Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling and analysis of internet key exchange protocolv2 and a proposal for its variant

With the growing concerns on the information security and the capabilities of an attacker, Denial of Service (DoS) attacks have become one of the most serious and potent form of network security attacks. The attackers target the protocols to exhaust resources by either disabling the servers or disrupting the protocol exchange. In fact, almost all the communication protocols including TCP, HIP, etc. are vulnerable to resource exhaustion attacks. One of the ways of dealing with the DoS attacks is to carry out a cost analysis of the impact of the DoS attacks and ensure that the impact of the same is minimized to the extent possible. We illustrate the applicability of the same to analyze the Internet Key Exchange (IKE) version2 protocol. IKEv2 is one of the significant protocol of IPSec suite. It establishes the security association between source and destination before IPSec connection establishes. In this paper, we analyze IKEv2 protocol to show that IKE v2 is susceptible to DoS attacks. To the best of our knowledge, although IKE v1 has been analyzed for susceptibility to the DoS attacks, IKE v2 has not yet been. We also propose a new variant of IKE v2 protocol using model given by Stebila and et al. to ensure mitigation of DoS attacks in IKEv2.
Mammalian Casein Kinase 1α and Its Leishmanial Ortholog Regulate Stability of IFNAR1 and Type I Interferon Signaling

ABSTRACT Phosphorylation of the degron of the IFNAR1 chain of the type I interferon (IFN) receptor triggers ubiquitination and degradation of this receptor and, therefore, plays a crucial role in negative regulation of IFN-α/β signaling. Besides the IFN-stimulated and Jak activity-dependent pathways, a basal ligand-independent phosphorylation of IFNAR1 has been described and implicated in downregulating IFNAR1 in response to virus-induced endoplasmic reticulum (ER) stress. Here we report purification and characterization of casein kinase 1α (CK1α) as a bona fide major IFNAR1 kinase that confers basal turnover of IFNAR1 and cooperates with ER stress stimuli to mediate phosphorylation-dependent degradation of IFNAR1. Activity of CK1α was required for phosphorylation and downregulation of IFNAR1 in response to ER stress and viral infection. While many forms of CK1 were capable of phosphorylating IFNAR1 in vitro, human CK1α and L-CK1 produced by the protozoan Leishmania major were also capable of increasing IFNAR1 degron phosphorylation in cells. Expression of leishmania CK1 in mammalian cells stimulated the phosphorylation-dependent downregulation of IFNAR1 and attenuated its signaling. Infection of mammalian cells with L. major modestly decreased IFNAR1 levels and attenuated cellular responses to IFN-α in vitro. We propose a role for mammalian and parasite CK1 enzymes in regulating IFNAR1 stability and type I IFN signaling.
Association between coffee consumption and the estimated glomerular filtration rate in the general Japanese population: preliminary data regarding C-reactive protein concentrations

Abstract Background: Cardiometabolic disorders including cardiovascular disease (CVD) where the relevance of regular coffee consumption is debatable, has been linked with the development of chronic kidney disease (CKD). A more recent study suggests that coffee consumption is associated with normal or increased kidney function as assessed by the estimated glomerular filtration rate (eGFR). The present study investigated whether the association between coffee and the eGFR was independent of chronic inflammation, and whether adding sugar to coffee could affect the eGFR. Methods: A total of 114 age- and gender-matched Japanese individuals (females/males=68/46, mean age=59.5 years), without CVD and severe CKD, were studied. Clinical variables, such as body mass index, blood pressure, blood glucose, lipids and high-sensitivity C-reactive protein (hsCRP), in addition to eGFR [the Modification of Diet in Renal Disease (MDRD) study equation], were measured. Results: Coffee drinkers had higher eGFR values [73.9±16.5 (SD) mL/min/1.73 m2] than non-coffee drinkers (68.6±11.7). The difference remained significant (F=5.04, p=0.027), independently of clinical variables, including hsCRP. The eGFR values among coffee drinkers were similar between the subjects with and without use of sugar. Conclusions: The association of coffee drinking habits to eGFR may occur independently of inflammation as assessed by hsCRP. The use of sugar may have no effect on GFR. Further research is needed to clarify this phenomenon. Clin Chem Lab Med 2010;48:1773–6.
A Genomic Approach to Understanding Chronic Mountain Sickness

Chronic mountain sickness (CMS) is a disease that affects many high-altitude dwellers, particularly in the Andean Mountains in South America. The hallmark symptom of CMS is polycythemia, which causes increased risk of pulmonary hypertension and stroke (among other symptoms). A prevailing hypothesis in high-altitude medicine is that CMS results from a population-specific “maladaptation” to the hypoxic conditions at high altitude. In contrast, the prevalence of CMS is very low in other high-altitude populations (e.g., Tibetans and Ethiopians), which are seemingly well adapted to hypoxia. In recent years, concurrent with the advent of genomic technologies, several studies have investigated the genetic basis of adaptation to altitude. These studies have identified several candidate genes that may underlie the adaptation, or maladaptation. Interestingly, some of these genes are targeted by known drugs, raising the possibility of new treatments for CMS and other ischemic diseases. We review recent discoveries, alongside the methodologies used to obtain them, and outline some of the challenges remaining in the field. Roy Ronen, Dan Zhou, Vineet Bafna,* and Gabriel G. Haddad* Bioinformatics & Systems Biology Graduate Program, University of California San Diego, La Jolla, California; Department of Pediatrics, Division of Respiratory Medicine, University of California San Diego, La Jolla, California; Department of Computer Science and Engineering, University of California San Diego, La Jolla, California; Department of Neurosciences, University of California San Diego, La Jolla, California; and Rady Children’s Hospital, San Diego, California *V. Bafna and G. G. Haddad contributed equally to this work.
An attack tree-based approach for vulnerability assessment of communication-based train control systems

With the enhancement of informatization and automation, the capacity and efficiency of CBTC systems are increasing. However, the wide application of information technologies brings serious security threats on CBTC systems. Due to inherent characteristics of railway services, obtaining the security situation of CBTC systems is necessary. The methodlogy in this paper to evaluate the vulnerability of systems adopts attack tree modelling based on the functional architecture of CBTC systems. Assessments cover the current security states, port auditing, password policies and communication protocols of systems with the advantages of simplicity and operability. Based on the attack tree, leaf vulnerability, scenario vulnerability and system vulnerability are defined. During this assessment process, a typical scan tool, Nessus, and a vulnerability scoring system, CVSS, are used to achieve the port auditing. Moreover, a method to calculate the password strength and a piecewise linear function to normalize password strength are proposed. In the end, this approach is applied to a CBTC test-bed, and the assessment results show the difference of the vulnerability between the system with or without the improved countermeasures.
Health Services Utilization of a Care Coordination/Home‐Telehealth Program for Veterans With Diabetes: A Matched‐cohort Study

This study examined the effectiveness of a veterans affairs (VA) patient-centered care coordination/home-telehealth (CC/HT) program as an adjunct to treatment for veterans with diabetes. Using an adapted version of the Chronic Care Model, we analyzed the differences in healthcare service use between a cohort of 400 veterans with diabetes who were enrolled in a VA CC/HT program and a matched comparison cohort of 400 veterans with diabetes who received no CC/HT intervention. Propensity scores were used to improve the balance between the treatment and comparison groups. Service use outcomes were assessed at 12 months before and after enrollment. A difference-in-differences approach was used in the multivariate models to assess the treatment effect for patients in the CC/HT programs. Twelve months after enrollment, there was a significant difference between the treatment and comparison groups in terms of need-based primary care visits (newly scheduled visits that enable the veteran to be seen “just in time,” where the health status is monitored and met before health deteriorates), increasing in the treatment group and decreasing in the comparison group (P < .01). In a subgroup analysis, where we were able to control for the patients' Hb A1c values, we found that the treatment group had a lower likelihood of having 1 or more hospitalizations than patients in the comparison group. Our findings have implications for management in that the CC/HT program appears to improve the ability of older veterans with diabetes to receive appropriate, timely care, thereby improving the quality of care for them and making more efficient use of VA healthcare resources.
PaToPa: A Data-Driven Parameter and Topology Joint Estimation Framework in Distribution Grids

The increasing integration of distributed energy resources calls for new planning and operational tools. However, such tools depend on system topology and line parameters, which may be missing or inaccurate in distribution grids. With abundant data, one idea is to use linear regression to find line parameters, based on which topology can be identified. Unfortunately, the linear regression method is accurate only if there is no noise in both the input measurements (e.g., voltage magnitude and phase angle) and output measurements (e.g., active and reactive power). For topology estimation, even with a small error in measurements, the regression-based method is incapable of finding the topology using nonzero line parameters with a proper metric. To model input and output measurement errors simultaneously, we propose the error-in-variables model in a maximum-likelihood estimation framework for joint line parameter and topology estimation. While directly solving the problem is NP-hard, we successfully adapt the problem into a generalized low-rank approximation problem via variable transformation and noise decorrelation. For accurate topology estimation, we let it interact with parameter estimation in a fashion that is similar to expectation-maximization algorithm in machine learning. The proposed PaToPa approach does not require a radial network setting and works for mesh networks. We demonstrate the superior performance in accuracy for our method on IEEE test cases with actual feeder data from Southern California Edison.
Osteopontin adsorption to Gram-positive cells reduces adhesion forces and attachment to surfaces under flow

ABSTRACT The bovine milk protein osteopontin (OPN) may be an efficient means to prevent bacterial adhesion to dental tissues and control biofilm formation. This study sought to determine to what extent OPN impacts adhesion forces and surface attachment of different bacterial strains involved in dental caries or medical device–related infections. It further investigated if OPN’s effect on adhesion is caused by blocking the accessibility of glycoconjugates on bacterial surfaces. Bacterial adhesion was determined in a shear-controlled flow cell system in the presence of different concentrations of OPN, and interaction forces of single bacteria were quantified using single-cell force spectroscopy before and after OPN exposure. Moreover, the study investigated OPN’s effect on the accessibility of cell surface glycoconjugates through fluorescence lectin-binding analysis. OPN strongly affected bacterial adhesion in a dose-dependent manner for all investigated species (Actinomyces naeslundii, Actinomyces viscosus, Lactobacillus paracasei subsp. paracasei, Staphylococcus epidermidis, Streptococcus mitis, and Streptococcus oralis). Likewise, adhesion forces decreased after OPN treatment. No effect of OPN on the lectin-accessibility to glycoconjugates was found. OPN reduces the adhesion and adhesion force/energy of a variety of bacteria and has a potential therapeutic use for biofilm control. OPN acts upon bacterial adhesion without blocking cell surface glycoconjugates.
Role of Salmonella typhimurium Mn-superoxide dismutase (SodA) in protection against early killing by J774 macrophages

The Salmonella typhimurium gene for Mn-cofactored superoxide dismutase (sodA) was cloned by complementation of an Escherichia coli sodA sodB mutant for growth on minimal medium. Sequence analysis revealed an open reading frame of 618 bp encoding a polypeptide with 97% identity to E. coli SodA. A S. typhimurium sodA mutant was created by allelic exchange and tested for the ability to survive in the murine macrophage-like cell line J774. Growth of bacteria under iron-limiting conditions, inactivation of the Fur repressor, or expression of sodA from a plasmid resulted in increased resistance to early killing by J774 cells, which was abolished in the sodA mutant. These results suggest that resistance to the early oxygen-dependent microbicidal mechanisms of phagocytes involves the SodA gene product. The S. typhimurium sodA mutant was not significantly attenuated in mice, however, which suggests that resistance to early oxygen-dependent microbicidal mechanisms in vivo may play only a minor role in Salmonella pathogenesis.
Children’s Privacy in the Big Data Era: Research Opportunities

This article focuses on the privacy implications of advertising on social media, mobile apps, and games directed at children. Academic research on children’s privacy has primarily focused on the safety risks involved in sharing personal information on the Internet, leaving market forces (such as commercial data collection) as a less discussed aspect of children’s privacy. Yet, children’s privacy in the digital era cannot be fully understood without examining marketing practices, especially in the context of “big data. ” As children increasingly consume content on an ever-expanding variety of digital devices, media and advertising industries are creating new ways to track their behaviors and target them with personalized content and marketing messages based on individual profiles. The advent of the so-called Internet of Things, with its ubiquitous sensors, is expanding these data collection and profiling practices. These trends raise serious concerns about digital dossiers that could follow young people into adulthood, affecting their access to education, employment, health care, and financial services. Although US privacy law provides some safeguards for children younger than 13 years old online, adolescents are afforded no such protections. Moreover, scholarship on children and privacy continues to lag behind the changes taking place in global media, advertising, and technology. This article proposes collaboration among researchers from a range of fields that will enable cross-disciplinary studies addressing not only the developmental issues related to different age groups but also the design of digital media platforms and the strategies used to influence young people.
A mathematical model for strategic generation expansion planning

This paper proposes a mathematical model for strategic generation expansion planning problem. The model is developed based on the the simultaneous-move game between Gencos. Gencos investment decisions are passed to the dispatch center which decides about the production level in operating scenarios considered. Using Karush-Kuhn-Tucker conditions (KKTs) and disjunctive linearization, the model is formulated as a mixed-integer linear program (MILP). The concepts of worst Nash equilibrium (WNE) and best Nash equilibrium (BNE) are introduced to handle multiple NE problem. The impact of uncertainty (scenarios) on equilibria band, i.e., the difference between WNE and BNE is discussed. The developed model is simulated on illustrative 2-node and 3-node example systems and also on IEEE-RTS96 test system.
Effect of Feeding Diets Containing Treated Jatropha Seed Meal on Performance of Growing Rabbits

A study was assigned to assess the ameliorate the feeding value of jatropha seed meal by chemical or autoclave treatments and the feasibility of using in rabbit diets. Sixty weaned APRI rabbits, six weeks old with an average live body weight 707.26±4.54g were allotted randomly to five groups (twelve rabbits/treatment in 3 replicates). Five experimental diets were formulated where soybean meal protein of the basal diet (control) was replaced by chemically or autoclaved jatropha seed meal protein (CTJSM or ATJSM, respectively) of the rate of 15 or 30%. The growth trail continued lasted up to 14 week of age. There were final body weight and daily body weight gain with rabbits fed diets containing 15% CTJSM and 15% ATJSM diets close to rabbis fed control diets. The feed conversion ratio was significantly improved with 15% ATJSM and CTJSM diets compared with control. Digestion coefficients and nutritive values were insignificantly differed with tested diet contained 15% CTJSM compared to control. The control and tested groups resulted in the better dressing% compared to 30% CTJSM group. There were significantly increased in plasma ALT when replacing 15 or 30% ATJSM and 15% CTJSM, while plasma AST was significantly decreased when rabbit fed 15 % ATJSM compared to control. Economic efficiency and relative economic efficiency recorded the highest values with 15% CTJSM followed by 15% ATJSM, compared to control.Conclusively, It could be concluded soybean meal protein could be replaced by CTJSM and ATJSM protein at the level of 15%without an adverse in rabbits performance.
Multipath QoS routing with bandwidth guarantee

Recently, QoS routing has been studied intensively. In QoS routing, an essential issue is routing granularity. Most of the research adopts per-flow granularity in the forwarding table. Some research advocates per-source-destination pair granularity in the forwarding table with route pinning. The flow based approach has finer granularity, thus is more efficient in traffic engineering and resource utilization. However, the computation overhead and storage overhead are also higher. On the other hand, source-destination based granularity is more efficient on packet processing and forwarding, but has higher blocking probability. We propose the concept of forwarding with routing marks. With a limited number of routing marks, the proposed routing algorithm reduces the forwarding complexity and storage overhead significantly while yielding very competitive performance in terms of fractional reward loss.
Robot miners of the briny deep

For decades, futurists have predicted that commercial miners would one day tap the unimaginable mineral wealth of the world's ocean floor. Soon, that subsea gold rush could finally begin: The world's first deepsea mining robots are poised to rip into rich deposits of copper, gold, and silver 1,600 meters down at the bottom of the Bismarck Sea, near Papua New Guinea. The massive machines, which are to be tested later this year, are part of a high-stakes gamble for the Toronto-based mining company Nautilus Minerals.
Gene Extraction and Identification Tumor/Cancer for Microarray Data of Ovarian Cancer

A typical microarray data of ovarian cancer consists of the expressions of tens of thousands of genes on a genomic scale. To avoid higher computational complexity, we want to find the most likely differentially expressed gene that best explain the effects of tumor/cancer for ovarian cancer. In this paper, we derive a hybrid approach for extracting and evaluating informative genes from microarray data of ovarian cancer. Furthermore, the expression patterns of extracted genes are used to identify tumor/cancer for ovarian cancer. In the proposed approach, the method analysis of variance (ANOVA) will, using P-value, test gene expressions that are significantly different in microarray data. The genetic algorithm is applied to extract genes and then the support vector machine is processed to identify tumor/cancer for ovarian cancer. We show that this extracted set of genes can be used to significantly identify ovarian tumors (OVT) and ovarian cancers (OVCA)
A Test for Multimodality of Regression Derivatives with an Application to Nonparametric Growth Regressions

This paper presents a method to test for multimodality of an estimated kernel density of parameter estimates from a local-linear least-squares regression derivative. The procedure is laid out in seven simple steps and a suggestion for implementation is proposed. A Monte Carlo exercise is used to examine the finite sample properties of the test along with those from a calibrated version of it which corrects for the conservative nature of Silverman-type tests. The test is included in a study on nonparametric growth regressions. The results show that in the estimation of unconditional β-convergence, the distribution of the parameter estimates is multimodal with one mode in the negative region (primarily OECD economies) and possibly two modes in the positive region (primarily non-OECD economies) of the parameter estimates. The results for conditional β-convergence show that the density is predominantly negative and unimodal. Finally, the application attempts to determine why particular observations posess positive marginal effects on initial income in both the unconditional and conditional frameworks.
Modeling of cardiac electrical activity for characterizing vortex components

In this study, source model for solving biomagnetic inverse problem is developed with a new method, where vortex components along with the flow component of the equivalent source is considered. The model is an aggregation of a single current dipole and a magnetic dipole. The single current dipole denotes the flow component while the magnetic dipole is an abstract of the vortex component of the biomagnetic source. Simulation results indicate that this model could be more efficient for modeling cardiac electrical activity, compared with single current dipole. Despite that this model is more complicated than the single current dipole model; simple algorithm can still be used for solving inverse problem with only small revision. Meaning of the model parameters solved from the inverse problem is also discussed.
Dynamics of gas-liquid interfaces in turbulent flows over superhydrophobic surfaces

The present work studies superhydrophobic surfaces for turbulent drag reduction, focusing on the effect of finite surface tension for the interfaces between the overlying water flow and the pockets of gas attached to the surface. It has been previously reported (Seo et al. 2013a) that, once the interface is not assumed to be perfectly rigid, spanwise-coherent, upstream-traveling waves can develop, increasing the pressure fluctuations that the interfaces experience. Here we study the nature and scaling of those waves through direct numerical simulation and quasi-analytical modeling. The results suggest that the waves are not directly connected to the overlying turbulence or the lengthscale of the roughness protrusions, but to the capillary waves that develop from the normal modes of oscillation of the interface as a membrane.