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.
Understanding the development and characteristics of burrow fillings (BF) is crucial for predicting porosity, permeability, and fluid flow behavior in bioturbated carbonate reservoirs. Advanced imaging, digital rock modeling, and backstripping techniques offer valuable insights into this development. In this study, we examined the BF in the bioturbated strata of the Upper Jurassic Hanifa Formation (central Saudi Arabia) to understand how sedimentological and diagenetic processes—such as compaction, dolomitization, and dissolution—influence porosity and permeability over time.
Backstripping results provide significant insights into the evolution of porosity and permeability within packstone BF of the studied strata. We found that compacted, grain-supported BF exhibit limited improvement in porosity and permeability post-compaction. In contrast, less compacted intervals with open fabric BF can achieve up to 20 …
Medical image copyright protection is becoming increasingly relevant as medical images are used more frequently in medical networks and institutions. The traditional embedded watermarking system is inappropriate for medical images since it degrades the original images’ quality. Furthermore, medical-colored image watermarking options are constrained since most medical watermarking systems are built for gray-scale images. This paper proposes a zero-watermarking scheme for medical color image copyright protection based on a chaotic system and Resnet50, which is a convolutional neural network method. The network Resnet50 is used to extract features from the color medical image, and then a logistic Gaussian map is used to scramble these features and scramble the binary image. Finally, an exclusive OR operation is performed (scrambled binary image, scrambled features for the medical color image) to form a zero watermarking. The experimental result proves that our scheme is effective and robust to geometric and common image processing attacks. The BER values of the extracted watermarks are below 0.0039, and the NCC values are above 0.9942, while the average PSNR values of the attacked images are 29.0056 dB. Also, it is superior to other zero-watermark schemes for medical images in terms of robustness to conventional image processing and geometric attacks. Furthermore, the experimental results show that the Resnet50 model outperforms other models in terms of reducing the mean squared errors of the features between the attacked and original image.
This work focuses on exploiting the naturally occurring microbial calcium carbonate precipitation
catalyzed by microbial consortia within lakes and oceans biogeochemistry for carbon dioxide removal
from atmosphere. In this work, Bacillus subtilis OQ119616 was used for carbon dioxide sequestration
in equi-molar concentrations into Bacillus-induced calcium carbonate precipitation (BICCP). As this
process requires alkaline media, urea degradation by urease and nitrogen fixation were traced.
BICCP has been formed from calcium salts in the following order: chloride > nitrate > acetate > citrate.
However, conversion efficiency percentage (CE%) of calcium salts to CaCO3 exhibited a different
attitude of citrate > acetate > chloride > nitrate. Calcium citrate is excluded from consideration. Acetate,
however, is the most efficient salt; it significantly exhibited the highest CE%, with the least cost and
highest economic feasibility. The wide range in quantities, efficiency and feasibility indicates the
importance of the salt anion in BICCP. In addition, BICCP exhibited applicability in healing concrete
cracks, improving field capacity of sand soil and the subsequently improved seed germination of Vicia
faba. BICCP was also accompanied by adsorption of heavy metals as partial purging of waste/sewage
water for hygiene/reuse. Bacillus subtilis exhibited the ability to perform MICP, utilizing various calcium
salts in the following order: chloride > acetate > nitrate > citrate. However, acetate is the most efficient
salt of calcium to be converted to calcium carbonate precipitate by B. subtilis, as it exhibited the
highest conversion efficiency percentage (g/g %), with the least cost and highest economic feasibility.
Carbon dioxide removal (CDR) occurs at simultaneous equity to CaCO3 precipitation at mole/mole
ratios. Economic feasibility (US$/m3) showed that BICCP may be applicable in CDR for cleansing carbon
dioxide inside closed systems and for environmental safety. The bacterially induced CaCO3 proved
successful applicability in improving the field capacity of sand soil and growth of V. faba, healing
concrete cracks and sorption of heavy metals for depolluting sewage/wastewater for hygiene reuse.
BICCP could repair concrete cracks of 1–2 mm wide in 7 days by 210 * 106 cells/mL. Adsorption of heavy
metals (Pd, Zn, Cd and Cu) for partial removal of contaminants in/from waste/sewage water for hygiene
reuse.
Recent increases in the release of untreated water containing cationic dyes have led to significant environmental issues in ecosystems. Many industries contribute to this pollution by discharging water containing various organic pollutants, including crystal violet (CV). Therefore, a novel hybrid mesoporous sulfur-doped copper oxide embedded in Cu-alginate-derived carbon micro-beads (SCO@CACBs) adsorbent was developed for CV-decolorization through batch and fixed-bed columnar techniques. Comparative studies on the effectiveness of CV removal using CACBs and SCO@CACBs under different conditions such as pH, stirring time, amount of sorbent, initial CV concentration, and temperature were conducted. The results demonstrated that the optimal CV removal reached up to 99 % at neutral pH conditions (pH of 7), with an adsorption capacity of 87 mg/g through a batch approach. The CV adsorption process was analyzed using various methods, including adsorption isotherms, kinetics, thermodynamics, zeta potential measurements, and density-functional theory (DFT) calculations. Langmuir (R2 = 0.995) and pseudo 2nd order (R2 = 0.998) models most agree with experimental CV-adsorption data. Thermodynamic parameters indicated that CV adsorption is spontaneous, favorable, and endothermic. The columnar adsorption tests showed that the adsorption capacity of SCO@CACBs varied from 83.6 to 71.3 mg/g as the flow rate varied from 2 to 6 mL/min and 81.5–115.6 mg/g as the adsorbent mass varied from 1 to 4 g. The Thomas and Yoon-Nelson models fitted the breakthrough curves. The adsorbent maintained high removal efficiency (about 93 %) after five reuse cycles through batch and fixed-bed columnar approaches. Notably, the SCO@CACBs showed over 96 % efficiency in removing CV dye from actual agricultural and textile wastewater samples using batch and column setups. Thus, SCO@CACBs is an effective sorbent for removing CV dye from water contaminated by natural sources.
Biodegradable naturally occurring adsorbents derived from waste precursors are essential for water sustainability. This study investigates using modified cellulose nanostructure (m-CNS) with thiols from wood pulp as a waste source to remove Cr(VI) ions from aqueous solution under different conditions, such as temperature, initial dye concentration, and contact time. The equilibrium adsorption of Cr(VI) is assessed at various temperatures (30, 40, and 50 °C) and concentrations (10, 20, 30, 40, and 50 mg L−1). The m-CNS is detected by Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), and dispersive X-ray spectroscopy (EDS). Experiments are being carried out to investigate the removal of Cr(VI) ions in equilibrium state. The results showed that the highest percent removal of Cr(VI) ions was 95.95% at pH = 4.0 and after a relatively short adsorption time (80 min). The experimental data is presented using a diverse range of seven isotherm models. There are four models with two parameters: Freundlich, Langmuir, Dubinin-Radushkevich, and Temkin. In addition, three models with three parameters, namely the Redlich-Peterson, Sips, and Toth models, are employed to analyze the experimental adsorption data comprehensively. The depth of our analysis is further enriched using six error functions: the chi-square test (χχ2), the sum of squares of the errors (SSE), the derivative of Marquard’s percent standard deviation (MPSD), the average relative error (ARE), the sum of absolute errors (EABS), and the coefficient of determination. Unlike the Dubinin-Radushkevich isotherm, linear and non-linear regression procedures produced equivalent results for two-parameter isotherms at different temperatures. This is especially noteworthy since the Freundlich, Langmuir, and Temkin isotherms, which provided the greatest fit to the data, are frequently utilized in isotherm modeling and adsorption research. Three-parameter isotherms yielded conflicting linear and non-linear model findings across different temperatures. Furthermore, the findings show that the most optimum error function for prediction was χχ2.
Camel whey protein (CWP) offers various health benefits, including immune enhancement, anti-inflammatory, anticancer, and antibacterial properties. It also possesses antioxidant activity. However, its limited efficacy and stability restrict its broader application. Metal–organic frameworks (MOFs) are crystalline materials composed of multiple organic groups and metal ions, known for their unique structural properties. In this study, we aimed to synthesize and evaluate the biological activity of a CWP-Co-MOF conjugate. The structural characterization of the synthesized materials was conducted using X-ray diffraction (XRD), Fourier-transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM), and energy-dispersive X-ray (EDX) analysis. The comparison of the XRD and FTIR patterns of ZIF-67, CWP and CWP-Co-MOF conjugate indicate successful conjugation of CWP with ZIF-67, confirming the structural integrity of the conjugate. The EDX maps further corroborate the effective conjugation of CWP with ZIF-67. The conjugated CWP-MOF nanoparticles (NPs) exhibited promising antioxidant activity, as assessed by the DPPH assay. Furthermore, they showed more potent anti-inflammatory effects in LPS-induced BV2 microglial cells and superior anticancer activity against HepG2 and Caco-2 cell lines, as determined by the MTT assay and flow cytometry, compared to free CWP. Additionally, the CWP-MOF-NPs exhibited enhanced antimicrobial properties and increased efficacy as an anti-biofilm agent against pathogenic bacteria.
This work lies in the integration of a one-micron-gap gold electrode with SnO₂ nanowires, enhancing electric field intensity and interfacial charge transfer. This configuration enables highly sensitive gas detection at a low operating temperature of 50◦C. The study presents a SnO₂ nanowire-based gas sensor featuring a novel onemicron-gap electrode configuration for enhanced sensitivity and selectivity in detecting atmospheric pollutants such as NO₂, H₂S, H₂, and CO. The SnO₂ nanowires were synthesized via thermal evaporation, with the electrode gaps created using focused ion beam (FIB) technology. The fabricated sensor demonstrated efficient gas response characteristics, particularly for NO₂ at 2 ppm and H₂S at 5 ppm, across a range of low temperatures (RT - 350◦C). At an operating temperature of 50◦C, the sensor responded quickly to NO₂, with a response time of 105 s and a recovery time of 121 s. The sensor demonstrated a response time of 147 s and a recovery time of 147 s for H₂S at 5 ppm. The high surface-to-volume ratio of SnO₂ nanowires, combined with the concentrated electric field of the narrow-gap electrodes, facilitated rapid charge transfer and efficient gas adsorption. These results underline the potential of this configuration for low-power, high-sensitivity gas sensing applications. The plasmonic changes in micro-gold electrodes upon exposure to NO₂, H₂S, CO, and H₂ gases enhance the gas sensor’s selectivity by modulating the localized electric field and charge transfer at the electrode surface. The results demonstrate a promising approach for low-power, high-performance gas sensing using optimized electrode geometry.
