Hashtags Influence Maximization: Choosing the most Influential Hashtags on Instagram

This study aims to find influential hashtags using Influence Maximization (IM). The IM approach was implemented using hashtags network collected from Instagram. This study can help business or ordinary users to choose the most engaging hashtags for posting, as opposed to selecting influencers, which was widely studied using the IM approach. The network was build based on the hashtags co-appearance frequency. Three IM algorithms, i.e. SSA, DSSA, and IMM, were simulated under the IC and LT models. The algorithms were compared against TopUsage, which is the top hashtags based on the usage count. The IM algorithms have a similar performance with TopUsage in influence spread, which shows that IM can adapt to the hashtags network. However, the IM algorithms produced better hashtags based on the UER (unique engagement rate) metric. The best UER performance was shown by DSSA under the LT model, where it outperformed TopUsage by 17.23%. In the hashtags categorization scenario, DSSA-LT outperformed the UER of TopUsage by up to 6.87%. This categorization is more useful in a practical scenario, to find only relevant hashtags for posting. The hashtags generated by DSSA-LT are about 30-35% different from TopUsage.

Path to Diversity and to Resistant Uniformity: Intracellular Adaptation to Nutrient Environment

Two adaptation strategies are known, which provide variability and resistance of population. We study the laws of adaptation by the example of proteins and changes in their conformations. The data were obtained in the experiments of V.I. Korogodin on yeast cells with mutations, which have demonstrated the effect of the culture medium on the appearance frequency of pseudo-wild type cells. Here, these archived and published data are analyzed by the statistical approach. Statistical analysis shows the emergence of a sequence of independent foci of the pseudo-wild cells induced by intracellular factor and their association with the cytosolic and nuclear-mitochondrial oxidative pathways; the foci dispersions conform the regularities of the folding energy landscape; intracellular imbalances and gene mutations affect their frequency and diversity. We conclude that the paths from diversity to uniformity of protein conformations obeys the laws of the energy landscape. The nuclear-mitochondrial machinery generates new proteins and their homogeneous foci. Variable foci consist mainly of the former conformations remodeled under ROS from several cytosolic sources. Strong gene expression induces oxidative stress, which increases the frequency of homogeneous conformations and reduces variability. Further, stress activates a new focus of new homogeneous conformations.

State-of-the-art augmented NLP transformer models for direct and single-step retrosynthesis

We investigated the effect of different training scenarios on predicting the (retro)synthesis of chemical compounds using text-like representation of chemical reactions (SMILES) and Natural Language Processing (NLP) neural network Transformer architecture. We showed that data augmentation, which is a powerful method used in image processing, eliminated the effect of data memorization by neural networks and improved their performance for prediction of new sequences. This effect was observed when augmentation was used simultaneously for input and the target data simultaneously. The top-5 accuracy was 84.8% for the prediction of the largest fragment (thus identifying principal transformation for classical retro-synthesis) for the USPTO-50k test dataset, and was achieved by a combination of SMILES augmentation and a beam search algorithm. The same approach provided significantly better results for the prediction of direct reactions from the single-step USPTO-MIT test set. Our model achieved 90.6% top-1 and 96.1% top-5 accuracy for its challenging mixed set and 97% top-5 accuracy for the USPTO-MIT separated set. It also significantly improved results for USPTO-full set single-step retrosynthesis for both top-1 and top-10 accuracies. The appearance frequency of the most abundantly generated SMILES was well correlated with the prediction outcome and can be used as a measure of the quality of reaction prediction.

Synoptic climatological analysis on the rather abrupt seasonal transition to mid-winter situation around Germany with intermittent appearance of extremely low temperature events.

<p>  To know the detailed seasonal cycle in various regions, confined only to the middle and higher latitudes, is the common basis for deeper understanding of the seasonal backgrounds of (1) extreme meteorological or climatological events and (2) cultural generation through the “seasonal feeling” leading to cultural understanding education. For example, our previous studies (e.g., Kato et al. 2017) pointed out that the “seasonal feeling” on the severe winter relating to the traditional event for driving the winter away (“Fasnacht”) around Germany might be due to the intermittent appearance of the extremely low temperature events, although the winter mean temperature there is lower only by about 3~5℃ than in southern Japan. Hamaki et al.(2018) suggested the appearance of such events to be controlled greatly by the intraseasonal behaviors of the Icelandic low. Furthermore, Kuwana et al. (EGU2018 and 2019) pointed out the asymmetric seasonal progression of the behaviors of the Icelandic low including its intraseasonal variation from the autumn to the next spring. However, it has not been clarified yet what kind of seasonal transition of the dominant large-scale daily fields was related to the increase in appearance frequency of such extremely low temperature events after mid-December. Thus the present study will further examine the detailed features on the above processes, mainly for the 2000/2001 winter based on the NCEP/NCAR reanalysis data.</p><p>  Appearance frequency of extremely low temperature events (e.g., below -5℃) rapidly increased around mid-December of 2000 with the large amplitude of its intraseasonal variation although the seasonal mean the Icelandic low appeared from mid-October. It is interesting that the daily mean temperature decreased gradually with shorter-period fluctuation until mid-December, even after the seasonal formation of the Icelandic low.</p><p>  As for the seasonal mean fields from mid-December to the next March, the northeastern portion of the Icelandic low area extended more closely to the northwestern Europe and the baroclinicity was enhanced especially to the south of ~55°N. Composite analyses suggest that the extremely low temperature events after mid-December around Germany was related not only to the weakening and westward retreat of the Icelandic low but also to the cold air advection by the low-level easterly wind along the southeastern edge of the intraseasonal-scale surface high to the north of Germany.</p>

Environmental Groundwater Depth for Groundwater-Dependent Terrestrial Ecosystems in Arid/Semiarid Regions: A Review

Groundwater in arid/semiarid regions plays crucial roles in providing drinking water supply, supporting irrigated agriculture, and sustaining important native terrestrial ecosystems. Groundwater depth controls water availability to vegetation and is essential for conserving groundwater-dependent terrestrial ecosystems. Environmental groundwater depth can be defined as a mean depth or a range of depths, satisfying the growth of natural vegetation that is not under stress, either due to lack of water or anoxia or soil salinization. Five methodologies have been reported to estimate environmental groundwater depth: the direct ones rely on response functions that relate vegetation condition, e.g., physiological parameters, appearance frequency, community structure, and remotely sensed physical indexes, to changes in groundwater depth; the indirect one estimates environmental groundwater depth based on the threshold of soil moisture content. To fill a knowledge gap of unique recognized methodology, a conceptual framework was proposed, which involves initial estimation (data collection, response assessment, and estimation) and feedback adjustment (implementation and modification). A key component of the framework is to quantify the linkage between ecological conditions and geohydrological features. This review may provide references for groundwater resources management, ecological conservation, and sustainable development in arid/semiarid regions.

Reduction of Conveyance Power Consumption of District Cooling and Heating Systems using Demand-Supply Coordinated Control

This study aims to discuss the effectiveness of “Demand-Supply Coordinated control” in reducing the power consumption required for conveyance by the heat transport medium in District Cooling and Heating (DHC) systems. The problem with DHC systems is that increased conveyance power is required to provide heating to consumers. As one of the measures to solve this problem, Demand-Supply Coordinated (DSC) control is introduced; however, its effectiveness and limitations have not been clarified so far. In this paper, first, the fundamental characteristics of a DHC system under DSC control are numerically examined. The results showed that the conveyance power consumption of DHC systems under DSC control can be classified into three regions, depending on the relative rate of demand change against the load-following capability of the heat source. Next, the authors compared the conveyance power of DSC control with that of Constant Supply Pressure (CSP) control adopted in conventional DHC, and showed regularity for each of the three regions mentioned above. Finally, the authors show the appearance frequency of these three regions of the practical DHC system under a real heat load in Japan. The results showed that the conveyance power required for DSC control is markedly lower than that of CSP control.

Caractérisation des insectes et des champignons infestant les fèves de cacao dans les principales zones de production en Côte d’Ivoire

If the culture of the cocoa in Côte d’Ivoire gives a great satisfaction concerning the production level, the quality of raw cocoa beans remains to be improved. One of the causes of this depreciation is the moulds development in beans. In order to identify responsible fungus, cocoa beens have been collected in the maine production areas which are the East, the Mid-West and the South-West, represented respectively by the localities of Abengourou, Oumé and Soubré. From collected beans, the fungus have been insulated and purified on PDA medium and then, they have been identified by observing their morphocultural and microscopic characteristics. The results show that 9 mushroom species belonging to 5 genera were identified in cocoa beans collected in the whole of the localities. There are Aspergillus, Penicillium, Fusarium, Curvularia and Streptomyces. Among them, the Aspergillus genus which is able to produce ochratoxine, was found with an appearance frequency of 86.30 %.