Miracle-dz/UniFAR-FTUs huggingface dataset:
Climate Services Transformed: Decision-Making Practice for the Coast in a Changing Climate

Climate services play an important role in informing decision makers about how to reduce the impact of climate-related hazards, by building capacity through access to relevant data and information globally and regionally. Different types of climate services include long-term warning systems, projections, monitoring/triggers and signals, risk evaluation tools, and behavior change tools. However, climate services are often promoted as “improving uptake” and “translating and communicating science” This framing, which assumes that climate services are developed by scientists and “provided” to users, has limitations for decision makers designing actions to address changing coastal hazard risk driven by sea-level rise. Acting upon the IPCC 1.5 Degree Special Report imperative for urgent actions to reduce exposure and vulnerability at the coast will require a transformation in the way climate services are developed and delivered, in tandem with an understanding of the decision-making and policy context. Tools and policies must explicitly address deepening uncertainty and changing risk over long timeframes. Their use also must be compatible with the jurisdiction’s institutional frameworks and decision-making practice and relevant to user needs as changing risks unfold. Attention to both short- and long-term decisions are paramount to avoid lock-in and path dependency of decisions taken today, and to ensure relevance for the timeframes of investments in infrastructure and settlements. This requires actionable science and usable tools developed through multi-disciplinary efforts by scientists, co-producing them with decision agencies and communities. We give examples of different types of climate services developed with users and draw out some universal lessons learned in developing and applying them in New Zealand.
Longitudinal changes of spinal cord grey and white matter following spinal cord injury

Objectives Traumatic and non-traumatic spinal cord injury produce neurodegeneration across the entire neuraxis. However, the spatiotemporal dynamics of spinal cord grey and white matter neurodegeneration above and below the injury is understudied. Methods We acquired longitudinal data from 13 traumatic and 3 non-traumatic spinal cord injury patients (8–8 cervical and thoracic cord injuries) within 1.5 years after injury and 10 healthy controls over the same period. The protocol encompassed structural and diffusion-weighted MRI rostral (C2/C3) and caudal (lumbar enlargement) to the injury level to track tissue-specific neurodegeneration. Regression models assessed group differences in the temporal evolution of tissue-specific changes and associations with clinical outcomes. Results At 2 months post-injury, white matter area was decreased by 8.5% and grey matter by 15.9% in the lumbar enlargement, while at C2/C3 only white matter was decreased (−9.7%). Patients had decreased cervical fractional anisotropy (FA: −11.3%) and increased radial diffusivity (+20.5%) in the dorsal column, while FA was lower in the lateral (−10.3%) and ventral columns (−9.7%) of the lumbar enlargement. White matter decreased by 0.34% and 0.35% per month at C2/C3 and lumbar enlargement, respectively, and grey matter decreased at C2/C3 by 0.70% per month. Conclusions This study describes the spatiotemporal dynamics of tissue-specific spinal cord neurodegeneration above and below a spinal cord injury. While above the injury, grey matter atrophy lagged initially behind white matter neurodegeneration, in the lumbar enlargement these processes progressed in parallel. Tracking trajectories of tissue-specific neurodegeneration provides valuable assessment tools for monitoring recovery and treatment effects.
Studies on in vitro evaluation of antidiabetic potentials of watermellon and pomegranate peels

Diabetes is a metabolic disorder which results due to deficiency in insulin and its metabolism. At present, the prevalence of Diabetes has increased worldwide and predicted to increase to greater extent in future generations. Among various therapeutic approaches implemented to prevent diabetes is to regulate the blood glucose levels by various mechanisms. This is being assessed by in vitro antidiabetic assays such as inhibition of carbohydrate digesting enzymes and non-enzymatic glycosylation of haemoglobin. Inhibition of alpha-amylase enzyme suppresses the level of production of glucose and by inhibiting glycosylation of haemoglobin the level of blood glucose is maintained. Hence the current work focuses on investigating the anti-diabetic activity of fruit peel of Citrullus lanatus (watermelon) and Punica granatum (pomegranate) using the above mentioned assays. Our results suggested that methanol extract of Citrullus lanatus and Punica granatum peels showed potential anti-diabetic activity in vitro which indicates that these extracts can be taken further for in vivo studies. Keywords: fruit peels, antidiabetic activity, α-amylase enzyme, glycosylated haemoglobin
Synchronisation and Circuit Realisation of Chaotic Hartley System

Abstract Hartley chaotic system is topologically the simplest, but its dynamical behaviours are very rich and its synchronisation has not been seen in literature. This paper aims to introduce a simple chaotic system which can be used as alternative to classical chaotic systems in synchronisation fields. Time series, phase portraits, and bifurcation diagrams reveal the dynamics of the mentioned system. Chaotic Hartley model is also supported with electronic circuit model simulations. Its exponential dynamics are hard to realise on circuit model; this paper is the first in literature that handles such a complex modelling problem. Modelling, synchronisation, and circuit realisation of the Hartley system are implemented respectively in MATLAB-Simulink and ORCAD environments. The effectiveness of the applied synchronisation method is revealed via numerical methods, and the results are discussed. Retrieved results show that this complex chaotic system can be used in secure communication fields.
An up to date review of continuously variable speed wind turbines with mechatronic variable transmissions

As a promising and potential alternative to conventional fixed or variable speed wind turbines, continuously variable speed wind turbines (CVSWTs) with variable transmissions offer improved power efficiency and enhanced power control capabilities. The CVSWTs can be generally achieved by adapting mechatronic variable transmissions in the turbine drive train for continuously variable speed operations for wind turbines. Therefore, this paper serves to provide an up to date and exhaustive review of the CVSWTs with mechatronic variable transmissions such as mechanical variable transmission, electrical variable transmission, and power splitting transmission. In this paper, the analysis of CVSWTs with different mechatronic transmission topologies is performed regarding basic configurations, dynamic characteristics, control principles, and experimental or simulation results. Review results indicate the feasibility of applying CVSWTs with such mechatronic transmissions and highlight superiorities of the CVSWTs with power splitting transmission. The CVSWT with power splitting transmission will be particularly suitable for megawatt‐scale turbine systems and will hence increase the economic competitiveness of these turbines due to its large power capacity and high reliability. The directions or challenges for future investigations of CVSWTs with such mechatronic transmissions are also presented to foster in‐depth understanding of such CVSWTs and their control strategies.
Patient preference and pain-reported outcomes for topical versus subtenon anesthetic for cataract surgery

PURPOSE: Cataract extraction and lens implantation is the most common surgical procedure performed worldwide, with surgeons opting for either a topical or a subtenon anesthetic in majority of cases. While complication rates and pain scores have been previously examined in a bid to determine which modality was better, patients who have had both eyes operated upon under different techniques have never previously been asked which method they prefer. We undertook this study to fill in this crucial gap in our knowledge. METHODS: This is a retrospective study of patients who have undergone bilateral cataract surgery with one eye operated on with topical anesthesia and the other eye with subtenon anesthesia. Patients were identified who had had surgery undertaken in the previous 6 months at Singleton Hospital, Swansea, where both eyes had been operated upon using different anesthetic techniques. Telephone interviews with these patients were performed and their pain scores recorded on a scale from 0 (no pain) to 10 (severe pain) for both eyes, with the patients then being asked which the method of anesthetic they preferred. Statistical analysis of pain scores was compared using Wilcoxon rank-sum testing. RESULTS: One hundred and fifty-two patients in total were identified. One hundred and forty-one of the applicable patients participated in the study. Of these, 78 patients received topical anesthesia for their first operation and 63 had subtenon block for their first operation. The mean pain scores reported for surgery with topical anesthesia and subtenon block were 2.30 and 1.38, respectively. The pain data were analyzed using a Wilcoxon signed-rank test, returning a z-score of 4.038. This result therefore suggests that patients experience statistically significantly less pain from cataract surgery when given a subtenon block. Patients expressed a preference for subtenon anesthesia, with 70% preferring subtenon block, 23% preferring topical anesthesia, and 7% having no preference. CONCLUSIONS: Patients report less pain with subtenon anesthesia compared with topical anesthesia in cataract surgery, where both eyes were operated upon with different anesthetic techniques. This is the first study in which patients who have had both anesthetic techniques performed independently for cataract surgery have had their pain scores reported and statistically analyzed.
Assessment of Knowledge, Practice and Treatment Adherence of Patients with Hypothyroidism in Endocrinology Department

Assess the knowledge, practice, and treatment adherence of patients with hypothyroidism attending in endocrinology department in Chennai. The research design adopted for this study was descriptive. Using convenience sampling technique, a total of 120 patients both male and female who had diagnosed with hypothyroidism, Sri Ramachandra Hospital who met the inclusion criteria were recruited. The data related to background variables and assessment of knowledge, practice and treatment adherence on patients with hypothyroidism were obtained using questionnaires through interview method. The data were analyzed using descriptive and inferential statistics. The study findings showed that 61.7% of patients had moderately adequate level of knowledge on hypothyroidism, 76.7% of them had adequate level of practice and 49.2% of them had low adherence. The mean score of knowledge on hypothyroidism was 16.69, practice was 8.28, and treatment adherence was 2.09. The study showed that the knowledge, practice, and treatment adherence with hypothyroidism were moderately adequate among patients with hypothyroidism.
Exercise Prescription Practices to Improve Mental Health

Objective: There is growing evidence that higher levels of physical activity are associated with better mental health. Furthermore, interventional studies have shown that exercise may improve symptoms in a number of psychiatric conditions. Despite this evidence, relatively little information is available about how these findings have been translated into clinical practice. The goal of this study was to characterize the exercise prescribing practices of health care providers from different subspecialties and evaluate factors that may influence their prescribing practices. Methods: We conducted a cross-sectional survey among faculty and staff from a large academic tertiary care medical center in the southeastern United States. Participants were invited to complete the survey via email or departmental newsletters. Descriptive statistics were used to characterize the sample and ordered logistic regression was used to analyze practices about exercise as a therapy for psychiatric illness. Results: A total of 185 respondents completed the survey. More than half of the providers (58%) reported that they regularly recommend exercise as part of the treatment for patients with psychiatric conditions; however, few providers offered specific exercise instructions (24%) or followed national guidelines (30%). Depression (84.9%) and anxiety (69.2%) were the most common indications for exercise prescription, while insufficient knowledge or training was the most common barrier to prescribing exercise. We also found significant differences in prescription practices depending on the providers’ formal clinical degree and their reported personal exercise habits. Conclusions: Exercise is recognized by most clinicians as a therapeutic option for psychiatric conditions. Despite this recognition, only a small proportion provide recommendations consistent with national guidelines or empirical research.
Acid hydrolysis of glycosidic bonds in oat β‐glucan and development of a structured kinetic model

Homogeneous acid-catalyzed hydrolysis of oat β-glucan, which contains β-(1,4) and β-(1,3) glycosidic bonds in a nonrandom order, was studied at 353 K using HCl and H2SO4. A new structured kinetic model was developed that takes into account the difference in the reactivity of β-(1,4) and β-(1,3) glycosidic bonds as well as their positions in the polysaccharide chain. To minimize the correlation of adjustable parameters in the new model, the reactivities of these bonds were studied independently (T = 313…363 K; cH+ = 0.1…2 mol/L) using cellobiose and laminaribiose. The difference in kinetic parameters (e.g., T = 338 K: kβ-(1,4) = 0.693 × 10−3 L/mol/min, kβ-(1,3) = 1.027 × 10−3 L/mol/min) was found to be statistically significant (P < 0.0001), which emphasizes the need for the structured model for oat β-glucan hydrolysis. The simulation of β-glucan hydrolysis with the new model was in good agreement with the experimental data and shows improvement over existing nonstructured models. © 2018 American Institute of Chemical Engineers AIChE J, 2018
Pleurotus ostreatus cultivation medium and preparation method thereof

The invention relates to a Pleurotus ostreatus cultivation medium. The Pleurotus ostreatus cultivation medium is prepared through using the following raw materials, by weight, 40-50 parts of wheat straw, 20-30 parts of oat straw, 4-6 parts pear leaf powder, 5-6 parts of vinegar residue, 10-15 parts of expired bread, 8-10 parts of expired biscuit, 8-10 parts of bean dregs, 5-6 parts of cattle bone meal, 2-3 parts of quicklime, 0.3-0.4 parts of calcium carbonate, 1-2 parts of quicklime, 0.5-1.0 part of calcium superphosphate and 5-10 parts of a sustained-release nutritional particle. The Pleurotus ostreatus cultivation medium have the advantages of wide sources of the raw materials, increase of the healthcare efficacies of liver nourishing and eyesight improving of Pleurotus ostreatus cultivated through the medium, and low raw material cost.
Research on the Realization and Application of Intelligent IoT Platform for Electrical Equipment under Industrial Internet

In the context of the industrial Internet, the new generation of information technologies such as the cloud, large, and mobile smart areas are becoming more mature and widely used. Intelligent manufacturing leads the transformation of manufacturing methods. The new development concept represented by “modern smart supply chain” is also getting more and more attention. Therefore, building a smart supply chain has become a new research direction, and building a smart IoT platform for electrical equipment is conducive to building a modern smart supply chain system. The current research on the intelligent IoT platform for electrical equipment is mainly in the platform structure design and key technologies, and there is a lack of implementation and application research on the intelligent IoT platform for electrical equipment. Therefore, this article will conduct research from the realization and application status of the intelligent IoT platform for electrical equipment, the problems in the implementation process, the key technologies and solutions used to solve the problems, etc., to provide a good basis for the construction and application of the intelligent IoT platform for electrical equipment. Provide reference for development.
Convolve4D: A Novelty Approach to Improve Convolutional Process

Convolutional neural networks (ConvNet or CNN) are deep learning algorithms that can process input images, assign meaning to various aspects or objects in the image (biases and learnable weight) and recognize one image from another. The bigger kernel size will take more time to process the input.We present a novelty way to use a 4D rank tensor to improve a convolutional process. At the early stage of the Convolve4D development, the edge detection with 3×3 kernel and The Laplacian of Gaussian (LoG) with 5×5 kernel size was used to demonstrate the convolutional process improvement. The Convolve4D needs more elaboration to be used into a CNN algorithm. The advantage of convolve4D is only need 9 loops to calculate 81 outputs, whereas convolve2D need 9 × 9 × 3 × 1 × 7 × 7 = 11.907 loops. The result is 18.5% shorter when using a 5×5 kernel; it reduces from 0.54 seconds to 0.44 seconds for the edge detection convolution process.
Numerical study of the liquid sloshing in the cylindrical tank with baffles

Many kinds of dangerous chemicals, like liquefied natural gas etc., are stored or transported in liquid state by pressure vessel. Liquid sloshing will occur in many scenarios such as during the geological disasters, and the transit operations. Sloshing might lead to large deformation or even damage to containers, causing serious safety threats. In this study, the sloshing phenomenon in a cylindrical tank with four baffle shapes are investigated. The volume-of-fluid (VOF) method is used to track the distorted and broken free surface. Fluid movement phenomenon in tank with different baffles is observed. The effect of four different baffles shapes is compared, impacting force on tank and baffle walls which induced by liquid sloshing is analyzed. Baffles openings affect the impact forces on the tank and baffle walls. More number of baffle orifices, liquid distribution is more even in sections of the tank. Maximum force value of y direction occurs as the liquid climbs up the tank ceiling. Reasonable number and position of baffle openings can increase the stability of the tank during driving. For this simulation method, more validation with experimental data is necessary, the same size of tank and four baffle shapes will be tested on the shaking platform.
Analysis and innovation prospect of intelligent ship visual tracking and recognition system

In recent years, due to the rise of the concept of intelligent ship and the development of the intelligent ship, the ship intelligent has become a global shipping the trend of The Times, with the rapid development of maritime shipping industry, sea lanes and port ship intensity increasing, shipping safety risk increasingly improve, intelligent traffic regulation becomes increasingly important task, shipping information acquisition is more accurate. Ship tracking and identification system is not only the core of shipping safety supervision system, but also has an effective role in the collection of ship navigation information and intelligent supervision of navigation traffic. Computer vision is a technology developed rapidly in recent years, as the current research hotspot, with its access to large amount of information, and the advantages of fast response speed, strong anti-jamming capability compared with traditional of AIS and radar easily affected by obstacles, affected by the operator subjective behavior of communication system device, it can well realize the target ship recognition and tracking, to the modern channel intelligent regulation of ship sailing information collection, transportation, ship navigation safety are very important significance. This article mainly from the principle of development background significance, system characteristics, the visual technology, tracking algorithm for visual identification and tracking system to do a detailed description of principle, on the basis of AIS and radar, based on traditional visual algorithm combined with some data and AIS system on personal improvement ideas on the application of the system innovation, and finally puts forward personal has been developed out of a visual tracking innovative device of the ship.
Regression analysis and prediction using LSTM model and machine learning methods

In this paper, the LSTM model in deep learning is applied to regression analysis, and the LSTM model is used to solve the problems of nonlinearity and data interdependence in regression analysis, so as to improve the traditional regression analysis model. Through the actual modeling application experiment, on the one hand, the prediction accuracy of different model parameters is compared and analyzed, on the other hand, the effectiveness and practicability of LSTM model in multiple regression analysis and prediction are confirmed.
Research on artificial intelligence machine learning character recognition method based on Feature Fusion

In this paper, the artificial intelligence machine learning based on feature fusion is briefly introduced, and on this basis, the character recognition method based on artificial intelligence machine learning is studied from the perspective of character recognition system classifier and character recognition performance. The continuous development of artificial intelligence technology has made people more in-depth research on it. Machine learning has also become a new core research issue in artificial intelligence. It has been widely used in network search, language recognition, and machine vision. The emergence of artificial intelligence has brought great changes to people’s life and production mode, coupled with the development of science and technology and network technology, people have successfully entered the information age, and information technology is indispensable in all aspects of people’s life. With the progress of science and technology in the current era, artificial intelligence has developed very rapidly, and people’s research on machine learning has also made a breakthrough. Learning ability is an important intelligent behavior of human beings. Human beings can adjust their own actions through learning, so as to obtain strong environmental adaptability.
Numerical Investigation of the Inlet with Different Lip-plane Shapes under Ground Running

The inlet of the UAV is usually designed on the back of the aircraft in order to give consideration to the overall arrangement and stealth performance. Under ground running, there are often severe vortices in the duct of the backpack inlet, which leads to low total pressure recovery and large circumferential distortion index at the AIP. Different shapes of the lip-plane produce different vortices, which have great impact on circumferential distortion index at the AIP. In this paper, the characteristics of three different lip-plane shapes were studied under the ground running. Results indicate: (1) W-shaped inlet has lowest circumferential distortion index and the flow distribution is the most uniform at the AIP; (2) Λ-shaped inlet has the weakest of the vortex strength and the largest total pressure recovery, which means the thrust loss caused by the inlet is smallest; (3) V-shaped inlet has the strongest vortex strength and the lowest total pressure recovery.