bluuebunny/crossref_metadata_2025 huggingface dataset:
PENGARUH KONSELING INDIVIDU TERHADAP BULLYING PADA SISWA
Authors: Sulastri Ni Made
Published: October 2023

Pendidikan pada dasarnya menghantarkan siswa untuk menuju pada perubahan-perubahan tingkah laku baik intelektual, moral, maupun social. Perubahan tersebut diharapkan menghasilkan individu yang mampu berinteraksi sosial dengan manusia lain dan dengan lingkungannya, tetapi pendidikan tidak terlepas dari permasalahan seperti kekerasan seksual, kekerasan guru terhadap peserta didik, pergaulan bebas, serta permasalahan yang sangat umum terjadi adalah bullying. Hal ini mengakibatkan banyak peserta didik yang kemudian tidak fokus dalam menuntut ilmu sehingga prestasi belajar menurun dan kecenderungan untuk tidak mengikuti proses belajar mengajar di sekolah, mereka kemudian cenderung mencari kesenangan lain yang lebih menjurus pada hal-hal berbau negatif. Sehingga perlu dilakukan penelitian tentang pengaruh konseling individu terhadap bullying pada       siswa. Sampel yang digunakan adalah 8 orang siswa. Metode pengumpulan data yang digunakan dalam penelitian ini adalah metode angket sebagai metode utama, metode dokumentasi dan wawancara sebagai pelengkap. Sedangkan metode analisa data yang digunakan dalam penelitian ini adalah metode analisis statistik dengan rumus t-tes. Berdasarkan hasil analisis data bahwa t hitung yang diperoleh adalah sebesar 5.559, sedangkan nilai t-tabel (5.559 > 2.365). Hal ini berarti H0 ditolak sedangkan     Ha diterima. Kesimpulan yang diperoleh dalam penelitian ini adalah ada pengaruh konseling individu terhadap bullying pada siswa.
PENAGRUH PENGGUNAAN MATEMATIKA REALISTIC DALAM MENINGKATKAN KEMAMPUAN BERHTUNG SISWA SD KELAS TINGGI DI SD HADI SAKTI
Authors: Jaswandi Lalu , Kartiani Baiq Sarlita
Published: October 2023

Kemampuan berhitung merupakan bagian dari matematika yang dapat menumbuh kembangkan kemampuan kognitif anak. Masih banyak siswa yang memiliki kemampuan berhitung sangat rendah. Hal ini disebabkan oleh berbagai factor antara lain, model dan pendekatan pembelajaran yang digunakan guru kurang tepat dan kurang media matematika di sekolah. Tujuan dalam penelitian ini adalah untuk melihat apakah ada pengaruh pembelajaran matematika realistics terhadap kemampuan berhitung siswa kelas tinggi di SD Hadi Sakti.Penelitian ini merupakan penenlitian eksperimen menggunakan post-test only control group design. Variabel dalam penelitian ini adalah matematika realistic dan kemampuan berhitung. Sampel dalam penelitian adalah seluruh kelas V SD Hadi Sakti yang terdiri dari kelas VA dan VB. Teknik pengambilan sampel dalam penelitian ini menggunakan Teknik ramdom sampling. Penngujian hipotesis dilakukan dengan menggunakan uji-t. Persyaratan pengujian hipotesis adalah data terlebih dahulu dilakukan pengujian populasi dengan menggunakan uji normalitas dan uji homogenitas.Hasil analisis data penelitian diperoleh ttabel sebesar 2,020. Karena thitung (3,140) > ttabel (2,020) maka H0 ditolak. Artinya bahwa ada pengaruh model pembelajaran Matematika Realistics terhadap  kemampuan berhitung siswa
An Atypical Case of Hepatitis B-Associated Vasculitis
Authors: Ren Zhihong , El Hasbani Georges , Jenkins Christopher S. , Chehab Mohamad R. , Gummadi Jyotsna
Published: October 2023

One of the many extra-hepatic manifestations of hepatitis B virus (HBV) infections is vasculitis. While the classic HBV-associated vasculitis is polyarteritis nodosa, other vasculitides have been reported. The authors present an atypical case of acute HBV-associated vasculitis in a 57-year-old male with tobacco use disorder, characterised by extremity ischaemia, gangrene, splenic infarction, and positive proteinase-3 antibodies without sinopulmonary, gastrointestinal, or renal disease. The aggressiveness of the patient’s disease necessitated pulse-dose corticosteroids, cyclophosphamide, and two courses of plasmapheresis, and ultimately required multiple amputations of fingers and toes.
A Note on Qandahar Pashtuns: An Early Eighteenth-Century Pashto Source and Its Literary Context
Authors: Pelevin Mikhail
Published: October 2023

The article offers a discussion of a little-known Pashto document from 1712 containing presumably the earliest report on the Ghilzay revolt of 1709 in Qandahar and a few additional notes on relations between the Abdālī chieftains and the regional Safavid authorities. The text has been preserved in the Tārīkh-i muraṣṣaʿ (The Ornamented History) by Afżal Khān Khaṫak (d. c. 1740/41). The content, stylistic peculiarities, and underlying tribalist ideologies of the document are examined with an overview of sporadic remarks about Qandahar Pashtuns in the writings of Khushḥāl Khān Khaṫak (d. 1689). To better comprehend the specificity of Afżal Khān’s account as a specimen of Pashtun “counter-narrative,” the article considers the text in the broader context of available sources, predominantly in Persian, which impart mostly retrospective data on the activities of Pashtun tribes in the Qandahar region. The article also includes a full translation of the Pashto text under study.
Simulation of Oil Recovery Through Advanced Wells Using a Transient Fully Coupled Well-Reservoir Model
Authors: Anuththara Madhawee , Moradi Ali , Kumara Amaranath S. , Moldestad Britt M. E.
Published: October 2023

Oil recovery can be enhanced by maximizing the well-reservoir contact using long horizontal wells. One of the main challenges of using such wells is the early breakthrough of unwanted fluids due to the heel-toe effect and heterogeneity along the well. To tackle this problem, advanced wells are widely applied today. The successful design of such wells requires an accurate integrated dynamic model of the well and reservoir. This paper aims at developing appropriate integrated well-reservoir models for achieving optimal long-term oil recovery from advanced well models.In this study, OLGA® which is a dynamic multiphase flow simulator is implicitly coupled to ECLIPSETM which is a dynamic reservoir simulator for developing accurate models to simulate oil production from advanced wells under various production/injection strategies. A realistic heterogeneous light oil reservoir with an advanced horizontal well is used as a case study. Flow Control Devices (FCDs) are the key component of advanced wells and the functionality of the main types of FCDs in improving the oil production, minimizing the cost and carbon footprint is investigated.According to the obtained results, by implementation of FCDs the water breakthrough time is delayed by 180 days and the cumulative water production with ICD, AICD, and AICV completions is reduced by 26.8%, 33.1%, and 49.1%, respectively, compared to the open-hole case. Besides, the results show that linking OLGA and ECLIPSE is a numerically stable and accurate approach for modeling the interaction between the dynamic reservoir and dynamic well behavior for simulation oil recovery from advanced wells.
Sustainability analysis and simulation of a Polymer Electrolyte Membrane (PEM) electrolyser for green hydrogen production
Authors: Rabascall Jordi Béjar , Mirlekar Gaurav
Published: October 2023

In recent years, green hydrogen has emerged as an important energy carrier for future sustainable development. Due to the possibility of not emitting CO2 during its generation and use, hydrogen is considered a perfect substitute for current fossil fuels. However, a major drawback of hydrogen production by water electrolysis, supplied by renewable electricity, is its limited economic competitiveness compared to conventional energy sources. Therefore, this work focuses on analyzing the sustainability of a green hydrogen production plant, not only considering its environmental parameters, as well as its economic, energy and efficiency parameters. The polymer electrolyte membrane (PEM) is selected as the most promising method of green hydrogen production in the medium and long term. Subsequently, a small-scale production plant is simulated using chemical process simulation software to obtain key data for computing a set of sustainability indicators. The selected indicators are based on the Gauging Reaction Effectiveness for the Environmental Sustainability of Chemistries with a Multi-Objective Process Evaluator (GREENSCOPE) methodology and are used to compare the sustainability of the simulated PEM plant with alkaline water electrolysis (AWE) plant. Finally, the process is scaled-up to analyze the feasibility of the simulated PEM system and validated against data to determine the operation of the electrolyser at a large production scale.
ESP Lifted Oil Field: Core Model, and Comparison of Simulation Tools
Authors: Lie Bernt
Published: October 2023

Optimal operation of petroleum production is important in a transition from energy systems based on fossil fuel to sustainable systems. One sub-process in petroleum production deals with transport from the (subsea) well-bore to a topside separator. Here, a simple model in Sharma & Glemmestand (2014) has been streamlined into a dynamic model suitable for illustration of the dynamics of oil transport, as well for control studies. The advantages of using dimensionless equipment models are emphasized. The model is then used to compare two popular modeling languages: Modelica, and ModelingToolkit for Julia. Key advantages and disadvantages of these two languages are emphasized.
Numerical Investigation on Performance of Gas Turbine Blade: Effects of simulation Models and Blade Geometry
Authors: Hu Heng , Hushmandi Narmin , Genrup Magnus
Published: October 2023

With a significant impact on turbomachinery blade performance, surface curvature distribution becomes one of the essential factors in the design of high-efficiency blades. This study focuses on applying computational fluid dynamics (CFD) to evaluate turbine rotor blade performance. The main aim is to analyze the influence of incidence and geometry shape on the performance of a gas-turbine blade in two dimensions. To achieve this, an investigation was conducted to identify a suitable turbulence model for this case, with two turbulence models combined with two different solvers explored in ANSYS Fluent: Realizable k-ε model in pressure and density based solver; k-ω shear stress transport (SST) model in pressure and density based solver. The blade total pressure loss across different blade exit Mach numbers is the comparison factor, with validation against experimental data. Subsequently, the chosen pressure-based k-ω SST model mode is used to study the performance of various air inflow incidence angles and compare two different blade geometries. In this paper, two geometries, Geometry 1 and Geometry 2, were designed by setting two different exit blade angles, β2=79.5° and β2=70° respectively, while the inlet blade angles have the same value, β1=48.8°. Furthermore, the effect of varying air inflow incidence angles between -48.8° and 10° on the blade performance distribution is also investigated. Within the studied range, the inflow incidence angle of 10° is found to have the best performance in terms of turbine work output. On the other hand, the blade performance of Geometry 2 appears superior to Geometry 1.
Developing a Multi-Building Scale Energy Model for a University Campus using URBANopt
Authors: Pahlavan Hamed Mohseni , Nord Natasa
Published: October 2023

Building energy models are developed to describe energy performance. The energy performance of buildings is influenced by physical and human influenced factors. Therefore, to improve energy efficiency and renewable energy implementation in buildings on large scale, there is a need to analyze buildings on a large scale. In this study, URBANopt, a multi-building energy evaluation tool, was used to develop an accurate Multi building scale energy model for a university campus. This model will be useful in the future work to evaluate various available and emerging building-level and district-level technologies and retrofitting options to improve energy performance. URBANopt is a unique tool that leverages high-fidelity simulations of buildings, community-scale systems, distributed energy resources, and the associated interactions with local distribution electric infrastructure. A university campus in Norway was chosen as a case study. Results obtained from URBANopt were compared with a typical building energy simulation model in IDA-ICE for a representative building. This representative building was developed based on building characteristics, functionality, and geographic location, including indoor and outdoor climate conditions. Both models were validated by using measurement data. The results showed better simulation accuracy of the multi-building method of URBANopt with the measurement data, mainly due to the averaging of the characteristics of all buildings in the development of the representative building. Furthermore, the URBANopt allowed assigning a different scenario of technologies and retrofit options to each building in the evaluation process, which is impossible in the typical model due to its nature. However, it should be pointed out that the computational time of the model developed in URBANopt was higher and will increase more with the increased number of buildings.
Simulation of blue hydrogen production by natural gas in the North Sea
Authors: Deeraksa Chidapha , Moldestad Britt Margrethe Emilie , Furuvik Nora Cecilie Ivarsdatter S.
Published: October 2023

Hydrogen is an efficient energy carrier and an important contribution to sustainable energy development. Hydrogen can be produced based on different methods and on different raw materials. Blue hydrogen is hydrogen produced from natural gas via a steam-methane reformer with subsequent carbon capture and storage. The CO2 from the process can be stored in matured oil and gas fields or in an aquifer.This paper studies the potential of producing blue hydrogen from methane from the Troll gas field on the Norwegian continental shelf. The production rate of methane from the Troll field is predicted and based on the calculated methane production the steam-methane reformation process is modelled and simulated. The model includes the required steps to convert natural gas into hydrogen and CO2 and further to catch the CO2. The volume of captured CO2 per m3 of produced hydrogen is calculated. Production of blue hydrogen also includes storage of CO2, and the required storage capacity is calculated.The purpose of this paper was to investigate whether blue hydrogen produced by natural gas from the Troll field is an alternative to reducing CO2 emissions to reach the climate target. The simulation was performed with Aspen HYSYS 12 and the calculation on how much CO2 must be stored and the storage capacity needed were performed manually. The mass of CO2 resulting from the conversion of about 2400 tons natural gas/h to blue hydrogen and CO2 at the Troll field is 5600 tons CO2/hour or 49 megatons CO2/year. The produced hydrogen had a purity of 95%. The predicted storage capacity for CO2 at the Troll field is found to be 136 megatons. A profitability analysis is performed and the results are promissing.
Traceable System of Systems Explorations Using RCE Workflows
Authors: Lovaco Jorge , Staack Ingo , Krus Petter
Published: October 2023

The System of Systems (SoS) framework plays a pivotal role in delimiting aircraft design spaces by examining interactions among its Constituent Systems (CS). Each CS has a distinct collection of capabilities, some of which may be shared with other CS. The framework explores emergent behaviours that arise from communication between the CS within the SoS. These emergent behaviours are characterized by their unattainability by any individual CS and result from their collaborative nature. The identification of these emergent behaviours enables System of Systems Engineering (SoSE) to pinpoint the most valuable configurations of the SoS, thereby maximizing the collective value. Furthermore, these emergent behaviours aid in stipulating design requirements for new systems based on the capabilities outlined in the SoS study. To map the relationship between needs, capabilities, requirements, and behaviours, maintaining traceability throughout the study is paramount.This research employs workflows created using the Remote Component Environment (RCE), a specialized tool for structured and automated task development. The objective is to showcase RCE's integration capabilities- specifically for software tools and Python scripts- with task scheduling. This integration enables swift extraction of results, making them available at every step, thus augmenting analysis efficiency. The study focuses on the perspective of an aircraft designer during the early concept generation phase, specifically applied to the development of an electric Unmanned Aerial Vehicle (UAV) concept for wildfire detection.
An embedded industrial control framework for model predictive control of district heat substation
Authors: Örneskans Joakim , Kyprianidis Konstantinos , Vouros Stavros , Bengtsson Gunnar
Published: October 2023

In this paper we present a standard platform XC05 for an Edge Controller based on an Industrial Control System, where functions made in Modelica and Python can be run as an integrated part of an automation system. We demonstrate how the platform is used to run a complex Model Predictive Control (MPC) strategy to optimize indoor heating in a residential building. MPC strategies have been increasingly popular due to their ability to handle nonlinear dynamics with constraints and multi-objective optimization. Since industrial control systems are real-time based, consideration must also be taken to running security and the real-time characteristics and timing of the overall system solution. We also show that heavy calculation, protected by the industrial control system operative, can run safely together within fast automation using standard electronics. The controlled variable in the MPC strategy is the supply water temperature (Space heating), and the objective is to keep the indoor temperature at a predefined setpoint despite variations in outdoor weather conditions by using local measurements and weather forecasts from the Swedish weather service SMHI. The model used in the MPC is trained automatically with real-time data during running. We describe the controller architecture and briefly the model predictive control algorithm, analyze the overall system performance regarding safety and real-time characteristics. The proposed model predictive control application showed stable operation and expected real-time characteristics during operation. Furthermore, a reduction in indoor temperature deviations was achieved.
Development of a MATLAB-based code for quantification of effective void space in porous pavement
Authors: Allen Rebecca , Dongmo-Engeland Berthe , Al-Batat Saja
Published: October 2023

Porous pavement is a well-documented, low-impact stormwater management technique. When it comes to design of the top layer, the amount of void space (porosity) is often of interest as it influences both infiltration and strength of the pavement. Laboratory equipment can be used to measure the porosity of core samples, but when more detail is required, other equipment or methods must be used. One such method is to scan the entire sample using a computer tomography (CT) machine and then perform some image processing techniques on the scanned data to reconstruct the sample digitally. While the workflow of scanning and processing to produce the 3D digital twin of porous pavement is not new and can be in fact done by open-source or commercial software, there are still some parts of the process that deserve a deeper investigation, for example binarization and segmentation algorithms applied to the solid-and-void space and void space, respectively. This is difficult to do with commercial software which operates like a black-box, and there needs to be more open-source codes that are user-friendly, extendable, and competitive to what commercial software can do. This work presents a MATLAB-based code that allows for a deeper investigation of how one can accurately and efficiently quantify the effective (or connected) void space of a porous pavement sample from a 3D digital model. We demonstrate the effect of dataset coarsening, which can be used to reduce the computational intensity of the algorithm while preserving accuracy. The code is publicly available online to allow for reproducible research and the possibility of extensions for increased functionality and complexity.
Machine learning assisted adaptive heat load consumption forecasting in district heating network
Authors: Renuke Avinash , Vouros Stavros , Kyprianidis Konstantinos
Published: October 2023

District heating system often consists of a long, complex network of piping carrying heat from a power plant to the consumers. The supply temperature from the plant is either controlled by the operator from experience or a predefined curve based on the outdoor temperature. An optimized supply temperature which would be lower than the one obtained traditionally would lead to lower heat loss and reduced peak load on the power plant. In this paper, we investigate the machine learning models for heat load forecasting which is a crucial parameter in the optimizing process. Models are generated using supervised machine learning algorithms: Linear models (Linear Regression, Ridge and Gaussian Process Regressor), Random Forest Regressor, Support Vector Machine (SVM) and Long Short-Term Memory (LSTM) recurrent neural network (RNN). Data-driven models are used extensively in the literature to predict heat load prediction based on the weather and the time effect on a fixed training set, however, in this study, we model the heat load in the network in real-time scenarios i.e., adaptive training and forecasting. The model is adaptively updated as well as the training of the machine learning model in real time. It provides a “plug-and-play” solution for real-time prediction without significant pre-tuning requirements. The results of all the models are compared with various time horizons i.e., 6 hrs, 10 hrs, 24 hrs and 1 week, using the district heating data obtained for the city of Vasteras in Sweden. The performance of the prediction algorithms is evaluated using Mean Absolute Percentage Error (MAPE) and Root Mean Squared Error (RMSE). An algorithm with the best accuracy is selected based on the performance comparison. Also, models suitable for short-term and long-term forecasting are discussed towards the end of the article
Editorial
Authors: Zaniboni Hâmara Milaneze de Souza , Pina Ticiana Petean
Published: October 2023

É com grande entusiasmo que apresentamos a segunda edição da Revista Puxirum: Abordagem Multidisciplinar em Ciências Agrárias, dedicada a um tema que é o alicerce da pesquisa acadêmica e científica em nosso país: os Trabalhos de Conclusão de Curso (TCCs). No âmbito acadêmico, os TCCs são reflexos da pesquisa e dedicação dos estudantes, representando uma etapa fundamental em suas jornadas educacionais. Na Revista Puxirum, reconhecemos a importância dos TCCs e seu impacto na pesquisa nacional, representando uma oportunidade valiosa para os estudantes imergirem em questões pertinentes e desafiadoras em suas respectivas áreas de estudo. Esses trabalhos não apenas promovem o desenvolvimento de habilidades de pesquisa e pensamento crítico, mas também têm o potencial de gerar contribuições significativas para o avanço de nossos campos acadêmicos e científicos. Eles capacitam os futuros pesquisadores e impulsionam a inovação, o desenvolvimento e o crescimento sustentável de nossas disciplinas, e acreditamos que, ao apoiar e promover os TCCs, estamos investindo no futuro da ciência no Brasil.
Plant microbiomes as contributors to agricultural terroir
Authors: Johnston-Monje David , Vergara Laura Isabella , Lopez-Mejia Jessica , White James Francis
Published: October 2023

Agricultural products such as tea, chocolate, coffee and wine are valued for their sensorial and nutritional qualities. Variation in the growing conditions of a crop can influence the plant’s phenotype, thus it behooves agriculturalists to optimize the conditions on their farms to grow the highest quality product. The set of growing conditions associated with a certain geographic location and its influence on the product’s chemistry is known as terroir. Although terroir plays a significant role in marketing and consumer appreciation as well as product identity and valorization, rarely are the biochemical differences or the factors creating them very well understood. The word derives from the Latin for “land”, suggesting terroir is simply a function of the geographical location where a plant grew, while in its modern usage, terroir is understood to be the result of soil type, climate, landscape, topography, biotic interactions and agricultural practice. Except for fermented food products like wine and chocolate, plant associated microbiomes have been little studied for their contribution to a crop’s terroir; however, modern metagenomics and metabolomics technologies have given scientists the tools to better observe how microbial diversity can impact the chemical variation in plant products. Differences in the microbiomes inhabiting plant organs can change phytochemistry by altering host metabolism, for example increasing the nutrients absorbed by roots that then are deposited in leaves, seeds and fruits. Plant associated microbes can consume plant molecules, removing them from the metabolome, or they can contribute smells and flavors of their own. This review aims to synthesize research into rhizosphere, endosphere, phyllosphere, spermosphere, carposphere, and anthosphere microbiome influences on plant biochemistry and crop derived products, while helping to increase the appreciation that beneficial microbes are able to contribute to agriculture by improving phytochemical quality.
Yield stability of silage maize double cropping systems across nine German environments
Authors: Schmidt Fruzsina , Böhm Herwart , Piepho Hans-Peter , Urbatzka Peer , Wachendorf Michael , Graß Rüdiger
Published: October 2023

Introduction

Yield and its stability are both vital characteristics to evaluate the viability of cropping systems. However, the current frames of field research hardly allow an accurate evaluation of short-term effect stability. Therefore, over nine German environments (three years and three locations), first crop, maize, total harvested dry biomass yield (DMY), and maize dry matter content (DMC) variability were evaluated through a risk assessment in an organically managed silage maize experiment comprising 18 cropping systems.

Material and methods

The treatment factors included first crop group (pure legume, legume–cereal mixture), first crop (winter pea, hairy vetch and their mixtures with rye, control), management—incorporating first crop use and tillage (double cropping system no-till, double cropping system reduced till, double-cropped, mulched system terminated with roller-crimper, control), fertilization and mechanical weed control (yes–no), and row width (75 cm, 50 cm).

Results and discussion

The first crop DMY and maize DMC had a positive relationship with its variance, whereas maize DMY and total DMY had a negative relationship. The differences in risks were governed by system (number of crops), management and first crop (group), and followed compatible patterns with what was observed for their influence on the mean of the parameters. The pedological and climatic conditions, especially near maize sowing and establishment, and therefore the length of season are crucial in double cropping and double-cropped, mulched systems. In its current state, the location in the northern region of Germany was not well suited for the studied alternative systems, whereas in the other regions (central and south), double cropping systems with reduced tillage as well as double-cropped systems with pure legume mulches may offer alternative management systems for silage maize. Further optimization of the critical sowing and establishment phase may result in more diversified options for double cropping and double-cropped, mulched systems in the future.
3D multiplexed tissue imaging reconstruction and optimized region of interest (ROI) selection through deep learning model of channels embedding
Authors: Burlingame Erik , Ternes Luke , Lin Jia-Ren , Chen Yu-An , Kim Eun Na , Gray Joe W. , Chang Young Hwan
Published: October 2023

Introduction: Tissue-based sampling and diagnosis are defined as the extraction of information from certain limited spaces and its diagnostic significance of a certain object. Pathologists deal with issues related to tumor heterogeneity since analyzing a single sample does not necessarily capture a representative depiction of cancer, and a tissue biopsy usually only presents a small fraction of the tumor. Many multiplex tissue imaging platforms (MTIs) make the assumption that tissue microarrays (TMAs) containing small core samples of 2-dimensional (2D) tissue sections are a good approximation of bulk tumors although tumors are not 2D. However, emerging whole slide imaging (WSI) or 3D tumor atlases that use MTIs like cyclic immunofluorescence (CyCIF) strongly challenge this assumption. In spite of the additional insight gathered by measuring the tumor microenvironment in WSI or 3D, it can be prohibitively expensive and time-consuming to process tens or hundreds of tissue sections with CyCIF. Even when resources are not limited, the criteria for region of interest (ROI) selection in tissues for downstream analysis remain largely qualitative and subjective as stratified sampling requires the knowledge of objects and evaluates their features. Despite the fact TMAs fail to adequately approximate whole tissue features, a theoretical subsampling of tissue exists that can best represent the tumor in the whole slide image.

Methods: To address these challenges, we propose deep learning approaches to learn multi-modal image translation tasks from two aspects: 1) generative modeling approach to reconstruct 3D CyCIF representation and 2) co-embedding CyCIF image and Hematoxylin and Eosin (H&E) section to learn multi-modal mappings by a cross-domain translation for minimum representative ROI selection.

Results and discussion: We demonstrate that generative modeling enables a 3D virtual CyCIF reconstruction of a colorectal cancer specimen given a small subset of the imaging data at training time. By co-embedding histology and MTI features, we propose a simple convex optimization for objective ROI selection. We demonstrate the potential application of ROI selection and the efficiency of its performance with respect to cellular heterogeneity.
A portable AFO solution for pneumatic actuator with cable tendon mechanism to assist ankle dorsiflexion
Authors: Wang Junming , Shu Jing , Su Yujie , Hu Chengpeng , Yeung Ling-Fung , Li Zheng , Tong Raymond Kai-Yu
Published: October 2023

The limited portability of pneumatic pumps presents a challenge for ankle-foot orthosis actuated by pneumatic actuators. The high-pressure requirements and time delay responses of pneumatic actuators necessitate a powerful and large pump, which renders the entire device heavy and inconvenient to carry. In this paper, we propose and validate a concept that enhances portability by employing a slack cable tendon mechanism. By managing slack tension properly, the time delay response problem of pneumatic actuators is eliminated through early triggering, and the system can be effectively controlled to generate the desired force for dorsiflexion assistance. The current portable integration of the system weighs approximately 1.6 kg, with distribution of 0.5 kg actuation part on the shank and 1.1 kg power system on the waist, excluding the battery. A mathematical model is developed to determine the proper triggering time and volumetric flow rate requirements for pump selection. To evaluate the performance of this actuation system and mathematical model, the artificial muscle’s response time and real volumetric flow rate were preliminarily tested with different portable pumps on a healthy participant during treadmill walking at various speeds ranging from 0.5 m/s to 1.75 m/s. Two small pumps, specifically VN-C1 (5.36 L/min, 300 g) and VN-C4 (9.71L/min, 550 g), meet our design criteria, and then tested on three healthy subjects walking at normal speeds of 1 m/s and 1.5 m/s. The kinematic and electromyographic results demonstrate that the device can facilitate ankle dorsiflexion with a portable pump (300–500 g), generating sufficient force to lift up the foot segment, and reducing muscle activity responsible for ankle dorsiflexion during the swing phase by 8% and 10% at normal speeds of 1 m/s and 1.5 m/s respectively. This portable ankle robot, equipped with a compact pump weighing approximately 1.6 kg, holds significant potential for assisting individuals with lower limb weakness in walking, both within their homes and in clinical settings.
Effect of central corneal curvature on corneal material stiffness parameter acquired by dynamic corneal responses
Authors: Chu Zhe , Ren Qi , Su Wenjie , Cui Wei , Wu Jie
Published: October 2023

The stress–strain index (SSI) is a measure of corneal material stiffness, which is obtained using the Corvis ST algorithm based on dynamic corneal response parameters. The reduced SSI corresponds to the longer axial length (AL). In a previous study, we found SSI increases as the corneal curvature flattens, whereas a flatter corneal curvature indicates a longer AL (emmetropia or myopia). Therefore, in this cross-sectional study, we aimed to address these contradictory findings. First, we characterized the features of SSI, curvature radius of the anterior corneal surface (CR), and AL and analyzed their correlation with advanced myopia. Next, we compared the relationship between AL and SSI after adjusting for the effect of CR. We found a significant positive correlation between SSI and CR, which contradicts the developmental law of axial myopia. Furthermore, after accounting for the effect of CR, we observed a stronger correlation between SSI and AL than that in the unadjusted model. In conclusion, CR is an independent influencing factor for SSI in addition to AL, which masked the decrease in SSI caused by prolonged AL in axial myopia.
Non-invasive technologies for heart failure, systolic and diastolic dysfunction modeling: a scoping review
Authors: Al Younis Sona M. , Hadjileontiadis Leontios J. , Stefanini Cesare , Khandoker Ahsan H.
Published: October 2023

The growing global prevalence of heart failure (HF) necessitates innovative methods for early diagnosis and classification of myocardial dysfunction. In recent decades, non-invasive sensor-based technologies have significantly advanced cardiac care. These technologies ease research, aid in early detection, confirm hemodynamic parameters, and support clinical decision-making for assessing myocardial performance. This discussion explores validated enhancements, challenges, and future trends in heart failure and dysfunction modeling, all grounded in the use of non-invasive sensing technologies. This synthesis of methodologies addresses real-world complexities and predicts transformative shifts in cardiac assessment. A comprehensive search was performed across five databases, including PubMed, Web of Science, Scopus, IEEE Xplore, and Google Scholar, to find articles published between 2009 and March 2023. The aim was to identify research projects displaying excellence in quality assessment of their proposed methodologies, achieved through a comparative criteria-based rating approach. The intention was to pinpoint distinctive features that differentiate these projects from others with comparable objectives. The techniques identified for the diagnosis, classification, and characterization of heart failure, systolic and diastolic dysfunction encompass two primary categories. The first involves indirect interaction with the patient, such as ballistocardiogram (BCG), impedance cardiography (ICG), photoplethysmography (PPG), and electrocardiogram (ECG). These methods translate or convey the effects of myocardial activity. The second category comprises non-contact sensing setups like cardiac simulators based on imaging tools, where the manifestations of myocardial performance propagate through a medium. Contemporary non-invasive sensor-based methodologies are primarily tailored for home, remote, and continuous monitoring of myocardial performance. These techniques leverage machine learning approaches, proving encouraging outcomes. Evaluation of algorithms is centered on how clinical endpoints are selected, showing promising progress in assessing these approaches’ efficacy.
The GSH responsive indocyanine green loaded PD-1 inhibitory polypeptide AUNP12 modified MOF nanoparticles for photothermal and immunotherapy of melanoma
Authors: Hao Ying , Liu Tailuo , Zhou Hao , Peng Jinrong , Li Ka , Chen Yuwen
Published: October 2023

Introduction: Photothermal therapy (PTT) holds significant potential for the treatment of malignant tumors. However, conventional single PTT often struggles to effectively inhibit tumor metastasis and recurrence. In this study, we constructed a MOF nanoparticle with a synergistic therapeutic effect combining photothermal and immunotherapy, enabling selective blocking of the PD-1/PD-L1 pathway within the tumor microenvironment.

Methods: Firstly, MOF nanoparticles were synthesized using NH2-TPDC as ligands and Zr+4 as metal ions. Subsequently, NH2 was modified to N3 via azide transfer reagents. Through a copper free catalytic click chemical reaction, the PD-1/PD-L1 blocking agent AUNP-12 functionalized with disulfide bonds of DBCO was covalently introduced into MOF nanoparticles which were then loaded with the photothermal agent indocyanine green (ICG) to successfully obtain uniformly sized and stable ICG-MOF-SS-AUNP12 nanoparticles.

Results and discussion: ICG-MOF-SS-AUNP12 exhibited GSH-triggered release of PD-1/PD-L1 blockers while demonstrating potent photothermal effects capable of efficiently killing tumor cells. Under 808 nm near-infrared (NIR) irradiation, ICG-MOF-SS-AUNP12 effectively promoted the maturation of DC cells and activated immune responses. This study presents a novel method for constructing MOF-based nanodrugs and offers new possibilities for the synergistic treatment of tumors involving photothermal combined with immunotherapy.
Use of a ferroptosis-related gene signature to construct diagnostic and prognostic models for assessing immune infiltration in metabolic dysfunction-associated fatty liver disease
Authors: Lian Xin , Tang Xulei
Published: October 2023

Introduction: Metabolic dysfunction-associated fatty liver disease (MAFLD), a serious health problem worldwide, can involve ferroptosis. This study aimed to comprehensively analyze the ferroptosis-related genes associated with MAFLD.

Methods: Ferroptosis-related differentially expressed genes (FRDEGs) were identified in patients with MAFLD and healthy individuals. Gene ontology functional enrichment analysis, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, and gene set enrichment analysis (GSEA) were used to analyze the relevant action pathways of the FRDEGs. The Encyclopedia of RNA Interactomes, CHIPBase, and comparative toxicogenomics databases were used to build mRNA-miRNA, mRNA-transcription factor (TF), and mRNA-drug interaction networks, respectively. A diagnostic model was constructed and bioinformatics analysis methods, such as least absolute shrinkage and selection operator regression analysis, Cox regression analysis, nomogram-based analysis, consensus clustering analysis, and single-sample GSEA, were used to systematically investigate the prognostic values and immunologic characteristics.

Results: A total of 13 FRDEGs were obtained and eight were used to construct a diagnostic model and perform a prognostic analysis. Hub genes were also used to construct mRNA-miRNA and mRNA-TF interaction networks and potential drug or molecular compounds. Two MAFLD subtypes were identified: cluster2, which represents an “immunoactive” type, and cluster1, which represents an “immunosuppressive” type; a significant correlation was observed between the immune cell contents and the expression of three FRDEGs (NR4A1, FADS2, and SCD).

Conclusion: A ferroptosis-related gene signature was constructed to diagnose MAFLD-associated steatohepatitis, predict the prognosis of MAFLD patients, and analyze the immunologic characteristics of MAFLD. Our findings may provide insights into developing innovative MAFLD treatment techniques.
Modeling and optimization study on degradation of organic contaminants using nZVI activated persulfate based on response surface methodology and artificial neural network: a case study of benzene as the model pollutant
Authors: Luo Moye , Zhang Xiaodong , Long Tao , Chen Sheng , Zhan Manjun , Zhu Xin , Yu Ran
Published: October 2023

Due to the complicated transport and reactive behavior of organic contamination in groundwater, the development of mathematical models to aid field remediation planning and implementation attracts increasing attentions. In this study, the approach coupling response surface methodology (RSM), artificial neural networks (ANN), and kinetic models was implemented to model the degradation effects of nano-zero-valent iron (nZVI) activated persulfate (PS) systems on benzene, a common organic pollutant in groundwater. The proposed model was applied to optimize the process parameters in order to help predict the effects of multiple factors on benzene degradation rate. Meanwhile, the chemical oxidation kinetics was developed based on batch experiments under the optimized reaction conditions to predict the temporal degradation of benzene. The results indicated that benzene (0.25 mmol) would be theoretically completely oxidized in 1.45 mM PS with the PS/nZVI molar ratio of 4:1 at pH 3.9°C and 21.9 C. The RSM model predicted well the effects of the four factors on benzene degradation rate (R2 = 0.948), and the ANN with a hidden layer structure of [8-8] performed better compared to the RSM (R2 = 0.980). In addition, the involved benzene degradation systems fit well with the Type-2 and Type-3 pseudo-second order (PSO) kinetic models with R2 > 0.999. It suggested that the proposed statistical and kinetic-based modeling approach is promising support for predicting the chemical oxidation performance of organic contaminants in groundwater under the influence of multiple factors.
Sex differences in ventricular arrhythmia, atrial fibrillation and atrioventricular block complicating acute myocardial infarction
Authors: Alnsasra Hilmi , Tsaban Gal , Weinstein Jean Marc , Nasasra Mhamad , Ovdat Tal , Beigel Roy , Orvin Katia , Haim Moti
Published: October 2023

Background

Acute myocardial infarction (AMI) complicated by tachyarrhythmias or high-grade atrioventricular block (HAVB) may lead to increased mortality.

Purpose

To evaluate the sex differences in patients with AMI complicated by tachyarrhythmias and HAVB and their associated outcomes.

Materials and methods

We analyzed the incidence rates of arrhythmias following AMI from the Acute Coronary Syndrome Israeli Survey database from 2000 to 2018. We assessed the differences in arrhythmias incidence and the associated mortality risk between men and women.

Results

This cohort of 14,280 consecutive patients included 3,159 (22.1%) women and 11,121 (77.9%) men. Women were less likely to experience early ventricular tachyarrhythmia (VTA), (1.6% vs. 2.3%, p = 0.034), but had similar rates of late VTA (2.3% vs. 2.2%, p = 0.62). Women were more likely to experience atrial fibrillation (AF) (8.6% vs. 5.0%, p < 0.001) and HAVB (3.7% vs. 2.3%, p < 0.001). The risk of early VTAs was similar in men and women [adjusted Odds Ratio (aOR) = 0.76, p = 0.09], but women had a higher risk of AF (aOR = 1.27, p = 0.004) and HAVB (aOR = 1.30, p = 0.03). Early [adjusted hazard ratio (aHR) = 2.84, p < 0.001] and late VTA (aHR =- 4.59, p < 0.001), AF (aHR = 1.52, p < 0.001) and HAVB (aHR = 2.83, p < 0.001) were associated with increased 30-day mortality. Only late VTA (aHR = 2.14, p < 0.001) and AF (aHR = 1.44, p = 0.002) remained significant in the post 30 days period.

Conclusions

During AMI women experienced more AF and HAVB but fewer early VTAs than men. Early and late VTAs, AF, and HAVB were associated with increased 30-day mortality. Only late VTA and AF were associated with increased post-30-day mortality.
Pathways, technology and the patient—connected health through the lifecycle
Authors: MacMahon Silvana Togneri , Richardson Ita
Published: October 2023

Connected Health solutions are ubiquitous in providing patient centered care and in responding to a new paradigm of care pathways where Health Information Technology is being introduced. This paper defines Connected Health, and, in particular, describes standards and regulations which are important to the implementation of safe, effective and secure Connected Health solutions. This paper provides: a holistic view of Connected Health; provides a standards and regulations based view of the lifecycle of the Health IT system; and identifies the relevant roles and responsibilities at the various stages of the lifecycle for both manufacturers of connected health solution and healthcare delivery organization solutions. We discuss how the implementation of standards and regulations, while implementing and using Health IT infrastructure, requires close collaboration and ongoing communication between Healthcare Delivery Organizations and Accountable Manufacturers throughout the lifecycle of the health IT system. Furthermore, bringing technology into the healthcare system requires a robust and comprehensive approach to Clinical Change Management to support the business and clinical changes that the implementation of such solutions requires. Ultimately, to implement safe, effective, and secure Connected Health solutions in the healthcare ecosystem, it requires that all those involved work together so that the main requirement—patient-centered care—is realized.
Emergency remote assessment practices in higher education in sub-Saharan Africa during COVID-19
Authors: Baidoo-Anu David , Asamoah Daniel , Quainoo Eric Atta , Gyamerah Kenneth , Amoateng Ernest Y. , Sasu Ernest Ofori
Published: October 2023

Following the disruptions to in-person schooling during COVID-19 and the need for emergency remote teaching, this study explored the assessment experiences of teacher educators in Ghana. Through a qualitative transcendental phenomenological approach, purposive criterion sampling was used to select 25 teacher educators from 15 teacher training institutions in Ghana who participated in online teaching during COVID-19 school closure. The findings show that teacher-centered approaches to assessment dominate emergency remote assessment practices of teacher educators. Hodgepodge grading and general feedback were more prevalent during remote assessment. Teachers were also found to randomly select a few students to provide individualized feedback due to the large class size. Challenges including limited knowledge of the use of the online teaching platform for assessment, inadequate professional training and access to technological resources, and concerns about academic dishonesty were reported. However, teachers reported that their involvement in abrupt remote teaching and assessment has been a learning opportunity for them to develop new skills, which is imperative for their professional development.