Symptoms Based Image Predictive Analysis for Citrus Orchards Using Machine Learning Techniques: A Review

In Agriculture, orchards are the deciding factor in the country’s economy. There are many orchards, and citrus and sugarcane will cover 60 percent of them. These citrus orchards satisfy the necessity of citrus fruits and citrus products, and these citrus fruits contain more vitamin C. The citrus orchards have had some problems generating good yields and quality products. Pathogenic diseases, pests, and water shortages are the three main problems that plants face. Farmers can find these problems early on with the support of machine learning and deep learning, which may also change how they feel about technology.  By doing this in agriculture, the farmers can cut off the major issues of yield and quality losses. This review gives enormous methods for identifying and classifying plant pathogens, pests, and water stresses using image-based work. In this review, the researchers present detailed information about citrus pathogens, pests, and water deficits. Methods and techniques that are currently available will be used to validate the problem. These will include pre-processing for intensification, segmentation, feature extraction, and selection processes, machine learning-based classifiers, and deep learning models. In this work, researchers thoroughly examine and outline the various research opportunities in the field. This review provides a comprehensive analysis of citrus plants and orchards; Researchers used a systematic review to ensure comprehensive coverage of this topic

Anti-Obesity Effect of Rhizophora Mucronata-A True Mangrove

The present study aimed to investigate the effects of Methanolic extract of Rhizophora mucronata (MERM) on phytochemical studies and body weight, behaviour, organ weight, serum biochemical parameters in obese mice. The preliminary phytochemical analysis of MERM revealed the presence of protein, phenols, flavonoids, saponins, glycosides, terpenoids and tannins. Six groups of male Wistar albino mice were used. Group I was negative control and the other 4 groups were fed on progesterone for 6 weeks to induce obesity. Group II was kept obese (positive control) and the other 3 groups were orally given MERM at 100, 200 and 400 mg/kg/day, respectively, for 4 weeks. Group VI were orally given by standard drug Sibutramine 10 mg/kg. Blood samples were collected for biochemical analyses. Oral dosage of MERM to obese mice significantly reduced food intake, body weight, organ weight and decreased serum levels of aspartate amino transferase (AST), alanine amino transferase (ALT), gamma-glutamyl transpeptidase (GGT) enzymes, total cholesterol (TC), triglycerides (TG), and low density lipoproteins (LDL-c) and improved atherogenic index. Blood glucose, insulin and leptin hormone decreased by administration of MERM.Keywords: Rhizophora mucronata, Obesity, Wistar albino mice, Phytochemical analaysis, Biochemical analysi

DuraSeal Exact is a safe adjunctive treatment for durotomy in spine: Postapproval study

Study designA nonrandomized, two-armed prospective study.ObjectiveWater-tight dural closure is paramount to the prevention of cerebrospinal fluid (CSF) leakage and associated complications. Synthetic polyethylene glycol (PEG) hydrogel has been used as an adjunct to sutured dural repair; however, its expansion postoperatively is a concern for neurological complications. A low-swell formulation of PEG sealant was introduced as DuraSeal Exact Spine Sealant System (DESS). A Post-Approval Study was performed primarily to evaluate the safety and efficacy of DESS for spinal dural repair compared to current alternatives, in a large patient population, reflecting a real-world practice.MethodsA total of 36 sites in the United States enrolled 429 patients treated with DESS as an adjunct to dural repair in the spinal sealant group and 406 patients treated with all other modalities in the control arm, from October 2011 to June 2016. The primary endpoint was the incidence of CSF leak within 90 days of operation. The secondary endpoints evaluated were deep surgical site infection and neurological serious adverse events.ResultsThe CSF leakage in the DESS group (6.6%) was not significantly different from the control group (6.5%) (p = .83), and there was no significant difference in the time to first leak. The two groups had no significant differences in deep surgical site infection (1.6% versus control 2.1%, p = .61) or proportion of subjects with neurological serious adverse events (2.9% versus control 1.6%, p = .516).ConclusionsDuraSeal Exact Spinal Sealant is safe when compared to current alternatives for spinal dural repair

Energetics Based Spike Generation of a Single Neuron: Simulation Results and Analysis

Existing current based models that capture spike activity, though useful in studying information processing capabilities of neurons, fail to throw light on their internal functioning. It is imperative to develop a model that captures the spike train of a neuron as a function of its intracellular parameters for non-invasive diagnosis of diseased neurons. This is the first ever article to present such an integrated model that quantifies the inter-dependency between spike activity and intracellular energetics. The generated spike trains from our integrated model will throw greater light on the intracellular energetics than existing current models. Now, an abnormality in the spike of a diseased neuron can be linked and hence effectively analyzed at the energetics level. The spectral analysis of the generated spike trains in a time–frequency domain will help identify abnormalities in the internals of a neuron. As a case study, the parameters of our model are tuned for Alzheimer’s disease and its resultant spike trains are studied and presented. This massive initiative ultimately aims to encompass the entire molecular signaling pathways of the neuronal bioenergetics linking it to the voltage spike initiation and propagation; due to the lack of experimental data quantifying the inter dependencies among the parameters, the model at this stage adopts a particular level of functionality and is shown as an approach to study and perform disease modeling at the spike train and the mitochondrial bioenergetics level

Predicting Academic Performance: A Systematic Literature Review

The ability to predict student performance in a course or program creates opportunities to improve educational outcomes. With effective performance prediction approaches, instructors can allocate resources and instruction more accurately. Research in this area seeks to identify features that can be used to make predictions, to identify algorithms that can improve predictions, and to quantify aspects of student performance. Moreover, research in predicting student performance seeks to determine interrelated features and to identify the underlying reasons why certain features work better than others. This working group report presents a systematic literature review of work in the area of predicting student performance. Our analysis shows a clearly increasing amount of research in this area, as well as an increasing variety of techniques used. At the same time, the review uncovered a number of issues with research quality that drives a need for the community to provide more detailed reporting of methods and results and to increase efforts to validate and replicate work.Peer reviewe

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Omecamtiv mecarbil in chronic heart failure with reduced ejection fraction, GALACTIC‐HF: baseline characteristics and comparison with contemporary clinical trials

Aims: The safety and efficacy of the novel selective cardiac myosin activator, omecamtiv mecarbil, in patients with heart failure with reduced ejection fraction (HFrEF) is tested in the Global Approach to Lowering Adverse Cardiac outcomes Through Improving Contractility in Heart Failure (GALACTIC‐HF) trial. Here we describe the baseline characteristics of participants in GALACTIC‐HF and how these compare with other contemporary trials. Methods and Results: Adults with established HFrEF, New York Heart Association functional class (NYHA) ≥ II, EF ≤35%, elevated natriuretic peptides and either current hospitalization for HF or history of hospitalization/ emergency department visit for HF within a year were randomized to either placebo or omecamtiv mecarbil (pharmacokinetic‐guided dosing: 25, 37.5 or 50 mg bid). 8256 patients [male (79%), non‐white (22%), mean age 65 years] were enrolled with a mean EF 27%, ischemic etiology in 54%, NYHA II 53% and III/IV 47%, and median NT‐proBNP 1971 pg/mL. HF therapies at baseline were among the most effectively employed in contemporary HF trials. GALACTIC‐HF randomized patients representative of recent HF registries and trials with substantial numbers of patients also having characteristics understudied in previous trials including more from North America (n = 1386), enrolled as inpatients (n = 2084), systolic blood pressure < 100 mmHg (n = 1127), estimated glomerular filtration rate < 30 mL/min/1.73 m2 (n = 528), and treated with sacubitril‐valsartan at baseline (n = 1594). Conclusions: GALACTIC‐HF enrolled a well‐treated, high‐risk population from both inpatient and outpatient settings, which will provide a definitive evaluation of the efficacy and safety of this novel therapy, as well as informing its potential future implementation

High-level timing and power analysis of embedded systems

Timing and power are two metrics that have become increasingly important to system level designers especially with the advent of the system-on-a-chip era. This dissertation combines the analyses of timing and power for system level designs and enables complex timing-power tradeoffs at the. system level itself. It allows system designers to identify subsystems that are timing critical and power critical.Timing plays an important role in the design of embedded real-time systems. Unfortunately, the process of designing a temporally correct system is a difficult one. The current practice is based on trial and error, guided by engineering experience and therefore is rather ad-hoc. Moreover, the emphasis is usually on designing a functionally correct system first, leaving the temporal correctness to be checked after the system's components are integrated. This usually results in expensive redesign iterations in order to satisfy temporal constraints. In this dissertation, we extend the generalized task graph model proposed for timing models at the system level to include a timing model of communication between nodes (tasks) of the task graph model. We also extend the timing analysis tool, RADHA-RATAN, to identify timing critical subsystems and generate a process timing model for the behavior of the system. This allows designers to simulate the timng behavior of the system with a minimal description of the system's functionality.Most of the previous work on system level power management are based on experimental observations and heuristics. In this dissertation, we propose techniques that enable the designer to identify power critical subsystems and develop effective power management strategies for them. These strategies are based on shutting down the system after a specific period of time. This dissertation shows that power management techniques for real-time embedded systems can be modeled as on-line problems and examines their efficiency using a formal technique called competitive analysis. We classify algorithms for power management as either adaptive or non-adaptive and analyze their effects on system latency and resources needed to implement them. The results of this dissertation can be used to design effective power management strategies for embedded systems that trade-off system latency, resources and power dissipation

The Problem of Renting versus Buying

The problem studied here is a member of a large class of on-line decision problems. The basic question is to choose from two possible alternatives at a given instance, for the use of an item. This choice is based solely on previous experience. One alternative di#ers the permanent acquisition of the item #rents it# and has a small recurring #xed cost #rent# associated with its use. The other choice secures the item #buys it#, but has a larger, though one time, cost #purchase price# associated with it. The item is used regularly. The choices have to be made to minimize the total cost of the item. As an example, we describe the car rental problem