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Cyber-physical systems (CPS) have gained an increasing attention recently for their immense potential towards the next generation smart systems that integrate cyber technology into the physical processes. However, CPS did not initiate either smart factories or smart manufacturing, and vice versa. Historically, the smart factory was initially studied with the introduction of the Internet of Things (IoT) in manufacturing, and later became a key part of Industry 4.0. Also emerging are other related models such as cloud manufacturing, social manufacturing and proactive manufacturing with the introduction of cloud computing (broadly, the Internet of Services, IoS), social networking (broadly, the Internet of People, IoP) and big data (broadly, the Internet of Content and Knowledge, IoCK), respectively. At present, there is a lack of a systemic and comprehensive study on the linkages and relations between these terms. Therefore, this study first presents a comprehensive survey and analysis of the CPS treated as a combination of the IoT and the IoS. Then, the paper addresses CPS-based smart manufacturing as an eight tuple of CPS,IoT, IoS and IoCK as elements. Further, the paper extends the eight-tuple CPS-based manufacturing to social-CPS (SCPS)-based manufacturing, termed wisdom manufacturing, which forms a nine tuple with the addition of one more element, the IoP and which is based on the SCPS instead of CPS. Both architectures and characteristics for smart and wisdom manufacturing are addressed. As such, these terms’ linkages are established and relations are clarified with a special discussion. This study thus contributes as a theoretical basis and as a comprehensive framework for emerging manufacturing integration.

A measurement intensive was carried out in Barrow, Alaska, in spring 2009 as part of the Ocean‐Atmosphere‐Sea‐Ice–Snowpack (OASIS) program. The central focus of this campaign was the role of halogen chemistry in the Arctic. A chemical ionization mass spectrometer (CIMS) performed in situ bromine oxide (BrO) measurements. In addition, a long path‐differential optical absorption spectrometer (LP‐DOAS) measured the average concentration of BrO along light paths of either 7.2 or 2.1 km. A comparison of the 1 min observations from both instruments is presented in this work. The two measurements were highly correlated and agreed within their uncertainties (R2 = 0.74, slope = 1.10, and intercept = −0.15 pptv). Better correlation was found (R2 = 0.85, slope = 1.04, and intercept = −0.11 pptv) for BrO observations at moderate wind speeds (>3 m s−1 and <8 m s−1) and low nitric oxide (NO) mixing ratios (<100 pptv). The improved agreement is likely due to the elimination of periods when the spatial distribution of BrO is inhomogeneous. The detection limit obtained for the CIMS was 2.6 pptv (3σ) for a 4 s integration period, and the estimated uncertainty was ∼30%. The detection limits for the LP‐DOAS ranged from 0.7 to 5 pptv (3σ) depending on the level of ambient light and the chosen light path, and the estimated systematic error was 10%. The agreement between the CIMS and LP‐DOAS is excellent and demonstrates the capability of both instruments to selectively and accurately measure BrO with high sensitivity.

Optically active citramalic acid (CMA) is naturally present as an acidic taste component in fruits, such as apples. The absolute configuration of CMA in such fruits was investigated by high-performance liquid chromatography–tandem mass spectrometry (LC–MS/MS) following pre-column derivatization with a chiral reagent, benzyl 5-(2-aminoethyl)-3-methyl-4-oxoimidazolidine-1-carboxylate. The developed LC–MS/MS method successfully separated the enantiomers of CMA using an octadecylsilica column with a resolution and separation factor of 2.19 and 1.09, respectively. Consequently, the R-form of CMA was detected in the peel and fruit of three kinds of apple at concentrations in the 1.24–37.8 and 0.138–1.033 mg/wet 100 g ranges, respectively. In addition, R- CMA was present in commercial apple juice, whereas no quantity was detected in commercial blueberry, perilla, or Japanese apricot juice.

Smart healthcare systems integrated with advanced deep neural networks enable real‐time health monitoring, early disease detection, and personalized treatment. In this work, a novel 3D AND‐type flash memory array with a rounded double channel for computing‐in‐memory (CIM) architecture to overcome the limitations of conventional smart healthcare systems: the necessity of high area and energy efficiency while maintaining high classification accuracy is proposed. The fabricated array, characterized by low‐power operations and high scalability with double independent channels per floor, exhibits enhanced cell density and energy efficiency while effectively emulating the features of biological synapses. The CIM architecture leveraging the fabricated array achieves high classification accuracy (93.5%) for electrocardiogram signals, ensuring timely detection of potentially life‐threatening arrhythmias. Incorporated with a simplified spike‐timing‐dependent plasticity learning rule, the CIM architecture is suitable for robust, area‐ and energy‐efficient in‐memory arrhythmia detection systems. This work effectively addresses the challenges of conventional smart healthcare systems, paving the way for a more refined healthcare paradigm. This study introduces a novel 3D AND‐type flash memory for computing‐in‐memory architecture, enhancing the efficiency of smart healthcare systems. The fabricated high‐density and low‐power array effectively emulates biological synapses. The proposed architecture is suitable for robust, area‐ and energy‐efficient in‐memory arrhythmia detection systems, enabling timely detection of potentially life‐threatening arrhythmias. This research paves the way for more sophisticated healthcare solutions.

Secondary organic aerosol (SOA) represents a significant fraction of the tropospheric aerosol and its precursors are volatile organic compounds (VOCs). Anthropogenic VOCs (AVOC) dominate the VOC budget in many urban areas with 1,3,5-trimethylbenzene (TMB) being among the most reactive aromatic AVOCs. TMB formed highly oxygenated organic molecules (HOMs) in an NOx-free environment, which could contribute to new particle formation (NPF) depending on oxidation conditions where elevated OH oxidation enhanced particle formation. The experiments were performed in an oxidation flow reactor, the Go:PAM unit, under controlled OH oxidation conditions. By addition of NOx to the system we investigated the effect of NOx on particle formation and on the product distribution. We show that the formation of HOMs, and especially HOM accretion products, strongly varies with NOx conditions. We observe a suppression of HOM and particle formation with increasing NOx/ΔTMB ratio and an increase in the formation of organonitrates (ONs) mostly at the expense of HOM accretion products. We propose reaction mechanisms and pathways that explain the formation and observed product distributions with respect to oxidation conditions. We hypothesise that, based on our findings from TMB oxidation studies, aromatic AVOCs may not contribute significantly to NPF under typical NOx/AVOC conditions found in urban atmospheres.

We present the first measurements of nitryl chloride (ClNO2) over continental Europe. Significant quantities of ClNO2, up to 800 pptv, were measured at a mountaintop field site in Hessen, southwest Germany. ClNO2 was detected during the majority of nights between the 15th August and 16th September 2011, its largest mixing ratios being associated with air masses influenced by sea salt and anthropogenic NOx emissions. ClNO2 persisted in measurable quantities until early afternoons on days with low photolysis frequencies. As a consequence, early morning production rates of Cl atoms could significantly exceed the production of OH via ozone photolysis, likely leading to increased O3 production. Key Points Nitryl chloride exists in significant mixing fractions over Europe Nitryl chloride is likely of marine origin, deriving from aged sea salt and N2O5 Nitryl chloride is a significant radical source in early morning

Computing data-intensive applications on the von Neumann architecture lead to significant performance and energy overheads. The concept of computation in memory (CiM) addresses the bottleneck of von Neumann machines by reducing the data movement in the computing system. Emerging resistive non-volatile memory technologies, as well as volatile memories (SRAM and DRAM), can be used to realize architectures based on the CiM paradigm. In this paper, we propose a hybrid cell design to provide the opportunity for CiM by combining the magnetic tunnel junction (MTJ) and the conventional 6T-SRAM cell. The cell performs CiM operations based on stateful in-array computation, which has better scalability for multiple operands compared with stateless computation in the periphery. Various logic operations such as XOR, OR, and IMP can be performed with the proposed design. In addition, the proposed cell can also operate as a conventional memory cell to read and write volatile as well as non-volatile data. The obtained simulation results show that the proposed CiM-A design can increase the performance of regular memory architectures by reducing the delay by 8 times and the energy by 13 times for database query applications consisting of consecutive bitwise operations with minimum overhead.

Preparing a city for the impact of global warming is becoming of major importance. Adopting climate-proof policies and strategies in response to climate change has become a fundamental element for city planning. To this end, this research considers a multidisciplinary approach, at the local scale, able to connect urban planning and architecture, as a vital base for considering a coastal cities’ ability to control the consequences of climate change, specifically floods. So far, there is a scarcity of research connecting sea ground and land surveys, and this study could become a foundational reference for coastline settlement management using BIM. We found in BIM (Building Information Modeling) a possible tool for managing coastal risk, since it can combine crowdsourced data for geometric and information modeling of the city. The proposed BIM model includes a topography used for 3D thematic maps, a riverbed model, and a waterway model. This model aims to facilitate coordination across separate actors and interests since the urban area model is always updatable and improvable. Focusing on a case study of Lisbon, we developed risk-based 3D maps of the area close to the shoreline of the Tagus River.

‘Smart cities’ are a new type of city where stakeholders are jointly responsible for urban management. City Information Management (CIM) is an output tool for smart city planning and management, which assists in achieving the sustainable development of urban infrastructure, and promotes smart cities to achieve the goals of stable global economic development, sustainable environmental development, and improvement of people’s quality of life. Existing research has so far established that blockchain and BIM have great potential to enhance construction project performance. However, there is little research on how blockchain and BIM can support sustainable building design and construction. Therefore, the aim of this paper is to explore the potential impact of the integration of blockchain and BIM in a smart city environment on making buildings more sustainable within the context of CIM/Smart Cities. The paper explores the relationships between blockchain, BIM and sustainable building across the life cycle stage of a construction project. This paper queries the Web of Science (WoS) database with keywords to obtain relevant publication, and then uses the VOSviewer to visually analyze the relationships between blockchain, BIM, and sustainable building within the context of smart cities and CIM, which is conducted in bibliometric analysis followed by micro scheme analysis. The results demonstrate the value of this method in gauging the importance of these three topics, highlighting their interrelationships and identifying trends, giving researchers an objective research direction. Those aspects reported in the paper constitute an original contribution.

Immobilized enzyme reactors (IMERs) are critical tools for developing novel oligosaccharides based on the enzymatic catalysis of polysaccharides. In this paper, a novel glucuronan lyase from Peteryoungia rosettiformans was produced, purified, and then immobilized on a CIM® CDI disk for cleaving glucuronan. The results showed that around 63.6% of glycuronan lyases (800.9 μg) were immobilized on the disk. The Vmax values of immobilized glucuronan lyases did not significantly change (56.9 ± 4.7 μM∙min−1), while the Km values (0.310 ± 0.075 g∙L−1) increased by 2.5 times. It is worth noting that immobilized glucuronan lyases overcame the catalytic inhibition of free enzymes observed under high glucuronan concentrations (0.5–2 g∙L−1). circumscribed central composite design (CCCD) and response surface methodology (RSM) showed that glucuronan concentration, flow rate, and reaction time significantly affected the yield of oligoglucuronans. The degree of polymerization (DP) of degraded glucuronan ranged from DP 2–8 according to the results obtained by high performance anion exchange chromatography coupled with a pulsed amperometric detector (HPAEC-PAD). The IMER retained 50.9% activity after running 2373 column volumes of glucuronan. Finally, this glucuronan lyase reactor was tentatively connected to an immobilized laccase reactor to depolymerize, and gallic acid (GA) was added to glucuronan. Approximately 8.5 mg of GA was added onto 1 g of initial glucuronan, and the GA–oligoglucuronan conjugates showed notable antioxidant activity.