This study presents a comprehensive assessment of indoor particulate matter (PM) concentrations, focusing on PM1, PM2.5, and PM10 in five Primary Health Centers (PHCs): Arakale, Federal College of Agriculture (FECA), Iju, Oba-Ile, and Owode within Akure Local Government Areas in Nigeria. The primary novelty of this research lies in its detailed exploration of the toxicity potential of these PM fractions, providing valuable insights into the local air quality and associated health risks. The study assesses the health implications by calculating the toxicity potential (TP), Relative Risk (RR), Excess Risk (ER), and Attributable Fractions (AF) for cardiopulmonary and lung cancer mortality. The results reveal varying RR values for all-cause mortality, with Arakale showing a slight elevation (RR: 1.061), indicating potential health risks. ER values for cardiopulmonary mortality range from 14.728±7.25 to 19.04±0.38, emphasizing the substantial excess risk associated with long-term PM2.5 exposure. The study also uncovers AF for cardiopulmonary mortality ranging between 11.03±0.31 to 19.22±0.04, underscoring the significant contribution of PM to cardiovascular and respiratory health risks. Similarly, AF for lung cancer mortality ranges from 10.03±0.012 to 17.13±0.10, highlighting the substantial association between PM2.5 exposure and lung cancer risk. These findings underscore the urgent need for targeted air quality management strategies and public health interventions in the studied locations to mitigate the heightened health risks associated with particulate matter pollution. The calculated RR, ER, and AF values offer crucial insights into the complex relationship between PM exposure and adverse health outcomes, providing a foundation for informed decision-making and future research endeavors.

Multiple sclerosis is a chronic, autoimmune disease that mainly affects the central nervous system, including the brain, spinal cord, and optic nerve. This disease can cause clinical symptoms such as cognitive decline, muscle weakness, spasms, and fatigue in patients, and the onset tends to be younger. Current medication can only prevent or alleviate symptoms, so early diagnosis of this disease can increase patients' chances of treatment. Although the use of nuclear magnetic resonance detection can improve the efficiency of early auxiliary diagnosis, it still requires experienced doctors to spend too much time and energy on comprehensive judgment. To reduce the time cost and improve the efficiency of multiple sclerosis diagnosis, this article proposes a detection and recognition algorithm for multiple sclerosis based on wavelet entropy and self-adaptive particle swarm optimization. Firstly, a triple discrete wavelet transform is performed on the brain image of multiple sclerosis, and then 10 wavelet entropies are extracted from the decomposed wavelet subbands, which can reduce the feature dimensions of the image; Then, the algorithm of self-adaptive particle swarm optimization is used to optimize the feedforward neural network, in order to obtain the optimal connection weights and thresholds during the training process. The result of the model is with an average sensitivity of 92.29±1.89, specificity of 92.54±0.67, precision of 92.48±0.59, accuracy of 92.42±0.88, and F1 score of 84.85±1.74, Matthews correlation coefficient of 92.37±0.96, and Fowlkes223 Mallows Index of 92.38±0.96. The experimental results indicate that this algorithm has a very important data support role in detecting multiple sclerosis.

Background: We aimed to evaluate the impact of two different phytotherapeutic agents on the decision making regarding prostate biopsy in patients with higher-than-normal prostate-specific antigen (PSA) levels. Methods: From June 2022 to May 2023, all patients attending two urological institutions due to higher-than-normal PSA levels were randomized to receive either oral capsules of Curcuma Longa, Boswellia, Pinus pinaster and Urtica dioica (Group A) or Serenoa Repens 320 mg (Group B), for 3 months. At the follow-up visit after 3 months all patients underwent PSA test and multiparametric magnetic resonance imaging (mpMRI). Results: In the per-protocol analysis, data from 66 patients in Group A and 76 in Group B were analyzed. Fifty patients in Group A (75.7%) showed a significant reduction of total PSA compared to 49 in Group B (64.4%) (p<0.001). Twenty-eight patients had PI-RADS III or higher at mpMRI: 12 in Group A and 14 in Group B. Twenty-three patients (34.8%) in Group A underwent prostate biopsy based on mpMRI findings and PSA values and 59 (77.6%) in Group B (p<0.001). Three patients in Group A showed a significant reduction of total PSA value while having positive findings at mpMRI (6%) compared with 9 in Group B (19.5%) (p<0.001). On the contrary, 7 patients in Group A did not show a significant reduction of total PSA value and had negative findings at mpMRI (43%) compared to 22 in Group B (81.4%) (p&lt;0.001). Conclusions: In conclusion, a three-month course of a combination of Curcuma Longa, Boswellia, Pinus pinaster, and Urtica dioica seems an interesting tool to avoid unnecessary prostate biopsies in men with higher-than-normal PSA levels.

Object detection is important in many applications, such as autonomous driving. While 2D images are lack of depth information and are sensitive to environmental conditions, 3D point cloud can provide accurate depth information and a more descriptive environment. However, sparsity is always a challenge in single-frame point cloud object detection. This paper introduces a two-stage proposal-based feature fusion method for object detection using multiple frames. The proposed method, called proposal features fusion (PFF), utilizes a cosine-similarity approach to associate proposals from multiple frames and employs an attention weighted fusion module to merge features from these proposals. It allows for feature fusion specific to individual objects and offers lower computational complexity while achieving higher precision. The experimental results on the nuScenes dataset demonstrate the effectiveness of our approach, achieving a mAP of 46.7%, which is 1.3% higher than the state-of-the-art 3D object detection method.

Increased volume of untreated and inadequately treated municipal wastewater undermines the circular economy potential of wastewater resources, particularly in low-income region. This present study focused on and evaluated the performance of native microalgae-activated sludge (MAS) growth for tertiary treatment of anaerobically digested wastewater from an upflow anaerobic sludge blanket (UASB) in an outdoor lab-scale photobioreactors (2 L). Seven conditions with distinct inoculum concentrations were operated in batch mode in triplicate for 5-days hydraulic retention time (HRT) at 11.5:12.5 Photo-hours. MAS inoculum concentration influenced treatment outcome. The best performance was observed in MAS concentration 0.10/0.20 g L-1, with cell density count (2.03 x 107 cells mL-1), biomass productivity 0.125 g TSS L-1 d-1 and total phosphorus uptake (85.07%), total nitrogen uptake (66.14%). Logarithmic removal (Log-Re) of bacterial pathogens (water quality indicators) showed Log-Re ((3.4 for total coliforms (1.37E+02 CFU 100 mL-1) and 4.7 for Escherichia coli (0.00E+00 CFU 100 mL-1)). Results revealed optimum remediation performance and nutrients’ recovery potential with appropriate inoculum concentration, in admiration to advancing the science of circular economy.

Global croplands, pastures, plantations, and human settlement areas have expanded in recent decades, accompanied by large increases in energy, water, and fertilizer consumption, along with considerable losses of biodiversity. In sub-Saharan Africa, policies are implemented without critical consideration e.g., agricultural expansions impair ecosystem services of the several river basins. The current study has studied landuse/cover and associated rate of change for four-time epochs i.e., 1991, 2001, 2011 and 2021. This employed remote sensing and GIS techniques for LULC analysis while future projection was modelled using cellular automata and Markov chain. The Kappa coefficient statistics were used to assess the accuracy of final classified image while reference images for accuracy assessment were developed based on ground truthing. Overall change results between 1991 and 2021, showed that major percentage loss in area were experienced by water, forest, woodland and wetland which decreased by 8,222Ha (44.11%), 426,161Ha (35.72%), 399,584Ha (35.01%) and 105,186Ha (34.82%). On the other hand, percentage increase in area during the same period were experienced in cultivated land, built up areas and grasslands which increased by 659,346Ha (205.28%), 11,894Ha (159.93%) and 33,547Ha (98.47%). However, even with the expanding thirsty sectors water discharged out of the catchment is on increment at a rate of 498.6 m3/s/year. For dualistic benefits, agroforest practices are recommended along with participatory law enforcement and capacity building of local communities through their institutions.

In the pursuit of sustainable solutions for carbon dioxide CO2 sequestration and emission reduction in the steel industry, this study presents an innovative integration of steelmaking slag with the modified Solvay process for sodium bicarbonate (NaHCO3) synthesis from saline brines. Utilizing diverse minerals, including electric arc furnace (EAF) slag, olivine, and kimberlite, the study explored their reactivity under varied pH conditions and examined their potential in ammonium regeneration. Advanced techniques such as XRD and ICP-OES were employed to meticulously analyze mineralogical transformations and elemental concentrations. The findings demonstrate that steelmaking slag, owing to its superior reactivity and pH buffering capabilities, outperforms natural minerals. The integration of finer slag particles significantly elevated pH levels, facilitating efficient ammonium regeneration. Geochemical modeling provided valuable insights into mineral stability and reactivity which aligned with the ICP-OES results. This synergistic approach not only aids in CO2 capture through mineral carbonation but also minimizes waste, showcasing its potential as a sustainable and environmentally responsible solution for CO2 mitigation in the steel industry.

Micro-arc oxidation (MAO) is an emerging technology employed to produce high hardness or anti-corrosion ceramic coatings on lightweight metals such Al, Ti, Mg and their respective alloys. However, under non-lubrication conditions, such coatings exhibit relatively high friction coeffi-cients. To enhance the friction reduction properties of the MAO coatings, we employed a one-step MAO process with varying concentrations of graphene oxide (GO) in an aluminate sys-tem electrolyte to create composite coatings on the surfaces of Ti-6Al-4V alloy. The effect of concentrations of GO particles on microstructure, composition, and wear behavior of the result-ing composite coatings was investigated. Measurements of the coating's thickness, hardness, and roughness have also been conducted. Ball-on-disk friction test under dry condition were carried out to reveal tribological behavior of the MAO coating. The addition of graphene oxide in the electrolyte reduces the friction coefficient, with the composite coating containing 5 g/L of GO particles displaying the most effective friction reduction. Moreover, coating thickness increases with higher GO concentration. This friction reduction can be attributed to the particles in the coating acting as lubricants during friction, while GO also reduces adhesive damage, shifting the wear mechanism from adhesive to abrasive.

The Third Generation Partnership Project(3GPP) has specified the Cellular Vehicle-to-Everything (C-V2X) radio access technology in Releases 14 and 15, with a focus on facilitating direct communication between vehicles through the sidelink PC5 interface. This interface offers a robust cloud-native core network with end-to-end network slicing functionality. The performance of di-rect vehicle-to-vehicle (V2V) communications has been improved by using the sidelink interface, which allows for network infrastructure by-pass. Sidelink transmissions make use of orthogonal resources that are either centrally allocated (Mode 1) or chosen by the vehicles themselves (Mode 2). The development of radio access technologies that enable dependable and low-latency vehicular communications has become of utmost relevance with the rise in interest in connected and autonomous vehicles. This is especially necessary when there are heavy traffic conditions and patterns. We thoroughly examined the New Radio (NR) sidelink’s performance under various vehicle densities, speeds, and distance settings. Thus, by evaluating sidelink’s strengths and drawbacks, we are able to optimize resource allocation to obtain maximum coverage in urban areas. The performance evaluation is conducted on Network Simulator 3 (NS3.34/5G-LENA) utilizing various network metrics such as average packet reception rate, throughput, and latency.

The optimal regime of three-photon resonant excitation of a helium atom by a femtosecond ul-traviolet (UV) pulse was discovered and numerically studied, at which the maximum power of the third harmonic of the UV field is achieved in the spectrum of dipole acceleration (the second time derivative of the induced dipole moment) of the atom. It is shown that the optimal frequency of the UV field nearly coincides with the frequency of the three-photon transition 1s2 – 1s2p, taking into account its shift as a result of the dynamic Stark effect, and the intensity of the UV field is dictated by the condition of maximizing the product of the populations of the 1s2 and 1s2p states, averaged over the time interval during which the UV field is non-zero. For the considered UV field durations, from 10 to 100 cycles of the carrier frequency (from units to tens of femtoseconds), the optimal intensity lies in the range from 10^14 W/cm^2 to several units of 10^14 W/cm^2. It is shown that with an optimal choice of the frequency and intensity of the UV field, the dynamics of excitation of bound and continuum states, as well as the shape of the time envelope of the dipole acceleration of the atom, weakly depend on the duration of the UV field envelope; only their time scale changes significantly. In addition, under the optimal conditions the average power of the third harmonic signal in the dipole acceleration spectrum is practically independent of the duration of the UV field envelope.

This article reviews the introduction of Alzheimer's Disease (AD), neural networks, training and learning of neural networks, applications of neural networks in early diagnosis of AD, applications of neural networks in AD drug discovery, other brain diseases, and challenges faced by AD. First, the paper introduces the background and characteristics of AD. AD is a degenerative neurological disorder characterized by impaired memory, decreased cognitive function, and loss of neurons. These characteristics place a huge burden on the lives and families of patients. Next, the basic principle and structure of neural network are discussed. A neural network is a computational model made up of multiple neurons that can perform tasks by learning and adapting to input data. In particular, the key concepts of neural network hierarchy, activation function and weight adjustment are discussed. Then, the training and learning methods of neural networks are discussed. Common techniques such as backpropagation algorithm and gradient descent optimizer are introduced in detail, as well as the importance of data preprocessing and model evaluation. Next, the paper focuses on the application of neural network in early diagnosis of AD. By extracting features from brain image data, neural networks can automatically identify differences between AD patients and healthy subjects, enabling early diagnosis and intervention. In addition, the application of neural networks in AD drug discovery is also discussed. By analyzing and predicting a database of known drugs, neural networks can help discover potential treatments for AD and speed up the drug discovery process. The paper further explores the application of neural networks in other brain diseases and highlights the challenges faced by AD, such as the lack of reliable biomarkers, complex pathological mechanisms, etc. In summary, this paper presents a systematic overview of AD, neural networks, training and learning of neural networks, applications of neural networks in early diagnosis of AD and drug discovery, and other brain diseases and challenges associated with AD.

Anxiety is a complex emotional state that can arise from the anticipation of a threatening event, and preoperative anxiety is a common experience among adult patients undergoing surgery. In adult patients, the incidence of preoperative anxiety varies widely across different surgical groups, and it can result in a variety of psychophysiological responses and problems. Despite its negative impact, preoperative anxiety often receives insufficient attention in clinical practice. To improve pain management strategies, there is a need for further research on personalized approaches that take into account various factors that contribute to an individual's pain experience. These personalized approaches could involve developing tools to identify individuals who are more likely to experience increased pain and may require additional analgesia. To address this, regular assessments of anxiety levels should be conducted during preoperative visits, and counseling should be provided to patients with high levels of anxiety. Identifying and addressing preoperative anxiety in a timely manner can help reduce its incidence and potential consequences.

The use of plant-based and microorganism-based biological inputs is a sustainable agricultural practice, promoting a suitable and better utilization of non-renewable resources in the environment. The benefits of using microorganisms are associated with both direct and indirect mechanisms, primarily related to improvements in nutrient absorption and availability, as well as plant growth. The main benefits of using biochemical pesticides are the promotion of sustainability and the management of resistance. Although the use of microorganisms and botanical metabolites is a promising agricultural alternative, it is still primarily concentrated in grain crops. However, due to the wide range of mechanisms of action of plant-based and microorganism-based biological inputs, there is an opportunity to expand their use in agriculture. In the Brazilian biological inputs market, various terminologies have been used to characterize biological-based products, with many of these terms being employed incorrectly and sometimes conflicting with the country’s legislation. Therefore, this review presents the classes of biological inputs and the application and evolution of the plant-based and microbiological-based product market in different crops in Brazil.

The brief paper utilises Zimbabwe as a case study to discuss the effects of El Nino in Southern Africa. It offers potential adaptation and mitigation measures for farmers to prepare for the forecasted El Nino-influenced rainy season 2023/24 and the future. To reduce climate and weather hazards connected with El Nino, the brief report suggests anticipatory action methods be applied in southern Africa, using Zimbabwe as a case study. To protect farmers' livelihoods and enhance drought readiness for the forthcoming agricultural seasons, the paper suggests a degree of strategic, tactical, and operational decision-making that the agriculture industry should adhere to. It emphasised the significance of providing farmers with knowledge and advice regarding drought and heat stress, including cultivating crop varieties and livestock and sufficient fire safety precautions. The brief paper calls to advocate for anticipatory action to avert El Nino in Southern Africa.

Ship detection in large-scene offshore synthetic aperture radar (SAR) images is crucial in civil and military fields, such as maritime management and wartime reconnaissance. However, the problems of low detection rates, high false alarm rates, and high missed detection rates of offshore ship targets in large-scene SAR images are due to the occlusion of objects or mutual occlusion among targets, especially for small ship targets. To solve this problem, this study proposes a target detection model (TAC_CSAC_Net) that incorporates a multi-attention mechanism for detecting marine vessels in large-scene SAR images. Experiments were conducted on two public datasets, the SAR-Ship-Dataset and high-resolution SAR image dataset (HRSID), with multi-scene and multi-size, and the results showed that the proposed TAC_CSAC_Net model achieves good performance for both small and occluded target detection. Experiments were conducted on a real large-scene dataset, LS-SSDD, to obtain the detection results of subgraphs of the same scene. Quantitative comparisons were made with classical and recently developed deep learning models, and the experiments demonstrated that the proposed model outperformed other models for large-scene SAR image target detection.

In many ports, the ship's speed is limited for the safety of navigation. At the same time, ship captains and port pilots choose the speed of the ship, but not higher than the permitted speed of the ship in the port, therefore the speed of the ship also depends on the experience of the ship captains and port pilots and the sailing conditions of the ship in specific conditions. Choosing the optimal speed of ships in port, including the effect of shallow depth, can reduce fuel consumption and ship emissions in ports, which is important for the development of green and sustainable ports. In all cases, shipping safety is the highest priority. The main objectives of the article are determining the optimal speed of ships in ports with low clearance, ensuring navigational safety, reducing fuel consumption and emissions, and at the same time creating a sustainable port. The article presents the methodology of optimal ship speed calculation, minimum ship controllable speed maintenance, fuel consumption and emission reduction methodology and their impact on sustainable and green maritime transport and port development. The developed methodology was tested on real ships and with the help of a calibrated simulator, sailing through harbor channels and harbor waters in low clearance conditions.

(1) Background: The goal of the study was to evaluate psychological tolerance and health-related quality of life (QOL) in head and neck (HN) cancer patients treated with definitive accelerated radiotherapy (DART); (2) Methods: Seventy-six recurrence-free patients eligible for the study, who were treated with DART in the CAIR-2 phase III clinical study (median of follow-up=47 months), completed EORTC QLQ-C30 with H&amp;N35 module, Hospital Anxiety and Depression Scale (HADS) and Visual–Analog Scales (VAS) of pain in HN and the neck / arm area.; (3) Results: The most dominating symptoms measured with QLQ-C30 were: fatigue (44/100), sleeplessness (39/100), financial problems (38/100) and pain (32/100). Within H&amp;N35 the highest scores were reported on the subscales of sticky saliva (60/100), mouth dryness (65/100) and increased intake of painkillers (50/100). Pain (VAS) was reported by 87% (HN area) and 78% (shoulder) of the patients, with a mean score of 3/10. One-third reported depressive mood (HADS≥15 points) with an average score of 12.5/42 p. The depressed group, who smoked more as compared to non-depressed before DART (96% vs 78%) and required steroids treatment (85% vs 58%) during DART, also scored significantly worse on 23 of 35 subscales of QLQ-C30 and H&amp;N35 and experienced more intense pain (VAS). Women, and less advanced patients scored better in several aspects of the quality of life; (4) Conclusions: Patients treated with DART struggle with low quality of life and persisting treatment-related symptoms including constant pain. HNC survivors, especially those, who are depressed, may require additional psychosocial, rehabilitation and medical intervention programs..

Carbon fiber reinforced polymers (CFRPs) are being used extensively in modern industries that require high strength-to-weight ratio such as aerospace, automotive, motorsport, and sports equipment. However, although reinforcement with carbon fibers improves the mechanical properties of polymer, this comes on the expense of abrasive wear resistance. Therefore, to efficiently utilize CFRPs in dry sliding contacts, solid lubricant is used as a filler. Further, to facilitate fabrication of objects with complex geometries, selective laser sintering (SLS) can be employed. Accordingly, in the present work, graphite-filled carbon fiber-reinforced polyamide 12 (CFR-PA12) specimens were prepared using SLS process to explore the dry sliding friction and wear characteristics of the composite. The test specimens were aligned along four different orientations in the build chamber of SLS machine to determine the orientation-dependent tribological properties. The experiments were conducted using pin-on-disc tribometer to measure the coefficient of friction (COF), interface temperature, friction-induced noise, and specific wear rate. In addition, scanning electron microscopy (SEM) of tribo-surfaces was conducted to specify the dominant wear pattern. The results indicated that the steady state COF, contact temperature, and wear pattern of graphite-filled CFR-PA12 are orientation-independent, and that the contact temperature is likely to approach an asymptote far below the glass transition temperature of amorphous PA12 zones, thus eliminating the possibility of matrix softening. Additionally, the results showed that the Z-oriented specimen exhibits the lowest level of friction-induced noise along with the highest wear resistance. Moreover, SEM of tribo-surfaces determined that abrasive wear is the dominant wear pattern.

Due to the imbalance between the supply and demand of oxygen, the oxygen system of iron- and steel-making enterprises in China has problems with high oxygen emission and high pressure in the pipelines, resulting in the energy consumption of oxygen production being high. To relieve this problem, using a large-scale iron- and steel-making mill as a case study, the research on demand forecasting and optimal scheduling of the oxygen system was carried out. The ARIMA model and the GABP model are employed to forecast oxygen demand. Based on the forecast results, an optimal scheduling model for the oxygen system was developed to conduct optimal scheduling. The case study shows that based on the oxygen demand forecast and the optimal scheduling, the oxygen emission and the pipeline pressure in the studied iron- and steel-making enterprise can be significantly reduced, thereby achieving considerable energy-saving effects and economic benefits. Specifically, the following conclusions are obtained: (1) For the oxygen demand forecast, the prediction accuracy of the GABP model is better than that of the ARIMA model. The average MAPE of the 12 sets of data of the ARIMA and GABP models are 23.8% and 20.2%, respectively. (2) By comparing the scheduling results and the field data, it is found that after the scheduling, the amount of oxygen emission has decreased by 6.32%, the pipeline pressure has decreased by 0.61%, and the energy consumption of oxygen compression has decreased by 1.6%. Considering both the oxygen emission loss and the energy consumption of oxygen compression, the total power consumption of the oxygen system is reduced by 1.38%, which saves the electricity cost of about 9.03 million RMB per year.

A medium-Mn steel was processed by a route involving twin-roll strip casting, hot-rolling and quenching and partitioning with different quenching temperatures. The effects of quenching temperature on the microstructure and mechanical properties were studied. It was found primary martensite and retained austenite (RA) were obtained at the quenching temperature of 140–180 °C, while primary martensite, RA and secondary martensite were obtained when the quenching temperature was 220–300 °C. With increase in quenching temperature from 140 to 260 and to 300 °C, RA fraction first increased from 15.4% to 31.8% and then decreased to 16.6%. The sample at quenching temperature of 220 °C yielded the mechanical properties with yield strength of 992 MPa, tensile strength of 1159 MPa and total elongation of 20.4%. The superior mechanical properties were achieved by an optimum combination of high RA fraction (26.5 vol%), appropriate mechanical stability of RA and a small amount of secondary martensite.

The prefabricated houses supply in Chile was analyzed from web platforms, public market, social media, and Internal Revenue Service, using indicators according to regulatory compliance, complexity, and sustainability attributes, which are essential in advancing to industrialization, and climate change adaptability. The 80% is concentrated in construction, and manufacturing companies, 83% of them are legally registered,with the capacity of meeting technical requirements. To delve deeper into this, 54% has low level, 35% medium level, and 11% high level. The sustainability was measured in 5 levels: 2.7% (1), 37,5% (2), 58,6% (3), 1,1% (4) and 0% (5), which is the highest one. This attribute was determined as the weakest one. The proposed evaluation, based on indicators by attribute, is objective and relevant to consideration since there is still a lack of capacity to supply the housing deficit, and there is not attributes associated to security in habitability to address the climate change, and environment threats, with a lack of action by the state to promote this productive sector, therefore focusing more in provide products, than taking responsibility of the site, not advancing to become a real state agency, which could be improved if management, and regulation were incorporated.

In the particular configuration of the scalar field K-essence in the Wheeler-DeWitt quantum equation, for some age in the Bianchi type I anisotropic cosmological model, a fractional differential equation for the scalar field arises naturally. The order of the fractional differential equation is $\beta=\frac{2\alpha}{2\alpha - 1}$. This fractional equation belongs to different intervals, depending on the value of the barotropic parameter; when $\omega_{X} \in [0,1]$, the order belongs to the interval $1\leq \beta \leq 2$, and when $\omega_{X}\in[-1,0)$, the order belongs to the interval $0<\beta \leq 1$. In the quantum scheme, we introduce the factor ordering problem in the variables $(\Omega,\phi)$ and its corresponding momenta $(\Pi_\Omega, \Pi_\phi)$, obtaining a linear fractional differential equation with variable coefficients in the scalar field equation, then the solution is found using a fractional power series expansion. The corresponding quantum solutions are also given. We found the classical solution in the usual gauge N obtained in the Hamiltonian formalism and without a gauge. In the last case, the general solution is presented in a transformed time $T(\tau)$, however in the dust era we found a closed solution in the gauge time $\tau$.

Vancomisin resistant enterococcus(VRE), is a resistant microorganism which colonizates and causes infections in hospitalized patients. It was aimed to show the spread of vancomycin-resistant Enterococcus (fVREfm) step-by-step in all intensive care units, which started with the growth of vancomycin-resistant Enterococcus faecium (VREfm) on 02.12.2021 in the blood culture of a patient hospitalized in the anesthesia intensive care unit of our hospital and was found to have reached epidemic size in the surveys. Rectal swab samples were taken from all patients hospitalized in intensive care units, VRE colonization was determined and the VanA and VanB resistance genes associated with vancomycin resistance of VREfm isolates were determined by PCR method, and clonal association analysis was performed by Arbitrarily Primed-PCR (AP-PCR) and Pulsed-Field Gel Electrophoresis. In our study, VRE was detected in 61 of 2601 rectal swab samples. 54 (85.52%) of the VRE isolates were Enterococcus faecium, 3 (4.91%) was Enterococcus faecalis, 3 (4.91%) was Enterococcus gallinorum, 1 (1.63%) was Enterococcus casseliflavus. It was determined that all of the 54 VREfm isolates, which were the most detected among all VRE isolates, carried the vanA gene. In the clonal association analysis of the isolates by AP-PCR and PFGE methods, it was found that they had 12 different genotypes, 48 of them were included in any cluster, the clustering rate was 88.8%, and the largest cluster was genotype 1 cluster with 36 isolates. Of the 54 patients with VREfm isolated recently, 18.51 percent of the clinical samples were isolated before the survey, and 9.24% were isolated after the survey. It was determined that 100% of VREfm isolates were resistant to ampicillin, levofloxacin, ciprofloxacin, high-level gentamicin, trimethoprim-sulfamethoxazole, teicoplanin, 7.4% to tigecycline and 1.85% to linezolid. In our study, in the clonal association analysis performed by isolating VREfm in rectal swab samples, it was found that 88.8% of the samples were indistinguishably similar and the increase in the number of VREfm infections after the index case in our hospital was associated with the epidemic. VREfm infections cause long term hospitalization, costs and also deaths, which shows the seriousness of the event, and the importance of the combination of epidemiological and molecular analysis in epidemic research.

This article explores the cross-cultural significance of three iconic fairy tales: Cinderella, Snow White, and Sleeping Beauty. Using a comparative analysis approach, the study investigates recurring themes, motifs, and symbolism found in these tales across different cultures and time periods. The research draws on primary and secondary sources such as literary works and scholarly articles to uncover the underlying messages that resonate with audiences worldwide. The historical and cultural contexts of the tales are also examined to provide a deeper understanding of their significance in shaping cultural identity and values. The findings of the research demonstrate the enduring legacy of these tales and their continued relevance in contemporary society. The study highlights how the tales have evolved and adapted over time to reflect changing cultural values and beliefs. The interpretation of the findings offers insights into the role of storytelling in shaping cultural identity and values, and the ways in which these stories continue to inspire and captivate audiences worldwide. Overall, this research provides a comprehensive and nuanced understanding of the significance of these three fairy tales across cultures and time. By illuminating the similarities and differences in these tales, the study offers a fresh perspective on the power of storytelling and its ability to transcend cultural boundaries. The research contributes to the fields of folklore, cultural studies, and cross-cultural communication, inspiring further exploration into the captivating world of fairy tales.

Ankle joint flexion and extension exercises play an important role in the rehabilitation training of patients who have been injured or bedridden for a long time before and after surgery. Accurately guiding patients to perform ankle flexion and extension exercises can significantly reduce deep vein thromboembolism. Currently, most ankle rehabilitation devices focus on assisting patients with ankle flexion and extension movements, and there is a lack of devices for effectively monitoring these movements. In this study, we designed an ankle joint flexion and extension movement monitoring device based on a pressure sensor. It is composed of an STM32 microcontroller, a pressure sensor, an HX711A/D conversion chip, and an ESP8266 WiFi communication module. The value of force and effective number of ankle joint flexion and extension movements were obtained. An experimental device was designed to verify the accuracy of the system. The results showed that the device can effectively monitor and control ankle flexion and extension movements remotely, ultimately ensuring that the patient can effectively monitor and grasp the active ankle pump movement.

In the food sector, packaging is one of the important steps that ensures the safe, unspoiled, min-imum cost of storing, transporting and delivering the food that goes into production to the con-sumer. Food spoilage caused by foodborne pathogens and microorganisms is a serious problem in the food chain, reducing the shelf life of foods. Therefore, consumers' demands for more natural, disposable, biodegradable and recyclable antibacterial food packaging materials have considera-bly increased. This review covers a comprehensive current literature review of antibacterial food packaging, which includes with titles antibacterial agents, organic acids and other compounds, enzymes, bacteriocins, natural extracts, essential oils, application of encapsulation and antimi-crobial packaging. Research findings on antimicrobial food packaging used to extend the shelf life of foods were collected from online databases such as PubMed/MedLine, Wiley Online Li-brary, Scopus, Web of Science, and Google Scholar. In this review, the activities of different bio-materials and compounds used to extend the shelf life of foods were compared

In order to better realize rural revitalization, this paper analyzes the spatial and temporal char-acteristics and influencing factors of agricultural surface source pollution in the Yangtze River Economic Belt from the three perspectives of government, enterprise and agriculture by using the spatial Durbin model and the dynamic GMM method in the period of 2006-2021, and further re-searches the threshold characteristics of the distortion of the factor market on the agricultural surface source pollution under the different strengths of environmental regulation. The results show that there is a positive spatial correlation between agricultural surface pollution in the Yangtze River Economic Belt, and government environmental regulation, input factor market distortion and labor force transfer all have a significant impact on agricultural surface pollution. Among them, factor market distortion has a significant spatial spillover effect on agricultural surface pollution in the Yangtze River Economic Zone, and has a significant single-threshold ef-fect on environmental regulation. Accordingly, the government should strengthen environmental regulation, continuously improve the agricultural factor market mechanism, and pay attention to the construction of talents to provide support for rural revitalization.

COVID-19 transmission models have conferred great value in informing public health understanding, planning, and response. However, the pandemic also demonstrated the infeasibility of basing public health decision-making on transmission models with pre-set assumptions. No matter how favourably evidenced when built, a model with fixed assumptions is challenged by numerous factors that are difficult to predict. Ongoing planning associated with rolling back and re-instituting measures, initiating surge planning, and issuing public health advisories can benefit from approaches that allow state estimates for transmission models to be continuously updated in light of unfolding time series. A model being continuously regrounded by empirical data in this way can provide a consistent, integrated depiction of the evolving underlying epidemiology and acute care demand, offer the ability to project forward such a depiction in a fashion suitable for triggering the deployment of acute care surge capacity or public health measures, support quantative evaluation of tradeoffs associated with prospective interventions in light of the latest estimates of the underlying epidemiology. We describe here the design, implementation and multi-year daily use for public health and clinical support decision-making of a particle filtered COVID-19 compartmental model, which served Canadian federal and provincial governments via regular reporting starting in June 2020. The use of the Bayesian Sequential Monte Carlo algorithm of Particle Filtering allows the model to be re-grounded daily and adapt to new trends within daily incoming data – including test volumes and positivity rates, endogenous and travel-related cases, hospital census and admissions flows, daily counts dose-specific vaccinations administered, measured concentration of SARS-CoV-2 in wastewater, and mortality. Important model outputs include estimates (via sampling) of the count of undiagnosed infectives, the count of individuals at different stages of the natural history of frankly and pauci-symptomatic infection, the current force of infection, effective reproductive number, and current and cumulative infection prevalence. Following a brief description of model design, we describe how the machine learning algorithm of particle filtering is used to continually reground estimates of dynamic model state, support probabilistic model projection of epidemiology and health system capacity utilization and service demand and probabilistically evaluate trade-offs between potential intervention scenarios. We further note aspects of model use in practice as an effective reporting tool in a manner that is parameterized by jurisdiction, including support of a scripting pipeline that permits a fully automated reporting pipeline other than security-restricted new data retrieval, including automated model deployment, data validity checks, and automatic post-scenario scripting and reporting. As demonstrated by this multi-year deployment of Bayesian machine learning algorithm of particle filtering to provide industrial-strength reporting to inform public health decision making across Canada, such methods offer strong support for evidence-based public health decision making informed by ever-current articulated transmission models whose probabilistic state and parameter estimates are continually regrounded by diverse data streams.

Some traditional robots are based on offline programming reciprocal motion, and with the continuous upgrading of vision technology, more and more tasks are replaced by machine vision. For the current problem of insufficient accuracy of robot target localization based on binocular vision, and an improved random sampling consistency algorithm is proposed to complete parallel robot target localization and grasping under the guidance For the current problem of insufficient accuracy of robot target localization based on binocular vision, an improved random sampling consistency algorithm is proposed to complete parallel robot target localization and grasping under the guidance of multi Firstly, the RANSAC algorithm is improved based on the SURF algorithm; then the parallax gradient method is applied to iterate the matched point pairs several times to further optimize the data; then the 3D reconstruction is completed by the program technique; finally the obtained data is finally the obtained data is input into the robot arm and the camera internal and external parameters are obtained by the calibration method so that the robot can accurately locate and The experiments show that the improved algorithm has advantages in recognition accuracy and grasping success rate under multi- The experiments show that the improved algorithm has advantages in recognition accuracy and grasping success rate under multi-vision system.

The combination of e-commerce and the green economy allows enterprises to distribute their green products directly to consumers through Internet channels. This paper investigates the impact of service spillovers on emission reduction and channel decisions in a two-echelon supply chain,in which the supplier is a Stackelberg leader and the retailer is a follower.By comparing the equilibrium outcomes of the single-channel and dual-channel supply chain in a setting with and without retail services, we observe that the supplier prefers to encroach on the market when services that retail locations provide largely spillover to and benefit the direct sales channel. Contrary to popular belief, a higher degree of service spillovers is beneficial for the retailer to get more returns under the dual-channel structure, whereas supplier encroachment will lead to a decline in the service level if the spillover degree is relatively low. In addition, the emission reduction level of products under supplier encroachment is always higher than that employed in the single-channel structure if consumers have both low-carbon preference and high degree of service sensitivity. Furthermore, we extend the equilibrium decisions under a carbon cap-and-trade (CCT) mechanism; the results fully verify the above conclusions. Interestingly, the implementation of a carbon price not only motivates carbon emission abatement and supplier encroachment, but also helps achieve a win-win outcome for supply chain members when service spillovers happen.

Background: We aimed to investigate the effectiveness of postnatal ultrasonography in determining congenital anomalies of the kidney and urinary tract in term infants with or without a history of congenital anomalies of the kidney and urinary tract in the prenatal period. Methods: In this retrospective cohort study, the records of term infants aged between six weeks and three months undergoing urinary system ultrasonography during routine child care were examined. Results: Congenital anomalies of the kidney and urinary tract was determined in 121 (4.62%) of the 2620 cases included in the study. The most common anomaly was hydronephrosis (in 69.4% of the congenital anomalies of the kidney and urinary tract cases and 3.21% of all cases). Thirty-two of the 84 (38.1%) hydronephrosis cases detected by postnatal ultrasonography, three of the nine (33.3%) renal agenesis cases, four of the seven (57.1%) horseshoe kidneys cases, one of the four (25%) multicystic dysplastic kidney cases and two of the two (100%) duplex system cases could not be detected by prenatal ultrasonography. On the other hand, hydronephrosis was not detected at postnatal ultrasonography in 29 (1.1%) cases which detected mild or moderate hydronephrosis by prenatal ultrasonography scanning. Conclusions: In our study, it was observed that approximately one-third of the cases of hydronephrosis, unilateral renal agenesis, duplex system, horseshoe kidney, and ectopic kidney could not be detected at prenatal ultrasonography screening. We therefore believe that, in addition to prenatal ultrasonography screening, postnatal ultrasonography screening of all children for urinary tract anomalies would be beneficial.

According to the cognitive radio (CR) paradigm, the efficient use of the radio spectrum is achieved by performing four main functions: spectral perception, spectral mobility, decision-making, and cooperation. In this work, a multivariable algorithm that considers geographic mobility (GM) is presented. The decision-making process includes a feedback mechanism for the dynamic selection of reservation channels in a wireless network with cognitive capabilities. Geographic mobility plays a crucial role in how radio takes advantage of its environment; however, it has been scarcely explored in the literature. In the present work, geographic mobility tests were carried out involving the interaction of CR and primary users (PU), where a measurement of the latency time of the proposed algorithm called: Algorithm for Decision-Making with Geographic Mobility (ATDeMoGeo) was evaluated and compared with other algorithms such as: Dijkstra's Algorithm, Analytic Hierarchical Process (AHP), Fuzzy Analytic Hierarchical Process (FAHP) and Decision-Making Algorithm with Modified Dijkstra (ATDDiM). It was found that the proposed algorithm is robust and that it considerably reduces the latency time to accurately determine the best communication channels, thanks to the decision-making function implemented to establish which channels the CRs can occupy. For the selection of the best reserve channels, a series of criteria were considered, such as: signal-to-interference plus noise ratio (SINR), bandwidth (BW), probability of channel availability (AP), estimated channel time of availability (ETA) using the random waypoint mobility model (RWPM). These criteria are evaluated for two types of service, i.e., real time (RT) and best effort (BE). For the evaluation and validation of the ATDeMoGeo algorithm, a network with cognitive characteristics in NS-3 was simulated. The simulation scenarios consisted of a base station (BS) with mobile CRs and PUs. Based on the previous criteria, i.e., BW, SINR, AP and ETA, the BS assesses the spectrum occupancy information obtained by the CRs. The results show that the proposed algorithm can be used without problem for the proposed scenarios with higher speed and accuracy for the selection of better communication channels.

The aim of this study is to improve the therapeutic effectiveness of the sorafenib loaded polymeric nanoparticles, surface modified by the pluronic F-127 for the treatment of hepatocellular (HCC) and renal cell carcinomas (RCC). Poly Lactic co-glycolic acid (PLGA) was used to encapsulate sorafenib by simple modified solvent evaporation technique. The nanoparticles were prepared with different concentration of sorafenib and pluronic F-127 keeping PLGA concentration constant. There were no incompatibilities among the sorafenib, PLGA and pluronic F-127 showing that the integrity of polymer, stabilizer and drug remain the same under different conditions. The size of the coated and plain PLGA nanoparticles were ~140 ± 14.7 nm and ~ 200 ± 10.1 nm, respectively. The in-vitro release studies demonstrated that the PLGA controlled the release of sorafenib, avoiding the initial burst release. The effect of coated and plain nanoformulations was found out in squamous cell carcinoma cells. The results showed that surface modified nanoparticles treated hepatocellular and renal carcinoma in a better way as compared to plain PLGA nanoparticles and free dug by keeping the dose constant (20 mg/kg body weight).The targeted delivery of polymeric PLGA nanoparticles into squamous cell carcinoma was improved. The pharmacokinetic parameters have been improved significantly as compared to the reported nanoformulations.

Objective: To explore the application effect of Atropine injection combined with nursing intervention on the interventional treatment of PATENTS with ST-segment elevation myocardial infarction. Methods: A total of 60 patients with ST-segment elevation myocardial infarction treated in our hospital from January 2022 to January 2023 were selected as the research objects. According to different nursing methods, they were divided into conventional group (n = 30) and systematic group (n = 30), both groups were treated with percutaneous coronary intervention (PCI). The conventional group received routine nursing before and after operation. On the basis of routine nursing, systematic nursing cooperation was given in the system group. The time of opening infarct vessels, the incidence of total adverse reactions during interventional treatment, mortality, success rate of treatment, improvement of cardiac function and length of hospital stay were compared between the two groups. Results: The time of opening infarct vessel in system group was significantly better than that in routine group (P < 0.05). The total adverse reaction rate in system group was significantly lower than that in routine group (P < 0.05); The mortality of routine group was significantly higher than that of system group (P < 0.05). The success rate of system group was significantly higher than that of routine group (P < 0.05); The number of patients with improved cardiac function and length of hospital stay in system group were significantly better than those in routine group (P < 0.05). Conclusion: Good intraoperative cooperation and nursing is an important guarantee for patients with ST-segment elevation myocardial infarction, which can effectively reduce the occurrence of adverse reactions during interventional treatment, improve the success rate of treatment, and reduce the death of patients during interventional treatment.

TThis paper delves into the extension and characterization of radial positive definite functions into non-integer dimensions. We provide a thorough investigation by employing the Riemann-Liouville fractional integral and fractional Caputo derivatives, enabling a comprehensive understanding of these functions. Additionally, we introduce a secondary characterization based on the Bernstein characterization of completely monotone functions. The practical significance of our study is showcased through an examination of the positivity of the fundamental solution of the space-fractional Bessel diffusion equation, highlighting the real-world applicability of the developed concepts. Through this work, we contribute to the broader understanding of radial positive definite functions and their utility in diverse mathematical and applied contexts.

Fourteen quinolizidine derivatives, structurally related to the alkaloids lupinine and cytisine and previously studied for other pharmacological aims, were presently tested for antiarrhythmic, inotropic, and chronotropic effects on isolated guinea pig heart tissues, and to assess calcium antagonism in comparison to amiodarone, lidocaine, procainamide, and quinidine. All compounds, but two, compared favorably with the reference drugs. Potent antiarrhythmic activity was observed for compounds (in increasing order) 4, 1, 6 and 5. The last compound N-(3,4,5-trimethoxybenzoyl)aminohomolupinane) was outstanding, exhibiting a nanomolar potency (EC50 = 0.017 µM) for the increase of threshold of ac-arrhythmia, and being devoid of antihypertensive activity against spontaneously hypertensive rats.

Building on the carbon reduction targets agreed in the Paris Agreements, many nations have renewed their efforts toward achieving carbon neutrality by the year 2050. In line with this ambitious goal, nations are seeking to understand the appropriate combination of technologies which will enable the required reductions in such a way that they are appealing to investors. Around the globe, solar and wind power lead in terms of renewable energy deployment, while carbon capture and storage (CCS) is scaling up toward making a significant contribution to deep carbon cuts. Using Japan as a case study nation, this research proposes a linear optimization modeling approach to identify the potential contributions of renewables and CCS toward maximizing carbon reduction and identifying their economic merits over time. Results identify that the combination of these three technologies could enable a carbon dioxide emission reduction of between 55 and 67 percent in the energy sector by 2050 depending on resilience levels and CCS deployment regimes. Further reductions are likely to emerge with increased carbon pricing over time. The findings provide insights for energy system design, energy policy making and investment in carbon reducing technologies which underpin significant carbon reductions, while identifying potential regional social co-benefits.

Most IoT systems meant for implementing mission-critical systems are multi-layered based. The majority of the computing is done in the services and gateway layer. The Gateway layer connects the Internal section of the IoT to the cloud through the Internet. The failure of any node between the services servers and the gateways will isolate the entire network leading to zero tolerance. A networking topology is required to connect the service servers to the gateways, yielding 100% fault tolerance. Empirical formulation of the model chosen to connect the service’s servers to gateways through routers is required to compute the fault tolerance of the network. Rectangular and Interstitial Mesh have been proposed in this paper to connect the service servers to the gateways through the servers that yield 0.999 fault tolerance of the IoT network. An empirical formulation is also presented using which the Fault tolerance of the IoT network can be computed. An enhancement of 11% in the fault tolerance capability of an IoT network has been achieved by implementing Rectangular and Interstitial Mesh in the gateway layer of the network.

With technological transformations such as big data, blockchain, artificial intelligence, and cloud computing, digital techniques are penetrating the field of finance. Digital finance is a resource-saving and environmentally friendly innovative financial service. It shows great green attributes and can drive the flow of financial resources towards environmentally friendly enterprises, thereby promoting green and low-carbon development. This paper investigates the effects of digital finance on green and low-carbon cyclic development and the mechanism. First, the level of green and low carbon cyclic development in China is estimated from multiple aspects based on the panel data of 31 provinces by using the spatio-temporal range entropy weight method. Then, the working mechanism of digital finance on green and low carbon cyclic development is revealed by performing empirical tests based on panel regression models, mediating effect models, and threshold models. Finally, the effects of digital finance and conventional variables on green and low-carbon cyclic development are investigated by using a random forest model and a CatBoost model in based on the machine learning. The results show that digital finance has significant positive effects on green and low-carbon cyclic development, and technological innovation plays a key role in the effects of digital finance on green and low-carbon cyclic development; meanwhile, the driving effect of digital finance on green and low carbon cyclic development shows nonlinear features with increasing “marginal effect”; besides, both digital finance and conventional factors have significant impacts on green and low carbon cyclic development. This study provides an empirical basis and path reference for digital finance to achieve “carbon peak, carbon neutralization” in China.

Recently, some authors have claimed that we may live in one of a pair of universes in which one is expanding receding from the Big Bang and its partner is contracting and moving towards the Big Bang. We show that near a black hole binary system, this event may be occurring. If we suppose that there is a N dimensional brane which contains many smaller k dimensional branes and black holes, there is a possibility that the curved space times near black holes act like mirrors. This is because these space-times contain two regions such that the branes in the one region have opposite quantum numbers with respect to the branes in the other region. Also, if branes in one region are expanding and go away from a point state and the Big Bang, anti-branes in the other region are contracting and moving towards the point state and the Big Bang. If black holes join and form a binary system, then their states become similar to two mirrors that are facing each other and producing many images themselves of smaller branes and even black holes in the binary system. Summing over all branes and images give the CPT system. Dark energy could be a result of the images of observed matter. Comparing the masses of the observed objects and dark energy, the angle between cosmic mirrors like black hole binary systems could be determined.

: Molecular targeting strategies have been used for years to control cancer progression and are often based on targeting various enzymes involved in metabolic pathways. Keeping that in mind, it is essential to know the role of each enzyme in a particular metabolic pathway. In this review, we are providing in-depth knowledge of various enzymes such as ceramidase, sphingosine kinase, sphingomyelin synthase, dihydroceramide desaturase, and ceramide synthase, which are associated with multiple types of cancer that depend on ceramide metabolism. Focus has also been given to discussing physicochemical properties of well-studied inhibitors of natural products origin and their related structures for these enzymes. Targeting ceramide metabolism exhibited promise in mono and combination therapies at preclinical stages to prevent cancer progression and paved the way for the significance of sphingolipid metabolism in cancer treatments. Targeting ceramide metabolizing enzymes will help the medicinal chemist to design potent and selective small molecules for treating cancer progression at various levels.

This paper studies the trajectory tracking control of an autonomous underwater vehicle (AUV) based on a stochastic uncertain nonlinear system. We investigate the time-varying gain adaptive control method looking for possible approaches to alleviate the heavy computational burden. Under nonlinear growth, conditions satisfy polynomial growth conditions. These two problems are resolved the fast response time and good path tracking, respectively. Novel adaptive algorithms are developed exploiting the dynamic properties of the AUV motion. By appropriately turning the original controller design problems into parameters choosing problems and then solving them in a functional time-varying observer technical theorem. In order to deal with the station error of system converges to arbitrarily small domains with stochastic uncertain disturbance. A coordinate transformation is proposed for all system states to meet boundedness. We show that the convergence of the AUV trajectory errors can be guaranteed by the proposed contraction constraints in the stability analysis, closed-loop stability is proved, and the system is asymptotically probabilistic in the global scope. They are taking advantage of the guaranteed stability. Extensive simulation studies on the AUV model demonstrate the effectiveness and robustness of the proposed approach. A real-time time-varying gain constructive control strategy is further developed for the Hardware-in-the-loop simulation; the controller design results are imported into the AUV actuator model to verify the effectiveness of the controller design.

Concrete is the most utilized construction material worldwide. In the marine environment, it is subject to chemical degradation through reactions with chloride (the most important ion), sulfate and magnesium ions in seawater and to biodeterioration resulting from biological (initially microbiological) activities, principally acid production. These two types of corrosion are reviewed and the failure of attempts to predict the degree of deterioration resulting from each is noted. Chemical (abiotic) corrosion is greatest in the splash zone of coastal constructions, while phenomenological evidence suggests that biodeterioration is greatest in tidal zones. There have been no comparative experiments to determine the rates and types of microbial biofilm formation in these zones. Both chemical and microbiological concrete deterioration are complex and have not been successfully modeled. The interaction between abiotic corrosion and biofilm formation is considered. EPS can maintain surface hydration, potentially reducing abiotic corrosion. The early marine biofilm contains relatively specific bacterial colonizers, including cyanobacteria and proteobacteria; these change over time, producing a generic concrete biofilm, but adhesion of microorganisms to concrete in the oceans is little investigated. The colonization of artificial reefs is briefly discussed. Concrete appears to be a relatively prescriptive substrate, with modifications necessary to increase colonization for the required goal of increasing biological diversity.

The global environmental impact of plastic waste is significant, with only 9% being recycled, causing pollution and harming the environment and humans. Due to increased traffic, limited funding, and dwindling natural resources, Jordan's road network is deteriorating rapidly. Pavement performance can be improved through high-quality materials and sustainable construction practices. The research investigates using Polyethylene Terephthalate as a polymer additive in asphalt mixtures to enhance their properties. Basalt and limestone mixtures were applied to asphalt mixtures. The optimal binder content for the control mixture was 4.8% for basalt and 4.93% for limestone. When modified with 10% PET, the basalt mixture showed slightly better stability than the control mix, while higher PET proportions led to reduced strength. PET-modified mixtures consistently displayed higher flows and bulk densities, with a more pronounced impact on the basalt mixture. PET increased the air-void ratio in basalt but had minimal effect on VMA. PET offers economic and environmental advantages, saving 8.4% of the original bitumen cost. As a result, limestone mixture properties, which are inferior to basalt mixture properties, improved significantly compared to basalt mixture properties. PET has the potential to create sustainable and high-performing asphalt mixtures, providing valuable insights for road construction and environmental management.

This study presents the synthesis of graphitic carbon nitride (g−C3N4) and its nanostructures with cobalt ferrite oxide (CoFe2O4) and silver nanocubes (Ag) using the combined pyrolysis of melamine and polyol method. The resulted nanostructures were tested as electrocatalysts for hydrogen and oxygen evolution reactions in alkaline media. It was found that the Ag/CoFe2O4/g−C3N4 shows the highest current density and gives the lowest overpotential of −259 mV for HER to reach a current density of 10 mA cm−2 in 1 M KOH. Overpotentials to reach the current density of 10 mA·cm−2 for OER are 370.2 mV and 382.7 mV for Ag/CoFe2O4/g−C3N4 and CoFe2O4/g−C3N4, respectively. The above results demonstrate that CoFe2O4/g−C3N4 and Ag/CoFe2O4/g−C3N4 materials could act as a bifunctional catalyst due to the notable performance towards HER and OER and for total water splitting in practical applications is a promising alternative to noble metal-based electrocatalysts.

The decentralized treatment of wastes is studied for an urban scenario considering a high-density population of 2500 inhab./km2. Food and garden waste were assumed to be treated in a co-digestion configuration using several mid-size digesters. In contrast biogas and digestate valorization were carried out in a centralized manner. Electricity and thermal energy were produced from this configuration, accounting for 1.3% of residential electricity demand and 3.2% of thermal demand when using double-turbocharged engines. However, the location of the treatment plants is a factor that may raise social discomfort. Rejection of locating the plant in specific sites close to residential neighbors, nuisance due to possible odor and gaseous emissions, and house market distortions are just a few of a long list of problematic aspects that may threaten the decentralized alternative. These factors are of great relevance and must be given a practical solution if the circular economic model is to be implemented by considering the insertion of waste streams into the production system and generating local energy sources and raw materials.

In the end, this paper analyzed the economy from the investment in plant construction, raw material collection, product production and product sales. The resulting products include pyrolytic carbon, pyrolytic oil, pyrolysis gas. The results showed that when the treatment scale was 1 ton h−1, the pyrolysis plants with three loading modes will always be in a state of loss during the 20-year running time. When the processing scale was 9 ton h−1, the pyrolysis plant can be profitable in the first year. In the sensitivity analysis, the influence of three pyrolysis products on the total return on investment was explored. The results showed that the price change of pyrolysis oil has the greatest influence on the total return on investment (Total ROI) under the three loading methods, The price change of pyrolysis gas has minimal impact on the Total ROI. This study provides basic data and basis for the commercialization of coal-biomass co-pyrolysis technology and investment in plant construction.

Combinations of Dilwet, an organosilicone surfactant, and ethephon, a hormonal compound often applied to fruit trees to thin the crop, were applied at full bloom to prevent fruit development in two young vineyards differing in elevation by 600 m. Each vineyard was planted with the same 19 red and 10 white grape cultivars from a range of countries of origin. Vineyard elevation did not affect response to treatment. A combined spray of 0.5% Dilwet with 0.04% ethephon reduced cluster number by an average of 85%, while weight of the remaining clusters was reduced by 63%, compared to unsprayed controls. Increasing the concentration of Dilwet to 1% reduced cluster number by 93% and cluster weight by 76%. There were significant differences in the response of cultivars to the treatments, depending on country of origin, with grapes originating in France responding better to higher concentrations of Dilwet. White grapes were more responsive than red grapes. These results highlight the need to test different cultivars and genetic origins of crops when examining the effects of new agricultural chemicals.

Microalgae are a source of carotenoids, phycocyanin, phenol, amino acids, polyunsaturated fatty acids, sulfated polysaccharides, pigments, and other bioactive molecules with antimicrobial, antioxidant, antiviral, antitumor, anti-inflammatory, and fat-burning properties. The increasing incidence of infectious processes, including tuberculosis, caused by antimicrobial resistant strains of microorganisms necessitates the search for alternative sources of compounds with antimicrobial activity, including microalgae. In this study, the antimicrobial properties of marine and freshwater microalgae extracts were evaluated against Gram-positive (Staphylococcus aureus, Enterococcus faecalis, and Streptococcus pyogenes) and Gram-negative (Klebsiella pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa), Mycobacterium tuberculosis strain H37Rv and Mycobacterium smegmatis. Water, dimethyl sulfoxide, and ethanol were used as extractants. The obtained microalgae extract exhibited cytotoxicity against splenocytes and, to a lesser extent, against peritoneal macrophages of CBA mice. The bacteriostatic effect of the microalgae extracts against bacteria and mycobacteria was demonstrated by MTT test. In addition, activation of bacterial and mycobacterial growth was observed in a number of cases with high levels of microalgae extracts in the medium. In an expression model of tuberculosis in mice, a decrease in mycobacterial load in the lungs and spleen was observed. Thus, microalgae have moderate to weak antimicrobial activity.

The purpose of this study was to investigate the horizontal force and contribution of shoulder horizontal adductor and elbow extensor muscles activity during wide and narrow grip bench press (BP) in various conditions, such as resistance trained/non-trained, concentric/eccentric and muscle fatigue/non-fatigue.　We measured the horizontal force on the bar and the electromyographic (EMG) muscle activity of pectoralis major (PM) and triceps brachii (TB) during 10RM BP with wide grip (81cm) and narrow grip (40cm)　in 7　resistance trained men and 7 non-trained men. The all-reps average of the horizontal to vertical force ratio both in resistance trained and non-trained subjects was about 30% outward for the wide grip, and about 10% inward for the narrow grip. The EMG contribution ratio PM/TB shows no significant differences between narrow and wide grip in all evaluated conditions except in non-trained subjects muscle fatigue eccentric phase. Both resistance trained and non-trained subjects did not push the bar straight upward, and the EMG PM/TB was almost unchanged by hand width. The direction adjustment of the force on the bar that achieves almost the same muscle activity degree of the shoulder and elbow joints might be optimal BP kinetics.

In an era of global connectivity, language and literature education faces the challenge of navigating multilingualism, cultural diversity, and technological advancements. This paper explores the challenges and opportunities in language and literature education in the era of global connectivity. Through a qualitative research approach, interviews, focus group discussions, and classroom observations were conducted with 30 Arts and Sciences students and teachers. The findings reveal significant themes related to cultural diversity, multilingualism, and the integration of technology in language learning. The study emphasizes the importance of inclusive pedagogies, critical thinking development, and the incorporation of authentic and diverse literary works. Recommendations are provided for educators and policymakers to promote intercultural understanding and enhance language and literature education. The limitations of the study suggest areas for future research, including long-term language proficiency and diverse contextual considerations. Overall, this paper calls for ongoing innovation and collaboration to meet the evolving needs of language and literature education in an interconnected world.

Kenya’s construction industry is experiencing exponential growth in tandem with construction trends globally. With the growth experienced in the industry, there has been significant growth in the economy and a 50% contribution to the world’s landfill waste and pollution to the adjacent environment. Globally, the construction industry is among the largest consumers of natural resources and significant contributors to pollution. This has given rise to high pressure to adopt environmentally sensitive approaches in the construction industry to present a competitive advantage. It is, therefore, crucial to address the need for sustainability measures for Landscape Architecture projects to increase knowledge and awareness, create incentives geared towards supporting sustainable practices, and leverage legal instruments and policies. Green construction practices and strategies have positively impacted the environment and the Kenyan construction industry’s social and economic performance. However, there are several barriers to the adoption and improvement of monitoring and evaluation of sustainable practices, thus slowing down the industry in taking charge of sustainability.

Autonomous driving vehicles rely on sensors for the robust perception of surroundings. Such vehicles are equipped with multiple perceptive sensors with a high level of redundancy to ensure safety and reliability in any driving condition. However, multi-sensor, such as camera, LiDAR and radar, systems bring up the requirements related to sensor calibration and synchronization, which are the fundamental blocks of any autonomous system. On the other hand, sensor fusion and integration have become important aspects of autonomous driving research and directly determine the efficiency and accuracy of advanced functions such as object detection and path planning. Classical model-based estimation and data-driven models are two mainstream approaches to achieving such integration. Most recent research is shifting to the latter, showing high robustness in real-world applications but requiring large quantities of data to be collected, synchronized, and properly categorized. To generalize the implementation of the multi-sensor perceptive system, we introduce an end-to-end generic sensor dataset collection framework that includes both hardware deploying solutions and sensor fusion algorithms. The framework prototype integrates a diverse set of sensors, such as cameras, LiDAR, and radar. Furthermore, we present a universal toolbox to calibrate and synchronize three types of sensors based on their characteristics. The framework also includes the fusion algorithms, which utilize the merits of three sensors , namely, camera, LiDAR and radar, and fuse their sensory information in a manner that is helpful for object detection and tracking research. The generality of this framework makes it applicable in any robotic or autonomous applications, also suitable for quick and large-scale practical deployment.

The deployment of a manufacturing execution system (MES) holds promising potential in facilitating the accumulation of a substantial amount of inspection data. Low quality levels in discrete manufacturing environments are the result of multi-factor coupling and failure to find quality issues in a timely manner within manufacturing settings may trigger the propagation of defects downstream. Currently, most of the inspection quality methods are direct measurement followed by manual judgment. The integration of deep learning methods provides a feasible way to identify defects in a timely manner, thus improving the acceptance rate of factories. This paper focuses on the design of a data-driven quality prediction and control model around discrete manufacturing characteristics, and use fuzzy theory to evaluate the quality level of production stages. Building Multivariate Long and short-term memory learning hidden quality representations to extract predictions from multi-level inspection data in manufacturing systems. Finally, by validating the data of actual produced water dispensers according to three evaluation indexes, RMSE, MAE, MAPE, the results show that Multivariate Long and short-term memory has better prediction performance.

Single and multi-vehicle crashes are a significant issue that causes economic and social costs and has therefore gained attention. This study explored the factors associated with injury severity for both single- and multi-vehicle crashes using over 550,000 crash data points in Japan between 2019 and 2021. We identified the determinants of road infrastructure and traffic control while controlling for driver, vehicle, environmental, and accident characteristics by applying ordered logit and bias-reduced binomial regression models. Our findings are as follows. 1) Traffic control variables did not affect single-vehicle crashes. 2) Guardrails had a higher severity in both single-vehicle crashes and multi-vehicle crashes at intersections. 3) The impact of the centerline differed between intersections and non-intersections for multi-vehicle crashes.  These results of this study provide transportation agencies with important guidance as to the road infrastructure and transport control.

As a part of the European Green Deal, the Corporate Sustainable Reporting Directive will apply to over 50,000 companies in Europe, meant to advance the quality of sustainability reporting in the EU, and reduce global emissions and emission distribution inequality. Part of the requirements centre around organisational emission quantification, which will bring much attention to the methodological aspects and resulting decision support capability, which calls for synthesis and argues for clarity. Currently, quantifying the emissions embedded in global transactions mostly focus on direct value-chain attributes, and do not consider unintended consequences beyond the scope of assessment. To achieve genuine reductions, estimated emissions must be considered from a systems perspective to accurately reflect their true impact. While emission inventories serve several purposes, incorrect application limits their potential. The CSRD aligns itself with the GHG Protocol, which does not explicitly facilitate this distinction, although new Land Sector and Removals Guidance draft does, in part. With first CSRD reports expected in 2025, and the GHG protocol entering a revisions period, it presents an opportunity to marry systems thinking with carbon literacy, thereby equipping the expected surge of activity with the sufficient tools for an accelerated transition.

Background: Pulmonary sequestration (PS), generally diagnosed using computed tomography pulmonary angiography (CTPA), is a rare congenital developmental malformation of the lung that is characterized by nonfunctional lung tissue independent of the normal lung tissue. This study summarizes the imaging features of the supplying arteries and draining vessels in patients with PS with an aim to assist with timely clinical diagnosis and operation guidance. Materials and Methods: A total of 55 patients with PS diagnosed on CTPA from multiple clinical centers were retrospectively analyzed. Data included demographic characteristics, imaging features, disease location, isolation type, and the features of supplying and draining vessels, as shown on CTPA images. Results: Of the 55 patients reviewed, 3 (5.45%) were children, 3 (5.45%) were adolescents, and 49 (89.09%) were adults, with a mean age of 44 years. Fifty-four (98.18%) patients had intralobar sequestration and one (1.82%) had extralobar sequestration. PS was noted 3.5 times more frequently in the left lower lobe than in the right lower lobe. For the supplying arteries, 47 (85.45%) were derived from the descending thoracic aorta, 1 (1.82%) from the abdominal aorta, 7 (12.73%) from the celiac axis, and 1 (1.82%) from the bronchial artery. The draining vessels were the pulmonary veins in 49 patients (89.09%), the umbilical vein in 1 (1.82%), the venae intercostal in 1 (1.82%), the pulmonary arteries in 11 (20.00%), and not shown on the images in 2 (3.64%). Conclusion: Clinical presentations of PS are non-specific and can be easily missed or misdiagnosed. However, CTPA can help improve the diagnostic accuracy and identify the supplying arteries and draining vessels, which significantly contribute to surgical planning.

Heart transplantation is a treatment of choice for patients with severe heart failure. Infection transmission from a donor to a recipient remains a prominent problem in organ transplantation. However, the risk of SARS-CoV-2 transmission through nonlung organ transplantation is still unclear. In the article we present a case of a 28-year-old pregnant woman who developed heart failure soon after recovery from SARS-CoV-2 infection in the third trimester of gestation. In the postpartum period the disease worsened and the patient required cardiac transplantation. We examined the recipient's heart and diagnosed left ventricular noncompaction cardiomyopathy. Immunohistochemical analysis showed the SARS-CoV-2 antigen expression in the donor’s heart before transplantation and after the surgery the endomyocardial biopsy was taken. Moreover, an ultrastructural assessment of the endomyocardial specimen revealed endothelial and pericyte injury and single particles on the surface of endothelium consistent with SARS-CoV-2. Recent findings were associated these damages with SARS-CoV-2 infection. The present study describes the rare case of SARS-CoV-2 transmission from donor to recipient through a heart transplant and resulting in endothelial cell and pericyte activation and humoral immune response activation.

Background: Chronic non-specific low back pain (CNSLBP) is defined as back pain that lasts longer than 12 weeks. Objectives: To investigate the efficacy of manual therapy (MT) program combined with Capacitive and Resistive Electric Transfer (TECAR) therapy in individuals with CNSLBP. Method: Sixty adults with CNSLBP were randomly equally divided into three groups. The first group followed an MT protocol in the lumbar region (MT group), the second group followed the same MT protocol combined with TECAR therapy (MT + TECAR group) using a conventional capacitive electrode as well as a special resistive electrode bracelet and the third group (Control group) received no treatment. Both intervention programs included six treatments over two weeks. Pain in the last 24 hours with the Numeric Pain Rating Scale (NPRS), functional ability with the Roland-Morris Disability Questionnaire (RMDQ), Pressure Pain Threshold (PPT) in the lumbar region with pressure algometry, and mobility of the lumbo-pelvic region through fingertip-to-floor distance (FFD) test were evaluated before and after the intervention period with a one-month follow-up. Analysis of variance with repeated measures was applied. Results: In the NPRS score, both intervention groups showed statistically significant differences compared to the control group both in the second week as well as in the one-month follow-up (p < .001). Between-groups differences were also noticed between the two intervention groups in the second week (p < .05). Differences in the RMDQ score in the second week and on the one-month follow-up were detected between the intervention groups and the control group (p < .001), while differences between the two intervention groups were only detected in the one-month follow-up (p < .001). Regarding the PPT values, differences were found mainly between the MT + TECAR and the control group and between the MT + TECAR and the MT group (p < .05), with the MT + TECAR group in most cases showing the greatest improvement compared to the other two groups, which remained statistically significant in the one-month follow-up (p < .05). Finally, both intervention groups improved the mobility of the lumbo-pelvic region in both time points compared to the control group without, however, statistically significant differences between them (p> .05). Conclusion: The application of an MT protocol with TECAR therapy appeared more effective than conventional MT as well as compared to the control group in reducing pain and disability and improving PPT in individuals with CNSLBP. No further improvement was noted in mobility of the lumbo-pelvic region by adding TECAR to the MT intervention.

Enhanced oil recovery using nanoparticles is a promising method. However, when injected into a reservoir, nanoparticles can block pores and cause permeability damage. Therefore, enhancing their performance to lower the permeability damage effect is crucial. This study investigated the effect of pH alteration through carbon dioxide (CO2) injection on the permeability damage of limestone caused by the aluminum oxide (α-Al2O3) nanofluid. The methodology involved nanofluid alternating CO2 core flooding experiments by using nanofluids with pH of 4.5 and 2.8. After core flooding, permeability damage was calculated as a percentage of the reduction of the original permeability. The results revealed that the permeability damage in the case of nanofluid alternating CO2 injection was 23.23%. In only nanofluid with a pH of 4.5 injection case, permeability damage was 47.53%. In the 2.8 pH nanofluid injection case, permeability damage was 31.01%. The retention of nanoparticles was confirmed through scanning electron microscopy and energy dispersive X-ray analysis. Permeability damage could be attributed to a large nanoparticles’ agglomeration size, roughness of pore surfaces, and nanoparticle sedimentation. The results of the study revealed that altering pH through the α-Al2O3 nanofluid alternating CO2 injection can effectively reduce the permeability damage of limestone.

Achieving universal access to water and sanitation services in developing countries requires a coherent legal, political, and institutional environment, along with a clear financial strategy. Regionalizing utilities may be crucial for addressing disparities, economic inequalities, and governance challenges. Regionalization offers economies of scale, resource efficiency, knowledge sharing, and collaboration. The cornerstone will be ensuring the financial-economic viability of regional utilities, considering their social impacts in terms of affordability. The State of Santa Catarina case study is assessed. In the case of Santa Catarina, only four regional utilities currently generate sufficient revenue, without factoring in necessary investments, indicating the need to review design parameters to improve operational efficiency and increase revenues. Additional financial support may be required to ensure universal access. Tariff adjustments must strike a balance between cost-effectiveness and affordability for families.

The stability of the filling roof as an important bearing unit in the stope of the access stope in the filling mining method is of great significance to guarantee the safe and efficient production of the mine. Arrangement of mining approach in downward cemented filling stope is the key factor af-fecting stability of filling body roof. Based on combination of laboratory test, theoretical analysis and numerical simulation, the influence of different mining approach arrangement on stability of filling body roof is analyzed. The weak filling surface is formed between adjacent mining paths. The mechanical strength of the weak filling surface is significantly reduced by laboratory experiments. The relationship between distribution of the weak filling surface, azimuth angle and stability of filling roof is further studied by numerical simulation. The results show that the stability of the filler roof is the best when the upper and lower stratified mining approach is arranged vertically.

Perovskite solar cells are an evolving technology owing to self-assembling and highly tunable bandgap properties of materials. In this context, thin films of perovskites have attracted immense attention and witnessed great advancement because of their low manufacturing cost. The key development in these devices is the conversion efficiency, which rose from 3.8% to 28%. The formulation of innovative materials with the proper replacement of lead in perovskites is imperative to mitigate lead toxicity. Here, we analyzed the challenges like material and structural stability, device stability under high temperature and humidity conditions, lifetime, manufacturing cost, etc. faced in the commercialization of perovskite devices. This review shows that challenges such as device engineering, performance stability against the harsh environment, cost-effectiveness, and environmental concern should be taken into consideration for the widespread acceptance of perovskite-based solar devices. In conclusion, we suggested that an enormous scope exists for exploring high-performance and long-lasting perovskites for energy applications.

Introduction: Osteosarcomas of the jaw (OSJ) are rare tumors with a different behavior from osteosarcomas of other bones. This study aims to analyze the clinical, pathological, and therapeutic characteristics of this type of sarcoma. Methods: a retrospective observational study of cases diagnosed with OSJ registered at the “La Paz” University Hospital (Madrid). Results: Eight cases with a diagnosis of OSJ were obtained in a study period of 22 years (2000-2022). The mean age was 41 years. The distribution was 1:1 between the maxilla and mandible. Painful inflammation was the most frequent clinical manifestation. Conventional osteoblastic osteosarcoma was the most common. Survival at 5 years was 50%, while at 10 years, it decreased to 25%. Conclusions: OSJ differs from conventional osteosarcomas of long tubular bones. Surgery continues to be the mainstay of treatment; more studies are needed in which more standardized protocols can be proposed for adjuvant therapeutic management.

The coronavirus disease 2019 (COVID-19) is a novel global pandemic infectious disease with higher potential for outbreaks than the other epidemic disease such as severe acute respiratory syndrome (SARS), influenza A (H1N1), and the Middle East respiratory syndrome (MERS), which identified in China on December 31, 2019. This disease is caused by a new generation of betacoronavirus termed as the 2019 novel coronavirus (2019-nCoV) or SARS-CoV-2. Although, the first report of this disease was in recent months, now, the COVID-19 is known as a global pandemics. Hence, the aim of this article is the quick review of the recent studies on the novel coronavirus disease 2019 including researches on the epidemiological parameters, mechanism of action, diagnosis, and treatment of the novel coronavirus disease, as well as clinical features of patients infected with COVID-19. Moreover, the novel COVID-19 has comprised of SARS, H1N1, and MERS.

Radiomics involves the extraction of information from medical images not visible to the human eye. There is evidence these features can be used for treatment stratification and outcome prediction. However, there is much discussion about the reproducibility of results between different studies. This paper studies the reproducibility of CT texture features used in radiomics, comparing two feature extraction implementations namely Matlab toolkit and Pyradiomics when applied on independent datasets of CT scans of patients i) the open access RIDER dataset containing a set of repeat CT scans taken 15 minutes apart for 31 patients (RIDER Scan 1 and Scan 2 respectively) treated for lung cancer and ii) the open access HN1 dataset containing 137 patients treated for head and neck cancer. Gross tumor volume (GTV) manually outlined by an experienced observer available on both datasets was used. 43 common radiomics features available on Matlab and Pyradiomics were calculated using 2 intensity-level quantization methods with and without an intensity threshold. Cases were ranked for each feature for all combinations of quantization parameters and the Spearman’s rank coefficient, rs, calculated. Reproducibility was defined when a highly correlated feature in the RIDER dataset also correlated highly in the HN1 dataset and vice versa. 29 out of 43 reported stable features were found to be highly reproducible between Matlab and Pyradiomics implementations, having consistently high correlation in rank ordering for RIDER Scan 1 and RIDER Scan 2 (rs &gt; 0.8). 18/43 reported features were common in RIDER and HN1 datasets, suggesting they may be agnostic to disease site. Useful radiomics features should be selected based on reproducibility. This study identified a set of features that meet this requirement and validated the methodology for evaluating reproducibility between datasets.

Infrared dim and small target detection is a key technology of various detection tasks. However, due to the lack of shape, texture, and other information, it is a challenging task to detect dim and small targets. Recently, since many traditional algorithms ingore global information of infrared images, they generate some false alarms in complicated environments. To address this problem, in this paper, a coarse-to-fine deep learning-based method is proposed to detect dim and small targets. Firstly, a coarse-to-fine detection framework integrating deep learning and background prediction is applied for detecting targets. The framework contains of coarse detection module and fine detection module. In coarse detection stage, Region Proposal Network (RPN) is employed to generate masks in target candidate regions. Then, for further optimize the result, inpainting is utilized to predict the background by the global semnantic of images. In this paper, inpainting algorithm with a mask aware dynamic filtering module is incorporated into the fine detection stage to estimate background in candidate target areas. Finally, compared with existing algorithms, the experimental results indicate that the proposed framework have effective detection capability and robustness for complex surroundings.

There is little information about moisture changes in different altitudinal belts in mountainous regions of the Southern Russian Far East. We present ecological-taxonomic composition of the diatom flora, the botanical composition of peat of small mountain lake/mire complexes located in the Central Sikhote-Alin within large landslides on the paleovolcano slopes are identified. Frequent changes in diatom assemblages and peat-forming plants indicate unstable hydroclimatic conditions with varying degrees of watering and dry condition up to complete overgrowth of the lakes. Frequent change of sphagnum mosses with different trophic preferences was established. The chronology is based on 11 radiocarbon dates. Accumulation rates reached up to 1.9 mm/year, the temporal resolution for the reconstructions is up to 30–40 years. The tendencies of lake evolution depended on different-scale hydroclimatic changes for the last 4400 yr. The most detailed data for the last 2600 yr were obtained from the Nizhnee Lake sequence, more sensitive to climatic changes. The main reason for the change in the hydrological regime of the lakes was variations in precipitation during short-term climatic changes. The sediment record moisture fluctuations are relatively well correlated with regional patterns reflecting summer monsoon intensity and cyclogenesis activity.

Food demand and food supply have been heavily affected by Covid-19 pandemic. To understand changes in households’ behavior related to the pandemic, we investigate the willingness to pay for local organic apples pre- and during Covid-19. Besides, we assess whether the changes occurred within the family, estimating also separate models for the two members of the couple. Our findings show that respondents show a positive price premium for local organic apples whose consumption helps reducing the environmental costs associated with food production. The median estimated values during the pandemic range from 34% to 250%. Overall, respondents show a positive mean willingness to pay which increase with the pandemic. The socio-economic variables are the most important in explaining the willingness to pay, while the behavioral variables have more heterogeneous results even if the lifestyle and the request for information through the label are important variables. The pandemic tends to narrow the gaps in preferences between members of the couple. In conclusion, the local and organic dimension is embodied in the short chain in which knowledge and trust in the producer are crucial elements in the consumer's choices.

‘‘Sustainable Supply Chain Management’’ (SSCM) has become a hot topic on which eminent researchers are working on every day. However, it is clear that we still observe in this field of research, an artistic vagueness on the fundamental differences between Sustainable Supply Chain Management and Green Supply Chain Management (GSCM) Moreover, it is regrettable to note that previous researchers haven't yet thought about having a specific theory which can be applied to SSCM, the use of macro theories still being observed. In addition, we observe a lack of research in the oil and gas industry especially in Developing Countries when we know that this industry is the most lucrative and polluting. Therefore, this paper’s purpose consists to make a Systematic Literature Review (SLR) of 38 papers published from 2005 to 2023 especially in oil and gas industry and in Developing Countries, in order to make a clear distinction between SSCM and GSCM while highlighting the practices related to them and at the same time, generating a united theory which will bring together the triple bottom line of the SSCM. As findings, the authors built a Conceptual Framework that applies the triple bottom line of the SSCM in oil and gas industry by demonstrating that GSCM which is more related to environmental issues and is a part of the SSCM. Therefore, in order to be more efficient and to have a great impact on their performances, Oil and gas companies should apply SSCM practices rather than GSCM practices which are very different from what is applied in Developed Countries because of certain barriers and pressures.

Abstract: The purpose of this study is to explore, from the perspective of government interven-tion, behavioral logic and game relationship among farmers, service organizations and the gov-ernment in the pest and disease control outsourcing system, as well as the endogenous motiva-tion of each subject. The results indicate that the stronger the willingness of each subject, the faster the stable state of joint pest and disease control among the three parties can be formed; In the case of implementing a single policy tool, the convergence rate of each party that imple-ments the regulatory policy alone is fast but may be unstable, while the rate is slow but more stable when a guidance- or incentive-based policy is solely applied; The effect of policy tool combination is much better than that of a single policy tool applied. The simultaneous imple-mentation of the three types of policy tools can form a policy system with both positive and negative mechanisms, which can maximize complementary and superposition effect.

Antiretroviral therapy has effectively suppressed HIV infection and replication and prolonged the lifespan of HIV-infected individuals. In the meantime, various complications including type 2 diabetes associated with long-term antiviral therapy have shown steady increases. Metformin has been the front-line anti-hyperglycemic drug of choice and the most widely prescribed medication for the treatment of type 2 diabetes. However, little is known about the effects of Metformin on HIV infection and replication. In this study, we showed that Metformin treatment enhanced HIV gene expression and transcription in HIV-transfected 293T and HIV-infected Jurkat and human PBMC. Moreover, we demonstrated that Metformin treatment resulted in increased CREB expression and phosphorylation, and TBP expression. Furthermore, we showed that Metformin treatment increased the recruitment of phosphorylated CREB and TBP to the HIV LTR promoter. Lastly, we showed that inhibition of CREB activation significantly abrogated Metformin-enhanced HIV gene expression. Taken together, these results demonstrated that Metformin treatment increased HIV transcription, gene expression, and production though increased CREB phosphorylation and recruitment to the HIV LTR promoter. These findings may help design the clinical management plan and HIV cure strategy of using metformin to treat type 2 diabetes, a comorbidity with an increasing prevalence, in people living with HIV.

The purpose of this study is to analyse the ways of visualization of hidden violence through a map of the city of violence called La Manada City, in its transformation from defensive to artistic strategies. For this analysis, firstly we propose the contextualization of the artwork and its authorship, and later, the research about the artistic and visual resources of the 257 items that make up the map and its guide street, in a sort of rustic hypertext of the emotions linked to the violence in the territory. The main findings of this study demonstrate the strength of the strategy used as a survival method in cases of bullying. As a conclusion, in spite of the therapeutic effects, this work cannot be understood as Art Therapy, but as combat art: it provides an understanding of the emotional city, of the disadvantaged groups that inhabit it, from the most local (as a transcript of the city of Seville) to global and universal effects on community life.

With the continuous growth of electric and electronic appliances’ usage, the waste produced with obsolete material (e-waste) has an increasing environmental impact. Also, the production of such appliances bears to increased consumption of natural resources and produces a multitude of toxic and hazardous substances, which typically are not properly treated. One of the approaches that may be adopted to reduce such problems relies on the circularization of the current linear model, commonly adopted in the EEE value chain. This includes recovering eol products and reintroducing its parts, components, or raw materials into the value chain (e.g. semiconductors, circuit boards, raw metals, etc.), thus contributing to a more sustainable value chain. In this article, we present a state-of-art review that focuses on approaches and solutions for the EEE value chain traceability, and analyses the technologies that may be beneficial for promoting and implementing the CE model in this value chain.

Senegal central regions face rainfall deficit combined with scarcity of surface water and poor quality. Populations use groundwater for drinking and irrigation. A Groundwater assessment studiebased on 42 samples aims to determine their quality. Several parameters (TDS, TH, WQI, SAR, RSC, %N, PI, KR and MR) and ion chemistry determined . Samples exhibit an alcaline pH (7.6) and hydrochemical facies mainly Ca-Na-Mg-HCO3. The ionic dominance is Na+ ˃ Ca2+ ˃ Mg2+ ˃ K+ and HCO3- ˃ Cl- ˃ SO42- ˃ NO3- ˃ F-. From TDS and WQI index most of the groundwaters are suitable for drinking. Irrigation quality (based on SAR, %N, RSC, KR, MR) varie from excellent to good water type. Plotting chemical data (USSL salinity & Wilcox diagrams) reveals that the majority of the groundwater samples belong to the fields excellent to good and from good to permissible . Natural processes (rock weathering, mineral dissolution, evaporation and ion exchange) control groundwater quality. As the region faced a persistent rainfall deficit combine with fragile groundwater quality should alert the stakeholders. A sustainable development of the region can be faced if strong measures are planned to follow water quality evolution and quantity available for human purposes

The risk of 'zoonotic spillovers,' or the transmission of viruses from animals to humans, has been raised by climate change and the devastation of nature, as infectious disease experts have long warned. Even as the world works to stop the spread of the currently unfolding pandemic of coronavirus disease 2019 (COVID-19) and the breakout of monkeypox virus (MPXV), a new animal virus, the Langya henipavirus (LayV), has been discovered in humans in Eastern China. The scientists say there is little danger of the virus spreading among humans, but it shares genetic material with Hendra virus and Nipah virus, two other henipaviruses that infect humans and cause life-threatening respiratory diseases. Humans infected with LayV can expect to experience high body temperature, cough, weariness, poor appetite, muscle discomfort, myalgia, nausea and vomiting. It is likely that the virus will spread from animals to humans. Currently, the health authorities of Taiwan and other health organizations are tracking the progress of the ailment to ensure it does not reach humans. Researchers have examined 25 species of small wild animals for presence of the virus, and so far, shrews are the only ones that have tested positive for the virus's RNA. Based on these results, shrews are a possible candidate for the virus's natural reservoir. Too far, no therapies or vaccines have been developed and licensed for henipaviruses like the LayV. When other therapies fail to alleviate viral infections, ribavirin may be the next best thing. The need for novel vaccinations against the LayV infection and the timely delivery of these vaccines to areas at high epidemiological risk is real. To lessen the likelihood of a health calamity being caused by this newly developing virus, it is crucial to conduct active surveillance in a transparent and globally collaborative manner. The questions that have not been answered yet require additional study.

Japan is experiencing a super-aging society faster than is anywhere else worldwide. Consequently, extending healthy life expectancy is an urgent social issue. To understand diet that supports the extension of healthy life expectancy, we studied the relationships among quality of life (QOL: SF-36 questionnaire), physical activity (number of steps and activity calculated using an accelerometer), physical function (muscle strength, movement function, agility, static balance, dynamic balance, and walking function) and dietary intake among 469 older adults living in the Tokyo metropolitan area (65–75 years old, men/women = 166/303) from February 23, 2017, to March 31, 2018. There was a significant positive association between physical QOL and steps, moderate-intensity activity, and high-intensity activity (p &lt; 0.05), and a significant positive association (p &lt; 0.05) between physical activity and movement, static balance, and walking functions, but no association with muscle strength. These three body functions were significantly positively correlated with intake of vegetables, seeds, fruits, and milk, and with magnesium, potassium, vitamin B6, and the dietary fibre/carbohydrate ratio and composition ratios (p &lt; 0.05). Balancing food and nutrition may improve QOL in older adults through increased physical function and physical activity. Future verification of interventions is needed.

Policies are adopted and implemented to achieve specific goals. In this regard, the Government of Zambia in 2019 adopted the higher education policy with many objectives which include, the expansion of access to higher education; reduction of gender and other forms of inequity in accessing higher education; the improvement of quality of higher education by increasing funding to higher education institutions, construction, and repair of infrastructure in higher and improvement in the provision of learning materials in higher education institutions (HEIs).This paper, therefore, sought to evaluate the higher education policy of 2019. The four criteria were used namely; effectiveness, equity, policy sustainability, and consistency. Other principles such as political and social acceptability of a policy were not used because the policy is already adopted and being implemented. Further, the principle of efficiency was not used because it would have been problematic to gauge the expenditure against the outcomes.The findings have revealed that the policy to some extent has been effective; some of the objectives such as increased access to higher education and reduction of inequality have been partially achieved. It has been established that the number of students pursuing higher education has been increased to 114,049 in 2020 from 91,969 in 2017. Further, in 2021, 48.5% of scholarships in public universities were awarded to female students while 51.5% were awarded to female students. Further, more students are encouraged to pursue science, technology, engineering, and mathematics (STEM); and more women are pursuing studies in STEM-related fields. However, the policy has not helped to achieve the quality of higher education as funding in public HEIs has not improved. Further, infrastructure remains very poor and inadequate; and access to update and relevant learning materials also remains a challenge in HEIs. However, the policy seems to be duplicated by the recent re-launched Technical Education Vocation Entrepreneurship Training (TEVET) national policy.Given the above findings, it has been recommended that the government among other things improve funding and build infrastructure in public HEIs. There is also a need to harmonise the TEVET national policy with the higher education policy.

[Co(AMPY)(DAPY)Cl2(H2O)].H2O (1) [Cu(AMPY)(DAPY)Cl2(H2O)].H2O (2) [Zn(AMPY)(DAPY)Cl2(H2O)] (3) were prepared from the ligands; AMPY = 2-amino-4-methylpyrimidine (L1), DAPY = 2,3-diaminopyridine (L2) and CoCl2.6H2O, CuCl2.2H2O and ZnCl2 in water/ethanol solutions and the three products characterized by elemental analysis, ultraviolet-visible spectroscopy (UV–Vis), Fourier-transform infrared spectroscopy (FT-IR), magnetic susceptibility, molar conductivity methods, and TGA analysis. The X-ray powder diffraction of the Co(II), Cu(II), and Zn(II) compounds showed that the geometry of monoclinic and SEM analysis revealed their morphology with a smooth surface. Molecular modeling was performed for all compounds using the density functional method DFT/B3LYP to study the structures and the frontier molecular orbitals (HOMO and LUMO). We have used Gaussian09 software for the calculations. In this study, different complexes were tested against Gram negative and Gram positive bacterial species to give insight into their broad-spectrum effects. The used pathogenic strains were two Gram positive species "Staphylococcus aureus and Micrococcus luteus" and two Gram negative species "Salmonella thyphimurium and Escherichia coli. The antifungal activity was evaluated against a pathogenic reference strain of the yeast Candida albicans. The antimicrobial and antioxidant assay results demonstrate that the tested compounds are effective against Gram positive and negative bacteria. Additionally, the compounds have an antifungal effect against Candida albicans with a maximum inhibitory zone of 2.5cm. The results demonstrated high antioxidant potential for the Zn(II) complex with a DPPH scavenging of 91.5%, however, the Cu(II) complex was low (16.5%). The data of docking with tyrosyl-tRNA synthetase presented that all compounds fit very well in the catalytic pockets of the proteins of the receptor.

In this article we investigate the impact of “Renewable Electricity Output” on green economy in the context of circular economy for 193 countries in the period 2011-2020. We use data from World Bank ESG framework. We perform Panel Data with Fixed Effects, Panel Data with Random Effects, WLS, and Pooled OLS. Our results show that Renewable Electricity Output is positively associated, among others, to “Adjusted Savings-Net Forest Depletion” and “Renewable Energy Consumption” and negatively associated, among others, to “CO2 Emission” and “Cooling Degree Days”. Furthermore, we perform a cluster analysis implementing the k-Means algorithm optimized with the Elbow Method and we find the presence of 4 clusters. Finally, we confront seven different machine learning algorithms to predict the future level of “Renewable Electricity Output”. Our results show that Linear Regression is the best algorithm and that the future value of renewable electricity output is predicted to growth on average at a rate of 0.83% for the selected countries.

Earthworm invasions often reduce biodiversity and affect the ability of ecosystems to perform ecosystem functions. Over the past few decades, European lumbricide species have spread widely in natural habitats in Western Siberia, without completely displacing the native species. The aim of the present experiment is to study the survival, reproductive potential, vertical distribution, abundance, and biomass of Aporrectodea caliginosa and Lumbricus rubellus invasive for the region and the native species Eisenia nordenskioldi and their influence on each other. For this purpose, winter and vegetation experiments were conducted in mesocosms simulating the real situation of invasions in the same communities on the same types of soils with the same amount and composition of litter. The authors found that the native species was significantly inferior to A. caliginosa in reproduction rate, number of offspring, and final biomass, but had an advantage over L. rubellus. The native species was positively influenced by the presence of A. caliginosa. In the experiment, there was a significant rejuvenation of the populations of the studied species, an increase in abundance and relative mass under interaction conditions compared to mono variants. The native species had advantages over the invasive species in terms of winter survival. The natural volume of litter used in the experiment was insufficient for L. rubellus. According to the results of the experiment, it can be assumed that the spread of L. rubellus will continue to be limited to non-freezing biotopes rich in organic matter. A. caliginosa will spread in natural communities and agrocenoses of Western Siberia.

Predominantly rural areas make up half of Europe and account for about 20 per cent of the population. Yet most of them are among the least privileged regions in the European Union, with a GDP per capita significantly below the European average and with an average population age higher than in urban areas, although this gap will only slowly begin to narrow in the next decade. Together with a lack of connectivity, inadequate infrastructure, lack of diversified job opportunities and limited access to services, this makes rural areas a less attractive place to live and work. At the same time, however, rural areas actively participate in the EU's green and digital transition. Achieving the EU's digital goals for 2030 can offer more opportunities for the sustainable development of rural areas in areas other than agriculture, livestock and forestry, opening up new perspectives for the growth of manufacturing and, even more, service industries, and contributing to a better geographical distribution of services and industries. In this context, the objective of this work is the construction of a synthetic index of the welfare of European nations, through the Wroclaw taxonomic method and through the use of logit models, for the identification of best practices of local realities and the interpretation in a more im-mediated way of the fair and sustainable welfare of each European nation at a rural level

A series of cysteine-based perfluoroaromatic (hexafluorobenzene (I) and decafluorobiphenyl (II) were synthesized and established as a chemoselective and available core to simple or more complex systems since small molecules to biomolecules with interesting properties. As proof of concept of the potential application of perfluorinated derivatives as non-cleavable linkers, some antibody-perfluorinated conjugates were prepared via thiol, demonstrating that the bioconjugation process doesn’t affect to the macromolecular entity. Besides, some molecular properties of synthesized compounds are evaluated using a combination of spectroscopic characterization (FT-IR and 19F-NMR chemical shifts) and theoretical calculations. Moreover, molecular Docking was also developed to predict cysteine-based hexafluorobenzene and decafluorobiphenyl derivatives’ affinity against topoisomerase Il and cyclooxygenase 2 (COX-2). The results suggested that mainly cysteine-based decafluorobiphenyl derivatives could be potential topoisomerase II α and COX-2 inhibitors, becoming potential anticancer agents and candidates for anti-inflammatory treatment.

Specialized classes of proteins, working together in a tightly orchestrated manner, induce and maintain highly curved cellular and organelles membrane morphology. Due to the various ex- perimental constraints, including the resolution limits of imaging techniques, it is non-trivial to accurately elucidate interactions among the various components involved in membrane deformation. The spatial and temporal scales of the systems also make it formidable to investigate them using simulations with molecular details. Interestingly, mechanics-based mesoscopic models have been used with great success in recapitulating the membrane defor- mations observed in experiments. In this review, we collate together and discuss the various mechanics based mesoscopic models for protein-mediated membrane deformation studies. In particular, we provide an elaborate description of a mesoscopic model where the membrane is modeled as a triangulated sheet and proteins are represented as either nematics or fila- ments. This representation allows us to explore the various aspects of protein-protein and protein-membrane interactions as well as examine the underlying mechanistic pathways for emergent behavior such as curvature-mediated protein localization and membrane deforma- tion. We also put forward current efforts in the field towards back-mapping these mesoscopic models to finer-grained particle based models - a framework that could be used to explore how molecular interactions propagate to physical scales and vice-versa. We end the review with an integrative-modeling based road map where experimental imaging micrograph and biochemical data are combined with mesoscopic and molecular simulations methods in a theoretically consistent manner to faithfully recapitulate the multiple length and time scales in the membrane remodeling processes.

Maritime transport has become very important due to its ability to internationally unite all continents. In turn, during the last two years, we have observed that the increase of consumer goods has resulted in global shipping deadlocks. In addition, the future goes through the role of ports and efficiency in maritime transport, with the aim of decarbonizing its impact on the environment. In order to improve the economy and people's lives, in this work, we propose to enhance services offered in maritime logistics. To do this, a communications system is designed on the deck of ships to transmit data through a constellation of satellites using interconnected smart devices based on IoT. Among the services, we highlight the monitoring and tracking of refrigerated containers, the transmission of geolocation data from GPS, and security through AIS. This information will be used for a fleet of ships to make better decisions and help guarantee the status of the cargo, as well as maritime safety on the routes. The system design, network dimensioning, and a communications protocol for decision-making will be presented.

Although the fusion energy sector is at a nascent stage, the private fusion energy market has grown. There are currently 38 private fusion energy companies around the world aiming to commercialise fusion energy in early 2030s and 2040s. Given the capability of fusion energy in transforming today’s energy paradigm and the global character of the market, it is important to analyse how these companies are interacting with international human rights standards. Therefore, this work investigates the involvement of the private fusion energy sector with two voluntary international initiatives in particular: the UN Global Compact and the UN Guiding Principles on Business and Human Rights (UNGP). This study attempts to answer two research questions: (i) Are private fusion energy companies participating in the UN Global Compact? (ii) How are private fusion energy companies publicly implementing the UNGP? Content analysis of secondary data collected from the UN Global Compact, Fusion Industry Association, ITER and companies’ official website as well as published reports is adopted. In summary, this work finds that private fusion energy companies are neither participants nor signatories of the UN Global Compact. Their observance of the UNGP is also very poor. This study contributes to the field by highlighting this gap which the private fusion energy companies need to consider and take measures in order to create a salutary human rights sector.

Primary and middle school teachers are a critical part of China’s foundational education; teacher turnover heavily affects the stable development of foundational education. In this study, interviews with 20 teachers found that relatively low income, high work pressure, unfair distribution, and difficulty in achieving promotion to higher professional titles are the main reasons for teacher turnover intention. This study investigates 485 primary and middle school teachers from Zhejiang and Jiangsu provinces. We found that primary and middle school teachers reported intense feelings of unfairness about their distribution of income. Their salary satisfaction was low, and the ratio of turnover intention was high. The main reasons for teachers’ high turnover intentions were low income, high pressure from work, unfair distribution, and the difficulty of achieving professional title promotion. To lower teachers’ turnover intentions, China should raise teachers’ income appropriately and increase the number of teachers with high professional titles. Schools should improve procedural, distributive, and interactive justice. Teachers should adjust their income references and perceptions of fairness. This situation can be effectively resolved only if all parties work hard to make positive changes.

The Metabolic Food Waste [MFW (kg of food)], first time developed in 2016 as a new indicator by Serafini and Toti, indicates the amount of food consumed over the nutritional requirements and the impact of this overconsumption on the environment. It is necessary to identify the causes and to develop potential methods to prevent and reduce MFW, at the same time with increasing consumer awareness about unsustainable diets and changing diet habits toward more environmentally conscious consumption patterns. By analysing and corroborating external data available for food waste, nutritional requirements, environmental impact of food waste and consumer behaviour, we identified as primary causes for MFW the lack of nutritional education and little understanding of the nutritional requirements amongst all categories of consumers, no access to appropriate food resources or reduced availability of fresh produced food. We conclude that for the quantification of the negative impact of MFW on both the environment and human health, we need a decisive action to raise consumer awareness for healthy and sustainable diets, together with an uniform worldwide distribution of the nutritious food.

Ayurveda as a healthcare system has survived for thousands of years but continues to be dogged by reported lack of efficacy of the treatments in clinical trials. The reported lack of efficacy could be due to a real lack of efficacy (which then contradicts the survival of Ayurveda as a functional medical system enjoying considerable public patronage) or could be attributed to inadequacies in the efforts towards evidence generation or in a larger context the overall scientific conduct of research in Ayurveda. In an effort towards better evidence generation, there is an immediate need for standardizing the design, conduct and reporting of clinical trials of Ayurveda but it is a daunting task. For this effort to benefit the scientific endeavors of Ayurveda researchers, it should allow the researchers to be able to apply Ayurveda’s multi-component, individualized and inherently holistic approach. Statistical principles can benefit this effort. Statistical hypothesis testing (SHT) is central to these statistical principles and also aligns well with conventional scientific principles of evidence generation. Although there are challenges with SHT, good practitioners engaged in it do much more than just apply the mathematical theory behind it. As a particular example, lot of time in clinical trial designing is spent in addressing biases and designing trials prudently by minimizing the effect of such biases. SHT can benefit such an effort objectively. There is a need for Ayurveda researchers to engage deeply and mindfully about biases in study design in order to gain scientific validity and acceptability. The article highlights issues that arise in Ayurveda research, and discusses few ways of dealing with these issues using statistical principles.

Inverse problems of recovering surface fluxes on the boundary of a domain from pointwise observations are considered. Sharp conditions on the data ensuring existence and uniqueness of solutions in Sobolev classes are exposed. They are smoothness conditions on the data, geometric conditions on the location of measurement points, and the boundary of a domain. The proof relies on asymptotics of fundamental solutions to the corresponding elliptic problems and the Laplace transform. The problem is reduced to a linear algebraic system with a nondegerate matrix.

We derive the thermal noise spectrum of the Fourier transform of the electric field operator of a given wave vector starting from the quantum-statistical definitions and relate it to the complex frequency and wave vector dependent complex conductivity in a homogeneous, isotropic system of electromagnetic interacting electrons. We analyze separately the longitudinal and transverse case with their peculiarities. The Nyquist formula for vanishing frequency and wave vector, as well as its modification for non-vanishing frequencies and wave vectors follow immediately. Furthermore we discuss also the noise of the photon occupation numbers. It is important to stress that no additional assumptions at all were used in this straightforward proof.

The global spread of COVID-19 led the World Health Organization to declare a pandemic on 11 March 2020. To decelerate this spread, countries have taken strict measures that affected the lifestyle and economy. Various studies have been focused on the identification of COVID-19 impact to mental health of children and adolescents via traditional statistical approaches. However, a machine learning methodology must be developed to explain the main factors that contribute to the change of mood state of children and adolescents during the first lockdown. Therefore, to this study an explainable machine learning pipeline is presented focusing on children and adolescents in Greece, where a strict lockdown was imposed. The target group consists of children and adolescents, recruited from children and adolescent mental health services, who present mental health problems diagnosed before the pandemic. The proposed methodology imposes: (i) data collection via questionnaires; (ii) a clustering process to identify the groups of subjects with amelioration, deterioration and stability to their mood state; (iii) a feature selection process to identify the most informative features that contribute to mood state prediction; (iv) a decision-making process based on an experimental evaluation among classifiers; (v) calibration of the best performing model and (v) a post-hoc interpretation of the features’ impact on the best performing model. The results showed that a blend of heterogeneous features from almost all feature categories is necessary to increase our understanding regarding the effect of COVID-19 pandemic on the mood state of children and adolescents.

In view of the problem of cracking easily and partial distortion of images after encryption or decryption, a novel image encryption and decryption algorithm based on Arnod Transform and fractional chaotic is proposed. To begin with, the Arnold transform is used to encrypt. So that the spatial confidence of the original image has been comprehensively disturbed. Secondly, the XOR involving the fractional order chaotic sequence is used to encrypt. The key sequence is dynamically generated to ensure the randomness and difference of key generation. When decryption is required, the first decryption is performed using the key and XOR. Then the second decryption is carried out by using the inverse Arnold transform, and finally the decrypted image is obtained. Experimental results show that the improved algorithm has achieved better performance in encryption and decryption.

In a previous paper, the authors dealt with the current showstoppers for morphing systems and with the reasons that have inhibited their commercial applicability. In this work, the authors ex-press a critical vision of the current status of the proposed architectures and the needs that should be accomplished to make them viable for installation onboard of commercial aircraft. The distinc-tion is essential because military and civil issues and necessities are very different, and both the solutions and difficulties to be overcome are widely diverse. Yet, still remaining in the civil seg-ment, there can be other differences, depending on the size of the aircraft, from large jets to com-muters or general aviation, in turn classifiable in tourism, acrobatic, ultralight and so on, each with their own peculiarities. Therefore, the paper wants to try to trace a common technology de-nominator, if possible, and envisage a future perspective of actual applications.

Sub-Saharan social-ecological systems are undergoing changes in environmental conditions, including modifications in rainfall pattern and biodiversity loss. Consequences of such changes depend on complex causal chains which call for integrated management strategies whose efficiency could benefit from ecosystem dynamic modelling. However, ecosystem models often require lots of quantitative information for estimating parameters, which is often unavailable. Alternatively, qualitative modelling frameworks have proved useful for explaining ecosystem response to perturbations, while requiring fewer information and providing more general predictions. However, current qualitative methods have some shortcomings which may limit their utility for specific issues. In this paper, we propose the Ecological Discrete-Event Network (EDEN), an innovative qualitative dynamic modelling framework based on "if-then" rules which generates many alternative event sequences (trajectories). Based on expert knowledge, observations and literature, we use this framework to assess the effect of permanent changes in surface water and herbivores diversity on vegetation and socio-economic transitions in an East African savanna. Results show that water availability drives changes in vegetation and socio-economic transitions, while herbivore functional groups had highly contrasted effects depending on the group. This first use of EDEN in a savanna context is promising for bridging expert knowledge and ecosystem modelling.

The fifth Generation (5G) mobile networks use millimeter Waves (mmWaves) to offer giga bit data rates. However, unlike microwaves, mmWave links are prone to user and topographic dynamics. They easily get blocked and end up forming irregular cell patterns for 5G. This in turn cause too early, too late, or wrong handoffs (HOs). To mitigate HO challenges, sustain connectivity and avert unnecessary HO, we propose a HO scheme based on Jump Markov Linear System (JMLS) and Deep Reinforcement Learning (DRL). JMLS is widely known to account for abrupt changes in system dynamics. DRL likewise emerges as an artificial intelligence technique for learning highly dimensional and time-varying behaviors. We combine the two techniques to account for time-varying, abrupt, and irregular changes in mmWave link behaviour by predicting likely deterioration patterns of target links. The prediction is optimized by meta training techniques that also reduces training sample size. Thus, the JMLS-DRL platform formulates intelligent and versatile HO policies for 5G. Results show our proposed prediction scheme about target link behavior post HO to be highly reliable. The scheme also averts unnecessary HOs thus ably supports longer dew time.

Poplar is a globalized commercial tree species that supports humanity's economy, energy, and ecology. To evaluate the twelve hybrid Populus euramericana genotypes developed in China, a total of six locations were selected for the test, comprising four climatic types and three soil kinds. The objective of this study is to characterize the early stages of Populus euramericana growth and test locations; to identify good genotypes for stable and high yield that may be encouraged; and to offer practical experience and technical assistance for further breeding of Populus euramericana. Main research methods include the statistical description of tree heights and diameter at breast heights[DBH], the establishment of a mixed effect model to analyze the genotype and environmental interaction effect [G×E], the use of best linear unbiased prediction[BLUP] values as GGE biplots to achieve visual screening, and the calculation of genetic parameters. Results show that the genotype effect [G], the environmental effect [E], and the G×E is significant; the BLUP value has a strong correspondence with the observed value; the goodness of fit of all biplots can explain more than 85% of the variation; broad-sense heritability of tree height and DBH is 0.13 and 0.3, type-B correlation is 0.36 and 0.65; G5, G7, G4 and G9 are excellent genotypes with high yield and stability; using these four genotypes tree height and DBH can get 3.35% and 0.81% genetic gains.The study concludes as follows: Rank-change interaction and scale-effect interaction were distinctly occurred. The G, E, and G×E all had a significant effect on the growth of poplar trees during their early stage. G4, G5, G7, and G9 genotypes have favorable development characteristics. N146 is a great source of paternal genetics.

The nonlocal boundary value problem, dtρu(t)+Au(t)=f(t) (0&lt;ρ&lt;1, 0&lt;t≤T), u(ξ)=αu(0)+φ (α is a constant and 0&lt;ξ≤T), in an arbitrary separable Hilbert space H with the strongly positive selfadjoint operator A, is considered. The operator dt on the left hand side of the equation expresses either the Caputo derivative or the Riemann-Liouville derivative; naturally, in the case of the Riemann - Liouville derivatives, the nonlocal boundary condition should be slightly changed. Existence and uniqueness theorems for solutions of the problems under consideration are proved. The influence of the constant α on the existence of a solution to problems is investigated. Inequalities of coercivity type are obtained and it is shown that these inequalities differ depending on the considered type of fractional derivatives. The inverse problems of determining the right-hand side of the equation and the function φ in the boundary conditions are investigated.

Fiber laser technology has been demonstrated as a versatile and reliable approach for laser source manufacturing with a wide range of applicability in various fields ranging from science to industry. The power/energy scaling of single fiber laser systems has faced several fundamental limitations. To overcome them and to boost the power/energy level even further, combining the output powers of multiple lasers has become the primary approach. Among various combining techniques, the coherent beam combining of fiber amplification channels is the most promising approach, instrumenting ultra-high power/energy lasers with near-diffraction-limited beam quality. This paper provides a comprehensive review of the progress of coherent beam combining for both continuous-wave and ultrafast fiber lasers. The concept of coherent beam combining from basic notions to specific details of methods, requirements, and challenges are discussed, along with reporting some practical architectures for both continuous and ultrafast fiber lasers.

We create a model universe by equipping a topological surface (system) with compact dimensions insulated by an information blocking horizon. The insulated compact WF can produce entanglement independent of distance. Interaction between the system and the WF changes the curvature of the first and the quantum state (frequency) of the second in an interconnected relationship. Thus, the field curvature measures the evolution of the particle WF as time. Positive field curvature creates pressure, whereas negative field curvature generates a vacuum, satisfying the Borsuk-Ulam Theorem and the Page and Wootters mechanism of static time. The accumulation of pressure or vacuum generates poles with contrasting dimensionalities, two-dimensional black hole horizons (time infinite), and four-dimensional cosmic voids (time zero). The orthogonality of the field and the compact WF give rise to global self-regulation that fine-tunes the cosmic parameters and can promote fractal topology. The four-dimensional vacuum in cosmic voids can produce an accelerating expansion without dark energy. When gravity effects are eliminated, we find a new, so far unexplored, order-increasing side of entropy. The verifiable and elegant hypothesis satisfies Mach's principle.