Tag: statistics

Ecology. 2022 Dec 1:e3934. doi: 10.1002/ecy.3934. Online ahead of print.

ABSTRACT

Open-population spatial capture-recapture (OPSCR) models use the spatial information contained in individual detections collected over multiple consecutive occasions to estimate occasion-specific density, but also demographic parameters. OPSCR models can also estimate spatial variation in vital rates, but such models are neither widely used nor thoroughly tested. We developed a Bayesian OSPCR model that not only accounts for spatial variation in survival using spatial covariates, but also estimates local density-dependent effects on survival within a unified framework. Using simulations, we show that OPSCR models provide sound inferences on the effect of spatial covariates on survival, including multiple competing sources of mortality, each with potentially different spatial determinants. Estimation of local density-dependent survival was possible but required more data due to the greater complexity of the model. Not accounting for spatial heterogeneity in survival led to up to 10% positive bias in abundance estimates. We provide an empirical demonstration of the model by estimating the effect of country and density on cause-specific mortality of female wolverines (Gulo gulo) in central Sweden and Norway. The ability to make population-level inferences of spatial variation in survival is an essential step towards a fully spatially-explicit OPSCR model that can disentangle the role of multiple spatial drivers on population dynamics. This article is protected by copyright. All rights reserved.

PMID:36458376 | DOI:10.1002/ecy.3934

Ultrasonography. 2022 Jul 19. doi: 10.14366/usg.22082. Online ahead of print.

ABSTRACT

PURPOSE: Although the taller-than-wide (TTW) sign has been regarded as one of the most specific ultrasound (US) features of thyroid malignancy, uncertainty still exists regarding the US probe’s orientation when evaluating it. This study investigated which US plane would be optimal to identify the TTW sign based on malignancy risk stratification using a registry-based imaging dataset.

METHODS: A previous study by 17 academic radiologists retrospectively analyzed the US images of 5,601 thyroid nodules (≥1 cm, 1,089 malignant and 4,512 benign) collected in the webbased registry of Thyroid Imaging Network of Korea through the collaboration of 26 centers. The present study assessed the diagnostic performance of the TTW sign itself and fine needle aspiration (FNA) indications via a comparison of four international guidelines, depending on the orientation of the US probe (criterion 1, transverse plane; criterion 2, either transverse or longitudinal plane).

RESULTS: Overall, the TTW sign was more frequent in malignant than in benign thyroid nodules (25.3% vs. 4.6%). However, the statistical differences between criteria 1 and 2 were negligible for sensitivity, specificity, and area under the curve (AUC) based on the size effect (all P<0.05, Cohen’s d=0.19, 0.10, and 0.07, respectively). Moreover, the sensitivity, specificity, and AUC of the four FNA guidelines were similar between criteria 1 and 2 (all P>0.05, respectively).

CONCLUSION: A longitudinal US probe orientation provided little additional diagnostic value over the transverse orientation in detecting the TTW sign of thyroid nodules.

PMID:36458371 | DOI:10.14366/usg.22082

Proc Inst Mech Eng H. 2022 Dec 1:9544119221139593. doi: 10.1177/09544119221139593. Online ahead of print.

ABSTRACT

Prostheses control using electromyography signals have shown promising aspects in various fields including rehabilitation sciences and assistive technology controlled devices. Pattern recognition and machine learning methods have been observed to play a significant role in evaluating features and classifying different limb motions for enhanced prosthetic executions. This paper proposes feature extraction and evaluation method using intramuscular electromyography (iEMG) signals at different arm positions and hand postures based on the RES Index value statistical criterion method. Sixteen-time domain features were selected for the study at two main circumstances; fixed arm position (FAP) and fixed hand posture (FHP). Eight healthy male participants (30.62 ± 3.87 years) were asked to execute five motion classes including hand grip, hand open, rest, hand extension, and hand flexion at four different arm positions that comprise of 0°, 45°, 90°, and 135°. The classification process is accomplished via the application of the k-nearest neighbor (KNN) classifier. Then RES index was calculated to investigate the optimal features based on the proposed statistical criterion method. From the RES Index, we concluded that Variance (VAR) is the best feature while WAMP, Zero Crossing (ZC), and Slope Sign Change (SSC) are the worst ones in FAP conditions. On the contrary, we concluded that Average Amplitude Change (AAC) is the best feature while WAMP and Simple Square Integral (SSI) resulted in least RES Index values for FHP conditions. The proposed study has possible iEMG based applications such as assistive control devices, robotics. Also, working with the frequency domain features encapsulates the future scope of the study.

PMID:36458327 | DOI:10.1177/09544119221139593

Heliyon. 2022 Nov 18;8(11):e11672. doi: 10.1016/j.heliyon.2022.e11672. eCollection 2022 Nov.

ABSTRACT

The aim of this research is to examine the trend of water use efficiency (WUE) and the spillover effect of its determinants in 28 sub-Saharan Africa (SSA) countries over the period 2007 to 2018 using the directional distance function (DDF) and the spatial Durbin model. Results of the DDF revealed that the most efficient countries include Botswana, and Liberia whereas countries with poor performance include Niger and South Africa. Also, the average efficiency scores over the study period improved steadily from 0.582 in 2007 to 0.698 in 2018. The study showed that under economic distance weight in the spatial Durbin model, the values of the spatial lag coefficients of urbanisation (URB), export (EX), and education (EDU) depict positive and statistically significant effects on WUE, while industrial activities (IND), foreign direct investment (FDI), and government interference (COR) had an adverse influence on WUE in SSA. Results of the spatial decomposition effect of URB demonstrated a major impact on WUE in both the local and adjacent countries. However, a significant decline of WUE through the direct and indirect impacts of FDI, EX, and COR in the local and neighboring countries was recorded which indicate the presence of a negative spatial dependency on WUE in SSA. The outcome of this study implies that policymakers in SSA countries must strengthen sustainable water resources management decisions with neighbouring countries to achieve sustainable development goal 6 by 2030 and beyond.

PMID:36458314 | PMC:PMC9706135 | DOI:10.1016/j.heliyon.2022.e11672

Heliyon. 2022 Nov 23;8(11):e11862. doi: 10.1016/j.heliyon.2022.e11862. eCollection 2022 Nov.

ABSTRACT

Cryptocurrency is an advanced digital currency that is secured by encryption, making it nearly impossible to forge or duplicate. Many cryptocurrencies are blockchain-based with decentralized networks. The prediction of cryptocurrency prices is a very difficult task because of the absence of an appropriate analytical basis to substantiate their claims. Cryptocurrencies are also dependent on several variables, such as technical advancement, internal competition, market pressure, economic concerns, security, and political considerations. This paper proposed the hybrid walk-forward ensemble optimization technique and applied it to predict the daily prices of fifteen cryptocurrencies, such as Cardano (ADA-USD), Bitcoin (BTC-USD), Dogecoin (DOGE-USD), Ethereum Classic (ETC-USD), Chainlink (LINK-USD), Litecoin (LTC-USD), NEO (NEO-USD), Tron (TRX-USD), Tether (USDT-USD), NEM (XEM-USD), Stellar (XLM-USD), Ripple (XRP-USD), and Tezos (XTZ-USD). A performance comparison of these cryptocurrencies was done using classical statistical models, machine learning algorithms, and deep learning algorithms on different cryptocurrency time series. Simulation results show that our proposed model performed better in terms of cryptocurrency prediction accuracy compared to the classical statistical model and machine and deep learning algorithms used in this paper.

PMID:36458312 | PMC:PMC9706710 | DOI:10.1016/j.heliyon.2022.e11862

Heliyon. 2022 Nov 23;8(11):e11834. doi: 10.1016/j.heliyon.2022.e11834. eCollection 2022 Nov.

ABSTRACT

With the continuous development of automation and information technology, large amounts of safety data are produced in the processes of coal production. Most enterprises simply focus on statistics and do not conduct systematic big data analyses. Therefore, it is necessary to study the theory of coal mine safety while using big data systematically. This paper expounds on the changes in coal mine safety that have been driven by big data from three aspects: the connotation, characteristics and research framework. First, the connotation of coal mine safety big data (CMSBD) is redefined by changing the safety entities and methods. Second, the advantages and disadvantages of the big data model are compared from the perspective of feature analysis. Finally, the research paradigm and technical framework of CMSBD are designed. The results show that the management connotation of CMSBD focuses on the role of big data in coal mine safety. Compared with coal mine safety small data (CMSSD), CMSBD has both advantages and disadvantages. Therefore, CMSBD must be combined with a small data method. The research paradigm emphasizes the intersection of the research, the relevance of safety thinking, the importance of safety data analysis, and the fusion of big data with traditional small data models.

PMID:36458302 | PMC:PMC9706694 | DOI:10.1016/j.heliyon.2022.e11834

Heliyon. 2022 Nov 22;8(11):e11781. doi: 10.1016/j.heliyon.2022.e11781. eCollection 2022 Nov.

ABSTRACT

The citrus agro-industry is one of the world’s most important agricultural sectors. The Persian lime is one of six citrus fruit groups with economic significance. The technological lifecycle of Persian lime sector is assessed in this study using the growth S-curve approach. The objective is to depict the technology life cycle trajectory and current stage of the Persian lime citrus fruit, as well as each of its value chain phases, in order to facilitate better decision-making and technological strategies. The study uses technological patents collected from the World Intellectual Property Organization (WIPO) database from 1975 to 2009. The S-curve model of Persian lime and its value chain stages is generated using logistic mathematical regression. According to the findings of this study, Persian lime is in the maturity stage of the technology life cycle. As a result, the primary strategy could be cost reduction, process innovation, and price strategies to capitalize on market opportunities. When compared to other value chain phases, the transformation phase has the highest number of patents according to the value chain analysis and it is the unique value chain phase with statistical significance in the model. The transformation phase is also at the maturity stage of the technology life cycle. This creates opportunities in two ways: first, to adopt previously developed technologies in the transformation phase and improve process efficiency to reduce costs; and second, to reinforce innovative technological efforts in other phases of the Persian lime value chain, such as growth, harvest, or post-harvest.

PMID:36458301 | PMC:PMC9706162 | DOI:10.1016/j.heliyon.2022.e11781

Front Dent. 2022 Jul 3;19:22. doi: 10.18502/fid.v19i22.9969. eCollection 2022.

ABSTRACT

Objectives: Parents are aware of the importance of anterior tooth esthetics in their children. Children also pay attention to their appearance more than ever. Today, charcoal has been added to toothpastes. Charcoal can help whiten teeth through abrasion. This study aimed to investigate the degree of bleaching and abrasion of charcoal toothpaste on primary teeth. Materials and Method: This in-vitro study was performed on 30 extracted primary teeth. Initially, the samples were polished, cut, and mounted in blocks of putty. The samples were placed in a coffee solution and then the tooth color was measured by a spectrophotometer and the initial surface profile was measured by a profilometer. The samples were brushed back and forth by the brushing machine with 20 gr Bancer, Beverly, and Colgate toothpastes (mixed with 40 ml of distilled water) for 2000 times (equivalent to 3 times a day for 1.5 months). A color determination was performed again and a second surface profile was measured. The data were analyzed by one-way ANOVA, ANCOVA and paired t-test. Results: The results of this study showed that all three Beverly, Bencer and Colgate whitening toothpastes increased the surface profile and made significant statistical changes in the roughness of dental specimens (P=0.01, P=0.005, P=0.001). The statistical study of the data did not show a significant difference between the groups in terms of abrasion and whitening properties (P=0.78, P= 0.99). Conclusion: Three whitening toothpastes whiten primary teeth and increase their surface roughness. These three toothpastes are not statistically different in terms of abrasion and whitening properties.

PMID:36458278 | PMC:PMC9675625 | DOI:10.18502/fid.v19i22.9969

BMC Public Health. 2022 Dec 1;22(1):2242. doi: 10.1186/s12889-022-14633-4.

ABSTRACT

BACKGROUND: The COVID-19 pandemic disrupted access to healthcare services in Canada. Research prior to the pandemic has found that depression and anxiety symptoms were associated with increased unmet healthcare needs. The primary objective of this study was to examine if mental health was associated with perceived access to healthcare during the pandemic METHODS: A cross-sectional study was conducted using data from 23,972 participants (aged 50-96) in the Canadian Longitudinal Study on Aging COVID-19 Exit Survey (Sept-Dec 2020). We used logistic regression to estimate how the presence of depression and anxiety symptoms, defined using scores of ≥10 on the Center for Epidemiologic Studies Depression Scale and ≥10 on the Generalized Anxiety Disorder Scale, were associated with the odds of reporting: 1) challenges accessing healthcare, 2) not going to a hospital or seeing a doctor when needed, 3) experiencing barriers to COVID-19 testing. Models were adjusted for sex, age, region, urban/rural residence, racial background, immigrant status, income, marital status, work status, chronic conditions, and pre-pandemic unmet needs.

RESULTS: The presence of depressive (aOR=1.96; 95% CI=1.82, 2.11) and anxiety symptoms (aOR=2.33; 95% CI=2.04, 2.66) compared to the absence of these symptoms were independently associated with higher odds of challenges accessing healthcare. A statistically significant interaction with sex suggested stronger associations in females with anxiety. Symptoms of depression (aOR=2.88; 95% CI=2.58, 3.21) and anxiety (aOR=3.05; 95% CI=2.58, 3.60) were also associated with increased odds of not going to a hospital or seeing a doctor when needed. Lastly, depressive (aOR=1.99; 95% CI=1.71, 2.31) and anxiety symptoms (aOR=2.01; 95% CI=1.58, 2.56) were associated with higher odds of reporting barriers to COVID-19 testing. There was no significantly significant interaction with sex for the latter two outcomes.

CONCLUSION: The presence of depression and anxiety symptoms were strongly associated with perceived unmet healthcare needs during the COVID-19 pandemic. Interventions to improve healthcare access for adults with depression and anxiety during the pandemic may be necessary.

PMID:36456993 | DOI:10.1186/s12889-022-14633-4

Diabetol Metab Syndr. 2022 Dec 2;14(1):183. doi: 10.1186/s13098-022-00938-2.

ABSTRACT

INTRODUCTION: Diabetic foot ulcers (DFU) are one of the leading long-term complications experienced by patients with diabetes. Dipeptidyl Peptidase 4 inhibitors (DPP4is) are a class of antihyperglycemic medications prescribed to patients with diabetes to manage glycaemic control. DPP4is may also have a beneficial effect on DFU healing. This study aimed to determine vildagliptin’s effect on inflammatory markers and wound healing.

TRIAL DESIGN: Prospective, randomized, double-blind, placebo-controlled, single-center study.

METHODS: Equal number of participants were randomized into the treatment and placebo groups. The treatment was for 12 weeks, during which the participants had regular visits to the podiatrist, who monitored their DFU sizes using 3D camera, and blood samples were taken at baseline, six weeks, and 12 weeks during the study for measurement of inflammatory markers. In addition, demographic characteristics, co-morbidities, DFU risk factors, and DFU wound parameters were recorded.

RESULTS: 50 participants were recruited for the study, with 25 assigned to placebo and 25 to treatment group. Vildagliptin treatment resulted in a statistically significant reduction of HBA1c (p < 0.02) and hematocrit (p < 0.04), total cholesterol (p < 0.02), LDL cholesterol (p < 0.04), and total/HDL cholesterol ratio (P < 0.03) compared to the placebo group. Also, vildagliptin had a protective effect on DFU wound healing, evidenced by the odds ratio (OR) favoring the intervention of 11.2 (95% CI 1.1-113.5; p < 0.04) and the average treatment effect on the treated (ATET) for vildagliptin treatment group showed increased healing by 35% (95%CI; 10-60, p = 0.01) compared to placebo with the model adjusted for microvascular complications, smoking, amputation, dyslipidemia, peripheral vascular disease (PVD) and duration of diabetes.

CONCLUSIONS: Vildagliptin treatment was effective in healing DFU in addition to controlling the diabetes. Our findings support the use of DPP4is as a preferred option for treating ulcers in patients with diabetes. Further studies on a larger population are warranted to confirm our findings and understand how DPP4is could affect inflammation and DFU healing.

PMID:36456992 | DOI:10.1186/s13098-022-00938-2