Miracle-dz/UniFAR-FTUs huggingface dataset:
The Infinite Push: A New Support Vector Ranking Algorithm that Directly Optimizes Accuracy at the Absolute Top of the List

Ranking problems have become increasingly important in machine learning and data mining in recent years, with applications ranging from information retrieval and recommender systems to computational biology and drug discovery. In this paper, we describe a new ranking algorithm that directly maximizes the number of relevant objects retrieved at the absolute top of the list. The algorithm is a support vector style algorithm, but due to the different objective, it no longer leads to a quadratic programming problem. Instead, the dual optimization problem involves l1, ∞ constraints; we solve this dual problem using the recent l1, ∞ projection method of Quattoni et al (2009). Our algorithm can be viewed as an l∞-norm extreme of the lp-norm based algorithm of Rudin (2009) (albeit in a support vector setting rather than a boosting setting); thus we refer to the algorithm as the ‘Infinite Push’. Experiments on real-world data sets confirm the algorithm’s focus on accuracy at the absolute top of the list.
New Summary Measures of Population Health and Well-Being for Implementation by Health Plans and Accountable Care Organizations

Health plans and accountable care organizations measure many indicators of patient health, with standard metrics that track factors such as patient experience and cost. They lack, however, a summary measure of the third leg of the Triple Aim, population health. In response, HealthPartners has developed summary measures that align with the recommendations of the For the Public’s Health series of reports from the Institute of Medicine. (The series comprises the following 3 reports: For the Public’s Health: Investing in a Healthier Future, For the Public’s Health: Revitalizing Law and Policy to Meet New Challenges, and For the Public’s Health: The Role of Measurement in Action and Accountability.) The summary measures comprise 3 components: current health, sustainability of health, and well-being. The measure of current health is disability-adjusted life years (DALYs) calculated from health care claims and death records. The sustainability of health measure comprises member reporting of 6 behaviors associated with health plus a clinical preventive services index that indicates adherence to evidence-based preventive care guidelines. Life satisfaction represents the summary measure of subjective well-being. HealthPartners will use the summary measures to identify and address conditions and factors that have the greatest impact on the health and well-being of its patients, members, and community. The method could easily be implemented by other institutions and organizations in the United States, helping to address a persistent need in population health measurement for improvement.
Conceptualizing human resource management in the gig economy

Purpose Although it is transforming the meaning of employment for many people, little is known about the implications of the gig economy for human resource management (HRM) theory and practice. The purpose of this paper is to conceptually explore the notion of HRM in the gig economy, where intermediary platform firms design and implement HRM activities while simultaneously trying to avoid the establishment of employment relationships with gig workers. Design/methodology/approach To conceptualize HRM in the gig economy, the authors offer a novel ecosystem perspective to develop propositions on the role and implementation of HRM activities in the gig economy. Findings The authors show that HRM activities in the gig economy are designed to govern platform ecosystems by aligning the multilateral exchanges of three key gig economy actors: gig workers, requesters and intermediary platform firms, for ensuring value co-creation. The authors argue that the implementation of HRM activities in the gig economy is contingent on the involvement and activities of these gig economy actors. This means that they are not mere recipients of HRM but also actively engaged in, and needed for, the execution of HRM activities. Originality/value The study contributes to research by proposing a theoretical framework for studying the design of HRM activities, and their implementation, in the gig economy. From this framework, the authors derive directions for future research on HRM in the gig economy.
Combining Multiple Optimization Runs with Optimal Dependency Trees

Abstract : When trying to solve a combinatorial optimization problem, often multiple algorithms and/or multiple runs of the same algorithm are used in order to find multiple local minima. The information gained from previous search runs is commonly discarded when selecting initialization points for future runs. We present a method which uses information from previous runs to determine promising starting points for future searches. Our algorithm, termed COMIT, models inter-parameter dependencies present in the previously found high-evaluation solutions. COMIT incrementally learns optimal dependency trees that model the pairwise dependencies in a set of good solutions found in previous searches. COMIT then samples the probability distributions modeled by these trees to generate new starting points for future searches. This algorithm has been successfully applied to jobshop scheduling, traveling salesman, knapsack, rectangle packing, and bin-packing problems.
Multiview Face Detection and Registration Requiring Minimal Manual Intervention

Most face recognition systems require faces to be detected and localized a priori. In this paper, an approach to simultaneously detect and localize multiple faces having arbitrary views and different scales is proposed. The main contribution of this paper is the introduction of a face constellation, which enables multiview face detection and localization. In contrast to other multiview approaches that require many manually labeled images for training, the proposed face constellation requires only a single reference image of a face containing two manually indicated reference points for initialization. Subsequent training face images from arbitrary views are automatically added to the constellation (registered to the reference image) based on finding the correspondences between distinctive local features. Thus, the key advantage of the proposed scheme is the minimal manual intervention required to train the face constellation. We also propose an approach to identify distinctive correspondence points between pairs of face images in the presence of a large amount of false matches. To detect and localize multiple faces with arbitrary views, we then propose a probabilistic classifier-based formulation to evaluate whether a local feature cluster corresponds to a face. Experimental results conducted on the FERET, CMU, and FDDB datasets show that our proposed approach has better performance compared to the state-of-the-art approaches for detecting faces with arbitrary pose.
Runtime feedback in a meta-tracing JIT for efficient dynamic languages

Meta-tracing JIT compilers can be applied to a variety of different languages without explicitly encoding language semantics into the compiler. So far, they lacked a way to give the language implementor control over runtime feedback. This restricted their performance. In this paper we describe the mechanisms in PyPy's meta-tracing JIT that can be used to control runtime feedback in language-specific ways. These mechanisms are flexible enough to express classical VM techniques such as maps and runtime type feedback.
Multi-Instance Classification by Max-Margin Training of Cardinality-Based Markov Networks

We propose a probabilistic graphical framework for multi-instance learning (MIL) based on Markov networks. This framework can deal with different levels of labeling ambiguity (i.e., the portion of positive instances in a bag) in weakly supervised data by parameterizing cardinality potential functions. Consequently, it can be used to encode different cardinality-based multi-instance assumptions, ranging from the standard MIL assumption to more general assumptions. In addition, this framework can be efficiently used for both binary and multiclass classification. To this end, an efficient inference algorithm and a discriminative latent max-margin learning algorithm are introduced to train and test the proposed multi-instance Markov network models. We evaluate the performance of the proposed framework on binary and multi-class MIL benchmark datasets as well as two challenging computer vision tasks: cyclist helmet recognition and human group activity recognition. Experimental results verify that encoding the degree of ambiguity in data can improve classification performance.
Towards the Genetic Programming of a Billion Neuron Artificial Brain which Grows/Evolves at Electronic Speeds in a Cellular Automata Machine

This paper reports on progress made in the first year of an 8 year research project which aims to build/grow/evolve (at electronic speeds) an artificial brain which contains a billion neurons inside a Cellular Automata Machine (CAM). This paper introduces the CAM-Brain concept, discusses some implementation issues, and justifies how it should be possible to build artificial brains containing a billion neurons by the year 2001. If successful, the CAMBrain research project should provide a powerful, if not revolutionary, new tool for the study of behavior, because the project intends to evolve a CAMBrain which is capable of controlling roughly 1000 "behaviors" in a robot kitten. Since it is unlikely that all these behaviors will be evolved in one step, the CAM-Brain project will need to focus its attention upon the issue of "incremental evolution", i.e. how does one add neural modules to an already functional nervous system, so as to increase its functionality.
P-uniform circuit complexity

Much complexity-theoretic work on parallelism has focused on the class NC, which is defined in terms of logspace-uniform circuits. Yet P-uniform circuit complexity is in some ways a more natural setting for studying feasible parallelism. In this paper, P-uniform NC (PUNC) is characterized in terms of space-bounded AuxPDAs and alternating Turing Machines with bounded access to the input. The notions of general-purpose and special-purpose computation are considered, and a general-purpose parallel computer for PUNC is presented. It is also shown that NC = PUNC if all tally languages in P are in NC; this implies that the NC = PUNC question and the NC = P question are both instances of the ASPACE(<italic>S</italic>(<italic>n</italic>)) = ASPACE,TIME(<italic>S</italic>(<italic>n</italic>), <italic>S</italic>(<italic>n</italic>)<supscrpt><italic>o</italic>(1)</supscrpt>) question. As a corollary, it follows that NC = PUNC implies PSPACE = DTIME(2<supscrpt><italic>no</italic>(1)</supscrpt>).
CHAPTER 5 Free-living microorganisms

In addition to microorganisms introduced to recreational waters through human or animal faecal contamination (see chapter 4), a number of pathogenic microorganisms are indigenous to such areas or, (like the leptospires) once introduced are capable of colonizing the environment. This chapter describes the principal freeliving microorganisms of concern; the diseases that they may cause associated with recreational water use; and potential control measures.
Bigh3 silencing increases retinoblastoma tumor growth in the murine SV40-TAg-Rb model

BIGH3, a secreted protein of the extracellular matrix interacts with collagen and integrins on the cell surface. BIGH3 can have opposing functions in cancer, acting either as tumor suppressor or promoter by enhancing tumor progression and angiogenesis. In the eye, BIGH3 is expressed in the cornea and the retinal pigment epithelium and could impact on the development of retinoblastoma, the most common paediatric intraocular neoplasm. Retinoblastoma initiation requires the inactivation of both alleles of the RB1 tumor suppressor gene in the developing retina and tumor progression involves additional genomic changes. To determine whether BIGH3 affects retinoblastoma development, we generated a retinoblastoma mouse model with disruption of the Bigh3 genomic locus. Bigh3 silencing in these mice resulted in enhanced tumor development in the retina. A decrease in apoptosis is involved in the initial events of tumorigenesis, followed by an increased activity of the pro-survival ERK pathway as well as an upregulation of cyclin-dependent kinases (CDKs). Taken together, these data suggest that BIGH3 acts as a tumor suppressor in the retina.
Phonological features in discriminative classification of dysarthric speech

In an attempt to overcome problems associated with articulatory limitations and generative models, this work considers the use of phonological features in discriminative models for disabled speech. Specifically, we train feed-forward and recurrent neural networks, and radial basis and sequence-kernel support vector machines to abstractions of the vocal tract, and apply these models to phone recognition on dysarthric speech. The results show relative error reduction of between 1.5% and 10.9% with this approach against standard hidden Markov modeling, and increases in accuracy with speaker intelligibility across all classifiers. This work may be applied within components of assistive software for speakers with dysarthria.
Surface Stereo for Shallow Underwater Scenes

Imaging underwater scenes with a surface based stereo system allows for reconstruction where having an underwater system is unsafe or impractical. Refraction and other optical phenomena complicate the reconstruction process, and here we analyze these factors and propose techniques for mitigating problems. Existing techniques are of limited use in practical settings, or have ignored physical properties which complicate the reconstruction task. We demonstrate that physical properties can be used to aid in reconstruction and surface modeling using optical and thermal properties of water. In this work we analyze these properties and provide a grounded example with ecological and geophysical applications.
An Efficient Next Hop Selection Algorithm for Multi-Hop Body Area Networks

Body Area Networks (BANs) consist of various sensors which gather patient’s vital signs and deliver them to doctors. One of the most significant challenges faced, is the design of an energy-efficient next hop selection algorithm to satisfy Quality of Service (QoS) requirements for different healthcare applications. In this paper, a novel efficient next hop selection algorithm is proposed in multi-hop BANs. This algorithm uses the minimum hop count and a link cost function jointly in each node to choose the best next hop node. The link cost function includes the residual energy, free buffer size, and the link reliability of the neighboring nodes, which is used to balance the energy consumption and to satisfy QoS requirements in terms of end to end delay and reliability. Extensive simulation experiments were performed to evaluate the efficiency of the proposed algorithm using the NS-2 simulator. Simulation results show that our proposed algorithm provides significant improvement in terms of energy consumption, number of packets forwarded, end to end delay and packet delivery ratio compared to the existing routing protocol.
Polyubiquitin Is Required for Growth, Development and Pathogenicity in the Rice Blast Fungus Magnaporthe oryzae

Protein ubiquitination, which is highly selective, regulates many important biological processes including cellular differentiation and pathogenesis in eukaryotic cells. Here, we integrated pharmacological, molecular and proteomic approaches to explore the role of ubiquitination in Magnaporthe oryzae, the leading fungal disease of rice world-wide. Inhibition of ubiquitin-mediated proteolysis using the 26S proteasome inhibitor, Bortezomib, significantly attenuated conidia germination, appressorium formation and pathogenicity in M. oryzae. Gene expression analysis revealed that many genes associated with protein ubiquitination were developmentally regulated during conidia germination. Only a few, including a polyubiquitin encoding gene, MGG_01282, were more abundantly expressed during appressorium formation and under nitrogen starvation. Targeted gene deletion of MGG_01282, in addition to a significant reduction in protein ubiquitination as determined by immuno blot assays, resulted in pleiotropic effects on M. oryzae including reduced growth and sporulation, abnormal conidia morphology, reduced germination and appressorium formation, and the inability to cause disease. Mutants were also defective in sexual development and were female sterile. Using mass spectrometry, we identified 63 candidate polyubiquitinated proteins under nitrogen starvation, which included overrepresentation of proteins involved in translation, transport and protein modification. Our study suggests that ubiquitination of target proteins plays an important role in nutrient assimilation, development and pathogenicity of M. oryzae.
Observed relationships of ozone air pollution with temperature and emissions

Higher temperatures caused by increasing greenhouse gas concentrations are predicted to exacerbate photochemical smog if precursor emissions remain constant. We perform a statistical analysis of 21 years of ozone and temperature observations across the rural eastern U.S. The climate penalty factor is defined as the slope of the ozone/temperature relationship. For two precursor emission regimes, before and after 2002, the climate penalty factor was consistent across the distribution of ozone observations. Prior to 2002, ozone increased by an average of ∼3.2 ppbv/°C. After 2002, power plant NOx emissions were reduced by 43%, ozone levels fell ∼10%, and the climate penalty factor dropped to ∼2.2 ppbv/°C. NOx controls are effective for reducing photochemical smog and might lessen the severity of projected climate change penalties. Air quality models should be evaluated against these observations, and the climate penalty factor metric may be useful for evaluating the response of ozone to climate change.
The Compulsory Education Law in Israel and Liquidity Constraints

Israel's Compulsory Education Law was amended several times in the 1970s, changes that were reflected in an increase in the number of years of both compulsory education and free education. This process caused a significant reduction in the school dropout rate among students from ninth to twelfth grades, principally among Sephardic (Oriental) Jews (Jews of Asian or North- African origin) and the non-Jewish population. The fact that compulsory schooling and free schooling were dealt with separately during these years makes it possible to examine what effective constraint deters some individuals from continuing their studies. To examine this question, I compared the 'compulsory effect' to the 'free effect' on the duration of studies and the return to education derived from each of these amendments. It was found that the extra years of compulsory schooling caused a steep fall in the dropout rate in the ninth and tenth grades that had been included in the provisions of the Law, and a moderate decline in dropout rates in the following grades (eleventh and twelfth), which were not compulsory or free at that time. The introduction of free education in the eleventh and twelfth grades also contributed to reducing dropout rates, mostly among female students. It was also found that the return in terms of salary derived from the added years of compulsory education did not differ from the return derived from the added years of free education, and that they both resembled the return to the years of high-school education estimated using the OLS method. These findings indicate that a liquidity constraint deters some individuals from making an optimal investment in their human capital. According to the findings, this constraint is not only due to the need to pay tuition, but also apparently derives from the family decision making framework, which does not necessarily take into account the benefit that the individual will derive from acquiring additional education.
Differential Cataractogenic Potency of TGF-/ 3 X ,-j 82 , and-/ 33 and Their Expression in the Postnatal Rat Eye

METHODS. Lens epithelial explants and whole lenses from weanling rats were cultured with TGF-/3,, TGF-j32, or TGF-j33 at concentrations ranging from 0.025 ng/ml to 4 ng/ml for 3 to 5 days. Cataractous changes were monitored daily by phase contrast microscopy and by immunofluorescent detection of cataract markers a-smooth muscle actin and type I collagen. Expression of TGF-/3 was studied by immunofluorescence and in situ hybridization on eye sections from neonatal and weanling rats.
Enhancing Event Descriptions through Twitter Mining

We describe a simple IR approach for linking news about events, detected by an event extraction system, to messages from Twitter (tweets). In particular, we explore several methods for creating event-specific queries for Twitter and provide a quantitative and qualitative evaluation of the relevance and usefulness of the information obtained from the tweets. We showed that methods based on utilization of word co-occurrence clustering, domain-specific keywords and named entity recognition improve the performance with respect to a basic approach.
A SLIT-LOADED NOTCH-CUT PATCH ANTENNA FOR BROADBAND APPLICATIONS H

In this paper we have Investigated various meandering techniques for obtaining compact and broadband patch antenna. We have designed a slit-loaded notch-cut patch antenna based on investigations. The antenna patch is fed by coaxial feed. Meandering techniques and the new design are simulated in HFSS environment. Results show good return loss for new design.
Exploring Architecture-Based Reliability Analysis of Current Multi-layered Web Applications

Web applications architecture evolved from simple web sites add-ons to complex n-layer applications. However, identifying components in this domain is usually a subjective task, as web applications typically comprise web pages, scripts, forms, applets, servlets or simply web objects. As a result of this subjectivity, a component-based life-cycle might reflect on inconsistencies not only on a clear definition of web components, but also on the process development itself. In addition, it is hard to identity which components are more critical according to specific tasks, such that developers could spend more time to improve their design. That quality certainly comprises reliability, availability and security, summing up as dependability attributes. The application of architecture-based reliability analysis techniques in various domains have contributed to solve those problems. However, very little has been done towards the assessment of current web applications in a real-life setting. In this work, we explore the feasibility to apply an architecture-based reliability analysis method in a real-life web application. Our preliminary results show the potential use of this method for the web applications domain, with a considerably accuracy.