On the problem of the densest packing of spherical segments into a sphere

The paper considers a particular variant of the classical optimal packing problem when the container is a sphere, the packed elements are equal spherical caps, and the optimality criterion is to maximize their geodesic radius. At the same time, we deal with a special integral metric to determine the distance between points, which becomes Euclidean in the simplest case. We propose a heuristic numerical algorithm based on the construction of spherical Voronoi diagrams, which makes it possible to obtain a locally optimal solution to the problem under consideration. Numerical calculations show the operability and effectiveness of the proposed method and allow us to draw some conclusions about the properties of packings

Developing a restaurant recommended system via the Vietnamese food image classification

A recommendation system is a system that recommends products and services to users based on daily online searching habits. The recommender system is applied in many fields such as job searching, health care, education, music, and tourism. However, few studies have combined computer vision and collaborative filtering to build a restaurant recommendation system in the tourism sector. In this study, we presented a solution to build a restaurant recommendation system through Vietnamese food image classification. First, we used ResNet-34 which is a variant of the convolutional neural network to classify Vietnamese food images. Then, the system applied the alternative least square technique in matrix factorization and Apache Spark in distributed computing to train the restaurant location dataset. The output was the most relevant restaurant places list to show many choices to users. The experimental datasets included the Vietnamese image and the restaurant location datasets that were collected from kaggle.com and foody.vn websites. For image classification task evaluation, we compared ResNet-34 to variants of ResNet. For the restaurant recommendation task evaluation, we compared alternative least squares with k-nearest neighbor. The comparison results show that the proposed solution is better than traditional popular models

Synergic Activity Against MCF-7 Breast Cancer Cell Growth of Nanocurcumin-Encapsulated and Cisplatin-Complexed Nanogels

Nanogel-based systems loaded with single anticancer drugs display miscellaneous effectiveness in tumor remission, gradually circumventing mutation and resistance in chemotherapy. Hence, the existence of dual-drug delivered nano-sized systems has been contemporaneous with drug development and preceded the conventional-dose chemotherapy. Among outstanding synergistic drug nanoplatforms, thermosensitive copolymer heparin-Pluronic F127 (Hep-F127) co-delivering cisplatin (CDDP) and curcumins (Cur) (Hep-F127/CDDP/Cur) has emerged as a notable candidate for temperature-responsive drug delivery. The procedure was based on the entrapment of curcumin into the hydrophobic core of bio-degradable co-polymer Hep-F127 while the hydrophilic drug CDDP subsequently conjugated to the backbone heparin to form the core-shell structure. The copolymer was characterized by Fourier transform infrared (FT-IR) spectrophotometry, Transmission Electron Microscopy (TEM), and Dynamic Light Scattering (DLS), to corroborate the successful synthesis and via HPLC along with AES-ICP to evaluate the high drug loading along with a controllable release from the nano-gels. A well-defined nano-shell with size in the 129.3 ± 3.8 nm size range could enhance higher the efficacy of the conjugated-CDDP to Hep-F127 than that of single doses. Moreover, the considerable amount of dual-drug released from thermosensitive nanogels between different conditions (pH = 7.4 and pH = 5.5) in comparison to CDDP from Hep-F127 partially indicated the significantly anti-proliferative ability of Hep-F127/CDDP/Cur to the MCF-7 cell line. Remarkably, drug testing in a xenograft model elucidates the intricate synergism of co-delivery in suppressing tumor growth, which remedies some of the problems affecting in cancer chemotherapy

A review of the applicability of existing tree and forest characteristics prediction models to forest inventory in Vietnam and Nepal

Forest inventories provide vital and up-to-date information for use in basic decision making on the ma¬nagement and conservation of forest resources. Data collected in forest inventories are stored and pro¬cessed in databases which can be updated by conducting additional measurements or by applying pre¬dictive models for imputing missing values of tree and forest stand-level variables. The inventory results can thereafter be calculated based on sample units, i.e. sample plots or forest stands within them, after which the forest inventory variables can be aggregated using different stratification units. For strategic decision-making, however, the future development of forest resources needs to be predicted. For this purpose, growth and yield simulators comprising tree and stand-level growth models are utilised to ob¬tain prediction results for alternative scenarios based on inventory information, i.e. sample-based field data. In large-scale forest inventories, only easily assessable characteristics are measured for all tallied trees, whereas height characteristics and other variables, which are difficult to measure accurately, are collected from a sub-sample only. In order to generalise the variables measured from sample trees to also cover tally trees, generalization techniques need to be applied. The ongoing national-level forest as¬sessments conducted in Nepal and Vietnam require efficient calculation procedures for reporting inven¬tory results and quantifying the availability and location of forest resources. The aim of this review was to assess the availability of the existing models for the prediction of tree and forest characteristics and their applicability to large-scale forest inventory in Nepal and Vietnam. Through comparisons made bet¬ween country- and species-specific models and prediction systems and through an assessment based on modelling literature, recommendations are also given for further developing the model-based prediction systems used in the ongoing national forest inventories of Nepal and Vietnam. The existing model sets can be used to estimate conventional stand volume characteristics for the inventoried areas. However, according to the new reporting requirements set for the current National Forest Inventory (NFI) of Viet¬nam and the Forest Resource Assessment (FRA) of Nepal, it is recommended that their model bases, which are currently under upgrading, be updated and improved in the future