Types Of Segments Research Articles

Differences in drivers of healthy eating and nutrition app preferences across motivation-based consumer groups

The aim is to explore whether and how different consumer groups, based on health motivations, differ in their drivers to adopt a healthy diet and their preferences for nutrition app properties. Four groups were identified: Health-motivated, Moderately-motivated, Body-motivated and Mind-motivated consumers. All groups are motivated to consume a healthy diet, although the Moderately-motivated less than the other groups. In addition, all groups feel sufficiently able to consume a healthy diet. Most differences were found regarding the perceived opportunity to consume a healthy diet. Although the perceived financial opportunity and the eating context are barriers to all groups, physical opportunity (lack of availability) is only perceived as a problem by the Moderately-motivated group. Worries about data protection is an issue to all groups, except for the Body-motivated group. Finally, social acceptance is not perceived as a barrier. Since different health motivations (e.g. physical health) can be related to different properties of nutrition apps (e.g. positive feedback), differences in app preferences were researched, but groups showed little differences in their preferences. For all groups easy navigation and a complete and reliable food database are important requirements for a nutrition app. In conclusion, this study suggests that consumer groups based on health motivations need different approaches to support them in healthy eating, but there is no clear need to adapt properties of nutrition apps to these groups. In the future, it could be interesting to study app preferences for other types of consumer segments e.g. based on socio-economic status or body mass index.

Analysis of forced aligner performance on L2 English speech

There is growing interest in how speech technologies perform on L2 speech. Largely omitted from this discussion are tools used in the early data processing steps, such as forced aligners, that can introduce errors and biases. This study adds to the conversation and tests how well a model pre-trained for the alignment of L1 American English speech performs on L2 English speech. We test and discuss the impact of language variety, demographic factors, and segment type on the performance of the forced aligner. We also examine systematic errors encountered.Forty-five speakers representing nine L2 varieties were selected from the Speech Accent Archive and force aligned using the Montreal Forced Aligner. The phoneme-level boundary placements were manually corrected in order to assess differences between the automatic and manual alignments. Results show marked variation in the performance across language groups and segment types for the two metrics used to assess accuracy: Onset Boundary Displacement, a distance metric between the automatic and manual boundary placements, and Overlap Rate, which indicates to what extent the automatically aligned segment overlaps with the manually aligned segment. The highest accuracy on both measures was obtained for German and French, and lowest accuracy for Russian. The aligner's performance on all varieties was comparable to that on conversational American English and non-standard varieties of English. Furthermore, the percentage of boundary placements within 10 and 20 ms of the corrected boundary was similar to that observed between transcribers. Apart from errors due to variety mismatch, most issues encountered in the alignment were due to issues not exclusive to L2 speech such as inaccurate orthographic transcriptions, hesitations, specific voice qualities, and background noise.The results of this study can inform the use of automatic aligners on L2 English speech and provide a baseline of potential errors and information to help the development of more robust alignment tools for further development of automatic systems using L2 English.

Automatic enhancement preprocessing for segmentation of low quality cell images

We present a novel automatic preprocessing and ensemble learning technique for the segmentation of low-quality cell images. Capturing cells subjected to intense light is challenging due to their vulnerability to light-induced cell death. Consequently, microscopic cell images tend to be of low quality and it causes low accuracy for semantic segmentation. This problem can not be satisfactorily solved by classical image preprocessing methods. Therefore, we propose a novel approach of automatic enhancement preprocessing (AEP), which translates an input image into images that are easy to recognize by deep learning. AEP is composed of two deep neural networks, and the penultimate feature maps of the first network are employed as filters to translate an input image with low quality into images that are easily classified by deep learning. Additionally, we propose an automatic weighted ensemble learning (AWEL), which combines the multiple segmentation results. Since the second network predicts segmentation results corresponding to each translated input image, multiple segmentation results can be aggregated by automatically determining suitable weights. Experiments on two types of cell image segmentation confirmed that AEP can translate low-quality cell images into images that are easy to segment and that segmentation accuracy improves using AWEL.

Influence of the Type of Soft Segment on the Selected Properties of Polyurethane Materials for Biomedical Applications.

This work presents the synthesis and characterization of new TPUs obtained by melt polyaddition using 1,1'-methanediylbis(4-isocyanatocyclohexane) (HMDI, Desmodur W®), a new unconventional chain extender, i.e., (methanediyldibenze-ne-4,1-diyl)dimethanediol, and five types of soft segments differing in structure and molar masses. The structure of the obtained polymers was determined (by using the Fourier transform infrared spectroscopy and X-ray diffraction methods), and the physicochemical (reduced viscosity, density), optical (UV-VIS), processing (MFR) and thermal (DSC and TGA-FTIR) as well as surface, antibacterial and cytotoxic properties were determined. Based on the results obtained, it can be stated that the type of soft segment used significantly affects the properties of the obtained polymers. The most favorable properties for use in medicine were demonstrated by materials based on a polycarbonate soft segment.

Static performance of precast concrete arches with carbon fiber reinforced polymer reinforcement

In this paper, static performances of a new precast concrete arch system with carbon fiber reinforced polymer (CFRP) reinforcement were investigated. Varied concrete strengths and segment types of precast concrete arches were tested. The results show that the increase of concrete strength can improve the bearing capacity of the precast arches with CFRP reinforcement. The ultimate bearing capacity of the precast arches segmented at the arch vault with CFRP reinforcement can reach or even exceed that of complete arches, while the precast arch segmented at the shoulder had lower ultimate load. A theoretical analysis method was proposed to predict the failure and bearing capacity of the precast concrete arches with CFRP reinforcement, which were found to be in close agreement with the experimental result.

Globalization of Stock Markets and The Factors Affecting It

Stock exchanges occupy a special place among the links of the financial and credit system. Mobilization of temporarily free cash and its effective distribution is carried out on the stock exchange. The financial market is an extremely complex and multifaceted structure, where the following participate: 1. Market infrastructure institutions; 2. Financial intermediaries; 3. Consumers of financial services. It is important to note that trading on modern stock exchanges is mainly carried out through electronic trading terminals. However, in the world stock markets today, all the conditions exist for stock trading and stock exchange settlement to be affected by blockchain technology, and even more so than traditional currency markets. One of the important benchmarks for investors and speculators in organized stock markets to make transactions is the stock market index. Stock market indices are directly related to share prices and are calculated based on the value of shares (in appropriate proportions) included in the base for calculating the index. Thus, the participants of the financial market and the instruments circulating in the market, which serve its various types of operations and segments, are characterized by great diversity at the modern stage. Therefore, it is necessary to go through the listing procedures on the stock exchanges and trade in the securities of only those issuers that meet the established requirements, which include financial indicators of the issuer, level of liquidity and degree of risk. Keywords: stock markets; globalization of exchanges; Factors affecting

Off-Road Terrain Identification And Analysis

Background: The role of the Terrain is paramount for any autonomous vehicle to drive safely on any type of surface. The Autonomous vehicles should have the capability of identifying the terrain and should adapt to the environment. With the evolution of robotics and Artificial Intelligence, and understanding diverse terrains, the techniques for terrain identification are also advancing with a major focus on safety.
 Methodology: To make Terrain Detection and Identification more reliable we used instance segmentation which is a more sophisticated type of segmentation that goes a step ahead of semantic segmentation by performing both object detection and segmentation at the same time. In order to perform Instance segmentation, we used the YOLOv8 architecture which is considered to be the state-of-the-art CNN (Convolutional Neural Network) architecture. The YOLOv8 model was trained on an Off-road Terrain Dataset.
 Results: Our findings indicate that the state-of-the-art YOLOv8 instance segmentation model provided the best results for terrain detection and segmentation with a threshold confidence of 0.60, and the results provide a maximum confidence of 0.92 which indicates an accurate segmentation model for the given terrain detection problem.
 Conclusion: The present work motivates for a more viable hardware model that makes use of trained computer vision models and cutting-edge sensors that can be tested on different soils and terrain. The results obtained can be used to study about the different Terrains and select the most suitable model, this in turn drives for further research in the subject of Terrain Identification and Detection.

Spatial lipidomics of coronary atherosclerotic plaque development in a familial hypercholesterolemia swine model

Coronary atherosclerosis is caused by plaque build-up, with lipids playing a pivotal role in its progression. However, lipid composition and distribution within coronary atherosclerosis remain unknown. This study aims to characterize lipids and investigate differences in lipid composition across disease stages to aid in the understanding of disease progression. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) was used to visualize lipid distributions in coronary artery sections (n = 17) from hypercholesterolemic swine. We performed histology on consecutive sections to classify the artery segments and to investigate colocalization between lipids and histological regions of interest in advanced plaque, including necrotic core and inflammatory cells. Segments were classified as healthy (n = 6), mild (n = 6), and advanced disease (n = 5) artery segments. Multivariate data analysis was employed to find differences in lipid composition between the segment types, and the lipids' spatial distribution was investigated using non-negative matrix factorization (NMF). Through this process, MALDI-MSI detected 473 lipid-related features. NMF clustering described three components in positive ionization mode: triacylglycerides (TAG), phosphatidylcholines (PC), and cholesterol species. In negative ionization mode, two components were identified: one driven by phosphatidylinositol(PI)(38:4), and one driven by ceramide-phosphoethanolamine(36:1). Multivariate data analysis showed the association between advanced disease and specific lipid signatures like PC(O-40:5) and cholesterylester(CE)(18:2). Ether-linked phospholipids and LysoPC species were found to colocalize with necrotic core, and mostly CE, ceramide, and PI species colocalized with inflammatory cells. This study, therefore, uncovers distinct lipid signatures correlated with plaque development and their colocalization with necrotic core and inflammatory cells, enhancing our understanding of coronary atherosclerosis progression.

Comparison of intraocular lens tilt after capsular sutured scleral fixation with capsular segments versus uneventful cataract surgery.

To evaluate and compare intraocular lens (IOL) tilt between uneventful phacoemulsification with in-the-bag IOL implantation and sutured scleral fixation (SSF) of the lens bag with a capsular tension segment (type 6 D / Morcher) using a Sheimpflug camera. Clinical Practice, Hospital. Barcelona and A Coruña, Spain. Retrospective, comparative multicenter study. IOL tilt was compared between patients who underwent sutured scleral fixation with a capsular tension segment in a single eye (SSF group, n = 15) with patients who underwent uneventful IOL implantation (control group, n = 12) that were matched by biometric measurements. Post-operative refractive accuracy of biometric formulas by means of mean absolute error (MAE) was also reported. All patients underwent a general ophthalmic evaluation, anterior segment photography, and postoperative optical biometry (Zeiss IOLMaster® 500). In addition, IOL tilt was measured with a Scheimpflug camera (Pentacam R, Oculus Optikgerate Gmbh). Mean vertical tilt was similar in both groups (2.20+/-2.47° SSF vs 1.97 +/- 1.79° control; p = 0.836) but mean horizontal tilt tended to higher values in the SSF series (2.09 +/- 2.74° vs 0.94 +/- 1.17°; p = 0.139). Considering post-operative refractive error in diopters by MAE calculations, there was an underestimation of IOL power in the SSF group which was only statistically significant for Barrett Universal II (1.07 vs 0.32; p = 0.028) and Hill-RBF (0.95 vs 0.26; p = 0.024) formulas, but not for SRK/T (0.99 vs 0.42; p = 0.285) and Kane (0.96 vs 0.33; p = 0.083). Sutured scleral fixation of capsular tension segments in the presence of zonular instability does not seem to induce clinically significant IOL tilt compared to uneventful cataract extraction cases.

Siccanin-related drimane meroterpenoids: biological activities and synthesis.

Covering: 1962 to 2023Drimane (hydro)quinones biosynthetically arise from the combination of drimane-type terpenoids with phenols or equivalents. Since the isolation of siccanin in 1962 (structure identified in 1967), over 200 natural drimane (hydro)quinones have been reported. They are widespread with remarkably diverse architectures and biological functions, which are achieved by varying either the drimane subunit, hydroquinone segment, or the fusion types of drimane and hydroquinone segment both of them. This type of natural products has drawn increasing attention in the discovery of novel pharmaceutical leads. Enormous efforts have been devoted to developing efficient and divergent synthesis approaches to facilitate the SAR study of drimane (hydro)quinones, aiming for more promising functional leads. This review is arranged mainly in terms of scaffold types of drimane (hydro)quinones and further categorized on the basis of biological functions. The mechanisms of action are also briefly discussed. Synthetic methods are categorized according to the strategies forging the Csp2-Csp3 linker between drimane segments and (hydro)quinone subunits.

FLMatchQA: a recursive neural network-based question answering with customized federated learning model.

More sophisticated data access is possible with artificial intelligence (AI) techniques such as question answering (QA), but regulations and privacy concerns have limited their use. Federated learning (FL) deals with these problems, and QA is a viable substitute for AI. The utilization of hierarchical FL systems is examined in this research, along with an ideal method for developing client-specific adapters. The User Modified Hierarchical Federated Learning Model (UMHFLM) selects local models for users' tasks. The article suggests employing recurrent neural network (RNN) as a neural network (NN) technique for learning automatically and categorizing questions based on natural language into the appropriate templates. Together, local and global models are developed, with the worldwide model influencing local models, which are, in turn, combined for personalization. The method is applied in natural language processing pipelines for phrase matching employing template exact match, segmentation, and answer type detection. The (SQuAD-2.0), a DL-based QA method for acquiring knowledge of complicated SPARQL test questions and their accompanying SPARQL queries across the DBpedia dataset, was used to train and assess the model. The SQuAD2.0 datasets evaluate the model, which identifies 38 distinct templates. Considering the top two most likely templates, the RNN model achieves template classification accuracy of 92.8% and 61.8% on the SQuAD2.0 and QALD-7 datasets. A study on data scarcity among participants found that FL Match outperformed BERT significantly. A MAP margin of 2.60% exists between BERT and FL Match at a 100% data ratio and an MRR margin of 7.23% at a 20% data ratio.

Tarefas com base na Fonotática para estimulação de consciência fonológica

The purpose of this paper is to present some fundamental phonotactic concepts and their importance in phonological awareness tasks in literacy. Only after the beginning of their schooling do children start to observe and notice the segmental elements of words. Furthermore, mastery of phonological awareness will determine children’s reading success in school, which in turn affects their proficiency in adulthood (BYRNE; LEDEZ, 1983). In this study, we present a playful way to explore the sonority scale perception with students through the recognition of geometric shapes (circle and straight line), according to the Sonority Syllable Model (SSM), proposed by Basbøll (2005). It is an alternative proposal to the phonotactic description and analysis that uses distinctive features in its sound organization. In our proposal, we use a phoneme-grapheme correspondence, but, as Basbøll (2005) suggests, we firstly establish which one is the prototypical syllable peak, i.e., main/central peak, in order to determine the implicational relations among the segment types. In addition, in a playful way to illustrate this relation, we make use of a set of concentric circles known as Euler’s diagram. This set of circles is a mathematical set used to demonstrate the intersection among elements. Lastly, we show how this adaptation may be used in a pedagogical practice with children and adults in the literacy stage.

Evaluation of environmental and economic compatibility of different types of segment linings based on the structural performance with some aggravating factors

The performance of supporting systems can be significantly affected by aggravating factors that contribute to segmental tunnel lining damage. Based on previous studies and statistical data, the excessive thrust force and defect in support conditions are the crucial factors that can aggravate the damage of segmental linings during the installation stage. This study aims to evaluate the effect of influential factors, including the excessive thrust force, the incomplete contact of loading shoes, configuration of loading shoes, defect gap thickness, and segment type. In addition, a series of numerical simulation are performed to investigate the impact of the influential factors on the performance of three different segmental lining types, including conventional reinforced concrete segment, recycled steel fiber reinforced concrete segment, and new hybrid design recycled steel fiber reinforced concrete segment. The results indicated that numerical modeling can accurately simulate stress concentration and damage patterns of segmental lining in different conditions. This method can provide useful information about the performance of segmental tunnel linings, considering essential phenomena that are neglected in traditional design methods, such as the effect of incomplete contact of the support area, and the thickness of circumferential gap. Numerical analysis of segmental tunnel lining behavior by considering different conditions can help reduce undesirable consequences and construction costs. The results indicated that the increase in the thickness of the gap significantly increase in crack opening and destructive damages. While, the configuration of the loading shoes affects the amount of crack openings, the number and position of these cracks; the effect of this parameter is very lower compared to the presence of defects in the supporting area. Finally, it was concluded that the hybrid design showed high efficiency for all investigated conditions, in terms of structural performance, environmental impact and economic compatibility.

Piezoelectric sensing method for segmental joint contact stress during shield tunnel construction

The emergence of curved shield tunnels poses a significant construction challenge. If the quality of the segment assembly is not guaranteed, many segment cracks and damage will result from the stress concentration. Sensing the contact stresses between segmental joints is necessary to improve the quality of segments assembled for shield tunnel construction. Polyvinylidene difluoride (PVDF) piezoelectric material was chosen for the sensor because it can convert contact stresses into electrical signals, allowing the state of the segmental joints to be effectively sensed. It matches the working environment between the segmental joints of the shield tunnel, where flexible structures such as rubber gaskets and force transfer pads are present. This study proposes a piezoelectric sensing method for segmental joints in shield tunnels and conducts laboratory tests, numerical analyses, and field tests to validate the feasibility of the method. The results indicate that the PVDF film sensor can effectively sense the entire compression process of the gasket with different amounts of compression. The piezoelectric cable sensor can effectively sense the joint offset direction of the gasket. For differently shaped sections, the variation in the force sensed by the piezoelectric cable sensors was different, as verified by numerical simulation. Through the field test, it was found that the average contact stress between the segmental joints was in the range of 1.2–1.8 MPa during construction of the curved shield tunnels. The location of the segmental joints and the type of segment affect the contact stress value. The field monitoring results show that piezoelectric sensing technology can be successfully applied during assembly of the segments for effective sensing of the contact stress.

Spatio-Temporal Pattern of China’s Urban Network Under the Substitution Effect of High-Speed Rail on Aviation

High-speed rail (HSR) and aviation have played an important role in shaping urban connections and building urban networks. However, with the continuous expansion of the scale of HSR, the competition between the two has become increasingly fierce, and HSR has gradually been substituted for aviation in some regions. Therefore, based on HSR flow and airline flow data, we depicted the spatio-temporal evolution pattern of China’s urban network from 2017 to 2021 by constructing the HSR–aviation composite network, then identified the spatial scope and network form of the substitution of HSR for aviation through classifying the four types of segments, and analyzed the influencing factors of this substitution effect. The results showed that the spatial form of the HSR–aviation composite network is “spindle-shaped” and has a right-skewness distribution; the spatial scope of HSR completely or partially substituting for aviation is mainly distributed in the “diamond-shaped” space with Beijing–Shanghai–Guangzhou–Chengdu as the apex; and 0–770 km is the absolute advantage distance range of HSR. Moreover, the scale expansion of the composite network, the comparative advantages of HSR in shaping the urban network, the personal travel preference for HSR, and the distance between cities and city attributes are the main factors that make HSR a substitute for aviation.

Circulus Willis Anomalies Diagnosed with CT Angiography and Evaluation of Their Relations with Ischemic Stroke

Our aim in this study is examining the frequency of posterior communicating artery (PCoM), Anterior Cerebral Artery A1 segment (ACA AI) and Fetal type posterior cerebral artery (FPCA) anomalies and their effects on ischemic stroke by retrospectively analyzing examinations of Computerized Tomography Angiography (CTA) taken in our hospital within 2017. 22 cases (26.5%) diagnosed with bilateral hypoplastic / aplastic PCoA anomaly, were diagnosed with anterior circulation infarct, 24 cases (28.9%) were diagnosed with posterior circulation infarct, but 37 cases (44.6%) were not diagnosed with ischemic stroke. 17 (37.8%) of the cases who have unilateral hypoplastic / aplastic PCoA anomaly, were diagnosed with anterior circulation infarct, 14 cases (31.1%) were diagnosed with posterior circulation infarct. 13 (26%) of 50 cases diagnosed with unilateral hypoplastic / aplastic ACA A1 segment, were diagnosed with anterior circulation infarct, 10 cases (20%) were diagnosed with posterior circulation infarct. 27 cases (54%) were not diagnosed with ischemic stroke. Both of 2 cases diagnosed with bilateral hypoplastic / aplastic ACA A1 segment, had anterior circulation infarct. 4 (30.8%) of 13 cases diagnosed with unilateral FPCA anomaly, were diagnosed with anterior circulation infarct, 3 cases (23.1%) were diagnosed with posterior circulation infarct, 6 cases (46.2%) did not have ischemic stroke symptoms. In conclusion, even though these variations’ role in optimum stroke prophylaxis in individuals having one or more stroke risk factors, has not determined yet, there is no doubt that clinical researcher will eliminate these uncertainties in future studies.

Improving road safety at horizontal curves using V2I speed warning messages

Introduction: According to the Federal Highway Administration, a quarter of fatal collisions has occurred at horizontal curves. The average collision rate at horizontal curves was found to be three times higher than other types of highway segments. The lack of compliance with the speed limit and driver-related factors are among the main contributing factors to those collisions. Vehicle to Infrastructure (V2I) communications can address these limitations by providing drivers with valuable in-vehicle warning messages based on operational and safety data. There is limited effort investigating the impact of different types of V2I warning messages at horizontal curves and among different profiles of drivers. This study aims to thoroughly examine drivers’ behavior and compliance with different V2I warning messages when approaching horizontal curves. Methods: A driving simulator experiment and self-reported survey were conducted. Three main hypotheses were analyzed in this study. First, whether supplying drivers with in-vehicle V2I warning messages will positively affect drivers’ behavior at horizontal curves compared to the standard road signs. Second, whether there will be a significant difference in drivers’ behavior when receiving text and audio V2I warning messages. Third, whether seniors and female drivers will comply more with speed limit advisory provided through V2I message than younger and male drivers. Results: The Analysis of Covariance confirmed the first two hypotheses. Two main measures of drivers’ behavior found to be lower in the V2I communication scenarios compared to the base one. The audio warning message was found to be more promising in increasing drivers’ compliance with speed limit advisory when approaching the curves. Analyzing the third hypothesis revealed that younger and male drivers had higher curve initiation speed compared to females and seniors. Practical Applications: The findings of this study can be used by transportation researchers, authorities, and car manufacturers to improve the effectiveness of in-vehicle V2I warning messages among different profiles of drivers.

A Critical Analysis of the Robustness of Radiomics to Variations in Segmentation Methods in 18F-PSMA-1007 PET Images of Patients Affected by Prostate Cancer.

Radiomics shows promising results in supporting the clinical decision process, and much effort has been put into its standardization, thus leading to the Imaging Biomarker Standardization Initiative (IBSI), that established how radiomics features should be computed. However, radiomics still lacks standardization and many factors, such as segmentation methods, limit study reproducibility and robustness. We investigated the impact that three different segmentation methods (manual, thresholding and region growing) have on radiomics features extracted from 18F-PSMA-1007 Positron Emission Tomography (PET) images of 78 patients (43 Low Risk, 35 High Risk). Segmentation was repeated for each patient, thus leading to three datasets of segmentations. Then, feature extraction was performed for each dataset, and 1781 features (107 original, 930 Laplacian of Gaussian (LoG) features, 744 wavelet features) were extracted. Feature robustness and reproducibility were assessed through the intra class correlation coefficient (ICC) to measure agreement between the three segmentation methods. To assess the impact that the three methods had on machine learning models, feature selection was performed through a hybrid descriptive-inferential method, and selected features were given as input to three classifiers, K-Nearest Neighbors (KNN), Support Vector Machines (SVM), Linear Discriminant Analysis (LDA), Random Forest (RF), AdaBoost and Neural Networks (NN), whose performance in discriminating between low-risk and high-risk patients have been validated through 30 times repeated five-fold cross validation. Our study showed that segmentation methods influence radiomics features and that Shape features were the least reproducible (average ICC: 0.27), while GLCM features the most reproducible. Moreover, feature reproducibility changed depending on segmentation type, resulting in 51.18% of LoG features exhibiting excellent reproducibility (range average ICC: 0.68-0.87) and 47.85% of wavelet features exhibiting poor reproducibility that varied between wavelet sub-bands (range average ICC: 0.34-0.80) and resulted in the LLL band showing the highest average ICC (0.80). Finally, model performance showed that region growing led to the highest accuracy (74.49%), improved sensitivity (84.38%) and AUC (79.20%) in contrast with manual segmentation.

A Smart Status Based Monitoring Algorithm for the Dynamic Analysis of Memory Safety

C is a dominant programming language for implementing system and low-level embedded software. Unfortunately, the unsafe nature of its low-level control of memory often leads to memory errors. Dynamic analysis has been widely used to detect memory errors at runtime. However, existing monitoring algorithms for dynamic analysis are not yet satisfactory as they cannot deterministically and completely detect some types of errors, e.g., segment confusion errors, sub-object overflows, use-after-frees and memory leaks. We propose a new monitoring algorithm, namely Smatus , short for smart status , that improves memory safety by performing comprehensive dynamic analysis. The key innovation is to maintain at runtime a small status node for each memory object. A status node records the status value and reference count of an object, where the status value denotes the liveness and segment type of this object, and the reference count tracks the number of pointer variables pointing to this object. Smatus maintains at runtime a pointer metadata for each pointer variable, to record not only the base and bound of a pointer’s referent but also the address of the referent’s status node. All the pointers pointing to the same referent share the same status node in their pointer metadata. A status node is smart in the sense that it is automatically deleted when it becomes useless (indicated by its reference count reaching zero). To the best of our knowledge, Smatus represents the most comprehensive approach of its kind. We have evaluated Smatus by using a large set of programs including the NIST Software Assurance Reference Dataset, MSBench, MiBench, SPEC and stress testing benchmarks. In terms of effectiveness (detecting different types of memory errors), Smatus outperforms state-of-the-art tools, Google’s AddressSanitizer, SoftBoundCETS and Valgrind, as it is capable of detecting more errors. In terms of performance (the time and memory overheads), Smatus outperforms SoftBoundCETS and Valgrind in terms of both lower time and memory overheads incurred, and is on par with AddressSanitizer in terms of the time and memory overhead tradeoff made (with much lower memory overheads incurred).

Evaluation of Styloid Process Length and Calcification Degrees of Renal Transplant Patients with Panoramic Radiographs

Purpose: The aim of this study was to evaluate the styloid process length and calcification degrees of renal-transplant patients and compare them with the healthy control group. Materials & Methods: Panoramic radiographs of 93 patients who had renal transplantation and 93 healthy patients were reviewed retrospectively. Length measurements were made from the apex to the base of the styloid process with a line following the profile. The elongation degrees were classified into five groups as normal (type 0), elongated (Type 1), pseudo-segmented (Type 2), segmented (Type 3) and non-continuous (Type 4). Calcification degrees were classified into four different groups as external (Type A), partial (Type B), nodular (Type C) and complete calcification (Type D). Results: The study and control groups were matched for age and gender. Styloid process length was found to be significantly higher in male than in female (p<0.001). The extent of elongation and calcification did not differ in terms of gender. The mean styloid process length values were found to be significantly higher in the study group compared to the control group (p<0.001). There was a significant difference between the groups in terms of elongation degrees (p<0.001). For elongation types, while the majority of the study group was type 1, type 0 was observed more in the control group. No difference was observed between the groups in terms of the calcification degrees (p=0.076). Conclusion: Changes in phosphate balance and parathyroid hormone levels, possibly due to hemodialysis treatment in renal transplant patients, may have led to styloid process elongation.