Miracle-dz/UniFAR-FTUs huggingface dataset:
Temporary-Permanent Workers’ Wage Gap across the Wage Distribution: A Simple Comment on the Use of a Linear Probability Model Instead of a Binary Probability Model when using Unconditional Quantile Regression with Individual Fixed-Effects

In order to estimate the temporary-permanent workers’ wage gap which is caused by the difference in contract types across the marginal wage distribution with controlling for individual unobserved heterogeneity, recent studies applied UQR (unconditional quantile regression) with individual FE (fixed-effects). Since, as a dependent variable, UQR uses the RIF (recentered influence function) which has a binary outcome, UQR is a BPM (binary probability model) that has a theoretical interest in the effects on a latent dependent variable which is continuous. Based on the empirical results of Firpo et al. (2009) and the widely held belief that a LPM (linear probability model) well approximates a BPM, subsequent studies have generally used a LPM instead of a BPM. In the case of controlling for individual FE, linear FE regression and logistic FE regression can be used for a LPM and a BPM, respectively. However, these two regressions have a critical difference that individuals having no longitudinal variation in the RIF are excluded in logistic FE regression and not in linear FE regression. In a strict sense, however, individuals having no longitudinal variation in the RIF have to be excluded from the sample because the partial effects of explanatory variables on a latent continuous dependent variable are not non-existent but just not identified in these individuals. By analyzing panel data of South Korea, I find that the inclusion of individuals having no longitudinal variation in the RIF substantially underestimates both the temporary-permanent wage gap and the confidence interval of that, especially at the extreme quantiles. Even so, if the aim of the study is to just use the within-variance and not to strictly control for individual FE based on the binary choice model, it could be possible to include individuals having no longitudinal variation in a dependent variable in the analysis.
Ectomycorrhizal Fungi on South Kalimantan Serpentine Soil

Serpentine soil contains highly heavy metals, such as manganese, chromium, cobalt, and nickel,which could bean inappropriate growthmediaofmostplants. Someplants thatfound able to grow optimally on South Kalimantan serpentine soil have been known to do association with ectomycorrhizal fungi. This research aimed to obtain and characterize mushrooms assumed as ectomycorrhizal fungi indigenous South Kalimantan serpentine soil. This study used field exploration of fungal fruiting bodies and identified the genus based on morphological characters of fruiting bodies such as shape, size, and ornamentation, which are unique for the genus identification, then compared the characteristics on mushroomexpert.com. The mushrooms were also confirmed of genera assumed as ectomycorrhizal fungi based on mycorrhizas.info. Seven fruiting bodies were obtained and classified as Cantharellus (Ct), Chlorophyllum (Ch1 and Ch2), Lycoperdon (Ly), Ramaria (Rm1 and Rm2), and Thelephora (Tp). The results showed that all of those fruiting bodies belong to Basidiomycetes. There were 4 genera of Cantharellus, Lycoperdon, Ramaria, and Thelephora, assumed as ectomycorrhizal fungi. But Chlorophyllum genus was never reported as ectomycorrhizal fungus
Efficient incident identification from multi-dimensional issue reports via meta-heuristic search

In large-scale cloud systems, unplanned service interruptions and outages may cause severe degradation of service availability. Such incidents can occur in a bursty manner, which will deteriorate user satisfaction. Identifying incidents rapidly and accurately is critical to the operation and maintenance of a cloud system. In industrial practice, incidents are typically detected through analyzing the issue reports, which are generated over time by monitoring cloud services. Identifying incidents in a large number of issue reports is quite challenging. An issue report is typically multi-dimensional: it has many categorical attributes. It is difficult to identify a specific attribute combination that indicates an incident. Existing methods generally rely on pruning-based search, which is time-consuming given high-dimensional data, thus not practical to incident detection in large-scale cloud systems. In this paper, we propose MID (Multi-dimensional Incident Detection), a novel framework for identifying incidents from large-amount, multi-dimensional issue reports effectively and efficiently. Key to the MID design is encoding the problem into a combinatorial optimization problem. Then a specific-tailored meta-heuristic search method is designed, which can rapidly identify attribute combinations that indicate incidents. We evaluate MID with extensive experiments using both synthetic data and real-world data collected from a large-scale production cloud system. The experimental results show that MID significantly outperforms the current state-of-the-art methods in terms of effectiveness and efficiency. Additionally, MID has been successfully applied to Microsoft's cloud systems and helped greatly reduce manual maintenance effort.
Characterization of the complete chloroplast genome of Tulipa iliensis (Liliaceae)

Abstract The chloroplast genome and evolutionary relationship analysis of Tulipa gesneriana L. could provide fundamental genetic reference for its molecular breeding and biological research. The complete chloroplast genome of Tulipa iliensis was sequenced and reported here. Its chloroplast genome was 151,744 bp in length, containing a pair of inverted repeated regions (26,354 bp) which were separated by a large single copy region of 81,794 bp, and a small single copy region of 17,242 bp. Moreover, a total of 133 functional genes were annotated, including 87 mRNA, 38 tRNA genes, and 8 rRNA genes.The phylogenetic relationships of 16 species indicated that T. iliensis was closely related to T. altaica.
Identification of compounds that rescue otic and myelination defects in the zebrafish adgrg6 (gpr126) mutant

Adgrg6 (Gpr126) is an adhesion class G protein-coupled receptor with a conserved role in myelination of the peripheral nervous system. In the zebrafish, mutation of adgrg6 also results in defects in the inner ear: otic tissue fails to down-regulate versican gene expression and morphogenesis is disrupted. We have designed a whole-animal screen that tests for rescue of both up- and down-regulated gene expression in mutant embryos, together with analysis of weak and strong alleles. From a screen of 3120 structurally diverse compounds, we have identified 68 that reduce versican b expression in the adgrg6 mutant ear, 41 of which also restore myelin basic protein gene expression in Schwann cells of mutant embryos. Nineteen compounds unable to rescue a strong adgrg6 allele provide candidates for molecules that interact directly with the Adgrg6 receptor. Our pipeline provides a powerful approach for identifying compounds that modulate GPCR activity, with potential impact for future drug design.
A Learning Variable Neighborhood Search Approach for Induction Machines Bearing Failures Detection and Diagnosis

This paper proposes a three-phase metaheuristic-based approach for induction machine bearing failure detection and diagnosis. It consists of extracting and processing different failure types features to set up a knowledge base, which contains different failure types. The first phase consists in pre-processing the measured signals by aggregating them and preparing the data in exploitable formats for the clustering. The second phase ensures the induction machine operating mode diagnosis. A measured signals clustering is performed to build classes where each one represents a health state. A variable neighborhood search (VNS) metaheuristic is designed for data clustering. Moreover, VNS is hybridized with a classical mechanics-inspired optimization (CMO) metaheuristic to balance global exploration and local exploitation during the evolutionary process. The third phase consists of two-step failure detection, setting up a knowledge base containing different failure types, and defining a representative model for each failure type. In the learning step, different class features are extracted and inserted in the knowledge base to be used during the decision step. The proposed metaheuristic-based failure detection diagnosis approach is evaluated using PRONOSTIA and CWR bearing data experimental platforms vibration and temperature measurements. The achieved results clearly demonstrate the failure detection and diagnosis, efficiency, and effectiveness of the proposed metaheuristic approach.
Genetic Basis of Thermal Divergence in Saccharomyces species

The genetic architecture of phenotypic divergence is a central question in evolutionary biology. Genetic architecture is impacted by whether evolution occurs through accumulation of many small-effect or a few large-effect changes, the relative contribution of coding and cis-regulatory changes, and the prevalence of epistatic effects. Our empirical understanding of the genetic basis of evolutionary change remains incomplete, largely because reproductive barriers limit genetic analysis to those phenotypes that distinguish closely related species. In this dissertation, I use hybrid genetic analysis to examine the basis of thermal divergence between two post-zygotically isolated species, Saccharomyces cerevisiae and S. uvarum. S. cerevisiae is relatively heat tolerant, whereas S. uvarum is heat sensitive but outperforms S. cerevisiae at 4 degree C. Gene expression analysis with an S. cerevisiae and S. uvarum hybrid revealed a small set of 136 genes with temperature-dependent cis-acting differences, suggesting that the temperature divergence has not caused widespread cis-regulatory divergence. Using a genome-wide non-complementation screen, I found a single nuclear-encoded gene with a modest contribution to heat tolerance, and a large effect of the species' mitochondrial DNA (mitotype). Recombinant mitotypes and allele replacements indicate multiple mitochondria-encoded genes contribute to thermal divergence, with the coding sequence of COX1 showing a moderate effect on both heat and cold tolerance. The non-complementation approach also identified allele differences of CUP2, a copper-binding transcription factor, in copper resistance of S. cerevisiae and S. uvarum. Chimeric alleles showed that multiple changes underlie the resistance of S. cerevisiae CUP2, with cis-regulatory changes having a larger effect than coding changes. Taken together, my findings suggest that evolution of interspecific phenotypic differences often involves accumulation of small-to-medium effect changes, such as those in mitochondrial DNA and CUP2, and can occur through both coding and cis-regulatory changes.
Parametric Degradation Model with Multiple Competing Risks

Abstract The paper considers a particular degradation and failure time model with multiple failure modes. It provides a review of the nonparametric estimator of survival function in a specific statistical degradation model, studied by Bagdonavicius et al. [2], and also proposes the parametric estimator of survival function supposing the dependency of traumatic failure intensities on the degradation level. In addition, real tire wear and failure time data are analyzed and the comparison of both parametric and nonparametric methods according to the simulation is discussed.
Physical, frictional and thermal properties of turmeric rhizomes

It is important to study the engineering properties to design the dryers. The present investigation aimed to design a rotary dryer, so that some physical and thermal properties of fresh and dried turmeric rhizomes of PTS 10 variety were studied with a moisture content range between 410 to 7% (d.b.). The size of the turmeric decreased as the moisture decreased from 410 to 7% (d.b.). The bulk and true density was decreased with decrease in moisture content. The porosity was increased from 39.14 o ± 1.16 to 46.34° ± 3.5 with decrease in moisture content. The coefficient of friction of turmeric rhizomes was decreased as the moisture content decreased. The thermal conductivity and specific heat was decreased from 0.2532 to 0.13 W m K and 3.9 to 1.01 kJ kgK, respectively whereas the thermal diffusivity increased from 9.26 x 10 to 1.9 x 10 ms as the moisture content decreases.
Evolution of Phototransduction Genes in Lepidoptera

Vision is underpinned by phototransduction, a signaling cascade that converts light energy into an electrical signal. Among insects, phototransduction is best understood in Drosophila melanogaster. A survey of phototransduction genes in four insect genomes found gains and losses between D. melanogaster and other insects; this study did not include lepidopterans. Diurnal butterflies and nocturnal moths occupy different light environments and have distinct eye morphologies, which might impact the expression of their phototransduction genes. Here, we used transcriptomics and phylogenetics to identify phototransduction genes that vary between D. melanogaster and Lepidoptera, and between moths and butterflies. Most phototransduction genes were conserved between D. melanogaster and Lepidoptera, with some exceptions. We found two lepidopteran opsins lacking a D. melanogaster ortholog, and using antibodies found that one, a candidate retinochrome which we name unclassified opsin (UnRh), is expressed in the crystaline cone cells and the pigment cells of the butterfly Heliconius melpomene. We also found differences between Lepidoptera and D. melanogaster phototransduction in diacylglycerol regulation where a lepidopteran paralog, DAGβ, may be taking on a role in vision. Lastly, butterflies express similar amounts of trp and trpl channel mRNAs, while moths express approximately 50x less trp. Since TRP/TRPL channels allow Ca2+ and Na+ influx this might explain why moths appear to express less Calx and Nckx30C Na+/Ca2+ channel mRNAs. Our findings suggest that while many single-copy D. melanogaster phototransduction genes are conserved in lepidopterans, phototransduction gene expression differences exist between moths and butterflies that may be linked to their visual light environment.
Has Mortality Risen Disproportionately for the Least Educated?

We examine whether the least educated population groups experienced the worst mortality trends at the beginning of the 21st century by measuring changes in mortality across education quartiles. We document sharply differing gender patterns. Among women, mortality trends improved fairly monotonically with education. Conversely, male trends for the lowest three education quartiles were often similar. For both sexes, the gap in mortality between the top 25 percent and the bottom 75 percent is growing. However, there are many groups for whom these patterns are reversed - with better experiences for the less educated - or where the differences are statistically indistinguishable.
Pleistocene rhinoceros from Bogovina Cave: the first report of Stephanorhinus hundsheimensis Toula, 1902 (Mammalia, Rhinocerotidae) from Serbia

Finds of Pleistocene rhinoceros are rare in Serbia, and only one species (the woolly rhinoceros Coelodonta antiquitatis Blumenbach, 1799) has been reported so far. The current paper presents the dental material of an extinct so-called Hundsheim rhinoceros, Stephanorhinus hundsheimensis Toula, 1902 from Bogovina Cave (East-ern Serbia). Both the morphological and metric characteristics of the teeth are consis-tent with the attribution to S. hundsheimensis . Unfortunately, the rhinoceros material originated from an uncertain geological context, so there is no firm basis for dating. However, a potential association with a caballoid horse tooth could hint at an age of 600 ka or less for the assemblage, which would indicate a relatively late date for the Hundsheim rhinoceros from Bogovina Cave.
Selecão de documentos baseado em centróides para classificacão de patentes usando Word2Vec e KNN

Este artigo apresenta um método de categorizacão de patentes baseado na representacão vetorial utilizando word embedding vectors (Word2Vec), na selecão de documentos através do cálculo dos centróides das classes e no algoritmo K-Nearest Neighbour (KNN), com o objetivo de classificar documentos de patentes no nível de secão da hierarquia IPC do conjunto de dados WIPO. Os resultados experimentais indicam que o método de classificacão proposto alcancou a acurácia de 75%.
Preparation and kinetic study of organic amine‐loaded ion‐exchange resin as CO2 adsorbents

Organic amine adsorbents prepared by template method using ion exchange resin (D001) as support and polyethyleneimine (PEI) as a modifier, and the preparation process was optimized by orthogonal experiment plan. The results showed that adsorbents prepared under conditions (the copper ion concentration was 0.2 mol/L, the ultrasonic time was 3 hr, and the PEI loadings were 30%) had an excellent CO2 adsorption properties. The effects of temperature and gas influent velocity on CO2 adsorption properties were investigated in a fixed bed reactor. When PEI loadings were 30%, the adsorption temperature was 65°C and the gas influent velocity was 40 ml/min, organic amine adsorbents performed a better PEI dispersion, stability, and CO2 adsorption capacity. Maximum CO2 adsorption capacity was 4.00 mmol/g. Besides, the CO2 adsorption capacity decreased by only 10% after 10 cycles of adsorption–desorption tests, attribute to a small amount of PEI was volatilize during the regeneration process. The external diffusion was eliminated by increasing the gas influent velocity, and the adsorption data were well fitted the Weber‐Morris particle diffusion model, indicating that CO2 adsorption was controlled by internal diffusion.
A Multi-Agent Deep Reinforcement Learning Method for Cooperative Load Frequency Control of a Multi-Area Power System

This paper proposes a data-driven cooperative method for load frequency control (LFC) of the multi-area power system based on multi-agent deep reinforcement learning (MA-DRL) in continuous action domain. The proposed method can nonlinearly and adaptively derive the optimal coordinated control strategies for multiple LFC controllers through centralized learning and decentralized implementation. The centralized learning is achieved by MA-DRL based on a global action-value function to quantify overall LFC performance of the power system. To solve the MA-DRL problem, multi-agent deep deterministic policy gradient (DDPG) is derived to adjust control agents’ parameters considering the nonlinear generator behaviors. For implementation, each individual controller only needs local information in its control area to deliver optimal control signals. Numerical simulations on a three-area power system and the fully-modeled New-England 39-bus system demonstrate that the proposed method can effectively minimize control errors against stochastic frequency variations caused by load and renewable power fluctuations.
Therapeutic Benefits and Applications of Whey Protein

Whey is a good source of bioactive peptides, which are produced from whey by enzymatic hydrolysis during fermentation and gastrointestinal digestion. These bioactive peptides are utilized widely to improve human health and have inevitable roles, such as anti-hypertensive, anti-oxidative, immunomodulant, anti-mutagenic, antiInternational Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 9 Number 7 (2020) Journal homepage: http://www.ijcmas. com
PROFILING THE PERCEIVED MANGROVE FOREST USE VALUE AND COMMUNITY’S WILLINGNESS TO PAY FOR MANGROVE CONSERVATION

A broad range of ecological services from mangrove forest encompasses a mixture of landward and seaward transition around tropical and subtropical areas in many regions that are threatened by humans. Among the issues highlighted in this research are i) the decline in mangrove areas due to development activities, and ii) zero price value of mangrove areas. This study reports on the direct use value of mangrove forest, willingness to pay for the conservation of mangrove forests, and satisfaction towards current mangrove management in Kampung Sungai Melayu, located at Johor state in Malaysia. A face-to-face survey was employed, targeting 111 heads of households and 219 individuals from the local community through a simple random sampling technique. This study concludes that the local community are willing to pay for mangrove conservation at RM17.84 per year. Based on the significant results from the Chi Square analysis, three factors have a significant correlation with the “willingness to pay” for mangrove conservation which includes the length of residency (X2 = 11.780) and household income (X2 =13.463).
Analysis of Climate Change Education (CCE) Programs: Focusing on Cultivating Citizen Activists to Respond to Climate Change

Climate change education (CCE) programs should foster citizen response to climate change by integrating knowledge/skill development with reflection on the need for actively changing current social systems and personal actions. An analytical framework was developed to examine 16 Korean and international CCE programs to identify (1) structure and content and (2) to categorize action-emphasized climate change education (AECCE) programs. Results show most CCE programs are for elementary levels and place emphasis on knowledge/skill development, but not on action. AECCE categorized programs were less structured, included more reflexive activities, and promoted more action. Korean AECCE programs offered online content and promoted action at the personal level. International AECCE programs balanced online/real-life content and promoted more action at the socio-political level. AECCE programs need to foster values/attitudes and to promote participation and action at all grade levels, should balance potential and practical components, and target both personal and socio-political levels of action.
Key Performance Indicators (KPIs) to Promote Building Developers Safety Performance in the Construction Industry

Purpose: The aim of this study is to establish key performance indicators (KPIs) that can be deployed in the evaluation and promotion of safety performance of building developer`s in NigeriaDesign/methodology/approach: A thorough review of the literature was performed to generally identify sets of KPIs used to evaluate the safety performances of building developer`s during construction. Interviews and focus group discussions were conducted with eleven (11) subject matter experts and professionals to ensure inclusion, validation and clarity of the indicators and to further provide agreement/disagreement, and importance ratings for the identified KPIs. The KPIs was grouped into appropriate categories, keeping out redundant KPIs, and ensuring KPIs are clear and measurable. The Relative Importance Index (RII) and Mean values were computed.Findings: Results from the study consist of 137 KPIs, grouped into 9 categories including: Planning, design and procurement, communication on & maintenance of effective safety behaviour, construction safety policy, construction safety personnel, management effort and support, safety training and enlightenment, administration of safety processes, investigation and reporting of accidents, and rewards and sanctions for project stakeholders. These KPIs were observed to be at different levels of importance from the respondents. The following KPIs were considered based on their extreme importance judging from the respective RII values: communicating safety requirements to designer (98.18%), safety performance set as part of contractor selection criterion (96.36%), availability and accessibility of the relevant insurance policies (98.18%) and appropriate issuance of motivational directives by the top management (100%). Originality/value: Many studies have been done in the past where KPIs as it relates to construction safety were identified. However, the specificity of these KPIs to countries other than Nigeria requires similar research be conducted to identify building developer safety performance KPIs for the Nigerian construction industry.