Miracle-dz/UniFAR-FTUs huggingface dataset:
Paraguayan Guarani: Tritonal pitch accent and Accentual Phrase

This paper investigates the intonation system of Paraguayan Guarani in the Autosegmental-metrical (AM) framework of intonational phonology. Previous work on Guarani intonation stated that Guarani has two types of pitch accent, rising (L*+H or LH) and falling (H+L* or HL), and there is no prosodic unit between a word and an Intonational Phrase. But these findings seem to have resulted from the limitation of the data examined. When longer words/sentences and various syntactic structures are examined, it was found that Guarani has one type of pitch accent, a tritonal HLH*, and has an Accentual Phrase (AP). The tonal pattern of AP is /H HLH* Ha/, i.e., it has one pitch accent and its edges are marked by a H tone. However, because the pitch accent is tritonal, AP edge tones are realized only when there are unstressed syllables before and after the syllables carrying the tritonal pitch accent, suggesting that the function of AP boundary tone is not marking word prominence as in other AP languages. Instead, an important function of Guarani AP seems to mark specific syntactic categories and groupings. These findings are compared with other AP languages and discussed in terms of the typology of word-prominence type.
Functional Interactions of Kluyveromyces lactis Telomerase Reverse Transcriptase with the Three-Way Junction and the Template Domains of Telomerase RNA

The ribonucleoprotein telomerase contains two essential components: telomerase RNA (TER) and telomerase reverse transcriptase (TERT, Est2 in yeast). A small portion of TER, termed the template, is copied by TERT onto the chromosome ends, thus compensating for sequence loss due to incomplete DNA replication and nuclease action. Although telomerase RNA is highly divergent in sequence and length across fungi and mammals, structural motifs essential for telomerase function are conserved. Here, we show that Est2 from the budding yeast Kluyveromyces lactis (klEst2) binds specifically to an essential three-way junction (TWJ) structure in K. lactis TER, which shares a conserved structure and sequence features with the essential CR4-CR5 domain of vertebrate telomerase RNA. klEst2 also binds specifically to the template domain, independently and mutually exclusive of its interaction with TWJ. Furthermore, we present the high-resolution structure of the klEst2 telomerase RNA-binding domain (klTRBD). Mutations introduced in vivo in klTRBD based on the solved structure or in TWJ based on its predicted RNA structure caused severe telomere shortening. These results demonstrate the conservation and importance of these domains and the multiple protein–RNA interactions between Est2 and TER for telomerase function.
Impact of Environmental Information Disclosure Policy and Trade on Chinese Paper Industry Environmental Effects

While participation in the international division of labor has led to rapid economic development, it has also resulted in pressing environmental issues in China. In the context of “building a resource-saving and environment-friendly society” and the current sustainability requirements, research on the environmental impact of Chinese paper companies from the perspective of Environmental Information Disclosure (EID) policy and trade has not yet reached a consensus. This study constructs an analytical framework for the EID policy impact mechanism and trade on the environmental effects of the paper industry and enterprises. It explores the direct and indirect effects of EID policy and import-and-export trade on the paper industry environmental effects using the Propensity Score Matching and Difference-in-Differences (PSM-DID) model. EID positively impacts the pollution reduction of enterprises mainly through the technical effect. Export trade positively impacts the reduction of enterprises’ emissions through the technology effect. However, the demand of the international market increases the pollution from the paper industries, which has a negative impact. Importing will enable enterprises to obtain greater price advantages which can alleviate and transfer the costs brought by EID. This study analyzes the impact of trade on the environmental effects of Chinese paper enterprises and identifies the impact of China’s EID policy and trade on enterprises’ pollution emissions. It provides a theoretical and practical foundation for the Chinese government to formulate environmental and trade policies.
Asymptotic Solution for Dam-Break Problem

The kinematic wave approximation is used to obtain a simple, closed-form solution for the catastrophic failure of a dam upon a dry, sloping channel. The solution validity is investigated by computing orders of magnitude for neglected terms in the equations of motion and by comparing the solution with the results of previously calculated numerical solutions and with experimental results. These calculations and comparisons suggest that the kinematic wave solution becomes asymptotically valid after the flood wave has advanced about four reservoir lengths downstream.
Harmonized Chlorophyll-a Retrievals in Inland Lakes From Landsat-8/9 and Sentinel 2A/B Virtual Constellation Through Machine Learning

Moderate-high-resolution satellite missions provide an opportunity to capture subtle spatial variability in lakes; however, the sparsity of time series for individual satellite instruments cannot monitor temporal variation in the lake environment. To date, studies on the joint observations of chlorophyll-a (Chl-a) in inland lakes from multiple missions have been poorly reported. Here, we generated a harmonized Chl-a dataset for the lakes in the Yunnan–Guizhou Plateau in China from 2013 to 2022 by the Landsat 8/9 (L8/L9) and Sentinel-2A/B (S2A/S2B) virtual constellation. This study first examined the performance of four atmospheric correction processors to derive the remote sensing reflectance (<inline-formula> <tex-math notation="LaTeX">$R_{\mathrm {rs}})$ </tex-math></inline-formula> from L8/L9 Operational Land Imager (OLI) and S2A/S2B multispectral instrument (MSI) images. We determined that the dark spectral fitting algorithm generated better <inline-formula> <tex-math notation="LaTeX">$R_{\mathrm {rs}}$ </tex-math></inline-formula> than the other processors, e.g., <inline-formula> <tex-math notation="LaTeX">$R_{\mathrm {rs}}$ </tex-math></inline-formula>(561) mean absolute percentage error (MAPE) = 15.2%, <inline-formula> <tex-math notation="LaTeX">$R_{\mathrm {rs}}$ </tex-math></inline-formula>(665) MAPE = 27.5%, and <inline-formula> <tex-math notation="LaTeX">$R_{\mathrm {rs}}$ </tex-math></inline-formula>(704) MAPE = 25.7%. OLI-derived <inline-formula> <tex-math notation="LaTeX">$R_{\mathrm {rs}}$ </tex-math></inline-formula> at five visible and near-infrared bands showed satisfactory agreement with MSI (slope = 0.94 and MAPE = 11.8%). The mixed density network outperformed the six state-of-the-art algorithms and other two machine learning models in retrieving Chl-a [MSI: MAPE = 31.4% (<inline-formula> <tex-math notation="LaTeX">$N $ </tex-math></inline-formula> = 109) and OLI: MAPE = 38.0% (<inline-formula> <tex-math notation="LaTeX">$N $ </tex-math></inline-formula> = 74)]. The satisfactory agreement of Chl-a retrievals between the synchronous MSI and OLI images (<inline-formula> <tex-math notation="LaTeX">$N $ </tex-math></inline-formula> = 2 293 821 and MAPE = 34.6%) supported the establishment of the virtual constellation. MSI- and OLI-derived Chl-a in nine major lakes in the studied area exhibited apparent seasonal variability from 2013 to 2022, particularly after 2017. Results highlight a solution to establish the Landsat/Sentinel-2 virtual constellation for improving the spatial and temporal resolutions of a database of lake water quality.
Rules of interpretation – qualitative research in tourism by incorporating legal science canons

ABSTRACT Achieving rigour is one of the key challenges in qualitative research. Despite a significant amount of triangulation efforts in regards to data, methods, researcher and theory, actual coding aspects do not get the same level of analytical attention. This ‘technical’ triangulation can be improved and made more transparent by incorporating methodology of other disciplines, like legal science. Within the traditional ‘black-letter’ research, at least in continental Europe, the application of canons, especially the ‘Savigny Canons’, has a proven track record of structuring legal interpretation. Such interpretation from a technical perspective shares quite a few similarities with interpretation in qualitative research. Hence, it is proposed to also apply them in qualitative research in tourism, given the interdisciplinary nature of tourism as a field of research.
The hard X-ray burst spectrometer event listing, 1980 - 1985

This event listing is a comprehensive reference for the hard x-ray bursts detected with the Hard x-Ray Burst Spectrometer on the Solar Maximum Mission from the time of launch on February 14, 1980 to September 1985. Over 8000 X-ray events were detected in the energy range from 30 to approx. 500 keV with the vast majority being solar flares. The listing includes the start time, peak time, duration and peak rate of each event.
Self-tuning and the derivation of a class of scalar-tensor theories

We have recently proposed a special class of scalar tensor theories known as the Fab Four. These arose from attempts to analyse the cosmological constant problem within the context of Horndeski's most general scalar tensor theory. The Fab Four together give rise to a model of self-tuning, with the relevant solutions evading Weinberg's no-go theorem by relaxing the condition of Poincare invariance in the scalar sector. The Fab Four are made up of four geometric terms in the action with each term containing a free potential function of the scalar field. In this paper we rigorously derive this model from the general model of Horndeski, proving that the Fab Four represents the only classical scalar tensor theory of this type that has any hope of tackling the cosmological constant problem. We present the full equations of motion for this theory, and give an heuristic argument to suggest that one might be able to keep radiative corrections under control. We also give the Fab Four in terms of the potentials presented in Deffayet et al's version of Horndeski.
Chemopreventive Efficacy of Thymoquinone in Chemically Induced Urinary Bladder Carcinogenesis in Rat

The effects of thymoquinone (TQ) in a carcinogen-based models of urinary bladder cancer were evaluated, using 45 male rats in five groups. In negative control (n = 10), only tap water was given. In positive control (n = 10), the rats received 0.05% N-butyl-N-(4-hydroxybutyl)-nitrosamine (BBN) in drinking water for 9 weeks. In preventive groups with 25 mg/kg (n = 10) and 50 mg/kg (n = 10), oral TQ was concurrently given with 0.05% BBN for 9 weeks and continued for one more week after cessation of BBN. Preventive-treatment group (n = 5) received 50 mg/kg TQ orally for 20 weeks. Five rats from each group were sequentially sacrificed in two phases: the induction phase at 12th week (except the last group) and the rest in postinduction phase at 20th week. The bladders were examined macroscopically for lesion formation, and the masses were submitted for histopathological evaluation. Markers for total oxidant status (TOS), inflammation (nuclear factor kappa B (NF-κB)), and angiogenesis (vascular endothelial growth factor (VEGF)) were also assessed. There was a reduced number of bladder lesions in the TQ groups versus the carcinogen group at both phases. Histopathological findings demonstrated a significant improvement in the abnormal morphological changes in the urothelium of the TQ-treated groups. Thymoquinone exerted a significant antioxidant and anti-inflammatory effect by a decrease in serum level of TOS and NF-κB at week 12 which was maintained low in phase two at week 20. The serum level of VEGF was also alleviated in the induction phase at week 12 and maintained low in postinduction period. In TQ preventive-treatment approach, a nonsignificant elevation of serum level of TOS and NF-κB and slight reduction in VEGF were observed at the end of the experiment. These data suggest that TQ may be effective in preventing bladder carcinogenesis, and the suggested mechanisms might be related to antioxidant, prooxidant, and anti-inflammatory properties of TQ.
Influencers As Endorsers and Followers As Consumers: Exploring the Role of Parasocial Relationship, Congruence, and Followers’ Identifications on Consumer–Brand Engagement

Abstract Given the benefits and effectiveness of consumer online brand engagement, influencer advertising and marketing have become increasingly popular on social media. Consumer online brand engagement, including consuming, contributing, and creating brand-related content, is closely related to a brand’s reputation and image. This study determines how the two aspects related to influencer endorsement—namely, influencer–follower parasocial interaction (PSI) and influencer–brand congruence (congruence)—affect the three levels of consumer online brand-related activities (COBRAs) on Sina Weibo. We also examined the mediation effect of consumers’ personal identification (PI) and social identification (SI) with brands in this process. The data were collected from 390 Weibo users in China, and valid data were analyzed using structural equation modeling (SEM). The results show that PSI and congruence have a direct positive effect on consuming brand-related content; PSI has an indirect influence on contributing brand-related content through SI’s mediation effect; and both PSI and congruence contributed to creating brand-related content, with the mediating effect of PI and SI. This study extends the literature on the motivation of consumer–brand engagement (engagement) on social media and discusses the roles of PI and SI in influencer marketing, filling a gap in the research and bringing new perspectives for brands and corporates.
Representing functional data in reproducing Kernel Hilbert Spaces with applications to clustering and classification

Functional data are difficult to manage for many traditional statistical techniques given their very high (or intrinsically infinite) dimensionality. The reason is that functional data are essentially functions and most algorithms are designed to work with (low) finite-dimensional vectors. Within this context we propose techniques to obtain finitedimensional representations of functional data. The key idea is to consider each functional curve as a point in a general function space and then project these points onto a Reproducing Kernel Hilbert Space with the aid of Regularization theory. In this work we describe the projection method, analyze its theoretical properties and propose a model selection procedure to select appropriate Reproducing Kernel Hilbert spaces to project the functional data.
Endovascular Abdominal Aortic Aneurysm Repair: Overview of Current Guidance, Strategies, and New Technologies, Perspectives from the United Kingdom

Endovascular aortic aneurysm repair has changed the management of patients affected by this condition, offering a minimally invasive solution with satisfactory outcomes. Constant evolution of this technology has expanded the use of endovascular devices to more complex cases. The purpose of this review article is to describe the current strategies, guidance, and technologies in this field, with a particular focus on practices in the United Kingdom.
Entrainment in trouble: cool cloud acceleration and destruction in hot supernova-driven galactic winds

Efficient thermalization of overlapping supernovae within star-forming galaxies may produce a supernova-heated fluid that drives galactic winds. For fiducial assumptions about the timescale for cloud shredding from high-resolution simulations (which neglect magnetic fields) we show that cool clouds with temperature from $T_{c}\sim 10^{2}-10^{4}$ K seen in emission and absorption in galactic winds cannot be accelerated to observed velocities by the ram pressure of a hot wind. Taking into account both the radial structure of the hot flow and gravity, we show that this conclusion holds over a wide range of galaxy, cloud, and hot wind properties. This finding calls into question the prevailing picture whereby the cool atomic gas seen in galactic winds is entrained and accelerated by the hot flow. Given these difficulties with ram pressure acceleration, we discuss alternative models for the origin of high velocity cool gas outflows. Another possibility is that magnetic fields in cool clouds are sufficiently important that they prolong the cloud's life. For $T_{c}=10^{3}$\,K and $10^{4}$\,K clouds, we show that if conductive evaporation can be neglected, the cloud shredding timescale must be $\sim15$ and 5 times longer, respectively, than the values from hydrodynamical simulations in order for cool cloud velocities to reach those seen in observations.
Fully Automatic Balance between Directivity Factor and White Noise Gain for Large-scale Microphone Arrays in Diffuse Noise Fields

In diffuse noise ﬁelds, a superdirective beamformer maximizes the directivity factor at the expense of amplifying spatially white noise in low-frequency bands. It is extremely important to balance directivity factor and white noise gain automatically for practical applications, especially when using large-scale microphone arrays. Considering both environmental noise and spatially white noise, this paper proposes two robust adaptive superdirective beamformers that aim to automatically maximize the amount of noise reduction without introducing a constraint on the white noise gain manually. Speciﬁcally, one is an adaptive combination of the delay-and-sum and superdirective beamformers, and the other can be regarded as an adaptively regularized superdirective beamformer. We derive that both the optimal combination parameter and the optimal regularization parameter in each time-frequency bin are related to the power spectral density of the spatially white noise and that of the diffuse noise. Simulations and experimental results show that the proposed two robust beamformers are superior to many state-of-the-art beamformers in different environmental noise and spatially white noise levels.
The Cost of Recidivism: A Dynamic Systems Model to Evaluate the Benefits of a Restorative Reentry Program

Abstract Hawai‘i Friends of Restorative Justice has developed and implemented a reentry planning process to support incarcerated individuals as they prepare to reenter society. With 16 years of successful practice, research has shown that the program has many benefits, including reducing recidivism by 26 percent among recipients. In this paper, we use systems analysis to explore the long-term effects of a reduction in recidivism on the prison population and evaluate the economic and social benefits of such a program. The paper describes a simulation modeling method that quantifies the predicted effect of recidivism on the prison population, shows the net benefit of the reentry program, and demonstrates the usefulness of modern simulation tools in policy analysis of the criminal justice system. We calibrate the model with data on Hawai‘i state prisons. The model indicates that a 26 percent reduction in recidivism leads to a 17 percent reduction in the prison population over 15 years by reducing the number of recidivists in prison by 40 percent. Considering the marginal and average cost of imprisonment, the estimated benefits substantially outweigh the cost of the program with even the most conservative accounting of marginal costs.
Using Data Augmentation and Consistency Regularization to Improve Semi-supervised Speech Recognition

State-of-the-art automatic speech recognition (ASR) networks use attention mechanism and optimize transducer loss on labeled acoustic data. Recently, Semi-Supervised Learning (SSL) techniques that leverage large amount of unlabeled data have become an active area of interest to improve the performance of ASR networks. In this paper we approach SSL based on the framework of consistency regularization, where data augmentation transforms are used to make ASR network predictions in-variant to perturbations in the acoustic data. To increase data diversity we present a combination technique that randomly fuses multiple waveform and feature transforms. For each unlabeled acoustic waveform, two versions, i.e., a weakly augmented and a strongly augmented version of the unaugmented input are generated. During training, a semi-supervised loss is assigned that enforces consistent outputs between the weak and strong augmentations of the unlabeled input. Moreover, we employ model averaging technique to generate stable outputs over time. We compare and demonstrate the beneﬁts of the proposed approach against standard SSL strategies like iterative self-labeling. We leverage over 100000 hours of unlabeled data to train the ASR network using streaming transducer loss and reach improvements in the range of 8% - 12% over self-labeling baseline.
Lightweight frequency-based attention network for image super-resolution

Abstract. The advent of convolutional neural networks has been driving the rapid development of image super-resolution (SR) tasks. Existing works, however, tend to devise deeper and wider networks to boost accuracy, leading to huge model sizes and computation costs. In addition, they also ignore the effect of frequency domain information on image restoration. To address these challenges, we propose a simple and effective frequency-based attention network, comprising a series of frequency-domain enhancement modules (FDEMs), for accurate image SR. Each FDEM integrates a two-dimensional discrete wavelet transform, progressive frequency enhancement module (PFEM), and frequency aggregation module (FAM). Specifically, DWT first decomposes the features into high-frequency and low-frequency parts, and then the low-frequency branch is processed and gradually added to the high-frequency branch to realize the interaction of frequency information in PFEM. Finally, frequency representations from the PFEM are upsampled to the FAM to further achieve information enhancement in a specific space. Extensive experiments indicate that our method is efficient in reconstruction accuracy with less model capacity, exceeding most existing lightweight SR networks.