Miracle-dz/UniFAR-FTUs huggingface dataset:
Metabolic resting-state brain networks in health and disease

Significance We present an innovative approach to evaluate default mode network (DMN) activity in individual subjects using metabolic imaging. After characterizing a distinct set of metabolic resting state networks (RSNs) in healthy subjects, network activity was tracked over time in patients with neurodegenerative disorders, such as Parkinson’s disease and Alzheimer’s disease. We found that the dominant normal metabolic RSN, which corresponded to the DMN, is preserved in early-stage Parkinson’s disease patients. Although significant DMN reductions developed later, these changes were reversible in part by dopamine treatment. This finding contrasts with Alzheimer’s disease, in which DMN loss is rapid and continuous, beginning before clinical diagnosis. Metabolic imaging can provide a versatile, quantitative means of assessing brain disease at the network level. The delineation of resting state networks (RSNs) in the human brain relies on the analysis of temporal fluctuations in functional MRI signal, representing a small fraction of total neuronal activity. Here, we used metabolic PET, which maps nonfluctuating signals related to total activity, to identify and validate reproducible RSN topographies in healthy and disease populations. In healthy subjects, the dominant (first component) metabolic RSN was topographically similar to the default mode network (DMN). In contrast, in Parkinson’s disease (PD), this RSN was subordinated to an independent disease-related pattern. Network functionality was assessed by quantifying metabolic RSN expression in cerebral blood flow PET scans acquired at rest and during task performance. Consistent task-related deactivation of the “DMN-like” dominant metabolic RSN was observed in healthy subjects and early PD patients; in contrast, the subordinate RSNs were activated during task performance. Network deactivation was reduced in advanced PD; this abnormality was partially corrected by dopaminergic therapy. Time-course comparisons of DMN loss in longitudinal resting metabolic scans from PD and Alzheimer’s disease subjects illustrated that significant reductions appeared later for PD, in parallel with the development of cognitive dysfunction. In contrast, in Alzheimer’s disease significant reductions in network expression were already present at diagnosis, progressing over time. Metabolic imaging can directly provide useful information regarding the resting organization of the brain in health and disease.
CBR System for Leukemia Patients Diagnosis

The use of computational methods is fundamental in cancer research. One of the possibilities is the use of Artificial Intelligence techniques. Several of these techniques have been used to analyze expression arrays. However, the new Exon arrays which work with a large amount of data require novel solutions. This paper presents a Case-based reasoning (CBR) system for automatic classification of leukemia patients from Exon array data. The proposed CBR system incorporates novel algorithms for data filtering and classification. The system has been tested and the results obtained are presented in this paper.
Low-Cost Approaches to Robust Temperature Compensation in Near-Infrared Calibration and Prediction Situations

The traditional way of handling temperature shifts and other perturbations in calibration situations is to incorporate the non-relevant spectral variation in the calibration set by measuring the samples at various conditions. The present paper proposes two low-cost approaches based on simulation and prior knowledge about the perturbations, and these are compared to traditional methods. The first approach is based on augmentation of the calibration matrix through adding simulated noise on the spectra. The second approach is a correction method that removes the non-relevant variation from new spectra. Neither method demands exact knowledge of the perturbation levels. Using the augmentation method it was found that a few, in this case four, selected samples run under different conditions gave approximately the same robustness as running all the calibration samples under different conditions. For the carbohydrate data set, all robustification methods investigated worked well, including the use of pure water spectra for temperature compensation. For the more complex meat data set, only the augmentation method gave comparable results to the full global model.
Mre11 is essential for the maintenance of chromosomal DNA in vertebrate cells

Yeast Mre11 functions with Rad50 and Xrs2 in a complex that has pivotal roles in homologous recombination (HR) and non‐homologous end‐joining (NHEJ) DNA double‐strand break (DSB) repair pathways. Vertebrate Mre11 is essential. Conditionally, MRE11 null chicken DT40 cells accumulate chromosome breaks and die upon Mre11 repression, showing frequent centrosome amplification. Mre11 deficiency also causes increased radiosensitivity and strongly reduced targeted integration frequencies. Mre11 is, therefore, crucial for HR and essential in mitosis through its role in chromosome maintenance by recombinational repair. Surprisingly perhaps, given the role of Mre11 in yeast NHEJ, disruption of NHEJ by deletion of KU70 greatly exacerbates the effects of MRE11 deficiency, revealing a significant Mre11‐independent component of metazoan NHEJ.
Diffusion Tensor Imaging, Structural Connectivity, and Schizophrenia

A fundamental tenet of the “disconnectivity” theories of schizophrenia is that the disorder is ultimately caused by abnormal communication between spatially disparate brain structures. Given that the white matter fasciculi represent the primary infrastructure for long distance communication in the brain, abnormalities in these fiber bundles have been implicated in the etiology of schizophrenia. Diffusion tensor imaging (DTI) is a magnetic resonance imaging (MRI) technique that enables the visualization of white matter macrostructure in vivo, and which has provided unprecedented insight into the existence and nature of white matter abnormalities in schizophrenia. The paper begins with an overview of DTI and more commonly used diffusion metrics and moves on to a brief review of the schizophrenia literature. The functional implications of white matter abnormalities are considered, particularly with respect to myelin's role in modulating the transmission velocity of neural discharges. The paper concludes with a speculative hypothesis about the relationship between gray and white matter abnormalities associated with schizophrenia.
A novel phase-noise cancelled optical frequency domain reflectometry using modulation sidebands

We propose a novel OFDR method which improves spatial resolution by cancelling laser phase noise. Laser light is intensity-modulated with linearly swept frequency. Both the backscattered light and the reference light are divided into upper- and lower-sideband by optical filter. These two signals are detected and multiplied each other. The laser phase noise is cancelled by this multiplication. The proposed method is confirmed experimentally. The laser phase noise having 1.5MHz linewidth is cancelled by this method. This result confirms that this method is feasible to improve spatial resolution for OFDR.
Curtain Time 20: 00 GMT: Experiments in Virtual Theater on Internet Relay Chat

This is a study of the Hamnet Players, a group who perform parodies of Shakespeare and Tennessee Williams on IRC (Internet Relay Chat). We focus primarily on their first production, a hilarious parody of Hamlet, called “Hamnet”. The main source of humor is the playfully irreverent juxtaposition of Shakespearean plot, characters and language with materials from Net and IRC culture. Hamnet productions are currently primarily textual, but the players are already experimenting with graphics and sound. We analyze (1) the substantive and stylistic features of the “Hamnet” script; (2) the logistics of virtual production; (3) improvisational play with the Shakespearean canon, the “theater game,” language itself, the IRC software, and the situation of typed online interaction. Our approach draws on sociolinguistics and discourse analysis; the ethnography of oral genres of verbal art; Shakespearean studies and analyses of literary genres; research on communication and popular culture; and recent studies of language, play and performance in computer-mediated communication. Hamnet productions are not only experiments in virtual theater; they are also carnivals of wordplay, chock-full of wit and humor. They provide new and important evidence for the rise of interactive digital writing as stylized performance.
Characterizing high-impact features for content retention in social web applications

One of the core challenges of automatically creating Social Web summaries is to decide which posts to remember, i.e., to consider for summary inclusion and which to forget. Keeping everything would overwhelm the user and would also neglect the often intentionally ephemeral nature of Social Web posts. In this paper, we analyze high-impact features that characterize memorable posts as a first step for this selection process. Our work is based on a user evaluation for discovering human expectations towards content retention.
Talent Management in Academies.

Purpose – Academies are semi‐autonomous schools set up outside the normal local government structures with sponsors from business and charity groups to create new and innovative ways of creating and sustaining school transformation. The aim of this paper is to assist in a strategic conversation within the academy movement on talent development.Design/methodology/approach – The paper looks at talent identification, talent development and establishing a talent culture. It provides points in the text for readers to reflect on their own talent practice and provides case examples from current academies.Findings – The paper shows that the longer‐term sustainability of the academy movement needs to address the key issue of developing leadership talent.Originality/value – The paper provides an original and useful framework for developing talent management in academies.
Effect of forage-concentrate ratio in complete feeds fed ad libitum on feed intake prepartum and the occurrence of abomasal displacement in dairy cows.

Abstract Forty Holstein cows were assigned to four complete feeds of: a) 75:25; b) 60:40; c) 45:55; and d) 30:70 forage to concentrate ratios, 28 days before parturition, to examine the effect of ration energy level on the ad libitum consumption of energy in relation to requirements. During 25 days following parturition, 0, 2, 4, and 4 cases of left displacement of the abomasum occurred in the four ration groups, respectively. The mean daily dry matter intake 28 days prepartum did not differ significantly (P Digestible energy consumed during the 28 days before calving averaged 155, 138, 159, and 173% of National Research Council's maintenance requirements for the four treatment groups, respectively.
The cryptic tetracycline resistance determinant on Tn4400 mediates tetracycline degradation as well as tetracycline efflux

Escherichia coli containing the cryptic tetracycline resistance determinant (class F) from the Bacteroides fragilis transposon Tn4400 on plasmid pGAT400 expressed a detoxification of tetracycline as well as an active efflux of tetracycline. This finding concurs with the report of detoxification for a related tetracycline resistance determinant from B. fragilis on Tn4351 (B. S. Speer and A. Salyers, J. Bacteriol. 170:1423-1429, 1987), which specifies a 10-fold-higher resistance than Tn4400. Inactivation of tetracycline occurred at an initial rate of congruent to 0.7 micrograms of tetracycline per h per 10(8) cells, as determined by biologic assay and chromatographic analysis. The detoxification is a chemical degradation which can occur in the absence of energy-dependent efflux. The products of this degradation were not substrates for active transport into susceptible cells or out of pGAT400-containing E. coli. These results indicate that Tn4400 mediates two functionally different mechanisms for tetracycline resistance: an active efflux of tetracycline and a degradation of tetracycline.
Locus of control : daily variability within a stressful context

Research has established locus of control as a strong trait-level predictor of health and well-being and indicates that individuals with a greater sense of internal control benefit from healthier outcomes across a broad range of domains. To date, however, little research has investigated the potential malleability and state-level functioning of locus of control. Drawing from social learning theories, it was predicted that locus of control would vary on a daily basis and further that this variation would be influenced by daily hassles and anxiety. Additionally, an individual’s trait-level of internal locus of control was expected to moderate this association. The current study consists of 58 couples expecting their first child. Couples were asked to independently complete three weeks of daily diaries during their third trimester. Diaries assessed daily feelings of control, anxiety, and number of hassles encountered. Once reliable daily variation of locus of control was established, within-person analyses revealed a negative relationship such that on a day when an individual reported more anxiety or more hassles, that individual also reported feeling less control than on an average day. Further analyses revealed that an individual’s trait-level of internal control influenced this association such that, overall, those individuals with a higher trait-level of internality maintained higher levels of daily control in the face of hassles and anxiety. These findings extend prior research by providing a better understanding of locus of control and suggest important implications for efforts aimed at improving health and well-being.
Improving Estimation of Distribution Algorithm on Multimodal Problems by Detecting Promising Areas

In this paper, a novel multiple sub-models maintenance technique, named maintaining and processing sub-models (MAPS), is proposed. MAPS aims to enhance the ability of estimation of distribution algorithms (EDAs) on multimodal problems. The advantages of MAPS over the existing multiple sub-models based EDAs stem from the explicit detection of the promising areas, which can save many function evaluations for exploration and thus accelerate the optimization speed. MAPS can be combined with any EDA that adopts a single Gaussian model. The performance of MAPS has been assessed through empirical studies where MAPS is integrated with three different types of EDAs. The experimental results show that MAPS can lead to much faster convergence speed and obtain more stable solutions than the compared algorithms on 12 benchmark problems.
Nutritional and clinical associations of food cravings in pregnancy

Abstract Background Cravings in pregnancy are considered to alter dietary intake; however, the nutritional consequences are unknown. The present study aimed to investigate the prevalence of food cravings in pregnancy, and their contribution, as a potentially modifiable determinant of weight gain and the development of obesity in pregnancy. Methods Healthy pregnant women were participants in the Belfast cohort of the Hyperglycaemia and Adverse Pregnancy Outcome study (HAPO), a prospective observational study examining maternal glycaemia and pregnancy outcome. Diet was assessed at an average of 29 weeks of gestation using a self‐administered validated food frequency questionnaire over the previous 2 weeks that included questions on food cravings experienced at any time during pregnancy. Clinical measurements collected included, height, weight, blood glucose and neonatal outcomes. Mean daily nutrient intakes were analysed with appropriate software. Results Food cravings were reported by 39% (n = 635) of women, with sweet foods, fruit and dairy products most frequently consumed. Those who craved foods had a higher mean (SD) energy intake [9721 (3016) kJ] (P = 0.002) even when under‐reporters were removed [10131 (2875) kJ] (P = 0.008). However, no differences were found in nutrient or food intake between groups when adjusted for energy. Similarly, no differences were observed between groups and glycaemic control, anthropometric measurements or offspring outcome measures. Conclusions Cravings commonly occur in pregnancy and contributed to a small increase in energy intake; however, this did not impact on overall dietary intake, nor was it associated with excessive gestational weight gain, maternal glycaemia or offspring outcome measurements.
Preventing Cryptographic Key Leakage in Cloud Virtual Machines

In a typical infrastructure-as-a-service cloud setting, different clients harness the cloud provider's services by executing virtual machines (VM). However, recent studies have shown that the cryptographic keys, the most crucial component in many of our daily used cryptographic protocols (e.g., SSL/TLS), can be extracted using cross-VM side-channel attacks. To defeat such a threat, this paper introduces HERMES, a new system that aims to protect the cryptographic keys in the cloud against any kind of cross-VM side-channel attacks by simply partitioning the cryptographic keys into random shares, and storing each share in a different VM. Moreover, it also periodically re-shares the cryptographic keys, thereby invalidating the potentially extracted partial ones. We have implemented HERMES as a library extension that is transparent to the application software, and performed deep case studies with a web and a mail server on Amazon EC2 cloud. Our experimental results show that the runtime overhead of the proposed system can be as low as 1%.
Streak Lines as Tangent Curves of a Derived Vector Field

Characteristic curves of vector fields include stream, path, and streak lines. Stream and path lines can be obtained by a simple vector field integration of an autonomous ODE system, i.e., they can be described as tangent curves of a vector field. This facilitates their mathematical analysis including the extraction of core lines around which stream or path lines exhibit swirling motion, or the computation of their curvature for every point in the domain without actually integrating them. Such a description of streak lines is not yet available, which excludes them from most of the feature extraction and analysis tools that have been developed in our community. In this paper, we develop the first description of streak lines as tangent curves of a derived vector field - the streak line vector field - and show how it can be computed from the spatial and temporal gradients of the flow map, i.e., a dense path line integration is required. We demonstrate the high accuracy of our approach by comparing it to solutions where the ground truth is analytically known and to solutions where the ground truth has been obtained using the classic streak line computation. Furthermore, we apply a number of feature extraction and analysis tools to the new streak line vector field including the extraction of cores of swirling streak lines and the computation of streak line curvature fields. These first applications foreshadow the large variety of possible future research directions based on our new mathematical description of streak lines.
Young nonresident biological fathers

This paper summarizes research, policies, and pro- grams related to nonresident, adolescent and young adult biological fathers and outlines avenues for future initiatives in these areas. The discussion is informed by a conceptual model that illustrates how a set of interrelated macro and micro factors affect the way young fathers respond to their paternity and father roles. Research on nonresident young fathers is limited because it is largely based on data from small convenience samples. While sev- eral studies use national survey data to address issues relevant to young fathers, they are restricted because the samples are not repre- sentative of those who have fathered a child, many young men are unwilling or unable to provide an accurate report of their paternity history, surveys either omit or include only cursory measures of key concepts that address fatherhood issues, data are not collected as part of a larger conceptual framework, and data are based on older co- horts of youth. Survey data do indic.
High performance informatics for pandemic preparedness

Pandemics such as H1N1 influenza are global outbreaks of infectious disease. Human behavior, social contact networks, and pandemics are closely intertwined. The ordinary behavior and daily activities of individuals create varied and dense social interactions that are characteristic of modern urban societies. They provide a perfect fabric for rapid, uncontrolled disease propagation. Individuals' changing behaviors in response to public policies and their evolving perception of how an infectious disease outbreak is unfolding can dramatically alter normal social interactions. Effective planning and response strategies must take these complicated interactions into account. Recent quantitative changes in high performance computing and networking have created new opportunities for collecting, integrating, analyzing and accessing information related to such large social contact networks and epidemic outbreaks. The paper will describe our efforts to build a Cyber Infrastructure for EPIdemics (CIEPI) - a high performance computing oriented decision-support environment to support planning and response in the event of epidemics.
Modeling correlation between multi-modal continuous words for pLSA-based video classification

Seeing that probabilistic Latent Semantic Analysis (pLSA) deals with discrete quantity only, pLSA with Gaussian Mixtures (GM-pLSA) extends it to continuous feature space by treating continuous feature as continuous word. However, GM-pLSA does not provide a clear way of modeling multimodal features, and also neglects the intrinsic correlation between these continuous words. In this paper, we present a graph regularized multi-modal GM-pLSA (GRMMGM-pLSA) model to incorporate such correlation between multimodal continuous words into the process of model learning. First, multiple GMMs are adopted with each depicting the distribution of continuous words from each modality; and then, a graph regularizer is introduced to capture the word correlation. In the task of video classification, GRMMGM-pLSA that takes both multi-modal visual features of sub-shots and word correlation in terms of temporal consistency between sub-shots into account is exploited to perform feature mapping. Experiments on YouTube videos show the effectiveness of our proposed model.
Bireylerin Kişisel Özellikleri Yönünden İş Doyum Düzeylerine Göre Tükenmişlikleri: Afyonkarahisar İlinde Bir Araştırma

Bu arastirmanin amaci Afyonkarahisar ili ve ilcelerindeki hastanelerde yonetici olarak calisan bireylerin kisisel ozelliklerine gore is doyumlari ve is doyumlarina gore tukenmisliklerini incelemektir. Arastirmanin sonucunda, calisanlarin egitim duzeyine ve medeni durumlarina, hizmet yilina ve gorev pozisyonlarina gore is doyumlari arasinda bir fark olmadigi gorulmustur. Is doyum duzeyi dusuk calisanlarda duygusal tukenme ve duyarsizlasmanin is doyum duzeyi yuksek olanlardan anlamli duzeyde yuksek oldugu, kisisel basarinin anlamli duzeyde dusuk oldugu sonucu elde edilmistir. Hizmet yili on yildan daha uzun olan yoneticilerde kisisel basarinin hizmeti on yildan az olanlara gore anlamli bir sekilde daha yuksek oldugu bulunmustur. Yine, is doyum duzeyi dusuk olan grup uzerinde yapilan analizlerde hizmetinin ilk bes yilinda olanlarda duygusal tukenmenin daha yuksek oldugu sonucu elde edilmistir