Miracle-dz/UniFAR-FTUs huggingface dataset:
The ins and outs of phospholipid asymmetry in the plasma membrane: roles in health and disease

A common feature of all eukaryotic membranes is the non-random distribution of different lipid species in the lipid bilayer (lipid asymmetry). Lipid asymmetry provides the two sides of the plasma membrane with different biophysical properties and influences numerous cellular functions. Alteration of lipid asymmetry plays a prominent role during cell fusion, activation of the coagulation cascade, and recognition and removal of apoptotic cell corpses by macrophages (programmed cell clearance). Here we discuss the origin and maintenance of phospholipid asymmetry, based on recent studies in mammalian systems as well as in Caenhorhabditis elegans and other model organisms, along with emerging evidence for a conserved role of mitochondria in the loss of lipid asymmetry during apoptosis. The functional significance of lipid asymmetry and its disruption during health and disease is also discussed.
Creating advanced mobility models with LEMMA

In this paper we introduce an open-source multiagent microsimulator implementing the Layered Mobility Model Architecture (LEMMA) [1]. Its design is described briefly, along with several examples of layers that have been implemented. Even though the number of layer descriptions is limited, we have introduced 8 layers, allowing the creation of 16 unique mobility models. Moreover, we have detailed the architecture of the microsimulator itself, describing its core modules and their relations. We have illustrated its usage with the help of several examples. The creation of advanced mobility models is also discussed, including the creation of hybrid or group models, or executing cooperative simulations with ns-3. The source code is freely available at the following address: http://mobilitymodels.org/lemma
Comparative Analysis of Asynchronous I/O in Multithreaded UNIX

I/O operations in UNIX are inherently synchronous. The need for asynchronous I/O comes first from multithreaded applications where thrads cannot block for I/O, and second from the fact that asynchronous I/O has much less overhead than synchronous I/O . There are two main approaches to accomplishing asynchronous I/O in UNIX. We compare the two approaches in design and implementation, and report the results of extensive experiments to measure the performance differences.
Analyzing for Patterns in the Cattell's 16 Personality Factors Dataset using Social Segmentation

Personality psychology has an essential prediction of behaviors. Cattell’s personality theory is implemented to almost 49259 testers by asking 162 questions which occurred by 16 different question group types and testers answered these questions by using dataset for finding related pieces of information between these questions and forecast behaviors of the matter. These questions are established for answering the subject with appropriateness and some of these questions are based on the predicted questions for the same aim. Two social segments are completed by using the social segmentation with dividing the whole dataset with few mathematical equations and as a result, the general procedure is done. These two groups are compared for seeing the result in detail and which questions are mostly answered. The results show that different question groups play varied roles in how they correlate to other questiongroups
Sensor less control of PMSM fed from three phase four switch inverter based on back EMF observer and sliding mode controller with fast reaching law

Closed Loop control of PMSM drives require rotor position and angular velocity information, the use of position sensor increases cost of the drive and increases complexity in motor construction. A position sensor less vector control technique is proposed where a back EMF observer is used to estimate motors speed and position signal. Back EMF observer method is simple and has high accuracy in estimating speed of PMSM motor. Permanent magnet synchronous motor is fed from a three-phase four-switch inverter and sliding mode controller is used as a speed regulator. Fast reaching law is added to sliding mode speed controller, which replaces constant switching gain function by variable switching function based on sliding surface. Variable switching function for SMC eliminates the chattering problem that occurs due to high value of constant switching gain. The proposed reaching law for sliding mode controller reduces the time taken for the controller to reach convergence and also increases robustness of the drive during parameter variation and full load conditions. Use of sensor less control technique and four-switch inverter reduced the overall cost of the drive whilst maintaining the performance of the system. Merits of pro-posed sensor less control technique and sliding mode controller with fast reaching law is verified by simulations using MATLAB/Simulink software. Motor (PMSM); Sliding Mode Controller with Fast Reaching Law; Speed Estimation; Three Phase 4 Switch Inverter (TPFSI).
Composition and Sources of Particulate Matter Measured near Houston, TX: Anthropogenic-Biogenic Interactions

Particulate matter was measured in Conroe, Texas (~60 km north of downtown Houston, Texas) during the September 2013 DISCOVER-AQ campaign to determine the sources of particulate matter in the region. The measurement site is influenced by high biogenic emission rates as well as transport of anthropogenic pollutants from the Houston metropolitan area and is therefore an ideal location to study anthropogenic-biogenic interactions. Data from an Aerosol Chemical Speciation Monitor (ACSM) suggest that on average 64 percent of non-refractory PM1 was organic material, including a high fraction (27%–41%) of organic nitrates. There was little diurnal variation in the concentrations of ammonium sulfate; however, concentrations of organic and organic nitrate aerosol were consistently higher at night than during the day. Potential explanations for the higher organic aerosol loadings at night include changing boundary layer height, increased partitioning to the particle phase at lower temperatures, and differences between daytime and nighttime chemical processes such as nitrate radical chemistry. Positive matrix factorization was applied to the organic aerosol mass spectra measured by the ACSM and three factors were resolved—two factors representing oxygenated organic aerosol and one factor representing hydrocarbon-like organic aerosol. The factors suggest that the measured aerosol was well mixed and highly processed, consistent with the distance from the site to major aerosol sources, as well as the high photochemical activity.
Decentralized and optimal control of shared resource pools

Resource pools are collections of computational resources (e.g., servers) which can be used by different applications in a shared way. A crucial aspect in these pools is to allocate resources so as to ensure their proper usage, taking into account workload and specific requirements of each application. An interesting approach, in this context, is to allocate the resources in the best possible way, aiming at optimal resource usage. Workload, however, varies over time, and in turn, resource demands will vary too. To ensure that optimal resource usage is always in place, resource shares should be defined dynamically and over time. It has been claimed that utility functions are the main tool for enabling such self-optimizing behavior. Whereas many solutions with this characteristic have been proposed to date, none of them presents true decentralization within the context of shared pools. In this article, we then propose a decentralized model for optimal resource usage in shared resource pools, providing practical and theoretical evidence of its feasibility.
Automatic 3D modelling of palatal plaster casts

We introduce a procedure for automatic 3D modelling and discusses its performance in the context of a medical application, namely the 3D modelling of palate's casts. The general interest of the proposed method lays in the fact that a widespread use of 3D modelling in nonengineering applications requires automatic procedures. The specific interest is in the intriguing mixture of open issues concerning 3D modelling, geometrical metrology and medicine represented by the modelling of free-form surfaces of anatomical interest.
Valuation of New Goods Under Perfect and Imperfect Competition

The Consumer Price Index (CPI) attempts to answer the question of how much more (or less) income does a consumer require to be as well off in period 1 as in period 0 given changes in prices, changes in the quality of goods, and the introduction of new goods (or the disappearance of existing goods). In this paper I explain the theory of cost-of-living indices and demonstrate how new goods should be included using the classical theory of Hicks and Rothbarth. The correct price to use for the good in the pre-intro- duction period is a `virtual' price which sets demand to zero. Estimation of this virtual price requires estimation of a demand function which in turn provides the expenditure function which allows exact calucation of the cost of living index. The data requirements and need to specify and estimate a demand function for a new brand among many existing brands requires extensive data and some new econometric methods which may have proven obstacles to the inclusion of new goods in the CPI up to this point. As an example I use the introduction of a new cereal brand by General Mills in 1989-Apple Cinnamon Cheerios. I find the virtual price is about 2 times the actual price of Apple Cinnamon Cheerios and that increase in consumer surplus is substantial. Based on some simplifying approximations, I find that CPI may be overstated for cereal by about 25% because of its neglect of the effect of new brands. When I take imperfect competition into account I find that the increase in consumer welfare is only 85% as high with perfect competition so CPI for cereal would still be 20% too high
Wine consumers’ environmental knowledge and attitudes: Influence on willingness to purchase

The last two decades have witnessed a dramatic increase in environmental consciousness worldwide. Consumers are now changing their behavior to integrate environmental considerations into lifestyle choices. This change includes consumers' purchasing decisions based upon how well products satisfy their needs and how these products affect the natural environment. In some cases, consumers are willing to pay a premium for environmentally friendly products. Marketing professes to serve the benefi t of the public by informing them of the availability of goods and services that will advance their quality of life. However, this is only true if marketing's communication approach and methods of promotion aid in informing, educating, and channeling the needs of current and future consumers toward "green" products and services. Using wine as the product, the purpose of this study is to determine the relation- ship of a consumer's involvement with a product and the environment, their knowledge of environmental issues and attitudes toward the environment, and their willingness to purchase the product. The results suggest personality segmentation, through selective marketing and redirecting of consumers needs and wants toward environmentally friendly wine products. For example, what wine consumers actually know about environmental wine issues is associated with their involvement with environmental issues more than what they self-assess they know about wine.
Polylactide-co-glycolide nanoparticles for controlled delivery of anticancer agents

The effectiveness of anticancer agents may be hindered by low solubility in water, poor permeability, and high efflux from cells. Nanomaterials have been used to enable drug delivery with lower toxicity to healthy cells and enhanced drug delivery to tumor cells. Different nanoparticles have been developed using different polymers with or without surface modification to target tumor cells both passively and/or actively. Polylactide-co-glycolide (PLGA), a biodegradable polyester approved for human use, has been used extensively. Here we report on recent developments concerning PLGA nanoparticles prepared for cancer treatment. We review the methods used for the preparation and characterization of PLGA nanoparticles and their applications in the delivery of a number of active agents. Increasing experience in the field of preparation, characterization, and in vivo application of PLGA nanoparticles has provided the necessary momentum for promising future use of these agents in cancer treatment, with higher efficacy and fewer side effects.
An interpretation of the results of the analysis of pair programming during novices integration in a team

In this paper we present a study on how Pair Programming (PP) facilitates the introduction of new developers (novices) in a team. Data has been collected non-invasively on how people paired in an industrial team of developers for 10 months; during such time novices joined the team. We focused on spontaneous PP, that is, on PP occurring when developers think it is most effective. Social network analysis techniques are used to analyze developers interactions and infer possible conclusions. It appears that initially PP is used to initiate novices, then it is drastically reduced to be resumed eventually when novices “feel” they have reached a significant level of maturity in the team. These phases are coherent with available works on group development and confirm existing findings on the importance of PP in the introduction of novices in teams, and, more generally, on team dynamics.
Convergent and Divergent Functional Connectivity Patterns in Schizophrenia and Depression

Major depression and schizophrenia are two of the most serious psychiatric disorders and share similar behavioral symptoms. Whether these similar behavioral symptoms underlie any convergent psychiatric pathological mechanisms is not yet clear. To address this issue, this study sought to investigate the whole-brain resting-state functional magnetic resonance imaging (MRI) of major depression and schizophrenia by using multivariate pattern analysis. Thirty-two schizophrenic patients, 19 major depressive disorder patients and 38 healthy controls underwent resting-state functional MRI scanning. A support vector machine in conjunction with intrinsic discriminant analysis was used to solve the multi-classification problem, resulting in a correct classification rate of 80.9% via leave-one-out cross-validation. The depression and schizophrenia groups both showed altered functional connections associated with the medial prefrontal cortex, anterior cingulate cortex, thalamus, hippocampus, and cerebellum. However, the prefrontal cortex, amygdala, and temporal poles were found to be affected differently by major depression and schizophrenia. Our preliminary study suggests that altered connections within or across the default mode network and the cerebellum may account for the common behavioral symptoms between major depression and schizophrenia. In addition, connections associated with the prefrontal cortex and the affective network showed promise as biomarkers for discriminating between the two disorders.
Unsafe exposure analysis of mobile in-app advertisements

In recent years, there has been explosive growth in smartphone sales, which is accompanied with the availability of a huge number of smartphone applications (or simply apps). End users or consumers are attracted by the many interesting features offered by these devices and the associated apps. The developers of these apps are also benefited by the prospect of financial compensation, either by selling their apps directly or by embedding one of the many ad libraries available on smartphone platforms. In this paper, we focus on potential privacy and security risks posed by these embedded or in-app advertisement libraries (henceforth "ad libraries," for brevity). To this end, we study the popular Android platform and collect 100,000 apps from the official Android Market in March-May, 2011. Among these apps, we identify 100 representative in-app ad libraries (embedded in 52.1% of them) and further develop a system called AdRisk to systematically identify potential risks. In particular, we first decouple the embedded ad libraries from host apps and then apply our system to statically examine the ad libraries, ranging from whether they will upload privacy-sensitive information to remote (ad) servers or whether they will download untrusted code from remote servers. Our results show that most existing ad libraries collect private information: some of them may be used for legitimate targeting purposes (i.e., the user's location) while others are hard to justify by invasively collecting the information such as the user's call logs, phone number, browser bookmarks, or even the list of installed apps on the phone. Moreover, additional ones go a step further by making use of an unsafe mechanism to directly fetch and run code from the Internet, which immediately leads to serious security risks. Our investigation indicates the symbiotic relationship between embedded ad libraries and host apps is one main reason behind these exposed risks. These results clearly show the need for better regulating the way ad libraries are integrated in Android apps.
Individual Behavior and Population Dynamics 1

Differential equations have been used in population biology to describe dynamics of interacting populations since the pioneering work of Lotka and Volterra. However, most of the work on population dynamics does not take into consideration individual decisions of animals. In behavioral ecology it was shown that animals often behave in such a way which maximizes certain criterion like energy or nutrient intake. Typically, this criterion is related to reproduction of animals, thus to fitness. We show how the theory of optimal foraging may be included into models of population dynamics. Typically, this leads to discontinuous differential equations, or more generally, to differential inclusions. We will discuss a few biologically relevant examples together with the underlying mathematics. IThis work was supported by the Academy of Sciences of the Czech Republic (Grant No. 107101).
X Brain Imaging and Machine Learning for Brain-Computer Interface

Human-computer interfaces are in continuous development, from keyboard, mouse, touch screen, to voice dictation, gesture recognition, etc. The aim is to facilitate the interaction between the human brain and the resources offered by a machine or a computer. Recently, a wider interest has emerged in directly interfacing the brain and the computer. The development of methods that combine the nervous system with artificial devices is attracting a growing interest from clinical research, because the interaction between brain and machines may lead to novel prosthetic devices or to a more efficient use of computer resources by breaking the barriers imposed at present by the classical human-machine interfaces. Individuals with impaired motor control may be disabled in the performance of their daily activities. Their motor performance, however, can be supported by artificial motor control systems. Such motor support systems may also assist healthy individuals in performing their tasks. One can also imagine interacting with different systems in parallel, or developing newer software tools without the need to physically typing the code.
ESD protection circuits with novel MOS-bounded diode structures

On-chip ESD protection circuits realized with novel diode structures, without the field-oxide boundary across the p/n junction, are proposed. A PMOS (NMOS) structure is especially inserted into the diode structure to form the PMOS-bounded (NMOS-bounded) diode, which is used to block the field oxide isolation across the p/n junction in the diode structure. Without the field oxide boundary across the p/n junction of the diode structure, the proposed PMOS-bounded and NMOS-bounded diodes can sustain much higher ESD stress, especially under the reverse-biased condition. Such PMOS-bounded and NMOS-bounded diodes are fully process-compatible with general CMOS processes without additional process modification or mask layers. The ESD protection circuits designed by such new diodes, with different junction parameters, have been successfully verified in a 0.35 /spl mu/m CMOS process.
NS3 Peptide, a Novel Potent Hepatitis C Virus NS3 Helicase Inhibitor: Its Mechanism of Action and Antiviral Activity in the Replicon System

ABSTRACT Hepatitis C virus (HCV) chronic infections represent one of the major and still unresolved health problems because of low efficiency and high cost of current therapy. Therefore, our studies centered on a viral protein, the NS3 helicase, whose activity is indispensable for replication of the viral RNA, and on its peptide inhibitor that corresponds to a highly conserved arginine-rich sequence of domain 2 of the helicase. The NS3 peptide (p14) was expressed in bacteria. Its 50% inhibitory activity in a fluorometric helicase assay corresponded to 725 nM, while the ATPase activity of NS3 was not affected. Nuclear magnetic resonance (NMR) studies of peptide-protein interactions using the relaxation filtering technique revealed that p14 binds directly to the full-length helicase and its separately expressed domain 1 but not to domain 2. Changes in the NMR chemical shift of backbone amide nuclei (1H and 15N) of domain 1 or p14, measured during complex formation, were used to identify the principal amino acids of both domain 1 and the peptide engaged in their interaction. In the proposed interplay model, p14 contacts the clefts between domains 1 and 2, as well as between domains 1 and 3, preventing substrate binding. This interaction is strongly supported by cross-linking experiments, as well as by kinetic studies performed using a fluorometric assay. The antiviral activity of p14 was tested in a subgenomic HCV replicon assay that showed that the peptide at micromolar concentrations can reduce HCV RNA replication.
Loneliness and internet addiction in doctors and medical students: a cross-sectional study

Background: Our aim in this study is to determine the level of internet addiction in medical school students and primary care physicians and the factors affecting them. Methods: A 68 physicians and 167 students participated in this descriptive study. The participants were administered the young internet addiction test, UCLA loneliness scale and asked to respond to survey questions about their ssociodemographic characteristics, and the relations were evaluated with appropriate statistical methods. Results: It has been identified that playing games online, surfing the internet aimlessly and loneliness score affected internet addiction regardless of other variables (p<0.05). A statistically significant correlation between addiction level and age (r= (-0.341), p<0,001), loneliness score (r=0,284, p<0,001) and online time (r=0,387, p<0,001) has been discovered. Conclusions: In this study, it was found statistically significant that students with internet addiction stayed online for long periods of time and it seemed in line with the criteria observed in substance use disorders such as longer duration of use than intended and not being able to spare time for other activities.