Defendroid: real-time Android code vulnerability detection via blockchain federated neural network with XAI

Ensuring strict adherence to security during the phases of Android app development is essential, primarily due to the prevalent issue of apps being released without adequate security measures in place. While a few automated tools are employed to reduce potential vulnerabilities during development, their effectiveness in detecting vulnerabilities may fall short. To address this, “Defendroid”, a blockchain-based federated neural network enhanced with Explainable Artificial Intelligence (XAI) is introduced in this work. Trained on the LVDAndro dataset, the vanilla neural network model achieves a 96% accuracy and 0.96 F1-Score in binary classification for vulnerability detection. Additionally, in multi-class classification, the model accurately identifies Common Weakness Enumeration (CWE) categories with a 93% accuracy and 0.91 F1-Score. In a move to foster collaboration and model improvement, the model has been deployed within a blockchain-based federated environment. This environment enables community-driven collaborative training and enhancements in partnership with other clients. The extended model demonstrates improved accuracy of 96% and F1-Score of 0.96 in both binary and multi-class classifications. The use of XAI plays a pivotal role in presenting vulnerability detection results to developers, offering prediction probabilities for each word within the code. This model has been integrated into an Application Programming Interface (API) as the backend and further incorporated into Android Studio as a plugin, facilitating real-time vulnerability detection. Notably, Defendroid exhibits high efficiency, delivering prediction probabilities for a single code line in an average processing time of a mere 300 ms. The weight-sharing transparency in the blockchain-driven federated model enhances trust and traceability, fostering community engagement while preserving source code privacy and contributing to accuracy improvement

Android source code vulnerability detection: a systematic literature review

The use of mobile devices is rising daily in this technological era. A continuous and increasing number of mobile applications are constantly offered on mobile marketplaces to fulfil the needs of smartphone users. Many Android applications do not address the security aspects appropriately. This is often due to a lack of automated mechanisms to identify, test, and fix source code vulnerabilities at the early stages of design and development. Therefore, the need to fix such issues at the initial stages rather than providing updates and patches to the published applications is widely recognized. Researchers have proposed several methods to improve the security of applications by detecting source code vulnerabilities and malicious codes. This Systematic Literature Review (SLR) focuses on Android application analysis and source code vulnerability detection methods and tools by critically evaluating 118 carefully selected technical studies published between 2016 and 2022. It highlights the advantages, disadvantages, applicability of the proposed techniques and potential improvements of those studies. Both Machine Learning (ML) based methods and conventional methods related to vulnerability detection are discussed while focusing more on ML-based methods since many recent studies conducted experiments with ML. Therefore, this paper aims to enable researchers to acquire in-depth knowledge in secure mobile application development while minimizing the vulnerabilities by applying ML methods. Furthermore, researchers can use the discussions and findings of this SLR to identify potential future research and development directions

Electrophysiological correlates of respiratory failure in acute organophosphate poisoning: Evidence for differential roles of muscarinic and nicotinic stimulation

Background. Respiratory failure in acute organophosphate (OP) poisoning can occur early and also relatively late in the clinical course, and the pathophysiology of respiratory failure at these different phases may have important clinical implications. Objective. To compare the electrophysiological findings in patients with early and late respiratory failure following acute OP poisoning. Methods. A prospective observational case series of consenting symptomatic patients with acute OP poisoning were assessed with daily physical examinations and repetitive nerve stimulation (RNS) studies. RNS was done on right and left median and ulnar nerves at 1, 3, 10, 15, 20, and 30 Hz. Outcomes such as need for ventilation and development of intermediate syndrome (IMS) were noted. Early respiratory failure was defined as occurring within 24 hours of ingestion. Results. Seventy-eight patients were recruited for the clinical and electrophysiological study and of those 59 (75.6%) patients had ingested chlorpyrifos. Seven patients developed respiratory failure within 24 hours of ingestion with overt muscarinic signs. They had no electrophysiological abnormalities at median and ulnar nerves before intubation. Three of them later developed “forme fruste” IMS. Five other patients developed late respiratory failure after 24 hours of ingestion, and all of them showed progressive RNS changes indicating severe IMS prior to intubation. Conclusion. The normal RNS in all patients developing early respiratory failure suggests that it is due to a central nervous system (CNS) and muscarinic effect. This emphasizes the need for early rapid atropinisation as a priority, combating the nicotinic effects being less urgent. This is in contrast with the late respiratory failure, which has been shown to be associated with neuromuscular dysfunction. Further studies are needed to quantify CNS and muscarinic dysfunction to assist in the development of better treatments for the severe and early OP poisoning

Association of endometriosis and p53 gene codon 72 polymorphism in a group of Sri Lankan women

Objectives: To evaluate the association between endometriosis and the p53 gene polymorphism in a group of Sri Lankan women.Methods: A case control study was conducted in a tertiary care hospital where women with endometriosis (N=25) were compared with women without endometriosis (N=25), both confirmed by laparoscopy or laparotomy. Genotype distribution of the p53 codon 72 polymorphism was analyzed by allele specific polymerase chain reaction and direct sequencing. Allele frequency was compared using chi square test to determine the association.Results: Allele frequencies of the three p53 genotypes, Arg/Arg, Arg/Pro and Pro/Pro in the study population (26%, 60% and 14% respectively) conformed with the Hardy-Weinberg equilibrium. There was no statistically significant difference (p = 0.155) in the frequency of proline allele between the cases and controls {odds ratio of 1.5 (95% CI 0.83- 2.73)}. However among the women with endometriosis the proline allele frequency was 36.7% in stage IV and 50% in stage III compared to 25% and 16.7% respectively in stages II and I.Conclusions: In this group of Sri Lankan women, p53 codon 72 polymorphism was not associated with endometriosis although a higher frequency of proline allele was observed in advanced stages of the disease.

Prompt engineering for digital mental health: a short review

Prompt engineering, the process of arranging input or prompts given to a large language model to guide it in producing desired outputs, is an emerging field of research that shapes how these models understand tasks, process information, and generate responses in a wide range of natural language processing (NLP) applications. Digital mental health, on the other hand, is becoming increasingly important for several reasons including early detection and intervention, and to mitigate limited availability of highly skilled medical staff for clinical diagnosis. This short review outlines the latest advances in prompt engineering in the field of NLP for digital mental health. To our knowledge, this review is the first attempt to discuss the latest prompt engineering types, methods, and tasks that are used in digital mental health applications. We discuss three types of digital mental health tasks: classification, generation, and question answering. To conclude, we discuss the challenges, limitations, ethical considerations, and future directions in prompt engineering for digital mental health. We believe that this short review contributes a useful point of departure for future research in prompt engineering for digital mental health

Cancer survivor preferences for breast cancer follow-up care: A discrete choice experiment

Purpose: To identify the key attributes of breast cancer follow-up care models preferred by cancer survivors in Australia. Methods: A discrete choice experiment (DCE) was conducted to elicit preferences for attributes of breast cancer follow-up care. Respondents were presented with two hypothetical scenarios, known as choice sets, and asked to select a preference. Respondents were individuals living in Australia who were diagnosed with breast cancer within the past five years prior to survey completion and were recruited through the Breast Cancer Network of Australia and other community or consumer networks. Latent class modelling (LCM) approach under a random utility framework was used for the analysis. Results: 123 breast cancer survivors completed the DCE survey. LCA revealed two latent classes, those with older age and lower quality of life (class 1) and younger women with higher quality of life (class 2). Class 2 preferred a care team comprising specialists, nurses and GPs and emphasised the importance of shared survivorship care plans. Class 1 remained neutral regarding the team’s composition but was notably concerned about the out-of-pocket costs per consultation, a finding not seen in Class 2. Conclusions: Age and quality of life status are associated with patient preference for types and attributes of breast cancer follow-up care. The health system can work towards enhancing flexibility of follow-up care delivery, ultimately achieving person-centred care. Implications for cancer survivors. Efforts need to be made by policymakers to ensure consumer preferences are taken into consideration to implement tailored person-centred follow-up care pathways

Characterisation and evaluation of paramagnetic fluorine labelled glycol chitosan conjugates for 19F and 1H magnetic resonance imaging

Medium molecular weight glycol chitosan conjugates have been prepared, linked by an amide bond to paramagnetic Gd(III), Ho(III) and Dy(III) macrocyclic complexes in which a trifluoromethyl reporter group is located 6.5 Å from the paramagnetic centre. The faster relaxation of the observed nucleus allows modified pulse sequences to be used with shorter acquisition times. The polydisperse materials have been characterised by gel permeation chromatography, revealing an average molecular weight on the order of 13,800 (Gd), 14,600 (Dy) and 16,200 (Ho), consistent with the presence of 8.5, 9.5 and 13 complexes, respectively. The gadolinium conjugate was prepared for both a q = 1 monoamide tricarboxylate conjugate (r 1p 11.2 mM−1 s−1, 310 K, 1.4 T) and a q = 0 triphosphinate system, and conventional contrast-enhanced proton MRI studies at 7 T were undertaken in mice bearing an HT-29 or an HCT-116 colorectal tumour xenograft (17 μmol/kg). Enhanced contrast was observed following injection in the tail vein in tumour tissue, with uptake also evident in the liver and kidney with a tumour-to-liver ratio of 2:1 at 13 min, and large amounts in the kidney and bladder consistent with predominant renal clearance. Parallel experiments observing the 19F resonance in the holmium conjugate complex using a surface coil did not succeed owing to its high R 2 value (750 Hz, 7 T). However, the fluorine signal in the dysprosium triphosphinate chitosan conjugate [R 1/R 2 = 0.6 and R 1 = 145 Hz (7 T)] was sharper and could be observed in vivo at −65.7 ppm, following intravenous tail vein injection of a dose of 34 μmol/kg

Identification of Highly Selective Surface Pathways for Methane Dry Reforming Using Mechanochemical Synthesis of Pd-CeO2

The methane dry reforming (DRM) reaction mechanism was explored via mechanochemically prepared Pd/CeO2 catalysts (PdAcCeO2M), which yield unique Pd-Ce interfaces, where PdAcCeO2M has a distinct reaction mechanism and higher reactivity for DRM relative to traditionally synthesized impregnated Pd/CeO2 (PdCeO2IW). In situ characterization and density functional theory calculations revealed that the enhanced chemistry of PdAcCeO2M can be attributed to the presence of a carbon-modified Pd0 and Ce4+/3+ surface arrangement, where distinct Pd-CO intermediate species and strong Pd-CeO2 interactions are activated and sustained exclusively under reaction conditions. This unique arrangement leads to highly selective and distinct surface reaction pathways that prefer the direct oxidation of CHx to CO, identified on PdAcCeO2M using isotope labeled diffuse reflectance infrared Fourier transform spectroscopy and highlighting linear Pd-CO species bound on metallic and C-modified Pd, leading to adsorbed HCOO [1595 cm-1] species as key DRM intermediates, stemming from associative CO2 reduction. The milled materials contrast strikingly with surface processes observed on IW samples (PdCeO2IW) where the competing reverse water gas shift reaction predominates

Location and content of counselling and acceptance of postpartum IUD in Sri Lanka

Background: The immediate postpartum IUD (PPIUD) is a long-acting, reversible method of contraception that can be used safely and effectively following a birth. To appropriately facilitate the immediate postpartum insertion of IUDs, women must be informed of the method’s availability and must be counselled on its benefits and risks prior to entering the delivery room. We examine the relationship between the location and quality of antenatal counselling and women’s acceptance of immediate postpartum IUD (PPIUD) in four hospitals in Sri Lanka. Methods: Data were collected between January 2015 and May 2015. Modified Poisson regressions with robust standard errors are used to assess the relationships between place of counselling, indicators of counselling quality, and PPIUD uptake following delivery. Results: We find that women who were counselled in hospital antenatal clinics and admission wards were much more likely to have a PPIUD inserted than women who were counselled in field clinics or during home visits. Hospital-based counselling had higher quality indicators for providing information on PPIUD, and women were more likely to receive PPIUD information leaflets in hospital locations than in lower-tiered clinics or during home visits. Women who were counselled at hospital locations also reported a higher level of satisfaction with the counselling that they received. Receipt of hospital-based counselling was also linked to higher PPIUD uptake, in spite of the fact that women were more likely to be given information about the risks and alternatives to PPIUD in hospitals. The information about the risks of and alternatives to PPIUD, whether provided in hospital or in non-hospital settings, tended to lower the likelihood of acceptance to have a PPIUD insertion. Counselling in hospital admission wards was focused on women who had not been counselled at field clinics. Conclusions: The study findings call for efforts that improve the training of midwives who provide PPIUD counselling at field clinics and during the home visits. We also recommend that routine PPIUD counselling be conducted in hospitals, even if women have already been counselled elsewhere