bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of climate change on stratification of a small, monomictic, temperate, karstic lake (Lake Kozjak, Croatia)
Authors: Šarović Kristina , Klaić Zvjezdana Bencetić 
Published: April 2023

Abstract
As delicate closed systems, lakes are extremely vulnerable to climate change. In this paper, we examine Lake Kozjak, Croatia, a small karstic, monomictic lake that belongs to the Plitvice Lake system. The Plitvice Lakes represent a special hydrogeological karstic phenomenon that is closely dependent on a delicate biochemical balance necessary for tufa formation. We apply a simple one-dimensional model for monomictic lakes, SIMO v.1.0, to predict the water temperature at Lake Kozjak in three future scenarios (RCP2.6, RCP4.5 and RCP8.5) for the period between 2006 and 2100. The model captures the seasonal stratification and deepening of the thermocline as well as convective mixing. The results show that the significant increase in the lake water temperature that is expected in the more pessimistic scenarios is not accompanied by significant stratification strengthening due to significant heating of not only the epilimnion but also the hypolimnion. However, significant lengthening of the stratification period is observed even for the most stringent scenario, RCP2.6.
Predicting phenotype to mechanotype relationships in cells based on intra-cellular signaling network
Authors: Katira Parag , Karabay Esra , Turnlund Amy , Grear Jessica , Fraley Stephanie 
Published: April 2023

Abstract
Cells originating from the same tissue can respond differently to external signals depending on the genotypic and phenotypic state of the cell and its local environment. We have developed a semi-quantitative-computational model to analyze the intracellular signaling network and its outcome in the presence of multiple external signals including growth factors, hormones, and extracellular matrix. We use this model to analyze the cell’s mechanical response to external stimuli and identify the key internal elements of the network that drive specific outcomes within the response space. The model is built upon the Boolean approach to network modeling, where the state of any given node is determined using the state of the connecting nodes and Boolean logic. This allows us to analyze the network behavior without the need to estimate all the various interaction rates between different cellular components. However, such an approach is limited in its ability to predict network dynamics and temporal evolution of the cell state. So, we introduce modularity in the model and incorporate dynamical aspects, mass-action kinetics, and chemo-mechanical effects on only certain transition rates within specific modules as required, creating a Boolean-Hybrid-Modular (BoHyM) signal transduction model. We present this model as a comprehensive, cell-type agnostic, user-modifiable tool to investigate how extra-and intra-cellular signaling can regulate cellular cytoskeletal components and consequently influence cell-substrate interactions, force generation, and migration. Using this tool, we show how slight changes in signaling network architectures due to phenotypic changes can alter cellular response to stress hormone signaling in an environment-dependent manner. The tool also allows isolating effector proteins driving specific cellular mechanical responses. Ultimately, we show the utility of the tool in analyzing transient chemo-mechanical dynamics of cells in response to time-varying chemical stimuli.
Ecological and evolutionary success in a parthenogenetic praying mantis: population genetics and reproductive strategy
Authors: Hurd Lawrence , Cooper Gregory J. , Cabe Paul R. 
Published: April 2023

Abstract
Brunneria borealis, a praying mantid endemic to North America, is wingless, and among more than 2400 worldwide is the only one consisting entirely of parthenogenetic females. In spite of the putative handicaps associated with low vagility and parthenogenetic reduction in genetic variation, this mantid is both abundant and widely distributed along the coastline of North America from eastern Texas to North Carolina. We sampled populations across the mantid’s geographic range to discover clues to its ecological and evolutionary success: (1) the specific genetic mechanism of parthenogenesis, and (2) reproductive output. We found no variation in the mitochondrial COI gene among specimens collected over the extensive geographic range, suggesting recent establishment of this range. Surprisingly, observed heterozygosity in nuclear DNA was higher than expected for most loci, and together with SNP data suggest automictic thelytoky with central fusion for populations originating recently from a single individual. Reproduction was remarkable for its long duration: oviposition of multiple oothecae from a single female (up to six oothecae over 56 days), and time between successive emergences of nymphs from individual oothecae (mean = 31.6+4.75 days) would spread out life history stages in a population, potentially mitigating low egg viability (mean = 14+4.0% of eggs hatched per ootheca) by ensuring survival in a seasonal environment with temporally irregular availability of suitable prey.
Distributed Out-of-Memory NMF on CPU/GPU Architectures
Authors: Boureima Ismael , Bhattarai Manish , Eren Maksim , Skau Erik , Romero Philip , Eidenbenz Stephan , Alexandrov Boian 
Published: April 2023

Abstract
We propose an efficient distributed out-of-memory implementation of the Non-negative Matrix Factorization (NMF) algorithm for heterogeneous high-performance-computing (HPC) systems. The proposed implementation is based on prior work on NMFk, which can perform automatic model selection and extract latent variables and patterns from data. In this work, we extend NMFk by adding support for dense and sparse matrix operation on multi-node, multi-GPU systems. The resulting algorithm is optimized for out-of-memory (OOM) problems where the memory required to factorize a given matrix is greater than the available GPU memory. Memory complexity is reduced by batching/tiling strategies, and sparse and dense matrix operations are significantly accelerated with GPU cores (or tensor cores when available). Input/Output (I/O) latency associated with batch copies between host and device is hidden using CUDA streams to overlap data transfers and compute asynchronously, and latency associated with collective communications (both intra-node and inter-node) is reduced using optimized NVIDIA Collective Communication Library (NCCL) based communicators. Benchmark results show significant improvement, from 32X to 76x speedup, with the new implementation using GPUs over the CPU-based NMFk. Good weak scaling was demonstrated on up to 4096 multi-GPU cluster nodes with approximately 25,000 GPUs when decomposing a dense 340 Terabyte-size matrix and an 11 Exabyte-size sparse matrix of density 10^{-6}.
Cancer- related protein profile of patient-derived and commercial glioblastoma cell lines exposed to Temozolomide
Authors: Wajdman Anna Maria Bielecka , Machnik Grzegorz , Linnebacher Michael , Linnebacher Christina , Obuchowicz Ewa 
Published: April 2023

Abstract
Purpose
Since recurrence is observed in almost all glioma patients deeper insight into mechanisms responsible for therapy resistance and identification of new biomarkers is urgently required.
In this study were analyzed differences in expression of 84 cancer- related proteins in three GBM cell lines: the commercial T98G cells and two patient-derived cell lines.
Materials and Methods
Influence of temozolomide (TMZ) on changes in proteins expression, cell morphology and migration was investigated. Analyzed lines were characterized by different remarkable plasticity of proteins expression and proteomic alterations induced by TMZ. Among 10 proteins expressed in all lines, 5 (Cathepsin b, FGF, Survivin, AXL, Osteopontin) were modulated by TMZ administration.
Results
As a result of TMZ exposition in both HROG02 and T98G cell lines proteins involved in chemoresistance and invasion (TIE-2, Thrombospondin) were detected. This suggests that TMZ promoted their malignant phenotype even further. In control culture (not subjected to TMZ) of HROG17 cells proteins involved in metabolism were strongly suppressed.
Conclusion
The presented data shed a new light on the immunometabolic profile of glioma proteome and its plasticity in response to Temozolomide interventions. Cathepsin b, FGF, Survivin, AXL and Osteopontin seem to be promising targets for a multimodal treatment that could be applied to inhibit GBM recurrence in the future.
Iron-oxide embemded lipid nanoparticles against ductal infiltration carcinoma as photodynamic therapy using red diode laser irradiation technique: Apoptosis , ferroptosis , EAC model
Authors: V sandhiya , K Senthilkumaran K , U Ubaidulla 
Published: April 2023

Abstract
The purpose of the current study is to examine the effectiveness of folic acid-tagged, PLGA/PEGylated iron oxide nanoparticles in overcoming multidrug resistance when used in PDT therapy. The raw medicine and produced nanoparticles were analysed using techniques like FTIR, DSC, XRD, TGA, and Raman spectra. The nanoparticles were produced using the emulsion solvent evaporation method, and they were examined using AFM, SEM, TEM, DLS, in-vitro release, in-vitro cytotoxicity analysis (MTT-assay), cell cycle analysis, in-vitro morphological alterations (PDT), in-vivo research, and other methods.The results of pre-formulation experiments showed that the drug and polymer are compatible, and the nano-formulation makes sure that the drug is well enclosed within the polymer matrix. According to the morphological examination, the nanoparticles had bilayer covering and were round and spherical in shape. Due to their capacity to incorporate into membranes and then translocate into cells where they affect a variety of cellular processes like mitochondrial respiration, ATP synthesis, and activity of drug efflux transporters, MTT-assay results show that PF68-loaded nanoparticles have a higher inhibition rate than other types. Cell cycle analysis research shows that when concentration increases, apoptosis initially increases, and necrosis then increases as concentration increases. According to an in-vitro photodynamic study, nanoparticles treated with lasers cause more cell death than nanoformulations do in a dose- and time-dependent manner. PDT therapy has greater anticancer activity than GANPs, according to an animal study. Conclusion: When compared to polyvinyl alcohol (PVA) loaded nanoparticles, the drug formulated as a nanocarrier with PF68 may have greater bioavailability and anticancer activity. PDT has been used as a co-therapy to ensure that tumour cells undergo morphological changes and to accelerate the rate of cell death. Finally, it was predicted that in the future, it would be a highly effective and well-thought-out treatment for breast cancer.
New Variable Precision Reduction Algorithm for Decision Tables
Authors: Li Xu , Xiao Hongping , Tang Jianguo 
Published: April 2023

Abstract

Variable precision reduction (VPR) and positive region reduction (PRR) are common definitions in attribute reduction. The compacted decision table is an extension of a decision table. In this paper, we propose another extension, called the weighted decision table. In both types of decision tables, VPR is defined, and the corresponding discernibility matrices for the PRR are proposed. Then, algorithms for obtaining the PRR from the discernibility matrices are presented. In both types of decision tables, the relationship between VPR and PRR is established by comparing the corresponding discernibility matrices. If the precision of the VPR meets the given conditions, then the PRR algorithms can be used to obtain the results after modifying some decision values in the decision tables. An analysis of the modification process of the decision values and the compression process of decision tables is used to propose a new algorithm for VPR in decision tables that ensures credibility. The effectiveness of the proposed algorithm was evaluated by an experimental comparison with existing VPR algorithms.
Forecasting infection fatality rate of COVID-19, Measuring the effciency of several hybrid models.
Authors: SEBA Djillali 
Published: April 2023

Abstract
The main goal of this study is to study a significant index in epidemiology, the daily infection fatality rate in COVID-19. To do this, we put into application several hybrid models. We use machine learning tools such as Support Vector Machine, Relevance Vector Machine, Random Forest , and statistical models such as ARIMA, BATS and exponential smoothing. We measure the models’ performance using RMSE, MSE, and MAE
Train rescheduling with the consideration of re-servicing during a severe disruption
Authors: Zhao Junduo , Li Haiying , Meng Lingyun , Luan Xiaojie 
Published: April 2023

Abstract
Train dispatching is critical for the punctuality and reliability of passenger transportation, especially in railway systems with ticketing reservations required. In such a system, e.g., the high-speed railway in China, the service frequency is usually low on most lines, and passengers often have very limited route options (no diversity and flexibility). In the presence of disruptions, e.g., segment blockage, trains services may be canceled due to insufficient infrastructure capacity, which can cause big troubles to passengers since they are very unlikely to find alternative, consequently being stranded. Thus, transporting these stranded passengers becomes the most important but complicated task. In this study, we propose to add extra stops to the running trains, i.e., re-servicing, in order to effectively utilize the reduced capacity of tracks. We identify and formulate the complex relation between track utilization, trains stop adding, and passenger rerouting, based on a time-space network. Local rerouting of trains is represented, and the tracks in each station are categorized by main track (stopping with no passenger activities) and siding track (train passing without a stop is not allowed). An integer linear programming (ILP) model is constructed to solve the integrated problem of train rescheduling and passenger rerouting with the consideration of re-servicing, which includes train cancelation and extra stop adding. Finally, a Lagrangian solution framework is introduced to solve the NP-hard problem, and the method is test on a real-world network of Chinese high-speed railway, conducting several experiments to demonstrate the reasonability, effectiveness, and efficiency of the proposed method.
Health risk assessment of trace elements in the Tonle Sap Great Lake and the Tonle Sap River in Cambodia during the rainy season
Authors: Phan Kongkea , Kim Kyoung-Woong 
Published: April 2023

Abstract

To investigate the potential health risk of trace elements in the Tonle Sap Great Lake system, lake (n = 37) and river (n = 14) water samples were collected and analyzed for 19 trace elements (Ag, Al, As, B, Ba, Cd, Co, Cr, Cu, Fe, Ga, Mn, Mo, Ni, Pb, Se, Tl, U and Zn) using inductively coupled plasma mass spectrometry. As a result, Cd was not detected in any river and lake water samples. Al, Fe and Mn in lake water exceeded the regulation limits of Cambodia, USEPA and WHO. Health risk assessment using the USEPA model indicated that male and female Cambodian residents are at minimal risk of non-carcinogenic effects from single and mixed trace elements through lake and river water consumption. Nevertheless, As, Tl, Co, Ba, Mn and Cr might pose high potential health risks to consumers which requires more attention. Therefore, regular monitoring and further studies are required to investigate the pollution trends and toxic behavior of these trace elements in the Tonle Sap Great Lake system.
Frequency and degradation of SARS-CoV-2 markers N1, N2, and E in sewage
Authors: Hart John J. , Jamison Megan N. , McNair James N. , Szlag David C. 
Published: April 2023

Abstract
Coronavirus disease 2019 (COVID-19) is an infectious disease that is mainly spread through aerosolized droplets containing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and is excreted in feces by infected individuals. Sewage surveillance has been applied widely to obtain data on the prevalence of COVID-19 in whole communities. We used SARS-CoV-2 gene targets N1, N2, and E to determine the prevalence of COVID-19 at both municipal and building levels. Frequency analysis of wastewater testing indicated that single markers detected only 85% or less of samples that were detected as positive for SARS-CoV-2 with the three markers combined, indicating the necessity of pairing markers to lower the false-negative rate. The best pair of markers in both municipal and building level monitoring was N1 and N2, which correctly identified 98% of positive samples detected with the three markers combined. The degradation rates of all three targets were assessed at two different temperatures (25 and 35 °C) as a possible explanation for observed differences between markers in frequency. Results indicated that all three RNA targets degrade at nearly the same rate, indicating that differences in degradation rate are not responsible for the observed differences in marker frequency.
Dynamic population normalisation in wastewater-based epidemiology for improved understanding of the SARS-CoV-2 prevalence: a multi-site study
Authors: Sweetapple Chris , Wade Matthew J. , Melville-Shreeve Peter , Chen Albert S. , Lilley Chris , Irving Jessica , Grimsley Jasmine M.S. , Bunce Joshua T. 
Published: April 2023

Abstract

Wastewater-based epidemiology (WBE) is a valuable tool for monitoring the circulation of COVID-19. However, while variations in population size are recognised as major sources of uncertainty, wastewater SARS-CoV-2 measurements are not routinely population-normalised. This paper aims to determine whether dynamic population normalisation significantly alters SARS-CoV-2 dynamics observed through wastewater monitoring, and whether it is beneficial or necessary to provide an understanding of COVID-19 epidemiology. Data from 394 sites in England are used, and normalisation is implemented based on ammoniacal nitrogen and orthophosphate concentrations. Raw and normalised wastewater SARS-CoV-2 metrics are evaluated at the site and spatially aggregated levels are compared against indicators of prevalence based on the Coronavirus Infection Survey and Test and Trace polymerase chain reaction test results. Normalisation is shown, on average, to have a limited impact on overall temporal trends. However, significant variability in the degree to which it affects local-level trends is observed. This is not evident from previous WBE studies focused on single sites and, critically, demonstrates that while the impact of normalisation on SARS-CoV-2 trends is small on average, this may not always be the case. When averaged across many sites, normalisation strengthens the correlation between wastewater SARS-CoV-2 data and prevalence indicators; however, confidence in the improvement is low.
Investigation of water utility efficiency features: production variables and the DEA model choices
Authors: Gidion Dickson K. 
Published: April 2023

Abstract
Data envelopment analysis (DEA) has been used for decades to investigate utility efficiency- and management-specific features. DEA has been extended in various industries with different models that consume different types of production variables to meet industry-specific efficiencies. However, the discernment of production variables and proper DEA models is still a problem in the water industry. Ratio information has been used in DEA for absolute data to assess utility efficiency- and management-specific features; using ratios in DEA for absolute data produces wrong efficiency results because the convexity axiom of DEA for absolute data is not satisfied. This study presents a collection of information and an assessment of DEA for absolute and ratio data to identify the strengths of the production variables and the DEA model that are appropriate for assessing utility efficiency- and management-specific features. The analysis shows that the use of ratio variables in DEA for ratios improves utility economics, the working environment, and the social trust dimension.
Fitoplancton de la zona litoral del departamento del Atlántico, Colombia
Authors: De la Parra-Guerra Ana C. , García-Alzate Carlos , Gutiérrez-Moreno (†) Luis C. 
Published: April 2023

Las comunidades biológicas están conformadas por grupos taxonómicos, donde el fitoplancton, como productor primario, tiene una relevancia ecológica: sirve para comprender la estructura y el funcionamiento de un ecosistema y la manera en la que los organismos interactúan con los parámetros fisicoquímicos. Con el fin de evaluar la riqueza y la abundancia del fitoplancton de la zona litoral del departamento del Atlántico y su asociación con las variables fisicoquímicas para conocer sus cambios espaciales y temporales, se realizaron monitoreos durante el año 2013. Se ubicaron cinco zonas a lo largo de la zona litoral como Astilleros, Santa Verónica, Puerto Velero, Puerto Colombia y Mallorquín. En cada una se establecieron tres estaciones, distribuidas en línea recta, con distancia entre ellas de 5 km. Para la recolecta de las muestras de fitoplancton y clorofila a (Cl-a), en cada una de las estaciones se filtraron 24 L de agua superficial, con un tambor cónico con malla de diámetro de poro de 24 µm y con botellas ámbar de 500 mL, respectivamente, las cuales se mantuvieron en oscuridad. Adicionalmente, se registraron in situ variables fisicoquímicas. Se identificaron un total de 560 cél.mL-1 de fitoplancton, agrupadas en 47 especies y cinco clases. Las Bacillariophyceae presentaron las mayores densidad y riqueza, seguidas de las Dinophyceae, Cyanophyceae, Euglenophyceae y Chlorophyceae. Chaetoceros sp. (83 cél.mL-1) y Chaetoceros lorenzianus (64 cél.mL-1) fueron las especies más abundantes y más representativas, precisamente por su abundancia. El análisis de Jaccard mostró una disimilitud de un 80 % entre las estaciones 5A, 5B y 5C, lo que indica una composición diferente. En general, las estaciones de monitoreo se comportaron como sitios contaminados con alta influencia de las aguas del río Magdalena.