Miracle-dz/UniFAR-FTUs huggingface dataset:
Functional Connectivity Parcellation of the Human Thalamus by Independent Component Analysis

As a key structure to relay and integrate information, the thalamus supports multiple cognitive and affective functions through the connectivity between its subnuclei and cortical and subcortical regions. Although extant studies have largely described thalamic regional functions in anatomical terms, evidence accumulates to suggest a more complex picture of subareal activities and connectivities of the thalamus. In this study, we aimed to parcellate the thalamus and examine whole-brain connectivity of its functional clusters. With resting state functional magnetic resonance imaging data from 96 adults, we used independent component analysis (ICA) to parcellate the thalamus into 10 components. On the basis of the independence assumption, ICA helps to identify how subclusters overlap spatially. Whole brain functional connectivity of each subdivision was computed for independent component's time course (ICtc), which is a unique time series to represent an IC. For comparison, we computed seed-region-based functional connectivity using the averaged time course across all voxels within a thalamic subdivision. The results showed that, at p < 10-6, corrected, 49% of voxels on average overlapped among subdivisions. Compared with seed-region analysis, ICtc analysis revealed patterns of connectivity that were more distinguished between thalamic clusters. ICtc analysis demonstrated thalamic connectivity to the primary motor cortex, which has eluded the analysis as well as previous studies based on averaged time series, and clarified thalamic connectivity to the hippocampus, caudate nucleus, and precuneus. The new findings elucidate functional organization of the thalamus and suggest that ICA clustering in combination with ICtc rather than seed-region analysis better distinguishes whole-brain connectivities among functional clusters of a brain region.
Prevalence of Mycoplasma Pneumoniae Infection in Patients with COPD Exacerbation; a Letter to the Editor

Dear editor; Currently, control and prevention of respiratory illnesses is considered a health priority in most developed countries and managing the risk factors is necessary for improving the population’s health. Chronic obstructive pulmonary disease (COPD) is the 5 th cause of death around the world and estimations have indicated that due to an increase in environmental pollution, this disease will become the 3 rd cause of death in the future. In previous studies, pulmonary infection with mycoplasma pneumoniae has been introduced as one of the causes for COPD exacerbation. Mycoplasma pneumoniae affects the upper and lower respiratory tract and its clinical manifestation is trachea-bronchitis accompanied by restlessness and dry coughs. The pathogenesis spectrum of this bacterium ranges from mild pharyngitis and trachea-bronchitis to acute pneumonia. Epidemiologic studies have shown that this bacterium is responsible for more than 20% of community acquired pneumonias. In a cross-sectional study by the authors of the present letter, 66 patients over the age of 18 years who had presented to the emergency department of Imam Reza Hospital, Mashhad, Iran, with diagnosis of COPD exacerbation were evaluated. Sputum sample of the patients was obtained and sent to the laboratory for performing polymerase chain reaction (PCR). Mean age of the patients participating in this study was 67.28 ± 13.68 years (60.6% male). The result of PCR was positive in 6 patients out of the total of 66 patients (9.1%). The results of the present study showed that there was no correlation between age (p=0.18), sex (p=0.25), duration of being affected with COPD (p=0.20), consumption of antibiotics (p=0.35), smoking (p=0.62), opioid abuse (p=0.44), corticosteroid use (p=0.57), underlying illness (p=0.94) and health care—associated pneumonia (HCAP) (p=0.46) with mycoplasma infection. However, prevalence of leukocytosis (p=0.01) and myalgia (p=0.02) was significantly higher in the mycoplasma group. Numerous studies have confirmed the presence of mycoplasma pneumoniae in exacerbation of COPD using serologic diagnosis. For instance, in a study by Lieberman et al. prevalence of mycoplasma pneumoniae in patients with COPD exacerbation was reported as 14.2% and in Meloni et al. study the prevalence of this infection was expressed to be 6.7%. These rates were reported between 5% and 14% in other studies. Thus, it seems that prevalence of mycoplasma is high in COPD exacerbation, but there is still no answer to the question if this infection results in exacerbation of COPD or not and there is controversy between the studies in this regard. Therefore, it is suggested to design case-control or cohort studies to find the answer to this question.
Type V secretion: mechanism(s) of autotransport through the bacterial outer membrane

Autotransport in Gram-negative bacteria denotes the ability of surface-localized proteins to cross the outer membrane (OM) autonomously. Autotransporters perform this task with the help of a β-barrel transmembrane domain localized in the OM. Different classes of autotransporters have been investigated in detail in recent years; classical monomeric but also trimeric autotransporters comprise many important bacterial virulence factors. So do the two-partner secretion systems, which are a special case as the transported protein resides on a different polypeptide chain than the transporter. Despite the great interest in these proteins, the exact mechanism of the transport process remains elusive. Moreover, different periplasmic and OM factors have been identified that play a role in the translocation, making the term ‘autotransport’ debatable. In this review, we compile the wealth of details known on the mechanism of single autotransporters from different classes and organisms, and put them into a bigger perspective. We also discuss recently discovered or rediscovered classes of autotransporters.
On the Value of Ensemble Effort Estimation

Background: Despite decades of research, there is no consensus on which software effort estimation methods produce the most accurate models. Aim: Prior work has reported that, given M estimation methods, no single method consistently outperforms all others. Perhaps rather than recommending one estimation method as best, it is wiser to generate estimates from ensembles of multiple estimation methods. Method: Nine learners were combined with 10 preprocessing options to generate 9 × 10 = 90 solo methods. These were applied to 20 datasets and evaluated using seven error measures. This identified the best n (in our case n = 13) solo methods that showed stable performance across multiple datasets and error measures. The top 2, 4, 8, and 13 solo methods were then combined to generate 12 multimethods, which were then compared to the solo methods. Results: 1) The top 10 (out of 12) multimethods significantly outperformed all 90 solo methods. 2) The error rates of the multimethods were significantly less than the solo methods. 3) The ranking of the best multimethod was remarkably stable. Conclusion: While there is no best single effort estimation method, there exist best combinations of such effort estimation methods.
ASR error segment localization for spoken recovery strategy

Even though small ASR errors might not impact downstream processes that make use of the transcript, larger error segments like those generated by OOVs can have a considerable impact on applications such as speech-to-speech translation and can eventually lead to communication failure between users of the system. This work focuses on error detection in ASR output targeted towards significant error segments that can be recovered using a dialog system. We propose a CRF system trained to recognize error segments with ASR confidence-based, lexical and syntactic features. The most significant error segment is passed to a dialog system for interactive recovery in which rephrased words are reinserted in the original. 22% of utterances can be fully recovered and an interesting by-product is that rewriting error segments as a single token reduces WER by 17% on an adverse corpus.
Disruption of Maternal Parenting Circuitry by Addictive Process: Rewiring of Reward and Stress Systems

Addiction represents a complex interaction between the reward and stress neural circuits, with increasing drug use reflecting a shift from positive reinforcement to negative reinforcement mechanisms in sustaining drug dependence. Preclinical studies have indicated the involvement of regions within the extended amygdala as subserving this transition, especially under stressful conditions. In the addictive situation, the reward system serves to maintain habitual behaviors that are associated with the relief of negative affect, at the cost of attenuating the salience of other rewards. Therefore, addiction reflects the dysregulation between core reward systems, including the prefrontal cortex (PFC), ventral tegmental area (VTA), and nucleus accumbens (NAc), as well as the hypothalamic–pituitary–adrenal axis and extended amygdala of the stress system. Here, we consider the consequences of changes in neural function during or following addiction on parenting, an inherently rewarding process that may be disrupted by addiction. Specifically, we outline the preclinical and human studies that support the dysregulation of reward and stress systems by addiction and the contribution of these systems to parenting. Increasing evidence suggests an important role for the hypothalamus, PFC, VTA, and NAc in parenting, with these same regions being those dysregulated in addiction. Moreover, in addicted adults, we propose that parenting cues trigger stress reactivity rather than reward salience, and this may heighten negative affect states, eliciting both addictive behaviors and the potential for child neglect and abuse.
Is spreadsheet ambiguity harmful? detecting and repairing spreadsheet smells due to ambiguous computation

Spreadsheets are widely used by end users for numerical computation in their business. Spreadsheet cells whose computation is subject to the same semantics are often clustered in a row or column. When a spreadsheet evolves, these cell clusters can degenerate due to ad hoc modifications or undisciplined copy-and-pastes. Such degenerated clusters no longer keep cells prescribing the same computational semantics, and are said to exhibit ambiguous computation smells. Our empirical study finds that such smells are common and likely harmful. We propose AmCheck, a novel technique that automatically detects and repairs ambiguous computation smells by recovering their intended computational semantics. A case study using AmCheck suggests that it is useful for discovering and repairing real spreadsheet problems.
Gaussian predictive process models for large spatial data sets

Summary. With scientific data available at geocoded locations, investigators are increasingly turning to spatial process models for carrying out statistical inference. Over the last decade, hierarchical models implemented through Markov chain Monte Carlo methods have become especially popular for spatial modelling, given their flexibility and power to fit models that would be infeasible with classical methods as well as their avoidance of possibly inappropriate asymptotics. However, fitting hierarchical spatial models often involves expensive matrix decompositions whose computational complexity increases in cubic order with the number of spatial locations, rendering such models infeasible for large spatial data sets. This computational burden is exacerbated in multivariate settings with several spatially dependent response variables. It is also aggravated when data are collected at frequent time points and spatiotemporal process models are used. With regard to this challenge, our contribution is to work with what we call predictive process models for spatial and spatiotemporal data. Every spatial (or spatiotemporal) process induces a predictive process model (in fact, arbitrarily many of them). The latter models project process realizations of the former to a lower dimensional subspace, thereby reducing the computational burden. Hence, we achieve the flexibility to accommodate non‐stationary, non‐Gaussian, possibly multivariate, possibly spatiotemporal processes in the context of large data sets. We discuss attractive theoretical properties of these predictive processes. We also provide a computational template encompassing these diverse settings. Finally, we illustrate the approach with simulated and real data sets.
A hierarchical decomposition method for object-oriented systems based on identifying omnipresent clusters

System decomposition has become a research focus in software maintenance and evolution for a long time. In this paper, we propose a hierarchical decomposition method for object oriented systems based on identification of omnipresent clusters. The distinctive features of this approach are as follow: firstly, we addressed the problem of omnipresent classes for class diagram. Secondly, we proposed a hierarchical decomposition strategy which can deal with unbalanced hierarchical organization for software system. Thirdly, we presented a revised independency metric that can offset the impact of the measured clusters' size. The experimental results show that this method can be both effective and efficient.
Alcohol consumption and breast cancer recurrence and survival among women with early-stage breast cancer: the life after cancer epidemiology study.

PURPOSE To examine the association of alcohol consumption after breast cancer diagnosis with recurrence and mortality among early-stage breast cancer survivors. PATIENTS AND METHODS Patients included 1,897 LACE study participants diagnosed with early-stage breast cancer between 1997 and 2000 and recruited on average 2 years postdiagnosis, primarily from the Kaiser Permanente Northern California Cancer Registry. Alcohol consumption (ie, wine, beer, and liquor) was assessed at cohort entry using a food frequency questionnaire. Cox proportional hazards models were used to estimate hazard ratios (HR) and 95% CI with adjustment for known prognostic factors. RESULTS Two hundred ninety-three breast cancer recurrences and 273 overall deaths were ascertained after an average follow-up of 7.4 years. Nine hundred fifty-eight women (51%) were considered drinkers (> 0.5 g/d of alcohol), and the majority drank wine (89%). Drinking ≥ 6 g/d of alcohol compared with no drinking was associated with an increased risk of breast cancer recurrence (HR, 1.35; 95% CI, 1.00 to 1.83) and death due to breast cancer (HR, 1.51; 95% CI, 1.00 to 2.29). The increased risk of recurrence appeared to be greater among postmenopausal (HR, 1.51; 95% CI, 1.05 to 2.19) and overweight and obese women (HR, 1.60; 95% CI, 1.08 to 2.38). Alcohol intake was not associated with all-cause death and possibly associated with decreased risk of non-breast cancer death. CONCLUSION Consuming three to four alcoholic drinks or more per week after a breast cancer diagnosis may increase risk of breast cancer recurrence, particularly among postmenopausal and overweight/obese women, yet the cardioprotective effects of alcohol on non-breast cancer death were suggested.
An extraction-based verification methodology for MEMS

Micromachining techniques are being increasingly used to develop miniaturized sensor and actuator systems. These system designs tend to be captured as layout, requiring extraction of the equivalent microelectromechanical circuit as a necessary step for design verification. This paper presents an extraction methodology to (re-)construct a circuit schematic representation from the layout, enabling the designer to use microelectromechanical circuit simulators to verify the functional behavior of the layout. This methodology uses a canonical representation of the given layout on which feature-based and graph-based recognition algorithms are applied to generate the equivalent extracted schematic. Extraction can be performed to either the atomic level or the functional level representation of the reconstructed circuit. The choice of level in hierarchy is governed by the trade off between simulation time and simulation accuracy of the extracted circuit. The combination of the MEMS layout extraction and lumped-parameter circuit simulation provides MEMS designers with VLSI-like tools enabling faster design cycles, and improved design productivity.
Recognizing Characters in Scene Images

An effective algorithm for character recognition in scene images is studied. Scene images are segmented into regions by an image segmentation method based on adaptive thresholding. Character candidate regions are detected by observing gray-level differences between adjacent regions. To ensure extraction of multisegment characters as well as single-segment characters, character pattern candidates are obtained by associating the detected regions according to their positions and gray levels. A character recognition process selects patterns with high similarities by calculating the similarities between character pattern candidates and the standard patterns in a dictionary and then comparing the similarities to the thresholds. A relaxational approach to determine character patterns updates the similarities by evaluating the interactions between categories of patterns, and finally character patterns and their recognition results are obtained. Highly promising experimental results have been obtained using the method on 100 images involving characters of different sizes and formats under uncontrolled lighting. >
Petri net models of fuzzy neural networks

Artificial neural networks (ANN's) are highly parallel and distributed computational structures that can learn from experience and perform inferences. Petri nets, on the other hand, provide an effective modeling framework for distributed systems. The basic concepts of Petri net are utilized to develop ANN-like multilayered Petri net architectures of distributed intelligence having learning ability. A Petri net model of single neuron is presented. A two-layer Petri net model-neural Petri net (NPN)-that uses this neuron model as a building block is described. A new class of Petri nets called the fuzzy neural Petri net (FNPN) is defined. The FNPN can be used for representing a fuzzy knowledge base and for fuzzy reasoning. Some application examples for the two Petri net based models are given. >
Late Triassic (Norian) mollusks from the Taylor Mountains Quadrangle, southwestern Alaska

We describe a diverse molluscan fauna of silicified fossils from two localities in the Taylor Mountains D-3 quadrangle of southwestern Alaska. The molluscan fauna consists of at least 8 species of bivalves, including 1 new species, Cassianella cordillerana McRoberts n.sp. , and at least 11 species of gastropods, including 2 new species, Neritaria nuetzeli Blodgett n.sp. and Andangularia wilsoni Blodgett n.sp. Bivalve and gastropod affinities suggest an early Norian age, with taxonomic similarities to several southern Alaskan tectonostratigraphic terranes (for example, Alexander and Chulitna), as well as to the South American Cordillera of Peru. The mollusks are associated with numerous brachiopods that also support a Norian age and similar biogeographic affinities.
Structure of a Thiol Monolayer-Protected Gold Nanoparticle at 1.1 Å Resolution

Structural information on nanometer-sized gold particles has been limited, due in part to the problem of preparing homogeneous material. Here we report the crystallization and x-ray structure determination of a p-mercaptobenzoic acid (p-MBA)–protected gold nanoparticle, which comprises 102 gold atoms and 44 p-MBAs. The central gold atoms are packed in a Marks decahedron, surrounded by additional layers of gold atoms in unanticipated geometries. The p-MBAs interact not only with the gold but also with one another, forming a rigid surface layer. The particles are chiral, with the two enantiomers alternating in the crystal lattice. The discrete nature of the particle may be explained by the closing of a 58-electron shell.
Control Functionals for Quasi-Monte Carlo Integration

Quasi-Monte Carlo (QMC) methods are being adopted in statistical applications due to the increasingly challenging nature of numerical integrals that are now routinely encountered. For integrands with $d$-dimensions and derivatives of order $\alpha$, an optimal QMC rule converges at a best-possible rate $O(N^{-\alpha/d})$. However, in applications the value of $\alpha$ can be unknown and/or a rate-optimal QMC rule can be unavailable. Standard practice is to employ $\alpha_L$-optimal QMC where the lower bound $\alpha_L \leq \alpha$ is known, but in general this does not exploit the full power of QMC. One solution is to trade-off numerical integration with functional approximation. This strategy is explored herein and shown to be well-suited to modern statistical computation. A challenging application to robotic arm data demonstrates a substantial variance reduction in predictions for mechanical torques.
Study of SESAR implied safety validation needs

Safety validation of changes to an individual organization’s local ATM system has become common p ractice in Europe. However, the SESAR program is planning chan ges in air traffic operations in Europe that go much further than changes to a local ATM system. This paper identifies the is sues on which safety validation approaches need extensions, in or der to move from safety validation of changes to a local ATM sy stem to safety validation in SESAR. Subsequently, it identifies aproaches that address the identified extension needs. This way an i tegrated view is developed from the fragmented research resu lts in this area. Keywords-Safety validation, ATM, SESAR.
Validity of the Spanish 8-item Short-form Generic Health-related Quality-of-Life Questionnaire in Surgical Patients: A Population-based Study

Background:Health-related quality of life is usually reported for specific rather than heterogeneous populations such as those treated in routine anesthesia practice. The 8-item short-form generic health-related quality-of-life questionnaire (SF-8) is a candidate instrument for this setting. The authors evaluated the feasibility, reliability, validity, and responsiveness to change of the Spanish version of SF-8 in a population-based surgical cohort. Methods:Recruiting patients from a large population-based study of risk factors for pulmonary complications, before surgery, the authors administered the 1-week recall SF-8 to 2,991 patients undergoing nonobstetric elective or emergency surgery in 59 hospitals, each of which collected data on seven randomly assigned days in 2006. The SF-8 was administered again 3 months later. Reliability was evaluated using the Cronbach &agr; coefficient and validity by comparing physical and mental component summary SF-8 scores with clinical variables. Responsiveness after surgery was evaluated using the standardized response mean. Results:Cronbach &agr; for the overall test was 0.92. Physical and mental component summary scores and all individual scores were lower (worse quality of life) in women (P < 0. 01) and decreased with age (P < 0.01). Preoperative scores were lower for those in worse clinical condition (higher body mass index, American Society of Anesthesiologists physical status class, or surgical risk scores), with preoperative respiratory symptoms, and in emergency situations (P < 0.01). The standardized response mean ranged from 0.1 to 0.5. Conclusions:The SF-8 is a feasible, reliable, valid, and responsive instrument for assessing health-related quality of life in a broad-spectrum surgical population.