Search Results (70)

This study investigates the impact of data distribution and bootstrap resampling on the anomaly detection performance of the Isolation Forest (iForest) algorithm in statistical process control. Although iForest has received attention for its multivariate and ensemble-based nature, its performance under non-normal data distributions and varying bootstrap settings remains underexplored. To address this gap, a comprehensive simulation was performed across 18 scenarios involving log-normal, gamma, and t-distributions with different mean shift levels and bootstrap configurations. The results show that iForest substantially outperforms the conventional Hotelling’s T² control chart, especially in non-Gaussian settings and under small-to-medium process shifts. Enabling bootstrap resampling led to marginal improvements across classification metrics, including accuracy, precision, recall, F1-score, and average run length (ARL)₁. However, a key limitation of iForest was its reduced sensitivity to subtle process changes, such as a 1σ mean shift, highlighting an area for future enhancement. Full article

This study aimed to propose a probability-guaranteed spectrum method to enhance the reliability of seismic building designs, thereby addressing the inadequacy of the current code-specified response spectrum based on mean fortification levels. This study systematically evaluated the fitting performance of dynamic coefficient spectra under normal, log-normal, and gamma distribution assumptions based on 288 ground motion records from type II sites. MATLAB(2010) parameter fitting and the Kolmogorov–Smirnov test were used, revealing that the gamma distribution optimally characterized spectral characteristics across all period ranges (p < 0.05). This study innovatively established dynamic coefficient spectra curves for various probability guarantee levels (50–80%), quantitatively revealing the insufficient probability assurance of code spectra in the long-period range. Furthermore, this study proposed an evaluation framework for load safety levels of spectral values over the design service period, demonstrating that increasing probability guarantee levels significantly improved safety margins over a 50-year reference period. This method provides probabilistic foundations for the differentiated seismic design of important structures and offers valuable insights for revising current code provisions based on mean spectra. Full article

A series of fault depressions developed in the Kailu area on the southwestern margin of the Songliao Basin, where thick lacustrine fine-grained sedimentary rocks were widely deposited during the initial faulting stage in the Early Cretaceous. These formations serve as the primary source rocks within the depressions. To investigate the depositional cyclicity framework, paleoenvironmental conditions, and source rock development patterns of fine-grained sedimentary strata, this study focuses on the Naiman Sag, selecting Well Nai-10 for wavelet transform and spectral analysis based on natural gamma ray logs. Combining core, well logging, and geochemical element analyses, Milankovitch cycles within the Yixian Formation were identified. The relationship between theoretical orbital periods and sedimentary cycles in a single well was established, enabling the high-precision identification and classification of fine-grained sedimentary cycles. Furthermore, the study explores the sedimentary response to orbital forcing and the development patterns of source rocks. The results indicate that fine-grained sedimentary strata exhibit distinct Milankovitch cyclicity, with a strong correlation between astronomical periods and sedimentary cycles. Using the 100 kyr short eccentricity cycle as the tuning curve, an astronomical timescale and high-frequency cyclic division for the target interval were established. Under the control of long eccentricity cycles, sedimentation exhibits strong response characteristics: near the peak of short eccentricity cycles, the climate was warm and humid, redox conditions were strong, and precipitation was high, facilitating organic matter accumulation. Based on this response relationship, two ideal enrichment models of mudstone and shale under different paleoclimatic conditions are proposed, providing valuable insights for identifying high-quality source rocks and unconventional hydrocarbons in hydrocarbon exploration. Full article

The Yan’an Formation in the Liupanshan Basin hosts substantial coal and oil shale resources. However, coal and oil shale often exhibit different types of associated or syngenetic combinations, which makes it difficult to recognize coal and oil shales, and research on the patterns of development of coal and oil shales is lacking. In this study, field outcrop, core, logging, and analytical data are comprehensively utilized to describe the characteristics of coal and oil shale, classify their syngenetic combinations, and establish a developmental model. Analytical results from the Tanshan area reveal that coal exhibits a lower density and higher oil content than oil shale. Specifically, coal shows oil contents ranging from 7.22% to 13.10% and ash contents of 8.25–35.66%, whereas oil shale displays lower oil contents (3.88–6.98%) and significantly higher ash contents (42.28–80.79%). The oil and ash contents of both coal and oil shale in the Tanshan area show a negative correlation, though this correlation is significantly stronger in coal than in oil shale. In long-range gamma-ray and resistivity logs, coal exhibits substantially higher values compared to oil shale, whereas in density logs, oil shale shows greater values than coal. Acoustic time difference logging reveals marginally higher values for coal than for oil shale, though the difference is minimal. There are five combination types between coal and oil shale in this area. The oil shale formed in a warm, humid, highly reducing lacustrine environment within relatively deep-water bodies, while coal developed in swampy shallow-water environments; both derive organic matter from higher plants. Variations in depositional settings and environmental conditions resulted in five distinct combination types of coal and oil shale. Full article

The Miocene Hanjiang Formation (HJF) is a remarkable exploration target in the Pearl River Mouth Basin (PRMB). However, challenges such as bias in current sequence stratigraphic schemes, limitations in high-resolution stratigraphic schemes, and incomplete understanding of genetic mechanisms may present obstacles for refining hydrocarbon exploration strategies. This study integrates gamma ray (GR) logging data, lithological variations, sequence stratigraphy, and cyclostratigraphy to delineate connections between sequence stratigraphy and astronomical forcing. The analysis utilizes gamma-ray logging data from boreholes LFA (1250–1960 m) and LFB (1070–1955 m) in the HJF. We constructed an absolute astronomical time scale anchored at the HJF’s top boundary (10.221 ± 0.4 Ma), identifying 6 third-order sequences through detailed analysis. Notably, 18 long-eccentricity cycles (405 kyr) and distinctive 1.2-Myr obliquity modulation signals were detected in the stratigraphic record. Our study demonstrates distinct connection between third-order sequence boundaries and the 1.2-Myr obliquity cycles, congruent with both global eustatic sea-level fluctuations and regional sea-level changes in the PRMB. The integration of cyclostratigraphic methods with sequence stratigraphic analysis proves particularly valuable for objective stratigraphic subdivision and understanding third-order sequence evolution in the divergent continental margin settings of the South China Sea. This approach enhances temporal resolution on a regional scale while revealing astronomical forcing mechanisms governing sedimentary cyclicity. Full article

The aim of this study is to quantitatively analyze the long-term climate variability in Poland during the period 1901–2010, using Shannon entropy as a measure of uncertainty and complexity within the atmospheric system. The analysis is based on the premise that variations in temperature and precipitation reflect the dynamic nature of the climate, understood as a nonlinear system sensitive to fluctuations. This study focuses on monthly distributions of temperature and precipitation, modeled using the bivariate Clayton copula function. A normal marginal distribution was adopted for temperature and a gamma distribution for precipitation, both validated using the Anderson–Darling test. To improve estimation accuracy, a bootstrap resampling technique and numerical integration were applied to calculate Shannon entropy at each of the 396 grid points, with a spatial resolution of 0.25° × 0.25°. The results indicate a significant increase in Shannon entropy during the summer months, particularly in July (+0.203 bits) and January (+0.221 bits), compared to the baseline period (1901–1971), suggesting a growing unpredictability of the climate. The most pronounced trend changes were identified in the years 1985–1996 (as indicated by the Pettitt test), while seasonal trends were confirmed using the Mann–Kendall test. A spatial analysis of entropy at the levels of administrative regions and catchments revealed notable regional disparities—entropy peaked in January in the West Pomeranian Voivodeship (4.919 bits) and reached its minimum in April in Greater Poland (3.753 bits). Additionally, this study examined the relationship between Shannon entropy and global climatic indicators, including the Land–Ocean Temperature Index (NASA GISTEMP) and the ENSO index (NINO3.4). Statistically significant positive correlations were observed between entropy and global temperature anomalies during both winter ($\rho$ = 0.826) and summer ($\rho$ = 0.650), indicating potential linkages between local climate variability and global warming trends. To explore the direction of this relationship, a Granger causality test was conducted, which did not reveal statistically significant causality between NINO3.4 and Shannon entropy ($p$ > 0.05 for all lags tested), suggesting that the observed relationships are likely co-varying rather than causal in the Granger sense. Further phase–space analysis (with a delay of $\tau$ = 3 months) allowed for the identification of attractors characteristic of chaotic systems. The entropy trajectories revealed transitions from equilibrium states (average entropy: 4.124–4.138 bits) to highly unstable states (up to 4.768 bits), confirming an increase in the complexity of the climate system. Shannon entropy thus proves to be a valuable tool for monitoring local climatic instability and may contribute to improved risk modeling of droughts and floods in the context of climate change in Poland. Full article

Deoxyribonucleic acid, more commonly known as DNA, is a fundamental genetic material in all living organisms, containing thousands of genes, but only a subset exhibit differential expression and play a crucial role in diseases. Microarray technology has revolutionized the study of gene expression, with two primary types available for expression analysis: spotted cDNA arrays and oligonucleotide arrays. This research focuses on the statistical analysis of data from spotted cDNA microarrays. Numerous models have been developed to identify differentially expressed genes based on the red and green fluorescence intensities measured using these arrays. We propose a novel approach using a Gaussian copula model to characterize the joint distribution of red and green intensities, effectively capturing their dependence structure. Given the right-skewed nature of the intensity distributions, we model the marginal distributions using gamma distributions. Differentially expressed genes are identified using the Bayes estimate under our proposed copula framework. To evaluate the performance of our model, we conduct simulation studies to assess parameter estimation accuracy. Our results demonstrate that the proposed approach outperforms existing methods reported in the literature. Finally, we apply our model to Escherichia coli microarray data, illustrating its practical utility in gene expression analysis. Full article

A joint distribution of significant wave heights ($H_s$) and peak wave periods ($T_p$) in the northwestern South China Sea is created using a conditional distribution model in this work. An unstructured triangular mesh wave model covering the northwestern South China Sea is established based on the third-generation spectral wave model SWAN. This wave model has been extensively validated against field data and was run from 1979 to 2020 to generate long enough one-hourly $H_s$ and $T_p$. Four probability density functions including Normal, Lognormal, Gamma and 3P Weibull distributions are adopted to construct the marginal independent distribution of $H_s$. The results show that the 3P Weibull distribution is more suitable in fitting the marginal distribution of $H_s$ compared to the other three distributions. Three combinations of dependence functions ($\mu \mathrm{and} \sigma$), namely, power3 and exp3, insquare2 and asymdecrease3, and logistics4 and alpha3, are used to create the Normal and Lognormal distributions for $T_p$. The estimations of dependence functions and corresponding fitted $T_p$ demonstrate that the $\mu \mathrm{and} \sigma$ using power3 and exp3 perform best in producing the conditional distribution of $T_p$. In addition, the environmental contours derived by an IFORM are used to generate the extreme sea states with return periods of 1, 5, 10, 25, 50 and 100 years. Full article

This paper develops a new approach for the detection of spatial clusters in the presence of random environmental effects and covariates when the observed data consist of counts over a regular grid. Such data are frequently overdispersed and spatially dependent. Overdispersion and spatial dependence must be taken into account in the modeling, otherwise the classical scan statistics method may lead to the detection of false clusters. Therefore, we consider that the observed counts are generated by a Cox process, allowing for overdispersion and spatial correlation. The environmental effects here represents unobserved covariates, as opposed to observed covariates whose observations are used via the link function in the model. These random effects are modeled by means of spatial copula with margins distributed according to a Gamma distribution. We then prove that the counts are dependent and negative binomial and propose a spatial cluster detection test based on data augmentation techniques. It is worth noting that our model also includes the case of independent effects for which the counts are independent and negative binomial. An illustration of these spatial scan techniques is provided by a Black Leaf Streak Disease (BLSD) dataset from Martinique, French West Indies. The comparison of our model with Poisson models, with or without covariates, demonstrates the importance of our approach in avoiding false clusters. Full article

Background: Gamma Knife Radiosurgery (GKRS), a specific type of Stereotactic Radiosurgery (SRS), has developed as a significant modality in the treatment of glioblastoma, particularly in conjunction with standard chemotherapy. The goal of this study is to evaluate the efficacy of combining GKRS with surgical resection and chemotherapy in enhancing therapeutic effects for glioblastoma patients aged 55 years and older. Methods: This prospective clinical study, conducted in accordance with the STROBE guidelines, involved 49 glioblastoma patients aged 55 years and older, treated between January 2013 and January 2023. Data were collected prospectively, and strict adherence to the STUPP protocol was maintained. Only patients who conformed to the STUPP protocol were included in the analysis. Due to concerns regarding the cognitive impairment associated with conventional radiotherapy, and at the patients’ request, a radiosurgery plan was offered. Radiosurgery was administered for 4–8 weeks following surgical resection. Any patients who had not received previous radiotherapy received open surgical tumor removal, followed by GKRS along with adjuvant chemotherapy. Results: In this prospective clinical study of 49 glioblastoma patients aged 55 years and older, the average lifespan post-histopathological diagnosis was established at 22.3 months (95% CI: 12.0–28.0 months). The median time before disease progression was 14.3 months (95% CI: 13.0–29.7 months). The median duration until the first recurrence after treatment was 15.2 months, with documented cases varying between 4 and 33 months. The Gamma Knife Radiosurgery (GKRS) treatment involved a median marginal recommended dose of 12.5 Gy, targeting an average volume of 5.7 cm³ (range: 1.6–39 cm³). Local recurrence occurred in 21 patients, while distant recurrence was identified in 8 patients. Within the cohort, 34 patients were subjected to further therapeutic approaches, including reoperation, a second GKRS session, the administration of bevacizumab and irinotecan, and PCV chemotherapy. A cognitive function assessment revealed that the patients treated with GKRS experienced significantly less cognitive decline compared to the historical controls, who were treated with conventional radiotherapy. The median MMSE scores declined by 1.9 points over 12 months, and the median MoCA scores declined by 2.9 points. Conclusion: This study demonstrates that Gamma Knife Radiosurgery (GKRS), when integrated with surgical resection and adjuvant chemotherapy, offers a substantial benefit for glioblastoma patients aged 55 years and older. The data reveal that GKRS not only prolongs overall survival and progression-free survival but also significantly reduces cognitive decline compared to conventional radiotherapy. These findings underscore the efficacy and safety of GKRS, advocating for its incorporation into standard treatment protocols for older glioblastoma patients. The potential of GKRS to improve patient outcomes while preserving cognitive function is compelling and warrants further research to optimize and confirm its role in glioblastoma management. Full article

The Pareto–Feller distribution has been widely used across various disciplines to model “heavy-tailed” phenomena, where extreme events such as high incomes or large losses are of interest. In this paper, we present a new bivariate distribution based on the Appell hypergeometric function with marginal Pareto–Feller distributions obtained from two independent gamma random variables. The proposed distribution has the beta prime marginal distributions as special case, which were obtained using a Kibble-type bivariate gamma distribution, and the stochastic representation was obtained by the quotient of a scale mixture of two gamma random variables. This result can be viewed as a generalization of the standard bivariate beta I (or inverted bivariate beta distribution). Moreover, the obtained bivariate density is based on two confluent hypergeometric functions. Then, we derive the probability distribution function, the cumulative distribution function, the moment-generating function, the characteristic function, the approximated differential entropy, and the approximated mutual information index. Based on numerical examples, the exact and approximated expressions are shown. Full article

According to the American Joint Commission on Cancer (AJCC) 8th edition guidelines, SLN biopsy is recommended for primary melanomas with a Breslow thickness of at least 1 mm. Additionally, the National Comprehensive Cancer Network (NCCN) recommends that a SLN biopsy may be considered for melanoma patients with T1b lesions, which are 0.8–1 mm thick or less than 0.8 mm thick with ulceration. It can also be considered for T1a lesions that are less than 0.8 mm thick but have other adverse features, such as a high mitotic rate, lymphovascular invasion, or a positive deep margin. To reduce the false negative rate of melanoma SLN biopsy, we have introduced the intraoperative use of Sentinella, a gamma camera, to enhance the identification rate of SLNs beyond that of the traditional gamma hand-held probe. At the Center for Melanoma Research and Treatment at the California Pacific Medical Center, a multidisciplinary approach has been established to treat melanoma patients when the diagnosis of primary melanoma is made with a referral to our melanoma center. This comprehensive approach at the melanoma tumor board, including the efforts of pathologists, radiologists, dermatologists, surgical, medical and radiation oncologists, results in a consensus to deliver personalized and high-quality care for our melanoma patients. This multidisciplinary program for the management of melanoma can be duplicated for other types of cancer. This article consists of current knowledge to document the published methods of identification of sentinel lymph nodes. In addition, we have included new data as developed in our melanoma center as newly published materials in this article to demonstrate the utility of these methods in melanoma sentinel lymph node surgery. Informed consent has been waived by our IRB regarding the acquisition of clinical data as presented in this study. Full article

For the past 70 years, the dopamine hypothesis has been the key working model in schizophrenia. This has contributed to the development of numerous inhibitors of dopaminergic signaling and antipsychotic drugs, which led to rapid symptom resolution but only marginal outcome improvement. Over the past decades, there has been limited research on the quantifiable pathological changes in schizophrenia, including premature cellular/neuronal senescence, brain volume loss, the attenuation of gamma oscillations in electroencephalograms, and the oxidation of lipids in the plasma and mitochondrial membranes. We surmise that the aberrant activation of the aryl hydrocarbon receptor by toxins derived from gut microbes or the environment drives premature cellular and neuronal senescence, a hallmark of schizophrenia. Early brain aging promotes secondary changes, including the impairment and loss of mitochondria, gray matter depletion, decreased gamma oscillations, and a compensatory metabolic shift to lactate and lactylation. The aim of this narrative review is twofold: (1) to summarize what is known about premature cellular/neuronal senescence in schizophrenia or schizophrenia-like disorders, and (2) to discuss novel strategies for improving long-term outcomes in severe mental illness with natural senotherapeutics, membrane lipid replacement, mitochondrial transplantation, microbial phenazines, novel antioxidant phenothiazines, inhibitors of glycogen synthase kinase-3 beta, and aryl hydrocarbon receptor antagonists. Full article

Background: The role of stereotactic radiosurgery (SRS) for patients with brain metastases from hepatopancreaticobiliary (HPB) cancers has yet to be established. The authors present a single-institution experience of patients with HPB cancers who underwent SRS when their cancer spread to the brain. Methods: We surveyed our Gamma Knife SRS data base of 18,000 patients for the years 1987–2022. In total, 19 metastatic HPB cancer patients (13 male) with 76 brain metastases were identified. The median age at SRS was 61 years (range: 48–83). The primary cancer sites were hepatocellular carcinoma (HCC, 11 patients), cholangiocarcinoma (CCC, 2 patients), and pancreatic carcinoma (PCC, 6 patients). The median Karnofsky Performance Score (KPS) was 80 (range: 50–90). Two patients underwent pre-SRS whole-brain fractionated radiation therapy (WBRT) and eight patients underwent pre-SRS surgical resection. All SRS was delivered in single session. The median margin dose was 18 Gy (range: 15–20). The median cumulative tumor volume was 8.1 cc (range: 1.0–44.2). Results: The median patient overall survival (OS) after SRS was 7 months (range 1–79 months). Four patients had documented local tumor progression after SRS at a median time of 8.5 months (range: 2–15) between SRS and progression. Out of 76 treated tumors, 72 tumors exhibited local control. The local tumor control rate per patient was 78.9%. The local tumor control per tumor was 94.7%. Four patients developed new brain metastases at a median of 6.5 months (range: 2–17) after SRS. No patient experienced adverse radiation effects (AREs). At the last follow-up, 18 patients had died, all from systemic disease progression. Conclusions: Metastatic spread to the brain from HPB cancers occurs late in the course of the primary disease. In this study, all deceased patients ultimately died from primary disease progression. SRS is a non-invasive strategy that maximally preserves quality of life, and our results reported favorable outcomes compared to the existing literature. SRS should be considered as one of the primary management strategies for patients with brain metastatic spread from HPB cancer. Full article

This paper measures two main inefficiency features (many publications other than articles; many co-authors’ reciprocal citations) and two main inequity features (more co-authors in some disciplines; more citations for authors with more experience). It constructs a representative dataset based on a cross-disciplinary balanced sample (10,000 authors with at least one publication indexed in Scopus from 2006 to 2015). It estimates to what extent four additional improvements of the H-index as top-down regulations (∆H_h = H_h − H_h+1 from H₁ = based on publications to H₅ = net per-capita per-year based on articles) account for inefficiency and inequity across twenty-five disciplines and four subjects. Linear regressions and ANOVA results show that the single improvements of the H-index considerably and decreasingly explain the inefficiency and inequity features but make these vaguely comparable across disciplines and subjects, while the overall improvement of the H-index (H₁–H₅) marginally explains these features but make disciplines and subjects clearly comparable, to a greater extent across subjects than disciplines. Fitting a Gamma distribution to H₅ for each discipline and subject by maximum likelihood shows that the estimated probability densities and the percentages of authors characterised by H₅ ≥ 1 to H₅ ≥ 3 are different across disciplines but similar across subjects. Full article