Complex Products Research Articles

Anti-inflammatory Fatty Acid Derivatives From Mangrove-derived Actinomycetes Streptomyces sp.

Mangrove-derived actinomycetes are prolific chemical sources of complex and novel natural products, providing an excellent chance for new drug discovery. The chemical investigation of the mangrove-derived Streptomyces sundarbansensis 06037, led to the discovery of two previously undescribed enone fatty acids (1-2), one new phenylpropionate derivate (3), along with the isolation of the ten known components (4-13). Those chemical structures of isolates were elucidated on the basis of the analysis of diverse spectroscopic data. Initial anti-inflammatory tests of 1-3 in lipopolysaccharide (LPS)-activated RAW 264.7 murine macrophage cells revealed that compound 1 possess significant inhibitory effect on the production of Nitro oxidase (NO), with the IC50 value around 15.33±1.32 μM, together with the suppression of NF-κB phosphorylation and reducing the release of oxygen species (ROS) in RAW 264.7 macrophages, those results indicated that compound 1 may exert its anti-inflammatory activity through a reduction in ROS level and the suppression of NF-κB activation pathway.

Recognition of Sheep Feeding Behavior in Sheepfolds Using Fusion Spectrogram Depth Features and Acoustic Features

In precision feeding, non-contact and pressure-free monitoring of sheep feeding behavior is crucial for health monitoring and optimizing production management. The experimental conditions and real-world environments differ when using acoustic sensors to identify sheep feeding behaviors, leading to discrepancies and consequently posing challenges for achieving high-accuracy classification in complex production environments. This study enhances the classification performance by integrating the deep spectrogram features and acoustic characteristics associated with feeding behavior. We conducted the task of collecting sound data in actual production environments, considering noise and complex surroundings. The method included evaluating and filtering the optimal acoustic features, utilizing a customized convolutional neural network (SheepVGG-Lite) to extract Short-Time Fourier Transform (STFT) spectrograms and Constant Q Transform (CQT) spectrograms’ deep features, employing cross-spectrogram feature fusion and assessing classification performance through a support vector machine (SVM). Results indicate that the fusion of cross-spectral features significantly improved classification performance, achieving a classification accuracy of 96.47%. These findings highlight the value of integrating acoustic features with spectrogram deep features for accurately recognizing sheep feeding behavior.

Evaluation and Application of Machine Learning Techniques for Quality Improvement in Metal Product Manufacturing

This article presents a discussion of the application of machine learning methods to enhance the quality of drive shaft production, with a particular focus on the identification of critical quality issues, including cracks, scratches, and dimensional deviations, which have been observed in the final stages of machining. A variety of classification algorithms, including neural networks (NNs), bagged trees (BT), and support vector machines (SVMs), were employed to efficiently analyse and predict defects. The results show that neural networks achieved the highest accuracy (94.7%) and the fastest prediction time, thereby underscoring their efficiency in processing complex production data. The BT model demonstrated stability in its predictions with a slower prediction time, while the SVM model exhibited superior training speed, though with slightly lower accuracy. This article proposes that optimising key process parameters, such as temperature, machining speed, and the type of coolant used, can markedly reduce the prevalence of production defects. It also recommends integrating machine learning with traditional quality management techniques to create a more flexible and adaptive control system, which could help reduce production losses and enhance customer satisfaction.

Design and building CNC engraving router machine using Arduino Uno with GRBL control system

Computer Numerical Control Machines are one of the advances in automatically operated machining technology that can meet the need for complex and high-precision products. CNC machine parts generally have a mechanical and electrical system, also called a machine controller, that uses a Human Machine Interface at a high price. One of the software used to control the CNC machine is Arduino Uno, a PC-based GRBL System with a low price and the same function. This software is not far from the advantages of the HMI panel. Operating the machine with this software is also not that difficult. In this research, we intend to make a CNC machine using the Arduino Uno control system and software with a PC-based GRBL System, making it easier for operators to operate it. The results of the research that has been carried out show that the CNC has a size of 800x600x50mm with a system that is operated well and precisely

Noncanonical Functions of Ketosynthase Domains in Type I Polyketide Synthases.

Modular type I polyketide synthases (PKSs) are remarkable molecular machines that can synthesize structurally complex polyketide natural products with a wide range of biological activities. In these molecular machines, ketosynthase (KS) domains play a central role, typically by catalyzing decarboxylative Claisen condensation for polyketide chain extension. Noncanonical KS domains with catalytic functions rather than Claisen condensation have increasingly been evidenced, further demonstrating the capability of type I PKSs for structural diversity. This review provides an overview of the reactions involving unusual KS activities, including PKS priming, acyl transfer, Dickmann condensation, Michael addition, aldol-lactonization bicyclization, C-N bond formation and decarbonylation. Insights into these reactions can deepen the understanding of PKS-based assembly line chemistry and guide the efforts for rational engineering of polyketide-related molecules.

Concise Synthesis of Norzoanthamine Enabled by a Set of Photochemical Transformations.

Norzoanthamine is a structurally complex polycyclic natural product that expresses a broad range of biological activities, rendering facile access to it and its analogs of considerable importance in drug discovery and development. However, strategies for efficient access to this class of marine alkaloids remain lacking. Here, we report a strategy, characterized by three key photochemical reactions, that we used to synthesize norzoanthamine in 16 steps. A photoinduced dearomative-6π-desymmetrization was developed for facile access to the ABC-tricyclic core of the alkaloid. This was supplemented by a [2 + 2]-photocycloaddition, a visible-light-induced decarboxylative borylation, and a retro-aldol process, constituting an effective solution to the challenging problem of establishing the C9-C22 vicinal all-carbon quaternary stereogenic centers. Finally, a one-pot cascade transformation, involving global deprotection, cyclization, and epimerization reaction, was designed for efficient and stereocontrolled assembly of the core framework of norzoanthamine.

Multitask scheduling on cloud additive manufacturing using NSGA-II

Purpose: Cloud manufacturing (CM) represents a new manufacturing paradigm that integrates distributed resources to provide on-demand services. The high consumer demand from various locations, coupled with the customizability and complexity of manufacturing, complicates task scheduling. In this context, 3D printers are crucial as innovative manufacturing technologies with significant potential in producing complex and custom products. Scheduling in CM falls under the non-deterministic polynomial time-hard category, where tasks must be scheduled and distributed rapidly. Considerations of distance, minimization of delays, and makespan become critical variables that must be considered. This research aims to schedule and distribute tasks in CM using the non-dominated sorting genetic algorithm II (NSGA-II) to minimize delays, reduce makespan, and decrease costs.Methodology: NSGA-II is employed to tackle the complexities of scheduling in CM. The strength of NSGA-II lies in its ability to determine optimal and efficient solutions for multiobjective problems. Tasks originating from requests at various locations are adjusted based on material parameters and dimensions and then distributed to providers while considering aspects such as makespan, delay minimization, and cost.Findings: The optimization results using NSGA-II demonstrate effective and efficient task distribution to providers. Across the four tested task distribution scenarios, the average computational time required was 5.59 seconds. Pareto analysis indicates a trade-off between various objective functions. Solutions with short distances tend to have increased maximum time and delays.Originality/value: NSGA-II is effective for task distribution with multiobjective considerations. Not all three objective functions can be optimized simultaneously, given the trade-offs between distance, maximum time, and lateness. The priority of the objective functions should be determined to achieve optimal results. If minimizing lateness is most important, the focus should be on points with low lateness values. Further development can be done by modifying the Pareto front to make data-driven decisions that consider these trade-offs.

Markets of agro-industrial complex products in conditions of geoeconomic fragmentation of the international trade

For decades, international trade has contributed to the reduction of global poverty and the income gap between countries, and the development of intercountry exchange of agricultural products has largely ensured the solution of problems of poverty and food security. At the same time, at the present stage, a high degree of dependence of many developing countries on food imports has occured, while its global exporters have faced a number of restrictions on the supply of their agricultural products. This article analyses the impact of geoeconomic fragmentation of the international trade on the development of exports and imports of products of the agro-industrial complex (hereinafter referred to as AIC). In particular, the problems of competition in the world agro-food markets are discussed in a new context, since the growing problems of monopolisation in certain segments of the AIC disrupt the stability of agricultural markets. Exclusive attention is paid to the key aspects of the application of non-tariff measures in regulating trade of the agricultural products, which, in addition to the protective role, can have a distorting effect on world prices. Our analysis places particular emphasis on the hidden costs of global agri-food systems, which necessitate their rapid modernisation to ensure sustainability in the development of the agricultural markets and to address global food security issues.

Complex product quality prediction based on ResNeSt model combining class-aware attention mechanism and dynamically updating class weights

Complex product quality prediction based on ResNeSt model combining class-aware attention mechanism and dynamically updating class weights

Enabling Unfavorable Hydroamination Reactions Using a Chemoselective N-O Bond Reduction.

Despite major advances, intramolecular alkene hydroamination reactions often face limitations. Herein, a redox-enabled process featuring oxidation of an amine to a hydroxylamine, a concerted hydroamination step, followed by catalytic reduction of N-oxide is shown to be broadly applicable. Catalyst screening and optimization showed that a K2OsO2(OH)4-pinacol complex rapidly and chemoselectively reduces the N-oxide cycloadduct in the presence of hydroxylamine and dimethyl sulfoxide. This selectivity was exploited to drive the equilibria toward complex products.

Total Synthesis of Ryanodane Diterpenoids Garajonone and 3‐epi‐Garajonone

AbstractRyanodane diterpenes are structurally complex natural products that are well‐known for their high degree of oxidation and the challenges associated with synthesizing them within the terpene class. Herein, we present a two‐stage synthetic strategy that draws inspiration from the broad biosynthesis of terpenes, allowing us to achieve the first chemical synthesis of garajonone, a ryanodane diterpenoid that occurs naturally at low abundance, as well as its epimer, 3‐epi‐garajonone. The key to this success lies in the rapid construction of the carbon framework of the target molecule by employing an early‐stage palladium‐catalyzed Heck/carbonylative esterification cascade annulation, followed by successive late‐stage selective redox manipulation to establish the desired oxidation state of the molecule. This research not only showcases the synthesis of garajonone and its epimer but also provides a platform for the chemical synthesis of other members and analogs of this complex diterpenoid family.

Total Synthesis of Ryanodane Diterpenoids Garajonone and 3-epi-Garajonone.

Ryanodane diterpenes are structurally complex natural products that are well-known for their high degree of oxidation and the challenges associated with synthesizing them within the terpene class. Herein, we present a two-stage synthetic strategy that draws inspiration from the broad biosynthesis of terpenes, allowing us to achieve the first chemical synthesis of garajonone, a ryanodane diterpenoid that occurs naturally at low abundance, as well as its epimer, 3-epi-garajonone. The key to this success lies in the rapid construction of the carbon framework of the target molecule by employing an early-stage palladium-catalyzed Heck/carbonylative esterification cascade annulation, followed by successive late-stage selective redox manipulation to establish the desired oxidation state of the molecule. This research not only showcases the synthesis of garajonone and its epimer but also provides a platform for the chemical synthesis of other members and analogs of this complex diterpenoid family.

Orderly Coating of Bilayer Polymer to Tailor Microenvironment for Efficient C−N Coupling Toward Highly Selective Urea Electrosynthesis

AbstractElectrosynthesis of urea from co‐reduction of carbon dioxide and nitrate is a promising alternative to the industrial process. However, the overwhelming existence of proton and nitrate as well as the insufficient supply of CO2 at the reaction interface usually result in complex product distributions from individual nitrate reduction or hydrogen evolution, instead of C−N coupling. In this work, we systematically optimize this microenvironment through orderly coating of bilayer polymer to specifically tackle the above challenges. Polymer of intrinsic microporosity is chosen as the upper polymer to achieve physical sieving, realizing low water diffusivity for suppressing hydrogen evolution and high gas permeability for smooth mass transfer of CO2 at the same time. Polyaniline with abundant basic amino groups is capable of triggering chemical interaction with acidic CO2 molecules, so that is used as the underlying polymer to serve as CO2 concentrator and facilitate the carbon source supply for C−N coupling. Within this tailored microenvironment, a maximum urea generation yield rate of 1671.6 μg h−1 mg−1 and a high Faradaic efficiency of 75.3 % are delivered once coupled with efficient electrocatalyst with neighboring active sites, which is among the most efficient system of urea electrosynthesis.

Experimental and advanced equilibrium studies on the enhanced adsorption of phosphate, cadmium, and safranin dye pollutants using methoxy exfoliated glauconite

Natural glauconite, as a mixed-layered clay mineral, was subjected to exfoliation processes, producing silicate monolayers or individual sheets that were further modified with methanol into methoxy exfoliated glauconite (Mth/EXG). The structure was assessed as an enhanced adsorbent for three types of common water contaminants, including phosphate (PO43-), safranin-O dye (SFR), and cadmium metal ions (Cd2+). The Mth/EXG structure achieved promising adsorption capacities at the saturation points equal to 269.9 mg/g for PO43-, 312 mg/g for SFR, and 234.5 mg/g for Cd2+ which are significantly better than the reported values for several studied adsorbents of higher costs and complex production procedures. The adsorption processes and the predicted regulated mechanisms in terms of the adsorbate/adsorbent interface were illustrated based on the steric and energetic findings that correspond to the applied monolayer equilibrium model of one energy site. The structure displays active site densities of 82.5 mg/g (PO43-), 136.3 mg/g (SFR), and 83.4 mg/g (Cd2+), which illustrate the high uptake performance of SFR. Also, the steric parameters reflected the suitability of each existing site to be filled with 4 ions of PO43-, SFR, and Cd2+. The adsorption energy (less than 40 kJ/mol) in conjunction with free adsorption energy from D-R model (8–16 kJ/mol) and steric parameters validate the dominant impact of the multi-ionic physical mechanisms (hydrogen bonding and van der Waals forces), in addition to the assistant impact of some weak chemical processes that might be assigned to the formed inner-sphere complex. Also, these reactions all occurred spontaneously with exothermic behaviors according to the thermodynamic functions. Additionally, the structure exhibit significant affinity for the studied pollutants even in the existing of completive chemical including anions, cations and organic molecules.

Wooden hafting technology in the early Neanderthal site of Poggetti Vecchi (Italy)

The invention of hafted tools, between about 500 Ka and 250 Ka years ago, was a fundamental technological innovation that has shaped human social, cognitive, and biological capabilities. Despite the recurrent evidence of hafting observed on lithic tools, handles from this period are rare since they were probably made of perishable materials. Three exceptional wooden sticks interpreted as handles have been found in the Poggetti Vecchi site, allowing a deeper investigation of the technical capabilities of the early Neanderthals who frequented the site around 170,000 years ago. The handles and the lithic tools with hafting traces were analysed using a techno-functional approach, suggesting that they could have been attached to each other to create a specific composite hafted tool. The efficiency of the composite hafted tool was tested through a detailed experimental programme. The results highlighted, for the first time, the complex production processes used to create a composite hafted tool that could have been used to butcher the carcases of the large fauna that are well attested at the site.

Electrochemical Synthesis of Metal Complexes Using Dissolving Anodes.

The use of dissolving metal electrodes for the direct electrochemical synthesis of metal complexes has been used widely in the last decade. A major benefit of the electrochemical approach is the minimal by-products resulting from the synthesis. As such, metal complexes can be produced on-demand and used directly in catalysis without the need for purification. Furthermore, the electrochemical method enables the production of metal complexes that cannot be synthesized using other methods, including those with base-sensitive ligands. General principles of the electrochemical method and recent advances in the field are discussed.

Rapid and Specific Detection of Bacillus cereus Using Phage Protein-Based Lateral Flow Assays.

Rapid and precise diagnostic techniques are essential for identifying foodborne pathogens, including Bacillus cereus (B. cereus), which poses significant challenges to food safety. Traditional detection methods are limited by long incubation times and high costs. In this context, gold nanoparticle (AuNP)-based lateral flow assays (LFAs) are emerging as valuable tools for rapid screening. However, the use of antibodies in LFAs faces challenges, including complex production processes, ethical concerns, or variability. Here, we address these challenges by proposing an innovative approach using bacteriophage-derived proteins for pathogen detection on LFAs. We used the engineered endolysin cell-wall-binding domain (CBD) and distal tail proteins (Dit) from bacteriophages that specifically target B. cereus. The protein-binding properties, essential for the formation of efficient capture and detection biointerfaces in LFAs, were extensively characterized from the microstructural to the LFA device level. Machine-learning models leverage knowledge of the protein sequence to predict advantageous protein orientations on the nitrocellulose membrane and AuNPs. The study of the biointerface binding quantified the degree of attachment of AuNPs to bacteria, providing, for the first time, a microscopic model of the number of AuNPs binding to bacteria. It highlighted the binding of up to one hundred 40 nm AuNPs per bacterium in conditions mimicking LFAs. Eventually, phage proteins were demonstrated as efficient bioreceptors in a straightforward LFA prototype combining the two proteins, providing a rapid colorimetric response within 15 min upon the detection of 105 B. cereus cells. Recombinantly produced phage binding proteins present an opportunity to generate a customizable library of proteins with precise binding capabilities, offering a cost-effective and ethical alternative to antibodies. This study enhances our understanding of phage protein biointerfaces, laying the groundwork for their utilization as efficient bioreceptors in LFAs and rapid point-of-care diagnostic assays, thus potentially strengthening public health measures.

Enantioselective Synthesis of Azatricycles via Post-Ugi Cyclizations.

We report a new method to create enantioenriched azatricycles using chiral α-amino acids in a two-step process after an Ugi reaction. Amino acids are great building blocks for making pure chiral molecules. Using chiral natural molecules in multicomponent reactions (MCRs) helps increase their variety by adding new chiral centers. The Ugi reaction, discovered by Ivar Karl Ugi in 1959, is a versatile MCR that helps create complex molecular structures and natural products through additional transformations called post-Ugi modifications. Designing these modifications requires selecting the right amine, acid, aldehyde/ketone, and isocyanide. Amino acids, with their primary amine and carboxylic acid groups and a pre-existing chiral center, are ideal for making diverse and selective post-Ugi modifications. Our method uses ipso-cyclization and aza-Michael cyclization with hypervalent iodine to create various azaspirotricyclic structures with high stereocontrol. This approach works well with different substrates and shows promise for further development in drug discovery.

Robot arm grasping based on YOLOv5 in the perspective of automated production

Abstract The rapid development of industrial intelligence has gradually expanded the application of automated production. As a typical automated production equipment, the robotic arm still faces the problems of low grasping efficiency and high control costs when facing highly integrated and miniaturized components. Given this, to improve the grasping level of the robotic arm in complex production environments, this study first constructs a kinematic mathematical model of the robotic arm. Secondly, based on the algorithm that You Only Look Once, improvements are made to its convolution operation and feature extraction modules, ultimately proposing a new type of robotic arm grasping control model. The results showed that the loss test value of the new model was the lowest at 2.75, the average detection error of the captured object was the lowest at 0.003, and the average detection time was the shortest at 1.28 seconds. The highest success rate for grasping six types of industrial parts was 94%, and the lowest average energy consumption was 35.67 joules. Therefore, research models can significantly improve the grasping performance of robotic arms under various complex conditions, thereby achieving efficient manipulation of robotic arms in industrial automation.

Low-energy (0–9 eV) electron interaction with gas phase 1,3-dichlorobenzene: an experimental and theoretical study

Abstract Dichlorobenzene used widely in industry for the synthesis of complex products, such as polymers. The processes using this compound require, as the initial step, the breakage of the C–Cl bond. In this work, we study the interaction of electrons with 1,3 dichlorobenzene molecules not only below 2 eV [M Mahmoodi-Darian et al 2001 J. Phys. Chem. A 113 11923–14929] but also at higher energies, i.e., up to 10 eV. In this investigated energy range, the electron induces the cleavage of the C–Cl bond producing essentially a Cl− anion and the chlorobenzene radical via dissociative electron attachment. The experimental measurements are completed with quantum scattering treatments providing the resonant states and also the integral scattering cross sections. These outcomes may potentially contribute to elaborate synthesis strategies using electrons (i.e., cold plasma, surface plasmon resonance, …).