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Sample preparation refers to the task of generating fluids with a specified target concentration. Generally, this is achieved by performing a set of mixing operations between biochemical fluids with a given volumetric ratio. Sample preparation plays a crucial role in several medical applications. Microfluidic devices or labs-on-chips (LoCs) got established as a suitable solution to realize this task in a miniaturized, integrated, and automatic fashion. Over the years, a variety of different microfluidic platforms emerged, which all have their respective pros and cons. Accordingly, numerous approaches aiming at the sample preparation problem have been proposed—each specialized on a single platform only. More precisely, sample preparation methods introduced thus far provide solutions for a particular platform only, i.e., they are platform specific. In this work, we propose a generic approach that generalizes the constraints of the different microfluidic platforms and, by this, provides a platform-independent sample preparation method. This allows designers to quickly check what existing platform is most suitable for the considered task and to easily support upcoming and future microfluidic platforms as well. We evaluated the performance of the proposed method with a wide range of test cases and concluded (from the evaluations) that the proposed generic approach is capable of efficiently generating results for various platforms with a quality that is close to results from dedicated approaches presented thus far. [ABSTRACT FROM AUTHOR]

Droplet-based microfluidic networks allow to process biological or medical samples by standard unit operations, such as mixing, incubating, sorting, or sensing. However, many of these networks usually perform such operations in a predefined way and, thus, lack in their flexibility. To overcome this problem, ring networks are used, since they allow to execute multiple operations in a row. But while several concepts and also prototypical implementations exist that realize such ring networks, the design process for them is still mainly conducted manually thus far. This is a severe drawback since various aspects, such as the dimensions of the channels, the effects of droplets, the used fluids, the volumetric flow rates inside the channels, etc., have to be considered for this purpose. In this article, we propose design automation methods which address this problem. The proposed solution will automatically generate a proper design as well as correspondingly needed droplet sequences. A case study demonstrates the applicability of the resulting methods and simulations confirms the validity of the proposed approach. [ABSTRACT FROM AUTHOR]

Microfluidic networks can be applied to droplet-based Lab-on-a-Chip devices, where droplets are used to confine samples which flow through closed microchannels along different paths in order to execute (bio-)chemical experiments. In order to allow this routing of droplets, the design of the microfluidic network has to be precisely defined and afterward fabricated. However, neither the fabrication process nor the applied materials and components are perfect and, therefore, the fabricated microfluidic device frequently contains defects (produced by fabrication tolerances, properties of the used material, or fluctuation of supply pumps). Those may have a severe impact on the behavior of the microfluidic network and can even render the network useless. Furthermore, these defects complicate the design process, which eventually results in a “trial-and-error”-approach causing high costs with respect to time and money. Consequently, designers want to anticipate how robust their design is against those defects. This article, for the first time, describes how these defects can be abstracted, which eventually allows to evaluate the robustness already in the design process. We additionally introduce models considering single and multiple defects as well as corresponding methods for their analysis. Evaluations on a microfluidic network which is used to screen drug compounds confirm that the resulting robustness analysis indeed provides designers with a simple metric to decide how sensitive their design is against defects. The models and methods proposed in this article are grounded on the established 1-D analysis model. [ABSTRACT FROM AUTHOR]

Stochastic computing (SC) is a promising candidate for fault-tolerant computing in digital circuits. We present a novel stochastic computing estimation architecture allowing to solve a large group of estimation problems including least squares estimation as well as sparse estimation. This allows utilizing the high fault tolerance of stochastic computing for implementing estimation algorithms. The presented architecture is based on the recently proposed linearized-Bregman-based sparse Kaczmarz algorithm. To realize this architecture, we develop a shrink function in stochastic computing and analytically describe its error probability. We compare the stochastic computing architecture to a fixed-point binary implementation and present bit-true simulation results as well as synthesis results demonstrating the feasibility of the proposed architecture for practical implementation. [ABSTRACT FROM AUTHOR]

In this brief, we present a novel inner product (IP) design for stochastic computing (SC). SC is an emerging computing technique, that encodes a number in the probability of observing a one in a random bit stream. This leads to reduced hardware costs and high error tolerance. The proposed IP design is based on a two-line bipolar encoding format and applies sequential processing of the input in a central accumulation unit. Sequential processing significantly increases the computation accuracy, since it allows for preliminary cancelation of carry bits. Moreover, the central accumulation unit gives a much better scalability compared to conventional adder tree approaches. We show that the proposed IP design outperforms a state-of-the-art design in terms of hardware costs for high accuracy requirements and fault tolerance. [ABSTRACT FROM AUTHOR]

In stochastic computing (SC), a real-valued number is represented by a stochastic bit stream, encoding its value in the probability of obtaining a one. This leads to a significantly lower hardware effort for various functions and provides a higher tolerance to errors (e.g., bit flips) compared to binary radix representation. The implementation of a stochastic max/min function is important for many areas where SC has been successfully applied, such as image processing or machine learning (e.g., max pooling in neural networks). In this work, we propose a novel shift-register-based architecture for a stochastic max/min function. We show that the proposed circuit has significantly higher accuracy than state-of-the-art architectures for uncorrelated bit streams at comparable hardware costs. Moreover, we analytically proof the correctness of the proposed circuit and provide a new error analysis, based on the individual bits of the stochastic streams. Interestingly, the analysis reveals that for a certain practical bit stream length a finite optimal shift register length exists and it allows to determine the optimal length. [ABSTRACT FROM AUTHOR]

Droplet-based microfluidic devices are a well-established and highly potential Labs-on-Chip technology as droplets are especially suited to encapsulate biological samples like cells, proteins, or DNA. These droplets are injected in a continuous phase and flow through closed microchannels to modules executing operations on the droplets—eventually realizing a (bio-)chemical experiment. Moreover, this technology even allows for the realization of multiple experiments on a single device by letting droplets take different paths through the microfluidic network. This requires, however, a mechanism to route the droplets along these paths. To this end, the concept of passive droplet routing has been suggested which entirely avoids complex valves or switches and, instead, realizes the routing by exploiting the hydrodynamic effect that a droplet will always flow along the path with the highest volumetric flow rate. Since droplets themselves affect the volumetric flow rate, a dedicated sequence of droplets can define what path is taken and, hence, what experiment is executed. However, determining such a droplet sequence is a nontrivial task, as it is nonobvious how much droplets are needed, when to inject them, and how they are interacting. In this paper, we are addressing this issue by providing, for the first time, an automatic method for the generation of droplet sequences realizing the desired experiments on a given network. Evaluations confirm the practicability of the proposed solution. Moreover, the suitability of the obtained droplet sequences is additionally validated through simulations on the 1D analysis model. [ABSTRACT FROM AUTHOR]

Two-phase flow microfluidics is a sophisticated and frequently applied Labs-on-Chip (LoC) technology as they allow to automatically conduct medical/biochemical experiments. In this technology, small volumes of reagents, so-called droplets, flow in an immiscible continuous flow inside closed channels making it particularly biocompatible. In the recent past, this technology was extended by a concept allowing to passively navigate droplets through the system—leading to so-called Networked Labs-on-Chips (NLoCs). After the design of an NLoC architecture which defines the comprising connectivity between components and, by this, how the considered medical/biochemical experiments are supposed to be realized, the question remains how to properly dimension the used components, i.e. especially how to dimension the used channels. However, this is a challenging task which is conducted manually thus far and frequently leads to specifications that do not work as intended. In this paper, we are addressing this issue by providing the designer with methods that allow to 1) automatically validate whether a chosen specification of an NLoC indeed works as intended and 2) automatically dimension NLoCs. Case studies demonstrate the importance and usefulness of the proposed methods for determining proper specifications of NLoCs. [ABSTRACT FROM AUTHOR]

Motivated by the numerous healthcare applications of molecular communication inside blood vessels of the human body, this paper considers multiple relay/cooperative nanomachine (CN)-assisted molecular communication between a source nanomachine (SN) and a destination nanomachine (DN) where each nanomachine is mobile in a diffusion-advection flow channel. Using the first hitting time model, the impact of the intermediate CNs on the performance of the aforementioned system with fully absorbing receivers is comprehensively analyzed taking into account the presence of various degrading factors, such as inter-symbol interference, multi-source interference, and counting errors. For this purpose, the optimal decision rules are derived for symbol detection at each of the CNs and the DN. Furthermore, closed-form expressions are derived for the probabilities of detection and false alarm at each CN and DN, along with the overall end-to-end probability of error and channel achievable rate for communication between the SN and DN. Simulation results are presented to corroborate the theoretical results derived and also to yield insights into the system performance under various mobility conditions. [ABSTRACT FROM AUTHOR]

Abstract Two-phase flow microfluidics is a promising platform for realizing Lab-on-a-Chip (LoC) devices, that perform different laboratory functions on a single chip. This is accomplished by processing droplets, containing biological/chemical samples, by different elements each performing specific operations. Usually, the sequence of elements in which droplets are processed is fixed, which limits the flexibility, effectiveness and reusability of such LoC devices. Recently, microfluidic networks for two-phase flow microfluidics have been introduced with the aim of realizing programmable and flexible LoC devices. In particular, the goal is to dynamically and passively assign the droplets' path through a microfluidic network, which enables to reuse the LoC devices for different laboratory functions. This paper presents the state-of-the-art and discusses various aspects of the practical realization. First, we provide a survey on microfluidic networking, including passive switching, network topologies and validation methods. Second, we propose a simple Droplet-on-Demand (DoD) system, which allows generating droplets at prescribed times and with prescribed volumes – a crucial accomplishment in order to exploit the potential of microfluidic networks for practical purposes. We verify its functionality through experimental results. Third, we describe two promising applications for microfluidic networks, namely fast and flexible drug screening and screening of waterborne pathogens. Finally, we discuss future research opportunities and challenges. [ABSTRACT FROM AUTHOR]

In this paper, we consider diffusion-based molecular communication with and without drift between two static nano-machines. We employ type-based information encoding, releasing a single molecule per information bit. At the receiver, we consider an asynchronous detection algorithm which exploits the arrival order of the molecules. In such systems, transposition errors fundamentally undermine reliability and capacity. Thus, in this paper, we study the impact of transpositions on the system performance. Toward this, we present an analytical expression for the exact bit error probability (BEP) caused by transpositions and derive computationally tractable approximations of the BEP for diffusion-based channels with and without drift. Based on these results, we analyze the BEP when background is not negligible and derive the optimal bit interval that minimizes the BEP. Simulation results confirm the theoretical results and show the error and goodput performance for different parameters such as block size or noise generation rate. [ABSTRACT FROM AUTHOR]

Labs-on-Chips (LoCs) implement laboratory procedures on a single chip and are successfully used for chemical and biomedical applications. A promising and emerging realization of such chips are Networked LoCs (NLoCs) in which small volumes of fluids, so-called droplets, flow in closed channels of submillimeter diameters. NLoCs allow for an incubation and storage of assays over a long period of time and, hence, avoid evaporation and unwanted reactions. To increase the flexibility, effectiveness, and reusability, network functionalities allow to passively route droplets in channels and, hence, to dynamically select operations depending on the executed experiment. However, only manually designed architectures are considered for NLoCs thus far. They frequently suffer from large execution times and/or a high contamination of channels. To overcome these drawbacks, we propose the consideration of application-specific architectures for NLoCs. To this end, an automatic design method is proposed which, for a given set of experiments as well as constraints and objectives from the designer, is able to generate an optimized NLoC architecture realizing these experiments. Evaluations and case studies demonstrate the potential of the proposed solution for design exploration. Moreover, we are able to show that application-specific architectures are capable of realizing experiments in just a fraction of the time needed by architectures used thus far as well as with a substantially reduced contamination. [ABSTRACT FROM PUBLISHER]

In this letter, we investigate the extrinsic log-likelihood ratio (LLR) computation of a soft-input soft-output equalizer used in a turbo equalization system. The optimum LLRs are obtained by a maximum a posteriori -based equalizer, which may be computationally expensive. Thus, several reduced-complexity equalizers have been proposed. The most promising approach first applies linear minimum mean square error filtering to the channel output and then computes the LLRs based on a scalar Gaussian approximation of the filter output. The resulting LLRs can be viewed as an approximation of the optimum LLRs. In order to improve the approximation, we investigate the computation of the LLRs based on a vector Gaussian approximation of the filter output, which incorporates the correlation between the estimated symbols after filtering. Surprisingly, it turns out that both approaches, although their derivation is different, give the same LLRs. We verify this remarkable result through an analytical proof and bit error ratio simulations. [ABSTRACT FROM PUBLISHER]

In multi-cellular organisms, molecular signaling spans multiple distance scales and is essential to tissue structure and functionality. Molecular communications is increasingly researched and developed as a key subsystem in the Internet-of-Nano-Things paradigm. While short range microscopic diffusion communications is well understood, longer range channels can be inefficient and unreliable. Static and mobile relays have been proposed in both conventional wireless systems and molecular communication contexts. In this paper, our main contribution is to analyze the information delivery energy efficiency of bacteria mobile relays. We discover that these mobile relays offer superior energy efficiency compared with pure diffusion information transfer over long diffusion distances. This paper has widespread implications ranging from understanding biological processes to designing new efficient synthetic biology communication systems. [ABSTRACT FROM PUBLISHER]

In this letter, we investigate diffusion-based molecular communication between two mobile nano-machines. We derive a closed-form expression for the first hitting time distribution by characterizing the motion of the information particles and the nano-machines via Brownian motion. We validate the derived expression through a particle-based simulation. For the information transfer we consider single particles of different types, where transposition errors are the dominant source of errors. We derive an analytical expression for the expected bit error probability and evaluate the error performance for the static and the mobile case by means of computer simulations. [ABSTRACT FROM PUBLISHER]

Timestamp free clock synchronization in a master–slave network, i.e., synchronization where no timestamps are exchanged between the nodes, is considered. For highly accurate synchronization, a novel discrete-valued clock model is introduced. It is based on the observation that clocks are discrete counters in digital wireless radios. Considering this model, it is shown that the round-trip time (RTT) measurements follow specific pulse or step shaped functions. The estimated parameters of these RTT functions are used to determine the clock parameters (clock skew and phase) and the propagation delay. Numerical analysis illustrate that when RTT measurements are collected using discrete-valued clocks, the proposed estimation schemes outperform estimators derived from the continuous clock model, which is used in the state-of-the-art methods. Moreover, the presented scheme performs similar to recently presented discrete-valued clock approaches with more stringent hardware assumption. The correctness of the proposed models is validated through hardware experiments. [ABSTRACT FROM PUBLISHER]

In this letter we consider a MIMO communication system with iterative detection over a frequency-selective MIMO channel. We present a soft-input soft-output MIMO detector based on a cyclic factor graph representation and the sum-product algorithm with two different message schedules (serial and parallel). Computer simulations show that both schedules provide near-optimum performance in terms of bit error rate, while achieving a remarkable reduction in complexity compared to the optimal MAP detector. [ABSTRACT FROM PUBLISHER]

A challenge for real-time monitoring of biochemical processes, such as cells, is detection of biologically relevant molecules. This is due to the fact that spectroscopy methods for detection may perturb the cellular environment. One approach to overcome this problem is coupled microfluidic-spectroscopy, where a microfluidic output channel is introduced in order to observe biologically relevant molecules. This approach allows for non-passive spectroscopy methods, such as mass spectrometry, to identify the structure of molecules released by the cell. Due to the non-negligible length of the microfluidic channel, when a sequence of stimuli are applied to a cell it is not straightforward to determine which spectroscopy samples correspond to a given stimulus. In this paper, we propose a solution to this problem by taking a molecular communication (MC) perspective on the coupled microfluidic-spectroscopy system. In particular, assignment of samples to a stimulus is viewed as a synchronization problem. We develop two new algorithms for synchronization in this context and carry out a detailed theoretical and numerical study of their performance. Our results show improvements over maximum-likelihood synchronization algorithms in terms of detection performance when there are uncertainties in the composition of the microfluidic channel.

The functional performance of passively operated droplet microfluidics is sensitive with respect to the dimensions of the channel network, the fabrication precision as well as the applied pressure because the entire network is coupled together. Especially, the local and global hydrodynamic resistance changes caused by droplets make the task to develop a robust microfluidic design challenging as plenty of interdependencies which all affect the intended behavior have to be considered by the designer. After the design, its functionality is usually validated by fabricating a prototype and testing it with physical experiments. In case that the functionality is not implemented as desired, the designer has to go back, revise the design, and repeat the fabrication as well as experiments. This current design process based on multiple iterations of refining and testing the design produces high costs (financially as well as in terms of time). In this work, we show how a significant amount of those costs can be avoided when applying simulation before fabrication. To this end, we demonstrate how simulations on the 1D circuit analysis model can help in the design process by means of a case study. Therefore, we compare the design process with and without using simulation. As a case study, we use a microfluidic network which is capable of trapping and merging droplets with different content on demand. The case study demonstrates how simulation can help to validate the derived design by considering all local and global hydrodynamic resistance changes. Moreover, the simulations even allow further exploration of different designs which have not been considered before due to the high costs., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)