Miracle-dz/UniFAR-FTUs huggingface dataset:
Sound Event Localization and Detection of Overlapping Sources Using Convolutional Recurrent Neural Networks

In this paper, we propose a convolutional recurrent neural network for joint sound event localization and detection (SELD) of multiple overlapping sound events in three-dimensional (3-D) space. The proposed network takes a sequence of consecutive spectrogram time frames as input and maps it to two outputs in parallel. As the first output, the sound event detection (SED) is performed as a multi-label classification task on each time frame producing temporal activity for all the sound event classes. As the second output, localization is performed by estimating the 3-D Cartesian coordinates of the direction-of-arrival (DOA) for each sound event class using multi-output regression. The proposed method is able to associate multiple DOAs with respective sound event labels and further track this association with respect to time. The proposed method uses separately the phase and magnitude component of the spectrogram calculated on each audio channel as the feature, thereby avoiding any method- and array-specific feature extraction. The method is evaluated on five Ambisonic and two circular array format datasets with different overlapping sound events in anechoic, reverberant, and real-life scenarios. The proposed method is compared with two SED, three DOA estimation, and one SELD baselines. The results show that the proposed method is generic and applicable to any array structures, robust to unseen DOA values, reverberation, and low SNR scenarios. The proposed method achieved a consistently higher recall of the estimated number of DOAs across datasets in comparison to the best baseline. Additionally, this recall was observed to be significantly better than the best baseline method for a higher number of overlapping sound events.
A reconfigurable multi-ratio charge pump with wide input/output voltage range for wireless energy harvesting system

A charge pump (CP) with reconfigurable multi-ratio is proposed for wireless energy harvesting system, which has almost eight ratios with small step to suit for wide input or output voltage range applications. Six flying capacitors are adopted to generate different conversion ratios (CRs) from ×0.25 to ×2 with step of 0.25. The CR of the CP is determined by input voltage and on-chip control unit. Thus, an almost constant output voltage is obtained in a wide input voltage range. Besides, the MOS switches of the CP are driven by a two-phase non-overlapping clock to reduce quiescent current and improve the power conversion efficiency (PCE). As a result, a configurable CP is achieved by using a standard 0.35 μm CMOS process with 1.7 mm2 die area (include PADs.) The output voltage of the CP can be kept almost constant at 3.6 V when Vin varies from 1.77 V to 4.80 V. The PCE is over 80% no matter which CR is, and the maximum PCE of 93.8% is achieved when Vin=3.6 and CR=1 @ 1.2 KΩ load resistance. The wide input/output voltage range and PCE of the proposed CP shows its good practicality for DC-DC converter of wireless energy harvesting system.
Structural and Functional Insights Into Lysostaphin–Substrate Interaction

Lysostaphin from Staphylococcus simulans and its family enzymes rapidly acquire prominence as the next generation agents in treatment of S. aureus infections. The specificity of lysostaphin is promoted by its C-terminal cell wall targeting domain selectivity toward pentaglycine bridges in S. aureus cell wall. Scission of these cross-links is carried out by its N-terminal catalytic domain, a zinc-dependent endopeptidase. Understanding the determinants affecting the efficiency of catalysis and strength and specificity of interactions lies at the heart of all lysostaphin family enzyme applications. To this end, we have used NMR, SAXS and molecular dynamics simulations to characterize lysostaphin structure and dynamics, to address the inter-domain interaction, the enzyme-substrate interaction as well as the catalytic properties of pentaglycine cleavage in solution. Our NMR structure confirms the recent crystal structure, yet, together with the molecular dynamics simulations, emphasizes the dynamic nature of the loops embracing the catalytic site. We found no evidence for inter-domain interaction, but, interestingly, the SAXS data delineate two preferred conformation subpopulations. Catalytic H329 and H360 were observed to bind a second zinc ion, which reduces lysostaphin pentaglycine cleaving activity. Binding of pentaglycine or its lysine derivatives to the targeting domain was found to be of very low affinity. The pentaglycine interaction site was located to the N-terminal groove of the domain. Notably, the targeting domain binds the peptidoglycan stem peptide Ala-d-γ-Glu-Lys-d-Ala-d-Ala with a much higher, micromolar affinity. Binding site mapping reveals two interaction sites of different affinities on the surface of the domain for this peptide.
Multi-level SDN with vehicles as fog computing infrastructures: A new integrated architecture for 5G-VANETs

The spectacular emergence of connected and autonomous vehicles coupled with their evergrowing demands on processing, computation and communication resources pose new challenges to provide reliable vehicular services. Here, a combination of a multi-level SdN Approach and a foG computing architEcture based on Vehicles as Infrastructures paradigm, called VISAGE, is proposed for future 5G-VANET systems. By using vehicles as fog infrastructures and integrating them with local SDN controllers, the QoS of vehicular applications and protocols becomes more efficient in terms of computation time and communication delays. This is explained by offloading the computing services from the cloud to the edge of networks, making use of the abundant resources offered by vehicles and making network control decisions locally. Through three typical uses cases of our proposed 5G era vehicular architecture, we show the promising benefits of our approach in terms of communication and computation capacities.
The Potential Correlation Between Bacterial Sporulation and the Characteristic Flavor of Chinese Maotai Liquor

The relationship between the formation of characteristic Maotai-flavor substances (MTFS) and the dominant bacteria in Maotai Daqu (MTDQ) has long been a topic of research interest in the field of liquor brewing in China. To investigate the connection between MTFS and the Bacillus subtilis (one of dominant bacteria in MTDQ) cultured on solid plates of wheat extract medium at, temperatures of 37, 46, and up to 55°C (Group A), and at a constant 37°C (Group B), the transcriptomes of the bacteria grown in the two groups were studied. About 10 out of 84 differentially expressed genes (DEGs) were related to promoting sporulation. Furthermore, observations made with transmission electron microscopy (TEM) showed that a thicker spore cortex appeared in Group A. The content of 2, 6-pyridinedicarboxylic acid (DPA), an important component of the spore, was 49.77 (±2.50) and 38.23 (±3.96) μg/mg of dried spores from the bacteria cultured in Groups A and B, respectively. Combined with the production process of Maotai liquor, more DPA accumulates in the high-temperature fermentation stage and is then released by spore germination during the subsequent temperature-drop stage. We suggest that DPA (or its derivatives) can then be transformed into MTFS by the Maillard reaction after many rounds of microbial fermentation. The viewpoint that there is a potential correlation between bacterial sporulation and the production of MTFS is proposed.
Adversarial Perturbations Against Real-Time Video Classification Systems

Recent research has demonstrated the brittleness of machine learning systems to adversarial perturbations. However, the studies have been mostly limited to perturbations on images and more generally, classification that does not deal with temporally varying inputs. In this paper we ask "Are adversarial perturbations possible in real-time video classification systems and if so, what properties must they satisfy? " Such systems find application in surveillance applications, smart vehicles, and smart elderly care and thus, misclassification could be particularly harmful (e.g., a mishap at an elderly care facility may be missed). We show that accounting for temporal structure is key to generating adversarial examples in such systems. We exploit recent advances in generative adversarial network (GAN) architectures to account for temporal correlations and generate adversarial samples that can cause misclassification rates of over 80% for targeted activities. More importantly, the samples also leave other activities largely unaffected making them extremely stealthy. Finally, we also surprisingly find that in many scenarios, the same perturbation can be applied to every frame in a video clip that makes the adversary's ability to achieve misclassification relatively easy.
Conservation genetics of Lacerta viridis populations in the Czech Republic (Reptilia: Lacertidae)

In order to obtain genetic data for the conservation of populations of Czech Lacerta viridis (Laurenti, 1768) the genetic diversity of 12 microsatellite markers was assessed for five Bohemian and three Moravian populations. Comparison of the genetic variation and differentiation between the highly fragmented and isolated Bohemian populations and the Moravian populations connected to the continuous species range revealed a lower level of genetic variation in Bohemian populations. Presence of a genetic split between the Bohemian and Moravian populations indicates that these populations have been isloted from one another for long time and currently there is no gene flow between them. The genetic structures of the populations in both regions are significantly correlated with respective geographic distances and influenced by the low level of habitat connectivity between the populations. Basic implications for the conservation of L. viridis in the Czech Republic are suggested.
Design and testing methodologies for true random number generators towards industry certification

The objective of this paper is to provide insight on the design, evaluation and testing of modern True Random Number Generators (TRNGs) aimed towards certification. We discuss aspects related to each of these stages by means of two illustrative TRNG designs: PLL-TRNG and DC-TRNG. Topics covered in the paper include: the importance of formal security evaluations based on a stochastic model of the entropy source, the development of suitable and lightweight embedded tests to detect failures, the implementation and testing of TRNGs in dedicated FPGA platforms, and a robustness assessment to environmental and/or physical modifications.
Impact of Cell Density and Collagen Concentration on the Electromagnetic Properties of Dermal Equivalents in the Terahertz Band

In this paper, the measurement of collagen gels and dermal equivalents (DEs) with three kinds of fibroblast cell densities and collagen concentrations is performed, respectively, using terahertz time-domain spectroscopy (THz-TDS) in transmission mode. With the objective to reduce the thickness uncertainty, an algorithm to extract material parameters and sample thickness of thin samples simultaneously is employed. The statistical mean and standard deviation of the refractive indexes and absorption coefficients in a THz band from 0.2 to 1.5 THz are presented. It is shown that the refractive indexes of DEs drop by around 10%, whereas the absorption coefficients decrease by 20% when cell density increases by one order from 0.1 to 1 <inline-formula><tex-math notation="LaTeX">$ \text{M/mL}$</tex-math></inline-formula>. In addition, the complex refractive indexes of DEs with 3-mg/mL collagen are higher than those with 2 <inline-formula><tex-math notation="LaTeX">$\text{mg/mL}$</tex-math></inline-formula>, whereas the THz optical parameters of DEs with 2.5 mg/mL are the lowest. The obtained results indicate that the difference in the intrinsic biological features, initial cell density, and collagen concentration changes the tissue hydration, which in turn brings changes to the electromagnetic properties.
Mammography Dual View Mass Correspondence

Standard breast cancer screening involves the acquisition of two mammography X-ray projections for each breast. Typically, a comparison of both views supports the challenging task of tumor detection and localization. We introduce a deep learning, patch-based Siamese network for lesion matching in dual-view mammography. Our locally-fitted approach generates a joint patch pair representation and comparison with a shared configuration between the two views. We performed a comprehensive set of experiments with the network on standard datasets, among them the large Digital Database for Screening Mammography (DDSM). We analyzed the effect of transfer learning with the network between different types of datasets and compared the network-based matching to using Euclidean distance by template matching. Finally, we evaluated the contribution of the matching network in a full detection pipeline. Experimental results demonstrate the promise of improved detection accuracy using our approach.
Probabilistic Analysis of Weakly-Hard Real-Time Systems

Modeling and analysis of non-functional properties, such as timing constraints, is crucial in automotive real-time embedded systems. EAST-ADL is a domain specific architectural language dedicated to safetycritical automotive embedded system design. We have previously specified EAST-ADL timing constraints in Clock Constraint Specification Language (CCSL) and proved the correctness of specification by mapping the semantics of the constraints into Uppaal models amenable to model checking. In most cases, a bounded number of violations of timing constraints in automotive systems would not lead to system failures when the results of the violations are negligible, called Weakly-Hard (WH). Previous work is extended in this paper by including support for probabilistic analysis of timing constraints in the context of WH: Probabilistic extension of CCSL, called PrCCSL, is defined and the EAST-ADL timing constraints with stochastic properties are specified in PrCCSL. The semantics of the extended constraints in PrCCSL is translated into Uppaal-SMC models for formal verification. Furthermore, a set of mapping rules is proposed to facilitate guarantee of translation. Our approach is demonstrated on an autonomous traffic sign recognition vehicle case study.
Emergency Surgery in a Critically Ill Patient with Major Drug-Induced Bleeding and Severe Ischaemic Heart Failure

Abstract Introduction: Anticoagulant overdose frequently occurs in elderly populations especially in remote areas where medical services are scarce. When emergency surgery is required, such patients offer major anaesthetic challenges. Case presentation: We describe the case of an elderly patient admitted to a surgical ward with acute abdominal pain, on dual anti-platelet therapy and acenocoumarol for a recent acute myocardial infarction treated percutaneously with two drug-eluting stents. Laboratory tests showed severe anticoagulant overdose with uncoagulable INR. The decision was made to use of both light transmission aggregometry [LTA] for platelet function testing and thromboelastography to aid in the management of perioperative haemostasis in order to prevent both severe bleeding and stent thrombosis. Surgery revealed haemoperitoneum, volvulus of the ileum and a venous mesenteric infarction. Intraoperative blood loss was minimal and no blood products were administered. Postoperative course was uneventful without either thrombotic or haemorrhagic complications and the patient was discharged from the Postanaesthesia Care Unit on postoperative day two. Conclusion: The use of aggregometry and thrombography helped in both evaluation and management of haemostasis of a high-risk patient by goal-directed administration of pro-and anti-coagulants.
Fast multi-parametric method for mechanical properties estimation of clamped — clamped perforated membranes

In this work, an approximate function is proposed for describing the deflection of RF-MEMS bridges clamped on two opposite edges in response to quasi-point pressure loads applied by a surface profiler. The deflection law was written as a function of geometric and mechanical properties of the membrane bridge. Used as interpolating function of experimental deflection-load measurements performed in-situ, it allows to indirectly extract residual stress and Young's modulus of the investigated membrane. Multilayer thin film membranes of different sizes and porosities were fabricated by low temperature Plasma Enhanced Chemical Vapor Deposition (PECVD) process using surface micromachining approach. The work discussed in this paper was supported by experimental nanoindentation and stress measurements performed on continuous thin films and by Finite Element Analysis (FEA) using Comsol Multiphysics for modeling the perforated membrane, in agreement with the experimental data.
Explicit Fixed-Point Computation of Nonlinear Delay-Free Loop Filter Networks

An iterative method is proposed for the explicit computation of discrete-time nonlinear filter networks containing delay-free loops. The method relies on a fixed-point search of the signal values at every temporal step. The formal as well as numerical properties of fixed-point solvers delimit its applicability: On the one hand, the method allows for a reliable prediction of the frequency rates where the simulation is stable, while, on the other hand, its straightforward applicability is counterbalanced by low speed of convergence. Especially in presence of specific nonlinear characteristics, the use of a fixed-point search is limited if the real-time constraint holds. For this reason, the method becomes useful especially during the digital model prototyping stage, as exemplified while revisiting a previous discrete-time realization of the voltage-controlled filter aboard the EMS VCS3 analog synthesizer. Further tests conducted on a digital ring modulator model support the above considerations.
Verifying Security Protocols using Dynamic Strategies

Current formal approaches have been successfully used to find design flaws in many security protocols. However, it is still challenging to automatically analyze protocols due to their large or infinite state spaces. In this paper, we propose a novel framework that can automatically verifying security protocols without any human intervention. Experimental results show that SmartVerif automatically verifies security protocols that cannot be automatically verified by existing approaches. The case study also validates the effectiveness of our dynamic strategy.
Theoretical Modeling of Cognitive Dysfunction in Schizophrenia by Means of Errors and Corresponding Brain Networks

The current evidence of cognitive disturbances and brain alterations in schizophrenia does not provide the plausible explanation of the underlying mechanisms. Neuropsychological studies outlined the cognitive profile of patients with schizophrenia, that embodied the substantial disturbances in perceptual and motor processes, spatial functions, verbal and non-verbal memory, processing speed and executive functioning. Standardized scoring in the majority of the neurocognitive tests renders the index scores or the achievement indicating the severity of the cognitive impairment rather than the actual performance by means of errors. At the same time, the quantitative evaluation may lead to the situation when two patients with the same index score of the particular cognitive test, demonstrate qualitatively different performances. This may support the view why test paradigms that habitually incorporate different cognitive variables associate weakly, reflecting an ambiguity in the interpretation of noted cognitive constructs. With minor exceptions, cognitive functions are not attributed to the localized activity but eventuate from the coordinated activity in the generally dispersed brain networks. Functional neuroimaging has progressively explored the connectivity in the brain networks in the absence of the specific task and during the task processing. The spatio-temporal fluctuations of the activity of the brain areas detected in the resting state and being highly reproducible in numerous studies, resemble the activation and communication patterns during the task performance. Relatedly, the activation in the specific brain regions oftentimes is attributed to a number of cognitive processes. Given the complex organization of the cognitive functions, it becomes crucial to designate the roles of the brain networks in relation to the specific cognitive functions. One possible approach is to identify the commonalities of the deficits across the number of cognitive tests or, common errors in the various tests and identify their common “denominators” in the brain networks. The qualitative characterization of cognitive performance might be beneficial in addressing diffuse cognitive alterations presumably caused by the dysconnectivity of the distributed brain networks. Therefore, in the review, we use this approach in the description of standardized tests in the scope of potential errors in patients with schizophrenia with a subsequent reference to the brain networks.
Saving Face in Front of the Computer? Culture and Attributions of Human Likeness Influence Users' Experience of Automatic Facial Emotion Recognition

In human-to-human contexts, display rules provide an empirically sound construct to explain intercultural differences in emotional expressivity. A very prominent finding in this regard is that cultures rooted in collectivism—such as China, South Korea, or Japan—uphold norms of emotional suppression, contrasting with ideals of unfiltered self-expression found in several Western societies. However, other studies have shown that collectivistic cultures do not actually disregard the whole spectrum of emotional expression, but simply prefer displays of socially engaging emotions (e.g., trust, shame) over the more disengaging expressions favored by the West (e.g., pride, anger). Inspired by the constant advancement of affective technology, this study investigates if such cultural factors also influence how people experience being read by emotion-sensitive computers. In a laboratory experiment, we introduce 47 Chinese and 42 German participants to emotion recognition software, claiming that it would analyze their facial micro-expressions during a brief cognitive task. As we actually present standardized results (reporting either socially engaging or disengaging emotions), we manipulate participants’ impression of having matched or violated culturally established display rules in a between-subject design. First, we observe a main effect of culture on the cardiovascular response to the digital recognition procedure: Whereas Chinese participants quickly return to their initial heart rate, German participants remain longer in an agitated state. A potential explanation for this—East Asians might be less stressed by sophisticated technology than people with a Western socialization—concurs with recent literature, highlighting different human uniqueness concepts across cultural borders. Indeed, while we find no cultural difference in subjective evaluations of the emotion-sensitive computer, a mediation analysis reveals a significant indirect effect from culture over perceived human likeness of the technology to its attractiveness. At the same time, violations of cultural display rules remain mostly irrelevant for participants’ reaction; thus, we argue that inter-human norms for appropriate facial expressions might be loosened if faces are read by computers, at least in settings that are not associated with any social consequence.