N-Heterocyclic Carbene-Catalyzed Random Copolymerization of N-Carboxyanhydrides of α-Amino Acids

Synthetic polypeptides prepared from N-carboxyanhydrides (NCAs) of α-amino acids are useful for elucidating the relationship between the primary structure of natural peptides and their immunogenicity. In this study, complex copolypeptide sequences were prepared using a recently developed technique; specifically, the random copolymerization of l-alanine NCA with NCAs of l-glutamic acid 5-benzylester (Bn-Glu NCA), S-benzyl-cysteine (Bn-Cys NCA), O-benzyl-l-serine (Bn-Ser NCA), and l-phenylalanine (Phe NCA) was performed using N-heterocyclic carbene (NHC) catalysts. The NHC-initiated Ala NCA/Bn-Glu NCA and Ala NCA/Bn-Cys NCA copolymerization reactions achieved 90% conversion within 30 min. The reactivity ratio values estimated using the Kelen and Tüdos method show that poly(Bn-Glu-co-Ala) and poly(Bn-Cys-co-Ala) have random repeating units with rich alternating sequences, whereas poly(Bn-Ser-co-Ala) and poly(Phe-co-Ala) contain a larger proportion of Ala-repeating units than Bn-Ser and Phe in random placement.

Evaluating the correlation between area, environmental heterogeneity, and species richness using terrestrial isopods (Oniscidea) from the Pontine Islands (West Mediterranean)

Area and environmental heterogeneity influence species richness in islands. Whether area or environmental heterogeneity is more relevant in determining species richness is a central issue in island biogeography. Several models have been proposed, addressing the issue, and they can be reconducted to three main hypotheses developed to explain the species-area relationship: (1) the area-per se hypothesis (known also as the extinction-colonisation equilibrium), (2) the random placement (passive sampling), and the (3) environmental heterogeneity (habitat diversity). In this paper, considering also the possible influence of geographic distance on island species richness, we explore the correlation between area, environmental heterogeneity, and species richness by using faunistic data of Oniscidea inhabiting the Pontine Islands, a group of five small volcanic islands and several islets in the Tyrrhenian Sea, located about 60 km from the Italian mainland. We found that the colonisation of large Pontine Islands may occur via processes independent of geographic distance which could instead be an important factor at a much smaller scale. Such processes may be driven by a combination of anthropogenic influences and natural events. Even in very small-size island systems, environmental heterogeneity mostly contributes to species richness. Environmental heterogeneity could influence the taxocenosis structure and, ultimately, the number of species of Oniscidea via direct and indirect effects, these last mediated by area which may or may not have a direct effect on species richness.

The effect of NPK fertilizer with different dosage on the growth rate seaweed (Caulerpa racemosa)

NPK is a type of fertilizer that plays a role in increasing growth and survival in plants such as seaweed. This study aims to determine the effect of different NPK fertilizer doses on the growth rate of seaweed (Caulerpa racemosa), and to determine which NPK fertilizer dosage has the best effect on the growth rate of C. racemosa. Research begins with collecting samples of seaweed in coastal waters. Ternate Island District Kastela, and the cultivation process is carried out on Jalan Jan, Tabona Village, South Ternate City. The time of the research was two months from August to October, 2020. This study used 12 units of cool box in the form of cork with a size of 90 x 30 cm, which is used as a container for maintaining of C. racemosa. In each treatment using a seed weight of 50 grams. The NPK fertilizer dosage treatment tested was 4 doses, with 3 replications, namely: treatment A: 40 ml NPK fertilizer; B: 60 ml NPK fertilizer; C: 80 ml NPK fertilizer; D: 0 ml NPK fertilizer (control). Research containers using random placement. The design used was a completely randomized design (CRD), using analysis of variance (ANOVA). The results obtained showed that NPK fertilizer with different doses the effect is not significantly different on the growth rate of C. racemosa with the highest average growth rate in treatment C amounting to 8.725%, followed by treatment B of 8.178%, treatment A of 7.761%, and the lowest was treatment D of 6.519%.Keywords:NPKSeaweedCaulerpa racemosaGrowth rate

Relating the Strength of Density Dependence and the Spatial Distribution of Individuals

Spatial patterns in ecology contain useful information about underlying mechanisms and processes. Although there are many summary statistics used to quantify these spatial patterns, there are far fewer models that directly link explicit ecological mechanisms to observed patterns easily derived from available data. We present a model of intraspecific spatial aggregation that quantitatively relates static spatial patterning to negative density dependence. Individuals are placed according to the colonization rule consistent with the Maximum Entropy Theory of Ecology (METE), and die with probability proportional to their abundance raised to a power α, a parameter indicating the degree of density dependence. This model can therefore be interpreted as a hybridization of MaxEnt and mechanism. Our model shows quantitatively and generally that increasing density dependence randomizes spatial patterning. α = 1 recovers the strongly aggregated METE distribution that is consistent with many ecosystems empirically, and as α → 2 our prediction approaches the binomial distribution consistent with random placement. For 1 < α < 2, our model predicts more aggregation than random placement but less than METE. We additionally relate our mechanistic parameter α to the statistical aggregation parameter k in the negative binomial distribution, giving it an ecological interpretation in the context of density dependence. We use our model to analyze two contrasting datasets, a 50 ha tropical forest and a 64 m2 serpentine grassland plot. For each dataset, we infer α for individual species as well as a community α parameter. We find that α is generally larger in the tightly packed forest than the sparse grassland, and the degree of density dependence increases at smaller scales. These results are consistent with current understanding in both ecosystems, and we infer this underlying density dependence using only empirical spatial patterns. Our model can easily be applied to other datasets where spatially explicit data are available.

Randomized Self-Organizing Map

We propose a variation of the self-organizing map algorithm by considering the random placement of neurons on a two-dimensional manifold, following a blue noise distribution from which various topologies can be derived. These topologies possess random (but controllable) discontinuities that allow for a more flexible self- organization, especially with high-dimensional data. The proposed algorithm is tested on one-, two- and three-dimensional tasks, as well as on the MNIST handwritten digits data set and validated using spectral analysis and topological data analysis tools. We also demonstrate the ability of the randomized self-organizing map to gracefully reorganize itself in case of neural lesion and/or neurogenesis.

Matching-based cache placement decision for 5G network caching

In this thesis, we present a cache placement scheme to deal with backhaul link constraint in Small Cell Network for 5G wireless network. We formulated the cache placement problem as a graph matching problem and presented an optimal file-helper matching algorithm. We defined stability criterion for the matching and found that our matching solution is stable in the sense that every helper finds at least one file to cache given that no file exceed minimum cache size. We achieved a unique placement of a file within a cluster of helpers to increase the number of files cached within a cluster. Further, our experimental evaluation demonstrates that our algorithm increases local and neighbor hit ratios as compared to a random placement, which in turn significantly decreases the traffic that goes over the backhaul bottleneck link.

Matching-based cache placement decision for 5G network caching

In this thesis, we present a cache placement scheme to deal with backhaul link constraint in Small Cell Network for 5G wireless network. We formulated the cache placement problem as a graph matching problem and presented an optimal file-helper matching algorithm. We defined stability criterion for the matching and found that our matching solution is stable in the sense that every helper finds at least one file to cache given that no file exceed minimum cache size. We achieved a unique placement of a file within a cluster of helpers to increase the number of files cached within a cluster. Further, our experimental evaluation demonstrates that our algorithm increases local and neighbor hit ratios as compared to a random placement, which in turn significantly decreases the traffic that goes over the backhaul bottleneck link.

Features Application of the Dissection-Placing Method for Secure Data Storage in External Data Warehouses

The article considers the application of the dissection-placing method for secure storage of information in external, primarily cloud-based data warehouses. Various approaches to the implementation of the method, including patent material, are analyzed. It is shown that the method is most effective for bitwise dissection of files and random placement of bits in data streams sent to separate warehouses.