Miracle-dz/UniFAR-FTUs huggingface dataset:
Outdoor Absolute Humidity Predicts the Start of Norovirus GII Epidemics

Viral gastroenteritis causes considerable morbidity, especially in vulnerable groups such as the elderly and chronically ill. Predicting the beginning of seasonal epidemics is important for the health care system to withstand increasing demands. ABSTRACT Seasonal variation of viral gastroenteritis is related to weather conditions, but the relationship with the incidence of viral gastroenteritis (GE) is not fully understood. This study examined the impact of outdoor climate factors on seasonal variation in detection rates of gastroenteritis viruses, with emphasis on norovirus. Weekly detection rates of norovirus genogroup I (GI) and II (GII), rotavirus, adenovirus, astrovirus, and sapovirus were analyzed in relation to average weekly means of meteorological parameters. Associations between rates of PCR detection of the viral GE pathogens and climate factors were investigated with generalized linear models. Low absolute humidity was correlated with increased detection of adenovirus (P = 0.007), astrovirus (P = 0.005), rotavirus (P = 0.004), norovirus GI (P = 0.001), and sapovirus (P = 0.002). In each investigated season, a drop in absolute humidity preceded the increase in norovirus GII detections. We found a correlation between declining absolute humidity and increasing norovirus GII detection rate. Absolute humidity was a better predictor of gastrointestinal virus seasonality compared to relative humidity. IMPORTANCE Viral gastroenteritis causes considerable morbidity, especially in vulnerable groups such as the elderly and chronically ill. Predicting the beginning of seasonal epidemics is important for the health care system to withstand increasing demands. In this paper we studied the association of outdoor climate factors on the detection rates of gastrointestinal viruses and the association between these factors and the onset of annual norovirus epidemics. Declining absolute humidity preceded the increase in diagnosed norovirus GII cases by approximately 1 week. These findings contribute to the understanding of norovirus epidemiology and allow health care services to install timely preventive measures and can help the public avoid transmission.
An example of multiple gaps in the spectrum of a?periodic waveguide

A periodic waveguide is constructed, whose shape depends on a? small parameter 0$ SRC=http://ej.iop. org/images/1064-5616/201/4/A04/tex_sm_4082_img1. gif/>, in which the essential spectrum of the operators for some boundary-value problems (Dirichlet, Neumann, and mixed under certain restrictions) for a? formally self-adjoint elliptic system of second-order differential equations acquires any pre-assigned number of gaps. The geometric shape of the waveguide can be interpreted as an infinite periodic set of beads connected by thin, short ligaments. The proof of that gaps appear is based on an application of the max-min principle and the weighted Korn inequality. Bibliography: 43 titles.
ABA collaborates with lignin and flavonoid to improve pre-silking drought tolerance by tuning stem elongation and ear development in maize (Zea mays L.).

Drought is a major abiotic stress reducing maize yield worldwide especially before and during silking. The mechanism underlying drought tolerance in maize has not been elucidated especially from the perspective of different organs. Hence, we conducted field trials under pre-silking drought using two maize genotypes, FM985 (drought tolerant) and ZD958 (drought sensitive). The two genotypes did not differ in plant height, grain number, and yield under control. However, grain number per ear and yield of FM985 were 38.1% and 35.1% higher and plant height was 17.6% shorter than ZD958 under drought. More 13 C-photosynthates were transported to the ear in FM985 than in ZD958, which increased floret fertility and grain number. The number of differentially expressed genes were greatly higher in stem than in other organs. Stem-ear interactions are key determinants of drought tolerance, in which genes expression related to ABA, lignin and flavonoid biosynthesis, and carbon metabolism in the stem were induced by drought, which inhibited stem elongation and promoted assimilates allocation to the ear in FM985. In comparison with ZD958, the activities of trehalose-6-phosphate phosphatase and sucrose non-fermentation-associated kinase 1 were higher in the stem and lower in the kernel of FM958, which facilitated kernel formation. These results reveal that, beyond ear response, stem elongation is involved in the whole process of drought tolerance before silking. ABA together with T6P, lignin and flavonoid suppresses stem elongation and allocates assimilate into ear, providing a novel and systematic regulatory pathway for drought tolerance in maize.
When and where did it happen? Systematic differences in recall of core and optional sentence information

This article reports on four experiments aiming to examine immediate post-sentential recall of core sentence information (conveyed by direct objects), and optional/additional information (conveyed by temporal or locative adjuncts). Participants read simple and unambiguous Czech sentences such as Starší důchodce velmi pečlivě pročetl noviny v neděli v knihovně: “An older retiree read the newspaper very carefully on Sunday in the library. ” Sentences always appeared as a whole after pressing a space bar. Immediately after the sentence disappeared, an open-ended (free response) question was presented targeting either the direct object (e.g., newspaper), temporal adjunct (e.g., on Sunday), or locative adjunct (e.g., in the library). Altogether, it was found that the core information (conveyed by the direct object) was recalled almost perfectly, whereas additional information, conveyed by temporal and locative adjuncts, was recalled with significantly lower accuracy rates. Information structure also played a role: if the temporal or locative adjunct was focused, it was recalled better than if it was unfocused. The present article thus shows systematic differences in recall success for different pieces of information. These findings suggest the presence of selective attention mechanisms during early stages of sentence processing. Factors such as syntactic function or information structure influence the degree of attention to different pieces of information conveyed by a sentence. In turn, certain pieces of information may not be consciously accessible already after the sentence is processed.
Multifunctional Scaffold for Osteoporotic Pathophysiological Microenvironment Improvement and Vascularized Bone Defect Regeneration

Osteoporosis is a degenerative bone disease resulting from bone homeostasis imbalance regulated by osteoblasts and osteoclasts. Treating osteoporotic bone defects tends to be more difficult due to suppressed osteogenic differentiation, hyperactive osteoclastogenesis, and impaired angiogenesis. Hence, a drug carrier system composed of gelatin‐coated hollow mesoporous silica nanoparticles (HMSNs/GM) loaded with pro‐osteogenic parathyroid (PTH) and anti‐osteoclastogenic alendronate (ALN) is constructed and compounded into calcium magnesium phosphate cement (MCPC). The spatial‐temporal release of ions and drugs, controllable degradation rate, and abundant pore structure of MCPC composites enhance osteoporotic bone regeneration in ovariectomized rats by accelerating vascularization, promoting osteogenic differentiation and mineralization, and inhibiting osteoclastogenesis and bone resorption. The MCPC/HMSNs@ALN‐PTH/GM demonstrates a synergistic threefold effect on osteogenesis, osteoclastogenesis, and angiogenesis. It improves the osteoporotic pathophysiological microenvironment and promotes osteoporotic vascularized bone defect regeneration, holding huge potential for other functional biomaterials design and clinical management.
The impact of ADHD symptom severity on reinforcement and punishment learning among adults

ABSTRACT Introduction: Aberrations in feedback learning are hypothesised to contribute to the behavioural disruptions and impairment of attention-deficit/hyperactivity disorder (ADHD). However, few studies have evaluated the relation of reward/punishment feedback and ADHD symptom severity on learning. The current study evaluates the differential effects of reward and punishment feedback on learning among adults with elevated ADHD. Methods: One hundred five participants self-reported their level of current ADHD symptoms and completed an innovative instrumental learning task. Results: Consistent with predictions, participants with low self-reported ADHD symptom severity benefitted equally from reward and punishment feedback during the learning task, whereas participants with high self-reported symptom severity performed better (indexed by accuracy on learning task) from reward than punishment feedback trials. Conclusions: Overall, adults with high self-reported symptom severity of ADHD learned more from reward-based feedback, which provides critical implications for motivational theories about ADHD, as well as for treatment protocols. Future work should examine the translatability of results within a treatment setting.
Material Substrate Physical Properties Control Pseudomonas aeruginosa Biofilm Architecture

The biofilm lifestyle is the most widespread survival strategy in the bacterial world. Pseudomonas aeruginosa biofilms cause chronic infections and are highly recalcitrant to antimicrobials. The genetic requirements allowing P. aeruginosa to grow into biofilms are known, but not the physical stimuli that regulate their formation. ABSTRACT In the wild, bacteria are most frequently found in the form of multicellular structures called biofilms. Biofilms grow at the surface of abiotic and living materials with wide-ranging mechanical properties. The opportunistic pathogen Pseudomonas aeruginosa forms biofilms on indwelling medical devices and on soft tissues, including burn wounds and the airway mucosa. Despite the critical role of substrates in the foundation of biofilms, we still lack a clear understanding of how material mechanics regulate their architecture and the physiology of resident bacteria. Here, we demonstrate that physical properties of hydrogel material substrates define P. aeruginosa biofilm architecture. We show that hydrogel mesh size regulates twitching motility, a surface exploration mechanism priming biofilms, ultimately controlling the organization of single cells in the multicellular community. The resulting architectural transitions increase P. aeruginosa’s tolerance to colistin, a last-resort antibiotic. In addition, mechanical regulation of twitching motility affects P. aeruginosa clonal lineages, so that biofilms are more mixed on relatively denser materials. Our results thereby establish material properties as a factor that dramatically affects biofilm architecture, antibiotic efficacy, and evolution of the resident population. IMPORTANCE The biofilm lifestyle is the most widespread survival strategy in the bacterial world. Pseudomonas aeruginosa biofilms cause chronic infections and are highly recalcitrant to antimicrobials. The genetic requirements allowing P. aeruginosa to grow into biofilms are known, but not the physical stimuli that regulate their formation. Despite colonizing biological tissues, investigations of biofilms on soft materials are limited. In this work, we show that biofilms take unexpected forms when growing on soft substrates. The physical properties of the material shape P. aeruginosa biofilms by regulating surface-specific twitching motility. Physical control of biofilm morphogenesis ultimately influences the resilience of biofilms to antimicrobials, linking physical environment with tolerance to treatment. Altogether, our work established that the physical properties of a surface are a critical environmental regulator of biofilm biogenesis and evolution.
The Effects of Smoking on Human Pharynx Microbiota Composition and Stability

Smoking is associated with an increased risk of respiratory infections. Hypothetically, the altered community diversity of smokers’ pharyngeal microbiota, together with changes in their ecological stability properties, could facilitate their invasion by pathogens. ABSTRACT The oral microbiota is essential to the health of the host, yet little is known about how it responds to disturbances. We examined the oropharyngeal microbiota of 30 individuals over 40 weeks. As the oropharynx is an important gateway to pathogens, and as smoking is associated with increased incidence and severity of respiratory infections, we compared the microbiota of smokers and nonsmokers to shed light on its potential for facilitating infections. We hypothesized that decreased species diversity, decreased community stability, or increased differences in community structure could facilitate invading pathogens. We found that smoking is associated with reduced alpha diversity, greater differences in community structure, and increased environmental filtering. The effects of short-term perturbations (antibiotic use and participants exhibiting cold symptoms) were also investigated. Antibiotic use had a negative effect on alpha diversity, irrespective of smoking status, and both antibiotic use and cold symptoms were associated with highly unique bacterial communities. A stability analysis of models built from the data indicated that there were no differences in local or global stability in the microbial communities of smokers, compared to nonsmokers, and that their microbiota are equally resistant to species invasions. Results from these models suggest that smoker microbiota are perturbed but characterized by alternative stable states that are as stable and invasion-resistant as are the microbiota of nonsmokers. Smoking is unlikely to increase the risk of infectious disease through the altered composition and ecological function of the microbiota; this is more likely due to the effects of smoking on the local and systemic immune system. IMPORTANCE Smoking is associated with an increased risk of respiratory infections. Hypothetically, the altered community diversity of smokers’ pharyngeal microbiota, together with changes in their ecological stability properties, could facilitate their invasion by pathogens. To address this question, we analyzed longitudinal microbiota data of baseline healthy individuals who were either smokers or nonsmokers. While the results indicate reduced biodiversity and increased species turnover in the smokers’ pharyngeal microbiota, their ecological stability properties were not different from those of the microbiota of nonsmokers, implying, in ecological terms, that the smokers’ microbial communities are not less resistant to invasions. Therefore, the study suggests that the increased propensity of respiratory infections that is seen in smokers is more likely associated with changes in the local and systemic immune system than with ecological changes in the microbial communities.
OpenHLS: High-Level Synthesis for Low-Latency Deep Neural Networks for Experimental Science

In many experiment-driven scientific domains, such as high-energy physics, material science, and cosmology, high data rate experiments impose hard constraints on data acquisition systems: collected data must either be indiscriminately stored for post-processing and analysis, thereby necessitating large storage capacity, or accurately filtered in real-time, thereby necessitating low-latency processing. Deep neural networks, effective in other filtering tasks, have not been widely employed in such data acquisition systems, due to design and deployment difficulties. We present an open source, lightweight, compiler framework, without any proprietary dependencies, OpenHLS, based on high-level synthesis techniques, for translating high-level representations of deep neural networks to low-level representations, suitable for deployment to near-sensor devices such as field-programmable gate arrays. We evaluate OpenHLS on various workloads and present a case-study implementation of a deep neural network for Bragg peak detection in the context of high-energy diffraction microscopy. We show OpenHLS is able to produce an implementation of the network with a throughput 4.8 $\mu$s/sample, which is approximately a 4$\times$ improvement over the existing implementation
Single-frequency blue light source based on optically injected diode lasers

We describe a diode-laser-based system capable of generating >50 mW of single-frequency radiation near 425 nm. An alternative extended cavity diode laser injection seeds a semiconductor amplifier, whose output is frequency doubled by a nonlinear crystal placed in a power enhancement cavity. This system is particularly well suited for high-resolution spectroscopy in the blue region, and for laser cooling and trapping of calcium atoms.
MicroFog: A Framework for Scalable Placement of Microservices-based IoT Applications in Federated Fog Environments

MicroService Architecture (MSA) is gaining rapid popularity for developing large-scale IoT applications for deployment within distributed and resource-constrained Fog computing environments. As a cloud-native application architecture, the true power of microservices comes from their loosely coupled, independently deployable and scalable nature, enabling distributed placement and dynamic composition across federated Fog and Cloud clusters. Thus, it is necessary to develop novel microservice placement algorithms that utilise these microservice characteristics to improve the performance of the applications. However, existing Fog computing frameworks lack support for integrating such placement policies due to their shortcomings in multiple areas, including MSA application placement and deployment across multi-fog multi-cloud environments, dynamic microservice composition across multiple distributed clusters, scalability of the framework, support for deploying heterogeneous microservice applications, etc. To this end, we design and implement MicroFog, a Fog computing framework providing a scalable, easy-to-configure control engine that executes placement algorithms and deploys applications across federated Fog environments. Furthermore, MicroFog provides a sufficient abstraction over container orchestration and dynamic microservice composition. The framework is evaluated using multiple use cases. The results demonstrate that MicroFog is a scalable, extensible and easy-to-configure framework that can integrate and evaluate novel placement policies for deploying microservice-based applications within multi-fog multi-cloud environments. We integrate multiple microservice placement policies to demonstrate MicroFog's ability to support horizontally scaled placement, thus reducing the application service response time up to 54%.
Cyber-Physical Power System Layers: Classification, Characterization, and Interactions

This paper provides a strategy to identify layers and sub-layers of cyber-physical power systems (CPPS) and characterize their inter- and intra-actions. The physical layer usually consists of the power grid and protection devices whereas the cyber layer consists of communication, and computation and control components. Combining components of the cyber layer in one layer complicates the process of modeling intra-actions because each component has different failure modes. On the other hand, dividing the cyber layers into a large number of sub-layers may unnecessarily increase the number of system states and increase the computational burden. In this paper, we classify system layers based on their common, coupled, and shared functions. Also, interactions between the classified layers are identified, characterized, and clustered based on their impact on the system. Furthermore, based on the overall function of each layer and types of its components, intra-actions within layers are characterized. The strategies developed in this paper for comprehensive classification of system layers and characterization of their inter- and intra-actions contribute toward the goal of accurate and detailed modeling of state transition and failure and attack propagation in CPPS, which can be used for various reliability assessment studies.
Quantiled conditional variance, skewness, and kurtosis by Cornish-Fisher expansion (preprint)

The conditional variance, skewness, and kurtosis play a central role in time series analysis. These three conditional moments (CMs) are often studied by some parametric models but with two big issues: the risk of model mis-specification and the instability of model estimation. To avoid the above two issues, this paper proposes a novel method to estimate these three CMs by the so-called quantiled CMs (QCMs). The QCM method first adopts the idea of Cornish-Fisher expansion to construct a linear regression model, based on $n$ different estimated conditional quantiles. Next, it computes the QCMs simply and simultaneously by using the ordinary least squares estimator of this regression model, without any prior estimation of the conditional mean. Under certain conditions that allow estimated conditional quantiles to be biased, the QCMs are shown to be consistent with the convergence rate $n^{-1/2}$. Simulation studies indicate that the QCMs perform well under different scenarios of estimated conditional quantiles. In the application, the study of QCMs for eight major stock indexes demonstrates the effectiveness of financial rescue plans during the COVID-19 pandemic outbreak, and unveils a new ``non-zero kink'' phenomenon in the ``news impact curve'' function for the conditional kurtosis.
SpeckleNN: a unified embedding for real-time speckle pattern classification in X-ray single-particle imaging with limited labeled examples

This paper presents a neural network model called SpeckleNN for real-time classification of X-ray single-particle imaging (SPI) speckle patterns, ideal for use in high-data-rate facilities like the European XFEL and LCLS-II-HE. It possesses the capability to carry out few-shot classification on novel samples and demonstrates robust performance even in the presence of substantial missing detector area, rendering it an excellent candidate for real-time high-throughput SPI experiments.
On the degree-Kirchhoff index, Gutman index and the Schultz index of pentagonal cylinder/ Möbius chain

The degree-Kirchhoff index of a graph is given by the sum of inverses of non-zero eigenvalues of the normalized Laplacian matrix of the graph multiplied with the total degree of the graph. Explicit formulas for the degree-Kirchhoff index of various types of cylinder chain and M\"{o}bius chain have been obtained by many researchers in the recent past. In the present paper, we obtain closed-form formulas for the degree-Kirchhoff index of pentagonal cylinder/ M\"{o}bius chain. Also we find here the Gutman index and the Schultz index for those graphs.
Improved Learning-Augmented Algorithms for the Multi-Option Ski Rental Problem via Best-Possible Competitive Analysis

In this paper, we present improved learning-augmented algorithms for the multi-option ski rental problem. Learning-augmented algorithms take ML predictions as an added part of the input and incorporates these predictions in solving the given problem. Due to their unique strength that combines the power of ML predictions with rigorous performance guarantees, they have been extensively studied in the context of online optimization problems. Even though ski rental problems are one of the canonical problems in the field of online optimization, only deterministic algorithms were previously known for multi-option ski rental, with or without learning augmentation. We present the first randomized learning-augmented algorithm for this problem, surpassing previous performance guarantees given by deterministic algorithms. Our learning-augmented algorithm is based on a new, provably best-possible randomized competitive algorithm for the problem. Our results are further complemented by lower bounds for deterministic and randomized algorithms, and computational experiments evaluating our algorithms' performance improvements.