Miracle-dz/UniFAR-FTUs huggingface dataset:
What's new, what's next?

There are a number of new developments in the fight against the HIV epidemic. New drugs are being developed, results are being reported from a number of clinical trials, and there are some new strategies in disease management. Currently, there are eleven approved medications for HIV. Several new drugs or studies are highlighted: adefovir dipivoxil (preveon), which is now available under an expanded access program; abacavir (GW1592U89, efavirenz), which shows promise as an antiretroviral ten times more effective than AZT; amprenavir (141W94, VX-478), a new protease inhibitor nearing the end of clinical trials; Fortovase (soft-gel Saquinavir), which is proving much more effective than its earlier formulation; and Hydroxyurea (HU), a long-approved anti-cancer drug which enhances the effectiveness of other HIV medications. Several drugs under development are discussed, such as ABT-378, which show great promise in the treatment arsenal.
PAC-Bayesian Analysis of Contextual Bandits

We derive an instantaneous (per-round) data-dependent regret bound for stochastic multiarmed bandits with side information (also known as contextual bandits). The scaling of our regret bound with the number of states (contexts) N goes as $\sqrt{N I_{\rho_t}(S;A)}$, where Iρt(S; A) is the mutual information between states and actions (the side information) used by the algorithm at round t. If the algorithm uses all the side information, the regret bound scales as $\sqrt{N \ln K}$, where K is the number of actions (arms). However, if the side information Iρt (S; A) is not fully used, the regret bound is significantly tighter. In the extreme case, when Iρt(S; A)= 0, the dependence on the number of states reduces from linear to logarithmic. Our analysis allows to provide the algorithm large amount of side information, let the algorithm to decide which side information is relevant for the task, and penalize the algorithm only for the side information that it is using de facto. We also present an algorithm for multiarmed bandits with side information with O(K) computational complexity per game round.
Detecting Human Action in Active Video

We propose a novel scheme to detect human actions in active video. Active videos such as movies or sports broadcasting are taken purposively by "clever" photographers. They are object and action oriented and usually involve complex camera motions. Detecting actions in active videos is both important and challenging. We study a three-step scheme to detect complex human actions in such videos. The proposed method first locates potential objects and removes clutter with a composite filter scheme. The detected object candidates in successive frames are then associated to form object trajectories based on a consistent labeling formulation, and solved with belief propagation. Finally, specific human actions are detected in video with a linear programming matching approach that can efficiently deal with matching problems having a large target point set. The proposed method has been successfully applied in action detection for general videos and TV hockey games
Near-field optics on flatland: from noble metals to van der Waals materials

ABSTRACT Near-field optics, with the capability for nanoscale manipulation of photons and enhancement of light-matter interactions, has drawn tremendous attentions in recent years. Compared with traditional noble metals, near-field optics in low-dimensional van der Waals (vdW) materials has revealed various polaritonic modes with gate-tunable competence, high confinement and novel quantum physics. Advanced near-field imaging technique, named scattering-type scanning near-field optical microscopy, allows launching and visualizing the polaritonic waves in both noble metals and vdW materials. In this review, we introduce the fundamental principles of near-field optics and summarize up-to-date near-field studies and related quantum physics in three aspects: (1) In-situ electric field distribution around metallic nanostructures; (2) various polaritons in vdW materials and heterostructures; (3) quantum physical phenomena related to near-field optics in low-dimensional system. Then, we discuss the state-of-the-art near-field optics combing imaging with spectroscopy, transient measurement or Terahertz lasers for revealing new physics. To conclude, we summarize the nowadays challenges and present perspectives in the near-field optics field. Graphical Abstract
GA-Based Feature Extraction for Clapping Sound Detection

Automatically extracting semantic content from audio streams can be helpful in many multimedia applications. In this paper, we introduce a framework for automatic feature subspace selection from a common feature vector. The selected features build a new representation which is better suitable for a given learning task and recognition. In order to solve this problem, we propose the GA-based (genetic algorithm) method to improve the representativeness and robustness of the features generic audio recognition task
Assessing Multi-task Placement Algorithms in RCUs

In response to the current requirements of energy efficiency and high performance in computing systems, architects have turned towards customization. General purpose computing however remains a challenge as processors must adhere to a variety of applications, on-chip resources, and increased performance without solely relying on transistor scaling and additional cache levels. For this reason, the concept of Reconfigurable Computing Unit (RCU) processors have been proposed which redesign the conventional processor on the microarchitectural and architectural level. RCUs are extended in this work to support a multi-task workload using OmpSs, where task and instruction placement algorithms are thoroughly assessed for effects of performance and energy efficiency. Experimental results demonstrate that a single RCU processor with a double engine configuration is able to exceed single-core performance on average by 1.48x and achieve/exceed dual-core performance. The various inter-and intra-task placement algorithms tested also display up to 16.7% and 23% fluctuation in performance and energy efficiency, respectively, depending on the method and RCU engine combination employed.
Geriatric Nutrition Risk Index is an Important Predictor of Cancer-Specific Survival, but not Recurrence-Free Survival, in Patients Undergoing Surgical Resection for Non-Metastatic Renal Cell Carcinoma

Background: The objective of this study was to assess the prognostic value of the Geriatric Nutrition Risk Index (GNRI), a simplified, objective screening parameter of nutrition-related risk for various pathological conditions, on patients with non-metastatic renal cell carcinoma (RCC) who underwent surgical resection. Patients and Methods: This study included 432 consecutive patients with non-metastatic RCC who received complete surgical resection. The prognostic outcomes of these patients were evaluated focusing on the significance of GNRI, calculated from serum albumin and the body mass index. Results: Of the 432 patients, 107 (24.8%) and 325 (75.2%) were classified into low (GNRI ≤ 98) and high (GNRI > 98) nutritional groups, respectively. Both recurrence-free survival and cancer-specific survival in the low nutritional group were significantly poorer compared with those in the high nutritional group. Despite the lack of independent significance as a predictor of recurrence-free survival, GNRI, in addition to microvascular invasion, appeared to be independently associated with cancer-specific survival on multivariate analysis. Conclusion: A low nutritional status evaluated by GNRI may have an unfavorable impact on postoperative cancer control, particularly cancer-specific survival, in non-metastatic RCC patients who received surgical resection.
Modeling and Verifying Workflow-based Regulations

In this paper we present our approach to model and verify workflowintensive systems. Besides the functional properties (given by the temporal workflow description) we augment the model and model checking with additional property treatment to deal with multifarious non-functional properties and property hierarchies. This enables a more powerful verification of requirements such as given business-driven regulations in these system workflows.
Pre-classification of chest radiographs for improved active shape model segmentation of ribs

The parenchymal and skeletal structure as recorded on chest radiographs can vary significantly from person to person. The active shape model (ASM) rib-parenchyma model is defined using the 14 chest radiographs from the International Labor Organization (ILO) set of standard chest X-rays. Groundtruth was established by manually segmenting the ribs for the standard X-rays. A "leave one out" procedure was used to perform the tests on the ILO set. The measure of success was defined by the sensitivity of the segmentation in correctly classifying a pixel as parenchyma, ie, not rib. In one experiment, the chest radiographs were first pre-classified according to the number of parenchymal regions visible in each lung, and consecutive ASM model training and testing was performed over each class. In a second, similar experiment, the X-rays were first pre-classified by the height of the lungs, e.g., "tall" and "short" X-rays. It was found that the sensitivity improved an average of 0.20 over the baseline test (no pre-classification), when pre-classifying the lung by the number of parenchymal regions (8 or 9). Sensitivity improved an average of 0.19 over the baseline, when pre-classifying the lung by height (tall or short).
Unmanned Aerial Vehicle Emergency Landing Site Identification System Using Machine Vision

Unmanned Aerial Vehicles (UAVs) rely on navigation commands from autonomous flight control system or from Ground Control System (GCS) via line-ofsight wireless data link. UAV needs to perform immediate landing on predefined airfield in case of extreme emergency like navigation, data link, engine or control surface failure, that cannot be accomplished in some cases and accidents can occur which can result collateral damage as well. This paper presents the system design which can discover the appropriate area within the surroundings for immediate landing in case of emergency. The proposed system design consists of two stages. During first stage, system takes top view images from UAV onboard camera, then image processing algorithm extracts and refine the attributes of the image. In second stage, machine learning based algorithm evaluates the results from previous stage, and based on its previous training, decides whether the area visible in image is good for safe landing or not. We implement proposed system design in MATLAB and the approach used is validated with experimental results on test data. Proposed system design uses combination of simple techniques, which makes it less computationally intensive, having reduced latency, low implementation cost and easy to implement on high speed real time hardware like FPGA/ASIC. 
Energy efficient sensor, relay and base station placements for coverage, connectivity and routing

We consider a wireless sensor network made of sensor nodes capable of sensing and communication, relay nodes capable of communication, and base stations responsible for collecting data generated by sensor nodes, to be deployed in sensor field. We address the problem of placing the sensor nodes, relay nodes and base stations in the sensor field such that (i) each point of interest in the sensor field is covered by a subset of sensors of desired cardinality (ii) the resulting sensor network is connected and (iii) the sensor network has sufficient bandwidth. We propose several deployment strategies to determine optimal placements of sensor nodes, relay nodes and base stations for guaranteed coverage, connectivity, bandwidth and robustness. We study several different objectives such as minimizing the number of sensor nodes deployed, minimizing the total cost, minimizing the energy consumption, maximizing the network lifetime and maximizing the network utilization. The placement problems for reliable as well as unreliable/probabilistic detection models are formulated as integer linear programs (ILPs). The practicality, effectiveness and performance of the proposed strategies are illustrated through simulations.
Properties of Fixed Effects Dynamic Panel Data Estimators for a Typical Growth Dataset

This paper investigates the properties of dynamic panel data (DPD) estimators in the context of a typical growth dataset. Using Monte Carlo simulations, we compare the performance of various DPD estimators, namely the Anderson-Hsiao (AH) and Arellano-Bond's General Method of Moment (GMM) one-step and two- step estimators, using the least-square dummy variable (LSDV) as a benchmark. We arrive at three conclusions. First, LSDV produces biased estimates and the biases are significant even for a moderate-sized time dimension. Second, there is no immediately obvious choice to replace LSDV among the estimators considered here. For one, there is the bias-efficiency trade-off. In addition, differences in the characteristics of data influence the performances of the various estimators. Finally, serial correlations in the error terms, even at a low degree, can introduce significant biases to the estimations.
Diversity in treatment modalities of Stage II/III urothelial cancer in Japan: sub-analysis of the multi-institutional national database of the Japanese Urological Association.

OBJECTIVE We aimed to survey treatment modalities for the patients with Stage II/III urothelial cancer in Japan. METHODS We used the multi-institutional national database of the Japanese Urological Association from 348 Japanese institutions, in which a total of 3707 patients with muscle-invasive bladder cancer and 1538 with upper urinary tract urothelial carcinoma were registered in 2008 and 2011, respectively. Primary treatment was classified as surgery alone, surgery with chemotherapy, surgery with radiation, radiation alone, chemotherapy alone, combination of radiation and chemotherapy and observation. Overall and cancer-specific survivals were examined using the Kaplan-Meier method, and survival in the subgroups was analyzed using the log-rank test. RESULTS In Stage II/III bladder cancer patients, 49.7% of those were treated with radical operation and 22.3% received observation only. A total 97.2% of Stage II/III upper urinary tract urothelial carcinoma patients treated with radical surgery. A total 30.4% of Stage II/III bladder cancer patients received chemotherapy. Majority of the patients received cisplatin-based regimen, however, regimens of chemotherapy was rich in variety up to 13 regimens. Chemotherapy regimens for the patients with upper urinary tract urothelial carcinoma were also various up to eight regimens. Overall and cancer-specific survivals were statistically significantly stratified according to the clinical stage. The upper urinary tract urothelial carcinoma patients diagnosed with clinical stage T3 had significantly poor prognosis compared with those diagnosed with clinical stage T2. CONCLUSIONS This study demonstrated the variety of treatments used for Japanese patients with Stage II/III urothelial cancer. Treatment standardization for these entities may be necessary.
An energy efficient resource management and planning system for 5G networks

The concept of heterogeneous networks and small cells is likely to be a key addition to the fifth generation (5G) wireless communication standard, the prospect of which has motivated 5G researchers to investigate the coverage and integration of various small cells. Heterogeneous networks with small cells offer key benefits such as high frequency reuse, huge data rates and low power consumption for mobile nodes. High frequency reuse is particularly important given the exponential growth of data rates and the looming frequency scarcity problem. Another major consideration for 5G is the energy efficiency as with the exponential growth of demand, power consumption in the information and communication technology (ICT) sector is also expected to significantly increase. While the concept of small cells in heterogeneous networks addresses the frequency scarcity problem to a great extent, unless otherwise carefully managed, a large number of uncoordinated and lightly loaded small cells significantly increase the overall power consumption, contrary to the green communication target of the 5G standard. In this paper, we focus on an energy efficient resource management and planning system that investigates the impact of growing number of small cells in a macro cell. We present an analytical model for calculating the optimum number of small cells that need to be kept awake at various hours of a day for meeting the quality of service demands from all users. Simulation results show significant power consumption improvement than an existing model.
Discover Aggregates Exceptions over Hidden Web Databases

Nowadays, many web databases "hidden" behind their restrictive search interfaces (e.g., Amazon, eBay) contain rich and valuable information that is of significant interests to various third parties. Recent studies have demonstrated the possibility of estimating/tracking certain aggregate queries over dynamic hidden web databases. Nonetheless, tracking all possible aggregate query answers to report interesting findings (i.e., exceptions), while still adhering to the stringent query-count limitations enforced by many hidden web databases providers, is very challenging. In this paper, we develop a novel technique for tracking and discovering exceptions (in terms of sudden changes of aggregates) over dynamic hidden web databases. Extensive real-world experiments demonstrate the superiority of our proposed algorithms over baseline solutions.
Comparative Evaluation of Latency-Tolerating and -Reducing Techniques for Hardware-Only and Software-Only Directory Protocols

Abstract We study in this paper how effective latency-tolerating and -reducing techniques are at cutting the memory access times for shared-memory multiprocessors with directory cache protocols managed by hardware and software. A critical issue for the relative efficiency is how many protocol operations such techniques trigger. This paper presents a framework that makes it possible to reason about the expected relative efficiency of a latency-tolerating or -reducing technique by focusing on whether the technique increases, decreases, or does not change the number of protocol operations at the memory module. Since software-only directory protocols handle these operations in software they will perform relatively worse unless the technique reduces the number of protocol operations. Our experimental results from detailed architectural simulations driven by six applications from the SPLASH-2 parallel program suite confirm this expectation. We find that while prefetching performs relatively worse on software-only directory protocols due to useless prefetches, there are examples of protocol optimizations, e.g., optimizations for migratory data, that do relatively better on software-only directory protocols. Overall, this study shows that latency-tolerating techniques must be more carefully selected for software-centric than for hardware-centric implementations of distributed shared-memory systems.
Membrane-Bound Lytic Endotransglycosylase inEscherichia coli

ABSTRACT The gene for a novel endotype membrane-bound lytic transglycosylase, emtA, was mapped at 26.7 min of theE. coli chromosome. EmtA is a lipoprotein with an apparent molecular mass of 22 kDa. Overexpression of the emtA gene did not result in bacteriolysis in vivo, but the enzyme was shown to hydrolyze glycan strands isolated from murein by amidase treatment. The formation of tetra- and hexasaccharides, but no disaccharides, reflects the endospecificity of the enzyme. The products are characterized by the presence of 1,6-anhydromuramic acid, indicating a lytic transglycosylase reaction mechanism. EmtA may function as a formatting enzyme that trims the nascent murein strands produced by the murein synthesis machinery into proper sizes, or it may be involved in the formation of tightly controlled minor holes in the murein sacculus to facilitate the export of bulky compounds across the murein barrier.
Interpretations of Directed Information in Portfolio Theory, Data Compression, and Hypothesis Testing

We investigate the role of directed information in portfolio theory, data compression, and statistics with causality constraints. In particular, we show that directed information is an upper bound on the increment in growth rates of optimal portfolios in a stock market due to causal side information. This upper bound is tight for gambling in a horse race, which is an extreme case of stock markets. Directed information also characterizes the value of causal side information in instantaneous compression and quantifies the benefit of causal inference in joint compression of two stochastic processes. In hypothesis testing, directed information evaluates the best error exponent for testing whether a random process <i>Y</i> causally influences another process <i>X</i> or not. These results lead to a natural interpretation of directed information <i>I</i>(<i>Yn</i> → <i>Xn</i>) as the amount of information that a random sequence <i>Yn</i> = (<i>Y</i><sub>1</sub>,<i>Y</i><sub>2</sub>,., <i>Yn</i>) causally provides about another random sequence <i>Xn</i> = (<i>X</i><sub>1</sub>,<i>X</i><sub>2</sub>,.,<i>Xn</i>). A new measure, directed lautum information, is also introduced and interpreted in portfolio theory, data compression, and hypothesis testing.
Edit-Distance Of Weighted Automata: General Definitions And Algorithms

The problem of computing the similarity between two sequences arises in many areas such as computational biology and natural language processing. A common measure of the similarity of two strings is their edit-distance, that is the minimal cost of a series of symbol insertions, deletions, or substitutions transforming one string into the other. In several applications such as speech recognition or computational biology, the objects to compare are distributions over strings, i.e., sets of strings representing a range of alternative hypotheses with their associated weights or probabilities. We define the edit-distance of two distributions over strings and present algorithms for computing it when these distributions are given by automata. In the particular case where two sets of strings are given by unweighted automata, their edit-distance can be computed using the general algorithm of composition of weighted transducers combined with a single-source shortest-paths algorithm. In the general case, we show tha.
Read-once polynomials: How many summands suffice?

An arithmetic read-once formula (ROF) is a formula (circuit of fan-out 1) over $+, \times$ where each variable labels at most one leaf. Every multilinear polynomial can be expressed as the sum of ROFs. In this work, we prove, for certain multilinear polynomials, a tight lower bound on the number of summands in such an expression.