bluuebunny/crossref_metadata_2025 huggingface dataset:
Topology Planning in Swarm Production System: Framework and Optimization
Authors: Avhad Akshay , Schou Casper , Madsen Ole
Published: June 2023

A Swarm Production System (SPS) aims to be an agile and resilient Reconfigurable manufacturing system (RMS) paradigm that incorporates mobile workstations and transport robots on the factory production floor. This paper primarily focuses on SPS’s initial but recurring planning stage termed topology planning, which dynamically changes throughout the production runtime with spatially adaptive workstations and transporters handled exclusively by a Topology Manager (TM). TM is essential to multi-variant production with the optimal positioning of the workstations and provides a topology that optimizes the traffic flow for the product carrier robots. TM is a bridge to enable SPS to integrate with general planning and scheduling systems like ERP and MES and is comprised of a Topology Planner (TP) that evaluates the ideal configuration of on factory floor for a batch of product mix and a Reconfiguration Decision System (RDS) that decides on applying the estimated new topology during the batch changeover. The paper proposes a framework for the TM to identify its essential functionalities, responsibilities and working principle in a swarm production system. The paper also describes a grid-based heuristic approach applicable to two-dimensional spatial problems to reduce the complexity of the NP-hard problem. The paper focuses on a framework to estimate a reconfigurable shop floor layout with a Force-directed Graph-theory algorithm. A stochastic statistical model evaluates the performance of the optimal topology for throughput and makespan.
Using Meta-Learning to Reduce the Effort of Training New Workpiece Geometries for Entanglement Detection in Bin-Picking Applications
Authors: Moosmann Marius , Bleifuß Julian , Rosport Johannes , Spenrath Felix , Kraus Werner , Bormann Richard , Huber Marco F.
Published: June 2023

In this paper, we introduce a scaling method for the training of neural networks used for entanglement detection in Bin-Picking. In the Bin-Picking process of complex-shaped and chaotically stored objects, entangled workpieces are a common source of problems. It has been shown that deep neural networks, which are trained using supervised learning, can be used to detect entangled workpieces. However, this strategy requires time-consuming data generation and an additional training process when adapting to previously unseen geometries. To solve this problem, we analyze and compare several Meta-Learning techniques like Reptile, MAML and TAMS for their feasibility as a scaling method for the entanglement detection. These methods search for a strongly generalized model for entanglement detection by learning from the training process of various workpieces with different geometries. Using this generalized model for entanglement detection as initialization helps to increase the learning success with only few training epochs and reduces the required amount of data and therefore the setup effort significantly.
Unlocking the Potential of Digital Twins
Authors: Pohlkötter Fabian J. , Straubinger Dominik , Kuhn Alexander M. , Imgrund Christian , Tekouo William
Published: June 2023

Increasing competitive pressure is confronting the automotive industry with major challenges. As a result, conventional reactive maintenance is being transformed into predictive maintenance. In this context, wearing and aging effects no longer lead to plant failure since they are predicted at an earlier stage based on comprehensive data analysis.

Furthermore, the evolution towards Smart Factory has given rise to virtual commissioning in the planning phase of production plants. In this process, a Hardware-in-the-Loop (HiL) system combines the real controls (e.g., PLC) and a virtual model of the plant. These HiL systems are used to simulate commissioning activities in advance, thus saving time and money during actual commissioning. The resulting complex virtual models are not further used in the series production.

This paper builds upon virtual commissioning models to develop a Digital Twin, which provides inputs for predictive maintenance. The resulting approach is a methodology for building a hybrid predictive maintenance system. A hybrid prediction model combines the advantages of data-driven and physical models. Data-driven models analyse and predict wearing patterns based on real machine data. Physical models are used to reproduce the behaviour of a system. From the simulation of the hybrid model, additional insights for the predictions can be derived.

The conceptual methodology for a hybrid predictive maintenance system is validated by the successful implementation in a bottleneck process of the electric engine production for an automotive manufacturer. Ultimately, an outlook on further possible applications of the hybrid model is presented.
Hybrid Digital Twins Using FMUs to Increase the Validity and Domain of Virtual Commissioning Simulations
Authors: Pfeifer Denis , Baumann Andreas , Giani Marco , Scheifele Christian , Fehr Jörg
Published: June 2023

The main objective of virtual commissioning is to help design and validate the control systems of entire production plants. Therefore, simulations on a logical and kinematic level are performed, typically in a Software- or Hardware-in-the-Loop configuration using the original control software and controller [1].

However, the lack of level of detail means that this type of simulation is insufficient for an integrated system dynamics and control algorithms design. These engineering tasks are currently performed in separate tools, e.g. by finite element analysis, multibody simulations or by a combination, i.e. elastic multibody systems (EMBS) [2]. However, the designed components are only considered individually and not in the context of the control technology used. Therefore, primarily synthetic inputs are used and not the original control behavior. With a higher level of simulation detail, further questions about the system, such as the effect of control algorithms on the dynamic processes, can be virtually validated.

Therefore, this paper explores hybrid component-based digital twins to combine the advantages of both VC and EMBS. Hybrid components allow the simulation of the interactions between process, machine and control system with a high level of detail where this is beneficial. Such integration is achieved using the Functional Mock-up Interface (FMI) to couple different simulation models in a co-simulation environment [3]. This is demonstrated in a simulation use case of an inverted pendulum. The level of detail of individual components in the virtual commissioning tool ISG-virtuos [4] is increased by the modular integration of elastic multibody simulations via FMI so that the swing-up controller can be designed in the simulation.
Analysis of Real-Time Execution Models for Container-Based Control Applications
Authors: Walker Moritz , Tasci Timur , Lechler Armin , Verl Alexander
Published: June 2023

Software-defined Manufacturing (SDM) aims to enhance the flexibility of production systems. Classical automation systems are not a suitable technological basis for SDM. While their hierarchical, rigid structures are increasingly being dissolved. Container-based virtualization, and modular software architectures, gain traction in automation systems. However, today’s PLCs are not a perfect fit for virtualization, as the control program still is a monolithic piece of software. We analyze cyclic and event-based real-time scheduling models for modular PLCs. Furthermore, techniques for reconfiguration at runtime are developed based on the selected execution models.
Towards the Smart Factory: Process Optimization in Virtual Commissioning
Authors: Kuhn Alexander M. , Christ Michael , Kuhn Christopher B. , Liu Peng , Tekouo William , Kestler Hans A.
Published: June 2023

Since the early 1990s, virtual models have been used in production planning to digitally support production lines before beginning physical construction. These digital models, commonly referred to as “digital twins”, are currently primarily used for virtual commissioning. Despite being first used decades ago, digital twins are still not established in production planning on a global scale. The benefits of developing and testing a planned system in a virtual model are often not fully capitalized. While this can be partially explained by the technological challenges of designing accurate virtual models, we argue that the current processes for production planning are another important factor that hinder the widespread use of digital twins. In this paper, we summarize and analyze each step and the involved participants in a typical production planning workflow. Based on this analysis, we discuss how current practices conflict with the goal of incorporating virtual models into the established work environment. Then, we derive concrete recommendations of how a production process can be adjusted to allow easier digital twinning, showing how comparatively few changes could make virtual models significantly easier to apply.
A New IT Architecture for the Digital Factory
Authors: Lorch Christopher , Lüdemann-Ravit Bernd
Published: June 2023

In general, current systems for the Digital Factory implement a product-process-resource (PPR) data model in a monolithic rich-client/server architecture with a single database persistence layer. Common data objects are the product bills of material, descriptions of the production processes, or the resource structure, e.g. bill of equipment. The main drawback of the current monolithic architecture is the slow rate of development, which prevents fast adoption of the software to the new production planning process (i.e., due to new technologies for the transformation of the automotive industry with the goal of electrification) is not possible. Furthermore, time-consuming and error-prone export-import operations characterize the collaboration of the engineering supply chain. Mercedes-Benz has created a new IT system architecture for their Digital Factory. The core idea of this architecture is a module-based approach. Each planning step has its own module, e.g. product analysis, layout planning or cost calculation. One single module consists of a server-based business logic, a web-based user interface and its own database. Each module is the source of master data objects that originate from the corresponding planning step and refers to data objects from predecessor planning steps. The single modules communicate mostly via KAFKA. The usage of a model based application engine allows the fast creation of different modules. Best-of-breed third-party systems for specific planning steps can be integrated into the system architecture. Web technologies allow suppliers to access the Mercedes-Benz systems directly for a fully integrated supplier collaboration. Roll-out has started and has already led to significant efficiencies.
Security Analysis of a Blockchain Based Data Collection Method for Cross Company Information Sharing
Authors: Bux Tobias , Riedel Oliver , Lechler Armin
Published: June 2023

Digitization within medium-sized enterprises advanced in the last years. Collecting and analyzing data for optimizing internal production processes therefor is the current state of many companies. The next step of digitization is using this collected data not only for internal processes but for cross company business models along the value network. This step brings new requirements for how data is collected, stored and shared. In this paper those requirements are listed and explained. Afterwards, an implemented solution for data collection fulfilling the requirements is analyzed. The focus of the analysis lies on security issues within the data flow between data creation and cross-company usage. Therefore, the timespan between data creation on a sensor, processing the data within local IT-systems and reliably storing data within a blockchain is considered. A threat modeling approach considering attack vectors along the described data flow is used to quantitatively compare the proposed solution to regular industrial solutions. The analysis will highlight the differences of the compared solutions on different topics like data integrity and immutability. Lastly, an outlook on industrial usage of the analyzed solution is given.
The Potential of High Speed Sintering for Small Series in the Automotive Industry
Authors: Huse Timo , Rehberg Laura
Published: June 2023

Individualization in the high-performance segment within the automotive industry is becoming increasingly important. Especially when small volumes are required, conventional manufacturing processes often no longer prove profitable. The use of additive processes in general and high-speed sintering (HSS) in particular offer the freedom to produce complex organic shapes in a cost-effective and resource-saving manner from batch size one onwards. The HSS process is a powder bed-based additive manufacturing process in which thermoplastics are sintered at a constant layer time using an infrared lamp instead of a laser

For this reason, we shed light on the use of high-speed sintering specifically for small components in low-volume production. More precisely, we add the process-specific properties of high-speed sintering to Design for Additive Manufacturing (DfAM) rules. We propose an approach that also enables a time-saving alternative to conventional manufacturing processes and optimizes the design process for the use of high-speed sintering.
Resilience to Pandemics through Flexibility in Sourcing, in Order Fulfillment, and Production Capacity of the Automotive Supply Chain
Authors: Gebauer Marc , Tangour Cyrine
Published: June 2023

Since the COVID-19 pandemic, the automotive industry which is regarded as a best practice considering its supply chain has experienced new threats which render its supply chain vulnerable. For instance, the many lockdowns, associated with collapsing of global distribution channels sunk vehicle sales dramatically. The purpose of this study is to identify capabilities to strengthen the resilience of automotive supply chains to pandemics. By using the supply chain resilience framework developed by Sytch et al. [4] we analyze the resilience of the automotive supply chain with evidence from the literature to a pandemic crisis with vulnerability factors similar to those of COVID-19.

We do find evidence that seven out of ten capabilities we looked for are present in the automotive supply chain. Capabilities to improve are i.e., multiple sources for tier 1 suppliers, improving risk pooling/sharing, and defining means of production postponement.

With the evidence on resilience factors for pandemics, we provide managers with a set of factors to focus on in pandemics. Thus, our study helps managers to better prepare their supply chain to resist global crises such as the COVID-19 pandemic. We used a methodology that can be applied with more secondary and also primary sources and therefore is interesting for researchers.
Dynamic Safety Distance Determination for Human Robot Coexistence in Industrial Applications
Authors: Fischer Marc , Klingel Lars , Lechler Armin , Verl Alexander , Neubauer Michael
Published: June 2023

The coexistence of humans and robots in manufacturing requires safety. Typically, safety functionalities for coexistence are based on speed and separation monitoring according to EN ISO 10218. Thereby, a robot should reduce speed or stop completely when an obstacle is too close to avoid collisions. Nowadays, despite this standard, speed and separation monitoring are still realized with static worst-case safety assumptions about the kinematics of humans and robots. Over the years, different static techniques have evolved in the industrial environment like fences, light fences, or camera-based systems where critical zones can be configured. The latter is admittedly more flexible in the configuration but still static during the run-time of the manufacturing system. The static worst-case assumptions result in large unnecessary distances between humans and robots, which leads to inefficient use of space. Therefore, factories are larger than they need to be, which leads to higher costs. This work aims to enhance the use of space in human-robot coexistence applications to make factory layouts more efficient. Therefore, a dynamic minimum distance calculation based on the DIN ISO 15066 with the kinematic information of the coexisting human and industrial robots is provided. It is shown in a simulation that this approach of a dynamic safety distance calculation leads to a reduction of the required space.
Integrated Framework for Safety Management and Software-Assisted Safety Assessment in Fluid Production
Authors: Koo Chee H. , Neuschwander Bernd , Vorderer Marian , Stehle Patrick , Kretzschmann Roman , Tasci Timur , Leberle Urs , Verl Alexander
Published: June 2023

In the factory of the future, the concept of fluid production allows production processes to be adapted more frequently and efficiently to fulfill rapidly-changing product requirements and to prevail in an increasingly challenging market environment. Production resources, machinery and humans are integrated seamlessly to achieve common production goals. Rapid changes in system configurations are also enabled by highly modular, self-descriptive and reusable machinery modules called Mechatronic Objects. The high reconfigurability in fluid production poses new challenges for the safety management of future production systems. Every modification done to an existing system needs to be risk assessed and approved during the commissioning to allow its safety-compliant operation. As current industrial practices for risk assessment are still labor-intensive and time-consuming, new methods are needed to quickly integrate the aforementioned highly modular Mechatronic Objects into fluid production systems. In this paper, we propose a safety management and assessment framework to address the safety-related challenges for fluid production. This paper proposes a new modeling method to describe the different types of Mechatronic Objects and derives different stages for the assessment and approval of fluid production systems. This allows a more efficient and accelerated commissioning phase, a seamlessly integrated production and the reduction of manual efforts needed for the system commissioning. The proposed framework, the methods and the implemented software tools are validated using a case study for a highly reconfigurable assembly system at the research campus ARENA2036 at the University of Stuttgart.
Mixed-Integer Programming Model for Scheduling of Modular Automotive Body-In-White Production Systems
Authors: Gelgfren Jan M. , Arvis Hélène , Hagemann Simon , Wenzel Sigrid
Published: June 2023

The turbulent transition in the automotive industry towards electric vehicles is highly challenging, both in product development and in production. Conventional, linear assembly lines struggle to meet the flexibility requirements imposed by this market development. This

paper presents the first mixed-integer programming (MIP) model which is tailor-made for the scheduling of modular body-in-white (BIW)

production systems. The main novelty of the presented approach lies in using precedence graphs for modelling the joining steps of the BIW production and allowing for different capabilities at each workstation of the production system. Thus, the presented approach captures the characteristics of BIW production systems in more detail than comparable models available in the literature. The application of the presented approach to an exemplary production scenario with five jobs and 22 operations underlines the strengths of the proposed model but also indicates potential for future improvements.
Robotic Assembly Line Balancing with Multimodal Stochastic Processing Times
Authors: Stade Dawid , Manns Martin
Published: June 2023

In this paper, a genetic algorithm for the robotic assembly line balancing problem (RALBP) is developed that supports multimodal stochastic processing times and multiple parallel-working robots per workstation. It has the objective to minimize the amount of workstations at a given production rate and probability limit for violating the cycle time (PL). The algorithm is evaluated on the BARTHOLD data set in a range of 1 % to 50 % for PL using an experimentally determined and a normal distribution for the task times. The increase of PL results in a shift of tasks from rear to front stations, because more tasks can be assigned to each station. The shift using normal distributed task times is stronger. This demonstrates the importance of realistic stochastic distribution assumptions. For practical applicability, more constraint types have to be included in the future.
Elementary Welding Operations for Automatic Robot Programming
Authors: Sarivan Ioan-Matei , Larsen Jørgen S. , Madsen Ole , Wæhrens Brian V.
Published: June 2023

Highly-skilled engineers are needed to reprogram a welding-robot upon a new variant or product introduction. This paper addresses the complexity of the welding-robot programming process by proposing and demonstrating the theoretical concept of “elementary welding operation” (EWO). The EWO is a fundamental building block for robot-welding programs containing most of the data necessary to generate a program automatically. The EWO is a descriptive data structure for the welding process, comprehensible by humans and machines. A technical proof of concept is put together and tested. The results indicate that the programming of the welding robot can be automated as part of a one-piece information flow based on a product model. Further development is required to ensure the system can handle complex weldment geometries, multi-pass welding, and proper validation of the robot program upon deployment.
Abnormal visual and olfactory sensations during radiation therapy: a prospective study
Authors: Mai Yiling , Vogel Celina , Thiele Julia , Hölscher Tobias , Hummel Thomas
Published: June 2023

Purpose

Patients sometimes report phosphene and phantosmia during radiation therapy (RT). However, the detail features and related factors are not well understood. Our prospective study aimed to investigate the characteristics of phantosmias and phosphenes, to identify factors that influence the occurrence, intensity and hedonic (pleasantness/unpleasantness) ratings of such sensations during RT.

Methods

We included a total of 106 patients (37 women), who underwent RT in regions of the brain, ear, nose, throat (ENT), and other areas of the body for a duration of 43 ± 5 days. Medical history and treatment parameters were collected in a structured medical interview. Olfactory function was measured using the Sniffin’ Stick Odor Identification Test at baseline. Phantosmia and phosphene were recorded weekly based on a self-report questionnaire.

Results

There were 37% of the patients experiencing phantosmias, 51% experiencing phosphenes, and 29% simultaneously experiencing both sensations. Phosphenes were typically perceived as a flashily blue, white and/or purple light, phantosmias were typically perceived as a chemical-like, metallic or burnt smell. Younger age (F = 7.81, p < 0.01), radiation in the brain region (χ2 = 14.05, p = 0.02), absence of taste problems (χ2 = 10.28, p = 0.01), and proton RT (χ2 = 10.57, p = 0.01) were related to these abnormal sensations. History of chemical/dust exposure predicted lower intensity (B = −1.52, p = 0.02) and lower unpleasantness (B = 0.49, p = 0.03) of phantosmia. In contrast, disease (tumor) duration (B = 0.11, p < 0.01), food allergy (B = 2.77, p < 0.01), and epilepsy (B = −1.50, p = 0.02) influence phosphenes intensity. Analgesics intake predicted a higher pleasantness of the phosphenes (B = 0.47, p < 0.01).

Conclusions

Phantosmias and phosphenes are common during RT. The treatment settings and individual arousal level influence the occurrence, intensity and hedonic of such abnormal sensations. Phantosmias and phosphenes may involve more central neural than peripheral mechanism, and they could be elicited with activation of areas that are not regarded to be part of the olfactory or visual network.
Infizierte, pathologische Humerusfraktur bei Sichelzellanämie – noch ein Einzelfall?
Authors: Ballhause Tobias Malte , Linke Philip , Hättich Annika , Klatte Till Orla , Frosch Karl-Heinz , Mader Konrad
Published: June 2023

Die vasookklusiven Krisen der Sichelzellkrankheit gehen mit Knochennekrosen einher, welche eine endogene Keimbesiedlung und somit eine Osteomyelitis begünstigen. Dies bringt eine große Herausforderung für die Eradikation und Frakturversorgung mit sich.

Ein 22-jähriger Patienten mit Sichelzellkrankheit erlitt eine mehrfragmentäre Humerusschaftfraktur. Im Rahmen der operativen Versorgung entleerte sich Pus im Frakturbereich, und es zeigte sich in der weiterführenden Diagnostik eine Osteomyelitis mit dem Nachweis von Klebsiella aerogenes. Fünf Monate vor dem Unfall kam es zu einer Septikämie durch Klebsiella aerogenes aufgrund einer vasookklusiven Krise. Diese gehen gehäuft mit Knochennekrosen und endogener Keimbesiedelung einher. Die Eradikation der Keime und die Frakturversorgung werden zu einer Herausforderung. Eine erfolgreiche Therapieoption sind wiederholte operative Eingriffe mit Segmenttransfer.
Klinische Ergebnisse der Ellenbogentotalendoprothetik nach Therapieversagen bei Monteggia-like-Verletzungen
Authors: Hockmann Jan , Ott Nadine , Leschinger Tim , Müller Lars Peter , Hackl Michael
Published: June 2023

Hintergrund

Monteggia-like-Frakturen (MLF) sind komplexe Verletzungen mit hohen Komplikationsraten und häufig unbefriedigenden funktionellen Ergebnissen. Bei posttraumatischer Gelenkdestruktion nach MLF stellt die Implantation einer Ellenbogentotalendoprothese (EB-TEP) oftmals die einzige Option zum Erhalt der Funktionalität des Ellenbogens dar. Diese Fallserie beleuchtet die klinischen Ergebnisse der EB-TEP nach gescheiterter Behandlung einer MLF.

Methoden

Alle Patienten mit EB-TEP-Implantation (2017–2022) nach Therapieversagen bei MLF wurden retrospektiv eingeschlossen. Die Komplikationen sowie Revisionen vor und nach EB-TEP und das funktionelle Ergebnis, bemessen mittels Broberg and Morrey-Score, wurden evaluiert.

Ergebnisse

In diese Studie wurden 9 Patienten mit einem Alter zum Zeitpunkt der EB-TEP-Implantation von 68 (±7; 54 bis 79) Jahren inkludiert. Der Nachbetrachtungszeitraum betrug 12 (±9; 2 bis 27) Monate. Die wesentlichen Ursachen, die zur Gelenkdestruktion führten, waren die chronische Osteomyelitis (44,4 %), die knöcherne Instabilität durch einen Processus-coronoideus-Defekt (33,3 %) bzw. einen kombinierten Processus-coronoideus- und Radiuskopfdefekt (22,2 %) sowie die Pseudarthrose der proximalen Ulna mit Radiuskopfnekrose (11,1 %). Die Anzahl an Revisionsoperationen von der Primärversorgung bis zur EB-TEP lag bei 2,7 (±1,8; 0 bis 6) Eingriffen. Die Revisionsrate nach EB-TEP betrug 44 %. Der Broberg/Morrey Score lag zum Zeitpunkt der letzten Nachuntersuchung bei 83 (±10; 71 bis 97) Punkten.

Die chronische Osteomyelitis und der Defekt des Processus coronoideus sind die führenden Ursachen für eine Gelenkdestruktion nach MLF, die zur EB-TEP führen. Wenngleich die klinischen Ergebnisse insgesamt zufriedenstellend sind, so muss angesichts der hohen Revisionsrate die Indikationsstellung streng selektiert werden.
Precipitation variability using GPCC data and its relationship with atmospheric teleconnections in Northeast Brazil
Authors: dos Santos Daris Correia , Santos Celso Augusto Guimarães , Brasil Neto Reginaldo Moura , da Silva Richarde Marques , dos Santos Carlos Antonio Costa
Published: June 2023

The present study investigates the influence of different atmospheric teleconnections on the annual precipitation variability in Northeast Brazil (NEB) based on the annual precipitation data from the Global Precipitation Climatology Center (GPCC) from 1901 to 2013. The objective of this study is to analyze the influence of different atmospheric teleconnections on the total annual precipitation of NEB for the 1901–2013 period, considering the physical characteristics of four subregions, i.e., Mid-north, Backwoods, Agreste, and Forest zone. To analyze the influence of different atmospheric teleconnections, GPCC data were used, and the behavior of the teleconnections was assessed using Pearson correlation coefficient, Rainfall Anomaly Index (RAI), and cross-wavelet analysis. The Pearson correlation was used to analyze the influence on the annual precipitation for the studied region. RAI was used to calculate the frequency of atmospheric patterns and drought episodes. The cross-wavelet analysis was applied to identify similarity signals between precipitation series and atmospheric teleconnections. The results of the Pearson correlation assessed according to Student's t test and cross-wavelet analysis showed that the Atlantic Multidecadal Oscillation (AMO) exerts a more significant influence on the Backwoods region at an interannual scale. In contrast, the Pacific Decadal Oscillation (PDO) exerts greater control over the modulation of the climatic patterns in NEB. The results of the study are insightful and reveal the differential impacts of teleconnections such as the AMO, PDO, MEI, and NAO on precipitation in the four sub-regions of NEB. The Atlantic circulation patterns strongly influence the interannual and interdecadal precipitation in the Agreste, Backwoods, and Mid-north regions, possibly associated with the Intertropical Convergence Zone (ITCZ) position. Finally, this study contributes to understanding internal climatic variability in NEB and planning of water resources and agricultural activities in such a region.

Graphic abstract
Forest gaps increase true bug diversity by recruiting open land species
Authors: Achury Rafael , Staab Michael , Blüthgen Nico , Weisser Wolfgang W.
Published: June 2023

Forests canopy gaps play an important role in forest ecology by driving the forest mosaic cycle and creating conditions for rapid plant reproduction and growth. The availability of young plants, which represent resources for herbivores, and modified environmental conditions with greater availability of light and higher temperatures, promote the colonization of animals. Remarkably, the role of gaps on insect communities has received little attention and the source of insects colonizing gaps has not been studied comprehensively. Using a replicated full-factorial forest experiment (treatments:Gap;Gap + Deadwood;Deadwood;Control), we show that following gap creation, there is a rapid change in the true bug (Heteroptera) community structure, with an increase in species that are mainly recruited from open lands. Compared with closed-canopy treatments (DeadwoodandControl), open canopy treatments (GapandGap + Deadwood) promoted an overall increase in species (+ 59.4%, estimated as number of species per plot) and individuals (+ 76.3%) of true bugs, mainly herbivores and species associated to herbaceous vegetation. Community composition also differed among treatments, and all 17 significant indicator species (out of 117 species in total) were associated with the open canopy treatments. Based on insect data collected in grasslands and forests over an 11-year period, we found that the species colonizing experimental gaps had greater body size and a greater preference for open vegetation. Our results indicate that animal communities that assemble following gap creation contain a high proportion of habitat generalists that not occurred in closed forests, contributing significantly to overall diversity in forest mosaics.
Quantitative Evaluation of the Fracturing State of Crystalline Rocks Using Infrared Thermography
Authors: Franzosi Federico , Casiraghi Stefano , Colombo Roberto , Crippa Chiara , Agliardi Federico
Published: June 2023

The fracturing state of rocks is a fundamental control on their hydro-mechanical properties. It can be quantified in the laboratory by non-destructive geophysical techniques that are hardly applicable in situ, where biased mapping and statistical sampling strategies are usually exploited.  We explore the suitabilty of infrared thermography (IRT) to develop a quantitative, physics-based approach to predict rock fracturing starting from laboratory scales and conditions. To this aim, we performed an experimental study on the cooling behaviour of pre-fractured gneiss and mica schist samples, whose 3D fracture networks were reconstructed using Micro-CT and quantified by unbiased fracture abundance measures. We carried out cooling experiments in both controlled (laboratory) and natural (outdoor) environmental conditions and monitored temperature with a thermal camera. We extracted multi-temporal thermograms to reconstruct the spatial patterns and time histories of temperature during cooling. Their synthetic description show statistically significant correlations with fracture abundance measures. More intensely fractured rocks cool at faster rates and outdoor experiments show that differences in thermal response can be detected even in natural environmental conditions. 3D FEM models reproducing laboratory experiments outline the fundamental control of fracture pattern and convective boundary conditions on cooling dynamics. Based on a lumped capacitance approach, we provided a synthetic description of cooling curves in terms of a Curve Shape Parameter, independent on absolute thermal boundary conditions and lithology. This provides a starting point toward the development of a quantitative methodology for the contactless in situ assessment of rock mass fracturing.
A Novel Platinum Resistance-Related Immune Gene Signature for Overall Survival Prediction in Patients with Ovarian Cancer
Authors: Zhou Chenfei , Ma Junnan , Luo Wanjun , Hu Jiemei , Chen Jing , Liang Suiying , He Shanyang
Published: June 2023

Ovarian cancer (OV) is a highly heterogeneous gynecological tumor that makes the prognostic prediction challenging. Resistance to platinum-based chemotherapy is associated with a poor prognosis in OV. There seems to be an overlap between molecular mechanisms responsible for platinum resistance and immunogenicity in OV. However, the predictive role of platinum resistance-related immune genes for OV prognosis needs to be further explored. In our study, the mRNA expression data of OV patients with corresponding clinical information were collected from The Cancer Genome Atlas (TCGA) cohort and International Cancer Genome Consortium (ICGC) cohort. A multigene signature was constructed for OV patients in the TCGA cohort using the least absolute shrinkage and selection operator (LASSO) Cox regression model according to the optimal value of λ and was validated in the ICGC cohort. Furthermore, we performed functional analysis to explore the immune status between low- and high-risk groups based on the median value of the risk score for the multigene signature. Our data showed that there were 41.1% of the platinum resistance-related genes which differentially expressed between immune score low- and high-OV patients in the TCGA cohort. Univariate Cox regression analysis identified 30 differentially expressed genes (DEGs) associated with overall survival (OS) (P < 0.05). 14 genes were identified to construct a novel platinum resistance-related immune model for classifying OV patients into the low- and high- risk groups. Patients in the low-risk group showed significantly higher OS than those in the high-risk group (P < 0.0001 in the both TCGA and ICGC cohort), which was associated with different immune status for the two risk groups. A novel platinum resistance-related immune model can be used for prognostic prediction in OV. Targeting tumor immunity may be a therapeutic alternative for OV with platinum resistance.
Heat Capacity of Various (Solvent + Terpene) Mixtures as Function of Composition and Temperature
Authors: Castellanos Nicolás Stiven , Villa Aída Luz
Published: June 2023

The heat capacity of different mixtures of terpenes (α-pinene, β-pinene, limonene oxide) and solvents (acetone, toluene, ethyl acetate) at atmospheric pressure (85.1 kPa atm in Medellin, Colombia) were measured using a microcalorimeter at several terpene molar fractions and from room temperature to a value close to the solvent boiling point. The mixtures analyzed were acetone + α-pinene from 298.15 to 323.15 K, toluene + limonene oxide and toluene + β-pinene from 298.15 to 358.15 K, and ethyl acetate + β-pinene between 298.15 and 338.15 K. These mixtures, at the selected temperature ranges, are used in fine chemical catalytic reactions. The experimental heat capacity values were fitted to polynomials as a function of temperature. Excess heat capacity was calculated with the measured molar heat capacity for all the mixtures, it decreased with temperature. Experimental uncertainty was less than 1.5% with a confidence level of 95% using k = 2. The experimental results were consistent, for example the heat capacity of ethyl acetate + β-pinene mixture increased as the temperature increased and decreased with the composition of the solvent; at 308.15 K the heat capacity decreased from 252.73 to 245.17 J mol−1 K−1 when solvent composition increased from 0.1546 to 0.2797 and at a solvent composition of 0.1546, heat capacity increased from 237.26 to 252.73 J·mol−1·K−1 when temperature increased from 298.15 to 308.15 K.
Nitrous oxide emissions after struvite application in relation to soil P status
Authors: Yang Zhongchen , Ferron Laura M. E. , Koopmans Gerwin F. , Sievernich Angela , van Groenigen Jan Willem
Published: June 2023

Purpose

Although struvite (MgNH4PO4·6H2O) is mostly considered to be a novel phosphorus (P) fertiliser, it does contain a significant amount of nitrogen (N). Yet, relatively little is known about the soil N dynamics in struvite-amended soils. Here, we focus on how struvite application impacts emissions of the greenhouse gas nitrous oxide (N2O), in relation to soil P status.

Methods

We conducted a 54-day greenhouse pot experiment on two similar soils with different P status (“low-P soil”; “high-P soil”) seeded with Lolium perenne L. We applied seven fertiliser treatments (Control; Struvite granules; Struvite powder; Urea; Triple superphosphate (TSP); TSP + Struvite granule; TSP + Urea). Except for the unfertilised Control and the TSP treatments, N application rate was 150 kg N‧ha−1. Nitrous oxide (N2O) fluxes, aboveground yield, plant N and P uptake and readily plant-available soil N and P contents were measured.

Results

In the low-P soil, none of the fertiliser treatments induced a significant increase in N2O emission compared to the control. In the high-P soil, struvite application resulted in lower emissions than urea application, statistically not different from the control treatment. Struvite powder significantly increased both plant N and P uptake compared to granular struvite and the resulting yield was similar to conventional fertilisation (TSP and Urea). Any struvite application also resulted in lower readily plant-available soil nitrate contents than urea.

Conclusion

Our results suggest that struvite fertilisation can reduce the risk of gaseous N losses without compromising agronomic performance. Pulverizing struvite granules further promotes its dissolution, which could be useful for crops with early nutrient needs.
Numerical simulation and PIV measurements of the wave-induced flow field near semi-circular breakwaters
Authors: Gomaa Mona A. , Kasem Tamer H. M. A. , Huzayyin Omar A. , Schlenkhoff Andreas , Sasaki Jun
Published: June 2023

Careful design of the high-tech semi-circular breakwaters (SBW), which are used for protection against sea waves, is essential to avoid the failure of these large-scale projects. An improved design tool adopting numerical simulations, complemented with experimental measurements is introduced. Unstructured boundary-fitted grids are used to model the curved SBW boundary accurately and resolve the flow adjacent to it. Experimental measurements based on Particle Image Velocimetry (PIV) are introduced and the numerically simulated velocity fields are validated. For the first time, the strong free surface deformation upstream of the SBW, termed trough-breaking, is reproduced numerically. The phenomenon is investigated in detail and its impact on several SBW advantages and stability is emphasized. The improved accuracy due to unstructured boundary-fitted grids complemented by the PIV data set, offers valuable prospects for performing complex designs and exploring future applications.

Article Highlights

An efficient design tool for the high-tech semi-circular breakwater is introduced adopting numerical simulations and experimental measurements.

The numerical results agree well with the experimental measurements. Hence, this experimental data set should be used extensively for validation in future studies.

The important flow phenomenon of “trough-breaking” is reproduced numerically for the first time, and its impact on the semi-circular breakwater features is clarified.
A novel scale based on biomarkers associated with COVID-19 severity can predict the need for hospitalization and intensive care, as well as enhanced probabilities for mortality
Authors: Nieto-Ortega Eduardo , Maldonado-del-Arenal Alejandro , Escudero-Roque Lupita , Macedo-Falcon Diana Ali , Escorcia-Saucedo Ana Elena , León-del-Ángel Adalberto , Durán-Méndez Alejandro , Rueda-Medécigo María José , García-Callejas Karla , Hernández-Islas Sergio , Romero-López Gabriel , Hernández-Romero Ángel Raúl , Pérez-Ortega Daniela , Rodríguez-Segura Estephany , Montaño‑Olmos Daniela , Hernández-Muñoz Jeffrey , Rodríguez-Peña Samuel , Magos Montserrat , Aco-Cuamani Yanira Lizeth , García-Chávez Nazareth , García-Otero Ana Lizeth , Mejía-Rangel Analiz , Gutiérrez-Losada Valeria , Cova-Bonilla Miguel , Aguilar-Arroyo Alma Delia , Sandoval-García Araceli , Martínez-Francisco Eneyda , Vázquez-García Blanca Azucena , Jardínez-Vera Aldo Christiaan , del Campo Alejandro Lechuga-Martín , Peón Alberto N.
Published: June 2023

Prognostic scales may help to optimize the use of hospital resources, which may be of prime interest in the context of a fast spreading pandemics. Nonetheless, such tools are underdeveloped in the context of COVID-19. In the present article we asked whether accurate prognostic scales could be developed to optimize the use of hospital resources. We retrospectively studied 467 files of hospitalized patients after COVID-19. The odds ratios for 16 different biomarkers were calculated, those that were significantly associated were screened by a Pearson’s correlation, and such index was used to establish the mathematical function for each marker. The scales to predict the need for hospitalization, intensive-care requirement and mortality had enhanced sensitivities (0.91 CI 0.87–0.94; 0.96 CI 0.94–0.98; 0.96 CI 0.94–0.98; all withp < 0.0001) and specificities (0.74 CI 0.62–0.83; 0.92 CI 0.87–0.96 and 0.91 CI 0.86–0.94; all withp < 0.0001). Interestingly, when a different population was assayed, these parameters did not change considerably. These results show a novel approach to establish the mathematical function of a marker in the development of highly sensitive prognostic tools, which in this case, may aid in the optimization of hospital resources. An online version of the three algorithms can be found at:http://benepachuca.no-ip.org/covid/index.php
Microbial diversity in the vaginal microbiota and its link to pregnancy outcomes
Authors: Baud Agnes , Hillion Kenzo-Hugo , Plainvert Céline , Tessier Véronique , Tazi Asmaa , Mandelbrot Laurent , Poyart Claire , Kennedy Sean P.
Published: June 2023

The vaginal microbiota refers to the microorganisms that reside in the vagina. These microorganisms contribute significantly to a woman’s reproductive and general health. A healthy vaginal microbiota is typically a low-diversity environment with a predominance of lactic acid-producing Lactobacillus species. Factors such as antibiotic use, sexual activity, and hormonal changes can disrupt the balance of the vaginal microbiota, leading to conditions such as bacterial vaginosis. The composition of the vaginal microbiota changes and takes on added importance during pregnancy, serving as a barrier against infection for both mother and fetus. Despite the importance of the microorganisms that colonize the vagina, details of how changes in composition and diversity can impact pregnancy outcomes is poorly understood. This is especially true for woman with a high prevalence of Gardnerella vaginalis. Here we report on a diverse cohort of 749 women, enrolled in the InSPIRe cohort, during their final trimester of pregnancy. We show that Lactobacilli, including L. crispatus are important in maintaining low diversity, and that depletion in this critical community is linked with preterm delivery. We further demonstrate that it is overall diversity of the vaginal microbiota, not specific species, which provides the best indicator of risk.
Key management scheme of distributed IoT devices based on blockchains
Authors: Liu Qingyuan , Luo Lei , Wang Jian , Li Wenshun , Liu Ruijia , Yu Ming
Published: June 2023

With the rapid development of Internet of Things devices and communication technology, the number of devices connected to the Internet of Things is growing exponentially. However, in the context of the rapid increase in the number of devices, data security issues such as data leakage and data tampering also follow. Therefore, communication security between devices is particularly important. However, in the traditional network environment, the identity authentication and information encryption methods to ensure communication security mostly adopt centralized network structure, relying on the central equipment to manage the access edge equipment. However, due to the heterogeneity of IoT devices and limited resources, the traditional centralized management scheme does not fully comply with the IoT system. In order to solve the above problems, this paper proposes a blockchain distributed IoT device key management scheme under the blockchain technology framework, which proposes a blockchain based distributed IoT architecture, and designs a hash chain based identity authentication scheme and a key distribution scheme based on network security coding on the basis of this architecture. Because blockchain technology has the characteristics of openness, immutability, traceability and fault tolerance, it can ensure the privacy of data transmission in the IoT scene, thus providing a secure communication environment. In this paper, the performance indexes related to the scheme are evaluated, and the experimental analysis confirms the efficiency and scalability of the proposed scheme.
Performance study of HF communication using NOMA over narrowband HF channel
Authors: Ismail Ahmad , Mohamedpour Kamal
Published: June 2023

High frequency systems (HF) are still used in many communication applications. Data can be sent for hundreds of kilometers at a low power cost with only one drawback, low bitrate. To increase the bitrate, several methods were reported using the single‐Tone modulation with 24 kHz bandwidth, but still not practical in real‐time applications because, the 24 kHz is unavailable due to the instability of the ionosphere layer. In this work, we propose a structured method built on the Non‐Orthogonal Multiple Access technique (NOMA) to increase the bit rate per HF narrowband channel. To increase the data rate, two parts of the data are divided and sent to one user over two different power levels. We use the NOMA technique on the receiver's side to recognize the two parts of data. The results show a significant improvement (up to 45%) using NOMA in narrowband 3 kHz channels. The bit rate at the receiver has increased up to 200 Kb/s concerning, while the maximum bit rate recorded by conventional methods used in previous studies is 138 Kb/s. The system is built on the SDR platform and tested in multiple channels, weather, and power conditions in real‐time experiments to validate its reliability.