In this study, we evaluated the potential of fungal endophytes to control yellow rust in wheat (Triticum aestivum L.) as endophytes are beneficial microbes and alternate to pesticides for confronting pathogens. The in-vitro efficacy of the fungal endophytes isolated from different desert plants was evaluated and the best four namely Colletotrichum lindemuthianum, Piriformospora indica, Acremonium lolii and Trichoderma viride were selected. Seeds of two susceptible wheat genotypes namely Fareed-06 and Shafaq-06 obtained from screening experiment were inoculated by dipping in four endophytic spore suspensions and were sown using randomized complete block design under factorial arrangement. Data concerning about area under disease progress curve, final disease severity percentage, coefficient of infection,1000- grains weight and grain yield were recorded. Results showed that endophyte P. indica showed significant decrease in final disease severity (FDS) and area under disease progress curve (AUDPC), resultantly 12.2% grain yield gain in rust susceptible wheat genotypes of Fareed-06 and Shafaq-06 followed by the endophytes T. viride, C. lindemuthianum and A. lolii with the grain yield gain of 10.6%, 06.2% and 04.2% respectively. In crux, fungal endophytes are valuable microbes which can be employed to induce tolerance against P. striiformis in yellow rust vulnerable areas for better and sustainable wheat production.

Nanoparticles (NPs) are commonly used in healthcare and nano therapy, but their toxicity at high concentrations is well-known. Recent research has shown that NPs can also cause toxicity at low concentrations, disrupting various cellular functions and leading to altered mechanobiological behavior. While researchers have used different methods to investigate the effects of NPs on cells, including gene expression and cell adhesion assays, the use of mechanobiological tools in this context has been underutilized. This review emphasizes the importance of further exploring the mechanobiological effects of NPs, which could reveal valuable insights into the mechanisms behind NP toxicity. Such investigations could aid in developing new strategies to mitigate NP toxicity and improve their safety for biomedical applications. Moreover, understanding how NPs affect cell cytoskeletal functions through mechanobiology could have significant implications, including the development of innovative drug delivery systems and tissue engineering techniques. In summary, this review highlights the significance of incorporating mechanobiology into the study of NP toxicity and demonstrates the potential of this interdisciplinary field to advance our knowledge and practical use of NPs.

Sentiment analysis is a technique used to understand the publics’ opinion towards an event, product, or organization. For example, positive or negative opinion or attitude towards electric vehicle (EV) brands. This provides companies with valuable insight about the public's opinion of their products and brands. In the field of natural language processing (NLP), transformer models have shown great performances over the traditional machine learning algorithms. However, these models have not been explored extensively in the EV domain. EV companies are becoming signif-icant competitors in the automotive industry and are projected to cover up to 30% of the United States light vehicle market by 2030 [1]. In this study, we present a comparative study of large language models (LLMs) including bidirectional encoder representations from transformers (BERT), robustly optimized BERT approach and generalized autoregressive pretraining for language un-derstanding using Lucid motors and Tesla motors YouTube datasets. Results evidenced LLMs like BERT and her variants are off-the-shelf algorithms for sentiment analysis, specifically, when fi-ne-tuned. Furthermore, our findings presents the need for domain adaptation whilst utilizing LLMs. Finally, the experimental results showed that RoBERTa achieved consistent performance across the EV datasets with a F1 score of at least 92%.

Accurate and efficient medicinal plant image classification is of utmost importance as these plants produce a wide variety of bioactive compounds that offer therapeutic benefits. With a long history of medicinal plant usage, different parts of plants, such as flowers, leaves, and roots, have been recognized for their medicinal properties and are used for plant identification. However, leaf images are extensively used due to their convenient accessibility and are a major source of information. In recent years, transfer learning and fine-tuning, which use pre-trained deep convolutional networks to extract pertinent features, has emerged as an extremely effective approach for image identification problems. This study is leveraging the power of three component deep convolutional neural networks, namely VGG16, VGG19 and DenseNet201, to derive features from the input images of the medicinal plant dataset, containing leaf images of 30 classes. The models were compared and ensembled to make four hybrid models to enhance the predictive performance by utilizing the averaging and weighted averaging strategies. Quantitative experiments were carried out to evaluate the models on the Mendeley medicinal leaf dataset. The resultant ensemble of VGG19+DensNet201 with fine-tuning showcases enhanced capability in identifying medicinal plant images with an improvement of 7.43% and 5.8% compared with VGG19 and VGG16. Furthermore, VGG19+DensNet201 can outperform its standalone counterparts by achieving an accuracy of 99.12% on the test set. A thorough assessment with metrics such as accuracy, recall, precision, and f1-score firmly establishes the effectiveness of the ensemble strategy.

Punica granatum (PG) or Pomegranate is a bush, having many trunks and often get taller 1.8 to 4.7m long and their leaves are shiny and fleshy, approximately 7 to 8cm in length. Traditionally, it is used in diarrhea and dysentery due to its strong constricting property. Punica Granatum covering used in dysentery, diarrhea, piles, bronchitis. It is also used to minimize the risk of heart disease. The peel extract of Punica Granatum contain methanol and their dried peels has antidiarrheal venture, also help in wound healing activity. Peels of the pomegranate also holds around 60% of the fruit and they contain different types of ingredients including ellagitannins and proanthocyanidin compounds and minerals such as calcium, phosphorus, magnesium, potassium, flavonoids and sodium. Some animals were found in different local areas with both acute and chronic diarrhea. The condition of these animals were quite miserable because of dehydration and loss of electrolytes in the body cells of the animals. They were unable to move due to seriousness of the disease. 8 grams of PG Peel Powder mixed with 1 liter of water, 2 g of PG Peel Powder mixed with 250 ml water and 8 g of PG Peel Powder mixed with 1 liter of water were administrated orally by using sterilized bottles to the selected three cases. 3 days after the administration of different doses, all cases of diarrheal animals show a significant recovery. The condition of the animals seem to be healthier. Before administration of the pomegranate peel powder extract, all three cases had weak body structure due to diarrhea. Watery stool that may be yellow in color and mucus was also evident in the stool, due to this reason the patient calf was weak and depressed. In sometimes they also show unconsciousness and blood glucose levels seem to be reduced from the normal level.

Trypanosomes are the extracellular protozoan parasites that cause human African trypanosomiasis disease in humans and nagana disease in animals. The disease is endemic in African countries where tsetse flies which act as a vector for the transmission of disease are present. The animals infected by these parasites become useless or workless and disease can become fatal if not treated. Old drugs used for treatment have many side effects and some are responsible for death in 5% of the patients. The parasite possesses a major surface protein known as variant surface glycoprotein. The immune system of the host develops antibodies against this antigen but due to antigenic variation, parasites evade the immune response. Currently, no vaccine is available that provides complete protection. Only partial protection using certain antigens in murine models was investigated. The tools of molecular biology and immunology have enabled a novel approach to the development of vaccines against trypanosomes. Immunization is the sole method for the control of disease because the eradication of the vector from endemic areas is an impossible task. Genetic vaccines can carry multiple genes encoding different antigens of the same parasite or different parasites. DNA immunization induces the activation of both cellular immune response and humoral immune response along with the generation of memory. This review highlights the importance of DNA vaccines and advances in the development of DNA vaccines against T. brucei.

In this paper, a local meshless method (LMM) based on radial basis functions (RBFs) is utilized for the numerical solution of various types of PDEs, due to the flexibility with respect to geometry and high order of convergence rate. In case of global meshless methods, the two major deficiencies are the computational cost and the optimum value of shape parameter. Therefore, research is currently focus towards localized radial basis function approximations, as the local meshless method is proposed here. The local meshless procedures is used for spatial discretization whereas for temporal discretization different time integrators are employed. The proposed local meshless method is testified in terms of efficiency, accuracy and ease of implementation using regular and irregular domains.

The hybrid method proposed in the study, ANFIS-GWO, combines the Adaptive Neuro-Fuzzy Inference System (ANFIS) with Grey Wolf Optimization (GWO) for the diagnosis of liver disorders. ANFIS is a powerful tool that combines the advantages of neural networks and fuzzy logic to create a hybrid model capable of handling complex and uncertain data. GWO is a metaheuristic optimization algorithm inspired by the social behaviour of grey wolves. In the ANFIS-GWO method, the hyperparameters of ANFIS are optimized using GWO. This optimization process aims to fine-tune the ANFIS model based on the available dataset, which consists of 7 characteristic attributes and 354 samples related to liver diseases. By adopting the hyper-parameters, the ANFIS-GWO method enhances the overall performance and accuracy of the diagnostic system. To evaluate the effectiveness of the ANFIS-GWO intelligent medical system, the study employs classification accuracy, sensitivity, and specificity analysis. Classification accuracy measures the overall correctness of the system in predicting liver disease cases. Sensitivity refers to the system’s ability to correctly identify individuals with liver disorders, while specificity measures its ability to correctly identify those without liver disorders. Experimental results demonstrate that the performance of the ANFIS-GWO method surpasses that of traditional Fuzzy Inference Systems (FIS) and ANFIS models that do not undergo an optimization phase. This suggests that the integration of GWO optimization significantly improves the diagnostic accuracy of the ANFIS model for liver disease diagnosis.

In this work, meshless methods are applied for the solution of two-dimensional steady-state heat conduction problems with nonlocal multi-point boundary conditions (NMBC). These meshless procedures are based on multiquadric radial basis function (MQ RBF) and its modified version (i.e. integrated MQ RBF). The proposed meshless methods which were recently published in \cite{Reutskiy2016} is compared with standard collocation method (i.e. Kansa's method). Three different sorts of solution domain are considered in which Dirichlet boundary condition is specified on some part of the boundary and is related to the unknown function values at a discrete set of interior points. The influence of NMBC on the accuracy and condition number of the system matrix associated to the proposed methods is investigated. The sensitivity of the shape parameter is also analyzed in the proposed methods. Performance of the proposed approaches in terms of accuracy and efficiency is confirmed on the benchmark problems.

The current study emphasizes on optimizing a suitable ratio of enzymatically hydrolyzed potato powder (EHPP) and whole milk powder (WMP) to produce a quality yogurt by evaluating the physicochemical and rheological properties. The results showed that the addition of EHPP decreased the pH towards acidic conditions which resulted in the high acidity of yoghurt. The proximate composition showed that EHPP increased the ash, protein, water holding capacity (WHC) while fat, synersis, color parameters and total solid were decreased when compared to control yoghurt (CY) sample. Moreover, texture profile (TPA) analysis showed that the addition of EHPP decreased the hardness and cohesiveness while springiness did not show significant difference. Furthermore, rheological properties revealed that EHPP decreased the storage modulus (G’) and loss modulus (G”) when compared with control. In addition to this, sensory analysis revealed that the treatment P4M (1:3) was found as optimum ratio regarding taste, flavor, and aroma. Besides this, scanning electron microscopy (SEM) confirms that the high amount of EHPP resulted in the void holes while CY showed dense gel structure. The prepared yogurt with EHPP provides an excellent flavor, satisfying sweetness and homogeneous texture. These findings suggest the optimum formulation ratio of prepared yogurt was found to be P4M (1:3) for desirable attributes and consumer acceptance. The prepared yogurt from the EHPP presents the potential industrial applications.

Stabilized un-doped Zinc Telluride (ZnTe) thin films were grown on glass substrates under vacuum using closed space sublimation (CSS) technique. A dilute copper nitrate solution (0.1/100 ml) was prepared for copper doping known as ion exchange process in the matrix of ZnTe thin film. The reproducible polycrystalline cubic structure of undoped and Cu doped ZnTe thin films with preferred orientation (111) was confirmed by X-rays diffraction (XRD) technique. Lattice parameter analyses verified the expansion of unit cell volume after incorporation of Cu species into ZnTe thin films samples. The micrographs of scanning electron microscopy (SEM) were used to measure the variation in crystal sizes of samples. The energy dispersive X-rays was used to validate the elemental composition of undoped and Cu-doped ZnTe thin films. The bandgap energy 2.24 eV of ZnTe thin film decreased after doping Cu to 2.20 eV may be due to the introduction of acceptors states near to valance band. Optical studies showed that refractive index was measured from 2.18 to 3.24 whereas thicknesses varied between 220 nm to 320 nm for un-doped and Cu doped ZnTe thin film respectively using Swanepoel model. The oxidation states of Zn⁺², Te⁺² and Cu⁺¹ through high resolution X-ray photoelectron spectroscopy (XPS) analyses was observed. The resistivity of thin films changed from ~10⁷ Ω-cm for undoped ZnTe to ~1 Ω-cm for Cu-doped ZnTe thin film, whereas p-type carrier concentration increased from to respectively. These results predicted that Cu-doped ZnTe thin film can be used as an ideal, efficient and stable intermediate layer between metallic and absorber back contact for the heterojunction thin film solar cell technology.

Background: Hepatitis B virus (HBV), a lethal form of viral hapatitis, is an extra burden on the socioeconomic status of a country. Objectives: The population-based studies to quantify the incidence of hepatitis B. Data sources: in the North Waziristan, formally known as EX-FATA (Federal Administrated Tribal Area), Pakistan, are still rare. Study eligibility criteria: 943 individuals were selected on the basis of signs and symptoms to determine the epidemiology of HBV in the study population. Tests: Hepatitis B virus (HBV). Methods of data synthesis: Among these, 626 were male and 317 were female. All the HBV suspected individual were screened through ICT (Indirect Coombs Test) , ELISA (enzyme-linked immunosorbent assay) and RT-PCR (Re-verse transcription polymerase chain reaction). Results: The results obtained from the screening tests for HBV revealed that RT-PCR based results are more reliable and it indicated that HBV infection is more common in male 41 (6.54%) than female 15 (4.73%). The age range selected for the study was 1-75 years. Age wise analysis indicated that HBV is more prevalent among individuals of age group between 16 to 45 years. This age range also showed higher number of patients having either mild, moderate or elevated viral loads. The HBV genotype D was the most common, present in 62.5% patients. However, 16.07 % patients were having genotype U, 12.5 % genotype C, 8.92 % genotype A, and 7.14% had genotype B. Discussion: The questionnaire based investigation revealed that HBV was most prevalent among married individuals (64.6%), whereas least prevalent among individuals having HBV positive family member (1.4 %). The other risk factors contributed were history of dental procedures (57.8%), ear, nose, piercing, or tattooing and uses of un-disposable syringes (56.5%), transfusion of blood or plasma (42.9%), surgery (41.8%), frequent visits to barber shops (39.45%), and addiction of injectable drugs (38.1%). The current study is providing a clear picture of the alarming situation HBV transmission and emphasis on the need for more effective planing, strategies and policies for the control and prevention of HBV.

The build-up of greenhouse gases (GHGs) is causing warmness in the Earth’s atmosphere, resulting in climate change. The transport sector is one of the active members of GHG emissions and it is imperative to use sustainable transport sources to control climate change. The measure aims to encourage citizens to stop using their private vehicles as their choice of transport and instead opt for joint sustainable mobility during traveling. In this study, a quantitative research method was used and data were collected from a sample of 410 respondents through questionnaire. On the other hand, study also took a simulation-based (N=10000) sample size of private vehicle data. The data were analyzed using structural equation modelling. The results revealed that sustainable transportation, climate change technologies and electric rail vehicles reduce climate change in the ecoregions of China. We conclude that sustainable transportation policies could be formulated and implemented to reduce climate change. In response to the research results, it is recommended that, since climate change is a multi-level governance issue and the outdated pyramidal transport industry models must be shifted to a sustainable transportation system model.

Herein, we present the design technique of a resonant rectifier for piezoelectric (PE) energy harvesting. We propose two diode equivalents to reduce the voltage drop in the rectifier operation, a minuscule-drop-diode equivalent (MDDE) and a low-drop-diode equivalent (LDDE). The diode equivalents are embedded in resonant rectifier integrated circuits (ICs), which use symmetric bias-flip to reduce the power wasted for charging and discharging the internal capacitance of a PE transducer. The self-startup function is supported by synchronously generating control pulses for the bias-flip from the PE transducer. Two resonant rectifier ICs, using both MDDE and LDDE, are fabricated in a 0.18 μm CMOS process and their performances are characterized under external and self-power conditions. Under the external-power condition, the rectifier using LDDE delivers an output power POUT of 564 μW and a rectifier output voltage VRECT of 3.36 V with a power conversion efficiency (PCE) of 90.1%. Under self-power conditions, the rectifier using MDDE delivers a POUT of 288 μW and a VRECT of 2.4 V with a corresponding PCE of 74.6%. The result shows that the power extraction capability of the proposed rectifier is 5.9 and 3.0 times higher than that of a conventional full-bridge rectifier.

Dark energy and dark matter are described as different manifestations of vacuum energy in a new cyclic universe framework of Extra Dimensional Symmetry (EDS) that doubles large spatial dimensions with microscopic partners. In this testable framework, vacuum energy, constrained by a Planck density constraint, exists in a gravitationally dark state where actual gravitational constant G_o = 0G. While a small repulsive component is constrained by an asymptotically evolving asymmetry to the active state where G_o = 2G, some components in the inert state are enabled to gravitationally attract by neutrino induced gravitational constant with light and shear activated heavy components. Observational and experimental tests are briefly discussed.

The anthropometric features offer an overall image of the nutritional status. The investigated groups were aged 19 and 21. The anthropometric measurements of height and weight were recorded following standard procedures. The objectives of this study were to evaluate the harmonious body development, the nutrition status and the body composition. The evolution of the stature increases until 20 years after which stagnation follows. The body mass index of subjects was found to be normal. The body fat may vary over time in subjects depending on age and gender. Body water and body muscle mass content increased with age. The harmony of body development was assessed by means of the Amar index. Regarding the constitutional index, the women subjects belong to the leptosome type and the male subjects belong to the picnic type. The status of the investigated subjects is within the average stature.

Aedes aegypti mosquito is a vector that could transmit various pathogens, such as viruses, bacteria, and parasites. Several human diseases transmitted by Ae. aegypti mosquito are dengue fever (DHF), Chikungunya, Yellow Fever and Zika. The occurance of resistance to various insecticides, including pyrethroid, is a current problem faced by various countries. In this research, a WHO bioassay test on Palembang and Jakarta Ae. aegypti was conducted using 0.25% permethrin pyrethroid insecticide. VGSC gene fragments associated with pyrethroid resistance (L982, S989, I1011, L1014, V1016 and F1534) of resistant and sensitive strains were amplified and analyzed. The test showed the presence of resistance in Ae. aegypti isolates from Palembang and Jakarta. From the results of VGSC gene fragment analyses, it was known that there were mutations (S989P and/or V1016G) on isolates from Palembang and (S989P and/or V1016G) on resistant isolates from Jakarta.

This study evaluates the effectiveness of an integrated vestibular rehabilitation program in improving balance, motor control, and proprioceptive function in patients diagnosed with Benign Paroxysmal Positional Vertigo (BPPV). The prospective observational study involved 107 participants who underwent a tailored rehabilitation regimen, including the Epley maneuver, Brandt-Daroff exercises, and balance and proprioceptive training. The program was designed to address the vestibular and proprioceptive deficits caused by BPPV, with the goal of restoring normal function and reducing the risk of symptom recurrence. Dynamic Gait Index (DGI) and Balance Beam Test were used to assess progress, showing significant improvements in balance stability and dynamic motor function. The findings support the integration of vestibular rehabilitation into standard care for BPPV patients, highlighting the program's potential to enhance patient outcomes and reduce recovery time. However, the study also notes limitations such as the lack of a control group and the need for further research to explore the long-term effects of such interventions.

Cervical Cancer affects a large part of female population that makes the prediction of this disease based on Machine Learning (ML) by outmost importance. ML algorithms can be integrated in complex intelligent agent-based systems that can offer decision support to the resident medical doctors or even to experienced medical doctors. For instance can be mentioned the situation when an experienced medical doctor diagnose a case but he/she needs expertise support that is related to another medical specialty. Data imbalance is frequent in healthcare data and has a negative influencing effect in making predictions using ML algorithms. Cancer data generally and cervical cancer data particularly are frequently imbalanced. Based on this fact the study of data imbalance impact on diverse state-of-the-art ML prediction algorithms is important. This research subject is also motivated by the fact that in many research are presented experimental evaluations of algorithms without characterization of the data on that they have been applied. Such characterizations could give clear indication to other researchers regarding the applicability of the algorithms on their specific data. Specifically, if the data have the respective characteristics than are expectable the same performance evaluation results like those in the reported research. For the study we chosed a messy real-life Cervical Cancer dataset available in a recognized data repository included a large amount of missing and noisy values. To identify the best imbalanced technique for this medical dataset, it is compared the performance of eleven important resampling methods combined with the following state-of-the-art ML models: K-Nearest Neighbours (with k values of 2 and 3), binary Logistic Regression, and Random Forest, that are frequently applied in prediction types of researches in healthcare. The studied resampling methods includes seven undersampling methods namely Condensed Nearest Neighbour, Tomek Links, Edited Nearest Neighbours, Repeated Edited Nearest Neighbours, All K-Nearest Neighbours, NearMiss, Neighbourhood Cleaning Rule, and Instance Hardness Threshold, and four oversampling methods namely Synthetic Minority Oversampling Technique (SMOTE), Adaptive Synthetic Sampling Approach for Imbalanced Learning SMOTE, Support Vector Machine SMOTE and Borderline SMOTE. In the case of the dataset for the confidence interval with 95% confidence level was between 9.23 and 16.22, while the imbalance ratio is 12.73. The obtained results show that resampling methods help the learning models to improve the classification ability of cervical cancer. The applied oversampling techniques generally showed better results than undersampling methods. In the case of Logistic Regression classifier had the highest impact on balanced techniques, while Random Forest had promising performance, even before balancing techniques and KNN2 was generally better than KNN3.

This study investigates the efficacy of an integrated rehabilitation program that combines vestibular and knee-focused therapies to improve proprioceptive function, balance, and motor control in patients suffering from both Benign Paroxysmal Positional Vertigo (BPPV) and knee joint conditions. The study involved 59 participants diagnosed with both vestibular dysfunction and knee impairments, who were enrolled in a comprehensive rehabilitation program. Vestibular interventions included specific maneuvers such as the Epley maneuver and Brandt-Daroff exercises, aimed at repositioning otoliths and reducing vertigo symptoms, while balance retraining exercises were implemented to enhance stability and prevent falls. Additionally, TECAR therapy was used for its deep tissue heating and regenerative benefits, and specific proprioceptive exercises targeting the knee joint were conducted to improve joint position sense and reduce the risk of falls. The intervention resulted in significant improvements in proprioceptive accuracy, as evidenced by enhanced joint position sense measurements and increased scores on the Dynamic Gait Index (DGI). These findings suggest that the dual-targeted rehabilitation approach not only addresses the individual impairments associated with vestibular dysfunction and knee pathology but also effectively improves overall functional outcomes by tackling the complex interplay between these conditions. The study further highlights the importance of a multidisciplinary approach in rehabilitation, where addressing vestibular and musculoskeletal dysfunctions simultaneously can lead to better patient outcomes. The integrated rehabilitation strategy presented in this study offers a comprehensive approach to managing complex clinical cases, ultimately contributing to improved quality of life and functional independence in patients affected by concurrent vestibular and knee joint issues.

Hypotrochoidal profile contours have been produced in industrial applications in recent years using twin-spindle processes, and they are considered effective high-quality solutions for positive shaft–hub connections. This study mainly concerns analytical approaches to determine the bending stresses in hypotrochoidal profile shafts. The formulation was developed according to bending principles using the mathematical theory of elasticity and conformal mappings. The loading was further used to investigate the rotating bending behaviour. The stress factors for the classical calculation of maximum bending stresses were also determined for all those profiles presented and compiled in the German standard DIN3689-1 for practical applications. The results were also compared with the corresponding numerical and experimental results, and very good agreement was observed. Additionally, based on previous work, the stress factor was determined for the case of torsional loading to calculate the maximum torsional stresses in the standardised profiles, and the results are listed in a table. This study contributes to the further refinement of the current DIN3689 standard.

The feasibility of using zeolites, synthesized from components found in municipal solid waste fly ash (MSW-FA), as sorbents for the recovery of nutrients (nitrate and phosphate) and heavy metals is critically assessed in this review. The inherent drawbacks of utilising a highly contaminated, variable, and relatively Al- and Si-dilute source such as MSW-FA to synthesize zeolites are discussed, and different methods to extract and decontaminate zeolite precursor materials from MSW-FA are considered. Ways to synthesize tailored zeolites and how their properties as well as the operational conditions impact the adsorption of cations such as ammonium and heavy metals are summarized. The use of surface-modified zeolites to adsorb nitrate and phosphate is also reviewed. And subsequently, approaches to utilise directly or recover for reuse the adsorbed compounds are considered, discussing potential challenges and mitigating measures related to leaching of unwanted compounds from the zeolites. Moreover, the possibility to regenerate the adsorption capacity of the zeolites for multiple adsorption cycles is considered. In the final chapter of the review a more general discussion of the main challenges and existing research gaps is provided, giving directions for recommended studies.

this paper focuses on a scientific study of the restoration, rehabilitation and reuse of the great throne hall, the most important hall in al-jawhara palace. it also aims to study the most important factors and forces of damage that affected the great throne hall, natural, biological, and human, and the resulting damage. field tests were performed, laboratory tests to determine fracture stress, liquidity and spandex limits tests, chemical analysis on soil samples and geoelectrical testing of the soil, and the results did not show caves or voids in the ground until a depth of 10.00 m, construc-tion materials were studied and tested using x-ray, (xrd), mechanical tests (tensile, shear, com-pression), and a study of the effect of seismic loads on the walls; the results showed horizontal and vertical cracks; based on the study and analysis of these cracks, it was possible to present modern techniques in restoration and reinforcement methods, and in conclusion, the researcher's recommendations.

Antibiotic-loaded bone cement has been traditionally advocated as a key step for the success of one-stage hip revision surgery, while cementless techniques have been recently proposed with and without the use of local antibacterials as an equally successful alternative. Aim of this review is to investigate the effective role of local antimicrobial protection for one-stage cemented and cementless hip revision surgery. Twelve studies reporting the results of cemented single-stage procedure at a minimum two years follow-up were reviewed. When pooling together the data, no infection recurrence was observed on average in 83.3% of the patients (range 75.0% to 100%). Only two papers, both from the same French group, included patients treated without the use of antibiotic-loaded bone cement, with an average infection control of 95.9% in a total of 195 patients. This figure appears better that the 80.7% infection control obtained by pooling together all the remaining studies. Concerning cementless one-stage revision, a total of 17 studies, reporting on 521 patients, showed an average 90.0% (range 56.8% to 100%) no infection recurrence, at a minimum two years follow-up. Eight papers reported the outcomes of cementless implants without any local antibacterial protection and nine more described four different techniques for local antimicrobial implant protection. No comparative study investigated cementless revision with or without local antibacterial protection. Pooled data showed an average infection control of 86.7%, without the application of local antibacterials, compared to 90.1% to 100% with local antimicrobial protection, depending on the technology used. However, due to the relatively low number of patients treated with each local antimicrobial protection, no statistical difference could be found, either considering local antibacterial strategies alone or pooled together. No side effect had been reported by any local antibacterial technique. This review points out that local antibacterial protection for one-stage hip revision surgery, although safe and largely performed in the clinical setting, appears still to rely mainly on experts’ opinion and on observational series with no prospective or comparative trial, hence no definitive conclusion can be drawn concerning its effective role in one-stage hip revision surgery.

There is a sustained rise in incidence of cancer and toxicity related to chemicals exerting enormous burden to public health and biodiversity. Polycyclic Aromatic Hydrocarbons (PAHs) are mong such contaminants, precisely the sixteen-priority characterized by United States Environmental Protection Agency (USEPA). Therefore, this review is aimed at further elaboration about the 16 USEPA characterized PAHs and threat portend to public health and biodiversity. PAHs are a class of very stable organic pollutants produced most commonly, by incomplete combustion of fossil fuel and are formed when complex organic substances are exposed to heat. PAHs in great amount due to build up over time by bioaccumulation can be perilous: to human beings of all age and levels, aquatic organisms, amphibians and reptiles. The soil like the aquatic environment contains substantial quantity of PAHs since, atmospheric PAHs sediments on the soil due to dry and wet deposition, terrestrial organism are impacted if the soil is saturated with PAHs. Therefore, PAHs are a great source of trepidation for food safety, public health and biodiversity sustenance. Hence, tackling the spade of the menacing ubiquity of PAHs becomes necessary from its sources by encouragement of alternatives to petroleum fuels for machines and vehicles.

Falls are a frequent and serious problem for older adults and especially those living with Parkinson’s. The relationship between falls and physical activity is complex and people often restrict activity following a fall. Exercise is an important aspect of re-ducing further risk of a fall and a key component of the management of Parkinson’s. The aim of this study was to understand the types of activity that are engaged in, the environments in which they take place and the experience of people with and without Parkinson’s who have fallen. 17 people with Parkinson’s and 13 older adults, who had experienced at least one fall in the previous year, were recruited to this mixed methods study. Activity levels were captured over one week using accelerometers and body worn cameras, allowing the type and location of activity to be recorded and analysed. This information informed an interview. Findings showed that although both groups often achieved up to 10,000 steps per day, this was in very short bouts of activity. Sedentary activity such as watching television dominated the findings. Participants were aware of the benefits of being active but described many barriers to achieving the level of activity they would like to.

Accurate and reliable measurement of real-world walking activity is clinically relevant, particularly for people with mobility difficulties. Insights on walking can help understand mobility function, disease progression, and fall risks. People living in long-term residential care environments have heterogeneous and often pathological walking patterns, making it difficult for conventional algorithms paired with wearable sensors to detect their walking activity. We designed two walking bout detection algorithms for people living in long-term residential care. Both algorithms used thresholds on the magnitude of acceleration from a 3-axis accelerometer on the lower back to classify data as “walking” or “non-walking”. One algorithm had generic thresholds, while the other used personalized thresholds. To validate and evaluate the algorithms, we compared the classifications of walking/non-walking from our algorithms to the real-time research assistant annotated labels and the classification from an algorithm validated on a healthy population. Both the generic and personalized algorithms had acceptable accuracy (0.83 and 0.82 respectively). The personalized algorithm showed the highest specificity (0.84) of all tested algorithms, meaning it was the best suited to determine input data for gait characteristic extraction. The developed algorithms were almost 60% quicker than the previously developed algorithms, suggesting they are adaptable for real-time processing.

MIGAL – Galilee Research Institute is a regional R&D center in the northeast peripheral region of Israel. An internationally recognized applied research institute, MIGAL specializes in biotechnology and computational sciences, plant sciences, precision agriculture and environmental sciences, as well as food, nutrition and health. Most of MIGAL’s researchers serve as the core faculty at Tel Hai Academic College (TH). Despite the country’s small surface area, socioeconomic inequality in Israel is high by OECD standards, with wage differences between rich and poor regions reaching up to 400%. The aims of this study are to identify possible socioeconomic impacts of MIGAL–TH on the peripheral northeast’s development. We discuss the effects of academic research and institutions of higher education on mitigating differences between the center and periphery of the country. Data for MIGAL, TH and the northeastern peripheral region were collected from the yearly reports of the two institutions and the Israel Central Bureau of Statistics. MIGAL was found to serve as a link between research, academic teaching and socioeconomic development in the northeast periphery. Several variables related to this link and describing MIGAL–TH and northeastern periphery development were analyzed over time: MIGAL’s budget, total number of employees and number of employees with PhDs; number of TH graduate students; socioeconomic index (SEI) of the northeastern periphery and its position on the Israeli list of regional SEIs. The signs and significance levels of their trends indicate a potential socioeconomic impact of academic research and higher education on peripheral development in the northeast of the country. Research budgets and the creation of jobs for academics living in the region are just a few examples of this impact.

Working capital management requires a careful attention by the corporate managers because it plays an important role in corporate stability. Social belongingness of managers induced them to learn from their society, colleagues and from overall industrial movement. They also learn from their peers which have more strategical efficiency. In line with these arguments, the objective of current study is to explores the peer influence on corporate working capital management practices. To making analysis, ten-years data (2009-2018) of non-financial publicly listed firms at PSX were collected and the cash conversion cycle (CCC) uses as a proxy variable of working capital management (WCM). To estimate the regression, an econometric technique named the Generalized Method of Moments (GMM) was used. The empirical findings suggest the significant impact of peer WCM on corporate WCM. It also suggests the significant impact of other variables that determine the WCM. This study recommends social learning policy to corporate managers. They can learn from their peers to manage the working capital. Most previous studies discuss the peer influence on investment decisions, corporate cash holding and financing policy, etc., but no study explores such a relationship specifically in the Pakistani non-financial sector data set.

This study investigates the asymmetric impacts of oil price changes on inflation in Algeria, Angola, Libya and Nigeria. Three different oil price data were applied in this study; the specific spot oil price of individual countries, the OPEC reference basket oil price and an average of the Brent, WTI and Dubai oil price. The dynamic panels ARDL were used to estimate the short and the long-run impacts. Also, this study partitioned the oil price into positive and negative changes to capture asymmetric impacts and found both positive and negative oil price changes positively influenced inflation. However, the impact was found to be more significant when oil prices dropped. The results from the study also found that money supply, the exchange rate and GDP are positively related to inflation while food production is negatively related to inflation. Accordingly, policymakers should be cautious in formulating policies between the positive and negative changes in oil prices as it was shown that inflation increased when the oil price dropped. Additionally, the use of contractionary monetary policy would help to reduce the inflation rate, and lastly, it is proposed that the government should encourage domestic food production both in quantity and quality to reduce inflation.

A Partial discharge (PD) occurrence in high-voltage (HV) and medium-voltage (MV) power assets is a warning sign of insulation system degradation or defective manufacturing/assembly, that may cause catastrophic damage and eventually lead to the breakdown of the power equipment. Ultra-high frequency (UHF) PD measurement technology has extensively been used to monitor the insulation health of the HV or MV equipment due to its high immunity against ambient noise and conducted disturbances. This paper presents experimental validation of a new design of a UHF planar rectangular microstrip antenna that can be used for PD monitoring of HV and/or MV power equipment, such as power transformers. The designed planar rectangular microstrip antenna has a compact size of 80mmx70mmx1.6mm. Laboratory experiments were performed to validate the antenna sensitivity to PD activity caused by insulation defects created inside an oil-filled transformer tank model. PD measurement results confirm that the proposed rectangular microstrip antenna has high sensitivity and high signal-to-noise ratio (SNR), thanks to its capability to suppress external noise disturbances, especially during online PD monitoring. Thus, the proposed UHF antenna seems to be a promising and alternative PD sensor that can be employed in UHF PD monitoring systems of HV or MV power equipment.

Millet is a staple food in Northern Nigeria, widely used for the preparation of various millet-based dishes. However, traditional processing methods, such as de-husking, can significantly affect the grain's nutritional and antioxidant properties. This study evaluates the antioxidant composition and nutritional value of four millet varieties cultivated in Northern Nigeria, with a particular focus on the impact of de-husking on these parameters. Our analysis encompasses the proximate composition, phytochemical content, antioxidant vitamins, mineral elements, amino acid profile, and antioxidant activities of the millet samples. The findings reveal that all millet varieties contain significant levels of antioxidant compounds, including phenolics, flavonoids, and vitamins, although their concentrations varied due to genetic differences and environmental factors. Notably, in the mineral composition, higher (p

This article discusses the impact of new financial technologies, such as Non-Fungible Tokens (NFTs) on traditional industries such as art, sports, and game, while focusing on the recently formed "Metaverse" market. As a component of the overall blockchain ecosystem, the history of the establishment of NFT is analyzed. The impact of Web3 and intelligent contracts on Fintech are also investigated. This study examines the general trends in the NFTs market, including their price formation, price-influencing factors, and available patterns. Then the paper provides classifications and examples of NTFs. Besides, the technological application and primary technical path are also described. Later, the paper assesses the market's and marketplaces' accessibility. Finally, this study evaluates the management applications of NFTs and analyzes existing platforms, and demonstrates how they can be implemented effectively in various settings. The concluding portion discusses technological obstacles. The study concludes with a discussion of potential applications for the results and prospects for future research.

Distributed Manufacturing (DM) is becoming increasingly important in operations management due to its potential to support sustainability goals, reduce risks in global supply chains, and boost local economies. However, previous analyses of the advantages and disadvantages of DM have mainly focused on operations, overlooking additional benefits across the supply chain. For example, DM can enable local sourcing, better serve end-users, and tackle reverse supply chain challenges. While economies of scale are essential for reducing costs and improving productivity, highly centralised manufacturing can increase transportation costs, vulnerability, and supply chain disruptions, particularly during pandemics or other times of restricted transportation. To address these challenges, this study introduces a Multi-attribute Decision Support System (MADSS) and assessment process that considers impacts across the supply chain and guides stakeholders, academics, and decision-makers. The MADSS handles quantitative and qualitative information, missing data, and uncertainty, and a team of experts from academia and industry in New Zealand has developed the evaluation. The MADSS was used to analyse DM and traditional construction alternatives from economic, social, environmental, and resilience perspectives in New Zealand. The research contributes to a better understanding of the impacts of DM across the entire supply chain. Also, it proposes a flexible decision-making framework to engage with stakeholders and support decision-making in other industries and regions.

We proposed a so-called Beta Kumaraswamy Burr Type X distribution which gives the extension of the Kumaraswamy-G class of family distribution. Some properties of this proposed model were provided, like: the expansion of densi- ties and quantile function. We considered the Bayes and maximum likelihood methods to estimate the parameters and also simulate the model parameters to validate the methods based on dierent set of true values. Some real data sets were employed to show the usefulness and exibility of the model which serves as generalization to many sub-models in the elds of engineering, medical, survival and reliability analysis.

We proposed a so-called Beta Kumaraswamy Burr Type X distribution which gives the extension of the Kumaraswamy-G class of family distribution. Some properties of this proposed model were provided, like: the expansion of densities and quantile function. We considered the Bayes and maximum likelihood methods to estimate the parameters and also simulate the model parameters to validate the methods based on different set of true values. Some real data sets were employed to show the usefulness and flexibility of the model which serves as generalization to many sub-models in the field of engineering, medical, survival and reliability analysis.

Enhancing the management and monitoring of oil and gas processes demands developing precise predictive analytics techniques. Over the past two years, oil and its prediction have advanced significantly using conventional and modern Machine Learning techniques. Several review articles detail the developments in predictive maintenance and technical and non-technical aspects of influencing the uptake of big data. The absence of references for machine learning techniques impacts the effective optimization of predictive analytics in the oil and gas sector. This review paper offers readers thorough information on the latest machine learning methods utilized in this industry's predictive analytical modelling. The review covers forms of Machine Learning techniques used in predictive analytic modelling from 2021 to 2023 (91 articles). It provides an overview of the details of the papers that were reviewed, comprising of the model’s categories, the data's temporality, field, and name, the dataset's type, predictive analytics (classification or clustering or prediction), the models' input and output parameters, performance metrics, optimal model, and benefits and its drawbacks. Additionally, suggestions for future research directions are provided to raise the potential of the associated knowledge and increase the accuracy of oil and gas predictive analytics models.

Investigation into a modified deterministic rumour spread model using mathematical epidemiology approach as an extension of Daley and Kendall (D-K) model was carried out. It is proven that the spread of a rumour is fairly comparable to a contagious disease transmission, except that the spread depends solely on the fraction of individuals who are aware of the rumour at the early stage as well as the intrinsic rumour spread rate . Model simulation reveals a rumour diminishing strategy so far as is maintained.

Though studies have characterized lizard dung as an unconventional psychoactive substance of abuse, this has not been demonstrated in experimental settings. We evaluated the toxicity and CNS activity of lizard dung in Wistar rats. The acute and subacute toxicity studies were conducted via oral and inhalational routes. Classical models of tail suspension, forced swim, elevated plus maze, hole board, and sodium pentobarbital-induced sleeping time tests were adopted and the lizard dung were administered via both routes. No mortality was observed for all doses of the test substance administered via both routes during the toxicity studies. Significant changes in serum urea, creatinine, bilirubin, ALP, ALT and AST were recorded. Mixed inflammatory infiltrates and oedema were observed in the lungs from the group that inhaled 1.0g darkish part of lizard dung. Lizard dung produced marked reduction in the exploratory behaviour. Our findings indicate depression of the CNS.

Rainfall runoff modeling has been a subject of interest for decades due to a need to understand a catchment system for management, for example regarding extreme event occurrences such as flooding. Tropical catchments are particularly prone to the hazards of extreme precipitation and the internal drivers of change in the system, such as deforestation and land use change. A model framework of dynamic TOPMODEL, DECIPHeR v1 - considering the flexibility, modularity and portability - and Generalized Likelihood Uncertainty Estimation (GLUE) method are both used in this study. They reveal model performance for the streamflow simulation in a tropical catchment, i.e. the Kelantan River in Malaysia, that is prone to flooding and experiences high rates of land use change. 32 years' continuous simulation at a daily time scale simulation along with uncertainty analysis resulted in a Nash Sutcliffe Efficiency (NSE) score of 0.42 from the highest ranked parameter set, while 25.35% of the measurement falls within the uncertainty boundary based on a behavioral threshold NSE 0.3. The performance and behavior of the model in the continuous simulation suggests a limited ability of the model to represent the system, particularly along the low flow regime. In contrast, the simulation of eight peak flow events achieves moderate to good fit, with the four peak flow events simulation returning an NSE > 0.5. Nonetheless, the parameter scatterplot from both the continuous simulation and analyses of peak flow events indicate unidentifiability of all model parameters. This may be attributable to the catchment modelling scale. The results demand further investigation regarding the heterogeneity of parameters and calibration at multiple scales.

In this paper, a new relay system that uses the UAV as a relay station between the tethered UAV and ground user (TU2U2G) is proposed. The TU2U2G system replaces the base station (BS) in the cellular system with a tethered UAV (TUAV). The TUAV is a UAV that receives power over a cable from a ground control station. It has advantages of high and variable altitude up to (100m) compared to BS. In addition, it overcomes the UAV drawback of the batteries' limited capacity. After that, a 3D placement Algorithm of the UAV as a relay station in the TU2U2G system is proposed. It is presented to maximize the coverage by jointly optimizing the transmitting power and relaying distance. The TU2U2G system shows better results than the traditional cellular system in terms of optimum UAV height, maximum coverage radius, and maximum distance between BS and UAV.

Food insecurity is a multidimensional concept adequately challenging not only the complex operationalization effort but also judgments of who is food secure and who is not. This study aimed to assess the level of household food insecurity in the study area. Both probability and non-probability sampling procedures were employed to draw the 367 respondents, key informants, and focus group discussants. The Consolidated Approach for Reportig Indicators (CARI) console model was constructed with four indicators: Food consumption score, Food energy shortfall, Food expenditure share, and Livelihood asset depletion. Descriptive statistics was used to analyze data in the models. The CARI result revealed that 41.1%, 9.3%, 20.4% and 29.2% of households were food secure, marginally food secure, moderately food insecure and severely food insecure, respectively. The overall prevalence showed that 49.6% households were food insecure and 50.4% were food secure. Moreover, female-headed households and households living the Belg and CHV livelihood zones were more food insecure than their counterparts. The study concluded that the problem of food insecurity is pervasive in the study area in general and Belg and CHV livelihood zones, in particular. Therefore, more attention and intervention should be given by policymakers and concerned development partners to alleviate the problem.

The construction industry, a major player in economic development, is facing increased pressure to address sustainability concerns amidst rapid population growth and urbanization. With global projections indicating a significant rise in building demand by 2050 , sustainability emerges as a crucial focus area and paradigm shift to enhance environmental friendliness, improved quality, and project outcomes. The UAE, renowned for its vibrant construction industry, offers a unique context for examining the integration of sustainable practices. The growing use of sustainable construction practices is growing in the U.A.E., where the built environment plays a key role in economic growth and environmental stewardship. The United Arab Emirates (UAE) aims to foster long-term sustainability while enhancing the standard of living for current as well as future generations by integrating social, environmental, and economic aspects within construction projects, while also reevaluating conventional sustainable development frameworks and embracing a Triple -Bottom Line approach. Through an exploration of the significance of sustainable construction materials, this researcher underscores the multifaceted benefits of locally sourced, recyclable, and renewable materials in reducing environmental impacts, fostering economic and social well-being, and improving overall project performance, and project management practices. The construction sector's role in economic development and its substantial environmental impact are discussed in, alignment with sustainable construction materials, sustainable construction practices, and the need to enhance environmental sustainability; and create healthier built environments. In the realm of sustainable construction materials, project management knowledge areas encompass a range of factors. These include the properties of materials sourced regionally;, the incorporation of recycled content;, considerations for indoor air quality, energy, and water efficiency parameters;, and how these properties relate to project scope, scheduling constraints, and challenges. Additionally, the availability of resources and competency levels, quality control standards, specifications, communication strategies, and stakeholder involvement play crucial roles. It is important to assess both the positive and negative risks associated with these elements across construction projects.

Teeth segmentation plays a pivotal role in dental diagnosis, treatment, planning, and the development of computer-aided dental systems. It enables precise identification and analysis of dental structures, aiding in detecting dental abnormalities, measuring tooth dimensions, and assessing oral health conditions. Accurate teeth segmentation also facilitates the automation of dental workflows, leading to improved efficiency and reduced human error. Artificial Intelligence (AI) has witnessed rapid advancements, with various approaches developed or enhanced. While Convolutional Neural Networks (CNNs) have been widely used in medical image segmentation, the U-Net architecture has emerged as a standout performer due to its exceptional segmentation capabilities. This paper presents a proof of concept for the Attention U-Net architecture, as previously used in [1], applied to teeth segmentation. The study demonstrates the superior performance of this network in accurately segmenting teeth using a newly available benchmark dataset called Tufts Dental X-Ray Dataset. When trained and tested on 10-fold cross-validation, the model achieved an average dice coefficient of 95.01%, intersection over union of 90.6%, and pixel accuracy of 98.82%. These scores surpass those of all other networks implemented on the same dataset. By leveraging the Attention U-Net architecture, our research showcases the potential of advanced AI techniques in dental radiography. The findings contribute to the ongoing efforts to develop automated systems to assist dental professionals in their clinical practice.

Education for Sustainable Development (ESD) is a global initiative towards transforming education for sustainability. The integration of SD into the education portfolio is considered to be an important approach that ensures strategic alignment of higher education with SDGs. A document review was used to identify and discuss the difference between transmissive and transformative education in relation to SDGs and in the context of Somali education. In this trajectory, it is expected that the concept of ‘‘transformative education is likely to become more common to meet the emerging social, economic and environmental issues, yet practical challenges remain in Somaliland HE sector. The roadmap towards addressing transformative education for sustainability is not included in the Somaliland national portfolios; particularly ESD has not been presented. In this regard, this paper proposed a generic framework that spotlights the integration of HEIs and the national development goals (NDGs) in Somaliland. Meanwhile, developed and developing countries are prioritizing structural transformation in their HEIs that are tailored to national and regional development programs. Consistent with the Rio + 20 outcomes, the authors analyzed the concept of the ‘‘sustainable university’’ and identified the fact that it is practically divided into three interrelated and complementary categories, namely social-, environmental-, and economic-oriented university in pursuit of actualizing SD. The paper recommends major reforms in the education sector including availing investment portfolios for R&D, renovation of education goals and transforming universities for sustainability

Food allergy has been recognised by the World Health Organisation as a chronic disease that could lead to fatality. The symptoms can mediate from mild to severe consequences. Some cases have reported that food allergy sufferers are bullied and are discriminated at workplace, thus increasing their stress level, apart from facing difficulty in consuming certain food due to allergy. This has an adverse effect on the quality of life amongst food allergy sufferers. Medical bills are increased when food allergy sufferers become unknowingly exposed to food allergen. Hence, this study investigated food allergens among food allergy sufferers in order to make their lives better. A total of 250 respondents participated in an online survey. Surprisingly, apart from chicken, soybean and other food allergens that have been listed under the Big Eight Allergens, the respondents mentioned some fruits that could trigger allergic reactions, such as rambutans and watermelons. Food allergy sufferers can be allergic to seafood and seafood products as well, such as shrimp paste or locally known as belacan, which refers to fermented shrimp paste cured under the sun. It is a common food ingredient used among Malaysians. The study findings offer practical insights, such as avoidance of food allergens amidst food allergy sufferers and help the government to carefully manage for menu planning. The knowledge contribution of this study reveals several specific food and fruits, as aforementioned, which appear to be common and nutritious food, yet harmful to food allergy sufferers.

Accessing energy in the world is crucial nowadays. Energy is an essential factor to achieve other SDGs including SDG7. However, the determination and evaluation of the relationship between different energy scenarios to achieve SDG 7 and other SDGs have not done yet. This paper seeks to fill this gap by investigating how energy seniors can contribute to achieving SDG 7 and other SDGs. Web of Science, ScienceDirect and Scopus databases were utilized for conduction a systematic review. A total finial 25 from 249 papers were filtered from 2015 to December 2020 via inclusion and exclusion criteria. This review involves six seniors of energy which primary linked to achieving the SDG 7 and other SDGs: modern energy 20% (n = 5/25), energy access 16% (n = 4/20), energy efficiency 8% (n= 2/16), renewable energy 28% (n= 7/14), energy services 8% (n= 2/7), and miscellaneous energy 20% (n= 5/5). This systematic review explores the opportunities, constraints and limitations, recommendations, and new directions. The results show that different energy scenarios contribute to achieving mainly (SDG7) and other SDGs. The outcomes from this systematic review provide a sense of direction for future researchers for future studies in this domain.

Cissus populnea Guill. & Perr. (Vitaceae) is used in traditional medicine to treat microbial infec-tions, venereal diseases, and infertility, among others. The aim of the research is to isolate and characterize the antimicrobial constituent(s) from the stem of C. populnea. The n-butanol fraction of C. populnea being most active was subjected to silica gel column chromatography which led to the isolation of a white solid and white crystalline substances coded compounds C1 and C4C5, respectively. Spectral analysis (1D & 2D-NMR) of the isolated compounds and comparison with literature data indicated C1 to be Bis-(2-ethyloctyl)-phthalate and C4C5 to be a mixture of stig-masterol and β-sitosterol; C4C5 exhibited zone of inhibition ranging from 24 – 29 mm against the test organisms with Candida albicans being the most sensitive organism while Trichophyton rubrum was the least sensitive organism. The standard drugs, Ciprofloxacin had 27 – 37 mm while Flu-conazole and Fulcin exhibited zone of inhibition ranging from 34 mm and 29 – 32 mm, respec-tively. The MIC and MBC/MFC values for C4C5 ranges from 12.5 – 25.0 µg/cm3 and 25.0 – 50.0 µg/cm3 against MRSA, S. aureus, E. coli, C. albicans, T. rubrum, and T. mentagrophyte, respectively. In conclusion, three bioactive compounds were identified for the first time from the stem of C. populnea

This research suggests a multi-stakeholder framework to increase the use of fintech in Africa, which would help the continent boost its financial inclusion and reach its Sustainable Development Goals (SDGs). The study evaluates previous research and frameworks that have been created to aid in the adoption of fintech by several stakeholders in developing nations, some of which have been tested in African nations with limited success. To begin with, the study suggests the use of the World Bank’s Maximising Finance for Development (MFD) approach through the prioritization of national ownership, creation of an enabling environment for private sector investment, partnering with multilateral development banks and other stakeholders, fostering innovation and digital literacy, and focusing on cost-effective, non-government guaranteed financing. In the same vein, in line with the G20’s High-Level Principles for Digital Financial Inclusion, the adoption of financial technologies and digital financial services in Africa can be promoted through the creation of a country-specific strategy. Each government can create a regulatory environment that encourages innovation and competition, improve its digital infrastructure, increase its digital literacy and awareness, and collaborate with private sector stakeholders to expand financial inclusion. Furthermore, The Better Than Cash Alliance’s strategy to increase fintech adoption can also be implemented through partnership with businesses, international organizations, and other nations. By joining the Alliance, countries can enact rules and regulations that facilitate fintech adoption, promote awareness and education, and design and execute national digital payment infrastructure with the help of fintech companies. Finally, the mSTAR initiative suggests collaborating with USAID, in order to provide support to underrepresented populations, incorporate digital financial services, increase public-private collaboration, and educate and train policymakers, practitioners, and technologists. By implementing these strategies, African nations can accelerate the adoption of fintech solutions and increase financial inclusion.

The aim of this research work was to provide model for predicting stock volatility in Nigeria Stock market. To achieve this, monthly data for Nigerian stock exchange, Exchange rate, Share index and inflation rate was collected for a period of January 1990 to December 2016.The descriptive statistics revealed these variables to exhibit volatility as a characteristics of financial time –varying series. DCC Model was fitted, were the coefficients for all the parameters and that of the correlation-Targeting (rho_21) are both negative and positive and tend very close to 1 and -1, indicating that high persistence in the conditional variances. The Model DCC, satisfied the properties of a good model of conditional mean and variance of the confidential Interval (C.I) of 1 and -1, that is, the conditional variances are finites and their series are strictly stationary. This therefore implies that the Nigerian Stock Exchange, Exchange rate, share index and Inflation rate will experience a non-steady shock in the Stock market. However Each of these variables have different length of recovery (volatility half- life) ranging from 1.5month, 6.5months, 6months to 2,4months for stock exchange, exchange rate, share index and inflation rate respectively. By implication, the volatility of these variables had a long memory, persistence and mean-reverting.

Despite the fact that COVID-19 is no longer a global pandemic due to development and integration of different technologies for the diagnosis and treatment of the disease. Technological advancement in the field of molecular biology, electronics, computer science, artificial intelligence, Internet of Things, nanotechnology etc. has led to the development of molecular approaches and computer aided diagnosis for the detection of COVID-19. This study provides a holistic approach on COVID-19 detection based on (1) molecular diagnosis which include RT-PCR, antigen-antibody and CRISPR-based biosensors and (2) computer aided detection based on AI-driven models which include Deep Learning and Transfer learning approach. The review also provide comparison between these 2 emerging technologies and open research issues for the development of smart-IoMT-enable platform for the detection of COVID-19.

Background/Aims: Screening for gestational diabetes mellitus (GDM) are currently done at 24 - 28 weeks of conception, missing out on the most vulnerable period of organogenesis and thus preventing clinicians from starting treatments until the late second or third trimester. MicroRNAs (miR) are small non-coding RNA molecules that could aid in detecting or predicting GDM through establishing a novel non-invasive prenatal testing (NIPT) tool. The objective of this study was to summarize the most recent updates on plasma microRNAs as GDM diagnostic biomarkers. Methods: Between April and June 2021, a PubMed literature search was undertaken to review recent articles on human plasma miR associated with GDM. Animal studies and papers that are written in languages other than English were excluded. Only plasma miRNAs were used to avoid coagulation biases. Results: A total of 31 miRNAs were found significantly upregulated in the plasma samples of patients with GDM. It was found mainly during the 2nd or 3rd trimester except for miR-223 and miR-23a that were upregulated at 9 – 11 weeks of gestation. Conclusion: Though extensive prospective cohort studies are required, miR-223 and miR-23a should be considered the most promising to develop a successful NIPT tool because they were found to be upregulated earliest, during the first trimester.

Sinulariolide, a natural product extracted from cultured-type soft coral Sinularia flexibilis, possesses bioactivity against the movement of several types of cancer cell. However, the molecular pathway of its effects on human bladder cancer remain poorly understood. Using a human bladder cancer cell line as an in vitro model, this study investigated the underlying mechanism of sinulariolide against cell migration/invasion in TSGH-8301 cells. We found that sinulariolide inhibited TSGH-8301 cell migration/invasion, and the effect was concentration-dependent. Furthermore, the protein expressions of matrix metalloproteinases (MMPs) MMP-2 and MMP-9, as well as urokinase, were significantly decreased after 24-h sinulariolide treatment. Meanwhile, the increased expressions of tissue inhibitors of metalloproteinases (TIMPs) TIMP-1 and TIMP-2 were in parallel with an increased concentration of sinulariolide. Finally, the expressions of several key phosphorylated proteins in the mTOR signaling pathway were also downregulated by sinulariolide treatment. Our results demonstrated that sinulariolide has significant effects against TSGH-8301 cell migration/invasion, and its effects were associated with decreased levels of MMP-2/-9 and urokinase expression, as well as increased TIMP-1/TIMP-2 expression. The inhibitory effects were mediated by reducing phosphorylation proteins of the PI3K, AKT and mTOR signaling pathway. The findings suggested that sinulariolide is a good candidate for advanced investigation with the aim of developing a new drug for the treatment of human bladder cancer.

Neurological disorders, such as amyotrophic lateral sclerosis, Parkinson’s disease, and Alzheimer’s disease, are commonly associated with persistent neuro-inflammation, and there is an urgent need to discover new therapeutic agents that may target the various pathways involved in neurodegeneration. In this study, we investigated the therapeutic potential of folecitin, a flavonoid isolated from Hypericum oblongifolium, against lipopolysaccharide (LPS)-induced oxidative stress associated with neurodegeneration, amyloidogenic Aβ production pathway, and memory dysfunction in mice. LPS was administered i.p. at 250 µg/kg/day for 3 weeks, followed by the administration of folecitin at a dose of 30 mg/kg/day for the last two weeks. A Western blot technique was used to assess the expression of different proteins involved in oxidative stress, neurodegeneration, and neuronal synapse. Results indicated that folecitin significantly reduced LPS-induced apoptotic neurodegeneration, including the expression of BAX, Caspase-3, and PARP-1 proteins, inhibited BACE1, and the amyloidogenic Aβ production pathway. Folecitin improved both pre- and post-neuronal synapse, as well as memory dysfunction. Furthermore, folecitin significantly activated endogenous antioxidant proteins such as Nrf-2 and HO-1 via stimulating the phosphorylation of Akt proteins. These findings suggest that folecitin may be a suitable lead to design new drugs for neurotoxin-triggered neurodegenerative disorders.

Family Phyllanthaceae is one of the largest segregates of the eudicot order Malpighiales and its species are herb, shrub, and tree, which are mostly distributed in tropical regions. Certain taxonomic discrepancies exist at genus and family level. Here, we report chloroplast genomes of three Phyllanthaceae species—Phyllanthus emblica, Flueggea virosa, and Leptopus cordifolius— and compare them with six others previously reported Phyllanthaceae chloroplast genomes. The species of Phyllanthaceae displayed quadripartite structure, comprising inverted repeat regions (IRa and IRb) that separate large single copy (LSC) and small single copy (SSC) regions. The length of complete chloroplast genome ranged from 154,707 bp to 161,093 bp; LSC from 83,627 bp to 89,932 bp; IRs from 23,921 bp to 27,128 bp; and SSC from 17,424 bp to 19,441 bp. Chloroplast genomes contained 111 to 112 unique genes, including 77 to 78 protein-coding, 30 transfer RNA (tRNA), and 4 ribosomal RNA (rRNA) that showed similarities in arrangement. The number of protein-coding genes varied due to deletion/pseudogenization of rps16 genes in Baccaurea ramiflora and Leptopus cordifolius. High variability was seen in number of oligonucleotide repeats while analysis of guanine-cytosine (GC) content, codon usage, amino acid frequency, simple sequence repeats analysis, synonymous and non-synonymous substitutions, and transition and transversion substitutions showed similarities in all Phyllanthaceae species. We detected a higher number of transition substitutions in the coding sequences than non-coding sequences. Moreover, the high number of transition substitutions was determined among the distantly related species in comparison to closely related species. Phylogenetic analysis shows the polyphyletic nature of the genus Phyllanthus which requires further verification. We also determined suitable polymorphic coding genes, including rpl22, ycf1, matK, ndhF, and rps15 which may be helpful for the reconstruction of the high-resolution phylogenetic tree of the family Phyllanthaceae using a large number of species in the future. Overall, the current study provides insight into chloroplast genome evolution in Phyllanthaceae.

In this paper, we report orthogonal fuzzy versions of some celebrated iterative mappings. We provide various concrete conditions on the real valued functions J,S:(0,1]→(−∞,∞) for the existence of fixed-points of (J,S)-fuzzy iterative mappings. We obtain many fixed point theorems in orthogonal fuzzy metric spaces. We apply (J,S)-fuzzy version of Banach fixed point theorem to show the existence and uniqueness of the solution. We support these results with several non-trivial examples and applications to Volterra-type integral equations and fractional differential equations.

"The wisdom of crowd'' is so often observed in social discourses and activities around us. The manifestations of it are, however, so intrinsically embedded and behaviorally accepted that an elaboration of a social phenomenon evidencing such wisdom is often cheered as a discovery; or at least an astonishing fact. One such scenario is explored here, namely conceptualization and modeling of a food safety system, a system directly related to social cognition. Food safety is an area of concern these days. Models representing the food safety systems are recently published to study the effect of interactions between important entities of the system. For example, Knowles’s model finds conditions leading to a more efficient and dependable system of entities like consumers, regulators and stores with specific focus on regulators behavior and their impact on the food safety. The first contribution of this paper is reevaluation of Knowles’s model towards a more conscious understanding of ``the wisdom of crowd'' effects on inspection and consuming behaviors. The second contribution is augmenting of the model with social networking capabilities, which acts as a medium to spread information about stores and help consumers find stores which are not contaminated. Simulation results reveal that stores’ respecting social cognition improve effectiveness of the food safety system for consumers and stores both. Simulation findings also reveals that an active society has a capability to self-organize effectively even in the absence of any regulatory compulsion.

This bibliometric analysis delves into the realm of botanical gardens through the process of mapping literature and discerning research frontiers, underlying themes, and interconnections within the extant body of knowledge. The study uses a dataset of 1340 publications and employs methodologies such as authors' keywords co-occurrence data to examine the discipline's trends, patterns, and knowledge gaps. The study finds significant growth in literature from 1960 to 2023, emphasizing botanical gardens, conservation, taxonomy, biodiversity, ex-situ conservation, and diversity. Key influencers such as Sanja Kovačić, Elaissi, and Chemli have steered research directions towards ex-situ conservation and essential oils, reflecting the field's interdisciplinary nature. The study shows global institutional variation, with entities like the Chinese Academy of Sciences, the Royal Botanic Gardens UK, and the New York Botanical Garden US leading the discourse. Thematic analyses have identified core themes and emerging research topics, with ecological restoration, essential oils, invasive species, and climate change mirroring the field's expanding scope. The consistent prevalence of themes such as 'botanical gardens' and 'conservation' over time underscores their enduring significance. Emerging topics like climate change and biodiversity are gaining prominence, signaling a shift in research priorities. The expanding array of subjects, including 'invasive species' and 'genetic diversity,' indicates an amplified scope and growing complexity in botanical garden research. This study aims to bridge a crucial gap by outlining the developmental trajectory of botanical gardens and offering guidance for future research directions. Diverse research domains within botanical garden studies, including biodiversity, essential oils, taxonomy, and ex-situ conservation, present extensive avenues for exploration. Future research endeavors should delve into these impactful themes to better understand botanical ecosystems and their conservation. The study emphasizes the importance of nurturing interdisciplinary collaborations and multidisciplinary projects, advocating for a comprehensive and collaborative approach to future research in botanical garden studies.

Cellular biomolecular condensates termed ribonucleoprotein (RNP) granules often are enriched in messenger RNA (mRNA) molecules relative to the surrounding cytoplasm. Yet, the spatial localization and diffusion of mRNAs in close proximity to phase separated RNP granules is not well understood. In this study, we performed single molecule fluorescence imaging experiments of mRNAs in live cells in the presence of two types of RNP granules, stress granules (SG) and processing bodies (PB), which are distinct in their molecular composition and function. We developed a photobleaching- and noise-corrected colocalization imaging algorithm that was employed to determine the accurate positions of individual mRNAs relative to the granule’s boundaries. We found that mRNAs are often localized at granule boundaries, an observation consistent with recently published data. We suggest that mRNA molecules become spontaneously confined at the RNP granule boundary similar to the adsorption of polymer molecules at liquid-liquid interfaces, which is observed in various technological and biological processes. We also suggest that this confinement could be due to a combination of intermolecular interactions associated with, first, the screening of a portion of the RNP granule interface by the polymer and, second, electrostatic interactions due to a strong electric field induced by a Donnan potential generated across the thin interface.

The integration of sign language recognition systems into digital platforms has the potential to bridge communication gaps between the deaf community and the broader population. This paper introduces an advanced Israeli Sign Language (ISL) recognition system designed to interpret dynamic motion gestures, addressing a critical need for more sophisticated and fluid communication tools. Unlike conventional systems that focus solely on static signs, our approach incorporates both Deep Learning and Computer Vision techniques to analyze and translate dynamic gestures captured in real-time video. We provide a comprehensive account of our preprocessing pipeline, detailing every stage from video collection to the extraction of landmarks using MediaPipe, including the mathematical equations used for preprocessing these landmarks and the final recognition process. The dataset utilized for training our model is unique in its comprehensiveness and is publicly accessible, enhancing the reproducibility and expansion of future research. The deployment of our model on a publicly accessible website allows users to engage with ISL interactively, facilitating both learning and practice. We discuss the development process, the challenges overcome, and the anticipated societal impact of our system in promoting greater inclusivity and understanding.

The current revolution in communication and information technology is facilitating the Internet of Things (IoT) infrastructure. Wireless Sensor Networks (WSN) are a broad category of IoT applications. However, power management in WSN poses a significant challenge when the WSN is required to operate for a long duration without the presence of a consistent power source. In this paper, we develop a batteryless, ultra-low-power Wireless Sensor Transmission Unit (WSTx) depending on the solar-energy harvester and LoRa technology. We investigate the feasibility of harvesting ambient indoor light using polycrystalline photovoltaic (PV) cells with a maximum power of 1.4mW. The study provides comprehensive power management design details and a description of the anticipated challenges. The power consumption of the developed WSTx was 21.09µW during the sleep mode and 11.1mW during the operation mode. The harvesting system can harvest energy up to 1.2mW per second, where the harvested energy can power the WSTx for six hours with a maximum power efficiency of 85.714%.

Glioblastoma multiforme (GBM) is the most frequent and aggressive primary brain tumor. GBM is formed by a very heterogeneous astrocyte population, neurons, neovascularization and infiltrating myeloid cells (microglia and monocyte derived macrophages). The IQGAP1 scaffold protein interacts with components of the cytoskeleton, cell adhesion molecules, and several signaling molecules to regulate cell morphology and motility, cell cycle and other cellular functions. IQGAP1 overexpression and delocalization has been observed in several tumors, suggesting a role for this protein in cell proliferation, transformation and invasion. IQGAP1 has been identified as a marker of amplifying cancer cells in GBMs. To determine the involvement of IQGAP1 in the onco-biology of GBM, we performed immunohistochemical confocal microscopic analysis of the IQGAP1 protein in human GBM tissue samples using cell type-specific markers. IQGAP1 immunostaining and subcellular localization was heterogeneous; the protein was located in the plasma membrane and, at variable levels, in nucleus and/or cytosol. Moreover, IQGAP1 positive staining was found in podosome/invadopodia-like structures. IQGAP1⁺ staining was observed in neurons (Map2⁺ cells), in cancer stem cells (CSC; nestin⁺) and in several macrophages (CD31⁺ or Iba1⁺). Our results indicate that the IQGAP1 protein is involved in normal cell physiology as well as oncologic processes.

COVID-19 outbreak started in the Chinese city of Wuhan and spread around the globe in months due to its high contagious level. Hence, this disease posed a great challenge to researchers and mathematicians. Numerous mathematical models have been suggested to visualize the spreading speed and trends of this pandemic. In this paper, a comparison of a widely established and accepted method, the Susceptible-Exposed-Infected-Quarantined-Recovered-Death-Insusceptible (SEIQRDP) model with a newly-proposed fractional-order SEIQRDP is studied. Densely populated Countries of Asia (Pakistan, India, and Bangladesh) have been chosen as data sets and both algorithms have been applied to their data. The same comparison technique has also been used on the data of two polar countries, New Zealand and Russia, that validated our findings. Error comparison of both algorithms has been recorded in a tabulated form which shows multi-fold erroneous trends over WHO data of selected countries.

Post-harvest handling and ripening techniques have an impact on peach quality and shelf life, which has a big impact on consumer satisfaction and market competitiveness. This review paper examines recent advancements in ripening techniques and post-harvest technologies with the goal of improving peach fruit quality and sustainability. The factors impacting fruit quality after harvest and the physiological changes that occur throughout peach ripening are fully explained. For maintaining peach freshness and reducing losses, novel handling methods like modified atmosphere packaging (MAP) and controlled atmosphere storage (CAS) have been investigated. The study explores the possibilities of nanotechnology applications and low-temperature storage for prolonging shelf life while maintaining texture, flavor, and aroma. Examining the effectiveness and waste reduction potential of automation and mechanization in post-harvest activities. The paper also discusses ethylene-based and non-ethylene-based ripening agents, as well as innovative techniques including gene editing and RNAi technology for controlled and delayed ripening. Analyses are done on how these technologies affect the sensory qualities and nutrient profiles of peaches. The study emphasizes the significance of sustainable practices in the peach industry by focusing on waste reduction, resource efficiency, and circular economy integration. Post-harvest technologies' potential environmental consequences have been taken into consideration and the paper encourages more study and cooperation to increase sustainability.

The Kabul River basin (KRB) of Afghanistan, a lifeline of around 10 million people, has multiplicity of governance, management and development related challenges leading to inequity, inadequacy and unreliability of irrigation water distribution. Prior to any uplifting intervention, there is a need to evaluate the performance of irrigation system on long term basis to identify the existing bottlenecks. Although there are several indicators used for the performance evaluation of the irrigation schemes, but we used the coefficient of variation (CV) of actual evapotranspiration (ETa) in space (basin, sub-basin, and provincial level), relative evapotranspiration (RET) and temporal CV of RET to assess the equity, adequacy and reliability of water distribution respectively, from 2003 to 2013. The ETa was estimated through surface energy balance system (SEBS) algorithm and the ETa estimates were validated using advection aridity (AA) method with R2 value of 0.81 and 0.77 at Nawabad and Sultanpur stations respectively. The global land data assimilation system (GLDAS) and moderate-resolution imaging spectroradiometer (MODIS) products were used as main inputs to the SEBS. Results show that mean seasonal sub-based RET values during summer (May – September) (0.37 ± 0.06) and winter (October – April) (0.40 ± 0.08) are below the target values (RET ≥0.75) during 2003-2013. The CV of mean ETa within sub-basins and provinces for the entire study period has equitable distribution of water from October-January (0.09±0.04) whereas the highest inequity (0.24±0.08) in water distribution is during early summer. The range of the CV of mean ETa (0.04-0.06) on monthly and seasonal basis shows the unreliability of water supplies in several provinces or sub-basins. The analysis of temporal CV of mean RET highlights unreliable water supplies across the entire basin. The maximum ETa during the study period was estimated for Shamal sub-basin (552±43mm) while among provinces Kunar experienced the highest ETa (544±39mm). This study highlights the dire need for interventions to improve the irrigation performance in time and space. The proposed methodology can be used as a framework for monitoring and implementing the water distribution plans in future.

Escherichia coli is a gram-negative commensal bacterium living in human and animal intestines. Its pathogenic strains are cause of high morbidity which can adversely affect people by causing urinary tract infections, food poisoning, septic shock, or meningitis. Humans can contract E. coli by eating contaminated food—such as raw or undercooked raw milk, meat products, and fresh produce sold in open markets—as well as by coming into contact with contaminated settings like wastewater, municipal water, soil, and faeces. Some pathogenic strains of E. coli have been identified in Nigeria such as enterohemorrhagic (EHEC), as well as enterotoxigenic (ETEC), enteropathogenic (EPEC), enteroinvasive (EIEC), enteroaggregative (EAEC), and verotoxigenic (VTEC). This causes acute watery or bloody diarrhoea, stomach cramps, and vomiting. Apart from the virulence profile of E. coli, antibiotic resistance mechanisms such as the presence of blaCTX-M found in humans, animals and environmental isolates which are of great importance and require surveillance and monitoring for emerging threats in resource-limited countries. This review is aimed at understanding the underlying mechanisms of evolution and antibiotic resistance in E. coli in Nigeria and highlighting the use of improving One Health approaches to combat the problem of emerging infectious diseases.

Tuberculosis (TB) disease still remain a major global threat due to the growing number of drug-resistant species and global warming. Despite the fact that there are new molecular diagnostic approaches, however, majority of developing countries and remote clinics depends on conventional approaches such as Tuberculin test, microscopic examinations and radiographic imaging (Chest X-ray). These techniques are hindered by several challenges which can lead to miss-diagnosis especially when interpreting large number of sample cases. Thus, in order to reduce workload and prevent miss-diagnosis, scientists incorporated computer-aided technology for detection of medical images known as Computer aided Detection (CADe) or Diagnosis (CADx). The use of AI-powered techniques has shown to improve accuracy, sensitivity, specificity. In this review, we discussed about the epidemiology, pathology, diagnosis and treatment of tuberculosis. The review also provides background information on Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Transfer Learning (TL) and their applications in detection of tuberculosis from both microscopic slide images and X-ray images. The review also proposed an IoT/AI powered system which allows transfer of results obtained from DL models with end users through internet networks. The concept of futuristic diagnosis, limitations of current techniques and open research issues are also discussed.

Ovarian lymphoma is an infrequent disease, accounting for less than 1% of all non-Hodgkin lymphoma diagnosis. Symptoms include abnormal vaginal bleeding or discharge, abdominal pain, and urinary obstruction due to the large mass. In our case, a 60-year-old woman, underwent a total abdominal hysterectomy and bilateral salpingo-oophorectomy, as she presented with low-grade follicular lymphoma (FL) in both the ovaries, and the left ovary was observed to be enlarged. The tumor is categorized as lymphoma based upon immunohistochemical markers. Computed tomography (CT) scan of the chest, abdomen, and pelvis and bone marrow biopsy are important for the staging of primary lymphoma of the ovary. The first-line chemotherapy regimen includes rituximab, cyclophosphamide, doxorubicin hydrochloride (hydroxydaunorubicin), vincristine sulfate (Oncovin), and prednisone (R-CHOP) for rapidly proliferative non-Hodgkin lymphoma (NHL). Lymphomas with slower growth patterns can be treated with Bendamustine-Rituximab and don’t need aggressive R-CHOP treatment.

We report on a 2D-gap surface plasmon metasurface based composed of a bottom metal layer, middle insulator layer, and top metal nanostructure of gold nanoblocks (nanoantennas). The proposed structure enables us to generate simultaneous multi plasmonic resonances and offers the possibility to tune them, within the near-infrared domain. The simplicity of the metasurface makes it promising for compact optical platforms based on reflection mode operation with potential application in multi-channel biosensors, second-harmonic generation, and multi-wavelength surface-enhanced spectroscopy among other interesting fields

The purpose of this research is to present a thorough evaluation of the energy management system, which consists of hybrid energy storage systems, and its control algorithms, which may be used in electric vehicles. This paper outlines the characteristics of electric vehicles, research methods, analysis of the hybrid energy storage system architecture, converter topology, and energy management techniques. The strength and co-occurrence of keywords over the past ten years are shown in this study using a systematic research framework for performing a literature review and using keyword analysis techniques. The study reveals a pattern of recently and frequently used terms in works of literature. Consequently, their suitability, benefits, and drawbacks are assessed. In this study, the hybrid energy storage system and converter circuit architecture are evaluated and rated. Non-isolate DC-DC converter converter connected to SC is a suitable configuration for the hybrid converter because it is simple to build, reliable, and has minimal loss/weight/cost, which improves vehicle performance. In terms of the application of control strategies, it is shown that deterministic and fuzzy rule-based control techniques are successfully assessed using real-scale vehicle experiments and selected for manufacturing. On the other hand, real-time optimization-based energy management techniques have been effectively shown in lab-scale tests and may be used in a future real-scale vehicle.

Membrane transporters (MTs) are mainly localized at the plasma membrane (PM), tonoplast and vacuolar membrane (VM) of cells in all plant organs. Their work is to maintain the cellular homeostasis by controlling ionic movements across PM channels from roots to upper plant parts, xylem loading and remobilization of sugar molecules from photosynthesis tissues in the leaf (source) to roots, stem and seeds (sink) via phloem loading. The plant’s whole source-to-sink relationship is regulated by multiple transporting proteins in a highly sophisticated manner and driven based on different stages of plant growth and development (PG&D), and environmental changes. The MTs play a pivotal role in PG&D in terms of increased plant height, branches/tiller numbers, enhanced numbers, length and filled panicles per plant, seed yield and grain quality. Dynamic climatic changes disturbed the ionic balance (salt, drought and heavy metals) and sugar supply (cold and heat stress). Due to poor selectivity, some of the MTs also uptake toxic elements in the roots that negatively impact on PG&D, later on also exported to upper parts and then deteriorate the grain quality. As an adaptive strategy, in response to salt and HMs plants activated PM and VM localized MTs that export toxic elements into vacuole, and also translocate in the root’s tips and shoot. However, in case of drought, cold and heat stresses, MTs increased the water and sugar supply to all organs. In this review, we mainly reviewed recent literature from Arabidopsis, halophytes, and major field crops such as rice, wheat, maize and oilseed rape to argue on the global role of MTs in PG&D and abiotic stress tolerance. We also discussed the gene expression level changes and genomic variations within a species as well as within a family in response to developmental and environmental cues.

Introduction Color vision deficiency (CVD) constitutes one of the frequently observed eye disorders in all human populations. Color is a prominent sign utilized in the medical profession to study and identify histopathological specimens, lab instruments, and patient examination. Color deficiency affects the medical skills of students resulting in poor clinical examination and color appreciation. There is no effective screening of CVD at any level of the medical profession. Hence, this study was aimed to determine the prevalence of CVD among medical students. Materials and methods This was a cross-sectional study conducted from September 2019 to February 2020 over a period of six months in Karachi, Pakistan. All medical students aged 18-21 years of either gender enrolled in the first and second years of medical college were included in this study. The examination was performed during daylight. Ishihara plates were placed at a distance of 75 cm from the subject and tilted so that the plane of the paper lies perpendicular to the line of vision. Students were given five seconds to read the plate and one examiner was instructed to mark the checklist. A score of less than 12 out of 14 red/green test plates (not including the demonstration plate) was considered as a CVD. All statistical analysis was performed using Statistical Package for Social Sciences version 20.0 (Armonk, NY: IBM Corp). Results The mean age of the medical students was 19.61± 1.22 years. There were (n=123) 53.0% females and (n=111) 47.0% males. Most of the medical students (n=131, 56.0%) belonged to the upper-middle-class socioeconomic group. CVD was observed in (n=13) 6.0%of medical students. Age (p=0.001) and socioeconomic status (p=0.001) were the only demographic factors significantly associated with color deficiency. Conclusions Color deficiency, although an unnoticed concern, is fairly common among medical students. Medical students must be screened for CVD as this will enable them to be aware of their limitations in their future observational skills as a doctor and devise ways of overcoming them in clinical practice.

Contamination of the environment with nano- and microplastic particles exerts a threatened impact on the aquatic ecosystems and sustainable catfish aquaculture. The presence of nanoplastics has been found to have a detrimental impact on both aquatic and terrestrial ecosystems. The present study examines the effect of polystyrene nanoplastics on DNA, erythrocytes, oxidative status and renal of catfish in addition to the potential protective effects of Chlorella vulgaris bioremeditation and selenium to hinder this effect. Six equal groups of fish were used as follows: Group 1: served as a control group and received water free from PS NPs; Group 2: was exposed to PS NPs at a concentration of 5mg/L; Group 3: was exposed to PS NPs (5mg/L) + selenium (1mg/kg diet); Group 4: was exposed to PS NPs (5mg/L) + C. vulgaris (25g/kg diet); Group 5: was supplemented with C. vulgaris (25g/kg diet); and Group 6: was supplemented with selenium (1mg/kg diet). The results indicated that PS NPs induced oxidative stress by significantly elevating MDA activities and slightly reducing antioxidant biomarkers, resulting in DNA damage, increased frequency of micronuclei, erythrocyte alterations, and numerous histopathological alterations in kidney tissue. Selenium and C. vulgaris significantly ameliorated the oxidative/antioxidant status, reduced DNA damage, micronucleus frequency, erythrocyte alterations, and morphology of kidney tissue. Nevertheless, further research is needed to evaluate in detail the mechanism behind the toxicity with nano-microplatics in aquatic system.

Type 2 Diabetes (T2D) is a growing global health problem that requires new and effective prevention and management strategies. Recent research has highlighted the role of epigenetic changes in the development and progression of T2D, and the potential of functional foods as complementary therapy for the disease. This review aims to provide an overview of the current state of knowledge on the preventive epigenetic mechanisms of functional foods in T2D. We provide background information on T2D and its current treatment approaches, an explanation of the concept of epigenetics, and an overview of the different functional foods with demonstrated preventive epigenetic effects in T2D. We also discuss the epigenetic mechanisms by which these functional foods prevent or manage T2D and the studies that have investigated their preventive epigenetic effects. In addition, we revisit works on the beneficial influence of functional foods against the programming and complications of parentally-triggered offspring diabetes. We also postulate, albeit based on the scarce data, that epigenetic inheritance mechanistically mediates the impacts of functional nutrition against the metabolic risk of diabetes in the offspring. Finally, our review highlights the importance of considering the preventive epigenetic mechanisms of functional foods as a potential avenue for the development of new prevention and management strategies for T2D.

The work carried out first-principles calculations within the framework of density functional theory to study the structural stability of the CsSnI₃ compound and the influence of phase transitions on their electronic and optical properties. Using the GGA and SCAN functionals, the relaxed structures of the CsSnI₃ phases were obtained and their geometric characteristics were assessed. Using the Phonopy code based on VASP, calculations of phonon and thermodynamic properties were performed, and the temperatures of phase transitions of CsSnI₃ were determined. The temperature dependences of the thermodynamic parameters α-, β-, γ- and δ-phases of CsSnI₃ were analyzed. The trends in free energy, entropy, enthalpy, heat of formation energy and heat capacity were justified in terms of the pattern of changes in the total energy of the four phases of CsSnI₃ from VASP calculations. It is shown that at 0 K the non-perovskite structure of the CsSnI₃ compound (δ-CsSnI₃) is the most stable (followed by γ-CsSnI₃), and the tetragonal phase (β) is quite unstable, having the highest energy among the perovskite phases. It was revealed that at temperatures above 450 K the tetragonal phase becomes stable, and when the temperature drops, it transforms into the cubic phase (α-CsSnI₃). The phase transition between the β and γ phase of perovskite occurs in the range of 300-320 K, and at 320 K a black-yellow transformation of CsSnI₃ occurs in which the cubic phase (black perovskite) undergoes a phase transition to a non-perovskite conformation (yellow phase). The presence of temperature phase transitions between two orthorhombic phases of CsSnI₃ at 360 K was discovered, although direct transitions of the α⟷γ and γ⟷δ types have not yet been reported in any experiment, except for γ→δ transitions under the influence of moisture. Based on well-relaxed structures (from the SCAN calculations), the band gap widths for four CsSnI₃ phases were calculated and compared with experimental measurements. Electronic properties and Fermi level shifts as a result of phase transformations of CsSnI₃ were assessed using the HSE06 functional and machine learning prediction. The values of the complex dielectric constant and the refractive index of all phases of the CsSnI₃ were determined.

Photosynthesis is a pivotal process that determines the synthesis of carbohydrates required for sustaining growth under normal or stress situation. Stress exposure reduces the photosynthetic potential owing to the excess synthesis of reactive oxygen species that disturb the proper functioning of photosynthetic apparatus. This decreased photosynthesis is associated with disturbances in carbohydrate metabolism resulting in reduced growth under stress. We evaluated the importance of melatonin in reducing heat stress-induced severity in wheat plants (Triticum aestivum L.). The plants were subjected to 25 ˚C (optimum temperature) or 40 ˚C (heat stress) for 15 days at 6 hours time duration and then developed the plants for 30 days. Heat stress led to oxidative stress with increased production of TBARS and H2O2 content and reduced accrual of total soluble sugars, starch and carbohydrate metabolism enzymes which are reflected in reduced photosynthesis. Application of melatonin not only reduced oxidative stress through lowering TBARS and H2O2 content, through augmenting the activity of antioxidative enzymes but also increased the photosynthesis in plant and carbohydrate metabolism that is needed to provide energy and carbon skeleton to the developing plant under stress. However, the increase in these parameters with melatonin was mediated via hydrogen sulfide (H2S), as the inhibition of H2S by hypotaurine (HT; H2S inhibitor) reversed the ameliorative effect of melatonin. This suggests a crosstalk of melatonin and H2S in protecting heat stress-induced photosynthetic inhibition via regulation of carbohydrate metabolism.

Researchers are always looking to find ways to use energy more efficiently while keeping people comfortable at home. They've tried different methods like fuzzy logic and genetic algorithms to do this. In this paper, we introduce a novel model that combines different techniques like data smoothing, optimization, machine learning, and control algorithms to reach this goal in smart homes. The proposed model is made up of three main parts: smoothing, optimization, and control. The smoothing part uses the Kalman filter to get rid of any unnecessary noise and make sure the data used to predict energy use is clean and smooth. The optimization part uses both genetic with firefly algorithms and artificial neural networks to minimize the gap between the actual environmental conditions and the conditions users find comfortable. It adjusts the comfort settings in real-time using machine learning. The control part uses Mamdani fuzzy logic to make sure energy is delivered in the best way possible to the systems that control temperature, lighting, etc., making the home comfortable and saving energy at the same time. Comparative analyses demonstrate the superiority of the proposed model over existing algorithms, including the Particle Swarm Optimization (PSO) algorithm. Additionally, the paper discusses the importance of adaptive controllers in addressing issues associated with incorrect PID controller selection and highlights the benefits of using the FA-GA in energy optimization and comfort improvement. Overall, the proposed model offers an effective solution for efficient energy consumption optimization and enhanced user comfort in diverse settings through the integration of advanced algorithms and optimization modules.

This study addressed the need for efficient data collection in micro-mobility using low-end hardware, focusing on developing a system capable of handling large real-time data streams. We proposed a novel data collection system that leverages incremental learning techniques, enabling AI-based services for micro-mobility passengers through smartphones. Our approach utilizes 3-axis acceleration sensors integrated into micro-mobility devices, collecting motion data in real-time. This data is processed through an incremental learning pre-processing server, employing the Broad Learning System algorithm, to ensure robust performance in noisy, real-world environments. The use of incremental learning is pivotal, allowing our system to adapt continuously to new data, enhancing the accuracy and relevance of the AI services provided to passengers. This research not only advances the technical capabilities in micro-mobility data handling but also has the potential to enhance the overall passenger experience through improved AI-based services.

Despite decades of conflict and political instability, drought has also severely affected Afghanistan’s rural population and agriculture sector. Agriculture is a primary livelihood source in the country, and recurring droughts have put cascading pressures on the agricultural economy and food security. Therefore, understanding the key drivers of all risk components through a comprehensive risk assessment is critical for proactive drought risk management. This study assesses agricultural drought risk from an integrated perspective, emphasizing the combined effects of drought hazard, exposure, and vulnerability. Multi-methods research was conducted, employing remote-sensing-based analysis covering a period from 2001 to 2023. We used the Vegetation Condition Index (VCI) to analyze the drought hazard for the agricultural system during the winter growing season. The vulnerability indicators and exposure levels of the agricultural system were determined through spatial analysis combined with a literature review and expert consultation. An adapted conceptual framework of the Intergovernmental Panel on Climate Change (IPCC) was utilized, which incorporates hazard, exposure, and vulnerability to define risk. The results revealed that droughts occur frequently and in changing patterns throughout the country. All provinces have experienced drought over the past two decades, albeit with varying severities and frequencies. Severe droughts were observed in 2001-2002, 2008, 2011, 2018, and consecutively in 2021-2022-2023. Drought vulnerability and exposure vary widely across the country, particularly in the northern, western, and southern provinces. The final calculated risk shows that most provinces in southern and southwestern zones face a high risk of recurrent droughts, further exacerbating agricultural challenges in these regions. Such analyses under a multimethod approach provide information on spatial patterns of drought risk and drivers of agricultural systems that can support decision-makers and policymakers in formulating strategies to reduce drought risk and adapt to the agricultural sector.

Plastics have become an important environmental concern due to their durability and resistance to degradation. Out of all plastic materials, polyesters such as polyethylene terephthalate (PET) are amenable to biological degradation due to the action of microbial polyester hydrolases. The hydrolysis products obtained from PET can thereby be used for the synthesis of novel PET as well as becoming a potential carbon source for microorganisms. In addition, microorganisms and biomass can be used for the synthesis of the constituent monomers of PET from renewable sources. The combination of both biodegradation and biosynthesis would enable a completely circular bio-PET economy beyond the conventional recycling processes. Circular strategies like this could contribute to significantly decrease the environmental impact of our dependence on this polymer. Here we review the efforts made towards turning PET into a viable feedstock for microbial transformations. We highlight current bottlenecks in the degradation of the polymer and the metabolism of the monomers and we showcase fully biological or semisynthetic processes leading to the synthesis of PET from sustainable substrates.

The videofluorographic study is indicated for diseases potentially causing dysphagia and aspiration, such as gastrointestinal reflux disease, cancers of the oropharynx and esophagus, and certain neurologic diseases needing swallowing assessment. The study is designed to survey the anatomy and physiology of swallowing to diagnose any swallowing impairment and is standardized using scales such as the Modified Barium Swallow Impairment Profile (MBSImP). The procedure requires the patient to swallow a barium contrasted bolus which helps to visualize and obtain a real-time result. There are certain complications of the procedure including radiation exposure which requires necessary safety protocols to be followed.

The Vehicle Routing Problem (VRP) and its variants are found in many fields, especially logistics. In this study, we introduced an adaptive method to a complex VRP. It combines multi-objective optimization and several forms of VRPs with practical requirements for an urban shipment system. The optimizer needs to consider terrain and traffic conditions. The proposed model also considers customers' expectations, shipper considerations as goals, and the common goal like transportation cost. We offered compromise programming to approach the multi-objective problem by decomposing the original multi-objective problem into a minimized distance-based problem. We designed a hybrid version of the Genetic algorithm with the Local Search algorithm to solve the proposed problem. We evaluate the effectiveness of the proposed algorithm with the Tabu Search algorithm, the original Genetic algorithm on the tested dataset. The results show that our method is an effective decision-making tool for the multi-objective VRP and an effective solver for the new variation of VRP.

The advancements in social networking have empowered open expression on micro blogging platforms like Twitter. Traditional Twitter Sentiment Analysis (TSA) faced challenges due to rule-based or dictionary algorithms, dealing with feature selection, ambiguity, sparse data, and language variations. This study proposed a classification framework for Twitter sentiment data using word count vectorization and machine learning techniques to reduce the difficulties addressed on annotated sentiment-labelled tweets. Various classifiers (Naive Bayes, Decision Tree, K Nearest Neighbours, Logistic Regression, and Random Forest) were evaluated based on Accuracy, Precision, Recall, F1-score, and Specificity. Random Forest outperformed others with an Area under Curve (AUC) value of 0.96, and an Average Precision (AP) score of 0.96 in sentiment classification, especially effective with minimal Twitter-specific features.

In contemporary narratives, the rural and regional identities of a place, as judged by its inhabitants’ sense of belonging, continue to be important points that need to be (re)considered when discussing places as instruments for local development. This paper pushes forward these debated and explores the construction of rural and regional identity in Romania with the help of a case study that focuses on two rural communities situated on opposite sides of the river Mureș. Based on participant and ethnographic observation and making use of a qualitative analysis, this paper highlights the most significant features of the local cultural identities expressed by the two sets of people, which often coincide with the most important characteristics attributed to the regions separated by the river Mureș. The results of this study underline the dividing role of a river in the preservation of rural and regional identity. They also demonstrate that rural identity construction along the river has generated both rural development opportunities and various risks.

Nine components (C1-C9) were isolated from chloroform fraction of fractionated methanol extracts of Vernonia amygdalina leaves (FMEVA) by column chromatography. All the components C1 to C9 were purified and screened for hypoglycaemic activities in type-2 diabetic rats. The most potent hypoglycaemic component was elucidated on the basis of extensive spectroscopic (1D-, 2D-NMR, GC-MS, FTIR) data analysis. The Component C5 was found to be the most potent hypoglycaemic in reducing blood glucose by 12.55 ± 3.55% at 4 h post-oral administration, when compared to the positive (18.07 ± 1.20%) and negative (-1.99 ± 0.43%) controls. The spectroscopic data analysis reveals that the isolated compound has a structure consistent with 11β,13-dihydrovernolide. The isolated compound is part of the hypoglycaemic components present in V. amygdalina leaves that is responsible for the anti-diabetic activities. Further research is needed in the development of this compound or its derivatives for pharmaceutical use.

Purpose: Glue inhalation is a common unconventional substance of abuse and it contains neurotoxic and volatile solvents. We examined the toxicity profile and CNS activities of glue inhalation in Wistar rats.Methods: Acute toxicity was investigated using graded concentrations of 0.5, 1, and 2 mL of glue inhalation (n=3/group) for 4 hours in phase one followed by concentrations of 5, 10, and 20 mL of glue (n=1/group) for 4 hours in phase two. These animals were then observed for signs of toxicity and/or mortality for 24hours. The sub-acute toxicity was studied using 24 male Wistar rats at graded concentrations of Air, 2, 4 and 8mL glue (n=6/group) for 28 days. Blood samples were collected for biochemical and haematological evaluations, and vital organs (lung, liver, kidney, heart, brain, and eye) were used for histological analysis. Behavioural studies were carried out using Elevated Plus Maze, Hole Board Test, Open Field Test, Tail Suspension Test and Forced Swim Test. Dependence and abstinence effect were also evaluated. Results: The Lethal Dose (LD₅₀) of the inhalational glue was 14.14 ml. Glue significantly increased liver function parameters like TB, DB, ALP, ALT, TP, electrolyte levels (K⁺ and HCO₃) but reduced cholesterol level in exposed rats. Glue inhalation had significant anxiolytic and depressant effects on the rats at concentrations of 4mL and 8mL. Histological analysis revealed liver and lung tissue abnormalities and subconjunctival inflammation in eye tissue at 8mL. Conclusion: The study therefore suggests that glue inhalation has anxiolytic and depressant effects in Wistar rats.

Among various metal-based nanoparticles, silver nanoparticles (AgNPs) manifest superior inhibitory effect against several microorganisms. In fact, the AgNPs based therapy has been reported to inhibit both sensitive as well resistant isolates of bacteria and other disease causing microbes with equal propensity. Keeping this fact into consideration, we executed bio-mediated synthesis of AgNPs employing Hibiscus rosa sinensis flower extract. The as-synthesized AgNPs were evaluated for their potential to inhibit Streptococcus mutans (S. mutans), one of the main causative bacteria for dental caries. Beside several other reasons, orthodontic appliances have also been reported to facilitate infliction of oral cavity with a range of microbes including S. mutans. To determine the growth inhibitory and anti-adherence activity of AgNPs on orthodontic appliance, we performed microbiological assays employing AgNPs adsorbed on to the orthodontic wires. Topographic analysis of orthodontic wires was executed by scanning electron microscopy. In addition to antimicrobial and antibiofilm activity against oral S. mutans, the as-fabricated AgNPs demonstrated significant inhibitory and anti-biofilm properties against other biofilm forming bacteria such as Escherichia coli and Listeria monocytogenes as well.

This paper presents a symmetrical topology for the design of solid-state transformer, made up of power switching converters, to replace conventional bulky transformers. The proposed circuitry not only reduces the overall size but also provides power flow control with the ability to be interfaced with renewable energy resources (RESs) to fulfill the future grid requirements at consumer end. Solid state transformer provides bidirectional power flow with variable voltage and frequency operation and has the ability to maintain unity power factor, and current total harmonic distortion (THD) for any type of load within defined limits of IEEE standard. Solid State Transformer offers much smaller size as compared to that of the conventional iron core transformer. MATLAB/Simulink platform is adopted to test the validity of the proposed circuit for different scenarios by providing the simulation results evaluated at 25 kHz switching frequency.

The prevalence of diabetes mellitus (DM) continues to rise globally, posing significant health challenges and burdens. This metabolic disorder, characterized by elevated blood glucose levels, contributes to various complications including cardiovascular diseases, kidney failure, and stroke. While conventional diabetic drugs exist, they often come with adverse side effects, necessitating the exploration of safer and more cost-effective alternatives, particularly from natural sources like medicinal plants. This study investigates the potential of Neocarya macrophylla (Nm) Ethyl acetate leaf fraction in managing DM. Utilizing a high-fat diet/streptozotocin-induced diabetic rat model, the study explores several key aspects including effective dose determination, biological activity, impact on body mass index (BMI), and complete blood count. Statistical analysis was conducted using GraphPad Prism version 9.1. The determination of the minimum effective dose reveals that 120mg/kg of Ethyl acetate fraction of Nm reduced the blood glucose by 28.9% after 4 hours. In addition, ethyl acetate fraction (120 mg/kg) possessed the most hypoglycemic activity compared to the other fractions of Nm. The Ethyl acetate fraction of Nm at 120mg/kg significantly reduced fasting blood glucose levels compared to the diabetic control(p=0.001) and slightly decreased BMI. Furthermore, the fraction demonstrated significant improvement in the parameters of some of the blood count indices such as red blood cells (p<0.001), total white cells (p<0.01) and platelet (p<0.001) compared to the diabetic control. These findings underscore the potential of Nm as a holistic therapeutic option for managing DM and its haematological complications. In conclusion, this study sheds light on the hypoglycemic potential of Nm Ethyl acetate leaf fraction, offering valuable insights into its effectiveness, safety, and broader physiological impacts. Further research into the mechanisms underlying its therapeutic effects is warranted to fully harness its therapeutic potential in diabetes management.

Nutrition therapy is the best solution to human chronic diseases, especially beer and barley which play an important role in human health and civilization. We demonstrated the actional mechanism of functional ingredients in beer and barley to combat chronic diseases, based on PubMed, google, CNKI, and ISI Web of Science databases from 1997 to 2024. Beer is rich in functional ingredients that is a complex of barley malt and hops; the health effect of beer against 26 chronic diseases is highly similar to that of barley, due to molecular mechanism of polyphenols (phenolic acids, flavonoids), melatonin, minerals, bitter acids, vitamins, and peptides. The ancient German Beer Purity Law provides much scientific basis today, especially indirectly supporting the human one cell disease theory. Low purine beer can be produced by enzymatic and biological degradation and adsorption of purines as well as dandelion addition. Functional beer with low purine and high active ingredients made from Beer Purity and barley malt as well as functional foods addition will be the key and important development direction, such as ginger beer and ginseng beer, especially coix-lily beer at the ancestors ca. 9000 years ago. This review paper not only reveals the actional mechanism of beer overcoming human chronic diseases, but also provides scientific basis for the development of functional beer for the prevention and treatment of human chronic diseases.

Novel ZNF proteins such as ZNF671 that are located on chromosome 19q13 are known to be hypermethylated at a high frequency in HNSCC as well as in other epithelial solid tumors. Their function is largely unknown. Here, we show that ZNF671 is epigenetically silenced in HNSCC primary tumors compared to matched adjacent normal tissue. Moreover, low expression of ZNF671 is significantly associated with decreased survival in HNSCC patients. Over-expression of ZNF671 in UM-SCC-1 oral cancer cells resulted in a significant reduction in tumor cell mobility and invasion compared to the empty-vector control cells. Transcriptomic analysis showed that ZNF671 re-expression resulted in a significant decrease in the expression of a major oncogenic long non-coding RNA LINC00665. Together, these results suggest that epigenetic silencing of ZNF671 may activate multiple oncogenic signaling pathways via the resulting up-regulation of LINC00665.

Resveratrol (RSV), a naturally occurring phytoalexin, is the most important stilbenoid synthesized by plants, as a defense mechanism, in response to microbial aggression, toxins or ultraviolet radiation. RSV came to the attention of researchers both as a potential chemopreventive agent and a possible explanation for the low incidence of cardiovascular disease (CVD) in French people with a high-fat diet. RSV is mainly administered as a food supplement, its properties being evaluated in vitro or in vivo, on various experimental models. RSV modulates signaling pathways that limit the spread of tumor cells, protects nerve cells from damage, is useful in the prevention of diabetes, and generally acts as an anti-aging natural compound. It was highlighted that RSV could ameliorate the consequences of an unhealthy lifestyle caused by an exaggerated caloric intake. This paper reviews the evidence supporting the beneficial effect of RSV for various pathological conditions, e.g., neoplastic diseases, neurodegeneration, metabolic syndrome, diabetes, obesity, CVDs, immune diseases, bacterial, viral, and fungal infections. The study also focused on the chromatographic analysis of trans-RSV (tRSV) in Romanian wine samples, providing a comprehensive overview of tRSV content across different types of wine.

(1) Background: To fight for COVID-19 pandemic, immunity against SARS-CoV-2 should be achieved not only through natural infection but also vaccination. Controversies exist about the effect of COVID-19 vaccination on previously infected persons; (2) Methods: A prospective cohort was undergone to collect sera from unvaccinated survivors and vaccinated persons--with and without COVID-19 pre-infection. The sera were analyzed for the anti-Receptor Binding Domain (RBD) titers by ELISA and for the capacity to neutralize the pseudovirus of the Wuhan-Hu-1 strain by luciferase assays; (3) Results; Neither the antibody titers nor the neutralization capacity was significantly different between the three groups. However, the correlation between the antibody titers and the percentage of viral neutralization derived from sera of unvaccinated survivors was higher than that from vaccinated persons with pre-infection (Spearman correlation coefficient (r) = -0.8558; 95% CI, -0.9259 to -0.7288), p &lt;0.0001 vs -0. 581; 95% CI, -0.7679 to -0.3028; p = 0.0002, respectively), indicating the capacity to neutralize the virus is better among the unvaccinated individuals. (4) Conclusions: Vaccines induced anti-RBD titers as high as the natural infection with lower neutralization capacity, and it did not boost the immunity in pre-infected persons.

Biobased greases are derived from renewable resources, being considered more environmentally friendly, and offering comparable performance with petroleum-based greases. In this study, lubricating greases from frying cooking oils were prepared, thus valorizing waste, in order to obtain sustainable and environmentally friendly products. 12 batches (500 g each) were produced from sunflower and palm frying oils, with 20% by weight calcium/ lithium stearate soaps prepared in situ, and additivated with 15% wt. cellulose or lignin sulphate. The greases were rheologically characterized. Their consistency was assessed by the penetration test, performed before and after working the greases. Dropping point determinations offered information about the stability at higher temperatures, and oil bleeding tests were performed. The average values of the friction coefficient (COF), the contact resistance and the wear scar diameter were measured, through mechanical tests. Additivated greases prove to be comparable with those obtained from mineral oils, with good rheological properties, soft consistency and good antiwearing behavior, e.g.in open or total- loss lubricating systems, like in open gears and certain food processing machinery; they are thermally stable, and prone for use in low-loading working mechanisms.

Background: Removable prostheses have seen a fundamental change recently because of advances in polymer materials, allowing improved durability and performance. Despite these advancements, notable differences still occur amongst various polymer materials and processing technologies, requiring a thorough grasp of their mechanical, physical, and therapeutic implications. Methods: Fours different processing techniques, all utilizing Polymethyl methacrylate (PMMA) as the main material, were used to construct complete dentures. The specimens underwent a mechanical test. Results: All the specimens broke under the influence of a certain force, rather than yielding through flow, as is characteristic for plastic materials. For each specimen, the maximum force (N) was recorded (figure 4), as well as the breaking energy, Conclusions: The best results were obtained in the case of the thermoplastic injection system and, surprisingly and contrary to those in the specialized literature, the worst results were recorded in the case of 3D printed samples.

In the quest for more efficient solar thermal systems, accurately determining the thermal emittance of low-emissive materials is crucial in determining the power losses. This paper describes the calorimetric method designed to precisely measure the thermal emittance of Selective Solar Absorbers (SSAs) to be used in High Vacuum Flat Plate Collectors (HVFPCs). The method's capability is demonstrated through the successful correction of thermal emittance values for copper samples of varying sizes, including dimensions down to 49 cm². Results highlight the method's potential to significantly reduce measurement errors associated with small-size and/or low-emittance samples, providing a path forward to improve the design and efficiency of SSAs. This research marks a significant step in advancing solar thermal technology by enabling emittance measurements with a precision better than 0.003, which is essential for the development of high-performance solar thermal absorbers. The method has also been applied to correct the thermal emittance value of SSA measured in previous measurement campaigns, and it allows a better estimation of the SSA efficiency conversion curve.

Introduction: Lymph-nodal prostate cancer oligometastases are differently treated according to their site: pelvic are locoregional lymph-nodes, instead para-aortic lymph-nodes are considered as distant metastases. Aim of the study was a comparison between para-aortic and pelvic oligometastases treated with stereotactic body radiation therapy (SBRT). Material/methods: This is a retrospective analysis. De-novo metastatic or extra-nodal disease were excluded. Univariate and multivariate analyses were performed; pattern of recurrence was evaluated too. A propensity score matching (PSM) was applied to create comparable cohorts. Primary end-point was the progression-free survival (PFS). Secondary end-points were biochemical relapse-free survival (BRFS), ADT-free survival (ADTFS), polymetastases-free survival (PMFS), local progression-free survival (LPFS) and pattern of relapse. Results: 240 lymph-nodal oligometastases in 164 patients (127 pelvic and 37 para-aortic) were treated. Median PFS was 20 and 11 months in pelvic and para-aortic patients respectively (p=0.042). The difference was not confirmed at the multivariate analysis (p=0.06). Median BRFS was 16 and 9 months respectively in pelvic and para-aortic group (p=0.07). No statistically significant differences for ADTFS or PMFS were detected. The cumulative 5-years LPFS was 90.5%. At PSM no statistically significant differences for all the study end-points were detected. Conclusions: Patients affected by para-aortic disease might have PFS comparable to pelvic disease; local control is high in both cohorts. Our results support the use of SBRT also to para-aortic metastases.

Background: Early diagnosis of postoperative complications is an urgent task, allowing timely prescribing of appropriate therapy and reducing the cost of patient treatment. Prognostic models based on various data could help in the early diagnosis of postoperative complications after cardiac surgery. Objectives: The purpose of the study was to determine whether an integrated approach based on clinical data along with metabolites and biomarkers had greater predictive value than the models built on less data. Methods: The study included patients (n=62) admitted for planned cardiac surgery (coronary artery bypass grafting with cardiopulmonary bypass), who were retrospectively divided into two groups depending on the presence (n=26) or absence (n=36) of postoperative complications of all types. Clinical and laboratory data on the first day after surgery were analyzed. Additionally, patients' blood samples were collected before and on the first day after surgery to determine biomarkers (interleukin-6, procalcitonin, NT-proBNP, high-sensitivity troponin T) and metabolites (8 aromatic and 2 dicarboxylic acids were detected using gas chromatography-mass spectrometry). Results: Patients before surgery, compared with healthy donors, differed in the concentration of metabolites (p &lt; 0.05), and had concentrations of a number of biomarkers exceeding the corresponding reference values. Multivariate PLS-DA models, predicting the presence or absence of postoperative complications, were built using clinical data (ROC-AUC=0.71), concentrations of metabolites and biomarkers (ROC-AUC=0.60), and the entire data set (ROC-AUC=0.75). For comparison we built univariate models using the EuroScore2 (ROC-AUC=0.59) and SOFA (ROC-AUC=0.76) scales; concentrations of lactate (ROC-AUC=0.71), the dynamic changes of 4-hydroxyphenyllactic acid (ROC-AUC=0.69), and the sum of three sepsis-associated metabolites (ROC-AUC=0.70). The proposed complex model using entire data set was comparable to the SOFA scale, which confirms the expediency of searching for new predictive models based on a variety of factors.

Milk serves as a crucial source of natural bioactive compounds essential for human nutrition and health. The gastrointestinal digestion of milk proteins releases various biologically active peptides that positively impact human health and enhance physiological performance. With the growing production of cheese, Greek yogurt, and other dairy products, the volume of unutilized acid whey is significantly increasing. Acid whey, containing almost all whey proteins and approximately one-quarter of casein, presents a valuable raw material for generating peptides with potential health benefits. These peptides exhibit properties such as antioxidant, antimicrobial, anti-inflammatory, anticarcinogenic, antihypertensive, antithrombotic, opioid, mineral-binding, and growth-stimulating activities, contributing to improved human immunity and the treatment of chronic diseases. Enzymatic hydrolysis of milk proteins has been developed as a method to produce these peptides, facilitating their use in food fortification. To incorporate whey into functional beverages, it undergoes fermentation by lactic acid bacteria with proteolytic activity. To specifically enrich these beverages with peptides exhibiting targeted bioactivities, it is essential to select lactic acid bacteria strains possessing the requisite protease profiles. Additionally, the sensory properties of the final product can be enhanced using starter cultures with diverse metabolic capabilities, even in the absence of added flavoring agents. Given the imperative to develop waste-free technologies and enhance the profitability of the dairy industry, there is a growing need to efficiently utilize and transform acid whey into a broad spectrum of valuable products and food additives. This approach is justified not only by the nutritional benefits of the bioactive components in whey but also by the commercial potential of safe and health-enhancing products.

The paper focuses on the application of a multilevel, integrative and territorial approach to the protection of cultural heritage through planning instruments in Serbia. It points out the problems of the sectoral approach and discusses international recommendations that can be integrated into the planning methodology. The case study is the area of Djerdap National Park, which has an already established international and national importance. The research suggests that the cultural heritage in the area, with the exception of the Roman limes, is still recognized at the level of individual localities. The study emphasizes the importance of aligning all levels of governance to safeguard the whole spatial entity rather than focusing solely on its particular areas. The interna-tional and national importance of the planning area contributes to the strengthening of awareness of heritage and its institutional protection. However, the vitality of the area, which is key to its sustainable development, comes from the local level. Planning documents contribute to the inte-gration of local values and local communities into development programs and projects.