieves the highest classification accuracy among all the five classifiers. Linear spectral unmixing method exhibited similar mapping accuracy with neural network methods in estimating abundance of saltcedar at a spatial resolution of 30 by 30 square meters, but with significantly better computing efficiency. Overall, this study reflects the maximum capability of contemporary remote sensing in assisting reconnaissance of saltcedar, the most threatening invasive species in southwest United States.
Dynamic State Warping

The ubiquity of sequences in many domains enhances significant recent interest in sequence learning, for which a basic problem is how to measure the distance between sequences. Dynamic time warping (DTW) aligns two sequences by nonlinear local warping and returns a distance value. DTW shows superior ability in many applications, e.g. video, image, etc. However, in DTW, two points are paired essentially based on point-to-point Euclidean distance (ED) without considering the autocorrelation of sequences. Thus, points with different semantic meanings, e.g. peaks and valleys, may be matched providing their coordinate values are similar. As a result, DTW is sensitive to noise and poorly interpretable. This paper proposes an efficient and flexible sequence alignment algorithm, dynamic state warping (DSW). DSW converts each time point into a latent state, which endows point-wise autocorrelation information. Alignment is performed by using the state sequences. Thus DSW is able to yield alignment that is semantically more interpretable than that of DTW. Using one nearest neighbor classifier, DSW shows significant improvement on classification accuracy in comparison to ED (70/85 wins) and DTW (74/85 wins). We also empirically demonstrate that DSW is more robust and scales better to long sequences than ED and DTW.
Randomized Kinodynamic Planning

This paper presents the first randomized approach to kinodynamic planning (also known as trajectory planning or trajectory design). The task is to determine control inputs to drive a robot from an ini ial configuration and velocity to a goal configuration and velocity while obeying physically based dynamical models and avoiding obstacles in the robot’s environment. The authors consider generic systems that express the nonlinear dynamics of a robot in terms of the robot’s high-dimensional configuration space. Kinodynamic planning is treated as a motion-planning problem in a higher dimensional state space that has both first-order differential constraints and obstacle-based global constraints. The state space serves the same role as the configuration space for basic path planning; however, standard randomized path-planning techniques do not directly apply to planning trajectories in the state space. The authors have developed a randomized planning approach that is particularly tailored to trajectory planning problems in high-dimensional state spaces. The basis for this approach is the construction of rapidly exploring random trees, which offer benefits that are similar to those obtained by successful randomized holonomic planning methods but apply to a much broader class of problems. Theoretical analysis of the algorithm is given. Experimental results are presented for an implementation that computes trajectories for hovercrafts and satellites in cluttered environments, resulting in state spaces of up to 12 dimensions.
TDDB characteristics of thin polycrystalline and amorphous HfO2 films

We investigated time-zero dielectric breakdown (TZDB) and time-dependent dielectric breakdown (TDDB) characteristics of thin polycrystalline and amorphous HfO2 films. It was confirmed that the leakage current through polycrystalline HfO2 films was larger than that of amorphous films. However, the TDDB lifetime of polycrystalline films was longer than that of amorphous films. It was also found that polycrystalline HfO2 films are more uniform than amorphous in terms of the lifetime distribution.
Estimating multimedia instruction performance based on workload characterization and measurement

The increasing popularity in multimedia applications provokes microprocessors to include media-enhancement instructions. In this paper, we describe a methodology to estimate performance improvement of a new set of media instructions on emerging applications based on workload characterization and measurement. Application programs are characterized into a sequential segment, a vectorizable segment, and extra data moves for utilizing the SIMD capability of new media instructions. Techniques based on benchmarking and measurement on existing systems are used to estimate the execution time of each segment. Based on the measurement results, the speedup and the additional data moves of using the new media instructions can be estimated to help processor architects and designers evaluate different design tradeoffs.
N-Way Model Merging Project Report for CSC 2125 Special Topics in Software Engineering : Modeling – Methods , Tools and Techniques

We consider the problem of model merging. We focus on cases when several input models are merged into one, e.g., when combining a set of related products into a software product line representation. Most of the existing works on model merging focus on combining two input models, suggesting to merge n models by performing n-1 pairwise merges. In this paper, we show that combining n models simultaneously can produce a better result. We thus propose an n-way model merging framework and formally define its properties. We instantiate the framework using the Alloy Analyzer and provide two examples for demonstrating the differences between the pairwise and n-may merging. We conclude by discussing issues with the implementation of the framework the remaining steps.
Improved speed estimation in sensorless PM brushless AC drives

The paper reports on the application of flux observer based sensorless control techniques to PM brushless AC motors. Current methods of speed estimation and their relative merits are assessed, both theoretically and experimentally, and an improved speed estimation method, which combines the best features of the average of the estimated rotor position differential and the ratio of the EMF to excitation flux-linkage, is proposed. Its performance is verified experimentally.
On Measuring the Complexity of Code-Mixing

The paper discusses the practical applicability of a Code-Mixing Index as a measurement of the level of complexity and mixing in texts written in several different languages, and contrasts it to other ways of measuring the complexity of texts. In particular, we describe the application of the proposed Index to corpora of code-mixed Indian social media texts and compare their complexity to social media texts for other language pairs.
Women come of age : perspectives on the lives of older women

Part 1 The social and demographic situation: being an older woman in the late 20th century women and the life course old age is a women's issue. Part 2 Exploring the issues: poverty and older women age or disease? - health issues and the older woman relationships, friendships and sexuality a labour of love? - older women and caring community care - ideology versus reality living in institutions an English woman's home is. - education in retirement or retirement education all play and no work? - leisure and older women. Part 3 Meeting the challenges: strategies for policy strategies for provision and practice.
Is Transthyretin a Regulator of Ubc9 SUMOylation?

Ageing and mutations of transthyretin (TTR), the thyroid hormones and retinol transporting protein lead to amyloidosis by destabilizing the structure of TTR. Because protein structure is regulated through posttranslational modifications, we investigated the Small Ubiquitin-like Modifier (SUMO)ylation of TTR. We chose the widely used Ubc9 fusion-directed SUMOylation system, which is based on a fusion of the SUMOylation substrate of interest with Ubc9, a sole SUMO conjugating enzyme. Surprisingly, despite our presumptions, we found that Ubc9 fused to TTR was SUMOylated at a unique set of lysine residues. Three unknown SUMOylation sites of Ubc9—K154, K18 and K65—were revealed by mass spectrometry (MS). The previously reported SUMOylation at K49 of Ubc9 was also observed. SUMOylation of the lysine residues of TTR fused to Ubc9 was hardly detectable. However, non-fused TTR was SUMOylated via trans-SUMOylation by Ubc9 fused to TTR. Interestingly, mutating the catalytic residue of Ubc9 fused to TTR did not result in complete loss of the SUMOylation signal, suggesting that Ubc9 linked to TTR is directly cross-SUMOylated by the SUMO-activating enzyme E1. Ubc9, TTR or fusion proteins composed of TTR and Ubc9 specifically affected the global SUMOylation of cellular proteins. TTR or Ubc9 alone increased global SUMOylation, whereas concomitant presence of TTR and Ubc9 did not further increase the amount of high-molecular weight (HMW) SUMO conjugates. Our data suggest that TTR may influence the SUMOylation of Ubc9, thereby altering signalling pathways in the cell.
Fast loopy belief propagation for topological Sam

SLAM has been one of the main focuses of attention in robotics research. In the last years, some new graphical solutions for this problem have been proposed, which are concerned about jointly determining the environment map and the robot localization history, a more specific problem known as smoothing and mapping (SAM). When applied to topological maps, loopy belief propagation (LBP) provides an incremental and distributed solution to this problem, but eventually may incur time-consuming convergence. This work introduces the concept of starting points of belief propagation, a technique that can be used to reduce the convergence time of the LBP algorithm. We then propose an approach for determining starting points using information about the specific SAM graph structure in order to limit the number of iterations needed by LBP to provide an approximated global maximum a posteriori (MAP) estimate of the map and the robot trajectory. The experiments presented, performed with real-world data, confirm the adequacy of the proposed approach and encourage further investigation on it.