Dynamic Translation Research Articles

Dynamic Multi-Granularity Translation System: DAG-Structured Multi-Granularity Representation and Self-Attention

In neural machine translation (NMT), the sophistication of word embeddings plays a pivotal role in the model’s ability to render accurate and contextually relevant translations. However, conventional models with single granularity of word segmentation cannot fully embed complex languages like Chinese, where the granularity of segmentation significantly impacts understanding and translation fidelity. Addressing these challenges, our study introduces the Dynamic Multi-Granularity Translation System (DMGTS), an innovative approach that enhances the Transformer model by incorporating multi-granularity position encoding and multi-granularity self-attention mechanisms. Leveraging a Directed Acyclic Graph (DAG), the DMGTS utilizes four levels of word segmentation for multi-granularity position encoding. Dynamic word embeddings are also introduced to enhance the lexical representation by incorporating multi-granularity features. Multi-granularity self-attention mechanisms are applied to replace the conventional self-attention layers. We evaluate the DMGTS on multiple datasets, where our system demonstrates marked improvements. Notably, it achieves significant enhancements in translation quality, evidenced by increases of 1.16 and 1.55 in Bilingual Evaluation Understudy (BLEU) scores over traditional static embedding methods. These results underscore the efficacy of the DMGTS in refining NMT performance.

The ART of Sharing Points-to Analysis: Reusing Points-to Analysis Results Safely and Efficiently

Data-flow analyses like points-to analysis can vastly improve the precision of other analyses, and enable powerful code optimizations. However, whole-program points-to analysis of large Java programs tends to be expensive – both in terms of time and memory. Consequently, many compilers (both static and JIT) and program-analysis tools tend to employ faster – but more conservative – points-to analyses to improve usability. As an alternative to such trading of precision for performance, various techniques have been proposed to perform precise yet expensive fixed-point points-to analyses ahead of time in a static analyzer, store the results, and then transmit them to independent compilation/program-analysis stages that may need them. However, an underlying concern of safety affects all such techniques – can a compiler (or program analysis tool) trust the points-to analysis results generated by another compiler/tool? In this work, we address this issue of trust in the context of Java, while accounting for the issue of performance. We propose ART: Analysis-results Representation Template – a novel scheme to efficiently and concisely encode results of flow-sensitive, context-insensitive points-to analysis computed by a static analyzer for use in any independent system that may benefit from such a precise points-to analysis. ART also allows for fast regeneration of the encoded sound analysis results in such systems. Our scheme has two components: (i) a producer that can statically perform expensive points-to analysis and encode the same concisely, (ii) a consumer that, on receiving such encoded results (called artwork), can regenerate the points-to analysis results encoded by the artwork if it is deemed “safe”. The regeneration scheme completely avoids fixed-point computations and thus can help consumers like static analyzers and JIT compilers to obtain precise points-to information without paying a prohibitively high cost. We demonstrate the usage of ART by implementing a producer (in Soot) and two consumers (in Soot and the Eclipse OpenJ9 JIT compiler). We have evaluated our implementation over various benchmarks from the DaCapo and SPECjvm2008 suites. Our results demonstrate that using ART, a consumer can obtain precise flow-sensitive, context-insensitive points-to analysis results in less than (average) 1% of the time taken by a static analyzer to perform the same analysis, with the storage overhead of ART representing a small fraction of the program size (average around 4%).

A dosimetrically motivated pathfinding approach for non-isocentric dynamic trajectory radiotherapy

Objective.Non-isocentric dynamic trajectory radiotherapy (DTRT) involves dynamic table translations in synchrony with intensity modulation and dynamic gantry, table, and/or collimator rotation. This work aims to develop and evaluate a novel dosimetrically motivated path determination technique for non-isocentric DTRT.Approach.The path determination considers all available beam directions, given on a user-specified grid of gantry angle, table angle, and longitudinal, vertical, and lateral table position. Additionally, the source-to-target distance of all beam directions can be extended by moving the table away from the gantry along the central beam axis to increase the collision-free space. The path determination uses a column generation algorithm to iteratively add beam directions to paths until a user-defined total path length is reached. A subsequent direct aperture optimization of the intensity modulation along the paths creates deliverable plans. Non-isocentric DTRT plans using the path determination and using a manual path setup were created for a craniospinal and a spinal irradiation case. Furthermore, VMAT, isocentric DTRT, and non-isocentric DTRT plans are created for a breast, head and neck (H&N), and esophagus case. Additionally, a HyperArc plan is created for the H&N case. The plans are compared in terms of the dosimetric treatment plan quality and estimated delivery time.Main results.For the craniospinal and spinal irradiation case, using path determination results in dose distributions with improved conformity but a slightly worse target homogeneity compared to manual path setup. The non-isocentric DTRT plans maintained target coverage while reducing the mean dose to organs-at-risk on average by 1.7 Gy (breast), 1.0 Gy (H&N), and 1.6 Gy (esophagus) compared to the VMAT plans and by 0.8 Gy (breast), 0.6 Gy (H&N), and 0.8 Gy (esophagus) compared to the isocentric DTRT plans.Significance.A general dosimetrically motivated path determination applicable to non-isocentric DTRT plans is successfully developed, further advancing the treatment planning for non-isocentric DTRT.

A spatial atlas of mitochondrial gene expression reveals dynamic translation hubs and remodeling in stress.

Mitochondrial genome expression is important for cellular bioenergetics. How mitochondrial RNA processing and translation are spatially organized across dynamic mitochondrial networks is not well understood. Here, we report that processed mitochondrial RNAs are consolidated with mitoribosome components into translation hubs distal to either nucleoids or processing granules in human cells. During stress, these hubs are remodeled into translationally repressed mesoscale bodies containing messenger, ribosomal, and double-stranded RNA. We show that the highly conserved helicase SUV3 contributes to the distribution of processed RNA within mitochondrial networks, and that stress bodies form downstream of proteostatic stress in cells lacking SUV3 unwinding activity. We propose that the spatial organization of nascent chain synthesis into discrete domains serves to throttle the flow of genetic information in stress to ensure mitochondrial quality control.

Can magnetic resonance imaging findings effectively diagnose the instability observed on radiographs in patients with degenerative lumbar spinal stenosis?

BackgroundDegenerative lumbar spinal stenosis (LSS) is a common condition that involves the narrowing of the spinal canal. Diagnosing instability traditionally requires standing lateral radiographs to detect dynamic translation, but there is debate about relying solely on radiographs due to challenges like patient discomfort and radiation exposure. This study aimed to evaluate if Magnetic Resonance Imaging (MRI) findings could effectively diagnose instability observed on radiographs.MethodsWe reviewed 478 consecutive patients with degenerative LSS who had surgery at our institution. Instability was defined as a sagittal translation exceeding 3 mm on standing lateral radiographs in both extension and flexion. Patients were divided into stable (those with < 3 mm translation) and unstable groups (those with > 3 mm translation). The study assessed potential variables for instability, including MRI findings like facet joint effusion, facet joint angle, disk height index, intradiscal vacuum presence, endplate sclerosis, ligamentum flavum hypertrophy, and multifidus muscle fatty degeneration, comparing these factors between the two groups.ResultsA total of 478 consecutive patients diagnosed with degenerative Lumbar Spinal Stenosis (LSS) were included. The average age of the patients was 66.32 years, with 43.3% being male. Approximately 27.6% of the cases exhibited signs of instability on the standing lateral radiograph during extension and flexion. The multivariate analysis using binary logistic regression revealed that facet joint effusion (odds ratio [OR] 2.73; 95% confidence interval [CI] 1.27–3.94; P = 0.002), disk height index (OR 2.22; 95% CI 1.68–3.35; P = 0.009), and the presence of the Vacuum sign (OR 1.77; 95% CI 1.32–2.84; P = 0.021) were identified as factors associated with instability.ConclusionsOur findings showed thata higher facet joint effusion, the presence of Vacuum sign, and a greater Disk Height Index were associated with the presence of instability on the standing lateral radiograph in extension and flexion in patients with degenerative LSS.

Advancing IOT Interoperability: Dynamic Protocol Translation through Machine Learning For Enhanced Communication Efficiency

This study presents a pioneering methodology for Dynamic Protocol Translation in the Internet of Things (IoT), aiming to overcome challenges posed by diverse communication protocols among IoT devices. The primary objective is to develop a two-fold approach: first, acquiring data from IoT devices through their specific protocols, preprocessing it for consistency, and employing Natural Language Processing (NLP) techniques for semantic extraction and normalization; second, implementing a machine learning model, incorporating neural networks, to discern correlations between normalized representations and target protocol structures. The emphasis is on rigorous testing, validation, &amp; real-time translation capabilities. The main conclusions of the study demonstrate how well the suggested Logistic Regression model performed, with an accuracy of 96.76%, in contrast to an existing model (XML-JSON) that had an accuracy of 82.41%. The detailed evaluation metrics, which include F1 score, precision, and recall, demonstrate how well the suggested method works to solve protocol translation issues. The iterative feedback loop, real-time translation, and secure data transfer of the proposed system improve its adaptability and reliability. This research enhances the field of IoT communication by offering a comprehensive solution for smooth interoperability &amp; communication efficiency in a range of IoT applications.

A Rigorous 2D-3D Registration Method for a High-Speed Bi-Planar Videoradiography Imaging System.

High-speed biplanar videoradiography can derive the dynamic bony translations and rotations required for joint cartilage contact mechanics to provide insights into the mechanical processes and mechanisms of joint degeneration or pathology. A key challenge is the accurate registration of 3D bone models (from MRI or CT scans) with 2D X-ray image pairs. Marker-based or model-based 2D-3D registration can be performed. The former has higher registration accuracy owing to corresponding marker pairs. The latter avoids bead implantation and uses radiograph intensity or features. A rigorous new method based on projection strategy and least-squares estimation that can be used for both methods is proposed and validated by a 3D-printed bone with implanted beads. The results show that it can achieve greater marker-based registration accuracy than the state-of-the-art RSA method. Model-based registration achieved a 3D reconstruction accuracy of 0.79 mm. Systematic offsets between detected edges in the radiographs and their actual position were observed and modeled to improve the reconstruction accuracy to 0.56 mm (tibia) and 0.64 mm (femur). This method is demonstrated on in vivo data, achieving a registration precision of 0.68 mm (tibia) and 0.60 mm (femur). The proposed method allows the determination of accurate 3D kinematic parameters that can be used to calculate joint cartilage contact mechanics.

Catalyst: a Python JIT compiler for auto-differentiable hybrid quantum programs

Catalyst: a Python JIT compiler for auto-differentiable hybrid quantum programs

AI approach on identifying change in public sentiment for major events: Dubai Expo 2020

Existing research in identifying changes in public sentiment for major events faces limitations in capturing the intricacies of temporal changes, especially with large-scale data and diverse linguistic nuances. This study addresses this problem, with a particular focus on the globally acclaimed Dubai Expo 2020. The methodology employed in this research introduces a groundbreaking approach by leveraging advanced data engineering techniques on a massive corpus of 118,025 Tweets obtained from diverse users across 60 languages, covering the period from April 2021 to March 2023. The study pioneers the application of artificial intelligence (AI), natural language processing (NLP), and Large Language Models (LLMs) for sentiment analysis and topic modeling on Twitter discourse. Through the meticulous data engineering process, including language detection, dynamic translation, and sentiment analysis, the research identifies subtle yet statistically significant changes in public sentiment, as evidenced by ANOVA testing (p=0.018 in average positive sentiment, p=0.004 in average neutral sentiment, and p=0.005 in average negative sentiments). Additionally, the study innovatively extracts and analyzes support-related Tweets, revealing distinct phases in temporal domains (pre-Expo, Expo, Post-Expo1, and Post-Expo2) and yielding 11,116 support-related tweets. The application of NLP techniques further uncovers 19 topics from UAE-related Tweets, providing a comprehensive understanding of the dynamic landscape of public sentiment over a two-year period. This research contributes significantly to the field by offering a novel and comprehensive framework for analyzing public sentiment, particularly in the context of major events, and sheds light on its broader implications for event management and public perception analysis.

Clavicular tunnel widening in chronic acromioclavicular joint instabilities after primary versus revision arthroscopically-assisted acromio- and coracoclavicular stabilization.

To evaluate joint reduction (loss of reduction [LOR]; dynamic posterior translation [DPT]) and clavicular tunnel widening (cTW) in patients treated with arthroscopically-assisted acromioclavicular joint (ACJ) stabilization after previously failed nonoperative versus surgical treatment. Patients undergoing arthroscopically-assisted ACJ stabilization (bidirectional tendon allograft with a low-profile TightRope) after previously failed nonoperative versus surgical treatment were included retrospectively. Bilateral anteroposterior stress views served for evaluating LOR (side-comparative coracoclavicular distance [CCD]) and cTW at a 6-weeks- and 6-months-follow-up (FU) and for evaluating the filling ratio (FR, vertical device insertion depth relative to clavicle height) at the 6-weeks-FU. Postoperative DPT was assessed on Alexander's views. Twenty-seven patients (20 male, mean age 46.1 ± 14.8 years) were included (prior treatment: nonoperative: n = 15; surgical: n = 12). There were no differences in LOR, DPT or cTW between groups postoperatively. Initial CCD-symmetry at the 6-weeks-FU (CCD: -0.1 mm [95% confidence interval, CI, -2 to 1.4 mm]) was followed by LOR at the 6-months-FU (CCD: -3.5 mm [95% CI, -5.2 to -1.9 mm]; p < 0.001). cTW increased towards the inferior cortex, compared to the superior cortex and the intermediate level (p < 0.001, respectively). cTW at the inferior cortex was associated with more LOR (r = -0.449; p = 0.024) and DPT (r = 0.421; p = 0.036), dependent on a smaller FR (r = -0.430; p = 0.032). Patients undergoing arthroscopically-assisted ACJ stabilization for chronic bidirectional ACJ instabilities showed comparable radiologic results after previous nonoperative versus surgical treatment. cTW increased towards the inferior cortex and was associated with recurrent vertical and horizontal instability, related to a smaller FR. More research into reduced cTW, for example, by a more filling device, should be performed. Level III, retrospective comparative study.

The Development of New Scoring System to Define the Presence of Instability and the Need of Fusion in Degenerative Lumbar Spinal Stenosis - Jakarta Instability Score.

Systematic review, expert opinion and Delphi technique, and validity and reliability studies. We developed Jakarta Instability Score (JIS) to identify spinal instability and the need of fusion in degenerative lumbar spinal stenosis (LSS). This study consisted of systematic review to find predictors of spinal instability, expert opinion and modified Delphi technique to develop JIS, and validity and reliability studies of the newly developed JIS. A total of 54 studies were included in the systematic reviews to obtain predictors of spinal instability. Through expert opinion and modified Delphi technique, JIS was developed and consisted of the clinical component (back pain), dynamic radiograph component (dynamic translation and angulation), and MRI component (facet joint effusion), each of the component would be scored, and the total scoring would be from 0 to 14. The final scoring would classify patients into three groups: stable group (score of 0 to 4) in which the fusion is not needed, potentially unstable group (score of 5 to 8) in which the decision of fusion is based on surgeon's clinical judgment, and unstable group (score of 9 to 14) in which the fusion is needed. Final step of study concluded that this JIS had a high validity and reliability. The newly developed JIS was a valid and reliable scoring system that could help to identify the presence of instability in LSS and can be used as a guideline to decide whether spinal fusion will be needed.

COGNITIVE PROCESSING AND MEMORY TECHNIQUES IN CONSECUTIVE INTERPRETATION

This study investigates the psychophysiological characteristics and memory utilization in professional translators specializing in consecutive interpretation. Utilizing a comprehensive questionnaire, the study gathered data from practicing translators to understand how mechanical, logical, and imaginative memory strategies impact their translation performance, particularly focusing on spoken information retention over extended periods. Results indicate a strong preference for logical memorization due to its effectiveness in structuring and understanding complex information. However, imaginative memorization also plays a crucial role in scenarios requiring dynamic translation solutions. These findings suggest that training programs should emphasize versatile memory strategies to enhance translation accuracy and efficiency.

Dynamic Weighting Translation Transfer Learning for Imbalanced Medical Image Classification.

Medical image diagnosis using deep learning has shown significant promise in clinical medicine. However, it often encounters two major difficulties in real-world applications: (1) domain shift, which invalidates the trained model on new datasets, and (2) class imbalance problems leading to model biases towards majority classes. To address these challenges, this paper proposes a transfer learning solution, named Dynamic Weighting Translation Transfer Learning (DTTL), for imbalanced medical image classification. The approach is grounded in information and entropy theory and comprises three modules: Cross-domain Discriminability Adaptation (CDA), Dynamic Domain Translation (DDT), and Balanced Target Learning (BTL). CDA connects discriminative feature learning between source and target domains using a synthetic discriminability loss and a domain-invariant feature learning loss. The DDT unit develops a dynamic translation process for imbalanced classes between two domains, utilizing a confidence-based selection approach to select the most useful synthesized images to create a pseudo-labeled balanced target domain. Finally, the BTL unit performs supervised learning on the reassembled target set to obtain the final diagnostic model. This paper delves into maximizing the entropy of class distributions, while simultaneously minimizing the cross-entropy between the source and target domains to reduce domain discrepancies. By incorporating entropy concepts into our framework, our method not only significantly enhances medical image classification in practical settings but also innovates the application of entropy and information theory within deep learning and medical image processing realms. Extensive experiments demonstrate that DTTL achieves the best performance compared to existing state-of-the-art methods for imbalanced medical image classification tasks.

Evaluation of Anterior Tibial Translation Under Physiological Axial Load After ACL Reconstruction With Lateral Extra-articular Tenodesis.

Postoperative laxity correlates with negative clinical outcomes after anterior cruciate ligament reconstruction (ACLR). The influence of lateral extra-articular tenodesis (LET) on anteroposterior translation is unclear. This study aimed to evaluate the reduction in radiographic static anterior tibial translation (SATT) and dynamic anterior tibial translation (DATT) after LET as an adjunctive procedure to ACLR. It was hypothesized that adding a LET procedure would have no effect on postoperative SATT and DATT. Cohort study; Level of evidence, 3. Patients who underwent primary ACLR with hamstring tendon autografts between 2020 and 2022 were reviewed, and those who underwent ACLR and LET as an anterolateral associate procedure were paired 1 to 1 with those who underwent isolated ACLR (control) based on age, sex, preoperative SATT, and posterior tibial slope (PTS). The indications for LET were age <18 years and anterolateral rotary instability (grade ≥2 pivot shift). A previously validated technique was used to measure SATT, DATT, and PTS on lateral weightbearing and lateral stress knee radiographs. Preoperative and 9-month postoperative radiographs were compared between the 2 groups. A total of 72 patients were included in the analysis (n = 36 patients in each group). The inter- and intraobserver reliability of the SATT, DATT, and PTS measurements was excellent (intraclass correlation coefficients, 0.88-0.99). The mean pre- and postoperative SATT in the ACLR+LET group was 2.44 ± 2.90 mm and 2.44 ± 2.38 mm, respectively, compared with 2.60 ± 2.99 mm and 2.12 ± 2.74 mm, respectively, in the control group. The mean pre- and postoperative reduction in side-to-side DATT in the ACLR+LET group was 5.44 ± 4.65 mm and 1.13 ± 2.95 mm, respectively, compared with 5.03 ± 3.66 mm and 2 ± 3.12 mm, respectively, in the control group. There was no pre- to postoperative difference in SATT (P = .51). However, the side-to-side DATT was reduced by 3.66 ± 3.37 mm postoperatively (P < .001), without significant differences between groups (P = .24). Including a LET procedure for patients undergoing ACLR did not reduce SATT; that is, it did not decrease the amount of tibial translation due to physiological axial load.

Analysis of Interaction Mechanisms between Java and JavaScript Programming Languages: from LiveConnect to Graal.js

The article is devoted to the study of the mechanisms of interaction between the popular programming languages Java and JavaScript using a retrospective approach. The author consistently examines the development of tools of this kind, starting from LiveConnect technology and Java applets of the mid-1990s and ending with the interpreters of the last decade. Particular attention is paid to comparing the performance of the currently relevant tools Nashorn and Graal.js. The latter is an implementation of the JavaScript language based on the Truffle framework and Context API, which is a Polyglot context for executing all supported guest languages with the Graal JIT compiler, ensuring their optimal performance. The author gives a definition to the term "warm-up", which is recommended by the GraalVM developers to achieve the highest performance. This is a kind of pre-compilation mode, the process of repeated preliminary execution of JavaScript code by the interpreter before its actual usage in order to obtain information about the most frequently utilized fragments of the program, its functions, types and data structures, alongside with their subsequent caching and optimization. The results of testing based on a project from Oracle and the authors application made it possible to verify the results declared by the GraalVM developers and can be used to optimize and improve the performance of multilingual projects using a unified technology stack, as well as when migrating the server code base from Java to JavaScript.

Contrastive Unfolding Deraining Network.

Due to the fact that the degradation of image quality caused by rain usually affects outdoor vision tasks, image deraining becomes more and more important. Focusing on the single image deraining (SID) task, in this article, we propose a novel Contrastive Unfolding DEraining Network (CUDEN), which combines the traditional iterative algorithm and deep network, exhibiting excellent performance and nice interpretability. CUDEN transforms the challenge of locating rain streaks into discovering rain features and defines the relationship between the image and feature domains in terms of mapping pairs. To obtain the mapping pairs efficiently, we propose a dynamic multidomain translation (DMT) module for decomposing the original mapping into sub-mappings. To enhance the feature extraction capability of networks, we also propose a new serial multireceptive field fusion (SMF) block, which extracts complex and variable rain features with convolution kernels of different receptive fields. Moreover, we are the first to introduce contrastive learning to the SID task and combine it with perceptual loss to propose a new contrastive perceptual loss (CPL), which is quite generalized and greatly helpful in identifying the appropriate gradient descent direction during training. Extensive experiments on synthetic and real-world datasets demonstrate that our proposed CUDEN outperforms the state-of-the-art (SOTA) deraining networks.

A Comparative Study of the English Translations of Four Selected Surahs of Qur’an

The main objective of the research is to gain a greater comprehension of Allah's message, which He has revealed in the form of the Holy Quran. The purpose of this research is to investigate which translation has succeeded in presenting the most accurate interpretation of the meaning of the verses. In this research, three different translations of 4 selected Surahs of the Qur'an, also known as the four Quls, are analyzed by using a comparative approach. The selected translators are Abdullah Yusuf Ali, Muhammad Marmaduke Pickthall, and Muhammad Asad. Qualitative and quantitative methodologies have been employed. The verses are first evaluated qualitatively. To be more accurate, the total amount of words in every translation is compared to the total number of words in the target language's surah. The study shows that Pickthall's translation is "formal correspondences," while M. Asad's translation is "dynamic." The translation of Yusuf Ali follows both paths. In the case of Surah Ikhlas and Surah Falaq, it is more "formal", and in the case of the other two surahs, it is "dynamic translation".

Synthetic turf finite element model development and validation

Assessment of synthetic turf performance has been undertaken using a variety of experimental methods but is limited in understanding the complex physics of cleat-turf interaction. Computational models could provide insight, but there is currently no validated model of synthetic turf available. The scope of this study was to develop a Finite Element (FE) model of synthetic turf using a hierarchical approach and validate the model using independent test data. A physical third-generation synthetic turf comprising slit-film fibers with sand and rubber crumb infill was constructed. Experiments were conducted using a direct impact (Clegg) device and an artificial cleat-form. Material characterization tests were performed on the individual turf components, integrated into constitutive models, and a full turf FE model was constructed. The carpet was modeled with shell elements while the granular infill was modeled using smoothed-particle hydrodynamics (SPH) elements. A method to simulate the physical pre-conditioning performed on the experimental turf was developed. Both unconditioned and pre-conditioned turfs were assessed using Clegg tests. The re-created Clegg tests on the turf model demonstrated good agreement with the physical tests, with higher acceleration for the pre-conditioned turf. The turf model was validated using experiments with a turf test apparatus including dynamic translation and rotation of a cleat-form. The model predicted results in good agreement with the experiments (average CORA rating of 0.863) on pre-conditioned turf. The resulting model and methods can be expanded to synthetic turf of different constituent materials, to investigate their effects on cleat-surface interaction, optimizing performance, and reducing injury risk.

Experimental validation of IoT image encryption scheme based on a 5-D fractional hyperchaotic system and Numba JIT compiler

In the realm of Internet of Things (IoT) systems, the interconnectivity of physical hardware devices is a fundamental aspect, and as a result, data exchange assumes a critical role in the network. Given the sensitivity of such information, it is imperative to adopt appropriate measures to encrypt the data to safeguard it from unauthorized access. It is, therefore, paramount to prove novel encryption algorithms at an experimental level. To overcome that, a potential solution is fractional-order multi-scroll chaotic systems, which provide an extra degree of freedom to enhance ergodicity and random-like behaviors, which can help to improve encryption keyspace to get robust ciphers. However, the numerical algorithms to obtain a fractional chaotic series increase the computational cost because they demand extensive simulation time to model the memory of the standard fractional derivatives, limiting high-speed encryption. In this framework, a fast encryption scheme using a 5D fractional-order (FO) hyper-chaotic multi-scroll (HCMS) system is proposed and verified experimentally. Based on multiprocessing strategies and the Numba just-in-time (JIT) compiler, the Python code that describes the FO-HCMS system is optimized, which enables image encryption in real-time. The physical implementation of the encryption scheme is performed on an Advance RISC Machine (ARM) processor, and it is applied for image encryption on a machine-to-machine (M2M) communication using the message queuing telemetry transport (MQTT) protocol. The obtained results indicate that the proposed encryption scheme can reach encryption throughputs of up to 19.891 Mbps on an ARM with a 1.4 GHz CPU and 77.864 Mbps on a PC with a 3.1 GHz CPU.

Orality in Translating Biblical Hebrew Proverbs in Sesotho

This paper evaluates how Sesotho translators have translated Biblical Hebrew proverbs in the 1989 Sesotho translation of the Bible. Because this 1989 translation is undergoing revision by the Bible Society of South Africa, it is important to determine the success of the translation. The orality of proverbs relates to their origin as orally transmitted sapiential sayings. In evaluating how some of the Biblical Hebrew proverbs are translated in Sesotho, the literal translation of 1909/61 will be compared to the 1989 dynamic equivalent translation. Using complexity thinking as a theoretical framework, the paper argues that the Hebrew proverbs are better translated in the 1989 version than they are in the 1909/61 version of the Bible in Sesotho in terms of numerous features of orality. In the 1989 version and its revision, proverbs are translated in a poetic format. This means that the translated proverbs in this version of the Bible, informed by the principles of orality, exhibit Sesotho poetic features or structures. The article is divided into the following components: proverbs in Hebrew and Sesotho, theoretical frameworks, how the theoretical frameworks are used to translate certain Hebrew proverbs in the 1989 version, and conclusions.