A superior variant of dried jujube in China is ‘Huizao’ (HZ) jujube. Nonetheless, detailed evaluations of the texture quality of HZ fruits have been the subject of few studies. Texture is a significant indicator of the sensory and processed quality of a fruit. Here, we differentiate and characterize the texture quality of HZ fruits from the four primary producing regions in southern Xinjiang, as well as develop a system for assessing the texture quality of HZ fruits. Furthermore, five texture indices of HZ fruits from 109 plantations were exhaustively evaluated utilizing principal component analysis, Pearson correlation analysis, and hierarchical clustering analysis. Consequently, by the 10th, 30th, 70th, and 90th percentiles, each index was classified into five grades—lower, medium, high, and higher. Correlation investigation indicated strong relationships between the springiness, chewiness, cohesiveness, gumminess, and hardness of HZ fruits. Springiness, hardness, and adhesiveness are essential indicators that influence the texture of HZ fruits. We used clustering analysis to separate the six texture indices into three major categories (hard factor, stick-elastic factor, and adhesive factor), with indices representing hardness, springiness, and adhesiveness, respectively. Furthermore, according to the factor molecules, the texture quality of HZ fruits in the four production areas was evaluated as Bazhou (1.24) > Hotan (0.773) > Kashi (-0.577) > Aksu (-0.852). RDA analysis of six texture quality parameters and 24 climate conditions identified higher mean temperature (TEM) and lower relative humidity (RHU) as the primary factors contributing to the improved texture quality of HZ fruits in Xinjiang. This study identified the texture quality characteristics of HZ fruits in four major producing areas of Southern Xinjiang, and it offered a theoretical foundation for optimizing the dominant producing areas and regional production of HZ varieties in Xinjiang.

Many types of banana (Musa spp.)—one of the most economically important horticultural crops—exist, and their ploidy (diploid, triploid, and tetraploid, usually) and genome types (containing A or/and B genome in most cases) differ. At present, observation and genome type detection are commonly used to identify banana germplasm resources. However, the former is tedious, while the latter cannot distinguish categories below genome types. It is therefore urgent that a simple and effective method for identifying banana germplasm resources is established. We sequenced and analyzed the ribosomal DNA internal transcribed spacer (ITS) sequences of 62 banana germplasm and found that the sequencing peaks, especially the 20 bp region near the 420 bp position (referred to as the “420 bp region”), exhibited relatively recognizable and repeatable polymorphism characteristics. Using the “420 bp region” as a marker, we were able to quickly distinguish bananas belonging to different genome type groups (comprising the AA, AB, AAA, ABB, AAB, ABBB, AAAB, and AAAA groups) or different subgroups in the same genome type group (for example, the Cavendish, Gros Michel, Red, Lakatan, and Ibota Bota subgroups in the AAA group; and the Pisang Raja, Plantain, Pome and Silk subgroups in the AAB group). Moreover, it appeared that Sanger sequencing of ITS could be used for identifying banana hybrid offspring. These results demonstrated that the banana ITS region contains rich genetic information that is useful for genotyping. In general, ITS sequencing simplifies the classification of banana germplasm resources and has potential application in several areas of Musa improvement.

Hazelnuts are one of the most valuable nuts in the world due to their unique organoleptic properties and nutritional characteristics. This work was intended to analyze some physical and chemical properties of various hazelnut cultivars grown in Zakataly (Azerbaijan), namely Ata-baba, Elbari, Topqara, Firovan, Nasimi, Qalib, Mirzebeyli, Tala, Dash findiq, Barli, Azeri and Sachaqli. In general, the results showed statistically significant differences between the studied cultivars. The density of kernels, depending on the hazelnut cultivars, varied from 0.71 g/cm³ (Azeri) up to 1. 03 g/sm³ (Sachaqli). The peeled fruits of Dash findiq were heavier on average (1.64±0.34 g), and the peeled fruits of Nasimi, Qalib, Mirzebeyli and Sachaqli were lighter on average (0.8±0.23 g, 0.8±0.31 g, 0.8±0.20 g and 0.80±0.09 g, respectively. In the unpeeled form, Dash findiq nuts were the heaviest (3.70±0.34 g), and Nasimi and Qalib nuts were the lightest of all cultivars (2.0 ±0.48 g and 2.0 ±0.36 g, respectively). Ata-baba nuts account for 49 masses per kernel. %, in other studied cultivars - 33.3- 45.3 wt. %. Nasimi nuts are rounded (in the equatorial zone); Tala, Ata-baba, Firovan and Azeri - rounded-oblong; Topqara, Barli and Dash findiq – oblong; Elbari, Qalib, Mirzebeyli and Sachaqli - elongated. Firovan, Tala and Topqara have thicker shells. Ata-baba is significantly ahead of other varieties in the yield of kernels (490 kg / 1 ton of nuts), Tala is in second place in this indicator (453 kg / 1 ton of nuts), Topqara is in third (433 kg/ 1 ton of nuts). According to the maximum fat content, the cultivars Mirzebeyli (77.00±2.20 g/100 g of kernels) and Firovan (75.0±3.08 u/100 kernels), protein - Sachaqli (16.02±0.50 u/100 kernels) and Ata-baba (15.92±0.48 g/100 g of kernels) were distinguished. The results of this study help to better understand the differences between some varieties of hazelnuts grown in Azerbaijan, which provides important clues for all players involved in this sector.

Improperly prepared fresh fruit and vegetable juices are recognized as an emerging cause of food borne illnesses. Therefore, this study was aimed at evaluating the microbiological safety of fresh fruit juices marketed in Debre-Markos town and their hygienic conditions of preparations. Thirty six fruit juices samples were collected from 6 cafés and restaurants of Debre-Markos town and analyzed for total aerobic viable bacterial count (TAVBC), total staphylococcal count (TSC), aerobic spore forming bacterial count (ASFBC), total coliform count (TCC), fecal coliform count (FCC), yeast and mould count (YMC). The spread plate method was used for the isolation of microorganisms on appropriate selective media. All isolates were characterized following standard methods. Bacterial and fungal species were isolated following standard methods. Questionnaires were distributed for 30 juice makers to obtain preliminary information on hygienic and safety practices of fruit juice makers. Results show that the mean TAVBC, ASFBC, TSC, yeast and mold, TCC and FCC of mango were 2.2±0.48x10⁶,0.13±0.04x10⁵ ,0.004x10⁵ ,1.1±0.2x10⁶ ,0.15±0.05x10⁵,5.7±3.73x10⁴ and 0.06±0.04x10⁴ cfu/ml respectively. The mean of TAVBC, ASFBC, TSC, YMC, TCC, and FCC of avocado juice were 3.6±0.6x10⁶, 0.08±0.02x10⁵, 0.27±0.07x10⁵, 1.2±0.4x10⁶, 0.02±0.01x10⁵, 6.46±3.7x10^4, and 0.2±0.1x10⁴ cfu/ml respectively. The bacterial isolates were identified as Staphylococcus aureus, Escherichia coli, Klebsiella spp. Bacillus cereus, Enterobacter spp., Enterococcous spp., Streptococcus spp., and Serratia spp. while the identities of the fungal isolates were Fusarium spp., Mucor spp. and Saccharomyces cerevisiae. The results also showed that the microbial loads of most of the fruit juices were higher than the specifications set for fruit juices sold in the Gulf region and other parts of the world. Most venders obtained fruit from the open market and all juice makers lacked special training in food hygiene and safety. Therefore, regular training and health education on food hygiene and safety is recommended for juice handlers to improve the quality of fresh fruit juices in the study area.

In the case of a Cu-Mo-W polymetallic ore, the wastewater from the scheelite cleaning flowsheet contains large amounts of residual flocculants and metal ions, and the separation of chalcopyrite and molybdenite require a large number of environmentally harmful depressants. Therefore, it is necessary to find new methods to reduce the environmental and cost pressures of wastewater treatment and the use of depressants. In this work, the flotation wastewater from scheelite cleaning flowsheet for the separation of chalcopyrite and molybdenite by selective surface passivation was investigated for the first time. Flotations of single minerals and artificially mixed minerals with or without immersion pretreatment in the presence and absence of aeration were performed. The results showed that pulp pH had no effect on the flotation of either mineral, and a molybdenite recovery of 93.22% with chalcopyrite recovery of 10.77% was achieved under the conditions of 10 days of immersion pretreatment with aeration, 350 mg/L of kerosene, and 100 mg/L of MIBC. By combining the electrochemical cyclic voltammetry analysis and characterization by XRD and SEM, the selective surface passivation mechanism of chalcopyrite was discussed, which could be due to the coverage of the insoluble oxidation products, especially jarosite. This work has simultaneously achieved the depressant-free flotation separation of molybdenite and chalcopyrite and the reuse of scheelite flotation wastewater, which is of great significance for environmental protection and cost saving.

In Germany, the phloem sucking planthopper Pentastiridius leporinus (Hemiptera: Cixiidae) currently represents the epidemiological driver for the spread of the syndrome “Basses Richesses” in sugar beet, which results in a reduced sugar content and an economic loss for the farmers. This disease is associated with the γ-proteobacterium ‘Candidatus Arsenophonus phytopathogenicus’ and the Stolbur phytoplasma ‘Candidatus Phytoplasma solani’. Recently, P. leporinus was found in potato fields in Germany associated with Stolbur-like symptoms in this crop. In this study, we confirmed that the vector completes its lifecycle on sugar beet as well as on potato when reared under controlled conditions. Transmission experiments with adults of this vector combined with molecular analyses showed for the first time that both pathogens are transmitted by this vector to potato. For an accurate assessment of the Ca. P. solani and Ca. A. phytopathogenicus titers in the vector and host plants, gBlocks derived from the hsp20- and 16S rRNA gene were employed, respectively. For Ca. P. solani the limit of detection was determined in potato and sugar beet material. The results of this study will further research on the epidemiology of the syndrome “Basses Richesses” and “Stolbur” diseases and the response of host plants and vector insects to both pathogens.

In order to understand the defense response of Sanchezia nobilis to biotic and abiotic stresses, this study investigated the phenomenon of S. nobilis under biotic of feeding by Achatina fulica, and measured the temporal changes of malondialdehyde content, catalase and peroxidase activities under biotic of feeding by Achatina fulica and abiotic stress of garden pruning conditions on S. nobilis. The results showed that: 1) S. nobilis was seriously damaged by A. fulica and the average hourly food intake of A. fulica is 0.22 ± 0.01 g. 2) Leaf cutting stimulation and snail feeding stress significantly affected the content of malondialdehyde, the activities of catalase and peroxidase in the leaves of S. nobilis. 3) Compared with the control group, the snail feeding and leaf cutting stimulated stress could induce the leaf of S. nobilis to synthesize more malondialdehyde under varying durations, and the activities of catalase and peroxidase were significantly enhanced in a short time, and the induction response of snail feeding biological stress was faster than that of leaf cutting stimulated abiotic stress. 4) After the defense enzyme was strengthened, the activities of catalase and peroxidase in the feeding stress group of snails showed a gradual downward trend, while the activities of catalase and peroxidase in the leaf cutting stimulation stress group showed a first upward and then downward trend, indicating that abiotic stress had more lasting effects on plants than biological stress. It can be seen that biotic stress and abiotic stress significantly affect the defense response of plants, and the defense-related substances malondialdehyde, catalase and peroxidase play an important role in plants' response to biotic and abiotic stress. This study has important production guidance significance for carrying out stress resistance breeding or cultivation management of garden plants.

The global warming has caused poor grape skin coloration and reduced the production of high-quality berries. To overcome these problems, the effect of synephrine (Syn) on anthocyanin accumulation was investigated. Syn treatment above 1 mM increased anthocyanin content in cultured grape cells in a molecular-structure-specific and concentration-dependent manner, and increased only the anthocyanin without affecting the sugar/acid ratio in grape bunches. It increased the expression of genes linked to anthocyanin synthesis after 24 h of treatment, without affecting phytohormone levels. Syn treatment induced the expression of SOD3, elevating hydrogen peroxide (H2O2) production from 3 to 24 h after treatment in cultured cells. Subsequent increases in CAT and APX6 expression occurred, which encode H2O2-eliminating enzymes. In cultured grape cells, Syn and H2O2 treatments upregulated the H2O2-responsive gene Chit4 and the anthocyanin-biosynthesis-related genes mybA1 and UFGT 4 days after the treatments and promoted anthocyanin accumulation 7 days after the treatments. In berries, both treatments enhanced anthocyanin accumulation after 9 days. These results suggest that Syn promotes anthocyanin accumulation through the production of H2O2 without the upregulation of phytohormone biosynthesis. Syn treatment is expected to improve poor grape coloration and contribute to higher-quality fruit production.

The state-of-the-art smart city has been calling for an economic but efficient energy management over large-scale network, especially for the electric power system. It is a critical issue to monitor, analyze and control electric loads of all users in system. In this paper, we employ the popular computer vision techniques of AI to design a non-intrusive load monitoring method for smart electric energy management. First of all, we utilize both signal transforms (including wavelet transform and discrete Fourier transform) and Gramian Angular Field (GAF) methods to map one-dimensional current signals onto two-dimensional color feature images. Second, we propose to recognize all electric loads from color feature images using a deep neural network with multi-scale feature extraction and attention mechanism. Third, we design our method as a cloud-based, non-intrusive monitoring of all users, thereby saving energy cost during electric power system control. Experimental results on both public and our private datasets have demonstrated our method achieves superior performances than its peers, and thus supports efficient energy management over large-scale Internet of Things.

Salt stress is a major limiting factor for alfalfa yield due to its relatively low salt tolerance. High soil salinity adversely impacts alfalfa growth and development, leading to reduced yield. Melatonin (MT) is known to play a significant role in enhancing plant resistance to abiotic stresses. However, the mechanisms underlying melatonin-mediated abiotic stress responses, particularly salt stress, are not well understood. To address this gap, we conducted a study focusing on germinating alfalfa seeds under salt stress. Physiological indexes and transcriptomics analyses were carried out on the germinated seeds to investigate the effects of melatonin on alfalfa seedlings under salt stress conditions. Our results revealed that the application of melatonin led to an increase in shoot length and fresh weight of alfalfa seedlings under salt stress. Moreover, key physiological indexes such as peroxidase (POD) activity and glutathione (GSH) content were enhanced, while levels of malondialdehyde and superoxide anions decreased. Transcriptomic analysis identified a total of 2,131 differentially expressed genes in the salt-treated group, with 726 up-regulated and 1,405 down-regulated genes, while the MT-treated group showed 2896 differentially expressed genes, of which 1,097 were up-regulated and 1,799 were down-regulated. Further, KEGG enrichment analysis highlighted the enrichment of differentially expressed genes in pathways including flavonoid biosynthesis, ABC transporter, glutathione metabolism, and the MAPK signaling pathway, with these pathways more significantly enriched in the MT-treated group. These findings collectively suggest that melatonin plays a crucial role in alfalfa's response to salt stress and offer new insights into the genomic mechanisms underlying melatonin-mediated salt tolerance in alfalfa.

Fabric phase sorptive extraction, an innovative integration of solid phase extraction and solid phase microextraction principles, has been combined with gas chromatography-mass spectrometry for the rapid extraction and determination of nineteen organochlorine pesticides in various fruit juices and water samples. FPSE consolidates the advanced features of sol-gel derived extraction sorbents with the rich surface chemistry of cellulose fabric substrate, which could directly extract target analytes from complex sample matrices and substantially simplifies the sample preparation operation. Important FPSE parameters including sorbent chemistry, extraction time, stirring speed, type and volume of back-extraction solvent and back-extraction time have been optimized. Calibration curves were obtained in the concentration range 0.1-500 ng/mL. Under the optimum conditions, the limits of detection were obtained in the range 0.007-0.032 ng/mL with satisfactory precision (RSD<6%). The relative recoveries obtained by spiking organochlorine pesticides in water and selected juice samples were in the range of 91.56–99.83%. The sorbent sol-gel poly(ethylene glycol)-poly(propylene glycol)-poly(ethylene glycol) was applied for the extraction and preconcentration of organochlorine pesticides in aqueous and fruit juice samples prior to analysis with gas chromatography-mass spectrometry. The results demonstrated that the present method is simple, rapid, and precise for the determination of organochlorine pesticides in aqueous samples.

Salt stress is one of the major abiotic stresses that lead to crop yield reduction worldwide. Melatonin (MT), an endogenous hormone synthesized in plants, plays an important role in responding to abiotic stimuli such as drought, salinity, heat, cold, etc. However, the molecular mechanisms of MT-mediated abiotic stresses remain to be better understood. In order to explore the key genes and pathways of melatonin in alleviating salt stress, physiological and biochemical indicators as well as transcriptomics profile were conducted in alfalfa seedlings. The results showed that the germination rate, bud length and fresh weight of alfalfa seedlings added with melatonin were higher than those treated with salt alone. In addition, Malondialdehyde (MDA) and Superoxide anion (O2-) contents also displayed a decreasing trend. The activity and content of Superoxide dismutase (SOD)、peroxidase (POD) and Glutathione (GSH) increased to varying degrees. In order to further reveal the molecular mechanism of MT-mediated salt tolerance of alfalfa, transcriptome analysis was performed on alfalfa seedlings. 2,181 differentially expressed genes (DEGs) were obtained in the salt-treated group, including 780 upregulated genes and 1,401 down-regulated genes, while 4,422 DEGs were obtained in the MT group, among which 1,438 were upregulated and 2,984 were downregulated. By using GO functional annotation and KEGG pathway enrichment, we found that DEGs were mainly enriched in the biosynthesis of flavonoids, isoflavones, plant hormones, Glutathione (GSH), soluble sugars and other substances, as well as in the ABC transporter and MAPK signaling pathways. Among them, the DEGs in the MT group was more enriched in these pathways, suggesting that MT can combat salt stress by regulating the expression of genes related to phytohormone and antioxidant capacity, which has important reference value for the breeding of salt-tolerant alfalfa and other crops.

Citrus species essential oils (EOs) are significant sources of bioactive compounds and demonstrate diverse therapeutic effects. However, limited documentation exists regarding the phytochemicals associated with their biological activities. This study aims to assess the antioxidant activity, plant inhibitory properties, and brine shrimp cytotoxic effects of EOs derived from three Citrus species: C. sinensis, C. limon, and C. hystrix. Utilizing chemometric analysis and gas chromatography-mass spectrometry (GC-MS) fingerprints, the volatile components contributing to antioxidant activity were elucidated. The peels of the Citrus samples were hydro-distillated to obtain EOs, and subsequently subjected to antioxidant, plant inhibitory, and brine shrimp cytotoxic assays. The results indicated that C. limon EO exhibited the highest antioxidant activity, while C. hystrix and C. sinensis EOs demonstrated pronounced inhibitory effects against Aetrmia salina and Lactuca sativa, respectively. GC-MS analysis facilitated the identification of key compounds in each EO. Principal component analysis (PCA) and hierarchy cluster analysis (HCA) effectively categorized Citrus EOs based on their antioxidant properties, highlighting the proximity of C. limon and C. sinensis. Among the identified compounds, D-limonene, α-Terpineol, Caryophyllene, (+)-3-Carene, β-Pinene, (-)-Spathulenol, trans-p-Mentha-1(7),8-dien-2-ol, and trans-Verbenol were the most discriminating compounds affected the antioxidant activity of C.limon and C. sinensis EOs.

In this study, we successfully synthesized a novel branched polyamide 6 with ε-caprolactam(CPL) and α-Amino-ε-caprolactam(ACL) through hydrolytic ring-open co-polymerization. The NMR characterization and rheological test result proved the existence of branched chain structure additionally. The branched chain structure caused a remarkable enhancement in the rheological properties. The met index(MFR),zero shear rate viscosity and storage modulus at low frequency region had a remarkable increase.The shear thinning phenomenon became more obvious. The thermal properties test determined by differential scanning calorimetry(DSC) showed that the melting point and crystallinity of co-polymers decreased with the increase of ACL addition.However, the crystal structure of the samples remained unchanged. The appropriate addition amount of ACL can improve the tensile mechanical properties of the co-polymers. When the amount of ACL was 1%, the tensile strength and fracture elongation rate of the co-polymers had the most significant increase.

A total of 473 metabolites were identified from 4 sour cherry genotypes using UPLC-TOF-MS. Untargeted metabolomics revealed the dominant chemical groups present in sour cherries. PCA showed that the diversity in sour-cherry metabolites was due to the genotype differences indicating iditol, malic acid, chlorobenzene, 2-mercaptobenzothiazole, and pyroglutamic acid as the predominant contributors. The variable importance in the projection (VIP &gt; 1.0) in partial least-squares–discriminant analysis described 20 biomarker metabolites, representing the cherry metabolome profiles. A heatmap of Pearson’s correlation analysis between the 20 biomarker metabolites and antioxidant activities identified seven antioxidant determinants that displayed the highest correlations with different types of antioxidant activities. This study of correlating metabolomics and antioxidant activities elucidated that the higher nutritional value and biological functions of select sour cherry genotypes can be useful for the development of nutraceutical and functional foods.

A low-cost bio-mass-derived carbon substrate has been employed to synthesize MoS₂@carbon composites through a hydrothermal method. Carbon fibers derived from natural cotton provide a three-dimensional and open framework for the uniform growth of MoS₂ nanosheets, thus constructing hierarchically coaxial architecture. The unique structure could synergistically benefit fast Li-ion and electron transport from the conductive carbon scaffold and porous MoS₂ nanostructures. As a result, the MoS₂@carbon composites, when served as anodes for Li-ion batteries, exhibit a high reversible specific capacity of 820 mAh g^-1, high-rate capability (457 mAh g^-1 at 2 A g^-1), and excellent cycling stability. The superior electrochemical performance makes the MoS₂@carbon composites to be low-cost and promising anode materials for Li-ion batteries.

Sea cucumber peptides are small molecular peptides with biological function obtained from fresh sea cucumber as feedstock, which were hydrolyzed by protease, separated ,and purified. As the main product of sea cucumber refinement, it more accurately expresses the nutritional effect of sea cucumber and has a wide range of potential applications. It has been demonstrated that sea cucumber has a certain value-added effect on bone mineral density regulation, but the differences in bone mineral density regulation of extracts from different parts of sea cucumber and the techniques contributing to the efficient isolation of bone sea cucumber peptides have not been reported. Firstly, the aim of this study was to reveal the differences in osteogenic activities of enzymatic peptides from three major parts of sea cucumber: the body wall, the egg protein, and the intestinal protein. Then, the bone-enhancing sea cucumber peptides were isolated based on the characteristics of the dif-ferences in molecular weight distribution, hydrophilicity, and ionisation degree of sea cucumber, and to explore the possible mechanisms of their action. The findings indicated that sea cucumber peptides extracted from three distinct sites exhibited a dose-dependent enhancement of osteoblast proliferation and differentiation. Upon evaluating the three methods of sea cucumber peptide separation based on molecular weight distribution, hydrophilicity, and ionization, it was observed that the fraction isolated by hydrophobicity and

MIMO (multiple-input multiple-output) radar provides much more flexibility than the traditional radar for its ability to realize far more observation channels than the actual number of T/R (transmit and receive) elements. Designing the array of MIMO imaging radar, the commonly used virtual array theory generally assumes that all elements are placed on the same line. However, due to the physical size of the antennas and coupling effect between T/R elements, a certain height difference between T/R arrays is essential, resulting in the defocusing of edge points of the scene. On the other hand, the virtual array theory implies far-field approximation, leading to inevitable high grating lobes in the imaging result of near-field edge points of the scene observed by common MIMO array. To tackle these problems, this paper derives the relationship between target’s PSF (point spread function) and pattern of T/R arrays, by which the design criterion of near-field imaging MIMO array is presented. Firstly, the proper height between T/R arrays is designed to focus the near-field edge points well. Secondly, the far-field array is modified to suppress the grating lobes in the near-field area. Finally, the validity of the proposed methods is verified by simulations and an experiment.

Three-dimensional V₂O₅ hollow structures have been prepared through a simple synthesis strategy combining solvothermal treatment and a subsequent thermal annealing. The V₂O₅ materials are composed of microspheres 2–3 μm in diameter and with a distinct hollow interior. The as-synthesized V₂O₅ hollow microspheres, when evaluated as a cathode material for lithium-ion batteries, can deliver a specific capacity as high as 273 mAh·g⁻¹ at 0.2 C. Benefiting from the hollow structures that afford fast electrolyte transport and volume accommodation, the V₂O₅ cathode also exhibits a superior rate capability and excellent cycling stability. The good Li-ion storage performance demonstrates the great potential of this unique V₂O₅ hollow material as a high-performance cathode for lithium-ion batteries.

Proteomics research has become one of the most important topics in the fields of life science and natural science. At present, research on protein–protein interaction networks (PPINs) mainly focuses on detecting protein complexes or function modules. However, existing approaches are either ineffective or incomplete. In this paper, we investigate function module detection mechanisms in PPIN, including open databases, existing detection algorithms and recent solutions. After that, we describe the proposed solution based on simplified swarm optimization (SSO) algorithm and gene ontology knowledge. The proposed solution implements SSO algorithm for clustering proteins with similar function, and imports biological gene ontology knowledge for further identifying function complexes and improving detection accuracy. Furthermore, we use four different categories of species dataset for experiment: Fruitfly, Mouse, Scere, and Human. The testing and analysis result show that the proposed solution is feasible, efficient and could achieve a higher accuracy of prediction than existing approaches.

Accurate power curve modelling is essential to continuously evaluate the performance of a wind turbine (WT). In this work, we characterize the wind power curves using SCADA data acquired at a frequency of 5 minutes in a wind farm (WF) consisting of 5 WTs. Regarding the non-parametric methods, we select artificial neural networks (ANNs) to make curve estimations. Given that, we have the curves provided by the manufacturer of the WTs given by some very precisely measured pair of wind speed and power points. We can evaluate the difference between the manufacturer characterization and the ones estimated with the data provided by the SCADA system. Before the estimation, we propose a method of filtering the anomalies based on the characteristics provided by the manufacturer. We use three-quarters of the available data for curve estimation and one-quarter for the test. One WT suffered a break in the test part, so we can check how the test estimates reflect this problem in its wind-power curve compared to the estimations obtained in the WTs that worked adequately.

Molecular markers, including Simple Sequence Repeat (SSR), Single Nucleotide Polymorphism (SNP), and Intron Length Polymorphism (ILP), are widely utilized in crop improvement and population genetics studies. However, these marker resources remain insufficient for Musa species. In this study, we developed genome-wide SSR, SNP, and ILP markers from Musa and its sister species, creating a comprehensive molecular marker repository for the improvement of Musa species. This database contains 2115474 SSR, 63588 SNP, and 91547 ILP markers developed from thirteen Musa species and two of its relative species. We found that 77% of the SSR loci are suitable for marker development; 38% of SNP markers originated from the genic region, and transition mutations (C↔T; A↔G) were more frequent than transversion. The database is freely accessible and follows a ‘three-tier architecture,’ organizing marker information in MySQL tables. It has a user-friendly interface, written in JavaScript, PHP, and HTML code. Users can employ flexible search parameters, including marker location in the chromosome, transferability, polymorphism, and functional annotation, among others. These distinctive features distinguish the Musa Marker Database (MMdb) from existing marker databases by offering a novel approach that is tailored to the precise needs of the Musa research community. Despite being an in silico method, searching for markers based on various attributes holds promise for Musa research. These markers serve various purposes, including germplasm characterization, gene discovery, population structure analysis, and QTL mapping.

The objective of this research was to study the drying kinetics of passion fruit seeds, which are a byproduct of the industrial processing of passion fruit, with the potential to produce byproducts such as oil and flour. After drying, the seeds were directed for cold-press oil extraction, and the quantification of fatty acids was performed. Following the oil extraction, the residues underwent a grinding process to produce flour, which was characterized in terms of its nutritional aspects. The drying process was conducted using an experimental forced convection dryer with controlled temperatures of 40, 50, 60, and 70 °C, and a drying air velocity of 1.5 m s-1. This work introduced a novel approach using mathematical models, all derived from Fick's equation. For each model, the activation energy and thermodynamic properties related to the drying procedure were determined. Fatty acids in the oils and physicochemical characteristics of the defatted residue's flour were also analyzed. The Cavalcanti Mata, Henderson &amp; Pabis, and Page models modified by Cavalcanti Mata were found to best fit the experimental data. The highest proportions of unsaturated fatty acids in passion fruit oil were linoleic acid (Omega-6) at 68.8% and oleic acid (Omega-9) at 16.1%. The predominant saturated fatty acid was palmitic acid at 10.61%, with no significant differences observed in relation to the drying temperatures. It can be concluded that the composition of the flour from the residue of passion fruit grain oil extraction varies in terms of crude fiber content, ranging from 56.36% to 58.8%, and protein content, ranging from 15.6% to 18.26%, with significant differences observed concerning the drying temperatures. The lipid content varied from 13.5% to 13.76%, with no significant differences observed across the evaluated drying temperature variations.

A convenient and efficient strategy for the preparation of 2-sulfonylindoles has been achieved through iodophor/H2O2-mediated 2-sulfonylation of indoles with readily available sulfonyl hydrazides in aqueous phase. Iodophor is commercially available and serves as the green catalyst and aqueous phase. A series of 2-sulfonylated products from indoles and N-methylpyrrole were synthesized in moderate yields in only 10 min. Control experiments were also conducted to reveal the mechanism. This method is environment friendly, easy to operate and suitable for a wide range of substrates.

In order to correct attenuated millimeter-wavelength (Ka-band) radar data and address the problem of instability, an attenuation correction methodology (attenuation correction with variation trend constraint; VTC) was developed. Using synchronous observation conditions and multi-band radars, the VTC method adopts the variation trends of reflectivity in X-band radar data captured with wavelet transform as a constraint to adjust reflectivity factors of millimeter-wavelength radar. The correction was evaluated by comparing reflectivities obtained by millimeter-wavelength cloud radar and X-band weather radar. Experiments showed that attenuation was a major contributory factor in the different reflectivities of the two radars when relatively intense echoes exist, and the attenuation correction developed in this study significantly improved data quality for millimeter-wavelength radar. Reflectivity differences between the two radars were reduced and reflectivity correlations were enhanced. Errors caused by attenuation were eliminated, while variation details in the reflectivity factors were retained. The VTC method is superior to the bin-by-bin method in terms of correction amplitude and can be used for attenuation correction of shorter wavelength radar assisted by longer wavelength radar data.

Green manure could improve soil nutrients and crop production, playing a significant role in sustainable agriculture. However, the impacts of green manure on crop health and the roles soil microbial communities play in the process haven’t been clarified clearly yet. In this study, we investigated soil microbial community composition and structure in four tobacco farmlands, which were treated with different green manure (control, ryegrass, pea and rape), using 16S rRNA gene amplicons sequencing. Results showed that green manure had significant impacts on soil properties, microbial communities and tobacco health. First, soil total C, N and Ca content increased significantly in groups treated with green manure than control. Second, soil community diversity was significantly higher in groups treated with green manure. Third, green manure especially ryegrass, decreased tobacco disease (bacterial wilt) rate dramatically, and the process might be mediated by soil microbial communities. On the one hand, several microbial populations were found to be potentially disease inducible or suppressive. For example, the abundances of Dokdonella and Rhodanobacter were positively correlated to tobacco disease rate, while Acidobacteira_Gp4 and Gp6 had negative correlations with tobacco disease. On the other hand, soil microbial communities were shaped by soil properties (e.g., pH, C and N content). In conclusion, our research showed that green manure could increase soil nutrients directly, and further improve tobacco health mediated by soil microorganisms, which may shed light on revealing interactions among soil properties, microorganisms and plants.

The Fruit Harvest Helper, a mobile application developed by Northwest Nazarene University’s (NNU) Robotics Vision Lab, aims to assist farmers in estimating fruit yield for apple orchards. Currently, farmers manually estimate the fruit yield for an orchard, which is a laborious task. Fruit Harvest Helper seeks to simplify their process. While prior research efforts at NNU concentrated on developing an iOS app for blossom detection, this current research aims to adapt that smart farming application for apple detection across multiple platforms, iOS and Android. The old and new applications were designed with an intuitive user interface that is easy for farmers to use, allowing for quick image selection and processing. Unlike before, the adapted app utilizes a color ratio-based image segmentation algorithm implemented in OpenCV C++ to detect apples in apple tree images selected for processing. The results of testing the algorithm with a dataset of images indicate an 8.52% Mean Absolute Percentage Error (MAPE) and a Pearson correlation coefficient of 0.6 between detected and actual apples on the trees. These findings were obtained by evaluating the images from both the east and west sides of the trees, which was the best method to reduce the error of this algorithm. Although the Fruit Harvest Helper shows promise, there are many opportunities for improvement. These opportunities include exploring alternative machine-learning approaches for apple detection, conducting real-world testing without any human assistance, and expanding the app to detect various types of fruit. The Fruit Harvest Helper mobile application is among the many mobile applications contributing to precision agriculture, nearing readiness for farmers to use in yield monitoring and farm management.

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

Polymeric Intraocular lenses (IOLs) are vital for restoring vision following cataract surgery and for correcting refractive errors. Despite technological and medical advancements, challenges persist in achieving optimal vision and preventing complications. Surface modifications aim to mitigate the risk of posterior capsule opacification (PCO), while pre-operative measurements aid in selecting suitable IOLs. However, individualized solutions are lacking and there is a clear demand for the development of fully customised IOL surfaces. We employ laser micromachining technology for precise modifications via ablation on PMMA and Acrylic IOLs, using femtosecond (fs), nanosecond (ns), and diode continuous wave (CW) lasers, at wavelengths ranging from near-ultraviolet to infrared. Characterization reveals controlled ablation patterning, achieving feature sizes from as small as 400 nm to several micrometers. Regular and confocal Micro-Raman spectroscopy revealed alterations of the IOL materials' structural integrity for some pattering cases, thus affecting the optical properties, while these can be minimised by proper selection of micromachining conditions. The results suggest the feasibility of accurate IOL patterning, which could offer personalized vision correction solutions, based on relevant corneal wavefront data, thus surpassing standard lenses, marking a significant advancement in cataract surgery outcomes.

Vibrio parahaemolyticus is an important foodborne bacterium that causes severe gastroenteritis following the consumption of contaminated seafood. To identify V. parahaemolyticus and determine its pathogenicity, the U.S. Food and Drug Administration (FDA)’s Bacteriological Analytical Manual (BAM) recommends a multiplex polymerase chain reaction (PCR) protocol to simultaneously detect the species-specific thermolabile hemolysin (tlh) gene and the pathogenic thermostable-related hemolysin (trh) and thermostable-direct hemolysin (tdh) genes. However, this assay has shown two limitations: difficulty in separating the amplicons of the trh (486 bp) and tlh (450 bp) genes due to their similar sizes, and the weaker band exhibited by the tdh gene amplicon (270 bp). The present study aimed to improve the BAM’s multiplex PCR assay by separating the three amplicons with similar intensity. A new primer set was applied for the tlh gene (369 bp) alongside the existing primers for the trh and tdh genes. The amplicons for the three genes were effectively separated by electrophoresis on a 2% tris-borate-EDTA (TBE) agarose gel within 45 minutes. Primer concentrations of 0.2 µM for trh, 0.2 µM for tlh, and 0.4 µM for tdh produced a significant amount of amplicons among various combinations of primer concentrations with 35 PCR cycles (P &lt; 0.05). This assay exhibited a detection limit of 10 pg of bacterial DNA, demonstrating its high sensitivity. It did not display amplicons from nine Vibrio strains known to be human pathogens or from 18 well-documented foodborne pathogens. Therefore, the present multiplex PCR protocol could help overcome the limitations of existing assays and provide a more reliable method for detecting the three genes of V. parahaemolyticus.

Adult neurogenesis involves generation of functional neurons from neural progenitor cells, which have the potential to complement and restore damaged neurons and neural circuits. Therefore, the development of drugs that stimulate neurogenesis represents a promising strategy in stem cell therapy and neural regeneration, greatly facilitating the reconstruction of neural circuits in cases of neurodegeneration and brain injury. Our study reveals that compound A5, previously designed and synthesized by our team, exhibits remarkable neuritogenic activities, effectively inducing neurogenesis in neural stem/progenitor cells (NSPCs). Subsequently, transcriptome analysis using high-throughput Illumina RNA-seq technology was performed to further elucidate the underlying molecular mechanisms by which compound A5 promotes neurogenesis. Notably, comparative transcriptome analysis showed that the up-regulated genes were mainly associated with neurogenesis and the down-regulated genes were mainly concerned with cell cycle progression. Furthermore, we confirmed that compound A5 significantly affected the expression of transcription factors related to neurogenesis and cell cycle regulatory proteins. Collectively, these findings identify a new compound with neurogenic activity and may provide insights into drug discovery for neural repair and regeneration.

Recently, the popularity of fermented foods has increased significantly. Lactofermented vegetable juice products are particularly important for our diet. The combination of the richness of the ingredients derived from vegetable juices and the products formed during lactic fermentation is a valuable source of nutrients. This study aimed to analyse the selected properties of fermented beetroot, carrot, and beetroot-carrot juices. The juices obtained from beetroot and carrot were fermented with bacterial strains Lactiplantibacillus plantarum or Levilactobacillus brevis. Density, extract, dry matter content, pH, total acidity, pigments (betalain or carotenoids), color, and LAB count were measured in the samples. The results obtained in this study showed that the used LAB strains were capable of fermenting the analyzed juices. It was proven that Lactiplantibacillus plantarum was a better strain for fermentation ion of vegetable juice. This might have been influenced by the fermentation temperature and the duration of the fermentation. However, this strain had a lower effect on carotenoids, which are water-insoluble pigments, than Lactiplantibacillus plantarum. The opposite observation was made for betalain, a water-soluble pigment with nitrogen in its structure.

Pyrops candelaria is one of the common pests of fruit trees, but the research on the pathogenic microorganisms it may carry is very limited. Therefore, it is essential to reveal the pathogenic microbes it carries and their potential hazards. This study found a new virus from the transcriptome of P. candelaria, which was first reported in P. candelaria and named as PyCaV (Pyrops candelaria associated virus). RACE and bioinformatics assay revealed that the full-length of PyCaV is 10855 bp with the polyA tail, containing a single open reading frame (ORF) encoding a polyprotein consisting of 3171 amino acid (aa). The virus has a typical Iflavirus structure, including two rhv domains, a RNA helicase domain (HEL), a 3C cysteine protease domain (Pro), and a RNA-dependent RNA polymerase domain (RdRp). Further phylogenetic analysis revealed that this virus belongs to family Iflaviridae and sequence alignements analysis suggedted PyCaV is new member in unassigned genus of family Iflaviridae. Further in-depth analysis of virus-infection-part showed that PyCaV is distributing in the whole longan lanternfly, including its head, chest, and abdomen, but more PyCaV was identified in the chest. The distribution of PyCaV in different parts of P. candelaria was further explored, which showed that more PyCaV were detected in its piercing-sucking mouthparts and chest viscera. Statistical analysis showed that the PyCaV infection was affected by time and locations.

In order to shorten the detection time and improve the average precision on embedded devices, A lightweight and high accuracy model is proposed for passion fruit in complex environments (backlight, occlusion, overlap, sunny, cloudy, rainy). Firstly, replacing the backbone network of YOLOv5 with a lightweight GhostNet model reduces the number of parameters and computation while improving detection speed. Secondly, a new feature branch is added to the GhostNet network, and the feature fusion layer in the neck network is reconstructed to effectively combine the lower-level and higher-level features, which not only improves the accuracy of the model but also maintains its lightweight. Finally, the knowledge distillation methods are used to transfer the knowledge from the more capable teacher model to the less capable student model, which significantly improving the detection accuracy. The improved model is denoted as G-YOLO-NK. The average accuracy of the G-YOLO-NK network is 96.00%, which is 1.00% higher than the original YOLOv5s model. Furthermore, the improved model size is 7.14MB, reduced to half of the original model, and the real-time detection frame rate is 11.25 FPS on the Jetson Nano. Compared to the state-of-the-art model, the proposed model outperforms them in terms of average precision and detection performance. The present work provides an effective model for real-time detection of passion fruits in complex orchard scenes, which can provide valuable technical support for the development of orchard picking robots and greatly improve the intelligence level of orchards.

A new Mg-Zn-Zr-Ca alloy in powder state was obtained via mechanical alloying method, from pure elemental powder. Further, the obtained powder-alloy was processed by selective laser melting (SLM) procedure to obtain 3D printed samples for small biodegradable implants. A series of microstructural, mechanical and corrosion analysis were performed. The SEM analysis of powder-alloy reveal a good dimensional homogeneity, with uniform colored, no agglutinated and almost rounded particles, suitable for selective laser melting procedure. Further, the SLM samples reveal a robust and unbreakable morphology, with a suitable porosity and without undesirable balling effect. The tested Young’s modulus of the SLM samples, of 42 GPa, is close to cortical bone one, of 30 GPa. The corrosion tests performed in PBS (Phosphate-buffered saline) solution show that the corrosion parameters have a satisfactory evolution.

Modernizing the retail sector is essential to societal progress toward creating a smart city. The retail sector is crucial to the development of a smart city because of its adaptability and capacity for innovation. However, due to their perishability, supermarkets throw away a lot of fruits and vegetables. This article discusses the design of a sub-optimal process for processing sorted fruits using a reverse logistics approach, demonstrating how productivity can be increased despite constraints on processing capacity. This paper presents the results of a case study conducted in a Qatari supermarket that offers a variety of regular fruit processing techniques. In order to maximize output and cut down on waste, this project aimed to develop a reverse logistics system for imperfect fruit.

In this work, we explore the ability to dynamically group the Wind Turbine (WT) of a Wind Farm (WF) based on the behaviour of some of their Supervisory Control And Data Acquisition (SCADA) signals to detect the turbines that exhibit abnormal behaviour. We centre this study on a small WF of five WTs. We use the fact that the same signals from different turbines in the same WF coherently evolve temporally in a time domain, describing very similar waveforms. In this contribution, we use averaged signals from the SCADA system and omit maximums, minimums and standard deviations, focusing mainly on velocities and other slowly varying signals. For the temporal analysis, sliding windows of different temporal durations and overlapings are explored. The capability to automatically identify WTs whose signals differ from the group’s behaviour can alert and program preventive maintenance operations on such WTs before a major breakdown occurs.

Despite its growing importance as a dry beneficiation method, there is a lack of studies exploring the fundamentals aspects of dry jigging. In this sense, this study focuses on explore some essential aspects of density-based separation in dry jigs, like pulse profile, energy consumption and, especially, stratification over time, also exploring an innovative operational strategy here called “transient pulsation”. The tests were carried out using density tracers distributed across 11 density ranges (0.4-2.4 g/cm³) and employing a base bed (gravel) to analyze their segregation in a pilot-scale dry jig. Pressure drop and active power data were acquired to measure the pulse characteristics and energy consumption. The findings suggest that establishing the dry jigging cycle is more complex than in hydraulic jigs due to the compressibility of air. Stationary pulsation tests revealed an unstable behavior of stratification over time, contrasting with traditional hydraulic jigs, while transient pulsation tests unveiled varied trends in separation quality. Energy consumption analysis underscored the significant role of the blower drive. These insights have the potential to inform operational enhancements in dry jigging.

A configurable design of a microstrip square spiral RFID tag antenna, for a wide range of microwave frequencies in S- and C-band, is presented. The design is parameterized in dimensions, and hence changing the design frequency (or frequencies) is easy, by changing only an initial value for the spiral geometry. A tag specimen was fabricated using Cu electroplating technique according to the design for frequencies of interest in the areas of 2.4 and 5.8 GHz. The substrate material is a 320 μm high resistivity Si and the bridge dielectric is a 15μm polyimide PI2525. The microfabrication process involves steps of metallic structure pattern transfer techniques with optical UV lithography procedures. The reflection coefficient and gain of the specimen were measured inside an anechoic enclosure using a vector network analyzer (VNA) and a TEM horn test antenna over a frequency range of up to 6 GHz. Simulated and measured results are presented and discussed, exhibiting reasonable agreement.

Commercially cultivated Prunus species are commonly grown in adjacent or mixed orchards, and can be infected with unique or commonly shared viruses. Apple (Malus domestica), another member of the Rosacea and distantly related to Prunus, can share the same growing regions and common pathogens. Pollen can be a major route for virus transmission, and analysis of the pollen virome in tree fruit orchards can provide insights into these virus pathogen complexes from mixed production sites. Commercial honey bee (Apis mellifera) pollination is essential for improved fruit set and yield in tree fruit production systems. Here we describe the metagenomics-based detection of plant viruses through bee and pollen samples collected during the spring bloom period from a mixed Prunus and Malus orchard. Twenty-one unique viruses were detected in samples collected during apricot (Prunus armeniaca), sweet cherry (Prunus avium), peach (Prunus persica), and apple blooms. Ilarviruses prune dwarf virus (PDV) and prunus necrotic ringspot virus (PNRSV), Secoviridae family members tomato necrotic ringspot virus, tobacco necrotic ringspot virus, and prunus virus F, and Capillovirus cherry virus A (CVA) were detected in all time points, while other viruses were detected with restricted ranges. These results demonstrate the benefits of area-wide monitoring through bee pollination activities, and provide new insights into the diversity of viruses in tree fruit pollination ecosystems.

The existing methods of oil palm Fresh Fruit Bunch (FFB) evacuation from in-field to temporary collection point which typically apply medium to large tractors, often result in unexpected soil compaction. Meanwhile, smaller size equipment indicates low working capacity and unable to perform direct unloading to collection bin. This paper addresses the challenge of FFB evacuation by focusing on preventing soil compaction, increasing working capacity and enabling direct unloading to collection bin. For this purpose, a 6x6WD transporter prototype with a scissor lift mechanism was developed. With the design, the transporter could evacuate FFB in both steep mineral terrain and low ground pressure peatland, able to carry FFB with capacity of 750 kg and provide direct unloading into collection bin. The average field working capacity of the transporter was found to be 15 tons day-1. This research offers insights for future designs of medium-sized FFB transporters with advanced unloading mechanisms.

This review deals with the adaptive mechanisms that plants can implement to cope with the challenge of salt stress. Plants tolerant to NaCl implement a series of adaptations to acclimate to salinity, including morphological, physiological and biochemical changes. These changes include increases in the root/canopy ratio and in the chlorophyll content in addition to changes in the leaf anatomy that ultimately lead to preventing leaf ion toxicity, thus maintaining the water status in order to limit water loss and protect the photosynthesis process. Furthermore, we deal with the effect of salt stress on photosynthesis and chlorophyll fluorescence and some of the mechanisms thought to protect the photosynthetic machinery, including the xanthophyll cycle, photorespiration pathway and water-water cycle. Finally, we also provide an updated discussion on salt-induced oxidative stress at the subcellular level and its effect on the antioxidant machinery in both salt-tolerant and salt-sensitive plants. The aim is to extend our understanding of how salinity may affect the physiological characteristics of plants.

Precision agriculture is a farm management technology that involves sensing and then responding to the observed variability in the field. Remote sensing is one of the tools of precision agriculture. The emergence of small unmanned aerial vehicles (sUAV) have paved the way to accessible remote sensing tools for farmers. This paper describes the comparison of two popular off-the-shelf sUAVs: 3DR Iris and DJI Phantom 2. Both units are equipped with a camera gimbal attached with a GoPro camera. The comparison of the two sUAV involves a hovering test and a rectilinear motion test. In the hovering test, the sUAV was allowed to hover over a known object and images were taken every second for two minutes. The position of the object in the images was measured and this was used to assess the stability of the sUAV while hovering. In the rectilinear test, the sUAV was allowed to follow a straight path and images of a lined track were acquired. The lines on the images were then measured on how accurate the sUAV followed the path. Results showed that both sUAV performed well in both the hovering test and the rectilinear motion test. This demonstrates that both sUAVs can be used for agricultural monitoring.

The informational synthesis of neural structures, processes, parameters and characteristics that allow a unified description and modeling as neural machines of natural and artificial neural systems is presented. The general informational parameters as the global quantitative measure of the neural systems computing potential as absolute and relative neural power were proposed. Neural information organizing and processing follows the way in which nature manages neural information by developing functions, functionalities and circuits related to different internal or peripheral components and also to the whole system through a non-deterministic memorization, fragmentation and aggregation of afferent and efferent information, deep neural information processing representing multiple alternations of fragmentation and aggregation stages. The relevant neural characteristics were integrated into a neural machine type model that incorporates unitary also peripheral or interface components as the central ones. The proposed approach allows overcoming the technical constraints in artificial computational implementations of neural information processes and also provides a more relevant description of natural ones.

Breast cancer stands as a predominant health concern for women globally. As mammography is the primary screening tool for breast cancer detection, improving the detection of breast cancer at screening could save more lives. This mammography re-view paper provides a systematic review of computer-aided techniques during a specific time frame for the segmentation and classification of microcalcification, evaluating image processing, machine learning, and deep learning techniques. The systematic review is meticulously carried out, adhering closely to the preferred reporting items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. This article focuses on mammographic breast cancer detection approaches based on automated systems, discussed chronologically from 1970 through 2023. This article encompasses the breadth of artificial intelligence-based methods from the most primitive to the most sophisticated models. Image processing and machine learning-based methods are compre-hensively reviewed. The evaluation of a deep learning architecture based on self-extracted features for classification tasks demonstrated outclass performance. Large-scale datasets required for a broader and in-depth analysis of novel methods for breast cancer detection are also discussed in this article. This research work is aligned with the United Nations' sustainability de-velopment goals.

High-density olive groves, despite their interesting production potential, have several limitations, also due to the high fruit load and the irrigation requirements.The study aimed to evaluate the effects of fruit load and deficit irrigation on oil yield and fruit quality, and on olive chemical composition in a high-density olive grove (cv Sikitita). Our main hypothesis was that the primary metabolism, as influenced by crop load and stress, could modify the accumulation of different phenolic classes.Different fruit loads were generated through flower thinning (66%, 50%, 33%, 0%) and two deficit irrigation treatments (-60%, -75%) were compared to the well-watered control (920 m3/ha).Thinning treatments had a limited effect on oil yield, on the other hand, deficit irrigation caused considerably less oil accumulation in the fruit on all sampling dates.Thinning 66% and deficit irrigation 75% were considered with the control for untargeted metabolomic analysis, considering three sampling dates. 233 different phenolic compounds were annotated. Multivariate HCA results indicated the impact of harvest time on the phenolic profile of olive fruits, yielding two separate clusters grouping t1 and t2 together and apart from t3. Regarding agronomic techniques, they played a differential role in the phenolic profile (supervised OPLS – DA). Fruit load mostly affected flavonoid glycosides. In contrast, the phenolic response to deficit irrigation is more heterogeneous, with phenolic acids (35%), flavonoids (25%), LMW, and other phenols (25%).

In the present study, a multilayer high barrier thin blown film based on a polybutylene adipate terephthalate (PBAT) blend with polyhydroxyalkanoate (PHA), and composed of four layers, including a cellulose nanocrystals (CNC) barrier layer and an electrospun poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) hot-tack layer, was characterized in terms of surface roughness, surface tension, migration, mechanical and peel performance, barrier properties and disintegration rate. The results showed a material with a smooth surface. The overall migration test showed that the material was suitable for its use as a food contact layer. The addition of the CNC interlayer had a significant effect on the mechanical properties of the system, drastically reducing the elongation at break and, thus, the flexibility of the material. However, the material retained its elastic modulus and tensile strength. The CNC coating had a negative impact on the peeling strength, weakening the inherently strong interlayer adhesivity of the electrospun PHBV fibers. The multilayer had a good barrier to water vapor, and especially to oxygen, with its permeance reduced by up to a 90 % when the CNC layer was present. Finally, the monolayer blend film disintegrated in a period of less than 55 days in a laboratory-scale composting experiment, while the multilayer system disintegrated in 60 days. Overall, the multilayer system formed a fully compostable structure with great potential for use in food packaging applications.

Nowadays, inquiries are one of the most important tasks to be executed in order to get valued information. When an inquiry is done to gather information about a human behavior there are some problems inherent to it. One of the main problems is how the information about many different persons can be processed to give good information about their environment. Most of the information gathered by these inquiries is used to analyze the behavior of the respondents. It can be used to estimate the success of a certain product on the market or just to validate the satisfaction of current costumers. The veracity of this information can be critical to model environments with some acceptable level of precision. Modelling environments through Artificial Neural Networks (ANN) is highly common because ANN’s are excellent to model predictable environments using a set of data. ANN’s are good in deal with sets of data with some noise, but they are fundamentally surjective mathematical functions and they aren’t able to give different results for the same input. So if an ANN is trained using data where the same input has different images which can be the case of survey data, this can be a problem for the success of modelling the environment. Therefore is necessary to process the data in order to adjust and eliminate invalid data.

Transcription is carried out in most eukaryotes by three multimeric complexes (RNA polymerases I, II and III). However, plants contain two additional RNA polymerases (IV and V), which have evolved from RNA polymerase II. RNA polymerases II, IV and V contain both common and specific subunits that may specialize some of their functions. In this study, we conducted a search for the genes that putatively code for the specific subunits of RNA polymerases IV and V, as well as the corresponding of RNA polymerase II in olive. Based on the homology with the genes of Arabidopsis thaliana, we identified 13 genes that putatively code for the specific subunits of polymerases IV and V, and 16 genes that code for the corresponding specific subunits of polymerase II in olive. The transcriptomic analysis by RNA-Seq revealed that the expression of the RNA polymerases IV and V genes was induced during the initial stages of fruit development. Given that RNA polymerases IV and V are involved in the transcription of long non-coding RNAs, we investigated their expression and observed relevant changes in the expression of this type of RNAs. Particularly, the expression of the intergenic and intronic long non-coding RNAs tended to increase in the early steps of fruit development, suggesting their potential role in this process. The positive correlation between the expression of RNA polymerases IV and V subunits and the expression of non-coding RNAs supports the hypothesis that RNA polymerases IV and V may play a role in fruit development throughout the synthesis of this type of RNAs.

This study examined the impact of differences in fruit load of olive trees on the rate of stem refilling. The experiment was conducted in a commercial olive orchard over the consecutive years of 2021 and 2022, during which the biennial bearing cycle of olive trees resulted in minimal fruit production in 2021 and maximal production in 2022. The rate of stem refilling was determined by quantifying the differences in water volume traversing the apex and base of the principal branches of experimental trees using sap flow sensors. Concurrent measurements of tree water status were also conducted using psychrometers, while soil moisture content dynamics were continuously recorded. Results indicate that alternate bearing significantly influences the stem refilling process, while soil moisture availability also plays a pivotal role. Water reserves were more intensively utilized during the year of full production (“ON” year) primarily to fulfill the water demands of developing fruits. This replenishment occurred in various periods during the day, including early morning, afternoon, and night, when stomatal conductance measurements indicated stomatal closure. The study suggests a more intense replenishment of reserves during the night in "ON" year trees, irrespective of soil moisture, water vapor pressure deficit, or phenological fruit development stage.

Both soybean variety and processing affect product characteristics. This study’s objective was to characterize the effect of four extraction methods (variations of soaking and grinding) combined with cooking on the content and composition of phenolic substances, antioxidant and anti-DU145 prostate cancer cell proliferative properties of soymilk prepared from a yellow soybean of the ProSoy variety, which is a high protein variety. Results showed soymilk processing yield was the greatest by Method 4, but Method 2 gave the highest solids and protein yields by about 14 and 12%, respectively. Method 4, a two-step grinding also increased yields (8 and 7%, for solids and protein, respectively), and in all but one instance produced higher total phenolic content (TPC), total flavonoid content (TFC), condensed tannin content (CTC) and total isoflavone content in both raw and cooked soymilk as compared to Method 1. Cooking soymilk reduced 14-17% of total phenolic substances. Cooking reduced anticancer capacity of Method-4-prepared soymilk phenolic extract by increasing IC50 value from about 4.9 mg/mL to 6.8 mg/mL. The increases in phenolic compounds and antioxidants produced in Prosoy soymilk by Methods 2 and 4 with simultaneous increases in product solids yield are significant to benefit the soymilk industry and consumer health. Keywords: ProSoy yellow soybean, soymilk processing, phenolics, isoflavones, antioxidant capacity, anti-DU145 prostate cancer proliferation

In wireless sensor networks (WSNs), each sensor node can estimate the global parameter from the local data in distributed manner. This paper proposed a robust diffusion estimation algorithm based on minimum error entropy criterion with self-adjusting step-size, which are referred to as diffusion MEE-SAS (DMEE-SAS) algorithm. The DMEE-SAS algorithm has fast speed of convergence and is robust against non-Gaussian noise in the measurements. The detailed performance analysis of the DMEE-SAS algorithm is performed. By combining the DMEE-SAS with diffusion minimum error entropy (DMEE) algorithms, an Improving DMEE-SAS algorithm is proposed, in non-stationary environment where tracking is very important. The Improving DMEE-SAS algorithm can avoid insensitivity of the DMEE-SAS algorithm due to the small effective step-size near the optimal estimator, and obtain a fast convergence speed. Numerical simulations are given to verify the effectiveness and advantages of these proposed algorithms.

A co-curing resin system consisting of 9368 epoxy resin for prepreg and 6808 epoxy resin for resin transfer molding (RTM) was developed. A corresponding preparation method of novel polymer composite bolted T-joint with internal skeleton and external skin was proposed based on prepreg-RTM co-curing process, and novel T-joints were fabricated. A series of conventional configuration T-joints based on RTM process and T-joints made of 2A12 aluminum alloy were prepared simultaneously. Bending performances were studied on these T-joints experimentally. The results indicate that 9368 epoxy resin and 6808 epoxy resin exhibit good compatibility in rheological and thermophysical properties. The novel T-joints prepared with prepreg-RTM co-curing process show no obvious fiber local winding or resin-rich regions inside, and the interface quality between internal skeleton and external skin is excellent. The main failure modes of the novel T-joint under bending load include separation of skin and skeleton and fracture along the thickness on the base panel; the skeleton carries the main bending load, but there is still load transfer between external skin and internal skeleton through their interface. The internal damages of the novel T-joint are highly consistent with surface damages observed visually, facilitating the detection and timely discovery of damages. The initial stiffness, damage initiation load, and ultimate load of the novel T-joint are 1.65 times, 5.89 times, and 3.45 times that of conventional T-joint, respectively. When considering the influence of density, the relative initial stiffness and relative ultimate load of the novel T-joint are 1.44 times and 2.07 times that of aluminum alloy T-joint, respectively.

A set of polymer composite bolted T-joints with novel configuration consisting of internal skeleton and external skin was fabricated using a prepreg-RTM co-curing molding process. Experiments were conducted to study their mechanical properties under bending load. A finite element model with a polymer resin area between the skin and skeleton was established and verified by the experimental results. Then, the damage propagation process and failure mechanism of the joint and the influence of three factors related to the layer characteristics of the skin and skeleton were investigated by the validated models. The results show that the bending stiffness and the yield limit load of the novel composite T-joint are 0.81 times and 1.65 times that of the 2A12 aluminum T-joint respectively, while at only 55.4% of its weight. The damage of the joint initiates within the resin area and leads to a degradation of the joint bending performances. The preferred stacking sequence of the skeleton is [0/+45/90/-45]ns when primarily subjected to bending loads. The decrease in bending performances is within 5% with the inclining angle of the skeleton less than 12 degrees. The more layers of 90° in the skin, the better bending performances of the joints, while the more layer of 0°, the poorer bending performances.

With a view to understand and resolve the complexity of the food matrix, ohmic technologies alone or in combination were extensively employed. In this sense, the newest developments and advances of proteomics, metabolomics, lipidomics whith their unique benefits could simplify and understand the link between physiological and pathological activities in biology, physiology, pathology, and food science and processing. This review aims to briefly introduce the basis of proteomics, metabolomics, lipidomics, then expansively review their impact on the assessment of meat quality and safety. Here, also, we discuss the application of proteomics, metabolomics, lipidomics for the authentication and adulteration of meat and meat derivatives from different sources, and provides some perspectives regarding the use of emerging techniques such as rapid mass spectrometry (MS) and non-invasive measurements for the analysis of meat quality and safety. This paper summarizes all significant investigation in these matters, and underlines the advances in analytical chemistry technologies and meat science areas. By emphasizing the requirement for additional examinations, this paper attempts a comprehensive knowledge of “foodomics” and their potential to improve their employment in meat science.

Background: Functional beverages are ordinary foods with components or ingredients able to provide specific health effects other than purely nutritional effect. Aim: This study aims to formulate a new functional beverage obtained from the recovery of YoAlp® whey, a bovine fermented milk obtained using autochthonous starter cultures, added with Renetta Canada/Golden Delicious-Raspberry (YWL), Renetta Canada-Aronia (YWA) and Ravèntse (YWR) fruit juices to improve the functionality of the beverage. Methods: Microbiological analysis and chemical characterization, by a proteomic approach and spectrophotometric microassay, have been conducted on beverages to investigate the expected shelf-life and potential health promoting effects. Results: The microbiological assessment confirmed the safety of the beverages and the probiotic bacteria vitality over a shelf life of seven days. Biochemical analysis performed highlight the presence of different bioactive peptides (ACE inhibitory and antioxidant), and the betacasomorphin 9 (BCM-9), marker of A2 variant of β-casein typically present in Aosta Valley cattle breeds. Moreover, high amounts of total polyphenols, which concur to the antioxidant activity values observed, have been found. Furthermore, ACE inhibitory activity is well correlated to the bioactive peptides detected. Finally, a consumer test confirmed the YoAlp® whey-based beverages appreciation. Conclusions: The production of these beverages could represent a huge opportunity for Aosta Valley’s farms to increase their income and competitiveness, creating a circular economy by recovering a by-product like whey and following sustainability and healthy trends, which are driving the food sector.

Two experiments were conducted to develop a Nano green manganese and assess its effect on grapevines. The first experiment was microbiological, where several incorporation strategies were utilized to enrich the yeast with manganese, as follows: (1) adding manganese to the liquid medium (growth phase), (2) adding after 24 h of incubation (non-growth phase). As the results, growth phase reduced the possibility of medium contamination. Manganese concentration in the yeast cells was increased as that of manganese sulphate in the medium. Manganese incorporation in yeast cells was 99.93% higher than that of the medium at 0.0195 g/l of manganese. Although the concentration of manganese in the medium raised the OD of yeast cell biomass, manganese sulphate had no passive influence on it. The second experiment was horticultural, done on Flame Seedless grapevines, since both active fresh and frozen yeast enriched with manganese resulted from the first experiment were sprayed twice a year at 10 or 20 cm3/l comparing with manganese sulphate, and manganese chelate. The results demonstrated that yeast extracts in both forms increased the yield and improved fruit properties. The most effective treatment on vegetative growth, yield and fruit properties was the frozen yeast enriched with manganese at 20 cm3/l.

With the increasing interest in CM as a potential source of nutrients and bioactive compounds, there arises a necessity to delve into methods for its processing and drying. Over recent decades, a significant amount of research has been conducted on the chemical composition of CM and its potential health benefits. Consequently, this study is directed towards examining CM drying technology, including an analysis of the influence of different drying methods on its chemical composition and nutri-tional properties. The objective of this review is to systematically summarize the available literature on CM drying processes and their impact on its chemical composition. Special attention is devoted to comparing various drying methods such as freeze-drying, spray drying, and freeze-drying, as well as investigating factors affecting the quality of dried CM. To achieve this goal, we scrutinize a series of studies published between 2003 and 2022 to identify optimal drying methods that promote the maximum preservation of CM's nutritional components and bioactive compounds. Additionally, we explore possibilities for reducing drying time to enhance production efficiency. This research is grounded in the analysis of data from diverse scientific research databases, including Scopus and Google Scholar, encompassing a systematic review of scientific literature and a comparative analysis of the obtained results.

The most relevant fungal disease of the olive tree in Portugal is anthracnose, which has negative effects on fruit destruction and consequently on the yield and quality of the olive oil. Moreover, the loss of quality caused by olive fruit fly is associated with the presence of fungi in the galleries made by the larvae. The present study focuses on the effect of olive anthracnose and olive fly on the content of bioactive compounds, namely on hydroxytyrosol (HYT) and its derivatives (health claim) in olive oils extracted from 'Galega Vulgar' and 'Cobrançosa' cultivars. The olives, with different damage levels (olive fly and anthracnose disease), were harvested in Castelo Branco (Center of Portugal) in organic rainfed orchards, at four harvest times during 2019, 2020 and 2021 harvest years. The fruits were immediately submitted to olive oil extraction. The results of the quality criteria show that Galega olive oils extracted from olives with a higher anthracnose incidence show no conformity for the Extra Virgin Olive Oil (EVOO) and Virgin Olive Oil (VOO) categories, with high acidity values and negative sensory notes accompanied by the disappearance of oleacein (the main phenolic compound of both monovarietal olive oils). Conversely, no sensory defects were observed in Cobrançosa olive oils extracted from fruit with high anthracnose and olive fly incidence. Moreover, despite a decrease in all the positive attributes associated with the cultivar, namely in oleacein and oleocanthal contents, quality criteria were still in accordance with the EVOO category. The total HYT and tyrosol (TYR) content (&gt; 5 mg/20g) allows the use of the health claim on the label of all the analysed Cobrançosa olive oils.

Solid waste management in Accra is a major challenge to the Metropolitan Authorities and inhabitants. The rapidly increasing population coupled with poor capacity of the municipal and private waste management companies to management waste effectively has created issues of environmental concern. Due to poor waste managements systems, most household dispose waste indiscriminately leading to floods and health issues. The study showed that about 60% of household waste is organic materials which has the potential to be converted to compost for agriculture purpose. Meanwhile plastics and rubbers which litters the environment as well as blocking major storm drains and gutters hence creating huge environmental hazard is made of 11% of the total component of most household waste generated daily. The study also revealed that among the methods of disposing waste, dumping waste in skip containers located at authorized places was the preferred means of disposing waste by household though others also dispose waste by other means such as burying and burning. Inadequate skip containers per population of household in an area coupled with irregularity of tracks picking these containers makes skip containers dumping site ugly scene, hence creating health issues. Among the constraints that impact negatively on sustainable waste management in Accra Metropolis, economic constraints was perceived as the main challenge which affect efficient waste management. Currently the country is going through serious economic challenges so government does not release money timely to fund projects which waste management is key. Most donor partners that use to support the government with funds have either reduced or redrawn their services as they have no confidence in the state of Ghana economy. Aside the constrains, the study also indicated that factors such as poor public attitude towards waste management, poor enforcement of sanitation by-laws, inadequate and untimely release of government funds were also seen as the main factors affecting waste management.

Since the beginning of the internet era, there has been an explosion of growth in structured data (such as numbers, symbols, and labels) as well as unstructured data (including images, videos, and text). Efficient and accurate mixed query of these two types of data is a key technology to achieve high-quality information retrieval, and it is also a major challenge that needs to be solved urgently in the industry. In this study, we employ an advanced Transformer model that combines strategies and fine-tuning techniques for multi-task learning. Specifically, the model is first pre-trained on a large-scale, general-purpose dataset to learn different types of data representations and basic language comprehension skills. After that, we fine-tuned the parameters of the model to better suit these specific data processing tasks for specific application scenarios, such as image annotation, video content analysis, and structured data query. At the heart of the model is the self-attention mechanism, which allows the model to automatically emphasize the important parts and ignore irrelevant information when processing the input data. In addition, we have introduced task-specific adaptation layers that are designed to add additional processing power to the original Transformer architecture, such as a semantic analysis layer for unstructured text data and a relational extraction layer for structured data. This combination of general pre-training and task-specific fine-tuning allows the model to flexibly process and integrate information from different data sources, improving processing efficiency and accuracy. Experimental results show that the model performs well in a variety of data processing tasks, significantly improves the accuracy and efficiency of information retrieval, and verifies the strong potential and adaptability of large language models in processing mixed data types.

With continuous increase in integration of the semiconductor devices, the requirements on size accuracy and surface quality of the etched lead frame are higher. The etchant is a key factor on etching process and etched surface quality, while effects of the difference in etchants on microscopic etched surface morphology of the Cu alloy have not been directly studied. In this study, the aqua regia, acidic FeCl3 and CuCl2 solutions were used as etchants, and the CuCrSn alloy specimens with different microstructure were etched and characterized. The results show that the etching rate in aqua regia is high, and the grain orientation, grain boundary (GB) and dislocation have significant influence on the local etching rate. The preferential etching of some atomic planes forms steps between grains with different orientations, and the preferential etching around the GB and dislocation group forms grooves, resulting in high surface roughness. For etching of the FeCl3 and CuCl2 etchants, the steps and grooves become blurred, and almost invisible on the surface etched by the CuCl2 etchant, thus the surface roughness is much lower. The CuCrSn alloy surface etched by the aqua regia is clean, with little Cr-rich particles, while high density Cr-rich particles are remained on the surfaces etched with the FeCl3 and CuCl2 etchants. For the same kind of etchant, the ion concentration can affect the etching mechanism and etching surface morphology.

For a wide field of view (FoV) wavefront coding athermalized infrared imaging system with a single decoding kernel, the off-axis aberration tends to cause artefacts. In order to correct off-axis aberration, many pieces of lenses will reduce the transmission efficiency and increase the weight and cost. To meet requirements for wide FoV, wide operating temperature and low weight of infrared imaging systems, this paper reports a wide-FoV wavefront coding athermalized infrared imaging system with a two-piece lens. Its principle, design, manufacture, measurement and performance validation are successively discussed. This paper constructs an optimization problem which maximizes the weighted mean of PSF consistency for both the FoV and operating temperature range. The two-piece lens contains four surfaces, where three aspheric surfaces are introduced to reduce optical off-axis aberrations and a cubic surface is introduced to achieve athermalization. The optical phase mask containing an aspheric surface and a cubic surface is manufactured by nano-metric machining of ion implanted material(NiIM). Experimental results validate that our wide-FoV wavefront coding athermalized infrared imaging system has a full FoV of 26.10° and an operating temperature over -20°C to +70°C.

Zucchini (Cucurbita pepo L.) is an important crash crop for producing seeds in Inner Mongolia, China. In August 2021, the harvest season of seed-producing zucchini, fruit rot symptom (cv. Jindi No.1) was found in the Wuyuan region. The incidence of infected fruits of zucchini ranged from 10% to 30% and symptom consisted in 4 to 5 cm diameter lesions where the fruit was in contact with the soil. Ten isolations from six symptomatic fruits were preliminary classified as Fusarium species based on its morphological characters in potato dextrose agar. Phylogenetic tree was constructed by concatenating TEF-1α and RPB2 gene and exhibited the isolates clustered together with the Fusarium solani f. sp. cucurbitae sequences. Pathogenicity tests revealed that two isolates caused over 3 cm diameter lesions on the fruits while negative-controls remained asymptomatic. The colonies reisolated from the leasions were morphologically identical to the original isolates, thus fulfilling Koch’s postulates. Results demonstrated that F. solani f. sp. cucurbitae was the causal agent of fruit rot observed in the field. To our knowledge, this is the first report of fruit rot of seed-producing zucchini caused by F. solani f. sp. cucurbitae in Inner Mongolia, China.

In contemporary construction, the prevalence of vibration serviceability issues in lightweight and slender structures has become increasingly common, owing to advancements in building materials and construction methods. While these structures often meet the criteria for ultimate limit states, they can still elicit complaints due to excessive vibrations induced by human activity. To address this challenge, the Integral Resonant Control (IRC) technique has emerged as a favored approach for actively damping vibrations in various systems. This study introduces a fresh perspective on implementing a multi-input multi-output (MIMO) IRC scheme for active vibration control (AVC) specifically tailored for pedestrian structures utilizing inertial mass actuators. Building upon a common framework and design methodology outlined in previous research, this work presents a novel application of MIMO IRC for AVC. The designed controller is rigorously tested and implemented on a laboratory floor structure to validate its efficacy.

Autophagy is a highly conserved self-degradation process involving the degradation and recycling of cellular components and organelles. Although the involvement of autophagy in metabolic changes during fruit ripening has been preliminarily demonstrated, the variations in autophagic flux and specific functional roles in fruit ripening remain to be elucidated. In this study, we analyzed the occurrence of autophagy during tomato fruit ripening. The results revealed differential expression of SlATG8 family member during tomato fruit ripening. Transmission electron microscopy observations and dansylcadaverine (MDC) staining confirmed the presence of autophagy at the cellular level in tomato fruits. Furthermore, the overexpression of SlATG8f induced the formation of autophagosomes, increased autophagic flux within tomato fruits, effectively enhanced the expression of ATG8 proteins during the color transition phase of fruit ripening, thereby promoting tomato fruit maturation. This overexpression also led to the accumulation of vitamin C (VC) and soluble solids while reducing acidity in the fruit. Collectively, our findings highlight the pivotal role of SlATG8f in enhancing tomato fruit ripening, providing insights into the mechanistic involvement of autophagy in this process. This research contributes to a better understanding of key factors regulating tomato fruit quality and offers a theoretical basis for tomato variety improvement.

Nanocellulose (CNC) seems to be a promising surfactant, which, together with expandable graphite (EG), forms the essence of an effective natural-based fire retardant wood coating. In our research, the most suitable composition of the mixture was tested concerning good solubility, dispersion, and consistency. Favorable results were achieved with the formulation composed of a 4% CNC alkaline solution with 80 wt.% of selected EG. Subsequently, six different EG were used to prepare these wood fire retardant coatings. The effectiveness of treatments was verified using a test with a radiant heat source, where the test samples' relative weight loss, relative burning rate, and surface temperature during 600 sec were evaluated. All prepared formulations can be characterized as more or less equally effective. However, the best results were obtained with EG of GG 200 – 100 N, where the mass loss of the sample was 8.10 ± 1.24%. Very good results were also achieved by graphite 25 E + 180 HPH (8.70 ± 0.89%), which is similar to the previous one, even according to the microscopic assessment of the coating as well as the expanded layer. Graphite type 25 K + 180 (8.86 ± 0.65 %) shows the expanded layer's best cohesion, coating uniformity, and ease of application. The results of this work confirmed that the CNC coating itself has significant retardation effects.

Understanding morphological and genetic diversity of forest trees is essential to facilitate their conservation, sustainable management and genetic improvement for addressing the economic and environmental demands and challenges. We have examined variation in morphometric seed and pod traits and seed germination of multipurpose and widely distributed forest tree Albizia lebbek (Indian siris) from 12 provenances covering the species’ range in northern India and its relationships with bioclimatic factors. Highly significant inter-provenance variation was observed in seed size (seed length (SL), seed width (SW), SW/SL, SL×SW), seed mass (1000 seed weight), pod size (pod length (PL), pod width (PW), PW/PL), seed germination, number of seeds per pod, and insect infected seeds (IIS). The provenance effect contributed a major portion to the total phenotypic variance. Morphometric variation in all traits except for IIS was not clinal related to longitude, latitude, altitude or rainfall. There was an indication of the presence of ecotypic variation. IIS showed clinal variation with significant negative correlation with latitude. Most seed size and pod size traits showed positive correlations with several temperature bioclimatic factors and negative correlations with several precipitation bioclimatic factors. Our results have significance for genetic improvement, population genetics and genomics studies and conservation and sustainable management of A. lebbek genetic resources.

Verticillium dahliae (Vd) and Fusarium oxysporum f. sp. lycopersici (Fol) are two major fungal pathogens that infect tomato plants, causing significant challenges in their control since both pathogens can persist in the soil for several years even in the absence of a host plant and no effective fungicides are available at present. This study investigated the efficacy of two biocontrol formulations, Clonotri and Strepse, against Vd and Fol, and their impact on tomato fruit quality and yield under greenhouse conditions. Pathogenicity experiment demonstrated that the Clonotri formulation, containing Trichoderma and Clonostachys spores, significantly reduced Fusarium wilt disease by 32% compared to the control group. However, in Vd pathogenicity experiment, the formulations did not exhibit disease reduction, although the treatment with Strepse, containing Streptomyces and Pseudomonas microorganisms, resulted in preserved total fruit number when compared to uninfected plants. Analysis of fruit quality attributes revealed no significant differences among the various interventions. Furthermore, Fol infection in the first fruit set significantly increased fruit firmness, while Vd infection resulted in elevated levels of total soluble solids in fruits. These findings demonstrate that the evaluated biocontrol formulations provide a degree of protection against fungal wilt pathogens in tomato plants and can increase yield in greenhouse conditions, while having minimal impact on overall fruit quality attributes.

Background: Capsaicinoid are a group of compounds and widely used in the food, medical, and pharmaceutical industries. Capsaicinoid are unique synthesized and accumulated in the pepper fruits. MeJA can enhance the capsaicinoid production. Temporal and spatial expression of capsaicinoid biosynthetic genes are helpful to understand the molecular mechnism of capsaicinoid biosynthesis in the fruits of pepper. Although some of the capsaicinoid biosynthetic genes in pepper have been identified, the expression of these genes at different developing stages of fruit has not been systemically investigated, and little is known about the molecular basis of MeJA inducing capsaicinoid biosynthesis. Results: HPLC study revealed that the capsaicinoid accumulation in the developing fruit of pepper initially appeared at 24 DAP (day after pollination), was actively development at 36 DAP and peaked at 48 DAP. 11 genes that encoded enzymes involved in capsaicinoid biosynthesis were isolated and characterized. Gene expression with quantitative reverse-transcription polymerase chain reaction analysis demonstrated that the CaCS was unique expressed in placenta and the other 10 genes were expressed in all selected tissues and 9 of 11 genes (except CaCa4H and CaCa3H) were strongly expressed in placenta tissue. Spatial expression analysis demostrated that the 11 gene could be collectively grouped into four categories based on the patterns of relative expression of the genes during fruit development. Category I has 2 and they displayed a bell-shaped expression pattern with the peak expression at 24 DAP, Category II contains 5 genes and expression of the 5 genes was constantly increased from 0 to 36 DAP and peaked at 36 DAP. Category III comprises of 2 genes and both genes reached the peak at 48 DAP. Category IV consists of 2 genes and they showed a high expression at 36 and 48 DAF, but unexpressed from 0 to 12 DAP. The gene expressions of the 11 genes were up-regulated by MeJA. 3 genes showed a high expression at 24 h; 4 genes reached the peak at 12 h; the top expression were observed at 18 h; The last one, CaACYase, achieved the highest level at 8 h. Conclusion: The biosynthesis of capsaicinoid in pepper fruit is developmentally regulated. The expression of the majority of capsaicinoid biosynthetic genes is highly consistent with the development accumulation of capsaicinoid in pepper fruit. These results not only provide the initial information on spatial and temporal expression of capsaicinoid biosynthetic genes in pepper developing fruit, but are also valuable to identify the MeJA-induced genes for capsaicinoid biosynthesis and accumulation during pepper fruit development.

In this paper, we introduce new formulas for calculating the restoring and repulsive magnetic forces between two non-coaxial circular loops with parallel axes. These formulas are derived from a modified version of Grover’s formula for mutual inductance between the coils in question. Utilizing these formulas, we compute the restoring and repulsive magnetic forces between two non-coaxial thick coils of rectangular cross-sections with parallel axes. In these calculations, we apply the filament method and conduct investigations to determine the optimal number of subdivisions for the coils in terms of computational time and accuracy. The method presented in this paper is also applicable to all conventional non-coaxial coils, such as disks, solenoids, and non-conventional coils like Bitter coils, all with parallel axes. This paper emphasizes the accuracy and computational efficiency of the calculations. Furthermore, the new method is validated according to several previously established methods

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.

High level of noise is a disturbance to the human environment. Noise in industries is also an occupational hazard because of its attendant effects on workers’ health. Noise presents health and social problems in industrial operations, and the source is related to the machineries used in the industries. One of the unique features of the noise associated with wood machinery is the level of exposure and duration. Equipment used in a factory can be extremely loud. They can produce noise at decibels high enough to cause environmental health and safety concerns. The mechanically driven transport and handling equipment, cutting, milling, shaping and dust extractor installations in the wood industry generate noise. The sources of noise pollution have increased due to non-compliance with basic safety practices. The increased use of locally fabricated machine in the industry has increased the level of noise and vibration. The effects of industrial noise pollution as discussed include: increase in blood pressure; increased stress; fatigue; vertigo; headaches; sleep disturbance; annoyance; speech problems; dysgraphia, which means reading/learning impairment; aggression; anxiety and withdrawal. As presented in this paper, noise control techniques include; sound insulation, sound absorption, vibration damping and Vibration isolation.

The chestnut tree (Castanea sativa Mill.) is gaining importance in the mountainous regions of southern Europe due to the high value of its fruits. It is essential to establish effective cultivation protocols, considering that this species is still relatively understudied. In this study, we present the outcomes of the initial establishment of a chestnut orchard conducted through a nutrient omission trial for four years. The treatments included a fertilization plan with nitrogen, phosphorus, potassium, and boron (NPKB), the control, and four other treatments corresponding to the omission of each nutrient (-NPKB, N-PKB, NP-KB, NPK-B). The -NPKB and NP-KB treatments showed significantly lower trunk circumferences and canopy volumes compared to the other treatments. The NPK-B treatment resulted in the lowest fruit production, with a total accumulated yield (2020-2022) of 0.56 kg tree–1, a value significantly lower than that of NPKB (1.12 kg tree–1) and N-PKB (1.19 kg tree–1). The assessment of nutrient concentrations in the leaves revealed plants with deficient levels of B and K in treatments that did not receive these nutrients. Conversely, N levels in the leaves in the -NPKB treatment fell within the sufficiency range (20 to 28 g kg–1). This suggests that the sufficiency range should be adjusted to higher values, given the treatment's effect on tree growth. It was also observed that the -NPKB treatment led to lower soil organic matter compared to the other treatments, likely due to reduced herbaceous vegetation development under the canopy, leading to decreased organic substrate deposition in the soil. The main findings of this study are that N and K were crucial elements for the optimal growth of chestnut trees, while B played a significant role in fruit production.

The high genetic diversity of the tomato and its high micronutrient content make this fruit very interesting from an economic and nutritional point of view. The genetic erosion suffered by this crop, due to breeding objectives based on yield and marketing, makes it necessary to return to the origins in search of the nutritional and organoleptic quality lost in traditional varieties. In this study, the agronomic, physical, organoleptic and nutritional characteristics of eighteen F1 hybrids obtained by crossing fourteen traditional varieties, previously selected for their quality, were studied to select genotypes of superior quality that could be candidates for new. All parameters studied were strongly influenced by genotype, showing a wide range between cultivars. Principal Component Analysis revealed the characteristics of each hybrid that made it stand out from the others. Some hybrids (H3, H4, and H6) stand out because of their high concentration of active compounds, others (H16, H15, H10, H17, H9, and H11) because of agronomic performance and high content of β-carotene, and H5 was the only one to contain chlorophyll in their ripe fruits. Finally, the evaluation index allowed the selection of five hybrids with interesting characteristics, combining good yield performance and high quality

This study evaluates the efficacy of the salts, sodium metabisulfite (SMB), ammonium bicarbonate, sodium bicarbonate and potassium dihydrogen orthophosphate first in vitro against the main postharvest fruit rot fungi, Alternaria alternata, Botrytis cinerea, Penicillium italicum and Penicillium digitatum. Results showed that 0.2% SMB completely inhibited mycelium growth of the fungal species. Ammonium bicarbonate and sodium bicarbonate were less effective at 0.2% in inhibiting mycelial growth, ranging from 57.6% to 77.6%. The least effective was potassium dihydrogen or-thophosphate. Experiments were also performed in vivo on wounded apples inoculated with the most pathogenic fungus, B. cinerea, and treated with SMB at concentrations of 0.2, 0.5, 1, 2 and 3%, both preventively and curatively. Results based on the decay size showed that SMB, when used as a preventive treatment, had a reduced efficacy, even with the highest concentration. However, this salt proved to be very effective at 0.5% in curative treatment, since the decay was completely blocked. Our results suggest that the appropriate concentration of SMB for post-harvest treatment is 0.5% as a curative treatment. On the other hand, the 1% dose induced the onset of phytotoxicity around the wound. To assess the extent of phytotoxicity reaction, higher concentrations of 1-4% SMB were applied to wounded fruit. Apples and oranges were inoculated or not with B. cinerea and P. digitatum respectively. Doses of 1- 4% induced phytotoxicity in the form of a discoloured ring surrounding the wound on the epidermis of the fruit; this phytotoxicity enlarged as the concentration of SMB increased. The phytotoxic features were similar on apples and oranges. The methodological procedure made it possible to carry out a quantitative assess-ment of SMB phytotoxicity. This method is proposed as an easy-to-use technique for quantitatively estimating the phytotoxicity of antifungal compounds on post-harvest fruit.

Fragile X syndrome (FXS) is caused by the full mutation in the FMR1 gene on the Xq27.3 chromosome region. It is the most common monogenic cause of Autism Spectrum Disorder (ASD) and inherited intellectual disability (ID). Besides ASD, ID and other issues, individuals with FXS may exhibit sleep problems and impairment of circadian rhythm (CR). The Drosophila melanogaster models of FXS, such as dFMR1B55, present excellent model for research in the FXS field. During this study, sleep pattern and CR in dFMR1B55 mutants were analyzed, using a new platform based on continuous high-resolution videography in integration with a highly-customized version of software. This methodology provides more sensitive results, which could be crucial for all further research in this model of fruit flies. The study revealed that dFMR1 B55 male mutants can be considered weak rhythmic flies rather than totally arrhythmic, and present a good alternative animal model of genetic disorder, which includes impairment of CR and sleep behavior. The combination of videography and software used in the current study should be recommended as a gold-standard methodology for such further research.

Artificial intelligence provides a new research concept for digital image processing. However, at present, artificial intelligence is rarely introduced into the teaching of digital image processing in colleges and universities, and there are problems such as obsolete teaching content, single teaching methods, and simple course experiments, which affect the teaching effect and are not conducive to the cultivation of comprehensive and innovative talents. Digital image processing technology brings more possibilities to communication engineering and makes communication more convenient. For example, video calls and photo transmission make people's communication methods in daily life more and more diversified. Time and space limitations allow people to meet online, creating more communication possibilities. However, there are still many problems and methods worthy of in-depth exploration. Therefore, this paper has a comprehensive understanding and mastery of the traditional and deep learning methods of digital image processing to improve the relevant project practice and scientific research exploration ability and refer for similar research conclusions.

Abstract Global marine fish harvest has reached a plateau over the last decade. Efforts to increase aquaculture tend to face limitations in water resources and contamination problems. Of the current fish harvest at least 50% is discarded as waste. The chemical and microbiological contaminations limit the utilization of harvested fish. There is a need to improve fish preservation to minimize spoilage and process them into more appealing products. Instead of resorting to individual food processing methods, the efficiency of processing could best be increased by a combination of conventional and modern processing methods, or combinations of modern processing methods. Fish waste is a rich source of oils containing essential fatty acids, polypeptides, and amino polysaccharides that could be utilized through upscaling of the current scientifically proven methods, to new processing technologies. Separation of collagens, gelatins, bioactive peptides, edible fish oils, and chitosan form the primary stages in the utilization of fish waste. The products need purification to meet food quality and safety standards, and desirable industrial characteristics. The diversity of information and products generated through new methods requires advanced data handling and prediction systems, such as artificial intelligence, to address food safety and get the best out of fish processing and utilization.

Precision agriculture is a technology used by farmers to help food sustainability amidst growing population. One of the tools of precision agriculture is yield monitoring, which helps a farmer manage his production. Yield monitoring is usually done during harvest, however it could also be done early in the growing season. Early prediction of yield, specifically for fruit trees, aids the farmer in the marketing of their product and assists in managing production logistics such as labor requirement and storage needs. In this study, a machine vision system is developed to estimate fruit yield early in the season. The machine vision system uses a color camera to capture images of fruit trees during the full bloom period. An image segmentation algorithm based on an artificial neural network was developed to recognize and count the blossoms on the tree. The artificial neural network segmentation algorithm uses color information and position as input. The resulting correlation between the blossom count and the actual number of fruits on the tree shows the potential of this method to be used for early prediction of fruit yield.

Color change is the most obvious characteristic of tomato ripening stage and an important indicator of tomato ripening condition, which directly affects the commodity value of tomato. To visualize the color change of tomato fruit in mature stage, a gated recurrent unit network with an encoder-decoder structure that dynamically simulates tomato growth and development with time-dependent lines using tomato color and shape as real-time data was proposed in this paper. Firstly, the .json file was converted into a mask.png file, the tomato mask was extracted, and the tomato was separated from the complex background environment, and the tomato growth and development data set was successfully constructed. Then, a network of gated recurrent units with encoder-decoder structure was constructed to predict the future growth trend of tomato under different greenhouse temperatures. The experimental results showed that for the gated recurrent unit network of encoder-decoder structure proposed, when the hidden layer number was 1 and hidden layer number was 512, a high consistency and similarity between the model predicted image sequence and the actual growth and development image sequence would be realized, and the structural similarity index measure was 0.746. It was proved that when the average temperature was 24.93℃, the average soil temperature was 24.06℃, and the average light intensity was 11.26 Klux, the environment was the most suitable for tomato growth. The environmental data-driven tomato growth model was constructed to explore the growth status of tomato under different environmental conditions, thus to understand the growth status of tomato in time. The statement provided a theoretical foundation for determining the optimal greenhouse environmental conditions to achieve tomato maturity. And it offered recommendations for investigating the growth cycle of tomatoes, as well as technical assistance for standardized cultivation in solar greenhouses.

Historic expeditions are events that are flavored by exploratory, scientific, military or geographic characteristics. Such events are often documented in literature, journey notes or personal diaries. A typical historic expedition involves multiple site visits and their descriptions contain spatiotemporal and attributive contexts. Expeditions involve movements in space that can be represented by triplet features (location, time and description). However, such features are implicit and innate parts of textual documents. Extracting the geospatial information from these documents requires understanding the contextualized entities in the text. To this end, we developed a semi-automated framework that has multiple Information Retrieval and Natural Language Processing components to extract the spatiotemporal information from a two-volumes historic expedition gazetteer. Our framework has three basic components, namely, the Text Preprocessor, the Gazetteer Processing Machine and the JAPE (Java Annotation Pattern Engine) Transducer. We used the Brazilian Ornithological Gazetteer as an experimental dataset and extracted the spatial and temporal entities from entries that refer to three expeditioners’ site visits and mapped the trajectory of each expedition using the extracted information. Finally, one of the mapped trajectories was manually compared with a historical reference map of that expedition to assess the reliability of our framework. The reference map was manually prepared in previous research work by others.

At present, nanomaterials (NMs) show extreme potential for a wide range of applications ranging from aerospace to energy storage applications owing to a number of properties which, in a number of contexts have been reported to be superior as compared to those of bulk counterparts. However, the high surface area to volume ratio which yields extraordinary properties to NMs also turns out to be the major limitation in a number of different contexts. For instance, the high surface area to volume ratio in these materials leads to a high reactivity, especially in electrochemical environments which are prevalent during energy storage applications. In this context, it is worthwhile mentioning that processing of NMs play a crucial role in influencing their mechanical properties. On the other hand, surface engineering has emerged as a powerful tool to deconvolute bulk properties from surface characteristics and has been reported to exhibit tremendous potential for overcoming the aforementioned limitation of NMs. The present review therefore, is aimed at highlighting the present status of research in the field of processing and applications of surface engineered NMs. Moreover, challenges and future perspectives in the aforementioned avenue have been discussed.

Knowledge processing is an important feature of intelligence in general and artificial intelligence in particular. To develop computing systems working with knowledge, it is necessary to elaborate means of working with knowledge representations (as opposed to data) because knowledge is an abstract structure. There are different forms of knowledge representations derived from data. One of the basic forms is called a schema. The goal of this paper is the development of theoretical and practical tools for processing schemas. To achieve this goal, we use schema representations elaborated in the mathematical theory of schemas and use structural machine as a powerful theoretical tool for modeling parallel and concurrent computational processes. We describe the schema of autopoietic machines as physical realizations of structural machines. An autopoietic Machine is a technical system capable of regenerating, reproducing and maintaining itself by production, transformation and destruction of its components and the networks of processes downstream contained in them. We present the theory and practice of designing and implementing autopoietic machines as information processing structures integrating both symbolic computing and neural networks. Autopoietic machines use knowledge structures containing the behavioral evolution of the system and its interactions with the environment to maintain stability by counteracting fluctuations.

Irrigation and fertilization are indispensable links in the jujube planting industry in southern Xinjiang, China. However, the water and fertilizer integration effects on jujube growth and fruit quality remain unclear. A two-year water and fertilizer optimization coupling test was conducted to determine the optimal water- and nutrient-supply scheme. The three-factor randomized block experiment included water (W), nitrogen (N), and phosphorus (P). According to the principal component analysis of each index, each treatment’s comprehensive score was obtained. Using yield and economic regression models, the theoretical value and yield value of the optimal economic benefit are inferred. When W, N, and P were applied together, the fruit quality and yield of each treatment significantly differed, and the vitamin C, soluble sugar, and sugar–acid ratio increased significantly with an increase in nitrogen fertilizer. However, the titratable acid decreased. An increase in irrigation and nitrogen application significantly increased fruit yield. The comprehensive score was the highest in the N3P3W2 treatment, which improved fruit quality, and the lowest in the N4P3W2 treatment. When the amounts of N, P, and W were 275.56 kg·hm-2, 413.66 kg·hm-2, and 7278.19 m3·hm-2, respectively, the theoretical economic benefit was the best. The N4P3W2 treatment is the optimal treatment.

Reducing the carbon footprint of energy production is one of the most pressing challenges facing humanity today. Lignocellulosic biomass residues from fruit production industries show promise as a viable energy source. This paper presents a study of the Italian context concerning the utilization of orchard lignocellulosic residues for energy production as electricity or bioethanol. The potential of various orchard residues was assessed through chemical and physical analysis, and an equivalent electrical energy of about 6441.62 GWh or an amount of 0.48 Mt/y of bioethanol was obtained based on the average annual dry residue mass availability of about 3.04 Mt/y. These data represent the 9.30% of the national electrical energy production from renewable sources, as well as the 6.21% of the Italian demand for gasoline in 2022. Electricity generation from these residues shown its potential as a reliable and sustainable baseload power source, as well as source of renewable transportation fuel. The studied process could be a valuable reference to expand these concepts on global scale to achieve a greener and more sustainable energy future.

Fruit cracking or splitting, a severe physiological disease that highly affects appearance and quality, compromise the commodity value of fruit and also causes huge economical losses to the producers of several fleshy fruit crops. The growth-promoting phytohormone gibberellic acid (GA) and growth-inhibiting phytohormone abscisic acid (ABA) antagonistically regulate numerous developmental processes throughout the plant life cycle. Homeostasis of endogenous GA and ABA play a significant role in the normal growth of fruits, and its imbalance may lead to the occurrence of cracking or splitting during the process of fruit growth, development, ripening and postharvest storage. The pathways of GA and ABA metabolism and signaling have been studied widely, and the major components were well characterized, which including the genes encoding major biosynthesis and catabolism enzymes and the key signaling components. Nevertheless, our knowledge of the mechanisms of GA and ABA governing fruit cracking is not comprehensive enough. In this review, we not only focus on the scenarios of effects of endogenous GA and ABA contents in the fruit and exogenous plant growth regulators GA and ABA treatments, but also endeavor to provide some genetic cues on the function of GA and ABA responsible for fruit cracking modulation. Information from this review aims to strengthen the understanding of potential molecular bases underlying GA and ABA in fruit cracking control and provide guidance in breeding of fruit cultivars with cracking-resistant ideotypes, and also make great theoretical significance in guiding the establishment of integrated prevention and control measures to fruit cracking or splitting.

Pruning is one of the most important tree fruit production activities, which is highly dependent on human labor. Skilled labor is in short supply, and the increasing cost of labor is becoming a big issue for the tree fruit industry. Growers are motivated to seek mechanical or robotic solutions for reducing the amount of hand labor required for pruning. This paper reviews the research and development of sensing and automated systems for branch pruning for tree fruit production. Horticultural advancements, pruning strategies, 3D structure reconstruction of tree branches, as well as practice mechanisms or robotics are some of the developments that need to be addressed for an effective tree branch pruning system. Our study summarizes the potential opportunities for automatic pruning with machine-friendly modern tree architectures, previous studies on sensor development, and efforts to develop and deploy mechanical/robotic systems for automated branch pruning. We also describe two examples of qualified pruning strategies that could potentially simplify the automated pruning decision and pruning end-effector design. Finally, the limitations of current pruning technologies and other challenges for automated branch pruning are described, and possible solutions are discussed.

Imaging systems mounted to ground vehicles are used to image fruit tree canopies for estimation of fruit load, but frequently need correction for fruit occluded by branches, foliage or other fruits. This can be achieved using an orchard ‘occlusion factor’, estimated from a manual count of fruit load on a sample of trees (referred to as the reference method). It was hypothesised that canopy images could hold information related to the number of occluded fruit. Five approaches to correct for occluded fruit based on canopy images were compared using data of three mango orchards in two seasons. However, no attribute correlates to the number of hidden fruit were identified. Several image features obtained through segmentation of fruit and canopy areas, such as the proportion of fruit that were partly occluded, were used in training Random forest and multi-layered perceptron (MLP) models for estimation of a correction factor per tree. In another approach, deep learning convolutional neural networks (CNNs) were directly trained against harvest fruit count on trees. The supervised machine learning methods for direct estimation of fruit load per tree delivered an improved prediction outcome over the reference method for data of the season/orchard from which training data was acquired. For a set of 2017 season tree images (n=98 trees), a R2 of 0.98 was achieved for the correlation of the number of fruits predicted by a Random forest model and the ground truth fruit count on the trees, compared to a R2 of 0.68 for the reference method. The best prediction of whole orchard (n = 880 trees) fruit load, in the season of the training data, was achieved by the MLP model, with an error to packhouse count of 1.6% compared to the reference method error of 13.6%. However, the performance of these models on new season data (test set images) was at best equivalent and generally poorer than the reference method. This result indicates that training on one season of data was insufficient for the development of a robust model. This outcome was attributed to variability in tree architecture and foliage density between seasons and between orchards, such that the characters of the canopy visible from the interrow that relate to the proportion of hidden fruit are not consistent. Training of these models across several seasons and orchards is recommended.

Dissimilar welds between ferritic and austenitic steels represent a good solution for exploiting the best performance of stainless steels at high and low temperatures and in aggressive environments, while minimizing costs. Therefore, they are widely used in nuclear and petrochemical plants, however, due to the different properties of the steels involved, the welding process can be challenging. Fusion welding can be specifically addressed to connect low-carbon, or low-alloy steels, with high-alloy steels, which have similar melting point. Welding of thick plates can be performed with electric arc in multiple passes or in a single pass by means of a laser beam equipment. Since microstructure and consequently mechanical properties of the weld are closely related to composition, the choice of the filler metal and processing parameters, which in turn affects the dilution rate, plays a fundamental role. Numerous technical solutions were proposed for welding dissimilar steels and much research was developed on the weldment metallurgy; therefore, this article is aimed at a review of the most recent scientific literature on the issues relating to the fusion welding of ferritic / austenitic steels. Two specific sections are dedicated respectively to electric arc and laser beam welding; finally, metallurgical issues, related to dilution and thermal field are debated in the discussion section.

Quinoa is a resilient crop known for its adaptability to diverse environmental conditions. This study examined the agronomic performance and ecological adaptability of quinoa across four distinct altitudes in the northwestern regions of China. Six quinoa genotypes were assessed for agronomic traits, phenology and yield performances, and nutritional quality characteristics in Yining city, Nilka County, Tekes County and Zhaosu County under varied environmental conditions. Our findings demonstrate significant variations in all measured traits including agronomic and nutritional quality traits across the various altitudes and genotypes. In Yining City, a warmer and lower altitude area, genotypes exhibit superior traits for fodder production, including increased branches, longer panicles, robust stems, and high seed protein content. Genotypes Jinli 1 and Beijing 2 achieve yields exceeding 3 tons per hectare (T/ha), highlighting the region’s productivity. Nilka and Tekes counties boasted the shortest quinoa crop cycles, with Jinli 1 yielding 4.05 T/ha seeds in Tekes County, exhibiting high protein and fat content alongside low saponins, making it prime location for yield production. Zhaosu County, with its cooler climate and fertile chernozem soil, elicited high 1000 seed weight and more robust protein response than Nilka and Tekes counties, illustrating the impact of soil fertility on nutritional composition. Correlation analyses further elucidated that the plants characterized by shorter flowering times, crop cycles, compact inflorescence, and taller heights exhibited superior seed yields. Our study contributes significant insights into the ecological adaptability and nutritional dynamics of quinoa, with implications for sustainable crop production and food security in diverse agroecosystems.

Epigallocatechin gallate (EGCG), the principal catechin in green tea, exhibits diverse therapeutic properties. However, its clinical efficacy is hindered by poor stability and low bioavailability. This study investigated solid particle-in-oil-in-water (S/O/W) emulsions stabilized by whey protein isolate (WPI) and sodium caseinate (NaCas) as carriers to enhance the bioavailability and intestinal absorption of EGCG. Molecular docking revealed binding interactions between EGCG and these macromolecules. The emulsions exhibited high encapsulation efficiencies and augmented EGCG bioaccessibility by 64% compared to free EGCG in a simulated gastrointestinal digestion model. EGCG-loaded emulsions demonstrated minimal cytotoxicity towards Caco-2 cells and facilitated EGCG transport across the intestinal epithelial layer without compromising tight junction integrity. Notably, EGCG-loaded emulsions protected Caco-2 cells against oxidative stress by suppressing intracellular reactive oxygen species generation. The results demonstrate the potential of WPI- and NaCas-stabilized S/O/W emulsions to enhance the bioavailability, intestinal absorption, and bioactivity of EGCG, expanding its applications in functional foods and nutraceuticals.

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.

Transportation systems through the ages have seen drastic evolutions in terms of transportation methods, speed of transport, infrastructure, technology, connectivity, influence on the environment, and accessibility. The massive transformation seen in the transportation sector has been fueled by the industrial revolutions which have continued expansion and progress into the fourth industrial revolution. However, the methodologies of data collection and processing used by the many drivers of this progress differ. The significance of standardized data and its mode of collection cannot be overstated as it has a major impact on the process outcomes. In order to achieve a better understanding of the impact of this, this study methodically reviewed the literature on the subject of the data collection and processing mechanism of 4IR technologies in the context of the transport industry with an emphasis on the areas of accomplishment of several studies and drawing attention to their limitations. Although the industry has advanced significantly as a result of the adoption and application of various research studies in this field, considerable focus needs to be placed in the areas of standardized data collection and computational approaches, which will ultimately assist in achieving various benefits in the transportation industry.

Fruits and vegetable diagnosis and inspection is a crucial part of quality control and health safety. From harvesting to retailing, stakeholders encounter tons of food losses due to the lack of monitoring of the fruit condition in retail. The problem gets worse because it is being handled by many people, including retailers and customers. We propose a transparent fiberglass-made vertical fruit showcase, which provides 80 percent more visibility, takes lesser shop space, and prevents human contact. It is convenient for the retailer and customer to use. Moreover, the controlled fruit environment is easy to integrate with IoT, which will help to generate consensus data for fruit management decisions in machine learning.

Storing apples for up to a year is a well-established practice aimed at providing a continuous, locally-produced fruit supply to consumers and adapting to market trends for optimized profits. Temperature control is the cornerstone of postharvest conservation and apples are typically kept at temperatures from 0 to 3 °C. However, the energy-intensive process of the initial cool down and subsequent temperature maintenance poses significant financial challenges and contributes to the carbon footprint. Higher storage temperatures could reduce cooling-related energy usage but also pose the risk of enhanced ripening and quality loss. This work explores different storage technologies aiming to reduce energy consumption such as 1-methylcyclopropene, ultra-low oxygen and dynamic controlled atmosphere together with raised temperatures. The integration of advanced monitoring and control systems, coupled with data analytics and energy management in apple storage is also discussed. These sustainable strategies can be implemented without cost-intensive construction measures in standard storage facilities. Furthermore, beneficial side effects of higher storage temperatures in terms of a reduced occurrence of storage disorder symptoms and higher maintenance of quality attributes are also discussed for this special issue on sustainable horticultural production systems and supply chains.

Passion fruit is a valued tropical fruit crop that faces environment-related growth strains. TCP genes are important for both growth modulation and stress prevention in plants. Herein, we systematically analyzed the TCP gene family in passion fruit, recognizing 30 members. Genes exhibiting closer phylogenetic relationships exhibited similar protein and gene structures. Gene members of the TCP family showed developmental stage or tissue-specific expression profiles during the passion fruit life cycle. Transcriptome data also demonstrated that many PeTCPs showed induced expression in response to hormonal treatments and cold, heat, and salt stress. Based on transcriptomics data, eight candidate genes were chosen for preferential gene expression confirmation under cold stress conditions. Additionally, four TCP genes exhibited in silico binding with cold stress-related miRNA319s. This study will aid in the establishment of novel germplasm, as well as the further investigation of the roles of PeTCPs and their cold stress resistance characteristics.

Scientists are gradually becoming aware of the challenges in the understanding of the very root mechanisms of massively parallel computations that are observed in literally all scientific disciplines ranging from cosmology, physics, across chemistry, biochemistry, and ending in biology. This leads us to the main motivation and simultaneously to the central thesis of this review: “Can we design artificial, massively-parallel, self-organized, emergent, error-resilient, computational environments?” A large number of simulations along with examples and counter-examples, finalized by a list of the future directions, are giving hints and partial answers to the main thesis. This all together is opening the crucial question whether there is existing a deeper, beyond the Turing machine theoretical description of massively-parallel computing. Important information dealing with this topic is reviewed along with highly expressive animations generated by the open-source, Python software GoL-N24. The perspective, future directions including applications in robotics and biology of this research are discussed in the light of known information.

The need to develop novel lightweight materials and their manufacturing processes is sets out to meet the new aerospace, automotive and construction requirements. Within this context, this research work is proposed to develop a novel thermoplastic composite material with high mechanical properties. These composites will be based on thermoplastic matrixes made from polyamide and 35% short glass fiber filled-polyamide reinforced with different types of fabrics. As reinforcement, glass fiber fabrics will be used as the base. They will be treated with different processes, both chemical and physical, to promote adherence to the matrix. Textile overmoulding technology was selected for manufacturing these composites. This technology was primarily developed to manufacture aesthetic lined components and has achieved a great implantation. Once these new composites are manufactured, they will be submitted to different tests to evaluate their behavior regarding adhesion, impact strength and stiffness. It is expected an improvement on stiffness and impact absorption.

In strawberry production, the combination of high productive performance and fruits with desirable physicochemical characteristics requires the use of plants of good quality and high initial vigor. This study aimed to evaluate the effect of plants with different crown diameters on the productive performance and fruit quality of strawberry plants of the cultivar 'Pircinque.' The study was conducted in two evaluation cycles (2016/2017 and 2017/2018). The experimental design was in randomized blocks, with four repetitions, and plots consisting of 20 plants. This study evaluated the crown diameters of plants of 5, 7, 9, 11, 13, 15, 17, and 19 mm. The productivity and number of fruit values increased significantly with larger caliber plants, which also provided precocity of productivity. The use of more vigorous plants also favored the production of fruits with higher soluble solids / titratable acidity ratios and with epidermis coloration closer to intense red. For the cultivar 'Pircinque', the plant crown diameters between 15 and 17 mm are the most favorable because they condition the best productive performances in combination with precocity and good fruit quality.