A model for the noninvasive, habitat-inclusive estimation of upper limit abundance for synanthropes, exemplified by M. fascicularis.

Accurately estimating population sizes for free-ranging animals through noninvasive methods, such as camera trap images, remains particularly limited by small datasets. To overcome this, we developed a flexible model for estimating upper limit populations and exemplified it by studying a group-living synanthrope, the long-tailed macaque (Macaca fascicularis). Habitat preference maps, based on environmental and GPS data, were generated with a maximum entropy model and combined with data obtained from camera traps, line transect distance sampling, and direct sightings to produce an expected number of individuals. The mapping between habitat preference and number of individuals was optimized through a tunable parameter ρ (inquisitiveness) that accounts for repeated observations of individuals. Benchmarking against published data highlights the high accuracy of the model. Overall, this approach combines citizen science with scientific observations and reveals the long-tailed macaque populations to be (up to 80%) smaller than expected. The model's flexibility makes it suitable for many species, providing a scalable, noninvasive tool for wildlife conservation.

NeSiFC: Neighbors' Similarity-Based Fuzzy Community Detection Using Modified Local Random Walk.

This article proposes a neighbors' similarity-based fuzzy community detection (FCD) method, which we call "NeSiFC." In the proposed NeSiFC approach, we compute the similarity between two neighbors by introducing a modified local random walk (mLRW). Basically, in a network, a node and its' neighbors with noticeable similarities among them construct a community. To measure this similarity, we introduce a new metric, called the peripheral similarity index (PSI). This PSI is used to construct the transition probability matrix for the mLRW. The mLRW is applied for each node until it meets a parameter called step coefficient. The mLRW gives better neighbors' similarity for community detection. Finally, a fuzzy membership function is used iteratively to compute the membership degrees for all nodes with reference to existing communities. The proposed NeSiFC has no dependence on the network characteristics, and no adjustment or fine tuning of more than one parameter is needed. To show the efficacy of the proposed NeSiFC approach, we provide a thorough comparative performance analysis considering a set of well-known FCD algorithms viz., the genetic algorithm for fuzzy community detection, membership degree propagation, center-based fuzzy graph clustering, FMM/H2, and FuzAg on a set of popular benchmarks, as well as real-world datasets. For both disjoint and overlapping community structures, results of various accuracy and quality metrics indicate the outstanding performance of our proposed NeSiFC approach. The asymptotic complexity of the proposed NeSiFC is found as O(n2).

Study of structural, electronic and magnetic properties of Ti doped Co2FeGe Heusler alloy: Co2Fe1-xTixGe (x= 0, 0.5, and 0.75).

Tunability of structural, magnetic and electronic properties of Co2FeGe Heusler alloy is experimentally demonstrated by doping Ti in the Fe site (i.e. Co2Fe1-xTixGe), followed by in-depth first principle calculations. Co2FeGe in its pure phase shows very high saturation magnetization, Curie temperature and spin-wave stiffness constant which were reported in our earlier work. With gradual increase in Ti doping concentration (x= 0.5 and 0.75), the experimental saturation magnetization is found to be decreased to 4.3 µB/f.u. and 3.1 µB/f.u. respectively as compared to the parent alloy (x= 0) having the saturation magnetization of 6.1 µB/f.u. Variation of spinwave stiffness constant is also studied for differentxand found to be decreasing from peak value of 10.4 nm2 meV (forx= 0) to the least value of 2.56 nm2 meV forx= 0.5. Justification of the experimental results is given with first principle calculations. Computational phase diagram of the alloys is found in terms of formation energy showing that the doping in Fe site (i.e. Co2Fe1-xTixGe) is more stable rather than in Co site (i.e. Co2-xFeTixGe). The change in magnetic moment and half-metallicity with Ti doping concentration is better explained under GGA +Uapproach as compared to GGA approach signifying that the electron-electron correlation (U) has a distinct role to play in the alloys. Effect of variation ofUfor Ti atom is studied and optimized with reference to the experimental results. The dynamical stability of the Co2Fe1-xTixGe alloy crystal structure is explained in terms of phonon dispersion relations and the effect ofUon the phonon density of states is also explored. Close agreement between the experimental and theoretical results is observed.

HaVec: An Efficient de Bruijn Graph Construction Algorithm for Genome Assembly.

BACKGROUND: The rapid advancement of sequencing technologies has made it possible to regularly produce millions of high-quality reads from the DNA samples in the sequencing laboratories. To this end, the de Bruijn graph is a popular data structure in the genome assembly literature for efficient representation and processing of data. Due to the number of nodes in a de Bruijn graph, the main barrier here is the memory and runtime. Therefore, this area has received significant attention in contemporary literature. RESULTS: In this paper, we present an approach called HaVec that attempts to achieve a balance between the memory consumption and the running time. HaVec uses a hash table along with an auxiliary vector data structure to store the de Bruijn graph thereby improving the total memory usage and the running time. A critical and noteworthy feature of HaVec is that it exhibits no false positive error. CONCLUSIONS: In general, the graph construction procedure takes the major share of the time involved in an assembly process. HaVec can be seen as a significant advancement in this aspect. We anticipate that HaVec will be extremely useful in the de Bruijn graph-based genome assembly.