Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing the Temperamental Basis of the Sense of Humor: Adaptation of the English Language Version of the State-Trait Cheerfulness Inventory Long and Standard Form

The State-Trait Model of Cheerfulness assesses the temperamental basis of the sense of humor with the traits and respective states of cheerfulness, seriousness, and bad mood. Cheerfulness is a dominant factor in current measures of the sense of humor and explains both, the disposition to engaging in smiling and laughter, as well as humor behaviors, and trait seriousness and bad mood are antagonistic to the elicitation of amusement (albeit for different reasons). Several studies have shown the validity and reliability of the STCI questionnaire in German and other language versions (i.e., Spanish). In this study, the English language version with 106 items (STCI-T <106>) was translated, checked for its item and scale characteristics, and tested with a confirmatory factor analysis approach (N = 1101) to investigate the factorial validity of the STCI-T <106> scale. Results show good psychometric characteristics, good internal consistencies, and a fit to the postulated underlying structure of the STCI-T. Then, the standard form with 60 items (STCI-T <60>) was developed and the psychometric characteristics initially tested. In an independent sample (N = 169), the characteristics of the standard form were compared to the parent form and German equivalent. It showed good psychometric characteristics, internal consistencies, as well as a good self- and peer-report congruence. To conclude, the STCI-T <106> is the measure of choice for the assessment of the temperamental basis of the sense of humor and the separate facets of the traits, while the standard form (60 items) allows of an economic assessment of cheerfulness, seriousness, and bad mood, free of context-saturated items and humor preferences.
Slum Segmentation and Change Detection : A Deep Learning Approach

More than one billion people live in slums around the world. In some developing countries, slum residents make up for more than half of the population and lack reliable sanitation services, clean water, electricity, other basic services. Thus, slum rehabilitation and improvement is an important global challenge, and a significant amount of effort and resources have been put into this endeavor. These initiatives rely heavily on slum mapping and monitoring, and it is essential to have robust and efficient methods for mapping and monitoring existing slum settlements. In this work, we introduce an approach to segment and map individual slums from satellite imagery, leveraging regional convolutional neural networks for instance segmentation using transfer learning. In addition, we also introduce a method to perform change detection and monitor slum change over time. We show that our approach effectively learns slum shape and appearance, and demonstrates strong quantitative results, resulting in a maximum AP of 80.0.
Mindfulness-Based Cognitive Therapy for Trichotillomania: A Bayesian Case-Control Study

Over the last years, mindfulness-based interventions combined with habit reversal training have been demonstrated to be particularly suitable for addressing trichotillomania. However, because these studies always combined mindfulness training to habit reversal without including either a mindfulness or habit reversal condition alone, it is still unclear whether clinical benefits are the consequences of mindfulness or merely result from habit reversal training. The primary purpose of the present study was thus to examine whether a mindfulness training procedure without habit reversal could alleviate trichotillomania. Using a Bayesian probabilistic approach for single-case design, client’s hair loss severity and level of mindfulness were compared to a normative sample (n = 15) before treatment, after treatment, and at six-month follow-up. Improvement in mindfulness first occurred, and that beneficial effect then transferred to hair-pulling. Indeed, as compared to the normative sample, the client exhibited, from baseline to post-treatment, an improvement in mindfulness. Although a marginal trend to improvement was already evidenced at post-treatment, the mindfulness program only had a significant beneficial effect transferred to hair-loss severity at six-month follow-up. Although it remains particularly difficult to infer generalization from one client, the data from the present case study are the first to suggest that mindfulness training per se might be a suitable clinical intervention for trichotillomania.
Primitive based control of the Utah/MIT dextrous hand

An abstraction of dextrous manipulation and a control scheme for the Utah/MIT dextrous hand is described. The abstraction of robotic manipulation is based on motion primitives. Each primitive represents a small, coordinated set of joint motions that performs a distinct functional task. Primitives are defined as sequences of joint position changes that, when executed, cause functionally significant motion of the fingers. By defining the primitives as changes in position, rather than as absolute position trajectories, the ability to execute a primitive from any pose of the hand is gained. Hand programming language (HPL), a language and execution environment supporting the primitive abstraction, has been developed. Programming in HPL allows the user to describe dextrous manipulation tasks at a high level, insulated from the complex multiprocessing hierarchy controlling the hand. <<ETX>>
A priori knowledge in the inversion of linear kernel-driven BRDF models

A priori knowledge can come from field measurements of bidirectional reflectance factors for various surface cover types. How to express and use this kind of knowledge is very important currently. 73 sets of field observations are used to explore the possible expression of a priori knowledge in linear kernel-driven BRDF models in this paper.
Analogue feed‐forward carrier recovery for millimetre‐wave broadband wireless links

An analogue modulation-type independent feed-forward carrier recovery approach for broadband wireless communication systems is introduced in this work. The focus is on the deliberately increased local oscillator (LO) signal feed-through to the radio frequency (RF) port of the up-converter in a direct conversion transmitter (TX). The strong LO feed-through is used at the receiver (RX) side to demodulate the RF signal. The heart of the carrier recovery block is a narrowband bandpass filter (BPF) and a frequency divider-by-n operated in injection-locking mode to the strong LO feed-through. The proposed method is investigated through circuit level simulations; while its feasibility is examined via the successful demodulation of complex data with various modulation types up to 8 Gbps for an E-band front-end. This method can be used for transceivers working at high carrier frequencies as far as the realisation of frequency divider circuits and narrowband BPFs is technically feasible.
Double density wavelet transformation for speckle reduction of SAR images

Discrete wavelet transformations (DWTs) based on oversampled filter banks, proposed by I. W. Selesnick (2001), are used for speckle reduction of SAR images. The oversampled DWT is called double density DWT (DD-DWT) and is based on a single scaling function (lowpass) and two distinct wavelet functions (highpass). The DD-DWT is useful for speckle reduction through its subband images and the speckle reduction is obtained by thresholding the subband-image coefficients of the digitized SAR images. A thresholding method using non-linear functions which are adapted for each selected subband is used in the paper. The non-linear functions are based on sigmoid functions. The denoising method shows great promise for speckle removal and hence can provide good detection performance for SAR based recognition.
Wireless binaural hearing aid technology for telephone use and listening in wind noise

Abstract Objective: To assess the speech perception benefits of binaural streaming technology for bilateral hearing aid users in two difficult listening conditions. Design: Two studies were conducted to compare hearing aid processing features relating to telephone use and wind noise. Speech perception testing was conducted in four different experimental conditions in each study. Study sample: Ten bilaterally-aided children in each study. Results: Significant improvements in speech perception were obtained with a wireless feature for telephone use. Significant speech perception benefits were also obtained with wireless hearing aid features when listening to speech in simulated wind noise. Conclusions: Binaural signal processing algorithms can significantly improve speech perception for bilateral hearing aid users in challenging listening situations.
Two-Step Read Scheme in One-Selector and One-RRAM Crossbar-Based Neural Network for Improved Inference Robustness

Introducing a threshold switching selector in a resistive random access memory (RRAM) is essential for implementing a crossbar array that accurately accelerates neuromorphic computations. But, at an expense, a read voltage (<inline-formula> <tex-math notation="LaTeX">${V}_{\text {read}}$ </tex-math></inline-formula>) to be used for inference tasks is inevitably boosted. Therefore, this brief shows the effect of the enlarged <inline-formula> <tex-math notation="LaTeX">${V}_{\text {read}}$ </tex-math></inline-formula> on the stability of conductance states of the RRAM relevant to the inference robustness. The multiple conductance states of the analog RRAM achieved by a SPICE simulation are stable under consecutive 106 cycles of nominal <inline-formula> <tex-math notation="LaTeX">${V}_{\text {read}}$ </tex-math></inline-formula>. However, each state of the one selector and one RRAM begins to be disturbed at ~10<sup>4</sup> cycles due to the boosted <inline-formula> <tex-math notation="LaTeX">${V}_{\text {read}}$ </tex-math></inline-formula>. More importantly, when a certain state exceeds to the next state due to the accumulated <inline-formula> <tex-math notation="LaTeX">${V}_{\text {read}}$ </tex-math></inline-formula> stress, a classification accuracy of the neural network is significantly degraded. We, thus, introduce a two-step read scheme that separates the roles of turning on the selector and reading the states. As the selector is turned on rapidly with an additional large pulse, the following <inline-formula> <tex-math notation="LaTeX">${V}_{\text {read}}$ </tex-math></inline-formula> can be lowered. As a result, the read disturbance is minimized, and the optimized two-step pulse scheme allows 10<sup>6</sup> MNIST images to be recognized with >95% accuracy in the neural network.
3D Deep Learning with voxelized atomic configurations for modeling atomistic potentials in complex solid-solution alloys

The need for advanced materials has led to the development of complex, multi-component alloys or solid-solution alloys. These materials have shown exceptional properties like strength, toughness, ductility, electrical and electronic properties. Current development of such material systems are hindered by expensive experiments and computationally demanding first-principles simulations. Atomistic simulations can provide reasonable insights on properties in such material systems. However, the issue of designing robust potentials still exists. In this paper, we explore a deep convolutional neural-network based approach to develop the atomistic potential for such complex alloys to investigate materials for insights into controlling properties. In the present work, we propose a voxel representation of the atomic configuration of a cell and design a 3D convolutional neural network to learn the interaction of the atoms. Our results highlight the performance of the 3D convolutional neural network and its efficacy in machine-learning the atomistic potential. We also explore the role of voxel resolution and provide insights into the two bounding box methodologies implemented for voxelization.
A Proposed Strategy to Facilitate Clinical Decision Making in Physical Therapist Students

Background and Purpose. An educational strategy is presented that combines a decisionmaking algorithm with the results from a single‐subject research project to provide physical therapist students with an opportunity to practice clinical decision making in the classroom setting. Clinical reasoning activities that emphasize hypothesis generation and reflection on patient problems may help students develop their evaluation and diagnostic skills. Method/Model Description. The Hypothesis‐Oriented Algorithm for Clinicians (HOAC) provides an organized framework to guide students through the clinical decision‐making process, and the utilization of a single‐subject research design within this algorithm provides a relevant and systematic approach to assessing change resulting from an intervention. Utilizing part 1 of the HOAC model, students generated hypotheses from examination findings of an actual patient case to develop options for treatment. In this case illustration, the hypothesis that ankle joint hypomobility is the primary impairment limiting the subject's ability to stand up was explored using a single‐subject ABA research design to examine the effectiveness of ankle joint mobilizations. Following the presentation of the results from this actual singlesubject case study, students used part 2 of the HOAC model as a guide to determine whether the intervention was effective and explored the different options for continuing treatment in the case. Outcomes. This activity has been used for 2 consecutive years with students in an entry‐level (professional) Master of Physical Therapy program. Students indicated that this activity was beneficial, with generally high levels of agreement with statements using a Likert scale. Discussion and Conclusion. This teaching strategy gives students the opportunity to reflect on actual intervention outcomes, integrate research evidence into the clinical decision‐making process, and practice clinical decision making with a variety of patient problems in the classroom environment.
Genetic and structural characterization of 20 autosomal short tandem repeats in the Chinese Qinghai Han population and its genetic relationships and interpopulation differentiations with other reference populations

Abstract China is a multinational country composed of 56 ethnic groups of which the Han Chinese accounts for 91.60%. Qinghai Province is located in the northeastern part of the Qinghai–Tibet Plateau, has an area of 72.12 km2, and is the fourth largest province in China. In the present study, we investigated the genetic polymorphisms of 20 short tandem repeat (STR) loci in a Qinghai Han population, as well as its genetic relationships with other populations. A total of 273 alleles were identified in 2 000 individuals at 20 loci, and the allelic frequency ranged from 0.000 2 to 0.532 7. The 20 STR loci showed a relatively high polymorphic rate in the studied group. Observed and expected heterozygosities ranged 0.613 0–0.907 5 and 0.614 8–0.920 0, respectively. The combined power of discrimination, and the probability of exclusion in duo and trio cases were 0.999 999 999 999 999 999 999 999 34, 0.999 996 0 and 0.999 999 996 5, respectively. Analyses of interpopulation differentiation revealed that the most significant differences were found between the Qinghai Han and Malaysian, while no significant differences were found between the Qinghai Han and Han people from Shaanxi and Jiangsu. The results of principal component analysis, multidimensional scaling analysis and phylogenetic reconstructions also suggested the close relationships between the Qinghai Han and other two Han populations. The present results, therefore, indicated that these 20 STR loci could be used for paternity testing and individual identification in forensic applications, and may also provide information for the studies of genetic relationships between Qinghai Han and other groups.
Contribution of chlorophyll fluorescence to the reflectance of corn foliage

To assess the contribution of chlorophyll fluorescence (ChlF) to apparent reflectance (Ra) in the red/far-red, spectra were collected on a C/sub 4/ agricultural species (corn, Zea mays L.) under conditions ranging from nitrogen deficiency to excess. A significant contribution of ChlF to Ra was observed, with on average 10-25% at 685nm and 2-6% at 740nm of Ra being due to ChlF. Higher ChlF was consistently measured from the abaxial leaf surface as compared to the adaxial. Using 350-665nm excitation, the study confirms the trends in three ChlF ratios established previously by active F technology, suggesting that the ChlF utility this technology has developed for monitoring vegetation physiological status is likely applicable also under natural solar illumination.
Processing capacity for perceptual information in Gaussian noise tokens

The ability to discriminate two noise auditory stimuli increases with bandwidth. This ability also increases with duration, but only up to a duration of about 25 to 40 ms. Beyond this duration the discriminability decreases. In template-matching and multiple-look models [e.g. Dau et al., J. Acoust. Soc. Am. 99, 3615-3622 (1996)] this decrease of discriminability with increasing duration is not modelled correctly. At most, discriminability remains constant for durations above 25 to 40 ms. This suggests there is a limitation in the information processing capacity for long duration stimuli. The current study proposes a model which restricts the amount of stimulus information across time that is allowed in the internal representation of each noise token to a fixed amount. This approach implies is that stimuli with different durations have incompatible internal representations. Accordingly, the model predicts that the ability to discriminate degrades strongly when a fringe is added to one of the stimuli. A listening test confirmed the model prediction that adding a fringe to one of the stimuli severely impairs the discriminability. Apparently stimulus fringes cannot be ignored, suggesting that these stimuli are processed as inseparable units which is in line with the basic assumptions of the model.
Spontaneous pre‐stimulus oscillatory activity shapes the way we look: A concurrent imaging and eye‐movement study

Previous behavioural studies have accrued evidence that response time plays a critical role in determining whether selection is influenced by stimulus saliency or target template. In the present work, we investigated to what extent the variations in timing and consequent oculomotor controls are influenced by spontaneous variations in pre‐stimulus alpha oscillations. We recorded simultaneously brain activity using magnetoencephalography (MEG) and eye movements while participants performed a visual search task. Our results show that slower saccadic reaction times were predicted by an overall stronger alpha power in the 500 ms time window preceding the stimulus onset, while weaker alpha power was a signature of faster responses. When looking separately at performance for fast and slow responses, we found evidence for two specific sources of alpha activity predicting correct versus incorrect responses. When saccades were quickly elicited, errors were predicted by stronger alpha activity in posterior areas, comprising the angular gyrus in the temporal‐parietal junction (TPJ) and possibly the lateral intraparietal area (LIP). Instead, when participants were slower in responding, an increase of alpha power in frontal eye fields (FEF), supplementary eye fields (SEF) and dorsolateral pre‐frontal cortex (DLPFC) predicted erroneous saccades. In other words, oculomotor accuracy in fast responses was predicted by alpha power differences in more posterior areas, while the accuracy in slow responses was predicted by alpha power differences in frontal areas, in line with the idea that these areas may be differentially related to stimulus‐driven and goal‐driven control of selection.
Spectral Properties of Brain Activity Under Two Anesthetics and Their Potential for Inducing Natural Sleep in Birds

Both mammals and birds exhibit two sleep states, slow wave sleep (SWS) and rapid eye movement (REM) sleep. Studying certain aspects of sleep-related electrophysiology in freely behaving animals can present numerous methodological constraints, particularly when even fine body movements interfere with electrophysiological signals. Interestingly, under light general anesthesia, mammals and birds also exhibit slow waves similar to those observed during natural SWS. For these reasons, slow waves occurring under general anesthesia are commonly used in the investigation of sleep-related neurophysiology. However, how spectral properties of slow waves induced by anesthesia correspond to those occurring during natural SWS in birds has yet to be investigated systematically. In this study, we systematically analyzed spectral properties of electroencephalographic (EEG) patterns of pigeons (Columba livia) occurring under two commonly used anesthetics, isoflurane and urethane. These data were compared with EEG patterns during natural sleep. Slow waves occurring during spontaneous SWS, and those induced with isoflurane and urethane all showed greatest absolute power in the slowest frequencies (<3 Hz). Isoflurane and urethane-induced slow waves had near-identical power spectra, and both had higher mean power than that observed during SWS for all frequencies examined (0–25 Hz). Interestingly, burst suppression EEG activity observed under deeper planes of isoflurane anesthesia could occur bihemispherically or unihemispherically. Electrophysiological patterns while under isoflurane and urethane share phenomenological and spectral similarities to those occurring during SWS, notably the generation of high amplitude, slow waves, and peak low-frequency power. These results build upon other studies which suggest that some anesthetics exert their effects by acting on natural sleep pathways. As such, anesthesia-induced slow waves appear to provide an acceptable model for researchers interested in investigating sleep-related slow waves utilizing electrophysiological methods not suitable for use in freely behaving birds.
A non-feedback multiphase clock generator using direct interpolation

This paper presents a new multiphase clock generator using direct interpolators. No feedback loop is required. A single-stage direct interpolation architecture is proposed. A 1/4 frequency divider and a short-circuit current suppression interpolator are developed to achieve the precise interpolation. The circuit was fabricated in a standard 0.35 /spl mu/m, 3.3 V CMOS process. The multiphase clock generator can operate in a wide range of input clock frequencies from 500 MHz to 1 GHz.
Evaluation methodology for classification process of digital images

A methodology is proposed for selecting the best training set, the best classifier and the best set of parameters associated to the classifier. A performance indicator is defined from measures of signatures separability, accuracy between signatures in the training set and in the classified final image, and probability that a pixel belongs to the class which has been assigned. The theoretical description of the suggested methodology has been proved using a image from the Fourier time series analysis. The algorithm has been executed and the obtained results for the best and the worst classifier have been analyzed and evaluated.