Correctional Settings Research Articles

Reaching for 90:90:90 in Correctional Facilities in South Africa and Zambia: Virtual Cross-Section of Coverage of HIV Testing and Antiretroviral Therapy During Universal Test and Treat Implementation.

People in correctional settings are a key population for HIV epidemic control. We sought to demonstrate scale-up of universal test and treat in correctional facilities in South Africa and Zambia through a virtual cross-sectional analysis. We used routine data on 2 dates: At the start of universal test and treat implementation (time 1, T1) and 1 year later (time 2, T2). We obtained correctional facility census lists for the selected dates and matched HIV testing and treatment data to generate virtual cross-sections of HIV care continuum indicators. In the South African site, there were 4193 and 3868 people in the facility at times T1 and T2; 43% and 36% were matched with HIV testing or treatment data, respectively. At T1 and T2, respectively, 1803 (43%) and 1386 (36%) had known HIV status, 804 (19%) and 845 (21%) were known to be living with HIV, and 60% and 56% of those with known HIV were receiving antiretroviral therapy (ART). In the Zambian site, there were 1467 and 1366 people in the facility at times T1 and T2; 58% and 92% were matched with HIV testing or treatment data, respectively. At T1 and T2, respectively, 857 (59%) and 1263 (92%) had known HIV status, 277 (19%) and 647 (47%) were known to be living with HIV, and 68% and 68% of those with known HIV were receiving ART. This virtual cross-sectional analysis identified gaps in HIV testing coverage, and ART initiation that was not clearly demonstrated by prior cohort-based studies.

Introduction of ICD-11 in Germany: Seizing opportunities together.

With the new ICD-11 developed by the WHO and translated into German for use in Germany by the Federal Institute for Drugs and Medical Devices, the German healthcare system is facing a change that is more than a simple change of a medical coding system. The ICD-11 modernises the coding system, for example, by including new, separate health conditions such as sleep-wake disorders and conditions related to sexual health, thus making the corresponding diseases more visible. The ICD-11 is more precise than the ICD-10: it allows cross-referencing between diagnoses, symptoms, functionality and locations and partially abandons the strict hierarchy of the ICD-10. In addition, a greater number of rare diseases are represented with their own specific code than was previously possible with ICD-10. Finally, the ICD-11 is also significantly more "modern" than the ICD-10 (which dates back to pre-digital times) in that it enables new, digitally-supported processes, such as keywords flexibility and sustainability when updating the system as well as actual coding at the point of care. The switch to ICD-11 can be a great opportunity for the German healthcare system that should not be missed. It will benefit health service research, which at best will be able to work with much more detailed and correct data sets. But medical care will also benefit because the ICD-11 reflects current medical knowledge. In addition, certain illnesses will be removed from the psychiatric category, meaning that those affected will no longer be stigmatised by their classification in the ICD. The improved coding of diagnoses will ultimately also support guideline-based treatments. However, the changeover is only the first step. The challenges - also for health service research - include in particular the latency of introduction and uniform use as well as the necessary change in coding habits. For ICD-11 to be a success in Germany, authorities, the medical profession, payers and patients must work together on strategies to ensure not only a rapid but also a comprehensive implementation that maximises the potential of ICD-11.

The interdependence of caring, safety, and health in correctional settings: Analysis of a survey of security staff in a large county jail system

The health of incarcerated populations is intertwined with the health of security staff, but the social mechanisms, and especially the specific interventions, that might mitigate these health harms are underexplored. We examine one possible mechanism of interrelated health harms: whether and how jail security staff are willing and able to care for mentally ill detainees. We hypothesize that the attitudes of security staff towards care affect the well-being of everyone in a jail setting—staff, as well as detainees. Analyzing 539 anonymous respondent surveys administered to a stratified cluster sample of security staff working in a large U.S. county jail system, we (1) describe the prevalence of a perceived duty to care and availability of caring resources among security staff and (2) analyze whether variations in a duty to care and caring resources predict outcomes associated with staff and detainee well-being. Across five maximum likelihood models estimated, both perceived duty to care and availability of caring resources are significantly associated with collaborative relationships with medical staff, increased perceptions of personal safety, decreased frequency of hostile encounters, and better self-reported health outcomes. Our models explain 20 percent of the variation in self-reported health outcomes (R2 = .20), a meaningful effect of care on security personnel's well-being. Our findings suggest security staff have an often-overlooked duty to care akin to that experienced by healthcare staff. Among healthcare staff, dual loyalty trainings have successfully amplified caring duties relative to security duties; similar trainings for security staff might better leverage their caring duties to improve both staff and detainee well-being.

Development and implementation of a self-directed violence prevention training program for correctional behavioral health providers: a clinical trial study protocol

BackgroundSelf-directed violence (SDV) comprises both suicide and self-injury and represents a pressing problem among incarcerated persons. Negative impacts of SDV in correctional settings also extend to behavioral health clinicians (BHCs) (e.g., job turnover). Correctional SDV risk assessment and management standards include staff training as part of the comprehensive approach. The Core Competency Model for Corrections (CCM-C) is a novel, evidence-informed training program for BHCs covering both clinician self-management and clinical care skills.MethodsThis pilot trial is a type 3 hybrid implementation–effectiveness approach. It will employ a wait-list control sequential cross-over design. Participants (N = 50–100) will be BHCs employed by the North Carolina Department of Adult Corrections. Following stratification for years of clinical experience, BHCs will be randomly assigned to (1) a training group that receives CCM-C immediately and (2) a wait-list control receiving CCM-C approximately 6 weeks later. Electronically administrated survey evaluation will occur across baseline and two follow-up (i.e., 2 weeks after each training session) time points.DiscussionThe primary outcome is feasibility assessed through collaboration with a Corrections Advisory Panel and feedback from BHCs. Secondary effectiveness outcomes that will be evaluated over time include SDV-related knowledge, attitudes, stigma, and intent to use training content. We will examine a tertiary outcome, namely compassion fatigue. Clinical trial limitations and impacts are discussed.Trial registrationClinicaltrials.gov, NCT06359574. This study was registered on 04/05/2024.

“Helping Me Get Through the Day”: The Importance of Social Contact and Support for Incarcerated Young People During the COVID-19 Pandemic

Background: There is limited knowledge about how incarcerated young people have been affected by the COVID-19 pandemic. An improved understanding of the impact of pandemic circumstances could help to advance a multitude of practices and policies, including those that strengthen personal relationships. Objectives: This study aimed to (a) describe self-reported perceptions that social contact and support for incarcerated young people are powerful protective factors with the potential to attenuate the negative impacts of incarceration, (b) explore the impact of the COVID-19 pandemic on their personal and relational well-being, (c) determine the extent to which the pandemic restricted access to social support and other resources, and (d) consider potential identity-related differences in these perceptions and impacts. Methods: This exploratory study employed interpretative phenomenological analysis (Smith et al., 2010) of semi-structured interviews with 30 incarcerated youth in an adult correctional setting, ages 16-21 years, in addition to some preliminary information about social contact and multidimensional social support. Results: Significant benefits of family support were identified, such as moral guidance, hopefulness, and goal maintenance, as well as the necessity of relationships for youth well-being given the especially challenging circumstances created by the pandemic. Limitations and barriers to social support, as well as access to services, were identified that may have implications for programmatic and system-level changes. Conclusion: Contact with and involvement in supportive relationships is important for incarcerated young people, perhaps especially so during times of crisis. Specific implications for both forensic social work practice, such as family-focused advocacy and services, and further qualitative social work research, including with incarcerated young people, are further explored.

Art therapy in mitigating pervasive loss and grief within correctional settings

Those incarcerated often experience different types of loss. Because of where they are, such experiences often result in unresolved, unacknowledged, disenfranchised grief. Recognizing such vulnerability by those who are incarcerated is often difficult and, in some ways, dangerous. Not addressing such losses further exacerbates their chances of completing any respective programs established for success. Art therapy has been effective in alleviating such complications, including for those incarcerated inside correctional institutions. This article draws from the authors’ experiences of providing art therapy services in a statewide program for youthful offenders–those who are 14–22 years old but in the adult institutions–to mitigate obstacles for completing their General Education Degree—and will provide an overview of the various losses that incarcerated individuals experience, their potential grief responses, and the value of art therapy in addressing such grief. The case vignettes provided underscore how, as their expressions were made visible and subsequently seen, validated and acknowledged through art therapy, the incarcerated youth were able to begin the process of moving beyond their grief and attend to their goals, allowing them to succeed in their respective programs, which may include but are not limited to; re-entry focused, substance abuse, GED prep classes, college courses and technical trade programs.

The Impact of Mindfulness Apps and Cognitive Behavioral Therapy on Prisoners' Mental Health

Prisoners' mental health and overall wellbeing are given significant consideration throughout the COVID-19 pandemic. The correctional facility's setting separates prisoners from the outside world, and their lack of access to modern medical care will result in depressive symptoms and other mental health issues. Prisons can benefit from the cost-effective and useful usage of CBT and mindfulness apps to enhance the mental health and general well-being of their inmates. This study provides an overview of possible ways to use smartphone apps to lessen mental health problems among prisoners. Applications of mindfulness have shown potential benefits in reducing mental health issues, including anxiety, depression, and stress. This paper reviews existing research on the effectiveness of these interventions and explores the feasibility of implementing such applications in prison settings. Although long-term effects are not yet well-documented, preliminary findings suggest that these apps could serve as a valuable tool for enhancing mental health care in correctional facilities. It is worthwhile to employ these applications as a pilot test to investigate their benefits further. By integrating technology with traditional practices and addressing challenges such as noncompliance and lack of personalization, prison systems can develop more effective and engaging mental health interventions. These efforts can contribute to better mental health outcomes, reduced recidivism, and a more rehabilitative prison environment. Future research should focus on long-term studies and strategies to improve adherence to online psychological treatments.

Directly Observed Therapy in Correctional Settings

What Is the Issue? Directly observed therapy ensures patient adherence to a prescribed treatment regimen by having a health care worker watch the patient take the drug (s). However, it can result in patients needing to wait to see an available health care provider, and long waits can lead to patients being late for or missing out on work, school, or other therapy. What Did We Do? We conducted a literature search to identify, gather, synthesize, and summarize relevant evidence to inform our understanding of how directly observed therapy is used and what drugs are administered via directly observed therapy in correctional settings in Canada and internationally. What Did We Find? We identified practice manuals and guidelines from Canada, British Columbia, Manitoba, Nova Scotia, Ontario, and Saskatchewan, as well as Australia and the UK, related to using directly observed therapy in correctional settings. Drugs recommended to be provided via directly observed therapy included methadone, other drugs for opioid use disorder, and drugs at high risk of misuse or diversion (e.g., benzodiazepines, opioids). Most documents noted the high risk of misuse and/or diversion, suggesting these are the main justifications for providing drugs via directly observed therapy. Some strategies that may help reduce administration or wait times include an in-possession policy (where patients keep their drugs and self-administer if possible) and long-acting injectable forms of drugs (e.g., buprenorphine, antipsychotics). In-possession is typically not recommended for drugs at high risk of misuse and diversion. Still, it may be allowed for specific drugs or on a case-by-case basis, considering factors like the particular drug, available local resources, and patient characteristics. What Does This Mean? When considering alternatives to directly observed therapy, it may be helpful to assess risks, which may be influenced by the facility, the drug being provided, and individual patients. It may also be beneficial to implement methods of monitoring drug adherence and checking for potential misuse or diversion, such as by reviewing drug administration or supply records. While some alternatives to directly observed therapy may help to reduce time spent administering drug, some potential risks include increased risk of misuse and/or diversion and higher cost of drugs. Additional time may be required initially to allow staff to learn and adapt to the new process. It may be helpful to consider alternatives to directly observed therapy as additional options for patients, allowing patients to have input into what drug they will take based on their needs and concerns.

Medical Decision Making in Correctional Facilities: Highlighting Gaps and Advocating for Policy Change.

In the United States, a disproportionately high number of incarcerated individuals suffer from serious mental illnesses, substance use disorders, chronic medical conditions, infectious diseases, and traumatic brain injuries. Correctional facilities are often ill-equipped to address the incarcerated community's physical and mental health needs. Current laws and policies remain outdated and do not adequately address the complex health issues faced by incarcerated individuals, particularly the aging and terminally ill patients in correctional settings. We present a case of a male with schizophrenia whose ongoing psychiatric symptoms impaired his decisional capacity, leading to him to refuse medical treatment for an initially treatable medical condition, ultimately resulting in his death due to the lack of a surrogate decision-maker. This case underscores the urgent need for policy revisions to assign medical decision-making authority for individuals in custody and highlights potential interventions to bridge existing gaps in care for this population.

Changes in maternal blood and placental lipidomic profile in obesity and gestational diabetes: Evidence for sexual dimorphism.

Obesity and gestational diabetes (GDM) are associated with adverse pregnancy outcomes and program the offspring for cardiometabolic disease in a sexually dimorphic manner. The placenta transfers lipids to the fetus and uses these substrates to support its own metabolism impacting the amount of substrate available to the growing fetus. We collected maternal plasma and placental villous tissue following elective cesarean section at term from women who were lean (pre-pregnancy BMI 18.5-24.9), obese (BMI>30) and type A2 GDM (matched to obese BMI) with male or female fetus (n=4 each group). Lipids were extracted and fatty acid composition of different lipid classes were analyzed by LC-MS/MS analysis. Significant changes in GDM vs obese, GDM vs lean, and obese vs lean were determined using t-test with a Tukey correction set at p<0.05. In placental samples 436 lipids were identified, among which 85 showed significant changes. Of note only in male placentas significant decreases in C22:6 - docosahexaenoic acid (DHA) in phosphatidylcholine (PC) and triglyceride lipid species were seen when comparing tissue from GDM women to lean. In maternal plasma we observed no effect of obesity. GDM or fetal sex. This is the first study assessing fatty acid composition of lipids in matched maternal plasma and placental tissue from lean, obese, and GDM women stratified by fetal sex. It highlights how GDM affects distribution of fatty acids in lipid classes changes in a sexually dimorphic manner in the placenta.

Identification of fermented soy sauce and blended soy sauce based on dielectric spectra

A new method based on dielectric properties has been developed to distinguish blended soy sauce from fermented soy sauce. Fifty samples of pure fermented soy sauce and blended soy sauce with different contents of hydrolyzed vegetable protein (HVP) were prepared. The dielectric constant and dielectric loss factor of all soy sauce samples in the 30 MHz–3000 MHz frequency range were measured using an impedance analyzer. The sample set was divided into a correction set and a prediction set using the joint x-y distances (SPXY) algorithm, and the partial least squares (PLS) and support vector machine (SVM) models were adopted to distinguish the different samples. The effects of selecting characteristic variables on model prediction using the full spectra (FS), principal component analysis (PCA), and successive projection algorithm (SPA) were compared. Results indicate that the discriminant effect of the PLS model was better than that of the SVM model overall. The SPA–PLS model had the best predictive performance among the six developmental models. The correlation coefficients of the correction set and prediction set were 0.9205 and 0.9096, respectively. The root mean square error of the calibration set was 1.3699 and that of the prediction set was 1.5950. The study demonstrated that the combination of dielectric spectra and stoichiometry can be utilized to determine whether soy sauce has been adulterated.

Non-occlusive Mesenteric Ischemia – A Rare but Deadly Condition

Non-occlusive mesenteric ischemia is a rare but often fatal condition that occurs due to spasms in the splanchnic arteries leading to hypoperfusion, cellular death, bowel ischemia, and eventually perforation. Having a high clinical suspicion in the correct setting is crucial to identify and treating the medical condition quickly. This is a unique case of an 82-year-old Caucasian male who presented with peritonitis secondary to acute mesenteric ischemia caused by hypotension leading to the eventual finding of bowel ischemia and perforation. J MEDICINE 2024; 25: 176-178

Cognitive Assessment with Cognivue Clarity®: Psychometric Properties and Normative Ranges in a Diverse Population.

Detecting cognitive impairment in clinical practice is challenging as most instruments do not perform well in diverse samples of older adults. These same instruments are often used for eligibility into clinical trials making it difficult to recruit minoritized adults into Alzheimer's disease (AD) studies. Cognivue Clarity® is an FDA-cleared computerized 10-minute cognitive screening platform using adaptive psychophysics to detect cognitive impairment. Test the ability of Cognivue Clarity to measure cognitive performance in a diverse community sample compared with the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). This study enrolled 452 participants across 6 US study sites and completed both Cognivue Clarity device and RBANS. Psychometric properties and exploratory factor analysis of Cognivue Clarity were explored and comparisons against RBANS across different age, sex, education, and ethnoracial groups were conducted. Participants had a mean age of 47.9±16.1 years (range: 18-85), 63.6% were female, 45.9% had ≤12 years of education, 31.2% were African American and 9.2% were Hispanic. Cognivue Clarity had strong internal consistency, test-retest reliability and minimal practice effects. A 4-factor structure (Memory, Attention, Visuomotor, and Discrimination) had excellent goodness-of-fit. Normalizing age effects improved performance. Race and education effects were similar to those seen with RBANS. Cognivue Clarity had strong correlations with RBANS. Our study supports the use of Cognivue Clarity as an easy-to-use, brief, and valid cognitive assessment that measures cognitive performance. In the correct clinical setting, Cognivue Clarity may identify individuals with likely cognitive impairment who could be candidates for AD research studies.

Prognostic Factors in Idiopathic Sudden Sensorineural Hearing Loss: The Experience of Two Audiology Tertiary Referral Centres.

Background and Objectives: Although different hypotheses have been proposed over time, there is a dearth of information on factors able to predict the response to treatment for idiopathic sudden sensorineural hearing loss (ISSNHL) and hearing recovery. The aim of this study was to apply univariate and multivariate statistical models in a retrospective clinical setting of patients given therapy for ISSNHL at our tertiary academic audiological centers to investigate the prognostic value of clinical signs, symptoms, and comorbidities in relation to hearing recovery. Materials and Methods: The inclusion criteria were: history of ISSNHL diagnosed and treated at the Padova or Modena tertiary academic audiological centers; age ≥ 18 years; availability of clinical and audiological outcome data. The exclusion criteria were: hearing loss in acoustic schwannoma, endolymphatic hydrops, meningitis, trauma (head trauma, temporal bone fracture, acoustic trauma), barotrauma, perilymphatic fistula; exposure to noise levels ≥ 80 dB in the work environment; any unilateral or bilateral hearing loss (except for presbycusis) prior to ISSNHL diagnosis; any disorders affecting the external or middle ear; any previous ear surgery; refusal to make medical data available for research purposes. Eighty-six consecutive patients (38 females, 48 males; median age: 58 years; interquartile range: 47.00-69.00 years) were included. A systemic steroid therapy was administered to all patients, either orally with prednisone or intravenously with methylprednisolone. Second-line therapy included intratympanic steroid injections and/or hyperbaric oxygen therapy. Results: A multivariate logistic regression model was used, including the non-multicollinear clinical and audiological variables, which showed a p-value < 0.10 at the univariate analyses (namely age at diagnosis, time to diagnosis, oral steroid dose, and PTA on the affected side). Only PTA on the affected side retained its statistical significance (OR: 1.0615, 95% CI: 1.0185-1.1063, p = 0.005). Conclusions: The analysis of our data showed an association between the hearing threshold before treatment and the recovery from ISSNHL. Further studies on larger cohorts (especially in a prospective setting) are needed to shed more light on the prognostic role of clinical parameters in patients with ISSNHL. In a correct counseling setting, with regard to the patient's concern about not being able to recover hearing, it is important to offer perspectives of appropriate hearing rehabilitation approaches.

Risk to reoffend changes over time: Improving correctional programming through progress monitoring.

Progress monitoring is integral to evidence-based practice. Correctional settings, especially the supervision of individuals who commit sexual offenses, elicit public concern; negative outcomes can be catastrophic. Using a prospective longitudinal study of 2,939 men with a history of sexual offenses undergoing community supervision, we examined different models of progress monitoring and how they should inform the assessment of risk for sexual recidivism. We found that the most recent assessment scores of the ACUTE-2007 and STABLE-2007 sexual recidivism risk tools provided the best information about reoffending risk compared to using (a) the worst period of adjustments (i.e., highest risk score), (b) the best period of adjustments (i.e., lowest risk score), or (c) a rolling average of scores. We also found that the latest STABLE-2007 scores incrementally predicted sexual recidivism beyond baseline risk as assessed by demographic and criminal history variables (Static-99R). We conclude that the risk for sexual recidivism changes over time and that community corrections is advanced by repeated assessment of dynamic (changeable) risk factors. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Lifetime HIV testing among three samples of adults with histories of incarceration in Southern California

ABSTRACT Justice-impacted persons may inconsistently access HIV testing. This cross-sectional secondary analysis investigates lifetime HIV testing prevalence among adults with prior histories of incarceration in Southern California, United States, participating in health-focused programming (n = 3 studies). Self-reported demographic and lifetime HIV testing data were collected between 2017–2023; descriptive analyses were conducted. Across the three samples, at least 74% of participants were male; Latino and African American individuals accounted for nearly two-thirds of participants. Lifetime HIV testing ranged from 72.8% to 84.2%. Males were significantly more likely than females to report never being tested in two samples and accounted for >95% of those never tested. No statistically significant differences in testing were observed by race/ethnicity. Single young adults (ages 18–26) were less likely than their partnered peers to report testing. HIV testing is critical for ensuring that individuals access prevention and treatment. HIV testing among justice-impacted adults in this study was higher than in the general population, potentially due to opt-out testing in correctional settings. Nevertheless, these findings underscore the importance of implementing targeted interventions to reduce structural (e.g., health insurance, access to self-testing kits) and social barriers (e.g., HIV stigma) to increase HIV testing among justice-impacted males and single young adults.

Limitations of Current Machine-Learning Models in Predicting Enzymatic Functions for Uncharacterized Proteins.

Thirty to seventy percent of proteins in any given genome have no assigned function and have been labeled as the protein "unknownme". This large knowledge gap prevents the biological community from fully leveraging the plethora of genomic data that is now available. Machine-learning approaches are showing some promise in propagating functional knowledge from experimentally characterized proteins to the correct set of isofunctional orthologs. However, they largely fail to predict enzymatic functions unseen in the training set, as shown by dissecting the predictions made for 450 enzymes of unknown function from the model bacteria Escherichia coli using the DeepECTransformer platform. Lessons from these failures can help the community develop machine-learning methods that assist domain experts in making testable functional predictions for more members of the uncharacterized proteome.

Exploring the impact of sequence context on errors in SNP genotype calling with whole genome sequencing data using AI-based autoencoder approach.

A critical step in the analysis of whole genome sequencing data is variant calling. Despite its importance, variant calling is prone to errors. Our study investigated the association between incorrect single nucleotide polymorphism (SNP) calls and variant quality metrics and nucleotide context. In our study, incorrect SNPs were defined in 20 Holstein-Friesian cows by comparing their SNPs genotypes identified by whole genome sequencing with the IlluminaNovaSeq6000 and the EuroGMD50K genotyping microarray. The dataset was divided into the correct SNP set (666 333 SNPs) and the incorrect SNP set (4 557 SNPs). The training dataset consisted of only the correct SNPs, while the test dataset contained a balanced mix of all the incorrectly and correctly called SNPs. An autoencoder was constructed to identify systematically incorrect SNPs that were marked as outliers by a one-class support vector machine and isolation forest algorithms. The results showed that 59.53% (±0.39%) of the incorrect SNPs had systematic patterns, with the remainder being random errors. The frequent occurrence of the CGC 3-mer was due to mislabelling a call for C. Incorrect T instead of A call was associated with the presence of T in the neighbouring downstream position. These errors may arise due to the fluorescence patterns of nucleotide labelling.

SENSITIVITY OF A 1D LAKE MODEL TO THE INPUT METEOROLOGICAL DATA

The paper evaluates how the choice of a source of meteorological data used as boundary conditions and the changes in model calibration parameters affect the adequate performance of a model of lake thermo- and hydrodynamics. The quality of simulation of water temperature dynamics in a small lake by a onedimensional GLM model using data from an automatic meteorological station on the lake shore, a state weather station and two global reanalyses was quantitatively assessed. It is shown that the best modeling result (RMSE of water temperature calculation 0,8-2,0°C, Nash-Sutcliffe efficiency &gt;0,7) can be achieved using data sets that explicitly provide incoming shortwave and longwave radiation fluxes. At the same time, good representation of the bottom water temperature requires correct setting of wind regime, which is only possible if data from instrumental ground-based observations at a stationary weather station are applied. Combining ground-based observations of wind speed, air temperature and humidity with radiation fluxes from global reanalyses makes it possible to achieve a calculation error ≤1°C at all depths.The analysis of model sensitivity to calibration parameters in case when the reanalysis data are applied showed that parameters related to wind mixing, i.e. the scaling factor for wind speed and constants related to the in-model description of wind impact energy, have the greatest influence on the final calculation error. If we change the intensity coefficients of other types of mixing during calibration it does not lead to an obvious trend in the quantitative estimates of modeling quality. It could also be reasonable to introduce correction multipliers to the values of air temperature and solar radiation fluxes, thus neutralizing the effect of unrepresentativeness of the meteorological data applied for a particular lake, as well as to correct the value of solar radiation extinction coefficient relative to the value obtained from the Secchi depth. The results of the study could be used to justify the choice of meteorological data source and to optimize the methods of calibration of lake thermal stratification models

Detection of Anthocyanins in Potatoes Using Micro-Hyperspectral Images Based on Convolutional Neural Networks.

The color potato has the function of both a food and vegetable. The color potato not only contains various amino acids and trace elements needed by the human body but also contains anthocyanins. Anthocyanins have many functions, such as antioxidation, inflammation inhibition, vision improvement, and cancer prevention, so colored potatoes are deeply loved by consumers and have good market prospects. However, at present, the detection of anthocyanin content in color potatoes mainly depends on chemical methods, which are time-consuming and laborious, so it is necessary to study a fast and accurate detection method. In this study, microscopic hyperspectral equipment was used to collect the spectral information of the outer skin and inner skin of potatoes. The original spectrum, pretreatment spectrum, and characteristic spectrum variables of the outer skin and inner skin were predicted by the convolution neural network (CNN) algorithm and partial least squares regression (PLS) algorithm, respectively, and the performance of the model was evaluated by the prediction set correlation coefficient (Rp), prediction set root mean square error (RMSEP), correction set correlation coefficient (Rc), correction set root mean square error (RMSEC), and residual prediction deviation (RPD). The results revealed that the inner skin Raw + CNN model constructed under raw spectral data is optimal with Rc = 0.9508, RMSEC = 0.0374%, Rp = 0.9461, RMSEP = 0.2361% and RPD = 4.4933. The inner skin Savitzky-Golay (SG) + Detrend (DET) + CNN model constructed from pre-processed spectral data is optimal with Rc = 0.9499, RMSEC = 0.0359%, Rp = 0.9439, RMSEP = 0.2384%, RPD = 4.6516. The inner skin DET + competitive adaptive reweighted sampling (CARS) +CNN model constructed from the feature-based spectral data was optimal with Rc = 0.9527, RMSEC = 0.0708%, Rp = 0.9457, RMSEP = 0.2711%, and RPD = 4.1623. It can be seen that the Rp, RMSEP, Rc, RMSEC, and RPD values for modeling the spectral information of the inner skin were higher than those of the outer skin under the three different spectral data. The prediction accuracy of the model built by the CNN algorithm was better than the conventional algorithm PLS, the application of the CNN algorithm in inner skin can achieve accurate prediction of anthocyanin content in potato.