Search results for: human activity detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 16237

Search results for: human activity detection

15547 Data-Centric Anomaly Detection with Diffusion Models

Authors: Sheldon Liu, Gordon Wang, Lei Liu, Xuefeng Liu

Abstract:

Anomaly detection, also referred to as one-class classification, plays a crucial role in identifying product images that deviate from the expected distribution. This study introduces Data-centric Anomaly Detection with Diffusion Models (DCADDM), presenting a systematic strategy for data collection and further diversifying the data with image generation via diffusion models. The algorithm addresses data collection challenges in real-world scenarios and points toward data augmentation with the integration of generative AI capabilities. The paper explores the generation of normal images using diffusion models. The experiments demonstrate that with 30% of the original normal image size, modeling in an unsupervised setting with state-of-the-art approaches can achieve equivalent performances. With the addition of generated images via diffusion models (10% equivalence of the original dataset size), the proposed algorithm achieves better or equivalent anomaly localization performance.

Keywords: diffusion models, anomaly detection, data-centric, generative AI

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15546 Anticancer Activity of Edible Coprinus Mushroom (Coprinus comatus) on Human Glioblastoma Cell Lines and Interaction with Temozolomide

Authors: Maria Borawska, Patryk Nowakowski, Sylwia K. Naliwajko, Renata Markiewicz-Zukowska, Anna Puscion-Jakubik, Krystyna Gromkowska-Kepka, Justyna Moskwa

Abstract:

Coprinus comatus (O. F. Müll.) Pers.) should not be confused with the common Ink Cap, which contains coprine and can induce coprine poisoning. We study the possibility of applying coprinus mushroom (Coprinus comatus), available in Poland, as food product supporting the treatment of human glioblastoma cells. The U87MG and T98 glioblastoma cell lines were exposed to water (CW) or ethanol 95° (CE) Cantharellus extracts (50-500 μg/ml), with or without temozolomide (TMZ) during 24, 48 or 72 hours. The cell division was examined by the H³-thymidine incorporation. The statistical analysis was performed using Statistica v. 13.0 software. Significant differences were assumed for p < 0.05. We found that both, CW and CE, administrated alone, had inhibitory effect on cell lines growth, but the CE extract had a higher degree of growth inhibition. The anti-tumor effect of TMZ (50 μM) on U87MG was enhanced by mushroom extracts, and the effect was lower to the effect after using Coprinus comatus extracts (CW and CE) alone. A significant decrease (p < 0.05) in pro-MMP2 (82.61 ± 6.3% of control) secretion in U87MG cells was observed after treated with CE (250 μg/ml). We conclude that extracts of Coprinus comatus, edible mushroom, present cytotoxic properties on U87MG and T98 cell lines and may cooperate with TMZ synergistically enhancing its growth inhibiting activity against glioblastoma U87MG cell line.

Keywords: anticancer, glioma, mushroom, temozolomide

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15545 Isolation of Soil Thiobacterii and Determination of Their Bio-Oxidation Activity

Authors: A. Kistaubayeva, I. Savitskaya, D. Ibrayeva, M. Abdulzhanova, N. Voronova

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36 strains of sulfur-oxidizing bacteria were isolated in Southern Kazakhstan soda-saline soils and identified. Screening of strains according bio-oxidation (destruction thiosulfate to sulfate) and enzymatic (Thiosulfate dehydrogenises and thiosulfate reductase) activity was conducted. There were selected modes of aeration and culture conditions (pH, temperature), which provide optimum harvest cells. These strains can be used in bio-melioration technology.

Keywords: elemental sulfur, oxidation activity, Тhiobacilli, fertilizers, heterotrophic S-oxidizers

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15544 In vitro Antioxidant Activity of Caesalpinia sappan Extract

Authors: Monthon Tangjitmungman

Abstract:

Numerous diseases have been linked to oxidative stress, in which a disproportion of free radicals in the body leads to tissue or cell damage. Polyphenols are the most abundant antioxidants found in plants, and they are highly effective at scavenging oxidative free radicals. Due to the presence of phenolic compounds in Caesalpinia sappan has been discovered to have antioxidant activity. It has several health benefits, the most important of which is preventing cardiovascular and cancer diseases. This study aimed to determine the phenolic content and antioxidant activity of C. sappan extract using a variety of antioxidant assays. The extract of C. sappan was made using a mixture of solvents (ethyl alcohol: water in ratio 8:2). The total phenolic content of C. sappan extract was determined and expressed as gallic acid equivalents using the Folin-Cioucalteu method (GAE). The antioxidant activity of C. sappan extract was assessed using the 2, 2-diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging assay and the ABTS radical scavenging capacity assay. An association was found between antioxidant activity and total phenol content. The antioxidant activity of C. sappan extract was also determined by DPPH and ABTS assays. The IC50 values for C. sappan extract from DPPH and ABTS assays were 54.48 μg/mL ± 0.545 and 25.46 μg/mL ± 0.790, respectively, in the DPPH assay. In the DPPH assay, vitamin C was used as a positive control, whereas Trolox was used as a positive control in the ABTS assay. In conclusion, C. sappan extract contains a high level of total phenolics and exhibits significant antioxidant activity. Nevertheless, more research should be done on the antioxidant activity, such as SOD and ROS scavenging assays and in vivo experiments, to determine whether the compound has antioxidant activity.

Keywords: ABTS assay, antioxidant activity, Caesalpinia sappan, DPPH assays, total phenolic content

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15543 An Electrocardiography Deep Learning Model to Detect Atrial Fibrillation on Clinical Application

Authors: Jui-Chien Hsieh

Abstract:

Background:12-lead electrocardiography(ECG) is one of frequently-used tools to detect atrial fibrillation (AF), which might degenerate into life-threaten stroke, in clinical Practice. Based on this study, the AF detection by the clinically-used 12-lead ECG device has only 0.73~0.77 positive predictive value (ppv). Objective: It is on great demand to develop a new algorithm to improve the precision of AF detection using 12-lead ECG. Due to the progress on artificial intelligence (AI), we develop an ECG deep model that has the ability to recognize AF patterns and reduce false-positive errors. Methods: In this study, (1) 570-sample 12-lead ECG reports whose computer interpretation by the ECG device was AF were collected as the training dataset. The ECG reports were interpreted by 2 senior cardiologists, and confirmed that the precision of AF detection by the ECG device is 0.73.; (2) 88 12-lead ECG reports whose computer interpretation generated by the ECG device was AF were used as test dataset. Cardiologist confirmed that 68 cases of 88 reports were AF, and others were not AF. The precision of AF detection by ECG device is about 0.77; (3) A parallel 4-layer 1 dimensional convolutional neural network (CNN) was developed to identify AF based on limb-lead ECGs and chest-lead ECGs. Results: The results indicated that this model has better performance on AF detection than traditional computer interpretation of the ECG device in 88 test samples with 0.94 ppv, 0.98 sensitivity, 0.80 specificity. Conclusions: As compared to the clinical ECG device, this AI ECG model promotes the precision of AF detection from 0.77 to 0.94, and can generate impacts on clinical applications.

Keywords: 12-lead ECG, atrial fibrillation, deep learning, convolutional neural network

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15542 Adaptive Target Detection of High-Range-Resolution Radar in Non-Gaussian Clutter

Authors: Lina Pan

Abstract:

In non-Gaussian clutter of a spherically invariant random vector, in the cases that a certain estimated covariance matrix could become singular, the adaptive target detection of high-range-resolution radar is addressed. Firstly, the restricted maximum likelihood (RML) estimates of unknown covariance matrix and scatterer amplitudes are derived for non-Gaussian clutter. And then the RML estimate of texture is obtained. Finally, a novel detector is devised. It is showed that, without secondary data, the proposed detector outperforms the existing Kelly binary integrator.

Keywords: non-Gaussian clutter, covariance matrix estimation, target detection, maximum likelihood

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15541 USBware: A Trusted and Multidisciplinary Framework for Enhanced Detection of USB-Based Attacks

Authors: Nir Nissim, Ran Yahalom, Tomer Lancewiki, Yuval Elovici, Boaz Lerner

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Background: Attackers increasingly take advantage of innocent users who tend to use USB devices casually, assuming these devices benign when in fact they may carry an embedded malicious behavior or hidden malware. USB devices have many properties and capabilities that have become the subject of malicious operations. Many of the recent attacks targeting individuals, and especially organizations, utilize popular and widely used USB devices, such as mice, keyboards, flash drives, printers, and smartphones. However, current detection tools, techniques, and solutions generally fail to detect both the known and unknown attacks launched via USB devices. Significance: We propose USBWARE, a project that focuses on the vulnerabilities of USB devices and centers on the development of a comprehensive detection framework that relies upon a crucial attack repository. USBWARE will allow researchers and companies to better understand the vulnerabilities and attacks associated with USB devices as well as providing a comprehensive platform for developing detection solutions. Methodology: The framework of USBWARE is aimed at accurate detection of both known and unknown USB-based attacks by a process that efficiently enhances the framework's detection capabilities over time. The framework will integrate two main security approaches in order to enhance the detection of USB-based attacks associated with a variety of USB devices. The first approach is aimed at the detection of known attacks and their variants, whereas the second approach focuses on the detection of unknown attacks. USBWARE will consist of six independent but complimentary detection modules, each detecting attacks based on a different approach or discipline. These modules include novel ideas and algorithms inspired from or already developed within our team's domains of expertise, including cyber security, electrical and signal processing, machine learning, and computational biology. The establishment and maintenance of the USBWARE’s dynamic and up-to-date attack repository will strengthen the capabilities of the USBWARE detection framework. The attack repository’s infrastructure will enable researchers to record, document, create, and simulate existing and new USB-based attacks. This data will be used to maintain the detection framework’s updatability by incorporating knowledge regarding new attacks. Based on our experience in the cyber security domain, we aim to design the USBWARE framework so that it will have several characteristics that are crucial for this type of cyber-security detection solution. Specifically, the USBWARE framework should be: Novel, Multidisciplinary, Trusted, Lightweight, Extendable, Modular and Updatable and Adaptable. Major Findings: Based on our initial survey, we have already found more than 23 types of USB-based attacks, divided into six major categories. Our preliminary evaluation and proof of concepts showed that our detection modules can be used for efficient detection of several basic known USB attacks. Further research, development, and enhancements are required so that USBWARE will be capable to cover all of the major known USB attacks and to detect unknown attacks. Conclusion: USBWARE is a crucial detection framework that must be further enhanced and developed.

Keywords: USB, device, cyber security, attack, detection

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15540 A Case Study of Deep Learning for Disease Detection in Crops

Authors: Felipe A. Guth, Shane Ward, Kevin McDonnell

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In the precision agriculture area, one of the main tasks is the automated detection of diseases in crops. Machine Learning algorithms have been studied in recent decades for such tasks in view of their potential for improving economic outcomes that automated disease detection may attain over crop fields. The latest generation of deep learning convolution neural networks has presented significant results in the area of image classification. In this way, this work has tested the implementation of an architecture of deep learning convolution neural network for the detection of diseases in different types of crops. A data augmentation strategy was used to meet the requirements of the algorithm implemented with a deep learning framework. Two test scenarios were deployed. The first scenario implemented a neural network under images extracted from a controlled environment while the second one took images both from the field and the controlled environment. The results evaluated the generalisation capacity of the neural networks in relation to the two types of images presented. Results yielded a general classification accuracy of 59% in scenario 1 and 96% in scenario 2.

Keywords: convolutional neural networks, deep learning, disease detection, precision agriculture

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15539 Natural Radionuclides and Doses Assessment in Soil Samples from Agbara Industrial Estate, Ogun State, Nigeria

Authors: Ayorinde B. Ogunremi, Kehinde A. Adewoyin, Adebamwo Adebayo

Abstract:

Record of radionuclide concentration in an environment is essential to ensure human safety due to exposure to ionizing radiation. This study aimed at assessing the radionuclide concentration and doses from soil samples in the study area. Twenty soil samples were collected and dried in the oven at 110°C to remove the moisture, pulverized, and sieved. 200 g of each of the samples were sealed in cylindrical sample holders; they were left for four weeks to attain secular equilibrium between ²²⁶Ra and its decay daughters, after which the sample was analyzed using gamma-ray spectrometry. After the well-guided procedure for the calibrations, the analysis of the samples was carried out using a well-calibrated NaI (TI) and well-shielded detector coupled to a computer resident quantum MCA2100 R Multichannel analyzer for 36,000 s. The mean activity concentrations of ⁴⁰K, ²²⁶Ra, and ²³²Th obtained were calculated to be 272.37 ± 33.58, 10.97 ± 3.24, 9.39 ± 2.27 Bqkg-1 respectively. The average absorbed dose obtained was 22.10 nGy/h. The radium equivalent activity (Raeq) was estimated to be 43.27 Bq/kg. The activity concentrations (Bq/kg) were below the recommended values, which are 420, 33, and 45 for ⁴⁰K, ²²⁶Ra, and ²³²Th, respectively. Considering the results, we conclude thus, the radiation level within the estate poses no significant health risk on dwellers and workers.

Keywords: absorbed, effective, multichannel, radionuclide

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15538 Automated Computer-Vision Analysis Pipeline of Calcium Imaging Neuronal Network Activity Data

Authors: David Oluigbo, Erik Hemberg, Nathan Shwatal, Wenqi Ding, Yin Yuan, Susanna Mierau

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Introduction: Calcium imaging is an established technique in neuroscience research for detecting activity in neural networks. Bursts of action potentials in neurons lead to transient increases in intracellular calcium visualized with fluorescent indicators. Manual identification of cell bodies and their contours by experts typically takes 10-20 minutes per calcium imaging recording. Our aim, therefore, was to design an automated pipeline to facilitate and optimize calcium imaging data analysis. Our pipeline aims to accelerate cell body and contour identification and production of graphical representations reflecting changes in neuronal calcium-based fluorescence. Methods: We created a Python-based pipeline that uses OpenCV (a computer vision Python package) to accurately (1) detect neuron contours, (2) extract the mean fluorescence within the contour, and (3) identify transient changes in the fluorescence due to neuronal activity. The pipeline consisted of 3 Python scripts that could both be easily accessed through a Python Jupyter notebook. In total, we tested this pipeline on ten separate calcium imaging datasets from murine dissociate cortical cultures. We next compared our automated pipeline outputs with the outputs of manually labeled data for neuronal cell location and corresponding fluorescent times series generated by an expert neuroscientist. Results: Our results show that our automated pipeline efficiently pinpoints neuronal cell body location and neuronal contours and provides a graphical representation of neural network metrics accurately reflecting changes in neuronal calcium-based fluorescence. The pipeline detected the shape, area, and location of most neuronal cell body contours by using binary thresholding and grayscale image conversion to allow computer vision to better distinguish between cells and non-cells. Its results were also comparable to manually analyzed results but with significantly reduced result acquisition times of 2-5 minutes per recording versus 10-20 minutes per recording. Based on these findings, our next step is to precisely measure the specificity and sensitivity of the automated pipeline’s cell body and contour detection to extract more robust neural network metrics and dynamics. Conclusion: Our Python-based pipeline performed automated computer vision-based analysis of calcium image recordings from neuronal cell bodies in neuronal cell cultures. Our new goal is to improve cell body and contour detection to produce more robust, accurate neural network metrics and dynamic graphs.

Keywords: calcium imaging, computer vision, neural activity, neural networks

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15537 Human Rights Regulations and Rules Affecting Community

Authors: Mariana Sary Khalifa Rezk

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The problem of respect for human rights in Southeast Asia has emerged as a main situation and is attracting the attention of the international network. Basically, the affiliation of Southeast Asian Nations (ASEAN) made human rights certainly one of its main troubles inside the ASEAN constitution in 2008. In the end, the Intergovernmental Fee on Human Rights ASEAN Human Rights (AICHR) was set up. AICHR is the Southeast Asia Human Rights Enforcement fee charged with the duties, functions and powers to sell and defend human rights. However, at the cease of 2016, the protecting feature assigned to the AICHR was no longer fulfilled. That is shown via several instances of human rights violations, which can be nonetheless ongoing and have not been solved. One case that has these days come to light is human rights violations against the Rohingya people in Myanmar. Using a felony-normative method, the study examines the urgency of setting up a human rights tribunal in Southeast Asia able to decide binding on ASEAN members or responsible parties. Information indicates ASEAN desires regional courts to cope with human rights abuses in the ASEAN region. Furthermore, the look also highlights 3 critical elements that ASEAN ought to take into account whilst establishing a human rights tribunal, particularly quantity. A good sized distinction in phrases of democracy and human rights improvement a few of the participants, a consistent implementation of the principle of non-interference and the economic trouble of the continuation of the court docket.

Keywords: politics, human rights, humanities, mankind, law human rights, Nigerian legal provisions, shariah law, comparative study, charter

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15536 Antibacterial Activity of Libyan Seaweed Extracts

Authors: Salmin K. Alshalmani, Nada H. Zobi, Ismaeel H. Bozakouk

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Marine organisms are potentially prolific sources of highly bio active secondary metabolites that might represent useful leads in the development of new pharmaceutical agents. The Libyan marine biodiversity including macroalgae remains partially unexplored in term of their potential bio activities. The phytochemical analysis of the alcoholic extracts of some commonly occurring seaweed Cystoseira compressa, enteromorpha intestinals, corallina, and Ulva lactuca and their evaluated for antibacterial activity by well diffusion assay were studied. Four different solvents namely water, ethanol 99 %, methanol 99 %, and methylated spirit 95 % were used for extraction. The phytochemical analysis revealed the presence of carbohydrates, steroids, tannin & phenols, saponins, proteins, and glycosides. The extracts were subjected for study of antibacterial activity. The zone of inhibition ranged between 8 to 16 mm in aqueous extract and up to 16 mm in methanol extract. The maximum activity (16 mm) was recorded from methanol extract of Ulva lactuca against Staphylococcus aureus and, minimum activity (8mm) recorded by Cystoseira compressa against S. aureus.

Keywords: macroalgae, phytochemicals, antibacterial activity, methanolic extract

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15535 Effect of Oral Administration of “Gadagi” Tea on Superoxide Dismutase Activity in Humans

Authors: A. M. Gadanya, B. A. Ahmad, U. Maigatari

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Effect of oral administration of Gadagi tea on superoxide dismutase activity was assessed on twenty (20) male subjects (aged 21-40years). Ten (10) male non Gadagi tea consumers (aged 20-26 years), were used as control. Blood samples were collected from the subjects and analysed for serum superoxide dismutase activity using R&D Enzyme Linked Immunosorbent Assay method (ELISA). The subjects were grouped into four based on age i.e group I (21-25 years), group II (26-30 years), and also based on duration of the tea consumption, i.e group A (5-9 years) , group B (10-14 years), group C (15-19 years) and group D (20-24 years). The subjects in group I (0.12 U mg-l +0.05), group II (0.11 U mg-l +0.01), group III (0.14 U mg-l +0.08) and group IV (0.17 U mg-l +0.11) showed increased activity of serum superoxide dismutase when compared with the control subjects (0.88 U mg-l +0.02) (P<0.05). There was no statistical significant difference in superoxide dismutase activity within the case groups (P<0.05), based on age and duration of consumption of the tea. Thus, Gadagi tea consumption could increase serum superoxide dismutase activity in humans.

Keywords: “Gadagi” tea, Serum, Superoxide dismutase, Humans.

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15534 An Intrusion Detection Systems Based on K-Means, K-Medoids and Support Vector Clustering Using Ensemble

Authors: A. Mohammadpour, Ebrahim Najafi Kajabad, Ghazale Ipakchi

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Presently, computer networks’ security rise in importance and many studies have also been conducted in this field. By the penetration of the internet networks in different fields, many things need to be done to provide a secure industrial and non-industrial network. Fire walls, appropriate Intrusion Detection Systems (IDS), encryption protocols for information sending and receiving, and use of authentication certificated are among things, which should be considered for system security. The aim of the present study is to use the outcome of several algorithms, which cause decline in IDS errors, in the way that improves system security and prevents additional overload to the system. Finally, regarding the obtained result we can also detect the amount and percentage of more sub attacks. By running the proposed system, which is based on the use of multi-algorithmic outcome and comparing that by the proposed single algorithmic methods, we observed a 78.64% result in attack detection that is improved by 3.14% than the proposed algorithms.

Keywords: intrusion detection systems, clustering, k-means, k-medoids, SV clustering, ensemble

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15533 Biomechanical Modeling, Simulation, and Comparison of Human Arm Motion to Mitigate Astronaut Task during Extra Vehicular Activity

Authors: B. Vadiraj, S. N. Omkar, B. Kapil Bharadwaj, Yash Vardhan Gupta

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During manned exploration of space, missions will require astronaut crewmembers to perform Extra Vehicular Activities (EVAs) for a variety of tasks. These EVAs take place after long periods of operations in space, and in and around unique vehicles, space structures and systems. Considering the remoteness and time spans in which these vehicles will operate, EVA system operations should utilize common worksites, tools and procedures as much as possible to increase the efficiency of training and proficiency in operations. All of the preparations need to be carried out based on studies of astronaut motions. Until now, development and training activities associated with the planned EVAs in Russian and U.S. space programs have relied almost exclusively on physical simulators. These experimental tests are expensive and time consuming. During the past few years a strong increase has been observed in the use of computer simulations due to the fast developments in computer hardware and simulation software. Based on this idea, an effort to develop a computational simulation system to model human dynamic motion for EVA is initiated. This study focuses on the simulation of an astronaut moving the orbital replaceable units into the worksites or removing them from the worksites. Our physics-based methodology helps fill the gap in quantitative analysis of astronaut EVA by providing a multisegment human arm model. Simulation work described in the study improves on the realism of previous efforts, incorporating joint stops to account for the physiological limits of range of motion. To demonstrate the utility of this approach human arm model is simulated virtually using ADAMS/LifeMOD® software. Kinematic mechanism for the astronaut’s task is studied from joint angles and torques. Simulation results obtained is validated with numerical simulation based on the principles of Newton-Euler method. Torques determined using mathematical model are compared among the subjects to know the grace and consistency of the task performed. We conclude that due to uncertain nature of exploration-class EVA, a virtual model developed using multibody dynamics approach offers significant advantages over traditional human modeling approaches.

Keywords: extra vehicular activity, biomechanics, inverse kinematics, human body modeling

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15532 Enhanced Photocatalytic H₂ Production from H₂S on Metal Modified Cds-Zns Semiconductors

Authors: Maali-Amel Mersel, Lajos Fodor, Otto Horvath

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Photocatalytic H₂ production by H₂S decomposition is regarded to be an environmentally friendly process to produce carbon-free energy through direct solar energy conversion. For this purpose, sulphide-based materials, as photocatalysts, were widely used due to their excellent solar spectrum responses and high photocatalytic activity. The loading of proper co-catalysts that are based on cheap and earth-abundant materials on those semiconductors was shown to play an important role in the improvement of their efficiency. In this research, CdS-ZnS composite was studied because of its controllable band gap and excellent performance for H₂ evolution under visible light irradiation. The effects of the modification of this photocatalyst with different types of materials and the influence of the preparation parameters on its H₂ production activity were investigated. The CdS-ZnS composite with an enhanced photocatalytic activity for H₂ production was synthesized from ammine complexes. Two types of modification were used: compounds of Ni-group metals (NiS, PdS, and Pt) were applied as co-catalyst on the surface of CdS-ZnS semiconductor, while NiS, MnS, CoS, Ag₂S, and CuS were used as a dopant in the bulk of the catalyst. It was found that 0.1% of noble metals didn’t remarkably influence the photocatalytic activity, while the modification with 0.5% of NiS was shown to be more efficient in the bulk than on the surface. The modification with other types of metals results in a decrease of the rate of H₂ production, while the co-doping seems to be more promising. The preparation parameters (such as the amount of ammonia to form the ammine complexes, the order of the preparation steps together with the hydrothermal treatment) were also found to highly influence the rate of H₂ production. SEM, EDS and DRS analyses were made to reveal the structure of the most efficient photocatalysts. Moreover, the detection of the conduction band electron on the surface of the catalyst was also investigated. The excellent photoactivity of the CdS-ZnS catalysts with and without modification encourages further investigations to enhance the hydrogen generation by optimization of the reaction conditions.

Keywords: H₂S, photoactivity, photocatalytic H₂ production, CdS-ZnS

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15531 Continuous Land Cover Change Detection in Subtropical Thicket Ecosystems

Authors: Craig Mahlasi

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The Subtropical Thicket Biome has been in peril of transformation. Estimates indicate that as much as 63% of the Subtropical Thicket Biome is severely degraded. Agricultural expansion is the main driver of transformation. While several studies have sought to document and map the long term transformations, there is a lack of information on disturbance events that allow for timely intervention by authorities. Furthermore, tools that seek to perform continuous land cover change detection are often developed for forests and thus tend to perform poorly in thicket ecosystems. This study investigates the utility of Earth Observation data for continuous land cover change detection in Subtropical Thicket ecosystems. Temporal Neural Networks are implemented on a time series of Sentinel-2 observations. The model obtained 0.93 accuracy, a recall score of 0.93, and a precision score of 0.91 in detecting Thicket disturbances. The study demonstrates the potential of continuous land cover change in Subtropical Thicket ecosystems.

Keywords: remote sensing, land cover change detection, subtropical thickets, near-real time

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15530 The Investigation of Enzymatic Activity in the Soils Under the Impact of Metallurgical Industrial Activity in Lori Marz, Armenia

Authors: T. H. Derdzyan, K. A. Ghazaryan, G. A. Gevorgyan

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Beta-glucosidase, chitinase, leucine-aminopeptidase, acid phosphomonoestearse and acetate-esterase enzyme activities in the soils under the impact of metallurgical industrial activity in Lori marz (district) were investigated. The results of the study showed that the activities of the investigated enzymes in the soils decreased with increasing distance from the Shamlugh copper mine, the Chochkan tailings storage facility and the ore transportation road. Statistical analysis revealed that the activities of the enzymes were positively correlated (significant) to each other according to the observation sites which indicated that enzyme activities were affected by the same anthropogenic factor. The investigations showed that the soils were polluted with heavy metals (Cu, Pb, As, Co, Ni, Zn) due to copper mining activity in this territory. The results of Pearson correlation analysis revealed a significant negative correlation between heavy metal pollution degree (Nemerow integrated pollution index) and soil enzyme activity. All of this indicated that copper mining activity in this territory causing the heavy metal pollution of the soils resulted in the inhabitation of the activities of the enzymes which are considered as biological catalysts to decompose organic materials and facilitate the cycling of nutrients.

Keywords: Armenia, metallurgical industrial activity, heavy metal pollutionl, soil enzyme activity

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15529 Exploring the Application of Human Resource Management Bundles: A Case Study

Authors: Maniam Kaliannan

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Studies on best practice or “bundles” of human resource management aims at providing a ‘universal solution’ to organizations yet critics challenge this view and place importance on the architecture of human resource processes in response to the dynamic needs of organizations. This paper identifies these best practices and explores how the applications of selected human resource management practices to a case study help solved their human resource problems. The case study includes insights on the problems faced; the approach taken to identify its root causes and explores how selected human resource management practices helped managed the overall predicament. The case study results supports the importance of aligning ‘bundles’ of practices with organizational architecture and ensuring that the architecture of human resource practices evolve with the changing needs of organizations. In addition, a framework based on the events of the case study is proposed to systematically manage their human resources

Keywords: bundles, best practices, human resource management, organizational architecture, framework

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15528 A Promising Thrombolytic and Anticoagulant Serine Protease Purified from Lug Worms Inhabiting Tidal Flats

Authors: Hye Jin Kim, Hwa Sung Shin

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Ischemic stroke means the caused brain damage due to neurological defects, occurring occlusion of cerebral vascular resulting in thrombus or embolism. t-PA (tissue Plasminogen Activator) is the only thrombolytic agent passed the FDA (Food and Drug Administration). However, t-PA directly dissolves the thrombus (direct activity) through fibrinolysis, showing side effects such as re-occlusion. In this study, we evaluated the thrombolytic activities of the serine protease extracted from lugworms inhabiting tidal flats. The new serine protease identified as 38 kDa by SDS-PAGE was not toxic to brain endothelial cells line (hCMEC/D3). Also, the plasmin synthesis inhibition activity (indirect activity) of the new serine protease was confirmed through fibrin zymography assay and fibrin plate assay. It was higher than direct activity as compared to u-PA (urokinase Plasminogen Activator). The activities were found to be maintained at a wide range of temperature (4-70 ℃) and pH 7-10 compared to previous thrombolytic agents from the azocasein assay. In addition, the new serine protease has shown anticoagulant activity from fibrinogenolytic activity assay. In conclusion, the serine protease in lug worms inhabiting the tidal flats could be considered a promising thrombolytic candidate for the treatment of ischemic stroke.

Keywords: alkaline serine protease, bifunctional thrombolytic activity, fibrinolytic activity, ischemic stroke, lug worms

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15527 Effectiveness of Public Speaking Extracurricular in Gontor in Raising Leaders of the Advanced Global World's Needs

Authors: Ummi Sholihah Pertiwi Abidin, Khusnul Hajar Nuansari

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Human resource is one of the most important components that can not be separated from communication fields, either in a large community like a mass or narrow ones such as an institution, office, group and even family. Human resource is an asset which is often used as a tool to achieve certain goals. Therefore, development of human resources is essential for improving skills and character of a person especially at the time that has entered globalization era. People are required to be able to compete both in the local and international arena, no matter what. This paper raised topic related to human resource development solution by a unique educational leadership and communication skill improvement through a linguistic approach. Here the authors want to go by form of public speaking method applied in Modern Islamic Boarding School Darussalam Gontor as the extracurricular activity that is using three languages, they are: Indonesian as the mother language or the nation language of the students, Arabic and English as the second language and Gontor’s mean to supply its students to be able to conquer the globalization needs. This implementation produced the establishment of great leaders through confidence growing to speak in public by adjusting the listener context. In linguistic term, it will help enhancing verbal and nonverbal communication skills and so forth in owning a lot of vocabulary.

Keywords: public speaking, Gontor, language, leadership

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15526 Actuator Fault Detection and Fault Tolerant Control of a Nonlinear System Using Sliding Mode Observer

Authors: R. Loukil, M. Chtourou, T. Damak

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In this work, we use the Fault detection and isolation and the Fault tolerant control based on sliding mode observer in order to introduce the well diagnosis of a nonlinear system. The robustness of the proposed observer for the two techniques is tested through a physical example. The results in this paper show the interaction between the Fault tolerant control and the Diagnosis procedure.

Keywords: fault detection and isolation FDI, fault tolerant control FTC, sliding mode observer, nonlinear system, robustness, stability

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15525 Screening for Antibacterial, Antifungal and Cytotoxic Agents in Three Hard Coral Species from Persian Gulf

Authors: Maryam Ehsanpou, Majid Afkhami, Flora Mohammadizadeh, Amirhoushang Bahri, Rastin Afkhami

Abstract:

Within the frame of a biodiversity and bioactivity study of marine macro organisms from the Persian Gulf, three hard coral species extracts were investigated for cytotoxic, antibacterial and antifungal activities against five human pathogenic microorganisms. All concentrations of extracts from three hard corals showed no antifungal activity towards the tested strains. In antibacterial assays, the hard coral extracts showed significant activity solely against Staphylococcus aureus with MICs ranging from 3 to 9 μg/ml. The highest antibacterial activity was found in the aqueous methanol extract of Porites compressa with an inhibition zone of 22 mm against Staphylococcus aureus at 18 μg/ml extract concentration. Methanol extracts from Porites harrisoi and Porites compressa exhibited only weak cytotoxic activities. It is important for future research to concentrate on finding the mechanisms employed by corals to defend themselves against invasion, the mechanism of infections and the type of chemical compounds in coral extracts that inhibit antibacterial growth or proliferation in underexplored areas such as the Persian Gulf.

Keywords: antibacterial, antifungal, cytotoxic, hard corals, Persian Gulf

Procedia PDF Downloads 485
15524 A Finite Memory Residual Generation Filter for Fault Detection

Authors: Pyung Soo Kim, Eung Hyuk Lee, Mun Suck Jang

Abstract:

In the current paper, a residual generation filter with finite memory structure is proposed for fault detection. The proposed finite memory residual generation filter provides the residual by real-time filtering of fault vector using only the most recent finite observations and inputs on the window. It is shown that the residual given by the proposed residual generation filter provides the exact fault for noise-free systems. Finally, to illustrate the capability of the proposed residual generation filter, numerical examples are performed for the discretized DC motor system having the multiple sensor faults.

Keywords: residual generation filter, finite memory structure, kalman filter, fast detection

Procedia PDF Downloads 694
15523 Detectability Analysis of Typical Aerial Targets from Space-Based Platforms

Authors: Yin Zhang, Kai Qiao, Xiyang Zhi, Jinnan Gong, Jianming Hu

Abstract:

In order to achieve effective detection of aerial targets over long distances from space-based platforms, the mechanism of interaction between the radiation characteristics of the aerial targets and the complex scene environment including the sunlight conditions, underlying surfaces and the atmosphere are analyzed. A large simulated database of space-based radiance images is constructed considering several typical aerial targets, target working modes (flight velocity and altitude), illumination and observation angles, background types (cloud, ocean, and urban areas) and sensor spectrums ranging from visible to thermal infrared. The target detectability is characterized by the signal-to-clutter ratio (SCR) extracted from the images. The influence laws of the target detectability are discussed under different detection bands and instantaneous fields of view (IFOV). Furthermore, the optimal center wavelengths and widths of the detection bands are suggested, and the minimum IFOV requirements are proposed. The research can provide theoretical support and scientific guidance for the design of space-based detection systems and on-board information processing algorithms.

Keywords: space-based detection, aerial targets, detectability analysis, scene environment

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15522 Suppression of DMBA/TPA-Induced Skin Tumorigenesis by Menthol through Inhibition of Inflammation, NF-kappaB, Ras-Raf-ERK Pathway

Authors: Zhaoguo Liu, Cunsi Shen, Yin Lu

Abstract:

Growing evidence has shown that menthol has potent anticancer activity in various human cancers. However, its effect on skin cancer remains largely unknown. In the present study, we investigated the chemopreventive potential of menthol against 7, 12-dimethylbenz[a] anthracene(DMBA)/12-O-tetradecanoylphorbol 13-acetate (TPA)-induced skin tumorigenesis in ICR mice. Our results showed that menthol significantly inhibited TPA-induced inflammatory responses and pro-inflammatory cytokine release. We also found that menthol treatment significantly inhibited TPA-induced lipid peroxidation (LPO), mouse UDP-glucumno-syltransferase (UGT), mouse NADH Dehydrogenase, Quinone 1 (NQO1) release. Furthermore, we found menthol treatment significantly inhibited the tumor incidence and number of tumors (P < 0.001). Interestingly, we observed that menthol treatment significantly inhibited TPA-induced altered activity of NF-κB in skin tumor. Consistently, menthol-treated tumors also showed significantly suppressed the Ras-Raf-ERK signaling pathway. Thus, our results suggest that menthol inhibits DMBA/TPA-induced skin tumorigenesis by attenuating the Ras and inhibiting NF-κB activity via inhibition of inflammation responses and pro-inflammatory cytokine release.

Keywords: DMBA/TPA, NF-κB, Ras-Raf-ERK, skin tumorigenesis

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15521 Integrating RAG with Prompt Engineering for Dynamic Log Parsing and Anomaly Detections

Authors: Liu Lin Xin

Abstract:

With the increasing complexity of systems, log parsing and anomaly detection have become crucial for maintaining system stability. However, traditional methods often struggle with adaptability and accuracy, especially when dealing with rapidly evolving log content and unfamiliar domains. To address these challenges, this paper proposes approach that integrates Retrieval Augmented Generation (RAG) technology with Prompt Engineering for Large Language Models, applied specifically in LogPrompt. This approach enables dynamic log parsing and intelligent anomaly detection by combining real-time information retrieval with prompt optimization. The proposed method significantly enhances the adaptability of log analysis and improves the interpretability of results. Experimental results on several public datasets demonstrate the method's superior performance, particularly in scenarios lacking training data, where it significantly outperforms traditional methods. This paper introduces a novel technical pathway for log parsing and anomaly detection, showcasing the substantial theoretical value and practical potential.

Keywords: log parsing, anomaly detection, RAG, prompt engineering, LLMs

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15520 Building and Tree Detection Using Multiscale Matched Filtering

Authors: Abdullah H. Özcan, Dilara Hisar, Yetkin Sayar, Cem Ünsalan

Abstract:

In this study, an automated building and tree detection method is proposed using DSM data and true orthophoto image. A multiscale matched filtering is used on DSM data. Therefore, first watershed transform is applied. Then, Otsu’s thresholding method is used as an adaptive threshold to segment each watershed region. Detected objects are masked with NDVI to separate buildings and trees. The proposed method is able to detect buildings and trees without entering any elevation threshold. We tested our method on ISPRS semantic labeling dataset and obtained promising results.

Keywords: building detection, local maximum filtering, matched filtering, multiscale

Procedia PDF Downloads 318
15519 The Impact of Human Rights Violation in Modern Society

Authors: Hanania Nasan Shokry Abdelmasih

Abstract:

The interface between improvement and human rights has long been the subject of scholarly debate. As an end result, a hard and fast of principles, starting from the proper improvement to a human rights-based totally technique to development, have been adopted to understand the dynamics among the two concepts. In spite of those attempts, the precise link between development and human rights is not yet fully understood. However, the inevitable interdependence between the two standards and the idea that development efforts must be made while respecting human rights have received prominence in recent years. Then again, the emergence of sustainable development as a widely spread method in development dreams and rules similarly complicates this unresolved convergence. The place of sustainable improvement inside the human rights discourse and its role in ensuring the sustainability of improvement programs require systematic research. The purpose of this newsletter is, therefore, to take a look at the relationship between development and human rights, with particular attention to the area of the standards of sustainable improvement in international human rights regulation. It's going to examine whether it recognizes the proper to achieve sustainable improvement. Hence, the Article states that the principles of sustainable improvement are diagnosed immediately or implicitly in numerous human rights devices, which is an affirmative solution to the question posed above. Therefore, this report scrutinizes worldwide and local human rights gadgets, as well as the case regulation and interpretations of human rights in our bodies, to support this speculation.

Keywords: sustainable development, human rights, the right to development, the human rights-based approach to development, environmental rights, economic development, social sustainability human rights protection, human rights violations, workers’ rights, justice, security.

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15518 In vitro Synergistic Antioxidant Activity of Honey-Mentha Spicata Combination

Authors: Yuva Bellik, Selles Mohamed Amar

Abstract:

The beneficial health effects including antioxidant properties of mint (Mentha spicata) and honey bees (Apis mellifera) have been extensively studied. However, there is no data about the effects of their associated use. In this study the total phenolic and flavonoid contents for individual extracts of mint and honey and their combination were determined. The antioxidant activity was investigated by using reducing power, 1,1-diphenyl-2-picrylhydrazyl (DPPH), 2,2´- azinobis-(3-ethylbenzothiazoline-6-sulphonic acid diamonium salt (ABTS), and chelating power methods. The results showed that individual extracts contained important quantity of phenolics and flavonoids and their combination was found to produce best antioxidant activity. A significant linear correlation between the phenolic/flavonoid contents and antioxidant activity, especially with reducing power and free radical scavenging abilities, was observed.

Keywords: honey, mint, synergy, antioxidant activity

Procedia PDF Downloads 385