Miracle-dz/UniFAR-FTUs huggingface dataset:
Bubble rise velocities and drag coefficients in non-Newtonian polysaccharide solutions.

Microbially produced polysaccharides have properties which are extremely useful in different applications. Polysaccharide producing fermentations start with liquid broths having Newtonian rheology and end as highly viscous non-Newtonian solutions. Since aerobic microorganisms are used to produce these polysaccharides, it is of great importance to know the mass transfer rate of oxygen from a rising air bubble to the liquid phase, where the microorganisms need the oxygen to grow. One of the most important parameters determining the oxygen transfer rate is the terminal rise velocity of air bubble. The dynamics of the rise of air bubbles in the aqueous solutions of different, mostly microbially produced polysaccharides was studied in this work. Solutions with a wide variety of polysaccharide concentrations and rheological properties were studied. The bubble sizes varied between 0.01 mm3 and 10 cm3. The terminal rise velocities as a function of air bubble volume were studied for 21 different polysaccharide solutions with different rheological properties. It was found that the terminal velocities reached a plateau at higher bubble volumes, and the value of the plateau was nearly constant, between 23 and 27 cm/s, for all solutions studied. The data were analyzed to produce the functional relationship between the drag coefficient and Reynolds number (drag curves). It was found out that all the experimental data obtained from 21 polysaccharide solutions (431 experimental points), can be represented by a new single drag curve. At low values of Reynolds numbers, below 1.0, this curve could be described by the modofoed Hadamard-Rybczynski model, while at Re > 60 the drag coefficient was a constant, equal to 0.95. The latter finding is similar to that observed for bubble rise in Newtonian liquids which was explained on the basis of the "solid bubble" approach.
The Design and Implementation of A Network Provenance System Framework

Network forensic analysis and fault diagnosis are becoming increasingly important in network management and network security domain. This requires network management system has the ability to query network metadata, i.e. the network provenance functionality. For instance, network provenance can be used in tracking the path of dataflow through the network to obtain the source of message data. This paper presents the design and implementation of a network provenance system (NPS) framework, the framework is used to support the full range of functionality required for enabling forensics in distributed systems. We adopt the declarative networking coding method proposed in the networking domain to maintain and query distributed network provenance. The framework prototype is developed using Rapidnet, a declarative networking platform based on the ns-3 network simulator. Simulation experiments are conducted in simulated network, the experiment results indicates that our network provenance system could support provenance process in a large-scale distributed network and significantly reduce bandwidth cost compared to traditional approach.
Chemotherapeutic Agents Redox-Dependent Activation of Nrf 2 by Cancer Driven Reporter Gene Cell Line and Its Use to Show − Generation of a Stable Antioxidant Response Element

The NF-E2 p45-related factor 2 (Nrf2) regulates cytoprotective genes that contain an antioxidant response element (ARE) in their promoters. To investigate whether anticancer drugs can induce ARE-driven gene expression, we have developed a stable human mammary MCF7-derived reporter cell line called AREc32, which contains a luciferase gene construct controlled by eight copies of the cis-element. In these cells, luciferase activity was increased up to 50-fold following treatment with 50 Mmol/L tert-butylhydroquinone (t-BHQ). Basal and inducible luciferase activities in AREc32 cells were increased by forced overexpression of Nrf2 and reduced by knockdown of endogenous Nrf2 expression with RNA interference. Depletion of cellular reduced glutathione (GSH) by treatment of AREc32 cells with L-buthionine-S,R-sulfoximine (BSO) did not influence basal levels of luciferase activity, but pretreatment with BSO augmented induction of luciferase activity by t-BHQ. Induction of reporter activity by t-BHQ in AREc32 cells was suppressed markedly by the antioxidants N-acetylcysteine and GSH but only modestly by vitamins C or E, suggesting that ARE-luciferase expression is induced primarily by thiol-active electrophiles rather than free radicals. The anticancer drugs cisplatin, etoposide, mitoxantrone, chlorambucil, melphalan, and carmustine [1,3-bis (2-chloroethyl)-1-nitrosourea (BCNU)] weakly induced luciferase activity in AREc32 cells. Moreover, treatment of AREc32 cells with BSO immediately before exposure to anticancer drugs enhanced induction of ARE-driven luciferase activity by cisplatin, BCNU, chlorambucil, and melphalan and also induced endogenous AKR1C (AKR1C refers to AKR1C1 and AKR1C2), a target gene of Nrf2. Our findings show that Nrf2 can be activated by certain anticancer agents, and this will influence the effectiveness of chemotherapy. (Cancer Res 2006; 66(22): 10983-94)
Entropy-Based Characterization of Internet Background Radiation

Network security requires real-time monitoring of network traffic in order to detect new and unexpected attacks. Attack detection methods based on deep packet inspection are time consuming and costly, due to their high computational demands. This paper proposes a fast, lightweight method to distinguish different attack types observed in an IP darkspace monitor. The method is based on entropy measures of traffic-flow features and machine learning techniques. The explored data belongs to a portion of the Internet background radiation from a large IP darkspace, i.e., real traffic captures that exclusively contain unsolicited traffic, ongoing attacks, attack preparation activities and attack aftermaths. Results from an in-depth traffic analysis based on packet headers and content are used as a reference to label data and to evaluate the quality of the entropy-based classification. Full IP darkspace traffic captures from a three-week observation period in April, 2012, are used to compare the entropy-based classification with the in-depth traffic analysis. Results show that several traffic types present a high correlation to the respective traffic-flow entropy signals and can even fit polynomial regression models. Therefore, sudden changes in traffic types caused by new attacks or attack preparation activities can be identified based on entropy variations.
Hybrid system simulation of computer control applications over communication networks

Discrete event-driven simulations of digital communication networks have been used widely. However, it is difficult to use a network simulator to simulate a hybrid system in which some objects are not discrete event-driven but are continuous time-driven. A networked control system (NCS) is such an application, in which physical process dynamics are continuous by nature. We have designed and implemented a hybrid simulation environment which effectively integrates models of continuous-time plant processes and discrete-event communication networks by extending the open source network simulator NS-2. To do this a synchronisation mechanism was developed to connect a continuous plant simulation with a discrete network simulation. Furthermore, for evaluating co-design approaches in an NCS environment, a piggybacking method was adopted to allow the control period to be adjusted during simulations. The effectiveness of the technique is demonstrated through case studies which simulate a networked control scenario in which the communication and control system properties are defined explicitly.
Declining β-Cell Function Relative to Insulin Sensitivity With Increasing Fasting Glucose Levels in the Nondiabetic Range in Children

OBJECTIVE In adults, higher fasting plasma glucose (FPG) levels, even within the normoglycemic range, are associated with increased diabetes risk. This investigation tested the hypothesis that β-cell function relative to insulin sensitivity decreases with increasing FPG in youth. RESEARCH DESIGN AND METHODS A total of 223 youth with FPG <126 mg/dl underwent evaluation of first- and second-phase insulin secretion during a 2-h hyperglycemic (∼225 mg/dl) clamp, insulin sensitivity during a 3-h hyperinsulinemic-euglycemic clamp, body composition, and abdominal adiposity with dual-energy X-ray absorptiometry and computed tomographic scan. β-Cell function relative to insulin sensitivity was calculated as the product of first-phase insulin and insulin sensitivity, i.e., glucose disposition index (GDI). The subjects were divided into three FPG categories: ≤90, >90–<100, and ≥100–<126 mg/dl. RESULTS GDI decreased significantly across the three categories as FPG increased (1,086 ± 192 vs. 814 ± 67 and 454 ± 57 mg/kg/min, P = 0.002). This decline remained significant after adjustment for race, sex, BMI, and percent body fat or visceral fat. Within each FPG category, GDI declined with increasing BMI percentiles. CONCLUSIONS The impairment in β-cell function relative to insulin sensitivity is apparent even within the nondiabetic FPG range in children. At the current cutoff of 100 mg/dl for impaired fasting glucose (IFG), there is an ∼49% decline in the GDI independent of obesity and race. This observation may reflect a heightened risk of β-cell dysfunction and progression to diabetes in these children. Considering the near doubling of IFG prevalence among youth between National Health and Nutrition Examination Survey 1999–2000 and 2005–2006, our findings have important public health implications.
Engaged Teaching-Learning: Outcome Evaluation for Social Work Students in a Graduate-Level Service Learning Research Course

The challenges of engaging social work students in the research curriculum are well-documented, and the literature supports the use of service learning to increase engagement. This study explores self-efficacy as one measure of learning outcomes. Changes in students’ (N=88) assessment of their ability to perform research and program evaluation tasks skillfully were measured by administering the Evaluation Self-Efficacy Scale (ESE) on the first and last days of a graduate-level advanced research class that included a service learning project. ESE scores on the last day of class were significantly higher than on the first day of class. The effect size was larger than in prior similar studies, suggesting that service learning contributed to students’ sense of mastery of course content. These results support the use of an engaged-learning model such as a service learning project in advanced social work research courses to improve students’ evaluation self-efficacy.
Brain Radiation Doses to Patients in an Interventional Neuroradiology Laboratory

BACKGROUND AND PURPOSE: In 2011, the International Commission on Radiologic Protection established an absorbed-dose threshold to the brain of 0.5 Gy as likely to produce cerebrovascular disease. In this paper, the authors investigated the brain doses delivered to patients during clinical neuroradiology procedures in a university hospital. MATERIALS AND METHODS: The radiation dose delivered to the brain was investigated in 99 diagnostic and therapeutic interventional neuroradiology procedures. Brain doses were calculated in a mathematic model of an adult standard anthropomorphic phantom by using the technical and radiation dose data of an x-ray biplane system submitted to regular quality controls and calibration programs. RESULTS: For cerebral embolizations, brain doses resulted in a maximum value of 1.7 Gy, with an average value of 500 mGy. Median and third quartile resulted in 400 and 856 mGy, respectively. For cerebral angiography, the average dose in the brain was 100 mGy. CONCLUSIONS: This work supports the International Commission on Radiologic Protection recommendation on enhancing optimization when doses to the brain could be higher than 0.5 Gy. Radiation doses should be recorded for all patients and kept as low as reasonably achievable. For pediatric patients and young adults, an individual evaluation of brain doses could be appropriate.
Revisiting the fair queuing paradigm for end-to-end congestion control

Today, the dominant paradigm for congestion control in the Internet is based on the notion of TCP friendliness. To be TCP-friendly, a source must behave in such a way as to achieve a bandwidth that is similar to the bandwidth obtained by a TCP flow that would observe the same round-trip time (RTT) and the same loss rate. However, with the success of the Internet comes the deployment of an increasing number of applications that do not use TCP as a transport protocol. These applications can often improve their own performance by not being TCP-friendly, which severely penalizes TCP flows. To design new applications to be TCP-friendly is often a difficult task. The idea of the fair queuing (FQ) paradigm as a means to improve congestion control was first introduced by Keshav (1991). While Keshav made a fundamental step toward a new paradigm for the design of congestion control protocols, he did not formalize his results so that his findings could be extended for the design of new congestion control protocols. We make this step and formally define the FQ paradigm as a paradigm for the design of new end-to-end congestion control protocols. This paradigm relies on FQ scheduling with per-flow scheduling and longest queue drop buffer management in each router. We assume only selfish and noncollaborative end users. Our main contribution is the formal statement of the congestion control problem as a whole, which enables us to demonstrate the validity of the FQ paradigm. We also demonstrate that the FQ paradigm does not adversely impact the throughput of TCP flows and explain how to apply the FQ paradigm for the design of new congestion control protocols. As a pragmatic validation of the FQ paradigm, we discuss a new multicast congestion control protocol called packet pair receiver-driven layered multicast (PLM).
ATR1, a Saccharomyces cerevisiae gene encoding a transmembrane protein required for aminotriazole resistance

In Saccharomyces cerevisiae, 3-amino-1,2,4-triazole (aminotriazole) competitively inhibits the activity of imidazoleglycerolphosphate dehydratase, the product of the HIS3 gene. Wild-type strains are able to grow in the presence of 10 mM aminotriazole because they induce the level of imidazoleglycerolphosphate dehydratase. However, strains containing gcn4 mutations are unable to grow in medium containing aminotriazole because they lack the GCN4 transcriptional activator protein necessary for the coordinate induction of HIS3 and other amino acid biosynthetic genes. Here, we isolated a new gene, designated ATR1, which when present in multiple copies per cell allowed gcn4 mutant strains to grow in the presence of aminotriazole. In wild-type strains, multiple copies of ATR1 permitted growth at extremely high concentrations of aminotriazole (80 mM), whereas a chromosomal deletion of ATR1 caused growth inhibition at very low concentrations (5 mM). When radioactive aminotriazole was added exogenously, cells with multiple copies of ATR1 accumulated less aminotriazole than wild-type cells, whereas cells with the atr1 deletion mutation retained more aminotriazole. Unlike the mammalian mdr or yeast PDR genes that confer resistance to many drugs, ATR1 appears to confer resistance only to aminotriazole. Genetic analysis, mRNA mapping, and DNA sequencing revealed that (i) the primary translation product of ATR1 contains 547 amino acids, (ii) ATR1 transcription is induced by aminotriazole, and (iii) the ATR1 promoter region contains a binding site for the GCN4 activator protein. The deduced amino acid sequence suggests that ATR1 protein is very hydrophobic with many membrane-spanning regions, has several potential glycosylation sites, and may contain an ATP-binding site. We suggest that ATR1 encodes a membrane-associated component of the machinery responsible for pumping aminotriazole (and possibly other toxic compounds) out of the cell.
Throughput and energy performance of TCP on a wideband CDMA air interface

In this paper, we present a study on the performance of TCP, in terms of both throughput and energy consumption, in the presence of a wideband CDMA radio interface typical of third generation wireless systems. The results show that the relationship between throughput and average error rate is largely independent of the network load, making it possible to introduce a universal throughput curve, empirically characterized, which gives throughput predictions for each value of the user error probability. Furthermore, the study of the energy efficiency shows the possibility to select an optimal power control threshold to maximize the trade-off between throughput and energy, thereby potentially achieving very significant energy gains. Copyright © 2001 John Wiley & Sons, Ltd.
Overexpression of KIAA0101 Predicts High Stage, Early Tumor Recurrence, and Poor Prognosis of Hepatocellular Carcinoma

Purpose: KIAA0101 is a proliferating cell nuclear antigen–associated factor and involved in cell proliferation. This study is to elucidate its role in the progression, early tumor recurrence (ETR), and prognosis of hepatocellular carcinoma (HCC). Experimental Design: KIAA0101 mRNA was measured by reverse transcription-PCR in 216 resected, unifocal, primary HCCs and its protein in 164 cases by immunohistochemistry. Results: KIAA0101 mRNA was overexpressed in 131 (61%) HCCs, and protein was detected in 105 (64%). KIAA0101 mRNA overexpression correlated with higher tumor grade (P = 0.0001), higher tumor stage with vascular invasion and various extents of intrahepatic spread (P = 1 × 10−8), ETR (P = 1.8 × 10−6), and lower 5-year survival (P = 0.0026). Multivariate analysis confirmed that KIAA0101 overexpression was an independent risk factor associated with high-grade tumor (P = 0.0001), high-stage tumor (P < 0.0001), and ETR (P = 0.0052) and thus contributed to poor prognosis. KIAA0101 protein–positive tumor cells accumulated at the borders of tumor macrotrabeculae and were more abundant in tumor thrombi than in the main tumors. Hence, KIAA0101 may contribute to growth advantage and resistance to hypoxic insult. In this series, p53 mutation was detected in 93 of 184 (51%) HCCs. In both p53-mutated and non–p53-mutated HCCs, KIAA0101 overexpression correlated with higher vascular invasion (stages IIIA to IV; all Ps < 0.0001) and, accordingly, led to lower 5-year survival rates (P = 0.011 and 0.029, respectively). Conclusion: KIAA0101 correlates with enhanced metastatic potential and is a significant prognostic factor of HCC.
Plasma Membrane Ganglioside Sialidase Regulates Axonal Growth and Regeneration in Hippocampal Neurons in Culture

It has been long recognized that the ganglioside GM1 plays a role in axonal growth and neuronal differentiation. However, the involvement of plasma membrane GM1 has been difficult to elucidate. This is possible now thanks to the recent cloning of plasma membrane ganglioside sialidase (PMGS), the enzyme responsible for the localized hydrolysis of oligosialogangliosides into GM1. In this work we show that PMGS mRNA and protein levels are high at early developmental stages of the hippocampus and low in adulthood both in vivo and in vitro. We also demonstrate that inhibition of PMGS activity blocks axonal elongation, whereas the increase in PMGS activity dramatically enhances axon growth and accelerates the polarization of cytoskeletal proteins. Finally, we show that axotomy close to the cell body in PMGS overexpressing neurons results in the regrowth of the original axon instead of randomly, as is the case in control neurons. In all, these results imply that PMGS activity through the modulation of GM1 surface levels is an important component of the machinery controlling axonal growth. We hypothesize that increasing PMGS activity in the adult nervous system may be useful to improve regeneration after nerve damage.
Automatic derivation of curved human walking trajectories from synthetic vision

The scope of this paper is to propose a system for the automatic derivation of a human curved walking trajectory from the analysis provided by its synthetic vision module. The study context is a planar environment with still and sparse foothold locations. A general methodology associates the two low-level modules of vision and walking with a planification module which establishes the middle term path from the knowledge of the visualized environment. The planification is made under the constraint of minimizing the distance, the speed variation and the curvature cost. Moreover, the planification may trigger the alternate walking motion whenever the decreasing in curvature cost is higher than the associated increasing in speed variation cost due to the corresponding halt and restart. Finally, the characteristic of the next step location is derived in the context of a constant velocity walking motion along a circular trajectory. <<ETX>>
Structure-Based Analysis Reveals Cancer Missense Mutations Target Protein Interaction Interfaces

Recently it has been shown that cancer mutations selectively target protein-protein interactions. We hypothesized that mutations affecting distinct protein interactions involving established cancer genes could contribute to tumor heterogeneity, and that novel mechanistic insights might be gained into tumorigenesis by investigating protein interactions under positive selection in cancer. To identify protein interactions under positive selection in cancer, we mapped over 1.2 million nonsynonymous somatic cancer mutations onto 4,896 experimentally determined protein structures and analyzed their spatial distribution. In total, 20% of mutations on the surface of known cancer genes perturbed protein-protein interactions (PPIs), and this enrichment for PPI interfaces was observed for both tumor suppressors (Odds Ratio 1.28, P-value < 10−4) and oncogenes (Odds Ratio 1.17, P-value < 10−3). To study this further, we constructed a bipartite network representing structurally resolved PPIs from all available human complexes in the Protein Data Bank (2,864 proteins, 3,072 PPIs). Analysis of frequently mutated cancer genes within this network revealed that tumor-suppressors, but not oncogenes, are significantly enriched with functional mutations in homo-oligomerization regions (Odds Ratio 3.68, P-Value < 10−8). We present two important examples, TP53 and beta-2-microglobulin, for which the patterns of somatic mutations at interfaces provide insights into specifically perturbed biological circuits. In patients with TP53 mutations, patient survival correlated with the specific interactions that were perturbed. Moreover, we investigated mutations at the interface of protein-nucleotide interactions and observed an unexpected number of missense mutations but not silent mutations occurring within DNA and RNA binding sites. Finally, we provide a resource of 3,072 PPI interfaces ranked according to their mutation rates. Analysis of this list highlights 282 novel candidate cancer genes that encode proteins participating in interactions that are perturbed recurrently across tumors. In summary, mutation of specific protein interactions is an important contributor to tumor heterogeneity and may have important implications for clinical outcomes.