Miracle-dz/UniFAR-FTUs huggingface dataset:
Do Class Size Reductions Protect Students from Infectious Diseases?

We evaluate the causal effect of class size (number of students in a classroom) on incidence of class closure due to the flu, as an outcome of an infectious disease epidemic. For identification of causal effects, we apply a regression discontinuity design using discontinuous variation of class sizes, around the class size cap set by regulation, to administrative data of public primary and middle school students in one of the largest municipalities within the Tokyo metropolitan area from 2015 to 2017. Most classrooms in Japan are constructed in accordance with a standard of classroom area, 63 square meters; class size reduction improves social distancing among students in a classroom. We find that class size reduction is effective in reducing class closures due to the flu: a one-unit reduction of class size decreases class closure by about 5 percent. Additionally, forming small classes with 27 students at most, satisfying the social distancing of 1.5 meters recommended to prevent droplet infection including influenza and COVID-19, reduces class closure by about 90 percent. Moreover, we find that the older the students, the larger the effects of class size reduction. Our findings provide evidence for the effectiveness of social distancing policy in primary and middle schools to protect students from droplet infectious disease spread, including COVID-19.
Optical Gravitational Lensing Experiment. The Distance Scale: Galactic Bulge - LMC - SMC

We analyze the mean luminosity of three samples of field RRab Lyr stars observed in the course of the OGLE microlensing experiment: 73 stars from the Galactic bulge and 110 and 128 stars from selected fields in the LMC and SMC, respectively. The fields are the same as in the recent distance determination to the Magellanic Clouds with the red clump stars method by Udalski et al (1998). We determine the relative distance scale d_{GB}:d_{LMC}:d_{SMC} equal to: (0.194+/-0.010):1.00:(1.30+/-0.08). We calibrate our RR Lyr distance scale with the recent calibration of Gould and Popowski (1998) based on statistical parallaxes. We obtain the following distance moduli to the Galactic bulge, LMC and SMC: m-M=14.53+/-0.15, m-M=18.09+/-0.16 and m-M=18.66+/-0.16 mag. We use the RR Lyr mean V-band luminosity at the Galactic bulge metallicity as the reference brightness and analyze the mean, I-band luminosity of the red clump stars in objects with different ages and metallicities. We add to our analysis the metal poor Carina dwarf galaxy which contains old RR Lyr stars and intermediate age red clump population. We find a weak dependence of the mean red clump brightness on metallicity and we calibrate its zero point with the nearby local red clump stars measured by Hipparcos: M^{RC}_I=(0.09+/-0.03) *[Fe/H]^{RC}-0.23+/-0.03. Our revised red clump distance moduli to the Galactic bulge, LMC and SMC are m-M=14.53+/-0.06, m-M=18.13+/-0.07 and m-M=18.63+/-0.07 mag, respectively. The distance modulus to the Carina galaxy is m-M=19.84+/- 0.07 mag. Excellent agreement of RR Lyr and red clump distances which have independent absolute calibrations confirms the short distance scale to the LMC.
Generalization from correlated sets of patterns in the perceptron

Generalization is a central aspect of learning theory. Here, we propose a framework that explores an auxiliary task-dependent notion of generalization, and attempts to quantitatively answer the following question: given two sets of patterns with a given degree of dissimilarity, how easily will a network be able to ‘unify’ their interpretation? This is quantified by the volume of the configurations of synaptic weights that classify the two sets in a similar manner. To show the applicability of our idea in a concrete setting, we compute this quantity for the perceptron, a simple binary classifier, using the classical statistical physics approach in the replica-symmetric ansatz. In this case, we show how an analytical expression measures the ‘distance-based capacity’, the maximum load of patterns sustainable by the network, at fixed dissimilarity between patterns and fixed allowed number of errors. This curve indicates that generalization is possible at any distance, but with decreasing capacity. We propose that a distance-based definition of generalization may be useful in numerical experiments with real-world neural networks, and to explore computationally sub-dominant sets of synaptic solutions.
Towards the cycle structures in complex network: A new perspective

Stars and cycles are basic structures in network construction. The former has been well studied in network analysis, while the latter attracted rare attention. A node together with its neighbors constitute a neighborhood star-structure where the basic assumption is two nodes interact through their direct connection. A cycle is a closed loop with many nodes who can influence each other even without direct connection. Here we show their difference and relationship in understanding network structure and function. We define two cycle-based node characteristics, namely cycle number and cycle ratio, which can be used to measure a node's importance. Numerical analyses on six disparate real networks suggest that the nodes with higher cycle ratio are more important to network connectivity, while cycle number can better quantify a node influence of cycle-based spreading than the common star-based node centralities. We also find that an ordinary network can be converted into a hypernetwork by considering its basic cycles as hyperedges, meanwhile, a new matrix called the cycle number matrix is captured. We hope that this paper can open a new direction of understanding both local and global structures of network and its function.
Physiological Sensing for Media Perception & Activity Recognition

Wearable sensors have the intriguing potential to continuously evaluate human physiological characteristics in real-time without being obtrusive. This thesis aims to incorporate physiological sensors data to investigate the Media Perception and Activity Recognition. Our primary research goals include (a) neural encoding-based psycho-acoustic attribute analysis for data sonification, (b) empirical evidence for perceptual subjectivity in neural encoding during human-media interactions, the impact of incorporating behavioral ratings, and (c) the efficacy of attention-based transformer models on physiological data on human activity recognition problems.
In-vitro efficacy of some fungicides , bioagents and culture filtrates of selected saprophytic fungi against Sclerotium rolfsii

The inhibitory effect of the fungicides, different formulations of bioagents and culture filtrate of some saprophytic fungal isolates against the growth of Sclerotium rolfsii was evaluated in-vitro. The obtained results indicate that all evaluated materials significantly reduced the linear growth of Sclerotium rolfsii. Rhizolex fungicide was found to highly effective and gave 100% reduction in growth when used at lower concentration (12.5ppm). The same effect was recorded at 100, 200, and 400 ppm of Top zin and at 400ppm of Score fungicide. Tazolen showed also 100% inhibition at concentrations of 100 to 400ppm.The bioagent Bio-arc (T. albium) was the most effective against S. rolfsii growth responsible for 44.66 mean % inhibition, followed by Biocure-F (T.viride) responsible for 29.08 mean % inhibition with significant difference. Bio-arc (B. megatherium), Biocure-Z (T. harzianum) and Plant guard (T. harzianum) bioagents were fare less effective, as the mean percentage inhibition were 2.81, 2.97 and 3.49% respectively. Maximum inhibition was observed in the culture filtrate of T. harzianum drawn from potato dextrose broth with mean reduction of 52.33%. Among the tested saprophytic fungal isolates, Aspergillus ochraceus and Rhizopus nigricans showed high mean reduction of 47.18 and 46.71 % respectively.The treatments with culture filtrates of all tested fungal isolates were effective in reducing mycelia growth of S. rolfsii. [Lubna S. Nawar. In-vitro efficacy of some fungicides, bioagents and culture filtrates of selected saprophytic fungi against Sclerotium rolfsii. Life Sci J 2013;10(4):2222-2228]. (ISSN:1097-8135). http://www.lifesciencesite. com. 297 Keyword: Antifungal, saprophytic soil fungi, root-rot, fungicide, Sclerotium rolfsii, bioagents, culture filtrates,
Very large dielectric response of thin ferroelectric films with the dead layers

We study the dielectric response of ferroelectric (FE) thin films with the ``dead'' dielectric layer at the interface with electrodes. The domain structure inevitably forms in the FE film in the presence of the dead layer. As a result, the effective dielectric constant of the capacitor ${\ensuremath{\epsilon}}_{\mathrm{eff}}$ increases abruptly when the dead layer is thin and, consequently, the pattern of $180\ifmmode^\circ\else\textdegree\fi{}$ domains becomes ``soft. '' We compare the exact results for this problem with the description in terms of a popular ``capacitor'' model, which is shown to give qualitatively incorrect results. We relate the present results to fatigue observed in thin ferroelectric films.
Mood-Emotion Interplay: A Computational Perspective

Emotion and mood influence human cognition, memory, judgement, and decision making abilities. The two affective states differ in terms of duration, intensity, and the cause of occurrence. While studies in psychology demonstrate the interactions between mood and emotion, on the contrary, research in the affective computing domain has predominantly focused on emotion inference from various modalities like facial expression, speech, physiological signals, etc., and hardly any studies exist either on mood inference or examining the relation between mood and emotion. In this regard, the objective of this research is to simultaneously model the two affective states even though they might occur on different timelines. By using in-the-wild video data and leveraging the emotion information, the aim of this research is to infer mood and observe the mood-emotion interplay. To this end, the research to date uses AFEW-VA dataset and runs experiments using temporal emotional change in addition to the mood ratings to predict mood. This approach demonstrates that mood prediction is enhanced when emotional change labels are incorporated apart from the mood labels.
Topological phase preparation in a pair of atomic Bose-Einstein condensates

We theoretically study the optical properties of a Fermi-Dirac gas in the presence of a superfluid state. We calculate the leading quantum-statistical corrections to the standard column density result of the electric susceptibility. We also consider the Bragg diffraction of atoms by means of light-stimulated transitions of photons between two intersecting laser beams. Bardeen-Cooper-Schrieffer pairing between atoms in different internal levels magnifies incoherent scattering processes. The absorption linewidth of a Fermi-Dirac gas is broadened and shifted. Bardeen-Cooper-Schrieffer pairing introduces a collisional local-field shift that may dramatically dominate the Lorentz-Lorenz shift. For the case of the Bragg spectroscopy the static structure function may be significantly increased due to superfluidity in the nearforward scattering.
Training Computational Models of Group Processes without Groundtruth: the Self- vs External Assessment’s Dilemma

Supervised learning relies on the availability and reliability of the labels used to train computational models. In research areas such as Affective Computing and Social Signal Processing, such labels are usually extracted from multiple self- and/or external assessments. Labels are, then, either aggregated to produce a single groundtruth label, or all used during training, potentially resulting in degrading performance of the models. Defining a “true” label is, however, complex. Labels can be gathered at different times, with different tools, and may contain biases. Furthermore, multiple assessments are usually available for a same sample with potential contradictions. Thus, it is crucial to devise strategies that can take advantage of both self- and external assessments to train computational models without a reliable groundtruth. In this study, we designed and tested 3 of such strategies with the aim of mitigating the biases and making the models more robust to uncertain labels. Results show that the strategy based on weighting the loss during training according to a measure of disagreement improved the performances of the baseline, hence, underlining the potential of such an approach.
GENEA Workshop 2022: The 3rd Workshop on Generation and Evaluation of Non-verbal Behaviour for Embodied Agents

Embodied agents benefit from using non-verbal behavior when communicating with humans. Despite several decades of non-verbal behavior-generation research, there is currently no well-developed benchmarking culture in the field. For example, most researchers do not compare their outcomes with previous work, and if they do, they often do so in their own way which frequently is incompatible with others. With the GENEA Workshop 2022, we aim to bring the community together to discuss key challenges and solutions, and find the most appropriate ways to move the field forward.
ACCELERATED FITTING OF STELLAR SPECTRA

Stellar spectra are often modeled and fitted by interpolating within a rectilinear grid of synthetic spectra to derive the stars’ labels: stellar parameters and elemental abundances. However, the number of synthetic spectra needed for a rectilinear grid grows exponentially with the label space dimensions, precluding the simultaneous and self-consistent fitting of more than a few elemental abundances. Shortcuts such as fitting subsets of labels separately can introduce unknown systematics and do not produce correct error covariances in the derived labels. In this paper we present a new approach—Convex Hull Adaptive Tessellation (chat)—which includes several new ideas for inexpensively generating a sufficient stellar synthetic library, using linear algebra and the concept of an adaptive, data-driven grid. A convex hull approximates the region where the data lie in the label space. A variety of tests with mock data sets demonstrate that chat can reduce the number of required synthetic model calculations by three orders of magnitude in an eight-dimensional label space. The reduction will be even larger for higher dimensional label spaces. In chat the computational effort increases only linearly with the number of labels that are fit simultaneously. Around each of these grid points in the label space an approximate synthetic spectrum can be generated through linear expansion using a set of “gradient spectra” that represent flux derivatives at every wavelength point with respect to all labels. These techniques provide new opportunities to fit the full stellar spectra from large surveys with 15–30 labels simultaneously.
FkpA enhances membrane protein folding using an extensive interaction surface

Outer membrane protein (OMP) biogenesis in gram-negative bacteria is managed by a network of periplasmic chaperones that includes SurA, Skp, and FkpA. These chaperones bind unfolded OMPs (uOMPs) in dynamic conformational ensembles to suppress uOMP aggregation, facilitate diffusion across the periplasm, and enhance OMP folding. FkpA primarily responds to heat-shock stress, but its mechanism is comparatively understudied. To determine FkpA chaperone function, we monitored the folding of a cognate client uOmpA171 and found that FkpA increases the folded uOmpA171population but also slows the folding rate, dual functions distinct from the other periplasmic chaperones. The results indicate that FkpA behaves as a chaperone and not as a folding catalyst to directly influence the uOmpA171folding trajectory. We determine the binding affinity between FkpA and uOmpA171 by globally fitting sedimentation velocity titrations and found it to be intermediate between the known affinities of Skp and SurA for uOMP clients. Notably, complex formation steeply depends on the urea concentration, suggestive of an extensive binding interface. Initial characterizations of the complex using photo-crosslinking indicates that the binding interface spans the inner surfaces of the entire FkpA molecule. In contrast to prior findings, folding and binding experiments performed using subdomain constructs of FkpA demonstrate that the full-length chaperone is required for full activity. Together these results support that FkpA has a distinct and direct effect on uOMP folding and that it achieves this by utilizing an extensive chaperone-client interface. Significance The periplasmic chaperone network is required for the survival and virulence of gram-negative bacteria. Here we find that the chaperone FkpA enhances outer membrane protein folding and tightly binds its clients with an extensive interaction interface. This modified holdase function of FkpA distinguishes it from other periplasmic chaperones and complements their functions to ensure robust outer membrane biogenesis.
Integrated multi-omics analysis of brain aging in female nonhuman primates reveals altered signaling pathways relevant to age-related disorders

The prefrontal cortex (PFC) has been implicated as a key brain region responsible for age-related cognitive decline. Little is known about aging-related molecular changes in PFC that may mediate these effects. To date, no studies have used untargeted discovery methods with integrated analyses to determine PFC molecular changes in healthy female primates. We quantified PFC changes associated with healthy aging in female baboons by integrating multiple omics data types (transcriptomics, proteomics, metabolomics) from samples across the adult age span. Our integrated omics approach using unbiased weighted gene co-expression network analysis (WGCNA) to integrate data and treat age as a continuous variable, revealed highly interconnected known and novel pathways associated with PFC aging. We found GABA tissue content associated with these signaling pathways, providing one potential biomarker to assess PFC changes with age. These highly coordinated pathway changes during aging may represent early steps for aging-related decline in PFC functions, such as learning and memory, and provide potential biomarkers to assess cognitive status in humans.
A Checking Model of Obsessive-Compulsive Disorder Based on the Hypothalamic Defensive System Against a Potential Threat

BACKGROUND Obsessive-compulsive disorder (OCD) is a psychiatric disorder characterized by obsessive thoughts and compulsive behavior. While some theories imply that OCD patients have cognitive biases and dysfunctional motivation regarding a potential threat, these views are not adequately supported by neurological evidence. Hypothalamic perifornical (PeF) urocortin-3 (UCN3) neurons are involved in defensive responses to a potential threat, and the activation of these neurons in mice induces repetitive and excessive checking and burying of novel objects. In this study, we evaluated the hypothesis that mice in which PeF UCN3 neurons are activated can serve as an OCD model. METHODS PeF UCN3 neurons were chemogenetically activated with clozapine-N oxide (CNO) in Ucn3-Cre mice. Marble-burying activity, repetitive/stereotypic behaviors in the homecage, and excessive responses to a novel object were measured as OCD-like behaviors. The effects of clinically used drugs for treating OCD on these behaviors were evaluated. The effect of CNO on neural activity in the cortico-striato-thalamo-cortical loop (which is regarded as an OCD circuit) was assessed with c-Fos immunolabeling. RESULTS CNO increased marble-burying activity, evoked homecage-specific repetitive/stereotypic behaviors that probably aimed to seal entrances, and induced repetitive and excessive checking and burying of novel objects. These behaviors were suppressed by selective serotonin-reuptake inhibitors but not by diazepam. CNO increased neural activity in the cortico-striato-thalamo-cortical loop. CONCLUSIONS These results indicated that mice whose PeF UCN3 neurons are activated can serve as a model of OCD, particularly as a checking model. This supports theories concerning the role of potential threats in the pathophysiology of OCD.
Transcriptome profiles of eggplant (Solanum melongena) and its wild relative S. dasyphyllum under different levels of osmotic stress provide insights into response mechanisms to drought

Defence mechanisms to abiotic stresses, like drought, are very broad and RNA sequencing (RNA-Seq) can help in understanding the complex responses triggered. In this study, we performed RNA-Seq of the transcriptomes of eggplant (Solanum melongena) and its related wild species (S. dasyphyllum) under two PEG concentrations (20% and 30%), two different times (after 0.5 h and 2 h of osmotic stress) and at two plant phenological stages (three and five true fully developed leaves). Solanum dasyphyllum was more tolerant to osmotic stress, and a differential expression pattern of drought-related genes was identified between the two species. Plants subjected to a higher osmotic potential, at a more adult stage and at a higher stress exposure time displayed a higher number of DEGs (differential expressed genes). Gene ontology (GO) enrichment analysis revealed that, compared to S. melongena, S. dasyphyllum triggered the regulation of a wide range of transcription factors (AP2/ERF, DREB, bZIP, WRKY and bHLH). In both species, the abscisic acid (ABA) signaling response pathway played a crucial role leading to stomatal closure. Other important pathways involved in abiotic stresses tolerance including flavonoid, carotenoid and phenylpropanoid biosynthesis, chlorophyll metabolism and photosynthesis pathway among others were found to have a relevant role under both moderate and severe osmotic stresses. Our results reveal that S. dasyphyllum is a potential source of genes for breeding resilient eggplant varieties.
A Morse-theoretical analysis of gravitational lensing by a Kerr-Newman black hole

Consider, in the domain of outer communication M+ of a Kerr-Newman black hole, a point p (observation event) and a timelike curve γ (worldline of light source). Assume that γ (i) has no past endpoint, (ii) does not intersect the caustic of the past light cone of p, and (iii) goes neither to the horizon nor to infinity in the past. We prove that then for infinitely many positive integers k there is a past-pointing lightlike geodesic λk of (Morse) index k from p to γ, hence an observer at p sees infinitely many images of γ. Moreover, we demonstrate that all lightlike geodesics from an event to a timelike curve in M+ are confined to a certain spherical shell. Our characterization of this spherical shell shows that in the Kerr-Newman space-time the occurrence of infinitely many images is intimately related to the occurrence of centrifugal-plus-Coriolis force reversal.
Real-time observation of oxidation and photo-oxidation of rubrene thin films by spectroscopic ellipsometry

The authors follow in real time and under controlled conditions the oxidation of the organic semiconductor rubrene grown on SiO2 using spectroscopic ellipsometry. They derive the complex dielectric function e1+ie2 for pristine and oxidized rubrene showing that the oxidation is accompanied by a significant change of the optical properties, namely, the absorption. The authors observe that photo-oxidation of rubrene is orders of magnitude faster than oxidation without illumination. By following different absorption bands (around 2.5 and 4.0eV for pristine rubrene and around 4.9eV for oxidized rubrene) they infer that the observed photo-oxidation of these films involves non-Fickian diffusion mechanisms.