Osteoarthritis (OA) is a common joint disorder found mostly in elderly people. The role of mechanical behavior in the progression of OA is complex and remains unclear. The stress-relaxation behavior of human articular cartilage in clinically defined osteoarthritic stages may have importance in diagnosis and prognosis of OA. In this study we investigated differences in the biomechanical responses among human cartilage of ICRS grades I, II and III using polymer dynamics theory. We collected 24 explants of human articular cartilage (eight each of ICRS grade I, II and III) and acquired stress-relaxation data applying a continuous load on the articular surface of each cartilage explant for 1180 s. We observed a significant decrease in Young’s modulus, stress-relaxation time, and stretching exponent in advanced stages of OA (ICRS grade III). The stretch exponential model indicated that significant loss in hyaluronic acid polymer might be the reason for the loss of proteoglycan in advanced OA. This work encourages further biomechanical modelling of osteoarthritic cartilage utilizing these data as input parameters to enhance the fidelity of computational models aimed at revealing how mechanical behaviors play a role in pathogenesis of OA.

Mental stress is one of the serious factors that lead to many health problems. Scientists and physicians have developed various tools to assess the level of mental stress in its early stages. Several neuroimaging tools have been proposed in the literature to assess mental stress in the workplace. Electroencephalogram (EEG) signal is one important candidate because it contain rich information about mental states and condition. In this paper, we review the existing EEG signal analysis methods on the assessment of mental stress. The review highlights the critical differences between the research findings and argues that variations of the data analysis methods contribute to several contradictory results. The variations in results could be due to various factors including lack of standardized protocol, the brain region of interest, stressor type, experiment duration, proper EEG processing, feature extraction mechanism, and type of classifier. Therefore, the significant part related to mental stress recognition is choosing the most appropriate features. In particular, a complex and diverse range of EEG features, including time-varying, functional, and dynamic brain connections, requires integration of various methods to understand their associations with mental stress. Over this, the review suggests fusing the cortical activations with the connectivity network measures and deep learning approaches to improve the accuracy of mental stress level assessment.

Organisms in the wild have cryptic life stages that are sensitive to changing environmental conditions and can be difficult to survey. In this study, I used mark-recapture methods to repeatedly survey Anaea aidea (Nymphalidae) caterpillars in nature, then modeled caterpillar demography as a hidden Markov process to assess if temporal variability in temperature and density influence the survival and growth of A. aidea over time. Individual encounter histories result from the joint likelihood of being alive and observed in a particular stage, and I included hidden states by separating demography and observations into parallel and independent processes. I constructed a demographic matrix containing the probabilities of all possible fates for each stage, including hidden states, e.g., eggs and pupae. I observed both dead and live caterpillars with high probability. Peak caterpillar abundance attracted multiple predators, and survival of fifth instars declined as per capita predation rate increased through spring. A time lag between predator and prey abundance was likely the cause of improved fifth instar survival estimated at high density. Growth rates showed an increase with temperature, but the most likely model did not include temperature. This work illustrates how state-space models can include unobservable stages and hidden state processes to evaluate how environmental factors influence vital rates of cryptic life stages in the wild.

Non-Alcoholic Fatty Liver Disease (NAFLD) is a term that covers a range of hepatic disorders involving fat deposits in the liver. NAFLD begins with simple steatosis and progresses into non-alcoholic steatohepatitis (NASH) characterised by inflammation, fibrosis, apoptosis, oxidative stress, lipid peroxidation, mitochondrial dysfunction and release of adipokines and pro-inflammatory cytokines. Oxidative stress and antioxidants are known to play a vital role in the pathogenesis and severity of NAFLD/NASH. A number of oxidative stress and antioxidant markers are employed in the assessment of the pathological state and progression of the disease. In this article, we review several biomarkers of oxidative stress and antioxidants that have been measured at clinical and experimental levels. The levels/ activity in various models reviewed are also included. Also included is a comprehensive description of oxidative stress, sources and contribution to the pathogenesis of NAFLD/NASH

Cardiovascular disease is the most common cause of death. Oxidative stress and inflammation are pathophysiological processes involved in the development of cardiovascular diseases, so anti-inflammatory and antioxidant agents that modulate redox balance have become the targets of research to evaluate their molecular mechanisms and therapeutic properties. Astaxanthin, a carotenoid of the xanthophyll group, has potent antioxidant effects due to its molecular structure and its arrangement in the plasma membrane, factors that favor the neutralization of reactive oxygen and nitrogen species. This carotenoid also stands out for its anti-inflammatory activity, possibly interrelated with its antioxidant effect, as well as for its modulation of lipid and glucose metabolism. Considering the potential positive effects of astaxanthin on cardiovascular health evidenced by preclinical and clinical studies, this paper describes the molecular and cellular mechanisms related to the antioxidant and anti-inflammatory properties of this carotenoid in cardiovascular diseases, especially atherosclerosis.

Evolutionary convergence provides natural opportunities to investigate how, when, and why novel traits evolve. Many convergent traits are complex, highlighting the importance of explicitly considering convergence at different levels of biological organization, or ‘multi‐level convergent evolution’. To investigate multi‐level convergent evolution, we propose a holistic and hierarchical framework that emphasizes breaking down traits into several functional modules. We begin by identifying long‐standing questions on the origins of complexity and the diverse evolutionary processes underlying phenotypic convergence to discuss how they can be addressed by examining convergent systems. We argue that bioluminescence, a complex trait that evolved dozens of times through either novel mechanisms or conserved toolkits, is particularly well suited for these studies. We present an updated estimate of at least 94 independent origins of bioluminescence across the tree of life, which we calculated by reviewing and summarizing all estimates of independent origins. Then, we use our framework to review the biology, chemistry, and evolution of bioluminescence, and for each biological level identify questions that arise from our systematic review. We focus on luminous organisms that use the shared luciferin substrates coelenterazine or vargulin to produce light because these organisms convergently evolved bioluminescent proteins that use the same luciferins to produce bioluminescence. Evolutionary convergence does not necessarily extend across biological levels, as exemplified by cases of conservation and disparity in biological functions, organs, cells, and molecules associated with bioluminescence systems. Investigating differences across bioluminescent organisms will address fundamental questions on predictability and contingency in convergent evolution. Lastly, we highlight unexplored areas of bioluminescence research and advances in sequencing and chemical techniques useful for developing bioluminescence as a model system for studying multi‐level convergent evolution.

The RPL protocol is a routing protocol for low power and lossy networks. In such a network, energy is a very scarce resource; so many studies are focused on minimizing global energy consumption. End-to-end latency is another important performance indicator of the network, but existing research tends to focus more on energy consumption and ignore the end-to-end delay of data transmission. In this paper, we propose a kind of energy equalization routing protocol to maximize the surviving time of the restricted nodes so that the energy consumed by each node is close to each other. At the same time, a multi-path forwarding route is proposed based on the cache utilization. The data is sent to the sink node through different parent nodes at a certain probability, not only by selecting the preferred parent node, thus avoiding buffer overflow and reducing end-to-end delay. Finally, the two algorithms are combined to accommodate different application scenarios. The experimental results show that the proposed three improved schemes improve the reliability of the routing, extend the lifetime of the network, reduce the end-to-end delay, and reduce the number of DAG reconfiguration.

Traditional potential transformers have problems of large volume, difficulty in insulation, iron core saturation, ferroresonance overvoltage and poor transient response characteristics. The voltage sensor based on the principle of electric field coupling and differential input structure does not need to contact the measured object or ground, and can avoid the above problems. However, it requires a sufficiently high capacitance between the differential electrodes to obtain sufficient accuracy and a high voltage division ratio. The existing method of using mutual capacitance between the differential electrodes will cause many problems and fail to meet the practical needs. To solve the above problems, this paper innovatively uses multi-layer ceramic capacitor to replace the mutual capacitance and designs a new type of voltage sensor. In addition, by using single bypass small resistance grounding method to increase the input impedance of the differential signal processing circuit, error of the sensor is further reduced. The experimental results show that the sensor has excellent accuracy and great transient response characteristics. The ratio error under power frequency is within ±0.5% and the phase error is within 1. The ratio error in the range of 500 Hz∼30 kHz is within ±5% and the phase error is within 5. Moreover, it has the advantages of low cost, miniaturization, flexible shape and easy to adjust the voltage division ratio. These characteristics indicate that the sensor has good voltage measurement and sensor network potential.

The quality of digital elevation models (DEMs) is inevitably affected by the limitations of the imaging modes and the generation methods. One effective way to solve this problem is to merge the available datasets through data fusion. In this paper, a fusion-based global DEM dataset (82°S-82°N) is introduced, which we refer to as GSDEM-30. This is a 30-m DEM mainly reconstructed from the unfilled SRTM1, AW3D30, and ASTER GDEM v2 datasets combining the multi-source and multi-scale fusion techniques. A comprehensive evaluation of the GSDEM-30 data, as well as the 30-m ASTER GDEM v2 and AW3D30 DEM, was presented. Global ICESat GLAS data and the local National Elevation Dataset (NED) were used as the reference for the vertical accuracy validation, while GlobeLand30 was introduced for the landscape analysis. Furthermore, we employed the maximum slope approach to detect the potential artefacts in the DEMs. The results show that the GDEM data are seriously affected by noise and artefacts. With the advantage of the multiple datasets and the refined post-processing, the GSDEM-30 are contaminated with fewer anomalies than both ASTER GDEM and AW3D30. The fusion techniques used can also be applied to the reconstruction of other fused DEM datasets.

We present information theoretic search strategies for single and multi-robot teams to localize the source of biochemical contaminants in turbulent flows. The robots synthesize the information provided by sporadic and intermittent sensor readings to optimize their exploration strategy. By leveraging the spatio-temporal sensing capabilities of a mobile sensing network, our strategies result in control actions that maximize the information gained by the team while optimizing the time spent localizing the position of the biochemical source. By leveraging the team's ability to obtain simultaneous measurements at different locations, we show how a multi-robot team is able to speed up the search process resulting in a collaborative information theoretic search strategy. We validate our proposed strategies in both simulations and experiments.

Accurate and timely rainfall prediction enhances productivity and can aid proper planning in sectors such as agriculture, health, transport and water resources. This study is aimed at improving rainfall prediction using ensemble methods. It first assesses the performance of six convective schemes (Kain–Fritsch (KF); Betts–Miller–Janji´c (BMJ); Grell–Fretas (GF); Grell 3D ensemble (G3); New–Tiedke (NT) and Grell–Devenyi (GD)) using the root mean square error (RMSE) and mean error (ME) focusing on the March–May 2013 rainfall period over Uganda. 18 ensemble members are generated from the three best performing convective schemes (i.e. KF, GF & G3). The performance of three ensemble methods (i.e. ensemble mean (EM); ensemble mean analogue (EMA) and multi–member analogue ensemble (MAEM)) is also analyzed using the RMSE and ME. The EM presented a smaller RMSE compared to individual schemes (EM:10.02; KF:23.96; BMJ:26.04; GF:25.85; G3:24.07; NT:29.13 & GD:26.27) and a better bias (EM:-1.28; KF:-1.62; BMJ:-4.04; GF:-3.90; G3:-3.62; NT:-5.41 & GD:-4.07). The EMA and MAEM presented 13 out of 21 stations & 17 out of 21 stations respectively with smaller RMSE compared to EM thus demonstrating additional improvement in predictive performance. The MAEM is a new approach proposed and described in the study.

In the oil palm industry, stands age is an important parameter to monitor the sustainability of cultivation, to develop the growth yield model, to identify the disease or stressed area, and to estimate the carbon storage capacity. This research is focused to estimate and distinguish oil palm stands age based on crown/ canopy density obtained using Forest Canopy Density (FCD) model derived from four indices as follows; Advanced Vegetation Index, Bare Soil Index, Shadow Index, and Thermal Index. FCD model employs multi temporal image analysis resulting four classes of oil palm stands age categorized as seed with FCD value of 29–56% (0 years), young with FCD value of 56–63% (1–9 years), teen with FCD value of 63–80% (10–15 years), and mature with FCD value of >80% (>15 years). Minimum canopy density value is 29% even in the zero years old indicates incomplete land clearance or the type of seed planted in the land.

The scratch test consists in pushing a tool across the surface of a material at a given penetration depth or applied load. It has several applications in Science and Engineering including strength testing, damage and quality control of thin films and coatings. Despite numerous attempts in scientific literature, the application of scratch test to characterizations of fracture properties remains a heavily controversial topic. Therefore, this investigation arises as an experimental study in order to assess the fracture toughness using scratch test. A study on the effect of cryogenic treatment, performed after tempering, on fracture toughness, via scratch test experiments, of different tool steels has been made. A laboratory investigation on AISI D2, AISI M2 and X105CrCoMo18 steel confirms the possibility of increasing the fracture toughness by carrying out the cryogenic treatment after the usual heat treatment

Urban areas are centres of business and innovation. Freight transport is indispensable for the proper functioning of any modern urban society. Urban areas can’t function without an appropriate freight transport system, due to the need to replenish stocks of food and other goods in retail shops. The complexity of the decisions concerning implementation of measures to improve the movement of goods in the city requires tools designed to support this process. The purpose of this article is to introduce the possibility of applying the Analytic Hierarchy Process (AHP) as well as the Decision Making Trial and Evaluation Laboratory Method (DEMATEL) in choosing a set of measures and in analysing in the field of distribution logistics, which will help to solve the delivery problems and streamline the cargo flows in Szczecin, in the context of sustainable development.

Nanopores with irregularities are promising tools for distinguishing nano-size objects by their shape, but the forces on the object that critically influence its axial and rotational movement are unclear. The physics of the situation was described using the Poisson-Nernst-Planck and Navier-Stokes equations. With uniformly charged object the axial Coulomb and dielectric pressure (which opposes it and is surprisingly important), control the object's axial movement and rotation. Even without external pressure the hydrodynamic pressure is significant (negative at its upper and positive at its lower surface), but its total value is almost zero. If the object is charged only on the upper surface the axial upper Coulomb pressure is near zero close to the center, but negative near its end (the pressure is zero at the lower surface). The total axial dielectric pressure, which is largely dominated by the pressure at the upper surface, is positive along the length of the object becoming pronounced near its end. The axial hydrodynamic pressure is negative and significant at the upper surface (zero at the lower surface), diminishes in value near the object's end, critically influencing its axial movement, which becomes much faster. At its end the axial dielectric pressure prevails, and controls its rotation.

Surface damage on honeycomb aircraft panels is often measured manually, and is therefore subject to variation based on inspection personnel. Eddy current testing (ECT) is sensitive to variations in probe-to-specimen spacing, or lift-off, and is thus promising for high resolution profiling of surface damage on aluminum panels. Lower frequency testing also allows inspection through the face sheet, an advantage over optical 3D scanning methods. This paper presents results from the ECT inspection of surface damage on an approximately flat aluminum honeycomb aircraft panel, and compares the measurements to those taken using optical 3D scanning technology. An ECT C-Scan of the dented panel surface was obtained by attaching the probe to a robotic scanning apparatus. Data was taken simultaneously at four frequencies of 25, 100, 400 and 1,600 kHz. A reference surface was then defined that approximated the original, undamaged panel surface, which also compensated for the effects of specimen tilt and thermal drift within the ECT instrument. Data was converted to lift-off using height calibration curves developed for each probe frequency. A damage region of 22,550 mm² area with dents ranging in depth from 0.13-1.01 mm was analyzed. The method was accurate at 1,600 kHz to within 0.05 mm (2s) when compared with 231 measurements taken via optical 3D scanning. Testing at 25 kHz revealed a 3.2 mm cell size within the honeycomb core, which was confirmed via destructive evaluation. As a result, ECT demonstrates potential for implementation as a method for rapid in-field aircraft panel surface damage assessment.

Recent developments in the cryopreservation space has increased the trend in germplasm collections established through cryopreserved in vitro material. Cryopreservation of recalcitrant seeds through embryos and embryonic axes, is not uncommon. Tropical and sub-tropical plants are not acclimated to the cold season, therefore have no in-built natural resilience to the cold. Also, larger seeds from trees, such as avocado (Persea americana Mill.), mango (Mangifera indica) and durian (Durio zibethinus L.) are sensitive to desiccation, chilling and freezing stress, making them unsuitable for seed banking or cryopreservation. Alternatively, as seeds do not carry the same genetic make-up as the mother plant, especially in the context of woody rainforest species of which the cross-pollination is dominant; seed conservation does not serve the purpose of germplasm preservation. Other plant material and methods are needed for these plants to be successfully stored in liquid nitrogen (LN). One such method commonly used is shoot-tip cryopreservation which ensures the clonal fidelity of germplasm. There are many problems when using shoot tips of tropical recalcitrant-seeded species. These include: 1) the toxic effects of cryoprotective agents towards structural integrity; 2) optimum developmental stage for success and 3) oxidative stress associated with excision injury leading to necrosis triggering cell death and hindering regeneration for the shoot tips in culture. A pre-requisite for any cryopreservation system is the availability of an established tissue culture regeneration platform. This review will outline conservation strategies for avocado with special emphasis on attempts and improvements made in the cryopreservation space for storing this horticulturally important crop ‘avocado’ at ultra-low temperatures.

There is growing recognition in research and policy of a mental health crisis among Canada’s paramedics but despite this, epidemiological surveillance of the problem is in its infancy. Just weeks before the emergence of the COVID-19 pandemic, we surveyed paramedics from a single, large, urban paramedic service in Ontario, Canada to assess for symptom clusters consistent with Post-Traumatic Stress Disorder (PTSD), major depressive disorder, and generalized anxiety disorder and to identify potential risk factors for each. In total, we received 589 completed surveys (a 97% completion rate) and found that 11% screened positive for PTSD, 15% for depression, and 15% for anxiety, with 1 in 4 active-duty paramedics screening positive for any of the three as recently as February 2020. In adjusted analyses, the risk of a positive screen varied as a function of employment classification, gender, self-reported resilience, and previous experience as a member of the service’s peer support team. Our findings support the position that paramedics screen positive for mental disorders at high rates – a problem likely to have worsened since the onset of the COVID-19 pandemic. We echo the calls of researchers and policymakers for urgent action to support paramedic mental health in Canada.

Athletes are exposed to high-intensity loads to promote athletic performance, however without appropriate evaluation for its effects. This study investigates the effects of four types of exhaustion exercises on Heart Rate Variability (HRV) and Poincaré features as markers of central fatigue; Creatine Kinase (CK) and blood lactate concentrations ([LA-]b) as biomarkers of peripheral fatigue. To achieve this purpose, ten healthy volunteers were exposed to exhaustive exercise using isotonic-, isometric-, aerobic-, and anaerobic-fatigue protocols. HRV Poincaré features, standard deviation of instantaneous beat-to-beat R-R interval variability (SD1) and standard deviation of continuous long-term R-R interval variability (SD2) variables were collected. Central fatigue was tested through the sympathetic stress index (SS) and the sympathetic and parasympathetic index (SS/SD1). Blood samples were collected at the beginning and at the end of the exercises to determine CK and [LA-]b. The SD1 decreased in each exercise protocol, while the SS and SS/SD1 increased. [LA-]b and CK increased at the end of each protocol and correlated with SD1 and SS/SD1. HRV, CK, and [LA^-]_b are acute markers to detect, both central and peripheral fatigue; sensitive to the type, duration, and intensity of exercise, being HRV a novel noninvasive marker, simple and useful for sports coaches and athletes.

Primary importance is devoted to Fault Detection and Diagnosis (FDI) of electrical machine and drive systems in modern industrial automation. The widespread use of Machine Learning techniques has made it possible to replace traditional motor fault detection techniques with more efficient solutions that are capable of early fault recognition by using large amounts of sensory data. However, the detection of concurrent failures is still a challenge in the presence of disturbing noises or when the multiple faults cause overlapping features. The contribution of this work is to propose a novel methodology using multi-label classification method for simultaneously diagnosing multiple faults and evaluating the fault severity under noisy conditions. Performance of various multi-label classification models are compared. Current and vibration signals are acquired under normal and fault conditions. The applicability of the proposed method is experimentally validated under diverse fault conditions such as unbalance and misalignment.

Environmental darkness signal is transferred from the retina to the pineal gland triggering melatonin secretion. Melatonin influences the synthesis and release of the hypothalamic GnRH and the adenohypophyseal gonadotropin hormones and therefore, regulates testicular function in photoperiodic species. Besides the brain, direct actions of melatonin at the testicular level have also been described. Melatonin released from the pineal gland to the circulation is taken up by peripheral tissues including testes. Testicular synthesis of melatonin has also been reported. The two key somatic cell types in the testis, Leydig and Sertoli cells, express melatonergic receptors. Melatonin acts as a local modulator of the endocrine activity in Leydig cells. In Sertoli cells, melatonin influences the oxidation state and the energy metabolism, and consequently may regulate spermatogenesis. Melatonergic receptors were also described in testicular macrophages and mast cells of infertile patients. Whereas melatonin exerts anti-proliferative and anti-inflammatory effects on testicular macrophages, it provides protective effects against oxidative stress in testicular mast cells. These data pinpoints melatonin as a key player in the regulation of testicular physiology (i.e. steroidogenesis, spermatogenesis) mostly in seasonal breeders. More importantly, melatonin is also involved in the modulation of testicular inflammatory and oxidant/anti-oxidant states in patients with idiopathic infertility.

Mapping forest extent and forest cover classification are important for the assessment of forest resources in socio-economic as well as ecological terms. Novel developments in the availability of remotely sensed data, computational resources, and advances in areas of statistical learning have enabled fusion of multi-sensor data, often yielding superior classification results. Most former studies of nemoral forests fusing multi-sensor and multi-temporal data have been limited in spatial extent and typically to a simple classification of landscapes into major land cover classes. We hypothesize that multi-temporal, multi-censor data will have a specific strength in further classification of nemoral forest landscapes owing to the distinct seasonal patterns of the phenology of broadleaves. This study aimed to classify the Danish landscape into forest/non-forest and further into forest types (broadleaved/coniferous) and species groups, using a cloud-based approach based on multi-temporal Sentinel 1 and 2 data and machine learning (random forest) trained with National Forest Inventory (NFI) data. Mapping of non-forest and forest resulted in producer accuracies of 99% and 90 %, respectively. The mapping of forest types (broadleaf and conifer) within the forested area resulted in producer accuracies of 95% for conifer and 96% for broadleaf forest. Tree species groups were classified with producer accuracies ranging 34-74%. Species groups with coniferous species were the least confused whereas the broadleaf groups, especially Oak, had higher error rates. The results are applied in Danish National accounting of greenhouse gas emissions from forests, resource assessment and assessment of forest biodiversity potentials.

The increased availability of high resolution remote sensor data for precision agriculture 1 applications permits users to aquire deeper and more relevant knowledge about crops states that lead 2 inevitably to better decisions. The algorithm libraries being developed and evolved around these 3 applications rely on multi-spectral or hyper-spectral data acquired by using manned or unmanned 4 platforms. The current state of the art makes thorough use of vegetational indicies to guide the 5 operational management of agricultural land plots. One of the most challenging sub-problems is 6 to correctly identify and separate crop from soil. Thresholding techniques based on Normalized 7 Difference Vegetation Index (NDVI) or other such similar metrics have the advantage of being simple, 8 easy to read transformations of the data packed with useful information. Obvious difficulties arise 9 when crop/tree and soil have similar spectral responses as in case of grass filled areas in vineyards. 10 In this case grass and canopy are close in terms of NDVI values and thresholding techniques will 11 generally fail. Radiometric approaches could be integrated or replaced by a geometric approach that 12 is based on terrain data like Digital Surface Models (DSMs). These models are one of the ouputs 13 of orthorectification engines usually present in data acquired by using unmanned platforms. In 14 this paper we present two approaches based on DSM that are able to segment crop/tree from soil 15 while over gradient terrain. The DSM data are processed through a two dimensional data slicing or 16 reduction technique. Each slice is separately processed as a one dimensional time series to derive the 17 terrain and tree structures separately, here interpreted as object probability densities. In particular 18 the first approach is a Cartesian grid rasterization (CARSCAN) of the terrain and the second is its 19 immediate generalisation or radial grid rasterization of the DSM model (FANSCAN). The FANSCAN 20 recovers information from the original image at greater frequencies on the Fourier plane. These 21 approaches enable the identification of crop/tree from soil in case of slopes or hilly terrain without 22 any constraint on the displacement / direction of plant/tree row. The proposed algorithm uses pure 23 DSM information even if it is possible to fuse its output with other classifiers.

With the increasing demand for precise condition monitoring and diagnosis of gas-insulated switchgears (GIS), it has become a challenge to improve the detection sensitivity of partial discharge (PD) induced in the GIS spacer. This paper deals with the elimination of the capacitive component from the phase resolved partial discharge (PRPD) signal generated in GIS spacer based on the discrete wavelet transform. Three types of typical insulation defects were simulated using PD cells. The single PD pulses were detected and were further used to determine the optimal mother wavelet. As a result, the bior6.8 was selected to decompose the PD signal into 8 levels and the signal energy at each level was calculated. The decomposed components related with capacitive disturbance were discarded whereas those associated with PD were de-noised by a threshold and a thresholding function. Finally, the PRPD signals were reconstructed using the de-noised components.

Additive manufacturing has already been established as a highly versatile manufacturing technique with demonstrated potential to completely transform conventional manufacturing in the future. The objective of this paper is to review the latest progress and challenges associated with the fabrication of multi-material parts using additive manufacturing technologies. Various manufacturing processes and materials used to produce functional components were investigated and summarized. The latest applications of multi-material additive manufacturing (MMAM) in automotive, aerospace, biomedical and dentistry field were demonstrated. Investigation on the current challenges were also carried out to predict the future direction of MMAM processes. It is concluded that the further research and development needed in the design of multi-material interfaces, manufacturing processes and material compatibility of MMAM parts are necessary.

We describe a multi-resolution approach for audio classification and illustrate its application to the open data set for environmental sound classification. The proposed approach utilizes a multi-resolution based ensemble consisting of targeted feature extraction of approximation (coarse scale) and detail (fine scale) portions of the signal under the action of multiple transforms. This is paired with an automatic machine learning engine for algorithm and parameter selection and the LSTM algorithm, capable of mapping several sequences of features to a predicted class membership probability distribution. Initial results show an improvement in multi-class classification accuracy.

Multi-criteria decision analysis (MCDA), one of the prevalent branches of operations research, aims to design mathematical and computational tools for selecting the best alternative among several choices with respect to specific criteria. In the cloud, MCDA based online brokers uses customer specified criteria to rank different service providers. However, subjected to limited domain knowledge, the customer may exclude relevant or include irrelevant criterion, which could result in suboptimal ranking of service providers. To deal with such misspecification, this research proposes a model, which uses notion of factor analysis from the domain of unsupervised machine learning. The model is evaluated using two quality-of-service (QoS) based datasets. The first dataset i.e., feedback from customers, was compiled using leading review websites such as Cloud Hosting Reviews, Best Cloud Computing Providers, and Cloud Storage Reviews and Ratings. The second dataset i.e., feedback from servers, was generated from cloud brokerage architecture that was emulated using high performance computing (HPC) cluster at University of Luxembourg (HPC @ Uni.lu). The simulation runs in a stable cloud environment i.e. when uncertainty is low, shows that online broker (equipped with the proposed model) produces optimized ranking of service providers as compared to other brokers. This is due the fact that proposed model assigns priorities to criteria objectively (using machine learning) rather than using priorities based on subjective judgments of the customer. This research will benefit potential cloud customers that view insufficient domain knowledge as a limiting factor for acquisition of web services in the cloud.

Transposable elements (TEs) are highly abundant in plant genomes. Environmental stress is one of the critical stimuli that activate TEs. We analyzed a heat-activated retrotransposon named ONSEN in cruciferous vegetables. The multiple copies of ONSEN-like elements (OLEs) were found in all the cruciferous vegetables that were analyzed. The copy number of OLE was abundant in Brassica oleracea, which includes cabbage, cauliflower, broccoli, Brussels sprout, and kale. Phylogenic analysis demonstrated that some OLEs transposed after the allopolyploidization of parental Brassica species. Furthermore, we found that the increasing number of OLEs in B. oleracea appeared to be induced transpositional silencing by epigenetic regulation, including DNA methylation. The results of this study would be relevant to the understanding of evolutionary adaptations to thermal environmental stress in different species.

The purpose of the present study was to investigate the effects of psychological pressure on corticospinal excitability, the spinal reflex, lower limb muscular activity, and reaction times during a task involving dominant leg movements. Ten healthy participants performed a simple reaction time task by raising the heel of their dominant foot from a switch. After 20 practice trials, participants performed 20 non-pressure and 20 pressure trials in a counterbalanced order. Stress responses were successfully induced, as indexed by significant increases in state anxiety, mental effort, and heart rates under pressure. Significant increases in motor evoked potential (MEP) amplitude of the tibialis anterior muscle (TA) occurred under pressure. In terms of task-related EMG amplitude, the co-contraction rate between the soleus (SOL) and TA muscles significantly increased along with SOL and TA EMG amplitudes under pressure. Hoffmann reflexes for SOL and reaction times did not change under pressure. These results indicate that corticospinal excitability and leg muscle-related EMG activity increase homogeneously during lower limb movements that are performed under psychological pressure.

Multi-cameras system is widely applied in 3D computer vision especially when multiple cameras are distributed on both sides of the measured object. The calibration methods of multi-cameras system are critical to the accuracy of vision measurement and the key is to find an appropriate calibration target. In this paper, a high-precision camera calibration method for multi-cameras system based on transparent glass checkerboard and ray tracing is described, which is used to calibrate multiple cameras distributed on both sides of the glass checkerboard. Firstly, the intrinsic parameters of each camera is obtained by Zhang’s calibration method. Then, multiple cameras capture several images from the front and back of the glass checkerboard with different orientations, and all images contain distinct grid corners. As the cameras on one side are not affected by the refraction of glass checkerboard, extrinsic parameters can be directly calculated. However, the cameras on another side are influenced by the refraction of glass checkerboard, and the direct use of projection model will produce calibration error. A multi-cameras calibration method using refractive projection model and ray tracing is developed to eliminate this error. Furthermore, both synthetic and real data are employed to validate the proposed approach. The experimental results of refractive calibration show that the error of the 3D reconstruction is smaller than 0.2 mm, the relative errors of both rotation and translation are less than 0.014%, and the mean and standard deviation of reprojection error of 4-cameras system are 0.00007 and 0.4543 pixel. The proposed method is flexible, high accurate, and simple to carry out.

Irritable bowel syndrome (IBS) is one of the most common gastrointestinal diseases in humans. It is characterized by visceral pain and/or discomfort, hypersensitivity and abnormal motor responses along with change in gut habits. Although the etio-pathogenesis of IBS is only partially understood, a main role has been attributed to psychosocial stress of different origin. Animals models such as neonatal maternal separation, water avoidance stress and wrap restraint stress have been developed as psychosocial stressors in the attempt to reproduce the IBS symptomatology and identify the cellular mechanisms responsible for the disease. The study of these models has led to the production of drugs potentially useful for IBS treatment. This review intends to give an overview on the results obtained with the animal models; to emphasize the role of the enteric nervous system in IBS appearance and evolution and as a possible target of drug therapies.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has resulted in the current COVID-19 pandemic. Worldwide this disease has infected around 1.5 million individuals with a mortality rate ranging from 5 to 10%. It has also imposed extreme challenges on global health, economy, and social behavior. Due to the unavailability of therapeutics, several efforts are going on in the drug discovery to control the SARS-CoV-2 viral infection. The main protease (M^Pro) plays a critical role in viral replication and maturation, thus can serve as the primary drug target. To understand the structural evolution of M^Pro, we have performed phylogenetic and SSN analysis, that depicted divergence of Coronaviridae M^Pro in five clusters specific to viral hosts. This clustering was also corroborated with the comparison of M^Pro structures. Furthermore, it has been observed that backbone and binding site conformations are conserved despite variation in some of the residues. This conservation can be exploited to repurpose available viral protease inhibitors against SARS-CoV-2 M^Pro. In agreement with this, we performed screening of the custom-made library of ~7100 molecules including active ingredients present in the Ayurvedic anti-tussive medicines, anti-viral phytochemicals and synthetic anti-virals against SARS-CoV-2 M^Pro as the primary target. We identified several natural molecules that strongly binds to SARS-CoV-2 M^Pro among which top seven molecules are d-Viniferin, Myricitrin, Taiwanhomoflavone A, Lactucopicrin 15-oxalate, Nympholide A, Biorobin and Phyllaemblicin B. Most of the predicted lead molecules are from Vitis vinifera, also reported for anti-tussive and/or antiviral activities. These molecules also showed strong binding with other main targets RdRp and hACE-2. We anticipate that our approach for identification of multi-target-directed ligand will provide new avenues for drug discovery against SARS-CoV-2 infection.

The increasing complexity of the design and operation evaluation process of multi-energy grids (MEGs) requires tools for the coupled simulation of power, gas and district heating grids. Most tools analyzed in this paper either do not allow coupling of infrastructures, simplify the grid model or are not publicly available. We introduce the open source piping grid simulation tool pandapipes that – in interaction with pandapower - fulfills three crucial criteria: clear data structure, adaptable MEG model setup and performance. In an introduction to pandapipes we illustrate how it fulfills these criteria through its internal structure and demonstrate how it performs in comparison to STANET®. Then we show two case studies that have been performed with pandapipes already. The first case study demonstrates a peak shaving strategy as interaction of a local electricity and district heating grid in a small settlement. The second case study analyzes the potential of a power-to-gas device to serve as flexibility in a power grid under consideration of gas grid constraints. They both show the importance of a clear database, a simple simulation setup and good performance to set up different large and complex studies on grid infrastructure design and operation.

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.

Aquaporin-11 (AQP11) is an intracellular water channel expressed at the endoplasmic reticulum (ER) of the kidney proximal tubule. Its gene disruption in mice leads to intracellular vacuole formation at one week old and the subsequent development of polycystic kidneys at three week old. As the damaged proximal tubular cells with intracellular vacuoles later form cysts, autophagy may play a role in their survival. We examined the autophagy activity before and after the development of cysts in AQP11(-/-) kidneys. We first observed an enhanced expression of LC3 gene (Map1lc3b) as well as other autophagy-related genes in AQP11(-/-) mice by quantitative PCR analysis. We then examined the formation of autophagosomes visualized by a green fluorescent fusion protein, GFP–LC3 in its transgenic mice. The expression of GFP-LC3 puncta was increased in the proximal tubule of AQP11(-/-) mice before the cyst formation. Interestingly, they were also observed in the cyst-lining epithelial cell. Further PCR analyses revealed the enhanced expression of apoptosis- and ER stress-related caspase genes before and after the cyst formation suggesting that ER stress may have enhanced autophagy. We conclude that autophagy will play an important role in the development and the survival of the kidney cysts in AQP11(-/-) mice.

The study aimed to investigate the effects of colonization with two arbuscular mycorrhizal (AM) fungi, Funneliformis mosseae , Diversispora versiformis , alone and in combination on the growth and nutrient acquisition of NaCl-stressed Chrysanthemum morifolium (Hangbaiju) plants in the greenhouse experiment. Mycorrhizal and non-mycorrhizal Hangbaiju plants were grown under different salinity levels imposed by 0, 50 and 200 mM NaCl for five months, following 6 weeks of non-saline pre-treatment. The results showed that root length, shoot and root dry weight, total dry weight, shoot and root N concentration were higher in mycorrhizal than in non-mycorrhizal plants under moderate saline conditions especially with D. versiformis colonization. As salinity increased, the mycorrhizal colonization, the mycorrhizal dependence (MD) decreased. Enhancement of tissue N acquisition is probably the main mechanism underlying salt tolerance in AM plants. It is suggested that the symbiotic associations between D. versiformis fungus and C. morifolium plants may be taken as a biotechnological practice in culture.

Abiotic stresses, including drought, salinity, cold, heat, and heavy metals, extensively reduce global agricultural production. Approaches such as conventional breeding and transgenic breeding have been widely used to cope with these environmental stresses. The clustered regularly interspaced short palindromic repeat- Cas (CRISPR/Cas) based gene-editing tool has revolutionized due to its simplicity, accessibility, adaptability, flexibility, and wide applicability. This system has a great potential to build up crop varieties with enhanced tolerance against abiotic stresses. In this review, we summarize the most recent findings on understanding the mechanism of abiotic stress response in plants and the application of CRISPR/Cas mediated gene-editing system towards enhanced tolerance to drought, salinity, cold, heat, and heavy metals stresses. Furthermore, in this review, we highlighted the recent advancements in prime editing and base editing tools for crop improvement.

This paper deals with a generic methodology to evaluate the magnetic parameters of contactless power transfer systems. Neumann's integral has been used to create a matrix method that can model the magnetics of single coils (circle, square, rectangle). The principle of superposition has been utilised to extend the theory to multi-coil geometries such as double circular, double rectangle and double rectangle quadrature assuming linearity of magnetics. Numerical and experimental validation has been performed to validate the analytical models developed. A rigorous application of the analysis has been carried out to study misalignment and hence the efficacy of various geometries to misalignment tolerance. Comparison of single-coil and multi-coil shapes considering coupling variation with misalignment, power transferred and maximum efficiency is carried out.

The creation of hydrophobic, antifreeze and self-cleaning coatings is currently being pursued by many industrial sectors. The potential applications include the production of liquid and gas separators and filters, new materials, optical and microelectronic devices, and textiles and clothing. These coatings will also have wide application in the construction and automobile industries, shipping, and energy and agricultural sectors. The article proposes a simple approach to the creation of superhydrophobic and antifreeze coatings, by applying powder from multi-walled carbon nanotubes (MW-CNTs) to the sample surface. This method enables combination of the necessary factors: low surface energy, micro–nano-roughness and hierarchical multi-scale. The authors investigated the dependence of the wetting angle of such a surface on the time, type and degree of functionalization. The electrophysical properties of modified MW-CNTs were studied over wide frequency and temperature ranges. This method of obtaining hydrophobic coatings differs from currently available methods in that it is simpler to prepare, is of lower cost and has less environmental impact. The proposed approach can be used to create superhydrophobic coatings that have the additional function of removing static charge and therefore reducing surface heating, and which can be used in the field of energetics for protection against the freezing of wind turbine blades and aircraft surfaces.

This study revisits the Reynolds-averaged Navier--Stokes equations (RANS) and finds that the existing literature is erroneous regarding the primary unknowns and the number of independent unknowns in the RANS. The literature claims that the Reynolds stress tensor has six independent unknowns, but in fact the six unknowns can be reduced to three that are functions of the three velocity fluctuation components, because the Reynolds stress tensor is simply an integration of a second-order dyadic tensor of flow velocity fluctuations rather than a general symmetric tensor. This difficult situation is resolved by returning to the time of Reynolds in 1895 and revisiting Reynolds' averaging formulation of turbulence. The study of turbulence modeling could focus on the velocity fluctuations instead of on the Reynolds stress. An advantage of modeling the velocity fluctuations is, from both physical and experimental perspectives, that the velocity fluctuation components are observable whereas the Reynolds stress tensor is not.

The feasible, reliable and selective multi-template molecularly imprinted polymers (MT-MIPs) based on SBA-15 (SBA-15@MT-MIPs) for the selective separation and determination of the trace level of ginsenoside Rb₁ (Rb₁), ginsenoside Rg₁ (Rg₁) and notoginsenoside R₁ (R₁) (Panax notoginseng saponins, PNS) from biological samples were developed. The polymers were constructed by SBA-15 as support, Rb₁, Rg₁, R₁ as multi-template, acrylamide (AM) as functional monomer and ethylene glycol dimethacrylate (EGDMA) as cross-linker. The new synthetic SBA-15@MT-MIPs were satisfactorily applied to solid-phase extraction (SPE) coupled with high performance liquid chromatography (HPLC) for the separation and determination of trace PNS in plasma samples. Under the optimized conditions, the limits of detection (LODs) and quantitation (LOQs) of the proposed method for Rb₁, Rg₁ and R₁ were in the range of 0.63-0.75 ng mL^-1 and 2.1-2.5 ng mL^-1, respectively. The recoveries of R₁, Rb₁ and Rg₁ were obtained between 93.4% and 104.3% with relative standard deviations (RSDs) in the range of 3.3-4.2%. All results show that the obtained SBA-15@MT-MIPs could be a promising prospect for the practical application in the selective separation and enrichment of trace PNS in the biological samples.

There is robust evidence that major depression (MDD) is accompanied by a low-grade activation of the immune-inflammatory response system, which is involved in the pathophysiology of this disorder. It is also becoming apparent that glia cells are in reciprocal communication with neurons and orchestrate various neuromodulatory, homeostatic, metabolic, and immune mechanisms and have a crucial role in neuroinflammatory mechanisms in MDD. Those cells mediate the central nervous system (CNS) response to systemic inflammation and psychological stress, but at the same time, they may be an origin of the inflammatory response in the CNS. The sources of activation of the inflammatory response in MDD are immense, however, in recent years, it is becoming increasingly evident that the gastrointestinal tract with gut-associated lymphoid tissue (GALT) and increased intestinal permeability to bacterial LPS and food-derived antigens contribute to activation of low-grade inflammatory response with subsequent psychiatric manifestations. Furthermore, an excessive permeability to gut-derived antigenic material may lead to subsequent autoimmunities which are also known to be comorbid with MDD. In this chapter, we discuss fascinating interactions between the gastrointestinal tract, increased intestinal permeability, intestinal microbiota, and glia-neuron crosstalk, and their roles in the pathogenesis of the inflammatory hypothesis of MDD. To emphasize those crucial intercommunications for the brain functions, we propose the term of microbiota-gut-immune-glia (MGIG) axis.

When the antioxidants in our immune system cannot neutralize or convert Reactive oxygen species into safe molecules at the rate at which it is produced then this imbalance is termed as “oxidative stress”. It is related with a wide array of diseases that includes cancer, diabetes, cardiovascular diseases, hypertension etc. These ROS species however are utmost essential for the proper functioning of human body which are produced as a consequence of partial oxidation of cellular metabolism performing essential functions such as protein phosphorylation, activation of several transcriptional factors, apoptosis, immunity, and differentiation. The sources by which these are produced can be broadly classified are intrinsic and extrinsic sources. There are variety of natural antioxidant enzymes of human body that combat against this oxidative stress. The extrinsic sources of ROS include the use of natural plants, extracted flavonoids and vitamins. In this review we will briefly explain how the sources of ROS, its essential function in human body, its elevation and associated damage to organs and effect on various diseases, and a hope of finding a way of how this oxidative stress can be exploited for therapeutic potential.

This review presents a comprehensive and systematic study of the field of bacterial plant biostimulants and considers the fundamental and innovative principles underlying this technology. Plant biostimulants are an important tool for modern agriculture as part of an integrated crop management (ICM) system; helping make agriculture more sustainable and resilient. Plant biostimulants contain substance(s) and/or microorganisms whose function when applied to plants or the rhizosphere, is to stimulate natural processes to enhance plant nutrient uptake, nutrient use efficiency, tolerance to abiotic stress, biocontrol, and crop quality. The use of plant biostimulants has gained substantial and significant heed worldwide as an environment-friendly alternative for sustainable agricultural production. Presently, there is an increasing curiosity of industry and researchers in microbial biostimulants especially, bacterial plant biostimulants (BPBs) to improve crop growth and productivity. The BPBs that are based on PGPR (plant growth-promoting rhizobacteria) play plausible roles to promote/stimulate the crop plant growth through several mechanisms that include, i) nutrient acquisition by nitrogen (N₂) fixation and solubilization of insoluble minerals (P, K, Zn), organic acids and siderophores, ii) antimicrobial metabolites and various lytic enzymes, iii) action of growth regulators and stress-responsive/induced phytohormones, iv) ameliorating abiotic stress like drought, high soil salinity, extreme temperatures, oxidative stress, and heavy metals by using different modes of action, and v) plant defense induction modes. Presenting here is a brief review emphasizing the applicability of BPBs as an innovative exertion to fulfill the current food crisis.

Abstract: Comparing outcrop data to laboratory results is important to verify and validate experiments of analogue and reservoir materials especially regarding conditions for deformation experiments. This is important better understand highly complex carbonate reservoir strata and their response to changes in subsurface conditions, reducing subsurface uncertainty. This study develops methods to allow for a more straightforward comparison of outcrop data (m-scale) with experimentally created fracture arrays developed in cylindrical samples (cm-scale). The main objective is to assess usefulness of experimentally-produced fracture networks as analogues for subsurface structures, typically at the meter and above scale by developing new techniques to use the lab deformation. It analyses key characteristics of laboratory-induced fracture networks by adapting scanline methods to use with x-ray tomography (XRT) images to allow for comparison with outcrop and field data. To test and verify these new methods two low permeability carbonate samples were used for deformation testing and analysis. Applying the different scanline methods we show that they can be used to analyse lab induced fractures (mm to cm-scale) identified in XRT images for comparison with outcrop data (m-scale). In addition, these methods also allow for quantification of fracture network attributes e.g. fracture spacing, fracture apertures, orientation. This new data bridges the gap between micro-scanlines using thin sections and outcrop scanlines.

Metabolic disorders have become among the most serious threats to human health, leading to severe chronic diseases such as obesity, type 2 diabetes, non-alcoholic fatty liver disease, as well as cardiovascular diseases. Interestingly, despite the fact that each of these maladies has different physiological and clinical symptoms, they appear to share certain pathological traits such as intracellular stress and inflammation induced by metabolic derangements stemmed from over nutrition frequently aggravated by modern sedentary life style. These modern ways of living inundate cells and organs with saturating levels of sugar and fat, leading to glycotoxicity and lipotoxicity that induce intracellular stress signaling ranging from oxidative to ER stress response to cope with the metabolic insults [1]. In this review, we discuss the roles played by cellular stress and its responses in shaping metabolic disorders. We have summarized here current mechanistic insights explaining the pathogenesis of these disorders. These are followed by a discussion of the latest therapies targeting the stress response pathways.

Recent analyses of cosmic microwave background surveys have revealed hints that there may be a non-trivial running of the running of the spectral index. If future experiments were to confirm these hints, it would prove a powerful discriminator of inflationary models, ruling out simple single field models. We discuss how isocurvature perturbations in multi-field models can be invoked to generate large runnings in a non-standard hierarchy, and find that a minimal model capable of practically realising this would be a two-field model with a non-canonical kinetic structure. We also consider alternative scenarios such as variable speed of light models and canonical quantum gravity effects and their implications for runnings of the spectral index.

In the current study, the failure behavior of retrofitted steel structures was studied experimentally and theoretically with steel/CFRP double strap joints (DSJs) under quasi-static tensile loading. A series of DSJs with different bonding lengths are also considered and examined to experimentally assess the effective bond length. To predict the failure load values of the tested specimens, a new stress-based criterion, namely the point stress (PS) criterion is proposed. Although some theoretical predictive modelling for the strength between steel/CFRP joints under various loading conditions has been presented, in this work by using the new proposed approach, one can calculate rapidly and conveniently the failure loads of the steel/CFRP specimens. Furthermore, to assess the validity of the new proposed criterion, further experimental data on steel/CFRP DSJs available in the open literature are predicted using the PS criterion. Finally, it was found that a good agreement exists between the experimental results and the theoretical predictions based on the PS criterion.

Work context is essential to understand in relation to handle the stress at work that ultimately creates a feeling of satisfaction or dissatisfaction among health professionals. The current study was conducted to investigate the relationship of work context and work stress among sonographers (n=153) in Riyadh, Saudi Arabia. Additionally, the study provided a gender-based comparison of both variables among sonographers. Work context was measured by administering subscale of work context derived from Work Design Questionnaire. Whereas, work stress was measured by Job Stress Scale. In addition, relationship of lifestyle was explored with work context and work stress. Data was collected through survey research forms. Results revealed the significant relationship of work context and work stress (r=.251, p=.002). Among lifestyle variables, perceived good health (r= .214, p=.008) and sleep (r=.242. p=.003) were found positively related with satisfaction toward work. Whereas, the strong positive correlation was found between work context and frequency of physical activity (r=.255, p=.005). No significant difference was found among male and female sonographers. The findings of this study contributed to evaluating the working condition of sonographers in relation to work stress. Effective strategies for better working settings as well as strategies for achieving satisfaction in work will be discussed to enhance the performance of sonographers.

In the process of sustainable development in the future, human society faces problems such as severe population load, economic transition, and lack of educational measures. One of the root causes of these problems is the shortage of innovative talents. Therefore, how to cultivate learners with multi-disciplinary integration and innovation ability is the key point that should be paid attention to in promoting the concept of quality education and coping with the future sustainable development process. This paper uses questionnaire survey method and literature analysis method to analyze the development of many educational institutions with STEAM concept as the core in China since 2017. It is found that the existing STEAM educational institutions generally have the following problems: the lack of team composition、difficulty in independent research and development、single course content and insufficient validation of course effectiveness. In order to more effectively promote the sustainable development of China's future course, STEAM education institutions should focus on strengthening the following development strategy: gradient team building, continuous independent research and development, cutting-edge projects curriculum transformation mechanism and multi-angle course effectiveness verification.

In recent years, land supply in Hong Kong has fallen sharply and fails to keep pace with the growth of population and number of households. Land shortage becomes urgent and dire. With the inadequate provision of residential land, housing supply is also adversely affected.Insufficient housing supply leads to surging property and rental price in the private market. According to the Rating and Valuation Department (RVD), the overall private domestic price index peaked in June 2017 at 336.1. Keen housing demand is also observed in the private rental market. RVD statistics showed that the domestic rental index also reached the peak at 183.6 in June 2017 and the vacancy rate of about 3.8% as at the end-2016, which is much lower than the average vacancy rate of 5% from 1996 to 2015 (Development Bureau, 2017).In addition, there is soaring housing demand in public housing. As at the end-December 2021, the average waiting time for general applicants was 5.7 years, which is nearly double of the Housing Authority’s target for providing the first flat offer to general applicants at around three years on average (Housing Authority, 2021). Identifying and securing sufficient land to meet both current and anticipated pressing housing demand becomes a key challenge of the government. In the light of this, the government has established a dedicated task force (Task Force on Land Supply) in September 2017 and appointed 30 professionals from different disciplines, such as planning, engineering, academia and think tank, to take a Marco-review on the land supply sources, look for feasible options as well as consider the pros and cons of various options. 18 land supply options were worked out for the public to make choices in the public engagement exercise. Among the 18 choices, the development area on the Periphery of Country Parks was regarded as one of the land supplies sources. This option does not only include the Hong Kong Housing Society’s studies on developing Two Pilot Areas on the Periphery of Tai Lam and Man On Shan Country Parks, but also include developing more areas on the periphery of Country Parks. The proposed option received overwhelming attention from the public and aroused debates in various perspectives. Its ecological value, recreational value, financial viability and even legitimacy were discussed. However, spatial analysis on the suitability of having residential development in Country Parks has not been conducted. Therefore, in this study, multi criteria GIS analysis is conducted to evaluate the geographic suitability of Hong Kong Country Parks for residential purpose with the consideration of various criteria.

Satellite scene classification is challenging because of the high variability inherent in satellite data. Although rapid progress in remote sensing techniques has been witnessed in recent years, the resolution of the available satellite images remains limited compared with the general images acquired using a common camera. On the other hand, a satellite image usually has a greater number of spectral bands than a general image, thereby permitting the multi-spectral analysis of different land materials and promoting low-resolution satellite scene recognition. This study advocates multi-spectral analysis and explores the middle-level statistics of spectral information for satellite scene representation instead of using spatial analysis. This approach is widely utilized in general image and natural scene classification and achieved promising recognition performance for different applications. The proposed multi-spectral analysis firstly learns the multi-spectral prototypes (codebook) for representing any pixel-wise spectral data, and then based on the learned codebook, a sparse coded spectral vector can be obtained with machine learning techniques. Furthermore, in order to combine the set of coded spectral vectors in a satellite scene image, we propose a hybrid aggregation (pooling) approach, instead of conventional averaging and max pooling, which includes the benefits of the two existing methods but avoids extremely noisy coded values. Experiments on three satellite datasets validated that the performance of our proposed approach is much more accurate than even the deep learning framework for spatial analysis.

Stess in laser cladding coating is an important factor affecting the safe operation of remanufacturing components. Ultrasonic testing has become a hot direction in nondestructive evaluation of stress, because it has the advantages of safety, non-destructive and on-line detection. This paper provides a review of ultrasonic testing for stress in remanufacturing laser cladding coating. It summarizes the recent research outcomes on ultrasonic testing for stress, analyzes mechanism of ultrasonic testing for stress. Remanufacturing laser cladding coating shows typical anisotropic behaviors, the ultrasonic testing signal in laser cladding coating is influenced by many complex factors, such as microstructure, defect, temperature and surface roughness, etc. At present, ultrasonic testing for stress in laser cladding coating can only be done roughly. The paper discusses active mechanism of micro / macro factors to the reliability of stress measurement and the impact of stress measurement to the quality and safety of remanufacturing components. Base on the discussion, the paper proposes strategies for acquisition of nondestructive, rapid and accurate measurement of stress in remanufacturing laser cladding coating.

Nitrogen use efficiency (NUE) in maize (Zea mays L.) is an important trait to maximize yield with minimal input of nitrogen (N) fertilizer. Expired Plant Variety Protection (ex-PVP) Act-certified germplasm may be an important genetic resource for public breeding sectors. The objectives of this research were to evaluate the genetic variation of N-use traits and to characterize maize ex-PVP inbreds adapted to the U.S. Corn Belt for NUE performance. Eighty-nine ex-PVP inbreds [36 stiff stalk synthetic (SSS), and 53 non-stiff stalk synthetic (NSSS)] were genotyped using 26,769 single-nucleotide polymorphisms, then 263 single-cross maize hybrids derived from these inbreds were grown in eight environments from 2011 to 2015 at two N fertilizer rates (0 and 252 kg N ha⁻¹) and three replications. Genetic utilization and the yield response to N fertilizer were stable across environments and were highly correlated with yield under low and high N conditions, respectively. Cluster analysis identified inbreds with desirable NUE performance. However, only one inbred (PHK56) was ranked in the top 10% for yield under both N-stress and high N conditions. Broad-sense heritability across 12 different N-use traits ranged from 0.11 to 0.77, but was not associated with breeding value accuracy. Nitrogen-stress tolerance was negatively correlated with the yield increase from N fertilizer.

The breeding of stress-tolerant cultivated plants that would allow for a reduction in harvest losses and undesirable decrease in quality attributes requires a new quality of knowledge on molecular markers associated with relevant agronomic traits, on quantitative metabolic responses of plants on stress challenges, and on the mechanisms controlling the biosynthesis of these molecules. By combining metabolomics with genomics, transcriptomics and proteomics datasets a more comprehensive knowledge of the composition of crop plants used for food or animal feed is possible. In order to optimize crop trait developments, to enhance crop yields and quality, as well as to guarantee nutritional and health factors, that provides the possibility to create functional food or feedstuffs, the knowledge about the plants’ metabolome is crucial. Next to classical metabolomics studies, this review focusses on several metabolomics based working techniques, such as sensomics, lipidomics, hormonomics and phytometabolomics, which were used to characterize metabolome alterations during abiotic and biotic stress, to find resistant food crops with a preferred quality or at least to produce functional food crops are highlighted.

Intelligent systems are driven by the latest technological advances in so different areas as sensing, embedded systems, wireless communications or context recognition. This paper focuses on some of those areas. Concretely, the paper deals with wireless communications issues on embedded systems. More precisely, the paper combines the multi-hop networking with Bluetooth technology and a quality of service (QoS) metric, the latency. Bluetooth is a radio license free worldwide communication standard that makes low power multi-hop wireless networking available. It establishes piconets (point-to-point and point-to-multipoint links) and scatternets (multi-hop networks). As a result, many Bluetooth nodes can be interconnected to set up ambient intelligent networks. Then, this paper presents the results of the investigation on multi-hop latency with park and sniff Bluetooth low power modes conducted over the hardware test bench previously implemented. In addition, the empirical models to estimate the latency of multi-hop communications over Bluetooth Asynchronous Connectionless Links (ACL) in park and sniff mode are given. The designers of devices and networks for intelligent systems will benefit from the estimation of the latency in Bluetooth multi-hop communications that the models provide.

We present a first formal analysis of specific and complete local integration. Complete local integration was previously proposed as a criterion for detecting entities or wholes in distributed dynamical systems. Such entities in turn were conceived to form the basis of a theory of emergence of agents within dynamical systems. Here, we give a more thorough account of the underlying formal measures. The main contribution is the disintegration theorem which reveals a special role of completely locally integrated patterns (what we call ι-entities) within the trajectories they occur in. Apart from proving this theorem we introduce the disintegration hierarchy and its refinement-free version as a way to structure the patterns in a trajectory. Furthermore we construct the least upper bound and provide a candidate for the greatest lower bound of specific local integration. Finally, we calculate the i-entities in small example systems as a first sanity check and find that ι-entities largely fulfil simple expectations.

The introduction of the Internet of Things (IoT), i.e. the interconnection of embedded devices over the Internet, has changed the world we live in from the way we measure, make calls, print information and even the way we get energy in our offices or homes. The convenience of IoT products, like CCTV cameras, IP phones, and oscilloscopes, is overwhelming for end-users. In parallel, however, security issues have emerged and it is essential for infrastructure providers to assess the associated security risks. In this paper, we propose a novel method to detect IoT devices and identify the manufacturer, device model, and the firmware version currently running on the device using the page source from the web user interface. We performed automatic scans of the large-scale network at the European Organization for Nuclear Research (CERN) to evaluate our approach. Our tools identified 233 IoT devices that fell into eleven distinct device categories and included 49 device models manufactured by 26 vendors from across the world.

Unmanned aerial vehicles (UAV) provide an unprecedented capacity to monitor the development and dynamics of tree growth and structure through time. It is generally thought that the pruning of tree crops encourages new growth, has a positive effect on fruiting, makes fruit-picking easier, and may increase yield, as it increases light interception and tree crown surface area. To establish the response of pruning in an orchard of lychee trees, an assessment of changes in tree structure, i.e. tree crown perimeter, width, height, area and Plant Projective Cover (PPC), was undertaken using multi-spectral UAV imagery collected before and after a pruning event. While tree crown perimeter, width and area could be derived directly from the delineated tree crowns, height was estimated from a produced canopy height model and PPC was most accurately predicted based on the NIR band. Pre- and post-pruning results showed significant differences in all measured tree structural parameters, including an average decrease in tree crown perimeter of 1.94 m, tree crown width of 0.57 m, tree crown height of 0.62 m, tree crown area of 3.5 m², and PPC of 14.8%. In order to provide guidance on data collection protocols for orchard management, the impact of flying height variations was also examined, offering some insight into the influence of scale and the scalability of this UAV based approach for larger orchards. The different flying heights (i.e. 30, 50 and 70 m) produced similar measurements of tree crown width and PPC, while tree crown perimeter, area and height measurements decreased with increasing flying height. Overall, these results illustrate that routine collection of multi-spectral UAV imagery can provide a means of assessing pruning effects on changes in tree structure in commercial orchards, and highlight the importance of collecting imagery with consistent flight configurations, as varying flying heights may cause changes to tree structural measurements.

Background: The primary objective worldwide during the COVID-19 pandemic has been controlling disease transmission. However, lockdown measures used to mitigate transmission have affected human behavior and altered lifestyles, with a likely impact on chronic non-communicable diseases. More than a year into the pandemic, substantial peer-reviewed literature has emerged on altered lifestyles following the varying lockdown measures imposed globally to control the virus spread. Objective: To explore the impact of lockdown measures on the six lifestyle factors, namely diet, physical activity, sleep, stress, social connectedness, and the use of tobacco, alcohol, or other harmful substances.Methods: We comprehensively searched PubMed and the World Health Organization’s global literature database on COVID-19 and retrieved 649 relevant articles for the narrative review. A critical interpretative synthesis of the articles was performed.Results: Most of the articles included in the review identified the negative effect of lockdown measures on each of the lifestyle factors in many parts of the world. Interestingly, encouraging lifestyle trends were also highlighted in a few articles. Such trends can positively influence the outcome of lifestyle-related chronic diseases, such as obesity and diabetes.Conclusions: The COVID-19 pandemic provides an opportunity to better understand the negative impact of strict lockdown measures on lifestyles. At the same time, it helps us identify and initiate positive behavioral changes, which, if consolidated, could improve chronic disease outcomes. It is up to governments, communities, and healthcare/academic entities to derive benefit from lessons learned from the pandemic, with the ultimate objective of better educating and promoting healthy lifestyles among communities.

The difficult current environmental situation, caused by construction industry residues containing ceramic materials could be improved by using these materials as recycled aggregates in mortars, with their processing causing a reduction in their use in landfill, contributing to recycling and also minimizing the consumption of virgin materials. Although some research is currently being carried out into recycled mortars, little is known about their stress-strain (σ-ε); therefore this work will provide the experimental results obtained from recycled mortars with recycled ceramic aggregates (with contents of 0, 10, 20, 30, 50 and 100%), such as: the density, the compression strength, as well as the σ-ε curves representative of their behavior. The values obtained from the analysis process of the results are those of: σ (elastic ranges and failure maximum), ε (elastic ranges and failure maximum), and Resilience and Toughness; in order to finally obtain, through numerical analysis, the equations to predict their behavior (related to their recycled content). At the end of the investigation it is established that mortars with recycled ceramic aggregate contents of up to 20% could be assimilated just like mortars with the usual aggregates, and the prediction equations produced could be used in cases of similar applications.

A metastable β-Ti alloy, Ti–10V–3Fe–3Al (wt.%), was subjected to thermos-mechanical processing including the compression test at 725°C, which is below the β transus temperature (780°C), and at strain rate of 10-3s-1. The presence of phases was determined using transmission electron microscopy and X-ray diffraction. Although the dynamic recovery took place together with slip, both deformation-induced α˝ martensite and ω were detected as other operating mechanisms for the first time in metastable-β Ti alloys deformed in α+β region. The volume fraction of stress-induced α˝ was higher than that of the same alloy deformed at room temperature due to higher strain applied. Stress-induced twinning was not operational, which could be related to the priority of slip mechanism at high temperature resulted from thermally-assisted nucleation and lateral migration of kink-pairs.

Since crystals are made of periodic structures in space, predicting their three period vectors starting from any values based on the inside interactions is a basic theoretical physics problem. For the general situation where crystals are under constant external stress, we derived dynamical equations of the period vectors in the framework of Newtonian dynamics, for pair potentials recently (doi:/10.1139/cjp-2014-0518). The derived dynamical equations show that the period vectors are driven by the imbalance between the internal and external stresses. This presents a physical process where when the external stress changes, the crystal structure changes accordingly, since the original internal stress can not balance the external stress. The internal stress has both a full kinetic energy term and a full interaction term. It is extended to many-body interactions in this paper. As a result, all conclusions in the pair-potential case also apply for many-body potentials.

Developing countries like Pakistan is among those where lack of adoption to science and technology advancement is a major constraint for Satellite Remote Sensing use in crops and land use land cover digital information generation. Exponential rise in country population, increased food demand, limiting natural resources coupled with migration of rural community to urban areas had further led to skewed official statistics. This study is an attempt to demonstrate the possible use of freely available satellite data like Landsat8 under complex cropping system of Okara district of Punjab, Pakistan. An Integrated approach has been developed for the satellite data based crops and land use/cover spatial area estimation. The resultant quality was found above 96% with Kappa statistics of 0.95. Land utilization statistics provided detail information about cropping patterns as well as land use land cover status. Rice was recorded as most dominating crop in term of cultivation area of around 0.165 million ha followed by autumn maize 0.074 million ha, Fallow crop fields 0.067 million ha and Sorghum 0.047 million ha. Other minor crops observed were potato, fodder and cotton being cultivated on less than 0.010 million ha. Population settlements were observed over an area of around 0.081 million ha of land.

Sustainable agricultural production is endangered by several ecological factors such as drought, extreme temperatures, excessive salts, parasitic ailments, and insect pest infestation. These challenging environmental factors may have adverse effects on future agriculture production in many countries. In modern agriculture, conventional crop breeding techniques alone are inadequate for achieving the increasing population’s food demand on a sustainable basis. The advancement of molecular genetics and related technologies are promising tools for the selection of new crop species. Gene pyramiding through marker assisted selection (MAS) and other techniques have accelerated the development of durable resistant/tolerant lines with high accuracy in the shortest possible period of time for agricultural sustainability. Gene stacking has not been fully utilized for biotic stress resistance development and quality improvement in most of the major cultivated crops. This review emphasizes on gene pyramiding techniques that are being successfully deployed in modern agriculture for improving crop tolerance to abiotic and biotic stresses for sustainable crop improvement.

Due to the complexity of Alzheimer's disease, multiple cellular types need to be targeted simultaneously in order for a given therapy to demonstrate any major effectiveness. Ultrasound-sensitive coated microbubbles (in a targeted lipid nanoemulsion) are available. Versatile small molecule drug(s) targeting multiple pathways of Alzheimer's disease pathogenesis are known. By incorporating such drug(s) into the targeted LCM/ND lipid nanoemulsion type, one obtains a multitasking combination therapeutic for translational medicine. This multitasking therapeutic targets cell-surface scavenger receptors (mainly SR-BI), making possible for various Alzheimer's-related cell types to be simultaneously searched out for localized drug treatment in vivo. Besides targeting cell-surface SR-BI, the proposed LCM/ND-nanoemulsion combination therapeutic(s) include a characteristic lipid-coated microbubble [LCM] subpopulation (i.e., a stable LCM suspension); such film-stabilized microbubbles are well known to substantially reduce the acoustic power levels needed for accomplishing temporary noninvasive (transcranial) ultrasound treatment, or sonoporation, if additionally desired for the Alzheimer's patient.

As professionals, social workers have a special position in relation to considering the needs of children with cancer and their families. Hence, it is important to recognize the experiences and challenges of social workers to improve care of their clients. This study was a qualitative content analysis that aimed to determine a comprehensive understanding of 19 pediatric oncology social workers’ experiences in Iran. Data were collected using semi structured interviews and field observations, analyzed through face content analysis. Concepts extracted from social workers’ experiences consisted of the nature of oncology work, lack of professional competence, low organizational support and professional inferiority that were related to main concept of "exhausting and stressful service". The results indicated that social workers' involvement in stressful and emotionally demanding situations and professional and organizational challenges caused personal exhaustion. In addition to explaining the social workers’ experiences and related factors, the results emphasize the importance of taking care of service providers to prevent them becoming stressed and exhausted. It is also important to protect patients from the consequences of stressed and exhausted care providers so further research is recommended to develop specific intervention.

Apart from their established role in embryonic development Nerve Growth Factors (NGFs) have diverse functions in the nervous system. Their role in integration of physiological functioning of the nervous system is now attracting attention. In the present analysis, we propose a novel paradigm about a novel role of NGFs: NGFs play imperative role in maintaining psychological integrity of an individual as a biological system. This function may be mediated through HPA-axis- operated homeostatic mechanisms; stress induced disruption of which may lead to psychiatric disorders. Current literature suggests existence of constitutive homeostatic regulatory mechanisms for NGFs disruption which may lead to pertinent and imperative behavioural effects. NGFs are known to play crucial role in endocrine regulation. This is especially true with the prototype ‘NGF’ and Brain Derived Neurotrophic Factor (BDNF). These moieties have been observed to play important function in maintaining neuro-endocrine homeostasis thereby having a profound impact on the psychological health of an individual. Role of NGFs and HPA-axis activation (in separate studies) in developing psychiatric disorders - especially those born of stress - have been reported. Literature suggests their unique interplay for producing a common effect which might be implicated in stress induced genesis of psychiatric disorders. This aspect, therefore, needs to be elucidated further as a disease etiogenesis model. This model may yield important insights into the biology of psychiatric disorders and may open ways for new therapeutic approaches.

Nanosilver plays an important role in nanoscience and nanotechnology, and is becoming increasingly used for applications in nanomedicine. Nanosilver ranges in size from one to one hundred nanometers. Smaller particles more readily enter cells and interact with the cellular components. The exposure dose, particle size, coating, and aggregation state of the nanosilver, as well as the cell type or organism that it is tested on, all have a large determining factor on the effect and potential toxicity of nanosilver. A high exposure dose to nanosilver alters the cellular stress responses and initiates cascades of signaling that can eventually trigger organelle autophagy and apoptosis. This review summarizes the current knowledge of the effects of nanosilver on cellular metabolic function and response to stress. Both the causative effects of nanosilver on oxidative stress, endoplasmic reticulum stress, and hypoxic stress, as well as the effects of nanosilver on the responses to such stresses, are outlined. The interactions and effects of nanosilver on cellular uptake, oxidative stress (reactive oxygen species), inflammation, hypoxic response, mitochondrial function, endoplasmic reticulum function and the unfolded protein response, autophagy and apoptosis, angiogenesis, epigenetics, genotoxicity, and cancer development and tumorigenesis, as well as other pathway alterations are examined in this review.

The bottleneck in creating dynamic models of biological networks and processes often lies in estimating unknown kinetic model parameters from experimental data. In this regard, experimental conditions have a strong influence on parameter identifiability and should therefore be optimized to give the maximum information for parameter estimation. Existing model-based design of experiment (MBDOE) methods commonly rely on the Fisher Information Matrix (FIM) for defining a metric of data informativeness. When the model behavior is highly nonlinear, FIM-based criteria may lead to suboptimal designs since the FIM only accounts for the linear variation of the model outputs with respect to the parameters. In this work, we developed a multi-objective optimization (MOO) MBDOE, where model nonlinearity was taken into consideration through the use of curvature. The proposed MOO MBDOE involved maximizing data informativeness using a FIM-based metric and at the same time minimizing the model curvature. We demonstrated the advantages of the MOO MBDOE over existing FIM-based and other curvature-based MBDOEs in an application to the kinetic modeling of fed-batch fermentation of Baker's yeast.

Evodiamine is a bioactive alkaloid that is specified as a biomarker for the quality assessment of Evodia rutaecarpa and for traditional Chinese medicines containing this plant. We previously reported that quantitative structure-activity modeling indicated that evodiamine may cause cardiotoxicity. However, previous investigations have indicated that evodiamine has beneficial effects in patients with cardiovascular diseases and there are no previous in vitro or in vivo reports of evodiamine-induced cardiotoxicity. The present study investigated the effects of evodiamine on primary cultured neonatal rat cardiomyocytes in vitro, and on zebrafish in vivo. Cell viability was reduced in vitro, where evodiamine had a 24-h 50% inhibitory concentration of 28.44 µg/mL. Cells exposed to evodiamine also showed increased lactate dehydrogenase release and maleic dialdehyde levels, and reduced superoxide dismutase activity. In vivo, evodiamine had a 10% lethal concentration of 354 ng/mL and induced cardiac malfunction, as evidenced by changes in heart rate and circulation, and pericardial malformations. This study indicated that evodiamine could cause cardiovascular side effects involving oxidative stress. These findings suggest that cardiac function should be monitored in patients receiving preparations containing evodiamine.

This paper studies the combined effect of corrosion and fatigue on the growth of cracks in aircraft and on the effect of skin corrosion and stress corrosion cracking on the load bearing capacity of rib stiffened aircraft wings. In this context it is shown that the growth of cracks from surface pitting, and also from intergranular cracking at a fastener hole, can be accurately computed using the Hartman-Schijve variant of the NASGRO crack growth equation. The examples studied support the lead crack approach, that has been independently developed by the USAF and the Australian Defence Science Technology Group, in which the growth of lead cracks is often exponential. In the case of skin corrosion it is shown that to be consistent with the US Joint Service Structural Guidelines (JSSG2006) assessment of its effect on the load bearing capacity of the wing should involve an assessment of whether at 115% DLL the remaining material exceeds the yield stress of the material.

The influence of short term water absorption on the mechanical properties of halloysite nanotubes-multi layer graphene reinforced polyester hybrid nanocomposites has been investigated. The addition of nano-fillers significantly increased the flexural strength; tensile strength and impact strength in dry and wet conditions. After short term water exposure; the maximum microhardness; tensile; flexural and impact toughness values were observed at 0.1 wt% MLG. The microhardness increased up to 50.3%; tensile strength increased up to 40% and flexural strength increased up to 44%. Compared to dry samples; the fracture toughness and surface roughness of all types of produced nanocomposites were increased that may be attributed to plasticization effect. Scanning electron microscopy revealed that the main failure mechanism is caused by the weakening of nano-filler-matrix interface induced by water absorption. It was further observed that synergistic effects were not effective at concentration of 0.1 wt% to produce considerable improvement in mechanical properties of produced hybrid nanocomposites.

Multi-walled carbon nanotubes (MWCNTs) and graphene oxide (GO) reinforced carbon foam (CF) composite were prepared by direct pyrolysis of MWCNTs, GO and mesophase coal tar pitch. The effect of additive amount of the mixture of MWCNTs and GO on the microstruture and properties of carbon foam was analzyed by transmission electron miscroscopy (TEM), scanning electron microscopy (SEM), X-ray diffraction (XRD), Four-probe resistance meter, universal testing machine, and laser thermal conductivity tester respectively. The result shows that MWCNTs and GO had significant impact on the microstructure of carbon foam. Futhermore, the electrical, mechanical and thermal properties of carbon foam composites were significantly enhanced by increasing the additive amount. Maximum compressive strenght of 19.2 MPa and Young’s modulus of 56.8 MPa of CF composite were observed. Similarly, Highest thermal conductivity of 30.91 W/m.K and electrical conductivity of 27.2 ×103 S/m were observed at 2 wt. % of MWCNTs-GO additive loading.

Optical and mechanical properties of multilayer coatings depend on the selected layer materials and the deposition technology; therefore, knowledge of the performances of thin films is essential. In the present work, titanium dioxide (TiO2) and silicon dioxide (SiO2) thin films have been prepared by plasma ion-assisted deposition (PIAD). The optical, structural, and mechanical properties of thin films have been investigated using spectrometer/ellipsometer, X-ray diffraction (XRD), atomic force microscopy (AFM), and laser interferometer. The results show that TiO2 film fabricated by PIAD induces a high refractive index, wide optical band gap, amorphous structure, smooth surface, and tensile stress. In the case of SiO2 film, high bias voltage leads to dense structure and compressive stress. As an application, a three-wavelength high reflectance at 632.8, 808, and 1550nm is optimized and deposited. The dependence of total stress in the multilayer on the substrate temperature is studied as well. In conclusion, it is demonstrated that PIAD is an effective method for the preparation of ultralow stress TiO2/SiO2 multilayer films. The achieved stress is as low as 1.4Mpa. The result could provide guidance to the stress optimization of most optical components without prefiguring, backside coating, and post-deposition treatments.

BACKGROUND: Stable-phase schizophrenia may comprise two distinct nosological entities namely Major Neuro-Cognitive Psychosis (MNP, largely overlapping with the deficit syndrome) and simple NP (SNP), which are defined by neuroimmune and neurocognitive abnormalities. Furthermore, cognitive impairments and PHEM (psychotic, hostility, excitation, mannerism) and negative symptoms load on the same dimension.METHODS: The current study aimed to investigate associations of psychomotor retardation (PMR) and clinical as well as biomarker characteristics of schizophrenia. We recruited 40 healthy controls and 79 schizophrenia patients and measured IgA responses to tryptophan catabolites (TRYCATs), IgM to malondialdehyde and nitroso (NO)-cysteinyl, macrophage inflammatory protein-1 (MIP-1), soluble interleukin (IL)-1 receptor antagonist (sIL-1RA), IL-10, CCL-11 as well as PMR items of different rating scales and motor screening task (MOT). RESULTS: PMR differentiated schizophrenia from controls and MNP from SNP. In addition, PMR was strongly associated with executive functions, deficits in episodic and semantic memory, PHEM and negative (PHEMN) symptoms. Around 50% of the variance in PMR was predicted by the cumulative effects of immune activation, CCL-11, TRYCATs and NO-Cysteinyl levels, and lowered natural IgM. PRM may be reliably combined with PHEMN symptoms and memory and executive impairments into one latent vector reflecting overall psychopathology.CONCLUSIONS: Current findings indicate that PMR may be a key psychopathological feature of schizophrenia and mainly MNP. In addition, PMR and associated impairments in memory and executive functions, and PHEMN symptoms may be driven by deficits in the compensatory immune regulatory system (natural IgM) combined with increased production of neurotoxic immune products, namely TRYCATs and IgM to NO-cysteinyl, and an endogenous cognition deteriorating chemokine, namely CCL-11.

Background: Post-traumatic stress disorder (PTSD) is a common debilitating psychiatric condition for which pharmacological therapy is not always solvable. Various treatments have been suggested for these patients. Deep brain stimulation (DBS) is currently under investigation for patients affected by PTSD. 2) Methods: We review the neurocircuitry and up to date clinical concepts that may be of relevance for the implementation of DBS in posttraumatic stress disorder (PTSD). 3) Results: The role of DBS in treatment-refractory PTSD patients has been investigated relying on both preclinical and clinical studies. 4) Conclusions: DBS for PTSD is in its preliminary phases and likely to provide hope to patients with medical refractory PTSD following the results of randomized controlled studies.

Using hierarchical regression analysis within a mediation model framework, the present study explores direct and indirect (through life satisfaction) causal impacts of commuting stress on turnover intention of employees from 29 business organizations in six populous cities of Turkey. A semi-random heterogeneous sample of 214 employees with different demographics was surveyed in winter and summer times for also capturing seasonal variations of variables. The results supporting the partial mediating role of life satisfaction in the positive relationship between commuting stress and turnover intention infer that commuting stress induces turnover intention directly and indirectly (by reducing life satisfaction). The analysis of variance reveals that demographic characteristics of employees such as gender, marital status, age, and family size together with commuting type and commuting duration matter for their perceived commuting stress, life satisfaction, and turnover intention levels. Commuting stress perception is relatively higher in summer time whereas the other magnitudes are consistently and significantly invariant between two survey implementations. The study concludes with a call for the consideration of commuting stress and life satisfaction together with environmental and demographic factors when analyzing the antecedents and consequences of employee turnover intention.

Multi-step ahead streamflow forecasting is of practical interest for the operation of hydropower reservoirs. We provide generalized results on the error evolution in multi-step ahead forecasting by conducting several large-scale experiments based on simulations. We also present a multiple-case study using monthly time series of streamflow. Our findings suggest that some forecasting methods are more useful than others. However, the errors computed at each time step of a forecast horizon within a specific case study strongly depend on the case examined and can be either small or large, regardless of the forecasting method used and the time step of interest.

This review describes the positive effects of growth hormone on the cardiovascular system. We analyze why the vascular endothelium is a real internal secretion gland, whose inflammation is the first step for developing atherosclerosis, as well as the mechanisms by which GH acts on the vascular endothelium improving its dysfunction. We also report how GH acts on coronary arterial disease and heart failure, and on peripheral arterial disease inducing the generation of new collateral vessels able to bypass a major artery occlusion. We include some preliminary data from a trial in which GH or placebo is given to elder people suffering from critical limb ischemia, showing the effects of the hormone on plasma markers of inflammation, and stating that the administration of GH in short periods of time is safe and effective even in diabetic patients. We also analyze how Klotho may have strong relationships with GH, inducing, after being released from the damaged vascular endothelium, the pituitary secretion of GH to repair the damaged tissue. Lastly, we show how GH induces wound healing by increasing the blood flow to the ischemic tissue. In summary, we postulate that short-time GH administration is useful for treating cardiovascular diseases.

Background: Appendicular skeletal muscle (or lean) mass (ALM) estimated using dual-energy X-ray absorptiometry (DXA) is considered to be a preferred method for sarcopenia studies. However, DXA is expensive, has limited portability, and requires radiation exposure. Bioelectrical impedance analysis (BIA) is inexpensive, easy to use, and portable; thus BIA might be useful in sarcopenia investigations. However, a large variety of models have been commercially supplied by different companies, and for most consumer products, the equations estimating ALM are not disclosed. It is therefore difficult to use these equations for research purposes. In particular, the BIA equation is often age-dependent, which leads to fundamental difficulty in examining age-related ALM loss. The aims of the current study were as follows: (1) to develop and validate an equation to estimate ALM using multi-frequency BIA (MF-BIA) based on theoretical models, and (2) to establish sarcopenia cutoff values using the equation for the Japanese population. Methods: We measured height (Ht), weight, and ALM obtained using DXA and a standing-posture 8-electrode MF-BIA (5, 50, 250 kHz) in 756 Japanese individuals aged 18 to 86-years-old (222 men and 301 women as developing equation group and 97 men and 136 women as a cross validation group). The traditional impedance index (Ht²/Z₅₀) and impedance ratio of high and low frequency (Z₂₅₀/Z₅) of hand to foot values were calculated. Multiple regression analyses were conducted with ALM as dependent variable in men and women separately. Results: We created the following equations: ALM = (0.6947 × (Ht²/Z₅₀)) + (−55.24 × (Z₂₅₀/Z₅)) + (−10,940 × (1/Z₅₀)) + 51.33 for men, and ALM = (0.6144 × (Ht²/Z₅₀)) + (−36.61 × (Z₂₅₀/Z₅)) + (−9332 × (1/Z₅₀)) + 37.91 for women. Additionally, we conducted measurements in 1624 men and 1368 women aged 18 to 40 years to establish sarcopenia cutoff values in the Japanese population. The mean values minus 2 standard deviations of the skeletal muscle mass index (ALM/Ht²) in these participants were 6.8 and 5.7 kg/m² in men and women, respectively. Conclusion: The current study established and validated a theoretical and age-independent equation using MF-BIA to estimate ALM and provided reasonable sarcopenia cutoff values.

With the proliferation of locating devices, more and more raw spatial trajectories are formed, and many works enrich these raw trajectories with semantics, and mine patterns from both raw and semantic trajectories, but access control of spatial trajectories is not considered yet. We present a multi-policy secure model for semantic spatial trajectories. In our model, Mandatory Access Control, Role Based Access Control and Discretionary Access control are all enforced, separately and combined, and we represent the model semi-formally in Ontology Web Language.

Many studies were done in the development of drought stress-tolerant transgenic plants, including crop plants. Rice is considered to be a vital crop target for improving drought stress tolerance. Much transgenic rice showed improved drought stress tolerance was reported to date. They are genetically engineered plants that are developed by using genes that encode proteins involved in drought stress regulatory networks. These proteins include protein kinases, transcription factors, enzymes related to osmoprotectant or plant hormone synthesis, receptor-like kinase. Of the drought stress-tolerant transgenic rice plants described in this review, most of them display retarded plant growth. In crop crops, plant health is a fundamental agronomic trait that can directly affect yield. By understanding the regulatory mechanisms of retarded plant growth under drought stress, conditions are necessary precursors to developing genetically modified plants that result in high yields.

This study aims to understand the current state of research in urban resilience and to open a discussion about multi-level perspectives for this concept. Starting with the history of the concept of resilience, we identify three main stages in resilience concept’s evolution: conceptualization, contextualization and operationalization. Confusion occurs between sustainability and resilience, therefore we clearly separate these two concepts by creating conceptual maps. Such maps also underline the specificities of urban and regional resilience discourses. We illustrate that urban resilience research, operating within intra-urban processes, is oriented towards natural disasters, while regional resilience research, operating mostly within inter-urban processes, is oriented towards economic shocks. We show that these two approaches to resilience – urban and regional – are complementary, and we propose to integrate them into a multi-level perspective. By combining these two discourses, we propose a multi-level approach to urban resilience that takes into account both top-down and bottom-up resistance processes. In the discussion section, we propose to take the panarchy perspective as a theoretical framework for multi-level urban resilience, that explains the interactions between different levels through adaptive cycles, relationships between which can help to explain urban resilience.

In the extra-thick coal seams and multi-layered hard roofs, the longwall hydraulic support yielding, coal face spalling, strong deformations of goaf-side entry, and severe ground pressure dynamic events typically occur at the longwall top coal caving longwall faces. Based on the Key strata theory an overburden caving model is proposed here to predict the multilayered hard strata behaviour. The proposed model together with the measured stress changes in coal seam and underground observations in Tongxin coal mine provides a new idea to analyse stress changes in coal and help to minimise rock bursts in the multi-layered hard rock ground. Using the proposed primary Key and the sub-Key strata units the model predicts the formation and instability of the overlying strata that leads to abrupt dynamic changes to the surrounding rock stress. The data obtained from the vertical stress monitoring in the 38 m wide coal pillar located adjacent to the longwall face indicates that the Key strata layers have a significant influence on ground behaviour. Sudden dynamically driven unloading of strata was caused by the first caving of the sub-Key strata while reloading of the vertical stress occurred when the goaf overhang of the sub-Key strata failed. Based on this findings several measures were recommended to minimise the undesirable dynamic occurrences including pre-split of the hard Key strata by blasting and using the energy consumption yielding reinforcement to support the damage prone gate road areas. Use of the numerical modelling simulations was suggested to improve the key theory accuracy.

Exercise-based cardiac rehabilitation requires patients to perform a set of certain prescribed exercises a specific number of times. Local muscular endurance (LME) exercises are an important part of the rehabilitation program. Automatic exercise recognition and repetition counting, from wearable sensor data is an important technology to enable patients to perform exercises independently in remote settings, e.g. their own home. In this paper we first report on a comparison of traditional approaches to exercise recognition and repetition counting, corresponding to supervised machine learning and peak detection from inertial sensing signals respectively, with more recent machine learning approaches, specifically Convolutional Neural Networks (CNNs). We investigated two different types of CNN: one using the AlexNet architecture, the other using time-series array. We found that the performance of CNN based approaches were better than the traditional approaches. For exercise recognition task, we found that the AlexNet based single CNN model outperformed other methods with an overall 97.18% F1-score measure. For exercise repetition counting , again the AlexNet architecture based single CNN model outperformed other methods by correctly counting repetitions in 90% of the performed exercise sets within an error of ±1. To the best of our knowledge, our approach of using a single CNN method for both recognition and repetition counting is novel. In addition to reporting our findings, we also make the dataset we created, the INSIGHT-LME dataset, publicly available to encourage further research.

This paper presents a new and enhanced fusion module for the Multi-Sensor Precipitation Estimator (MPE) that would objectively blend real-time satellite quantitative precipitation estimates (SQPE) with radar and gauge estimates. This module consists of a preprocessor that mitigates systematic bias in SQPE, and a two-way blending routine that statistically fuses adjusted SQPE with radar estimates. The preprocessor not only corrects systematic bias in SQPE, but also improves the spatial distribution of precipitation based on SQPE and makes it closely resemble that of radar-based observations. It uses a more sophisticated radar-satellite merging technique to blend preprocessed datasets, and provides a better overall QPE product. The performance of the new satellite-radar-gauge blending module is assessed using independent rain gauge data over a 5-year period between 2003-2007, and the assessment evaluates the accuracy of newly developed satellite-radar-gauge (SRG) blended products versus that of radar-gauge products (which represents MPE algorithm currently used in the NWS operations) over two regions: I) inside radar effective coverage and II) immediately outside radar coverage. The outcomes of the evaluation indicate a) ingest of SQPE over areas within effective radar coverage improve the quality of QPE by mitigating the errors in radar estimates in region I; and b) blending of radar, gauge, and satellite estimates over region II leads to reduction of errors relative to bias-corrected SQPE. In addition, the new module alleviates the discontinuities along the boundaries of radar effective coverage otherwise seen when SQPE is used directly to fill the areas outside of effective radar coverage.

Impervious surface mapping with high-resolution remote sensing imagery has attracted increasing interest as it can provide detailed information for urban structure and distribution. Previous studies have suggested that the combination of LiDAR data and high-resolution imagery for impervious surface mapping performs better than using only high-resolution imagery. However, due to the high cost of the acquisition of LiDAR data, it is difficult to obtain the multi-sensor remote sensing data acquired at the same acquisition time for impervious surface mapping. Consequently, real landscape changes between multi-sensor remote sensing data at different acquisition times would lead to the error of misclassification in impervious surface mapping. This issue has mostly been neglected in previous works. Furthermore, the observation differences generated from multi-sensor data, including the problems of misregistration, missing data in LiDAR data, and shadow in high-resolution images would also challenge the final mapping result in the fusion of LiDAR data and high-resolution images. In order to conquer these problems, we propose an improved impervious surface mapping method incorporating both LiDAR data and high-resolution imagery at different acquisition times in consideration of real landscape changes and observation differences. In the proposed method, a multi-sensor change detection by supervised multivariate alteration detection is employed to obtain changed areas and misregistration areas. The no-data areas in the LiDAR data and the shadow areas in the high-resolution imagery are extracted by independent classification yielded by its corresponding single sensor data. Finally, an object-based post-classification fusion is proposed to take advantage of independent classification results with single-sensor data and the joint classification result with stacked multi-sensor data. Experiments covering the study site in Buffalo, NY, USA demonstrate that our method can accurately detect landscape changes and obviously improve the performance of impervious surface mapping.

Different organisms, cell types, and even similar cell lines can dramatically differ in resistance to genotoxic stress. This testifies to the wide opportunities for genetic and epigenetic regulation of stress resistance. These opportunities could be used to increas the effectiveness of cancer therapy, develop new varieties of plants and animals, and search for new pharmacological targets to enhance human radioresistance, for example, for -manned deep space expeditions. Based on the comparison of transcriptomic studies in cancer cells, in this review we propose that there is a high diversity of genetic mechanisms of development of genotoxic stress resistance. This review focused onpossibilities and limitations of the proposed regulation of the resistance of normal cells whole organisms to genotoxic and oxidative stress by overexpressing of stress-response genes. Moreover, the existing experimental data on the effect of such overexpression on the resistance of cells and organisms to various genotoxic agents has been analyzed and systematized. We suggest that the recent advances in the development of multiplex and highly customizable gene overexpression technology that utilizes the mutant Cas9 protein and the wealth of available data on gene functions and their signal networks open new opportunities for research in this field.

The interaction between single or a fixed number of photons with a single absorber is of fundamental interest in quantum technology. The harnessing of light matter interactions at the single particle limit has several potential applications ranging from quantum communication and quantum metrology to quantum imaging. In this letter, a setup for heralded two-photon absorption at the single absorber level is proposed. The setup is based on a heralded two-photon source utilizing spontaneous parametric down-conversion, entanglement swapping and sum frequency generation for joint detection. The feasibility of the scheme is discussed by reviewing recent achievements in utilizing entangled and correlated photons for two-photon absorption as well as single photon absorption experiments at the limit of single absorbers in the context of applications in imaging (here mainly microscopy) and spectroscopy.

The burdens of malnutrition, protein and micronutrient deficiency, and obesity cause enormous costs to society. Crop nutritional quality has been compromised by the emphasis on edible yield and through the loss of biodiversity due to the introduction of high-yielding uniform cultivars. Heirloom crop cultivars are traditional cultivars grown for a long time (> 50 years), and whose heritage has been preserved by regional, ethnic or family groups. Heirlooms are recognized for their unique appearance, names, uses and historical significance. They are gaining in popularity because of their unique flavors and cultural significance to local cuisine, and their role in sustainable food production for small-scale farmers. As a contrast to modern cultivars, heirlooms may offer a welcome alternative in certain markets. Recently, market channels have emerged for heirloom cultivars in the form of farmer-breeder-chef collaborations and seed savers organizations. There is therefore urgent need to know more about the traits available in heirloom cultivars, particularly for productivity, stress tolerance, proximate composition, sensory quality and flavor. This information is scattered and the intention of this review is to document some of the unique characteristics of heirloom cultivars that may be channeled into breeding programs for developing locally adapted high value cultivars.

The GAI‐RGA ‐ and ‐SCR (GRAS) proteins belong to the plant-specific transcription factor gene family and involved in several developmental processes, phytohormone and phytochrome signaling, symbiosis, stress responses etc. GRAS proteins have a conserved GRAS domain at C-terminal and hypervariable N-terminal. The C-terminal conserved domain directly affects the function of the GRAS proteins. For instance, in Arabidopsis, mutations in this domain in Slender rice 1 (SLR1) and Repressor of GA (RGA) proteins cause significant phenotypic changes. GRAS proteins have been reported in more than 30 plant species and till now it has been divided into 17 subfamilies. This review highlighted GRAS protein's importance during several biological processes in plants, structural features of GRAS proteins, their expansion and diversification in the plants, GRAS-interacting proteins complexes and their role in biological processes. We also summarized available recent research that utilized CRISPR-Cas9 technology to manipulate GRAS genes in a plant for different traits. Further, the exploitation of GRAS genes in crop improvement programs has also been discussed

To understand great disparities in disease outcomes between CIVID-19 patients, we explore infection and host responses in kinetics. From existing data, we deduced a model that the lungs are damaged by rapidly rising flow resistance as a result of retaining white blood cells in lung tissues. The retention of white blood cells is initially triggered by viral infection but aggravated by injuries caused by low temperature. Lungs are initially damaged by fluid leakage, rapidly followed by extruding blood into alveolar spaces. The step of blood extruding is predicted to take place in a very short time. Our simulations show that as little as 0.1% retention of white blood cells in the lungs can lead to their failure in 5 to 10 days. The small degrees of imbalance implies that this imbalance could be corrected by a large number of factors that are known to reduce flow resistance. The model implies that the top priority is maintaining blood micro-circulation and preserving organ functions in the entire disease course, especially after the virus has spread the whole lungs. From exploring a large number of hypothetical infection modes, we propose preventive, mitigating and treatment strategies for ultimately ending the pandemic. The first strategy is avoiding exposures that could result in widespread damages to lungs and taking post exposure mitigating measures that would reduce disease severity. The second strategy is reducing death rate and disability rate from the current levels to one tenth for infected patients by using multiple factors health optimization method. The double reduction strategies are expected to generate a series of chain reactions that favor mitigating or ending the pandemic. Some reactions include a big reduction of the amount of viral discharges from infected patients into the air, the avoidance of panic, chronic stress and emotional distress, and cross-infections which are expected in quarantines. The double reductions would have a final effect of ending the pandemic.

The purpose of the present study was to examine if 14 days of supplementation with a pine bark extract leading up to and following an exercise test would increase performance and reduce biomarkers associated with muscle damage, inflammation and oxidative stress. The study used a double-blind, placebo controlled, cross-over design. Participants ingested either 800mg pine bark extract or placebo for 14 days prior to the first exercise trial and for 2 days post-exercise. On the exercise day, participants submitted a pre-exercise blood sample, then completed a VO₂ peak test until volitional failure. A post-blood sample was collected 1 hour after completion of exercise. Participants returned at 24 & 48 hours after the exercise testing for measures of muscle pain in the lower body using an algometer. Participants then had a 7-day washout period before beginning to crossing over to the alternate treatment. Analysis via ordinal regression demonstrated a significant difference in oxidative stress in the pine bark extract group compared to placebo (ChiSq = 2.63; p = 0.05). The pine bark extract was effective at affording protection from oxidative stress post exercise. Further work should be undertaken to evaluate the findings with other exercise modes or in participants with known metabolic syndrome.

Alcohol abuse can result in detrimental multisystem effects. Chronic alcohol abuse is known to be associated with pathophysiological changes in multiple organs often resulting in life threatening clinical outcomes e.g. breast and colon cancer, pancreatic disease, cirrhosis of the liver, diabetes, osteoporosis, arthritis, kidney disease, immune system dysfunction, hypertension, coronary artery disease, alcohol-induced cardiomyopathy and heart failure as well as central nervous system disorders. In this review article, we will discuss the multisystemic effects of alcohol abuse and explore in greater detail alcohol’s impact on two main systems that result in pathophysiological changes i.e. the cardiovascular and central nervous systems.

Since January, the disease caused by the Sars Cov-2 virus has spread and following pandemic. In a few months, the virus is seriously affecting the health systems of the various countries of the world and placing people in difficult psychological conditions. Few scientific resources on mental health have been published but still no one has proposed an action plan to cope the future psychological problems.This manuscript provides a plan to easily frame the priorities of mental health area related to COVID-19 to be taken into consideration which should be disseminated and that should be known by all health professionals and also by the major administrators of public health.

Neutrosophic cubic set is the hybridization of the concept of neutrosophic set and interval neutrosophic set. Neutrosophic cubic set has the capacity to express the hybrid information of both the interval neutrosophic set and the single valued neutrosophic set simultaneously. As newly defined, little research on the operations and applications of neutrosophic cubic sets appear in the current literature. In the present paper we propose the score, accuracy functions for neutrosophic cubic sets and prove their basic properties. We firstly develop TODIM method to solve multi attribute group decision making in neutrosophic cubic set environment, which we call NC-TODIM. Also, we solve a MAGDM problem using the proposed NC-TODIM method to show the applicability and effectiveness of the developed method. We also conduct sensitivity analysis to show the impact of ranking order of the alternatives for different values of attenuation factor of losses for multi-attribute group decision making problem.

By using the new recently proposed extended rational methods, we set some solitary and multi wave solutions of the coupled Higgs system in the present study. Some new families of hyperbolic and trigonometric solutions of the coupled Higgs equations are successfully obtained. Some solutions are real as some are complex valued functions. Particular forms of some solutions derived by choice of some parameters are demonstrated in three dimensional spaces. The complex valued solutions are also depicted by plotting both real and complex component.

Geometric Akaike Information Criteria (G-AICs) for generalized noise-level dependent crystallographic symmetry classifications of two-dimensional (2D) images that are more or less periodic in either two or one dimensions as well as Akaike weights for multi-model inferences and predictions are reviewed. Such novel classifications do not refer to a single crystallographic symmetry class exclusively in a qualitative and definitive way. Instead, they are quantitative, spread over a range of crystallographic symmetry classes, and provide opportunities for inferences from all classes (within the range) simultaneously. The novel classifications are based on information theory and depend only on information that has been extracted from the images themselves by means of maximal likelihood approaches so that these classifications are objective. This is in stark contrast to the common practice whereby arbitrarily set thresholds or null hypothesis tests are employed to force crystallographic symmetry classifications into apparently definitive/exclusive states, while the geometric feature extraction results on which they depend are never definitive in the presence of generalized noise, i.e. in all real world applications. Thus, there is unnecessary subjectivity in the currently practiced ways of making crystallographic symmetry classifications, which can be overcome by the approach outlined in this review.

In this paper, some new properties of the fundamental solution to the multi-dimensional space- and time-fractional diffusion-wave equation are deduced. We start with the Mellin-Barnes representation of the fundamental solution that was derived in the previous publications of the author. The Mellin-Barnes integral is used to get two new representations of the fundamental solution in form of the Mellin convolution of the special functions of the Wright type. Moreover, some new closed form formulas for particular cases of the fundamental solution are derived. In particular, we solve an open problem of representation of the fundamental solution to the two-dimensional neutral-fractional diffusion-wave equation in terms of the known special functions.