Cheapest Set Research Articles

Identification, characterization and classification of prokaryotic nucleoid-associated proteins.

Common throughout life is the need to compact and organize the genome. Possible mechanisms involved in this process include supercoiling, phase separation, charge neutralization, macromolecular crowding, and nucleoid-associated proteins (NAPs). NAPs are special in that they can organize the genome at multiple length scales, and thus are often considered as the architects of the genome. NAPs shape the genome by either bending DNA, wrapping DNA, bridging DNA, or forming nucleoprotein filaments on the DNA. In this mini-review, we discuss recent advancements of unique NAPs with differing architectural properties across the tree of life, including NAPs from bacteria, archaea, and viruses. To help the characterization of NAPs from the ever-increasing number of metagenomes, we recommend a set of cheap and simple invitro biochemical assays that give unambiguous insights into the architectural properties of NAPs. Finally, we highlight and showcase the usefulness of AlphaFold in the characterization of novel NAPs.

Outward Appearance or Inward Significance? On Experts' Perspectives When Studying and Solving Water Scarcity

In the first decade of the 21st century, a water harvesting approach based on contour trenches—ditches to catch runoff—from Kenya was proposed as groundwater recharge technology in a semi-arid area in Ninh Phuoc district, Vietnam. In order to modify this solutions to tackle water scarcity, hydrological conditions at the site needed to be known. For such small-scale interventions, finding the most suitable set of (cheap and quick) efforts to study local hydrology is not easy. After our own study, we explored how different experts evaluated the chosen approach. The results from this evaluation suggest that different perspective for appropriate hydrological research can be found within a group of experts. This finding—in line with anthropologically inspired science studies—suggests that integrating different perspectives from stakeholders when working on suitable solutions in real-life water scarcity situations needs to be complemented with attention for different perspectives on the underlying hydrological processes and how they are to be studied. We discuss how this notion on the multiple perspectives intrinsic to hydrological research can be fruitfully included when developing water interventions.

Simultaneous Detection of Multiple Plant Growth Regulator Residues in Cabbage and Grape Using an Optimal QuEChERS Sample Preparation and UHPLC-MS/MS Method.

At present, plant growth regulators (PGRs) are widely used in agricultural and forestry production. PGRs, like traditional pesticides, have certain toxicities. Naively excessively applying them will cause the acute and chronic poisoning of humans and animals and potentially harm human health. In order to assess, prevent, and control the residues of PGRs in fruits and vegetables, a set of quick, easy, cheap, effective, rugged, and safe (QuEChERS) analytical methods that simultaneously detect multiple PGR residues are urgently needed for quality and safety inspection of agricultural product. In this study, grapes (representative of fruits) and cabbages (representative of vegetables) were used as the detected objects. The 30 commercial product residues of PGRs were detected in both with an ultra-high performance liquid chromatography (UHPLC)-tandem mass spectrometry (MS/MS) method, based on optimized chromatographic, MS, and preparation conditions (extraction solvent and cleanup conditions). Grape and cabbage samples were extracted with acetonitrile containing 5% (v/v) acetic acid, dehydrated using a salt package, purified using the QuEChERS method, ionized using electrospray ionization under positive and negative ion switching mode, detected using multi-reaction monitoring, and quantification using an external standard method of matrix matching standard curve. Methanol was selected as the strong elution phase. A methanol-0.1% formic acid-5 mmol/L ammonium acetate solution was selected as the best mobile phase. The optimal extraction solvent was acetonitrile containing 5% acetic acid. Primary secondary amine cleanup could met the determination requirements of PGR residues. The developed method for determination of 30 commercial products of PGR, such as betaine, showed excellent linearity in 1-500, 10-1000, ∼500, ∼2000, and 100-10 000 μg/kg (R ≥ 0.98). At the 0.001 (0.01), 0.05, 0.20, and 1.00 mg/kg additive concentrations, the average addition standard recovery of 30 commercial products of PGR were 61-132% with the relative standard deviations of 1-14% and the LOQs were confirmed to be 1.0-100 μg/kg through the actual addition values of samples. The set of optimized QuEChERS UHPLC-MS/MS methods simultaneously detect residues of PGRs in fruits and vegetables with one-time sample preparation for high-throughput, rapid quantitative screening, and confirmation. The methods cover a wide range of PGRs with simple and convenient preparation and small amounts of solvent, and can provide technical support for the supervision of PGR residues in fruits and vegetables. The optimizations of extraction solvent screening, different ratios of various purification packages in the QuEChERS method, and UPLC-MS conditions were conducted and the precision, sensitivity, and recovery rates of the methods were investigated in order to establish a QuEChERS UPLC-MS/MS method for simultaneously detecting 30 kinds of PGR residues in fruits and vegetables. The methods allow high-throughput determination of multiple PGR residues in fruits and vegetables and can also provide technical references for related compound residue detection of other matrixes.

Good speciation and endogenous business cycles in a constraint satisfaction macroeconomic model

We introduce a prototype agent-based model of the macroeconomy, with budgetary constraints at its core. The model is related to a class of constraint satisfaction problems (CSPs), which has been thoroughly investigated in computer science. The CSP paradigm allows us to propose an alternative price-setting mechanism: given agents’ preferences and budgets, what set of prices satisfies the maximum number of agents? Such an approach permits the coupling of production and output within the economy to the allowed level of debt in a simplified framework. Within our model, we identify three different regimes upon varying the amount of debt that each agent can accumulate before defaulting. In presence of a very loose constraint on debt, endogenous crises leading to waves of synchronized bankruptcies are present. In the opposite regime of very tight debt constraining, the bankruptcy rate is extremely high and the economy remains structure-less. In an intermediate regime, the economy is stable with very low bankruptcy rate and no aggregate-level crises. This third regime displays a rich phenomenology: the system spontaneously and dynamically self-organizes in a set of cheap and expensive goods (i.e. some kind of ‘speciation’), with switches triggered by random fluctuations and feedback loops. Our analysis confirms the central role that debt levels play in the stability of the economy. More generally, our model shows that constraints at the individual scale can generate highly complex patterns at the aggregate level.

A perturbed parameter ensemble of HadGEM3-GC3.05 coupled model projections: part 1: selecting the parameter combinations

This is the first of two papers that describe the generation of a 25-member perturbed parameter ensemble (PPE) of high-resolution, global coupled simulations for the period 1900–2100, using CMIP5 historical and RCP8.5 emissions. Fifteen of these 25 coupled simulations now form a subset of the global projections provided for the UK Climate Projections 2018 (UKCP18). This first paper describes the selection of 25 variants (combinations of 47 parameters) using a set of cheap, coarser-resolution atmosphere-only simulations from a large sample of nearly 3000 variants. Retrospective 5-day weather forecasts run at climate resolution, and simulations of 2004–2009 with prescribed SST and sea ice are evaluated to filter out poor performance. We opted for a single design choice and sensitivity tests were done after the PPE was generated to demonstrate the effect of design choices on the filtering. Given our choice, only 38 of the parameter combinations were found to have acceptable performance at this stage. Idealised atmosphere-only simulations were then used to select the subset of 25 members that were as diverse as possible in terms of their CO2 and aerosol forcing, and their response to warmer SSTs. Using our parallel set of atmosphere-only and coupled PPEs (the latter from paper 2), we show that local biases in the atmosphere-only experiments are generally informative about the biases in the coupled PPE. Biases in radiative fluxes and cloud amounts are strongly informative for most regions, whereas this is only true for a smaller fraction of the globe for precipitation and dynamical variables. Therefore, the cheap experiments are an affordable way to search for promising parameter combinations but have limitations.

A perturbed parameter ensemble of HadGEM3-GC3.05 coupled model projections: part 2: global performance and future changes

This paper provides a quantitative assessment of large-scale features in a perturbed parameter ensemble (PPE) of Met Office Unified Model HadGEM-GC3.05 in coupled global historical and future simulations. The main motivation for the simulations is to provide a major component of the UK Climate Projections 2018 (UKCP18), but they will also be used to make worldwide projections and inform future model development. Initially, a 25-member PPE, with 25 different parameter combinations, was simulated. Five members were subsequently dropped because either their simulated climate was unrealistically cool by 1970 or they suffered from numerical instabilities. The remaining 20 members were evaluated after completing the historical phase (1900–2005) against 13 separately selected Climate Model Intercomparison Project Phase 5 (CMIP5) models, and five more members were dropped. The final product is a combined projection system of 15 PPE members and 13 CMIP5 models, which has a number of benefits. In particular, the range of outcomes available from the combined set of 28 is often larger than from either of the two constituent ensembles, thus providing users with a more complete picture of plausible impacts. Here we mainly describe the evaluation process of the 20 PPE members. We evaluate biases in a number of important properties of the global coupled system, including assessment of climatological averages, coupled modes of internal variability and historical and future changes. The parameter combinations yielded plausible yet diverse atmosphere and ocean model behaviours. The range of global temperature changes is narrow, largely driven by use of different CO2 pathways. The range of global warming is seemingly not linked to range of feedbacks estimated from atmosphere-only runs, though we caution that the range of the latter is narrow relative to CMIP5, and therefore this result is not unexpected. This is the second of two papers describing the generation of the PPE for UKCP18 projections. Part 1 (Sexton et al. 2021) describes the selection of 25 parameter combinations of 47 atmosphere and land surface parameters, using a set of cheap atmosphere-only runs at a coarser resolution from nearly 3000 samples of parameter space.

A Constraint-Satisfaction Agent-Based Model for the Macro-economy

We introduce a prototype agent-based model of the macroeconomy, with budgetary constraints at its core. The model is related to a class of constraint satisfaction problems (CSPs), which has been thoroughly investigated in computer science. The CSP paradigm allows us to propose an alternative price-setting mechanism: given agents' preferences and budgets, what set of prices satisfies the maximum number of agents? Such an approach permits the coupling of production and output within the economy to the allowed level of debt in a simplified framework. Within our model, we identify three different regimes upon varying the amount of debt that each agent can accumulate before defaulting. In presence of a very loose constraint on debt, endogenous crises leading to waves of synchronized bankruptcies are present.In the opposite regime of very tight debt constraining, the bankruptcy rate is extremely high and the economy remains structure-less. In an intermediate regime, the economy is stable with very low bankruptcy rate and no aggregate-level crises. This third regime displays a rich phenomenology: the system spontaneously and dynamically self-organizes in a set of cheap and expensive goods (i.e. some kind of ``speciation''), with switches triggered by random fluctuations and feedback loops. Our analysis confirms the central role that debt levels play in the stability of the economy. More generally, our model shows that constraints at the individual scale can generate highly complex patterns at the aggregate level.

Evolutionary Hyperheuristics for Location-Routing Problem with Simultaneous Pickup and Delivery

This paper presents an evolution-based hyperheuristic (EHH) for addressing the capacitated location-routing problem (CLRP) and one of its more practicable variants, namely, CLRP with simultaneous pickup and delivery (CLRPSPD), which are significant and NP-hard model in the complex logistics system. The proposed approaches manage a pool of low-level heuristics (LLH), implementing a set of simple, cheap, and knowledge-poor operators such as “shift” and “swap” to guide the search. Quantum (QS), ant (AS), and particle-inspired (PS) high-level learning strategies (HLH) are developed as evolutionary selection strategies (ESs) to improve the performance of the hyperheuristic framework. Meanwhile, random permutation (RP), tabu search (TS), and fitness rate rank-based multiarmed bandit (FRR-MAB) are also introduced as baselines for comparisons. We evaluated pairings of nine different selection strategies and four acceptance mechanisms and monitored the performance of the first four outstanding pairs in 36 pairs by solving three sets of benchmark instances from the literature. Experimental results show that the proposed approaches outperform most fine-tuned bespoke state-of-the-art approaches in the literature, and PS-AM and AS-AM perform better when compared to the rest of the pairs in terms of obtaining a good trade-off of solution quality and computing time.

Semi-parametric regression when some (expensive) covariates are missing by design

The paper deals with the scenario where some covariates are observed by design for a subset of the observations only. In the example treated in the paper this occurs with a two phase sampling scheme where in the first phase a relatively large sample is drawn to record a response variable Y and a set of (cheap) covariates x. In a second phase a smaller sample is drawn from the first phase sample where additional (usually expensive) covariates z are also recorded. The second phase can be drawn with unequal probability sampling, where the sampling weights depend on the observed Y and x. The overall intention is to fit a regression model of Y on both, x and z. Due to the design of the data collection we are faced with missing values for z for a majority of observations. We propose an approximate estimation approach using semi-parametric mean and variance regression of Y on x only and augment this fit with a full regression model of Y on x and z. The idea extends the approach of Little (1992) towards non-normal data and non-linear models. The proposed estimation is numerically rather simple and performs convincingly well in simulation studies compared to alternatives such as complete-case and multiple imputation analysis.

Incentive Mechanisms for Crowdsensing: Crowdsourcing With Smartphones

Smartphones are programmable and equipped with a set of cheap but powerful embedded sensors, such as accelerometer, digital compass, gyroscope, GPS, microphone, and camera. These sensors can collectively monitor a diverse range of human activities and the surrounding environment. Crowdsensing is a new paradigm which takes advantage of the pervasive smartphones to sense, collect, and analyze data beyond the scale of what was previously possible. With the crowdsensing system, a crowdsourcer can recruit smartphone users to provide sensing service. Existing crowdsensing applications and systems lack good incentive mechanisms that can attract more user participation. To address this issue, we design incentive mechanisms for crowdsensing. We consider two system models: the crowdsourcer-centric model where the crowdsourcer provides a reward shared by participating users, and the user-centric model where users have more control over the payment they will receive. For the crowdsourcer-centric model, we design an incentive mechanism using a Stackelberg game, where the crowdsourcer is the leader while the users are the followers. We show how to compute the unique Stackelberg Equilibrium, at which the utility of the crowdsourcer is maximized, and none of the users can improve its utility by unilaterally deviating from its current strategy. For the user-centric model, we design an auction-based incentive mechanism, which is computationally efficient, individually rational, profitable, and truthful. Through extensive simulations, we evaluate the performance and validate the theoretical properties of our incentive mechanisms.

The BehaviorScope framework for enabling ambient assisted living

The in-house monitoring of elders using intelligent sensors is a very desirable service that has the potential of increasing autonomy and independence while minimizing the risks of living alone. Because of this promise, the efforts of building such systems have been spanning for decades, but there is still a lot of room for improvement. Driven by the recent technology advances in many of the required components, in this article, we present a scalable framework for detailed behavior interpretation. Our framework supports in-house monitoring of elders using an intelligent gateway and a set of cheap commercially available sensors, in addition to more advanced camera-based human localization sensors and a client for GPS-enabled mobile phones that provides monitoring when outdoors. In this article, we report our experiences and present our current progress in three main components: sensors, middleware, and behavior interpretation mechanisms spanning from simple programmable rule-based alerts to algorithms for extracting the temporal routines of individuals.

Cost-optimal replenishment of chemical baths: an application of linear programming

The concentrations of components in chemical baths used in industrial applications often have to meet certain requirements. Production or evaporation may change the relative amounts of the components so that some of the concentrations fall outside their limits, resulting in output deterioration. Determining how much should be added of each of the components is not as straightforward as it may seem at first sight. In this paper we describe a case where this problem was encountered in a quality improvement project at the factory of Philips Semiconductors Stadskanaal, the Netherlands. A linear programming model is developed that can be used to determine the cheapest set of additions under the restriction that the new concentrations in the bath meet their requirements. The simplex algorithm can then be used to solve this problem. An interesting feature of this application is that a standard basic feasible solution that is needed to start up the algorithm is available for every instance of the problem. The results of the method are compared with those of an old method that was used for computing additions. It turns out that for the cases considered, a cost reduction of about 60% is possible. Copyright © 2000 John Wiley & Sons, Ltd.