A Fuzzy Credibility-Based Chance-Constrained Optimization Model for Multiple-Objective Aggregate Production Planning in a Supply Chain under an Uncertain Environment

In this study, a Multiple-Objective Aggregate Production Planning (MOAPP) problem in a supply chain under an uncertain environment is developed. The proposed model considers simultaneously four different conflicting objective functions. To solve the proposed Fuzzy Multiple-Objective Mixed Integer Linear Programming (FMOMILP) model, a hybrid approach has been developed by combining Fuzzy Credibility-based Chance-constrained Programming (FCCP) and Fuzzy Multiple-Objective Programming (FMOP). The FCCP can provide a credibility measure that indicates how much confidence the decision-makers may have in the obtained optimal solutions. In addition, the FMOP, which integrates an aggregation function and a weight-consistent constraint, is capable of handling many issues in making decisions under multiple objectives. The consistency of the ranking of objective’s important weight and satisfaction level is ensured by the weight-consistent constraint. Various compromised solutions, including balanced and unbalanced ones, can be found by using the aggregation function. This methodology offers the decision makers different alternatives to evaluate against conflicting objectives. A case experiment is then given to demonstrate the validity and effectiveness of the proposed formulation model and solution approach. The obtained outcomes can assist to satisfy the decision-makers’ aspiration, as well as provide more alternative strategy selections based on their preferences

OPTICAL BISTABILITY IN A DEGENERATE TWO-LEVEL EIT MEDIUM UNDER THE INFLUENCE OF AN EXTERNAL MAGNETIC FIELD: AN ANALYTICAL APPROACH

We investigate the behavior of optical bistability in a degenerate two-level atomic medium using an external magnetic field to separate the lower level into two distinct levels that both connect to an upper level by the probe and coupling laser fields. Based on analytical solutions, the absorption spectrum and behavior of optical bistability in an electromagnetically induced transparency regime under an external magnetic field are investigated. By controlling the external magnetic field, we find that the appearance and disappearance of the optical bistability can be easily controlled according to the strength of the magnetic field in the transparent window domain. Furthermore, the effects of the intensity of the coupling laser field and the parameters of the system on the behavior of optical bistability are also considered. The proposed model is useful for applications in all-optical switches and magneto-optic storage devices.We investigate the behavior of optical bistability in a degenerate two-level atomic medium using an external magnetic field to separate the lower level into two distinct levels that both connect to an upper level by the probe and coupling laser fields. Based on analytical solutions, the absorption spectrum and behavior of optical bistability in an electromagnetically induced transparency regime under an external magnetic field are investigated. By controlling the external magnetic field, we find that the appearance and disappearance of the optical bistability can be easily controlled according to the strength of the magnetic field in the transparent window domain. Furthermore, the effects of the intensity of the coupling laser field and the parameters of the system on the behavior of optical bistability are also considered. The proposed model is useful for applications in all-optical switches and magneto-optic storage devices

On the Impact of Dataset Size: A Twitter Classification Case Study

The recent advent and evolution of deep learning models and pre-trained embedding techniques have created a breakthrough in supervised learning. Typically, we expect that adding more labeled data improves the predictive performance of supervised models. On the other hand, collecting more labeled data is not an easy task due to several difficulties, such as manual labor costs, data privacy, and computational constraint. Hence, a comprehensive study on the relation between training set size and the classification performance of different methods could be essentially useful in the selection of a learning model for a specific task. However, the literature lacks such a thorough and systematic study. In this paper, we concentrate on this relationship in the context of short, noisy texts from Twitter. We design a systematic mechanism to comprehensively observe the performance improvement of supervised learning models with the increase of data sizes on three well-known Twitter tasks: sentiment analysis, informativeness detection, and information relevance. Besides, we study how significantly better the recent deep learning models are compared to traditional machine learning approaches in the case of various data sizes. Our extensive experiments show (a) recent pre-trained models have overcome big data requirements, (b) a good choice of text representation has more impact than adding more data, and (c) adding more data is not always beneficial in supervised learning

Small-scale commercial chicken production: A risky business for farmers in the Mekong Delta of Vietnam.

Small-scale farming of meat chicken flocks using local native breeds contributes to the economy of many rural livelihoods in Vietnam and many other low- and middle-income countries (LMICs). These systems are also the target of high levels of antimicrobial use (AMU); however, little is known about the profitability and sustainability of such systems. Since small-scale farms are commercial enterprises, this knowledge is essential to develop successful strategies to curb excessive AMU. Using longitudinal data from 203 small-scale (100-2,000 heads) native chicken flocks raised in 102 randomly selected farms in Dong Thap province (Mekong Delta, Vietnam), we investigated the financial and economic parameters of such systems and the main constraints to their sustainability. Feed accounted for the largest financial cost (flock median 49.5 % [Inter-quartile range (IQR) 41.5-61.8 %]) of total costs, followed by day-old-chicks (DOCs) (median 30.3 % [IQR 23.2-38.4 %]), non-antimicrobial health-supporting products (median 7.1 % [IQR 4.7-10.5 %]), vaccines (median 3.1 % [IQR 2.2-4.8 %]), equipment (median 1.9 % [IQR 0.0-4.9 %]) and antimicrobials (median 1.9 % [IQR 0.7-3.6 %]). Excluding labor costs, farmers achieved a positive return on investment (ROI) from 120 (59.1 %) flocks, the remainder generating a loss (median ROI 124 % [IQR 36-206 %]). Higher ROI was associated with higher flock size and low mortality. There was no statistical association between use of medicated feed and flock mortality or chicken bodyweight. The median daily income per person dedicated to raising chickens was 202,100 VND, lower than alternative rural labor activities in the Mekong Delta. In a large proportion of farms (33.4 %), farmers decided to stop raising chickens after completing one cycle. Farmers who dropped off chicken production purchased more expensive feed (in 1000 VND per kg): 11.1 [10.6-11.5] vs. 10.8 [10.4-11.3] for farms that continued production (p = 0.039), and experienced higher chicken mortality (28.5 % [12.0-79.0 %] vs. 16 [7.5-33.0 %]; p = 0.004). The rapid turnover of farmers raising chickens in such systems represents a challenge to the uptake of messages on appropriate AMU and chicken health. To ensure sustainability of small-scale commercial systems, advisory services need to be available to farmers as they initiate new flocks, and support them in the early stages to help overcome their limited experience and skills. This targeted approach would support profitability whilst reducing risk of emergence of AMR and infectious disease from these systems

Simultaneous quantitative analyses of Tanshinone I, Cryptotanshinone, and Tanshinone IIA in Danshen (Salvia miltiorrhiza Bunge) cultivated in Vietnam using LC-MS/MS

74-83By using chromatography methods, the principal compounds tanshinon I, cryptotanshinone, tanshinone IIA were isolated from danshen (Salvia miltiorrhiza Bunge). Based on the spectroscopic data (1H-NMR, 13C-NMR and ESI-MS mass spectra), the structures were determined. The compound was purified (purity > 99.8%) by Agilent 218 purification system, which was used as the standard for analyzing tanshinon I, cryptotanshinone, tanshinone IIA in six samples. In this study, one LC-MS/MS method was developed for the simultaneous quantitative determination of three bioactive principles, tanshinone I, cryptotanshinone, and tanshinone IIA in Radix Salviae miltiorrhizae (RSM, the root of S. miltiorrhiza). The quantification of these diterpenoids is based on the fragments of [M+H]+ under collision-activated conditions and in selected reaction monitoring (SRM) mode. The quantitative method is validated by determining the mean recovery from fortified samples of tanshinone I, cryptotanshinone, and tanshinone IIA as higher than 98%. The established method is successfully applied to the quality assessment of six batches of RSM samples collected from different regions of Vietnam. The results show that Lam Dong sample has the highest tanshinone I content (4.4286±0.0009 µg/mg), meanwhile Muong Long sample has the lowest (1.2717±0.0013µg/mg). Lam Dong sample has the highest cryptotanshinone content (8.1589±0.0006 µg/mg), whereas Guangxi-China sample has the lowest (2.8630±0.0008 µg/mg). Ha Giang sample has the highest tanshinone IIA content (13.0252±0.0004 µg/mg), whereas Muong Long sample has the lowest (3.8278±0.0003 µg/mg)

Assessment of Drivers of Antimicrobial Usage in Poultry Farms in the Mekong Delta of Vietnam: A Combined Participatory Epidemiology and Q-Sorting Approach

In the Mekong Delta of Vietnam, poultry farmers use high amounts of antimicrobials, but little is known about the drivers that influence this usage. We aimed to identify these drivers using a novel approach that combined participatory epidemiology (PE) and Q-sorting (a methodology that allows the analysis of the subjectivity of individuals facing a common phenomenon). A total of 26 semi-structured collective interviews were conducted with 125 farmers representative of the most common farming systems in the area (chickens, meat ducks, and mobile grazing ducks), as well as with 73 farmers' advisors [veterinarians, veterinary drug shop owners, and government veterinarians/commune animal health workers (CAHWs)] in five districts of Dong Thap province (Mekong Delta). Through these interviews, 46 statements related to the antimicrobials' perceived reliability, costs, and impact on flock health were created. These statements were then investigated on 54 individuals (28 farmers and 26 farmers' advisors) using Q-sorting interviews. Farmers generally indicated a higher propensity for antimicrobial usage (AMU) should their flocks encounter bacterial infections (75.0–78.6%) compared with viral infections (8.3–66.7%). The most trusted sources of advice to farmers were, in decreasing order: government veterinarian/CAHWs, their own knowledge/experience, veterinary drug shop owners, and sales persons from pharmaceutical and feed companies. The highest peak of AMU took place in the early phase of the production cycle. Farmers and their advisors showed considerable heterogeneity of attitudes with regards to AMU, with, respectively, four and three discourses representing their views on AMU. Overall, farmers regarded the cost of AMU cheaper than other disease management practices implemented on their farms. However, they also believed that even though these measures were more expensive, they would also lead to more effective disease prevention. A key recommendation from this finding would be for the veterinary authorities to implement long-term sustainable training programs aiming at reducing farmers' reliance on antimicrobials

Simultaneous quantitative analyses of Tanshinone I, Cryptotanshinone, and Tanshinone IIA in Danshen (Salvia miltiorrhiza Bunge) cultivated in Vietnam using LC-MS/MS

By using chromatography methods, the principal compounds tanshinon I, cryptotanshinone, tanshinone IIA were isolated from danshen (Salvia miltiorrhiza Bunge). Based on the spectroscopic data (1H-NMR, 13C-NMR and ESI-MS mass spectra), the structures were determined. The compound was purified (purity > 99.8%) by Agilent 218 purification system, which was used as the standard for analyzing tanshinon I, cryptotanshinone, tanshinone IIA in six samples. In this study, one LC-MS/MS method was developed for the simultaneous quantitative determination of three bioactive principles, tanshinone I, cryptotanshinone, and tanshinone IIA in Radix Salviae miltiorrhizae (RSM, the root of S. miltiorrhiza). The quantification of these diterpenoids is based on the fragments of [M+H]+ under collision-activated conditions and in selected reaction monitoring (SRM) mode. The quantitative method is validated by determining the mean recovery from fortified samples of tanshinone I, cryptotanshinone, and tanshinone IIA as higher than 98%. The established method is successfully applied to the quality assessment of six batches of RSM samples collected from different regions of Vietnam. The results show that Lam Dong sample has the highest tanshinone I content (4.4286±0.0009 µg/mg), meanwhile Muong Long sample has the lowest (1.2717±0.0013µg/mg). Lam Dong sample has the highest cryptotanshinone content (8.1589±0.0006 µg/mg), whereas Guangxi-China sample has the lowest (2.8630±0.0008 µg/mg). Ha Giang sample has the highest tanshinone IIA content (13.0252±0.0004 µg/mg), whereas Muong Long sample has the lowest (3.8278±0.0003 µg/mg)