Miracle-dz/UniFAR-FTUs huggingface dataset:
Effective, Rapid, and Small-Scale Bioconjugation and Purification of “Clicked” Small-Molecule DNA Oligonucleotide for Nucleic Acid Nanoparticle Functionalization

Nucleic acid-based therapeutics involves the conjugation of small molecule drugs to nucleic acid oligomers to surmount the challenge of solubility, and the inefficient delivery of these drug molecules into cells. “Click” chemistry has become popular conjugation approach due to its simplicity and high conjugation efficiency. However, the major drawback of the conjugation of oligonucleotides is the purification of the products, as traditionally used chromatography techniques are usually time-consuming and laborious, requiring copious quantities of materials. Herein, we introduce a simple and rapid purification methodology to separate the excess of unconjugated small molecules and toxic catalysts using a molecular weight cut-off (MWCO) centrifugation approach. As proof of concept, we deployed “click” chemistry to conjugate a Cy3-alkyne moiety to an azide-functionalized oligodeo-xynucleotide (ODN), as well as a coumarin azide to an alkyne-functionalized ODN. The calculated yields of the conjugated products were found to be 90.3 ± 0.4% and 86.0 ± 1.3% for the ODN-Cy3 and ODN-coumarin, respectively. Analysis of purified products by fluorescence spectroscopy and gel shift assays demonstrated a drastic amplitude of fluorescent intensity by multiple folds of the reporter molecules within DNA nanoparticles. This work is intended to demonstrate a small-scale, cost-effective, and robust approach to purifying ODN conjugates for nucleic acid nanotechnology applications.
Recursive Watermarking-Based Transient Covert Attack Detection for the Industrial CPS

The subject of attack detection for industrial cyber-physical systems (IPCSs) is covered in this paper, which addresses threats from transient covert attacks (TCAs), also referred to as the second version of replay attacks with a specific frequency and short duration. A comprehensive model of the TCAs is built using the active instant and period of the attacks, as well as the dynamics of a virtual system to replicate IPCS function and produce attack signals. Though watermarking-based detection algorithms have been shown to be effective in detecting TCAs, the induced system performance loss is too significant, and as such, our primary goal is to minimize system performance degradation while maintaining the detection rate. Because the active periods of TCAs are substantially shorter than their sleep ones, or even because they are practically always silent, it makes sense that reducing superfluous watermarking will facilitate system performance. So, using an “event-triggered” strategy, a unique recursive watermarking-based detection algorithm is proposed. Here, the trigger modes of watermarking are divided into three types: forced, high probability, and low probability. The design principles are proven via algorithms and criteria, and a theoretical analysis of the detection rate and the system performance loss is also supplied. The advantages of the suggested algorithms are finally demonstrated by numerical simulations of a quadruple-water-tank system and experiments with a permanent magnet synchronous motor on the dSpace platform.
Effect of Contact Force on Local Electrical Impedance in Atrial Tissue - an In Silico Evaluation

Regions with pathologically altered substrate have been identified as potential drivers for atrial fibrillation (AF) maintenance. Recently, local impedance (LI) measurements have gained attention as surrogate for atrial substrate assessment as it does not rely on electrical activity of the heart. However, an appropriate electrode-tissue contact force (CF) is needed and its effect on the LI measurements has not yet been characterized in depth. In this study, we applied several CF to a catheter in contact with a tissue patch modeled as healthy and scar atrial myocardium whose thickness was varied in anatomical ranges to study the impact of the mechanical deformation the LI measurements. When applying CF between 0 and 6g, in silico LI ranged from 160 $\Omega$ to 175 $\Omega$ in healthy my-ocardium, whereas 148 $\Omega$ and 151 $\Omega$ for scar tissue. Increasing CF in scar tissue up to 25 g, increased LI up to 156 $\Omega$. The model was validated against clinically measured LI at different CF from AF patients. Simulation results applying identical CF in both tissues yielded lower LI values in scar. Moreover, LI increased in healthy and scar tissue when the thickness and CF were increased. Given the results of our study, we conclude that in silico experiments can not only distinguish between healthy and scar tissue by combining CF and LI, but also that our simulation environment represents clinical LI measurements with and without mechanical deformation in a tissue model.
A CNN for COVID-19 Detection Using ECG signals

We developed an end-to-end automatic algorithm for the detection of signs of COVID-19 virus infection in ECGs. We analyzed 12-lead ECGs from patients infected by COVID-19 (C-group) and from a control group (NC-group). The C-group (896 cases) included patients (age range [19–96] years) hospitalized at Ospedale San Matteo in Pavia (Italy) during the first 2020 pandemic outbreak. Infection was confirmed by nasal swab testing. The NC-group (also 896 cases) was built by collecting ECG in sinus rhythm from 3 datasets: Georgia ECG (USA), PTB-XL (Germany) and CPSC 2018 (China). Control ECGs were matched by gender, age and heart rate. An additional control group, only used for testing, was extracted from the Ningbo (China) database. A 4-layers convolutional neural network (CNN), with increasing filter size plus a final fully connected (FC) layer, was designed to classify C vs NC-group. The CNN was trained and k-fold cross validated $(k=7)$ on 1536 ECGs (1316 for testing-220 for validation). Every fold model was used to classify the remaining, separate common test set of 256 ECGs. The accuracy was $0.86\pm 0.01$ on validation, $0.86\pm 0.01$ on the test set. The FPR on the NC-group was $0.14\pm 0.03$ on validation, $0.13\pm$ 0.02 on test and $0.10\pm 0.01$ on the Ningbo test set $(p > 0.05,ns)$ showing that no bias was induced by the selection of datasets.
Cardiopulmonary Analysis of Sleep Apnea Based on Weighted Limited Penetrable Visibility Graph

Cardiopulmonary coupling (CPC) has been recognized as an important and low-cost technique for in-home sleep monitoring. Clinically, sleep staging is a prior for evaluation of sleep state, especially for the sleep disorders, such as sleep apnea. However, there are few studies on CPC-based characteristic parameters that could be applied to sleep staging. In this study, inspired by the Visibility Graph and complex networks, we realized CPC analysis using ECG-derived respiration (EDR) technique and mapped the EDR time series of different sleep stages for 16 sleep apnea patients into networks and calculated characteristic parameters using Weighted Limited Penetrable Visibility Graph (WLPVG), including the characteristic path length L, the weighted clustering coefficient entropy ECW and the weight distribution entropy Eω. Each characteristic parameter was evaluated among different sleep stages. Results showed the significant variation of characteristic parameters during different sleep stages. In particular, the characteristic path length L out of three parameters presented high sensitivity for capturing the difference in different stages. This study explored the mechanism of the cardiorespiratory dynamic system during sleep and supported an interpretable basis for subsequent characterization and differentiation of sleep stages.
Supervised Local Training With Backward Links for Deep Neural Networks

The restricted training pattern in the standard backpropagation (BP) requires end-to-end error propagation, causing large memory costs and prohibiting model parallelization. Existing local training methods aim to resolve the training obstacles by completely cutting off the backward path between modules and isolating their gradients. These methods prevent information exchange between modules and result in inferior performance. This work proposes a novel local training algorithm, BackLink, which introduces intermodule backward dependence and facilitates information to flow backward along with the network. To preserve the computational advantage of local training, BackLink restricts the error propagation length within the module. Extensive experiments performed in various deep convolutional neural networks demonstrate that our method consistently improves the classification performance of local training algorithms over other methods. For example, our method can surpass the conventional greedy local training method by 6.45% in accuracy in ResNet32 classifying CIFAR100 and recent work by 2.58% in ResNet110 classifying STL-10 with much lower complexity. Analysis of computational costs reveals that small overheads are incurred in GPU memory costs and runtime on multiple GPUs. Our method can lead up to a 79% reduction in memory cost and 52% in simulation runtime in ResNet110 compared to the standard BP. Therefore, our method could create new opportunities for improving training algorithms toward better efficiency for real-time learning applications.
A functional approach to estimating finite population distribution functions

Existing estimators of a finite population distribution function that utilize auxiliary information are often constructed by a point wise argument. As a result, these estimators are not always monotone. We adopt a functional approach to the problem and propose two estimators based on compositions of functions. Asymptotic variance formulae are derived for the proposed es-timators. Comparisons are made with existing estimators in a simulation study using three natural populations.
Integration Analysis of circRNA–miRNA–mRNA and Identification of Critical Networks in Valgus-Varus Deformity (Gallus gallus)

Valgus-valgus deformity (VVD) is a common leg deformity in broilers with inward or outward deviation of the tibiotarsus and tarsometatarsus. The competing endogenous RNA (ceRNA) network plays an essential role in the study of leg disease. However, its role in the etiology and pathogenesis of VVD remains unclear. Here, based on case (VVD) and control (normal) group design, we performed analyses of differentially expressed circRNAs (DEcircRNAs), differentially expressed miRNAs (DEmiRNAs) and differentially expressed mRNAs (DEmRNAs). Transcriptome data derived 86 DEcircRNAs, 13 DEmiRNAs and 410 DEmRNAs. Functional analysis showed that DEmRNAs were significantly enriched in cell cycle, apoptosis, ECM-receptor interaction, FoxO signaling pathway and protein processing synthesis. DEcirc/miRNA-associated DEmRNAs were associated with skeletal and muscle growth and development pathways, including mTOR, Wnt, and VEGF signaling pathways. Subsequently, a circRNA–miRNA–mRNA regulatory network was constructed based on the ceRNA hypothesis, including 8 circRNAs, 6 miRNAs, and 31 mRNAs, which were significantly enriched in the skeletal developmental pathway. Finally, two key mRNAs (CDC20 and CTNNB1) and their regulatory axes were screened by the PPI network and cytohubba. The expression levels of CDC20 and CTNNB1 in cartilage and seven other tissues were also quantified by qPCR. In conclusion, we analyzed the functions of DEmRNA, DEcircRNA and DEmiRNA and constructed the hub ceRNA regulatory axis, and obtained two hub genes, CDC20 and CTNNB1. The study more deeply explored the etiology and pathogenesis of VVD and lays the foundation for further study of the role of the ceRNA network on skeletal development.
Satellite-Aerial Communications With Multi-Aircraft Interference

Satellite-aerial communication (SAC) is envisioned as a fundamental component of the sixth-generation (6G) wireless networks. Motivated by its importance, we investigate a SAC system including a geostationary satellite (S), a target aircraft (TA), and a set of interfering aircraft (IA). Specifically, TA sends signals to S in the presence of IA interference. Considering the trajectory, hierarchy, and safety distance of the aircraft’s flight routes, we propose a novel three-dimensional stacked Poisson line hardcore point process. That is, we introduce safety distances to the stacked Poisson line Cox process in order to describe the locations of IA in the sky. We also propose two approximations, namely, the equi-dense model and the discretization model, to maintain the tractability of the analysis. To this end, the uplink coverage probability is studied by using the two proposed mathematical models. Moreover, we investigate the coverage probability of the aviation use case with predefined flight altitudes. Finally, numerical results and Monte Carlo simulations are presented to validate the accuracy of the proposed analysis.
Robust Estimation of Variance Components

Outliers may occur with respect to any of the random components in the mixed linear model. A procedure for limiting the influence of these outliers on the estimates of the model parameters is described. Given the variances or estimates of them, the model effects are estimated by augmenting the original observations with auxiliary observations that contain the prior information represented by the variances. Large residuals among either the original or the auxiliary observations are interpreted as outlying random errors or outlying random effects, as appropriate, and Winsorized. The robust estimation of the variances is obtained by modifying the defining equations for the restricted maximum likelihood estimates under normality along the lines of Huber's proposal 2. A numerical example illustrates the use of the methodology, both as a diagnostic and as an estimation tool.
Exploring the Influence of Aggressive and Target-Framing Messages on Proenvironmental Behaviors

As the tenor of climate change debates continues to intensify, it is critical to understand how shifts in style and target affect individuals’ proenvironmental behaviors. Using two online experiments, we investigated how these changes can violate expectations in ways that affect persuasive power. The results suggest that an aggressive style is likely to expectancy violation, which negatively affects individuals’ private- and public-sphere behavioral intentions. Differences in the framing of responsibility between individuals and institutions had limited impacts. The findings offer insights and practical implications for environmental communicators on how communication styles and framing affect efforts to shift climate change behaviors.
Instability of Synchronized Binary Neutron Stars in the First Post-Newtonian Approximation of General Relativity

We investigate the stability property of binary neutron stars (BNSs) just before the merging in the first post-Newtonian(PN) approximation. Stability analysis is performed making use of equilib­ rium configurations for synchronized BNSs which are obtained by the numerical scheme developed in a previous paper. NSs are modeled by means of the polytropic equation of state with the polytropic exponent r=2 and 3. From numerical calculations, we find that as in the Newtonian case, in the PN approximation, the secular instability will occur for synchronized BNSs at a critical angular velocity . krlt before the surfaces of the two stars come into contact. The PN correction changes not only the gravitational attraction force between two NSs, but also the configuration of each NS of a binary system. As a result, Jhlt in the PN approximation is ~10-15 % larger than that in the Newtonian case for a NS of mass MADM~ 1.4 M. and radius rA ~ 10-15 km. The implication of this property to the orbital evolution of BNSs just before merging is discussed.
Singles' similarity preferences in an ideal partner: What, when, and why

This study investigated singles' similarity preferences concerning their ideal partner's personality traits, physical attractiveness, and social resources, as well as potential moderators (fear of being single and mate value) and mediators (forecasted satisfaction). With 1,014 Chinese singles, we found that singles preferred their ideal partner to share similarities in the HEXACO traits, physical attractiveness, and social resources, and they preferred higher similarity in Honesty–Humility and Openness to Experience. Fear of being single, mate value, and forecasted satisfaction did not affect similarity preferences concerning Honesty–Humility and Openness to Experience but had some mixed influence over similarity preferences for other features.
Relationship between body temperature and behavior of nonpregnant early-lactation dairy cows

Graphical Abstract Summary: The behavior and core body temperature of 11 early-lactation Holstein cows in a freestall barn were recorded with a frequency of 10 minutes for a 48-hour period. The probability of increment in body temperature given each of the observed behaviors (feeding, lying, standing, mounting, and rumination) was analyzed with a generalized mixed model. The results showed that body temperature oscillations in early-lactation cows were associated with milking, but not with any of the other observed behaviors. The rhythmicity of body temperature was analyzed using cosinor models. Body temperature in early-lactation cows milked twice daily was best described by a 2-component cosinor model that included a circadian rhythm and a 12-hour ultradian rhythm, with the 2 peaks coincident with milking time. Together, these findings indicate that the schedule of milking sessions can be an important input for establishing daily rhythms of body temperature and activities of early-lactation cows.
Effective energy gap of semiconductors under irradiation with an ultrashort VUV laser pulse

We study theoretically the electronic excitation within semiconductors under irradiation with an ultrashort VUV laser pulse as provided by the new free-electron laser FLASH in Hamburg, Germany. Applying Monte Carlo technique we obtain the transient distribution of the excited electrons within solid silicon. We find the statistical nature of an effective energy gap for multiple electronic excitation, providing the fundamental understanding of the experimentally accessible pair creation energy measured as a long time limit. Considering photoabsorbtion, impact ionizations and Coster-Kroning transitions, we estimate the pair creation energy and give a general formula to calculate the effective energy gap for semiconductors.
Effect of 11 Weeks of Physical Exercise on Physical Fitness and Executive Functions in Children

Object: The aim of our study was to evaluate and compare the effects of physical exercise interventions on physical fitness and executive functions in children. Methods: Six-year-old children participated in the study and were randomly divided into physical exercise group (PE group, n = 43) and control group (C group, n = 46). The children in the PE group participated in a physical exercise program for 45 min daily, four days a week for 11 weeks. The children in the C group continued with their usual routines. Then, all the children were tested before and after the experiment for body composition (height, weight, BMI), physical fitness (20-m shuttle run test, standing long jump test, grip strength test, 4 × 10 m shuttle run test and sit and reach tests), and executive functions test (animal go/no-go task, working memory span task, simple reaction test and flexible item selection task) before and after the 11-week period. Results: The 11 weeks of physical exercise did not significantly affect the body composition of the children (p > 0.05). The physical fitness and executive functions test results showed that 11 weeks of physical exercise interventions improves physical fitness (cardiopulmonary fitness, muscle strength, speed sensitivity and flexibility quality) and executive functions parameters (inhibitory control, working memory, the reaction time, and cognitive flexibility) in children (p < 0.05, p < 0.01). Conclusion: 11 weeks of physical exercise can improve the physical fitness and executive functions of six-year-old children.
Test–Retest Reliability and Internal Consistency of a Newly Developed Questionnaire to Assess Explanatory Variables of 24-h Movement Behaviors in Adults

A questionnaire on explanatory variables for each behavior of the 24-h movement behaviors (i.e., physical activity, sedentary behavior, sleep) was developed based on three levels of the socio-ecological model, i.e., the intrapersonal level, interpersonal level and the physical environmental level. Within these levels, different constructs were questioned, i.e., autonomous motivation, attitude, facilitators, internal behavioral control, self-efficacy, barriers, subjective norm, social modeling, social support, home environment, neighborhood, and work environment. The questionnaire was tested for test–retest reliability (i.e., intraclass correlation (ICC)) for each item and internal consistency for each construct (i.e., Cronbach’s Alpha Coefficient) among a group of 35 healthy adults with a mean age of 42.9 (±16.1) years. The total questionnaire contained 266 items, consisting of 14 items on general information, 70 items on physical activity, 102 items on sedentary behavior, 45 items on sleep and 35 items on the physical environment. Seventy-one percent of the explanatory items showed moderate to excellent reliability (ICC between 0.50 and 0.90) and a majority of constructs had a good homogeneity among items (Cronbach’s Alpha Coefficient ≥ 0.70). This newly developed and comprehensive questionnaire might be used as a tool to understand adults’ 24-h movement behaviors.
The Combination of Hearing Impairment and Frailty Is Associated with Cognitive Decline among Community-Dwelling Elderly in Japan

Hearing impairment and frailty are associated with cognitive decline in older people. This study aimed to investigate the effect of the interaction between hearing impairment and frailty on cognitive decline in community-dwelling older people. A mail survey of community-dwelling, older people (age ≥ 65 years) who lived independently was conducted. Cognitive decline was defined using the self-administered dementia checklist (≥18 out of 40 points). Hearing impairment was assessed using a validated self-rated questionnaire. Furthermore, frailty was assessed using the Kihon checklist, and robust, pre-frailty, and frailty groups were identified. Multivariate logistic regression analysis, adjusted for potential confounding factors, was performed to determine the association of the interaction between hearing impairment and frailty with cognitive decline. Data obtained from 464 participants were analyzed. Hearing impairment was independently associated with cognitive decline. Additionally, the interaction term of hearing impairment and frailty was significantly related to cognitive decline. For participants in the robust group, hearing impairment was not associated with cognitive decline. In contrast, for participants in the pre-frailty or frailty groups, hearing impairment was associated with cognitive decline. The association between hearing impairment and cognitive decline was affected by frailty status in community-dwelling, older people.