Level Of Credibility Research Articles

Constraining the gravitational-wave spectrum from cosmological first-order phase transitions using data from LIGO-Virgo first three observing runs

We search for a first-order phase transition (PT) gravitational wave (GW) signal from Advanced LIGO and Advanced Virgo's first three observing runs. Due to the large theoretical uncertainties, four shapes of GW energy spectral from bubble and sound wave collisions widely adopted in literature are investigated, separately. Our results indicate that there is no evidence for the existence of such GW signals, and therefore we give the upper limits on the amplitude of GW energy spectrum Ωpt(f *) in the peak frequency range of f * ∈ [5,500] Hz for these four theoretical models, separately. We find that Ωpt(f * ≃ 40 Hz) < 1.3 × 10-8 at 95% credible level, and roughly H */β ≲ 0.1 and α ≲ 1 at 68% credible level in the peak frequency range of 20 ≲ f * ≲ 100 Hz corresponding to the mostsensitive frequency band of Advanced LIGO and Advanced Virgo's first three observing runs, where H * is the Hubble parameter when PT happens, β is the bubble nucleation rate and α is the normalized latent heat.

Nonparametric Representation of Neutron Star Equation of State Using Variational Autoencoder

We introduce a new nonparametric representation of the neutron star (NS) equation of state (EOS) by using the variational autoencoder (VAE). As a deep neural network, the VAE is frequently used for dimensionality reduction since it can compress input data to a low-dimensional latent space using the encoder component and then reconstruct the data using the decoder component. Once a VAE is trained, one can take the decoder of the VAE as a generator. We employ 100,000 EOSs that are generated using the nonparametric representation method based on Han et al. as the training set and try different settings of the neural network, then we get an EOS generator (the trained VAE’s decoder) with four parameters. We use the mass–tidal-deformability data of binary NS merger event GW170817, the mass–radius data of PSR J0030+0451, PSR J0740+6620, PSR J0437-4715, and 4U 1702-429, and the nuclear constraints to perform the Bayesian inference. The overall results of the analysis that includes all the observations are , , and (90% credible levels), where R 1.4/Λ1.4 are the radius/tidal deformability of a canonical 1.4 M ⊙ NS, and is the maximum mass of a nonrotating NS. The results indicate that the implementation of these VAE techniques can obtain reasonable results, while accelerating calculation by a factor of ∼3–10 or more, compared with the original method.

Bühlmann's Credibility Model with Claims of Negative Binomial and 2-Poisson Distribution

One of the premium determination techniques is to use credibility theory. In this study, a credibility premium determination model was derived with the best accuracy approach in the form of Bühlmann’s credibility premium. The claim data is assumed to have a Negative Binomial and 2-Poisson distribution. Bühlmann's credibility premium formula is given explicitly for these two data distributions. The obtained model is also applied to the correct data following these distributions. From the simulation results, it is obtained that the premium values are very close in value so that both models can be applied to the data and have a high level of credibility because they have a high credibility factor value.

Basic aspects of meta-analysis. Part 1

Meta-analysis is one of the concepts of scientific methodology, and is a frequent but optional component of systematic reviews of empirical research. It joins the results of several scientific studies and tests one or more interrelated scientific hypotheses using quantitative (statistical) methods. This analysis can either use primary data from the original studies or published (secondary) results of studies dealing with the same problem. Meta-analysis is used to obtain an estimate of the magnitude of an unknown effect, and compare the results of different studies, identifying patterns or other relationships in them, as well as possible sources of disagreement. Meta-analyses are the highest level of credibility within evidence-based medicine (EBM), so meta-analysis results are considered as the most reliable source of evidence. Understanding all the procedures of a meta-analysis will allow researchers to analyze the results of such studies correctly, as well as formulate tasks when conducting meta-analyses on their own. In this article the reader will be introduced to key concepts such as weighted effects, heterogeneity, the different types of statistical models used, and how to work with some of the types of plots produced in meta-analyses.

LAYANAN BIMBINGAN KELOMPOK DENGAN TEKNIK SOSIODRAMA TERHADAP MOTIVASI BELAJAR SISWA KELAS XI DI SMAN 1 MANIIS PURWAKARTA

The purpose of this study is to find out the implementation, response of teachers and students, student difficulties, and teacher difficulties of group guidance services with sociodramaic techniques to increase learning motivation. This research uses qualitative approaches as for the methods used that are descriptive. Data collection techniques are carried out through observation, interviews, and documentation. The research site is focused on class XI SMAN 1 Maniis Purwakarta. The subject of the study is to the guidance and counseling teacher and the student. Data analysis is done by selecting and sorting the answers to the data obtained and then collected for analysis and conclusions. The data analysis used is using data triangulation. Data validity tests use levels of credibility, transferability, dependability, and confirmation. The study found that 1) Implementation of group guidance services with sociodramaic techniques is carried out with the formation stage, transition stage, activity stage, and termination stage. Activities are carried out with due regard to guidance and sociodramaic procedures; 2) Student response is that students are very excited, comfortable, and more cooperating, more creative, and very enthusiastic; 3) Difficulties experienced by students that some students do not focus and sometimes disturb their friends; and 4) The teacher's constraints are limited time. The study concluded that the implementation of group guidance services with sociodrama techniques can increase students' learning motivation.Keywords: Guidance, Learning Motivation, Sociodrama

Nursing students' experiences of workplace violence in clinical practice: a qualitative systematic review protocol.

The objective of this review is to investigate the experience of workplace violence against nursing students on clinical placement. Workplace violence affects nursing students during clinical placements in hospitals and other health care settings. Nursing students are uniquely vulnerable to workplace violence due to their limited experience and skills in challenging abusive behavior. Up to half of nursing students have reported experiencing horizontal or lateral physical or verbal violence during clinical placement, both from colleagues and patients. As a result of workplace violence, many students consider leaving nursing practice within their first year. This has implications for individual students' progression and for health care systems that rely on nursing graduates to deliver health care services. Only qualitative primary studies will be included. The population is registered nurse students, the phenomenon of interest is the experience of workplace violence, and the context is clinical placement. A comprehensive database search of MEDLINE, CINAHL, Web of Science Core collection, Scopus, Embase, Cochrane Central Register of Controlled Trials, ERIC, ProQuest Central, ProQuest Social Science Premium Collection, and ProQuest Dissertations and Theses will be conducted. Databases will be searched from inception to present for English-language qualitative literature of any study design that meets the inclusion criteria. A search of unpublished and gray literature will also be conducted. The JBI critical appraisal checklist for qualitative research will be used to assess the studies. Findings and illustrations will be extracted and assigned a level of credibility. Meta-aggregation of findings will be performed, and a ConQual Summary of Findings will be presented. PROSPERO CRD42022337674.

Asymptotic uncertainty quantification for communities in sparse planted bi-section models

Posterior distributions for community structure in sparse planted bi-section models are shown to achieve exact (resp. almost-exact) recovery, with sharp bounds for the sparsity regimes where edge probabilities decrease as O(log(n)/n) (resp. O(1/n)). Assuming posterior recovery, one may interpret credible sets (resp. enlarged credible sets) as asymptotically consistent confidence sets; the diameters of those credible sets are controlled by the rate of posterior concentration. If credible levels are chosen to grow to one quickly enough, corresponding credible sets can be interpreted as frequentist confidence sets without conditions on posterior concentration. In the regimes with O(1/n) edge sparsity, or when within-community and between-community edge probabilities are very close, credible sets may be enlarged to achieve frequentist asymptotic coverage, also without conditions on posterior concentration.

Fenomen Hekimler Sosyal Medyayı Nasıl Kullanıyor? Pazarlama İletişimi, Hasta Mahremiyeti ve Etik Üzerine Bir İçerik Analizi

Medical doctors have a high level of source credibility and a reputable profession. Some of them also share their expertise on social media. This led to so some doctors gaining thousands and millions of followers and becoming “influencer doctors”. Every bit of information that a medical doctor share is important for the followers. Influencers are content creators with a large social media following, and this makes them appealing for brands. Collaborations with brands are common for influencers. When it comes to influencer doctors, who have more credibility due to their profession, it can be said that they have an advantage over ordinary influencers, a power to drive their followers’ decisions. However, it is prohibited by law and regulations for medical doctors to advertise in any medium. Thus, in this study it was aimed to reveal medical doctors’ compliance with Turkish Medical Association’s rules on social media. A content analysis on 13 medical doctors’ Instagram stories was conducted. Each doctor has more than 500.000 followers and they shared a total of 565 stories. According to the findings, product promotions are most common content for the stories of these influencer doctors. They also share stories that showcase or promote their services; that contain patient information in which more than half are privacy breaches; and none included a disclosure on patient permission to reveal such information.

Multi-criteria decision-making model using trigonometric aggregation operators of single-valued neutrosophic credibility numbers

An important idea is to enhance the credibility measures of single-valued neutrosophic sets/numbers (SvNSs/SvNNs) and operational requirements of multiple time-phases/periods for ensuring the credibility and rationality of multiple periodic decision-making problems. Motivated by this idea, this study aims to propose a multi-criteria decision-making (MCDM) model based on the trigonometric weighted average and geometric operators of single-valued neutrosophic credibility numbers (SvNCNs). First, a single-valued neutrosophic credibility set is presented to enhance the credibility levels of SvNSs. Then, the score and accuracy functions of SvNCNs are defined to rank SvNCNs. Next, in view of multiple time-phase/period characteristics of trigonometric functions (sine and arcsine functions and cosine and arccosine functions), we propose the trigonometric t-norm and t-conorm operational laws of SvNCNs and the SvNCN trigonometric weighted average (SvNCNTWA) and SvNCN trigonometric weighted geometric (SvNCNTWG) operators to aggregate SvNCNs. Furthermore, a MCDM model is established in terms of the proposed two aggregation operators and the score and accuracy functions to solve MCDM problems in a SvNCN circumstance. Lastly, the proposed MCDM model is applied to an actual example of the choice issue of slope design schemes for an open-pit mine to indicate the validation and rationality of the proposed model.

Inferring the Rate of Technosignatures from 60 yr of Nondetection

For about the last 60 yr the search for extraterrestrial intelligence has been monitoring the sky for evidence of remotely detectable technological life beyond Earth, with no positive results to date. While the lack of detection can be attributed to the highly incomplete sampling of the search space, technological emissions may be actually rare enough that we are living in a time when none cross the Earth. Here we explore the latter possibility and derive the likelihood of the Earth not being crossed by signals for at least the last 60 yr to infer upper bounds on their rate of emission. Under the assumption that technological emitters are distributed uniformly in the Milky Way and that they generate technoemissions at a constant rate, we find less than about one to five emissions generated per century with 95% credible level. This implies optimistic waiting times until the next crossing event of no less than 60–1800 yr with a 50% probability. A significant fraction of highly directional signals increases the emission rates’ upper bounds, but without systematically changing the waiting time. Although these probabilistic bounds are derived from a specific model and their validity depends on the model’s assumptions, they are nevertheless quite robust against weak time dependences of the emission rate or nonuniform spatial distributions of the emitters. Our results provide therefore a benchmark for assessing the lack of detection and may serve as a basis to form optimal strategies for the search for extraterrestrial intelligence.

Predicting College Students’ Preventative Behavior During a Pandemic: The Role of the Health Belief Model, Source Credibility, and Health Literacy

In this study, we examined the effects of perceived source credibility of the Centers for Disease Control (CDC) and college student health literacy in predicting the likelihood of enacting preventative behaviors related to mitigating COVID-19. Using the Health Belief Model (HBM) as an explanatory tool, we analyzed how perceived source credibility and health literacy levels predict college students’ likelihood to enact preventative behaviors during a public health crisis. Sample population entirely consisted of undergraduate students enrolled in a basic communication course at a large, southern university. The participants completed survey questionnaires about their perceived health literacy, health beliefs, trust in the CDC, perceptions of COVID-19, and demographic measures during the fall 2020 semester. A multiple regression analysis revealed that (a) HBM predictors, health literacy and CDC source credibility accounted for 44% of the variance in likelihood of enacting preventative health behaviors, and (b) health literacy, CDC source credibility, and perceived severity were all positive predictors of enacting preventative health behaviors, while (c) perceived barriers negatively predicted enactment of preventative health behaviors. Perceived susceptibility and perceived benefits were not significant predictors of college student risk mitigation. Our data suggests the importance of health literacy and source credibility in predicting college students’ likelihood to enact preventative behaviors during public health crises.

Abstract 4287: The combination of statistical methods to compare observed and simulated data allowed to assess effectively the validity of mathematical model predictions in a context of a EGFR+ lung adenocarcinoma

Abstract Introduction In silico models proved to be a promising tool to complement and optimize clinical trials. These models should be validated to assess their capacity to reproduce real life behaviors. Opposed to real-life clinical trials where the amount of available data might be low, in silico approaches give us the possibility to simulate virtual populations of thousands of patients. This data size heterogeneity might be an issue. Moreover, in real life data, patients are seen at scheduled visits, leading to an observation time uncertainty (OTU), which is not the case in simulated data.In the context of the validation of a EGFR-mutant Lung Adenocarcinoma mathematical model, we depicted the interest of using combined validation methods to assess the capacity of the model to predict the time to tumor progression, from heterogeneous clinical trials datasets. Methods In this context, to overcome the limitation of using default log-rank test that could lead to biased results, 4 bootstrapped methods have been used: - 2 methods based on the log-rank test where the ratio of significant tests at a given alpha risk level is assessed, taking into account the OTU: The “default Log-rank test” and the “modified test” based on a combination of weighted log-rank tests (MaxCombo). - 2 methods based on prediction intervals. The “raw coverage”, which corresponds to the proportion of the observed time-to-event curve included in the prediction interval and the “juncture metric” which corresponds to the proportion of the observation period where the prediction interval overlaps with an interval bound between the observed data and the same data shifted by the OTU. Results As each one of the validation approaches has its own strengths and weaknesses and conditions of application, the validation process has been based on the combination of well selected methods. Validation metrics showed that the model reproduces successfully real life data depending on a given context. When all the metrics give the same result, we were able to easily conclude. But when it was not the case, this led us to investigate the origin of these discrepancies, taking into account method robustness. Conclusion The validation process is of the utmost importance to assess the level of credibility of the model. We showed that in order to fully evaluate the model, a combination of validation approaches is preferable. The use of multiple metrics highlights the eventual inconsistencies in model predictions and validation dataset’s content that would not have been detected by only a single approach. The drawback of combining metrics is that it complexifies the decision making, implying that the final decision, regarding whether the model is validated or not, is assumed by the user, without forgetting that the validation is not an end objective per se but a stepwise process. Citation Format: Evgueni Jacob, Laura Villain, Nicoletta Ceres, Jean-Louis Palgen, Adele L'Hostis, Claudio Monteiro, Riad Kahoul. The combination of statistical methods to compare observed and simulated data allowed to assess effectively the validity of mathematical model predictions in a context of a EGFR+ lung adenocarcinoma. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4287.

Editor’s Note

Editor’s Note: For the fifth time since its original 1949 production that ran for 742 shows, Death of a Salesman has been revived on Broadway. This time it is the transfer of a Young Vic production that was first produced in 2019 in the United Kingdom and won two Olivier Awards. While the leads for the U.S. production remain the same—Wendell Pierce and Sharon D. Clarke—many of the other cast members are changed, and the sole director this time round is Miranda Cromwell, who had worked with Marianne Elliott on the Young Vic show. While there have been all-Black and mixed-cast productions in the United States since 1962 (Steve Marino offers a brief overview of these in his review), this is the first Broadway production trying this out, and they decided not to use an all-Black cast but keep certain characters in the show as white, which creates a slightly different resonance. That is clearly the focus of several of these reviewers, some of whom were more appreciative than others.David Palmer suggests that since Salesman has become so well-known, contemporary directors can approach it like jazz musicians, ready to take the drama in new and exciting directions to create fresh levels of meaning, and this latest version is an African American riff, one that allows Biff and Linda a greater dignity, Willy a credible level of insanity, and Happy a new interpretation borne out through a series of telling handshakes. Through the lens of Blackness the Loman family is able to morph into something entirely new, and Palmer concludes that this production presents “the struggle for dignity and acknowledgment as the core of the play.” Pointing out that Miller’s plays have been subjected to a variety of innovative approaches in the past, Marino describes how this new production incorporates Black cultural elements into its design, though he questions some of its staging decisions. While he did not feel that the play’s casting choices had that great of an impact overall given the play’s universality, Marino notes some moments when it was more effective than others. And while Marino tolerates most of the play’s innovations, Deborah Simon is less benevolent, suggesting that the set and a variety of effects were too disconcerting, as well as the cast lacking in cohesion, which all ultimately diminish the impact of Willy’s fate. Jane Dominik is similarly critical of certain aspects of the production, but offers even more detail and finds elements to also approve in this latest Broadway rendering of what has arguably become America’s best-known drama, to which, as Simon reminds us, “attention must be paid!”

Postnatal experiences of South Asian immigrant women in Australia, Canada, the United Kingdom, and the United States: a qualitative systematic review protocol.

The goal of this review is to gain an understanding of the postnatal experiences of South Asian immigrant women in 4 English-speaking countries: Australia, Canada, the United Kingdom, and the United States. The postnatal period is an important time in the lives of women and their families. Major changes take place during this time as a woman's body gradually returns to its pre-pregnancy state. The postnatal period is also a time for women to adapt and transition into their new role as a mother. Immigrant women experience many challenges in accessing quality postnatal care in comparison to non-migrant populations. South Asian immigrant women, specifically, encounter unique postnatal experiences and face a myriad of hardships in accessing proper postnatal care. The presence of cultural factors and traditional norms largely influence postnatal experiences of South Asian immigrant women. Cultural factors include, but are not limited to, relationships with family and in-laws, gender-specific roles, newborn gender, mental health stigma, language barriers, acculturative stress, and expression of depression. Qualitative studies in English reporting postnatal experiences of South Asian immigrant women published after January 2000 will be considered for this review. Research designs may include, but are not limited to, feminist research, exploratory descriptive design, or ethnography. Gray literature will be limited to theses and dissertations only. MEDLINE, Embase, CINAHL, EthOS, and ProQuest Dissertations and Theses will be searched. Disagreement resolution, data extraction, and meta-aggregation will be completed through discussion between 2 reviewers. Studies will be critically appraised and assigned a level of credibility. PROSPERO CRD42022354306.

The Code of Ethics and Conduct for Forensic Specialists: A Framework from The Portuguese Association of Forensic Sciences

Forensic sciences aggregate a series of scientific and technological domains that aid the judiciary and judicial system. Despite the highly specialized and qualified professionals taking a role in forensic practice, this paradigmatic integration of law, science, and technology often leads them to face significant ethical challenges. Indeed, forensic sciences hold a unique position due to the social and legal implications inherent to forensic expertise. The potential interference with personal rights and freedoms requires the professional practice of the forensic specialist to be guided by alignment with scientific-technical competence under the seal of the highest ethical principles. However, the absence of a specific statutory regulation blurs the performance of the forensic professional and may harm the professional credibility but also the scientific domain as a whole. The existence of ethical pillars is essential to support professional practice, following international recommendations in this regard. Herein, we propose a framework for a code of ethics and conduct that is based on the professional particularities characterizing the forensic practice but also considers the ethical issues that are mandatory to ensure high levels of reliability and credibility of forensic specialists.

A Bidirectional Self-Rectifying Network With Bayesian Modeling for Vision-Based Crack Detection

Robotic vision is increasingly applied for surface inspection of built infrastructure. For this, it is essential to develop robust algorithms for semantic segmentation. This article presents a deep learning approach using a bidirectional self-rectifying network with Bayesian modeling (BSNBM) for improving detection accuracy, in dealing with the embedded uncertainty caused by false-positive labels and nonlinearity in sequentially convolutional blocks. For integration with residual encoders, a feature preserving branch is designed, wherein the output of previous dilated convolutional blocks is upsizedly or downsizedly passed on and concatenated with the following blocks recursively and bidirectionally. Further, to achieve robustness in feature representation with an acceptable level of credibility, convolutional kernels are randomized via a Bayesian model and adjusted per evidence update. As such, the network becomes less sensitive to uncertainty and redundant nonlinearity, which is inevitable in activation layers. Experimental results confirm the advantage of our BSNBM over current crack detection approaches.

Reconciling crop production and ecological conservation under uncertainty: A fuzzy credibility-based multi-objective simulation-optimization model

To cope with the problems of agricultural water conflicts and secondary soil salinization in arid regions, a fuzzy credibility-based multi-objective simulation-optimization model is proposed for optimizing irrigation water allocation and crop area planning under uncertainty. This model combines simulation module of enabling to quantify daily physical process of water-salt movement among soil water, crop root zone and groundwater aquifers, optimization module of managing water resources and fuzzy credibility-constrained programming into a general framework. It's applied to a case study in the Jiefangzha Irrigation Subarea in Hetao Irrigation District, Northwest China. Three objectives encompassing maximizing net economic benefits, maximizing nutritional water productivity and minimizing carbon emissions from agricultural system are interconnected through decision variables. Four credibility scenarios of fuzzy constrains including β = 0.6 to 0.9 are presented for obtaining decision-making solutions. Through NSGA-III, such a high-dimensional multi-objective problem is solved. This study uses the multi-objective constraint-handling strategy to handle constraints, which exploits the effective information within infeasible solutions. Moreover, it emphasizes the importance of soil water-salt movement processes in determining optimal solutions and helps decision makers weigh the system outputs and risk level of violating constraints. Results illustrate that when β increases from 0.6 to 0.9, net economic benefit decreases from 1.742 × 109 Yuan to 1.706 × 109 Yuan, nutritional water productivity decreases from 9136.0 kcal/m3 to 8819.6 kcal/m3, and carbon emissions increase from 439.6 × 106 kg. C to 441.6 × 106 kg.C, which shows that an increasing credibility level leads to lower system benefits and conservative system outputs. The results can provide valuable information for managing irrigation water resources and controlling salinity accumulation. Furthermore, dynamic decisions related to water-salt movement processes can be readily generated. These findings show that the developed approach is globally applicable for managing irrigation water in arid and semiarid regions that face similar problems.

Real-time estimation and forecasting of COVID-19 cases and hospitalizations in Wisconsin HERC regions for public health decision making processes

BackgroundThe spread of the COVID-19 (SARS-CoV-2) and the surging number of cases across the United States have resulted in full hospitals and exhausted health care workers. Limited availability and questionable reliability of the data make outbreak prediction and resource planning difficult. Any estimates or forecasts are subject to high uncertainty and low accuracy to measure such components. The aim of this study is to apply, automate, and assess a Bayesian time series model for the real-time estimation and forecasting of COVID-19 cases and number of hospitalizations in Wisconsin healthcare emergency readiness coalition (HERC) regions.MethodsThis study makes use of the publicly available Wisconsin COVID-19 historical data by county. Cases and effective time-varying reproduction number R_t by the HERC region over time are estimated using Bayesian latent variable models. Hospitalizations are estimated by the HERC region over time using a Bayesian regression model. Cases, effective Rt, and hospitalizations are forecasted over a 1-day, 3-day, and 7-day time horizon using the last 28 days of data, and the 20%, 50%, and 90% Bayesian credible intervals of the forecasts are calculated. The frequentist coverage probability is compared to the Bayesian credible level to evaluate performance.ResultsFor cases and effective R_t, all three time horizons outperform the three credible levels of the forecast. For hospitalizations, all three time horizons outperform the 20% and 50% credible intervals of the forecast. On the contrary, the 1-day and 3-day periods underperform the 90% credible intervals. Questions about uncertainty quantification should be re-calculated using the frequentist coverage probability of the Bayesian credible interval based on observed data for all three metrics.ConclusionsWe present an approach to automate the real-time estimation and forecasting of cases and hospitalizations and corresponding uncertainty using publicly available data. The models were able to infer short-term trends consistent with reported values at the HERC region level. Additionally, the models were able to accurately forecast and estimate the uncertainty of the measurements. This study can help identify the most affected regions and major outbreaks in the near future. The workflow can be adapted to other geographic regions, states, and even countries where decision-making processes are supported in real-time by the proposed modeling system.

Tests of general relativity with gravitational-wave observations using a flexible theory-independent method

We perform tests of general relativity (GR) with gravitational waves (GWs) from the inspiral stage of compact binaries using a theory-independent framework, which adds generic phase corrections to each multipole of a GR waveform model in frequency domain. This method has been demonstrated on Laser Interferometer Gravitational Wave Observatory-Virgo observations to provide stringent constraints on post-Newtonian predictions of the inspiral and to assess systematic biases that may arise in such parametrized tests. Here, we detail the anatomy of our framework for aligned-spin waveform models. We explore the effects of higher modes in the underlying signal on tests of GR through analyses of two unequal-mass simulated binary signals similar to GW190412 and GW190814. We show that the inclusion of higher modes improves both the precision and the accuracy of the measurement of the deviation parameters. Our testing framework also allows us to vary the underlying baseline GR waveform model and the frequency at which the non-GR inspiral corrections are tapered off. We find that to optimize the GR test of high-mass binaries, comprehensive studies would need to be done to determine the best choice of the tapering frequency as a function of the binary's properties. We also carry out an analysis on the binary neutron-star event GW170817 to set bounds on the coupling constant ${\ensuremath{\alpha}}_{0}$ of Jordan-Fierz-Brans-Dicke gravity. We take two plausible approaches; the first approach involves translating directly the ``theory-agnostic'' bound on dipole-radiation into a bound on ${\ensuremath{\alpha}}_{0}$ for different neutron-star equations of state (EOS). The second ``theory-specific'' approach involves reparametrizing the test such that the deviation parameter is ${\ensuremath{\alpha}}_{0}$ itself. The two approaches provide slightly different bounds, namely, ${\ensuremath{\alpha}}_{0}\ensuremath{\lesssim}2\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}1}$ and ${\ensuremath{\alpha}}_{0}\ensuremath{\lesssim}4\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}1}$, respectively, at 68% credible level. These differences arise mainly since in the theory-specific approach the tidal and scalar-charge parameters are fixed coherently for each neutron-star EOS and mass.

First search for the weak radiative decays Λc+→Σ+γ and Ξc0→Ξ0γ

We present the first search for the weak radiative decays Λc+→Σ+γ and Ξc0→Ξ0γ using a data sample of 980 fb−1 collected by the Belle detector operating at the KEKB asymmetric-energy e+e− collider. There are no evident Λc+→Σ+γ or Ξc0→Ξ0γ signals. Taking the decays Λc+→pK−π+ and Ξc0→Ξ−π+ as normalization channels, the upper limits at 90% credibility level on the ratios of branching fractions B(Λc+→Σ+γ)/B(Λc+→pK−π+)<4.0×10−3 and B(Ξc0→Ξ0γ)/B(Ξc0→Ξ−π+)<1.2×10−2 are determined. We obtain the upper limits at 90% credibility level on the absolute branching fractions B(Λc+→Σ+γ)<2.6×10−4 and B(Ξc0→Ξ0γ)<1.8×10−4.Received 27 June 2022Accepted 2 August 2022DOI:https://doi.org/10.1103/PhysRevD.107.032001Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI. Funded by SCOAP3.Published by the American Physical SocietyPhysics Subject Headings (PhySH)Research AreasBranching fractionElectroweak radiative correctionsPhysical SystemsCharmed baryonsParticles & Fields