Miracle-dz/UniFAR-FTUs huggingface dataset:
Process Related Impurities In Anti-Diabetic Drug Linagliptin

During the Linagliptin process development, several related substances in the range of 0.05% to 0.15% were observed by high performance liquid chromatography [HPLC] method. Liquid chromatography mass spectrometry [LC-MS] study was performed to identify the molecular mass of these impurities. The origin of these impurities was investigated. These impurities were synthetically prepared and characterized by IR, NMR and Mass analyzes. They were co-injected for their further confirmation. These impurities are 8-[( S )-3-Aminopiperidin-1-yl]-7-(but-2-ynyl)-3-methyl-1-[(4-methylquinazolin-2-yl)methyl]-1 H -purine-2,6(3 H ,7 H )-dione (Impurity-I), 7-(But-2-ynyl)-3-methyl-1-[(4-methylquinazolin-2-yl)methyl]-8-(piperidin-3-ylamino)-1 H -purine-2,6(3 H ,7 H )-dione (Impurity-II), 8-[( R )-3-Aminopiperidin-1-yl]-3-methyl-1,7-bis((4-methylquinazolin-2-yl)methyl)-1 H -purine-2,6(3 H ,7 H )-dione (Impurity-III), 8-[( R )-3-Aminopiperidin-1-yl]-1-(but-2-ynyl)-3-methyl-7-[(4-methylquinazolin-2-yl)methyl]-1 H -purine-2,6(3 H ,7 H )-dione (Impurity-IV), 1,7-Di(but-2-ynyl)-3-methyl-8-[( R )-3-(methyleneamino) piperidin -1-yl]-1 H -purine-2,6(3 H ,7 H )-dione (Impurity-V), 7-(But-2-ynyl)-8-(dimethylamino)-3-methyl-1-[(4-methylquinazolin-2-yl)methyl]-1 H -purine-2,6(3 H ,7 H )-dione (Impurity-VI) and 8-[( R )-3-Aminopiperidin-1-yl]-7-[( E )-3-bromobut-2-enyl]-3-methyl-1-[(4-methylquinazolin-2-yl)methyl]-1 H -purine-2,6(3 H ,7 H )-dione (Impurity-VII).
Peer mentoring experience on becoming a good doctor: student perspectives

Background PASS is a peer-led structured academic mentoring program designed to provide academic assistance for new students in their transition from college to university studies and also for students struggling in certain units. This study aims to establish acquired skills by peer leaders associated with peer-led mentoring via the PASS program, and to explore the role played by these acquired skills in their journey to become a successful doctor. Methods Study participants were forty selected second-year undergraduate medical students at Monash University Malaysia with commendable examination results. Validated pre-test and post-test questionnaires were administered to explore changes in the level of communication, leadership, professional, and pedagogical skills before and after participation in peer mentoring program. Qualitative analysis of focused group interviews was performed by an independent investigator to identify how the skills developed as a peer mentor may help with becoming a good doctor. Major themes were identified with the thematic-analysis approach. Results Thirty-eight students completed the pre-test and post-test questionnaires. Peer leaders reported improvement in oral and written skills for teaching; increased confidence to give constructive feedback; better stress management; efficient time management; improved interpersonal skills; and enhanced problem-solving and critical thinking capabilities. Eight major themes were identified from the interview and peer leaders reported positive experience of working in diverse environments and shouldering of responsibilities. Conclusions Peer-led mentoring provides a good opportunity for medical students to shoulder responsibilities as a leader and offers an experience of managing a team of their peers and juniors which in turn may enhance their communication, interpersonal, and leadership skills.
EFFECTS OF IONIC STRENGTH ON CHEMISORPTION AND POTENTIAL‐DETERMINING SORPTION OF PHOSPHATE BY SOILS

Summary Amounts of inorganic phosphate (P) sorbed by two unfertilized soils, during times less than required to reach equilibrium, were affected by the ionic strength and cation species of the matrix solution. For non-equilibrium conditions the amounts of P sorbed increased with increasing ionic strength and were greater with Ca2+ than Na+. For higher P additions, resulting in equilibrium solution P concentrations greater than 30 to 40μrnole 1−1, the effects of the matrix solution on P sorption were maintained at equilibrium, whereas at lower P additions the dependence of sorption on matrix solution composition was eliminated at equilibrium. Equilibrium sorption isotherms for each soil and matrix solution were described by three Langmuir equations, which corresponded to distinct concentration ranges or regions (I, II, and III) on the overall isotherm. The free energies of sorption (ΔG) for each region, were essentially independent of the soil matrix solution. The sorption maxima for regions I and II of the isotherm for a particular soil were also virtually independent of the matrix solution used. The sorption maximum for region III, however, was markedly dependent on the matrix solution, implying a potential-determining (p.d.) sorption mechanism.
Sample size calculations for single‐arm survival studies using transformations of the Kaplan–Meier estimator

In single‐arm clinical trials with survival outcomes, the Kaplan–Meier estimator and its confidence interval are widely used to assess survival probability and median survival time. Since the asymptotic normality of the Kaplan–Meier estimator is a common result, the sample size calculation methods have not been studied in depth. An existing sample size calculation method is founded on the asymptotic normality of the Kaplan–Meier estimator using the log transformation. However, the small sample properties of the log transformed estimator are quite poor in small sample sizes (which are typical situations in single‐arm trials), and the existing method uses an inappropriate standard normal approximation to calculate sample sizes. These issues can seriously influence the accuracy of results. In this paper, we propose alternative methods to determine sample sizes based on a valid standard normal approximation with several transformations that may give an accurate normal approximation even with small sample sizes. In numerical evaluations via simulations, some of the proposed methods provided more accurate results, and the empirical power of the proposed method with the arcsine square‐root transformation tended to be closer to a prescribed power than the other transformations. These results were supported when methods were applied to data from three clinical trials.
Personal Disability Identity Measurement: Self-Worth and Personal Meaning

Author(s): Zapata, Mercedes | Advisor(s): Worrell, Frank | Abstract: In this study, I examined validity evidence for a new disability identity scale, Personal Disability Identity Scale–Self-Worth and Meaning, in a sample of 525 adults with visual impairment (VI) or blindness. Personal disability identity (PDI) refers to feelings about having a disability as well as incorporation of disability status into overall self-concept (Dunn a Burcaw, 2013). Pre-existing measures of PDI (Darling a Heckert, 2010; Hahn a Belt, 2004) operationalize three factors of the PDI concept (i.e., Affirmation, Denial, Pride), which has been theorized to encompass more domains (Dunn a Burcaw, 2013; Forber-Pratt, Lyew, Samples, a Mueller, 2017). The Self-Worth and Meaning subscales were intended to capture previously unexplored PDI domains, including self-worth as a person with a disability (Putnam, 2005) and personal meaning found in the experience of disability (Dunn a Burcaw, 2013). Exploratory and confirmatory factor analyses supported the structural validity of Self-Worth and Meaning scores as well as an overarching four-factor structure of PDI scores composed of Pride/Affirmation, Acceptance (versus Denial), Self-Worth, and Positive Personal Meaning (i.e., Meaning). Correlational analyses between Self-Worth, Meaning, and existing PDI measures supported the convergent and divergent validity of Self-Worth and Meaning scores. Further correlational analyses between Self-Worth and Meaning subscales and indicators of well-being (i.e., satisfaction with life, anxiety/depression) offered support for the external validity of Self-Worth and Meaning. This dissertation contributes to the literature on disability identity by offering an expanded empirical model of PDI as well as a new PDI measure that is derived from models of disability identity that had not been explored empirically (Dunn a Burcaw, 2013; Putnam, 2005).
SOBA: Session optimal MDP-based network friendly recommendations

Caching content over CDNs or at the network edge has been solidified as a means to improve network cost and offer better streaming experience to users. Furthermore, nudging the users towards low-cost content has recently gained momentum as a strategy to boost network performance. We focus on the problem of optimal policy design for Network Friendly Recommendations (NFR). We depart from recent modeling attempts, and propose a Markov Decision Process (MDP) formulation. MDPs offer a unified framework that can model a user with random session length. As it turns out, many state-of-the-art approaches can be cast as subcases of our MDP formulation. Moreover, the approach offers flexibility to model users who are reactive to the quality of the received recommendations. In terms of performance, for users consuming an arbitrary number of contents in sequence, we show theoretically and using extensive validation over real traces that the MDP approach outperforms myopic algorithms both in session cost as well as in offered recommendation quality. Finally, even compared to optimal state-of-art algorithms targeting specific subcases, our MDP framework is significantly more efficient, speeding the execution time by a factor of 10, and enjoying better scaling with the content catalog and recommendation batch sizes.
Alternative back contacts in kesterite Cu2ZnSn(S1-xSex)4 thin film solar cells

Molybdenum (Mo) is the most used back contact in Cu2ZnSn(S1-xSex)(4) based solar cells. However, it has been suggested recently that Mo is not stable at the interface with Cu2ZnSn(S1-xSex)(4). In addition, to the best of our knowledge, no experimental study has been carried out so far to test whether solar cells built on another back contact could exhibit better photovoltaic properties. For this purpose, various metals (Au, W, Pd, Pt, and Ni) are deposited on top of Mo, and it is demonstrated that it is possible to synthesize device-quality Cu2ZnSn(S1-xSex)(4) thin films on W, Au, and Pt back contacts. It is shown that that W and Au back contacts allow enhancing the photogenerated current, but that Mo remains the best back contact in terms of power conversion efficiency. (C) 2014 AIP Publishing LLC.
Antioxidant Activity of Ribes multiflorum Kit. ex Roem. & Schult (blackcurrant) Extract

Abstract In this study, the antioxidant contents of Ribes multiflorum Kit. Ex Roem. & Schult (black currant) which was grown in Emir and Kumalar mountains in Afyonkarahisar were investigated. Ribes multiflorum Kit. Ex Roem. & Schult is found on 1700 m at Emir Mountain in Dumluca, on 1400 and 1600 m at Kumalar Mountains in Basören. Antioxidant activities of samples were determined by free radical scavenging effect, chelating activity with Fe +2 and H2O2 inhibition methods. The lower EC50 value, the higher antioxidant power. In the presence of metal ions, super reactive hydroxyl radical may be formed by Fenton reaction. The findings obtained in the present work indicated that the Ribes multiflorum are potential source of natural antioxidant. Their antioxidant properties probably depend on concentration of sample.
3d Image Reconstruction of Frog Virus 3 At 2.6nm

Frog virus 3 (FV3), a member of the genus Ranavirus (family Iridoviridae), was isolated from the leopard frog Rana pipiens. Members of this genus are recognized pathogens of amphibians, reptiles and fish and have been associated with declines of amphibians in the United Kingdom and the USA. Neutron-scattering studies showed that FV3 virions are composed of four concentric layers: an outer lipid envelope containing protein VP58; an icosahedral capsid shell with major capsid protein VP48; an inner lipid membrane with VP63 and 44; and a central core of dsDNA (∼170 kbps) and associated proteins. The FV3 genome has a terminally-redundant and circularly-permuted sequence. Naked virions (i.e. without the envelope lipid) contain more than 20 different proteins and about 9% lipid, which is required for infectivity. to date, structural information about FV3 has primarily been obtained in electron microscopy studies by means of thin-sectioning and negative staining techniques.
High-sensitivity Millimeter Imaging of Molecular Outflows in Nine Nearby High-mass Star-forming Regions

We present a study of molecular outflows using six molecular lines (including 12CO/13CO/C18O/HCO+ (J = 1−0) and CS/SiO (J = 2−1)) toward nine nearby high-mass star-forming regions with accurate known distances. This work is based on the high-sensitivity observations obtained with the 14 m millimeter telescope of the Purple Mountain Observatory in Delingha. The detection rate of outflows (including 12CO, 13CO, HCO+, and CS) is 100%. However, the emission of SiO was not detected for all sources. The full line widths (ΔV) at 3σ above the baseline of these molecular lines have the relationship > . 12CO and HCO+ can be used to trace relatively high-velocity outflows, while 13CO and CS can be employed to trace relatively low-velocity outflows. The dynamical timescales of the 13CO and CS outflows are longer than those of the 12CO and HCO+ outflows. The mechanical luminosities, masses, mass-loss rates and forces of all outflows (including 12CO, 13CO, HCO+, and CS) are correlated with the bolometric luminosities of their central IRAS sources.
Anomalous Wetting Layer at the Au(111) Surface

In this paper we present a microscopic picture of the interface between liquid water and a Au(111) surface at room temperature conditions, as obtained from ab initio molecular dynamics simulations. We find that the first wetting layer has peculiar structural and electronic features that can be revealed only by considering the dynamical evolution of the system. Surface phonons and molecular vibrations lead to instantaneous charge density distortions that are pivotal to explain the features of such an atypical wetting layer, and, in turn, the surface hydrophilicity.
Rethinking FUN: Frequency-Domain Utilization Networks

The search for efficient neural network architectures has gained much focus in recent years, where modern architectures focus not only on accuracy but also on inference time and model size. Here, we present FUN, a family of novel Frequency-domain Utilization Networks. These networks utilize the inherent efficiency of the frequency-domain by working directly in that domain, represented with the Discrete Cosine Transform. Using modern techniques and building blocks such as compound-scaling and inverted-residual layers we generate a set of such networks allowing one to balance between size, latency and accuracy while outperforming competing RGB-based models. Extensive evaluations verifies that our networks present strong alternatives to previous approaches. Moreover, we show that working in frequency domain allows for dynamic compression of the input at inference time without any explicit change to the architecture.
The Effect of Differential Attentional Focus Strategies on the Performance of Military Elite Shooters

Methods This study is semiexperimental with an intragroup design. A number of 10 military marksmen (30-42 years old) with at least 10 years of experience in shooting performed under four attentional focus strategies in a counterbalanced design. In each strategy, two blocks (each consisting of 20 trials) were conducted. Shooters' performance was recorded using SCATT device and analyzed using the factorial variance analysis with repeated measure. Results Results showed that the interactional effects of internal-external/relevant-irrelevant focuses of attention were significant on shooting record, shooting accumulation, and stability on the target center. Results suggest that the external-relevant attentional focus strategies were more effective than other focus strategies. Conclusion The results of the study support the hypothesis that external-relevant attentional focus produced better scores, better accumulation, more stability at the target center, and less average fluctuation. Therefore, this attentional focus strategy improves performance precision of military elite shooters.
Measuring the Current Distribution with Sub-Millimeter Resolution in PEFCs II. Impact of Operating Parameters

In the first paper of this series, an experimental technique for measuring the current-density distribution with a resolution better than the sub-millimeter scale of the channel and rib structures in the flow-field plates of polymer electrolyte fuel cells (PEFCs) was introduced. This method is extended to the determination of local membrane resistance with the same spatial resolution in the present paper. The combined measurement of current and resistance allows for investigating the interaction of mass- and charge-transport processes, which determine the local rate distribution across the domain of channels and ribs. Therewith, the influence of relevant operating parameters such as reactant composition, dew points, and cell compression on local current generation is investigated. The results show that the distribution of water and oxidant across the channel and rib are the main reasons for significant current gradients on a scale smaller than a millimeter. Humidity variation mainly affects the membrane resistance under the channel, while reactant concentration predominantly influences current generation under the rib-covered cell area.
Combining Deep Transfer Learning with Signal-image Encoding for Multi-Modal Mental Wellbeing Classification

The quantification of emotional states is an important step to understanding wellbeing. Time series data from multiple modalities such as physiological and motion sensor data have proven to be integral for measuring and quantifying emotions. Monitoring emotional trajectories over long periods of time inherits some critical limitations in relation to the size of the training data. This shortcoming may hinder the development of reliable and accurate machine learning models. To address this problem, this paper proposes a framework to tackle the limitation in performing emotional state recognition on multiple multimodal datasets: 1) encoding multivariate time series data into coloured images; 2) leveraging pre-trained object recognition models to apply a Transfer Learning (TL) approach using the images from step 1; 3) utilising a 1D Convolutional Neural Network (CNN) to perform emotion classification from physiological data; 4) concatenating the pre-trained TL model with the 1D CNN. Furthermore, the possibility of performing TL to infer stress from physiological data is explored by initially training a 1D CNN using a large physical activity dataset and then applying the learned knowledge to the target dataset. We demonstrate that model performance when inferring real-world wellbeing rated on a 5-point Likert scale can be enhanced using our framework, resulting in up to 98.5% accuracy, outperforming a conventional CNN by 4.5%. Subject-independent models using the same approach resulted in an average of 72.3% accuracy (SD 0.038). The proposed CNN-TL-based methodology may overcome problems with small training datasets, thus improving on the performance of conventional deep learning methods.
Protein-Surface Interactions with Coarse-Grain Simulation Methods

Protein-Surface Interactions with Coarse-Grain Simulation Methods Shuai Wei Department of Chemical Engineering Doctor of Philosophy The interaction of proteins with surfaces is a major process involved in protein microarrays. Understanding protein-surface interactions is key to improving the performance of protein microarrays, but current understanding of the behavior of proteins on surfaces is lacking. Prevailing theories on the subject, which suggest that proteins should be stabilized when tethered to surfaces, do not explain the experimentally observed fact that proteins are often denatured on surfaces. This document outlines several studies done to develop a model which is capable of predicting the stabilization and destabilization of proteins tethered to surfaces. As the start point of the research, part of this research showed that the stability of five mainly-alpha, orthogonal-bundle proteins tethered to surfaces can be correlated to the shape of the loop region where the tether is placed and the free rotation ability of the part of proteins near surfaces. To test the expandability of the protein stability prediction pattern derived for mainly-alpha, orthogonal-bundle proteins, same analysis is performed for proteins from other structure motifs. Besides the study in these small two-state proteins, a further analysis of surface-induced change of folding mechanism is also studied with a multistate lysozyme protein 7LZM. The result showed that by tethering a protein on a surface, the melting temperature of a part of the protein changed, which leads to an avoidance of the meta-stable state. Besides the change of folding mechanism, by tethering the lysozyme protein to a certain site, the protein could both keep a stable structure and a good orientation, allowing active sites to be available to other proteins in bulk solution. All the work described above are done with a purely repulsive surface model which was widely used to roughly simulate solid surfaces in protein microarrays. For a next-level understanding of protein-surface interactions, a novel coarse-grain surface model was developed, parameterized, and validated according to experimental results from different groups. A case study of interaction between lysozyme protein 7LZM and three types of surfaces with the novel model has been performed. The results showed that protein stabilities and structures are dependent on the types of surfaces and their different hydrophobicities. This result is consistent with previously published experimental work[1].
Probability distribution function of the aperture mass field with large deviation theory

In the context of tomographic cosmic shear surveys, a theoretical model for the one-point statistics of the aperture mass (Map) is developed. This formalism is based on the application of the large deviation principle to the projected matter density field and more specifically to the angular aperture masses. The latter holds the advantage of being an observable that can be directly extracted from the observed shear field and to be, by construction, independent from the long wave modes. Furthermore we show that, with the help of a nulling procedure based on the so-called BNT transform, it is possible to build observables that depend only on a finite range of redshifts making them also independent from the small-scale modes. This procedure makes predictions for the shape of the one-point Probability Distribution Function of such an observable very accurate, comparable to what had been previously obtained for 3D observables. Comparisons with specific simulations reveal however inconsistent results showing that synthetic lensing maps were not accurate enough for such refined observables. It points to the need for more precise dedicated numerical developments whose performances could be benchmarked with such observables. We furthermore review the possible systematics that could affect such a formalism in future weak-lensing surveys like Euclid, notably the impact of shape noise as well as leading corrections coming from lens-lens couplings, geodesic deviation, reduced shear and magnification bias.