Miracle-dz/UniFAR-FTUs huggingface dataset:
Harmonic emission spectra and attosecond pulse generation from helium atom driven by the mid-infrared nonhomogeneous field

ABSTRACT The generations of the high-order harmonics and the attosecond pulses from helium atom driven by the mid-infrared symmetric and asymmetric nonhomogeneous field have been theoretically investigated. It is found that (i) due to the surface plasmon polaritons in the metallic nanostructure, the extensions of the harmonics from the positive and the negative laser amplitudes, or only from the positive laser amplitude can be found for the cases of symmetric and asymmetric nonhomogeneous fields, respectively. (ii) The wavelength scalings of the harmonic cutoff and the harmonic yield show that the harmonic cutoff and the harmonic yield can be extended and decreased with the increase in laser wavelength, respectively. However, due to the limit of the gap size of the nanostructure, the threshold value of the harmonic cutoff can be achieved for a given gap size of the nanostructure. (iii) By adding a weak terahertz field to the mid-infrared fundamental field with the asymmetric nonhomogeneous effect, the intensity of the harmonic plateau can be enhanced by one order of magnitude, showing a 1280 eV supercontinuum with the single quantum trajectory contribution. Finally, by properly superposing the harmonics, some attosecond X-ray pulses shorter than 35 as can be produced.
On tests of full spectral fitting algorithms

A recent paper by Ge et al. performs a series of experiments with two full spectral fitting codes, pPXF and starlight, finding that the two yield consistent results when the input spectrum is not heavily reddened. For E(B-V) > 0.2, however, they claim starlight leads to severe biases in the derived properties. Counterintuitively, and at odds with previous simulations, they find that this behaviour worsens significantly as the signal-to-noise ratio of the input spectrum increases. This communication shows that this is entirely due to an A_V < 1 mag condition imposed while initializing the Markov chains in the code. This choice is normally irrelevant in real-life galaxy work but can become critical in artificial experiments. Alleviating this usually harmless initialization constraint changes the Ge et al. results completely, as was explained to the authors before their publication. We replicate their spectral fitting experiments, finding much smaller biases. Furthermore both bias and scatter in the derived properties all converge as S/N increases, as one would expect. We also show how the very output of the code provides ways of diagnosing anomalies in the fits. The code behaviour has been documented in careful and extensive experiments in the literature, but the biased analysis of Ge et al. is just not representative of starlight at all.
The Suitability of Hybrid Waveforms for Advanced Gravitational Wave Detectors

The Suitability of Hybrid Waveforms for Advanced Gravitational Wave Detectors Ilana R. MacDonald Doctor of Philosophy Graduate Department of Astronomy & Astrophysics University of Toronto 2013 The existence of Gravitational Waves from binary black holes is one of the most interesting predictions of General Relativity. These ripples in space-time should be visible to ground-based gravitational wave detectors worldwide in the next few years. One such detector, the Laser Interferometer Gravitational-wave Observatory (LIGO) is in the process of being upgraded to its Advanced sensitivity which should make gravitational wave detections routine. Even so, the signals that LIGO will detect will be faint compared to the detector noise, and so accurate waveform templates are crucial. In this thesis, we present a detailed analysis of the accuracy of hybrid gravitational waveforms. Hybrids are created by stitching a long post-Newtonian inspiral to the late inspiral, merger, and ringdown produced by numerical relativity simulations. We begin our investigation with a study of the systematic errors in the numerical waveform, and errors due to hybridization and choice of detector noise. For current NR waveforms, the largest source of error comes from the unknown high-order terms in the post-Newtonian waveform, which we first explore for equal-mass, non-spinning binaries, and also for unequal-mass, non-spinning binaries. We then consider the potential reduction in hybrid errors if these higher-order terms were known. Finally, we investigate the possibility of using hybrid waveforms as a detection template bank and integrating NR+PN hybrids into the LIGO detection pipeline.
Prevalence of Self-Medication in Dental Patients: A Case Study of Saudi Arabia

The present study focuses on the prevalence of self-medication in dental patients’ pre-post dental consultation- a case study of Saudi Arabia. It was a descriptive study based on a structured close-ended interviewer-administered questionnaire. The questionnaire consisted of socio-demographic characteristics and also encompassed reasons, sources, duration, types of medicines used for self-medication, and reasons for hesitancy towards dental consultation. Respondents were selected using a non-probability convenience sampling technique, the data were analyzed using SPSS ver 22. Outcomes of the present study envisage that self-medication is quite prevalent among dental patients using both orthodox and traditional drugs. Results of Bivariate analysis revealed that the majority of patients were not cognizant of the specific dental ailments as revealed in pre-post diagnosis. The multivariate technique of decision trees exhibited that two groups of patients need to be focused on regarding self-medication – those who are less than 20 years of age and Non-Saudi Arabic speakers who are more than 20 years of age. The results of the present study can form the basis for framing future policies for easy accessibility of dental consultation to the populace which may result in containment of self-medication within the Saudian context.
Changes in Healthcare Utilization During the COVID-19 Pandemic and Potential Causes—A Cohort Study From Switzerland

Objectives: To describe the frequency of and reasons for changes in healthcare utilization in those requiring ongoing treatment, and to assess characteristics associated with change, during the second wave of the pandemic. Methods: Corona Immunitas e-cohort study (age ≥20 years) participants completed monthly questionnaires. We compared participants reporting a change in healthcare utilization with those who did not using descriptive and bivariate statistics. We explored characteristics associated with the number of changes using negative binomial regression. Results: The study included 3,190 participants from nine research sites. One-fifth reported requiring regular treatment. Among these, 14% reported a change in healthcare utilization, defined as events in which participants reported that they changed their ongoing treatment, irrespective of the reason. Reasons for change were medication changes and side-effects, specifically for hypertension, or pulmonary embolism treatment. Females were more likely to report changes [Incidence Rate Ratio (IRR) = 2.15, p = 0.002]. Those with hypertension were least likely to report changes [IRR = 0.35, p = 0.019]. Conclusion: Few of those requiring regular treatment reported changes in healthcare utilization. Continuity of care for females and chronic diseases besides hypertension must be emphasized.
Some Localization Properties of the Lp Continuous Wavelet Transform

ABSTRACT We shall prove some simultaneous localization or concentration inequalities for the continuous wavelet transform. We will also show that simultaneous localization in the scale-time(space) is impossible, in the sense that the scale sections of the support of wavelet transform of a nonnull Lp-function can not have finite Lebesgue measure. Finally, some properties of the support of continuous wavelet transform of band-limited functions are studied.
The Experience of Family Medicine Residents during the Early Phase of COVID-19 Pandemic in Tunisia

The COVID-19 pandemic has overwhelmed healthcare systems particularly the training curriculum for post-graduate medical students. Our aim was to assess family medicine residents’ perceived impact of the COVID-19 pandemic on training and medical education in Tunisia. Methods: We conducted a cross-sectional survey among all Tunisian family medicine residents who were in training during the year 2020. Residents starting their first-year residency studies in 2021 were excluded. A structured questionnaire was created and shared via Google Forms. Residents' anonymity and consent were respected. Results: We included 107 residents (85% females). During the first semester of 2020, a significant reduction in workload was reported including working hours (58.9%), patient's flow (65.1%) and elective admission (83%). The workload tended to partially normalize during the second half of the year. The restriction of academic activities (staff, grand rounds, and congresses) was considered the major obstacle (73.8%) hindering residents’ training. About 72% benefited from E-learning during the second period. By the end of 2020, 48.6% of participants reported being infected by the virus. The majority (97.2%) reported feeling anxious, irritable and/or depressed. The pandemic significantly decreased residents' satisfaction with their medical training (4.22±2.15 before the crisis versus 2.78±1.18 during COVID-19) (p<10-3). Conclusion: The COVID-19 pandemic had decreased residents' level of satisfaction with their training and had negatively affected their mental health. The key findings of the present research can be a starting point to provide high quality residency training and to avoid bypassing their weaknesses in the upcoming outbreaks.
Comparison of 2010 Census Nonresponse Follow-Up Proxy Responses with Administrative Records Using Census Coverage Measurement Results

Abstract The U.S. Census Bureau is currently conducting research on ways to use administrative records to reduce the cost and improve the quality of the 2020 Census Nonresponse Followup (NRFU) at addresses that do not self-respond electronically or by mail. Previously, when a NRFU enumerator was unable to contact residents at an address, he/she found a knowledgeable person, such as a neighbor or apartment manager, who could provide the census information for the residents. This was called a proxy response. The Census Bureau’s recent advances in merging federal and third-party databases raise the question: Are proxy responses for NRFU addresses more accurate than the administrative records available for the housing unit? Our study attempts to answer this question by comparing the quality of proxy responses and the administrative records for those housing units in the same timeframe using the results of 2010 Census Coverage Measurement (CCM) Program. The assessment of the quality of the proxy responses and the administrative records in the CCM sample of block clusters takes advantage of the extensive fieldwork, processing, and clerical matching conducted for the CCM.
Sentiment-Based Prediction of Alternative Cryptocurrency Price Fluctuations Using Gradient Boosting Tree Model

In this paper, we analyze Twitter signals as a medium for user sentiment to predict the price fluctuations of a small-cap alternative cryptocurrency called \emph{ZClassic}. We extracted tweets on an hourly basis for a period of 3.5 weeks, classifying each tweet as positive, neutral, or negative. We then compiled these tweets into an hourly sentiment index, creating an unweighted and weighted index, with the latter giving larger weight to retweets. These two indices, alongside the raw summations of positive, negative, and neutral sentiment were juxtaposed to $\sim 400$ data points of hourly pricing data to train an Extreme Gradient Boosting Regression Tree Model. Price predictions produced from this model were compared to historical price data, with the resulting predictions having a 0.81 correlation with the testing data. Our model's predictive data yielded statistical significance at the $p < 0.0001$ level. Our model is the first academic proof of concept that social media platforms such as Twitter can serve as powerful social signals for predicting price movements in the highly speculative alternative cryptocurrency, or "alt-coin", market.
An integrated ancient Chinese philosophical perspective on corporate governance

Although the concept of corporate governance began with the emergence of corporations, the concept of governance can be traced back to ancient China. Currently, discussions of this topic focus mainly on the differences between approaches to and theories about corporate governance and examine their effectiveness, an integrated view that draws on Chinese theories and cultures is missing. This paper attempts to address the gaps by conceptually synthesizing insights from ancient Chinese philosophies to construct an integrated framework; it further defines the legal and ethical constraints while incorporating both an ancient Chinese (i.e., Eastern) philosophical perspective and Western governance elements and both national-level and firm-level variables. Drawing on institutional theory (Scott, 1995, 2004, 2008a, 2008b) and considering the interaction of legal and ethical constraints, a model — the ethical-legal model — constructs and categorizes corporate governance approaches into four types driven by different types of institutions and compares how these approaches are related to different governance perspectives (agent, stewardship and stakeholder). An autonomous (Wu Wei) governance approach is trigged when the cognitive institution is formed as a result of high levels of both legal and ethical constraints and drives autonomous corporate governance with a shift in focus from compliance to commitments
A recursive technique for tracking the feasible parameter set in bounded error estimation

In this paper, a new recursive algorithm is proposed for tracking parameter changes of a time‐varying linear system. Since a bounded error approach is adopted for both modeling the measurement noise and the parameter change process, the problem addressed amounts to the design of a procedure for updating an estimate of the feasible parameter set. The approximating regions considered are in the form of outbounding orthotopes. The novelty of the approach lies in the use of a selection technique which keeps track only of a special subset of the constraints defining the feasible set. These inequalities represent the binding constraints of suitable linear programs of limited size. The devised algorithm is tested on several numerical examples, showing remarkable performance both in computational burden, which is comparable to that of classical recursive estimation algorithms like recursive least squares (RLS) and quality of the set estimate as compared to alternative techniques available in the literature.
Casein Kinase 2 (CK2): A Possible Therapeutic Target in Acute Myeloid Leukemia

Simple Summary Acute myeloid leukemia (AML) is an aggressive blood cancer disease that can only be cured by intensive anticancer treatment, and for several patients, allogeneic stem cell transplantation is needed. The protein kinase casein kinase 2 (CK2) is an intracellular signaling molecule that supports cellular growth and survival. This is true both for normal and cancer cells, and the growth- and survival-supporting effects seem to be more important for many cancer cells (including AML cells) than for normal cells. Several pharmacological inhibitors of CK2 have been developed, and this therapeutic strategy is now tried in patients with various malignant diseases. In this article, we review available studies suggesting CK2 inhibition as an effective strategy also for the treatment of AML, either as monotherapy or as a part of drug combinations. Abstract The protein kinase CK2 (also known as casein kinase 2) is one of the main contributors to the human phosphoproteome. It is regarded as a possible therapeutic strategy in several malignant diseases, including acute myeloid leukemia (AML), which is an aggressive bone marrow malignancy. CK2 is an important regulator of intracellular signaling in AML cells, especially PI3K–Akt, Jak–Stat, NFκB, Wnt, and DNA repair signaling. High CK2 levels in AML cells at the first time of diagnosis are associated with decreased survival (i.e., increased risk of chemoresistant leukemia relapse) for patients receiving intensive and potentially curative antileukemic therapy. However, it is not known whether these high CK2 levels can be used as an independent prognostic biomarker because this has not been investigated in multivariate analyses. Several CK2 inhibitors have been developed, but CX-4945/silmitasertib is best characterized. This drug has antiproliferative and proapoptotic effects in primary human AML cells. The preliminary results from studies of silmitasertib in the treatment of other malignancies suggest that gastrointestinal and bone marrow toxicities are relatively common. However, clinical AML studies are not available. Taken together, the available experimental and clinical evidence suggests that the possible use of CK2 inhibition in the treatment of AML should be further investigated.
Behavioral finance factors and investment decisions: A mediating role of risk perception

Abstract Modern finance theory assumes that the stock market is efficient, and stock prices reflect all available information. However, behavioral finance theory argues that stock prices can be influenced by psychological and emotional factors. This study aims to examine the impact of behavioral finance factors on investment decisions in the Saudi equity markets through the mediating variable of risk perception. An online questionnaire was distributed to 150 individual investors, out of which 134 were returned and ready for analysis. The data is analyzed using structural equation modeling (SEM). The results show that herding, disposition effect, and blue chip bias have a significant positive impact on risk perception. Overconfidence has a significant positive effect only on investment decision making, but not on risk perception. Risk perception is found to be significantly positively related to investment decision making. All four behavioral finance factors have a significant positive indirect effect on investment decision making through risk perception. This study is conducted in a particular cultural context, namely Saudi Arabia, and may not be generalizable to other cultural contexts. Moreover, this study focused only on four behavioral finance factors, and there may be other factors that could impact risk perception and investment decision making. The results highlight the importance of considering an individual’s perception of risk when making investment decisions, as it can significantly impact their willingness to take risks and ultimately affect the performance of their investment portfolio. The results suggest the need for investors to consider their behavioral biases and for advisors and policymakers to develop strategies to mitigate their impact.
Language-switching and retrieval-based learning: an unfavorable combination

Language-switching costs arise when learners encode information in one language and subsequently recall that information in a different language. The assumed cognitive mechanism behind these costs is the principle of encoding specificity that implies language-dependent representations of information. The aim of our study was to test this mechanism and to gain insights into the impact of language-switching on subsequent learning. To this end, we used retrieval-based learning as a carrier-paradigm. In a 2×3-design, 117 participants learned mathematical concepts with a practice-test or a restudy opportunity (within-subjects factor). In addition, the sample was divided into three groups regarding language-switching (between-subjects factor): one group without switching, one switched for the final tests, and one switched between initial learning and subsequent learning. Results show the expected main effects: participants performed better for the items learned via retrieval-based learning (testing-effect) and worse in conditions with language-switching (language-switching-costs). Most importantly, we were able to find an interaction between learning condition and language-switching: retrieval-based learning suffers particularly from language-switching. Additionally, our results indicate that language switching before subsequent learning seems to be particularly detrimental. These results provide both validation for encoding specificity as mechanism underlying language-switching costs and new information on the impact of the time of language-switching that can be considered in educational designs such as “Content and Language Integrated Learning. ”
Shallow S-wave Velocity Profile Estimation using Surface Velocity and Microtremor HVSR with a Linear Velocity Increase Approach

We propose a simple method for 1D S-wave velocity (Vs) profile estimation using a measured surface S-wave velocity (V1) and peak frequency of the observed microtremor horizontal-to-vertical spectral ratio (HVSR). In this method, the S-wave velocity profile is presented as linear velocity increase with depth in sediments over a bedrock layer that has a given constant S-wave velocity. Thus, the profile can be parameterized with the measured surface S-wave velocity and the velocity gradient. The gradient can be estimated based on the agreement of the peak frequencies of the observed microtremor HVSR and the theoretical ellipticity of the fundamental mode of the Rayleigh wave. We examined the applicability of the proposed method using numerical tests as well as application to actual data at five sites in the Bandung Basin, Indonesia, where observed Rayleigh wave phase velocities from microtremor array surveys were available. The applicability was confirmed in numerical tests using sample models of soil profiles in the basin. Actual application indicated the appropriateness of the estimated S-wave velocity profiles due to the similarity of their theoretical Rayleigh wave phase velocities with the observed Rayleigh wave phase velocities. Since the proposed method needs prior confirmation of the linear increase of the S-wave velocity, it is suitable for use in spatial interpolation of shallow S-wave velocity profiles with simple data acquisition.
Potential Involvement of HLA-DR/DQ Polymorphisms with Schizophrenia Among Yemeni Schizophrenia Patients

Objectives : The hypothesis that human leukocyte antigens (HLAs) confer susceptibility to schizophrenic disorders has been tested by studying linkage and association in family samples. Our objective was to assess the contribution of HLA to the schizophrenia risk in the Yemeni community. Methods: The researchers approached patients who had been diagnosed with schizophrenia at Al-Amal Hospital for Psychiatric Diseases. Controls were drawn at random from the list of census takers in the Sana'a governorate and were drawn from the general population. The HLA class II alleles of the participants were examined. The genotypes of the HLA-DQB1 and HLA-DRB1 alleles were determined by polymerase chain reaction using sequence-specific primers. Results: The occurrence of HLA DRB1*04 was increased significantly with patients than with controls (7.3% versus 0%, p = 0.003), also HLA DRB1*07 was significantly increased with patients ( 62.7% versus 17.3%, OR= 8.1, 95% CI = 4.3 - 15.1 , p < 0.001), at the same time as HLA DRBI*14 was less common significantly with patients (0.9% vs. 11.8% with the control group) with OR = 0.06, CI = 0.008–0.5, X 2 = 10.9, p = 0.0009; grant protection against schizophrenia. HLADQB1*07 was the generally common allele discovered in patients and was found at extensively higher incidence for patients above the control group (22.7% vs. 4.5%, OR=6.2, 95% CI = 2.3–16.8, X 2 = 15.4., p < 0.0001), indicating a strong predisposing effect. Conclusion: The HLA-DQB1 and HLA-DRB1 gene loci have been linked to schizophrenia in the Yemeni population, according to the current study's evidence.