bluuebunny/crossref_metadata_2025_split huggingface dataset:
On a Reduction for a Class of Resource Allocation Problems
Authors: Schoot Uiterkamp Martijn H. H. , Gerards Marco E. T. , Hurink Johann L. 
Published: December 2021

In the resource allocation problem (RAP), the goal is to divide a given amount of a resource over a set of activities while minimizing the cost of this allocation and possibly satisfying constraints on allocations to subsets of the activities. Most solution approaches for the RAP and its extensions allow each activity to have its own cost function. However, in many applications, often the structure of the objective function is the same for each activity, and the difference between the cost functions lies in different parameter choices, such as, for example, the multiplicative factors. In this article, we introduce a new class of objective functions that captures a significant number of the objectives occurring in studied applications. These objectives are characterized by a shared structure of the cost function depending on two input parameters. We show that, given the two input parameters, there exists a solution to the RAP that is optimal for any choice of the shared structure. As a consequence, this problem reduces to the quadratic RAP, making available the vast amount of solution approaches and algorithms for the latter problem. We show the impact of our reduction result on several applications, and in particular, we improve the best-known worst-case complexity bound of two problems in vessel routing and processor scheduling from [Formula: see text] to [Formula: see text]. Summary of Contribution: The resource allocation problem (RAP) with submodular constraints and its special cases are classic problems in operations research. Because these problems are studied in many different scientific disciplines, many conceptual insights, structural properties, and solution approaches have been reinvented and rediscovered many times. The goal of this article is to reduce the amount of future reinventions and rediscoveries by bringing together these different perspectives on RAPs in a way that is accessible to researchers with different backgrounds. The article serves as an exposition on RAPs and on their wide applicability in many areas, including telecommunications, energy, and logistics. In particular, we provide tools and examples that can be used to formulate and solve problems in these areas as RAPs. To accomplish this, we make three concrete contributions. First, we provide a survey on algorithms and complexity results for RAPs and discuss several recent advances in these areas. Second, we show that many objectives for RAPs can be reduced to a (simpler) quadratic objective function, which makes available the extensive collection of fast and efficient algorithms for quadratic RAPs to solve these problems. Third, we discuss the impact that RAPs and the aforementioned reduction result can make in several application areas.
Learning-Based Branch-and-Price Algorithms for the Vehicle Routing Problem with Time Windows and Two-Dimensional Loading Constraints
Authors: Zhang Xiangyi , Chen Lu , Gendreau Michel , Langevin André 
Published: December 2021

A capacitated vehicle routing problem with two-dimensional loading constraints is addressed. Associated with each customer are a set of rectangular items, the total weight of the items, and a time window. Designing exact algorithms for the problem is very challenging because the problem is a combination of two NP-hard problems. An exact branch-and-price algorithm and an approximate counterpart are proposed to solve the problem. We introduce an exact dominance rule and an approximate dominance rule. To cope with the difficulty brought by the loading constraints, a new column generation mechanism boosted by a supervised learning model is proposed. Extensive experiments demonstrate the superiority of integrating the learning model in terms of CPU time and calls of the feasibility checker. Moreover, the branch-and-price algorithms are able to significantly improve the solutions of the existing instances from literature and solve instances with up to 50 customers and 103 items. Summary of Contribution: We wish to submit an original research article entitled “Learning-based branch-and-price algorithms for a vehicle routing problem with time windows and two-dimensional loading constraints” for consideration by IJOC. We confirm that this work is original and has not been published elsewhere, nor is it currently under for publication elsewhere. In this paper, we report a study in which we develop two branch-and-price algorithms with a machine learning model injected to solve a vehicle routing problem integrated the two-dimensional packing. Due to the complexity brought by the integration, studies on exact algorithms in this field are very limited. Our study is important to the field, because we develop an effective method to significantly mitigate computational burden brought by the packing problem so that exactness turns to be achievable within reasonable time budget. The approach can be generalized to the three-dimensional case by simply replacing the packing algorithm. It can also be adapted for other VRPs when high-dimensional loading constraints are concerned. Broadly speaking, the study is a typical example of adopting supervised learning to achieve acceleration for operations research algorithms, which expands the envelop of computing and operations research. Hence, we believe this manuscript is appropriate for publication by IJOC.
Consumer Online Search with Partially Revealed Information
Authors: Gu Chris , Wang Yike 
Published: December 2021

Modern-day search platforms generally have two layers of information presentation. The outer layer displays the collection of search results with attributes selected by platforms, and consumers click on a product to reveal all its attributes in the inner layer. The information revealed in the outer layer affects the search costs and the probability of finding a match. To address the managerial question of optimal information layout, we create an information complexity measure of the outer layer, namely orderedness entropy, and study the consumer search process for information at the expense of time and cognitive costs. We first conduct online random experiments to show that consumers respond to and actively reduce cognitive cost for which our information complexity measure provides a representation. Then, using a unique and rich panel tracking consumer search behaviors at a large online travel agency (OTA), we specify a novel sequential search model that jointly describes the refinement search and product clicking decisions. We find that cognitive cost is a major component of search cost, while loading time cost has a much smaller share. By varying the information revealed in the outer layer, we propose information layouts that Pareto-improve both revenue and consumer welfare for our OTA. This paper was accepted by Juanjuan Zhang, marketing.
Bias-corrected maximum-likelihood estimation of multiplicity of infection and lineage frequencies
Authors: Hashemi Meraj , Schneider Kristan A. 
Published: December 2021

BackgroundThe UN’s Sustainable Development Goals are devoted to eradicate a range of infectious diseases to achieve global well-being. These efforts require monitoring disease transmission at a level that differentiates between pathogen variants at the genetic/molecular level. In fact, the advantages of genetic (molecular) measures like multiplicity of infection (MOI) over traditional metrics, e.g.,R0, are being increasingly recognized. MOI refers to the presence of multiple pathogen variants within an infection due to multiple infective contacts. Maximum-likelihood (ML) methods have been proposed to derive MOI and pathogen-lineage frequencies from molecular data. However, these methods are biased.Methods and findingsBased on a single molecular marker, we derive a bias-corrected ML estimator for MOI and pathogen-lineage frequencies. We further improve these estimators by heuristical adjustments that compensate shortcomings in the derivation of the bias correction, which implicitly assumes that data lies in the interior of the observational space. The finite sample properties of the different variants of the bias-corrected estimators are investigated by a systematic simulation study. In particular, we investigate the performance of the estimator in terms of bias, variance, and robustness against model violations. The corrections successfully remove bias except for extreme parameters that likely yield uninformative data, which cannot sustain accurate parameter estimation. Heuristic adjustments further improve the bias correction, particularly for small sample sizes. The bias corrections also reduce the estimators’ variances, which coincide with the Cramér-Rao lower bound. The estimators are reasonably robust against model violations.ConclusionsApplying bias corrections can substantially improve the quality of MOI estimates, particularly in areas of low as well as areas of high transmission—in both cases estimates tend to be biased. The bias-corrected estimators are (almost) unbiased and their variance coincides with the Cramér-Rao lower bound, suggesting that no further improvements are possible unless additional information is provided. Additional information can be obtained by combining data from several molecular markers, or by including information that allows stratifying the data into heterogeneous groups.
Pemodelan Sistem Karbonat di Laut Jawa
Authors: Koropitan Alan Frendy 
Published: December 2021

<p class="Papertext"><strong>Modeling Carbonate System in the Java Sea</strong>. Besides the global fossil fuel burning activities, forest fires in Kalimantan could potentially increase atmospheric CO<sub>2</sub> concentrations, impacting air-sea CO<sub>2</sub> gas exchange in the Java Sea and changing the balance of the marine carbonate system. This study uses a marine carbonate model to examine the processes that control CO<sub>2</sub> flux in the Java Sea and their relationship to CO<sub>2</sub> increase in the atmosphere. OCMIP-2 (<em>Ocean Carbon-Cycle Model Intercomparison Model Project, Phase-2</em>) is performed in this marine carbonate model coupled with the marine ecosystem model. The model results show that the quantity of carbon air flux differs during February and October 2000. More considerable flux is produced during February 2000, where the wind speeds are higher than in October 2000. However, the wind speeds have less impact when the CO<sub>2</sub> level in the atmosphere rises significantly. Due to the influence of a relatively high surface temperature in the tropical Java sea, the Java Sea functions as a carbon source to the atmosphere in general. In this case, the role of the <em>solubility pump</em> is more significant than that of biological processes in carbon absorption. Moreover, increased CO<sub>2</sub> in the atmosphere could alter the partial pressure equilibrium. In the case of 2002 forest fires (atmospheric CO<sub>2</sub> = 460 ppm), the carbon source of the Java Sea was less than before forest fires and even became carbon sink when atmospheric CO<sub>2</sub> rose to 1135.2 ppm based on the highest SSP scenario in 2100. This modeling also reveals marine acidification issues and could rapidly assess the future changes in marine ecosystems due to CO<sub>2</sub> levels rising in the atmosphere.</p>
Preferensi Teripang Pasir Holothuria scabra Terhadap Pakan Berbahan Dasar Makroalga
Authors: Kurnianto Dedy , Indriana Lisa Fajar , Suparmo Suparmo , Tarmin Nurhalis , Wahab Abdul , Badi Balkam F. , Pesilette Rosmi Nuslah , Jasmadi Jasmadi 
Published: December 2021

<p class="Papertext"><strong>The Preference of The Sandfish Holothuria scabra on Macroalgae-Based Feed. </strong>The sandfish, <em>Holothuria scabra</em>, is one ofthe marine species that has the potential to be developed as a source of high-value functional food. However, the growth of sandfish is still constrained by the availability of suitable feed. This study aimed to determine the level of preference of sea cucumbers for artificial feed made from macroalgae. This study used six main ingredients: control (sea-sand), FF-1 (commercial shrimp feed), FF-2 (<em>Padina</em> sp.), FF-3 (<em>Ulva</em> sp.), FF-4 (<em>Sargassum</em> sp.), FF-5 (combination). A completely randomized design with three replications was implemented. Nutritional values of feed and the sandfish body, feed consumption, specific growth rate (SGR), survival, and water quality were investigated. The results revealed that all treatments had a 100 percent survival rate, even though the SGR for all treatmentswere negative. Artificial feed made from <em>Padina</em> sp. (FF-2) had the highest average feed consumption of 0.51 gram/day. This value was significantly greater than the other treatments (p&lt;0.05). The SGR reached a positive value in the last week of the maintenance phase. The nutritional quality of the sandfish body generally decreased compared to the initial rearing condition. On the other hand, water quality was optimal for sandfish growth throughout the experiment.It can be concluded that the feed derived from <em>Padina</em> sp. is preferable for <em>Holothuria scabra </em>and has the potential to be further developed.</p>
Social Efficiency of Entry in an Open Economy
Authors: Han Tien-Der , Haque M. Emranul , Mukherjee Arijit 
Published: December 2021

Abstract
We show that cost asymmetry between the domestic and foreign firms is not necessary for the occurrence of insufficient entry in the domestic country. This result provides a rationale for pro-competitive domestic policies even in the absence of cost asymmetries among the domestic and foreign firms. However, if significant demand comes from foreign countries, and the market structures are determined endogenously in the domestic and foreign countries, domestic-entry in an open economy might not be insufficient, implying that foreign competition might not reduce the importance of anti-competitive domestic policies.
Modelling and performance analysis for cumene production process in a four-layer packed bed reactor
Authors: Mundakkal Lakshmanan Vinila , Kallingal Aparna , Sreekumar Sreepriya 
Published: December 2021

AbstractA mathematical model is developed and designed for the cumene reactor in cumene production process in Hindustan Organic Chemicals Limited (HOCL), Kochi with improved operating conditions. High purity cumene is produced by the alkylation of benzene with propylene in this catalytic condensation process where solid phosphoric acid (SPA) is used as the catalyst. The mathematical model has been derived from mass and energy balance equations considering the reactor as fixed packed bed reactor and two different numerical methods are presented here to solve the modelling equations. The explicit finite difference method (FDM) involves the approximation of derivatives into finite differences, and in the other one, orthogonal collocation (OC), Ordinary Diffeential Equations (ODEs) are formed at the collocation points and are solved using Runge–Kutta fourth order numerical scheme. Here the analysis shows that the predictions from the model are in good alignment with the plant data. The combined feed has the optimum value of 1:2:8 for propylene, propane and benzene and the profiles of temperature and concentration can be obtained along the reactor. The model has been implemented in COMSOL Multiphysics as a packed bed reactor using the same parameters collected from the plant of study. It has been found that the reaction occurs at a satisfactory level even with a low temperature than the reactor temperature at the plant by changing the catalytic particle size. The reaction performance is also analysed for the physical properties like porosity and catalyst size.
Advances and challenges in the development of nanosheet membranes
Authors: Kadja Grandprix T. M. , Himma Nurul F. , Prasetya Nicholaus , Sumboja Afriyanti , Bazant Martin Z. , Wenten I G. 
Published: December 2021

Abstract
The development of highly efficient separation membranes utilizing emerging materials with controllable pore size and minimized thickness could greatly enhance the broad applications of membrane-based technologies. Having this perspective, many studies on the incorporation of nanosheets in membrane fabrication have been conducted, and strong interest in this area has grown over the past decade. This article reviews the development of nanosheet membranes focusing on two-dimensional materials as a continuous phase, due to their promising properties, such as atomic or nanoscale thickness and large lateral dimensions, to achieve improved performance compared to their discontinuous counterparts. Material characteristics and strategies to process nanosheet materials into separation membranes are reviewed, followed by discussions on the membrane performances in diverse applications. The review concludes with a discussion of remaining challenges and future outlook for nanosheet membrane technologies.
The Uniform and Nonuniform Nature of Slow and Rapid Scaling in Embryonic Motoneurons
Authors: Pekala Dobromila , Wenner Peter 
Published: December 2021

Neurons regulate the strength of their synapses in response to a perturbation to stabilize neuronal signaling through a form of homeostatic plasticity known as synaptic scaling. The process of scaling has the potential to alter all of a cell's miniature postsynaptic current (mPSC) amplitudes by a single multiplicative factor (uniform scaling), and in doing so could change action potential-dependent or evoked synaptic strength by that factor. However, recent studies suggest that individual synapses scale with different scaling factors (nonuniform). This could complicate the simple multiplicative transform from mPSC scaling to the evoked response. We have previously identified a slow AMPAergic and GABAergic synaptic scaling in chick embryo motoneurons following 2 din vivoperturbations inhibiting neuronal activity or GABAAR function, and now show a rapid form of scaling following NMDAR blockadein vitro. Slow GABAergic scaling appeared to be of a classical uniform pattern. Alternatively, other forms of rapid and slow scaling demonstrated a uniform and nonuniform component in their mPSC amplitude distributions. Slow and rapid AMPAergic scaling was mediated by insertion of GluA2-lacking AMPA receptors. The nonuniform pattern of scaling may contribute to the observed complexity of the changes in evoked responses. Scaling-induced changes in mPSC amplitudes were not associated with changes in probability of release (Pr). Together, our results demonstrate a new rapid form of scaling in embryonic motoneurons, that slow and rapid scaling is not purely uniform, and that upscaling does not translate to an increase in evoked responses in a simple manner.SIGNIFICANCE STATEMENTDifferent forms of homeostatic plasticity are thought to play a critical role in maintaining neural function. For example, altering the amplitudes of spontaneous currents through a form of homeostatic plasticity known as synaptic scaling could affect evoked transmission; however, this is rarely tested. Here we demonstrate two forms of scaling and show that in many cases synaptic strength scales differently for distinct synapses within an embryonic motoneuron. These results have functional consequences for evoked synaptic strength and suggest that, like Hebbian plasticity, scaling can change relative synaptic strengths within a cell. Furthermore, our results demonstrate how different forms of homeostatic plasticity influence neuronal communication as the nascent spinal network is first established in the embryonic period.
Collagen VI Regulates Motor Circuit Plasticity and Motor Performance by Cannabinoid Modulation
Authors: Lam Daniel D. , Williams Rhîannan H. , Lujan Ernesto , Tanabe Koji , Huber Georg , Saw Nay Lui , Merl-Pham Juliane , Salminen Aaro V. , Lohse David , Spendiff Sally , Plastini Melanie J. , Zech Michael , Lochmüller Hanns , Geerlof Arie , Hauck Stefanie M. , Shamloo Mehrdad , Wernig Marius , Winkelmann Juliane 
Published: December 2021

Collagen VI is a key component of muscle basement membranes, and genetic variants can cause monogenic muscular dystrophies. Conversely, human genetic studies recently implicated collagen VI in central nervous system function, with variants causing the movement disorder dystonia. To elucidate the neurophysiological role of collagen VI, we generated mice with a truncation of the dystonia-related collagen α3 VI (COL6A3) C-terminal domain (CTD). TheseCol6a3CTTmice showed a recessive dystonia-like phenotype in both sexes. We found that COL6A3 interacts with the cannabinoid receptor 1 (CB1R) complex in a CTD-dependent manner.Col6a3CTTmice of both sexes have impaired homeostasis of excitatory input to the basal pontine nuclei (BPN), a motor control hub with dense COL6A3 expression, consistent with deficient endocannabinoid (eCB) signaling. Aberrant synaptic input in the BPN was normalized by a CB1R agonist, and motor performance inCol6a3CTTmice of both sexes was improved by CB1R agonist treatment. Our findings identify a readily therapeutically addressable synaptic mechanism for motor control.SIGNIFICANCE STATEMENTDystonia is a movement disorder characterized by involuntary movements. We previously identified genetic variants affecting a specific domain of the COL6A3 protein as a cause of dystonia. Here, we created mice lacking the affected domain and observed an analogous movement disorder. Using a protein interaction screen, we found that the affected COL6A3 domain mediates an interaction with the cannabinoid receptor 1 (CB1R). Concordantly, our COL6A3-deficient mice showed a deficit in synaptic plasticity linked to a deficit in cannabinoid signaling. Pharmacological cannabinoid augmentation rescued the motor impairment of the mice. Thus, cannabinoid augmentation could be a promising avenue for treating dystonia, and we have identified a possible molecular mechanism mediating this.