Abstract—

The verification of Arabic handwritten signatures is an important research area in the fields of computer vision, machine learning, and deep learning. It is essential to distinguish between genuine and forged signatures due to its significance in preventing fraud and forgery, as well as in various legal contexts. Handwritten signatures vary due to several influencing factors, such as mood, writing surface, and writing instrument. In this research paper, three different datasets were utilized: the first dataset (Dataset1) is an English signature dataset known as CEDAR; the second dataset (Dataset2) is an Arabic signature dataset specifically created for this research; and the third dataset (Dataset3) combines the CEDAR dataset with the Arabic signatures. These datasets were utilized to develop a transfer learning model for signature recognition called MobileNet-V2, which is a deep neural network (DNN) model developed by Google, aimed at achieving a balance between accuracy and performance speed. It is primarily designed for image classification tasks in resource-constrained environments. Standard training and k-fold cross-validation (CV) methods were applied to evaluate the model's performance. The model achieved an accuracy of 97.74% on the CEDAR dataset, 98.49% on the Arabic dataset, and 99.49% on the combined dataset.

This study presents a descriptive statistical analysis of a retrospective study on Polycystic Ovary Syndrome (PCOS), a common endocrine disorder among women of reproductive age that can lead to various metabolic, hormonal, and reproductive complications. Data were collected from the Misurata Infertility Center between 2023 and 2024 from 250 women undergoing infertility evaluation. Demographic data, including age and body mass index (BMI), along with medical records, were reviewed. Hormonal parameters assessed were Luteinizing Hormone (LH), Follicle-Stimulating Hormone (FSH), Estradiol, Prolactin, Anti-Müllerian Hormone (AMH), and Thyroid-Stimulating Hormone (TSH). Biochemical markers included blood sugar (BS), HbA1c, and Vitamin D levels. Results indicated that the average BMI was 28.72, which is above the World Health Organization's ideal range (18.5–24.9), suggesting that most patients were overweight. The mean Estradiol level was 47.95 pg/mL (within the ideal range of 0–80), and the mean FSH was 7.704 mIU/mL (within the ideal range of 1.37–9.9). In contrast, the mean Prolactin level was 23.148 ng/mL, exceeding the ideal range (4.5–21.5), indicating hyperprolactinemia in most patients. The mean Vitamin D level was 21.22 ng/mL, below the ideal range (30–50), indicating a deficiency. The mean BS was 105.92 mg/dL (within normal range: 70–110), and the average HbA1c was 5.622%, suggesting most patients were not diabetic. Keywords: Polycystic Ovary Syndrome; Demographic Data; Medical Records; Hormonal Levels; Misurata Infertility Center.

STUDY DESIGN: Retrospective observational study.

OBJECTIVE: The study aims to evaluate the effects of early transfer of individuals with traumatic spinal cord injuries to a specialist

spinal injury centre, focusing on the duration of hospital and intensive care stays, as well as the incidence of medical complications.

SETTING: Regional Spinal Injuries Centre, UK.

PATIENTS AND METHODS: All patients with traumatic SCI admitted over a 4-year period to our Regional Spinal Injury Centre were

included in this study. A total of 104 patients were divided into 2 groups: those referred within 48 h (34 patients) and those referred

later after the injury but within 2 months of injury (70 patients). There were no differences in the number of patients with

tetraplegia or paraplegia or in the average age or sex between the two groups. there is no significant difference in the incidence of

associated injuries between the 2 groups.

RESULTS: Patients who were transferred early stayed less in the ICU than did those who were transferred late (9 and 25 days,

respectively; p < 0.05). The percentage of patients requiring ICU stay was also significantly lower (from 41–9%; p < 0.001); 24% of

patients in the early group had medical complications, while 45% of patients in the delayed group had these complications

(p < 0.05).The average length of hospital stay ( ± SD), including rehabilitation, in the early admission group was 121 (86.9) days,

while that in the delayed admission group was 188 (84.9) days (p < 0.0001).

CONCLUSION: Earlier admission of traumatic SCI patients to a spinal injury centre is associated with shorter acute care period,

shorter total hospital stay and reduced preventable complications.

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A new mechanical framework is introduced to describe bodies with time-continuous mass

variation, incorporating a functional dependence on mass. In this approach, the dynamics

are governed by momentum balance equations formulated using Caputo fractional

derivatives, which adhere to a weak form of Galilean invariance. The formulation is

particularly focused on the Meshchersky kinetics, accounting for both mass and velocity

changes. As a practical example, this paper presents a novel model for the motion of a

material body with continuously varying mass in a constant gravitational field—leading to

a time-fractional version of the Tsiolkovsky rocket equation, augmented by a dissipative

term. Under time-based approximation, deviations from vertical projectile motion are

analyzed to assess the internal consistency of the proposed model.

A three-parameter generalization of the Tsallis entropy based on the properties of the power functions and Weyl fractional calculus like extension of quantum calculus, are introduced. The generalization of the Shannon-Khinchin axioms corresponding to the fractional Tsallis entropy is verified and proposed. These axioms uniquely characterize new entropy function. For a certain sets of parameter values satisfied the second and third law of thermodynamics, the Lesche and thermodynamic stability criteria.