Background: Parkinson's disease (PD) is a neurodegenerative aging disease, with idiopathic PD being most common. Gastrointestinal tract disorders (GITD) and microbiota changes may trigger idiopathic PD. Neurotoxins from microbiota can travel from the gut to the brain via the brain-gut axis (BGA), leading to α-syn protein misfolding and dopaminergic neuron death. Methods: The aim of the current study was to investigate the link between PD and GITD by measuring several biochemical and immunological markers in 142 patients. The biochemical markers measured were vitamins B6, B12, and D, calcium, serotonin, ghrelin, dopamine, and α-syn protein. The immunological markers included transforming growth factor-beta (TGF-β), tumor necrosis factor-alpha (TNF-α), interleukin-1 beta (IL-1β), and interferon-gamma (IFN-γ). All markers were measured using the Enzyme-Linked Immunosorbent Assay (ELISA) technique. Results: PD patients were significantly older (63.76±12.29 years) compared to GITD and control groups (41.00±15.54 and 41.25±18.30 years, respectively). Males predominated in the PD group (74.5%), while females were more common in the GITD and control groups. PD and GITD patients showed significantly lower levels of vitamins and neurotransmitters but higher calcium and α synuclein compared to controls. Immunological markers were elevated in PD and GITD groups, with significant differences between them (P-value < 0.001). Conclusion: The study concluded that certain biochemical and immunological markers provide strong evidence of the brain-gut axis's involvement in the initiation of idiopathic Parkinson's disease.
The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com
... Show MoreIn this work, novel compounds of hydrazones derived from (2,4-dinitrophenyl) hydrazine were synthesized. Benzamides derivatives and sulfonamides derivatives were prepared from p-amino benzaldehyde. Then these compounds were condensed with (2,4-dinitrophenyl) hydrazine through Imine bond formation to give hydrazones compounds. The compounds were characterized using FT-IR (IR Affinity-1) spectrometer, and 1HNMR analyses. The majority of the compounds have a moderate antimicrobial activity against “Gram-positive bacteria staphylococcus Aureus, and staphylococcus epidermidis, Gram-negative bacteria Escherichia coli, and Klebsiella pneumoniae, and fungi species Candida albicans” using concentrations of 250 µg\ml.
Cyber-attacks keep growing. Because of that, we need stronger ways to protect pictures. This paper talks about DGEN, a Dynamic Generative Encryption Network. It mixes Generative Adversarial Networks with a key system that can change with context. The method may potentially mean it can adjust itself when new threats appear, instead of a fixed lock like AES. It tries to block brute‑force, statistical tricks, or quantum attacks. The design adds randomness, uses learning, and makes keys that depend on each image. That should give very good security, some flexibility, and keep compute cost low. Tests still ran on several public image sets. Results show DGEN beats AES, chaos tricks, and other GAN ideas. Entropy reached 7.99 bits per pix
... Show MoreThis study employs wavelet transforms to address the issue of boundary effects. Additionally, it utilizes probit transform techniques, which are based on probit functions, to estimate the copula density function. This estimation is dependent on the empirical distribution function of the variables. The density is estimated within a transformed domain. Recent research indicates that the early implementations of this strategy may have been more efficient. Nevertheless, in this work, we implemented two novel methodologies utilizing probit transform and wavelet transform. We then proceeded to evaluate and contrast these methodologies using three specific criteria: root mean square error (RMSE), Akaike information criterion (AIC), and log
... Show MoreABSTRACT: Polypyrrole and polypyrrole / silver nanocomposites were fabricated by in-situ polymerization employing Ammonium Persulphate as an oxidizing agent. Nanocomposites were synthesized by combining polypyrrole and silver nanoparticles in various weight percentages (0.1%, 0.5%, 3%, 5% and 7% wt.). Crystallographic data were collected using X-ray diffraction. PPy particles were found to have an orthorhombic symmetry. In contrast, PPy/Ag nanocomposites were reported to have monoclinic structure. The crystallite size was determined by XRD using Scherrer equation and considered to be within 49 nm range. DC conductivity of pelletized samples was evaluated in the temperature range of 323.15k to 453.15k. The conductivity displayed an
... Show MoreThe study explored applications of artificial intelligence and its dialectical relationship with international human rights law of individuals, which requires assessing the effects of this technology on human rights and freedoms. The problem of privacy of humanity, as AI technologies can control human rights and freedoms, while monitoring potential violations in this context. The study use of documentary research and qualitative lens to analyze the data. In conclusion, unawareness of the use of AI may impose significant hurdles on future generations and may infringe on human rights across all sectors of society. The government should mandate obligations for artificial intelligence businesses concerning education, health, human right
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