Total Collection Time Research Articles

Blockchain-Enabled Infection Sample Collection System Using Two-Echelon Drone-Assisted Mechanism

The collection and transportation of samples are crucial steps in stopping the initial spread of infectious diseases. This process demands high levels of safety and timeliness. The rapid advancement of technologies such as the Internet of Things (IoT) and blockchain offers a viable solution to this challenge. To this end, we propose a Blockchain-enabled Infection Sample Collection system (BISC) consisting of a two-echelon drone-assisted mechanism. The system utilizes collector drones to gather samples from user points and transport them to designated transit points, while deliverer drones convey the packaged samples from transit points to testing centers. We formulate the described problem as a Two-Echelon Heterogeneous Drone Routing Problem with Transit point Synchronization (2E-HDRP-TS). To obtain near-optimal solutions to 2E-HDRP-TS, we introduce a multi-objective Adaptive Large Neighborhood Search algorithm for Drone Routing (ALNS-RD). The algorithm’s multi-objective functions are designed to minimize the total collection time of infection samples and the exposure index. In addition to traditional search operators, ALNS-RD incorporates two new search operators based on flight distance and exposure index to enhance solution efficiency and safety. Through a comparison with benchmark algorithms such as NSGA-II and MOLNS, the effectiveness and efficiency of the proposed ALNS-RD algorithm are validated, demonstrating its superior performance across all five instances with diverse complexity levels.

Optimal heap limits for reducing browser memory use

Garbage-collected language runtimes carefully tune heap limits to reduce garbage collection time and memory usage. However, there's a trade-off: a lower heap limit reduces memory use but increases garbage collection time. Classic methods for setting heap limits include manually tuned heap limits and multiple-of-live-size rules of thumb, but it is not clear when one rule is better than another or how to compare them. We address this problem with a new framework where heap limits are set for multiple heaps at once. Our key insight is that every heap limit rule induces a particular allocation of memory across multiple processes, and this allocation can be sub-optimal. We use our framework to derive an optimal "square-root" heap limit rule, which minimizes total memory usage for any amount of total garbage collection time. Paradoxically, the square-root heap limit rule achieves this coordination without communication: it allocates memory optimally across multiple heaps without requiring any communication between those heaps. To demonstrate that this heap limit rule is effective, we prototype it for V8, the JavaScript runtime used in Google Chrome, Microsoft Edge, and other browsers, as well as in server-side frameworks like node.js and Deno. On real-world web pages, our prototype achieves reductions of approximately 16.0% of memory usage while keeping garbage collection time constant. On memory-intensive benchmarks, reductions of up to 30.0% of garbage collection time are possible with no change in total memory usage.

OPTIMIZING THE INTERNAL CELL STRUCTURE OF THE RADON MONITOR BASED ON ELECTROSTATIC COLLECTION METHOD.

As Rn-222 decays, an alpha particle is emitted and the residual polonium nucleus recoils in the opposite direction. At the end of the recoil path, 88% of the polonium atoms have a positive charge and 12% are neutral. The electric potential distribution in the 60ml hemispherical internal cell of the radon monitor based on electrostatic collection is studied for reducing the combined probability of the positively charged Po-218 and the OH- produced by the ionization of water vapour in the air. The COMSOL software is used to simulate the electric potential distribution in the internal cell of the radon monitor based on the electrostatic collection method at 27°C, a pressure of 0.1 Mpa. For improving the collection efficiency of Po-218 ions, the average collection time along vertical and oblique lines is calculated when the upper surface of the internal cell is plastic, uncharged metal and charged metal, respectively. Assuming that the gas in the internal cell is uniformly distributed, the results show that if the upper surface of the hemispherical internal cell is plastic or uncharged metal, the electric potential formed in the internal cell is more uniform, and it is beneficial to reduce the total collection time of the positively charged Po-218 ions, thereby improving collection efficiency. The simulation results can be used as an effective reference for optimizing the design of the internal cell structure of the radon monitor based on electrostatic collection method.

An integrated framework for temporary disaster debris management sites selection and debris collection logistics planning using geographic information systems and agent-based modeling

Effective temporary debris management sites (TDMS) planning requires the consideration of its subsequent impact on debris collection logistics. This study establishes an integrated framework to determine the optimal locations for TDMSs that meet geographic requirements while minimizing the social and economic impacts imposed on the community due to uncollected debris. A geographic information system (GIS) was used to locate candidate TDMSs based on geographic parameters set forth by governing agencies. To consider the subsequent impact of TDMSs on debris collection, an agent-based model was constructed to evaluate post-disaster debris removal performance with varying TDMSs planning scenarios. Using the AnyLogic Optimization engine, the selection of TDMSs locations was optimized to minimize both overall debris collection time and subsequent negative impacts of uncollected debris on the public. The validity of the proposed framework was demonstrated through its application for determining optimal TDMSs locations in Liberty County, Florida, in response to Hurricane Michael where vegetative debris (i.e., potential fire hazards) and the debris within the urban areas are prioritized for collection. Compared to the actual debris collection time, the selected near-optimal TDMS locations resulted in a decrease in the total debris collection time from 156 to 112 days, with vegetative debris and debris located within the urban areas being collected within 60 and 70 days, respectively. The proposed framework will enable planners to (i) evaluate different TDMS planning scenarios in order to inform debris resource planning and management and (ii) prioritize the collection of specific types of debris based on their emergency/recovery preferences.

A multi-objective location inventory routing problem with pricing decisions in a sustainable waste management system

This paper presents a multi-objective optimization model for a sustainable municipal solid waste management system, emphasizing recycling and waste-to-energy technologies. The objective functions attempt to minimize total net cost, greenhouse gas emissions, and total waste collection and treatment time. The social aspect of the system is controlled by assessing the social performance of waste treatment technologies. The novel feature of this study is incorporating pricing decisions into the traditional location-allocation-routing-inventory waste management problems. The model is implemented on a case study in the southeast part of Tehran and is solved using the Lexicographic and AUGMECON2 approaches. Comparing the results of these methods indicates that considering all three objective functions as equally important leads to 21.5% more costs and 27% less environmental effects, comparing when minimizing costs is the priority. Moreover, results suggest establishing a landfill with gas recovery, material recovery facility, and composting plant with capacities of 700, 500, and 1170 tons/day. The model's outcomes suggest considering a minimum social performance score between 1.5 and 2.5 for the system under study regarding the impact of social performance on the objective functions

Estimating Time Spent at the Waste Collection Point by A Garbage Truck with A Multiple Regression Model

The planning of the garbage trucks’ routes is an essential process in waste collection companies. The main issues in garbage truck routing are determining the optimal routes, minimizing time, decreasing the costs, and reducing the pollution’s emission. In the literature, the time spent at a waste collection point (WCP) is considered as the average time, or it is not included at all. Time spent at a WCP is determined by the processes of picking up, emptying, and putting down the waste containers and the factors specific for different WCPs. Those factors impact the time spent at WCP significantly. Excluding time spent at a WCP or taking the average of that in the planning approach may lead to the inaccurate estimation of total collection time. The aim of this article is to present the multiple regression model for estimating time spent at a WCP. We analyzed the impact of the WCP factors (i.e., building type and number of containers) on the time that a garbage truck spends at it. We initially considered seven chosen factors, five categorical and two numerical. Based on this, we developed the multiple regression model based on linear regression use. Later, the proposed model was validated based on data obtained from the municipal company operating in Wroclaw city, Poland. The study confirmed that the defined factors significantly affect garbage truck’s time spent at a WCP and should be taken into account during waste collection planning processes’ performance.

Instrumentation and experimental procedures for robust collection of X-ray diffraction data from protein crystals across physiological temperatures.

Traditional X-ray diffraction data collected at cryo-temperatures have delivered invaluable insights into the three-dimensional structures of proteins, providing the backbone of structure-function studies. While cryo-cooling mitigates radiation damage, cryo-temperatures can alter protein conformational ensembles and solvent structure. Furthermore, conformational ensembles underlie protein function and energetics, and recent advances in room-temperature X-ray crystallography have delivered conformational heterogeneity information that can be directly related to biological function. Given this capability, the next challenge is to develop a robust and broadly applicable method to collect single-crystal X-ray diffraction data at and above room temperature. This challenge is addressed herein. The approach described provides complete diffraction data sets with total collection times as short as ∼5 s from single protein crystals, dramatically increasing the quantity of data that can be collected within allocated synchrotron beam time. Its applicability was demonstrated by collecting 1.09-1.54 Å resolution data over a temperature range of 293-363 K for proteinase K, thaumatin and lysozyme crystals at BL14-1 at the Stanford Synchrotron Radiation Lightsource. The analyses presented here indicate that the diffraction data are of high quality and do not suffer from excessive dehydration or radiation damage.

GRASP with Variable Neighborhood Descent for the online order batching problem

The Online Order Batching Problem (OOBP) is a variant of the well-known Order Batching Problem (OBP). As in the OBP, the goal of this problem is to collect all the orders that arrive at a warehouse, following an order batching picking policy, while minimizing a particular objective function. Therefore, orders are grouped in batches, of a maximum predefined capacity, before being collected. Each batch is assigned to a single picker, who collects all the orders within the batch in a single route. Unlike the OBP, this variant presents the peculiarity that the orders considered in each instance are not fully available in the warehouse at the beginning of the day, but they can arrive at the system once the picking process has already begun. Then, batches have to be dynamically updated and, as a consequence, routes must too. In this paper, the maximum turnover time (maximum time that an order remains in the warehouse) and the maximum completion time (total collecting time of all orders received in the warehouse) are minimized. To that aim, we propose an algorithm based in the combination of a Greedy Randomized Adaptive Search Procedure and a Variable Neighborhood Descent. The best variant of our method has been tested over a large set of instances and it has been favorably compared with the best previous approach in the state of the art.

Simultaneous determination of the partial vapor pressures for a binary mixture of ferrocene and benzoic acid using UV/Vis absorbance spectroscopy

Determining the vapor pressure of the individual components within a mixture is extremely challenging. Herein, a commercial UV/Vis absorbance spectrometer is used for the direct and simultaneous determination of the vapor pressures and the enthalpies of sublimation of a binary mixture of benzoic acid and ferrocene. In accordance with the Beer–Lambert law, the total absorbance in a series of overlapping isothermal absorbance spectra, in the temperature range of 323.15–373.15 K, is related to the number of vapor molecules at each temperature relative to their predetermined absorbance cross sections. Each component is assumed to behave as an ideal gas whose partial pressure contributions are approximated from Dalton’s law of partial pressures. All results for the vapor pressures and enthalpies are in good agreement (< 5%) with their respective literature values. Furthermore, the methodology presented allows for a significant reduction in the total experimental collection times relative to other standard techniques as well as being mostly independent of errors associated with sample purity.

Measurement of low concentrations of NO2 gas by differential optical absorption spectroscopy method

The availability of inexpensive light emitting diodes (LEDs) makes them an excellent source of light in active Differential Optical Absorption Spectroscopy (DOAS) to measure and monitor trace toxic gases. In this paper, we report the experimental details and outcomes of a new setup developed to detect low concentrations of toxic NO2 gas based on active DOAS with a white light emitting diode employed as the light source. A detection limit of 0.2 part per million (0.4 mg/m3) is achieved per meter of path length with a total collection time of 5 s. The achieved detection limit makes the developed setup suitable for real-time industrial monitoring of NO2 emissions at atmospheric pressure.

MON-293 NEUTROPHIL-LYMPHOCYTE RATIO IN PATIENTS WITH DIABETIC KIDNEY DISEASE

A major complication of diabetes is diabetic kidney disease (DKD) which is currently the leading cause of end-stage renal disease worldwide. Furthermore, DKD has been shown to be an independent risk factor for cardiovascular disease morbidity and mortality. Hence, DKD places a huge burden on healthcare systems. Therefore, early detection of DKD is hoped to reduce morbidity and mortality and to improve patient quality of life. Considering the inflammatory pathways involved in the development of the DKD, markers of inflammation could be potentially used for detecting the disease at early stages. Given that the neutrophil-to-lymphocyte ratio (NLR) is a reliable measure of systemic inflammation, we hypothesized that higher NLR would be associated with an increased risk of having DKD with albuminuria. In a cross-sectional study, 535 patients with type 1 or type 2 diabetes attending Austin Health Diabetes Clinics were recruited. NLR was calculated by dividing the total neutrophil count by total lymphocyte count from a full blood examination. The Albumin excretion rate (AER) was calculated using urine albumin concentration, total urine volume and total collection time. Serum creatinine was run on the Roche Cobas C800 and then measured using the kinetic colorimetric assay based on the Jaffe method. Estimated glomerular filtration rate (eGFR) was calculated using the creatinine-based CKD-EPI equation. Multivariate logistic regression models adjusted for age, HbA1c, fasting cholesterol and CRP were run for the following three outcomes: 1) eGFR <60ml/min/1.73m2 and AER ≥20 µg/min, 2) eGFR <60ml/min/1.73m2 and AER <20 µg/min 3) eGFR <60ml/min/1.73m2. Analysis of 535 patients with a full set of observations for 1,202 visits (mean visit per patient =2.2) demonstrated that one unit increase in NLR was associated with 44% increased risk of having eGFR <60ml/min/1.73m2 along with an AER ≥20µg/min [ odds ratio (OR), 95% confidence interval (CI): 1.44 (1.01-2.05); p= 0.046]. However, there was no statistically significant association between NLR and having eGFR <60ml/min/1.73m2 and an AER <20µg/min [OR (95% CI): 0.87 (0.63-1.20); p=0.39] as well as having eGFR <60ml/min/1.73m2 alone [OR (95% CI): 0.75 (0.53-1.05); p= 0.096]. Higher NLR values are independently associated with stage 3-5 chronic kidney disease with albuminuria (AER≥20µg/min). These data support the potential association of inflammation in the development of diabetic kidney disease and support the need for future studies.

Collection and identification of an unknown component from Eugenia uniflora essential oil exploiting a multidimensional preparative three-GC system employing apolar, mid-polar and ionic liquid stationary phases.

The present research deals with the collection and structural elucidation of an unknown component, accounting for about 35% of the essential oil obtained upon distillation of the leaves of Eugenia uniflora L., harvested during summer (January, 2017) in Paraná State (Southern Brazil). A multidimensional gas chromatographic preparative system, based on the coupling of three GC systems equipped with apolar, PEG and ionic liquid-based stationary phases, was successfully applied for the isolation of the chromatographic band relative to the unknown molecule. The use of wide-bore columns allowed for an increased sample capacity compared to conventional micro-bore columns, thus the injection of a neat sample was feasible, greatly reducing the total collection time. A higher chromatographic efficiency was afforded by the use of a multidimensional approach in the heart-cut mode, exploiting the different selectivity of three stationary phases, which ensured the attainment of a highly pure fraction. In only five runs, more than 3 milligrams were collected, with an average purity greater then 95%. Finally, the unknown component was subjected to nuclear magnetic resonance spectroscopy, mass spectrometry and condensed phase Fourier-transform infrared spectroscopy, leading to the identification of 6-ethenyl-6-methyl-3,5-di(prop-1-en-2-yl)cyclohex-2-en-1-one. The presented approach has been demonstrated to be effective for the isolation and structural elucidation of unknown molecules in complex samples, which will allow for further in-depth studies, like biological evaluation or pharmacological tests.

Deploying a Proximal Sensing Cart to Identify Drought-Adaptive Traits in Upland Cotton for High-Throughput Phenotyping.

Field-based high-throughput phenotyping is an emerging approach to quantify difficult, time-sensitive plant traits in relevant growing conditions. Proximal sensing carts represent an alternative platform to more costly high-clearance tractors for phenotyping dynamic traits in the field. A proximal sensing cart and specifically a deployment protocol, were developed to phenotype traits related to drought tolerance in the field. The cart-sensor package included an infrared thermometer, ultrasonic transducer, multi-spectral reflectance sensor, weather station, and RGB cameras. The cart deployment protocol was evaluated on 35 upland cotton (Gossypium hirsutum L.) entries grown in 2017 at Maricopa, AZ, United States. Experimental plots were grown under well-watered and water-limited conditions using a (0,1) alpha lattice design and evaluated in June and July. Total collection time of the 0.87 hectare field averaged 2 h and 27 min and produced 50.7 MB and 45.7 GB of data from the sensors and RGB cameras, respectively. Canopy temperature, crop water stress index (CWSI), canopy height, normalized difference vegetative index (NDVI), and leaf area index (LAI) differed among entries and showed an interaction with the water regime (p < 0.05). Broad-sense heritability (H2) estimates ranged from 0.097 to 0.574 across all phenotypes and collections. Canopy cover estimated from RGB images increased with counts of established plants (r = 0.747, p = 0.033). Based on the cart-derived phenotypes, three entries were found to have improved drought-adaptive traits compared to a local adapted cultivar. These results indicate that the deployment protocol developed for the cart and sensor package can measure multiple traits rapidly and accurately to characterize complex plant traits under drought conditions.

Submultiple Data Collection to Explore Spectroscopic Instrument Instabilities Shows that Much of the “Noise” is not Stochastic

As has long been understood, the noise on a spectrometric signal can be reduced by averaging over time, and the averaged noise is expected to decrease as t1/2, the square root of the data collection time. However, with contemporary capability for fast data collection and storage, we can retain and access a great deal more information about a signal train than just its average over time. During the same collection time, we can record the signal averaged over much shorter, equal, fixed periods. This is, then, the set of signals over submultiples of the total collection time. With a sufficiently large set of submultiples, the distribution of the signal's fluctuations over the submultiple periods of the data stream can be acquired at each wavelength (or frequency). From the autocorrelations of submultiple sets, we find only some fraction of these fluctuations consist of stochastic noise. Part of the fluctuations are what we call "fast drift", which is defined as drift over a time shorter than the complete measurement period of the average spectrum. In effect, what is usually assumed to be stochastic noise has a significant component of fast drift due to changes of conditions in the spectroscopic system. In addition, we show that the extreme values of the fluctuation of the signals are usually not balanced (equal magnitudes, equal probabilities) on either side of the mean or median without an inconveniently long measurement time; the data is almost inevitably biased. In other words, the unbalanced data is collected in an unbalanced manner around the mean, and so the median provides a better measure of the true spectrum. As is shown here, by using the medians of these distributions, the signal-to-noise of the spectrum can be increased and sampling bias reduced. The effect of this submultiple median data treatment is demonstrated for infrared, circular dichroism, and Raman spectrometry.

Dissimilar arc routing problems

Money collection presents particular problems in terms of effective vehicle routing. Planning the collection or distribution of money for ATMs or parking meters gives rise to two problems: while the total collecting time should be minimized, tours on successive days should be different to prevent robberies. The combination of these two problems is named as the Dissimilar Routing Problem. When the safes to be collected are located along the streets, it corresponds to an arc routing problem, which we call D, and when the money is from ATMs, it corresponds to a vehicle routing problem, usually referred to as the peripatetic routing problem. The former problem arises in a Portuguese company in charge of street parking in Lisbon. The firm needs to define tours to collect safes from parking meters, minimizing the total collecting time. To avoid robberies these tours cannot be repeated or somehow anticipated. For this new problem, we present a mixed integer linear programming (MILP) model and develop a matheuristic. Preliminary experiments are provided with data that mimic the real confidential data. Results point to a good performance of the matheuristic, while the smaller instances can be solved to optimality with the MILP model and a commercial solver. © 2017 Wiley Periodicals, Inc. NETWORKS, Vol. 70(3), 233–245 2017

High-speed fixed-target serial virus crystallography.

We report a method for serial X-ray crystallography at X-ray free-electron lasers (XFELs), which allows for full use of the current 120-Hz repetition rate of the Linear Coherent Light Source (LCLS). Using a micropatterned silicon chip in combination with the high-speed Roadrunner goniometer for sample delivery, we were able to determine the crystal structures of the picornavirus bovine enterovirus 2 (BEV2) and the cytoplasmic polyhedrosis virus type 18 polyhedrin, with total data collection times of less than 14 and 10 min, respectively. Our method requires only micrograms of sample and should therefore broaden the applicability of serial femtosecond crystallography to challenging projects for which only limited sample amounts are available. By synchronizing the sample exchange to the XFEL repetition rate, our method allows for most efficient use of the limited beam time available at XFELs and should enable a substantial increase in sample throughput at these facilities.

Pipelined forwarding with energy balance in hexagonal wireless sensor networks

ABSTRACTThis paper presents a pipelined forwarding scheme with energy balance for hexagonal wireless sensor networks (H‐WSN). An H‐WSN consists of hexagonal clusters in which the distance between any two cluster heads is , where R is the radius of a hexagonal cluster. A trade‐off exists in pipelined forwarding for an H‐WSN; that is, reducing pipeline lengths can decrease data forwarding delay, but it will adversely increase the number of clusters, which consequently increases the total collecting time of a mobile sink. This paper therefore introduces a mobile sink data collecting and routing scheme to dynamically adjust the pipeline lengths and to periodically switch pipeline directions. With this mobile sink data collecting and routing, the overall system throughput is increased, and the energy consumptions among all cluster heads are balanced. Copyright © 2012 John Wiley &amp; Sons, Ltd.

Reducing Neonatal Pain during Routine Heel Lance Procedures

To measure the difference in pain scores for newborns who were held and swaddled while undergoing routine heel lance procedures compared to newborns who were lying on their backs and not swaddled during heel lance. Additionally, we sought to compare the total amount of time it took to collect the specimens in each group. A total of 42 neonates recruited from a large tertiary hospital were enrolled in a randomized controlled trial. Infants in the experimental group (n = 22) were swaddled and held in an upright position during routine heel lance procedures while neonates in the control group (n = 20) remained in a standard care position. Pain was measured with the Neonatal Inventory Pain Scale (NIPS) at two points in time for each group (just before the heel lance procedure and at the completion of the heel lance). Total collection time was measured using a stopwatch accurate to 1/100th of a second. Specimen quality was measured based on the number of rejected specimens for each group. Descriptive statistics and t tests were used to analyze the data. The mean NIPS score for neonates who were swaddled and held during the procedure (experimental group) was significantly lower (M = 1.3, SD = .9) than the score for infants in the standard position (control group) (M = 2.7, SD = 1.3), t (40) = -4.48, p < .001. Although the total collection time was lower for infants who were swaddled (2 minutes and 17 seconds, SD = 59) versus (2 minutes and 47 seconds, SD = 85) for controls, this was not a statistically significant difference (p = .45). Swaddling combined with positioning neonates upright during routine heel lance procedures offers nurses a nonpharmacologic method of neonatal pain reduction for heel sticks. This technique can be easily implemented on any unit independent of facility protocols. Furthermore, the technique is not associated with any cost or policy development, making it more likely that nurses can use it in practice.

Power to Advocate for Health

<h3>Abstract</h3> Traditional X-ray diffraction data collected at cryo-temperatures have delivered invaluable insights into the three-dimensional structures of proteins, providing the backbone of structure-function studies. While cryo-cooling mitigates radiation damage, cryo-temperatures can alter protein conformational ensembles and solvent structure. Further, conformational ensembles underlie protein function and energetics, and recent advances in room-temperature X-ray crystallography have delivered conformational heterogeneity information that is directly related to biological function. The next challenge is to develop a robust and broadly applicable method to collect single-crystal X-ray diffraction data at and above room temperatures and was addressed herein. This approach provides complete diffraction datasets with total collection times as short as ~5 sec from single protein crystals, dramatically increasing the amount of data that can be collected within allocated synchrotron beam time. Its applicability was demonstrated by collecting 1.09-1.54 Å resolution data over a temperature range of 293–363 K for proteinase K, thaumatin, and lysozyme crystals. Our analyses indicate that the diffraction data is of high-quality and do not suffer from excessive dehydration or damage.

The time and energy signals, counter plateau, energy resolution and gas gains performances of a new kind of micro-pattern gaseous detector-Micromegas

In present paper, a new Micromegas detector is developed, and its time and energy signals are obtained in the figure form. The rising time of fast time signal is less than 2 ns due to the very fast collection of avalanche electrons, and the rising time of the energy pulse is about 100 ns, which is corresponding to the total collecting time of the electrons and ions in the avalanche process. The counter plateau, energy resolution and the gas gains of the detector have been compared with other groups’ experimental results and the Garfield simulation result.