Introduction: The COVID-19 severely marred the Indian poultry industry, worth approximately one trillion INR. Hence, this study was conducted to understand the COVID-19 related factors that harmed the poultry production and distribution network and explore their varied impact on its actors in Gujarat, India. Methods: An exploratory qualitative study, using semi-structured interviews, was conducted with 34 poultry stakeholders in Gujarat. The data were thematically analysed using an interpretative phenomenological approach. Results: The study revealed that COVID-19 and the associated lockdown had hugely impacted the production, distribution and consumption of poultry products. The first COVID-19 lockdown disrupted the supply of production inputs and the distribution of poultry and poultry products because of movement restrictions. Rumours also played a crucial role in decreasing the consumption of poultry products between March and June 2020. The market situation, including the prices and availability of poultry products, was found to be improved post-lockdown as there was an increase in consumption; however, the profits were not sufficient to immediately compensate for the losses incurred during the lockdown. Conclusion: The first COVID-19 lockdown restricted the production and distribution of essential goods and influenced the perception of consumers regarding poultry products. COVID-19 resulted in many short- and medium-term challenges in the poultry sectors in India, which need to be addressed to make this sector more resilient to face any such crisis in future.

Introduction: Heat is a kinetic process whereby energy flows from between two systems; hot-to-cold objects. In oro-dental implantology, conductive heat transfer/(or thermal stress) is a complex physical phenomenon to analyze and consider in treatment planning. Hence, ample research has attempted to measure heat-production to avoid over-heating during bone-cutting and -drilling for titanium (Ti) implant-site preparation and insertion, thereby preventing/minimizing early (as well as delayed) implant-related complications and failure. Objective: Given the low bone-thermal conductivity whereby heat generated by osteotomies is not effectively dissipated and tends to remain within the surrounding tissue (peri-implant), increasing the possibility of thermal-injury; this work attempts to obtain an exact analytical solution of the heat equation under exponential thermal-stress, modeling transient heat transfer and temperature changes in Ti implants upon hot-liquid intake. Materials and Methods: We investigate the impact of the material, the location point along implant length, and the exposure time of the thermal load on temperature changes. Results: Despite its simplicity, the presented solution contains all the physics and reproduces the key features obtained in previous numerical analyses studies. To the best of knowledge, this is the first introduction of the intrinsic time, a “proper” time that characterizes the geometry of the dental implant, where we show, mathematically and graphically, how the interplay between “proper” time and exposure time influences temperature changes in Ti implants, under the suitable initial and boundary conditions. Conclusions: This work aspires to accurately complement the overall clinical diagnostic and treatment plan for enhanced bone-implant interface, implant stability and success rates, whether for immediate or delayed loading strategies.

Background: Level of perceived competence as a basic psychological need could trigger achievement of diabetes self-management goals. Due to lack of a specific data collection tool to measure level of self-competence among Persian speaking patients with diabetes this study was conducted for cross-cultural adaptation and psychometric assessment of the Persian version of Perceived Competence Scale for Diabetes (PCSD-P). Methods: Standard translation/back-translation procedure was carried out to prepare a preliminary draft of the PCSD-P. Content and face validity of the early draft were checked by an expert panel including 15 scholars in the field of health education and promotion as well as nursing education with experience of working and research on diabetes. The final drafted questionnaire was completed by 177 randomly selected patients with type 2 diabetes. Based on the collected data structural validity of the contrived version was appraised using exploratory and confirmatory factor analysis (EFA, CFA). Cronbach's alpha and Intraclass Correlation coefficients (ICC) were used to check the scale’s reliability and internal consistency. ; (3) Results: The estimated measures of Content Validity Index (CVI= 0.95) and Content Validity Ratio (CVR= 0.8) were in the range of acceptable recommended limits. The EFA analysis results demonstrated a single factor solution according to the items’ loadings for the component. The model fit indices i.e. RMSEA= 0.000, CFI=1, TLI=1, GFI= 0.998, NFI= 0.999 RFI= 0.995 confirmed consistency of the hypothesized one-factor solution. Values of the internal consistency and reliability coefficients were also in the vicinity of acceptable range (α= 0.892, ICC=0. 886, P= 0.001). Conclusions: The study findings revealed good internal validity and applicability of the PCSD-P to measure degree of self-competence among Persian speaking type 2 diabetes patients to manage the chronic disease. Due to unrepresentativeness of the study sample future cross-cultural test of PCSD-P on diverse and broader Persian speaking populations is recommended.

Sustainable development and education in sustainable development (ESD) are crucial and interconnected topics under wide discussion today. Young adults need to be educated in how to help bring about change. Thus, the dynamic relationship between school and home is important. In education, use could be made of English language classes, especially since English is a global language that enables access to the sustainability literature and facilitates discussion in global conferences and meetings. Consequently, English as a foreign language (EFL) students could gain confidence from being able to understand and use the terminology of, for example, sustainability. In this paper, the use of competence-based language teaching (CBLT) is proposed as a means of introducing sustainability topics into EFL writing classes at a university in Saudi Arabia. Students’ competence in sustainable development is therefore considered based on their ability to write about suggested sustainable development topics, measured on a scale for five dimensions of ESD proposed by Michelsen and Fischer (2017). The results demonstrate that the students possessed competence in sustainable development and intended to participate in its implementation. Thus, recommendations are made for the stakeholders in the education sector to include sustainable development topics as an initial offering in the curricula of various specialties using the CBLT approach.

The Kampar Peninsula, a significant peatland region in Riau, Indonesia, is vital for its carbon re-serves and biodiversity, including the Sumatran tiger. Covering approximately 735,091 hectares, it comprises critical peat domes essential for hydrological balance. This research investigates land use changes from 1990-2020 using the Normalized Difference Fraction Index (NDFI) to map disturb-ances and land cover changes. Additionally, interviews and regulatory analysis were conducted to examine the historical drivers of land use change in the Kampar Peninsula. In 2020, natural forests covered 433,395.20 hectares (59.9% of the total area), industrial pulpwood plantations (primarily acacia) covered 27.3%, oil palm plantations accounted for 10.4%, infrastructure occupied 2.4%, and water bodies made up 0.9%. Key drivers of land use change include the construction of access roads by oil companies since 1975 and government policies during the New Order period (1980s-1998) promoting forest exploitation and transmigration programs. These activities have significantly transformed the Kampar Peninsula's land cover, highlighting the need for sustainable management and conservation efforts.

The rising importance of Big Data in modern information analysis is supported by vast quantities of user data, but it is only possible to collect sufficient data for all tasks within certain data-gathering contexts. There are many cases where a domain is too novel, too niche, or too sparsely collected to adequately support Big Data tasks. To remedy this, we have created ADG Engine that allows for the generation of additional data that follows the trends and patterns of the data that’s already been collected. Using a database structure that tracks users across different activity types, ADG Engine can use all available information to maximize the authenticity of the generated data. Our efforts are particularly geared towards data analytics by identifying abnormalities in the data and allowing the user to generate normal and abnormal data at custom ratios. In situations where it would be impractical or impossible to expand the available dataset by collecting more data, it can still be possible to move forward with algorithmically expanded data datasets.

Two representable substructural logics ${\rm {\bf UL}}_\omega $ and ${\rm {\bf IUL}}_\omega $ are logics for finite UL and IUL-algebras, respectively. In this paper, the standard completeness of ${\rm {\bf UL}}_\omega $ and ${\rm {\bf IUL}}_\omega $ is proved by the method developed by Jenei, Montagna, Esteva, Gispert, Godo and Wang. This shows that ${\rm {\bf UL}}_\omega $ and ${\rm {\bf IUL}}_\omega $ are substructural fuzzy logics.

The EFQM Model, established in 1991, serves as a framework for organizational excellence, helping achieve sustainable success through an integrated management system. The model's evo-lution is driven by the need to adapt to global trends, threats, and technological innovations such as: digital transformation, employee engagement and well-being, remote work, agile performance management, diversity, equity and inclusion (DEI), sustainability, AI, and big data. The new EFQM Model 2025, presented in Istanbul in June 2024, introduces significant changes, emphasiz-ing sustainability, innovation, and technology. These changes are analyzed based on the logic of three questions: Why, How, and What. Why: There is a necessity for better alignment of organizations with contemporary challenges through flexibility, risk resilience, and innovation capabilities in a dynamic business environ-ment, including alignment with the UN Sustainable Development Goals (SDGs). How: The model introduces an integrated approach to performance management and transfor-mation, incorporating advanced technologies such as AI and data analytics. What: Implementing the EFQM Model 2025 enhances organizational adaptability, innovation, and flexibility, improving financial, operational, and strategic outcomes. Better alignment with sustainability goals leads to long-term value and social responsibility. Improved stakeholder engagement methods enhance understanding and satisfaction. The use of advanced technologies supports innovation and operational efficiency, while better strategic and operational performance and risk management ensures greater stability and the ability to anticipate future challenges.

Worldwide, hypoxia-related conditions, including cancer, COVID-19, and neuro-degenerative diseases, often lead to multi-organ failure and significant mortality. Oxygen, crucial for cellular function, becomes scarce as levels drop below 10 mmHg (<2% O2), triggering mitochondrial dysregulation and activating hypoxia-induced factors (HiFs). Herein, Oxygen nanoBubbles (OnB), an emerging versatile oxygen de-livery platform, implies to offer a novel approach to address hypoxia-related pathologies. This review explores OnB oxygen delivery strategies and systems, including diffusion, ultrasound, photodynamic, and pH-responsive nanobubbles. It delves into the nanoscale mechanisms of OnB, elucidating their role in mitochondrial metabolism (TFAM, PGC1alpha), hypoxic responses (HiF-1alpha), and their interplay in chronic pathologies including cancer and neurodegenerative disorders, amongst others. By understanding these dynamics and underlying mechanisms, this article aims to contribute to our accruing knowledge of OnB and the developing potential in ameliorating hypoxia- and metabolic stress-related conditions and fostering innovative therapies.

Here we present calculation of the critical current of DC SQUID based on the Josephson junction on multi-band superconductor with frustration effect. It is shown that the changing of the critical current of DC SQUID with small geometrical inductance is determined by the ratio of supercurrent amplitude in different channels and the external magnetic field. In the a case of DC SQUID with high inductance frustration effects can be ignored.

The article focusses on detecting the unbalance of a mechanical component in the electric drive system of a two-mass servomechanism with a PMSM motor, which is connected to the load via a long, flexible shaft. In the example analysed, the degree of unbalance was determined using the reference current signal from the speed controller of the FOC control system. The authors pre-sented a two-mass model with an unbalanced mechanical system. The STFT transform was used to analyse the symptoms of unbalance and an artificial neural network MLP was used for system state inference. The effectiveness of the presented analysis, based on the reference current signal from the sensor embedded in the control system, was experimentally confirmed.

This research paper describes the social engineering concepts, techniques, and security countermeasures. This research aims to study various social engineering techniques to find the best countermeasures that would help to reduce social engineering attacks.

The new diprotic ligand 3,5-di-tert-butylsalicylaldehyde 4-ethyl-3-thiosemicarbazone, abbreviated H2(3,5-t-Bu2)-sal4eT, exists as the thio-keto tautomer and adopts the E-configuration with respect to the imine double bond as evidenced by single-crystal X-ray analysis and corroborated by spectroscopic characterisation. Upon treatment with Cu(OAc)2·H2O in the presence of either 2,9-dimethyl-1,10-phenanthroline (2,9-Me2-phen) or 1,10-phenanthroline (phen) as a co-ligand in MeOH, this thiosemicarbazone undergoes conformational transformation (relative donor-atom orientations: syn,anti → syn,syn) concomitantly with tautomerization and double deprotonation to afford the ternary copper(II) complexes [Cu{(3,5-t-Bu2)-sal4eT}(2,9-Me2-phen)] (1) and [Cu2{3,5-t-Bu2)-sal4eT}2(phen)] (2). Crystallographic elucidation has revealed that complex 1 is a centrosymmetric dimer of mononuclear copper(II) complex molecules brought about by intermolecular H-bonding. The coordination geometry at the copper(II) centre is best described as distorted square pyramidal in accord with the trigonality index (τ = 0.14). The co-ligand adopts an axial-equatorial coordination mode; hence there is a disparity between its two Cu–N coordinate bonds arising from weakening of the apical one as a consequence of the tetragonal distortion. The axial X-band ESR spectrum of complex 1 is consistent with retention of this structure in solution. Complex 2 is a centrosymmetric dimer of dinuclear copper(II) complex molecules exhibiting intermolecular H-bonding and π-π-stacking interactions. The two copper(II) centres, which are 4.8067(18) Å apart and bridged by the thio-enolate nitrogen of the quadridentate thiosemicarbazonate ligand, display two different coordination geometries, one distorted square planar (τ4 = 0.082) and the other distorted square pyramidal (τ5 = 0.33). Such dinuclear copper(II) thiosemicarbazone complexes, which are crystallographically characterised, are extremely rare. In vitro, complexes 1 and 2 outperform cisplatin as antiproliferative agents in terms of potency and selectivity towards HeLa and MCF-7 cancer cell lines.

Cervical fusion has been a standard procedure for treating the abnormalities associated with the cervical spine. However, the reliability of anterior cervical discectomy and fusion (ACDF) has become arguable due to its adverse effects on the biomechanics of adjacent segments. One of the drawbacks associated with ACDF is adjacent segment degeneration (ASD) which has served as the base for the development of dynamic stabilization systems (DSS) and total disc replacement (TDR) devices for cervical spine. However, the hybrid surgical technique has also gained popularity recently but their effect on the biomechanics of cervical spine is not well researched. Thus, the objective of this FE study was to draw the comparison among single, bi-level and hybrid surgery with DCI implant with traditional fusion. Reduction in range of motion (ROM) for all the implanted models was observed for all the motions except extension, compared to intact model. The maximum increase in ROM of 42% was observed at C5-C6 level in Hybrid-DCI model. The maximum increase in adjacent segment’s ROM of 8.7% was observed in multilevel fusion model. The maximum von Mises stress in the implant was highest for the multilevel DCI model. Our study also showed that the shape of DCI implant permits flexion/extension relatively more compared to lateral bending and axial rotation.

Background: The use of medicinal plants and their effective compounds as natural sources that have antioxidant properties, has been considered by researchers. Antioxidants are compounds that effectively inhibit the reaction of oxygen and nitrogen-free radicals with biomolecules in a variety of ways, reducing damage or preventing cell death, cardiovascular diseases, and cancers. Objective: In this study, chemical compounds of Adiantum capillus-veneris essential oil were used to evaluate its antioxidant and antimicrobial activity using water distillation and gas chromatography. Methods: The whole plant was dried at room temperature at 25 ° C and the distillation method with water with modifications was used using a Clevenger device for essential oil extraction. Gas chromatography-mass spectrometry (GC/MS) was used to identify the resulting essential oil compounds and the antioxidant and antibacterial activity of the essential oil was evaluated. Results: The most important chemical constituents of Adiantum capillus-veneris essential oil were carvone (33.00%), carvacrol (15.05%), hexadecanoic acid (7.02%), hexahydrofarnesyl acetone (4.25%) and n-nonanal (4.2%). The antibacterial activity of Adiantum capillus-veneris essential oils (mg/ml) was calculated and the highest antibacterial activity was determined by Staphylococcus aureus (8.23±1.07), Streptococcus pyogenes (12.46±1.62), and Diphtheroid (11.37±1.36) at a concentration of 100 mg/ml of essential oils. Conclusion: The results of the present study showed that the essential oil of Adiantum capillus-veneris prevented the growth of three pathogenic bacteria. This antibacterial property is due to the presence of flavonoid compounds in Adiantum capillus-veneris has the capacity for therapeutic and medical uses.

In this short communication, a concept has been presented to model geographical data to predict future temperature of Tabuk, region. Machine learning has been applied to the weather station data to develop a prediction model. The preliminary results are promising and encouraging and are envisaging to further this research towards the determination of unknown temperature rise in the region. This is important to mention here, that the problem has been formulated as a Regression problem, NOT as a classification problem. Hence, applying Convolutional neural networks is not possible, due to the non-existence of classes or converting the temperature values to classes does not make any sense. Hence, this is defined as a regression problem which achieved encouraging desirable results.

Olive fruits at different ripening stages give rise to various table olive products and oil qualities. Therefore, developing an efficient method for recognizing and sorting olive fruits based on their ripening stages can greatly facilitate postharvest processing. This study introduces an automatic computer vision system that utilizes deep learning technology to classify the `Roghani` Iranian olive cultivar into five ripening stages using color images. The developed model employs convolutional neural networks (CNN) and transfer learning based on the Xception architecture and ImageNet weights as the base network. The model was fine-tuned by testing multiple configurations of well-known CNN layers. To minimize overfitting and enhance model generality, data augmentation techniques were employed. By considering different optimizers and two image sizes, four final candidate models were generated. These models were then compared in terms of loss and accuracy on the test dataset, classification performance (classification report and confusion matrix), and generality. All four candidates exhibited high accuracies ranging from 86.93% to 93.46% and comparable classification performance. In all models, at least one class was recognized with 100% accuracy. However, by taking into account the risk of overfitting, two models were discarded. Finally, a model with an image size of 224 × 224 and an SGD optimizer, which had a loss of 1.23 and an accuracy of 86.93%, was selected as the preferred option. The results of this study offer robust tools for automatic olive sorting systems, simplifying the differentiation of olives at various ripening levels for different post-harvest products.

In the article, the results of research on a NiTi alloy with a high nickel content (51.7 at.%), produced using the additive technology SLM method and subjected to isothermal aging after so-lution annealing, are presented. The study involved the determination of the sequence of phase transformations occurring using differential scanning calorimetry (DSC), and the determination of the temperature range of these transformations. In parallel, the phase composition was determined using the XRD method; hardness and the Young’s modulus were also determined. The analysis of the DSC results obtained indicates the following characteristic features of the NiTi alloy, which change with ageing time: (1) during cooling (from +1500C to -500C), the type of transformation changes from a one-step transformation after solution annealing to a two-step transformation after the ageing process over 1, 20 and 100 hours at 500°C; (2) during heating (from -500C to +1500C) for all the samples, regardless of the ageing time, only a one-step transformation from martensite M(B19’) to austenite A(B2) is observed; (3) the temperature at which the transformation starts increases with the ageing time, (4) the width of the total temperature range of the transformation M(B19’)  A(B2) during heating changes from large (∆T=49,7°C), after solution annealing, to narrow (∆T=19.3°C and ∆T=17.9°C after 20 h and 100 h of ageing) and, most importantly, (5) a comparison with literature data shows that, irrespective of the composition of the NiTi alloy and the manufacturing technology of the alloy samples (regardless of the fact whether this was traditional or additive technology), a sufficiently long ageing process period leads to the occurrence of the martensite  austenite transformation in the same temperature range.

The growth of social media has changed the face of many aspects of marketing such as online, digital, etc. It also has changed the way modern human communicates and connects with others. Moreover, the behavior on this platform could not and should not be justified with strategies of other marketing channels and media. Due to the nature of social media, they are rich in precise and lean data, but processing these data and extracting knowledge and insights from them are problematic. Evaluating the effectiveness of a marketing endeavor is also a task related to these data. The current research attempts to assess the effectiveness of an advertising campaign on Instagram via advertising cost and sentiment classification of audience opinion regarding the campaign. The methodology used in this research is the standard process of data mining, i.e., CRISP-DM. Furthermore, multiple machine learning models and approaches were studied to train a prediction model based on data. In order to find the most accurate algorithm, grid search was used among the trained models and different algorithms with different combinations of hyper-parameters. The obtained results revealed that although the number of not profitable advertising media was higher than the profitable media, the overall status of the campaign was profitable, both in the cost-effectiveness approach and sentiment analysis approach. The other valued outcome of this research was important general and specific insights which can be used to shape a better-performing and effective advertising campaign on Instagram.

Despite Low Power Wide Area Networks’ ability to offer an extended range, it might still encounter challenges with coverage blind spots in the network. This article proposes an innovative energy-efficient nature-inspired relay selection algorithm for LoRa-based LPWAN networks, serving as a solution for challenges related to poor signal range in areas with limited coverage. A behavior swarm-inspired approach has been utilized to select the relays’ localization in the network, providing network energy efficiency and radio signal extension. These relays help bridge communication gaps, significantly reducing the impact of coverage blind spots by forwarding signals from devices with poor direct connectivity with the gateway. The proposed algorithm considers critical factors for the LoRa standard, such as the Spreading Factor or device energy budget analysis. The simulation experiments validate the proposed scheme’s effectiveness in terms of energy efficiency under diverse multi-gateway topology scenarios involving thousands of devices. Specifically, it has been verified that the proposed approach outperforms the reference method in preventing the battery depletion of relays, which is vital for battery-powered IoT devices. Furthermore, for some large-scale problems, the proposed heuristic method achieves over twice the speed of the exact method with a negligible accuracy loss of less than 2%.

The research aims to improve some of the physical and hydro-physical properties of some Vertisols in the southern region (part of the eastern Houran Plateau) in Sweda Governorate at the south of Syria. Using different quantities of volcanic ash, soil samples were collected from the Al-Thahallah village from a depth of (0-30) cm, The experiment was designed according to the complete random design with one factor that represents the ash quantity (1.25, 2.5, 5) %, with three replicates for each treatment in addition to the control treatment a0. The experiment was carried out within the plastic pots during agricultural season 2018/2019, in which the wheat of the Sham variety 3 were cultivated as a cover plant. The results showed that the addition of volcanic ash at the quantity of 5% led to a significant increase in the infiltration rate by (328.60) %,%, where the filtration rate increased from 0.42 cm/hr -1 to 1.80 cm.h-1, as well as for each of the air porosity by (89) % and the volume of infiltrate water by (40) %, compared with the control. The above-mentioned addition also resulted in a decrease in both dry bulk density, total soil porosity and volumetric swelling coefficient by (18.60, 5.80, 314) % Respectively, compared to the control. The addition also contributed to the reduce in the weighted moisture content when saturation and the field capacity, at the level of significance of 5%. The research recommends adding volcanic ash to the soil at a quantity of 5%, and adding enhancements with volcanic ash at various levels such as organic waste.

Accidents and mishaps in industrial environments like construction, mining, and transport are rampant - mainly due to human negligence and improper monitoring of the workplace. In this paper, we address the safety of workers operating in dangerous environments by improving their situational awareness. According to Occupational health and safety rules, everyone must wear hard hats while on site. Our main idea is to make the hard hats smart by incorporating miniature-sized Doppler radars sensing the users’ surroundings. These Doppler radars are lightweight, rugged, and consume low-power compared to vision-based solutions. This paper discusses the observability of range from Doppler frequency measurements and the magnitude of estimation errors introduced by the human head, walking, and working motions. We present the framework to estimate the position of walls and targets surrounding the worker. For testing, we simulated an indoor environment with randomly moving workers. Experiments showed that once observability conditions are met, human head and walking movements can be handled through added noise in the system. We also present an innovative idea of using two Doppler radars to obtain the estimators’ initial estimates, reducing the estimation error to less than 5cm and convergence time by more than 80

In a generalized topological space Tg = (Ω, Tg), ordinary interior and ordinary closure operators intg, clg : P (Ω) −→ P (Ω), respectively, are defined in terms of ordinary sets. In order to let these operators be as general and unified a manner as possible, and so to prove as many generalized forms of some of the most important theorems in generalized topological spaces as possible, thereby attaining desirable and interesting results, the present au- thors have defined the notions of generalized interior and generalized closure operators g-Intg, g-Clg : P (Ω) −→ P (Ω), respectively, in terms of a new class of generalized sets which they studied earlier and studied their essen- tial properties and commutativity. The outstanding result to which the study has led to is: g-Intg : P (Ω) −→ P (Ω) is finer (or, larger, stronger) than intg : P (Ω) −→ P (Ω) and g-Clg : P (Ω) −→ P (Ω) is coarser (or, smal ler, weaker) than clg : P (Ω) −→ P (Ω). The elements supporting this fact are reported therein as a source of inspiration for more generalized operations.

Applications for Wireless Sensor Networks (WSNs) range from monitoring the environment to automating factories. However, sustained and effective functioning is made more difficult by Sensor Nodes (SNs) limited energy supplies in which optimization is the main issue. So with the aim of increasing the lifespan by decreasing the energy consumption of WSN, Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol with Deep Learning (DL) algorithm is analyzed in this paper. LEACH is a hierarchical mechanism that elects Cluster Heads (CHs) and regularly rotates their positions in order to allocate energy use effectively by using the same amount of energy. However, Deep Learning (DL) method is used to further improve energy optimization. In many applications, the types of Deep Learning methods like Artificial Neural Networks (ANNs) have shown to be very useful. Using this method, WSNs may make more efficient decisions that reduce energy consumption. Data aggregation, duty cycling, and transmission protocols may all be optimized by Deep Learning model's ability to recognize patterns and forecast network behavior. This results in lower energy consumption, a longer lifespan for the network, and better overall performance.

In a generalized topological space T_g = (Ω, T_g) (T_g-space), the g-topology T_g : P (Ω) −→ P (Ω) can be characterized in the generalized sense by specifying the generalized open, generalized closed sets (g-T_g-open, g-T_g-closed sets), generalized interior, generalized closure operators g-Intg, g-Cl_g : P (Ω) −→ P (Ω) (g-T_g-interior, g-T_g-closure operators), or generalized derived, generalized coderived operators g-Der_g, g-Cod_g : P (Ω) −→ P (Ω) (g-T_g-derived, g-T_g-coderived operators), respectively. For very many T_g-spaces, the δ^th-iterates g-Der_g^(δ), g-Cod_g^(δ) : P (Ω) −→ P (Ω) of g-Der_g, g-Cod_g : P (Ω) −→ P (Ω), respectively, defined by transfinite recursion on the class of successor ordinals are also themselves g-T_g-derived, g-T_g-coderived operators for new g-topologies in the generalized sense on Ω. Thus, the use of novel definitions of g-T_g-derived, g-T_g-coderived operators g-Der_g, g-Cod_g : P (Ω) −→ P (Ω), respectively, based on a very clever construction, together with their δ^th-iterates g-T_g-operators g-Der_g^(δ), g-Cod_g^(δ) : P (Ω) −→ P (Ω), defined by transfinite recursion on the class of successor ordinals, will give rise to novel generalized g-topologies on Ω. The present authors have been actively engaged in the study of g-T_g-operators in T_g-spaces. The study of the essential properties and the commutativity of novel definitions of g-T_g-interior and g-T_g-closure operators g-Int_g, g-Cl_g : P (Ω) −→ P (Ω), respectively, in T_g has formed the first part, and the study of the essential properties and sets of consistent, independent axioms of novel definitions of g-T_g-exterior and g-T_g-frontier operators g-Ext_g, g-Fr_g : P (Ω) −→ P (Ω), respectively, has formed the second part. In this work, which forms the last part on the theory of g-T_g-operators in T_g-spaces, the present authors propose to present novel definitions and the study of the essential properties of g-T_g-derived and g-T_g-coderived operators g-Der_g, g-Cod_g : P (Ω) −→ P (Ω), respectively, and their δ^th-iterates, and the notions of g-T_g-open and g-T_g-closed sets of ranks δ in T_g-spaces.

In a generalized topological space Tg = (Ω, Tg), generalized interior and generalized closure operators g-Intg, g-Clg : P (Ω) −→ P (Ω), respectively, are merely two of a number of generalized primitive operators which may be employed to topologize the underlying set Ω in the generalized sense. Generalized exterior and generalized frontier operators g-Extg, g-Frg : P (Ω) −→ P (Ω), respectively, are other generalized primitive operators by means of which characterizations of generalized operations under g-Intg, g-Clg : P (Ω) −→ P (Ω) can be given without even realizing generalized interior and generalized closure operations first in order to topologize Ω in the generalized sense. In a recent work, the present authors have defined novel types of generalized interior and generalized closure operators g-Intg, g-Clg : P (Ω) −→ P (Ω), respectively, in Tg and studied their essential properties and commutativity. In this work, they propose to present novel definitions of generalized exterior and generalized frontier operators g-Extg, g-Frg : P (Ω) −→ P (Ω), respectively, a set of consistent, independent axioms after studying their essential properties, and established further characterizations of generalized operations under g-Intg, g-Clg : P (Ω) −→ P (Ω) in Tg.

Salmon aquaculture generates a substantial volume of waste material, offering potential for biomaterial production. This industry produces significant waste, which can be repurposed for various biological applications, particularly in biomaterial production for tissue engineering with pertinent applications in osteo-conduction, osteo-induction, and clinical/surgical bone regeneration and repair. The process involves a standardized pre-treatment stage aimed at minimizing biological waste content. Subsequently, the treatment stage, contingent on the chosen methodology, facilitates the removal of proteins, lipids, molecules, and other compounds, leaving the mineral phase as a valuable substrate. The selection of the optimal method, whether alkaline hydrolysis, calcination, or NaOH hydrolysis, for obtaining this substrate necessitates thorough examination through chemical, physical, and biological assessments, including Raman Spectroscopy and X-Ray Diffraction. This study aims to identify the most efficient laboratory process for biofunctional nano-sized hydroxyapatite mineral production derived from Chilean salmon fish backbone waste.

This study aims at providing a climatological analysis of annual and long-term variability of dry periods in the Polish Carpathians in the period of 35 years between 1986 and 2020. Aside days with precipitation, dry periods, namely sequences of days with no precipitation, constitute an inherent characteristic of the climate. The input data for the research was formed by daily precipitation totals from 17 meteorological stations acquired from the Institute of Meteorology and Water Management - National Research Institute, and T. Niedźwiedź catalogue of circulation types over southern Poland. Frequency of dry periods of different duration has been presented. The incidence of long-term periods has been related to the atmospheric circulation. An analysis was performed regarding the change of the average quantity and average length of dry sequences in the 35-year period covered. At most stations, there were no statistically significant trends with respect to the analysed dry day characteristics. This is an obvious result of high variability year-to-year, which means that exclusively large changes may achieve statistical significance. Dry days have been evidenced to related to circulation types. A vast majority of dry days is related to anti-cyclonal systems, particularly the anti-cyclonal wedge (Ka) and western anti-cyclonal (Wa) situations.

Background/Objectives: The aim of the project is a longitudinal assessment of body image and mental health in scoliosis females pre-, postoperatively and in a follow-up, and implementation (one group-CBT scoliosis sample, CBTSS) or not (second group-control scoliosis sample, CSS) of CBT interventions. A healthy female sample (HFS) was also selected for comparative purposes. Methods. 36 in total AIS patients participated in the 1st and 2nd study phases, whereas 23 were eligible in the follow-up. Regarding HFS, 18 participants were included in the study. The CBT intervention took place pre- and postoperatively, during the patients' stay in hospital. Participants completed the Spinal Appearance Questionnaire (SAQ), Body Esteem Scale (BES) and Strengths and Difficulties Questionnaire-25 (SDQ-25). Body image was also assessed using a virtual reality-based application “Avatar Scoliosis 3D”. Results: The difference between the desired and objective, actual body shape is significant preoperatively both in the CBTSS and CSS at p

This study evaluated the using of machine vision in combination with deep learning to identify weeds in real-time for wheat production system. PMAS-Arid Agriculture university research farm were selected for collection of images (6000 total images) of weeds and wheat crops under different weather condition. During growing season, the database was constructed to identify the weeds. For this study two framework were used TensorFlow and PyTorch under CNNs and Deep learning. Deep learning perfromed better with in PyTourch value as compared to another model in Tensorflow. comparing with other networks such as YOLOv4, we concluded that our network reaches a better result between speed and accuracy. Specifically, the maximum precision of weed and wheat plants were 0.89 and 0.91 respectively with 9.43 ms and 12.38 ms inference time per image (640 × 640) NVIDIA RTX2070 GPU.

The effect of contamination of polypropylene (PP) with selected polymers is studied to simulate the effect of mis-sorting in recycling streams. Polystyrene (PS), polyethylene terephthalate (PET), polycarbonate (PC), acrylonitrile-butadiene-styrene (ABS) and polylactic acid (PLA) were compounded with PP at different concentrations varying between 3 and 10%. Infrared spectroscopy proved the absence of chemical bonds between the constituents. The samples for mechanical testing were injection moulded and further tested for their tensile and impact properties. Critical behaviour was induced by the introduction of a weld line as a result of the application of multiple gating points during injection moulding. Results generally show the applicability of PP mixtures within the investigated range of inclusions, without much sacrifice in mechanical performance. However, in the case of ABS and PLA, more care should be taken when designing complex parts with weld lines, due to reduced toughness.

Osteoarthritis of the hand (HOA) is one of the most common musculoskeletal diseases affecting health. Osteophytes, documented by imaging procedures are often used as diagnostic criteria. The gold standard is the radiographic image, however, more sensitive and saver methods such as ultrasound are gaining in importance. We investigated the prevalence, grade and pattern of osteophytes by high resolution ultrasound investigation (US) in a population-based cross-sectional study. Factory workers were recruited at work. 26 finger joints of each participant were examined with US with grading the occurrence of osteophytes in a semiquantitative score ranging 0-3, increasing scores indicated larger osteophytes. 427 participants (mean age 53.5 years, range. 20-79 years) were investigated, resulting in 11,000 scored joints. At least one osteophyte was found in 4,546/11,000 (41.3%) joints or 426/427 (99.8%) participants but grade 2 or 3 osteophytes were seen in only 553 (5.0%) joints. The number of os-teophyte sum score increased with age (0.18/year of age increase, p<0.001). Distal interphalange-al joints (DIP) were predominantly affected with 61%, followed by proximal interphalangeal joints (PIP) with 48%, carpometacarpal joint 1 (CMC1) with 39% and metacarpophalangeal joints (MCP) with 16%. In conclusion, US is a feasible screening tool for osteophytes and HOA. Grade 1 osteophytes are a common finding in the working population when assessed by ultrasound and their prevalence is increasing with age. Prevalence of grade 2 or 3 osteophytes is less common and reflects clini-cal presence of HOA. Follow up investigations are necessary to recognize the predictive rele-vance of early osteophytes.

The spread of micro- (MPs) and nanoplastics (NPs) in the environment has become a significant environmental concern, necessitating effective removal strategies. In this comprehensive scientific review, we examine the use of magnetic nanoparticles (MNPs) as a promising technology for the removal of MPs and NPs from water. We first describe the issue of MPs and NPs and their impact on the environment and human health. Then the fundamental principles of using MNPs for the removal of these pollutants will be presented, emphasizing that MNPs enable selective binding and separation of MPs and NPs from water sources. Furthermore, we provide a short summary of various types of MNPs that have proven effective in the removal of MPs and NPs. These include ferromagnetic nanoparticles, MNPs coated with organic polymers, as well as nanocomposites and magnetic nanostructures. We also review their properties, such as magnetic saturation, size, shape, surface functionalization and stability, and their influence on removal efficiency. Next, we describe different methods of utilizing MNPs for the removal of MPs and NPs. We discuss their advantages, limitations, and potential for further development in detail. In the final part of the review, we provide an overview of existing studies and results demonstrating the effectiveness of using MNPs for the removal of MPs and NPs from water. We also address challenges that need to be overcome, such as nanoparticle optimization, process scalability, and the removal and recycling of nanoparticles after the completion of the process. This comprehensive scientific review offers an extensive insight into the use of MNPs for the removal of MPs and NPs from water. With improved understanding and the development of advanced materials and methods, this technology can play a crucial role in addressing the issue of MPs and NPs and preserving a clean and healthy environment.

Endolysin of bacteriophage T5 (EndoT5) is a Zn2+-dependent and Ca2+-activated L-alanyl-D-glutamate peptidase that hydrolyses peptidoglycans during the destruction of the cell wall of the phage host bacterium Escherichia coli. To elucidate the mechanism of calcium activation, the spatial solution structure of EndoT5 in a complex with two ions - catalytic Zn2+ and regulatory Ca2+ (EndoT5-Zn2+Ca2+, PDB ID: 8P3A) was determined by high-resolution NMR and deposited in the Protein Data Bank. We show that coordination of the Ca2+ ion fix the spatial position of polar amino acid residues D113, N115 and S117. As a result, the intramolecular mobility of extended protein loops (residues 40-70 and 111-132) is significantly reduced compared to the mobility of these loops in the structure of an enzyme containing only a catalytic a Zn2+ ion (EndoT5-Zn2+, PDB ID: 2MXZ). In the stabilized EF-like calcium-binding loop (residues 111-132), the number of van der Waals interactions with amino acid residues of the globular core of the protein increases. The binding of the Ca2+ ion is accompanied by the selection of the functional states of both extended loops of the enzyme (residues 40-70 and 111-132), because of which EndoT5-Zn2+Ca2+ acquires the structural integrity necessary for catalysis. Therefore, the mechanism of activation of L-alanyl-D-glutamate peptidase of bacteriophage T5 by Ca2+ ions involves stabilization of the enzyme molecule in a catalytically active “open” conformation. This work sheds light on the structural grounds of the ion-dependent functional proteoforms of this interesting protein.

Aims: Angiotensin-converting enzyme 2 (ACE2) plays an important role in the entry of coronaviruses into host cells. This paper described how carnosine, a naturally occurring supplement, can be an effective drug candidate for coronavirus disease (COVID-19) on the basis of molecular docking and modeling to host ACE2 co-crystallized with COVID-19 spike protein. Methods: First, the starting point was ACE2 inhibitors and their structure-activity relationship (SAR). Next, chemical similarity (or diversity) and PubMed searches made it possible to repurpose and assess approved or experimental drugs for COVID-19. In parallel, at all stages, authors performed bioactivity scoring to assess potential repurposed inhibitors at ACE2. Finally, investigators performed molecular docking and modeling of the identified drug candidate to host ACE2 co-crystallized with COVID-19 spike protein. Results: Carnosine emerged as the best known drug candidate to match ACE2 inhibitor structure. Preliminary docking was more optimal to ACE2 than the known typical angiotensin-converting enzyme 1 (ACE1) inhibitor (enalapril) and quite comparable to known or presumed ACE2 inhibitors. Viral spike protein elements binding to ACE2 were retained in the best carnosine pose in SwissDock at 1.75 Angstroms. Out of the three main areas of attachment expected to the co-crystallized protein structure, carnosine bind with higher affinity to two compared to the known ACE2 active site. LibDock score was 92.40 for site 3, 90.88 for site 1, and inside the active site 85.49. Conclusion: Carnosine has promising inhibitory interactions with host ACE2 co-crystallized with COVID-19 spike protein and hence could offer potential mitigating effect against current COVID-19 pandemic.

The main aim of this article is to examine the inter-relationships among the top cryptocurrencies on the crypto stock market in the presence and absence of the COVID-19 pandemic. The nine chosen cryptocurrencies are Bitcoin, Ethereum, Ripple, Litecoin, Eos, BitcoinCash, Binance, Stellar, and Tron and their daily closing price data are captured from coinmarketcap over the period from 9/13/2017 to 9/21/2020. To determine the order of integration, the Augmented Dickey-Fuller (ADF), Phillips-Perron (PP), and Kwiatkowski, Phillips, Schmidt, and Shin (KPSS) unit root tests were carried out, and all of the cryptocurrencies were found to be integrated of order 1 i.e. I(1). It has been found that there is strong evidence of a long-run relationship between Bitcoin and altcoins irrespective of whether it is pre-pandemic or pandemic period. Hence these cryptocurrencies' prices and their inter-relationship are resilient to the pandemic.

LIFI was first introduce by Professor Harald Haas on July 2011. Light fidelity (LI-FI) may be a technology which uses light as a medium to travel from one place to a different. It uses Light like Light Emitting Diode (LED) visible radiation Communication (VLC) for data Transferring and Internet connection. LIFI may be a technique which uses light as a medium because it uses light to travel it's 20 times faster than any WIFI within the world. during this paper we speak about things like what's LIFI and the way it's better then WIFI why we want LIFI and What changes did bring LIFI in our Future LIFI. How it'll make IOT devices far better than before The Technique to implement LIFI and also the problem we face of implementation of LIFI

Urban environments face escalating challenges, e.g. due to uncontrolled urbanization, rapid population growth or climate changes, prompting the exploration of sustainable solutions for enhancing urban green spaces (UGS). For this reason, poplars (Populus L.), due to their rapid growth, wide range adaptability to environmental conditions and versatility of use, would have emerged as very promising. This comprehensive review synthesizes current knowledge regarding poplar's application in urban landscapes, emphasizing its multifaceted contributions and benefits. However, challenges arise from the variable lifespans of different poplar cultivars, necessitating strategic management approaches. Selecting cultivars based on growth rates, root system characteristics, and adaptability to urban conditions is pivotal. Adaptive replanting strategies, incorporating species with varying lifespans, offer solutions to maintain continual greenery in urban landscapes. Collaborative efforts between researchers, urban planners, and policymakers are essential for devising comprehensive strategies that maximize benefits while addressing challenges associated with their variable lifespans. In conclusion, harnessing poplar's potential in urban greenery initiatives requires a balanced approach that capitalizes on their benefits while mitigating challenges. Further research and adaptive strategies are crucial for sustained and effective utilization in creating resilient and vibrant urban landscapes.

Carbon dioxide capture and storage (CCS) is highly expected to be mitigating the discharges of carbon dioxide in a surrounding environment. Solvents are an integral part of CCS. So far, several solvents have been explored the interest of meeting the requirements such as accessibility, non-harmfulness, biocompatibility, recyclability, and inexpensiveness. However, most solvents face failure in fulfilling the requirements due to many factors, so, this review paper gives a brief discussion about another category of solvent, an analogue of ionic liquids (ILs) named deep eutectic solvent (DES). Extensive research has been done on DES in recent years because of their various attractive advantages, i.e., non-poisonousness, biodegradability, cheap cost and easy preparation, that make them as a promising green solvent for many industrial procedure and application, for instance, polymer synthesis, biodiesel treatment, green chemistry, electrochemistry etc. Therefore, this manuscript mainly focusses on CO2 capturing through DES in oil and gas field. In addition, the preparation and chemical structures of this novel solvent (DES) is also discussed. Moreover, a detailed study based on experimental solubility of CO2 in DESs is also reported in this article.

Green spaces localized in cities create favourable environmental conditions for Ixodes ricinus, the most widespread and important vector of tick-borne pathogens in Central Europe. In this study, we described the prevalence of Borrelia burgdorferi s.l. and Babesia species found in mono- and double infections among I. ricinus ticks occurring in urban areas of the city of Poznań, west-central Poland. Two tick groups were examined: (i) a group of 1,029 host-seeking ticks (460 nymphs, 289 females, and 280 males and (ii) a group of 1,268 engorged female ticks removed from 1,115 tick-infested animals, dogs and cats. The overall prevalence of B. burgdorferi s.l. found in host-seeking ticks was almost two-fold higher in comparison to ticks derived from pets (8.7 vs. 4.7%, respectively, χ2 test, P = 0.001). Borrelia afzelii and B. garinii were the most prevalent species both in ticks from vegetation (3.7% and 3.7%, respectively) and from pets (3.7% and 0.6%, respectively). Babesia infections were slightly more common in feeding ticks compared to those from vegetation (6.0 vs. 4.7%, respectively), however, the difference was not significant. Three Babesia species including Ba. microti, Ba. venatorum and Ba. canis were identified. Babesia canis and Ba. microti were the most prevalent in host-seeking (2.6% and 1.4%, respectively) and feeding ticks (2.8% and 2.2%, respectively), whereas Ba. venatorum was the rarest piroplasm. All Ba microti obtained sequences (n=42) were identical to Ba. microti genotype "Jena/Germany" that is considered as pathogenic to humans. Furthermore, the sequences of Ba. venatorum (n=17) were identical with those isolated from patients in Italy, Austria and Poland. Altogether, out of 121 Babesia-positive ticks, 19.8% were simultaneously infected with B. burgdorferi s.l. spirochetes. We found similar prevalences of co-infections in host-seeking (1.1%) as well as in feeding ticks (1.0%). In the first group, Ba. canis prevailed in coinfections (73%), mostly with B. afzelii and B. garinii, in the second group, Babesia microti dominated with B. afzelii (92.7%). This is the first finding documenting the co-occurrence of both pathogens in ticks from companion animals. The detection of Ba. microti and Ba. venatorum sequences identical to strains pathogenic to humans as well as predominance of LB spirochetes, B. afzelii and B. garinii in I. ricinus from vegetation and animals indicates that there is a potential risk of acquiring human babesiosis and/or Lyme borreliosis in urban areas of the city of Poznań. Although, the overall risk of encountering a Ba. microti and B. burgdorferi s.l. co-infected tick was low (1.0%), the potential for more severe clinical symptoms and complications deserves notice. A relatively high infection rates of Ba. canis in dog-derived ticks (3.2%) and in host-seeking ticks (2.6%), suggests that I. ricinus could potentially be involved in the circulation of this piroplasm in areas, where the competent vector, Dermacentor reticulatus is absent or rare.

Vaccination against HPV significantly reduced the incidence of HPV-related le-sions worldwide. Considering the increasingly younger age of patients in the gynaecological office and the resulting earlier sexual initiation and potentially contact with the HPV virus, doctors need to have tools to verify the diagnosis. Nowadays, women plan motherhood later, so it is necessary to consider whether sexual treatment in the form of, among others, LEEP-conization may increase the risk of premature birth or difficulty dilating the cervix during labour.For this reason, to avoid overtreatment of LSIL changes, methylation testing may be considered. In patients with histopathologically confirmed HSIL during biopsy and ultimately a lower diagnosis - i.e., LSIL or no signs of atypia - methylation turned out to be a useful tool. We performed Pap-smear, HPV genotyping, punch biopsy, LEEP-conization (if needed) and methylation test in 108 women admitted to the District Public Hospital in Poland. Women with a negative methylation test result were significantly more likely to be ultimately diagnosed with LSIL (p=0.013). This means that in 85.7% of patients with HSIL, major cervical surgery could have been avoided if methylation was negative. Methylation testing, as well as dual-staining and diagnostics detecting mRNA transcripts of highly oncogenic types of HPV, might be used in future in the diagnosis of pre-cancerous conditions, mainly of the cervix, and in HPV-dependent cervical cancer screening. The methylation test may also be used in the diagnosis and identification of lesions within the cervical canal, including those located deep within the frontal crypts, not visible even during a professional colposcopic evaluation of the cervix, as well as within the crypts of the palatine tonsils - in diagnostics of head and neck diseases.

For a graph G, let P(G, λ) be its chromatic polynomial. Two graphs G and H are said to be chromatically equivalent if P(G,λ) = P(H,λ). A graph is said to be chromatically unique if no other graph shares its chromatic polynomial. In this paper, chromatic polynomial of the necklace graph N_n, for n ≥ 2 has been determined. It is further shown that N₃ is chromatically unique.

The perception in pair trading is to recognize two stocks that move together, and their prices will converge to a mean value in future. However, finding the mean-reverted point at which the value of the pair will converge, and optimal boundaries of the trade is not easy. As uncertainty and model misspecifications may lead to losses. To cater for the problems, this study employs the novel entropic approach that utilizes entropy as penalty function for the misspecification of the model. The use of entropy as a measure of risk in pair trading is a nascent idea and this study utilizes daily data for 64 companies listed on PSX for the years 2017, 2018, and 2019, respectively to compute the returns based on the entropic approach. These companies cover the major sectors including Cement, Chemical, Automobile Assembler, Food and Personal Care Products, Oil and Gas Marketing Companies, Oil and Gas Exploration Companies Ltd, Power Generation and Distribution, Refinery and Pharmaceuticals. The returns to these stocks are then evaluated and compared with the Buy and Hold strategy. The results show positive and significant returns from pair trading using an entropic approach.

Areas covered with vegetation play a key role for life on Earth and should be inventoried in a clear and complete manner in order to improve the process of its protection and development. Data showing the amount of greenery in areas most deformed by humans, i.e. urbanized areas, are particularly important. Local governments need to know how to invest theirs limited sources in the quality of life of residents by supplementing the urban fabric with additional vegetation. The article presents a proposal for how to calculate the degree of greenness of cities based on remote sensing data. Additionally, a novel method was proposed to help in planning the development of areas covered with vegetation, taking into account the spatial distribution of the local population. The result was a comprehensive method presenting the actual natural situation in a specific city.

Diesel is consistently a very popular fuel for internal combustion engines. Its consumption in the European Union has been rising over recent years, as has the number of engines increasingly sensitive to fuel contamination. One of the most important parameters affecting diesel quality is water content. Although its exceedances of the standard’s permissible amount are not common, they carry the risk of serious damage to expensive, modern fuel injection systems. Current methods of measuring water content require both specialised personnel and equipment, as well as transporting the sample to a suitable laboratory. The research presented in this paper was aimed at verifying whether it would be possible to test the moisture content of diesel using impedance spectroscopy. Once refined, such measurement method could be used in situ. Analysing the properties of diesel is challenging, mainly because many types of the fuel are sold, the chemical composition of which is always a well-guarded manufacturer’s secret. The experimental results obtained on many types of commercially available diesel show that it is possible to use impedance spectroscopy to estimate the water content of different types of diesel fuel. The measurement accuracy achieved makes it possible to detect approaching or exceeding the permissible water content.

The newly developed friction-interlocking armor unit, called ‘Double cube’ (DC), has been designed to improve the performance of the concrete armor unit used in river/marine structures against currents/waves actions. DC unit, is an octagonal-shaped block, made up of two parts: an upper cube set on a lower base that is either square or octagonal in shape. The innovative design aims to provide a good performance in terms of stability, high tolerance placement with various contact points and ease of placement. DC’s shape and placement enhance the stability by bringing the center of gravity closer to the underlayer and providing a large contact surfaces with surrounding blocks that reduce the chance of extraction and limit movements (rocking, lifting) via "keystone" effect. The characteristics of this new unit provides a relatively high hydraulic stability number for the armor layer (NS=2.9), a favorable hydraulic performance due to energy dissipation from turbulence and aeration, as well as a high roughness coefficient (γf≈0.46) helping to reduce the overtopping.

: Digital communication is becoming an integral component of contemporary society and the use of mobile devices is increasing faster than ever. The function of message communication is becoming more popular as for mobile phone users, a short messaging service (SMS) requires an extremely high level of security. Any SMS that enters a person's smartphone must be considered a private affair, with privacy and security safeguarded. This research study found a novel Deoxyribonucleic acid (DNA) Cryptography method that uses a dynamic DNA sequence table to increase security. Cryptography is a popular approach for ensuring the confidentiality of a message. This paper proposed an Efficient Cryptographic Scheme for SMS (ECSS) algorithm to protect texts received from an Android smartphone. ECSS-based encryption has been identified as a novel method of securing information in the form of DNA molecules that employ DNA strands to conceal the information. This Paper provides the DNA cryptography approach for encrypting and decrypting plain texts in this work. The primary goal of ECSS cryptography is to guarantee secrecy when people transfer data across a network. This paper examines DNA Crypto, the distinction between classical cryptography and DNA Data encryption. An Android-based app is created to perform the proposed technique and the results show that the algorithms produce a consistent encryption result in which the length of the message before encryption is always the same as the length of the message after decryption. The suggested security solution has the potential to greatly improve the security of mobile communication. This Paper also provides experimental results for our chat application performance, such as received text message correctness, cipher text, average encryption time and average decryption time. According to the findings/results of this study, the speed of average encryption and decryption of the description is roughly 0.011 and 0.037 sec and prevents plaintext and dictionary attacks.

The importance of contact with nature for human health was confirmed by numerous research. One of the sometimes neglected fields is the landscape design of hospital premises. This study focuses on the perception and preferences of prospective patients regarding the hospital site design. The methodology included anonymous survey with images and lists of adjectives. The online questionnaire was distributed using e-mails and social media from 4th May to 8th July 2024. The objective was to include all age groups. The results confirm previous studies and demonstrate the importance of landscape architecture design of hospital premises for the well-being of patients. The findings may inform the design of hospital sites.

Clinical and laboratory diagnostics are particularly important in monitoring the internal homeostasis of the body in high-yielding animals, especially in dairy cows, whose metabolism is under constant pressure to obtain high parameters of milk production and reproduction. Knowledge of laboratory test results and relationships based on significant correlations between various milk and blood parameters may be very useful in veterinary diagnostics and helpful in cattle practice in order to protect animal health and the quality of milk production. The aim of the study was to analyze the correlation between selected hematological biomarkers such as white blood corpuscles (WBC), red blood corpuscles (RBC), hemoglobin concentration (HGB), hematocrit (HCT), platelets (PLT), erythrocyte mean corpuscular volume (MCV), mean corpuscular hemoglobin content (MHC), mean corpuscular hemoglobin concentration (MCHC) and selected quantitative-qualitative parameters of cow’s milk such as current milk production, somatic cells count (SCC), colony of bacteria forming units (CFU), milk fat (MF), milk protein (MP), milk lactose (ML), milk solids (S), solids non-fat in milk (SNF), daily milk production. Samples were collected three times at daily intervals from 11 clinically healthy late-lactation dairy cows obtaining 33 sets of test results. This repeated study of cows allowed for obtaining a homogeneous group in order to determine statistical correlations between selected blood and milk parameters. Many significant correlations were found between the examined parameters. In cows, significant positive correlations were recorded between milk production and HGB, HCT, MCV or MHC. Significant negative correlations were also found between SCC and HGB, SCC and HCT, SNF and MCV, SNF and MHC, and between MF and RBC.

We developed an artificial neural network as an air quality model and estimated the scope of the impact of climate change on future (until 2064) summertime trends of hourly Ozone (O3) concentrations at an urban air quality station in Tehran, Iran. Our developed scenarios assume that present-time emissions conditions of O3 precursors will remain constant in the future. Therefore, only the impact of climate change on future O3 concentrations is investigated in this study. GCM projections indicate more favorable climate conditions for O3 formation over the study area in the future: the surface temperature increases over all months of the year, solar radiation increases, and precipitation decreases in future summers, and summertime daily maximum temperature increases about 1.2 ∘C to 3 ∘C until 2064. In the scenario based on present-time O3 conditions in 2012 summer without any axceedances, the summertime exceedance days of 8-hr O3 standard are projected to increase in the future by about 4.2 days in the short term and about 12.3 days in the mid-term. Similarly, in the scenario based on present-time O3 conditions in 2010 summer with 58 days of exceedance from 8-hr O3 standard, exceedances are projected to increase about 4.5 days in the short term and about 14.1 days in the mid-term. Moreover, the number of Unhealthy and Very Unhealthy days in 8-hr AQI is also projected to increase based on pollution scenarios of both summers.

Background: Health Care Workers (HCWs) are at increased risk of acquiring and transmitting COVID-19 infection. Also, they present role models for communities with regards to attitudes towards COVID-19 vaccination. Hence, hesitancy of HCWs towards vaccination can crucially affect the efforts aiming to contain the pandemic. Previously published studies paid little attention to HCWs in Arab countries, which has a population of over 440 million. Objectives: to assess the rates of COVID-19 vaccine hesitancy in Arabic-speaking HCWs residing in and outside the Arab countries, and their perceived barriers towards vaccination. Methods: a cross-sectional study based on an online survey was conducted from 14-Jan 2021 to 29-Jan 2021, targeting Arabic-speaking HCWs from all around the world. Results: the survey recruited 5,708 eligible participants (55.6% males, 44.4% females, age 30.6±10 years) from 21 Arab countries (87.5%) and 54 other countries (12.5%). Our analysis shows a significant rate of vaccine hesitancy among Arabic-speaking HCWs residing in and outside Arab countries (25.8% and 32.8%, respectively). The highest rates of hesitancy were among participants from the west region of the Arab world (Egypt, Morocco, Tunisia, and Algeria). The most cited reasons for hesitancy were concerns about side effects and distrust in vaccine expedited production and healthcare policies. Factors associated with higher hesitancy included age of 30-59, previous or current suspected or confirmed COVID-19, female gender, not knowing the vaccine type authorized in the participant’s country, and not regularly receiving the influenza vaccine. Conclusion: this is the first large-scale, multinational, post-vaccine-availability study on COVID-19 vaccine hesitancy among HCWs. It reveals high rates of hesitancy among Arab-speaking HCWs. Unless addressed properly, this hesitancy can impede the efforts for achieving widespread vaccination and collective immunity.

Several specific types of generalized compactness of generalized topological spaces have been defined, investigated and related to compactness in ordinary topological spaces from time to time in the literature of topological spaces. Our recent research in the field of a new class of generalized compactness in a generalized topological space is reported herein as a starting point for more generalized classes.

Several specific types of ordinary and generalized connectedness in a generalized topological space have been defined and investigated for various purposes from time to time in the literature of topological spaces. Our recent research in the field of a new type of generalized connectedness in a generalized topological space is reported herein as a starting point for more generalized types.

Several specific types of generalized maps of a generalized topological space have been defined and investigated for various purposes from time to time in the literature of topological spaces. Our recent research in the field of a new class of generalized maps of a generalized topological space is reported herein as a starting point for more generalized classes.

Several specific types of generalized sets of a generalized topological space have been defined and investigated for various purposes from time to time in the literature of topological spaces. Our recent research in the field of a new class of generalized sets of a generalized topological space is reported herein as a starting point for more generalized classes.

The study presents an overview of how phase change materials (PCMs) can enhance the freeze-thaw resistance of concrete pavement and mitigate urban heat island (UHI) effects. It discusses various types of PCMs and methods for incorporating them into concrete pavement, along with the mechanical properties of concrete pavement and its compressive strength when using different PCMs. Also, a Python script was used to simulate the effect of PCMs on the surface temperature of concrete pavement in different cold regions. Previous research suggests that porous aggregates, microencapsulation, and pipelines containing liquid PCM are the most common methods for incorporating PCMs into concrete pavement. The researchers reported that using PCMs in concrete pavement results in beneficial thermal properties, indicating that PCM concrete pavement has the potential for anti-freezing and UHI applications. Additionally, this study's simulation results suggest that local climate conditions should guide the selection of PCM materials.

The SARS-CoV-2 was confirmed to cause the regional outbreak of coronavirus disease 2019 (COVID-19) in Wuhan, China. The 3C-like protease (3CL^pro), an essential enzyme for viral replication, is a valid target to compacts SARS-CoV and MERS-CoV. In this research, an integrated library consisting of 1000 compounds from Asinex Focused Covalent (AFCL) library and 16 FDA-approved protease inhibitors were screened against SARS-CoV-2 3CL^pro. Top compounds with significant docking scores and making stable interactions with catalytic dyad residues were obtained. The screening results in identification of compound 621 from AFCL library as well as Paritaprevir and Simeprevir from FDA-approved protease inhibitors as potential inhibitors of SARS-CoV-2 3CL^pro. The mechanism and dynamic stability of binding between the identified compounds and SARS-CoV-2 3CL^pro were characterized using 50 nanoseconds (ns) molecular dynamic (MD) simulation approach. The identified compounds are potential inhibitors worthy of further development as SARS-CoV-2 3CLpro inhibitors/drugs. Importantly, the identified FDA-approved therapeutics could be ready for clinical trials to treat infected patients and help to curb the COVID-19.

Innovation is rapidly growing and affecting various industries, including hydrocarbon processing. This study aims to conduct a comprehensive and organized review of the literature on innovation ecosystems and their performance. It will examine existing definitions of innovation ecosystems and related concepts and identify metrics and indicators for measuring innovation and entrepreneurial ecosystems. The term "innovation ecosystem" has gained considerable attention from scholars and practitioners over the past fifteen years. Despite the proliferation of research in this area, there are concerns about its fragmented knowledge base. While previous reviews have highlighted the theoretical connections between innovation ecosystems and related concepts, there is still a need for a more comprehensive understanding of the current state of innovation ecosystem research. The study used a systematic literature review approach that combines bibliographic coupling and content analysis methods, drawing on over 100 studies to identify five streams of current innovation ecosystem research: technology innovation, platform innovation ecosystems, regional development, innovation ecosystem conceptualization and theorization, and entrepreneurship and innovation. The study's contribution lies in decoding the intellectual structure of current innovation ecosystem research and providing targeted recommendations for future research.

The complexity of plastic polymers and even more so of additives has increased enormously in recent years. This makes the high-quality recycling of mixed plastic waste considerably more difficult. Some additives have now been strictly regulated or even completely banned for good reasons ('legacy additives'). Material or mechanical recycling generally utilises old plastics that still contain these substances. Consequently, products that are manufactured using such recyclates are contaminated with these harmful substances. We therefore recommend avoiding the use of these recyclates for products with intensive contact with consumers until further notice. We also show that the climate policy challenges for the plastics (and chemical) industry necessitate a defossilisation ('feedstock change'). This turnaround can only succeed if solely high-quality recycling takes place in future; recyclates should primarily replace virgin plastics. This can only work if used plastics with a high degree of homogeneity and known formulation are collected separately, as is already the case today with PET bottles. In this context, we would like to point out inconsistencies in the current legislation on the European emissions trading system.

This paper proposes a game-theoretic framework for quantifying effects of strategic bidding behavior of load aggregators (LAs) on wholesale electricity market equilibrium. The independent system operator (ISO) employs double-sided auction design to settle transactions in the wholesale electricity market. Generating companies (GENCOs) and LAs submit their bids to the ISO in the economic model of supply function equilibrium. Under the smart grid paradigm, a LA participates in the electricity market on behalf of end-consumers to minimize their total payment for purchasing electricity. In this paper, bi-level programming (BLP) method is employed to determine optimal bidding strategy of self-interested market participants. In the upper level, the profit of intended market participant is maximized and in the lower level, the ISO clears the market via a bid-based security constrained economic dispatch (SCED). Also, competition of GENCOs and LAs is modeled as a non-cooperative game. To examine the effects of strategic bidding behavior of LAs on market equilibrium, the proposed model is applied to the IEEE 9-bus and the IEEE 30-bus test systems. According to numerical results, to allow the LAs to behave strategically along with the GENCOs makes the former better off and the latter worse off, while the net effect of this on total social welfare turns out to be case-contingent.

(1) Background: The significant progress observed over last two decades in coherent beam combining (CBC) technology has mainly focused on its applications in high-energy physics and laser weapons. This work provides insight into the basic principles of CBC and the search for an alternative, namely optical angular momentum (OAM) generation using CBC; (2) Methods: The semi-analytical model based on the paraxial wave equation explored generating OAM-CBC beams by manipulating the tilts and phases of CBC (T&amp;P-CBC) of hexagonal architecture; (3) Results: The specially arranged T&amp;P-CBC shows typical properties of OAM, such as annular profiles for the zero diffraction order and 1-st order replicas in the far field and correlation coefficients of 1% between different OAM-CBC fields; (4) Conclusions: The differences between classical OAM beams and OAM-CBC are substantial due to hexagonal lattice properties. Moreover, applications in free space optical communications are feasible as T&amp;P CBC fulfills the main conditions and requirements for OAM generation.

Natural cytokinins are a promising group of cytoprotective and anti-tumor agents. In this research, we synthesized a set of novel cytokinin analogs with alkyl substituents at various positions of the aromatic moiety, as well as with oxygen-containing groups, and tested their antiproliferative activity in MDA-MB-231, A-375, and U-87 MG cell lines, and cytoprotective properties in H2O2 and CoCl2 models. Two amino-linked compounds were anti-proliferative with the ability to act synergistically with doxorubicin, and two carbamate-based ones were cytoprotective. According to the molecular docking data, anti-proliferation was based on the A2AR and APRT inhibition and cytoprotection on the CDK2 inhibition. The obtained results are promising for the development of novel anti-cancer therapeutics.

Nuclear export of viral mRNAs, is an essential step in the HIV replication cycle. This role is played by a small regulatory protein of HIV-1 called Rev.The N-terminal region of Rev contains an arginine-rich sequence. The arginine-rich motif (ARM) is located between amino acids 38-50 and forms an alpha-helical secondary structure. Expression of the structural proteins of human immunodeficiency virus type 1 requires the direct interaction of multiple copies of the viral Rev protein with its highly structured RNA target sequence, the Rev Response element (RRE). The major viral proteins are not produced if this transport of RNA is stopped. Therefore, knowledge of Rev structure is essential for understanding of its cooperative binding to the RRE, for understanding the mechanism of HIV infection and for the development of antiviral drugs that interfere with Rev’s essential functions and for acknowledgment of good candidate drugs for treatment of AIDS. To understand how REV interact with RRE element of HIV-RNA and its formation of oligomeric complex it is better to characterize the domain wise structure of REV with regard in function of each domain. Due to lack of structural data on Rev no single compound is reported as inhibitor of REV expect antiviral drugs. Identification of a high-affinity RNA-binding site for the human immunodeficiency virus type 1 Rev Protein is much more important. The ARM is a highly specific sequence which allows for the multimerization of Rev and also binding of REV with RNA. Here we are first time exploring the structural characteristics of REV protein both in free form and in complex with RNA at domain function level especially explore the role of ARM motif in REV HIV-1 protein as RNA binding sites by molecular dynamics (MD) simulation and homology modeling studies. Results indicate that the arginine-rich motif (ARM) is crucial in stability of this complex. The residues ARG38, 39, 41, 43, 44, 48, 50, and ASN40 are most interacting with nucleobases of RRE in Crystal structure of Rev and Rev-response-element RNA complex. Our study plays a major role in elaboration of binding of RNA with REV and pave the way for further investigation for therapeutically agent for HIV.

Several specific types of ordinary and generalized separation axioms of a generalized topological space have been defined and investigated for various purposes from time to time in the literature of topological spaces. Our recent research in the field of a new class of generalized separation axioms of a generalized topological space is reported herein as a starting point for more generalized classes.

Developing countries like Pakistan is among those where lack of adoption to science and technology advancement is a major constraint for Satellite Remote Sensing use in crops and land use land cover digital information generation. Exponential rise in country population, increased food demand, limiting natural resources coupled with migration of rural community to urban areas had further led to skewed official statistics. This study is an attempt to demonstrate the possible use of freely available satellite data like Landsat8 under complex cropping system of Okara district of Punjab, Pakistan. An Integrated approach has been developed for the satellite data based crops and land use/cover spatial area estimation. The resultant quality was found above 96% with Kappa statistics of 0.95. Land utilization statistics provided detail information about cropping patterns as well as land use land cover status. Rice was recorded as most dominating crop in term of cultivation area of around 0.165 million ha followed by autumn maize 0.074 million ha, Fallow crop fields 0.067 million ha and Sorghum 0.047 million ha. Other minor crops observed were potato, fodder and cotton being cultivated on less than 0.010 million ha. Population settlements were observed over an area of around 0.081 million ha of land.

Optimizing the nitrogen (N) timings and rate can improve nutrient uptake, and nutrient-efficiencies, especially of N in wheat under the changing climate scenario. Climatic stress in the form of high temperature and drought resulted in the decreased crop physiology and, ultimately, grain yield. Taking the example of rainfed wheat, we quantified the impact of N application rates as full and split-dose at three variable sites of rainfed Pothwar, Pakistan by conducting field experiments for two years (2013-14 and 201-15). Treatments include, T1 = Control (No fertilizer applied), full dose of N applied at the time of crop sowing, i.e. T2 = 50 kg N ha^-1, T3 = 100 kg N ha^-1 and T4 = 150 kg N ha^-1 and split application of N at different timings during different stages of the crop called as split application of N, i.e. T5: Application of 50 kg N ha^-1 (15 kg N ha^-1 (Sowing) : 20 kg N ha^-1 (Tillering) :15 kg N ha^-1 (Anthesis), T6: Application of 100 kg N ha^-1 (30 kg N ha^-1 (Sowing): 40 kg N ha^-1 (Tillering) : 30 kg N ha^-1 (Anthesis) and T7: Application of 150 kg N ha^-1(45 kg N ha^-1 (Sowing) : 60 kg N ha^-1 (Tillering) : 45 kg N ha^-1 (Anthesis). Three study sites include viz. Islamabad (High rainfall with optimum temperature), University Research Farm (URF)-Koont (Medium rainfall with moderate temperature), and Talagang (low rainfall with high temperature). Results showed that the highest stomatal conductance (0.80 mole m^-2 sec^-1), net photosynthetic rate (20.07 μmole m^-2s^-1), transpiration rate (9.58 mmole m^-2s^-1), intercellular CO2 concentration (329.25 μmole CO₂ mol^-1 air), SPAD values (58.86 %) and proline contents (35.42 μg g^-1) were obtained for split application of N (T6 = Split N100) compared to control and full dose of N treatments. Among sites, these physiological traits remained highest at Islamabad and lowest at Talagang, while among years, maximum values of the measured parameters were obtained in 2013-14. A similar trend was observed for crop total N, N efficiencies, and agronomic traits of the crop. Our results suggest that optimum N application rate and its suitable timings can help to harvest real benefits of N as in our findings, split dose resulted in the maximum performance of the crop from physiological parameters to the agronomic traits of the rainfed wheat crop.

Cricket, the most popular sports in the world to chase by the fans. Many cricket fans are interested in analyzing the elements and activities that affect the outcomes of matches. Machine learning in sports analytics is a relatively new topic in computer science. The purpose of this survey is to anticipate the outcome of a PSL champion team and build a winning strategy. Machine learning (ML) has exhibited favorable outcomes in a variety of sectors for diverse prediction using classification, regression, and so on, and is proven to be accurate. The innovative frameworks based on ML have the ability to learn from previous experiences. The cricket pitch is the most important aspect, alongside home game an edge, coin toss, innings of play, day/night match, physical conditioning, and dynamic plans, among other things. The dataset from previously ESPN Cricifno was used for this purpose. Recent classification approaches including, Random Forest, Gradient Boost, Deep Neural Networks used to conduct a comparative analysis based on their results and performances, as well as team strategies.

This report aimed to know the performance of local mineral-based composite ceramic. The materials used consist of Indonesian local minerals, which are jarosite and manganite minerals as sources of oxide iron and Mangan. The materials were synthesized using the precipitation method, whereas composite ceramic was fabricated using a screen printing method and fired at 600 oC using a furnace. The results of the characterizations indicate that the sample forms three phases on diffraction peaks. The differences in the resistance values in ambient and ethanol environments indicate that the sample has very different responses. The high porosity of the sample greatly support the gas adsorption process. Thus, the sample has a high level of sensitivity. With the above characteristics, the composite ceramic which was fabricated has the potential to be applied to gas sensors, especially ethanol gas sensors.

This study presents a comprehensive investigation of entropy generation during natural convection in a porous medium with Casson fluid. The governing equations, including the momentum, energy, and entropy balance equations, are solved numerically using finite element method. Through the analysis, various parameters affecting entropy generation are investigated, such as the Casson fluid parameter, Radiation, Prandtl number, and Rayleigh number. The results indicate that the Casson fluid parameter significantly influences the flow and heat transfer characteristics, while the Darcy number and Rayleigh number control the intensity of natural convection. Moreover, the Prandtl number determines the relative significance of heat transfer compared to viscous effects.

In this unprecedented era of computer-supported and distance learning, it is critical to rethink the way students are supported through vital skills like self-regulation and peer collaboration. A variety of digital media has emerged, allowing learners autonomy while requiring the ability to effectively regulate different components of the educational process for long-term academic success. We reviewed collaboration, communication, and self-regulation in digital learning environments as part of online learning. We discussed how these abilities are reflected in highly cited content. High-impact factor studies were identified using advanced software Herzing Publish or Perish to retrieve highly cited research publications metrics. The search resulted in 272 records from 2010 to 2022, 192 duplicates were identified to remove and 48 JCR articles were shortlisted for review. We examined and reflected on sufficient connections to make firm judgments about correlations of concepts. The review identified prominent themes surfaced in the high impact factor academic publication e.g., digital learning environment, interaction, engagement, feedback, self-efficacy, motivation, meta-cognition, achievement, technology, blended learning, and orientation of ICT. Many studies support different features of SRL &amp; PCL through different tools, access to educators or feedback, encouragement, and through peers. However, all of them discuss the processes that students use to self-regulate learning in these situations. It is suggested to examine whether the effectiveness of certain SRL processes varies by online learning mode.

Background and Objectives: Pregnant women living with HIV (WLHIV) are likely to be traumatized and stigmatized, hindering their ARV treatment uptake and leading to the spread of the virus and low quality of life. Previous research has examined HIV stigma reduction interventions, yet syntheses of such evidence among pregnant WLHIV have not been presented. Our literature synthesis aims to identify effective HIV stigma reduction interventions and create an emergent pragmatic framework for future education, research, and clinical practice. Methods: Mixed Systematic-Realist Review (MSRR), an innovative approach developed by our team, was applied to synthesize studies on stigma reduction interventions among pregnant WLHIV. Combining the principles and processes of systematic review and realist review, MSRR is a 5-step evidence-based, context-bound strategy, starting from topic identification through pragmatic framework creation. Results: Using pre-determined inclusion criteria to search for relevant articles in five databases, we identified 238 articles and then reduced them to four after using pre-determined exclusion criteria. All four studies were conducted in Sub-Saharan countries with adult pregnant WLHIV (n = 824). Multicomponent stigma reduction interventions in the literature yielded positive outcomes (de-creased stigma and lessened depressive symptoms). The emergent framework, depicted in a diagram format, was based on the input-process-output framework. Conclusions: The novel MSRR adopts the strengths of both systematic and realist reviews and can be applied across diverse populations. Additionally, the results and emergent pragmatic framework can be used for HIV stigma reduction education and to advance research and clinical practice.

This study investigated the prevalence and severity of depression, anxiety, and stress and determined the association between various factors, social support, and depression and anxiety among university healthcare workers in Malaysia after the government lifted the movement control order (MCO) put in place to curb the coronavirus disease 2019 (COVID-19) pandemic. This online, cross-sectional survey recruited 399 participants from two university hospitals, and they were administered a self-reported questionnaire on demographic, personal, and clinical characteristics; COVID-19-related stressors; and coping. In addition, they completed the Multidimensional Scale of Perceived Social Support (MSPSS) to measure perceived social support, as well as the 21-item Depression, Anxiety, and Stress Scale (DASS-21) to assess depression, anxiety, and stress. We found that the prevalence of depression, anxiety, and stress were 21.8%, 31.6%, and 29.1%, respectively. Participants with moderate to extremely severe depression, anxiety, and stress made up 13.3%, 25.8%, and 8.1% of the sample, respectively. Being single or divorced, fear of frequent exposure to COVID-19 patients, those who agreed that their area of living had a high prevalence of COVID-19 cases, and uncertainty regarding the prevalence of COVID-19 cases in the area of living were associated with higher odds of depression and anxiety. Conversely, having more than three children and greater perceived friend support were associated with lower odds of depression and anxiety. The prevalence of depression, anxiety, and stress remained elevated even after the MCO was lifted.

The contextual and risk perception of climate change plays a critical role in an individual’s decision-making process. It could also help people to respond appropriately to the consequences of global climate change and eventually take necessary adaptation actions. However, the perceptions of climate change are often gendered and vary among men and women. Therefore, this study explores different perceptions of climate change and its local adaptation options among ultra-poor vulnerable women, particularly in highly vulnerable flood-prone regions of Bangladesh. The research followed an empirical research methodology to collect primary and secondary information using qualitative and quantitative research tools. The study findings reveal that climate change perceptions at the individual level are relatively low (63%). Still, they have been observing significant changes in various climatic variables over the past 30 years. Moreover, this study identified some major adaptation options such as plinth raising (100%), livestock rearing (100%), homestead gardening (82%), seasonal migration (82%), and using indigenous knowledge (69%), and so on to tackle the adverse impacts of climate change-induced extreme events including flooding at the local level. For implementing these adaptation measures, the respondents spent a significant amount of financial resources from individual sources in the study area. Structural Equation Modeling (SEM) is used in addition to the statistical analyses to understand any connections between the climate change perceptions and other variables associated with the community under study. The SEM result shows that climate change will be a long–term problem, which offers a strong predictor in this model, considering standardized regression weight β= 0.56. It means, despite inadequate knowledge on climate change of the respondent’s, climate change is occurring and becoming the worst factor limiting cultural, economic, and environmental development in the study area.

Land Surface Temperature (LST) is a basic parameter in energy exchange between the land and atmosphere and is frequently used in many sciences such as climatology, hydrology, agriculture, ecology, etc. LST time series data have usually deficient, missing and unacceptable data caused by the presence of clouds in images, presence of dust in atmosphere and sensor failure. In this study, Singular Spectrum Analysis (SSA) algorithm was used to resolve the problem of missing and outlier data caused by cloud cover. The region studied in the present research included an image frame of MODIS with horizontal number 22 and vertical number 05 (h22v05). This image involved a large part of Iran and Turkmenistan and Caspian Sea. In this study, MODIS LST sensor (MOD11A1) was used during 2015 with 1×1 Km spatial resolution and day/night LST data (daily temporal resolution). The results of the data quality showed that cloud cover caused 36.37% of missing data in the studied time series with 730 day/night LST images. Further, the results of SSA algorithm in reconstruction of LST images indicated the Root Mean Square Error (RMSE) of 2.95 K between the original and reconstructed data in LST time series in the study region. In general, the findings showed that SSA algorithm using spatio-temporal interpolation in LST time series can be effectively used to resolve the problem of missing data caused by cloud cover.

Rice (Oryza sativa L.) processing yields ~60 million metric tons of bran annually. Rice genes producing bran metabolites of nutritional and human health importance were assessed across 17 diverse cultivars from seven countries using non-targeted metabolomics and resulted in 378-430 metabolites. Gambiaka cultivar had the highest number and Njavara had the lowest number of metabolites. The 71 rice bran compounds of significant variation by cultivar included 21 amino acids, seven carbohydrates, two metabolites from cofactors and vitamins, 33 lipids, six nucleotides, and two secondary metabolites. Tryptophan, -ketoglutarate, γ-tocopherol/β-tocopherol and γ-tocotrienol are example bran metabolites with extensive cultivar variation and genetic information. 34 rice bran components that varied between cultivars linked to 535 putative biosynthetic genes using to the OryzaCyc 4.0, Plant Metabolic Network database. Rice genes responsible for bran composition with animal and human health importance is available for rice breeding programs to utilize in crop improvement.

Solid-phase joining is a technique used to fuse two materials by applying heat and pressure, causing plastic deformation without reaching the melting point. This method is applicable for similar and dissimilar materials, including metals, polymers, and ceramics, without the need for filler material. Among the various methods, Friction Stir Welding (FSW) is preferred for joining dissimilar materials due to its solid-state process, which enhances mechanical properties, metallurgical compatibility, and reduces distortion. FSW is particularly effective for materials with significant differences in melting points. The current project focuses on assessing the strength and mechanical properties of FSW joints between aluminum and polymer-based composites. FSW was selected for its ability to produce fine-grained, strong welds free from fusion-related defects such as porosity and cracks. Applications in sectors like automotive, aerospace, and shipbuilding are explored, with impact, hardness, and tensile tests conducted to evaluate joint performance. This comprehensive study includes literature review, fabrication, testing, and tool design to ensure a thorough understanding of dissimilar joint properties.

Research on titanium oxo complexes (TOCs) are usually focused on their structure and photocatalytic properties. Findings from these investigations spurred our interest in exploring also their potential biological activities. In this study, we focused on the synthesis and structure of a compound with the general formula [Ti8O2(OiPr)20(man)4] (1), which was isolated from the reaction mixture of titanium(IV) isopropoxide with mandelic acid (Hman) in a molar ratio of 4:1. The structure (1) was determined using single-crystal X-ray diffraction, while spectroscopic studies provided insights into its physicochemical properties. To assess the potential practical applications of (1), its microcrystals were incorporated into a polymethyl methacrylate (PMMA) matrix, yielding composite materials of the type PMMA + (1) (2 wt.%, 5 wt.%, 10 wt.%, and 20 wt.%). The next stage of our research involved the antimicrobial activity evaluation of the obtained materials. Investigations carried out demonstrated antimicrobial activity of pure (1) and its composites (PMMA + (1)) against both Gram-positive and Gram-negative strains. Furthermore, MTT tests conducted on the L929 murine fibroblast cell line confirmed the lack of cytotoxicity of these composites. Our study identified (1) as a promising antimicrobial agent, also for producing composite coatings.

In this research, a screw-barrel system was designed and implemented, coupled with material extrusion, to print high-melt-temperature thermoplastic materials. The aim was to integrate two methods: the direct extrusion of thermoplastic polymer pellets with material extrusion,utilize various polymers in the form of pellets, especially high melt temperature ones, instead of traditional filaments. This addresses one of the significant challenges in filament preparation for various materials that are not readily available in the market or nearly impossible to fabricate (such as highly filled plastics). First, the screw-barrel assembly performance and factors influencing feed rate were evaluated. Subsequently, specimens were printed with polyether ether ketone (PEEK), an advanced plastic material known for its outstanding mechanical properties, high-temperature tolerance, and broad applications in various sectors, such as medical. Additionally, the material was reinforced with 2.5% continuous glass fibers while printing, which presented a novel product. Upon comparing theoretical values with experimental data from the tensile testing, a notable observation emerged: the inclusion of 2.5% glass fibers led to an approximate 43% increase in the tensile strength of the material. Furthermore, SEM images provided visual evidence of satisfactory adhesion between layers and fibers.

Momordica charantia is a plant of the Cucurbitaceae family which is known as bitter gourd and grows widely in tropical and subtropical regions of the world. The various properties of bitter gourd are closely related to the substances or compounds they contain. Bitter gourd contains many secondary metabolites including alkaloids, terpenoids, steroids and flavonoids. These chemical compounds are spread in several parts of the plant such as roots, stems, leaves, and fruit. Apart from containing several organic compounds, bitter melon also contains the phytohormone gibberellin which is quite potential and useful as a biostimulant. The aim of the research was to isolate, purify, and determine the content of gibberellin (GA-3) contained in bitter gourd (M. charantia), and to determine its effect on the vegetative and generative growth of soybean plants, as well as the effect of GA-3 application on the nutritional content of soybean seeds. resulting from. Apart from that, it was also observed the effect of GA-3 application on the chlorophyll content of soybean plants, as well as the activity of the alpha-amylase enzyme in treated soybean seeds. The process of isolation and purification of GA-3 was carried out by thin layer chromatography and adsorption column chromatography on Silica Gel G-60. Characterization of GA-3 was carried out by Reversed-Phase High-Performance Liquid Chromatography (RP-HPLC), Fourier Transform Infrared (FT-IR), and Mass Spectroscopy (MS). RP-HPLC and FTIR results from gibberellin GA-3 isolates showed retention times and wave numbers that were relatively the same as GA-3 standards. From the results of the study it was found that the content of the gibberellin GA-3 hormone in bitter gourd was 4.12 mg/g dry weight. The GA-3 isolate had a significant effect on the growth of soybean plants in both the vegetative and generative phases for each parameter observed compared to the control and 1% NPK fertilizer. The protein content in soybean seeds was 38.17%. The chlorophyll content at the end of the vegetative and generative phases were 33.34 and 11.5 CCI, respectively. The addition of GA-3 isolate increased the activity of the α-amylase enzyme in soybean seeds compared to the control with an average of 271.65 U/mL.

On the basis of a stocktaking on PVC in Europe and on a current ECHA investigation report, we conclude that regulatory action at EU level is recommended. We support ECHA's regulatory proposals in the main, but come to a more comprehensive proposal for the phasing-out of PVC beyond the area of electrical installations. PVC stored in buildings and infrastructure to date amounts to around 160 million tonnes ("stock") and this mass is still increasing. Parts from the stock have entered the waste management sector for years and their mass is gradually increasing. Neither material, chemical nor energy recovery will be able to absorb these incoming quantities. We therefore come to the conclusion that PVC should be collected separately and disposed of in an infrastructure designed for chlorine recovery. The required infrastructure should be set up and operated by the chemical industry. So, PVC will lose its status as a particularly economically favorable plastic. In view of the constantly increasing stock, we recommend phasing-out the production of virgin PVC as early as possible. In our opinion, this would also be justifiable because the effects of the closed loop recycling announced by VinylPlus ('Vinyl') would go in the same direction.

The spatiotemporal variability of vegetation in the Middle East was investigated for the period 2001–2019 using the Moderate Resolution Imaging Spectroradiometer (MODIS) 16-day/500 m composites of the Normalized Difference Vegetation Index (NDVI; MOD13A1). The results reveal a strong increase in the NDVI coverage in the Middle East during the study period (R = 0.75, p-value = 0.05). In Egypt, the annual coverage exhibits the strongest positive trend (R = 0.99, p-value = 0.05). In Turkey, both the vegetation coverage and density increased from 2001 to 2019, which can be attributed to the construction of some of the biggest dams in the Middle East, such as the Atatürk and Ilisu dams. Significant increases in the annual coverage and maximum and average NDVI in Saudi Arabia are due to farming in the northern part of the country for which groundwater and desalinated seawater are used. The results of this study suggest that the main factors affecting the vegetation coverage in the Middle East are governmental policies. These policies can have a positive effect on the vegetation coverage in some countries such as Egypt, Saudi Arabia, Qatar, Kuwait, Iran, and Turkey.

Abstract: Heavy metals (HMs) contamination is one of the main among abiotic factors affecting crop productivity and also threatens human health via consuming metal contaminated crops as a food source. Over the past few years, HMs have drawn a lot of attention due to their increased use for commercial purposes and their harmful effects on plants and other life forms, thus threatening human survival. However, in recent years, several methods have been adopted to combat the harsh effects of HMs. After phytohormones, use of mineral nutrients such as selenium (Se) in the prevention of HM stress has been explored by the researchers more recently. Selenium is an important micronutrient widely known for its antioxidant properties in both plants and animals. Exogenous Se inhibits metal uptake and its translocation and also improves the antioxidant system, thus imparts resistance to HM toxicity in plants. Moreover, Se also regulates the production of various osmolytes in cells that helps in developing cell osmolarity. Selenium also induces the production of different types of secondary metabolites (SMs) that are also involved in plant's secondary defense mechanisms to different stresses. Uptake of mineral nutrients is a vital process for plant growth and development, which is also positively correlated with Se under metalloid toxicity. However, in order to understand the exact mechanism of Se in HM tolerance, different metabolic processes stimulated by Se and their pathways need to be explored. Hence, this review focuses on the role of Se on nutritional status, antioxidants metabolism, interaction with phytohormones and its role in the regulation of various genes involved in Se induced HM tolerance. Thus, this study will help researchers in the future for the improvement of HM tolerance via Se application in plants.

Imaging of the ocular vasculature can provide new insights into the pathophysiology of ocular diseases. This study proposes a novel high-frequency super-resolution ultrasound localization microscopy (SRULM) technique and evaluates its ability to measure in vivo perfusion changes in the rat eye at elevated intraocular pressure (IOP). A 38.4 MHz center frequency linear array transducer on a VisualSonics Vevo F2 imaging platform was used to collect high frame rate (1 kHz) radiofrequency data of the posterior rat eye following systemic microbubble contrast injection. Following clutter and spatiotemporal non-local means filtering, individual microbubbles were localized and tracked. The microbubble tracks were accumulated over 10,000 frames to generate vascular images quantifying perfusion velocity and direction. Experiments were performed using physiologic relevant controlled flow states for algorithm validation and subsequently performed in vivo on the rat eye at 10 mm Hg IOP increments from 10 to 60 mm Hg. The posterior vasculature of the rat eye, including the ophthalmic artery, long posterior ciliary arteries and their branches, central retinal artery and retinal arterioles and venules were successfully visualized, and velocities quantified at each IOP level. Significant reductions in arterial flow were measured as IOP was elevated. High-frequency SRULM can be used to visualize and quantify perfusion velocity of the rat eye in both the retrobulbar and intraocular vasculature simultaneously. The ability to detect ocular perfusion changes throughout the depth of the eye may help elucidate the role ischemia has in the pathophysiology of ocular diseases such as glaucoma.

Reservoirs created by damming rivers significantly modify the environment and problems may arise: the storage of nutrients and organic matter in reservoirs often leads to decreased water quality due to eutrophication. Reservoirs built on lowland rivers are exposed to significant nutrient loads, often leading to eutrophication. In this article, the Sulejów Reservoir, in Central Poland, was the subject of the research, which focused on the use of Sentinel-2 remote sensing data to detect phytoplankton blooms, and on understanding the pattern of wind-driven surface currents using the CCHE2D model (a depth-averaged hydrodynamic model). The calculation of the total phosphorus load has shown that the reservoir mainly acts as nutrient storage. Still, during the low flow and intensive phytoplankton bloom, it can be a source of nutrients. The distribution of phytoplankton bloom on the Sulejów Reservoir was documented using eight Sentinel-2 satellite images from the vegetation season of 2020 and the Normalized Difference Chlorophyll Index (NDCl). Coupling remote sensing data and numerical modelling helps to interpret the hydrodynamic model results and understand nutrients and sediment dynamics within the reservoir. Hydrodynamic modelling combined with remote sensing data can be a valuable tool for selecting appropriate locations for water quality measurements at monitoring stations.

In this study, an optimized multi-material system was designed and developed to print samples in various applications, including biomedical fields (e.g., mandibular bone loss). To improve the mechanical and biological properties of scaffolds utilized for dental bone loss applications, a multi-material setup was devised, which employs digital light processing technology. This setup consists of a linear system comprising two resin vats and one ultrasonic cleaning tank, enabling the integration of diverse materials and structures to optimize the composition of the scaffold. This approach was used to print multi-material PLLA scaffolds containing 20 wt.%. HA on the interior side, and PLLA containing 1 wt.% GO on the exterior surface of the scaffold, which were evaluated mechanically and biologically after printing. The scaffold was designed using a triply periodic minimal surface (TPMS) lattice structure, which is known to possess favorable mechanical and biological properties. Various multi-material samples were successfully printed and evaluated to illustrate the multiple-material setup's potential for ensuring proper function, cleaning, and adequate interface bonding. By numerically evaluating several TMPS structures, a novel Gyroid TPMS scaffold with a nominal porosity of 50% was developed and validated experimentally. The biological properties of the scaffolds were also evaluated, including surface morphology, (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) MTT assay, and cell adhesion. Based on the results, multi-material components with the least contaminations with suitable mechanical and biological properties were successfully printed. By combining PLLA-HA and PLLA-GO, this innovative technique holds tremendous potential for enhancing the effectiveness of regenerative procedures in the field of dentistry.

Background: Delivery of quality family planning services depends on availability of skilled health care providers, which is often a challenge in Low- and middle-income countries. This study evaluates the effects of a targeted training program on family planning services delivered by the Lady Health Workers (LHWs) in six districts of Punjab, Pakistan. The primary goal was to enhance the quality and accessibility of family planning services, recognizing the pivotal role of LHWs in community health. Methods: Using a robust panel data difference-in-differences (DiD) approach, we analyzed the electronic medical records (EMR) of 1,410 LHWs over a nine-month period. This timeframe in-cluded both pre-training (July to December 2022) and post-training (April to June 2023) phases. Our assessment focused on the impact of training on five outcome variables: the number of follow-up clients, the number of Intrauterine Contraceptive Device (IUCD) clients, the number of condom clients, the number of modern method clients, and the number of injection clients. We also con-sidered control variables such as LHW age, LHW education, the number of eligible couples in each LHW's catchment area, and a categorical variable for the districts. Results: The positive and statistically significant (p<0.05) coefficients across various service cat-egories – Follow Up Clients [Coeff: 1.00, CI: (0.30 - 1.70)], IUCD Clients [Coeff: 0.23, CI: (-0.01 - 0.46)], Condom Clients [Coeff: 1.41, CI: (0.97 – 1.86)], Modern Method Clients [Coeff: 1.82, CI: (0.96 – 2.68)], and Injection Clients [Coeff: 0.32, CI: (0.14 – 0.50)]. These findings indicate enhanced productivity among LHWs who have received training, with results significant at the 95% con-fidence interval (CI). Conclusion: The study highlights the effectiveness of targeted training programs in boosting family planning services at the community level and offers insightful implications for policy-makers and health practitioners. While focused on six districts in Punjab, these promising results emphasize the need for ongoing training and support for frontline health workers to bolster family planning initiatives.

Social media platforms are not serving only as tools of communication rather they are acting like intricate systems managing our interactions. A major setback to our interactions occur when the flow of information in these networks gets distorted through polarization. It resembles a society where every debate turns into divide. Our research focuses exclusively on quantifying polarization as well as solving this issue head-on. In order to accurately gauge polarization, we’ve developed a new method that takes into consideration majority of its influencing factors. This helps us in correctly quantifying the polarization value of a given network and then by proposing it as an optimization problem we are attempting to maximally decrease polarization while staying within the set budget. We test our method on synthetic and real-world data sets, and find out that polarization is declining, and diversity is increasing. This proves that our recommendation engine has a penchant for finding the ideal connections between the nodes to start a dialogue. Our research presents a successful tactic to quantifying and reducing polarization in social media networks. The results indicate that our novel metric and intervention technique are effective in dismantling echo chambers, thereby promoting diversity in these networks.

The world is growing very rapidly concerning technology. In the next-generation Internet, the existing architecture requires to be upgraded from Host-Centric Networking paradigm to Information-centric networking architecture. The unique aspect of information-centric networking is in-network cashing. Due to the system augmentation and In-network cashing technique, this novel system needs extremely high content security to ensure system integrity and maintenance. 5G network may be supported by the Information-Centric Network due to its high data transmission rate. In order to handle the serious security issues such as attack on confidentiality, authentication and integrity of the content, a Digital Signature based Access Control Mechanism in Information-Centric Network (DSAC) scheme is proposed to enhance security of ICN. Briefly, this new scheme uses Digital Signature, hash function, Trusted Third Party (TTP) and Proxy TTP. The client request for content, after receiving a request, the content provider generates and encrypts content with the digital signature and random value ‘k’ hash function and send it to TTP. After the signing process, the TTP sends the encryption hash key to Proxy TTP. In this proposed scheme authentication, confidentiality, the integrity aspects of the content security are improved.

Protein molecules show varying degrees of flexibility throughout their three-dimensional structures. This flexibility is associated with the fluctuation of the torsion angle in proteins. The protein backbone can be defined mainly by two torsion angles, phi (φ) and psi (ψ). The fluctuation of torsion angles is derived from different NMR models’ variations in backbone torsion angles. The angle fluctuations in the cartesian coordinate space are used to characterize the protein’s structural flexibility. Fluctuation of torsion angle is useful in predicting protein function and structure when the torsion angles are used as restraints. This study aims to develop a machine learning method to predict torsion angle fluctuations directly from protein sequences. It explores various useful features such as disorder probability, position-specific scoring matrix profiles, secondary structure probabilities, monograms, bigram, position-specific estimated energy, half-sphere exposures, etc. Likewise, it explores well-known machine learning methods and proposes an optimized Light Gradient Boosting Machine Regressor (LightGBM) method, named TAFPred, to predict torsion angle fluctuations with the selected features. The proposed method achieves ten-fold cross-validated correlation coefficients of 0.746 and 0.737 and mean absolute errors of 0.114 and 0.123 for the angle fluctuation of φ and ψ, respectively, and attains an improvement of 10.08% in MAE, 24.83% in PCC in the phi angle, and 9.93% in MAE, 22.37% in PCC in psi angle compared to the state-of-the-art method proposed by Zhang et al.

Several depth image based rendering (DIBR) watermarking methods have been proposed, but they have various drawbacks, such as non-blindness, low imperceptibility, and vulnerability to signal or geometric distortion. This paper proposes a template based DIBR watermarking method that overcomes the drawbacks of previous methods. The proposed method exploits two properties to resist DIBR attacks: the pixel is only moved horizontally by DIBR, and the smaller block is not distorted by DIBR. The one dimensional (1D) discrete cosine transform (DCT) and curvelet domains are adopted to utilize these two properties. A template is inserted in the curvelet domain to restore the synchronization error caused by geometric distortion. A watermark is inserted in the 1D DCT domain to insert and detect a message from the DIBR image. Experimental results of the proposed method show high imperceptibility and robustness to various attacks, such as signal and geometric distortions. The proposed method is also robust to DIBR distortion and DIBR configuration adjustment, such as depth image preprocessing and baseline distance adjustment.

In the realm of artificial intelligence (AI), generative systems, most notably Midjourney, have tremendous power to generate creative images of buildings and sites of Islamic architectural heritage through text-to-image generation based on the internet. The AI-generated representations have significant potential for architects, specialists, and common users. However, the system has considerable limitations when generating images for some buildings and sites where the representations appear too far from their original represented structures. This research article attempts to answer the question: What are the limitations of using the AI system of Midjourney in producing images similar to the original buildings and sites of the Islamic architectural heritage? The research employs prompt engineering techniques based on historical sources as inputs to examine the accuracy of the output of the AI-generated images of selected examples of structures of the Islamic tradition. It compares the output with the original look by employing direct observation and critical analysis of human intelligence (HI). It categorizes these limitations into four groups: (1) limits of the prompt, (2) limits of fame, (3) limits of regionality and historical styles, and (4) limits of architectural elements and details. It concludes that while Midjourney has great capability to represent high-end AI-generated images inspired by the Islamic tradition, it currently falls short of presenting the actual appearance of some of their original structures.

Skin cancer is an exquisite disease globally nowadays. Because of the poor contrast and apparent resemblance between skin and lesions, automatic identification of skin cancer is complicated. The rate of human death can be massively reduced if melanoma skin cancer can be detected quickly using dermoscopy images. In this research, an anisotropic diffusion filtering method is used on dermoscopy images to remove multiplicative speckle noise and the fast-bounding box (FBB) method is applied to segment the skin cancer region. Furthermore, the paper consists of two feature extractor parts. One of the two features extractor parts is the hybrid feature extractor (HFE) part and another is the convolutional neural network VGG19 based CNN feature extractor part. The HFE portion combines three feature extraction approaches into a single fused feature vector: Histogram-Oriented Gradient (HOG), Local Binary Pattern (LBP), and Speed Up Robust Feature (SURF). The CNN method also is used to extract additional features from test and training datasets. This two-feature vector is fused to design the classification model. This classifier performs the classification of dermoscopy images whether it is melanoma or non-melanoma skin cancer. The proposed methodology is performed on two ordinary datasets and achieved the accuracy 99.85%, sensitivity 91.65%, and specificity 95.70%, which makes it more successful than previous machine learning algorithms.

Imperfection sensitivity of large amplitude vibration of curved single-walled carbon nanotubes (SWCNTs) is considered in this study. The SWCNT is modeled as a Timoshenko nano-beam and its curved shape is included as an initial geometric imperfection term in the displacement field. Geometric nonlinearities of von Kármán type and nonlocal elasticity theory of Eringen are employed to derive governing equations of motion of nano-beam. Spatial discretization of governing equations and associated boundary conditions is performed using differential quadrature (DQ) method and the corresponding nonlinear eigenvalue problem is iteratively solved. Effects of value and location of the geometric imperfection, and the nonlocal small-scale parameter on the nonlinear frequency ratio and imperfection sensitivity of a curved SWCNT for various boundary conditions are investigated. The results show that the geometric imperfection plays a significant role in the nonlinear vibration characteristics of curved SWCNTs.

Objectives: Human herpes viruses can cause life-threatening diseases in immunocompromised children, especially leukemic patients. Therefore, the aim of this study is to detect the human herpes viruses (HHV1-7) and to investigate its clinical significance in Middle Eastern Pediatric Leukemia Patients by using 2 Independent PCR assays. Methods: Detection of human herpes virus DNA has been done in blood samples of 200 pediatric leukemia patients in addition to 90 blood donors as a control group using multiplex PCR assays. When a ‘‘positive’’ result was observed, real-time PCR was performed to measure the viral load. Results: The most frequent herpes virus infection in Middle Eastern Pediatric Leukemia cases was CMV, followed by EBV, then HHV6, VZV, HHV7, HSV1, and HSV2, where they were 92/200 (46%), 76/200 (38%), 72/200 (36%), 48/200 (24%), 12/200 (6%), 8/200 (4%), and 2/200 (1%) respectively. Also, there was a statistically significance difference between leukemic patients and their controls regarding CMV, EBV, HHV6, and VZV (P <0.05). Correlation between percentage of co-infection, and clinical parameters for the 7 herpes viruses has been studied, and there is an increase in absolute neutrophilic count (ANC), total leukocyte count (TLC) and duration of fever and neutropenia in age group 6-11 years for HHV6/CMV, then in age group 12-18 years especially for EBV/CMV and CMV/HHV6. Also, our results show that multiplex PCR assay is close to single PCR assay in relation to specificity and sensitivity which in turn prove its validity for early diagnosis of herpes viral infection. Conclusions: Adopting multiplex PCR technique is helpful in screening of virus infections. It will save time, effort, cost effective and will assist in rapid diagnosis. However, the clinical relevance of the virus infection needs to be evaluated by quantitative real-time PCR which in turn will help patient's management by using appropriate antiviral treatment.

Due to the low content, few studies are focused on the essential oils (EOs) of Phlomoides rotata (Benth. ex Hook. f.) Mathiesen (syn. Lamiophlomis rotata (Benth.) Kudô. This plant has been used to treat rheumatic arthritis and grasserie in China. However, such EOs may have important pharmacological activities such as anti-cancer. To identify the chemical markers (CM) in the EOs and evaluate their antioxidant activities (AAs), we firstly conduct a thoroughly investigation on their chemicals and AAs, to the best of our knowledge. Light yellow EOs with fresh and elegant smell are obtained by hydro-distillation with average yield 0.11% (volume mL/weight g). The crystals are separated from the EOs through cryoprecipitation, respectively. A total of 81 components are qualified and quantified in the EOs, crystals and EOs removed crystals, in which 44 ones are first reported. As for content, the main compounds are long-chain fatty acids (FAs) and their esters. The most abundant one n-hexadecanoic acid (palmitic acid, PA) accounting for 43.15-54.8%, 58.49-64.57% and 15.9-41.1%, in the EOs, crystals and EOs removed crystals, respectively. Seven compounds including PA, tetradecanoic acid, linoleic acid, oleic acid, methyl hexadecanoate, hexahydrofarnesyl acetone and phytol can be chosen a the CMs in these EOs. The AAs are evaluated through in vitro assays. PA presents pro-oxidant activities in a concentration dependence manner. Usually, the EOs removed crystals demonstrate stronger AAs, and the crystals demonstrate weaker AAs compared with that of the corresponding EOs, which is related to the different content of PA in these samples. This study can give some hints for the utilization of such EOs which are abundant in FAs such as PA.

Utilization of medicine derived from plants has been documented in various traditional systems of medicines throughout the world for different diseases. Therefore, the current research work was carried out to evaluate the phytochemical and biological potential of Ficus carica L ethanolic leaf extract. For this purpose, physicochemical and phytochemical analysis, total phenolic and flavonoids contents was performed. Antioxidant potential was determined by FRAP, DPPH and H2O2 assay. Proteinase inhibition, heat induced hemolysis and BSA denaturation assay was carried out for inflammation. Antiglycation potential was assessed by fructosamine assay, Congo-red assay and estimation of free carbonyl groups. In-vivo antidiabetic, anti-obesity, effect on liver and kidney were investigated by high fat high sugar diet model. FTIR, HPLC and LCMS/MS analysis was performed to find out the compounds. Tablet based formulation was developed using wet granulation method and tested for physicochemical parameters. Results shows that total phenolic and flavonoids content was (333 mg GAE/g) and (123 mg RE/g) respectively, H2O2 assay shows 35.6% free radical inhibition potential, DPPH assay shows (IC50) inhibitory concentration at 0.58 mg/mL, and 88.769 µg/g Fe2SO4 solution FRAP values. Proteinase inhibition assay, Heat induced hemolysis and BSA-denaturation assay shows percentage inhibition of 28 ± 0.01, 55 ± 0.03 and 51.2 ± 0.05 respectively. In Antiglycation activity β-amyloid formation assay shows absorption of 0.017, Fructosamine assay shows inhibition of 19.4±0.06 and free carbonyl group estimation shows inhibition of 17.0±0.03. In in-vivo study FLE at (500 mg/kg) significantly decreased total bilirubin (p ≤ 0.001), decreased (p ≤ 0.05) alanine transferase, aspartate aminotransferase, alkaline phosphatase, decreased blood glucose, triglycerides and total cholesterol (p ≤ 0.01) while HDL (p ≤ 0.01) was significantly increased in comparison to obesity and diabetic-obesity groups. Different functional groups presence was confirmed by FTIR spectrum. HPLC analysis revealed the existence of ferulic acid, rutin, chlorogenic acid, coumarin and thymoquinone and these results are corelated by LC-MS/MS. Pre-compression characterization showed angle of repose (33.04°), bulk density (0.54 g/cm3), tapped density (0.73 g/cm3), compressibility index (35.179 %) and Hausner’s ratio (1.35), while the post-compression characterization showed weight variation 826±4.17 mg, thickness 10.50±0.25 kg/cm2, friability 0.57 %, and disintegration time 8.19 min. From the above results it is concluded that F. carica L. leaves extract has strong antioxidant, antidiabetic and hypolipidemic potential and can be used for an obesity and diabetes treatment.

To investigate the dynamics of land surface temperature (LST) in Afghanistan in the period 2000-2021 and to assess the impact of such factors as soil moisture, precipitation, and vegetation coverage on it, remotely sensed soil moisture data from Land Data Assimilation System (FLDAS), precipitation data from Climate Hazards Group Infra-Red Precipitation with Station (CHIRPS), and NDVI and LST from Moderate Resolution Imaging Spectroradiometer (MODIS) were downloaded and correlations between them were analyzed using the regression method. The result shows that the LST in Afghanistan has a slightly decreasing, but insignificant trend during the study period (R=0.2, p-value=0.25), while vegetation coverage, precipitation, and soil moisture had an increasing trend. It was revealed that soil moisture has the highest impact on LST (R=0.7, p-value=0.0007), and the soil moisture, precipitation, and vegetation coverage explain almost 80% of spring (R2=0.73) and summer (R2=0.76) LST variability in Afghanistan. The LST variability analysis done separately for Afghanistan’s rivers subbasins shows that the LST of the Amu Darya subbasin had an upward trend in the study period, while for the Kabul subbasin the trend was downward.

Severe thunderstorms are often accompanied by strong vertical air currents, temporary wind gusts, and heavy rainfall. The development of this atmospheric phenomenon over tropical shallow water zones, such as bays, can lead to intensification of atmospheric disturbances and produce a small-scale storm surge. Here, the storm surge that occurred on 19 March 2017 in the Persian Gulf coastal area has been investigated. Air temperature, precipitation, mean sea level pressure, wave height, wind direction, wind speed, geopotential height, zonal components, meridional winds, vertical velocity, relative humidity, and specific humidity obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF (and Global Forecast System (FNL) were used to implement the Weather Research and Forecasting (WRF) model. The results showed that the main cause of the storm surge was the occurrence of a supercell thunderstorm over the Persian Gulf. The formation of this destructive phenomenon resulted from a downburst under Cumulonimbus cloud and high-velocity air subsidence, after collision with the sea surface coinciding with the high tide. This caused a severe, yet temporary, gust, which in turn caused the creation of the four waves of 3.1 m height along the coast of Bandar Dayyer.

The application of instrumented indentation to assess material properties like Young’s modulus and micro-hardness has become a standard method. In recent developments, indentation experiments and simulations have been combined to inverse methods, from which further material parameters as yield strength, work hardening rate, and tensile strength can be determined. In this work, an inverse method is introduced by which material parameters for cyclic plasticity, i.e. kinematic hardening parameters, can be determined. To accomplish this, cyclic Vickers indentation experiments are combined with finite element simulations of the indentation with unknown material properties, which are then determined by inverse analysis. To validate the proposed method, these parameters are subsequently applied to predict the uniaxial stress-strain response of a material with success. The method has been validated successfully for a quenched and tempered martensitic steel and for technically pure copper, where an excellent agreement between measured and predicted cyclic stress-strain-curves has been achieved. Hence, the proposed inverse method based on cyclic nanoindentation, as a quasi-non-destructive method, could complement or even substitute the resource-intensive conventional fatigue testing in the future for some applications.

Objective Ovarian pregnancy is a rare but well-known pathology. However, pathophysiology, diagnosis and treatment are not clearly established. Data sources. All case reports published in Pubmed from Nov 2011 till Nov 2022. Study eligibility criteria. A systematic review and 2 case reports of ovarian pregnancy Study appraisal and synthesis methods. Not applicable Results Ovarian pregnancies occur in 8% of women without or blocked oviducts and in 23% on the other side than the corpus luteum and the symptoms of ovarian pregnancies are not specific. Therefore ovarian pregnancy has to be suspected in all women with abdominal bleeding. As for extrauterine pregnancies, the presence of an intrauterine pregnancy does not rule out an ovarian pregnancy. Surgical excision is the preferred treatment. Important is that in women with both an intra-uterine and an ovarian pregnancy, care should be taken not to damage the corpus luteum. Conclusions Ovarian pregnancies can occur in women with blocked tubes, on the other side of the corpus luteum, in the presence of an intrauterine pregnancy, and even when pregnancy tests or tranvaginal ultrasonography are negative. The diagnosis being difficult to exclude, a laparoscopy is indicated in all women with intra-abdominal bleeding, keeping in mind that an intra-uterine pregnancy cannot be exluded and that a corpus luteum need to be respected.