Miracle-dz/UniFAR-FTUs huggingface dataset:
Atomistic Models of General Anesthetics for Use in in Silico Biological Studies

While small molecules have been used to induce anesthesia in a clinical setting for well over a century, a detailed understanding of the molecular mechanism remains elusive. In this study, we utilize ab initio calculations to develop a novel set of CHARMM-compatible parameters for the ubiquitous modern anesthetics desflurane, isoflurane, sevoflurane, and propofol for use in molecular dynamics (MD) simulations. The parameters generated were rigorously tested against known experimental physicochemical properties including dipole moment, density, enthalpy of vaporization, and free energy of solvation. In all cases, the anesthetic parameters were able to reproduce experimental measurements, signifying the robustness and accuracy of the atomistic models developed. The models were then used to study the interaction of anesthetics with the membrane. Calculation of the potential of mean force for inserting the molecules into a POPC bilayer revealed a distinct energetic minimum of 4–5 kcal/mol relative to aqueous solution at the level of the glycerol backbone in the membrane. The location of this minimum within the membrane suggests that anesthetics partition to the membrane prior to binding their ion channel targets, giving context to the Meyer–Overton correlation. Moreover, MD simulations of these drugs in the membrane give rise to computed membrane structural parameters, including atomic distribution, deuterium order parameters, dipole potential, and lateral stress profile, that indicate partitioning of anesthetics into the membrane at the concentration range studied here, which does not appear to perturb the structural integrity of the lipid bilayer. These results signify that an indirect, membrane-mediated mechanism of channel modulation is unlikely.
Income inequality and redistribution: the role of tax evasion

Using a simple model of income redistribution, we examine the effect of income inequality on redistribution in the presence of tax evasion. Our results suggest that in the presence of tax evasion, higher income inequality may be associated with lower per capita transfers but inefficiently high taxation. This is because in countries characterized by weak institutional framework parties may increase the probability of winning the elections by choosing policies that expand the number of tax evading individuals.
Whole-Genome Sequence of the Cheese Isolate Lactobacillus rennini ACA-DC 565

ABSTRACT In this study, we present the first complete genome sequence of Lactobacillus rennini ACA-DC 565, a strain isolated from a traditional Greek overripened Kopanisti cheese called Mana. Although the species has been associated with cheese spoilage, the strain ACA-DC 565 may contribute to the intense organoleptic characteristics of Mana cheese.
Clustering Based on Task Dependency for Data-Intensive Workflow Scheduling Optimization

Scientists in each experiment team share their data and use distributed resources for conducting their experiments. These experiments are being accompanied in collaboration with teams that are globally dispersed. Scientific data need to be replicated or cached at distributed locations around the world. Data locality problem and transferred data overhead are important challenges for scheduling such data-intensive scientific workflow application in cloud computing. These applications are leading to the era of big data and task execution involves consuming and producing huge amount of input/output data with data dependencies among tasks. Scheduling and execution overhead are high when low performance of fine-grained tasks is a common problem in widely distributed platforms. Clustering Method based Task Dependency (CMTD) to reduce execution overhead and to improve the computational granularity of scientific workflow tasks is presented in this paper. And this paper proposes the data-intensive workflow scheduling system to minimize makespan of the data-intensive workflow applications, which can be modeled as a directed acyclic graph. Clustering method is validated by using simulation based analysis though WorkflowSim.
Electroencephalogram as a mechanism for human communication

This paper investigates a method to evaluate the potential of electroencephalogram (EEG) as a method of human communication. Nineteen sets of simulated EEG data were compared using the set of prediction filter coefficients. This method shows that we can precisely identify similar patterns between two simulated data set of subjects who are thinking of the same thought in a given time. Our approach shows that we can find the exact frequency component from the data which we attribute to thinking the same things. This result suggest that the methods used in this simulation may be applicable in the analysis of actual EEG data when two people are trying to communicate with each other or having the same thoughts.
Study of BitTorrent based Video on Demand Systems

BitTorrent (BT) is one of the most successful and effective mechanisms for distributing large volumes of content over the Internet. One of the primary reasons behind its success is its robustness to 'free-riding', in which peers manage to get a good download rate in spite of not uploading the content to others. It works well even in flash-crowd scenarios. In fact, more the crowd better is its performance. Although BT was primarily designed for distributing time-insensitive content, in this paper we study the modifications that could be performed in BT algorithms to support streaming. Video-on-demand (VoD) has become an immensely popular Internet service in recent years. But due to its high bandwidth requirements and popularity, it is also a costly service to provide. In this paper we consider the design and potential benefits of using BT for video streaming. Various BT-like video streaming systems have been reviewed and suggestions have been made for improving their performance.
Dual-Thread Speculation: Two Threads in the Machine are Worth Eight in the Bush

As chip multiprocessors with simultaneous multithreaded cores are becoming commonplace, there is a need for simple approaches to exploit thread-level parallelism. In this paper, we consider thread-level speculation as a means to reap thread-level parallelism out of application binaries. We first investigate the tradeoffs between scheduling speculative threads on the same core and on different cores. While threads contend for the same resources using the former approach, the latter approach is plagued by the overhead for inter-core communication. Despite the impact of resource contention, our detailed simulations show that the first approach provides the best performance due to lower inter-thread communication cost. The key contribution of the paper is the proposed design and evaluation of the dual-thread speculation system. This design point has very low complexity and reaps most of the gains of a system supporting eight threads
The Impact of No Child Left Behind on Non-cognitive Skills

Smolensky, and seminar participants at the Goldman School of Public Policy, the Institute for the Study of Societal Issues, and APPAM's 2014 conference " The Decline of the Middle Class? " for their helpful comments. All errors are my own. Abstract Beginning in 2002, the No Child Left Behind Act (NCLB) mandated the monitoring of student performance and rewarded or sanctioned schools based on students' standardized " high-stakes " test scores. Non-cognitive skills, such as self-control, have been identified as key determinants of adult success in the labor market. Students' growth in non-cognitive skills are not well captured by standardized tests of literacy and numeracy. Consequently, this crucial dimension of child development may be neglected due to NCLB's focus on cognitive testing outcomes. I use the Early Childhood Longitudinal Study of Kindergarten, a panel data set of children attending kindergarten in 1998 that spans the onset of NCLB, in order to analyze the impact of the federal mandate on non-cognitive skills. In a departure from most of the prior economic and policy research on non-cognitive dimensions, this paper focuses on the growth of underlying non-cognitive skills (or " traits ") rather than aberrant behaviors like truancy. I find little impact of NCLB on nine dimensions of non-cognitive growth for students overall. However, these precise null effects at the national level mask distinct heterogeneity across student subgroups and domains of behavior-classroom skills improved for African-American and Hispanic students but worsened for white and Asian students. Parents reported declines in home traits across most demographic subgroups.
Incremental reachability checking of KernelC programs using matching logic

A fundamental phase in software development deals with verifying that software behaves correctly. Although accurate testing can discover many wrong behaviours, formal software verification techniques can help in developing applications that dependably satisfy their requirements. However, since formal verification techniques are time consuming and software changes continuously, incremental verification methods, i.e., methods which reuse the results of the verification of a previous version when verifying a new version of a program, are very useful, since they can significantly reduce the time required to perform the verification. In this work I apply a syntactic-semantic incremental approach to reachability checking of KernelC programs using matching logic. KernelC is a significant, non-trivial subset of the C programming language. Matching logic is a language-independent proof system to reason about programs in any language that has a rewrite-based operational semantics. Incrementality is achieved by encoding the verification procedure in a syntax-driven fashion based on semantic attributes defined on top of an operator-precedence grammar.
The Work-Averse Attacker Model

In this paper we present and validate a novel attacker model based on the economic notion that the attacker has limited resources to forge a new attack. We focus on the vulnerability exploitation case, whereby the attacker has to choose whether to exploit a new vulnerability or keep an old one. We postulate that most vulnerabilities remain unattacked, and that the exploit development cycle relates to software updates rather than to the disclosure of new vulnerabilities. We develop a simple mathematical model to show the mechanisms underlying our observations and name it “The Work-Averse Attacker Model”. We then leverage Symantec’s data sharing platform WINE to validate our model by analysing records of attacks against more than 1M real systems. We ﬁnd the ‘Model of the Work-Averse Attacker’ to be strongly supported by the data and, in particular, that: (a) the great majority of attacks per software version is driven by one vulnerability only; (b) an exploit lives two years before being substituted by a new one; (c) the exploit arrival rate depends on the software’s update rate rather than on time or knowledge of the vulnerability.
MADIT II (second Multicenter Automated Defibrillator Implantation Trial) debate: risk stratification, costs, and public policy.

After extensive deliberation, on June 6, 2003, the Centers for Medicare and Medicaid Services (CMS) reached a long-awaited decision on coverage of implantable cardioverter defibrillators (ICDs) for patients meeting the clinical profile of the second Multicenter Automated Defibrillator Implantation Trial (MADIT II). 1 CMS offered a split decision, extending coverage only to Medicare patients meeting the MADIT II inclusion and exclusion criteria and having a QRS duration >120 ms. Information on and a timeline of the CMS coverage determination process are publicly available at their World Wide Web site,2 which has a link to a detailed decision memorandum.3 Although versions of the “MADIT II debate” have already taken place in many forums, we believe several issues regarding both the trial and the CMS decision require further discussion. We will focus on the intertwined issues of risk stratification and cost that have arisen repeatedly in this debate. The MADIT II debate boils down to the question posed by Dr Alfred Buxton in a recent editorial4: Should all patients with an ejection fraction <30% because of coronary artery disease receive ICDs, regardless of other risk-stratifying tests? Dr Buxton suggested the answer to this question should be “no”: “I believe it is premature to recommend ICDs on the basis of only one trial that may not be generalizable to all patients. ”4 Dr Buxton’s remarks and the CMS decision stand in contrast to the otherwise unimpeded march the MADIT II results have made toward clinical acceptance. After publication of MADIT II, the Food and Drug Administration quickly approved the Guidant ICD used in the trial for this new indication, and updated American Heart Association/American College of Cardiology/North American Society of Pacing and Electrophysiology (AHA/ACC/NASPE) consensus guidelines5 recommended the trial’s inclusion/exclusion criteria as a class IIa indication for ICD …
Augmenting brain function with meditation: can detachment coincide with empathy?

These findings showed that different meditations are associated with distinct neural activity during sustained attention and processing emotions. Hence, meditation causes changes in parts of the brain and modifies brain activity, in distinct ways based on the meditation technique. To our knowledge no study has checked whether detachment and empathy can co-exist as a result of meditation; and the pathway has not been determined. The dorsal MPFC showed increased activation associated with mental activity during introspection (Gusnard et al., 2001), which is believed to lead to detachment (Raichle et al., 2001). The ventral MPFC has been associated with cognitive empathy (Shamay-Tsoory, 2011). The ventral and dorsal MPFC are functionally connected via the amygdala (Kim et al., 2011). It is speculated that this neural circuit, involving the dorsal and ventral MPFC and the amygdala, a circuit which could be the basis for simultaneous detachment and empathy. It hence appears that detachment and empathy are associated with activation in closely connected areas of the brain.
HER2 Amplification and Clinicopathological Characteristics in a Large Asian Cohort of Rare Mucinous Ovarian Cancer

Mucinous epithelial ovarian cancer has a poor prognosis in the advanced stages and responds poorly to conventional chemotherapy. We aim to elucidate the clinicopathological factors and incidence of HER2 expression of this cancer in a large Asian retrospective cohort from Singapore. Of a total of 133 cases, the median age at diagnosis was 48.3 years (range, 15.8–89.0 years), comparatively younger than western cohorts. Most were Chinese (71%), followed by Malays (16%), others (9.0%), and Indians (5%). 24% were noted to have a significant family history of malignancy of which breast and gastrointestinal cancers the most prominent. Majority of the patients (80%) had stage I disease at diagnosis. Information on HER2 status was available in 113 cases (85%). Of these, 31 cases (27.4%) were HER2+, higher than 18.8% reported in western population. HER2 positivity appeared to be lower among Chinese and higher among Malays patients (p = 0.052). With the current standard of care, there was no discernible impact of HER2 status on overall survival. (HR = 1.79; 95% CI, 0.66–4.85; p = 0.249). On the other hand, positive family history of cancer, presence of lymphovascular invasion, and ovarian surface involvements were significantly associated with inferior overall survival on univariate and continued to be statistically significant after adjustment for stage. While these clinical factors identify high risk patients, it is promising that the finding of a high incidence of HER2 in our Asian population may allow development of a HER2 targeted therapy to improve the management of mucinous ovarian cancers.
Analytical modeling of offset-induced priority in multiclass OBS networks

In this paper, we present for the first time an analytical model that quantifies the mechanism by which offset size affects priority in multiclass optical-burst switching (OBS) systems. Using the model, we derive an exact expression for the distribution of the number of bursts that contend with an arriving burst. The model is applicable to systems in which each class has an arbitrary burst-length distribution and an arbitrary offset size. We also derive accurate approximate expressions for the burst-blocking probability of premium-class traffic, as well as expressions for the sensitivity of premium-class performance to offset jitter and variations in the arrival rates of each class. In a case study, we find that scaling up a system in terms of the number of wavelengths and the traffic load significantly improves not only the burst-blocking performance of the premium class, but also its sensitivity to lower class traffic variations. We also use the model to dimension and provision the system to guarantee a minimum level of premium-class blocking and premium-class robustness to low-class load variations.
Dietary sugar, glycemic load, and pancreatic cancer risk in a prospective study.

BACKGROUND Evidence from both animal and human studies suggests that abnormal glucose metabolism plays an important role in pancreatic carcinogenesis. We investigated whether diets high in foods that increase postprandial glucose levels are associated with an increased risk of pancreatic cancer. METHODS In a cohort of U.S. women (n = 88 802) participating in the Nurses' Health Study, 180 case subjects with pancreatic cancer were diagnosed during 18 years of follow-up. We used frequency of intake of individual foods as reported on a food-frequency questionnaire in 1980 to calculate sucrose, fructose, and carbohydrate intakes; glycemic index (postprandial blood glucose response as compared with a reference food); and glycemic load (glycemic index multiplied by carbohydrate content). Analyses of relative risk (RR) were performed by using multivariable Cox proportional hazards models to adjust for potential confounders. All statistical tests were two-sided. RESULTS Carbohydrate and sucrose intake were not associated with overall pancreatic cancer risk in this cohort. A statistically nonsignificant 53% increase in risk of pancreatic cancer (RR = 1.53, 95% confidence interval [CI] = 0.96 to 2.45) was observed among women with a high glycemic load intake, and a similar association was observed for fructose intake (RR = 1.57, 95% CI = 0.95 to 2.57). The associations of glycemic load and fructose intakes with pancreatic cancer risk were most apparent among women with elevated body mass index (>or=25 kg/m(2)) or with low physical activity. Among women who were both overweight and sedentary, a high glycemic load was associated with an RR of 2.67 (95% CI = 1.02 to 6.99; highest versus lowest quartile of intake; P for trend =.03), and high fructose was associated with an RR of 3.17 (95% CI = 1.13 to 8.91; P for trend =.04). CONCLUSION Our data support other findings that impaired glucose metabolism may play a role in pancreatic cancer etiology. A diet high in glycemic load may increase the risk of pancreatic cancer in women who already have an underlying degree of insulin resistance.
Measuring and understanding surface heat fluxes in a changing Arctic environment

Calendar . 16 IN THIS ISSUE Early climate models projected Arctic warming and sea ice loss in response to increased greenhouse gas forcing (Manabe and Stouffer, 1980). The Arctic climate change predicted by these early models and the current generation of climate models is occurring. Passive microwave satellite observations from 1979 to present show steady declines in Arctic sea ice extent in all seasons, especially in late summer (Figure 1). Observations from ships and satellite laser altimeters indicate that Arctic sea ice has been thinning (Kwok and Rothrock, 2009). That Arctic sea ice loss is occurring is not surprising, but the record-breaking loss in recent years has impressed both experts and the general public alike. Some climate models can reproduce observed 20th century Arctic sea ice extent loss and simulate extreme events akin to the 2007 melt year (Holland et al., 2006). Yet, our understanding and modeling of Arctic climate processes remains far from perfect. Stroeve et al. (2007) found that many climate models under-predict the observed 20th century sea ice loss. The reasons behind the mean climate model under-prediction of observed sea ice loss are multi-faceted. Biases in sea ice thickness (Bitz et al., 2008) and longwave feedback strengths (Boe et al., 2009) may help explain the deficit in modeled Arctic sea ice loss. Beyond model biases, we must remember that Arctic climate trajectories are inherently difficult to predict. Natural variability in large-scale Arctic circulation patterns is appreciable and contributes to observed Arctic climate change (e.g., early 20th century warming (Wood et al. 2009), 1979-2007 Arctic sea ice loss trends (Deser and Teng, 2008)). The magnitude of aerosol and greenhouse gas forcing affects Arctic climate trajectories and depends on human decisions. Even if we could perfectly model the Arctic climate system, we expect spread in Arctic climate projections. Observed Arctic climate change and the March 2007-March 2009 International Polar Year have galvanized the scientific community to understand the processes that control Arctic climate in a warming world. Many important questions remain unanswered: How do natural variability and human-forced changes contribute to observed Arctic climate change? How will increasing greenhouse gas concentrations and aerosol burdens affect the trajectory of Arctic warming and sea ice loss? When will the Arctic be seasonally ice-free? How do the ocean and atmosphere interactions change in warming world? Observations of a changing Arctic system provide invaluable new information. For example, from the 2007 melt season, we learned that long-term trends and conditions during an individual melt season can combine to generate record-breaking ice loss. Measuring and understanding surface heat fluxes in a changing Arctic environment
Quantitative Expression Analysis in Brassica napus by Northern Blot Analysis and Reverse Transcription-Quantitative PCR in a Complex Experimental Setting

Analysis of gene expression is one of the major ways to better understand plant reactions to changes in environmental conditions. The comparison of many different factors influencing plant growth challenges the gene expression analysis for specific gene-targeted experiments, especially with regard to the choice of suitable reference genes. The aim of this study is to compare expression results obtained by Northern blot, semi-quantitative PCR and RT-qPCR, and to identify a reliable set of reference genes for oilseed rape (Brassica napus L.) suitable for comparing gene expression under complex experimental conditions. We investigated the influence of several factors such as sulfur deficiency, different time points during the day, varying light conditions, and their interaction on gene expression in oilseed rape plants. The expression of selected reference genes was indeed influenced under these conditions in different ways. Therefore, a recently developed algorithm, called GrayNorm, was applied to validate a set of reference genes for normalizing results obtained by Northern blot analysis. After careful comparison of the three methods mentioned above, Northern blot analysis seems to be a reliable and cost-effective alternative for gene expression analysis under a complex growth regime. For using this method in a quantitative way a number of references was validated revealing that for our experiment a set of three references provides an appropriate normalization. Semi-quantitative PCR was prone to many handling errors and difficult to control while RT-qPCR was very sensitive to expression fluctuations of the reference genes.