Miracle-dz/UniFAR-FTUs huggingface dataset:
Spoken language condensation in the 21st century

While the field of Information Retrieval originally had the search for the most relevant documents in mind, it has become increasingly clear that in many instances, what the user wants is a piece of coherent information, derived from a set of relevant documents and possibly other sources. Reducing relevant documents, passages, and sentences to their core is the task of text summarization or information condensation. Applying text-based technologies to speech is not always workable and often not enough to capture speech specific phenomena. In this paper, we will contrast speech summarization with text summarization, give an overview of the history of speech summarization, its current state, and, finally, sketch possible avenues as well as remaining challenges in future research.
A Design Architecture For Sensor Data Fusion Systems With Application To Automotive Safety

In this paper we present a modular sensor data fusion functional architecture, tailored for development of automotive active safety systems. The purpose of the fusion system is to provide active safety applications with accurate knowledge regarding the environment surrounding the vehicle. Our proposed functional architecture is designed in such way that the fusion system is easy to maintain, upgrade and re-use. These aspects are assessed by the use of a reference implementation which is evaluated in terms of tracking performance and scalability. Furthermore, the reference implementation demonstrates that a system can be implemented using rapid prototyping tools, from which we can automatically generate c-code.
Modeling tool-body assimilation using second-order Recurrent Neural Network

Tool-body assimilation is one of the intelligent human abilities. Through trial and experience, humans are capable of using tools as if they are part of their own bodies. This paper presents a method to apply a robot's active sensing experience for creating the tool-body assimilation model. The model is composed of a feature extraction module, dynamics learning module, and a tool recognition module. Self-Organizing Map (SOM) is used for the feature extraction module to extract object features from raw images. Multiple Time-scales Recurrent Neural Network (MTRNN) is used as the dynamics learning module. Parametric Bias (PB) nodes are attached to the weights of MTRNN as second-order network to modulate the behavior of MTRNN based on the tool. The generalization capability of neural networks provide the model the ability to deal with unknown tools. Experiments are performed with HRP-2 using no tool, I-shaped, T-shaped, and L-shaped tools. The distribution of PB values have shown that the model has learned that the robot's dynamic properties change when holding a tool. The results of the experiment show that the tool-body assimilation model is capable of applying to unknown objects to generate goal-oriented motions.
Exploration of Generalized Residual Prediction in scalable HEVC

After having issued the version 1 of the new video coding standard HEVC, ISO-MPEG and ITU-T VCEG groups are specifying its scalable extension. The candidate schemes are based on a multi-layer multi-loop coding framework, exploiting inter-layer texture and motion prediction and full base layer picture decoding. Several inter-layer prediction tools have been explored, implemented either using high-level syntax or block-level core HEVC design changes. One of these tools, Generalized Residual Prediction (GRP), has been extensively studied during several meeting cycles. It is based on second order residual prediction, exploiting motion compensation prediction residual in the base layer. This paper is focused on this new mode. The principle of GRP is described with an analysis of several implementation variants completed by a complexity analysis. Performance of these different implementations is provided, showing that noticeable gains can be obtained without significant complexity increase compared to a simple scalable design comprising only texture and motion inter-layer prediction.
Long wires and asynchronous control

As integrated circuit technologies get smaller, circuit and architectural trends make transmitting data across long on-chip wires increasingly important yet increasingly expensive in both latency and throughput. Inserting repeaters can reduce latency by breaking up long wires with gain stages but offers only limited throughput improvement, while breaking long wires with clocked latches improves latency and throughput but requires generating fast local clocks. In contrast, asynchronous handshaking over long wires can improve both latency and bandwidth with lower control overhead. We introduce simple latency models that relate best stage separation to technology parameters. In addition, the transactional nature of handshaking presents a fundamental limitation on throughput exacerbated by long wires. We present twin request/acknowledge control scheme that overcomes this throughput cost.
The Algorithms of Updating Sequential Patterns

Because the data being mined in the temporal database will evolve with time, many researchers have focused on the incremental mining of frequent sequences in temporal database. In this paper, we propose an algorithm called IUS, using the frequent and negative border sequences in the original database for incremental sequence mining. To deal with the case where some data need to be updated from the original database, we present an algorithm called DUS to maintain sequential patterns in the updated database. We also define the negative border sequence threshold: Min_nbd_supp to control the number of sequences in the negative border.
Stabilization of multirate networked control systems

In this paper, we study the stabilization of multirate networked control systems with norm bounded uncertainties in the input channels. The key idea is to use the channel resource allocation, i.e., given the overall capacity of the transmission network, we do have the freedom to allocate the capacities among different input channels. With this idea, we successfully show that a multirate networked control system could be stabilized by state feedback under an appropriate resource allocation if and only if the overall network capacity is larger than the topological entropy of the plant. We also apply the result to multirate quantized networked control systems. A sufficient condition for stabilization is obtained which involves a trade-off between the densities of time quantization and spatial quantization.
Handedness Shift as a Consequence of Motor Cortex Reorganization After Early Functional Impairment in Left Temporal Lobe Epilepsy—An fMRI Case Report

Abstract The impact of epileptiform activity on the functional organization of various cortical regions is currently a widely discussed topic. Our patient, suffering from left-sided temporal lobe epilepsy with typical mesiotemporal sclerosis, had a remarkable history of a clear-cut handedness shift in early childhood. In this study, we considered the possibility of the functional reorganization of the motor cortex using functional MRI. The results reflect epileptiform activity as an important formative factor for motor cortex development in our patient.
Joint Detection and Channel Estimation of LTE Downlink System using Unique Iterative Decoding Technique

Long Term Evolution (LTE) is emerging as a strong option towards wireless broad band. Inclusion of Orthogonal Frequency Multiplexing (OFDM) and Multiple Input Multiple Output (MIMO) has exploited the efficient spectrum utilization, realizing high bandwidth potential and latencies in the current hostile wireless communication. LTE Advanced (LTE-A) is shaping up to be a pervasive technology with solutions that not only meet the ever-increasing data demand of traditional mobile broadband services, but also open up opportunities to transform new industries. In this paper we propose to improve the performance of channel estimation and detection for LTE downlink systems under the effect of increased channel length. Focus is on to the joint channel estimation and mitigation of inter-symbol Interference (ISI). Cyclic prefix (CP) is used to compensate for the ISI. Proposed iterative technique gives improved detection in terms of mean square error (MSE) as well as bit error rate (BER) for the given CP and channel length. In this paper Iterative channel estimation using Least Square (LS) and Minimum Mean Square Error (MMSE) methods are explored to improve the channel estimation. With the use of iterative algorithms, it is shown that within adequate number of iterations channel estimation can be improved. Key-Words: MIMO, OFDM, Channel estimation, Least Square, LMMSE.
Digital design at a crossroads How to make statistical design methodologies industrially relevant

Statistical analysis is generally seen as the next EDA technology for timing and power sign-off. Research into this field has seen significant activity started about five years ago. Recently, interest appears to have fallen off somewhat. Also, while a lot of focus has been put on research fundamentals, extremely few applications in industry have been reported so far. Therefore, a group including Infineon Technologies as a leading semiconductor IDM and various universities and research institutes, as well as an EDA provider has tackled key challenges to enable statistical design in industry in a publicly funded project called ldquoSigma65rdquo. Sigma65 strives to provide key foundations to allow a change from traditional deterministic design methods to future design methods driven by statistical considerations. The project starts with statistical modeling and optimization of library components and ranges to statistical techniques for designing ICs on gate level and higher levels. In this paper, we present some results of this project, demonstrating how the interaction between industrial perspective, research institutions and EDA provider enables solutions which are applicable already in the near future. After an overview of the industrial perspective of the current situation in dealing with variations recent results on both statistical timing and power analysis will be given. In addition, recent research advances on fast yield estimation concerning parametric timing yield will be given.
The effect of interleukin 4 (BSF-1) on infection of peripheral blood monocyte-derived macrophages with HIV-1.

The effects of various cytokines were examined in an in vitro model of human immunodeficiency virus type 1 (HIV-1) infection of human peripheral blood monocyte-derived macrophages (MDM). Monocytes were obtained from blood of normal donors by Ficoll/hypaque gradient centrifugation and adherence. These cells were allowed to mature in the presence of varying concentrations of cytokines. After five days in culture, cells were harvested, counted, and inoculated with S5G7, an HTLV-IIIB subclone. The cells were replated in the presence of the same concentrations of cytokines. Culture supernatants were sampled over 28 days for p24 antigen (Ag) as measured by Ag capture assay. In repeat experiments, the following observations were made: 1. MDM from some donors could be infected only in the presence of tumor necrosis factor-alpha (TNF-α), granulocyte/macrophage colony-stimulating factor (GM-CSF) or interleukin 4 (IL-4); 2. The effect of GM-CSF was variable; TNFα also enhanced HIV replication above controls; 3. IL-4.
Assessment and Decomposition of Total Factor Energy Efficiency: An Evidence Based on Energy Shadow Price in China

By adopting an energy-input based directional distance function, we calculated the shadow price of four types of energy (i.e., coal, oil, gas and electricity) among 30 areas in China from 1998 to 2012. Moreover, a macro-energy efficiency index in China was estimated and divided into intra-provincial technical efficiency, allocation efficiency of energy input structure and inter-provincial energy allocation efficiency. It shows that total energy efficiency has decreased in recent years, where intra-provincial energy technical efficiency drops markedly and extensive mode of energy consumption rises. However, energy structure and allocation improves slowly. Meanwhile, lacking an integrated energy market leads to the loss of energy efficiency. Further improvement of market allocation and structure adjustment play a pivotal role in the increase of energy efficiency.
Low-Dose Angiotensin II Enhances Pressor Responses Without Causing Sustained Hypertension

Abstract—Subpressor doses of angiotensin II (SP-Ang II) cause a slow increase in blood pressure in rats as assessed by tail cuff plethysmography (TCP), reflecting either sustained hypertension or an exaggerated pressor response to diverse stimuli. We examined whether subpressor doses of Ang II enhance blood pressure responses to simple stress (handling of trained rats for TCP). We implanted telemetry in Sprague-Dawley rats. After 10 days of recovery and TCP training, we implanted osmotic minipumps with either SP-Ang II (50 ng/kg per minute) or vehicle, and then measured systolic blood pressure continuously in unrestrained rats for 13 days. We also recorded telemetry readings while obtaining TCP measurements every 2 days. SP-Ang II increased blood pressure from 134±19 to 159±22 mm Hg by TCP, which matched the simultaneous telemetry readings of 131±20 to 154±25 mm Hg. In contrast, SP-Ang II did not change the blood pressure in the unrestrained rats (measured with continuous telemetry: 124±2 versus 127±1 mm Hg). The blood pressure in the control rats did not change in the unrestrained state (125±3 versus 128±5 mm Hg on days 0 and 12, respectively), and only slightly increased during TCP (11±5 and 6±4 mm Hg by TCP and simultaneous telemetry, respectively; P =NS). In summary, SP-Ang II, although unable to provoke sustained hypertension, nonetheless magnifies the pressor response to otherwise trivial stimuli. We speculate that even modestly elevated Ang II levels may contribute to hypertensive complications because such levels promote the punctuation of an apparent normotensive state by episodic hypertension occasioned by seemingly innocuous stimuli.
The energetic basis of acoustic communication

Animals produce a tremendous diversity of sounds for communication to perform life's basic functions, from courtship and parental care to defence and foraging. Explaining this diversity in sound production is important for understanding the ecology, evolution and behaviour of species. Here, we present a theory of acoustic communication that shows that much of the heterogeneity in animal vocal signals can be explained based on the energetic constraints of sound production. The models presented here yield quantitative predictions on key features of acoustic signals, including the frequency, power and duration of signals. Predictions are supported with data from nearly 500 diverse species (e.g. insects, fishes, reptiles, amphibians, birds and mammals). These results indicate that, for all species, acoustic communication is primarily controlled by individual metabolism such that call features vary predictably with body size and temperature. These results also provide insights regarding the common energetic and neuromuscular constraints on sound production, and the ecological and evolutionary consequences of producing these sounds.
microRNAs: An Emerging Paradigm in Lung Cancer Chemoresistance

Lung cancer is considered the most deadly of all cancers, with limited therapeutic options. Although advanced drugs have been tried in clinic, the therapeutic success has largely been hampered due to rapid development of drug-resistance mechanisms. Recently, microRNAs (miRNAs), a class of small non-coding RNAs, have occupied center stage in cancer biology. miRNAs negatively regulate gene expression either by promoting degradation or by interfering with translation of messenger RNA targets. Several lines of evidence have confirmed the crucial role of miRNAs in carcinogenesis, and, importantly, in the acquisition of resistance to chemotherapeutics. Modulation of miRNA expression levels has been proven to increase the efficacy of genotoxic drugs in various preclinical cancer studies. Therefore, comprehensive understanding of the role(s) of these key players in drug resistance may provide novel opportunities to design effective combinatorial therapeutic strategies for cancer treatment. In this review, we highlight recent findings on miRNAs acting as oncomiRs and tumor suppressor genes in lung cancer. Moreover, we discuss the involvement of miRNAs in different mechanisms of drug resistance in this deadly disease.
General Notes on Law and Economics: Foundations, History and Schools

The application of concepts and tools of economic theory to the science of law with the aim to obtain a comprehensive vision of the human behavior has become, in the last years, in auxiliary discipline that soaks legal and economic sciences. In this paper we examine, in an simple manner, how this practice has being implemented from the Fifties from the last century, specially in the United States, under the ep? teto of "economic analysis of the right", whose generalized conception aims to establish that this one consists of "the application of the economic theory and the econom? tricos methods to examine the formation, structures, process and the legal impact of the law and institutions". The object of this work is to study those schools of economic analysis that determined a way to understand the behavior of that additional variable of the economic system: the law. The aim of the book, then, is not other than to provide to students and professionals with the right, and so that no, of the economy, a frame of reference in Economic Analysis of Law, of way so that the access to the class contents facilitates so much as the consultation of some specific topics in the subject. The first part of the text develops a simple way to undertand the reason why law is a subject of economic theory.
Exact Path Delay Fault Coverage with Fundamental Zero-Suppressed BDD Operations

1 2 We formulate the path delay fault grading problem as a combinatorial problem that amounts to storing and manipulating sets on a special type of Binary Decision Diagrams (BDD), called zero-suppressed binary decision diagrams (ZBDD). The zero-suppressed BDD is a canonical data structure inherently having the property of representing combinational sets very compactly. A simple modification of the basic scheme allows us to increase significantly the storage capability of the data structure with minimal loss in the fault coverage. Experimental results on the ISCAS’85 benchmarks show considerable improvement over all existing techniques for exact PDF grading. The proposed methodology is simple, it consists of a polynomial number of increasingly efficient ZBDD based operations and can handle very large test sets that grade very large number of faults. 1Preliminary results of this work was presented at the International Test Conference, 2001. 2Research supported by NSF grant CCR 0096119.
Options of partners improve carbon for phosphorus trade in the arbuscular mycorrhizal mutualism.

The mutualism between plants and arbuscular mycorrhizal fungi (AMF) is widespread and has persisted for over 400 million years. Although this mutualism depends on fair resource exchange between plants and fungi, inequality exists among partners despite mechanisms that regulate trade. Here, we use (33) P and (14) C isotopes and a split-root system to test for preferential allocation and reciprocal rewards in the plant-AMF symbiosis by presenting a plant with two AMF that differ in cooperativeness. We found that plants received more (33) P from less cooperative AMF in the presence of another AMF species. This increase in (33) P resulted in a reduced (14) C cost per unit of (33) P from less cooperative AMF when alternative options were available. Our results indicate that AMF diversity promotes cooperation between plants and AMF, which may be an important mechanism maintaining the evolutionary persistence of and diversity within the plant-AMF mutualism.
Fulvestrant 500 mg Versus Anastrozole 1 mg for the First-Line Treatment of Advanced Breast Cancer: Overall Survival Analysis From the Phase II FIRST Study

Purpose To compare overall survival (OS) for fulvestrant 500 mg versus anastrozole as first-line endocrine therapy for advanced breast cancer. Patients and Methods The Fulvestrant First-Line Study Comparing Endocrine Treatments (FIRST) was a phase II, randomized, open-label, multicenter trial. Postmenopausal women with estrogen receptor–positive, locally advanced/metastatic breast cancer who had no previous therapy for advanced disease received either fulvestrant 500 mg (days 0, 14, 28, and every 28 days thereafter) or anastrozole 1 mg (daily). The primary end point (clinical benefit rate [72.5% and 67.0%]) and a follow-up analysis (median time to progression [23.4 months and 13.1 months]) have been reported previously for fulvestrant 500 mg and anastrozole, respectively. Subsequently, the protocol was amended to assess OS by unadjusted log-rank test after approximately 65% of patients had died. Treatment effect on OS across several subgroups was examined. Tolerability was evaluated by adverse event monitoring. Results In total, 205 patients were randomly assigned (fulvestrant 500 mg, n = 102; anastrozole, n = 103). At data cutoff, 61.8% (fulvestrant 500 mg, n = 63) and 71.8% (anastrozole, n = 74) had died. The hazard ratio (95% CI) for OS with fulvestrant 500 mg versus anastrozole was 0.70 (0.50 to 0.98; P = .04; median OS, 54.1 months v 48.4 months). Treatment effects seemed generally consistent across the subgroups analyzed. No new safety issues were observed. Conclusion There are several limitations of this OS analysis, including that it was not planned in the original protocol but instead was added after time-to-progression results were analyzed, and that not all patients participated in additional OS follow-up. However, the present results suggest fulvestrant 500 mg extends OS versus anastrozole. This finding now awaits prospective confirmation in the larger phase III FALCON (Fulvestrant and Anastrozole Compared in Hormonal Therapy Naïve Advanced Breast Cancer) trial (ClinicalTrials.gov identifier: NCT01602380).
Gaze guidance reduces the number of collisions with pedestrians in a driving simulator

Our study explores the potential of gaze guidance in driving and analyzes eye movements and driving behavior in safety-critical situations. We collected eye movements from subjects instructed to drive predetermined routes in a driving simulator. While driving, the subjects performed various cognitive tasks designed to divert their attention away from the road. The 30 subjects were equally divided in two groups, a control and a gaze guidance group. For the latter, potentially dangerous events, such as a pedestrian suddenly crossing the street, were highlighted with temporally transient gaze-contingent cues, which were triggered if the subject did not look at the pedestrian. For the group that drove with gaze guidance, eye movements have a reduced variability after the gaze-capturing event and shorter reaction times to it. More importantly, gaze guidance leads to a safer driving behavior and a significantly reduced number of collisions.