Search results for: automated fraud detection

Authors: Fathi Kallel, Abdulelah Alabd Uljabbar, Abdulrahman Aldukhail, Abdulaziz Alomran

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The brain is an important organ in our body since it is responsible about the majority actions such as vision, memory, etc. However, different diseases such as Alzheimer and tumors could affect the brain and conduct to a partial or full disorder. Regular diagnosis are necessary as a preventive measure and could help doctors to early detect a possible trouble and therefore taking the appropriate treatment, especially in the case of brain tumors. Different imaging modalities are proposed for diagnosis of brain tumor. The powerful and most used modality is the Magnetic Resonance Imaging (MRI). MRI images are analyzed by doctor in order to locate eventual tumor in the brain and describe the appropriate and needed treatment. Diverse image processing methods are also proposed for helping doctors in identifying and analyzing the tumor. In fact, a large Computer Aided Diagnostic (CAD) tools including developed image processing algorithms are proposed and exploited by doctors as a second opinion to analyze and identify the brain tumors. In this paper, we proposed a new advanced CAD for brain tumor identification, classification and feature extraction. Our proposed CAD includes three main parts. Firstly, we load the brain MRI. Secondly, a robust technique for brain tumor extraction is proposed. This technique is based on both Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA). DWT is characterized by its multiresolution analytic property, that’s why it was applied on MRI images with different decomposition levels for feature extraction. Nevertheless, this technique suffers from a main drawback since it necessitates a huge storage and is computationally expensive. To decrease the dimensions of the feature vector and the computing time, PCA technique is considered. In the last stage, according to different extracted features, the brain tumor is classified into either benign or malignant tumor using Support Vector Machine (SVM) algorithm. A CAD tool for brain tumor detection and classification, including all above-mentioned stages, is designed and developed using MATLAB guide user interface.

Keywords: MRI, brain tumor, CAD, feature extraction, DWT, PCA, classification, SVM

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Authors: Diana A. Sokolova

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This article is devoted to one of the possibilities for identifying the author of an oral or written text - sociolinguistic profiling. Sociolinguistic profiling is utilized as a forensic linguistics technique to identify individuals through language patterns, particularly in criminal cases. It examines how social factors influence language use. This study aims to showcase the significance of linguistic profiling for attributing authorship in texts and emphasizes the necessity for its continuous enhancement while considering its strengths and weaknesses. The study employs semantic-syntactic, lexical-semantic, linguopragmatic, logical, presupposition, authorization, and content analysis methods to investigate linguistic profiling. The research highlights the relevance of sociolinguistic profiling in authorship attribution and underscores the importance of ongoing refinement of the technique, considering its limitations. This study emphasizes the practical application of linguistic profiling in legal settings and underscores the impact of social factors on language use, contributing to the field of forensic linguistics. Data collection involves collecting oral and written texts from criminal and civil court cases to analyze language patterns for authorship attribution. The collected data is analyzed using various linguistic analysis methods to identify individual characteristics and patterns that can aid in authorship attribution. The study addresses the effectiveness of sociolinguistic profiling in identifying authors of texts and explores the impact of social factors on language use in legal contexts. In spite of advantages challenges in linguistics profiling have spurred debates and controversies in academic circles, legal environments, and the public sphere. So, this research highlights the significance of sociolinguistic profiling in authorship attribution and emphasizes the need for further development of this method, considering its strengths and weaknesses.

Keywords: authorship attribution, detection of identifying, dialect, features, forensic linguistics, social influence, sociolinguistics, unique speech characteristics

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Authors: Won Hyuck Kim, Chang Hwan Kim, Hyun Wook Kim, Myoung Hoon Lee, Chan Hong Park, Hyeon Yeong Park

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We conducted submarine topography & beach survey from December 2015 and January 2016 using multi-beam echo sounder EM3001(Kongsberg corporation) & Shipborne Mobile LiDAR System. Our survey area were the Anmok beach in Gangneung, South Korea. We made Shipborne Mobile LiDAR System for these survey. Shipborne Mobile LiDAR System includes LiDAR (RIEGL LMS-420i), IMU ((Inertial Measurement Unit, MAGUS Inertial+) and RTKGNSS (Real Time Kinematic Global Navigation Satellite System, LEIAC GS 15 GS25) for beach's measurement, LiDAR's motion compensation & precise position. Shipborne Mobile LiDAR System scans beach on the movable vessel using the laser. We mounted Shipborne Mobile LiDAR System on the top of the vessel. Before beach survey, we conducted eight circles IMU calibration survey for stabilizing heading of IMU. This exploration should be as close as possible to the beach. But our vessel could not come closer to the beach because of latency objects in the water. At the same time, we conduct submarine topography survey using multi-beam echo sounder EM3001. A multi-beam echo sounder is a device observing and recording the submarine topography using sound wave. We mounted multi-beam echo sounder on left side of the vessel. We were equipped with a motion sensor, DGNSS (Differential Global Navigation Satellite System), and SV (Sound velocity) sensor for the vessel's motion compensation, vessel's position, and the velocity of sound of seawater. Shipborne Mobile LiDAR System was able to reduce the consuming time of beach survey rather than previous conventional methods of beach survey.

Keywords: Anmok, beach survey, Shipborne Mobile LiDAR System, submarine topography

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Authors: William Michael Short

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Semantic Web’ technologies such as the Unified Medical Language System Metathesaurus, SNOMED-CT, and MeSH have been touted as transformational for the way users access online medical and health information, enabling both the automated analysis of natural-language data and the integration of heterogeneous healthrelated resources distributed across the Internet through the use of standardized terminologies that capture concepts and relationships between concepts that are expressed differently across datasets. However, the approaches that have so far characterized ‘semantic bioinformatics’ have not yet fulfilled the promise of the Semantic Web for medical and health information retrieval applications. This paper argues within the perspective of cognitive linguistics and cognitive anthropology that four features of human meaning-making must be taken into account before the potential of semantic technologies can be realized for this domain. First, many semantic technologies operate exclusively at the level of the word. However, texts convey meanings in ways beyond lexical semantics. For example, transitivity patterns (distributions of active or passive voice) and modality patterns (configurations of modal constituents like may, might, could, would, should) convey experiential and epistemic meanings that are not captured by single words. Language users also naturally associate stretches of text with discrete meanings, so that whole sentences can be ascribed senses similar to the senses of words (so-called ‘discourse topics’). Second, natural language processing systems tend to operate according to the principle of ‘one token, one tag’. For instance, occurrences of the word sound must be disambiguated for part of speech: in context, is sound a noun or a verb or an adjective? In syntactic analysis, deterministic annotation methods may be acceptable. But because natural language utterances are typically characterized by polyvalency and ambiguities of all kinds (including intentional ambiguities), such methods leave the meanings of texts highly impoverished. Third, ontologies tend to be disconnected from everyday language use and so struggle in cases where single concepts are captured through complex lexicalizations that involve profile shifts or other embodied representations. More problematically, concept graphs tend to capture ‘expert’ technical models rather than ‘folk’ models of knowledge and so may not match users’ common-sense intuitions about the organization of concepts in prototypical structures rather than Aristotelian categories. Fourth, and finally, most ontologies do not recognize the pervasively figurative character of human language. However, since the time of Galen the widespread use of metaphor in the linguistic usage of both medical professionals and lay persons has been recognized. In particular, metaphor is a well-documented linguistic tool for communicating experiences of pain. Because semantic medical knowledge-bases are designed to help capture variations within technical vocabularies – rather than the kinds of conventionalized figurative semantics that practitioners as well as patients actually utilize in clinical description and diagnosis – they fail to capture this dimension of linguistic usage. The failure of semantic technologies in these respects degrades the efficiency and efficacy not only of medical research, where information retrieval inefficiencies can lead to direct financial costs to organizations, but also of care provision, especially in contexts of patients’ self-management of complex medical conditions.

Keywords: ambiguity, bioinformatics, language, meaning, metaphor, ontology, semantic web, semantics

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Authors: Anshika Kankane, Dongshik Kang

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Marine debris has a significant influence on coastal environments, damaging biodiversity, and causing loss and damage to marine and ocean sector. A functional cost-effective and automatic approach has been used to look up at this problem. Computer vision combined with a deep learning-based model is being proposed to identify and categorize marine debris of seven kinds on different beach locations of Japan. This research compares state-of-the-art deep learning models with a suggested model architecture that is utilized as a feature extractor for debris categorization. The model is being proposed to detect seven categories of litter using a manually constructed debris dataset, with the help of Mask R-CNN for instance segmentation and a shape matching network called HOGShape, which can then be cleaned on time by clean-up organizations using warning notifications of the system. The manually constructed dataset for this system is created by annotating the images taken by fixed KaKaXi camera using CVAT annotation tool with seven kinds of category labels. A pre-trained HOG feature extractor on LIBSVM is being used along with multiple templates matching on HOG maps of images and HOG maps of templates to improve the predicted masked images obtained via Mask R-CNN training. This system intends to timely alert the cleanup organizations with the warning notifications using live recorded beach debris data. The suggested network results in the improvement of misclassified debris masks of debris objects with different illuminations, shapes, viewpoints and litter with occlusions which have vague visibility.

Keywords: computer vision, debris, deep learning, fixed live camera images, histogram of gradients feature extractor, instance segmentation, manually annotated dataset, multiple template matching

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Authors: Saule Mussabekova

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Recent advances in genetics have allowed increasing acutely the capacities of the formation of reliable evidence in conducting forensic examinations. Thus, traces of biological origin are important sources of information about a crime. Currently, around the world, sexual offenses have increased, and among them are those in which the criminals use various detergents to remove traces of their crime. A feature of modern synthetic detergents is the presence of biological additives - enzymes. Enzymes purposefully destroy stains of biological origin. To study the nature and extent of the impact of modern washing powders on saliva stains on the physical evidence, specially prepared test specimens of different types of tissues to which saliva was applied have been examined. Materials and Methods: Washing machines of famous manufacturers of household appliances have been used with different production characteristics and advertised brands of washing powder for test washing. Over 3,500 experimental samples were tested. After washing, the traces of saliva were identified using modern research methods of forensic medicine. Results: The influence was tested and the dependence of the use of different washing programs, types of washing machines and washing powders in the process of establishing saliva trace and identify of the stains on the physical evidence while washing was revealed. The results of experimental and practical expert studies have shown that in most cases it is not possible to draw the conclusions in the identification of saliva traces on physical evidence after washing. This is a consequence of the effect of biological additives and other additional factors on traces of saliva during washing. Conclusions: On the basis of the results of the study, the feasibility of saliva traces of the stains on physical evidence after washing is established. The use of modern molecular genetic methods makes it possible to partially solve the problems arising in the study of unlaundered evidence. Additional study of physical evidence after washing facilitates detection and investigation of sexual offenses against women and children.

Keywords: saliva research, modern synthetic detergents, laundry detergents, forensic medicine

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Authors: Teodora Vukovic, Christoph Hottiger, Noah Bubenhofer

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The development of VIAN-DH aims at bridging two linguistic approaches: conversation analysis/interactional linguistics (IL), so far a dominantly qualitative field, and computational/corpus linguistics and its quantitative and automated methods. Contemporary IL investigates the systematic organization of conversations and interactions composed of speech, gaze, gestures, and body positioning, among others. These highly integrated multimodal behaviour is analysed based on video data aimed at uncovering so called “multimodal gestalts”, patterns of linguistic and embodied conduct that reoccur in specific sequential positions employed for specific purposes. Multimodal analyses (and other disciplines using videos) are so far dependent on time and resource intensive processes of manual transcription of each component from video materials. Automating these tasks requires advanced programming skills, which is often not in the scope of IL. Moreover, the use of different tools makes the integration and analysis of different formats challenging. Consequently, IL research often deals with relatively small samples of annotated data which are suitable for qualitative analysis but not enough for making generalized empirical claims derived quantitatively. VIAN-DH aims to create a workspace where many annotation layers required for the multimodal analysis of videos can be created, processed, and correlated in one platform. VIAN-DH will provide a graphical interface that operates state-of-the-art tools for automating parts of the data processing. The integration of tools that already exist in computational linguistics and computer vision, facilitates data processing for researchers lacking programming skills, speeds up the overall research process, and enables the processing of large amounts of data. The main features to be introduced are automatic speech recognition for the transcription of language, automatic image recognition for extraction of gestures and other visual cues, as well as grammatical annotation for adding morphological and syntactic information to the verbal content. In the ongoing instance of VIAN-DH, we focus on gesture extraction (pointing gestures, in particular), making use of existing models created for sign language and adapting them for this specific purpose. In order to view and search the data, VIAN-DH will provide a unified format and enable the import of the main existing formats of annotated video data and the export to other formats used in the field, while integrating different data source formats in a way that they can be combined in research. VIAN-DH will adapt querying methods from corpus linguistics to enable parallel search of many annotation levels, combining token-level and chronological search for various types of data. VIAN-DH strives to bring crucial and potentially revolutionary innovation to the field of IL, (that can also extend to other fields using video materials). It will allow the processing of large amounts of data automatically and, the implementation of quantitative analyses, combining it with the qualitative approach. It will facilitate the investigation of correlations between linguistic patterns (lexical or grammatical) with conversational aspects (turn-taking or gestures). Users will be able to automatically transcribe and annotate visual, spoken and grammatical information from videos, and to correlate those different levels and perform queries and analyses.

Keywords: multimodal analysis, corpus linguistics, computational linguistics, image recognition, speech recognition

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Authors: P. Joshna, Souvik Kundu

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Detection of ultraviolet (UV) radiation is very important as it has exhibited a profound influence on humankind and other existences, including military equipment. In this work, a self-powered UV photodetector was reported based on oxides heterojunctions. The thin films of p-type nickel oxide (NiO) and n-type reduced graphene oxide (rGO) were used for the formation of p-n heterojunction. Low-Cost and low-temperature chemical synthesis was utilized to prepare the oxides, and the spin coating technique was employed to deposit those onto indium doped tin oxide (ITO) coated glass substrates. The top electrode platinum was deposited utilizing physical vapor evaporation technique. NiO offers strong UV absorption with high hole mobility, and rGO prevents the recombination rate by separating electrons out from the photogenerated carriers. Several structural characterizations such as x-ray diffraction, atomic force microscope, scanning electron microscope were used to study the materials crystallinity, microstructures, and surface roughness. On one side, the oxides were found to be polycrystalline in nature, and no secondary phases were present. On the other side, surface roughness was found to be low with no pit holes, which depicts the formation of high-quality oxides thin films. Whereas, x-ray photoelectron spectroscopy was employed to study the chemical compositions and oxidation structures. The electrical characterizations such as current-voltage and current response were also performed on the device to determine the responsivity, detectivity, and external quantum efficiency under dark and UV illumination. This p-n heterojunction device offered faster photoresponse and high on-off ratio under 365 nm UV light illumination of zero bias. The device based on the proposed architecture shows the efficacy of the oxides heterojunction for efficient UV photodetection under zero bias, which opens up a new path towards the development of self-powered photodetector for environment and health monitoring sector.

Keywords: chemical synthesis, oxides, photodetectors, spin coating

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Authors: Milena Nanova, Martin Georgiev, Radul Shishkov, Damyan Damov

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Modern residential architecture is increasingly influenced by rapid urbanization, technological advancements, and growing investor expectations. The integration of AI and digital tools such as CAD and BIM (Building Information Modelling) are transforming the design process by improving efficiency, accuracy, and speed. However, urban development faces challenges, including the high competition for viable sites and the time-consuming nature of traditional investment feasibility studies and architectural planning. Finding and analysing suitable sites for residential development is complicated by intense competition and rising investor demands. Investors require quick assessments of property potential to avoid missing opportunities, while traditional architectural design processes are relying on experience of the team and can be time consuming, adding pressure to make fast, effective decisions. The widespread use of CAD tools has sped up the drafting process, enhancing both accuracy and efficiency. Digital tools allow designers to manipulate drawings quickly, reducing the time spent on revisions. BIM further advances this by enabling native 3D modelling, where changes to a design in one view are automatically reflected in all others, minimizing errors and saving time. AI is becoming an integral part of architectural design software. While AI is currently being incorporated into existing programs like AutoCAD, Revit, and ArchiCAD, its full potential is reached in parametric modelling. In this process, designers define parameters (e.g., building size, layout, and materials), and the software generates multiple design variations based on those inputs. This method accelerates the design process by automating decisions and enabling quick generation of alternative solutions. The study utilizes generative design, a specific application of parametric modelling which uses AI to explore a wide range of design possibilities based on predefined criteria. It optimizes designs through iterations, testing many variations to find the best solutions. This process is particularly beneficial in the early stages of design, where multiple options are explored before refining the best ones. AI’s ability to handle complex mathematical tasks allows it to generate unconventional yet effective designs that a human designer might overlook. Residential architecture, with its anticipated and typical layouts and modular nature, is especially suitable for generative design. The relationships between rooms and the overall organization of apartment units follow logical patterns, making it an ideal candidate for parametric modelling. Using these tools, architects can quickly explore various apartment configurations, considering factors like apartment sizes, types, and circulation patterns, and identify the most efficient layout for a given site. Parametric modelling and generative design offer significant benefits to residential architecture by streamlining the design process, enabling faster decision-making, and optimizing building layouts. These technologies allow architects and developers to analyse numerous design possibilities, improving outcomes while responding to the challenges of urban development. By integrating AI-driven generative design, the architecture industry can enhance creativity, efficiency, and adaptability in residential projects.

Keywords: architectural design, residential buildings, generative design, parametric models, workflow optimization

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Authors: Guillaume Lemahieu, Matthias Sentis, Giovanni Brambilla, Gérard Meunier

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Static Multiple Light Scattering (SMLS) has been shown to be a straightforward technique for the characterization of colloidal dispersions without dilution, as multiply scattered light in backscattered and transmitted mode is directly related to the concentration and size of scatterers present in the sample. In this view, the use of SMLS for stability measurement of various dispersion types has already been widely described in the literature. Indeed, starting from a homogeneous dispersion, the variation of backscattered or transmitted light can be attributed to destabilization phenomena, such as migration (sedimentation, creaming) or particle size variation (flocculation, aggregation). In a view to investigating more on the dispersibility of colloidal suspensions, an experimental set-up for “at the line” SMLS experiment has been developed to understand the impact of the formulation parameters on particle size and dispersibility. The SMLS experiment is performed with a high acquisition rate (up to 10 measurements per second), without dilution, and under direct agitation. Using such experimental device, SMLS detection can be combined with the Hansen approach to optimize the dispersing and stabilizing properties of TiO₂ particles. It appears that the dispersibility and the stability spheres generated are clearly separated, arguing that lower stability is not necessarily a consequence of poor dispersibility. Beyond this clarification, this combined SMLS-Hansen approach is a major step toward the optimization of dispersibility and stability of colloidal formulations by finding solvents having the best compromise between dispersing and stabilizing properties. Such study can be intended to find better dispersion media, greener and cheaper solvents to optimize particles suspensions, reduce the content of costly stabilizing additives or satisfy product regulatory requirements evolution in various industrial fields using suspensions (paints & inks, coatings, cosmetics, energy).

Keywords: dispersibility, stability, Hansen parameters, particles, solvents

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Authors: Eric Jacob Bacon, Chaoyang Jin, Dianning He, Shuaishuai Hu, Lanbo Wang, Han Li, Shouliang Qi

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Objective: Refractory epilepsy is a complicated type of epilepsy that can be difficult to diagnose. Recent technological advancements have made resting-state functional magnetic resonance (rsfMRI) a vital technique for studying brain activity. However, there is still much to learn about rsfMRI. Investigating rsfMRI connectivity may aid in the detection of abnormal activities. In this paper, we propose studying the functional connectivity of rsfMRI candidates to diagnose epilepsy. Methods: 45 rsfMRI candidates, comprising 26 with refractory epilepsy and 19 healthy controls, were enrolled in this study. A data-driven approach known as independent component analysis (ICA) was used to achieve our goal. First, rsfMRI data from both patients and healthy controls were analyzed using group ICA. The components that were obtained were then spatially sorted to find and select meaningful ones. A two-sample t-test was also used to identify abnormal networks in patients and healthy controls. Finally, based on the fractional amplitude of low-frequency fluctuations (fALFF), a chi-square statistic test was used to distinguish the network properties of the patient and healthy control groups. Results: The two-sample t-test analysis yielded abnormal in the default mode network, including the left superior temporal lobe and the left supramarginal. The right precuneus was found to be abnormal in the dorsal attention network. In addition, the frontal cortex showed an abnormal cluster in the medial temporal gyrus. In contrast, the temporal cortex showed an abnormal cluster in the right middle temporal gyrus and the right fronto-operculum gyrus. Finally, the chi-square statistic test was significant, producing a p-value of 0.001 for the analysis. Conclusion: This study offers evidence that investigating rsfMRI connectivity provides an excellent diagnosis option for refractory epilepsy.

Keywords: ICA, RSN, refractory epilepsy, rsfMRI

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Authors: Randa M. Ali, Naguiba F. Loutfy, Osama M. Awad

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Background: Leishmaniasis is a worldwide disease, affecting 88 countries, it is estimated that about 350 million people are at risk of leishmaniasis. Overall prevalence is 12 million people with annual mortality of about 60,000. Annual incidence is 1,500,000 cases of cutaneous leishmaniasis (CL) worldwide and half million cases of visceral Leishmaniasis (VL). Objectives: The objective of this study was to assess primary health care physicians knowledge (PHP) and attitude about leishmaniasis and to assess awareness of local inhabitants about the disease and its vector in four areas in west Alexandria, Egypt. Methods: This study was a cross sectional survey that was conducted in four PHC units in west Alexandria. All physicians currently working in these units during the study period were invited to participate in the study, only 20 PHP completed the questionnaire. 60 local inhabitant were selected randomly from the four areas of the study, 15 from each area; Data was collected through two different specially designed questionnaires. Results: 11(55%) percent of the physicians had satisfactory knowledge, they answered more than 9 (60%) questions out of a total 14 questions about leishmaniasis and sandfly. The second part of the questionnaire is concerned with attitude of the primary health care physicians about leishmaniasis, 17 (85%) had good attitude and 3 (15%) had poor attitude. The second questionnaire showed that the awareness of local inhabitants about leishmaniasis and sandly as a vector of the disease is poor and needs to be corrected. Most of the respondents (90%) had not heard about leishmaniasis, Only 3 (5%) of the interviewed inhabitants said they know sandfly and its role in transmission of leishmaniasis. Conclusions: knowledge and attitudes of physicians are acceptable. However, there is, room for improvement and could be done through formal training courses and distribution of guidelines. In addition to raising the awareness of primary health care physicians about the importance of early detection and notification of cases of lesihmaniasis. Moreover, health education for raising awareness of the public regarding the vector and the disease is necessary because related studies have demonstrated that if the inhabitants do not perceive mosquitoes to be responsible for diseases such as malaria they do not take enough measures to protect themselves against the vector.

Keywords: leishmaniasis, PHP, knowledge, attitude, local inhabitants

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Authors: Hung-Sheng Lin, Cheng-Hsuan Li

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Over the past few years, kernel-based algorithms have been widely used to extend some linear feature extraction methods such as principal component analysis (PCA), linear discriminate analysis (LDA), and nonparametric weighted feature extraction (NWFE) to their nonlinear versions, kernel principal component analysis (KPCA), generalized discriminate analysis (GDA), and kernel nonparametric weighted feature extraction (KNWFE), respectively. These nonlinear feature extraction methods can detect nonlinear directions with the largest nonlinear variance or the largest class separability based on the given kernel function. Moreover, they have been applied to improve the target detection or the image classification of hyperspectral images. The double nearest proportion feature extraction (DNP) can effectively reduce the overlap effect and have good performance in hyperspectral image classification. The DNP structure is an extension of the k-nearest neighbor technique. For each sample, there are two corresponding nearest proportions of samples, the self-class nearest proportion and the other-class nearest proportion. The term “nearest proportion” used here consider both the local information and other more global information. With these settings, the effect of the overlap between the sample distributions can be reduced. Usually, the maximum likelihood estimator and the related unbiased estimator are not ideal estimators in high dimensional inference problems, particularly in small data-size situation. Hence, an improved estimator by shrinkage estimation (regularization) is proposed. Based on the DNP structure, LDA is included as a special case. In this paper, the kernel method is applied to extend DNP to kernel-based DNP (KDNP). In addition to the advantages of DNP, KDNP surpasses DNP in the experimental results. According to the experiments on the real hyperspectral image data sets, the classification performance of KDNP is better than that of PCA, LDA, NWFE, and their kernel versions, KPCA, GDA, and KNWFE.

Keywords: feature extraction, kernel method, double nearest proportion feature extraction, kernel double nearest feature extraction

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Authors: P. Bauer, K. Mougin, V. Vignal, A. Buch, P. Ponthiaux, D. Faye

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Nowadays, noble metallic nanostructures with unique morphology are widely used as new sensors due to their fascinating optical, electronic and catalytic properties. Among various shapes, dendritic nanostructures have attracted much attention because of their large surface-to-volume ratio, high sensitivity and special texture with sharp tips and nanoscale junctions. Several methods have been developed to fabricate those specific structures such as electrodeposition, photochemical way, seed-mediated growth or wet chemical method. The present study deals with a novel approach for a controlled growth pattern-directed organisation of Au flower-like crystals (NFs) deposited onto stainless steel plates to achieve large-scale functional surfaces. This technique consists in the deposition of a soft nanoporous template on which Au NFs are grown by electroplating and seed-mediated method. Size, morphology, and interstructure distance have been controlled by a site selective nucleation process. Dendritic Au nanostructures have appeared as excellent Raman-active candidates due to the presence of very sharp tips of multi-branched Au nanoparticles that leads to a large local field enhancement and a good SERS sensitivity. In addition, these structures have also been used as electrochemical sensors to detect traces of molecules present in a solution. A correlation of the number of active sites on the surface and the current charge by both colorimetric method and cyclic voltammetry of gold structures have allowed a calibration of the system. This device represents a first step for the fabrication of MEMs platform that could ultimately be integrated into a lab-on-chip system. It also opens pathways to several technologically large-scale nanomaterials fabrication such as hierarchically ordered crystal architectures for sensor applications.

Keywords: dendritic, electroplating, gold, template

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Authors: Susana Aragoneses Garrido

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Every day, the roads are scenery of numerous accidents involving vehicles, producing thousands of deaths and serious injuries all over the world. Investigations have revealed that Human Factors (HF) are one of the main causes of road accidents in modern societies. Distracted driving (including external or internal aspects of the vehicle), which is considered as a human factor, is a serious and emergent risk to road safety. Consequently, a further analysis regarding this issue is essential due to its transcendence on today’s society. The objectives of this investigation are the detection and assessment of the HF in order to provide solutions (including a better vehicle design), which might mitigate road accidents. The methodology of the project is divided in different phases. First, a statistical analysis of public databases is provided between Spain and The UK. Second, data is classified in order to analyse the major causes involved in road accidents. Third, a simulation between different paths and vehicles is presented. The causes related to the HF are assessed by Failure Mode and Effects Analysis (FMEA). Fourth, different car models are evaluated using the Rapid Upper Body Assessment (RULA). Additionally, the JACK SIEMENS PLM tool is used with the intention of evaluating the Human Factor causes and providing the redesign of the vehicles. Finally, improvements in the car design are proposed with the intention of reducing the implication of HF in traffic accidents. The results from the statistical analysis, the simulations and the evaluations confirm that accidents are an important issue in today’s society, especially the accidents caused by HF resembling distractions. The results explore the reduction of external and internal HF through the global analysis risk of vehicle accidents. Moreover, the evaluation of the different car models using RULA method and the JACK SIEMENS PLM prove the importance of having a good regulation of the driver’s seat in order to avoid harmful postures and therefore distractions. For this reason, a car redesign is proposed for the driver to acquire the optimum position and consequently reducing the human factors in road accidents.

Keywords: analysis vehicles, asssesment, ergonomics, car redesign

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Authors: Lorenzo Cocola, Massimo Fedel, Dragiša Savić, Bojana Danilović, Luca Poletto

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An instrument for the detection and evaluation of gaseous carbon dioxide in the headspace of closed containers has been developed in the context of Packsensor Italian-Serbian joint project. The device is based on Tunable Diode Laser Absorption Spectroscopy (TDLAS) with a Wavelength Modulation Spectroscopy (WMS) technique in order to accomplish a non-invasive measurement inside closed containers of fermented dairy products (yogurts and fermented cheese in cups and bottles). The purpose of this instrument is the continuous monitoring of carbon dioxide concentration during incubation and storage of products over a time span of the whole shelf life of the product, in the presence of different microorganisms. The instrument’s optical front end has been designed to be integrated in a thermally stabilized incubator. An embedded computer provides processing of spectral artifacts and storage of an arbitrary set of calibration data allowing a properly calibrated measurement on many samples (cups and bottles) of different shapes and sizes commonly found in the retail distribution. A calibration protocol has been developed in order to be able to calibrate the instrument on the field also on containers which are notoriously difficult to seal properly. This calibration protocol is described and evaluated against reference measurements obtained through an industry standard (sampling) carbon dioxide metering technique. Some sets of validation test measurements on different containers are reported. Two test recordings of carbon dioxide concentration evolution are shown as an example of instrument operation. The first demonstrates the ability to monitor a rapid yeast growth in a contaminated sample through the increase of headspace carbon dioxide. Another experiment shows the dissolution transient with a non-saturated liquid medium in presence of a carbon dioxide rich headspace atmosphere.

Keywords: TDLAS, carbon dioxide, cups, headspace, measurement

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Authors: Taha Enes Kon, Vanshika Reddy

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This project focuses on developing a gamified mobile application to aid in stroke rehabilitation by enhancing motor skills through interactive activities. The primary goal was to design a companion app for a passive haptic rehab glove, incorporating Google MediaPipe for gesture tracking and vibrotactile feedback. The app simulates farming activities, offering a fun and engaging experience while addressing the monotony of traditional rehabilitation methods. The prototype focuses on a single minigame, Flower Picking, which uses gesture recognition to interact with virtual elements, encouraging users to perform exercises that improve hand dexterity. The development process involved creating accessible and user-centered designs using Figma, integrating gesture recognition algorithms, and implementing unity-based game mechanics. Real-time feedback and progressive difficulty levels ensured a personalized experience, motivating users to adhere to rehabilitation routines. The prototype achieved a gesture detection precision of 90%, effectively recognizing predefined gestures such as the Fist and OK symbols. Quantitative analysis highlighted a 40% increase in average session duration compared to traditional exercises, while qualitative feedback praised the app’s immersive design and ease of use. Despite its success, challenges included rigidity in gesture recognition, requiring precise hand orientations, and limited gesture support. Future improvements include expanding gesture adaptability and incorporating additional minigames to target a broader range of exercises. The project demonstrates the potential of gamification in stroke rehabilitation, offering a scalable and accessible solution that complements clinical treatments, making recovery engaging and effective for users.

Keywords: stroke rehabilitation, haptic feedback, gamification, MediaPipe, motor control

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Authors: Ahmed Abdullah Ahmed

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The task of recognizing the writer of a handwritten text has been an attractive research problem in the document analysis and recognition community with applications in handwriting forensics, paleography, document examination and handwriting recognition. This research presents an automatic method for writer recognition from digitized images of unconstrained writings. Although a great effort has been made by previous studies to come out with various methods, their performances, especially in terms of accuracy, are fallen short, and room for improvements is still wide open. The proposed technique employs optimal codebook based writer characterization where each writing sample is represented by a set of features computed from two codebooks, beginning and ending. Unlike most of the classical codebook based approaches which segment the writing into graphemes, this study is based on fragmenting a particular area of writing which are beginning and ending strokes. The proposed method starting with contour detection to extract significant information from the handwriting and the curve fragmentation is then employed to categorize the handwriting into Beginning and Ending zones into small fragments. The similar fragments of beginning strokes are grouped together to create Beginning cluster, and similarly, the ending strokes are grouped to create the ending cluster. These two clusters lead to the development of two codebooks (beginning and ending) by choosing the center of every similar fragments group. Writings under study are then represented by computing the probability of occurrence of codebook patterns. The probability distribution is used to characterize each writer. Two writings are then compared by computing distances between their respective probability distribution. The evaluations carried out on ICFHR standard dataset of 206 writers using Beginning and Ending codebooks separately. Finally, the Ending codebook achieved the highest identification rate of 98.23%, which is the best result so far on ICFHR dataset.

Keywords: off-line text-independent writer identification, feature extraction, codebook, fragments

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Authors: Stoyanka Vladeva, Elena Kirilova, Nikola Kirilov

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Background: The creatinine clearance is a widely used value to estimate the GFR. Increased creatinine clearance is often called hyperfiltration and is usually seen during pregnancy, patients with diabetes mellitus preceding the diabetic nephropathy. It may also occur with large dietary protein intake or with plasma volume expansion. Renal injury in lupus nephritis is known to affect the glomerular, tubulointerstitial, and vascular compartment. However high creatinine clearance has not been found in patients with SLE, Target: Follow-up of creatinine clearance values in patients with systemic lupus erythematosus without history of kidney injury. Material and methods: We observed the creatinine, creatinine clearance, GFR and dipstick protein values of 7 women (with a mean age of 42.71 years) with systemic lupus erythematosus. Patients with active lupus have been monthly tested in the period of 13 months. Creatinine clearance has been estimated by Cockcroft-Gault Equation formula in ml/sec. GFR has been estimated by MDRD formula (The Modification of Diet in renal Disease) in ml/min/1.73 m2. Proteinuria has been defined as present when dipstick protein > 1+.Results: In all patients without history of kidney injury we found elevated creatinine clearance levels, but GFRremained within the reference range. Two of the patients were in remission while the other five patients had clinically and immunologically active Lupus. Three of the patients had a permanent presence of high creatinine clearance levels and proteinuria. Two of the patients had periodically elevated creatinine clearance without proteinuria. These results show that kidney disturbances may be caused by the vascular changes typical for SLE. Glomerular hyperfiltration can be result of focal segmental glomerulosclerosis caused by a reduction in renal mass. Probably lupus nephropathy is preceded not only by glomerular vascular changes, but also by tubular vascular changes. Using only the GFR is not a sufficient method to detect these primary functional disturbances. Conclusion: For early detection of kidney injury in patients with SLE we determined that the follow up of creatinine clearance values could be helpful.

Keywords: systemic Lupus erythematosus, kidney injury, elevated creatinine clearance level, normal glomerular filtration rate

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Authors: Rashmi Tomar, A. Srinivasan, Nayan K. Mohanty, Arun K. Jain

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Phthalates have been used as additives in industrial products since the 1930s, and are universally considered to be ubiquitous environmental contaminants. The general population is exposed to phthalates through consumer products, as well as diet and medical treatments. Animal studies showing the existence of an association between some phthalates and testicular toxicity have generated public and scientific concern about the potential adverse effects of environmental changes on male reproductive health. Unprecedented declines in fertility rates and semen quality have been reported during the last half of the 20th century in developed countries and increasing interest exists on the potential relationship between exposure to environmental contaminants, including phthalates, and human male reproductive health Studies. Phthalates may be associated with altered endocrine function and adverse effects on male reproductive development and function, but human studies are limited. The aim of the present study was detection of phthalate compounds, estimation of their metabolites in infertile & fertile male. Blood and urine samples were collected from 150 infertile patients & 75 fertile volunteers recruited through Department of Urology, Safdarjung Hospital, New Delhi. Blood have been collected in separate glass tubes from the antecubital vein of the patients, serum have been separate and estimate the phthalate level in serum samples by Gas Chromatography / Mass Spectrometry using NIOSH / OSHA detailed protocol. Urine of Infertile & Fertile Subjects was collected & extracted using solid phase extraction method, analysis by HPLC. In conclusion, to the best of our knowledge the present study based on human is first to show the presence of phthalate in human serum samples and their metabolites in urine samples. Significant differences were observed between several phthalates in infertile and fertile healthy individuals.

Keywords: Gas Chromatography, HPLC, male infertility, phthalates, serum, toxicity, urine

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Authors: Mitiku Tefera

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Background: Meconium-stained amniotic fluid is one of the primary causes of birth asphyxia. Each year, over five million neonatal deaths occur worldwide due to meconium-stained amniotic fluid, with 90% of these deaths due to birth asphyxia. In Ethiopia meconium-stained amniotic fluid is under investigated, specifically in North Shoa Zone Amhara region Ethiopia. Objective: The aim of this study was to assess the magnitude of meconium-stained amniotic fluid and associated factors among women who gave birth in the North Shoa Zone Hospital’s Amhara Region, Ethiopia, in 2022. Methods: An institutional-based, cross-sectional study was conducted among 628 women who gave birth at North Shoa Zone Hospitals, Amhara, Ethiopia. The study was conducted from 08/June-08/August 2022. Two-stage cluster sampling was used to recruit study participants. The data was collected by using a structured interview-administered questionnaire and chart review. The collected data was entered into Epi-Data Version 4.6 and exported to SPSS Version 25. Logistics regression was employed, and a p-value <0.05 was considered significant. Result: The magnitude of meconium-stained amniotic fluid was 30.3%. Women presented with normal hematocrit level 83% less likely develop meconium-stained amniotic fluid. Women had mid-upper arm circumference value was less than 22.9cm(AOR=1.9; 95% CI;1.18-3.20), obstructed labor(AOR=3.6; 95% CI;1.48-8.83), prolonged labor ≥ 15hr (AOR=7.5; 95% CI ;7.68-13.3), the premature rapture of the membrane (AOR=1.7; 95% CI; 3.22-7.40), fetal tachycardia(AOR=6.2; 95% CI; 2.41-16.3) and Bradycardia (AOR=3.1; 95% CI;1.93-5.28) were significant association with meconium stained amniotic fluid. Conclusion: The magnitude of meconium-stained amniotic fluid, which was high. In this study, MUAC value <22.9 cm, obstructed and prolonged labor, PROM, bradycardia, and tachycardia were factors associated with meconium-stained amniotic fluid. A follow-up study and pooled similar articles will be mentioned for better evidence, enhancing intrapartum services and strengthening early detection of meconium-stained amniotic fluid for the health of the mother and baby.

Keywords: women, meconium-staned amniotic fluid, magnitude, Ethiopia

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Authors: Michaela Storen, Michelle Harvey, Xavier Conlan

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Gun violence internationally is increasing at an unprecedented level, becoming a favoured means for executing violence against another individual. Not only is this putting a strain on forensic scientists who attempt to determine the cause of death in circumstances where firearms have been involved in the death of an individual, but it also highlights the need for an alternative technique of identification of a gunshot wound when other established techniques have been exhausted. A corpse may be colonized by necrophagous insects following death, and this close association between the time of death and insect colonization makes entomological samples valuable evidence when remains become decomposed beyond toxicological utility. Entomotoxicology provides the potential for the identification of toxins in a decomposing corpse, with recent research uncovering the capabilities of entomotoxicology to detect gunshot residue (GSR) in a corpse. However, shortcomings of the limited literature available on this topic have not been addressed, with the bioaccumulation, detection limits, and sensitivity to gunshots not considered thus far, leaving questions as to the applicability of this new technique in the forensic context. Larvae were placed on meat contaminated with GSR at different concentrations and compared to a control meat sample to establish the uptake of GSR by the larvae, with bioaccumulation established by placing the larvae on fresh, uncontaminated meat for a period of time before analysis using ICP-MS. The findings of Pb, Ba, and Sb at each stage of the lifecycle and bioaccumulation in the larvae will be presented. In addition, throughout these previously mentioned experiments, larvae were washed once, twice and three times to evaluate the effectiveness of existing entomological practices in removing external toxins from specimens prior to entomotoxicologyical analysis. Analysis of these larval washes will be presented. By addressing these points, this research extends the utility of entomotoxicology in cause-of-death investigations and provides an additional source of evidence for forensic scientists in the circumstances involving a gunshot wound on a corpse, in addition to advising the effectiveness of current entomology collection protocols.

Keywords: bioaccumulation, chemistry, entomology, gunshot residue, toxicology

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Authors: Ana Londral, Burcu Demiray, Marcus Cheetham

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Speech recording is a methodology used in many different studies related to cognitive and behaviour research. Modern advances in digital equipment brought the possibility of continuously recording hours of speech in naturalistic environments and building rich sets of sound files. Speech analysis can then extract from these files multiple features for different scopes of research in Language and Communication. However, tools for analysing a large set of sound files and automatically extract relevant features from these files are often inaccessible to researchers that are not familiar with programming languages. Manual analysis is a common alternative, with a high time and efficiency cost. In the analysis of long sound files, the first step is the voice segmentation, i.e. to detect and label segments containing speech. We present a comprehensive methodology aiming to support researchers on voice segmentation, as the first step for data analysis of a big set of sound files. Praat, an open source software, is suggested as a tool to run a voice detection algorithm, label segments and files and extract other quantitative features on a structure of folders containing a large number of sound files. We present the validation of our methodology with a set of 5000 sound files that were collected in the daily life of a group of voluntary participants with age over 65. A smartphone device was used to collect sound using the Electronically Activated Recorder (EAR): an app programmed to record 30-second sound samples that were randomly distributed throughout the day. Results demonstrated that automatic segmentation and labelling of files containing speech segments was 74% faster when compared to a manual analysis performed with two independent coders. Furthermore, the methodology presented allows manual adjustments of voiced segments with visualisation of the sound signal and the automatic extraction of quantitative information on speech. In conclusion, we propose a comprehensive methodology for voice segmentation, to be used by researchers that have to work with large sets of sound files and are not familiar with programming tools.

Keywords: automatic speech analysis, behavior analysis, naturalistic environments, voice segmentation

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Authors: Ralene Sim, Stefan Mueller, N. Gopalakrishna Iyer, Ngian Chye Tan, Khee Chee Soo, R. Shetty Mahalakshmi, Hiang Khoon Tan

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Background: Regional failure in nasopharyngeal carcinoma (NPC) is managed by salvage treatment in the form of neck dissection. Radical neck dissection (RND) is preferred over modified radical neck dissection (MRND) since it is traditionally believed to offer better long-term disease control. However, with the advent of more advanced imaging modalities like high-resolution Magnetic Resonance Imaging, Computed Tomography, and Positron Emission Tomography-CT scans, earlier detection is achieved. Additionally, concurrent chemotherapy also contributes to reduced tumour burden. Hence, there may be a lesser need for an RND and a greater role for MRND. With this retrospective study, the primary aim is to ascertain whether MRND, as opposed to RND, has similar outcomes and hence, whether there would be more grounds to offer a less aggressive procedure to achieve lower patient morbidity. Methods: This is a retrospective study of 66 NPC patients treated at Singapore General Hospital between 1994 to 2016 for histologically proven regional recurrence, of which 41 patients underwent RND and 25 who underwent MRND, based on surgeon preference. The type of ND performed, primary treatment mode, adjuvant treatment, and pattern of recurrence were reviewed. Overall survival (OS) was calculated using Kaplan-Meier estimate and compared. Results: Overall, the disease parameters such as nodal involvement and extranodal extension were comparable between the two groups. Comparing MRND and RND, the median (IQR) OS is 1.76 (0.58 to 3.49) and 2.41 (0.78 to 4.11) respectively. However, the p-value found is 0.5301 and hence not statistically significant. Conclusion: RND is more aggressive and has been associated with greater morbidity. Hence, with similar outcomes, MRND could be an alternative salvage procedure for regional failure in selected NPC patients, allowing similar salvage rates with lesser mortality and morbidity.

Keywords: nasopharyngeal carcinoma, neck dissection, modified neck dissection, radical neck dissection

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Authors: Angkrit Phitchayangkoon, Ar-Aishah Dadeh

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Background: A key aim of triage is to identify the patients with high risk of cardiac arrest because they require intensive monitoring, resuscitation facilities, and early intervention. We aimed to identify the predicting factors such as initial vital signs, serum pH, serum lactate level, initial capillary blood glucose, and Modified Early Warning Score (MEWS) which affect the occurrence of cardiac arrest in an emergency department (ED). Methods: We conducted a retrospective data review of ED patients in an emergency department (ED) from 1 August 2014 to 31 July 2016. Significant variables in univariate analysis were used to create a multivariate analysis. Differentiation of predicting factors between cardiac arrest patient and non-cardiac arrest patients for occurrence of cardiac arrest in an emergency department (ED) was the primary outcome. Results: The data of 527 non-trauma patients with Emergency Severity Index (ESI) 1-3 were collected. The factors found to have a significant association (P < 0.05) in the non-cardiac arrest group versus the cardiac arrest group at the ED were systolic BP (mean [IQR] 135 [114,158] vs 120 [90,140] mmHg), oxygen saturation (mean [IQR] 97 [89,98] vs 82.5 [78,95]%), GCS (mean [IQR] 15 [15,15] vs 11.5 [8.815]), normal sinus rhythm (mean 59.8 vs 30%), sinus tachycardia (mean 46.7 vs 21.7%), pH (mean [IQR] 7.4 [7.3,7.4] vs 7.2 [7,7.3]), serum lactate (mean [IQR] 2 [1.1,4.2] vs 7 [5,10.8]), and MEWS score (mean [IQR] 3 [2,5] vs 5 [3,6]). A multivariate analysis was then performed. After adjusting for multiple factors, ESI level 2 patients were more likely to have cardiac arrest in the ER compared with ESI 1 (odds ratio [OR], 1.66; P < 0.001). Furthermore, ESI 2 patients were more likely than ESI 1 patients to have cardiovascular disease (OR, 1.89; P = 0.01), heart rate < 55 (OR, 6.83; P = 0.18), SBP < 90 (OR, 3.41; P = 0.006), SpO2 < 94 (OR, 4.76; P = 0.012), sinus tachycardia (OR, 4.32; P = 0.002), lactate > 4 (OR, 10.66; P = < 0.001), and MEWS > 4 (OR, 4.86; P = 0.028). These factors remained predictive of cardiac arrest at the ED. Conclusion: The factors related to cardiac arrest in the ED are ESI 1 patients, ESI 2 patients, patients diagnosed with cardiovascular disease, SpO2 < 94, lactate > 4, and a MEWS > 4. These factors can be used as markers in the event of simultaneous arrival of many patients and can help as a pre-state for patients who have a tendency to develop cardiac arrest. The hemodynamic status and vital signs of these patients should be closely monitored. Early detection of potentially critical conditions to prevent critical medical intervention is mandatory.

Keywords: cardiac arrest, predicting factor, emergency department, emergency patient

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Authors: Gargi Prasad, Ashiho A. Mao, Deepu Vijayan, S. Mandal

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The main objective of the present study was to optimize and develop an efficient protocol for in vitro propagation of a medicinally important orchid Cephalantheropsis obcordata (Lindl.) Ormerod along with genetic stability analysis of regenerated plants. This plant has been traditionally used in Chinese folk medicine and the decoction of whole plant is known to possess anticancer activity. Nodal segments used as explants were inoculated on Murashige and Skoog (MS) medium supplemented with various concentrations of isopentenyl adenine (2iP). The rooted plants were successfully acclimatized in the greenhouse with 100% survival rate. Inter-simple sequence repeats (ISSR) markers were used to assess the genetic fidelity of in vitro raised plants and the mother plant. It was revealed that monomorphic bands showing the absence of polymorphism in all in vitro raised plantlets analyzed, confirming the genetic uniformity among the regenerants. Phytochemical analysis was done to compare the antioxidant activities and HPLC fingerprinting assay of 80% aqueous ethanol extract of the leaves and stem of in vitro and in vivo grown C. obcordata. The extracts of the plants were examined for their antioxidant activities by using free radical 1, 1-diphenyl-2-picryl hydrazyl (DPPH) scavenging method, 2,2’-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) radical scavenging ability, reducing power capacity, estimation of total phenolic content, flavonoid content and flavonol content. A simplified method for the detection of ascorbic acid, phenolic acids and flavonoids content was also developed by using reversed phase high-performance liquid chromatography (HPLC). This is the first report on the micropropagation, genetic integrity study and quantitative phytochemical analysis of in vitro regenerated plants of C. obcordata.

Keywords: Cephalantheropsis obcordata, genetic fidelity, ISSR markers, HPLC

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Authors: Thamer Alshuwaili, Yonglin Ren, Bob Du, Manjree Agarwal

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The warehouse beetle, Trogoderma variabile Ballion (Coleoptera: Dermestidae), is a major pest of packaged and processed stored products. Warehouse beetle is the common name which was given by Okumura (1972). This pest has been reported to infest 119 different commodities, and it is distributed throughout the tropical and subtropical parts of the world. Also, it is difficult to control because of the insect's ability to stay without food for long times, and it can survive for years under dry conditions and low-moisture food, and it has also developed resistance to many insecticides. The young larvae of these insects can cause damage to seeds, but older larvae prefer to feed on whole grains. The percentage of damage caused by these insects range between 30-70% in the storage. T. variabile is the species most responsible for causing significant damage in grain stores worldwide. Trogoderma spp. is a huge problem for cereal grains, and there are many countries, such as the USA, Australia, China, Kenya, Uganda and Tanzania who have specific quarantine regulations against possible importation. Also, grain stocks can be almost completely destroyed because of the massive populations the insect may develop. However, the purpose of the current research was to optimize conditions to collect volatile organic compound from Trogoderma variabile at different life stages by using headspace solid phase microextraction (SPME) coupled with gas chromatography-mass spectrometry (GC-MS) and flame ionization detection (FID). Using SPME technique to extract volatile from insects is an efficient, straightforward and nondestructive method. Result of the study shows that 15 insects were optimal number for larvae and adults. Selection of the number of insects depend on the height of the peak area and the number of peaks. Sixteen hours were optimized as the best extraction time for larvae and 8 hours was the optimal number of adults.

Keywords: Trogoderma variabile, warehouse beetle , GC-MS, Solid phase microextraction

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Authors: Geevika J. Ganegama Arachchi, Steve H. Flint, Lynn McIntyre, Cristina D. Cruz, Beatrice M. Dias-Wanigasekera, Craig Billington, J. Andrew Hudson, Anthony N. Mutukumira

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In seafood processing plants, Listeriamonocytogenes(L. monocytogenes)likely exists in a metabolically stressed state due to the nutrient-deficient environment, processing treatments such as heating, curing, drying, and freezing, and exposure to detergents and disinfectants. Stressed L. monocytogenes cells have been shown to be as pathogenic as unstressed cells. This study investigated lytic efficacy of (LiMN4L, LiMN4p, and LiMN17) which were previouslycharacterized as virulent against physiologically stressed cells of three seafood borne L. monocytogenesstrains (19CO9, 19DO3, and 19EO3).Physiologically compromised cells ofL. monocytogenesstrains were prepared by aging cultures in TrypticaseSoy Broth at 15±1°C for 72 h; heat injuringcultures at 54±1 - 55±1°C for 40 - 60 min;salt-stressing cultures in Milli-Q water were incubated at 25±1°C in darkness for three weeks; and incubating cultures in 9% (w/v) NaCl at 15±1°C for 72 h. Low concentrations of physiologically compromised cells of three L. monocytogenesstrainswere challenged in vitrowith high titre of three phages in separate experiments using Fish Broth medium (aqueous fish extract) at 15 °C in order to mimic the environment of seafood processing plant. Each phage, when present at ≈9 log10 PFU/ml, reduced late exponential phase cells of L. monocytogenes suspended in fish protein broth at ≈2-3 log10 CFU/ml to a non-detectable level (< 10 CFU/ml). Each phage, when present at ≈8.5 log10 PFU/ml, reduced both heat-injured cells present at 2.5-3.6 log10 CFU/ml and starved cells that were showed coccoid shape, present at ≈2-3 log10 CFU/ml to < 10 CFU/ml after 30 min. Phages also reduced salt-stressed cellspresent at ≈3 log10 CFU/ml by > 2 log10. L. monocytogenes (≈8 log10 CFU/ml) were reduced to below the detection limit (1 CFU/ml) by the three successive phage infections over 16 h, indicating that emergence of spontaneous phage resistance was infrequent. The three virulent phages showed high decontamination potential for physiologically stressed L. monocytogenes strains from seafood processing environments.

Keywords: physiologically stressed L. monocytogenes, heat injured, seafood processing environment, virulent phage

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Authors: Agoston Restas

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Introduction: This paper describes many initiatives and shows also practical examples which happened recently using Unmanned Aerial Systems (UAS) to support disaster management. Since the operation of manned aircraft at disasters is usually not only expensive but often impossible to use as well, in many cases managers fail to use the aerial activity. UAS can be an alternative moreover cost-effective solution for supporting disaster management. Methods: This article uses thematic division of UAS applications; it is based on two key elements, one of them is the time flow of managing disasters, other is its tactical requirements. Logically UAS can be used like pre-disaster activity, activity immediately after the occurrence of a disaster and the activity after the primary disaster elimination. Paper faces different disasters, like dangerous material releases, floods, earthquakes, forest fires and human-induced disasters. Research used function analysis, practical experiments, mathematical formulas, economic analysis and also expert estimation. Author gathered international examples and used own experiences in this field as well. Results and discussion: An earthquake is a rapid escalating disaster, where, many times, there is no other way for a rapid damage assessment than aerial reconnaissance. For special rescue teams, the UAS application can help much in a rapid location selection, where enough place remained to survive for victims. Floods are typical for a slow onset disaster. In contrast, managing floods is a very complex and difficult task. It requires continuous monitoring of dykes, flooded and threatened areas. UAS can help managers largely keeping an area under observation. Forest fires are disasters, where the tactical application of UAS is already well developed. It can be used for fire detection, intervention monitoring and also for post-fire monitoring. In case of nuclear accident or hazardous material leakage, UAS is also a very effective or can be the only one tool for supporting disaster management. Paper shows some efforts using UAS to avoid human-induced disasters in low-income countries as part of health cooperation.

Keywords: disaster management, floods, forest fires, Unmanned Aerial Systems

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Authors: Tania Vasquez Mata, Luis A. Herrera, Cristian Arriaga Canon

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Background: Locally advanced breast cancer of the luminal B phenotype, poses challenges due to its variable response to neoadjuvant chemotherapy. A predictive biomarker is needed to identify patients who will not respond to treatment, allowing for alternative therapies. This study aims to validate the use of the lncRNA GATA3-AS1, as a predictive biomarker using RNA in situ hybridization. Research aim: The aim of this study is to determine if GATA3-AS1 can serve as a biomarker for resistance to neoadjuvant chemotherapy in patients with locally advanced luminal B breast cancer. Methodology: The study utilizes RNA in situ hybridization with predesigned probes for GATA3-AS1 on Formalin-Fixed Paraffin-Embedded tissue sections. The samples underwent pretreatment and protease treatment to enable probe penetration. Chromogenic detection and signal evaluation were performed using specific criteria. Findings: Patients who did not respond to neoadjuvant chemotherapy showed a 3+ score for GATA3-AS1, while those who had a complete response had a 1+ score. Theoretical importance: This study demonstrates the potential clinical utility of GATA3-AS1 as a biomarker for resistance to neoadjuvant chemotherapy. Identifying non-responders early on can help avoid unnecessary treatment and explore alternative therapy options. Data collection and analysis procedures: Tissue samples from patients with locally advanced luminal B breast cancer were collected and processed using RNA in situ hybridization. Signal evaluation was conducted under a microscope, and scoring was based on specific criteria. Questions addressed: Can GATA3-AS1 serve as a predictive biomarker for neoadjuvant chemotherapy response in locally advanced luminal B breast cancer? Conclusion: The lncRNA GATA3-AS1 can be used as a biomarker for resistance to neoadjuvant chemotherapy in patients with locally advanced luminal B breast cancer. Its identification through RNA in situ hybridization of tissue obtained from the initial biopsy can aid in treatment decision-making.

Keywords: biomarkers, breast neoplasms, genetics, neoadjuvant therapy, tumor

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