Miracle-dz/UniFAR-FTUs huggingface dataset:
Clinical Factors Asssociated with Treatment Outcomes following Whole-brain Irradiation in Patients with Prostate Cancer.

BACKGROUND/AIM Patients with prostate cancer represent a small minority of cancer patients presenting with metastases to the brain. This study investigated the role of whole-brain irradiation (WBI) in this rare group. PATIENTS AND METHODS Eighteen such patients were included. Clinical factors including fractionation program of WBI, age at WBI, Karnofsky performance score (KPS), number of metastases to the brain, involvement of extracerebral metastatic sites, time from prostate cancer diagnosis to WBI and recursive-partitioning-analysis (RPA) class were investigated regarding local (intracerebral) control and survival. RESULTS On multivariate evaluation, longer time from prostate cancer diagnosis to WBI showed a trend towards improved local control (hazard ratio 2.77, p=0.098). Better KPS (hazard ratio 5.64, p=0.021) and longer time from prostate cancer diagnosis to WBI (hazard ratio 5.64, p=0.013) were significantly associated with better survival. CONCLUSION Two independent predictors of survival were identified and should be considered when designing for personalized treatment regimens and clinical trials.
Predicting Lightning Strikes for the Enhancement of Fire Weather Forecasts

Lightning is a safety risk to anyone working outdoors and is the source of ignition for nearly 60% of all wildfires each year in the Black Hills of South Dakota and Wyoming (Andrews and Bradshaw, 1997). The prediction of lightning has previously been an elusive aspect of a fire weather forecast. Improvements in forecasting the daily probability of lightning in fire weather forecasts could potentially greatly improve general planning operations of fire management officials.
S-R compatibility: spatial characteristics of stimulus and response codes.

The present paper reports the results of two experiments designed to demonstrate the utility of the concept of stimulus-response compatibility in the development of a theory of perceptual-motor behavior. A task involves compatible S-R relations to the extent that the ensemble of stimulus and response combinations comprising the task results in a high rate of information transfer. Admittedly, degree of compatibility can be defined in terms of operations other than those used to secure a measure of information, for example, it could be specified in terms of measures of speed or accuracy. However, the present writers prefer the preceding definition because of the theoretican interpretation that they wish to give to compatibility effects. This interpretation makes use of the idea of a hypothetical process of information transformation or recoding in the course of a perceptual-motor activity, and assumes that the degree of compatibility is at a maximum when recoding processes are at a minimum. The concept of compatibility can be
Integration of multiple methods for robust object recognition

Service robots need to be able to recognize and identify objects located within complex backgrounds. Since no single method may work in every situation, several methods need to be combined so that robots can select the appropriate one automatically. In this paper we propose a scheme to classify situations depending on the characteristics of the object of interest and user demand. We classify situations into four categories and employ different techniques for each. We use SIFT, kernel PC A (KPCA) in conjunction with support vector machine (SVM) using intensity, color, and Gabor features for four categories. We show that the use of appropriate features is important for the use of KPCA and SVM based techniques on different kinds of objects. Through experiments we show that by using our categorization scheme a service robot can select an appropriate feature and method, and considerably improve its recognition performance. Yet, recognition is not perfect. Thus, we propose to combine the autonomous method with an interactive method that allows the robot to recognize the user request for a specific object and class when the robot fails to recognize the object.
Parallel asynchronous lock-free algorithms for nonconvex big-data optimization

We propose a novel parallel asynchronous lock-free algorithmic framework for the minimization of the sum of a smooth nonconvex function and a convex nonsmooth regularizer. This class of problems arises in many big-data applications, including deep learning, matrix completions, and tensor factorization. Key features of the proposed algorithm are: i) it deals with nonconvex objective functions; ii) it is parallel and asynchronous; and iii) it is lock-free, meaning that components of the vector variables may be written by some cores while being simultaneously read by others. Almost sure convergence to stationary solutions is proved. The method enjoys properties that improve to a great extent over current ones and numerical results show that it outperforms existing asynchronous algorithms on both convex and nonconvex problems.
Structure, paleogeographic inheritance, and deformation history of the southern Atlas foreland fold and thrust belt of Tunisia

Structural analysis of the southern Tunisian Atlas was carried out using field observation, seismic interpretation, and cross section balancing. It shows a mix of thick‐skinned and thin‐skinned tectonics with lateral variations in regional structural geometry and amounts of shortening controlled by NW‐SE oblique ramps and tear faults. It confirms the role of the Late Triassic–Early Jurassic rifting inheritance in the structuring of the active foreland fold and thrust belt of the southern Tunisian Atlas, in particular in the development of NW‐SE oblique structures such as the Gafsa fault. The Late Triassic–Early Jurassic structural pattern is characterized by a family of first‐order NW‐SE trending normal faults dipping to the east and by second‐order E‐W trending normal faults limiting a complex system of grabens and horsts. These faults have been inverted during two contractional tectonic events. The first event occurred between the middle Turonian and the late Maastrichtian and can be correlated with the onset of the convergence between Africa and Eurasia. The second event corresponding to the principal shortening tectonic event in the southern Atlas started in the Serravalian‐Tortonian and is still active. During the Neogene, the southern Atlas foreland fold and thrust belt propagated on the evaporitic décollement level infilling the Late Triassic–Early Jurassic rift. The major Eocene “Atlas event,” described in hinterland domains and in eastern Tunisia, did not deform significantly the southern Tunisian Atlas, which corresponded in this period to a backbulge broad depozone.
Which problems have strongly exponential complexity?

For several NP-complete problems, there have been a progression of better but still exponential algorithms. In this paper we address the relative likelihood of sub-exponential algorithms for these problems. We introduce a generalized reduction which we call sub-exponential reduction family (SERF) that preserves sub-exponential complexity. We show that Circuit-SAT is SERF-complete for all NP-search problems, and that for any fixed k, k-SAT, k-Colorability, k-Set Cover Independent Set, Clique, Vertex Cover are SERF-complete for the class SNP of search problems expressible by second order existential formulas whose first order part is universal. In particular, sub-exponential complexity for any one of the above problems implies the same for all others. We also look at the issue of proving strongly exponential lower bounds (that is, bounds of the form 2/sup /spl Omega/(n)/) for AC/sup 0/. This problem is even open far depth-3 circuits. In fact, such a bound for depth-3 circuits with even limited (at most n/sup /spl epsiv//) fan-infer bottom-level gates would imply a nonlinear size lower bound for logarithmic depth circuits. We show that with high probability even degree 2 random GF(2) polynomials require strongly exponential site for /spl Sigma//sub 3//sup k/ circuits for k=o(loglogn). We thus exhibit a much smaller space of 2(0(/sup n2/)) functions such that almost every function in this class requires strongly exponential size /spl Sigma//sub 3//sup k/ circuits. As a corollary, we derive a pseudorandom generator (requiring O(n/sup 2/) bits of advice) that maps n bits into a larger number of bits so that computing parity on the range is hard for /spl Sigma//sub 3//sup k/ circuits. Our main technical lemma is an algorithm that, for any fixed /spl epsiv/>0, represents an arbitrary k-CNF formula as a disjunction of 2/sup /spl epsiv/n/ k-CNF formulas that are sparse, e.g., each having O(n) clauses.
MUSCLE FIBER TYPES AND FIBER MORPHOMETRY IN THE SOLEUS MUSCLE OF THE RAT

Muscle fiber type composition, distribution and size of fibers were investigated in the soleus muscle of young adult male and female rats, using histochemical and morphometric methods, to determine whether these parameters vary according to the sex of animals. Combined myofibrillar ATPase (mATPase) and metabolic enzyme histochemistry were performed on serial cross-sections from the belly region of muscle. Three fiber types (I, IIA, and IIC) were identified on the basis of mATPase activity after preincubation at pH values of 9.4, 4.5 and 4.3. The type IIC fibers, present in a small number (about 4%), were included within the type IIA fiber class for purposes of quantitative analysis. The fiber type composition of the slow soleus muscle showed type I dominance (78%). There has been observed a variation in the regional distribution of muscle fiber types. A relative number of type IIA fibers increased towards the lateral part of the muscle, and so did type IIC, but the general organization was not as regular as those previously found in the fast tibialis anterior and tibialis posterior muscles. The size of predominating fibers of type I was larger than of IIA type fibers in the soleus muscles from the both groups. No significant difference was detected between male and female rats in respect to the morphometric parameters examined.
Disentangling scene content from its spatial boundary: Complementary roles for the PPA and LOC in representing real-world scenes

Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Behavioral and computational studies suggest that visual scene analysis rapidly produces a rich description of both the objects and the spatial layout of surfaces in a scene. However, there is still a large gap in our understanding of how the human brain accomplishes these diverse functions of scene understanding. Here we probe the nature of real-world scene representations using multivoxel functional magnetic resonance imaging pattern analysis. We show that natural scenes are analyzed in a distributed and complementary manner by the parahippocampal place area (PPA) and the lateral occipital complex (LOC) in particular, as well as other regions in the ventral stream. Specifically, we study the classification performance of different scene-selective regions using images that vary in spatial boundary and naturalness content. We discover that, whereas both the PPA and LOC can accurately classify scenes, they make different errors: the PPA more often confuses scenes that have the same spatial boundaries, whereas the LOC more often confuses scenes that have the same content. By demonstrating that visual scene analysis recruits distinct and complementary high-level representations, our results testify to distinct neural pathways for representing the spatial boundaries and content of a visual scene.
Correlation of Body Composition, Grip Strength, and Core Stability with Balance in Older Adults

Purpose: Balance is important to everyday functioning in older adults. The purpose of this study is to determine the correlation between body composition, grip strength, and core stability with balance. Methods: 30 subjects, (17 males, 13 females) age 55 to 75 years, were assessed for fall risk via Biodex Balance System, body composition, grip strength, and core stability. Results: The strongest correlation to balance was observed in the waist-to-hip ratio (r=.78, n=29, p<.001); this was stronger in females than in males. Overall core stability was also associated with better balance (r=-.43, n=28, p= .023). For body fat percent there was a weak association to balance for females but virtually no association for males. Similarly grip strength had no clear association with balance. Conclusion: The correlations in this population suggest better balance is associated with lower waist-to-hip ratio and higher core strength, but is not associated with higher grip strength and lower body fat. Core stability and decreasing waist-to-hip ration should be focal points when working towards decreasing fall risk in older adults.
The fragility of standard inferential approaches in principal stratification models relative to direct likelihood approaches

Many empirical settings involve the specification of models leading to complicated likelihood functions, for example, finite mixture models that arise in causal inference when using Principal Stratification (PS). Traditional asymptotic results cannot be trusted for the associated likelihood functions, whose logarithms are not close to being quadratic and may be multimodal even with large sample sizes. We first investigate the shape of the likelihood function with models based on PS by providing diagnostic tools for evaluating ellipsoidal approximations based on the second derivatives of the log‐likelihood at a mode. In these settings, inference based on standard approximations is inappropriate, and other forms of inference are required. We explore the use of a direct likelihood approach for parsimonious model selection and, specifically, propose comparing values of scaled maximized likelihood functions under competitive models to select preferred models. An extensive simulation study provides guidelines, for calibrating the use of scaled log‐likelihood ratio statistics, as functions of the complexity of the models being compared.
AVERAGE-CASE ANALYSIS OF TWO REVOCATION SCHEMES FOR STATELESS RECEIVERS

We consider the mean and variance of the number of encryptions necessary over all subsets of privileged users to revoke a set of users in the complete subtree scheme (CST) and the subset-difference scheme (SD). These are well-known tree based broadcast encryption schemes. Park and Blake in: Journal of Discrete Algorithms, vol. 4, 2006, pp. 215–238 [4], give the mean number of encryptions for these schemes. We continue their analysis and show that the standard deviations are small compared to the means as the number of users gets large. Therefore, the mean number is a good estimate of the number of necessary encryptions used by these schemes.
Enhancing learning accessibility through fully automatic captioning

The simple act of listening or of taking notes while attending a lesson may represent an insuperable burden for millions of people with some form of disabilities (e.g., hearing impaired, dyslexic and ESL students). In this paper, we propose an architecture that aims at automatically creating captions for video lessons by exploiting advances in speech recognition technologies. Our approach couples the usage of off-the-shelf ASR (Automatic Speech Recognition) software with a novel caption alignment mechanism that smartly introduces unique audio markups into the audio stream before giving it to the ASR and transforms the plain transcript produced by the ASR into a timecoded transcript.
Fine particle retention within stream storage areas at base flow and in response to a storm event

Fine particles (1–100 µm), including particulate organic carbon (POC) and fine sediment, influence stream ecological functioning because they may contain or have a high affinity to sorb nitrogen and phosphorus. These particles are immobilized within stream storage areas, especially hyporheic sediments and benthic biofilms. However, fine particles are also known to remobilize under all flow conditions. This combination of downstream transport and transient retention, influenced by stream geomorphology, controls the distribution of residence times over which fine particles influence stream ecosystems. The main objective of this study was to quantify immobilization and remobilization rates of fine particles in a third‐order sand‐and‐gravel bed stream (Difficult Run, Virginia, USA) within different geomorphic units of the stream (i.e., pool, lateral cavity, and thalweg). During our field injection experiment, a thunderstorm‐driven spate allowed us to observe fine particle dynamics during both base flow and in response to increased flow. Solute and fine particles were measured within stream surface waters, pore waters, sediment cores, and biofilms on cobbles. Measurements were taken at four different subsurface locations with varying geomorphology and at multiple depths. Approximately 68% of injected fine particles were retained during base flow until the onset of the spate. Retention was evident even after the spate, with 15.4% of the fine particles deposited during base flow still retained within benthic biofilms on cobbles and 14.9% within hyporheic sediment after the spate. Thus, through the combination of short‐term remobilization and long‐term retention, fine particles can serve as sources of carbon and nutrients to downstream ecosystems over a range of time scales.
Development and evaluation of models to predict death and myocardial infarction following coronary angioplasty and stenting

Prior estimates of the risk death and myocardial infarction following percutaneous coronary intervention (PCI) may not be uniformly applicable due to recent significant changes in clinical practice. Accordingly, we studied 2,804 cases from January 1997 through February 1999, in order to develop risk models to predict death, and post-procedural myocardial infarction following PCI. Risk models were constructed using multivariate logistic regression, artificial neural networks and prognostic risk scoring systems. Composite logistic regression models and artificial neural networks performed similarly in predicting the risk of major acute complications (c-index for predicting death of 0.812 and 0.807, respectively). Risk scoring models, based on the composite logistic regression beta coefficients, performed only slightly worse (c-index death = 0.794). Risk score models appear to provide reasonable discrimination while offering the potential for simple clinical implementation in the estimation of the risk of death and myocardial infarction in interventional cardiology.
Zoning reconfiguration for coordinated voltage regulation in future transmission grids

Hierarchically structured Automatic Voltage Control (AVC) architecture enables wide-area closed-loop Coordinated Voltage Regulation (CVR). Owing to the inherent complexity of the task, CVR relies on reduced control models, i.e. simplified models of the system suitable for voltage control. It is a fact however that a single reduced control model (static RCM) cannot be optimal for all network configurations and operating conditions. In pursuit of advanced online voltage control for a future smart transmission grid, this paper presents adaptive control model reduction (adaptive RCM) for CVR. The proposed formulation is based on a complex network representation of the transmission grid. Additionally, the formulation employs spectral clustering complemented by perturbation theory to deliver the adaptive RCM. Indicative results are presented on the New England 39-bus network and provide adequate justification of the proposed approach. The implications of an adaptive RCM scheme to control algorithm design and selection are also discussed.
Integrating State Machine Analysis with System-Theoretic Process Analysis

Safety becomes a critical aspect for software-intensive systems in different applications areas. Many hazard analysis techniques are proposed and used to investigate system design models to elicit hazards and design flaws. STPA (SystemTheoretic Process Analysis) is a modern hazard analysis technique, which is based on a new systems-theoretic model of accidents for large and complex systems. With STPA, the system is viewed as interacting control loops and the accidents are considered as results from inadequate enforcement of safety constraints in design, development and operation. STPA still needs appropriate diagrammatic notations to represent the relation between the process model variables, control actions and hazards. For this purpose, we propose to integrate state machine analysis with STPA to provide a suitable notation of arguments between the states of controllers, control actions and hazards.
Improving the use of environmental diversity as a surrogate for species representation

Abstract The continuous p‐median approach to environmental diversity (ED) is a reliable way to identify sites that efficiently represent species. A recently developed maximum dispersion (maxdisp) approach to ED is computationally simpler, does not require the user to reduce environmental space to two dimensions, and performed better than continuous p‐median for datasets of South African animals. We tested whether maxdisp performs as well as continuous p‐median for 12 datasets that included plants and other continents, and whether particular types of environmental variables produced consistently better models of ED. We selected 12 species inventories and atlases to span a broad range of taxa (plants, birds, mammals, reptiles, and amphibians), spatial extents, and resolutions. For each dataset, we used continuous p‐median ED and maxdisp ED in combination with five sets of environmental variables (five combinations of temperature, precipitation, insolation, NDVI, and topographic variables) to select environmentally diverse sites. We used the species accumulation index (SAI) to evaluate the efficiency of ED in representing species for each approach and set of environmental variables. Maxdisp ED represented species better than continuous p‐median ED in five of 12 biodiversity datasets, and about the same for the other seven biodiversity datasets. Efficiency of ED also varied with type of variables used to define environmental space, but no particular combination of variables consistently performed best. We conclude that maxdisp ED performs at least as well as continuous p‐median ED, and has the advantage of faster and simpler computation. Surprisingly, using all 38 environmental variables was not consistently better than using subsets of variables, nor did any subset emerge as consistently best or worst; further work is needed to identify the best variables to define environmental space. Results can help ecologists and conservationists select sites for species representation and assist in conservation planning.
Continuous estimation of gross primary productivity and evapotranspiration from an Unmanned Aerial System

Satellite-based optical imagery cannot provide information on the land surface during cloudy periods. This issue is especially relevant for high latitudes where overcast days are common. Current remote sensing-based models of gross primary productivity (GPP) or evapotranspiration (ET) are biased towards clear sky conditions, lacking important information on biophysical processes under cloudy conditions (Wang et al., 2018). Introduction