Miracle-dz/UniFAR-FTUs huggingface dataset:
Weakly-Supervised Classification of Pulmonary Nodules Based on Shape Characters

Accurate classification and recognition of pulmonary nodules is an important and key process of Computer-Aided Diagnosis (CAD) system in lung cancer diagnose. Although it has become an increasingly popular research topic, it remains a lot of scientific and technical challenges. Not only do we lack the accurate and effective algorithm of recognition and classification, but also we have difficulties in shape features representation and samples labeling. So this paper presents a weakly-supervised method based on the Partial Label Error-Correcting Output Codes (PL-ECOC) algorithm for solving nodules' classification problem. During the training phase, we use a small amount of labeled pulmonary nodules from experts as weakly-supervised information, for generating a binary classifier. This classifier will be used to compare the Humming distance with the testing samples, in order to obtaining the final category labels. Experiments on Lung Imaging Database Consortium (LIDC) and real-world data sets have shown the efficient performance of our method.
Immigrant Selectivity and Wages: The Evidence for Women

In an effort to extend the analysis of selectivity to female immigrants this paper examines the impact of economic conditions at the time of migration on the subsequent wages of foreign-born women in the United States. In addition the variables chosen to describe the migration decision have been expanded to include the effects of household status and immigration policy. These results are compared to previous results for men and provide additional evidence about how the context of the migration decision affects the subsequent success of immigrants in the United States.The sample for this project comes from the April 1983 Current Population Survey and consists of married native- and foreign-born women between the ages of 16 and 64. (EXCERPT)
Enhanced frequency discrimination near the hearing loss cut-off: a consequence of central auditory plasticity induced by cochlear damage?

Patients with steeply sloping hearing losses of cochlear origin may exhibit enhanced difference limens for frequency (DLFs) near the cut-off frequency (Fc) of their hearing loss. This effect has been related to observations in deafened animals of an over-representation of Fc in the primary auditory cortex. However, alternative interpretations in terms of peripheral mechanisms have not been eliminated. In the present study, we assessed the possible role of two peripheral mechanisms [loudness cues and spontaneous otoacoustic emissions (SOAEs)] in a group of patients with high-frequency hearing loss. We tested first whether the DLF enhancement effect was still observed under conditions where subjects could not rely on loudness cues to perform the frequency discrimination task. To achieve this, we adjusted the nominal level of each stimulus so that it fell on an equal loudness contour measured at very fine (1/8 octave) frequency intervals, and we roved the level of each stimulus over a large range (12 dB). Under these conditions, the DLF enhancement was still observed in all patients; this demonstrates that the effect cannot be explained simply by loudness cues. We then screened the patients for SOAEs to test whether the DLF enhancement effect could be explained by the presence of such emissions in the vicinity of the Fc. None of the patients exhibited SOAEs. Finally, we tested whether the patients had cochlear dead regions, i.e. regions lacking functional inner hair cells and/or auditory nerve fibres. Using a refined version of a non-invasive clinical test for the identification of dead regions, we assessed the presence of such regions in fine frequency steps (1/4 octave) up to very high frequencies. All of the patients had cochlear dead regions. The first two findings support the hypothesis that DLF enhancement is due to injury-induced central reorganization in the auditory system. The last one is consistent with neurophysiological data in animals, which suggest that complete deprivation from auditory input at certain cochlear sites may be a necessary condition for the occurrence of injury-induced cortical reorganization.
Query Processing in a Fragmented Relational Distributed System: Mermaid

This paper describes the query optimizer of the Mermaid system which provides a user with a unified view of multiple preexisting databases which may be stored under different DBMS's. The algorithm is designed for databases which may contain replicated or fragmented relations and for users who are primarily making interactive, ad hoc queries. Although the implementation of the algorithm is a front-end system, not an integrated distributed DBMS, it should be applicable to a distributed DBMS also.
Multi-functional double mode inverter for power quality enhancement in smart-grid applications

This paper introduces a new multi-functional double mode inverter (MFDMI) scheme, which is able to operate under a variety of operational conditions for aggregation of PV-based renewable energy resources. Detecting islanded situation within a new and fast approach, regulating the voltage in the islanded mode, smooth transition between islanded and grid-tied (GT) modes, injecting both active and reactive powers to the grid in addition to compensating the harmonics from nonlinear loads are beyond the most notable functionalities of the proposed framework. Technically, we exploit a combinational control scheme formed by instantaneous power theory, vector-control and a proportional integral resonant (PIR) controller to address the required functionalities. To deal with the low output power issue, photovoltaic (PV) cells are aggregated through a high gain DC-DC floating interleaved boost converter (FIBC). Moreover, a battery back-up module with bidirectional DC-DC floating interleaved buck-boost converter (FIBBC) is used to improve the system reliability and dispatch ability. The effectiveness of the proposed framework has been first verified within a comprehensive PSIM simulation results and then has been examined under realistic situations using the real-time simulator OPAL-RT with DSP modules (hardware in the loop) for a broad range of conditions and within different practical scenarios.
A Semisupervised Segmentation Model for Collections of Images

In this paper, we consider the problem of segmentation of large collections of images. We propose a semisupervised optimization model that determines an efficient segmentation of many input images. The advantages of the model are twofold. First, the segmentation is highly controllable by the user so that the user can easily specify what he/she wants. This is done by allowing the user to provide, either offline or interactively, some (fully or partially) labeled pixels in images as strong priors for the model. Second, the model requires only minimal tuning of model parameters during the initial stage. Once initial tuning is done, the setup can be used to automatically segment a large collection of images that are distinct but share similar features. We will show the mathematical properties of the model such as existence and uniqueness of solution and establish a maximum/minimum principle for the solution of the model. Extensive experiments on various collections of biological images suggest that the proposed model is effective for segmentation and is computationally efficient.
Measuring the Dynamics of Global Business Cycle Connectedness

Using a connectedness-measurement technology fundamentally grounded in modern network theory, we measure real output connectedness for a set of six developed countries, 1962-2010. We show that global connectedness is sizable and time-varying over the business cycle, and we study the nature of the time variation relative to the ongoing discussion about the changing nature of the global business cycle. We also show that connectedness corresponding to transmissions to others from the United States and Japan is disproportionately important.
A Simple Method for Estimating the Weight Decay Parameter

(modified abstract: does not include equations) A new method for determining the optimal weight decay parameter is suggested. We demonstrate the method on a large set of data sets, both synthetic and real-life, and show that it is essentially as good an estimator for the optimal as the standard search method. THis new method is several orders of magnitude faster than the standard method.
The long-run effects of a permanent change in defense purchases

In this article, Mark A. Wynne explores how a permanent reduction in defense spending might affect the average U.S. household. He finds that, in the long run, Americans will reap a peace dividend. For example, if Congress reduces annual defense spending from 6 percent of gross national product to 3 percent, in the long run private consumption as a share of GNP could rise 3 percentage points. In the short run, some businesses and households will sustain losses. Over time, however, the economy will reabsorb the resources freed by lower defense-related production and will expand production for private consumption. ; Underlying Wynne's analysis is the assumption that Congress will use the funds saved on defense spending either to lower taxes or to reduce the federal deficit. Wynne develops a simple empirical model to explain the relationship between the share of GNP spent on private consumption and the share spent on defense over the past one hundred years.
Using constant traffic to specific IP destinations for detecting spoofed MAC addresses in Local Area Networks

This paper addresses the issue of detecting spoofed MAC addresses in a Local Area Network using constant traffic to specific IP destinations, as a fingerprint of the authorized station. In the chapters that follow, the authors describe how to determine this fingerprint and then how can it be used by applications to monitor network traffic in order to determine if one network station is or is not who it claims to be.
Comparative Analysis of DNA Nanoparticles and AAVs for Ocular Gene Delivery

Gene therapy is a critical tool for the treatment of monogenic retinal diseases. However, the limited vector capacity of the current benchmark delivery strategy, adeno-associated virus (AAV), makes development of larger capacity alternatives, such as compacted DNA nanoparticles (NPs), critical. Here we conduct a side-by-side comparison of self-complementary AAV and CK30PEG NPs using matched ITR plasmids. We report that although AAVs are more efficient per vector genome (vg) than NPs, NPs can drive gene expression on a comparable scale and longevity to AAV. We show that subretinally injected NPs do not leave the eye while some of the AAV-injected animals exhibited vector DNA and GFP expression in the visual pathways of the brain from PI-60 onward. As a result, these NPs have the potential to become a successful alternative for ocular gene therapy, especially for the multitude of genes too large for AAV vectors.
Enhancement of the security of RBS for wireless sensor networks

Time synchronization is one of the fundamental techniques for the wireless sensor networks to obtain the real-time effective information. The security of this technology is becoming increasingly important. In this paper, we analyze the security of RBS, the synchronization algorithm in WSN, point out the potential vulnerabilities existing in the algorithm, and propose optimization on security for the algorithm. Simulation result shows improved algorithm not only defends external attacks effectively, but greatly reduces the effects of internal attack.
Automatic problem size sensitive task partitioning on heterogeneous parallel systems

In this paper we propose a novel approach which automatizes task partitioning in heterogeneous systems. Our framework is based on the Insieme Compiler and Runtime infrastructure. The compiler translates a single-device OpenCL program into a multi-device OpenCL program. The runtime system then performs dynamic task partitioning based on an offline-generated prediction model. In order to derive the prediction model, we use a machine learning approach that incorporates static program features as well as dynamic, input sensitive features. Our approach has been evaluated over a suite of 23 programs and achieves performance improvements compared to an execution of the benchmarks on a single CPU and a single GPU only.
An assessment of antineutrino detection as a tool for monitoring nuclear explosions

The antineutrino is the only real‐time inherently nuclear signature from a fission explosion that propagates great distances through air, water, and ground. The size and sensitivity of antineutrino detectors has increased dramatically in the last decade, and will continue to do so in the next, thanks in part to the renewed interest in neutrino physics brought on by the mounting evidence that neutrinos may have mass. The evolution of antineutrino detectors, and the evident interest of the signature as a means for monitoring nuclear tests motivates this review of the capabilities of existing and possible future detectors as test ban verification tools. Existing liquid scintillator ion‐ization detectors, operating a few tens of meters below the Earth's surface and containing a few thousand tons of active material, could be used to monitor an area of a few square kilometers for nuclear explosions at the 1 kt level. Purified water Cerenkov detectors of sizes comparable to existing detectors (50,000 m3) could be used to detect 1 kt explosions at distances of a few tens of kilometers. The addition of neutron‐absorbing dopants such as sodium chloride or gadolinium to purified water would allow range extension out to approximately 1000 km for sensitivity to a pulse of 10 antineutrino events from a 1 kt explosion. Beyond 1000 km, backgrounds from the world's nuclear reactors would become prohibitively large (at this assumed signal strength). The engineering hurdles for such detectors would be formidable. The size of a doped detector operating at the 100 km range, suitable for cooperative monitoring of existing nuclear test sites, is about 60 times that of the largest existing water detector, and would require a factor of several dozen more photomultiplier tubes than what is now used in large scale physics experiments. Capital costs (primarily phototubes, excavation and the cost of maintaining high radiopurity) would amount to several billion dollars, even for a detector at this modest range. Detectors sensitive to a 1 kt explosion at only a few kilometer distance would still cost tens of millions of dollars. Due to these limitations, practical applications of this method for nuclear test detection are almost certainly out of reach for the foreseeable future.
Whole Body Muscle Activity during the FIFA 11+ Program Evaluated by Positron Emission Tomography

Purpose This study investigated the effect of the FIFA 11+ warm-up program on whole body muscle activity using positron emission tomography. Methods Ten healthy male volunteers were divided into a control group and a group that performed injury prevention exercises (The 11+). The subjects of the control group were placed in a sitting position for 20 min and 37 MBq of 18F-fluorodeoxyglucose (FDG) was injected intravenously. The subjects then remained seated for 45 min. The subjects of the exercise group performed part 2 of the 11+for 20 min, after which FDG was injected. They then performed part 2 of the 11+for 20 min, and rested for 25 min in a sitting position. Positron emission tomography-computed tomography images were obtained 50 min after FDG injection in each group. Regions of interest were defined within 30 muscles. The standardized uptake value was calculated to examine the FDG uptake of muscle tissue per unit volume. Results FDG accumulation within the abdominal rectus, gluteus medius and minimus were significantly higher in the exercise group than in the control group (P<0.05). Conclusion The hip abductor muscles and abdominal rectus were active during part 2 of the FIFA 11+ program.
Proteases in Malaria Parasites - A Phylogenomic Perspective

Malaria continues to be one of the most devastating global health problems due to the high morbidity and mortality it causes in endemic regions. The search for new antimalarial targets is of high priority because of the increasing prevalence of drug resistance in malaria parasites. Malarial proteases constitute a class of promising therapeutic targets as they play important roles in the parasite life cycle and it is possible to design and screen for specific protease inhibitors. In this mini-review, we provide a phylogenomic overview of malarial proteases. An evolutionary perspective on the origin and divergence of these proteases will provide insights into the adaptive mechanisms of parasite growth, development, infection, and pathogenesis.B
Simulator and benchmark for RFID anti-collision evaluation

This paper proposes an RFID benchmark and simulator in order to evaluate anti-collision algorithms. The proposed suite was specially developed to the MAC layer evaluation since to our knowledge there is no standard on RFID anti-collision simulator software. Although some simulators for RFID networks have been proposed, none of them are designed to the MAC layer performance evaluation. This paper, however, does present the design and validation of an RFID benchmark suite based on the EPCGlobal Class 1 Generation 2 standard which can help researchers to provide fair and fast comparisons between the existing algorithms.
The Role of Estrogen in Schizophrenia: Implications for Schizophrenia Practice Guidelines for Women

Objective: The objective of this paper is to integrate what is known about estrogen effects on symptoms and treatment response into a global understanding of schizophrenia. The aim is to expand Canadian schizophrenia guidelines to include the specific needs of women. Method: We searched the Medline database; keywords included estrogen, estrogen replacement therapy, schizophrenia, psychosis, treatment, tardive dyskinesia (TD), and women. We examined reference lists from relevant articles to ensure that our review was complete. We review the evidence for the effects of estrogen in schizophrenia and we make recommendations for the next revision of official practice guidelines. Results: The epidemiologic evidence suggests that, relative to men, women show an initial delay in onset age of schizophrenia, with a second onset peak after age 44 years. This points to a protective effect of estrogen, confirming animal research that has documented both neurotrophic and neuromodulatory effects. Clinical research results indicate that symptoms in women frequently vary with the menstrual cycle, worsening during low estrogen phases. Pregnancy is often, though not always, a less symptomatic time for women, but relapses are frequent postpartum. Some work suggests that in the younger age groups women require lower antipsychotic dosages than men but that following menopause they require higher dosages. Estrogen has been used effectively as an adjunctive treatment in women with schizophrenia. Estrogen may also play a preventive role in TD. Conclusions: Symptom evaluation and diagnosis in women needs to take hormonal status into account. Consideration should be given to cycle-modulated neuroleptic dosing and to careful titration during pregnancy, postpartum, and at menopause. We recommend that discretionary use of newer neuroleptic medication and adjuvant estrogen therapy be considered.
SIRC-Rep, a Multiple Isolation Level Protocol for Middleware-based Data Replication Architectures ∗

One of the weaknesses of replicated protocols, compared to centralized ones, is that they are unable to manage concurrent execution of transactions at different isolation levels. In the last years, some theoretical works related to this research line have appeared but none of them has proposed and implemented a real replication protocol with support to multiple isolation levels. This paper takes advantage of our MADIS middleware and one of its implemented Snapshot Isolation protocols to design and implement the SIRC-Rep, a protocol that is able to execute concurrently both Generalized Snapshot Isolation (SI) and Read Committed (RC) transactions. We have also made a performance analysis to show how this kind of protocols can improve the system performance and decrease the transaction abortion rate in applications that do not require the strictest isolation level in every transaction.
Structuring Cognitive Information for Software Complexity Measurement

Cognitive complexity of software has emerged as an interesting research area recently with the growing studies in Cognitive Informatics disciplines. Cognitive complexity measurement attempts to quantify the software from the perspective of the difficulty for human brain to process and comprehend the software, in order to enable more precise prediction of the critical information about testability, reliability, and maintainability, as well as the effort spent in the software project. Cognitive Informatics theories suggest that cognitive complexity of software depends on fundamental factors such as inputs, outputs, loops/branches structure, and number of operators and operands. Analysis in this paper shows the significant flaw of current cognitive complexity measures that they quantify the factors without considering the dependencies among them. We therefore propose a new method to solve this problem by structuring the factors. The proposed measure was evaluated comparatively to existing metrics, and also proven by satisfying all nine Weyuker's properties.
Stability Analysis of Grid-Connected Inverter With LCL Filter Adopting a Digital Single-Loop Controller With Inherent Damping Characteristic

The stability problem of the grid-connected inverter with LCL filter adopting a digital single-loop controller without extra damping resistance is analyzed. The digital single-loop control based on the grid-side current feedback can attenuate the resonance introduced by LCL filters due to the inherent damping characteristic embedded in the control loop. The stability analysis is performed by means of a Nyquist diagram in the discrete domain and to provide a general design direction for filter and controller. The quantitative relationship of ratios of LCL resonance angular frequency to control frequency and controller parameters on the system stability is investigated. It is derived that the system would obtain preferable stability margin when the ratio is located at a certain range. The theoretical analyses are validated by experimental tests based on a 5-kW single-phase inverter laboratory prototype.
An Algebraic Framework for Compositional Program Analysis

The purpose of a program analysis is to compute an abstract meaning for a program which approximates its dynamic behaviour. A compositional program analysis accomplishes this task with a divide-and-conquer strategy: the meaning of a program is computed by dividing it into sub-programs, computing their meaning, and then combining the results. Compositional program analyses are desirable because they can yield scalable (and easily parallelizable) program analyses. This paper presents algebraic framework for designing, implementing, and proving the correctness of compositional program analyses. A program analysis in our framework defined by an algebraic structure equipped with sequencing, choice, and iteration operations. From the analysis design perspective, a particularly interesting consequence of this is that the meaning of a loop is computed by applying the iteration operator to the loop body. This style of compositional loop analysis can yield interesting ways of computing loop invariants that cannot be defined iteratively. We identify a class of algorithms, the so-called path-expression algorithms [Tarjan1981,Scholz2007], which can be used to efficiently implement analyses in our framework. Lastly, we develop a theory for proving the correctness of an analysis by establishing an approximation relationship between an algebra defining a concrete semantics and an algebra defining an analysis.