Dependent Type Research Articles

Selection processes, transportability, and failure time analysis in life history studies.

In life history analysis of data from cohort studies, it is important to address the process by which participants are identified and selected. Many health studies select or enrol individuals based on whether they have experienced certain health related events, for example, disease diagnosis or some complication from disease. Standard methods of analysis rely on assumptions concerning the independence of selection and a person's prospective life history process, given their prior history. Violations of such assumptions are common, however, and can bias estimation of process features. This has implications for the internal and external validity of cohort studies, and for the transportabilty of results to a population. In this paper, we study failure time analysis by proposing a joint model for the cohort selection process and the failure process of interest. This allows us to address both independence assumptions and the transportability of study results. It is shown that transportability cannot be guaranteed in the absence of auxiliary information on the population. Conditions that produce dependent selection and types of auxiliary data are discussed and illustrated in numerical studies. The proposed framework is applied to a study of the risk of psoriatic arthritis in persons with psoriasis.

Extracting efficient exact real number computation from proofs in constructive type theory

Abstract Exact real computation is an alternative to floating-point arithmetic where operations on real numbers are performed exactly, without the introduction of rounding errors. When proving the correctness of an implementation, one can focus solely on the mathematical properties of the problem without thinking about the subtleties of representing real numbers. We propose a new axiomatization of the real numbers in a dependent type theory with the goal of extracting certified exact real computation programs from constructive proofs. Our formalization differs from similar approaches, in that we formalize the reals in a conceptually similar way as some mature implementations of exact real computation. Primitive operations on reals can be extracted directly to the corresponding operations in such an implementation, producing more efficient programs. We particularly focus on the formalization of partial and nondeterministic computation, which is essential in exact real computation. We prove the soundness of our formalization with regards to the standard realizability interpretation from computable analysis and show how to relate our theory to a classical formalization of the reals. We demonstrate the feasibility of our theory by implementing it in the Coq proof assistant and present several natural examples. From the examples we have automatically extracted Haskell programs that use the exact real computation framework AERN for efficiently performing exact operations on real numbers. In experiments, the extracted programs behave similarly to native implementations in AERN in terms of running time and memory usage.

An integrated method of extended STPA and BN for safety assessment of man-machine phased-mission system

Man-Machine Phased-Mission System (MMPMS) usually demands the cooperation of operators with different responsibilities and machines to accomplish multi-phase missions. Its machine configuration and human organization structure may change across phases, and phase dependencies of machine failures and human errors may exist. In current studies, the safety of man-machine system is usually analyzed qualitatively by System Theoretic Process Analysis (STPA) and assessed quantitatively by the integration of STPA with Bayesian Networks (BN). These studies only focus on single-phase systems and conduct single-phase BN while cannot address the features of MMPMS. In this paper, a qualitative analysis and quantitative assessment method for phase dependencies is proposed and integrated into the method that combines STPA and BN. Firstly, four types of phase dependencies in MMPMS are identified. Secondly, new mapping rules for phase dependencies are proposed to integrate single-phase BN into a multi-phase BN. Thirdly, the quantitative assessment method for phase dependencies considering the effects of human organization structure changes are proposed to quantify the parameters of multi-phase BN. Fourthly, the safety of MMPMS can be assessed through multi-phase BN. Finally, an Unmanned Aerial Vehicle system with three-phase missions is presented as a case study to demonstrate the effectiveness of the proposed method.

Correlation Between Level of Physical Activity Using GPAQ and Exercise Capacity Using 6 Min Walk Test in Non-Insulin Dependent Type 2 Diabetes Mellitus

Background: This study was designed to find the Correlation Between the Level of Physical Activity and Exercise Capacity in Non-Insulin Dependent Type 2 Diabetes Mellitus. Purpose: To find the Correlation between the Level of Physical Activity and Exercise Capacity in Non-Insulin Dependent Type 2 Diabetes Mellitus. Materials and Methods: Materials required for this study were Countdown timer (or stopwatch), Two small cones, Chair, Worksheet on a clipboard, Sphygmomanometer. It was a correlational study design. The sampling method used was Convenient type of sampling. Sixty subjects with non-insulin dependent type 2 were included in this study. The written informed consent was taken. Informed consent document was signed, retained by the principal investigator and a copy was given to the participant. Global Physical Activity Questionnaire and 6 Minutes walk test was used to study the Physical Activity and Exercise Capacity respectively. All the data obtained was statistically analysed using proper tests. Results: The results showed positive significant (p value < 0.0001) correlation between the level of physical activity and exercise capacity, Physical activity level correlates statistically with distance walked in percentage. Conclusion: Our study concluded that Physical activity level correlate statistically with distance walked in type 2 diabetic patients.

A Dependent Nominal Physical Type System for Static Analysis of Memory in Low Level Code

We tackle the problem of checking non-proof-carrying code , i.e. automatically proving type-safety (implying in our type system spatial memory safety) of low-level C code or of machine code resulting from its compilation without modification. This requires a precise static analysis that we obtain by having a type system which (i) is expressive enough to encode common low-level idioms, like pointer arithmetic, discriminating variants by bit-stealing on aligned pointers, storing the size and the base address of a buffer in distinct parts of the memory, or records with flexible array members, among others; and (ii) can be embedded in an abstract interpreter. We propose a new type system that meets these criteria. The distinguishing feature of this type system is a nominal organization of contiguous memory regions, which (i) allows nesting, concatenation, union, and sharing parameters between regions; (ii) induces a lattice over sets of addresses from the type definitions; and (iii) permits updates to memory cells that change their type without requiring one to control aliasing. We provide a semantic model for our type system, which enables us to derive sound type checking rules by abstract interpretation, then to integrate these rules as an abstract domain in a standard flow-sensitive static analysis. Our experiments on various challenging benchmarks show that semantic type-checking using this expressive type system generally succeeds in proving type safety and spatial memory safety of C and machine code programs without modification, using only user-provided function prototypes.

StarMalloc: Verifying a Modern, Hardened Memory Allocator

We present StarMalloc, a verified, efficient, security-oriented, and concurrent memory allocator. Using the Steel separation logic framework, we show how to specify and verify a multitude of low-level patterns and delicate security mechanisms, by relying on a combination of dependent types, SMT, and modular abstractions to enable efficient verification. We produce a verified artifact, in C, that implements the entire API surface of an allocator, and as such works as a drop-in replacement for real-world projects, notably the Firefox browser. As part of StarMalloc, we develop several generic datastructures and proof libraries directly reusable in future systems verification projects. We also extend the Steel toolchain to express several low-level idioms that were previously missing. Finally, we show that StarMalloc exhibits competitive performance by evaluating it against 10 state-of-the-art memory allocators, and against a variety of real-world projects, such as Redis, the Lean compiler, and the Z3 SMT solver.

12333 46 XX/XY Chimerism - Positive NIPT And Post-natal Karyotype Is It Real?

Abstract Disclosure: K.L. Del Rosario: None. N. Sheriden: None. N. Vijayakanthi: None. Introduction: Non-Invasive Prenatal Testing(NIPT) using cell free fetal DNA in plasma of pregnant women has become a routine part of prenatal care in screening for fetal aneuploidies including sex chromosome abnormalities in most regions around the world. False positive results are increasingly imposing challenges in pre-natal as well as post-natal care. Case Discussion: We report a neonate born at 32+2 weeks gestation to a 42-year-old G2 P2 mother. Pregnancy was complicated by insulin dependent maternal type 2 diabetes mellitus, maternal chronic hypertension and a positive NIPT for high-risk monosomy X. Prenatal ultrasound showed male anatomy. Interestingly on physical exam after birth, the neonate had typical male external genitalia with bilateral normal male gonads. Chromosome analysis done immediately after birth revealed the presence of two cell lines: 40 of the 50 cells (80%) had a normal female 46 XX karyotype and 10 of the 50 cells (20%) had a normal male 46 XY karyotype. These findings could be due to reabsorbed twin, Klinefelter syndrome with two trisomy rescue events, maternal cell contamination or true chimerism. In addition, fluorescence in situ hybridization (FISH) analysis for X and Y probes revealed the presence of two cell lines. The first cell line (70% of the cells) had two hybridization signals for chromosome X and the second cell line (∼25% of the cells) had one hybridization signal for chromosome X and one for chromosome Y. Postnatal ultrasound showed normal testicles with no evidence of Mullerian structures. Newborn screening was negative for congenital adrenal hyperplasia (CAH). Genetics was consulted and recommended repeat chromosomal analysis, parental testing to determine sex chromosome segregation, and follow-up with pediatric endocrinology. Repeat cytogenetic testing at 2 weeks of life resulted in a normal male chromosome complement of 46,XY. Previous abnormal cytogenetics were thought to be due to maternal cell contamination. Further endocrine labs showed LH(1.16 uIU/ml) and testosterone levels ( 87 ng/dL), appropriate levels for age indicating normal Hypothalamic Pituitary Gonadal (HPG) axis and testicular Leydig cell function. Since the family was previously counseled regarding the concept of maternal cell contamination, they expressed understanding and were happy with the update of the normal karyotype result. Conclusion: False-positive results concerning for rare chimerism on NIPT can occur and should prompt a thorough history, physical exam, ultrasound studies and repeat testing to confirm its presence. Careful consideration should be taken when counseling family about the implications of these results, especially communication about gender assignment of the infant. Presentation: 6/3/2024

8494 A Case of Diabetic Ketoacidosis in Setting of COVID-19 Infection and SGLT-2 Inhibitor Use

Abstract Disclosure: N. Abrahimi: None. S. Bajpay: None. A. Abrahimi: None. Background: COVID-19 infection can cause endocrine system disruptions leading to the development of diabetic ketoacidosis (DKA) in patients with type 1, 2 or new onset diabetes mellitus. (1) DKA is a side effect of SGLT-2 inhibitor use and its development on the medication can lead to discontinuation of SGLT-2 inhibitor. (2) SGLT-2 inhibitors are part of guideline directed medical therapy for management of heart failure with reduced ejection fraction (HFrEF). (3) Case: 67-year-old female history of non-insulin dependent diabetes mellitus type 2 on Empagliflozin presented with shortness of breath and hypoxia. Initial BMP: Glucose 141 mg/dL, bicarb 24 mmol/L, anion gap of 10 mmol/L. Patient test positive for COVID-19 and was admitted for acute hypoxic respiratory failure in setting of COVID-19 infection. Six hours after patient received first dose of dexamethasone, labs showed BMP: Glucose 582 mg/dL, bicarb 14 mmol/L, anion gap of 20 mmol/L. ABG: pH 7.09, bicarb 13.2 mmol/L, glucose 509 mg/dL, lactate 9.6, beta-hydroxybutyrate 1.15 mmol/L. Patient was diagnosed and treated for DKA. Patient had an echocardiogram which showed new HFrEF. There was initial hesitation to restart patient on home Empagliflozin due to recent development of DKA. Literature review showed cases of DKA associated with COVID-19 infection. Etiology of DKA remained unclear. Ultimately, it was decided to restart patient on home Empagliflozin for management of diabetes and HFrEF. Conclusion: An abundance of evidence support the benefits of SGLT-2 inhibitors for patients with and without type 2 diabetes mellitus. (4) It is important to consider other causes of DKA for patients who develop DKA on SGLT-2 Inhibitors. Furthermore, additional research into endocrinopathies related to COVID-19 infections should be considered.

7378 Glargine Induced Neuroglycopenia in Patients with End-Stage Renal Disease: Importance of Insulin Regimen Optimization in Haemodialysis Patients

Abstract Disclosure: M. Shrivastava: None. L. Kaur: None. B. Armendariz: None. R. Kaur: None. A. Shetty: None. In patients with end stage renal disease (ESRD), hypoglycemia accounts for up to 3.6% of all the admissions with mortality rates of up to 30%. A combination of impaired insulin clearance, changes in glucose metabolism and dialysis process makes the patients with end stage renal disease vulnerable to neuroglycopenia.Case description:53 year old female with past medical history of insulin dependent type 2 diabetes mellitus, ESRD secondary to diabetes, on hemodialysis(HD) thrice weekly since two years, presented to the emergency with altered mental status, respiratory distress, tachycardia. Lab work revealed blood glucose(BG) of 23 mg/dl, HbA1c of 8.4%, eGFR of 6, and arterial blood gas showed hypercapnic respiratory acidosis. Patient received dextrose, with no improvement of symptoms. Eventually she developed acute hypercapnic respiratory failure requiring endotracheal intubation with mechanical ventilation, and was transferred to the ICU. As per family, a night prior to presentation, last recorded BG after dinner was 253 mg/dl, she took her night time glargine, which was recently increased by her primary care for poorly controlled HbA1c levels. Brain MRI and long term EEG monitoring findings were consistent with underlying extensive brain injury secondary to prolonged hypoglycemia. Unfortunately, the patient's condition did not improve despite HD and BG correction, eventually she underwent compassionate extubation. Case Discussion:The insulin requirements in ESRD patients are reduced by approximately 50%, regardless of residual insulin secretion. Malnutrition and acidosis reduce hepatic glycogen stores and availability of gluconeogenic precursor, expected compensatory renal gluconeogenesis is compromised by decreased renal function causing hypoglycemia, which is further worsened by inappropriately high plasma insulin levels caused by reduced renal insulin breakdown. Diabetes mellitus patients with ESRD are frequently managed with basal-bolus insulin regimen, and HD up to thrice weekly, leaving them without HD for up to 3 days especially over the weekend. This can result in accumulation of insulin metabolites causing delayed insulin clearance as seen in our patient. In such cases even long acting insulin, such as glargine, can have compounding effects, which could possibly cause fatal complications such as neuroglycopenia. In such patients continuous glucose monitor use with tapering dose glargine regimen may help eliminate this compounding effect. Conclusion: Neuroglycopenia is a rare manifestation of diabetes mellitus with ESRD. Compromised renal gluconeogenesis and impaired insulin clearance can cause inappropriately high plasma levels of insulin. In such patients continuous glucose monitoring along with tapering dose of long acting insulin should be utilized for proper glycemic control to limit compounded effect of insulin metabolite accumulation. Presentation: 6/3/2024

7491 Post operative Euglycemic Diabetic Ketoacidosis in Type 2 Diabetic patient - A diagnostic challenge

Abstract Disclosure: S. Azmat: None. O. Lodhi: None. H. Ashok: None. M.F. Siddiqui: None. Euglycemic Diabetic Ketoacidosis (EDKA) is a rare but potentially fatal condition that is often difficult to diagnose as underlying ketoacidosis is masked by euglycemia. The diagnosis and management of this condition requires a swift and comprehensive approach to avoid delay. We report a case of 66-year-old female with Insulin-dependent Type 2 DM who developed postoperative euglycemic diabetic ketoacidosis, highlighting the significance of maintaining a high degree of suspicion for EDKA in postoperative patients, whose surgical course may obscure the underlying diabetic ketoacidosis symptoms. Clinical Case: A 66-year-old female with past medical history of Insulin dependent Type 2 DM presented to the emergency department with severe epigastric pain. CT Abdomen revealed perforated gastric ulcer with pneumoperitoneum requiring urgent laparoscopic graham patch repair. Patient’s outpatient medications include Lantus and metformin. She had mild hyperglycemia on admission with blood glucose of 176 mg/dL (140-160mg/dL) without metabolic abnormality. Insulin administration was omitted due to pre and post operative normoglycemia. The patient was NPO followed by initiation of nasogastric tube feeds. Postoperative course was complicated by hypotension, generalized abdominal discomfort and anion gap metabolic acidosis. Graham patch failure, abdominal infection, and post-surgical complications were systematically ruled out. Patient continued to decline with worsening anion gap metabolic acidosis; pH of 7.18 (7.35-7.45), HCO3 < 10 mEq/L (21 mEq/L - 31 mEq/L), anion gap15 mmol/L (8 to 12 mmol/L), blood sugar (147-208 mg/dl). There was no lactic acidosis or renal impairment. Beta hydroxybutyrate levels were elevated at > 4.5 mmol/L. Thus diagnosis of euglycemic DKA was established and treated with insulin drip per DKA protocol and dextrose fluids. EDKA resolved within five days with clinical improvement. She was transitioned to subcutaneous basal bolus insulin. She remained euglycemic and and had good surgical outcomes.Discussion: Euglycemic DKA is rare with only 2.6% to 3.2% of DKA, presenting as euglycemic. It presents as unique diagnostic challenge due to atypical DKA presentation with blood glucose less than 250 mg/dL. The primary driver for EDKA is either a reduction in hepatic glucose production at times of fasting or the overabundance of counter-regulatory hormones resulting in excess glucosuria. Literature has reported the effects short-term fasting on developing EDKA and starvation induced ketosis secondary to extreme ketogenic diets or bariatric surgery primarily among Type 1 diabetics. Clinically patients may exhibit symptoms similar to classic DKA, however, this classic picture may be confounded in a critically ill post-surgical patient, thus delaying recognition. This emphasizes the importance of including EDKA in differentials while evaluating such patients. Presentation: 6/1/2024

Risk Factors for Gastric Cancer at RSUP Prof. Dr. I.G.N.G. Ngoerah Year 2018-2023

Gastric cancer is the fifth most common cancer and the fourth most common cause of death due to cancer in the world. The development of gastric cancer tends to be quite slow and takes years, so it is often found in the late stages. The cause of stomach cancer is not known for certain, but it is believed to be caused by many factors. This study aims to determine the risk factors for gastric cancer at RSUP Prof. Dr. I.G.N.G. Ngoerah was diagnosed in 2018-2023. This research was conducted using a retrospective descriptive method using secondary data in the form of medical records on 46 samples of gastric cancer patients who were controls or treated at RSUP Prof. Dr. I.G.N.G. Ngoerah was diagnosed in 2018-2023 The variables studied include the dependent variables, namely age, gender, peptic ulcers, blood type, obesity, alcohol consumption and smoking. The results of the analysis showed that gastric cancer patients at RSUP Prof. Dr. I.G.N.G. The majority are over 50 years old (82.6%), male (58.7%), have no peptic ulcers (89.1%), have blood type A (37%), underweight (50%), are not consume alcohol (97.8%), and do not smoke (97.8%).It can be concluded that the risk factors for gastric cancer patients at RSUP Prof. Dr. I.G.N.G. Ngoerah majority are over 50 years old, male, have no peptic ulcers, have blood type A, are underweight, do not consume alcohol and do not smoke. Keywords: Gastric Cancer, Risk Factors, RSUP Prof. Dr. I.G.N.G. Ngoerah

Interferon Regulatory Factor 4 (IRF4)-Dependent Type 2 Conventional Dendritic Cells (cDC2s) Promote Kidney Inflammation and Injury in Ischemia-Reperfusion Injury (IRI)-Induced AKI/AKD

Interferon Regulatory Factor 4 (IRF4)-Dependent Type 2 Conventional Dendritic Cells (cDC2s) Promote Kidney Inflammation and Injury in Ischemia-Reperfusion Injury (IRI)-Induced AKI/AKD

IDSV-GCN: Integrating Dual Syntactic Views Graph Convolutional Network for aspect-based sentiment analysis

Aspect-based sentiment analysis (ABSA) aims to predict the sentiment polarity towards given aspects in a sentence. Recent research has highlighted that graph neural networks based on syntactic dependency trees effectively convey rich syntactic information and are suitable for ABSA tasks. Most existing work typically adopt either dependency type or minimum distance between nodes in the original syntactic tree to construct different views. However, existing work overlooks the high-dimensional local feature information in dependency relations, resulting in inadequate exploration of this view. Meanwhile, most work ignores that the minimum distance view and the dependency view can be complementary and integrated in syntactic analysis. Unfortunately, directly adding the two views introduces noise issues, leading to unsatisfactory results after their integration. To address these issues, this paper introduces an integrating dual syntactic views graph convolutional network (IDSV-GCN) model that seamlessly integrates dependency type view and minimum distance view, enabling comprehensive utilization of syntactic structure and information. To better address the computation of weights in the dependency type view, we innovatively propose a fusion attention mechanism. This approach effectively captures both global and local feature information. To more effectively integrate the two views and reduce the impact of noise, we employ a syntactic mask layer to filter out noise in the dependency type view and highlighting important dependency feature information. Then, we construct a minimum distance weight matrix based on the matrix obtained from the dependency type view. Finally, we merge the two matrices and feed them into the GCN to facilitate the model’s learning of syntactic information. Experimental results on three widely-used benchmark datasets demonstrate that our proposed IDSV-GCN model outperforms state-of-the-art methods.

The effectiveness of continuous glucose monitoring with remote telemonitoring-enabled virtual educator visits in adults with non-insulin dependent type 2 diabetes: A randomized trial

AimsEstimate the effectiveness of continuous glucose monitoring (CGM) with remote telemonitoring-enabled virtual diabetes educator visits for improving glycemic management in adults with type 2 diabetes, not on insulin. MethodsParticipants with type 2 diabetes, not on insulin, and HbA1c > 7.0 % were enrolled in an open-label randomized trial of 6 weeks of CGM with telemonitoring versus enhanced usual care. Both groups received educator visits. HbA1c was assessed at 12 weeks. ResultsOf 105 participants (mean age 57.3 years, 49.5 % females, mean baseline HbA1c 8.0 %), 86 remained at follow-up. Change in HbA1c was −0.69 % (CGM) versus −0.33 % (enhanced usual care). Adjusting for baseline HbA1c, CGM was superior (0.65 % greater HbA1c reduction [95 % CI 0.17–1.12 %], p = 0.008). CGM participants were 92 % (RR = 1.92, 1.19–3.06, p = 0.007) more likely to have an HbA1c reduction ≥ 0.5 %, lost more weight (difference in weight reduction 2.17 kg, 0.22–4.11, p = 0.029) and were more satisfied with their treatment. No treatment-related adverse events were observed. ConclusionsCGM with virtual diabetes educator visits is effective, safe, and acceptable in adults with type 2 diabetes not on insulin and should be considered as an alternative to drug therapy for improving blood glucose.

미취업 청년 캥거루족의 부모 경제적 의존 유형화 및 결정요인

The primary objective of this study is to categorize the different forms of economic reliance that unemployed young adults have on their parents and identify the factors contributing to this dependency. The study utilized data from the Youth Panel Survey (YP) conducted by the Korea Employment Information Service and performed a latent class analysis on unemployed young adults receiving financial support from their parents. Based on the reasons for and levels of parental financial support, four distinct types of economic dependency were identified: 'Moderate Living Expense Dependency,' 'High Housing Expense Dependency,' 'Minimal Living Expense Dependency,' and 'Unconditional Dependency.' Each type is differentiated by the specific reasons young adults rely on their parents and the level of financial support they receive. The study further analyzed how sociodemographic characteristics, career maturity, job search preparation, and work values influence these types of economic dependency. The results indicated that the 'High Housing Expense Dependency' type was more common among young adults living in metropolitan areas and those with a university degree or higher. This group tended to receive higher amounts of financial support from their parents for housing costs. On the other hand, the 'Unconditional Dependency' type was prevalent among students and those whose parents had greater wealth. This group exhibited lower levels of career maturity and placed more importance on economic rewards and job security in their work values. Additionally, the study demonstrated that economic dependency among unemployed young adults is closely linked not only to financial factors but also to their career maturity and job search preparation. For example, those categorized under 'Moderate Living Expense Dependency' and 'High Housing Expense Dependency' exhibited lower career maturity but higher levels of job search preparation. This research aims to provide important policy insights by offering an in-depth understanding of the complex reasons behind young adults' financial dependence on their parents and the types of support they receive. The findings will contribute to developing policies that promote the economic independence of young adults and support a smoother transition into the workforce. Furthermore, the study provides foundational data to help reduce the challenges these young adults face during their transition into employment.

A generalized wall-pressure spectral model for non-equilibrium boundary layers

This study uses high-fidelity simulations (direct numerical simulation or large-eddy simulation) and experimental datasets to analyse the effect of non-equilibrium streamwise mean pressure gradients (adverse or favourable), including attached and separated flows, on the statistics of boundary-layer wall-pressure fluctuations. The datasets collected span a wide range of Reynolds numbers ( $Re_\theta$ from 300 to 23 400) and pressure gradients (Clauser parameter from $-0.5$ to 200). The datasets are used to identify an optimal set of variables to scale the wall-pressure spectrum: edge velocity, boundary layer thickness and the peak magnitude of Reynolds shear stress. Using the present datasets, existing semi-empirical models of the wall-pressure spectrum are shown unable to capture effects of strong, non-equilibrium adverse pressure gradients, due to inappropriate scaling of the wall pressure using the wall shear stress, calibration with limited types of flows and dependency on model parameters based on the friction velocity, which reduces to zero at the detachment point. To address these shortcomings, a generalized wall-pressure spectral model is developed with parameters that characterize the extent of the logarithmic layer and the strength of the wake. Derived from the local mean streamwise velocity profile, these two parameters inherently carry the effect of the Reynolds number, as well as those of the non-equilibrium pressure gradient and its history. Comparison with existing models shows that the proposed model behaves well and is more accurate in strong-pressure-gradient flows and in separated-flow regions.

Estimation of the distribution and density functions using Bernstein polynomials under weak dependence

The purpose of this paper is to investigate the asymptotic properties of Bernstein estimators for the distribution and density function under ψ-weak dependence. This work focuses on a type of weak dependence that is different from the notion of mixing. The asymptotic properties, namely, strong consistency and asymptotic normality are established under some regularity conditions. A simulation study based on a ψ-weak dependent model that is not necessarily mixing shows that the Bernstein estimator can outperform the Rosenblatt kernel density estimator.

Potential Benefits and Challenges of Quantifying Pseudoreplication in Genomic Data with Entropy Statistics.

Generating vast arrays of genetic markers for evolutionary ecology studies has become routine and cost-effective. However, analyzing data from large numbers of loci associated with a small number of finite chromosomes introduces a challenge: loci on the same chromosome do not assort independently, leading to pseudoreplication. Previous studies have demonstrated that pseudoreplication can substantially reduce precision of genetic analyses (and make confidence intervals wider), such as FST and linkage disequilibrium (LD) measures between pairs of loci. In LD analyses, another type of dependency (overlapping pairs of the same loci) also creates pseudoreplication. Building on previous work, we explore the potential of entropy metrics to improve the status quo, particularly total correlation (TC), to assess pseudoreplication in LD studies. Our simulations, performed on a monoecious population with a range of effective population sizes (Ne) and numbers of loci, attempted to isolate the overlapping-pairs-of-loci effect by considering unlinked loci and using entropy to quantify inter-locus relationships. We hypothesized a positive correlation between TC and the number of loci (L), and a negative correlation between TC and Ne. Results from our statistical models predicting TC demonstrate a strong effect of the number of loci, and muted effects of Ne and other predictors, adding support to the use of entropy-based metrics as a tool for estimating the statistical information of complex genetic datasets. Our results also highlight a challenge regarding scalability; computational limitations arise as the number of loci grows, making our current approach limited to smaller datasets. Despite these challenges, this work further refines our understanding of entropy measures, and offers insights into the complex dynamics of genetic information in evolutionary ecology research.

The use of Oral Anti-Diabetic Medications in Diabetes Mellitus type 1: An Educational Article and Expert Opinion

Diabetes mellitus type 1 is lifelong condition resulting from failure of production of insulin because of the loss of pancreatic islet beta-cells because of autoimmune damage. Patients with this type of diabetes need lifelong treatment with insulin to remain alive. Poor diabetic control which predisposes to a variety of complications is not uncommon in patients treated with insulin alone. Therefore, the use of medications that can possibly enhance the therapeutic effect of insulin and reduce the risk of diabetic complications has been considered. Oral anti-diabetics including acarbose, an inhibitor of intestinal α-glucosidase, metformin, a biguanide, sulfonylureas including glipizide, and sitagliptin, an inhibitor of dipeptidyl peptidase 4 (DPP-4) are primarily used for the treatment of non-insulin dependent diabetes (Type 2). The aim of this paper is to provide an overview of the use of oral anti-diabetics in the treatment of insulin dependent diabetes (Type 1). Expert opinion: The current evidence-based expert opinion recommends the judicious use of oral anti-diabetics especially acarbose and metformin in the treatment of unsatisfactorily controlled insulin dependent diabetes type 1. These medications can help in improving diabetic control through reducing glucose levels after meals, and can contribute to lowering the levels of glycosylated hemoglobin (HbA1c). The use of these oral anti-diabetics can also help in reducing insulin requirement.

Patterns of Use and Withdrawal Syndrome in Dual Cannabis and Tobacco Users (DuCATA_GAM-CAT): Protocol for a Mixed Methods Study.

Approximately 1 in 6 cannabis users develop a cannabis use disorder (CUD) and the odds increase to 1 in 2 for daily users. The Dual use of Cannabis and Tobacco Monitoreing through a Gamified Web app (DuCATA_GAM-CaT) project aims to identify cannabis-tobacco patterns of use and withdrawal symptoms among individuals with CUD who are attending substance abuse programs. The project uses a mixed methods approach consisting of 3 studies. First, a participatory qualitative study involves focus groups comprising individuals with CUD, clinicians, project researchers, and an expert gamification company to co-design a gamified web app. Second, a longitudinal prospective study to follow up individuals over 6 weeks with CUD attending substance abuse programs . Participants report their cannabis-tobacco usage patterns, type and frequency of tobacco use, nicotine dependence, withdrawal symptoms, psychoemotional factors, and motivation to quit both substances. Predictive analysis techniques are used to analyze clinical, demographic, psychological, and environmental data to predict the probability of achieving abstinence. Third, homogeneous focus groups to explore participants' experiences during their CUD treatment. By June 2024, the project had completed the first study, defining eligible cannabis user profiles, developed the initial web app prototype, and initiated recruitment across 10 centers, with 74 participants enrolled, aiming to reach 150 participants in total. All participants are required to provide informed consent, and their information is kept confidential and anonymized following confidentiality rules. The research team is committed to disseminating the results obtained to professional and patient groups, as well as informing public health agents, to positively influence political and social decision makers and design programmers. Additionally, we aim to prioritize the publication of the results in high-impact journals specialized in drug abuse, public health, and health care services research. ClinicalTrials.gov NCT05512091; https://clinicaltrials.gov/study/NCT05512091. DERR1-10.2196/58335.