Miracle-dz/UniFAR-FTUs huggingface dataset:
Memory analysis and significance test for agent behaviours

Many agent problems in a grid world have a restricted sensory information and motor actions. The environmental conditions need dynamic processing of internal memory. In this paper, we handle the artificial ant problem, an agent task to model ant trail following in a grid world, which is one of the difficult problems that purely reactive systems cannot solve. We provide an evolutionary approach to quantify the amount of memory needed for the agent problem and explore a systematic analysis over the memory usage. We apply two types of memory-based control structures, Koza's genetic programming and finite state machines, to recognize the relevance of internal memory. Statistical significance test based on beta distribution differentiates the characteristics and performances of the two control structures.
5‐HT2 receptors in Drosophila are expressed in the brain and modulate aspects of circadian behaviors

Dysregulation of 5‐HT2 receptor function has been strongly implicated in many neuropsychiatric disorders, including schizophrenia. At present, the molecular mechanisms linking 5‐HT2 receptor activation to behaviors is not well understood. In efforts to elucidate these processes, the fruit fly, Drosophila melanogaster, is proposed to serve as a powerful genetically tractable model organism to study 5‐HT2 receptor function. Data are presented here on the expression of the fly ortholog of the mammalian 5‐HT2 receptor, 5‐HT2Dro, in the larval and adult brain of the fly, and on the involvement of these circuits in certain circadian behaviors. In the adult brain, 5‐HT2Dro is expressed in the protocerebrum and ellipsoid body, areas believed to participate in higher order behaviors including learning, locomotion, and sensory perception. In the third instar larva, 5‐HT2Dro receptor expression is detected in a specific pattern that markedly changes from early to late third instar. To probe the function of this receptor we have examined the effects of the 5‐HT2 receptor‐specific agonist DOI in wild type and 5‐HT2Dro hypomorphic flies on circadian behaviors. DOI was found to increase early day activity, eliminate anticipatory behavior, and reduce viability. The effects of DOI were significantly diminished in a 5‐HT2Dro hypomorphic strain. Identifying the 5‐HT2Dro receptor circuitry and behaviors they mediate are significant steps towards developing this model system to study conserved molecular mechanisms underlying behaviors mediated by 5‐HT2 receptors in mammalian systems. © 2007 Wiley Periodicals, Inc. Develop Neurobiol, 2007.
Local Color Contrastive Descriptor for Image Classification

Image representation and classification are two fundamental tasks towards multimedia content retrieval and understanding. The idea that shape and texture information (e.g. edge or orientation) are the key features for visual representation is ingrained and dominated in current multimedia and computer vision communities. A number of low-level features have been proposed by computing local gradients (e.g. SIFT, LBP and HOG), and have achieved great successes on numerous multimedia applications. In this paper, we present a simple yet efficient local descriptor for image classification, referred as Local Color Contrastive Descriptor (LCCD), by leveraging the neural mechanisms of color contrast. The idea originates from the observation in neural science that color and shape information are linked inextricably in visual cortical processing. The color contrast yields key information for visual color perception and provides strong linkage between color and shape. We propose a novel contrastive mechanism to compute the color contrast in both spatial location and multiple channels. The color contrast is computed by measuring \emph{f}-divergence between the color distributions of two regions. Our descriptor enriches local image representation with both color and contrast information. We verified experimentally that it can compensate strongly for the shape based descriptor (e.g. SIFT), while keeping computationally simple. Extensive experimental results on image classification show that our descriptor improves the performance of SIFT substantially by combinations, and achieves the state-of-the-art performance on three challenging benchmark datasets. It improves recent Deep Learning model (DeCAF) [1] largely from the accuracy of 40.94% to 49.68% in the large scale SUN397 database. Codes for the LCCD will be available.
Integer-Forcing MIMO Linear Receivers Based on Lattice Reduction

A new architecture called integer-forcing (IF) linear receiver has been recently proposed for multiple-input multiple-output (MIMO) fading channels, wherein an appropriate integer linear combination of the received symbols has to be computed as a part of the decoding process. In this paper, we propose a method based on Hermite-Korkine-Zolotareff (HKZ) and Minkowski lattice basis reduction algorithms to obtain the integer coefficients for the IF receiver. We show that the proposed method provides a lower bound on the ergodic rate, and achieves the full receive diversity. Suitability of complex Lenstra-Lenstra-Lovasz (LLL) lattice reduction algorithm (CLLL) to solve the problem is also investigated. Furthermore, we establish the connection between the proposed IF linear receivers and lattice reduction-aided MIMO detectors (with equivalent complexity), and point out the advantages of the former class of receivers over the latter. For the 2 × 2 and 4× 4 MIMO channels, we compare the coded-block error rate and bit error rate of the proposed approach with that of other linear receivers. Simulation results show that the proposed approach outperforms the zero-forcing (ZF) receiver, minimum mean square error (MMSE) receiver, and the lattice reduction-aided MIMO detectors.
Liquid tunable microlenses based on MEMS techniques

The recent rapid development in microlens technology has provided many opportunities for miniaturized optical systems, and has found a wide range of applications. Of these microlenses, tunable-focus microlenses are of special interest as their focal lengths can be tuned using micro-scale actuators integrated with the lens structure. Realization of such tunable microlens generally relies on the microelectromechanical system (MEMS) technologies. Here, we review the recent progress in tunable liquid microlenses. The underlying physics relevant to these microlenses are first discussed, followed by description of three main categories of tunable microlenses involving MEMS techniques, mechanically driven, electrically driven and those integrated within microfluidic systems.
Segmentation-Assisted Detection of Dirt Impairments in Archived Film Sequences

In this correspondence, a novel segmentation-assisted method for film-dirt detection is proposed. We exploit the fact that film dirt manifests in the spatial domain as a cluster of connected pixels whose intensity differs substantially from that of its neighborhood, and we employ a segmentation-based approach to identify this type of structure. A key feature of our approach is the computation of a measure of confidence attached to detected dirt regions, which can be utilized for performance fine tuning. Another important feature of our algorithm is the avoidance of the computational complexity associated with motion estimation. Our experimental framework benefits from the availability of manually derived as well as objective ground-truth data obtained using infrared scanning. Our results demonstrate that the proposed method compares favorably with standard spatial, temporal, and multistage median-filtering approaches and provides efficient and robust detection for a wide variety of test materials
Optimal User Scheduling and Rate Selection for REMA Broadcast-Channel Transmission

Superposed transmission on the broadcast channel delivers multiple private messages simultaneously to the intended users. Superposed transmission is employed in non-orthogonal multiple access to increase the aggregate throughput and connectivity of wireless cellular systems. Rate-adaptive constellation Expansion Multiple Access (REMA, a.k.a. RA-CEMA) is a non-orthogonal multiple access scheme which exhibits performance similar to the conventional superposed transmission schemes for transmission on the degraded broadcast channel, while requiring less complex signal processing and scheduling algorithms. This paper solves the problem of user scheduling and rate&#126;allocation for REMA. We pose the problem as a weighted sum-rate optimization and develop provably optimal algorithms for user selection and rate allocation with REMA broadcast-channel transmission. System-level evaluations show that our schemes outperform an LTE-A compliant orthogonal multiple access system and exhibit similar or better performance compared to other known non-orthogonal multiple access schemes.
System requirements prioritization based on AHP

When analyzing software requirements specification, the question of determining which tasks need to be implemented first arises often. In fact, in any software project, it's important to begin by identifying and defining priority tasks. This process is called software requirements prioritization. However in this process, the effect of NFRs on FRs to be prioritized has always been neglected, and all the requirements are prioritized independently. In this paper, we propose a new technique for software requirements prioritization taking account of the relationship of dependency between FR and NFR.
Exploring the Relevance of the Personal and Social Responsibility Model in Adapted Physical Activity: A Collective Case Study

The purpose of this study was to examine the application of the Personal and Social Responsibility Model (PSRM) in an adapted physical activity program. Although the PSRM was developed for use with underserved youth, scholars in the field of adapted physical activity have noted its potential relevance for children with disabilities. Using a collective case study, we explored the relevance and perceived benefits of the PSRM in an adapted martial arts program. Participants were five male children with spastic diplegic cerebral palsy. Data sources included observational field notes, medical records, and interviews with participants’ physicians, therapists, and parents. The following themes were generated from the data: increased sense of ability, positive feelings about the program, positive social interactions, and therapeutic relevance. These results indicate that the PSRM can be made relevant to children with disabilities, especially when coupled with appealing and therapeutically relevant content.
CURRENT STATUS AND FUTURE PERSPECTIVES OF ENDOSCOPIC SUBMUCOSAL DISSECTION FOR COLORECTAL TUMORS

Endoscopic submucosal dissection (ESD) allows for en bloc tumor resection irrespective of the size of the lesion. In Japan, ESD has been established as a standard method for endoscopic ablation of malignant tumors in the upper gastrointestinal tract. Although the use of colorectal ESD has been gradually spreading with the development of numerous devices, ESD has not yet been fully established as a standard therapeutic method for colorectal lesions. Currently, colorectal ESD is performed as an ‘advanced medical treatment’ without national health insurance coverage. With the recent accumulation of numerous cases, the safety and simplicity of colorectal ESD have improved remarkably. Currently in Japan, a prospective multicenter cohort study organized by the Japan Gastroenterological Endoscopy Society is ongoing to clarify the safety and efficacy of colorectal ESD to obtain remuneration from national health insurance. In this report, we showed the outcome regarding safety and efficacy of colorectal ESD through a review of the published work. Of 2719 cases with colorectal ESD at 13 institutions, the complete en bloc resection and perforation rates were 82.8% (61–98.2%, 2082/2516) and 4.7% (1.4–8.2%, 127/2719), respectively. Additional surgery for perforation was very rare because perforations were tiny enough to be closed endoscopically by clips in most of the cases and treated conservatively. In the near future, colorectal ESD will be a common therapeutic method for early colorectal carcinoma.
A Fully-Integrated 40-Gb/s Transceiver in 65-nm CMOS Technology

This paper introduces a fully-integrated wireline transceiver operating at 40 Gb/s. The transmitter incorporates a 5-tap finite-inpulse response (FIR) filter with LC-based delay lines precisely adjusted by a closed-loop delay controller. The receiver employs a similar 3-tap FIR filter as an equalizer front-end with digital adaptation, and a sub-rate clock and data recovery circuit using majority voting phase detection. The transceiver delivers 40-Gb/s 27-1 PRBS data across a Rogers channel of 20 cm (19-dB loss at 20 GHz) with BER <; 10-12 while consuming a total power of 655 mW.
Cosmological data analysis of f(R) gravity models

A class of well-behaved modified gravity models with long enough matter domination epoch and a late-time accelerated expansion is confronted with SNIa, CMB, SDSS, BAO and H(z) galaxy ages data, as well as current measurements of the linear growth of structure. We show that the combination of geometrical probes and growth data exploited here allows to rule out f(R) gravity models, in particular, the logarithmic of curvature model. We also apply solar system tests to the models in agreement with the cosmological data. We find that the exponential of the inverse of the curvature model satisfies all the observational tests considered and we derive the allowed range of parameters. Current data still allows for small deviations of Einstein gravity. Future, high precision growth data, in combination with expansion history data, will be able to distinguish tiny modifications of standard gravity from the ΛCDM model.
An improved lightweight synchronisation primitive for sensornets

Sensornets must allocate limited computation and energy resources efficiently to maximise utility and lifetime. This task is complicated by the need to coordinate activity between nodes as sensornets are necessarily real-time collaborative systems. In this paper we present and evaluate lightweight adaptive protocols based on pulse-coupled oscillators to synchronise tasks within a unicellular sensornet. A near-optimal schedule is constructed and dynamically maintained under non-ideal network conditions.
IBMG: interpretable behavioral model generator for nonlinear analog circuits via canonical form functions and genetic programming

The paper presents IBMG, an approach to generate behavioral models of nonlinear analog circuits, with the special distinction that it generates models that are compact and interpretable expressions which are not restricted to any pre-defined functional templates. IBMG outputs a small set of interpretable nonlinear differential equations that approximate the time-domain behavior of the circuit being modeled. The approach uses genetic programming (GP), which evolves functions, but GP has been heavily modified so that the behavioral expressions follow a special "canonical functional form" grammar to remain interpretable. IBMG has explicit error control; it provides a set of models that trade off complexity and accuracy. Experimental results on a strongly nonlinear latch circuit demonstrate the usefulness of IBMG.
Evidence for the Effects of Xanthohumol in Disrupting Angiogenic, but not Stable Vessels

Angiogenesis is a complex multistep process that comprises proliferation, migration, and anastomosis of endothelial cells, followed by stabilization of the newly formed vessel through the attachment of support cells. This process is imbalanced in a large number of disorders, including cardiovascular disease, diabetes and cancer. Evidence indicates that xanthohumol (XN), a prenylated chalcone present in beer, exerts anti-angiogenic properties. However, its precise effect within the angiogenic steps is not accurately established. The purpose of the present study was to examine which features of the angiogenic process can be disturbed by XN. Human umbilical vein endothelial cells (HUVEC) and human fetal aortic smooth muscle cells (SMC) were incubated with xanthohumol at 5 and 10 μM, and cell viability, apoptosis, invasion and capillary-like structures formation were examined. Treatment with 10 μM XN significantly decreased viability and invasion capacity and increased apoptosis in both cell types as assessed by MTT, double-chamber assay and TUNEL assay respectively. The two concentrations of XN further led to a significant reduction in the number of capillary-like structures, when HUVEC were cultured on growth factor reduced-Matrigel-coated plates. Interestingly, XN exhibited the opposite effect when HUVEC were co-cultured with SMC, leading to an increase in the number of cord structures. In addition, incubation of both types of cells with XN resulted in reduced activity of NFκB, a transcription factor implicated in these cell fates. Given the absence of adverse effects in mature vasculature by XN, these findings emphasize the potential use of XN against pathological situations where angiogenesis is stimulated.
Simultaneous Identification of Multiple Driver Pathways in Cancer

Distinguishing the somatic mutations responsible for cancer (driver mutations) from random, passenger mutations is a key challenge in cancer genomics. Driver mutations generally target cellular signaling and regulatory pathways consisting of multiple genes. This heterogeneity complicates the identification of driver mutations by their recurrence across samples, as different combinations of mutations in driver pathways are observed in different samples. We introduce the Multi-Dendrix algorithm for the simultaneous identification of multiple driver pathways de novo in somatic mutation data from a cohort of cancer samples. The algorithm relies on two combinatorial properties of mutations in a driver pathway: high coverage and mutual exclusivity. We derive an integer linear program that finds set of mutations exhibiting these properties. We apply Multi-Dendrix to somatic mutations from glioblastoma, breast cancer, and lung cancer samples. Multi-Dendrix identifies sets of mutations in genes that overlap with known pathways – including Rb, p53, PI(3)K, and cell cycle pathways – and also novel sets of mutually exclusive mutations, including mutations in several transcription factors or other genes involved in transcriptional regulation. These sets are discovered directly from mutation data with no prior knowledge of pathways or gene interactions. We show that Multi-Dendrix outperforms other algorithms for identifying combinations of mutations and is also orders of magnitude faster on genome-scale data. Software available at: http://compbio.cs. brown.edu/software.
Enhancing medication use safety: benefits of learning from your peers

Background: Maryland hospitals have been improving the safety of medication use practices since 2000. A retrospective analysis of 35 hospitals was conducted for 2005–2007 to determine the changes in medication use practices, communication methods within hospitals, patient education and changes in medical record management. Methods: Thirty-five Maryland hospitals completed the Institute for Safe Medication Practices Medication Safety Self-Assessment for Hospitals, a voluntary initiative to improve the safety of medication use. A weighting structure is applied to calculate key element scores, core characteristic scores and overall self-assessment scores that were used in ANOVA and regression analyses. Findings: The state-wide aggregate score significantly increased from 74.2% in 2005 to 81.2% in 2007 (p<0.05). The 35 hospitals scored highest in the following key areas in 2007: drug standardisation, storage and distribution (90.2%); drug labelling, packaging and nomenclature (88.1%); and environmental factors (84.3%). Results indicated that hospitals scored lowest in the key element area related to accessibility of patient information (72.5%) and in the core characteristics pertaining to redundancies and independent double checks (64.2%) in 2007. A substantial number of hospitals had positive and significant (p<0.05) changes in certain key elements and/or core characteristics. Few hospitals showed significant (p<0.05) decreases in their scores. Conclusion: MEDSAFE has directly assisted Maryland hospitals in improving medication use safety. The strategies and tools of MEDSAFE have been used in Maryland since 2000 and Singapore and Austria since 2006.
Unsupervised Approaches to Detecting Anomalous Behavior in the Bitcoin Transaction Network

Bitcoin is an electronic crypto-currency created in 2008 by Satoshi Nakamoto (pseudonym). At the time the original bitcoin client was written, the idea of a purely peer-to-peer (P2P) digital currency which did not require a trusted-thirdparty to confirm transactions / prevent double spending was unique. In the bitcoin network, all transactions are public, effectively rendering double-spending impossible. A criminal who wishes to double-spend or falsify some segment of the transaction history must convince the majority of the bitcoin network that his transaction history is correct, but in order to do that, he must provide the appropriate proof of work. Under the assumption that the majority of the network is honest, the criminal would have to have more computational power than the majority of the network in order to falsify the transaction history, as described in [1]. Since the onset of bitcoin, several other crypto-currencies have sprung into existence, but bitcoin continues to be the most popular. Because transactions in the bitcoin network are specified by the public keys of the payer and payee, some level of anonymity is guaranteed provided public keys are not traceable to real-world identities. For criminal organizations and others using bitcoin which require strong anonymity, this is not enough, so a so-called “mixing service” is employed. The mixing service takes in bitcoins from a group of individuals requiring strong anonymity, sends the coins around randomly in an attempt to obfuscate their origins, and then sends similar amounts of bitcoins back to new addresses specified by the individuals using the service. This is discussed in more detail in [2]. For our CS229 project, we were interested in using machine learning techniques to explore a dataset of bitcoin transactions; in particular, we were interested in exploring the anonymity guarantees of the bitcoin network. The questions we were hoping to answer are:
An abstract model for e-content search using ontology

The relevant content search has become a challenging task with the increase in the availability of knowledge and volume of information on the web. Among the various factors that affect the search, the terms or keywords used in the input query has utmost effect on the retrieved results by any search application. The resultant links corresponding to a search request are dependent on the input query supplied by the user. Query expansion is the concept to expand the input query for the inclusion of more relevant terms. This study is an attempt to present state-of-art query expansion approaches along with an abstract model for e-content search in engineering domain using ontological approach. Ontology is the major focus area for semantic search where the search approaches either use generic ontology (such as WordNet) while other augment search with domain specific ontology or the combination of both.