Background Discrimination Research Articles

P-895. Perceptions of Bias and Discrimination Among Antimicrobial Stewardship Providers

Abstract Background Bias and discrimination influence the experience of many in healthcare, and antimicrobial stewardship providers are no exception as demonstrated by work documenting differential uptake of recommendations made by men and women stewards. In this mixed method study, we explored the perceptions and experiences of bias and discrimination among antimicrobial stewards. Methods We conducted a nationwide survey of stewardship providers including physicians, pharmacists, advanced practice providers and trainees. Participants were recruited via convenience sampling using X and professional listservs during May and June 2023. We solicited steward and program demographics and responses to statements exploring bias and discrimination in the execution of stewardship duties through a 67-item electronic survey (Qualtrics). Statistical analysis using chi-squared were performed in STATA. We further explored these experiences through semi-structured interviews. Results Stewards identifying as females and those with < =5 years were more likely to report their identities negatively influenced interactions with primary teams than male and more experienced stewards, respectively (table 1). Similarly, female stewards and those with the least experience reported these identities negatively influenced their interactions with health system representatives compared to male and more experienced stewards, respectively (table 2). Although there was no difference in the reported negative influence of race/ethnicity on interactions with primary teams, more non-white stewards reported their race/ethnicity negatively influenced interactions with health system representatives (tables 1 & 2). Themes from our 16 interviews illuminated sources of perceived bias, the impact they had, and strategies to mitigate the influence of these biases. Conclusion Bias and discrimination are felt disproportionately by women and junior antimicrobial stewardship providers and can lead to poor job satisfaction and lack of perceived effectiveness. Acknowledging these experiences and equipping stewards with strategies to mitigate the harmful personal, professional and programmatic effects of bias and discrimination should be a priority of institutions and professional societies. Disclosures Jessica S. Tischendorf, MD, MS, Merck: Grant/Research Support

Detection of reactor neutrinos using gadolinium-doped plastic scintillators enhanced by machine learning techniques

Abstract In this study, we present a detailed approach for detecting reactor neutrinos by employing gadolinium-doped plastic scintillators combined with machine learning techniques. The proposed detector design was simulated using the Geant4 framework, featuring segmented modules of plastic scintillators doped with gadolinium to enhance neutron capture efficiency. Inverse beta decay (IBD) events generated by ERNIE and background events produced by cosmic ray simulations were used to train and test an Extreme Gradient Boosting (XGBoost) model for signal-background discrimination. The model demonstrated high discrimination accuracy for prompt IBD events but encountered challenges with delayed neutron background discrimination due to similarities in neutron capture. Performance comparisons with traditional cut-based analyses highlighted the improved accuracy achieved through machine learning, particularly when utilizing additional event features. This work establishes the potential of gadolinium-doped plastic scintillators and machine learning in enhancing neutrino detection and lays the groundwork for future experimental validation and detector optimization.

Underwater-MLA: lightweight aggregated underwater object detection network based on multi-branches for embedded deployment

Abstract In response to the limited memory and computing capabilities of underwater devices, as well as the various target leakage issues caused by complex underwater environments, we propose a lightweight aggregation underwater target detection algorithm called multi-branch lightweight aggregate networks underwater (underwater-MLA). The algorithm designs a new mixed convolutional fusion with contextual attention module. It constructs a multi-branch structure that integrates mixed convolutions and contextual attention to enhance the feature extraction capability for complex underwater targets. Additionally, to address the shortcomings of information loss and significant target localization errors during detection, we propose the SPPELAN efficient aggregation module to improve the model’s perception of target localization and background discrimination ability. Furthermore, targeting the issues of blurred boundaries and sample imbalance in underwater targets, we introduce the Focaler-IoU module to focus more on the distribution of sample boundaries. Finally, we deploy the underwater-MLA algorithm on a Raspberry Pi 4B development board and utilize a camera for real-time underwater target detection. Simulation results on the URPC dataset demonstrate that this method achieves an 85.86% detection accuracy, a 2.94% improvement over the original architecture. The computational complexity and parameter count are reduced by 32.94% and 11.31%, respectively. Moreover, it achieves satisfactory target detection performance on embedded terminals. Link to open-source code: https://github.com/fanchenye/fanchenye.

ANALISIS KEBIJAKAN PEMBIAYAAN SHORT COURSE TOEFL DALAM MENINGKATKAN PELAYANAN UNIT PEMBINAAN BAHASA (UBINSA)

The importance of fair and effective education financing policies is increasing in the context of higher education, especially to support English language competency which is the main provision in the global era. There is a research gap regarding the effectiveness of the implementation of TOEFL short course program financing policies in higher education institutions, especially related to accessibility and service quality. This study aims to analyze the policy, effectiveness, and impact of TOEFL short course financing at the Language Development Unit (UBINSA) STAI Sangatta Kutai Timur. The approach used is a qualitative approach with a case study design. The results of the study indicate that the financing policy reflects the principle of fair education financing, by providing subsidies without discrimination of economic background and setting an annual budget that includes operational costs and instructor honorariums. This policy has also succeeded in improving students' English competence, as seen from the increase in participants' TOEFL scores and their motivation to develop further language skills. However, challenges such as limited facilities, infrastructure, and instructor qualifications need to be addressed to maintain the sustainability and effectiveness of the program on an ongoing basis. The implication of this study is the importance of improving facilities and improving the quality of instructors as a strategic step in increasing the effectiveness of the TOEFL short course program at UBINSA, in line with the principles of fair and sustainable education management. The implication of this study is the need for evaluation and improvement of financing policies and more efficient management to ensure the sustainability and improvement of the quality of the TOEFL short course program at UBINSA, so that it can meet the needs of students in the global era.

한부모이주여성 차별 경험 연구

Objectives In order to create an equal multicultural society, the purpose of this study is to explore the discriminatory experiences experienced by single-parent migrant women who receive relatively little attention among immigrant groups in the process of adapting to Korean life and becoming independent, and then suggest ways to mitigate and solve them. Furthermore, It also presents educational and policy proposals to address and mitigate discrimination against single-parent immigrant women Methods For this purpose, a basic survey was conducted on 50 members of the *** Single Parent Center, and 21 of them were interviewed in depth about their specific experiences of discrimination. Based on this, the types of discrimination experiences experienced by single-parent immigrant women and their implications were derived. Results The results show that the discrimination experienced by single-parent immigrant women during the process of adapting to life in Korea and becoming independent mainly appear in “workplace,” “social life,” and “daily life,” and include “discrimination by country of origin,” “discrimination by inexperience in using the Korean language.” It was confirmed that there were experiences such as “foreigner (immigrant) status discrimination,” “family type discrimination,” “mother tongue discrimination,” “policy system discrimination,” “public institution discrimination,” “gender discrimination,” and “educational background discrimination.” In in-depth interviews, research participants claimed to have felt discriminatory emotions most often in the other person's “eyes and expressions,” “verbal behavior,” and “media.” The coping strategies single-parent immigrant women employed when encountering such discriminatory situations and experiences include “Hiding family type or identity,” “Ignoring discrimination and neglect,” “Coping wisely,” and “Overcoming discrimination through self-development.” Four types of “developments” were identified. Conclusions Based on the results of the study, five educational and policy proposals were presented to solve and alleviate the problem of discrimination against single-parent migrant women.

Measurement of scintillation from proportional electron multiplication in liquid xenon using a needle

Charge amplification in liquids could provide single-phase xenon time projection chambers with background discrimination and fiducialisation capabilities similar to those found in dual-phase detectors. Although efforts to achieve the high electric field required for charge amplification and proportional scintillation in liquid xenon have been previously reported, their application to large-scale detectors remains elusive. This work presents a new approach to this challenge, where — instead of the thin-wire approach of previous studies — a needle-like high-voltage electrode is employed to demonstrate proportional charge amplification and secondary scintillation production in liquid xenon. This is an important milestone towards the development of an electrode structure that could be utilised in a large-scale, single-phase time projection chamber with dual read-out.

Stigmatizing intimate relationships in schizophrenia: a study comparing mental health professionals, health students and the general population

Background Discrimination in intimate relationships (IR) is frequently reported among persons with schizophrenia. Despite ongoing effort of international organizations to combat mental illness stigma, there remain a limited understanding of specific IR-related stereotypes. Aims The study aimed to i) identify the stereotypes related to IR of persons with schizophrenia held by Mental Health Professionals (MHP), health students and the general population, and ii) explore the effects of several factors associated with these stereotypes. Methods This study used a mixed-methods approach. A survey developed collaboratively with persons with lived experience of mental health conditions (PWLE) was disseminated among MHP, health students and the general population. Results The majority of the nine IR-related stereotypes previously identified by PWLE were endorsed by the participants (N = 532). PWLE were perceived as particularly incompetent in the domain of IR (e.g. to achieve couple project). Stereotypes endorsement varied among the groups. Continuum beliefs, perceived similarities and recovery beliefs were negatively associated with stereotype endorsement. Conclusions The general population, MHP and health students endorsed several stereotypes regarding IR of persons with schizophrenia. The results provide support for the role of theoretical beliefs in IR stigmatization, suggesting they may be relevant targets for evidence-based stigma reduction programs.

Novel Detection of Pleomorphic Adenomas via Analysis of 68Ga-DOTATOC PET/CT Imaging.

Currently, the diagnosis of salivary gland tumors using imaging techniques is unreliable. In this monocentric retrospective study, we examined patients who received a 68Ga-DOTATOC PET/CT and subsequently underwent a salivary gland tumor resection between 1 January 2010 and 31 December 2021. PET/CT image assessment was compared with somatostatin receptor (SSTR) expression and histology. Thirteen patients (five pleomorphic adenoma (PA) and eight other parotid lesions (OPL)) received a 68Ga-DOTATOC PET/CT. Imaging displayed strong focal tracer uptake in all PA except for one with strong tumor to background discrimination. PA revealed higher SUVmax, SUVmean, liver and blood pool quotients than those of Warthin tumors (WT) and of OPL. In comparison to the contralateral parotid, SUVmax (p = 0.02), SUVmean (p = 0.02), liver quotient (p = 0.03) and blood pool quotient (p = 0.03) were all significantly higher. In contrast, WT and OPL showed in relation to the contralateral parotid no significant differences of SUVmax (WT p = 0.79; OPL p = 0.11), SUVmean (WT p = 1.0; OPL p = 0.08), liver quotient (WT p = 0.5; OPL p = 0.08) and blood pool quotient (WT p = 0.8; OPL p = 0.19). Two PA and one granuloma were not available for examination. In the immunohistochemal analysis, all PA demonstrated the highest intensity of SSTR2 expression (grade 3). Furthermore, PA had a high percentage of cells expressing SSTR2 (20%, 80% and 55%). A strong tracer uptake in PA was shown in 68Ga-DOTATOC PET/CT. This may allow physicians to utilize radioligated somatostatin analogue PET CT/MR imaging to accurately diagnose PA. Additionally, it may be possible in the future to treat the PA with a noninvasive peptide receptor radionuclide therapy or with somatostatin analogues.

Photon classification with Gradient Boosted Trees at CLAS12

Dihadron semi-inclusive deep inelastic scattering (SIDIS) of 10.6 GeV longitudinally polarized electrons off the proton has been measured using the CLAS12 detector at Jefferson Lab. Two separate channels, π + π 0 and π - π 0, were analyzed, requiring the reconstruction of diphoton pairs. In this analysis, we addressed the problem of false neutral particles being reconstructed by CLAS12's event builder, polluting the otherwise physical combinatorial background underneath the π 0 peak. A photon classifier using a Gradient Boosted Trees (GBTs) architecture was trained with Monte Carlo simulations to reduce the amount of background π 0's. We show that the nearest-neighbor features learned by the model lead to a substantial increase in signal vs. background discrimination compared to previous CLAS12 π^0 analyses. The machine learning approach recovers several times more dihadron statistics for the dataset.

Background discrimination with a Micromegas detector prototype and veto system for BabyIAXO

In this paper we present measurements performed with a Micromegas X-ray detector setup. The detector is a prototype in the context of the BabyIAXO helioscope, which is under construction to search for an emission of the hypothetical axion particle from the Sun. An important component of such a helioscope is a low background X-ray detector with a high efficiency in the 1–10 keV energy range. The goal of the measurement was to study techniques for background discrimination. In addition to common techniques we used a multi-layer veto system designed to tag cosmic-ray induced neutron background. Over an effective time of 52 days, a background level of 8.6 × 10−7 counts keV−1 cm−2 s−1 was reached in a laboratory at above ground level. This is the lowest background level achieved at surface level. In this paper we present the experimental setup, show simulations of the neutron-induced background, and demonstrate the process to identify background signals in the data. Finally, prospects to reach lower background levels down to 10–7 counts keV−1 cm−2 s−1 are discussed.

Dark matter detection with liquid argon

Liquid argon has very desirable timing characteristics for the detection of interactions of Weakly Interacting Massive Particles (WIMPs) as Dark Matter candidates. Nuclear recoil interactions emit light with time constants of the order of nanoseconds, whereas gammas and betas have time constants of the order of microseconds, enabling discrimination of such backgrounds by factors greater than 108. The global community using liquid argon for the detection of WIMPs includes a series of experiments ranging from Dark-Side-50, ArDM, DEAP-3600, DarkSide-20k and in the future ARGO and a detector studying low-mass WIMPs. Characteristics and status of this series of detectors are presented.

A Multi-View Integrated Ensemble for the Background Discrimination of Semi-Supervised Semantic Segmentation

The key to semi-supervised semantic segmentation is to assign the appropriate pseudo-label to the pixels of unlabeled images. Recently, various approaches to consistency-based training and the filtering of reliable pseudo-labels have shown remarkable results. Nonetheless, there are still issues to be addressed. We find that recent approaches have specific problems in common. In pseudo-labels for training unlabeled images, we confirm that false foreground class pseudo-labels are mostly caused by background class confusion, not confusion between different foreground classes. To solve this problem, we propose a foreground and background discrimination model for semi-supervised semantic segmentation. Our proposed model is trained using a novel approach called multi-view integrated ensemble (MVIE) via output perturbation. Experimental results in various partition protocols show that our approach outperforms the existing state of the art (SOTA) in binary prediction on unlabeled data, and the segmentation model trained with the help of our model outperforms existing models.

A Spatially Resolved X-Ray Polarization Map of the Vela Pulsar Wind Nebula

In this paper, we present a full spatially resolved polarization map for the Vela pulsar wind nebula (PWN) observed by IXPE. By employing effective background discrimination techniques, our results show a remarkably high degree of local polarization in the outskirt region, exceeding 60% (55%) with a probability of 95% (99%), which approaches the upper limit predicted by the synchrotron emission mechanism. The high degree of polarization suggests that the turbulent magnetic energy is at most 33% of the ordered one. In addition, the X-ray polarization map exhibits a toroidal magnetic field pattern that is consistent with the field revealed by radio observations across the entire nebula. This consistency reveals that the observed X-ray and radio emissions are radiated by electrons from the same magnetic field. Different from the Crab PWN, the consistency observed in the Vela PWN may be attributed to the interaction between the reverse shock of the supernova blast wave and the PWN, which leads to a displacement between the synchrotron-cooled nebula and the fresh nebula close to the pulsar. These findings deepen our understanding of the structure and evolution of the Vela PWN and the magnetohydrodynamic interaction in PWNe.

HCV treatment outcome depends on SNPs of IFNL3-Gene polymorphisms (rs12979860) and cirrhotic changes in liver parenchyma

Background and objectiveThe allelic discrimination of IFNL3-(rs12979860 C > T) polymorphism reveals ambiguous associations with the effectiveness of oral HCV treatment. Solitary intra peripheral-blood-mononuclear-cells (PBMCs) HCV-RNA antisense-strands are independently detected in naïve and experienced cases regardless of viremia or hepatic-parenchymal alterations. We examined the frequencies of IFNL3-genetic variants with chronic-HCV-induced liver changes during the sustained virologic response (SVR) by evaluating the PBMCs- HCV-PCR after oral antiviral therapy. Methods: Twelve weeks after finishing oral antiviral therapy, the effects of IFNL3-genetic variants were evaluated in three groups of patients: Group-I (n = 25) showed HCV-RNA negativity in both serum and PBMCs-, group II (n = 52) showed positivity of HCV-RNA in PBMCs, and group-III (n = 25) had positive HCV-RNA in serum. The genetic variants of the IFNL3-gene were estimated for all the enrolled cases and correlated with their hepatic image changes. Results: IFNL3-(rs12979860) genotyping in post-direct acting antivirals (DAAs) SVR and HCV-relapse revealed: a) high frequency of CC-genotype and C-allele in group I compared to group II (P < 0.005) and group III(P ≤ 0.05) when hepatic-parenchyma looks normal by ultrasound b) frequent CT-genotype and T-allele in group II compared with I(P < 0.01) and III(P < 0.05) when liver tissues are bright (early cirrhotic-changes) c) frequent TT-genotype and T-allele in group III relative to I (P < 0.05) and II (P ≤ 0.08) when liver-tissues appear coarse by ultrasound. Conclusion: Outcomes of HCV treatment depend on host IFNL3-gene polymorphism and hepatic-parenchymal changes. A high frequency of wild-CC-genotype and C-allele is observed in patients with normal hepatic parenchyma and that achieved SVR. Solitary relapse in PBMCs occurs on increasing CT-genotype frequency when liver tissues are bright. Serologic relapse is detected when TT-genotype and T-allele are dominant in association with the cirrhotic liver. Therefore, IFNL3-gene-SNP analysis as a genetic predictor in relation to ultra-sonographic hepatic-parenchymal changes could be valuable for selecting the patients with the highest priority for treatment.

Reconstruction of missing data of the PandaX-IIIexperiment TPC using neural network

The PandaX-III is a Neutrinoless Double-Beta Decay (NLDBD) experiment which uses a Time Projection Chamber (TPC) detector with a readout plane formed of Micromegas modules, which allows reconstruction of track topology for the background discrimination as well as reconstruction of the energy of the events. In NLDBD experiments, in order to achieve the highest sensitivity to the decay, it is necessary for the detector to have a high energy resolution, the background level should be low, and techniques for background discrimination must be applied as well. In reality, inhomogeneous signal gain at each module and the presence of missing channels lead to an incorrect energy reconstruction of the events. In this work, a method based on a Convolutional Neural Networks (CNN) aiming to reconstruct the kinematics of the event from imperfect data with missing channels is presented. Preliminary results of the reconstruction of the missing data using CNN are showing an increase in detection efficiency. The detection efficiency was evaluated on the simulated data with three channels randomly chosen per Micromegas module and artificially set as missing. Direct reconstruction of the energy gives the efficiency of 78%, while after applying CNN it increases to 86%, providing a promising application of this technique.

Signal to background discrimination for the production of double Higgs boson events via vector boson fusion mechanism in the decay channel with four charged leptons and two b-jets in the final state at the LHC experiment

At the CERN Large Hadron Collider experiment, the non-resonant double Higgs production via vector-boson fusion represents a unique mean to probe the VVHH (V=Z, W±) Higgs self-coupling at the current center of mass energies. Such a rare signal cannot be separated efficiently from huge backgrounds by applying a few-observables cut-based selection. Indeed, in this work, a Deep Learning algorithm is used to decide whether an event is more signal- or background-like. In particular, we report on two main aspects: results on a hyper-parameters parallel scanning strategy to distribute the training process across multiple nodes on the ReCaS-Bari data center computing resources and on the discriminating performance of a Deep Neural Network architecture.

An Examination of Discrimination on Stress, Depression, and Oppression-Based Trauma During the COVID-19 Pandemic and the Racial Awakening of 2020

Background Discrimination is a pervasive societal issue that monumentally impacts people of color (POC). Many Black, Asian, and Hispanic/Latinx individuals report experiencing race-based discrimination in their lifetime. Discrimination has previously been linked to adverse health outcomes among POC, including stress, depressive, and posttraumatic stress disorder symptoms. These health disparities are posited to have become exacerbated by COVID-19 and the racial awakening of 2020. The current study examined the short- and long-term effects of discrimination on stress, depression, and oppression-based trauma among POC. Methods Participants were (n = 398) who identified as Black, Indigenous, Hispanic/Latinx, and Asian completed an online self-report survey assessing discrimination, depression, stress, and oppression-based trauma collected at 3 time points: (T1) beginning of the COVID-19 pandemic (May 2020), (T2) 6 weeks later during the racial awakening of 2020 (June 2020), (T3) one year later (June 2021). Results Significant positive paths were revealed from T1 discrimination to T2 depression, T2 stress, and T3 oppression-based trauma. The association between T1 discrimination and T3 oppression-based trauma was partially mediated by T2 depression, but not by stress; total and total indirect effects remained significant. The final model accounted for a significant proportion of the variance in T3 oppression-based trauma, T2 depression, and T2 stress. Conclusion Findings are consistent with prior research linking discriminatory experiences with mental health symptomatology and provide evidence that race-based discrimination poses harmful short-and long-term mental health consequences. Further research is necessary to better understand oppression-based trauma to improve the accuracy of clinical diagnosis and treatment of POC.

3D silicon detectors for neutron imaging applications

Neutron detection is of great importance in many fields spanning from scientific research, to nuclear science, and to medical application. The development of silicon-based neutron detectors with enhanced neutron detection efficiency can offer several advantages such as spatial resolution, enhanced dynamic range and background discrimination. In this work, increased detection efficiency is pursued by fabricating high aspect ratio 3D micro-structures filled with neutron converting materials (B4C) on planar silicon detectors. An in-depth feasibility study was carried out in all aspects of the sensor fabrication technology. Passivation of the etched structures was studied in detail, to ensure good electrical performance. The conformal deposition of B4C with a newly developed process showed excellent results. Preliminary electrical characterisation of the completed devices is promising, and detectors have been mounted on dedicated boards in view of the upcoming tests with neutrons.

Culture of discrimination in healthcare: A grounded theory.

Discrimination in health care is an international challenge and a serious obstacle to justice and equality in health. The purpose of this study was to design a grounded theory of discrimination in health care based on the experiences and perceptions of Iranian healthcare providers and patients. This qualitative study was conducted using by the grounded theory method. Data were collected through semi-structured interviews with 18 healthcare providers including 11 nurses, two physicians, two nurse's assistants, and three patients in two general hospitals in Tehran, Iran. Participants were selected through purposeful sampling and analyzed simultaneously using the Corbin and Strauss (2015) approach. The study was approved by the Research Ethics Committee of the University of Social Welfare and Rehabilitation Sciences (Ethics code: IR.USWR.REC.1398.023). Also, after explaining the objectives of the study, all the participants completed and signed the written consent form. The "culture of discrimination" was the study's core category, reflecting the nature of discrimination in health care. The theory of "culture of discrimination in health care" is the result of five main categories: "individual social stimuli," "culture of discrimination," "unintentional discrimination," "conflict with discrimination," and "dissatisfaction with discriminatory behavior." These categories cover the underlying factors, strategies, and outcomes of the discrimination process in health care. The results of the study showed that nurses and other health care providers experience unintentional discrimination. Unintentional discrimination refers to discriminatory behaviors and practices of health care providers. The theory of culture of discrimination in health care can be used as a practical guide to describe and understand the role of health care providers, especially nurses. Further studies with a quantitative approach to applying this theory in medical settings are recommended.

Improving heavy Dirac neutrino prospects at future hadron colliders using machine learning

In this work, by using the machine learning methods, we study the sensitivities of heavy pseudo-Dirac neutrino N in the inverse seesaw at the high-energy hadron colliders. The production process for the signal is pp → ℓ → 3ℓ + {E}_T^{mathrm{miss}} , while the dominant background is pp → WZ → 3ℓ + {E}_T^{mathrm{miss}} . We use either the Multi-Layer Perceptron or the Boosted Decision Tree with Gradient Boosting to analyse the kinematic observables and optimize the discrimination of background and signal events. It is found that the reconstructed Z boson mass and heavy neutrino mass from the charged leptons and missing transverse energy play crucial roles in separating the signal from backgrounds. The prospects of heavy-light neutrino mixing |VℓN|2 (with ℓ = e, μ) are estimated by using machine learning at the hadron colliders with sqrt{s} = 14 TeV, 27 TeV, and 100 TeV, and it is found that |VℓN|2 can be improved up to mathcal{O} (10−6) for heavy neutrino mass mN = 100 GeV and mathcal{O} (10−4) for mN = 1 TeV.