Miracle-dz/UniFAR-FTUs huggingface dataset:
Collaborative thermal- and traffic-aware adaptive routing scheme for 3D network-on-chip systems

Due to the stacking dies and unequal cooling eﬃency of dif- ferent layers, 3D NoC-based systems suﬀer sever thermal issues. Adaptive routing can alleviate the thermal issues, but current routing algorithms either suﬀer from the thermal balance or traﬃc congestion. This paper proposed a collaborative thermal- and traﬃc-aware adaptive routing (CTTAR) scheme, which considers the traﬃc and temperature information together and avoids the packets transferring to congested region. Experiments show that, there is 19.4% to 48.4% system performance improvement compared with other routing algorithms under the same thermal limit.
Efecto de un inóculo microbiano en el crecimiento de plantas de tomate (Solanum lycopersicum L.)

Sowing the tomato crop through inoculated seedlings constitutes an ecologically acceptable alternative that guarantees greater growth and reduces external inputs. In order to increase the growth and development of tomato, a study was carried out in a traditional seedbed with the objective of evaluating the most effective dilutions in the growth of tomato plants previously embedded in the seeds in the microbial inoculum (MI). This experiment was conducted under a Completely Random Design with five treatments and five repetitions. The data were through the Statgraphics Centurion program (version 15.1) processed. The imbibition of tomato seeds for 15 minutes in 5, 10 and 15 mL L -1 of the MI did not cause statistical differences between them. There is a similarity expressed in the different moments evaluated and for all the variables under study stimulating the height of the plant, the root length, the number of leaves, the diameter of the stem and the foliar and root mass. Taking into account the results obtained in this research, the effect of dilutions on the growth and development of tomato plants was demonstrated. However, even when the three dilutions reached the highest values, to produce plants in less time and with the necessary quality; the imbibition in 5 and 10 mL L -1 constituted an alternative that represents a saving for bioproduct to be used.
Investigation of the Impact of Two Types of Epoxidized Vietnam Rubber Seed Oils on the Properties of Polylactic Acid

To minimize the brittleness of polylactic acid (PLA), the epoxidized rubber seed oils (ERO) or epoxidized ester rubber seed oils (EERO) are blended with PLA. The mechanical properties of ERO bioblend are higher than that of EERO bioblend and significantly improved compared to that of the PLA sample. Elongation at break is increased by 9.1 times, and impact strength and tensile toughness improved by 139% and 1370%, respectively. The morphological study showed the microdroplets of epoxidized oils distributed in the ERO bioblend are much smaller than those in the EERO bioblend. This means that the ERO is better compatible with PLA, and both ERO and EERO are partially miscible with PLA. This compatibility is confirmed by the decrease in the glass transition temperature, T g , from 65.7 to 60.5°C. The TGA analysis shows a sharp increase in an initial decomposition temperature (from 261.8 to 311.9°C) meaning an improvement in thermal properties. The NMR analysis proves that the epoxidized vegetable oils are linked to PLA chains, so both the melt flow index and an acid value of ERO or EERO bioblend decrease while the thermal stability is improved. The NMR peak area of some signals shows that the ERO is more attached to PLA, proving better compatibility of ERO with PLA, resulting in higher mechanical properties of ERO bioblend. The plasticizing effect of plasticizers is not dependent on the oxygen-oxirane content of the epoxidized oil but is strongly influenced by the acid value. Overall results show that both ERO and EERO can be used as a biodegradable, renewable plasticizer to replace petroleum-based plasticizers for PLA. In addition, the successful modification of PLA by using ERO or EERO promotes the use of this polymer as a potential material for researchers working on PLA applications.
Leaf area index in Earth system models: how the key variable of vegetation seasonality works in climate projections

Earth system models (ESMs) are widely used in scientific research to understand the responses of various components of Earth systems to natural and anthropogenic forcings. ESMs embody terrestrial ecosystems on the basis of the leaf area index (LAI) to formulate various interactions between the land surface and atmosphere. Here, we evaluated the LAI seasonality of deciduous forests simulated by 14 ESMs participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) and CMIP6 to understand the efficacy of recent ESMs in describing leaf dynamics in the northern extratropics from 1982 to 2014. We examined three indicators of LAI seasonality (annual mean, amplitude, and phase) and three phenological dates (start (SOS), end (EOS), and length of growing season (LOS)) of the models in comparison to the third-generation LAI of Global Inventory Modeling and Mapping Studies (GIMMS LAI3g) and the Climate Research Unit gridded time series dataset. CMIP6 models tend to simulate larger annual means (1.7 m2 m−2), weaker amplitudes (0.9 m2 m−2), and delayed phases (226 DOY) compared to the GIMMS LAI3g (1.2 m2 m−2, 1.2 m2 m−2, and 212 DOY, respectively), yet are similar to the CMIP5 models (2.2 m2 m−2, 1.0 m2 m−2, and 225 DOY). The later phase is attributed to a systematic positive bias in EOS of the CMIP5 and CMIP6 models (later by 22 and 18 d, respectively) compared to the GIMMS LAI3g (261 DOY). Further tests on phenological responses to seasonal temperature revealed that the majority of CMIP5 and CMIP6 ESMs inaccurately describe the sensitivities of SOS and EOS to seasonal temperature and the recent changes in mean SOS and EOS distributions (2005–2014 minus 1982–1991). This study suggests that phenology schemes of deciduous forests, especially for autumn leaf senescence, should be revisited to achieve an accurate representation of terrestrial ecosystems and their interactions.
Individual Heterogeneity Screened Umbilical Cord Derived Mesenchymal Stem Cells With High Treg Promotion Significantly Recovered the Mouse Liver Fibrosis

BackgroundTo compare the heterogeneities of human umbilical cord mesenchymal stem cells (HUCMSCs) derived from different donors and test their therapeutic variations in mouse liver fibrosis model. MethodsThe HUCMSCs derived multiple donors were performed comprehensively analysis and potent assays including expressions of surface markers, viability, growth curve, karyotype analysis, tumorigenicity, differentiation potentials, and immune regulation capability. Then the HUCMSCs with distinct immunomodulatory effects were tested for treating liver fibrosis in mice and then therapeutic effects were observed. ResultsThe HUCMSCs derived multiple donors kept a high consistency in surface marker expressions, viability, growth curve, tumorigenicity in nude mic, but had robust heterogeneities in differentiation potentials and immune regulations. In addition, three HUCMSC lines applied to mice liver fibrosis model had different therapeutic outcomes, in line with individual immune regulation capability. ConclusionThe HUCMSCs derived different donors have individual heterogeneity, which potentially lead to distinct therapeutic outcomes in mouse liver fibrosis, indicating we could make use of the donor-variation of MSCs to screen out guaranteed general indicators of MSCs for specific diseases in further stem cell therapy.
The trend and cycle components of China’s housing prices: a new decomposition method

ABSTRACT The paper proposes a novel hybrid method that extends previous work incorporating the fractionally cointegrated vector autoregressive and the permanent-transitory decomposition model. Using the hybrid method, we investigate whether the rapid rise in China’s housing prices is a trend or cyclical fluctuation as well as whether there exists a housing price bubble. The findings indicate there exists a fractional cointegration relationship between housing prices and macroeconomic fundamentals in China, and that the fundamental value of housing prices is determined by macroeconomic factors. In particular, the upward trend in China’s housing prices has shifted and decelerated since 2012, in line with GDP and money supply. Moreover, we provide evidence of the existence of a housing price bubble in China since 2012, particularly during the 2015–2018 period. We demonstrate that the hybrid model has a superior forecasting performance and decomposes the trend and cycle components more accurately than the conventional methods when estimating a system of possibly fractional cointegration relationship.
Efficient and Privacy-Preserving Similarity Range Query Over Encrypted Time Series Data

Similarity query over time series data plays a significant role in various applications, such as signal processing, speech recognition, and disease diagnosis. Meanwhile, driven by the reliable and flexible cloud services, encrypted time series data are often outsourced to the cloud, and as a result, the similarity query over encrypted time series data has recently attracted considerable attention. Nevertheless, existing solutions still have issues in supporting similarity queries over time series data with different lengths, query accuracy and query efficiency. To address these issues, in this article, we propose a new efficient and privacy-preserving similarity range query scheme, where the time warp edit distance (TWED) is used as the similarity metric. Specifically, we first organize time series data into a <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="lu-ieq1-3061611.gif"/></alternatives></inline-formula>d-tree by leveraging TWED’s triangle inequality, and design an efficient similarity range query algorithm for the <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="lu-ieq2-3061611.gif"/></alternatives></inline-formula>d-tree. Second, based on a symmetric homomorphic encryption technique, we carefully devise a suite of privacy-preserving protocols to provide a security guarantee for <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="lu-ieq3-3061611.gif"/></alternatives></inline-formula>d-tree based similarity range queries. After that, by using the similarity range query algorithm and these protocols, we propose our privacy-preserving similarity range query scheme, in which we elaborate on two strategies to make our scheme resist against the cloud inference attack. Finally, we analyze the security of our scheme and conduct extensive experiments to evaluate its performance, and the results indicate that our proposed scheme is indeed privacy-preserving and efficient.
Temporal pyramid attention-based spatiotemporal fusion model for Parkinson's disease diagnosis from gait data

Parkinson's disease (PD) is currently an ongoing challenge in daily clinical medicine. To reduce diagnosis time and arduousness and even assess PD levels, a temporal pyramid attention ‐ based spatiotemporal (PAST) fusion model for diagnosis of PD is produced by using gait data from ground reaction forces. This model is innovative in two aspects. First, by using the temporal pyramid attention module, multiscale temporal attention is obtained from raw sequences. Second, 1D convolutional neural network and bidirectional long short ‐ term memory layers are used together to learn spatial fusion features from multiple channels in the spatial domain to obtain multichannel, multiscale fusion features. Experiments are performed on the PhysioBank data set, and the results show that the proposed PAST model outperforms other state ‐ of ‐ the ‐ art methods on classification results. This model can assist in the diagnosis and treatment of PD by using gait data.
Method for Obtaining Coefficients of Powers of Bivariate Generating Functions

In this paper, we study methods for obtaining explicit formulas for the coefficients of generating functions. To solve this problem, we consider the methods that are based on using the powers of generating functions. We propose to generalize the concept of compositae to the case of generating functions in two variables and define basic operations on such compositae: composition, addition, multiplication, reciprocation and compositional inversion. These operations allow obtaining explicit formulas for compositae and coefficients of bivariate generating functions. In addition, we present several examples of applying the obtained results for getting explicit formulas for the coefficients of bivariate generating functions. The introduced mathematical apparatus can be used for solving different problems that are related to the theory of generating functions.
Discovery of Two Lineages of Hynobius tsuensis (Amphibia, Caudata) Endemic to Tsushima Island, Japan

The Tsushima salamander, Hynobius tsuensis, is a lotic-breeding species endemic to Tsushima Island, Japan. We investigated genetic variation in this species using samples covering all known localities on the island. Phylogenetic analyses based on mitochondrial cytochrome b gene sequences divided H. tsuensis populations into two genetic groups: true H. tsuensis and an unknown species (Hynobius sp.) showing a closer relationship to Hynobius nebulosus than to H. tsuensis. The genetic distance between the two groups was greater than the genetic distances between different species of Hynobius. Both groups were found to breed in mountain streams, sometimes in the same streams syntopically. Population structure analysis based on several nuclear microsatellite loci strongly indicated reproductive isolation between the two groups in the syntopic localities. This is the first report confirming the syntopic occurrence of two lotic salamanders of Hynobius on a small island. We propose that the lotic breeding habits of the two salamanders were independently acquired.
Identifying quantitative trait loci for lodging‐associated traits in the wheat doubled‐haploid population Avalon × Cadenza

Assigned to Associate Editor Eric Olson. Abstract Lodging affects grain quality and grain yield in wheat (Triticum aestivum L.) and is difficult to breed for because its sporadic incidence and laborious protocols to measure lodging traits. Thus, developing molecular markers for these traits can increase selection efficiency in breeding programs. The aim of this article is to identify quantitative trait loci (QTL) associated with stem/anchorage strength and leverage traits (lodging traits) in a doubled-haploid population of UK bread wheat Avalon × Cadenza. Field experiments were conducted in the UK during 2012–2013 near High Mowthorpe and during 2013–2014 at Sutton Bonington. Phenotypic and genetic analysis indicated significant genetic variation for all traits. Stem strength (diameter, wall width, and material strength) and leverage (plant height) traits were highly heritable (0.64–0.95), whereas anchorage strength traits (root plate spread and structural rooting depth) and ear number per plant (leverage trait) were less heritable (0.21– 0.33). This study identified 18 QTL for lodging traits and grain yield in chromosomes 1D, 2B, 2D, 3A, 3B, 4A, 4D, 5B, and 6B. Two QTL for stem strength on chromosome 1D and 3B explaining 49.6% of the total phenotypic variation (PVE) are estimated to reduce stem lodging risk and shortening the plant height by 12 cm. One QTL for root plate spread on chromosome 5B explaining 22.4% of the PVE could increase root lodging resistance.
Anxiety and depression associated cardiovascular health behaviors among patients with hypertension

Background: Anxiety and depression in hypertensive patients may lead to poor blood pressure control and increases the risk of disease mortality. Lifestyle impacts depression and anxiety. This study aimed to assess cardiovascular health behaviors (CHBs) associated with co-morbid anxiety and depression among patients with hypertension.Methods: We included 488 hypertensive patients from Changsha, China. We measured anxiety and depression using the self-rating anxiety scale (SAS), and the self-rating depression scale (SDS), respectively. CHBs (smoking, overweight/obesity, leisure physical activity (LPA), and fruit and vegetable consumption (FVC)) were assessed using the Cardiovascular Health in Ambulatory Care Research Team (CANHEART) index. We compared anxiety and depression prevalence of participants in different socio-demographic, CHBs, co-morbidities, family histories, assessed risk factors and their biological synergistic interaction.Results: The proportion of not ideal in smoking, overweight/obesity, LPA, and FVC were 63.9%, 49.8%, 30.7%, 78.3%, respectively. Displaying comorbidity of HLP and not obtaining adequate amounts of LPA were risk factors for both anxiety and depression. The synergy interaction between obtaining secondary education or less and displaying comorbidity of hyperlipidemia (HLP) for anxiety (OR=5.238, 95% CI=2.784, 9.856), and between not obtaining adequate amounts of LPA and obtaining manual labor for depression (OR=7.164, 95% CI=3.553, 14.443) was statistically significant.Conclusion: Our study indicated that doctors should pay more attention to the psychiatric health of hypertensive patients at lower education levels and with second comorbidities. More importantly, patients with hypertension working on manual jobs need to pay closer attention to how they spend their leisure time and strengthen LPA.
Comparison of nurse effect zones of shrubs versus trees for dryland rehabilitation in Northeast China

Nurse plants can form islands of fertility to rehabilitate degraded land. Areas outside plant canopies may not recover as much as areas under canopies, but the spatial extent of nurse plants' beneficial impacts is not fully understood. This study aimed to quantify the spatial and temporal aggregate nurse effects (zones of influence) of shrubs compared with trees planted for land rehabilitation in a desertified region of Inner Mongolia, China. We conducted vegetation surveys in pairs of replicate 20 × 20 m plots, each subdivided into 100 subplots (each 2 × 2 m), on four types of rehabilitation sites: shrub (Caragana microphylla) plantation sites managed for 6 or 24 years and tree (Populus simonii) plantation sites managed for 5 or 24 years. Surface soil physiochemical properties and litter amount were also measured inside and outside of nine canopies on each site. The aggregate nurse effects of improved understory vegetation and surface soil conditions extended beyond the canopies of individual plants in C. microphylla and P. simonii plantations. However, these effects were more concentrated under the canopies of C. microphylla, whereas the effects under P. simonii were spread evenly over the plantation site. This difference resulted in faster rehabilitation at the site scale in P. simonii plantations. A major factor contributing to the higher rehabilitation performance of P. simonii appeared to be larger plant height, which provides greater windbreak and shading effects compared to shrubs. Xerophytic native trees that require less water than P. simonii may be a better option for rehabilitation.
Synbiotic Efficacy as Therapeutic Approach in Human Disease: A Review

In combatting the increase in healthcare costs, at present, one of the preventive approaches to medicine has been developed with the upliftment of new synbiotic products. Synbiotic is the synergistic effect of probiotics and prebiotics which exert multiple beneficial effects and have been increasingly used in preventing or treating human diseases since the last ten years. Several trials have reported that synbiotic therapy could help in the treatment of human disease prevention. PubMed, Science Direct, and Google Scholar were searched by keywords ‘prebiotic’, ‘probiotic’, and ‘synbiotic’ for relevant literature from 2000 to 2020. A total of 58 articles were selected and revised. This paper evaluates the effect of synbiotic supplementation on different diseases, for instance, obesity, insulin resistance syndrome, diabetes, and non-alcoholic fatty liver disease. The progressive knowledge on the outcome of synbiotic supplementation on health, recent trends and developments in this field are summarised. However, further research is required to understand the mechanism of how synbiotics affect in different diseases.
A framework for association rule learning with social media networks

We present an application of association rule learning to analyze Twitter account follow patterns. In doing so, we develop a basic framework and tutorial for future researchers to build on, which takes advantage of the Twitter API. To demonstrate the method, we take samples of Twitter accounts following Joe Biden and Donald Trump. For each account in our sample population, we pull the account’s 100 most recently followed accounts. This data is cleaned and formatted for use with Python’s apyori package, which uses the well-known apriori algorithm to learn association rules for a given dataset. This work has two objectives: (1) demonstrate the application association rule learning to social media networks and (2) perform exploratory analysis on the resulting association rules. We successfully demonstrate association rule learning in a Jupyter-notebook environment with Python. The resulting association rules indicate some interesting similarities and differences in the networks of Biden’s and Trump’s Twitter followers. The demonstrated method can be generalized to any non-private Twitter account(s). Extensions of our work can apply the method to larger datasets, with a focus on analyzing the learned association rules. Our study demonstrates an innovative application of association rule learning outside of the traditional use cases, which suggests similar opportunities in fields such as politics, education, public health, and more.
Regional Differentiation of the Constituent Entities of the Russian Federation by the Level of Socio-Economic Development

This article presents the results of a cluster analysis of the regions of the Russian Federation in terms of the main parameters of socio-economic. The major objective of the article is to develop a method for the division of the Russian regions into clusters in order to improve the quality of the policymaking process. The authors studied and analyzed the domestic and foreign (Eurostat) methodology for assessing the socio-economic development of territories. The major results of the study are the determination of the main parameters of territorial differentiation and identification of the key indicators that affect the socio-economic development of Russian regions. The authors have carried out a classification of the constituent entities of the Russian Federation not in terms of territorial location and geographical features, but in terms of the specifics and key parameters of the socio-economic situation into 4 clusters. The results of the cluster analysis allow specifying specific areas, where state control and interference is needed in order to ease the economic and social inequity in Russia and cease social unrest.