Search Results (17)

The article investigates the accuracy of nonparametric univariate density estimation methods applied to various Gaussian mixture models. A comprehensive comparative analysis is performed for four popular estimation approaches: adaptive kernel density estimation, projection pursuit, log-spline estimation, and wavelet-based estimation. The study is extended with modified versions of these methods, where the sample is first clustered using the EM algorithm based on Gaussian mixture components prior to density estimation. Estimation accuracy is quantitatively evaluated using MAE and MAPE criteria, with simulation experiments conducted over 100,000 replications for various sample sizes. The results show that estimation accuracy strongly depends on the density structure, sample size, and degree of component overlap. Clustering before density estimation significantly improves accuracy for multimodal and asymmetric densities. Although no formal statistical tests are conducted, the performance improvement is validated through non-overlapping confidence intervals obtained from 100,000 simulation replications. In addition, several decision-making systems are compared for automatically selecting the most appropriate estimation method based on the sample’s statistical features. Among the tested systems, kernel discriminant analysis yielded the lowest error rates, while neural networks and hybrid methods showed competitive but more variable performance depending on the evaluation criterion. The findings highlight the importance of using structurally adaptive estimators and automation of method selection in nonparametric statistics. The article concludes with recommendations for method selection based on sample characteristics and outlines future research directions, including extensions to multivariate settings and real-time decision-making systems. Full article

Background and Objectives: Alzheimer’s disease (AD) is a progressive neurodegenerative condition that significantly affects cognitive, emotional, and functional abilities in older adults. This study aimed to explore how demographic, clinical, and psychological factors influence the progression of cognitive decline in patients diagnosed with AD. Materials and Methods: A total of 101 patients were evaluated retrospectively and followed longitudinally at three different time points, using standardized instruments, including the MMSE, Reisberg’s GDS, clock-drawing test, MADRS, and Hamilton depression scale. Statistical methods included non-parametric tests, mixed-effect modeling, and Bayesian analysis. Results: Most patients were older women from rural areas, predominantly in moderate-to-severe stages of AD. Age showed a significant association with cognitive decline (p < 0.05), and depression—particularly in moderate and severe forms—was strongly linked to lower MMSE scores (p < 0.001). Over 70% of the participants had some degree of depression. The clock-drawing test highlighted visuospatial impairments, consistent with everyday functional loss. Although donepezil and memantine combinations appeared to be more frequently prescribed, no treatment showed a statistically significant advantage, and confidence interval overlaps suggest caution in interpreting differences between therapies. Longitudinal models confirmed a progressive and accelerated decline, with inter-individual variability becoming more pronounced in later stages. Although comorbidities, such as hypertension and diabetes, were frequent, they did not show a statistically significant effect on MMSE scores in this cohort. Conclusions: Age and depression appear to play central roles in the pace of cognitive deterioration in AD. Given the limited efficacy of most current therapies, these findings highlight the need for earlier intervention and a more personalized, integrated approach—combining cognitive care, psychiatric support, and comorbidity management—to better meet the needs of patients with AD. Full article

Specific monosaccharide residue, β-D-galactofuranose (Galf) featuring a five-membered ring structure, is found in the glycans of fungi and bacteria, but is normally absent in healthy mammals and humans. In this study, synthetic oligosaccharides mimicking bacterial and fungal glycans were investigated by SERS (Surface-Enhanced Raman Scattering) techniques for the first time to distinguish between different types of glycan chains. SERS spectra of oligosaccharides related to fungal α-(1→2)-mannan, β-(1→3)-glucan, β-(1→6)-glucan, galactomannan of Aspergillus, galactan I of Klebsiella pneumoniae, and diheteroglycan of Enterococcus faecalis were measured. To analyze the spectra, a number of machine learning methods were used that complemented each other: principal component analysis (PCA), confidence interval estimation (CIE), and logistic regression with L1 regularization. Each of the methods has shown own effectiveness in analyzing spectra. Namely, PCA allows the visualization of the divergence of spectra in the principal component space, CIE visualizes the degree of overlap of spectra through confidence interval analysis, and logistic regression allows researchers to build a model for determining the belonging of the analyte to a given class of carbohydrate structures. Additionally, the methods complement each other, allowing the determination of important features representing the main differences in the spectra containing and not containing Galf residue. The developed mathematical models enabled the reliable identification of Galf residues within glycan compositions. Given the high sensitivity of SERS, this spectroscopic technique serves as a promising basis for developing diagnostic test systems aimed at detecting biomarkers of fungal and bacterial infections. Full article

The navel orangeworm, Amyelois transitella, is the principal pest of pistachio and almond in California. The timing of the insecticide application is challenging because there is no model that predicts when pistachio is vulnerable to infestation. Sixteen years of pistachio flight data from Madera and Fresno counties (541,892 adults) were analyzed to determine if there was a consistent starting point each year for flights that overlap pistachio vulnerability. This effort was complicated by changes in trap lures over this period, as unmated females were replaced by a combination lure consisting of the synthetic pheromone and phenyl propionate, which is needed because mating disruption suppresses pheromone lure trap capture. There were two additional complications: the increased degree day accumulation during the growing season and the three-fold hectarage expansion of pistachio. A biofix at 944.4 degree days °C from the beginning of the year was identified from the dataset, which was consistent across all years in both counties. Using the biofix, subsequent flight peaks occurred at 277.78 degree day °C intervals (generation time on new crop pistachios), corresponding to three weeks in the field. This biofix can be used to improve the timing of field scouting, which in turn will improve the timing of insecticide application. Full article

In many species of animals, males aggregate in particular locations and produce calls to attract searching females for reproduction. One striking feature of such choruses is synchronization. On a scale of hours, choruses are often concentrated at particular times of day, such as dawn or dusk. On a scale of seconds, males may also synchronize the rhythm of their calls with one another. While synchronized calling at this scale suggests benefits acting at the collective level, competitive interactions between males to attract females can also lead to synchronized calling as an epiphenomenon. Why males in some species synchronize the rhythm of their calls is still debated, and more work is needed to understand the evolution of this behavior. I investigated chorus organization in the Emerald cicada (Zammara smaragdula), a Neotropical forest cicada in southern Belize, to explore these issues. Choruses in this species occurred at dawn and dusk and, occasionally, during daytime. There was no evidence for synchronization in the rhythm of calls among males, as bouts of collective calling occurred after quiet intervals of variable rather than fixed durations. The temporal aggregation of calls in this species thus probably emerged from competitive interactions among males to attract females. The degree of temporal overlap in the calls of males during a chorus varied as a function of chorus phase and time of day, suggesting flexibility in chorus organization, perhaps in relation to temporal variations in factors such as the number of calling cicadas, the number of predators present or ambient temperature during a chorus. Full article

The four-dimensional ellipsoid of an anisotropic hyper-structure corresponds to the four-dimensional sphere of an isotropic hyper-structure. In three dimensions, both theories for spherical and ellipsoidal harmonics have been developed by Laplace and Lamé, respectively. Nevertheless, in four dimensions, only the theory of hyper-spherical harmonics is hitherto known. This void in the literature is expected to be filled up by the present work. In fact, it is well known that the spectral decomposition of the Laplace equation in three-dimensional ellipsoidal geometry leads to the Lamé equation. This Lamé equation governs each one of the spectral functions corresponding to the three ellipsoidal coordinates, which, however, live in non-overlapping intervals. The analysis of the Lamé equation leads to four classes of Lamé functions, giving a total of 2n + 1 functions of degree n. In four dimensions, a much more elaborate procedure leads to similar results for the hyper-ellipsoidal structure. Actually, we demonstrate here that there are eight classes of the spectral hyper-Lamé equation and we provide a complete analysis for each one of them. The number of hyper-Lamé functions of degree n is (n + 1)²; that is, n² more functions than the three-dimensional case. However, the main difficulty in the four-dimensional analysis concerns the evaluation of the three separation constants appearing during the separation process. One of them can be extracted from the corresponding theory of the hyper-sphero-conal system, but the other two constants are obtained via a much more complicated procedure than the three-dimensional case. In fact, the solution process exhibits specific nonlinearities of polynomial type, itemized for every class and every degree. An example of this procedure is demonstrated in detail in order to make the process clear. Finally, the hyper-ellipsoidal harmonics are given as the product of four identical hyper-Lamé functions, each one defined in its own domain, which are explicitly calculated and tabulated for every degree less than five. Full article

Spatial and temporal uncertainties are found in data for many critical applications. This paper describes the use of interval-based representations of some spatial and temporal information. Uncertainties in the information can arise from multiple sources in which degrees of support and non-support occur in evaluations. This motivates the use of intuitionistic fuzzy sets to permit the use of the positive and negative memberships to capture these uncertainties. The interval representations will include both simple and complex or nested intervals. The relationships between intervals such as overlapping, containing, etc. are then developed for both the simple and complex intervals. Such relationships are required to support the aggregation approaches of the interval information. Both averaging and merging approaches to interval aggregation are then developed. Furthermore, potential techniques for the associated aggregation of the interval intuitionistic fuzzy memberships are provided. A motivating example of maritime depth data required for safe navigation is used to illustrate the approach. Finally, some potential future developments are discussed. Full article

This paper presents a numerical simulation of the steel grade transition from the ladle nozzle to the solidification end of the bloom. The simulation is based on models encompassing fluid flow, solidification, heat transfer, an electromagnetic field, and solute transport. To validate the accuracy of the steel grade transition model, transition blooms of high-carbon steel are sampled. Subsequently, the model is applied to investigating the steel grade transition between medium-carbon steel and low-carbon steel. The findings indicate that the regions exhibiting significant differences between their molten steel flow velocity and bloom casting speed in the strand model are primarily concentrated within 1 m below the meniscus. Additionally, the mushy zone in the strand model possesses a substantial volume. Solute elements continuously permeate the liquid phase from the solid phase through the mushy zone. Consequently, the distribution of solute elements in the transition bloom is primarily influenced by the molten steel flow in the tundish and macro-segregation in the casting process. The segregation degree of each solute element varies among grades with different carbon contents. In the austenite phase, the segregation degree of each element follows the order C > Si > Mo > Mn > Cr > Ni, while in the ferrite phase, the segregation degree is ordered as C > Si = Mn. Considering macro-segregation, the transition bloom partition model proves to be more stringent than the original partition method. This results in longer transition blooms when a significant difference exists between the new and old grades. For example, in Scheme 1, the original plan transition bloom length is 8.88 m, whereas the new plan transition bloom length is 10.88 m. Similarly, in Scheme 2, the original plan transition bloom length is 34.64 m, and the new plan transition bloom length is 35.16 m. Conversely, shorter partition intervals occur when there is an overlap in the composition of the new and old grades. In Scheme 3, the original plan partition interval for the new and old grades is 4.08 m, while the new plan partition interval is reduced to 0.94 m. Full article

Brain responses to discrete stimuli are modulated when multiple stimuli are presented in sequence. These alterations are especially pronounced when the time course of an evoked response overlaps with responses to subsequent stimuli, such as in a rapid serial visual presentation (RSVP) paradigm used to control a brain–computer interface (BCI). The present study explored whether the measurement or classification of select brain responses during RSVP would improve through application of an established technique for dealing with overlapping stimulus presentations, known as irregular or “jittered” stimulus onset interval (SOI). EEG data were collected from 24 healthy adult participants across multiple rounds of RSVP calibration and copy phrase tasks with varying degrees of SOI jitter. Analyses measured three separate brain signals sensitive to attention: N200, P300, and occipitoparietal alpha attenuation. Presentation jitter visibly reduced intrusion of the SSVEP, but in general, it did not positively or negatively affect attention effects, classification, or system performance. Though it remains unclear whether stimulus overlap is detrimental to BCI performance overall, the present study demonstrates that single-trial classification approaches may be resilient to rhythmic intrusions like SSVEP that appear in the averaged EEG. Full article

Salinity stress is one of the major abiotic stresses affecting crop growth and production. Rice is an important food crop in the world, but also a salt-sensitive crop, and the rice seedling stage is the most sensitive to salt stress, which directly affects the final yield formation. In this study, two RIL populations derived from the crosses of CD (salt-sensitive)/WD (salt-tolerant) and KY131 (salt-sensitive)/XBJZ (salt-tolerant) were used as experimental materials, and the score of salinity toxicity (SST), the relative shoot length (RSL), the relative shoot fresh weight (RSFW), and the relative shoot dry weight (RSDW) were used for evaluating the degree of tolerance under salt stress in different lines. The genetic linkage map containing 978 and 527 bin markers were constructed in two RIL populations. A total of 14 QTLs were detected on chromosomes 1, 2, 3, 4, 7, 9, 10, 11, and 12. Among them, qSST12-1, qSST12-2, and qRSL12 were co-localized in a 140-kb overlap interval on chromosome 12, which containing 16 candidate genes. Furthermore, transcriptome sequencing and qRT-PCR were analyzed in CD and WD under normal and 120 mM NaCl stress. LOC_Os12g29330, LOC_Os12g29350, LOC_Os12g29390, and LOC_Os12g29400 were significantly induced by salt stress in both CD and WD. Sequence analysis showed that LOC_Os12g29400 in the salt-sensitive parents CD and KY131 was consistent with the reference sequence (Nipponbare), whereas the salt-tolerant parents WD and XBJZ differed significantly from the reference sequence both in the promoter and exon regions. The salt-tolerant phenotype was identified by using two T₃ homozygous mutant plants of LOC_Os12g29400; the results showed that the score of salinity toxicity (SST) of the mutant plants (CR-3 and CR-5) was significantly lower than that of the wild type, and the seedling survival rate (SSR) was significantly higher than that of the wild type, which indicated that LOC_Os12g29400 could negatively regulate the salinity tolerance of rice at the seedling stage. The results lay a foundation for the analysis of the molecular mechanism of rice salinity tolerance and the cultivation of new rice varieties. Full article

Over the past century, there has been a dramatic increasing interest in the multi-criteria group decision-making (MCGDM) technique, with a considerable amount of studies published regarding it. One of the well-known approaches in the MCGDM paradigm is Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The integration of the TOPSIS method with fuzzy set theory has proven to be successful in various applications. Recently, a wide array of publications has proposed implementing a type-2 fuzzy set with TOPSIS. However, the additional degree of uncertainty represented by type 2 has largely been ignored, especially in a few specific mathematical operations in the model. We propose constructing interval type-2 fuzzy membership functions (IT2 MFs) using interval-based data gathered from a survey, where this is used to generate a new scale to represent ratings for each alternative. This procedure utilized all information gathered from decision makers. In addition, we present a complete algorithm for TOPSIS based on IT2 fuzzy sets (IT2 FSs) which preserve the interval-based form output. The output in the form of intervals offers decision makers (DMs) with more detailed information, enabling them to make more nuanced decisions. This can include cautious decisions when intervals are wider and overlapping. Although understanding the exact meaning of these intervals and their widths in a decision-making context is challenging, this paper introduces a systematic method for connecting input uncertainty to output uncertainty in the TOPSIS technique. This approach establishes a solid foundation for future research. Thus far, no other researchers have suggested a data-driven method that combines TOPSIS with fuzzification and provides intervals as the final output. Full article

Pipe conveyors provide sustainable solutions for environmentally sensitive or topographically complex powdered and bulk-solid handling processes; however, belt rotation is among the most critical failure modes of these equipment, influencing engineering, operational, and maintenance activities throughout the conveyors’ lifecycles. Position changes in the overlap are mechanical responses to uneven contact forces between the vulcanizing rubber belt and the idler rolls, owing to the highly nonlinear process of the belt folding from a trough to a tubular shape, and no method for quantifying the belt’s stability is currently available. In this study, we analyzed the failure mode of belt rotation and proposed a linearized model of an overlap stability index to evaluate the resilience of the overlap position through a case study of a short-flight curved pipe conveyor. Our proposal considers an interference model between the simulated torque of a curved flight in a pipe conveyor and the calculated torque of its equivalent straight flight by using kernel-smoothed density functions. It is adapted to incorporate adjustment factors for the filling degree based on simulations, the effect of the overlap in the forming force of the belt, the remaining useful life of the belt, and the coefficients of friction between the belt back cover and the idler rolls due to adhesion and hysteresis. An application was developed to calculate the belt’s rotational holding torque and rotary moment by processing real operational data, simulated contact forces, and the relevant equipment parameters. This analysis identified the reduced transverse bending stiffness and increased belt tension forces as the root causes for position changes with a loss of contact in the upper idler rolls of curved flights 10, 13, 15–16, and 17. The contributing factors included spots of augmented contact forces during the initial stages of the belt lifespan in curved flights 15–16, which presented unstable conditions due to increased opening forces, with an OSI of 0.8657. Furthermore, we proposed corrective and preventive action plans, an optimized replacement interval for the belt, and recommendations for design changes according to the relevant standards. Full article

Wi-Fi-based fingerprint indoor positioning technology has gained special attention, but the development of this technology has been full of challenges such as positioning time cost and positioning accuracy. Therefore, selecting reasonable Wireless Access Points (APs) for positioning is essential, as the more APs used for positioning, the higher the online computation, energy and time cost. Furthermore, the received signal strength (RSS) is easily affected by diverse interference (obstacles, multipath effects, etc.), decreasing the positioning accuracy. AP selection and positioning algorithms are proposed in this paper to solve these issues. The proposed AP selection algorithm fuses RSS distribution and interval overlap degree to select a small number of APs with high importance for positioning. The proposed positioning algorithm uses the location distance between reference points (RPs) to construct a circle and leverages extreme values (maximum and minimum values) of circles to determine the possibility that the test point (TP) appears in each circle, then it finds useful APs to determine the weight of RPs. Extensive experiments are conducted in two different areas, and the results show the effectiveness of the proposed algorithm. Full article

Home range overlap/segregation has several important applications to wildlife conservation and management. In this work, we first address the issue of measuring the degree of overlap/segregation among an arbitrarily large number (i.e., n ≥ 2) of probabilistic animal home ranges (i.e., utilization distributions). This subject matter has recently been solved for home ranges measured as polygons (e.g., percent minimum convex polygons and multinuclear cores) but not yet for probabilistic ones. Accordingly, we introduce a novel index named the PGOI (probabilistic general overlap index), and its complement, the PGSI (probabilistic general segregation index), an index for computation of probabilistic home range overlap/segregation at individual, population and species levels. Whatever the number of probabilistic home ranges, the PGOI returns a single score ranging in the [0, 100] interval. We applied the PGOI to five lesser kestrels (Falco naumanni) at Santeramo in Colle (Apulia region; Southern Italy) as a case study. Our new index can be applied to any animal species and to home ranges derived from any type of probabilistic home range estimator. Full article

Identifying regional variations and agronomical records can turn into a function of magnitude and timing for sustainable maize production. The crop characteristics are directly related with the temperature and precipitation from the growing season. Therefore, the main aim of this study was to highlight maize crop requirements from the most suggestive records from Romania. A literature search was performed based on keywords related to both maize crop and agrometeorological requirements. After the evaluation of the temperature requirements on maize phenology’s principal stages, some inconsistencies were identified. These are related to the leaf development stage and the development of the fruit stage, where the minimum temperature interval overlaps with the optimum. A wide variety of assessments were also made, taking into account mainly the monthly temperature and precipitation requirements. The number of principal growth stages assessed differed greatly from one source to another. The growth degree days has been incoherently expressed and calculated, and these details must be taken into account for developing further models. The results regarding phenology aim to propose the setting up of comparable records at a regional (PannEx area) and global scale. This review will help to develop new climate projections in Romania in the climate change context through the project Agroclim. Full article