Miracle-dz/UniFAR-FTUs huggingface dataset:
Cross-correlation analysis of aeroacoustic sound and flow field using time-resolved PIV

We constructed a system for the simultaneous measurement of flow field by time-resolved PIV and sound pressure by a microphone in a small-scale wind tunnel; further, we investigated the cross- correlation between the two. In the case of the PIV measurement, a dual-plane PIV system is realized using a polarizing technique to measure flow fields of two cross-sections simultaneously and evaluate the coherence and phase structure of sound sources in the axial direction of a cylinder. The analysis of single cross-section PIV measurement showed a strong cross-correlation between the PIV-predicted sound pressure and the actual sound pressure at Strouhal number St = 0.2, which corresponds with the frequency of the Aeolian tone of a cylinder. In addition, downstream a cylindrical specimen, a well-ordered structure of sound sources was observed; this structure was related with the distribution of the Karman vortex, whereas the sound source around the separation points was independent of St. We also reported that both power spectra and coherence distribution are necessary in estimating the aeroacoustic sound at the far field through a PIV measurement. We also experimentally demonstrated the cancellation of sound waves except at St = 0.2 and the doubling of the sound pressure at St = 0.2 as a dipole sound around the two separation points. Through the newly developed dual-plane PIV measurement, the linearity of the coherence and phase between two cross-sections with respect to the separation distance is clarified. Finally, the integration in a longitudinal direction is carried out by applying the obtained phase difference and the difference in the predicted aeroacoustic sound at the far field is shown by considering the phase.
Transtorno do espectro autista: o impacto na dinâmica familiar e as habilidades no cuidado

Objetivo: Entender o Transtorno do Espectro Autista (TEA) no que tange as suas características comportamentais, o impacto disso na dinâmica familiar, além de identificar algumas habilidades no cuidado. Revisão bibliográfica: As manifestações comportamentais do TEA se apresentam precocemente. Dentre eles, tem-se irregularidade e atraso no controle e desenvolvimento motor; dificuldade para reconhecer emoções, apresentando um afeto negativo; sensibilidade diminuída a recompensas sociais; e dificuldade para manter sua atenção. Em razão disso, toda a rotina e dinamicidade do núcleo familiar acaba sofrendo alterações e, com isso, altos níveis de estresse e ansiedade podem estar presentes entre os cuidadores, sobretudo, nas mães. Assim, incentivar o desenvolvimento de habilidades intervencionistas pelos cuidadores através de atividades que incentivem a comunicação e socialização, por exemplo, é fundamental, a fim de possibilitar um melhor acolhimento ao indivíduo. Considerações finais: O TEA ainda hoje é muito estigmatizado pela sociedade. Isso, infelizmente, se perpetua, dentre outras razões, por carência de pesquisas com embasamento teórico-científico que possa compreender melhor as suas características, além das próprias ideologias civis, resultando, dentre outros fatores, em comportamentos superprotetores.
Instability Boundaries of a Vocal Fold Modelled as a Flexibly Supported Rigid Body Vibrating in a Channel Conveying Fluid

A generalised leakage-flow induced vibration model for vibration onset of the vocal folds in the airflow is presented. Especially the influence of various physical properties of the vocal folds (e.g., their shape, adduction, mass and mass distribution) on the thresholds of instability is studied. A vibrating element with two-degrees-of-freedom (rotation and translation) placed on an elastic foundation and vibrating in the wall of a channel conveying air is used to approximate the vocal fold. The inviscid incompressible 1-D fluid flow theory is used. A generally defined shape of the vocal fold is considered for expressing the unsteady aerodynamic forces in the glottis. The parameters of the mechanical part of the model, i.e., the mass, stiffness and damping matrices are related to the known geometry, size and material density of the vocal folds as well as to the fundamental natural frequencies and damping known from the experiments. The numerical solution yields the natural frequencies, damping, mode shapes of vibration and the instability thresholds of the system. The calculated vibration and stability characteristics appear to be close to the known physiological data. The developed aeroelastic model is able to provide qualitative information, e.g., on conditions for a soft voice onset or for breathy voicing and could be helpful also in design of artificial voice prosthesis.Copyright © 2002 by ASME
Fireflies in South East Asia: Species Diversity, Distribution, and Habitat (2015-2021)

Fireflies are one of the most famous luminous insects that emit bioluminescence. The most famous fireflies in Southeast Asia are Pteroptyx, of the order Coleoptera and the Lampyridae family. This review paper combined the data on the species diversity and firefly distribution in Southeast Asian countries such as Malaysia, the Philippines, Indonesia, Cambodia, Myanmar, Singapore, Sri Lanka, Papua New Guinea, Laos, Thailand, and Vietnam published in 2015-2021. Some countries have limited data and no studies to identify firefly species and their habitat from 2015 to 2021; the data before 2015 was used. Furthermore, the lack of studies by Southeast Asian researchers regarding the richness of firefly species has been reviewed. Malaysian and Thailand researchers are among the forerunners in the study related to fireflies in the Southeast Asian region compared to other Southeast Asian countries. Lastly, not much is known about the display trees or habitat of fireflies in many areas such as the Philippines, Indonesia, Cambodia, Myanmar, Singapore, Sri Lanka, Papua New Guinea, Laos, Thailand, and Vietnam. More studies are warranted to be conducted in the future on firefly species and their habitat.
DEFORMATIONS DURING CUT-AND-COVER CONSTRUCTION OF MUNI METRO TURNBACK PROJECT

Construction of the MUNI Metro Turnback project involved deep excavations in soft soils along the Embarcadero waterfront in downtown San Francisco, California. The excavations and shoring system were designed by the Engineer of Record to control ground deformations within specified limits in order to minimize the impacts of the deformations on a block of adjacent, settlement-sensitive buildings. The design included estimates of deformations caused by the excavations and other construction activities, evaluation of potential settlements of adjacent buildings, and structural evaluation of the response of the buildings to the estimated settlements. A comprehensive monitoring program combined with an instrumented test section, appropriate contingency measures, and construction controls were planned so as to allow early warning for appropriate response in the event that the deformations exceeded tolerable limits. This paper reviews the subsurface conditions, base stability analyses, and estimated deformations, describes the instrumentation program, and presents a comprehensive summary of the instrumentation measurements. It interprets the instrumentation measurements and draws conclusions regarding the general nature and magnitude of deformations and their impacts on adjacent structures.
Proposal for a Skin Layer-Wise Decomposition Model of Spatially-Resolved Diffuse Reflectance Spectra Based on Maximum Depth Photon Distributions: A Numerical Study

In the context of cutaneous carcinoma diagnosis based on in vivo optical biopsy, Diffuse Reflectance (DR) spectra, acquired using a Spatially Resolved (SR) sensor configuration, can be analyzed to distinguish healthy from pathological tissues. The present contribution aims at studying the depth distribution of SR-DR-detected photons in skin from the perspective of analyzing how these photons contribute to acquired spectra carrying local physiological and morphological information. Simulations based on modified Cuda Monte Carlo Modeling of Light transport were performed on a five-layer human skin optical model with epidermal thickness, phototype and dermal blood content as variable parameters using (i) wavelength-resolved scattering and absorption properties and (ii) the geometrical configuration of a multi-optical fiber probe implemented on an SR-DR spectroscopic device currently used in clinics. Through histograms of the maximum probed depth and their exploitation, we provide numerical evidence linking the characteristic penetration depth of the detected photons to their wavelengths and four source–sensor distances, which made it possible to propose a decomposition of the DR signals related to skin layer contributions.
Strategic investment analysis using activity based costing concepts and analytical hierarchy process techniques

An increasing number of organizations are using Activity Based Costing (ABC) to gain insight into manufacturing activities and processes as well as product costing. The natural logic of ABC can also be applied to strategic decisions. This paper presents a methodology that ties investment decisions to ABC concepts using the Analytical Hierarchy Process (AHP). By using AHP, both monetary and non-monetary benefits can be included in the analysis. First, the relationships between goals, activities, cost, and performance measures are developed, then they are combined to make two models: a cost impact model and a performance impact model. The final selection is made using a cost vs performance graph. The goal of the decision process is to evaluate investment alternatives based on their impact on activities and their contribution to organizational goals.
Fault Diagnosis of DCV and Heating Systems Based on Causal Relation in Fuzzy Bayesian Belief Networks Using Relation Direction Probabilities

The state-of-the-art provides data-driven and knowledge-driven diagnostic methods. Each category has its strengths and shortcomings. The knowledge-driven methods rely mainly on expert knowledge and resemble the diagnostic thinking of domain experts with a high capacity in the reasoning of uncertainties, diagnostics of different fault severities, and understandability. However, these methods involve higher and more time-consuming effort; they require a deep understanding of the causal relationships between faults and symptoms; and there is still a lack of automatic approaches to improving the efficiency. The data-driven methods rely on similarities and patterns, and they are very sensitive to changes of patterns and have more accuracy than the knowledge-driven methods, but they require massive data for training, cannot inform about the reason behind the result, and represent black boxes with low understandability. The research problem is thus the combination of knowledge-driven and data-driven diagnosis in DCV and heating systems, to benefit from both categories. The diagnostic method presented in this paper involves less effort for experts without requiring deep understanding of the causal relationships between faults and symptoms compared to existing knowledge-driven methods, while offering high understandability and high accuracy. The fault diagnosis uses a data-driven classifier in combination with knowledge-driven inference with both fuzzy logic and a Bayesian Belief Network (BBN). In offline mode, for each fault class, a Relation-Direction Probability (RDP) table is computed and stored in a fault library. In online mode, we determine the similarities between the actual RDP and the offline precomputed RDPs. The combination of BBN and fuzzy logic in our introduced method analyzes the dependencies of the signals using Mutual Information (MI) theory. The results show the performance of the combined classifier is comparable to the data-driven method while maintaining the strengths of the knowledge-driven methods.
Prefrontal Lobe and Posterior Cingulate Cortex Activations in Patients with Major Depressive Disorder by Using Standardized Weighted Low-Resolution Electromagnetic Tomography

Background: The differences in brain activity between patients with major depressive disorder (MDD) and healthy adults have been confirmed by functional magnetic resonance imaging (fMRI), positron emission tomography (PET), and electroencephalography (EEG). The prefrontal lobe and posterior cingulate cortex (PCC) are related to emotional regulation in patients with MDD. However, the high cost and poor time resolution of fMRI and PET limit their clinical application. Recently, researchers have used high time resolution of standardized weighted low-resolution electromagnetic tomography (swLORETA) to investigate deep brain activity. This study aimed to convert raw EEG signals into swLORETA images and explore deep brain activity in patients with MDD and healthy adults. Methods: BrainMaster EEG equipment with a 19-channel EEG cap was used to collect resting EEG data with eyes closed for 5 min. NeuroGuide software was used to remove the EEG artifacts, and the swLORETA software was used to analyze 12,700 voxels of current source density (CSD) for 139 patients with MDD and co-morbid anxiety symptoms (mean age = 43.08, SD = 13.76; 28.78% were male) and 134 healthy adults (mean age = 40.60, SD = 13.52; 34.33% were male). Deep brain activity in the frontal lobe and PCC at different frequency bands was analyzed, including delta (1–4 Hz), theta (5–7 Hz), alpha (8–11 Hz), beta (12–24 Hz), beta1 (12–14 Hz), beta2 (15–17 Hz), beta3 (18–24 Hz), and high beta (25–29 Hz). Results: There was lower delta and theta and higher beta, beta1, beta2, beta3, and high-beta activity at the prefrontal lobe (dorsal medial prefrontal cortex [dmPFC], ventral medial prefrontal cortex [vmPFC], and dorsal lateral prefrontal cortex [dlPFC], ventral lateral prefrontal cortex [vlPFC], orbital frontal cortex [OFC]) and PCC in MDD patients compared with healthy adults. There was no significant difference in alpha activity between the two groups. Conclusion: This study indicates brain hyperactivity in the right prefrontal lobe (dlPFC and vmPFC) and PCC in patients with MDD with co-morbid anxiety symptoms, and the dlPFC and PCC were also related to emotion regulation in MDD. Inhibiting high-beta activity or restoring delta and theta activity to the normal range in the right frontal lobe and PCC may be possible in z-score neurofeedback protocols for patients with MDD in future studies.
MJO Initiation Triggered by Amplification of Upper‐Tropospheric Dry Mixed Rossby‐Gravity Waves

A possibly important dynamical process for the Madden–Julian oscillation (MJO) convective initiation is proposed. An MJO event during the “CINDY2011” field campaign is triggered by eastward‐moving lower‐tropospheric mixed Rossby‐gravity (MRG) wave packets, and its leading precursor is predominance of upper‐tropospheric MRGs in the Indian Ocean (IO). Simple three‐dimensional model experiments reveal that the upper‐tropospheric MRGs in the IO are amplified particularly in the western IO (WIO) by their westward advection and wave accumulation due to the upper‐level convergence in mean easterlies of the Walker circulation. The model also predicts downward dispersion of the amplified upper‐tropospheric MRGs and resultant lower‐tropospheric MRG wave packet formation. This MRG evolution consistently explains the MJO initiation process during CINDY2011, which is further verified by ray tracing for MRGs. Upper‐tropospheric circumnavigating Kelvin waves assist the proposed mechanism by promoting MRG‐wave accumulation (advection) in their westerly (easterly) phases via enhanced zonal convergence and weakened easterlies (enhanced easterlies).
“From Tool to Agent”: The Evolution of (Cockpit) Automation and Its Impact on Human-Machine Coordination

In a variety of domains, researchers have observed breakdowns in human-automation coordination and cooperation. One form of breakdown is a lack of mode awareness which can result in ‘automation surprises’. These are, in part, related to a lack of adequate feedback on system status and behavior. The need for effective and timely feedback has become even more pressing with the evolution of systems that operate at increasingly high levels of authority and autonomy. In the absence of improved feedback design, however, the gap between required and available information has widened. To explore the impact of this trend towards ‘strong yet silent’ machine agents, a line of research was conducted on pilot-automation coordination on the Airbus A-320, an aircraft that exemplifies these trends. This research involved a survey of pilots' line experiences with the A-320 automation, observations of transition training to the airplane, and an experimental simulation study on pilots' mode awareness and pilot-automation coordination. The results of this work indicate a trend from mode errors of commission (which represented a more frequent problem on early generation ‘glass cockpit’ aircraft) to errors of omission. In other words, pilots were more likely to fail to observe and interfere with uncommanded and undesired automation and aircraft behavior. Such errors of omission also seem to have played a role in recent incidents and accidents. They illustrate the need for improved communicative abilities in autonomous and powerful systems to enable them to actively support the coordination between human and machine.
Understanding the post‐monsoon tropical cyclone variability and trend over the Bay of Bengal during the satellite era

An effort is made to investigate the tropical cyclone (TC) variability over the Bay of Bengal in the warming climate scenario during the satellite era (1979–2018). In this study, the authors investigate interannual variations in the overall capacity of the Bay of Bengal (BoB) basin in the post‐monsoon season to produce either intense or moderate TCs. Globally accepted and widely used metrics accumulated cyclone energy (ACE) and power dissipation index (PDI) are used to examine the energy and damage generated by TCs. A statistical change‐point analysis is conducted to detect the shift in the tropical cyclone frequency and ACE during the study period, indicating the year 1999 as a change point. The results show the increasing trend in ACE in the BoB during the post‐monsoon season with a statistical significance of 95%. On the contrary, the overall frequency is almost unchanged but has shown an increasing trend in the last decade of the study period. Additionally, atmospheric and ocean factors influencing the TC intensity are investigated by applying principal component analysis for three categories of TCs, viz. the very severe cyclonic storm, severe cyclonic storm, and cyclonic storm. Implementation of principal component analysis and correlations of maximum sustained wind speed (MSW2; intensity) with relative vorticity, minimum sea‐level pressure (MSLP), sea‐surface temperature (SST), specific rainwater content, and vertical wind shear revealed relative vorticity as the most dominating parameter amongst all governing factors which determine the final intensity of the BoB TCs. On the contrary, SST shows the different nature of the relationship with different TC categories.
NC-Net: Efficient Neuromorphic Computing Using Aggregated Subnets on a Crossbar-Based Architecture With Nonvolatile Memory

Neuromorphic computing chips consisting of crossbar arrays of emergent nonvolatile memory (NVM) have the potential of achieving both high energy efficiency and throughput as the low-power implementation of convolutional neural network (CNN) inference engines. However, such hardware has design constraints, such as its limited fan-in/fan-out and resource-inefficient mapping, that make the design and deployment of CNN on them challenging. As a result, the user has to design the CNN model with intricate knowledge of the hardware architecture and even cannot fit the models in the hardware for CNN with high resolution image input. In this article, we propose the use of aggregated subnets, NC-net, which is a constrained form of the traditional layer structure, to solve these issues. With our method, we put forward an energy-efficient buffer- and analogue-to-digital converter and digital-to-analogue converter (ADC/DAC)-free architecture and a scalable end-to-end solution that automatically satisfies the hardware constraints of crossbar architectures, while optimizing the resource usage. In our solution, the exploration and deployment of a CNN for a neuromorphic crossbar hardware start with a design front end based on TensorFlow. Our automated design flow maps the NC-net network from TensorFlow to the crossbar architecture. We tested our designs on both a simulator and a field-programmable gate array (FPGA) emulator with various benchmarks. In addition to general benchmarks, including MNIST, SVHN, CIFAR-10, and CIFAR-100, we tested our system on a real-world application, human detection with high resolution (224 $\times $ 224) images as the input. Our system achieves the state-of-the-art accuracy for these benchmarks on the crossbar-based neuromorphic hardware, with an accuracy of more than 90% for the latter. It also yielded up to $4.25\times $ improvement in the efficiency of spiking core usage compared to TrueNorth.
Teaching Geoheritage Values: Implementation and Thematic Analysis Evaluation of a Synchronous Online Educational Approach

The purpose of this article is to present the results of an environmental education program on “Storm-Tossed Sea Rocks in Pelion Seaside” designed for junior high school students and implemented as a synchronous online educational approach and main and with a main goal to empower students to the values of geoheritage. In order to examine the effectiveness of the program and in particular the achievement of the objectives that encourage the development of values, the research question was identified as to whether the implementation of the environmental program achieved the empowerment of students in geoheritage values. In order to answer this question, we implemented a rather unusual technique to evaluate the educational procedure, which was based on the qualitative research technique of thematic analysis. This technique was selected as the most appropriate in order to “mine” conceptual patterns, the analysis of which would, in a valid, reliable, and simultaneously easy to use and quick way, inform the teachers that the values of geoheritage were disseminated to the students through the program. Thus, four-question interviews were conducted with randomly selected students who participated in the program. The data were examined and conceptual patterns were identified which were classified in eighteen codes. The codes were divided into five categories, the analysis of which led to the answer to the research question. Thus, it was found that the implementation of the environmental program achieved the empowerment of students in geocultural heritage values. The development of feelings of environmental sensitivity has also been seen, which suggests further investigation is needed. It was concluded that for the students, the given educational approach was necessary as well as cognitively, pedagogically, and emotionally beneficial; therefore, the need to enrich the curricula of environmental education/education for sustainable development with issues of geodiversity and geocultural heritage is justified. Finally, what was ascertained is that the thematic-analysis-based evaluation technique of the educational procedure, which was implemented, provided the teachers with the requested information, and it is recommended as an evaluation technique of educational procedures which aim at empowering students on values—even for daily use in school.