Miracle-dz/UniFAR-FTUs huggingface dataset:
The Duality of the Formal Local Homology Together With The Edge Ideal of a Graph

In this paper, is discuted about the formal local homology mo dule and the formal local cohomology module, this last which is the dual of the formal local homology module. For the defini tio of this two modules are used the definitions of the local c ohomology module with respect to an ideal and of the local homology modu le with respect to an ideal, where this modules are mencioned i the text. Also are put some connection between the formal loc l cohomology module and the formal local homology module, u sing some results of the theory of commutative algebra. Moreover , w involve the theory of graphs within of such modules achie ving some applications for the edge ideal of a graph.
Compliance with Public Health Orders: The Role of Trust, Representation, and Expertise

Governments rely on citizen compliance to implement policies. Yet, in the current climate where citizens express low levels of trust in government, gaining compliance can prove challenging. Scholarship suggests other factors that might promote compliance even in the absence of trust. We examine two: expertise and descriptive representation across race, gender, and partisanship. We experimentally activate general (dis)trust in government and use a conjoint experiment to examine multiple factors that might shape citizens’ willingness to comply with and trust government guidance related to COVID-19. We find that shared partisanship and consultation with experts have the largest effects. We also see an effect of shared racial identity on compliance for Black Americans, at least when trust is relatively low. As we consider the role of trust, expertise, and descriptive representation across race, gender, and partisanship simultaneously, the results offer important insights into factors that underpin citizens’ willingness to comply with government mandates. Our results have important real-world implications, highlighting the importance of bipartisan responses to crises as well as ensuring racial representation in government. They also demonstrate that explicitly involving experts in decision-making processes increases citizens’ willingness to comply with policy.
Investigating quantum wireless multihop teleportation in amplitude damping channel

This paper scrutinizes quantum routing protocol with multihop teleportation for wireless mesh backbone networks, in an amplitude damping channel. After analyzing the quantum multihop protocol, we select a four-qubit cluster state as the quantum channel for the protocol. The quantum channel linking the intermediate nodes has been established via entanglement swapping based on four-qubit cluster state. Also, we established the classical and the quantum route in a distributed manner. We show that from the source node to the destination node, quantum information can be teleported hop-by-hop through an amplitude damping channel. We show that the quantum teleportation could be successful if the sender node performs Bell state measurements (BSM), and the receiver introduces auxiliary particles, applies positive operative value measure and then utilizes corresponding unitary transformation to recover the transmitted state. We scrutinize the success probability of transferring the quantum state through a noisy channel. We found that optimum probability would be attained if decoherence rate of amplitude damping channel ($\xi_a$) is zero or the number of hops ($N$) is above $75$. Our numerical results evince susceptibility of success probability to $\xi_a$ and $N$. It has been shown that as the decoherence increases, the fidelity exponentially decays until it vanishes. This decay is as a consequence of information loss from the system to the surrounding. However, the fidelity can be enhanced by considering fewer hops.
Getting Back on Track: Understanding COVID-19 Impact on Urban Mobility and Segregation with Location Service Data

Understanding the impact of COVID-19 on urban life rhythms is crucial for accelerating the return-to-normal progress and envisioning more resilient and inclusive cities. While previous studies either depended on small-scale surveys or focused on the response to initial lockdowns, this paper uses large-scale location service data to systematically analyze the urban mobility behavior changes across three distinct phases of the pandemic, i.e., pre-pandemic, lockdown, and reopen. Our analyses reveal two typical patterns that govern the mobility behavior changes in most urban venues: daily life-centered urban venues go through smaller mobility drops during the lockdown and more rapid recovery after reopening, while work-centered urban venues suffer from more significant mobility drops that are likely to persist even after reopening. Such mobility behavior changes exert deeper impacts on the underlying social fabric, where the level of mobility reduction is positively correlated with the experienced segregation at that urban venue. Therefore, urban venues undergoing more mobility reduction are also more filled with people from homogeneous socio-demographic backgrounds. Moreover, mobility behavior changes display significant heterogeneity across geographical regions, which can be largely explained by the partisan inclination at the state level. Our study shows the vast potential of location service data in deriving a timely and comprehensive understanding of the social dynamic in urban space, which is valuable for informing the gradual transition back to the normal lifestyle in a “post-pandemic era”.
Investigating the Environmental Properties of Galaxies in the SDSS-MaNGA Survey

This thesis presents a study of galaxy evolution in the local universe. I study how environments shape the structures of galaxies, and how internal and external processes affect star formation. I perform four investigations of galaxy properties: a study of the relations between size, mass and velocity dispersion of 124,524 galaxies from SDSS DR7; I estimate star formation rates using Hα and Dn4000 for galaxies in the MaNGA survey; a study of the spatial distribution of star formation in 1494 MaNGA galaxies; and finally, a study of 215 barred and 402 unbarred galaxies, to investigate how bars affect star formation. I find that environment plays a key role in the evolution of galaxies, both structurally and in terms of their star formation. Using core velocity dispersion to study the effects of minor mergers and tidal/ram pressure stripping, I find that central galaxies are up to 30% larger and more massive than satellites. I suggest that minor mergers play a crucial role in the increase in size and mass of centrals. In addition, I find that satellites have a uniform radial suppression of star formation, compared to centrals, which may be due to the strangulation of their cold gas supplies. I study the internal processes that affect star formation and find that specific star formation rate is suppressed at all radii for high mass galaxies. Massive galaxies are more likely to have suppressed star formation in their cores, which I determined is caused by a combination of morphological quenching and AGN feedback. Finally, I study the role of galaxy bars in regulating the cirumnuclear and disk star formation in late-type galaxies. I find that barred galaxies have lower star formation in their disks than unbarred galaxies, and that they are more likely to have enhanced star formation in their cores.
Nexus among Service Quality and Participants Loyalty in Jordanian Trade Shows: A Mediated-Moderated Model

Trade shows help potential stakeholders meet, promote, speed up the sales process, provide opportunities to enter new markets, and launch new products. Trade shows are also the most expensive marketing activity and have a set period. Therefore; this study determined the factors which lead to participant loyalty in the Jordanian trade shows context while investigating the mediating roles of participants' satisfaction, and the moderating role of participation cost. This model was tested using a quantitative method and the questionnaire technique. In order to examine the data, structural equation modeling was used. Findings indicate that service quality is significantly influenced by participants' satisfaction and loyalty. Moreover; participants' satisfaction has a significant relationship with loyalty. More importantly, participants' satisfaction plays a mediating role between service quality and, loyalty. Also; the trade shows participation cost the moderating role between service quality and, participants' satisfaction. This study may help to encourage the organizers of Jordan exhibitions to focus on the tangible aspects along with the participating cost, to achieve overall satisfaction and loyalty that makes attending the exhibition is very important and worthy.
Deep learning approach for one-hour ahead forecasting of weather data

ABSTRACT Weather is made up of multiple parameters, including solar radiation (SR), atmospheric pressure (AP), soil temperature (ST), atmospheric temperature (AT), wind speed (WS), relative humidity (RH), and sunshine duration (SD). These factors are also crucial for the renewable energy sector, solar simulation, agriculture, air pollution, water supply and distribution, avalanche warning, forestry, and town and regional planning. A deep learning method based on a neural network with Long Short-Term Memory (LSTM) was employed in this investigation for one-hour-ahead weather data forecasting. The ability of the LSTM model was compared with the Adaptive Neuro-Fuzzy Inference System (ANFIS) with that of the fuzzy c-means (FCM), Autoregressive Integrated Moving Average (ARIMA) model, and the Autoregressive Moving Average (ARMA) model. Mean absolute error (MAE), correlation coefficient (R), root means square error (RMSE), average bias, Nash – Sutcliffe efficiency coefficient (NSE), and mean absolute percentage error (MAPE) were selected as evaluation criteria. Results indicated that the proposed LSTM model presented good enough results compared to other used methods. 7 different types of meteorological data from a total of 4 years (35040 hours) were divided into 25% test data and 75% training data for the models. The best result was obtained for the hourly ST estimation of Adana province using the LSTM method, the MAE, RMSE, R, bias, NSE, and MAPE values were computed as 0.016°C, 0.078°C, 0.9999, −0.00018°C, 0.0805%, and 0.9999, respectively. On the other hand, the worst result was obtained for the hourly SD for Mardin province when ARIMA was used, and the statistical measures were derived as 0.128 hours for MAE, 0.215 hours for RMSE, 0.8851 for R, 0.00091 hours for bias, and 0.7657 for NSE. In this regard, it is demonstrated that the LSTM technique outperformed the other models in terms of all-weather data estimates and delivered highly sensitive outcomes.
Cross-cultural validity of the Nature Relatedness Scale (NR-6) and links with wellbeing

Nature relatedness refers to individual differences in subjective connectedness with the natural environment. We aimed to cross-culturally validate the Nature Relatedness scale and examine links between nature relatedness and wellbeing. We also tested whether spirituality or self-transcendent emotions such as gratitude mediate the relationship between nature relatedness and wellbeing. University student participants (N = 798) from four countries (Hungary, India, South Korea, and Canada) completed the short-form Nature Relatedness scale (NR-6; Nisbet & Zelenski, 2013), the Inclusion of Nature in Self scale (Schultz, 2002a), and measures of hedonic and eudaimonic wellbeing. Cross-cultural differences were found in a number of nature relatedness principal components, as well as differences in links between nature relatedness, spirituality, and wellbeing. In all four countries, gratitude formed a significant indirect path from nature relatedness to mental health and quality of life. The findings suggest that spiritual aspects of human-nature relationships may contribute to wellbeing across cultures.
Asymptotic properties and information criteria for misspecified generalized linear mixed models

The problem of misspecification poses challenges in model selection. The paper studies the asymptotic properties of estimators for generalized linear mixed models with misspecification under the framework of conditional Kullback–Leibler divergence. A conditional generalized information criterion is introduced, and a model selection procedure is proposed by minimizing the criterion. We prove that the model selection procedure proposed is asymptotically loss efficient when all the candidate models are misspecified. The model selection consistency of the model selection procedure is also established when the true data‐generating procedure lies within the set of candidate models. Simulation experiments confirm the effectiveness of the method proposed. The use of the criterion for model selection is illustrated through an analysis of the European Currency Opinion Survey data.
A hierarchical modelling framework for estimating individual‐ and population‐level reproductive success from movement data

Rapidly advancing animal telemetry technologies paired with new statistical models can provide insight into the behaviour of otherwise unobservable free‐living animals. Changes in behaviour apparent from pairing telemetry with statistical models often occur as animals undertake key life‐history activities, such as reproduction. For many species that are secretive or occupy remote areas, these life‐history events are difficult to detect with conventional survey techniques, and consequently, vital rates are difficult to estimate. We present a hierarchical modelling framework, which integrates movement data observed via animal‐borne telemetry and optional, infrequent survey data, to estimate individual‐ and population‐level reproductive success. The approach combines a mechanistic movement model and survival model, and allows for assessing the effects of hypothesized individual and environmental covariates on reproductive success. We first tested our approach with simulated data, and then applied it to movement data from migratory golden eagles (Aquila chrysaetos) breeding in southcentral Alaska across four breeding seasons. We show that results supported our biological hypotheses that changes in movement coincided with the timing of reproductive failures, and that changes in movement could be used to assess breeding success (and failure) at the individual and population levels. The analysis also provided evidence of inter‐annual variation in population‐level nest success and the timing of nesting failures. This new approach is adaptable to many species that care for young and can be tracked with telemetry devices, and can provide not only individual‐level information useful for testing ecological hypotheses, but estimates of demographic parameters that can directly inform conservation and management if tagged animals are representative of the population.
b-Quark Production in Proton-Proton Collisions at Center of Mass Energies of 510 GeV in the PHENIX Detector at RHIC

Heavy flavor quarks are an important probe of the initial state of the Quark Gluon Plasma formed in heavy-ion collisions. Bottom and charm quarks are produced early in the collision, primarily through hard interactions, and experience the full time evolution of the medium. Understanding bottom quark production in p + p collisions gives a baseline reference for studying larger collision systems. The measurement of the bb̄ cross section can directly test pQCD predictions and ∆φ correlations gives insight into the b quark production mechanisms. The bb̄ signal can be isolated by taking advantage of the properties of B oscillations in the invariant mass region of 5-10 GeV. Measuring like-sign dimuons within this mass range provides an enriched bottom signal with a minimal amount of open charm background and without any contributions from quarkonia or Drell-Yan pairs. bb̄ will be measured through the semi-leptonic decay like-sign dimuon signal, in the rapidity range 1.2 < |y| < 2.2 and at √ s = 510 GeV from data recorded in 2013 at the PHENIX experiment. The measured total cross section is σbb̄ = 14.9± 0.7(stat)± 2.0(type B sys.)± 3.4(type C sys.)[μb]. INDEX WORDS: nuclear physics, RHIC, PHENIX, heavy flavor, bottom quark, p+ p, dimuon, cross section, correlations bb̄ PRODUCTION IN p+ p COLLISIONS AT √ s = 510 GeV IN THE PHENIX DETECTOR AT RHIC
Three‐dimensional nonlinear evolution of equatorial ionospheric spread‐F bubbles

Using numerical simulation techniques, we present the first study of the three‐dimensional nonlinear evolution of an equatorial spread‐F bubble. The background ionosphere used to initialize the bubble evolution is computed using a time‐dependent first‐principles equatorial plasma fountain model together with a prereversal enhancement vertical drift model. We find that finite parallel conductivity effects slow down both the linear and nonlinear bubble evolution compared to the two‐dimensional evolution. In addition we find that bubble‐like structures with extremely sharp density gradients can be generated off the equator at equatorial anomaly latitudes in agreement with recent observations.
Perceptual sources for closed-syllable vowel laxing and derived environment effects

This dissertation claims that allowing perceptual factors to play a role in phonology helps make some progress on the understanding of two challenging phenomena: closed-syllable vowel laxing (CSVL), i.e. the tendency for vowels to be lowered and centralized before word-final and preobstruent consonants, and phonologically-derived environment effects (PDEEs), i.e. patterns where a phonological process is blocked unless accompanied by another phonological process. CSVL is challenging because the mechanism that relates vowel quality and the postvocalic context is not obvious. In particular, CSVL cannot be analyzed as a coarticulatory effect driven by vowel shortening. PDEEs are challenging because they imply that a smaller input-output change may be worse than a strictly larger one, in violation of a basic principle of faithfulness. Part I proposes that CSVL is a strategy to enhance contrasts among postvocalic consonants in contexts where these consonants lack good release cues and are therefore perceptually weak. In particular, laxing is argued to enhance contrasts of place of articulation (e.g. contrasts involving [p], [t], [k]). This hypothesis is supported by the results of a perception experiment showing that, in French, [p], [t], and [k] are generally more distinct after lax mid vowels than after tense mid vowels. An analysis of CSVL is proposed using constraints on contrasts. Part II proposes that PDEEs follow from the hypothesis that the input-output distance is perceived logarithmically: this predicts that a feature change may be less salient perceptually and therefore represent a smaller violation of faithfulness if accompanied by another feature change. This theory has two desirable consequences: it reconciles the analysis of PDEEs with the idea of a minimal input-output modification bias and it derives a number of perceptual constraints on the features that can interact in PDEEs, therefore providing a restrictive account of the typology. Thesis Supervisor: Edward Flemming Title: Associate Professor of Linguistics Thesis Supervisor: Michael Kenstowicz Title: Professor of Linguistics Thesis Supervisor: Donca Steriade Title: Professor of Linguistics
HEAT TRANSFER DETERIORATION EFFECTS OF CRYOGENIC METHANE IN ROCKET ENGINE COOLING CHANNELS

Prediction of heat transfer deterioration in rocket engine coolant channels with supercritical flow is essential while designing high pressure rocket engines. Three-dimensional conjugate heat transfer of cryogenic methane in rectangular engine cooling channels at supercritical pressures with asymmetric heating imposed on the bottom channel surface is numerically investigated, focusing on the effects of key parameters such as aspect ratio, heat flux and coolant pressure. Due to the similarity of the coolant channel with that of an actual rocket engine, the results obtained herein are beneficial for the design and optimization of rocket engine cooling systems. Heat flux is varied from 1 MW/m2 to 5 MW/m2 and the coolant pressure from 6 MPa to 12 MPa. Results indicate that the aspect ratio has significant effect on the conjugate heat transfer owing to heat flux re-distribution in the walls. From the heat transfer point of view, channels with high aspect ratio perform well. Heat transfer deterioration is observed due to the drastic property variation near pseudocritical temperature in the region close to the wall. Increasing the operating pressure would result in improved heat transfer at supercritical pressures, particularly under high wall heat fluxes.
Attention and DCT Based Global Context Modeling for Text-Independent Speaker Recognition

Learning an effective speaker representation is crucial for achieving reliable performance in speaker verification tasks. Speech signals are high-dimensional, long, and variable-length sequences containing diverse information at each time-frequency (TF) location. The standard convolutional layer that operates on neighboring local regions often fails to capture the complex TF global information. Our motivation is to alleviate these challenges by increasing the modeling capacity, emphasizing significant information, and suppressing possible redundancies. We aim to design a more robust and efficient speaker recognition system by incorporating the benefits of attention mechanisms and Discrete Cosine Transform (DCT) based signal processing techniques, to effectively represent the global information in speech signals. To achieve this, we propose a general global time-frequency context modeling block for speaker modeling. First, an attention-based context model is introduced to capture the long-range and non-local relationship across different time-frequency locations. Second, a 2D-DCT based context model is proposed to improve model efficiency and examine the benefits of signal modeling. A multi-DCT attention mechanism is presented to improve modeling power with alternate DCT base forms. Finally, the global context information is used to recalibrate salient time-frequency locations by computing the similarity between the global context and local features. This effectively improves the speaker verification performance compared to the standard ResNet model and Squeeze & Excitation block by a large margin. Our experimental results show that the proposed global context modeling method can efficiently improve the learned speaker representations by achieving channel-wise and time-frequency feature recalibration.
Assessment of the Fungistatic Properties of Calendula officinalis L. Water Extract and the Effect of Its Addition on the Quality of Wheat Bread

The potential of Calendula officinalis water extract against fungi Aspergillus niger and Penicillium sp. and the effect of extract addition on the quality of wheat bread were investigated. In vitro, the extract reduced the mycelial growth and biomass production of A. niger, but there was no inhibitory effect on Penicillium sp. Enriched bread showed significantly higher total phenolic content, by about 77% and 95% in the bread, in which 10% and 15% of the water was replaced with extract, respectively. The antioxidant potential against DPPH• was significantly higher (compared to the control) in both variants used in the experiment, and the level of antioxidant activity increased with the addition of extract. The enriched bread had good quality characteristics—lower baking losses and higher volume than the control. The moisture content and acidity of the crumb of the extract-enriched bread were also higher. The extract additive used did not affect the sensory properties of the bread.