Miracle-dz/UniFAR-FTUs huggingface dataset:
What happens to offspring when parents are inbred, old or had a poor start in life? Evidence for sex‐specific parental effects

Parental effects on offspring performance have been attributed to many factors such as parental age, size and condition. However, we know little about how these different parental characteristics interact to determine parental effects, or the extent to which their effect on offspring depends on either the sex of the parent or that of the offspring. Here we experimentally tested for effects of variation in parents’ early diet and inbreeding levels, as well as effects of parental age, and for potential interactive effects of these three factors on key aspects of offspring development in the mosquitofish (Gambusia holbrooki). Older mothers produced offspring that were significantly smaller at birth. This negative effect of maternal age on offspring size was still evident at maturation as older mothers had smaller daughters, but not smaller sons. The daughters of older mothers did, however, reach maturity sooner. Paternal age did not affect offspring body size, but it had a complex effect on their sons’ relative genital size. When initially raised on a food‐restricted diet, older fathers sired sons with relatively smaller genitalia, but when fathers were initially raised on a control diet their sons had relatively larger genitalia. The inbreeding status of mothers and fathers had no significant effects on any of the measured offspring traits. Our results indicate that the manifestation of parental effects can be complex. It can vary with both parent and offspring sex; can change over an offspring's life; and is sometimes evident as an interaction between different parental traits. Understanding this complexity will be important to predict the role of parental effects in adaptation.
Evidence that divergent selection shapes a developmental cline in a forest tree species complex

Background and Aims Evolutionary change in developmental trajectories (heterochrony) is a major mechanism of adaptation in plants and animals. However, there are few detailed studies of the variation in the timing of developmental events among wild populations. We here aimed to identify the climatic drivers and measure selection shaping a genetic-based developmental cline among populations of an endemic tree species complex on the island of Tasmania. Methods Seed lots from 38 native provenances encompassing the clinal transition from the heteroblastic Eucalyptus tenuiramis to the homoblastic Eucalyptus risdonii were grown in a common-garden field trial in southern Tasmania for 20 years. We used 27 climatic variables to model the provenance variation in vegetative juvenility as assessed at age 5 years. A phenotypic selection analysis was used to measure the fitness consequences of variation in vegetative juvenility based on its impact on the survival and reproductive capacity of survivors at age 20 years. Key Results Significant provenance divergence in vegetative juvenility was shown to be associated with home-site aridity, with the retention of juvenile foliage increasing with increasing aridity. Our results indicated that climate change may lead to different directions of selection across the geographic range of the complex, and in our mesic field site demonstrated that total directional selection within phenotypically variable provenances was in favour of reduced vegetative juvenility. Conclusions We provide evidence that heteroblasty is adaptive and argue that, in assessing the impacts of rapid global change, developmental plasticity and heterochrony are underappreciated processes which can contribute to populations of long-lived organisms, such as trees, persisting and ultimately adapting to environmental change.
Sporulation environment influences spore properties in Bacillus: evidence and insights on underlying molecular and physiological mechanisms

Bacterial spores are resistant to physical and chemical insults, which makes them a major concern for public health and industry. Spores help bacteria to survive extreme environmental conditions that vegetative cells cannot tolerate. Spore resistance and dormancy are important properties for applications in medicine, veterinary health, food safety, crop protection and other domains. The resistance of bacterial spores results from a protective multilayered structure and from the unique composition of the spore core. The mechanisms of sporulation and germination, the first stage after breaking of dormancy, and organization of spore structure have been extensively studied in Bacillus species. This review aims to illustrate how far the structure, composition and properties of spores are shaped by the environmental conditions in which spores form. We look at the physiological and molecular mechanisms underpinning how sporulation media and environment deeply affect spore yield, spore properties like resistance to wet heat and physical and chemical agents, germination and further growth. For example, spore core water content decreases as sporulation temperature increases, and resistance to wet heat increases. Controlling the fate of Bacillus spores is pivotal to controlling bacterial risks and process efficiencies in, for example, the food industry, and better control hinges on better understanding how sporulation conditions influence spore properties.
Analysis of blood and bone marrow smears using multispectral imaging analysis techniques

Counting of different classes of white blood cells in bone marrow smears can give pathologists valuable information regarding various cancers. But it is tedious to manually locate, identify, and count these classes of cells, even by skilled hands. This paper presents a novel approach for automatic detection of White Blood Cells in bone marrow microscopic images. Different from traditional color imaging method, we use multispectral imaging techniques for image acquisition. The combination of conventional digital imaging with spectroscopy can provide us with additional useful spectral information in common pathological samples. With our spectral calibration method, device-independent images can be acquired, which is almost impossible in conventional color imaging method. A novel segmentation algorithm using spectral operation is presented in this paper. Experiments show that the segmentation is robust, precise, with low computational cost and insensitive to smear staining and illumination condition. Once the nuclei and cytoplasm have been segmented, more than a hundred of features are extracted under the direction of a pathologist, including shape features, textural features and spectral ratio features. In pattern recognition, a maximum likelihood classifier (MLC) is implemented in a hierarchical tree. The classification results are also discussed. This paper is focused on image acquisition and segmentation.
The Kinase Complex mTOR Complex 2 Promotes the Follicular Migration and Functional Maturation of Differentiated Follicular Helper CD4+ T Cells During Viral Infection

Follicular helper CD4+ T (TFH) cells are critical for optimal B-cell-mediated humoral immunity by initiating, fueling, and sustaining germinal center reactions. The differentiation of TFH cells relies on multiple intrinsic and extrinsic factors; however, the details by which these factors are integrated to coordinate TFH differentiation are largely unknown. In this study, using a mouse model of acute lymphocytic choriomeningitis virus (LCMV) viral infection, we demonstrate that mTOR complex 2 (mTORC2) kinase integrates TCR signaling and ICOS-mediated co-stimulation to promote late differentiation and functional maturation of virus-specific TFH cells. Specifically, mTORC2 functions to maintain TFH lineage specifications, including phenotypes, migratory characteristics, and functional properties. Thus, our results highlight the importance of mTORC2 in guarding TFH phenotypic and functional maturation.
Flexural resonance mechanism of thermal transport across graphene-SiO2 interfaces

Understanding the microscopic mechanism of heat dissipation at the dimensionally mismatched interface between a two-dimensional (2D) crystal and its substrate is crucial for the thermal management of devices based on 2D materials. Here, we study the lattice contribution to thermal (Kapitza) transport at graphene-SiO2 interfaces using molecular dynamics (MD) simulations and non-equilibrium Green's functions (NEGF). We find that 78 percent of the Kapitza conductance is due to sub-20 THz flexural acoustic modes, and that a resonance mechanism dominates the interfacial phonon transport. MD and NEGF estimate the classical Kapitza conductance to be hK ≈ 10 to 16 MW K−1 m−2 at 300 K, respectively, consistent with existing experimental observations. Taking into account quantum mechanical corrections, this value is approximately 28% lower at 300 K. Our calculations also suggest that hK scales as T2 at low temperatures (T < 100 K) due to the linear frequency dependence of phonon transmission across the graphene-SiO2 interface at low frequencies. Our study sheds light on the role of flexural acoustic phonons in heat dissipation from graphene to its substrate.Understanding the microscopic mechanism of heat dissipation at the dimensionally mismatched interface between a two-dimensional (2D) crystal and its substrate is crucial for the thermal management of devices based on 2D materials. Here, we study the lattice contribution to thermal (Kapitza) transport at graphene-SiO2 interfaces using molecular dynamics (MD) simulations and non-equilibrium Green's functions (NEGF). We find that 78 percent of the Kapitza conductance is due to sub-20 THz flexural acoustic modes, and that a resonance mechanism dominates the interfacial phonon transport. MD and NEGF estimate the classical Kapitza conductance to be hK ≈ 10 to 16 MW K−1 m−2 at 300 K, respectively, consistent with existing experimental observations. Taking into account quantum mechanical corrections, this value is approximately 28% lower at 300 K. Our calculations also suggest that hK scales as T2 at low temperatures (T < 100 K) due to the linear frequency dependence of phonon transmission across the graphene-SiO.
β3GnT8 Promotes Colorectal Cancer Cells Invasion via CD147/MMP2/Galectin3 Axis

β1,3-N-acetylglucosaminyltransferase (β3GnT8) and β3GnT2 are key enzymes that catalyzes the formation of polylactosamine glycan structures by transferring GlcNAc to tetra-antennary β1-6-branched N-glycan and it also has an important effect on the progression of various types of human cancer. They have been reported to participate in tumor invasion and metastasis by regulating the expression of matrix metalloproteinases (MMPs), CD147, and polylactosamine. However, whether β3GnT8 and β3GnT2 play a role in colorectal cancer and, if so, the underlying mechanisms remain unclear. In our study, we detected the expression of β3GnT8, CD147, MMP2, and galectin3 by immunohistochemistry on 90 paraffin-embedded slices. And β3GnT8, CD147, MMP2, and galectin3 were over-expressed in colorectal cancer tissues. We found that overexpression of β3GnT8 and β3GnT2 promoted invasion of colorectal cancer cells, whereas knockdown of β3GnT8 and β3GnT2 inhibited the invasive activity. Mechanistically, β3GnT8 and β3GnT2 regulated the expression of HG-CD147 and the level of polylactosamines in colorectal cancer cells. Together, these results illustrate that the novel role and the molecular mechanism of β3GnT8 and β3GnT2 in promotion of colorectal cancer invasion. These results suggest that the potential use of β3GnT8 as a tumor target for the therapy of colorectal cancer.
Sentiment Analysis of Arabic Tweets: Feature Engineering and A Hybrid Approach

Sentiment Analysis in Arabic is a challenging task due to the rich morphology of the language. Moreover, the task is further complicated when applied to Twitter data that is known to be highly informal and noisy. In this paper, we develop a hybrid method for sentiment analysis for Arabic tweets for a specific Arabic dialect which is the Saudi Dialect. Several features were engineered and evaluated using a feature backward selection method. Then a hybrid method that combines a corpus-based and lexicon-based method was developed for several classification models (two-way, three-way, four-way). The best F1-score for each of these models was (69.9,61.63,55.07) respectively.
Cost-Benefit Analysis of Data Intelligence - Its Broader Interpretations

The core of data science is our fundamental understanding about data intelligence processes for transforming data to decisions. One aspect of this understanding is how to analyze the cost-benefit of data intelligence workflows. This work is built on the information-theoretic metric proposed by Chen and Golan for this purpose and several recent studies and applications of the metric. We present a set of extended interpretations of the metric by relating the metric to encryption, compression, model development, perception, cognition, languages, and media.
Cosmic Evolutionary Philosophy and a Dialectical Approach to Technological Singularity

The philosophy of cosmic evolution provides a worldview for thinking about the human position and relationship to universal processual dynamics. This evolutionary process is conceptualized as a network of relations with a specific astrophysical singularity origin as the first cause in a progressive complexification of organization from sub-atomic particles to human civilization. Throughout this complexification of organization key events are identified as representing qualitative phase transitions where new relations form emergent integrated ordered wholes. The hypothesized/anticipated next stage of cosmic evolutionary imminence is often described by futurists as a technological singularity where complex organization generated by scientific knowledge in the form of artificial general intelligence and distributed digital networks create an integrated ordered whole beyond any previous known level of complexity. This paper does not challenge this hypothesis/anticipation but rather seeks to reframe the human position and relationship to such processes by approaching technological singularity from the internal subjective view of the conscious ideational landscape of human mind in-itself via the triadic logic of negative dialectics ((1) abstract, (2) transform, (3) concrete). Consequently, such a view focuses on the motion of embodied cognitive processes teleodynamically oriented towards ideal real attractor states. From this works the fundamental chaos, uncertainty, and unpredictability of the future is situated next to a structural analysis of the ordered intention, goal-directedness, and value-laden cognitive motion that we can observe on the abstract horizon of human becoming.
Guided Feature Transformation (GFT): A Neural Language Grounding Module for Embodied Agents

Recently there has been a rising interest in training agents, embodied in virtual environments, to perform language-directed tasks by deep reinforcement learning. In this paper, we propose a simple but effective neural language grounding module for embodied agents that can be trained end to end from scratch taking raw pixels, unstructured linguistic commands, and sparse rewards as the inputs. We model the language grounding process as a language-guided transformation of visual features, where latent sentence embeddings are used as the transformation matrices. In several language-directed navigation tasks that feature challenging partial observability and require simple reasoning, our module significantly outperforms the state of the art. We also release XWorld3D, an easy-to-customize 3D environment that can potentially be modified to evaluate a variety of embodied agents.
Analysis of New IKEA Stores Using Machine Learning

This paper studied public emotion and opinion concerning the opening of new IKEA stores, specifically, how much attention are attracted, how much positive and negative emotion are aroused, what IKEA-related topics are talked due to this event. Emotion is difficult to measure in retail due to data availability and limited quantitative tools. Twitter texts, written by the public to express their opinion concerning this event, are used as a suitable data source to implement sentiment analysis. Around IKEA opening days, local people post IKEA related tweets to express their emotion and opinions on that. Such “IKEA” contained tweets are collected for opinion mining in this work. To compute sentiment polarity of tweets, lexiconbased approach is used for English tweets, and machine learning methods for Swedish tweets. The conclusion is new IKEA store are paid much attention indicated by significant increasing tweets frequency, most of them are positive emotions, and four studied cities have different topics and interests related IKEA. This paper extends knowledge of consumption emotion studies of prepurchase, provide empirical analysis of IKEA entry effect on emotion. Moreover, it develops a Swedish sentiment prediction model, elastic net method, to compute Swedish tweets’ sentiment polarity which has been rarely conducted.
Multilayer Modular Balancing Strategy for Individual Cells in a Battery Pack

The least cell state-of-charge (SOC) in a battery pack directly determines the left runtime of the total battery pack. Hence, an equalizing strategy is often needed to balance the battery cells, especially for lithium-ion batteries. In this paper, it is shown that this can be achieved with a simple equalizing circuit, which only needs a power semiconductor switch and an inductor for each cell. To avoid the intensive requirement on the processing power of existing control algorithms, two simple control schemes are proposed to obtain better modular performance. First, the operating modes under different switching states are illustrated with a four-cell battery module. After that, the required duty cycles to operate the switches are obtained by comparing the SOC of the relevant cells and the average SOC of all cells. By fixing the maximum of the duty cycle of the highest SOC cell, the inductor can be easily designed and the rated currents of switches and cells can also be regulated. Moreover, the multilayer and modular concept is developed to speed up the balancing process and modularize the design of equalizing circuits. Finally, experiments were completed to demonstrate the proposed scheme.
Jens Waschke Æ Nikola

Protein kinase C (PKC) is activated in response to various inflammatory mediators and contributes significantly to the endothelial barrier breakdown. However, the mechanisms underlying PKC-mediated permeability regulation are not well understood. We prepared microvascular myocardial endothelial cells from both wild-type (WT) and caveolin-1-deficient mice. Activation of PKC by phorbol myristate acetate (PMA) (100 nM) for 30 min induced intercellular gap formation and fragmentation of VE-cadherin immunoreactivity in WT but not in caveolin-1-deficient monolayers. To test the effect of PKC activation on VE-cadherin-mediated adhesion, we allowed VE-cadherin-coated microbeads to bind to the endothelial cell surface and probed their adhesion by laser tweezers. PMA significantly reduced bead binding to 78±6% of controls in WT endothelial cells without any effect in caveolin-1-deficient cells. In WT cells, PMA caused an 86±18% increase in FITCdextran permeability whereas no increase in permeability was observed in caveolin-1-deficient monolayers. Inhibition of PKC by staurosporine (50 nM, 30 min) did not affect barrier functions in both WT and caveolin-1deficient MyEnd cells. Theses data indicate that PKC activation reduces endothelial barrier functions at least in part by the reduction of VE-cadherin-mediated adhesion and demonstrate that PKC-mediated permeability regulation depends on caveolin-1.
Wage Stickiness and Nonclearing Labor Market in Business Cycles ∗

This paper presents a dynamic optimization model of RBC type augmented by wage stickiness, and nonclearing labor market. Agents are required to adaptively optimize when facing constraints on the markets. Calibration for the U. S. economy shows that the model will produce higher volatility in employment. Moreover, it provides more reasonable cross-correlation of employment and wages with other macroeconomic variables and improves on the correlation of the technology shock with employment. Overall, the model fits the data better than the benchmark RBC model.
THE MODEL OF INTERNET-BASED MARKETING COMMUNICATION

In today’s global marketing environment, the Internet is the one true and really global medium or tool for global marketing communications. As the marketing concept itself lacks theoretical framework, which is under discussion by academicians, the same is valid for marketing communication as well as the Internet – they lack theoretical basis. The goal of current paper is to provide a model for deeper understanding of Internet’s role in marketing communication framework, and to do it in a simple and easily understandable format. Clearer understanding of Internet’s role would help academicians and practitioners to use the Internet in everyday’s global marketing communication.
MINING CENSUS AND GEOGRAPHIC DATA IN URBAN PLANNING ENVIRONMENTS

Urban planning is a knowledge-intensive activity. It acquires useful knowledge by analysing jointly socio-economic data and topographic maps. When supported by computers, this preliminary information gathering triggers a knowledge discovery process, which often consists of exploratory data analysis tasks. Advances in georeferencing have caused among the other things a growing demand for more powerful exploratory data analysis techniques. We resort to the field of spatial data mining and propose the task of mining spatial association patterns/rules, i.e. frequent associations between spatial objects, as a means for data exploration. Strong points of the proposed technique for this task are the power of logics as a knowledge representation and reasoning means and the capability of discovering associations at multiple levels of description granularity. This enables new interesting exploratory tasks for spatial data. The technique has been implemented in SPADA and tested on census and geographic data of Stockport, one of the ten metropolitan districts of Greater Manchester, UK. We show results obtained by applying SPADA to a problem of urban accessibility of the Stepping Hill hospital in Stockport.
VARIABILITY ASSESSMENT OF SOME MORPHOLOGICAL TRAITS AMONG BLUE PINE ( PINUS WALLICHIANA ) COMMUNITIES IN HINDUKUSH RANGES OF SWAT , PAKISTAN

Pinus wallichiana dominated forest communities, located in the Hindukush ranges of Swat, Pakistan were analysed for variability in the cone and seed traits. The results disclosed significant variability in mean values, critical difference, coefficient of variation, broad sense heritability, genetic gain and genetic advance. Genotypic variance (Vg) and genotypic coefficient of variance (GCV) were noted to be lower than the corresponding environmental variance (Ve) and environmental coefficient of variability (ECV) for most of the parameters which clearly shows that these traits are under the control of environment. Both Number of male clusters/branch and 100 seeds weight are heritable traits as having higher genotypic variance and genotypic coefficient of variance. Traits like 100 seeds weight, Number of male cluster/branch, number of female cones/tree, female cone weight and number of sterile scales/cone showed moderate to high percentage of heritability indicates that these traits are under strong genetic control. These heritable additive genetic traits can be used for future breeding and tree improvement plans for the species. It is further concluded that the alleged traits should be given priority while selecting superior genotypes.