Miracle-dz/UniFAR-FTUs huggingface dataset:
A mixed‐source model for speech compression and synthesis

This paper presents an excitation source model for speech compression and synthesis that allows the degree of voicing to be varied continuously by mixing voiced (pulse) and unvoiced (noise) excitations in a frequency‐selective manner. The mix is achieved by dividing the speech spectrum into two regions, with the pulse source exciting the low‐frequency region and the noise source exciting the high‐frequency region. The degree of voicing is specified by a parameter Fc, which corresponds to the cut‐off frequency between the voiced and unvoiced regions. For speech compression applications, Fc can be extracted automatically from the speech spectrum and transmitted. Experiments performed with the new model indicate its power in synthesizing natural sounding voiced fricatives and in largely eliminating the ’’buzzy’’ quality of vocoded speech. A functional definition of buzziness and naturalness is given in terms of the model.
Asymptotic Chow polystability in K\"ahler geometry

It is conjectured that the existence of constant scalar curvature K\"ahler metrics will be equivalent to K-stability, or K-polystability depending on terminology (Yau-Tian-Donaldson conjecture). There is another GIT stability condition, called the asymptotic Chow polystability. This condition implies the existence of balanced metrics for polarized manifolds $(M, L^k)$ for all large $k$. It is expected that the balanced metrics converge to a constant scalar curvature metric as $k$ tends to infinity under further suitable stability conditions. In this survey article I will report on recent results saying that the asymptotic Chow polystability does not hold for certain constant scalar curvature K\"ahler manifolds. We also compare a paper of Ono with that of Della Vedova and Zuddas.
Radial Dependence of Magnetohydrodynamic Continuum Modes in Axisymmetric Toroidal Geometry

A characteristic feature of modes in the continua (“Alfven” and “slow”) of magnetohydrodynamics (MHD) is their singularity at a magnetic surface ψ=ψ0. For axisymmetric toroidal configurations the dependence of continuum modes on the distance ψ−ψ0 is reexamined. It is found that, in general, the normal component ξψ of the plasma displacement has an oscillatory type of singularity: ξψ∼(ψ−ψ0)σ∼sin(|σ|ln|ψ−ψ0|+const), where σ is an imaginary constant. For special classes of MHD configurations σ vanishes. In this case the previously derived law ξψ∼ln|ψ−ψ0|, [Y. Pao, Nucl. Fusion 15, 631 (1975)] remains valid. Configurations with up/down symmetry pertain to these classes.
Sparsistent and constansistent estimation of the varying-coefficient model with a diverging number of predictors

ABSTRACT The varying-coefficient model is a flexible class of approaches that extends simple linear relationships between covariates and responses. Two related problems concerning these models are selecting relevant variables and determining non-varying coefficients among those relevant ones. In this paper we study the sparsistency and constansistency of the regularized estimation approach when the number of predictors diverges with the sample size. Here, constansistency refers to the desired property that the non-zero, non-varying coefficients are identified with probability tending to one.
Carbohydrate Intake and Closed-Loop Insulin Delivery System during Two Subsequent Pregnancies in Type 1 Diabetes

Carbohydrate intake is one of the main determinants of glycemic control. In pregnancy, achievement of tight glycemic control is of utmost importance; however, data on the role of hybrid closed-loop systems (HCLs) in pregnancy are scarce. Therefore, we aimed to assess glycemic control achieved through the use of HCLs, and its association with carbohydrate intake in type 1 diabetes pregnancy. We included data from women with a sensor-augmented pump (SAP) during their first pregnancy and HCL use during the subsequent pregnancy. Student’s paired t-test was used to compare data between both pregnancies. Six women were identified, with age 30.2 ± 3.6 vs. 33.0 ± 3.6 years, diabetes duration 23 ± 5 vs. 26 ± 5 years, and baseline HbA1c 6.7 ± 0.7% (50.1 ± 7.7 mmol/mol) vs. 6.3 ± 0.6% (45.2 ± 6.5 mmol/moll) in the first and second pregnancies, respectively. Time with glucose in the range 3.5–7.8 mmol/L was 69.1 ± 6.7 vs. 78.6 ± 7.4%, p = 0.045, with the HCLs compared to SAP. Higher meal frequency, but not the amount of carbohydrate consumption, was associated with more time spent in the target range and lower glycemic variability. HCLs and meal frequency were associated with better glycemic control in a small series of pregnant women with type 1 diabetes. Whether this translates to better perinatal outcomes remains to be seen.
The Relationship between Brachionus calyciflorus-Associated Bacterial and Bacterioplankton Communities in a Subtropical Freshwater Lake

Simple Summary This study explored the relationship between Brachionus calyciflorus-associated bacterial and bacterioplankton communities in freshwater. We believe that our study makes a significant contribution because zooplankton and bacterioplankton are the basic components in the aquatic ecosystem, zooplankton has an important role between lower (phyto-, protozooplankton) and higher (fish) trophic levels, and bacteria participate in biogeochemical cycle processes such as nitrogen and carbon cycle, where the symbiotic relationship between them plays an important role in the nutrient cycle, so researching the symbiotic relationship between them will contribute to monitoring the process of environmental change and ecological restoration. Overall, our study expands the current understanding of zooplankton–bacteria interaction and promotes the combination of two different research fields. Abstract Zooplankton bodies are organic-rich micro-environments that support fast bacterial growth. Therefore, the abundance of zooplankton-associated bacteria is much higher than that of free-living bacteria, which has profound effects on the nutrient cycling of freshwater ecosystems. However, a detailed analysis of associated bacteria is still less known, especially the relationship between those bacteria and bacterioplankton. In this study, we analyzed the relationships between Brachionus calyciflorus-associated bacterial and bacterioplankton communities in freshwater using high-throughput sequencing. The results indicated that there were significant differences between the two bacterial communities, with only 29.47% sharing OTUs. The alpha diversity of the bacterioplankton community was significantly higher than that of B. calyciflorus-associated bacteria. PCoA analysis showed that the bacterioplankton community gathered deeply, while the B. calyciflorus-associated bacterial community was far away from the whole bacterioplankton community, and the distribution was relatively discrete. CCA analysis suggested that many environmental factors (T, DO, pH, TP, PO43-, NH4+, and NO3-) regulated the community composition of B. calyciflorus-associated bacteria, but the explanatory degree of variability was only 37.80%. High-throughput sequencing revealed that Raoultella and Delftia in Proteobacteria were the dominant genus in the B. calyciflorus-associated bacterial community, and closely related to the biodegradation function. Moreover, several abundant bacterial members participating in carbon and nitrogen cycles were found in the associated bacterial community by network analysis. Predictive results from FAPROTAX showed that the predominant biogeochemical cycle functions of the B. calyciflorus-associated bacterial community were plastic degradation, chemoheterotrophy, and aerobic chemoheterotrophy. Overall, our study expands the current understanding of zooplankton–bacteria interaction and promotes the combination of two different research fields.
Period three actions on lens spaces

We show that a free period three action on a lens space is standard, i.e. the quotient is homeomorphic to a lens space. This is an extension of the result for period three actions on the three-sphere, arXiv:math.GT/0204077, by the author and J. Hyam Rubinstein.
Intelligent Resource Management Using Multiagent Double Deep Q-Networks to Guarantee Strict Reliability and Low Latency in IoT Network

With the rapid adoption of the Internet of Things, it is necessary to go beyond fifth-generation applications and apply stringent high reliability and low latency requirements, closely related to strict delay demands. These requirements support massive network connectivity for multiple Internet of Things devices. Hence, in this paper, we optimize energy efficiency and achieve quality-of-service requirements by mitigating co-channel interference, performing efficient power control of transmitters, and harvesting energy using time-slot exchanges. Due to a nonconvex optimization problem, we propose an iterative algorithm for power allocation and time slot interchange to reduce the computational complexity. To achieve a high degree of ultra-reliability and low latency with quality-of-service-aware instantaneous reward under massive connectivity, we efficiently employ multiagent reinforcement learning by addressing the intelligent resource management problem via a novel Double Deep Q Network. The network prioritizes experience replay to exploit the best policy and maximize accumulative rewards. It also learns the optimal policy and enhances learning efficiency by maximizing its reward function to make decisions with high intelligence and guarantee strict ultra-reliability and low latency. The simulation result shows that the Double Deep Q Network with prioritized experience replay can guarantee stringent ultra-reliability and low latency. As a result, the co-channel interference between transmission links and the high-power consumption density associated with the massive connectivity of the Internet of Things devices are mitigated.
Patients’ Intention to Adopt Fintech Services: A Study on Bangladesh Healthcare Sector

Advancement in technology has facilitated the shift toward new financial services. Numerous industries have undergone a digital transformation because of the expansion of cashless payment systems and other cutting-edge technologies. This study aimed to identify the factors that stimulate the patient’s intention to adopt fintech services in the Bangladesh healthcare sector. To facilitate the study, data were collected through survey questionnaires from different hospitals and diagnostic centers patients. A total of 279 patients responded to the survey. The study employed structural equation modelling to analyze the data using SMART PLS 3.2. 9. The results revealed that a significant relationship exists between perceived ease of use, social influence, facilitating conditions, personal innovativeness, and perceived trust in fintech services, and the adoption intention of the patients. The results of the study are beneficial to the healthcare sector and fintech companies who wish to make necessary arrangements to advance the growth of cashless fintech-based transactions.
CLASSIFICATION, CASIMIR INVARIANTS, AND STABILITY OF LIE{POISSON SYSTEMS

We classify Lie-Poisson brackets that are formed from Lie algebra extensions. The problem is relevant because many physical systems owe their Hamiltonian structure to such brackets. A classification involves reducing all brackets to a set of normal forms, independent under coordinate transformations, and is achieved with the techniques of Lie algebra cohomology. For extensions of order less than five, we find that the number of normal forms is small and they involve no free parameters. A special extension, known as the Leibniz extension, is shown to be the unique ``maximal'' extension. We derive a general method of finding Casimir invariants of Lie-Poisson bracket extensions. The Casimir invariants of all brackets of order less than five are explicitly computed, using the concept of `coextension. ' We obtain the Casimir invariants of Leibniz extensions of arbitrary order. We also offer some physical insight into the nature of the Casimir invariants of compressible reduced magnetohydrodynamics. We make use of the methods developed to study the stability of extensions for given classes of Hamiltonians. This helps to elucidate the distinction between semidirect extensions and those involving cocycles. For compressible reduced magnetohydrodynamics, we find the cocycle has a destabilizing effect on the steady-state solutions.
Corporate Mergers, Acquisitions and Value Creation of Firms in Nigeria

This study seeks to scrutinize the effect of corporate mergers, acquisition and value creation of firms in Nigeria and to identify areas of synergy. The study employed secondary data collected from the bank’s annual report. The data collected covered a period of fourteen years, which is divided into the pre and post-merger periods of seven years respectively. The study adopted panel least square estimation technique and other estimation for the analysis. The study finds out that shareholders’ funds and earnings per share are significant in determining the return on asset. Also shareholders’ funds and total asset values are statistically significant in the pre-merger periods in determining return on asset. That profit after tax is statistically significant in explaining financial efficiency in the pre-merger periods; the study concludes that there was increase in the shareholders’ funds for the post-merger periods.
In Vitro Screening for Anti-Acetylcholinesterase and Antioxidant Activities of Hottonia palustris L. Extracts and Their Unusual Flavonoids

Hottonia palustris L. is from the genus Hottonia (Primulaceae), and the understanding of its phytochemical and pharmacological properties is limited. In this study, the use of chromatographic techniques led to the isolation of a further eleven compounds, including three new flavonoids: 2′,5-dihydroxyflavone 2′-O-β-glucopyranoside, 5,6-dihydroxyflavone 6-O-(6”-O-glucopyranosyl)-β-glucopyranoside (hottonioside A), and 4′,5,7-trihydroxyflavone 7-O-(2”-O-β-glucuronide)-β-glucopyranoside. Their structures were determined using extensive 1D and 2D NMR data and mass spectrometry (HRMS). The qualitative assessment of the chemical composition of the investigated extracts and fractions was performed using the LC-HRMS technique. Furthermore, the antioxidant potential of extracts, fractions, and compounds and their ability to inhibit acetylcholinesterase were also evaluated. Thus, we may conclude that the observed biological effects are the result of the presence of many biologically active compounds, of which dibenzoylmethane is the most active. Therefore, H. palustris is a source of substances with desirable properties in the prevention and treatment of neurodegenerative diseases.
Effectiveness of Strategically Located Green Stormwater Infrastructure Networks for Adaptive Flood Mitigation in a Context of Climate Change

Studies indicate Green Stormwater Infrastructure (GSI) on industrial land can provide substantial adaptive flood mitigation within urban catchments under climate change. To identify a cost-effective adaptive GSI network, planners need to evaluate flood mitigation capabilities of industrial properties through time and understand key characteristics informing when, where, and how GSI should be implemented for maximum effect. We applied the Hydrology-based Land Capability Assessment and Classification (HLCA+C) methodology to a catchment in Christchurch, New Zealand, to evaluate the capabilities of industrial properties clustered into Storm Water Management (SWM) zones under different climate change scenarios. SWM zone potentials and limitations were assessed to develop the most capable adaptive flood mitigation network with climate change. We prioritised six of twenty SWM zones for inclusion in the network based on their substantial flood mitigation capabilities. To maximise their capabilities through time, we orchestrated, and implemented GSI in zones incrementally, using different implementation approaches based on key characteristics determining their capability. The results indicated that the most capable zone could mitigate climate change-induced flooding, by itself, up to the end of this century under the moderate climate change scenario. However, if its capability was combined with that of five others, together they could mitigate flooding just shy of that associated with the major climate change scenario up to the end of this century. The resulting adaptive industrial GSI network not only provides substantial flood protection for communities but allows costly investments in flood mitigation structures, such as barriers and levees, to be safely delayed until their cost-effectiveness has been confirmed under increased climate certainty.
Relief Policy and the Sustainability of COVID-19 Pandemic: Empirical Evidence from the Italian Manufacturing Industry

This work investigates the impact of COVID-19 on the Italian manufacturing industry, testing whether the recovery measures introduced by the government were effective in alleviating the economic consequences of the virus in 2020. In particular, this work aims to address the impact of COVID-19 on the Italian manufacturing industry, and evaluation of the adopted recovery measures. Considering the current situation, with the war in Ukraine and the related gas crisis across the European Union, such investigation on policy relief is even more relevant, contributing to the current debate. Adopting RE models, and considering the latest economic and financial information available, we analyzed active private limited firms in the Italian manufacturing industry between 2019 and 2020, investigating the impact of layoff on their productivity (i.e., Total Factor Productivity) and profitability (i.e., Return On Assets), as well as their expected probability of default. According to the results of these regression models, and assuming 8 weeks of layoff, we observed an increase in productivity (between 1.20% and 1.59%), a decrease in profitability (1.47%) and an increase in bankruptcy risk (2.27%). Hence, the relief policy was not able to alleviate the economic consequences of COVID-19 for these firms, even though the layoffs were able to support their productivity. Practical implications concern the necessary improvements for the above relief policy, i.e., interventions to support the demand of manufactured products, interventions to support the digitalization of services, interventions to support the remote working, and interventions to support the introduction of innovative products on the market.
Personality Traits and Family Environment: Antecedents of Child Aggression

Previous research reported significant relationship between Big Five personality traits and aggression in both adolescent’s and adult population. However, it is unclear about whether similar connection exist in early age. This study investigated how personality traits and family environment influence the development of aggression in school aged Saudi children. A sample of 315 school going children were recruited voluntarily to complete a set of measures examining Big Five personality factors, family environment and aggression. Correlation analysis were employed to evaluate association between Big Five personality traits, family environment and aggression. The results showed a significant relationship of Big Five personality factors and family environment factors to aggression. The findings of the study revealed that amongst the Big Five personality traits conscientiousness, agreeableness, and neuroticism were strongest antecedents of childhood aggression. Family environment characterized by family cohesion, expressiveness and conflict were appeared to be significant antecedents of aggressive behavior in children. This study expands our knowledge about the intervention strategies of aggression from Big Five traits and family environment perspectives.
Thermochemical evolution of the acapulcoite–lodranite parent body: Evidence for fragmentation‐disrupted partial differentiation

Primitive achondrites of the acapulcoite–lodranite clan (ALC) are residues of partial melting that displays a continuum of thermal metamorphism and partial melting most likely set by burial depth within an internally heated, primordial acapulcoite–lodranite parent body (ALPB). New major and trace element data from eight ALC meteorites and the application of several thermometric methods suggest that the ALPB was affected by partial differentiation disrupted by rapid cooling from peak, magmatic temperatures. Application of rare earth element‐in‐two‐pyroxene thermometry recovers temperatures of 1125–1250 °C for lodranites, while two‐pyroxene solvus and Ca‐in‐olivine thermometry recover lower temperatures for ALC meteorites (941–1114 °C and 686–850 °C, respectively). Major and trace element disequilibrium in acapulcoite and transitional groups provides evidence for cryptic melt infiltration and melt rock reaction within these layers of the ALPB. From lodranites, we determined rapid cooling rates of ~1 to ~26 °C yr−1 from peak temperatures, consistent with collisional fragmentation of the parent body during differentiation. After this initial period of rapid cooling, cooling rates decreased by two to four orders of magnitude through Ca‐in‐olivine closure temperatures (~750 °C). We hypothesize that the primordial ALPB possessed an onion shell‐type layered structure that was disrupted by collisional breakup during partial differentiation. Thermal modeling suggests that ALC samples originate from ~300 m to ~10 km radius collisional fragments that cooled rapidly over time scales of several to ~20,000 yr, then reaccreted to form a slower cooling, second‐generation rubble‐pile asteroid. The source of ALC meteorites is a second‐generation (or later) rubble‐pile body of S‐type spectral class located near the Jupiter 3:1 mean motion resonance in the Main Belt of asteroids.