Trigger Pattern Research Articles

Seismic stress perturbation and triggering patterns induced by the 2016 Central Italy earthquake sequences

Seismic stress perturbation and triggering patterns induced by the 2016 Central Italy earthquake sequences

DeHiB: Deep Hidden Backdoor Attack on Semi-supervised Learning via Adversarial Perturbation

The threat of data-poisoning backdoor attacks on learning algorithms typically comes from the labeled data. However, in deep semi-supervised learning (SSL), unknown threats mainly stem from the unlabeled data. In this paper, we propose a novel deep hidden backdoor (DeHiB) attack scheme for SSL-based systems. In contrast to the conventional attacking methods, the DeHiB can inject malicious unlabeled training data to the semi-supervised learner so as to enable the SSL model to output premeditated results. In particular, a robust adversarial perturbation generator regularized by a unified objective function is proposed to generate poisoned data. To alleviate the negative impact of the trigger patterns on model accuracy and improve the attack success rate, a novel contrastive data poisoning strategy is designed. Using the proposed data poisoning scheme, one can implant the backdoor into the SSL model using the raw data without hand-crafted labels. Extensive experiments based on CIFAR10 and CIFAR100 datasets demonstrated the effectiveness and crypticity of the proposed scheme.

An experimental and numerical analysis on influence of triggering for composite automotive crash boxes under compressive impact loads

In automobiles there is large scope for composite materials to be used for manufacture of structural parts. The development of electric vehicles has caused for a gain in utilization of composites in automotive applications. In the event of a collision composites afford for an electrical insulation aimed at safety in contradiction of electric shock along with higher strength to weight ratios, which helps in making light weight automobile structures. But composite materials have peculiar as well as complex deformation patterns under compressive impact loading, which is common in vehicle collisions. The deformation pattern of the composites depends on the type of materials used for reinforcement as well as matrix and their layout. Triggers which are accommodated in the design of an element so that deformation initiates at the specific region and has a high impact on the attribute with reference to energy absorption the component as they modify the deformation modes. Therefore before using composite materials for structural parts in automobiles, it is essential to characterize their behaviour when subjected to impacts. For the parts under compressive impact loadings the common method employed for studying the behavior under such conditions is Drop weight impact testing. In this study a GFRP (glass fiber reinforced plastic) composites crash boxes with four different cross sections (square, cylindrical, hexagonal and decagonal) provided with two different triggering patterns (slot trigger and front end trigger) are subjected to drop weight impact testing. In this study, influence of triggering on composite crash box is investigated using experimental drop weight testing along with correlation of numerical simulation. The prime motive of this study is to illustrate the influence of triggers on the deformation pattern along with the force and energy absorption level for a GFRP crash boxes under drop weight axial impacts.

The origami inspired design of polyhedral cells of truss core panel

Truss core panel (TCP), inspired by origami engineering, is a novel lightweight structure with periodical pyramid truss core cells in regular plane tilling patterns. Such panels are increasingly seen in a range of application form civil infrastructure to vehicle components, and show same bending stiffness and better aspects in shear strength and in-plane compressive load than honeycomb panel The geometric structure of TCP can be easily adjusted by changing the shape of the cell, which in hence influence the panel properties. However, in general, the geometry structure of truss core cells in TCP is triangular pyramid or rectangular pyramid. In this paper, a novel design method for polyhedral cells in TCP based on origami are developed, which comprise expanding and shrinking operation (design strategy 1), independent cutting and single cutting operation (design strategy 2), and combined operations (design strategy 3). By varying the geometric patterns of deployed polyhedral truss core cells (PTCCs), all possible patterns based on geometrical considerations are devised, systematically devising four types of PTCCs. These pattern variations are ruled by two design parameters, similarity ratio (w) and cutting ratio (k). In addition, the critical values of these two parameters for triggering pattern transformation and theoretical criteria for feasible transition among the four types of PTCCs was determined.

A Novel Single-Gate Driver Circuit for SiC+Si Hybrid Switch With Variable Triggering Pattern

Hybrid switches are attracting increasing attention recently, due to their high efficiency and low cost. Normally, two separated gate drivers and driving signals are needed for the hybrid switch, which leads to more cost and more control complexity. A novel gate driver circuit for SiC+Si hybrid switches is proposed using single driving signal and single-gate driver in this article. Two simple resistance-capacitance (RC) delay circuits are used for generating different time-delays required by two different triggering patterns to provide more flexibility. The detailed operation principles, mathematical analysis, and the guidance for the selection of key components of the proposed circuit are provided. The merits of the proposed driver are: first, simple structure; second, low control complexity; third, more flexibility; and fourth, low cost. A 2-kW Silicon Carbide (SiC)-MOSFET+Si-insulated gate bipolar transistor (IGBT) hybrid switch buck converter is built to validate the proposed gate driver circuit. The analysis and experimental results match very well, which shows the effectiveness and merits of the proposed method.

Patterns of triggers for on-task and off-task behaviors: university students in independent study

ABSTRACT With the rapid development of mobile devices and web-based technologies, it becomes common for students to switch between different tasks during study time. However, it remains unclear how the transition between on-task and off-task states happens and how digital devices affect the process. This study examines college students’ independent study in the library to delineate the pattern of on-task and off-task behavior, and identify the triggers for students’ engagement or disengagement. Through video recordings, the researchers captured the behaviors of over 266 students at the library. Observations were taken and used to double-check and confirm the behaviors. The study adopted the behavioral sequences method to scrutinize behavioral transition and explored gender differences. The results indicate that on-task behaviors tended to decline as the learning duration increased, whereas off-task behaviors tended to increase when students interacted with personal devices. As the most used device, smartphones posed persistent interference for learners, leading to reduced focus during independent study time. Moreover, male students were more likely to be influenced by external interruptions, whereas female students were more prone to the influence of internal interruptions. These findings can contribute to the development of research-based guidelines for improving students’ attention and self-adjusting during self-study time.

The Heterogeneous Landscape and Early Evolution of Pathogen-Associated CpG Dinucleotides in SARS-CoV-2.

COVID-19 can lead to acute respiratory syndrome, which can be due to dysregulated immune signaling. We analyze the distribution of CpG dinucleotides, a pathogen-associated molecular pattern, in the SARS-CoV-2 genome. We characterize CpG content by a CpG force that accounts for statistical constraints acting on the genome at the nucleotidic and amino acid levels. The CpG force, as the CpG content, is overall low compared with other pathogenic betacoronaviruses; however, it widely fluctuates along the genome, with a particularly low value, comparable with the circulating seasonal HKU1, in the spike coding region and a greater value, comparable with SARS and MERS, in the highly expressed nucleocapside coding region (N ORF), whose transcripts are relatively abundant in the cytoplasm of infected cells and present in the 3′UTRs of all subgenomic RNA. This dual nature of CpG content could confer to SARS-CoV-2 the ability to avoid triggering pattern recognition receptors upon entry, while eliciting a stronger response during replication. We then investigate the evolution of synonymous mutations since the outbreak of the COVID-19 pandemic, finding a signature of CpG loss in regions with a greater CpG force. Sequence motifs preceding the CpG-loss-associated loci in the N ORF match recently identified binding patterns of the zinc finger antiviral protein. Using a model of the viral gene evolution under human host pressure, we find that synonymous mutations seem driven in the SARS-CoV-2 genome, and particularly in the N ORF, by the viral codon bias, the transition–transversion bias, and the pressure to lower CpG content.

Dynamic triggering of earthquakes in the North Island of New Zealand following the 2016 Mw 7.8 Kaikōura earthquake

Large earthquakes are capable of triggering microseismicity, deep tremor and slow-slip events from intermediate- to long-distance ranges. Unfortunately, earthquake catalogs are typically incomplete right after large mainshocks. Hence, mapping triggering patterns and understanding the underlying triggering mechanism are challenging. Here we present two different types of seismicity responses to dynamic stressing by passing seismic waves in the North Island of New Zealand following the 2016 Mw 7.8 Kaikōura earthquake. Based on a template matching technique, we identify up to 4-7 times more earthquakes than listed in New Zealand's GeoNet catalog. We also compute the dynamic stress perturbations in the North Island due to the Kaikōura mainshock and compare them to seismicity rate changes to identify regions with high susceptibility to dynamic stress triggering. Abundant triggered earthquakes occurred immediately following the mainshock in the shallow crust around the active Taupo Volcano Zone, likely related to activation of crustal faults/fluids associated with back-arc rifting and volcanism. Approximately 8 days after the initial dynamic stressing, an active burst of seismicity with the largest event of ML 5.55 occurred along the shallow megathrust near Porangahau on the east coast of the North Island. This burst of seismicity is likely driven by a ∼Mw 7.1 shallow slow slip event dynamically triggered by the mainshock. Our findings reveal the heterogeneous nature of dynamic triggering in a plate boundary region with recent large earthquake sequences and aseismic transient events and further highlight the difficulties in time-dependent earthquake forecasting following large mainshocks.

Deep Neural Backdoor in Semi-Supervised Learning: Threats and Countermeasures

Semi-Supervised Learning (SSL) is a powerful derivative for humans to discover the hidden knowledge, and will be a great substitute for data taggers. Although the availability of unlabeled data rises up a huge passion to SSL, the untrustness of unlabeled data leads to many unknown security risks. In this paper, we first identify an insidious backdoor threat of SSL where unlabeled training data are poisoned by backdoor methods migrated from supervised settings. Then, to further exploit this threat, a Deep Neural Backdoor (DeNeB) scheme is proposed, which requires less data poisoning budgets and produces stronger backdoor effectiveness. By poisoning a fraction of our unlabeled training data, the DeNeB achieves the illegal manipulation on the trained model without modifying the training process. Finally, an efficient detection-and-purification defense (DePuD) framework is proposed to thwart the proposed scheme. In DePuD, we construct a deep detector to locate trigger patterns in the unlabeled training data, and perform secured SSL training with purified unlabeled data where the detected trigger patterns are obfuscated. Extensive experiments based on benchmark datasets are performed to demonstrate the huge threatening of DeNeB and the effectiveness of DePuD. To the best of our knowledge, this is the first work to achieve the backdoor and its defense in semi-supervised learning.

Characteristics of Frequent Dynamic Triggering of Microearthquakes in Southern California

AbstractDynamic triggering of earthquakes has been reported at various fault systems. The triggered earthquakes are thought to be caused either directly by dynamic stress changes due to the passing seismic waves, or indirectly by other nonlinear processes that are initiated by the passing waves. Distinguishing these physical mechanisms is difficult because of the general lack of high‐resolution earthquake catalogs and robust means to quantitatively evaluate triggering responses, particularly, delayed responses. Here we use the high‐resolution Quake Template Matching catalog in Southern California to systematically evaluate teleseismic dynamic triggering patterns in the San Jacinto Fault Zone and the Salton Sea Geothermal Field from 2008 to 2017. We develop a new statistical approach to identify triggered cases, finding that approximately 1 out of every 5 globalMw ≥ 6 earthquakes dynamically trigger microearthquakes in Southern California. The triggering responses include both instantaneous and delayed triggering, showing a highly heterogeneous pattern and indicating possible evolving triggering thresholds. We do not observe a clear peak ground velocity triggering threshold that can differentiate triggering earthquakes from nontriggering events, but there are subtle differences in the frequency content of the ground motion that may differentiate the earthquakes. In contrast to the depth distribution of background seismicity, the identified triggered earthquakes tend to concentrate at the edges of the seismogenic zones. Although instantaneously triggered earthquakes are likely a result of dynamic Coulomb stress changes, the cases of delayed‐dynamic triggering are best explained by nonlinear triggering processes, including cyclic material fatigue, accelerated transient creep, and stochastic frictional heterogeneities.

Patterns of triggers, ideation and motivational factors of contraceptive utilization among women and gate-keepers in Nigeria: a scoping study on the resilient and accelerated scale up of DMPA-SC in Nigeria (RASUDIN)

BackgroundWomen have unfair share in the burden of unintended pregnancy outcome and unhealthy interpregnancy intervals. An understanding of the triggers, ideation and motivational factors influencing utilization of modern contraceptives is relevant for efforts aimed at increasing utilization among the general public, specifically sexually active women. The objective of this study is to explore the triggers, ideation and motivational factors influencing the use of modern family planning methods including depot-medroxyprogesterone acetate subcutaneous (DMPA-SC).MethodsQualitative methods which include; Focus Group Discussions (FGDs) and In-depth Interviews (IDIs) were used to elicit information from women of reproductive age and gate-keepers in selected Nigerian states; Rivers, Ogun, Kwara, Niger, Anambra, Delta, Lagos, Enugu and Oyo. The categories of respondents include; unmarried women aged 18-25 years, women in union aged 18-24 years using modern family planning (FP), women in union aged 25-49 years using modern FP, women in union aged 26-49 years non-users of modern FP, community leaders, health facility focal person, husbands of current users of modern FP, husbands of non-users of modern FP, religious leaders, state FP coordinators and women aged 18-49 years who currently use DMPA-SC. Maximum variation sampling techniques was used to enlist participants to participate in both FGDs and IDIs.ResultsRespondents reported being motivated to use FP for reasons such as benefits of the method, economic situation, suitability of the methods, fear of unwanted pregnancy and its convenience. Further analysis showed that the unmarried respondents discussed more about fear of unwanted pregnancy and accessibility and affordability as a key motivator; while women in union discussed more on economic situations, encouragement from partners and benefits of FP when compared with the unmarried. In addition, respondents reported that their partners, health workers and friends influenced their decisions to use FP. Partners’ encouragement, personal experience, accessibility and availability, awareness of FP and its benefits; willingness to space children and costs were notable enablers of FP use. The triggers for FP use were; appointment cards, phone calls from health workers, reminders (text messages, phone alarms and partners’ support).ConclusionIncreasing utilization therefore requires a well-planned horizontal approach that considers all enabling factors influencing utilization including women’s empowerment. Family planning programmes that are client centered, address socio-cultural and gender norms and ensure access to contraceptive mix methods are recommended to improve utilization rate. This study recommends improved care-seeking behaviour through community-based awareness creation to address myths and misconceptions of family planning use, establishment of contraceptive delivery teams to prevent challenges of availability and accessibility, value clarification and tasks shifting among others to deal with the issue of inadequate family planning utilization.

Triggers in Patients with Atypical Hemolytic Uremic Syndrome: An Observational Cohort Study Using a US Claims Database

Introduction Atypical hemolytic uremic syndrome (aHUS) is a rare systemic thrombotic microangiopathy (TMA) characterized by hemolytic anemia, thrombocytopenia and end organ damage, predominately in the kidneys. Disease emergence is often unpredictable, occurring with or without an identified trigger or in the presence of a concomitant clinical condition. The persistence of TMA and long-term disease manifestations are also not well described. The aims of this study were to characterize the frequency and distribution of potential triggering conditions preceding a diagnosis of aHUS, and to describe the persistence of TMA and long-term disease manifestations in those not treated with eculizumab. Methods This retrospective study included two cohorts of patients with aHUS identified in the Optum® Clinformatics® Data Mart commercial and the Medicare Advantage claims databases, encompassing approximately 62 million patients, from January 2007 to March 2019. As aHUS does not have a dedicated diagnosis code, patients with aHUS were defined as having ≥ 2 HUS or TMA diagnostic codes, and ≥ 1 claim for each of the following aHUS-associated clinical manifestations: hemolytic anemia, thrombocytopenia, and renal/neurological/gastrointestinal organ involvement. Patients with paroxysmal nocturnal hemoglobinuria, myasthenia gravis or Shiga toxin-producing E. coli diagnoses were excluded. Additionally, patients were required to have ≥ 1 lactate dehydrogenase, reticulocyte, schistocyte, haptoglobin or blood smear test within 3 months of any HUS or TMA diagnosis, or ≥ 1 ADAMTS13 test with results demonstrating activity of ≥ 5%. Eculizumab, a C5 inhibitor, was the only approved therapy during this time period. Two cohorts were analyzed. Cohort 1: eligible patients with aHUS were required to have ≥ 12 months continuous database enrollment prior to and ≥ 18 months after the date of first HUS or TMA diagnostic code, and may or may not have been receiving eculizumab. Clinical disease manifestations were evaluated up to 15 months after the date of first aHUS diagnosis. Cohort 2: patients with aHUS and persistent TMA (≥ 1 International Classification of Diseases code for TMA and one diagnosis of thrombocytopenia within 12 months following the first TMA diagnosis) were identified. Eligible patients were required to have 3 months enrollment prior to and 12 months after the date of first TMA diagnosis. Those receiving eculizumab were excluded. Claims data relating to prespecified potential triggers of aHUS were identified during the 0-3-month period prior to the first diagnosis of HUS or TMA. Data were summarized using descriptive statistics. Results Cohort 1: a total of 431 patients with aHUS were identified (mean age of 58 years, 55% female). Prespecified triggers for the development of aHUS were identified in 147 patients (34%), with infections representing the most common trigger (reported by 92 patients [63%]), followed by chemotherapy (28 patients [19%]) and systemic lupus erythematosus (26 patients [18%]), as shown in the Table. Among patients not receiving eculizumab (n = 415), disease manifestations persisted for > 1 year following the first diagnosis date of aHUS, with 298 patients (72%) reporting clinical disease manifestations 13-15 months after diagnosis. Kidney disease represented the most common manifestation (90 patients [30%] with chronic kidney disease and 26 patients [9%] with end-stage renal disease), followed by thrombocytopenia (87 patients [29%]) and hemolytic anemia (82 patients [28%]). Cohort 2: among those with aHUS and persistent TMA (n = 218; 69.3% of patients aged 35-74 years, 67% female), a total of 191 patients had data available for analysis. Of these, 95 patients (50%) reported prespecified triggers, with a similar trigger pattern observed as in the patients with aHUS in Cohort 1. Conclusions Triggers of aHUS were identified in 34% of patients with aHUS and 50% of those with aHUS and persistent TMA. In those with aHUS alone not receiving eculizumab, long-term clinical disease manifestations persisted in the majority of patients. Further evidence on treating trigger-associated aHUS with complement inhibition is required. Disclosures Tomazos: Alexion Pharmaceuticals Inc.: Current Employment. Garlo:Alexion Pharmaceuticals Inc.: Current Employment. Wang:Alexion Pharmaceuticals Inc.: Current Employment. Chen:Alexion Pharmaceuticals Inc.: Current Employment. Laurence:Alexion Pharmaceuticals: Honoraria, Research Funding.

Drop-weight impact testing for the study of energy absorption in automobile crash boxes made of composite material

There is an ever-increasing demand in the automotive sector to continuously improve the performance and reduce cost through weight reduction in the structure of the vehicle. In the present scenario, it is also necessary to meet the standards set by crash safety regulating authorities in various parts of the world. In automobiles, the crash box is placed in the anterior region to absorb the impact energy in the event of an accident. Glass fiber reinforced plastic crash boxes have a high strength-to-weight ratio and also are good in energy absorption, particularly useful in this scenario. In this paper, the effectiveness of different triggers in combination with various geometries is investigated for Glass fiber reinforced plastic crash boxes using drop-weight impact testing. A trigger is a geometric irregularity introduced in the crash box design to alter the energy as well as force levels by modifying the deformation mode under loading. Comparison of change in force level, absorption of impact energy, specific energy absorption values was performed for composite crash boxes made of various types of cross-sectional geometries along with multiple patterns of triggers. Force versus displacement (F–D) curves are drawn for all the cases of the glass fiber reinforced plastic crash boxes to understand the behavior of each combination formed with various types of geometries and triggers, under impact loading. Strength-to-weight ratio was considered as the deciding factor for the comparisons to know the best and worst cases of the crash boxes made of different cross-sections along with various trigger types. This study provides detailed insights into the drop-weight impact testing procedure including the preparation of specimens, setting up the drop-weight impact test, preparation of specimen clamps, safety precautions involved, data acquisition from the test and its processing.

Understanding What People With Migraine Consider to be Important Features of Migraine Tracking: An Analysis of the Utilization of Smartphone-Based Migraine Tracking With a Free-Text Feature.

Headache mobile health (mHealth) applications (apps) have gained popularity in use but there is little research into what people with migraine find important to track. This information is important for helping with adherence and determining meaningful data to patients. We conducted several clinical trials using a headache research app (RELAXaHEAD). The app contains a "notes" feature (a free-text input section) where patients could record notes related to their headache. To identify what patients view as important when tracking migraine/headaches within a headache tracking mHealth app. This was a retrospective study where smartphone diary notes inputted by people with migraine were qualitatively analyzed; notes were extracted, a preliminary codebook was developed and used to code each note. Using grounded theory, themes and subthemes emerged. About 288 subjects in the trials used the notes function. There were 5364 total notes with an average of 18.6±39.2 notes/user. The qualitative analysis yielded 759 unique codes and the emergence of 4 major themes. The first theme was "Utility in free-text tracking of headache characteristics, medications, and sleep" which emerged as a space for users to elaborate on data that could have been inputted into other sections of the app. The second theme was "Monitoring coexisting conditions both related to and distinct from headache." The third theme was "Personal records of behavioral therapy adherence," which included a range of concepts from behavioral therapy session frequency/adherence to subjects' thoughts or emotions regarding the behavioral therapy. The fourth theme was "Migraine trigger, prevention, and relief patterns deciphered through consistent data tracking." We found that the majority of patients choose to expand on information beyond what can be inputted into specific icons in a headache app. Moreover, they want to be able to monitor not only headache-related symptoms but symptoms they experience from other conditions. In addition to tracking their pharmacologic treatment, they may choose to track their nonpharmacologic, that is, behavioral therapy use, and they also use a smartphone diary app to assess what triggers versus relieves a migraine. While the RELAXaHEAD app was designed with features to extract data that would be useful to physicians and patients in treating migraine, our study results indicated that users also prefer a range of tracking capabilities that may or may not be useful to physicians but may be important for headache smartphone user engagement.

Unsupervised Classification of Atrial Fibrillation Triggers Using Heart Rate Variability Features Extracted from Implantable Cardiac Monitor Data.

Catheter ablation is a common treatment of atrial fibrillation (AF), but its success rate is around 60%. It is believed that the success rate can be improved if the procedure were to be guided by the specific AF triggers found in the "Flashback", i.e. the trend of around 500 ventricular beats preceding the AF onset stored in an implantable cardiac monitor (ICM). The need to automatically classify these different triggers: atrial tachycardia (AT), atrial flutter, premature atrial contractions (PAC) or Spontaneous AF has motivated the design in this paper of an unsupervised classification method evaluating statistical and geometrical Heart Rate Variability (HRV) features extracted from the Flashback. From a cohort of 132 patients (57± 12 years, male 67%), 528 Flashbacks were extracted and classified into 5 different clusters after the Principal Component Analysis (PCA) was computed on the HRV features. 2 principal components explained more than 95% of the variance and were a combination of the mean R-R interval, Square root of the mean squared differences of successive R-R intervals (RMSSD), Standard deviation of the R-R intervals (SDNN) and Poincare descriptors, SD1 and SD2. RMSSD and SD1 were significantly different among all clusters (p-value < 0.05, with Holm's correction) showing that distinct patterns can be found using this method.Clinical Relevance-Preliminary step towards ablation strategy guidance using the AF trigger patterns to improve catheter ablation success rates.

Association of itch triggers with atopic dermatitis severity and course in adults

BackgroundAtopic dermatitis (AD) is associated with heterogeneous triggers of itch, which may affect AD course and severity. ObjectiveTo characterize the triggers of itch in adult AD. MethodsThis was a prospective dermatology practice–based study using questionnaires and evaluation by a dermatologist (n = 587). Thirteen itch triggers were assessed using the patient-reported outcomes measurement information system Itch-Triggers. ResultsOverall, 381 (64.9%) patients reported greater than or equal to 1 itch trigger in the past week and 212 (36.1%) reported greater than or equal to 3 itch triggers. The most commonly reported triggers were stress (35.4%), sweat (30.5%), weather change (24.7%), dry air (24.4%), and heat (24.0%). In multivariable Poisson regression models, the number of itch triggers was associated with more severe patient-reported global AD severity, Numeric Rating Scale worst itch, Patient-Oriented Eczema Measure, Scoring Atopic Dermatitis sleep, Numeric Rating Scale skin pain, Eczema Area and Severity Index, and objective Scoring Atopic Dermatitis. The seasonality of AD was associated with distinct itch triggers. In multivariable logistic regression models, the number of itch triggers was associated with less than or equal to 3 months of AD remission during the year, greater than or equal to 2 AD flares, and AD being worse during some seasons. Four patterns of itch triggers were identified using latent class analysis, each associated with different clinical characteristics. ConclusionItch triggers are common and affect the course of AD. Itch triggers are an important end point to assess in patients with AD.

High Energy Background Event Identification Using Local Group Trigger in a 240-pixel X-ray TES Array

A novel triggering function developed for 240-pixel Transition-Edge Sensors is demonstrated under the high rate of particle background. The function is integrated into the standard data acquisition system in the NIST TES framework. It enables any type of combination of trigger pattern when a pixel is triggered, which is called “group trigger.” As a practical implementation, the primary trigger is distributed to the four physically nearest pixels. The group trigger function was utilized throughout the entire one-month J-PARC experiment for the measurement of the Kaonic-atom X-rays. This trigger allowed us to confirm that the increased background and degraded energy resolution we observed when operating the TES array in the presence of an ion beam are the result of thermal crosstalk from charged particles. We show that the maximum of the average of the signals among the neighboring four pixels is useful for event selection. We use cuts based on this parameter to improve the peak-to-background level in a measured x-ray energy spectrum by a factor of $$\sim$$ 2, while keeping 95% of measured events. This flexible group triggering technique allows us to improve the signal to noise on the very faint Kaonic Helium x-ray lines we are measuring, better understand our experiment environment, and we believe this technique may prove useful in other ground and space-based TES applications.

Survival analysis of failures based on Hawkes process with Weibull base intensity

In this paper, we construct a Hawkes process with time-varying base intensity to model the sequence of failure, i.e., failure events of the compressor station, and we combine survival analysis and point process model on various failure events of the compressor station based on Hawkes process. To our best knowledge, until now, nearly all relevant literature of the Hawkes point processes assumes that the base intensity of the conditional intensity function is time-invariant. This assumption is apparently too harsh to be verified. For example, in the practical application, including financial analysis, reliability analysis, survival analysis and social network analysis, the truth variation of the base intensity of the failure occurrence over time is not constant. The constant base intensity will not reflect the base intensity trend of the failure occurring over time. Thus, in order to solve this problem, in this paper, we propose a new time-varying base intensity, e.g. which is treated as obeying Weibull distribution. First, we introduce the base intensity into a Hawkes process that obeys the Weibull distribution, and then we propose an effective learning algorithm based on the maximum likelihood estimator. Experiments on the constant base intensity synthetic data, time-varying base intensity synthetic data, and real-world data show that our method can learn the triggering patterns of the Hawkes processes and the time-varying base intensity simultaneously and robustly. Experiments on real-world data also reveal the Granger causality of different types of failures and the base probability of failure varying over time. We put forward some suggestions for practical production based on the experimental results.

A survey of pattern mining in dynamic graphs

AbstractGraph data is found in numerous domains such as for the analysis of social networks, sensor networks, bioinformatics, industrial systems, and chemistry. Analyzing graphs to identify useful and interesting patterns is an important research area. It helps understanding graphs, and hence support decision making. Since two decades, many graph mining algorithms have been proposed to identify patterns such as frequent subgraphs, paths, cliques, and trees. But most of them assume that graphs are static. This simplifying assumption makes it easy to design algorithms but discard information about how graphs evolve. This article provides a detailed survey of techniques for mining interesting patterns in dynamic graphs, which can serve both as an introduction and as a guide to recent advances and opportunities in this research area. The main tasks related to mining patterns in dynamic graphs are reviewed such as discovering frequent subgraphs, evolution rules, motifs, subgraph sequences, recurrent and triggering patterns, and trend sequences. In addition, an overview of strategies and approaches to solve dynamic graph mining problems is presented, and their advantages and limitations are highlighted. Various extensions are also discussed such as to discover patterns in data streams and big data. Finally, the article mentions several research opportunities.This article is categorized under: Algorithmic Development &gt; Spatial and Temporal Data Mining Algorithmic Development &gt; Association Rules

PH-responsive poly(lactic acid)/sodium carboxymethyl cellulose film for enhanced delivery of curcumin in vitro

Curcumin is a nutraceutical having variety of pharmacological activities including chemopreventive and chemotherapeutic properties. However, it is poorly absorbed after oral administration due to the low solubility, rapid metabolism and pre-systemic metabolic degradation. In this study, poly(lactic acid)/sodium carboxymethyl cellulose/curcumin film prepared by solvent casting method is proposed to improve the curcumin (CUR) release in intestinal alkaline condition. Cellulose extracted from oil palm empty fruit brunch (OPEFB) is modified into sodium carboxymethyl cellulose (CMC) using etherification process. Prepared CMC is introduced to the film with the aim of enhancing the solubility of curcumin and imparting pH sensitivity to the film. Fourier transform infrared spectroscopy (FTIR) confirms the successful carbomethylation of cellulose. The solubility of curcumin increases from 24 ± 0.38 mg/L to 147 ± 5.66 mg/L with increasing the CMC content from 0.1% to 2% (w/v) in phosphate buffered saline (PBS) medium. The tensile strength of the film decreases upon the addition of CMC, but elongation at break increases with the addition of 16% CMC to the film. The films show pH triggered swelling pattern with the highest swelling ratio of 707 ± 10.91% at pH 12. The in vitro release profiles of the films are consistent with the results of the swelling studies and it shows pH sensitivity towards the drug release. The cumulative drug release increases from 0.81 ± 0.09 mg/L to 8.41 ± 0.04 mg/L with increasing the CMC content from 0% to 80% of the film in phosphate buffer saline (PBS) medium. It is around 7-fold increase compared to simulated gastric fluid (SGF) medium. However, the encapsulation efficiency slightly decreases with increasing the CMC content. According to the results of this study, PLA/CMC/CUR films can be suggested to improve the curcumin release in the intestinal alkaline condition.