Miracle-dz/UniFAR-FTUs huggingface dataset:
Food and bile micelle binding of quaternary ammonium compounds

Background and Purpose Physiologically-based biopharmaceutics modeling (PBBM) has been widely used to predict the oral absorption of drugs. However, the prediction of food effects on oral drug absorption is still challenging, especially for negative food effects. Marked negative food effects have been reported in most cases of quaternary ammonium compounds (QAC). However, the mechanism has remained unclear. The purpose of the present study was to investigate the bile micelle and food binding of QACs as a mechanism of the negative food effect. Experimental Approach Trospium (TRS), propantheline (PPT), and ambenonium (AMB) were selected as model QAC drugs. The oral absorption of these QACs has been reported to be reduced by 77% (TRS), > 66% (PPT), and 79% (AMB), when taken with food. The fasted and fed state simulated intestinal fluids (FaSSIF and FeSSIF, containing 3 and 15 mM taurocholic acid, respectively) with or without FDA breakfast homogenate (BFH) were used as the simulated intestinal fluid. The unbound fraction (fu) of the QACs in these media was measured by dynamic dialysis. Key Results The fu ratios (FeSSIF/ FaSSIF) were 0.67 (TRS), 0.47 (PPT), and 0.76 (AMB). When BFH was added to FeSSIF, it was reduced to 0.39 (TRS), 0.28 (PPT), and 0.59 (AMB). Conclusion These results suggested that bile micelle and food binding play an important role in the negative food effect on the oral absorption of QACs.
The effects of income tax on the unemployment rate in the United States

This study investigates the correlation between state income tax and unemployment rates across the United States. Using panel data in 50 states pertaining to the period from 2006 to 2022 with different regression models, the results suggest that the state corporate and personal income tax rates are positively correlated with the state unemployment rate. Specifically, a 1% decrease in the personal income tax rate may lead to a 0.712% decrease in the state unemployment rate, and a 1% decrease in the corporate income tax rate may cause a drop of 0.328% in the state unemployment rate. In addition, the results show that a personal income tax hike is associated with an increase of 1.532% in the state unemployment rate, and a corporate income tax hike may increase the state unemployment rate by 0.78%. The results of this study are relevant in the context of increasing government spending in the US and the world. Policymakers and government officials may not want to abuse the tax policy to fund the budget deficits.
Optimal Shaping of the MMC Circulating Currents for Preventing AC-Side Power Oscillations From Propagating Into HVdc Grids

A constrained optimization problem based on the Lagrange multipliers method is formulated to derive the circulating current references of modular multilevel converters (MMCs) directly in abc coordinates. The resulting analytic expressions for calculating the circulating current reference signals are designed to eliminate oscillations in the dc-side power flow, independently of the ac-side operation of the MMC. As a result of the constrained optimization, the circulating currents are shaped to optimally utilize the degrees of freedom provided by the internal energy buffering capacity of the MMC, to effectively decouple the ac-grid conditions from the dc bus. This property of the proposed control method makes it especially suitable for preventing oscillations due to unbalanced ac-grid voltage conditions from propagating into multiterminal high-voltage dc systems. It is shown that the power flow at the dc-side of the MMC will be most effectively decoupled from ac-side transients if the desired steady-state power flow is imposed by acting directly on the circulating current references instead of by acting on the ac-side current references. The operation of an MMC controlled by the proposed approach is demonstrated by simulation studies, verifying the ability to keep the dc power flow free of second harmonic oscillations, independently of the power control objectives applied for calculating the ac-side current references of the converter.
WAVS: The Wide Area Variability Survey

The Wide Area Variability Survey (WAVS) project used the CFH12k mosaic camera as the world's largest time series photometer to obtain images of a 0.33 square degree galactic field with a time resolution of 3 minutes over 2 nights of observations. The main aim of the WAYS project was to try and differentiate between the current competing models of cataclysmic variable (CV) population and evolution by obtaining an unbiased sample using a characteristic that all known CVs exhibit. All CVs show 'flickering' in their lightcurves, that is stochastic variations in luminosity with an amplitude of tenths of a magnitude on timescales of minutes to hours, and it is this characteristic that the WAYS project exploits. Lightcurves for each of the 52000 objects in the WAYS field were created and searched for variability. Spectroscopic observations using the Nordic Optical Telescope (NOT) were carried out to further investigate candidate objects. In searching for variability on this timescale it was apparent that the WAYS project would also discover many variables of other types which may also be of great interest. Thus, the secondary goal of the WAYS project was to investigate these objects and obtain population statistics wherever possible. This thesis gives an introduction to various types of stellar variability and covers the observable characteristics of CV s in some depth. Competing models of CV evolution are considered and the goals and strategies of the WAYS programme are outlined in more detail. An account of the process of obtaining high quality photometry and spectroscopy is given, both in the general case and in the more specific case applicable to the WAYS data and the methods used to search for variability in the WAYS sample are discussed. The WAYS project has currently discovered 229 new variable objects and the lightcurves of these systems are presented in Appendices A to C. Some of these objects are discussed in detail, but for others accurate classification is difficult without more data, although a tentative classification is made. Currently the WAYS project has not discovered any new CVs and the relevance of this null result is considered. However, 30 possible flickering objects have been identified.
Radiative Forcing of Climate Changes in the Vertical Distribution of Ozone

The authors describe a simple method for evaluating the radiative forcing of surface temperature caused by changes in the vertical distribution of ozone. The method employs a parameterization based on one-dimensional radiative-convective equilibrium calculations; these calculations predict that the surface temperature should warm in response to both decreases in ozone above 30 km and increases in ozone below 30 km. The parameterization is used to investigate the response of surface temperature to observed changes in the vertical distribution of ozone at northern mid-latitudes. The authors show that the observed ozone trends, taken at face value, suggest a cooling of the surface temperature at northern mid-latitudes during the 1970s equal in magnitude to about half the warming predicted for CO{sub 2} for the same time period. However, the measurement uncertainty of the observed trends is large, with the best estimates for mid-latitude cooling being {minus}0.05 {plus minus}0.05. The surface cooling is caused by ozone decreases in the lower stratosphere, which outweigh the warming effects of ozone increases in the troposphere. The results obtained differ from predictions based on one-dimensional photochemical model simulations of ozone trends for the 1970s, which suggest a warming of the surface temperature equal to {approximately}20% of themore » warming contributed by CO{sub 2}. Also, the ozone decreases observed in the lower stratosphere during the 1970s produce atmospheric cooling by several tenths of a degree in the 12- to 20-km altitude region over the northern mid-latitudes. This temperature decrease is larger than the cooling due to CO{sub 2} and thus may obscure the expected stratospheric CO{sub 2} greenhouse signature. « less
Unleashing the financial aspect of Covid-19: How organizations managed the crisis?

Abstract Globally the COVID-19 pandemic has had a significant impact on both individuals and organizations. Challenges on the financial, psychological, and physical levels have been felt, especially in the business sector. The purpose of this research is to examine how COVID-19 has financially affected firms in Pakistan and the United States. In order to do this, surveys and interviews with experts in various business disciplines were carried out to utilize convenience and snowball sampling techniques. Partial least squares (Smart PLS) statistical analysis employing structural equation modeling was used in the research. The results showed that COVID-19 greatly impacted the workers’ financial and psychological health. The research also demonstrated that moderators were crucial in lessening the pandemic’s effects. Discussion in this research also includes the study’s ramifications and practical implications.
The Potential of Digested Sludge-Assimilating Microflora for Biogas Production from Food Processing Wastes

Food processing wastes (FPWs) are residues generated in food manufacturing, and their composition varies depending on the type of food product being manufactured. Therefore, selecting and acclimatizing seed microflora during the initiation of biogas production is crucial for optimal outcomes. The present study examined the biogas production capabilities of digested sludge-assimilating and biogas-yielding soil (DABYS) and enteric (DABYE) microflorae when used as seed cultures for biogas production from FPWs. After subculturing and feeding these microbial seeds with various FPWs, we assessed their biogas-producing abilities. The subcultures produced biogas from many FPWs, except orange peel, suggesting that the heterogeneity of the bacterial members in the seed microflora facilitates quick adaptation to FPWs. Microflorae fed with animal-derived FPWs contained several methanogenic archaeal families and produced methane. In contrast, microflorae fed with vegetable-, fruit-, and crop-derived FPWs generated hydrogen, and methanogenic archaeal populations were diminished by repeated subculturing. The subcultured microflorae appear to hydrolyze carbohydrates and protein in FPWs using cellulase, pectinase, or protease. Despite needing enhancements in biogas yield for future industrial scale-up, the DABYS and DABYE microflorae demonstrate robust adaptability to various FPWs.
HOCD: Overlapping Community Detection based on Hypergraph Convolutional Neural Networks

Community structure is one of the universal topological attributes in complex networks. Finding community structure is the basic task of complex network analysis. Community detection is designed to divide the network into multiple substructures, which plays an important role in understanding the network and revealing the potential function of the network. As the amount of data increases, the network becomes more complex. In particular, nodes in a network may have multiple identities, such as node features and whether communities overlap. In recent years, many community detection methods based on deep learning have made great progress. However, the problem of these works is that the representation ability of models is limited. How to design an efficient and powerful representation model is very important. We have noticed that the hypergraph model can detect the higher-order relationship in the data. We use the powerful representation ability of the hypergraph convolutional network and apply it to the task of community detection, and finally realize our idea, and our method has achieved the best performance in the experiment.
Edge Truncation Effect Suppression of Phased Cavity-Backed Stacked Patch Array

A wide-band and wide-angle stacked patch phased array antenna with a cavity-back configuration is proposed in this letter. The array can feature an operating frequency bandwidth of 21.3% with voltage standing wave ratio of less than 2.5 when scanning up to ±60° in both E- and H-planes. The unit is backed by an aluminum cavity to enhance the scanning performance of the array. To restrain the edge truncation effect of the patch array, a novel solution has been proposed by adding perfect electric condition boundaries and slots at the edges of the cavity in each direction respectively. This solution has been validated to improve the total efficiency of the array compared to the original design in both planes under finite-by-infinite condition. A 10 × 10 prototype has been manufactured and measured to verify the design.
The Effect of a Bacillus Probiotic and Essential Oils Compared to an Ionophore on the Rumen Microbiome Composition of Feedlot Cattle

Simple Summary Consumer preferences are demanding the removal of antibiotic growth promoters from animal diets. To meet the demand of animal protein for the growing human population, alternative feed additives, such as probiotics and essential oils, need to be investigated to increase the overall efficiency of farm animals. The microorganisms in the rumen are important to the functioning of the animal as they produce the majority of energy the animal uses for production. In this study, the effect of essential oils and a probiotic was compared to the effect of monensin, an antibiotic growth promoter, on the rumen microbiome. There were no substantial differences in the effect of the two natural feed additives compared to monensin on the microorganisms in the rumen. These feed additives hold potential as alternatives to the use of antibiotic growth promoters; large scale production studies are needed to confirm growth performance. Abstract The rising concern of antibiotic growth promoter use in livestock has necessitated the investigation into alternative feed additives. The effect of a probiotic and essential oils to an ionophore on the rumen microbiome composition of Bonsmara bulls raised under feedlot conditions was compared. Forty-eight Bonsmara weaners were allocated to four groups: a group with basal diet (CON) and three groups supplemented with monensin (MON), probiotic (PRO), and essential oils (EO). During the 120 days feeding period, rumen content was collected from four animals per group within each phase via a stomach tube for 16S rRNA and internal transcribed spacer (ITS) sequencing as well as volatile fatty acid analysis. In the starter phase, MON had a significantly lower acetate to propionate ratio and a higher Succinivibrionaceae abundance. The abundance of Lachnospiraceae was significantly higher in EO compared to MON. In the finisher phase, PRO had a significantly higher bacterial diversity. The alpha diversity did not differ between the fungal populations of the groups. The abundance of Proteobacteria was the lowest in PRO compared to the other groups. Limited variation was observed between the rumen microbiome composition of monensin compared to the other treatment groups, indicating that these alternatives can be considered.
Incorporating context into non-autoregressive model using contextualized CTC for sequence labelling

Connectionist Temporal Classification (CTC) loss has become widely used in sequence modeling tasks such as Automatic Speech Recognition (ASR) and Handwritten Text Recognition (HTR) due to its ease of use. CTC itself has no architecture constraints, but it is commonly used with recurrent models that predict letters based on histories in order to relax the conditional independent assumption. However, recent sequence models that incorporate CTC loss have been focusing on speed by removing recurrent structures, hence losing important context information. This thesis presents Contextualized Connectionist Temporal Classification (CCTC) loss, which induces prediction dependencies in non-recurrent and non-autoregressive neural networks for sequence modeling. CCTC allows the model to implicitly learn the language model by predicting neighboring labels via multi-task learning. Experiments on ASR and HTR tasks in two different languages show that CCTC models offer improvements over CTC models by 2.2-8.4% relative without incurring extra inference costs.
Microstructured Light Fields for Optical Trapping: Zero Order Continuous Vector Frozen Waves in the Rayleigh Regime

This paper investigates, for the first time in the literature, the optical forces exerted by a new class of non-diffracting beams on Rayleigh (dipole) scatterers, envisioning applications e.g. in optical trapping and micromanipulation, atom guiding, particle sorting and so on. Such microstructured light fields can be designed to provide a wide variety of longitudinal intensity patterns along the optical (longitudinal) axis and on the micrometer scale, being constructed from a continuous superposition of Bessel beams. Coined "continuous vector Frozen Waves" (CVFWs), here we focus on their linear polarized zero-order versions, studying radial and longitudinal optical forces in situations involving different paraxiality conditions, including absorbing characteristics and distinct refractive indices of the scatterers. Power requirements reveal that the strength and spatial profile of the optical forces here found are within those expected for an effective trapping and manipulation of very small dielectric particles.
Study of Tunable Dielectric Permittivity of PBDB-T-2CL Polymer in Ternary Organic Blend Thin Films Using Spectroscopic Ellipsometry

The ellipsometric analyses reported in this paper present a novelty by bringing an in-depth optical investigation of some ternary organic blends. This study focuses on the tunability and control of the relative permittivity of active layers by varying the weight ratio of blended materials spin-coated as thin films. To investigate this, an extensive approach based on spectroscopic ellipsometry was conducted on ternary blend (D:A1:A2) thin films, involving a donor [D = chlorinated conjugated polymer (PBDB-T-2Cl)] and two acceptor materials [A1 = a non-fullerene (ITIC-F) and A2 = a fullerene (PCBM)]. The refractive index constitutes a key parameter that exposes insights into the feasibility of photovoltaic cells by predicting the trajectory of light as it transits the device. In this term, higher obtained refractive indexes support higher absorption coefficients. Notably, the dielectric constant can be rigorously tuned and finely calibrated by modest variations in the quantity of the third element, resulting in considerable modifications. Moreover, the inclusion of fullerene in blends, as the third element, results in a smooth topographical profile, further refining the surface of the film. From an electrical point of view, the ternary blends outperform the polymer thin films. The synergistic interaction of constituents emphasizes their potential to enhance solar conversion devices.
60-GHz Scalable LTCC Phased Array With Compact Symmetric Hybrid Feeding Network for Antenna-in-Package Application

In this article, a 60-GHz phased array with a compact symmetric hybrid feeding network in low-temperature co- fired ceramic (LTCC) technology is proposed. To improve the bandwidth and cross-polarization level, a magnetoelectric (ME) dipole with a strip and five pairs of slots is designed. Meanwhile, a theoretical model is developed to provide physical insight into the working mechanism of the ME-dipole element. To reduce the feeding loss and the element gain variation in the phased array, a symmetric hybrid microstrip (MS)/substrate-integrated waveguide (SIW) feeding network is proposed. The ME-dipole element achieves a measured <inline-formula> <tex-math notation="LaTeX">$\vert {S} _{\mathbf {11}}\,\,\vert < -10$ </tex-math></inline-formula> dB and a stable gain of 4.6 ± 0.7 dBi from 55.3 to 67 GHz. By combining the ME-dipole element and the hybrid feeding network, a <inline-formula> <tex-math notation="LaTeX">$4\times $ </tex-math></inline-formula> 4 antenna-in-package (AiP) phased array based on four <inline-formula> <tex-math notation="LaTeX">$2\times $ </tex-math></inline-formula> 2 scalable subarrays is proposed. The total dimension is <inline-formula> <tex-math notation="LaTeX">$14.75\times 14.75\times0.855$ </tex-math></inline-formula> mm. The measured results show that the fractional impedance bandwidth (<inline-formula> <tex-math notation="LaTeX">$\vert {S} _{\mathbf {11}} \vert < -10$ </tex-math></inline-formula> dB) of each element is <inline-formula> <tex-math notation="LaTeX">$\ge 21.4$ </tex-math></inline-formula>% with <inline-formula> <tex-math notation="LaTeX">$\le \pm $ </tex-math></inline-formula>0.73-dBi element-to-element gain variation and ~16.9-dBi array peak gain (including ~0.35-dB simulated interconnection loss).
Lived Experience of Business School Faculty in post COVID-19 New Normal

Two years of COVID-19 pandemic was a unique experience for many of us. The impact of the pandemic in the academic sector was distinct. This study explored the impact of pandemic on business schools and business school teaching through the examination of the lived experience of business school faculty members. The Hermeneutic phenomenology was used to capture the lived experience of the faculties who were involved in online teaching during pandemic and are teaching in the post COVID-19 new normal at graduate and undergraduate level in different business schools in Nepal. The data were collected through in depth interviews. The analysis of the data revealed four themes: (1) Not ready for hybrid mode, (2) Possibility opened up by online experience, (3) Challenge to maintain academic standard, and (4) Measures to tackle behavioral change among students. The findings suggest that COVID-19 and the time after directed business education towards transformation. However, the Nepali business school and business school faculty members have a long ground to cover. The implication and limitation of the study have been indicated.
An application of reinforcement learning to credit scoring based on the logistic Bandit framework

This study applies reinforcement learning to credit scoring by using the logistic bandit framework. The credit scoring and the credit underwriting are modeled into a single sequential decision problem where the credit underwriter takes a sequence of actions over an indefinite number of time steps. The traditional credit scoring approach considers the model construction separately from the underwriting process. This approach is identified as a greedy algorithm in the reinforcement learning literature, which is commonly believed to be inferior to an efficient reinforcement learning approach such as Thompson sampling. This is true under the simple setting, i.e., granting credit to a single borrower per action while the pool of the borrowers is fixed. However, under the more realistic scenario where these two conditions are relaxed, the greedy approach can outperform Thompson sampling since the greedy algorithm does not commit too early to an inferior action as it does in the simple setting. Still, the efficient exploration feature of Thompson sampling is beneficial. When the borrower characteristics are captured by a large number of features, the exploration mechanism enables Thompson sampling to outperform the greedy algorithm. The results from the simulation study permit a deeper understanding of the reinforcement learning approaches towards the logistic bandits, especially in the setting of credit scoring and credit underwriting processes.