This work presents an approach for the recognition of plastics using a low-cost spectroscopy sensor module together with a set of machine learning methods. The sensor is a multi-spectral module capable of measuring 18 wavelengths from the visible to the near-infrared. Data processing and analysis are performed using a set of ten machine learning methods (Random Forest, Support Vector Machines, Multi-Layer Perceptron, Convolutional Neural Networks, Decision Trees, Logistic Regression, Naive Bayes, k-Nearest Neighbour, AdaBoost, Linear Discriminant Analysis). An experimental setup is designed for systematic data collection from six plastic types including PET, HDPE, PVC, LDPE, PP and PS household waste. The set of computational methods is implemented in a generalised pipeline for the validation of the proposed approach for the recognition of plastics. The results show that Convolutional Neural Networks and Multi-Layer Perceptron can recognise plastics with a mean accuracy of 72.50% and 70.25%, respectively, with the largest accuracy of 83.5% for PS plastic and the smallest accuracy of 66% for PET plastic. The results demonstrate that this low-cost near-infrared sensor with machine learning methods can recognise plastics effectively, making it an affordable and portable approach that contributes to the development of sustainable systems with potential for applications in other fields such as agriculture, e-waste recycling, healthcare and manufacturing. Full article

Muscle synergy has been widely acknowledged as a possible strategy of neuromotor control, but current research has ignored the potential inhibitory components in muscle synergies. Our study aims to identify and characterize the inhibitory components within motor modules derived from electromyography (EMG), investigate the impact of aging and motor expertise on these components, and better understand the nervous system’s adaptions to varying task demands. We utilized a rectified latent variable model (RLVM) to factorize motor modules with inhibitory components from EMG signals recorded from ten expert pianists when they played scales and pieces at different tempo–force combinations. We found that older participants showed a higher proportion of inhibitory components compared with the younger group. Senior experts had a higher proportion of inhibitory components on the left hand, and most inhibitory components became less negative with increased tempo or decreased force. Our results demonstrated that the inhibitory components in muscle synergies could be shaped by aging and expertise, and also took part in motor control for adapting to different conditions in complex tasks. Full article

Cloud detection technology is crucial in remote sensing image processing. While cloud detection is a mature research field, challenges persist in detecting clouds on reflective surfaces like ice, snow, and sand. Particularly, the detection of cloud shadows remains a significant area of concern within cloud detection technology. To address the above problems, a convolutional self-attention mechanism feature fusion network model based on a U-shaped structure is proposed. The model employs an encoder–decoder structure based on UNet. The encoder performs down-sampling to extract deep features, while the decoder uses up-sampling to reconstruct the feature map. To capture the key features of the image, Channel Spatial Attention Module (CSAM) is introduced in this work. This module incorporates an attention mechanism for adaptive field-of-view adjustments. In the up-sampling process, different channels are selected to obtain rich information. Contextual information is integrated to improve the extraction of edge details. Feature fusion at the same layer between up-sampling and down-sampling is carried out. The Feature Fusion Module (FFM) facilitates the positional distribution of the image on a pixel-by-pixel basis. A clear boundary is distinguished using an innovative loss function. Finally, the experimental results on the dataset GF1_WHU show that the segmentation results of this method are better than the existing methods. Hence, our model is of great significance for practical cloud shadow segmentation. Full article

Laser cladding has unique advantages in improving the wear resistance of materials or workpiece surfaces. CeO₂ could play a role in promoting the flow of the molten pool and grain refinement during the laser cladding process, which is likely to further improve the wear resistance of the coating. In this work, CeO₂ was introduced into the MgAl₂O₄/Fe-based laser cladding coating on the surface of GCr15 steel. The effects of the CeO₂ content on the phase composition, microstructure, hardness, and wear resistance of the coatings were also systematically investigated. The results showed that the addition of CeO₂ enhanced the continuity of the coating and reduced the size of the MgAl₂O₄ particles, which was associated with the addition of CeO₂’s intensification of the melt pool flow. The metal grain size reduced and then increased as the CeO₂ content increased, whereas the hardness and wear resistance of the MgAl₂O₄/Fe-based coatings increased and then decreased. Compared with the MgAl₂O₄/Fe-based coating without CeO₂, the hardness of the MgAl₂O₄/Fe-based coating with 1.0 wt% CeO₂ increased by 10% and the wear rate decreased by 40%, which was attributed to the metal grain refinement and particle dispersion strengthening. Full article

The effects of solution treatment and annealing temperature on the microstructure and mechanical properties of a new TWIP steel that was alloyed from aluminum (Al), silicon (Si), vanadium (V), and molybdenum (Mo) elements were investigated by a variety of techniques such as microstructural characterization and room tensile testing. The austenite grain size grew slowly with the increase in annealing temperature. The relatively weak effect of the solution treatment and annealing temperature on the austenite grain size was attributed to the precipitation of MC and M₂C, which hindered the growth of the austenite grain. The plasticity of the TWIP steel in cold rolling and annealing after solution treatment was obviously higher than that in cold rolling and annealing without solution treatment. This was because the large-size precipitates redissolved in the matrix after solution treatment, which were not retained in the subsequently annealed structure. Through cold rolling and annealing at 800 °C after solution treatment, the prepared steel exhibited excellent strength and plasticity simultaneously, with a yield strength of 877 MPa, a tensile strength of 1457 MPa, and an elongation of 46.1%. The strength improvement of the designed TWIP steel was mainly attributed to the grain refinement and precipitation strengthening. Full article

The movement from regular lexicon to onomasticon, especially anthroponomasticon, is often mediated by cultural principles which may determine which concepts could normally be selected for the formation of personal names. Restrictive traditions have guiding principles making some concepts acceptable or not, and some names central or peripheral. In this paper, I discuss the principle of commemorability as gatekeeping the selection of concepts for the formation of personal names in Akan; and, having established the restrictiveness of the Akan anthroponomastic system, I identify the two considerations of honourability and preservability as making up the commemorability principle. The study is inductive, establishing the theory that explains the principles for the selection of appropriate concepts for the construction of personal names, and it relies on ethnographic resources including observation, interviews, and focus group discussions supported by name content analysis to generate the theory. The paper establishes that commemorability is founded on a general philosophy that upholds the societal, effort and perseverance, and social cognitive value in the selection of concepts for constructing personal names. Guided by these considerations, concepts are placed within a value ranking system to determine their ‘commemorability’, with items that rank as ‘honourable’ normally selected and processed as personal names. In the construction itself, there is a preference for the cognitive over the physical and the general beyond the specific, and there is an overriding preference for the use of general commemorability concepts which represent excellence, prominence, fullness, abundance, inexhaustibility, strength, endurance, and resilience, among others, which are used both as base-concepts for family names or as ‘amplifier’ concepts in the construction of extension names. Full article

Driven by environmental concerns, firms close to end-users are increasingly co-creating with customers for green product development within their supply chains. However, a challenge called “spillover” can hinder the incentive for green co-creation by these firms. This paper examines the spillover issue in a dual-channel structure, where downstream firms implement co-creation with customers for green product development. Our findings indicate that spillover from green investments can negatively impact the investing firm’s profits. However, in low-competition scenarios, spillover benefits the supplier and customers within the supply chain. Additionally, under specific circumstances, it can improve overall supply chain performance. Crucially, to safeguard the sustainability of green co-creation in supply chains and prevent detrimental co-destruction, we propose implementing revenue-sharing contracts that can generate Pareto improvements, benefiting all green supply chain members. As a result, unlike traditional intellectual property protection, which hinders spillover, this study offers an alternative strategy that is also somewhat complementary, promoting collaboration over restrictions to leverage the positive aspects of spillover. Full article

Hydroformylation of olefins is widely used in the chemical industry due to its versatility and the ability to produce valuable aldehydes with 100% atom economy. Herein, a hybrid phosphate promoter was found to efficiently promote rhodium-catalyzed hydroformylation of styrenes under remarkably mild conditions with high regioselectivities. Preliminary mechanistic studies revealed that the weak coordination between the Rhodium and the P=O double bond of this pentavalent phosphate likely induced exceptional reactivity and high ratios of branched aldehydes to linear products. Full article

Geological hazards are widely distributed, cause huge losses, and have always been the focus of attention for engineering and environmental geologists. Geological hazard evaluation is the basis of research and has important theoretical significance for preventing and controlling geological hazards. Therefore, geological hazard evaluation has become the focus of engineering and environmental geology. The question of how to build a universal index system model of geological hazard evaluation is an urgent problem that needs to be solved in geological hazard evaluation. Based on a large amount of previous research data, this paper takes landslide hazard as an example and systematically expounds the main problems that need to be solved in the current geological hazard evaluation from five aspects: basic concept, evaluation scope and accuracy, evaluation index system and evaluation criteria, evaluation method, and applicability of evaluation results. A landslide hazard assessment index system model is proposed, which applies to all regions, including all of the factors that may affect the formation of landslides. It is also hoped that this will be used as an example to establish various types of disaster evaluation and assessment systems. If the parameter has no value in the assessment process, it can be processed as 0. On this basis, further research is suggested from the perspectives of the geological hazard evaluation level, geological hazard evaluation theory, and method. To provide thoughts on and suggestions for geological hazard risk assessment method research, standard revision, investigation and evaluation, and risk management and control need to be considered. Full article

Biochar and beneficial microorganisms have been widely used in ecological agriculture. However, the impact of biochar loaded with microbes (BM) on plant growth remains to be understood. In this study, BM was produced by incubating pecan biochar with the bacterial strain N33, and the effects of BM on pecan growth and the microbial community in the rhizosphere were explored. BM application significantly enhanced the biomass and height of pecan plants. Meanwhile, BM treatment improved nutrient uptake in plants and significantly increased the chlorophyll, soluble sugars, and soluble proteins of plants. Furthermore, BM treatment improved the soil texture and environment. Finally, BM application substantially enhanced the diversity of soil fungi and bacteria as well as the relative abundances of the phyla Firmicutes and Chloroflexi, and families Bacillaceae and Paenibacillaceae, as shown by high-throughput sequencing. Together, this study clarified the growth-promotive effects of BM on pecan plants and suggested an alternative to synthetic fertilizers in their production. Full article

Migrant workers from rural China often leave their children at home to be raised by grandparents or other family members. This study explored the relationship between parents’ educational expectations, parental involvement, and the academic performance of left-behind children in China. A total of 19,487 student samples were obtained from the China Education Panel Survey (CEPS), and 5078 of these met the criteria for being considered as ‘left behind’ children. Results indicated: (1) a significant positive correlation between parents’ educational expectations and left-behind children’s academic achievement; (2) parental education involvement plays a partial mediating role between parents’ educational expectations and left-behind children’s academic performance; (3) a significant negative correlation between parental intellectual involvement and educational expectations of left-behind children; (4) parental management involvement was not significantly correlated with parents’ educational expectations and left-behind children’s academic performance; and (5) a significant positive correlation between parental emotional involvement and educational expectations of left-behind children. The findings highlight the important role of parental educational expectations and have implications for the improvement of educational outcomes in China. Full article

Cluster thinning has been widely applied in yield management and its effect on green leaf volatiles (GLVs) in wines has seldom been studied. GLVs are important flavor compositions for grapes and wines. This work aimed to investigate the impact of cluster thinning on these volatiles and their precursors in grapes and wines. Severe cluster thinning (CT1) and medium cluster thinning (CT2) were performed on Cabernet Sauvignon (Vitis vinifera L.) vines in two sites (G-farm and Y-farm) from Xinjiang province in the Northwest of China. The impact of cluster thinning treatments on the accumulation of GLVs and their precursors, long chain fatty acids (LCFAs) of grape berries and C₆ volatiles, in resulting wines was investigated. Multivariate analysis showed that cluster thinning treatments induced significant changes in fruit and wine composition in both farms. In Y-farm, medium cluster thinning (CT2) significantly increased the average cluster weight of harvested berries. Additionally, both cluster thinning treatments (CT1 and CT2) increased fatty acids in harvested berries and CT2 led to an increase in C₆ esters and a decrease in C₆ alcohols in the wines of Y-farm under the warmer and drier 2012 vintage. However, the effect of cluster thinning was likely negative in G-farm due to its wetter soil and excessive organic matter. The treatments may be applicable for local grape growers to improve viticultural practices for the more balanced vegetative and reproductive growth of Cabernet Sauvignon grapevines. This work also provided further knowledge on the regulation of fatty acids and the derived C₆ volatiles through the lipoxygenase (LOX) pathway. Full article

Demethylation inhibitors (DMIs), including prochloraz, are popular fungicides to control citrus postharvest pathogens such as Penicillium digitatum (green mold). However, many P. digitatum strains have developed prochloraz resistance, which decreases drug efficacy. Specific major facilitator superfamily (MFS) transporter gene mfs2, encoding drug-efflux pump protein MFS2, has been identified in P. digitatum strain F6 (PdF6) to confer fungal strain prochloraz resistance. However, except for the drug-efflux pump function of MFS2, other mechanisms relating to the Pdmfs2 are not fully clear. The present study reported a transcriptome investigation on the mfs2-defective P. digitatum strain. Comparing to the wild-type strain, the mfs2-defective strain showed 717 differentially expressed genes (DEGs) without prochloraz induction, and 1221 DEGs with prochloraz induction. The obtained DEGs included multiple isoforms of MFS transporter-encoding genes, ATP-binding cassette (ABC) transporter-encoding genes, and multidrug and toxic compound extrusion (MATE) family protein-encoding genes. Many of these putative drug-efflux pump protein-encoding genes had significantly lower transcript abundances in the mfs2-defective P. digitatum strain at prochloraz induction, as compared to the wild-type strain, including twenty-two MFS transporter-encoding genes (MFS1 to MFS22), two ABC transporter-encoding genes (ABC1 and ABC2), and three MATE protein-encoding genes (MATE1 to MATE3). The prochloraz induction on special drug-efflux pump protein genes in the wild-type strain was not observed in the mfs2-defective strain, including MFS21, MFS22, ABC2, MATE1, MATE2, and MATE3. On the other hand, the up-regulation of other drug-efflux pump protein genes in the mfs2-defective strain cannot recover the fungal prochloraz resistance, including MFS23, MFS26, MFS27, MFS31, MFS33, and ABC3 to ABC8. The functional enrichment of DEGs based on Kyoto Encyclopedia of Genes and Genomes (KEGG), Clusters of Orthologous Groups (COG), and euKaryotic Orthologous Groups (KOG) database resources suggested some essential contributors to the mfs2-relating prochloraz resistance, including ribosome biosynthesis-related genes, oxidative phosphorylation genes, steroid biosynthesis-related genes, fatty acid and lipid metabolism-related genes, and carbon- and nitrogen-metabolism-related genes. The results indicated that the MFS2 transporter might be involved in the regulation of multiple drug-efflux pump protein gene expressions and multiple metabolism-related gene expressions, thus playing an important role in developing P. digitatum prochloraz resistance. Full article

The application of artificial intelligence to point-of-care testing (POCT) disease detection has become a hot research field, in which breath detection, which detects the patient’s exhaled VOCs, combined with sensor arrays of convolutional neural network (CNN) algorithms as a new lung cancer detection is attracting more researchers’ attention. However, the low accuracy, high-complexity computation and large number of parameters make the CNN algorithms difficult to transplant to the embedded system of POCT devices. A lightweight neural network (LTNet) in this work is proposed to deal with this problem, and meanwhile, achieve high-precision classification of acetone and ethanol gases, which are respiratory markers for lung cancer patients. Compared to currently popular lightweight CNN models, such as EfficientNet, LTNet has fewer parameters (32 K) and its training weight size is only 0.155 MB. LTNet achieved an overall classification accuracy of 99.06% and 99.14% in the own mixed gas dataset and the University of California (UCI) dataset, which are both higher than the scores of the six existing models, and it also offers the shortest training (844.38 s and 584.67 s) and inference times (23 s and 14 s) in the same validation sets. Compared to the existing CNN models, LTNet is more suitable for resource-limited POCT devices. Full article

The hydrogenation of carbon monoxide (CO) offers a promising avenue for reducing air pollution and promoting a cleaner environment. Moreover, by using suitable catalysts, CO can be transformed into valuable hydrocarbons. In this study, we elucidate the mechanistic aspects of the catalytic conversion of CO to hydrocarbons on the surface of manganese-doped graphene oxide (Mn-doped GO), where the GO surface includes one OH group next to one Mn adatom. To gain insight into this process, we have employed calculations based on the density functional theory (DFT) to explore both the thermodynamic properties and reaction energy barriers. The Mn adatoms were found to significantly activate the catalyst surface by providing stronger adsorption geometries. Our study concentrated on two mechanisms for CO hydrogenation, resulting in either CH₄ production via the reaction sequence CO → HCO → CH₂O → CH₂OH → CH₂ → CH₃ → CH₄ or CH₃OH formation through the CO → HCO → CH₂O → CH₂OH → CH₃OH pathway. The results reveal that both products are likely to be formed on the Mn-doped GO surface on both thermodynamic grounds and considering the reaction energy barriers. Furthermore, the activation energies associated with each stage of the synthesis show that the conversion reactions of CH₂ + OH → CH₃ + O and CH₂O + OH → CH₂OH + O with energy barriers of 0.36 and 3.86 eV are the fastest and slowest reactions, respectively. The results also indicate that the reactions: CH₂OH + OH → CH₂ + O+H₂O and CH₂OH + OH → CH₃OH + O are the most exothermic and endothermic reactions with reaction energies of −0.18 and 1.21 eV, respectively, in the catalytic pathways. Full article

The Hetian Qing donkey is an excellent local donkey breed in Xinjiang. It is of great significance to accelerate breeding and the speed of breeding and rejuvenation, as well as to understand the genetic basis of the strategies and population. This study collected a total of 4 male donkeys and 28 female donkeys. It then obtained genotype data through Simplified Genomic Sequencing (GBS) technology for data analysis. The results detected a total of 55,399 SNP loci, and the genotype detection rate of individuals was ≥90%. A total of 45,557 SNP loci were identified through quality control, of which 95.5% were polymorphic. The average minimum allele frequency was 0.250. The average observed heterozygosity was 0.347. The average expected heterozygosity was 0.340. The average IBS (state homologous) genetic distance was 0.268. ROH: 49 (homozygous fragments), with 73.47% of the length between 1 and 5 Mb. The average per-strip ROH length was 1.75 Mb. The mean inbreeding coefficient was 0.003. The 32 Hetian green donkeys could be divided into six families. The number of individuals in each family is significant. To sum up, the Hetian Qing donkey population has low heterozygosity, few families, and large differences in the number of individuals in each family, which can easily cause a loss of genetic diversity. In the subsequent process of seed protection, seed selection should be conducted according to the divided pedigree to ensure the long-term protection of the genetic resources of Hetian green donkeys. Full article

The unclear pathogenesis of chronic itch originating from several systemic disorders poses challenges to clinical intervention. Recent studies recapitulate the spinal neurocircuits associated with neuroinflammation and synaptic plasticity responsible for pruriceptive sensations. The resolution of nociception and inflammation by Annexin 1 (ANXA1) has been identified. Given that pain and itch share many neural mechanisms, we employed two mice models of chronic itch to study the underlying targets and therapeutic potential of ANXA1, comprising allergic contact dermatitis-induced itch and cholestatic itch. Herein, we report that spinal expression of ANXA1 is down-regulated in mice with dermatitis-induced itch and cholestatic itch. Repetitive injections of ANXA1-derived peptide Ac2-26 (intrathecal, 10 μg) reduce itch-like scratching behaviors following dermatitis and cholestasis. Single exposure to Ac2-26 (intrathecal, 10 μg) alleviates the established itch phenotypes. Moreover, systemic delivery of Ac2-26 (intravenous, 100 μg) is effective against chronic dermatitis-induced itch and cholestatic itch. Strikingly, Ac2-26 therapy inhibits transferrin receptor 1 over-expression, iron accumulation, cytokine IL-17 release and the production of its receptor IL-17R, as well as astrocyte activation in the dorsal horn of spinal cord in mouse with dermatitis and cholestasis. Pharmacological intervention with iron chelator deferoxamine impairs chronic itch behaviors and spinal iron accumulation after dermatitis and cholestasis. Also, spinal IL-17/IL-17R neutralization attenuates chronic itch. Taken together, this current research indicates that ANXA1 protects against the beginning and maintenance of long-term dermatitis-induced itch and cholestatic itch, which may occur via the spinal suppression of IL-17-mediated neuroinflammation, astrocyte activation and iron overload. Full article

Effective agricultural management in maize production operations starts with the early quantification of seedlings. Accurately determining plant presence allows growers to optimize planting density, allocate resources, and detect potential growth issues early on. This study provides a comprehensive analysis of the performance of various object detection models in maize production, with a focus on the effects of planting density, growth stages, and flight altitudes. The findings of this study demonstrate that one-stage models, particularly YOLOv8n and YOLOv5n, demonstrated superior performance with AP₅₀ scores of 0.976 and 0.951, respectively, outperforming two-stage models in terms of resource efficiency and seedling quantification accuracy. YOLOv8n, along with Deformable DETR, Faster R-CNN, and YOLOv3-tiny, were identified for further examination based on their performance metrics and architectural features. The study also highlights the significant impact of plant density and growth stage on detection accuracy. Increased planting density and advanced growth stages (particularly V6) were associated with decreased model accuracy due to increased leaf overlap and image complexity. The V2–V3 growth stages were identified as the optimal periods for detection. Additionally, flight altitude negatively affected image resolution and detection accuracy, with higher altitudes leading to poorer performance. In field applications, YOLOv8n proved highly effective, maintaining robust performance across different agricultural settings and consistently achieving rRMSEs below 1.64% in high-yield fields. The model also demonstrated high reliability, with Recall, Precision, and F1 scores exceeding 99.00%, affirming its suitability for practical agricultural use. These findings suggest that UAV-based image collection systems employing models like YOLOv8n can significantly enhance the accuracy and efficiency of seedling detection in maize production. The research elucidates the critical factors that impact the accuracy of deep learning detection models in the context of corn seedling detection and selects a model suited for this specific task in practical agricultural production. These findings offer valuable insights into the application of object detection technology and lay a foundation for the future development of precision agriculture, particularly in optimizing deep learning models for varying environmental conditions that affect corn seedling detection. Full article

Correct nutrition and diet are directly correlated with mental health, functions of the immune system, and gut microbiota composition. Diets with a high content of some nutrients, such as fibers, phytochemicals, and short-chain fatty acids (omega-3 fatty acids), seem to have an anti-inflammatory and protective action on the nervous system. Among nutraceuticals, supplementation of probiotics and omega-3 fatty acids plays a role in improving symptoms of several mental disorders. In this review, we collect data on the efficacy of nutraceuticals in patients with schizophrenia, autism spectrum disorders, major depression, bipolar disorder, and personality disorders. This narrative review aims to provide an overview of recent evidence obtained on this topic, pointing out the direction for future research. Full article

This work presents a comprehensive analysis of the adsorption of selected aromatic organic compounds on activated carbons. Both the equilibrium and kinetics of adsorption were studied using UV–Vis spectrophotometry. The influence of a number of factors: pH, contact time, presence of an accompanying substance, adsorbate concentration, as well as the mass and size of adsorbent grains, on the adsorption process from aqueous solutions was investigated. Phenol, 2-nitrophenol, 3-nitrophenol, 4-nitrophenol and methylene blue (as an accompanying substance) were selected as adsorbates. GAC 1240W and RIAA activated carbons were used as adsorbents. The equilibrium data were analyzed using the generalized Langmuir isotherm equation (R² = 0.912–0.996). Adsorption rate data were fitted using a multi-exponential kinetic equation (1 − R² = (1.0 × 10⁻⁶)–(8.2 × 10⁻⁴)). As an additional parameter, the half-time was also used to present the influence of selected factors on the adsorption kinetics. An increase in the amount of adsorption was demonstrated with increasing contact time as well as with decreasing solution pH and adsorbent grain size. For selected systems, an increase in the adsorption rate was observed with increasing adsorbate concentration, adsorbent mass and at lower pH values. In some cases, the presence of an accompanying substance also resulted in an increase in adsorption kinetics. In the tested experimental systems, optimal conditions for adsorption were established (T = 298 K, pH = 2, contact time: 7 days, grain diameter: >0.5 mm and the ratio of the mass of the adsorbent to the volume of the adsorbate solution: 1 g/L). Additionally, the acid–base properties (potentiometric titration), morphology (SEM) and structure (TEM) of the used adsorbents were also examined. Full article

Coffee is not merely a refreshing beverage but also invigorates people, provides relaxation, contributes to human health, and fosters closer social connections. Coffee is one of the most widely consumed beverages worldwide and the most traded commercial commodity. Moreover, the rapid development of the Vietnamese coffee industry caused some concerns due to its insufficient performance and the fierce competition within the industry. It is significant to establish an efficient supply network; notwithstanding, supplier selection has always been a challenge for companies. Therefore, this paper employs a hybrid model to determine the supplier selection criteria, a vital factor for a manufacturer under practical operating conditions. Firstly, a combined model of Grey forecasting and the Grey Fourier series is applied to forecast future rainfall and temperature data for six consecutive years. Secondly, based on the criteria, strategies, and buyer requirements, the single-objective linear programming model helps identify the outperformed suppliers. The results found that prices and location change are determinants of supplier selection, and supplier shortage is an enormous barrier for the industry. In this study, these price forecasts allow supply chain management to make informed decisions about inventory levels, transportation routes, and resource allocation to ensure smooth operation and optimize coffee supply chain management. Full article

The core of sustainable public procurement lies in its ability to stem uneconomical public expenditures that waste taxpayer money and stifle social trust and development. The external audit of public procurement proves problematic since current research fails to provide sufficient empirical studies aimed at identifying procurement fraud. The development of online portals with embedded e-procurement solutions, along with the big data revolution, open new horizons and allow us to reveal trends otherwise impossible to spot, such as transactions achieved in an exclusive commercial relationship, in which a vendor engages only with a single public entity. By using innovative data acquisition techniques, our research encompasses 2.25 million online direct public procurement procedures conducted in 2023 using the Romanian portal for public procurement, totaling EUR 3.22 billion. By aggregating databases obtained from various public sources, our analysis achieved remarkable granularity, using over 112 million data elements—50 pertaining to each transaction. Research results indicate a unique sub-population of public procurement procedures—those conducted with “in-house” vendors totaling 14.28% of all direct public acquisitions and which is significantly differentiated along the entire list of analyzed criteria—financial, geographical, statistical, or risk-wise—illustrating a troubling phenomenon: possible gerrymandering of the online public procurement landscape, which, at least in theory, resembles a perfect market, by cultivating preferential commercial relations, thus affecting the legality, regularity, and economical aspects of public procurement. Full article