bluuebunny/crossref_metadata_2025 huggingface dataset:
Influence of a Novel Double Tempering Process on the Microstructure and Mechanical Properties of Cu-Alloyed Austempered Ductile Iron with Possible Nano (Micro)-Characterization Using Neutron Beam Techniques
Authors: Čatipović Nikša , Rogante Massimo , Avdušinović Hasan , Grgić Karla
Published: September 2023

In this paper, a novel method for the double heat treatment of ductile iron was applied. Ten sets of specimens (three specimens in each set) of ductile cast iron (DCI) containing 0.51% wt. Cu were prepared and converted to austenitic ductile iron. All specimens were austenitized at 850 °C for 60 min and annealed at 420 °C, 331 °C and 250 °C for 120, 68 and 30 min, respectively. Five sets of samples were then annealed at 500 °C for 60 min, creating a novel double heat treatment process for annealing. Finally, all specimens were slowly cooled in air at ambient temperature. Tensile strength, hardness and elongation were measured in all specimens to compare the specimens with and without subsequent tempering. A microstructural analysis was also performed, which showed that the microstructure changed for the specimens that were subsequently tempered with. The results show that specimens with subsequent tempering have slightly higher hardness, a small decrease in tensile strength and significantly higher elongation. In addition, specimens with subsequent tempering exhibit more uniform mechanical properties compared to specimens without subsequent tempering. The use of neutron beam techniques was proposed to further characterize the newly formed microstructure after subsequent tempering.
Influence of TiC Particles on Mechanical and Tribological Characteristics of Advanced Aluminium Matrix Composites Fabricated through Ultrasonic-Assisted Stir Casting
Authors: Golla Chitti Babu , Babar Pasha Mahammod , Rao Rajamalla Narasimha , Ismail Syed , Gupta Manoj
Published: September 2023

The present investigation highlights the development of high-performance materials in the construction materials industry, with a special focus on the production of aluminium matrix composites (AMCs) containing titanium carbide (TiC) particles. The stir casting method with ultrasonic assistance was employed to enhance the mechanical and tribological properties. ASTM standards were employed to evaluate the influence of TiC particles on density, hardness (VHN), ultimate tensile strength (UTS), and wear resistance at various TiC weight fraction percentages (0.0 wt.%, 2.0 wt.%, 4.0 wt.%, 6.0 wt.%, and 8.0 wt.%). Field emission scanning electron microscopy (FESEM) and X-ray diffraction (XRD) analysis were performed to analyse the microstructural changes and elemental phases present in the synthesised composite. Results revealed that the incorporation of 8 wt.% TiC reinforcement in the metal matrix composites demonstrated significant improvements compared to the base alloy. In particular, a substantial enhancement in hardness by 32%, a notable increase of 68% in UTS, and a significant 80% rise in yield strength were observed when contrasted with the pure aluminium alloy. The tensile fracture analysis of the specimens revealed the presence of dimples, voids, and cracks, suggesting a brittle nature. To assess the wear characteristics of the composites, dry sliding wear experiments were performed using a pin-on-disc wear tester. Incorporation of TiC particles resulted in a lower coefficient of friction than the base alloy, with the lowest friction coefficient being recorded at 0.266 for 6 wt.% TiC, according to the data. FESEM and energy-dispersive X-ray spectroscopy (EDXS) were used to examine the surfaces of the worn pin. Overall, the inclusion of TiC reinforcement particles in the matrix alloy greatly enhanced the wear resistance and friction coefficient of the Al-6TiC composites. Ploughing and adhesion under lower loads and delamination under higher loads were the wear mechanisms observed in the wear test.
DNA Barcodes for Evolution and Biodiversity
Authors: Koblmüller Stephan
Published: September 2023

Questions centered around how biological diversity is being generated and maintained, as well as how this biodiversity can be conserved/protected, are being frequently asked in basic and applied evolutionary biological and biodiversity research [...]
Characterization of Lacinutrix neustonica sp. nov., Isolated from the Sea Surface Microlayer of Brackish Lake Shihwa, South Korea
Authors: Choi Jy Young , Kim Soo Yoon , Hong Yeon Woo , Kim Bok Jin , Shin Dong Young , Kang Jin Kyeong , Cho Byung Cheol , Hwang Chung Yeon
Published: September 2023

A Gram-negative, strictly aerobic, non-motile, slightly curved rod-shaped bacterial strain, designated as HL-RS19T, was isolated from a sea surface microlayer (SML) sample of the brackish Lake Shihwa. Here, we characterized the new strain HL-RS19T using a polyphasic approach to determine its taxonomic position. A phylogenetic analysis of its 16S rRNA gene sequence revealed that strain HL-RS19T belonged to the genus Lacinutrix and was closely related to L. mariniflava AKS432T (97.9%), L. algicola AKS293T (97.8%), and other Lacinutrix species (<97.3%). The complete genome sequence of strain HL-RS19T comprised a circular chromosome of 3.9 Mbp with a DNA G+C content of 35.2%. Genomic comparisons based on the average nucleotide identity and digital DNA-DNA hybridization showed that strain HL-RS19T was consistently discriminated from its closely related taxa in the genus Lacinutrix. Strain HL-RS19T showed optimal growth at 20–25 °C, pH 6.5–7.0, and 3.0–3.5% (w/v) sea salts. The major fatty acids (>5%) of strain HL-RS19T were identified as iso-C15:1 G (16.5%), iso-C16:0 3-OH (12.9%), anteiso-C15:1 A (9.9%), anteiso-C15:0 (9.7%), iso-C15:0 (9.0%), and iso-C15:0 3-OH (8.3%). The polar lipids consisted of phosphatidylethanolamine, three unidentified aminolipids, an unidentified phospholipid, and two unidentified lipids. The major respiratory quinone was MK-6. Based on phylogenetic, genomic, phenotypic, and chemotaxonomic data, strain HL-RS19T represents a novel species belonging to the genus Lacinutrix, for which the name Lacinutrix neustonica sp. nov. is proposed. The type strain is HL-RS19T (=KCCM 90497T = JCM 35710T). The genome sequence analysis of strain HL-RS19T suggests that it may be well adapted to a harsh SML environment and is likely involved in arsenic cycling, potentially contributing to the bioremediation of anthropogenic arsenic pollution.
The Diversity of Arbuscular Mycorrhizal Fungi and Their Associations in South America: A Case Study of Argentinean and Brazilian Cattle Raising Productive Ecosystems: A Review
Authors: Lugo Mónica A. , Ontivero Roberto Emanuel , Iriarte Hebe J. , Yelikbayev Bakhytzhan , Pagano Marcela C.
Published: September 2023

Mycorrhizal fungus diversity is an ecosystem health indicator, and thus, the appreciation of the aboveground as well as the belowground biota, such as fungi associated with natural and managed ecosystems, is essential to provide sustainable products and suggestions to farmers. Less is known about the totally arbuscular mycorrhizal fungi (AMF) and fungal endophytes useful to agroecology, which are environment friendly microbial biofertilizers to mitigate the complications of conventional farming. Specific AMF are found in most covers; grassy ecosystems are increasingly investigated through their exclusive fungal species that improve sustainable cultivation. Different grazed pastures, forages, and their diversity are important objects of study either in economic or ecological scope. Based on recent reports, the occurrence of AMF in grasslands and pastures is significant, supporting more diverse AMF than native forests. Therefore, we show current information on these topics. We conducted a Web of Science search of published articles on AMF, pastures, and grasslands and analyzed them. The results confirmed the important role of pH as the driver of AMF diversity distribution between the grassy ecosystems from Argentina and Brazil. In grasslands, the main family represented was Glomeraceae, while pastures maintain predominantly Acaulosporaceae. Brazilian grasslands and pastures presented four times the AMF richness of those from Argentina.
Bradykinin-Mediated Angioedema Induced by Commonly Used Cardiovascular Drugs
Authors: Hahn Janina , Greve Jens , Bas Murat , Kojda Georg
Published: September 2023

ACE inhibitors, sartans, and sacubitril are among the most important drugs for the prevention of cardiovascular mortality and morbidity. At the same time, they are known to cause non-allergic bradykinin-mediated angioedema, a potentially fatal swelling of the mucosa and/or submucosa and deeper skin without signs of urticaria or pruritus, occurring mainly in the head and neck region. In contrast with hereditary angioedema, which is also mediated by bradykinin, angioedema triggered by these drugs is by far the most common subtype of non-allergic angioedema. The molecular mechanisms underlying this type of angioedema, which are discussed here, are not yet sufficiently understood. There are a number of approved drugs for the prevention and treatment of acute attacks of hereditary angioedema. These include inhibitors of bradykinin synthesis that act as kallkrein inhibitors, such as the parenterally applied plasma pool, and recombinant C1 esterase inhibitor, ecallantide, lanadelumab, and the orally available berotralstat, as well as the bradykinin receptor type 2 antagonist icatibant. In contrast, no diagnostic tools, guidelines, or treatments have yet been approved for the diagnosis and treatment of acute non-allergic drug-induced angioedema, although it is more common and can take life-threatening courses. Approved specific drugs and a structured diagnostic workflow are needed for this emergency diagnosis.
Patients’ Perspective on Barriers to Utilization of a Diabetic Retinopathy Screening Service
Authors: Owusu-Afriyie Bismark , Gende Theresa , Tapilas Martin , Zimbare Nicholas , Kewande Jeffrey
Published: September 2023

This study was conducted to determine the barriers to the utilization of diabetic retinopathy (DR) screening in Papua New Guinea (PNG). A list of patients booked for DR screening at Madang Provincial Hospital Eye Clinic (MPHEC) between January 2017 and December 2021 who had not been screened was retrieved, and the patients were invited to participate in the study. The data were collected using a structured questionnaire, and IBM Statistical Package for Social Sciences version 26 was used for the analysis. p < 0.05 was considered statistically significant. One hundred and twenty-nine patients (37.4%) did not attend DR screening for the period under study. The study response rate was 80.6%. The mean ± SD age of the respondents was 51.5 ± 10.9 years. The majority of the study respondents were female (62.5%), people living in rural settings (53.8%), and farmers (22.1%). Time constraints, poor knowledge about DR, and long waiting periods at the DR screening center were the main barriers to the uptake of DR screening. Compared to respondents in urban communities, those in rural settings were significantly concerned about cost (p < 0.001), travel distance to the MPHEC (p < 0.001), and poor information about DR screening (p = 0.002). More than half of the respondents (63.5%) had discontinued using pharmacotherapy for DM. There is a high rate of nonadherence to diabetes (DM) and DR treatment in PNG. There is a need for public health campaigns about DM and strategic DR screening at the community level in PNG and similar countries.
Imaging of Acute Abdominopelvic Pain in Pregnancy and Puerperium—Part I: Obstetric (Non-Fetal) Complications
Authors: Bonito Giacomo , Masselli Gabriele , Gigli Silvia , Ricci Paolo
Published: September 2023

Acute abdominopelvic pain in pregnant and postpartum patients presents clinical and therapeutic challenges, often requiring quick and accurate imaging diagnosis. Ultrasound remains the primary imaging investigation. Magnetic resonance imaging (MRI) has been shown to be a powerful diagnostic tool in the setting of acute abdominal pain during pregnancy and puerperium. MRI overcomes some drawbacks of US, avoiding the ionizing radiation exposure of a computed tomography (CT) scan. Although CT is not usually appropriate in pregnant patients, it is crucial in the emergency evaluation of postpartum complications. The aim of this article is to provide radiologists with a thorough familiarity with the common and uncommon pregnancy and puerperium abdominal emergencies by illustrating their imaging appearances. The present first section will review and discuss the imaging findings for acute abdominopelvic pain of obstetric (non-fetal) etiology.
MicroRNAs as Biomarkers and Therapeutic Targets for Acute Kidney Injury
Authors: Tsuji Kenji , Nakanoh Hiroyuki , Fukushima Kazuhiko , Kitamura Shinji , Wada Jun
Published: September 2023

Acute kidney injury (AKI) is a clinical syndrome where a rapid decrease in kidney function and/or urine output is observed, which may result in the imbalance of water, electrolytes and acid base. It is associated with poor prognosis and prolonged hospitalization. Therefore, an early diagnosis and treatment to avoid the severe AKI stage are important. While several biomarkers, such as urinary L-FABP and NGAL, can be clinically useful, there is still no gold standard for the early detection of AKI and there are limited therapeutic options against AKI. miRNAs are non-coding and single-stranded RNAs that silence their target genes in the post-transcriptional process and are involved in a wide range of biological processes. Recent accumulated evidence has revealed that miRNAs may be potential biomarkers and therapeutic targets for AKI. In this review article, we summarize the current knowledge about miRNAs as promising biomarkers and potential therapeutic targets for AKI, as well as the challenges in their clinical use.
Detection of Mosaic Absence of Heterozygosity (AOH) Using Low-Pass Whole Genome Sequencing in Prenatal Diagnosis: A Preliminary Report
Authors: Lü Yan , Jiang Yulin , Zhou Xiya , Hao Na , Xu Chenlu , Guo Ruidong , Chang Jiazhen , Li Mengmeng , Zhang Hanzhe , Zhou Jing , Zhang Wei (Victor) , Qi Qingwei
Published: September 2023

Objective: Mosaicism is a common biological phenomenon in organisms and has been reported in many types of chromosome abnormalities, including the absence of heterozygosity (AOH). Due to the detection limitations of the sequencing approach, mosaic AOH events are rarely assessed in clinical cases. Herein, we report the performance of mosaic AOH identification using a low-pass (5~8-fold) WGS method (termed ‘CMA-seq’, an abbreviation for ‘Chromosome Analysis by Sequencing’) in fetal genetic diagnosis. Methods: Thirty AOH-negative, eleven constitutional AOH, and three mosaic AOH samples were collected as training data sets to develop the algorithm and evaluate the suitable thresholds for distinguishing mosaic AOH. Twenty-four new chromosomal aberrant cases, along with sixteen constitutional AOH samples, which were previously ascertained via the SNP-array-based method, were used as a validation data set to measure the performance in terms of sensitivity and specificity of this algorithm. Results: A new statistic, ‘D-value’, was implemented to identify and distinguish constitutional and mosaic AOH events. The reporting thresholds for constitutional and mosaic AOH were also established. In the validation set consisting of 24 new cases, seven constitutional AOH cases and 1 mosaic AOH case were successfully identified, indicating that the results were consistent with those of the SNP-array-based method. The results of all sixteen constitutional AOH validation samples also met the threshold requirements. Conclusions: In this study, we developed a new bioinformatic algorithm to accurately distinguish mosaic AOH from constitutional AOH by low-pass WGS. However, due to the small sample size of the training data set, the algorithm proposed in this manuscript still needs further refinements.
Optical Coherence Tomography as a Valuable Tool for the Evaluation of Cutaneous Kaposi Sarcoma Treated with Imiquimod 5% Cream
Authors: Cantisani Carmen , Baja Alexandru-Vasile , Gargano Luca , Rossi Giovanni , Ardigò Marco , Soda Giuseppe , Boostani Mehdi , Kiss Norbert , Pellacani Giovanni
Published: September 2023

Kaposi sarcoma (KS) is a rare disease that was not frequently identified before the widespread occurrence of AIDS. Even today, it remains a challenge for physicians to diagnose, particularly in its early stages, often requiring referral to specialists and further investigations. Dermoscopy, a non-invasive imaging technique, reveals a distinctive rainbow pattern that strongly indicates KS. Moreover, advanced imaging tools like optical coherence tomography (OCT) can provide additional information though specific disease-related patterns have not been fully established yet. These emerging techniques show promise in facilitating early diagnosis of skin-related KS and monitoring the effectiveness of treatments. However, biopsy remains the definitive method for confirming the disease. In this study, we present two cases of cutaneous Kaposi sarcoma, documented using OCT, both before and after treatment with imiquimod 5% cream. The study highlights the potential of OCT in evaluating disease progression and treatment response, as well as the usefulness of dermoscopy in detecting early indicators of KS. By integrating these advanced imaging techniques, the diagnosis and management of cutaneous KS could be improved, leading to timely interventions and better patient outcomes.
Imaging of Acute Abdominopelvic Pain in Pregnancy and Puerperium—Part II: Non-Obstetric Complications
Authors: Masselli Gabriele , Bonito Giacomo , Gigli Silvia , Ricci Paolo
Published: September 2023

Emergency imaging in pregnancy and puerperium poses unique challenges both for clinicians and radiologists, requiring timely and accurate diagnosis. Delay in treatment may result in poor outcomes for both the patient and the foetus. Pregnant and puerperal patients may present in the emergency setting with acute abdominopelvic pain for various complications that can be broadly classified into obstetric and non-obstetric related diseases. Ultrasonography (US) is the primary diagnostic imaging test; however, it may be limited due to the patient’s body habitus and the overlapping of bowel loops. Computed tomography (CT) carries exposure to ionising radiation to the foetus, but may be necessary in selected cases. Magnetic resonance imaging (MRI) is a valuable complement to US in the determination of the etiology of acute abdominal pain and can be used in most settings, allowing for the identification of a broad spectrum of pathologies with a limited protocol of sequences. In this second section, we review the common non-obstetric causes for acute abdominopelvic pain in pregnancy and post partum, offering a practical approach for diagnosis and pointing out the role of imaging methods (US, MRI, CT) with the respective imaging findings.
Biventricular Tissue Tracking with Cardiovascular Magnetic Resonance: Reference Values of Left- and Right-Ventricular Strain
Authors: Barison Andrea , Ceolin Roberto , Palmieri Alessandro , Tamborrino Pietro Paolo , Todiere Giancarlo , Grigoratos Chrysanthos , Gueli Ignazio Alessio , De Gori Carmelo , Clemente Alberto , Pistoia Laura , Pepe Alessia , Aquaro Giovanni Donato , Positano Vincenzo , Emdin Michele , Cademartiri Filippo , Meloni Antonella
Published: September 2023

We derived reference values of left-ventricular (LV) and right-ventricular (RV) strain parameters in a cohort of 100 healthy subjects by feature tracking cardiac magnetic resonance (FT-CMR). Global and regional strain values were calculated for the LV; circumferential and radialSAX strain parameters were derived from the short-axis (SAX) stack, while longitudinal and radialLAX strain parameters were assessed in three long-axis (LAX) views. Only global longitudinal strain (GLS) was calculated for the RV. Peak global LV circumferential strain was −16.7% ± 2.1%, LV radialSAX strain was 26.4% ± 5.1%, LV radialLAX strain was 31.1% ± 5.2%, LV GLS was −17.7% ± 1.9%, and RV GLS was −23.9% ± 4.1%. Women presented higher global LV and RV strain values than men; all strain values presented a weak relationship with body surface area, while there was no association with age or heart rate. A significant association was detected between all LV global strain measures and LV ejection fraction, while RV GLS was correlated to RV end-diastolic volume. The intra- and inter-operator reproducibility was good for all global strain measures. In the regional analysis, circumferential and radial strain values resulted higher at the apical level, while longitudinal strain values were higher at the basal level. The assessment of cardiac deformation by FT-CMR is feasible and reproducible and gender-specific reference values should be used.
Ordinal Conditional Entropy Displays Reveal Intrinsic Characteristics of the Rosenberg Self-Esteem Scale
Authors: Furfaro Emanuela , Hsieh Fushing
Published: September 2023

Individual subjects’ ratings neither are metric nor have homogeneous meanings, consequently digital- labeled collections of subjects’ ratings are intrinsically ordinal and categorical. However, in these situations, the literature privileges the use of measures conceived for numerical data. In this paper, we discuss the exploratory theme of employing conditional entropy to measure degrees of uncertainty in responding to self-rating questions and that of displaying the computed entropies along the ordinal axis for visible pattern recognition. We apply this theme to the study of an online dataset, which contains responses to the Rosenberg Self-Esteem Scale. We report three major findings. First, at the fine scale level, the resultant multiple ordinal-display of response-vs-covariate entropy measures reveals that the subjects on both extreme labels (high self-esteem and low self-esteem) show distinct degrees of uncertainty. Secondly, at the global scale level, in responding to positively posed questions, the degree of uncertainty decreases for increasing levels of self-esteem, while, in responding to negative questions, the degree of uncertainty increases. Thirdly, such entropy-based computed patterns are preserved across age groups. We provide a set of tools developed in R that are ready to implement for the analysis of rating data and for exploring pattern-based knowledge in related research.
Revocable Signature Scheme with Implicit and Explicit Certificates
Authors: Pejaś Jerzy , Hyla Tomasz , Zabierowski Wojciech
Published: September 2023

This paper addresses the certificate revocation problem and proposes the first revocable pairing-based signature scheme with implicit and explicit certificates (IE-RCBS-kCAA). We should no longer discuss whether to revoke certificates but how to do it effectively, ensuring both the scalability of the revocation operation and the non-repudiation of the signature in the short or long term. Under the computational difficulty assumptions of the modified collusion attack algorithm with k traitors (k-mCAA) and discrete logarithm (DL) problems, we demonstrate that our scheme is secure against existential unforgeability under chosen message attacks (EUF-IERCBS-kCAA-CMA) in a random oracle model. The proposed solution is scaled and allows the use of many trusted status authorities that issue explicit short-term certificates confirming the validity of explicit long-term certificates. Furthermore, we demonstrate that our signature scheme has a short-term non-repudiation property for the shell validity model.
“A Constant Juggling Act”—The Daily Life Experiences and Well-Being of Doctoral Students
Authors: Prendergast Alison , Usher Ruth , Hunt Eithne
Published: September 2023

(1) Background: There are increasing numbers of doctoral students globally. Poor mental health and well-being among university students, including doctoral students, is a growing concern globally, not least in this post-pandemic era. Engaging in a range of activities every day and maintaining balance between necessary and desired activities is believed to improve health and increase well-being. However, little is currently known about the daily life, activity balance and well-being of doctoral students. This study explored and described the daily life experiences of doctoral students and how pursuing their degree impacted their activity balance and well-being. (2) Method: Purposive sampling methods were used in this qualitative interpretive descriptive study to recruit 10 doctoral students in an Irish university. The data were generated through individual semi-structured interviews and thematically analysed. (3) Findings: Doctoral students have a range of roles, responsibilities and activities that they need to and want to engage in daily. For many, balancing their daily activities and roles alongside their doctoral degree is challenging. Undertaking a doctoral degree can have both a positive and negative impact on well-being. (4) Conclusions: Obtaining an insight into the perspectives and daily life experiences of doctoral students allows for a better understanding of the students’ journey. Supporting the well-being of doctoral students is essential to enhance their doctoral education and assist them in successfully completing their degree.
Software Requirement Risk Prediction Using Enhanced Fuzzy Induction Models
Authors: Mamman Hussaini , Balogun Abdullateef Oluwagbemiga , Basri Shuib , Capretz Luiz Fernando , Adeyemo Victor Elijah , Imam Abdullahi Abubakar , Kumar Ganesh
Published: September 2023

The development of most modern software systems is accompanied by a significant level of uncertainty, which can be attributed to the unanticipated activities that may occur throughout the software development process. As these modern software systems become more complex and drawn out, escalating software project failure rates have become a critical concern. These unforeseeable uncertainties are known as software risks, and they emerge from many risk factors inherent to the numerous activities comprising the software development lifecycle (SDLC). Consequently, these software risks have resulted in massive revenue losses for software organizations. Hence, it is imperative to address these software risks, to curb future software system failures. The subjective risk assessment (SRM) method is regarded as a viable solution to software risk problems. However, it is inherently reliant on humans and, therefore, in certain situations, imprecise, due to its dependence on an expert’s knowledge and experience. In addition, the SRM does not allow repeatability, as expertise is not easily exchanged across the different units working on a software project. Developing intelligent modelling methods that may offer more unbiased, reproducible, and explainable decision-making assistance in risk management is crucial. Hence, this research proposes enhanced fuzzy induction models for software requirement risk prediction. Specifically, the fuzzy unordered rule induction algorithm (FURIA), and its enhanced variants based on nested subset selection dichotomies, are developed for software requirement risk prediction. The suggested fuzzy induction models are based on the use of effective rule-stretching methods for the prediction process. Additionally, the proposed FURIA method is enhanced through the introduction of nested subset selection dichotomy concepts into its prediction process. The prediction performances of the proposed models are evaluated using a benchmark dataset, and are then compared with existing machine learning (ML)-based and rule-based software risk prediction models. From the experimental results, it was observed that the FURIA performed comparably, in most cases, to the rule-based and ML-based models. However, the FURIA nested dichotomy variants were superior in performance to the conventional FURIA method, and rule-based and ML-based methods, with the least accuracy, area under the curve (AUC), and Mathew’s correlation coefficient (MCC), with values of approximately 98%.
Improved Smooth Watermarking Methods for Detecting Replay Attacks in Process Control Systems
Authors: Zhao Shunli , Li Qisen , Cao Haifeng
Published: September 2023

Network attack detection is a crucial issue in cyber–physical systems. One classical type of network attack is the replay attack. Although the watermarking scheme has proven to be effective in detecting replay attacks, it may confront numerous challenges when applied to process control systems. The watermarking signal, which consists of independent and identically distributed Gaussian noise sequences, responds slowly to industrial process control systems. To address this issue, two novel smooth watermarking methods are proposed. The smooth watermarking signals exhibit low-frequency characteristics, enabling them to effectively handle large inertia processes. The proposed schemes are validated through two simulated examples. These examples indicate that the proposed methods can significantly enhance detection efficiency while minimizing additional control performance loss.
A Universal-Verification-Methodology-Based Testbench for the Coverage-Driven Functional Verification of an Instruction Cache Controller
Authors: Liu Cong , Xu Xinyu , Chen Zhenjiao , Wang Binghao
Published: September 2023

The Cache plays an important role in computer architecture by reducing the access time of the processor and improving its performance. The hardware design of the Cache is complex and it is challenging to verify its functions, so the traditional Verilog-based verification method is no longer applicable. This paper proposes a comprehensive and efficient verification testbench based on the SystemVerilog language and universal verification methodology (UVM) for an instruction Cache (I-Cache) controller. Corresponding testcases are designed for each feature of the I-Cache controller and automatically executed using a python script on an electronic design automation (EDA) tool. After simulating a large number of testcases, the statistics reveal that the module’s code coverage is 99.13%. Additionally, both the function coverage and the assertion coverage of the module reach 100%. Our results demonstrate that these coverage metrics meet the requirements and ensure the thoroughness of function verification. Furthermore, the established verification testbench exhibits excellent scalability and reusability, making it easily applicable to higher-level verification scenarios.
A Comparative Study of Post-Quantum Cryptographic Algorithm Implementations for Secure and Efficient Energy Systems Monitoring
Authors: Satrya Gandeva Bayu , Agus Yosafat Marselino , Mnaouer Adel Ben
Published: September 2023

The Internet of Things (IoT) has assumed a pivotal role in the advancement of communication technology and in our daily lives. However, an IoT system such as a smart grid with poorly designed topology and weak security protocols might be vulnerable to cybercrimes. Exploits may arise from sensor data interception en route to the intended consumer within an IoT system. The increasing integration of electronic devices interconnected via the internet has galvanized the acceptance of this technology. Nonetheless, as the number of users of this technology surges, there must be an aligned concern to ensure that security measures are diligently enforced within IoT communication systems, such as in smart homes, smart cities, smart factories, smart hospitals, and smart grids. This research addresses security lacunae in the topology and configuration of IoT energy monitoring systems using post-quantum cryptographic techniques. We propose tailored implementations of the Rivest–Shamir–Adleman (RSA), N-th degree Truncated Polynomial Ring Units (NTRU), and a suite of cryptographic primitives based on Module Learning With Rounding (Saber) as post-quantum cryptographic candidate algorithms for IoT devices. These aim to secure publisher–subscriber end-to-end communication in energy system monitoring. Additionally, we offer a comparative analysis of these tailored implementations on low-resource devices, such as the Raspberry Pi, during data transmission using the Message Queuing Telemetry Transport (MQTT) protocol. Results indicate that the customized implementation of NTRU outperforms both SABER and RSA in terms of CPU and memory usage, while Light SABER emerges as the front-runner when considering encryption and decryption delays.
Large Language Models as Recommendation Systems in Museums
Authors: Trichopoulos Georgios , Konstantakis Markos , Alexandridis Georgios , Caridakis George
Published: September 2023

This paper proposes the utilization of large language models as recommendation systems for museum visitors. Since the aforementioned models lack the notion of context, they cannot work with temporal information that is often present in recommendations for cultural environments (e.g., special exhibitions or events). In this respect, the current work aims to enhance the capabilities of large language models through a fine-tuning process that incorporates contextual information and user instructions. The resulting models are expected to be capable of providing personalized recommendations that are aligned with user preferences and desires. More specifically, Generative Pre-trained Transformer 4, a knowledge-based large language model is fine-tuned and turned into a context-aware recommendation system, adapting its suggestions based on user input and specific contextual factors such as location, time of visit, and other relevant parameters. The effectiveness of the proposed approach is evaluated through certain user studies, which ensure an improved user experience and engagement within the museum environment.
Energy-Aware Evolutionary Algorithm for Scheduling Jobs of Charging Electric Vehicles in an Autonomous Charging Station
Authors: Różycki Rafał , Waligóra Grzegorz
Published: September 2023

The paper considers an innovative model of autonomous charging stations where a program implementing a scheduling algorithm and a set of jobs being scheduled are driven by the same common power source. It is assumed that one of the well-known local search metaheuristics—an evolutionary algorithm—is used for the scheduling process. The algorithm is designed to search for a sequence of charging jobs resulting in a schedule of the minimum length. Since processors with variable processing speeds can be used for computations, this has interesting consequences both from a theoretical and practical point of view. It is shown in the paper that the problem of choosing the right processor speed under given constraints and an assumed scheduling criterion is a non-trivial one. We formulate a general problem of determining the computation speed of the evolutionary algorithm based on the proposed model of a computational task and the adopted problem of scheduling charging jobs. The novelty of the paper consists of two aspects: (i) proposing the new model of the autonomous charging station operating according to the basics of edge computing; and (ii) developing the methodology for dynamically changing the computational speed, taking into account power and energy constraints as well as the results of computations obtained in the current iteration of the algorithm. Some approaches for selecting the appropriate speed of computations are proposed and discussed. Conclusions and possible directions for future research are also given.
Piezoelectric Energy Harvester for Harnessing Rotational Kinetic Energy through Linear Energy Conversion
Authors: Abdulkhaliq Habib , Crawley Fergus , Luk Patrick , Luo Zhenhua
Published: September 2023

Real-time condition monitoring of various types of machinery using sensor technology has gained significant importance in recent years. However, relying on batteries to power these sensors proves to be sub-optimal, as it necessitates regular charging or replacement. To address this, harvesting waste energy from ambient sources emerges as a more efficient alternative. Everyday applications like vehicle wheels, fans, and turbines present ambient sources of waste rotational energy. In this study, we propose a novel rotational energy harvester design that converts rotational energy into linear energy. This linear energy impacts a piezoelectric disk, generating an electric potential. Through simulations, the expected electric potential at varying frequencies was evaluated. Subsequently, experimental tests were conducted by connecting the harvester to a rectifier for AC-to-DC signal conversion and an oscilloscope for voltage measurement. A DC motor replicated the rotational motion at the frequencies from the simulation, and the power output was measured. Using the power transfer theorem, simulation and experimental power outputs were calculated, resulting in values of 188, 513, and 1293 μW and 88.89, 336, and 923 μW, respectively. These results reveal that the designed harvester is competitive with those of existing rotational energy harvester designs, demonstrating the promising potential of this novel harvester.
Reliability of Microinverters for Photovoltaic Systems: High-Temperature Accelerated Testing with Fixed and Cyclic Power Stresses
Authors: Afridi Muhammad , Tatapudi Sai , Flicker Jack , Srinivasan Devarajan , Tamizhmani Govindasamy
Published: September 2023

This paper presents an extended, accelerated reliability evaluation of forty microinverters, module-level power electronic (MLPE) units for photovoltaic (PV) modules. The forty microinverters were stressed at two static temperatures (65 °C and 75 °C) with two input power profiles (fixed and cyclic power). These power profiles were employed to replicate field-use conditions closely. The accelerated testing was performed for an extended duration (over a period of 15,000 h) to determine the acceleration factor and estimate the service life of microinverters in field-use conditions. Electrical performance and thermal data were continuously monitored during the experiment for all the microinverters. The accelerated stress testing had no failures even after 15,000 h of operation. Using the Arrhenius life-stress model along with average field-measured temperature and military handbook-based analysis, it was estimated that the microinverters should be able to survive for 24–48 years during their service life in field conditions, with a reliability of 74%, having a lower one-sided confidence bound of 95%, obtained using the classical success run approach. Moreover, the lifetime of microinverters was statistically analyzed using a Weibull distribution model. Weibull slope factors were used to estimate a range of characteristic lifetime periods and the reliability of the microinverters with a 95% lower one-sided confidence limit, demonstrating a similar or even exceeding the lifetime of the associated PV modules of 25 years.
Sustainable Consumption of Households According to the Zero Waste Concept
Authors: Bogusz Małgorzata , Matysik-Pejas Renata , Krasnodębski Andrzej , Dziekański Paweł
Published: September 2023

The actions, decisions and behavior of consumers in a circular economy are defined as a circular consumption system. The circular economy is an alternative economic model to the linear model of production and consumption. This model is in line with the zero waste concept, which according to the Zero Waste International Alliance, is an ethical, economical, efficient and forward-looking concept in which consumer behavior includes buying products, caring for them and then recycling or reusing them. This is closely linked to adopting and committing to the circular business model of extending and reusing products. The aim of the study was to identify and describe consumer behavior and activities related to the zero waste concept. The analysis was conducted in the context of reusable products. The research was based on the CAWI method. The tool used to obtain the information was a structured questionnaire. The survey included 821 respondents from Poland, Slovakia and Ukraine. The survey shows that consumers are becoming increasingly aware of the consequences of consumption not based on choices with a positive attitude towards the environment. In addition, consumer sensitivity to environmental problems is growing. Growing consumer awareness and the promotion of healthy lifestyles by environmental organizations and movements are reversing unfavorable trends in favor of conscious consumption based on rational consumer choices, which translates into economic effects for households. The study found that the behavior of many respondents fits into the zero waste concept, implementing habits on a daily basis that are in line with sustainable consumption.
Comparative Analysis of Data-Driven Algorithms for Building Energy Planning via Federated Learning
Authors: Ali Mazhar , Singh Ankit Kumar , Kumar Ajit , Ali Syed Saqib , Choi Bong Jun
Published: September 2023

Building energy planning is a challenging task in the current mounting climate change scenario because the sector accounts for a reasonable percentage of global end-use energy consumption, with a one-fifth share of global carbon emissions. Energy planners rely on physical model-based prediction tools to conserve energy and make decisions towards decreasing energy consumption. For precise forecasting, such a model requires the collection of an enormous number of input variables, which is time-consuming because not all the parameters are easily available. Utilities are reluctant to share retrievable consumer information because of growing concerns regarding data leakage and competitive energy markets. Federated learning (FL) provides an effective solution by providing privacy preserving distributed training to relieve the computational burden and security concerns associated with centralized vanilla learning. Therefore, we aimed to comparatively analyze the effectiveness of several data-driven prediction algorithms for learning patterns from data-efficient buildings to predict the hourly consumption of the building sector in centralized and FL setups. The results provided comparable insights for predicting building energy consumption in a distributed setup and for generalizing to diverse clients. Moreover, such research can benefit energy designers by allowing them to use appropriate algorithms via transfer learning on data of similar features and to learn personalized models in meta-learning approaches.
The Impact of Energy Consumption Costs on the Profitability of Production Companies in Poland in the Context of the Energy Crisis
Authors: Milewska Beata , Milewski Dariusz
Published: September 2023

The paper presents the results of the authors’ research on the share of energy costs in revenues and their impact on the profitability of companies. This research was inspired by a large increase in energy prices in 2022. The authors analyzed the shares of energy consumption costs in production companies from various industries, using various sources: scientific literature, expert studies, and statistical data. Based on the results of these analyses, the authors simulated the impact of changes in energy prices on the profitability of companies. The research results are as follows: according to the authors, the share of these costs in the value of sales is much lower (several percent) than presented in various literature sources (a dozen or so, and even up to 30% in some cases). Despite this, however, the change in energy prices should significantly reduce profitability according to the simulations conducted by the authors. However, the financial reports analyzed by the authors show that profitability in many cases not only did not deteriorate, but revenues and profits increased in a large number of companies. In many cases, this can be explained by the actions taken by companies to reduce energy consumption costs and by increases in product prices. The authors’ research also shows that if factors such as the specificity of the industry or the size of the company have an impact on energy efficiency, it is only to a small extent. The share of energy costs in sales and financial results, even within a given industry and in companies of similar size, varies greatly. The authors therefore believe that the effectiveness of the management of a given company has the greatest impact. Therefore, the results of the analysis differ significantly from the results of studies presented in the literature. Energy consumption data were analyzed using various literature sources from different countries. However, the main analyses conducted by the authors focused on Poland.
Optimizing Solar Parabolic Trough Receivers with External Fins: An Experimental Study on Enhancing Heat Transfer and Thermal Efficiency
Authors: Limboonruang Teerapath , Oyinlola Muyiwa , Harmanto Dani , Bunyawanichakul Pracha , Phunapai Nittalin
Published: September 2023

Several researchers have shown that the heat transfer performance of solar parabolic trough (SPT) receivers may be improved by increasing their surface area or by adding internal fins to the tubes. Unfortunately, the manufacture of internally finned tubes involves complex processes, resulting in significant cost increases. On the other hand, the addition of external fins to tubes is more technically and economically feasible in a low-resource setting. This study investigates the potential benefits of integrating external fins on the receiver tubes of a low-cost SPT collector system. Experiments were conducted using an SPT system with a focal length of 300 mm and a collector length of 5.1 m, and they were positioned by an automated Sun tracking system. Tests were undertaken using both smooth and externally finned receiver tubes operating at five different water flow rates. The solar receiver with a finned tube was able to provide a maximum water temperature of 59.34 °C compared with that of 56.52 °C for a smooth tube at a flow rate of 0.5 L per minute. The externally finned absorber tube was also found to have a maximum efficiency of 18.20% at an average daily solar intensity of 834.61 W/m2, which is approximately 48% more efficient than the smooth tube. The calculations indicate that the experimental SPT system using finned tubes potentially avoids 0.2726 metric tons of CO2e per year, with finned tubes outperforming smooth tubes by up to 44%. The results show that using externally finned receiver tubes can significantly enhance the thermal performance of SPT collector systems.
Biomass Gasification and Applied Intelligent Retrieval in Modeling
Authors: Meena Manish , Kumar Hrishikesh , Chaturvedi Nitin Dutt , Kovalev Andrey A. , Bolshev Vadim , Kovalev Dmitriy A. , Sarangi Prakash Kumar , Chawade Aakash , Rajput Manish Singh , Vivekanand Vivekanand , Panchenko Vladimir
Published: September 2023

Gasification technology often requires the use of modeling approaches to incorporate several intermediate reactions in a complex nature. These traditional models are occasionally impractical and often challenging to bring reliable relations between performing parameters. Hence, this study outlined the solutions to overcome the challenges in modeling approaches. The use of machine learning (ML) methods is essential and a promising integration to add intelligent retrieval to traditional modeling approaches of gasification technology. Regarding this, this study charted applied ML-based artificial intelligence in the field of gasification research. This study includes a summary of applied ML algorithms, including neural network, support vector, decision tree, random forest, and gradient boosting, and their performance evaluations for gasification technologies.