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Algebraic periods and minimal number of periodic points for smooth self-maps of 1-connected 4-manifolds with definite intersection forms
- Haibao Duan
- Grzegorz Graff
- Jerzy Jezierski
- Adrian Myszkowski
2024 Pełny tekst Journal of Fixed Point Theory and Applications
Let M be a closed 1-connected smooth 4-manifolds, and let r be a non-negative integer. We study the problem of finding minimal number of r-periodic points in the smooth homotopy class of a given map f: M-->M. This task is related to determining a topological invariant D^4_r[f], defined in Graff and Jezierski (Forum Math 21(3):491–509, 2009), expressed in terms of Lefschetz numbers of iterations and local fixed point indices of iterations. Previously, the invariant was computed for self-maps of some 3-manifolds. In this paper, we compute the invariants D^4_r[f] for the self-maps of closed 1-connected smooth 4-manifolds with definite intersection forms (i.e., connected sums of complex projective planes). We also present some efficient algorithmic approach to investigate that problem.
Alginate-based sorbents in miniaturized solid phase extraction techniques - Step towards greenness sample preparation
- Natalia Jatkowska
2024 Pełny tekst TRAC-TRENDS IN ANALYTICAL CHEMISTRY
In response to growing concerns about environmental degradation, one of the main areas of research activity in recent years has been to make sample preparation methods more sustainable and eco-friendly. The increasing greenness of this step can be achieved by minimizing the usage of reagents, automating individual stages, saving energy and time, and using non-toxic, biodegradable substances. Therefore, the use of natural materials as sorbents in miniaturized extraction techniques is becoming a main trend. One of the natural material that is increasingly being used, not only due to eco-friendly nature but also because of their easy applicability to various sample preparation techniques, is alginate hydrogel. Following this trend, this review discusses the recent application of alginate-based sorbents in various microextraction techniques, focusing on functionalization approaches that enhance extraction performance. Additionally, the green profile of alginate-based sorbent microextraction approaches, along with the sorbent synthesis, were investigated.
Algorithmic Human Resources Management
- Łukasz Sienkiewicz
2024
The rapid evolution of Digital Human Resources Management has introduced a transformative era where algorithms play a pivotal role in reshaping the landscape of workforce management. This transformation is encapsulated in the concepts of algorithmic management and algorithmic Human Resource Management (HRM). The integration of advanced analytics, predictive and prescriptive analytics and the power of Artificial Intelligence (AI) has given rise to algorithmic approaches that go beyond traditional human-centric decision-making. This paradigm shift is marked by comprehensive data collection, real-time responses to data influencing management decisions and automated decision-making processes. The culmination of algorithmic management is illustrated in a scheme where human-configured management processes are automated, leading to autonomous decision-making by an information system. The ongoing development of AI-driven algorithms, adapting and becoming self-learning, raises the prospect of increased automation, potentially leading to the displacement of human managers. This chapter provides a comprehensive overview of the evolution of algorithmic management and algorithmic HRM, setting the stage for a deeper exploration of their implications on organisational decision-making, employee management and the future of algorithm-supported management. While algorithmic HRM brings benefits to organisations it also poses risks, such as hidden errors and ethical concerns, emphasising the need for transparency and responsible application. Unconscious system errors, especially in fully automated systems, can lead to detrimental personnel decisions. Organisations must actively counteract potential negative consequences, striking a balance between technology and human decision-making, fostering organisational culture that embraces digital transformation while prioritising the human element. Enterprises should view technology as a tool to enhance work processes, focusing on connecting people and technology to create an innovative and inclusive work environment.
Alphitobius diaperinus larvae (lesser mealworm) as human food – An approval of the European Commission – A critical review
- Shahida Anusha Siddiqui
- Y.s. Wu
- K. Vijeepallam
- K. Batumalaie
- M.h.m. Hatta
- H. Lutuf
- Roberto Castro Munoz
- I. Fernando
- S.a. Ibrahim
2024 Pełny tekst Journal of Insects as Food and Feed
Due to the increasing threat of climate change and the need for sustainable food sources, human consumption of edible insects or entomophagy has gained considerable attention globally. The larvae of Alphitobius diaperinus Panzer (Coleoptera: Tenebrionidae), also known as the lesser mealworm, have been identified as a promising candidate for mass-rearing as a food source based the on evaluation on several aspects such as the production process, the microbiological and chemical composition, and the potential allergenicity to humans. As a consequence, the European Commission has recently approved the utilization of lesser mealworms as human foods. Lesser mealworms are considered a good source of protein, with a protein content ranging from 50-65% of their dry weight and containing various essential amino acids. Lesser mealworms are also rich in other essential nutrients such as iron, calcium, and vitamins B12 and B6. Furthermore, the hydrolysates of lesser mealworms are known to contain antioxidants, suggesting the therapeutic properties of the insects. To enable and ensure a continuous supply of lesser mealworms, various rearing procedures of the insects and information on optimal environmental rearing conditions have been reported. However, like other edible insects, lesser mealworms are still not commonly consumed in Western countries because of various consumer- and product-related factors. Ultimately, the European Commission’s approval of lesser mealworms as a novel food is a key milestone in the development of the insect food industry. Embracing the consumption of edible insects can help address the challenges of feeding a growing population, mitigate the environmental impact of food production, and promote a more sustainable and resilient food system for the future.
An absorbing set for the Chialvo map
- Paweł Pilarczyk
- Grzegorz Graff
2024 Communications in Nonlinear Science and Numerical Simulation
The classical Chialvo model, introduced in 1995, is one of the most important models that describe single neuron dynamics. In order to conduct effective numerical analysis of this model, it is necessary to obtain a rigorous estimate for the maximal bounded invariant set. We discuss this problem, and we correct and improve the results obtained by Courbage and Nekorkin (2010). In particular, we provide an explicit formula for an absorbing set for the Chialvo neuron model. We also introduce the notion of a weakly absorbing set, outline the methodology for its construction, and show its advantage over an absorbing set by means of numerical computations.
An Adaptive Network Model for a Double Bias Perspective on Learning from Mistakes within Organizations
- Mojgan Hosseini
- Jan Treur
- Wioleta Kucharska
2024
Although making mistakes is a crucial part of learning, it is still often being avoided in companies as it is considered as a shameful incident. This goes hand in hand with a mindset of a boss who dominantly believes that mistakes usually have negative consequences and therefore avoids them by only accepting simple tasks. Thus, there is no mechanism to learn from mistakes. Employees working for and being influenced by such a boss also strongly believe that mistakes usually have negative consequences but in addition they believe that the boss never makes mistakes, it is often believed that only those who never make mistakes can be bosses and hold power. That’s the problem, such kinds of bosses do not learn. So, on the one hand, we have bosses who select simple tasks to be always seen as perfect. Therefore, also they believe they should avoid mistakes. On the other hand, there exists a mindset of a boss who is not limited to simple tasks, he/she accepts more complex tasks and therefore in the end has better general performance by learning from mistakes. This then also affects the mindset and actions of employees in the same direction. This paper investigates the consequences of both attitudes for the organizations. It does so by computational analysis based on an adaptive dynamical systems modeling approach represented in a network format using the self-modeling network modeling principle.
An Adversarial Machine Learning Approach on Securing Large Language Model with Vigil, an Open-Source Initiative
- Kushal Pokhrel
- Cesar Sanín
- Md Rafiqul Islam
- Edward Szczerbicki
2024 Pełny tekst Procedia Computer Science
Several security concerns and efforts to breach system security and prompt safety concerns have been brought to light as a result of the expanding use of LLMs. These vulnerabilities are evident and LLM models have been showing many signs of hallucination, repetitive content generation, and biases, which makes them vulnerable to malicious prompts that raise substantial concerns in regard to the dependability and efficiency of such models. It is vital to have a complete grasp of the complex behaviours of malicious attackers in order to build effective strategies for protecting modern artificial intelligence (AI) systems through the development of effective tactics. The purpose of this study is to look into some of these aspects and propose a method for preventing devastating possibilities and protecting LLMs from potential threats that attackers may pose. Vigil is an open-source LLM prompt security scanner, that is accessible as a Python library and REST API, specifically to solve these problems by employing a sophisticated adversarial machine-learning algorithm. The entire objective of this study is to make use of Vigil as a security scanner. and asses its efficiency. In this case study, we shed some light on Vigil, which effectively recognises and helps LLM prompts by identifying two varieties of threats: malicious and benign.
An Analysis of Airline GRI and SDG Reporting
- Eljas Johansson
2024 Pełny tekst
This study aims to increase our understanding of the Global Reporting Initiative’s (GRI) topic-specific disclosures and the sustainable development goals (SDGs) addressed in the global passenger airline industry’s sustainability reporting (SR). Based on a quantitative content analysis of the industry’s sustainability reports from the financial year 2019 (FY19), this study reveals that airlines focused more on reporting environmental issues, especially emissions, than economic or social dimensions, demonstrating this emission-intensive industry’s responsiveness to stakeholders’ information needs. However, a closer look at the reported impacts shows that many topic-specific disclosures and SDGs, which industry associations have not identified as relevant to the industry, were also mentioned across the reports. Moreover, the results indicated a broader use of SDGs in Asia-Pacific reports than in European. The results are expected to interest practitioners and academics in assessing and developing the industry’s SR.
An analytical approach to determine the health benefits and health risks of consuming berry juices
- Magdalena Fabjanowicz
- Anna Rożańska
- Nada S. Abdelwahab
- Marina Pereira-Coelho
- Isabel Cristina da Silva Haas
- Luiz Augusto dos Santos Madureira
- Justyna Płotka-Wasylka
2024 Pełny tekst FOOD CHEMISTRY
Food products composition analysis is a prerequisite for verification of product quality, fulfillment of regulatory enforcements, checking compliance with national and international food standards, contracting specifications, and nutrient labeling requirements and providing quality assurance for use of the product for the supplemen- tation of other foods. These aspects also apply to the berry fruit and berry juice. It also must be noted that even though fruit juices are generally considered healthy, there are many risks associated with mishandling both fruits and juices themselves. The review gathers information related with the health benefits and risk associated with the consumption of berry fruit juices. Moreover, the focus was paid to the quality assurance of berry fruit juice. Thus, the analytical methods used for determination of compounds influencing the sensory and nutritional characteristics of fruit juice as well as potential contaminants or adulterations.
An ANN-Based Method for On-Load Tap Changer Control in LV Networks with a Large Share of Photovoltaics—Comparative Analysis
- Klara Janiga
- Piotr Miller
- Robert Małkowski
- Michał Izdebski
2024 ENERGIES
The paper proposes a new local method of controlling the on-load tap changer (OLTC) of a transformer to mitigate negative voltage phenomena in low-voltage (LV) networks with a high penetration of photovoltaic (PV) installations. The essence of the method is the use of the load compensation (LC) function with settings determined via artificial neural network (ANN) algorithms. The proposed method was compared with other selected local methods recommended in European regulations, in particular with those currently required by Polish distribution system operators (DSOs). Comparative studies were performed using the model of the 116-bus IEEE test network, taking into account the unbalance in the network and the voltage variation on the medium voltage (MV) side.
An annotated timeline of sensitivity analysis
- Marta Kuc-Czarnecka
- Stefano Tarantolo
- Federico Ferretti
- Samuele Lo Piano
- Mariia Kozlova
- Alesio Lachi
- Rosana Rosati
- Arnald Puy,
- Pamphile Roy
- Giulia Vannucci
- Andrea Saltelli,
2024 Pełny tekst ENVIRONMENTAL MODELLING & SOFTWARE
The last half a century has seen spectacular progresses in computing and modelling in a variety of fields, applications, and methodologies. Over the same period, a cross-disciplinary field known as sensitivity analysis has been making its first steps, evolving from the design of experiments for laboratory or field studies, also called ‘in-vivo’, to the so-called experiments ‘in-silico’. Some disciplines were quick to realize the importance of sensitivity analysis, whereas others are still lagging behind. Major tensions within the evolution of this discipline arise from the interplay between local vs global perspectives in the analysis as well as the juxtaposition of the mathematical complexification and the desire for practical applicability. In this work, we retrace these main steps with some attention to the methods and through a bibliometric survey to assess the accomplishments of sensitivity analysis and to identify the potential for its future advancement with a focus on relevant disciplines, such as the environmental field.
An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
- Sasirekha Natarajan
- Smitha Kurian
- Parameshachari Bidare Divakarachari
- Przemysław Falkowski-Gilski
2024 EXPERT SYSTEMS
Sentiment analysis is an automated approach which is utilized in process of analysing textual data to describe public opinion. The sentiment analysis has major role in creating impact in the day-to-day life of individuals. However, a precise interpretation of text still relies as a major concern in classifying sentiment. So, this research introduced Bidirectional Long Short Term Memory with Ranger AdaBelief Optimizer (Bi-LSTM RAO) to classify sentiment of tweets. Initially, data is obtained from Twitter API, Sentiment 140 and Stanford Sentiment Treebank-2 (SST-2). The raw data is pre-processed and it is subjected to feature extraction which is performed using Bag of Words (BoW) and Term Frequency-Inverse Document Frequency (TF-IDF). The feature selection is performed using Gazelle Optimization Algorithm (GOA) which removes the irrelevant or redundant features that maximized model performance and classification is performed using Bi LSTM–RAO. The RAO optimizes the loss function of Bi-LSTM model that maximized accuracy. The classification accuracy of proposed method for Twitter API, Sentiment 140 and SST 2 dataset is obtained as 909.44%, 99.71% and 99.86%, respectively. These obtained results are comparably higher than ensemble framework, Robustly Optimized BERT and Gated Recurrent Unit (RoBERTa-GRU), Logistic Regression-Long Short Term Memory (LR-LSTM), Convolutional Bi-LSTM, Sentiment and Context Aware Attention-based Hybrid Deep Neural Network (SCA-HDNN) and Stochastic Gradient Descent optimization based Stochastic Gate Neural Network (SGD-SGNN).
An Efficient PEEC-Based Method for Full-Wave Analysis of Microstrip Structures
- Jinyan Ma
- Da Li
- Hanzhi Ma
- Ruifeng Li
- Ling Zhang
- Michał Mrozowski
- Erping Li
2024 IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY
This article introduces an efficient method for the equivalent circuit characterization and full-wave analysis of microstrip structures, leveraging the full-wave partial element equivalent circuit (PEEC). In particular, the multilayered Green's function is evaluated using the discrete complex-image method (DCIM) and employed to establish the mixed potential integral equations. The proposed strategy considers time delays for the retarded electric and magnetic couplings, offering a new efficient full-wave approach to extract equivalent circuit components, which encapsulate the contributions of the quasi-static, surface-wave, and complex images. It is noted that the proposed full-wave PEEC strategy allows each component contribution derived from DCIM to be efficiently represented as frequency-independent lumped circuit elements and corresponding frequency factors, thereby simplifying the extraction process of the entire frequency-dependent lumped elements in the traditional PEEC method. Moreover, the proposed PEEC model, equipped with full-wave equivalent circuits, offers clear physical insight into electromagnetic behaviors, thereby facilitating design and optimization. Finally, the accuracy and efficiency of the proposed PEEC model are fully demonstrated through various examples and experiments.
An Example of Using Low-Cost LiDAR Technology for 3D Modeling and Assessment of Degradation of Heritage Structures and Buildings
- Piotr Kędziorski
- Marcin Jagoda
- Paweł Tysiąc
- Jacek Katzer
2024 Materials
This article examines the potential of low-cost LiDAR technology for 3D modeling and assessment of the degradation of historic buildings, using a section of the Koszalin city walls in Poland as a case study. Traditional terrestrial laser scanning (TLS) offers high accuracy but is expensive. The study assessed whether more accessible LiDAR options, such as those integrated with mobile devices such as the Apple iPad Pro, can serve as viable alternatives. This study was conducted in two phases—first assessing measurement accuracy and then assessing degradation detection—using tools such as the FreeScan Combo scanner and the Z+F 5016 IMAGER TLS. The results show that, while low-cost LiDAR is suitable for small-scale documentation, its accuracy decreases for larger, complex structures compared to TLS. Despite these limitations, this study suggests that low-cost LiDAR can reduce costs and improve access to heritage conservation, although further development of mobile applications is recommended.
An Extremely Compact Frequency Reconfigurable Antenna Diplexer Employing Dielectric Liquids
- Rusan Kumar Barik
- Xiaohu Wu
- Xiaoguang Liu
- Sławomir Kozieł
2024 IEEE Antennas and Wireless Propagation Letters
The letter presents an extremely compact frequency reconfigurable antenna diplexer based on fluidic channels for sub6 GHz applications. The proposed antenna diplexer is modelled by employing half-mode (HM) and quarter-mode (QM) substrateintegrated rectangular cavities, two slots, orthogonal feed lines, and fluidic vias. To comprehend the radiation mechanism, the equivalent circuit, electric field distributions, and frequency responses are analyzed. Utilization of HM and QM cavities that are loaded with slots results in an extremely compact antenna diplexer. Three fluidic vias are bored from the bottom plane of each cavity and filled with different dielectric liquids to enable frequency reconfigurability. For validation of the concept, an antenna diplexer is built and demonstrated. The constructed antenna prototype has a small footprint 0.078lg2 with 15% and 16% of reconfigurability in lower and upper frequency bands, respectively. The proposed antenna offers high-isolation exceeding 28 dB, realized gain better than > 3.8 dBi, front-to-back-ratio of > −18 dB, and cross-polarization level of > −18 dB. A good consistency is obtained in between full-wave simulations and measurement.
An image processing approach for fatigue crack identification in cellulose acetate replicas
- Krzysztof Pałczyński
- Jan Seyda
- Dariusz Skibicki
- Łukasz Pejkowski
- Wojciech Macek
2024 ENGINEERING FAILURE ANALYSIS
The cellulose acetate replication technique is an important method for studying material fatigue. However, extracting accurate information from pictures of cellulose replicas poses challenges because of distortions and numerous artifacts. This paper presents an image processing procedure for effective fatigue crack identification in plastic replicas. The approach employs thresholding, adaptive Gaussian thresholding, and Otsu binarization to convert gray-scale images into binary ones, enhancing crack visibility. Morphological operations refine object shapes, and Connected Components Analysis facilitates crack identification. Despite limited data, the handcrafted feature extraction algorithm proves robust, addressing challenges. The algorithm shows efficacy in detecting cracks as small as 30 μm, even in the presence of cellulose replication artifacts. The results highlight ability to capture significant cracks’ orientation, length, and growth stages, essential for understanding fatigue mechanisms. Analysis of results, especially evaluation metrics encompassing false positives and false negatives, provides a comprehensive understanding of the algorithm’s strengths and limitations. The proposed tool is available on GitHub.
An improved methodology for accelerated marine immersed corrosion testing of ship structural components
- Krzysztof Wołoszyk
- Emil Roch
- Beata Zima
- Yordan Garbatov
2024 Ships and Offshore Structures
Corrosion degradation is a prominent ageing mechanism in engineering structures (e.g. ships and offshore structures), leading to safety concerns and significant economic expenses. This study presents an improved methodology for indoor accelerated corrosion testing of structural components. The method involves controlling natural factors (oxygen saturation, temperature, salinity, and flow rate) to accelerate the corrosion in a controlled environment. The study uses small coupons, medium specimens, and stiffened plates made of steel with different thicknesses. Significant degradation acceleration was achieved compared to natural conditions (approx. twenty times faster). The mean corrosion equals 3.3 mm/year with a maximum 10% variation for different specimen sizes and thicknesses. A novel approach to account for the mass of corrosion products during periodical measurements was proposed and validated. The improved methodology offers an efficient and accurate way to simulate marine immersed corrosion, enabling further research on corrosion degradation behaviour and resistance in ship structures.
An improvement of body surface area formulas using the 3D scanning technique
- Grzegorz Redlarski
- Sławomir Kozieł
- Marek Krawczuk
- Janusz Siebert
- Marek Tałałaj
- Aleksander Pałkowski
- Piotr Tojza
- Zuzanna Cieślikowska
- Leszek Litzbarski
2024 Pełny tekst International Journal of Occupational Medicine and Environmental Health
Objectives: Body surface area (BSA) is one of the major parameters used in several medical fields. However, there are concerns raised about its usefulness, mostly due to the ambiguity of its estimation. Material and Methods: Authors have conducted a voluntary study to investigate BSA distribution and estimation in a group of 179 adult people of various sex, age, and physique. Here, there is provided an extended analysis of the majority of known BSA formulas. Furthermore, it was supplement with a comparison with the authors' propositions of enhanced formulas coefficients for known formulas models as well as with new power models based on an increased number of anthropometric data. Results: Introduction of the enhanced formulas coefficients cause a reduction of at least 30.5% in mean absolute error and 21.1% in maximum error in comparison with their known counterparts. Conclusions: In the context of the analysis presented it can be stated that the development of a single universal body surface area formula, based on a small number of state variables, is not possible. Therefore, it is necessary and justified to search for new estimation models that allow for quick and accurate calculation of body surface area for the entire population, regardless of individual body variations. The new formulas presented are such an alternative, which achieves better results than the previously known methods. Int J Occup Med Environ Health 2024;37(2)
An Innovative Floating System with a Savonius Rotor as a Horizontal-Axis Wind Turbine
- Joanna Grzelak
- Lara Guijarro Carrillo
- Jacek Nakielski
- Michał Piotrowicz
- Krzysztof Doerffer
2024 Pełny tekst Polish Maritime Research
In this project, an innovative wind turbine was designed for a floating plant. A large Savonius rotor was replaced with a double-rotor wind turbine implemented as a horizontal-axis turbine. This double rotor was positioned on the tip of a thrust plate and fixed to the deck of a catamaran. Simple 2D numerical simulations were performed to confirm the effectiveness of the concept. An analysis of the floating system configuration was carried out, and the loads and stresses on the system components were verified. Next, floating supports with appropriate sizes were selected to counteract the forces on the wind turbine system. Finally, an anchoring system with full rotational freedom was selected for the f loating platform. The present work was conducted as part of a Master’s thesis.
An Innovative New Approach to Light Pollution Measurement by Drone
- Katarzyna Bobkowska
- Paweł Burdziakowski
- Paweł Tysiąc
- Mariusz Pulas
2024 Drones
The study of light pollution is a relatively new and specific field of measurement. The current literature is dominated by articles that describe the use of ground and satellite data as a source of information on light pollution. However, there is a need to study the phenomenon on a microscale, i.e., locally within small locations such as housing estates, parks, buildings, or even inside buildings. Therefore, there is an important need to measure light pollution at a lower level, at the low level of the skyline. In this paper, the authors present a new drone design for light pollution measurement. A completely new original design for an unmanned platform for light pollution measurement is presented, which is adapted to mount custom sensors (not originally designed to be mounted on a unmanned aerial vehicles) allowing registration in the nadir and zenith directions. The application and use of traditional photometric sensors in the new configuration, such as the spectrometer and the sky quality meter (SQM), is presented. A multispectral camera for nighttime measurements, a calibrated visible-light camera, is used. The results of the unmanned aerial vehicle (UAV) are generated products that allow the visualisation of multimodal photometric data together with the presence of a geographic coordinate system. This paper also presents the results from field experiments during which the light spectrum is measured with the installed sensors. As the results show, measurements at night, especially with multispectral cameras, allow the assessment of the spectrum emitted by street lamps, while the measurement of the sky quality depends on the flight height only up to a 10 m above ground level.