Miracle-dz/UniFAR-FTUs huggingface dataset:
Mutant p53 protein expression and antioxidant status deficiency in breast cancer

It is well recognized that cancers develop and grow as a result of disordered function of tumor suppressor genes and oncogenes, which may be exploited for screening purposes. Extensive evidence indicated tumor suppressor protein p53 as candidate marker for mutation identification. We have investigated mutant p53 protein expression in human breast tumors in relation to antioxidant status deficiency. The study included 100 breast cancer patients. p53 protein expression was evaluated by Western blot assay and immunostaining using a CM-1, DO-7 and Pab240 antibodies. Antioxidant parameters and lipid peroxidation were estimated by biochemical analyses. Western blotting with epitopespecific monoclonal antibody Pab240 strongly suggests that nuclear extracts from breast cancer cells express mutant forms of p53. It is of interest that the mutant forms of p53 overexpression in conjunction with the appearance of nuclear bodies are observed in highly aggressive carcinomas. Expression of isoform Δp53 (45 kDa) and isoform of ~ 29 kDa were more common in cases with LN metastasis. These studies point out the molecular consequences of oxidative stress (lipid peroxides, LP, p<0.001) and antioxidant status deficiency (copper, zinc superoxid dismutase, SOD, p<0.001; catalase, CAT, p<0.01; glutathione reductase, GR, p<0.001; glutathione, GSH, p<0.05) and indicate the importance of p53 mutation as the commonest genetic alteration detected in breast cancer cells. The expression of mutant p53 is correlated to increased lipid peroxides (0.346, p<0.05 ) and lowered antioxidant activity of CAT (- 0.437, p<0.01) in the breast cancer patients.
On the use of different feature extraction methods for linear and non linear kernels

The speech feature extraction has been a key focus in robust speech recognition research; it significantly affects the recognition performance. In this paper, we first study a set of different feature extraction methods such as linear predictive coding (LPC), mel frequency cepstral coefficient (MFCC) and perceptual linear prediction (PLP) with several features normalization techniques including rasta filtering and cepstral mean subtraction (CMS). Based on this, a comparative evaluation of these features is performed on the task of text independent speaker identification using a combination between gaussian mixture models (GMM) and linear or non-linear kernels based on support vector machine (SVM).
Beetroot (Beta vulgaris L.) Extract Ameliorates Gentamicin-Induced Nephrotoxicity Associated Oxidative Stress, Inflammation, and Apoptosis in Rodent Model

The present investigation was designed to investigate the protective effect of (Beta vulgaris L.) beat root ethanolic extract (BVEE) on gentamicin-induced nephrotoxicity and to elucidate the potential mechanism. Serum specific kidney function parameters (urea, uric acid, total protein, creatinine, and histopathology of kidney tissue) were evaluated to access gentamicin-induced nephrotoxicity. The oxidative/nitrosative stress (Lipid peroxidation, MDA, NP-SH, Catalase, and nitric oxide levels) was assessed. The inflammatory response (TNF-α, IL-6, MPO, NF-κB (p65), and NF-κB (p65) DNA binding) and apoptotic marker (Caspase-3, Bax, and Bcl-2) were also evaluated. BVEE (250 and 500 mg/kg) treatment along with gentamicin restored/increased the renal endogenous antioxidant status. Gentamicin-induced increased renal inflammatory cytokines (TNF-α and IL-6), nuclear protein expression of NF-κB (p65), NF-κB-DNA binding activity, myeloperoxidase (MPO) activity, and nitric oxide level were significantly down regulated upon BVEE treatment. In addition, BVEE treatment significantly reduced the amount of cleaved caspase 3 and Bax, protein expression and increased the Bcl-2 protein expression. BVEE treatment also ameliorated the extent of histologic injury and reduced inflammatory infiltration in renal tubules. These findings suggest that BVEE treatment attenuates renal dysfunction and structural damage through the reduction of oxidative stress, inflammation, and apoptosis in the kidney.
G2 Hitchin functionals at one loop

We consider the quantization of the effective target space description of topological M-theory in terms of the Hitchin functional whose critical points describe seven manifolds with a G2 structure. The one-loop partition function for this theory is calculated and an extended version of it, that is related to the generalized G2 geometry, is compared with the topological G2 string. We relate the reduction of the effective action for the extended G2 theory to the Hitchin functional description of the topological string in six dimensions. The dependence of the partition functions on the choice of background G2 metric is also determined.
The SmartTer-a Vehicle for Fully Autonomous Navigation and Mapping in Outdoor Environments

The driving factor for the development of the vehicle presented in this paper was to construct a hardware platform that allows to perform the tasks of environment mapping and autonomous navigation in large scale outdoor environments. Our robot is based on a standard Smart car that has been equipped with five distance laser sensors, three cameras, a differential GPS, an Inertial Measurement Unit (IMU), an optical gyroscope and four computers. The car’s systems states are directly accessed through the vehicle’s CAN bus. Localization and Navigation are realized by fusing all available sensory information in a probabilistic way. This allows for high precision localization and dynamic local and global path planning. Using the 3D point clouds extracted from the rotating lasers and the omnidirectional image the smartTer is able to consistently register the 3D maps and analyse the scene for regions of interest. To control the car in both longitudinal and lateral direction we applied a couple of modifications to the car, namely providing access to the car’s power steering system, electronic gas and brake pedal. Keywords—sensor fusion, outdoor vehicle, 3D mapping
Aspects of Radical Constructivism *

* The main difference between science and religion, we were told in school, is that religion is founded on a dogma that is absolute and immutable because it stems from divine revelation, whereas science is tentative because it develops theories that are always open to refutation by new findings or novel experiments. Scientists, therefore, are supposed to be open-minded and to welcome the solution of stubborn problems, even if the new solutions entail a change of thinking and the demise of concepts that seemed well established in the past. A look at the history of scientific ideas, quickly shows that scientists do not always live up to this ideal open-mindedness. The concepts and methods they grew up with frequently seem to be as unshakable as any matter of religious faith, and the perpetrators of innovation tend to be treated as heretics. This happened to Darwin and his theory of evolution, to Einstein when he first published the theory of relativity, and it happened to Alfred Wegener when he suggested the idea of continental drift. In these spectacular instances the break with tradition advocated by the new theory was unmistakable and, consequently, triggered violent indignation on the part of those who were anxious to maintain the familiar established dogma. The new theories won out eventually, because they enabled scientists to do things they had not been able to do before and to cover a larger area of experience with fewer assumptions. In philosophy, the pattern has been different, especially with regard to the problems of epistemology, i.e., those concerning knowledge, its origin, and its " truth ". These problems remained unchanged and unsolved, and they have troubled Western philosophy for more than 2500 years. It is an historical fact that some of the pre-Socratics, the philosophers who wrote before Plato's reports of the Socratic dialogues, had already seen the basic epistemological crux. Its source can be found in two presuppositions that have always seemed natural and inevitable: a) that a fully structured world exists independently of any experiencing or knowing human subject; * This text contains revised segments of three earlier publications: Cognition, construction of
License Plate Location Based on Compound Mathematical Morphology

License plate location is the key to the recognition system of motor vehicle license. This paper presents an algorithm for license plate location based on compound mathematical morphology. An edge detection operator is designed for the edge extraction of the license plate image, with a clear edge image obtained. Then, the horizontal and vertical projections are used to locate the license plate area. The experimental result shows that the algorithm is accurate and efficient in the license plate location.
Interspecies and Intraspecies Analysis of Trehalose Contents and the Biosynthesis Pathway Gene Family Reveals Crucial Roles of Trehalose in Osmotic-Stress Tolerance in Cassava

Trehalose is a nonreducing α,α-1,1-disaccharide in a wide range of organisms, and has diverse biological functions that range from serving as an energy source to acting as a protective/signal sugar. However, significant amounts of trehalose have rarely been detected in higher plants, and the function of trehalose in the drought-tolerant crop cassava (Manihot esculenta Crantz) is unclear. We measured soluble sugar concentrations of nine plant species with differing levels of drought tolerance and 41 cassava varieties using high-performance liquid chromatography with evaporative light-scattering detector (HPLC-ELSD). Significantly high amounts of trehalose were identified in drought-tolerant crops cassava, Jatropha curcas, and castor bean (Ricinus communis). All cassava varieties tested contained high amounts of trehalose, although their concentrations varied from 0.23 to 1.29 mg·g−1 fresh weight (FW), and the trehalose level was highly correlated with dehydration stress tolerance of detached leaves of the varieties. Moreover, the trehalose concentrations in cassava leaves increased 2.3–5.5 folds in response to osmotic stress simulated by 20% PEG 6000. Through database mining, 24 trehalose pathway genes, including 12 trehalose-6-phosphate synthases (TPS), 10 trehalose-6-phosphate phosphatases (TPP), and two trehalases were identified in cassava. Phylogenetic analysis indicated that there were four cassava TPS genes (MeTPS1–4) that were orthologous to the solely active TPS gene (AtTPS1 and OsTPS1) in Arabidopsis and rice, and a new TPP subfamily was identified in cassava, suggesting that the trehalose biosynthesis activities in cassava had potentially been enhanced in evolutionary history. RNA-seq analysis indicated that MeTPS1 was expressed at constitutionally high level before and after osmotic stress, while other trehalose pathway genes were either up-regulated or down-regulated, which may explain why cassava accumulated high level of trehalose under normal conditions. MeTPS1 was then transformed into tobacco (Nicotiana benthamiana). Results indicated that transgenic tobacco lines accumulated significant level of trehalose and possessed improved drought stress tolerance. In conclusion, cassava accumulated significantly high amount of trehalose under normal conditions due to multiplied trehalose biosynthesis gene families and constant expression of the active MeTPS1 gene. High levels of trehalose subsequently contributed to high drought stress tolerance.
Is experimentally induced pain associated with socioeconomic status? Do poor people hurt more?

Background The association of pain and socioeconomic status is widely reported, yet much less clearly understood. The aim of this study was to investigate the association of experimentally induced pain threshold and tolerance with socioeconomic status. Material/Methods The study sample consisted of 319 adult subjects from the population of the island of Vis, Croatia, which was previously shown to have a high level of social homogeneity. A manual dolorimeter was used to measure mechanical pressure pain threshold (least stimulus intensity) and pain tolerance (maximum tolerance stimulus intensity) on both hands. Pain tolerance interval was defined as the difference between pain tolerance and threshold. Years of schooling and material status were used as socioeconomic estimates. Results Both of the socioeconomic estimates were significantly correlated with pain threshold, tolerance, and tolerance interval (P<0.001). The mixed modeling analysis, controlled for the effects of age, gender, and 4 psychological variables, indicated that education was not a significant predictor in any of the 3 models. However, lower material status was significantly associated with lower pain tolerance (P=0.038) and narrower pain tolerance interval (P=0.032), but not with pain threshold (P=0.506). The overall percentages of explained variance were lower in the tolerance interval model (20.2%) than in pain tolerance (23.1%) and threshold (33.1%), suggesting the increasing share of other confounding variables in pain tolerance and even more so in tolerance interval model. Conclusions These results suggest a significant association between experimentally induced pain tolerance and tolerance interval with material status, suggesting that poor people indeed do hurt more.
Two Essays on Analytical Capabilities: Antecedents and Consequences

Although organizations are rapidly embracing business analytics (BA) to enhance organizational performance, only a small proportion have managed to build analytical capabilities. While BA continues to draw attention from academics and practitioners, theoretical understanding of antecedents and consequences of analytical capabilities remain limited and lack a systematic view. In order to address the research gap, the two essays investigate: (a) the impact of organization’s core information processing mechanisms and its impact on analytical capabilities, (b) the sequential approach to integration of IT-enabled business processes and its impact on analytical capabilities, and (c) network position and its impact on analytical capabilities. Drawing upon the Information Processing Theory (IPT), the first essay investigates the relationship between organization’s core information processing mechanisms–i.e., electronic health record (EHRs), clinical information standards (CIS), and collaborative information exchange (CIE)–and its impact on analytical capabilities. We use data from two sources (HIMSS Analytics 2013 and AHA IT Survey 2013) to test the theorized relationships in the healthcare context empirically. Using the competitive progression theory, the second essay investigates whether organizations sequential approach to the integration of IT-enabled business processes is associated with increased analytical capabilities. We use data from three sources (HIMSS Analytics 2013, AHA IT Survey 2013, and CMS 2014) to test if sequential integration of EHRs –i.e., reflecting the unique organizational path of integration–has a significant impact on hospital’s analytical capability. Together the two essays advance our understanding of the factors that underlie enabling of firm’s analytical capabilities. We discuss in detail the theoretical and practical implications of the findings and the opportunities for future research. ACKNOWLEDGEMENT First and foremost, I acknowledge the love, support, sacrifice, and patience of my wonderful wife, Sunita. It has been her unflinching support that sustained me throughout the five years of academic pursuit. Second, I would like to thank my dissertation chair, Dr. Pankaj Setia, who had faith in me to see this through to the end. Third, I would also like to thank my dissertation committee, Dr. Rajiv Sabherwal, Dr. David Douglas, and Dr. Nirup Menon for their time and valuable feedback.
The friendship paradox in scale-free networks

Our friends have more friends than we do. That is the basis of the friendship paradox. In mathematical terms, the mean number of friends of friends is higher than the mean number of friends. In the present study, we analyzed the relationship between the mean degree of vertices (individuals), , and the mean number of friends of friends, , in scale-free networks with degrees ranging from a minimum degree (k_min) to a maximum degree (k_max). We deduced an expression for - for scale-free networks following a power-law distribution with a given scaling parameter (alpha). Based on this expression, we can quantify how the degree distribution of a scale-free network affects the mean number of friends of friends.
DEVELOPING EMPATHY ABILITY BY STORY-TELLING WITH PUPPET FOR EARLY CHILDHOOD STUDENT IN LENTERA ALAM LEARNING CENTER

The root of empathy has been planted in person since he/she was a baby. Then one of the way to despite foundation of moral education and built children empathy has to be done since early life. Empathy is an ability to understand others’ feeling and capability to put self on others condition. This research used Action Research Method and aims to know children’s empathy after they performs a folklore story by using puppet in front of their friends. This research engaged 5 students aged 5 years old in Lentera Alam Learning Center. There were four steps, 1) Planning; 2) Action; 3) Observation; and 4) Reflection which were done in two cycles. The treatment was teacher told a folklore story to children, then ask children to retell the story for his/her friend by using puppets in front of the class. Check list observation was used during the performance on the first and second cycle. It was found an improvement on children’s empathy, before the treatment pre-test score is 11.2 then post-test on the first cycle 16.8 and the second cycle 22.4. Children’s empathy shown by the ability to distinguished emotions, sharing, helping, asking apologize, giving forgiveness and cheering others friend when they were sad.
of the TSP and it ’ s Variants 3 . 1 Traveling Salesman Problem

This paper describes an algorithm for minimizing the non-productive time or ‘airtime’ for a tool by optimally connecting the toolpaths for that tool. This problem is formulated as a generalized traveling salesman problem with precedence constraints and is solved using a heuristic method. The performance of the heuristic algorithm and the amount of improvement obtained for different problem sizes is also presented. This algorithm has been implemented in our automated process planning system and can be applied easily to other areas of path planning optimization like fused deposition modeling and laser cutting.
Unravelling the Architecture of Duplications in Tumor Genomes

Tumor cells frequently exhibit large-scale changes in their genome, including genome rearrangements (e.g. chromosome inversions and translocations), duplications, and deletions. Such genomic changes are directly implicated in the pathogenesis of cancer and can alter gene structure and regulation. While many individual rearrangements and duplications in tumors have been identified, little is known about the detailed architecture of tumor genomes. A recently introduced technique called End Sequence Profiling (ESP) allows the identification of both rearrangements and duplications in tumor genomes at high resolution [5, 3]. In contrast, array-based techniques such as comparative genomic hybridization (CGH) are very useful in the identification of duplicated material in a tumor genome, but give little information about the organization and locations of duplicated material within the genome. For example, it is difficult to infer from CGH data whether two duplicated regions are located close together (or even on the same chromosome) in the tumor genome. In some tumors, duplicated material from several disparate regions of the human genome is co-localized [1, 6]. However, the precise architecture of these complex duplications and the mechanisms that explain their formation are not completely understood. We develop a computational method that allow us to unravel the architecture of complex duplications in a tumor genome using ESP data. The technique relies on a model of breakagefusion-bridge (BFB) cycles, a biological process that produces both rearrangements and duplications in tumor genomes. We apply our method to ESP data from the MCF7 breast tumor cell line. This work complements earlier analyses of genome rearrangements [3] and duplication by amplisome [4] using ESP data.
Integration Strategy Is a Key Step in Network-Based Analysis and Dramatically Affects Network Topological Properties and Inferring Outcomes

An increasing number of experiments have been designed to detect intracellular and intercellular molecular interactions. Based on these molecular interactions (especially protein interactions), molecular networks have been built for using in several typical applications, such as the discovery of new disease genes and the identification of drug targets and molecular complexes. Because the data are incomplete and a considerable number of false-positive interactions exist, protein interactions from different sources are commonly integrated in network analyses to build a stable molecular network. Although various types of integration strategies are being applied in current studies, the topological properties of the networks from these different integration strategies, especially typical applications based on these network integration strategies, have not been rigorously evaluated. In this paper, systematic analyses were performed to evaluate 11 frequently used methods using two types of integration strategies: empirical and machine learning methods. The topological properties of the networks of these different integration strategies were found to significantly differ. Moreover, these networks were found to dramatically affect the outcomes of typical applications, such as disease gene predictions, drug target detections, and molecular complex identifications. The analysis presented in this paper could provide an important basis for future network-based biological researches.
Joint localization of stationary and moving targets behind walls using sparse scene recovery

Abstract. We consider sparsity-driven joint localization of stationary and moving targets inside enclosed structures using a reduced set of spatial-fast time-slow time observations in ultra-wideband (UWB) pulsed radar platforms. We exploit the compact temporal support of the UWB signal to suppress the front wall clutter through time gating. The resulting enhancement in the signal-to-clutter ratio enables application of compressive sensing (CS) for scene reconstruction. We establish an appropriate signal model that permits formulation of linear modeling with sensing matrices so as to achieve efficient CS-based localization of stationary and moving targets in the downrange-crossrange-velocity space. We demonstrate the effectiveness of the proposed scheme using real data collected in a laboratory environment.