“Alphabet” Selenoproteins: Implications in Pathology (preprint)

Selenoproteins are a group of proteins containing selenium in the form of selenocysteine (Sec, U) as the 21st amino acid coded in the genetic code. Their synthesis is dependent on dietary selenium uptake and a common set of cofactors. Selenoproteins accomplish diverse roles in the body and cell processes by acting, for example, as antioxidants, modulators of the immune function, detoxification agents for heavy metals, and other xenobiotics, key compounds in thyroid hormone metabolism. Although the functions of all this protein family are still unknown, several disorders in their structure, activity or expression have been described by researchers. They concluded that selenium or cofactors deficiency, on one hand, or the polymorphism in selenoproteins genes and synthesis, on the other hand, are involved in a large variety of pathological conditions, including type 2 diabetes, cardiovascular, muscular, oncological, hepatic, endocrine, immuno-inflammatory, neurodegenerative diseases. This review is focused on specific roles in medicine only of selenoproteins that are each named after an alphabet letter, less known than the rest of them, regarding their implications in patho-logical processes of several prevalent diseases and also in disease prevention.

Evaluation of the Relationship between CRP/Lymphocyte Ratio and Blood Sugar Regulation and Other Metabolic Parameters in Patients with Type 2 Diabetes Mellitus (preprint)

C-reactive protein to lymphocyte ratio (CLR) has been shown to be associated with diseases characterized by chronic, low-grade inflammation. Since type 2 diabetes (T2DM) is also associated with inflammation, we aimed to study the association between CLR and T2DM. Patients with T2DM who presented to internal medicine outpatient clinics of our institution were divided into 2 groups according to their glycosylated hemoglobin (HbA1c) levels as well-controlled (HbA1c<7%) and poorly controlled (HbA1c≥7%) T2DM groups. Subjects assigned as healthy in routine check-up were included as control group. CLR values of the well and poorly controlled diabetics and control cases were compared. CLR of T2DM group (3.51 (0.03-21.78)) was significantly higher than that of the controls (0.65 (0.02-2.92)) (p<0.001). CLR was found to have a sensitivity of 63.2% and a specificity of 97.3% in predicting T2DM. The CLR value of patients with poor diabetic control was 4.76 (0.06-21.78), while the CLR value of patients with well controlled disease was 2.53 (0.03-12.07) (p<0.001). The sensitivity and specificity of the CLR in demonstrating poor diabetic control was 41.2% and the 86.1%, respectively. In conclusion, elevated CLR in T2DM patients and even more increased levels in poorly controlled diabetics suggest that CLR could be a useful additional diagnostic tool in treatment follow-up of the T2DM population.

Numerical Aperture Dependent Spatial Scaling of Plasma Channels in HPHT Diamond (preprint)

The investigation of plasma channels induced by focused ultra-short 1030-nm laser pulses in bulk of synthetic HPHT diamond revealed strong dependence of their size and shape on the used numerical aperture of the lens (NA=0.15-0.45). It was shown that at loose focusing conditions, it is possible to significantly increase the length of the plasma channel with a slight increase in pulse power, while tight focusing allows to obtain more compact structures in the same range of used powers. Such dependence paves the way to new possibilities in 3D processing of transparent dielectrics, allowing, for example, to vary the spatial parameters of modified regions without changing the setup, but only by controlling the lens aperture, which seems very promising for industrial applications.

Effects of Foliar Spraying Organic Selenium and Nano-Selenium Fertilizer on Pak Choi (Brassica chinensis var. pekinensis. cv. ‘Suzhouqing’) Under Low Temperature Stress (preprint)

In recent years, frequent occurrences of low temperature disasters due to global climate change have significantly impacted the normal growth of crops. Research has indicated that inorganic selenium (which is more toxic) can not only enhance the effects of low temperature stress but also increase selenium content on plants; however, there is a scarcity of studies investigating the impacts of organic selenium and nano-selenium on crops. In order to investigate whether organic selenium and nano-selenium can enhance low-temperature tolerance and increase selenium content in pak choi (Brassica chinensis var. pekinensis. cv. ‘Suzhouqing’), different concentrations (0, 5, 10, 20 mg L-1) of exogenous selenium were applied in this experiment to assess their effects on plant growth, nutritional quality and antioxidant properties. RNA-Seq technology was used to sequence the transcriptome of the leaves. Based on the transcriptome data, a Weighted Gene Co-expression Network Analysis (WGCNA) was employed to construct a network that associates with physiological traits related to stress resistance. Two highly correlated gene co-expression modules were identified, and within them, nine hub genes associated with endocytosis, antioxidant stress, absorption, transport, and metabolism of selenium were discovered. The results indicated that the beneficial effects on yield and total selenium content under low temperature were attributed to (1) protection of photosynthetic pigments for enhancing photosynthetic capacity by the up-regulation of LHca2, LHcb1, LHca1, LHcb4 in KEGG pathway: photosynthesis-antenna proteins; (2) activation of antioxidant system for efficient ROS homeostasis such as SOD, POD and CAT by the genes such as Superoxide dismutase, Monodehydroascorbate and (3) selenium absorption by endocytosis, seleninum transportation by ABC transporter gene family and selenium metabolism related genes such as Cysteine synthase, Glutaredoxin. These findings provide a foundation for further investigation into the molecular mechanisms underlying the effects of organic selenium and nano-selenium on cyanochloride production at low temperatures.

Comparison of the 10-, 14- and 20-Item CES-D Scores as Predictors of Cognitive Decline (preprint)

The association between depressive symptomatology and cognitive decline has been examined using the Centre for Epidemiologic Studies-Depression Scale (CES-D), however, concerns have been raised about this self-report measure. Here, we examined how the CES-D total score from the 14- and 10-item versions compared to the 20-item version in predicting progression to cognitive decline from a cognitively unimpaired baseline. Data from 1,054 participants were analysed using ordinal logistic regression, alongside moderator and receiver-operating characteristics curve analyses. All baseline total scores significantly predicted progression to cognitive decline. The 14-item version was better than the 20-item version in predicting consensus diagnosis, as shown by their AICs, while also showing the highest accuracy when discriminating between participants by diagnosis at last visit. We did not find sex to moderate the relationship between CES-D score and cognitive decline. Current findings suggest the 10- and 14-item versions of the CES-D are comparable to the 20-item version, and that the 14-item version may be better at predicting longitudinal consensus diagnosis compared to the 20-item version.

Surveying and Geographic Information Systems (GIS): Exploring the Capabilities of Unmanned Aerial Vehicles (UAV)/Drones (preprint)

Unmanned aerial vehicles (UAV) have emerged as a solution to day to day survey tasks, allowing users to visualize phenomena in real-time. This paper explores the capabilities of UAV or drones in the collection of accurate, geo-tagged data quickly, including photogrammetry software processes to deliver standardized data output. In order to explore the capabilities of UAV, Gatu Township in Centenary, Muzabani District of Zimbabwe was chosen from the national mapping topographic series. This study demonstrates the efficiency of data collection using drones, generate 2D orthomosaics in real time, so that analysts can easily visualize land cover and identify any changes, map and model large areas to produce data for 2D and 3D models. The recent development of innovative optical image processing has further lowered the costs high resolution topographic surveys.

Prophylactic Therapy with Emicizumab in Patients with Hemophilia A: Benefits and Challenges (preprint)

This study presents a transversal investigation, that we performed at Fundeni hospital, into the therapeutic benefits and efficacy of Emicizumab, a non-factor therapy, in the context of hemophilia A. Ten patients diagnosed with hemophilia A were closely monitored, using clinical and laboratory resources, during the course of Emicizumab treatment, with an average of 12.8 months. Among these patients, six exhibited anti-factor VIII inhibitors, changing the medical approach and adding complexity to their clinical profiles. A comprehensive approach was adopted to assess the coagulation status of patients under Emicizumab therapy. The study employed several key coagulation monitoring tools, of which including thrombin generation time (TGT) and thrombelastography (TEG). These methodologies proved highly valuable results in evaluating the patients' coagulation profiles during the treatment regimen. Additionally, traditionally coagulation assays were utilized to gain a comprehensive understanding of the overall coagulation dynamics. Noteworthy, impressive outcomes emerged from the study. During prophylaxis with Emicizumab all patients had experienced a reduced number of bleeding events. Moreover, a subset of these patients underwent major surgical procedures (orthopedic joint replacements) with successful outcomes. These findings underscore the potential of Emicizumab therapy as an effective option for hemophilia A patients, including those that presented a prompt production of anti-factor VIII inhibitors. As for the outcomes, this transversal study sheds some light on the positive impact of Emicizumab therapy in addressing the coagulation challenges posed by hemophilia A. The utilization of global coagulation assays, such as thrombin generation time, thrombelastography and combined with traditional coagulation assays, used as monitoring tools highlights their significance once more in evaluating the therapeutic response. This research contributes by providing physicians with valuable insights to the field, offering a potential avenue for improved patients’ care and treatment strategies that translate in enhanced quality of life for hemophilia A patients undergoing Emicizumab therapy.

Unveiling the Railway Traffic Knowledge in Tibet: An Advanced Model for Relational Triplet Extraction (preprint)

To address the deficiency of existing relation extraction models in effectively extracting relational triplets pertaining to railway traffic knowledge in Tibet, this paper constructs a Tibet Railway Traffic text dataset and provides an enhanced relation extraction model. The proposed model incorporates subject feature enhancement and relational attention mechanisms. It leverages a pre-trained model as the embedding layer to obtain vector representations of text. Subsequently, the subject is extracted and its semantic information is augmented using an LSTM neural network. Furthermore, during object extraction, the multi-head attention mechanism enables the model to prioritize relations associated with the aforementioned features. Finally, objects are extracted based on the subjects and relations. The proposed method has been comprehensively evaluated on multiple datasets, including the Tibet Railway Traffic text dataset and two public datasets. The results on the Tibet dataset achieves an F1-score of 93.3\%, surpassing the baseline model CasRel by 0.8\%, indicating a superior applicability of the proposed model. On the other hand, the model achieves F1-scores of 91.1\% and 92.6\% on two public datasets, NYT and WebNLG, respectively, outperforming the baseline CasRel by 1.5\% and 0.8\%, which highlights the good generalization ability of the proposed model.

Research on Wavelet Transform Modulus Maxima and OTSU in Edge Detection (preprint)

During routine bridge maintenance, edge detection allows the partial condition of the bridge to be viewed. However, many edge detection methods often have unsatisfactory performances when dealing with images with complex backgrounds. Moreover, the processing often involves the manual selection of thresholds, which can result in repeated testing and comparisons. To address these problems in this paper, the wavelet transform modulus maxima method is used to detect the target image, and then the threshold value of the image can be determined automatically according to the OTSU method to remove the pseudo-edges. Thus, the real image edges can be detected. The results show that the information entropy and SSIM of the detection results are the highest when compared with the commonly used Canny and Laplace algorithms, which means that the detection quality is optimal. To more fully illustrate the advantages of the algorithms, images with more complex backgrounds were detected and the processing results of the algorithms in this paper are still optimal. In addition, the automatic selection of thresholds saves the operator’s effort and improves the detection efficiency. Thanks to the combined use of the above two methods, detection quality and efficiency are significantly improved, which has a good application in engineering practice.

A Solution of The Collatz Conjecture Problem (preprint)

Build a special identical equation, use its calculation characters to prove and search for solution of any odd converging to 1 equation through (*3+1)/2^k operation, change the operation to (*3+2^m-1)/2^k, get a solution for this equation. Furthermore, analysis the sequences produced by iteration calculation during the procedure of searching for solution, build a weight function model, prove it decrease progressively to 0, build a complement weight function model, prove it increase to its convergence state. Build a (*3+2^m-1)/2^k odd tree, prove if odd in (*3+2^m-1)/2^k long huge odd sequence can not converge, the sequence must walk out of the boundary of the tree after infinite steps of (*3+2^m-1)/2^k operation.

Is Mulching a Cost-Effective System? Case Study of Pineapple Cropping Systems of the Donomadè Ecovillage in Yoto Prefecture in Togo, West Africa (preprint)

One of the main constraints of agriculture in sub-Saharan Africa is the steady decline in the level of soil fertility resulting in a continuous decline in crop yields. This study assessed the impact of grass mulch on: the productivity, the income, the soil carbon, and the phytodiversity within three pineapple-based systems of the ecovillage of Donomade in Togo. They are: a model farm with mulch, adopters’ farms, and non-adopters. Production-related data (e.g., number of plants, the number of productive individuals, the mass of products harvested) was obtained by a sampling an area of 100 m². These measurements were coupled with a semi-structured individual’s interviews of producers on the history of the plots and production costs in order to assess their profitability. The fruit production was three times higher within the adopters’ plots (21240 ± 11890 kg/ha) than the non-adopters (7840 ± 7890 kg/ha) and the two thirds of the model farm (33838 ± 9460 kg/ha). Consequently, the net income was 8 to 11 times higher than the conventional pineapple cropping system. According to the cropping systems, the total soil carbon was higher within mulching plots including the model farm and the adopters’ plots and lower within the non-adopters’ plots.

The United Nations Convention on the Rights of Persons with Disabilities and Social Work: Evidence for Impact? (preprint)

The United Nations Convention on the Rights of Persons with Disabilities (hereafter CRPD) has provided a radical imperative for the reform of mental health and capacity legislation around the world. The interpretation of the CRPD has been controversial, ranging from complete abolition of detention, forcible treatment and substitute decision making, to acceptance that elements of these measures need to be retained but based on non-discriminatory criteria, additional safe-guards and a comprehensive shift towards supported decision-making. While the potential ef-fects of the CRPD on mental health social work and social work generally are considerable given their shared commitment towards social justice, to date there has been no review of research evi-dence exploring their relationship. In addressing this knowledge gap, this study held a prelimi-nary discussion with practitioners and academics at the European Association of Social Work Mental Health Special Interest Group in Amsterdam 2022, followed by a scoping literature re-view on the question: What impact, if any, has the CRPD had on social work practice? The review produced four main findings: impact on legislation; positive impact on practice; limited impact on practice; and impact on social work education and research. In sum, while there were some positive indications of social work and mental health social work practice being influenced by the CRPD, these were scant. Barriers to change included tendencies among some social workers to practise substitute decision-making, in part related to resourcing and policy contexts, and under-standings of disability aligned to individualised/medical rather than social perspectives. The results indicate that legal reform on its own is insufficient to impact social work practice, and that realising the potential of the CRPD will necessitate good quality training, as well as improv-ing social workers’ knowledge of the human rights of people with mental impairment.

Skull Biomechanics and Simplified Cephalometric Lines for the Estimation of Muscular Lines of Action (preprint)

This study proposes a cephalometric analysis that can be used for biomechanical simulation by considering the important and complex relationship between craniofacial morphology and masseter muscle (MM) size and inclination and by including muscle values. The MM line of action drawn between the Gonion (Go) and Orbital (Or) point relative to dental and skeletal references (occlusal and Frankfort planes) were analyzed. A total of 510 pre-treatment lateral cephalometric tracings (217 males, 293 females, 6-50 years) and lateral Bolton standard tracings (6-18 years) were analyzed. The study examined the following: a) skeletal-cutaneous class (linear distance in mm between the projections of points A' and B' on the occlusal plane), b) the angle between the perpendicular line to the occlusal plane and the Go-Or line at the molar occlusal point, and c) the angle between the Go-Or line and the Frankfort plane. The skeletal classes of the patients ranged from -14.5 to 15.5 mm and did not differ by sex or age; the angle between the Go-Or line and the normal to the occlusal plane averaged 39° (range 15° to 53°) and decreased with age, while the angle between the Go-Or line and the Frankfort plane averaged 42° (range 30° to 54°), increased in older patients. No effect of gender was observed. The two angles were also significantly correlated with each other, but not with sagittal jaw discrepancy. Similar results were obtained with Bolton tracings; the positional relationship of the Go-Or line to the teeth and skeletal landmarks is partially consistent with the literature. The present cephalometric analysis can be usefully used to estimate the mechanical advantage of MM in biomechanical simulations of masticatory muscle performance.

Permian Granitic Plutons from the Northern Margin of the North China Craton: Implications for the Tectonic Evolution of the Central Asian Orogenic Belt (preprint)

As the largest accretionary orogen in the world, the Central Asian Orogenic Belt (CAOB) has continuous juvenile crustal growth in the Phanerozoic. The northern margin of the North China Craton(NCC) and its adjacent area is the eastern segment of the CAOB, and is a key area to study the geological evolution of Paleo-Asian Ocean (PAO). In the Permian, the west of the northern margin of NCC belongs to a post-collision extensional environment, and the east belongs to a subduction stage. But, As a connecting area, the Permian evolution of PAO in the middle of northern margin of NCC has not been systematically studied. In order to fill the blank and understand the temporal and spatial continuous evolution process of PAO, this paper focused on the Permian granitic rocks in the Chifeng area, zircon U-Pb dating and the geochemical analysis of the whole rock main and trace elements were conducted in order to build a granite chronological framework, discuss the genesis and tectonic background of the granite rocks as well as the magma-tectonic evolution history in the Chifeng area. Zircon U-Pb dating results of 8 samples are 269±1 Ma, 268±3 Ma, 260±4 Ma, 260±1 Ma, 260±1 Ma, 255±2 Ma, 254±2 Ma, 256±1Ma, which showed that the Permian granitic rocks had undergone three stages of emplacement: (1) The monzogranite and syenite (294-284 Ma); (2) The monzogranite (269-260Ma) and (3) The monzogranite and syenite (256-254Ma). The Middle Permian magmatism (269-260Ma) was represented by the monzogranite assemblages with different grain sizes. The geochemical characteristics showed that they were high-potassium calc-alkaline-potassium dossonite series of granites formed in compressional environment, indicating there was a collision between the Xing’an-Mongolian Orogenic Belt (XMOB) and the North China Craton (NCC). During the Late Permian-Early Triassic (256-248Ma), the granites in the Chifeng area are dominated by the A-type and I-type granites of high-potassium calc-alkaline series formed under an extensional environments, which constituted typical "bimodal" rock assemblage combined with the coeval basic rocks, suggesting the study area was in an extensional environment where the subducting slab is fragmented during the collision between the XMOB and the NCC. According to emplacement time and occurrence location, the plutons are interpreted to have been generated by the subduction-collision of the Paleo-Asian oceanic crust beneath the NCC. This study provides strong evidence for Permian tectonic evolution and the characterization of the eventual closure of the Paleo-Asian Ocean in the Chifeng City at the northern margin of the NCC.

Harnessing Oleanolic Acid as A Modulator of Metabolic Nuclear Receptors (preprint)

Nuclear receptors (NRs) constitute a superfamily of ligand-activated transcription factors with a paramount role in ubiquitous physiological functions such as metabolism, growth, and reproduction. Owing to their physiological role and druggability, NRs are deemed attractive and valid targets for medicinal chemists. Pentacyclic triterpenes (PTs) represent one of the most important phytochemical classes present in higher plants, where oleanolic acid (OA) is the most studied PTs representative owing to its multitude of biological activities against cancer, inflammation, diabetes, and liver injury. PTs possess a lipophilic skeleton that imitates the NRs endogenous ligands. Herein, we report a literature overview on the modulation of metabolic NRs by OA and its semi-synthetic derivatives, highlighting their health benefits and potential therapeutic applications. Indeed, OA exhibited varying pharmacological effects on FXR, PPAR, LXR, RXR, PXR, and ROR in a tissue-specific manner. Owing to those NRs modulation, OA exhibited prominent hepatoprotective properties comparable to ursodeoxycholic acid (UDCA) in a bile duct ligation mice model and antiatherosclerosis effect as simvastatin in a model of New Zealand white (NZW) rabbits. It also demonstrated a great promise in alleviating non-alcoholic steatohepatitis (NASH) and liver fibrosis, attenuated alpha-naphthol isothiocyanate (ANIT)-induced cholestatic liver injury, and controlled blood glucose levels, making it a key player in the therapy of metabolic diseases. We also compiled OA semi-synthetic derivatives and explored their synthetic pathways and pharmacological effects on NRs, showcasing their structure-activity relationship (SAR). To the best of our knowledge, this is the first review article to highlight OA activity in terms of NRs modulation.

Deep Ontology Alignment using Natural Language Processing Approach for Automatic M2M Translation in IIoT (preprint)

The technical capabilities of modern Industry 4.0 and Industry 5.0 are rather vast and growing exponentially daily. The present-day Industrial Internet of Things (IIoT) combines manifold underlying technologies that require real-time interconnections and communications among heterogeneous devices. Smart cities are established with sophisticated designs and control for seamless Machine-to-Machine (M2M) communication to optimize resources, costs, performances, and energy distribution. All the sensory devices within a building interact to maintain a sustainable climate for residents and intuitively optimize the energy distribution to optimize energy production. However, it encompasses quite a few challenges for devices that lack compatible and interoperable designs. Conventional solutions are restricted to limited domains or rely on engineers to design and deploy translators for each pair of ontologies. This is a costly process in terms of engineering efforts and computational resources. The issue persists that a new device with a different ontology must be integrated into an existing IoT network. We propose a self-learning model that can determine the taxonomy of devices given their ontology meta-data and structural information. The model finds matches between two distinct ontologies using the Natural Language Processing (NLP) approach for learning linguistic contexts. Then, by visualizing the ontology network as a knowledge graph, it is possible to learn the structure of the meta-data and understand the device's message formulation. Finally, it can align entities of both ontology graphs similar in context and structure. Furthermore, the model performs dynamic M2M translation without requiring extra engineering or hardware efforts.

Modeling Requirements for Collaborative Robotic Services (preprint)

Collaborative robots have experienced low acceptance in applications, especially in industry. 1 This fact has attracted the attention of researchers and practitioners, who point to different causes 2 for this low acceptance. One of the main reasons is the difficulty in converging on suitable methods 3 for modeling collaborative interactions between robots and their surrounding context during the 4 requirements phase. These interactions must be elicited and modeled during requirements modeling 5 to maximize value creation through collaboration and must be formally verified, taking into account 6 the risks of human-robot interaction. However, such modeling is often not present in collaborative 7 robot design, and the choice of an appropriate approach remains an open problem. In this paper, 8 this problem is addressed from a requirements engineering perspective, a goal-oriented model and 9 a service-based approach supported by an additional verification method based on Petri nets is 10 proposed. A case study based on collaborative robots used in a hospital environment is presented.

Design and Analysis of the High-Speed Underwater Glider with a Bladder-Type Buoyancy Engine (preprint)

This study entailed the design and analysis of a 400 m-class underwater glider operated by a bladder-type buoyancy engine. The underwater glider was designed for high-speed movement with a maximum velocity of 2 knots. The shape of the hull was designed to reduce water resistance using the Myring hull profile equation. The reliability was verified by performing simulations using resistance coefficients. The relationship between the control value of the ballast discharged from the buoyancy engine and the glider's speed according to the path angle was analyzed. Further, the relationship between the optimal glide angle and the design control value of the ballast was derived, and the optimal glider speed was estimated accordingly. Based on the analysis results, a bladder-type buoyancy engine was developed, and the maximum speed of the tested underwater glider was measured via sea trials.

Chicken Value Chain Analysis in The Gambia (preprint)

The development of the chicken value chain in The Gambia has immense potentials to lead to the modernisation of agriculture and creating employment for young people and women. Chicken can be raised throughout the year in most parts of The Gambia. With increasing populations, environmental degradation and loss of rangelands, chicken is easier to producer than other livestock, such as cattle and small ruminants. The development of the chicken value chain in The Gambia is also mainly constrained at commercialisation. Commercial farmers in The Gambia are not able to compete with cheap import. Critical inputs such as day-old chicks and feed are imported. Most farms are operating below 40% capacity and only less than 4% utilisation of the available processing capacity. At full capacity and with some needed investments along the value chain, The Gambia has the capacity to meet the demand for chicken and eggs. 88% of the value chain actors believe that the imposition of tariffs on chicken imports will lead to the upward transformation of the chicken value chain being able to employ at least 10% of the Gambian population.

Finite Element Analysis of Cold-Formed Steel Stud Wall Subjected to Blast Loading and Validation Using Artificial Neural Network and Response Surface Methodology (preprint)

This paper focused on the finite element analysis of structural system in extreme loading condition. Two different stud shape and thicknesses were analyzed under blast. The stud thickness such as 1.19 mm and 1.5 mm were modelled and analyzed using ABAQUS 6.14. FEM is a tool which predicts the engineering physics of the real structure. To validate the finite element modelling performed by authors, a reference work published by earlier researchers on cold-formed steel stud wall is considered and examined in the present study. The novelty of this study was web corrugation and influence of flange width on stud. The models mimic like an air bag in a car to delay the pressure timing inside the stud wall. The mass of explosive used as 1.56 kg at a standard scaled distance. Time versus displacement was captured out at four locations in the stud wall. One of the objectives is to develop mathematical model to validate the deformation of stud under blast loading. Two mathematical models were validated using Artificial Neural Network (ANN). The results captured in ANN model was error histogram, regression plot, best performance fit and training data. The models were capable of resisting the moderate blast load. The response surface methodology (RSM) was employed to evaluate model performance Regression equations are useful for predicting future trends and outcomes, which is crucial for planning and decision-making. The primary goal of this work is to evaluate cold-formed steel stud walls with varying stud sizes under blast loading using finite element analysis and validated by ANN and RSM.