Empirical and simulated investigation of the solid waste reverse supply chain: A complex adaptive system perspective

Solid waste is increasing rapidly worldwide. In this study, the solid waste (household waste, construction and demolition waste and industrial waste) management systems are treated as reverse supply chain to analyze the critical operational issues based on complex adaptive system theory. At the single-layer, the complexity of the various nodes at a layer arises from rational decision-making and behavioral heterogeneity. The solid waste generation layer is employed as an example to investigate the complexity of node behavioral decisions. Regression analysis results reveal that both endogenous (Attitude, Subjective norm, and Perceived behavioral control) and exogenous factors (Economic incentive, Government supervision, Technical support) positively influence sorting behavior. The effect of Economic incentive (β=0.327P<0.001) and Attitude (β=0.249P<0.001) on sorting behavior are the largest. In the multi-layer system, different layers communicate with each other through the material and financial flows and have cross-layer impacts. An agent-based model is developed to investigate the multi-layer feedforward influence mechanism of changes in key layers (e.g., sorting rate, disposal rate) and the material and financial flows adaptive adjustment direction of the solid waste reverse supply chain. High rate of participation and accuracy of source sorting can shorten material flow paths and reduce storage and transportation costs. The increase in disposal rate encourages the transition of solid waste from backfill to resource utilization. This study provides a practice reference for solid waste reverse supply chain and related enterprises managers.

An overview of floral regulatory genes in annual and perennial plants

The floral initiation in angiosperms is a complex process influenced by endogenous and exogenous signals. With this approach, we aim to provide a comprehensive review to integrate this complex floral regulatory process and summarize the regulatory genes and their functions in annuals and perennials. Seven primary paths leading to flowering have been discovered in Arabidopsis under several growth condition that include; photoperiod, ambient temperature, vernalization, gibberellins, autonomous, aging and carbohydrates. These pathways involve a series of interlinked signaling pathways that respond to both internal and external signals, such as light, temperature, hormones, and developmental cues, to coordinate the expression of genes that are involved in flower development. Among them, the photoperiodic pathway was the most important and conserved as some of the fundamental loci and mechanisms are shared even by closely related plant species. The activation of floral regulatory genes such as FLC, FT, LFY, and SOC1 that determine floral meristem identity and the transition to the flowering stage result from the merging of these pathways. Recent studies confirmed that alternative splicing, antisense RNA and epigenetic modification play crucial roles by regulating the expression of genes related to blooming. In this review, we documented recent progress in the floral transition time in annuals and perennials, with emphasis on the specific regulatory mechanisms along with the application of various molecular approaches including overexpression studies, RNA interference and Virus-induced flowering. Furthermore, the similarities and differences between annual and perennial flowering will aid significant contributions to the field by elucidating the mechanisms of perennial plant development and floral initiation regulation.

Association of exogenous factors with molecular epidemiology of Staphylococcus aureus in human oral cavity

The frequency of Staphylococcus aureus strains associated with oral cavity microbiota has prodigious consideration. Although S. aureus has been reflected as an ephemeral member of the human oral cavity microbiota, the isolation, identification, and characterization of S. aureus is important. The present study aimed to characterize S. aureus strains from the oral cavity microflora, isolation of S. aureus from the human oral cavity microbiota, and demographic information of the participants to evaluate exogenous factors associated with the presence of S. aureus and their genetic analysis linkage with different factors. The method used in this study is the isolation of oral cavity microbiomes using sheep blood agar and Mannitol salt agar. We performed antibiotic profiling with various antibiotics and genetic analysis utilizing gene-specific primers for specific genes, including nuc, mecA, pvl, agr, and coa. A significant number of S. aureus isolates were found in the oral cavity of humans 18/84 (21.42%), and all 18 strains tested positive for the confirmatory nuc gene. Antibiotic resistance-conferring gene mecA was positive in 10 (55.6%) isolates. It was found that the occurrence of pvl, agr, and coagulase (coa) genes was 9 (50%), 6 (33.33%), and 10 (55.6%), respectively. The genetic analysis reported that significant associations were present between male and mecA gene (P = 0.03) and coa (P = 0.03), smokers with the occurrence of mecA (P = 0.02), agr (P = 0.048) and coa (P = 0.02) genes. Likewise, the association of antibiotic usage was significantly found with mecA (P = 0.02), coa (P = 0.02); however, the individuals who have taken orthodontic treatment recently have a significant association with agr (P = 0.017). The use of mouth rinse was significantly associated with the prevalence of the pvl gene (P = 0.01), and tooth brushing frequency and inflammation of the buccal cavity were also statistically significant in relation to pvl gene prevalence (P = 0.02, 0.00, respectively). Moreover, calories and weight-controlled diet were significantly associated with mecA, agr, and highly significant with coa (P = 0.02, 0.048, 0.000), so all P < 0.05, and no significant association was found between the socioeconomic status of individuals with aforementioned analyzed genes.

A systematic methodology for the robust quantification of energy efficiency at wastewater treatment plants featuring Data Envelopment Analysis

This article examines the potential benefits of using Data Envelopment Analysis (DEA) for conducting energy-efficiency assessment of wastewater treatment plants (WWTPs). WWTPs are characteristically heterogeneous (in size, technology, climate, function …) which limits the correct application of DEA. This paper proposes and describes the Robust Energy Efficiency DEA (REED) in its various stages, a systematic state-of-the-art methodology aimed at including exogenous variables in nonparametric frontier models and especially designed for WWTP operation. In particular, the methodology systematizes the modelling process by presenting an integrated framework for selecting the correct variables and appropriate models, possibly tackling the effect of exogenous factors. As a result, the application of REED improves the quality of the efficiency estimates and hence the significance of benchmarking. For the reader's convenience, this article is presented as a step-by-step guideline to guide the user in the determination of WWTPs energy efficiency from beginning to end. The application and benefits of the developed methodology are demonstrated by a case study related to the comparison of the energy efficiency of a set of 399 WWTPs operating in different countries and under heterogeneous environmental conditions.

Descriptive epidemiology and risk factors of primary central nervous system tumors: Current knowledge

Although comparisons are difficult due to differences in methodologies, the annual incidence rates of central nervous system (CNS) tumors range from 8.5 to 21.4/100,000 population according to cancer registries, with a predominance of neuroepithelial tumors in men and meningiomas in women. An increase in the incidence of CNS tumors has been observed during the past decades in several countries. It has been suggested that this trend could be due to aging of the population, and improvements in diagnostic imaging and healthcare access, but these factors do not explain differences in incidence by gender and histological subtypes. Several etiological hypotheses related to intrinsic (sociodemographic, anthropometric, hormonal, immunological, genetic) and exogenous (ionizing radiation, electromagnetic fields, diet, infections, pesticides, drugs) risk factors have led to analytical epidemiological studies to establish relationships with CNS tumors. The only established environmental risk factor for CNS tumors is ionizing radiation exposure. However, for other risk factors, studies have been inconsistent and inconclusive due to systematic differences in study design and difficulties in accurately measuring exposures. Thus, the etiology of CNS tumors is complex and may involve several genetic and/or environmental factors that may act differently according to histological subtype.