Correctional Settings Research Articles

Implementing High-Intensity, Trauma-Informed Sexual Risk Reduction in Women Involved in the Criminal Legal System.

Although research supports using brief or extended behavioral interventions to increase prevention of sexually transmitted infections (STIs), there is a shortage of current information about the specific effects on women in a short-stay carceral environment. This evidence-based practice implementation project aimed to employ the Safer Sex Efficacy (SSE) Workshop in a jail setting. A repeated measures design was used to compare STI knowledge acquisition and reports of condom use self-efficacy in a group of incarcerated women before, immediately after, and 3 weeks after participation in a high-intensity behavioral counseling intervention. Twenty-one females between the ages of 20 and 45 years participated in the program. STI knowledge acquisition and reports of condom use self-efficacy were measured using the Sexually Transmitted Disease Knowledge Questionnaire and the Condom Use Self-Efficacy Scale. Findings support the feasibility of implementing evidence-based sexual health education programming incorporating information about sexual risk behaviors, STI knowledge, and behavioral skills practice in a short-stay correctional setting and further investigation with a larger sample.

Verification of optimal conditions for the scattering correction of 123I-FP-CIT SPECT on a single-photon emission tomography system with a two-detector whole-body cadmium-zinc-telluride semiconductor detector.

To identify the optimal scattering correction for 123I-FP-CIT SPECT (DAT-SPECT) using a two-detector whole-body cadmium-zinc-telluride semiconductor detector (C-SPECT) system with a medium-energy high-resolution sensitivity (MEHRS) collimator. The C-SPECT system with the MEHRS collimator assessed image quality and quantification using a striated phantom. Different reconstruction methods and scattering correction settings were compared, including filtered back projection (FBP) and ordered subset expectation maximization (OSEM). Higher %contrast and %CV values were observed > 10% subwindow (SW) for all conditions, with no significant differences between images without scattering correction and those < 7% SW. The FBP images show a greater increase in %CV > 10% SW than the OSEM images. The specific binding ratio in the radioactivity ratio of 8:1 was higher than the true value under all conditions. The C-SPECT system with an MEHRS collimator provided accurate scattering suppression and enabled high-quality imaging for DAT-SPECT. Careful setting of the scattering correction is essential for total count accuracy.

FRI250 Dual Aldosterone And Cortisol Secreting Adrenal Cortical Carcinoma: Pre- And Perioperative Evaluation And Management

Abstract Disclosure: R. Rosenberg: None. M.R. Clay: None. C. Raeburn: None. M.E. Wierman: None. Representing 0.3% of all adrenal tumors, adrenal cortical carcinoma (ACC) is a rare and understudied disease. It is estimated that 60% of patients with ACC present with hormone excess syndromes, while the remainder present incidentally or with compressive symptoms from tumor invasion. ACC presentation with a combination of hormonal excess syndromes from different adrenal zones is rare and only described previously in four case reports. We present a case of dual-secreting ACC with hyperaldosteronism and cortisol excess. The previously healthy patient was noted to have new onset hypertension and hypokalemia during a primary care visit. On hormonal evaluation, he was found to have evidence of hyperaldosteronism and ACTH-independent cortisol excess (aldosterone 28.2ng/dL, plasma renin activity 0.1ng/mL/hr, and overnight 1mg dexamethasone suppression test cortisol of 13ug/dL). Imaging revealed a 2.7 x 3.1 x 3.5cm left adrenal mass suggestive of an adenoma. He underwent laparoscopic adrenalectomy and required glucocorticoid replacement for adrenal insufficiency post-operatively. Pathologic review of the gross specimen showed a sizable neoplasm measuring 6.5 x 3.0 x 2.5 cm, much larger than on CT imaging. Microscopic review showed stage T2N0M0 ACC with modified Weiss score of 6 and 68 mitoses per 50 hpf, indicative of aggressive disease. The patient’s hypokalemia resolved post-operatively, and glucocorticoids were tapered within a month. The mechanism of dual aldosterone/cortisol secretion is hypothesized to be due to overlap between genes coding for 11β-hydroxylase and aldosterone synthase, resulting in a chimeric gene with increased secretion of both enzymes, and, therefore, both hormones. Though dual secretion is rare, this case report stresses the importance of screening for cortisol excess, and hyperaldosteronism in the correct clinical setting, in patients with adrenal masses detected on imaging. A complete biochemical hormone evaluation should be performed regardless of the discovery of other hormone secreting syndromes, ideally preoperatively with a multidisciplinary team including endocrinology. The medical team should continue to bear in mind that the existence of one hypersecretory syndrome does not rule out the presence of a second or third, and hormonal excess syndromes may affect patient outcomes peri- and postoperatively. Presentation: Friday, June 16, 2023

Perception of Correctional Officers’ Legitimacy in South African Correctional Centers

Studies from developed western societies have shown that the legitimacy of correctional officers is pivotal to incarcerated offenders’ voluntary compliance and deference. However, we are uncertain if such an assertion holds for incarcerated offenders in transitional African correctional settings, such as South Africa. From a cross-sectional survey of participants from selected correctional centers in South Africa (Male = 89.6%; African = 85.1%; Mage = 25 years, SD = 0.81), this paper explores incarcerated offenders’ perception of the legitimacy of correctional officers. Findings indicate that procedural justice, the effectiveness of the correctional officers, gender, and offender citizenship predicted the perception of correctional officers’ legitimacy. The implications of these findings for the effective management of custodial institutions are discussed.

Methods of automation and interpretation of the quality educational tests in distributed virtual learning systems

The subject matter of the article is the development of mathematical and algorithmic support for intellectual tools, which allows you to conduct continuous control of the knowledge of students (subjects of study) objectively and comprehensively. The goal of the work is to create methods for assessing the quality of educational tests and automating such processes. The following tasks were solved in the article: formation of a testing model in a distributed virtual learning environment and a validity assessment model based on the content of sets of test tasks. The following methods used are – algebra of finite predicates and operations, methods of mathematical statistics and methods of intellectual data analysis. The following results were obtained – the principles of intellectual analysis of the value of reliability coefficients, validity coefficients, discriminability coefficient, the difficulty index of the task of assessing the knowledge of subjects of training are formulated. Conclusions: the application of methods of formalization of test evaluation, analysis of software requirements, software development confirm the need to introduce quantitative methods of assessing students' knowledge into educational practice. The introduction of quantitative methods involves the correct setting of control goals, the selection of the measurement object and the selection of measurement tools. The use of pedagogical tests contributes to the effective implementation of all control functions and corresponds to its main principles for solving the problem of assessing the quality of tests, based on distributed virtual learning models and analysis methods. A test example of calculations was developed, with the help of which the efficiency of the proposed methods was researched.

Dementia care behind prison walls: A descriptive study understanding nurse’s knowledge and educational needs

Aim/objectiveTo establish correctional nurses’ dementia knowledge base and identify their educational needs related to caring for prisoners with dementia. BackgroundThe aging prison population is growing, posing a heightened risk of dementia among older inmates. This study examined the knowledge and perceived educational needs of nurses caring for prisoners with dementia. DesignA descriptive study which was qualitative in nature was undertaken. MethodsData was collected using an online survey which included Demographics, the Dementia Knowledge Assessment Tool 2 and open-ended questions. Descriptive statistics such as percentages and frequency were used to analyse the quantitative data and a qualitative analysis was undertaken to identify common themes and extract meaningful insight from the open-ended questions. ResultsNurses showed a general understanding of dementia and its environmental impact but lacked knowledge of late-stage changes. Eight main themes relating more broadly to the environmental and staffing challenges faced by nurses are presented. ConclusionAlthough participants appeared to have a reasonable dementia knowledge base the study highlights the need for specific dementia education and support focussed on the correctional setting and collaborative partnerships with dementia experts in the community.

SANA: Sensitivity-Aware Neural Architecture Adaptation for Uniform Quantization

Uniform quantization is widely taken as an efficient compression method in practical applications. Despite its merit of having a low computational overhead, uniform quantization fails to preserve sensitive components in neural networks when applied with ultra-low bit precision, which could lead to a non-trivial accuracy degradation. Previous works have applied mixed-precision quantization to address this problem. However, finding the correct bit settings for different layers always demands significant time and resource consumption. Moreover, mixed-precision quantization is not well supported on current general-purpose machines such as GPUs and CPUs and, thus, will cause intolerable overheads in deployment. To leverage the efficiency of uniform quantization while maintaining accuracy, in this paper, we propose sensitivity-aware network adaptation (SANA), which automatically modifies the model architecture based on sensitivity analysis to make it more compatible with uniform quantization. Furthermore, we formulated four different channel initialization strategies to accelerate the quantization-aware fine-tuning process of SANA. Our experimental results showed that SANA can outperform standard uniform quantization and other state-of-the-art quantization methods in terms of accuracy, with comparable or even smaller memory consumption. Notably, ResNet-50-SANA (24.4 MB) with W4A8 quantization achieved 77.8% top-one accuracy on ImageNet, which even surpassed the 77.6% of the full-precision ResNet-50 (97.8 MB) baseline.

Using Particle Swarm Optimization for Power System Stabilizer and energy storage in the SMIB system under load shedding conditions

Generator instability, which manifests as oscillations in frequency and rotor angle, is brought on by sudden disruptions in the power supply. Power System Stabilizer (PSS) and Energy Storage are additional controllers that enhance generator stability. Energy storage types include superconducting magnetic (SMES) and capacitive (CES) storage. If the correct settings are employed, PSS, SMES, and CES coordination can boost system performance. It is necessary to use accurate and effective PSS, SMES, and CES tuning techniques. Artificial intelligence techniques can replace traditional trial-and-error tuning techniques and assist in adjusting controller parameters. According to this study, the PSS, SMES, and CES parameters can be optimized using a method based on particle swarm optimization (PSO). Based on the investigation's findings, PSO executes quick and accurate calculations in the fifth iteration with a fitness function value of 0.007813. The PSO aims to reduce the integral time absolute error (ITAE). With the addition of a load-shedding instance, the case study utilized the Single Machine Infinite Bus (SMIB) technology. The frequency response and rotor angle of the SMIB system are shown via time domain simulation. The analysis's findings demonstrate that the controller combination can offer stability, reducing overshoot oscillations and enabling quick settling times.

Complete NLO corrections to off-shell tt¯Z\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \ extrm{t}\\overline{\ extrm{t}}\ extrm{Z} $$\\end{document} production at the LHC

Measuring precisely top-pair-associated processes at hadron colliders will become possible with the upcoming LHC running stages. The increased data statistics will especially enable differential measurements leading to an improved characterisation of such processes. Aiming at a consistent data-theory comparison, precise Standard-Model predictions are needed, including higher-order corrections and full off-shell effects. In this work we present NLO-accurate predictions for the production and decay of a top-antitop pair in association with a Z boson at the LHC, in the multi-lepton decay channel. The complete set of LO contributions and NLO corrections of EW and QCD origin is included. The calculation is based on full matrix elements, computed with all resonant and non-resonant contributions, complete spin correlations and interference effects. Integrated and differential cross-sections are presented for a realistic fiducial setup.

Predictors of Seeking Mental Health Treatment in Black Men: Therapy Fears and Expectations About Counseling

The current study examined predictors of mental health treatment among Black men while incarcerated. Participants were 76 individuals who identified as Black Americans and were recruited from a correctional setting. Using secondary data analysis (Shaw, L. B., & Morgan, R. D. (2011). Inmate attitudes toward treatment: Mental health service utilization and treatment effects. Law and Human Behavior, 35(4), 249–261. https://doi.org/10.1007/s10979-010-9233-5.), results indicated that Black men with a mental health diagnosis were more likely than those without a diagnosis to report receiving mental health treatment while incarcerated. Additionally, linear regression analyses indicated that only expectations about treatment (i.e., personal commitment; not therapy fears or history of mental health diagnosis) significantly predicted the current use of mental health treatment. Implications for research and practice are discussed.

Treatments for ADHD in adults in jails, prisons and correctional settings: a scoping review of the literature

BackgroundAttention-Deficit / Hyperactivity Disorder (ADHD) is prevalent at a higher rate in correctional settings than in the general population. Treatment of ADHD in this environment is challenging as stimulants, the most common treatment for ADHD, require cautious prescribing in the context of frequent substance use disorders (SUD) and diversion in the institutional setting. In addition, both pharmacological and non-pharmacological treatment approaches require significant staff resources. The aim of this scoping review is to map and summarize all literature addressing treatment of ADHD specifically in correctional settings, synthesize the evidence supporting various approaches, and highlight areas for future research. Due to the limited number of primary research studies addressing this question directly, we chose a scoping review methodology that would allow us to explore what kinds of studies and literature exist and include all types of articles directly related to our question.ResultsFive-hundred sixty-five relevant articles were screened. Thirty-two articles were included in the final review. Eleven of the articles reported primary research. Five of these articles were based on three randomized controlled trials. Among randomized controlled trials on the effect of stimulants, inclusion criteria, outcome measures and effectiveness varied widely. Non-male and non-white populations were under-represented. Among review articles and recommendations opinion was inconsistent, with some recommending stimulants as first-line treatment and others recommending they be avoided altogether. The effect of non-stimulant medications was examined in 2 small studies. The only non-pharmacological treatment examined was dialectical behavior therapy, and only feasibility was reported. Four articles provided practice recommendations from consensus or expert opinion. Two of these recommended stimulants as first-line treatment, and two recommended stimulants as treatment of last resort.ConclusionsWe found a diverse but shallow literature addressing our research question. Primary research in the corrections setting is limited and varies in inclusion criteria, outcomes studied, and effectiveness. Recommendations on treatment are inconsistent. Future research should address methods of diagnosis, the role of non-stimulants, non-pharmacological interventions, non-male and non-white people who are incarcerated (PWAI), and effects of treatment method on patients, staff and other PWAI. Better research and guidance on treating ADHD has potential to improve health of PWAI, the institutional environment, and resource utilization.

Unsupervised machine learning to classify the confinement of waves in periodic superstructures.

We propose a rigorous method to classify the dimensionality of wave confinement by utilizing unsupervised machine learning to enhance the accuracy of our recently presented scaling method [Phys. Rev. Lett.129, 176401 (2022)10.1103/PhysRevLett.129.176401]. We apply the standard k-means++ algorithm as well as our own model-based algorithm to 3D superlattices of resonant cavities embedded in a 3D inverse woodpile photonic band gap crystal with a range of design parameters. We compare their results against each other and against the direct usage of the scaling method without clustering. Since the clustering algorithms require the set of confinement dimensionalities present in the system as an input, we investigate cluster validity indices (CVIs) as a means to find these values. We conclude that the most accurate outcome is obtained by first applying direct scaling to find the correct set of confinement dimensionalities, and subsequently utilizing our model-based clustering algorithm to refine the results.

Risk Factors for Alcohol Withdrawal-related Hospital Transfer in a Correctional Setting.

A major health concern among individuals with alcohol use disorder is alcohol withdrawal syndrome (AWS), where individuals with physical dependence on alcohol may experience withdrawal signs and symptoms upon stopping or reducing alcohol use. AWS has a range of severity, with the most severe cases referred to as complicated AWS, presenting as seizure or signs and symptoms indicative of delirium or new onset of hallucinations. In the general community, risk factors or predictors of complicated AWS among hospitalized patients have been described, but there is no literature that examines such risk factors in a correctional population. The Los Angeles County Jail (LACJ) is the nation's largest jail system and manages 10-15 new patients per day for AWS. Here we aim to identify the risk factors associated with alcohol withdrawal-related hospital transfers among incarcerated patients being managed for AWS in the LACJ. From January 1, 2019 to December 31, 2020, data were gathered about LACJ patients who required transfer to an acute care facility for alcohol withdrawal-related concerns while on the Clinical Institute Withdrawal Assessment for Alcohol revised (CIWA-Ar) protocol. Log regression analysis was performed to generate an odds ratio for acute care facility transfer for the following variables: race, sex assigned at birth, age, CIWA-Ar scores, highest systolic blood pressure (SBP), and highest heart rate (HR). Out of 15,658 patients on CIWA-Ar protocol during this 2-year timeframe, a total of 269 (1.7%) were transferred to an acute care facility for alcohol withdrawal-related concerns. Of those 269 patients, significant risk factors associated with withdrawal-related hospital transfer included: Other race (OR 2.9, 95% CI 1.5-5.5), male sex assigned at birth (OR 1.6, 95% CI 1.0-2.5), age ≥ 55 years (OR 2.3, 95% CI 1.1-4.9), CIWA-Ar score 9-14 (OR 4.1, 95% CI 3.1-5.3), CIWA-Ar score ≥ 15 (OR 21.0, 95% CI 12.0-36.6), highest SBP ≥ 150 mmHg (OR 2.3, 95% CI 1.8-3.0), highest HR ≥ 110 bpm (OR 2.8, 95% CI 2.2-3.8). Among patients studied, the higher CIWA-Ar score was the most significant risk factor associated with alcohol withdrawal-related hospital transfer. Other significant risk factors identified are race other than Hispanic, white, and African American; male sex assigned at birth; age ≥ 55 years; highest SBP ≥ 150mmHg; and highest HR ≥ 110 bpm.

Corrections for Geostationary Cloud Liquid Water Path Using Microwave Imagery

Abstract Geostationary observations provide measurements of the cloud liquid water path (LWP), permitting continuous observation of cloud evolution throughout the daylit portion of the diurnal cycle. Relative to LWP derived from microwave imagery, these observations have biases related to scattering geometry, which systematically varies throughout the day. Therefore, we have developed a set of bias corrections using microwave LWP for the Geostationary Operational Environmental Satellite-16 and -17 (GOES-16 and GOES-17) observations of LWP derived from retrieved cloud-optical properties. The bias corrections are defined based on scattering geometry (solar zenith, sensor zenith, and relative azimuth) and low cloud fraction. We demonstrate that over the low-cloud regions of the northeast and southeast Pacific, these bias corrections drastically improve the characteristics of the retrieved LWP, including its regional distribution, diurnal variation, and evolution along short-time-scale Lagrangian trajectories. Significance Statement Large uncertainty exists in cloud liquid water path derived from geostationary observations, which is caused by changes in the scattering geometry of sunlight throughout the day. This complicates the usefulness of geostationary satellites to analyze the time evolution of clouds using geostationary data. Therefore, microwave imagery observations of liquid water path, which do not depend on scattering geometry, are used to create a set of corrections for geostationary data that can be used in future studies to analyze the time evolution of clouds from space.

Correlation between Chest Computed Tomography Score and Laboratory Biomarkers in the Risk Stratification of COVID-19 Patients Admitted to the Emergency Department.

It has been reported that mid-regional proadrenomedullin (MR-proADM) could be considered a useful tool to stratify the mortality risk in COVID-19 patients upon admission to the emergency department (ED). During the COVID-19 outbreak, computed tomography (CT) scans were widely used for their excellent sensitivity in diagnosing pneumonia associated with SARS-CoV-2 infection. However, the possible role of CT score in the risk stratification of COVID-19 patients upon admission to the ED is still unclear. The main objective of this study was to assess if the association of the CT findings alone or together with MR-proADM results could ameliorate the prediction of in-hospital mortality of COVID-19 patients at the triage. Moreover, the hypothesis that CT score and MR-proADM levels together could play a key role in predicting the correct clinical setting for these patients was also evaluated. Epidemiological, demographic, clinical, laboratory, and outcome data were assessed and analyzed from 265 consecutive patients admitted to the triage of the ED with a SARS-CoV-2 infection. The accuracy results by AUROC analysis and statistical analysis demonstrated that CT score is particularly effective, when utilized together with the MR-proADM level, in the risk stratification of COVID-19 patients admitted to the ED, thus helping the decision-making process of emergency physicians and optimizing the hospital resources.

Not a Rare Disease Anymore? A Case of Ocular Syphilis at the Correctional Facility.

Los Angeles County has been facing a syphilis crisis since 2018. Cases of ocular syphilis have become increasingly identified and reported in the past few years, predominantly in HIV-positive men. Here we report a case of ocular syphilis in an otherwise healthy 49-year-old male in the Los Angeles County jail. This case study emphasizes the importance of increasing awareness of ocular syphilis so that it can be diagnosed promptly to prevent irreversible vision loss. Health care providers who work in the correctional facility setting need to be aware of this disease entity given that they serve a population with high risk of sexually transmitted diseases (STDs). This case study further stresses the importance of initial screening for sexual history and/or history of STDs within this population.

Associated production of a top-quark pair with two isolated photons at the LHC through NLO in QCD

We report on the computation of NLO QCD corrections to top-quark pair production in association with two photons at the LHC. Higher-order effects and photon bremsstrahlung are taken into account in the production and decays of the top-quark pair. Top-quark and W-boson decays are treated in the Narrow Width Approximation conserving spin correlations up to NLO in QCD. This is the first time that the complete set of NLO QCD corrections to the ppto toverline{t}gamma gamma process including top-quark decays is calculated. We present results at the integrated and differential cross-section level in the di-lepton and lepton + jet channel. In addition, we investigate the effect of photon bremsstrahlung in toverline{t} production and top-quark decays, as well as the mixed contribution. The latter contribution, in which two photons occur simultaneously in the production and decay of the toverline{t} pair, proved to be significant at both the integrated and differential cross-section level.

A TAGUCHI-TOPSIS HYBRID TECHNIQUE TO ENHANCE THE FRETTING WEAR CHARACTERISTICS FOR SiC AND SILICA-ENRICHED BLA-REINFORCED AZ91D Mg ALLOY-BASED MMCs

This investigation intends to come up with a cost-efficient and easily available bamboo leaf ash (BLA) which has high content of Silica, as an effective and complimenting reinforcement for the production of magnesium alloy-based metal matrix composites. By incorporating SiC and BLA reinforcement to AZ91D Mg alloy, the composites were made using the bottom pouring stir casting technique. The ratio between SiC and BLA in the composite, respectively, varied as 0:0, 6:0, 0:6, 4:2, 3:3, 2:4 wt.%. Fretting wear is one of the fundamental modes of wear for any mating parts which have vibration with low amplitude. In this study, an integrated Taguchi-TOPSIS is adapted to make the process variables more optimal for fretting wear of composites. Material composition, load, temperature, time, frequency and stroke length are selected as process parameters. The objective is to minimize the coefficient of friction, volume loss and surface roughness. Using the TOPSIS approach, the multi-criteria optimization approach was reduced to a single-criteria issue. The results revealed AZ91D/2 wt.% SiC/4 wt.% BLA, 10N, room temperature, 30-min, 30 Hz and 0.7 mm stroke as optimal parameters. Microscopic study demonstrates that fretting wear occurs in the partial slip zone for the composite tested at optimal condition. With temperature, the wear regime in composites shifts from partial slip to mixed fretting, whereas in alloys, the wear regime shifts from mixed fretting to gross slip. When the correct set of circumstances are available, hybrid composite can function well as a replacement for traditional materials in machineries vulnerable to fretting wear.

Racial, Ethnic, Sex, and Age Differences in COVID-19 Cases, Hospitalizations, and Deaths Among Incarcerated People and Staff in Correctional Facilities in Six Jurisdictions, United States, March-July 2020.

To examine disparities by sex, age group, and race and ethnicity in COVID-19 confirmed cases, hospitalizations, and deaths among incarcerated people and staff in correctional facilities. Six U.S. jurisdictions reported data on COVID-19 confirmed cases, hospitalizations, and deaths stratified by sex, age group, and race and ethnicity for incarcerated people and staff in correctional facilities during March 1- July 31, 2020. We calculated incidence rates and rate ratios (RR) and absolute rate differences (RD) by sex, age group, and race and ethnicity, and made comparisons to the U.S. general population. Compared with the U.S. general population, incarcerated people and staff had higher COVID-19 case incidence (RR = 14.1, 95% CI = 13.9-14.3; RD = 6,692.2, CI = 6,598.8-6,785.5; RR = 6.0, CI = 5.7-6.3; RD = 2523.0, CI = 2368.1-2677.9, respectively); incarcerated people also had higher rates of COVID-19-related deaths (RR = 1.6, CI = 1.4-1.9; RD = 23.6, CI = 14.9-32.2). Rates of COVID-19 cases, hospitalizations, and deaths among incarcerated people and corrections staff differed by sex, age group, and race and ethnicity. The COVID-19 hospitalization (RR = 0.9, CI = 0.8-1.0; RD = -48.0, CI = -79.1- -16.8) and death rates (RR = 0.8, CI = 0.6-1.0; RD = -11.8, CI = -23.5- -0.1) for Black incarcerated people were lower than those for Black people in the general population. COVID-19 case incidence, hospitalizations, and deaths were higher among older incarcerated people, but not among staff. With a few exceptions, living or working in a correctional setting was associated with higher risk of COVID-19 infection and resulted in worse health outcomes compared with the general population; however, Black incarcerated people fared better than their U.S. general population counterparts.

Construction of grinding wheel decision support system using random forests for difficult-to-cut material

The grinding wheels comprise three elements (abrasive grain, bonding material, and pores) and five factors (grain size, grain type, grade, structure, and bonding strength). However, owing to their impact on the material's surface quality and grinding efficiency, optimal combinations must be identified for each work material. The correct setting of the elements and factors is challenging and requires in-depth knowledge and engineering expertise. In this study, a random forest data-mining method was used to construct a system that can determine the abrasive grain, grain size, and bonding strength from various combinations of material property values. The verification of the developed system was conducted through grinding experiments on difficult-to-cut materials using the general-purpose grinding wheels recommended by the system. This system facilitates highly accurate interpolation prediction by adding an interpolative property value set in 10% increments to the learning data. A grinding experiment using Inconel 718, a difficult-to-cut material that did not exist in the learning database, resulted in a 12% reduction in wear on the recommended grinding wheels. Thus, the usefulness of the system constructed using the random forest method was established.