Miracle-dz/UniFAR-FTUs huggingface dataset:
The classification of Boolean degree $1$ functions in high-dimensional finite vector spaces

We classify the Boolean degree $1$ functions of $k$-spaces in a vector space of dimension $n$ (also known as Cameron-Liebler classes) over the field with $q$ elements for $n \geq n_0(k, q)$, a problem going back to a work by Cameron and Liebler from 1982. This also implies that two-intersecting sets with respect to $k$-spaces do not exist for $n \geq n_0(k, q)$. Our main ingredient is the Ramsey theory for geometric lattices.
A perturbative construction of primitive forms from log Landau-Ginzburg mirrors of toric manifolds

We introduce the notion of a logarithmic Landau-Ginzburg (log LG) model, which is essentially given by equipping the central degenerate fiber of the family of Landau-Ginzburg (LG) models mirror to a projective toric manifold with a natural log structure. We show that the state space of the mirror log LG model is naturally isomorphic to that of the original toric manifold. Following Li-Li-Saito, we give a perturbative construction of primitive forms by studying the deformation theory of such a log LG model, which involves both smoothing of the central degenerate fiber and unfolding of the superpotential. This yields a logarithmic Frobenius manifold structure on the base space of the universal unfolding. The primitive forms and flat coordinates we obtained are computable and closely related to the bulk-deformed Lagrangian Floer superpotential of a projective toric manifold, at least in the semi-Fano case.
Remaining-Useful-Life Prediction and Uncertainty Quantification using LSTM Ensembles for Aircraft Engines

This paper proposes "LSTM (Long Short Term Memory) Ensemble" technique in building a regression model to predict the Remaining-Useful-Life (RUL) of aircraft engines along with uncertainty quantification, utilising the well-known run-to-failure turbo engine degradation dataset. This paper addressed the overlooked yet crucial aspect of uncertainty estimation in previous research, by revamping the LSTM architecture to facilitate uncertainty estimates, employing Negative Log Likelihood (NLL) as the training criterion. Through a series of experiments, the model demonstrated self-awareness of its uncertainty levels, correlating high confidence with low prediction errors and vice versa. This initiative not only enhances predictive maintenance strategies but also significantly improves the safety and reliability of aviation assets by offering a more nuanced understanding of predictive uncertainties. To the best of our knowledge, this is a pioneering work in this application domain from a non-Bayesian approach.
Crustal structure in the Yunnan region determined by modeling receiver functions

We selected broadband teleseismic waveform data recorded by the Yunnan Seismic Network and CDSN to study the crustal structure in Yunnan and its adjacent region.The crustal thickness and Vp/Vs ratio are estimated by the grid-search method using crustal conversion and multiples,assuming an average P-wave velocity in the crust.Teleseismic P waveform modeling is carried out to investigate the S-wave velocity structure,assuming the fixed Vp/Vs value inferred from the grid-search method.The results from the two estimation techniques were consistent.Our results show strong lateral variations in crustal thickness in this area.Our results also indicate that there exist low velocity zones and high Vp/Vs beneath the Yunnan region,especially in western Yunnan.All these are the possible evidence of the crustal flow in middle-to-lower crust,which are responsible for the thickening of crust.The Vp/Vs and crustal thickness are different across the Red-river fault,which implies that the Red-river fault is one main boundary fault.Combining results from other geophysical investigations,we conclude that both the Simao terrane and Baoshan-Tengchong terrane belong to the Gondwana plate.
Zero-Class Poisson for Rare-Event Studies

We developed a statistical theory of zero-count-detector (ZCD), which is defined as a zero-class Poisson under conditions outlined in the paper. ZCD is often encountered in the studies of rare events in physics, health physics, and many other fields where counting of events occurs. We found no acceptable solution to ZCD in classical statistics and affirmed the need for the Bayesian statistics. Several uniform and reference priors were studied and we derived Bayesian posteriors, point estimates, and upper limits. It was showed that the maximum-entropy prior, containing the most information, resulted in the smallest bias and the lowest risk, making it the most admissible and acceptable among the priors studied. We also investigated application of zero-inflated Poisson and Negative-binomial distributions to ZCD. It was showed using Bayesian marginalization that, under limited information, these distributions reduce to the Poisson distribution.
Origins of electromagnetic radiation from spintronic terahertz emitters: A time-dependent density functional theory plus Jefimenko equations approach

Microscopic origins of charge currents and electromagnetic (EM) radiation generated by them in spintronic THz emitters -- such as, femtosecond laser pulse-driven single magnetic layer or its heterostructures with a nonmagnetic layer hosting strong spin-orbit coupling (SOC) -- remain poorly understood despite nearly three decades since the discovery of ultrafast demagnetization. We introduce a first-principles method to compute these quantities, where the dynamics of charge and current densities is obtained from real-time time-dependent density functional theory (TDDFT), which are then fed into the Jefimenko equations for properly retarded electric and magnetic field solutions of the Maxwell equations. By Fourier transforming different time-dependent terms in the Jefimenko equations, we unravel that in 0.1--30 THz range the electric field of far-field EM radiation by Ni layer, chosen as an example, is {\em dominated by charge current pumped by demagnetization}, while often invoked magnetic dipole radiation from time-dependent magnetization of a single magnetic layer is a negligible effect. Such overlooked case of charge current pumping by time-dependent quantum system, whose magnetization is shrinking while its vector does not rotate, does not require any spin-to-charge conversion via SOC effects. In Ni/Pt bilayer, EM radiation remains dominated by charge current within Ni layer, whose magnitude is larger than in the case of single Ni layer due to faster demagnetization, while often invoked spin-to-charge conversion within Pt layer provides additional but smaller contribution. By using Poynting vector and its flux, we also quantify efficiency of conversion of light into emitted EM radiation, as well as the angular distribution of the latter.
Resource Allocation for Semantic Communication Under Physical-layer Security

Semantic communication is deemed as a revolution of Shannon's paradigm in the six-generation (6G) wireless networks. It aims at transmitting the extracted information rather than the original data, which receivers will try to recover. Intuitively, the larger extracted information, the longer latency of semantic communication will be. Besides, larger extracted information will result in more accurate reconstructed information, thereby causing a higher utility of the semantic communication system. Shorter latency and higher utility are desirable objectives for the system, so there will be a trade-off between utility and latency. This paper proposes a joint optimization algorithm for total latency and utility. Moreover, security is essential for the semantic communication system. We incorporate the secrecy rate, a physical-layer security method, into the optimization problem. The secrecy rate is the communication rate at which no information is disclosed to an eavesdropper. Experimental results demonstrate that the proposed algorithm obtains the best joint optimization performance compared to the baselines.
Determining Bed-Tilt Compliance with a Wireless Sensing System and Bedside Feedback

Purpose : Ventilator-associated pneumonia, a common nosocomial infection, has been shown to occur less frequently when the head-of-bed angle (HOBA) is maintained between 30 and 45 degrees. Our team developed and deployed a novel, real-time , wireless sensing system to track HOBAs of ventilated hospital patients. We utilized the data to determine rates of compliance, causes for noncompliance , and methods for raising protocol adherence. Scope : A review of bed-angle compliance studies suggests that less structured and controlled observations produce higher compliance rates. A portable sensing system offers an objective tool to continuously monitor and report bed angles over a sustained period of time without human-recorded logs or charts. Methods : Following a 1 -week pilot study, HOBA monitors were placed on 20 patient beds over a 3-week experimental period. Then, 83,655 bed-angle samples were recorded over 1,579 hours and compared with staff-recorded bed angles. The final experiment acquired 224,000 angle records to measure the effectiveness of HOBA feedback at the bedside. Results : The monitoring system found an average HOBA of 27.34 degrees—a compliance rate of 35.8%. Noncompliant angles slightly less than the desired angles, or slips, accounted for 55.9% of all HOBA s . Long periods of low-HOBA, or lapses, accounted for only 7.1% of the angles. Bedside feedback improved compliance rates from 41.3% to 64.5%.
BayesAge: A Maximum Likelihood Algorithm To Predict Epigenetic Age

DNA methylation is a reaction that results in the formation of 5-methylcytosine when a methyl group is added to the cytosine’s C5 position. As organisms age, DNA methylation patterns change in a reproducible fashion. This phenomenon has established DNA methylation as a valuable biomarker in aging studies. Epigenetic clocks based on weighted combinations of methylation sites have been developed to accurately predict the age of an individual from their methylome. However, many epigenetic clocks, particularly those that utilize penalized regression, model the changes in methylation linearly with age. Moreover, these models, which use methylation levels as features, are not robust to missing data and do not account the count-based nature of bisulfite sequence data. Additionally, the models are generally not interpretable. To overcome these challenges, we present BayesAge, an extension of the previously developed scAge approach that was developed for the analysis of single cell DNA methylation datasets. BayesAge utilizes maximum likelihood estimation (MLE) to infer ages, models count data using binomial distributions, and uses LOWESS smoothing to capture the non-linear dynamics between methylation and age. Our approach is designed for use with bulk bisulfite sequencing datasets. BayesAge outperforms scAge in several respects. Specifically, BayesAge’s age residuals are not age associated, thus providing a less biased representation of epigenetic age variation across populations. Moreover, BayesAge enables the estimation of error bounds on age inference and, when run on down-sampled data, its coefficient of determination between predicted and actual ages surpasses both scAge and penalized regression.
Strategic Communication and Barriers to Strategy Implementation

This research work's core objective is to categorise and understand the barriers to strategic implementation, focusing, then, through an inquiry, in the most voted of them, to make a deeper analysis on one of the variables. To that end, this document begins with a literature review and begins to identify the importance that strategic communication has in the process of propagating a given individual idea or, in the terms that interests us most, within of an organization - whether ascending or descending, horizontal or vertical. In the organizational arena, business and communication are two inseparable issues.Then it is explained more deeply in what barriers to strategic implementation consists, in its variances of application and how it is immersed in the multiple possibilities that can cause the collapse of the plans orchestrated by the companies. In the end, as a theoretical complement, a questionnaire was designed for a relatively large number of people who were confronted with the topics under discussion throughout this article.
Efficient Monotonic Multihead Attention

We introduce the Efficient Monotonic Multihead Attention (EMMA), a state-of-the-art simultaneous translation model with numerically-stable and unbiased monotonic alignment estimation. In addition, we present improved training and inference strategies, including simultaneous fine-tuning from an offline translation model and reduction of monotonic alignment variance. The experimental results demonstrate that the proposed model attains state-of-the-art performance in simultaneous speech-to-text translation on the Spanish and English translation task.
Maximum elastic scheduling of virtual machines in general graph cloud data center networks

The assignment of task resources has drawn a lot of attention in the applications of cloud-based data center networks (DCNs). In this work, we provide a novel method that evaluates the maximum admissible load (MAL) given a set of virtual machines (VMs) in physical machines (PMs). This is the first study that considers the general case of DCNs with no constraints on their topologies, contrary to previous research. We prove that this problem can be reduced to a single-source, multiple-sink maximum flow problem. In addition, we find the optimal load assignment that supports the maximum uniform growth rate without resorting to task reassignment to PMs. This is called the maximum elastic scheduling problem. A new effective strategy is devised to solve the two problems. We demonstrate the efficiency of its performance using an extensive simulation.
Loyola eCommons Loyola eCommons

Social scientists are facing a crisis of con ﬁ dence in quantitative results. Multiverse analysis provides concerned scholars a tool for verifying the robustness of ﬁ ndings. This article introduces political scientists to multiverse analysis through an application. It identi ﬁ es how differing approaches to data processing led to divergent conclusions about the representation of lesbian, gay, and bisexual (LGB) Americans in Congress in a 2015 Journal of Politics article. The analysis casts doubt on the original conclusion that the size of the LGB population in a district is signi ﬁ cantly associated with the bill sponsorship activity of its representative. More broadly, it demonstrates how researchers can keep a running tally of data-processing decisions and parsimoniously present the consequences of those decisions for the ﬁ ndings. Multiverse analysis can help scholars publish replicable results in original work as well as replicate and extend previously published work.
Intermediate CA1 is Required for Object-in-Place Recognition Memory in Mice

Many behaviors that are essential for survival, such as retrieving food, finding shelter and locating predator cues, rely on forming effective associations between the identity and location of spatial elements. This identity-location association is commonly assessed in rodents using spontaneous object-in-place (OiP) recognition memory tasks. OiP recognition memory deficits are seen in autism spectrum disorder, schizophrenia, and are used to detect early onset of Alzheimer’s disease. These deficits are replicated in animal models of neurodevelopmental, neurodegenerative and chromosomal disorders. Mouse models have been widely adopted in behavioral and systems neuroscience research for their ease of genetic manipulations, and yet very few studies have successfully assessed OiP recognition memory or its neural correlates in mice. To address this limitation, we first established that adult C57/129J and C57BL/6J male and female mice are able to successfully perform the two-object, but not the four-object version of the spontaneous OiP recognition task, with retention intervals of five minutes and one hour. Next, using chemogenetic inhibition, we found that two-object OiP requires the activity of the intermediate CA1 (iCA1) subregion of the hippocampus, but not the medial prefrontal cortex or iCA1-medial prefrontal cortex connections. Our data identify hippocampal subregion specialization in the successful assessment of OiP recognition memory in mice, expanding our understanding of the neural basis of spatial memory processing. Significance Statement Associations between the identity and location of spatial elements (what-where associations), underlie essential behaviours such as finding food, locating shelter and safely navigating the environment. Deficits in identity-location processing occur in patients with neurodevelopmental and neurodegenerative disorders, and are replicated in rodent models using object-in-place (OiP) recognition tasks. While mice have emerged as a widely used animal model to study the biological mechanisms underlying these disorders, nothing is known about the neural substrates of OiP memory in mice. Here we have established and validated a robust experimental paradigm to assess OiP memory in mice, uncovering a specialized contribution of the hippocampal subregion intermediate CA1 to OiP performance and deepening our understanding of the neural signatures of spatial memory processing.
Visible and infrared images fusion for object detection: a survey

Object detection is a fundamental task in computer vision that has garnered significant attention and made remarkable strides in recent times. Most object detection tasks are designed only for visible images, but the fusion between visible and infrared images can play a complementary role in information so that object detection can play a better effect in low light, bad weather, and drone shooting environment. Although some progress has been made in visual and infrared image fusion object detection, and a series of algorithms have been proposed, there is no article on the comprehensive introduction of RGB-Infrared image fusion object detection. Therefore, we summarize the current status of object detection based on RGB-Infrared fusion and discuss the limitations of current techniques and potential research directions in the future. We hope that this article can help researchers quickly understand the field, then provide certain suggestions and references for relevant scholars.
The additive effects of anaemia and transfusion on long-term survival after coronary artery bypass surgery

Abstract OBJECTIVES To compare the independent and combined effects of anaemia and red blood cell transfusion on late survival after isolated coronary artery bypass grafting. METHODS Retrospective analysis of 5243 consecutive patients undergoing primary isolated coronary artery bypass grafting, performed from 2000 to 2015, in a Portuguese Academic Hospital. We identified 1649 patients with preoperative anaemia (A+) and 1422 patients who received a perioperative transfusion (T+)—the 4 possible combinations allowed for the creation of 4 subgroups (A−/T−, A−/T+, A+/T− and A+/T+). The primary endpoint was all-cause mortality at 10 years. We employed inverse probability weighting to control for confounding variables. RESULTS Thirty-one percent of the patients had preoperative anaemia, and 27.0% had at least one packed red blood cell transfusion. Inverse probability weighting was effective in eliminating differences in all significant baseline characteristics. The primary endpoint of all-cause mortality at 10 years occurred in 568 patients (20.5%) in the A−/T− group, as compared with 204 (24.4%) in the A−/T+ group (hazard ratio, 1.14; 95% confidence interval, 1.00 to 1.31; P = 0.053), 358 (33.8%) in the A+/T− group (hazard ratio, 1.53; 95% confidence interval, 1.38 to 1.71; P < 0.001), 254 (43.6%) in the A+/T+ group (hazard ratio, 2.25; 95% confidence interval, 1.97 to 2.56; P < 0.001). CONCLUSIONS This longitudinal, population-level study emphasizes the adverse long-term outcomes of preoperative anaemia and perioperative red blood cell transfusion. It stresses the importance of an evidence-based, multimodal and multidisciplinary approach to conserving blood resources and optimizing outcomes in patients at high risk for transfusion.
Perspectives on the Emotional Response to Consonance and Dissonance in Music

In music, the tendency for certain combinations of notes to sound either pleasant (i.e., consonant) or unpleasant (i.e., dissonant) seems to be innate, universal, and uniquely human—provoking the question of why these intervals are able to trigger these emotional reactions. Evidence will be reviewed here to explore several aspects of this question: (1) which neural circuits are involved; (2) what acoustic properties lead to emotional reactions; and (3) why these preferences might have evolved. Brain imaging research shows that many emotion-processing areas respond differentially to consonant and dissonant music. In addition, lesion studies have found specialized neural circuitry involved in emotional responses to music. Studies of people with amusia, a pitch processing disorder, have identified the acoustic properties that determine a sound’s pleasantness—specifically, the harmonic series, rather than beating as previously assumed, distinguishes consonant from dissonant intervals. Consonant intervals are also the ones most prevalent in the harmonics of the human voice. This may explain why humans show a preference for consonant intervals. Abstract
A power substation monitoring system based on artificial intelligence

In order to solve the problems of difficult safety control and low intelligence level in substation maintenance operation, a substation monitoring system based on artificial intelligence is proposed in this paper, which gives early warning and supervision to the safety protection of substation maintenance operators and the safety production of construction behavior. On the one hand, the paper builds the image sample library by collecting employee image information and capturing personnel images through monitoring equipment such as intelligent camera; On the other hand, HOG algorithm, CNN and image processing algorithm are used to build the operation and maintenance detection model. By exporting the personnel images to the face recognition model, safety helmet intelligent detection model and personnel clothing intelligent detection model for detection, the accuracy of the system is improved, and then the monitoring of personnel entering and leaving the substation is realized, and the information and intelligent level of substation safety control is effectively improved.
A new filled function for constrained global optimization

This article introduces a solitary adjustable parameter-based filled function technique tailored for constrained global optimization. The devised filled function strives to encapsulate the idiosyncrasies inherent in the optimization quandary, and the single parameter can be easily tuned during the optimization process. The paper explores the analytical characters of the filled function and presents an algorithm based on the filled function approach. Finally, numerical tests are implemented to demonstrate the effectiveness of the proposed filled function method.