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Precise estimation of the rare direct 3α decay of the Hoyle state of 12C has been made to unveil its unusual α-cluster configurations ranging from linear 3α chain structure to diffuse Bose gas as well as Bose Einstein condensate. The present new high precision, nearly zero background experimental study with 1.6×105 Hoyle events has converged on the upper limit for direct decay at ∼0.019% with 95% confidence limit, which is more than a factor of 2 lower than the limit obtained in the previous studies. Keywords: 3α cluster state, 12C(α, α)3α reaction, Complete kinematics reaction, The Hoyle state decay, Direct versus sequential decay, Inelastic scattering

The emergence of a new era reaching beyond current state-of-the-art ultrashort and ultraintense laser technology has been enabled by the approval of around € 850 million worth of structural funds in 2011–2012 by the European Commission for the installation of Extreme Light Infrastructure (ELI). The ELI project consists of three pillars being built in the Czech Republic, Hungary, and Romania. This challenging proposal is based on recent technical progress allowing ultraintense laser fields in which intensities will soon be reaching as high as I0 ∼ 1023 W cm−2. This tremendous technological advance has been brought about by the invention of chirped pulse amplification by Mourou and Strickland. Romania is hosting the ELI for Nuclear Physics (ELI-NP) pillar in Măgurele near Bucharest. The new facility, currently under construction, is intended to serve the broad national, European, and international scientific community. Its mission covers scientific research at the frontier of knowledge involving two domains. The first is laser-driven experiments related to NP, strong-field quantum electrodynamics, and associated vacuum effects. The second research domain is based on the establishment of a Compton-backscattering-based, high-brilliance, and intense γ beam with Eγ ≲ 19.5 MeV, which represents a merger between laser and accelerator technology. This system will allow the investigation of the nuclear structure of selected isotopes and nuclear reactions of relevance, for example, to astrophysics with hitherto unprecedented resolution and accuracy. In addition to fundamental themes, a large number of applications with significant societal impact will be developed. The implementation of the project started in January 2013 and is spearheaded by the ELI-NP/Horia Hulubei National Institute for Physics and Nuclear Engineering (IFIN-HH). Experiments will begin in early 2020.

The High-spin states in 195Tl, populated through the 185,187Re(13C, xn) fusion evaporation reaction at the beam energy of 75 MeV, were studied using the Indian National Gamma Array (INGA). More than 50 new γ transitions have been placed in the proposed level scheme which is extended up to the excitation energy of ≈ 5.6 MeV and spin=22.5ħ. Two pairs of degenerate bands based on two different quasi-particle configurations have been identified in this nucleus indicating the first observation of such bands in an odd-A nucleus in A∼190 region and signify the first evidence of multiple chiral bands in a nucleus in this region. The total Routhian surface calculations predict triaxial shapes for both the configurations and thereby, support the experimental observation. The importance of multiple neutron holes in the i13/2 orbital and the stability of shapes for these two configurations have been discussed. Keywords: Nuclear Structure, γ-ray spectroscopy, Doubly degenerate bands, TRS calculation

The phenomenon of collective enhancement in nuclear level density and its fadeout has been probed using neutron evaporation study of two strongly deformed (173Lu, 185Re), and one spherical (201Tl) compound nuclei over the excitation energy (E⁎) range of ∼22–56 MeV. Clear signature of the fadeout of collective enhancement in nuclear level density was observed for the first time in both the deformed evaporation residues 172Lu and 184Re at an excitation energy range ∼14–21 MeV. Calculations based on finite temperature density functional theory, as well as macroscopic–microscopic shape transition model, have strongly established a close correlation between the observed fadeout of collective enhancement and a deformed to spherical nuclear shape transition in these nuclei occurring in the same excitation energy zone. Interestingly, a weak signature of fadeout has also been observed for the spherical residue 200Tl. This is due to a similar shape transition of the deformed excited state configuration of 200Tl.

Abstract Background Clinical trials play a crucial role in biomedical research, and it is important to register them in public registries to ensure transparency and prevent research waste. In this study, we wished to determine what steps need to be taken to identify every clinical trial run in India that has been registered in any of the (non-Indian) World Health Organization-recognised primary registries. Of the 16 registries, we studied all except that of the European Union, which will be studied separately. Methods Two methodologies were employed for each registry, except for four that did not facilitate one or the other method. Methodology A involved downloading all the records in a registry and querying them. Methodology B involved conducting a search via the registry website. Results Only four registries provided consistent results with both methodologies. Seven registries had different results from the two methodologies. Of these, in four cases, in Methodology A one field indicated that the study ran in India, while another indicated otherwise. Conclusions The above-mentioned ambiguities should be addressed by the concerned registries. Overall, this study reinforces the need for improved data accuracy and transparency in clinical trial registries and emphasizes the importance of resolving complications faced by users while navigating the registries. Ensuring accurate and comprehensive registration of clinical trials is essential for meta-research and the use of such data by a variety of stakeholders.

Sea level rise (SLR) is a crucial indicator of climate change, primarily driven by greenhouse gas emissions and the subsequent increase in global temperatures. The impact of SLR, however, varies regionally due to factors such as ocean bathymetry, resulting in distinct shifts across different areas compared to the global average. Understanding the complex factors influencing SLR across diverse spatial scales, along with the associated uncertainties, is essential. This study focuses on the East Coast of the United States and Gulf of Mexico, utilizing historical SLR data from 1993 to 2023. To forecast SLR trends from 2024 to 2103, a weighted ensemble model comprising SARIMAX, LSTM, and exponential smoothing models was employed. Additionally, using historical greenhouse gas data, an ensemble of LSTM models was used to predict real-time SLR values, achieving a testing loss of 0.005. Furthermore, conductance and dissolved oxygen (DO) values were assessed for the entire forecasting period, leveraging forecasted SLR trends to evaluate the impacts on marine life, agriculture, and infrastructure.

Groundnut (Arachis hypogaea) is a widely cultivated legume crop that plays a vital role in global agriculture and food security. It is a major source of vegetable oil and protein for human consumption, as well as a cash crop for farmers in many regions. Despite the importance of this crop to household food security and income, diseases, particularly Leaf spot (early and late), Alternaria leaf spot, Rust, and Rosette, have had a significant impact on its production. Deep learning (DL) techniques, especially convolutional neural networks (CNNs), have demonstrated significant ability for early diagnosis of the plant leaf diseases. However, the availability of groundnut-specific datasets for training and evaluation of DL models is limited, hindering the development and benchmarking of groundnut-related deep learning applications. Therefore, this study provides a dataset of groundnut leaf images, both diseased and healthy, captured in real cultivation fields at Ramchandrapur, Purba Medinipur, West Bengal, using a smartphone camera. The dataset contains a total of 1720 original images, that can be utilized to train DL models to detect groundnut leaf diseases at an early stage. Additionally, we provide baseline results of applying state-of-the-art CNN architectures on the dataset for groundnut disease classification, demonstrating the potential of the dataset for advancing groundnut-related research using deep learning. The aim of creating this dataset is to facilitate in the creation of sophisticated methods that will aid farmers accurately identify diseases and enhance groundnut yields.

BackgroundIn the past, clinical trials run in India have been the subject of criticism. Among other steps to improve the trial ecosystem, for some time the government limited the number of trials that a Principal Investigator (PI) could run to three at a time. We were interested to know how many trials PIs in India tend to run at a time.MethodsWe accessed the 52,149 trial records hosted by the Clinical Trials Registry—India in April 2023. Of these, we shortlisted trials that had run in India, were interventional, and involved certain interventions such as drug, biological etc. We used multiple parameters, such as email ID, phone number etc. to determine whether one name always represented the same PI and whether two names corresponded to the same PI. We then determined how many trials each PI had run.ResultsWe found that 3,916 unique PI names were associated with 6,665 trials. Of these, 2,963 (75.7%) PIs had run a single study. Only 251 (6.4%) had run more than three trials. A mere 14 PIs had run 20 or more trials. The 14 PIs were affiliated with local pharma companies (6), local or global contract research organizations (4), multinational pharma companies (3) and the Central Council for Research in Homeopathy (1). The maximum number of trials run by a single PI was 108. Of these, the largest number run in a single year, 2022, was 53.ConclusionEach PI name needs to be connected to a unique ID that does not change with time, so that it is easier to track the number of trials that a given PI has run. The number of studies run by a given PI at a given time must not be excessive and needs to be monitored more actively. The government needs to consider whether a cap on the number of trials that a PI runs at a time is required and what infrastructure needs to be in place to facilitate higher numbers of trials. Trial registry records need to be updated more regularly. Other countries may wish to do likewise.