bluuebunny/crossref_metadata_2025 huggingface dataset:
Implementation of a Novel Fully Convolutional Network Approach to Detect and Classify Cyber-Attacks on IoT Devices in Smart Manufacturing Systems
Authors: Shahin Mohammad , Chen FFrank , Bouzary Hamed , Hosseinzadeh Ali , Rashidifar Rasoul
Published: October 2022

In recent years, Internet of things (IoT) devices have been widely implemented and industrially improved in manufacturing settings to monitor, collect, analyze, and deliver data. Nevertheless, this evolution has increased the risk of cyberattacks, significantly. Consequently, developing effective intrusion detection systems based on deep learning algorithms has proven to become a dependable intelligence tool to protect Industrial IoT devices against cyber-attacks. In the current study, for the first time, two different classifications and detection long short-term memory (LSTM) architectures were fine-tuned and implemented to investigate cyber-security enhancement on a benchmark Industrial IoT dataset (BoT-IoT) which takes advantage of several deep learning algorithms. Furthermore, the combinations of LSTM with FCN and CNN demonstrated how these two models can be used to accurately detect cyber security threats. A detailed analysis of the performance of the proposed models is provided. Augmenting the LSTM with FCN achieves state-of-the-art performance in detecting cybersecurity threats.
A Mathematical Model for Cloud-Based Scheduling Using Heavy Traffic Limit Theorem in Queuing Process
Authors: Rashidifar Rasoul , Chen F. Frank , Bouzary Hamed , Shahin Mohammad
Published: October 2022

Cloud manufacturing (CMfg) is a service-oriented manufacturing paradigm that distributes resources in an on-demand business model. In the cloud manufacturing environment, scheduling is considered as an effective tool for satisfying customer requirements which has attracted attention from researchers. In this case, quality of service (QoS) in the scheduling plays a vital role in assessing the impacts of the distributed resources in operation on the performance of scheduling functions. In this paper, a queuing system is employed to model the scheduling problem with multiple servers and then scheduling in cloud manufacturing is classified based on various QoS requirements. Moreover, a set of heavy traffic limit theorems is introduced as a new approach to solving this scheduling problem in which different heavy traffic limits are provided for each of QoS-based scheduling classes. Finally, the number of operational resources in the scheduling is determined by considering the results obtained in the numerical analysis of the heavy traffic limit with different queue disciplines. The results show that different numbers of active machines in various QoS requirements classes play a vital role in that the required QoS metrics such as the expected waiting time and the expected completion time which are critical performance indicators of the cloud’s service are intimately related.
Cost-Minimal Selection of Material Supply Strategies in Matrix Production Systems
Authors: Ranke Daniel , Bauernhansl Thomas
Published: October 2022

Companies are facing changing market demands, high variance, and volatile quantities. Resilient production systems are needed to meet these challenges. The matrix production is such a system. It offers degrees of freedom in terms of operation sequence flexibility and work distribution flexibility through redundantly used resources. For the material supply this is a challenge in planning. The material must be supplied in a cost-efficient manner and without shortages.

To increase planning quality, a method for selecting the least expensive material supply strategy is developed. Depending on consumption, constraints of space, and supply framework conditions, different strategies are advantageous for each material. The developed method requires three steps.

First, required data for step 2 and step 3 is collected. In step 2, standardized process blocks combine to describe a company-specific material supply strategy. The approach is company-independent and added by cost functions to the process blocks. Through the cost functions applied to the process blocks the costs of a supply strategy is achieved. As material can be supplied in alternative ways, multiple expected costs for supplying arise. As only one supply strategy needs to be selected, step 3 is necessary. It uses the branch-and-cut algorithm on the mathematical description of the logistic selection problem to find the cost-minimal configuration of supply strategies. As the problem is in the context of matrix production, several conditions and requirements need to be included in the selection process.

The result is the assignment of a material supply strategy to each material while minimizing the costs.
Feasibility Analysis of Safety Training in Human-Robot Collaboration Scenario: Virtual Reality Use Case
Authors: Dianatfar Morteza , Heshmatisafa Saeid , Latokartano Jyrki , Lanz Minna
Published: October 2022

Design and modification of human-robot collaboration workspace requires analysis of the safety of systems. Generally, the safety analysis process of a system commences with conducting a risk assessment. There exists a number international standards for design robotics work cells and collaborative shared workspaces. These guidelines expound on principles and measures to identify hazards and reduce risks. Measures of risk reductions include eliminating hazards by design, safeguarding, and providing supplementary protective measures such as user training. This study analyzed the technical feasibility and industrial readiness of Virtual Reality (VR) technology for safety training in manufacturing sector. The test case of a VR-based safety training application is defined in the human-robot collaboration pilot-line of diesel engines. The Analytic Hierarchy Process method was utilized for conducting a quantitative analysis of the survey with ten experts. The participants performed the importance rating with respect to two hierarchy level criteria. Regarding the evaluation of safety training methods in a human-robot collaboration environment, two alternatives of traditional and Virtual Reality -based training are compared. The results indicates that the VR-based training is valued over the traditional method, with a scored proportion of approximately 65 percent over 35 percent.
The Impact of Learning Factories on Teaching Lean Principles in an Assembly Environment
Authors: Monetti Fabio Marco , Boffa Eleonora , de Giorgio Andrea , Maffei Antonio
Published: October 2022

Learning factories are realistic manufacturing environments built for education; many universities have recently introduced learning factories in engineering programs to tackle real industrial problems; however, statistical studies on its effectiveness are still scarce. This paper presents a statistical study on the impact of learning factories on the students’ learning process, when teaching the lean manufacturing concepts in an assembly environment. The analysis is carried out through the Lean Manufacturing Lab at KTH, a learning factory supporting the traditional educational activities. In the lab, the students assemble a product on an assembly line; during three rounds, they identify problems on the line, apply the appropriate lean tools to overcome the problems, and try to achieve a higher productivity. The study is based on the analysis of the times recorded during the sessions of the lab. A questionnaire submitted to the students after the course evaluates the level of knowledge of lean production principles that the students achieved. The results are twofold: the improvement of the assembly times through the implementation of the lean tools and the positive effect of a hands-on experience on the students’ understanding of the lean principles, highlighted by the answers to the questionnaire. The main contributions are that applying the lean tools on an assembly line improves the productivity even with inexperienced operators, implementing a learning factory is effective in enhancing the learning process, and, lastly, that a first-hand experience applying the lean tools in a real assembly environment is an added value to the students’ education.
Generation of Synthetic AI Training Data for Robotic Grasp-Candidate Identification and Evaluation in Intralogistics Bin-Picking Scenarios
Authors: Holst Dirk , Schoepflin Daniel , Schüppstuhl Thorsten
Published: October 2022

Robotic bin picking remains a main challenge for the wide enablement of industrial robotic tasks. While AI-enabled picking approaches are encouraging they repeatedly face the problem of data availability. The scope of this paper is to present a method that combines analytical grasp research with the field of synthetic data creation to generate individual training data for use-cases in intralogistics transportation scenarios. Special attention is given to systematic grasp finding for new objects and unknown geometries in transportation bins and to match the generated data to a real two-finger parallel gripper. The presented approach includes a grasping simulation in Pybullet to investigate the general tangibility of objects under uncertainty and combines these findings with a previously reported virtual scene generator in Blender, which generates AI-images of fully packed transport boxes, including depth maps and necessary annotations. This paper, therefore, contributes a synthesizing and cross-topic approach that combines different facets of bin-picking research such as geometric analysis, determination of tangibility of objects, grasping under uncertainty, finding grasps in dynamic and restricted bin-environments, and automation of synthetic data generation. The approach is utilized to generate synthetic grasp training data and to train a grasp-generating convolutional neural network (GG-CNN) and demonstrated on real-world objects.
Objectifying Machine Setup and Parameter Selection in Expert Knowledge Dependent Industries Using Invertible Neural Networks
Authors: Müller Kai , Posada-Moreno Andrés , Pelzer Lukas , Gries Thomas
Published: October 2022

The textile industry is one of the oldest and largest industries in the world. The fields of application for textile products are diverse. Although the technologies for manufacturing textiles are extensively researched, the industry is still highly dependent on expert knowledge. To date, manual process- and machine adjustments and quality control are the norms rather than the exception. Heat setting is used in the process chain to dissolve or selectively introduce tensions from the weaving or knitting process and to prepare the products for digital printing. The correct setting of the machine depends on a large number of different materials-, processes- & environmental parameters. For each product, the machine has to be set up again by an experienced textile engineer. To ease the training for new workers and shorten the machine setting process, this study aims to use machine learning to facilitate and objectify the setting of the heat-setting process. Machine parameters are generated using an invertible neural network (INN) based on pre-defined target parameters. The results can be used to identify trends in machine settings and respond accordingly. Thus, a reduction of machine setting time could be realized.
Augmented Virtuality Input Demonstration Refinement Improving Hybrid Manipulation Learning for Bin Picking
Authors: Blank Andreas , Zikeli Lukas , Reitelshöfer Sebastian , Karlidag Engin , Franke Jörg
Published: October 2022

Beyond conventional automated tasks, autonomous robot capabilities aside human cognitive skills are gaining importance in industrial applications. Although machine learning is a major enabler of autonomous robots, system adaptation remains challenging and time-consuming. The objective of this research work is to propose and evaluate an augmented virtuality-based input demonstration refinement method improving hybrid manipulation learning for industrial bin picking. To this end, deep reinforcement and imitation learning are combined to shorten required adaptation timespans to new components and changing scenarios. The method covers initial learning and dataset tuning during ramp-up as well as fault intervention and dataset refinement. For evaluation standard industrial components and systems serve within a real-world experimental bin picking setup utilizing an articulated robot. As part of the quantitative evaluation, the method is benchmarked against conventional learning methods. As a result, required annotation efforts for successful object grasping are reduced. Thereby, final grasping success rates are increased. Implementation samples are available on: https://github.com/FAU-FAPS/hybrid_manipulationlearning_unity3dros
3D Printing of Hydrogel-Based Seed Planter for In-Space Seed Nursery
Authors: Huang Yanhua , Yu Li , Jiang Liangkui , Shi Xiaolei , Qin Hantang
Published: October 2022

Interest in manufacturing parts using 3D printing became popular across academic and industrial sectors because of its improved reliability and accessibility. With the necessity of self-sustentation, growing plant in space is one of the most popular topics. Carboxymethyl cellulose (CMC) is one of the best candidates for sprouting substrate with 3D printing fabrication as it is non-toxic, biodegradable, and suitable for extrusion-based 3D printing. Soybeans were placed into the designed and printed CMC gel with different orientations. Without visible light, soybeans with hilum facing side had the highest water absorption average comparing those facing up or down. Hydrogel weight dominated the water absorption efficiency. These findings signified that bean orientation affects the sprouting process. This study demonstrates the substrate geometry and seed orientation impacts on germination of soybeans, proposed guidelines for optimizing the sprouting process for high-level edible plants and promoting innovated in-space seed nursery approach.
Assessment of Reconfigurable Vibrating Screen Technology for the Mining Industries
Authors: Ramatsetse Boitumelo , Mpofu Khumbulani , Daniyan Ilesanmi , Makinde Olasumbo
Published: October 2022

Vibrating screens are very vital in the mineral processing industries for the beneficiation (separation) of mineral particles into different sizes. The breaking down of vibrating screens due to unforeseen contingencies have reduced the productivity of these machines thereby reducing the competitiveness, availability and reliability of these machines for the set production target made by the company. Also since human wants are insatiable, fluctuation in the mineral concentrates demands has been an inevitable scenario, thus, reducing the efficiency of the mineral beneficiation industries. During peak mineral concentrates demand, most of these industries do not have an option than to purchase another beneficiation screen in order to meet up with the continuously increasing production demand. A solution called the Reconfigurable Vibrating Screen (RVS) that can cover the gaps created by machine breakdown, and ensure that the variations in quantity of mineral concentrates needed by customers are met. In this paper, a state of configurations achieved by RVS as compared to the existing conventional vibrating screens was made. In addition to this, a market assessment of the proposed RVS and other existing screening technologies was performed. The index parameters used for this analysis are capacity, reliability, efficiency, versatility and cost. From the comparative analysis, it was observed that there are high advantages for using RVS for beneficiation operations in the mineral beneficiation in place of existing vibrating screens.
Ausgangslage
Authors: Lorenz Sandro
Published: October 2022

Das anästhesiologische Prämedikationsgespräch beinhaltet drei grundlegende Kernprozesse, nämlich die anästhesiologische Prämedikation mit Anamnese, präoperativen Anordnungen, Medikation und der Auswahl des geeigneten Narkoseverfahrens; die Aufklärung und Einwilligung des Patienten im Sinne des informed consents und aller rechtlich vorgeschriebenen Teilaspekte und den Aufbau einer tragfähigen Arzt-Patienten-Beziehung.
Präoperative Angst
Authors: Lorenz Sandro
Published: October 2022

In diesem Kapitel soll Angst, im Rahmen von operativen Eingriffen und im Speziellen im Vorfeld einer derartigen Prozedur besprochen werden. Dabei sollen sowohl die Definitionen, die Genese, die Auswirkungen und die Messung detailliert betrachtet werden.
Qualität und Qualitätsmanagement im stationären Sektor
Authors: Lorenz Sandro
Published: October 2022

Um Qualität und Qualitätsmanagement im Krankenhausbereich adäquat beleuchten zu können ist ein Exkurs in die politischen und gesundheitsökonomischen Strukturen notwendig. Die Verhältnisse im Gesundheitsbereich und insbesondere im stationären Bereich haben sich in den letzten 20 Jahren drastisch verändert [371].
Leptogenesis in SO(10) models with A4 modular symmetry
Authors: Ding Gui-Jun , King Stephen F. , Lu Jun-Nan , Qu Bu-Yao
Published: October 2022

Abstract

We study the prediction for leptogenesis in two renormalizable supersymmetric SO(10) × A4 modular models in which the neutrino mass is dominantly generated by the type I seesaw mechanism. The evolution of the lepton asymmetries are described in terms of the three-flavored density matrix equations for three heavy Majorana neutrinos, where both vanishing initial condition and thermal initial condition of the right-handed neutrinos are considered. We also present an analytical approximation based on the Boltzmann equations. We find regions of parameter space compatible with the measured fermion masses and mixing parameters as well as the baryon asymmetry of the Universe. The predictions for the light neutrino masses, the effective mass in neutrinoless double beta decay and the leptonic CP violation phases are discussed.
Celestial holography on Kerr-Schild backgrounds
Authors: Gonzo Riccardo , McLoughlin Tristan , Puhm Andrea
Published: October 2022

Abstract

We explore the celestial holography proposal for non-trivial asymptotically flat backgrounds including the Coulomb field of a static and spinning point charge, their gravitational counterparts described by the Schwarzschild and Kerr metrics, as well as the Aichelburg-Sexl shockwave and spinning shockwave geometries and their electromagnetic cousins. We compute celestial two-point amplitudes on these Kerr-Schild type backgrounds which have the desirable feature, due to the presence of an external source, that they are non-vanishing for general operator positions and are not constrained by the kinematic delta functions of flat space celestial CFT correlators. Of particular interest is the case of shockwave backgrounds where the two-point scattering amplitude of massless scalars can be interpreted as a standard CFT three-point correlator between two massless asymptotic states and a conformal primary shockwave operator. We furthermore show that the boundary on-shell action for general backgrounds becomes the generating functional for tree-level correlation functions in celestial CFT. Finally, we derive (conformal) Faddeev-Kulish dressings for particle-like backgrounds which remove all infrared divergent terms in the two-point functions to all orders in perturbation theory.
Lumbo-pelvino-azetabuläres Alignment – Grundlagen und klinische Konsequenzen
Authors: Heimkes Bernhard , Berger Nina , Frimberger Vincent
Published: October 2022

Die Wirbelsäulenform wie auch die pelvine Ante‑/Retroversion eines Individuums werden durch seine angeborene, genetisch fixierte lumbosakrale Angulation bestimmt. Diese kann wenig aufwendig in der seitlichen Stehaufnahme des Patienten vermessen werden. In der Wirbelsäulenchirurgie existiert zum Thema eine große Anzahl von Originalarbeiten, in der Hüftchirurgie wurde die individuelle Beckenversion und ihre Konsequenzen für die azetabuläre Orientierung der Hüftpfanne bisher weniger beachtet.

Im vorliegenden Review werden bisherige Kenntnisse zum Zusammenhang zwischen lumbosakraler Angulation und pelviner Ante‑/Retroversion dargestellt. Es lassen sich hierbei vier anatomisch definierbare Beckentypen unterscheiden, wovon drei als fakultativ pathogen angesehen werden müssen. Klinische Konsequenzen ergeben sich für die Krankheitsbilder der Spondylolisthesis, des nichtspezifischen Kreuzschmerzes, der azetabulären Retroversion, der kongenitalen Hüftdysplasie sowie für die Pfannenpositionierung in der Hüftendoprothetik.
Abdominelle Weichgewebstumoren
Authors: Wardelmann Eva , Kuntze Anna , Trautmann Marcel , Hartmann Wolfgang
Published: October 2022

Gastrointestinale Stromatumoren sind mit einer Inzidenz von 10–15 Fällen pro 1 Mio. Einwohner in Deutschland die häufigsten mesenchymalen Tumoren im Abdominalbereich. Ihre eindeutige Identifikation und Charakterisierung ist für betroffene Personen prognostisch und therapeutisch von großer Bedeutung. Ebenso wichtig ist aber auch die klare Abgrenzung anderer mesenchymaler Neoplasien, zu denen leiomyomatöse, neurogene, adipozytäre und fibroblastäre Tumoren gehören. Zudem wächst die Zahl der translokationspositiven Entitäten, die sich nur mit entsprechenden molekularen Methoden eindeutig diagnostizieren lassen. Ziel dieses Beitrags ist es, für deren sichere Identifikation praktische Hinweise zu geben. Eine mögliche Referenzpathologie kann die Diagnosefindung unterstützen.
Fast and Stable Approximation of Analytic Functions from Equispaced Samples via Polynomial Frames
Authors: Adcock Ben , Shadrin Alexei
Published: October 2022

We consider approximating analytic functions on the interval $$[-1,1]$$

[
-
1
,
1
]

from their values at a set of $$m+1$$

m
+
1

equispaced nodes. A result of Platte, Trefethen & Kuijlaars states that fast and stable approximation from equispaced samples is generally impossible. In particular, any method that converges exponentially fast must also be exponentially ill-conditioned. We prove a positive counterpart to this ‘impossibility’ theorem. Our ‘possibility’ theorem shows that there is a well-conditioned method that provides exponential decay of the error down to a finite, but user-controlled tolerance $$\epsilon > 0$$

ϵ
>
0

, which in practice can be chosen close to machine epsilon. The method is known as polynomial frame approximation or polynomial extensions. It uses algebraic polynomials of degree n on an extended interval $$[-\gamma ,\gamma ]$$

[
-
γ
,
γ
]

, $$\gamma > 1$$

γ
>
1

, to construct an approximation on $$[-1,1]$$

[
-
1
,
1
]

via a SVD-regularized least-squares fit. A key step in the proof of our main theorem is a new result on the maximal behaviour of a polynomial of degree n on $$[-1,1]$$

[
-
1
,
1
]

that is simultaneously bounded by one at a set of $$m+1$$

m
+
1

equispaced nodes in $$[-1,1]$$

[
-
1
,
1
]

and $$1/\epsilon $$

1
/
ϵ

on the extended interval $$[-\gamma ,\gamma ]$$

[
-
γ
,
γ
]

. We show that linear oversampling, i.e. $$m = c n \log (1/\epsilon ) / \sqrt{\gamma ^2-1}$$

m
=
c
n
log

(
1
/
ϵ
)

/

γ
2

-
1

, is sufficient for uniform boundedness of any such polynomial on $$[-1,1]$$

[
-
1
,
1
]

. This result aside, we also prove an extended impossibility theorem, which shows that such a possibility theorem (and consequently the method of polynomial frame approximation) is essentially optimal.
Density-impact functions for invasive house mouse (Mus musculus) effects on indigenous lizards and invertebrates
Authors: Norbury Grant , Wilson Deborah J. , Clarke Dean , Hayman Ella , Smith James , Howard Simon
Published: October 2022

House mice are among the most widely distributed mammals in the world, and adversely affect a wide range of indigenous biota. Suppressing mouse populations, however, is difficult and expensive. Cost-effective suppression requires knowing how low to reduce mouse numbers to achieve biodiversity outcomes, but these targets are usually unknown or not based on evidence. We derived density-impact functions (DIFs) for mice and small indigenous fauna in a tussock grass/shrubland ecosystem. We related two indices of mouse abundance to five indices of indigenous lizard and invertebrate abundance measured inside and outside mammal-resistant fences. Eight of 22 DIFs were significantly non-linear, with positive responses of skinks (Oligosoma maccanni,O. polychroma) and ground wētā (Hemiandrusspp.) only where mice were not detected or scarce (< 5% footprint tunnel tracking rate or printing rate based on footprint density). Kōrero geckos (Woodworthiaspp.) were rarely detected where mice were present. A further 9 DIFs were not differentiated from null models, but patterns were consistent with impacts at 5% mouse abundance. This study suggests that unless mouse control programmes commit to very low abundances, they risk little return for effort. Impact studies of invasive house mice are largely restricted to island ecosystems. Studies need to be extended to other ecosystems and species to confirm the universality or otherwise of these highly non-linear DIFs.
Bifurcation of frozen orbits in a gravity field with zonal harmonics
Authors: Cavallari Irene , Pucacco Giuseppe
Published: October 2022

We propose a methodology to study the bifurcation sequences of frozen orbits when the second-order fundamental model of the satellite problem is augmented with the contribution of octupolar terms and relativistic corrections. The method is based on the analysis of twice-reduced closed normal forms expressed in terms of suitable combinations of the invariants of the Kepler problem, able to provide a clear geometric view of the problem.
The Influence of Bilingual Language Exposure on the Narrative, Social and Pragmatic Abilities of School-Aged Children on the Autism Spectrum
Authors: Beauchamp Myriam L. H. , Rezzonico Stefano , Bennett Terry , Duku Eric , Georgiades Stelios , Kerns Connor , Mirenda Pat , Richard Annie , Smith Isabel M. , Szatmari Peter , Vaillancourt Tracy , Waddell Charlotte , Zaidman-Zait Anat , Zwaigenbaum Lonnie , Elsabbagh Mayada
Published: October 2022

We examined the narrative abilities of bilingual and monolingual children on the autism spectrum (AS), whether bilinguals presented stronger social and pragmatic language abilities compared to monolinguals, and the link between narrative, social, and pragmatic language abilities.

The narrative, social, and pragmatic language skills of school-aged bilinguals (n = 54) and monolinguals (n = 80) on the AS were assessed using normed measures. Language exposure was estimated through a parent questionnaire.

Bilinguals performed similarly to monolinguals on measures of narrative, social, and pragmatic language skills. However, balanced bilinguals performed better on a nonliteral language task.

Overall, results indicate that bilingual children on the AS can become as proficient in using language as monolinguals and may enjoy a bilingual advantage.
Cooling access and energy requirements for adaptation to heat stress in megacities
Authors: Mastrucci Alessio , Byers Edward , Pachauri Shonali , Rao Narasimha , van Ruijven Bas
Published: October 2022

As urban areas are increasingly exposed to high temperatures, lack of access to residential thermal comfort is a challenge with dramatic consequences for human health and well-being. Air-conditioning (AC) can provide relief against heat stress, but a massive AC uptake could entail stark energy demand growth and mitigation challenges. Slums pose additional risks due to poor building quality, failing to provide adequate shelter from severe climatic conditions. Thus, it is unclear how many people in the Global South will still lack access to basic cooling under different future climate and socioeconomic developments. We assess the impact of different shared socioeconomic pathways (SSPs) and climate futures on the extent of population lacking access to cooling where needed—the cooling gap—and energy requirements for basic comfort for a set of 22 megacities in the Global South. We find that different SSPs greatly influence the extent of future cooling gaps, generally larger in SSP3 due low income levels, and consequent limited access to AC and durable housing. Megacities in Sub-Saharan Africa and South Asia have the largest share of population affected, ranging from 33% (SSP1) to 86% (SSP3) by mid-century. Energy requirements to provide basic cooling for all are higher in SSP1 for most megacities, driven by urbanization, and can increase by 7 to 23% moving from 2.0 to 3.0 °C temperature rise levels. Strategies combining improved building design and efficient cooling systems can improve adaptation to heat stress in cities while reducing energy and emission requirements to reach climate and sustainability goals.
Development and Evaluation of Dissolving Microarray Patches for Co-administered and Repeated Intradermal Delivery of Long-acting Rilpivirine and Cabotegravir Nanosuspensions for Paediatric HIV Antiretroviral Therapy
Authors: Moffatt Kurtis , Tekko Ismaiel A. , Vora Lalitkumar , Volpe-Zanutto Fabiana , Hutton Aaron R. J. , Mistilis Jessica , Jarrahian Courtney , Akhavein Nima , Weber Andrew D. , McCarthy Helen O. , Donnelly Ryan F.
Published: October 2022

Purpose

Whilst significant progress has been made to defeat HIV infection, the efficacy of antiretroviral (ARV) therapy in the paediatric population is often hindered by poor adherence. Currently, two long-acting (LA) intramuscular injectable nanosuspensions of rilpivirine (RPV) and cabotegravir (CAB) are in clinical development for paediatric populations. However, administration requires access to healthcare resources, is painful, and can result in needle-stick injuries to the end user. To overcome these barriers, this proof-of-concept study was developed to evaluate the intradermal delivery of RPV LA and CAB LA via self-disabling dissolving microarray patches (MAPs).

Methods

Dissolving MAPs of two conformations, a conventional pyramidal and a bilayer design, were formulated, with various nanosuspensions of RPV and CAB incorporated within the respective MAP matrix. MAPs were mechanically robust and were capable of penetrating ex vivo skin with intradermal ARV deposition.

Results

In a single-dose in vivo study in rats, all ARV MAPs demonstrated sustained release profiles, with therapeutically relevant plasma concentrations of RPV and CAB detected to at least 63 and 28 d, respectively. In a multi-dose in vivo study, repeated MAP applications at 14-d intervals maintained therapeutically relevant plasma concentrations throughout the duration of the study.

Conclusions

These results illustrate the potential of the platform to repeatedly maintain plasma concentrations for RPV and CAB. As such, these MAPs could represent a viable option to improve adherence in the paediatric population, one that is capable of being painlessly administered in the comfort of the patient’s own home on a biweekly or less frequent basis.

Graphical abstract
N- or/and P-deprived Coccomyxa chodatii SAG 216–2 extracts instigated mercury tolerance of germinated wheat seedlings
Authors: Dawood Mona F. A. , Sofy Mahmoud R. , Mohamed Heba I. , Sofy Ahmed R. , Abdel-Kader Huwida A. A.
Published: October 2022

Purpose

This research studies the alleviation potential of N- or/and P- deprived Coccomyxa chodatii SAG 216–2 extracts as biostimulants on mercury stress (10 and 30 mg L−1) of wheat seedlings.

Materials

The study includes the interactive effect of mercury and biostimulants on growth, reactive nitrogen and oxygen species, membrane stability, and antioxidant activity in wheat seedlings.

Results

The imposed toxic effects of Hg-stress on the studied parameters were to a great extent less noticeable under different algal extracts, and the magnitude of augmentation was P-deprived extract > P-&N-deprived extract > N-deprived extract > Normal algal extract. Higher Hg-tolerance modulated by algal extracts, especially P-deprived extract, was associated with high antioxidant capacity and ferric reducing power. These activities could instigate the antioxidant system (enzymatic and non-enzymatic) under Hg-stress. Furthermore, the algal extracts broadly alleviated wheat chelating mechanism deterioration by Hg-stress via enhancing phytochelatins, reduced glutathione, and metallothioneins. Thus, the applied algal extracts retarded Hg accumulation in wheat tissues exposed to Hg stress. In addition, the nitrosative stress induced by Hg-stress in terms of high nitric oxide content was minimized by various algal extracts. All these regulations by algal extracts are reflected in high membrane stability as denoted by the reduction of lipid peroxidation, lipoxygenase, and methylglyoxal as a sign of reducing oxidative damage and reactive oxygen species (ROS).

Conclusion

Thus, we recommended using the macronutrient-deprived algal extracts of Coccomyxa chodatii SAG 216–2 as potential biostimulants of wheat growth under Hg-stress and may be under other stresses.
Identifying soil-plant interactions in a mixed-age orange orchard using electrical resistivity imaging
Authors: Vanella Daniela , Ramírez-Cuesta Juan Miguel , Longo-Minnolo Giuseppe , Longo Domenico , D’Emilio Alessandro , Consoli Simona
Published: October 2022

Background and aims

The ever-increasing demand of fresh water from irrigated agriculture and the water scarcity condition that characterizes the Mediterranean region, encourages the adoption of efficient water saving strategies. In this study, the electrical resistivity imaging (ERI) technique was applied for characterizing the mass exchange mechanisms affecting the continuous soil-plant system of heterogeneous micro-irrigated orchards.

Methods

Time-lapse ERI surveys were carried out in a multi-variety and mixed-age orange orchard located in Eastern Sicily (insular Italy). The time-lapse ERI monitoring was coupled with the use of independent soil water content (SWC) measurements.

Results and conclusions

A clear relationship between the soil electrical resistivity (ER) and the measured SWC changes was identified in the soil under the mixed-age orchard (with an overall coefficient of determination value of 0.63). Specifically, this study highlights the dependency of SWC dynamics as function of tree age. Overall, an increase in ER was obtained in correspondence to the soil domain where the younger trees were located ( < = 3 years). This behaviour was inferred to result from the higher soil evaporation process active at these locations, due to less vegetation cover of the younger trees and, consequently to their lesser root extension in comparison to the mature trees ( > = 8 years). On the other hand, in mature trees, characterized by denser root biomass, there were more evident decreasing patterns of ER (i.e., greater changes in SWC), due to greater transpiration rates that caused lower initial SWC under these conditions in comparison to the younger trees.
Hybrid deep transfer learning architecture for industrial fault diagnosis using Hilbert transform and DCNN–LSTM
Authors: Zabin Mahe , Choi Ho-Jin , Uddin Jia
Published: October 2022

Early-stage fault detection has become an indispensable part of modern industry to prevent potential hazards or sudden hindrances to the production process. With the advent of deep learning (DL) applications in several fields, DL models have been used to classify faults in specific environments. Uniform texture extraction has been performed using transformed-signal processing techniques and deep transfer learning (DTL) architectures in a few studies. Traditional signal processing techniques encounter difficulties in extracting distinct fault features due to the nonlinear and non-stationary nature of the time-series fault data. In this paper, a hybrid DTL architecture comprising a deep convolutional neural network and long short-term memory layers for extracting both temporal and spatial features enhanced by Hilbert transform 2D images is presented. Three standard audio sound fault datasets comprising the malfunctioning industrial machine investigation and inspection dataset, toy anomaly detection in machine operating sounds dataset, and machinery failure prevention technology bearing vibration fault dataset with various loads and noisy environments were utilized in the experimental evaluation. The proposed model with an input size of 32 × 32 achieved an average F1 score of 0.998 on the tested datasets. The implementation of transfer learning using the three benchmark datasets resulted in the highest accuracy of the proposed model and over fivefold reduction in the training epochs. In addition, the proposed model outperformed the state-of-art models in accuracy in various environments.
GoMIC: Multi-view image clustering via self-supervised contrastive heterogeneous graph co-learning
Authors: Fang Uno , Li Jianxin , Akhtar Naveed , Li Man , Jia Yan
Published: October 2022

Graph learning is being increasingly applied to image clustering to reveal intra-class and inter-class relationships in data. However, existing graph learning-based image clustering focuses on grouping images under a single view, which under-utilises the information provided by the data. To address that, we propose a self-supervised multi-view image clustering technique under contrastive heterogeneous graph learning. Our method computes a heterogeneous affinity graph for multi-view image data. It conducts Local Feature Propagation (LFP) for reasoning over the local neighbourhood of each node and executes an Influence-aware Feature Propagation (IFP) from each node to its influential node for learning the clustering intention. The proposed framework pioneeringly employs two contrastive objectives. The first targets to contrast and fuse multiple views for the overall LFP embedding, and the second maximises the mutual information between LFP and IFP representations. We conduct extensive experiments on the benchmark datasets for the problem, i.e. COIL-20, Caltech7 and CASIA-WebFace. Our evaluation shows that our method outperforms the state-of-the-art methods, including the popular techniques MVGL, MCGC and HeCo.
Trajectories in life satisfaction before and during COVID-19 with respect to perceived valence and self-efficacy
Authors: de Vries Jantje H. , Horstmann K. T. , Mussel P.
Published: October 2022

Actions taken by governments to counteract the spread of the COVID-19 pandemic led to profound restrictions in daily lives, especially for adolescents and young adults, with closed schools and universities, travel restrictions, and reduction in social contacts. The purpose of the current study is to investigate the development of life satisfaction with assessments before and during the pandemic, including separate measurement occasions during a strict lockdown and when the implemented restrictions were relaxed again. Data are based on the German Personality Panel (GePP) with 1,920 young adults, assessed on four measurement occasions over a period of three years. Using latent change score modeling, we investigate the outbreak of the COVID-19 pandemic with respect to its perception as a critical life event over time. Further, we examine the influence of self-efficacy on change in life-satisfaction, as the belief in one’s innate abilities has been shown to promote health related behavior and buffers against effects of negatively perceived critical life events. While average life satisfaction remained stable across time, we found a main effect of perceived positive valence and self-efficacy on latent change in life satisfaction at the within person level. Expressions of self-efficacy did not moderate the influence of the perception of the pandemic on self-reported life satisfaction. This study provides an important contribution to the recent COVID-19 literature as well as to the debate on stability and change of self-reported life satisfaction.
High photocatalytic capacity of porous ceramic-based powder doped with MgO
Authors: Bouras Dikra , Fellah Mamoun , Mecif Abla , Barillé Régis , Obrosov Aleksei , Rasheed Mohammed
Published: October 2022

To purify water at low cost for our daily life, the effect of ceramic-based (mullite–cristobalite) and (mullite–zircon) powders doped with different amounts of magnesium oxide (MgO) (10 and 20 wt%) was studied. These compounds are made of a local raw material DD3 with addition of zirconia (ZrO2) to create an open porosity. The powders were prepared by the traditional mixing method with the help of an automated crushing. The effect of MgO doping on structural, morphological and photocatalytic properties of the material was studied by various analytical techniques such as X-ray diffraction, scanning electron microscopy, energy dispersive X-ray spectroscopy, infrared, and UV–visible spectrometry. The results of XRD proved that there was a deformation in the crystal structure of the two types of ceramics after addition, which resulted in a shift of the spectra to the right, while SEM proved the presence of pores with a larger size as the proportion of MgO increases. The chemical composition of the basic components of the ceramic compounds as well as the additive was confirmed with EDS and IR spectra. The final results show that ceramics with added zirconia (DD3Z) and doped with 10% of MgO have a better photocatalytic efficiency than ceramics without zirconia. This important effect could be related to the higher rate of porosity, which provides a more active surface. The 10% MgO content showed a high photoactivity of 77.33% in only 15 min. The maximum hydrolysis rate obtained with Orange II was 92.95% after a period of 45 min with DD3Z/MgO powders.
Checklisten in der Medizin
Authors: Nöthiger Christoph B. , Tscholl David W.
Published: October 2022

Zusammenfassung. Dieses Mini-Review beleuchtet die Erfolgsgeschichte der Checklisten in der perioperativen Medizin. Es liefert einen Hintergrund zur Einführung von medizinischen Checklisten, zu den WHO-Leitlinien für sichere Operationen und zu den wichtigsten Checklisten-Studien. Wir skizzieren die Vorteile von Checklisten und zu beachtende Überlegungen bei ihrer Einführung und geben Beispiele für verschiedene Checklisten. Wir kommen zu dem Schluss, dass Checklisten hilfreich sind und ihr bestmöglicher Nutzen von ihrer korrekten Umsetzung abhängt.
Trigeminusneuralgie – was wissen wir über die Ursachen, Diagnostik und Therapie?
Authors: Zoller Sophia , Oertel Markus Florian , Stieglitz Lennart Henning
Published: October 2022

Zusammenfassung. Die klassische Trigeminusneuralgie äussert sich typischerweise durch blitzartig einschiessende, kurze und wiederkehrende Schmerzattacken im Innervationsbereich des Nervus trigeminus. In seiner Intensität zählt der Trigeminusschmerz zu den stärksten vorstellbaren Schmerzen, wird aber dennoch häufig fehldiagnostiziert und unzureichend behandelt. Alltägliche Aktivitäten wie Sprechen oder Essen können Trigger einer Schmerzexazerbation sein. Ursächlich bei der klassischen Form ist ein Gefäss-Nerven-Konflikt im Bereich der Nerveneintrittszone in den Hirnstamm. Bei der sekundären Trigeminusneuralgie kommt es aus anderen Gründen (beispielsweise aufgrund einer Multiplen Sklerose oder Kompression durch einen Hirntumor) zu Gesichtsschmerzen, und bei der idiopathischen Form ist die Ätiologie unbekannt. Die Behandlungsmöglichkeiten umfassen sowohl medikamentöse (meist Antiepileptika) wie auch eskalative interventionelle Therapieansätze (mikrovaskuläre Dekompression, neuroläsionale perkutane Verfahren, neuromodulative Therapieoptionen und die Radiochirurgie).
Release Timing and Duration Control the Fate of Photolytic Compounds in Stream‐Hyporheic Systems
Authors: Hixson Jase L. , Ward Adam S. , McConville Megan B. , Remucal Christina K.
Published: October 2022

Predicting environmental fate requires an understanding of the underlying, spatiotemporally variable interaction of transport and transformation processes. Photolytic compounds, for example, interact with both time‐variable photolysis and the perennially dark hyporheic zone, generating potentially unexpected dynamics that arise from time‐variable reactivity. This interaction has been found to significantly impact environmental fate but is commonly oversimplified in predictive models. Our primary objective was to explore how time‐variable photolysis and hyporheic storage interact across a range of photolysis rates to control the fate and transport of photolytic solutes in stream‐hyporheic systems. In this study, we released a photolytic compound in a natural system at different times of day and simulated variable release timing and durations of photolytic compounds spanning half‐lives ranging from about 2 min to 900 hr. To contextualize these results, we simulated five photolytic compounds with varied half‐lives to systematically study the interaction between release timing, duration, and reactivity. We found that the environmental fate and transport of photolytic compounds are highly variable as a function of release timing, which controls when, where, and for how long solute is stored in the hyporheic zone or exposed to in‐channel photolysis. This knowledge can be used to improve predictions for photolytic compounds or assess potential impacts for an anticipated discharge or treatment.
Leak Localization in Looped Pipe Networks Based on a Factorized Transient Wave Model: 2. Regularization of Ill‐Conditioned Problems
Authors: Che Tong‐Chuan , Wang Xun , Louati Moez , Zhou Ling , Ghidaoui Mohamed S.
Published: October 2022

A previous paper proposed an accurate and efficient matched‐field processing method for leak localization in looped pipe networks based on the known discharge and pressure head (i.e., hydraulic properties) at all internal nodes. However, the computation of these internal hydraulic properties from boundary measurements is an ill‐conditioned inverse problem: for a small perturbation in the boundary measurements there is a huge change in the internal hydraulic properties. We prove and clarify the invalidity of the classic Tikhonov regularization for this ill‐conditioned problem. As an alternative, this paper derives the theoretical upper bounds of noise‐induced errors, based on which a threshold is determined for identifying ill‐conditioned frequencies. The leak localization is implemented by discarding wave information at all ill‐conditioned frequencies. This results in an efficient and robust algorithm for leak localization in noisy environments. Numerical experiments demonstrate that an unknown leak anywhere in looped pipe networks can be accurately localized by the proposed algorithm.
SET/PP2A signaling regulates macrophage positioning in hypoxic tumor regions by amplifying chemotactic responses
Authors: Zhang Shaolong , Zhou Jingping , Shang Pengzhao , Zhao Guomeng , Wang Anlei , Mao Jinlei , Tao Yuhang , Chen Ziyi , Wang Xuehao , Guo Changying
Published: October 2022

Tumor-associated macrophages (TAMs) are one of the main cellular components in the tumor microenvironment (TME). In many types of solid tumors, TAMs tend to accumulate in hypoxic areas and are intimately related to poor patient prognosis. However, the underlying mechanisms by which TAMs infiltrate hypoxic tumor regions remain unclear. In this study, we report that genetic deletion of SE translocation (SET) in myeloid cells inhibited the entry of TAMs into the hypoxic tumor region and abated their proangiogenic and immunosuppressive functions, ultimately inhibiting tumor growth. Mechanistically, in response to hypoxic tumor supernatant stimulation, SET in macrophages shuttled between the nucleus and cytoplasm via the PKC-CK2α signaling axis. Cytoplasmic retention of SET increased ERK and P38 signaling by inhibiting PP2A, which promoted TAM migration into the hypoxic area and polarization toward the M2 phenotype. Therefore, we conclude that SET modulates tumor immunity by acting as a key regulator of macrophage positioning and function in the tumor.