Dilute stuffing in the pyrochlore iridate Eu2Ir2O7Eu_2Ir_2O_7

The pyrochlore Eu$_2$Ir$_2$O$_7$ has recently attracted significant attention as a candidate Weyl semimetal. The previous reports on this compound unanimously show a thermally induced metal to insulator (MI) transition, concomitant with antiferromagnetic (AFM) long-range ordering of the Ir-moments below T$_\textit{N} \sim$120 K. However, there are contradictory reports concerning the slope d$\rho/$dT of the resistivity plots ($\rho$) in the "metallic" state above the metal-insulator (MI) transition, and the value of $\rho$ in the insulating state, both of which show significant sample dependence. Here, we explore this issue by investigating six different Eu$_2$Ir$_2$O$_7$ samples with slightly varying Eu:Ir ratio. High-resolution synchrotron powder diffraction are done to probe minor variations in the cell parameters of the various Eu$_2$Ir$_2$O$_7$ samples investigated here. Specific heat (C$_p$) and magnetic susceptibility of all the samples showed long-range antiferromagnetic ordering upon cooling below T$_\textit{N} \sim$120 K. The transitions are, however, found to be smeared out for the off-stoichiometric samples. We show that the sign of d$\rho/$dT above the metal-insulator (MI) transition is highly sensitive to the unit cell length, which, in turn, depends on the level of Eu-stuffing at the Ir-site. Samples with composition close to the ideal stoichiometry (Eu : Ir $=$ 1) showed a change of sign of d$\rho/$dT from negative to positive upon cooling below a certain temperature T $^*$ $>$ T$_\textit{MI}$. With increasing Eu-stuffing T$^*$ decreased until a negative d$\rho/$dT persisted without any sign change down to T$_\textit{MI}$.Comment: 12 pages, 7 figure

Overlap-aware End-to-End Supervised Hierarchical Graph Clustering for Speaker Diarization

Speaker diarization, the task of segmenting an audio recording based on speaker identity, constitutes an important speech pre-processing step for several downstream applications. The conventional approach to diarization involves multiple steps of embedding extraction and clustering, which are often optimized in an isolated fashion. While end-to-end diarization systems attempt to learn a single model for the task, they are often cumbersome to train and require large supervised datasets. In this paper, we propose an end-to-end supervised hierarchical clustering algorithm based on graph neural networks (GNN), called End-to-end Supervised HierARchical Clustering (E-SHARC). The E-SHARC approach uses front-end mel-filterbank features as input and jointly learns an embedding extractor and the GNN clustering module, performing representation learning, metric learning, and clustering with end-to-end optimization. Further, with additional inputs from an external overlap detector, the E-SHARC approach is capable of predicting the speakers in the overlapping speech regions. The experimental evaluation on several benchmark datasets like AMI, VoxConverse and DISPLACE, illustrates that the proposed E-SHARC framework improves significantly over the state-of-art diarization systems.Comment: 10 page

Selection method by fuzzy set theory and preference matrix

In fuzzy decision making problems, fuzzy ranking is one of the most preferred aeras. The aim of this paper to develop a new ranking method which is reliable and doesnot need tremendous arithmetic calculations. Also it can be used for all type of fuzzy numbers which are represented as crisp form or in linguistic form. Fuzzy multi criteria decision making commonly employs methods such as ordering method,Fuzzy Analytic Hierarchy Process [FAHP], Fuzzy Technique for Order Preference by Similarity to Ideal Solution [FTOPSIS]and hybrid method. The FAHP commonly uses triangular fuzzy numbers and trapezoidal fuzzy numbers while the FTOPSIS method identifies the best alternative as the one that is nearest to the positive ideal solution and farthest to the negative ideal solution. Although both these methods have been widely used, they have their drawbacks. The accuracy of these methods decreases as the number of alternative increases i.e. the more complex the problem, less the accuracy and all the methods have many computations. In order to overcome this problem, we propose a method which is a combination of method of Blin and Whinston(1973) and method of Shimura(1973). This way the advantages of both the methods may be utilized to arrive at a decision that involves vague data. In this  paper, we use the concept of preference matrix to find the membership grades and calculate the ranking. Keywords: Fuzzy set, preference matrix, multi person decision making, multi criteria decision making(MCDM), relativity function matrix

Deep Self-Supervised Hierarchical Clustering for Speaker Diarization

The state-of-the-art speaker diarization systems use agglomerative hierarchical clustering (AHC) which performs the clustering of previously learned neural embeddings. While the clustering approach attempts to identify speaker clusters, the AHC algorithm does not involve any further learning. In this paper, we propose a novel algorithm for hierarchical clustering which combines the speaker clustering along with a representation learning framework. The proposed approach is based on principles of self-supervised learning where the self-supervision is derived from the clustering algorithm. The representation learning network is trained with a regularized triplet loss using the clustering solution at the current step while the clustering algorithm uses the deep embeddings from the representation learning step. By combining the self-supervision based representation learning along with the clustering algorithm, we show that the proposed algorithm improves significantly 29% relative improvement) over the AHC algorithm with cosine similarity for a speaker diarization task on CALLHOME dataset. In addition, the proposed approach also improves over the state-of-the-art system with PLDA affinity matrix with 10% relative improvement in DER.Comment: 5 pages, Accepted in Interspeech 202

Assay of Bacillus cereus Emetic toxin produced in orange squash

The contamination of squash by B. cereus, an enterotoxin producer, was found to range between 7.5×104  and 1.8×104 CFU/g in orange squash (during storage), that is hazardous. Orange squash is widely produced and consumed in India, but has a low rating of 3 on the scale of 10 (on feedback), mostly due to high sugars, not preferred these days. It can be preserved for >9 months due to added sugars and preservatives. During processing squash, if juice is not quickly cooled and/or squash is kept for long at temperatures <48 °C after processing, it can be a source of food poisoning. Reason, a large number of toxins can be produced by B. cereus. B. cereus strains, isolated from squash, produce heat stable toxin. Vacuolar assay confirmed them as emetic toxins, produced in squash. The toxin behaved like an ionophore in assay using mitochondria, extracted from liver cells of chicken with potassium ions in buffer. The toxicity of toxin by assay was 3200 IU/ng (BC IV strain) and 800 IU/ng (BC X strain). By the vacuolar expansions of mitochondria in assay, toxins of B. cereus demonstrated a toxic effect, in the range of 20.93 to 60.94 % by BC IV toxin and 43.28 to 45.02 % by BC X toxin, on the 3rd day growth of B. cereus in squash and toxin extraction for assay. It was also possible to produce antibodies against the B. cereus whole cell and toxin of BC IV, as an attempt to detect B. cereus contaminations in foods, by Ouchterlony’s immune-diffusion tes

Anomalous lattice contraction and emergent electronic phases in Bi-doped Eu2_2Ir2_2O7_7

We study the pyrochlore series (Eu$_{1-x}$Bi$_x$)$_2$Ir$_2$O$_7$ for $0 \leq x \leq 1$. We show that for small $x$, the lattice undergoes an anomalous contraction but the all-in/all-out and metal-to-insulator transitions remain robust, and the resistivity approaches a $1/T$ dependence at low-T, suggesting proximity to the Weyl semimetallic phase, as previously predicted theoretically. At the boundary between Eu$_2$Ir$_2$O$_7$ and Bi$_2$Ir$_2$O$_7$ a qualitatively different ground state emerges, which is characterized by its unusual metallic behavior and absence of magnetic ordering at least down to $0.02$ K.Comment: 5 Pages, 4 figure