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Heat stress has adverse effects on the health and performance of broilers. This study was conducted to investigate the protective effects of black seed (BS) supplementation on broilers subjected to heat stress (HS). A total of 500 (day-old) Ross-308 male broiler chicks were randomly assigned into five groups with five replicated pens (20 broilers per pen): thermoneutral (TN), heat stress (HS), and HS with a diet supplemented with three different levels of black seed (Nigella sativa) powder (BSP (at rates of 5g/kg (BSP-5), 10 g/kg (BSP-10), and 15 g/kg (BSP-15. Exposure to HS reduced feed intake, and weight gain and elevated feed conversion ratio (FCR), mortality (P < 0.05). Also, low antioxidant enzyme activity (such as glutathione peroxidase, superoxide dismutase, and catalase) and high malondialdehyde levels in serum, liver, and spleen were observed in the birds of the heat stress group compared to the TN treatment (P < 0.05). Moreover, HS elevated interleukin-6 and tumor necrosis factor-α and lowered interleukin-10 levels in serum, liver, and spleen (P < 0.05). In addition, heat stress causes an increase in ALT, AST, ALP, triglycerides, and cholesterol levels compared to the TV group (P < 0.05). Compared with the HS group, broilers in the BSP-10 group had a higher body weight gain, a lower feed conversion ratio, and mortality (P < 0.05). Broilers in the BSP-10 and BSP-10 groups showed higher levels of antioxidant enzyme activities and lower malondialdehyde in serum, liver, and spleen compared to the HS group. BSP supplementation at 10 and 15 mg/kg reduced TNF-α and interleukin-6 levels and enhanced interleukin-10 in serum, liver, and spleen compared to the HS group. Additionally, BSP supplementation at 15 mg/kg reduced the effect of the heat stress on ALT, AST, ALP, triglycerides, and cholesterol compared to the HS group. Obtained results showed that BSP in diet during heat stress may have a role in the reduction of the changes exerted by heat stress in broiler chickens.

Abstract Recently, various distributed energy resources are significantly integrated into the modern power systems. This introduction of distributed energy resource‐rich systems can cause various power quality issues, due to their uncertainties and capacity variations. Therefore, it is crucial to establish energy balance between generation and demand to improve power system's reliability and stability and to minimize energy costs without sacrificing customers’ comfort or utility. In this regard, power system flexibility concept is highlighted as a robust and cost‐effective energy management system, especially on the demand side, to provide consumers’ demands with an acceptable level of power quality. Accordingly, here, a comprehensive review of recent developments in the power system flexibility and demand‐side management strategies and demand response programs are provided to include mainly classifications, estimation methods, distributed energy resource modelling approaches, infrastructure requirements, and applications. In addition, current research topics for applying power system flexibility solutions and demand‐side management strategies based on modern power system operation are deliberated. Also, prominent challenges, research trends, and future perspectives are discussed. Finally, this review article aims to be an appropriate reference for comprehensive research trends in the power system flexibility concept in general and in demand‐side management strategies and demand response programs, specifically.

The research aims to study and analyze the role of adopting artificial intelligence technologies in supporting the predictive ability of financial statements in the context of big data. To achieve the research objective, the researchers designed a questionnaire that included three axes related to the research variables. It was distributed electronically to a sample of accountants, auditors, and investors in the Iraq Stock Exchange. Around 70 responses were collected from the sample members and relied upon in the practical aspect of the research. The SPSS statistical program was used to analyze the results. The research found that artificial intelligence technologies have a statistically significant effect in improving the predictive value of accounting information, and this effect increases in light of big data. Among the most important recommendations of the research is the necessity for financial analysts and investors to use artificial intelligence technologies because it contributes to the accuracy and speed of conducting analyses and comparisons that help improve the predictive value of information, as well as the necessity of employing and adopting big data analytics and capabilities due to the rapid and accurate data processing it provides.

ObjectiveThe main objective of this paper is to document the changing paradigm of malnutrition in Bangladesh and estimating how this is creating an intergenerational risk. This paper also examines national policy responses to tackle the silent epidemic of double burden of malnutrition.MethodsPublicly available datasets of five Bangladesh Demographic and Health Surveys were used to see the changing paradigm of malnutrition among Bangladesh women. In addition to that, four national policies concerning, maternal and child health; and nutrition were reviewed using CDC’s 2013 Policy Analytical Framework.ResultsIn Bangladesh, the share of ever-married women aged 15–49 who were underweight declined sharply between 2007 and 2017–2018, from 30 to 12%. In the same period, the proportion of women who were overweight or obese increased from 12 to 32%. Despite remarkable progress in reducing undernourishment among women, the share of well-nourished remained unchanged: 58% in 2007 and 56% in 2017–2018, mainly due to the shift in the dominant burden from undernutrition to overnutrition. This shift occurred around 2012–2013. Currently, in Bangladesh 0.8 million of births occur to overweight women and 0.5 million births occur to underweight women. If the current trend in malnutrition continues, pregnancies/births among overweight women will increase. Bangladesh’s existing relevant policies concerning maternal health and nutrition are inadequate and mostly address the underweight spectrum of malnutrition.DiscussionBoth forms of malnutrition pose a risk for maternal and child health. Underweight mothers are at risk of having anemia, antepartum/postpartum hemorrhage, and premature rupture of membranes. Maternal obesity increases the risk of perinatal complications, such as gestational diabetes, gestational hypertension, and cesarean deliveries. Currently, around 24% of the children are born to overweight/obese mothers and 15% to underweight mothers. Bangladesh should revise its national policies to address the double burden of malnutrition among women of reproductive age across pre-conception, pregnancy, and post-natal stages to ensure optimum maternal and child health.

A chronic metabolic condition, type 2 diabetes mellitus (T2DM) typically presents with hyperglycemia owing to elevated tissue insulin resistance or inadequate insulin release. In addition to the use of pharmaceutical agents and lifestyle changes for the management of T2DM, supplementation with various vitamins and minerals has also been proven to be of benefit. The objective of the present research was to establish the effectiveness of vitamin B12, vitamin C, selenium, and chromium as adjunctive therapy given over 120 days in diminishing insulin resistance. In total, 32 individuals (16 men and 16 women) living with diabetes were enrolled in the study. Fasting blood glucose (FBG), glycated hemoglobin (HbA1c), serum insulin concentrations, and homeostatic model assessment of insulin resistance (HOMA-IR) were quantified at baseline and on day 120 of supplementation. Mean FBG and HbA1c levels and insulin concentrations all decreased, i.e. 185.11 ± 22.67 mg/dL vs. 163.57 ± 19.31 mg/dL (P = 0.02), 8.47 ± 0.52% vs. 7.80 ± 0.48% (P = 0.003), and 23.15 ± 3.87 vs. 15.85 ± 1.46 (P = 0.02), respectively. HOMA-IR values remained unchanged. The association between therapy and clinical features was examined using logistic regression analysis. In the subjects with T2DM, FBG, and HbA1c levels were diminished by a factor of 2. It was concluded that vitamin and mineral supplementation was of benefit with respect to glycemic parameters. Nevertheless, high-quality evidence that supports the efficacy of such substances to improve glucose homeostasis and insulin resistance in individuals with T2DM in a clinical setting is lacking

Iron oxide nanoparticles were synthesized using a biological approach using the Beauveria bassiana fungus. The synthesized nanoparticles were characterized using X-ray diffraction (XRD), scanning analysis (SEM), and atomic energy microscope (AFM). The iron nanoparticles in an average grain size of ~ 39 nm. The topography and features of the surface show that there are ripples distributed regularly and homogeneously on the surface and that the deposited film is regular. The optical properties of iron oxide were studied using UV/Vis spectroscopy, and it was found that the absorbance gradually decreases as we approach the visible light region, starting from its peak at short wavelengths, where the surface plasmon resonance was recorded, which showed the absorbance at the UV wavelength at (282 nm), and the absorbance is at its maximum at high energies (short wavelengths), then decreases with increasing wavelength to reach its lowest value in the visible region of the spectrum, and for this reason the absorbance decreases with increasing wavelength, where the energy gap value is (2.5 electron volts). The FTIR spectrum showed functional groups have been recorded in a range These results confirm the presence of the fungal extract belonging to the fungus Beauveria bassiana. The vibrations in the phenolic compounds are responsible for the interaction process with the salts of the basic materials used in the preparation

This paper presents a thin film coupled Fabry–Perot cavities optical interleaver. The simulation results for the interleaver shows an outstanding performance in accurately selecting the required channels and robustness in the channel profile. The accuracy is achieved by varying the range of the incident angle. Furthermore, the interleaver has a re-configurable incident angle range with fine and coarse angle ranges, which provides a broader range of applications for such an interleaver. Moreover, the proposed approach provides the reconfigurability for the interleaver performance, which is now a reconfigurable thin-film-based device for selecting the odd/even interleaved channels. The channel selection is based on specific angle values for fine and coarse ranges. Such a device will add more flexibility and multi-functionality to the optical system.

Pupillometry is used in humans to monitor pain, nociception and analgesia. This single-center, non-randomized, non-blinded intervention trial, evaluated the effect of nose twitching on the pupil size in awake, sedated, and anesthetized horses. Pupil height (H) and length (L) were measured before (Be) and after (Af) nose twitching in fourteen non-painful adult awake horses (T0). The percentage of variation (PSV) was calculated (PSVTn = [(TnAf-TnBe)/TnBe]*100). Measurements were repeated (Tn) after acepromazine (0.04 mg kg−1 IV) (T1), romifidine (0.04 mg kg−1 IV) (T2), morphine (0.1 mg kg−1 IV) (T3), after anesthesia induction with diazepam (0.05 mg kg−1 IV) and ketamine (2.2 mg kg−1 IV), at the time the horse was placed on the operating table (T4) and when the expiratory fraction of sevoflurane was 2% (T5). HAf vs. HBe, LAf vs. LBe as well as PSVH vs. PSVL at each time were compared with a Mann–Whitney Wilcoxon test. The PSVL and PSVH, as well as HBe and LBe over time were compared with the Skillings-Mack test followed by a Wilcoxon test for paired data to make pairwise comparisons (Tn + 1 vs. Tn). In non-sedated horses (T0), the application of the nose twitch induced a significant increase in pupil length (LT0Be: 17.09 [16.05; 19.67] mm versus LT0Af: 19.52 [18.74; 21.40]) mm (p = 0.004). Thirty minutes after acepromazine administration (T1), nose twitching induced a significant increase in pupil length (LT1Be: 16.45 [14.80; 18.66] mm versus LT1Af 18.31 [17.20; 20.52] mm) (p = 0.016) and height (HT1Be: 8.44 [5.68; 12.04] mm versus HT1Af: 11.09 [7.97; 14.3] mm) (p

Abstract Background: Diabetes mellitus is a major noncommunicable disease worldwide, and its prevalence is rapidly increasing. The Finish score helps in the prediction of the risk of future diabetes development, as well as in the identification of undiagnosed diabetes. The current study was conducted to identify people at risk of developing type II diabetes mellitus in River Nile State, Sudan. Methods: This cross-sectional community-based study was conducted in River Nile state between 2019 October and 2020 March. Data were collected using a questionnaire that included the Finnish Diabetes Risk Score variables from 400 participants after an informed consent. Chi-square test was used to test the associations, with the P-value considered significant when < 0.05. Results: The majority of participants (257 [64.3%]) were < 45 years old, and 229 (57.3%) were male. The risk of type II diabetes mellitus was found to be low in 187 (46.8%) people and high in 213 (53.2%). Moreover, 128 (32%) had a body mass index (BMI) between 25and 30 kg/m2, while 46 (11.5%) had > 30 kg/m2. Waist circumference of < 94 cm was found in 147 (36.8%) males, while only 63 females (15.8%) had a waist circumference < 80 cm. Age, gender, BMI, daily activity, history of hypertension, history of hyperglycemia, and family history of diabetes were all significantly associated with the risk of developing diabetes mellitus (P < 0.001). Conclusion: The Finnish Diabetes Risk Score was found to be useful in facilitating wider access to the risk of type II diabetes among the study population. More than half of the study population were at risk of developing diabetes mellitus.

Abstract For the past few years, the addition of renewable energy sources has been on the rise, but the unregulated addition of these sources can cause severe harm to the grid. Therefore, it is necessary to have a predefined limit for a grid, beyond which no further addition of renewables should be allowed without reinforcement. That limit is called the hosting capacity (HC), which is addressed in the literature by search‐based methods with heavy computational burdens. This manuscript first presents a framework to find the HC for a grid. The same framework is then applied to 503 different simulated but realistic LV distribution feeders in Finland to find their HCs and the most effective network parameters in defining a network specific HC. Next, different machine learning models, that is, Decision Tree (DT), Random Forest (RF), Linear Regression (LR), K nearest neighbours (KNN), Logistic Regression, and Support Vector Machine (SVM) are implemented on the generated data. For the classification case, the accuracy values for logistic regression, KNN, and SVM were 0.89, 0.84, and 0.81, respectively. The findings demonstrate that the developed machine learning based technique will enable distribution network operators in finding the HC without applying any deterministic or probabilistic approaches.

The present study was conducted to explore the impact of corn starch nanoparticles (CSNPs) on the morphological, optical, and dielectric behaviors of the PVA/PMMA/PAAm (PPP) hybrid polymer matrix. The resultant PPP-CS nanocomposite films were synthesized employing the solvent casting procedure. Scanning electron microscope(SEM) images of the as-synthesized films revealed the successful embedding, homogeneity, and fine dispersion of CSNPs within the host PPP. No changes in the infrared ray(IR) band positions were seen upon embedding. The absorbance-λ chart illustrated an absorption band at 220 nm with red-shift toward higher wavelengths, which points out the semi crystalline structure of PPP-CS films. The optical coefficients were improved upon inclusion of CSNPs. The optical bandgap energy reduces from 4.50 to 4.12 eV as CSNPs’ weight percentage increases from 0 wt% to 4 wt%. Furthermore, the refractive index values for PPP-CS films are in the range of 0.5 and 2.5. The dielectric constants of the obtained films decreased with the increase in CSNPs, except for the conductivity. The embedding of a small amount of CSNPs into the hydrophilic matrix significantly improved the composite’s bioactivity. The inhibition zone diameters of Staphylococcus aureus bacteria were calculated to be 0, 26, and 32 mm for 0 wt%, 2 wt%, and 4 wt% CSNPs, respectively. The findings of this study are significant for the development of novel nanocomposite materials with antibacterial activity for optoelectronic device applications.

Abstract Accurate localization of gliomas, the most common malignant primary brain cancer, and its different sub-region from multimodal magnetic resonance imaging (MRI) volumes are highly important for interventional procedures. Recently, deep learning models have been applied widely to assist automatic lesion segmentation tasks for neurosurgical interventions. However, these models are often complex and represented as “black box” models which limit their applicability in clinical practice. This article introduces new hybrid vision Transformers and convolutional neural networks for accurate and robust glioma segmentation in Brain MRI scans. Our proposed method, TransXAI, provides surgeon-understandable heatmaps to make the neural networks transparent. TransXAI employs a post-hoc explanation technique that provides visual interpretation after the brain tumor localization is made without any network architecture modifications or accuracy tradeoffs. Our experimental findings showed that TransXAI achieves competitive performance in extracting both local and global contexts in addition to generating explainable saliency maps to help understand the prediction of the deep network. Further, visualization maps are obtained to realize the flow of information in the internal layers of the encoder-decoder network and understand the contribution of MRI modalities in the final prediction. The explainability process could provide medical professionals with additional information about the tumor segmentation results and therefore aid in understanding how the deep learning model is capable of processing MRI data successfully. Thus, it enables the physicians’ trust in such deep learning systems towards applying them clinically. To facilitate TransXAI model development and results reproducibility, we will share the source code and the pre-trained models after acceptance at https://github.com/razeineldin/TransXAI .

Giant Congenital Melanocytic Naevi (GCMN) is a very rare condition that mostly occurs due to an oncogenic mutation involving the NRAS (neuroblastoma RAS viral oncogene homologue) gene. GCMNs can be clinically diagnosed due to their typical features, but histopathology confirms the diagnosis. GCMN has a high propensity for transforming into malignant melanoma and leptomeningeal melanocytosis, leading to neurological deficits such as epilepsy and neurofibromatosis. As it is associated with Central Nervous System (CNS) melanosis, Magnetic Resonance Imaging (MRI) of the brain and spine is crucial. Here, three cases are reported of the babies born with GCMN from August 2022 to July 2023 in a tertiary care hospital among a total of 11,915 live births, where the incidence is much higher than found in the literature. Present series describes three cases with GCMN, including clinical features, MRI findings, short-term outcomes, risk factors, and modalities of the management. All three cases showed extensive blackish pigmented patches involving most of the body surface and MRI evidence of Neurocutaneous Melanosis (NCM). The third baby succumbed to death due to fulminant sepsis on day 2 of life. Management of GCMN requires a multimodal approach, including medical, surgical, chemotherapeutic, palliative, and psychological support for patients as well as parents, and follow-up is necessary for the early detection of malignant transformation. Detailed knowledge of this very rare condition may enable us to develop newer treatment modalities to achieve better outcomes in the near future.

The performance of intensity modulation (IM) with direct detection (DD) transmission systems is enhanced through a novel combination of multidimensional coding, Nyquist pulse shaping, and electronic dispersion compensation (EDC) at the transmitter using a finite impulse response (FIR) filter. A 24-dimensional (24D) extended Golay binary code effectively transforms each incoming 12-bit message into a 24-bit codeword, achieving a coding efficiency of 0.5 bits per symbol for a 56 Gb/s on-off keying (OOK) transmission over 80 km of single mode fiber. While this encoding process introduces a 50% overhead, the required bandwidth is maintained at 56 GHz through doubling the symbol rate and the application of Nyquist pulse shaping with a raised cosine (RC) profile and a roll-off factor of zero, resulting in a flat power spectral density. This flat distribution contrasts with standard OOK transmission at 56 Gb/s with a roll-off factor of 1.0, where signal power is predominantly concentrated in the lower frequency range. One of the key advantages of the 24D Golay code is its substantial error correction capability. However, the benefits of this multidimensional coding and Nyquist pulse shaping extend beyond error correction. It is shown that, while both the proposed and standard OOK methods exhibit comparable performance in a white Gaussian noise channel at back-to-back, they differ significantly under frequency selective power fading conditions caused by the interplay of chromatic dispersion (CD) and direct detection. The misalignment between the frequency notches introduced by the FIR pre-EDC and those inherent in the channel response, especially severe at lower frequencies, favors transmission schemes with a flat power spectral density, like the 24D Golay-coded Nyquist pulses.

The aim of the current study is to investigate the use of screen in young children before and during the pandemic and the attitudes of mothers towards their children's screen-viewing time. To achieve this, 20 mothers who have children between 1.5 and 6 years-old included in the study. The design of this qualitative study is phenomenology to collect more extensive and rich descriptions of experiences. These mothers were selected through convenient sampling method and due to the Covid-19 pandemic; interviews were carried out with one-on-one phone call. 21 open-ended interview questions were used to get information about the participants' views and practices. The findings showed that there are differences between mothers' expectations and practices about the screen meeting of their children, they could not implement their expectations on their own children, and their children met the screen at an earlier age. Also, findings revealed that mothers are conscious about the influences of screen-viewing and it has both physical and behavioral consequences for their children.