algorithms for testing Research Articles (Page 1)

To evaluate the outcomes of a street medicine intervention offering syphilis testing and treatment to people experiencing homelessness in South Los Angeles, California-a population disproportionately affected by syphilis and underserved by traditional healthcare systems. From September 2024 to January 2025, a multidisciplinary street medicine team provided testing and treatment for syphilis during outreach visits to patients experiencing homelessness. A total of 99 patients were tested using the reverse syphilis testing algorithm. Demographic data included gender, race/ethnicity, substance use disorder, mental illness and HIV status. χ2 tests were used to evaluate associations between syphilis diagnosis and each demographic characteristic. Thirty-six (36.4%) of the 99 patients had reactive syphilis test results, with 94.4% (n=34) classified as late-stage infections. Of those diagnosed, 72.2% (n=26) were treated during follow-up visits. Statistically significant associations were found between syphilis diagnosis and gender (p=0.002), substance use disorder (p=0.008) and HIV status (p=0.020). Patients identifying as female or transgender female, and those with cooccurring substance use disorder or HIV, were more likely to be diagnosed with syphilis. This study demonstrates the feasibility and outcomes of delivering sexually transmitted infection care through street medicine. The high prevalence of late-stage syphilis and its syndemic overlap with substance use disorder and HIV underscores the need for low-barrier, community-based services. Street medicine interventions should be recognised and resourced as essential tools in public health responses to rising syphilis rates, particularly among unhoused populations.

Feasibility, accuracy, and effect of a rapid point-of-care serological test (SeroSelectTB) to identify presumptive pulmonary TB patients for confirmatory testing in Ethiopia, South Africa, and Tanzania: a multicenter, open-label, parallel-group, randomized, controlled trial.

Virtual evaluation method of bridge load-bearing capacity based on dynamic load test and intelligent algorithm

The primary aims of this best practice article are to provide a laboratory perspective of the merits and pitfalls of different markers currently in use in UK National Health Service (NHS) hospital laboratories, and how best these tests can be used for the detection of heavy (harmful) alcohol consumption. Included are suggested testing algorithms for carbohydrate-deficient transferrin (CDT), ethyl glucuronide (EtG), ethyl sulphate (EtS) and phosphatidylethanol (PEth16:0/18:1), for the purpose of creating suitable bench-to-bedside alcohol services in support of the delivery of hospital alcohol strategy, and the NHS long-term health plan.

The recognition of human activities through images represents a fundamental research domain in computer vision and pattern recognition, with practical applications in human–computer interaction, video analysis, and surveillance. This research objective is to develop an enhanced neurocomputing network for humans using Deep Neural Networks (DNNs) for precise image-based behaviour classification. Our proposed DNN-based framework unites several preprocessing and feature extraction methods to accomplish this goal. The system begins with Hue, Saturation, and Value (HSV) colour processing to enhance image visibility, followed by Gaussian filtering for noise reduction. The statistical method performs silhouette extraction, and the feature extraction process utilises Local Intensity Order Pattern (LIOP) and Features from accelerated segment test (FAST) algorithms together. Feature discrimination is enhanced through the application of fuzzy optimisation techniques. The optimised features are processed by a DNN, which classifies human activities. The proposed framework demonstrates high effectiveness through its recognition performance, which achieved 94% accuracy on BIT interaction data and 88.25% accuracy on SBU interaction data. This work presents an advanced human activity recognition system that shows promise for real-world applications, such as surveillance systems, video analytics, and interactive technologies, enabling more precise analysis of human behaviour.

This study aimed to develop practical, cost-effective screening guidelines using Robert's Test and J48 decision tree algorithm to optimize microalbuminuria detection in health screening programs. Data were collected from random spot urine samples during daytime from 709 participants who received routine health checks at the Center of Medical Laboratory Service, Medical Technology Program, Nakhonratchasima College. The samples were screened with protein and microalbumin dipsticks, confirmed by Robert's test, and analyzed for the microalbumin-to-creatinine ratio (MA/CR). Kruskal-Wallis and Pearson correlation tests assessed statistical significance at p < 0.05 and 95% confidence intervals. Several significant correlations were found, including the relationship between increasing age and higher blood pressure, fasting plasma glucose, creatinine, and urea nitrogen levels. The reduced estimated glomerular filtration rate (eGFR) was significantly correlated with microalbuminuria (p < 0.01) among participants younger than 83 years. The J48 analysis showed that Robert's test and fasting plasma glucose (FPG) were effective for screening. Participants with a negative Robert's test and FPG < 96 mg/dL had 97.7% normal microalbumin levels. However, participants with trace protein and FPG > 84 mg/dL had a 35% chance of microalbuminuria. This algorithm can develop practical guidelines for detecting microalbuminuria, potentially reducing costs and laboratory burden and identifying high-risk groups in population health.

Nonstabilizerness, or ‘magic’, is a crucial resource for quantum computation, but quantifying the magic of mixed states has been a notoriously difficult task. We introduce efficient magic witnesses based on stabilizer Rényi entropy that both robustly indicate magic and quantitatively estimate magic monotones. Building on these witnesses, we design testing algorithms that distinguish high- and low-magic states under entropy constraints and apply them to certify the number of noisy T-gates for a broad class of noise models. Using the IonQ quantum computer, we experimentally verify magic in noisy random circuits and find that magic remains robust, persisting even under depolarizing noise with probability exponentially close to one. Our witnesses are efficiently computable for matrix product states, showing that subsystems of many-body states can host extensive magic even when the system is entangled. Finally, we show that mimicking high-magic states with minimal magic requires an extensive amount of entropy, implying that entropy is a necessary cryptographic resource for hiding magic from eavesdroppers. Our results provide practical tools for characterizing the complexity of noisy quantum systems.

BackgroundGroup A Streptococcus (GAS) is highly contagious and can cause invasive infections including bacteremia, sepsis, and necrotizing fasciitis. Thus, it is important to limit transmission and treat infections promptly and appropriately. In 2019, the Centers for Disease Control and Prevention (CDC) listed resistant GAS as a concerning threat due to increasing rates of clindamycin (CLI) and erythromycin (ERY) resistance. The Wadsworth Center (WC) is one of 10 laboratories in the country funded to perform GAS surveillance through the Emerging Infections Program (EIP) and receives isolates of GAS from hospitals, laboratories, and local health departments. WC also receives isolates from healthcare-associated investigations. In the past 6 years, over 2,200 GAS isolates have been received, including isolates from over 100 outbreaks.MethodsThese isolates are analyzed using multiple methods for identification and characterization, including antimicrobial resistance (AR) and whole genome sequencing (WGS). Antimicrobial susceptibility testing (AST) is performed using the bioMérieux E-test gradient strip to assess increased resistance to CLI and ERY.ResultsTo date, WC has tested over 1,400 GAS isolates and identified CLI resistance in 130 isolates and ERY resistance in 230 isolates. Inducible clindamycin resistance (ICR) in GAS can develop when the pathogen is exposed to other antibiotics, such as ERY, and can result in treatment failure. To address this concern, the ICR test is currently under validation and will be used alongside the E-test when applicable. In addition to culture AST, isolates are sent for WGS and analyzed using an AR bioinformatic gene detection pipeline to screen for genes potentially leading to AR in strains circulating in New York State (NYS). To date, this method has identified over 400 samples containing one or more AR genes. Data analysis is underway to assess the relationship between the presence of AR genes and the correlation with phenotypic AST results.ConclusionThe surveillance testing performed at WC represents an extensive testing algorithm that can be used for the identification of trends in antimicrobial resistance in GAS. Data analysis may lead to the development of new assays to improve testing algorithms at WC and other public health laboratories.DisclosuresAll Authors: No reported disclosures

BackgroundIDSA recommends that, prior to testing for Clostridiodes difficile in patients with new-onset diarrhea, clinicians should consider other potential causes, such as recent laxative use. Clinical decision support systems (CDSS) can nudge providers to reduce inappropriate CDI testing and 2-step testing algorithms can optimize diagnostic accuracy. We assessed the long-term clinical utility of clinical nudges for CDI diagnostic stewardship.MethodsA retrospective analysis of inpatient CDI tests (n=44,677) ordered for 10 years after the introduction of 2-step diagnostic testing (toxin→DNA-NAAT) in the 2nd quarter of 2015 (Q2 2015) to evaluate the long-term impact of a CDSS nudge for providers to reconsider testing in patients receiving laxatives in the 48 hours prior. Univariate and multivariate analyses were performed via Pearson’s chi-squared test.ResultsAn informational popup (Q3 2016) produced a marked decrease in CDI testing (Fig. 1). It was transitioned to an interactive popup prompting either cancelation or acknowledgment that a “positive result will be of no value” (Q2 2017). The test positivity rate was significantly lower (7.0% vs. 8.5%, P < .001) for inpatients who triggered the popup (n=9231) versus those who did not during the same period.No significant change in overall propensity to override the CDSS popup was observed over the study period (µ=57%). Popups were most frequently overridden in ICUs (62.0%), compared with Floor and Post-Acute Units, at 56.1 and 58.0%, respectively (p< .0001). There was a significant difference in rate of override between ordering provider types (APP vs. Attending vs. Resident) with rates of 59.4%, 57.2% and 55.5%, respectively (p< .01). In looking at individual providers, 2.5% of providers (n=50) were responsible for 20% of popup triggers, with a negative correlation between frequency of override and ordered test positivity (Fig. 2).ConclusionWhile it has been shown that CDSS nudges can decrease diagnostic ordering, here we show that implementation of a CDSS yielded a statistically significant decrease in test positivity for a patient population at low-risk for CDI. Subgroup analyses looking at provider, unit, and level of care provide opportunities for targeted educational intervention to further improve diagnostic stewardship.DisclosuresAll Authors: No reported disclosures

This article describes the design, control, and implementation of a photovoltaic (PV) emulator using two-switch forward-converter topology. The system is designed to emulate the nonlinear electrical behavior of an actual PV panel under different environmental conditions including radiation level and temperature. The emulator provides galvanic isolation and also accurate current modulation to provide a safe yet reliable means of testing PV-related devices and algorithms within a laboratory setting. A dual-loop PI control is proposed to adjust the output current according to voltage feedback (VF), thus making accurate I–V and P–V curves achievable. Besides software simulation, a tailored printed circuit board (PCB) was fabricated. The simulation result demonstrated that the system can achieve a fast response and stable operation, with a maximum error percentage of about 2.1%, indicating high emulation fidelity, thereby providing an attractive platform for various evaluation purposes such as MPPT algorithms, inverters, and EMS.

This study investigates the causal effects of promotional push notifications on short-term ROI, long-term retention, and user heterogeneity. Results show that while promotions drive short-term revenue growth (H1), these effects are mediated by repeat purchases (H2) and fail to sustain longterm loyalty (H3). Theoretically, this work bridges the gap between short-term promotional gains and lasting customer outcomes, while practically emphasizing precision targeting to maximize ROI and preserve loyalty. Despite limitations in proxy user identification, dataset generalizability, and potential confounding, the study highlights future directions such as real user data, randomized testing, multichannel strategies, and adaptive algorithms to balance immediate profit with enduring engagement.

Globally 36.7 million people have HIV, and in Kenya it is estimated that 1.5 million are infected. The HCV burden is estimated to be 32 million in sub Saharan Africa with Kenya having a prevalence of less &lt;1%. In Kenya Injection Drug Users [IDU’s] are estimated to be 50,000. There is increased public concern on the rising cases of injection substance users, which has also led to increased HIV prevalence in Mombasa County, which stands at 8.6%. This is above Kenya’s prevalence rate, which is at 6.3%. Lymphopaenias among the HIV and HCV co-infected IDU’s has also not been explored and therefore this study was aimed to address this gap. Through this study significant fibrosis and lymphopaenias among HIV- and HCV-co-infected injection substance users were determined. While HIV promotes acceleration of HCV infections towards fibrotic liver disease, HCV increases immunosuppression in HIV infections, leading to early acquired immunodeficiency syndrome (AIDS) and death in untreated cases. Liver disease related to hepatitis C virus (HCV) and human immunodeficiency virus (HIV) infection may affect the immune status of the injection substance users. Limited data exists on significant fibrosis and lymphopaenia among human immunodeficiency virus and hepatitis C virus co-infected injection drug users. This was a cross-sectional study involving consenting adult (≥18 years) IDUs at Bomu Hospital, Mombasa, Kenya. The study groups were HCV-/HIV- IDUs (n=114); HCV-/HIV+ IDUs (n=73); HCV+/HIV- IDUs (n=19); and HCV+/HIV+ co-infected (n=17). A total of 223 participants were recruited. Socio-demographic and clinical characteristics data were collected using a pre-tested structured participant questionnaire. Consenting participants were serologically screened for the hepatitis C virus and also screened for the human immunodeficiency virus using the national algorithm of testing. Immunological status was tested by the BD FACS Calibur flow cytometer. Immunologic staging was based on the CD4 count, where lymphopaenia was a count of &lt;500 cells/µl. Platelets alongside aspartate aminotransferase (AST) and alanine aminotransferase (ALT) were also determined. The aspartate aminotransferase to platelet ratio index (APRI), fibrosis 4 index (FIB 4) and non-alcoholic fatty liver score (NAFLD) were used to determine significant fibrosis. APRI approached significant difference (P=0.054) across the groups. Age showed significance P 0.001 and gender P&lt;0.0001. The AST levels across the groups are P=0.001. In immunological staging, lymphopaenia was more profound in HIV mono-infected injection drug users (65.8%), HCV/HIV co-infected injection substance users (41.2%), HCV/HIV uninfected (21.1%) and lastly HCV mono-infected injection substance users (15.8%). From the results it can be concluded that HCV/HIV co-infection among IDU’s, is associated with high burden of significant fibrosis and lymphopaenia. Significant fibrosis was more pronounced across groups with HCV mono-infected IDUs leading, while lymphopaenia was most severe in HIV mono-infected IDUs (65.8%). The HCV/HIV co-infected burden of both significant fibrosis and lymphopaenia (41.2%) is progressively high. These findings highlight the profound impact of HIV and HCV on liver disease progression and immune suppression. This emphasises the urgent need for early screening, monitoring and integrated management of co-infected individuals to reduce morbidity and mortality in this vulnerable population.

The diagnosis of Lyme borreliosis (LB) relies primarily on clinical evaluation supported by appropriate serologic testing in selected cases. Serology is recommended only in suspected disseminated LB, characterized by compatible clinical signs and history of tick exposure. In early localized disease such as erythema migrans, laboratory testing is unnecessary due to low sensitivity and the reliability of clinical diagnosis. A two-tiered testing algorithm remains the standard: enzyme-linked immunosorbent assay (ELISA) followed by immunoblot confirmation when ELISA results are positive or equivocal. For patients with symptoms lasting less than six weeks and negative initial results, serology should be repeated after three weeks. Only IgG are considered to confirm LB diagnosis. Intrathecal antibody synthesis is critical for diagnosing Lyme neuroborreliosis (LNB), achieving>99% sensitivity after 6-8weeks, although isolated antibody index elevation without pleocytosis suggests alternative etiologies. Interpretation of serology must always consider clinical context: IgG may remain for years after recovery, and isolated IgM beyond six weeks typically represents a false positive. Serologic limitations include low sensitivity in early disease and cross-reactivity, particularly for IgM. PCR may aid diagnosis from synovial fluid or skin lesions but is rarely informative for cerebrospinal fluid. Emerging biomarkers such as CXCL13 and advanced molecular approaches remain experimental and require further validation.

We give a pair of algorithms that efficiently learn a quantum state prepared by Clifford gates and O ( log &amp;#x2061; n ) non-Clifford gates. Specifically, for an n -qubit state | &amp;#x03C8; &amp;#x27E9; prepared with at most t non-Clifford gates, our algorithms use p o l y ( n , 2 t , 1 / &amp;#x03B5; ) time and copies of | &amp;#x03C8; &amp;#x27E9; to learn | &amp;#x03C8; &amp;#x27E9; to trace distance at most &amp;#x03B5; .The first algorithm for this task is more efficient, but requires entangled measurements across two copies of | &amp;#x03C8; &amp;#x27E9; . The second algorithm uses only single-copy measurements at the cost of polynomial factors in runtime and sample complexity. Our algorithms more generally learn any state with sufficiently large stabilizer dimension, where a quantum state has stabilizer dimension k if it is stabilized by an abelian group of 2 k Pauli operators. We also develop an efficient property testing algorithm for stabilizer dimension, which may be of independent interest.

Syphilis incidence has been rising worldwide over the last few decades, raising concern for a resurgence of tertiary complications. Syphilitic cardiovascular disease is a rare but serious manifestation of tertiary syphilis, formerly a major cause of aortitis and thoracic aortic aneurysms before the antibiotic era. This review provides an updated overview of syphilitic cardiac and vascular disease for the cardiology specialist. We will discuss the historical and epidemiological context of cardiovascular syphilis, including longitudinal preantibiotic era studies and contemporary case series. We outline the pathophysiology of syphilitic aortitis, highlighting mechanisms whereby Treponema pallidum infection causes obliterative endarteritis of the vasa vasorum, ischemic injury to the aortic wall, and resulting aneurysm formation with aortic valve and coronary ostia involvement. The clinical manifestations are presented, with emphasis on the triad of classic tertiary cardiovascular syphilis, which includes syphilitic thoracic aortic aneurysm, aortic regurgitation, and coronary ostial stenosis. The diagnostic strategies are covered, including modern imaging findings (CT, MRI, echocardiography), serologic test algorithms for syphilis, and histopathologic features. Differential diagnosis is covered in depth, contrasting syphilitic aortitis with other causes of aortitis such as Takayasu arteritis, giant cell arteritis, and other infectious or idiopathic aortitides. Management principles are laid out, with antibiotic therapy and surgery as indicated for late disease. We also cover reported case outcomes and registry reports-including modern surgical series and a recent population-based study implicating syphilis in increased cardiovascular risk-and highlight prognosis with modern therapies. Syphilitic cardiac and vascular disease remains a relevant clinical entity-the "great imitator" of cardiovascular medicine-despite decreased incidence in the antibiotic. Early recognition of this treatable cause of aortitis is critical. Outcomes may be favorable with appropriate antibiotic treatment and early surgical repair of complications, but delayed diagnosis is perilous. Ongoing vigilance, research into optimal management, and public health measures to restrict syphilis are required to further reduce the impact of this disease.

We present a coverage-guided testing algorithm for distributed systems implementations. Our main innovation is the use of an abstract formal model of the system that is used to define coverage. Such abstract models are frequently developed in the early phases of protocol design and verification but are infrequently used at testing time. We show that guiding random test generation using model coverage can be effective in covering interesting points in the implementation state space. We have implemented a fuzzer for distributed system implementations and abstract models written in TLA+. Our algorithm achieves better coverage over purely random exploration as well as random exploration guided by different notions of scheduler coverage and mutation. In particular, we show consistently higher coverage on implementations of distributed consensus protocols such as Two-Phase Commit and the Raft implementations in Etcd-raft and RedisRaft and detect bugs faster. Moreover, we discovered 12 previously unknown bugs in their implementations, four of which could only be detected by model-guided fuzzing.

Greening the lab: Creation of a national playbook on environmental sustainability in lab medicine.

Wearable physiological sensors (WPS) can provide real-time, continuous data to make immediate safety decisions based on how workers respond under a given heat exposure. Estimated core temperature (TEST) calculated from WPS can provide meaningful data on heat illness, strain, and risk, but they must be validated against gold standard measures and during intermittent physical activity in the heat. Two TEST algorithm models (2013 and 2020) are commonly used to assess heat strain in warfighters using heart rate in WPS; however, these models may have limitations when applied to non-military populations. PURPOSE: To examine the validity of TEST (2013 and 2020) compared to a validated measure [rectal temperature (TREC)] during physical activity in the heat in physically active men. METHODS: Twelve healthy men [age, 32 ± 7 years; peak oxygen consumption (VO2peak), 48.19 ± 7.09 ml·kg−1·min−1] completed four experimental trials (~4.5 hours) consisting of cycles of intermittent exercise. WPS were placed at three different locations [chest strap (CS), armband (AB), and wristwatch (WW)] and each incorporated TEST 2013 and 2020. Bland-Altman plots and linear regression were utilized to measure mean difference (MD), 95% limits of agreement (LoA), and coefficient of determination (R2), respectively. TREC was used as the reference measurement. An acceptable MD was determined as ≤0.27 °C. Data were also stratified by TREC value (<38.0 °C, 38.0-38.5 °C, 38.5-39.0 °C, 39.0-39.5 °C, >39.5 °C). RESULTS: The lowest and only acceptable MD was noted in CS, AB, and WW devices that utilized TEST 2020 (0.21 °C, 0.19 °C, 0.27 °C, respectively). For all WPS, 95% of the data fell between MD of -0.54 and 1.22 °C (95% LoA). R2 for all WPS ranged from 0.32-0.39. Poor agreement (>0.27 °C) occurred above 38.5 °C across all WPS TEST 2020 (CS:0.53-0.73 °C, AB: 0.52- 0.74 °C, WW:0.67-0.97 °C). CONCLUSION: Overall, WPS utilizing TEST 2020 demonstrated acceptable MD, but exhibited moderate variability, reflected by R2 values. As TREC increased above 38.5 °C, the MD for all WPS TEST 2020 was greater than the acceptable MD, thus indicating that WPS utilized in this study may not be acceptable for hyperthermic individuals performing intermittent work in the heat. Supported by: This study was funded by Vigilife.

Rapid diagnosis of resistance-conferring mutations to antibiotics used for the treatment of tuberculosis (TB) is critical for patient care and public health control efforts. Prior guidelines included the use of fluoroquinolones (FQs) for the treatment of drug-resistant TB, including multidrug-resistant TB, pre-extensively drug-resistant TB, and extensively drug-resistant TB. More recently, a short-course regimen for antibiotic-susceptible TB was introduced, which includes the use of a FQ, a drug class that diagnostic algorithms in the United States (US) typically do not test for if all first-line agents are susceptible. However, FQ mono-resistance has been documented by previous studies, and for this reason, we tested 319 archived Mycobacterium tuberculosis complex (MTBC) strains spanning a 14-year period of time using the Xpert MTB/XDR assay. Resistance to FQs was detected in 4.4% (14/319) of the isolates tested, with mutations predominating in the gyrA region (13/14; 92.9%). A single isolate (1/14; 7.1%) was found to have a gyrB mutation. A broth microdilution assay demonstrated the minimum inhibitory concentrations for resistant strains that ranged from 0.5 µg/mL to 8.0 µg/mL. Importantly, three strains were FQ mono-resistant and would have been completely missed by standard testing algorithms. Although currently unavailable in the US, the GeneXpert XDR assay has the potential to fill the significant diagnostic gap in susceptibility testing of MTBC resistance to FQs and support the use of the currently recommended short-course regimen.IMPORTANCE This study provides insight into the need for additional rapid testing for the detection of drug resistance (specifically to fluoroquinolones) in tuberculosis (TB) cases in the United States (US). The current regimens for TB treatment rely on knowing resistance patterns to optimize treatment, and missed resistance could have a negative impact on the health of the patient, as well as contribute to increased drug-resistance mutations in new TB cases. There are currently limited platforms for expanded rapid drug resistance testing for TB cases in the US, and this study looks at past TB cases that had drug resistance missed by routine testing.

Instance Space Analysis is a methodology to evaluate algorithm performance across diverse problem fields. Through visualisation and exploratory data analysis techniques, Instance Space Analysis offers objective, data-driven insights into the diversity of test instances, algorithm behaviour, and algorithm strengths and weaknesses. As such, it supports automated algorithm selection and synthetic test instance generation, increasing testing reliability in optimisation, machine learning, and scheduling fields. This paper introduces instancespace , a Python package that implements an automated pipeline for Instance Space Analysis. This package supports research by streamlining the testing process, providing unbiased metrics, and facilitating more informed algorithmic design and deployment decisions, particularly for complex and safety-critical systems.