Miracle-dz/UniFAR-FTUs huggingface dataset:
On the robustness of two time-scale stochastic approximation algorithms

Motivated by the problem of the asymptotic behavior of a class of actor-critic learning algorithms recently proposed by Konda and Tsitsiklis, the almost sure asymptotic properties of two time-scale stochastic approximation are analyzed under violated Kushner-Clark noise conditions and very general stability conditions. The analysis covers the algorithms with additive noise, as well as those with nonadditive noise. The algorithms with additive noise are analyzed for the case where the noise is state-dependent. The analysis of the algorithms with non-additive state-dependent noise is carried out for the case where the noise is a Markov chain controlled by the algorithm states, while the algorithms with non-additive exogenous noise are analyzed for the case where the noise is correlated and satisfies uniform or strong mixing conditions. The obtained results characterize the robustness of two time-scale stochastic approximation towards the violation of the Kushner-Clark noise condition. Moreover, they cover a fairly broad class of highly non-linear two time-scale stochastic approximation algorithms, including the actor-critic learning algorithms proposed by Konda and Tsitsiklis.
Probabilistic models for the transcription of single-voice melodies

A method is proposed for the automatic transcription of single-voice melodies from an acoustic waveform into a symbolic musical notation (a MIDI file). The system consists of a signal processing front-end which calculates a continuous pitch track and of a probabilistic model which converts the pitch track into a discrete musical notation. Our proposed probabilistic model consists of three parts operating in parallel: a pitch trajectory model, a musicological model, and a duration model. The first handles imperfections in the performed/estimated pitch values using a hidden Markov model, the second estimates musical key signature to improve the transcription accuracy, and the last models the duration of the notes.
Analysis and design of a low sidelobe level and wide-band aperture coupled microstrip antenna array using FDTD

This paper presents a low sidelobe level (SLL) and wide-band 8×8 aperture coupled microstrip antenna array. For rigorous analysis of element characteristics, a single aperture coupled microstrip antenna is analyzed using finite difference time domain (FDTD). Consideration imperfect ground planes in antenna and the finite structure, one finds that FDTD gives more precise results for element designing. To achieve improvement in SLL, Dolf-Chebyshev power distribution is used in the antenna design. Measured results demonstrate that the impedance bandwidth of the proposed antenna is 12% at the center frequency of 5 GHz and average E-plane and H-plane SLL are less than -23 dB. The average gain of the antenna array is 22.5 dB.
Excluded volume in protein side-chain packing.

The excluded volume occupied by protein side-chains and the requirement of high packing density in the protein interior should severely limit the number of side-chain conformations compatible with a given native backbone. To examine the relationship between side-chain geometry and side-chain packing, we use an all-atom Monte Carlo simulation to sample the large space of side-chain conformations. We study three models of excluded volume and use umbrella sampling to effectively explore the entire space. We find that while excluded volume constraints reduce the size of conformational space by many orders of magnitude, the number of allowed conformations is still large. An average repacked conformation has 20 % of its chi angles in a non-native state, a marked reduction from the expected 67 % in the absence of excluded volume. Interestingly, well-packed conformations with up to 50 % non-native chi angles exist. The repacked conformations have native packing density as measured by a standard Voronoi procedure. Entropy is distributed non-uniformly over positions, and we partially explain the observed distribution using rotamer probabilities derived from the Protein Data Bank database. In several cases, native rotamers that occur infrequently in the database are seen with high probability in our simulation, indicating that sequence-specific excluded volume interactions can stabilize rotamers that are rare for a given backbone. In spite of our finding that 65 % of the native rotamers and 85 % of chi(1) angles can be predicted correctly on the basis of excluded volume only, 95 % of positions can accommodate more than one rotamer in simulation. We estimate that, in order to quench the side-chain entropy observed in the presence of excluded volume interactions, other interactions (hydrophobic, polar, electrostatic) must provide an additional stabilization of at least 0.6 kT per residue in order to single out the native state.
One-class Classification to Detect Botnets in IoT devices ∗

With the increasing number of different Internet of Things devices, new threats to network security emerge due to these devices’ low security. Botnets are a widespread threat that takes advantage of IoT devices vulnerabilities to compromise multiple devices and perform coordinated attacks. To tackle this, new methods addressing IoT botnets detection are required. In this paper, we propose a host-based detection system based on one-class classifiers. It was used a One-class Support Vector Machine built with features such as CPU and memory usage to detect malicious activities. The predictive performance and resource consumption of the proposed approach was evaluated in a controlled network using three different legitimate settings and seven IoT botnets. The results indicate that the proposed system is efficient in detecting different botnets with low resource consumption.
Relating complexity and precision in control flow analysis

We analyze the computational complexity of kCFA, a hierarchy of control flow analyses that determine which functions may be applied at a given call-site. This hierarchy specifies related decision problems, quite apart from any algorithms that may implement their solutions. We identify a simple decision problem answered by this analysis and prove that in the 0CFA case, the problem is complete for polynomial time. The proof is based on a nonstandard, symmetric implementation of Boolean logic within multiplicative linear logic (MLL). We also identify a simpler version of 0CFA related to η-expansion, and prove that it is complete for logarithmic space, using arguments based on computing paths and permutations. For any fixed k>0, it is known that kCFA (and the analogous decision problem) can be computed in time exponential in the program size. For k=1, we show that the decision problem is NP-hard, and sketch why this remains true for larger fixed values of k. The proof technique depends on using the approximation of CFA as an essentially nondeterministic computing mechanism, as distinct from the exactness of normalization. When k=n, so that the "depth" of the control flow analysis grows linearly in the program length, we show that the decision problem is complete for exponential time. In addition, we sketch how the analysis presented here may be extended naturally to languages with control operators. All of the insights presented give clear examples of how straightforward observations about linearity, and linear logic, may in turn be used to give a greater understanding of functional programming and program analysis.
Gendered Challenge, Gendered Response

This article integrates research on gendered organizations and the work-family interface to investigate an innovative workplace initiative, the Results-Only Work Environment (ROWE), implemented in the corporate headquarters of Best Buy, Inc. While flexible work policies common in other organizations “accommodate” individuals, this initiative attempts a broader and deeper critique of the organizational culture. We address two research questions: How does this initiative attempt to change the masculinized ideal worker norm? And what do women’s and men’s responses reveal about the persistent ways that gender structures work and family life? Data demonstrate the ideal worker norm is pervasive and powerful, even as employees begin critically examining expectations regarding work time that have historically privileged men. Employees’ responses to ROWE are also gendered. Women (especially mothers) are more enthusiastic, while men are more cautious. Ambivalence about and resistance to change is expressed in different ways depending on gender and occupational status.
Genetic Deletion of Neuronal PPARγ Enhances the Emotional Response to Acute Stress and Exacerbates Anxiety: An Effect Reversed by Rescue of Amygdala PPARγ Function

PPARγ is one of the three isoforms of the Peroxisome Proliferator-Activated Receptors (PPARs). PPARγ is activated by thiazolidinediones such as pioglitazone and is targeted to treat insulin resistance. PPARγ is densely expressed in brain areas involved in regulation of motivational and emotional processes. Here, we investigated the role of PPARγ in the brain and explored its role in anxiety and stress responses in mice. The results show that stimulation of PPARγ by pioglitazone did not affect basal anxiety, but fully prevented the anxiogenic effect of acute stress. Using mice with genetic ablation of neuronal PPARγ (PPARγNestinCre), we demonstrated that a lack of receptors, specifically in neurons, exacerbated basal anxiety and enhanced stress sensitivity. The administration of GW9662, a selective PPARγ antagonist, elicited a marked anxiogenic response in PPARγ wild-type (WT), but not in PPARγNestinCre knock-out (KO) mice. Using c-Fos immunohistochemistry, we observed that acute stress exposure resulted in a different pattern of neuronal activation in the amygdala (AMY) and the hippocampus (HIPP) of PPARγNestinCre KO mice compared with WT mice. No differences were found between WT and KO mice in hypothalamic regions responsible for hormonal response to stress or in blood corticosterone levels. Microinjection of pioglitazone into the AMY, but not into the HIPP, abolished the anxiogenic response elicited by acute stress. Results also showed that, in both regions, PPARγ colocalizes with GABAergic cells. These findings demonstrate that neuronal PPARγ is involved the regulation of the stress response and that the AMY is a key substrate for the anxiolytic effect of PPARγ. SIGNIFICANCE STATEMENT Peroxisome Proliferator-Activated Receptor Gamma (PPARγ) is a classical target for antidiabetic therapies with thiazolidinedione compounds. PPARγ agonists such as rosiglitazone and pioglitazone are in clinical use for the treatment of insulin resistance. PPARγ has recently attracted attention for its involvement in the regulation of CNS immune response and functions. Here, we demonstrate that neuronal PPARγ activation prevented the negative emotional effects of stress and exerted anxiolytic actions without influencing hypothalamic–pituitary–adrenal axis function. Conversely, pharmacological blockade or genetic deletion of PPARγ enhanced anxiogenic responses and increased vulnerability to stress. These effects appear to be controlled by PPARγ neuronal-mediated mechanisms in the amygdala.
A controllable anti-aliasing filter for digital film cameras

In this paper, the theoretical foundation and practical implementation of a controllable anti-aliasing filter for digital film cameras is presented. A prototype of an optical anti-aliasing filter that is based on moving a parallel optical window was designed and built to demonstrate the ability to control the spatial frequency response of an acquisition system. During the image exposure, four spring-preloaded voice coils rapidly change the pitch and yaw of the parallel window, resulting in a displacement of the image content that is projected onto the sensor. The image content displacement during the exposure results in altering the frequency response of the scene that is captured by the sensor. Specifically, during the exposure time, a carefully controlled movement of the parallel optical window results in a circular trajectory of the image content that is projected onto the sensor. By increasing or decreasing the radius of the circular trajectory, the spatial cut-off frequency of the system is dynamically modified. In addition to the circular path, this paper shows theoretical justification and demonstrates the use of more complex trajectories, such as double circular, elliptical, and one-dimensional rectangular trajectories. These trajectories improve the suppression of aliased components in the acquired image.
National trends in Staphylococcus aureus infection rates: impact on economic burden and mortality over a 6-year period (1998-2003).

BACKGROUND We evaluated historical trends in the Staphylococcus aureus infection rate, economic burden, and mortality in US hospitals from 1998 through 2003. METHODS The Nationwide Inpatient Sample was used to assess trends over time of S. aureus infection during 1998-2003. Historical trends were determined for 5 strata of hospital stays, including all inpatient stays, surgical procedure stays, invasive cardiovascular surgical stays, invasive orthopedic surgical stays, and invasive neurosurgical stays. RESULTS During the 6-year study period from 1998 through 2003, the rate of S. aureus infection increased significantly for all inpatient stays (from 0.74% to 1.0%; annual percentage change (APC), 7.1%; P=. 004), surgical stays (from 0.90% to 1.3%; APC, 7.9%; P=.001), and invasive orthopedic surgical stays (from 1.2% to 1.8%; APC, 9.3%; P<.001). For invasive neurosurgical stays, the rate of S. aureus infection did not change from 1998 to 2000 but increased at an annual rate of 11.0% from 2000 to 2003 (from 1.4% to 1.8%; P=.034). The total economic burden of S. aureus infection for hospitals also increased significantly for all stay types, with the annual percentage increase ranging from 9.2% to 17.9% (P<.05 for all). In 2003, the total economic burden of S. aureus infection was estimated to be $14.5 billion for all inpatient stays and $12.3 billion for surgical patient stays. However, there were significant decreases in the risk of S. aureus-related in-hospital mortality from 1998 to 2003 for all inpatient stays (from 7.1% to 5.6%; APC, -4.6%; P=.001) and for surgical stays (from 7.1% to 5.5%; APC, -4.6%; P=.002). CONCLUSIONS The inpatient S. aureus infection rate and economic burden of S. aureus infections for US hospitals increased substantially from 1998 to 2003, whereas the in-hospital mortality rate decreased.
Class-dependent two-dimensional linear discriminant analysis using two-pass recognition strategy

In this paper, we introduce a novel class-dependent extension of two-dimensional linear discriminant analysis (2DLDA) named CD-2DLDA, applied in automatic speech recognition using two-pass recognition strategy. In the first pass, the class labels of test sample are obtained using baseline recognition. The labels are then used in CD transformation of test features. In the second pass, recognition of previously transformed test samples is performed using CD-2DLDA acoustic model. The novelty of the paper lies in improvement of the present 2DLDA algorithm by its modification to more precise, class-dependent estimations repeated separately for each class. The proposed approach is evaluated in several scenarios using the TIMIT corpus in phoneme-based continuous speech recognition task. CD-2DLDA features are compared to state-of-the-art MFCCs, conventional LDA and 2DLDA features. The experimental results show that our method performs better than MFCCs and LDA. Furthermore, the results confirm that CD-2DLDA markedly outperforms the 2DLDA method.
A building-transmission model for improved propagation prediction in urban microcells

This paper presents a model for the propagation of radiowaves through buildings. The model can be used as a seamless extension to ray-based propagation prediction models that only consider external reflection and diffraction, as do most current models. This involves the use of so-called transmitted rays, which are traced through building walls. Outdoor-to-indoor propagation (building penetration) is automatically taken into account as a "by-product". The transmission model requires no information about each building's interior other than a specific attenuation factor that describes the global behavior of the field inside the building. This coefficient can be determined for individual buildings by measuring the excess loss associated with the propagation path through the building. It is shown, however, that no large errors are to be expected if all buildings are characterized by the average of the empirical values obtained in this study, at 1.9 GHz. Path loss predictions generated with the aid of the new model are shown and compared with measured data to illustrate the considerable improvement in accuracy that can be achieved in realistic urban microcell scenarios by taking into account building penetration and transmission.
Subspace Gaussian mixture model with state-dependent subspace dimensions

In recent years, under the hidden Markov modeling (HMM) framework, the use of subspace Gaussian mixture models (SGMMs) has demonstrated better recognition performance than traditional Gaussian mixture models (GMMs) in automatic speech recognition. In state-of-the-art SGMM formulation, a fixed subspace dimension is assigned to every phone states. While a constant subspace dimension is easier to implement, it may, however, lead to overfitting or underfitting of some state models as the data is usually distributed unevenly among the states. In a later extension of SGMM, states are split to sub-states with an appropriate objective function so that the problem is eased by increasing the state-specific parameters for the underfitting state. In this paper, we propose another solution and allow each sub-state to have a different subspace dimension depending on its amount of training frames so that the state-specific parameters can be robustly estimated. Experimental evaluation on the Switchboard recognition task shows that our proposed method brings improvement to the existing SGMM training procedure.
Insights into the environmental reservoir of pathogenic Vibrio parahaemolyticus using comparative genomics

Vibrio parahaemolyticus is an aquatic halophilic bacterium that occupies estuarine and coastal marine environments, and is a leading cause of seafood-borne food poisoning cases. To investigate the environmental reservoir and potential gene flow that occurs among V. parahaemolyticus isolates, the virulence-associated gene content and genome diversity of a collection of 133 V. parahaemolyticus isolates were analyzed. Phylogenetic analysis of housekeeping genes, and pulsed-field gel electrophoresis, demonstrated that there is genetic similarity among V. parahaemolyticus clinical and environmental isolates. Whole-genome sequencing and comparative analysis of six representative V. parahaemolyticus isolates was used to identify genes that are unique to the clinical and environmental isolates examined. Comparative genomics demonstrated an O3:K6 environmental isolate, AF91, which was cultured from sediment collected in Florida in 2006, has significant genomic similarity to the post-1995 O3:K6 isolates. However, AF91 lacks the majority of the virulence-associated genes and genomic islands associated with these highly virulent post-1995 O3:K6 genomes. These findings demonstrate that although they do not contain most of the known virulence-associated regions, some V. parahaemolyticus environmental isolates exhibit significant genetic similarity to clinical isolates. This highlights the dynamic nature of the V. parahaemolyticus genome allowing them to transition between aquatic and host-pathogen states.
Continuous-Time Markowitz's Model with Transaction Costs

A continuous-time Markowitz's mean-variance portfolio selection problem is studied in a market with one stock, one bond, and proportional transaction costs. This is a singular stochastic control problem, inherently with a finite time horizon. Via a series of transformations, the problem is turned into a so-called double obstacle problem, a well-studied problem in physics and PDE literature, featuring two time-varying free boundaries. The two boundaries, which define the buy, sell, and no-trade regions, are proved to be smooth in time. This in turn characterizes the optimal strategy, via a Skorokhod problem, as one that tries to keep a certain adjusted bond-stock position within the no-trade region. Several features of the optimal strategy are revealed that are remarkably different from its no-transaction-cost counterpart. It is shown that there exists a critical length in time, which is dependent on the stock excess return as well as the transaction fees but independent of the investment target and the stock volatility, so that an expected terminal return may not be achievable if the planning horizon is shorter than that critical length (while in the absence of transaction costs any expected return can be reached in an arbitrary period of time). It is further demonstrated that anyone following the optimal strategy should not buy the stock beyond the point when the time to maturity is shorter than the aforementioned critical length. Moreover, the investor would be less likely to buy the stock and more likely to sell the stock when the maturity date is getting closer. These features, while consistent with the widely accepted investment wisdom, suggest that the planning horizon is an integral part of the investment opportunities.
Specific Hypotheses on the Geographic Mosaic of Coevolution

Coevolution is one of the major processes organizing the earth's biodiversity. The need to understand coevolution as an ongoing process has grown as ecological concerns have risen over the dynamics of rapidly changing biological communities, the conservation of genetic diversity, and the population biology of diseases. The biggest current challenge is to understand how coevolution operates across broad geographic landscapes, linking local ecological processes with phylogeographic patterns. The geographic mosaic theory of coevolution provides a framework for asking how coevolution continually reshapes interactions across different spatial and temporal scales. It produces specific hypotheses on how geographically structured coevolution differs from coevolution at the local scale. It also provides a framework for understanding how local maladaptation can result from coevolution and why coevolved interactions may rarely produce long lists of coevolved traits that become fixed within species. Long‐term field studies of the same interaction across multiple communities and spatially structured mathematical models are together beginning to show that coevolution may be a more important ongoing process than had been indicated by earlier empirical and theoretical studies lacking a geographic perspective.