Supply Chain Optimization and Economic Analysis of Using Industrial Spent Microbial Biomass (SMB) in Agriculture

This thesis uses a mixed integer program to minimize the transport and storage cost of delivering spent microbial biomass (SMB), a bio-coproduct resulting from the production of 1,3-propanediol, to farm fields as a soil amendment and fertilizer substitute. The case study examines focuses on a bioprocessing facility and corn production in East Tennessee. The results indicate on-farm storage of SMB minimizes transport and storage costs of the material. A one percent decrease in the moisture content of SMB results in less than five percent decrease in the total transport and storage costs. Future research should investigate farmers\u27 willingness to adopt the practice, cost sharing design, and to apply SMB to other crop production

IMPROVING IRRIGATION WATER ALLOCATION EFFICIENCY USING ALTERNATIVE POLICY OPTIONS IN EGYPT

This study provides an empirical perspective on alternative irrigation policies for allocating limited water to agricultural production in Egypt. Positive mathematical programming is used for model calibration. Three policy options for Egypt are tested: water pricing, water complementary input factor taxes, and output taxes. The results of the research show that: 1) water pricing needs to be much higher than the recovery cost in order to be effective in limiting irrigation water use; 2) at a higher tax rate, fertilizer and energy taxes are effective in reducing the irrigation water demand while maintaining adequate welfare levels; 3) a pesticide tax is less effective than fertilizer or energy taxes; and 4) an output tax on sugar cane and rice would decrease irrigation water demand substantially while allocating land to other crops which are less water intensive and have higher market values.Resource /Energy Economics and Policy,

Risk and Return for Bioenergy Crops under Alternative Contracting Arrangements

This study evaluated the potential to supply biomass feedstocks under alternative contract arrangements for a northwest Tennessee 2,400 acre grain farm. The four potential types of contracts analyzed in this study offer different levels of biomass price, yield, and production cost risk sharing between the representative farm and the processor.Farm Management, Resource /Energy Economics and Policy,

Strategic Policy Options to Improve Irrigation Water Allocation Efficiency: Analysis on Egypt and Morocco

For a number of reasons government the world over have been unwilling to use water pricing to achieve water use efficiency. This research addresses questions of what policy alternatives to water pricing might improve irrigation water allocation efficiency. An empirical framework is provided to compare irrigation policies for allocating scarce water to agricultural production in Egypt and Morocco. Partial equilibrium agricultural sector models specific to Egypt and Morocco were employed for policy tests. Positive Mathematical Programming (PMP) was used to calibrate the models. Water pricing policy, water complementary input factor tax policy, and output tax policy are tested. Results suggest that effective policy depends on the social, economic, and environmental contexts of specific regions. The results for both countries demonstrate that some of the alternative irrigation policies can work towards directing cropping decisions to less water intensive crops and also generating revenues for governments in situations where governments choose not to price water.Resource /Energy Economics and Policy,

Biosensing Technologies for Mycobacterium tuberculosis Detection: Status and New Developments

Biosensing technologies promise to improve Mycobacterium tuberculosis (M. tuberculosis) detection and management in clinical diagnosis, food analysis, bioprocess, and environmental monitoring. A variety of portable, rapid, and sensitive biosensors with immediate “on-the-spot” interpretation have been developed for M. tuberculosis detection based on different biological elements recognition systems and basic signal transducer principles. Here, we present a synopsis of current developments of biosensing technologies for M. tuberculosis detection, which are classified on the basis of basic signal transducer principles, including piezoelectric quartz crystal biosensors, electrochemical biosensors, and magnetoelastic biosensors. Special attention is paid to the methods for improving the framework and analytical parameters of the biosensors, including sensitivity and analysis time as well as automation of analysis procedures. Challenges and perspectives of biosensing technologies development for M. tuberculosis detection are also discussed in the final part of this paper

Enhanced DCT-OFDM system with index modulation

Discrete cosine transform (DCT) based orthogonal frequency division multiplexing (OFDM), which has double number of subcarrier compared to the classic discrete fourier transform (DFT) based OFDM (DFT-OFDM) at the same bandwidth, is a promising high spectral efficiency multicarrier techniques for future wireless communication. In this paper, an enhanced DCT-OFDM with index modulation (IM) (EDCT-OFDM-IM) is proposed to further exploit the benefits of the DCT-OFDM and IM techniques. To be more specific, a pre-filtering method based DCT-OFDM-IM transmitter is first designed and the non-linear maximum likelihood (ML) is developed for our EDCT-OFDM-IM system. Moreover, the average bit error probability (ABEP) of the proposed EDCT-OFDM-IM system is derived, which is confirmed by our simulation results. Both simulation and theoretical results are shown that the proposed EDCT-OFDM-IM system exhibits better bit error rate (BER) performance over the conventional DFT-OFDM-IM and DCT-OFDM-IM counterparts

Index Modulation Assisted DCT-OFDM with Enhanced Transceiver Design

An index modulation (IM) assisted Discrete Cosine Transform based Orthogonal Frequency Division Multiplexing (DCT-OFDM) with Enhanced Transmitter Design (termed as EDCT-OFDM-IM) is proposed. It amalgamates the concept of Discrete Cosine Transform assisted Orthogonal Frequency Division Multiplexing (DCT-OFDM) and Index Modulation (IM) to exploit the design freedom provided by the double number of available subcarrier under the same bandwidth. In the proposed EDCT-OFDM-IM scheme, the maximum likelihood (ML) detector used for symbol bits and index bits recovering is derived and the sophisticated designing guidelines for EDCT-OFDM-IM are provided. Based on the derived pairwise error event probability, a theoretical upper bound on the average bit-error probability (ABEP) of EDCT-OFDM-IM is provided over multipath fading channels. Furthermore, the maximum peak-to-average power ratio (PAPR) of our proposed EDCT-OFDM-IM scheme is derived and compared to than the general Discrete Fourier Transform (DFT) based OFDM-IM counterpart

Normal Red Blood Cell Count Reference Values in Chinese Presenile Women Given by Geographical Area

Background/PurposeWe aimed to standardize the normal reference value of red blood cell (RBC) counts in Chinese presenile women using an underlying scientific basis.MethodsThis research was conducted to study the relationship between the normal reference value of 31,405 RBC samples from presenile women in eight different geographical areas in China. RBC counts were determined using a microscopic counting method.ResultsThere was a significant correlation between geographical factors and the normal reference RBC value in presenile women (F = 187.82, p = 0.000). Using stepwise regression analysis, one regression equation was obtained.ConclusionIf geographical values are obtained in a certain area, the normal RBC reference value in presenile women in this area can be obtained using the regression equation

G2PTL: A Pre-trained Model for Delivery Address and its Applications in Logistics System

Text-based delivery addresses, as the data foundation for logistics systems, contain abundant and crucial location information. How to effectively encode the delivery address is a core task to boost the performance of downstream tasks in the logistics system. Pre-trained Models (PTMs) designed for Natural Language Process (NLP) have emerged as the dominant tools for encoding semantic information in text. Though promising, those NLP-based PTMs fall short of encoding geographic knowledge in the delivery address, which considerably trims down the performance of delivery-related tasks in logistic systems such as Cainiao. To tackle the above problem, we propose a domain-specific pre-trained model, named G2PTL, a Geography-Graph Pre-trained model for delivery address in Logistics field. G2PTL combines the semantic learning capabilities of text pre-training with the geographical-relationship encoding abilities of graph modeling. Specifically, we first utilize real-world logistics delivery data to construct a large-scale heterogeneous graph of delivery addresses, which contains abundant geographic knowledge and delivery information. Then, G2PTL is pre-trained with subgraphs sampled from the heterogeneous graph. Comprehensive experiments are conducted to demonstrate the effectiveness of G2PTL through four downstream tasks in logistics systems on real-world datasets. G2PTL has been deployed in production in Cainiao's logistics system, which significantly improves the performance of delivery-related tasks