Miracle-dz/UniFAR-FTUs huggingface dataset:
Statistical Mechanics and Dynamics of Liquids in and out of Equilibrium

Liquids display an astonishing array of phenomena that, at first glance, seem to have little in common. In this thesis, we study two of these phenomena. The first is the hydrophobic effect, the well-known tendency of oil and water to demix and the driving force for biological assembly. The second is the glass transition, the process by which liquids cooled to very low temperatures become increasingly viscous until succumbing to structural arrest and displaying the rigidity of a solid with none of its microscopic ordering.In the first part of this thesis, we expand upon our prior understanding of the hydrophobic effect. We study the behavior of water in the confined volume created by a pair of RNA helices at the inter-subunit interface of the bacterial ribosome, which provides an opportunity to apply our contemporary understanding of the hydrophobic effect, first detailed by Lum, Chandler, and Weeks almost twenty years ago, to a context that is less idealized than previously studied. We also discuss and improve upon computational models of hydrophobic solvation, expanding their applicability to more complicated solute geometries.In the second part of this thesis, we study the glass transition from the perspective of the East model, a kinetically constrained lattice model of glass formers. We review and derive a number of results for East model glasses that we expect to emerge in more realistic, atomistic models of glass formers. We choose one such model and drive it out of equilibrium by cooling, forming a glass. We then check whether our East model predictions are correct. Of particular interest to us is whether inter-excitation correlations emerge out of equilibrium, a key prediction of the East model. Our atomistic results suggest that they do not, forcing us to reconsider our conceptual mapping between the highly abstract East model and more realistic models of glass formers.The common thread in these seemingly disparate parts of the thesis is the importance of collective fluctuations in liquid-state phenomena. The hydrophobic effect is a physical consequence of liquid-vapor interfacial fluctuations near extended hydrophobic surfaces, while dynamics in supercooled liquids, the precursors to glasses, are dominated by small, collective motions of particles in an otherwise jammed material. The importance of fluctuations in these and other liquid-state phenomena make the tools of statistical mechanics particularly suitable to their study. In this thesis, we employ these tools in the service of furthering our understanding of the liquid state.
Nonlinear optical investigations in nine-atom silver quantum clusters and graphitic carbon Nitride Nanosheets

Absorption saturation due to surface plasmon resonance affects the optical limiting efficiency of metal nanoparticles (NPs) by raising the limiting threshold to higher laser fluences. It has been shown that in gold, compared to the larger NPs, smaller quantum clusters (QCs) exhibit better optical limiting with lower limiting thresholds due to the absence of absorption saturation. Here we report optical limiting properties of two novel materials, namely, nine-atom silver (Ag9) QCs and graphitic carbon nitride (GCN) nanosheets. The relatively large nonlinear absorption of Ag9 QCs compared to Ag NPs is revealed from open-aperture Z-scan measurements carried out using 532 nm, 5 ns laser pulses. Optical nonlinearity in the QCs arises mostly from free carrier absorption and a relatively weak saturable absorption. The superior limiting efficiency of Ag9 QCs is complemented by excellent chemical stability, which makes silver quantum clusters ideal candidates for optical limiting applications. The two-dimensional .
A normalized score-based weighted PageRank algorithm on ranking prediction of basketball games

Ranking of sports teams has always been significant to sponsors, coaches, as well as audiences. Prevailing prediction methods investigate probabilities by taking into account of different kinds of attributes (e.g. field goals, fields goal attempts) in order to establish a detail-based mechanism for analyzing the capability among competing teams. The different types of activation and inhibition actions between athletes provide a considerable challenge in the framework of network analysis. Moreover, these attributes interactions might add up the substantial redundancy to network frame as well. This paper proposes a weighted PageRank algorithm based on the normalized basketball match scores from a macroscopic point of view. Taking Chinese Basketball Association and Chinese University Basketball Association as examples, the developed approach takes into account the win/lose nature of interactions between each pair of competing teams in the framework of PageRank network. We also evolve a weighted network model for the network matrix which highlights the capability difference of teams whose PageRank probabilities are most sensitive with respect to the scores of the two competing teams. The chance of championship of teams can be better demonstrated by the PageRank probabilities. The results show that our method achieves more precise predicting result than that of original PageRank algorithm and Hypertext-Induced Topic Search algorithm.
Social inclusion through mixed-income development: Design and practice in the Choice Neighborhoods Initiative

ABSTRACT Social Inclusion is an emerging term, used to encompass ideas of equity, social, economic and civic participation, and the proactive protection of human rights. In the United States, one potential vehicle for social inclusion is the development of mixed-income communities. Using a process perspective, this study explores the design and practice of social inclusion in the context of mixed-income development, by conducting a qualitative analysis of the federal Choice Neighborhoods Initiative. Utilizing a combined content analysis and grounded theory analysis of archival grant reports and conducted interviews, this study aims to answer the question: How do mixed-income development practitioners design and practice social inclusion? Through this analysis, the study generates a process theory of social inclusion through mixed-income development, identifying 57 practices, processes, programs, and structures that mixed-income development practitioners utilize in designing and practicing social inclusion.
Scalable Data Processing for Prediction, Batch Computation and Analysis and Response Times using Google BigQuery

Computing a complex dataset analysis is tedious task because distributed resource management is difficult task. Google disperses the registering utilized by BigQuery across process assets powerfully which implies that we don't need to oversee figure asset, for example, bunches, register motor, stockpiling structure. Fighting commitments customarily require custom estimating (and esteeming) of unequivocal procedure gatherings, and this can change after some time which can be trying. Since Google logically assigns resources, costs are dynamic too. Google offers both a compensation all the more just as costs emerge elective where you pay for the data brought into BigQuery and subsequently per question costs. Since BigQuery is a totally managed organization, the backend game plan and tuning is managed by Google. This is much more direct than battling plans that anticipate that you should pick a number and sort of gatherings to make and to administer after some time. BigQuery consequently recreates information between zones to empower high accessibility. It additionally naturally load adjusts to give ideal execution and to limit the effect of any equipment disappointments. So getting benefits of BigQuery we did complex data analysis in huge amount of data set within a friction of second. Our result is showing the capability of our research work in the field of scalable data processing.
Effect of Covid-19 Pandemic in Construction Labor Productivity: A Quantitative and Qualitative Data Analysis

This research aims to identify and analyze the various factors affecting construction labor productivity covering the period from December 9, 2020 - January 31, 2021, a year after it was declared Covid-19 a pandemic. Due to the pandemic effect, the local government units in four selected study areas imposed intermittent Enhance Community Quarantine on all places to control the Coronavirus spread in compliance with the health department protocol. Fifty-five questionnaires returned out of 63 distributed are tabulated according to each group-related factor. The correlation analysis resulted in the highest coefficient value of 0.89 between the CTDEO and contractor groups. Meaning, most respondents have the same perception of the factors affecting construction's low labor productivity. Besides, results depicted that the absence of health workers on the construction site ranked 1st in the health & safety provision factor group with an RII of 0.97, followed by no safety engineers on the construction project sites with an RII of 0.93. From all the seven groups of factors, the health and safety group-related factors ranked 1st with an RII of 0.81, next, the schedule compression group with an RII of 0.78. Hypothesis testing asserted that working six days per week was one of the significant factors affecting labor productivity on the contractor's side, suggested by more than 50% of the respondents. The workforce group-related factors with an RII of 0.77 demonstrated a slight difference with the schedule compression group-related factors. Thus, the Covid-19 pandemic has a significant effect on the essential factors affecting construction's low labor productivity.
Intra Prediction and Mode Coding in VVC

This paper presents the intra prediction and mode coding of the Versatile Video Coding (VVC) standard. This standard was collaboratively developed by the Joint Video Experts Team (JVET). It follows the traditional architecture of a hybrid block-based codec that was also the basis of previous standards. Almost all intra prediction features of VVC either contain substantial modifications in comparison with its predecessor H.265/HEVC or were newly added. The key aspects of these tools are the following: 65 angular intra prediction modes with block shape-adaptive directions and 4-tap interpolation filters are supported as well as the DC and Planar mode, Position Dependent Prediction Combination is applied for most of these modes, Multiple Reference Line Prediction can be used, an intra block can be further subdivided by the Intra Subpartition mode, Matrix-based Intra Prediction is supported, and the chroma prediction signal can be generated by the Cross Component Linear Model method. Finally, the intra prediction mode in VVC is coded separately for luma and chroma. Here, a Most Probable Mode list containing six modes is applied for luma. The individual compression performance of tools is reported in this paper. For the full VVC intra codec, a bitrate saving of 25% on average is reported over H.265/HEVC using an objective metric. Significant subjective benefits are illustrated with specific examples.
Unraveling Crystal Structure and Transport Properties of Fast Ion Conducting SrCo0.9Nb0.1O3−δ

SrCo0.9Nb0. 1O3−δ (SCN) has been investigated for oxygen transport membrane and solid oxide fuel cell applications as it is more stable than the state-of-the-art Ba0.5Sr0. 5Co0.8Fe0. 2O3−δ (BSCF) material. Here, the crystal structure and transport properties of SCN were systematically investigated. Combined neutron and high-temperature X-ray powder diffraction analyses over the temperature range of 25–800 °C showed that the crystal structure of SCN belongs to the tetragonal space group P4/mmm with the unit cell ac × ac × 2ac, where ac is the lattice parameter of the cubic perovskite at temperatures <160 °C. The tetragonal (P4/mmm) to cubic (Pm3m) phase transition occurred in SCN with increasing temperature. This phase transition affected the electrical conductivity, whereas the impact on the magnetic susceptibility was not significant. The surface exchange and diffusion coefficients of SCN in the temperature range of 600–850 °C were characterized by electrical conductivity relaxation and oxygen permeation m.
The Effect of High-Fidelity Simulation–Based Learning in Acute Cardiorespiratory Physical Therapy—A Mixed-Methods Systematic Review

Supplemental Digital Content is Available in the Text. Background and Purpose. Simulation-based learning is commonly used in physical therapy education. However, given the financial cost and resources required to provide high-fidelity simulation (HFS)-based learning, it is necessary to determine its effectiveness. Therefore, the purpose of this study was to investigate the effect of HFS-based learning using computerized mannequins on clinical performance and preparedness of physical therapy students and physical therapists in acute cardiorespiratory physical therapy. Methods. We undertook a mixed-methods systematic review and meta-analysis. Search strategies were used to find articles in electronic databases. Reference lists of studies were also searched. Included studies investigated the effect of HFS-based learning on physical therapy students' and physical therapists' clinical performance and preparedness in acute cardiorespiratory physical therapy and included the use of computerized mannequins. Both quantitative and qualitative studies were considered. Results. A total of 12 trials from 11 articles were included. Quantitative findings of pooled studies indicated a small, but not statistically significant, effect of simulation training on clinical performance of physical therapy students' when compared with traditional learning methods (Hedges' g = 0.18; 95% confidence interval, −0.18 to 0.64; P = .07; I2 = 57%). Qualitative data were synthesized into 4 themes in which HFS positively impacted students' preparedness: familiarization with the clinical setting, real-world learning in a controlled environment, learning about patient safety, and self-efficacy and confidence. Only the theme of self-efficacy and confidence were able to be integrated with quantitative data, demonstrating a positive effect of HFS on students' and physical therapists' self-efficacy and confidence. Discussion and Conclusion. High-fidelity simulation involving the use of computerized mannequins improves students' preparedness for clinical practice but does not improve students' clinical performance, although limited evidence exists for physical therapists' preparedness and clinical performance, indicating that further research of physical therapy clinicians is required.
Comparative study of regression testing tools feature on unit testing

Regression testing is one of the essential activities in software development. Regression testing ensures that the software is still working properly and new software modifications do not cause unexpected defects. Most of the software industry carries out regression testing on the system under test (SUT) by utilizing tools automatically rather than being done manually which requires a long time estimation and ineffective process. Currently, there are many regression testing tools and variations that make software practitioners need additional time and money to analyze the capabilities of the tools. This paper is a comparative study of the capabilities of tools in carrying out the regression testing process in the java programming language. Each tool has experimented with user input data in the form of a SUT program and a test case that has the same characteristics. Furthermore, the tool’s performance is observed based on the feature evaluation criteria. The criteria used are support platform and technology, test case selection, and functionality. The results showed the similarities and differences in the features of the selected testing tool in performing regression testing. Thus it can help users to choose regression testing tools that suit their needs.
Light Stress and Photoprotection in Green algae, Mosses and Diatoms

The molecular bases of responses to light excess in photosynthetic organisms having different evolutionary histories and belonging to different lineages are still not completely characterized. Therefore I explored the functions of photoprotective antennae in green algae, mosses and diatoms, together with the role of the two xanthophyll cycles present in diatoms.I studied the Light Harvesting Complex Stress-Related (LHCSR) proteins in different organisms. In the green alga Chlamydomonas reinhardtii, LHCSR3 is a protein important for photoprotection. I used site-specific mutagenesis in vivo and in vitro and identified three residues of LHCSR3 that are responsible for its activation.With the moss Physcomitrella patens I studied the in vitro spectroscopic and quenching characteristics of different pigment-binding mutants of the protein LHCSR1, focusing in particular on chlorophylls A2 and A5.LHCSRs in diatoms are named LHCXs, and in Phaeodactylum tricornutum I found that multiple abiotic stress signals converge to regulate the LHCX content of cells, providing a way to fine-tune light harvesting and photoprotection.The other main driver of photoprotection in diatoms is the xanthophyll cycle. Here I found that the accumulation of viola- and zeaxanthin in P. tricornutum have a negative effect in the development of NPQ, showing that zeaxanthin does not participate in the enhancing of NPQ in diatoms.Thanks to these studies done on different organisms, we gained a deeper knowledge on the shared characteristics and on the peculiar features about photoprotection in green algae, mosses and diatoms.
Bayesian estimation-based sentiment word embedding model for sentiment analysis

Sentiment word embedding has been extensively studied and used in sentiment analysis tasks. However, most existing models have failed to differentiate high ‐ frequency and low ‐ frequency words. Accordingly, the sentiment information of low ‐ frequency words is insufficiently captured, thus resulting in inaccurate sentiment word embedding and degradation of overall performance of sentiment analysis. A Bayesian estimation ‐ based sentiment word embedding (BESWE) model, which aims to precisely extract the sentiment information of low ‐ frequency words, has been proposed. In the model, a Bayesian estimator is constructed based on the co ‐ occurrence probabilities and sentiment probabilities of words, and a novel loss function is defined for sentiment word embedding learning. The experimental results based on the sentiment lexicons and Movie Review dataset show that BESWE outperforms many state ‐ of ‐ the ‐ art methods, for example, C&W, CBOW, GloVe, SE ‐ HyRank and DLJT1, in sentiment analysis tasks, which demonstrate that Bayesian estimation can effectively capture the sentiment information of low ‐ frequency words and integrate the sentiment information into the word embedding through the loss function. In addition, replacing the embedding of low ‐ frequency words in the state ‐ of ‐ the ‐ art methods with BESWE can significantly improve the performance of those methods in sentiment analysis tasks.
Effect of Melatonin and Insulin on Oxidative Stress in Spleen, Impairment of Adherent Leukocytes Activity and Inflammatory Response in Lps Treated Diabetic Mice

The present study evaluated the protective effect of melatonin and insulin from LPS and diabetes-induced oxidative stress, impairment of peritoneal leukocyte functions, and inflammation in Swiss albino mice. Diabetes was induced in Swiss albino mice by streptozotocin treatment. Experimental mice were divided into two sets. Set-1 contains control, diabetic, melatonin, insulin, and melatonin+insulin groups of mice. In set-II, all groups of mice were challenged with a single dose of LPS (50mg/mice). Lipid peroxidation, antioxidant enzymes (SOD, Catalase, GPx) activity, non-enzymatic GSH level, Nrf2/HO-1 expression, phagocytic index, intracellular ROS generation, and proinflammatory cytokines were measured. Diabetic as well as LPS treated diabetic mice showed significantly increased lipid peroxidation, suppressed antioxidant defence system, and down regulated Nrf2/HO-1 expression in spleen tissues; suppressed phagocytic index and increased ROS generation in adherent peritoneal leukocytes and increased level of circulatory proinflammatory cytokines. Either treatment of melatonin or insulin significantly improved the harmful effects caused by both of LPS treatment and of diabetes in experimental mice. Simultaneous treatment of melatonin and insulin effectively ameliorated the LPS, as well as diabetes, caused oxidative load, impairment of adherent peritoneal leukocyte function, and improved the level of circulatory proinflammatory cytokines. In the present study, we have noted that combined treatment of melatonin and insulin was more effective in attenuation of diabetes and LPS induced devastating effects in laboratory mice. Therefore, the present study may suggest a combinatorial approach in the therapeutic use of melatonin and insulin to improve such devastating conditions.
Impact of Pharmacotherapy on Sexual Function of Persons with Schizophrenia

Schizophrenia is one among the most serious mental illnesses. Sexual dysfunction is commonly found associated with schizophrenia. Few studies have tried to identify the factors contributing to this issue. Pharmacotherapy for schizophrenia has an impact on sexual function of patients with schizophrenia. However, this is an area which is less explored. The current study tries to find out the impact of pharmacotherapy on sexual function of persons with schizophrenia in both positive symptoms subtype and negative symptoms subtype, before, after one month and after three months of pharmacotherapy. Quantitative approach with experimental design was selected to conduct the current study. The participants comprised of 60 male patients, 36 of them with positive symptoms subtype and 24 with negative symptoms subtype were selected through purposive sampling. Data were collected by administering Personal data sheet, Structured Clinical Interview for DSM – IV, Axis I disorder – SCID, Structured Clinical Interview – Positive and Negative Syndrome Scale (SCI – PANNS) and Brief Sexual Function Inventory (BSFI). The tools were administered to the same patients during first visit, after one month and after three months visits. Collected data were analysed using SPSS. The result reveal that there is significant difference in sexual functions before pharmacotherapy, after one month and after three months of pharmacotherapy in patients with both positive and negative symptoms of Schizophrenia.
Reusable Cellulose‐Based Hydrogel Sticker Film Applied as Gate Dielectric in Paper Electrolyte‐Gated Transistors

A new concept for reusable eco‐friendly hydrogel electrolytes based on cellulose is introduced. The reported electrolytes are designed and engineered through a simple, fast, low‐cost, and eco‐friendly dissolution method of microcrystalline cellulose at low temperature using an aqueous LiOH/urea solvent system. The cellulose solution is combined with carboxymethyl cellulose, followed by the regeneration and simultaneous ion incorporation. The produced free standing cellulose‐based electrolyte films exhibit interesting properties for application in flexible electrochemical devices, such as biosensors or electrolyte‐gated transistors (EGTs), because of their high specific capacitances (4–5 µF cm−2), transparency, and flexibility. Indium–gallium–zinc‐oxide EGTs on glass with laminated cellulose‐based hydrogel electrolytes (CHEs) as the gate dielectric are produced presenting a low working voltage (<2 V), showing an on–off current ratio (Ion/off) of 106, a subthreshold swing lower than 0.2 V dec−1, and saturation mobility (μSat) reaching 26 cm2 V−1 s−1. The flexible CHE‐gated transistors on paper are also demonstrated, which operate at switching frequencies up to 100 Hz. Combining the flexibility of the EGTs on paper with the reusability of the developed CHEs is a breakthrough toward biodegradable advanced functional materials allied with disposable/recyclable and low‐cost electronic devices.