Miracle-dz/UniFAR-FTUs huggingface dataset:
On the measurement of test collection reliability

The reliability of a test collection is proportional to the number of queries it contains. But building a collection with many queries is expensive, so researchers have to find a balance between reliability and cost. Previous work on the measurement of test collection reliability relied on data-based approaches that contemplated random what if scenarios, and provided indicators such as swap rates and Kendall tau correlations. Generalizability Theory was proposed as an alternative founded on analysis of variance that provides reliability indicators based on statistical theory. However, these reliability indicators are hard to interpret in practice, because they do not correspond to well known indicators like Kendall tau correlation. We empirically established these relationships based on data from over 40 TREC collections, thus filling the gap in the practical interpretation of Generalizability Theory. We also review the computation of these indicators, and show that they are extremely dependent on the sample of systems and queries used, so much that the required number of queries to achieve a certain level of reliability can vary in orders of magnitude. We discuss the computation of confidence intervals for these statistics, providing a much more reliable tool to measure test collection reliability. Reflecting upon all these results, we review a wealth of TREC test collections, arguing that they are possibly not as reliable as generally accepted and that the common choice of 50 queries is insufficient even for stable rankings.
An early stopping criterion for LDPC decoder based on CMMB standard

In this paper, we present an early stopping criterion for low density parity check (LDPC) codes decoding based on Chinese Mobile Multimedia Broadcasting standard (CMMB) while preserving a good performance. To reduce the average number of decoding iterations, it is crucial to detect undecodable blocks at the beginning of the decoding process. The proposed stopping criterion for undecodable blocks is based on the estimation of the variable node reliability (VNR) and this stopping criterion has to be switched off when VNR passes a threshold. Simulation results show that the proposed approach can effectively reduce the average number of iterations at low SNR region where most blocks are undecodable, meanwhile the performance loss at all SNR region is negligible.
A Study on MVDR Beamforming Applied to an ESPAR Antenna

The adaptive beamforming algorithm-minimum variance distortionless response (MVDR) has been studied based on the electronically steerable parasitic array radiator (ESPAR) antenna. The ESPAR antenna uses a single radio-frequency (RF) front end, and its beamforming is achieved by adjusting reactance loads of parasitic elements coupled to the central active element. In the proposed beamforming method, the MVDR beamformer optimizes weights applied to outputs of beams. The optimization problem is formulated as a second-order-cone programming (SOCP) problem including a Euclidean distance metric to approximate the optimal equivalent weight vector to a feasible solution. Then the ESPAR beampattern design strategy iterates between the SOCP problem and a simple projection of reactance loads. The simulations show that the proposed MVDR beamforming method based on an ESPAR antenna gives a beam steering at the desired direction and placing nulls at the interfering directions, and it converges fast. However, when the desired source is close to the interferer, the output signal-to-interference-plus-noise ratio (SINR) degrades and where we use the interference-plus-noise sample covariance matrix to improve the beamforming performance.
Evolution of nonsteroidal anti-inflammatory drugs (NSAIDs): cyclooxygenase (COX) inhibition and beyond.

PURPOSE NSAIDs constitute an important class of drugs with therapeutic applications that have spanned several centuries. Treatment of inflammatory conditions such as rheumatoid arthritis (RA) and osteoarthritis (OA) starting from the classic drug aspirin to the recent rise and fall of selective COX-2 inhibitors has provided an enthralling evolution. Efforts to discover an ultimate magic bullet to treat inflammation continues to be an important drug design challenge. This review traces the origins of NSAIDs, their mechanism of action at the molecular level such as cyclooxygenase (COX) inhibition, development of selective COX-2 inhibitors, their adverse cardiovascular effects, and some recent developments targeted to the design of effective anti-inflammatory agents with reduced side effects. METHODS Literature data is presented describing important discoveries pertaining to the sequential development of classical NSAIDs and then selective COX-2 inhibitors, their mechanism of action, the structural basis for COX inhibition, and recent discoveries. RESULTS A brief history of the development of NSAIDs and the market withdrawal of selective COX-2 inhibitors is explained, followed by the description of prostaglandin biosynthesis, COX isoforms, structure and function. The structural basis for COX-1 and COX-2 inhibition is described along with methods used to evaluate COX-1/COX-2 inhibition. This is followed by a section that encompasses the major chemical classes of selective COX-2 inhibitors. The final section describes briefly some of the recent advances toward developing effective anti-inflammatory agents such as nitric oxide donor NO-NSAIDs, dual COX/LOX inhibitors and anti-TNF therapy. CONCLUSIONS A great deal of progress has been made toward developing novel anti-inflammatory agents. In spite of the tremendous advances in the last decade, the design and development of a safe, effective and economical therapy for treating inflammatory conditions still presents a major challenge.
Spatial resolution enhancement for hyperspectral image based on wavelet Bayesian fusion

The fusion of multispectral (MS) and hyperspectral (HS) images to enhance the spatial resolution of the latter is considered in this paper, and a Bayesian estimation based fusion technique is proposed. The technique works in the wavelet domain, assuming a joint normal model for the images and a blurring and additive noise imaging model for the HS image. To keep the calculation feasible, an appropriately simplified estimation strategy is also proposed. In the simulated experiment, the technique is validated and also compared to its counterpart in the image domain.
Absolute Polar Duty Cycle Division Multiplexing (APDCDM); Technique for wireless communications

A new multiplexing and demultiplexing technique for wireless communications which is called Absolute Polar Duty Cycle Division Multiplexing (APDCDM) is presented in this paper. APDCDM can become an alternative multiplexing technique in wireless communications. The new technique allows for better error detection, correction, clock recovery and more efficient use of time slots as well as spectrum. The principle of the APDCDM technique has been discussed in this paper based on theoretical analysis as well as simulation studies. The performance comparison is made against time division multiplexing technique (TDM). The simulation has been set for wireless transmission, based on free space propagation model with adaptive white Gaussian noise (AWGN); QAM is used as modulation scheme to evaluate this technique against data rate and number of users. The simulation result correspond with the theoretical study show that APDCDM has better performance than TDM for supporting higher number of multiplexing users and bit rate.
Learning clinical anatomy

SUMMARY This article places the student at the center of their own learning experience. It draws together research to enable us to put forward a theoretical framework of best practice for student learning of clinical anatomy in a modern medical curricula. Anatomical knowledge involves both propositional knowledge and non-technical knowledge. For knowledge to be gained it must be contextualized and the content matter engaged with in a way that creates meaning for the students. From a neuroanatomical basis, this involves memory processing at a synaptic level within the circuitry of the hippocampus. It is important to recognize learners as individuals with their own personality traits and spatial ability. Both of which have been shown to influence the learning of anatomy. Students can vary the way they go about learning, they may utilize a surface, deep and/or strategic learning approach. It is quite possible that each student’s approach will differ depending on their personal experience. Approach will also vary at different points of their learning journey, because in higher education, students are free to engage in a wide range of learning activities. At some point in the future students may need to relearn or reconfigured their knowledge because the initial route to understanding is superseded by either a greater need or a more sophisticated line of reasoning, for example, knowledge can be challenged via more complex clinical scenarios. Knowledge consolidation is the next stage for students/trainees and this involves embedding the restructured learning and using it in practice. This stage will vary in time depending on the content it may occur during education or many years later. Anatomy learning is a personalized journey for the individuals. However, it is the role of the educators to aid learners in the development of a education framework that makes their learning effective, meaningful and stimulating.
Location and Super-Resolution Enhancement of License Plates Based on Video Sequences

Aiming at improving readability of the license plates in some real traffic surveillance video, a system of location and super-resolution of license plates is presented. After modeling the background by Gaussian mixture model and getting the vehicle region from the video, the license plates are located by connected component analysis and tracked by template matching. Then, the super-resolution reconstruction of the image sequences can be realized with projection onto convex sets (POCS) algorithm. The experiment suggests that it can effectively locate the license plates in the video, and an enhancement of the license plate image is obtained after super-resolution reconstruction.
Exploiting instruction redundancy for transient fault tolerance [microprocessor applications]

This paper presents an approach for integrating fault-tolerance techniques into microprocessors by utilizing instruction redundancy as well as time redundancy. Smaller and smaller transistors, higher and higher clock frequency, and lower and lower power supply voltage reduce the reliability of microprocessors. In addition, microprocessors are used in systems which require high dependability, such as e-commerce businesses. Based on these trends, it is expected that the quality with respect to reliability will become important as well as performance and cost for future microprocessors. To meet the demand, we have proposed and evaluated a fault-tolerance mechanism, which is based on instruction reissue and utilizes time redundancy, and found severe performance loss. In order to mitigate the loss, this paper proposes to exploit instruction redundancy. Using the reuse table, previously executed computing is reused for checking the occurrence of transient faults. From detailed simulations, we find that the performance loss caused by introducing fault tolerance into 4-way and 8-way superscalar processors is 12.5% and 20.8%, respectively.
PIT STRATEGIC MINE PLANNING UNDER UNCERTAINTY – ROBUST AND FLEXIBLE PLANS

A strategic mine plan is a fundamental part of any mining operation. It must provide a realistic extraction and processing schedule, as well as an accurate measure of the value of the project. There are several challenges to generating a successful strategic mine plan. Most importantly, key input information required for mine planning, such as actual ore grades and market prices, is uncertain in nature, thus a mine plan generated with deterministic data has a very low probability of performing as expected. Traditional mine planning approaches and existing software packages have failed to address uncertainty, which ultimately leads to underperforming and misvalued operations. In this paper we present the first software application that successfully takes into consideration market price uncertainty and generates feasible mine plans, in a timeframe competitive with commercially available software. The methodology presented provides a platform to consider market price uncertainty without an exponential increase in computational cost. By including uncertainty, our solution is able to create robust and flexible mine plans. A robust plan is one that best performs under unstable economic conditions. A flexible plan incorporates Real Options Analysis, allowing to postpone decisions such as expanding capacity, until the uncertainty has been reduced. The software has been tested for this paper in a real 12 million block model, with a mining operation lasting over 50 years, delivering competitive results for deterministic mine plans, increasing expected NPV in 2.4% with robust plans and the expected NPV of a fictitious expansion project in 68% with flexible plans.
Test-based extended finite-state machines induction with evolutionary algorithms and ant colony optimization

In this paper we consider the problem of extended finite-state machines induction. The input data for this problem is a set of tests. Each test consists of two sequences - an input sequence and a corresponding output sequence. We present a new method of Extended Finite-State Machines (EFSM) induction based on an Ant Colony Optimization algorithm (ACO) and a new meaningful test-based crossover operator for EFSMs. New algorithms are compared with a genetic algorithm (GA) using a traditional crossover, a (1+1) evolutionary strategy and a random mutation hill climber. This comparison shows that the use of test-based crossover greatly improves performance of GA. GA on average also significantly outperforms the hill climber and evolutionary strategy. ACO outperforms GA, and the difference between average performance of ACO and GA hybridized with hill climber is insignificant.
The impact of cultural differences in self-representation on the neural substrates of posttraumatic stress disorder

A significant body of literature documents the neural mechanisms involved in the development and maintenance of posttraumatic stress disorder (PTSD). However, there is very little empirical work considering the influence of culture on these underlying mechanisms. Accumulating cultural neuroscience research clearly indicates that cultural differences in self-representation modulate many of the same neural processes proposed to be aberrant in PTSD. The objective of this review paper is to consider how culture may impact on the neural mechanisms underlying PTSD. We first outline five key affective and cognitive functions and their underlying neural correlates that have been identified as being disrupted in PTSD: (1) fear dysregulation; (2) attentional biases to threat; (3) emotion and autobiographical memory; (4) self-referential processing; and (5) attachment and interpersonal processing. Second, we consider prominent cultural theories and review the empirical research that has demonstrated the influence of cultural variations in self-representation on the neural substrates of these same five affective and cognitive functions. Finally, we propose a conceptual model that suggests that these five processes have major relevance to considering how culture may influence the neural processes underpinning PTSD. Highlights of the article Cultural variations in individualistic-collectivistic self-representation modulate many of the same neural and psychological processes disrupted in PTSD. These commonly affected processes include fear perception and regulation mechanisms, attentional biases (to threat), emotional and autobiographical memory systems, self-referential processing and attachment systems. A conceptual model is proposed whereby culture is considered integral to the development and maintenance of PTSD and its neural substrates
Intravitreal Topotecan Inhibits Laser-induced Choroidal Neovascularization in a Rat Model

Purpose: A two-phase preclinical study was designed to determine the safe dose of intravitreal topotecan and its inhibitory effect on experimental choroidal neovascularization (CNV) in a rat model. Methods: In phase I, 42 rats were categorized into 6 groups, 5 of which received intravitreal topotecan injections of 0.125 μg, 0.25 μg, 0.5 μg, 0.75 μg, and 1.0 μg/5 μl, respectively; the control group received an injection of normal saline. Ophthalmic examination and electroretinography (ERG) were performed on days 7 and 28, and enucleated globes were processed for histopathology and immunostaining for glial fibrillary acidic protein. In phase II, CNV was induced via laser burns in 20 rats and the animals were divided into 2 groups. One group received topotecan and the other received normal saline intravitreally. Four weeks later, mean scores of fluorescein leakage on fluorescein angiography as well as mean CNV areas on histology sections were compared. Results: In phase I, clinical, ERG and histopathologic results were unremarkable in terms of retinal toxicity in all groups. Based on the results of phase I, a dose of 1 μg/5 μl topotecan was chosen for phase II. Leakage scores obtained from late-phase fluorescein angiography were significantly lower in topotecan-treated than control eyes (P < 0.01) four weeks after induction of CNV. Compared to control eyes, topotecan-treated eyes showed a significantly lower incidence of fibrovascular proliferation (8.7% vs. 96.2%) and significantly smaller areas of CNV (P < 0.01). Conclusion: Intravitreal injection of topotecan at a dose of 1 μg/5 μl is safe and may be a promising treatment for CNV.
On the security of modern Single Sign-On Protocols: Second-Order Vulnerabilities in OpenID Connect

OAuth is the new de facto standard for delegating authorization in the web. An important limitation of OAuth is the fact that it was designed for authorization and not for authentication. The usage of OAuth for authentication thus leads to serious vulnerabilities as shown by Zhou et. al. in [44] and Chen et. al. in [9]. OpenID Connect was created on top of OAuth to fill this gap by providing federated identity management and user authentication. OpenID Connect was standardized in February 2014, but leading companies like Google, Microsoft, AOL and PayPal are already using it in their web applications [1], [2], [3], [30]. In this paper we describe the OpenID Connect protocol and provide the first in-depth analysis of one of the key features of OpenID Connect: the Discovery and the Dynamic Registration extensions.We present a new class of attacks on OpenID Connect that belong to the category of second-order vulnerabilities. These attacks consist of two phases: First, the injection payload is stored by the legitimate application. Later on, this payload is used in a security-critical operation. Our new class of attacks - called Malicious Endpoints attacks - exploits the OpenID Connect extensions Discovery and Dynamic Registration. These attacks break user authentication, compromise user privacy, and enable Server Side Request Forgery (SSRF), client-side code injection, and Denial-of-Service (DoS). As a result, the security of the OpenID Connect protocol cannot be guaranteed when these extensions are enabled in their present form. We contacted the authors of the OpenID Connect and OAuth specifications. They acknowledged our Malicious Endpoint attacks and recognized the need to improve the specification [29]. We are currently involved in the discussion regarding the mitigation of the existing issues and an extension to the OAuth specification.
The Fourier-Stieltjes and Fourier algebras for locally compact groupoids

The Fourier-Stieltjes and Fourier algebras B(G), A(G) for a general locally compact group G, first studied by P. Eymard, have played an important role in harmonic analysis and in the study of operator algebras generated by G. Recently, there has been interest in developing versions of these algebras for locally compact groupoids, justification being that, just as in the group case, the algebras should play a useful role in the study of groupoid operator algebras. Versions of these algebras for the locally compact groupoid case appear in three related theories: (1) a measured groupoid theory (J. Renault), (2) a Borel theory (A. Ramsay and M. Walter), and (3) a continuous theory (A. Paterson). The present paper is expository in character. For motivational reasons, it starts with a description of the theory of B(G), A(G) in the locally compact group case, before discussing these three realted theories. Some open questions are also raised.
Arsenic Toxicity in Male Reproduction and Development

Arsenic is a toxic metalloid that exists ubiquitously in the environment, and affects global health problems due to its carcinogenicity. In most populations, the main source of arsenic exposure is the drinking water. In drinking water, chronic exposure to arsenic is associated with increased risks of various cancers including those of skin, lung, bladder, and liver, as well as numerous other non-cancer diseases including gastrointestinal and cardiovascular diseases, diabetes, and neurologic and cognitive problems. Recent emerging evidences suggest that arsenic exposure affects the reproductive and developmental toxicity. Prenatal exposure to inorganic arsenic causes adverse pregnancy outcomes and children’s health problems. Some epidemiological studies have reported that arsenic exposure induces premature delivery, spontaneous abortion, and stillbirth. In animal studies, inorganic arsenic also causes fetal malformation, growth retardation, and fetal death. These toxic effects depend on dose, route and gestation periods of arsenic exposure. In males, inorganic arsenic causes reproductive dysfunctions including reductions of the testis weights, accessory sex organs weights, and epididymal sperm counts. In addition, inorganic arsenic exposure also induces alterations of spermatogenesis, reductions of testosterone and gonadotrophins, and disruptions of steroidogenesis. However, the reproductive and developmental problems following arsenic exposure are poorly understood, and the molecular mechanism of arsenic-induced reproductive toxicity remains unclear. Thus, we further investigated several possible mechanisms underlying arsenic-induced reproductive toxicity.
Cell Clinics Technology Platform for Cell-Based Sensing

The cell clinics microsystem is a platform for long-term cell monitoring for such applications as cell-based sensing. This system includes microvials with individually actuated lids, integrated circuits that monitor cells and control the position of the vial hinges, and an automated cell loading mechanism that relies on dielectrophoresis to manipulate individual cells into the vials