Miracle-dz/UniFAR-FTUs huggingface dataset:
Beyond the Status Quo: A Contemporary Survey of Advances and Challenges in Audio Captioning

Automated audio captioning (AAC), a task that mimics human perception as well as innovatively links audio processing and natural language processing, has overseen much progress over the last few years. AAC requires recognizing contents such as the environment, sound events and the temporal relationships between sound events and describing these elements with a fluent sentence. Currently, an encoder-decoder-based deep learning framework is the standard approach to tackle this problem. Plenty of works have proposed novel network architectures and training schemes, including extra guidance, reinforcement learning, audio-text self-supervised learning and diverse or controllable captioning. Effective data augmentation techniques, especially based on large language models are explored. Benchmark datasets and AAC-oriented evaluation metrics also accelerate the improvement of this field. This article situates itself as a comprehensive survey covering the comparison between AAC and its related tasks, the existing deep learning techniques, datasets, and the evaluation metrics in AAC, with insights provided to guide potential future research directions.
The Assessment Of A Hybrid On Line/In Class Course Developed At Multiple Universities

In Fall 2007, a coalition of four universities was awarded an NSF CCLI grant to support the development of a curriculum with the goal of cultivating systems thinking in students. Systems thinking, as defined in this project, is the ability to envision architectures of complexengineered systems and the principles that underlie them. The effort, deemed MUSE – MultiUniversity Systems Education – has developed a unique course to instill such systems skills. This undergraduate course, Wireless Sensor Network Design, not only introduces students to a timely technology but utilizes this topic to bring together material from a variety of subject matters that students had heretofore studied in isolation. To develop the course, faculty at each institution contributed online modules in topics of their expertise but with the material refocused to emphasize relevance to sensor networks and interaction with other electrical engineering subdisciplines. These modules were created utilizing Tablet PCs and Camtasia Studio screen recording software. In Fall 2008, the course was piloted at Northern Arizona University. A hybrid lecturing approach was employed where students interacted with online content the equivalent one lecture per week and then discussed the material in-class, once a week. In this paper, assessment results of the initial course offering are reported in three areas. First, students evaluated the content delivery method along with the course content quality and engagement. Second, students were evaluated preand post-course with a systems-oriented task to evaluate whether holistic skills were being developed. Finally, the course developers were evaluated on the collaborative aspects of the project along with the approach for creating content.
Sibylvariant Transformations for Robust Text Classification

The vast majority of text transformation techniques in NLP are inherently limited in their ability to expand input space coverage due to an implicit constraint to preserve the original class label. In this work, we propose the notion of sibylvariance (SIB) to describe the broader set of transforms that relax the label-preserving constraint, knowably vary the expected class, and lead to significantly more diverse input distributions. We offer a unified framework to organize all data transformations, including two types of SIB: (1) Transmutations convert one discrete kind into another, (2) Mixture Mutations blend two or more classes together. To explore the role of sibylvariance within NLP, we implemented 41 text transformations, including several novel techniques like Concept2Sentence and SentMix. Sibylvariance also enables a unique form of adaptive training that generates new input mixtures for the most confused class pairs, challenging the learner to differentiate with greater nuance. Our experiments on six benchmark datasets strongly support the efficacy of sibylvariance for generalization performance, defect detection, and adversarial robustness.
A peculiar, long-duration gamma-ray burst from a neutron star-white dwarf merger

1School of Astronomy and Space Science, Nanjing University, Nanjing 210093, China 2Key Laboratory of Modern Astronomy and Astrophysics (Nanjing University), Ministry of Education, China 3Nevada Center for Astrophysics, University of Nevada Las Vegas, NV 89154, USA 4Department of Physics and Astronomy, University of Nevada Las Vegas, NV 89154, USA 5School of Physics, Nanjing University, Nanjing 210093, China 6Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China 7Guangxi Key Laboratory for Relativistic Astrophysics, School of Physical Science and Technology, Guangxi University, Nanning 530004, China
Cosmology with X-RAY galaxy cluster surveys ?

This talk reviews the scientific motivations, the potential difficulty and recent advances in cosmology using cluster number-counts in the X-ray band. Our forward modelling approach shows that many of the practical and conceptual shortcomings can now be overcome. We present recent results from the XMM-XXL survey. The next step is to apply artificial intelligence techniques on simulations. This allows us to bypass the unnecessarily complicated scaling relation formalism. The net gain is to significantly reduce the number of free parameters and to provide direct access both to the cosmological parameters and to truly physical ingredients, such as AGN feedback. In this way, we achieve cluster cosmology without explicit cluster mass calculation.
A new approach for the fractional Laplacian via deep neural networks

The fractional Laplacian has been strongly studied during past decades, see e.g. [9]. In this paper we present a diﬀerent approach for the associated Dirichlet problem, using recent deep learning techniques. In fact, recently certain parabolic PDEs with a stochastic representation have been understood via neural networks, overcoming the so-called curse of dimensionality . Among these equations one can ﬁnd parabolic ones in R d , see [20], and elliptic in a bounded domain D ⊂ R d , see [15]. In this paper we consider the Dirichlet problem for the fractional Laplacian with exponent α ∈ (1 , 2). We show that its solution, represented in a stochastic fashion by [22], can be approximated using deep neural networks. We also check that this approximation does not suﬀer from the curse of dimensionality. The spirit of our proof follows the ideas in [15], with important variations due to the nonlocal nature of the fractional Laplacian; in particular, the stochastic representation is given by an α -stable isotropic L´evy process, and not given by a standard Brownian motion.
Reconnecting the Estranged Relationships: Optimizing the Influence Propagation in Evolving Networks

Influence Maximization (IM), which aims to select a set of users from a social network to maximize the expected number of influenced users, has recently received significant attention for mass communication and commercial marketing. Existing research ef-forts dedicated to the IM problem depend on a strong assumption: the selected seed users are willing to spread the information after receiving benefits from a company or organization. In reality, how-ever, some seed users may be reluctant to spread the information, or need to be paid higher to be motivated. Furthermore, the existing IM works pay little attention to capture user’s influence propagation in the future period. In this paper, we target a new research problem, named Reconnecting Top- 𝑙 Relationships (RT 𝑙 R) query, which aims to find 𝑙 number of previous existing relationships but being estranged later, such that reconnecting these relationships will maximize the expected number of influenced users by the given group in a future period. We prove that the RT 𝑙 R problem is NP-hard. An efficient greedy algorithm is proposed to answer the RT 𝑙 R queries with the influence estimation technique and the well-chosen link prediction method to predict the near future network structure. We also design a pruning method to reduce unnecessary probing from candidate edges. Further, a carefully designed order-based algorithm is proposed to accelerate the RT 𝑙 R queries. Finally, we conduct extensive experiments on real-world datasets to demonstrate the effectiveness and efficiency of our proposed methods.
Mean Curvature and the Wave Invariants of the Basic Spectrum for a Riemannian Foliation

Given a (possibly singular) Riemannian foliation F with closed leaves on a compact manifold M with an adapted metric, we investigate the wave trace invariants for the basic Laplacian about a non-zero period. We compare them to the wave invariants of the underlying Riemannian orbifold that exists when the leaves in the regular region are identiﬁed to points, equipped with the metric that is transverse to the leaves of the foliation. Recalling that the basic Laplacian diﬀers from the underlying orbifold Laplacian by a term that is the mean curvature vector ﬁeld associated to the foliation, we show that the ﬁrst wave invariant about any non-zero period T corresponding to geodesics perpendicular to the leaves that all lie entirely in the regular region of M is independent of the mean curvature vector ﬁeld and depends only on the underlying orbifold structure of the leaf space quotient. Similar results hold on the singular strata whenever the transverse geodesic ﬂow remains conﬁned to the strata deﬁned by the leaf dimension of the foliation. Conversely, closed geodesics that pass through the exceptional leaves depend on the full laplacian, including the leafwise metric on the ambient space.We also discuss families of representations that yield the same leaf space and basic spectrum. We use this to give conditions under which non-trivial isotropy for orbifold quotients can be detected.
Externally Valid Treatment Choice

We consider the problem of learning treatment (or policy) rules that are externally valid in the sense that they have welfare guarantees in target populations that are similar to, but possibly diﬀerent from, the experimental population. We allow for shifts in both the distribution of potential outcomes and covariates between the experimental and target populations. This paper makes two main contributions. First, we provide a formal sense in which policies that maximize social welfare in the experimental population remain optimal for the “worst-case” social welfare when the distribution of potential outcomes (but not covariates) shifts. Hence, policy learning methods that have good regret guarantees in the experimental population, such as empirical welfare maximization, are externally valid with respect to a class of shifts in potential outcomes. Second, we develop methods for policy learning that are robust to shifts in the joint distribution of potential outcomes and covariates. Our methods may be used with experimental or observational data.
Diversity Stalled: Explorations into the Stagnant Numbers of African American Engineering Faculty

Ebony O. McGee is an Assistant Professor of Diversity and Urban Schooling at Vanderbilt University’s Peabody College and a member of Scientific Careers Research and Development Group at Northwestern University. She received her Ph.D. in Mathematics Education from the University of Illinois at Chicago; and she was a National Academy of Education/Spencer Foundation Postdoctoral Fellow and a National Science Foundation Postdoctoral Fellow. As a former electrical engineer, she is concerned with science, technology, engineering, and mathematics (STEM) learning and participation among historically marginalized students of color. Her research focuses on the role of racialized experiences and biases in STEM educational and career attainment, problematizing traditional notions of academic achievement and what is mean to be successful yet marginalized, and STEM identity and identity development in high-achieving students of color. She is currently the PI on two studies funded by NSF, the first of which investigates the causes behind why African Americans remain one of the most underrepresented racial groups in engineering faculty positions. The second study is working toward the design of a holistic racial and gender attentive mentoring program for engineering PhD students of color.
Fatigue Analysis of a Fire Truck Drop Tow Hitch for an O1 Category Water Pump Trailer

This paper presents static and fatigue analyses of a fire truck drop tow hitch for an O1 category water pump trailer. In total 4 geometry variants with different features have been analyzed using the FEM. The loading forces have been calculated based on two different weights: the weight of the water pump trailer (the only trailer meant to be towed by the fire truck) and the category O1 gross trailer weight. Two different calculation methods were used: a calculation method recommended by the standard and a calculation method based on the physical breaking tests performed on the fire truck. The results of the performed analyses show the structural differences of the 4 geometry variants. The additional stiffening elements added to the base design have decreased the maximum deformation values, but the maximum stress and strain values have been raised especially in areas where stress concentrators are present.
Striatal mechanism of the restless legs syndrome.

STUDY OBJECTIVES Brain iron deficiency has been reported to be associated with the restless legs syndrome (RLS). However, 30%-50% of RLS patients do not respond to iron therapy, indicating that mechanisms other than brain iron deficiency may also participate in this disease. The striatum is known to be involved in the modulation of motor activity. We speculated that dysfunction of the striatum may induce RLS. METHODS Two groups, wild-type (WT) and iron-deficient (ID) rats were used. Each group was divided into 2 subgroups, control and N-methyl-D-aspartate striatal-lesioned. After baseline recording, striatal-lesioned wild-type (WT-STL) and striatal-lesioned iron-deficient (ID-STL) rats were given pramipexole and thioperamide injections. Iron-deficient and ID-STL rats were then given a standard rodent diet for 4 weeks, and their sleep and motor activity were recorded. RESULTS WT-STL rats showed periodic leg movements (PLM) in wake, an increase in PLM in slow wave sleep (SWS), a decrease in rapid-eye-movement sleep, and a decrease in the daily average duration of episodes in SWS. The sleep-wake pattern and motor activity did not differ between ID and ID-STL rats. Thioperamide or pramipexole injection decreased PLM in sleep and in wake in WT-STL rats and ID-STL rats. Unlike ID rats, whose motor hyperactivity can be reversed by iron replacement, PLM in wake and in sleep in ID-STL rats were not fully corrected by iron treatment. CONCLUSIONS Lesions of the striatum generate RLS-like activity in rats. Dysfunction of the striatum may be responsible for failure to respond to iron treatment in some human RLS patients.
Possible bidirectional human–swine and subsequent human–human transmission of influenza virus A(H1N1)/2009 in Japan

In 2019, sows at a swine farm in Japan showed influenza‐like illness (ILI) shortly after contact with an employee that exhibited ILI. Subsequently, a veterinarian became sick shortly after examining the sows and was diagnosed with influenza A virus (IAV) infection. Then, her family also contracted the infection. Subsequently, Pandemic A(H1N1)2009 viruses were isolated from all samples obtained from the sows, veterinarian and her family. Whole‐genome analysis of the isolates confirmed that the viruses belonged to the same lineage (6B.1A) and the genome sequences obtained from all of the isolates were almost identical to each other. Furthermore, an epidemiological survey revealed no contact between veterinarians or their families and influenza patients prior to the onset of illness. These results strongly indicated a case of bidirectional infection between humans and sows. At the same time, we found a few unique mutations in the IAV genomes corresponding to the host species. The mutations that occurred in the virus after it was transferred from the farm worker to the sows were not observed in the humans infected from the sows, probably as a result of the mutations reverting to the original nucleotides. These results demonstrate that the bidirectional transmission of IAV is a potential risk for the next pandemic outbreak due to the emergence of new mutant strains.
The effect of crisping, misting, and storage temperature on the survival or growth of Listeria monocytogenes and natural psychrotrophic bacteria on romaine lettuce

L. monocytogenes has been linked to fresh produce and detected in the retail environment. This study simulated the retail practices (crisping, misting, and storage) of unbagged whole heads of romaine lettuce to determine the growth of L. monocytogenes and natural psychrotrophic microflora. Three nalidixic acid-resistant strains of L. monocytogenes strains were inoculated to each head of lettuce (≈5 log10 CFU/g). For crisping, 24 heads of romaine lettuce were immersed in tap water or electrolyzed water (EW; free chlorine: 55 ppm) for 5 min, followed by holding at 5 °C for 2 h. The water-crisped (WC), EW crisped (EWC), or non-crisped (NC) lettuces were placed in a commercial refrigerated cabinet for misting at 5 °C. After 24-h misting, heads of lettuce were placed in perforated drain boxes with cover at 5 °C or 15 °C. The tap water and EW crisping achieved 1.3 and 2.9 log10 CFU/g reduction of L. monocytogenes, respectively. Approximately 1 log additional reduction of L. monocytogenes in the non-crisped lettuce was shown after misting (p < 0.05), but no significant effect of misting on the population of L. monocytogenes was observed on WC or EWC lettuces (p > 0.05). Regardless of the storage temperature or misting, L. monocytogenes populations remained significantly (p < 0.05) lower on EWC lettuce than NC and WC lettuce. On days 4 and 7 of storage, the natural psychrotrophic bacteria on lettuce stored at 5 °C was significantly lower than stored at 15 °C, and its population was not affected by crisping and misting. These provide insight into the influence of retail lettuce handling practices on the risk of L. monocytogenes.
Associations of perceived stress, depressive symptoms, and caregiving with inflammation: a longitudinal study

ABSTRACT Objectives: Higher inflammation has been linked to poor physical and mental health outcomes, and mortality, but few studies have rigorously examined whether changes in perceived stress and depressive symptoms are associated with increased inflammation within family caregivers and non-caregivers in a longitudinal design. Design: Longitudinal Study. Setting: REasons for Geographic And Racial Differences in Stroke cohort study. Participants: Participants included 239 individuals who were not caregivers at baseline but transitioned to providing substantial and sustained caregiving over time. They were initially matched to 241 non-caregiver comparisons on age, sex, race, education, marital status, self-rated health, and history of cardiovascular disease. Blood was drawn at baseline and approximately 9.3 years at follow-up for both groups. Measurements: Perceived Stress Scale, Center for Epidemiological Studies-Depression, inflammatory biomarkers, including high-sensitivity C-reactive protein, D dimer, tumor necrosis factor alpha receptor 1, interleukin (IL)-2, IL-6, and IL-10 taken at baseline and follow-up. Results: Although at follow-up, caregivers showed significantly greater worsening in perceived stress and depressive symptoms compared to non-caregivers, there were few significant associations between depressive symptoms or perceived stress on inflammation for either group. Inflammation, however, was associated with multiple demographic and health variables, including age, race, obesity, and use of medications for hypertension and diabetes for caregivers and non-caregivers. Conclusions: These findings illustrate the complexity of studying the associations between stress, depressive symptoms, and inflammation in older adults, where these associations may depend on demographic, disease, and medication effects. Future studies should examine whether resilience factors may prevent increased inflammation in older caregivers.
Students’ Experiences and Perceptions of the Scientific Research Culture after Participating in Different Course-Based Undergraduate Research Experience Models

Undergraduate students interact with the culture of scientific research when they participate in direct mentorship experiences and laboratory courses such as course-based undergraduate research experiences (CUREs). Much work has been done to explore how CUREs impact the interest, motivation, and retention of undergraduate students in science. However, little work has been done exploring students’ experiences and perceptions of the culture of scientific research in the CURE context, and how different CURE models representing different subfields of science impact these experiences and perceptions. This study explored which cultural aspects of scientific research students experienced after participating in a CURE and whether their perceptions of those cultural aspects differed based on students’ participation in a bench-based or computer-based research project. Students discussed the Practices and Norms/Expectations of scientific research most frequently. Students in the bench-based and computer-based project areas mentioned different cultural aspects as important to their experiences. Bench-based and computational students also had different perceptions of some of the same cultural aspects, including Teamwork, Freedom & Independence, and Persistence & Resilience. These results suggest that different CURE models differentially impact students’ experiences and perceptions of the culture of scientific research, which has implications for examining how students move into scientific research.
The relationship between toluene diisocyanate exposure and respiratory health problems: A meta-analysis of epidemiological studies

Human epidemiological studies have shown inconclusive results over the effects of diisocyanates on respiratory health problems. A meta-analysis combined evidence on the association between occupational asthma (OA), respiratory function, and toluene diisocyanate (TDI) inhalation exposure. Sixty-one articles on occupational toluene diisocyanate exposure were identified via two databases. Fourteen studies were included in the meta-analysis. The Newcastle-Ottawa Scale (NOS) was used to assess the quality of the studies. Odds ratios (ORasthma) for the association between TDI exposure compared to non-exposure and OA were calculated. The difference in mean differences (MD) of forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC), and the annual mean change differences—in milliliters per year (mL/yr)—in FEV1 and FVC pulmonary function between TDI exposed and non-exposed, were calculated. When applicable, a random effects meta-analysis was performed. The overall summary ORasthma for TDI exposed versus non-exposed was 1.18 (95% CI = 0.78–1.79). The summary of the predicted mean percentage difference (MD%predicted) between exposed versus non-exposed was 2.96% for FEV1 and 3.75% for FVC. A very small decrease of 5 mL/yr for FEV1 and 10 mL/yr for FVC, respectively, was observed between the exposed and the non-exposed groups. There was moderate to low heterogeneity between study results, and most studies were evaluated as high-quality. This meta-analysis found no statistically significant adverse association between TDI occupational exposure and OA. No meaningful differences in lung function were detected between exposed and unexposed groups.