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The aim of this paper is to analyse the translation performance of German students at the University of Prishtina when translating literary texts from German into Albanian. The paper focuses on the question of whether errors occur during the translation process in the areas of grammar, orthography, semantics, and sentence structure, including possible interference errors between the two languages. These errors may arise due to uncertainties, carelessness, or the influence of other languages. The interference of German manifests itself primarily in the lexical level and sentence structure. If the languages have differences in sentence structure, this interference leads to grammatically incorrect sentences. An interference of Albanian is also noticeable, primarily on a pragmatic level, which is mainly determined by the cultural context. Errors are a characteristic feature of foreign language learners. They are a phenomenon that affects not only foreign language learners but also native speakers. This paper analyses and classifies the errors that German students at the University of Prishtina make when translating by applying the theoretical, analytical, and contrastive methods in the translation of literary texts. [ABSTRACT FROM AUTHOR]

The holographic signal-processing method for a single vector scalar receiver (VSR) in the high-frequency band in shallow water is developed in the paper. The aim of this paper is to present the results of the theoretical analysis, numerical modeling, and experimental verification of holographic signal processing for a noise source by the VSR. The developed method is based on the formation of the 2D interferogram and 2D hologram of a noise source in a shallow-water waveguide. The 2D interferograms and 2D holograms for different channels of the VSR (P sound pressure and V X and V Y vibration velocity components) are considered. It is shown that the 2D interferogram consists of parallel interference fingers in the presence of a moving noise source. As a result, the 2D hologram contains focal points located on a straight line, and the angular distribution of the holograms has the main extreme value. It is shown in the paper that the holographic signal-processing method allows detecting the source, estimating the source bearing, and filtering the useful signal from the noise. The results of the source detection, source bearing estimation, and noise filtering are presented within the framework of experimental data processing and numerical modeling. [ABSTRACT FROM AUTHOR]

This paper delves into the imperative need for coexistence and compatibility in the 470–694 MHz frequency band, as mandated by the World Radiocommunication Conference 2015 (WRC-15) and the WRC-23. It focuses on challenges in the coexistence of Digital Terrestrial Television Broadcasting (DTTB) and International Mobile Telecommunications-2020 (IMT-2020) services in downlink-only mode, particularly in adjacent-channel scenarios. Using Monte Carlo simulations, the study evaluates the probability of interference from IMT base stations with DTTB reception. The analysis thoroughly investigates the impact of the IMT transmitter's Adjacent Channel Leakage Ratio (ACLR) and the DTTB receiver's Adjacent-Channel Selectivity (ACS) on the probability of interference. The results demonstrate a significant degradation in the DTTB reception probability at the edge of coverage based on standard assumptions. To address these challenges, this paper provides recommendations for mitigating interference. These include defining enhanced ACLR regulations for IMT base stations, implementing antenna discriminations, providing specialized filters, and establishing national coordination procedures. The research provides valuable insights for informed decision making in spectrum management within the 470–694 MHz band, aiming to facilitate the coexistence of DTTB and IMT-2020 services, in line with international regulations and best practices. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Lingüística y Lenguas Aplicadas (RLLA) is the property of Universidat Politecnica de Valencia, Department of Applied Linguistics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of FME Transactions is the property of University of Belgrade, Faculty of Mechanical Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Text-based CAPTCHAs remain the most widely adopted security scheme, which is the first barrier to securing websites. Deep learning methods, especially Convolutional Neural Networks (CNNs), are the mainstream approach for text CAPTCHA recognition and are widely used in CAPTCHA vulnerability assessment and data collection. However, verification code recognizers are mostly deployed on the CPU platform as part of a web crawler and security assessment; they are required to have both low complexity and high recognition accuracy. Due to the specifically designed anti-attack mechanisms like noise, interference, geometric deformation, twisting, rotation, and character adhesion in text CAPTCHAs, some characters are difficult to efficiently identify with high accuracy in these complex CAPTCHA images. This paper proposed a recognition model named Adaptive CAPTCHA with a CNN combined with an RNN (CRNN) module and trainable Adaptive Fusion Filtering Networks (AFFN), which effectively handle the interference and learn the correlation between characters in CAPTCHAs to enhance recognition accuracy. Experimental results on two datasets of different complexities show that, compared with the baseline model Deep CAPTCHA, the number of parameters of our proposed model is reduced by about 70%, and the recognition accuracy is improved by more than 10 percentage points in the two datasets. In addition, the proposed model has a faster training convergence speed. Compared with several of the latest models, the model proposed by the study also has better comprehensive performance. [ABSTRACT FROM AUTHOR]

Simple Summary: The metabolic profile implies simultaneous determination of carbohydrate, fat, protein, and mineral metabolism parameters as well as endocrinological parameters in the blood of cows. Blood is exposed to a variety of preanalytical factors during sampling, transport to the laboratory, and laboratory preparation for analysis, which may cause hemolysis of the sample. As hemolysis affects the values of the metabolic profile, the analyzed blood parameters may falsely increase or decrease, and the metabolic status of the cows may be misinterpreted. Preventing hemolysis is important because severe hemolysis requires discarding the sample and resampling, which is very resource-intensive. In this paper, three levels of hemolysis were determined for each blood parameter tested: (a) a hemolysis level that does not affect the values of the parameters and allows the results to be issued without restriction; (b) a hemolysis level that affects the values of the parameters but remains within the acceptable biological variability and permits the results to be issued along with a note in the form of a correction formula; and (c) a hemolysis level at which the obtained values of the parameters or the entire sample must be discarded. The results are presented graphically using interferograms, which can be easily implemented in every laboratory after validation. Hemolysis is a common cause of errors in laboratory tests as it affects blood parameters and leads to a positive or negative bias. This study aims to examine the relationship between the level of hemolysis (expressed as cell-free hemoglobin concentration, g/L) and the variability of metabolic and endocrine parameters and to determine the threshold level of hemolysis that causes an analytically and clinically significant bias for the twenty most frequently examined blood parameters in cows. Paired blood samples of 10 mL each were obtained from 30 cows. One was subjected to mechanical trauma and plasma was extracted directly from the other. Hemolyzed and non-hemolyzed samples from the same animal were mixed to obtain final samples with cell-free hemoglobin concentrations of 0, 1, 2, 4, 6, 8, and 10 g/L. Metabolic and endocrine parameters were measured in the samples and their deviation and the linear equation between the level of hemolysis and the deviation were determined. The following threshold values of hemolysis were determined, which correspond to the acceptable analytical (lower value) and clinical (upper value) levels of parameter variability: BHB 0.96 and 4.81; NEFA 0.39 and 3.31; GLU 0.38 and 3.90; ALB 1.12 and 6.11; TPROT 1.40 and 6.80; UREA 6.62 and 20.1; TBIL 0.75 and 5.65; AST 0.11 and 2.18; GGT 1.71 and 8.90, LDH 0.01 and 0.11, ALP 0.97 and 2.95; TGC 1.56 and 15.5; CHOL 1.29 and 8.56; Ca 5.68 and 25.7; P 0.57 and 8.43; Mg 1.10 and 8.47; INS 1.15 and 3.89; T3 8.19 and 15.6; T4 8.97 and 18.5; and CORT 2.78 and 11.22 g/L cell-free hemoglobin. Three decision levels are available for each metabolic and endocrine parameter: if hemolysis is below the lower (analytical) threshold value, results can be reported without restriction; if hemolysis is between the lower and upper thresholds, the results can be issued with guidance in the form of corrective linear equations; and if hemolysis is above the upper (clinical) threshold, the results and sample must be discarded. This method contributes to an optimal approach to hemolysis interference with metabolic profile parameters in blood samples from cows. [ABSTRACT FROM AUTHOR]

Studies have indicated that the preservation of joint health and the facilitation of damage recovery are predominantly contingent upon the joint's microenvironment, including cell-cell interactions, the extracellular matrix's composition, and the existence of local growth factors. Mesenchymal stem cells (MSCs), which possess the capacity to self-renew and specialize in many directions, respond to cues from the microenvironment, and aid in the regeneration of bone and cartilage, are crucial to this process. Changes in the microenvironment (such as an increase in inflammatory mediators or the breakdown of the extracellular matrix) in the pathological context of arthritis might interfere with stem cell activation and reduce their ability to regenerate. This paper investigates the potential role of joint microenvironmental variables in promoting or inhibiting the development of arthritis by influencing stem cells' ability to regenerate. The present status of research on stem cell activity in the joint microenvironment is also outlined, and potential directions for developing new treatments for arthritis that make use of these intervention techniques to boost stem cell regenerative potential through altering the intra-articular environment are also investigated. This review's objectives are to investigate these processes, offer fresh perspectives, and offer a solid scientific foundation for the creation of arthritic treatment plans in the future. [ABSTRACT FROM AUTHOR]

Shape-memory alloys have various applications in different fields including medicine, robotics, aeronautics, and micro-electromechanical systems. This paper discusses shrink-fit joints formed by shape-memory alloy elements and their application for the axial fixation of mechanical components. The use of shape-memory alloys gives the shrink-fits some specific features: ease of assembly, insensitivity to tooling and human error, chemical resistance, low cost, etc. The friction force created between the components is experimentally investigated as a function of two parameters—the substrate diameter and the surface roughness (Ra) of one of the joined elements. The results of the experiments are presented analytically and graphically. Conclusions are drawn regarding the behavior of the studied shrink-fits. They can be beneficial to any engineering project making it less sensitive to manufacturing variations. [ABSTRACT FROM AUTHOR]

The advancement of underwater cognitive acoustic network (UCAN) technology aims to improve spectral efficiency and ensure coexistence with the underwater ecosystem. As the demand for short-term underwater applications operated under distributed topologies, like autonomous underwater vehicle cluster operations, continues to grow, this paper presents Underwater Multi-channel Medium Access Control with Cognitive Acoustics (UMMAC-CA) as a suitable channel access protocol for distributed UCANs. UMMAC-CA operates on a per-frame basis, similar to the Multi-channel Medium Access Control with Cognitive Radios (MMAC-CR) designed for distributed cognitive radio networks, but with notable differences. It employs a pre-determined data transmission matrix to allow all nodes to access the channel without contention, thus reducing the channel access overhead. In addition, to mitigate the communication failures caused by randomly occurring interferers, UMMAC-CA allocates at least 50% of frame time for interferer sensing. This is possible because of the fixed data transmission scheduling, which allows other nodes to sense for interferers simultaneously while a specific node is transmitting data. Simulation results demonstrate that UMMAC-CA outperforms MMAC-CR across various metrics, including those of the sensing time rate, controlling time rate, and throughput. In addition, except for in the case where the data transmission time coefficient equals 1, the message overhead performance of UMMAC-CA is also superior to that of MMAC-CR. These results underscore the suitability of UMMAC-CA for use in challenging underwater applications requiring multi-channel cognitive communication within a distributed network architecture. [ABSTRACT FROM AUTHOR]

Acquiring English as L2 and foreign language is different from context to context. It is important to remember that acquiring English needs suitable context and enough input in communication. Understanding of question words in EFL Context, especially the learners who learn English as a foreign language in Afghanistan was the new subject. The main purpose of this study is to characterize Wh-words on the performance of the learners who participated in ESP Courses at Badakhshan University and Borna Higher Education in Faizabad, Badakhshan Province in Afghanistan. Recently, some of these students graduated from Badakhshan University and Borna Higher Education and they occupied different positions in different national and international organization. The main criterion for recruiting of these students these organizations was knowing the fourth skills of English language. In this study, 50 subjects were selected from 150 students who participated in the exam. Among these subjects, 25 were female and who also graduated from different disciplines and participated in ESP classes. The task distributed for all these participants in a special large class and the data were collected. The data were analyzed based on quantitative research. Findings of this research represented wh-words and their movements in the sentences are sometimes complicated for the learners who use English as a foreign language, especially for intermediate level. They faced to challenges that they missed their using with auxiliaries and their movements from NP to CP positions. This paper ends with empirical search to represent the challenges to which the learners face when they use Wh-words in the sentences. [ABSTRACT FROM AUTHOR]

Twisted photonic crystals are photonic analogs of twisted monolayer materials such as graphene and their optical property studies are still in their infancy. This paper reports optical properties of twisted single-layer 2D+ moiré photonic crystals where there is a weak modulation in z direction, and bilayer moiré-overlapping-moiré photonic crystals. In weak-coupling bilayer moiré-overlapping-moiré photonic crystals, the light source is less localized with an increasing twist angle, similar to the results reported by the Harvard research group in References 37 and 38 on twisted bilayer photonic crystals, although there is a gradient pattern in the former case. In a strong-coupling case, however, the light source is tightly localized in AA-stacked region in bilayer PhCs with a large twist angle. For single-layer 2D+ moiré photonic crystals, the light source in Ex polarization can be localized and forms resonance modes when the single-layer 2D+ moiré photonic crystal is integrated on a glass substrate. This study leads to a potential application of 2D+ moiré photonic crystal in future on-chip optoelectronic integration. [ABSTRACT FROM AUTHOR]

Process aspects are prevalent in many domains of reality, and consciousness is no exception. Nevertheless, while the processual approach implicitly underlies the theories of consciousness, an explicit statement of the question is scarcely found in the literature. This paper tries to bridge this gap. Here, I argue that conscious experience fulfils all the requirements for a processual analysis: it is complex, functionally/causally determined, and has a temporal basis. Then, I revisit an old concept, self-transformative processes, which refers to processes that change themselves. These processes are very common. A stretched bow is the classical Heraclitean example. However, it is easy to misunderstand what selftransformativeness is. To provide a well-formed description, I characterize self-transformative processes in terms of composition (using a non-classic mereology) and in terms of functionality (by developing the concept of self-modulating variables). Finally, I apply self-transformative processes to explain consciousness. Traces of self-transformativeness can be found in many theories of consciousness, particularly when they are stressed about their internal mechanisms. Here, I focus on Integrated Information Theory as a paradigmatic example of a mathematically well-described theory, and I demonstrate that quantitative selftransformativeness is a requirement at the very core of the integration of the information. [ABSTRACT FROM AUTHOR]

Aim. We present two cases with clearly discrepant results of clinical examination and cardiac troponin I (cTnI) and cardiac troponin T (cTnT) concentrations. In similar cases with discrepant results, the possibility of interference should be considered. Methods. Due to the suspicion of the presence of macrotroponin I in both of the presented cases, the patients were invited to our laboratory and both cTnI (Architect i1000, Abbott) and cTnT (Cobas 8000, Roche) concentrations were analysed. The samples were treated by preincubation in a heterophilic antibodies blocking tube (HBT) and analysed. Precipitation with polyethylene glycol solution (PEG) and molecular weight separation by gel filtration on Sephadex G100 was performed and concentrations of cTnI were analysed. Results. In the same blood sample, the cTnT and cTnI concentrations were 7 and 1782 ng/L, respectively, in Case 1, and 6 and 96 ng/L, respectively, in Case 2. Incubation of samples in HBT had no significant effect. CTnI concentrations after precipitation with PEG - presented as the percentage of initial concentrations - were 7.4% in Case 1 (and 26.8% in the control sample) and 1.4% in Case 2 (and 56.0% in the control sample). These results indicate a significant decrease in both cases, supporting presence of macrotroponin I. Finally, analyses of cTnI concentrations after gel filtration also supported the presence of macrotroponin I. Conclusion. The present cases show that the presence of macrotroponin can lead to unnecessary investigation of the patient. When the possibility of interference is suspected, cooperation with laboratory staff to help with interpretation or to perform more detailed analysis is crucial.

The paper investigates punctuation rules and their application in Serbian and English, focusing on the examples that comply with different normative solutions in the two languages. The main goal of the research is to compare and contrast the results obtained from a survey done by a group of seventh-grade primary school students. The paper aims to determine how well the respondents apply punctuation rules in Serbian and English, to examine whether there is interference in the application of rules, and to investigate to what extent the detected errors illustrate the tendency of spreading pseudo-norms that violate the orthography of both languages. The results show that the respondents use punctuation marks with more precision in Serbian than in English. The percentage of incorrect answers to each question and the types of errors indicate interference and the creation of hybrid forms that are incorrect in both languages, which represent the creation of pseudo-norms. Furthermore, the results show a greater influence of the application of the rules adopted in the Serbian language on the English language, which can be interpreted by the bigger number of Serbian classes and clearly stated topics within the syllabus of the Serbian language course.

Frequency-modulated continuous-wave (FMCW) radars are becoming increasingly important in industrial applications due to their low cost, simple signal processing, and high resolution. The research is driven by the growing trend of radar applications in industrial settings, including tasks like autonomous robot navigation, radar-based monitoring of humans, and enhancing safety across various scenarios, such as smart factories, traffic control, or environmental monitoring. The network of distributed sensor nodes is a feature to be implemented by the sixth generation of wireless mobile networks. As a result, 6G will become an enabler technology that will develop even further use cases and advance the expansion of these technologies. Therefore, the mutual interference of these sensor systems is becoming highly relevant since they can be avoided by scheduling the individual resources of the sensor nodes by a network structure. This paper investigates the interference behavior of FMCW radar sensors in a dense indoor scenario. In these environments, in particular, the reliability of the sensor system plays an important role, and disruption can have critical consequences like not recognizing a target, triggering a false alarm, or the complete failure of the sensing. To correctly classify the expected interference in the overall context, the paper investigates the physical layer effects on the performance, such as multipath propagation, channel spread, delay, Doppler shift, and attenuation. By evaluating these effects using state-of-the-art signal processing, it was revealed that a high channel spread in particular and the dynamics of the radar channel can significantly reduce the detection quality, as the interference power can exceed the received power by up to 20 dB, depending on the scenario. The simulation results given in this paper show that a potential communication between the radars and compliance with a synchronization delay, the interference problems can be reliably prevented with an appropriately designed anti-aliasing filter. Our simulations have quantified the detection performance under interference through the entire signal chain by evaluating the physical layer, the radar signal processing with non-idealities, and the hardware. The paper has investigated interference probability in indoor environments by examining radars with uncoordinated transmissions. Integrating findings from the physical propagation characteristics, the deviations in chirp durations, and the frequency of interference cases offers insights into the potential risk of interference.

Quantum computing, a transformative field that emerged from quantum mechanics and computer science, has gained immense attention for its potential to revolutionize computation. This paper aims to address the fundamentals of quantum computing and provide a comprehensive guide for both novices and experts in the field of quantum computing. Beginning with the foundational principles of quantum computing, we introduce readers to the fundamental concepts of qubits, superposition, entanglement, interference, and noise. We explore quantum hardware, quantum gates, and basic quantum circuits. This study offers insight into the current phase of quantum computing, including the noisy intermediate-scale quantum (NISQ) era and its potential for solving real-world problems. Furthermore, we discuss the development of quantum algorithms and their applications, with a focus on famous algorithms like Shor’s algorithm and Grover’s algorithm. We also touch upon quantum computing’s impact on various industries, such as cryptography, optimization, machine learning, and material science. By the end of this paper, readers will have a solid understanding of quantum computing’s principles, applications, and the steps involved in developing quantum circuits. Our goal is to provide a valuable resource for those eager to embark on their quantum computing journey and for researchers looking to stay updated on this rapidly evolving field.

The holographic signal-processing method for a single vector scalar receiver (VSR) in the high-frequency band in shallow water is developed in the paper. The aim of this paper is to present the results of the theoretical analysis, numerical modeling, and experimental verification of holographic signal processing for a noise source by the VSR. The developed method is based on the formation of the 2D interferogram and 2D hologram of a noise source in a shallow-water waveguide. The 2D interferograms and 2D holograms for different channels of the VSR (P sound pressure and VX and VY vibration velocity components) are considered. It is shown that the 2D interferogram consists of parallel interference fingers in the presence of a moving noise source. As a result, the 2D hologram contains focal points located on a straight line, and the angular distribution of the holograms has the main extreme value. It is shown in the paper that the holographic signal-processing method allows detecting the source, estimating the source bearing, and filtering the useful signal from the noise. The results of the source detection, source bearing estimation, and noise filtering are presented within the framework of experimental data processing and numerical modeling.

In the vicinity of plasmonic nanostructures that support highly confined light fields, spontaneous emission processes, such as two-photon spontaneous emission (TPSE), exhibit higher-order multipolar emission pathways beyond the dipolar one. These multipolar emission channels occur simultaneously and can interfere with each other. We develop a novel framework that computes these interference effects for TPSE of a quantum emitter close to an arbitrary nanostructure. The model is based on the computation of Purcell factors that can be calculated with conventional electromagnetic simulations, which avoids complex analytic calculations for the environment. For a transition of a hydrogen-like emitter close to a graphene nanotriangle, we demonstrate a breakdown of the dipolar selection rule in the TPSE process. This breakdown is due to a huge enhancement of the two-electric dipole (2ED) and of the two-electric quadrupole (2EQ) transitions. We observe an important interference between these multipolar transitions, as it increases the total rate by 67 % . In the end, our framework is a complete tool to design emitters and nanostructures for TPSE, where the exploitation of previously ignored interference effects provides an additional degree of freedom, for example to boost desired transitions and to supress undesirable ones. [ABSTRACT FROM AUTHOR]

The black soldier fly (BSF) Hermetia illucens (Diptera: Stratiomyidae) plays a significant role at the larval stage in the circular economy due to its ability to convert organic waste into valuable products for energy, food, feed, and agricultural applications. Many data are available on larval development and biomass generation, but basic research on this species is lacking and little is known about adult biology, in particular about the cues involved in sexual recognition. In the present study, using various instruments (stereomicroscope, scanning and transmission electron microscope, hyperspectral camera and spectrophotometer), wing ultrastructure of both sexes was analysed, reflectance and transmission spectra of the wings were measured and behavioural bioassays were carried out to measure male response to specific visual stimuli. The collected data showed the existence of sexual dimorphism in the wings of H. illucens due to iridescent structural colouration generated by a multilayer of melanin located in the dorsal lamina of the central part of the wing. Wing sexual dimorphism is particularly evident regarding the strong emission of blue light of female wings. Blue colour induces in males a strong motivation to mate. The obtained results can help to improve and optimize the breeding techniques of BSF. [ABSTRACT FROM AUTHOR]

The demonstration of compliance of rolling stock against disturbance limits for railway signaling, and in particular track circuits, is subject to a large deal of variability, caused by the diverse values of the electrical parameters of the railway line and resulting transfer functions, as well as the operating conditions of the rolling stock during tests. Instrumental uncertainty is evaluated with a type B approach and shown to be much less than the experimental variability. Repeated test runs in acceleration, coasting, cruising, and braking conditions are considered, deriving both max-hold (spread) and sample (or experimental) standard deviation curves compared to the respective mean values (type A approach to the evaluation of uncertainty, as defined in of the Guide to the Uncertainty in Measurement. The major source of variability affecting a significant portion of the spectrum is caused by the superposed oscillations of the onboard LC filter, for which different choices of the transformation window duration are discussed. The test runs and the acquired data covered, overall, 1 day of tests along about 300 km of the Italian 3 kV DC railway network. [ABSTRACT FROM AUTHOR]

The 14 August 2021 Haiti earthquake mainly portrayed reverse motion to the east near L'Asile town and left‐lateral strike‐slip motion to the west near Camp‐Perrin town. To map the rupture and infer its segmentation, we conducted the first post‐seismic field reconnaissance along the left‐lateral strike‐slip Enriquillo fault from L'Asile to Macaya mountain. We identified 98 linear, minor cracks that are not representative of primary fault surface rupture. Analyzing the topographic slope distribution, we detected that the cracks were often located in areas that are prone to topographic instability. About 60% of the cracks are located in Quaternary alluvium and Middle‐Miocene continental marls, indicating a preference for soft sediments. The rivers also have an impact, as crack lengths and openings negatively correlate with their distance to neighboring rivers. In addition, the earthquake occurred in a rainy region with up to 2,479.34 mm of rainfall in 2021, increasing soil instability. Above all, we found a contrast and asymmetry between the eastern and the western parts of the rupture. By dividing the 60‐km long rupture into two equal parts, we observed 57 cracks to the west against 41 to the east. The longest and the widest cracks are to the west. Analyzing their orientation, the cracks mainly oriented as left‐lateral strike‐slip faults to the west and mainly thrusts to the east. This configuration appears to be influenced by the slip pattern of the 2021 Haiti earthquake and consistent with the regional stress field. Key Points: Alongside geology, topography, and hydroclimate, tectonics is the biggest factor for crack generation during the 14 August 2021, Mw 7.2 Haiti earthquakeThrust and sinistral strike‐slip cracks partition similarly to the earthquake slip pattern and to the oblique‐convergence margin [ABSTRACT FROM AUTHOR]

Skepticism of COVID-19 has consequences for public health. We examined several variables that we reasoned were related to skepticism, including demographic factors, people's perceptions and experiences related to COVID-19, and social media usage. The sample consisted of 294 participants recruited in April of 2020. Participants filled out a survey that included questions related to demographics, social media use, COVID-19 anxiety, COVID-19 interference, and COVID-19 skepticism. In the main, biological sex, ethnicity, and social media use were not significantly associated with skepticism regarding COVID-19. Alternatively, older participants and those who experienced greater anxiety related to the pandemic were less skeptical of COVID-19. Interestingly, people who experienced more interference in their lives because of COVID-19 were more skeptical of the pandemic. Finally, social media use moderated the influence of anxiety and interference on skepticism. The negative effect of anxiety on skepticism became weaker as people's use of social media increased. The positive effect of interference related to COVID-19 on skepticism became stronger as people used more social media. Our findings underscore the importance of personal beliefs, attitudes, and experiences when explaining skepticism of the pandemic. [ABSTRACT FROM AUTHOR]

This study investigates the impact of temperature variations on the torque capacity of shrink-fit junctions in water-jacketed permanent magnet synchronous motors. Focusing on both baseline and improved designs; torque capacities were evaluated across a temperature range from −40 °C to 120 °C under different material conditions: Least material condition, nominal, and maximum material condition. The baseline design exhibited torque capacities from 7648 Nm to 9032 Nm at −40 °C, decreasing significantly to 549 Nm to 1533 Nm at 120 °C. The improved design showed enhanced performance, with torque capacities ranging from 8055 Nm to 9247 Nm at −40 °C and from 842 Nm to 1618 Nm at 120 °C. The maximum improvement was observed at 120 °C for least material conditions, with a 55.4% increase, and the minimum improvement at −40 °C for maximum material conditions, with a 2.4% increase. Our findings demonstrate a significant increase in torque capacity by up to 20% under varied thermal conditions. These results underscore the effectiveness of design modifications in enhancing thermal stability and torque capacity, making the improved design a more reliable choice for high-performance applications subject to significant thermal fluctuations. This research highlights the critical role of material selection, thermal management, and precise design adjustments in optimizing the performance and reliability of permanent magnet synchronous motors. [ABSTRACT FROM AUTHOR]

In recent years, Orthogonal Time Frequency Space Modulation (OTFS) has gained popularity in integrated sensing and communications (ISAC) system due to its robustness against Doppler offset and delay changes. Traditional pilot‐based methods for accurate channel parameter estimation are complex and struggle with rapidly changing channel conditions. In this letter, a deep encode‐decode network (DED‐Net) is proposed. It uses DL to automatically learn and eliminate channel interference from OTFS signals. The framework employs a deep encoding and decoding network, similar to a filter, learning complex signal features to effectively remove interference. Our experiments demonstrate DED‐Net's ability to eliminate interference in OTFS modulation signals, offering an alternative to pilot‐based methods and showcasing DL's potential for ISAC systems. [ABSTRACT FROM AUTHOR]

Introduction: Cognitive control processes have been extensively studied in spoken word production, however, relevant investigations of written word production are scarce. Using data from a group of post-stroke individuals we studied, for the first time, the neural substrates of cognitive control in written word production. We addressed three questions: Are control mechanisms: (1) shared by language and non-language domains; (2) shared by lexical and segmental levels of word production within the word production system; (3) related to both interference and facilitation effect types? Methods: To address these questions, for each participant we calculated cognitive control indices that reflected the interference and facilitation effects observed in written Blocked Cyclic Naming (written language production) and Simon (visuo-spatial processing) tasks. These behavioral cognitive control indices were studied both on their own, as well as in relation to the distribution of structural (gray matter) lesions. Results: For Question 1, we provide strong evidence of domain-specific control mechanisms used in written word production, as, among other findings, distinct regions within Broca’s Area were associated with control in written word production vs. control in visuo-spatial processing. For Question 2, our results provide no strong evidence of shared control mechanisms for lexical and segmental levels of written word production, while they highlight the role of BA45 in instantiating control mechanisms that are specific to the two levels. For Question 3, we found evidence that BA45 supports distinct mechanisms associated with facilitation and interference, while orbital frontal cortex supports control process(es) associated with both. Discussion: These findings significantly advance our understanding of the cognitive control mechanisms involved in written language production, as well as of the role of Broca’s Area in cognitive control and language production more generally. [ABSTRACT FROM AUTHOR]

In recent years, chemiluminescent microparticle immunoassay (CMIA) has been widely used for determination of high-sensitivity troponin I (hs-cTnI). However, a CMIA analysis is usually affected by the presence of some endogenous or exogenous substances. This case-report aims to unveil the essence of the reoccurrence of false-positive results due to heterophilic antibodies interference with Abbott high-sensitivity cardiac troponin I assay, although the assay method applied a chimeric antibody. A 28-year-old female misdiagnosed with myocarditis due to falsely elevated hs-cTnI with an initial test result of 595.0 ng/L considered as critical value was reported. And the false critical value of hs-cTnI reoccurred five times after admission. The heterophilic blocking tube (HBT) procedure caused a decrease in troponin concentrations within the reference values, which suggests the presence of interference from heterophilic antibodies. It requires a close and strong collaboration between clinicians and laboratorians to manage the similar case on the interference from heterophilic antibodies. To prevent false-positive results caused by interferences from being used in clinical practice, the clinicians are suggested to contact the laboratorians whenever the clinical picture, historical data and laboratory values are not conclusive. [ABSTRACT FROM AUTHOR]

The interference of fermionic particles, specifically molecules comprising a small number of fermions, in a Mach–Zehnder interferometer is being investigated under the influence of both classical and non-classical external controls. The aim is to identify control strategies that can elucidate the relationship between the interference pattern and the characteristics of internal fermion–fermion interactions. [ABSTRACT FROM AUTHOR]

Due to the dissimilarity among different producing layers, the influences of inter-layer interference on the production performance of a multi-layer gas reservoir are possible. However, systematic studies of inter-layer interference for tight gas reservoirs are really limited, especially for those reservoirs in the presence of water. In this work, five types of possible inter-layer interferences, including both absence and presence of water, are identified for commingled production of tight gas reservoirs. Subsequently, a series of reservoir-scale and pore-scale numerical simulations are conducted to quantify the degree of influence of each type of interference. Consistent field evidence from the Yan'an tight gas reservoir (Ordos Basin, China) is found to support the simulation results. Additionally, suggestions are proposed to mitigate the potential inter-layer interferences. The results indicate that, in the absence of water, commingled production is favorable in two situations: when there is a difference in physical properties and when there is a difference in the pressure system of each layer. For reservoirs with a multi-pressure system, the backflow phenomenon, which significantly influences the production performance, only occurs under extreme conditions (such as very low production rates or well shut-in periods). When water is introduced into the multi-layer system, inter-layer interference becomes nearly inevitable. Perforating both the gas-rich layer and water-rich layer for commingled production is not desirable, as it can trigger water invasion from the water-rich layer into the gas-rich layer. The gas-rich layer might also be interfered with by water from the neighboring unperforated water-rich layer, where the water might break the barrier (eg weak joint surface, cement in fractures) between the two layers and migrate into the gas-rich layer. Additionally, the gas-rich layer could possibly be interfered with by water that accumulates at the bottom of the wellbore due to gravitational differentiation during shut-in operations. [ABSTRACT FROM AUTHOR]

Significance: The interference-holographic method of phase scanning of fields of scattered laser radiation is proposed. The effectiveness of this method for the selection of variously dispersed components is demonstrated. This method made it possible to obtain polarization maps of biological tissues at a high level of depolarized background. The scale-selective analysis of such maps was used to determine necrotic changes in the optically anisotropic architectonics of biological tissues. Objective: Development and experimental approbation of layered phase polarimetry of repeatedly scattered fields in diffuse layers of biological tissues. Application of scale-selective processing of the found coordinate distributions of polarization states in various phase sections of object fields. Determination of criteria (markers) for histological differential diagnosis of the causes of necrotic changes in optical anisotropy of biological tissues. Approach: We used a synthesis of three instrumental and analytical methods. Polarization-interference registration of laser radiation scattered by a sample of biological tissue. Digital holographic reconstruction and layered phase scanning of distributions of complex amplitudes of the object field. Analytical determination of polarization maps of various phase cross-sections of repeatedly scattered radiation. Application of wavelet analysis of the distributions of polarization states in the phase plane of a single scattered component of an object field. Determination of criteria (markers) for differential diagnosis of necrotic changes in biological tissues with different morphological structure. Two cases are considered. The first case is the myocardium of those who died as a result of coronary heart disease and acute coronary insufficiency. The second case is lung tissue samples of deceased with bronchial asthma and fibrosis. Results: A method of polarization-interference mapping of diffuse object fields of biological tissues has been developed and experimentally implemented. With the help of digital holographic reconstruction of the distributions of complex amplitudes, polarization maps in various phase sections of a diffuse object field are found. The wavelet analysis of azimuth and ellipticity distributions of polarization in the phase plane of a single scattered component of laser radiation is used. Scenarios for changing the amplitude of the wavelet coefficients for different scales of the scanning salt-like MHAT function are determined. Statistical moments of the first to fourth orders are determined for the distributions of the amplitudes of the wavelet coefficients of the azimuth maps and the ellipticity of polarization. As a result, diagnostic markers of necrotic changes in the myocardium and lung tissue were determined. The statistical criteria found are the basis for determining the accuracy of their differential diagnosis of various necrotic states of biological tissues. Conclusions: Necrotic changes caused by "coronary artery disease--acute coronary insufficiency" and "asthma--pulmonary fibrosis" were demonstrated by the method of wavelet differentiation with polarization interference with excellent accuracy. [ABSTRACT FROM AUTHOR]

This work reports the observation of sunlight diffraction through empty spaces in between twigs and leaves in tree crowns. The diffraction patterns are dominated by red wavelength on front followed by the trail of rest of spectral bands of white light rainbow bursts. Tree crowns act as obstacles and apertures causing diffraction/ interference of solar rays. Separation between leaves and twigs (d) is a few inches and distance between crown and camera (D) is in range of a few meters. Empty spaces in tree crown are much longer than red to violet wavelengths in sunlight therefore scattering, dispersion, reflection, diffraction and interference effects cannot be ruled out. Tree crown deflects solar rays into narrow angles all around to enable interference inside camera lens to create grating structure diffracting light into regular patterns. Diffraction pattern look like red petunia flower having 3 × 3 rose petals. Motorola mobile phone camera was used to record the sunlight diffraction patterns. Mobile camera consists of small focal length (≈5 mm) lens, a fixed opening aperture and an image sensor. Lens consists of few plastic or glass elements and sensor consists of charge coupled device (CCD) or CMOS technology. These diffraction/ interference patterns have potential to increase efficiency of Next Gen solar cells. This paper describes possible theoretical background of light diffraction and multiple ray interference through tree twigs and leaves.

In this paper, a novel interference-based nanostructure was designed and simulated to realize an all-optical 2-bit reversible comparator by employing a novel technique. The plane wave expansion (PWE) method was adopted to analyze the encoder design and frequency modes. Aside from downsizing, the finite-difference time-domain (FDTD) method was utilized for the simulation and numerical analysis of the design proposed herein. An ultra-compact nanostructure with a 129.8 μm2 footprint was utilized for the all-optical 2-bit reversible comparator. One of the noteworthy characteristics of the proposed nanostructure was its excellent contrast ratio (i.e., 13.8 dB) in comparison to other nanostructures. The bitrate and delay time in this nanostructure were 3.33 Tb/s and 300 fs, respectively. Based on the findings of the simulations conducted at a central wavelength of 1.55 μm, it is recommended to employ the nanostructure proposed herein during the third telecom window. A photonic crystal nano-resonator was utilized to design the high-performance all-optical 2-bit reversible comparator, which may also be employed in integrated optical circuits (IOCs).

Significance: Light-sheet fluorescence microscopy (LSFM) has emerged as a powerful and versatile imaging technique renowned for its remarkable features, including high-speed 3D tomography, minimal photobleaching, and low phototoxicity. The interference light-sheet fluorescence microscope, with its larger field of view (FOV) and more uniform axial resolution, possesses significant potential for a wide range of applications in biology and medicine. Aim: The aim of this study is to investigate the interference behavior among multiple light sheets (LSs) in LSFM and optimize the FOV and resolution of the light-sheet fluorescence microscope. Approach: We conducted a detailed investigation of the interference effects among LSs through theoretical derivation and numerical simulations, aiming to find optimal parameters. Subsequently, we constructed a customized system of multi-LSFM that incorporates both interference light sheets (ILS) and noninterference light-sheet configurations. We performed beam imaging and microsphere imaging tests to evaluate the FOV and axial resolution of these systems. Results: Using our custom-designed light-sheet fluorescence microscope, we captured the intensity distribution profiles of both interference and noninterference light sheets (NILS). Additionally, we conducted imaging tests on microspheres to assess their imaging outcomes. The ILS not only exhibits a larger FOV compared to the NILS but also demonstrates a more uniform axial resolution. Conclusions: By effectively modulating the interference among multiple LSs, it is possible to optimize the intensity distribution of the LSs, expand the FOV, and achieve a more uniform axial resolution. [ABSTRACT FROM AUTHOR]

In this manuscript, we present a novel deployment protection method aimed at safeguarding aeronautical radio altimeters (RAs) from interference caused by fifth-generation (5G) telecommunication base stations (BSs). Our methodology involves an integrated interference model for defining prohibited zones and utilizes power control and angle shutoff methods to mitigate interference. First, to ensure reliable protection, we define both horizontal and vertical prohibited zones and investigate their variations to immunize RA against 5G interference. Second, we validate the effectiveness of the model in various operational scenarios, analyzing the influence of factors such as base station types, antenna parameters, flight altitude, and aircraft attitudes to cover a wide range of real-world scenarios. Third, to mitigate interference, we propose and analyze the power control and angle shutoff methods through simulation for the RMa prohibited zone. Our results demonstrate the efficacy of the deployment protection method in safeguarding RAs from 5G interference, providing guidance for interference protection during civil aviation operations and base station deployment near airports. [ABSTRACT FROM AUTHOR]

The orbital angular momentum (OAM) associated with structured singular beams carries vital information crucial for studying various properties and applications of light. Determining OAM through the interference of light is an efficient method. The interferogram serves as a valuable tool for analyzing the wavefront of structured beams, especially identifying the order of singularity. In this study, we propose a modified Mach–Zehnder interferometer architecture to effectively determine the topological charge of Bessel–Gaussian (BG) beams. Several numerically generated self-referenced interferograms have been used for analysis. Moreover, this study examines the propagation property and phase distribution within BG beams after they are obstructed by an aperture in the interferometer setup. [ABSTRACT FROM AUTHOR]

Children aged 3–8 are in a critical period for motor development and postural control. Running is a basic motor skill that children need to master in early childhood. While running, children are prone to dangerous events such as falls. This study investigates the kinematic characteristics of running by children associated with different interference tasks, i.e., normalized running, cognitive dual-tasks, and obstacle crossing tasks, and provides a theoretical foundation for the interference mechanism of children's dynamic postural control and for screening of motor disorders. Two hundred children aged 3–8 were recruited. The BTS Bioengineering infrared motion capture system was used to collect spatiotemporal and kinematic running data under three tasks. Repeated measures of variance analysis were used to compare the effects of different interference tasks and ages on children's running signs. The main and interaction effect tests were compared by the Bonferroni method. The results and conclusions are as follows: (1) Running characteristics of early childhood are influenced by interference tasks and age. With interference tasks, the overall characteristics of running by children aged 3–8 showed an increasing trend in running cycle time and a decreasing trend in stride length, step length, cadence, and speed. (2) Both cognitive and obstacle crossing tasks had costs, and cognitive task costs were greater than obstacle crossing costs. Children adopted a "task first" running strategy with different interference tasks. When facing cognitive tasks, their overall joint motion decreased, and they reduced joint motions to promote task completion. When facing obstacle crossing tasks, because of the characteristics of the task itself, children increased joint motions to cope with interference. (3) In terms of age, the running characteristics showed a nonlinear development trend in various indicators, with a degree of recurrence and high variability in adjacent age groups. (4) The dual-task interference paradigm of "postural-cognition" can be used as a motor intervention tool to promote the development of basic motor skills in early childhood. [ABSTRACT FROM AUTHOR]

Species coexistence is a major issue in ecology. We disentangled the role of individual interference when competing in the classical interference competition model. For the first time, we considered simultaneously intra- and inter-species interference by introducing the Beddington–DeAngelis competitive response into the classical competition model. We found a trade-off between intra- and inter-species interference that refines in a sense the well-known balance of intra- and inter-species competition coefficients. As a result, we found that (i) global coexistence is possible for a larger range of values of the inter-/intra-species competition coefficients and contributes to explaining the high prevalence of species coexistence in nature. This feature is exclusively due to intra-species interference. (ii) We found multi-stability scenarios previously described in the literature that can be reinterpreted in terms of individuals interference. [ABSTRACT FROM AUTHOR]

Introduction: Overlap with prior experience facilitates learning in some cases while hindering it in others. As facilitation and interference are typically studied in separate lines of research, using distinct paradigms, it is unclear what key factors drive the opposing behavioral outcomes. Methods: In two experiments, we tested whether both effects can be observed within a single task, depending on what overlaps between experiences. Participants completed a novel task in which they learned a grid of object- location associations, followed by a second grid that overlapped with the first in locations and/or objects. We hypothesized that overlap of locations would serve as a spatial schema, facilitating new learning, while overlap of objects would create interference. Results: In line with our hypothesis, we found that location overlap facilitated learning of the second grid, while object overlap hindered learning of the second grid. We replicated these findings in a second experiment, additionally showing that both effects remain largely stable across two distinct grid shapes. Discussion: These results demonstrate that the effect of overlap can be manipulated within a single task, pinpointing one factor that determines the direction of the effect and highlighting the differential roles of "what" and "where" in the organization of memory. [ABSTRACT FROM AUTHOR]

Seasonal infection rates of individual viruses are influenced by synergistic or inhibitory interactions between coincident viruses. Endemic patterns of SARS-CoV-2 and influenza infection overlap seasonally in the Northern hemisphere and may be similarly influenced. We explored the immunopathologic basis of SARS-CoV-2 and influenza A (H1N1pdm09) interactions in Syrian hamsters. H1N1 given 48 h prior to SARS-CoV-2 profoundly mitigated weight loss and lung pathology compared to SARS-CoV-2 infection alone. This was accompanied by the normalization of granulocyte dynamics and accelerated antigen-presenting populations in bronchoalveolar lavage and blood. Using nasal transcriptomics, we identified a rapid upregulation of innate and antiviral pathways induced by H1N1 by the time of SARS-CoV-2 inoculation in 48 h dual-infected animals. The animals that were infected with both viruses also showed a notable and temporary downregulation of mitochondrial and viral replication pathways. Quantitative RT-PCR confirmed a decrease in the SARS-CoV-2 viral load and lower cytokine levels in the lungs of animals infected with both viruses throughout the course of the disease. Our data confirm that H1N1 infection induces rapid and transient gene expression that is associated with the mitigation of SARS-CoV-2 pulmonary disease. These protective responses are likely to begin in the upper respiratory tract shortly after infection. On a population level, interaction between these two viruses may influence their relative seasonal infection rates. [ABSTRACT FROM AUTHOR]

The orthogonal time-frequency space (OTFS) modulation is resistant to double selective fading, making it a promising modulation scheme for next-generation integrated sensing and communication (ISAC) systems. Nonetheless, there exists a problem of mutual interference between uplink communication signals and sensing echo signals, which leads to the degradation of both information transmission and sensing performance. For this reason, this paper investigates a successive interference cancellation (SIC) method based on the delay-Doppler (DD) domain to suppress the interference between the sensing signals and communication signals, thereby ensuring the accuracy of communication signal detection and sensing parameter estimation. After receiving the mixed signals at the receiver, these signals are transformed from the time-frequency (TF) domain to the DD domain. Firstly, the sensing echo signal is treated as interference to the communication signal, which is detected using a threshold-based channel estimation method and the Message Passing (MP) algorithm. The communication signal is then reconstructed and subtracted from the mixed signal. At last, the remaining signal is then subjected to parameter estimation with the Maximum Likelihood (ML) algorithm. Simulation results demonstrate that this method allows the ISAC system to operate effectively in both communication and sensing tasks. Compared to the scenario without considering signal interference, the sensing parameter estimation is improved by approximately 6 dB. Additionally, compared to traditional interference suppression methods belonging to TF domain, the performance of sensing parameter estimation is improved by approximately 2 dB.

Transmit power control (PC) will become increasingly crucial in alleviating interference as the densification of the wireless networks continues towards 6G. However, the practicality of most PC methods suffers from high complexity, including the sensing and signalling overhead needed to obtain channel state information. In a highly dense scenario such as the deployment of short-range cells installed within production entities, termed in-factory subnetworks (InF-S), sensing and signalling overhead become a major limitation. In this paper, we represent the InF-S as a graph and resort to graph neural networks for solving the power control problem. We present four graph-attribution methods requiring different degrees of channel information corresponding to different levels of sensing and signalling overhead and study the complexity and performance tradeoffs of the resulting power control graph neural network (PCGNN) algorithms. We then propose a PCGNN method with scalable sensing and signalling graph attribution which can meet the stringent outage target while maximizing the global performance by 10% relative to fixed power control. We further verified the size generalizability and robustness of the PCGNN methods to different network settings.

For multi-transmission rate environments, access point (AP) connection methods have been proposed for maximizing system throughput, which is the throughput of an entire system, on the basis of the cooperative behavior of users. These methods derive optimal positions for the users’ cooperative behavior, which means that new users move to improve the system throughput when connecting to an AP. However, conventional methods only focus on increasing the transmission rate of new users without regard to the performance impact on existing users. In addition, these methods do not account for co-channel or stacked frequency interference between users. In this paper, we propose a novel approach to access point connectivity which maximizes the system throughput by taking into account the interference between users and the initial position of all users. In addition, our proposed method can improve system throughput by about 6% at most compared to previous methods.

Distributed deep learning frameworks facilitate large deep learning workloads. These frameworks support sharing one GPU device among multiple jobs to improve resource utilization. Modern deep learning training jobs consume a large amount of GPU memory. Despite that, sharing GPU memory among jobs is still possible because a training job has iterative steps that its memory usage fluctuates over time. However, resource sharing also introduces the risk of job performance degradation. Co-located jobs sharing a GPU device may suffer from different levels of interference, mainly caused by memory oversharing. How to improve resource utilization while maintaining good job performance is a novel challenge for job placement strategies. This paper studies the job placement problem. We propose an opportunistic memory sharing model to describe the time-varying job memory requirements. Based on this model, we introduce an Opportunistic Job Placement Problem (OJPP) for shared GPU clusters that seek job placement configurations using a minimum number of GPU devices and guarantee user-defined performance requirements at the same time. We propose a greedy algorithm and a heuristic algorithm with computational complexities of O (n log ⁡ n) and O (n 2 log ⁡ n) , respectively, to solve the problem. We also propose an online adjustment algorithm with the computational complexity of O (n log ⁡ n) to perform updates to job placement configurations in runtime. A machine-learning-based interference prediction method is used to prepare accurate interference estimations. Extensive experiments are conducted on a GPU cluster to verify the correctness and effectiveness of our algorithms. Compared with standalone training jobs on dedicated clusters, the proposed approach reduces resource consumption by 46% in a shared cluster, while guaranteeing over 92.97% of the job performance, in terms of average job completion time. • Introduce a stochastic model to describe memory oversharing of deep learning jobs on a shared GPU device. • Introduce a novel interference-aware Opportunistic Job Placement Problem for shared distributed deep learning clusters. • Propose algorithms to handle both offline job placement and online adjustment problems. • Illustrate extensive experimental results to verify the correctness and effectiveness of the approaches. [ABSTRACT FROM AUTHOR]

Abstract Process aspects are prevalent in many domains of reality, and consciousness is no exception. Nevertheless, while the processual approach implicitly underlies the theories of consciousness, an explicit statement of the question is scarcely found in the literature. This paper tries to bridge this gap. Here, I argue that conscious experience fulfils all the requirements for a processual analysis: it is complex, functionally/causally determined, and has a temporal basis. Then, I revisit an old concept, self-transformative processes, which refers to processes that change themselves. These processes are very common. A stretched bow is the classical Heraclitean example. However, it is easy to misunderstand what self-transformativeness is. To provide a well-formed description, I characterize self-transformative processes in terms of composition (using a non-classic mereology) and in terms of functionality (by developing the concept of self-modulating variables). Finally, I apply self-transformative processes to explain consciousness. Traces of self-transformativeness can be found in many theories of consciousness, particularly when they are stressed about their internal mechanisms. Here, I focus on Integrated Information Theory as a paradigmatic example of a mathematically well-described theory, and I demonstrate that quantitative self-transformativeness is a requirement at the very core of the integration of the information.

Shape-memory alloys have various applications in different fields including medicine, robotics, aeronautics, and micro-electromechanical systems. This paper discusses shrink-fit joints formed by shape-memory alloy elements and their application for the axial fixation of mechanical components. The use of shape-memory alloys gives the shrink-fits some specific features: ease of assembly, insensitivity to tooling and human error, chemical resistance, low cost, etc. The friction force created between the components is experimentally investigated as a function of two parameters—the substrate diameter and the surface roughness (Ra) of one of the joined elements. The results of the experiments are presented analytically and graphically. Conclusions are drawn regarding the behavior of the studied shrink-fits. They can be beneficial to any engineering project making it less sensitive to manufacturing variations.

Text-based CAPTCHAs remain the most widely adopted security scheme, which is the first barrier to securing websites. Deep learning methods, especially Convolutional Neural Networks (CNNs), are the mainstream approach for text CAPTCHA recognition and are widely used in CAPTCHA vulnerability assessment and data collection. However, verification code recognizers are mostly deployed on the CPU platform as part of a web crawler and security assessment; they are required to have both low complexity and high recognition accuracy. Due to the specifically designed anti-attack mechanisms like noise, interference, geometric deformation, twisting, rotation, and character adhesion in text CAPTCHAs, some characters are difficult to efficiently identify with high accuracy in these complex CAPTCHA images. This paper proposed a recognition model named Adaptive CAPTCHA with a CNN combined with an RNN (CRNN) module and trainable Adaptive Fusion Filtering Networks (AFFN), which effectively handle the interference and learn the correlation between characters in CAPTCHAs to enhance recognition accuracy. Experimental results on two datasets of different complexities show that, compared with the baseline model Deep CAPTCHA, the number of parameters of our proposed model is reduced by about 70%, and the recognition accuracy is improved by more than 10 percentage points in the two datasets. In addition, the proposed model has a faster training convergence speed. Compared with several of the latest models, the model proposed by the study also has better comprehensive performance.