Miracle-dz/UniFAR-FTUs huggingface dataset:
Polychlorinated Biphenyls Interactions with Water—Characterization Based on the Analysis of Non-Covalent Interactions and Energy Partitioning

Although polychlorinated biphenyls (PCBs) have been long banned from use, both they and dioxins are still considered persistent organic pollutants. The reason is twofold: their relative inertness (especially to oxidation) and their ability to accumulate in fat tissue. The current study sheds light on the interactions of PCBs with water, chlorine, and chlorine dioxide. Necessary insight is gained from Atoms in Molecules (AIM) and Non-Covalent Interactions (NCI) index and analyses for the 1:1 complexes of PCBs with water and chlorine (Cl2) molecules. Further, Symmetry-Adapted Perturbation Theory (SAPT) calculations reveal the strength and nature of the intermolecular interactions, and the presence of halogen bonding is demonstrated in AIM, NCI, and SAPT studies. The stability of water, chlorine, and chlorine dioxide (ClO2) complexes with PCBs is discussed using the supramolecular MP2 approach. Finally, analysis of microsolvation shells of PCBs showed the origins of the hydrophobicity and environmental persistence of these chemicals. Our results are applicable to the sustainability of water treatment strategies providing a description of forces and interactions at the molecular level.
Tristaenone A: A New Anti-Inflammatory Compound Isolated from the Australian Indigenous Plant Tristaniopsis laurina

Inspired by ethnopharmacological knowledge, we conducted a bioassay-guided fractionation of the leaves of Tristaniopsis laurina which led to the discovery of a new anti-inflammatory compound, tristaenone A (1). The structure was elucidated by detailed spectroscopic data analysis, and the absolute configuration was established using X-ray crystallography analysis. Tristaenone A (1) suppressed LPS and IFN-γ-induced NO, TNF-α and IL-6 production in RAW 264.7 cells with IC50 values of 37.58 ± 2.45 μM, 80.6 ± 5.82 μM and 125.65 ± 0.34 μM, respectively. It also inhibited NF-κB nuclear translocation by 52.93 ± 14.14% at a concentration of 31.85 μM.
A transport process on graphs and its limiting distributions

Abstract Given a finite strongly connected directed graph $G=(V, E)$ , we study a Markov chain taking values on the space of probability measures on V. The chain, motivated by biological applications in the context of stochastic population dynamics, is characterized by transitions between states that respect the structure superimposed by E: mass (probability) can only be moved between neighbors in G. We provide conditions for the ergodicity of the chain. In a simple, symmetric case, we fully characterize the invariant probability.
Solving cosmological problems of supersymmetric axion models in an inflationary universe

We revisit inflationary cosmology of axion models in the light of recent developments on the inflaton decay in supergravity. We find that all the cosmological difficulties, including gravitino, axino overproduction, and axionic isocurvature fluctuation, can be avoided if the saxion field has large initial amplitude during inflation and decays before big bang nucleosynthesis.
OBSERVATIONS OF THE YOUNG SUPERNOVA REMNANT RX J1713.7−3946 WITH THE FERMI LARGE AREA TELESCOPE

We present observations of the young supernova remnant (SNR) RX J1713.7−3946 with the Fermi Large Area Telescope (LAT). We clearly detect a source positionally coincident with the SNR. The source is extended with a best-fit extension of 0. °55 ± 0. °04 matching the size of the non-thermal X-ray and TeV gamma-ray emission from the remnant. The positional coincidence and the matching extended emission allow us to identify the LAT source with SNR RX J1713.7−3946. The spectrum of the source can be described by a very hard power law with a photon index of Γ = 1.5 ± 0.1 that coincides in normalization with the steeper H.E. S.S. -detected gamma-ray spectrum at higher energies. The broadband gamma-ray emission is consistent with a leptonic origin as the dominant mechanism for the gamma-ray emission.
Carving the Research Proposal

This study aims at assessing the process of writing research proposal with its format and lay out used by different researchers and institutions. Using secondary sources of data, the study embarks the structure of the research proposal discussing with regards to the key sections of the proposal like proposal format provided by various institution, cover page, introduction, literature review, research and research question, research purpose and objectives, significance of the study, limitations and delimitations of the study, research methodology, ethical considerations, timeline, budget estimations and references employing a descriptive research design. Simple descriptive tools, content analysis and tables have been used for analysis of data. A research proposal is a detail description of a proposed study designed to explore a given problem. An excellent carved proposal has more possibility of persuading the evaluation committee on credibility, achievability, practicality and reproducibility of the research design as the evaluation committees may constitute academic colleagues, policy makers, practitioners and lay audience who potentially evaluate the research proposal. The first class research proposal includes practicality, broader linking, crystal clarity and good plan and also contains the concern literatures that support the study as well as writer’s thought explaining all about the time needed to conduct the each stage of the research.
The Re-Identification of Previously Unidentifiable Clinical Non-Tuberculous Mycobacterial Isolates Shows Great Species Diversity and the Presence of Other Acid-Fast Genera

Non-tuberculous mycobacteria that cannot be identified at the species level represent a challenge for clinical laboratories, as proper species assignment is key to implementing successful treatments or epidemiological studies. We re-identified forty-eight isolates of Ziehl–Neelsen (ZN)-staining-positive “acid-fast bacilli” (AFB), which were isolated in a clinical laboratory and previously identified as Mycobacterium species but were unidentifiable at the species level with the hsp65 PCR restriction fragment length polymorphism analysis (PRA). As most isolates also could not be identified confidently via 16S, hsp65, or rpoB DNA sequencing and a nBLAST search analysis, we employed a phylogenetic method for their identification using the sequences of the 16S rDNA, which resulted in the identification of most AFB and a Mycobacterium species diversity not found before in our laboratory. Most were rare species with only a few clinical reports. Moreover, although selected with the ZN staining as AFB, not all isolates belonged to the genus Mycobacterium, and we report for the first time in Latin America the isolation of Nocardia puris, Tsukamurella pulmosis, and Gordonia sputi from sputum samples of symptomatic patients. We conclude that ZN staining does not differentiate between the genus Mycobacterium and other genera of AFB. Moreover, there is a need for a simple and more accurate tree-based identification method for mycobacterial species. For this purpose, and in development in our lab, is a web-based identification system using a phylogenetic analysis (including all AFB genera) based on 16S rDNA sequences (and in the future multigene datasets) and the closest relatives.
Antifeeding and Oviposition Deterrent Effect of Ludwigia spp. (Onagraceae) against Plutella xylostella (Lepidoptera: Plutellidae)

Plants produce a wide variety of bioactive compounds with insecticidal properties, such as secondary metabolites capable of interfering with the nutrition and reproduction of pest species such as Plutella xylostella. Thus, the objective of this study was to evaluate the effects of aqueous and ethanolic extracts of Ludwigia spp. (Onagraceae) on the feeding and oviposition of P. xylostella. Choice bioassays were performed using aqueous and ethanolic extracts. The aqueous extract of L. tomentosa resulted in an approximately 81% reduction in larval feeding compared to that in the control, with an antifeedant index (AI) of 52%. The aqueous and ethanolic extract of L. nervosa acted by stimulating larval feeding. The oviposition was significantly reduced in the kale leaves treated with aqueous and ethanolic extracts of Ludwigia spp. The aqueous extracts promoted an average 90% reduction in oviposition when compared to that in the control, and an oviposition deterrent index (ODI) above 61% was classified as an oviposition deterrent. In addition, ethanolic extracts affected 81% of oviposition, with an ODI above 41%. Bioassays should be performed to clarify the use of aqueous and ethanolic extracts of L. nervosa as they acted as phagostimulants in the feeding tests and as deterrents in the oviposition tests. The phenolic compounds—flavonoids, condensed tannins, and alkaloids—were more abundant in L. nervosa, L. tomentosa, L. sericea, and L. longifolia. The extracts of L. longifolia and L. tomentosa showed the best results, interfering with the host choice for feeding and oviposition in P. xylostella and representing an alternative for the control of diamondback moths.
Noninvasive embedding of single Co atoms in Ge(111)2 × 1 surfaces

We report on a combined scanning tunneling microscopy (STM) and density functional theory (DFT) based investigation of Co atoms on Ge(111)2x1 surfaces. When deposited on cold surfaces, individual Co atoms have a limited diffusivity on the atomically flat areas and apparently reside on top of the upper pi-bonded chain rows exclusively. Voltage-dependent STM imaging reveals a highly anisotropic electronic perturbation of the Ge surface surrounding these Co atoms and pronounced one-dimensional confinement along the pi-bonded chains. DFT calculations reveal that the individual Co atoms are in fact embedded in the Ge surface, where they occupy a quasi-stationary position within the big 7-member Ge ring in between the 3rd and 4th atomic Ge layer. The energy needed for the Co atoms to overcome the potential barrier for penetration in the Ge surface is provided by the kinetic energy resulting from the deposition process. DFT calculations further demonstrate that the embedded Co atoms form four covalent Co-Ge bonds, resulting in a Co4+ valence state and a 3d5 electronic configuration. Calculated STM images are in perfect agreement with the experimental atomic resolution STM images for the broad range of applied tunneling voltages.
Kidney Cancer Prediction Empowered with Blockchain Security Using Transfer Learning

Kidney cancer is a very dangerous and lethal cancerous disease caused by kidney tumors or by genetic renal disease, and very few patients survive because there is no method for early prediction of kidney cancer. Early prediction of kidney cancer helps doctors start proper therapy and treatment for the patients, preventing kidney tumors and renal transplantation. With the adaptation of artificial intelligence, automated tools empowered with different deep learning and machine learning algorithms can predict cancers. In this study, the proposed model used the Internet of Medical Things (IoMT)-based transfer learning technique with different deep learning algorithms to predict kidney cancer in its early stages, and for the patient’s data security, the proposed model incorporates blockchain technology-based private clouds and transfer-learning trained models. To predict kidney cancer, the proposed model used biopsies of cancerous kidneys consisting of three classes. The proposed model achieved the highest training accuracy and prediction accuracy of 99.8% and 99.20%, respectively, empowered with data augmentation and without augmentation, and the proposed model achieved 93.75% prediction accuracy during validation. Transfer learning provides a promising framework with the combination of IoMT technologies and blockchain technology layers to enhance the diagnosing capabilities of kidney cancer.
AI Assistance for Home Surveillance

Home burglaries and house fires occur daily and bring hardships to the victims that suffered from these unfortunate events. Early detection of these situations allows for rapid responses and should always be a highly demanded feature amongst all homeowners. In this study, we propose an AI assistance framework specifically tailored to detect common household features using the home’s pre-existing surveillance cameras. This framework will allow homeowners to implement an extra layer of security on top of their existing hardware. We developed a prototype that detects abnormalities of fires, people, vehicles, and house pets. To the best knowledge of the authors, this is the first application of its kind to collectively monitor such a wide variety of activities to provide a holistic view of the state of home. We have verified the sustainability of the framework to monitor the home in real time.
6G toward Metaverse: Technologies, Applications, and Challenges

Metaverse opens up a new social networking paradigm where people can experience a real interactive feeling without physical space constraints. Social interactions are gradually evolving from text combined with pictures and videos to 3-dimensional virtual reality, making the social experience increasingly physical, implying that more metaverse applications with immersive experiences will be developed in the future. However, the increasing data dimensionality and volume for new metaverse applications present a significant challenge in data acquisition, security, and sharing. Furthermore, metaverse applications require high capacity and ultrareliability for the wireless system to guarantee the quality of user experience, which cannot be addressed in the current fifth-generation system. Therefore, reaching the metaverse is dependent on the revolution in the sixth-generation (6G) wireless communication, which is expected to provide low-latency, high-throughput, and secure services. This article provides a comprehensive view of metaverse applications and investigates the fundamental technologies for the 6G toward metaverse.
Exposing the dressed quark's mass

This snapshot of recent progress in hadron physics made in connection with QCD's Dyson-Schwinger equations includes: a perspective on confinement and dynamical chiral symmetry breaking (DCSB); a pre'cis on the physics of in-hadron condensates; results on the hadron spectrum, including dressed-quark-core masses for the nucleon and Delta, their first radial excitations, and the parity-partners of these states; an illustration of the impact of DCSB on the electromagnetic pion form factor, thereby exemplifying how data can be used to chart the momentum-dependence of the dressed-quark mass function; and a prediction that F_1^{p,d}/F_1^{p,u} passes through zero at Q^2\approx 5m_N^2 owing to the presence of nonpointlike scalar and axial-vector diquark correlations in the nucleon.
Stock Price Prediction through STL Decomposition using Multivariate Two-way Long Short-term Memory

With advancements in machine-learning techniques, stock-price movements can ostensibly be forecasted using time-series data. In this study, several different types of long short-term memory (LSTM) are used to predict the closing prices of Japanese stocks five days into the future. Also, in this study, four different features [i.e., simple moving average (SMA), linear weighted moving average (WMA), exponential WMA (EMA), and the Savitzky–Golay (SG) metric] are generated from daily stock-price data and split into two components (i.e., trend and seasonal) by applying seasonal–trend decomposition using Loess (STL) decomposition. The prediction results are evaluated in terms of return, root-mean-square error (RMSE), mean absolute error (MAE), and other relevant measures of accuracy and relevancy. As a result, the multivariate two-way LSTM model yielded the highest overall performance. With respect to the RMSE and MAE of the training data, the multivariate two-way LSTM was not superior to the other models. However, with respect to RMSE and MAE on the validation data, it was the best. Also, the multivariate two-way LSTM model yielded the highest overall performance in terms of the accuracy of the direction of stock prices.
Indane Based Molecular Motors: UV-Switching Increases Number of Isomers

We describe azophenylindane based molecular motors (aphin-switches) which have two different rotamers of trans-configuration and four different rotamers of cis-configuration. The behaviors of these motors were investigated both experimentally and computationally. The conversion of aphin-switch does not yield single isomer but a mixture of these. Although the trans to cis conversion leads to the increase of the system entropy some of the cis-rotamers can directly convert to each other while others should convert via trans-configuration. The motion of aphin-switches resembles the work of a mixing machine with indane group serving as a base and phenol group serving as a beater. The aphin-switches presented herein may provide a basis for promising applications in advanced biological systems or particularly in cases where on demand disordering of molecular packing has value, such as lipid bilayers.
Next-to-leading order corrections to top quark decays to heavy quarkonia

The decay widths of top quark to S-wave $b\overline{c}$ and $b\overline{b}$ bound states are evaluated at the next-to-leading-order accuracy in strong interaction. Numerical calculation shows that the next-to-leading-order corrections to these processes are remarkable. The QCD renormalization scale dependence of the results is obviously depressed, and hence the uncertainties lying in the leading order calculation are reduced.
Spin-charge soldering from tensor Higgs mechanism

Spin-charge separation, a crucial ingredient in 2D models of strongly correlated systems, is mostly considered in condensed matter applications. In this paper we present a relativistic field-theoretic model in which charged particles of spin $1/2$ emerge by soldering spinless charges and magnetic vortices in a confinement quantum phase transition modeled as a tensor Higgs mechanism. The model involves two gauge fields, a vector one and a two-form gauge field interacting by the topological $BF$-term. When this tensor gauge symmetry is spontaneously broken charges are soldered to the ends of magnetic vortices and thus confined by a linear potential. If the vector potential has a topological $\ensuremath{\theta}$-term with value $\ensuremath{\theta}=\ensuremath{\pi}$, the constituents of this ``meson'' acquire spin $1/2$ in this transition.
Analysis and Design of a Compact Bipolar High-Voltage Short-Pulse Power Supply for DBD Application

As known, a short-pulse excitation voltage with a high rising rate and idle time [At this period, the current of dielectric barrier discharge (DBD) loads is equal to or close to zero] simultaneously is conducive to taking advantage of the potential of DBD loads. However, how to use a simple and classical topology to provide such an excitation voltage is rarely researched and is still an important issue for DBD application fields. The adoption of a set of modes that can generate the excitation voltage in a half-bridge-inverter and the design of a control strategy for the inverter are the main contributions of this article. Through mode analysis, the characteristics of the power supply are discussed, and a design process of the power supply is demonstrated. The simulation and experimental results show that not only an expected bipolar pulse excitation voltage can be generated, but also the soft-switching of all power switches is realized. Compared with other types of power supplies, the potential of the excimer lamp can be well developed with the presented power supply, and the power supply has the advantages of a more compact structure, fewer components and higher working frequency.
D-optimal Mixture Design for Optimized Microencapsulation of Vitamin A Palmitate and Its Characterizations

Food fortification is an effective intervention strategy for combating micronutrient deficiencies. Vitamin A can be fortified in a wide range of food vehicles. In this research work, vitamin A in the form of palmitate (VAP) have been microencapsulated by emulsion technology intended for fortification purposes. D-optimal mixture design approach was applied for optimizing the experimental process parameters. Detailed physico-chemical –thermal characterization of the optimized VAP emulsion was done. VAP content was kept constant as per fortification limit. Desirability ramp function graphs and lab experimentations showed maltodextrin (2.5-2.7), OSA starch (1.5-1.6), Tween 80 (1.5-1.7), Span 40 (2.0-2.2) in terms of percentages gave encapsulation efficiency in the range of 98.2-98.8. The optimized VAP emulsion showed particle size in the range of 940-942 nm, polydispersity index 0.41, zeta potential (ζ) value ranging from -31.25 to -32.01 mv; viscosity and interfacial tension was determined to be 1.561±0.03 mPaS and 22.6 mNm−1 respectively. Low temperature DSC studies (-5ºC to 90ºC) of VAP emulsion showed sharp endothermic peaks of vitamin A that disappeared with further elevation in temperature and some flat thermograms of other excipients. The vitamin A content in VAP emulsion was determined to be 88.45±0.03%, the content being reduced to 86.01±0.04% after storage under accelerated conditions (75ºC, 80% RH). The formulated VAP emulsion showed high encapsulation efficiency and significant stability of the emulsion system.
PHYSICAL PROPERTIES OF THE B AND Be STAR POPULATIONS OF h AND χ PERSEI

We present a study of the B and Be star populations of the double cluster h and χ Persei. Blue optical spectroscopy is used to first measure projected rotational velocity, V sin i, effective surface temperature, Teff, and surface gravity, log g, for B-type sample stars, while available Strömgren photometry is used to calculate Teff and log g for the Be stars showing emission. In our sample of 104 objects for which we measured these stellar parameters, 28 are known or proposed Be stars. Of these Be stars, 22 show evidence of emission at the times of our observations, and furthermore, we find evidence in our data and the literature for at least 8 transient Be stars in the clusters. We find that the Be stars are not rotating near their critical velocity, contrary to the results of studies of similar open clusters. We compare the results of our analysis with other previous studies and find that the cluster members are more evolved than found by Huang & Gies but still retain much of their initial rotational angular momentum.
Reliable High-Voltage Drain-Extended FinFET With Thermoelectric Improvement

In this article, a reliable drain-extended (De) fin-shaped field-effect transistor (DeFinFET) with improved thermal performance and electrical performance is proposed for high-voltage (HV) system-on-chip (SoC) applications at 10-nm technology nodes. The proposed device structure uses the dual split field plate (DS) technique and high thermal conductivity of silicon dioxide (SiO2), which enables significant thermal improvement in DeFinFET. The proposed structure shows an improvement in maximum lattice temperature (<inline-formula> <tex-math notation="LaTeX">${T}_{\text {MAX}}$ </tex-math></inline-formula>) from 473 to 424 K, and an improvement in thermal resistance (<inline-formula> <tex-math notation="LaTeX">${R}_{\text {TH}}$ </tex-math></inline-formula>) from 18.7 to 11.9 K/<inline-formula> <tex-math notation="LaTeX">$\mu \text{W}$ </tex-math></inline-formula>. As a result, effective electron mobility (<inline-formula> <tex-math notation="LaTeX">$\mu _{\text {eff}}$ </tex-math></inline-formula>) is consequently enhanced, which enables the highest ON-current (<inline-formula> <tex-math notation="LaTeX">${I}_{\text {on}}$ </tex-math></inline-formula>) of the proposed device structure compared to the conventional DeFinFET (plate with SiO2) and previous DeFinFET (plate with HfO2). This thermal and electrical co-improvement indicates that the proposed device structure with DS technique could enable the thermal-aware design for next-generation HV SoC application.