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Fabrication areas in semiconductor industry are considered one of the most complex production systems. This complexity is caused by the high-mix of products and end-user market-based demands in that industry. Its dynamic and challenging processing requirements affect the handling capabilities of traditional production management paradigms. In this paper, we propose an application for dispatching and resources allocation through reinforcement learning. The application is based on a discrete-event simulation model for a case study of a real semiconductor manufacturing system. The model is built using both data-driven and agent-based approaches. The model simulates the various processing aspects that are present normally in these complex systems. The model’s agents are responsible for dispatching tasks and allocation of the different system’s resources. They employ Deep-Q-Network reinforcement learning. They learn simultaneously through the model execution. An independent Deep-Q-Network is trained for each agent. The model provides the training environment for the agents in which their decisions are applied and assessed for their adequacy. Our formulation of the environment’s state and the reward function for the learning algorithms creates cooperative decision-making policies for the agents. This results in improving the global performance of the whole system, and the performance of each agent’s resources. Our approach is compared to heuristics-based strategies that are applied in our case study. It achieved better production performance than the currently applied strategy.

Spent Ni–Cd batteries are now considered an important source for many valuable metals. The recovery of cadmium, cobalt, and nickel from spent Ni–Cd Batteries has been performed in this study. The optimum leaching process was achieved using 20% H2SO4, solid/liquid (S/L) 1/5 at 80 °C for 6 h. The leaching efficiency of Fe, Cd, and Co was nearly 100%, whereas the leaching efficiency of Ni was 95%. The recovery of the concerned elements was attained using successive different separation techniques. Cd(II) ions were extracted by a solvent, namely, Adogen® 464, and precipitated as CdS with 0.5% Na2S solution at pH of 1.25 and room temperature. The extraction process corresponded to pseudo-2nd-order. The prepared PTU-MS silica was applied for adsorption of Co(II) ions from aqueous solution, while the desorption process was performed using 0.3 M H2SO4. Cobalt was precipitated at pH 9.0 as Co(OH)2 using NH4OH. The kinetic and thermodynamic parameters were also investigated. Nickel was directly precipitated at pH 8.25 using a 10% NaOH solution at ambient temperature. FTIR, SEM, and EDX confirm the structure of the products.

Abstract Reverse pupillary block with intraocular pressure (IOP) elevation after cataract surgery with in-the-bag implantation of intraocular lens (IOL) is considered a very rare complication. We report the case of a 47-year-old female patient with bilateral high axial myopia and posterior staphyloma presented with left acute loss of vision and eye pain, headache, and vomiting 2 weeks after uneventful presenile cataract surgery with single-piece IOL implantation in the capsular bag 1 month and 2 weeks in the right and left eyes, respectively. Gonioscopy showed extremely wide angle in all quadrants compared to the other eye with Spaeth classification of E 60c + 2 (14). Ultrasound biomicroscopy of the left eye showed epithelial corneal edema, 4.56 mm-deep anterior chamber, abnormal iris configuration with posterior concavity, and angle opening ranging between 60° and 74°, with unremarkable posterior chamber IOL and ciliary body. We managed the patient with topical antiglaucoma medications and laser peripheral iridotomy. IOP returned to normal levels. The patient was followed for 12 consecutive months. Elevated IOP from the reverse pupillary block is a rare postoperative complication of cataract surgery. It was initially described in association with the ciliary sulcus implanted IOL. Elevated IOP from the reverse pupillary block was then reported associated with scleral sutured IOLs and Yamane technique, and most recently with in-the-bag implanted 3-piece-IOL. Herein, we report the first case of pseudophakic reverse pupillary block in association with in-the-bag implanted single-piece foldable acrylic IOL.

A new synthetic material, namely, (3-(((4-((5-(((S)-hydroxyhydrophosphoryl)oxy)-2-nitrobenzylidene) amino) phenyl) imino) methyl)-4-nitrophenyl hydrogen (R)-phosphonate)), was subjected to a quaternary ammonium salt and named (HNAP/QA). Several characterizations, such as FTIR spectrometry, 1H-NMR analysis, 13C-NMR analysis, 31P-NMR Analysis, TGA analysis, and GC-MS analysis, were performed to ensure its felicitous preparation. HNAP/QA is capable of the selective adsorption of W(VI) ions from its solutions and from its rock leachate. The optimum factors controlling the adsorption of W(VI) ions on the new adsorbent were studied in detail. Furthermore, kinetics and thermodynamics were studied. The adsorption reaction fits the Langmuir model. The sorption process of the W(VI) ions is spontaneous due to the negative value of ∆G° calculated for all temperatures, while the positive value of ∆H° proves that the adsorption of the W(VI) ions adsorption on HNAP/QA is endothermic. The positive value of ∆S° suggests that the adsorption occurs randomly. Ultimately, the recovery of W(IV) from wolframite ore was conducted successfully.

Objective To assess diagnostic validity and reliability of VI-RADS in predicting muscle invasion by bladder cancer (BCa) and evaluate reviewer acceptance of VI-RADS for clinical routine. Methods A prospective multicenter study enrolled 331 patients with suspected/untreated BCa who underwent preoperative multiparametric MRI examination (mp-MRI) of the urinary bladder. Four experienced radiologists independently evaluated all mp-MRI using VI-RADS. The diagnostic validity of VI-RADS for predicting muscle invasion by BCa was calculated using histopathology of the first transurethral resection bladder tumor (TURBT) and second TURBT as the reference standards. The kappa statistics ( κ ) were applied to assess the interreader agreement (IRA). Reviewer acceptance was evaluated with questionnaires. Results The risk of muscle invasion in VI-RADS 2, 3, 4, and 5 after the first and second TURBT was 21.8%, 45.8%, 69.6%, and 96.4% and 24.4%, 58.3%, 87%, and 99.2%, respectively. The overall diagnostic validity of VI-RADS was high. The optimal cut-off value for predicting muscle invasion after first TURBT was > VI-RADS 3 (sensitivity = 84.1% and specificity = 92.3%), and after second TURBT was > VI-RADS 2 (sensitivity = 89.9% and specificity = 90.1%). VI-RADS categorization showed a very good IRA ( κ = 0.93). Reviewers fully agreed with the statement, “The application of structured reporting of bladder tumor should be encouraged” (score = 20). Conclusions VI-RADS showed high diagnostic validity and reliability for predicting muscle invasion by BCa, especially VI-RADS 4 and 5. However, VI-RADS 2 and 3 require further modifications to enhance their diagnostic validity. VI-RADS is highly encouraged to be used in daily practice. Key Points • VI-RADS showed high diagnostic validity and reliability in predicting BCa muscle invasion, especially VI-RADS 4 and 5. • In VI-RADS 2 and 3, we observed a notable percentage of BCa with muscle invasion and this would require further modifications to enhance the diagnostic validity for these scores. • Overall VI-RADS is well-accepted by radiologists who recommend it for daily practice.

Colon cancer is the second most common cause of cancer death in women and the third most common cause of cancer death in men. Therefore, early detection of this cancer can lead to lower infection and death rates. In this research, we propose a new lightweight deep learning approach based on a Convolutional Neural Network (CNN) for efficient colon cancer detection. In our method, the input histopathological images are normalized before feeding them into our CNN model, and then colon cancer detection is performed. The efficiency of the proposed system is analyzed with publicly available histopathological images database and compared with the state-of-the-art existing methods for colon cancer detection. The result analysis demonstrates that the proposed deep model for colon cancer detection provides a higher accuracy of 99.50%, which is considered the best accuracy compared with the majority of other deep learning approaches. Because of this high result, the proposed approach is computationally efficient.

Considering how important rare earth elements (REEs) are for many different industries, it is important to separate them from other elements. An extractant that binds to REEs inexpensively and selectively even in the presence of interfering ions can be used to develop a useful separation method. This work was designed to recover REEs from spent nickel–metal hydride batteries using ammonium sulfate. The chemical composition of the Ni–MH batteries was examined. The operating leaching conditions of REE extraction from black powder were experimentally optimized. The optimal conditions for the dissolution of approximately 99.98% of REEs and almost all zinc were attained through use of a 300 g/L (NH4)2SO4 concentration after 180 min of leaching time and a 1:3 solid/liquid phase ratio at 120 °C. The kinetic data fit the chemical control model. The separation of total REEs and zinc was conducted under traditional conditions to produce both metal values in marketable forms. The work then shifted to separate cerium as an individual REE through acid baking with HCl, thus leaving pure cerium behind.

In this new information era, the transfer of data and information has become a very important matter. Transferred data must be kept secured from unauthorized persons using cryptography. The science of cryptography depends not only on complex mathematical models but also on encryption keys. Amino acid encryption is a promising model for data security. In this paper, we propose an amino acid encryption model with two encryption keys. The first key is generated randomly using the genetic algorithm. The second key is called the protein key which is generated from converting DNA to a protein message. Then, the protein message and the first key are used in the modified Playfair matrix to generate the cypher message. The experimental results show that the proposed model survives against known attacks such as the Brute-force attack and the Ciphertext-only attack. In addition, the proposed model has been tested over different types of characters including white spaces and special characters, as all the data is encoded to 8-bit binary. The performance of the proposed model is compared with other models using encryption time and decryption time. The model also balances all three principles in the CIA triad.

A new nano-silica/chitosan (SiO2/CS) sorbent was created using a wet process to eliminate uranium(VI) from its solution. Measurements using BET, XRD, EDX, SEM, and FTIR were utilized to analyze the production of SiO2/CS. The adsorption progressions were carried out by pH, SiO2/CS dose, temperature, sorbing time, and U(VI) concentration measurements. The optimal condition for U(VI) sorption (165 mg/g) was found to be pH 3.5, 60 mg SiO2/CS, for 50 min of sorbing time, and 200 mg/L U(VI). Both the second-order sorption kinetics and Langmuir adsorption model were observed to be obeyed by the ability of SiO2/CS to eradicate U(VI). Thermodynamically, the sorption strategy was a spontaneous reaction and exothermic. According to the findings, SiO2/CS had the potential to serve as an effectual sorbent for U(VI) displacement.

Purpose Rhegmatogenous retinal detachment (RRD) is a sight-threatening condition requiring prompt surgical intervention. Various adjunctive techniques are employed to enhance subretinal fluid drainage and retinal reattachment. This study aimed to evaluate the outcomes of perfluorocarbon liquid (PFCL) versus posterior retinotomy (PR) during pars plana vitrectomy (PPV) for RRD, focusing on anatomical success, visual acuity, intraocular pressure (IOP), and complications. Methods This is a prospective randomized controlled trial that included 58 eyes with RRD, divided into Group A (PFCL, n  = 29) and Group B (PR, n  = 29). Preoperative assessments included best-corrected visual acuity (BCVA), IOP, axial length, lens status, macula status, and PVR grade. Outcomes were evaluated at 1 week, 1 month, 2 months, and 3 months postoperatively. Primary outcomes included retinal reattachment rates and the number of operations; secondary outcomes included BCVA, IOP changes, complications like cataract development, retinal redetachment, epiretinal membrane (ERM) formation, and single-surgery success. Results Retinal reattachment rates were comparable (76% in Group A vs. 66% in Group B, p  = 0.387), as well as the number of operations ( p  = 0.375). Moreover, BCVA improved significantly in both groups ( p  < 0.05), with no intergroup differences. IOP increased postoperatively in both groups ( p  < 0.001), with no significant differences. No differences were observed in cataract formation or retinal redetachment. However, ERM incidence was significantly higher in the PR group (27% vs. 11%, p  = 0.049). Conclusion PFCL and PR are effective for RRD repair, with similar anatomical and visual outcomes. However, PFCL may reduce ERM risk, making it preferable in certain cases. These findings guide surgical decision-making and highlight the need for further research. Trial registration The study was retrospectively registered at ClinicalTrials.gov (NCT06919211) on April 4, 2025.