This paper presents the experimental results of the tensile, bending, hardness, hydrostatic testing, and microstructural properties of liquefied petroleum gas cylinders from local sources. The burst pressure and fracture sites were also investigated. In addition, know how LPG cylinders are compliant with ISO 4706 requirements as per standard to get approval and acceptance. The tests were performed on three samples (C1, C2, and C3), and all the tests were according to the specification. Tensile testing was carried out at room temperature (23C°) as per ISO 6892-2016. Tensile test specimens with a gauge length of 50 mm were prepared from the sidewall of cylinders. The equipment used is built up around a 250 KN maximum capacity of (Instron Servo-Hydraulic Testing Machine Model 1332). At the same time, micro-hardness testing was carried out as per ASTM A384. Diamond indenter (pyramid) with a face angle of 136° was used. During testing (1kg) load was applied on the sample with a dwell time of 15 seconds. As for bending tests were carried out in accordance with ISO 7438 for all cylinders to evaluate their welding qualities. The results of microstructural characterization show that the carbon content for all samples averaged ~ 0.067 wt.% and manganese ~ 0.46 wt.% and the microstructure was largely ferritic. The tensile strength of the parent metal showed that LPG gas cylinders recorded high tensile strength of ~ 418 MPa on average, yield strength of ~ 291 MPa on average, a % elongation 26.6 (for parent metal), the tensile strength of ~ 449 MPa as average, yield strength of ~ 314 MPa as average, % elongation 32 (for weld metal) and hardness of ~ 143 (kg/mm2) as average by Vickers scale. Moreover, in the hydrostatic pressure test, the computer controlled electro-hydraulic servo pressure test machine was used. The results of the hydrostatic pressure test were as follows, pressure burst (BP) 103 bar, nominal hoop stress 528 MPa, volumetric expansion 25%, hydrostatic extend ratio 3.9%, sites of failure exist out of welding, and finally no fragmentation observed regarding to fracture types. All samples tested exhibited high resilience to crack

propagation which showed ductile fracture after burst and tensile test

In this work, we investigate essential definitions, defining 𝐺 as a simple graph with vertices in ℤ𝑛 and subgraphs Γ𝑢 and Γ𝑞 as unit residue and quadratic residue graphs modulo 𝑛, respectively. The investigation extends to the degree of 𝐺, Γ𝑢, and Γ𝑞, illuminating the properties of these subgraphs in the context of quadratic congruences.

Globally, many studies are being conducted on foods, especially processed items, which actually play a role in changing the genetic characteristics of humans due to the genetic changes caused by these foods. Clear efforts are being made to use food as a treatment for many diseases by giving specific nutritional advice to specific people based on their genes and how they are affected by particular foods. Among these non-communicable diseases are obesity, diabetes, hypertension, and many lifestyle-related diseases. On the personal level, we are working on disseminating a diet system known as the ancestral diet (A-diet), which is a dietary modification plan that focuses on simplicity, traditions, and plant-based nutrients, inspired by ancient nutrition. The aim of this article was to focus on the importance of age and genetics in dealing with the change in foods intake behaviors and nutritional patterns that each individual consumes based on his/her genes and desires, the latter of which are linked to the lifestyle of each person’s age group. An example of this is the tendency of people to become obese, diabetic, or hypertensive as a result of a certain food. Some sort of food that makes people sick, while it does not effect on other people`s health, and the explanation for this is the difference in genes. While the change and diversity in eating patterns, especially among children and young people have become greatly influenced by the environment, friends, schoolmates, and social media.

The non-standalone architecture (NSA) of 5G networks builds upon existing 4G long-term evolution (LTE) infrastructure, integrating 5G new radio (NR) technology while still relying on the 4G core network. In contrast the standalone architecture (SA) of 5G networks is designed as a fully independent system, with its own 5G core network. It does not rely on the existing 4G LTE infrastructure. The NSA integrates 5G NR technology into existing 4G LTE networks, utilizing the 4G core network for control and signaling. On the other hand, the SA establishes a fully independent 5G network with its own core components, providing more advanced features and greater autonomy. The transition from NSA to SA architecture is expected as network operators deploy more comprehensive 5G networks. This paper investigated in details the major different between both architectures NSA and SA of 5G networks.

Abstract— Speech recognition is a valuable tool in various industries; however, achieving high accuracy remains a major challenge, despite the rapid growth of the speech recognition market. Arabic in particular lags behind other languages in the field of speech recognition, requiring further attention and development. To address this issue, this research uses deep neural networks to develop an automatic Arabic speech recognition model based on isolated words technology. A hybrid model, which is originally developed by Radfar et al. [1] for English speech recognition, is adopted and adapted to be used for Arabic speech recognition. This model combines the strengths of recurrent neural networks (RNNs), which are critical in speech recognition tasks, with convolutional neural networks (CNNs) to form a hybrid model known as ConvRNN. A specific model for Arabic speech recognition which is referred to as “Arabic_ConvRNN” model has been developed based on “ConvRNN” model. The adopted model is trained using an Arabic speech publicly available dataset of isolated words, along with a custom-generated dataset specially prepared for this research. The performance of the built model has been evaluated using standard metrics, including word error rate (WER), accuracy, precision, recall, and F-measure (also referred to as f1 score). In addition, K-fold cross-validation method has been employed generalizability. to ensure robustness and The results demonstrated that Arabic_ConvRNN model achieved a high accuracy rate of 95.7% on unseen data, with a minimal WER of about 4.3%. These findings highlight the model's effectiveness in accurately recognizing Arabic speech with minimal errors. Comparisons with similar models from previous studies further Arabic_ConvRNN validated model. the superiority Overall, of the Arabic_ConvRNN model shows great promise for applications requiring accurate and efficient Arabic speech recognition. This research contributes to narrowing the gap in Arabic speech recognition technology, offering a robust solution for accurately converting Arabic speech into text.