Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal Experimental Design for Parameterization of an Electrochemical Lithium-Ion Battery Model

We consider the problem of optimally designing an excitation input for parameter identification of an electrochemical Li-ion battery model. The conventional approach to performing parameter identification uses standard test cycles. In contrast, we optimally design the input trajectory to maximize parameter identifiability in the sense of Fisher information. Specifically, we derive sensitivity equations for the electrochemical model. This approach enables parameter sensitivity analysis and optimal parameter fitting via gradient-based algorithms. This paper presents a general systematic approach to identify the electrochemical parameters in a non-invasive way. First, we group parameters into two sets: (i) equilibrium parameters, and (ii) dynamical parameters. We also divide the dynamical parameters into subsets by calculating orthogonalized sensitivity, which mitigates linear dependence between parameters. A large number of input profiles have been devised to constitute an input library. Then, the optimal inputs are selected from the input library to maximize the Fisher information, via convex programming. Using this framework a number of relevant experiments are obtained to parameterize. To validate our approach experimentally, we consider a 18650 Lithium nickel cobalt aluminum oxide battery. Compared to the conventional approach, our proposal achieves lower voltage RMSE across all experimental testing cycles. zE-mail: sspark@berkeley.edu
CMAR_A_312085 5113..5125

1Department of General Surgery, The Fourth Affiliated Hospital of the China Medical University, Shenyang, 110032, People’s Republic of China; 2China Medical University, Shenyang, 110000, People’s Republic of China Purpose: We aimed to screen novel genetic biomarkers for use in a prognostic score (PS) model for the accurate prediction of survival outcomes for patients with colon adenocarcinoma (COAD). Methods: Gene expression and methylation data were downloaded from The Cancer Genome Atlas database, and the samples were randomly divided into training and validation sets for the screening of differentially methylated genes (DMGs) and differentially expressed genes (DEGs). Co-methylated genes were screened using weighted gene co-expression network analysis. Functional enrichment analysis was performed using the Database for Annotation, Visualization, and Integrated Discovery. Univariate and multivariate Cox regression analyses were performed to identify prognosis-related genes and clinical factors. Receiver operating characteristic curve analysis was carried out to evaluate the predictive performance of the PS model. Results: In total, 1434 DEGs and 1038 DMGs were screened in the training set, among which 284 were found to be overlapping genes. For 127 of these overlapping genes, the methylation and expression levels were significantly negatively correlated. An optimal signature from 10 DMGs was identified to construct the PS model. Patients with a high PS seemed to have worse outcomes than those with a low PS. Moreover, cancer recurrence and the PS model status were independent prognostic factors. Conclusion: This PS model based on an optimal 10-gene signature would help in the stratification of patients with COAD and improve the assessment of their clinical outcomes.
Fed-agent – a Transparent ACID-Enabled Transactional Layer for Multidatabase Microservice Architectures

With the recent expansion of specialized databases and departure from the "one size fits all" paradigm, engineers might decide to use multiple databases. Each database holds a representation of a data object but offers transactions and consistency guarantees only locally. Existing solutions either require additional coding or do not provide global ACID transactions. In this paper, we present fed-agent, a transactional layer that provides global consistency and ACID transactions for single data objects within multidatabase systems. It requires no additional coding besides configuration files. We show that fed-agent scales linearly and introduces an overhead small enough for most microservice solutions.
Biomimetic material functionalized mixed matrix membranes for enhanced carbon dioxide capture

Carbonic anhydrase (CA) has been widely used in gas separation membranes because of its high affinity for CO2 molecules. In this work, a novel biomimetic material (Co-2,6-bis(2-benzimidazolyl)pyridine, CoBBP) which has a similar molecular structure to the CA enzyme but with higher stability and a lower price was successfully synthesized. The excellent thermal stability, dispersibility and high CO2 selectivity make CoBBP a promising alternative to CA. Then, a series of Pebax–CoBBP mixed matrix membranes were constructed to explore their capability for CO2/N2 separation. Compared to the pristine Pebax-1657, the Pebax–CoBBP mixed matrix membrane with the optimized 1.33 wt% CoBBP loading showed an improved CO2 permeability of 675.5 barrer and a CO2/N2 selectivity of 62, surpassing the Robeson upper bound (2008). Furthermore, the hydrogen bonds between CoBBP and polyamide chains improved the chain stiffness of the linear glassy polymer, ensuring good operational mechanical stability. In short, this work could provide a promising method to exploit alternatives to the CA enzyme and to fabricate biomimetic membranes.
When Does Data Sharing Promote Innovation?

Many innovations today are data-driven, such as self-driving cars. To improve the algorithms of these products, firms make substantial investments in data collection. However, the data is limited for an individual firm, which caps the benefits of the algorithms. Therefore, companies and policymakers ponder whether data collected by individual competing firms should be shared. More specifically, we ask the following three questions. First, when do firms voluntarily share their data? Second, if governments were to regulate data sharing, when would they mandate or prohibit data sharing to promote innovation? Third, when are firms and governments (mis)aligned in their data sharing decisions? Using a game-theoretic model, we identify two key factors that determine the answers to the questions: (i) the degree of complementarity or substitutability among firms' datasets and (ii) the performance uncertainty of the innovation. Overall, our analysis offers guidance to governments on when and how to regulate data sharing. Specifically, governments should mandate (respectively, prohibit) data sharing when firms' datasets are complements (respectively, substitutes) and the performance uncertainty is moderate (respectively, high). Our findings also shed light on several recent developments, such as the new antitrust law proposals by governments to regulate data markets.
Reactive nitrogen fluxes over peatland and forest ecosystems using micrometeorological measurement techniques

Abstract. Interactions of reactive nitrogen (Nr) compounds between the atmosphere and the earth's surface play a key role in atmospheric chemistry and in understanding nutrient cycling of terrestrial ecosystems. While continuous observations of inert greenhouse gases through micrometeorological flux measurements have become a common procedure, information about temporal dynamics and longer-term budgets of Nr compounds is still extremely limited. Within the framework of the research projects NITROSPHERE and FORESTFLUX, field campaigns were carried out to investigate the biosphere-atmosphere exchange of selected Nr compounds over different land surfaces. The aim of the campaigns was to test and establish novel measurement techniques in eddy-covariance setups for continuous determination of surface fluxes of ammonia (NH3) and total reactive nitrogen (∑Nr) using two different analytical devices. While high-frequency measurements of NH3 were conducted with a quantum cascade laser (QCL) absorption spectrometer, a custom-built converter called Total Reactive Atmospheric Nitrogen Converter (TRANC) connected and operated upstream of a chemiluminescence detector (CLD) was used for the measurement of ∑Nr. As high-resolution data of Nr surface-atmosphere exchange are still scarce, but highly desired for testing and validating local inferential and larger scale models, we provide access to campaign data including concentrations, fluxes, and ancillary measurements of meteorological parameters. Campaigns (n = 4) were carried out in natural (forest) and semi-natural (peatland) ecosystem types. The published datasets stress the importance of recent advancements in laser spectrometry and help improve our understanding of the temporal variability of surface-atmosphere exchange in different ecosystems, thereby providing validation opportunities for inferential models simulating the exchange of reactive nitrogen. The dataset has been placed in the Zenodo repository (http://doi.org/10.5281/zenodo.4513854; Brümmer et al., 2021) and contains individual data files for each campaign.
Easy3D: a lightweight, easy-to-use, and efficient C++ library for processing and rendering 3D data

Easy3D is an open-source library for 3D modeling, geometry processing, and rendering. It is implemented in C++ and designed with an emphasis on simplicity (i.e., processing and visualizing 3D data can be achieved by few lines of API calls). The contributions of Easy3D are threefold: (1) efficient data structures for representing common 3D data (i.e., point clouds, surface meshes, polyhedral meshes, and graphs), (2) commonly used algorithms for processing 3D data, and (3) standard techniques for the visualization of 3D data. The data structures, geometry processing algorithms, and rendering techniques can be seamlessly and easily integrated for the fast development of research prototypes or 3D applications. Figure 1 and Figure 2 show overviews of the data structures and rendering functionalities respectively provided by Easy3D.
Characterisation of the Manchester Aerosol Chamber facility

Abstract. This study describes the design of the Manchester Aerosol Chamber (MAC) and its comprehensive characterisation. The MAC is designed to investigate multi-phase chemistry and the evolution of aerosol physico-chemical properties from the real-world emissions (e.g. diesel engine, plants) or of secondary organic aerosol (SOA) produced from pure volatile organic compounds (VOCs). Additionally, the generated aerosol particles in MAC can be transferred to the Manchester Ice Cloud Chamber (MICC), which enables investigation of cloud formation in warm, mixed-phase and fully glaciated conditions (with T as low as −55 °C). MAC is an 18 m3 FEP Teflon chamber, with the potential to conduct experiments at controlled temperature (15–35 °C) and relative humidity (25–80 %) under simulated solar radiation or dark conditions. Detailed characterisations were conducted at common experimental conditions (25 °C, 50 % RH) for actinometry and determination of background contamination, wall losses of gases (NO2, O3, and selected VOCs), aerosol particles at different sizes, auxiliary mechanism and aerosol formation. In addition, the influences of chamber contamination on the wall loss rate of gases and particles, and the photolysis of NO2 were estimated.
FIBO: A New Approach to Measuring Intercity Differences in Housing Costs

Intercity housing price indexes that rely on median house price or pooled hedonic regressions adjust imperfectly for differences in housing characteristics. Single equation hedonic methods produce estimates of intercity differences that vary substantially with the specific cities in the regression, the sample sizes from each city, and/or the housing characteristics used. To mitigate these shortcomings, we create intercity housing price indexes for both rental and asset prices, which is a Fisher Ideal aggregation of a two-way Blinder-Oaxaca decomposition, the FIBO index. Our method improves upon current house price indexes because it is far less influenced by the cities studied, sample sizes from each city, and housing characteristics included. We also find, as predicted by Carrillo and Yezer (2021), that asset prices substantially overstate variation in rental prices across cities.
Analysis of the Complete Genomes of Enterovirus 71 Subtypes in China

Enterovirus 71 (EV-A71) is one of the most pathogens to hand, foot, and mouth disease (HFMD) as well as neurological complications in young children. Molecular characteristic of EV-A71 is important to prevent the virus outbreak. Here, the complete genomes of EV-A71 from China between 1998 and 2019 were downloaded from GenBank. The phylogenetic trees were developed by MEGA7.0 software, and the complete genetic epidemiological characteristics and amino acid mutations of EV-A71 from China were also analysed. The results showed that major epidemic EV-A71 subtype was C4b before 2004, while it turned to C4a after 2004 in mainland China, and C4 and B5 were major subtypes in Taiwan. VP1, VP4, 2C, 3C, 3D, and complete genome sequence can be used for virus genotyping, and VP1, VP4, and complete genomes have obvious advantages over other segments. There were many significant mutations in the viral complete genome sequence. This study indicated that the major C4 and B5 subtypes will contribute to the development of vaccines and drugs of EV-A71 for prevention and monitoring of EV-A71-associated HFMD in China.
The competitiveness analysis of shallot in Indonesia: A Policy Analysis Matrix

Shallot is a national strategic commodity in Indonesia, but it is development has a fundamental technical, socioeconomic, and policy support problems. Therefore, it is essential to know the competitiveness of shallot in Indonesia and the incentive policy to implement the comparative advantage to become a sustainable competitive advantage. The purposes of this study are to (1) analyze the profitability of shallot farming privately and socially, (2) analyze the competitiveness of shallot farming from a competitive and comparative advantage perspective, (3) review the impact of government policy on shallot farming, and (4) formulate incentive policies in the development of shallot commodities. The empirical results of the Policy Analysis Matrix revealed that shallot farming in production centers in Indonesia has both competitive and comparative advantages. The highest competitive and comparative advantages were found in the dry season in the upland of Malang district with the coefficient values of PCR (Private Cost Ratio) of 0.268–0.508 and DRCR (Domestic Resource Cost Ratio) of 0.208–0.323. The lowest competitive advantage was found in the lowland of East Lombok district in the dry season with a coefficient value of PCR 0.728–0.844. The lowest comparative advantage in the dry season was found in East Lombok district with a DRCR of 0.448, while in the rainy season, it was found in Wonosobo district with a DRCR of 0.522. These results mean that it is more profitable for Indonesia to increase domestic shallot production than to import. Improving shallot competitiveness can be carried out by implementing advanced technology, agricultural infrastructure, capacity building of farmers’ resources, and government incentive policies to increase productivity and competitiveness sustainability.
Downregulation of LINC02615 Is Correlated with The Breast Cancer Progress: A Novel Biomarker for Differential Identification of Breast Cancer Tissues

Objective Breast cancer is one of the most frequent types of cancer with a gradually increasing incidence in developing countries. The aim of this study was to assess modulation of LINC02615 levels in breast cancer progress, using pairwise breast cancer and healthy control tissue samples with regard to the obesity and other conditions, as estrogen receptor (ER) expression. Materials and Methods In this cohort study, the genes, microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) in several important pathways of chromosomal instability, apoptosis and proliferation were analyzed through in silico studies pinpointing the important genes which were responsible for the breast cancer incidence. Then, the respective miRNAs and lncRNAs were selected by relevant databases. At the next step, Lncbase was used for interaction analysis of selected miRNAs and LncRNAs, which resulted in final selection of LINC02615. Total RNA was isolated from 24 pairwise breast cancer and healthy control tissue samples. Expression profile of LINC02615 was assessed using quantitative reverse transcription polymerase chain reaction (qRT-PCR). Correlation between LINC02615 expression and clinicopathological characteristics were analyzed using Pearson’s Chi-square test in breast cancer patients. Results Data demonstrated that expression of LINC02615 was significantly downregulated in breast cancer tissues compared to the healthy controls (P=0.046). In particular, the relative LINC02615 expression was significantly different in breast cancer tissues especially in obese patients compared to those persons without obesity (P=0.047). Furthermore, a significant difference in LINC02615 level was found between the high and low ER expressions (P=0.014). However, the aberrant expression of LINC02615 was significantly related to physical activity and diabetes disease as well as the stress and age at menopause (P=0.028, P=0.046, P=0.047 and P=0.025, respectively). Conclusion Taken together, we suggest that LINC02615 downregulation may be related to the risk of breast cancer in Iranian patients. Thus, it may serve as a novel biomarker for identification of breast cancer tissues.
COVID-19 and Long-Term Care: the Essential Role of Family Caregivers

Background Those most at risk from severe COVID-19 infection are older adults; therefore, long-term care (LTC) facilities closed their doors to visitors and family caregivers (FCGs) during the initial wave of the COVID-19 pandemic. The most common chronic health condition among LTC residents is dementia, and persons living with dementia (PLWD) rely on FCGs to maintain their care provision. This study aims to evaluate the impact of visitor restrictions and resulting loss of FCGs providing in-person care to PLWD in LTC during the first wave of the COVID-19 pandemic. Method An online survey and follow-up focus groups were conducted June to September 2020 (n=70). Mixed quantitative (descriptive statistics) and qualitative (thematic analysis) methods were used to evaluate study data. Results FCGs were unable to provide in-person care and while alternative communication methods were offered, they were not always effective. FCGs experienced negative outcomes including social isolation (66%), strain (63%), and reduced quality of life (57%). PLWD showed an increase in responsive behaviours (51%) and dementia progression. Consequently, 85% of FCGs indicated they are willing to undergo specialized training to maintain access to their PLWD. Conclusion FCGs need continuous access to PLWD they care for in LTC to continue providing essential care.
Founder Team Prior Work Experience - An Asset or a Liability for Startup Growth?

We examine the effects of founder teams' firm- and industry prior work experience on startup growth in the context of high technology industries. We study these effects both on the early growth of startups and on their growth, after accumulating experiential knowledge. Integrating the literatures on human capital, imprinting and competency traps, we develop a typology of four combinations of founder prior experience: founder same firm and same industry experience, founder same industry but other firm experience, founder same firm but other-industry experience, and founder other-industry and other firm experience. Using data from 153 Israeli high technology startups, we find significant variations in the effects of these combinations on startup growth, which also vary between the early and later years of these startups.
Classification of soybean frogeye leaf spot disease using leaf hyperspectral reflectance

In this study, the feasibility of classifying soybean frogeye leaf spot (FLS) is investigated. Leaf images and hyperspectral reflectance data of healthy and FLS diseased soybean leaves were acquired. First, image processing was used to classify FLS to create a reference for subsequent analysis of hyperspectral data. Then, dimensionality reduction methods of hyperspectral data were used to obtain the relevant information pertaining to FLS. Three single methods, namely spectral index (SI), principal component analysis (PCA), and competitive adaptive reweighted sampling (CARS), along with a PCA and SI combined method, were included. PCA was used to select the effective principal components (PCs), and evaluate SIs. Characteristic wavelengths (CWs) were selected using CARS. Finally, the full wavelengths, CWs, effective PCs, SIs, and significant SIs were divided into 14 datasets (DS1–DS14) and used as inputs to build the classification models. Models’ performances were evaluated based on the classification accuracy for both the overall and individual classes. Our results suggest that the FLS comprised of five classes based on the proportion of total leaf surface covered with FLS. In the PCA and SI combination model, 5 PCs and 20 SIs with higher weight coefficient of each PC were extracted. For hyperspectral data, 20 CWs and 26 effective PCs were also selected. Out of the 14 datasets, the model input variables provided by five datasets (DS2, DS3, DS4, DS10, and DS11) were more superior than those of full wavelengths (DS1) both in support vector machine (SVM) and least squares support vector machine (LS-SVM) classifiers. The models developed using these five datasets achieved overall accuracies ranging from 91.8% to 94.5% in SVM, and 94.5% to 97.3% in LS-SVM. In addition, they improved the classification accuracies by 0.9% to 3.6% (SVM) and 0.9% to 3.7% (LS-SVM).
Role of Endocytosis Pathways in Electropermeablization of MCF7 Cells Using Low Voltage and High Frequency Electrochemotherapy

Objective The cell membrane is a major barrier for delivery of hydrophilic drugs and molecules into the cells. Although low voltage and high frequency electric fields (LVHF) are proposed to overcome the cell membrane barrier, the mechanism of membrane permeabilization is unclear. The aim of study is to investigate endocytosis pathways as a possible mechanism for enhancing uptake of bleomycin by LVHF. Materials and Methods In this experimental study, MCF-7 cells were exposed to bleomycin or to electric fields with various strengths (10-80 V/cm), frequency of 5 kHz, 4000 electric pulse and 100 µs duration in the presence and absence of three endocytosis inhibitors-chlorpromazine (Cpz), amiloride (Amilo) and genistein (Geni). We determined the efficiency of these chemotherapeutic agents in each group. Results LVHF, depending on the intensity, induced different endocytosis pathways. Electric field strengths of 10 and 20 V/cm stimulated the macropinocytosis route. Clathrin-mediated endocytosis was observed at electric field intensities of 10, 30, 60 and 70 V/cm, whereas induction of caveolae-mediated endocytosis was observed only at the lowest electric field intensity (10 V/cm). Conclusion The results of this study imply that LVHF can induce different endocytosis pathways in MCF-7 cells, which leads to an increase in bleomycin uptake.