bluuebunny/crossref_metadata_2025 huggingface dataset:
Methods Used to Extinguish Fires in Electric Vehicles
Authors: Lesiak Piotr , Pietrzela Dariusz , Mortka Piotr
Published: December 2021

Aim: The aim of the article is to present the current state of knowledge regarding the possibility of suppressing or effectively extinguishing fires of electric vehicle. Due to the growing popularity of means of transport powered by electric batteries, the problem of emerging fires and their effects is becoming recognizable. Due to the possible violent process of combustion of lithium-ion batteries (hereinafter referred to as Li-Ion batteries), a fire in a vehicle may lead to a wide range of property damage. For at least a decade, intensive efforts have been made to develop appropriate methods to allow firefighters to deal with the problem of fires of electric vehicles. These activities were directed, among others, at new fire extinguishing/suppression techniques, innovative extinguishing agents and methods of their application. Introduction: Taking into account the current global trends in changing the method of powering vehicles from fossil fuels into electricity, the occurrence of such events should be expected to intensify. The authors systematize the issue by analysing the literature on fires, Li-Ion batteries being a critical ele- ment that may initiate a fire. The adopted and practiced methods of extinguishing/suppressing a fire as well as the used extinguishing agents were also analysed. The publication may be an element helpful in selecting the most optimal fire extinguishing method of the electric energy storage unit in a vehicle. Methodology: The review of the current state of knowledge was made based on publications on the fire characteristics of Li-Ion batteries, as well as works and research projects in the field of extinguishing methods and the effectiveness of various extinguishing agents. In addition, the procedures used by the emergency services and selected real events were analysed. Conclusions: Fires of Li-Ion batteries are a relatively new and growing phenomenon. Fires in fully or partially electric vehicles are much more difficult to fully extinguish compared to fires in vehicles with internal combustion engines. So far, no effective method has been developed that would allow a fire to be extinguished in a short time. Activities in this area focus on minimizing the effects. There is still a need to look for new technical and tactical solutions in order to optimize the procedures leading to more effective activities of the services in this type of incidents. Keywords: lithium-ion battery, Li-Ion, fire, extinguishing, suppression Type of article: review article
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.
Strategic Workforce Planning Under Uncertainty
Authors: Jaillet Patrick , Loke Gar Goei , Sim Melvyn
Published: December 2021

A new study in the INFORMS journal Operations Research proposes a data-driven model for conducting strategic workforce planning in organizations. The model optimizes for recruitment and promotions by balancing the risks of not meeting headcount, budget, and productivity constraints, while keeping within a prescribed organizational structure. Analysis using the model indicates that there are increased workforce risks faced by organizations that are not in a state of growth or organizations that face limitations to organizational renewal (such as bureaucracies).
Embedding Isolation, Contact Tracing, and Quarantine in Transmission Dynamics of the Coronavirus Epidemic—A Case Study of COVID-19 in Wuhan
Authors: Yu Miao , Hua Zhongsheng
Published: December 2021

Coronaviruses have caused multiple global pandemics. As an emerging epidemic, the coronavirus disease relies on nonpharmacological interventions to control its spread. However, the specific effects of these interventions are unknown. To evaluate their effects, we extend the susceptible–latent–infectious–recovered model to include suspected cases, confirmed cases, and their contacts and to embed isolation, close contact tracing, and quarantine into transmission dynamics. The model simplifies the population into two parts: the undiscovered part (where the virus spreads freely—the extent of freedom is determined by the strength of social distancing policy) and the discovered part (where the cases are incompletely isolated or quarantined). Through the isolation of the index case (suspected or confirmed case) and the subsequent tracing and quarantine of its close contacts, the infections flow from the undiscovered part to the discovered part. In our case study, multisource data of the novel coronavirus SARS-CoV-2 (COVID-19) in Wuhan were collected to validate the model, the parameters were calibrated based on the prediction of the actual number of infections, and then the time-varying effective reproduction number was obtained to measure the transmissibility of COVID-19 in Wuhan, revealing the timeliness and lag effect of the nonpharmacological interventions adopted there. Finally, we simulated the situation in the absence of a strict social distancing policy. Results show that the current efforts of isolation, close contact tracing, and quarantine can take the epidemic curve to the turning point, but the epidemic could be far from over; there were still 4,035 infected people, and 1,584 latent people in the undiscovered part on March 11, 2020, when the epidemic was actually over with a strict social distancing policy.
Resource Reconfiguration During Technological Change
Authors: Chaturvedi Tuhin , Prescott John E.
Published: December 2021

A central strategic imperative for surviving technological change requires firms to attenuate the inertia and rigidity imposed by its legacy technology orientation (defined as the relative emphasis placed on technological knowledge and products aligned to an incumbent technology) and successfully transition to a new technology. We theorize that resource reconfiguration through corporate scope decisions—alliances, acquisitions, divestitures, and different postacquisition integration approaches—enables firms to achieve the twin requirements of attenuation and transition. Initially, a legacy technology orientation exerts inertia due to legacy reinforcement—decreasing the likelihood of firms making new technology acquisitions and legacy technology divestitures. New technology alliances mitigate this inertia via legacy attenuation—increasing the likelihood of acquisitions and legacy divestitures. Finally, when firms make new technology acquisitions, we theorize that acquirers choosing partial acquisition integration approaches (partial integration and partial autonomy) are more likely to achieve a successful transition to the new technology-legacy transition and, thus, more likely to survive technological change relative to firms choosing full integration or full autonomy. Using a sample of firms from the digital camera product market over 1991–2006, we found strong empirical support for our predictions. We contribute to research on technological change by demonstrating that firms may overcome the inertia of a legacy technology orientation and adapt to an emerging new technology by employing corporate scope decisions and postacquisition integration as resource reconfiguration mechanisms. Specifically, we advance the novel finding that postacquisition integration is an important survival-enhancing mechanism that facilitates adaptation to technological change.
Spectroscopic second and third harmonic generation microscopy using a femtosecond laser source in the third near-infrared (NIR-III) optical window
Authors: Murakami Yusuke , Masaki Minori , Miyazaki Shinichi , Oketani Ryosuke , Hayashi Yu , Yanagisawa Masashi , Honjoh Sakiko , Kano Hideaki
Published: December 2021

In this study, second harmonic generation (SHG) and third harmonic generation (THG) spectroscopic imaging were performed on biological samples using a femtosecond laser source in the third near-infrared (NIR) optical window (NIR-III). Using a visible-NIR spectrometer, the SHG and THG signals were simultaneously detected and were extracted using spectral analysis. Visualization of biological samples such as cultured cells (HEK293 T), mouse brain slices, and the nematode Caenorhabditis elegans was performed in a label-free manner. In particular, in an SHG image of an entire coronal brain section (8 × 6 mm2), we observed mesh-like and filamentous structures in the arachnoid mater and wall of the cerebral ventricle, probably corresponding to the collagen fibers, cilia, and rootlet. Moreover, the THG images clearly depicted the densely packed axons in the white matter and cell nuclei at the cortex of the mouse brain slice sample and lipid-rich granules such as lipid droplets inside the nematode. The observations and conclusions drawn from this technique confirm that it can be utilized for various biological applications, including in vivo label-free imaging of living animals.
Computational framework for steady-state NLOS localization under changing ambient illumination conditions
Authors: Cao Yanpeng , Liang Rui , Yang Jiangxin , Cao Yanlong , He Zewei , Chen Jian , Li Xin
Published: December 2021

Non-line-of-sight (NLOS) imaging of hidden objects is a challenging yet vital task, facilitating important applications such as rescue operations, medical imaging, and autonomous driving. In this paper, we attempt to develop a computational steady-state NLOS localization framework that works accurately and robustly under various illumination conditions. For this purpose, we build a physical NLOS image acquisition hardware system and a corresponding virtual setup to obtain real-captured and simulated steady-state NLOS images under different ambient illuminations. Then, we utilize the captured NLOS images to train/fine-tune a multi-task convolutional neural network (CNN) architecture to perform simultaneous background illumination correction and NLOS object localization. Evaluation results on both stimulated and real-captured NLOS images demonstrate that the proposed method can effectively suppress severe disturbance caused by the variation of ambient light, significantly improving the accuracy and stability of steady-state NLOS localization using consumer-grade RGB cameras. The proposed method potentially paves the way to develop practical steady-state NLOS imaging solutions for around-the-clock and all-weather operations.
Ultra-precise determination of thicknesses and refractive indices of optically thick dispersive materials by dual-comb spectroscopy
Authors: Sumihara Kana A. , Okubo Sho , Okano Makoto , Inaba Hajime , Watanabe Shinichi
Published: December 2021

Precise measurements of the geometrical thickness of a sample and its refractive index are important for materials science, engineering, and medical diagnosis. Among the possible non-contact evaluation methods, optical interferometric techniques possess the potential of providing superior resolution. However, in the optical frequency region, the ambiguity in the absolute phase-shift makes it difficult to measure these parameters of optically thick dispersive materials with sufficient resolution. Here, we demonstrate that dual frequency-comb spectroscopy can be used to precisely determine the absolute sample-induced phase-shift by analyzing the data smoothness. This method enables simultaneous determination of the geometrical thickness and the refractive index of a planar sample with a precision of five and a half digits. The thickness and the refractive index at 193.414 THz (λ = 1550 nm) of a silicon wafer determined by this method are 0.5204737(19) mm and 3.475625(58), respectively, without any prior knowledge of the refractive index.
Nonlinear microscopy using impulsive stimulated Brillouin scattering for high-speed elastography
Authors: Krug Benedikt , Koukourakis Nektarios , Guck Jochen , Czarske Jürgen
Published: December 2021

The impulsive stimulated Brillouin microscopy promises fast, non-contact measurements of the elastic properties of biological samples. The used pump-probe approach employs an ultra-short pulse laser and a cw laser to generate Brillouin signals. Modeling of the microscopy technique has already been carried out partially, but not for biomedical applications. The nonlinear relationship between pulse energy and Brillouin signal amplitude is proven with both simulations and experiments. Tayloring of the excitation parameters on the biologically relevant polyacrylamide hydrogels outline sub-ms temporal resolutions at a relative precision of <1%. Brillouin microscopy using the impulsive stimulated scattering therefore exhibits high potential for the measurements of viscoelastic properties of cells and tissues.
Modeling CRISPR gene drives for suppression of invasive rodents using a supervised machine learning framework
Authors: Champer Samuel E. , Oakes Nathan , Sharma Ronin , García-Díaz Pablo , Champer Jackson , Messer Philipp W.
Published: December 2021

Invasive rodent populations pose a threat to biodiversity across the globe. When confronted with these invaders, native species that evolved independently are often defenseless. CRISPR gene drive systems could provide a solution to this problem by spreading transgenes among invaders that induce population collapse, and could be deployed even where traditional control methods are impractical or prohibitively expensive. Here, we develop a high-fidelity model of an island population of invasive rodents that includes three types of suppression gene drive systems. The individual-based model is spatially explicit, allows for overlapping generations and a fluctuating population size, and includes variables for drive fitness, efficiency, resistance allele formation rate, as well as a variety of ecological parameters. The computational burden of evaluating a model with such a high number of parameters presents a substantial barrier to a comprehensive understanding of its outcome space. We therefore accompany our population model with a meta-model that utilizes supervised machine learning to approximate the outcome space of the underlying model with a high degree of accuracy. This enables us to conduct an exhaustive inquiry of the population model, including variance-based sensitivity analyses using tens of millions of evaluations. Our results suggest that sufficiently capable gene drive systems have the potential to eliminate island populations of rodents under a wide range of demographic assumptions, though only if resistance can be kept to a minimal level. This study highlights the power of supervised machine learning to identify the key parameters and processes that determine the population dynamics of a complex evolutionary system.
Motif-pattern dependence of biomolecular phase separation driven by specific interactions
Authors: Weiner Benjamin G. , Pyo Andrew G. T. , Meir Yigal , Wingreen Ned S.
Published: December 2021

Eukaryotic cells partition a wide variety of important materials and processes into biomolecular condensates—phase-separated droplets that lack a membrane. In addition to nonspecific electrostatic or hydrophobic interactions, phase separation also depends on specific binding motifs that link together constituent molecules. Nevertheless, few rules have been established for how these ubiquitous specific, saturating, motif-motif interactions drive phase separation. By integrating Monte Carlo simulations of lattice-polymers with mean-field theory, we show that the sequence of heterotypic binding motifs strongly affects a polymer’s ability to phase separate, influencing both phase boundaries and condensate properties (e.g. viscosity and polymer diffusion). We find that sequences with large blocks of single motifs typically form more inter-polymer bonds, which promotes phase separation. Notably, the sequence of binding motifs influences phase separation primarily by determining the conformational entropy of self-bonding by single polymers. This contrasts with systems where the molecular architecture primarily affects the energy of the dense phase, providing a new entropy-based mechanism for the biological control of phase separation.
The automatic parameter-exploration with a machine-learning-like approach: Powering the evolutionary modeling on the origin of life
Authors: Liang Yuzhen , Yu Chunwu , Ma Wentao
Published: December 2021

The origin of life involved complicated evolutionary processes. Computer modeling is a promising way to reveal relevant mechanisms. However, due to the limitation of our knowledge on prebiotic chemistry, it is usually difficult to justify parameter-setting for the modeling. Thus, typically, the studies were conducted in a reverse way: the parameter-space was explored to find those parameter values “supporting” a hypothetical scene (that is, leaving the parameter-justification a later job when sufficient knowledge is available). Exploring the parameter-space manually is an arduous job (especially when the modeling becomes complicated) and additionally, difficult to characterize as regular “Methods” in a paper. Here we show that a machine-learning-like approach may be adopted, automatically optimizing the parameters. With this efficient parameter-exploring approach, the evolutionary modeling on the origin of life would become much more powerful. In particular, based on this, it is expected that more near-reality (complex) models could be introduced, and thereby theoretical research would be more tightly associated with experimental investigation in this field–hopefully leading to significant steps forward in respect to our understanding on the origin of life.
Patient-derived iPSCs link elevated mitochondrial respiratory complex I function to osteosarcoma in Rothmund-Thomson syndrome
Authors: Jewell Brittany E. , Xu An , Zhu Dandan , Huang Mo-Fan , Lu Linchao , Liu Mo , Underwood Erica L. , Park Jun Hyoung , Fan Huihui , Gingold Julian A. , Zhou Ruoji , Tu Jian , Huo Zijun , Liu Ying , Jin Weidong , Chen Yi-Hung , Xu Yitian , Chen Shu-Hsia , Rainusso Nino , Berg Nathaniel K. , Bazer Danielle A. , Vellano Christopher , Jones Philip , Eltzschig Holger K. , Zhao Zhongming , Kaipparettu Benny Abraham , Zhao Ruiying , Wang Lisa L. , Lee Dung-Fang
Published: December 2021

Rothmund-Thomson syndrome (RTS) is an autosomal recessive genetic disorder characterized by poikiloderma, small stature, skeletal anomalies, sparse brows/lashes, cataracts, and predisposition to cancer. Type 2 RTS patients with biallelic RECQL4 pathogenic variants have multiple skeletal anomalies and a significantly increased incidence of osteosarcoma. Here, we generated RTS patient-derived induced pluripotent stem cells (iPSCs) to dissect the pathological signaling leading to RTS patient-associated osteosarcoma. RTS iPSC-derived osteoblasts showed defective osteogenic differentiation and gain of in vitro tumorigenic ability. Transcriptome analysis of RTS osteoblasts validated decreased bone morphogenesis while revealing aberrantly upregulated mitochondrial respiratory complex I gene expression. RTS osteoblast metabolic assays demonstrated elevated mitochondrial respiratory complex I function, increased oxidative phosphorylation (OXPHOS), and increased ATP production. Inhibition of mitochondrial respiratory complex I activity by IACS-010759 selectively suppressed cellular respiration and cell proliferation of RTS osteoblasts. Furthermore, systems analysis of IACS-010759-induced changes in RTS osteoblasts revealed that chemical inhibition of mitochondrial respiratory complex I impaired cell proliferation, induced senescence, and decreased MAPK signaling and cell cycle associated genes, but increased H19 and ribosomal protein genes. In summary, our study suggests that mitochondrial respiratory complex I is a potential therapeutic target for RTS-associated osteosarcoma and provides future insights for clinical treatment strategies.
The relative abundance of languages: Neutral and non-neutral dynamics
Authors: Borda-de-Água Luís , Hubbell Stephen P.
Published: December 2021

Credible estimates suggest that a large number of the nearly 7000 languages in the world could go extinct this century, a prospect with profound cultural, socioeconomic, and political ramifications. Despite its importance, we still have little predictive theory for language dynamics and richness. Critical to the language extinction problem, however, is to understand the dynamics of the number of speakers of languages, the dynamics of language abundance distributions (LADs). Many regional LADs are very similar to the bell-shaped distributions of relative species abundance predicted by neutral theory in ecology. Using the tenets of neutral theory, here we show that LADs can be understood as an equilibrium or disequilibrium between stochastic rates of origination and extinction of languages. However, neutral theory does not fit some regional LADs, which can be explained if the number of speakers has grown systematically faster in some languages than others, due to cultural factors and other non-neutral processes. Only the LADs of Australia and the United States, deviate from a bell-shaped pattern. These deviations are due to the documented higher, non-equilibrium extinction rates of low-abundance languages in these countries.
Evaluating the impacts of non-pharmaceutical interventions on the transmission dynamics of COVID-19 in Canada based on mobile network
Authors: Xue Ling , Jing Shuanglin , Wang Hao
Published: December 2021

The COVID-19 outbreak has caused two waves and spread to more than 90% of Canada’s provinces since it was first reported more than a year ago. During the COVID-19 epidemic, Canadian provinces have implemented many Non-Pharmaceutical Interventions (NPIs). However, the spread of the COVID-19 epidemic continues due to the complex dynamics of human mobility. We develop a meta-population network model to study the transmission dynamics of COVID-19. The model takes into account the heterogeneity of mitigation strategies in different provinces of Canada, such as the timing of implementing NPIs, the human mobility in retail and recreation, grocery and pharmacy, parks, transit stations, workplaces, and residences due to work and recreation. To determine which activity is most closely related to the dynamics of COVID-19, we use the cross-correlation analysis to find that the positive correlation is the highest between the mobility data of parks and the weekly number of confirmed COVID-19 from February 15 to December 13, 2020. The average effective reproduction numbers in nine Canadian provinces are all greater than one during the time period, and NPIs have little impact on the dynamics of COVID-19 epidemics in Ontario and Saskatchewan. After November 20, 2020, the average infection probability in Alberta became the highest since the start of the COVID-19 epidemic in Canada. We also observe that human activities around residences do not contribute much to the spread of the COVID-19 epidemic. The simulation results indicate that social distancing and constricting human mobility is effective in mitigating COVID-19 transmission in Canada. Our findings can provide guidance for public health authorities in projecting the effectiveness of future NPIs.
Predictors of colorectal cancer survival using cox regression and random survival forests models based on gene expression data
Authors: Mohammed Mohanad , Mboya Innocent B. , Mwambi Henry , Elbashir Murtada K. , Omolo Bernard
Published: December 2021

Understanding and identifying the markers and clinical information that are associated with colorectal cancer (CRC) patient survival is needed for early detection and diagnosis. In this work, we aimed to build a simple model using Cox proportional hazards (PH) and random survival forest (RSF) and find a robust signature for predicting CRC overall survival. We used stepwise regression to develop Cox PH model to analyse 54 common differentially expressed genes from three mutations. RSF is applied using log-rank and log-rank-score based on 5000 survival trees, and therefore, variables important obtained to find the genes that are most influential for CRC survival. We compared the predictive performance of the Cox PH model and RSF for early CRC detection and diagnosis. The results indicate that SLC9A8, IER5, ARSJ, ANKRD27, and PIPOX genes were significantly associated with the CRC overall survival. In addition, age, sex, and stages are also affecting the CRC overall survival. The RSF model using log-rank is better than log-rank-score, while log-rank-score needed more trees to stabilize. Overall, the imputation of missing values enhanced the model’s predictive performance. In addition, Cox PH predictive performance was better than RSF.
Bias-corrected maximum-likelihood estimation of multiplicity of infection and lineage frequencies
Authors: Hashemi Meraj , Schneider Kristan A.
Published: December 2021

Background

The 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 findings

Based 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.

Conclusions

Applying 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.
HIV-1 Vpr protein upregulates microRNA-210-5p expression to induce G2 arrest by targeting TGIF2
Authors: Qiao Jialu , Peng Qian , Qian Feng , You Qiang , Feng Lingyan , Hu Song , Liu Wei , Huang Lixia , Shu Xiji , Sun Binlian
Published: December 2021

MicroRNAs (miRNAs) are important molecules that mediate virus-host interactions, mainly by regulating gene expression via gene silencing. Here, we demonstrated that HIV-1 infection upregulated miR-210-5p in HIV-1-inoculated cell lines and in the serum of HIV-1-infected individuals. Luciferase reporter assays and western blotting confirmed that a target protein of miR-210-5p, TGIF2, is regulated by HIV-1 infection. Furthermore, HIV-1 Vpr protein induced miR-210-5p expression. The use of a miR-210-5p inhibitor and TGIF2 overexpression showed that Vpr upregulated miR-210-5p and thereby downregulated TGIF2, which might be one of the mechanisms used by Vpr to induce G2 arrest. Moreover, we identified a transcription factor, NF-κB p50, which upregulated miR-210-5p in response to Vpr protein. In conclusion, we identified a mechanism whereby miR-210-5p, which is induced upon HIV-1 infection, targets TGIF2. This pathway was initiated by Vpr protein activating NF-κB p50, which promoted G2 arrest. These alterations orchestrated by miRNA provide new evidence on how HIV-1 interacts with its host during infection and increase our understanding of the mechanism by which Vpr regulates the cell cycle.
Damage evaluation and precursor of sandstone under the uniaxial compression: Insights from the strain-field heterogeneity
Authors: Cheng Hongming , Yang Xiaobin , Zhang Zewen , Li Wenlong , Ning Zhangxuan
Published: December 2021

The stress-induced microcrack evolution in rock specimens causes a series of physical changes and heterogeneous deformations. Some of these attributes (such as sound, electricity, heat, etc.) have been effectively used to identify the damage state and precursory information of the rock specimens. However, the strain-field heterogeneity has not been investigated previously. In this study, the relationship of the strain-field heterogeneity and damage evolution of three sandstone specimens under the uniaxial compressive load was analyzed statistically. The acoustic emission (AE) and two-dimensional digital image correlation were employed for real-time evaluation of the AE parameters and strain-field heterogeneity. The results showed that the strain-field heterogeneity was closely related to the rock damage that amplified with the applied stress, and exhibited two features; numerical difference and spatial concentration. Subsequently, these two features were characterized by the two proposed heterogeneous quantitative indicators (i.e., the degree and space heterogeneities). Further, their four transition processes were in agreement with the damage stages confirmed by AE parameters: a relatively constant trend; growth with a relatively constant rate; drastic increase trend; and increase with a high rate to maximum value. Moreover, a time sequence chain for damage precursor was built, where the heterogeneous quantitative indicators and AE parameters differed in sensitivity to microcrack development and can be used as a damage warning at the varying magnitude of the external load.
Cross-reactive and mono-reactive SARS-CoV-2 CD4+ T cells in prepandemic and COVID-19 convalescent individuals
Authors: Johansson Alexandra M. , Malhotra Uma , Kim Yeseul G. , Gomez Rebecca , Krist Maxwell P. , Wald Anna , Koelle David M. , Kwok William W.
Published: December 2021

Class II tetramer reagents for eleven common DR alleles and a DP allele prevalent in the world population were used to identify SARS-CoV-2 CD4+ T cell epitopes. A total of 112, 28 and 42 epitopes specific for Spike, Membrane and Nucleocapsid, respectively, with defined HLA-restriction were identified. Direct ex vivo staining of PBMC with tetramer reagents was used to define immunodominant and subdominant T cell epitopes and estimate the frequencies of these T cells in SARS-CoV-2 exposed and naïve individuals. Majority of SARS-CoV-2 epitopes identified have <67% amino acid sequence identity with endemic coronaviruses and are unlikely to elicit high avidity cross-reactive T cell responses. Four SARS-CoV-2 Spike reactive epitopes, including a DPB1*04:01 restricted epitope, with ≥67% amino acid sequence identity to endemic coronavirus were identified. SARS-CoV-2 T cell lines for three of these epitopes elicited cross-reactive T cell responses to endemic cold viruses. An endemic coronavirus Spike T cell line showed cross-reactivity to the fourth SARS-CoV-2 epitope. Three of the Spike cross-reactive epitopes were subdominant epitopes, while the DPB1*04:01 restricted epitope was a dominant epitope. Frequency analyses showed Spike cross-reactive T cells as detected by tetramers were present at relatively low frequency in unexposed people and only contributed a small proportion of the overall Spike-specific CD4+ T cells in COVID-19 convalescent individuals. In total, these results suggested a very limited number of SARS-CoV-2 T cells as detected by tetramers are capable of recognizing ccCoV with relative high avidity and vice versa. The potentially supportive role of these high avidity cross-reactive T cells in protective immunity against SARS-CoV-2 needs further studies.
Batik in Malaysia and Indonesia: A collaboration for reconciling issues of cultural heritage
Authors: Wahida Adam , Hendra Himawan Muhammad
Published: December 2021

Conflict claims for the cultural heritage of batik between Indonesia and Malaysia have created tensions between the people of these two countries. The Indonesian and Malaysian governments have never involved academics and arts education institutions in resolving such conflict claims, yet, these communities can play a significant role in post-conflict reconciliation efforts. This article describes a conflict reconciliation method initiated by academics, artists and art educators through a collaborative art project between art higher education institutions in Malaysia and Indonesia. Ways in which collaborations within and across the art and education communities may address the understanding and reconciliation of issues related to cultural heritage conflict are explored.
Pemodelan Sistem Karbonat di Laut Jawa
Authors: Koropitan Alan Frendy
Published: December 2021

Modeling Carbonate System in the Java Sea. Besides the global fossil fuel burning activities, forest fires in Kalimantan could potentially increase atmospheric CO2 concentrations, impacting air-sea CO2 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 CO2 flux in the Java Sea and their relationship to CO2 increase in the atmosphere. OCMIP-2 (Ocean Carbon-Cycle Model Intercomparison Model Project, Phase-2) 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 CO2 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 solubility pump is more significant than that of biological processes in carbon absorption. Moreover, increased CO2 in the atmosphere could alter the partial pressure equilibrium. In the case of 2002 forest fires (atmospheric CO2 = 460 ppm), the carbon source of the Java Sea was less than before forest fires and even became carbon sink when atmospheric CO2 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 CO2 levels rising in the atmosphere.
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

The Preference of The Sandfish Holothuria scabra on Macroalgae-Based Feed. The sandfish, Holothuria scabra, 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 (Padina sp.), FF-3 (Ulva sp.), FF-4 (Sargassum 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 Padina sp. (FF-2) had the highest average feed consumption of 0.51 gram/day. This value was significantly greater than the other treatments (p<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 Padina sp. is preferable for Holothuria scabra and has the potential to be further developed.
THE CONFUSING TAXONOMY AND NOMENCLATURE OF SYZYGIUM CONFUSUM COMPLEX (MYRTACEAE)
Authors: Widodo Pudji , Veldkamp Jan Frits
Published: December 2021

WIDODO, P. & VELDKAMP, J. F. 2021. The confusing taxonomy and nomenclature of Syzygiun confusum complex (Myrtaceae). Reinwardtia 20(2): 43‒49. ― The taxonomic and nomenclatural confusions surrounding the Syzygium confusum complex are elucidated. For that purpose, type specimens are designated and circumscriptions are presented for each species. Typifications, newly characterized descriptions and illustrations are presented for Syzygium korthalsii Widodo, S. confusum (Blume) Bakh.f., S. blumei (Steudel) Merr. & L.M.Perry, S. insigne (Blume) Merr. & L.M.Perry. The new species Syzygium sipirokense Widodo & Veldkamp is described.
A NEW SPECIES OF DEPARIA FROM NEW GUINEA
Authors: Wardani Wita , Jaenudin Jaenudin , Apandi Ismail , Kusumawaty Anne , Santoso Wahyudi
Published: December 2021

WARDANI, W., JAENUDIN, APANDI, I., KUSUMAWATY, A. & SANTOSO, W. 2021. A new species of Deparia from New Guinea. Reinwardtia 20(2): 57−61. — Deparia stellata is a new species of highland in Eastern New Guinea, described from a specimen found among unidentified piles of New Guinean Expedition in 1975. Its distinctive stellate-hairs on all axis and occasionally on rachis-scale margin are the main character that differentiate the species to other Deparia.
Incidence and Epidemiology of Thoracolumbar Spine Fractures: WFNS Spine Committee Recommendations
Authors: Zileli Mehmet , Sharif Salman , Fornari Maurizio
Published: December 2021

This review aims to search the epidemiology and incidence rates of thoracolumbar spine fractures. A systematic review of the literature of the last 10 years gave 586 results with “incidence,” and 387 results with “epidemiology,” of which 39 papers were analyzed. The review results were discussed and voted in 2 consensus meetings of the WFNS (World Federation of Neurosurgical Societies) Spine Committee. Out of 39 studies, 15 studies have focused on thoracolumbar trauma, remaining 24 studies have looked at all spine trauma. Most were retrospective in nature; few were prospective and multicenter. Some studies have focused on specific injuries. The annual incidence of TL fractures is about 30/100,000 inhabitants including osteoporotic fractures. There is a trend to increase the fractures in elderly population especially in developed countries, while an increase of motor vehicle accidents in developing countries. The mortality rate among male elderly patients is relatively high. The incidence of thoracolumbar spine fractures is increasing because of low-velocity falls in the elderly population. The main reasons are falls and traffic accidents. Learning the regional differences and some special forms of trauma such as extreme sports, war, and gunshot injuries will help the prevention of the thoracolumbar spine fractures.
Percutaneous Endoscopic Interbody Debridement and Fusion for Pyogenic Lumbar Spondylodiskitis: Surgical Technique and the Comparison With Percutaneous Endoscopic Drainage and Debridement
Authors: Lai Po-Ju , Wang Sheng-Fen , Tsai Tsung-Ting , Li Yun-Da , Chiu Ping-Yeh , Hsieh Ming-Kai , Kao Fu-Cheng
Published: December 2021

Objective: Surgical treatment of severe infectious spondylodiskitis remains challenging. Although minimally invasive percutaneous endoscopic drainage and debridement (PEDD) may yield good results in complicated cases, outcomes of patients with extensive structural damage and mechanical instability may be unsatisfactory. To address severe infectious spondylodiskitis, we have developed a surgical technique called percutaneous endoscopic interbody debridement and fusion (PEIDF), which comprises endoscopic debridement, bonegraft interbody fusion, and percutaneous posterior instrumentation.Methods: Outcomes of PEIDF in 12 patients and PEDD in 15 patients with infectious spondylodiskitis from April 2014 to July 2018 were reviewed retrospectively. Outcome were compared between 2 kinds of surgical procedures.Results: Patients in PEIDF group had significantly lower rate of revision surgery (8.3% vs. 58.3%), better kyphosis angle (-5.73° ± 8.74 vs. 1.07° ± 2.70 in postoperative; 7.09° ± 7.23 vs. 0.79° ± 4.08 in kyphosis correction at 1 year), and higher fusion rate (83.3% vs. 46.7%) than those who received PEDD.Conclusion: PEIDF is an effective approach for treating infectious spondylodiskitis, especially in patients with spinal instability and multiple medical comorbidities.