Ready Times Research Articles

Pediatric Living Donor Liver Transplantation for Congenital Absence of the Portal Vein With Pulmonary Hypertension: A Case Report

Few reports of liver transplantation exist in patients with congenital absence of the portal vein and pulmonary hypertension. Living donor liver transplantation is usually performed before exacerbation of pulmonary hypertension. A 7-year-old girl (height: 131.5 cm; weight: 27.4 kg) with congenital absence of the portal vein was diagnosed with pulmonary hypertension (mean pulmonary artery pressure 35 mm Hg), and liver transplantation was planned before exacerbation of pulmonary hypertension. We successfully managed her hemodynamic parameters using low-dose dopamine and noradrenaline under monitoring of arterial blood pressure, central venous pressure, cardiac output, and stroke volume variation. Anesthesia was maintained using air-oxygen-sevoflurane and remifentanil 0.1 to 0.6 μg∙kg-1∙min-1. It is necessary to understand the potential perioperative complications in such cases and to adopt a multidisciplinary team approach in terms of the timing of transplantation and readiness to deal with exacerbation of pulmonary hypertension.

Postoperative hunger after outpatient surgery in patients anesthetized with propofol vs sevoflurane: a randomized-controlled trial.

Previous preclinical and preliminary clinical data suggest an appetite-stimulating effect of propofol compared with halogenated drugs. This study compared the effects of propofol with those of sevoflurane on recovery of hunger during the postoperative period. Patients undergoing outpatient transvaginal oocyte retrieval were randomized to propofol-remifentanil (propofol group) or sevoflurane-remifentanil (sevoflurane group) anesthesia. The primary endpoint was the time before feeling hungry (≥ 50/100 mm on a visual analogue scale). Secondary endpoints included plasma levels of ghrelin, leptin, and insulin (ten minutes, one hour, and two hours after anesthesia), caloric intake at first feed, and discharge readiness time. In the 58 patients allocated to either the propofol or sevoflurane group, there was no difference in the median [interquartile range] recovery time of hunger (97 [75-138] vs 97 [80-140] min, respectively; median difference, 1; 95% confidence interval [CI], - 15 to 14; P = 0.91); caloric intake (245 [200-343] vs 260 [171-314] kcal; P = 0.39); or discharge readiness time (125 [85-153] vs 125 [95-174] min, P = 0.29). The groups showed no difference in crude plasma levels of ghrelin, leptin, and insulin at any time-point. When peptide plasma levels were expressed as a % change from baseline, there was a higher insulin plasma level one hour after anesthesia in the sevoflurane group (median difference, 4.9%; 95% CI, - 16.2 to 43.4) compared with the propofol group (median difference, - 21.2%; 95% CI, - 35.7 to 9.1; adjusted P = 0.01). Propofol did not accelerate the recovery of hunger compared with sevoflurane after outpatient minor surgery. Moreover, propofol did not have distinguishable effects on other clinical or biological parameters associated with food intake. www.ClinicalTrials.gov (NCT02272166); registered 22 October, 2014.

The consecutive multiprocessor job scheduling problem

We study a variant of the multiprocessor job scheduling problem, where jobs are processed by several identical machines. The machines are ordered in a sequence, and each job is processed by several consecutive machines simultaneously. The jobs are characterized by their processing time, the number of required consecutive machines, and their ready time. The objective function is to minimize the sum of general functions defined over the completion time of each job. This study is motivated by a real problem in the semiconductor industry. We present a time-indexed integer programming and a constraint programming formulations for the problem and demonstrate their applicability through an extensive numerical study and an industrial case study.

Minimizing Makespan of Batch Processing Machine with Unequal Ready Times

Minimizing Makespan of Batch Processing Machine with Unequal Ready Times

Improving the Performance of the Prediction by Machine Learning Algorithms

in the course of latest a long term, system gaining knowledge of (ML) has superior from the task of barely any laptop devotees abusing the plausibility of desktops figuring out a way to play around, and a chunk of mathematics (facts) that superb occasionally belief to be computational methodologies, to a free research area that has now not just given the essential base to measurable computational requirements of studying systems, yet moreover has created wonderful calculations which can be generally carried out for content material material translation, layout acknowledgment, and a numerous excellent commercial enterprise features or has precipitated a simply one among a type studies eagerness for data removal to differentiate wearing a veil regularities or abnormality within group facts that developing via way of next. This thesis centers round clarifying the concept and development of device learning, a portion of the mainstream device gaining knowledge of calculations and attempt to reflect onconsideration on 3 most ordinary calculations relying on a few essential thoughts. Sentiment140 dataset turn out to be utilized and execution of each estimate concerning getting ready time, expectation time and precision of forecast had been archived and analyzed.

PERAN BALAI PENGELOLAAN HUTAN MANGROVE WILAYAH I BALI DALAM PENGOLAHAN HASIL HUTAN MANGROVE BERBASIS PEMBERDAYAAN MASYARAKAT LOKAL

Mangrove degradation is increasing along the proliferation of purposely land conversion. The utilization of the products of mangrove forests are oriented to the timber. Processing of mangrove products that have economic value should be a form of mangrove conservation and sustainability. Balai Pengelolaan Hutan Mangrove (BPHM) Wilayah 1 Bali, has become a center to processing mangrove forest products, especially non-timber products in Mangrove Tahura Ngurah Rai, which empowers local communities with skill training to process mangrove products into the economic value products. This research was carried out at the Mangrove Tahura Ngurah Rai. The method used is by observing mangroves by random sampling which will then be harvested based on the characteristics of ready harvest and harvest time. Mangroves that have been harvested, among others Sonneratia caseolaris, Bruguiera gymnorrizha, and Xylocharpus granatum. Those mangrove products will be processed into products such as syrup, soap, dodol, flour, rice, and scrubs. The processing of non-timber products is done through empowering local communities. The utilization of mangroves is more focused on the non-timber of forest products by utilizing mangrove fruits and leaves, ecotourism utilization, and silvofishery. BPHM I. Bali has an important role in maintaining the sustainability of the Mangrove Tahura Ngurah Rai.

Introducing Temperature-Controlled Phase Transition Elastin-like Polypeptides to Transient Electronics: Realization of Proactive Biotriggered Electronics with Local Transience.

Transient electronics have dramatically changed inner-body therapy in health care. They stand out because of their harmless dissolution in the human body with no lingering electronic trash. However, high-precision biomedical implants require programmable and serial remedy operations, and controlling the whole-device destruction is not proactive and precise. Thus, a novel biotriggered and temperature-controlled transient electronics fabrication method using elastin-like polypeptides (ELPs) as triggers is proposed. Biocompatible ELPs simply mixed with trace silver nanowire (AgNW) can serve as the "switch" for the electronics to respond to local temperature changes in deionized water, exhibiting an agile response time. A ratio gradient experiment of the ELPs and AgNW shows that more programmable and precise transience properties (initial resistance, ready time, response time, and stable resistance) can be achieved by using a designated proportion. Further, we validated that the 3D-printing-based ELP-triggering transient electronics fabrication method is very simple yet effective for preparing transient wireless charging LEDs. Transient devices comprising ELPs-AgNW and PLGA-Ag respond within 160 s below 10 °C and degrade within a certain period.

Selecting algorithms for large berth allocation problems

This paper considers algorithm selection for the berth allocation problem (BAP) under algorithm runtime limits. BAP consists in scheduling ships on berths subject to ship ready times and size constraints, for a certain objective function. For the purposes of strategic port capacity planning, BAP must be solved many times in extensive simulations, needed to account for ship traffic and handling times uncertainties, and alternative terminal designs. The algorithm selection problem (ASP) consists in selecting algorithms with the best performance for a considered application. We propose a new method of selecting a portfolio of algorithms that will solve the considered BAP instances and return good solutions. The portfolio selection is based on the performance on the training instances. The performance is measured by the runtime and solution quality. In order to select the portfolio, a linear program minimizing the solution quality loss, subject to overall runtime limit is used. Thus, the portfolio evolves with the runtime limit, which is a key parameter in designing the port capacity simulations. For the training and validating datasets, random instances and real ship traffic logs are used. A portfolio of heuristics is developed which can be used for solving large instances of BAP, emerging when time horizons of months or years are considered. The evolution of the algorithm portfolios under changing runtime limits is studied. The portfolio abilities to solve new instances are assessed.

Assessment of the Time for Vessel's Readiness to Sail in Ice Conditions

It is shown that the preparation of the exploration for the swimming management of the ice and the process of such impact should be carried out with the external supply of demand of the company, the captain of the merchant and the crew on the information, leaving allowing the convenience of operating the external with due The level of related safety element of the ves-sel's degree of and so is the procurement and cargo of it on board, with the associated enforced element of protection to link the environment. The task of assessing the readiness of the vessel for safe navigation in ice conditions under the operating or restored elements of the ship's tech-nical equipment by the method of replacing with back-up elements is considered and an analyt-ical expression is proposed technical and ship readiness for safe ice sailing, taking into account the structure of the maintenance complex, reliability and reliability of the monitoring results. It is shown that the proposed procedure to assess readiness.

Does intravenous acetaminophen reduce perioperative opioid use in pediatric tonsillectomy?

Postoperative pain control is of significant interest in pediatric otolaryngology given the safety concerns with opioid use. We sought to determine if addition of intraoperative intravenous acetaminophen decreases perioperative morphine use in pediatric tonsillectomy. This study is a retrospective cohort study performed at a tertiary care academic children's hospital. 166 pediatric patients (aged 1-16 years) who underwent tonsillectomy with or without adenoidectomy were for review. Seventy-four patients received intraoperative intravenous acetaminophen (intervention cohort), while ninety-two patients served as our control and did not receive any intraoperative intravenous acetaminophen. Perioperative (intraoperative and postoperative) morphine use was our primary outcome measure. Rate of adverse events in the post anesthesia care unit and time for discharge readiness were secondary outcome measures. Wilcoxon two-sample t-test approximation and Fisher's exact test were used for data analyses. Patients in the intravenous acetaminophen cohort received less morphine (mg/kg) intraoperatively (0.058 versus 0.070, p = 0.089) and in the post anesthesia care unit (0.034 versus 0.051, p = 0.034) than the control cohort. The median time to discharge readiness for the intravenous acetaminophen and control groups was 108.5 versus 105 min (p = 0.018). There was no adverse respiratory event (oxygen desaturation <92% lasting more than a minute, requiring bag mask ventilation or reintubation) in either group in the post anesthesia care unit. There were 5 (7%) episodes of postoperative vomiting in the IV APAP, while 2 (2%) were recorded in the control cohort (p = 0.244). Our findings suggest intraoperative intravenous acetaminophen use in pediatric tonsillectomy can decrease the perioperative use of opioid for optimal pain management.

A bi-objective model for a scheduling problem of unrelated parallel batch processing machines with fuzzy parameters by two fuzzy multi-objective meta-heuristics

This paper considers a bi-objective model for a scheduling problem of unrelated parallel batch processing machines to minimize the makespan and maximum tardiness, simultaneously. Each job has a specific size and the data corresponding to its ready time, due date and processing time-dependent machine are uncertain and determined by trapezoidal fuzzy numbers. Each machine has a specific capacity, in which the number of jobs assigned to each batch on the machine does not violate the machine capacity. The batch processing time, the batch ready time and the batch due date are presented by the longest processing time, the longest ready time and the shortest due date of the jobs that belong to the batch, respectively. To determine the longest and shortest time, the method suggested by Jimenez et al.cite{c18} is used for ranking the fuzzy numbers. A bi-objective fuzzy mixed-integer linear programming model is proposed and solved by two exact methods (i.e., two-phase fuzzy and $epsilon$-constraint) for small-sized problems to obtain a set of Pareto solutions. Because the problem belongs to the class NP-hard, two meta-heuristics, namely fuzzy non-dominated sorting genetic algorithm (FNSGA-II) and fuzzy multi-objective discrete teaching–learning-based optimization (FMODTLBO), are proposed. Then, the comparison of results is illustrated to show their performances. Furthermore, a new representation of the solutions is a matrix with two rows and $N$ columns (i.e., jobs) used to assign the jobs to the batches that processed on the machines.

PENENTUAN KOMPONEN KRITIS UNTUK MENGOPTIMALKAN KEANDALAN MESIN CETAK

Equipment maintenance activities are very important in the operation of a system or equipment in the industry. With the maintenance strategy and methods that can affect the occurrence of damage resulting in equipment can operate in the long term. The methods used are Reliability Centered Maintenance (RCM) data required are working hours data, corrective time data, Supply Delay Time (SDT) and Administrative Delay Time (ADT) data, and prevetive maintenance data. To determine whether the data obtained suadah match, then used the exponential distribution, from the form of the data then it can be found treatment. From the exponential distribution will get the value of cumulative function, machine reliability, Maen Time Batwen Failure (MTBF), Mean Time Battery Maintenance (MTBM), machine readiness time (availability) for each machine. There are two critical components: laker / bearing and felt print. From the data processing obtained reliability of printing machine unit 1 99.9%, machine unit 2 92.52%, unit 3 91.85% machine. for that we need preventive maintenance. In addition to the reliability also obtained MTBM as a schedule of preventive maintenance on mesn print unit 1 66.105, unit 2 93.037 machine, machine unit 3 106,893 hours once.Keywords: Reliability, RCM, Preventive Maintenance

A Model-Free Affective Reinforcement Learning Approach to Personalization of an Autonomous Social Robot Companion for Early Literacy Education

Personalized education technologies capable of delivering adaptive interventions could play an important role in addressing the needs of diverse young learners at a critical time of school readiness. We present an innovative personalized social robot learning companion system that utilizes children’s verbal and nonverbal affective cues to modulate their engagement and maximize their long-term learning gains. We propose an affective reinforcement learning approach to train a personalized policy for each student during an educational activity where a child and a robot tell stories to each other. Using the personalized policy, the robot selects stories that are optimized for each child’s engagement and linguistic skill progression. We recruited 67 bilingual and English language learners between the ages of 4–6 years old to participate in a between-subjects study to evaluate our system. Over a three-month deployment in schools, a unique storytelling policy was trained to deliver a personalized story curriculum for each child in the Personalized group. We compared their engagement and learning outcomes to a Non-personalized group with a fixed curriculum robot, and a baseline group that had no robot intervention. In the Personalization condition, our results show that the affective policy successfully personalized to each child to boost their engagement and outcomes with respect to learning and retaining more target words as well as using more target syntax structures as compared to children in the other groups.

PENYELENGGARAAN PERIZINAN DAN NON PERIZINAN DI KABUPATEN BEKASI

The problem of this research is explore licensing dan non-licecensing policy services in Bekasi Regency. That must be carried out properly to the community. but in practice, the implementation of licensing in Bekasi Regency is still not going well, this condition actually keeps the concept of licensing away from the ideal concept, standard rules regarding the institution and authority of the Investment Agency and One Stop Integrated Service which are not yet clear have triggered various problems in the permit processing process. existing businesses in Bekasi Regency. The researcher conducted an in-depth analysis using a qualitative descriptive analysis method where the results of this study concluded that efforts to improve and improve licensing and non-licensing services in Bekasi Regency were divided based on several series of priority choices. Determination of priority options based on parameters of depth of resolution efforts, length of time for problem handling and readiness of human resources executing policies, programs and government activities in Bekasi Regency. Errors in the interpretation of national regulations related to licensing and non-licensing policies will result in the unclear function of permits. The same function is regulated in different regulations so that it is over regulated. It is necessary to improve the licensing and non-licensing policies, where based on the results of this study there are still many permits that were born because of the discretion of the regional government, or were born in the daily practice of governing.&#x0D; Keywords: Licensing, Non-Licensing, Bekasi Regency

Resonator to Laser Cavity Decoupling Interface for Chemical Oxygen Iodine Laser

In the present work, the conventional chemical oxygen iodine laser (COIL) source has been technologically upgraded and successfully tested after implementation of decoupling interface between laser cavity and resonator. In the technique, anti-reflection coated fused silica windows mounted in suitable mechanical assemblies are placed between resonator mirrors and laser cavity in such a way that the generated laser beam is out coupled through the resonator during the laser operation. The implemented decoupling assemblies isolate the caustic environment produced in low pressure laser cavity from that of resonator mirrors. Thus requirement of using isolation valves and cavity limbs between laser cavity and resonator as in conventional COIL source is eliminated. Such decoupling mechanism therefore effectively reduces the number of associated components as well as overall length of the laser source which in turn further reduces the overall weight of the laser making it suitable for use onto a mobile platform. Moreover the technique provides accrued benefits in terms of reduction in readiness time and checking of optical alignment of the laser source at will in practical operation scenarios.

Disease Prediction by Machine Learning from Healthcare Communities

To promote sustainable improvement, the smart town implies a global imaginative and prescient that merges artificial intelligence, choice making, statistics and conversation era (ICT), and the net-of-things (IoT). in this mission, the subject of disease prediction and prognosis in clever healthcare is reviewed. due to records progress in biomedical and healthcare groups, correct have a look at of clinical data advantages early disorder recognition, patient care and network services. whilst the exceptional of medical information is incomplete the exactness of study is reduced. moreover, exclusive areas exhibit specific appearances of certain regional illnesses, which can also bring about weakening the prediction of sickness outbreaks. within the proposed system, it offers gadget gaining knowledge of algorithms for effective prediction of various disorder occurrences in ailment-frequent societies and predicts the waiting time for each treatment project for every patient as well as a hospital Queuing advice (HQR) system is advanced for recommending treatment mission sequence with appreciate to anticipated ready time. It experiments on a nearby chronic illness of cerebral infarction. using structured and unstructured facts from health centre it makes use of system studying selection Tree algorithm and KNN algorithm. To the first-rate of our knowledge inside the place of medical huge records analytics none of the existing paintings focused on each information types. in comparison to several normal estimate algorithms, the calculation exactness of our proposed set of rules reaches 94.8% with a convergence speed which is faster than that of the CNN-based totally uni-modal ailment threat prediction (CNN-UDRP) algorithm. similarly, challenges within the deployment of sickness diagnosis in healthcare had been mentioned.

Binary Linear Programming Model in Solving Bus Crew Problem as Tactical Fixed Task Scheduling

In this paper, we consider a crew scheduling problem (CSP) of bus transportation with the objective of minimizing the cost of crew members. We address a different time frame and different type of crew members. The maximum total working limit for each type of crew member has been set. The problem can be formulated as a Tactical Fixed Task Scheduling Problem (TFTSP) where the ready time and due date of the tasks are fixed in advance. A Binary Linear Programming (BLP) model is used to obtain an optimal solution for the problem. We conduct a testing and implement the model using LINGO 17.0 software. Results of the computational testing give optimum values for the problem. Hence, a feasible crew scheduling is obtained.

‘Off pump’ self-expanding injectable tissue valves (IPVR) versus ‘on pump’ conventional tissue valves (PVR) for replacement of the pulmonary valve: trial protocol for a randomised controlled trial (InVITe trial)

IntroductionPatients with congenital heart disease often need repeated operations throughout life to replace the pulmonary valve. Valve replacement with ‘injectable’ self-expanding valves (which is performed ‘off pump’ without the use...

A Novel Multi-Objective Scheduling Method for Energy Based Unrelated Parallel Machines With Auxiliary Resource Constraints

The environmental and economic pressures caused by energy consumption have led to an increased consciousness of energy-saving in the manufacturing industry. To this end, this paper focuses on an unrelated parallel machine problem with multiple auxiliary resources, which is a typical configuration in the lithography process of wafer fabrication. By comprehensively considering the jobs with different processing demands, setup times, ready times, resource constraints and energy consumptions, a scheduling model with the objective functions of minimizing the total energy consumption of the system and the total weighted completion time is developed. Based on the mathematical model, a novel modified multi-objective artificial immune algorithm integrated with the non-domination sorting strategy is proposed to solve the problem. Furthermore, to improve the performance of the proposed algorithm, clone operators, neighborhood search operators, and elite preservation operators are applied to the algorithm. The experimental results and analysis validate that the presented algorithm is efficient and effective.

Performance of a Nonelectric Infant Warmer in Rwandan Health Centers.

Background. Neonatal hypothermia remains a challenge in resource-limited settings. Methods. We conducted a prospective mixed-methods cohort study in rural Rwandan health centers to assess the performance of an infant warmer we designed for low-resource settings. All hypothermic infants were eligible for enrollment. Outcomes. Safety: incidence of adverse reactions. Effectiveness: attainment of euthermia, rate of temperature rise. Feasibility: correct use of warmer, signs of wear. Interviews of caregivers and nurses. Findings. Of 102 encounters, there were no adverse reactions. Of 80 encounters for hypothermia when infants on warmer for ≥1 hour, 79 achieved euthermia; 73 in ≤2 hours. Of the 80 encounters, 64 had temperature rise ≥0.5°C/h. Of the 102 encounters, there were no instances of the warmer being prepared, used, or cleaned incorrectly. Five out of the 12 warmers exhibited wear. Interview participants were predominantly positive; some found time for readiness of warmer challenging. Interpretation. The warmer performed well. It is appropriate to study in larger scale.