Miracle-dz/UniFAR-FTUs huggingface dataset:
Physicochemical and Functional Modifications of Hemp Protein Concentrate by the Application of Ultrasonication and pH Shifting Treatments

According to the Food and Agriculture Organization (FAO), protein demand is expected to increase globally by around 40% by 2030 as a response to the world’s population growth. Due to their clean label, vegan or vegetarian based applications, nutritional value, and cost-efficient properties, plant-based proteins have been widely studied. However, most of the alternatives currently found in the market have some challenges because of their poor solubility, emulsifying, gelling, and foaming attributes. Hemp seed protein has gained increasing attention due to its unique amino acids and fatty acids profiles. In this study, commercial HPC mixtures were adjusted to pH 2, 4, 6, 8, 10, and 12 followed by ultrasonication (US) for 5 min (5 s on: 5 s off) and incubated for an hour before neutralizing to pH 7. Following the treatments, the samples were analyzed for their hydrodynamic diameter, conductivity, zeta potential, polydispersity index, surface hydrophobicity, solubility, electrophoresis (SDS-PAGE), free sulfhydryl group, and optical characteristics. The samples treated with ultrasound at pH 8 and 10 significantly (p < 0.05) enhanced the solubility of the hemp seed protein by 12.12% and 19.05%, respectively. Similarly, the samples treated with ultrasonication and pH shifting at pH 6, 8, and 10 also significantly increased the amount of free sulfhydryl content (p < 0.05) to 41.6, 58.72, and 46.54 mmol/g from 32.8 mmol/g, respectively. This study shows that the application of ultrasonication and pH shifting is a promising alternative method to modify the functional properties of HPC and widen their applications in the food, cosmetics, and pharmaceutical industries.
Better Fusion of Multi-scale Features for Remote Sensing Object Detection

In recent years, techniques for generating remotely sensed images have been widely developed and remote sensing object detection has received increasing attention. In order to detect as many objects at different scales as possible in high-resolution remote sensing images, existing remote sensing target detection methods tend to use feature pyramid networks to extract features. However, different levels of the feature map contain objects at different scales. As a result, while identifying one predictive result in one feature map as a positive sample, other scale feature maps may treat this one predictive result as background. This can reduce the accuracy of the object detection algorithm. To fuse multi-scale features more effectively, we propose a remote sensing object detection method (MSFF) based on multi-scale feature fusion, which classifies all targets into different scales for location and classification through adaptive pooling. Our method improves the network structure of the feature pyramid network and also recalculates the weights to reduce the semantic gap in feature fusion. Experimental results show that our method has good results. Our proposed method achieves a good result of 75.6% mAP on the DOTA dataset.
The roles of work-integrated learning in achieving critical cross-field outcomes in a hospitality management programme

Work-Integrated Learning (WIL) is a form of Experiential Learning (EL) which implies learning by experience. This article represents the findings of a study regarding the roles of WIL and how such roles can be quantified when measured against the achievement of Critical Cross-Field Outcomes (CCFOs). The study was based on an empirical mixed-method triangulation, which allowed the researchers to use both qualitative and quantitative methods to address the research problem. The sample size is 35, constituting the third and fourth-year groups in the Hospitality Management programme at a higher education institution in South Africa. The results of the quantitative study indicate that the students have identified various roles for WIL whereas the quantitative investigation revealed that students are of the opinion that WIL contributes significantly towards the achievement of CCFOs. WIL therefore contributes to skills development in general and to the attainment of skills and attributes as represented by the CCFOs in particular. Recommendations regarding the implications of the study are made for curriculation purposes as well as for credit values to be attached to WIL.
MoSe2/n‐GaN Heterojunction Induced High Photoconductive Gain for Low‐Noise Broadband Photodetection from Ultraviolet to Near‐Infrared Wavelengths

Heterojunction photodiodes comprising of layered metal chalcogenides and wide‐bandgap semiconductors are a promising candidate for broadband photodetection. In this work, nanolayered Molybdenum diselenide (MoSe2)/Gallium Nitride (GaN) based photodetector has been demonstrated from ultraviolet to near‐infrared range (300–1000 nm). The performance is investigated by conducting Kelvin probe force microscopy to measure the conduction band offset at the interface of the heterojunction. It is used to analyze the energy‐band diagrams to understand the current transport mechanism. The device exhibits a high photoconductive gain of 1.8 × 104, responsivity of 5580 A W−1, detectivity of 1.9 × 1011 Jones and low noise equivalent power of 10 fW Hz−1/2 at 365 nm. Additionally, finite difference time domain simulations are performed for the MoSe2/n‐GaN heterostructure to authenticate the broadband photodetection spectrum. Therefore, the outcomes of this study validate the suitability of MoSe2/n‐GaN heterojunction devices for high responsivity and detectivity applications.
Active object search using a pyramid approach to determine the next-best-view

The development of service robotics continues to arouse interest in the scientific community due to the complexity of the activities performed like interaction in human environments, identifying and manipulating objects, and even learning by themselves. This paper proposed to improve the perception of the environment by searching for objects in service robotics tasks. We present the development and implementation of an active object search method based on three main phases: Firstly, image pyramid segmentation to examine in detail the im- age features. Second step, object detection at each level of the pyramid through a local feature descriptor and a mutual information calculation. Finally, the next camera position selection through analyzing the object detections accumulation in the pyramid. To evaluate the implementation of the proposed method, we use a NAO robot in a familiar place for humans, such as an office or a home. Ordinary objects are part of our database with the premise that a robot must know them before looking for an object. The results in the experiments showed an acceptable performance in simulation and with a real platform.
An Effective Approach for Rumor Detection Based on ERNIE-BiGRU-Attention

For the field of rumor detection, most of the existing common pretraining models are based on deep learning or rule-based methods. These methods select a single topic in the rumor dataset during training, and the corpus of the selected model is difficult to match the data in the fake news detect direction. This paper will use the pretraining model named “ERNIE”(Knowledge Enhance Semantic Representation) developed by Baidu. ERNIE can potentially learn the dependence of knowledge and longer semantic dependence through a unified mask, making the model more generalized, including news-related corpus, which perfectly matches the direction of rumor detection. We take the output of ERNIE as the input of BiGRU, and then take the output of BiGRU as the input of the attention layer, and finally get the classification result. The accuracy of the ERNIE-BiGRU-Attention model reaches 89.40%, the F1 score reaches 0.8837, and the recall value reaches 94.37%. The above values are based on the results of CED-Dataset, which is higher than each index of other models under the same dataset.
Lambl’s Excrescences Associated with Cardioembolic Stroke

Patient: Male, 73-year-old Final Diagnosis: Lambl’s excrescence • stroke Symptoms: Blurring of vision • weakness Medication: — Clinical Procedure: — Specialty: Cardiology • Neurology Objective: Rare disease Background: Lambl’s excrescences (LE) are threadlike fronds that occur along valve closure lines where minor endothelial damage occurs, resulting in thrombus formation. It is often asymptomatic but can result in cerebral embolism and coronary artery obstruction. The criterion standard for diagnosis is transesophageal echocardiography. Case Report: We report an interesting case of a 73-year-old right-handed man presenting with a visual disturbance. An MRI head demonstrated an acute-to-subacute infarct in the right posterior cerebral artery territory involving the posterior right temporal, right occipital lobes, and right thalamus, which was in keeping with embolic stroke. Investigation with transthoracic and transesophageal echocardiography showed echo density on the ventricle surface of the left coronary cusp, which was concerning for Lambl’s excrescences, with no significant arrhythmia on his implantable loop recorder at 3-month follow-up. Therefore, we believe that his stroke was due to embolization from Lambl’s excrescences. Since this was his first episode of stroke, monotherapy with aspirin was continued. Conclusions: Although rare, Lambl’s excrescences should be considered in the differential diagnosis of embolic stroke. However, there is no established guideline for its management. Patients with the first stroke episode can be treated conservatively with antiplatelet therapy. In patients with recurrent ischemic events, anticoagulation should be offered, along with discussion about surgical excision.
Channel Mobility Model of Nano-Node MOSFETs Incorporating Drain-and-Gate Electric Fields

A novel channel mobility model with two-dimensional (2D) aspect is presented covering the effects of source/drain voltage (VDS) and gate voltage (VGS), and incorporating the drift and diffusion current on the surface channel at the nano-node level, at the 28-nm node. The effect of the diffusion current is satisfactory to describe the behavior of the drive current in nano-node MOSFETs under the operations of two-dimensional electrical fields. This breakthrough in the model’s establishment opens up the integrity of long-and-short channel devices. By introducing the variables VDS and VGS, the mixed drift and diffusion current model effectively and meaningfully demonstrates the drive current of MOSFETs under the operation of horizontal, vertical, or 2D electrical fields. When comparing the simulated and experimental consequences, the electrical performance is impressive. The error between the simulation and experiment is less than 0.3%, better than the empirical adjustment required to issue a set of drive current models.
Automation is a 10-Step Competitive Necessity

Incredibly, many executives still believe that the adoption of artificial intelligence (AI) and machine learning (ML) will be relatively slow.1,4 This miscalculation is potentially threatening to a company's very existence. Business models and processes will change radically as AI and ML continue to strengthen. It is a business-technology trend that is undeniable and unstoppable. Predictions about the “The Future of Work” and the “4th Industrial Revolution” reduce AI and ML to a single word: automation. In addition to the other application areas of AI and ML, companies that embrace automation will win; those that do not will lose. The automation arms race has already begun. New business models and countless business processes will be automated to save money and make money—the perfect twin metrics. Lagging here will force an expensive catch-up strategy (where nothing good ever happens).
Challenges of human resource accounting (HRA) in India-An exploratory study

Human resources are the assets of an organization. Human Resource Accounting (HRA) or human resource valuation is used to quantify the investments made in human resource of an enterprise. HRA can quantify the value of an employee. It is not an easy method. This value helps the management in decision making regarding the competency of an employee. The intangible services of the employees may not be touch but it can put as an intangible asset of the organization and it can be shown in the balance sheet.
Optimum Allocation For Multiple Thrusters

In one concept for a Mobile Offshore Base (MOB), the several modules are kept in alignment and properly positioned with respect to one another by the use of many steerable thruster units. The research reported here develops an algorithm using linear programming to rationally allocate commanded thrust and thruster azimuth to multiple thrusters (more than two) in order to best achieve the desired force system on the MOB module. The linear programming approach allows explicit consideration of many of the real-world characteristics of the thrusters, including maximum thrust capability, maximum slew rate of the thrusters, etc. The algorithm was programmed and the results of the optimum allocation for two different scenarios are presented.
Multichannel Audio Processing Using a Unified-Domain Representation

The unified-domain representation for synchronized multichannel audio streams is introduced. This lossless and invertible transformation describes multiple streams of audio as a single-frequency-domain magnitude component multiplied by a complex matrix encoding the spatial and phase relationship information for each channel. Unified-domain analysis and signal-processing techniques for applications such as high-resolution frequency analysis, sound source separation, spatial psychoacoustic models, and low-bit-rate audio coding are presented.
In Vitro Antileishmanial and Antitrypanosomal Activities of Plicataloside Isolated from the Leaf Latex of Aloe rugosifolia Gilbert & Sebsebe (Asphodelaceae)

Trypanosomiasis and leishmaniasis are among the major neglected diseases that affect poor people, mainly in developing countries. In Ethiopia, the latex of Aloe rugosifolia Gilbert & Sebsebe is traditionally used for the treatment of protozoal diseases, among others. In this study, the in vitro antitrypanosomal activity of the leaf latex of A. rugosifolia was evaluated against Trypanosoma congolense field isolate using in vitro motility and in vivo infectivity tests. The latex was also tested against the promastigotes of Leishmania aethiopica and L. donovani clinical isolates using alamar blue assay. Preparative thin-layer chromatography of the latex afforded a naphthalene derivative identified as plicataloside (2,8-O,O-di-(β-D-glucopyranosyl)-1,2,8-trihydroxy-3-methyl-naphthalene) by means of spectroscopic techniques (HRESI-MS, 1H, 13C-NMR). Results of the study demonstrated that at 4.0 mg/mL concentration plicataloside arrested mobility of trypanosomes within 30 min of incubation period. Furthermore, plicataloside completely eliminated subsequent infectivity in mice for 30 days at concentrations of 4.0 and 2.0 mg/mL. Plicataloside also displayed antileishmanial activity against the promastigotes of L. aethopica and L. donovani with IC50 values 14.22 ± 0.41 µg/mL (27.66 ± 0.80 µM) and 18.86 ± 0.03 µg/mL (36.69 ± 0.06 µM), respectively. Thus, plicataloside may be used as a scaffold for the development of novel drugs effective against trypanosomiasis and leishmaniasis.
Zonal Distribution Characteristics of Microplastics in the Southern Indian Ocean and the Influence of Ocean Current

As a new type of pollutant, microplastics widely exist in the marine environment and have attracted a lot of attention from the international community. In order to study the distribution of microplastics and the influence of ocean current, microplastic samples in seawater of the southern Indian Ocean were collected using a peristaltic pump equipped on-board and concentrated on site. Qualitative and quantitative analyses of microplastics were performed using a stereo-microscope and a micro-Fourier transform infrared spectroscope attenuated total reflection. The results showed that the average abundance of microplastics in seawater of the southern Indian Ocean was 2.3 ± 2.1 items/m3, which was consistent with that in other oceans. Polyethylene terephthalate (PET), polyethylene (PE), Rayon, polyamide (PA), and polyvinylidene chloride (PVDC) were the main polymers of microplastics in the southern Indian Ocean. The size range of all detected microplastics was 108.2–4703.0 µm. All microplastics had different colors, such as black, red, yellow, gray, blue, green, purple, and transparent. Fiber was the dominant shape of microplastics. The abundance distribution of microplastics fluctuated in the latitudinal direction. The abundance of microplastics from the present study area was higher in the coastal region of the South Africa continent and the Indian Ocean garbage patch, with an average abundance of 4.0 items/m3. The average abundance of microplastics was relatively high in the convergence area of the circulation, which revealed that the ocean current facilitated the agglomeration and transportation of microplastics.
Development in polymerization shrinkage control of dental light-cured resin composites: a literature review

Abstract Dental light-cured composite resin has been widely used in dental applications because of its easy operation and excellent biocompatibility to achieve the ideal aesthetic outcomes. However, the volume shrinkage generated during the curing process can cause microleakage, hypersensitivity, de-bonding, and fracture of materials or cusps, which would affect treatment efficacy and ultimately reduce the service life of the restoration. Several studies have figured out the mechanism of polymerization shrinkage of light-curable composite resins. Therefore, some strategies have been proposed to control the impact of polymerization shrinkage. This review summarizes the adverse effects, measurement, and mechanism of polymerization shrinkage in light-cured composite resin. It also reviews the studies on development in polymerization shrinkage control strategies in terms of modification of resin matrix, modification of filler, light mode, appropriate filling method and adhesive, and suitable oral temperature and humidity.
Coupled Poroelastic Modeling of Hydraulic Fracturing‐Induced Seismicity: Implications for Understanding the Post Shut‐In ML 2.9 Earthquake at the Preston New Road, UK

Post‐injection seismicity associated with hydraulic stimulation has posed great challenges to hydraulic fracturing operations. This work aims to identify the causal mechanism of the post shut‐in ML 2.9 earthquake in August 2019 at the Preston New Road, UK, amongst three plausible mechanisms, that is, the post shut‐in pore pressure diffusion, poroelastic stressing on a non‐overpressurized fault, and poroelastic stressing on an overpressurized fault. A 3D fully coupled poroelastic model that considers the poroelastic solid deformation, fluid flow in both porous rocks and fracture structures, and hydrofracturing‐induced pressure perturbations was developed to simulate the hydromechanical response of the shale reservoir formation to hydraulic fracturing operations at the site. Based on the model results, Coulomb stress changes and seismicity rate were further evaluated on the PNR‐2 fault responsible for the earthquake. Model results have shown that increased pore pressure plays a dominant role in triggering the fault slippage, although the poroelastic stress may have acted to promote the slippage. Amongst the three plausible mechanisms, the post shut‐in pore pressure diffusion is the most favored in terms of Coulomb stress change, seismicity rate, timing of fault slippage and rupture area. The coupled modeling results suggested that the occurrence of the post shut‐in ML 2.9 earthquake was a three‐staged process, involving first propagation of fracture tips that stimulated surrounding reservoir formations, then hydraulic connection with and subsequent pore pressure diffusion to the conductive PNR‐2 fault, and eventually fault activation primarily under the direct impact of increased pore pressure.
Molecular tools for the diagnosis of periodontitis

Periodontitis is a multifactorial chronic inflammatory disease associated with dysbiotic biofilms and aberrant host inflammatory response. It is characterized by destruction of the tissues that support the teeth. Periodontitis is the major cause of tooth loss in adults significantly affecting the quality of life and is associated with many chronic non communicable diseases by contributing to systemic inflammatory burden. Early and accurate diagnosis is the key to the successful management of periodontitis as the entire treatment plan, prognosis, and maintenance directly depend on the quality of periodontal diagnosis. Traditionally the diagnosis of Periodontitis is based on recording medical and dental history, periodontal examination and radiographic findings. The current periodontal diagnostic process reveals only historical tissue destruction and does not provide any information regarding current disease activity, future progression or for monitoring response to therapy. For these reasons, new molecular diagnostic aids are being developed that allow an early detection of disease, determine the presence of current disease activity, predict sites at risk for future breakdown and monitor the response to periodontal therapy. Advanced molecular diagnostic techniques are a class of diagnostic tests that are used to detect and measure nucleic acids, proteins or metabolites in clinical samples to identify risk factors, screen asymptomatic patients, provide more accurate diagnosis and guide the process of development of an ideal therapeutic intervention. This paper provides a review of the molecular diagnostic tools that have the potential to be utilized for diagnosis and management of periodontitis.
Key parameters controlling surface quality and dimensional accuracy: a critical review of FFF process

ABSTRACT Fused filament fabrication (FFF) is an additive manufacturing process, which constructs physical items by fused melt material, selectively deposited layer-by-layer through a heated extrusion mechanism. Parameters’ selection and control in FFF are of utmost importance since they significantly affect the surface quality (SQ) and dimensional accuracy (DA) of the FFF printed parts. In the present paper, initially, the FFF process is briefly presented. Next, a cause-and-effect diagram exhibits the process parameters’ categorization with the SQ and DA of the manufactured parts. Then, according to the robust design theory, the process parameters are divided into three classes, i.e., the signal, the control, and the noise. This classification supports the selection of appropriate FFF printers, according to the control parameters, whereas it facilitates the optimization of the SQ and DA of printed parts, concerning the signal parameters. Finally, the impact of each parameter on SQ and DA is presented, supported by an extensive literature review. Overall, the process parameters’ optimization is critical for the SQ and DA. Therefore, they should be adjusted to achieve higher quality and less post-processing work.