An Analysis of Factors Affecting Smallholder Rice Farmers’ Level of Sales and Market Participation in Tanzania; Evidence from National Panel Survey Data 2010 -2011

This study analyzed the determinants of market participation for smallholder rice farmers in the five major rice producing regions in Tanzania. The study used Tanzania National Panel Survey (NPS) data compiled data by FAO. A sample of 842 households from high rice producing regions (Mbeya, Morogoro, Shinyanga, Mwanza and Tabora) was extracted from the dataset. Quantitative as well as quantitative analyses were performed; quantitative analysis involved estimation of Weighted Least Squares (WLS) and the Tobit regression models were used to analyze factors affecting volume of sales and determinants of market participation respectively. The household socio-demographic characteristics of smallholder rice farmers were analyzed and discussed in relation to their influence on production and market participation. The WLS results indicated that 10 variable out of 11 variables included in the model were significantly influence the quantity of sold. While age has a positive relationship with quantity sold but was insignificant implying that age of the household head does not directly affect the volume of sales. Results of the Tobit regression model indicated that household consumption, land cultivated, livestock owned and dummy for rural areas indicated a positive significant relationship while non-farm income, dummy region for Mbeya region and Tabora region indicates that, a negative and significant relationship with market participation. Further, low rice production, underdeveloped transport infrastructure and lack of reliable markets closer to higher rice producing regions and inadequate access and use of improved seeds and input were found to be the main of the problems associated with smallholder farmers in the study area. Hence, we discuss and recommend some policy implications based on the study findings. Keywords: Agricultural Marketing, Market Participation, Smallholder rice Farmers, rice Production, Tanzani

ECL: Class-Enhancement Contrastive Learning for Long-tailed Skin Lesion Classification

Skin image datasets often suffer from imbalanced data distribution, exacerbating the difficulty of computer-aided skin disease diagnosis. Some recent works exploit supervised contrastive learning (SCL) for this long-tailed challenge. Despite achieving significant performance, these SCL-based methods focus more on head classes, yet ignoring the utilization of information in tail classes. In this paper, we propose class-Enhancement Contrastive Learning (ECL), which enriches the information of minority classes and treats different classes equally. For information enhancement, we design a hybrid-proxy model to generate class-dependent proxies and propose a cycle update strategy for parameters optimization. A balanced-hybrid-proxy loss is designed to exploit relations between samples and proxies with different classes treated equally. Taking both "imbalanced data" and "imbalanced diagnosis difficulty" into account, we further present a balanced-weighted cross-entropy loss following curriculum learning schedule. Experimental results on the classification of imbalanced skin lesion data have demonstrated the superiority and effectiveness of our method

TFormer: A throughout fusion transformer for multi-modal skin lesion diagnosis

Multi-modal skin lesion diagnosis (MSLD) has achieved remarkable success by modern computer-aided diagnosis technology based on deep convolutions. However, the information aggregation across modalities in MSLD remains challenging due to severity unaligned spatial resolution (dermoscopic image and clinical image) and heterogeneous data (dermoscopic image and patients' meta-data). Limited by the intrinsic local attention, most recent MSLD pipelines using pure convolutions struggle to capture representative features in shallow layers, thus the fusion across different modalities is usually done at the end of the pipelines, even at the last layer, leading to an insufficient information aggregation. To tackle the issue, we introduce a pure transformer-based method, which we refer to as ``Throughout Fusion Transformer (TFormer)", for sufficient information intergration in MSLD. Different from the existing approaches with convolutions, the proposed network leverages transformer as feature extraction backbone, bringing more representative shallow features. We then carefully design a stack of dual-branch hierarchical multi-modal transformer (HMT) blocks to fuse information across different image modalities in a stage-by-stage way. With the aggregated information of image modalities, a multi-modal transformer post-fusion (MTP) block is designed to integrate features across image and non-image data. Such a strategy that information of the image modalities is firstly fused then the heterogeneous ones enables us to better divide and conquer the two major challenges while ensuring inter-modality dynamics are effectively modeled. Experiments conducted on the public Derm7pt dataset validate the superiority of the proposed method. Our TFormer outperforms other state-of-the-art methods. Ablation experiments also suggest the effectiveness of our designs

Prototypical Information Bottlenecking and Disentangling for Multimodal Cancer Survival Prediction

Multimodal learning significantly benefits cancer survival prediction, especially the integration of pathological images and genomic data. Despite advantages of multimodal learning for cancer survival prediction, massive redundancy in multimodal data prevents it from extracting discriminative and compact information: (1) An extensive amount of intra-modal task-unrelated information blurs discriminability, especially for gigapixel whole slide images (WSIs) with many patches in pathology and thousands of pathways in genomic data, leading to an ``intra-modal redundancy" issue. (2) Duplicated information among modalities dominates the representation of multimodal data, which makes modality-specific information prone to being ignored, resulting in an ``inter-modal redundancy" issue. To address these, we propose a new framework, Prototypical Information Bottlenecking and Disentangling (PIBD), consisting of Prototypical Information Bottleneck (PIB) module for intra-modal redundancy and Prototypical Information Disentanglement (PID) module for inter-modal redundancy. Specifically, a variant of information bottleneck, PIB, is proposed to model prototypes approximating a bunch of instances for different risk levels, which can be used for selection of discriminative instances within modality. PID module decouples entangled multimodal data into compact distinct components: modality-common and modality-specific knowledge, under the guidance of the joint prototypical distribution. Extensive experiments on five cancer benchmark datasets demonstrated our superiority over other methods

Effects of purine nucleotide administration on purine nucleotide metabolism in brains of heroin-dependent rats

Heroin is known to enhance catabolism and inhibit anabolism of purine nucleotides, leading to purine nucleotide deficiencies in rat brains. Here, we determined the effect of exogenous purine nucleotide administration on purine nucleotide metabolism in the brains of heroin-dependent rats. Heroin was administrated in increasing doses for 9 consecutive days to induce addiction, and the biochemical changes associated with heroin and purine nucleotide administration were compared among the treated groups. HPLC was performed to detect the absolute concentrations of purine nucleotides in the rat brain cortices. The enzymatic activities of adenosine deaminase (ADA) and xanthine oxidase (XO) in the treated rat cortices were analyzed, and qRT-PCR was performed to determine the relative expression of ADA, XO, adenine phosphoribosyl transferase (APRT), hypoxanthine-guaninephosphoribosyl transferase (HGPRT), and adenosine kinase (AK). Heroin increased the enzymatic activity of ADA and XO, and up-regulated the transcription of ADA and XO. Alternatively, heroin decreased the transcription of AK, APRT, and HGPRT in the rat cortices. Furthermore, purine nucleotide administration alleviated the effect of heroin on purine nucleotide content, activity of essential purine nucleotide metabolic enzymes, and transcript levels of these genes. Our findings therefore represent a novel, putative approach to the treatment of heroin addiction

Underlying burning resistant mechanisms for titanium alloy

The "titanium fire" as produced during high pressure and friction is the major failure scenario for aero-engines. To alleviate this issue, Ti-V-Cr and Ti-Cu-Al series burn resistant titanium alloys have been developed. However, which burn resistant alloy exhibit better property with reasonable cost needs to be evaluated. This work unveils the burning mechanisms of these alloys and discusses whether burn resistance of Cr and V can be replaced by Cu, on which thorough exploration is lacking. Two representative burn resistant alloys are considered, including Ti14(Ti-13Cu-1Al-0.2Si) and Ti40(Ti-25V-15Cr-0.2Si)alloys. Compared with the commercial non-burn resistant titanium alloy, i.e., TC4(Ti-6Al-4V)alloy, it has been found that both Ti14 and Ti40 alloys form "protective" shields during the burning process. Specifically, for Ti14 alloy, a clear Cu-rich layer is formed at the interface between burning product zone and heat affected zone, which consumes oxygen by producing Cu-O compounds and impedes the reaction with Ti-matrix. This work has established a fundamental understanding of burning resistant mechanisms for titanium alloys. Importantly, it is found that Cu could endow titanium alloys with similar burn resistant capability as that of V or Cr, which opens a cost-effective avenue to design burn resistant titanium alloys.Comment: 6 figure

What is China doing in policy-making to push back the negative aspects of the nutrition transition?

OBJECTIVE: To review the nutrition policies and efforts related to nutrition transition in China. DESIGN AND SETTING: This paper reviews the nutrition policy and activities of China to prevent and control diet-related non-communicable diseases (DR-NCDs). Data came from the Ministry of Health, the Ministry of Agriculture, the State Council and some cross-sectional surveys. RESULTS: China is undergoing a remarkable, but undesirable, rapid transition towards a stage of the nutrition transition characterised by high rates of DR-NCDs in a very short time. Some public sector Chinese organisations have combined their efforts to create the initial stages of systematic attempts to reduce these problems. These efforts, which focus on both under- and overnutrition, include the new Dietary Guidelines for Chinese Residents and the Chinese Pagoda and The National Plan of Action for Nutrition in China, issued by the highest body of the government, the State Council. There are selected agricultural sector activities that are laudable and few other systematic efforts that are impacting behaviour yet. In the health sector, efforts related to reducing hypertension and diabetes are becoming more widespread, but there is limited work in the nutrition sector. This paper points to some unique strengths from past Chinese efforts and to an agenda for the next several decades. CONCLUSIONS: China is trying in its efforts to prevent and control the development of DR-NCDs but effects are limited. Systematic multi-sector co-operation is needed to effectively prevent and control DR-NCDs inside and outside the health sector

Survival analysis and probability density function of switching heroin model

We study a switching heroin epidemic model in this paper, in which the switching of supply of heroin occurs due to the flowering period and fruiting period of opium poppy plants. Precisely, we give three equations to represent the dynamics of the susceptible, the dynamics of the untreated drug addicts and the dynamics of the drug addicts under treatment, respectively, within a local population, and the coefficients of each equation are functions of Markov chains taking values in a finite state space. The first concern is to prove the existence and uniqueness of a global positive solution to the switching model. Then, the survival dynamics including the extinction and persistence of the untreated drug addicts under some moderate conditions are derived. The corresponding numerical simulations reveal that the densities of sample paths depend on regime switching, and larger intensities of the white noises yield earlier times for extinction of the untreated drug addicts. Especially, when the switching model degenerates to the constant model, we show the existence of the positive equilibrium point under moderate conditions, and we give the expression of the probability density function around the positive equilibrium point

An Analysis of Relationship among Income Inequality, Poverty, and Income Mobility, Based on Distribution Functions

Many studies show that the relationship among income inequality, poverty, and income mobility needs to be further discussed. Meanwhile, some researches on Distribution Function offer new perspective and methods to analyze this issue. First, this paper expresses the relationship among the Gini coefficient, poverty ratio, and income mobility of 5 common Distribution Functions through math deduction; this finding cannot be found in relevant literatures. Furthermore, an empirical research result proves that the income distribution of urban residents in the period from 2005 to 2010 fits Log-Logistic Distribution. On the basis of the above analysis and empirical data, the paper explores the relations of income inequality, poverty, and income mobility of urban residents and draws some useful conclusions