Miracle-dz/UniFAR-FTUs huggingface dataset:
SVM Classifier Estimation from Group Probabilities

A learning problem that has only recently gained attention in the machine learning community is that of learning a classifier from group probabilities. It is a learning task that lies somewhere between the well-known tasks of supervised and unsupervised learning, in the sense that for a set of observations we do not know the labels, but for some groups of observations, the frequency distribution of the label is known. This learning problem has important practical applications, for example in privacy-preserving data mining. This paper presents an approach to learn a classifier from group probabilities based on support vector regression and the idea of inverting a classifier calibration process. A detailed analysis will show that this new approach outperforms existing approaches.
Language-Restricted Iterated Function Systems, Koch Constructions, and L-systems

1 Introduction Linear fractals can be generated using a variety of methods. This raises the question of finding equivalent methods for generating the same fractal. Several aspects of this question have been addressed in the literature. These include: A method for converting Koch constructions to equivalent iterated function systems (IFS's) [11], Methods for converting selected classes of L-systems with geometric interpretation to extensions of IFS's, such as controlled iterated function systems (CIFS's) [10] and mutually recursive function systems (MRFS's) [4]. Previous course notes [9] introduced the notion of language-restricted iterated function systems (LRIFS's) encompassing CIFS's and MRFS's, and included a number of sample LRIFS's equivalent to L-systems with turtle interpretation. The present notes include the following further extensions to these results: Introduction of the notions of iterated transformations of coordinate systems (ITCS's) and their language
Human immunodeficiency virus type 1 Nef associates with a member of the p21-activated kinase family

Although human immunodeficiency virus (HIV) Nef is essential for the induction of AIDS, its biochemical function has remained an enigma. In this study, HIV Nef protein is shown to associate with a serine-threonine kinase that recognizes histone H4 as a substrate, is serologically related to rat p21-activated kinase (PAK), and is specifically activated by Rac and Cdc42. These characteristics define the Nef-associated kinase as belonging to the PAK family. PAKs initiate kinase cascades in response to environmental stimuli, and their identification as a target of Nef implicates these signaling molecules in HIV pathogenesis and provides a novel target for clinical intervention.
Keeping Doors Open: The Effect of Unavailability on Incentives to Keep Options Viable

Many of the options available to decision makers, such as college majors and romantic partners, can become unavailable if sufficient effort is not invested in them (taking classes, sending flowers). The question asked in this work is whether a threat of disappearance changes the way people value such options. In four experiments using "door games," we demonstrate that options that threaten to disappear cause decision makers to invest more effort and money in keeping these options open, even when the options themselves seem to be of little interest. This general tendency is shown to be resilient to information about the outcomes, to increased experience, and to the saliency of the cost. The last experiment provides initial evidence that the mechanism underlying the tendency to keep doors open is a type of aversion to loss rather than a desire for flexibility.
Continuous Remove Method and Equipment of LED Manufacturing Process Exhaust Gas Using Wet-Scrubber and Catalyst Reaction Scrubber

The present invention is an LED prepared as process for the continuous removal method and apparatus of the exhaust gas, more particularly to a LED according to discharge the process gas is toxic, flammable gas which is used in the manufacturing process, one step wet scrubber and two-phase catalytic reaction was passed through a scrubber to remove relates to a continuous method and apparatus of using the wet scrubber with the catalyst column for preventing environmental pollution and safety LED manufacturing process, the discharge gas by the discharge gas.
SIMES: A simulator for hybrid electrical energy storage systems

State-of-the-art electrical energy storage (EES) systems are mainly homogeneous, i.e., they consist of a single type of EES elements. None of the existing EES elements is capable of simultaneously fulfilling all the desired features of an ideal EES system, e.g., high charge/discharge efficiency, high energy density, low cost per unit capacity, long cycle life. A novel technology, i.e., a hybrid EES system that employs heterogeneous EES elements organized in a hierarchy of storage banks and linked by appropriate charge transfer interconnects, has shown great promise in overcoming the aforesaid limitations of conventional EES systems. However, the widespread adoption/deployment of hybrid EES systems is hampered by lack of a hybrid EES system simulator. This paper thus presents SIMES, a powerful and scalable simulator for hybrid EES systems, which provides fast and accurate system simulations, while accounting for key characteristics of various EES elements, power converters, charge transfer interconnect schemes, etc. Experimental results on two different applications (one targeting load shifting for households, the other related to battery rate capacity effect minimization in portable electronic devices) demonstrate the value and usefulness of SIMES for designing energy-aware facilities and products.
Youtube traffic characterization: a view from the edge

This paper presents a traffic characterization study of the popular video sharing service, YouTube. Over a three month period we observed almost 25 million transactions between users on an edge network and YouTube, including more than 600,000 video downloads. We also monitored the globally popular videos over this period of time. In the paper we examine usage patterns, file properties, popularity and referencing characteristics, and transfer behaviors of YouTube, and compare them to traditional Web and media streaming workload characteristics. We conclude the paper with a discussion of the implications of the observed characteristics. For example, we find that as with the traditional Web, caching could improve the end user experience, reduce network bandwidth consumption, and reduce the load on YouTube's core server infrastructure. Unlike traditional Web caching, Web 2.0 provides additional meta-data that should be exploited to improve the effectiveness of strategies like caching.
Computer generation of fourier transform libraries for distributed memory architectures

High-performance discrete Fourier transform (DFT) libraries are an important requirement for many computing platforms. Unfortunately, developing and optimizing these libraries for modern, complex platforms has become extraordinarily difficult. To make things worse, performance often does not port, thus requiring permanent re-optimizations. Overcoming this problem has been the goal of SPIRAL , a library generation system that can produce highly optimal DFT code from a high level specification of algorithms and target platforms. However, current techniques in SPIRAL cannot support all target platforms. In particular, several emerging target platforms incorporate a distributed memory parallel processing paradigm, where the cost of accessing non-local memories is relatively high, and handling data movement is exposed to the programmers. Traditionally used only in supercomputing environments, this paradigm is now also finding its way in the form of multicore processors into desktop computing. The goal of this work is the computer generation of high-performance DFT libraries for a wide range of distributed memory parallel processing systems, given only a high-level description of a DFT algorithm and some platform parameters. The key challenges include generating code for multiple target programming paradigms that delivers load balanced parallelization across multiple layers of the compute hierarchy, orchestrates explicit memory management, and overlaps computation with communication. We attack this problem by first developing a formal framework to describe parallelization, streaming, and data exchange in a domain-specific declarative mathematical language. Based on this framework, we develop a rewriting system that structurally manipulates DFT algorithms to "match" them to a distributed memory target architecture and hence extracts maximum performance. We implement this approach as a part of SPIRAL, together with a backend that translates the derived algorithms into actual libraries. Experimental results show that the performance of our generated code is comparable to hand-tuned code in all cases, and exceeds the performance of hand-tuned code in some cases.
Personal OAuth authorization server and push OAuth for Internet of Things

Internet of Things will connect millions of things to the Internet to make our lives more convenient. However, Internet of Things security is an essential factor. OAuth is one of the most successful authentication and authorization protocols on the Internet. This article proposes push OAuth and personal OAuth authorization server by expanding OAuth for a secure access to the information on Internet of Things devices. In personal OAuth, the smartphones that communicate with remote servers to deliver information on Internet of Things devices can be the OAuth authorization server. Hospitals (OAuth client) that intend to access the information on Internet of Things devices cannot know millions of OAuth authorization server when the smartphone becomes the OAuth authorization server. This article proposes the push OAuth that changes the OAuth protocol and issues the OAuth token when the OAuth authorization server registers to the OAuth client first. Personal OAuth authorization server is far more trustworthy than using a third-party OAuth authorization server to authenticate because users directly control access to the information generated by Internet of Things devices. The personal OAuth authorization server and push OAuth suggested here are expected to create a more secure Internet of Things environment as users can directly authenticate the OAuth client that can access the information on their Internet of Things devices.
Lessons Learned in Empirical Scoring with smina from the CSAR 2011 Benchmarking Exercise

We describe a general methodology for designing an empirical scoring function and provide smina, a version of AutoDock Vina specially optimized to support high-throughput scoring and user-specified custom scoring functions. Using our general method, the unique capabilities of smina, a set of default interaction terms from AutoDock Vina, and the CSAR (Community Structure-Activity Resource) 2010 data set, we created a custom scoring function and evaluated it in the context of the CSAR 2011 benchmarking exercise. We find that our custom scoring function does a better job sampling low RMSD poses when crossdocking compared to the default AutoDock Vina scoring function. The design and application of our method and scoring function reveal several insights into possible improvements and the remaining challenges when scoring and ranking putative ligands.
Evaluation of efficacy of commercial denture cleansing agents to reduce the fungal biofilm activity from heat polymerized denture acrylic resin: An in vitro study

Aims: To compare and evaluate Candida removing effects of three most commonly available varieties of commercial denture cleansers from heat polymerized acrylic resins. To compare and evaluate Candida lytic effects of denture cleansers. To assess the effect of time on ability of denture cleansers in reducing Candidal biofilm. Materials and Methods: A specially designed metal mold was fabricated to obtain wax plates of uniform dimensions which were used to fabricate heat cure acrylic resin plates. A square-shaped window of dimension 15 mm and thickness of 1.5 mm was provided in metal mould to simulate thickness of denture base. All samples used in this study were prepared using this mould. Candida albicans colonies were then cultured on this acrylic resin plates by colonization assay. Yeast removing test for samples was performed using microscope and yeast lytic test was performed using photo colorimeter. Results: Denture cleanser D2 showed the highest Candida removing activity when compared with cleansers D1, D3, and control solution. Denture cleansers D2 showed increased yeast lytic ability when compared with denture cleansers D1, D3, and control solution. More time span shared a definite influence on yeast lytic ability of denture cleansers. Conclusions: The effect of cleansing agents on removal of colonized yeasts particularly fungal biofilm from acrylic resins was assessed for clinical implications. The observation indicated superior performance of cleanser D2 when compared with D1 and D3 even though they all belong to same chemical group of alkaline peroxide. The increased effectiveness may be due to presence of sodium lauryl sulphate in formula of D2.
From tracking with RFID to intelligent products

The Internet of Things notion is sometimes being employed to signify the use of radio frequency identification (RFID) for tracking and tracing of products in supply chains. However, RFID is only one auto-ID technology among others. The world is already full of products with embedded identification, processing power, sensors etc. that can do much more than ordinary RFID tags. When such products will have the means to communicate between themselves and with other systems we will eventually reach a limit where they could be called intelligent products. Intelligent products are capable of collecting information and reacting on it proactively, e.g. estimating needs for maintenance or repair. With increased computing power and communication capabilities, products may also become pro-active.
Proposal of a timing model for CMOS logic gates driving a CRC /spl pi/ load

We present a gate delay model of CMOS logic gates driving a CRC /spl pi/ load for deep sub-micron technology. Our approach is to replace series-parallel connected MOSFETs to an equivalent MOSFET and calculate the output waveform by an analytically derived formula. We present a MOSFET drain current model improved from the n-th power law MOSFET model to represent the characteristic of the equivalent inverter accurately. The accuracy of our gate delay model is evaluated in several gates under various conditions of input transition time and CRC parameters. The maximum error is less than 10.3% in the experiments. Our approach contributes to fast and accurate estimation of circuit speed under various supply voltage, which will enable us to optimize the circuit speed and power dissipation.
Modeling the severity of drinking consequences in first-year college women: an item response theory analysis of the Rutgers Alcohol Problem Index.

OBJECTIVE The present study examined the latent continuum of alcohol-related negative consequences among first-year college women using methods from item response theory and classical test theory. METHOD Participants (N = 315) were college women in their freshman year who reported consuming any alcohol in the past 90 days and who completed assessments of alcohol consumption and alcohol-related negative consequences using the Rutgers Alcohol Problem Index. RESULTS Item response theory analyses showed poor model fit for five items identified in the Rutgers Alcohol Problem Index. Two-parameter item response theory logistic models were applied to the remaining 18 items to examine estimates of item difficulty (i.e., severity) and discrimination parameters. The item difficulty parameters ranged from 0.591 to 2.031, and the discrimination parameters ranged from 0.321 to 2.371. Classical test theory analyses indicated that the omission of the five misfit items did not significantly alter the psychometric properties of the construct. CONCLUSIONS Findings suggest that those consequences that had greater severity and discrimination parameters may be used as screening items to identify female problem drinkers at risk for an alcohol use disorder.
Economic learning for thermal-aware power budgeting in many-core architectures

One of the key challenges for multi-core processors in the nano-CMOS era is dealing with the increased temperatures. It is imperative that peak temperatures are reduced and that heat is spread as evenly on the chip as possible to avoid mutual heating and high thermal gradients between processor cores. Approaches have emerged which share a global power budget among multiple cores in order to meet these objectives. However, while these approaches act proactively in distributing power across the chip before thermal problems arise, changes in the respective strategies remain reactive to a temperature threshold. Our approach uses reinforcement learning in order to dynamically change what we call power trading strategies before thermal thresholds are hit based on past recorded observations. Through learning, our hierarchical approach is also able to distribute so-called multiple power budgets at once thereby making power trading more effective, reaching a decrease in peak temperatures of around 4% compared to a fully distributed approach - which can be critical at near-threshold temperatures in terms of transient errors - while also decreasing the number of deadline misses by a factor of 7. Our technique has been verified by deploying a thermal camera.
LCC Approaches to Knowledge Base Population at TAC 2010

The Knowledge Base Population (KBP) track at the Text Analysis Conference 2010 marks the second year of this important information extractionevaluation. Thispaperdescribesthe design and implementation of LCC’s systems which participated in the tasks of Entity Linking, Slot Filling, and the new task of Surprise Slot Filling. For the entitylinkingtask, ourtop score was achieved through a robust context modeling approach which incorporates topical evidence. For slot filling, we used the output of the entity linking system together with a combination of different types of relation extractors. For surprise slot filling, our customizableextractionsystem was extremely useful due to the time sensitive nature of the task.
Bio‐nanocapsule‐based scaffold improves the sensitivity and ligand‐binding capacity of mammalian receptors on the sensor chip

Mammalian receptors are recognized as target molecules for drug discovery, and chemical libraries have been screened for both potential antagonists and agonists mainly by ligand‐binding assays using immobilized receptors. A bio‐nanocapsule (BNC) of approximately 30 nm that displays a tandem form of the protein A‐derived immunoglobulin G (IgG) Fc‐binding Z domains (denoted as ZZ‐BNC) has been developed for both clustering and oriented immobilization of IgGs on the solid phase of immunosensors. In this study, human IgG1 Fc‐fused vascular endothelial growth factor (VEGF) receptor was immobilized through ZZ‐BNC on the sensor chip of quartz crystal microbalance (ZZ‐BNC‐coating). When compared with direct adsorption and protein A‐coating, the sensor chip showed higher sensitivity (∽46‐ and ∽165‐fold, respectively) and larger ligand‐binding capacity (∽4‐ and ∽18‐fold, respectively). Furthermore, the number of VEGF molecules bound to its receptor increased from 0.20 (direct adsorption) to 2.06 by ZZ‐BNC‐coating, strongly suggesting that ZZ‐BNC reduced the steric hindrance near ligand recognition sites through oriented immobilization. Similarly, the sensitivity and ligand‐binding capacity of leptin and prolactin receptors were both enhanced at a level comparable to that observed for the VEGF receptor. Thus, the combination of ZZ‐BNC and Fc‐fused receptors could significantly improve the function of ligand‐binding assays.
Intersected coexpressed subcube miner: An effective triclustering algorithm

Triclustering techniques extract genes that have similar expression patterns in a set of samples across a set of time points. A challenge in triclustering is to account for both inter-temporal and intra-temporal gene coherence. Other challenges include avoidance of time-dominated and sample-dominated results and detection of time latent triclusters. This paper presents a technique based on order preserving sub-matrices to find a set of triclusters from gene-sample-time data. The technique finds a set of initial modules in each unordered pair of gene-sample planes, which are then extended to final triclusters. We propose a planar similarity measure called PMRS to extend the initial modules to the final triclusters.
Protection with lubeluzole against delayed ischemic brain damage in rats. A quantitative histopathologic study.

BACKGROUND AND PURPOSE Cerebral ischemia may lead to glutamate-induced excitotoxic damage in vulnerable brain areas. Lubeluzole is not an N-methyl-D-aspartate antagonist but prevents postischemic increase in extracellular glutamate concentrations. The present study examined whether lubeluzole, administered after global incomplete ischemia in rats, is capable of preserving the structural integrity of CA1 hippocampus. METHODS Ischemia was induced by bilateral carotid artery occlusion and severe hypotension for a duration of 9 minutes. Delayed neuronal cell death was histologically evaluated 7 days later. This was done by scoring acidophilic cell change and coagulative necrosis and by counting the number of surviving neurons in the CA1 subfield. Experiments were performed according to a paired design (13 animals per treatment group). RESULTS Posttreatment with lubeluzole (0.31 mg/kg i.v. bolus at 5 minutes and 0.31 mg/kg i.v. infusion during 1 hour) resulted in significant neuroprotection. Whereas in the untreated rats there were 42 (median) viable neurons per millimeter CA1 layer in the left and 69 in the right hemisphere, in the drug-treated rats 99 viable neurons per millimeter were found in the left (P = .002) and 113 in the right hemisphere (P = .013). Histological scores, reflecting altered staining properties of the hippocampal cells, correlated strongly with the quantitative data, reflecting the structural integrity of CA1 pyramidal neurons. CONCLUSIONS Lubeluzole, when administered after an ischemic insult in rats, protects vulnerable brain regions against delayed structural injury. The results support the potential clinical use of this new drug in stroke treatment.
The integration of manufacturing and marketing: Impact on combinative competitive capabilities and business performance

A growing number of papers in the areas of both manufacturing and marketing have emphasized the integration of several decisions between the two functions. This paper proposes a structural equation modeling using AMOS to evaluate the relationship between manufacturing and marketing integration, combinative competitive capabilities and business performance. Data were collected from 199 manufacturing firms of various size, location, and industry to develop the instrument and test the relationships in the framework. The results show that two of the three hypothesized direct effects are significant at the 0.01 level. Manufacturing and marketing integration positively influences combinative competitive capabilities and combinative competitive capabilities positively influence business performance. Contrary to conventional wisdom, the influence of manufacturing and marketing integration on business performance is partially confirmed because of the insignificant statistics.