Miracle-dz/UniFAR-FTUs huggingface dataset:
Synergy between Ceria Oxygen Vacancies and Cu Nanoparticles Facilitates the Catalytic Conversion of CO2 to CO under Mild Conditions

The performance of supported metal catalysts can depend on many factors, including metal particle size and dispersion and metal–support interactions, and differentiation of these effects is challenging because of their interwoven relationship. Copper/ceria catalysts are well-known redox catalysts studied in the conversion of CO and CO2 via oxidation and/or reduction pathways. The redox behaviors of each species, Cu-CuO and CeOx-CeO2, are often suggested to be interlinked, allowing ceria-supported copper domains to outperform copper species on other, nonredox active supports. In this work, the catalytic activity of nanosized Cu supported on either cerium oxide or mesoporous silica is explored using samples where the Cu weight loading, particle size, and dispersion of Cu are held constant to highlight the impact of the two supports on catalytic performance without additional influencing factors. The Cu/CeO2 catalysts are synthesized via a space-confined method to limit the growth of CeO2 particles and to ac.
A Novel Mixed Method Using MM-SE with Change in Routhain Array for Model Order Reduction

The system modelling leads towards the higher-order differential equations. These systems are difficult to analyse. Therefore, for ease and understanding, the conversion of higher to lower order is required. The model order reduction(MOR) is a systematic procedure to tackle these kinds of situations. This paper offers a mixed method for MOR using the modified moment matching (MM) and stability equation (SE). The modification is applied in the routhain array of MM. The approach has been verified by examining the error between the original, proposed and compared with reduced order available in the literature. The obtained result has been compared on the basis of step response characteristics and the response indices error.
Who? What? Event Tracking Needs Event Understanding

: Humans ﬁrst learn, then think and ﬁnally perform a task. Machines neither learn nor think, but we still expect them to perform tasks as well as humans. In this position paper, we address the lack of understanding in Topic Detection and Tracking (TDT), an area that builds timelines of events, but which hardly understands events at all. Without understanding events, TDT has progressed slowly as the community struggles to solve the challenges of modern data sources, like Twitter. We explore understanding from different perspectives: what it means for machines to understand events, why TDT needs understanding, and how algorithms can generate knowledge automatically. To generate understanding, we settle on a structured deﬁnition of events based on the four Ws: the Who, What, Where and When. Of the four Ws, we focus especially on the Who and the What, aligning them with other research areas that can help TDT generate event knowledge automatically. In time, understanding can lead to machines that not only track events better, but also model and mine them.
SYNTHESIS AND PHOTOCATALYSIS OF CUPROUS OXIDE NANO-SPHERES IN AQUEOUS

Cuprous oxide (Cu2O) nanocrystallites were successfully prepared by using hydrazine hydrate as reducing agent and polyvinyl pyrrolidone (PVP) as the capping agent in aqueous phase, which was proved to be a green and convenient method for the synthesis of Cu2O Nano-spheres. Photocatalytic decolorization of Methyl Orange in aqueous Cu2O suspensions was investigated. Using X-ray diffraction, scanning electron microscope, High Resolution Transmission Electron Microscopy characterized the samples and UV–vis Spectroscopy was employed to investigate the photocatalysis behavior of the Cu2O samples.
A Detailed Study of Different Speech Enhancement Techniques

Speech enhancement is a topic of great importance and there are numerous existing methods to achieve the goal of enhancement. In this project, we study several speech enhancement techniques and compare them on the basis of enhancement quality, algorithm complexity, and overall performance. However, due to the different types of noise, lack of common speech database, and inconsistencies in testing methods, it is problematic to make comparisons between the performance of different algorithms. Hence, one of the goals of this project is to determine the best ways to asses quality of speech enhancement.
In Vivo MRI of Endogenous Remyelination in a Nonhuman Primate Model of Multiple Sclerosis

Remyelination is crucial for recovery from inflammatory demyelination in multiple sclerosis (MS). Investigating remyelination in vivo using magnetic resonance imaging (MRI) is difficult in MS, where collecting serial short-interval scans is challenging. Using experimental autoimmune encephalomyelitis (EAE) in common marmosets, a model of MS that recapitulates focal cerebral MS lesions, we investigated whether remyelination can be detected and characterized noninvasively. In 6 animals followed with multisequence 7-tesla MRI, 36 focal lesions, classified as demyelinated or remyelinated based on signal intensity on proton density-weighted images, were subsequently assessed with histopathology. Remyelination occurred in 5 of 6 marmosets and 51% of lesions. Radiological-pathological comparison showed high sensitivity (88%) and specificity (90%) for detecting remyelination by in vivo MRI. This study demonstrates the prevalence of spontaneous remyelination in marmoset EAE and the ability of in vivo MRI to detect it, with implications for preclinical testing of pro-remyelinating agents and translation to clinical practice.
The effects of immediate recall and subsequent retrieval strategy on eyewitness memory

The current study investigated the effects of immediate recall and subsequent interview on mock witnesses’ memory of a crime. After watching a video of a crime, 111 participants were randomly allocated to an immediate recall condition (the iWitnessed mobile app, free recall). One week later, participants were randomly allocated to a retrieval condition (timeline aid, category clustering recall, free recall). Results showed that iWitnessed elicited more correct details than free recall at immediate recall (Time 1), without compromising accuracy. However, the immediate recall tool did not affect memory performance at a one-week delay (Time 2). At Time 2, participants with retrieval support (timeline aid, category clustering recall) reported more details than those with no retrieval support (free recall), without compromising accuracy. The findings highlight that high-quality immediate recall and retrieval support during a subsequent interview are necessary to elicit more complete and accurate accounts.
A Case Study and Qualitative Analysis of Simple Cross-Lingual Opinion Mining

User-generated content from social media is produced in many languages, making it technically challenging to compare the discussed themes from one domain across different cultures and regions. It is relevant for domains in a globalized world, such as market research, where people from two nations and markets might have different requirements for a product. We propose a simple, modern, and effective method for building a single topic model with sentiment analysis capable of covering multiple languages simultanteously, based on a pre-trained state-of-the-art deep neural network for natural language understanding. To demonstrate its feasibility, we apply the model to newspaper articles and user comments of a specific domain, i.e., organic food products and related consumption behavior. The themes match across languages. Additionally, we obtain an high proportion of stable and domain-relevant topics, a meaningful relation between topics and their respective textual contents, and an interpretable representation for social media documents. Marketing can potentially benefit from our method, since it provides an easy-to-use means of addressing specific customer interests from different market regions around the globe. For reproducibility, we provide the code, data, and results of our study.
Political sorting in U.S. entertainment media

ABSTRACT Analysis of public opinion, news consumption, and social media has examined increasing political polarization and/or partisan sorting; however, few have explored the potential connection between entertainment programming and political sorting. This paper examines viewership of U.S. television entertainment from 2001 to 2016 and finds increasing differentiation in the shows watched in primarily Democratic versus primarily Republican markets. Notably, these years coincide with partisan sorting in news consumption and enhanced fracturing of the U.S. television landscape. The article confirms growing differences in the most-watched shows in heavily Democratic versus Republican regions, a finding that provides uncommon evidence of suspected differentiation by political view and of the need to adapt theories of the “mass” media function of entertainment television to a context of greater fragmentation and choice.
Nature, Human and City (Appreciating the Effect of Covid-19 on Human and City)

Despite the existing and potential characteristics of nature in urban planning process, technological progress and the rate of change in the physical identity of cities have increased natural mutations and taken the relationship between humans and nature out of the normal process. Among the natural mutations, we can mention infectious diseases, which have been nature's reaction against the city and the density of the urban population. Health issues and infectious diseases have long plagued cities, leading to changes in architecture and its rules and regulations. This process has been done less in urban planning regulations and this has increased the vulnerability of citizens in the urban environment against infectious diseases. Accordingly, this study attempted to offer principles centered on the physical nature of the city, while reviewing the history of infectious diseases in the world and considering urban planning theories related to urban health and pollution and the statistics of sample cities in the face of Covid-19 in order to accompany urban physical changes with human, technological, identity and natural changes to help urban management to reduce citizens’ vulnerability against infectious diseases. Data were collected using library and internet resources. Principles are derived from the Delphi method of experts. Some of the proposed principles are balanced building density, observing the minimum ratio of open space to urban residential space and balanced distribution of open space in the city, reducing per capita office use, establishing a crisis center with isolated conditions in each neighborhood, increasing per capita urban equipment and facilities land use, balanced distribution of neighborhood services, moving to multi-center cities, reducing concentration in city centers and using multifunctional urban spaces. Currently, due to natural mutations as well as changes in culture, traditions, and technological mutations, we need flexible rules and regulations to identify cities and align with nature. Therefore, it should be considered that the proposals offered are following the current situation and should be amended and updated over time and as circumstances change.
Density Functional Theory Study of Ethylene Carbonate Adsorption on the (0001) Surface of Aluminum Oxide α-Al2O3

Surface coating is one of the techniques used to improve the electrochemical performance and enhance the resistance against decomposition of cathode materials in lithium-ion batteries. Despite several experimental studies addressing the surface coating of secondary Li-ion batteries using α-Al2O3, the reactivity of the material toward the electrolyte components is not yet fully understood. Here, we have employed calculations based on the density functional theory to investigate the adsorption of the organic solvent ethylene carbonate (EC) on the major α-Al2O3(0001) surface. During adsorption of a single EC molecule, it was found that it prefers to bind parallel to the surface through its carboxyl oxygen. As the surface coverage (θ) was increased up to a monolayer, we observed larger adsorption energies per EC molecule (Eads/NEC) for parallel interactions and a reduction for perpendicular interactions. We also noted that increasing the surface coverage with both parallel and perpendicularly interacting EC molecules led to a decrease of the surface free energies and hence increased stability of the α-Al2O3(0001) surface. Despite the larger Eads/NEC observed when the molecule was placed parallel to the surface, minimal charge transfer was calculated for single EC interactions and at higher surface coverages. The simulated scanning tunneling microscopy images are also presented for a clean corundum α-Al2O3 surface and after adsorption with different coverages of parallel and perpendicularly placed EC molecules.
Contribution of Coagulase and Its Regulator SaeRS to Lethality of CA-MRSA 923 Bacteremia

Coagulase is a critical factor for distinguishing Staphylococcus aureus and coagulase-negative Staphylococcus. Our previous studies demonstrated that the null mutation of coagulase (coa) or its direct regulator, SaeRS, significantly enhanced the ability of S. aureus (CA-MRSA 923) to survive in human blood in vitro. This led us to further investigate the role of coagulase and its direct regulator, SaeRS, in the pathogenicity of CA-MRSA 923 in bacteremia during infection. In this study, we found that the null mutation of coa significantly decreased the mortality of CA-MRSA 923; moreover, the single null mutation of saeRS and the double deletion of coa/saeRS abolished the virulence of CA-MRSA 923. Moreover, the mice infected with either the saeRS knockout or the coa/saeRS double knockout mutant exhibited fewer histological lesions and less neutrophils infiltration in the infected kidneys compared to those infected with the coa knockout mutant or their parental control. Furthermore, we examined the impact of coa and saeRS on bacterial survival in vitro. The null mutation of coa had no impact on bacterial survival in mice blood, whereas the deletion mutation of saeRS or coa/saeRS significantly enhanced bacterial survival in mice blood. These data indicate that SaeRS plays a key role in the lethality of CA-MRSA 923 bacteremia, and that coagulase is one of the important virulence factors that is regulated by SaeRS and contributes to the pathogenicity of CA-MRSA 923.
Impacts of the Imidazolate Linker Substitution (CH3, Cl, or Br) on the Structural and Adsorptive Properties of ZIF-8

Zeolitic Imidazolate Frameworks (ZIFs) represent a thriving subclass of metal–organic frameworks (MOFs) owing to the large variety of their topologies, of which some of them are common with zeolites, and the ability to modulate the chemistry of their frameworks as well as the hydrophobicity/hydrophilicity balance, making them perfect examples of the isoreticular chemistry concept. One peculiar structural feature of ZIFs is their potential for structural transitions by rotation (or swing) of their linkers under external stimuli (guest adsorption, mechanical constraints, etc.). This singular characteristic, often denominated “swing effect” or “gate opening”, is related to flexible ZIFs. Our study focuses on the influence of the functional group (−CH3, −Cl, −Br) borne in position 2 by the imidazolate linker on the flexible/stiff nature of three isoreticular ZIFs with SOD topology. In the first part, we report the structures of ZIF-8_Cl and ZIF-8_Br, two halogenated analogs of the well-known ZIF-8 (herein nam.
Pseudo-random number generation based on digit isolation referenced to entropy buffers

Unpredictable pseudo-random number generators (PRNGs) are presented based on dissociated components with only coincidental interaction. The first components involve pointers taken from series of floating point numbers (float streams) arising from arithmetic. The pointers are formed by isolating generalized digits sufficiently far from the most significant digits in the float streams and may be combined into multi-digit pointers. The pointers indicate draw locations from the second component which are entropy decks having one or more cards corresponding to the elements used to assemble random numbers. Like playing cards, decks are cut and riffle-shuffled based on rules using digits appearing in the simulations. The various ordering states of the cards provide entropy to the PRNGs. The dual nature of the PRNGs is novel since they can operate either entirely on pointer variability to fixed decks or on shuffling variability using fixed pointer locations. Each component, pointers and dynamic entropy, is dissociated from the other and independently shown to pass stringent statistical tests with the other held as fixed; a “gold standard” mode involves changing the coincidental interaction between these two strong emulators of randomness by either cutting or shuffling prior to each draw. Gold standard modes may be useful in cryptography and in assessing tests themselves. One PRNG contains O ( 10 629675 ) states in the entropy pool, another generates integers approximately 50% faster than the Advanced Encryption Standard (AES) PRNG with similar empirical performance, and a third generates full double-precision floats at speeds comparable to unsigned integer rates of the AES PRNG.
Transcriptome Profiling of Elaeis guineensis Jacq. Under Heat Stress Condition

A bstract — Global warming is predicted to have a generally negative effect on agriculture activity. High temperatures stress could affect plant growth negatively. Developing plants with improved thermal tolerance using molecular genetic approaches could mitigate these heat stress effects. Elite palms with better adaptation to heat can be selected from germplasm using molecular markers. Transcriptome profiling by RNA sequencing is a way to find molecular markers of a particular trait. The objective of the study was to obtain differential expressed genes (DEGs) related to the heat stress effect. RNA sequencing results were displayed using heat maps which were useful for visualizing the expression of genes across the high-temperature treatment and control samples. In total, where 1,087 genes were identified involved in oil palm heat stress. Sixty-four (64) of them were differentially expressed, consisted of seventeen (17) up-regulated and forty-seven (47) down-regulated. The uni-gene was summarized in Gene Ontology (GO) categories, namely: biological process, molecular function, and cellular component, subsequently divided into 53 sub-categories. The single organism process, biosynthetic process, response to stimulus, oxidation-reduction process, and response stress were the five primary sub-categories. Sixty-four genes related to heat stress were found, and eight (12.5%) of them were determined as heat shock protein (HSP) family. The highest transcription level was the uncharacterized gene, a member of the heat response sub-category, and the others up-regulated gene consisted of HSP family gene, Bcl-2-associated athanogene (BAG) family and HIPP gene, slr0575 gene, CML14 gene, and PARP gene.
Comparison of amygdalin and benzaldehyde levels in California almond (Prunus dulcis) varietals

Almonds (Prunus dulcis), are characterized into three flavor phenotypes: bitter, semi-bitter and sweet. Amygdalin is a cyanogenic diglucoside responsible for bitterness in almonds. Studies have shown that amygdalin can hydrolyze to release benzaldehyde, which is the key component of almond aroma. In this study, the amygdalin and benzaldehyde content of fourteen sweet cultivars of almonds from four growing regions in California were determined. Solid-phase extraction and ultra high-pressure liquid chromatography coupled with electrospray triple-quadrupole mass spectrometry (UHPLC-(ESI)MS/MS) were used to determine the amygdalin content in the raw almond kernels. Headspace solid phase microextraction (HS-SPME) coupled with a gas chromatography mass spectrometry (GC/MS) was used to determine the benzaldehyde concentration in raw almond kernels. Saturated salt water was added to the sample to improve the extraction of benzaldehyde in the headspace. Results indicated that the mean concentration of both amygdalin and benzaldehyde are significantly different (p<0.0001) among the fourteen cultivar. Furthermore, a positive correlation was found between the amygdalin and benzaldehyde concentrations among the 14 cultivars. Although 'Nonpareil' cultivars is considered the premier snacking almond, 'Aldrich' has significantly higher concentrations of benzaldehyde in the headspace, the key contributor of the almond aroma.
Simulation of Autoregressive Integrated Moving Average- Generalized Autoregressive Conditional Heteroscedasticity (ARIMA-GARCH) to Forecast Traffic Flow

— Modeling the unprecedented traffic flow data generated by Intelligent Transportation Systems can boost the innovation-capacity of the transportation management systems to drive informed decision-making. Thus, this paper attempts to simulate traffic forecasting techniques that can be adopted in the Philippines to make fact-based decisions into accurate and effective traffic management schemes. In this research, a schematic framework is introduced organized into three stages (Preprocessing, Model Identification and Estimation, and Model Checking) sequentially arranged to comprehensively estimate the best-appropriate model to forecast traffic flow using ARIMA and GARCH models. The Model Identification and Estimation is the conditional stage in the framework that pre-determines if hybrid modeling is necessary based on the given datasets. Various accuracy metrics are also used to find the “best” model and select the optimal values for ARIMA and GARCH models. The proposed framework is simulated in R Programming using the vehicular traffic flow datasets at North Avenue, EDSA northbound, Manila, Philippines. The resulting models, consist of the best fit ARIMA (1,1,3) and GARCH (1,2), are combined as the hybrid model and compared using its prediction results. Based on the visual simulation data, the prediction accuracy result of the ARIMA model outperforms the combined ARIMA-GARCH model given the actual data. Conclusively, the simulation performance provides proof to suggest that the forecasting models are timely tools to predict future traffic flow and aid in making better traffic inventions and schemes.
Developing of keystroke dynamics analyzing systems using a presentation based on state contexts

This aim of the article is to discusses the main static and dynamic user identification methods by keystroke dynamics. As part of the research, a generalized way of representing the process of typing on the keyboard based on the sequential change of the keyboard state was proposed. The definition of the keyboard state context, which is the basis for the dynamic identification procedure, is formulated. The proposed approach will make it possible to apply a variety of static identification methods, significantly expanding the set of methods used for dynamic user identification by keystroke dynamics.