Chemiluminescent optical fiber immunosensor detection of Brucella cells presenting smooth-A antigen

Brucellosis is a worldwide distributed zoonotic re-emerging disease, causing abortions in domesticated animals and Malta fever in humans. Currently, the gold standard for confirmation of the existence of the causative agent genus Brucella is the isolation of the bacteria from body or liquid samples, whereas standard serological tests are used for diagnosis. The need for a rapid point of care identification of Brucella organisms has led us to develop a novel chemiluminescent optical fiber immunosensor. The immunosensor based on a conventional enzyme linked immunoassay (ELISA) technique was implemented on optical fibers and its performance was compared to the standard ELISA method. We show that depending on the detecting antibodies used specificity of the assay is achieved. Brucella cells presenting smooth-A O-chain determinant were detected at a minimal protein concentration of 1.098 ng/ml, correlating to 305 cfu/ml, while smooth-M O-chain cells, rough cells and two gram-negative bacteria other than Brucella sp. produced negative results, confirming the high specificity of the technique.     

The overall framework design of automatic logistics system using a hybrid ANN-PSO model

Automated logistic systems are commonly applied in the enterprise logistic processes while allowing to improve the reliability and efficiency of logistics procedures with computer simulation. The logistics system focuses on realizing the space and time efficiency of material and understanding the links of logistics to achieve the optimum economic effect. Therefore, in this study, 150 data were collected from 20 hospitals in Malaysia to adopt the automated logistic system under simulation of the computer to decrease the costs of hospitals and increase the serviceability (output). Since obtaining this information for the automated logistic systems is not easy and has a high cost in a traditional way, this study was performed by the integration of artificial neural network (ANN) and particle swarm optimization (PSO) as the ANN-PSO. The input data that were obtained from the processing of automated logistic system in hospitals verified by using a hybrid of ANN-PSO. Later, the results were measured with five regression indicators of determination coefficient (R²), root mean square (RMSE), Pearson correlation coefficient (r), Nash–Sutcliffe model efficiency coefficient (NSE) and Willmott’s index (WI). Considering the results of RMSE, RSQR and r in both testing and training phases, the good performance of ANN-PSO in determining the effectiveness of applying automated logistic system using computer simulation method in hospital management, in terms of raising its serviceability and reducing the costs was proved. As a result, it was shown that ANN-PSO can successfully determine the effectiveness of using an automated logistic system under computer simulation method in hospital management.

     

Automated immunomagnetic processing and separation of Legionella pneumophila with manual detection by sandwich ELISA and PCR amplification of the ompS gene

The culture-independent and automated detection of bacteria in the environment is a scientific and technological challenge. For detection alone, a number of sensitive methods are known (e.g., PCR, enzyme-linked immunosorbent assay [ELISA], fluorescent in situ hybridization) but a major problem remaining is the enrichment and separation of the bacteria that usually occur at low concentrations. Here, we present an automated capturing and separation system, which can easily be combined with one of the sensitive detection techniques. We have developed a method for enrichment and detection of Legionella pneumophila in liquid media. Concentrated microorganisms were either detected by PCR or by sandwich ELISA. The limit of detection with the immunological assay was about 750 bacteria. Using PCR, the equivalent of about 2000 genomes could be detected. The assays were then transferred to a laboratory prototype for automated processing. It was possible to automatically enrich L. pneumophila by immunomagnetic separation (IMS), and again, the bacteria were detected by sandwich ELISA and PCR amplification of the ompS gene. As a novel aspect, ompS gene was used for the first time as a target for the detection of L. pneumophila on magnetic beads. The aim of this work was to develop an automated procedure and a device for IMS of bacteria. With Legionella as a model organism, we could show that such a novel fully automated system can be an alternative to time-consuming conventional cultivation methods for detecting bacteria or other microorganisms.     

Fully Automated Anti-Varicella Zoster Enzyme-Linked Immunosorbent Assays Supporting Manufacture of a Novel Intravenous Therapeutic for Treatment of Ailments Caused by the Varicella Zoster Virus

Two non-competitive, antibody-capture enzyme-linked immunosorbent assays, a commercial Kit VZIG ELISA and an in-house developed, amplified VZIG ELISA were automated by using the liquid handling and plate processing abilities of the Microlab AT plus 2 and Microlab F.A.M.E. instruments, respectively. The evaluation of the experimental data has also been automated by using the F.A.M.E.-specific data import converter and PLA software program for data capture / uploading and analysis. The automation increased the economy of analytical operations and traceability of the experimental data thus better supporting the production and clinical studies on a therapeutic Varicella Zoster Immune Globulin manufactured at Cangene.     

Heraeus cytomat® 6000 Series Incubators and Storage Systems from Kendro Laboratory Products

There are a number of cases in high throughput screening systems where a controlled environment is desired. These include incubation periods for cellbased assays, incubation for protein detection assays such as ELISA or fluorescence assays, and branching assays for mRNA detection. In addition, as the density of wells in microplates increases and well volumes become smaller, evaporation becomes a concern in all assays.The cytomat® 6000 is a robot accessible, automated CO₂ incubator used for cell-based High Throughput Screening systems. The incubator provides superior environmental conditions, due to the unique access door at the back of the instrument, the PlateShuttle. This small access opening insures that the environment inside the system (temperature, humidity and CO₂) is undisturbed as microplates are accessed.The system provides high speed, random (bar-coded) access to all microplate formats for 24, 96, 384 and 1536 well microplates (up to 261-microplate capacity). Other cytomat configurations offer refrigerated and low humidity environments.     

A microfluidic chip for heterogeneous immunoassay using electrokinetical control

This article presents the development of a novel, automated, electrokinetically controlled heterogeneous immunoassay on a poly(dimethylsiloxane) (PDMS) microfluidic chip. A numerical method has been developed to simulate the electrokinetically driven, time-dependent delivery processes of reagents and washing solutions within the complex microchannel network. Based on the parameters determined from the numerical simulations, fully automated on-chip experiments to detect Helicobacter pylori were accomplished by sequentially changing the applied electric fields. Shortened assay time and much less reagent consumptions are achieved by using this microchannel chip while the detection limit is comparable to the conventional assay. There is a good agreement between the experimental result and numerical prediction, demonstrating the effectiveness of using CFD to assist the experimental studies of microfluidic immunoassay.     

Automation and ISO 17025 test validation of a Toxoplasma Gondii antibodies enzyme-linked immunosorbent assay

The authors automated an enzyme-linked immunosorbent assay to detect porcine serum antibodies to Toxoplasma gondii. Two thousand swine sera can be assayed in two eight-hour shifts using a robotic workstation. The automated-ELISA programming is not complex and the test configuration is flexible. This high-throughput screening (HTS) a-ELISA can achieve a 10-fold increase (100→1000 tests) in test capacity over the manual method. The assay has been validated according to the requirements of the ISO/IEC 17025 standard. These include repeatability, reproducibility, and optimal threshold value studies. Other requirements are proficiency panel testing, analyst training, standard operation procedure, and equipment certifications.     

Automated assume-guarantee reasoning for omega-regular systems and specifications

We develop a learning-based automated assume-guarantee (AG) reasoning framework for verifying ω-regular properties of concurrent systems. We study the applicability of non-circular (AG-NC) and circular (AG-C) AG proof rules in the context of systems with infinite behaviors. In particular, we show that AG-NC is incomplete when assumptions are restricted to strictly infinite behaviors, while AG-C remains complete. We present a general formalization, called LAG, of the learning based automated AG paradigm. We show how existing approaches for automated AG reasoning are special instances of LAG. We develop two learning algorithms for a class of systems, called ∞-regular systems, that combine finite and infinite behaviors. We show that for ∞-regular systems, both AG-NC and AG-C are sound and complete. Finally, we show how to instantiate LAG to do automated AG reasoning for ∞-regular, and ω-regular, systems using both AG-NC and AG-C as proof rules.     

Writing human factor research papers: a guidebook

Abstract

Hand hygiene (HH) prevents harmful contaminants spreading in settings including domestic, health care and food handling. Strategies to improve HH range from behavioural techniques through to automated sinks that ensure hand surface cleaning. This study aimed to assess user experience and acceptance towards a new automated sink, compared to a normal sink. An adapted version of the technology acceptance model (TAM) assessed each mode of handwashing. A within-subjects design enabled N = 46 participants to evaluate both sinks. Perceived Ease of Use and Satisfaction of Use were significantly lower for the automated sink, compared to the conventional sink (p < 0.005). Across the remaining TAM factors, there was no significant difference. Participants suggested design features including jet strength, water temperature and device affordance may improve HH technology. We provide recommendations for future HH technology development to contribute a positive user experience, relevant to technology developers, ergonomists and those involved in HH across all sectors.

Practitioner Summary: The need to facilitate timely, effective hand hygiene to prevent illness has led to a rise in automated handwashing systems across different contexts. User acceptance is a key factor in system uptake. This paper applies the technology acceptance model as a means to explore and optimise the design of such systems.     

Motion sickness in passenger vehicles during test track operations

Abstract

As automation transforms drivers into passengers, the deployment of automated vehicles (AVs) has the potential to greatly increase the incidence of motion sickness. A study was conducted to quantify motion sickness response of front-seat passengers performing ecologically relevant passenger activities during conditions consistent with driving on public roadways. Fifty-two adults with a large range of self-reported levels of motion sickness susceptibility and age participated in data collection on a closed test track in a passenger sedan. Motion sickness ratings increased with task vs. no-task and moderate vs. low acceleration test conditions. Increased motion sickness susceptibility was associated with higher motion sickness ratings. In comparison to older participants (age?>?60), younger participants (age?<?60) experienced increased motion sickness. This is the first in-vehicle study that systematically compared normative passenger activities and acceleration magnitudes typical of normative driving conditions on motion sickness response for a large, diverse sample of passengers, enabling the exploration of the effects of covariates.

Practitioner summary: The data demonstrate that a relatively large range of motion sickness response can be expected to result from passengers performing visual tasks in passenger vehicles. Measurement and modelling efforts should seek to elucidate relationships among the factors contributing to motion sickness for the purpose of informing and prioritising future countermeasures for automated vehicles (AVs).

Abbreviations: AV(S): automated vehicles; BMI: body mass index; BVP: blood volume pulse; EDA: electrodermal activity; FMS: fast motion sickness scale; GPS: global positioning system; IMU: inertial measurement unit; ISO: International Organization for Standardization; MISC: misery scale; MSDV: motion sickness dose value; NDS: naturalistic driving study; SAE: Society of Automotive Engineers International; UMTRI: The University of Michigan Transportation Research Institute

Key Aspect of Research: Motion sickness may be an important barrier to widespread adoption of automated vehicles @UMTRI.     

An Efficient Multibody Dynamics Model for Internal Combustion Engine Systems

The equations of motion for the major components in an internalcombustion engine are developed herein using a recursive formulation.These components include the (rigid) engine block, pistons, connectingrods, (flexible) crankshaft, balance shafts, main bearings, and enginemounts. Relative coordinates are employed that automatically satisfy allconstraints and therefore lead to the minimum set of ordinarydifferential equations of motion. The derivation of the equations ofmotion is automated through the use of computer algebra as the precursorto automatically generating the computational (C or Fortran) subroutinesfor numerical integration. The entire automated procedure forms thebasis for an engine modeling template that may be used to supportthe up-front design of engines for noise and vibration targets.This procedure is demonstrated on an example engine under free(idealized) and firing conditions and the predicted engine responses arecompared with results from an ADAMS model. Results obtained by usingdifferent bearing models, including linear, nonlinear, and hydrodynamicbearing models, are discussed in detail.     

深度空时婴幼儿表情识别模型下的ASD自动筛查

目的 高危孤独症谱系障碍（high-risk autism spectrum disorder,HR-ASD）筛查依赖于医师的临床评估和问卷量表,传统筛查方式效率低,亟需一种高效的自动筛查工具。为了满足自动筛查的需求,本文提出一种基于婴幼儿表情分析的孤独症谱系障碍自动筛查方法。方法 首先入组30例8~18个月的婴幼儿,包括10例ASD疑似患儿（HR-ASD）和20例正常发育婴幼儿;引入静止脸范式,并利用该范式诱发婴幼儿在社交压力条件下的情绪调节行为;提出一种面向婴幼儿视频表情识别的深度空时特征学习网络,首先在大规模公开数据集AffectNet预训练空域特征学习模型,然后在自建婴幼儿面部表情视频数据集RCLS&NBH+（Research Center of Learning Science&Nanjing Brain Hospital dataset+）上训练时空特征学习模型,从而建立一个较精准的婴幼儿表情识别模型;基于该模型深度特征序列的一阶统计量,构建婴幼儿社交压力环境下的表情行为症状与精神健康状态之间的关联,采用机器学习方法实现自动筛查。结果 1）基于婴幼儿表情人工标注的结果,发现：在1 min静止期,高危组的婴幼儿中性表情持续时长相对正常对照组偏高（p<0.01）,而其他表情未发现有统计学意义的差异;2）提出的深度空时特征学习网络在本研究的30例婴幼儿面部表情视频数据集上的总体平均识别率达到了87.1%,3类表情预测结果与人工标注结果具有较高的一致性,其中Kappa一致性系数达到0.63,Pearson相关系数达到0.67;3）基于面部表情深度特征序列一阶统计量的精神健康状态预测性能达到灵敏度70%,特异性90%,分类正确率83.3%（置换检验p<0.05）。结论 本文提出的基于婴幼儿面部表情深度特征序列一阶统计量的精神健康状态自动预测模型是有效的,有助于实现高危孤独症谱系障碍自动筛查。     

Automation of Serological Diagnosis for Herpes B Virus Infections Using Robot-Assisted Integrated Workstations

A robot-assisted automated facility was established within a biosafety level 3 laboratory located on a university campus. A unique integration of a Genesis (TECAN) liquid handler into the SAGIAN Core System (Beckman-Coulter) enabled tube liquid handling and transfer of reagents from tubes to microplates. An automated enzyme immunoassay (ELISA) for detecting herpes B virus antibodies was developed. Repetition experiments of the automated ELISA and comparison to the manual ELISA demonstrated the efficacy and high reproducibility of the automated method. It is anticipated that research and education activities will benefit from the establishment of the automated diagnostic laboratory in an academic environment.     

On the calculus of positively constructed formulas for automated theorem proving

The paper deals with an expressive logic language LF and its calculus. Formulas of this language consist of some large-scale structural elements, such as type quantifiers. The language LF contains only two logic symbols—∀ and ∃, which form the set of logic connectives of the language. The logic calculus JF and complete strategy for automated proof search based on a single unary rule of inference are considered. This calculus has a number of other features which lead to the reduction of the combinatorial complexity of finding the deductions in comparison to the known systems for automated theorem proving as the Resolution method and Genzen calculus. Problems of effective implementation of JF as a program system for automated theorem proving are considered.     

Planning Proofs of Equations in CCS

Most efforts to automate formal verification of communicating systems have centred around finite-state systems (FSSs). However, FSSs are incapable of modelling many practical communicating systems, including a novel class of problems, which we call VIPS. VIPSs are value-passing, infinite-state, parameterised systems. Existing approaches using model checking over FSSs are insufficient for VIPSs. This is due to their inability both to reason with and about domain-specific theories, and to cope with systems having an unbounded or arbitrary state space.We use the Calculus of Communicating Systems (CCS) (Communication and Concurrency. London: Prentice Hall, 1989) to express and specify VIPSs. We take program verification to be proving the program and its intended specification equivalent. We use the laws of CCS to conduct the verification task. This approach allows us to study communicating systems and the data such systems communicate. Automating theorem proving in this context is an extremely difficult task.We provide automated methods for CCS analysis; they are applicable to both FSSs and VIPSs. Adding these methods to the CL ^A M proof planner (Lecture Notes in Artificial Intelligence, Vol. 449, Springer, 1990, pp. 647, 648), we have implemented an automated verification planner capable of dealing with problems that previously required human interaction. This paper describes these methods, gives an account as to why they work, and provides a short summary of experimental results.     

Decentralised direct adaptive fuzzy control for a class of large-scale nonaffine nonlinear systems and application to AHS

A novel decentralised direct adaptive fuzzy controller design is presented for a class of large-scale nonaffine uncertain nonlinear systems in this article. By integrating a fuzzy logic system and H _∞ tracking technique, the designed controller is able to adaptively compensate for interconnections and disturbances with unknown bounds, but none of the control and adaptation laws contains a sign function so that control chattering can be shunned. The closed-loop large-scale system is guaranteed to be asymptotically stable and obtain good H _∞ tracking performance. The control approach developed is applied to the following control problem of a string of vehicles within an automated highway system (AHS) and simulation results verify its validity.     

Sequencing unreliable jobs on parallel machines

This paper addresses an allocation and sequencing problem motivated by an application in unsupervised automated manufacturing. There are n independent jobs to be processed by one of m machines or units during a finite unsupervised duration or shift. Each job is characterized by a certain success probability p _i , and a reward r _i which is obtained if the job is successfully carried out. When a job fails during processing, the processing unit is blocked, and the jobs subsequently scheduled on that machine are blocked until the end of the unsupervised period. The problem is to assign and sequence the jobs on the machines so that the expected total reward is maximized. This paper presents the following results for this problem and some extensions: (i) a polyhedral characterization for the single machine case, (ii) the proof that the problem is NP-hard even with 2 machines, (iii) approximation results for a round-robin heuristic, (iv) an effective upper bound. Extensive computational results show the effectiveness of the heuristic and the bound on a large sample of instances.     

Strategic Issues, Problems and Challenges in Inductive Theorem Proving

(Automated) Inductive Theorem Proving (ITP) is a challenging field in automated reasoning and theorem proving. Typically, (Automated) Theorem Proving (TP) refers to methods, techniques and tools for automatically proving general (most often first-order) theorems. Nowadays, the field of TP has reached a certain degree of maturity and powerful TP systems are widely available and used. The situation with ITP is strikingly different, in the sense that proving inductive theorems in an essentially automatic way still is a very challenging task, even for the most advanced existing ITP systems. Both in general TP and in ITP, strategies for guiding the proof search process are of fundamental importance, in automated as well as in interactive or mixed settings. In the paper we will analyze and discuss the most important strategic and proof search issues in ITP, compare ITP with TP, and argue why ITP is in a sense much more challenging. More generally, we will systematically isolate, investigate and classify the main problems and challenges in ITP w.r.t. automation, on different levels and from different points of views. Finally, based on this analysis we will present some theses about the state of the art in the field, possible criteria for what could be considered as substantial progress, and promising lines of research for the future, towards (more) automated ITP.