Miracle-dz/UniFAR-FTUs huggingface dataset:
Options to overcome the barriers to pricing European agricultural emissions

ABSTRACT Although agriculture could contribute substantially to European emission reductions, its mitigation potential lies untapped and dormant. Market-based instruments could be pivotal in incentivizing cost-effective abatement. However, sector specificities in transaction costs, leakage risks and distributional impacts impede its implementation. The significance of such barriers critically hinges on the dimensions of policy design. This article synthesizes the work on emissions pricing in agriculture together with the literature on the design of market-based instruments. To structure the discussion, an options space is suggested to map policy options, focusing on three key dimensions of policy design. More specifically, it examines the role of policy coverage, instruments and transfers to farmers in overcoming the barriers. First, the results show that a significant proportion of agricultural emissions and mitigation potential could be covered by a policy targeting large farms and few emission sources, thereby reducing transaction costs. Second, whether an instrument is voluntary or mandatory influences distributional outcomes and leakage. Voluntary instruments can mitigate distributional concerns and leakage risks but can lead to subsidy lock-in and carbon price distortion. Third, the impact on transfers resulting from the interaction of the Common Agricultural Policy (CAP) with emissions pricing will play a key role in shaping political feasibility and has so far been underappreciated. POLICY RELEVANCE Following the 2015 Paris Agreement, European climate policy is at a crossroads. Achieving cost-effectively the 2030 and 2050 European targets requires all sectors to reduce their emissions. Yet, the cornerstone of European climate policy, the European Union Emissions Trading System (EU ETS), covers only about half of European emissions. Major sectors have been so far largely exempted from carbon pricing, in particular transport and agriculture. While transport has been increasingly under the spotlight as a possible candidate for an EU ETS sectoral expansion, policy discussions on pricing agricultural emissions have been virtually absent. This article attempts to fill this gap by investigating options for market-based instruments to reduce agricultural emissions while taking barriers to implementation into account.
Assessing the association between the methylenetetrahydrofolate reductase (MTHFR) 677C>T polymorphism and blood folate concentrations: a systematic review and meta-analysis of trials and observational studies.

BACKGROUND The methylenetetrahydrofolate reductase (MTHFR) 677C>T polymorphism is a risk factor for neural tube defects. The T allele produces an enzyme with reduced folate-processing capacity, which has been associated with lower blood folate concentrations. OBJECTIVE We assessed the association between MTHFR C677T genotypes and blood folate concentrations among healthy women aged 12-49 y. DESIGN We conducted a systematic review of the literature published from January 1992 to March 2014 to identify trials and observational studies that reported serum, plasma, or red blood cell (RBC) folate concentrations and MTHFR C677T genotype. We conducted a meta-analysis for estimates of percentage differences in blood folate concentrations between genotypes. RESULTS Forty studies met the inclusion criteria. Of the 6 studies that used the microbiologic assay (MA) to measure serum or plasma (S/P) and RBC folate concentrations, the percentage difference between genotypes showed a clear pattern of CC > CT > TT. The percentage difference was greatest for CC > TT [S/P: 13%; 95% credible interval (CrI): 7%, 18%; RBC: 16%; 95% CrI: 12%, 20%] followed by CC > CT (S/P: 7%; 95% CrI: 1%, 12%; RBC: 8%; 95% CrI: 4%, 12%) and CT > TT (S/P: 6%; 95% CrI: 1%, 11%; RBC: 9%; 95% CrI: 5%, 13%). S/P folate concentrations measured by using protein-binding assays (PBAs) also showed this pattern but to a greater extent (e.g., CC > TT: 20%; 95% CrI: 17%, 22%). In contrast, RBC folate concentrations measured by using PBAs did not show the same pattern and are presented in the Supplemental Material only. CONCLUSIONS Meta-analysis results (limited to the MA, the recommended population assessment method) indicated a consistent percentage difference in S/P and RBC folate concentrations across MTHFR C677T genotypes. Lower blood folate concentrations associated with this polymorphism could have implications for a population-level risk of neural tube defects.
Wireless Ranging Performance Improvement Technique

: In the last few years many research efforts have been focused on various wireless measurement techniques for indoor object positioning. In this paper we focuses on the performance improvement of the classical wireless ranging techniques such as RSS approach and ToF approach. The novelty of the proposed method is a data fusion algorithm which combines the data obtained through the RSS approach and ToF approach with the aid of a kalman filter. The advantage of this proposed algorithm is that it provides great improvement in wireless ranging. The algorithm has been implemented and simulated to check the performance of the proposed system. The result obtained shows that there is typical improvement in the ranging accuracy and the combination of these two classical approach can significantly reduce the measurement uncertainity
Breast Cancer Detection using Artificial Neural Networks

Breast cancer is very common and is considered as the second dangerous disease all over the world due to its death rate. Affected can survive if the disease diagnoses before the appearance of major physical changes in the body. Now a day, mammographic (X-ray of breast region) images are widely used for premature revealing of breast cancer. Aim of the proposed system is to design a Computer Aided Diagnosis system (CAD) used to distinguish between benign (non-cancerous) and malignant (cancerous) mammogram. CAD system are used to help radiologist to increase his diagnosis accuracy. In the proposed system, texture features from mammogram were calculated using Gray Level Co-occurrence Matrix (GLCM) along 0°, from the calculate features most effective features having large contribution to achieve the desired output were chosen and applied to Artificial Neural Network (ANN) for training and classification, as ANN is widely use in various field such as, pattern recognition, medical diagnosis, machine learning and so on. For this research work mini-MIAS database is used and the overall sensitivity, specificity and accuracy achieved by using the proposed system is 99.3%, 100% and 99.4% respectively.
[Capital Utilization and Returns to Scale]: Comment

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Knowing your neighbourhood—the effects of Epichloë endophytes on foliar fungal assemblages in perennial ryegrass in dependence of season and land-use intensity

Epichloë endophytes associated with cool-season grass species can protect their hosts from herbivory and can suppress mycorrhizal colonization of the hosts’ roots. However, little is known about whether or not Epichloë endophyte infection can also change the foliar fungal assemblages of the host. We tested 52 grassland study sites along a land-use intensity gradient in three study regions over two seasons (spring vs. summer) to determine whether Epichloë infection of the host grass Lolium perenne changes the fungal community structure in leaves. Foliar fungal communities were assessed by Next Generation Sequencing of the ITS rRNA gene region. Fungal community structure was strongly affected by study region and season in our study, while land-use intensity and infection with Epichloë endophytes had no significant effects. We conclude that effects on non-systemic endophytes resulting from land use practices and Epichloë infection reported in other studies were masked by local and seasonal variability in this study’s grassland sites.
The microbiological quality of water in fish spas with Garra rufa fish, the Netherlands, October to November 2012.

In fish spas, clients may submerge their hands, feet or whole body in basins with Garra rufa fish, for dead skin removal. Skin infections may result from using these spas, transmitted from fish to clients, through either fish or water, or from client to client. The microbiological water quality was determined in 24 fish spas in 16 companies in the Netherlands through analysis of a single water sample per fish spa. Water samples were tested for the presence of Aeromonas spp. , Vibrio spp. ,Pseudomonas aeruginosa, nontuberculous mycobacteria,and faecal indicator bacteria by using standard culture methods. The majority of the examined fish spas contained Aeromonas spp. (n = 24), P. aeruginosa(n = 18), Vibrio spp. (n = 16) including V. cholerae non-O1/O139 and V. vulnificus, and several rapid growing Mycobacterium spp. (n = 23) including M. fortuitum, M.conceptionense, M. abscessus and M. chelonae. Faecal contamination of the fish spa water was low. Based on the detected concentrations of Aeromonas spp. , Vibriospp. , and P. aeruginosa, the detected Mycobacteriumspp. , and the health implications of these bacteria, the health risk from using fish spas is considered limited for healthy people with an intact skin and no underlying disease.
Adaptive Visual-Diagnostic Training : User Mental Model Development

Current diagnostic imaging identification techniques for skin lesions fail to address the visual nature of this task and do not provide information about the mental models users develop after receiving training. To address this issue, the MSKBLOCK medical training system uses a visual approach to support the development of a user’s mental model. Our study evaluates the usability of this adaptive system and how it affects the establishment of users’ mental models. Those using MSKBLOCK developed mental models based on visual information and learned to distinguish between malignant and benign skin lesions, suggesting the potential for reformulating medical training using technologies that align with the visual nature of some diagnostic tasks.
No Light at the End of the Tunnel : Corruption and Insecurity in Nigeria

Nigeria has become for long a reference point for corruption, and lately insecurity. The mindless looting of public funds, that is emblematic of governance in Nigeria, has proceeded apace with equally mindless destruction of lives and property, with palpable fear, and disenchantment pervading the land. The increasing sectarian strife has turned parts of the country into killing fields, with obvious threats on democratic consolidation and national stability. The festering sores of corruption and insecurity are inexorably related to the warped values. The paper contends that the nation is still mired in deep crisis of governance owing to misdiagnosis of the problem which renders nugatory the efforts of state agencies to checkmate the menace. The chronic nature of corruption and insecurity has been fuelled and sustained by perverted societal values. Nigeria faces an existential crisis and requires a reorientation of values and complete paradigm shift to be able to come out of the woods.
Robotic-assisted compared with conventional total hip arthroplasty: systematic review and meta-analysis

Background Robotic-assisted total hip arthroplasty (THA) allows for accurate preoperative planning and component positioning, potentially enhancing implant survival and long-term outcomes. The relative efficacy and safety of robotic-assisted and conventional THA, however, are unclear. This systematic review and meta-analysis compared the safety and efficacy of robotic-assisted and conventional THA. Methods Medline, Embase and the Cochrane Library were comprehensively searched in September 2017 to identify studies comparing the safety and efficacy of robotic-assisted and conventional THA. Seven studies were included. Data of interest were extracted and analysed using Review Manager 5.3. Results The seven included studies involved 1516 patients, with 522 undergoing robotic-assisted and 994 undergoing conventional THA. Compared with conventional THA, robotic-assisted THA was associated with longer surgical time (not significant); lower intraoperative complication rates (OR: 0.12, 95% CI: 0.05 to 0.34, p<0.0001 I2); better cup placement, stem placement and global offset and a higher rate of heterotopic ossifications. Functional scores, limb length discrepancy and rates of revision and stress shielding were similar in the two groups. The relative amount of blood loss was unclear. Conclusion The results of this meta-analysis suggest that robotic-assisted THA has certain advantages over conventional THA, including the results of component positioning and rates of intraoperative complications. Additional comparative studies are required to determine the long-term clinical outcomes of robotic-assisted THA.
Online customer identification based on Bayesian model of interpurchase times and recency

When it comes to customer segment, most researchers lay great emphasis on the aggregate view but neglect the individual view. In this article, the primary focus will be on both. The main purpose is to analyse how the activity of website browsing contributes to the segmentation of online customers (aggregate view) and how the current and prospective activities of the individual can be accurately determined and predicted (individual view). In aggregate view, we employ a finite mixture model on interpurchase times to segment customers into three states: super-active, active and inactive. In individual view, we apply the hierarchical Bayesian model of interpurchase times to achieve heterogeneity across customers. However, this heterogeneity is inadequate in the evaluation of the individual activity in the present or near future. Moreover, recency is one of the most effective behavioural indices on the relationship strength and one of the meaningful predictors for customer reconsumption. Specifically, in individual view, this article adopts not only the interpurchase times to evaluate customer status, but also adds a new variable or recency, to execute this evaluation. The procedure of customer identification via interpurchase times and recency are applied to the case study of an online company. The result of this case study shows that this approach provides a more genuine customer status than the procedure that merely involves interpurchase times. Further, inferences of mixture model and Bayesian model in our case study are solved by Winbugs, a software package of Markov Chain Monte Carlo method.
Macross : Activity Mining based on Metapath Guided Cross-Modal Embedding

As the ongoing rapid urbanization takes place with an everincreasing speed, fully modeling urban dynamics becomes more and more challenging, but also a necessity for socioeconomic development. It is challenging because human activities and constructions are ubiquitous; urban landscape and life content change anywhere and anytime. It’s crucial due to the fact that only up-to-date urban dynamics can enables governors to optimize their city planning strategy and help individuals organize their daily lives in a more efficient way. Previous geographic topic model based methods attempts to solve this problem, but suffer from high computational cost and memory consumption, limiting their scalability to city level applications. Also, strong prior assumptions make such models fail to capture certain patterns by nature. To bridge the gap, we propose Macross, a metapath guided embedding approach to jointly model location, time and text information. Given a dataset of geo-tagged social media posts, we extract and aggregate location and time and construct a heterogeneous information network using the aggregated space and time. Metapath2vec based approach is used to construct vector representations for times, locations and frequent words such that co-occurence pairs of nodes are closer in latent space. The vector representations will be used to infer related time, locations or keywords for a user query. Experiments done on enormous datasets show our model can generate comparable, if not better quality query results compared to state of the art models and outperforms some cutting-edge models for activity recovery and classification.
Analysis of Heavy Ion-Induced Chromosome Aberrations in Human Fibroblast Cells Using In Situ Hybridization

Confluent human fibroblast cells (AG1522) were irradiated with gamma rays, 490 MeV/nucleon Si, or with Fe ions at either 200 or 500 MeV/nucleon. The cells were allowed to repair at 37 0 C for 24 hours after exposure, and a chemically induced premature chromosome condensation (PCC) technique was used to condense chromosomes in the G2 phase of the cell cycle. Unrejoined chromosomal breaks and complex exchanges were analyzed in the irradiated samples. In order to verify that chromosomal breaks were truly unrejoined, chromosome aberrations were analyzed using a combination of whole chromosome specific probes and probes specific for the telomere region of the chromosome. Results showed that the frequency of unrejoined chromosome breaks was higher after high-LET radiation, and consequently, the ratio of incomplete to complete exchanges increased steadily with LET up to 440 keV/micron, the highest LET value in the present study. For samples exposed to 200 MeV/nucleon Fe ions, chromosome aberrations were analyzed using the multicolor FISH (mFISH) technique that allows identification of both complex and truly incomplete exchanges. Results of the mFISH study showed that 0.7 and 3 Gy dose of the Fe ions produced similar ratios of complex to simple exchanges and incomplete to complete exchanges, values for which were higher than those obtained after a 6 Gy gamma exposure. After 0.7 Gy of Fe ions, most complex aberrations were found to involve three or four chromosomes, indicating the maximum number of chromosome domains traversed by a single Fe ion track. 2
Circulating Long Non-Coding RNAs Act as Biomarkers for Predicting 131I Uptake and Mortality in Papillary Thyroid Cancer Patients with Lung Metastases

Purpose: The aims of the current study were to explore plasma lncRNAs as a novel biomarker panel for the diagnosis of non-131I-avid lung metastases of PTC and to investigate the plasma lncRNA expression levels associated with survival in PTC patients with lung metastases. Methods: The expression of lncRNAs was examined using an lncRNA microarray chip. The lncRNAs with the most significant difference in expression between PTC patients with non-131I-avid lung metastases and PTC patients with 131I-avid lung metastases were verified by quantitative reverse-transcription polymerase chain reaction. The Kaplan-Meier method was used to determine whether the plasma lncRNA levels might be indicative of patient prognosis. Results: Compared with 131I-avid lung metastases, we discovered that two lncRNAs (ENST00000462717 andENST00000415582) were upregulated and two (TCONS_00024700 and NR_028494) were downregulated in the non-131I-avid lung metastases of PTC. Receiver operating characteristic curve (ROC) analyses indicated that the use of these four lncRNAs had high diagnostic sensitivity and specificity for predicting non-131I-avid lung metastases of PTC. The merged areas under the curve for ENST00000462717, ENST00000415582, TCONS_00024700,and NR_028494 in the training and validation sets were 0.890, 0.936, 0.975, and 0.918, respectively. Low (ENST00000462717 and ENST00000415582) and high plasma lncRNA levels(TCONS_00024700and NR_028494) were also found to be associated with better prognosis of PTC patients with lung metastases(P<0.001). Conclusions: ENST00000462717, ENST00000415582, TCONS_00024700, and NR_028494 may be used as novel and minimally invasive markers for the diagnosis and prognostic assessment of non-131I-avid lung metastases from PTC.
International Trade and MIgration: A Quantitative Framework

Goods trade and international mobility of labor are typically analyzed separately. While there is excellent research in both fields, far less is known about the interrelationships between international migration and international trade. This paper provides a first structurally estimable model of international trade with endogenous international migration choices of workers which can be used for model-based counterfactual predictions. Using bilateral trade and migration data for 33 OECD countries we find that quantitative welfare predictions vastly change: investigating reasonable changes in the costs of factor and goods mobility across borders in this unified framework almost doubles the predicted welfare effects compared to established models. Our results sensitize policy makers who seek ex-ante evaluations of international trade agreements and migration policies.
Welfare implications of EU enlargement: the case of East Baltic cod

Recent research has warned that liberalising trade in capture fishery products originating from inefficient managed fisheries might cause over-exploitation, reduced fish stocks and thereby reduced steady state welfare. This paper qualifies the warning in a case study of the East Baltic cod market by introducing a quantitative supply model of the fishery with year classes. Welfare effects of trade liberalisation are identified taking minimum size limits and minimum mesh sizes into account and it is shown that even though liberalising trade supplied by such a fishery might cause long steady state welfare reductions in the supplier countries, this welfare reduction is almost solely related to economic over-exploitation through too large fishing costs more than to biological over-exploitation. Thus, the welfare effects of trade liberalisation are generally small and in particular for fishing mortalities well above the maximum sustainable yield. The consequence is that the argument that warns against trade liberalisation in certain situations gains less validity and conventional wisdom following from the Neo-classical theoretical tradition regains validity at several and probably most fish markets globally.
Zinc Solubilizing Rhizobacteria Associated with Sugarcane from South Gujarat Region

Zinc is a one of the eight essential micronutrients required for the normal healthy growth and reproduction of crop plants. Zinc deficiency in an agricultural soil is well-studied and wide spread problem worldwide. This study on zinc solubilization by bacteria has an immense importance in zinc nutrition to plant particularly in fields having alkaline soils as observed in present study. Among 309 isolates, 141 isolates were positive for zinc solubilization. Considering the quantitative aspects solubilization efficiency of bacterial isolates was ranged from (116-366) for 0.1% zinc oxide incorporated in the medium. Based on solubilization efficiency five isolates with highest Zn solubilization efficiency were chosen for multiple plant growth promoting traits from which BM/F1/ER/8, NFM/F2/RP/15, and KBM/F4/RH/5 have multiple plant growth promoting traits can be exploited as a potential biofertilizers.