Miracle-dz/UniFAR-FTUs huggingface dataset:
Fuzzy Mechanisms for Unified Reasoning about Heterogeneous Data

Human knowledge about monitoring process variables is usually incomplete. To deal with this partial knowledge many types of representation other than the quantitative one are used to describe process variables (qualitative, symbolic interval). Thus, the development of automatic reasoning mechanisms about the process is faced with this problem of multiple data representations. In this paper, a unified principle for reasoning about heterogeneous data is introduced. This principle is based on a simultaneous mapping of data from initially heterogeneous spaces into only one homogeneous space based on a relative measure using appropriate characteristic functions. Once the heterogeneous data are represented in a unified space, a single processing for various analysis purposes can be performed using simple reasoning mechanisms. An application of this principle within a fuzzy logic framework is performed here to demonstrate its effectiveness. We show that simple fuzzy reasoning mechanisms can be used to reason in a unified way about heterogeneous data in two well known machine learning problems.
Learning Data Set Similarities for Hyperparameter Optimization Initializations

Current research has introduced new automatic hyperparameter optimization strategies that are able to accelerate this optimization process and outperform manual and grid or random search in terms of time and prediction accuracy. Currently, meta-learning methods that transfer knowledge from previous experiments to a new experiment arouse particular interest among researchers because it allows to improve the hyperparameter optimization. In this work we further improve the initialization techniques for sequential model-based optimization, the current state of the art hyperparameter optimization framework. Instead of using a static similarity prediction between data sets, we use the few evaluations on the new data sets to create new features. These features allow a better prediction of the data set similarity. Furthermore, we propose a technique that is inspired by active learning. In contrast to the current state of the art, it does not greedily choose the best hyperparameter configuration but considers that a time budget is available. Therefore, the first evaluations on the new data set are used for learning a better prediction function for predicting the similarity between data sets such that we are able to profit from this in future evaluations. We empirically compare the distance function by applying it in the scenario of the initialization of SMBO by meta-learning. Our two proposed approaches are compared against three competitor methods on one meta-data set with respect to the average rank between these methods and show that they are able to outperform them.
Career Certainty and Major Satisfaction

Information-seeking is conceptualized by multiple career decision-making models but has received insufficient attention in the literature. This may be in part due to the difficulty in assessing the amount of information students have acquired about their chosen careers (i.e., their level of occupational knowledge). The present study, sampling 316 college students, modeled this process, with career exploration activities and occupational knowledge as exogenous variables. We expected both exogenous variables to directly and indirectly relate to career certainty and major satisfaction, with self-perceived occupational knowledge, occupational information self-efficacy (defined as the self-efficacy of seeking occupational information during the career decision-making process), and interest congruence acting as mediators. Results showed that career exploration activities indirectly related to the two outcome variables through both self-perceived knowledge and occupational information self-efficacy. Occupational knowledge only related to interest congruence; the latter did not relate to either outcome variable. This study was the first to objectively assess college students’ knowledge of the careers they were actively pursuing and the first to examine that construct along with other important career decision-making variables.
Protective effects of silymarin against photocarcinogenesis in a mouse skin model.

BACKGROUND Nonmelanoma skin cancer is the most common cancer among humans; solar UV is its major cause. Therefore, it is important to identify agents that can offer protection against this cancer. PURPOSE We evaluated the protective effects of silymarin, a flavonoid compound isolated from the milk thistle plant, against UVB radiation-induced nonmelanoma skin cancer in mice and delineated the mechanism(s) of its action. METHODS For long-term studies, three different protocols of treatment were employed, each evaluating protection by silymarin at a different stage of carcinogenesis. Female SKH-1 hairless mice were subjected to 1) UVB-induced tumor initiation followed by phorbol ester-mediated tumor promotion, 2) 7,12-dimethylbenz[a]anthracene-induced tumor initiation followed by UVB-mediated tumor promotion, and 3) UVB-induced complete carcinogenesis. Forty mice were used in each protocol and were divided into control and treatment groups. Silymarin was applied topically at a dose of 9 mg per application before UVB exposure, and its effects on tumor incidence (% of mice with tumors), tumor multiplicity (number of tumors per mouse), and average tumor volume per mouse were evaluated. In short-term studies, the following parameters were measured: formation of sunburn and apoptotic cells, skin edema, epidermal catalase and cyclooxygenase (COX) activities, and enzymatic activity and messenger RNA (mRNA) expression for ornithine decarboxylase (ODC), a frequently observed marker at tumor promotion stage. Fisher's exact test was used to evaluate differences in tumor incidence, two-sample Wilcoxon rank sum test was used for tumor multiplicity and tumor volume, and Student's t test was used for all other measurements. All statistical tests were two-sided. RESULTS In the protocol with UVB-induced tumor initiation, silymarin treatment reduced tumor incidence from 40% to 20% (P = .30), tumor multiplicity by 67% (P = .10), and tumor volume per mouse by 66% (P = .14). In the protocol with UVB-induced tumor promotion, silymarin treatment reduced tumor incidence from 100% to 60% (P<.003), tumor multiplicity by 78% (P<.0001), and tumor volume per mouse by 90% (P<.003). The effect of silymarin was much more profound in the protocol with UVB-induced complete carcinogenesis, where tumor incidence was reduced from 100% to 25% (P<.0001), tumor multiplicity by 92% (P<.0001), and tumor volume per mouse by 97% (P<.0001). In short-term experiments, silymarin application resulted in statistically significant inhibition in UVB-caused sunburn and apoptotic cell formation, skin edema, depletion of catalase activity, and induction of COX and ODC activities and ODC mRNA expression. CONCLUSIONS AND IMPLICATION Silymarin can provide substantial protection against different stages of UVB-induced carcinogenesis, possibly via its strong antioxidant properties. Clinical testing of its usefulness is warranted.
Using kernel density estimation to identify, rank, and classify severe weather outbreak events

A method for ranking severe weather outbreaks of any type using a linear-weighted multivariate scheme has been introduced recently. The results of using this ranking method indicated that the scheme was capable of identifying the most significant severe weather outbreaks. However, the inclusion of days in which numerous reports were widely dispersed across a large region, or in which multiple clusters of reports that were geographically widely separated, was problematic. Though the studies included a variable (the so-called middle-50% parameter) that was effective in identifying these cases, a new way was needed to account for these days in a manner that agrees with subjective perceptions of these events. A candidate scheme introduced here uses nonparametric kernel density estimation to identify clusters of severe weather reports associated with a single severe weather event. Clusters with relatively few reports or sparse coverage within the region associated with the event then can be excluded quite easily. This technique also allows for multiple, regionally-separated clusters of severe reports to be considered in one day. After identifying clusters of severe weather events from 1960-2008, the cases are ranked and classified in a way similar to past research, using multivariate linear-weighting and cluster analysis, respectively. Results suggest that the most significant severe weather outbreaks again are identified appropriately, and the cases could be classified as major tornado, hail-dominant, wind-dominant, and minor mixed-mode events. ––––––––––––––––––––––––
Contrast agents and renal cell apoptosis.

AIMS Contrast media (CM) induce a direct toxic effect on renal tubular cells. This toxic effect may have a role in the pathophysiology of contrast nephropathy. METHODS AND RESULTS We evaluated (i) the cytotoxicity of CM [both low-osmolality (LOCM) and iso-osmolality (IOCM)], of iodine alone, and of an hyperosmolar solution (mannitol 8%) on human embryonic kidney (HEK 293), porcine proximal renal tubular (LLC-PK1), and canine Madin-Darby distal tubular renal (MDCK) cells; and (ii) the effectiveness of various antioxidant compounds [n-acetylcysteine (NAC), ascorbic acid and sodium bicarbonate] in preventing CM cytotoxicity. The cytotoxicity of CM was assessed at different time points, with different methods: cell viability, DNA laddering, flow cytometry, and caspase activation. Both LOCM and IOCM produced a concentration- and time-dependent increase in cell death as assessed by the different methods. On the contrary, iodine alone and hyperosmolar solution did not induce any significant cytotoxic effect. There was not any significant difference in the cytotoxic effect between LOCM and IOCM. Furthermore, both LOCM and IOCM caused a marked increase in caspase-3 and -9 activities and poly(ADP-ribose) fragmentation, while no effect on caspase-8/-10 was observed, thus indicating that the CM activated apoptosis mainly through the intrinsic pathway. Both CM induced an increase in protein expression levels of pro-apoptotic members of the Bcl2 family (Bim and Bad). NAC and ascorbic acid but not sodium bicarbonate had a dose-dependent protective effect on renal cells after 3 h incubation with high dose (200 mg iodine/mL) of both LOCM and IOCM. CONCLUSION Both LOCM and IOCM induce a dose-dependent renal cell apoptosis. NAC and ascorbic acid but not sodium bicarbonate prevent this contrast-induced apoptosis.
Improved stability analysis and gain-scheduled controller synthesis for parameter-dependent systems

We present new algorithms for the robust stability analysis and gain-scheduled controller synthesis for linear systems affected by time-varying parametric uncertainties. Sufficient conditions for robust stability as well as conditions for the existence of a robustly stabilizing gain-scheduled controller are given in terms of a finite number of linear matrix inequalities; explicit formulae for constructing robustly stabilizing gain-scheduled controllers are given in terms of the feasible set of these LMI. Our approach is proven to be in general less conservative than existing methods for stability analysis and gain-scheduled controller synthesis for parameter-dependent linear systems; numerical examples are presented to show that our approach offers significant improvement in practice as well.
Visualization of Microtubule Growth in Cultured Neurons via the Use of EB3-GFP (End-Binding Protein 3-Green Fluorescent Protein)

Several microtubule binding proteins, including CLIP-170 (cytoplasmic linker protein-170), CLIP-115, and EB1 (end-binding protein 1), have been shown to associate specifically with the ends of growing microtubules in non-neuronal cells, thereby regulating microtubule dynamics and the binding of microtubules to protein complexes, organelles, and membranes. When fused to GFP (green fluorescent protein), these proteins, which collectively are called +TIPs (plus end tracking proteins), also serve as powerful markers for visualizing microtubule growth events. Here we demonstrate that endogenous +TIPs are present at distal ends of microtubules in fixed neurons. Using EB3-GFP as a marker of microtubule growth in live cells, we subsequently analyze microtubule dynamics in neurons. Our results indicate that microtubules grow slower in neurons than in glia and COS-1 cells. The average speed and length of EB3-GFP movements are comparable in cell bodies, dendrites, axons, and growth cones. In the proximal region of differentiated dendrites ∼65% of EB3-GFP movements are directed toward the distal end, whereas 35% are directed toward the cell body. In more distal dendritic regions and in axons most EB3-GFP dots move toward the growth cone. This difference in directionality of EB3-GFP movements in dendrites and axons reflects the highly specific microtubule organization in neurons. Together, these results suggest that local microtubule polymerization contributes to the formation of the microtubule network in all neuronal compartments. We propose that similar mechanisms underlie the specific association of CLIPs and EB1-related proteins with the ends of growing microtubules in non-neuronal and neuronal cells.
Parallel computers and complex systems

We present an overview of the state of the art and future trends in high performance parallel and distributed computing, and discuss techniques for using such computers in the simulation of complex problems in computational science. The use of high performance parallel computers can help improve our understanding of complex systems, and the converse is also true — we can apply techniques used for the study of complex systems to improve our understanding of parallel computing. We consider parallel computing as the mapping of one complex system — typically a model of the world — into another complex system — the parallel computer. We study static, dynamic, spatial and temporal properties of both the complex systems and the map between them. The result is a better understanding of which computer architectures are good for which problems, and of software structure, automatic partitioning of data, and the performance of parallel machines.
Optimization Methods for Designing Sequences With Low Autocorrelation Sidelobes

Unimodular sequences with low autocorrelation are desired in many applications, especially in radar systems and code-division multiple access (CDMA) communication systems. In this paper, we propose a new algorithm to design unimodular sequences with low autocorrelation via directly minimizing the integrated sidelobe level (ISL) of the autocorrelation. The algorithm is derived based on the general framework of majorization-minimization (MM) algorithms and thus shares the monotonic property of such methods, and two acceleration schemes have been considered to accelerate the overall convergence. In addition, the proposed algorithm can be implemented via fast Fourier transform (FFT) operations and thus is computationally efficient. Furthermore, after some modifications the algorithm can be adapted to incorporate spectral constraints, which makes the design more flexible. Numerical experiments show that the proposed algorithms outperform existing ones in terms of both the merit factors of designed sequences and the computational complexity.
A novel approach towards designing a wearable Smart Health Monitoring System measuring the vital parameters and emergency situations in real-time and providing the necessary medical care through telemedicine

Health Monitoring systems are progressively evolving with the potential to change the way health care is currently delivered. A Smart Health Monitoring System, such as the one designed in this study, aims to automate patient monitoring tasks. In the present study we have designed and developed a GSM (Global System for Mobile) based smart wearable system with 3-axis Accelerometer, 3-lead ECG recording system and real-time NIBP analysis system. The device is capable of detecting sudden fall situations, cardiac abnormalities & hyper/hypotension; thereby rendering it suitable for real-time monitoring, self-diagnosis and remote diagnosis purposes. The system is also capable of sending notifications to healthcare professionals immediately after the detection of any of the aforementioned health abnormalities so that the necessary steps are taken. The complete analysis and evaluation of the signals acquired from the patient have been performed using a software platform: NI LabVIEW. It is a cost-effective, smart and wearable health monitoring system that is of immense importance not only to the elderly and post-operative patients, but also to those residing in remote locations and are incapable of affording expensive healthcare in urban hospitals or clinics.
A Unified Design Method of Asynchronous Service-Oriented Architecture Based on the Models and Patterns of Asynchronous Message Exchanges

This article proposes a unified methodology for designing asynchronous SOA (Service-Oriented Architecture) based on the asynchronous messaging models and patterns. Conventional SOA focuses on synchronous messaging. Although asynchronous messaging provides much efficient and productive way to coordinate services, design of aSOA (asynchronous SOA) is far more complicated due to the variety of messaging and architecture while assuring behavioral consistency of architecture. This paper proposes a model-driven design methodology for aSOA. The methodology is based on aMEPs (Asynchronous Message Exchange Patterns) identified by classifying the messaging in terms of behavioral concerns. Based on the meta-model of aSOA, a set of aSOA patterns is generated by composing aMEPs. Then, an aSOA pattern is selected and transformed to a platform specific aSOA on top of Web services standards. We successfully implemented an aSOA on Apache Axis, which enables to asynchronous messaging of SOAP over SMTP. We demonstrated that conventional methods are subsets of the proposed methodology, which is the major contribution of this work.
Absence of Gender Differences in Actual Induced HMD Motion Sickness vs. Pretrial Susceptibility Ratings

The purpose of this paper is to report the gender differences in motion sickness susceptibility and reported sickness levels experienced during a study to determine how latency in a head-mounted display affects human performance. This experiment used a camera feeding an image of the room to an HMD to examine performance on a point and shoot task with added latency in a HMD. Twenty-nine participants completed a repeated measures study in which they performed a simple object location targeting task in base and varying latency conditions. Results showed a significant difference between genders in the pre-trial susceptibility rating using the MSSQ-S. Results also indicated that the participants’ sickness levels increased during their exposure to the HMD latency stimulus based on their SSQ scores. Further, when the sickness levels were examined, there were no differences found between male and female participants. As a result, gender should not be used as an exclusion factor in determining whether or not to use HMD and VR devices.
Directional light emission from a kite-shaped microcavity laser

The lasing modes in a thin kite-shaped active microcavity are considered as solutions to a specifically tailored two-dimensional (2-D) linear eigenvalue problem for the Maxwell equations with exact boundary and radiation conditions. This problem is reduced to the set of Muller's boundary integral equations discretized using the adequate quadrature formulas. The eigenvalues are found numerically as the roots of the corresponding determinantal equation. The results of the study of mode lasing thresholds, spectra and light emission directivities are presented.
Improving mesh-agnostic client announcement in B.A.T.M.A.N.-advanced

Research in Wireless Mesh Networking has been very active in the past years, with the birth of several new ideas and the protocols that implement them. Most common implementations rely on Layer-3 addressing and routing; however 802.11s and other successful protocols suggest that Mesh Networking on Layer-2 address space is more efficient, does not mingle with the global IP routing, and provides easier ways to support micro-mobility as well as client management. This paper focuses on the client announcement protocol, i.e., the functionality, somewhat embedded between Layer-2 and Layer-3, that allows routers in a mesh network to announce the clients they are serving and that in practice makes the entire routing protocol work correctly. In particular, it focuses on B.A.T.M.A.N. -Advanced, analyses the shortcomings of the simple implementation of this functionality present until v.2011. 2.0 and defines the new protocol and algorithms that we have implemented and are part of the distribution starting from v.2011. 3.0. Experiments in controlled scenarios show how performance increases dramatically even in scenarios designed specifically to stress the new protocol. The new mechanism and improved performance make it possible to design new features for B.A.T.M.A.N. -Advanced, most notably the support for fast and seamless handover, which is currently under testing.
Is There Such a Thing as “Ultimate” Meaning? A Review of Fluid versus Fixed Models of Different Forms of Human Striving

ABSTRACT A growing number of social psychological theories have posited that meaning-striving can be compensated for across domains; threats in one area can simply be addressed by gains in another. Other models argue that not all forms of meaning are created equal; certain forms of striving trump other ones. This review compares the assertions made by these different models related to meaning to illustrate that (a) with few exceptions, fluidity is central to meaning, and (b) despite such consensus on the fluid nature of meaning, existing models diverge on the existence and nature of “ultimate” meanings. Future directions for the empirical study of meaning and methodological considerations are discussed.
The Relationship between Natriuretic Peptide Precursor a Gene T2238C Polymorphism and Hypertension: A Meta-Analysis

Single studies attempting to associate ANP gene T2238C (rs5065) polymorphism with hypertension have so far reported inconclusive results. We therefore aimed to evaluate this association via a meta-analysis. Data on 7 studies with a total of 4068 subjects were available and analyzed using the random-effects model with assessment of heterogeneity and publication bias. Overall comparison of 2238C with 2238T yielded a 23% reduced, albeit nonsignificant, risk for hypertension (95% CI: 0.38–1.59; P = .485), while accompanying significant heterogeneity (I2 = 88.3%) and publication bias (P = .051). Subgroup analysis by study design demonstrated opposite associations between population-based (OR = 0.33; 95% CI: 0.13–0.80; P = .015) and hospital-based studies (OR = 1.15; 95% CI: 0.79–1.68; P = .454). Further meta-regression analysis exclusively indicated the significant influence of study design (P = .042) on heterogeneity. Taken together, these findings support the notion that carriers of 2238C allele were at moderate decreased risk of developing hypertension, whereas study design was identified as a potentially significant source of between-study heterogeneity.