Miracle-dz/UniFAR-FTUs huggingface dataset:
Industry 5 and the Human in Human-Centric Manufacturing

Industry 4 (I4) was a revolutionary new stage for technological progress in manufacturing which promised a new level of interconnectedness between a diverse range of technologies. Sensors, as a point technology, play an important role in these developments, facilitating human–machine interaction and enabling data collection for system-level technologies. Concerns for human labour working in I4 environments (e.g., health and safety, data generation and extraction) are acknowledged by Industry 5 (I5), an update of I4 which promises greater attention to human–machine relations through a values-driven approach to collaboration and co-design. This article explores how engineering experts integrate values promoted by policy-makers into both their thinking about the human in their work and in their writing. This paper demonstrates a novel interdisciplinary approach in which an awareness of different disciplinary epistemic values associated with humans and work guides a systematic literature review and interpretive coding of practice-focussed engineering papers. Findings demonstrate evidence of an I5 human-centric approach: a high value for employees as “end-users” of innovative systems in manufacturing; and an increase in output addressing human activity in modelling and the technologies available to address this concern. However, epistemic publishing practices show that efforts to increase the effectiveness of manufacturing systems often neglect worker voice.
Pareto-Optimized Non-Negative Matrix Factorization Approach to the Cleaning of Alaryngeal Speech Signals

Simple Summary This paper introduces a new method for cleaning impaired speech by combining Pareto-optimized deep learning with Non-negative Matrix Factorization (NMF). The approach effectively reduces noise in impaired speech while preserving the desired speech quality. The method involves calculating the spectrogram of a noisy voice clip, determining a noise threshold, computing a noise-to-signal mask, and smoothing it to avoid abrupt transitions. Using a Pareto-optimized NMF, the modified spectrogram is decomposed into basis functions and weights, allowing for reconstruction of the clean speech spectrogram. The final result is a noise-reduced waveform achieved by inverting the clean speech spectrogram. Experimental results validate the method’s effectiveness in cleaning alaryngeal speech signals, indicating its potential for real-world applications. Abstract The problem of cleaning impaired speech is crucial for various applications such as speech recognition, telecommunication, and assistive technologies. In this paper, we propose a novel approach that combines Pareto-optimized deep learning with non-negative matrix factorization (NMF) to effectively reduce noise in impaired speech signals while preserving the quality of the desired speech. Our method begins by calculating the spectrogram of a noisy voice clip and extracting frequency statistics. A threshold is then determined based on the desired noise sensitivity, and a noise-to-signal mask is computed. This mask is smoothed to avoid abrupt transitions in noise levels, and the modified spectrogram is obtained by applying the smoothed mask to the signal spectrogram. We then employ a Pareto-optimized NMF to decompose the modified spectrogram into basis functions and corresponding weights, which are used to reconstruct the clean speech spectrogram. The final noise-reduced waveform is obtained by inverting the clean speech spectrogram. Our proposed method achieves a balance between various objectives, such as noise suppression, speech quality preservation, and computational efficiency, by leveraging Pareto optimization in the deep learning model. The experimental results demonstrate the effectiveness of our approach in cleaning alaryngeal speech signals, making it a promising solution for various real-world applications.
Burn assessment: A critical review on care, advances in burn healing and pre-clinical animal studies

: Burn, a severe skin injury due to electricity, radiation, chemicals, or friction, may lead to the death of affected skin cells. Burns are a painful and crucial problem which causes disabilities. Sometimes, burns may also associate with the mortality of burn-injured patients. First-degree, second-degree, and third-degree are three categories of burns. First-degree burns (superficial burns) create minor skin damage as it affects the only uppermost layer of skin, and domestic care is sufficient for the treatment. Second-degree burns have injuries beyond the upper layer of skin, and third-degree burns reach every layer of skin, including nerve injuries that require critical care in treatment. Burn injuries are not limited to local; they may also give systemic responses and cause serious problems. Microbial infection is the most severe challenge associated with second and third-degree burns injuries. The ultimate goal for treating burn injuries is re-epithelialization with minimum tissue scarring. Selection of the appropriate treatment will be based on the extremity of the burn injury. The most prevalent and effective treatment is topical agents containing mafenide acetate, silver sulfadiazine, silver nitrate, etc. Skin substitutes, negative pressure wound therapy, and skin grafting are advanced treatments for burn injuries. Burn treatment is also associated with complications such as infection, dehydration, low body temperature, and emotional problems. Animal studies for burn models are performed using rabbits, rats, and pigs. This may be an effective way to find out the new forms of burn treatment, including assessing newly developed formulations.
On Operational Space Tracking Control of Robotic Manipulators With Uncertain Dynamic and Kinematic Terms

In this study, a continuous robust-adaptive operational space controller that ensures asymptotic end-effector tracking, despite the uncertainties in robot dynamics and on the velocity level kinematics of the robot, is proposed. Specifically, a smooth robust controller is applied to compensate the parametric uncertainties related to the robot dynamics while an adaptive update algorithm is used to deal with the kinematic uncertainties. Rather than formulating the tracking problem in the joint space, as most of the previous works on the field have done, the controller formulation is presented in the operational space of the robot where the actual task is performed. Additionally, the robust part of the proposed controller is continuous ensuring the asymptotic tracking and relatively smooth controller effort. The stability of the overall system and boundedness of the closed loop signals are ensured via Lyapunov based arguments. Experimental results are presented to illustrate the feasibility and performance of the proposed method.
Therapeutic Effect of Guilu Congnao Granules Combined with Acupuncture on Syndrome of Deficiency of Liver and Kidney with Mental Retardation

: To observe the clinical effect of Guilu Congnao granules combined with acupuncture in the treatment of mental retardation syndrome of liver and kidney insufficiency. Sixty children with mental retarding syndrome of liver and kidney deficiency were randomly divided into two groups. The treatment group was given Guilucongnao granules combined with acupuncture and rehabilitation training, while the control group was given rehabilitation training only. The children in both groups were treated for three months, and the intelligence level of the children in both groups was statistically measured by Nimodipine before and after treatment. The Chinese revised Wechsler Childhood Intelligence Scale was used to compare the efficacy before and after treatment. The overall efficacy of the treatment group was better than that of the control group, and the comparison between groups was statistically significant (p&lt; 0.05). The curative effect of Gulumcongnao granules combined with acupuncture on children with mental retardation syndrome of liver and kidney insufficiency is obvious.
The applications of chatbot

A chatbot is a program that uses natural language to simulate a human conversation. and can receive questions from users to answer, as well as engage in casual conversation with users in a set format or help them complete a matter. It can free up personnel in an organization that is needed for reasonably stable, repetitive, and demanding tasks or procedures. Natural language processing (NLP), an essential aspect of artificial intelligence, forms the foundation of the system. , and neural networks (NNs) that receive natural language and process responses. In recent years, chatbots have grown significantly with the rise of artificial intelligence, with achievements by major Internet companies, various universities, and research institutes. This review provides a detailed study of chatbots in five areas of intelligence in recent years, including education, intelligent question and answer, customer service, entertainment, and personal assistants. The goal is to summarize the cutting-edge and effective technologies in each area. In reviewing these papers, we pay closer attention to the technology in this paper's potential development possibilities and whether relevant experiments or detailed descriptions are done for the proposed future extensions, etc. While we discuss and study the current technologies, we also pay attention to the possibilities and trends in the development of new fields.
Characteristics and Treatment Patterns of Patients with Diabetic Macular Edema Non-Responsive to Anti-Vascular Endothelial Growth Factor Treatment in Ontario, Canada

Purpose To understand the demographics, clinical characteristics, treatment patterns, visual and anatomic responses of patients with diabetic macular edema (DME) initially treated with anti-vascular endothelial growth factor (anti-VEGF) agents in the real-world clinical setting. Patients and Methods This retrospective cohort study used electronic health records to identify consecutively presenting patients with DME who received their first documented anti-VEGF injection (index injection) on or after 1 October 2015 and before 30 September 2016 (index period) at 4 clinical sites in Ontario, Canada. Patients receiving anti-VEGF injections in the study eye were followed for ≥18 months. After the first 3 monthly injections, patients were classified as “responder” (≥20% reduction in central retinal thickness [CRT] from index date) or “nonresponder” (<20% reduction in CRT) to anti-VEGF treatment. Results At 12 months, change from baseline (CFB) in best visual acuity (BVA) of responders (n = 30) was mean (SD) 12.8 (13.00) letters; CFB in nonresponders (n = 56) was 3.2 (16.3) letters. Sensitivity analyses stratified by initial BVA were supportive. Mean (SD) change in CRT (μm) was −160.4 (111.4) in responders and −62.2 (98.6) in nonresponders. While changes in anti-VEGF therapy were lower in responders versus nonresponders (10.0% vs 23.2%), mean number of injections was similar (8.3 in each cohort). Conclusion Despite receiving a substantial number of injections and requiring changes in therapy more frequently, nonresponders showed a lack of clinically meaningful change in BVA and CRT. Nonresponders could be identified after 3 anti-VEGF injections. There remains an unmet need for treatment options in patients with DME who show a nonresponse after 3 months of anti-VEGF treatment.
Faba Bean Processing: Thermal and Non-Thermal Processing on Chemical, Antinutritional Factors, and Pharmacological Properties

The food industry, academia, food technologists, and consumers have become more interested in using faba bean seeds in the formulation of new products because of their nutritional content, accessibility, low costs, environmental advantages, and beneficial impacts on health. In this review, a systematic and up-to-date report on faba bean seeds’ antinutrients and bioactive and processing techniques is comprehensively presented. The chemical composition, including the oil composition and carbohydrate constituents, is discussed. Factors influencing the reduction of antinutrients and improvement of bioactive compounds, including processing techniques, are discussed. Thermal treatments (cooking, autoclaving, extrusion, microwaving, high-pressure processing, irradiation) and non-thermal treatments (soaking, germination, extraction, fermentation, and enzymatic treatment) are identified as methods to reduce the levels of antinutrients in faba bean seeds. Appropriate processing methods can reduce the antinutritional factors and enrich the bioactive components, which is useful for the seeds’ efficient utilization in developing functional foods. As a result, this evaluation focuses on the technologies that are employed to reduce the amounts of toxins in faba bean seeds. Additionally, a comparison of these methods is performed in terms of their advantages, disadvantages, viability, pharmacological activity, and potential for improvement using emerging technologies. Future research is expected in this area to fill the knowledge gap in exploiting the nutritional and health benefits of faba bean seeds and increase the utilization of faba bean seeds for different applications.
New Geographical Routing Protocol for Three-Dimensional Flying Ad-Hoc Network Based on New Effective Transmission Range

Flying ad-hoc network (FANET) consisting of multiple unmanned aerial vehicles (UAVs) has the merits of rapid deployment, widespread coverage, and independence of infrastructure. Designing a reliable and robust routing protocol for FANET is essential and challenging. This article proposes a robust and reliable geographical routing protocol, named best-link and three-dimensional (3D) perimeter forwarding routing protocol (BLPR). Different from the existing studies based on a constant transmission range assumption, we propose a more practical metric of time-varying effective transmission range (ER). Considering the wireless channel propagation and the interference from other UAVs, the expression for ER is derived. Then, we propose a new best-link forwarding strategy, which selects the next-hop relay to forward data from a relay selection region specified by the ER being the radius. Furthermore, a routing recovery model, named 3D perimeter forwarding strategy, is designed to avoid local optima. Numerical experiments on the NS-3.29 platform demonstrate that the BLPR achieves significant performance gains over traditional 3D geographical routing algorithms and a state-of-the-art centralized routing protocol in terms of packet delivery ratio and throughput.
Experimental Investigation of Augmented Electromagnetic Accelerators

Electromagnetic accelerators use electrical energy to accelerate projectiles to large velocities above 2 km/s [1]. A simple electromagnetic launcher consists of two rails, which are connected by a sliding armature in between them. Applying an electric current to the rails and the armature leads to a magnetic field in between the rails. The magnetic field together with the electric current in the armature leads to an accelerating Lorentz-force, acting on the armature. Due to magnetic field diffusion effects, the electric current is concentrated on the rear part of the armature and on the inner surfaces of the rails, resulting in high current concentrations and therefore heat generation. Together with the friction of the sliding contact between the armature and the rails, abrasive wear of the materials can occur and cause a transition from a solid contact to a plasma contact. This can further increase the temperature and the wear of the rail/armature interface. To decrease the electric current through the armature without decreasing the accelerating force on the projectile, an additional magnetic field can be applied in between the rails of the launcher. In order to study electromagnetic launchers with a magnetic field augmentation, the modular augmented staged electromagnetic launcher (MASEL) is designed, built and tested at ISL. This augmented launcher uses two external coils with up to four windings each, to produce a large additional magnetic field. The mechanical and electrical properties of the setup are calculated using different simulations. The results of the simulations are used to improve the structure of the launcher. The experimental setup of the MASEL allows to study multiple different configurations such as the simple electromagnetic launcher, the parallel augmented, the series augmented and the energy storage augmentation configuration. In addition, the setup allows the integration of a current multiplication system, which simultaneously augments the magnetic field in the launcher. The experiments show that it is possible to increase the velocity of the projectile by a factor of two and the system energy efficiency by a factor of four, without increasing the current through the armature. Furthermore, the integration of the pulse forming inductance of the power supply units into the launcher is demonstrated. The maximum projectile velocity of 181m/s from the experiments with the conventional electromagnetic launcher is increased to 389m/s, using the magnetic field augmentation. This translates to an energy efficiency increase from 0.9% to 4.4%. In the experiments with two stages of the MASEL, the velocity of the projectile increases to 713m/s, resulting in a larger energy efficiency of 4.8%. For this setup, a muzzle arc suppression device and a trigger management system are developed to ensure a reliable operation.
Performance and Stability Analysis of Selected Durum Wheat Genotypes Differing in Their Kernel Characteristics

Breeding of high-yielding and stable durum wheat varieties with improved kernel characteristics is needed for dry regions around the globe. The aim of this study was to investigate the performance and stability of eight durum wheat genotypes varying in their kernel characteristics across 15 contrasting environments. The tested material included three recombinant inbred lines (NUR-072, NUR-106 and NUR-238) derived from a cross between Norsi, a Jordanian landrace with special kernel characteristics and UC1113 Yr36+Gpc-B1, an elite line from USA. Field trials were carried out for three constitutive growing seasons under rainfed conditions, except for three environments where supplementary irrigation was provided. After the harvest, grain yield (GY), total yield (TW), and harvest index (HI) were recorded. Additionally, several kernel-related traits, including thousand kernel weight (TKW), kernel area (KA), kernel width (KW), kernel length (KL), kernel circularity (KC), and kernel length–width ratio (KL:KW) were evaluated. Analysis of variance for all tested traits revealed high significant variations (p ≤ 0.01) between the genotype (except for TW) and the genotype × environment (G × E) interaction. Genotype effect contributed to substantial percentage of variation (>75%) for KA, KL, KC and KL:KW, whereas KW showed a lower percentage similar to GY. Regarding the G × E effect, explained variation was highest for the TW (67.79%), and lowest for KL (6.47%). For GY, Norsi produced significantly the lowest mean value (249.99 g.m−2) while, Bolenga produced the highest mean value (377.85 g.m−2) although no significant differences were observed with the remaining genotypes. On the other hand, Norsi, NUR-072 and NUR-106 showed best performance for TKW and kernel-related traits with NUR-106 producing the highest mean value for KL (9.07 mm). The GGE biplot and AMMI analysis of GY identified Bolenga, Um Qais and NUR-106 as good performers across several environments, while Norsi exhibited the poorest performance. For TKW, Norsi was the best performer across different environments followed by NUR-106, which showed excellent performance under irrigated and saline conditions. For stability analysis, NUR-106 emerged as the most stable genotype in this study for GY and several kernel-related traits, particularly for KL and KC. In conclusion, the results of this study offer valuable insights for durum wheat breeders seeking to develop high-yielding and stable varieties with special kernel characteristics suitable for cultivation in dry areas.
Proteomic Analysis of Extremely Low-Frequency ElectroMagnetic Field (ELF-EMF) With Different Intensities in Rats Hippocampus

Background: Ourpreviousstudydeterminedthealterationinbehavioraltest-relatedmemoryandmovementinmaleratsexposed to extremely low frequency electromagnetic ﬁeld (ELF-EMF). The molecular mechanism of the eﬀect of ELF-EMF on brain damage of rat has not yet fully understood, thus the current study investigated the eﬀect of ELF-EMFs on hippocampus of male rats by the proteomics approach. The aim of this study was to investigate the eﬀects of 50 Hz ELF-EMF at 0.5 and 1 mT 50 Hz for 2 and 4 weeks on male rats and determined protein expression of the hippocampus. Methods: Eﬀects of 0.5 and 1 mT exposures for 2 and 4 weeks on protein expression was determined via proteomics techniques. Statisticalanalysisof proteomewasperformedusingtheProgensisSameSpotssoftware. Bioinformaticsanalysisbasedonnetwork was used for determining the mechanism. Results: Two-DE electrophoresis gels determined the eﬀect of ELF-EMF on rat hippocampus, indicating that protein expression was overalldown-regulatedbyincreasingELF-EMFintensityandtime. Thedetecteddiﬀerentiallyexpressedproteinsbetweenthegroups comprised of Sptan1, Dpysl2, Tpi1, Lap3, Vdac1, and Tppp. Almost all were cytoskeletal proteins, most of which were increased by intensity and time. These proteins attributed to impairment in short memory of hippocampus after exposure to ELF-EMF. The GO analysis based on network, enriched two important biological process, cytoskeletal neurons and metabolic process. Conclusions: This study determined the eﬀect of ELF-EMF, which led to change in protein expression related to the cytoskeleton that contributes to major processes in brain damage.
Numerical Study on a Rotationally-Symmetrical Dipole Array Antenna Position for a MIMO Full-Duplex System

: In this letter, a rotationally-symmetrical array (RSA) arrangement of a receiving dipole array antenna is optimized to maximize the performance of the null-beamforming method for the suppression of self-interference. The optimum RSA for a receiving dipole array with four elements is clari(cid:12)ed. Through numerical simulations, we found that the optimized RSA arrangement suppressed the self-interference signi(cid:12)cantly.
Identification of different functional hand grips using a sensor glove: reproducibility in healthy subjects

Measuring arm and hand function in patients is challenging. Current methods mostly rely on the opinion of an examinator at a single moment in a structured clinical setting, or on patient-reported outcome measures. This study investigates the within-subject and between-subject reproducibility of the multi-array signals of a sensor glove (Cynteract, featuring eleven sensors representing relative rotations of ten joints in the hand) during the performance of five manual tasks in healthy participants (n=10). Three isolated tasks involved reaching and grasping a daily object with either a cylinder grip, tripod pinch grip or lateral pinch grip. The other two tasks consisted of compound movements including a cylinder grip or tripod pinch grip. Secondary aims were i) the recognition of the cylinder and tripod pinch grip within the compound movements, and ii) assessment of the mutual distinguishability of the three isolated hand grips. The within-subject reproducibility was very high for all tasks (intraclass correlation coefficients (ICCs) > 0.98), while the between-subject reproducibility had a very broad range (percentage recognized with ICC > 0.80 ranged from 8.1% to 85.7%). The tripod pinch grip was very well recognized in the compound movement (mean ICC 0.9368). However, the cylinder grip was poorly recognized in the compound movement task (mean ICC 0.645). Distinguishability of the three isolated grips was good.