bluuebunny/crossref_metadata_2025 huggingface dataset:
A Novel Design to Enhance the Tribological Properties of High‐Cr Hot Work Die Steel via Trace TiC Ceramic Nanoparticles
Authors: Wang Bingxu , Xu Yong , Chen Lei , Qiu Feng , Chang Fang , Dong Baixin , Cai Gaoshen , Barber Gary C.
Published: July 2024

Excellent wear properties can improve the service performance and service life of high‐Cr hot work die steels. Herein, an innovative method is proposed to introduce TiC nanoparticles into the matrix of high‐Cr hot work die steels, and the effects of TiC nanoparticles on the microstructure and wear resistance of high‐Cr hot work die steels are investigated. In isothermal spheroidizing and quenching and tempering heat treatments, the TiC nanoparticles refine the granular pearlite, tempered martensite, and precipitates, which are attributed to the improved nucleation rates by increasing the number of heterogeneous cores. In sliding wear tests, the nanoparticle‐reinforced high‐Cr hot work die steels show higher wear resistance under the temperatures of 20 and 400 °C. The better wear properties of high‐Cr hot work die steels are because the substrates are strengthened and toughened, the dislocations are hindered, the mating areas are partially separated, and external loads are withstood by nanoparticles. This work shows new prospects for the development of high‐Cr hot work die steels with excellent wear performance.
Loss Minimization Model Predictive Current Control for Linear Induction Motors
Authors: Ma Shuhang , Zhao Jinghong , Yang Lv , Ma Yuanzheng , Wang Hanming
Published: July 2024

To further improve the operating efficiency of linear induction motor, this paper proposes a loss minimization model predictive current control method based on governable loss online calculation. First, the method derives the equivalent circuit of linear induction motor containing independent iron loss branches, and establishes the loss model containing iron loss. Second, the expressions of stator d‐axis current with governable losses and secondary flux amplitude are derived from theoretical analysis, and then a given value of stator d‐axis current is derived when the governable losses are minimal. Then, a chain observer is designed to observe the secondary flux and calculate the governable loss and stator d‐axis current under the current operation. Finally, a method is proposed to introduce the stator d‐axis current observation results into the model predictive current control, which ensures the loss suppression effect and improves the dynamic performance at the same time. In addition, this article also compares the loss minimization controllers with or without iron loss. The simulation results are consistent with the theory, and the optimal control of the secondary flux of the linear induction motor can be successfully realized, thus effectively reducing the energy loss of the motor in the dynamic operation process. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.
Transition to the Circular Economy: Innovative and Disruptive Production Technologies Adopted by Agribusiness Startups
Authors: Manganda Alexandre Sérgio , Sehnem Simone , Lara Ana Cláudia
Published: July 2024

This study aimed to analyze the impact of innovative and disruptive production technologies adopted by Brazilian agribusiness startups on the value chain, contributing to the transition to the circular economy. Qualitative research was carried out through 10 semi‐structured interviews with CEOs of startups in the agribusiness segment, also called agtechs. The results indicate that various disruptive innovative technologies are in use, such as precision agriculture, artificial intelligence, and biotechnology. The adoption of innovative technologies, especially those that have disruptive potential, contributes to the transition to a circular economy. These innovations enhance efficiency, productivity, resource waste reduction, greenhouse gas emission reduction, monitoring, and control. At the same time, they have the potential to contribute to the generation of food security, the minimization of environmental impact, and the promotion of sustainability in agribusiness, making it more resilient. It is concluded that disruptive technologies, especially those originating from Industry 4.0, have the potential to transform the agribusiness industry. They support sustainable and efficient practices and have the potential to replace the lack of human labor in the field. Furthermore, the study expands the theoretical understanding of the role of agtechs in the circular economy and provides practical insights into the formulation of public policies, investments, and business strategies to promote sustainability in the agricultural sector.
Quantitative and qualitative management of water resources with the use of treated wastewater in agriculture
Authors: Abbasmiri Seyedeh Samaneh , Mortazavi Seyed Abolghasem , Alamdarlo Hamed N. , Vakilpoor Mohammad Hassan
Published: July 2024

The principled utilization of treated wastewater can reduce the pollution load on the environment. Because on the one hand, treated wastewater can be a suitable fertilizer substitute, and on the other hand, using treated wastewater in irrigation prevents the discharge of polluted surface water into water sources. In the south of Tehran province, polluted surface water is used for irrigation in the agricultural sector, and this has led to environmental problems. To solve this problem, it has been decided to implement a plan to build surface water treatment plants and an irrigation and drainage network to transfer treated wastewater to farms. Therefore, the present study aimed to investigate the economic and environmental effects of this project in the region. A hydro‐economic model has been used to achieve this goal. According to the results, in the case of the application of environmental constraints in the optimization model, the cultivation area and the farmers' profit will be reduced by about 5% and 36%, respectively, compared with the noncompliance of environmental constraints. However, this decline in profit can be compensated by adopting solutions such as improving the irrigation system, the application of treated wastewater, or using the fertilizer potential of water sources in the agricultural sector.

Practitioner Points

In the optimal economic‐environmental situation, farmers' profit is reduced compared with the optimal economic situation.

In the case of implementing the treated wastewater application, the farmers' profit will increase despite environmental constraints.

In the optimal economic‐environmental situation, fewer lands are cultivated with diverse crops than in optimal economic conditions.
Mass Equidistribution for Saito-Kurokawa Lifts
Authors: Jääsaari Jesse , Lester Stephen , Saha Abhishek
Published: July 2024

Let F be a holomorphic cuspidal Hecke eigenform for $\mathrm{Sp}_{4}({\mathbb{Z}})$ of weight k that is a Saito–Kurokawa lift. Assuming the Generalized Riemann Hypothesis (GRH), we prove that the mass of F equidistributes on the Siegel modular variety as k⟶∞. As a corollary, we show under GRH that the zero divisors of Saito–Kurokawa lifts equidistribute as their weights tend to infinity.
Integrating data-driven system to predict temperature and distortion in multi-layer direct metal deposition processes
Authors: Shafaie Majid , Sarparast Mohsen , Zhang Hongyan
Published: July 2024

This study proposed a framework to train an artificial neural network (ANN) by a data-driven system to predict the temperature and distortion in multi-layer direct metal deposition (DMD) of SS 304. By integrating thermomechanical variables, the research ensures the fidelity of finite element (FE) simulations, which are validated against existing data. Notably, the study achieves enhanced precision over prior work by varying the heat input sources and heat transfer equations. A novel aspect of this research is the use verified FE simulation to add data to data-driven system to train an efficient ANN for predicting temperature and distortion based on key parameters such as laser power and scanning speed. The iterative process involved multiple FE simulations with varying laser parameters to refine the ANN’s predictive capabilities. This methodology enabled the identification of relationships between manufacturing parameters, temperature, and distortion. The iterative training continued until the ANN’s predictions and subsequent FE simulation results converged within an acceptable margin. The findings confirm that the trained ANN can predict temperature and distortion both accurately and expediently, marking a significant advancement in the control of the DMD process.

Graphical Abstract
Purity and 2-Calabi–Yau categories
Authors: Davison Ben
Published: July 2024

For various 2-Calabi–Yau categories $\mathscr{C}$
C
for which the classical stack of objects $\mathfrak{M}$
M
has a good moduli space $p\colon \mathfrak{M}\rightarrow \mathcal{M}$
p
:
M
→
M
, we establish purity of the mixed Hodge module complex $p_{!}\underline{{\mathbb{Q}}}_{{\mathfrak {M}}}$

p
!

Q
_

M

. We do this by using formality in 2CY categories, along with étale neighbourhood theorems for stacks, to prove that the morphism $p$
p
is modelled étale-locally by the semisimplification morphism from the stack of modules of a preprojective algebra. Via the integrality theorem in cohomological Donaldson–Thomas theory we then prove purity of $p_{!}\underline{{\mathbb{Q}}}_{{\mathfrak {M}}}$

p
!

Q
_

M

. It follows that the Beilinson–Bernstein–Deligne–Gabber decomposition theorem for the constant sheaf holds for the morphism $p$
p
, despite the possibly singular and stacky nature of ${\mathfrak {M}}$
M
, and the fact that $p$
p
is not proper. We use this to define cuspidal cohomology for ${\mathfrak {M}}$
M
, which conjecturally provides a complete space of generators for the BPS algebra associated to $\mathscr{C}$
C
. We prove purity of the Borel–Moore homology of the moduli stack $\mathfrak{M}$
M
, provided its good moduli space ℳ is projective, or admits a suitable contracting ${\mathbb{C}}^{*}$

C
∗

-action. In particular, when $\mathfrak{M}$
M
is the moduli stack of Gieseker semistable sheaves on a K3 surface, this proves a conjecture of Halpern-Leistner. We use these results to moreover prove purity for several stacks of coherent sheaves that do not admit a good moduli space. Without the usual assumption that $r$
r
and $d$
d
are coprime, we prove that the Borel–Moore homology of the stack of semistable degree $d$
d
rank $r$
r
Higgs sheaves is pure and carries a perverse filtration with respect to the Hitchin base, generalising the usual perverse filtration for the Hitchin system to the case of singular stacks of Higgs sheaves.
Aftermath of Ag embedding on structural, optical, and supercapacitor electrode attributes of USP-grown CuO thin films
Authors: Güney Harun , İskenderoğlu Demet , Güldüren Muhammed Emin , Demir Kübra Çinar , Karadeniz Sibel Morkoç
Published: July 2024

Here, ultrasonic spray pyrolysis method (USP) was utilized to produce pure and silver doped copper oxide nanostructures on glass substrates. Thereafter, several characterization techniques were conducted on the grown samples to delve into their morphological, structural, electrochemical, and optical aspects. The mentioned analyses were carried out by performing x-ray photoelectron spectroscopy, scanning electron microscope, X-ray diffraction, electrochemical impedance spectroscopy, galvostatic charge-discharge, cyclic voltammetry, and UV–visible spectroscopy measurements. Thus, the impact of silver impurity doping on the relevant aspects of host material were recorded as well as the features of unspoiled copper oxide films. Accordingly, the samples, as indicated by X-ray diffraction results, possessed (002) preferential plane orientation of copper oxide material along with the crystallite sizes ranging from 52.52 nm to 75.02 nm due to the imperfections caused by the silver doping. The scanning electron microscope images exhibited that the silver doping did not form significant modifications in the host material morphology where nanowire-like structures observed. The presence of the suggested materials in the films was verified by the x-ray photoelectron spectroscopy. Also, the UV–visible spectroscopy measurements detected that optical absorbance edge and bandgap energy values red shifted as a result of the impurity doping. The electrochemical supercapacitors performances of the silver doped copper oxide nanostructured thin films were inspected by using the GCD, EIS, and CV. The silver doped copper oxide films demonstrated a specific capacitance value of 66 F/g at a current density of 1 A/g in 1 M KOH electrolyte. From Nyquist plot, Rs, Rcor, Rpo, Ccor and Cc were obtained as 2.327 × 103 Ω.cm2, 43.63 × 103 Ω.cm2, 4.580 × 103 Ω.cm2, 111.5 × 10-6 S*s^a. cm-2 and 101.1 × 10-6 S*s^a. cm-2, respectively. The results indicated that the electrochemically synthesized the silver doped copper oxide electrodes can be obtained and developed as an alternative electrode material for supercapacitors (SCs).
Collaborative intrusion detection using weighted ensemble averaging deep neural network for coordinated attack detection in heterogeneous network
Authors: Wardana Aulia Arif , Kołaczek Grzegorz , Warzyński Arkadiusz , Sukarno Parman
Published: July 2024

Detecting coordinated attacks in cybersecurity is challenging due to their sophisticated and distributed nature, making traditional Intrusion Detection Systems often ineffective, especially in heterogeneous networks with diverse devices and systems. This research introduces a novel Collaborative Intrusion Detection System (CIDS) using a Weighted Ensemble Averaging Deep Neural Network (WEA-DNN) designed to detect such attacks. The WEA-DNN combines deep learning techniques and ensemble methods to enhance detection capabilities by integrating multiple Deep Neural Network (DNN) models, each trained on different data subsets with varying architectures. Differential Evolution optimizes the model’s contributions by calculating optimal weights, allowing the system to collaboratively analyze network traffic data from diverse sources. Extensive experiments on real-world datasets like CICIDS2017, CSE-CICIDS2018, CICToNIoT, and CICBotIoT show that the CIDS framework achieves an average accuracy of 93.8%, precision of 78.6%, recall of 60.4%, and an F1-score of 62.4%, surpassing traditional ensemble models and matching the performance of local DNN models. This demonstrates the practical benefits of WEA-DNN in improving detection capabilities in real-world heterogeneous network environments, offering superior adaptability and robustness in handling complex attack patterns.
Improved quantitative parameter estimation for prostate T2 relaxometry using convolutional neural networks
Authors: Bolan Patrick J. , Saunders Sara L. , Kay Kendrick , Gross Mitchell , Akcakaya Mehmet , Metzger Gregory J.
Published: July 2024

Objective

Quantitative parameter mapping conventionally relies on curve fitting techniques to estimate parameters from magnetic resonance image series. This study compares conventional curve fitting techniques to methods using neural networks (NN) for measuring T2 in the prostate.

Materials and methods

Large physics-based synthetic datasets simulating T2 mapping acquisitions were generated for training NNs and for quantitative performance comparisons. Four combinations of different NN architectures and training corpora were implemented and compared with four different curve fitting strategies. All methods were compared quantitatively using synthetic data with known ground truth, and further compared on in vivo test data, with and without noise augmentation, to evaluate feasibility and noise robustness.

Results

In the evaluation on synthetic data, a convolutional neural network (CNN), trained in a supervised fashion using synthetic data generated from naturalistic images, showed the highest overall accuracy and precision amongst the methods. On in vivo data, this best performing method produced low-noise T2 maps and showed the least deterioration with increasing input noise levels.

Discussion

This study showed that a CNN, trained with synthetic data in a supervised manner, may provide superior T2 estimation performance compared to conventional curve fitting, especially in low signal-to-noise regions.
Genotype and Year Effects on Some Production Characteristics in Three Blueberry Cultivars (Vaccinium corymbosum L.)
Authors: Cosmulescu Sina , Merca Laies Maria Marina , Sărățeanu Veronica
Published: July 2024

The current trend of expanding blueberry plantations requires studies on the production capacity of blueberry cultivars in different cultivation areas. The paper’s aim was to follow the effect of genotype and environment on some production characteristics of three blueberry cultivars (‘Duke’, ‘Hannah’s Choice’ and ‘Elliott’) grown in the Banat region of Romania. The average fruit weight, production per bush and production per hectare were calculated. The analysis of obtained data highlighted a variability from one cultivar to another, and within the cultivar from one year to another. The simulated models have highlighted the highly significant influence of considered factors combined (cultivar*year) on production features. ‘Duke’ and ‘Elliott’ cultivars have the best results in the study area, that is, ‘Duke’ cultivar can provide blueberries for market early (from June) and ‘Elliott’ cultivar provides blueberries during the summer–autumn time interval. The outputs are very useful, bearing in mind the low amount of available information from the literature.
Rechtfertigen hohe Behandlungskosten die Euthanasie des Heimtieres oder das grundsätzlich strafbare Unterlassen einer veterinärmedizinisch gebotenen Behandlung? – Über den schmalen Grat zwischen Tierhalterinteressen und Strafbarkeit
Authors: Poplat Tim
Published: July 2024

Erkrankt das Heimtier, fragt der Tierarzt typischerweise vor einer veterinärmedizinisch gebotenen
Behandlung, ob sich der Tierhalter die anfallenden Kosten leisten kann. Das suggeriert einen viel weiteren
Handlungs- und Entscheidungsspielraum des Tierhalters, als ihn §17 TierSchG gewährt. Angesichts
der bisher allenfalls rudimentären Befassung des Schrifttums mit diesem Thema, fehlt es an hinreichender
Klarheit, ob und inwiefern hohe Behandlungskosten für die Euthanasie oder das strafbare Unterlassen
einer solchen Behandlung als Ausschluss- oder Rechtfertigungsgrund angeführt werden können. Ein
Blick auf §266a StGB zeigt indes, dass die Zahlungsunfähigkeit der Rechtsordnung als Ausschlussmöglichkeit
keinesfalls fremd ist. Zugleich verdeutlicht er, dass nur in seltenen Ausnahmefällen die Kostenhöhe
den tierlichen Interessen erfolgreich entgegengehalten werden kann.
An Effective Teaching Pedagogy Involving an Online Learning Platform under a Multi-Campus Teaching Model
Authors: Poon Pak-Lok , Tang Sau-Fun
Published: July 2024

Nowadays, many universities around the globe have offered distance learning to their students in addition to the traditional face-to-face learning mode. Furthermore, a number of universities have multiple campuses, thereby requiring these universities to adopt a multi-campus learning model. This setting creates numerous teaching and learning challenges. This paper aims to: (a) explore what major teaching and learning challenges are faced by Central Queensland University (CQU) due to its multiple campuses and a diverse student cohort involving both on-campus and off-campus students, and (b) discuss our teaching pedagogy (including the use of an online learning platform) for an information systems analysis and design (ISAD) unit at CQU with a view to alleviating these teaching/learning challenges. We analyzed qualitatively and quantitatively the effectiveness of our teaching pedagogy in addressing the teaching/learning challenges. We performed a two-sample t-test involving a total of 216 ISAD students and found that, by adopting our teaching pedagogy, there was no significant difference in academic performance between urban (mostly on-campus) and regional (mostly off-campus) students. Also, our teaching pedagogy reduced the dropout percentages of both urban and regional students, particularly the regional students.
Extrapolation is not the same as interpolation
Authors: Wang Yuxuan , King Ross D.
Published: July 2024

We propose a new machine learning formulation designed specifically for extrapolation. The textbook way to apply machine learning to drug design is to learn a univariate function that when a drug (structure) is input, the function outputs a real number (the activity): f(drug) $$\rightarrow$$
→
activity. However, experience in real-world drug design suggests that this formulation of the drug design problem is not quite correct. Specifically, what one is really interested in is extrapolation: predicting the activity of new drugs with higher activity than any existing ones. Our new formulation for extrapolation is based on learning a bivariate function that predicts the difference in activities of two drugs F(drug1, drug2) $$\rightarrow$$
→
difference in activity, followed by the use of ranking algorithms. This formulation is general and agnostic, suitable for finding samples with target values beyond the target value range of the training set. We applied the formulation to work with support vector machines , random forests , and Gradient Boosting Machines . We compared the formulation with standard regression on thousands of drug design datasets, gene expression datasets and material property datasets. The test set extrapolation metric was the identification of examples with greater values than the training set, and top-performing examples (within the top 10% of the whole dataset). On this metric our pairwise formulation vastly outperformed standard regression. Its proposed variations also showed a consistent outperformance. Its application in the stock selection problem further confirmed the advantage of this pairwise formulation.
Noise propagation in linear stationary iterations
Authors: Elfving Tommy
Published: July 2024

We consider a stationary iteration for solving a linear system of arbitrary order. The method includes, e.g. Kaczmarz iteration, the Landweber iteration and the SOR (Gauss-Seidel) iteration. A study of the behavior of the iterates, both theoretically and experimentally, is performed. In particular we compare the behavior with and without noise in the data. The results give insight into the interplay between noise free and noisy iterates. For comparision we also included a Krylov type method CGLS in the experiments. As expected CGLS works well for noise free data but also tends to amplify the noise faster than the other methods, thus making it more critical when to stop the iterations.
Selection of outcome measurement instruments for a core outcome set for trials aimed at improving appropriate polypharmacy in older people in primary care: a Delphi consensus study
Authors: Alqahtani Mubarak N. , Barry Heather E. , Hughes Carmel M.
Published: July 2024

Background

Despite developing a polypharmacy core outcome set (COS) in primary care, it is not clear how these outcomes should be measured.

Aim

To select outcome measurement instruments (OMIs) for a COS targeting appropriate polypharmacy in older patients in primary care.

Method

Following the Consensus-based Standards for the selection of health Measurement Instruments (COSMIN) guideline, OMIs were identified from a Cochrane review focusing on appropriate polypharmacy. The quality of OMIs was assessed using a published checklist. Subsequently, two rounds of Delphi questionnaires were conducted via the SoGoSurvey® platform, engaging stakeholders (researchers, clinicians and journal editors specialising in geriatric primary care) to achieve consensus on OMIs using a scale encompassing “agree”, “disagree”, or “unsure”. Consensus was achieved if 70% or more participants chose “agree” and 15% or fewer chose “disagree.”

Results

The quality of 20 OMIs identified from the Cochrane review was evaluated. Seven OMIs were selected based on meeting the COSMIN guideline’s minimum requirements. Out of 188 potential participants, 57 (30.3%) consented to participate. Rounds 1 and 2 of Delphi exercises were completed by 50 respondents, achieving agreement on three OMIs: ‘number of serious adverse drug reactions (ADRs)’ (98%), ‘number of deaths’ (76%), and ‘number of patients who fell’ (70%) for measuring ‘serious ADRs,’ ‘mortality,’ and ‘falls,’ respectively. No agreement was reached for ‘medication appropriateness,’ ‘medication side-effects,’ ‘quality of life,’ and ‘medication regimen complexity.’

Conclusion

OMIs were selected for a limited number of outcomes in the polypharmacy COS. Future research should identify suitable OMIs for the remaining four outcomes.
A comprehensive survey of federated transfer learning: challenges, methods and applications
Authors: Guo Wei , Zhuang Fuzhen , Zhang Xiao , Tong Yiqi , Dong Jin
Published: July 2024

Federated learning (FL) is a novel distributed machine learning paradigm that enables participants to collaboratively train a centralized model with privacy preservation by eliminating the requirement of data sharing. In practice, FL often involves multiple participants and requires the third party to aggregate global information to guide the update of the target participant. Therefore, many FL methods do not work well due to the training and test data of each participant may not be sampled from the same feature space and the same underlying distribution. Meanwhile, the differences in their local devices (system heterogeneity), the continuous influx of online data (incremental data), and labeled data scarcity may further influence the performance of these methods. To solve this problem, federated transfer learning (FTL), which integrates transfer learning (TL) into FL, has attracted the attention of numerous researchers. However, since FL enables a continuous share of knowledge among participants with each communication round while not allowing local data to be accessed by other participants, FTL faces many unique challenges that are not present in TL. In this survey, we focus on categorizing and reviewing the current progress on federated transfer learning, and outlining corresponding solutions and applications. Furthermore, the common setting of FTL scenarios, available datasets, and significant related research are summarized in this survey.
Bewertung von Instrumenten zur Diagnosefindung des Restless-Legs-Syndroms im Kindes- und Jugendalter
Authors: Mollin Julian , Klug Lisa , Joost Theresa , Beyer Uta , Mayer Frank , Erler Thomas
Published: July 2024

Hintergrund

Das Restless-Legs-Syndrom (RLS) ist eine schlafbezogene Bewegungsstörung mit Beinbewegungen, die durch Missempfindungen verursacht werden. Die Symptome treten vorwiegend abends oder nachts auf und bessern sich durch Bewegung. Im Kindes- und Jugendalter wird das RLS meist spät diagnostiziert, weshalb es häufig zu einer verzögerten Behandlung und einem erschwerten Zugang zu spezialisierter Versorgung kommt. Die Diagnose wird mit Hilfe der Internationalen Restless-Legs-Syndrom-Study-Group(IRLSSG)-Kriterien, unter Berücksichtigung einer alters- und entwicklungsabhängigen Symptombeschreibung, gestellt.

Ziel der Arbeit

Bewertung von Instrumenten zur Diagnostik des RLS im Kindes- und Jugendalter.

Methodik

In einer dreiphasigen Studie wurden zur Diagnostik des RLS ein Fragebogen, ein halbstandardisiertes Interview und eine Polysomnographie (PSG) durchgeführt.

Ergebnisse

Für 1076 Proband/innen wurde anhand des Fragebogens ein individueller RLS-Index-Score (−1,9 ± 9,5 Punkte) zur Vorhersage eines möglichen RLS berechnet. Bei 188 auffälligen Proband/innen (RLS-Index-Score 8,0 ± 7,0 Punkte) erfolgte ein halbstandardisiertes Interview zur detaillierten Anamneseerhebung. Die Diagnose eines „wahrscheinlichen“ oder „unklaren“ RLS erhielten 60 Probanden. Bei 15 Proband/innen (RLS-Index-Score 13,3 ± 2,7 Punkte) erfolgte eine zweinächtige PSG. Fünf Proband/innen zeigten einen auffälligen PLMS-Index (periodische Beinbewegungen im Schlaf). Aus den Studiendaten, klinischer Erfahrung und der Literatur wurde ein Algorithmus erarbeitet.

Diskussion

Zur Diagnosestellung des RLS im Kindes- und Jugendalter bedarf es einer strukturierten Diagnostik. Der vorgestellte Algorithmus gibt ein aufbauendes Vorgehen vor, welches eine einheitliche Diagnosestellung und Therapieentscheidung ermöglicht.
What Western Philosophers of Technology Might Learn from Li Bocong’s Philosophy of Engineering
Authors: Wang Nan , Mitcham Carl
Published: July 2024

This essay aims to rectify a failure on the part of Western philosophers of technology to attend to the creative philosophical work of Li Bocong at the University of Chinese Academy of Sciences in Beijing. After a brief account of Li Bocong’s personal contacts with the West and some remarks on his relationship to Marxism, we take up three aspects of his philosophy that can contribute to enlarging Western philosophical thinking about engineering and technology: (1) Li’s analysis of engineering as more than design, (2) his argument for the relevance of the sociology of engineering, and (3) his conceptualization of engineering ethics as more than professional ethics.
Impact and Assessment of Research Integrity Teaching: A Systematic Literature Review
Authors: Crean Daniel , Gordijn Bert , Kearns Alan J.
Published: July 2024

Presented here is a systematic literature review of what the academic literature asserts about: (1) the stages of the ethical decision-making process (i.e. awareness, reasoning, motivation, and action) that are claimed to be improved or not improved by RI teaching and whether these claims are supported by evidence; (2) the measurements used to determine the effectiveness of RI teaching; and (3) the stage/s of the ethical decision-making process that are difficult to assess. Regarding (1), awareness was the stage most claimed to be amenable to improvement following RI teaching, and with motivation being the stage that is rarely addressed in the academic literature. While few, some sources claimed RI teaching cannot improve specific stages. With behaviour (action) being the stage referenced most, albeit in only 9% of the total sources, for not being amenable to improvement following RI teaching. Finally, most claims were supported by empirical evidence. Regarding (2), measures most frequently used are custom in-house surveys and some validated measures. Additionally, there is much debate in the literature regarding the adequacy of current assessment measures in RI teaching, and even their absence. Such debate warrants caution when we are considering the empirical evidence supplied to support that RI teaching does or does not improve a specific stage of the decision-making process. Regarding (3), only behaviour was discussed as being difficult to assess, if not impossible. In our discussion section we contextualise these results, and following this we derive some recommendations for relevant stakeholders in RI teaching.
An algebraic approach to the Fundamental Theorem of Algebra
Authors: Mandal Priyabrata , Sheikh Sajad A.
Published: July 2024

In this paper, we investigate the algebraic counterpart of the Fundamental Theorem of Algebra. We explore the concept of real-closed fields and quadratic forms. We show, by means of Galois theory, that $$\mathcal {F}(\sqrt{-1})$$

F
(

-
1

)

is algebraically closed if $$\mathcal {F}$$
F
is real-closed. Lastly, we explain the algebraic closure of $$\mathbb {R}(\sqrt{-1})=\mathbb {C}$$

R
(

-
1

)
=
C

by demonstrating the real-closeness of $$\mathbb {R}$$
R
.
Recovery of the Seagrass Zostera noltei and Commercial Bivalve Populations After Shellfish Harvesting
Authors: Román Marta , Vázquez Elsa , Simón Andrés , Román Salvador , Olabarria Celia
Published: July 2024

Conservation efforts have raised awareness about the impact of small-scale fisheries on the distribution of seagrass plants. The patterns of recovery of the seagrass Zostera noltei and of the commercial bivalves Cerastoderma edule, Ruditapes decussatus and Ruditapes philippinarum after shellfish harvesting were studied in a field experiment in a shellfish bed in NW Spain. Sample plots were subjected to a single disturbance in two types of shellfish harvesting treatments in three zones characterized by different harvesting frequency and seagrass density. The photosynthetic efficiency (Fv/Fm), shoot density, leaf length and carbohydrate content of Z. noltei were monitored every three months during one year, and the C and N content of leaves and biomass of plants were measured one year after the disturbance. The abundance of adults, juveniles and recruits and the condition index of adult bivalves were quantified after the experimental harvesting. Shoot density and biomass of Z. noltei remained low during the ten months after the disturbance but recovered to control values after one year. Carbohydrate contents of apical rhizomes were lower in disturbed (treated) plots, whereas no effect was observed on Fv/Fm. Denser and more complex seagrass patches recovered faster. The abundance of adult bivalves below commercial size was lower in the disturbed plots, while the abundance of adults of commercial size, juveniles and recruits did not vary, indicating that abundance and condition were not hampered by harvesting pressure. The findings also suggest that Z. noltei meadows can recover within one year of the impact of shellfish harvesting if the harvesting areas are rotated and dense patches are preserved.
Condensed-gradient boosting
Authors: Emami Seyedsaman , Martínez-Muñoz Gonzalo
Published: July 2024

This paper presents a computationally efficient variant of Gradient Boosting (GB) for multi-class classification and multi-output regression tasks. Standard GB uses a 1-vs-all strategy for classification tasks with more than two classes. This strategy entails that one tree per class and iteration has to be trained. In this work, we propose the use of multi-output regressors as base models to handle the multi-class problem as a single task. In addition, the proposed modification allows the model to learn multi-output regression problems. An extensive comparison with other multi-output based Gradient Boosting methods is carried out in terms of generalization and computational efficiency. The proposed method showed the best trade-off between generalization ability and training and prediction speeds. Furthermore, an analysis of space and time complexity was undertaken.
Fostering Computation Competence with Non-Counting Strategies and Conceptual Subitizing in Grade 1: An Intervention Study in Inclusive Classrooms
Authors: Leuenberger Delia , Diener Marion , Wehren-Müller Maria , Hofmann-Villiger Andreas , Vogt Franziska , Moser Opitz Elisabeth
Published: July 2024

Computation competence (CC) with non-counting (NC) strategies is an important aim of Grade 1 mathematics education, but studies have shown that many students struggle to acquire these skills and continue to rely on counting strategies in later years. Therefore, even though counting is an important first strategy for young children, it is vital to support the development of CC with NC strategies from the earliest stages of mathematics education. This study examined the success of an intervention to promote the use of CC and NC strategies and conceptual subitizing (CS). The study was conducted with a sample of N = 1017 Grade 1 students, and investigated whether the achievement gain was affected by the intervention setting: cooperative learning, individual support for low achievers, a combination of the two settings, and a control group. Students in the combined setting had greater achievement gains in CC with NC strategy use and CS than the control group and outperformed those in the other intervention groups in CS. The combined setting also benefitted low achievers in mathematics for CS, but not for CC and strategy use. A combination of cooperative learning and individual support seems to be the best option for improving the CS and CC and NC strategy use of first graders, especially low achievers in mathematics.
Enhanced performance of amine and thiol chemically modified graphene oxide for effective removal of Hg(II), Pb(II), and Cr(VI) from aqueous solution
Authors: Bakry Ayyob M. , Alamier Waleed M. , Abdallah A. B. , El-Reash Yasmeen G. Abou , El-Shall M. Samy , Awad Fathi S.
Published: July 2024

This study describes a novel adsorbent with a multidentate ligand that was facilely fabricated by covalently bonding 4-amino-3-hydrazino-5-mercapto-1,2,4-triazole on graphene oxide (AHMT-PRGO). The AHMT-PRGO nano-adsorbent was used for the effective removal of Hg(II), Pb(II), and Cr(VI) from wastewater. The AHMT-PRGO nano-adsorbent was synthesized by a nucleophilic substitution reaction between GO acyl chloride and AHMT chelating ligand in the presence of tetrabutyl-ammonium bromide as a catalyst. The successful modifications were confirmed via several spectroscopic and electron microscopy instrumentations including UV–Vis, FTIR, Raman, XRD, XPS, SEM, and TEM. The maximum adsorption capacities of Hg(II), Cr(VI), and Pb(II) on the AHMT-PRGO nano-adsorbent were 370.0, 136.2, and 109.6 mg/g, respectively, exceeding those of most previously reported adsorbents. Additionally, the equilibrium contact times for Hg(II), Pb(II), and Cr(VI) were 60, 30, and 400 min, respectively. In a mixture of nine heavy metal ions containing 250 ppm of each ion, the AHMT-PRGO nano-adsorbent exhibited high selectivity for Hg(II) ions. Furthermore, the AHMT-PRGO nano-adsorbent showed high stability over five adsorption–desorption cycles. Additionally, the AHMT-PRGO nano-adsorbent was successfully applied to remove heavy metal ions from real water samples. The novelty of AHMT-PRGO lies in the combination of a multidentate ligand for strong and selective binding with the high surface area and stability offered by covalently bonded graphene oxide. This combination offers potential advantages over traditional adsorbents in terms of adsorption capacity, selectivity, and reusability.
A 90-meter Split Hopkinson Tension–Torsion Bar: Design, Construction and First Tests
Authors: Sasso M. , Mancini E. , Chiappini G. , Utzeri M. , Amodio D.
Published: July 2024

This article describes the design, construction, and first experimental results of a 90 m-long Hopkinson bar which can perform high strain rate tests in a combined tension–torsion state. The system configuration is analogous to the classic Hopkinson bar technique, consisting of three bars: a pre-stressed bar, an input bar, and an output bar; the sample is placed between the input and output bar. The measurement is also based on the classical three-wave method, where the incident, transmitted and reflected waves are measured. Incident compression and torsional waves are simultaneously generated by the failure of a fragile element that connects the pre-stressed bar to electromechanical actuators; the indirect Hopkinson tension bar technique is exploited, where the compression wave reaches the end of the output bar without stressing the sample and is reflected as a tensile input wave. The length of the bars is designed so that the tensile wave reaches the sample from the output bar side at the same time as the torsion wave comes from the input bar. Void tests were carried out first, for preliminary analysis of the system behaviour. Then, successful tests have been conducted on samples made of AA7075 T6, both in combined and pure tension–torsion states; it has been possible to measure the tension–torsion stress–strain curves, from which the equivalent flow stress–strain curve has been evaluated and compared to the quasi-static ones.
Regional Climate Change and Drought Dynamics in Tunceli, Turkey: Insights from Drought Indices
Authors: Korkmaz Meral , Kuriqi Alban
Published: July 2024

Global warming and climate change are causing temperatures to rise, which is having a negative impact on water resources. Climate change is a worldwide problem that affects and will continue to affect the frequency and intensity of natural disasters in many regions of the world. Tunceli region in Turkey, which until 10 years ago was known as an environmentally friendly city with abundant water resources and frequent rainfall, is experiencing a decrease in precipitation during the snowy winter season. This situation has made the investigation of climate change impacts an important issue in the region. Therefore, effective climate change adaptation strategies need to be developed. To determine these strategies, in this study, we assessed long-term drought conditions using multiple drought indices such as Standardized Precipitation Index (SPI), Reconnaissance Drought Index (RDI), Normal Precipitation Index (PNI), and Aridity Index (AI). The SPI and RDI analyses were performed in annual reference periods on a time scale of 3, 6, 9, and 12 months using temperature, precipitation, and evaporation data. Consequently, the SPI and RDI results were compared, and both indices show similar behavior in dry, wet, and normal seasons. Nevertheless, RDI shows less variation between different time scales, which is an advantage over SPI and is probably due to the inclusion of potential evapotranspiration in RDI. The variations in PNI between humid and dry sub-humid categorizations throughout the years, combined with the AI results, indicate that the Tunceli region predominantly experiences a climate ranging from dry sub-humid to semi-arid. This study could help decision-makers take effective measures to become more resilient to climate change in temperate climate regions and take important steps toward sustainable water resources management.
Holistic Approaches in Endometriosis - as an Effective Method of Supporting Traditional Treatment: A Systematic Search and Narrative Review
Authors: Mazur-Bialy Agnieszka , Tim Sabina , Pępek Anna , Skotniczna Kamila , Naprawa Gabriela
Published: July 2024

Endometriosis is one of the gynecological diseases where women suffer from pain, quality of life decreased. The aim of this review was to describe the most common non-medical methods used in the treatment of symptoms associated with endometriosis and to determine their effectiveness. The review was performed in PubMed, Embase and Web of Science databases. Randomized controlled trials, case studies, observational studies, retrospective studies, prospective studies, pilot studies, trails, publications in English or Polish were searched based on the Participant-Intervention-Comparator-Outcomes-Study design (PICOS) format. The criteria used to select studies were: women with endometriosis, no cancer, included any physiotherapeutic or non-medical intervention. 3706 articles were found, however only 26 met the inclusion criteria and were included in the review. Quality of the studies was assessed by Risk of Bias 2 tool and ROBINS-1 tool. The most holistic approach used in the treatment of symptoms of endometriosis include physical therapy, manual therapy, electrophysical agents acupuncture, diet and psychological interventions. Most research has focused on relieving pain and increasing quality of life. Non-medical methods showed reduction of symptoms of endometriosis. Physical activity, manual therapy, electrophysical agents, acupuncture, diet and cognitive behavioral therapy showed no negative side effects and reduced pain, what improved the quality of life and reduced the perceived stress.
Examining potential health gains arising from reduced risk consumption in South Africa via the PRIME model
Authors: Koch Steven F.
Published: July 2024

Objectives

Non-communicable diseases (NCDs) account for over 30% of disability-adjusted life years in South Africa. In this research, we offer an estimate of the potential reduction in NCD incidence that would arise from an improvement in diet, combined with a reduction in both tobacco and alcohol consumption.

Methods

We apply the PRIME model, which simulates the effect of risk reduction on NCD incidence. The model inputs baseline data related to the population, risky consumption behaviour and NCD incidence. The model allows for counterfactual scenarios altering the risky consumption behaviour to yield revised NCD incidence.

Results

We find that reducing salt, tobacco and alcohol, along with improved fruit, vegetable and fiber consumption would yield a 10% reduction in NCDs from the 2018 baseline. NCD incidence reductions arise primarily from ischemic heart disease (49%), cerebrovascular diseases (33%) and bronchus and lung disease (11%).

Conclusion

South Africa’s NCD incidence is high because of relatively poor behavioural choices, despite plans and policies aimed at changing this. South Africa should increase their efforts to reach NCD goals. If the government is able to reduce harmful behaviour, with respect to a number of the underlying consumption choices, NCD incidence is expected to fall precipitously.
Assessing the adaptability and resilience of cowpea and maize varieties to various climatic zones of Côte d’Ivoire
Authors: Tioté Lassana , Bonny Béket Séverin , Neya Bouma James , Koffi Kouamé Kevin , Bi Irié Arsène Zoro
Published: July 2024

The cultivation of cowpea and maize is common, but it is carried out without a prior selection of varieties that can effectively adapt to the specific climatic conditions of the zones. This study aimed at assessing cowpea and maize varieties in different ecological zones in order to identify the resilient varieties with respect to zone. The experiments were conducted in three different climatic and vegetation zones of Côte d’Ivoire: tropical rainforest zone, forest-savannah mosaic, and sub-Sudanian savannah in South, Centre-West, and North Côte d’Ivoire, respectively. In each zone, a randomized complete block design was used. Four varieties of both cowpea and maize were used. The analysis of variance was realized using grain yield data to compare varieties and climatic zones. The best varieties obtained differed according to the zones. Thus, in the tropical rain forest zone, the cowpea variety KVX780-6 and maize variety Violet de Katiola were the most yielding, with 593.30 kg ha−1 and 1270.84 kg ha−1, respectively. In forest-savannah mosaic, the cowpea variety KVX745-11P and maize variety SR21 obtained the highest yields, with 761.82 kg ha−1 and 2212.99 kg ha−1, respectively. The cowpea variety Tiligre and maize variety SR21 were the most productive in the sub-Sudanian savannah zone, with yields of 327.31 kg ha−1 and 1797.3 kg ha−1, respectively. Overall, the highest yield of cowpea (513.20 kg ha−1) and maize (1757.13 kg ha−1) were observed in forest-savannah mosaic. The best cowpea and maize varieties identified in each zone can be recommended to farmers.
A scoping review on bolstering concussion knowledge in medical education
Authors: Husain Aisha
Published: July 2024

Background

Concussions are a public health concern. Underdiagnosis and mismanagement negatively impact patients, risking in persistent symptoms and permanent disability.

Objective

This scoping review consolidates the heterogeneous and inconsistent concussion research and identifies key areas for medical education curriculum design to focus on for effective knowledge acquisition and bolstering competency in family physician residency. We analyze the literature on concussion education spanning various healthcare disciplines in North America.

Methods

PRISMA-Sc was followed and MEDLINE and EMBASE Classic + EMBASE in the OvidSP search platform were used to find terms for brain concussion AND medical education OR specific education until 2021.

Results

There are significant knowledge gaps about concussions, increased clinical exposure is required for competency which bolster physical examination skills and streamlined concussion guidelines are required for family medicine specialists that filter undifferentiated symptoms25% of participants improved adherence to concussion guidelines after an educational intervention and knowledge increased after concussion workshop and clinics.

Conclusions

Multifaceted teaching improves concussion diagnosis and management. More research is needed to examine concussion competency and, more importantly, whether these interventions improve patient outcomes.