Electrokinetic delivery of persulfate to remediate PCBs polluted soils: Effect of different activation methods

Persulfate-based in-situ chemical oxidation (ISCO) for the remediation of organic polluted soils has gained much interest in last decade. However, the transportation of persulfate in low-permeability soil is very low, which limits its efficiency in degrading soil pollutants. Additionally, the oxidation-reduction process of persulfate with organic contaminants takes place slowly, while, the reaction will be greatly accelerated by the production of more powerful radicals once it is activated. Electrokinetic remediation (EK) is a good way for transporting persulfate in low-permeability soil. In this study, different activation methods, using zero-valent iron, citric acid chelated Fe²⁺, iron electrode, alkaline pH and peroxide, were evaluated to enhance the activity of persulfate delivered by EK. All the activators and the persulfate were added in the anolyte. The results indicated that zero-valent iron, alkaline, and peroxide enhanced the transportation of persulfate at the first stage of EK test, and the longest delivery distance reached sections S4 or S5 (near the cathode) on the 6th day. The addition of activators accelerated decomposition of persulfate, which resulted in the decreasing soil pH. The mass of persulfate delivered into the soil declined with the continuous decomposition of persulfate by activation. The removal efficiency of PCBs in soil followed the order of alkaline activation > peroxide activation > citric acid chelated Fe²⁺ activation > zero-valent iron activation > without activation > iron electrode activation, and the values were 40.5%, 35.6%, 34.1%, 32.4%, 30.8% and 30.5%, respectively. The activation effect was highly dependent on the ratio of activator and persulfate

Benefits and Challenges of the Educational Metaverse: Evidence from Quantitative and Qualitative Data

The metaverse, as a more advanced form of virtual reality, has great potential for education because of its unique affordances for enhancing immersion, interaction, and presence. However, because its development is still in its infancy, there are few empirical studies on the application of metaverse in education, with insufficient empirical evidence from the literature regarding its effectiveness and valued design features, as well as its advantages and disadvantages as a technology-enhanced learning environment. Utilizing the case study method, this study designed and implemented a 40-minute psychology course with 31 undergraduate students in the metaverse using the Virbela platform and collected both quantitative and qualitative data to empirically explore the benefits and challenges of the educational metaverse. The quantitative results showed that the students reported good learning experiences in the metaverse, but their learning outcomes were unsatisfactory, just over the passing level. The qualitative results revealed useful design features and common technical challenges of the educational metaverse. Based on the results, several implications for designing and developing effective courses in the educational metaverse were proposed

Split, Encode and Aggregate for Long Code Search

Code search with natural language plays a crucial role in reusing existing code snippets and accelerating software development. Thanks to the Transformer-based pretraining models, the performance of code search has been improved significantly compared to traditional information retrieval (IR) based models. However, due to the quadratic complexity of multi-head self-attention, there is a limit on the input token length. For efficient training on standard GPUs like V100, existing pretrained code models, including GraphCodeBERT, CodeBERT, RoBERTa (code), take the first 256 tokens by default, which makes them unable to represent the complete information of long code that is greater than 256 tokens. Unlike long text paragraph that can be regarded as a whole with complete semantics, the semantics of long code is discontinuous as a piece of long code may contain different code modules. Therefore, it is unreasonable to directly apply the long text processing methods to long code. To tackle the long code problem, we propose SEA (Split, Encode and Aggregate for Long Code Search), which splits long code into code blocks, encodes these blocks into embeddings, and aggregates them to obtain a comprehensive long code representation. With SEA, we could directly use Transformer-based pretraining models to model long code without changing their internal structure and repretraining. Leveraging abstract syntax tree (AST) based splitting and attention-based aggregation methods, SEA achieves significant improvements in long code search performance. We also compare SEA with two sparse Trasnformer methods. With GraphCodeBERT as the encoder, SEA achieves an overall mean reciprocal ranking score of 0.785, which is 10.1% higher than GraphCodeBERT on the CodeSearchNet benchmark.Comment: 9 page

Genetic sources and diversity of the paddy field carp in the Pearl River basin inferred from two mitochondrial loci

Paddy field carp (PF-carp) is an economically important fish cocultured with rice in traditional agricultural systems. Several distinctive strains of PF-carp have been formed through years of artificial and cross breeding. There is a concern about the status of germplasm resources among PF-carp, since little is known about the genetic sources, diversity, or differentiation. In this study we collected 17 PF-carp populations covering Daotian carp (DTL), Ru Yuan No. 1 (RY), Jinbian carp (JBL), Shaijiang carp (SJL), and Wu carp (WL) along the Pearl River basin to explore their genetic sources and diversity using concatenated sequences of the mitochondrial cytochrome b gene and the D-Loop region. According to the haplotype network analyses, 1, 9, and 57 haplotypes originated from Cyprinus carpio carpio, Cyprinus carpio haematopterus and Cyprinus carpio rubrofuscus, respectively, confirming that genetic introgression has occurred in Pearl River PF-carp populations and Cyprinus carpio carpio was the most common species for genetic origin. The results showed that RY exhibited the lowest level of nucleotide diversity (π = 0.0011) due to high-intensity breeding and was significantly differentiated from the other four strains. PF-carp strains in these remote traditional systems tended to experience artificial selection and a lack of farmer connection that gradually increased genetic differentiation among strains. Notably, three populations of JBL exhibited significant high-level differentiation, since they originated from mountainous areas hindering farmers from fry exchange. In contrast, no significant differentiation was uncovered in the WL populations, since this strain is the most popular cultured strain and has undergone artificial exchange of parents and fry in many cultured regions. This study helps us to understand the status of germplasm resources among PF-carp and to trace their genetic origin before being introduced for local cultivation

Isolation and characterization of a novel (S)-canadine synthase gene from Coptis chinensis

Background: Berberine acts primarily as an important active ingredient in Coptis chinensis and has been traditionally applied in clinical treatment. Nevertheless, little information has been released about C. chinensis, as far as functional genes and biosynthetic pathway of berberine are concerned. Here, we isolated a novel (S)-canadine synthase gene (designated as CAS-1) from C. chinensis by using RT-PCR and RACE techniques. Results: Bioinformatics analysis showed that the cDNA is 1942 bp in length with a complete open reading frame (ORF) of 1476 bp, and the ORF encodes a polypeptide of 491 amino acids with a calculated molecular mass of 55.29 kDa and a pI value of 8.92. Real-time quantitative PCR analysis showed that CcCAS-1 was constitutively expressed in leaf, petiole and rhizome tissues, especially in the leaves of C. chinensis. However, the results of berberine content in different tissues by high-performance liquid chromatography with photodiode array detection (HPLC-DAD)method showed that the leaves and the petiole tissues have similar content of berberine. Conclusions: We found that the berberine content in the rhizomewas seven times (more or less) than that in the leaves and the petioles. In addition, the full length coding sequence of CcCAS-1 was inserted into pET-32a andwas successfully expressed in Escherichia coli , laying a solid foundation for protein purification, activity assay and multi-clonal antibody preparation. Together, our data suggest that CcCAS-1 is a novel heme-thiolate enzyme essential for berberine biosynthesis in C. chinensis

Object Detection for Caries or Pit and Fissure Sealing Requirement in Children's First Permanent Molars

Dental caries is one of the most common oral diseases that, if left untreated, can lead to a variety of oral problems. It mainly occurs inside the pits and fissures on the occlusal/buccal/palatal surfaces of molars and children are a high-risk group for pit and fissure caries in permanent molars. Pit and fissure sealing is one of the most effective methods that is widely used in prevention of pit and fissure caries. However, current detection of pits and fissures or caries depends primarily on the experienced dentists, which ordinary parents do not have, and children may miss the remedial treatment without timely detection. To address this issue, we present a method to autodetect caries and pit and fissure sealing requirements using oral photos taken by smartphones. We use the YOLOv5 and YOLOX models and adopt a tiling strategy to reduce information loss during image pre-processing. The best result for YOLOXs model with tiling strategy is 72.3 mAP.5, while the best result without tiling strategy is 71.2. YOLOv5s6 model with/without tiling attains 70.9/67.9 mAP.5, respectively. We deploy the pre-trained network to mobile devices as a WeChat applet, allowing in-home detection by parents or children guardian

TraceDiag: Adaptive, Interpretable, and Efficient Root Cause Analysis on Large-Scale Microservice Systems

Root Cause Analysis (RCA) is becoming increasingly crucial for ensuring the reliability of microservice systems. However, performing RCA on modern microservice systems can be challenging due to their large scale, as they usually comprise hundreds of components, leading significant human effort. This paper proposes TraceDiag, an end-to-end RCA framework that addresses the challenges for large-scale microservice systems. It leverages reinforcement learning to learn a pruning policy for the service dependency graph to automatically eliminates redundant components, thereby significantly improving the RCA efficiency. The learned pruning policy is interpretable and fully adaptive to new RCA instances. With the pruned graph, a causal-based method can be executed with high accuracy and efficiency. The proposed TraceDiag framework is evaluated on real data traces collected from the Microsoft Exchange system, and demonstrates superior performance compared to state-of-the-art RCA approaches. Notably, TraceDiag has been integrated as a critical component in the Microsoft M365 Exchange, resulting in a significant improvement in the system's reliability and a considerable reduction in the human effort required for RCA

Comparative study of pancreatic vessels and mesopancreas of rhesus monkeys and humans

IntroductionWith the introduction of the concept of mesopancreas defining the perineural structures that includes neurovascular bundle and lymph nodes extending from the posterior surface of the pancreatic head to behind the mesenteric vessels,Total Mesopancreas Excision (TMpE) based on this theory has facilitated the development of pancreatic cancer surgery in clinical practice in recent years. However, the existence of so called mesopancreas in the human body is still in debate and the comparative study of mesopancreas of rhesus monkey and human have not been well investigated.PurposeThe aim of our study is to compare the pancreatic vessels and fascia of human and rhesus monkeys in anatomical and embryological perspectives and to support the utilization of rhesus monkey as animal model.MethodsIn this study, 20 rhesus monkey cadavers were dissected and their mesopancreas location, relationships and arterial distribution were analyzed. We compared the location and developmental patterns of mesopancreas in macaques and humans.ResultsThe results showed that the distribution of pancreatic arteries in rhesus monkeys was the same as that in humans, which is consistent with phylogenetic similarities. However, the morphological features of the mesopancreas and greater omentum is anatomically different from that of humans, including (1) the greater omentum is not connected to the transverse colon in monkeys. (2) The presence of the dorsal mesopancreas of the rhesus monkey suggests that it be an intraperitoneal organ. Comparative anatomical studies of mesopancreas and arteries in macaques and humans showed characteristic patterns of mesopancreas and similarities in pancreatic artery development in nonhuman primates, consistent with phylogenetic differentiation