bluuebunny/crossref_metadata_2025 huggingface dataset:
The burden of type 2 diabetes mellitus in states of the European Union and United Kingdom at the national and subnational levels: A systematic review
Authors: Soares Andrade Carlos Alexandre , Shahin Balqees , Dede Onisoyonivosekume , Akpeji Anne Omagu , Ajene Comfort‐Lucia , Albano Israel Frederico Epalanga , Varga Orsolya
Published: July 2023

Type 2 diabetes mellitus (T2D) is a highly prevalent disease worldwide, with an equally increased expenditure associated with it. We aimed to longitudinally evaluate the epidemiologic and economic burden of T2D in the current member states of the European Union and the United Kingdom (EU‐28). The present systematic review is registered on PROSPERO (CRD42020219894), and it followed the PRISMA guidelines. Eligibility criteria comprised original observational studies in English reporting economic and epidemiological data for T2D in member states of the EU‐28. Methodological assessment was performed with the Joanna Briggs Institute (JBI) Critical Appraisal Tools. The search retrieved 2253 titles and abstracts. After study selection, 41 studies were included in the epidemiologic analysis and 25 in the economic analysis. Economic and epidemiologic studies covered only 15 member states with reported data between 1970 and 2017, resulting in an incomplete picture. For children in particular, limited information is available. The prevalence, incidence, mortality, and expenditure of the T2D population have increased across the decades in member states. Therefore, policies should aim to prevent or reduce the burden of T2D in the EU and consequently mitigate the expenditure on T2D.
Comparison between absorbable dressing (Reso‐Pac®) and eugenol‐free dressing (Coe‐pak) after surgical removal of gingival pigmentation
Authors: Kazwini Rudwan , Kasem Tarek
Published: July 2023

Objective

Many dressings are used after the surgical removal of gingival pigmentation. This study aims to compare absorbed dressing (Reso‐Pac®) and eugenol‐free dressing (Coe‐pak) in accelerating wound healing, re‐epithelization and reducing pain after surgical removal of gingival pigmentation using a surgical scalpel.

Materials and Methods

This randomized clinical trial (RCT) used a split‐mouth design. According to Hedin's classification, 10 patients with maxillary physiological gingival pigmentation class 3 and 4 were selected. Reso‐Pac® and Coe‐pak were randomly applied on each side after surgery. Landry's scale was used to assess healing index, and re‐epithelization was evaluated using toluidine blue stain. Pain was measured using a visual analogue scale (VAS). Induced pain was evaluated after 1 week by applying airflow on each side for 5 s using VAS.

Results

The study group had higher but insignificant differences after 1 and 2 weeks in healing index and re‐epithelization. Pain was insignificantly higher in study group after 2 h but insignificantly higher in the control group in days (1–5). Induced pain was significantly higher (p = 0.015) in the control group after 1 week.

Conclusion

Reso‐Pac® can be considered as a viable alternative for Coe‐pak due to its effects in pain reduction and accelerating wound healing.
Paced P‐wave morphology templates to guide atrial tachycardia localization: A derivation and validation study
Authors: Damaty Ahmed El , Yahya Dhaifallah , El‐Mowafy Mahmoud , Rizk Hussien , Sapp John , Parkash Ratika , Gardner Martin , Gray Chris , AbdelWahab Amir
Published: July 2023

Background

Surface ECG is a useful tool to guide mapping of focal atrial tachycardia (AT).

Objectives

We aimed to construct 12‐lead ECG templates for P‐wave morphology (PWM) during endocardial pacing from different sites in both atria in patients with no apparent structural heart disease (derivation cohort), with the goal of creating a localization algorithm, which could subsequently be validated in a cohort of patients undergoing catheter ablation of focal AT (validation cohort).

Methods

We prospectively enrolled consecutive patients who underwent electrophysiology study, had no structural heart disease and no atrial enlargement. Atrial pacing, at twice diastolic threshold, was carried out at different anatomical sites in both atria. Paced PWM and duration were assessed. An algorithm was generated from the constructed templates of each pacing site. The algorithm was applied on a retrospective series of successfully ablated AT patients. Overall and site‐specific accuracy were determined.

Results

Derivation cohort included 65 patients (25 men, age 37 ± 13 years). Atrial pacing was performed in 1025 sites in 61 patients (95%) in RA and in 15 patients (23%) in LA. The validation cohort included 71 patients (28 men, age 52 ± 19 years). AT were right atrial in 66.2%. The algorithm successfully predicted AT origin in 91.5% of patients (100% in LA and 87.2% in RA). It was off by one adjacent segment in the remaining 8.5%.

Conclusions

A simple ECG algorithm based on paced PWM templates was highly accurate in localizing site of origin of focal AT in patients with structurally normal hearts.
Designing optimal training sets for genomic prediction using adversarial validation with probit regression
Authors: Montesinos‐López Osval A. ,   Kismiantini, Montesinos‐López Abelardo
Published: July 2023

Genomic selection (GS) is a disruptive methodology that is revolutionizing animal and plant breeding. However, its practical implementation is challenging since many times there is a mismatch in the distribution of the training and testing sets. Adversarial validation is an approach popular in machine learning to detect and address the difference between the training and testing distributions. For this reason, the adversarial validation method in this research was implemented using probit regression to detect the mismatch in distributions and also to select an optimal training set. We evaluated the proposed method with 14 datasets, and the results were benchmarked regarding of using the whole reference population and simple random samples. We found that the proposed method is effective for detecting the mismatch in distributions and outperformed in prediction accuracy by 11.67% (in terms of mean square error) and by 5.35% (in terms of normalized mean square error) when the whole reference population was used as training sets. Also, in general, this outperformed some existing methods for optimal training designs in the context of GS.
Serotonin: A frontline player in plant growth and stress responses
Authors: Mishra Vishnu , Sarkar Ananda K.
Published: July 2023

Serotonin is a well‐studied pineal hormone that functions as a neurotransmitter in mammals and is found in varying amounts in diverse plant species. By modulating gene and phytohormonal crosstalk, serotonin has a significant role in plant growth and stress response, including root, shoot, flowering, morphogenesis, and adaptability responses to numerous environmental signals. Despite its prevalence and importance in plant growth and development, its molecular action, regulation and signalling processes remain unknown. Here, we highlight the current knowledge of the role of serotonin‐mediated regulation of plant growth and stress response. We focus on serotonin and its regulatory connections with phytohormonal crosstalk and address their possible functions in coordinating diverse phytohormonal responses during distinct developmental phases, correlating with melatonin. Additionally, we have also discussed the possible role of microRNAs (miRNAs) in the regulation of serotonin biosynthesis. In summary, serotonin may act as a node molecule to coordinate the balance between plant growth and stress response, which may shed light on finding its key regulatory pathways for uncovering its mysterious molecular network.
A depositional model for meandering rivers without land plants
Authors: Hasson Michael , Marvin M. Colin , Gunn Andrew , Ielpi Alessandro , Lapôtre Mathieu G. A.
Published: July 2023

The recognition of meandering rivers in Earth's prevegetation stratigraphic record is hindered by an absence of depositional models specifically tailored to unvegetated single‐channel rivers. As a result, their abundance on the early Earth is currently unknown. Here, sedimentological studies of two modern meandering river reaches with unvegetated banks were conducted. Both reaches are located in arid basins of Nevada, USA. Stratigraphy was analysed in conjunction with satellite imagery and high‐resolution topographic data to understand how channels and floodplains record past flow conditions. Analyses of point‐bar and channel‐fill deposits showed that lateral accretion sets are not heterolithic but, rather, composed of mixed sand and sand‐sized mud aggregates (clumps of clay and silt) interpreted to have formed through flocculation. Levées are present but subdued. Notably, downstream‐migrating outer‐bank‐attached bars are prominent architectural features that may be common in unvegetated meandering rivers in arid landscapes elsewhere. The identification of such depositional elements in the stratigraphic record may enhance recognition of ancient unvegetated meandering rivers and improve reconstructions of palaeohydrology on early Earth and Mars.
Quality assessment and harmonization of laboratories across Europe for multiple SARS‐CoV‐2 serology assays
Authors: Steenhuis Maurice , Wouters Elise , Schrezenmeier Hubert , Rispens Theo , Tiberghien Pierre , Harvala Heli , Feys Hendrik B. , van der Schoot C. Ellen ,   SUPPORT‐E Collaborators
Published: July 2023

Background and Objectives

There is a need for conversion of SARS‐CoV‐2 serology data from different laboratories to a harmonized international unit. We aimed to compare the performance of multiple SARS‐CoV‐2 antibody serology assays among 25 laboratories across 12 European countries.

Materials and Methods

To investigate this we have distributed to all participating laboratories a panel of 15 SARS‐CoV‐2 plasma samples and a single batch of pooled plasma calibrated to the WHO IS 20/136 standard.

Results

All assays showed excellent discrimination between SARS‐CoV‐2 seronegative plasma samples and pre‐vaccinated seropositive plasma samples but differed substantially in raw antibody titres. Titres could be harmonized to binding antibody units per millilitre by calibration in relation to a reference reagent.

Conclusion

The standardization of antibody quantification is of paramount importance to allow interpretation and comparison of serology data reported in clinical trials in order to identify donor cohorts from whom the most effective convalescent plasma can be collected.
Bragg Scattering of Surface Gravity Waves by a Submerged Composite Wavy Porous Plate
Authors: Mohapatra A. K. , Sahoo T.
Published: July 2023

Surface gravity wave interaction of composite wavy porous plate is studied by developing a numerical model using the boundary element method in the context of two-dimensional linear potential theory. Bragg scattering phenomenon is studied by considering the linearized pressure drop condition known as Darcy’s law passing through the porous structure. Numerical results are obtained through the boundary element method for the special limiting case of the existing previous literature to authenticate the accuracy of the numerical solution. The influence of wave and structural design parameters such as the number of ripple wavelengths of the wavy plate, relative plate length, structural porosities, and relative submergence depth on hydrodynamics properties such as reflection, transmission, horizontal wave load, and vertical wave coefficients are discussed. The study results of composite wavy porous plate indicate improved hydrodynamic performance as compared to the horizontal porous plate and wavy porous plate. This study is significant for practical applications in coastal engineering environments.
A Simplified Thermal Plasto-Elastohydrodynamic Lubrication Model for Circular Contact With Real Surface Roughness
Authors: Romio P. C. , Marques P. M. T. , Fernandes C. M. C. G. , Seabra J. H. O.
Published: July 2023

The current increase in power density, contact load, and speeds have imposed new challenges on elastohydrodynamic lubrication (EHL) contact models. To overcome possible EHL limitations under such conditions, the present work presents a unified thermal plasto-elastohydrodynamic lubrication (TPEHL) model for circular contact with real surface roughness capable to simulate the different lubrication regimes. Among the main characteristics of the proposed model, one should mention the minimal implementation changes in standard EHL models; there is no need for a preliminary assessment to verify whether thermal and plastic effects are negligible (or not) since these effects will naturally take place in the simulations, and good agreement between the predictions using the model and the experimental measurements.
Simulation of a System of Nanoantennas Located in a TSV Channel as a System for Receiving and Transmitting Data
Authors: Serov D. A. , Khorin I. A.
Published: July 2023

The results of a theoretical study of the behavior of a system of nanophotonic devices, consisting of receiving and transmitting plasmonic metal antennas, are presented. Based on the finite element method, the main parameters of antennas located in the TSV channel and receiving a signal in the terahertz frequency range are calculated. The limiting range of signal transmission and the coefficient of its amplification are determined. Conclusions are drawn on the suitability of the presented configuration as a system for wireless data transmission and reception in three-dimensional integrated circuits.
Survival of patients with recurrent uveal melanoma after treatment with radiation therapy
Authors: Lane Anne M , Hartley Caleb , Go Ashley K , Wu Frances , Gragoudas Evangelos S , Kim Ivana K
Published: July 2023

Background/aims

We evaluated a large cohort of patients treated for local recurrence of choroidal or ciliary body melanomas at the Massachusetts Eye and Ear (MEE) to quantify the risk of melanoma-related mortality associated with recurrence, independent of other risk factors.

Methods

Patients treated with radiation therapy from 1982 to 2017 were identified through the Uveal Melanoma Registry at MEE. Competing risks regression was performed to investigate the risk of melanoma-related mortality associated with recurrence, treating recurrence as a time-varying covariate.

Results

Of 4196 patients treated, 4043 patients remained recurrence-free and 153 patients experienced a recurrence (median follow-up: 9.9 years). Median time from initial treatment to recurrence was 30.5 months (range: 2.0–238.7). Seventy-nine (69.9%) patients with recurrences and 826 (37.9%) patients in the recurrence-free group died of metastatic uveal melanoma (p<0.001). Median time from initial treatment to melanoma-related death was 4.9 years (1.0–31.8) for patients who developed recurrences and 4.3 years (0.59–33.8) for patients who did not (p=0.17). Five-year and 10-year probabilities of melanoma-related mortality were 9.5% and 15.0%, respectively, in patients without local recurrences compared with 32.0% and 46.6% in patients with recurrences (p<0.001).

Conclusion

These data confirm previous reports that local recurrence is associated with an increased risk of dying of melanoma and quantify the risk that can be attributed to local recurrence independent of other risk factors. This group of patients should be strongly considered for adjuvant therapies when available.
Diabetic retinopathy in African–Americans with end-stage kidney disease: a cross-sectional study on prevalence and impact on quality of life
Authors: Egeolu Michelle , Caleon Ramoncito L , Manishimwe Exaucee , Zabala Zohyra E , Moazzami Bobak , Gerges Amany , O’Keefe Ghazala D , Navarrete Jose , Galindo Rodolfo J , McCoy Rozalina Grubina , Vellanki Priyathama , Peng Limin , Umpierrez Guillermo E
Published: July 2023

Introduction

The prevalence, severity, and quality of life (QoL) impact of diabetic retinopathy (DR) among African–Americans (AAs) with end-stage kidney disease (ESKD) undergoing dialysis are unknown.

Research design and methods

A cross-sectional study was conducted on 93 AA adults with diabetes and ESKD. The diagnosis of DR was based on a review of medical records and/or a positive photograph with a portable hand-held device reviewed by both artificial intelligence software and a retinal specialist. QoL, physical disability social determinants of health (SDoHs) were assessed by standardized questionnaires.

Results

The prevalence of DR was 75%, with 33% of participants having mild, 9.6% moderate and 57.4% severe DR. A total of 43% had normal visual acuity; 45% had moderate visual impairment; and 12% had severe visual impairment. We found a high burden of disease, multiple SDoH challenges, and low QoL and general health among patients with ESKD. The presence of DR had no significant impact on physical health and QoL compared with participants without DR.

Conclusions

DR is present in 75% of AA patients with diabetes and ESKD on haemodialysis. ESKD has a significant burden on general health and QoL; however, DR has a minor additional impact on the overall physical health and QoL in people with ESKD.
Dexmedetomidine for end of life sedation: retrospective cohort comparison study
Authors: Thomas Benjamin , Barclay Gregory , Barbato Michael
Published: July 2023

Objectives

Infused sedatives are often utilised to alleviate distress at the end of life. Which sedative best achieves this is unknown. This study compares breakthrough medication requirements of patients treated with the novel agent dexmedetomidine compared with patients treated with standard-care sedatives.

Methods

A retrospective cross-cohort comparison. Two studies of patients at the end of life under sedation at the same palliative care unit, one utilising novel sedatives, and the other standard care were compared. Breakthrough medication requirements were compared using paired t-tests, including opioids, benzodiazepines and anticholinergics. Changes in background infusions were compared.

Results

The dexmedetomidine cohort required less breakthrough interventions per day compared with the standard care group, the reduction was significant (2.2 vs 3.9, p=0.003). There was a significant difference in benzodiazepine requirements, with the dexmedetomidine cohort requiring fewer doses per day than the standard care cohort (1.1 vs 0.6, p=0.03). Anticholinergics were more commonly utilised in the standard care cohort but there was no significant difference (p=0.22). Opioid requirements were similar across cohorts with comparable rates of breakthrough use and infusion increases.

Conclusions

This study demonstrates a reduction in breakthrough medication requirements, particularly benzodiazepines, for patients sedated with dexmedetomidine at end of life.
Traveller end of life care experiences and needs: thematic analysis
Authors: Dixon Kathryn Charlotte , Conci Riccardo , Bowers Ben , Duschinsky Robbie , Spathis Anna , Barclay Stephen
Published: July 2023

Objectives

Travelling communities are a significant, but poorly understood, group of ethnic minorities known to experience inequalities in many aspects of healthcare, including at the end of life. This study explored the end of life care experiences and needs of Travellers, along with the perspectives of healthcare professionals.

Methods

Secondary thematic analysis of data from two focus groups and 16 interviews. Eighteen UK-based members of Travelling communities and three healthcare professionals took part in two focus groups. Sixteen hospice staff were interviewed. Data were collected by UK charity One Voice 4 Travellers in 2018.

Results

Tensions permeated the healthcare experience of Travellers. The perceived need for concealment of ethnic identity in the healthcare setting conflicted with participants’ desire for personalised care and tailored services. Healthcare professionals’ limited awareness of Travellers’ cultural rituals around death led to difficulties, including misunderstandings relating to the large numbers of family gathered at the bedside of dying relatives in hospital and hospice settings. Approaches that could increase the acceptability of healthcare included Travellers working in liaison roles, increased provision of space for visiting family and cultural competency training for staff. However, challenges remain in converting ideal solutions into feasible changes.

Conclusions

Improved communication and understanding between Travelling communities and healthcare professionals is needed to relieve the multilevel tensions experienced at the end of life. At an individual level, this would enable personalised care; at a systems level, cocreation of end of life care services with Travellers would help ensure that their cultural needs are met.
Evaluation of a smoke-free beaches intervention in Barcelona: a quasi-experimental study
Authors: Valmayor Sara , González Kilian , López Maria J , Lacera Patricia , Giménez Patricia , Rumín-Caparrós Aitor , Pasarín Maria Isabel , Henderson Elisabet , Díez Elia
Published: July 2023

Background

We aim to assess the effect of a smoke-free beaches (SFB) intervention in Barcelona on smoking during the 2021 bathing season.

Methods

Quasi-experimental pre-post design (pre-intervention period: 15–28 May; post-intervention period: 29 May–12 September). Based on users’ profiles and location, four beaches were assigned to the intervention group (IG) and five to the comparison group (CG). The intervention involved: a mayoral decree (29 May), a communication campaign and beach on-site information. We established two 3 m × 3 m transects per beach from the coastline to the promenade. Trained teams collected smoking-related information in the transects through observations and surveys to beach users. Outcomes are as follows: percentage of people reporting witnessing smoking behaviours the last fortnight and percentage of people observed smoking. We calculated and compared prevalence ratios (PRs) with adjusted Poisson regressions.

Results

3751 interviews (1721 IG; 2030 CG) and 1108 observations (498 IG, 610 CG) were carried out. SFB were associated with a significant reduction in the percentage of people reporting witnessing smoking (IG (pre: 87.2%; post: 49.7%); CG (pre: 86.2%; post: 74.1%); PR (95% CI): 0.7 (0.6 to 0.8)); and in the users observed smoking in the beach (IG (pre: 3.8%; post: 3.0%); CG (pre: 2.3%; post: 9.9%); PR (95% CI): 0.3 (0.3 to 0.4)). Satisfaction scores were 8.3 (IG) and 8.1 (CG) out of 10.

Conclusion

An SFB intervention is an effective and well-accepted measure to reduce smoking and smokers’ visibility. Smoke-free measures should be extended to beaches and other non-regulated outdoor areas.
Hierarchical Bayesian model for predicting small-strain stiffness of sand
Authors: Tao Yuanqin , Phoon Kok-Kwang , Sun Honglei , Cai Yuanqiang
Published: July 2023

This paper develops a hierarchical Bayesian model (HBM) that integrates the physical knowledge and the test data to predict the small-strain shear modulus Gmax for a target sand type. The limited target-specific data are combined with the abundant generic data through a hierarchical structure so that the variability of Gmax within one sand type and across different sand types can be captured. The hyperparameters that characterize the same underlying distribution of physical model parameters across all the sand types are first estimated from the abundant generic data. The model parameters for the new sand type are then updated as the limited site-specific data become available. The approach is illustrated using a generic database and two real examples not covered by the generic database. Multiple possible hierarchical models are compared in terms of model complexity and goodness-of-fit. The results show that the hierarchical modeling of small-strain shear modulus data is reasonable and necessary. The hierarchical model can provide less biased and more accurate predictions of Gmax compared to the commonly used complete pooling model, especially in cases where the site-specific data are quite different from the overall average of the generic database.
Python API Misuse Mining and Classification Based on Hybrid Analysis and Attention Mechanism
Authors: He Xincheng , Liu Xiaojin , Xu Lei
Published: July 2023

APIs play a crucial role in contemporary software development, streamlining implementation and maintenance processes. However, improper API usage can result in significant issues such as unexpected outcomes, security vulnerabilities and system crashes. To detect API misuses, current methods primarily rely on comparing established API usage patterns with target points for automated detection, mainly based on pre-validated datasets. Nonetheless, there is a scarcity of publicly available datasets on API misuses and their corresponding fixes, which hinders data-driven research. Moreover, most existing techniques concentrate on statically typed languages, such as Java and C, with only a few addressing dynamic languages like Python effectively, due to difficulties in handling dynamic features. Therefore, it is essential to identify Python API misuses and their fixes automatically and promptly. In this paper, we introduce HatPAM, a Hybrid Analysis and Attention-based Python API-Misuse Miner, which (a) provides a method for automatically mining true-positive commits related to Python API-misuse fixes from GitHub and (b) presents the subsequent processing for classifying Python API misuses in true-positive cases. Particularly, HatPAM applies hybrid static analysis and introduces a structure-based attention mechanism to examine syntax, semantics and structural features in Python code context, and considers the consistency between code and developers’ natural intent to significantly reduce false-positive cases. Evaluation on six popular Python projects reveals that HatPAM outperforms various state-of-the-art baselines, achieving up to 92.2% Precision, 86.7% Recall and 89.3% F1-score, indicating its capability to identify and classify Python API-misuse commits.
The generalized weakly Ricci symmetric structure
Authors: Kundu Haradhan , Baishya Kanak Kanti , Roy Indranil
Published: July 2023

This paper attempts to study some geometric properties along with the existence of a generalized weakly Ricci symmetric manifold and find out the reduced form of defining conditions of such a manifold. It is observed that every generalized weakly Ricci symmetric manifold is an almost generalized pseudo-Ricci symmetric manifold. We also find out the conditions for which a weakly Ricci symmetric manifold becomes a Ricci pseudosymmetric manifold in the sense of Deszcz.
Formal Specification, Verification and Repair of Contiki’s Scheduler
Authors: Mousavi Hassan , Ebnenasir Ali , Mahmoudzadeh Elham
Published: July 2023

This article presents an approach for model extraction, formal specification, verification, and repair of the scheduler of Contiki, which is an event-driven lightweight operating system for the Internet of Things (IoT). We first derive a state machine–based abstraction of the scheduler’s modes of operation along with the control flow abstractions of the scheduler’s most important functions. We then use a set of transformation rules to formally specify the scheduler and all its internal functions in Promela. Additional contributions with respect to the conference version of this article include (1) modeling nested function calls in the Promela model of the scheduler using a novel technique amenable to model checking in SPIN; (2) modeling protothreads in Promela; (3) specifying and formally verifying 12 critical requirements of the scheduler; (4) detecting new design flaws in Contiki’s scheduler for the first time (to the best of our knowledge); (5) repairing the model and the source code of Contiki’s scheduler towards fixing the flaws detected through verification, as well as regression verification of the entire model of the scheduler; and (6) experimentally analyzing the time and space costs of verification before and after repair. The proposed formal model of Contiki’s scheduler along with novel modeling techniques enhance our knowledge regarding the most critical components of Contiki and provide reusable methods for formal specification and verification of other event-driven operating systems used in Cyber Physical Systems (CPSs) and the IoT.
Soft Delivery: Survey on a New Paradigm for Wireless and Mobile Multimedia Streaming
Authors: Fujihashi Takuya , Koike-Akino Toshiaki , Watanabe Takashi
Published: July 2023

The increasing demand for video streaming services is the key driver of modern wireless and mobile communications. Although many studies have designed digital-based delivery schemes to send video content over wireless and mobile networks, significant quality degradation, known as cliff and leveling effects, often occurs owing to fluctuating channel characteristics. In this article, we present a comprehensive summary of soft delivery, which is a new paradigm for wireless and mobile video streaming and discuss the future directions of soft delivery. Existing studies found that introducing multi-dimensional cosine transform, human vision system, and graph signal processing can make soft delivery schemes more effective in untethered immersive experiences, including virtual reality and volumetric media, than digital-based delivery schemes. In addition, this study finds that soft delivery has the potential to be a new standard to deliver deep neural network models and tactile information over wireless and mobile networks.
Adonis
: Practical and Efficient Control Flow Recovery through OS-level Traces
Authors: Liu Xuanzhe , Yang Chengxu , Li Ding , Zhou Yuhan , Li Shaofei , Chen Jiali , Chen Zhenpeng
Published: July 2023

Control flow recovery is critical to promise the software quality, especially for large-scale software in production environment. However, the efficiency of most current control flow recovery techniques is compromised due to their runtime overheads along with deployment and development costs. To tackle this problem, we propose a novel solution,
Adonis
, which harnesses
Operating System (OS)
-level traces, such as dynamic library calls and system call traces, to efficiently and safely recover control flows in practice.
Adonis
operates in two steps: It first identifies the call-sites of trace entries, and then it executes a pairwise symbolic execution to recover valid execution paths. This technique has several advantages. First,
Adonis
does not require the insertion of any probes into existing applications, thereby minimizing
runtime cost
. Second, given that OS-level traces are hardware-independent,
Adonis
can be implemented across various hardware configurations without the need for hardware-specific engineering efforts, thus reducing
deployment cost
. Third, as
Adonis
is fully automated and does not depend on manually created logs, it circumvents additional
development cost
. We conducted an evaluation of
Adonis
on representative desktop applications and real-world IoT applications.
Adonis
can faithfully recover the control flow with 86.8% recall and 81.7% precision. Compared to the state-of-the-art log-based approach,
Adonis
can not only cover all the execution paths recovered but also recover 74.9% of statements that cannot be covered. In addition, the runtime cost of
Adonis
is 18.3× lower than the instrument-based approach; the analysis time and storage cost (indicative of the deployment cost) of
Adonis
is 50× smaller and 443× smaller than the hardware-based approach, respectively. To facilitate future replication and extension of this work, we have made the code and data publicly available.
GraphPrior: Mutation-based Test Input Prioritization for Graph Neural Networks
Authors: Dang Xueqi , Li Yinghua , Papadakis Mike , Klein Jacques , Bissyandé Tegawendé F. , Le Traon Yves
Published: July 2023

Graph Neural Networks (GNNs) have achieved promising performance in a variety of practical applications. Similar to traditional DNNs, GNNs could exhibit incorrect behavior that may lead to severe consequences, and thus testing is necessary and crucial. However, labeling all the test inputs for GNNs can be costly and time-consuming, especially when dealing with large and complex graphs, which seriously affects the efficiency of GNN testing. Existing studies have focused on test prioritization for DNNs, which aims to identify and prioritize fault-revealing tests (i.e., test inputs that are more likely to be misclassified) to detect system bugs earlier in a limited time. Although some DNN prioritization approaches have been demonstrated effective, there is a significant problem when applying them to GNNs: They do not take into account the connections (edges) between GNN test inputs (nodes), which play a significant role in GNN inference. In general, DNN test inputs are independent of each other, while GNN test inputs are usually represented as a graph with complex relationships between each test. In this article, we propose GraphPrior (
GNN
-oriented Test
Prior
itization), a set of approaches to prioritize test inputs specifically for GNNs via mutation analysis. Inspired by mutation testing in traditional software engineering, in which test suites are evaluated based on the mutants they kill, GraphPrior generates mutated models for GNNs and regards test inputs that kill many mutated models as more likely to be misclassified. Then, GraphPrior leverages the mutation results in two ways, killing-based and feature-based methods. When scoring a test input, the killing-based method considers each mutated model equally important, while feature-based methods learn different importance for each mutated model through ranking models. Finally, GraphPrior ranks all the test inputs based on their scores. We conducted an extensive study based on 604 subjects to evaluate GraphPrior on both natural and adversarial test inputs. The results demonstrate that KMGP, the killing-based GraphPrior approach, outperforms the compared approaches in a majority of cases, with an average improvement of 4.76% ~49.60% in terms of APFD. Furthermore, the feature-based GraphPrior approach, RFGP, performs the best among all the GraphPrior approaches. On adversarial test inputs, RFGP outperforms the compared approaches across different adversarial attacks, with the average improvement of 2.95% ~46.69%.
Investigating the Effects of EMGBF Combined with Different Motion Directions on Improving Upper Limb Function, iEMC, and Pain in Patients with Shoulder Dislocation
Authors: Wu Di , Xu Jing , Lan Xiufang
Published: July 2023

The dislocation of the shoulder is a common complication of stroke, which is easy to occur after 3 months of stroke, with an incidence of 70%. There is no single standard for the pathogenesis of the disease, but the atrophy of the associated stability muscle, such as the triangle muscle, the oblique, and the upper muscle of the gonfield, may be the cause of the disease. In order to observe the effects of Electromyographic Biofeedback (EMGBF) combined with different motion directions on upper limb function with shoulder dislocation, a total of 84 patients with shoulder dislocation from May 2020 to February 2022 are selected for the study. The experimental results show that after treatment, upper limb motor function, iEMC, pain score, Barthel index, and quality of life score in the observation group are significantly higher than those in the control group, with statistical significance.
Salivary Biomarkers: Noninvasive Ways for Diagnosis of Parkinson’s Disease
Authors: Salaramoli Sanaz , Joshaghani Hamid Reza , Hashemy Seyed Isaac
Published: July 2023

Finding reliable biomarkers has a crucial role in Parkinson’s disease (PD) assessments. Saliva is a bodily fluid, which might be used as a source of biomarkers for PD. Our article has reviewed several publications on salivary proteins in PD patients and their potential as biomarkers. We find out that α-Syn’s proportion in oligomeric form is higher in PD patients’ saliva, which is potent to use as a biomarker for PD. The salivary concentration of DJ-1 and alpha-amylase is lower in PD patients. Also, substance P level is more moderate in PD patients. Although salivary flow rate is decreased in PD patients, high levels of heme oxygenase and acetylcholinesterase might be used as noninvasive biomarkers. Salivary miRNAs (miR-153, miR-223, miR-874, and miR-145-3p) are novel diagnostic biomarkers that should be given more attention.
COVID-19-Associated Thrombotic Complication: Is It Pulmonary Embolism or In Situ Thrombosis?
Authors: Umairi Rashid AL , Adawi Khadija AL , Khoori Maryam AL , Lawati Ahmed AL , Jose Sachin
Published: July 2023

Objectives. Acute pulmonary embolism is a protentional fatal complication of COVID-19. The aim of this study is to investigate whether pulmonary embolism is due to thrombus migration from the venous circulation to the pulmonary arteries or due to local thrombus formation secondary to local inflammation. This was determined by looking at the distribution of pulmonary embolism in relation to lung parenchymal changes in patients with COVID-19 pneumonia. Methods. Retrospectively, we identified pulmonary computed tomography angiography (CTPA) of patients admitted to the Royal Hospital between November 1st, 2020, and October 31, 2021, with a confirmed diagnosis of COVID-19. The CTPAs were examined for the presence of pulmonary embolism and the distribution of the pulmonary embolism in relation with lung parenchymal changes. Results. A total of 215 patients admitted with COVID-19 pneumonia had CTPA. Out of them, 64 patients had pulmonary embolisms (45 men and 19 women; mean age: 58.4 years with a range of 36–98 years). The prevalence of pulmonary embolism (PE) was 29.8% (64/215). Pulmonary embolism was more frequently seen in the lower lobes. 51 patients had PE within the diseased lung parenchyma and 13 patients had PE within normal lung parenchyma. Conclusion. The strong association between pulmonary artery embolism and lung parenchymal changes in patients admitted with COVID-19 pneumonia suggests local thrombus formation.
Spectrum-Effect Relationship between HPLC Fingerprint and Anti-Inflammatory and Analgesic Activities of Chloranthus fortunei (A. Gray) Solms-Laub
Authors: Shi Junhao , Qiu Qin , Lu Xianxing , Zhen Dandan , Liu Xiaofang , Gu Baojun , Qin Chunping , Mo Huiqing , Li Pengfei , Zhen Hanshen
Published: July 2023

The predominant objective of the research is to establish the anti-inflammatory and analgesic spectrum-effect relationship of Chloranthus fortunei (A. Gray) Solms-Laub (CF), to reveal the pharmacodynamic basis of the anti-inflammatory and analgesic effects of CF. The fingerprints of ten batches of CF from various origins were established by high-performance liquid chromatography (HPLC) and evaluated for similarity, hierarchical cluster analysis (HCA), and principal component analysis (PCA). The anti-inflammatory and analgesic effects of CF were evaluated with the xylene-induced ear swelling in mice and the acetic acid torsion test, while the anti-inflammatory and analgesic spectrum-effect relationship of CF was evaluated by gray relational analysis (GRA) and partial least squares regression analysis (PLSR) to effectively elucidate the anti-inflammatory and analgesic substance basis of CF. The ten batches of CF HPLC fingerprints established in this work successfully identified a total of 13 common peaks that refer to 4 components, with peak 1 being neochlorogenic acid, peak 3 being chlorogenic acid, peak 5 being cryptochlorogenic acid, and peak 10 being rosmarinic acid. The HCA results presented that the ten batches of CF samples were clustered into 3 categories, which was consistent with the PCA results. Simultaneously, the results of the spectrum-effect relationship also indicated that neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, and rosmarinic acid were the possible anti-inflammatory and analgesic substances of CF. In order to better understand the anti-inflammatory and analgesic substance basis of CF, this experiment established the anti-inflammatory and analgesic spectrum-effect relationship of CF, which can provide a scientific foundation for the quality evaluation and further research as well as the usage of CF herbs.
Multimodal Fake News Detection Incorporating External Knowledge and User Interaction Feature
Authors: Fu Lifang , Liu Shuai
Published: July 2023

With the development of online social media, the number of various news has exploded. While social media provides an information platform for news release and dissemination, it also makes fake news proliferate, which may cause potential social risks. How to detect fake news quickly and accurately is a difficult task. The multimodal fusion fake news detection model is the current research focus and development trend. However, in terms of content, most existing methods lack the mining of background knowledge hidden in the news content and ignore the connection between background knowledge and existing knowledge system. In terms of the propagation chain, the research tends to emphasize only the single chain from the previous communication node, ignoring the intricate communication chain and the mutual influence relationship among users. To address these problems, this paper proposes a multimodal fake news detection model, A-KWGCN, based on knowledge graph and weighted graph convolutional network (GCN). The model fully extracted the features of the content and the interaction between users of the news dissemination. On the one hand, the model mines relevant knowledge concepts from the news content and links them with the knowledge entities in the wiki knowledge graph, and integrates knowledge entities and entity context as auxiliary information. On the other hand, inspired by the “similarity effect” in social psychology, this paper constructs a user interaction network and defines the weighted GCN by calculating the feature similarity among users to analyze the mutual influence of users. Two public datasets, Twitter15 and Twitter16, are selected to evaluate the model, and the accuracy reaches 0.905 and 0.930, respectively. In the comparison experiments, A-KWGCN model has more significant advantages than the other six comparison models in four evaluation indexes. Also, ablation experiments are conducted to verify that knowledge module and weighted GCN module play the significant role in the detection of fake news.
A serious game about Covid-19: design and evaluation study
Authors: Bouroumane Farida , Abarkan Mustapha
Published: July 2023

As many countries experience the emergence of new waves of Covid-19, many governments around the world have reminded their citizens of the need for an engaging intervention that could improve compliance with Covid-19 safe behaviors using the media general public or social media. In the face of the serious threat of Covid-19, immunity issues are currently the subject of various research and studies. A promising approach is to use video game culture to educate and train citizens to healthily adopt eating habits to strengthen the immune system. The objective of this study is to develop a prototype of a serious game (SG) on how to strengthen the immune defenses in order to be able to fight a coronavirus infection and to constitute an anti-virus barrier. After defining the learning objectives by interviewing the stakeholders, we searched the scientific literature to establish the relevant theoretical bases. The learning contents have been validated by biology teachers. The learning mechanisms were then determined based on the learning objectives. The obtained experimental results show that 92% of the participants in the study have appreciated the quality of the scenario and the way in which the concept of interaction between the different game elements was presented.
Improved distribution and food safety for beef processing and management using a blockchain-tracer support framework
Authors: Adimabua Ojugo Arnold , Ogholuwarami Ejeh Patrick , Chukwufunaya Christopher Odiakaose , Okonji Eboka Andrew , Uchechukwu Emordi Frances
Published: July 2023

Agriculture has since become a major source of livelihood for Nigerians. It also accounts for over 85% of the total food consumed within her borders. The sector has maintained improved productivity and profitability via a concerted effort to address critical issues such as an unorganized regulatory system, lack of food safety data, no standards in agricultural produce, non-adaptation to precision farming, and non-harmony via inventory trace supports. This study proposes blockchain-based trace-support in a continued effort to ensure food quality, consumer safety, and trading of food assets. It uses the radio frequency identification (RFID) sensor to register and track livestocks, farms/farmers, and abattoir processes as well as provisions a databank to trace livestock data. Results show the model adequately perform about 1,101 transactions per seconds with a response time of 0.21 s for queries and 0.28 s for https pages respectively for 2,500 users. Also, it yields a slightly longer time of 0.32 s for queries and 0.38 s for https pages respectively with an increased 5,000 users via the world-state as stored in the blockchain’s hyper-fabric ledger. Overall, the framework can directly query and retrieve data without it traversing the whole ledger. This, in turn, improves the efficiency and effectiveness of the traceability system.
Acceleration of convolutional neural network based diabetic retinopathy diagnosis system on field programmable gate array
Authors: Dhouibi Meriam , Ben Salem Ahmed Karim , Saidi Afef , Ben Saoud Slim
Published: July 2023

Diabetic retinopathy (DR) is one of the most common causes of blindness. The necessity for a robust and automated DR screening system for regular examination has long been recognized in order to identify DR at an early stage. In this paper, an embedded DR diagnosis system based on convolutional neural networks (CNNs) has been proposed to assess the proper stage of DR. We coupled the power of CNN with transfer learning to design our model based on state-of-the-art architecture. We preprocessed the input data, which is color fundus photography, to reduce undesirable noise in the image. After training many models on the dataset, we chose the adopted ResNet50 because it produced the best results, with a 92.90% accuracy. Extensive experiments and comparisons with other research work show that the proposed method is effective. Furthermore, the CNN model has been implemented on an embedded target to be a part of a medical instrument diagnostic system. We have accelerated our model inference on a field programmable gate array (FPGA) using Xilinx tools. Results have confirmed that a customized FPGA system on chip (SoC) with hardware accelerators is a promising target for our DR detection model with high performance and low power consumption.
CNN inference acceleration on limited resources FPGA platforms_epilepsy detection case study
Authors: Saidi Afef , Ben Othman Slim , Dhouibi Meriam , Ben Saoud Slim
Published: July 2023

The use of a convolutional neural network (CNN) to analyze and classify electroencephalogram (EEG) signals has recently attracted the interest of researchers to identify epileptic seizures. This success has come with an enormous increase in the computational complexity and memory requirements of CNNs. For the sake of boosting the performance of CNN inference, several hardware accelerators have been proposed. The high performance and flexibility of the field programmable gate array (FPGA) make it an efficient accelerator for CNNs. Nevertheless, for resource-limited platforms, the deployment of CNN models poses significant challenges. For an ease of CNN implementation on such platforms, several tools and frameworks have been made available by the research community along with different optimization techniques. In this paper, we proposed an FPGA implementation for an automatic seizure detection approach using two CNN models, namely VGG-16 and ResNet-50. To reduce the model size and computation cost, we exploited two optimization approaches: pruning and quantization. Furthermore, we presented the results and discussed the advantages and limitations of two implementation alternatives for the inference acceleration of quantized CNNs on Zynq-7000: an advanced RISC machine (ARM) software implementation-based ARM, NN, software development kit (SDK) and a software/hardware implementation-based deep learning processor unit (DPU) accelerator and DNNDK toolkit.