Properties of time domain parameters of the vibration signal have been extensively studied for the fault diagnosis of rolling element bearings (REB). Parameters like kurtosis and Envelope Harmonic-to-Noise Ratio are most widely applied in this field and some important progress has been made. However, since only one-sided information is contained in these parameters respectively, problems still exist in practice when the signals collected are of complicated structure and/or contaminated by strong background noises. A new parameter, named Shock pulse index (SPI), is proposed in this paper. It integrates the mutual advantage of both parameters above and can help effectively identify fault related impulse components under the interference of strong background noises, unrelated harmonic components and random impulses. The SPI optimizes the parameters of Maximum Correlated Kurtosis Deconvolution (MCKD), which is used to filter the signals under consideration. Finally, the interested transient information contained in the filtered signal can be highlighted through demodulation with Teager Energy Operator (TEO). Fault related impulse components can therefore be extracted accurately. Simulations and experiment analyses verify the effectiveness and correctness of the SPI.

In this study, 10%PTFE/PEEK blend were modified by potassium titanate whisker (PTW) and chopped glass fiber (GF), respectively. The blends were prepared by three-screw extruder. Through the investigation of thermal stability, tribological properties, mechanical properties and rheological behavior, the effects of reinforcing agents were determined. The results illustrated that the mechanical properties of 10%PTFE/PEEK blend can be dramatically improved by adding reinforcing agent of PTW or GF, and the reinforcing effect of GF was especially obvious. As for tribological properties, 1% addition was the best proportion. The friction coefficient and wear rate of the blend with 1% PTW were 0.283 and 4.97 × 10^-6 mm³/N · m, which decreased by 7.2% and 21% compared with those of the blend without reinforcing agent.

Addressing the pressing challenge of global warming, reducing greenhouse gas emissions in the transportation sector is a critical imperative. Battery and fuel-cell electric vehicles have emerged as promising solutions for curbing emissions in this sector. In this study, we conducted a comprehensive life cycle assessment (LCA) for typical passenger vehicles, heavy duty trucks and city buses using either proton-exchange membrane fuel cells or Li-ion batteries with different cell chemistries. To ensure accuracy, we supplemented existing studies with data from the literature, particularly for the recycling phase, as database limitations were encountered. Our results highlight that fuel cell and battery systems exhibit large emissions in the production phase. Recycling can significantly offset some of these emissions, but a comparison of the technologies examined revealed considerable differences. Overall, battery electric vehicles consistently outperform fuel cell electric vehicles regarding absolute greenhouse gas emissions. Hence, we recommend prioritizing battery electric over fuel cell vehicles. However, deploying fuel cell electric vehicles could become attractive in a hydrogen economy scenario where other factors, e. g. the conversion and storage of surplus renewable electricity via electrolysis, become important.

A novel determination method using flow-through cartridge purification and ultra-high-performance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS) was developed for the identification and quantification of 30 mycotoxins (aflatoxin B1, B2, G1, G2, sterigmatocysin, T-2 toxin, diacetoxyscirpenol, roquefortine C, methylergonovine, ergocornine, lysergol, enniatin A, enniatin A1, enniatin B, enniatin B1, beauvericin, deoxynivalenol, 3-acetylDeoxynivalenol, 15-acetylDeoxynivalenol, patulin, verruculogen, neosolaniol, gliotoxin, HT-2 toxin, wortmannin, zearalenone, α-zearalenol, β-zearalenol, α-zearalanol, and β-zearalanol) in feedstuffs. Mycotoxins were extracted from sample by 0.1% formic acid aqueous solution/acetonitrile (16/84 v/v), then purified by a Cleanert® MC clean-up column. As a result, the pigments and other matrices were efficient removed from the sample extract solution. The purified eluate was collected, then evaporated and redissolved by 0.1% formic acid aqueous solution/acetonitrile (70:30 v/v) for UPLC-MS/MS detection. A BEH Shield RP18 chromatographic column was employed for separation of 30 mycotoxins in a total of 14 min. Multiple-reaction monitoring (MRM) mode was applied for qualitative and quantitative analysis, and matrix calibration curves obtained with the external-standard method was used for quantitation of target analytes. Under optimized conditions, the linearity range was from 2 to 1000 ng/g, and the limit of quantification of the developed method was from 2 to 50 ng/g. The recoveries of 30 mycotoxins spiked in urine samples were from 72.0% to 118.5%, and the relative standard deviation was below 20%. The method was also well approved by certified reference sample, and applied on the real feedstuff samples testing successfully.

The conformity assessment of products or a measured value with the given standards is carried out based on the global risk of producers and consumers calculation. A product may conform to specifications but be falsely rejected as non-conforming. This is about the producer's risk. If a product doesn't meet the requirements but is falsely accepted as conforming, that poses a risk to the consumer. The conventional approach to risk assessment, which yields only a single numerical value for the global risk of producers and consumers, is naturally extended, and utilized for assessing risk in measurement models with linear regression. The outcomes of the two-dimensional extension, along a moderate scale, are the parabolas with an opening upwards. Risk surfaces were obtained through three-dimensional extension over the area limited by the moderate scale and guard band axes. Four models with different ranges of tolerance intervals were used to test this innovative method of risk assessment in linear regression. The corresponding standard measurement uncertainties are determined by applying a simplified measurement model with the use of comprehensive data on the measurement performance and by determining measurement uncertainty derived from consideration of the functional relationship obtained by linear regression analysis. Models that utilize information from linear regression analysis to determine measurement uncertainty are biased towards risks at the edges of the moderate scale. Testing the model's performances with metrics related to the confusion matrix, such as the F1 score, further substantiated this assertion. The diagnostic odds ratio has been proven to be extremely effective in identifying the curve along the guard band axis, along which the global risks of producers and consumers are at their lowest.

In this study, a basic study was performed to analyze the seasonal temperature status of a research room in the Global Environment Research Building where ceiling-embedded indoor units are installed to study the room temperature status of the building as well as to improve its thermal environment. In addition, a direction for improvement of the indoor thermal environment in the winter was proposed through a CFD (computational fluid dynamics) simulation and was proven by an additional experiment. Through the results of this study, it appeared that if the ceiling-embedded indoor unit was installed in the small indoor space without considering the thermal vulnerability of its perimeter boundary, the air temperature of the upper part was greatly different from that of the bottom part in the winter. Hence, in this study, as a means to improve it, convectors were installed to minimize the effect of the external thermal environment and angle-controllable air flowing fans were installed to mitigate the stratification distribution. With such result, it was intended to present the essential data for improvement of the thermal environment as well as conservation of heating energy in the winter for buildings by reviewing the use of the ceiling-embedded indoor unit in the future.

Tea (Camellia sinenesis) is a health beneficial beverage and is also a source for extracting bioactive components such as theanine, tea polyphenols (TPP) and tea polysaccharides (TPS). TPS is a group of hetero-polysaccharides bounded with proteins. There were tests showing that TPS had various bioactivities, such as antioxidant, antitumors, antihyperglycemia, anti-inflammation and improving immunity. However, inconsistent results concerning chemical composition and bioactivity of TPS were published in recent years. The advances in chemical composition and bioactivities of TPS were reviewed in the present paper. The inconsistent and controversial results regarding composition and bioactivities of TPS were also discussed.

The adulteration of goat milk powder occurs frequently, cattle-derived and soybean-derived ingredients are common adulterants in goat milk powder. However, simultaneously and rapidly detecting cattle-derived and soybean-derived components is still a challenge. high throughput and efficient screening method for adulteration detection is need. In this study, a rapid method was developed to detect the adulteration of common cattle-derived and soybean-derived components simultaneously in goat milk powder by combining the CRISPR/ Cas12a system with recombinant polymerase amplification (RPA). A dual DNA extraction method was employed, primers and crRNA for dual detection were designed and screened, and a series of condition optimizations were carried out in this experiment. The optimized assay can rapidly detect cattle-derived and soybean-derived components in 40 min. The detection limits of both cattle-derived and soybean-derived components were 1% (w/w) for the mixed adulteration models. The established method was applied into a blind survey of 55 commercially available goat milk powder products. The results showed that 36.36% of the samples contained cattle-derived or soybean-derived ingredients, which revealed the noticeable adulteration situation in the goat milk powder market. This study realizes a fast flow of dual extraction, dual amplification and dual detection of cattle-derived and soybean-derived components in goat milk powder for the first time. It can be used for high-throughput and high-efficiency on-site primary screening of goat milk powder adulterants, and provide a technical reference for combating with food adulteration.

Until recently, no disease-specific health-related quality of life (HRQoL) instrument existed for pediatric traumatic brain injury (TBI). In this revalidation study, the psychometric properties and the validity of the final German version of the 35-item QOLIBRI-KID/ADO questionnaire were examined in 300 children and adolescents. It is the first self-reported TBI-specific instrument for measuring pediatric HRQoL in individuals aged 8–17 years. The six-factor model fits the data adequately. Internal consistencies were excellent for the total score and satisfactory to excellent for the scale scores. Intraclass correlations indicated good test-retest reliability. Construct validity was supported by overlaps between the QOLBRI-KID/ADO and the PedsQL, which measures generic HRQoL. Discriminant validity indicated that HRQoL was significantly lower in older children and girls, and in those with anxiety, depression, and post-concussion symptoms than in comparison groups, replicating the results of the questionnaire’s first development study. Our results suggest that the QOLIBRI-KID/ADO is a valid and reliable multidimensional instrument for assessing disease-specific HRQoL after pediatric TBI in clinical and research settings, which can additionally be used across the lifespan in combination with the adult version. This may help to improve care, treatment, daily functioning and HRQoL after TBI.

Two new dimacrolide sesquiterpene pyridine alkaloids (DMSPAs), dimacroregelines A (1) and B (2), were isolated from the stems of Tripterygium regelii. The structures of both compounds were characterized by extensive 1D and 2D NMR spectroscopic analyses, as well as HRESIMS data. Compounds 1 and 2 are two rare DMSPAs possessing unique 2-(3′-carboxybutyl)-3-furanoic acid units forming the second macrocyclic ring, representing the first example of DMSPAs bearing an extra furan ring in their second macrocyclic ring system. Compound 2 showed inhibitory effects on the proliferation of human rheumatoid arthritis synovial fibroblast cell (MH7A) at a concentration of 20 μM.

Vertical Indoor Farming (VIF) with hydroponics offers a promising perspective for sustainable food production. Intelligent control of VIF system components plays a key role in reducing operating costs and increasing crop yields. Modern machine vision (MV) systems use Deep Learning (DL) in combination with camera systems for various tasks in agriculture, such as disease and nutrient deficiency detection, and flower and fruit identification and classification for pollination and harvesting. This study presents the applicability of MV technology with DL modelling to detect the growth stages of chilli plants using YOLOv8 networks. The influence of different bird’s eye and side view datasets and different YOLOv8 architectures was analysed. To generate the image data for training and testing the YOLO models, chilli plants were grown in a hydroponic environment and imaged throughout their life cycle using four camera systems. The growth stages were divided into growing, flowering and fruiting classes. All trained YOLOv8 models showed reliable identification of growth stages with high accuracy. The results indicate that models trained with data from both views show better generalisation. YOLO’s middle architecture achieved the best performance.

Background/Objectives: PEMF therapy has gained significant attention due to its potential benefits in promoting tissue repair and improving overall well-being. Recent publications in the field of exercise physiology, showed that pulsed electromagnetic fields (PEMFs) enhanced the velocity and the quantity of muscle O2 available and the rate of muscle oxygen extraction and utilization, in semi-professional cyclists, during a heavy constant-load exercise. In this paper, we investigate the effect of stimulation on muscular activation, in sedentary young people, during a constant-load exercise, performed at moderate intensity. Methods: Nine male sedentary young people, partic-ipated in this study. The response of the muscle activity, was recorded by surface EMG and assessed measuring the root mean square (RMS) normalized to the peak of the maximum voluntary con-traction. Data were collected in the right vastus Medialis (RVM) and right Biceps Femoris (RBF) at the baseline (standstill sitting), on warm-up (unloaded cycling) and during 30 minutes of con-stant-load exercise, in two experimental conditions (PEMF ON vs PEMF OFF). Results: The mul-tivariate analysis of variance performed on RVM showed a significant effect of PEMF in both warmup and exercise, while on RBF showed a significant effect of PEMF and warmup. Conclusions: PEMF strongly enhanced the amplitude of muscle activity in young sedentary people. The increase in the amplitude of the muscular response may lead to a higher oxygen consumption and release.

Bacteriophages (phages) are potential alternatives to chemical antimicrobials against pathogens of public health significance. Understanding the diversity and host specificity of phages is important for developing effective phage biocontrol approaches. Here, we assessed the host range, morphology, and genetic diversity of eight Salmonella enterica phages isolated from a wastewater treatment plant. The host range analysis revealed that six out of eight phages lysed more than 81% of the 43 Salmonella enterica isolates tested. The genomic sequences of all phages were determined. Whole genome sequencing data (WGS) data revealed that phage genome sizes ranged from 41 to 114 kb with GC contents be-tween 39.9 and 50.0 %. Two of the phages SB13 and SB28 represent new species Epsep-timavirus SB13 and genera Macdonaldcampvirus, respectively as designated by the In-ternational Committee for the Taxonomy of Viruses (ICTV) as per genome based taxonomic classification. One phage (SB18) belonged to the Myoviridae morphotype while the re-maining phages belonged to the Siphoviridae morphotype. The gene content analyses showed that none of the phages possessed virulence, toxin, antibiotic resistance, type I-VI toxin-antitoxin modules or lysogeny genes. Three (SB3, SB15 and SB18) out of the eight phages possessed tailspike proteins. Whole genome-based phylogeny of the eight phages with their 113 homologs revealed three clusters A, B, C and seven subclusters (A1, A2, A3, B1, B2, C1 and C2). While cluster C1 phages were predominantly isolated from animal sources, cluster B contained phages from both wastewater and animal sources. The broad host range of these phages highlights their potential use to control the presence of S. enterica in foods.

Surface acoustic wave (SAW) is effective for the manipulation of fluids and particles in microscale. The current approach of integrating interdigitated transducers (IDTs) for SAW generation into microfluidic channels involves complex and laborious microfabrication steps. These steps often require the full access to clean room facilities and hours to align the transducers to the precise location. This work presents an affordable and innovative method for fabricating SAW-based microfluidic devices without the need of clean room facilities and alignment. The IDTs and microfluidic channels are fabricated in the same process and thus precisely self-aligned in accordance with the device design. With the use of the developed fabrication approach, a few types of different SAW-based microfluidic devices have been fabricated and demonstrated for particle separation and active droplet generation.

(1) Background: Grapes and their associated by-products (as grape pomace, GP) stand out for their polyphenol content, which makes them a source of bioactive compounds with antioxidant capacity. The aim of this research was to determine if the inclusion of 50 g/kg of GP in the diet of hens could enrich egg with antioxidants and to study its effect on internal and external egg quality parameters. (2) Methods: A trial was conducted with two genetic lines of hens, which were fed either a control diet or a diet containing 50 g/kg of GP. Performance, internal and external egg quality, and egg yolk content of vitamins E and A, and gallic acid were determined; (3) Results: In eggs laid by hens fed GP diet, Haugh units and yolk colour score were enhanced, and eggshell became thinner, but without affecting the breaking strength. No dietary effect was observed on vitamin contents in yolk. Higher gallic acid content was observed in yolk of eggs laid by hens fed the GP diet, suggesting that some dietary phenolic compounds could be transferred to the eggs. Hen genetics influenced egg weight, albumen Haugh units, shell thickness and α- and γ-tocopherol concentration in yolks; (4) Conclusions: Dietary inclusion of GP improved the internal quality of eggs, enriching yolks with a phenolic compound, but reduced shell thickness.

Computer systems are involved in many critical human applications today, so that a small error can lead to serious and dangerous problems. These errors can be from an error in the incorrect design of the user interface to an error in the program code. The success of a software product depends on several factors. Given that different organizations and institutions use software products, the need to have a quality and desirable Software according to the goals and needs of the organization makes measuring the quality of software products. an important issue for most organizations and institutions, To be sure of having the right software. It is necessary to use a standard quality model to examine the features and sub-features for a detailed and principled study in the quality discussion. In this study, the quality of Word software was measured by Adaptive Neural Fuzzy Inference System. In recent years, powerful systems called fuzzy inference systems on The basis of adaptive neural network (ANFIS) has been used in various sciences. Using the power of neural network training and the linguistic advantage of fuzzy systems, these types of systems have been able to realize the advantages of the two in terms of analyzing very powerful complex processes. Considering the importance of software quality and to have a good and usable software in terms of quality and measuring the quality of software during the study. It was applied at different levels to make the result of measuring the quality of Word software more accurate and closer to reality. In this research, the quality of the software product is measured based on the adaptive neural-fuzzy inference system in ISO standard. According to the results obtained in this study, it is understood that quality is a continuous and hierarchical concept and the quality of each part of the software at any stage of production can lead to high quality products.

This paper proposes a product design model for internalising users’ positive experiences through attachment. First, the research commences with a literature review to define the concepts and research status of positive experience design (PED) and product attachment. Subsequently, the design model is constructed, accompanied by relevant formulas for concept generation. Finally, the model’s validity is verified through a workshop, and its effectiveness is evaluated and discussed using the USE questionnaire. This study incorporates the seven factors of product attachment to activate positive states within the user–product relationship and facilitate the cultivation of positive thinking. Grounded in theories of PED and embracing a product attachment perspective, the attachment-driven PED model offers a systematic approach for generating design concepts that are relevant to user experience.

In the present study, the new biological sources in the form of lichen Usnea orientalis Motyka was screened for its antidermatophytic potential. Six species of dermatophytes were chosen on the basis of their prevalence for antidermatophytic assays, and the Clinical Laboratory Standard Institute (CLSI)-recommended broth microdilution procedure was used to detect the efficacy of extract against dermatophytes. Thin layer chromatography of lichen extracts reveals the presence of two secondary metabolites viz. salazinic acid and usnic acid. U. orientalis extract exhibited promising antidermatophytic activity against all tested pathogens. Amongst all tested pathogens, E. floccosum exhibited most susceptibility towards extract, whereas T. mentagrophytes exhibited the least susceptibility. Topical application of U. orientalis extract might be helpful in the cure of dermal infections.

For many years, the programmable positioners have been widely applied in structures of modern electro-pneumatic final control elements. The positioner consists of an electro-pneumatic transducer, embedded controller and measuring instrumentation. Electro-pneumatic transducers that are used in positioners are characterized by a relatively short mean time-to-failure. The practical and economical method of a reasonable prolongation of this time is proposed in this paper. It is principally based on assessment and minimizing the effort of the embedded controller. For this purpose, were introduced: the control value variability, mean-time and the cumulative controller's effort. The diminishing of controller effort has significant practical repercussions, because it reduces the intensity of mechanical wear of the final control element components. On the other hand, the reduction of the cumulative effort is important in the context of process economy due to limitation of the consumption of energy of compressed air supplying the final control element. Therefore, the minimization of introduced effort factors has an impact on increasing the functional safety and economics of the controlled process. As a result of the performed simulations, the recommendations regarding the selection of the structure and tuning of positioner controller were elaborated. The simulations were performed in the Matlab-Simulink environment with the use of the liquid level control system in which a phenomenological model of a final control element was deployed. It has been proven that under appropriate conditions, it is possible to extend significantly the lifetime of the final control element and simultaneously enhance the control quality factors.

This bibliographic study addresses key aspects related to fishing, product safety, and climate change in the Adriatic Sea region. The examination of product safety focuses on the assessment of contaminants originating from human activities such as industry, mining, agriculture, and household waste disposal. The contamination of the aquatic environment has emerged as a pressing global concern, extending to the Adriatic subbasin. Aquatic organisms, including fish, are prone to accumulating pollutants directly from polluted water sources and indirectly through the food web. The bio-accumulation of potentially hazardous substances, particularly heavy metals, pesticides, PCBs, PAHs, and antibiotic resistance in aquatic organisms, poses a significant threat to human health. Climate change effects will deplete our seafood supply in terms of quantity and safety owing to negative consequences such as higher levels of pollution, parasites, viruses, infections, acidification, and toxicities such as shellfish poisoning. Global food safety strategies should be developed to reduce greenhouse gas emissions and promote environmentally friendly technology, which indirectly affects seafood quality and microbiological safety, especially for Adriatic Sea, which is part of the Mediterranean Sea, characterized by the most polluted waters in the world.

Recent technological advancements such as IoT and Big Data have granted industries extensive access to data, opening up new opportunities for integrating Artificial Intelligence (AI) across various applications to enhance production processes. We can cite two critical areas where AI can play a key role in industry such as product quality control and predictive maintenance. This paper presents a survey of AI applications in the domain of Industry 4.0, with a specific focus on product quality control and predictive maintenance. Experiments were conducted using two datasets, incorporating different machine learning and deep learning models from the literature. Furthermore, this paper provides an overview of the AI solution development approach for product quality control and predictive maintenance. This approach includes several key steps, such as data collection, data analysis, model development, model explanation, and model deployment.

One of the main technological and economic challenges for an engineer is designing high-quality products in manufacturing processes. Most of these processes involve a large number of variables included the setting of controllable (design) and uncontrollable (noise) variables. Robust Design (RD) method uses a collection of mathematical and statistical tools to study a large number of variables in the process with a minimum value of computational cost. Robust design method tries to make high-quality products according to customers’ viewpoints with an acceptable profit margin. This paper aims to provide a brief up-to-date review of the latest development of RD method particularly applied in manufacturing systems. The basic concepts of the quality loss function, orthogonal array, and crossed array design are explained. According to robust design approach, two classifications are presented, first for different types of factors, and second for different types of data. This classification plays an important role in determining the number of necessity replications for experiments and choose the best method for analyzing data. In addition, the combination of RD method with some other optimization methods applied in designing and optimizing of processes are discussed.

This review provides a comprehensive and updated information on chalcones, presenting their sources, methods of identification and properties putting emphasis on applications in agricultural industry. Vast exploitation of synthetic pesticides led to the weed and pest resistance issue, causing economic loss but more importantly health risk due to pesticide overuse. Because one of the aim of the European Green Deal 2030 is the Farm to Fork strategy which targets on reducing by 50% the use of chemical pesticides by 2030, and push towards natural pesticides which are more environmentally friendly and restore natural resources, chalcones and their derivatives seem to fit perfectly. They have herbicidal, fungicidal, bactericidal and antiviral properties. Moreover, chalcones are naturally occurring substances, known for their favorable health effect for years, working on many areas. This review is complementary to the previous ones describing chalcones use in agriculture, updates them but additionally shows methods of detection.

Pardosa pseudoannulata is one of the most common wandering spiders in agricultural fields and a potentially good bioindicator for heavy metal contamination. However, little is known about the mechanism by which spiders respond to heavy metals at the molecular level. In this study, high-throughput transcriptome sequencing was employed to characterize the de novo transcriptome of the spiders and to identify differentially expressed genes (DEGs) after cadmium exposure. We obtained 60,489 assembled unigenes, 18,773 of which were annotated in the public databases. Ultimately, 3450 cDNA simple sequence repeats were identified and validated as potential molecular markers in the unigenes. A total of 2939, 2491 and 3759 DEGs were detected among the three libraries of two Cd-treated groups and the control. Functional enrichment analysis revealed that metabolism processes and digestive system function were predominately enriched in response to Cd stress. At the cellular and molecular levels, significantly enriched pathways in lysosomes and phagosomes as well as replication, recombination and repair demonstrated that oxidative damage resulted from Cd exposure. Based on the selected DEGs, certain critical genes involved in defence and detoxification were analysed. These results may elucidate the molecular mechanism underlying spiders' responses to heavy metal stress.

Background: Circulating rare cells participate in breast cancer evolution as systemic components of the disease and thus, are a source of theranostic information. Exploration of cancer-associated rare cells is in its infancy. We determined the validity of a rare-cell detection platform and demonstrated the usefulness of a certain rare cell subset as a novel approach to characterize the breast cancer system. Methods: Linearity of the Rarmax® platform was established using a spike-in approach. The platform includes red blood cell lysis, leukocyte depletion and high-resolution fluorescence image recording. Rare cell analysis was conducted on 28 samples (before and after surgery) from 14 patients with breast cancer, 20 healthy volunteers and 9 non-cancer control volunteers. In-depth identification of rare cells, including circulating tumor cells, endothelial-like cells, erythroblasts and inflammation-associated cells, was performed using a phenotype and morphology-based classification system. Results: The platform performed linearly over a range of 5-950 spiked cells, with an average recovery of 84.6%. Circulating epithelial and endothelial-like cell subsets have been demonstrated to be associated with or independent of cancer with tumor presence. Furthermore, certain cell patterns may be associated with treatment-related adverse effects. The sensitivity in detecting tumor-presence and cancer-associated abnormality before surgery was 50% and 85.7%, respectively and the specificity was 100% and 96.6%, respectively. Conclusion: The present study supports the idea of a cancer-associated rare cell abnormality to represent tumor entities as well as systemic cancer. The latter is independent of the apparent clinical cancer.

Grain quality, cooking quality and nutritional quality traits are some of the major attributes that enhance uptake and utilisation of improved cowpea varieties. Therefore, there is need for a better understanding of the genetic variation and inter-relationships among these quality traits in cowpea to integrate them in cowpea breeding programs. The study was conducted to determine genetic variability among 306 cowpea genotypes for grain quality, cooking quality and nutritional quality traits and to understand the interrelationships among these traits for exploitation in breeding programs. The results showed highly significant differences (P

The success of a software product depends on several factors. Given that different organizations and institutions use software products, the need to have a quality and desirable software according to the goals and needs of the organization makes measuring the quality of software products an important issue for most organizations and institutions. To be sure of having the right software. It is necessary to use a standard quality model to examine the features and sub-features for a detailed and principled study in the quality discussion. In this study, the quality of Word software was measured. Considering the importance of software quality and to have a good and usable software in terms of quality and measuring the quality of software during the study, experts and skilled in this field were used and the impact of each factor and quality characteristics. It was applied at different levels according to their opinion to make the result of measuring the quality of Word software more accurate and closer to reality. In this research, the quality of the software product is measured based on the fuzzy inference system in ISO standard. According to the results obtained in this study, it is understood that quality is a continuous and hierarchical concept and the quality of each part of the software at any stage of production can lead to high quality products.

The influence of short term water absorption on the mechanical properties of halloysite nanotubes-multi layer graphene reinforced polyester hybrid nanocomposites has been investigated. The addition of nano-fillers significantly increased the flexural strength; tensile strength and impact strength in dry and wet conditions. After short term water exposure; the maximum microhardness; tensile; flexural and impact toughness values were observed at 0.1 wt% MLG. The microhardness increased up to 50.3%; tensile strength increased up to 40% and flexural strength increased up to 44%. Compared to dry samples; the fracture toughness and surface roughness of all types of produced nanocomposites were increased that may be attributed to plasticization effect. Scanning electron microscopy revealed that the main failure mechanism is caused by the weakening of nano-filler-matrix interface induced by water absorption. It was further observed that synergistic effects were not effective at concentration of 0.1 wt% to produce considerable improvement in mechanical properties of produced hybrid nanocomposites.

Patients with metastatic epidural spinal cord compression (MESCC) and favorable survival prognoses may benefit from radiation doses exceeding 10 x 3.0 Gy. In a multi-center phase 2 trial, patients receiving 15 x 2.633 Gy (41.6 Gy10) or 18 x 2.333 Gy (43.2 Gy10) were evaluated for local progression-free survival (LPFS), motor/sensory functions, ambulatory status, pain, distress, toxicity, and overall survival (OS). They were compared (propensity score adjusted Cox regression) to a historical control group (N=266) receiving 10 x 3.0 Gy (32.5 Gy10). In the phase 2-cohort, 50 (of 62 planned) patients were evaluable for LPFS. Twelve-month rates of LPFS and OS were 96.8% and 69.9%, respectively. Motor and sensory functions improved in 56% and 57.1% of patients, and 94.0% were ambulatory following radiotherapy. Pain and distress decreased in 84.4% and 78.0% of patients. Ten and two patients experienced grade 2 and 3 toxicities, respectively. Phase 2 patients showed significantly better LPFS than the control group (p = 0.039) and a trend for improved motor function (p = 0.057). Ambulatory and OS rates were not significantly different. Radiotherapy with 15 x 2.633 Gy or 18 x 2.333 Gy was well tolerated and appeared superior to 10 x 3.0 Gy.

Refineries execute a series of interlinked processes, where the product of one unit serves as the input to another process. Potential failures within these processes affect the quality of the end products, operational efficiency, and revenue of the entire refinery. In this context, implementation of a real-time cognitive module, referring to predictive machine learning models, enables to provide equipment state monitoring services and to generate decision-making for equipment operations. In this paper, we propose two machine learning models: 1) to forecast the amount of pentane (C5) content in the final product mixture; 2) to identify if C5 content exceeds the specification thresholds for the final product quality. We validate our approach by using a use case from a real-world refinery. In addition, we develop a visualization to assess which features are considered most important during feature selection, and later by the machine learning models. Finally, we provide insights on the sensor values in the dataset, which help to identify the operational conditions for using such machine learning models.

This article investigates the information matching efficiency of the sponsored auction mechanism of search engine platform by implementing consumer purchase strategy. Then we examine the incentive mechanism for sellers to report product quality truthfully under information asymmetry and the reason how product quality signal could improve information matching efficiency of the sponsored auction mechanism. Using the data collected from Baidu search engine, we empirically test the theoretical research results. Our main research finding: under information asymmetry and without product quality signal mechanism, the equilibrium of bidding rank cannot match the consumer purchase strategy at all, causing the consumer welfare to suffer double losses due to the adverse selection of sellers. In the contrast, the search engine could improve partially the information matching efficiency of the sponsored search auction mechanism by identifying the product quality signal brought by the sellers with the highest product quality. However, the search engine has no incentive to design product quality signal for sellers.

In multi-objective optimization problems, the optimization target is to obtain a set of non-dominated solutions. Comparing solution sets is crucial in evaluating the performances of different optimization algorithms. The use of performance indicators is common in comparing those sets and, subsequently, optimization algorithms. A good solution set must be close to the Pareto-optimal front, well-distributed, maximally extended and fully filled. Therefore, an effective performance indicator must encompass these features as a whole and must be Pareto dominance compliant. Unfortunately, some of the known indicators often fail to properly reflect the quality of a solution set or cost a lot to compute. This paper demonstrates that the Degree of Approximation (DOA) quality indicator, is a weakly Pareto compliant unary indicator that gives a good estimation of the match between the approximated front and the Pareto-optimal front. Moreover, DOA computation is easy and fast.

We investigate and discuss in detail the structure of the restricted singular value decomposition for a tensor triplet under t-product (T-RSVD). The algorithm is provided with a numerical example illustrating the main result. For applications, we consider color image watermarking processing with T-RSVD.

As the most serious of the many worse new pathological changes caused by diabetes, there are many risk factors for the occurrence and development of DR. It mainly includes hyperglycemia, hypertension, hyperlipidemia and so on. Among them, hyperglycemia is the most critical cause, which plays a key role in the pathological changes of DR.High-sucrose diets(HSDs) lead to elevated blood glucose levels in vivo, which, through oxidative stress, inflammation, the production of AGEs and VEGF, causes plenty of pathological damages to the retina and ultimately bring about loss of vision. The existing therapies for DR primarily target the terminal stage of the disease, when irreversible visual impairment has appeared. Therefore, early prevention is particularly critical. Early prevention of DR-related vision loss requires adjustments to dietary habits, mainly by reducing sugar intake. This article primarily discusses the risk factors, pathophysiological processes, and molecular mechanisms associated with the development of DR caused by HSDs. It aims to raise awareness of the crucial role of diet in the occurrence and progression of DR, promote timely changes in dietary habits, prevent vision loss, and improve the quality of life. The aim is to make people aware of the importance of diet in the occurrence and progression of DR. According to the dietary modification strategies we give, patients can change their poor eating habits timely, avoid the retinopathy that can be avoided theoretically, and obtain a excellent outcome.

With our long experience in the field of unification of gravity and quantum mechanics, we understood that, when mass of any elementary is extremely small/negligible compared to macroscopic bodies, highly curved microscopic space-time can be addressed with large gravitational constants and magnitude of elementary gravitational constant seems to increase with decreasing mass and increasing interaction range. In our earlier publications, we proposed that, 1) There exist three atomic gravitational constants associated with electroweak, strong and electromagnetic interactions; 2) There exists a strong interaction elementary charge in such a way that, it's squared ratio with normal elementary charge is close to inverse of the strong coupling constant; and 3) Considering a fermion-boson mass ratio of 2.27, quarks can be split into quark fermions and quark bosons. Further, we noticed that, electroweak field seems to be operated by a primordial massive fermion of rest energy 584.725 GeV and hadron masses seem to be generated by a new hadronic fermion of rest energy 103.4 GeV. In this context, starting from lepton rest masses to stellar masses, we have developed many interesting and workable relations. With further study, a workable model of final unification can be developed.

A PLS-based quality prediction method is proposed for batch processes using two-dimensional extended windows. To realize the adoption of information in the direction of sampling time and batch, a new definition region of support (ROS), k-i-back-extended region of support (KIBROS), is proposed to establish the extended window, which including the data of the previous sampling times in the same batch, the data of the same sampling time in the historical batches, the data of the previous sampling times in the historical batches and the data of the later sampling times in the historical batches. According to these regions of support, extended windows are established, and different models are proposed based on the extended windows for batch processes quality prediction. Further, using a typical batch process as an example, the injection molding process, the proposed quality prediction method is experimentally verified, proving that the proposed methods have higher prediction accuracy than the traditional method and the prediction stability is also improved.

Several bio-actors are involved in the occurrence of leishmaniasis, which is made too complex for prevention and control options. Currently, all forms of leishmaniasis are being treated with chemical drugs, which have limitations and adverse effects on patients. Searching the bioactive molecules from plant sources allows the development of a novel drug. The essential oil and solvent extract of the roots of E. kebericho showed antileishmanial activity. But looking for biological activities of the isolated active ingredient from tubers of E. kebericho was scant. Thus, the isolation of the leishmanicidal compound from the roots of E. kebericho through a bioassay-guided technique was an aim of this work. Dehydrocostus lactone showed doubled potent than the standard drug miltefosine on leishmanicidal activities against L. major and L. tropica. Besides, the broad-spectrum biological activities of dehydrocostus lactone could be a potential drug candidate for co-infected patients caused by an association of leishmania and another pathogen.

Berberis vulgaris L. (Berberidaceae) is a shrub that has been widely used in European folk medicine as an anti-inflammatory and antimicrobial agent. The purpose of our study was to elucidate the mechanisms of antiproliferative action of the plant’s methanolic root extract (BVR) against colon cancer cells. Cytotoxicity and pro-apoptotic activity were determined in human colon adenocarcinoma cell lines (LS180 and HT-29) and control colon epithelial CCD841 CoN cells. According to the MTT assay, after 48 h of cell exposure, the IC50 values were as follows: 4.3; 46.1 and 50.2 µg/mL for LS180, HT-29, and CCD841 CoN cells, respectively, showing the greater sensitivity of cancer cells to BVR. The Cell Death Detection ELISAPLUS kit demonstrated that BVR induced programmed cell death only against HT-29 cells. RT-qPCR with relative quantification method showed significant changes in the expression of genes related to apoptosis in both colon cancer cell lines. The genes BCL2L1 (126.84-366.66%), BCL2L2 (277.08-330.12%), CASP3 (180.36-261.36%) and CASP9 (158.08-213.46%) had significantly elevated expression, while BCL2 (23.08-52.06%) had reduced expression. Furthermore, in a panel of antioxidant tests, BVR showed positive effects (63.93±0.01, 122.92±0.01, and 220.29±0.02 mg Trolox equivalents (TE)/g in the DPPH•, ABTS•+ and ORAC assays, respectively). In the lipoxygenase (LOX) inhibition test, BVR revealed 62,60±0.87% of enzyme inhibition. The chemical composition of BVR was determined using UHPLC-UV-CAD-MS/MS analysis and confirmed the presence of several known alkaloids, including berberine, as well as other alkaloids and two derivatives of hydroxycinnamic acid (ferulic and sinapic acid hexosides). This is the first such extensive assessment of the biological activity of BVR. The results are very promising and encourage for the use of BVR as a comprehensive chemopreventive agent (anti-inflammatory, antioxidant, and pro-apoptotic) in colorectal cancer.

Product introductions play a pivotal role in the success and competitiveness of manufacturing, particularly in the context of new product development. Low-volume manufacturing companies exhibit distinct characteristics that significantly influence the product introduction process. Notably, the quality of information exchange between product design and production interfaces becomes paramount in this high-mix and low-volume industry. Consequently, there exists a pressing need to explore various methods for adapting and customizing management mechanisms and strategies to align with the unique requirements and characteristics of low-volume manufacturing and its associated product introduction processes. While the need for this knowledge is critical in the context of low-volume manufacturing, a majority of existing studies predominantly focus on the management aspects within high-volume manufacturing. Therefore, the primary aim of this study is to investigate the customization of product introduction management strategies to enhance the quality of information content within the realm of low-volume manufacturing. Drawing upon a longitudinal analysis of new product introductions within a low-volume manufacturing company, this study narratively elucidates how the examined company implemented product introduction management strategies to facilitate the enhancement of information content quality during the product introduction phase. The study presents its findings on management strategies across three key stages: pre-implementation, post-implementation, and subsequent modification and refinement of strategies following the initial round of implementation. By shedding light on these strategies, this study offers a comprehensive understanding of management approaches in the context of low-volume product introduction. As a result, it makes a valuable contribution to the discourse on information management and interface management in the high-mix, low-volume manufacturing literature.

In this paper, some mixed type bounds on the spectral radius $\rho(A\circ B)$ for the Hadamard product of two nonnegative matrices ($A$ and $B$) and the minimum eigenvalue $\tau(C\star D)$ of the Fan product of two $M$-matrices ($C$ and $D$) are researched. These bounds complement some corresponding results on the simple type bounds. In addition, a new lower bound on the minimum eigenvalue of the Fan product of several $M$-matrices is also presented: $$ \tau(A_{1}\star A_{2}\cdots\star A_{m})\geq \min_{1\leq i\leq n}\{\prod^{m}_{k=1}A_{k}(i,i)-\prod^{m}_{k=1}[A_{k}(i,i)^{P_{k}}-\tau(A_{k}^{(P_{k})})]^\frac{1}{P_{k}}\}, $$ where $A_{1},\ldots, A_{k}$ are $n\times n$ $M$-matrices and $P_{1},\ldots, P_{k}>0$ satisfy $\sum^{m}_{k=1}\frac{1}{P_{k}}\geq 1$. Some special cases of the above result and numerical examples show that this new bound improves some existing results.

(1) Background: Although diagnostic criteria for massive hemorrhage with organ dysfunction such as disseminated intravascular coagulation associated with delivery have been empirically established based on clinical findings, strict logic has yet to be used to establish numerical criteria. (2) Methods: A dataset of 107 deliveries with ≥2,000 g of blood loss, among 13,368 deliveries from nine national perinatal centers in Japan between 2020 and 2023 was obtained. Twenty-three patients had fibrinogen levels <170 mg/dl, which is the initiation of coagulation system failure per our previous reports. Three of these patients had hematuria. We used six machine learning methods to identify the borderline criteria dividing the fibrinogen/fibrin/fibrinogen degradation product (FDP) planes, using 15 coagulation fibrinolytic factors. (3) Results: The boundaries of hematuria development on a two-dimensional plane of fibrinogen and FDP were obtained. If the FDP–fibrinogen/3–60 (mg/dl) value is positive, this indicates hematuria; otherwise, the case is non-hematuria, as demonstrated by the support vector machine method that seemed the most appropriate. (4) Conclusions: The borderline criterion dividing the fibrinogen/FDP plane for patients with hematuria that could be considered organ dysfunction in massive hemorrhage during delivery was obtained using artificial intelligence, and this method seemed to be useful.

Iron oxide nanoparticles have been investigated due to their suitable characteristics for diverse applications in the fields of biomedicine, electronics, water/wastewater treatment and sensors. Maghemite, magnetite and hematite are the most widely studied iron oxide particles and have ferrimagnetic characteristics. When very small, however, these particles have superparamagnetic properties and are called superparamagnetic iron oxide nanoparticles (SPIONs). Several methods are used for the production of these particles, such as coprecipitation, thermal decomposition and microemulsion. However, the variables of the different types of synthesis must be assessed to achieve greater control over the particles produced. In some studies, it is possible to compare the influence of variations in the factors for production with each of these methods. Thus, researchers use different adaptations of synthesis based on each objective and type of application. With coprecipitation, it is possible to obtain smaller, more uniform particles with adjustments in temperature, pH and the types of reagents used in the process. With thermal decomposition, greater control is needed over time, temperature as well as the proportion of surfactants and organic and aqueous phases in order to produce smaller particles and a narrower size distribution. With the microemulsion process, the control of the confinement of the micelles formed during synthesis through the proportions of surfactant and oil makes the final particles smaller and less dispersed. These nanoparticles can be used as additives for the creation of new materials, such as magnetic bacterial cellulose, which has different innovative applications. Composites that have SPIONs, which are produced with greater rigour with regards to size and distribution, have superparamagnetic properties and can be used in medical applications, whereas materials containing larger particles have ferromagnetic applications. To arrive at a particular particle with specific characteristics, researchers must be attentive to both the mechanism selected and the production variables to ensure greater quality and control of the materials produced.

Many farms are replacing the lighting with light emitting diode (LED) bulbs because of the technological modernization. We aimed to investigate the effects of incandescent light (IL) and LED lighting on Cobb500 broiler chickens for six weeks. Production parameters (body weight, feed consumption, feed conversion ratio), calculated slaughter values (yield%, relative breast%, thigh%) and breast meat quality parameters (pH at 45 min and 24 h postmortem, color, drip loss, kitchen equipment losses, shear force, meat composition) were recorded. Non-stop recordings were used to analyze the behavior of the birds in several periods of the rearing. LED group was significantly better in body weigh parameter between week 1-5 and feed conversion ratio between week 2-3. The most significant difference in behavior was observed in the middle of the rearing period. The chickens in the LED group spent more eating time, drinking time, interacting, and resting less. There was no difference in the meat quality parameters, only shear force was significantly lower in the LED group (1781.95±0.33 g/s vs. 2098.82±0.42 g/s). Based on our results, LED lighting can bring positive changes in animal production efficiency, behavior, and important characteristics for meat consumers.

Water quality assessment in pastoral of Tibetan Plateau, which is water sources for about 40% of world's population and the runoff-yield area of Yellow rivers, is very important. In this paper, Xiahe county which belongs to Tibetan Plateau pastoral was investigated. Six parameters(via, chloride, COD, ammonia nitrogen, nitrate, fluoride, sulfate) were selected to assess the water quality and health degree by using fuzzy comprehensive evaluation methods. The hydrochemical type in surface water was of HCO3--Mg2+-Ca2+ type. The cations and anions in surface water were mainly from weathering and dissolution of carbonate rock. Results showed that the water quality in all 69 sampling sites was all of class Ⅰ. The integrated health degree reached more than 0.85 and the health rate were 100%. Although ammonia nitrogen was regarded as the main contamination factor, but it had a little effect on the entire body of water. Overall, the surface water qualities of most samples in Xiahe County was good condition.

Artificial intelligence (AI) is increasingly being used to improve the quality control of point-of-care diagnostics. This is caused by a number of factors, including the following: 1. AI can accelerate and improve testing accuracy. In comparison to humans, AI technology can review data more quickly and precisely, reducing errors and improving overall quality assurance. 2. When it comes to improving POC test findings on healthcare issues such as infectious diseases or medical crises such as heart attacks, AI can be used for sophisticated predictive analytics and modeling that aid in better decision-making. 3. Artificial intelligence facilitates process automation, increasing productivity and lowering labor costs in labor-intensive tasks such as testing and analyzing samples collected at point-of-care facilities. 4. The use of AI enables organizations implementing these solutions to gain insights from large volumes of raw diagnostic data generated faster and more accurately, allowing them to build solid frameworks around preventive care initiatives and significantly influence public health outcomes.5. Artificial intelligence (AI) has been demonstrated to be a useful tool for real-time monitoring systems that identify any problems with test results early so that they can be corrected before affected patients receive inaccurate diagnoses or treatment plans based on false information provided by diagnostic tests performed at points of care such as clinics or hospitals.Using these technologies would allow healthcare organizations to spend less on labor while still receiving exact diagnoses and rapid treatment delivery at a fraction of the cost that manual approaches required earlier.

In recent decades, as eutrophication in inland and coastal waters (ICWs) has increased due to anthropogenic activities and global warming, so has the need for timely monitoring. Compared with traditional sampling and laboratory analysis methods, satellite remote sensing technology can provide macro-scale, low-cost, and near real-time water quality monitoring services. The Geostationary Ocean Color Imager (GOCI), integrated onboard the Communication Ocean and Meteorological Satellite (COMS) from the Republic of Korea, was the first geostationary ocean color observation satellite and was operational from April 1, 2011 to March 31, 2021. Over ten years, GOCI has observed oceans, coastal waters, and inland waters within its 2,500 km×2,500 km target area centered on the Korean Peninsula. The most attractive feature of GOCI, compared with other commonly used watercolor sensors, was its high temporal resolution (1h, eight times daily from 0 UTC to 7 UTC), providing the opportunity to monitor the quality of ICWs, where optical properties can change rapidly throughout the day. This systematic review aims to comprehensively review GOCI features and applications in ICWs, analyzing progress in atmospheric correction algorithms and water quality monitoring. Analyzing 123 articles from the Web of Science and China National Knowledge Infrastructure (CNKI) through a bibliometric quantitative approach, we examined GOCI’s strength and performance with different processing methods. These articles reveal that GOCI played an essential role in monitoring the ecological health of ICWs in its observation area in East Asia. GOCI has led the way to a new era of geostationary ocean satellites, providing new technical means for monitoring water quality in oceans, coastal zones, and inland lakes. We also discuss the challenges encountered by geostationary satellites in monitoring water quality and provide suggestions for improvements.

Cell-culture meat is a novel concept to replace traditional meat produced from animals, and to satisfy rising food demands due to the world population growth. It is still a young field and requires to solve technical issues including cell sources and types, efficient culture for large scale production, taste and texture for customer satisfaction. The current review summarized traditional beef meat production and evaluation methods for customer satisfaction. In particular, serum biomarkers for beef meat evaluation are discussed, which can be applicated for cell-culture meat production.

The paper delineates the developed vision system of the UR5 cobot and the operating algorithm of the robotic quality control station. The hardware-software architecture of the developed robotic station was shown, consisting of a UR5 cobot equipped with a web camera and a stationary industrial camera with a lighting system. Image processing and analysis algorithms were described, the method of control and communication between the station components was discussed, and two operating scenarios were presented as a single robotic station and a robotic line. Based on the results obtained, the level of measurement noise, accuracy, and repeatability of the developed vision system were estimated.

A large number of studies have indicated that plant community modulate the yield, improve growth and promote development of host plants, and among them rhizosphere growth-promoting bacteria play an important role in increasing crop yield. Bacteria benefit from the plant nutrients provided by the roots, but plants can benefit from their rhizobacteria as well. Rhizobia are considered as the most important candidate for plant growth promotion in comparison with rhizobacteria due to their endophytic nature and nitrogen fixing ability. They can also provide auxins which play a notable function in plant growth and plant-microbe interactions. Bacillus spp., the sporulating Gram-positive bacteria, have important roles in plant growth promotion and induction of systemic resistance. Pseudomonas are Gram-negative aerobic chemoheterotroph and are usually found in the environment. Streptomyces are important groups of soil bacteria from the actinomycetes family. Most of them are efficient rhizosphere and rhizoplane colonizers, and they can also be endophytes colonizing inner tissues of host plants. The present review aims to present the most up-to-date findings and results regarding the effects of plant growth promoting bacteria on yield of different crops, especially sorghum. Furthermore, the mechanisms of the actions of different bacteria briefly illustrated, aiming to present future needs to be addressed in sustainable crop production. Plant growth promoting rhizobacteria inoculation with different plants or treating plants with microbe-to-plant signal constituents can be an effectual technique to stimulate crop growth. They are also active in protecting crops from phytopathogens and environmental stress, plant pathogens and they have positive roles in nutrient cycling.

Environmental monitoring programs rely on periodic spot sampling at specific locations, followed by laboratory analysis, aiming at the evaluation of water quality at a catchment scale. For this purpose, automatic telemetric stations for specific parameters have been installed by the Institute of Marine Biological Resources and Inland Waters of Hellenic Centre for Marine Research (IMBRIW-HCMR) within several Greek rivers and lakes, providing continuous and temporal monitoring possibilities. Nevertheless, the employment of unmanned surface vehicles (USV) equipped with integrated sensors represents a tool valuable to several monitoring strategies, offering enhanced temporal and spatial coverage over specific timeframes, allowing for targeted examination of sites or events of interest. The USVs have been deployed by Athens Water and Sewerage Company (EYDAP) as a cost-effective tool for the environmental monitoring of surface water bodies of interest, with emphasis on the spatial fluctuations of chlorophyllα, electrical conductivity, dissolved oxygen and pH, observed in Koumoundourou Lake and rivers Acheloos, Asopos and Kifissos. The effectiveness of an innovative heavy metal (HM) system installed in the USV for thein situ determination of copper and lead was also evaluated herewith. The results obtained demonstrate that both the timely detection of potential pollution from both anthropogenic activities and natural processes as well as the monitoring of inland waters are made feasible through the employment of USV.

The supply chain has incorporated products by putting them into hair scarfs. This study introduces the use of mini chips in health and beauty products and can reduce fatigue through enhanced sleep patterns. The mini chip could be placed in the scarf and used as a prototype. RFID technology provides the supply chain with specific information that is used to identify products and make communication easier. (Muhammad, et. al. 2013) This paper presents a new tool herein referred to as a scarf prototype which is developed to analyse EMG (electromyogram), ECG (electrocardiography), EEG (electroencephalogram), and EOG (electro-oculogram) signals that focuses in the area of sleep disorders. The mini chips used can be used to determine a solution for sleep disruption by using automated analytics. This could lead to improvement in our understanding of sleep disruption and overall sleep physiology. Automated technology allows repeated measurements, evaluation of sleep patterns, and provide suggestions to improve a person’s quality of sleep. This analysis compares the use of polysomnography and the scarf prototype. The analytics provide models and shows correlation between variables, such as EMG, ECG, EEG, and EOG. This study shows that the results from the scarf prototype is just as reliable as the original method, polysomnography.

For a long time, a company's Product Development Process (PDP) was seen as supporting the operations department, although PDP decisions and mistakes have a considerable impact on market performance. This is critical even in agriculture where bad habits and practices in the PDP can lead rural producers to great losses. Therefore, this research investigated the effect on the market performance of rural products (banana) in the southern region of Brazil, based on two analyses: (i) how sustainability practices support the PDP phases and (ii) how the phases of the Product Life Cycle Assessment (LCA) mediate sustainability practices and PDP phases. This study presents a quantitative analysis using Confirmatory Factor Analysis (CFA) and hierarchical ordinary least squares (OLS) regression of data obtained from a survey of 110 rural producers who directly participate in the banana production and planning process in southern Brazil. Our results shows that sustainability practices support the PDP, and we confirm that the product development and post-development phase has an effect on market performance. In addition, we identified that in the pre-development phase of the PDP, dealing with rural products (bananas), the maturity stage of the LCA mediates sustainability. In the PDP development phase, we concluded that rural families that develop economic and environmental practices with their products in the market growth phase may have reduced results. As for the post-development phase of the PDP, we conclude that when companies invest in environmental and social practices, there is a complete mediation of the effect, where these practices lose strength if the product is in the introduction and maturity phases in the market. As originality, our study contributed to demonstrate value on the product life cycle for the product development process in agriculture using sustainability practices through a systemic approach, filling the gap in the literature due to the lack of research on these areas seen in an integrated way.

In this paper we introduce the hypo-q-norms on a Cartesian product of inner product spaces. A representation of these norms in terms of inner products, the equivalence with the q-norms on a Cartesian product and some reverse inequalities obtained via the scalar Shisha-Mond, Birnacki et al., Grüss type inequalities, Boas-Bellman and Bombieri type inequalities are also given.

Honey is a sweet substance extensively consumed in the world for its nutritional and healthy properties. However, residues of pesticides and environmental contaminants can compromise its quality. For this reason, the physicochemical parameters, and the organic contamination of monofloral and multifloral honeys from three regions of Algeria (Tiaret, Laghouat and Tindouf) were monitored to evaluate the quality of honey and the safety for consumers. In general, the results obtained from the physicochemical analyses were in line with the EU standards. In terms of contamination, pesticides authorised and used in Algerian agriculture (matalaxyl-M and cyromazine), as well as banned pesticide (carbaryl), were found in almost all the samples. However, only the concentration of cyromazine was higher than the relative EU maximum residue levels. PCB 180, PCB 189, anthracene, fluorene and phenanthrene were mainly detected. All the honeys show traces of DiBP, DBP, DEHP and DEHT, but no traces of bisphenols were found. Moreover, the dietary exposure assessment shows that a small amount of Algerian honey can be safely consumed. Overall, data from this study should motivate the Algerian government to enhance their monitoring activities in beekeeping and to find solutions for implementing more sustainable agricultural practices harmonizing with the international legislation.

The concept of economic self-reliance, widely known by Thai people as the philosophy of sufficiency economy, has been widely promoted in rural Thai societies. By practicing this philosophy, it is expected that the citizens’ quality of life and local environments could be sustainably improved. This study aims to explore the contribution of the community practices of the sufficiency economy philosophy to rural villagers’ quality of life improvement, and to investigate potential factors that determine the trust of villagers in the philosophy. With the purpose to propose strategies which could enhance trust and promote villagers’ practices of the philosophy, the study investigated influences of three relevant factors on trust towards the philosophy. Those factors included factors related to cognitive-based trust, factors related to emotional-based trust, and factors related to demographic characteristics. Questionnaire surveys and in-depth interviews with community leaders and local villagers were conducted in the Ban Jamrung community, in Thailand’s Rayong province. The results of the statistical analysis revealed that the residents who applied the sufficiency economy philosophy in their daily lives experienced a relatively better quality of life. Additionally, it was found that trust in the philosophy could be predicted more by rational factors than by emotional factors. These findings could be utilized to develop strategies to maintain and enhance the trust of the people in the philosophy of sufficiency economy.

COVID19 is a current pandemic disease due to the novel coronavirus SARS-CoV-2. The scientific community mounted a strong response by accelerating research and innovation, and rapidly setting the basis to the understanding of molecular determinants of the disease for the development of targeted therapeutic interventions. The replication of the viral genome within the infected cells is a key step of SARS-CoV2 life cycle. It is a complex process involving the action of several viral and host proteins in order to perform RNA polymerization, proofreading and final capping. This review provides an update of structural and functional data on key actors of the replicatory machinery of SARS-CoV-2, filling the gaps in the current availability of structural data using homology modelling. Moreover, learning from similar viruses, we collect literature data to reconstruct the pattern of interactions among protein actors of the SARS-CoV-2 RNA polymerase machinery. In this pattern, an important role is played by co-factors, like Nsp8 and Nsp10, not only as allosteric activators but also as molecular connectors holding the entire machinery together to enhance the efficiency of RNA replication.

Apple (Malus x domestica) fruit size is dependent on cell division and cell expansion, processes which are subsequently regulated by plant hormones such as auxins, gibberellins, and cytokinins. In this study, we investigated the role of cell division and cell expansion in apple growth and identified which of the two was more deterministic to final fruit size. Three cultivars of different sizes were selected, namely, ‘Twenty Ounce’ (large-sized), ‘Royal Gala’ (medium-sized), and ‘Crabapple’ (small-sized). Gene expression and cell size analyses were conducted over the course of two consecutive seasons. The expression patterns of three classes of genes were markedly similar across all cultivars. Two cell division markers, namely, MdCDKB2;2 and MdANT2, were discovered to be correlatively expressed as both displayed initially high expression levels, which gradually declined from the early to late stages of growth time course. For cell expansion markers, MdEXP3 was upregulated as the cells expanded, while MdARF106 was expressed in both the cell division and expansion stages. Meanwhile, the ripening related gene MdACO1 was expectedly expressed only during the ending stages associated with ripening. Interestingly, the cell measurements taken regularly from each cultivar throughout the same eperimental timespan showed that cell sizes were unaltered and remained constant from initial pollination at the zeroth Days After Pollination (DAP), to ripening at 120 Days After Full Bloom (DAFB).

This study addresses the urgent need for sustainable protein sources in aquaculture due to the depletion of marine resources and rising costs. Animal protein sources, particularly poultry by-product meal (PBM) and insect exuviae meal, are investigated as viable alternatives to fishmeal (FM). Research confirms the successful replacement of FM with a combination of PBM and insect exuviae meal (up to 50%) in the diet of European seabass without compromising growth, feed conversion, gut health and liver fat content. In particular, growth performance was robust with both PBM formulations, with the 25% PBM diet showing better results. Histological examinations showed good gut and liver health, contradicting the concerns of previous studies. The study emphasizes the importance of holistic analyzes that go beyond growth parameters and include histomorphological investigations. The results show that PBM in combination with insect/exuviae meal is well tolerated by seabass, which is consistent with literature reports of mitigating negative effects on gut health. A detailed analysis of the microbiota revealed a decrease in the Firmicutes/Proteobacteria ratio due to an increase in potentially pathogenic bacteria. However, the formulation containing insect exuviae partially counteracted this effect by preserving the beneficial Lactobacillus and promoting the synthesis of short-chain fatty acids (SCFA), particularly butyrate. Chitin-rich components from insect exuviae were associated with improved gut health, which was supported by increased production of SCFA, which are known for their anti-inflammatory properties. The study concludes that a combination of PBM and insect/exuviae meal can replace up to 50% of FM in the diet of seabass, supporting sustainable aquaculture practices. Despite some changes in the microbiota, the negative effects are mitigated by the addition of insect exuviae, highlighting their potential as a prebiotic to increase fish productivity and contribute to a circular economy in aquaculture.

Based on three assumptions of our 4G model of final unification, we have developed simple logics for estimating the unified atomic mass unit, atomic electrochemical equivalents, Faraday constant and Avogadro number. We appeal the science community to review the following points. 1) Unified atomic mass or energy unit can be considered as ‘average rest energy of nucleons minus average binding energy per nucleon of all atomic nuclides plus electron rest energy’. 2) Electrochemical equivalent of any atomic ion is nothing but the ratio of its mass to its charge. 3) Faraday charge is nothing but the ratio of elementary charge to unified atomic mass unit. 4) Faraday mass can be considered as the inverse of Faraday charge. 5) Avogadro number is nothing but the inverse of unified atomic mass unit. 6) Number of atoms per kg can be called as Kg-mole and number of atoms per gram can be called as gram-mole. Following our 4G model, starting form A=5 to 340, for isobars, ‘average binding energy per nucleon’ having maximum binding energy can be estimated with a simple relation of the form, BE/A=A^-1[1-(0.5+0.000935A²)-A^1/3]10.1MeV. It needs a review and fine tuning.

The hot rolling in the process chain of the aluminium rolled products present the critical element of material quality and influence on productivity. The desire to increase the letter demand modifications of hot rolling, consequential changes of microstructure, crystallographic texture, mechanical and formability properties must be knowledge and consistently considered in planning the rolling process and rolled product. Achieving lower thicknesses of the hot-rolled band would enable fewer passes with cold rolling; consequently, hot rolling with the same number of passes will complete with lower temperatures. Microstructural and texture characterization with the optical microscope and scanning electron microscope for the hot-rolled band 3.25 mm the smaller grains appeared in the center of the cross-section, unlike for the hot-rolled band 6 mm, the smaller grains were detected on the upper and bottom position of the cross-section. Furthermore, the comparison shows also that the hot-rolled band 6 mm has 64 % of random texture components and 83 % of recrystallized grains, and the proportional adjustment for the hot-rolled band 3.25 mm has the 42 % of random texture components and 55 % of recrystallized grains. For the mechanical testing results, the elongation values in rolling and transverse directions significantly differ just in the case of a hot rolled band of 3.25 mm. Consequently, the earing results are more than 1.5 % higher for the hot-rolled band, 3.25 mm, than the hot-rolled band, 6 mm.

Emulsifiers like egg yolk (EY) are necessary for the formation of mayonnaise, which is an oil-in-water type colloid. This study aimed to assess the potential of defatted soybean powder treated with supercritical carbon dioxide (DSF-SC) in enhancing the quality of plant-based may-onnaise as plant-based alternatives gain popularity. This study involved producing DSF-SC and comparing its quality attributes to those of mayonnaise made with varying amounts of control soy flour (CSF), DSF-SC, and EY. It was found that mayonnaise made with DSF-SC, with increased emulsifier quantity, showed better emulsion stability, viscosity, and smaller, more uniform particle size compared with CSF mayonnaise. Additionally, DSF-SC mayonnaise was overall rated higher in sensory evaluation. The addition of approximately 2% DSF-SC positively influenced the emul-sion and sensory properties of the vegan mayonnaise, making DSF-SC a promising plant-based alternative emulsifier for replacing animal ingredients.

Background: MOST-plus is a multicenter, randomized, open-label, adaptive Phase II trial evaluating the clinical benefit of targeted treatments matched to molecular alteration in advanced/metastatic solid tumors. Sorafenib was tested on patients with tumors harboring sorafenib-targeted genes Methods: The MOST-plus trial used a randomized discontinuation design. After 12 weeks of sorafenib (400 mg, po BID), patients with progressive disease dis-continued study, patients with objective response were proposed to continue sorafenib, whereas patients with stable disease (SD) were randomly assigned (1:1) to maintenance or interruption of treatment. Primary endpoint was RE-CIST version 1.1 progression-free rate at 16 weeks after randomization (PFR-16w). Secondary endpoints included progression-free survival (PFS), overall survival (OS), and toxicity. Statistical analyses used a sequential Bayes-ian approach with interim efficacy analyses. The enrolment could be stopped in the case of a 95% probability for the estimated PFR-16w to be higher in the maintenance than in the interruption arm (NCT02029001). Results: 151 patients were included, of whom 35 had SD at 12 weeks of Soraf-enib. For the 35 patients with SD on sorafenib, the PFR-16w was 65% [95% credibility interval 43.4–83.7] in the continuation arm and 25% [7.8–48.1] in the interruption arm. Median PFS and OS were improved in maintenance versus interruption arm (mPFS: 5.6 [95%CI 1.97–6.77] months versus 2.0 [95%CI 1.61–3.91] months (p =0.0231) and mOS : 14.3 [95%CI 8.9–23.8] versus 8.0 months [95%CI 3.5–15.2] (p =0.0857)). Conclusion: Sorafenib showed activity in progressive patients with solid tu-mors harboring somatic genomic alterations in sorafenib-targeted genes. Con-tinuing sorafenib when SD is achieved improves PFR compared to interruption

Introduction: Exams are a relatively stressful period for all students, especially undergraduate medical students. Exams bring anxiety and stress for the students. Some students experience such high stress that it hinders their academic productivity and reduces their exam performance. The aim of this study is to assess the effects of pre-exam anxiety on the academic performance of medical students. Methods: Two hundred and twenty-five final year medical students completed Westside Test Anxiety (WTA) Scale one month before their exams. Grade Point Average (GPA) of these students was noted when the results were announced. Data was processed and analyzed using SPSS v 22.0Results: The mean anxiety score on WTA scale was 3.46 ± 0.87. All students (100%) who scored ≤ 2.50 GPA were highly-extremely highly anxious. In the 2.51-3.00 GPA group, 46% were highly-extremely highly anxious, 32% were moderately anxious, and 21% had low to normal anxiety. In the 3.01-3.50 GPA group, 30% were highly-extremely highly anxious, 30% were moderately anxious, and 39% had low to normal anxiety. In the 3.51-4.00 GPA group, 29% were highly-extremely highly anxious, 23% were moderately anxious, and 47% had low to normal anxiety. The correlation coefficient between GPA and test anxiety of students was -.314 which shows inverse relationship.Conclusion: Pre-exam anxiety and stress imparts negative effects on the exam performance of final year medical students. Poor academic performance was associated with high to extremely high pre-exam anxiety while high achievers had relatively lower anxiety levels.

Contamination in coastal regions attributed to fluoride and nitrate cannot be disregarded, given the substantial environmental and public health issues they present worldwide. Maintaining water quality is crucial for environmental well-being. This comprehensive study was performed to assess the spatial as well as indexical water quality, identify contamination sources, and evaluate associated health risks pertaining to nitrate and flouride in AlHassa region, KSA. The physiochemical results revealed a pervasive pollution of the overall groundwater. The dominant water type was Na-Cl, indicating saltwater intrusion and reverse ion exchange impact. Spatiotemporal variations in physicochemical properties suggest diverse hydrochemical mechanisms, with geogenic factors primarily influencing groundwater chemistry. The groundwater pollution index varied between 0.8426 and 4.7172, classifying samples as moderately to very highly polluted. Similarly, the synthetic pollution index (in the range of 0.5021-4.0715) revealed that none of the samples had excellent water quality, with various degrees of pollution categories. Nitrate Health Quotient (HQ) values indicated chronic human health risks ranging from low to severe, with newborns being the most vulnerable. Household use of nitrate-rich groundwater for showering and cleaning did not pose significant health risks. Fluoride HQ decreased with age, and children faced the highest risk of fluorosis. The Hazard Index (HI) yielded moderate to high-risk values. Nitrate risks were 1.21 times higher than fluoride risks, as per average HI assessment. All samples fell into the vulnerable category based on the Total Hazard Index (THI), with 88.89% classified as very high risk. This research provides valuable insights into groundwater quality, guiding water authorities, inhabitants, and researchers in identifying safe water sources and vulnerable human populations. The results highlight the need for appropriate treatment techniques and long-term coastal groundwater management plans.

The role of initial state (ISI) and final state (FSI) ion–ion interactions in heavy ion double charge exchange (DCE) reactions A(Z,N)→A(Z±2,N∓2) are studied in the context of double single charge exchange (DSCE) reactions given by sequential actions of the isovector nucleon–nucleon (NN) T–matrix. The second order DSCE reaction amplitude is investigated in momentum representation in a formulation, focused on the extraction of nuclear matrix elements under the conditions of strong initial state (ISI) and final state (FSI) interactions. In closure approximation and using the momentum representation, the reaction amplitude is finally separated into ISI/FSI distortion coefficients and reaction kernels and nuclear matrix elements. The ISI/FSI reaction kernels emerge as the result of the repeated scattering on the avoided volume, introduced by the imaginary parts of the ion–ion optical potential and acting as sinks for the quantal probability current. The closure approximation allows derive a set of induced effective two–body isotensor interactions, given by products of spin–scalar, spin–vector central and rank–2 spin–tensor interactions. The intermediate propagator plays a key role in establishing correlation between the DCE transitions in the projectile and target nucleus. The presented approach emphasizes the special features of DSCE reaction dynamics as proceeding like a system of two coupled isospin dipoles whose strengths are determined by the momentum-space form factors of the NN isovector interaction. The properties of the DSCE interaction form factors are investigated and the approach is applied to data.

Background: the nature of alpha-D-mannose - natural aldohexose sugar, C-2 glucose epimer, whose intended use is for preventing urinary tract infections - in the interaction with E. coli is addressed in order to drive the issue of its regulatory classification as a medicinal product or medical device. Methods: PRISMA systematic review approach was applied; Delphi Panel method used to target consensus on statements retrieved from evidence. Results: Based of regulatory definitions and research evidences, the mechanism of D-mannose does not involve a metabolic or immunological action while there is an uncertainty regarding the pharmacological action. Specific interaction between the product and the bacteria within the body occurs, but its nature is inert: it does not induce a direct response activating or inhibiting body processes. Moreover, the action of D-mannose takes place, even if inside the bladder, outside the epithelium on bacteria that have not yet invaded the urothelial tissue. Therefore, its mechanism of action is not directed to host structures but to structures (bacteria) external to the host's tissues. Conclusions: From a regulatory perspective, D-mannose maintains the current medical device classification: new regulations and legal judgments can add further considerations. From a pharmacological perspective, research is driven versus synthetic mannosides: no further considerations are expected on alpha-D-mannose.

Product Development Process is widely known among industry and automobile companies. With the advance of technology and the need to improve product efficiency, many companies have been applying Lean Thinking principles. Their benefits lead those companies to implement their concepts and tools, like Value Stream Design in Indirect Areas, Obeya, Just-in-time (JIT) which is based on the production control system developed and implemented by Toyota. This article describes the case study of the implementation of Lean Product & Process Development (LPPD) on the current Product Development Process (PDP) in an automotive company. The PDP was created by the organization and adapted from Advanced Product Quality Planning (APQP). The main findings were a Value Stream Design model of an improved PDP as a useful and successfully contribution for the company. These improvements reduced the product development lead time from 700 days to 369 days. The process efficiency increased from 68% to 85%. The communication and transparency between the cross-functional team (CFT) was improved and show promise for achieving a successful launch of new products.

Natural products (NPs) are a rich source of structurally novel molecules, and the chemical space they encompass is far from being fully explored. Over history, NPs have represented a significant source of bioactive molecules and have served as a source of inspiration for developing many drugs on the market. On the other hand, computer-aided drug design (CADD) has contributed to drug discovery research, mitigating costs and time. In this sense, compound databases represent a fundamental element for the CADD. This work reviews the progress toward developing compound databases of natural origin, particularly databases developed in Latin America, and their practical applications in the drug discovery area. We also survey the computational methods, emphasizing chemoinformatic approaches to profile natural product databases.

This paper is devoted to the study of reproducing kernels on 2-inner product Hilbert spaces. We focus on a new structure to produce reproducing kernel Hilbert and Banach spaces. According to multi-variable computing, this structures can be useful in electrocardiographs, machine learning and economy

This study aims to model grinding of a Polish slag and evaluate the particle size distributions of the products obtained after different grinding times. Then, selected products were alkali activated in order to investigate the effect of particle size on the compressive strength of the produced alkali activated materials (AAMs). Other parameters affecting alkali activation, i.e. temperature, curing and ageing time were also examined. Among the different mathematical models used to simulate the particle size distribution, Rosin-Rammler (RR) was found to be the most suitable. When piecewise regression analysis was applied to experimental data it was found that the particle size distribution of the slag products exhibits multi fractal character. In addition, grinding of slag exhibits non-first-order behavior and the reduction rate of each size is time dependent. The grinding rate and consequently the grinding efficiency increases when the particle size increases, but drops sharply near zero after prolonged grinding periods. Regarding alkali activation, it is deduced that among the parameters studied, particle size (and the respective specific surface area) of the raw slag product and curing temperature have the most noticeable impact on the compressive strength of the produced AAMs.

A wide variety of bacteria, fungi and plants can produce bioactive secondary metabolites, which are often referred to as natural products. With the rapid development of DNA sequencing technology and bioinformatics, a large number of putative biosynthetic gene clusters have been reported. However, only a few natural products can be detected when isolated species are grown under conventional laboratory conditions, as most biosynthetic gene clusters are not expressed or are expressed at extremely low levels at these conditions. With the rapid development of synthetic biology, advanced genome mining and modification strategies have been reported, and they provide new opportunities for discovery of natural products. This review discusses advances in recent years that can accelerate the design, build, test, and learn (DBTL) cycle of natural product discovery, and prospects trends and key challenges for future research directions.

Ocean surface heat fluxes play a significant role in the genesis and evolution of various marine-based atmospheric phenomena, from the synoptic scale down to the microscale. While in-situ measurements from buoys and flux towers will continue to be the standard in regards to surface heat flux estimates, they commonly have significant gaps in temporal and spatial coverage. Previous and current satellite missions have filled these gaps; though they may not observe the fluxes directly, they can measure the variables needed (wind speed, temperature, and humidity) to estimate latent and sensible heat fluxes. However, current remote sensing instruments have their own limitations, such as infrequent coverage, signals attenuated by precipitation, or both. The Cyclone Global Navigation Satellite System (CYGNSS) mission overcomes these limitations over the tropical and subtropical oceans by providing improved coverage in nearly all weather conditions. While CYGNSS (Level 2) primarily estimates surface winds, when coupled with observations or estimates of temperature and humidity from reanalysis data, it can provide estimates of latent and sensible heat fluxes along its orbit. This paper describes the development of the Surface Heat Flux Product for the CYGNSS mission, its current results, and expected improvements and changes in future releases.

We discuss further details on the concepts of “drug-likeness”, “lead-likeness”, and “natural product-likeness”. The discussion will first focus on natural products as drugs, then a discussion of previous studies in which the complexities of the scaffolds and chemical space of naturally occurring compounds have been compared with synthetic, semi-synthetic compounds and FDA-approved drugs. This is followed by guiding principles for designing “drug-like” natural product libraries for lead compound discovery purposes. We end up by presenting a tool for measuring “natural product-likeness” of compounds and a brief presentation of machine learning approaches and a binary quantitative structure-activity relationship (QSAR) for classifying drugs from non-drugs and natural compounds from non-natural ones, respectively.

The analysis and simulation of water quality in distribution networks is a complex issue of great concern today. The analysis of the evolution of water age, as a simple indicator of water quality in the network, is of great interest in both design and operation phases. Understanding the factors that have the strongest influence on water quality is key to developing adequate strategies aimed at preserving it. This paper firstly analyses the factors with biggest influence in the tanks water age, to support the selection of the most appropriate configuration from the point of view of water quality during design phases. Then, the main considerations when modelling tanks following the different mixing models considered in Epanet have been presented. Also, a real tank behaviour has been characterised through field measurements and Epanet simulations in order to determine the best fitted mixing model.

Building fires are preventable incidents that have proven to be both deadly and costly. Addressing their root causes will lead to safer neighbourhoods for families and businesses to live and operate in. Multiple studies have established the effect of residents’ socioeconomic compositions on an area’s building fire rates; however, the existing model based on the classical stepwise regression procedure has several limitations. This paper aims to construct a more accurate predictive model of building fire rates based on a set of explanatory socioeconomic variables. In building the socioeconomic model, a backward elimination by Robust Final Predictor Error (RFPE) criterion is proposed to enhance the forecasting capability of the model. The proposed method has been implemented on the census data and the fire incident data of the South East Queensland region in Australia. A cross-validation was then conducted to assess the model’s accuracy. In addition, comparative analyses of other elimination criteria, such as p-value, adjusted R-squared, Akaike’s Information Criterion (AIC), Bayesian Information Criterion (BIC) and predicted residual error sum of squared (PRESS), were conducted. The cross-validation analyses demonstrate that the proposed criterion is a more accurate predictive model based on a couple of goodness-of-fit measures. All in all, the RFPE equation was found to be a suitable criterion for the backward elimination procedure in the socioeconomic modelling of building fires.

The European Union Water Framework Directive (2000/60/EC; WFD) aims to achieve a good ecological and chemical status of all bodies of surface water by 2027. The development of an integrated guidance on surface water chemical monitoring (e.g. WFD Guidance Document No. 7/19) has been transferred into national German law (Ordinance for the Protection of Surface Waters, OGewV). For the majority of compounds, this act requires a monthly sampling frequency to assess the chemical water quality status of a surface water body. To evaluate the representativeness of the sampling strategy under the OGewV, high-frequency online monitoring data is investigated under different sampling scenarios and compared with current, monthly grab sampling strategy. About 23 million data points were analyzed for this study, three chemical parameters (dissolved oxygen, nitrate-nitrogen, chloride concentration) and discharge data were selected from four catchment of different sizes ranging from 51391 km² to 84 km² (Elbe, Vereinigte Mulde, Neiße and two stations at Lockwitzbach). In this paper we proposed short-term online-monitoring (STOM) as a sampling alternative. STOM considers the placement of online sensors over a limited duration and return interval. In general we: (I) compare the results of conventional grab sampling with STOM, (II) investigate the different performance of STOM and grab sampling using discharge data as proxy for analyzing event-mobilized pollutants and (III) investigate the related uncertainties and costs of both sampling methods. Results show, that STOM outperforms grab sampling for parameters where minimum/maximum concentrations are required by law as the probability to catch a single extreme value is higher with STOM. Furthermore, parameters showing a pronounced diurnal pattern, like dissolved oxygen, are also captured considerably better. The performance of STOM showed no substantial improvements for parameters with small concentration variability, as nitrogen-nitrate The analysis of discharge events as a proxy parameter for event-mobilized pollutants proved that the probability of capturing samples during events is significantly increased by STOM.

Lactoperoxidase system (LPS) effect on quality of raw and pasteurized milk under real conditions along the dairy value chain in Ethiopia was evaluated. A total of 250 milk samples were collected from farmers, collectors, and factories. Experimental samples were LPS-activated of morning and overnight milk. The samples were tested with several chemical and microbiological tests such as total bacterial count (TBC), total coliform count (TCC) and Escherichia coli count (EC). Results indicated that all LPS-activated milk samples had a higher quality than all the control samples. For instance, both the morning and overnight farm milk samples had a mean TBCs of 5.79 log and 6.55 log cfu/ml which is significantly (p

In recent years the number of available chemical pesticides has been significantly reduced and there have been an urgent need for discovery of alternative to chemical pesticides products, as among others the natural zeolites (zeolitic rocks). We determined the mineralogical and chemical composition of a specific and continuous layers of zeolitic rock sample (ZeotP) from Petrota, Ev-ros, Greece and evaluated its oviposition deterrent effect for the olive fruit fly Bactrocera oleae (Diptera: Terphritidae). The tested natural zeolite contained 70 wt. % Clinoptilolite, 18 wt. % Amorphous material, 7 wt. % Feldspars, 4 wt. % Cristobalite and 1 wt. % Quartz. We tested the oviposition deterrent effect of ZeotP mixed or not with an emulsifier adjuvant NU-FILM-P® in water and applied on the surface of olive fruits. The ZeotP oviposition deterrent effect for the ol-ive fly was very high under a series of tested temperatures (17°C, 20°C, 25°C and 30°C) and RHs (23%, 33%, 55%, 75%, 94%). In addition, the ZeotP residual deterrent effect after equable water spraying was high and similar to the respective effect of a pyrethroid insecticide (Decis®). Our results may contribute to an effective control of the olive fruit fly using an alternative to chemical pesticides natural zeolite (zeolitic rocks) product.

mRNA-lipid nanoparticle (LNP) medicinal products can be considered a platform technology because the development process is similar for different diseases and conditions, with similar noncoding mRNA sequences and lipid nanoparticles and essentially unchanged manufacturing and analytical methods utilised often for different products. It is critical not to lose the momentum built using the platform approach during the development, regulatory approval and rollout of vaccines for SARS-CoV-2 and its variants. This Review proposes a set of modifications to existing regulatory requirements for mRNA products, based on a platform perspective for quality, manufacturing, preclinical and clinical data. For the first time, we address development and potential regulatory requirements when the mRNA sequences and LNP composition vary in different products as well. In addition, we propose considerations for self-amplifying mRNA, individualised oncology mRNA products and mRNA therapeutics. Providing a predictable development pathway for academic and commercial groups, so they can know in detail what product characterisation and data are required to develop a dossier for regulatory submission, has many potential benefits. These include reduced development and regulatory costs; faster consumer/patient access and more agile development of products in the face of pandemics; and for rare diseases where alternatives may not exist or to increase survival and the quality of life in cancer patients. Therefore, achieving consensus around platform approaches is both urgent and important. This approach with mRNA can be a template for similar platform frameworks for other therapeutics and vaccines to enable more efficient development and regulatory review.

Institutional sustainability is a dynamic and multifaceted concept that relies on the contributions of various institutions, including the legal and the scientific system. On the other side, consumers boycotts are an expression of political consumerism by which consumers can use their market power to attain sustainability objectives. This article explores institutional trust on the legal system and trust on scientists as potential drivers for consumers’ boycotts. Using data retrieved from the European Social Survey covering twenty-five countries, the study employs binary logistic regression to assess the importance of institutional trust and other potential drivers of product boycotts in Europe. Results confirm that boycotting behaviour is affected by institutional trust, as well as other individual variables including gender, age and life-cycle effects, education, interest in politics and level of satisfaction with the political system, generalized trust, personal well-being, and consumers’ use and perceptions of information and communication technologies. The results of this study enrich the literature on consumer boycotts and have implications for policymakers involved in sustainability initiatives.

The current paper has examined the effect of both export product diversification and poverty on non-resource tax revenue in developing countries. The analysis has used an unbalanced panel dataset of 111 countries over the period 1980-2014. Based on the Blundell and Bond two-step system Generalized Methods of Moments technique, the empirical analysis has shown interesting findings. Export product concentration and poverty influence negatively non-resource tax revenue over the full sample, but this effect varies across countries in the sample. Furthermore, the effect of export product diversification on non-resource tax revenue performance depends on the level of poverty. It appears that export product diversification influences positively non-resource tax revenue performance in countries that experience lower poverty rates. From a policy perspective, these findings show that policies in favour of diversifying export product baskets and reducing poverty would contribute to enhancing non-resource tax revenue performance in developing countries.

The accuracy of sales prediction models based on the big data of online word-of-mouth (eWOM) is still not satisfied. We argue that eWOM contains heat and sentiments of different product dimensions, which can improve the accuracy of these models. In this paper, we propose a dynamic topic analysis (DTA) framework in order to extract heat and sentiments of product dimensions from the big data of eWOM. Finally, we propose an autoregressive-heat-sentiment (ARHS) model, which integrates heat and sentiments of dimensions into the baseline predictive model. The empirical study in movie industry confirms that heat and sentiments of dimensions can improve the accuracy of sales prediction model. ARHS model is better for movie box-office revenue prediction than other models.

The recycling, incineration, and final disposal rate of municipal solid waste (MSW) are calculated based on the total amount of waste input to each facility in many countries. These statistic data have serious limitation in setting the national goal and policy for effective waste management because it is not considering the amount of foreign objectives in the process of each life-cycle stage. This case study is to estimate the actual rates of recycling, incineration, and final disposal by material flow analysis (MFA) after the collection of MSW in Korea. The actual rates of recycling, incineration and final disposal for MSW in 2016 were 49.9%, 32.9% and 23.1% respectively, indicating that the recycling rate was lower by 10.1%, while the incineration and final disposal rates were raised by 7.6% and 8.4% respectively, compared with the statistics for current MSW. In addition, the changed actual rates of recycling, incineration treatment, and final landfill, and variation of waste treatment charge according to treated amounts per treatment method was analyzed. This results of this study will contribute to establish national level of plan on effective waste management.

The main goal of the Soil Moisture and Ocean Salinity (SMOS) mission over land surfaces is the production of global maps of soil moisture (SM) and vegetation optical depth (τ) based on multi-angular brightness temperature (TB) measurements at L-band. The operational SMOS Level 2 and Level 3 soil moisture algorithms account for different surface effects, such as vegetation opacity and soil roughness at 4 km resolution, in order to produce global retrievals of SM and τ. In this study, we present an alternative SMOS product which was developed by INRA (Institut National de la Recherche Agronomique) and CESBIO (Centre d’Etudes Spatiales de la BIOsphère). This SMOS-INRA-CESBIO (SMOS-IC) product provides daily SM and τ at the global scale and differs from the operational SMOS Level 3 (SMOSL3) product in the treatment of retrievals over heterogeneous pixels. Specifically, SMOS-IC is much simpler and does not account for corrections associated to the antenna pattern and the complex SMOS viewing angle geometry. It considers pixels as homogeneous to avoid uncertainties and errors linked to inconsistent auxiliary data sets which are used to characterize the pixel heterogeneity in the SMOS L3 algorithm. SMOS-IC also differs from the current SMOSL3 product (Version 300, V300) in the values of the effective vegetation scattering albedo (ω) and soil roughness parameters. An inter-comparison is presented in this study based on the use of ECMWF (European Center for Medium range Weather Forecasting) SM outputs and NDVI (Normalized Difference Vegetation Index) from MODIS (Moderate-Resolution Imaging Spectroradiometer). A 6 year (2010-2015) inter-comparison of the SMOS products SMOS-IC and SMOSL3 SM (V300) with ECMWF SM yielded higher correlations and lower ubRMSD (unbiased root mean square difference) for SMOS-IC over most of the pixels. In terms of τ, SMOS-IC τ was found to be better correlated to MODIS NDVI in most regions of the globe, with the exception of the Amazonian basin and of the northern mid-latitudes.

An influenza A virus (H3N2) with an envelope with the same structure as COVID-19 was used for antiviral testing of material surfaces, in comparison with some results of feline calicivirus. The evaluation method used was the film adhesion method, in which the virus solution is placed on the material and adhered to it using a film. The evaluation method was based on the film adhesion method, in which the virus solution is placed on the material and adhered with a film, and the plaque method, in which the cell virus is allowed to infect the material and form plaques, but the appropriate virus concentration must be adjusted to observe the plaques. When not under that restriction, the plaques are often incomplete; this is observed. For this reason, this study applied an area measurement method that can reflect viral activity even when plaques are not obtained. This study revealed that different types of metallic materials have different antiviral properties. Specifically, the antiviral activity of iron, carbon steel, and nickel was relatively high, while that of stainless steel and titanium was relatively low. The order of antiviral activity was as follows: Fe, SS400, Ni, SUS316L, SUS304, and Ti.

Excretory-secretory products (ESPs) are the main research targets for investigating the hosts and helminths interaction. Parasitic worms can migrate to parasitic sites and avoid the host immune response by secreting this product. Angiostrongylus cantonensisis an important food-borne zoonotic parasite that causes severe neuropathological damage and symptoms, including eosinophilic meningitis or meningoencephalitis in humans. Benzaldehydes are organic compounds composed of a benzene ring and formyl substituents. This compound has anti-inflammatory and antioxidation properties. Previous studies showed that 3-hydroxybenzaldehyde (3-HBA) and 4-hydroxybenzaldehyde (4-HBA) can reduce apoptosis in A. cantonensis ESPs treated astrocytes. These results on the protective effect underlying benzaldehyde have primarily focused on cell survival. The study was designed to investigate the molecular mechanisms of endoplasmic reticulum stress (ER stress) and oxidative stress in astrocytes in A. cantonensis ESPs treated astrocytes and to evaluate the therapeutic consequent of 3-HBA and 4-HBA. First, we initially established the RNA-seq dataset in each group, including Normal, ESPs, ESPs+3-HBA, and ESPs+4-HBA. We also found that benzaldehyde (3-HBA and 4-HBA) can stimulate astrocytes to express ER stress-related molecules after ESP treatment. The level of oxidative stress could also be decreased in astrocytes by elevating antioxidant activity and reducing ROS generation. These results suggested that benzaldehyde may be a potential therapeutic compound for human angiostrongyliasis to support brain cell survival by inducing the expression levels of ER stress- and oxidative stress-related pathway.

High-power laser facilities necessitate predicting incremental damage to final optics to identify evolving damage trends. In this study, we propose a surface damage detection method utilizing image segmentation employing ResNet-18, and a damage area estimation network employing U-Net++. Paired sets of online and offline images of optics obtained from a large laser facility is used to train the network. The trends of varying damage could be identified by incorporating additional experimental parameters. A key advantage of the proposed method is that the network can be trained end-to-end on small samples, eliminating the need for manual labeling or feature extraction. The software developed based on these models can facilitate the daily inspection and maintenance of optics in large laser facilities.

Strata and surface movement induced by mining under open-pit final slope is a huge threat to mine safety. Physical model test is an important method to study mining-induced strata and surface movement laws. Because of rock joints predominantly control rock mass deformation and failure, thus physical model test leaving out of consideration of rock joints is difficult to reflect the influence of rock joints on rock mass deformation. Therefore, this paper presents a three-dimensional physical model test considering simplified dominant rock joints. This test process includes the design of testing equipment, the construction of physical model with dominant rock joint sets, conduction of mining and deformation monitoring. And mining under eastern final slope of Yanqianshan iron mine was selected as a case to study the behavior of mining-induced strata and surface movement.

Remote Photoplethysmography (rPPG) has emerged as a non-intrusive and promising physiological sensing capability in HCI research, gradually extending its applications in health-monitoring and clinical care contexts. With advanced machine learning models, recent datasets collected in real-world conditions have gradually enhanced the performance of rPPG methods in recovering heart-rate and heart-rate variability metrics. However, the signal quality of reference ground-truth PPG data in existing datasets is by and large neglected, while poor quality references negatively influence models. Here, this work introduces a new imaging blood volume pulse (iBVP) dataset of synchronized RGB and thermal infrared videos with PPG ground-truth signals from the ear and its high resolution signal quality labels, for the first time. Participants perform rhythmic breathing, head-movement, and stress-inducing tasks, which help reflect real-world variations in psycho-physiological states. This work conducts dense (per sample) signal quality assessment to discard noisy segments of ground-truth and corresponding video frames. We further present a novel end-to-end machine learning framework, iBVPNet that features an efficient and effective spatio-temporal feature aggregation for reliable estimation of BVP signals. Finally, this work examines the feasibility of extracting BVP signals from thermal video frames, which is underexplored. The iBVP dataset and source codes are publicly available for research use.

In this article, we prove an orthogonal decomposition theorem for real inner product gyrogroups, which unify some well-known gyrogroups in the literature: Einstein, M\"{o}bius, Proper Velocity, and Chen's gyrogroups. This leads to the study of left (right) coset partition of a real inner product gyrogroup induced from a subgyrogroup that is a finite-dimensional subspace. As a result, we obtain gyroprojectors onto the subgyrogroup and its orthogonal complement. We construct also quotient spaces and prove an associated isomorphism theorem. The left (right) cosets are characterized using gyrolines (cogyrolines) together with automorphisms of the subgyrogroup. With the algebraic structure of the decompositions, we study fiber bundles and sections inherited by the gyroprojectors. Finally, the general theory is exemplified for the aforementioned gyrogroups.

The fish supply chain (FSC) industry faces a significant challenge in terms of maintaining fish quality and authenticity throughout the chain. The main goal of modern FSC systems is tracking and tracing the fish product at each stage, from harvester to end customer, as well as assessing its quality and authenticity. Integrating FSC with new technologies, such as Blockchain (BC), Big Data, Artificial intelligence (AI), and Internet of Things (IoT), enhances fish product traceability, authenticity, visibility, and security. We propose a BC-based FSC framework that follows a layered architecture consisting of a SC layer, an IoT layer, and a BC layer. We integrate a new AI-based hand-held device, a Quality, Adulteration & Traceability (QAT) device, that can identify fish species and assess fish quality. We leverage the key features of BC and smart contracts, deployed over the Ethereum platform for the proposed framework integrated with QAT technology. Extensive validation of smart contracts is conducted to prove its practical feasibility.

The fourth industrial revolution, also known as Industry 4.0, has led to an increased transition towards automation and reliance on data-driven innovations and strategies. Companies in the manufacturing sector are heavily integrating Industry 4.0 technologies, including cloud compu-ting, cyber-physical systems (CPS), big data analytics, horizontal and vertical system integration, the internet of things (IoT), and additive manufacturing (3d printing). The interconnected systems and processes have significantly increased operational efficiency, enhanced organizational capacity to monitor and control functions, reduced costs, and improved product quality. One significant way that companies have achieved these benefits is by integrating diverse sensor technologies within these innovations, allowing critical data collection on products, equipment performance, and maintenance. The sensors connect systems and machines, allowing them to communicate and track operations for enhanced operations. While numerous research has been conducted to show the role of sensors in industry 4.0, limited studies show how these innovations can leverage product design to maximize benefits and opportunities. Given the rapidly changing market conditions, Industry 4.0 requires new products and business models to ensure companies adjust to the current and future changes. These requirements call for the evolutions in product design processes to accommodate design features and principles applicable in the current dynamic business environment. This research paper employs a systematic bibliometric literature review (LRSB) methodology to explore and synthesize data on how Industry 4.0 and sensors can leverage product design. The results show that various product design features create opportunities to be leveraged to guarantee the success of Industry 4.0 and sensor technologies. However, the research also identifies numerous challenges that undermine the ongoing transition towards intelligent factories and products.

To fulfil a need of limitation automotive emissions the reduction of vehicle weight is widely recommended and achieved in many ways, both by the construction of individual elements of the vehicle, and by the selection of light materials including Al alloys. Connecting these elements with each other and with elements made of iron alloys can be realized, inter alia, by welding or stir welding. However, the quality of the welds obtained varies widely and depends on many design, operational and environmental factors. The present study focused on a review of various welding technics used to joint both similar and dissimilar Al alloys utilized in automotive industry, the effect of various process parameters on welds quality, and phenomena appeared in such welds..

This qualitative research explores the dynamics of collaborative marketing and supply chain strategies for enhanced product lifecycle management. Through in-depth interviews with industry stakeholders, key themes, challenges, and implications of collaboration emerge. Trust, communication, technology, strategic alignment, and sustainability are identified as critical factors driving successful collaboration. The study highlights the transformative potential of collaboration in driving innovation, efficiency, and customer satisfaction. Despite challenges such as aligning objectives and ensuring data security, collaborative strategies offer significant opportunities for value creation and differentiation. The findings underscore the importance of building trust, leveraging technology, and integrating sustainability considerations in collaborative efforts. Strategic alignment and cultural fit among partners are essential for overcoming differences and achieving common goals. The implications of the research extend to practitioners seeking to enhance collaboration in their organizations and researchers exploring collaborative practices in different industries and contexts. Future research could further explore the impact of collaboration on stakeholder perspectives and outcomes. By addressing challenges and leveraging opportunities, organizations can maximize the benefits of collaborative marketing and supply chain strategies to drive sustainable growth and competitive advantage in today's dynamic business landscape.

Regular regimes of oil and oil products pipelines are studied. The problem is to develop an algorithm of effective pipeline system control that ensures the fulfillment of specified boundary conditions at the system boundaries. The product is pumped in batches, the flow is characterized by a change in temperature and pressure flow parameters over time. The developed solution method uses the principle of decomposition in the sense that each computational iteration is im-plemented in 3 stages, in three nested loops. The inner cycle is connected with the material bal-ance relations, at the next cycle the flow equations are introduced and the fulfillment of the 2nd Kirchhoff's law is monitored. If the flow process is significantly affected by temperature, then an external cycle is also implemented, correcting the solution so that the energy conservation equa-tion is satisfied. In the calculation procedure, some computational difficulties may arise, which consist in choosing an appropriate optimization method. On a specific example, the possibility of using various library programs to solve the problem was checked. The developed method is suita-ble for the analysis of systems of arbitrary topology. Since the method is not time-consuming, it can be recommended for online control of oil and oil products supply systems. The paper opens a new direction in the theory of hydraulic circuits. It uses both traditional methods of continuum mechanics and stochastic models.

The quality of healthcare services is a very important indicator of social welfare in developed and emerging countries. Good quality levels are critical to ensuring patient safety, improving health outcomes, increasing patient satisfaction, optimizing resource utilization, and meeting regulatory requirements. The stable and sustainable operation of medical institutions urgently requires the establishment of a reliable and effective medical quality performance evaluation platform. However, the complexity of the evaluation process, involving numerous evaluators and the consideration of different subjective and objective criteria, poses significant challenges and essentially constitutes a group multi-criteria decision-making problem. This article uses the overall medical environment of the institution, medical service attitude, medical security, administrative service measures, etc. as measurement standards to deal with this challenge. It proposes a medical service quality measurement model suitable for both qualitative and quantitative analysis. In view of the heterogeneity of information, the two-tuple fuzzy language calculation method is introduced to enable evaluators to skillfully manage diverse information and effectively avoid potential information omission problems in the subjective evaluation integration process. The effectiveness and feasibility of the model were demonstrated by applying it to the operational framework of a medical institution in central Taiwan.

To remain competitive in the current market, an enterprise must differentiate itself based on higher value propositions. For this purpose, since improving the product or service performance can reach some limits, one potential solution is to move towards new combinations of products and services. This evolution, called servitization, leads to the generation of Product-Service Systems (PSS). Servitization requires not only a clear understanding of enterprise core business but also a clear vision on the prevailing trends and challenges of PSS development from both business and technological points of view. In addition, the evolution path should be aligned with the enterprise strategy. This paper first highlights the notion of symbiotic PSS where Product Systems and Service Systems, and their stakeholders, interoperate seamlessly based on a win-win approach. Then it proposes a PSS Conceptual Framework (PSS-CF) which can be applied in the early stages of servitization to increase the understating of PSS dimensions and to facilitate the prioritization of the servitization investments. The framework dimensions were discussed in several iterations, from both academic and industrial points of view, in the frame of a European research project. Moreover, the applicability of the framework was studied in four different industrial Use-Cases.

Servitization or productization, indicating evolution from product to service economy or vice-versa, can be considered as a successful strategy to gain competitiveness based on novel combination of products and services. To decrease the risks of servitization and to support the sustainable development of its main outcome, being Product Service System (PSS), it is required not only to have a clear and common understanding of the core business and processes but also to share the same definitions on (PSS) concepts as the main outcome of servitization. For this purpose, managers could be supported by abstract models with a limited number and high ratio of known concepts in the early stages of PSS development. Through an extensive literature review on this subject, followed by a structured conceptualization approach and discussions with domain experts, this paper proposes a Conceptual Model (PSS-CM). To validate the results, PSS-CM and its elements were discussed in several iterations, from both academic and industrial points of view, in the frame of a European research project. In the frame of this project, a case study was also performed to illustrate the instantiation of PSS-CM.

The aim of this research work is to study the influence of temperature, solar irradiation and wind dust on the production of solar energy. In addition, it aims to study the assessment of water quality, in particular groundwater used for cooling and cleaning photovoltaic panels (quality analysis). it's an important source, stable and sustainable can be used entirely for cooling and cleaning PV modules from the sales dust, in order to improve their performance. To date, all research studies carried out in this context of cooling and cleaning using water have not taken account of the nature of this water. We have taken a sample of water from a well in a rural area in the Darra Tafilalet region of Morocco. This region has an arid and semi-arid climate, with very high temperatures and dust-laden winds, particularly in summer. These meteorological characteristics influence the efficiency of cells, particularly photovoltaic (PV) panels, reducing their performance. Next, the water sample was analysed in the laboratory. The results obtained show that the groundwater in this area is very sensitive to cooling and cleaning photovoltaic panels. Moreover, these results indicate that the temperature, solar irradiation and wind-blown dust have a significant influence on energy production.

We present a new method of estimating fitness of countries and complexity of products by exploiting a non-linear non-homogeneous map applied to the publicly available information on the goods exported by a country. The non homogeneous terms guarantee both convergence and stability. After a suitable rescaling of the relevant quantities, the non homogeneous terms are eventually set to zero so that this new method is parameter free. This new map reproduces the findings of the method proposed by Tacchella et al. [1], and allows for an approximate analytic solution in case of actual binarized matrices based on the Revealed Comparative Advantage (RCA) indicator. This solution is connected with a new quantity describing the neighborhood of nodes in bipartite graphs, representing in this work the relations between countries and exported products. Moreover, we define the new indicator of country net-efficiency quantifying how a country efficiently invests in capabilities able to generate innovative complex high quality products. Eventually, we demonstrate analytically the local convergence of the algorithm.