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This paper explores the electrical conductivity interphase of Ag/Epoxy composite using modified McLachlan theory and 3D finite element composite model through experimental verification. The model characteristic presents conductivity as a dynamic function influenced by particle content, particle electrical properties, electrical properties transition, and an exponent. This model was meticulously crafted, considering the intricate interplay between the polymer matrix and silver particles, the tunnelling distance between adjacent silver particles, and the interphase regions around particles. This model has proven its mettle through rigorous analysis of experimental results and the impact of various parameters on conductivity. The predictions have shown impressive alignment with the experimental data, highlighting the crucial roles played by the parameters in the conductivity of silver composites where the percolation threshold reached 6 vol % of filler loading. The experimental study demonstrated that the electrical conductivity was 3.84 × 10^-1 S/cm for micro-sized particles and 1.32 × 10^-2 S/cm for nano-sized particles. Notably, a large tunnelling distance drastically reduces conductivity, while higher and slighter surface energies of the polymer matrix and filler enhance conductivity. Furthermore, a thin interphase yields minimal conductivity, whereas a thick interphase and low waviness improve conductivity. The McLachlan-modified model falls slightly short in accuracy compared to the 3D finite element method models. Adjustments to the equations can enhance its alignment with experimental data.

Knowledge of domestic dog ecology and demography has been recognized as central to the design of an effective rabies control program. The study was conducted to assess owned dogs' ecology and demography and to identify predictors associated with dog ownership and rabies occurrence in the Amhara region, Ethiopia.

Method: ology: The study employed dog census and questionnaire surveys of 907 households selected using a multistage sampling technique from six rural and six urban districts of the Amhara region, Ethiopia. The ecology and demography of owned dogs in the selected areas were recorded and described using descriptive statistics. Mixed-effect logistic regression models were used to identify factors associated with dog ownership and rabies occurrence.

Results: A total of 6609 dogs were estimated from 42 kebeles in the 12 study districts. The male-to-female ratio of dogs was 1.7:1.0, and the mean age of dogs was 3.2 years. The proportion of households who owned at least one dog was 5.9 %. The average number of dogs per dog-owned household was 1.3. Dog to household ratio was 1.0:13.0, and dog to human ratio was 1.0:48.5. The majority of the dog owners (97 %) keep dogs for home guard and livestock herding. Only 57 % of the dogs were confined, and 16 % of them were vaccinated. Ninety-one percent of the dog owners did not practice neutering and spaying for dog population control. Religion, livestock ownership pattern, and occupation were associated with dog ownership (p < 0.05). Community residence and age of respondents were associated with rabies occurrence (p < 0.05), while zone was associated with both dog ownership and rabies occurrence at p-value <0.05.

Conclusions: The study indicated a low dog population relative to humans, which might make dog-based rabies control manageable. But at the same time, most dogs were not properly managed (confined and vaccinated), which calls for more awareness about responsible dog ownership to reduce zoonotic disease risk, including rabies. Generally, the study provides useful information about the demography and ecology of owned dogs in relation to rabies for making proper and effective rabies control strategies and is important to design the spatial distribution of rabies vaccination in dogs. However, as the study did not include stray dogs, which have great contributions to the spread of rabies, the information should be used with this caveat into consideration.

The study, herein, investigated the effects of the inclusion of longan peel (LP) powder in the diet of Nile Tilapia (Oreochromis niloticus), focusing on comparative evaluations of growth performance, immunity, and immune-antioxidant related gene expressions. For this purpose, a total of 300 healthy fish (average initial weight: 13.70 ± 0.06 g) were randomly distributed into five experimental treatment groups: 0 g kg^-1 (LP0), 10 g kg^-1 (LP10), 20 g kg^-1 (LP20), 40 g kg^-1 (LP40), and 80 g kg^-1 (LP80), all in triplicate, for 60 days. The results indicated that dietary supplementation with LP exhibited a significant influence (P < 0.05) in weight gain (WG), specific growth rate (SGR) and provided a better feed conversion ratio (FCR) in contrast to the control group (0 g kg^-1 LP). Moreover, skin mucus and serum immune parameters (lysozyme and peroxidase activity) were significantly higher (P < 0.05) in fish fed with different LP concentrations at both 4 and 8 weeks. Similarly, analysis of mRNA transcripts of immune (IL-1, IL-8, and LBP) and antioxidant (GSTa, GPX, and GSR) gene expressions showed a significant upregulation (P < 0.05) in LP-fed diet groups compared to the control group. Based on the polynomial regression analysis the inclusion of LP at 46-49 g kg^-1 can be used effectively in Nile tilapia diets for improving the growth, immunity, and immune-antioxidant gene expressions. All in all, our results prove that LP is a very promising feed supplement for the Nile tilapia in the context of aquaculture.

Sudden cardiac death (SCD) is a major health concern, which can be the sign of a latent mitochondrial disease. However, mitochondrial DNA (mtDNA) contribution is largely unexplored in SCD at population level. Recently, mtDNA variants have been associated with congenital cardiopathy and higher risk of ischemic heart disease, suggesting them as potential risk factors also in SCD. Therefore, we aimed to define the mtDNA mutational landscape in such phenotype, by sequencing the whole blood mtDNA genome in a pilot cohort of 28 unrelated subjects. Coding variants were prioritized according to their population and haplogroup frequency. Out of 28 patients, 36% were diagnosed with coronary artery disease, 39% with structural defects and 25% with unspecified cardiac disease. The overall frequency of macro-haplogroups followed the distribution in the European population. No known or novel mtDNA pathogenic variants were found. Two rRNA and 8 missense variants were rarer than polymorphisms as they had a frequency lower than 1% in population databases. 5/8 missense variants clustered in ATP synthase genes and 4/8 missense variants were previously detected in patients with suspected mitochondriopathy. We concluded that primary mitochondrial disease is not a major cause of SCD, but rare mtDNA variants may occur (35.7% in our cohort vs 0.65% in the population; p < 0.01), potentially modifying the risk.

Polymer matrix composites are popular for their lightweight and high strength. Poly (methyl methacrylate) (PMMA), known for its transparency, can be toughened with polyurethane (PU) to expand its applications. This study further strengthened PU-PMMA by adding carbon fiber powder from offcut fabrics (oCFP), enhancing mechanical and adhesion properties. Tensile, flexural, and lap-shear tests were conducted to investigate the effects of the oCFP on the mechanical and adhesion properties of the PU-PMMA resin. The oCFP-modified PU-PMMA was then used in scarf repair to assess its effectiveness on the impacted composite laminates. Tensile and flexural tests showed that 1 wt% oCFP improved tensile strength from 38 MPa to 43.31 MPa and flexural strength from 56.02 MPa to 82.21 MPa, while further addition of oCFP led to reductions in these strengths. Although oCFP-modified PU-PMMA did not significantly restore the impacted laminates' flexural strength, the repairing effect was still more pronounced than that of a commercial epoxy adhesive, demonstrating potential as a repair or structural adhesive.

Environmental antibiotic residues (EARs) and antibiotic-resistant bacteria (ARB) are known to contribute to global antimicrobial resistance (AMR). This study investigated EAR levels in selected wells, river, abattoir wastewater, bottled water and sachet water from Ede, Nigeria. Ecological risk quotient (RQ) and health risk (Hazard quotient) of the levels of these EARs, ARB and multidrug-resistant bacteria (MDR) with their antibiotic resistance were calculated. Antibiotic residues detected included tetracycline-TET (14.2-135.8 μg/L), chloramphenicol-CHL (6.8-224.7 μg/L), metronidazole-MET (3.7-83.8 μg/L), sulfamethoxazole-SUL (0.56-18.6 μg/L), and ciprofloxacin-CIP (3.8-97 μg/L). Antibiotic residues in STW samples were below the detection limit while ampicillin was not detected in any of the water samples. Chloramphenicol posed the highest ecological risk to algae while infants were particularly at risks of ciprofloxacin and metronidazole resistance in various water sources. No health risk due to bottled water exposure is observed for any population group. The mean log10 bacteria count (cfu/mL) followed the trend abattoir (5.68) > river (5.67) > hand-dug well (5.53) > sachet (5.03) > bottled (4.83). The most occurring ARB in water samples are Bacillus spp (36.3 %) > Staphylococcus (27.5 %) and the most dominant MDR isolate is Bacillus cereus. All isolates exhibited 62.5, 100, 31.3, 77.5, 58.8 and 33.8 % resistance to AMP, MET, CIP, TET, CHL and SUL, respectively. Visible-light composite material (Cu/Zn-doped delaminated kaolinite) completely disinfected 12.5 and 15.8 L of water containing Log₁₀ 7.5 cfu/mL of ARB Enterobacter sp and Bacillus sp respectively with no regrowth in treated water after storage for three days. Levels of EAR in the water sources in this study are among the highest in aquatic systems worldwide and can potentially lead to community AMR. Usage, discharge and sales of antibiotics should be guided by policies while routine monitoring of drinking water sources should be encouraged to reduce the AMR burden in the region. The photocatalytic material used in this study for water disinfection offers a promising, cost-effective solution for mitigating AMR risks from drinking water.

The prediction of energy consumption in households is essential due to the reliance on electrical appliances for daily activities. Accurate assessment of energy demand is crucial for effective energy generation, preventing overloads and optimizing energy storage. Traditional techniques have limitations in accuracy and error rates, necessitating advancements in prediction techniques. To enhance prediction accuracy, a proposed smart city system utilizes the Household Energy Consumption dataset, employing deep learning algorithms. In the beginning, data pre-processing addresses missing values and performs feature scaling for normalizing independent variables. Followed by that, Modified Deep CNN-Bi-LSTM (Convolutional Neural Network and Bi-directional Long Short Term Memory) with attention mechanism is utilized for regression which extracts temporal and spatial complex features. Deep CNN extracts features impacting energy consumption whereas Bi-LSTM with attention layer finds suitability for regression as it is capable of modelling irregular trends in the time-series components, where the attention mechanism is implemented to enhance the decoder's ability to selectively focus on the most relevant segments of the input sequence. This is achieved through a weighted integration of all encoded input trajectories, allowing the model to dynamically emphasize the vectors that carry the highest significance for accurate predictions. Based on regression outcomes from analysis taken in hourly, daily and monthly time intervals, enhanced prediction accuracy is estimated through evaluation metrics such as MSE (Mean Square Error), MAPE (Mean Absolute Percentage Error) and RMSE (Root Mean Square Error) which determines the efficacy of the system, where Specifically, the proposed model achieves MSE of 0.123, MAE of 0.22, and MAPE of 324.12. Furthermore, this model demonstrates a training time of 692.12 s and a prediction time of just 1.87 s. Therefore, present research highlights the critical need for accurate energy consumption prediction in households, driven by the increasing reliance on electrical appliances in daily life.

Research has demonstrated that POU3F4 is integral to various cancers, in addition to its significance in inner ear development, pancreatic differentiation, as well as neural stem cell differentiation. Nevertheless, comprehensive pan-cancer analyses focusing on POU3F4 remain limited. This study aims to assess the prognostic value of POU3F4 in thirty-three cancers and explore its immune-related functions. Based on data from The Cancer Genome Atlas (TCGA), Cancer Cell Line Encyclopedia (CCLE), Genotype-Tissue Expression (GTE), and Gene Set Cancer Analysis (GSCA), we employed various bioinformatics approaches to investigate the potential carcinogenic effects of POU3F4. Our study encompassed DNA methylation, RNA methylation, tumor mutation burden (TMB), mismatch repair (MMR) genes, microsatellite instability (MSI), the relationship between POU3F4 and prognosis, and immune cell infiltration (ICI) across different tumors. The analysis revealed that POU3F4 expression is typically low in most cancers but is elevated in breast invasive carcinoma, glioblastoma multiforme (GBM), liver hepatocellular carcinoma, and thyroid carcinoma, with the highest levels in GBM. Additionally, POU3F4 expression correlates with cancer prognosis, either positively or negatively. The expression of POU3F4 demonstrated significant associations with MSI in four cancers and TMB in six cancers. POU3F4 expression was significantly linked to DNA methylation in 13 cancer types and RNA methylation in most cancers. It also correlated with the tumor immune microenvironment, immune-related genes, immune checkpoint inhibitors, and drug resistance in various cancers. In vitro experiments demonstrated that POU3F4 enhances cell viability, proliferation, and migration in GBM. Our findings indicate that, given its critical role in carcinogenesis and tumor immunity, POU3F4 serves as a prognostic marker in diverse malignancies.

Background: Episiotomy is a surgical intervention performed during the second stage of labor to facilitate the baby's exit through the birth canal. There are different reasons that lead to an episiotomy; however, it is recommended to be performed occasionally and not systematically, since it may produce negative effects such as pain. Different therapies have been described to reduce this pain, including transcutaneous electrical nerve stimulation (TENS).

Objective: To conduct a systematic review and meta-analysis about the effects of Transcutaneous Electric Nerve Stimulation (TENS) on pain after episiotomy.

Methods: The databases PubMed, Cochrane, Scopus, Cinhal, PEDro and Web of Science were consulted using the terms "Episiotomy" and "Transcutaneous Electric Nerve Stimulation". The methodological quality was analyzed with the PEDro scale. A random-effects model was used to carry out the meta-analysis.

Findings: 88 studies were obtained and after applying the selection criteria, 6 were included in the systematic review and 5 in the meta-analysis. There were significant positive effects in decreasing the pain for TENS in comparison with pre-intervention (SMD = 1.19 [95 % CI - 0.33 to 2.05]; p < 0.01; I2 = 96 %), control group (SMD = -1.07 [95 % CI - -1.53 to -0.6]; p < 0.01; I2 = 82 %) and placebo group (SMD = -1.33 [95 % CI - -2.32 to -0.34]; p < 0.01; I2 = 86 %).

Conclusion: TENS appears to have a positive effect in reducing pain after 1 h of an episiotomy. The location of the electrodes does not seem to be relevant in the effects.