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Geological fault detection is a crucial aspect of oil exploration. With the advancements in deep learning, the challenging task of accurate fault detection has gained popularity. While traditional deep learning methods struggle due to the small sample problem and the labor-intensive fault labeling process, training a deep learning model solely on synthetic seismic data may not yield satisfactory results due to the disparities between synthetic and real seismic data. To mitigate the impact of these differences, we propose employing an instance weighting (IW)-based transfer learning (TL). This approach involves utilizing a pretrained deep-learning model to extract fault-related features from seismic data. By leveraging the knowledge learned from a different but related task, the TL model can capture general fault patterns that can be applicable to real seismic data. In this framework, a portion of the pretrained model is employed to learn fault-related features, which can then be fine-tuned using a smaller amount of labeled real seismic data. This allows the model to adapt to the complexities of the actual geological situation and improve fault detection performance in field data applications. The proposed method has been tested on the Indian Krishna Godavari Basin dataset. The method yields satisfying results in spite of the high imbalance between the fault and nonfault classes.

In this article, the design and analysis of a double cylindrical dielectric resonator antenna (CDRA) of compact size 40 × 40 mm2with extended wideband characteristics for C- and X-band applications is presented. A couple of CDRA is placed over the two adjoin rectangular slots which are excited by a modified microstrip feed line of 50 Ω. The proposed double CDRA resonates between frequency band 4.75 and14.43 GHz with 100.93% (9.68 GHz) impedance bandwidth. Two adjoin rectangularslots with a modified microstrip feed line generate two orthogonal degenerated hybrid modes (HEMx11δand HEMy11δ), which are liable for the creation of circular polarization characteristics between the frequency band 6.62 and 8.5 GHz with 24.86% (1.88 GHz) 3-dB axial ratio bandwidth. The stable peak gain of 6.27 dB at frequency 12.62 GHz, whereas the gain of 3.31–6.27 dB and radiation efficiency of more than 86% in the entire operating band is obtained.

Researchers are facing a strong reverse thrust toward the exfoliation of 2-D materials at a large scale. These limitations restrict so many intensively needed applications. We have demonstrated chemically exfoliated MoS2 nanosheets-assisted photosensor examined for low-incident optical power ( $3.78 ~\mu \text{W}$ ) and bias voltage −0.5 to +0.5 V.X-ray diffraction (XRD) results show no secondary peaks that neglect the presence of any impurity in the synthesized MoS2. The high-resolution scanning electron microscopy (HR-SEM) shows synthesized flower-like MoS2 nanosheets. Exfoliation of MoS2 nanosheets was carried out in ${N}$ , ${N}$ -methyl di-pyridine (NMP), a suitable solvent to develop single to few-layer MoS2 nanoflakes. During probe sonication, a low-temperature outer atmosphere arrangement has been ensured by using an ice bath. Sonicated solution has been centrifuged at 12 000 rpm, and the supernatant was collected and drop cast over a p-type (1,0,0) rectangular silicon wafer. Ohmic aluminum (Al) contact has been established. Current and voltage characteristics were performed to study the electrical behavior of fabricated p-Si and synthesized MoS2 heterostructure. The rectification ratio was ≈5800 achieved at ±2 V and the ideality factor was obtained 2.06 in the best-fitted region. The maximum responsivity and detectivity of 14.7 A/W and 2.25 jones were obtained at 300-nm wavelengths corresponding at low bias voltage of −0.5 V.

A diverse assemblage of plant macrofossils and the associated representative palynofloral elements are documented from the early Eocene subsurface beds of the Cambay Shale Formation exposed in an open cast lignite mine at Vastan Village in the Surat District, western India. The Vastan mine succession is cyclic, each cycle representing a transgressive burial event terminating in the low energy lagoonal conditions. The higher energy cycle begins with sandy lenses having rich biotic remains, followed by mudstones and molluscan shell beds and ends with lignite seams. The dominantly muddy facies and the associated biota demonstrate predominantly low energy near shore or coastal plain depositional setting with conditions varying from dominantly marine (shallow) through brackish to fresh water. The Vastan mine is a well dated fossil locality with a rich and diverse biota of mammals, birds, snakes, lizards, fish, insects, molluscs, foraminifers, dinoflagellates, and plants. The plants comprise leaf and fruit impressions, seeds, fruits, wood fragments, mangrove rooting structures, fungal thalli and spores, pteridophytic spores, and angiosperm pollen grains. Thirteen macrofossil species, including several morphotaxa, are represented by the families Calophyllaceae, Rutaceae, Anacardiaceae, Rubiaceae, Combretaceae, Lythraceae, Sapindaceae, Malvaceae, and Ebenaceae. The palynological assemblage representing fourteen taxa includes the new species, Notothyrites undulatus, Callimothallus semicircularis, and Carallioipollenites integerrimoides. Habitat and distribution of modern taxa comparable with the fossil assemblage from Vastan suggest a terrestrial lowland environment. The macrofossil taxa are indicative of mesophytic, mixed forest growing under tropical to subtropical climate with sufficient humidity. The occurrence of dipterocarp elements along with taxa such as Swintonia, Pterospermumand Diospyros, etc. seems to suggest the presence of a tropical rain forest in the vicinity of Vastan.