Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast Approximate Matching Algorithm for Phone-based Keyword Spotting

Generally, exact matching is widely used for keyword spotting (KWS). Its performance depends heavily on the recognition accuracy. As for phone-based KWS system, the influence of phoneme error rate (PER) on KWS increases as the length of phoneme sequence for the keyword grows. Approximate matching is an alteration to compensate errors in recognition. Compared to exact matching, the calculation cost of approximate matching is extremely larger, limiting its application in KWS systems. In this paper, a fast approximate matching algorithm based on phone confusion network (PCN) is proposed. Given the keyword sequence, only paths with possible minimum edit distance are reserved during detection. Then others with larger edit distance are “generated” by detected ones. All paths are split into sub-paths during processing, which further reduces calculation cost effectively. Experimental results show that our algorithm is faster significantly than before optimization, with little performance degradation
Modeling and analysis of ergodic capacity in network MIMO systems

This paper studies the downlink ergodic capacity of a network multiple-input multiple-output (MIMO) system. The system model includes base-stations (BSs) randomly distributed with a fixed density, each equipped with M antennas, scheduling K single-antenna users, and forming cooperating clusters via perfect backhaul links. Intra-cluster interference is eliminated by joint transmission using zero-forcing beamforming assuming perfect channel state information (CSI), while inter-cluster interference remains. This paper shows that although coordinating a large cluster of BSs eliminates strong interferers, the coordination gain depends on the network load factor, defined as the relative ratio of M and K. In particular, we show that with M = K, increasing the coordination cluster size is only beneficial for the cluster-edge users, while degrading the ergodic capacity of the users located close to the cluster center. In contrast, when M > K, increasing the cluster size potentially improves every user's ergodic capacity. In the second part of this paper, we use tools from stochastic geometry to account for random BS locations in characterizing the performance of network MIMO systems. In this setting, we model the BS locations according to a homogeneous Poisson point process with a fixed density, and propose tractable, yet accurate, distribution functions for the signal and inter-cluster interference powers. We then derive an efficiently computable expression for the user ergodic capacity as a function of the distance between a user and the cluster center.
Engaging Local Communities in Low Emissions Land-Use Planning: a Case Study from Laos

Reducing Emissions from Deforestation and Forest Degradation and enhancing forest carbon stocks (REDD+) is a performance-based payment mechanism currently being debated in international and national environmental policy and planning forums. As the mechanism is based on conditionality, payments must reflect land stewards' level of compliance with carbon-efficient management practices. However, lack of clarity in land governance and carbon rights could undermine REDD+ implementation. Strategies are needed to avoid perverse incentives resulting from the commoditization of forest carbon stocks and, importantly, to identify and secure the rights of legitimate recipients of future REDD+ payments. We propose a landscapelevel approach to address potential conflicts related to carbon tenure and REDD+ benefit sharing. We explore various landtenure scenarios and their implications for carbon ownership in the context of a research site in northern Laos. Our case study shows that a combination of relevant scientific tools, knowledge, and participatory approaches can help avoid the marginalization of rural communities during the REDD+ process. The findings demonstrate that participatory land-use planning is an important step in ensuring that local communities are engaged in negotiating REDD+ schemes and that such negotiations are transparent. Local participation and agreements on land-use plans could provide a sound basis for developing efficient measurement, reporting, and verification systems for REDD+.
Iterated Space-Time Code Constructions From Cyclic Algebras

We propose a full-rate iterative space-time code construction, which uses an algebraic space-time code in order to design a new space-time code of double the code rank. We give a condition for determining whether the resulting codes satisfy the full diversity property, and study their maximum likelihood decoding complexity with respect to sphere decoding. Particular emphasis is given to the asymmetric multiple input double output codes. In the process, we derive an interesting way of obtaining division algebras, and study their centers and maximal subfields.
The unreliability of CT numbers as absolute values.

The use of CT numbers as absolute values was examined by scanning a standard phantom on five CT scanners under a variety of conditions simulating those encountered in routine body CT scanning. The results show that: (1) There are significant differences in absolute CT numbers between most scanners (only one scanner produced CT numbers that were equal to zero for water); (2) There are significant differences in absolute CT numbers between two scanners of the same manufacturer and model that were examined; (3) There is a significant difference in CT numbers in a single phantom scan, dependent on location in the scan, and the format of this variability is not constant from one scanner to another; and (4) There may be a significant difference in absolute CT numbers depending on various physical factors (e.g., kilovoltage, phantom orientation in scan aperture, and position of the phantom in the scan aperture). The findings suggest that there is a wide range of CT numbers observed for a given tissue type as a result of scanner performance alone, and that if absolute CT numbers are to be used for diagnosis the user must document that these machine-related variations are less than the differences thought to be significant.
Surveillance with Alert Management System Using Conventional Cell Phones

In the present paper we expose the development of a real-time monitoring prototype of human activities using a single cell phone equipped with some sensors. The monitoring system is reduced to the minimum expression; no special hardware is required as far as a conventional cell phone will monitor the user, classify the user activities with respect to a customized rule’s set, and finally trigger the corresponding alerts, when necessary.
Achievable Rate of Downlink Superposition Coding with Channel State Feedback

In this paper, we consider superposition coding (SC) scheme in a multiple-input multiple-output (MIMO) broadcast channel when the transmitter obtains the channel state information (CSI) through user's quantized feedback. The algorithms for the base station (BS) scheduling, including users selection, power allocation among co-scheduled users, and precoding matrix assignment are investigated. We also derive bounds for the achievable rates of the SC scheme with quantized CSI feedback and imperfect user measurement being taken into account.
Efficient self-timed interfaces for crossing clock domains

With increasing integration densities, large chip designs are commonly partitioned into multiple clock domains. While the computation within each individual domain may be synchronous, the interfaces between these domains often use asynchronous methods. One such approach is the STARI technique where a self-timed FIFO compensates for clock-skew between the sender and receiver. We present implementations of STARI where the FIFO consists of a single, handshaking stage. We start with the simplest case where the sender and receiver operate at exactly the same frequency with an unknown skew. We then generalize this design for links with clocks whose frequencies are rational multiples of each other, clocks whose frequencies are closely matched, and arbitrary clocks. We show that in each of these cases, the STARI interface can exploit the stability of typical clocks to achieve low latencies and negligible probabilities of synchronization failure using very simple hardware.
Role of Redox Signaling and Inflammation in Skeletal Muscle Adaptations to Training

The inflammatory response to exercise-induced muscle damage has been extensively described. Exercise has important modulatory effects on immune function. These effects are mediated by diverse factors including pro-inflammatory cytokines, classical stress hormones, and hemodynamic effects leading to cell redistribution. As has been reported regarding oxidative stress, inflammation can have both detrimental and beneficial effects in skeletal muscle. In this review we will address the role of inflammation on protein metabolism in skeletal muscle. Specifically, we will review studies showing that treatment with cyclooxygenase-inhibiting drugs modulate the protein synthesis response to one bout of resistance exercise and to training. Understanding how these drugs work is important for the millions of individuals worldwide that consume them regularly. We will also discuss the importance of reactive oxygen species and inflammatory cytokines in muscle adaptations to exercise and the Janus faced of the use of antioxidant and anti-inflammatory drugs by athletes for optimizing their performance, especially during the periods in which muscle hypertrophy is expected.
A Case of Radiation Fibrosis Appearing as Mass-Like Consolidation after SBRT with Elevation of Serum CEA

We report a case of radiation fibrosis appearing as mass-like consolidation, which was difficult to distinguish from local recurrence. A 72-year-old woman was diagnosed as having primary lung cancer (cT1N0M0 stage IA) in the right upper lobe and was treated with SBRT of 48 Gy in 4 fractions. After 12 months, mass-like consolidation appeared around the irradiated area, and after 13 months, it had increased in size. FDG-PET revealed high uptake (SUV max = 5.61) for the consolidation. CT-guided biopsy was performed, but we could not confirm the diagnosis. Considering her poor respiratory function and her age, short-interval follow-up was performed. After 15 months, the consolidation enlarged at the dorsal side, and carcinoembryonic antigen (CEA) became elevated (14.6 ng/mL). Serum KL-6 (436 U/mL) and SP-D (204 ng/mL) were also elevated. However, after 16 months, serum CEA slightly decreased. The consolidation gradually retracted on follow-up CT images. CEA, KL-6, and SP-D were also decreased by degrees. After 40 months, there is no evidence of local recurrence.
POLITICAL LEADERSHIP AND NATIONAL SECURITY IN THE NIGERIA

This paper discusses political leadership and national security in the Nigerian fourth republic. The paper accentuates that the democratic process itself constitute a functional mechanism for interest articulation and aggregation thereby checking agent threat to national security that may arise from lack of input or participation in the political process. The paper through the use of leadership theoretical perspectives unfolds the practice of democratic governance in the Nigerian state as a characterization of poor political leade means of placing demands on the Nigerian political system by ethnic nationalities as a result of lost of confidence in the democratic process. This scenario to a great extent has created heightened political tension in the allocation of state resources and as a matter of fact threatens both the present democratic experiment and he unity of the Nigeria state. federalism that is anchored on fiscal responsibility of component states as well as quality political leadership that is anchored on the people.
Codename Revolution: The Nintendo Wii Platform

process for production itself’ (p. 251). Organizing, measuring, promoting and other ancillary activities improve production, distribution and consumption, but, Comor notes, ‘unwaged concrete prosumer labor . cannot itself produce surplus value’ (p. 258). Facebook, YouTube and other aggregators of UGC gather, organize and sell audiences attracted to their content, but the work formally exploited – and the value directly produced – is the result of a social media company ‘processing and packaging this content for its primary clients: advertisers and marketers’ (p. 259). Comor argues that only by revising the labour theory of value can we ‘view digital prosumption as the basis of some kind of universal exploitation’ (p. 259). Of course, it becomes increasingly difficult in a simulacrum world of spectacle to link capitalist production with the ‘upside-down illusions they generate’ (p. 263), but here, Comor models an exemplary insistence on historical materialist precision. In his closing essay, Christian Fuchs still insists that ‘the entire planet is today a capitalist factory’ (p. 276), which is one giant leap for humankind’s confusion. It is empirically undeniable that much of the planet is part of the capitalist system, but to collapse social classes, productive relations and all of the complex, diverse means of production into one amorphous factory churning out private profit in every human action seems a tad overstated. Even so, Fuchs’ polemical overview of contemporary debates clearly lays out a theoretical terrain informed by Smythe’s work that might inform critical research and political activity. Undoubtedly, competing theoretical positions have practical consequences for strategy and outcomes, but all readers should be inspired by Fuchs’ call for Marxist scholars to research, publish, organize, debate, support and connect with struggles for socialism. Although some of the arguments presented in this collection may politically misdirect, the project’s commitment and final call cannot be disputed: all times are the right times to fight for social justice. And now is that time.
Serum dehydroepiandrosterone sulfate concentration as an indicator of adrenocortical suppression during inhaled steroid therapy in adult asthmatic patients.

OBJECTIVE Supraphysiological doses of exogenous glucocorticosteroids cause adrenocortical suppression. Dehydroepiandrosterone sulfate (DHEA-S) is the most abundant adrenal androgen and estrogen precursor. We studied to what extent inhaled glucocorticosteroid therapy for asthma decreases serum DHEA-S concentrations. DESIGN AND METHODS We measured serum DHEA-S and cortisol concentrations in 101 adult patients with newly detected mild asthma before and after 2 and 12 weeks of treatment with inhaled glucocorticosteroids. The patients were randomized to receive budesonide 200 microg/day (low dose group, n=50) or 800 microg/day (high dose group, n=51) in two parallel groups double-blindly. RESULTS In the low dose group, serum DHEA-S concentrations decreased from the baseline by a mean of 8 % (95 % confidence interval (CI), 3-13 %, P<0.01) after 2 weeks of therapy, and by 2 % (95 % CI, 9 % decrease to 5 % increase, NS) after 12 weeks. In the high dose group, the respective decreases were 16 % (95 % CI, 10-21 %, P<0.001) and 18 % (95 % CI, 12-24 %, P<0.001). The difference between the treatment groups was significant at both 2 and 12 weeks. During the 12 week treatment period the baseline concentrations of serum cortisol did not decrease in the low dose group, while in the high dose group the decrease was significant at 12 weeks (P<0.01), but not at 2 weeks. The forced expiratory volume in 1 s improved equally well in both groups. CONCLUSIONS Inhaled budesonide decreased serum DHEA-S concentrations, which may indicate adrenocortical suppression. Reduced adrenal production of androgen and estrogen precursors may increase the risk of osteoporosis especially in postmenopausal women.
Fundamental characteristics of queues with fluctuating load

Systems whose arrival or service rates fluctuate over time are very common, but are still not well understood analytically. Stationary formulas are poor predictors of systems with fluctuating load. When the arrival and service processes fluctuate in a Markovian manner, computational methods, such as Matrix-analytic and spectral analysis, have been instrumental in the numerical evaluation of quantities like mean response time. However, such computational tools provide only limited insight into the functional behavior of the system with respect to its primitive input parameters: the arrival rates, service rates, and rate of fluctuation.For example, the shape of the function that maps rate of fluctuation to mean response time is not well understood, even for an M/M/1 system. Is this function increasing, decreasing, monotonic? How is its shape affected by the primitive input parameters? Is there a simple closed-form approximation for the shape of this curve? Turning to user experience: How is the performance experienced by a user arriving into a "high load" period different from that of a user arriving into a "low load" period, or simply a random user. Are there stochastic relations between these? In this paper, we provide the first answers to these fundamental questions.
Achievable error exponents for channel with side information — erasure and list decoding

We consider a decoder with an erasure option and a variable size list decoder for channels with non-causal side information at the transmitter. First, universally achievable error exponents are offered for decoding with an erasure option using a parameterized decoder in the spirit of Csiszar and Korner's decoder. Then, the proposed decoding rule is generalized by extending the range of its parameters to allow variable size list decoding. This extension gives a unified treatment for erasure/list decoding. Exponential bounds on the probability of list error and the average number of incorrect messages on the list are given. Relations to Forney's and Csiszar and Korner's decoders for DMC are discussed. These results are obtained by exploring a random binning code with conditionally constant composition codewords proposed by Moulin and Wang, but with a different decoder.
Subnetwork analysis reveals dynamic features of complex (bio)chemical networks

In analyzing and mathematical modeling of complex (bio)chemical reaction networks, formal methods that connect network structure and dynamic behavior are needed because often, quantitative knowledge of the networks is very limited. This applies to many important processes in cell biology. Chemical reaction network theory allows for the classification of the potential network behavior—for instance, with respect to the existence of multiple steady states—but is computationally limited to small systems. Here, we show that by analyzing subnetworks termed elementary flux modes, the applicability of the theory can be extended to more complex networks. For an example network inspired by cell cycle control in budding yeast, the approach allows for model discrimination, identification of key mechanisms for multistationarity, and robustness analysis. The presented methods will be helpful in modeling and analyzing other complex reaction networks.
MUltiple Sclerosis and Extract of Cannabis: results of the MUSEC trial

Objective Multiple sclerosis (MS) is associated with chronic symptoms, including muscle stiffness, spasms, pain and insomnia. Here we report the results of the Multiple Sclerosis and Extract of Cannabis (MUSEC) study that aimed to substantiate the patient based findings of previous studies. Patients and methods Patients with stable MS at 22 UK centres were randomised to oral cannabis extract (CE) (N=144) or placebo (N=135), stratified by centre, walking ability and use of antispastic medication. This double blind, placebo controlled, phase III study had a screening period, a 2 week dose titration phase from 5 mg to a maximum of 25 mg of tetrahydrocannabinol daily and a 10 week maintenance phase. The primary outcome measure was a category rating scale (CRS) measuring patient reported change in muscle stiffness from baseline. Further CRSs assessed body pain, spasms and sleep quality. Three validated MS specific patient reported outcome measures assessed aspects of spasticity, physical and psychological impact, and walking ability. Results The rate of relief from muscle stiffness after 12 weeks was almost twice as high with CE than with placebo (29.4% vs 15.7%; OR 2.26; 95% CI 1.24 to 4.13; p=0.004, one sided). Similar results were found after 4 weeks and 8 weeks, and also for all further CRSs. Results from the MS scales supported these findings. Conclusion The study met its primary objective to demonstrate the superiority of CE over placebo in the treatment of muscle stiffness in MS. This was supported by results for secondary efficacy variables. Adverse events in participants treated with CE were consistent with the known side effects of cannabinoids. No new safety concerns were observed. Trial registration number NCT00552604.
Roillo: Creating a Social Robot for Playrooms

In this paper, we introduce Roillo, a social robotic platform for investigating, in the context of children's playrooms, questions about how to design compelling nonverbal interactive behaviors for social robots. Specifically, we are interested in the importance of rhythm to natural interactions and its role in the expression of affect, attention, and intent. Our design process has consisted of rendering, animation, surveys, mechanical prototyping, and puppeteered interaction with children
Model Adaptation and Active Learning in the BBN Speech Activity Detection System for the DARPA RATS Program

Model adaptation is an important task in many human language technology fields, as it allows one to reduce differences that arise due to various forms of variability. Here, we focus on the speech activity detection (SAD) task, in the context of the DARPA RATS program, where the training data do not cover all channels (transmitter/receiver characteristics) that are encountered at test time. For supervised adaptation, limited manually labeled data from the (novel) channel of interest are used to adapt the model; for unsupervised adaptation, the labels are automatically generated with a baseline model. The modeling is done with long short-term memory neural networks, and we make the case that strong regularization is of paramount importance when adapting such models. Results on two different datasets show that adaptation gives rise to large gains (at least 27related task, that of active learning, is also considered. In active learning, data to be annotated for supervised adaptation are selected automatically, with the ultimate goal of maximizing performance. We investigate an algorithm for active learning that utilizes the output of a SAD decoder and show that it performs significantly better (by 10% relative) than random selection.