Miracle-dz/UniFAR-FTUs huggingface dataset:
GABAA Receptor Modulators with a Pyrazolo[1,5-a]quinazoline Core: Synthesis, Molecular Modelling Studies and Electrophysiological Assays

As a continuation of our study in the GABAA receptor modulators field, we report the design and synthesis of new 8-chloropyrazolo[1,5-a]quinazoline derivatives. Molecular docking studies and the evaluation of the ‘Proximity Frequencies’ (exploiting our reported model) were performed on all the final compounds (3, 4, 6a–c, 7a,b, 8, 9, 12a–c, 13a,b, 14–19) to predict their profile on the α1β2γ2-GABAAR subtype. Furthermore, to verify whether the information coming from this virtual model was valid and, at the same time, to complete the study on this series, we evaluated the effects of compounds (1–100 µM) on the modulation of GABAA receptor function through electrophysiological techniques on recombinant α1β2γ2L-GABAA receptors expressed in Xenopus laevis oocytes. The matching between the virtual prediction and the electrophysiological tests makes our model a useful tool for the study of GABAA receptor modulators.
Green and Integrated Wearable Electrochemical Sensor for Chloride Detection in Sweat

Wearable sensors for sweat biomarkers can provide facile analyte capability and monitoring for several diseases. In this work, a green wearable sensor for sweat absorption and chloride sensing is presented. In order to produce a sustainable device, polylactic acid (PLA) was used for both the substrate and the sweat absorption pad fabrication. The sensor material for chloride detection consisted of silver-based reference, working, and counter electrodes obtained from upcycled compact discs. The PLA substrates were prepared by thermal bonding of PLA sheets obtained via a flat die extruder, prototyped in single functional layers via CO2 laser cutting, and bonded via hot-press. The effect of cold plasma treatment on the transparency and bonding strength of PLA sheets was investigated. The PLA membrane, to act as a sweat absorption pad, was directly deposited onto the membrane holder layer by means of an electrolyte-assisted electrospinning technique. The membrane adhesion capacity was investigated by indentation tests in both dry and wet modes. The integrated device made of PLA and silver-based electrodes was used to quantify chloride ions. The calibration tests revealed that the proposed sensor platform could quantify chloride ions in a sensitive and reproducible way. The chloride ions were also quantified in a real sweat sample collected from a healthy volunteer. Therefore, we demonstrated the feasibility of a green and integrated sweat sensor that can be applied directly on human skin to quantify chloride ions.
New principals in the COVID corridor: an exploratory case study

PurposeThis paper aims to highlight how a group of novice principals in Connecticut and New York used relational, dispositional and situational factors to respond to the COVID-19 pandemic crisis. The study aims to support new principals and educational leaders.Design/methodology/approachUsing Mutch's (2015) dispositional, relational and situational framework to guide the inquiry, this paper uses qualitative methods and interviewing in particular to explore the questions of interest. Six novice principals were each interviewed over the 2020–2021 school year, each interview lasting approximately forty-five minutes. Data were analyzed thematically using both deductive coding techniques and cross comparative analysis.FindingsFindings show that novice principals tended to rely on dispositional factors to respond to the crisis. Additionally, novice principals reported limited responses to the situational factors of the crisis due to restricted access and guidance from the district leadership.Research limitations/implicationsDue to the small sample size and methodological approach, it may be inappropriate to generalize the findings across all novice principals in all settings. Further research in additional settings and larger samples are encouraged to support the proposed findings.Practical implicationsThis paper has several implications for districts and leadership preparation programs. Among these is the need for leadership preparation programs to adjust their curricula to train new principals properly.Originality/valueThis work fills a gap in the research regarding how new principals respond to a crisis. It also provides insights into practice and possible means to enhance the growing population of new principals entering the educational leadership workforce.
Eulerian-Lagrangian simulation of air-steam biomass gasification in a bubbling fluidized bed gasifier

To numerically study biomass gasification in a three-dimensional bubbling fluidized bed, a CFD-DEM (computational fluid dynamics – discrete element method) model with heat transfer and homogeneous and heterogeneous chemical reactions is implemented. An ideal reactor model is used for the air-steam bubbling fluidized bed (BFB) gasification reactor assuming perfectly mixed solids and plug flow. A validated computational particle fluid dynamics (CPFD) model has been applied to investigate the sensitivity analysis of mesh grids as well as to find the optimum number of grids. The result shows that 7452 grid cells are the optimal number of cells for the existence BFB gasifier. The effects of key process operating parameters such as steam to biomass ratio (SB), as well as temperature shows that by enhancing the SB ratio or reactor temperature, gas yields increase. H2 and CO2 concentrations promote by increasing the steam to biomass ratio while CO and CH4 production drop. The optimal value of SB for the gasification process can be found in the range of 0.3 to 1.
Developing an Automated Analytical Process for Disaster Response and Recovery in Communities Prone to Isolation

Today, unpredictable damage can result from extreme weather such as heat waves and floods. This damage makes communities that cannot respond quickly to disasters more vulnerable than cities. Thus, people living in such communities can easily become isolated, which can cause unavoidable loss of life or property. In the meantime, many disaster management studies have been conducted, but studies on effective disaster response for areas surrounded by mountains or with weak transportation infrastructure are very rare. To fill the gap, this research aimed at developing an automated analysis tool that can be directly used for disaster response and recovery by identifying in real time the communities at risk of isolation using a web-based geographic information system (GIS) application. We first developed an algorithm to automatically detect communities at risk of isolation due to disaster. Next, we developed an analytics module to identify buildings and populations within the communities and efficiently place at-risk residents in shelters. In sum, the analysis tool developed in this study can be used to support disaster response decisions regarding, for example, rescue activities and supply of materials by accurately detecting isolated areas when a disaster occurs in a mountainous area where communication and transportation infrastructure is lacking.
Influence of Primary Palatal Surgery on Craniofacial Morphology in Patients with Cleft Palate Only (CPO)—Systematic Review with Meta-Analysis

Background: Cleft palate only (CPO) is the second most prevalent cleft type. Both the cleft and palatal scarring may affect craniofacial growth. The aim of this systematic review was to summarize scientific evidence on effect of palatal surgery on craniofacial morphology in CPO. Methods: A search was conducted in PubMed, PMC, WoS, Scopus, Embase, using the keywords: “cleft palate” AND (“craniofacial morphology” OR “cephalometric analysis”) NOT “lip” with inclusion and exclusion criteria ensuring confident, direct comparison between study groups. The quality assessment was performed with Arrive’s scale for radiologic examinations. Results: Of 713 potential articles, 19 were subjected to qualitative analysis and 17 to meta-analysis, which confirmed reduced SNA in unoperated CPO versus non-cleft individuals. No scientific evidence was found directly assessing the effect of surgery on craniofacial morphology. The negative effect of palatal surgery was seen indirectly: in treated CPO versus non-cleft, the size effect of SNA is bigger than in untreated CPO versus non-cleft. A high heterogeneity came from a few non-European publications. Conclusions: CPO is associated with sagittal maxillary deficiency resulting both from the cleft and from primary surgery, disregarding cleft severity in operated CPO patients. Ethnic differences influence craniofacial morphology in CPO. This research received no external funding. Study protocol number in PROSPERO database: CRD42021268957.
Femtosecond X-ray absorption spectroscopy in warm dense matter

Exploring and understanding ultrafast processes at the atomic level is a scientific challenge. Femtosecond X-ray Absorption Spectroscopy (XAS) is an essential experimental probing technic, as it can simultaneously reveal both electronic and atomic structures, and thus unravel their non-equilibrium dynamic interplay which is at the origin of most of the ultrafast mechanisms. However, despite considerable efforts, there is still no femtosecond X-ray source suitable for routine experiments. Here we show that betatron radiation from relativistic laser-plasma interaction combines ideal features for femtosecond XAS. It has been used to investigate the non-equilibrium transition of a copper sample brought at extreme conditions of temperature and pressure by a femtosecond laser pulse. We measured a rise time of the electron temperature below 100 fs. This first experiment demonstrates the great potential of the betatron source and paves the way to a new class of ultrafast experiments.
Enterprise Operational Resilience with Digitalization Approach amid the COVID-19 Era: An Empirical Assessment

The development of the COVID-19 pandemic has had a devastating impact on one Chinese city that has depended heavily on tourism, which is the core focus of the current study. This article uses phenomenological research methods in qualitative research to conduct semistructured and in-depth interviews with travel agency managers in China Highlights. Through the application of tourism resilience theory in the tourism crisis management domain, this article investigates the performance of China Highlights, a local tourism enterprise in Guilin, China, to restore the functioning and growth of the tourism industry in the postpandemic period. The results show that China's tourism industry is in the early stages of the fast growth stage of economic recovery, and tourism enterprises are faced with a significant challenge in determining how to make sound business choices during the pandemic and after the crisis has passed. It proposes that the tourism resilient theory can serve as a modern crisis management model to facilitate tourism enterprises to revive their performance in times of hardship.
Predicting demand for long-term care using Japanese healthcare insurance claims data

Background Driven by the rapid aging of the population, Japan introduced public long-term care insurance to reinforce healthcare services for the elderly in 2000. Precisely predicting future demand for long-term care services helps authorities to plan and manage their healthcare resources and citizens to prevent their health status deterioration. Methods This paper presents our novel study for developing an effective model to predict individual-level future long-term care demand using previous healthcare insurance claims data. We designed two discriminative models and subsequently trained and validated the models using three learning algorithms with medical and long-term care insurance claims and enrollment records, which were provided by 170 regional public insurers in Gifu, Japan. Results The prediction model based on multiclass classification and gradient-boosting decision tree achieved practically high accuracy (weighted average of Precision, 0.872; Recall, 0.878; and F-measure, 0.873) for up to 12 months after the previous claims. The top important feature variables were indicators of current health status (e.g., current eligibility levels and age), risk factors to worsen future healthcare status (e.g., dementia), and preventive care services for improving future healthcare status (e.g., training and rehabilitation). Conclusions The intensive validation tests have indicated that the developed prediction method holds high robustness, even though it yields relatively lower accuracy for specific patient groups with health conditions that are hard to distinguish.
GLOBULAR CLUSTER SYSTEMS IN BRIGHTEST CLUSTER GALAXIES. III. BEYOND BIMODALITY

We present new deep photometry of the rich globular cluster (GC) systems around the Brightest Cluster Galaxies UGC 9799 (Abell 2052) and UGC 10143 (Abell 2147), obtained with the Hubble Space Telescope (HST) ACS and WFC3 cameras. For comparison, we also present new reductions of similar HST/ACS data for the Coma supergiants NGC 4874 and 4889. All four of these galaxies have huge cluster populations (to the radial limits of our data, comprising from 12,000 to 23,000 clusters per galaxy). The metallicity distribution functions (MDFs) of the GCs can still be matched by a bimodal-Gaussian form where the metal-rich and metal-poor modes are separated by dex, but the internal dispersions of each mode are so large that the total MDF becomes very broad and nearly continuous from [Fe/H] ≃ −2.4 to solar. There are, however, significant differences between galaxies in the relative numbers of metal-rich clusters, suggesting that they underwent significantly different histories of mergers with massive gas-rich halos. Last, the proportion of metal-poor GCs rises especially rapidly outside projected radii , suggesting the importance of accreted dwarf satellites in the outer halo. Comprehensive models for the formation of GCs as part of the hierarchical formation of their parent galaxies will be needed to trace the systematic change in structure of the MDF with galaxy mass, from the distinctly bimodal form in smaller galaxies up to the broad continuum that we see in the very largest systems.
Dimensional Reduction and its Breakdown in the Driven Random Field O(N) Model

We investigate the critical behavior of the driven random field O(N) model. First, from an intuitive argument, we derive a new dimensional reduction property, which predicts that the critical behavior of the driven disordered system at zero temperature is the same as that of the lower dimensional pure system in equilibrium. However, this dimensional reduction breaks down in low enough dimensions due to a nonperturbative effect associated with meta-stable states. By employing the nonperturbative formalism of the functional renormalization group, we derive the flow equation of the renormalized disorder correlator and clarify the condition that the dimensional reduction fails. We also calculate the critical exponents near three dimensions.We investigate the critical behavior of the driven random field O(N) model. First, from an intuitive argument, we derive a new dimensional reduction property, which predicts that the critical behavior of the driven disordered system at zero temperature is the same as that of the lower dimensional pure system in equilibrium. However, this dimensional reduction breaks down in low enough dimensions due to a nonperturbative effect associated with meta-stable states. By employing the nonperturbative formalism of the functional renormalization group, we derive the flow equation of the renormalized disorder correlator and clarify the condition that the dimensional reduction fails. We also calculate the critical exponents near three dimensions.
Slow two-level systems in point contacts

A great variety of experiments, like heat release measurements, acoustic measurements, and transport measurements on mesoscopic samples, have proved that two-level systems (TLSs) play a crucial role in the low-temperature thermal and electric properties of disordered systems. This paper is aimed at reviewing the role of slow TLSs in point contacts. First the theory of point contacts is summarized, concentrating on the discussion of different point-contact models, and on the different regimes of electron flow in the contact, mainly focusing on the ballistic and diffusive limit. The Boltzmann equation is solved in both regimes, and the position dependence of the electrical potential is determined. Then the scattering processes in point contacts are investigated, particularly concentrating on the scattering on slow TLSs. If the electron-assisted transitions between the two states are negligible the electron–two-level system interaction can be treated with a simplified Hamiltonian. The scattering on such slow TLSs causes non-linearity in the current–voltage characteristics of the point contact, which can be determined using Fermi's Golden Rule. These calculations are presented showing both the contribution of elastic and inelastic scattering, and including the dependence on the position of the TLS, and on the effect of high-frequency irradiation. These results are used to discuss the differences between these slow TLSs and the fast centres which may be described by the two-channel Kondo model. The available experimental results are analysed, distinguishing between the effects due to the different types of TLSs.
Prediction of Intracranial Hypertension and Brain Tissue Hypoxia Utilizing High-Resolution Data from the BOOST-II Clinical Trial

The current approach to intracranial hypertension and brain tissue hypoxia is reactive, based on fixed thresholds. We used statistical machine learning on high-frequency intracranial pressure (ICP) and partial brain tissue oxygen tension (PbtO2) data obtained from the BOOST-II trial with the goal of constructing robust quantitative models to predict ICP/PbtO2 crises. We derived the following machine learning models: logistic regression (LR), elastic net, and random forest. We split the data set into 70–30% for training and testing and utilized a discrete-time survival analysis framework and 5-fold hyperparameter optimization strategy for all models. We compared model performances on discrimination between events and non-events of increased ICP or low PbtO2 with the area under the receiver operating characteristic (AUROC) curve. We further analyzed clinical utility through a decision curve analysis (DCA). When considering discrimination, the number of features, and interpretability, we identified the RF model that combined the most recent ICP reading, episode number, and longitudinal trends over the preceding 30 min as the best performing for predicting ICP crisis events within the next 30 min (AUC 0.78). For PbtO2, the LR model utilizing the most recent reading, episode number, and longitudinal trends over the preceding 30 min was the best performing (AUC, 0.84). The DCA showed clinical usefulness for wide risk of thresholds for both ICP and PbtO2 predictions. Acceptable alerting thresholds could range from 20% to 80% depending on a patient-specific assessment of the benefit-risk ratio of a given intervention in response to the alert.
Information Disclosure in the Era of Voice Technology

Whenever consumers interact with technological devices connected to the internet, they disclose information about themselves. The rapid diffusion of voice technology is shifting the way consumers interact with technological devices from typing or clicking to speaking. This article offers a comprehensive analysis of how this shift from manual to oral communication with technology affects information disclosure. The authors first consider verbal disclosure and provide a conceptual framework that explicates how voice technology can influence consumers’ propensity to reveal information about themselves through semantic content disclosed voluntarily. They then consider nonverbal disclosure and provide an analysis of how voice technology enables the collection of information revealed unintentionally through vocal paralanguage and ambient sound. The article offers testable propositions and poses open research questions that can serve as impetus for future research. In addition, it provides insights to marketers regarding how to navigate voice technology as a source of consumer information and to policy makers regarding how to better protect consumer privacy in interactions with voice technology.
The Force of Symmetry

Preface Introduction 1. A matter of force 2. Stalking the wild rainbow 3. Light 4. Maybe I'm Heisenberg 5. Catch a falling quantum 6. Quantum beanbags 7. Symmetries 8. Quantum relativity: nothing is relative 9. Life, the Universe and everything 10. The physics of a tablecloth 11. Colour me red, green and blue 12. Smashing symmetry 13. How much is infinity minus infinity? 14. Excelsior! The ascent to SU( ) 15. A modest reading proposal.
Map-Matching Error Identification in the Absence of Ground Truth

Map-matching of trajectory data has widespread applications in vehicle tracking, traffic flow analysis, route planning, and intelligent transportation systems. Map-matching algorithms snap a set of trajectory points observed by a satellite navigation system to the most likely route segments of a map. However, due to the unavoidable errors in the recorded trajectory points and the incomplete map data, map-matching algorithms may match points to incorrect segments, leading to map-matching errors. Identification of these map-matching errors in the absence of ground truth can only be achieved by visual inspection and reasoning. Thus, the identification of map-matching errors without ground truth is a time-consuming and mundane task. Although research has focused on improving map-matching algorithms, to our knowledge no attempts have been made to automatically classify and identify the residual map-matching errors. In this work, we propose the first method to automatically identify map-matching errors in the absence of ground truth, i.e., only using the recorded trajectory points and the map-matched route. We have evaluated our method on a public dataset and observed an average accuracy of 91% in automatically identifying map-matching errors, thus helping analysts to significantly reduce manual effort for map-matching quality assurance.
Complete controllability of quantum systems

Sufficient conditions for complete controllability of N-level quantum systems subject to a single control pulse that addresses multiple allowed transitions concurrently are established. The results are applied in particular to Morse and harmonic-oscillator systems, as well as some systems with degenerate energy levels. Controllability of these model systems is of special interest since they have many applications in physics, e.g., Morse and harmonic oscillators serve as models for molecular bonds, and the standard control approach of using a sequence of frequency-selective pulses to address a single transition at a time is either not applicable or only of limited utility for such systems.