Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of Hyperglycemia on Survival and Infection-Related Adverse Events in Patients with Metastatic Colorectal Cancer Who Were Receiving Palliative Chemotherapy

Purpose Non-metastatic colorectal cancer patients with diabetes have poor overall survival than those without diabetes. However, the effect of hyperglycemia on survival after diagnosis of metastatic colorectal cancer (CRC) has not been assessed. Therefore, we assessed the impact of hyperglycemia on the survival and infection-related adverse events (AEs) in patients with metastatic CRC. Materials and Methods We reviewed the records of 206 patients with newly diagnosed metastatic CRC who were treated with palliative chemotherapy from March 2000 to December 2012 at Chungbuk National University Hospital. The mean glucose level of each patient was calculated using all available glucose results. Results The mean glucose levels ranged between 76.8 and 303.5 mg/dL, and patients were categorized into quartiles in accordance to their mean glucose level: group 1 (< 106.7 mg/dL), group 2 (106.7-117.2 mg/dL), group 3 (117.3-142.6 mg/dL), and group 4 (> 142.6 mg/dL). The median overall survival for patients in groups 1, 2, 3, and 4 were 22.6, 20.1, 18.9, and 17.9 months, respectively; however, this difference was not statistically significant (p=0.643). Compared with patients in group 1, those in groups 2, 3, and 4 were at a higher risk of infection-related AEs, according to a multivariate analysis (p=0.002). Conclusion Hyperglycemia was not associated with shorter survival; however, it was associated with infection-related AEs in patients with newly diagnosed metastatic CRC receiving palliative chemotherapy.
Social comparison and a defensive social mentality : an evolutionary perspective of group living.

SOCIAL COMPARISON AND A DEFENSIVE SOCIAL MENTALITY: AN EVOLUTIONARY PERSPECTIVE OF GROUP LIVING MATTHEW BOXALL Evolutionary psychology is becoming an area of increasing interest for understanding and explaining human cognition, emotion and behaviour. One key area of this field relates to our heritage of social living and the impact that this has had upon our inherited psychological makeup. The study aimed to consider the relationship between a number of variables related to this area guided by a basic theoretical model derived from the literature. The variables considered were social comparisons, two types of social anxiety, submissive behaviour and paranoid social cognitions. The study used a correlational design on a clinical group (A/=31) and non-clinical comparison group (N=27) of subjects. A between groups analysis was also undertaken. For the clinical group social comparisons were found be significantly correlated with scrutiny social anxiety. In turn scrutiny social anxiety was found to be significantly correlated with both paranoid social cognitions and submissive behaviour. For the comparison group no significant correlations were found between social comparison and the other variables. However, social scrutiny anxiety was again found to significantly correlate with paranoid social cognitions and submissive behaviour. Between group analyses showed highly significant differences between the groups on all variables measured. The results for the clinical group broadly supported the model put forward whilst this was not the case for the comparison group. The clinical group results indicated that where individuals took on a more subordinate role they would also assume a more competitive and defensive posture in their interactions with others. This was considered to form the basis of an evolutionary prepared set of responses that facilitate group living in the context of social hierarchies. Th*e differing results obtained for the comparison group were discussed as were the clinical and wider implications of the findings.
Specific Resistance Exercise Can Alter Masticatory Movement and Muscle Recruitment Patterns of the Human Jaw.

xi CONTENTS . xv LIST OF FIGURES . xviii LIST OF TABLES . xxii ABBREVIATIONS . xxiii CONFERENCES AND PRESENTATIONS . xxv PUBLICATIONS . xxvi CHAPTER 1 . 1 LITERATURE REVIEW .
Energy Saving Virtual Machine Allocation in Cloud Computing

In the data center, a server can work in either active state or power-saving state. The power consumption in the power-saving state is almost 0, thus it is always desirable to allocate as many VMs as possible to some active servers and leave the rest to power-saving state in order to reduce the energy consumption of the data center. In this paper, we study such a VM allocation problem. Given a set VMs and a set of servers in a data center, each VM has a resource demand (CPU, memory, storage) and a starting time and a finishing time, and each server has resource capacity. There is an additional energy cost for a server to switch from power-saving state to active state. The servers are non-homogeneous. The problem of our concern is to allocate the VMs onto servers, such that the VMs resource demands can be met and the total energy consumption of servers is minimized. The problem is formulated as a boolean integer linear programming problem. A heuristic algorithm is proposed to solve the problem. Extensive simulations have been conducted to demonstrate our proposed method can significantly save the energy consumption in data centers.
A generalized deterministic algorithm for blind channel identification with filter bank precoders

It is well-known that redundant filter bank precoders can be used for blind identification as well as equalization of FIR channels. Several algorithms have been proposed in the literature exploiting trailing zeros in the transmitter. In this paper we propose a generalized algorithm of which the previous algorithms are special cases. By carefully choosing system parameters, we can jointly optimize the system performance and computational complexity. Simulation shows that the proposed algorithm outperforms the previous ones when the parameters are optimally chosen
ZoneTrust: Fast Zone-Based Node Compromise Detection and Revocation in Wireless Sensor Networks Using Sequential Hypothesis Testing

Due to the unattended nature of wireless sensor networks, an adversary can physically capture and compromise sensor nodes and then mount a variety of attacks with the compromised nodes. To minimize the damage incurred by the compromised nodes, the system should detect and revoke them as soon as possible. To meet this need, researchers have recently proposed a variety of node compromise detection schemes in wireless ad hoc and sensor networks. For example, reputation-based trust management schemes identify malicious nodes but do not revoke them due to the risk of false positives. Similarly, software-attestation schemes detect the subverted software modules of compromised nodes. However, they require each sensor node to be attested periodically, thus incurring substantial overhead. To mitigate the limitations of the existing schemes, we propose a zone-based node compromise detection and revocation scheme in wireless sensor networks. The main idea behind our scheme is to use sequential hypothesis testing to detect suspect regions in which compromised nodes are likely placed. In these suspect regions, the network operator performs software attestation against sensor nodes, leading to the detection and revocation of the compromised nodes. Through quantitative analysis and simulation experiments, we show that the proposed scheme detects the compromised nodes with a small number of samples while reducing false positive and negative rates, even if a substantial fraction of the nodes in the zone are compromised. Additionally, we model the detection problem using a game theoretic analysis, derive the optimal strategies for the attacker and the defender, and show that the attacker's gain from node compromise is greatly limited by the defender when both the attacker and the defender follow their optimal strategies.
The Finnish Diabetes Prevention Study (DPS): Lifestyle intervention and 3-year results on diet and physical activity.

OBJECTIVE To describe the 1) lifestyle intervention used in the Finnish Diabetes Prevention Study, 2) short- and long-term changes in diet and exercise behavior, and 3) effect of the intervention on glucose and lipid metabolism. RESEARCH DESIGN AND METHODS There were 522 middle-aged, overweight subjects with impaired glucose tolerance who were randomized to either a usual care control group or an intensive lifestyle intervention group. The control group received general dietary and exercise advice at baseline and had an annual physician's examination. The subjects in the intervention group received additional individualized dietary counseling from a nutritionist. They were also offered circuit-type resistance training sessions and advised to increase overall physical activity. The intervention was the most intensive during the first year, followed by a maintenance period. The intervention goals were to reduce body weight, reduce dietary and saturated fat, and increase physical activity and dietary fiber. RESULTS The intervention group showed significantly greater improvement in each intervention goal. After 1 and 3 years, weight reductions were 4.5 and 3.5 kg in the intervention group and 1.0 and 0.9 kg in the control group, respectively. Measures of glycemia and lipemia improved more in the intervention group. CONCLUSIONS The intensive lifestyle intervention produced long-term beneficial changes in diet, physical activity, and clinical and biochemical parameters and reduced diabetes risk. This type of intervention is a feasible option to prevent type 2 diabetes and should be implemented in the primary health care system.
Geometric aspects of the theory of Krylov subspace methods

The development of Krylov subspace methods for the solution of operator equations has shown that two basic construction principles underlie the most commonly used algorithms: the orthogonal residual (OR) and minimal residual (MR) approaches. It is shown that these can both be formulated as techniques for solving an approximation problem on a sequence of nested subspaces of a Hilbert space, an abstract problem not necessarily related to an operator equation. Essentially all Krylov subspace algorithms result when these subspaces form a Krylov sequence. The well-known relations among the iterates and residuals of MR/OR pairs are shown to hold also in this rather general setting. We further show that a common error analysis for these methods involving the canonical angles between subspaces allows many of the known residual and error bounds to be derived in a simple and consistent manner. An application of this analysis to compact perturbations of the identity shows that MR/OR pairs of Krylov subspace methods converge q-superlinearly when applied to such operator equations.
On dataset biases in a learning system with minimum a priori information for intrusion detection

A critical design decision in the construction of intrusion detection systems is often the selection of features describing the characteristics of the data being learnt. Selecting features often requires a priori or expert knowledge and may lead to the introduction of specific attack biases ntended or otherwise. To this end, summarized network connections from the DARPA 98 Lincoln Labs dataset are employed for training and testing a data driven learning architecture. The learning architecture is composed from a hierarchy of self-organizing feature maps. Such a scheme is entirely unsupervised, thus the quality of the intrusion detection system is directly influenced by the quality of the dataset. Dataset biases are investigated through three different dataset partitions: 10% KDD (default training dataset); normal connections alone; 50/50 mix of attack and normal. The three resulting intrusion detection systems appear to be competitive with the alternative cluster based data-mining approaches.
Algorithm of face angle estimation in the image

The localization of the area of interest in face image to recognition is the key task in face recognition system. The face detection problem is first step before face recognition process. The properties of recognition system depend on the quality of processing images and area of face localization. Many systems are adapted to process the images with frontal type of faces only. We propose the approach to estimate a deviation angle of face from biometric standard in order to expand the range of variety of recognizable face images.
Construction of Quasi Cyclic LDPC Codes Based on Girth Opt-PSO Algorithm

The QC(quasi-cyclic) LDPC codes are an important subclass of LDPC codes. The key to improving the performance of QC LDPC codes is how to construct a parity-check matrix H with a girth distribution as good as possible. In this paper, method of girth detection of QC LDPC codes is described first. Furthermore, a novel algorithm, GirthOpt-PSO algorithm, is proposed to construct the QC LDPC codes, which achieves a good girth distribution based on the PSO algorithm. Simulation results show that the performance of the QC LDPC codes constructed by proposed algorithm is better than Tanner code and Array codes. Besides, the proposed algorithm is more flexible for designing the QC LDPC codes with desired block length and rate as well as good girth.
A Binary Descriptor Structured on More Spatial Information

Conventional binary descriptor only uses limited spatial information from original image patch, such as BRIEF, which will result in limited discriminative power. We settle this problem through further excavating feature information and propose a binary descriptor encoding not only intensity comparison information but also intensity order information. Results based on experiments of performance evaluation have shown that the proposed binary descriptor outperforms other binary descriptors under rotation and scale changes.
Correlation of single leg vertical jump, single leg hop, and single leg squat distances in healthy persons

Objective: To determine the correlation among three functional tests: single leg vertical jump (SLVJ), single leg hop for distance (SLHD), and single leg squat (SLSQ). Design: Cross sectional study. Methods: Twenty healthy men (n=10) and women (n=10) with no history of lower extremity dysfucntion participated in this study and performed in university research laboratory. The procedures consisted of a general warm-up, a task-specific warm-up, actual testing, and a cool down. All participants performed the three tests in random order. Each test was performed three times for the dominant and non-dominant lower extremity (LE). SLVJ, SLHD, SLSQ were measured using a standard tape measure. Results: Statistically significant difference was presented between dominant LE and non-dominant LE in each function test (p
Two Amino Acid Residues Contribute to a Cation-π Binding Interaction in the Binding Site of an Insect GABA Receptor

Cys-loop receptor binding sites characteristically possess an “aromatic box,” where several aromatic amino acid residues surround the bound ligand. A cation-π interaction between one of these residues and the natural agonist is common, although the residue type and location are not conserved. Even in the closely related vertebrate GABAA and GABAC receptors, residues in distinct locations perform this role: in GABAA receptors, a Tyr residue in loop A forms a cation-π interaction with GABA, while in GABAC receptors it is a loop B residue. GABA-activated Cys-loop receptors also exist in invertebrates, where they have distinct pharmacologies and are the target of a range of pesticides. Here we examine the location of GABA in an insect binding site by incorporating a series of fluorinated Phe derivatives into the receptor binding pocket using unnatural amino acid mutagenesis, and evaluating the resulting receptors when expressed in Xenopus oocytes. A homology model suggests that two aromatic residues (in loops B and C) are positioned such that they could contribute to a cation-π interaction with the primary ammonium of GABA, and the data reveal a clear correlation between the GABA EC50 and the cation-π binding ability both at Phe206 (loop B) and Tyr254 (loop C), demonstrating for the first time the contribution of two aromatic residues to a cation-π interaction in a Cys-loop receptor.
Approaches to modeling thermonuclear flames

Turbulence-flame interactions of thermonuclear fusion flames occurring in Type Ia Supernovae were studied by means of incompressible DNS with a highly simplified flame description. The flame is treated as a single diffusive scalar field with a nonlinear source term. It is characterized by its Prandtl number, Pr 1, and laminar flame speed, SL. We find that if SL ≥ u′, where u′ is the rms amplitude of turbulent velocity fluctuations, the local flame propagation speed does not significantly deviate from SL even in the presence of velocity fluctuations on scales below the laminar flame thickness. This result is interpreted in the context of subgrid-scale modeling of supernova explosions.
Dirac oscillator with nonzero minimal uncertainty in position

In the context of some deformed canonical commutation relations leading to isotropic nonzero minimal uncertainties in the position coordinates, a Dirac equation is exactly solved for the first time, namely that corresponding to the Dirac oscillator. Supersymmetric quantum mechanical and shape-invariance methods are used to derive both the energy spectrum and wavefunctions in the momentum representation. As for the conventional Dirac oscillator, there are neither negative-energy states for E = ? 1, nor symmetry between the and cases, both features being connected with supersymmetry or, equivalently, the ? transformation. In contrast with the conventional case, however, the energy spectrum does not present any degeneracy pattern apart from that associated with the rotational symmetry. More unexpectedly, deformation leads to a difference in behaviour between the states corresponding to small, intermediate and very large j values in the sense that only for the first ones supersymmetry remains unbroken, while for the second ones no bound state exists.
Fathers' Involvement and Children's Delay of Gratification:the Moderating Role of Gender

The study investigated the association between fathers' involvement with children's delay of gratification under the condition of mothers' involvement and children's age to be controlled,as well as the moderating role of gender between them. 92 healthy children aged between 35 to 74 months were measured with waiting paradigm for delay of gratification. Their parents were measured with Father Involvement Questionnaire and Mother involvement Questionnaire for father's involvement and mother's involvement respectively. The results showed that:( 1) three aspects of fathers ' involvement —— interaction,accessibility and responsibility —— significantly predicted children's delay of gratification;( 2) gender played a moderating role between fathers' involvement and children' s delay of gratification in that for boys,fathers' interaction and responsibility significantly predicted the delay of gratification,whereas for girls,no moderating effect was observed.
Application of Genetic Programming on Temper Mill Datasets

Temper rolling is essential for the quality of steel sheets. The degree of temper rolling determines the mechanical properties of the steel sheet and is highly influenced by the rolling force or strip tension. Since mathematical models generate unsatisfactory results for the calculation of these two process parameters, other methods for the presetting of tempers mills must be used. The parameter presetting of temper mills is of prime importance because it reduces the effort of tuning these parameters later. Hence, the production costs are reduced by minimizing the amount of wasted material that does not fulfill the quality requirements. Genetic Programming (GP) is an evolutionary inspired and population based modeling technique and has been successfully applied in different contexts. In this paper we present first results of advanced genetic programming concepts on large datasets from a temper mill in comparison to linear regression (LR), support vector machines (SVMs) and previous analysis on the datasets. The use of GP shows an improvement compared to previous work, but is still inferior to models obtained by SVMs. A major advantage of GP compared to support vector machines is that the identified models are mathematical formulae which can be interpreted and enable knowledge generation about the temper rolling process.
Normalization and quantification of differential expression in gene expression microarrays

Array-based gene expression studies frequently serve to identify genes that are expressed differently under two or more conditions. The actual analysis of the data, however, may be hampered by a number of technical and statistical problems. Possible remedies on the level of computational analysis lie in appropriate preprocessing steps, proper normalization of the data and application of statistical testing procedures in the derivation of differentially expressed genes. This review summarizes methods that are available for these purposes and provides a brief overview of the available software tools.
A 100 kpc INVERSE COMPTON X-RAY HALO AROUND 4C 60.07 AT z = 3.79

We analyze a 100 ks Chandra observation of the powerful radio galaxy, 4C 60.07 at z = 3.79. We identify extended X-ray emission with LX ∼ 1045 erg s−1 across a ∼90 kpc region around the radio galaxy. The energetics of this X-ray halo and its morphological similarity to the radio emission from the galaxy suggest that it arises from inverse Compton (IC) scattering, by relativistic electrons in the radio jets, of cosmic microwave background photons and potentially far-infrared photons from the dusty starbursts around this galaxy. The X-ray emission has a similar extent and morphology to the Lyα halo around the galaxy, suggesting that it may be ionizing this halo. Indeed, we find that the GHz-radio and X-ray and Lyα luminosities of the halo around 4C 60.07 are identical to those of 4C 41.17 (also at z = 3.8) implying that these three components are linked by a single physical process. This is only the second example of highly extended IC emission known at z>3, but it underlines the potential importance of IC emission in the formation of the most massive galaxies at high redshifts. In addition, we detect two X-ray luminous active galactic nuclei (AGNs) within ∼30 kpc of the radio galaxy. These two companion AGNs imply that the radio and starburst activity in the radio galaxy is triggered through multiple mergers of massive progenitors on a short timescale, ≲100 Myr. These discoveries demonstrate the wealth of information which sensitive X-ray observations can yield into the formation of massive galaxies at high redshifts.
Statistical comparison between max-dmin, max-SNR and MMSE precoders

In this study, we considered a MIMO system with available channel state information at the transmitter side and compared three known precoders based on different and pertinent criteria: the post processing signal-to-noise ratio (max-SNR), the mean square error between transmitted and received symbols (MMSE) and the minimum distance of the received constellation (max-dmin). We demonstrate that, alike the max-SNR and contrarily to the MMSE, the max-dmin gives the maximum diversity order for a Rayleigh channel. An upper- bound of the MMSE diversity order is given. On the other hand, dmin of the three precoders will be statistically studied as a function of the number of antennas. In addition, BER simulations showed that the best precoder is the max-dmin.