Solar light-driven water splitting offers a sustainable pathway for energy conversion. This study presents a straightforward electrodeposition method for decorating ZnO nanosheets with CdS nanonoodles, varying the deposition time. Structural and morphological analysis confirmed the formation of a crystalline, Cd-rich hexagonal CdS phase on the ZnO nanosheets, exhibiting a unique nanonoodles morphology. The thickness of the CdS/ZnO nanonoodles gradually increased to 30 μm with extended deposition times. Notably, the valence band of the hybrid CdS/ZnO nanonoodles exhibit a lower binding energy compared to both CdS nanonoodles and ZnO nanosheets, highlighting interfacial charge transfer and enhanced synergy. The hybrid CdS/ZnO nanonoodle photoanode, fabricated with a 60-min deposition time, exhibits a reduced band gap of 2.8 eV compared to the 3.2 eV band gap of the pristine ZnO nanosheets. This reduction in the band gap indicates enhanced solar light absorption capabilities. The CdS/ZnO nanonoodles demonstrate a gradual improvement in the photoelectrochemical water splitting efficiency with increasing deposition time. The hybrid photoanode achieves a remarkable photocurrent density of 9.49 mA cm⁻² at 1.23 V vs. reversible hydrogen electrode (RHE), representing a 20-fold increase compared to the ZnO nanosheets (0.46 mA cm⁻²) and a 7-fold increase compared to the CdS nanonoodles (1.45 mA cm⁻²). This heterostructured CdS/ZnO nanonoodles hybrid photoanode achieves an impressive conversion efficiency of 9.21 % at 0.4 V vs. RHE.

Ground-penetrating radar (GPR) is a noninvasive near-surface geophysical method. This method
is beneficial for imaging, characterization, and intrasite analysis of buried archaeological remains
within culture sediments at Ginah archaeological site. The investigation of these targets has intrinsic
value and has never been conducted at this site. In this study, GPR can be utilized to conduct a more
focused survey on individual features and understand their structures, dimensions, and depths. The
field survey on the studied area was conducted by SIR 4000 with 200 and 400-MHz antennae using
RADAN 7 software. The processed GPR radargrams, depth slices, and 3D subvolumes are used to
illustrate typical georadar facies associated with the stratigraphy and architectural elements of the
buried archaeological remains. The facies analysis helps to identify the nature of cultural sediment,
constructed materials, and the anticipated archaeological artifacts at various depths. These detected
features are beneficial for presenting a compelling justification of nature, constituents, architectural
patterns, and historical cultures. Also, this information is used to make guesses based on what is
seen in the field and the archaeological history found in the ruins of Ginah, Al-Ghuieta, and Al-Zayyan
fortresses along the Darb El-Arbine route. This information is essential to assume different successive
ancient periods at the examined site, which can help specialists hasten their excavations.

Supply Chain Management (SCM) is a critical business function that involves the planning, coordination,
and control of the flow of goods, information, and finances as they move from the
manufacturer to the wholesaler to the retailer and finally to the end customer. SCM is a holistic
approach to managing the entire process of delivering products or services to consumers. In this
study, we will enhance the findings as outlined in Anne et al. (2009). While certain attributes of
these systems will have been investigated, numerous aspects of these systems will still require
further scrutiny. This calls for additional research studies on these systems. This paper examines a
Fractional-Order Supply Chain Management (FOSCM) model utilizing the Adomian Decomposition
Method (ADM) and explores qualitative aspects through an approach that addresses existence
and uniqueness. By using Arzel`a–Ascoli’s principle, this system proves that the Caputo
FOSCM model has at least one solution. Furthermore, we investigate the dynamics of the system
by using the Lyapunov Exponent (LE), Bifurcation Diagram (BD), Complexity Analysis (CA) and
0–1 test. Finally, we introduce the control for FOSCM model using the Linear Feedback Control
(LFC) method. We verify the correctness of our analysis by using numerical simulations.