Segmental Pattern Research Articles

Estimating the Size and Composition of Customer Base Using Retail Transaction Data

ABSTRACTThe knowledge of the number of customers is the pillar of retail business analytics. In our setting, we assume that a portion of customers is monitored and easily counted due to the loyalty program while the rest is not monitored. The behavior of customers in both groups may significantly differ making the estimation of the number of unmonitored customers a nontrivial task. We identify shopping patterns of several customer segments which allows us to estimate the distribution of customers without the loyalty card using the maximum likelihood method. In a simulation study, we find that the proposed approach is quite precise even when the data sample is very small and its assumptions are violated to a certain degree. When a major violation is suspected, we suggest an interval approach. In an empirical study of a drugstore chain, we validate and illustrate the proposed approach in practice. The actual number of customers estimated by the proposed method is much higher than the number suggested by the naive estimate assuming the constant customer distribution. The proposed method can also be utilized to determine penetration of the loyalty program in the individual customer segments.

Redescription of Acartia (Acanthacartia) italica Steuer, 1910 (Copepoda, Calanoida), and description of the developmental stages from the small saline Lake Rogoznica, Adriatic Sea.

In Lake Rogoznica, a small saline and eutrophic lake on the coast of the Adriatic Sea, the copepod Acartia (Acanthacartia) italica Steuer, 1910 is common, occasionally as an extremely dense population. This phenomenon provided an opportunity for a redescription of the adults and for description of the developmental stages. The segmentation and setation patterns of the antennules, antennae and mandibles of A. italica are analysed in detail through the naupliar and copepodid phases and the other limbs are analysed through the copepodid phase. In addition, wider comparisons are made with available data for other species of the subgenus Acanthacartia Steuer, 1915.

Analysis of circularity metrology of small cylindrical workpiece with a segmenting scan method

Owing to eccentricity and inclination, circularity of a cylindrical workpiece cannot be measured precisely by a circularity measuring machine when the workpiece has a small dimension (diameter ≤ 3 mm). In this paper, with the aim of solving this problem, circularity metrology of a small cylindrical workpiece using a segmenting scanning method is analyzed. The cross-sectional circle of the cylinder is segmented into several equivalent arcs for measurement by a two-dimensional coordinate measuring machine (profilometer). The circularity contour is obtained by stitching together arc contours obtained by data processing of the coordinates. Different segmenting patterns for coordinate scanning are considered. Measurement results are presented for three segmentation patterns, with 8, 10, and 12 equal segments, respectively. These results are evaluated in terms of the matching coefficient between neighboring arc contours on circumferential stitching, the Euclidean distance between neighboring arc contours on radial stitching, and the curvature of the arcs. From these evaluations, it is found that as the number of segments is increased, the matching coefficient increases from 0.14 to 0.50, the Euclidean distance decreases from 32 nm to 26 nm, and the curvature becomes close to the standard value.

Driving Segment Embedding and Patterns Dictionary Generation from Real-World Data Using Self-Supervised Learning

Driving Segment Embedding and Patterns Dictionary Generation from Real-World Data Using Self-Supervised Learning

PS‐InSAR post‐processing for assessing the spatio‐temporal differential kinematics of complex landslide systems: A case study of DeBeque Canyon Landslide (Colorado, USA)

AbstractThe complex superimposition of different kinematics and nested sectors within landslide systems amplifies the challenge of interpreting their heterogeneous displacement pattern and targeting effective mitigation solutions. As an example of such peculiar spatio‐temporal behaviour, the DeBeque Canyon Landslide (Colorado, USA) is emblematic of the application of interferometric post‐processing analysis for a detailed, remotely‐based investigation. We employed a multi‐geometry Persistent Scatterers (PS) InSAR dataset to provide continuous information on the spatio‐temporal scale and achieve a solid representation of the segmented kinematics and timings. Using an updated geomorphological map of the landslide system, we performed a two‐dimensional decomposition of the Persistent Scatterers (PS) dataset to determine the displacement orientation and inclination for each internal sector of the landslide system. We then conducted statistical analyses on the displacement vector characteristics and time series data. These analyses enabled us to spatially characterize the segmented activity patterns of the landslide system and identify abrupt changes in trends associated with preparatory and triggering factors. A clear differentiation of the rotational or translational kinematics within the landslide system was accomplished solely using surface displacement measures. Moreover, the application of a Bayesian model on the bi‐dimensional vector time series leads to the identification of significant differences in the deformational behaviour of each sector with respect to precipitation and temperature factors. Our approach represents a replicable method for local‐scale characterization and monitoring of landslides exhibiting complex spatio‐temporal displacement patterns and providing an effective, low‐cost solution for transportation agencies from a risk‐reduction perspective.

Preoperative evaluation of the segmental artery of left upper lobe by thin-section CT and 3d-CTA.

Understanding pulmonary artery (PA) branches and their variations is crucial for successful lung resection. We aimed to evaluate the segmental PA branching pattern of the left upper lobe (LUL) using thin-section computed tomography (TSCT) images and 3D-CT angiography (3D-CTA). This study included 108 patients who underwent CTA and left upper lobectomy. The segmental PA branching pattern of the LUL was meticulously identified by two thoracic radiologists using 3D-CTA and TSCT images. The lingular artery branches from the left PA (LPA) were classified into mediastinal type (pars mediastinalis: PM), interlobar type (pars interlobaris: PI), and PI originating from the lower portion (PI'), specifically from A8. The intraoperative findings of the PA branches of the LUL were compared with the preoperatively obtained 3D-CTA and TSCT images in each patient's case. The median (range) number of LPA branches of the LUL was 4.36 (3-8). The most common number of A1 + 2 branches was two, seen in 34 cases (31.5%). One or more branches of A1 + 2c directly originating from the LPA were found in 63 cases (58.3%). The number of branches of A3 was single in 85 cases and the most frequent (78.7%). Instances where one or more branches of A3a directly originated from the LPA were found in seven cases (6.5%). A1 + 2 and A3 origins were separate and independent in 40 cases (37.0%). As the branching pattern of the lingular artery, PI/PI' was most frequent (61.1%). PI´ was observed in 26 cases (24.1%). Inter-observer agreement for A1 + 2, A1 + 2c, A3, A3a, and lingular artery branching patterns was moderate to substantial (κ = 0.53-0.72). Preoperative 3D-CTA and TSCT images identified 99.8% of LPA branches compared to intraoperative findings, except one. The segmental PA branching pattern of the LUL can be evaluated using TSCT and 3D-CTA images, providing precise preoperative information.

Genotypes and phenotypes of capillary malformation-arteriovenous malformation: characterization and correlation analysis.

Capillary malformation-arteriovenous malformation (CM-AVM) is a rare genetic disorder characterized by multiple small capillary malformations (CMs) and arteriovenous malformations (AVMs), which has been linked with pathogenic variants in RASA1 and EPHB4. However, more data are needed to explore the phenotypic characteristics and the association between genotypes and clinical phenotypes. Our aim was to investigate the phenotypic and genetic characteristics of CM-AVM in East Asians, identify potential unique phenotypes, and conduct genotype-phenotype association analyses. This is a single-center study prospectively collecting CM-AVM patients' clinical data, with genetic data from blood or tissue samples. A total of 59 patients were enrolled. Thirty-two individuals had a leading CM greater than Schobinger stage II. The trigeminal nerve branches and greater auricular, transverse cervical, and lesser occipital nerves' somatosensory innervation zones divided head and neck CMs into six zones: V1, V2, V3, GA, TC, and LO zones. GA, TC, and LO zones had a positive correlation with one another but a negative correlation with V2 zone involvement. The RASA1 and EPHB4 pathogenic variants were detected in 41 out of 59, which showed two types of variant allele frequency (VAF) distributions. VAF above 30% made RASA1 pathogenic variants more susceptible to multifocal CMs than those below 30%. Leading CMs in the head and neck exhibit two segmentation patterns, anterior and lateral, which may differ in ear involvement and progression. Germline RASA1 pathogenic variants increased multifocal CM risk more than the somatic variants.

A Transtensional Fault Zone on the Northeastern Margin of the Tibetan Plateau: Millennial Earthquake Recurrence and High Earthquake Hazard

AbstractThe seismic gaps between ruptures of large earthquakes in tectonically active deformation zones are usually considered to be dangerous areas for future earthquakes. The Western Tianzhu Basin fault (WTBF) with an oblique normal motion is located in the middle of the Tianzhu seismic gap between the M 8.5 Haiyuan and M 8.0 Gulang earthquakes, NE Tibetan Plateau. The faulting activity of the WTBF is key to understanding the seismic hazards of the seismic gap, but it remains poorly constrained. Using satellite images, field investigations, paleoseismic trenching, and radiocarbon dating, we found that the WTBF produced seven paleoearthquakes since ∼8,000 cal. yr BP, with the latest event occurring at 1,005 ± 584 cal. yr BP, yielding an average recurrence interval of 1,102 ± 100 yr and a coefficient of variation of 0.38, indicating that it features a millennial quasi‐periodic recurrence. Based on the comparative analysis of geometry, kinematics, and tectonic activity, we suggest that the Tianzhu seismic gap can be divided into three sections and is characterized by a segmented rupture pattern. Among them, the WTBF and Jinqianghe fault exhibit similar geometry and kinematics and together form the ∼55 km‐long Jinqianghe‐Tianzhu transtensional fault zone (JTTFZ) that is capable of producing earthquakes of Mw 7.2. Given the long elapsed time since the latest event and strong seismogenic potential, it is believed that the JTTFZ poses a high seismic hazard. Our results enhance the understanding of the high seismic hazard in seismic gaps and provide new insights into the seismic rupture behavior in the NE Tibetan Plateau.

Translation Consistent Semi-supervised Segmentation for 3D Medical Images.

3D medical image segmentation methods have been successful, but their dependence on large amounts of voxel-level annotated data is a disadvantage that needs to be addressed given the high cost to obtain such annotation. Semi-supervised learning (SSL) solves this issue by training models with a large unlabelled and a small labelled dataset. The most successful SSL approaches are based on consistency learning that minimises the distance between model responses obtained from perturbed views of the unlabelled data. These perturbations usually keep the spatial input context between views fairly consistent, which may cause the model to learn segmentation patterns from the spatial input contexts instead of the foreground objects. In this paper, we introduce the Translation Consistent Co-training (TraCoCo) which is a consistency learning SSL method that perturbs the input data views by varying their spatial input context, allowing the model to learn segmentation patterns from foreground objects. Furthermore, we propose a new Confident Regional Cross entropy (CRC) loss, which improves training convergence and keeps the robustness to co-training pseudo-labelling mistakes. Our method yields state-of-the-art (SOTA) results for several 3D data benchmarks, such as the Left Atrium (LA), Pancreas-CT (Pancreas), and Brain Tumor Segmentation (BraTS19). Our method also attains best results on a 2D-slice benchmark, namely the Automated Cardiac Diagnosis Challenge (ACDC), further demonstrating its effectiveness. Our code, training logs and checkpoints are available at https://github.com/yyliu01/ TraCoCo.

Utility of Cardiac Magnetic Resonance in Assessing Arrhythmic Risk in Patients With Nonischemic Cardiomyopathy Undergoing Biventricular Pacing.

Nonischemic cardiomyopathy (NICM) is responsible for approximately one-third of heart failure and is associated with significant morbidity and mortality. Recent data suggested the lack of mortality reduction from adding a defibrillator to cardiac resynchronization therapy (CRT) in all patients with NICM. Myocardial fibrosis detected by cardiac magnetic resonance late gadolinium enhancement (CMR-LGE) can help risk stratify patients who would benefit from adding a defibrillator to CRT in this patient population. We aim to assess the relationship between the presence of myocardial fibrosis detected by CMR-LGE and the rate of major arrhythmic events (MAE) that included sustained ventricular tachycardia (VT), appropriate cardiac resynchronization therapy-defibrillator (CRT-D) intervention, ventricular fibrillation (VF), and sudden cardiac death (SCD) in patients with NICM undergoing CRT and to compare all-cause mortality and heart failure improvement between patients receiving cardiac resynchronization therapy-pacing (CRT-P) versus those receiving CRT-D based on the presence of myocardial fibrosis. All consecutive patients with NICM satisfying a guideline-directed indication for CRT implantation were included in the study after excluding patients who refused to consent, patients with acute decompensated heart failure, and those contraindicated for a cardiac magnetic resonance (CMR). Patients were divided into two groups based on the presence of fibrosis in cardiac MRI: the LGE/CRT-D group and the No LGE/CRT-P group. They were then followed for 1 year. Sixty patients were enrolled. Sixteen patients (26.6%) developed MAE during the study duration, among those patients, seven had myocardial fibrosis (receiving CRT-D as per protocol), while nine had no myocardial fibrosis (receiving CRT-P as per protocol), (41.2%vs. 20.9%, p = 0.045). The presence of CMR-LGE, regardless of the extent and distribution, predicted MAE with an odds ratio of 2.6 (CI = 1.78-8.9, p = 0.04). The presence of ≥7.5% of myocardial fibrosis by CMR was associated with 54% sensitivity and 100% specificity for MAE in the study population. All-cause mortality was significantly higher in the No LGE/CRT-P group versus the LGE/CRT-D group (15 [34.9%] vs. 2 [11.8%], p = 0.076). In patients with NICM candidates for biventricular pacing, the presence of LGE on CMR, irrespective of the extent or segmental pattern, is independently associated with an MAE and is associated with worse heart failure outcomes. However, the absence of LGE did not rule out MAE, and implanting CRT-P based on lack of fibrosis may result in higher all-cause mortality.

The Use of Nitinol Staples as Reduction Aids in Fixation of Forearm Diaphyseal Fractures: Surgical Technique and Case Series.

Forearm diaphyseal fractures are common orthopedic injuries that typically require surgical intervention using various implants and approaches. Maintaining reduction while simultaneously achieving compression in radial and/or ulnar shaft fractures during compression plate application can be challenging, particularly with unstable segmental and/or transverse fracture patterns. Nitinol compression staples have become increasingly used as a reduction aid because of their ability to provide continuous compression between the staple legs at the fracture site, low profile, and ease of application. These staples have the potential to be an effective means of maintaining reduction and applying compression before definitive plate fixation for radial and ulnar shaft fractures. We present our surgical technique and an associated patient series detailing our institution's experience, highlighting favorable outcomes and potential considerations when using nitinol compression staples for forearm fracture management.

Experimental results using large area picosecond photo-detectors

We present experimental results obtained with the LAPPD Gen-II large-size MCP-PMT. Using a custom-designed PCB capacitively coupled to the anode backplane with different segmentation patterns, the photo-detector is read out using the PETsys TOFPET2 and FastIC ASICs. The results reported in this paper include characterization using focused laser light and temporal response to picosecond illumination at a single photon level.

Linear and whorled nevoid hypermelanosis: A report of two unusual cases of pigmentary mosaicism

Linear and whorled nevoid hypermelanosis (LWNH) is a rare pigmentary disorder presenting with brownish macules in a streaky configuration along the lines of Blaschko. A 5-year-old and a 6-year-old girl presented with multiple linear streaks of hyperpigmentation following the lines of Blaschko over the left half of their bodies for 2 years. The 5-year-old girl child also had several depigmented patches on her right arm and side of her back that were arranged in a segmental pattern. Dermoscopy of the depigmented patches showed a diffuse white color with leukotrichia, whereas hyperpigmented patches showed brownish curved lines, dots, and clods with focally dispersed whitish globules and lines. Here, we report one case of LWNH associated with segmental vitiligo and two girls with late-onset LWNH.

Programming gel automata shapes using DNA instructions

The ability to transform matter between numerous physical states or shapes without wires or external devices is a major challenge for robotics and materials design. Organisms can transform their shapes using biomolecules carrying specific information and localize at sites where transitions occur. Here, we introduce gel automata, which likewise can transform between a large number of prescribed shapes in response to a combinatorial library of biomolecular instructions. Gel automata are centimeter-scale materials consisting of multiple micro-segments. A library of DNA activator sequences can each reversibly grow or shrink different micro-segments by polymerizing or depolymerizing within them. We develop DNA activator designs that maximize the extent of growth and shrinking, and a photolithography process for precisely fabricating gel automata with elaborate segmentation patterns. Guided by simulations of shape change and neural networks that evaluate gel automata designs, we create gel automata that reversibly transform between multiple, wholly distinct shapes: four different letters and every even or every odd numeral. The sequential and repeated metamorphosis of gel automata demonstrates how soft materials and robots can be digitally programmed and reprogrammed with information-bearing chemical signals.

Rupture segmentation on the East Anatolian fault (Turkey) controlled by along-strike variations in long-term slip rates in a structurally complex fault system

Abstract The East Anatolian fault in Turkey exhibits along-strike rupture segmentation, typically resulting in earthquakes with moment magnitude (Mw) up to 7.5 that are confined to individual segments. However, on 6 February 2023, a catastrophic Mw 7.8 earthquake struck near Kahramanmaraş (southeastern Turkey), defying previous expectations by rupturing multiple segments spanning over 300 km and overcoming multiple geometric complexities. We explore the mechanics of successive single- and multi-segment ruptures using numerical models of the seismic cycle calibrated to historical earthquake records and geodetic observations of the 2023 doublet. Our model successfully reproduces the observed historical rupture segmentation and the rare occurrence of multi-segment earthquakes. The segmentation pattern is influenced by variations in long-term slip rate along strike across the kinematically complex fault network between the Arabian and Anatolian plates. Our physics-based seismic cycle simulations shed light on the long-term variability of earthquake size that shapes seismic hazards.

Segmentation and spending patterns in the Saudi Arabian coffee market

Segmentation and spending patterns in the Saudi Arabian coffee market

A Study on the Pattern of Arterial Segmentation in the Human Spleen

Abstract Background: Partial splenectomy is preferred after splenic injuries, which will help to preserve healthy splenic tissue, hence the immunity. During splenic surgery particularly in the resection of a segment of the spleen, ligation of branches of the splenic artery is necessary. A precise knowledge of the segmental arteries is prerequisite because the spleen is separated into avascular lobes and segments by splenic arterial branches. The aim of the present work was to study the pattern of arterial segmentation in the human spleen and variations of the splenic arterial pattern. Methodology: The present study was conducted on 31 spleens with intact splenic artery after getting the ethical clearance. Specimens were collected depending on the availability of cadaver or unclaimed autopsy body. Tracing from terminal branches, the segmental branches of the splenic artery were studied by piece-meal dissection. The terminal branches of the splenic artery and its segmental branches were cleaned and observed. The number of the segmental branches of the spleen and the presence of arterial anastomosis between adjacent segmental arteries were noted. Results: The splenic artery terminated as bifurcation in 66.73% and trifurcation in 33.27%. We also found two, three, four, five, six, and seven arterial segments in 2 (6.46%), 14 (45.16%), 7 (22.58%), 3 (9.67%), 3 (9.67%), and 2 (6.46%) specimens, respectively. These segments are separated by an avascular plane in all specimens except one where we found intersegmental arterial anastomosis. Conclusions: Knowledge of the splenic arterial branching pattern of the present study may help the general surgeon as well as surgical gastroenterologist in performing the surgery of the spleen, particularly partial splenectomy after splenic injuries. This may also help anatomists in learning and teaching arterial segmentation of the spleen.

An Unusual Glomerulopathy with Subepithelial Deposits Having Microspherular Structures Following COVID-19 Vaccine

We report an unusual glomerulopathy with nephrotic syndrome and acute kidney injury almost two weeks after the second injection of SARS CoV-2 vaccine covishield, ChAdOx1-nCoV-19 in a 75-year-old healthy man. Kidney biopsy revealed segmental stage 1 membranous glomerulopathy and collapsing focal segmental glomerulosclerosis pattern with immune complexes on IF. Electron microscopy (EM) revealed aggregates of spherular microparticles along glomerular capillary walls. After starting him on steroids, his kidney functions gradually improved with significantly reduced proteinuria. Our patient seems to be the only reported SARS CoV-2 vaccine-induced early membranous nephropathy showing a collapsing focal segmental glomerulosclerosis pattern and immune complexes on IF with subepithelial deposits consisting of microspherular particles on EM.

A Comparative Analysis on the Histomorphometric Pattern of Various Segments of Adult Male Long Bones: Forensic Implication

Abstract Background: Human bone analysis is a useful tool in assessing and identifying skeletal remains. To make this easier, newer and modified approaches have often being documented. Aims and Objectives: The aim of this study is to analyze the histomorphometric features of various bone segments and its relevance in forensic case diagnosis. Materials and Methods: The human bones used were that of cadaveric bone samples harvested from three adult male Nigerians. The proximal, midshaft and distal segments of the femur, tibia, and humerus were utilized for the study. The bone sections were subjected to processing using Frost’s rapid manual preparation of ground sections techniques. Histomorphometric evaluation studied the number of primary osteons, secondary osteons, and osteon fragments, as well as the Haversian canal diameter (HCD). Results: The primary osteons, secondary osteons, osteon fragments, and HCD in each of the segments of the long bones show that the F values are less than the F critical for an alpha level of 0.05. This shows that there is no statistically significant (P > 0.05) variation in the histomorphometric pattern for the various segments of the bones studied. Again differences in the haversian canal diameter of the various segments of the long bones shows statistically significant variation (P< 0.05) among the long bones investigated. Conclusion: These findings have laid to rest the challenges with using the only available bone fragment for forensic case investigation as no notable variations exist across various segments.

On Entropic Learning from Noisy Time Series in the Small Data Regime.

In this work, we present a novel methodology for performing the supervised classification of time-ordered noisy data; we call this methodology Entropic Sparse Probabilistic Approximation with Markov regularization (eSPA-Markov). It is an extension of entropic learning methodologies, allowing the simultaneous learning of segmentation patterns, entropy-optimal feature space discretizations, and Bayesian classification rules. We prove the conditions for the existence and uniqueness of the learning problem solution and propose a one-shot numerical learning algorithm that-in the leading order-scales linearly in dimension. We show how this technique can be used for the computationally scalable identification of persistent (metastable) regime affiliations and regime switches from high-dimensional non-stationary and noisy time series, i.e., when the size of the data statistics is small compared to their dimensionality and when the noise variance is larger than the variance in the signal. We demonstrate its performance on a set of toy learning problems, comparing eSPA-Markov to state-of-the-art techniques, including deep learning and random forests. We show how this technique can be used for the analysis of noisy time series from DNA and RNA Nanopore sequencing.