Potential Matches Research Articles

Different faces of cigarette butts, the most abundant beach litter worldwide.

Cigarette butts (CBs) are non-biodegradable residues of synthetic origin, prevalent on beaches all over the world. The study evaluates discarded CBs on an intensely used urban beach, determining variations in physical and chemical characteristics. CBs collected were observed, classified, and visually separated according to a proposed scale of four levels of degradation to test the potential match between physical and chemical decay. CBs (un-smoked, smoked, and discarded) were used to determine the average length (cm) and mass (g) in order to observe changes in these parameters among the levels. Cigarette butts experience consecutive mass loss during environmental exposure. Scanning electron microscopy (SEM) images were obtained to assess physical changes in fibers due to smoking. FTIR-ATR was used to assess CBs new (un-smoked), smoked, and discarded samples in relation to cellulose acetate decay. The FTIR-ATR spectroscopy of the most visually degraded cigarette butts indicated modifications in the spectra when compared to un-smoked cigarettes.

Robust image matching via local graph structure consensus

Image matching plays a vital role in many computer vision tasks, and this paper focuses on the mismatch removal problem of feature-based matching. We formulate the problem into a general yet effective optimization framework based on graph matching by combining integer quadratic programming with a compensation term for discouraging matches, termed as Local Graph Structure Consensus (LGSC). Considering the local area similarity of those potential true matches, we design a local graph structure for preserving geometric topology, which contains a local indicator vector and a local affinity vector for each correspondence. The local indicator vector is utilized for edge construction, while the local affinity vector represents the match correctness of the nodes and edges between two graphs. In particular, the ranking shift with scale and rotation invariance is exploited to represent the node affinity. Ultimately, we derive a closed-form solution with linearithmic time and linear space complexity. Moreover, a multi-scale and iterative graph construction strategy is proposed to promote the performance of our method in terms of robustness and effectiveness. Extensive experiments on various real image datasets demonstrate that our LGSC can achieve superior performance over current state-of-the-art approaches.

Enhancing the ATra Black Box Matching Algorithm: Use of All Names for Deduplication Across Jurisdictions.

Achieving accurate, timely, and complete HIV surveillance data is complicated in the United States by migration and care seeking across jurisdictional boundaries. To address these issues, public health entities use the ATra Black Box-a secure, electronic, privacy-assuring system developed by Georgetown University-to identify and confirm potential duplicate case records, exchange data, and perform other analytics to improve the quality of data in the Enhanced HIV/AIDS Reporting System (eHARS). We aimed to evaluate the ability of 2 ATra software algorithms to identify potential duplicate case-pairs across 6 jurisdictions for people living with diagnosed HIV. We implemented 2 matching algorithms for identifying potential duplicate case-pairs in ATra software. The Single Name Matching Algorithm examines only 1 name for a person, whereas the All Names Matching Algorithm examines all names in eHARS for a person. Six public health jurisdictions used the algorithms. We compared outputs for the overall number of potential matches and changes in matching level. The All Names Matching Algorithm found more matches than the Single Name Matching Algorithm and increased levels of match. The All Names Matching Algorithm identified 9070 (4.5%) more duplicate matches than the Single Name Matching Algorithm (n = 198 828) and increased the total number of matches at the exact through high levels by 15.4% (from 167 156 to 192 932; n = 25 776). HIV data quality across multiple jurisdictions can be improved by using all known first and last names of people living with diagnosed HIV that match with eHARS rather than using only 1 first and last name.

Evaluation of animal model congruence to human depression based on large-scale gene expression patterns of the CNS

Depression is a complex mental health disorder that is difficult to study. A wide range of animal models exist and for many of these data on large-scale gene expression patterns in the CNS are available. The goal of this study was to evaluate how well animal models match human depression by evaluating congruence and discordance of large-scale gene expression patterns in the CNS between almost 300 animal models and a portrait of human depression created from male and female datasets. Multiple approaches were used, including a hypergeometric based scoring system that rewards common gene expression patterns (e.g., up-up or down-down in both model and human depression), but penalizes opposing gene expression patterns. RRHO heat maps, Uniform Manifold Approximation Plot (UMAP), and machine learning were used to evaluate matching of models to depression. The top ranked model was a histone deacetylase (HDAC2) conditional knockout in forebrain neurons. Also highly ranked were various models for Alzheimer’s, including APPsa knock-in (2nd overall), APP knockout, and an APP/PS1 humanized double mutant. Other top models were the mitochondrial gene HTRA2 knockout (that is lethal in adulthood), a modified acetylcholinesterase, a Huntington’s disease model, and the CRTC1 knockout. Over 30 stress related models were evaluated and while some matched highly with depression, others did not. In most of the top models, a consistent dysregulation of MAP kinase pathway was identified and the genes NR4A1, BDNF, ARC, EGR2, and PDE7B were consistently downregulated as in humans with depression. Separate male and female portraits of depression were also evaluated to identify potential sex specific depression matches with models. Individual human depression datasets were also evaluated to allow for comparisons across the same brain regions. Heatmap, UMAP, and machine learning results supported the hypergeometric ranking findings. Together, this study provides new insights into how large-scale gene expression patterns may be similarly dysregulated in some animals models and humans with depression that may provide new avenues for understanding and treating depression.

The role of diffuse idiopathic skeletal hyperostosis (DISH) in positive identification.

The use of skeletal pathologies in establishing positive identifications via radiographic comparison is often avoided-and thus understudied-due to the dynamic nature of the skeleton in response to pathological conditions. Using an online survey, this study tests the accuracy of diffuse idiopathic skeletal hyperostosis (DISH), a relatively common vertebral pathology, in making positive identifications through radiographic comparison. Three digital radiographic images from 51 DISH-positive individuals were obtained from the Boston Medical Center: one image taken at a baseline date (Group A), one image taken within 2years from baseline (Group B), and one image taken greater than 4.5years from baseline (Group C). Survey participants were tasked with comparing between simulated lateral "antemortem" and "postmortem" images from living patients and identifying which pair represented the same individual at different time intervals. A total of 40 responses were recorded and analyzed by measuring accuracies, sensitivities, and specificities. Information about survey participants' field, degree, experience working with radiographs, and familiarity with DISH was also recorded. Series 1 compared Group A to Group B images and resulted in an accuracy of 87.3%, sensitivity of 46.9%, and specificity of 94.3%. Series 2 compared Group A to Group C images and resulted in an accuracy of 83.4%, sensitivity of 34.3%, and specificity of 95.8%. The results indicate that the progressive changes associated with DISH render the condition unreliable for making positive identifications but suggest that DISH could be used to winnow potential matches.

Assessing the performance of open-source, semi-automated pattern recognition software for harbour seal (P. v. vitulina) photo ID

Photographic identification (photo ID) is a well-established, non-invasive, and relatively cost-effective technique to collect longitudinal data from species that can be individually recognised based on natural markings. This method has been improved by computer-assisted pattern recognition software which speed up the processing of large numbers of images. Freely available algorithms exist for a wide range of species, but the choice of software can have significant effects on the accuracy of individual capture histories and derived demographic parameter estimates. We tested the performance of three open source, semi-automated pattern recognition software algorithms for harbour seal (Phoca vitulina vitulina) photo ID: ExtractCompare, I3S Pattern and Wild-ID. Performance was measured as the ability of the software to successfully score matching images higher than non-matching images using the cumulative density function (CDF). The CDF for the top ranked potential match was highest for Wild-ID (CDF1 = 0.34–0.58), followed by ExtractCompare (CDF1 = 0.24–0.36) and I3S pattern (CDF1 = 0.02–0.3). This trend emerged regardless of how many potential matches were inspected. The highest performing aspects in ExtractCompare were left heads, whereas in I3S Pattern and Wild-ID these were front heads. Within each aspect, images collected using a camera and lens performed higher than images taken by a camera and scope. Data processing within ExtractCompare took > 4 × longer than Wild-ID, and > 3 × longer than I3S Pattern. We found that overall, Wild-ID outperformed both ExtractCompare and I3S Pattern under tested scenarios, and we therefore recommend its assistance in harbour seal photo ID.

Development of the first DNA database and identification portal for identification of Unidentified bodies in India – UMID

Identifying missing persons and unidentified dead bodies is a well-documented global problem in recent years. To curb this issue, countries such as the USA, UK, and Australia already have well-established DNA databases. Considering the alarming number of unidentified/unclaimed dead bodies reported in India every year, it is evident that the current practices are not sufficient to establish their identities. Forensic medicine professionals are ethically, morally, and dutybound to collect information about missing and unidentified persons and work with the government agencies to determine their identity. Concerning the social and public interest, we have developed the first-ever identification portal and DNA database of unidentified dead bodies autopsied at the Department of Forensic Medicine and Toxicology, AIIMS, New Delhi, India. After the investigation officer's informed consent, biological samples from unidentified dead bodies and a detailed phenotypic description, anthropological data and other visual characteristics of the deceased are recorded at the time of autopsy. This information is uploaded on our database which is available for public access, and the genotypic information generated through STR analysis is only available for internal usage.Claimants (biological relatives) may browse through the URL (https://umid-aiims.icmr.org.in/), and if they wish to claim an unidentified dead body, they may approach as per the given guidelines. The DNA profiles generated include a total of 16 STRs (15 autosomal tetranucleotide microsatellite STRs and 1 Sex Chromosome Specific STR). The claimant's STR profile is run through the questioned database to look for a potential match. If positive, the investigating officer of that particular case is informed for further necessary action. Until December 2020, our database consisted the information of 255 individuals and two unidentified cadavers were identified. This project's success can also lead to a pioneering National DNA database of unidentified and missing persons in India.

Guided neighborhood affine subspace embedding for feature matching

Feature matching, which refers to determining reliable correspondences between two sets of feature points, is a fundamental component of numerous visual tasks. This paper proposes a novel method, termed as guided neighborhood affine subspace embedding (NASE), to eliminate false matches from the given tentative feature matches. Its essential philosophy is to preserve the underlying intrinsic manifold of potential true matches. Specifically, we aim to approximate the manifold of an inlier with an affine subspace fitted on its neighbors by imposing a motion-consistency constraint. Considering that the “corresponding manifold” of inliers may be biased by gross outliers, we introduce a density-based seed point selection strategy for neighborhood refinement. Based on the above two strategies, we further formulate the general feature matching problem into a mathematical optimization model and deduce a closed-form solution with linearithmic time complexity (i.e., O(NlogN)) for mismatch removal. Additionally, we devise a multi-scale strategy for neighborhood construction, making our method more robust to various degradations. Extensive experiments on general feature matching, fundamental matrix estimation, and loop closure detection demonstrate the clear superiority of NASE over the state-of-the-arts.

Using Median-LBPH Algorithm for Real-Time Face Recognition System

Abstract: The LBPH algorithm is used ubiquitously for Face Recognition applications in modern times because of its simplicity of implementation, despite providing high accuracy and less computation time. However, in conditions of varied illumination, face expression and angles at which face images are captured, its confidence is decreased. We propose a slightly modified algorithm that considers the median of the neighbourhood pixels rather than the pixel itself to overcome this issue. This algorithm is called Median-LBPH. The grey value of every pixel is replaced by the median of all the neighbourhood pixel values. Then the features are extracted, and a histogram representing the original image is saved in the model. This model, in turn, can be used to compare with histograms obtained from the faces in real-time footage to find a potential match. This algorithm is used in an end-to-end face recognition system, a web application prototype for Law Enforcement Agencies to maintain a central criminal database shared and accessed across various departments. A live surveillance system is added as part of this novel application so that whenever an already registered criminal appears live on surveillance cameras, a notification will be received, and personnel appropriate Law Enforcement authorities will receive e-mail and text messages through a secured channel. Keywords: Face Recognition, Median-Local Binary Pattern Histogram (MLBPH), Haar Cascade, Adaboost, Neighbourhood Median

Modification of polysulfone and the biomedical application of modified polysulfone

Polysulfone (PSF) as an expected potential biomaterial matches well with the urgent demand in biomedical applications on account of outstanding mechanical and chemical compatibility. In this review, the classification of some biological modifiers by the flow mosaic model was described. Then, several distinct modification approaches to PSF were introduced in detail, including blending, surface coating, and grafting. Moreover, diverse biomedical applications (hemodialysis, membrane oxygenator, cartilage scaffold, and so on) and up-to-date explorations were exhaustively presented to provide more information for further researches. Finally, the challenges in biomedical modifications of PSF were summarized and the potential application in biomedicine was forecasted.

Robust feature matching via neighborhood manifold representation consensus

Feature matching, which aims at seeking dependable correspondences between two sets of features, is of considerable significance to various vision-based tasks. This paper attempts to eliminate false correspondences from given tentative correspondences created on the basis of descriptor similarity. A simple yet efficient approach named neighborhood manifold representation consensus (NMRC) for robust feature matching is presented considering the stable neighborhood topologies of the potential true matches. The core principle of the proposed method is to preserve the local neighborhood structures between two feature points in a potential true match along a low-dimension manifold. Meanwhile, a neighborhood similarity-based iterative filtering strategy for neighborhood construction is designed to improve the matching performance under the circumstance of seriously deteriorated data. The matching problem is further formulated into a mathematical optimization model based on the neighborhood manifold representation and iterative filtering strategy, and a closed-form solution with linearithmic time complexity (i.e., O(NlogN)) is derived, which requires only tens of milliseconds to handle over 1000 putative correspondences. Extensive experiments on general feature matching (F-score > 94% for most cases), remote sensing image registration (RMSE < 3 for most cases), and loop closure detection demonstrate the significant superiority of the proposed method over several state-of-the-art competitors, such as RANSAC, MAGSAC++, and LPM.

Transparency in the Ophthalmology Residency Match: Background, Study, and Implications

BackgroundMedical students are applying to dramatically more ophthalmology residency programs than in the past, causing an increased administrative burden for programs and financial harm to students. This study considers the background of this situation and looks at how a lack of transparency surrounding potential residency match filters contributes. Furthermore, this study raises several potential solutions to this lack of transparency that may increase the functionality of the ophthalmology residency match.ObjectiveThe purpose of this study was to determine the availability and consistency of potential ophthalmology residency match filters through training program websites and the American Medical Association’s (AMA) Residency & Fellowship Database (FREIDA).MethodsThis study was a cross-sectional observational study of ophthalmology residency program websites and AMA's FREIDA database entries. For 119 ophthalmology residency programs, five potential filters were evaluated for both availability and consistency on individual residency websites and FREIDA. These filters were: (1) whether a program required a minimum United States Medical Licensing Examination (USMLE) Step 1 score; (2) minimum number of letters of recommendation required; 3) whether a minimum USMLE Step 2 score was required; (4) if the program accepts the Comprehensive Osteopathic Medical Licensing Examination (COMLEX) sequence in lieu of the USMLE; and (5) ability of the residency to sponsor a visa (J-1, H-1B, or F-1). Each program's website and FREIDA entry were independently evaluated by two authors to increase validity, with a third author brought in to break the tie in case of a disagreement.ResultsOnly two ophthalmology residency programs had information about all five filters both available and consistent on their website and FREIDA. Inter-reviewer reliability was 92.5%.ConclusionsInformation about potential filters used in the ophthalmology residency match is neither publicly available nor consistent. This lack of transparency may contribute to the phenomenon of medical students applying to dramatically more ophthalmology residency programs. A standardized database of these filters is needed to increase transparency to applicants, which may reduce the expenses of medical students and the workload of program directors.

RNALigands: a database and web server for RNA-ligand interactions.

RNA molecules can fold into complex and stable 3D structures, allowing them to carry out important genetic, structural, and regulatory roles inside the cell. These complex structures often contain 3D pockets made up of secondary structural motifs that can be potentially targeted by small molecule ligands. Indeed, many RNA structures in PDB contain bound small molecules, and high-throughput experimental studies have generated a large number of interacting RNA and ligand pairs. There is considerable interest in developing small molecule lead compounds targeting viral RNAs or those RNAs implicated in neurological diseases or cancer. We hypothesize that RNAs that have similar secondary structural motifs may bind to similar small molecule ligands. Toward this goal, we established a database collecting RNA secondary structural motifs and bound small molecule ligands. We further developed a computational pipeline, which takes as input an RNA sequence, predicts its secondary structure, extracts structural motifs, and searches the database for similar secondary structure motifs and interacting small molecule. We demonstrated the utility of the server by querying α-synuclein mRNA 5' UTR sequence and finding potential matches which were validated as correct. The server is publicly available at http://RNALigands.ccbr.utoronto.ca The source code can also be downloaded at https://github.com/SaisaiSun/RNALigands.

Differentiable molecular simulation can learn all the parameters in a coarse-grained force field for proteins.

Finding optimal parameters for force fields used in molecular simulation is a challenging and time-consuming task, partly due to the difficulty of tuning multiple parameters at once. Automatic differentiation presents a general solution: run a simulation, obtain gradients of a loss function with respect to all the parameters, and use these to improve the force field. This approach takes advantage of the deep learning revolution whilst retaining the interpretability and efficiency of existing force fields. We demonstrate that this is possible by parameterising a simple coarse-grained force field for proteins, based on training simulations of up to 2,000 steps learning to keep the native structure stable. The learned potential matches chemical knowledge and PDB data, can fold and reproduce the dynamics of small proteins, and shows ability in protein design and model scoring applications. Problems in applying differentiable molecular simulation to all-atom models of proteins are discussed along with possible solutions and the variety of available loss functions. The learned potential, simulation scripts and training code are made available at https://github.com/psipred/cgdms.

Pillin: A Family of Sword Cutlers

To many with an interest in British military swords the name of Pillin will be very familiar. Yet, for a firm which traded for at least 65 years there is little information available about its activities beyond a few bare dates and addresses often quoted from the same sources. The original source of much of this information is unclear and some of this now appears questionable. In writing this article my intention is to provide a more comprehensive account of the Pillin dynasty. By examining what new evidence may be available I hope to evaluate and revise contemporary wisdom regarding Pillin’s operations. In conducting this research during a global Covid-19 pandemic, amid national and local lockdowns, I am restricted in source material but have relied heavily on sources available online. Such methodology carries its own risks, there are gaps in the available datasets and frustratingly, transcription errors can both hamper searches and offer false positive matches. Nevertheless, with the rise in popularity of ancestry research, new data sources are constantly being made available. In today’s world of social media and online resources we have ready access to data of which researchers even 15 years ago could only have dreamed. Information regarding sword cutlers, such as their trading dates and addresses, is of particular interest as it can help to correctly date a sword. This in turn can assist with identifying an original owner. In the case of British blades, etched with the owner’s initials or a family crest, cross referencing with the Army lists will often provide multiple possible candidates over the lifetime of a sword pattern. Accurately identifying the year of manufacture can significantly assist in narrowing the field of potential matches against any one set of initials. A desire to identify the original owners of some of my own collected swords, and to assist others to do the same, provided the seed of motivation for my research into the Pillin dynasty. I hope this article provides a useful platform for additional research.

Strategic fit of mergers and acquisitions in Latin American airlines: a two-stage DEA approach

PurposeThe purpose of this paper is to assess the efficiency determinants of mergers and acquisitions (M&A) in the context of Latin American airlines based on business-related variables commonly found in the literature. The idea is to identify preferable potential airline matches in light of fleet mix, ownership structure and geographical proximity.Design/methodology/approachIn order to achieve the objective, all possible combinations of M&A pairs are considered in the analysis, which is developed in a two-stage approach. First, the M&A Data Envelopment Analysis model efficiency and returns-to-scale estimates are computed. Then, robust regression and multinomial logistic regression are respectively used to discriminate these estimates in terms of such business-related variables.FindingsThe results reveal that these different contextual variables significantly impact virtual efficiency and returns-to-scale levels. Private ownership, passenger focus and a better match between aircraft size and demand for flights appear to be key drivers for merged airline efficiency.Research limitations/implicationsThe study makes theoretical contributions, though limited to analyzing Latin American airlines only. The use of bootstrapped robust/multinominal logistic regression, compared to the methods adopted by previous literature studies, generates more accurate and robust results related to the efficiency drivers due to its special feature and ability to allow the discrimination of increasing, decreasing, and constant returns to scale in light of a given set of contextual variables.Practical implicationsThis study examines the pure effect of the merging activity on efficiency gains. Not only private ownership but also a hybrid public–private ownership has a positive influence on virtual efficiency, suggesting an important governmental role in promoting M&A in the airline industry.Originality/valueThe authors present an original take on the issue of airline mergers by exploring what are the major drivers possibly involved in efficiency gains of potentially merged (virtual) airlines. The authors identify preferable potential airline matches where efficiency gains would be positive in light of business-related variables such as fleet mix, ownership structure and geographical proximity. The analysis also includes an assessment of the impact of contextual variables such as cargo type, ownership structure and geographical proximity in relation to the strategic fit of mergers considering the resulting efficiency and returns-to-scale scores of virtually merged airlines. To the authors’ knowledge, no previous research has addressed these issues in Latin American airlines. Further research directions for this industry are also discussed.

P–559 Proof of principle for Extended Carrier Screening (ECS) in medically assisted reproduction: First 33 cases of genetic matching for donors and recipients

Abstract Study question Does implementation of ECS to reduce reproductive risk when using a donor with a known carrier status serves as a wider model for ART patients. Summary answer ECS should be routinely offered to ART patients using their own or donor gametes to reduce risk of having a child with a recessive condition. What is known already Responsible implementation of ECS in assisted reproduction is required as commercial offerings increase and become more accessible; ESHRE ethical guidelines are shortly to be published after consideration of stakeholder reviews. Increasingly ECS is included in donor screening, rejecting potential donors for a known carrier status will reduce donor gamete availability. Clinics should consider potential match yield in carrier panels to develop tools and specialist support to deliver and guide patients to help make informed decisions for ECS. Study design, size, duration Retrospective evaluation of ECS results for the first 33 patients who undertook counter screening in the clinic setting from April 2020 to December 2020 before using a donor with known carrier status. The findings would serve as proof of concept for wider application. Participants/materials, setting, methods Patients had opted to undertake ECS after discussion of risk estimates, family history review and personal options.Testing was commissioned between two ECS providers for international donor banks using panels of 283+ genes. Incidence of carrier match, the number of variants reported, and their clinical significance were reviewed. Main results and the role of chance: Of the 33 co-carrier tests, one carrier match for a patient and potential donor was identified. 41%, 26%, 9% and 3% of patients were carriers of 1, 2, 3 and 4 pathogenic variants respectively in 30 different genes. In 21% of patients, no pathogenic variants were reported. Of the variants identified as incidental findings, six were actionable and eligible for cascade screening to the wider family. This included Cystic Fibrosis, Sickle cell and Thalassemia. A variant for Familial hypercholesterolemia had preventative value. An incidental finding of a fragile X pre-mutation allowed for PGT-M as part of planned treatment Limitations, reasons for caution Findings from this first cohort of 33 tests may not represent the general population, follow up evaluation as participant numbers increase is required. Wider implications of the findings: Implementation of guidelines is required to ensure consistency of methodology and availability of transparent information for ECS to ART patients. Incidental findings may be of value to the patient and wider family. Trial registration number Not applicable

PLATYMATCH – A particle-matching algorithm for the analysis of platy particle kinematics using X-ray Computed Tomography

Particle scale mechanisms influence the mechanical behaviour of geomaterials. A better understanding of soil micromechanics will help develop more accurate constitutive models and, by extension, safer and more economic geotechnical design. Sand-grained soils have been widely studied at the particle scale using X-ray Computed tomography and this has revealed important micromechanical behaviour of sands. Clays are least understood and studied at the particle scale. As technology rapidly progresses, to understand clay kinematics, a particle kinematic algorithm to match plate shaped (platy) particles will be required. Current algorithms developed for the matching of quartz and carbonate sand particles may not be suitable, since particle attributes that are strong discriminators of round particles may be less unique on platy particles, due to their extremely small c-axis and the reduced image resolution associated with their smaller size. This study presents, particle tracking of kaolin sample using mica markers and provides a platy soil particle matching algorithm for evaluating platy particle kinematics. After testing a range of alternative particle attributes, it was observed that a combination of particle major axis length, intermediate axis length, and perimeter was a good discriminant of the platy mica particles studied. On this basis, we developed PLATYMATCH, an optimised platy particle matching algorithm that considers a minimised combined normalised error of unique particle attributes within a defined search volume space. The algorithm was implemented such that particle attributes were compared in parallel, rather than sequentially, to avoid filtering out a potential particle match based on a single non-unique attribute. PLATYMATCH was then successfully validated using a compressed mica soil sample.

Influences of soil and biochar properties and amount of biochar and fertilizer on the performance of biochar in improving plant photosynthetic rate: A meta-analysis

Most studies found the benefit of biochar in increasing plant photosynthetic rate (PR), but how experimental conditions affect PR response to biochar application remains unclear. Therefore, we performed a meta-analysis by including 965 pairwise comparisons from 135 studies. Generally, biochar application enhanced PR by 23 % on average, a statistically significant increase relative to the control. However, a large variation of percent change in PR ranging from −59 to +1267 % was also observed under different experimental conditions. Specifically, biochar properties including contents of potassium (K), phosphorus (P), sodium (Na), carbon (C) and ash and their determining factors (feedstock and pyrolysis temperature) significantly influenced PR responses to biochar addition, while biochar pH could not be used alone as an effective predictor of PR increases after biochar treatment. There was a potential match between soil pH and biochar pH, determining the performance of biochar in improving crop PR. However, the complementarity between soil pH and biochar pH was not sufficient to achieve the maximum increase in PR, appropriate biochar application rate was needed at the same time. The most suitable application rate of biochar was 10.1−20 t ha−1 or 2.01–4 %. Moreover, it is essential to take the compatibility and complementarity between biochar, soil texture and management factors such as Nitrogen (N) application rate and growing environment into consideration. Overall, adding biochar into coarse textured soils or heavy metal contaminated soils is highly recommended for increasing plant PR. Co-application of biochar with nitrogen fertilizer is also worth being advocated. When the N application rate was 101−200 kg ha−1 or ≤ 0.015 %, the maximum increase in PR was obtained. These findings can provide suggestions for biochar application in agricultural production to optimize PR benefits.

Assessment on effects of transplastomic potato plants expressing Colorado potato beetle β-Actin double-stranded RNAs for three non-target pests

RNA interference has been proved as an efficient technology for pest control through the silencing of essential genes of targeted insects. We had previously shown that the expression of double-stranded RNAs (dsRNAs) in plastids of plants offers a great potential for efficiently controlling Colorado potato beetle (CPB, Leptinotarsa decemlineata) (Coleoptera, Chrysomelidae). However, whether these transplastomic plants have an impact on other non-target pests was not investigated. In this study, we evaluated the potential effects of transplastomic plants expression dsRNAs target CPB β-Actin (referred to as ACT plants) on three other potato pests: Myzus persicae (Hemiptera, Aphididae), Henosepilachna vigintioctopunctata (Coleoptera, Coccinellidae), and Spodoptera litura (Lepidoptera, Noctuidae). Although no effects on M. persicae or S. litura were observed by feeding ACT plants, we found that feeding H. vigintioctopunctata with ACT plants can result in its growth retardation and suppressing the gene expression of HvACT, which has 91.7% identity to CPB β-Actin and shared 66 potential 21-mer matches. Taking together, these results indicated that ACT plants had cross-resistance to H. vigintioctopunctata, another coleopteran insect with the highly conserved nucleotide sequence of β-Actin gene. It also provided an opportunity to simultaneously control L. decemlineata and H. vigintioctopunctata by RNAi induced by intermediate dsRNAs with optimized sequences.