Manual material handling tasks in industry cause work-related musculoskeletal disorders. Exoskeletons are being introduced to reduce the risk of musculoskeletal injuries. This study investigated the effect of using a passive lumbar exoskeleton in terms of moderate ergonomic risk. Eight participants were monitored by electromyogram (EMG) and motion capture (MoCap) while performing tasks with and without the lumbar exoskeleton. The results showed a significant reduction in the root mean square (VRMS) for all muscles tracked: erector spinae (8%), semitendinosus (14%), gluteus (5%), and quadriceps (10.2%). The classic fatigue parameters showed a significant reduction in the case of the semitendinosus: 1.7% zero-crossing rate, 0.9% mean frequency, and 1.12% median frequency. In addition, the logarithm of the normalized Dimitrov’s index showed reductions of 11.5, 8, and 14% in erector spinae, semitendinosus, and gluteus, respectively. The calculation of range of motion in the relevant joints demonstrated significant differences, but in almost all cases, the differences were smaller than 10. The findings of the study indicate that the passive exoskeleton reduces muscle activity and introduces a minor change of strategies for motion. Thus, EMG and MoCap appear to be appropriate measurements for designing an exoskeleton assessment procedure.

The fields of electronics and information technology have witnessed rapid development during the last decades, providing significant technical support to the field of biological sciences. Radio-Frequency Identification (RFID) technology has been used to automate the monitoring of animal location and behaviors in a wide range of vertebrate and invertebrate species, including social insects such as ants and honey bees (Apis mellifera L.) This technology relies on electromagnetic fields to identify and track transponders attached to objects automatically. Implementing new technologies to serve research purposes could be time-consuming and require technical expertise from entomologists and researchers. Herein, we present a detailed description on how to harness RFID technology to serve honey bee research effectively. We describe how to build and operate a 32-antenna RFID system used to monitor various honey bee behaviors such as foraging, robbing, queen and drone mating, which can be used in other social insects as well. Preliminary data related to queen nuptial flights were obtained using this unit and presented in this study. Virgin queens labeled with ~5mg transponders performed multiple (1-4) nuptial/orientation flights a day (9 am to 5 pm) ranging from 8 to 145 seconds each. Contrary to virgin queens, no hive exit was recorded for mated-queens. At full capacity, this unit can monitor up to 32 honey bee colonies concurrently and is self-sustained by a solar panel to work in remote areas. All materials, hardware and software needed to build and operate this unit are detailed in this study, offering researchers and beekeepers a practical solution and a comprehensive source of information enabling the implementation of RFID technology in their research perspective.

With the depletion of shallow surface resources, the future mining work will develop towards the deep surface, and the objective conditions such as the mining environment will be more complex and dangerous than now, and the requirements for personnel and equipment will be higher and higher. The efficient exploitation of deep space cannot be separated from such mobile and flexible production and transportation equipment as scraper. In the new era, intelligence is the development trend of the LHD, and path tracking control technology is the key to the intelligent LHD, and it is also an urgent problem to be solved for its unmanned driving. This paper describes the realization of the automatic operation function of articulated LHD from two aspects of mathematical model and trajectory tracking control method, and focuses on the research of the path tracking control scheme in the field of unmanned driving, that is, LQR controller. On this basis, the parameters of the LQR controller are optimized by combining different intelligent cluster algorithms to find the optimal solution of the LQR controller.

The safety of people is an important phenomenon nowadays. This importance arises due to the crowded places including subway station, universities, colleges, airport, shopping mall and square, and city squares. Therefore, the development of an effective system based on physical characteristics of crowd layout is of significant demand. In this paper, we proposed a novel automated and intelligent systems for crowd event analysis based on a set of physical elements. For this purpose, we take into account optical flow and spatial-time gradient, contour features, and Gaussian processes. Our method combine these characteristics into a unique model to deal with the challenging problem of crowd event analysis. For evaluating our proposed method, we consider a benchmark dataset and a number of different performance metrics. These analysis demonstrate the robustness and effectiveness of our proposed method.

In tracking-by-detection paradigm for multi-target tracking, target association is modeled as an optimization problem that is usually solved through network flow formulation. In this paper, we proposed combinatorial optimization formulation and used a bipartite graph matching for associating the targets in the consecutive frames. Usually, the target of interest is represented in a bounding box and track the whole box as a single entity. However, in the case of humans, the body goes through complex articulation and occlusion that severely deteriorate the tracking performance. To partially tackle the problem of occlusion, we argue that tracking the rigid body organ could lead to better tracking performance compared to the whole body tracking. Based on this assumption, we generated the target hypothesis of only the spatial locations of person’s heads in every frame. After the localization of head location, a constant velocity motion model is used for the temporal evolution of the targets in the visual scene. Qualitative results are evaluated on four challenging video surveillance dataset and promising results has been achieved.

Accurate detection of players and teams in ice hockey games is crucial to the tracking of individual players on court and team tactical decisions, which is therefore becoming an important task for coaches and other analysts. However, hockey is a fluid sport due to complex dynamics and frequent substitutions by both teams, resulting in various body positions of players. Few traditional player detection models from other team sports take these characteristics into account, especially for the detection of teams without prior annotations. Here, we design a two-phase cascaded Convolutional Neural Network (CNN) model coupling between individual players position information and team uniform colors to hierarchically detect players in ice hockey games. Our model filters most of disturbing information, such as audience and sideline advertising bars, in Phase I, and refines the detection of targeted players in Phase II, which is efficient and accurate with a precision rate of 91.30% and a recall rate of 95.60% for individual players detection, and an average accuracy of 93.05% in team classification from a self-built dataset of collected images in the 2018 Winter Olympics. Meanwhile, we also present results based on the images and real-time detection from broadcasting videos of 2019-20 NHL regular games covering all 31 teams to show the robustness of our model.

Music acoustics is an interdisciplinary field and mathematics is the basis in the music art form. Music and mathematics correlation exist since the inception of music. Various philosophers, scientists, mathematicians and musicians have expressed their views about this relationship. This paper attempts to explore this association with focus on melodic pattern identification. Mathematics in Indian Classical music with raga as the basis and just intonation tuning system is discussed. Indian vocal music clips are used for different pitch estimation algorithms in the experimentation. Harmonic product spectrum and auto-correlation algorithms are tested for accurate pitch estimation. Enhanced auto-correlation function using audio segmentation is compared with other approaches for effective pitch extraction. Results indicate pitch extraction with enhanced auto-correlation function provides accurate results as compared with other approaches tested.

When a rotary machine is running, from which the acquired vibro-acoustic signals enable to reveal its operation status and health condition. The study proposed a DSP-based adaptive angular-velocity Vold-Kalman filtering order tracking (AV2KF_OT) algorithm with an online real-time nature for signal interpretation and machine condition monitoring. Theoretical derivation and numerical implementation of computation schemes are briefly introduced. An online real-time monitoring system based on the AV2KF_OT algorithm, which was implemented through both a digital signal processor and a user interface coded by using LabVIEW, was developed. Two experimental tasks were applied to justify the proposed technique, including (i) the detection of startup on the fluid-induced whirl performed through a journal-bearing rotor rig, and (ii) the separation of close orders from the measured signals of a multifunction transmission-element ball-bearing bench.

This paper presents a new adaptive and optimal algorithm for the trajectory tracking control of a quadrotor using iterative learning algorithm (ILA) and enumerative learning algorithm. Ordinarily the ILA, as an adaptive method, can perform well with PID control to improve the controller’s performance for a nonlinear system. Quadrotors are considered as non-linear and unstable systems which the use of an adaptive and optimal controller can increase its stability and decrease error level. In this method, a PID controller is proposed for the outer and inner control loops of a quadrotor and the ILA is used to adapt PID control gains. Subsequently, an enumerative learning algorithm is used to optimize the learning rates of the ILA. For this purpose, at first, the dynamic model of the quadrotor is acquired. After that, the structure of the inner and outer control loops is defined. In the end, the simulation results for the trajectory tracking control of a quadrotor are demonstrated. Through simulation, it is concluded that as time increases, the performance of the suggested control method in trajectory tracking control becomes better and better and error signals convergence to zero.

Sports video analysis is an interesting and emerging field in the domain of computer vision. It has become a very popular subject among scholars all over the world in the last decade due to the need of automated classification of events such as offsides, in/out situations, goals and so on. The most important problem in sports video analysis is detection and tracking of ball and players. Extraction of court lines is also another important problem since it is necessary in the classification of aforementioned events. In this study, considering some of the previous work on the subject, we develop a method for tracking the ball and players in tennis videos where the camera position and orientation is supposed fixed.

Continuous object tracking in WSNs, such as monitoring of mud-rock flows, forest fires etc., is a challenging task due to characteristic nature of continuous objects. They can appear randomly in the network field, move continuously, and can change in size and shape. Monitoring such objects in real-time generally require tremendous amount of messaging between sensor nodes to synergistically estimate object’s movement and track its location. In this paper, we propose a novel twofold-sink mechanism, comprising of a mobile and a static sink node. Both sink nodes gather information about boundary sensor nodes, which is then used to uniformly distribute energy consumption across all network nodes, thus helping in saving residual energy of network nodes. Numerous object tracking schemes, using mobile sink, have been proposed in the literature. However, existing schemes employing mobile sink cannot be applied to track continuous objects, because of momentous variation of network topology. Therefore, we present in this paper a mechanism, transformed from K-means algorithm, to find the best sensing location of the mobile sink node. It helps to reduce transmission load on the intermediate network nodes situated between static sink node and the ordinary network sensing nodes. The simulation results show that the proposed scheme can distinctly improve life time of the network, compared to one-sink protocol employed in continuous object tracking.

We develop an interactive likelihood (ILH) for sequential Monte-Carlo (SMC) methods for image-based multiple target tracking applications. The purpose of the ILH is to improve tracking accuracy by reducing the need for data association. In addition, we integrate a recently developed deep neural network for pedestrian detection along with the ILH with a multi-Bernoulli filter. We evaluate the performance of the multi-Bernoulli filter with the ILH and the pedestrian detector in a number of publicly available datasets (2003 PETS INMOVE, AFL, and TUD-Stadtmitte) using standard, well-known multi-target tracking metrics (OSPA and CLEAR MOT). In all datasets, the ILH term increases the tracking accuracy of the multi-Bernoulli filter.

Accidents and mishaps in industrial environments like construction, mining, and transport are rampant - mainly due to human negligence and improper monitoring of the workplace. In this paper, we address the safety of workers operating in dangerous environments by improving their situational awareness. According to Occupational health and safety rules, everyone must wear hard hats while on site. Our main idea is to make the hard hats smart by incorporating miniature-sized Doppler radars sensing the users’ surroundings. These Doppler radars are lightweight, rugged, and consume low-power compared to vision-based solutions. This paper discusses the observability of range from Doppler frequency measurements and the magnitude of estimation errors introduced by the human head, walking, and working motions. We present the framework to estimate the position of walls and targets surrounding the worker. For testing, we simulated an indoor environment with randomly moving workers. Experiments showed that once observability conditions are met, human head and walking movements can be handled through added noise in the system. We also present an innovative idea of using two Doppler radars to obtain the estimators’ initial estimates, reducing the estimation error to less than 5cm and convergence time by more than 80

Why do the eyes remain comparatively large whereas the cornea is reduced in most troglobiont mysids? Are there any important organ size-dependent functions served by non-visual eye rudiments? This issue was approached by measuring eye structures in five troglobiont species of Mysida and two Stygiomysida compared with 14 troglophile and 49 trogloxene Mysida species. The Organ of Bellonci (OB) was found in all Mysida and as first records also in Stygiomysida. The length of OBs increased with individual body length and eye length in four examined species: from postnauplioid larvae to adult stage in a troglophile and a trogloxene mysid species examined; and from juveniles to adults in a troglobiont mysid and a troglobiont stygiomysid. At the interspecific level, eye length was on average 26% shorter at a given body length while the OB was 40% longer at a given body length and 54% longer at a given eye length, respectively, in adult troglobionts compared with trogloxene mysids. The OB is clearly proliferating while the cornea is reduced in troglobionts. This points to sensory functions (possibly together with other functions). The sensory pore organ was found in all 15 Mysida species whose eyes were mounted on slides, and a first record of this organ was also found in Stygiomysida.

The orthodontic treatment brings numerous benefits and, in most cases, the benefits outweigh the possible disadvantages. Root resorption (RR) is a common adverse phenomenon associated with orthodontic treatment. This study evaluates the role of low-level laser emission / Photobiomodu-lation (LE/P) in quantitative measurements of root resorption (QRR). The application of LE/P was done after each orthodontic activation with 4 types of treatment intervention (TI) on the RR after fixed orthodontic treatment (FOT) of the upper arch with ectopic eye tooth/teeth [EET]. 32 Orthodontic patients scheduled for FOT were selected and assigned to the 4 groups. These were LE/P+Self ligating bracket (SLB), LE/P+Conventional bracket (CB), Non-Photobiomodulation (non-LE/P)+SLB, and non-LE/P+CB. Standard management stages of FOT were followed in the maxilla. Each patient received a single application of LE/P labially/buccally and palatally, a total of 5 different points during each activation or appointment. The main outcome measure was QRR in maxillary anteriors before and after FOT assessed via cone-beam computed tomography (CBCT) using 3D OnDemand software. Insignificant QRR was found between before and after FOT in SLB, CLB, and LE/P, non-LE/P groups (p > 0.05). QRR in the SLB vs CB and LE/P vs non-LE/P group was significantly different in 11, 13, and 23 (p < 0.05). QRR in the LE/P+SLB group (p < 0.05) was significantly different in 11, 13, and 23 than that in the other groups. The most severe QRR was found on the 13 (0.88 ± 0.28mm and 0.87±0.27mm) and 23 (1.19 ± 0.14 mm and 1.16±0.13mm) in the CB and non-LE/P group (p < 0.001). LE/P+SLB showed highly significant superior outcome (p < 0.001) in relation to non-LE/P+CB, the QRR of 23 were 0.813± 0.114mm and 1.156± 0.166mm respectively. Significantly higher amount of QRR found in EET patients after FOT treated with the CB, non-LE/P, and non-LE/P+CB system and warrants further investigation to explore potential specific causes.

: The radar multi target tracking (MTT) technique requires prior knowledge of a number of parameters about the sensor, the target and backgrounds. The Integrated Track Splitting (ITS) is a fully automatic track-while-scan (TWS) target tracking algorithm capable of extracting and tracking a target in a dense clutter environment using quality false track discrimination (FTD) methodology. The computational complexity in ITS algorithm is limited, compared to other algorithms they use statistical methods to discriminate between false and true tracks, such as multiple hypothesis tracking (MHT), mainly due to the FTD performed. The paper provides an analysis of tracking parameters that allows determining the limit of the possibility of successful target tracking. Extensive experiments have confirmed that the recursive determination of the probability of the existence of a track during tracking can confirm a true track and reject a false track. The clutter density, number of random occurred targets, targets load during the maneuver and the target detection probability were varied. The results of experiments, carried out via Monte Carlo simulations, shown over representative confirmed true tracks (CTT) diagrams, root mean square error position and normalized tracking efficiency parametric diagrams allow the user to select optimal multi-target tracking parameters for different scenarios and clutter densities.

The objective of the present work is to investigate the performance of flat-plate solar panels in Greece that continuously follow the daily motion of the Sun. To that end, the annual energy sums are estimated on such surfaces from hourly solar horizontal radiation values at 43 locations covering all of Greece. The solar horizontal radiation values are embedded in the typical meteorological years of the sites obtained from the PV-GIS tool. All calculations use a near-real surface albedo; an isotropic and an anisotropic model are used to estimate the diffuse-inclined radiation. The analysis provides regression equations for the energy sums as a function of time (month, season). The annual energy sums are found to vary between 2247 kWhm−2 and 2878 kWhm−2 under all-sky conditions with the anisotropic transposition model. Finally, maps of Greece showing the distribution of the annual and seasonal solar energy sums under all- and clear-sky conditions are derived for the first time.

The environmental impact and associated health issues have been seen as a significant global challenge. Efforts have been made to make solar cookers efficient to reduce the health risk and environmental impact of traditional cooking energy supplies used in rural areas. The solar cookers effectiveness for cooking purposes must be assessed in a specific area before installation. In essence, this paper assesses the experimental efficiency of German Scheffler, small mirror pieces, and aluminum foil based solar cookers. The solar cookers performances are evaluated at international standards by analyzing the figure of merits such as standard cooking power, sensible heating time, and exergy efficiency by using 1.7652 kg water and 1-liter oil as a heating material. The regression analysis is also performed to observe experimental data compliance with regression line. The time required to attain a water temperature of 95˚C by German Scheffler and small mirror pieces is 25 min and 1 hour with their exergy efficiency of 48.51% and 19.16% respectively, while the aluminum foil solar cooker achieves maximum water temperature of 74˚C within 2 hours and 5 minutes with 13.47% exergy efficiency. Similarly, the highest oil temperature of 275˚C is observed for the German Scheffler solar cooker. From experimental and regression results, it is revealed that German Scheffler possesses more cooking power relative to other solar cookers and their performances are highly dependent on following factors such as solar radiations, ambient temperature, environment (dust particles concentration and wind speed), radiation reflective material, aperture area, and heat losses respectively.

Beach sand may act as a reservoir for numerous micro-organisms, including enteric pathogens. Several of these pathogens originate in human or animal feces, which may pose a public health risk. In August 2019, high levels of fecal indicator bacteria (FIB) were detected in the sand of the Azorean beach Prainha, Terceira Island, Portugal. Remediation measures were promptly implemented, including sand removal and the spraying of chlorine to restore the beach sand quality. To determine the biological source of the contamination, during the first campaign, supratidal sand samples were collected from several sites along the beach, followed by microbial source tracking (MST) analyses of Bacteroides markers for five animal species, including humans. Some of the sampling sites revealed the presence of marker genes from dogs, seagulls, and ruminants. Making use of the information on biological sources originating partially from dogs, the municipality enforced restrictive measures for dog-walking at the beach. Subsequent sampling campaigns detected low FIB contamination due to the mitigation and remediation measures that were undertaken, thereby no longer requiring MST marker-gene analysis. This is the first case study where the MST approach was used to determine the contamination sources in the supratidal sand of a coastal beach. Our results show that MST can be an essential approach to determine sources of fecal contamination in the sand. This study shows the importance of holistic management of beaches that should go beyond water quality monitoring for FIB, putting forth evidence for the need for sands also to be monitored.

Background: global longitudinal strain (GLS) measures myocardial deformation and is a sensitive modality for detecting subclinical myocardial dysfunction and predicting cardiac outcomes. The accuracy of speckle-tracking echocardiography (STE) is dependent on temporal resolution. A novel software enables relatively high frame rate (Hi-FR) (~200 fps) echocardiographic images acquisition which empowers us to investigate the impact of Hi-FR imaging on GLS analysis. The goal of this pilot study was to demonstrate the feasibility of Hi-FR for STE. Methods: In this prospective study, we acquired echocardiographic images using clinical scanners on patients with normal left ventricular systolic function using Hi-FR and conventional frame rate (Reg-FR) (~50 FPS). GLS values were evaluated on apical 4-, 2- and 3-chamber images acquired in both Hi-FR and Reg-FR. Inter-observer and intra-observer variabilities were assessed in Hi-FR and Reg-FR. Results: There were 143 resting echocardiograms with normal LVEF included in this study. The frame rate of Hi-FR was 190 ± 25 and Reg-FR was 50 ± 3, and the heart rate was 71 ± 13. Strain values measured in Hi-FR were significantly higher than those measured in Reg-FR (all p < 0.001). Inter-observer and intra-observer correlations were strong in both Hi-FR and Reg-FR. Conclusions: We demonstrated that strain values were significantly higher using Hi-FR when compared with Reg-FR in patients with normal LVEF. It is plausible that higher temporal resolution enabled the measurement of myocardial strain at desired time point. The result of this study may inform clinical adoption of the novel technology. Further investigations are necessary to evaluate the value of Hi-FR to assess myocardial strain in stress echocardiography in the setting of tachycardia.

In the last two decades, extracellular vesicles (EVs) from the three domains of life, archae, bacteria and eukaryota, have gained increasing scientific attention. As such, the role of EVs in host-pathogen communication and immune modulation are being intensely investigated. Pivotal to EV research is the determination of how and where EVs are taken up by recipient cells and organs in vivo, which requires suitable tracking strategies including labelling. Labelling of EVs is often performed post-isolation which increases risks of non-specific labelling and the introduction of labelling artefacts. Here we exploited the inability of helminths to de novo synthesise fatty acids to enable labelling of EVs by whole organism uptake of fluorescent lipid analogues and the subsequent incorporation in EVs. We showed uptake of DOPE-Rhodamine in Anisakis spp. and Trichuris suis larvae. EVs isolated from supernatant of Anisakis spp. labelled with DOPE-Rhodamine were characterised to assess effects of labelling on size, structure and fluorescence of EVs. Fluorescent EVs were successfully taken up by the human macrophage cell line THP-1. This study therefore presents a novel staining method that can be utilized by the EV field in parasitology and potentially across multiple species.

Muon radiography is an imaging technique based on the measurement of the absorption of cosmic ray muons. This technique has recently been used successfully to investigate the presence of unknown cavities in the Bourbon Gallery in Naples and in the Cheops Pyramid at Cairo. The MIMA detector (Muon Imaging for Mining and Archaeology) is a muon tracker prototype for the application of muon radiography in the Archaeological and Mining fields. It is made of three couples of X-Y planes each consisting of 21 scintillator bars with silicon photomultiplier read-out. The detector is compact, robust, easily transportable and has a low power consumption: all of that makes the detector ideal for measurements in narrow and isolated environments. With this detector we have performed a measurement from inside the Temperino mine in the San Silvestro archaeo-mining park in Tuscany. The park includes about 25 km of mining tunnels arranged on several levels that have been excavated since the Etruscan time. The measured muon absorption was compared to the simulated one, obtained from the information provided by 3D laser scanner measurements and the cartographic maps of the mountain above the mine, in order to obtain information on the average density of the rock. This allowed to confirm the presence of a partially accessible exploitation opening and gave some hints on the presence of a high density body within the rock.

Multi-object tracking (MOT) in airborne videos is a challenging problem due to the uncertain airborne vehicle motion, vibrations of the mounted camera, unreliable detections, size, appearance and motion of the moving objects as well as occlusions due to the interaction between the moving objects and with other static objects in the scene.To deal with these problems, this work proposes a four-stage Hierarchical Association framework for multiple object Tracking in Airborne video (HATA). The proposed framework combines data association-based tracking (DAT) methods and target tracking using a Compressive Tracking approach, to robustly track objects in complex airborne surveillance scenes. In each association stage, different sets of tracklets and detections are associated to efficiently handle local tracklet generation, local trajectory construction, global drifting tracklet correction and global fragmented tracklet linking. Experiments with challenging airborne video datasets show significant tracking improvement compared to existing state-of-art methods.

Purpose: To evaluate the relationship between corneal nerve structure and function in a veteran population. Methods: 83 veterans (mean age: 55 ± 5 years) seen at the Miami Veterans Affairs (VA) eye clinic were included in the study. Each individual filled out questionnaires to evaluate ocular symptoms (5-Item Dry Eye Questionnaire, DEQ5, Ocular Surface Disease Index, OSDI) and ocular pain (Numerical Rating Scale, NRS, Neuropathic Pain Symptom Inventory modified for the Eye, NPSI-Eye). Individuals also underwent an ocular surface examination that captured functional nerve tests including corneal sensation, corneal staining, and Schirmer test for tear production. Corneal sub-basal nerve analysis was conducted using in vivo confocal microscopy (IVCM) images with corneal nerve density, length, area, width, and fractal dimension captured. IVCM and functional corneal metrics from the right eye were examined using correlational and linear regression analysis. Results: Most corneal structural metrics were not related to functional metrics, except for weak correlations between various IVCM metrics and tear production. In addition, corneal nerve fiber area was positively related to corneal sensation (r = 0.3, p = 0.01). On linear regression analyses, only corneal fractal dimension remained significantly related to tear production (β = -0.26, p = 0.02) and only corneal nerve fiber area remained significantly related to corneal sensation (β = 0.3, p = 0.01). Conclusions: Most corneal nerve structural metrics did not relate to functional metrics in our veteran population, apart from a few weak correlations between structural metrics and tear production. This highlights caution in using corneal nerve anatomy to predict corneal function.

This study demonstrates the efficacy of structured pruning and architectural fine-tuning on the YOLOv7-tiny model for eye state detection, emphasizing optimization for real-time applications. Structured pruning significantly reduced the model's complexity and storage size while maintaining high detection accuracy, as evidenced by stable precision, recall, and mAP@.5 metrics across iterations. Further fine-tuning adjusted the model's width and depth, optimizing efficiency and processing speed without compromising performance. These optimizations yielded YOLOv7-tiny variants that are both computationally efficient and accurate, suitable for resource-constrained environments. The findings highlight the critical role of model optimization in deploying effective neural networks for specific detection tasks in real-time scenarios.

Purpose: To assess the tolerability, safety, and efficacy of an ophthalmic topical formulation containing helenalin from Arnica montana and hyaluronic acid 0.4% (HA) in patients with mild to moderate dry eye disease (DED) exhibiting positive Matrix Metalloproteinase 9 (MMP-9) test results. Methods: Tolerability and safety were evaluated in 24 healthy subjects. Participants were in-structed to routinely apply one drop of the formulation three times a day in the study eye, for a period of two weeks, followed by a clinical follow-up of 21 days. Efficacy was studied in 48 DED patients randomized into Study (Group 1/ receiving the study formulation) or Control (Group 2/ Receiving HA 0.4% eye lubricant) groups, for 4 weeks. Assessments included MMP-9 positivity, conjunctival impression cytology (CIC), Ocular Surface Disease Index (OSDI), non-invasive tear film breakup time (NIF-BUT), non-invasive average breakup time (NIAvg-BUT), ocular surface staining, Schirmer's test, and meibomiography. A crossover design with a four-week follow-up was applied to the control group. Results: Healthy subjects receiving the study formulation exhibited good tolerability and no ad-verse events. Group 1 showed significant MMP-9 reduction (25% positivity rate) unlike Group 2 (87.5% positivity rate). Group 1 displayed improved CIC (33.3% vs. 0% SSD) compared to Group 2 (29.1%). OSDI and NIF-BUT scores improved in both groups (p < 0.001). Only Group 1 showed improved NIAvg-BUT and Schirmer’s test scores (p < 0.001), while Group 2 did not (p > 0.05). MMP-9-positive subjects shifted from 25% to 91.6% in Group 1 and 87.5% to 20.8% in Group 2 after the follow-up. Conclusion: The topical formulation containing helenalin from Arnica montana and hyaluronic acid is well tolerated and has a good safety profile. Our formulation reduces DED sympto-matology and modulates the ocular surface inflammatory process; this is evidenced by the en-hancement of CIC, the improvement of DED-related tear film status, and the reduction of MMP-9 positivity rate.

It is known that during the process of aging there is a significant decrease in the number of melanosomes in the retinal pigment epithelium (RPE) cells of the human eye. We have previously shown that the interaction of melanin melanosomes with superoxide radicals results in its oxidative degradation with the formation of water-soluble fluorescent products. In the present study, we show using fluorescence analysis, HPLC, and mass spectrometry, that visible light irradiation of melanolipofuscin granules isolated from RPE cells of the human eye results in the formation of water-soluble fluorescent products of oxidative degradation of melanin, in contrast to lipofuscin granules and melanosomes irradiation. The formation of these products occurs as a result of oxidative degradation of melanin by superoxide radicals, which are generated by the lipofuscin part of the melanolipofuscin granule. We identified these products both in the composition of melanolipofuscin granules irradiated with visible light, and in composition of non-irradiated but oxidized by superoxide radicals, melanosomes. In melanolipofuscin granules irradiated with visible light, ions that could be associated to melanin oxidative degradation products were identified by applying principal component analysis of time-of-flight secondary ion mass spectrometry (ToF-SIMS) data. Degradation of the intact melanosomes by visible light is also possible; however, this requires significantly higher irradiation intensities than for melanolipofuscin granules. It is concluded that the decrease in the concentration of melanin in RPE cells of the human eye with age is due to its oxidative degradation by reactive oxygen species generated by lipofuscin as part of melanolipofuscin granules under the action of light.

Gaze tracking of high-speed moving targets is a novel application mode for low Earth orbit microsatellites. In this mode, small satellites are equipped with high-resolution narrow-field-of-view video cameras for stable gaze-tracking imaging of high-speed moving targets. This paper proposes a high-precision attitude adaptive integral sliding mode control method with a feedforward compensation disturbance observer to enhance the capability of a microsatellite attitude control system for gaze tracking of high-speed moving targets. Specifically, first, we present the attitude control system model for microsatellites and the calculation method for the desired attitude of target tracking based on image feedback. Then, an adaptive integral sliding mode attitude control algorithm with a feedforward compensation disturbance observer, which meets the requirements of high-precision tracking control, is designed. The developed algorithm utilizes the disturbance observer to observe the friction torque of the flywheel and compensates for it through feedforward control. It also employs the adaptive integral sliding mode control algorithm to reduce the impact of uncertain disturbances, decrease the steady-state error of the system, and enhance the attitude control precision. Simulation experiments demonstrated that the designed disturbance observer can successfully observe the frictional disturbance torque of the flywheel. The attitude Euler angle control precision for high-speed moving target tracking reached 0.009°, and the angular velocity control precision reached 0.005°/s, validating the effectiveness of the proposed approach.

This paper proposed an optimal tracking control scheme through adaptive dynamic programming(ADP) for a class of partially unknown discrete-time nonlinear systems based on radial basis function neural network(RBF-NN). In order to acquire the unknown system dynamics, we use two RBF-NNs, the one is used to construct the identifier, and the another is used to directly approximate the steady-state control input, where a novel adaptive law is proposed to update neural network weights. While the optimal feedback control and the cost function are derived via feedforward neural networks approximating, it is proposed to regulate the tracking error, the critic network and the actor network are then trained online to obtain the solution of the associated Hamilton–Jacobi–Bellman (HJB) equation being built under the ADP framework. Simulations verify the effectiveness of the optimal tracking control technique using the neural networks.

The agricultural industry places a high priority on crop protection, especially when it comes to protecting cotton crops against pink bollworm infestations. Rapid disease identification is essential for effective crop management at the same time. In order to overcome these difficulties, this study offers a thorough process for utilizing the Robot Operating System (ROS) to deploy an autonomous robot. The robot is intended to identify infestations of pink bollworm in addition to counting and tracking red Disease that impact cotton harvests. Drones are used to check the condition of cotton fields, and the autonomous robot's path planning component is closely related to this process. Large fields are photographed by these drones in multispectral mode, and the robot's course planning technique is done by calculating the Normalized Difference Vegetation Index (NDVI) based on these images. This approach ensures targeted surveillance and intervention, optimizing the use of resources. A customized dataset was created especially for this application to improve the robot's detecting abilities. The dataset was utilized to train a YOLOV8 model, a state-of-the-art object detection architecture. Performance characteristics of the trained model are impressive; it has a mean Average Precision (mAP) of 67.1%, Precision of 67.9%, and Recall of 61.8%. These metrics highlight how well the model works to precisely locate and measure interesting occurrences in the cotton fields. In order to address the particular challenges presented by pink bollworm infestations and crop diseases in the context of cotton cultivation, this research contributes a comprehensive solution for autonomous crop monitoring and protection by seamlessly integrating ROS, drones, NDVI calculations, and a robust detection model.

The motion of Unmanned Surface Vehicles (USVs) is frequently disturbed by the ocean wind, wave and current. A poorly designed controller will lead to failures and even safety problems during actual navigation. In order to obtain satisfied control performance of the motion for the USVs, a Model Predictive Control (MPC) based on improved Nonlinear Disturbance Observer (NDO) is proposed. Firstly, the USV model is approximately linearized and MPC is designed for the multivariable system with constraints. In order to compensate the influence of disturbances, an improved NDO is designed, with which the calculation time for the MPC saved a lot. Finally, comparison experiments are conducted between the MPC with NDO and the MPC with improved NDO, and the results show that they have similar performance to the USVs. However, the proposed method has less parameter to be tuned and it is much more time-saving compared to the MPC with traditional NDO.

In this paper, the distributed formation tracking control problem of quadrotor unmanned aerial vehicles (UAVs) is considered. Adaptive backstepping technology is used to design flight control schemes for quadrotor UAVs. For the position subsystem, a distributed robust formation tracking control scheme is developed to achieve formation flight of quadrotor UAVs and track the desired flight trajectory. For the attitude subsystem, an adaptive disturbance rejection control scheme is proposed to achieve attitude stabilization during UAV flight under uncertain disturbances. Compared with the existing results, the novelty of this paper is that the proposed formation control scheme does not require the use of the quadrotor model parameters. Finally, a quadrotor UAV swarm system is used to verify the effectiveness of the proposed control scheme.

Illegal removal of road barricades without the notice of road emergency officials and road users has resulted in fatalities, injuries, and property damages. It is only after an incident has occurred or someone noticed the removal and alerted the authorities for the barricade to be placed back at its intended location. There is a need for traditional barricades to be equipped with mechanisms that would alert officials on illegal road barricade removal and warn road users of a road/lane(s) closure to prevent fatalities, injuries, and property damages to the traveling public. This research has used the Global Positioning System (GPS) module to implement the detection of barricade displacement and an alerting system for emergency officials and road users. The barricade displacement was estimated from the haversine distance formula, corrected for errors, and interfaced with the displacement threshold value for the road users within a geofenced area to be alerted. The geofenced area radius was estimated to be 1.04 miles from the barricade location using AASHTO, NSC, and TransGuide ITS manuals. The non-parametric bootstrapping method estimated the GPS position error to 10.5 feet and corrected the measured distances. Data from a clear sunny day shows the best response to barricade movements compared to a cloudy day where movements can’t be explained easily. The proposed monitoring and warning systems would warn road users and alert emergency officials of the danger when the physical barricades have been removed illegally hence saving lives and reducing property damages.

The goal of this report was to examine the behavioral economic demand for consumer sleep technologies with different levels of validation and endorsement. The value or importance consumers place in different validation methods and the organizations conducting the evaluations was also assessed. Survey data were collected from 113 participants on Amazon mTurk. Participants indicated their likelihood of purchasing devices that varied in level of validation across a series of increasing prices. Demand curves were analyzed to determine the relative value of each watch type. Participants also reported how valuable or important different aspects of device validation were to them. Devices that were both evaluated against laboratory measures and endorsed by sleep researchers had the most value, followed by those only evaluated against laboratory measures, and then those not evaluated against any laboratory measures. The unit price at which there was 50% probability of purchase was increased by $25 or $44 for evaluation or endorsement, respectively. Respondents indicated the most valuable features were a measure of sleep duration, that it was most important that devices were validated against measures of sleep from a laboratory or hospital, and that they would put a high value on sleep tracker endorsements from a university or academic institution. Consumer demand is greatest for a device that has been evaluated by an independent laboratory for accuracy in measuring sleep and is endorsed by an academic, medical, or government institution. These results indicate a role for scientific evaluation and endorsement in consumer preference for sleep trackers.

Feral cats are both difficult to manage and harder to monitor. We analysed the cost-efficacy of monitoring the pre- and post-bait abundance of feral cats via camera-traps or track counts using four years of data from the Matuwa Indigenous protected Area. Additionally, we report on the recovery of the feral cat population and the efficacy of subsequent Eradicat® aerial baiting programs following 12 months of intensive feral cat control in 2019 that consisted of aerial baiting and leg-hold trapping. Significantly fewer cats were captured in 2020 (n = 8) compared to 2019 (n = 126). Pre-baiting surveys for 2020 and 2021 suggested that the population of feral cats on Matuwa was very low, at 5.5 and 4.4 cats/100 km respectively, which is well below our target threshold of 10 cats/100 km. Post-baiting surveys then recorded 3.6 and 3.0 cats/100 km respectively, which still equates to a 35% and 32% reduction in cat activity. Track counts recorded significantly more feral cats than camera traps and were cheaper to implement. We recommend that at least two methods of monitoring cats be implemented to prevent erroneous conclusions.

The ever-burgeoning growth of autonomous unmanned aerial vehicles (UAVs) has demonstrated a promising platform for utilization in real-world applications. In particular, UAV equipped with a vision system could be leveraged for surveillance applications. This paper proposes a learning-based UAV system for achieving autonomous surveillance, in which the UAV can be of assistance in autonomously detecting, tracking, and following a target object without human intervention. Specifically, we adopted the YOLOv4-Tiny algorithm for semantic object detection and then consolidated it with a 3D object pose estimation method and Kalman Filter to enhance the perception performance. In addition, a back-end UAV path planning for surveillance maneuver is integrated to complete the fully autonomous system. The perception module is assessed on a quadrotor UAV, while the whole system is validated through flight experiments. The experiment results verified the robustness, effectiveness, and reliability of the autonomous object tracking UAV system in performing surveillance tasks. The source code is released to the research community for future reference.

Gastric emptying rate (GER) may impact diabetes and obesity in humans and could provide a method to reduce canine weight gain. Starch, the most common source of carbohydrates (CHOs) in pet food, is classified as rapidly or slowly digestible, or resistant to digestion. This study investigated starch source effects in commercial extruded dog foods on the GER of 11 healthy adult Siberian Huskies (5.63±0.72 years; mean±SEM). Test diets were classified as traditional, grain-free, whole-grain, and vegan. Dogs received each diet once, a glucose control twice, and acetaminophen (Ac) as a marker for GER in a randomized, partially-replicated, 6x6 Latin square design. Pre- and post-prandial blood samples were collected at 16 timepoints from -15 to 480 minutes. Serum Ac concentrations were assessed via standard spectrophotometric assays and fitted with a mathematical model to estimate parameters of GER. Data was analyzed using a repeated measures ANOVA, followed by a Tukey-Kramer post-hoc test when significant (p<0.05). More total emptying (p= 0.0430) occurred at faster rate (p=0.0668) in dogs fed the grain-free diet, which contained the lowest total starch (34.03 ± 0.23%) and highest resistant starch (0.52 ± 0.007%). This research may benefit future diet formulations to reduce the prevalence of canine weight gain.

Hand tracking enables controller-free interaction with virtual environments, which can, compared to traditional handheld controllers, make virtual reality (VR) experiences more natural and immersive. As naturalness hinges on both technological and user-based features, fine-tuning the former while assessing the latter can be used to increase usability. For a grab-and-place use case in immersive VR, we compared a prototype of a camera-based hand tracking interface (Leap Motion) with customized design elements to the standard Leap Motion application programming interface (API) and a traditional controller solution (Oculus Touch). Usability was tested in 32 young healthy participants, whose performance was analyzed in terms of accuracy, speed and errors as well as subjective experience. We found higher performance and overall usability as well as overall preference for the handheld controller compared to both controller-free solutions. While most measures did not differ between the two controller-free solutions, the modifications made to the Leap API to form our prototype led to a significant decrease in accidental drops. Our results do not support the assumption of higher naturalness for hand tracking but suggest design elements to improve the robustness of controller-free object interaction in a grab-and-place scenario.

Particle size can pose a challenge to random embankment compaction control methods, where practical techniques have hardly been developed and procedural control is used instead. In order to develop new quality control procedures for slate random fill, the necessary fieldwork and laboratory tests were carried out. This involved the revision of certain methods such as the wheel-tracking or topographic settlement tests. More than six hundred in-situ density and moisture content measurements were carried out for this research. In addition, more three hundred topographic settlements and three hundred wheel-tracking carriage tests were performed. The quality control processes were completed with more than thirty plate bearing tests. Possible evidence of statistical correlations between compaction control tests were identified. An analysis of variance (ANOVA) was performed. When testing proved relationships between them, the replacement of one of them by the other was assessed by deduction. Finally, the study suggests new procedures for compaction quality control of random slate fill used in crown area.

Prediction of the likely evolution in the traffic scenes is a challenging task because of high uncertainty of sensing technology and dynamic environment. It leads to failure of planning for intelligent agents like autonomous vehicles. In this paper, we propose a fluid-based physical model to present the influence of surrounding object's motion on driving safety. In our pipeline, the input sensor could be LiDAR, camera, or multi-modal data. We use a Kalman filter to estimate the state space of each detected object, and adopt the properties of stable fluid to build a riskmap based on the density field. The noisy state space are then modeled as the boundary conditions in the simulation of advection and diffusion process. We test our approach on the public KITTI dataset and find this model could handle the short-term prediction in case of misdetection and tracking failure caused by object occlusion, which shows promising in collision risk assessment on road scenes.

This paper discusses about control of the linear switched reluctance machines (LSRMs) network for the zero phase-difference tracking to a sinusoidal reference. The dynamics of each LSRM is derived by online system identification and modeled as a second-order linear system. Accordingly, based on the coupled harmonic oscillators synchronization manner, a distributed control is proposed to synchronize each LSRM state to a virtual LSRM node representing the external sinusoidal reference for tracking it with zero phase-difference. Subsequently, a simulation scenario and an experimental platform with the identical parameter setup are designed to investigate the tracking performance of the LSRMs network constructed by the proposed distributed control. Finally, the simulation and experimental results verify the effectiveness of the proposed LSRMs network controller, and also prove that the coupled harmonic oscillators synchronization method can improve the synchronization tracking performance and precision.

Extraocular eye muscles (EOMs) are innervated by axons of three ocular motor nuclei, the oculomotor (CNIII), trochlear (CNIV), and abducens (CNVI) neurons. The purpose of this review is to analyze the origin of ocular motor neurons, define the pattern of innervation of nerve fibers that project to the EOMs, pro-vide an overview of vestibular pathway inputs to ocular motor nuclei, and describe congenital disorders that alter the development of ocular motor neurons. Oculomotor neurons originate in the midbrain and innervate the ipsilateral orbit, except for the superior rectus and the levator palpebrae which are contra-laterally innervated. Trochlear motor neurons originate at the midbrain-hindbrain junction and innervate the contralateral superior oblique muscle. Abducens motor neurons originate variously in the rhombomeres r4-6 and innervate the posterior (or lateral) rectus muscle and innervate the retractor bulbi. Genes allow yielding a distinction between special somatic (CNIII, IV) and somatic (CNVI) ocular motor neurons. The ocular motor neurons are innervating somites, which receive innervates vestibular nuclei that connects with the brainstem motor neurons. Development of ocular motor neurons and their axonal projections to the EOMs may be derailed by various genetic causes, resulting in the congenital cranial dysinnervation disorders.

Elevated levels of oxidative stress in the corneal epithelium contribute to the progression of dry eye disease pathology. Previous studies have shown that antioxidant therapeutic intervention is a promising avenue to reduce disease burden and slow disease progression. In this study, we evaluated the pharmacological efficacy of Xanthohumol in preclinical models for dry eye disease. Xanthohumol is a naturally occurring prenylated chalconoid that promotes the transcription of phase II antioxidant enzymes. Xanthohumol exerted a dose-response in preventing tert-butylhydroxide-induced loss of cell viability in human corneal epithelial (HCE-T) cells and resulted in a significant increase in expression of nuclear factor erythroid 2-related factor 2 (Nrf2), the master regulator of the endogenous antioxidant system. Xanthohumol-encapsulating poly(lactic-co-glycolic acid) nanoparticles (PLGA NP) were cytoprotective against oxidative stress in vitro, and significantly reduced corneal fluorescein staining in the mouse desiccating stress/ scopolamine model for dry eye disease in vivo by reducing oxidative stress-associated DNA damage in corneal epithelial cells. PLGA NP represent a safe and efficacious drug delivery vehicle for hydrophobic small molecules to the ocular surface. Optimization of NP-based antioxidant formulations with the goal to minimize instillation frequency may represent future therapeutic options for dry eye disease and related ocular surface disease.

Objective: The Rho GTPase/Rho kinase pathway is an important target in glaucoma treatment. This study investigated the hypotensive effect of RKI-1447, a Rho kinase inhibitor developed for cancer treatment, in a porcine ex vivo pigmentary glaucoma model. Materials and Methods: Twenty-eight fresh porcine anterior chambers were perfused with pigment medium (1.67 × 10⁷ pigment particles/mL) for 48 hours before being subjected to the RKI-1447 (n = 16) or the vehicle control (n = 12). Another twelve eyes with normal medium perfusion served as the control. The intraocular pressure (IOP) was recorded at two-minute intervals and the outflow facility was calculated. To investigate the intracellular mechanism of the IOP reduction, primary trabecular meshwork cells were exposed to RKI-1447 or the vehicle control and then analyzed for changes in cytoskeleton, motility, and phagocytosis. Results: Compared to the baseline, the perfusion of pigment caused a significant increase in IOP in the RKI-1447 group (P = 0.003) at 48 hours. Subsequent treatment with RKI-1447 significantly reduced IOP from 20.14 ± 2.59 mmHg to 13.38 ± 0.91 mmHg (P = 0.02). Pigment perfusion reduced the outflow facility from 0.27 ± 0.03 at baseline to 0.18 ± 0.02 at 48 hours (P < 0.001). This was partially reversed with RKI-1447. RKI-1447 exhibited no apparent changes in the micro- or macroscopic appearance, including histology. Primary TM cells exposed to RKI-1447 showed a significant disruption of the actin cytoskeleton both in the presence and absence of pigment exposure (P < 0.001) but no effect on TM migration was observed. Pigment-treated TM cells exhibited a reduction in TM phagocytosis, which RKI reversed. Conclusions: RKI-1447 is a novel ROCK inhibitor that significantly reduces IOP by disrupting TM stress fibers and increasing TM phagocytosis. These features may make it especially useful for the treatment of secondary glaucomas with an increased phagocytosis load but also for other open angle glaucomas.

Suicide and suicidal behavior are major public health concerns and affect 3-9% of the population worldwide. Despite growing evidence, there are still few effective interventions available to reduce suicide risk. In this article, we describe theoretical models of suicide ideation and behavior and propose to examine the possible effectiveness of a new and innovative preventive strategy. A model of suicidal intrusion (mental imagery related to suicide, also referred to as suicidal flash-forwards) is presented describing one of the assumed mechanisms in the etiology of suicide and the mechanism of therapeutic change. We provide a brief rationale for an Eye Movement Dual Task (EMDT) treatment for suicidal intrusions describing techniques that can be used to target these suicidal mental images and thoughts to reduce overall behavior. Based on the available empirical evidence for the mechanisms of suicidal intrusions, this approach appears to be a promising new treatment to prevent suicidal behavior as it potentially targets one of the linking pins between suicidal ideation and suicidal actions.

The right heart catheterisation constitutes the gold standard for pulmonary hypertension (PH) diagnosis. However, echocardiography remains a reliable, non-invasive, inexpensive, convenient, and easily reproducible modality not only for the preliminary screening of PH but also for PH prognosis. The aim of this review is to describe a cluster of echocardiographic parameters for the detection and prognosis of PH and analyse the challenges of echocardiography implementation in patients with suspected or established PH. The most important echocardiographic index is the calculation of pulmonary arterial systolic pressure (PASP) through the tricuspid regurgitation (TR). It has shown high correlation with invasive measurement of pulmonary pressure, but several drawbacks have questioned its accuracy. Besides this, the right ventricular outflow track acceleration time (RVOT-AT) has been proposed for PH diagnosis. A plethora of echocardiographic indices: right atrial area, pericardial effusion, the tricuspid annular plane systolic excursion (TAPSE), the TAPSE/PASP ratio, tricuspid annular systolic velocity (s′) and recently, can reflect the severity and prognosis of PH. Recent advances in echocardiography with 3-dimensional right ventricular (RV) ejection fraction, RV free wall strain and right atrial strain may further assist the prognostication of PH.

Drones have been used in a variety of scenarios such as atmospheric monitoring, fire rescue, agricultural irrigation, etc., in which accurate environmental perception is of crucial importance for both decision-making and control. Among the drone sensors, the RGB camera is indispensable for capturing rich visual information for vehicle navigation but encounters a grand challenge in high-dynamic-range scenes that occur frequently in real applications. Specifically, the recorded frames suffer from under-exposure and over-exposure simultaneously and degenerate the successive vision tasks. To solve the problem, we take object tracking as an example and leverage the superior response of event cameras over a large intensity range to propose an event-assisted object tracking algorithm that can achieve reliable tracking under large intensity variations. Specifically, we propose to pursue feature matching from dense event signals, and based on which to (i) design a UNet-based image enhancement algorithm to balance the RGB intensity with the help of neighboring frames in the time domain, and then (ii) construct a dual-input tracking model to track the moving objects from intensity balanced RGB video and event sequence. The proposed approach is comprehensively validated in both simulation and real experiments.

In the field of maneuvering target tracking, the combined observations of azimuth and Doppler may cause weak observation or non-observation in the application of traditional target tracking algorithms. Additionally, traditional target-tracking algorithms require pre-defined multiple mathematical models to accurately capture the complex motion states of targets, while model mismatch and unavoidable measurement noise lead to significant errors in target state prediction. To address those above challenges, in recent years, the target-tracking algorithms based on neural networks, such as recurrent neural networks (RNNs), long short-term memory (LSTM) networks, and Transformer architectures, have been widely used for their unique advantages to achieve accurate predictions. To better model the nonlinear relationship between the observation time series and the target state time series, as well as the contextual relationship among time series points, we present a deep learning algorithm called recursive downsample-convolve-interact neural network (RDCINN) based on convolutional neural network (CNN) that downsamples time series into sub-sequences and extracts multi-resolution features to enable the modeling of complex relationships between time series, which overcomes the shortcomings of traditional target-tracking algorithms in using observation information inefficiently due to weak observation or non-observation. The experimental results show that our algorithm outperforms other existing algorithms in the scenario of strong maneuvering target tracking with the combined observations of azimuth and Doppler.

In recent years, the use of long-term seismic monitoring systems for the protection of structures is becoming increasingly widespread. This is because more and more awareness is gradually developing regarding the importance of keeping structures under observation so as to prevent any damage scenarios. Within the field of Structural Health Monitoring, data driven techniques allow to process and analyze data collected on site. This paper presents a Mode Tracking procedure to obtain the time-histories of the natural frequencies of a monumental structure. The procedure is applied on the Sanctuary of Vicoforte, an important monumental structure site in Piedmont known for its imposing oval dome and characterized by a permanent structural monitoring system. Through the procedure presented in the paper it has been possible to obtain and observe the time series of the first natural frequencies of the structure considering various aspects, including the temperature variation.

A class of controlled plants, whose dynamics is governed by a vector system of ordinary differential equations with a partially known right-hand side, is considered. The state variables and their velocities are assumed to be measurable. The aim is to design a controller which minimizes a loss function under certain constraints which arguments is the current state of the controlled plant. The designed control action is admitted to be a function of the current sub-gradient only, which supposed to be measurable on-line. The control design is based on ASG (Average Sub-Gradient method) — version of Integral Sliding Mode (ISM) concept, aimed to minimize on average a given convex (not obligatory strongly convex) cost function of the current state under a set of given constraints. An optimization type algorithm is developed and analyzed using ideas of SDM technique. The main results consist in proving the reachability of the "desired regime" (nonstationary analogue of sliding surface) from the beginning of the process and obtaining an explicit upper bound for the averaged loss function decrement, that is, the averaged in time functional convergence is proven and the rate of such convergence is estimated.

Natural gas hydrate has gained significant attention in recent years. To safely and sustainably exploit the natural gas from gas hydrate-bearing sediments, it is crucial to understand the long-term mechanical characteristics of the hydrate reservoir. In this study, the influence of hydrate and fine particles on the strain rate dependence of hydrate-bearing sediments under plane strain conditions has been studied. The experimental results show that the strain rate dependency of the mechanical properties of hydrate-bearing sediments is positively correlated with hydrate saturation instead of the morphology of hydrate in sediments. The residual strength of hydrate-bearing sediments is primarily controlled by the hydrate saturation and is independent of the strain rate. Changes in hydrate saturation, and fines content, can affect the relationship between the strain rate and shear band angle. Finally, the local volumetric expansion effect of hydrate-bearing sediments without fines content is more significant and shows a strong strain rate dependence characteristic. Overall, this study provides valuable insights into the long-term mechanical characteristics of hydrate reservoirs. These insights can contribute to the development of a constitutive model of hydrate-bearing sediments with time-dependence in the future, and which is meaningful to the exploitation of natural gas hydrate.

For a decade, the studies of dynamic control for unmanned aerial vehicles took a large interest, where drones as a useful technology in different areas were always suffering from several issues like instability-high energy consumption of batteries - inaccuracy of tracking targets. Different approaches are proposed for dealing with the non-linearity issues which present the most important features of this system. This paper describes our focus on the most common control strategies, known as model predictive control MPC, by developing a model based on the sensors embedded in our Tello quadrotor used for indoor purposes. The original controller of Tello quadrotor is supposed to be a slave, where the designed model predictive controller is created in MATLAB and imported to another embedded system, considered as a master; the objective of this model is to track the reference trajectory, almost keeping the stability of the system and ensure the low energy consumption. In the first part, a profound description of the modelling process of a dynamic model for drones is presented, explaining the design of MPC controller with both linear and non-linear strategies built in MATLAB. In the final part, simulation and results are discussed regarding its behaviour and performance, highlighting the MPC model's important role on drones' energy consumption profile.

Fabry disease (FD) is a X-linked inheritable storage disease caused by deficiency of al-pha-galactosidase causing lysosomal overload of sphingolipids. FD cardiomyopathy is character-ized by left ventricular (LV) hypertrophy and should be considered in differential diagnosis with all the other causes of LV hypertrophy. An early diagnosis of FD is very important because the enzyme replacement therapy (ERT) may change the fate of patients by blocking both cardiac and systemic involvement and improving prognosis. Diagnosis may be relatively easy in young patients with the typical signs ans symptoms of FD, but in male patients with late onset of disease and in females, diagnosis may be very challenging. Morphological and functional aspects are not specific for FD, which cannot be diagnosed or excluded by echocardiography. Cardiac magnetic resonance (CMR) with tissue characterization capability, is the preferred technique for the differential diagnosis of LV hypertrophy. The finding of decreased myocardial T1 value in LV hypertrophy is very specific for FD. Late gadolinium enhancement (LGE) is found in late stage of disease but it is useful to predict the cardiac response to ERT and to stratify the prognosis.

Motor impairments are among the most relevant, evident, and disabling symptoms of Parkinson’s disease that adversely affect quality of life, resulting in limited autonomy, independence, and safety. Recent studies have demonstrated the benefits of physiotherapy and rehabilitation programs specifically targeted to the needs of Parkinsonian patients in supporting drug treatments and improving motor control and coordination. However, due to the expected increase of patients in the coming years, traditional rehabilitation pathways in healthcare facilities could become unsustainable. Consequently, new strategies are needed, in which technologies play a key role in enabling more frequent, comprehensive, and out-of-hospital follow-up. The paper proposes a vision-based solution using the new Azure Kinect DK sensor to implement an integrated approach for remote assessment, monitoring, and rehabilitation of Parkinsonian patients, exploiting non-invasive 3D tracking of body movements to objectively and automatically characterize both standard evaluative motor tasks and virtual exergames. Preliminary results show the system’s ability to quantify specific features of motor performance, easily monitor changes and disease progression over time, and the possibility of using exergames to support motor condition assessment and training. The main innovation relies precisely on the integration of evaluative and rehabilitative aspects, which could be used as a closed loop to design new protocols for remote management of patients tailored to their actual conditions.

Tick-borne encephalitis virus (TBEV) is a RNA-containing enveloped virus, a member of the Flaviviridae family. Here we describe a detailed analysis of the size and structure of inactivated TBEV (the Sofyin-Chumakov TBEV strain, used in vaccines). Four analytical methods were used to analyze individual TBEV particles—negative staining TEM, cryo-EM, AFM, and NTA. All methods confirmed that the particles were monodisperse, and their mean size was ~50 nm. Cryo-EM data were used to obtain a 3D electron density model of the virus with clearly distinguishable E-proteins. STEM-EELS analysis detected phosphorous in the particles, which was interpreted as the RNA signal. Altogether, the described analytical procedures can be valuable for the further analysis of vaccine inactivated virus samples.

Lead-210 from natural atmospheric fallout is widely used in multidisciplinary studies to date recent sediments. Some of the ²¹⁰Pb-based dating models can produce historical records of sediment accumulation rates (SAR) and initial activity concentrations ( ). The former have been profusely used to track past changes in the sedimentary conditions. Both physical magnitudes are differently affected by model errors (those arising for the partial or null accomplishment of some model assumptions). This work is aimed at assessing the effects on SAR and of model errors in the CRS, CS, PLUM and TERESA dating models, due to random variability in ²¹⁰Pb fluxes, which is a usual sedimentary condition. Synthetic cores are used as virtual laboratories for this goal. Independently of the model choice, SARs are largely affected by model errors, resulting in some large and spurious deviations from the true values. This questions their general use for tracking past environmental changes. are less sensitive to model errors and their trends of change with time may reflect real changes in sedimentary conditions, as it is shown with some real cores from varved sediments.

The world's growing population is highly dependent on animal agriculture. Animal products provide nutrient-packed meals that help to sustain individuals of all ages in communities across the globe. As the human demand for animal proteins grows, the agricultural industry must continue to advance its efficiency and quality of production. One of the most commonly farmed livestock is poultry and their significance is felt on a global scale. Current poultry farming practices result in the premature death and rejection of billions of chickens on an annual basis before they are processed for meat. This loss of life is concerning regarding animal welfare, agricultural efficiency, and economic impacts. The best way to prevent these losses is through the individualistic and/or group level assessment of animal on a continuous basis. On large-scale farms, such attention to detail was generally considered to be inaccurate and inefficient, but with the integration of Artificial Intelligence (AI) assisted technology individualized and per-herd assessments of livestock are possible and accurate. Various studies have shown cameras linked with specialized systems of AI can properly analyze flocks for health concerns, thus improving the survival rate and product quality of farmed poultry. Building on the recent advancements, this review explores the aspects of AI in the detection, counting and tracking of the poultry in commercial and research-based applications.

The rapid development of multicopters has led to many security problems. In order to prevent multicopters from invading restricted areas or famous buildings, an Anti-UAV Defense System (AUDS) has been developed and become a research topic of interest. Topics under research in relation to this include electromagnetic interference guns for unmanned aerial vehicles (UAVs), high-energy laser guns, US military net warheads, and AUDSs with net guns. However, these AUDSs use either manual aiming or expensive radar to track UAVs. This paper proposes a dual-axis rotary platform with UAV automatic tracking. The tracking platform uses visual image processing technology to track and lock the dynamic displacement of a UAV. When a target UAV is locked, the system uses a nine-axis attitude meter and laser rangefinders to measure its flight altitude and calculates its longitude and latitude coordinates through sphere coordinates to provide UAV monitoring for further defense or attack missions. Tracking tests of UAV flights in the air were carried out using a DJI MAVIC UAV at a height of 30 meters to 100 meters. It was set up for UAV image capture and visual recognition for tracking under various weather conditions by a thermal imager and a full-color camera respectively. When there was no cloud during the daytime, the images captured by the thermal imager and full-color camera provide a high-quality image recognition result. However, under dark weather, black clouds will emit radiant energy and seriously affect the capture of images by a thermal imager. When there is no cloud at night, the thermal imager performs well in UAV image capture. When the UAV is tracked and locked, the system can effectively obtain the flight altitude and longitude and latitude coordinate values.

Research on bidirectional human-machine interfaces will enable the smooth interaction with robotic platforms in contexts ranging from industry to tele-medicine and rescue. This paper introduces a bidirectional communication system to achieve multisensory telepresence during the gestural control of an industrial robotic arm. We complement the gesture-based control by means of a tactile-feedback strategy grounding on a spiking artificial neuron model. Force and motion from the robot are converted in neuromorphic haptic stimuli delivered on the user’s hand through a vibro-tactile glove. Untrained personnel participated in an experimental task benchmarking a pick-and-place operation. The robot end-effector was used to sequentially press six buttons, illuminated according to a random sequence, and comparing the tasks executed without and with tactile feedback. The results demonstrated the reliability of the hand tracking strategy developed for controlling the robotic arm, and the effectiveness of a neuronal spiking model for encoding hand displacement and exerted forces in order to promote a fluid embodiment of the haptic interface and control strategy. The main contribution of this paper is in presenting a robotic arm under gesture-based remote control with multisensory telepresence, demonstrating for the first time that a spiking haptic interface can be used to effectively deliver on the skin surface a sequence of stimuli emulating the neural code of the mechanoreceptors beneath.

In this paper, an extensive study on the operation, control and performance of a hybrid photovoltaic and wind turbine (PV-WT) system is presented. The study includes the operation of the hybrid systems under different weather conditions which are reflected on a change in the wind speed and irradiance. Various loading conditions are investigated such a change in active and reactive power demands for static and dynamic loads. The performance of the hybrid system is examined via MATLAB/SIMULINK simulations.

Dietary patterns established during adolescence might play a role in adulthood disease. We examined the stability of dietary patterns (DPs) from childhood through adolescence and into young adulthood (from age 8 to 34 years). Data from 130 participants (53 females) of Saskatchewan Pediatric Bone Mineral Accrual Study (aged 8-15 years, at baseline) were included. Multiple 24-hour recalls were collected annually from 1991 to 1997, 2002 to 2005 and 2010 and 2011. Using principal component analysis, “Vegetarian-style”, “Western-like”, “High-fat, high-protein”, “Mixed” and “Snack” DPs were derived at baseline. Applied DP scores for all annual measurements were calculated using factor loading of baseline DPs and energy-adjusted food group intakes. We analyzed data using generalized estimating equations. The tracking coefficient represents correlation between baseline dietary pattern scores and all other follow-up dietary pattern scores. We found a moderate tracking for the “Vegetarian-style” (ß=0.44, P<0.001) and “High-fat, high-protein” (ß=0.39, P<0.001) DPs in females and “Vegetarian-style” DP (ß=0.30, P<0.001) in males. Remaining DPs showed a poor-to-fair tracking in both sexes. No tracking for “Western-like” DP in females was observed. Assessing overall change in DP scores from childhood to young adulthood showed an increasing trend in adherence to “Vegetarian-style” DP and decreasing trend in adherence to “High-fat, high-protein” DP by age in both sexes (P<0.001). While “Western-like” and “Mixed” DP scores increased only in males (P<0.001). These findings suggest that healthy dietary habits established during childhood and adolescence moderately continue into adulthood.

This paper investigates a distributed, coordinated motion control network based on multiple direct-drive, linear switched reluctance machines (LSRMs). A hierarchical, two-level synchronization control strategy is proposed for the four LSRMs based motion control network. The high-level, reference signals agreement algorithm is first employed to correct the asynchronous behaviors of the position commands. Then, the low-level tracking synchronization method is applied for the collaborative position control of the four LSRMs. The proposed two-level, fault-tolerant control strategy eliminates the asynchrony of the reference signals and it also guarantees the coordinated tracking control performance of the four LSRMs. Experimental results demonstrate that effective coordinated tracking control can be ensured, based on successful agreement of reference signals and an absolute tracking error falling within 2 mm can be achieved.

Glacier dynamics play an important role in the mass balance of many glaciers, ice caps and ice sheets. In this study we exploit Radarsat-2 (RS-2) Wide Fine (WF) data to determine the surface speed of Svalbard glaciers in the winters of 2012/2013 and 2013/2014 using Synthetic Aperture RADAR (SAR) offset and speckle tracking. The RS-2 WF mode combines the advantages of the large spatial coverage of the Wide mode (150 x 150 km) and the high pixel resolution (9m) of the Fine mode and thus has a major potential for glacier velocity monitoring from space through offset and speckle tracking. Faster flowing glaciers (1.95 m d^-1 - 2.55 m d^-1) which are studied in detail are Nathorstbreen, Kronebreen, Kongsbreen and Monacobreen. Using our Radarsat-2 WF dataset, we compare the performance of two SAR tracking algorithms, namely the GAMMA Remote Sensing Software and a custom written MATLAB script (GRAY method) that has primarily been used in the Canadian Arctic. Both algorithms provide comparable results, especially for the faster flowing glaciers and the termini of slower tidewater glaciers. A comparison of the WF data to RS-2 Ultrafine and Wide mode data reveals the superiority of RS-2 WF data over the Wide mode data.

This paper uses panel data to find the determinants of tracking errors in exchange traded funds (ETFs) in the Hong Kong stock market. A comparison of tracking errors between physical and synthetic ETFs also indicates that the synthetic ETFs have higher tracking errors. The magnitude of tracking errors is found to be negatively related to size but positively related to dividend yield, trading volumes of funds, and market risk. However, this study also finds that expense ratio has a negative impact on tracking error, which is not consistent with previous studies, and which this paper addresses.

COVID-19, a contagious disease caused by the novel coronavirus SARS-CoV-2, emerged in 2019 and quickly became a pandemic, infecting more than 700 million people worldwide. The disease incidence, morbidity and mortality rates have started to decline since the development of effective vaccines against the virus and the widespread immunization of the population. SARS-CoV-2 vaccines are associated with minor local or systemic adverse reactions, while serious adverse effects are rare. Thyroid-related disorders have been reported after vaccination for COVID-19, and Graves’ disease (GD) is the second most common amongst them. Thyroid eye disease (TED), an extrathyroidal manifestation of GD is rarely observed post COVID-19 vaccination. All TED cases followed mRNA-based vaccinations, but two new onset mild TED cases post viral vector vaccine (ChAdox1nCoV-19) have also been reported. We report the case of a 63-year-old woman who presented with new onset hyperthyroidism and moderate-to-severe and active TED ten days after she received the first dose of a viral vector vaccine against SARS-CoV-2. This is the first case of moderate-to-severe TED after such a vaccine. Our patient was initially treated with intravenous glucocorticoids and subsequently with intravenous rituximab, due to no response. The disease was rendered inactive after rituximab, but constant diplopia persisted, and the patient was referred for rehabilitative surgery.

Visual impairment and blindness are a growing public health problem, as they reduce the quality of life of millions of people. The management and treatment of these diseases represent a scientific and therapeutic challenge, since the different cellular and molecular actors involved in the pathophysiology are still being identified. The visual system components, particularly the retinal cells, are extremely sensitive to genetic or metabolic alterations, and immune cells activated by insults contribute to biological events that culminate with vision loss and irreversible blindness. Several ocular diseases are linked to retinal cell loss, and diseases such as retinitis pigmentosa, age-related macular degeneration, glaucoma and diabetic retinopathy are characterized by pathophysiological hallmarks that represent possibilities to study and develop novel treatments for retinal cells degeneration. Here, we present a compilation of revisited information on retinal degeneration, including pathophysiologic and molecular features, biochemical hallmarks and possible directions for novel treatments, aiming to assist as a guide for innovative research. The expansion of knowledge of the mechanistic bases of the pathobiology of eye diseases, including information on the complex interactions of genetic predisposition, chronic inflammation, and environmental and aging-related factors will allow the identification of new therapeutic strategies.

Less aligned emphasis has been given to the COVID-19 infodemic coordinating with the COVID-19 outbreak. Global profusion of tangled monikers and hashtags has found their ways in daily communication and contributed to backlash against Chinese. Official naming efforts against infodemic should be meet with a fair share of identification. Based on brief critical reviews on previous multifarious naming practices, we punctuate heuristic introspection in scientific conventions and sociocultural paradigms. Infodemiological analysis promises to articulate that people around the globe are divided in their favor stigmatized monikers in the public and scientific communities because of perceptual bias. There is no positive correlation between the degree of infection in their territories and collective perceptual bias to COVID-19. The official portfolio “COVID-19” and “SARS-CoV-2” has not become de facto standard usages, but full-fledged official names are excepted to duly contribute to the resilience of negative perceptual bias and collective behavioral propensities.

Sleep is still considered a mystery, despite intense scientific investigation. Here we present the first complete biological theory of sleep. The role of sleep is to restore the optimal homeostatic state, which is essential for tissue performance and health. Non-rapid eye movement sleep (NREMS) restores cortical and most other brain neurons, via relaxed global activity managed by thalamocortical circuits. The role of REM sleep is to restore acetylcholine (ACh) neurons, which support focused responses and hence cannot participate in global oscillations. Sleep enhances learning and memory via state restoration and ACh-affected paths. NREMS induces a lack of consciousness because global synchronous activity prevents focused responses, which are essential for consciousness. Dreams result from focused neural firing during sharp-wave ripples and REMS, and have a sense of reality because they involve the same neurons representing focused perceptual responses during wake. Anesthetics utilize a variety of mechanisms that prevent focused responses.

This paper studies the trajectory tracking control of an autonomous underwater vehicle (AUV) based on a stochastic uncertain nonlinear system. We investigate the time-varying gain adaptive control method looking for possible approaches to alleviate the heavy computational burden. Under nonlinear growth, conditions satisfy polynomial growth conditions. These two problems are resolved the fast response time and good path tracking, respectively. Novel adaptive algorithms are developed exploiting the dynamic properties of the AUV motion. By appropriately turning the original controller design problems into parameters choosing problems and then solving them in a functional time-varying observer technical theorem. In order to deal with the station error of system converges to arbitrarily small domains with stochastic uncertain disturbance. A coordinate transformation is proposed for all system states to meet boundedness. We show that the convergence of the AUV trajectory errors can be guaranteed by the proposed contraction constraints in the stability analysis, closed-loop stability is proved, and the system is asymptotically probabilistic in the global scope. They are taking advantage of the guaranteed stability. Extensive simulation studies on the AUV model demonstrate the effectiveness and robustness of the proposed approach. A real-time time-varying gain constructive control strategy is further developed for the Hardware-in-the-loop simulation; the controller design results are imported into the AUV actuator model to verify the effectiveness of the controller design.

This paper investigates the problem of cooperative standoff tracking using multiple fixed-wing unmanned aerial vehicles (UAVs) with control input constraints. In order to achieve accurate target tracking in the presence of unknown background wind and target motion, a coordinated standoff target tracking algorithm is proposed. The objective of the research is to steer multiple UAVs to fly a circular orbit around a moving target with prescribed intervehicle angular spacing. To achieve this goal, two control laws are proposed, including relative range regulation and space phase separation. On one hand, a heading rate control law based on Lyapunov guidance vector field is proposed. The convergence analysis show that the UAVs can asymptotically converge to a desired circular orbit around the target, regardless of their initial position and heading. Through rigorous theoretical proof, it is concluded that the command signal of the proposed heading rate controller will not violate the boundary constraint on heading rate. On the other hand, a temporal phase is introduced to represent the phase separation and avoid discontinuity of the wrapped space phase angle. On this basis, a speed controller is developed to achieve equal phase separation. The proposed airspeed controller met the requirement of airspeed constraint. In addition, to improve the robustness of the aircraft during target tracking, an estimator is developed to estimate the composition velocity of the unknown wind and target motion. The proposed estimator uses the offset vector between the UAV’s actual flight path and the desired orbit which is defined by Lyapunov guidance vector field to estimate the composition velocity. The stability of the estimator is proved. Simulations are conducted under different scenarios to demonstrate the effectiveness of the proposed cooperative standoff target tracking algorithm. The simulation results of indicate that, the temporal-phase-based speed controller can achieve fast convergence speed and small phase separation error. Additionally, the composition velocity estimator exhibits fast response speed and high estimation accuracy.

Dialogue State Tracking is an essential component in multi-domain dialogue systems, aiming to accurately determine the current dialogue state based on the dialogue history. Existing research has addressed the issue of multiple mappings in dialogues by employing slot self-attention as a data-driven approach. However, learning the relationships between slots from a single sample has limitations and introduces noise. In this paper, we propose an External Slot Relation Memory-based Dialogue State Tracking model (ER-DST). By utilizing an external memory storage, we learn the relationships between slots as a dictionary of multi-domain slot relations. Additionally, we employ a small filter to discard slot information irrelevant to the current dialogue state. Experimental results on the MultiWOZ2.0 and MultiWOZ2.1 benchmarks demonstrate significant improvements while reducing the time complexity to O(n).

The shield tunnels inevitably endure various damage with the service time increasing. Meanwhile, steel corrugated plate has been used extensively in multiple conditions and proved effective to strengthen the segmental joints by full-scale tests. A numerical model is proposed to probe the feasibility of using new Stainless Steel Corrugated Plate (SSCP) to reinforce the shield tunnel segments. A new method, called virtual tracking element technology, is employed to achieve the simulation of realistic stress state of the segmental joint. Moreover, the segmental joint component analysis and parametric study are conducted based on the numerical model. The results demonstrate that: (1) the virtual tracking element technology proves valid and efficient to simulate the secondary stress state of segmental joint; (2) SSCP reinforcement is not fully utilized when the grade of segmental concrete is C50 and it has abundant safety margin for potential overload; (3) SSCP reinforcement is well-performed regardless of the burial depth and reinforcement in advance is recommended.

A low-cost machine learning (ML) algorithm is proposed and discussed for spatial tracking of unknown, correlated signals in localized, ad-hoc wireless sensor networks. Each sensor is modeled as one neuron and a selected subset of these neurons are called to identify the spatial signal. The algorithm is implemented in two phases of spatial modeling and spatial tracking. The spatial signal is modeled using its M iso-contour lines at levels {ℓj}j=1M and those sensors that their sensor observations are in Δ margin of any of these levels report their sensor observations to the fusion center (FC) for spatial signal reconstruction. In spatial modeling phase, the number of these contour lines, their levels and a proper Δ are identified. In this phase, the algorithm may either use adaptive-weight stochastic gradient or scaled stochastic gradient method to select a proper Δ. Additive white Gaussian noise (AWGN) with zero mean is assumed along with the sensor observations. To reduce the observation noise’s effect, each sensor applies moving average filter on its observation to drastically reduce the effect of noise. The modeling performance, the cost and the convergence of the algorithm are discussed based on extensive computer simulations and reasoning. The algorithm is proposed for environmental monitoring. In this paper, the percentage of the communication attempts of wireless sensors is assumed as cost. Performance evaluation results show that the proposed spatial tracking approach is low cost and can model the spatial signal over time with the same performance as that of spatial modeling.

Autonomous systems require identifying the environment and it has a long way to go before putting it safely into practice. In autonomous driving systems, the detection of obstacles and traffic lights are of importance as well as lane tracking. In this study, an autonomous driving system is developed and tested in the experimental environment designed for this purpose. In this system, a model vehicle having a camera is used to trace the lanes and avoid obstacles to experimentally study autonomous driving behavior. Convolutional Neural Network models were trained for Lane tracking. For the vehicle to avoid obstacles, corner detection, optical flow, focus of expansion, time to collision, balance calculation, and decision mechanism were created, respectively.

Rigid-body visual tracking is an active research field with many practical applications including visual surveillance and intelligent transport system. In this paper, we define a new problem domain, called visual growth tracking, to track different parts of an object that grow non-uniformly over space and time for application in image-based plant phenotyping. The paper introduces a novel method to detect and track each leaf of a plant for automated leaf stage monitoring. The method has four phases: optimal view selection, plant architecture determination, leaf tracking and generation of a leaf status report. The proposed method uses a graph theoretic approach to reliably detect and track individual leaves by overcoming the challenge of leaf-losses based on temporal image sequence analysis for automatically generating the leaf status report containing the following phenotypes, i.e., the emergence timing of each leaf, total number of leaves present at any time, the day on which a particular leaf stopped growing, and the length and relative growth rate of individual leaves. The proposed method demonstrates high accuracy in detecting leaves and tracking them through the early vegetative stages of maize plants based on experimental evaluation on a publicly available benchmark dataset.

Acceptance of SNAP benefits has increased in farmers’ markets (FM) over the years. However, getting SNAP recipients to take up the opportunity of extra dollars for healthy food options remains a challenge. Thus, we tracked the use of the Double-up Food Buck (DUFB) program among SNAP recipients who visit participating FMs in Utah to understand the unique characteristics of the program users. Our results identified varying types of program users (multiple and single market shoppers, more frequent and less frequent shoppers). While our findings indicate a higher DUFB transaction in token value among frequent users, larger markets are more likely to have higher DUFB transactions with a higher number of market visits compared to smaller ones. In conclusion, while all types of users may add to the total revenue generated by participating FM, additional initiatives are required to encourage frequent visits and uptake of the program for better access to healthy foods.

Unmanned surface vehicles have the advantages of maneuverability, concealment, wide activity area and low cost of use. Therefore, they have broad application prospects. This makes unmanned surface vehicles a research hotspot at home and abroad, and the sensing technology is the basis for the unmanned surface vehicles to perform tasks. The perception technology based on optical vision has the advantages of convenient application, relatively low cost, easy data acquisition and large amount of information, and has been widely studied by scholars at home and abroad. This paper mainly discusses the research of optical vision in unmanned surface vehicles from five aspects: Firstly, the water surface image preprocessing based on unmanned surface vehicles, mainly including water surface image stabilization research and defogging enhancement research; two water boundary detection; It is the use of light vision target detection; the fourth is the surface target tracking method. Finally, the light vision research of unmanned surface vehicles is summarized and forecasted.

In Hawaiʻi, the transition from customary subsistence flooded taro agroecosystems, which regulate stream discharge rate trapping sediment and nutrients, to a plantation-style economy (c. the 1840s) led to nearshore sediment deposition - smothering coral reefs and destroying adjacent coastal fisheries and customary fishpond mariculture. To mitigate sediment transport, Rhizophora mangle was introduced in estuaries across Hawai’i (c. 1902) further altering fishpond ecosystems. Here, we examine the impact of cultural restoration between 2012-2018 at Heʻeia Fishpond, a 600-800-year-old walled fishpond. Fishpond water quality was assessed by calculating water exchange rates, residence times, salinity distribution, and abundance of microbial indicators prior to and after restoration. We hypothesized that R. mangle removal and concomitant reconstruction of sluice gates would increase mixing and decrease bacterial indicator abundance in the fishpond. We find that Heʻeia Fishpond’s physical environment is primarily tidally driven; wind forcing and river flux are secondary drivers. Post-restoration, two gates in the northeastern region account for >80% of relative flux in the fishpond. Increase in exchange rates during spring and neap tide and shorter minimum water residence time corresponded with the reconstruction of a partially obstructed 56 m gap together with the installation of an additional sluice gate in the fishpond wall. Lower mean salinities post-restoration suggests increased freshwater influx due to R. mangle removal. Spatial distribution of microbial bio-indicator species inversely correlated with salinity. Average abundance of Enterococcus and Bacteroidales did not significantly change after restoration efforts, however, average abundance of a biomarker specific to birds nesting in the mangroves decreased significantly after restoration. This study demonstrates the positive impact of biocultural restoration regimes on water flushing and water quality parameters, encouraging the prospect of revitalizing this and other culturally and economically significant sites for sustainable aquaculture in the future.

We develop and apply a systematic literature review methodology to identify and characterize the ways in which the peer-reviewed literature depicts how climate change adaptation is occurring in Australia. We reviewed the peer-reviewed, English-language literature between January 2005 and January 2018 for examples of documented adaptation actions. Our results challenge previous assumptions that adaptation action is not happening in Australia and describes adaptation processes that are underway. For the most part, actions can be described as preliminary or groundwork, with a particular focus on documenting stakeholder perspectives on climate change and adaptation, and modelling or scenario planning in the coastal zone, agriculture and health sectors. Where concrete adaptations are reported, they are usually in the agricultural sector and are most common in the Murray-Darling Basin, Australia’s food basket. The findings of the review advance our understanding of adaptation to climate change as a process and the need to consider different stages in the process when tracking adaptation.

In table tennis competitions the rule violation judgment with the greatest controversy is the height of the ball serve. This is because inaccuracy in the ball height judgment, which results in erroneous judgment, is unavoidable. Thus, we designed an automatic image judgment auxiliary system for table tennis ball height during service in this study. We used a high-speed camera to record the ball toss in the table tennis service. The designed algorithm architecture can automatically search for the ball and the position of the hand action under low light source conditions. The algorithm is mainly divided into hue-saturation-value color space processing and morphology processing using Hough transform to search for the circular ball. Experiment result shows that color segmentation can successfully and accurately determine the ball position under low light conditions. The morphology method can find the position of the hand and help determine the moment when the ball leaves the hand during the service ball toss. Finally, the actual size of the target is used to estimate the actual distance unit represented by the image pixel.

Handedness reflects functional body and hemispheric lateralization, proving relevant to contextualize cognitive and behavioral profiles. This study aimed to determine the lateralization of the hands, feet and eyes in patients with various neurological disorders and to test the Edinburgh Handedness Inventory (EHI), a widely used handedness measure. The study design included a literature overview and a clinical study. The overview spanned the literature of the past 50 years since the EHI was developed. Three hundred seventy-four patients with immune-mediated (IM) or noIM neurological diseases and healthy subjects underwent personal and family history of handedness, stressful events and IM diseases, and EHI. The literature overview showed that handedness, which develops under the influence of genetic and acquired factors, is an indirect indicator of hemispheric lateralization; hemispheric lateralization is bidirectionally related to the immune system. In the clinical study, the EHI showed appropriate reliability and structural validity; its scores related to chronological age, onset age, and disease duration and helped distinguish patients with IM disease from other patients and healthy subjects. Therefore, handedness may change over the course of life under the influence of pathology and could predict IM neurological diseases. The EHI is an appropriate measure of handedness.

Background and Objectives: Mucilaginous substances from plant extracts are known to be able to support the lubricating effect of hyaluronic acid (HA) in dry eye disease (DED). In this pilot study, the combined lubricating effect of HA and mallow extract (Malva sylvestris L.) in patients with DED was assessed. Materials and Methods: 20 patients at 5 ophthalmological practices in Italy were treated with eye drops, containing HA and mallow extract on the one hand, and with eye drops containing HA only, on the other hand, in a two-period crossover design. As primary endpoints, the tear film breakup time (TBUT), the reduction of lissamine green staining of the ocular surface (Oxford Scheme, OS), and the safety and efficacy assessment by the ophthalmologists were evaluated. As secondary variables, the patient symptom score, the ocular surface index (OSDI), and the satisfaction, preference and efficacy judgement by the patients were evaluated. All data were analysed descriptively in addition to an exploratory analysis of the target variables. Results: Both products were well tolerated. There were no statistically significant differences, with regard to the TBUT, OS and OSDI, between both treatments. Anyway, the efficacy and safety assessments by the ophthalmologists and the patients showed results in favour of the combined product. Conclusion: The addition of mallow extract to HA containing eye drops enhances the treatment of DED at least with respect to subjective measurements. Further assessments will have to be done to prove and explain this observation in terms of measurable parameters, e.g. markers for inflammatory cytokines.

Background: Systemic lupus erythematosus (SLE) is characterized by inflammation and cardiovascular complications. Our study aimed to investigate subclinical and early indicators of systolic myocardial dysfunction in SLE patients using advanced echocardiographic methods and biomarkers. Methods: In this cross-sectional study, we enrolled 102 SLE patients without known cardiac impairment and 51 healthy controls. Demographics, disease characteristics, laboratory results, disease activity (SLEDAI) and organ damage (SDI) indices were recorded. Left ventricular global longitudinal strain (GLS) and myocardial work indices were assessed by utilizing speckle tracking echocardiography. In addition, high sensitivity C-reactive protein (hsCRP), high sensitivity troponin (hsTn) and N-terminal-pro B-type natriuretic peptide (NT-proBNP) levels were measured in blood samples. Results: In comparison to controls, SLE patients had significantly higher GLS (-19.94±2.71%vs-21.15±1.55%, p&lt;0.001) and global wasted work (GWW) (94±71mmHg%vs71±49 mmHg%, p=0.025). Notably, NT-proBNP and hsTn were threefold and twofold higher in SLE group compared to control group, respectively (p&lt;0.001). Within SLE cohort, patients with at least moderate disease activity (SLEDAI≥4) both biomarkers were significantly elevated than those with low disease activity (SLEDAI&lt;4). Conclusion: Advanced echocardiographic parameters combined with specific biomarkers have a promising role in detecting systolic dysfunction at an early phase in SLE patients, potentially enabling timely interventions to mitigate cardiovascular risk.

This review study, delves into the groundbreaking potential of quantum dots in revolutionizing the field of stem cell tracking for regenerative medicine. Beginning with an introduction that underscores the pivotal role of stem cell tracking in regenerative medicine, this review introduces quantum dots as promising tools for this purpose. It proceeds to explore the fundamental properties of quantum dots, including the quantum confinement effect, size-dependent emission, and exceptional brightness, which render them ideal candidates for stem cell tracking. The historical evolution and recent advancements of quantum dot technology in biomedicine are discussed, emphasizing their growing importance in terms of biocompatibility and safety. Furthermore, various labeling strategies for stem cells using quantum dots are detailed, encompassing surface modification and internalization techniques, with a comparison of their respective advantages and drawbacks. A comprehensive exploration of the wide range of imaging modalities that synergize with quantum dots for stem cell tracking is presented, accompanied by an evaluation of their strengths and limitations. Real-world applications of quantum dot-based stem cell tracking in regenerative medicine, spanning tissue regeneration to disease modeling, are showcased, with illuminating case studies. Current challenges and limitations in quantum dot-based stem cell tracking, including long-term stability and regulatory considerations, are addressed, and innovative directions and emerging trends in quantum dot technology are proposed. Safety considerations and strategies to enhance quantum dot biocompatibility within biological systems are discussed, while ethical and regulatory implications related to their use in stem cell tracking are explored, promoting responsible research and development practices. Finally, the review concludes by summarizing key insights and takeaways, reaffirming the transformative potential of quantum dots in advancing stem cell tracking and the field of regenerative medicine.

This work focuses on addressing the dynamic positioning and trajectory tracking problem for a 4 degree-of-freedom (DOF) unmanned underwater vehicle (UUV) in the presence of nonlinear dynamics, parametric uncertainties, system constraints, and time-varying external disturbances. To tackle this problem, a disturbance observer-based control (DOBC) scheme is proposed. The scheme is structured around the model predictive control (MPC) method integrated with an extended active observer (EAOB). Compared to the conventional disturbance observer, the EAOB has the unique ability to handle both external disturbances and system/measurement noises simultaneously. The EAOB leverages a combination of sensor measurements and a system dynamic model to estimate disturbances in real-time, which allows continuous estimation and compensation of time-varying disturbances back to the controller. The proposed disturbance observer-based MPC (DOBMPC) is implemented by feeding the estimated disturbances back into the MPC’s prediction model, which forms a robust adaptive controller with a parameter-varying model. The proposed control strategy is validated through simulations in a Gazebo and Robot Operating System (ROS) environment. The results show that it can effectively reject unpredictable disturbances and improve the UUV’s control performance.

Environmental nanoparticles have been shown to exist in most aquatic environments, and environmental nanoparticles in water distribution systems significantly affect water quality. However, little research has been conducted on the environmental nanoparticles in mineral water, which is a special water resource. Nanoparticle tracking analysis (NTA) and high-resolution transmission electron microscopy (HRTEM) were conducted. This study was the first to identify many environmental nanoparticles in natural mineral water in Zibo City, Shandong Province, China. The results of the NTA showed that the concentration of the particles was 5.5 ×106 particles/mL and the peak diameter of the size distribution was 180 nm. The HRTEM showed that the nanoparticles were granular, pinniform, rodlike, and flakey in shape, and some of the nanoparticles existed in aggregation. The energy-dispersive spectrometry results showed that most of the nanoparticles contained O, Mg, Ca, Si, Fe, Ti, and P, and some of them also contained F, V, S, and Mn. When combined with the characteristics of the selected area electron diffraction pattern, the nanoparticles were confirmed to be Ca-bearing nanoparticles, attapulgite nanorods, MnO2 nanosheets, and TiO2 nanoparticles. These results indicate a new form of elements occurring in mineral water. In addition, based on the chemical and physical characteristics of the nanoparticles and mineral water, these environmental nanoparticles in the mineral water are likely to be the weathering byproducts of minerals. These nanoparticles within mineral water provide a good opportunity for understanding the behavior of nanoparticles in varied systems. Moreover, environmental nanoparticle science is important for continuing efforts in water safety, treatment, and remediation.

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.

Pig behavior is an integral part of health and welfare management, as pigs usually reflect their inner emotions through behavior change. The livestock environment plays a key role in pigs' health and wellbeing. A poor farm environment increases the toxic GHGs, which might deteriorate pigs' health and welfare. In this study a computer-vision-based automatic monitoring and tracking model was proposed to detect short-term pigs' physical activities in a compromised environment. The ventilators of the livestock barn were closed for an hour, three times in a day (07:00-08:00, 13:00-14:00, and 20:00-21:00) to create a compromised environment, which increases the GHGs level significantly. The corresponding pig activities were observed before, during, and after an hour of the treatment. Two widely used object detection models (YOLOv4 and Fast-er R-CNN) were trained and compared their performances in terms of pig localization and posture detection. The YOLOv4, which outperformed the Faster R-CNN model, coupled with a Deep-SORT tracking algorithm to detect and track the pig activities. The results showed that the pigs became more inactive with the increase in GHG concentration, reducing their standing and walking activities. Moreover, the pigs also shortened their sternal-lying posture increasing the lateral lying posture duration at higher GHG concentration. The high detection accuracy (mAP: 98.67%) and tracking accuracy (MOTA: 93.86% and MOTP: 82.41%) signify the models’ efficacy in monitoring and tracking pigs' physical activities non-invasively.

This paper is regarding design and program an Micro-controller Arduino Uno board by using Arduino software to work as a photo-sensor(Active) single axial solar tracker system(SASTS). A solar panel, two photo-resistors (LDR) in two sides (north/south) of the photo-voltaic(PV) and a servo motor are connected to the Uno board, which is running a code that prepared by Arduino software IDE in advanced then it works as a tracking system. Here, the LDRs send the signal of presence or absence of the light to the board and based on that sent signal the Uno reflects a new signal to the servo motor to rotate and finds the light source. Lastly, the photo-sensor single axis tracker is made while Continuously, the system tries to face the panel to the sun and whilst changing the irradiance intensity it starts searching to find the angle of highest irradiance. Based on results that are extracted from the data, the tracker system significantly boosts the output efficiency of the solar panel. By using the Micro-controller Uno board, LDRs, servo motor and special designed mechanical base, the tracking system is constructed, based on acquired data the influence of the STS on the increasing the solar panel efficiency is more obvious. Significantly, the tracker system rises the efficiency of the PV .

Precise and fast position tracking is essential for the correct operation of many industrial robots and CNC machine tools. This subject is also important in the control of the mount of the astronomical telescope, especially for the tracking of artificial satellites. As system parameters can change, a control method that is robust to changes in parameters must be used. Such a method is the sliding control, which, however, ensures the robustness only after reaching the sliding surface. Therefore, a new method was proposed in the paper, which eliminates the phase of reaching the sliding surface. The method consists of using a reference trajectory generator and determining the generalized error in relation to this trajectory. The procedure for designing the control system is presented. Next, the proposed method was verified on the laboratory stand. The described control method provides a robust system operation and can be easily implemented in the control system.

We introduce PyNTA, a modular instrumentation software for live particle tracking. By using the multiprocessing library of Python and the distributed messaging library pyZMQ, PyNTA allows users to acquire images from a camera at close to maximum readout bandwidth while simultaneously performing computations on each image on a separate processing unit. This publisher/subscriber pattern generates a small overhead and leverages the multi-core capabilities of modern computers. We demonstrate capabilities of the PyNTA package on the featured application of nanoparticle tracking analysis. Real-time particle tracking on megapixel images at a rate of 50 Hz is presented. Reliable live tracking reduces the required storage capacity for particle tracking measurements by a factor of approximately 10³, as compared with raw data storage, allowing for a virtually unlimited duration of measurements

Autonomous aerial refueling technology is an effective solution to extend flight duration of unmanned aerial vehicles, and also a great challenge due to its high risk. For autonomous probe-and-drogue refueling tasks, relative navigation to provide relative position between the receiver aircraft and the refueling drogue is the first and essential step, and vision-based method is the most frequently used. A new monocular vision navigation sensor with image processing strategy consisting of the drogue detection method and the tracking method is developed for autonomous aerial refueling in this paper. In the drogue detection method, thresholding and mathematical morphology method are adopted to eliminate image interference, and contours extraction method is applied to obtain all contours, which are then subsequently checked to achieve target contour of drogue. In the tracking method, a rectangle of interest (ROI) of current frame image is determined by positioning results of last frame, and then processed by the previous drogue detection method. Finally, the proposed image processing strategy in monocular vision navigation sensor is validated using real flight images, which are captured from an autonomous aerial refueling testbed using a micro six-rotor aircraft as receiver aircraft.

For improving the tracking accuracy and model switching speed of maneuvering target tracking in nonlinear systems, a new algorithm named interacting multiple model fifth-degree spherical simplex-radial cubature filter (IMM5thSSRCKF) is proposed in this paper. The new algorithm is a combination of the interacting multiple model (IMM) filter and fifth-degree spherical simplex-radial cubature filter (5thSSRCKF). The proposed algorithm makes use of Markov process to describe the switching probability among the models, and uses 5thSSRCKF to deal with the state estimation of each model. The 5thSSRCKF is an improved filter algorithm, which utilizes the fifth-degree spherical simplex-radial rule to improve the filtering accuracy. Finally, the tracking performance of the IMM5thSSRCKF is evaluated by simulation in a typical maneuvering target tracking scenario. Simulation results show that the proposed algorithm has better tracking performance and quicker model switching speed when disposing maneuver models compared with IMMUKF, IMMCKF and IMM5thCKF.

Abstract: The glucocorticoid receptor (GR), including both alternative spliced isoforms (GRa and GRb), has been implicated in the development of primary open-angle glaucoma (POAG) and iatrogenic glucocorticoid-induced glaucoma (GIG). POAG is the most common form of glaucoma, which is the leading cause of irreversible vision loss and blindness in the world. Glucocorticoids (GCs) are commonly used therapeutically for ocular and numerous other diseases/conditions. One serious side effect of prolonged GC therapy is the development of iatrogenic secondary ocular hypertension (OHT) and OAG (i.e. GC-induced glaucoma (GIG)) that clinically and pathologically mimics POAG. GC-induced OHT is caused by pathogenic damage to the trabecular meshwork (TM), a tissue involved in regulating aqueous humor outflow and intraocular pressure. TM cells derived from POAG eyes (GTM cells) have lower expression of GRb, a dominant negative regulator of GC activity, compared to TM cells from age-matched control eyes. Therefore, GTM cells have a greater pathogenic response to GCs. Almost all POAG patients develop GC-OHT when treated with GCs, in contrast to a GC responder rate of 40% in the normal population. Increased expression of GRb can block GC-induced pathogenic changes in TM cells and reverse GC-OHT in mice. Endogenous expression of GRb in the TM may relate to differences in the development of GC-OHT among the normal population. A number of studies have suggested increased levels of endogenous cortisol in POAG patients as well as differences in cortisol metabolism, suggesting that GCs may be involved in the development of POAG. Additional studies are warranted to better understand the molecular mechanisms involved in POAG and GIG in order to develop new disease modifying therapies to better treat these two sight threatening forms of glaucoma.

This paper proposes several LabVIEW applications to accomplish the data acquisition, processing, features extraction and real-time classification of the electroencephalographic (EEG) signal detected by the embedded sensor of the NeuroSky Mindwave Mobile headset. The LabVIEW applications are aimed at the implementation of a Brain-Computer Interface system, which is necessary to people with neuromotor disabilities. It is analyzed a novel approach regarding the preparation and automatic generation of the EEG dataset by identifying the most relevant multiple mixtures between selected EEG rhythms (both time and frequency domains of raw signal, delta, theta, alpha, beta, gamma) and extracted statistical features (mean, median, standard deviation, route mean square, Kurtosis coefficient and others). The acquired raw EEG signal is processed and segmented into temporal sequences corresponding to the detection of the multiple voluntary eye-blinks EEG patterns. The main LabVIEW application accomplished the optimal real-time artificial neural networks techniques for the classification of the EEG temporal sequences corresponding to the four states: 0 - No Eye-Blink Detected; 1 - One Eye-Blink Detected; 2 – Two Eye-Blinks Detected and 3 – Three Eye-Blinks Detected. Nevertheless, the application can be used to classify other EEG patterns corresponding to different cognitive tasks, since the whole functionality and working principle could estimate the labels associated with various classes.

Background: Inadequate meibomian glands (MGs) secretion can lead to dry eye signs and symptoms. Tear film lipid layer (TFLL) secreted by MGs protects and prevents rapid evaporation of tear film. Our purpose was to assess TFLL alteration and function in patients with evaporative dry eye (EDE) using tear interferometry after optimal pulse light technology (OPT) intense pulsed light (IPL). Methods: This prospective randomized examiner-masked sham- controlled study included 86 participants (142 eyes) with DED. IPL or sham procedure was performed on day 0, 21, and 42. Ocular Surface Disease Index (OSDI), non-invasive breakup time (NITBUT), interferometric fringe pattern determined TFLL quality, fluorescein staining (FS), and meibum gland (MG) were assessed at day 0, 21, 42 and 3-month. Results: At 3-month, TFLL, NITBUT, MG drop-out, MG quality, MG expressibility, FS and OSDI improved significantly (P<0.05) in the IPL group, while the sham group had no significant improvements. All DE parameters significantly correlated with the improvement in TFLL following IPL treatment. Additionally, artificial tears usage was significantly less in the IPL group from D-42 onwards. Conclusion: IPL treatment demonstrated the ability to improve TFLL quality and clinically reduced sign and symptoms of DED thereby reducing the frequency of artificial tears usage.

Abstract: We have filled a 24 mm diameter glass sphere with a transparent polymer-gel that is radio-fluorogenic, i.e. it becomes (permanently) fluorescent when irradiated, with an intensity proportional to the local dose deposited. The gel consists of >99.9% tertiary-butyl acrylate (TBA) pre-polymerized to ~15% conversion, and ~100 ppm maleimido-pyrene (MPy). Its dimensions and physical properties are close to those of the vitreous body of the human eye. We have irradiated the gel with a 3 mm diameter, 200 kVp X-ray beam with a dose rate of ~1 Gy/min. A 3D (video) view of the beam within the gel has been constructed from tomographic images obtained by scanning the sample through a thin sheet of UV light. To minimize optical artifacts, the cell was immersed in a square tank containing a refractive-index-matching medium. The 20%-80% penumbra of the beam was determined to be ~0.4 mm. The research was a preparatory investigation of the possibility of using the method to monitor the millimetre diameter proton pencil beams used in ocular radiotherapy.

The alteration of the delicate balance that regulates the secretion and distribution of the tear film determines the dry eye (DE) syndrome, because the tear film represents the interface between the eye and the environment. Despite having a multifactorial origin, the main risk factors for the emergence of the ocular disease are female gender and advanced age. Likewise, morphological changes in several glands and in chemical composition of their secretions such as proteins, mucins, lipidics, aqueous tears, and salinity, are highly relevant factors to maintain a condition of good health of the ocular anterior segment. Another key factor of recurrence and onset of the disease is the presence of local and/or systemic infiammation that reflex on the ocular surface. However, it is one of the most commonly encountered disease in clinical practice and many other causes related to daily life and to lengthen the average life will contribute to the beginning. This review will consider how and what disorders of the ocular surface are responsible for a widespread pathology so. In the end, the most appropriate and new therapies will be briefly exposed according to the specific pathology.

The performance of laser beams in tracking Lissajous scan trajectories is severely limited by beam jitter. To enhance the performance of fast steering mirror (FSM) control in tracking Lissajous scan trajectories, this paper proposed a fractional order active disturbance rejection controller (FOADRC) and verified its effectiveness in improving system scanning tracking accuracy. A dynamic mathematical model of fast steering mirror was studied and the design of parameters for the control mode of the closed-loop system was determined. A reduced order linear active disturbance rejection controller suitable for FSM systems was designed and the corresponding fractional order proportional differentiation (FOPD) controller were determined according to the mathematical model. The use of the designed controller enabled high-performance tracking of high-frequency Lissajous scanning curves (X-axis 500 Hz, Y-axis 350 Hz) and met the need for high-frequency repetitive scanning. The controller has the characteristics of simple implementation and low computational complexity and is suitable for closed-loop control applications in engineering.

With the vast amount of goods being shipped around the world, there is a need to track and manage various types of assets, particularly shipping containers. Logistics industries dealing with small facilities, shipments, equipment, and vehicles must be tracked. There are many applied asset tracking systems such as Radio-Frequency Identification (RFID), Bluetooth Low Energy (BLE) Beacon, and Long-Range Radio (LoRa). This paper presents these systems and focuses on locating assets using LoRaWAN technology, which has a positive impact on the responsive and sustainable cities in Egypt. IoT-based Long Range (LoRa) is a low-power, wide-area communication technology that uses radio frequencies to transmit data over long distances. The extended range, low power consumption, low maintenance, and the ability to store location data when the end node that needs to connect to the asset is out of the gateway's coverage make LoRa a good choice for developing asset-tracking applications. This paper introduces a real-time tracking experiment as a result of a project implementation, whose goals are aligned with industry, innovation, and infrastructure and Sustainable Cities and Communities, the Sustainable Development Goals (SDGs) No. 9 and 11.