Original File Research Articles

Listening for Silences: The Trap of Biased Sources

Listening for Silences: The Trap of Biased Sources

Blind Updates in Coded Caching

We consider the centralized coded caching system where a library of files is available at the server and their subfiles are cached at the clients as prescribed by a placement delivery array (PDA). We are interested in the problem where a specific file in the library is replaced with a new file at the server, the contents of which are correlated with the file being replaced, and this change needs to be communicated to the caches. Upon replacement, the server has access only to the updated file and is unaware of its differences with the original, while each cache has access to specific subfiles of the original file as dictated by the PDA. Scenarios such as (a) updating an unlogged file library, (b) ensuring privacy of updated subfiles against an eavesdropper, and (c) correcting errors in the client caches, can be captured as special cases of this problem framework. We model the correlation between the updated and the original files by assuming that they differ in at the most <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\epsilon $ </tex-math></inline-formula> subfiles, and aim to reduce the number of bits broadcast by the server to update the caches. We design a new elegant coded transmission strategy for the server to update the caches blindly, and also identify another simple scheme that is based on MDS codes. We then derive converse bounds on the minimum communication cost <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\ell ^{*}$ </tex-math></inline-formula> among all linear strategies. For two well-known families of PDAs – Maddah-Ali & Niesen’s caching scheme and a PDA by Tang & Ramamoorthy and Yan <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">et al.</i> – our new scheme has cost <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\ell ^{*}(1 + o(1))$ </tex-math></inline-formula> as the number of users grows large, when the updates are sufficiently sparse and the caching ratio is an arbitrary constant; whereas the scheme using MDS codes has order-optimal cost when the updates are dense.

Using genderize.io to infer the gender of first names: how to improve the accuracy of the inference

Objective:We recently showed that genderize.io is not a sufficiently powerful gender detection tool due to a large number of nonclassifications. In the present study, we aimed to assess whether the accuracy of inference by genderize.io can be improved by manipulating the first names in the database.Methods:We used a database containing the first names, surnames, and gender of 6,131 physicians practicing in a multicultural country (Switzerland). We uploaded the original CSV file (file #1), the file obtained after removing all diacritic marks, such as accents and cedilla (file #2), and the file obtained after removing all diacritic marks and retaining only the first term of the compound first names (file #3). For each file, we computed three performance metrics: proportion of misclassifications (errorCodedWithoutNA), proportion of nonclassifications (naCoded), and proportion of misclassifications and nonclassifications (errorCoded).Results:naCoded, which was high for file #1 (16.4%), was reduced after data manipulation (file #2: 11.7%, file #3: 0.4%). As the increase in the number of misclassifications was small, the overall performance of genderize.io (i.e., errorCoded) improved, especially for file #3 (file #1: 17.7%, file #2: 13.0%, and file #3: 2.3%).Conclusions:A relatively simple manipulation of the data improved the accuracy of gender inference by genderize.io. We recommend using genderize.io only with files that were modified in this way.

The mindset of extreme right-wing youth in neofascist songs from the late seventies

ABSTRACT The article analyses the mindset of right-wing extremist youth during the second wave of the protest movement in the seventies, making use of a source that historians have totally overlooked, namely neofascist political song. These songs were all but entirely self-produced, independently of the record industry, and scarce availability has led to them being largely forgotten. However, thanks to recent publications, along with many original audio files uploaded to YouTube, it is now possible to access this documentary heritage and enter a world of images, symbols and portrayals that, in the second half of the seventies, represented a clean break with classical neofascist iconography.

ANALISIS PENETAPAN ANGKA KREDIT KENAIKAN JABATAN FUNGSIONAL GURU SMAN/SMKN DI DINAS PENDIDIKAN PROVINSI JAWA BARAT

The research entitled "Analysis of Determination of Credit Scores for Promotion of Functional Positions for SMAN / Vocational Teachers at the Education Office of West Java Province" in general this research is to find out and obtain an overview of the determination of credit scores and promotions / teacher positions in the Education Office of West Java Province. The method used in this research is descriptive using a qualitative approach, data collection techniques with interviews, observations, and documentation studies. The results showed that many teachers did not meet the requirements in following the determination of credit scores. The credit score is a unit of value for each item of activity and/or the accumulated value of the items of activity that must be achieved by a teacher in the context of fostering a career of rank and position. In accordance with the Joint Regulation of the Minister of National Education and the Head of the State Civil Service Agency Number 03/V/PB/2010 Number 14 of 2010 the official authorized to propose the determination of the credit score submits the proposal for determining the credit score to the official authorized to determine the credit score through the secretariat of the assessment team. For the flow in applying for the determination of the teacher credit score, the teacher first uploads the file on the OPAK (Online Determination of Credit Score) application, then the original file is sent to the KCD (Office Branch Office), then to the Provincial Education Office which is managed by the Development Section. In 2018 the December period that passed only 205 (20.9%) experienced an increase in 2019 the June period which passed 952 (69.1%) while in 2020 the June period decreased again to 488 (54.6%). At the 2020 credit score determination session, there was a decrease in teachers who submitted a trial from 2019 because there was no appeal period and the impact of the COVID-19 pandemic was one of the inhibiting factors.

IoT-based Cloud Service for Secured Android Markets using PDG-based Deep Learning Classification

Software piracy is an act of illegal stealing and distributing commercial software either for revenue or identify theft. Pirated applications on Android app stores are harming developers and their users by clone scammers. The scammers usually generate pirated versions of the same applications and publish them in different open-source app stores. There is no centralized system between these app stores to prevent scammers from publishing pirated applications. As most of the app stores are hosted on cloud storage, therefore a cloud-based interaction system can prevent scammers from publishing pirated applications. In this paper, we proposed IoT-based cloud architecture for clone detection using program dependency analysis. First, the newly submitted APK and possible original files are selected from app stores. The APK Extractor and JDEX decompiler extract APK and DEX files for Java source code analysis. The dependency graphs of Java files are generated to extract a set of weighted features. The Stacked-Long Short-Term Memory (S-LSTM) deep learning model is designed to predict possible clones. Experimental results have shown that the proposed approach can achieve an average accuracy of 95.48% among clones from different application stores.

Recovering elevation in seismic datasets using Google Earth: A case study of Parnaíba Basin

Static corrections, especially in old land data, can be a challenging issue for adequate seismic processing and imaging. A frequently encountered problem is the lack of reliable elevation data for sources and receivers. In this work, we propose a simple method to reconstruct the elevation data for each seismic trace for a given dataset using freely available information. Such reconstruction enables all subsequent processing steps to be carried out in a proper way. As a proof of concept, we applied this methodology to a 30-year-old dataset from Parnaíba Basin, Brazil, and compared with refraction and residual statics results obtained with the elevation data recorded in the original seismic file header. The proposed method outperformed the original elevation results, being able to increase image quality and signal-to-noise ratio.

The Bridge between Screening and Assessment: Establishment and Application of Online Screening Platform for Food Risk Substances

In order to improve the risk identification ability of the technical support system of food safety supervision, an online screening platform for food risk substances (hereafter referred to as “platform”) was established. The platform aims at the qualitative analysis of unknown compounds and consists of three parts: a standard spectrum library, screening model, and online comparison module. The standard library contains the standard spectra of 527 food risk substances by high-performance liquid chromatography/high-resolution mass spectrometry. The screening comparison algorithm, the core of the screening model, is obtained through the improvement of the existing spectral library search algorithm. The inspector uploads the original spectrum file through the online comparison module; the online comparison module calls the corresponding script to convert the original spectrum file into a standard spectrum file and then uses the screening and comparison algorithm to achieve online real-time comparison. The comparison results are used to determine whether the sample to be tested contains the food risk substances contained in the standard library, so as to realize the preliminary screening of potential food risk substances. The platform supports the spectrogram data format of mainstream instrument manufacturers. The standard spectrogram database can be coconstructed and shared by cooperative laboratories to effectively enrich the types of food risk substances. Through laboratory comparison, data calibration, and model optimization, the screening accuracy of the platform can reach more than 97%. The platform adopts the Internet online screening method, which greatly facilitates the risk investigation and control of national food safety inspection and testing institutions. At the same time, the construction of the screening platform for food risk substances based on high-performance liquid chromatography/high-resolution mass spectrometry, the Internet, big data, and other technologies will provide a new technical means for food safety risk management and control. Hence, it can build a bridge between the screening of risk substances and illegally added substances, as well as risk assessment, risk management, and control.

Mspack: efficient lossless and lossy mass spectrometry data compression.

Mass spectrometry (MS) data, used for proteomics and metabolomics analyses, have seen considerable growth in the last years. Aiming at reducing the associated storage costs, dedicated compression algorithms for MS data have been proposed, such as MassComp and MSNumpress. However, these algorithms focus on either lossless or lossy compression, respectively, and do not exploit the additional redundancy existing across scans contained in a single file. We introduce mspack, a compression algorithm for MS data that exploits this additional redundancy and that supports both lossless and lossy compression, as well as the mzML and the legacy mzXML formats. mspack applies several preprocessing lossless transforms and optional lossy transforms with a configurable error, followed by the general purpose compressors gzip or bsc to achieve a higher compression ratio. We tested mspack on several datasets generated by commonly used MS instruments. When used with the bsc compression backend, mspack achieves on average 76% smaller file sizes for lossless compression and 94% smaller file sizes for lossy compression, as compared with the original files. Lossless mspack achieves 10-60% lower file sizes than MassComp, and lossy mspack compresses 36-60% better than the lossy MSNumpress, for the same error, while exhibiting comparable accuracy and running time. mspack is implemented in C++ and freely available at https://github.com/fhanau/mspack under the Apache license. Supplementary data are available at Bioinformatics online.

Trueness and precision of 3D-printed versus milled monolithic zirconia crowns: An in vitro study

PurposeTo compare the trueness and precision of 3D-printed versus milled monolithic zirconia crowns (MZCs). MethodsA model of a maxilla with a prepared premolar was scanned with an industrial scanner (ATOSQ®, Gom) and an MZC was designed in computer-assisted-design (CAD) software (DentalCad®, Exocad). From that standard tessellation language (STL) file, 10 MZCs (test) were 3D-printed with a Lithography-based Ceramic Manufacturing (LCM) printer (CerafabS65®, Lithoz) and 10 MZCs (control) were milled using a 5-axis machine (DWX-52D®, DGShape). All MZCs were sintered and scanned with the aforementioned scanner. The surface data of each sample (overall crown, marginal area, occlusal surface) were superimposed to the original CAD file (ControlX®, Geomagic) to evaluate trueness: (90-10)/2, absolute average (ABS AVG) and root mean square (RMS) values were obtained for test and control groups (MathLab®, Mathworks) and used for analysis. Finally, the clinical precision (marginal adaptation, interproximal contacts) of test and control MZCs was investigated on a split-cast model printed (Solflex350®, Voco) from the CAD project, and compared. ResultsThe milled MZCs had a significantly higher trueness than the 3D-printed ones, overall [(90-10)/2 printed 37.8 µm vs milled 21.2 µm; ABS AVG printed 27.2 µm vs milled 15.1 µm; RMS printed 33.2 µm vs milled 20.5 µm; p = 0.000005], at the margins [(90-10)/2 printed 25.6 µm vs milled 12.4 µm; ABS AVG printed 17.8 µm vs milled 9.4 µm; RMS printed 22.8 µm vs milled 15.6 µm; p= 0.000011] and at the occlusal level [(90-10)/2 printed 50.4 µm vs milled 21.9 µm; ABS AVG printed 29.6 µm vs milled 14.7 µm; RMS printed 38.9 µm vs milled 22.5 µm; p = 0.000005]. However, with regard to precision, both test and control groups scored highly, with no significant difference either in the quality of interproximal contact points (p = 0.355) or marginal closure (p = 0.355). ConclusionsMilled MZCs had a statistically higher trueness than 3D-printed ones; all crowns, however, showed high precision, compatible with the clinical use. Clinical significanceAlthough milled MZCs remain more accurate than 3D-printed ones, the LCM technique seems able to guarantee the production of clinically precise zirconia crowns.

Pitfalls of Advanced Retinopathy of Prematurity Presentation: A Content Analysis of Medical Records.

PurposeTo identify the pitfalls in retinopathy of prematurity (ROP) screening leading to advanced disease at Ministry of Health (MOH) hospitals in Saudi Arabia.MethodsA qualitative deductive content analysis was used to study the phenomena of defects in ROP screening. A retrospective review of medical records of newborns presenting to two tertiary eye care centers with advanced ROP (stage 4 and 5) from January 2012 to June 2019 was completed. An extensive review of the original files at the referring hospitals was conducted, including the general condition and findings of ophthalmic examination and the sequence of follow-up until the infant was discharged/referred. Data analysis was completed using pre-structured categorization matrix.ResultsRecords of 29 infants with advanced stage ROP were identified. Only 13 medical records were available and obtained. The pitfalls in screening found in the study were failure to refer by the neonatologist, delayed follow-up by the ophthalmologist, failure to follow-up by the ophthalmologist, failure to diagnose by the ophthalmologist, poor documentation in patient files, unavailability of ophthalmologist, family negligence, lack of treatment and delayed referral to a higher center, and progression despite timely screening and management.ConclusionAlthough clear ROP screening guidelines are available, implementations of these guidelines are suboptimal. This study showed that the most common defect in screening is physician’s inadequacy and unavailability. A proper network of competent ROP screening physicians in all neonatal intensive care units should be established. Centers for advanced ROP surgery should be allocated to deliver a timely surgical care if needed.

Sampling Rate Impact on Precise Point Positioning with a Low-Cost GNSS Receiver

Nowadays, with the incursion of low-cost GNSS receivers with modern characteristics, it is common to investigate and apply new methodologies and solutions with different receivers of this nature. Based on this fact, the performance of the solution obtained from the low-cost GNSS receiver is evaluated compared to a geodetic grade GNSS receiver at different sampling frequencies for the PPP-static and PPP-kinematic modes. For this, the original RINEX observation files were analyzed and decimated into different sampling rates as 0.1, 0.2, 1, 5, 15 and 30 s with TEQC software. All RINEX files were submitted to the Canadian Spatial Reference System Precise Point Positioning (CSRS-PPP) online service for processing with static and kinematic modes. The PPP-derived coordinates from the low-cost GNSS receiver were compared with the geodetic receiver to evaluate the obtained solution. The results reveal that the behavior of all studied sampling rates from the low-cost GNSS receiver are constant in achieved positioning. In addition, the achieved precision shows that it is recommendable to use a high sampling rate to obtain a cm level in PPP-static mode by using a low-cost GNSS receiver, this mode being the most accurate and potential alternative for structural health monitoring studies, mapping and positioning in urban areas.

Effects of content trimming iPhone 12 Pro Max video files in iOS 14.

In this audio/video authenticity research project, 44 original MOV files were produced on an Apple iPhone 12 Pro Max mobile device, running the iOS 14.2.1 operating system, in all available video formats and at four different nominal recording lengths. Each of the original files was then trimmed, using the Apple Photos app, in three different ways: deleting a portion of the beginning, a portion of the end, and portions of both the beginning and end. These 176 original and trimmed files were transferred to a laboratory computer and the footer and other metadata were analyzed with a hex editor. This analysis revealed that the trimmed recordings could be differentiated from the originals; that the iPhone model and the iOS operating system version could be identified; that important recording dates and times can be determined; and that the type of trimming, in some cases, could be determined.

A Dataset of Photos and Videos for Digital Forensics Analysis Using Machine Learning Processing

Deepfake and manipulated digital photos and videos are being increasingly used in a myriad of cybercrimes. Ransomware, the dissemination of fake news, and digital kidnapping-related crimes are the most recurrent, in which tampered multimedia content has been the primordial disseminating vehicle. Digital forensic analysis tools are being widely used by criminal investigations to automate the identification of digital evidence in seized electronic equipment. The number of files to be processed and the complexity of the crimes under analysis have highlighted the need to employ efficient digital forensics techniques grounded on state-of-the-art technologies. Machine Learning (ML) researchers have been challenged to apply techniques and methods to improve the automatic detection of manipulated multimedia content. However, the implementation of such methods have not yet been massively incorporated into digital forensic tools, mostly due to the lack of realistic and well-structured datasets of photos and videos. The diversity and richness of the datasets are crucial to benchmark the ML models and to evaluate their appropriateness to be applied in real-world digital forensics applications. An example is the development of third-party modules for the widely used Autopsy digital forensic application. This paper presents a dataset obtained by extracting a set of simple features from genuine and manipulated photos and videos, which are part of state-of-the-art existing datasets. The resulting dataset is balanced, and each entry comprises a label and a vector of numeric values corresponding to the features extracted through a Discrete Fourier Transform (DFT). The dataset is available in a GitHub repository, and the total amount of photos and video frames is 40,588 and 12,400, respectively. The dataset was validated and benchmarked with deep learning Convolutional Neural Networks (CNN) and Support Vector Machines (SVM) methods; however, a plethora of other existing ones can be applied. Generically, the results show a better F1-score for CNN when comparing with SVM, both for photos and videos processing. CNN achieved an F1-score of 0.9968 and 0.8415 for photos and videos, respectively. Regarding SVM, the results obtained with 5-fold cross-validation are 0.9953 and 0.7955, respectively, for photos and videos processing. A set of methods written in Python is available for the researchers, namely to preprocess and extract the features from the original photos and videos files and to build the training and testing sets. Additional methods are also available to convert the original PKL files into CSV and TXT, which gives more flexibility for the ML researchers to use the dataset on existing ML frameworks and tools.

Patenting Inventions or Inventing Patents? Strategic Use of Continuations at the USPTO

Continuations allow inventors to claim technology developed after the original filing date of a patent, leading to concerns about inadvertent infringement and hold-up. For researchers seeking to study this practice, a key challenge is the difficulty of linking patent applications to potentially infringing technology. We use the link created by disclosure of standard essential patents (SEPs) to analyze the relationship between standard publication -- a key observable milestone in technology development -- and continuation filing. More than half of the SEPs in our data are filed after standard publication. There is a substantial increase in continuation filings immediately after standard publication, and this increase is larger when the initial patent examiner is more lenient. We also find that claims in SEP continuations are more likely to be rejected for double patenting (indicating an effort to change the scope of previous patents), and that keywords in the claims of SEPs linked to the same standard become more similar after standard publication. Overall, these findings suggest widespread use of continuation procedures to opportunistically

An ensemble learning approach to digital corona virus preliminary screening from cough sounds

This work develops a robust classifier for a COVID-19 pre-screening model from crowdsourced cough sound data. The crowdsourced cough recordings contain a variable number of coughs, with some input sound files more informative than the others. Accurate detection of COVID-19 from the sound datasets requires overcoming two main challenges (i) the variable number of coughs in each recording and (ii) the low number of COVID-positive cases compared to healthy coughs in the data. We use two open datasets of crowdsourced cough recordings and segment each cough recording into non-overlapping coughs. The segmentation enriches the original data without oversampling by splitting the original cough sound files into non-overlapping segments. Splitting the sound files enables us to increase the samples of the minority class (COVID-19) without changing the feature distribution of the COVID-19 samples resulted from applying oversampling techniques. Each cough sound segment is transformed into six image representations for further analyses. We conduct extensive experiments with shallow machine learning, Convolutional Neural Network (CNN), and pre-trained CNN models. The results of our models were compared to other recently published papers that apply machine learning to cough sound data for COVID-19 detection. Our method demonstrated a high performance using an ensemble model on the testing dataset with area under receiver operating characteristics curve = 0.77, precision = 0.80, recall = 0.71, F1 measure = 0.75, and Kappa = 0.53. The results show an improvement in the prediction accuracy of our COVID-19 pre-screening model compared to the other models.

Secure audio file indexing based on hidden markov model (HMM) on the cloud storage

With the introduction of many social media applications and the exponential growth of the number of people using such applications to exchange Audio files as a main way of conveying confidential messages relaying on public telecommunications and networks. The need arise to secure audio data files and preserve the integrity of the message while traversing public networks and when the data is at rest in the cloud. Therefore, in this research, to ensure confidentiality and integrity of the audio files while reducing storage space several algorithms have been devised. To achieve this, we utilized Public key infrastructure and Hash functions along with Hidden Markov Models (HMM). The results show a significant drop in the storage space needed while remarkable reduction in network transmission time. When comparing the original audio file size with the converted file size after applying HMM, the results show a variation between 0% and 10% only, with over 50% reduction in the storage space in some cases.

PHYSICAL CONTENT OF COMPUTER STEGANOGRAPHY

Introduction. The development of computer technology has given a new impetus to the use of computer steganography. However, it is important to understand the physical content of this type of steganography.Purpose. The work aims to describe the practical use and physical content of the phenomenon of computer steganography, the results of the study on the hiding of files in the stegocontainer.Results. Describes the main ns currently computer steganography methods are actively used to solve the following tasks: Protection of confidential information from unauthorized access, overcoming monitoring and management of net-work resources, software camouflage, copyright protection, which is manifested in the use of digital watermarks, is one of the most promising areas of computer steganography. Among the methods of hiding information in images, the most common is the category of algorithms using the lower bits of the image data. They are considered in this paper. These algorithms are based on the fact that in some file formats, the lower bits of the values, although present in the file, but do not affect a person's perception of sound or image. The steganographic software S-Tools was chosen for the study. We created two test monotonous images with the size of 50 × 50 pixels in 24-bit bmp format to analyze the peculiarities of the placement of stego-data in container files. We chose black and white images for the study. A text file was hidden in each of the images, after which the reverse action was performed - extracting the file. As a result of hiding, two stego files were obtained. The paper compared the binary content of the original images and files containing private data. For comparison, the binary content of the black square image and the contents of the stegocontainer with a latent text file are given. Note that the contents of the container and the stego file are only partially listed, but the addresses of the memory cells have selected accordingly. The right column shows the contents of the memory cells in hexadecimal format. The bytes that display the colour of the square are set to "00" because the original image contains only black. We noted that the contents of the cells responsible for the image changed after hiding additional data (this reflected by cells with values of "01"). The paper also describes the procedure for hiding a group of different types of files. During the study, we found that the image file (1920 × 1080 pixels) with a volume of 6,220,854 bytes can hide 777,584 bytes of information.Conclusion. When using steganography, the program uses some algorithms that hide confidential data among the contents of the container: bits of the hidden file replace the bits of the original file at random positions. Thus, the size of the source file and the container file (containing the attached information) is the same, even if you hide a different number of files or different amounts of data.

Windowed multipole representation of R -matrix cross sections

Nuclear cross sections are basic inputs to any nuclear computation. Campaigns of experiments are fitted with the parametric R-matrix model of quantum nuclear interactions, and the resulting cross sections are documented - both point-wise and as resonance parameters (with uncertainties) - in standard evaluated nuclear data libraries (ENDF, JEFF, BROND, JENDL, CENDL, TENDL): these constitute our common knowledge of fundamental nuclear physics. In the past decade, a collaborative effort has been deployed to establish a new nuclear cross section library format - the Windowed Multipole Library - with the goal of considerably reducing the cost of cross section calculations in nuclear transport simulations. This article lays the theoretical foundations underpinning these efforts. From general R-matrix scattering theory, we derive the windowed multipole representation of nuclear cross sections. Though physically and mathematically equivalent, the windowed multipole representation is particularly well suited for subsequent temperature treatment of angle-integrated cross sections: we show that accurate Doppler broadening can be performed analytically up to the first reaction threshold; and we derive cross sections temperature derivatives to any order. Furthermore, we here establish a way of converting the R-matrix resonance parameters uncertainty (covariance matrices) into windowed multipole parameters uncertainty. We show that generating stochastic nuclear cross sections by sampling from the resulting windowed multipole covariance matrix can reproduce the cross section uncertainty in the original nuclear data file. Through this foundational article, we hope to make the Windowed Multipole Representation accessible, reproducible, and usable for the nuclear physics community, as well as provide the theoretical basis for future research on expanding its capabilities.

New targets acquired: Improving locus recovery from the Angiosperms353 probe set.

PREMISEUniversal target enrichment kits maximize utility across wide evolutionary breadth while minimizing the number of baits required to create a cost‐efficient kit. The Angiosperms353 kit has been successfully used to capture loci throughout the angiosperms, but the default target reference file includes sequence information from only 6–18 taxa per locus. Consequently, reads sequenced from on‐target DNA molecules may fail to map to references, resulting in fewer on‐target reads for assembly, and reducing locus recovery.METHODSWe expanded the Angiosperms353 target file, incorporating sequences from 566 transcriptomes to produce a ‘mega353’ target file, with each locus represented by 17–373 taxa. This mega353 file is a drop‐in replacement for the original Angiosperms353 file in HybPiper analyses. We provide tools to subsample the file based on user‐selected taxon groups, and to incorporate other transcriptome or protein‐coding gene data sets.RESULTSCompared to the default Angiosperms353 file, the mega353 file increased the percentage of on‐target reads by an average of 32%, increased locus recovery at 75% length by 49%, and increased the total length of the concatenated loci by 29%.DISCUSSIONIncreasing the phylogenetic density of the target reference file results in improved recovery of target capture loci. The mega353 file and associated scripts are available at: https://github.com/chrisjackson‐pellicle/NewTargets.