Miracle-dz/UniFAR-FTUs huggingface dataset:
C-Peptide Activates AMPKα and Prevents ROS-Mediated Mitochondrial Fission and Endothelial Apoptosis in Diabetes

Vasculopathy is a major complication of diabetes; however, molecular mechanisms mediating the development of vasculopathy and potential strategies for prevention have not been identified. We have previously reported that C-peptide prevents diabetic vasculopathy by inhibiting reactive oxygen species (ROS)-mediated endothelial apoptosis. To gain further insight into ROS-dependent mechanism of diabetic vasculopathy and its prevention, we studied high glucose–induced cytosolic and mitochondrial ROS production and its effect on altered mitochondrial dynamics and apoptosis. For the therapeutic strategy, we investigated the vasoprotective mechanism of C-peptide against hyperglycemia-induced endothelial damage through the AMP-activated protein kinase α (AMPKα) pathway using human umbilical vein endothelial cells and aorta of diabetic mice. High glucose (33 mmol/L) increased intracellular ROS through a mechanism involving interregulation between cytosolic and mitochondrial ROS generation. C-peptide (1 nmol/L) activation of AMPKα inhibited high glucose–induced ROS generation, mitochondrial fission, mitochondrial membrane potential collapse, and endothelial cell apoptosis. Additionally, the AMPK activator 5-aminoimidazole-4-carboxamide 1-β-d-ribofuranoside and the antihyperglycemic drug metformin mimicked protective effects of C-peptide. C-peptide replacement therapy normalized hyperglycemia-induced AMPKα dephosphorylation, ROS generation, and mitochondrial disorganization in aorta of diabetic mice. These findings highlight a novel mechanism by which C-peptide activates AMPKα and protects against hyperglycemia-induced vasculopathy.
Training MLP Network Using Scatter Search as a Global Optimizer

An out-of-line safing and arming mechanism (10) includes an explosive chain (12) having one link (24) movably mounted on a slider (30) to be removed from the chain in a safing configuration and to be located in the chain in an arming configuration. A head (42) prevents the slider from moving into an arming position and is attached to the slider by an annular connecting system (44) which is stronger in tension and compression than it is in shear. The connecting section is broken by activation of an explosive charge (62) which is located within the connecting section and generates forces (66) tending to shear the connecting section as well as forces (64) tending to move the slider toward an arming position.
Conservation of Species- and Trait-Based Modeling Network Interactions in Extremely Acidic Microbial Community Assembly

Understanding microbial interactions is essential to decipher the mechanisms of community assembly and their effects on ecosystem functioning, however, the conservation of species- and trait-based network interactions along environmental gradient remains largely unknown. Here, by using the network-based analyses with three paralleled data sets derived from 16S rRNA gene pyrosequencing, functional microarray, and predicted metagenome, we test our hypothesis that the network interactions of traits are more conserved than those of taxonomic measures, with significantly lower variation of network characteristics along the environmental gradient in acid mine drainage. The results showed that although the overall network characteristics remained similar, the structural variation was significantly lower at trait levels. The higher conserved individual node topological properties at trait level rather than at species level indicated that the responses of diverse traits remained relatively consistent even though different species played key roles under different environmental conditions. Additionally, the randomization tests revealed that it could not reject the null hypothesis that species-based correlations were random, while the tests suggested that correlation patterns of traits were non-random. Furthermore, relationships between trait-based network characteristics and environmental properties implied that trait-based networks might be more useful in reflecting the variation of ecosystem function. Taken together, our results suggest that deterministic trait-based community assembly results in greater conservation of network interaction, which may ensure ecosystem function across environmental regimes, emphasizing the potential importance of measuring the complexity and conservation of network interaction in evaluating the ecosystem stability and functioning.
On Dominating Your Neighborhood Profitably

Recent research on skyline queries has attracted much interest in the database and data mining community. Given a database, an object belongs to the skyline if it cannot be dominated with respect to the given attributes by any other database object. Current methods have only considered so-called min/max attributes like price and quality which a user wants to minimize or maximize. However, objects can also have spatial attributes like x, y coordinates which can be used to represent relevant constraints on the query results. In this paper, we introduce novel skyline query types taking into account not only min/max attributes but also spatial attributes and the relationships between these different attribute types. Such queries support a micro-economic approach to decision making, considering not only the quality but also the cost of solutions. We investigate two alternative approaches for efficient query processing, a symmetrical one based on off-the-shelf index structures, and an asymmetrical one based on index structures with special purpose extensions. Our experimental evaluation using a real dataset and various synthetic datasets demonstrates that the new query types are indeed meaningful and the proposed algorithms are efficient and scalable.
Immunohistochemical Detection of Islet-1 and Neuronal Nitric Oxide Synthase in the Dorsal Root Ganglia (DRG) of Sheep Fetuses During Gestation

This study first investigated the ontogeny of Islet-1 and neuronal nitric oxide synthase (nNOS) expression and their co-localization in the DRG of sheep fetuses during gestation by immunohistochemistry (IHC). The results showed that Islet-1 and nNOS were located in the nuclei and cytoplasm of DRG neurons, respectively. The relative percentages of Islet-1-immunopositive (Islet-1+) neurons accounting for the total DRG neurons were 90%, 79%, 66%, and 53% at days 60, 90, and 120 of gestation and postnatally, respectively. The percentage of nNOS-immunopositive (nNOS+) neurons was 94% at day 60 and declined to ∼30% at day 90, with no obvious further change until the postnatal period. Dual IHC showed that ∼69% Islet-1+ neurons express nNOS at day 60 of gestation. This proportion declined to ∼24% at day 90, after which there was no significant change until birth. We also observed that most Islet-1+ and nNOS+ neurons belonged to small and medium-sized DRG neurons from day 90 of gestation to the postnatal period. These results suggest that both Islet-1 and nNOS are important for the differentiation and maintenance of some specific phenotypes of DRG neurons during late gestation of sheep fetuses, although the related mechanisms need to be further elucidated. (J Histochem Cytochem 52:797–803, 2004)
An Efficient Wait-Free Vector

The vector is a fundamental data structure, which provides constant-time access to a dynamically-resizable range of elements. Currently, there exist no wait-free vectors. The only non-blocking version supports only a subset of the sequential vector API and exhibits significant synchronization overhead caused by supporting opposing operations. Since many applications operate in phases of execution, wherein each phase only a subset of operations are used, this overhead is unnecessary for the majority of the application. To address the limitations of the non-blocking version, we present a new design that is wait-free, supports more of the operations provided by the sequential vector, and provides alternative implementations of key operations. These alternatives allow the developer to balance the performance and functionality of the vector as requirements change throughout execution. Compared to the known non-blocking version and the concurrent vector found in Intel's TBB library, our design outperforms or provides comparable performance in the majority of tested scenarios. Over all tested scenarios, the presented design performs an average of 4.97 times more operations per second than the non-blocking vector and 1.54 more than the TBB vector. In a scenario designed to simulate the filling of a vector, performance improvement increases to 13.38 and 1.16 times. This work presents the first ABA-free non-blocking vector. Unlike the other non-blocking approach, all operations are wait-free and bounds-checked and elements are stored contiguously in memory.
The Use of Kalman Filter in Biomedical Signal Processing

The Kalman Filter (KF) is a powerful tool in the analysis of the evolution of a dynamical model in time. The filter provides with a flexible manner to obtain recursive estimation of the parameters, which are optimal in the mean square error sense. The properties of KF along with the simplicity of the derived equations make it valuable in the analysis of signals. In this chapter an overview of the Kalman Filter, its properties and its applications is presented. More specifically, we focus on the application of Kalman Filter in the Electroencephalogram (EEG) processing, addressing extensions of Kalman Filter such as the Kalman Smoother (KS) in the time varying autoregressive (TVAR) model. The model can be written in a state – space form and the employment of KF provides with an estimation of the AR parameters which can be used for the estimation of the non – stationary signal. It is also demonstrated how these parameters can be used as input features of the signal in a clustering approach. The Kalman Filter is an estimator with interesting properties like optimality in the Minimum Mean Square Error (MMSE). After its discovery in 1960 (Kalman, 1960), this estimator has been used in many fields of engineering such as control theory, communication systems, speech processing, biomedical signal processing, etc. An analogous estimator has been proposed for the smoothing problem (Rauch et al., 1963), which includes three different types of smoothers, namely fixed-lag, fixed-point and fixed interval (Anderson & Moore, 1979; Brown, 1983). In this chapter we address the fixed interval smoother. The difference between the two estimators, the Kalman Filter and the Kalman Smoother, it is related on how they use the observations to perform estimation. The Kalman Filter uses only the past and the present observations to perform estimation, while the Kalman Smoother uses also the future observations for the estimation. This means that the Kalman Filter is used for on - line processing while the Kalman Smoother for batch processing. The derivations of these two estimators is presented in (Kay, 1993; Grewal & Andrews, 2001; Haykin, 2001). Both estimators are recursive in nature. This means that the estimate of the present state is updated using the previous state only and not the entire past states. The Kalman Filter is not only an estimator but also a learning method (Grewal & Andrews, 2001; Bishop, 2006). The observations are used to learn the states of the model. The Kalman Filter is also a computational tool and some problems may exist due to the finite precision arithmetic of the computers.
Perceived investment in employee development and taking charge

Purpose – The purpose of this paper is to investigate whether the relationship between perceived investment in employee development (PIED) and taking charge is moderated by perceived job autonomy. Design/methodology/approach – Self-report data were obtained from 737 employees. In addition, manager ratings of taking charge were obtained for 154 employees from their respective managers. Hierarchical moderated regression analyses were used to test the hypotheses. Findings – The results revealed a positive relationship between PIED and both self-reported and manager-rated taking charge only for employees who perceived high levels of job autonomy. Research limitations/implications – Given the cross-sectional nature of the data, no causal inferences can be drawn. Practical implications – Managers and organizations may benefit from providing work conditions that facilitate a felt obligation to reciprocate, but at the same time provide sufficient levels of perceived job autonomy to actually do so with respect to .
JVM Susceptibility to Memory Errors

Modern computer systems are becoming more powerful and are using larger memories. However, except for very high end systems, little attention is being paid to high availability. This is particularly true for transient memory errors, which typically cause the entire system to fail. We believe that this situation can be improved by addressing memory errors at all levels of the system, bring commodity systems closer to mainframe-class availability. In this paper, we use fault injection experiments to investigate memory error susceptibility at the highest level using a JVM and four Java benchmark applications. We then consider JVM data structure checksums to increase detection of silent data corruption affecting the JVM and applications. Our results indicate that the JVM's heap area has a higher memory error susceptibility than its static data area and that we can detect up to 39% of all memory errors in the JVM and application. We believe that such techniques will allow commodity systems to be made much more robust and less error-prone to transient errors.
KLF11-mediated Repression Antagonizes Sp1/Sterol-responsive Element-binding protein-induced Transcriptional Activation of Caveolin-1 in Response to Cholesterol Signaling*

Cholesterol is a potent regulator of gene expression via a canonical pathway co-regulated by SREBP and Sp1. Here we establish the caveolin-1 gene promoter as a cell type-specific model for SREBP/Sp1 regulation whereby lipoprotein cholesterol depletion activates caveolin-1 transcription in endothelial type cells, but not in fibroblasts, both in vitro and in vivo. By extending this model, we describe a novel pathway distinct from the prototypical SREBP/Sp1 regulatory loop involving the Sp1-like protein, KLF11. Through a combination of RNA interference, chromatin immunoprecipitation assays, electrophoretic mobility shift assays, and reporter assays, we demonstrate that in the presence of cholesterol, KLF11 acts as a dominant repressor of the caveolin-1 gene. Mechanistically, cholesterol depletion results in displacement of KLF11 from an Sp1 site flanking an SRE, indicating that activation by SREBP/Sp1 requires antagonism of KLF11 repression. The displacement of KLF11 results from both a down-regulation of its expression and competition by Sp1 for DNA binding. Therefore, these studies identify a novel pathway whereby KLF11 repression is coordinated with Sp1/SREBP activation of cholesterol-dependent gene expression in a cell type-specific manner and outline the mechanisms by which these functions are achieved.
Next-generation sequencing of paired tyrosine kinase inhibitor-sensitive and -resistant EGFR mutant lung cancer cell lines identifies spectrum of DNA changes associated with drug resistance

Somatic mutations in kinase genes are associated with sensitivity of solid tumors to kinase inhibitors, but patients with metastatic cancer eventually develop disease progression. In EGFR mutant lung cancer, modeling of acquired resistance (AR) with drug-sensitive cell lines has identified clinically relevant EGFR tyrosine kinase inhibitor (TKI) resistance mechanisms such as the second-site mutation, EGFR T790M, amplification of the gene encoding an alternative kinase, MET, and epithelial–mesenchymal transition (EMT). The full spectrum of DNA changes associated with AR remains unknown. We used next-generation sequencing to characterize mutational changes associated with four populations of EGFR mutant drug-sensitive and five matched drug-resistant cell lines. Comparing resistant cells with parental counterparts, 18–91 coding SNVs/indels were predicted to be acquired and 1–27 were lost; few SNVs/indels were shared across resistant lines. Comparison of two related parental lines revealed no unique coding SNVs/indels, suggesting that changes in the resistant lines were due to drug selection. Surprisingly, we observed more CNV changes across all resistant lines, and the line with EMT displayed significantly higher levels of CNV changes than the other lines with AR. These results demonstrate a framework for studying the evolution of AR and provide the first genome-wide spectrum of mutations associated with the development of cellular drug resistance in an oncogene-addicted cancer. Collectively, the data suggest that CNV changes may play a larger role than previously appreciated in the acquisition of drug resistance and highlight that resistance may be heterogeneous in the context of different tumor cell backgrounds.
Dynamic-KNN: A novel locating method in WLAN based on Angle of Arrival

Location estimation as one of the most popular research areas has been recently attended because of wide range of its applications. K Nearest Neighbor (KNN) is a basic deterministic algorithm for locating which is widely used in fingerprinting approach. The performance of the KNN can be improved extensively by employing appropriate selection algorithm. In this paper, a novel algorithm called Dynamic KNN (D-KNN) which uses Angle of Arrival (AOA) and KNN as a hybrid method is proposed. This method comparing with KNN algorithm with constant K, selects the best number of nearest neighbors dynamically. It utilizes the adaptive antenna system to determine the user locative area by intersection of several obtained AOA. The best K neighbors which are located in the determined area can be selected to employ in the KNN. Analysis and simulation results are reported the best overall performance of D-KNN in different conditions.
AUTOREGRESSIVE MODELING OF CODING SEQUENCE LENGTHS IN BACTERIAL GENOME

Previous investigation of the length of coding sequence lengths (CDS) in the bacterial circular chromosome revealed short range correlation in the series of these data. We have further analyzed the averaged periodograms of these series and we found that the organization of CDS can be well described by first-order autoregressive processes. This involves interaction between the neighboring terms. The autoregressive analysis may have great potential in modeling various physical and biological processes like light emission of galaxies, protein organization, cell flickering, cognitive processes and perhaps others.
Understanding the security management of global third-party Android marketplaces

As an open platform, Android enables the introduction of a variety of third-party marketplaces in which developers can provide mo- bile apps that are not provided in the official marketplace. Since the initial release of Android OS in 2008, many third-party app marketplaces have been launched all over the world. e diversity of which leads us to the following research question: are these third- party marketplaces securely managed? is work aims to answer this question through a large-scale empirical study. We collected more than 4.7 million Android apps from 27 third-party market- places, including ones that had not previously been studied in the research community, and analyzed them to study their security measures. Based on the results, we also a empt to quantify the security index of these marketplaces.
Structured Interview of Personality Organization (STIPO): Preliminary Psychometrics in a Clinical Sample

In this article, we describe the development and preliminary psychometric properties of the Structured Interview of Personality Organization (STIPO), a semistructured interview designed for the dimensional assessment of identity, primitive defenses, and reality testing, the three primary content domains in the model of personality health and disorder elaborated by Kernberg (1984; Kernberg & Caligor, 2005). Results of this investigation, conducted in a clinical sample representing a broad range of personality pathology, indicate that identity and primitive defenses as operationalized in the STIPO are internally consistent and that interrater reliability for all 3 content domains is adequate. Validity findings suggest that the assessment of one's sense of self and significant others (Identity) is predictive of measures of positive and negative affect, whereas the maladaptive ways in which the subject uses his or her objects for purposes of regulating one's self experience (Primitive Defenses) is predictive of measures of aggression and personality disorder traits associated with cluster B personality disorders. We discuss implications of these findings in terms of the theory-driven and trait-based assessment of personality pathology.
A Novel Matchmaking Approach for Automated Semantic Web Service Discovery

With the increasing number of available Web services, the need for a sophisticated discovery mechanism becomes essential. Existing UDDI based discovery techniques fail to recognize similarities and differences between Web service capabilities and thus greatly limit the scope of service discovery. Hence, in this paper we present a framework for discovering the vast amount of Web services present in Internet based on a novel semantic approach to automatically discover the most appropriate services to user requirements. Our framework is based on a natural language query to facilitate usage of our implemented discovery framework. For this purpose, we first apply some computational linguistics techniques such as part-of-speech tagging and word sense disambiguation to format and extract useful semantic information from user query. Then, we propose an innovative semantic matchmaking technique based on significant concepts properties in the referenced domain ontology. The proposed technique is implemented in a prototype system to evaluate our system performance and compare it to a related work. The results obtained demonstrate the effectiveness of our approach.
α4β2 Nicotinic Acetylcholine Receptors on Dopaminergic Neurons Mediate Nicotine Reward and Anxiety Relief

Nicotine is the primary psychoactive substance in tobacco, and it exerts its effects by interaction with various subtypes of nicotinic acetylcholine receptors (nAChRs) in the brain. One of the major subtypes expressed in brain, the α4β2-nAChR, endogenously modulates neuronal excitability and thereby, modifies certain normal as well as nicotine-induced behaviors. Although α4-containing nAChRs are widely expressed across the brain, a major focus has been on their roles within midbrain dopaminergic regions involved in drug addiction, mental illness, and movement control in humans. We developed a unique model system to examine the role of α4-nAChRs within dopaminergic neurons by a targeted genetic deletion of the α4 subunit from dopaminergic neurons in mice. The loss α4 mRNA and α4β2-nAChRs from dopaminergic neurons was confirmed, as well as selective loss of α4β2-nAChR function from dopaminergic but not GABAergic neurons. Two behaviors central to nicotine dependence, reward and anxiety relief, were examined. α4-nAChRs specifically on dopaminergic neurons were demonstrated to be necessary for nicotine reward as measured by nicotine place preference, but not for another drug of addiction, cocaine. α4-nAChRs are necessary for the anxiolytic effects of nicotine in the elevated plus maze, and elimination of α4β2-nAChRs specifically from dopaminergic neurons decreased sensitivity to the anxiolytic effects of nicotine. Deletion of α4-nAChRs specifically from dopaminergic neurons also increased sensitivity to nicotine-induced locomotor depression; however, nicotine-induced hypothermia was unaffected. This is the first work to develop a dopaminergic specific deletion of a nAChR subunit and examine resulting changes in nicotine-related behaviors.