A hybrid model using 1D-CNN with Bi-LSTM, GRU, and various ML regressors for forecasting the conception of electrical energy

To solve power consumption challenges by using the power of Artificial Intelligence (AI) techniques, this research presents an innovative hybrid time series forecasting approach. The suggested model combines GRU-BiLSTM with several regressors and is benchmarked against three other models to guarantee optimum reliability. It uses a specialized dataset from the Ministry of Electricity in Baghdad, Iraq. For every model architecture, three optimizers are tested: Adam, RMSprop and Nadam. Performance assessments show that the hybrid model is highly reliable, offering a practical option for model-based sequence applications that need fast computation and comprehensive context knowledge. Notably, the Adam optimizer works better than the others by promoting faster convergence and obstructing the establishment of local minima. Adam modifies the learning rate according to estimates of each parameter's first and second moments of the gradients separately. Furthermore, because of its tolerance for outliers and emphasis on fitting within a certain margin, the SVR regressor performs better than stepwise and polynomial regressors, obtaining a lower MSE of 0.008481 using the Adam optimizer. The SVR's regularization also reduces overfitting, especially when paired with Adam's flexible learning rates. The research concludes that the properties of the targeted dataset, processing demands and job complexity should all be considered when selecting a model and optimizer

Optimizing the primary stability of dental implants in type IV bone: in-vitro comparison of machine-driven and ratcheting insertion protocols

Purpose The objective of this study was to assess the effects of various implant insertion techniques on the primary stability of dental implants in both type II and type IV cadaveric bovine. Materials and Methods A total of 48 dental implants (BEGO Semados RSX, BEGO Implant Systems GmbH & Co. KG, Germany) with a diameter of 3.75 mm and a length of 12 mm were used in the experiments. Bovine bone ribs were adjusted to mimic type II and type IV bone characteristics. Following the preparation of recipient sites, implants were inserted using three different protocols: machine-driven insertion (Standard group, Std group), ratchet insertion (Ratcheted, R Group), and a combination of both (Std + R group). The Osstell® Beacon device was used to record the implant stability quotient (ISQ) of each implant immediately after insertion. Two-way analysis of variance and Bonferroni tests were used for statistical evaluation. Results Bone type significantly influenced the ISQ values (p<0.05). However, when comparing insertion protocols separately for type II and type IV bone, no significant differences were observed. In type IV bone, both the Std group and R group exhibited significantly lower ISQ values compared to the same groups in type II bone (p<0.05 for each). Nevertheless, there were no significant differences in the ISQ values when employing the Std+R technique between the two types of bone. Conclusion Combining machine-driven and ratchet insertion techniques may prove beneficial in optimizing ISQ values in bovine samples simulating type IV bone

Recent advances of structure, function, and engineering of carboxylesterases for the pharmaceutical industry: A minireview

Carboxylesterases have a wide range of applications due to their catalytic efficiency, robust structure, and broad substrate specificity. These enzymes, which can hydrolyze carboxylic acid esters, amides, and thioesters, stand out with their regio- and enantioselective properties. They play a crucial role in synthesizing pharmaceutical intermediates, including secondary and tertiary alcohols, α-hydroxy acids, and various bioactive compounds. However, in some cases, the enantioselectivity of carboxylesterases may be insufficient to achieve conversions with the purity required by the pharmaceutical industry. This review summarizes the crucial role of carboxylesterases, particularly in the pharmaceutical field, focusing on the classification, structure, and engineering approaches. After introducing the main families of carboxylesterases, the structural studies are presented to give a comprehensive insight into the active site architecture and related key determinants for enantioselectivity. The protein engineering studies to improve the enantioselectivity of carboxylesterases are discussed along with solvent engineering and immobilization applications

Benzothiophene semiconductor polymer design by machine learning with low exciton binding energy: A vast chemical space generation for new structures

The development of new organic semiconductors with low exciton binding energies (Eb) is crucial for improving the efficiency of organic photovoltaic (PV) devices. Here, we report the generation of a chemical space of benzothiophene (BDT)-based organic semiconductors with lowest Eb energies using machine learning (ML). Our study involves the design of over 500 organic semiconductor structures with low Eb energies and their synthetic accessibility scores. For this, we collect 1061 BDT based compounds from literature, calculated their Eb energies, and predicted them using ML with Random Forest (RF) regression, yielding the best results. Our analysis, using SHAP values, reveals that heavy atoms are the main factors in lowering Eb values. Furthermore, we tested new organic chromophore structures, which showed an efficient shift of their molecular charges. The UV–Vis spectra of these structures exhibits a redshift in the range of 358–667 nm, while their open-circuit voltage (Voc) and light-harvesting efficiency (LHE) ranges from 1.64 to 1.954 V and 52–91 %, respectively. Current study provides a valuable chemical space for the development of new organic semiconductors with improved efficiency. © 2025 Elsevier Lt

Economic policy uncertainty and capital investment: Evidence from European tourism firms

This paper investigates the impact of economic policy uncertainty (EPU) on the capital investment behavior of tourism firms in Europe. Using firm-level data from 4874 firms in 11 European countries for the period 2012-2022, we conduct a dynamic panel data analysis that accounts for the different effects of domestic and global policy uncertainty on the tourism industry and its sub-industries. The results reveal that both domestic and global EPU slow down capital investment in the tourism industry. Notably, global EPU has a significant negative impact in all sub-industries, while domestic EPU mainly affects the hotel sub-industry. These findings remain robust when different firm- and country-specific factors are taken into account. Our study highlights the need for policymakers to reduce policy uncertainty to encourage greater investment. Tourism managers may also benefit from considering both domestic and global uncertainties along with industry-specific characteristics in their investment decisions

A COMPARISON OF THE EFFICACY OF DIFFERENT REMINERALIZATION AGENTS: AN IN VITRO STUDY

Purpose: The objective of this study was to evaluate and compare the remineralizing efficacy of a solution containing silver diamine fluoride (SDF) with agents containing sodium fluoride (NaF) and casein phosphopeptide-amorphous calcium phosphate (CPP-ACP) on artificial caries lesions using laser fluorescence (DIAGNODent) and micro-computed tomography (-CT). Methods: Artificial caries lesions were created on extracted primary incisors without any lesions or defects in the enamel tissue. The teeth were randomly divided into four groups (n = 8): Group 1: SDF (Advantage Arrest, Elevate Oral Care, USA); Group 2: NaF (Clinpro, 3M ESPE, USA); Group 3: CPP-ACP (GC Tooth Mousse, Recaldent, USA); Group 4: control. After applying remineralization agents, the samples were kept in an artificial saliva solution and measured by DIAGNODent at regular intervals. When the remineralization process was complete, enamel surfaces were analyzed by-CT for mineral density, lesion depth, and area using the computer program. Data obtained were statistically analyzed. Results: In the comparison of DIAGNODent values between the groups, a statistically significant difference was found between the values measured on the fourteenth day (p-value=0.003). A significant difference was found between the mineral density (g/cm3) values measured by-CT on the fourteenth day after remineralization according to the groups (p-value=0.001). Conclusions: All agents used in this study provided remineralization. The DIAGNODent and-CT measurements demonstrated that the SDF group had a higher remineralization value than the other groups. Considering the ease of use as well as its effectiveness, it is thought that the SDF solution can be used successfully to arrest early childhood caries. SDF application positively influences enamel remineralization

Unique MIMO system using Gaussian signals and the advantage of these signals in sensing CSI and multipath fading

To improve communication network efficiency, researchers must look at all aspects of transmission and the mechanisms that regulate their evolution as a whole. These features include solutions for dealing with the channel's noise and interference. To decrease interference and increase spectrum efficiency, orthogonal frequency division multiple access (OFDMA) systems employ orthogonal signals. While transmitting and receiving signals, noise and numerous feeds can be done in diverse ways. It has become increasingly common to use 256 quadratic modulation (QAM), which is more vulnerable to noise and has a higher bit error rate (BER). BERs in OFDM systems were high when multiple feeds and noise were present, as demonstrated in this article. Starting with the transmission and reception of Gaussian subband signals, an improved system has been designed that includes numerous stages of development. Thus, the need for “orthogonally” of transmitted signals to increase spectrum efficiency has been eliminated, as has the effect of surrounding channels. We have created a header for every frame that has been transmitted. Several transmitters and numerous receivers send these frames in parallel so that the channel state information (CSI) attributes may be evaluated using parallel processing. Using the identical transmission conditions for both OFDM systems and the proposed system, the simulation results reveal a significant reduction in BER values. This results in BER values of fewer than 10−1 when there are two tabs and 10−1 when there are three tabs for multiple feeding in the OFDM system. This corresponds to BER values of 10−11 in a suggested system when there are three tabs. Some improvements have been made to the proposed design to make it distinctive and qualified to be regarded as a multiaccess system in today's contemporary communication infrastructures

HawkFish Optimization Algorithm: A Gender-Bending Approach for Solving Complex Optimization Problems

Inspired by the gender transition behavior seen in hawkfish, this paper introduces the HawkFish optimization algorithm, a nature-inspired optimization technique modeled on the unique gender transition behavior of hawkfish. By leveraging this biological phenomenon, the proposed method addresses optimization problems through dual fitness functions, combining an original and inverse fitness function to drive search space exploration while avoiding local minima. The algorithm’s performance is rigorously evaluated against benchmark problems, including the CEC/GECCO 2019 suite, and applied to real-world engineering challenges like welded beam and tension/compression spring design. The proposed method consistently outperforms existing algorithms in terms of convergence rate, accuracy, and solution quality. The results underscore the algorithm’s efficiency in exploring unknown search spaces and solving complex optimization tasks, making it a promising tool for various domains requiring high precision and optimization efficiency

Identification of common genes associated with development of resistance against tamoxifen and doxorubicin in MCF7 cells

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Tailored Callosotomy in Third Ventricle Colloid Cyst Resection via Anterior Interhemispheric Transcallosal Approach

Background: The colloid cyst represents a relatively uncommon intracranial lesion. It garners significant attention from neurosurgeons due to its benign nature, deep-seated location, and promising prognosis when identified early and surgically removed. A variety of surgical methods are used to treat these cysts, each with their strengths and weaknesses. Objectives: The aim of this study to introduce and assess a precise microsurgical technique for managing colloid cysts using the anterior interhemispheric transcallosal approach. Methods: The research involved a retrospective analysis of 14 cases between 2021 and 2023 treated with the anterior interhemispheric transcallosal approach by two experienced skull base surgeons. The evaluation encompassed demographic, clinical, radiological, histological, and surgical data. Additionally, the Colloid Cyst Risk Score (CCRS) was used to assess the risk of obstructive hydrocephalus. The procedure incorporated neuronavigation and ultrasound to determine the precise entry point and to plan the trajectory. Results: The minimally invasive microsurgical technique was effectively employed in all 14 cases, with no reported postoperative complications. Post-surgery MRI scans confirmed complete cyst removal, with an average callosotomy measurement of 5.4 ± 2.5 mm. Importantly, none of the patients experienced disconnection syndrome associated with callosotomy. Conclusions: The adapted microsurgical approach via the anterior interhemispheric transcallosal method emerges as a secure and efficient way to address colloid cysts. It ensures comprehensive cyst removal while minimizing complications, boasting advantages such as reduced invasiveness, enhanced visibility, and minimal tissue disturbance, thereby confirming its role in colloid cyst surgical interventions