Andreev bound states with opposite phase-inversion asymmetries are observed in local tunneling spectra at the two ends of a superconductor-semiconductor-superconductor planar Josephson junction in ...the presence of a perpendicular magnetic field, while the nonlocal spectra remain phase symmetric. Spectral signatures agree with a theoretical model, yielding a physical picture in which phase textures in superconducting leads localize and control the position of Andreev bound states in the junction, demonstrating a simple means of controlling the position and size of Andreev states within a planar junction.
Research in corpus-driven Automatic Speech Recognition (ASR) is advancing rapidly towards building a robust Large Vocabulary Continuous Speech Recognition (LVCSR) system. Under-resourced languages ...like Bangla require benchmarking large corpora for more research on LVCSR to tackle their limitations and avoid the biased results. In this paper, a publicly published large-scale Bangladeshi Bangla speech corpus is used to implement deep Convolutional Neural Network (CNN) based model and Recurrent Neural Network (RNN) based model with Connectionist Temporal Classification (CTC) loss function for Bangla LVCSR. In experimental evaluations, we find that CNN-based architecture yields superior results over the RNN-based approach. This study also emphasizes assessing the quality of an open-source large-scale Bangladeshi Bangla speech corpus and investigating the effect of the various high-order N-gram Language Models (LM) on a morphologically rich language Bangla. We achieve 36.12% word error rate (WER) using CNN-based acoustic model and 13.93% WER using beam search decoding with 5-gram LM. The findings demonstrate by far the state-of-the-art performance of any Bangla LVCSR system on a specific benchmarked large corpus.
In analogy to conventional semiconductor diodes, the Josephson diode exhibits superconducting properties that are asymmetric in applied bias. The effect has been investigated in a number of systems ...recently, and requires a combination of broken time-reversal and inversion symmetries. We demonstrate a dual of the usual Josephson diode effect, a nonreciprocal response of Andreev bound states to a superconducting phase difference across the normal region of a superconductor-normal-superconductor Josephson junction, fabricated using an epitaxial InAs/Al heterostructure. Phase asymmetry of the subgap Andreev spectrum is absent in the absence of in-plane magnetic field and reaches a maximum at 0.15 T applied in the plane of the junction transverse to the current direction. We interpret the phase diode effect in this system as resulting from finite-momentum Cooper pairing due to orbital coupling to the in-plane magnetic field. At higher magnetic fields, we observe a sign reversal of the diode effect that appears together with a reopening of the spectral gap. Within our model, the sign reversal of the diode effect at higher fields is correlated with a topological phase transition that requires Zeeman and spin-orbit interactions in addition to orbital coupling.
Despite huge improvements in automatic speech recognition (ASR) employing neural networks, ASR systems still suffer from a lack of robustness and generalizability issues due to domain shifting. This ...is mainly because principal corpus design criteria are often not identified and examined adequately while compiling ASR datasets. In this study, we investigate the robustness of the fully supervised convolutional neural networks (CNNs), and the state-of-the-art transfer learning approaches, namely self-supervised wav2vec 2.0 and weakly supervised Whisper for multi-domain ASR. We also demonstrate the significance of domain selection while building a corpus by assessing these models on a novel multi-domain Bangladeshi Bangla ASR evaluation benchmark-BanSpeech, which contains approximately 6.52 hours of human-annotated speech, totaling 8085 utterances, across 13 distinct domains. SUBAK.KO, a mostly read speech corpus for the morphologically rich language Bangla, has been used to train the ASR systems. Experimental evaluation reveals that self-supervised cross-lingual pre-training with wav2vec 2.0 is the best strategy compared to weak supervision and full supervision to tackle the multi-domain ASR task. Moreover, the ASR models trained on SUBAK.KO face difficulty recognizing speech from domains with mostly spontaneous speech. The BanSpeech is publicly available to meet the need for a challenging evaluation benchmark for Bangla ASR.<xref ref-type="fn" rid="fn1">1
•Development of language resource of Bangladeshi bangla spoken language (BBSL).•Development of a large speech corpus named সুবাক্য (SUBAK.KO).•Evaluation of the strength and weakness of SUBAK.KO ...corpus by comparing it with another similar kind of open-source large corpus.•SUBAK.KO is a more balanced corpus compared to the open-source large corpus by google.•SUBAK.KO contains most of the regional accented speakers’ variability of Bangladeshi bangla.
This article reports the development of language resource for Bangladeshi Bangla spoken language (BBSL). Bangladeshi Bangla has inadequate large speech corpora for Large Vocabulary Continuous Speech Recognition (LVCSR) system. The accuracy of the automatic speech recognition (ASR) system rests on the quality of the speech corpus. This work discusses the common issues and activities related to the development of a large speech corpus named ▪ (SUBAK.KO). This corpus is designed to support ASR research in Bangladeshi Bangla. It has been labeled sentence-wise. We have trained this corpus with one of the well-known current End-to-End ASR algorithms, Recurrent Neural Networks (RNNs) with Connectionist Temporal Classification (CTC). To know the strengths and weaknesses, the CER (Character Error Rate) and the WER (Word Error Rate) of the trained RNNCTC model have been observed. Another open-source large Bangla ASR corpus has been trained using the same ASR algorithm. Both trained models have been compared to assess the quality of these corpora. It has been found that SUBAK.KO is a more balanced corpus and considered more regional accented speech variability for a LVCSR system compared to that open-source large Bangla ASR corpus.
Radio frequency identification (RFID) is a unique scientific invention that comprises individually recognizable, low-cost tags and readers where the readers monitor the tags using frequencies from ...the radio spectrum. Uniform distribution of the tags for gaining a balanced load of the readers is a significant concern to ensure successful collection of data from all of the tags of an RFID system with multiple readers. Moreover, some of the readers in an RFID network may become defective during operation and stop working. As a result, information would not be collected from those tags which were associated with the defective readers and the network would operate with partial information. We target to maintain a balance among the load of the readers by placing the tags as evenly as possible to address the fast tag reading problem. We convert the addressed issue as a load balancing problem and introduce a cellular automaton inspired localized algorithm as a solution to this problem. Our proposed algorithm utilizes the local information of the readers to relocate tags from a heavily loaded reader to a lightly loaded reader. We develop our proposed algorithm as a fault tolerant one so that all of the tags in the network are always under surveillance even if some of the readers become defective. Numerical analysis and comparison results suggest that the proposed localized load balancing algorithm outperforms the existing localized solution and gives a competitive result compared to the centralized algorithm. Finally, we implement our proposed algorithm in the parallel programming platform Compute Unified Device Architecture that greatly improves the runtime of the proposed algorithm.
Background
The principles of global surgery should be taught as a part of the core curriculum in medical schools. The need for medical students to be familiar with the topic is increasing in ...acceptance. There is, however, a paucity of data on how medical students are exposed to global surgery. This study aims to evaluate exposure of medical students to global surgery, awareness of the key messages of the Lancet Commission on Global Surgery, global surgery career aspirations and barriers to said aspirations.
Methods
ISOMERS was a multi-centre, online, cross-sectional survey of final year medical students globally. The questionnaire utilised a combination of Likert-scale, multiple-choice, and free text questions.
Results
In this study, 1593 final year medical students from 144 medical schools in 20 countries participated. The majority (
n
= 869/1496, 58.1%) believed global surgery to be relevant, despite 17.7% (
n
= 271/1535) having any exposure to global surgery. Most participants (
n
= 1187/1476, 80.4%) wanted additional resources on global surgery. Difficulty in providing appropriate care for patients living abroad (
n
= 854/1242, 68.8%) was the most common perceived barrier to a career in global surgery.
Conclusions
Participants believed global surgery was a relevant topic for medical students and wanted additional resources that they could access on global surgery. It is critical for medical students to become aware that global surgery is a field that aims to address inequity in surgical care not just internationally, but nationally and locally as well.
Possible protective effects of saffron (Crocus sativus L) have been reported in several randomized clinical trials (RCTs). Current systematic review was performed to summarize the efficacy of saffron ...intake on liver enzymes.
An electronic database search was conducted on PubMed/Medline, Scopus, Web of Science, and Cochrane for RCTs comparing effect of saffron and placebo on liver enzymes from inception to July 2021. There was no restriction in language of included studies and we calculated the standardized mean difference (SMD) and 95% Confidence Intervals (CI) for each variable. Random-effect model was used to calculate effect size.
Eight studies (n = 463 participants) were included in the systematic review. The saffron intake was associated with a statistically significant decrease in aspartate aminotransferase (AST) (SMD: −0.18; 95% CI: −0.34, −0.02; I2 = 0%) in comparison to placebo intake. Our results also indicated that saffron consumption did not have a significant effect on alanine aminotransferase (ALT) (SMD: −0.14; 95% CI: −0.36, 0.09; I2 = 47.0%) and alkaline phosphatase (ALP) levels (SMD: 0.14; 95% CI: −0.18, 0.46; I2 = 42.9%) compared to placebo.
Saffron intake showed beneficial impacts on circulating AST levels. However, larger well-designed RCTs are still needed to clarify the effect of saffron intake on these and other liver enzymes.
•Saffron may possess anti-oxidant, anti-inflammatory, and cytotoxic effects.•Saffron intake showed beneficial impacts on circulating AST levels.•Larger well-designed RCTs are still needed to clarify the effect of saffron intake on ALT and ALP.
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