Effect of melatonin on developmental competence, mitochondrial distribution, and intensity of fresh and vitrified/thawed in vitro matured buffalo oocytes.

BACKGROUND: In livestock breeding, oocyte cryopreservation is crucial for preserving and transferring superior genetic traits. This study was conducted to examine the additional effect of melatonin to maturation and vitrification media on the in vitro developmental capacity, mitochondrial distribution, and intensity of buffalo oocytes. The study involved obtaining ovaries from a slaughterhouse and conducting two phases. In the first phase, high-quality oocytes were incubated in a maturation medium with or without 10-9M melatonin for 22 h (at 38.5°C in 5% CO2). Matured oocytes were fertilized in vitro and cultured in SOF media for seven days. In the second phase, vitrified in vitro matured oocytes were stored in vitrified media (basic media (BM) containing a combination of cryoprotectants (20% Ethyl Glycol and 20% Dimethyl sulfoxide), with or without melatonin, and then stored in liquid nitrogen. Normal vitrified/thawed oocytes were fertilized in vitro and cultured as described. Finally, the matured oocytes from the fresh and vitrified/thawed groups, both with and without melatonin, were stained using DAPI and Mitotracker red to detect their viability (nuclear maturation), mitochondrial intensity, and distribution using a confocal microscope. The study found that adding 10-9M melatonin to the maturation media significantly increased maturation (85.47%), fertilization rate (84.21%)cleavage (89.58%), and transferable embryo (48.83%) rates compared to the group without melatonin (69.85%,79.88%, 75.55%, and 37.25% respectively). Besides that, the addition of melatonin to the vitrification media improved the recovery rate of normal oocytes (83.75%), as well as the cleavage (61.80%) and transferable embryo (27.00%) rates when compared to the vitrified TCM group (67.46%, 51.40%, and 17.00%, respectively). The diffuse mitochondrial distribution was higher in fresh with melatonin (TCM + Mel) (80%) and vitrified with melatonin (VS2 + Mel groups) (76.70%), Furthermore, within the same group, while the mitochondrial intensity was higher in the TCM + Mel group (1698.60) than other group. In conclusion, Melatonin supplementation improves the developmental competence and mitochondrial distribution in buffalo oocytes in both cases(in vitro maturation and vitrification).

Well Performance Classification and Prediction: Deep Learning and Machine Learning Long Term Regression Experiments on Oil, Gas, and Water Production.

In the oil and gas industries, predicting and classifying oil and gas production for hydrocarbon wells is difficult. Most oil and gas companies use reservoir simulation software to predict future oil and gas production and devise optimum field development plans. However, this process costs an immense number of resources and is time consuming. Each reservoir prediction experiment needs tens or hundreds of simulation runs, taking several hours or days to finish. In this paper, we attempt to overcome these issues by creating machine learning and deep learning models to expedite the process of forecasting oil and gas production. The dataset was provided by the leading oil producer, Saudi Aramco. Our approach reduced the time costs to a worst-case of a few minutes. Our study covered eight different ML and DL experiments and achieved its most outstanding R2 scores of 0.96 for XGBoost, 0.97 for ANN, and 0.98 for RNN over the other experiments.

Cough Sound Detection and Diagnosis Using Artificial Intelligence Techniques: Challenges and Opportunities.

Coughing is a common symptom of several respiratory diseases. The sound and type of cough are useful features to consider when diagnosing a disease. Respiratory infections pose a significant risk to human lives worldwide as well as a significant economic downturn, particularly in countries with limited therapeutic resources. In this study we reviewed the latest proposed technologies that were used to control the impact of respiratory diseases. Artificial Intelligence (AI) is a promising technology that aids in data analysis and prediction of results, thereby ensuring people's well-being. We conveyed that the cough symptom can be reliably used by AI algorithms to detect and diagnose different types of known diseases including pneumonia, pulmonary edema, asthma, tuberculosis (TB), COVID19, pertussis, and other respiratory diseases. We also identified different techniques that produced the best results for diagnosing respiratory disease using cough samples. This study presents the most recent challenges, solutions, and opportunities in respiratory disease detection and diagnosis, allowing practitioners and researchers to develop better techniques.

The effect of Red Seaweed (Chondrus crispus) on the fertility of male albino rats.

At different parts of the world, Red Seaweeds are one component of human diets especially at Southeast Asia. Red Seaweeds structurally contain bioactive molecules so; we studied the effect of Chondrus crispus on increasing the male albino rat fertility. Twelve male albino rats are used in this study as two group pre-treated group and post- treated one each with 6 animals. The pretreated group was dissected before the post-treated group injection. Each post treated rat injected intramuscular with 1 mg of Chondrus crispus with dose 0.1 ml/ twice per week for 48 day (Mukhtar et al., 2013). The results showed that increasing on the total testosterone levels insignificantly, sperm motility significantly, and decreasing in both FSH and DPPH levels insignificantly and significantly for the MDA levels in the post-treated group. The morphological appearance and histological examination for the sperm, testis and liver were normal as the pretreated group. The molecular studies showed absence of any DNA fragmentation for the testis of both group. The Red Seaweed has an enhanced effect in the testicular function of the animal which might increase their fertility and sexual activities.

Applications of Big Data Analytics to Control COVID-19 Pandemic.

The COVID-19 epidemic has caused a large number of human losses and havoc in the economic, social, societal, and health systems around the world. Controlling such epidemic requires understanding its characteristics and behavior, which can be identified by collecting and analyzing the related big data. Big data analytics tools play a vital role in building knowledge required in making decisions and precautionary measures. However, due to the vast amount of data available on COVID-19 from various sources, there is a need to review the roles of big data analysis in controlling the spread of COVID-19, presenting the main challenges and directions of COVID-19 data analysis, as well as providing a framework on the related existing applications and studies to facilitate future research on COVID-19 analysis. Therefore, in this paper, we conduct a literature review to highlight the contributions of several studies in the domain of COVID-19-based big data analysis. The study presents as a taxonomy several applications used to manage and control the pandemic. Moreover, this study discusses several challenges encountered when analyzing COVID-19 data. The findings of this paper suggest valuable future directions to be considered for further research and applications.