Search results for: publication patterns

Authors: Agnese Natali, Francesco Morelli, Walter Salvatore, José Humberto Matias de Paula Filho, Patrick Pol

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In the framework of the evaluation of the applicability of high strength steel to produce thin-walled elements to be used in Automated Rack Supported Warehouses, an experimental campaign is carried outto evaluate the structural performance of typical profile shapes adopted for such purposes and made of high strength steel. Numerical models are developed to fit the observed failure modes, stresses, and deformation patterns, and proper directions are proposed to simplify the numerical simulations to be used in further applications and to evaluate the mechanical behavior and performance of profiles.

Keywords: Steel racks, Automated Rack Supported Warehouse, thin walled cold-formed elements, high strength steel.

Procedia PDF Downloads 179

Authors: Warda Khan, Remo Lachmann, Adarsh S. Garakahally

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The increasing complexity of software and its applicability in a wide range of industries, e.g., automotive, call for enhanced quality assurance techniques. Test automation is one option to tackle the prevailing challenges by supporting test engineers with fast, parallel, and repetitive test executions. A high degree of test automation allows for a shift from mundane (manual) testing tasks to a more analytical assessment of the software under test. However, a high initial investment of test resources is required to establish test automation, which is, in most cases, a limitation to the time constraints provided for quality assurance of complex software systems. Hence, a computer-aided creation of automated test cases is crucial to increase the benefit of test automation. This paper proposes the application of machine learning for the generation of automated test cases. It is based on supervised learning to analyze test specifications and existing test implementations. The analysis facilitates the identification of patterns between test steps and their implementation with test automation components. For the test case generation, this approach exploits historical data of test automation projects. The identified patterns are the foundation to predict the implementation of unknown test case specifications. Based on this support, a test engineer solely has to review and parameterize the test automation components instead of writing them manually, resulting in a significant time reduction for establishing test automation. Compared to other generation approaches, this ML-based solution can handle different writing styles, authors, application domains, and even languages. Furthermore, test automation tools require expert knowledge by means of programming skills, whereas this approach only requires historical data to generate test cases. The proposed solution is evaluated using various multi-label evaluation criteria (EC) and two small-sized real-world systems. The most prominent EC is ‘Subset Accuracy’. The promising results show an accuracy of at least 86% for test cases, where a 1:1 relationship (Multi-Class) between test step specification and test automation component exists. For complex multi-label problems, i.e., one test step can be implemented by several components, the prediction accuracy is still at 60%. It is better than the current state-of-the-art results. It is expected the prediction quality to increase for larger systems with respective historical data. Consequently, this technique facilitates the time reduction for establishing test automation and is thereby independent of the application domain and project. As a work in progress, the next steps are to investigate incremental and active learning as additions to increase the usability of this approach, e.g., in case labelled historical data is scarce.

Keywords: machine learning, multi-class, multi-label, supervised learning, test automation

Procedia PDF Downloads 132

Authors: Abouamama Sidaoui, Noureddine Karkachi, Mebrouk Kihal

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The characteristics of Fusarium oxysporium f.sp. albedinis (Foa) isolates were investigated using electrophoretic studies of isozymes systems (esterase and phosphatase). All the (F.o.a) isolates were pathogenic to the date palm seedlings cultivar Deglet Nour, but they did not induce any disease symptoms on control plants. Fusarium sp. isolated from soil did not show aggression against these seedlings. The isoenzymes profiles revealed polymorphic bands. The data were subjected to analysis with the JMP method. The isolates were delineated into two main groups A and B which were divided into sub-groups. 19 isolates create the group A, and four isolates (E1, E2, E3 and M15A) formed the group B. Analysis of isozyme banding patterns was found to be a reliable marker technology, efficient, and effective tools to find the genetic variability among isolates isolated in different geographical areas.

Keywords: genetic diversity, Fusarium oxysporium f. sp. albedinis, isozyme analysis, pathogenicity

Procedia PDF Downloads 218

Authors: Sandra Thomas

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This study tries to analyse the level of food security and dietary diversity among households of different socio-economic classes in the urban centers of Thrissur. The study revealed that there is no much difference in purchasing patterns of food articles among the socio-economic classes indicating a very high level of both physical and economic accessibility of food. On analysing the dietary diversity of the households none of the households scored below five and fifty-three per cent of the households scored eleven or twelve indicating higher diversity in diet. It was also found that income and education are the two important factors that influence the level of household food security.

Keywords: food security, dietary diversity, household level, socio-economic classes

Procedia PDF Downloads 125

Authors: Victor V. Kuzenov, Sergei V. Ryzhkov

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Ongoing experimental and theoretical studies on magneto-inertial confinement fusion (Angara, C-2, CJS-100, General Fusion, MagLIF, MAGPIE, MC-1, YG-1, Omega) and new constructing facilities (Baikal, C-2W, Z300 and Z800) require adequate modeling and description of the physical processes occurring in high-temperature dense plasma in a strong magnetic field. This paper presents a mathematical model, numerical method, and results of the computer analysis of the compression process and the energy transfer in the target plasma, used in magneto-inertial fusion (MIF). The computer simulation of the compression process of the magnetized target by the high-power laser pulse and the high-speed plasma jets is presented. The characteristic patterns of the two methods of the target compression are being analysed.

Keywords: magnetized target, magneto-inertial fusion, mathematical model, plasma and laser beams

Procedia PDF Downloads 296

Authors: Rodrigo Costa, Thomas Mazzuchi, Shahram Sarkani

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This study analyzes the evolution of Bitcoin Improvement Proposals (BIPs), the self-governing mechanism that enables updates to the Bitcoin protocol. By modeling BIP submission frequencies with a Negative Binomial distribution and detecting change points with the Pelt Rupture model, we identify three distinct intervals of proposal activity, suggesting shifts in development priorities over time. Long-term growth patterns, captured by Gompertz and Weibull models, indicate an S-shaped trend in cumulative BIP counts, pointing toward a maturation phase in Bitcoin’s protocol. Our findings suggest that Bitcoin may be entering a stable stage, with fewer fundamental changes and more incremental enhancements. This trend highlights the need for further research into BIP content and more studies into its dynamics to better understand decentralized protocol governance and maturation.

Keywords: bitcoin improvement proposals, innovation management, change point detection, systems modeling, simulation

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Authors: W. S. Thulasitha, N. Umasuthan, G. I. Godahewa, Jehee Lee

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In fish, innate immune defense is the first immune response against microbial pathogens which consists of several antimicrobial components. Galectins are one of the carbohydrate binding lectins that have the ability to identify pathogen by recognition of pathogen associated molecular patterns. Galectins play a vital role in the regulation of innate and adaptive immune responses. Rock bream Oplegnathus fasciatus is one of the most important cultured species in Korea and Japan. Considering the losses due to microbial pathogens, present study was carried out to understand the molecular and functional characteristics of a galectin in normal and pathogenic conditions, which could help to establish an understanding about immunological components of rock bream. Complete cDNA of rock bream galectin like protein B (rbGal like B) was identified from the cDNA library, and the in silico analysis was carried out using bioinformatic tools. Genomic structure was derived from the BAC library by sequencing a specific clone and using Spidey. Full length of rbGal like B (contig14775) cDNA containing 517 nucleotides was identified from the cDNA library which comprised of 435 bp in the open reading frame encoding a deduced protein composed of 145 amino acids. The molecular mass of putative protein was predicted as 16.14 kDa with an isoelectric point of 8.55. A characteristic conserved galactose binding domain was located from 12 to 145 amino acids. Genomic structure of rbGal like B consisted of 4 exons and 3 introns. Moreover, pairwise alignment showed that rock bream rbGal like B shares highest similarity (95.9 %) and identity (91 %) with Takifugu rubripes galectin related protein B like and lowest similarity (55.5 %) and identity (32.4 %) with Homo sapiens. Multiple sequence alignment demonstrated that the galectin related protein B was conserved among vertebrates. A phylogenetic analysis revealed that rbGal like B protein clustered together with other fish homologs in fish clade. It showed closer evolutionary link with Takifugu rubripes. Tissue distribution and expression patterns of rbGal like B upon immune challenges were performed using qRT-PCR assays. Among all tested tissues, level of rbGal like B expression was significantly high in gill tissue followed by kidney, intestine, heart and spleen. Upon immune challenges, it showed an up-regulated pattern of expression with Edwardsiella tarda, rock bream irido virus and poly I:C up to 6 h post injection and up to 24 h with LPS. However, In the presence of Streptococcus iniae rbGal like B showed an up and down pattern of expression with the peak at 6 - 12 h. Results from the present study revealed the phylogenetic position and role of rbGal like B in response to microbial infection in rock bream.

Keywords: galectin like protein B, immune response, Oplegnathus fasciatus, molecular characterization

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Authors: Ayalew Yimam Ali

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The Y-shaped microchannel is used to mix both miscible or immiscible fluids with different viscosities. However, mixing at the entrance of the Y-junction microchannel can be a difficult mixing phenomena due to micro-scale laminar flow aspects with the two miscible high-viscosity water-glycerol fluids. One of the most promising methods to improve mixing performance and diffusion mass transfer in laminar flow phenomena is acoustic streaming (AS), which is a time-averaged, second-order steady streaming that can produce rolling motion in the microchannel by oscillating a low-frequency range acoustic transducer and inducing an acoustic wave in the flow field. The developed 3D trapezoidal, triangular structure spine used in this study was created using sophisticated CNC machine cutting tools used to create microchannel mold with a 3D trapezoidal triangular structure spine alone the Y-junction longitudinal mixing region. In order to create the molds for the 3D trapezoidal structure with the 3D sharp edge tip angles of 30° and 0.3mm trapezoidal triangular sharp edge tip depth from PMMA glass (Polymethylmethacrylate) with advanced CNC machine and the channel manufactured using PDMS (Polydimethylsiloxane) which is grown up longitudinally on top surface of the Y-junction microchannel using soft lithography nanofabrication strategies. Flow visualization of 3D rolling steady acoustic streaming and mixing enhancement with high-viscosity miscible fluids with different trapezoidal, triangular structure longitudinal length, channel width, high volume flow rate, oscillation frequency, and amplitude using micro-particle image velocimetry (μPIV) techniques were used to study the 3D acoustic streaming flow patterns and mixing enhancement. The streaming velocity fields and vorticity flow fields show 16 times more high vorticity maps than in the absence of acoustic streaming, and mixing performance has been evaluated at various amplitudes, flow rates, and frequencies using the grayscale value of pixel intensity with MATLAB software. Mixing experiments were performed using fluorescent green dye solution with de-ionized water in one inlet side of the channel, and the de-ionized water-glycerol mixture on the other inlet side of the Y-channel and degree of mixing was found to have greatly improved from 67.42% without acoustic streaming to 0.96.83% with acoustic streaming. The results show that the creation of a new 3D steady streaming rolling motion with a high volume flowrate around the entrance was enhanced by the formation of a new, three-dimensional, intense streaming rolling motion with a high-volume flowrate around the entrance junction mixing zone with the two miscible high-viscous fluids which are influenced by laminar flow fluid transport phenomena.

Keywords: micro fabrication, 3d acoustic streaming flow visualization, micro-particle image velocimetry, mixing enhancement

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Authors: Assel Jaxylykova, Alexnder Pak

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This study utilized a Self-Organizing Map (SOM) for unsupervised learning on the CONLL-2003 dataset for Named Entity Recognition (NER). The process involved encoding words into 300-dimensional vectors using FastText. These vectors were input into a SOM grid, where training adjusted node weights to minimize distances. The SOM provided a topological representation for identifying and clustering named entities, demonstrating its efficacy without labeled examples. Results showed an F1-measure of 0.86, highlighting SOM's viability. Although some methods achieve higher F1 measures, SOM eliminates the need for labeled data, offering a scalable and efficient alternative. The SOM's ability to uncover hidden patterns provides insights that could enhance existing supervised methods. Further investigation into potential limitations and optimization strategies is suggested to maximize benefits.

Keywords: named entity recognition, natural language processing, self-organizing map, CONLL-2003, semantics

Procedia PDF Downloads 47

Authors: Wei-Hsuan Hsu, Yi-Xuan Huang

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Nanoimprint lithography (NIL) possesses the advantages of sub-10-nm feature and low cost. NIL patterns the resist with physical deformation using a mold, which can easily reproduce the required nano-scale pattern. However, the variation of process parameters and environmental conditions seriously affect reproduction quality. How to ensure the quality of imprinted pattern is essential for industry. In this study, the authors used the electrowetting technology to assist mold filling in the NIL process. A special mold structure was designed to cause electrowetting. During the imprinting process, when a voltage was applied between the mold and substrate, the hydrophilicity/hydrophobicity of the surface of the mold can be converted. Both simulation and experiment confirmed that the electrowetting technology can assist mold filling and avoid incomplete filling rate. The proposed method can also reduce the crack formation during the de-molding process. Therefore, electrowetting technology can improve the process quality of NIL.

Keywords: electrowetting, mold filling, nano-imprint, surface modification

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Authors: Eugenia Jilinguirian

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In the healthcare industry, data mining is essential since it transforms the field by collecting useful data from large datasets. Data mining is the process of applying advanced analytical methods to large patient records and medical histories in order to identify patterns, correlations, and trends. Healthcare professionals can improve diagnosis accuracy, uncover hidden linkages, and predict disease outcomes by carefully examining these statistics. Additionally, data mining supports personalized medicine by personalizing treatment according to the unique attributes of each patient. This proactive strategy helps allocate resources more efficiently, enhances patient care, and streamlines operations. However, to effectively apply data mining, however, and ensure the use of private healthcare information, issues like data privacy and security must be carefully considered. Data mining continues to be vital for searching for more effective, efficient, and individualized healthcare solutions as technology evolves.

Keywords: data mining, healthcare, big data, individualised healthcare, healthcare solutions, database

Procedia PDF Downloads 66

Authors: Agustin Maciel-Padilla

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This paper explores the most significant change to Japan’s security strategy since the end of World War II, in particular Prime Minister Fumio Kishida’s government publication, in late 2022, of 3 policy documents (the National Security Strategy [NSS], the National Defense Strategy and the Defense Buildup Program) that basically propose to expand the country’s military capabilities and to increase military spending over a 5-year period. These policies represent a remarkable transformation of Japan’s defense-oriented policy followed since 1946. These proposals have been under analysis and debate since they were announced, as it was also Japan’s historic ambition to strengthening its deterrence capabilities in the context of a more complex regional security environment. Even though this new defense posture has attracted significant international attention, it is far from representing a done deal because of the fact that there is still a long way to go to implement this vision because of a wide variety of political and economic issues. Japan is currently experiencing the most dangerous security environment since the end of World War II, and this situation led Japan to intensify its dialogue with the United States to reflect a re-evaluation of deterrence in the face of a rapidly worsening security environment, a changing balance of power in East Asia, and the arrival of a new era of “great power competition”. Japan’s new documents, for instance, identify China and North Korea’s as posing, respectively, a strategic challenge and an imminent threat. Japan has also noted that Russia’s invasion of Ukraine has contributed to erode the foundation of the international order. It is considered that Russia’s aggression was possible because Ukraine’s defense capability was not enough for effective deterrence. Moreover, Japan’s call for “counterstrike capabilities” results from a recognition that China and North Korea’s ballistic and cruise missiles could overwhelm Japan’s air and missile defense systems, and therefore there is an urgent need to strengthen deterrence and resilience. In this context, this paper will focus on the impact of these changes on the US-Japan alliance. Adapting this alliance to Tokyo’s new ambitions and capabilities could be critical in terms of updating their traditional protection/access to bases arrangement, interoperability and joint command and control issues, as well as regarding the security–economy nexus. While China is Japan’s largest trading partner, and trade between the two has been growing, US-Japan economic relationship has been slower, notwithstanding the fact that US-Japan security cooperation has strengthened significantly in recent years.

Keywords: us-japan alliance, japan security, great power competition, interoperability

Procedia PDF Downloads 65

Authors: Amjad Naveed

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This study analysed the role of structural change in the process of labour productivity convergence at country and regional levels. Many forms of structural changes occurred within the European Union (EU) countries i.e. variation in sectoral employment share, changes in demand for products, variations in trade patterns and advancement in technology which may have an influence on the process of convergence. Earlier studies on convergence have neglected the role of structural changes which can have resulted in different conclusion on the nature of convergence. The contribution of this study is to examine the role of structural change in testing labour productivity convergence at various levels. For the empirical purpose, the data of 19 EU countries, 259 regions and 6 industries is used for the period of 1991-2009. The results indicate that convergence varies across regional and country levels for different industries when considered the role of structural change.

Keywords: labor produvitivty, convergence, structural change, panel unit root

Procedia PDF Downloads 285

Authors: Jamison Duckworth, Shankarachary Ragi

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Detection and segmentation of wildfire smoke plumes from remote sensing imagery are being pursued as a solution for early fire detection and response. Smoke plume detection can be automated and made robust by the application of artificial intelligence methods. Specifically, in this study, the deep learning approach Mask Region-based Convolutional Neural Network (RCNN) is being proposed to learn smoke patterns across different spectral bands. This method is proposed to separate the smoke regions from the background and return masks placed over the smoke plumes. Multispectral data was acquired using NASA’s Earthdata and WorldView and services and satellite imagery. Due to the use of multispectral bands along with the three visual bands, we show that Mask R-CNN can be applied to distinguish smoke plumes from clouds and other landscape features that resemble smoke.

Keywords: deep learning, mask-RCNN, smoke plumes, spectral bands

Procedia PDF Downloads 127

Authors: Tahereh Habibi

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The Oligocene carbonates are widespread along Fars Province, Zagros Basin, SW Iran. Distribution of planktonic and larger benthic foraminfera, stratal patterns and facies architecture are used as a tool to define microfacies and foraminiferal associations of these strata at Kavar Section. The presence of Nummulites spp. indicated the age of the sequence as Rupelian-Chattian (Nummulites vascus-Nummulites fichteli and Archaias asmaricus/hensoni-Miogypsinoides complanatus assemblage zones). The paleoenvironmental setting is interpreted as a homoclinal ramp environment according to the recognition of eight microfacies types. Four foraminiferal associations are recognized in the investigated ramp setting. They represent a salinity of 34-40 to 50 psu and higher than 50 psu in more restricted conditions. The depth ranges from 200 m as evidenced by the presence of planktonic foraminifera and to less than 30m in the more restricted inner ramp environment. Warm tropical and subtropical water with temperature of 18-25° C is proposed.

Keywords: foraminiferal associations, microfacies, oligocene, paleoecology

Procedia PDF Downloads 506

Authors: J. D. Martínez-Vargas, C. Castro-Hoyos, G. Castellanos-Dominguez

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In this work, we propose a novel approach for measuring the stationarity level of a multichannel time-series. This measure is based on a stationarity definition over time-varying spectrum, and it is aimed to quantify the relation between local stationarity (single-channel) and global dynamic behavior (multichannel dynamics). To assess the proposed approach validity, we use a well known EEG-BCI database, that was constructed for separate between motor/imagery tasks. Thus, based on the statement that imagination of movements implies an increase on the EEG dynamics, we use as discriminant features the proposed measure computed over an estimation of the non-stationary components of input time-series. As measure of separability we use a t-student test, and the obtained results evidence that such measure is able to accurately detect the brain areas projected on the scalp where motor tasks are realized.

Keywords: stationary measure, entropy, sub-space projection, multichannel dynamics

Procedia PDF Downloads 412

Authors: Ayalew Yimam Ali

Abstract:

The Y-shaped microchannel system is used to mix up low or high viscosities of different fluids, and the laminar flow with high-viscous water-glycerol fluids makes the mixing at the entrance Y-junction region a challenging issue. Acoustic streaming (AS) is time-average, a steady second-order flow phenomenon that could produce rolling motion in the microchannel by oscillating low-frequency range acoustic transducer by inducing acoustic wave in the flow field is the promising strategy to enhance diffusion mass transfer and mixing performance in laminar flow phenomena. In this study, the 3D trapezoidal Structure has been manufactured with advanced CNC machine cutting tools to produce the molds of trapezoidal structure with the 3D sharp edge tip angles of 30° and 0.3mm spine sharp-edge tip depth from PMMA glass (Polymethylmethacrylate) and the microchannel has been fabricated using PDMS (Polydimethylsiloxane) which could be grown-up longitudinally in Y-junction microchannel mixing region top surface to visualized 3D rolling steady acoustic streaming and mixing performance evaluation using high-viscous miscible fluids. The 3D acoustic streaming flow patterns and mixing enhancement were investigated using the micro-particle image velocimetry (μPIV) technique with different spine depth lengths, channel widths, high volume flow rates, oscillation frequencies, and amplitude. The velocity and vorticity flow fields show that a pair of 3D counter-rotating streaming vortices were created around the trapezoidal spine structure and observing high vorticity maps up to 8 times more than the case without acoustic streaming in Y-junction with the high-viscosity water-glycerol mixture fluids. The mixing experiments were performed by using fluorescent green dye solution with de-ionized water on one inlet side, de-ionized water-glycerol with different mass-weight percentage ratios on the other inlet side of the Y-channel and evaluated its performance with the degree of mixing at different amplitudes, flow rates, frequencies, and spine sharp-tip edge angles using the grayscale value of pixel intensity with MATLAB Software. The degree of mixing (M) characterized was found to significantly improved to 0.96.8% with acoustic streaming from 67.42% without acoustic streaming, in the case of 0.0986 μl/min flow rate, 12kHz frequency and 40V oscillation amplitude at y = 2.26 mm. The results suggested the creation of a new 3D steady streaming rolling motion with a high volume flow rate around the entrance junction mixing region, which promotes the mixing of two similar high-viscosity fluids inside the microchannel, which is unable to mix by the laminar flow with low viscous conditions.

Keywords: nano fabrication, 3D acoustic streaming flow visualization, micro-particle image velocimetry, mixing enhancement

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Authors: Xu Du, Aparna S. Varde

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In this research, we propose to conduct diagnostic and predictive analysis about the key factors and consequences of urban population relocation. To achieve this goal, urban simulation models extract the urban development trends as land use change patterns from a variety of data sources. The results are treated as part of urban big data with other information such as population change and economic conditions. Multiple data mining methods are deployed on this data to analyze nonlinear relationships between parameters. The result determines the driving force of population relocation with respect to urban sprawl and urban sustainability and their related parameters. Experiments so far reveal that data mining methods discover useful knowledge from the multicity urban data. This work sets the stage for developing a comprehensive urban simulation model for catering to specific questions by targeted users. It contributes towards achieving sustainability as a whole.

Keywords: data mining, environmental modeling, sustainability, urban planning

Procedia PDF Downloads 308

Authors: Parham Bakhtiari

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Between 1910 and 1912, Claude Debussy recorded twelve of his solo piano pieces. Although Debussy frequently provided advice to his students on performing while they followed the written notes when performing, his personal recordings are characterized by creative liberties and unique freedom interpretations. Debussy's use of numerous interpretive gestures in these recordings is fascinating and corresponds with the techniques utilized by French Baroque keyboard performers. This paper will situate Debussy's presentation in the Baroque musical approach. Initially, we will discuss the recording by analyzing Welte-Mignon's used technology to guarantee the reliability of these recordings. Then, we will find commonalities in the intricate performances of harpsichord musicians who played in the 1600s and 1700s and recordings of Debussy. Finally, by drawing comparisons, we will review the patterns by contrasting Debussy's execution with recordings of the same pieces from the latter half of the 20th century as striving for improved presentations while limiting artistic freedom.

Keywords: music, Debussy, piano, performance, prelude

Procedia PDF Downloads 46

Authors: Ryan B. Simpson, Margaret A. Waskow, Aishwarya Venkat, Elena N. Naumova

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The Centers for Disease Control and Prevention (CDC) estimate that 31 known foodborne pathogens cause 9.4 million cases of these illnesses annually in US. Over 90% of these illnesses are associated with exposure to Campylobacter, Cryptosporidium, Cyclospora, Listeria, Salmonella, Shigella, Shiga-Toxin Producing E.Coli (STEC), Vibrio, and Yersinia. Contaminated products contain parasites typically causing an intestinal illness manifested by diarrhea, stomach cramping, nausea, weight loss, fatigue and may result in deaths in fragile populations. Since 1998, the National Outbreak Reporting System (NORS) has allowed for routine collection of suspected and laboratory-confirmed cases of food poisoning. While retrospective analyses have revealed common pathogen-specific seasonal patterns, little is known concerning the stability of those patterns over time and whether they can be used for preventative forecasting. The objective of this study is to construct a calendar of foodborne outbreaks of nine infections based on the peak timing of outbreak incidence in the US from 1996 to 2017. Reported cases were abstracted from FoodNet for Salmonella (135115), Campylobacter (121099), Shigella (48520), Cryptosporidium (21701), STEC (18022), Yersinia (3602), Vibrio (3000), Listeria (2543), and Cyclospora (758). Monthly counts were compiled for each agent, seasonal peak timing and peak intensity were estimated, and the stability of seasonal peaks and synchronization of infections was examined. Negative Binomial harmonic regression models with the delta-method were applied to derive confidence intervals for the peak timing for each year and overall study period estimates. Preliminary results indicate that five infections continue to lead as major causes of outbreaks, exhibiting steady upward trends with annual increases in cases ranging from 2.71% (95%CI: [2.38, 3.05]) in Campylobacter, 4.78% (95%CI: [4.14, 5.41]) in Salmonella, 7.09% (95%CI: [6.38, 7.82]) in E.Coli, 7.71% (95%CI: [6.94, 8.49]) in Cryptosporidium, and 8.67% (95%CI: [7.55, 9.80]) in Vibrio. Strong synchronization of summer outbreaks were observed, caused by Campylobacter, Vibrio, E.Coli and Salmonella, peaking at 7.57 ± 0.33, 7.84 ± 0.47, 7.85 ± 0.37, and 7.82 ± 0.14 calendar months, respectively, with the serial cross-correlation ranging 0.81-0.88 (p < 0.001). Over 21 years, Listeria and Cryptosporidium peaks (8.43 ± 0.77 and 8.52 ± 0.45 months, respectively) have a tendency to arrive 1-2 weeks earlier, while Vibrio peaks (7.8 ± 0.47) delay by 2-3 weeks. These findings will be incorporated in the forecast models to predict common paths of the spread, long-term trends, and the synchronization of outbreaks across etiological agents. The predictive modeling of foodborne outbreaks should consider long-term changes in seasonal timing, spatiotemporal trends, and sources of contamination.

Keywords: foodborne outbreak, national outbreak reporting system, predictive modeling, seasonality

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Authors: Ahlem Dhahri, Waleed Omri, Audrey Becuwe, Abdelwahed Omri

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In industrial processes, decision-making ranges across different scales, from process control to supply chain management. The purchasing decision-making process in the supply chain is presently gaining more attention as a critical contributor to the company's strategic success. Given the scarcity of thorough summaries in the prior studies, this bibliometric analysis aims to adopt a meticulous approach to achieve quantitative knowledge on the constantly evolving subject of purchasing decision-making in supply chain management. Through bibliometric analysis, we examine a sample of 358 peer-reviewed articles from the Scopus database. VOSviewer and Gephi software were employed to analyze, combine, and visualize the data. Data analytic techniques, including citation network, page-rank analysis, co-citation, and publication trends, have been used to identify influential works and outline the discipline's intellectual structure. The outcomes of this descriptive analysis highlight the most prominent articles, authors, journals, and countries based on their citations and publications. The findings from the research illustrate an increase in the number of publications, exhibiting a slightly growing trend in this field. Co-citation analysis coupled with content analysis of the most cited articles identified five research themes mentioned as follows integrating sustainability into the supplier selection process, supplier selection under disruption risks assessment and mitigation strategies, Fuzzy MCDM approaches for supplier evaluation and selection, purchasing decision in vendor problems, decision-making techniques in supplier selection and order lot sizing problems. With the help of a graphic timeline, this exhaustive map of the field illustrates a visual representation of the evolution of publications that demonstrate a gradual shift from research interest in vendor selection problems to integrating sustainability in the supplier selection process. These clusters offer insights into a wide variety of purchasing methods and conceptual frameworks that have emerged; however, they have not been validated empirically. The findings suggest that future research would emerge with a greater depth of practical and empirical analysis to enrich the theories. These outcomes provide a powerful road map for further study in this area.

Keywords: bibliometric analysis, citation analysis, co-citation, Gephi, network analysis, purchasing, SCM, VOSviewer

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Authors: Tokuei Sako, Paul-Antoine Hervieux

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The energy-level structure of a pair of electron and positron confined in a quasi-one-dimensional nano-scale potential well has been investigated focusing on its trend in the small limit of confinement strength ω, namely, the Wigner molecular regime. An anisotropic Gaussian-type basis functions supplemented by high angular momentum functions as large as l = 19 has been used to obtain reliable full configuration interaction (FCI) wave functions. The resultant energy spectrum shows a band structure characterized by ω for the large ω regime whereas for the small ω regime it shows an energy-level pattern dominated by excitation into the in-phase motion of the two particles. The observed trend has been rationalized on the basis of the nodal patterns of the FCI wave functions.

Keywords: confined systems, positron, wave function, Wigner molecule, quantum dots

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Authors: Marzena Tomaszewska, Beata Bilska, Danuta Kolozyn-Krajewska

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Food loss and food waste are a global problem of the modern economy. The research undertaken aimed to analyze how food is handled in catering establishments when it comes to food waste and to demonstrate main ways of management with foods/dishes not served to consumers. A survey study was conducted from January to June 2019. The selection of catering establishments participating in the study was deliberate. The study included establishments located only in Mazowieckie Voivodeship (Poland). 42 completed questionnaires were collected. In some questions, answers were based on a 5-point scale of 1 to 5 (from 'always'/'every day' to 'never'). The survey also included closed questions with a suggested cafeteria of answers. The respondents stated that in their workplaces, dishes served cold and hot ready meals are discarded every day or almost every day (23.7% and 20.5% of answers respectively). A procedure most frequently used for dealing with dishes not served to consumers on a given day is their storage at a cool temperature until the following day. In the research, 1/5 of respondents admitted that consumers 'always' or 'usually' leave uneaten meals on their plates, and over 41% 'sometimes' do so. It was found additionally that food not used in food service sector is most often thrown into a public container for rubbish. Most often thrown into the public container (with communal trash) were: expired products (80.0%), plate waste (80.0%), and inedible products (fruit and vegetable peels, egg shells) (77.5%). Most frequently into the container dedicated only for food waste were thrown out used deep-frying oil (62.5%). 10% of respondents indicated that inedible products in their workplaces is allocate for animal feeds. Food waste in the food service sector still remains an insufficiently studied issue, as owners of these objects are often unwilling to disclose data pertaining to the subject. Incorrect ways of management with foods not served to consumers were observed. There is the need to develop the educational activities for employees and management in the context of food waste management in the food service sector. This publication has been developed under the contract with the National Center for Research and Development No Gospostrateg1/385753/1/NCBR/2018 for carrying out and funding of a project implemented as part of the 'The social and economic development of Poland in the conditions of globalizing markets - GOSPOSTRATEG' program entitled 'Developing a system for monitoring wasted food and an effective program to rationalize losses and reduce food wastage' (acronym PROM).

Keywords: food waste, inedible products, plate waste, used deep-frying oil

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Authors: Bhumi Shah

Abstract:

The aim of the study is to create understanding of communication strategies followed by Jain mendicants, educators, and lay persons. Second objective of the study is to see ancient means of communication have reformed in this digital generation. For these purposes of the study, research was carried out among Jain lay persons, educators and mendicants. To understand how traditional methods of communication affect the understanding of Jain religion. The paper attempts further elaborate and analyse various degrees of involvement and expectations of Jain Lay persons and mendicants in the process of religious discourse. In doing so the paper would provide an in- depth debate and discussion about communication patterns and the actual impact to the original meaning of the religion. The study was carried out in the city of Ahmedabad India, where Jains are concentrated in urban settings. In depth interviews were carried out as to understand different communication strategies followed by them.

Keywords: customs, ethics, Jainism, Jain mendicants, religious communication, traditions, rituals

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Authors: R. I. You, C. L. Ho, M. S. Dai, H. M. Hung, S. F. Yen, C. S. Chen, T. Y. Chao

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Neutrophils are the most abundant innate immune cells to against invading microorganisms. Numerous data shown neutrophils have plasticity in response to physiological and pathological conditions. Tumor-associated neutrophils (TAN) exist in distinct types of tumor and play an important role in cancer biology. Different transcriptomic profiles of neutrophils in tumor and non-tumor samples have been identified. Several miRNAs have been recognized as regulators of gene expression in neutrophil, which may have key roles in neutrophil activation. However, the miRNAs expression patterns in TAN are not well known. To address this question, magnetic bead isolated neutrophils from tumor-bearing mice were used in this study. We analyzed production of reactive oxygen species (ROS) by luminol-dependent chemiluminescence assay. The expression of miRNAs targeting NADPH oxidase, ROS generation and autophagy was explored using quantitative real-time polymerase chain reaction. Our data suggest that tumor environment influence neutrophil develop to differential states of activation via miRNAs regulation.

Keywords: tumor-associated neutrophil, miRNAs, neutrophil, ROS

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Authors: Jachin Pousson, Valdis Bernhofs

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Applications of the binaural sound experience are wide-ranged. This paper focuses on the interaction between binaural tones and human emotion with an aim to apply the resulting knowledge artistically. For the purpose of this study, binaural music is defined as musical arrangements of sound which are made of combinations of binaural difference tones. Here, the term ‘binaural difference tone’ refers to the pulsating tone heard within the brain which results from listening to slightly differing audio frequencies or pure pitches in each ear. The frequency or tempo of the pulsations is the sum of the precise difference between the frequencies two tones and is measured in beats per second. Polyrhythmic pulsations that can be heard within combinations of these differences tones have shown to be able to entrain or tune brainwave patterns to frequencies which have been linked to mental states which can be characterized by different levels of attention and mood.

Keywords: binaural auditory pulsations, brainwave entrainment, emotion, music composition

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Authors: N. Najafi, Laleh Maleknia , M. E. Olya

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An aqueous conductive ink of single-walled carbon nanotubes for inkjet printing was formulated. To prepare the homogeneous SWCNT ink in a size small enough not to block a commercial inkjet printer nozzle, we used a kinetic ball-milling process to disperse the SWCNTs in an aqueous suspension. When a patterned electrode was overlaid by repeated inkjet printings of the ink on various types of fabric, the fabric resistance decreased rapidly following a power law, reaching approximately 760 X/sq, which is the lowest value ever for a dozen printings. The Raman and Fourier transform infrared spectra revealed that the oxidation of the SWCNTs was the source of the doped impurities. This study proved also that the droplet ejection velocity can have an impact on the CNT distribution and consequently on the electrical performances of the ink.

Keywords: ink-jet printing, carbon nanotube, fabric ink, cotton fabric, raman spectroscopy, fourier transform infrared spectroscopy, dozen printings

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Authors: Danny Barash

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Riboswitches are RNA genetic control elements that were originally discovered in bacteria and provide a unique mechanism of gene regulation. They work without the participation of proteins and are believed to represent ancient regulatory systems in the evolutionary timescale. One of the biggest challenges in riboswitch research is that many are found in prokaryotes but only a small percentage of known riboswitches have been found in certain eukaryotic organisms. The few examples of eukaryotic riboswitches were identified using sequence-based bioinformatics search methods that include some slight structural considerations. These pattern-matching methods were the first ones to be applied for the purpose of riboswitch detection and they can also be programmed very efficiently using a data structure called affix arrays, making them suitable for genome-wide searches of riboswitch patterns. However, they are limited by their ability to detect harder to find riboswitches that deviate from the known patterns. Several methods have been developed since then to tackle this problem. The most commonly used by practitioners is Infernal that relies on Hidden Markov Models (HMMs) and Covariance Models (CMs). Profile Hidden Markov Models were also carried out in the pHMM Riboswitch Scanner web application, independently from Infernal. Other computational approaches that have been developed include RMDetect by the use of 3D structural modules and RNAbor that utilizes Boltzmann probability of structural neighbors. We have tried to incorporate more sophisticated secondary structure considerations based on RNA folding prediction using several strategies. The first idea was to utilize window-based methods in conjunction with folding predictions by energy minimization. The moving window approach is heavily geared towards secondary structure consideration relative to sequence that is treated as a constraint. However, the method cannot be used genome-wide due to its high cost because each folding prediction by energy minimization in the moving window is computationally expensive, enabling to scan only at the vicinity of genes of interest. The second idea was to remedy the inefficiency of the previous approach by constructing a pipeline that consists of inverse RNA folding considering RNA secondary structure, followed by a BLAST search that is sequence-based and highly efficient. This approach, which relies on inverse RNA folding in general and our own in-house fragment-based inverse RNA folding program called RNAfbinv in particular, shows capability to find attractive candidates that are missed by Infernal and other standard methods being used for riboswitch detection. We demonstrate attractive candidates found by both the moving-window approach and the inverse RNA folding approach performed together with BLAST. We conclude that structure-based methods like the two strategies outlined above hold considerable promise in detecting riboswitches and other conserved RNAs of functional importance in a variety of organisms.

Keywords: riboswitches, RNA folding prediction, RNA structure, structure-based methods

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Authors: Katarzyna Neffe-Skocinska, Marzena Tomaszewska, Beata Bilska, Dorota Zielinska, Monika Trzaskowska, Anna Lepecka, Danuta Kolozyn-Krajewska

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The aim of the study was to assess Polish consumer behavior towards food waste, including knowledge of information on food labels. The survey was carried out using the CAPI (computer assisted personal interview) method, which involves interviewing the respondent using mobile devices. The research group was a representative sample for Poland due to demographic variables: gender, age, place of residence. A total of 1.115 respondents participated in the study (51.1% were women and 48.9% were men). The questionnaire included questions on five thematic aspects: 1. General knowledge and sources of information on the phenomenon of food waste; 2. Consumption of food after the date of minimum durability; 3. The meanings of the phrase 'best before ...'; 4. Indication of the difference between the meaning of the words 'best before ...' and 'use by'; 5. Indications products marked with the phrase 'best before ...'. It was found that every second surveyed Pole met with the topic of food waste (54.8%). Among the respondents, the most popular source of information related to the research topic was television (89.4%), radio (26%) and the Internet (24%). Over a third of respondents declared that they consume food after the date of minimum durability. Only every tenth (9.8%) respondent does not pay attention to the expiry date and type of consumed products (durable and perishable products). Correctly 39.8% of respondents answered the question: How do you understand the phrase 'best before ...'? In the opinion of 42.8% of respondents, the statements 'best before ...' and 'use by' mean the same thing, while 36% of them think differently. In addition, more than one-fifth of respondents could not respond to the questions. In the case of products of the indication information 'best before ...', more than 40% of the respondents chosen perishable products, e.g., yoghurts and durable, e.g., groats. A slightly lower percentage of indications was recorded for flour (35.1%), sausage (32.8%), canned corn (31.8%), and eggs (25.0%). Based on the assessment of the behavior of Polish consumers towards the phenomenon of food waste, it can be concluded that respondents have elementary knowledge of the study subject. Noteworthy is the good conduct of most respondents in terms of compliance with shelf life and dates of minimum durability of food products. The publication was financed on the basis of an agreement with the National Center for Research and Development No. Gospostrateg 1/385753/1/NCBR/2018 for the implementation and financing of the project under the strategic research and development program social and economic development of Poland in the conditions of globalizing markets – GOSPOSTRATEG - acronym PROM.

Keywords: food waste, shelf life, dates of durability, consumer knowledge and behavior

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Authors: Amarachukwu B. Isiaka, Vivian N. Anakwenze, Chinyere C. Ezemba, Chiamaka R. Ilodinso, Chikodili G. Anaukwu, Chukwuebuka M. Ezeokoli, Ugonna H. Uzoka

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Infectious diseases continue to pose significant threats to global public health, necessitating advanced and timely detection methods for effective outbreak management. This study explores the integration of artificial intelligence (AI) in the early detection and management of infectious disease outbreaks. Leveraging vast datasets from diverse sources, including electronic health records, social media, and environmental monitoring, AI-driven algorithms are employed to analyze patterns and anomalies indicative of potential outbreaks. Machine learning models, trained on historical data and continuously updated with real-time information, contribute to the identification of emerging threats. The implementation of AI extends beyond detection, encompassing predictive analytics for disease spread and severity assessment. Furthermore, the paper discusses the role of AI in predictive modeling, enabling public health officials to anticipate the spread of infectious diseases and allocate resources proactively. Machine learning algorithms can analyze historical data, climatic conditions, and human mobility patterns to predict potential hotspots and optimize intervention strategies. The study evaluates the current landscape of AI applications in infectious disease surveillance and proposes a comprehensive framework for their integration into existing public health infrastructures. The implementation of an AI-driven early detection system requires collaboration between public health agencies, healthcare providers, and technology experts. Ethical considerations, privacy protection, and data security are paramount in developing a framework that balances the benefits of AI with the protection of individual rights. The synergistic collaboration between AI technologies and traditional epidemiological methods is emphasized, highlighting the potential to enhance a nation's ability to detect, respond to, and manage infectious disease outbreaks in a proactive and data-driven manner. The findings of this research underscore the transformative impact of harnessing AI for early detection and management, offering a promising avenue for strengthening the resilience of public health systems in the face of evolving infectious disease challenges. This paper advocates for the integration of artificial intelligence into the existing public health infrastructure for early detection and management of infectious disease outbreaks. The proposed AI-driven system has the potential to revolutionize the way we approach infectious disease surveillance, providing a more proactive and effective response to safeguard public health.

Keywords: artificial intelligence, early detection, disease surveillance, infectious diseases, outbreak management

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