Comparsion of bioleaching of copper sulphides by Acidithiobacillus ferrooxidans

Bioleaching of copper sulphides were investigated. The results show that the copper extraction from djurleite, bornite, covellite and chalcopyrite under the optimal conditions were 95.12, 84.5, 54.1, and 18.33%, respectively. A ranking for the bioleaching of copper sulfides was obtained: djurleite > bornite > covellite > chalcopyrite. A determination of the extent of adsorption of A. ferrooxidans on the surface of the minerals showed that the cell density of Acidithiobacillus ferrooxidans on djurleite was the highest. The order of adsorption on the copper sulphides was: djurleite > bornite > covellite > chalcopyrite. The results suggest a difference in affinity of bacteria for different copper sulphides. The higher the leaching rate of copper sulphides, the greater the density of bacteria absorbed on the surface of minerals.Keywords: Bioleaching, copper sulphides, Acidithiobacillus ferrooxidans, cell density, copper extractionAfrican Journal of Biotechnology, Vol. 13(5), pp. 664-672, 29 January, 201

Turning a CLIP Model into a Scene Text Detector

The recent large-scale Contrastive Language-Image Pretraining (CLIP) model has shown great potential in various downstream tasks via leveraging the pretrained vision and language knowledge. Scene text, which contains rich textual and visual information, has an inherent connection with a model like CLIP. Recently, pretraining approaches based on vision language models have made effective progresses in the field of text detection. In contrast to these works, this paper proposes a new method, termed TCM, focusing on Turning the CLIP Model directly for text detection without pretraining process. We demonstrate the advantages of the proposed TCM as follows: (1) The underlying principle of our framework can be applied to improve existing scene text detector. (2) It facilitates the few-shot training capability of existing methods, e.g., by using 10% of labeled data, we significantly improve the performance of the baseline method with an average of 22% in terms of the F-measure on 4 benchmarks. (3) By turning the CLIP model into existing scene text detection methods, we further achieve promising domain adaptation ability. The code will be publicly released at https://github.com/wenwenyu/TCM.Comment: CVPR202

Carbon materials : structures, properties, synthesis and applications

As one of the most versatile elements, carbon materials occupy the most plentiful allotropies composed of pure or mixed hybridization orbitals of sp1/sp2/sp3. The design and synthesis of new carbon materials may be stimulated based on a deeper understanding of underlying structures and related properties. In this review, the initial early discoveries of carbon materials are examined based on their hybridization of orbitals. According to the type of hybridization, the discovered carbon materials are firstly classified and introduced in detail based on their crystal structures. Secondly, its physical and chemical properties, mainly including mechanical properties, optical properties and electronic properties, are reviewed. Thirdly, the existing methods of predicting carbon structure and synthesizing carbon materials are classified and summarized, and some typical carbon materials predicted or prepared are discussed respectively. Then, the main applications of newly synthesized carbon materials in the last two decades are classified and summarized, and the microstructure is linked with the macro properties and specific applications. Finally, the future research opportunities for carbon materials and their potential applications are prospected from the aspects of the gap between theoretical prediction and preparation, the current research hotspot of carbon materials and the incomplete application of carbon materials. It is the authors' intention for this review paper to serve not only as a valuable reference for research into carbon materials and related composites, but also as a guidance for novel materials design at the atomic level

Responses of soil respiration and its temperature/moisture sensitivity to precipitation in three subtropical forests in southern China

Both long-term observation data and model simulations suggest an increasing chance of serious drought in the dry season and extreme flood in the wet season in southern China, yet little is known about how changes in precipitation pattern will affect soil respiration in the region. We conducted a field experiment to study the responses of soil respiration to precipitation manipulations – precipitation exclusion to mimic drought, double precipitation to simulate flood, and ambient precipitation as control (abbr. EP, DP and AP, respectively) – in three subtropical forests in southern China. The three forest sites include Masson pine forest (PF), coniferous and broad-leaved mixed forest (MF) and monsoon evergreen broad-leaved forest (BF). Our observations showed that altered precipitation strongly influenced soil respiration, not only through the well-known direct effects of soil moisture on plant and microbial activities, but also by modification of both moisture and temperature sensitivity of soil respiration. In the dry season, soil respiration and its temperature sensitivity, as well as fine root and soil microbial biomass, showed rising trends with precipitation increases in the three forest sites. Contrarily, the moisture sensitivity of soil respiration decreased with precipitation increases. In the wet season, different treatments showed different effects in three forest sites. The EP treatment decreased fine root biomass, soil microbial biomass, soil respiration and its temperature sensitivity, but enhanced soil moisture sensitivity in all three forest sites. The DP treatment significantly increased soil respiration, fine root and soil microbial biomass in the PF only, and no significant change was found for the soil temperature sensitivity. However, the DP treatment in the MF and BF reduced soil temperature sensitivity significantly in the wet season. Our results indicated that soil respiration would decrease in the three subtropical forests if soil moisture continues to decrease in the future. More rainfall in the wet season could have limited effect on the response of soil respiration to the rising of temperature in the BF and MF

Looking and Listening: Audio Guided Text Recognition

Text recognition in the wild is a long-standing problem in computer vision. Driven by end-to-end deep learning, recent studies suggest vision and language processing are effective for scene text recognition. Yet, solving edit errors such as add, delete, or replace is still the main challenge for existing approaches. In fact, the content of the text and its audio are naturally corresponding to each other, i.e., a single character error may result in a clear different pronunciation. In this paper, we propose the AudioOCR, a simple yet effective probabilistic audio decoder for mel spectrogram sequence prediction to guide the scene text recognition, which only participates in the training phase and brings no extra cost during the inference stage. The underlying principle of AudioOCR can be easily applied to the existing approaches. Experiments using 7 previous scene text recognition methods on 12 existing regular, irregular, and occluded benchmarks demonstrate our proposed method can bring consistent improvement. More importantly, through our experimentation, we show that AudioOCR possesses a generalizability that extends to more challenging scenarios, including recognizing non-English text, out-of-vocabulary words, and text with various accents. Code will be available at https://github.com/wenwenyu/AudioOCR

Attention Where It Matters: Rethinking Visual Document Understanding with Selective Region Concentration

We propose a novel end-to-end document understanding model called SeRum (SElective Region Understanding Model) for extracting meaningful information from document images, including document analysis, retrieval, and office automation. Unlike state-of-the-art approaches that rely on multi-stage technical schemes and are computationally expensive, SeRum converts document image understanding and recognition tasks into a local decoding process of the visual tokens of interest, using a content-aware token merge module. This mechanism enables the model to pay more attention to regions of interest generated by the query decoder, improving the model's effectiveness and speeding up the decoding speed of the generative scheme. We also designed several pre-training tasks to enhance the understanding and local awareness of the model. Experimental results demonstrate that SeRum achieves state-of-the-art performance on document understanding tasks and competitive results on text spotting tasks. SeRum represents a substantial advancement towards enabling efficient and effective end-to-end document understanding.Comment: Accepted to ICCV 2023 main conferenc

CNTF Induces Regeneration of Cone Outer Segments in a Rat Model of Retinal Degeneration

Cone photoreceptors are responsible for color and central vision. In the late stage of retinitis pigmentosa and in geographic atrophy associated with age-related macular degeneration, cone degeneration eventually causes loss of central vision. In the present work, we investigated cone degeneration secondary to rod loss in the S334ter-3 transgenic rats carrying the rhodopsin mutation S334ter.Recombinant human ciliary neurotrophic factor (CNTF) was delivered by intravitreal injection to the left eye of an animal, and vehicle to the right eye. Eyes were harvested 10 days after injection. Cone outer segments (COS), and cell bodies were identified by staining with peanut agglutinin and cone arrestin antibodies in whole-mount retinas. For long-term treatment with CNTF, CNTF secreting microdevices were implanted into the left eyes at postnatal day (PD) 20 and control devices into the right eyes. Cone ERG was recorded at PD 160 from implanted animals. Our results demonstrate that an early sign of cone degeneration is the loss of COS, which concentrated in many small areas throughout the retina and is progressive with age. Treatment with CNTF induces regeneration of COS and thus reverses the degeneration process in early stages of cone degeneration. Sustained delivery of CNTF prevents cones from degeneration and helps them to maintain COS and light-sensing function.Loss of COS is an early sign of secondary cone degeneration whereas cell death occurs much later. At early stages, degenerating cones are capable of regenerating outer segments, indicating the reversal of the degenerative process. Sustained delivery of CNTF preserves cone cells and their function. Long-term treatment with CNTF starting at early stages of degeneration could be a viable strategy for preservation of central vision for patients with retinal degenerations

Vascular endothelial growth factor and the risk of venous thromboembolism: A genetic correlation and two-sample Mendelian randomization study

Background: The relationship between vascular endothelial growth factor (VEGF) and the risk of venous thromboembolism (VTE) has always been one of the concerns in the medical field. However, the causal inferences from published observational studies on this issue may be affected by confounders or reverse causality. We performed a two-sample bidirectional Mendelian randomization (MR) to infer the associations between VEGF and VTE. Methods: Summary statistics from genome-wide association studies (GWAS) for VEGF and VTE were obtained from published meta-analysis studies and the FinnGen consortium, respectively. Independent genetic variables significantly associated with exposure were selected as instrumental variables. Linkage disequilibrium score regression (LDSC) and five robust MR analytical approaches were conducted to estimate the genetic correlations and causal inference. The MR-Egger intercept, Cochran’s Q, and MR pleiotropy residual sum and outlier (MR-PRESSO) were performed to evaluate the horizontal pleiotropy, heterogeneities, and stability of these genetic variants on outcomes. Notably, replication analyses were performed using different subgroups of VTE. Results: LDSC failed to identify genetic correlations between VEGF and VTE. Based on 9 SNPs, the circulating VEGF level was positively related to the risk of VTE using inverse variance weighting (IVW) method (odds ratio (OR) = 1.064, 95 % confidence interval (CI), 1.009 – 1.122). Reverse MR analyses showed that genetic liability for VTE was not associated with increased VEGF level (β = -0.021, 95 % CI, -0.087-0.045). Pleiotropy-robust methods indicated no bias in any estimates. Conclusions: Our findings failed to detect coheritability between VEGF and VTE. The suggestive positive effect of the higher VEGF level on the VTE risk may have clinical implications, suggesting that VEGF as a possible predictor and therapeutic target for VTE prevention need to be further warranted