The NW-SE trending dextral strike-slip faults on the north side of the Tian Shan play an important role in accommodating the crustal shortening, which mainly includes the Karatau fault, Talas-Fergana fault, Dzhalair-Naiman fault, Aktas fault, Dzhungarian fault (also named Bolokenu-Aqikekuduk fault) and Chingiz fault. The classic viewpoint is that the strike-slip fault is the adjustment product caused by the difference of the crustal shortening from west to east. Another viewpoint attributes the dextral strike-slip fault to large-scale sinistral shearing. The Alakol Lake Fault is situated along the northern margin of the Dzhungarian Gate, stretching for roughly 150 km from Lake Ebinur to Lake Alakol. Our team utilized aerial photographs, Satellite Stereo-imagery, and field observation to map the distribution of the Alakol Lake fault. Our findings provided evidence supporting the assertion that the fault is a dextral strike-slip fault. In reference to its spatial distribution, Lake Alakol is situated in a pull-apart basin that lies between two major dextral strike-slip fault lines: the Chingiz and Dzhungarian faults. The Alakol Lake Fault serves as a connecting point for these two faults, resulting in the formation of a mega NW-SE dextral strike-slip fault zone. According to our analysis of the dating samples taken from the alluvial fan, as well as our measurement of the displacement of the riser and gully, it appears that the Alakol Lake fault has a dextral strike-slip rate of 0.8-1.5mm/yr. The strike-slip rate of the Alakol Lake fault is comparatively higher than that of the Chingiz fault in the northern region (~0.7 mm/yr), but slower than that of the Dzhungarian fault in the southern (3.2-5 mm/yr). The Chingiz-Alakol-Dzhungarian fault zone shows a gradual decrease in deformation towards the interior of the Kazakhstan platform. We contend that the rate of deformation observed is better explained by the crustal shortening adjustment model, rather than the large-scale sinistral shearing model.

The availability of multi-rotor UAVs with lifting capacities of several kilograms, allows for a new paradigm in atmospheric measurement techniques, i.e. the integration of research-grade sonic anemometers for airborne turbulence measurements. With their ability to hover and move very slowly, this approach yields an unrevealed flexibility compared to mast-based sonic anemometers, for a wide range of boundary layer investigations that require an accurate characterization of the turbulent flow. For an optimized sensor placement, potential disturbances by the propeller-induced flow (PIF), as well as the potential impact of the sensor weight and angular momentum on the flight performance in the case of a boom-mounted sensor, have to be considered.

This research focuses on the development of an automated medication delivery system using Unmanned Aerial Vehicle (UAV) Technology and the Internet of Things (IoT) to support telemedicine and community welfare in the KLU region. The system is designed to improve the quality of medical services and medication management for the community in the area. One of the main challenges faced is how the KLU community responds and accepts automatic medication delivery using UAVs and IoT. To overcome this challenge, this research suggests providing education and training to the community about the benefits and usage of the system, as well as displaying a working simulation of the system to the community.

It is a challenging and meaningful task to carry out drone-based livestock monitoring in high-altitude and cold regions. The purpose of AI is to execute automated tasks and to solve practical problems in actual applications by combining the software technology with the hardware carrier to create integrated advanced devices. Only in this way, the maximum value of AI could be realized. In this paper, a real-time tracking system with dynamic target tracking ability is proposed. It is developed based on the tracking-by-detection architecture using YOLOv7 and DeepSORT algorithms for target detection and tracking, respectively. To address the existing problems of the DeepSORT algorithm, the following two optimizations are made: (1) Optical flow is used to compensate the Kalman filter for improvement of the prediction accuracy; (2) A low-confidence trajectory filtering method is adopted to reduce the influence of unreliable detection on target tracking. In addition, an visual servo controller for the UAV is designed to enable the automated tracking task. Finally, the system is tested using the Tibetan yaks living in the Tibetan Plateau as the tracking targets, and the results reveal the real-time multiple tracking ability and the ideal visual servo effect of the proposed system.

This manuscript reviews two decades of projects funded by the Kirkhouse Trust (KT), a charity registered in the UK. KT was established to improve the productivity of legume crops important in African countries and in India. KT’s requirements for support are: 1) the research must be done by national scientists in their home institution, either a publicly funded agricultural research institute or a university; 2) the projects need to include a molecular biology component, which to date has mostly comprised the use of molecular markers for the selection of one or more target traits in a crop improvement programme; 3) the projects funded are included in consortia, to foster the creation of scientific communities and the sharing of knowledge and breeding resources. This account relates to the key achievements and challenges, reflects on the lessons learned and outlines future research priorities.

"Enhancing the Efficiency of Natural Gas Liquid (NGL) Extraction and Fractionation Trains: An Integrated Approach of Simulation Analysis, Advanced Modifications, and Technological Advancements. Through comprehensive research, innovative solutions such as the heat pump aided distillation (HPAD) system and self-heat recuperation technology (SHRT) have been developed to significantly reduce the energy consumption associated with conventional distillation systems. To identify a practical system for NGL fractionation trains, this study extensively examined and compared various HPAD and SHRT options to retrofit a single column. The objective was to find the most suitable and efficient solution for the fractionation process of natural gas liquids (NGLs). The retrofit options analyzed in this study encompassed a range of techniques, including vapor compression (VC), mechanical vapor re-compression (MVR), thermal vapor re-compression (TVR), bottom flashing (BF), side heat exchanger (SHE), intermediate heating and cooling (IHC), self-heat recuperative (SHR), and modified self-heat recuperative (MSHR) distillation. These methods were carefully examined to determine their suitability and effectiveness in improving the performance of NGL fractionation trains In this study, a depropanizer column, typically employed in conventional NGL plants, was selected as a case study. The simulation software Aspen HYSYS V7.3 was employed to model and analyze eight retrofit designs based on predefined criteria. The simulation data was carefully evaluated to identify the most efficient design for minimizing energy consumption. Among the retrofit options, the mechanical vapor re-compression (MVR) technique demonstrated the most significant energy cost reduction, with a remarkable 68.11 percent improvement compared to the base case conventional column. These findings highlight the potential of MVR as an effective solution for lowering energy costs in NGL fractionation trainsFollowing the MVR retrofit option, the study found that vapor compression (VC) achieved a considerable energy cost reduction of 66.65 percent, closely followed by modified self-heat recuperative (MSHR) at 64.02 percent, bottom flashing (BF) at 62.88 percent, self-heat recuperative (SHR) at 55.85 percent, side heat exchanger (SHE) at 54.23 percent, intermediate heating and cooling (IHC) at 39.54 percent, and thermal vapor re-compression (TVR) also at 39.54 percent. These findings highlight the significant potential for energy savings offered by these retrofit options, with VC being the most popular choice, closely followed by MSHR, BF, SHR, SHE, IHC, and TVR.

Wild strawberry (Fragaria vesca L.) leaves possess diverse antioxidant properties, mainly due to the different classes of phenolics. In this study, microwave-assisted extraction (MAE) and accelerated solvent extraction (ASE) of wild strawberry phenolics were carried out to understand the impact of extraction temperature, extraction time and solvent-to-sample ratio (SSR) on the quantitative and qualitative properties of the obtained extracts. The highest total phenolic content (8027 mg GA/100 g DW), as well the highest DPPH• antiradical activity (903 mol TE/g DW) was obtained with ASE at 150 °C, static time 5 min and SSR of 40:1; while the highest ABTS•+ antiradical activity (681 mol TE/g DW,) and FRAP (2389 mol TE/g DW) was obtained with MAE after 5 min at 80 °C and a SSR of 40:1. The correlation analysis showed that phenolics largely contributed to the antioxidant properties of the studied MAE extracts, while correlation was not found in ASE extracts. A total of 54 different phenolics were identified by UPLC/MS-MS in MAE and ASE extracts obtained at optimal extraction conditions. MAE extract was shown to have a higher content of phenolic acids (40%), but lower content of proanthocyanidins (88%), flavonols (29%), flavan-3-ols (50%) and flavones (39%) than ASE extract.

Recent digital transformations have significantly impacted the current society, economy, and culture. This includes adoption of rapidly emerging technologies, such as artificial intelligence (AI), immersive technology (e.g., virtual, augmented, mixed and extended reality (VR/AR/MR/XR)), cloud services, and internet of things, in our day-to-day life. `Metaverse’ has emerged as a technology that incorporates many of these transforming technologies to deliver personalised immersive experience related to specific application areas. A potential major beneficiary of Metaverse is the educational ecosystem, where highly immersive learning experiences can be delivered to students, catering to their personal learning needs and train them on life skills such as empathy, ethical qualities, and communication skills. The present-day Metaverse allows physical engagement, enabling users to utilise limb movements to interact with the presented materials. However, ethical concerns and technical limitations impede the widespread implementation of the Metaverse in the real-world. This paper provides a comprehensive survey of the existing literature covering the architecture, type and components of Metaverse, followed by practical aspects of metaverse implementation. The paper is concluded by discussing on the open challenges and issues along with their mitigation strategies and future research directions after the detailed usecase of Metaverse in Education.

Obesity represents a worldwide epidemic disorder, increasing the overall morbidity and mortality rate. In this study we investigated the impact of obesity on peri-operative and long-term functional outcomes of Robotic assisted simple prostatectomy (RASP). Baseline flowmetry parameters and validated questionnaires’ scores were prospectively recorded. Follow-up assessments included Flowmetry and validated questionnaires. Composite outcomes (Trifecta) was defined as combination of: post-operative Q-max>15 ml/sec, IPSS score<8 and absence of complications. Pentafecta included also post-operative ejaculation persistence (MSHQ score>0) and the Erectile function maintenance (∆IEEF<6). Data were stratified by BMI (<30 or ≥30). 81 patients underwent RASP in our Institution. Baseline demographics and clinical features, questionnaires score and baseline flowmetry results were comparable between obese and non-obese cohorts. At follow-up, obese patients reported lower subjective improvement in IPSS (p=0.02) and OABQ scores (p<0.001) and higher incidence of stress incontinence requiring Duloxetin (p<0.001). Flowmetry outcomes, were also worse in this cohort (p=0.02 and p=0.03, respectively). At comprehensive outcomes assessment, obese patients had comparable Trifecta (67% vs 54%, p=0.39) and pentafecta achievement rate (p=0.76). Our prelimirary results proved that obesity is associated with worse functional outcomes (storage LUTS and incontinence rate) after RASP, but doesn’t affect trifecta and pentafecta achievement rate.

Reductive amination is a powerful tool in sustainable organic synthesis that allows chemists to access a wide range of valuable amine products using renewable feedstocks, mild reaction con-ditions, and with minimal waste generation. Practical applications can be found in various fields, including pharmaceuticals, contributing to greener and more sustainable chemical processes. In this work we present a heterogeneous (Rh and Pt) catalysed protocol for the fast and efficient synthesis of ractopamine hydrochloride (-adrenergic drug) under MW-assisted reductive ami-nation protocol starting from raspberry ketone and octapamine. Microwave (MW) successfully accelerated the hydrogenation reaction and reduced the reaction time from 13 hours to only 3 hours under mild conditions (50°C at 10 bar). The best catalysts were Pt/C and Rh/C, which led to high conversion and selectivity towards ractopamine:HCl. The solvent has a significant effect on the reaction outcome. The replacement of methanol with other solvents had a negative impact on the reaction yield. We also replaced the raspberry ketone with other ketone substrates, especially cyclohexanone. These preliminary experiments may be useful for further process improvements in the synthesis of β-adrenergic agonists and related structures.

The global prevalence of insulin resistance (IR) is increasing continuously, influencing metabolic parameters and fertility as well. The metabolic changes due to IR can alter the molecular composition of plasma and other body fluids. Follicular fluid (FF) is derived mainly from plasma, and it is a critical microenvironment for the developing oocytes. It contains various metabolites and amino acids, and the quality of the oocytes is linked at least partially to amino acid metabolism. Our goal was to determine quantitatively the amino acid (AA) profile of FF in IVF patients and to compare IR and non-insulin resistance (NIR) groups to investigate the AA changes in their FF. By UHPLC-based method we quantified the main 20 amino acids from human FF samples in the IR and NIR groups. Several amino acids (aspartate, glycine, glutamate, and cysteine) differed significantly (p&lt;0.05 or less) between the two groups. The most significant alterations between the IR and NIR groups were related to the glutathione metabolic pathway involving glycine, serine, and threonine. Since insulin resistance alters the amino acid composition of the FF, the oocytes may undergo metabolism-induced changes resulting in poor oocyte quality and less fertility in the insulin resistance groups.

Equine-assisted services (EAS) are being increasingly used as complementary interventions for military veterans who have experienced trauma. However, there is limited evidence of benefit for this population and almost no literature describing desired potential outcomes and possible mechanisms of action. The aim of this article is to address these gaps by reviewing the extant literature of animal-assisted interventions in general, and equine-assisted services in particular, with the goal of providing guidance for future investigations in the field. Currently, the field is in the early stage of scientific development, but published results are promising. Interventions that enhance treatment compliance and/or outcomes could benefit this population. Preliminary results, reviewed herein, indicate that EAS interventions might benefit the military veteran population by enhancing treatment engagement and therapeutic alliance, as well as contributing to symptom reduction and resulting in various transdiagnostic benefits. It is recommended that future studies include exploration of potential beneficial outcomes discussed herein as well as investigate suggested mechanisms of action.

Equine Assisted Activities (EAA) are considered a suitable innovative rehabilitative practice for children with neurodevelopmental disorders, including Autism Spectrum Disorder (ASD). While standardized scales have been previously used as a tool to evaluate the effects of EAA on different domains of functioning in ASD children, few studies have considered an ethological approach as a means to describe human-horse interactions in the context of ASD. In this study, we aimed to evaluate the behaviour of 19 children with ASD - in comparison with 19 typically developing children (TD) - during EAA sessions. We developed an ethogram from the video-recordings, to assess spatial relationships, social interactions and communicative behaviours displayed by the child towards the horse, as well as the occurrence of problem behaviours. Results indicate that children’s behaviours during EAA sessions are modulated by sex and age, while previous children’s experience with EAA appeared to improve interpersonal distance and horse handling. Results from this study highlight the importance of exploring children's behavioural response during animal-assisted activities through direct measurements. This may allow linking the quality/strength of the child-horse relationship to the benefits obtained by the child, particularly in the social/communicative domain, a core symptom of ASD.

The upper extremities limitation represents one of the essential functional impairments in patients with cervical spinal cord injury. Electromechanics assisted devices and robots are increasingly used in neurorehabilitation to help functional improvement in patients with neurological diseases. This review aimed to systematically report the evidence-based, state-of-art on clinical applications and robotic-assisted arm training (RAT) in motor and functional recovery in subjects affected by cervical spinal cord injury. The present study has been carried out within the framework of the Italian Consensus Conference on "Rehabilitation assisted by robotic and electromechanical devices for persons with disability of neurological origin" (CICERONE). PubMed/MEDLINE, Cochrane Library, and Physiotherapy Evidence Database (PEDro) databases were systematically searched from inception to September 2021. The 10-item PEDro scale assessed the study quality for the RCT and the AMSTAR-2 for the systematic review. Two different authors rated the studies included in this review. If consensus was not achieved after discussion, a third reviewer was interrogated. The 5-item Oxford CEBM scale was used to rate the level of evidence. A total of 11 studies were included. The selected studies were: two systematic reviews, two RCTs, one parallel-group controlled trial, one longitudinal intervention study and five case series. One RCT was scored as a high-quality study, while the systematic review was of low quality. RAT was reported as feasible and safe. Initial positive effects of RAT were found for arm function and quality of movement in addition to conventional therapy. The high clinical heterogeneity of treatment programs and the variety of robot devices could severely affect the generalizability of the study results; therefore, future studies are warranted to standardize the type of intervention and evaluate the role of robotic-assisted training in subjects affected by cervical spinal cord injury.

Sweet cherry pomace is a by-product that can be a source of bioactive phenolic compounds. Usually, polyphenols have been extracted using conventional extraction methodologies. However, a significant fraction, called non-extractable polyphenols (NEPs), remains retained in the conventional extraction residues. Therefore, this work is aimed, for the first time, to investigate the release of NEPs from cherry pomace combining pressurized liquid extraction (PLE) and enzyme-assisted extraction (EAE) using Promod enzyme. A response surface methodology was employed to study the influence of temperature, time, and pH on the NEPs extraction. The response variables were the total phenolic content (TPC) measured by Folin-Ciocalteu method, total proanthocyanidin (PA) content evaluated by vanillin, DMAC, and butanol/HCl assays, and total antioxidant capacity determined by Trolox equivalent antioxidant capacity and inhibition of hydroxyl radical assays. The results indicated that PLE-EAE was more suitable and selective to obtain NEPs from sweet cherry pomace than PLE alone. In fact, the extracts obtained by PLE-EAE displayed higher TPC, PA content, and bioactivity than the extracts obtained by PLE under the same extraction conditions, and those obtained by conventional methods. Moreover, size-exclusion chromatography profiles showed that the combination of PLE and EAE enabled the recovery of NEPs with higher molecular weight than PLE without EAE treatment.

Background. Shoulder in CrossFit should have a balance between mobility and stability. Glenohumeral internal rotation deficit and posterior shoulder stiffness are risk factors for overhead shoulder injury. Objective. To determine the effectiveness of instrument assisted soft tissue mobilization and horizontal adduction stretch in CrossFit practitioners’ shoulders. Methods: Twenty-one regular CrossFitters were allocated to experimental (stretching with isometric contraction and instrument assisted soft tissue mobilization) or control group (instrument assisted soft tissue mobilization). Each session lasted 5 minutes, 2 days a week, over a period of 4 weeks. Shoulder internal rotation and horizontal adduction (digital inclinometer), and posterior shoulder stretch perception (Park scale) were evaluated. Shapiro-Wilk test was used to analyze the distribution of the sample. Parametric student's t-test was used to obtain the intragroup differences. The inter- and intra-rater differences were calculated using a repeated measures ANOVA. Results. Changes were found in the experimental group following intervention (p < 0.05), and when comparing baseline and follow-up assessments (p < .05) in all variables. Significant differences were found in the control group following intervention (p < 0.05), in right horizontal adduction and left internal rotation. When comparing perception of internal rotation and horizontal adduction in both groups in the three assessments significant differences were found. Conclusions. Instrument assisted soft tissue mobilization can improve shoulder horizontal adduction and internal rotation. An instrument-assisted soft tissue mobilization technique yields the same results alone as those achieved in combination with post-isometric stretch with shoulder adduction.

The efficiency of producing embryos using in vitro technologies in livestock species rarely exceeds the 30 to 40% threshold, indicating that the proportion of oocytes that fail to develop after in vitro fertilization and culture is considerably large. Considering that the intrinsic quality of the oocyte is one of the main factors affecting blastocyst yield, the precise identification of non-invasive cellular or molecular markers that predict oocyte competence is of major interest to research and practical applications. The aim of this review was to explore the current literature on different non-invasive markers associated with oocyte quality in the bovine model. Apart from some controversial findings, the presence of cycle-related structures in ovaries, a follicle size between 6 and 10 mm, large number of surrounding cumulus cells, slightly expanded investment without dark areas, large oocyte diameter (>120 microns), dark cytoplasm, and the presence of a round and smooth first polar body have been associated to better competence. In addition, the combination of oocyte and zygote selection by BCB test and spindle imaging have the potential to further optimize the identification of oocytes with better developmental competence for in vitro-derived technologies in livestock species.

The ectoparasitic mite Varroa destructor is the most significant pathological threat to the western honey bee, Apis mellifera, leading to the death of most colonies if left untreated. An alternative approach to chemical treatments is to selectively enhance heritable honey bee traits of resistance or tolerance to the mite through breeding programs, or select for naturally surviving untreated colonies. We conducted a literature review of all studies documenting traits of A. mellifera populations either selectively bred or naturally selected for resistance and tolerance to mite parasitism. This allowed us to conduct an analysis of the diversity, distribution and importance of the traits in different honey bee populations that can survive V. destructor throughout the globe. In a second analysis, we investigated the genetic bases of these different phenotypes by comparing ’omics studies (genomics, transcriptomics, and proteomics) of A. mellifera resistance and tolerance to the parasite. Altogether, this review provides a detailed overview of the current state of the research projects and breeding efforts against the most devastating parasite of A. mellifera. By highlighting the most promising traits of varroa-surviving bees and our current knowledge on their genetic bases, this work will help direct future research efforts and selection programs to control this pest. Additionally, by comparing the diverse populations of honey bees that exhibit the traits, this review highlights the consequences of anthropogenic and natural selection on the interactions between hosts and parasites.

In order to solve the problem of measuring the distance and position between the flanges of two pipelines on the seabed, a measuring device for pulling rope in seawater was designed. Aiming at the sealing problem of the key equipment that is the rotating shaft of the rope winch, this paper used the principle of the magnetic coupling to transfer the driving moment, and adopted the method of converting the dynamic seal into the static seal structure to realize the reliable sealing of the motor. Through the experiment of measuring two pipelines with underwater rope pulling device, it was verified that the measuring accuracy of the device meets the design requirements, and the feasibility of the application of magnetic coupling technology in winch is also verified.

Optical biopsy describes a range of medical procedures in which light is used to investigate disease in the body, often in hard-to-reach regions via optical fibres. Optical biopsies can reveal a multitude of diagnostic information to aid therapeutic diagnosis and treatment with higher specificity and shorter delay than traditional surgical techniques. One specific type of optical biopsy relies on Raman spectroscopy to differentiate tissue types at the molecular level and has been used successfully to stage cancer. However, complex micro-optical systems are usually needed at the distal-end to optimise the signal-to-noise properties of the Raman signal collected. Manufacturing these devices remains a critical challenge, particularly in a way suitable for large scale adoption. In this paper, we describe a novel fibre-fed micro-optic system designed for efficient signal delivery and collection during a Raman spectroscopy based optical biopsy. Crucially, we fabricate the device using a direct-laser-writing technique known as ultrafast laser assisted etching which is scalable and allows components to be aligned passively. The Raman probe has a sub-millimetre diameter and offers confocal signal collection with 71.3 ± 1.5% collection efficiency over a 0.8 numerical aperture. Proof of concept spectral measurements were performed on mouse intestinal tissue and compared with results obtained using a commercial Raman microscope.

Silybum marianum (L.) Gaertn. (aka milk thistle) constitute the almost exclusive source of silymarin, a mixture of different flavonolignans, and is thus considered as a unique model for their extraction. The present research deals with ultrasound-assisted extraction (UAE) of S. marianum flavonolignans and their quantification using LC system. The optimal conditions for UAE were: aqueous EtOH 54.5% (v/v) as solvent, applying an ultrasound frequency of 36.6 kHz during an extraction time of 60 min at 45°C with a liquid to solid ratio of 25:1 ml/g DW. Following optimization, the extraction method was validated according to international standards of the association of analytical communities (AOAC) in order to ensure its precision and accuracy for the quantitation of the individual silymarin components. The efficiency of UAE was compared with maceration protocol of the same duration. The optimized and validated conditions allowed highest extraction yields of flavonolignans in comparison to maceration. The antioxidant capacity of the extracts was confirmed by the CUPRAC assays and inhibition of advanced glycation end products. The skin anti-aging action was also confirmed toward the strong in vitro inhibition capacity of the obtained extract against collagenase and elastase enzymes. The procedure presented here allows a green efficient extraction and quantification of the main flavonolignans from the fruits of S. marianum with attractive antioxidant and anti-aging activities for future cosmetic applications.

In laser-assisted milling, higher temperature in shear zone softens the material potentially resulting in a shift of mean residual stress, which significantly affects the damage tolerance and fatigue performance of product. In order to guide the selection of laser and cutting parameters based on the preferred mean residual stress, inverse analysis is conducted by predicting residual stress based on guessed process parameters, which is defined as the forward problem, and applying iterative gradient search to find process parameters for next iteration, which is defined as the inverse problem. An analytical inverse analysis is therefore proposed for the mean residual stress in laser-assisted milling. The forward problem is solved by analytical prediction of mean residual stress after laser-assisted milling. The residual stress profile is predicted through the calculation of thermal stress, by treating laser beam as heat source, and plastic stress by first assuming pure elastic stress in loading process, then obtaining true stress with kinematic hardening followed by the stress relaxation. The variance-based recursive method is applied to solve inverse problem by updating process parameters to match the measured mean residual stress. Three cutting parameters including depth of cut, feed per tooth, and cutting speed, and two laser parameters including laser-tool distance and laser power, are updated with respected to the minimization of resulting residual stress and measurement in each iteration. Experimental measurements are referred on the laser-assisted milling of Ti-6Al-4V grade 5 and ELI. The percentage difference between experiments and predictions is less than 5% for both materials, and the selection is completed within 50 loops.

This paper presents a system developed for the assistance with a collaborative robot in hand-assisted laparoscopic surgery (HALS). The system includes a sensing glove with piezoresistive sensors which capture continuously the flexion degree of the surgeon's fingers. These data are analyzed using an algorithm that detects and recognize the selected movements. This information is sent as commands to the collaborative robot throughout the surgical operation. The bending patterns, speed and execution times of the movements are modelled in a pre-phase in which it will extract all the necessary information for later detection during the motion execution. The results obtained with 10 different volunteers show a high degree of accuracy and a low false discovery rate.

This paper studies the maximum reliability of multi-hop relay UAV, in which UAV provides wireless services for remote users without direct communication link on the ground as a coded cooperative relay. In this paper, the analytical expressions of total power loss and total bit error rate are derived as reliability measures. Firstly, based on the environmental statistical parameters, a LOS probability model is proposed. Then the problem of minimizing the bit error rate of static and mobile UAVs is studied. The goal is to minimize the total bit error rate by jointly optimizing the height, elevation, power and path loss, and subject to the maximum allowable path loss con-straints, transmission power allocation constraints and UAV height and elevation constraints. At the same time the total path loss is minimized to achieve maximum ground communication cov-erage. However, the formulated joint optimization problem is non-convex and generally difficult to solve. Therefore, we decomposed the problem into two subproblems and proposed an effective joint optimization iteration algorithm. Finally, the simulation results are given, and the analysis shows that the optimal height of different reliability measures is slightly different, and using the mobility of UAVs can improve the reliability of communication performance.

Balsam fir trees are a specialty agricultural species that are largely used as Christmas trees. Soil or tissue sampling is seldom performed to assess balsam fir nutrition needs, which can contribute to over or under fertilization and subsequent environmental challenges. Remote sensing to determine the normalized difference vegetation index (NDVI) has had strong relationships with nutrition in other plants. This research aimed to determine whether there is a relationship between NDVI and nutrition in balsam fir. A random sample of 45 trees was selected in autumn of 2021 and then another 70 trees selected in spring of 2022. Soil and needle tissue samples were analyzed for N, P, K, Ca, Mg, S, Fe, Zn, Mn, B, and Cu. An uncrewed aerial vehicle equipped with a multispectral camera was flown over the orchard to determine the NDVI for each tree. Nutrition and NDVI were analyzed for correlations through all sampled trees. Separate correlation analyses were repeated for mature trees (greater than 5 years old) and young trees (less than 5 years old). Soil nutrients N, P, K had a significant relationship with NDVI in autumn sampling. Only N was correlated consistently in both autumn and spring, with R2 of 37% and 33% respectively. Relationships were much stronger when only mature trees were considered, increasing to 60% and 51% respectively. NDVI was found to offer predictive power for tissue N that can be useful to producers to help optimize fertilizer input. However, further work is needed to refine these relationships.

This work aims to develop an autonomous system for the unmanned aerial vehicle (UAV) to land on a moving platform such as the automobile or marine vessels, providing a promising solution for a long-endurance flight operation, a large mission coverage range, and a convenient recharging ground station. Different from most state-of-the-art UAV landing frameworks which rely on UAV’s onboard computers and sensors, the proposed system fully depends on the computation unit situated on the ground vehicle/marine vessel to serve as a landing guidance system. Such novel configuration can therefore lighten the burden of the UAV and computation power on the ground vehicle/marine vessel could be enhanced. In particular, we exploit a sensor fusion-based algorithm for the guidance system to perform UAV localization, whilst a control method based upon trajectory optimization is integrated. Indoor and outdoor experiments are conducted and the result shows that a precise autonomous landing on a 43 X 43 cm platform could be performed.

Infertility affects millions worldwide, posing a significant global health challenge. The proteomic analysis of follicular fluid provides a comprehensive view of the complex molecular landscape within ovarian follicles, offering valuable information on the factors influencing oocyte development and on the overall reproductive health. The follicular fluid is derived from the plasma and contains various proteins that can have different roles in oocyte health and infertility and this fluid is a critical microenvironment for the developing oocytes as well. Using HPLC/MS method we investigated the protein composition of the follicular fluid and after classification we did relative quantification of the identified proteins in the pregnant (P) and non-pregnant (NP) groups. Based on the protein-protein interaction analysis ALB and ApoA1 was found to be hub proteins and the quantitative comparison of the P and NP groups resulted significantly lower concentration of ApoA1 and HDL-cholesterol in the P group. As both molecules are involved in the cholesterol transport, we also investigated their role in the development of oocytes and in the prediction of fertility.

The feasibility of recovering bioactive antioxidants from Phyllantus emblica leaves using ethanol -water mixture (0 – 100%) and heat-assisted extraction technology (HAE-T) was investigated in this present study. To this effect, the process parameter of operating temperature (OT: 30 -50 oC), solid -to-liquid ratio (S:L: 1:20 - 1:60 g/mL) and extraction time (ET: 45 - 180 min) were investigated on the extract total phenolic content (TPC, mg GAE/g d.w), yield (EY, %) and antioxidant activity (μM AAE/g d.w) by employing the Box-Behnken experimental design (BBD) available in response surface methodology (RSM). Multi-objective process optimization using the desirability function algorithm to determine set of process variables that simultaneously optimize process responses of TPC, EY and AA was also investigated. The recovery process was thereafter modeled with BBD-RSM and multi gene genetic programming (MGGP) algorithm and model reliability assessment via Monte Carlo simulation were conducted for the best performing set of models for predicting TPC, EY and AA values. The HPLC characterization of the recovered extract was carried out to ascertain the phenolic compound constituents of the Phyllantus emblica leaf extract. The 50% ethanol solution was found to be the best for the optimal extraction of antioxidants from Phyllantus emblica leaves. The HAE-T was suitable for recovering bioactive extract from Phyllantus emblica leaves and investigated process parameters have impacts on the recovery process. The process parameters that simultaneously gave the optimum EY of 21.6565%, TPC of 67.116 mg GAE/g and AA of 3.68583 µM AAE/g were OT of 41.61 oC, S:L of 1:60 g/mL and ET of 180 min. The HPLC extract profiling revealed that the bioactive constituents present in the recovered extract were betulinic acid, gallic acid, chlorogenic acid, caffeic acid, ellagic acid, and ferulic acid. Both the developed BBD-RSM and evolved MGGP-based models predicted the observed process response of TPC, EY and AA satisfactorily with BBD-RSM models marginally better in their predictions. The reliability results showed that the BBD-RSM models predicted TPC, EY and AA values with high certainty of 99.985%, 97.569% and 98.661%, respectively.

When analyzing user geospatial information through deep learning methods, it is typically necessary to annotate existing geospatial data. Currently, manual annotation methods are commonly employed, suffering from issues related to low efficiency and accuracy. This design is based on the TensorFlow deep learning framework and first realizes the BiLSTM+CRF+AGG deep learning model. Among the models, AGG is the aggregation layer, which is introduced to solve the problem of solid particle size equilibrium. Secondly, based on the characteristics of original data and professional data, an automatic labeling algorithm is proposed. The algorithm first preprocesses the acquired original data set and professional data set, The most valuable unlabeled data set which can make the training model converge quickly is selected from the original data set as the target data set. Sort the target data set based on preset rules and set annotation parameters for the sorted target data set. Based on the set annotation parameters, the corpus is synthesized and used as the annotation result. Thirdly, based on the active learning strategy, a manual annotation auxiliary scheme is proposed, and an Excel generation module that is convenient for manual annotation correction is designed and developed to further improve the efficiency and quality of annotation through iterative processing. The combination of the BiLSTM+CRF+AGG deep learning model and high-quality annotation can accurately identify non-standard, incomplete, or even incorrect geographical information entities. This annotation method has found successful practical application within the context of the research project and has been granted an invention patent.

This study examined the eye movement patterns of 317 elementary students across reading conditions (audio-assisted reading (AR) and reading-only (R)) and text types (fiction and non-fiction), and identified eye movement parameters that predict their literal comprehension (LC) and inferential comprehension (IC). Participants, randomly assigned to either reading condition and either text type, answered questions assessing their LC and IC. Average fixation duration (AFD), total fixation duration (TFD), and scanpath length were used as eye movement parameters. There were main effects of age on all parameters and interaction effects between age and reading condition on TFD and scanpath length. Controlling for age, TFD had a positive impact on LC of both text types in the AR, while under the R, it affected negatively on IC of both text types. Longer scanpaths predicted IC of fiction in the AR, LC and IC of non-fiction under the AR, and LC of non-fiction within the R. AFD influenced negatively on IC of fiction in the AR, LC and IC of non-fiction in the AR, and LC of non-fiction under the R. These eye movement patterns and predictors indicate children employ different reading strategies based on reading modality and text type.

Ovarian hyperstimulation syndrome (OHSS) is the main severe complication of the ovarian stimulation for in vitro fertilization (IVF) cycles. The aim of the current study was to identify the interventions for prevention of and reduction in the incidence and severity of OHSS in patients who undergo IVF not included in systematic reviews with meta-analysis of randomized controlled trials (RCTs), assess and grade their efficacy and evidence base. The best available evidence for each specific intervention was identify, analyzed in terms of safety/efficacy ratio and of risk of bias, and graded using Oxford Centre for Evidence-Based Medicine (CEBM) hierarchy of evidence. A total of 15 interventions to prevent OHSS were included in the final analysis. In IVF population not at high risk for OHSS, follitropin delta for ovarian stimulation may reduce the incidence of early OHSS and/or preventive interventions for early OHSS. In high-risk patients, inositol pretreatment, ovulation triggering with low doses of urinary hCG, and the luteal phase administration of GnRH antagonist may reduce the OHSS risk. In conclusion, even if not supported by systematic reviews with homogeneity of the RCTs, several treatments/strategies to reduce the incidence and severity of OHSS have shown to be promising.

The objective of this study was to assess the impact of different inoculation technologies on the aerobic biological semi-decomposition process of bokashi-type biofertilizer formulations. We examined their effects on the chemical and biological quality of the product, as well as their influence on the agronomic and nutritional characteristics of red-beet and cabbage crops in the field. The highest yields of field-grown beet crops were obtained from seedlings produced using the following treatments: bokashi biofertilizer + biodynamic preparations 502-507 BPB (62.6 Mg ha-1), bokashi + Chamomilla 12CH (60.2 Mg ha-1), and bokashi + Carbo vegetabilis 12 CH (56.3 Mg ha-1). These results corresponded to an increase of 60.9%, 54.7%, and 44.7%, respectively, compared to the yield of the control treatment (38.9 Mg ha-1). The increase in productivity of cabbage plants was higher in the treatment bokashi + Calcarea carbônica 12 CH (35.8 Mg ha-1), being 148.6% higher than the control (14.4 Mg ha-1).The content of moisture, carbon, nitrogen, C/N ratio, and pH H2O in the majority of the evaluated formulations, comply with the standards outlined in IN Nº 61, 2020, by Ministry of Agriculture, Fisheries and Supply, qualifying them as class "A" solid organic compound fertilizers.

Background: Primary lymphedema is a chronic condition caused by a developmental abnormality of the lymphatic system and its malfunction. Different surgical options such as physiologic and excisional procedures have been proposed. The aim of this study was to present a complete algorithm for the treatment of primary lower extremity lymphedema: Primary LYmphedema Multidisciplinary Approach (P-LYMA). Methods: Nineteen patients were treated according to the P-LYMA. Patients underwent pre- and post-operative complex decongestive therapy (CDT). Different physiologic and excisional procedures were performed independently or in combination. The primary outcome was the circumferential reduction rate (CRR). The Lymphedema Quality of Life Score (LeQOLiS), reduction in the number of episodes of cellulitis, length of stay, and complications were recorded. Results: The mean CRR calculated was 72.8±19.6% after twelve months. The episodes of cellulitis per year decreased from a mean of 1.9±0.8 preoperative to 0.4± 0.6 throughtout follow-up. Two patients experienced minor complications. Mean hospitalization time was 5 days. Patients’ quality of life (LeQOLi score) drastically improved from 70.4±11.6 to 24.2 ±13.9 at twelve months post-op. Conclusion: The P-LYMA algorithm allows to maximize surgical results and improve the quality-of life in patients who suffer from primary lymphedema. CDT is mandatory to optimize results.

The ultrasonic vibration assisted pressing process can improve the fluidity, the uneven distribution of density and particle size of WC-Co powder. However, the microscopic mechanism of ultrasonic vibration on the powder remains unclear. In this paper, WC and Co particles are simulated by three-dimensional spherical models of two particle sizes with the aide of the secondary development of Python. At the same time, the forming process of powder at mesoscale is simulated in the virtue of the finite element analysis software ABAQUS. The influence of vibration amplitude on the fluidity, the filling density and the stress distribution of WC-Co powder is investigated when the ultrasonic vibration is applied to the conventional pressing process. From simulation results, the ultrasonic vibration amplitude has great influences on the density of the compact. With the increase of the ultrasonic amplitude, the compact density also increases gradually. At the initial stage of the compaction, the particles move violently under the action of ultrasonic vibration, the fluidity is obviously enhanced, the arch bridge effect between particles is destroyed, the fine particles quickly fill the pores between the large particles, which increase the density, and the residual stress in the billet decreases after the compaction. From the experimental results, the size distribution of the billet is more uniform, the elastic aftereffect is reduced, the dimensional instability is improved, and the density curves obtained by experiment and simulation are within a reasonable error range.

The standard treatment for early-stage lung cancer is complete tumor excision by limited resection of the lung. Pre-operative localization is used before video-assisted thoracoscopic surgery (VATS) to improve the accuracy of pulmonary nodule excision. However, lung atelectasis and hypoxia resulting from controlling apnea during the localization procedure may affect the localization accuracy. Pre-procedural pulmonary recruitment may improve respiratory mechanics and oxygenation during localization. In this study, we investigated the potential benefits of pre-localization pulmonary recruitment prior to pulmonary ground-glass nodule localization in a hybrid operating room. We hypothesized that pre-localization pulmonary recruitment would increase localization accuracy, improve oxygenation, and prevent the need for re-inflation during the localization procedure. We retrospectively enrolled patients with multiple pulmonary nodule localizations before surgical intervention in our hybrid operating room. We compared localization accuracies between patients who had undergone pre-procedure pulmonary recruitment and patients who had not. Saturation, re-inflation rate, apnea time, procedure-related pneumothorax, and procedure time were also recorded as secondary outcomes. Patients who had undergone pre-procedure recruitment had better saturation, shorter procedure time, and higher localization accuracy. The pre-procedure pulmonary recruitment maneuver was effective in increasing regional lung ventilation, leading to improved oxygenation and localization accuracy.

One-step reactive melt processing (REx) via radical reaction was evaluated with the aim of improving the rheological properties of poly(ε-caprolactone) (PCL). In particular, a water-assisted REx was designed under the hypothesis of increasing crosslinking efficiency with water as a low viscous medium in comparison with a slower PCL macroradicals diffusion in the melt state. To assess the effect of dry vs. water-assisted REx on PCL, its structural, thermo-mechanical and rheological properties were investigated. Water-assisted REx resulted in increased PCL gel fraction compared to dry REx (from 1 to 34 %), proving the rationale under the formulated hypothesis. From dynamic mechanical analysis and tensile tests, the crosslink did not significantly affect the PCL mechanical performance. Dynamic rheological measurements showed that higher PCL viscosity was reached with increasing branching/crosslinking and the typical PCL Newtonian behavior was shifting towards a progressively more pronounced shear thinning. A complete transition from viscous- to solid-like PCL melt behavior was recorded, demonstrating that higher melt elasticity can be obtained as a function of gel content by controlled REx. Improvement in rheological properties offers the possibility of broadening PCL melt processability without hindering its recycling by melt processing.

Almond (Prunus dulcis (Mill.) D.A.Webb) is one of the most important nut crops both in terms of area and production. Over the last decades, an important part of the beneficial actions for health associated with their consumption was attributed to the phenolic compounds, mainly accumulated in almond skin. Interestingly, after cold-pressed oil extraction, most of these antioxidant phenolic compounds are retained in a skin-enriched by-product, so-called almond cold-pressed oil residue. In Morocco, ranked fifth producer in the world, this production generates an important part of this valuable byproduct. In the present study, using a multivariate Box-Behnken design, an ultrasound-assisted extraction (USAE) method of phenolic compounds from Moroccan almond cold-pressed oil residue was developed and validated. Response surface methodology resulted in the optimal extraction conditions: the use of aqueous EtOH 53.0% (v/v) as green solvent, applying an US frequency of 27.0 kHz for an extraction duration of 29.4 min. The present USAE allowed substantial gains in terms of extraction efficiency compared to conventional heat reflux extraction. Applied to 3 different local Beldi genotypes growing at 3 different experimental sites, the optimal USAE conditions led to a total phenolic content of 13.86 mg/g dry weight (DW). HPLC analysis revealed that the main phenolic compounds from this valuable byproduct were: chlorogenic acid followed by protocatechuic acid, p-hydrobenzoic acid and p-coumaric acid. The accumulation of these phenolic compounds appeared to be more dependent on the genetic background than on the environmental impact here represented by the 3 experimental culture sites. Both in vitro cell free and cellular antioxidant assays were performed, and revealed the great potential of these extracts. In particular, correlation analysis evidenced the prominent roles of chlorogenic acid, protocatechuic acid and p-hydrobenzoic acid. To summarize, the USAE method presented here is a quick, green, simple and efficient validated USAE for the possible valorization of antioxidant phenolic compounds from Moroccan almond cold-Pressed oil residues, making it possible to generate extracts with attractive antioxidant activities for future nutraceutical and/or cosmetic applications.

This paper questions the potential shift of reproduction towards assisted reproductive technologies due to benefits provided by genetic manipulation of embryos. In order to examine the viability of such a shift and its implications from a regulatory perspective, we relied on two panels of experts from Israel and Spain, using the Delphi method and a series of in-depth interviews. We anticipate, at a first stage, a continuous-steady growth in the use of IVF, supplemented by preimplantation genetic diagnosis and the introduction of CRISPR/Cas. At a second stage, attracting a growing share of fertile people would require developments in genomics. While it is unclear whether these developments will fully materialize, they could be replaced by technoscientific imaginaries generating perceived benefits. We conclude that the regulation of reproductive genetics is becoming more critical and complex. The aim should be to ensure good practices and equity, while providing more information to the public. A broad and inclusive societal debate may overcome the difficulty of drawing a clear line between medical uses and non-medical uses of genetic selection and engineering and may contribute to finding the right balance between allowing autonomous decisions of patients and protecting the public interest.

Difficult-to-cut materials are being increasingly used in many industries because of their superior properties, including high corrosion resistance, heat resistance and specific strength. However, these same properties make the materials difficult to machine using conventional machining techniques. Laser-assisted milling (LAM) is one of the effective methods for machining difficult-to-cut materials. In laser-assisted milling machining occur after the workpiece is locally preheated using a laser heat source. Laser assisted machining has been studied by many researchers on flat workpiece or micro end-milling. However, there is no research on the curved shape using laser assisted milling. This study investigated the use of laser assisted milling to machine a three-dimensional curved shape workpiece based on NURBS. A machining experiment was performed on Inconel 718 using different tool paths (ramping, contouring) under various machining conditions. Finite elements analysis was conducted to determine the depth of cut. Cutting force, specific cutting energy and surface roughness characteristics were measured, analyzed and compared for conventional and LAM machining. LAM significantly improved these machining characteristics, compared to conventional machining. There results can be applied to the laser-assisted machining of various three-dimensional shapes.

Infertility affects approximately 15% of couples worldwide, an estimated 30% of which is related to male factor infertility. Application of low level laser therapy (LLLT) to improve fertility status is a rapidly growing discipline in medicine. Laser therapy triggers a variety of biological processes through interaction with primary cellular photoacceptors. The present review aims at evaluating the literature available in the MEDLINE/ PubMed on cellular and molecular mechanisms of photobiomodulation in the domains of reproductive and veterinary medicine. We primarily focused on the clinical application of laser treatment on seminal quality, in particular its role in promoting spermatozoa motility, as well as the role of phototherapy in modulating assisted reproduction (ART). Additionally, we investigated the strength of evidence in support of the positive impact of photobiomodulation on facilitating ART.

Based on the demographic shift and the related challenges resulting from the growing number of elderly and persons with chronic diseases, the idea of smart home that supports its inhabitants in the daily life, gains importance. The purpose of this paper was to examine in a prototypic Ambient Assisted Living environment if users after interaction with different health-supporting applications intend to use such in the future. Two experimental studies exemplary show possible applications of home-integrated technology that can support, assist and accompany the target group in different contexts, and examine to what extent participants are willing to future use such sophisticated technology at home. The results show that people in general, but especially the old and chronically ill ones are quite fascinated of health-supporting ambient technology and the majority intends to use such ambient assistance in the future (study I). Moreover, serious games for healthcare are shown as a hedonic use of technology in smart homes that have a great potential to retain or improve the physical health, mobility and the overall well-being of the inhabitants (study II). The article provides two examples of ambient technology to leverage the demographic change and presents important user factors for facilitating high user acceptance.

Coastal dunes worldwide are increasingly under pressure from the adverse effects of human activities. Therefore, more and more restoration measures are being taken to create conditions that help disturbed coastal dune ecosystems regenerate or recover naturally. However, many projects lack (open-access) monitoring observations needed to signal whether further actions are needed, and hence to learn by doing. This submission presents an open access data set of 37 high-resolution digital elevation models and 24 orthomosaics collected before and after the excavation of five artificial foredune trough blowouts ("notches") in winter 2012/2013 in the Dutch Zuid-Kennemerland National Park, one of the largest coastal dune restoration projects in northwest Europe. These high-resolution data provide a valuable resource for improving understanding of the biogeomorphic processes that determine the evolution of restored dune systems, as well as developing guidelines to better design future restoration efforts with foredune notching.

In recent years, unmanned aerial vehicles (UAVs) have become a valuable platform for many applications, including communication networks. UAV-enabled wireless communication faces challenges in complex urban and dynamic environments. UAVs can suffer from power limitations and path losses caused by non-line-of-sight connections, which may hamper better communication performance. To address these issues, reconfigurable intelligent surfaces (RIS) have been proposed as a helpful tool to enhance UAV communication networks. However, due to the high mobility of UAV, complex channel environments, and dynamic RIS configurations, it is challenging to estimate the link quality of ground users. In this paper, we propose a link quality estimation model using a gated recurrent unit (GRU) to assess the link quality of ground users for a multi-user RIS-assisted UAV-enabled wireless communication system. Our proposed framework uses a time series of user channel data and RIS phase shift information to estimate the quality of the link for each ground user. Simulation results showed that the proposed GRU model effectively and accurately estimates the link quality of the ground users in the RIS-assisted UAV-enabled wireless communication network.

In the past few decades, the use of agricultural waste has been increasing due to the increasing demand for sustainable materials. This paper aims to review the significance of agricultural waste as a type of wealth and its potential as an alternative material in the composite field. It was found that many agricultural wastes had been utilized in various production of ecological products. The review discusses the physical, mechanical, and chemical properties of the natural fibers made from agricultural waste and the use of Pineapple Leaf Fiber Reinforced Composite to manufacture UAVs (Unmanned Aerial Vehicles). The extracted waste fibers’ physical, mechanical, and chemical properties show that these agricultural wastes can produce better advanced composite materials suitable for structural applications. The use of pineapple leaf fiber in Unmanned Aerial Vehicles manufacturing has the potential to revolutionize this industry and contribute to a more sustainable future.

This paper proposes a compact planar Wi-Fi antenna with optimized radiation patterns for small uncrewed aerial vehicle (UAV) applications in both urban and open areas. It is suitable for mounting on the outermost side of the non-metallic wing of small UAVs. It has small dimensions of 16.5 mm (L) by 30.3 mm (W) by 1.6 mm (h), and the measured results of its prototype are in agreement with simulated data. Its impedance bandwidths over the two frequency ranges are 2.11 to 2.58 GHz and 5.06 to 7.5 GHz ( ). At 5.8 GHz, it has stronger radiation below the small UAV to reduce interference from rare-use directions. Its maximum radiations, the directions of the maximum radiation in each elevation plane, are below the UAV and between 14° and 29° from the horizontal plane. At 2.4 GHz, it has quasi-omnidirectional radiation to ensure a stable link in all directions, and its maximum radiations are near the horizontal plane. The optimized radiation patterns at 5.8 and 2.4 GHz can provide more antenna gain when the small UAV flies farther in urban and open areas, respectively. In addition, it has good vertically polarized radiation for long-distance applications.

Quadrotor drones have rapidly gained interest recently. Numerous studies are underway for the commercial use of autonomous drones, and especially the distribution businesses are taking serious reviews on drone delivery services. However, there are still many concerns about urban drone operations. The risk of failures and accidents makes it difficult to provide drone-based services in the real world with ease. There have been many studies that introduced supplementary methods to handle drone failures and emergencies. However, we discovered the limitation of the existing methods. The majority of approaches were improving PID-based control algorithms which is the dominant drone control method. This type of low-level approach lacks situation awareness and the ability to handle unexpected situations. This study introduces an event-based control methodology that takes a high-level diagnosing approach that can implement situation awareness via time-window. While leaving the low-level controller to involve in operating the drone for most of the time in normal situations, our controller operates at a higher level and detects unexpected behaviors and abnormal situations of the drone. We tested our method with real-time 3D computer simulation environments with Unreal Engine[15] and AirSim[31]. We were able to verify that our approach can provide enhanced double safety and better ensure safe drone operations. We hope our discovery to possibly contribute to the advance of real-world drone services in the near future.

Lower limb exoskeletons have the potential to reduce the prevalence of work-related musculoskeletal disorders; however, they often lack user-oriented control strategies. Human-in-the-loop (HITL) controls can adapt an exoskeleton’s assistance in real-time, to optimize the user-exoskeleton interaction. This study presents a HITL control for a knee exoskeleton to minimize the users’ physical effort, a parameter innovatively evaluated by their interaction torque with the exoskeleton (a muscular effort indicator) and metabolic cost. This work innovates by estimating the user’s metabolic cost within the HITL control through a machine-learning model. The regression model was able to estimate the metabolic cost, in real-time, with a root-mean-squared error of 0.66 W/kg and a mean absolute percentage error of 26%, making faster (10s) and less noisy estimations than a respirometer (K5, Cosmed) device. The HITL reduced the user’s metabolic cost and interaction torque by 7.3% and 32.3%, respectively, when compared to a zero-torque control. The developed HITL control surpassed both a non-exoskeleton and a zero-torque condition regarding the user’s physical effort, even for a simple task such as slow walking. Furthermore, the user-specific control enabled a lower metabolic cost than the non-user-specific assistance. This proof-of-concept demonstrated the potential for HITL controls in assisted working.

With the widespread Application of Virtual Reality (VR) in education, optimizing foreign language learning in VR has become a focal point of research. This paper introduces a comprehensive theoretical framework (VR-CCL) based on constructivism and cognitive load theory to enhance foreign language learning in VR. Through a literature review, we explore the applications of VR in education, foreign language learning theories, and prior works on technology-assisted language learning. We further detail the three main components of the VR-CCL framework and validate its effectiveness through two case studies: Duolingo VR and Rosetta Stone VR. Finally, we discuss the strengths and limitations of the framework and its implications for educators and developers.

Numerous reservoirs that play a significant role in worldwide petroleum production and reserves contain fractures. Typically, the fractures must form a connected network for a reservoir to be classified as naturally fractured. Characterizing the reservoir with a focus on its fracture network is crucial for modeling and predicting production performance. To simplify the solution, dual continuum modeling techniques are commonly employed. However, to use continuum-scale approaches, properties such as average aperture, permeability, and matrix fracture interaction parameters must be assigned, making it necessary to improve fracture depiction and modeling methods. This study investigates a fractured reservoir with a low matrix permeability and a well-connected fracture network. The focus is on the impact of the hyrachical fracture network on the production performance of gas-based enhanced oil recovery methods. The Discrete Fracture Model (DFN) was utilized to create comprehensive two-dimensional models for three processes: Gas Injection (GI), Water Alternating Gas (WAG), and Foam Assisted Water Alternating Gas (FAWAG). Moreover, dimensionless numbers were employed to establish connections between properties across the entire fracture hierarchy, spanning from minor to major fractures and encompassing the fracture intensity. The results indicate that the FAWAG is more sensitive to fracture types and networks than the WAG and GI processes. Hence, the sensitivity of the individual EOR method to the fracture network requires a respective depth of description of the fracture network. However, other factors, such as reservoir fluids properties and fracture properties, might influence the recovery when the minor fracture networks are excluded. This study has determined that, among the enhanced oil recovery (EOR) techniques examined, the significance of the hyrachical depth of fracture networks diminishes as the ratio of major (primary fracture) aperture to the aperture of medium and minor fractures increases. Additionally, the impact of the assisted-gravity drainage method was greater with increased reservoir height; however, as the intensity ratio increased, the relative importance of medium and minor fracture networks decreased.

A novel approach based on response surface methodology (RSM) was developed to predict and apply the best extraction conditions for the isolation of various-type polyphenolic antioxidants from the dried flower buds of Magnolia x soulangeana Soul.-Bod. var. ‘Lennei’ (Magnoliaceae). As a method of choice, ultrasound-assisted extraction was used and the optimized extraction parameters (temperature, time of extraction, the composition of aqueous-ethanolic extractants and solvent to solid ratio) have been determined using a central composite design factorial analysis, followed by appropriate spectrophotometric methods (with Folin–Ciocalteu and 2,2-diphenyl-1-picrylhydrazyl reagents) to determine the antioxidant and antiradical potential of extracts, respectively. The use of 66.8% (V/V) ethanol, as the extraction solvent during the 55.2 min extraction protocol, and the ratio of extractant volume to herbal substance of 46.8 mL/g gave the highest total yield of bioactive antioxidant phenolics in the extract obtained. For this herbal preparation, qualitative and quantitative analysis was performed using combined chromatographic (LC), spectroscopic (PDA) and tandem mass spectrometric (ESI-QTOF–MS/MS) techniques. A detailed phytochemical profiling, conducted for the first time, documented substantial amounts of polyphenolic antioxidants, especially phenylethanoids and flavonoids in the flower buds of M. soulangeana ‘Lennei’. Their average total content exceeded 30.3 and 36.5 mg/g dry weight, respectively.

The primary considerations while producing rice (Oryza sativa L.) include improving its nutritional quality and production. To tackle widespread hunger globally, better nutritional, high-yielding rice cultivars need to be developed. The conventional ways are to increase the production of rice and add balanced nutrients in the daily diet to fulfill the need of yield and nutrient quality. This article focuses on nutritional strategies for rice and illustrates the availability of omics technologies. Current advancements providing many methodologies and approaches for exploring genetic resources and for understanding the molecular mechanisms involved in trait formation have been highlighted. Studying the genetic influences of various characteristics has been proven to expedite crop breeding processes. In this perspective, genome-wide association research, genome selection (GS), and QTL mapping are all genetic analysis that helps in increasing the nutritional content of rice. Implementation of several omic techniques are effective approaches to enhance and regulate the nutritional quality of rice cultivars. Advancements in different types of omics including genomics and pangenomics, transcriptomics, metabolomics, nutrigenomics, and proteomics are also relevant to rice development initiatives. This review article compiles genes, locus, mutants and all omic approaches for rice enhancement. This knowledge will be very useful for now and for the future regarding rice studies.

Autonomous driving systems are increasingly becoming a necessary trend towards building smart cities of the future. Numerous proposals have been presented in recent years to tackle particular aspects of the working pipeline towards creating a functional end-to-end system, such as object detection, tracking, path planning, sentiment or intent detection. Nevertheless, few efforts have been made to systematically compile all of these systems into a single proposal that effectively considers the real challenges these systems will have on the road, such as real-time computation, hardware capabilities, etc. This paper has reviewed various techniques towards proposing our own end-to-end autonomous vehicle system, considering the latest state on the art on computer vision, DSs, path planning, and parallelization.

Background: The Micro Hand S robot is the first domestically produced surgical robot that has entered clinical use in China, and this is the first report of its application in colon cancer. Objective: This study aimed to validate the safety and efficacy of the domestically produced Chinese minimally invasive Micro Hand S surgical robot system in complex surgery, such as robotic complete mesocolic excision (R-CME). Methods: From March 2018 to December 2018, 30 patients with right hemicolon cancer underwent R-CME with the Micro Hand S robot system. The operative findings, morbidities, oncological findings and unique characteristics were summarizedwere analyzed. Result: 12 patients with right hemicolon cancer and 18 patients with sigmoid colon cancer underwent RCME with the Micro Hand S robot system. During the study period, the median operative duration was 209 (range, 180-255) min, and the median estimated blood loss volume was 35 (range, 25-75) ml. The median number of lymph nodes harvested was 42 (21-77), and the median postoperative hospital stay was 5 (range, 4-7) days. According to the Clavien-Dindo classification, there were no severe complications except for 7 cases of grade I complications and 5 cases of grade II complications. The conversion rate for all operations was 0%. There were no cases of 30-day readmission or 30-day mortality. Conclusion: Clinical application of domestically produced Chinese minimally invasive surgical robot system “Micro Hand S ” in selected colon cancer patients is technically feasible and safe.

Background: The Micro Hand S robot is the first domestically produced surgical robot that has entered clinical use in China, and this is the first report of its application in colon cancer.Objective: This study aimed to validate the safety and efficacy of the domestically produced Chinese minimally invasive Micro Hand S surgical robot system in complex surgery, such as robotic complete mesocolic excision (R-CME).Methods: From March 2018 to December 2018, 30 patients with right hemicolon cancer underwent R-CME with the Micro Hand S robot system. The operative findings, morbidities, oncological findings and unique characteristics were summarizedwere analyzed.Result: 12 patients with right hemicolon cancer and 18 patients with sigmoid colon cancer underwent RCME with the Micro Hand S robot system. During the study period, the median operative duration was 209 (range, 180-255) min, and the median estimated blood loss volume was 35 (range, 25-75) ml. The median number of lymph nodes harvested was 42 (21-77), and the median postoperative hospital stay was 5 (range, 4-7) days. According to the Clavien-Dindo classification, there were no severe complications except for 7 cases of grade I complications and 5 cases of grade II complications. The conversion rate for all operations was 0%. There were no cases of 30-day readmission or 30-day mortality. Conclusion: Clinical application of domestically produced Chinese minimally invasive surgical robot system “Micro Hand S ” in selected colon cancer patients is technically feasible and safe.

STRAS (Single access Transluminal Robotic Assistant for Surgeons) is a flexible robotic system based on the Anubis® platform of Karl Storz for application to intra-luminal surgical procedures. It consists of three cable-driven systems, one endoscope serving as guide and two inserted instruments. The flexible and bendable instruments have three degrees of freedom and can be teleoperated by a single user via two specially designed master interfaces. In this research, a pair of specific sensor gloves, which ergonomically fit to the master handles of the system was designed and the forces applied by one expert and one novice user during system-specific task execution in a simulator task (4-step-pick-and-drop) were compared. The results show that user expertise is not only reflected by shorter task execution times but also, more importantly, by specific differences in handgrip force profiles for specific sensor locations on anatomically relevant parts of the fingers and hand controlling the surgical instruments of the robotic master/slave system.

This paper aims to study the surface homogenization and integrity of Ti-6Al-4V alloy by longitudinal-torsional coupled ultrasonic vibration assisted ball-end milling. A method of continuous processing between the flat surface and freeform surface connection is proposed by using ultrasonic vibration assisted ball-end precision milling, during this process, it is not necessary to exchange the cutting tool. The way has been explored for changing the homogenization of surface on Ti-6Al-4V by ultrasonic vibration-assisted milling (UVAM). Cutting experiments employing three parameters, cutting speed, feed rate and depth of cut and two types of machining forms using ball-end milling with UVAM and conventional milling (CM) respectively. The high frequency cutting force, finished surface roughness, topography and residual stresses on the surface and tool wear have been measured by advanced instruments. Particularly, adopting the high frequency cutting force measurement system, it is concluded cutting force in ball-end milling decreased significantly using UVAM as against CM. Moreover, the surface roughness by UVAM with ball-end milling is much better than the CM at a high cutting speed. However, an opposite trend is observed at a low cutting speed. Especially, there is a steep decrease from Ra 0.828 μm average value at 4000 rpm to Ra 0.129 μm average value at 5000 rpm. At the same time, the homogenization of surface roughness and residual stresses decrease significantly in UVAM as compared to which in CM when taking the transversal-longitudinal ratio into consideration. Cutting experiments and measuring results are demonstrated the validity and feasibility of UVAM with ball-end milling, and this method enjoys significant advantages compared to CM process.

Spherical microparticles of TiO₂ were synthesized by the ionic liquid-assisted solvothermal method at different reaction time (3, 6, 12 and 24h). The properties of the prepared photocatalysts were investigated by means of UV-vis diffuse-reflectance spectroscopy (DRS), BET surface area measurements, scanning electron microscopy (SEM), X-ray diffraction analysis (XRD), and X-ray photoelectron spectroscopy (XPS). The results indicated that the efficiency of phenol degradation was related with a time of the solvothermal synthesis as determined for TiO₂_EAN(1:1)_24h sample. Microparticles of TiO₂_EAN(1:1)_3h formed during the only 3h of synthesis time revealed really high photoactivity under visible irradiation – 75%. This value increased to 80% and 82% after 12h and 24h, respectively. The photoactivity increase was accompanied by the increase of the specific surface area thus pores size, as well as ability to absorb UV-vis irradiation. The high efficiency of phenol degradation of IL-TiO₂ photocatalysts was ascribed to the interaction between the surface of TiO₂ and ionic liquid components (carbon and nitrogen).

In this paper, a novel permanent magnet-assisted synchronous reluctance machine (PMASynRM) with rare-earth PMs and ferrite magnets is proposed. The performance of PMASynRM is discussed with respected to the different magnet ratio of rare-earth PMs and ferrite magnets. Some characteristics including the flux density, output torque, cogging torque, output power, power factor, torque ripple, loss, efficiency, and demagnetization are calculated by 2-D finite element analysis (FEA). The analysis results show that the excellent performance can be obtained by using hybrid magnet of rare-earth PMs and ferrite magnets with the suitable magnet ratio, and provide some desirable cost-performance trade-off.

Unmanned aerial vehicle (UAV) systems are widely used in many forest-related fields owing to their cost-intensive and precise surveying technology. This study classified erosion susceptibility (ES) in a timber harvesting area using machine learning (ML) and statistical approaches. In dataset generation for the training and testing process, the digital surface model (DSM) of difference (DoD) for July–June was utilized as a dependent variable, and six terrain maps of the DSM for June were used as independent variables. The ES threshold was set at 5 cm for the binary classification of ES pixels while processing using ML (e.g., random forest and extra gradient boost [XGB]) and statistical (e.g., logistic regression) algorithms for model development. The overall accuracy (OA), receiver operating characteristics, and area under the curve (AUC) were calculated for model accuracy and validation. Although the AUC of all models did not appear acceptable (AUC &gt; 0.7), the XGB model showed the best performance regarding time duration, OA, and AUC by 2 h, 64%, and 0.63, respectively. Despite the low AUC and accuracy of the XGB model, the wheel tracks and edges of the operation road were determined to be susceptible areas in the ES map of the XGB.

Drones equipped with thermal cameras have recently become readily available, broadening the possibilities for monitoring wildlife. The European hare (Lepus europaeus) is a nocturnal mammal that is closely monitored in Denmark due to populations declining since the mid-1900s. The limitations of current population assessment methods, such as spotlight counts and hunting game statistics, could be overcome by relying on drone surveys with thermal imaging for population counts. The aim of this study was to investigate the use of a DJI Mavic 2 Enterprise Advanced drone with thermal imaging as a tool for monitoring the Danish hare population. Multiple test flights were conducted over agricultural areas in Denmark in spring 2022, testing various flight altitudes, camera settings, and recording methods. The test flights were used to suggest a method for identifying and counting hare. The applied use of this methodology was then evaluated through a case survey that had the aim of identifying and counting hare over an agricultural area of 242 ha. Hare could be detected with thermal imaging at flight altitudes up to 80 m and it was possible to fly as low as 40 m without observing direct behavior changes. Thermal images taken at these altitudes also provided enough detail to differentiate between species and animal body size proved to be a good species indicator. The case study confirmed the use of thermal imaging based drone surveys to identify hare and conduct population counts, thus, indicating the suggested methodology as a viable alternative to traditional counting methods.

Automation of forest field reference data collection has been an intensive research objective for laser scanning scientists ever since the invention of terrestrial laser scanning more than two decades ago. Recently, it has been proposed that such automated data collection providing both the tree heights and stem curves would require a combination of above-canopy UAV point clouds and terrestrial point clouds. In this study, we demonstrate that an under-canopy UAV laser scanning system utilizing a rotating laser scanner can alone provide accurate estimates of the canopy height and the stem volume for the majority of the trees in a boreal forest. To this end, we mounted a rotating laser scanner based on a Velodyne VLP-16 sensor onboard a manually piloted UAV. The UAV was commanded with the help of a live video feed from the onboard camera of the UAV. Since the system was based on a rotating laser scanner providing varying view angles, all important elements such as treetops, branches, trunks, and ground could be recorded with laser hits. In an experiment including two different forest structures, namely sparse and obstructed canopy, we showed that our system can measure the heights of individual trees with a bias of -20 cm and a standard error of 40 cm in the sparse forest and with a bias of -65 cm and a standard error of 1 m in the obstructed forest. The accuracy of the obtained tree height estimates was equivalent to airborne above-canopy UAV surveys conducted in similar forest conditions. The higher underestimation and higher inaccuracy in the obstructed site can be attributed to three trees with a height exceeding 25 m and the applied laser scanning system VLP-16 that had a limited height measurement capacity when it comes to trees taller than 25 m. Additionally, we used our system to estimate the stem volumes of individual trees with a standard error at the level of 10%. This level of error is equivalent to the error obtained when merging above-canopy UAV laser scanner data with terrestrial point cloud data. Future research is needed for testing new sensors, for implementing autonomous operation inside canopies through collision avoidance and navigation through canopies, and for developing robust methods that work also with more complex forest structure. The results show that we do not necessarily need a combination of terrestrial point clouds and point clouds collected using above-canopy UAV systems in order to accurately estimate the heights and the volumes of individual trees.

Using the Yellow-River-Source National Park (YRSNP) as a study site, an unmanned aerial vehicle (UAV) remote sensing and line transect method was used to investigate the number of wild herbivorous animals and livestock, including the kiang (Equus kiang) and Tibetan gazelle (Procapra picticaudata). A downscaling algorithm was used to generate the forage yield data in YRSNP based on 30 m spatial resolution. On this basis, we estimated the forage–livestock balance, which included both wild animals and livestock, and analyzed the effects of functional zone planning in national parks on the forage–livestock balance in YRSNP. The results showed that the estimates of large herbivore population numbers in YRSNP based on population density in the aerial sample strips, which were compared and validated with statistical data and warm season survey results, indicated that the number of kiangs and Tibetan gazelles in the 2017 cold season was 12900 and 12100, respectively. The number of domestic yaks, Tibetan sheep, and horses was 53400, 76800, and 800, respectively, and the total number of sheep units was 353200. The ratio of the number of large wild herbivores and livestock sheep units was 1:5; Large wild herbivores have different preferences for functional zones, preferring ecological restoration areas consisting mainly of degraded grassland; The grazing pressure indices of the core reserve areas and ecological restoration areas were 0.168 and 0.276, respectively, indicating that these two regions still have high grazing potential. However, the grazing pressure index of the traditional utilization areas was 1.754, indicating that these grasslands are severely overloaded; After the planning and implementation of functional zones, the grazing pressure index of YRSNP was 1.967. Under this measure, the number of livestock was not reduced and the grazing pressure nearly doubled, indicating that forage–livestock conflict has become more severe.

This article proposes the use of a multi-scale and multi-sensor approach to collect and modelling 3D data concerning wide and complex areas in order to obtain a variety of metric information in the same 3D archive, based on a single coordinate system. The employment of these 3D georeferenced products is multifaceted and the fusion or integration among different sensors data, scales and resolutions is promising and could be useful for the generation of a model that could be defined as hybrid. The correct geometry, accuracy, radiometry and weight of the data models are hereby evaluated comparing integrated processes and results from Terrestrial Laser Scanner (TLS), Mobile Mapping System (MMS), Unmanned Aerial Vehicle (UAV), terrestrial photogrammetry, using Total Station (TS) and Global Navigation Satellite System (GNSS) as topographic survey. The entire analysis underlines the potentiality of the integration and fusion of different solutions and is a crucial part of the “Torino 1911” project whose main purpose is mapping and virtually reconstructing the 1911 Great Exhibition settled in the Valentino Park in Turin (Italy).

In this paper, firstly, some questionable formulas and conceptual oversights of previous reduced sigma set unscented transformation (UT) methods are revised through theoretical analysis. Then the revised UT methods based Kalman filters are used in a GPS/INS tightly-coupled system. The Kalman filter flows are the kind of square-root, since the square-root unscented Kalman filters (SRUKFs) can guarantee the stability of the system. By using the reduced sigma set SRUKFs (which contain simplex sigma set square-root unscented Kalman filter (S-SRUKF), spherical simplex sigma set square-root unscented Kalman filter (SS-SRUKF) and minimum sigma set square-root unscented Kalman filter (M-SRUKF)), the computation cost is greatly saved compared with the standard SRUKF, while the accuracy of the GPS/INS tightly-coupled system still maintained. The structure of the GPS/INS tightly-coupled system is in the form of error state, and the time updates of the state and the state covariance of SRUKFs are directly estimated without using UT, thus the computational time is also greatly saved. The pseudo-satellite is introduced to aid the system when the observation information is deficient, for example, when the GPS signal is deficient in the maneuver environment. By using the pseudo-satellite, the optimal performance of the system is guaranteed. Experiment of unmanned aerial vehicle (UAV) showed that the pseudo-satellite aided mechanism worked well.

Digital health has added numerous promising solutions to enhance the health and wellness of people with neurocognitive disorders (NCDs) and their informal caregivers: (1) Background: It is important to get a comprehensive view of currently available technologies, their outcomes, and conditions of success to inform recommendations regarding digital health solutions for people with NCDs and their caregivers. This environmental scan was performed to identify the features of existing digital health solutions relevant to the targeted population. This work reviews currently available digital health solutions and their related characteristics to develop a decision support tool for older adults living with mild or major neurocognitive disorders and their informal caregivers. This knowledge will inform the development of a decision support tool to assist older adults and their informal caregivers in their search for adequate digital health solutions according to their needs and preferences, based on trustable information.; (2) Methods: We conducted an environmental scan to identify digital health solutions from a systematic review and targeted searches in grey literature covering the regions of Canada and Europe. Technological tools were scanned based on a preformatted extraction grid. We assessed their relevance based on selected attributes and summarized findings; (3) Results: We identified 100 available digital health solutions. The majority (56%) were not specific to NCDs. Only 28% provided scientific evidence of their effectiveness. Remote patient care, movement tracking, and cognitive exercises were the most common purposes of digital health solutions. Most solutions were presented as decision aid tools, pill dispensers, apps, web, or a combination of these platforms. (4) Conclusions: This environmental scan allowed the identification of current digital health solutions for older adults with mild or major neurocognitive disorders and their informal caregivers. Findings from the environmental scan highlight the need for additional approaches to strengthen digital health interventions for the well-being of older adults with mild and major NCDs and their informal and formal healthcare providers.

This study deals with the computational analysis of the kinetic processes of a microbial electrolysis cell assisted-anaerobic digestion (MEC-AD) treating raw-waste activated sludge (WAS), comparatively with a conventional AD, as well as the effect of the Organic Loading Rate (OLR) on the system’s performance. The aim was to derive a single kinetic and mathematical model for the study of the MEC-AD, using the ADM1 framework, which can be utilized to extract the effect of an applied potential on the kinetics of AD. The experimental data were obtained from the long-term, continuous operation of two identical reactors (an AD and a MEC-AD), which were operated at different OLRs (1.1, 1.7 and 2.9 gCOD/(L*d)). The results showed that the MEC-AD yielded improved biomass yields, substrate consumption kinetics and 1st order disintegration kinetics, with a predominant contribution to disintegration of complex particulates, comparatively with the AD. Moreover, it enabled operation at higher OLRs (achieving the highest divergence from the AD at the OLR of 4.14 gCOD/(L*d)), therefore accelerating sludge treatment, as well as an improved performance at an increased solids retention time (SRT). These findings can serve as a quantitative guide for the effects of the operating parameters on the raw-WAS-fed MEC-AD performance.

In this review, we focus on a small section of the extensive literature that deals with the materials containing pristine defective CNs and those incorporated in the hybrid materials. We will discuss only those topics that focus on structural defects related to the introduction of perturbation into the surface topology of a nanostructure. We focus mainly on the method using microwave (MW) irradiation, which is a powerful tool for synthesizing and modifying carbon-based solid materials. In addition, the simplicity of the technique, economy, and the possibility of conducting the reaction in solvents and solid phase, in the presence of components of different chemical nature, allows use in various combinations. In this review, we will emphasize the advantages of synthesis using MW-assisted heating and indicate the influence of the structure of the obtained materials on their physical and chemical properties. We will also highlight the role of the occurrence of defects in the carbon material and the implication in designing their properties and applications.

Computer and Smart Device-assisted Learning (CSDL) has gained increasing attention from educational researchers and practitioners in recent years. However, it remains controversial whether student can benefit from CSDL and what moderator could affect the impact of CSDL. Within the specific context of Korea, where the interest in digital education is steadily increasing, the number of empirical studies exploring the causal effect of CSDL remains relatively scarce. The primary objective of this empirical study was to investigate the impact of CSDL on students' academic achievement in Korea. To achieve this objective, a two-way fixed effect model was employed, utilizing a panel dataset spanning three years derived from the 'Korean Education Longitudinal Study 2013'. The findings revealed a significant positive impact of CSDL on students’ Mathematics achievement. Notably, higher income levels, increased availability of computer resources provided by schools, and the implementation of more individualized education were identified as factors that moderate the effect of CSDL on students' achievement levels in Korean and English subjects. These findings underscore the need for an approach that optimizes the educational benefits of CSDL by considering subject-specific characteristics. Furthermore, this study highlights the importance of allocating educational resources, such as computers and smart devices, and integrating individualized educational activities within the classroom environment.

This review article is aimed at exploring the possibility of developing an integrated approach in the management of the different needs of endometrial cancer (EC) patients seeking to become pregnant. Life preservation of the woman, health preservation of the baby, a precocious and – as much as possible – minimally invasive characterization of the health and fertility parameters of the patient, together with the concerns regarding the obstetric, neonatal, and adult health risks of the children conceived via assisted reproduction techniques (ART) are all essential aspects of the problem to be taken into consideration, yet the possibility to harmonize such needs through a concerted integrated approach is still highly challenging. This article aims to illustrate the main features of EC and how it affects the normal physiology of pre-menopausal women. Then, we focus on the prospect for a miR-based, molecular evaluation of patient health status, including both EC early diagnosis and staging and, similarly, the receptivity of the woman, discussing the possible evaluation of both aspects using a single specific panel of circulating miR in the patient, thus allowing a relatively fast, non-invasive way to perform such testing with a significantly reduced margin of error. Finally, the ethical and legal/regulatory complexities arising from such innovative techniques require not only a risk-benefit analysis; respect for patient autonomy and equitable health care access allocation are fundamental issues as well.

Geometrical assessments of human skull have been done based on the anatomical landmarks. Automatic detection of the landmarks, if developed, will be a great help not only medically, but also anthropologically. An automated system with multi-phased deep learning networks to predict three-dimensional coordinate values of cranio-facial landmarks, was developed. From a publicly available database, computed tomography images of craniofacial area were obtained. They were digitally reconstructed into three-dimensional models. Sixteen anatomical landmarks were plotted on each of the models and coordinate values of them were recorded. Three-phased regression deep learning networks were trained respectively with 90 training datasets. For evaluation, 30 testing datasets were employed. Three-dimensional error for the first phase, testing 30 data, was 11.60 pixels in average. (1 pixel = 500 / 512 mm) For the second phase, it was significantly improved to 4.66 pixels. For the third phase, it was significantly progressed to 2.88. This was comparable to the gaps between the landmarks, plotted by two experienced practitioners. Our proposing method of multi-phased prediction, coarse detection first and narrowing down the detection area, may be a possible solution, within the physical limitation of memory and computation.

Age-in-place can reduce the progress of dementia syndrome and improve the quality of life of the sufferers and their families. This work proposes an innovative information home support system to be established at the houses of people suffering from dementia. The main innovation of the system are its transparent character that overcomes the need for training of the sufferer, as well as the exploitation of a well-known technique for dementia, namely music therapy. It addresses the need of people suffering from dementia as well as their familiars to be recognized by them and have better interaction and collaboration. The system offers a ubiquitous recognition system, just by using smart devices like smart-phones or smart-wristbands. When a familiar person is detected in the house, then a sound file is reproduced on smart speakers placed in the house, in order to trigger the memory, based on the principles of music therapy. The system reproduced the appropriate time at 100% of the cases and the benefits of music therapy are evident daily. To the best of the authors' knowledge, this is the first system of its kind ever reported in the literature.

This study was designed for the first time to improve phenolic yield and antioxidant activity of ultrasonic-assisted extraction from Acer truncatum leaves (ATL) using response surface methodology, and phenolic composition in ATL extracted under the optimized condition were characterized by UPLC-QTOF-MS/MS. Solvent and extraction time were selected based on preliminary experiments, and a four-factors-three-levels central composite design was conducted to optimize solvent concentration (X₁), material-to-liquid ratio (X₂), ultrasonic temperature (X₃) and power (X₄) for an optimal total phenol yield (Y₁) and DPPH• antioxidant activity (Y₂). The results showed that the optimal combination was ethanol: water (v:v) 66.21%, material-to-liquid ratio 1:15.31 g/mL, ultrasonic temperature 60 °C, power 267.30 W, and time 30 min with three extractions, giving a maximal total phenol yield of 7593.62 mg gallic acid equivalent /100 g d.w. and a maximal DPPH• antioxidant activity of 74241.61 μmol Trolox equivalent/100 g d.w.. Furthermore, 22 phenolics were first identified in ATL extract obtained under the optimized conditions, indicating that gallates, gallotannins, quercetin, myricetin and chlorogenic acid derivatives were the main phenolic composition in ATL. What’s more, a gallotannins pathway existing in ATL from gallic acid to penta-O-galloyl-glucoside was interpreted. All these results provided practical information aiming at full utilization of phenolics in ATL, together with fundamental knowledge for further research.

Urban tree classification is pivotal in urban planning and management, facilitating informed decision-making processes. In this study, we introduce a novel data presentation method termed Pseudo Tree Crown, designed to enhance the accuracy and efficiency of urban tree classification. Leveraging the latest advancements in artificial intelligence (AI), we employ a state-of-the-art classification scheme, PyTorch, to maximize the accuracy of tree classification. Our results demonstrate a robust classification accuracy of over 95% from high spatial resolution imagery from Unmanned Aerial Vehicle (UAV), underscoring our proposed approach’s effectiveness. Moreover, the adaptability of our method renders it applicable to various study areas, highlighting its versatility and potential for widespread implementation in urban planning and management initiatives.

This paper presents the second stage of a tandem fixed wing unmanned aerial vehicle (UAV) aerodynamic development. In the initial stage, the UAV was optimized analyzing its characteristics only in symmetrical flight conditions. Posted requirements were that both wings should produce relevant positive lift, the initial stall must occur on the front wing first, the center of pressure should be close to the center of gravity, while longitudinal static stability should be in the optimum range. Computational fluid dynamics (CFD) analyses were performed, where applied calculation model was derived from the authors’ previous successful projects. The eight version TW V8 has satisfied all longitudinal requirements. Lateral-directional CFD analyses of V8 showed that the ratio of the lateral and directional stability at the nominal cruising regime was optimal, but both lateral and directional static stabilities were too high. On further development versions the lower vertical tail was eliminated, negative dihedral was implemented on the front wing, and four inverted blended winglets were added. Version TW V14 has largely improved lateral and directional stability characteristics, while their optimum ratio at cruising regime was preserved. Longitudinal characteristics were also well preserved. Maximum lift coefficient and lift-to-drag ratio were increased, compared to the V8.

To address the trajectory tracking issue for quadrotors working under the influence of external disturbances, a control scheme is designed for position and attitude trajectory tracking. Firstly, the quadrotor dynamic model is derived for control design. Secondly, adaptive integral backstepping control (AIBS) is employed in the position loop in which adaptive estimation is used to estimate the upper bounds of disturbances. Subsequently, a new adaptive backstepping fast nonsingular integral terminal sliding mode control (ABFNITSM) is proposed to follow desired Euler angles. The intro-duction of fast nonsingular terminal sliding mode and integral element is to realize fast convergence and accurate tracking. Dead zone technique is applied to minimize estimation errors. Besides, a saturation function is utilized to eliminate chattering phenomenon. Finally, simulation experiments are conducted under the Simulink environment. The proposed control is verified by comparing it with traditional integral terminal sliding mode control (ITSM) and integral backstepping control (IBS).

Precision farming, a labor-saving and highly productive management, is gaining popularity as the number of farmers declines in contrast to the increasing global food demand. However, it requires more efficient crop phenology observation and growth monitoring. One measure is the Leaf Area Index (LAI), which is essential for estimating biomass and yield, but its validation requires destructive field measurements. Remote sensing offers a non-destructive and effective method for ground- and UAV-based field observations. Thus, in this study, a method for indirect estimation of LAI was investigated using ground and UAV observation data. A weekly plant survey was done to measure the plant height, above-ground biomass, and light intensity. Furthermore, images from ground-based and UAV-based cameras were acquired to generate NDVI and the canopy height (CH), respectively. Using the canopy photosynthetic model, derived from Lambert-Beer’s law, the daily biomass was estimated by applying the weekly estimated LAI using CH, and the observed light intensity data as input. The results demonstrated the possibility of quantitatively estimating the daily growth biomass of rice plants, including its spatial variation. The near-real-time estimation method of rice biomass by integrating observation data at fields with numerical models can be applied to the management of major crops.

This paper aims at trying to answer the question of whether a low cost drone equipped with a regular camera can serve as a simple device to estimate the size of objects. Ad-ditionally, it assesses if the accuracy of measurement is good enough for using a drone for measurements, relying solely on GPS position and camera. A review of the literature pertaining to ground object measurements was conducted. The availability of such in-struments was evaluated in terms of purchase and rental costs, the number of instru-ments on the market, and the time to obtain them. The most common measurement methods were considered and their unit costs were reviewed. The cost of professional surveying and measuring equipment was compared to the possibility of using low-cost, non-commercial drones to measure objects and surfaces. The quality of the images ob-tained was compared with high-resolution satellite systems. Is an ordinary drone with a standard camera suitable for length measurement without professional measuring equipment? Should the results be considered only in the category of size estimation?

The effective integration of aerial remote sensing data and ground multi-source data has always been one of the difficulties of quantitative remote sensing. A new monitoring mode is designed which installs the hyperspectral imager on the UAV and places a buoy spectrometer on the river. Water samples are collected simultaneously to obtain in situ assay data of total phosphorus, total nitrogen, COD, turbidity and chlorophyll during data collection. The cross correlogram spectral matching (CCSM) algorithm is used to match the data of the buoy spectrometer with the UAV spectral data to reduce the UAV data noise significantly. An absorption characteristics recognition algorithm (ACR) is designed to realize a new method for comparing UAV data with laboratory data. This method takes into account the spectral characteristics and the correlation characteristics of test data synchronously. It is concluded that the most accurate water quality parameters can be calculated by using the regression method under five scales after the regression tests of multiple linear regression method (MLR), support vector machine method (SVM) and neural network (NN) method. This new working mode of integrating spectral imager data with point spectrometer data will become a trend in water quality monitoring.

Low-cost miniature hyperspectral and thermal cameras onboard lightweight unmanned aerial vehicles (UAV) bring new opportunities for monitoring land surface variables at unprecedented fine spatial resolution with acceptable accuracy. This research applies hyperspectral and thermal imagery from a drone to quantify upland rice growth and water use efficiency (WUE) after biochar application in a Costa Rican dry region. The field flights were conducted over two experimental groups with bamboo biochar and sugarcane biochar amendments and one control group without biochar application. Rice canopy biophysical variables were estimated by inversion of a canopy radiative transfer model on hyperspectral reflectance. Variations in gross primary production (GPP) and WUE across treatments were estimated from the normalized difference vegetation index (NDVI), canopy chlorophyll content (CCC), and evapotranspiration. We found that GPP was increased by 41.9±3.4 % when using bamboo biochar and 17.5±3.4 % when using sugarcane biochar, which was probably due to higher soil moisture in the biochar-amended plots and led to significantly higher WUE by 40.8±3.5 % in bamboo biochar and 13.4±3.5 % in sugarcane biochar. This study demonstrated the use of hyperspectral and thermal imagery from drone to provide indicators for quantifying biochar effects on tropical dry cropland by integrating with ground point samples and physical models.

Foliar fungal diseases in tomatoes include early blight (Alternaria linariae), Septoria leaf spot (Septoria lycopersici), and late blight (Phytophthora infestans) which is oomycetes. These are one of the significant production constraints in tomatoes. We describe the etiology, host range, distribution, symptoms, and disease cycle to understand the biology followed by management practices emphasizing the resistance breeding approach for these diseases. In crop improvement efforts, we provide an analytical review, including conventional and molecular methods for improving this disease resistance. Modern breeding tools, including genomics, genetic transformation, and genome editing, can be used to improve these traits. There is a good possibility of using these tools in the future to improve these traits.

Our wellbeing is greatly influenced by our childhood and adolescence, and the relationships that we form during those phases of our development. The human-dog bond started thousands of years ago. The higher prevalence of dog ownership around the world, especially in households including children along with the growing number of people studying dogs most likely explain the growing literature focusing on child-dog interactions. We review the potential effects of child-dog interactions on the physical, mental, and social wellbeing of both species. A scoping search of the SCOPUS database found several hundred documents meeting selection criteria. It allowed us to define the numerous ways in which children and dogs can interact, be it neutral (e.g., sharing a common area), positive (e.g., petting), or negative (e.g., biting). Then, we found evidence for an association between interacting with dogs during childhood and an array of health and mental benefits like stress relief and the development of empathy. Walking a dog and playing with one are perfect physical activity opportunities. Additionally, interacting with a dog can help lower stress and may have a role in the development of empathy. Nonetheless, a number of detrimental outcomes have also been identified in both humans and dogs. Children are the most at-risk population regarding dog bites and dog-borne zoonoses, which may lead to a subsequent fear of dogs or even death. Moreover, pet bereavement is generally inevitable when living with a canine companion and should not be trivialized. In terms of dogs, children sometimes take part in caretaking behaviors toward them which include going on walks. They are opportunities for dogs to relieve themselves outside, but also to exercise and socialize. In contrast, a lack of physical activity can lead to the onset of obesity. Dogs may present greater levels of stress when in the presence of children. Finally, the welfare of assistance, therapy, and free-roaming dogs remains underexplored. Overall, the study of the effects, positive as well as negative, on both species still requires further development. We call for more longitudinal studies and hope for cross-cultural research in the future in order to better understand the impact child-dog interactions might have.

Eating disorders (EDs) are serious, life-threatening psychiatric conditions associated with physical and psychosocial impairments, as well as high morbidity and mortality. Given the chronic refractory nature of EDs and the paucity of evidence-based treatments, there is a pressing need to identify novel approaches for this population. The noncompetitive N-methyl-D-aspartate receptor (NMDAr) antagonist, ketamine, has recently been approved for treatment-resistant depression, exerting rapid and robust antidepressant effects. It is now being investigated for several new indications, including obsessive-compulsive, post-traumatic, and substance use disorder; and shows transdiagnostic potential for EDs, particularly among clinical non-responders. As such, the aim of this review is to examine contemporary findings on the treatment of EDs with ketamine, whether used as a primary, adjunctive, or combination psychopharmacotherapy. Avenues for future research are also discussed. Overall, results are encouraging and point to therapeutic value, yet are limited to case series and reports on anorexia nervosa. Further empirical work is thus needed to explore ketamine efficacy across ED subgroups; establish safety profiles and optimize dosing; and develop theory-driven, targeted treatment strategies at the individual patient level.

Combining Matrix-Assisted Laser Desorption/Ionization Time-of-Flight (MALDI-TOF) spectra data and artificial intelligence (AI) has been introduced for rapid prediction on antibiotic susceptibility test (AST) of S. aureus. Based on the AI predictive probability, the cases with probabilities between low and high cut-offs are defined as “grey zone”. We aimed to investigate the underlying reasons of unconfident (grey zone) or wrong predictive AST. A total 479 S. aureus isolates were collected, analyzed by MALDI-TOF, and AST prediction, standard AST were obtained in a tertiary medical center. The predictions were categorized into the correct prediction group, wrong prediction group, and grey zone group. We analyzed the association between the predictive results and the demographic data, spectral data, and strain types. For MRSA, larger cefoxitin zone size was found in the wrong prediction group. MLST of the MRSA isolates in the grey zone group revealed that uncommon strain types composed 80%. Amid MSSA isolates in the grey zone group, the majority (60%) was composed of over 10 different strain types. In predicting AST based on MALDI-TOF AI, uncommon strains and high diversity would contribute to suboptimal predictive performance.

Nanometer-curved surfaces are abundant in biological systems as well as in nano-sized technologies. Properly functionalized polymer-grafted nanoparticles (PGNs) adhere to surfaces with different geometries and curvatures. This work explores some of the energetic and mechanical characteristics of the adhesion of PGNs to surfaces with positive, negative and zero curvatures using Coarse-Grained Molecular Dynamics (CGMD) simulations. Our calculated free energies of binding of the PGN to the curved and flat surfaces as a function of separation distance show that curvature of the surfaces critically impacts the adhesion strength. We find that the flat surface is the most adhesive, and the concave surface is the least adhesive surface. This somewhat counterintuitive finding suggests that while a bare nanoparticle is more likely to adhere to a positively curved surface than a flat surface, grafting polymer chains to the nanoparticle surface inverts this behavior. Moreover, we studied the rheological behavior of PGN upon separation from the flat and curved surfaces under external pulling force. The results presented herein can be exploited in drug delivery and self-assembly applications.

Nymphaea lotus L. is the medicinal plant that has long been used as food, cosmetic and traditional medicines in Africa and Asia since the ancient time. Its flavonoids and other interesting phytochemical compounds from rhizome, leaf, and the whole flowers have been reported in the previous published researches. However, stamens, which are essential for reproductive functions, may also represent new alternative sources of potential antioxidant flavonoids as investigated in this study. The innovative green chemistry method i.e. ultrasound-assisted extraction (USAE) as well as macroporous resin (MPR) purification procedure were employed in this current research. The optimal ultrasound-assisted extraction condition is 90 % (v/v) aqEtOH with 34.65 khz ultrasonic frequency and 46 minutes of extraction time. Comparing with heat reflux extraction (HRE) conventional method, the significant gain of 1.35 total flavonoids content was obtained using optimized USAE conditions, jumping to 2.80 when this USAE associated with MPR purification. Not only in vitro cell free antioxidant activity of N. lotus stamen extracts, but also in cellulo antioxidant investigation using yeast model showed the same trend to indicate that the best antioxidant flavonoid can be found in USAE coupled with MPR purification. Moreover, the key antioxidant genes expression in yeast model such as SIR2 and SOD2 were also expressed at the highest level in yeast cell treated with the extract from USAE together with MPR purification. Consequently, it can be seen that the USAE combined with MPR purification can help to enhance the flavonoids antioxidant potential of the stamens extract from this medicinal species.

Background: Animal-assisted therapy has positive effects on cognitive function, depression, performance ability, and social functioning in elderly patients. The aim of this study was to evaluate the effects of rearing pet insects on the cognitive function of healthy elderly participants, with fMRI (functional magnetic resonance imaging) being used for this purpose. Methods: Community-dwelling elderly women (≥60 years) with normal cognitive function were enrolled during April 2015. They were randomized at a 1:1 ratio into two groups: insect-rearing and control (n=16) groups, with the insect-rearing group being further classified into two groups for analysis according to the subjects’ scores in the Wisconsin Card Sorting Test, WCST) at the first fMRI: insect-rearing group I with a relatively high score (n=13), and insect-rearing group II with a relatively low score (n=6). All subjects were educated on a healthy lifestyle for better cognitive function at every visit, and the insect-rearing groups received and reared crickets as pet insects. The fMRI was performed at baseline and after 8 weeks using the WCST as a stimulus. The WCST consisted of two variations, a high level baseline (HLB) and semi-WCST version. Results: There were no significant differences in the baseline characteristics among the three groups. There was a significant difference accuracy of the HLB–semi-WCST (p<0.05) in insect-rearing group II after 8 weeks from the baseline test. In the fMRI analysis involving the WCST reaction test, increased activation was observed in the right dorsal lateral prefrontal cortex and parietal cortex in insect-rearing group II when the semi-WCST, rather than the HLB, was performed. There were no significant differences in the other groups. Conclusion: The rearing of pet insects as an animal-assisted therapy is cost-effective, easy, and occupies little space. In this study, it showed positive effects on executive functions and performance improvement in elderly women. Further larger studies on the effects of pet insects on cognitive function are warranted.

Background: Video assisted thoracoscopic surgery (VATS) has become the recommended approach for treatment of resectable lung cancer. However, no large randomized clinical trial has been conducted formally comparing surgical resections completed by VATS to those done by open thoracotomy (OT) in low volume centers. The current study sought to assess differences in recurrence-free survival (RFS), overall survival (OS), positive margins and postoperative length of stay (LOS) between VATS and OT lobectomies in our center. Method: A single institution retrospective chart review from May 2005 through May 2015 was conducted. All patients diagnosed with stage I through III lung cancer who underwent surgical resection were selected. Patient and tumor characteristics recorded included age at diagnosis, sex, tobacco use, tumor location (side and lobe), stage, size and receipt of chemotherapy or radiotherapy. Chis-square and Wilcoxon-Mann-Whitney tests were used to compare demographics, tumor characteristics and LOS. Multiple logistic and Cox regression analyses were used to compute relative risk (RR) for positive margins and mortality hazard ratios along with 95 percent confidence intervals (95%CI), respectively. Results: Of the 235 patients, 101 subjects had VATS while OT was performed in 134 patients. Age at diagnosis, sex, tobacco use, tumor location, and size were comparable for VATS and OT. No significant difference was observed in the relative risk of positive margins for VATS versus OT, RR = 0.56 (95%CI = 0.26, 1.05). However, VATS had shorter median LOS compared to OT (4 vs. 6 days, respectively), p = 0.002. A comparison of VATS versus OT showed no significant difference in the risk of recurrence, HR = 1.21 (95%CI = 0.74, 2.00), or death, HR = 1.34 (95%CI = 0.88, 2.06), in the intent-to-treat population. Similarly, no significant differences in recurrence or mortality risk were observed between VATS versus OT for analyses conducted separately for each cancer stage group or those limited to patients with negative margins. Conclusion: Our study indicates that compared to OT, VATS leads to shorter LOS while achieving comparable margins status, recurrence-free and overall survival regardless of tumor stage at diagnosis.

The persistent issue of bacterial and fungal colonization of artificial implantable materials and decreasing efficacy of conventional systemic antibiotics used to treat implant-associated infections has led to the development of a wide range of antifouling and antibacterial strategies. This article reviews one such strategy where inherently biologically active renewable resources, i.e. secondary plant metabolites (SPMs) and their naturally occurring combinations (i.e. essential oils) are used for surface functionalization and synthesis of polymer thin films. With a distinct mode of antibacterial activity, broad spectrum of action and diversity of available chemistries, secondary plant metabolites present an attractive alternative to conventional antibiotics. However, their conversion from liquid to solid phase without significant loss of activity is not trivial. Using select examples, this article shows how plasma techniques provide a sufficiently flexible and chemically reactive environment to enable the synthesis of biologically-active polymer-coatings from volatile renewable resources.

Structural self-organizing and pattern formation are universal and key phenomena observed during growth and cluster-assembling of the carbyne-enriched nanostructured metamaterials at the ion-assisted pulse-plasma deposition. Fine tuning these universal phenomena opens access to designing the properties of the growing carbyne-enriched nano-matrix. The structure of bonds in the grown carbyne-enriched nano-matrices can be programmed by the processes of self-organization and auto-synchronization of nanostructures. We propose the innovative concept, connected with application of the universal Cymatics phenomena during the predictive growth of the carbyne-enriched nanostructured metamaterials. We also propose the self-organization approach for increase stability of the long linear carbon chains. The main idea of suggested concept is manipulating by the self-organized wave patterns excitation phenomenon and their distribution by the spatial structure and properties of the nanostructured metamaterial grows region through the new synergistic effect. Mentioned effect will be provided through the vibration-assisted self-organized wave patterns excitation along with simultaneous manipulating by their properties through the electric field. We propose to use acoustic activation of the plasma zone of nano-matrix growing. Interaction between the inhomogeneous electric field distribution generated on the vibrating layer and the plasma ions will serve as the additional energizing factor controlling the local pattern formation and self-organizing of the nano-structures. Suggested concept makes it possible to provide precise predictive designing the spatial structure and properties of the advanced carbyne-enriched nanostructured metamaterials.

Tail-sitters aim to combine the advantages of fixed-wing and rotor-craft, but demand a robust and fast stabilization strategy to perform vertical maneuvers and transitions to and from aerodynamic flight. The research conducted in this work intends to assess the performance of nonlinear control strategies to stabilize the attitude of a X-Vert VTOL aircraft when hovering, comparing existing solutions to applications of Nonlinear Dynamics Inversion (NDI) and its incremental version, INDI. Such controllers are implemented and tuned in simulation in order to stabilize a model of the tail-sitter , complemented by estimation methods that allow to feed back the necessary variables. These estimators and controllers are then implemented in a microcontroller, validating them in a Hardware-in-the-Loop (HITL) scenario, with simple maneuvers in vertical flight. Lastly, the developed control solutions are used to stabilize the aircraft in experimental flight, being monitored by a motion capture system. The experimental results allow to validate the model of the X-Vert and compare the effectiveness of the different control solutions in stabilizing it, with the INDI presenting itself as a more robust control strategy, with better tracking capabilities and less actuator demands.

The use of unmanned aerial aircrafts (UAVs) is governed by strict regulatory frameworks that prioritize safety. To guarantee safety, it is necessary to acquire and maintain situational awareness (SA) throughout the operation. Existing Canadian regulations require pilots to operate their aircrafts in visual line-of-sight. Therefore, the task of acquiring and maintaining SA primary falls to the pilots. However, the development of aerial transport is entering a new era with the adoption of a highly dynamic and complex system known as advanced air mobility (AAM), which involves UAV operating autonomously beyond visual line-of-sight. SA must therefore be acquired and maintained primarily by each UAV through specific technologies and procedures. In this paper, we review these technologies and procedures in order to decompose the SA of the UAV in the AAM. We then use the system modeling language to provide a high-level structural and behavioral representation of the AAM as a system having UAV as its main entity. In a case study, we analyze one of the flagships UAVs of our industrial partner. Results show that this UAV doesn’t have all the technologies and methodologies necessary to achieve all the identified SA goals identified for the safety of the AAM. This work is a theoretical framework intended to contribute to the realization of the AAM, and we also expect to impact the future design and utilization of UAVs.

Tracking and early identification of suspected cases are essential to control and prevent potential COVID-19 outbreaks. One of the most popular techniques used to track this disease is the use of Infrared cameras to identify individuals with elevated body temperatures. However, they are limited by their inability to be implemented in open public settings such as public parks or even outdoor recreational centers. This limits their ability to effectively track possible COVID-19 patients as open public recreational places such as parks, concert venues and other public venues are hotspots for the spreading of the virus. Other technological solutions such as thermal scanners require an individual to perform the actual testing as they are not individual standalone technologies. This method of testing can potentially cause the transmission of the virus between the tester and the individual getting tested. As can be seen, an alternative solution is essential to solving this issue. In this study, we aim to present the system, design and potential scope of a non-invasive system that can diagnose and identify potential COVID-19 patients using thermal and optical images of the individual using drone technology. The proposed system (COVIDRONE) combines multi-modal machine intelligence, computer vision and real-time monitoring to enable scalable monitoring. The system will also involve the use of machine learning algorithms for better and more accurate diagnosis. We envisage that development of such technologies may help in developing technological solutions to combat infectious disease threats in the future pandemics.

Remote sensing is one of the modern methods that have significantly developed over the last two decades and nowadays provides a new means for forest monitoring. High spatial and temporal resolutions are demanded for accurate and timely monitoring of forests. In this study multi-spectral Unmanned Aerial Vehicle (UAV) images were used to estimate canopy parameters (definition of crown extent, top and height as well as photosynthetic pigment contents). The UAV images in Green, Red, Red-Edge and NIR bands were acquired by Parrot Sequoia camera over selected sites in two small catchments (Czech Republic) covered dominantly by Norway spruce monocultures. Individual tree extents, together with tree tops and heights, were derived from the Canopy Height Model (CHM). In addition, the following were tested i) to what extent can the linear relationship be established between selected vegetation indexes (NDVI and NDVIred edge) derived for individual trees and the corresponding ground truth (e.g., biochemically assessed needle photosynthetic pigment contents), and ii) whether needle age selection as a ground truth and crown light conditions affect the validity of linear models. The results of the conducted statistical analysis show that the two vegetation indexes (NDVI and NDVIred edge) tested here have a potential to assess photosynthetic pigments in Norway spruce forests at a semi-quantitative level, however the needle-age selection as a ground truth was revealed to be a very important factor. The only usable results were obtained for linear models when using the 2nd year needle pigment contents as a ground truth. On the other hand, the illumination conditions of the crown proved to have very little effect on the model’s validity. No study was found to directly compare these results conducted on coniferous forest stands. This shows that there is a further need for studies dealing with a quantitative estimation of the biochemical variables of nature coniferous forests when employing spectral data acquired by the UAV platform at a very high spatial resolution.

The amount and spatial distribution of foliage in a tree canopy have fundamental functions in ecosystems as they affect energy and mass fluxes through photosynthesis and transpiration. They are usually described by the Leaf Area Index (LAI) and the Leaf Area Density (LAD), which can be measured through a variety of methods, including voxel-based methods applied to LiDAR point clouds. A theoretical study recently compared the numerical errors arising from different voxel-based estimation methods for Plant Area Density (PAD) based on Beer’s law-based, contact frequency and Maximum-Likelihood Estimation, showing that the bias-corrected Maximum Likelihood Estimator was theoretically the most efficient. However, this earlier study i) ignored wood volumes; ii) neglected vegetation clumping inside the voxel; iii) ignored instrument characteristics in terms of effective footprint, iv) was limited to a single viewpoint. In practice, retrieving LAD from PAD is not straightforward, vegetation is not randomly distributed in volumes of interest, beams are divergent and forestry plots are usually sampled from more than one viewpoint, to mitigate the effect of occlusion. In the present short communication, we extend the previous efficient formulation to actual field conditions to i) account for the presence of both wood volumes and wood hits, ii) rigorously include correction terms for vegetation and instrument characteristics, iii) integrate multiview data. A numerical comparison with other methods commonly used to combine information from different viewpoints led to error reduction, especially in poorly-explored volumes, which are frequent in actual canopies. Beyond its concision, completeness and efficiency, this new formulation -which can be applied to multiview TLS, but also UAV LiDAR scanning - can help reducing errors in LAD estimation.

Human detection from Unmanned Aerial Vehicles (UAV) is gaining popularity in the field of disaster management, crowd counting, people monitoring. Real time human detection from UAV is a challenging task, because of many constraints involved. This study proposes a system for real time detection of humans on videos captured from UAVs addressing three of these constraints namely, flying height, computation time and scale of viewing. The proposed method integrated an android application with a binary classifier based on Haar-features to automatically detect human / non-human class from UAV images. The video frames were parsed and detected humans from image frames were geo-localized and visualized on Google Earth. The performance was evaluated for geo-localization accuracy, computation time and detection accuracy, considering human coverage – pixel size relationship for various heights and scale factor. Based on flying height - human size relationship and tradeoff between detection accuracy vs computation time, the study came up with optimal parameters for OpenCV’s cv2.cascadeClassifier. detectMultiScale function. This paper establishes a strong ground for further research relating to real time human detection from UAV.

UAV network operation enables gathering and fusion from disparate information sources for flight control in both manned and unmanned platforms. In this investigation, a novel procedure for detecting runways and horizons as well as enhancing surrounding terrain is introduced based on fusion of enhanced vision system (EVS) and synthetic vision system (SVS) images. EVS and SVS image fusion has yet to be implemented real-world situations due to signal misalignment. We address this through a registration step to align the EVS and SVS images. Four fusion rules combining discrete wavelet transform (DWT) sub-bands are formulated, implemented and evaluated. The resulting procedure is tested on real EVS-SVS image pairs and pairs containing simulated turbulence. Evaluations reveal that runways and horizons can be detected accurately even in poor visibility. Furthermore, it is demonstrated that different aspects of the EVS and SVS images can be emphasized by using different DWT fusion rules. The procedure is autonomous throughout landing, irrespective of weather. We believe the fusion architecture developed holds promise for incorporation into head-up displays (HUDs) and UAV remote displays to assist pilots landing aircraft in poor lighting and varying weather. The algorithm also provided a basis rule selection in other signal fusion applications.

When the distance between an obstacle and a power line is less than the discharge distance, a discharge arc can be generated, resulting in interruption of power supplies. Therefore, regular safety inspections are necessary to ensure safe operations of power grids. Tall vegetation and buildings are the key factors threatening the safe operation of extra high voltage transmission lines within a power line corridor. Manual or LiDAR based-inspections are time consuming and expensive. To make safety inspections more efficient and flexible, a low-altitude unmanned aerial vehicle remote-sensing platform equipped with optical digital camera was used to inspect power line corridors. We propose a semi-patch matching algorithm based on epipolar constraints using both correlation coefficient and the shape of its curve to extract three dimensional (3D) point clouds for a power line corridor. Virtual photography was used to transform the power line direction from approximately parallel to the epipolar line to approximately perpendicular to epipolar line to improve power line measurement accuracy. The distance between the power lines and the 3D point cloud is taken as a criterion for locating obstacles within the power line corridor automatically. Experimental results show that our proposed method is a reliable, cost effective and applicable way for practical power line inspection, and can locate obstacles within the power line corridor with measurement accuracies better than ±0.5 m.

The Folla Redonda grape is indigenous to the region of Rias Bajas in Galicia, Spain. This grape is distinguished by its characteristic acid flavor and pulp of remarkable coloration. Despite the wine obtained from this grape is highly valued by consumers of this region for its surprising acidic notes and thickness, it is important to note that it is not a variety of Vitis vinifera and its production is not legally regulated. In the present study, an evaluation of the physicochemical properties of the Folla Redonda grape (pH, °Brix, °Bé, density, acidity, sugar content, etc.) as well as its content in bioactive compounds (total polyphenols and anthocyanins) was carried out. Additionally, the antioxidant potential of the extracts obtained from this grape was demonstrated. This study proved the interesting organoleptic characteristics of the grape, along with a high content of compounds of interest and an important antioxidant activity comparable to that of Vitis vinifera grapes. Therefore, the grape's natural consumption and its application in different industries such as nutraceutical or pharmacological would result in an important revaluation of the grape and significant health benefits. In case that the production of wine from this variety is legalized, consumers will not only be able to enjoy a wine with a characteristic dense reddish color and important acid tones, but also with interesting concentrations of bioactive compounds.

The root extracts of Symphytum officinale (comfrey) are commonly used in traditional medicine to treat muscle, joint, skin and bone disorders. However, little information is available on the biomedical functions of comfrey leaves. In this study, sequencing results of Internal Transcribed Spacer and trnL-trnF genes showed that plants purchased from the local market were comfrey and named as S. officinale WL (WL). The optimal extraction conditions of WL leave with the highest extract yield and contents of total phenols and flavonoids by microwave-assisted extraction were identified. The antioxidative and anti-inflammatory activities and possible molecular mechanism(s) of the WL leaf extract (WLE) were evaluated. Furthermore, the major component of WLE was identified as rosmarinic acid by HPLC. Results showed that the optimal extract condition was obtained with 750W microwave power, 50℃, 75% methanol, the solid-to-solvent ratio of 1:10, and 15 minutes. Results of all DPPH, ABTS and superoxide radical scavenging activities, reducing power, ferrous ion chelating activity, and ferric reducing antioxidant power showed high antioxidative capacities of WLE. Furthermore, WLE showed obvious DNA protecting activity. WLE attenuated lipopolysaccharides-stimulated inflammation by suppressing iNOS, COX-2, IL-1β, IL-6, and TNF-α expressions in RAW264.7 macrophages. These attenuations involved in inactivations of lipopolysaccharides-induced NF-κB and MAPK signaling pathways.

Drone imagery has the potential to enrich urban planning and preservation, especially where it converges with the growing creation and use of 3D models. The authors have conducted a systematic literature review of articles published between 2002 and 2022, drawing from reputable academic repositories including Science Direct, Web of Science, and China National Knowledge Infrastructure (CNKI), to identify current gaps in existing research in the application of UAVs to the creation of 3D models in urban planning and preservation. Findings indicate five research shortcomings: limited participation of planning experts, research focus imbalance, lack of usage for special scenarios, lack of integration with smart city planning, and limited interdisciplinary collaboration. The study also acknowledges current limitations with UAV applications and discusses possible countermeasures as well as future prospects.