Alignment Procedure Research Articles

Microfluidic Device for Microinjection of Caenorhabditis elegans.

Microinjection is an established and reliable method to deliver transgenic constructs and other reagents to specific locations in C. elegans worms. Specifically, microinjection of a desired DNA construct into the distal gonad is the most widely used method to generate germ-line transformation of C. elegans. Although, current C. elegans microinjection method is effective to produce transgenic worms, it requires expensive multi degree of freedom (DOF) micromanipulator, careful injection alignment procedure and skilled operator, all of which make it slow and not suitable for scaling to high throughput. A few microfabricated microinjectors have been developed recently to address these issues. However, none of them are capable of immobilizing a freely mobile animal such as C. elegans worm using a passive immobilization mechanism. Here, a microfluidic microinjector was developed to passively immobilize a freely mobile animal such as C. elegans and simultaneously perform microinjection by using a simple and fast mechanism for needle actuation. The entire process of the microinjection takes ~30 s which includes 10 s for worm loading and aligning, 5 s needle penetration, 5 s reagent injection and 5 s worm unloading. The device is suitable for high-throughput and can be potentially used for creating transgenic C. elegans.

Nanoscopic X-ray tomography for correlative microscopy of a small meiofaunal sea-cucumber

In the field of correlative microscopy, light and electron microscopy form a powerful combination for morphological analyses in zoology. Due to sample thickness limitations, these imaging techniques often require sectioning to investigate small animals and thereby suffer from various artefacts. A recently introduced nanoscopic X-ray computed tomography (NanoCT) setup has been used to image several biological objects, none that were, however, embedded into resin, which is prerequisite for a multitude of correlative applications. In this study, we assess the value of this NanoCT for correlative microscopy. For this purpose, we imaged a resin-embedded, meiofaunal sea cucumber with an approximate length of 1 mm, where microCT would yield only little information about the internal anatomy. The resulting NanoCT data exhibits isotropic 3D resolution, offers deeper insights into the 3D microstructure, and thereby allows for a complete morphological characterization. For comparative purposes, the specimen was sectioned subsequently to evaluate the NanoCT data versus serial sectioning light microscopy (ss-LM). To correct for mechanical instabilities and drift artefacts, we applied an alternative alignment procedure for CT reconstruction. We thereby achieve a level of detail on the subcellular scale comparable to ss-LM images in the sectioning plane.

Distillation of an End-to-End Oracle for Face Verification and Recognition Sensors.

Face recognition functions are today exploited through biometric sensors in many applications, from extended security systems to inclusion devices; deep neural network methods are reaching in this field stunning performances. The main limitation of the deep learning approach is an inconvenient relation between the accuracy of the results and the needed computing power. When a personal device is employed, in particular, many algorithms require a cloud computing approach to achieve the expected performances; other algorithms adopt models that are simple by design. A third viable option consists of model (oracle) distillation. This is the most intriguing among the compression techniques since it permits to devise of the minimal structure that will enforce the same I/O relation as the original model. In this paper, a distillation technique is applied to a complex model, enabling the introduction of fast state-of-the-art recognition capabilities on a low-end hardware face recognition sensor module. Two distilled models are presented in this contribution: the former can be directly used in place of the original oracle, while the latter incarnates better the end-to-end approach, removing the need for a separate alignment procedure. The presented biometric systems are examined on the two problems of face verification and face recognition in an open set by using well-agreed training/testing methodologies and datasets.

Optofluidic detection setup for multi-parametric analysis of microbiological samples in droplets

High-throughput microbiological experimentation using droplet microfluidics is limited due to the complexity and restricted versatility of the available detection techniques. Current detection setups are bulky, complicated, expensive, and require tedious optical alignment procedures while still mostly limited to fluorescence. In this work, we demonstrate an optofluidic detection setup for multi-parametric analyses of droplet samples by easily integrating micro-lenses and embedding optical fibers for guiding light in and out of the microfluidic chip. The optofluidic setup was validated for detection of absorbance, fluorescence, and scattered light. The developed platform was used for simultaneous detection of multiple parameters in different microbiological applications like cell density determination, growth kinetics, and antibiotic inhibition assays. Combining the high-throughput potential of droplet microfluidics with the ease, flexibility, and simplicity of optical fibers results in a powerful platform for microbiological experiments.

Twin-field quantum key distribution based on twisted photon

Quantum key distribution (QKD) is a promising application to establish unconditional secure communications by quantum mechanics. However, its widespread application still faces a great challenge, that is, the fundamental linear key-rate constraint called Pirandola-Laurenza-Ottaviani-Banchi (PLOB) bound. Recently, twin-field QKD (TF-QKD) was proposed (Lucamarini et al., 2018 [4]), it overcomes the constraint mentioned above. However, the original TF-QKD is based on the phase-encoding strategy, which requires active alignment. In this paper, we improve the original TF-QKD with the photon orbital angular momentum (OAM), and propose a novel reference frame independent protocol to overcome the reference frame dependence. No more alignment procedure is needed, and the intrinsic misalignment errors are eliminated by utilizing the rotation-invariance of OAM photons. Besides, the security performance is also improved.

Performance of the Optimized Mechanical Design of the CLIC Main-Beam Quadrupole Magnet Prototype

The Main-Beam Quadrupole (MBQ) magnets of CLIC, the Compact Linear Collider understudy at the CERN Laboratory in Geneva, are part of a critical magnet family, considering the industrial production challenges. An R&D program on the MBQ magnets was launched in 2010 for studying and investigating several assembly solutions in order to minimize the procurement cost of a large series of magnets comprising more than 4000 units. In this paper, the performance of the latest configuration is presented, comparing the results of magnetic measurements with previous magnet model variants. Innovative solutions for an efficient and fast fiducialization of the MBQ quadrupoles and alignment with respect to beam trajectory were also studied and developed inside the PACMAN Project, a CERN project supported by the European Union via the $7^{th}$ Framework Programme Marie Curie actions. The advantages of the mechanical design of the iron yoke and the assembly and alignment procedures are presented and discussed.

TEMPORAL PROCESSES ALIGNMENT METHOD FOR COMPLICATED SYSTEMS

The presented work researches a possibility to compose temporal processes to reduce complicated system operation expenditures. It is established, that temporal processes are classified into three categories in view of their influence on a system’s functional state. They are single (1), repeating (2) and cyclic (3). It is also established, that presence of large number of temporal processes within a system requires an individual approach to their control. Temporal processes alignment method is developed consisting of six fundamental provisions: 1) with none additional restrictions the attraction point falls within the time interval of either of temporal processes; 2) temporal processes’ shifting does not involve additional expenditures if it does not generate extra temporal process within the time interval under review; 3) with increased system’s stoppage costs the attraction points tend to areas of the system’s forced stoppage and increase noticeably their attracting features; 4) attraction area is determined by an area where all the not repeating temporal processes are located; 5) in the course of alignment of temporal processes involving reduction of the number of system’s stoppages there is always a limit expenditures value justifying such an alignment; 6) alignment of temporal processes running within relative attraction zone may be implemented providing meeting the conditions. These provisions construe a basis to take a decision about possibility and feasibility of their alignment. It is identified, that one of essential parameters of the processes’ alignment is a choice of a proper time for their alignment. An algorithm is offered based on the developed method enabling to implement temporal processes alignment procedure depending on data processing systems’ resources to reduce substantially chance of error in adopting a decision in complicated systems’ management.

BioSeqZip: a collapser of NGS redundant reads for the optimization of sequence analysis.

MotivationHigh-throughput next-generation sequencing can generate huge sequence files, whose analysis requires alignment algorithms that are typically very demanding in terms of memory and computational resources. This is a significant issue, especially for machines with limited hardware capabilities. As the redundancy of the sequences typically increases with coverage, collapsing such files into compact sets of non-redundant reads has the 2-fold advantage of reducing file size and speeding-up the alignment, avoiding to map the same sequence multiple times.Method BioSeqZip generates compact and sorted lists of alignment-ready non-redundant sequences, keeping track of their occurrences in the raw files as well as of their quality score information. By exploiting a memory-constrained external sorting algorithm, it can be executed on either single- or multi-sample datasets even on computers with medium computational capabilities. On request, it can even re-expand the compacted files to their original state.ResultsOur extensive experiments on RNA-Seq data show that BioSeqZip considerably brings down the computational costs of a standard sequence analysis pipeline, with particular benefits for the alignment procedures that typically have the highest requirements in terms of memory and execution time. In our tests, BioSeqZip was able to compact 2.7 billion of reads into 963 million of unique tags reducing the size of sequence files up to 70% and speeding-up the alignment by 50% at least.Availability and implementation BioSeqZip is available at https://github.com/bioinformatics-polito/BioSeqZip.Supplementary information Supplementary data are available at Bioinformatics online.

A comprehensive system for analyzing the presence of print quality defects

Print quality (PQ) is most important in the printing industry. It plays a role in users’ satisfaction with their products. Page quality will be degraded when there are print quality defects on the printed page, which could be caused by the electrophotographic printer (EP) process and associated print mechanism. To identify the print quality issue, customers have to consult a printer user manual or contact customer service to describe the problems. In this paper, we propose a comprehensive system to analyze the printed page automatically and extract the important defect features to determine the type and severity of defects on the scanned page. This system incorporates many of our previous works. The input of this system is the master digital image and the scanned image of the printed page. The comprehensive system includes three modules: the region of interest (ROI) extraction module, the scanned image pre-processing module (image alignment and color calibration procedure), and the print defect analysis module (text fading detection, color fading detection, streak detection, and banding detection). This system analyzes the scanned images based on different ROIs, and each ROI will produce a printer defect feature vector. The final output is the whole feature vector including all the ROI feature vectors of the printed page, and this feature vector will be uploaded to customer service to analyze the printer defect.

Single IMU Displacement and Orientation Estimation of Human Center of Mass: A Magnetometer-Free Approach

In this article, a self-contained procedure to estimate the vertical, medial–lateral, and anterior–posterior displacement of a single sacrum-worn inertial measurement unit (IMU) is presented, which can be related to the human body center of mass (CoM) displacement during treadmill walking through an adaptation of the sacral marker method. Furthermore, a magnetometer-free custom sensor-fusion algorithm for orientation estimation is proposed alongside a practical alignment procedure to refer relative IMU orientation estimation to a ground-fixed reference frame. Twelve healthy subjects performed two trials of treadmill walking at 3, 4, and 5 km/h for 150 s, with a sacrum-worn IMU. Orientation and displacement estimations were then compared with those obtained from an optoelectronic measurement system. Roll, pitch, and yaw angles showed root mean square error (RMSE) lower than 2° for walking trials at 3, 4, and 5 km/h, with Pearson’s correlation coefficient higher than 0.90 for each angle. Displacement accuracy was evaluated in terms of peak-to-trough distances and RMSE. Mean errors resulted lower than 1 mm for each axis of interest and for each gait speed, with RMSE not higher than 2.5 mm. The proposed off-line algorithm can be used in low-budget and infrastructure-free environments, to achieve reliable CoM displacement estimation during cyclic activities such as treadmill walking.

Introducing a novel procedure for peak alignment in one-dimensional 1H-NMR spectroscopy: a prerequisite for chemometric analyses of wine samples.

Shifted peak positions in 1H-nuclear magnetic resonance (1H-NMR) spectroscopy of wine samples are inevitably occurring mainly due to variations in the sample matrix, which consists of ethanol, glycerol, carbohydrates, acids, phenolic compounds, minerals, and aroma compounds. Slight variations in pH during sample preparation or fluctuations in instrumental factors may contribute to shifted peak positions that need to be corrected before subjecting the NMR data to chemometric techniques to ensure samples are compared on the correct chemical shift scale. In the current work, a novel procedure for correcting 1H-NMR spectroscopy peak positions was developed by mapping of the raw NMR spectra on a common chemical shift axis using a simple interpolation approach. The mapping allowed a substantial correction of peak positions and subsequently reduced the computational burden in further spectral processing. Fine-tuning of the peak alignments was carried out efficiently by interval-wisely applying the correlation optimized warping (COW) algorithm. Our preceding mapping approach enabled the use of substantially simpler alignment parameters of the COW algorithm, thereby accelerating the whole peak alignment process. The developed procedure may also be suitable for facilitating NMR analyses of other sample types, such as agricultural, clinical or pharmaceutical samples in targeted or untargeted analytical approaches.

Segmentation of Lung Images Using Textural Features

This paper proposes a technology for lung image segmentation using textural features. To analyze the informativeness of the features, the K-Means method was used. The segmentation result can be used to describe the characteristics of the patient: age, gender, physique, etc. The study was conducted on a large set of fragmented images. X-ray clustering errors for the 12×12, 24×24, and 36×36 fragmentation windows were presented. Pre-processing of images was also used to estimate the quality. The study showed that the technology provided key objects selecting error at little more than 25%. However, the alignment procedure reduced this error to 13%. When using the k-means method, a link was found between the segmentation error and the size of the fragmentation window. The selection of the range of interest on the lungs x-ray in accordance with the equalization was considered preferable. The high error of the first clustering method was associated with the choice of feature space; in our case, image processing was conducted for all features calculated using MaZda software.

Nonparallel Voice Conversion With Augmented Classifier Star Generative Adversarial Networks

We previously proposed a method that allows for nonparallel voice conversion (VC) by using a variant of generative adversarial networks (GANs) called StarGAN. The main features of our method, called StarGAN-VC, are as follows: First, it requires no parallel utterances, transcriptions, or time alignment procedures for speech generator training. Second, it can simultaneously learn mappings across multiple domains using a single generator network and thus fully exploit available training data collected from multiple domains to capture latent features that are common to all the domains. Third, it can generate converted speech signals quickly enough to allow real-time implementations and requires only several minutes of training examples to generate reasonably realistic-sounding speech. In this article, we describe three formulations of StarGAN, including a newly introduced novel StarGAN variant called “Augmented classifier StarGAN (A-StarGAN)”, and compare them in a nonparallel VC task. We also compare them with several baseline methods.

Testing Different Polymers and Boron Nitride Nanotube Properties in Fabrication of Ion-selective Membranes

One largely untapped source of clean energy is the use of osmotic gradients where freshwater and saltwater are mixed, for example at estuaries. To harness such energy, charge-selective membranes are needed to separate the anions and cations in saltwater, establishing an electric potential like a battery. The objective of this study was twofold: to investigate the creation of the polymer matrix and test the properties of boron nitride nanotubes, as both are essential in the creation of an ion-selective membrane. The proposed polymer layer has many attractive properties: controllable thickness allowing nanotubes (typically 5-10 microns long) to pass through, being rapidly curable with a UV lamp, easy mounting on other substrates, resistance to O2 and SF6 plasma gas etching, and structural strength to prevent tears. The hypotheses for this study are that the Soltech 704 (SU704) will prove to be the best polymer in terms of both etching and curing results, in addition, the relationship between the magnetic dipole moment and the length of the nanotubes is predicted to be linear. The Soltech 704 is trifunctional, compared to the other difunctional polymers tested, which is why it is predicted to have the highest strength. The dipole moment was hypothesized to be linear with nanotube length, since a longer nanotube allows for more iron oxide particles to attach to it. Out of three polymer samples tested in this study, the mixture known as Soltech 704 showed the best resistance to etching, as well as the highest UV cure rate. These two traits are desirable since they lead to a sturdier membrane and one that is created more quickly. To allow such nanotubes to be aligned, we attached magnetic iron oxide particles and then applied a magnetic field. We then recorded the magnetic dipole moments of nanotubes and compared it to the length of the nanotube. The relationship between dipole moment and length can thus be discovered. Such results can be used to optimize the alignment procedure for the nanotubes, as well as the procedure for curing the polymer.

Improvements on marker-free images alignment for electron tomography

Electron tomography is a technique to obtain three-dimensional structural information of samples. However, the technique is limited by shifts occurring during acquisition that need to be corrected before the reconstruction process. In 2009, we proposed an approach for post-acquisition alignment of tilt series images. This approach was marker-free, based on patch tracking and integrated in free software. Here, we present improvements to the method to make it more reliable, stable and accurate. In addition, we modified the image formation model underlying the alignment procedure to include different deformations occurring during acquisition. We propose a new way to correct these computed deformations to obtain reconstructions with reduced artifacts. The new approach has demonstrated to improve the quality of the final 3D reconstruction, giving access to better defined structures for different transmission electron tomography methods: resin embedded STEM-tomography and cryo-TEM tomography. The method is freely available in TomoJ software.

CDPM: Convolutional Deformable Part Models for Semantically Aligned Person Re-identification.

Part-level representations are essential for robust person re-identification. However, common errors that arise during pedestrian detection frequently result in severe misalignment problems for body parts, which degrade the quality of part representations. Accordingly, to deal with this problem, we propose a novel model named Convolutional Deformable Part Models (CDPM). CDPM works by decoupling the complex part alignment procedure into two easier steps: first, a vertical alignment step detects each body part in the vertical direction, with the help of a multi-task learning model; second, a horizontal refinement step based on attention suppresses the background information around each detected body part. Since these two steps are performed orthogonally and sequentially, the difficulty of part alignment is significantly reduced. In the testing stage, CDPM is able to accurately align flexible body parts without any need for outside information. Extensive experimental results demonstrate the effectiveness of the proposed CDPM for part alignment. Most impressively, CDPM achieves state-of-the-art performance on three large-scale datasets: Market-1501, DukeMTMC-ReID, and CUHK03.

Self-aligned micro-optic integrated photonic platform.

In this work, we present the fabrication technology of a monolithically integrated photonic platform combining key components for optical coherence tomography (OCT) imaging, thereby including a photonic interferometer, a collimating lens, and a 45° reflecting mirror that directs the light from the interferometer to the collimator. The proposed integration process simplifies the fabrication of an interferometric system and inherently overcomes the complexity of costly alignment procedures while complying with the necessarily stringent optical constraints. Fabricated waveguide characterization shows total optical losses as low as 3 dB, and less than 1 dB of additional loss due to the Si 45° mirror facet. The alignment standard deviation of all components is within 15 nm. The integrated lens profile achieves a divergence angle smaller than 0.7°, which is close to that of a collimator. The proposed photonic platform provides the premise for low-cost and small-footprint single-chip OCT systems.

High‐precision alignment procedures for patterning processes in solar cell production

AbstractWe present two approaches for high‐accuracy aligning of patterning processes with each other when fabricating solar cells. We introduce the approaches on the example of two different patterning processes of which one is adjustable (laser process) and one is not adjustable (screen‐printing process). The basic idea is to measure the coordinates of the applied structures of each involved patterning process at discrete grid points with respect to a reference coordinate system. We chose the grid points such that they completely define the final cell pattern. Then, we adjust the grid point coordinates of one of the patterning processes (the laser process) according to the pattern of the other process (the screen‐printing process). The laser then performs the patterning by connecting the corrected grid points with each other in the desired direction. We perform the associated high‐precision measurement of the patterns' coordinates by using either a high‐precision offline coordinate measuring machine or a high‐resolution inline camera system with subsequent computer‐based data processing. The latter inline method enables high throughput and is, in turn, of great interest for mass production of solar cells. In this paper, we demonstrate the alignment procedure approaches on “pPassDop” solar cells by adjusting a locally applied laser process to the directly following screen‐printing step. This proof of principle includes both above‐mentioned methods for coordinate determination in separate cell batches. Our innovative alignment procedures so far demonstrated the successful matching of 40‐μm‐wide screen‐printed contact fingers to 70‐μm‐wide laser‐processed lines over the entire area of 6‐inch solar cells.

Replication of a Printed Volatile Mold: a novel microfabrication method for advanced microfluidic systems

A novel and simple method to fabricate microchannels is reported based on an inkjet printing of a volatile solid mold. A liquid ink -1,6 hexanediol- ejected from a piezoelectric nozzle is instantaneously frozen when touching a cooled substrate. The created mold is then poured with PDMS. Once the PDMS is crosslinked, the ink is sublimated and the device is ready. With this approach it is possible to make microchannels on different nature surfaces such as glass, paper, uncross-linked PDMS layer or non planar substrates. The versatility of this method is illustrated by printing channels directly on commercial electrodes and measuring the channel capacitance. Moreover, millimetric height microfluidic systems are easily produced (aspect ratio ge 25) as well as 3D structures such as bridges. To demonstrate, we have fabricated a combinatorial microfluidic system which makes 6 mixtures from 4 initial solutions without any stacking and tedious alignment procedure.

Structured light with digital micromirror devices: a guide to best practice

Digital micromirror devices (DMDs) have become ubiquitous as spatial light modulators in the optics community, but ambiguity remains on how best to implement them in a laboratory environment. Here, we explicitly tackle the problem of generating high fidelity modes of structured light while maintaining optical efficiency. We present a theoretical characterization of the diffractive properties of the DMD, allowing us to motivate an alignment procedure that improves optical efficiency. We also present a set of best practice recommendations that cover aspects of DMD operation that are not immediately intuitive, these best practice recommendations ensure structured light is generated with the correct spatial profile and wavefront. We present experimental results that show efficiency improvements of up to 20%. Further, we demonstrate the creation of modes of structured light with fidelities in excess of 96%. The best practices presented here provide a pragmatic set of procedures for ensuring DMDs are used to their fullest potential.