Miracle-dz/UniFAR-FTUs huggingface dataset:
Carob (Ceratonia siliqua) as Functional Feed Is Beneficial in Yellow Mealworm (Tenebrio molitor) Rearing: Evidence from Growth, Antioxidant Status and Cellular Responses

In terms of sustainability and circular economy, agricultural by-products may be efficiently reused in insects’ rearing for high-quality protein sources in human diet and animal feeds. The present study aimed to explore whether the utilization of carob pods as feeding substrate may beneficially affect Tenebrio molitor’s growth, nutritional value, antioxidant status and cellular responses. Increasing levels of milled whole carob pods (0, 25, 50, 75, 100%) were used as alternative wheat bran (control) substrates for yellow mealworm rearing, while growth performance, proximate composition, total phenolic content, antioxidant enzyme activity and the expression of stress- and apoptotic-related proteins were evaluated in larvae. The results showed that carob pods’ content up to 75% did not significantly differentiate larvae weight, development time and total dry matter. Larvae total phenolic content and antioxidant activity exhibited a significant increase at 75% content. Although the antioxidant enzymes’ activity decreased at both 25 and 50% levels, higher carob content levels (75 and 100%) resulted in no significant changes compared to the control. Carob pods led to decreased apoptotic indicators and the low expression of most stress-related proteins compared to the control. The present findings demonstrate that carob pods and their antioxidant properties exert beneficial effects on T. molitor’s rearing and nutritional status, although 100% carob content may impact adversely the larvae due to the high amounts of carob tannins.
Excitation of spin waves by spin polarized current

Numerical and analytical analysis is used to explain recently observed experimental phenomenon - excitation of spin waves in spin valves due to the applied spin polarized current. Excited spin waves are being identified and Lyapunov stability analysis is being used to identify different regions of stability depending on the value of the applied current.
Different helicity dependency of all-optical magnetization switching in GdFeCo films with optical interference layer

We observed helicity-dependent all-optical magnetization switching (HD-AOS) phenomena in GdFeCo films, which have equivalent magnetic properties but different optical properties due to optical interference layer thickness. Consequently, we found that these films have different properties of HD-AOS with the duality relation between magnetization direction and light helicity in light absorption, which generally means magnetic circular dichroism (MCD). Therefore, we also evaluated the effective absorption of the same GdFeCo samples which have similar intrinsic MCD by CW laser and intense femtosecond laser pulses. We confirmed that the contribution of this duality relation is much smaller in the absolute value of absorption. Furthermore, the magnitude and the sign of the duality relation change by the interference layer’s thickness. As a result, we concluded that the duality relation in HD-AOS is derived from the duality relation in absorption. Furthermore, its duality relation can be changed effectively using multiple interference effects.
Development and Evaluation of Amlodipine-Polymer Nanocomposites Using Response Surface Methodology

Introduction. Polymer nanoparticles are a key tool to deliver drugs to specific sites and to increase drug bioavailability. Aim. This research aims to use poly amide-disulfide nanoparticles as drug delivery systems. Method. Amlodipine (Amlop) was used as a model, forming Amlop-polymer nanocomposites. In this work, we investigated the effect of independent variables (polymer, Fe3+, Al3+, and pH) on the dependent variables (loading efficiency (%LE), zeta potential, and particle size). Nanocomposites were prepared by an inotropic method. Nanocomposites were characterized by powder X-ray diffraction (PXRD), field emission scanning electron microscopy (FE-SEM), Fourier transform infrared spectroscopy (FTIR), and a release study. Results. From the XRD data, the Amlop-polymer nanocomposite shows semi crystallinity. In addition, the disappearance of drug peaks indicates that the drug was incorporated between the polymer molecules and was amorphous in behavior. The FTIR for the nanocomposite shows the functional group of the drug, which indicates the incorporation of Amlop into the nanocomposite. From FE-SEM, the results showed that our nanocomposites have an average particle size of approximately 130 nm. The release of amlodipine from the Amlop-polymer nanocomposite was found to be controlled, with approximately 85% within approximately 24 hours. Conclusion. The amide-disulfide polymer nanoparticles are promising carriers for different types of drugs.
A Novel Strategy Dealing with Producing Period in Low Pressure Gas Wells

Low-pressure gas wells are of increasing interest to the petroleum industry as economic and environmental importance of natural gas continues to grow. To maximize the production of low permeability gas reservoir, a novel production strategy to determine reasonable producing periods, including the pressure draw down process and the pressure build up process, in low pressure gas wells has been investigated. Additionally, the variation of down-hole pressure and gas flow in both processes were considered to formulate the optimization model to find reasonable switching times for low-pressure gas wells in this research. In order to enhance the adaptability of the production strategy proposed in this research, parameters of erosion flow rate, critical flow rate of liquid loading and reasonable differential producing pressure of the reservoirs were considered in the proposed mathematical model which aims at maximizing gas production of low-pressure gas wells. Based on the application of the mathematical model dealing with reasonable production strategy of low-pressure gas wells, the pressure of gas well varies smoothly in both shut-in process and gas production process when the novel production strategy was applied. And nature gas production of the gas well increases dramatically compared with that before.
Functional and Healthy Yogurts Fortified with Probiotics and Fruit Peel Powders

The application of processing waste by-products along with probiotics is an interesting choice to confer potential functional aspects to food products. This study was designed to investigate the nutritional capacity of freeze-dried mango peel powder (MPP) and banana peel powder (BPP) in the presence of a mixture of three probiotic species (1% of each of three probiotics (Lacticaseibacillus casei (431®), Lacticaseibacillus rhamnosus (LGG®) and Bifidobacterium subsp. Lactis (Bb-12®)) as sources of additional nutrients and prebiotics in fresh and rehydrated freeze-dried (RFD) yogurts for 28 days of refrigerated storage. The net count of probiotics in yogurt fortified with MPP and BPP increased by at least 1 log CFU/g after 4 weeks of refrigerated storage. Adding fruit peel powder (FPP) significantly (p < 0.05) increased fat, ash, and protein contents in both fresh and RFD yogurts in comparison with the control yogurt. Similarly, the total phenolic contents (TPC) and antioxidant activity (AOA) was enhanced significantly (p < 0.05). The TPC reached 2.27 ± 0.18 and 2.73 ± 0.11 mg GAE/g in RFD enriched with BPP and MPP compared to a TPC of 0.31 ± 0.07 mg GAE/g in the control. Additionally, yogurt samples enriched with BPP (Y-5) and MPP (Y-6) demonstrated 12% more sugar contents than non-fortified yogurts (Y-1). Higher titratable acidity and lower pH values were also recorded in the RFD yogurt. Significant differences (p < 0.05) in the color parameters were detected in both fresh and RFD yogurts with reduced brightness (L*) and increased redness (a*) of the product. These findings demonstrated the suitability of MPP and BPP in yogurt formulations to optimize the advantages of such synbiotic products with higher availability of phenolic compounds.
Real-time 3D imaging using 2D curved array

A real-time volumetric imaging system using a curved 2-D array is presented, in which a small subaperture moves across the array surface to scan a volume of interest. The 2-D curved array designed for this purpose consists of 90/spl times/46 elements with an element pith of 1.5 /spl lambda/ and has the same view angles along both lateral and elevation directions as those of a commercial mechanical 1-D array for 3-D imaging. To obtain a required image quality with a small number of active channels, the four corners of the transmit and receive subapertures are tapered. In addition, the receive subaperture consists of sparsely distributed elements, and fold-over array scheme is adopted in transmit. Computer simulation results show that by using all these methods combined, the image resolution of a fully sampled 64/spl times/32 subaperture can be obtained using only 256 channels in both transmit and receive with slightly degraded resolution, which is much superior to that of 3-D imaging with a mechanical 1-D array.
Spectral Image-Based Multiday Surface Electromyography Classification of Hand Motions Using CNN for Human–Computer Interaction

Physiological signals such as electromyography (EMG) have been used in human–computer interaction (HCI) for medical applications. Wearable prostheses, such as robotic limbs, have seen a surge in popularity because of technological advancements in myoelectric interfaces. In spite of encouraging achievements with pattern-recognition-based control systems, user acceptability of prosthetic hands still needs improvement in control robustness. The purpose of this research is to compare multiday surface EMG (sEMG) recordings and measure the performance of convolutional neural network (CNN) to enhance myoelectric control. The performance metrics used in this study are accuracy, macro weighted precision (MWP), macro weighted recall (MWR), and macro ${F}1$ -score for eight able-bodied (healthy and nondisabled) and four amputee subjects. Using Mel-spectrogram-based sEMG data from both the able-bodied (healthy and nondisabled) and amputee participants, our proposed CNN has achieved a mean classification accuracy of 99.42% ± 0.42% and 98.00% ± 0.58% for the able-bodied (healthy and nondisabled) and amputee subjects for the within-day analysis, respectively. The proposed CNN outperformed other classifiers ( ${p} \leq0.05$ ) in the between-day analysis for twofold (65.88% ± 10.1% and 58.37% ± 9.11%) and for sevenfold validation (88.73% ± 1.43% and 77.35% ± 2.72%) using sEMG recordings from the able-bodied (healthy and nondisabled) and amputee subjects, respectively. The proposed CNN is compared with the pretrained transfer learning (TL) models and has achieved higher accuracy with lower computational cost. The results demonstrate that CNN can considerably increase the effectiveness of the pattern recognition myoelectric control schemes and can extract deep information from EMG data.
Natural products repurposing of the H5N1-based lead compounds for the most fit inhibitors against 3C-like protease of SARS-CoV-2

Context: COVID-19 pandemic has caused more than 2.7 million mortality worldwide. Although the COVID-19 vaccine has been developed, the amount is still limited, and very few countries have reached ‘herd immunity’ level. In this regard, imported and community infections is still happening in the world. In order to complement the vaccine rollout, the drug is still necessary. Up to now, all the COVID-19 drugs in the market are still in emergency use, and their clinical application is still under tight surveillance. Thus, a breakthrough in drug development is necessary. Based on an extensive protein crystallography experiment, it is known that the 3C-like protease of SARS-CoV-2 plays an important role in the pathogenicity of the virus. Several inhibitors have been developed for this protein, including remdesivir that served as the standard in this experiment. However, recent findings in the wet lab also showed possible significant bioactivities for the repurposed influenza, and human rhinovirus leads for SARS-CoV-2. Previous research has developed flavonoid-based leads as H5N1 virus inhibitors. Aims: To develop lead compounds to inhibit 3C-like protease of SARS-CoV-2 from the existing H5N1 leads. Methods: The ligands and protein were prepared with energy minimization and the “add protonation” procedure. Then, the QSAR analysis was conducted to determine whether the ligands fit as leads for the 3C-like protease SARS-CoV-2 inhibitor. Molecular docking simulation was deployed for the selected ligand toward the 3C-like protease enzyme. Moreover, the molecular dynamics simulation was devised to examine the protein flexibility of the protease ligands. Results: It was found that only 9 out of the 19 repurposed H5N1-leads elicited significant QSAR-based properties for general antivirus, influenza antivirus, and antihuman rhinovirus bioactivities. In this regard, the leads were screened further with molecular docking, in silico ADME-TOX prediction, and molecular dynamics methods. Based on the further screen, the ligands of M00009235 and M00006834 were selected as lead compounds for 3C-like protease SARS-CoV-2 inhibitors. Conclusions: The ligands of M00009235 and M00006834 were selected as the best leads for inhibiting 3C-like protease of SARS-CoV-2 based on the virtual screening methods.
Identification of evasive manoeuvres in traffic interactions and conflicts

The study presents a simple and easy to implement method for detection of the evasive action start in traffic interactions. The method is based on comparison of the studied trajectory with a reference set of ‘unhindered’ trajectories, interpreting the start of evasive action as the moment when no more similarities can be found. The suggested algorithm performs well for primary interactions when road users arrive in an unhindered state. It fails, however, in case of secondary interactions. Explorative application of the method on a large dataset of normal and conflict traffic situations concludes that traffic conflicts occur more frequently in secondary interactions, presumably due to higher cognitive load on the involved road users. Despite the limitations, the method can be used both for the safety studies based on traffic conflicts and for more general quantification and visualisation of the road user behaviour.
Muzzle flash localization for the dismounted soldier

The ability to accurately and rapidly know the precise location of enemy fire would be a substantial capability enhancement to the dismounted soldier. Acoustic gun-shot detections systems can provide an approximate bearing but it is desired to precisely know the location (direction and range) of enemy fire; for example to know from ‘which window’ the fire is coming from. Funded by the UK MOD (via Roke Manor Research) QinetiQ is developing an imaging solution built around an InGaAs camera. This paper presents work that QinetiQ has undertaken on the Muzzle Flash Locator system. Key technical challenges that have been overcome are explained and discussed in this paper. They include; the design of the optical sensor and processing hardware to meet low size, weight and power requirements; the algorithm approach required to maintain sensitivity whilst rejecting false alarms from sources such as close passing insects and sun glint from scene objects; and operation on the move. This work shows that such a sensor can provide sufficient sensitivity to detect muzzle flash events to militarily significant ranges and that such a system can be combined with an acoustic gunshot detection system to minimize the false alarm rate. The muzzle flash sensor developed in this work operates in real-time and has a field of view of approximately 29° (horizontal) by 12° (vertical) with a pixel resolution of 0.13°. The work has demonstrated that extension to a sensor with realistic angular rotation rate is feasible.
Toward Decreasing the Driving Risk: Speech-Based Driver’s Anger Regulation in Smart Cockpit

With the advent of intelligent connected vehicles, vehicles have gradually changed from traditional means of transportation to emotional third-party mobile space. However, driving anger has also become a severe problem in our daily life. As a medium of expression of information and emotion, speech plays a crucial role in the human-computer interaction of intelligent cockpits. Research shows that speech can regulate drivers’ anger and improve driving performance, which provides ways to control driving anger. This paper investigated the regulation quality of different speech types on driving anger. Thirty participants completed the driving simulator task as required to collect data. We analyzed the regulation effects of personalized speech and synthesized speech from the drivers’ subjective experience and driving behavior. This study found that personalized speech exhibited a more significant regulation effect than synthesized speech. Personalized speech can better control the expression of angry behavior and reduce the driving risk. The findings provide practical guidance for designing in-vehicle speech interactions for driving anger intervention.
Semi-inversion method for generalized cylindrical microwave structures

An efficient numerical analysis method is developed for calculating cylindrical structures of arbitrary cross section, which is based on an inversion of the principal singular part of the operator equation. The basis functions which are the eingenfunctions of the operator of the boundary-value problem of the diffraction of electromagnetic waves at a circular cylinder are used to do this in the Galerkin method. The method is used to calculate the inhomogeneities in a waveguide, waveguides and strip lines with a complex cross section
Space Node Topology Optimization Design Considering Anisotropy of Additive Manufacturing

At present, a large number of scholars have conducted related research on topology optimization for additive manufacturing (AM). However, there are few relevant research reports on the impact of different directions of additive manufacturing on the optimal design and manufacturing results. In this paper, using the bidirectional evolutionary optimization (BESO) method, anisotropic optimization analysis was carried out on space nodes that are currently popular in the field of additive manufacturing and topology optimization. The elastic constants in different directions were used as anisotropic material properties for optimization research in this paper through tensile testing, which was carried out on 316L stainless-steel specimens fabricated using Selective Laser Melting (SLM) technology. In addition, SEM analyses were performed to explore the microscopic appearance of the material. The study found that additive manufacturing is affected by the printing direction in terms of both macroscopic mechanical properties and microscopic material structure; the deformation obtained by anisotropic optimization was about 1.1–2.3% smaller than that obtained by isotropic optimization.
Deep Reinforcement Learning for Reactive Content Caching With Predicted Content Popularity in Three-Tier Wireless Networks

With the explosive growth of micro-video applications, the mobile traffic generated by retrieving a few user-generated micro-videos has brought a massive burden to backhaul links and backbone networks. Unlike other types of videos, user-generated micro-videos are typically requested by a large number of users within an extremely short period after their release. Therefore, it is crucial to predict the content popularity and make caching decision for the newly requested content timely. To predict content popularity in different locations, the request probabilities of the content in different locations are translated into rating scores. Then, a recommendation system-based prediction model is designed to predict rating scores of the newly requested content in different locations. To increase caching diversity and realize vertically collaboration in a three-tier wireless network, a deep reinforcement learning-based reactive content caching strategy is proposed to make caching decision for the newly requested content. The main goal is to obtain a higher caching gain at a lower caching space cost. To evaluate the caching performance, a new metric, cache benefit rate, is defined as the download latency reduction brought by each bit of cache. Compared with matrix factorization, the performance of prediction model can be increased by 23.98% and 12.44% in terms of mean absolute error and root mean square error, respectively. Extensive simulations demonstrate that the proposed reactive caching strategy outperforms other caching strategies under different system parameters in terms of the cache hit rate, average download time, and cache benefit rate.
Exploring the Characteristics and Functions of Nonsuicidal Self-Injury in Patients with Severe Personality Disorders

Nonsuicidal Self-Injury (NSSI) is a major public health problem. The present study covered three aspects of this behavior in an outpatient population with severe personality disorders. First, we compared a group that engaged in NSSI to a control group that did not. Second, we looked at the characteristics of the behavior. Third, we explored what the patients think are the reasons for NSSI. 50 (41%) of 121 patients had experienced NSSI during the seven-month data collection period. We found that the NSSI most often occurred in the evening (60%) and while being alone (82%). The most common forms of NSSI were the use of bodily force in some form (48%), followed by cutting (28%) and burning (10%). As triggers for NSSI, patients mentioned interaction with others and rising tension. Patients identified with both the ’distraction hypothesis’ and the ’self-punishment hypothesis’ as reasons for NSSI. They reported feeling less nervous and more relieved after NSSI, but also felt guilt about it. Although further research is necessary and the current findings should be interpreted with caution, weconclude based on our findings that it might be helpful for patients with severe personality disorders to be askedby their caregivers on a regular basis whether they use/ have used NSSI. We furthermore recommend consideringmaking an adequate crisis prevention plan with the patients who engage in NSSI.