bluuebunny/crossref_metadata_2025 huggingface dataset:
Sustainable technology and business development: application of simulation platforms in norwegian marine industries
Authors: Hansen Irina-Emily , Mork Ola Jon , Kleppe Paul Steffen
Published: July 2024

This article delves into the pivotal role of simulation platforms in efficiently advancing innovation projects, drawing insights from a case study involving Manulab, the Manufacturing Laboratory at the Norwegian University of Science and Technology, and regional fish industry companies. The utilization of simulation platforms emerges as a cornerstone for project success, notably in expediting the development of cutting-edge technologies and seamlessly integrating research findings into industrial practices. The study underscores how simulation platforms not only propel technology readiness level progression but also facilitate concurrent advancement along the business readiness level. This holds particularly true for simulation platforms like Unity and Omniverse by Nvidia, equipped with physics engines that meticulously simulate interactions within virtual environments. Several factors contribute to this success, including sustained engagement among stakeholders and the fostering of spin-off initiatives, which catalyze collaborative innovation. By nurturing a holistic and collaborative approach, simulation platforms serve as catalysts for translating research outcomes into tangible applications within the industrial sector. This underscores their indispensable role in propelling industrial innovation forward.
The prospects of financial opening-up in china in light of the trilemma of international finance
Authors: Boros Eszter , Sztano Gabor
Published: July 2024

The growing use of the renminbi (RMB) in cross border financial transactions is attracting much attention, but the existence of capital controls in China is frequently pointed out as a major obstacle for the RMB to become a global currency. The Chinese monetary policy mix is a special case from the point of view of Mundell’s “impossible trinity”. Beijing follows a cautious strategy to balance between the pros and cons of certain policy combinations. The ambitious goal to internationalise the RMB has added to this complexity and would benefit from the quicker opening-up of the onshore financial market. Our paper assesses the possible trade-offs this would entail for Chinese decision-makers in light of the different policy choices of the trilemma. We apply an ARDL model to reveal how the three aspects contributed to macroeconomic stability in China in the last 15 years. Results suggest that exchange rate stability remains an effective stabilising factor, and monetary policy independence is also relevant, especially for inflationary outcomes. Financial opening-up would thus possibly come with some loss of stability. However, without taking this risk, constraints remain for the RMB to reduce its reliance on the USD as the dominant world currency.
Gdp influence on the esg risk framework disclosure of the visegrad four banks
Authors: Voneki Zsuzsanna Tamasne , Lamanda Gabriella
Published: July 2024

The purpose of this paper is to investigate the relationship between the ESG risk management framework disclosure and GDP. We examined annual risk and sustainability reports published by 26 banks in the Visegrád Four countries (Czech Republic, Hungary, Poland, and Slovakia) during the period of 2017-2021. We applied content analysis and developed the ESG Framework Disclosure index (FD) to provide a comprehensive overview on how banks are committed to the integration of ESG aspects into their risk management system. Panel regression was performed to improve and ensure the robustness of our study. We found that our index is positively and significantly influenced by GDP per capita, as well as by bank size and capital adequacy.
Application of the nonlinear autoregressive model with exogenous inputs for predicting the gross operating product based on usali data
Authors: Labanowski Lukasz , Fracz Pawel , Wotzka Daria , Foltys Joachim
Published: July 2024

This study presents an advanced data analysis for developing a predictive model for the gross operating profit time series, using monthly data from two Polish hotels compliant with the Uniform System of Accounts for the Lodging Industry (USALI). Emphasizing the USALI data, the research utilized the Nonlinear Autoregressive with eXogenous (NARX) inputs model to capture both linear and nonlinear trends. Extensive testing involved eight neural network learning methods across double layer networks with 5 to 30 neurons in the hidden layer and various sizes of delay parameter. The effectiveness of each model was measured by the mean squared error, identifying the model with its lowest value as the most accurate, and by normality of test residuals.
Assessment the effect of green bonds on green innovation
Authors: Nemeth-Durko Emilia
Published: July 2024

In this study, the innovation-promoting effect of green bond issuance was investigated. Green bonds were expected to be the driving force behind the financing of innovation for the sustainable purposes of an economy, and thereby promote an increase in the number of green patents. The prevailing trend in capital markets may enhance green assets establishing long-term financing basis for the green transition. To identify the relationship among the variables, fixed effect regression model was applied to reveal the macro environment of green bond issuance. in the number of green patents between 2016-2020 in several European countries. The results show that there is a significant relationship between green bond issuance and the number of green patent meaning that green bond could stimulate green innovation efforts in several European countries between 2016 and 2020.
Soft body simulation of fish in fish processing factories
Authors: Kleppe Paul Steffen , Karlsen Benjamin , Pedersen Lersveen Fridtjof , Giske Lars Andre
Published: July 2024

When simulating manufacturing systems and the production of components, sufficient realistic behaviour is needed to use the simulation as a decision-making tool for optimising and verifying the design. To simulate, design, and optimise fish processing with the singular simulation of fish, a physics engine with soft body support and advanced interaction between bodies is beneficial. This paper explores the use of Omniverse as a simulation platform and Isaac Sim as a simulation tool. A digital simulation and representation of a fish processing line is developed and compared with a physical build production line for fish processing.
How to evaluate process discovery for digital twins in industry 4.0? process discovery, hypothesis testing and conformance analysis
Authors: Yoshiro Nishiura Juliano , Lopes Paulo Victor , Neto Verri Filipe Alves , Skoogh Anders
Published: July 2024

The field of data science is an emerging area of study that arises in the context of the production of a large volume of data in recent years. The objective of this area is to obtain valuable information that is extracted through data processing. In the industrial context, the identification of failures and bottlenecks in production lines is essential to increase the productivity of the evaluated systems. However, manual analysis can be time-consuming and costly. Process discovery is a set of techniques that includes the use of algorithms to extract a process model from the event log, which can be used as a basis for developing Digital Twins. Therefore, this paper proposes the use of an artificial production line generator so that process mining algorithms can be tested with a large number of samples and different network characteristics. Thus, the main contribution will be the testing of hypotheses to assist in choosing the best algorithms in a practical context.
Computer vision for reverse engineering in the design, simulation and operation of maritime systems
Authors: Legaz Maria Jose , Gaspar Henrique M.
Published: July 2024

We present, here, a compilation of attempts to use computer vision technology in the maritime field. The scope is mostly in reverse engineering, that is, get- ting information about an existing physical system and modelling it digitally, extracting information from images and videos. The paper starts with a broad defi- nition of computer vision, and how it can be adapted to reverse engineering. It is followed by a modest lit- erature review of cases in the maritime sector, namely photogrammetry, inspection and. Later, it describes a recent project supervised by the first author, using commercial software to re-model digitally the hull of a small sailing boat. The use of open-source tools is later mentioned, exemplified by the research con- ducted by the second author on the use of cameras as sensors for acquiring dynamic data, closing the dig- ital twin loop. A proposal for the use of image data extraction is presented at the end, as a substitute for the expensive re-sensoring of vessels in operating, in the current hype of remote operation and digital twins. We conclude by emphasizing the potential of this tech- nology for the transition from conventional to remote and autonomous operations.
Acoustic manifestations of symmetry breaking in self-similar signals
Authors: Zielinski Piotr
Published: July 2024

A gradual construction of signal based on the Weierstraß-Mandelbrot function starting from a single pure tone up to a fully developed self-similar waveform allows one to aurally perceive gain/loss of self-similarity symmetry. A numerically synthesized example involves a scaling transformation with the value of scaling factor increasing continuously from unity to the value defining the self-similarity of the full Weierstraß-Mandelbrot function. In the case of partially self-similar signals the sequence of a sequential repetition of this transformation is readily perceptible, whereas for the fully self-similar signal the repetitions manifest themselves as an ever-ascending glissando specific to Shepard tones. The usefulness of the concept of self-similarity in the condensed matter physics is discussed.
On the performance evaluation of synchronous and asynchronous parallel particle swarm optimisation
Authors: Tholen Christoph , Nolle Lars
Published: July 2024

In this work, the efficiency (time) and effectivity (fitness) of two parallel variants of Particle Swarm Optimisation (PSO) have been evaluated, the synchronous PSPSO and the asynchronous PAPSO. In this study, an implementation of PAPSO is utilised, which deviates from the master-slave principle. Instead, all particles function as independent workers, competing for the available computing resources. If a particle discovers a new best position, it shares this information with the other particles. Two well-known test functions, the Rosenbrock function and the Rastigin function, were applied for evaluating the efficiency and effectivity of PSPSO and PAPSO. Firstly, versions of the test functions with 10, 30, and 60 dimensions were used. The population size was increased for each dimensionality from 50 to 100 and finally 200 particles. The results of this set of experiments showed that both variants of PSO performed similar regarding to their effectiveness of finding the optimum solutions. The computing time used by PAPSO, on the other hand, is significantly smaller than the computing time needed by PSPSO. On average the PAPSO was 69.1 % faster than the PSPSO on the Rosenbrock function and 90.3 % faster on the Rastigin function. In a second set of simulations, the maximum waiting time was varied from 5 ms to 1,000 ms. It is shown for both algorithms, that the average computing time rises linearly with the maximum waiting time.
Global convergence limits of differential evolution algorithm
Authors: Knobloch Roman , Mlynek Jaroslav
Published: July 2024

In a recent period, evolutionary optimization techniques have been increasingly utilized for solving technical and scientific optimization tasks. The differential evolution algorithm is one of the most used optimization tools. This specific algorithm is often and in many published sources classified as a global optimizer. Such statements indicate that the differential evolution algorithm can identify the global minimum of a specific cost function. In the article, we demonstrate rigorously and in a simple way that in some special circumstances, this algorithm fails and is prone to premature convergence to a local minimum of the cost function.
Application of artificial neural network for predicting nutrient release from neem (azadirachtaindica) coated urea
Authors: Vashishtha Manish , Yadav Gaurav , Suhag Meenu , Meena Shiv Om
Published: July 2024

Population spike is driving up food consumption, while urbanization is clearly causing soil fertility to decline linearly, increasing production costs and reliance on conventional fertilizers. Alternatives, such as controlled-release fertilizers (CRF) like Neem-coated urea fertilizers (NCU) have several benefits, are required to address these issues. To forecast the release of nutrients from NCU, this labor-intensive research uses mathematical modeling, with a focus on developing and analyzing mathematical models that use ANN. Utilizing a GRNN to compute the amount of nutrients released from NCU, the contours of nitrogen release were predicted. By using a UV-Vis spectrophotometer, the nitrogen release contours were estimated experimentally in the lab. The findings demonstrated the striking similarity between the GRNN model's projected and experimental values. In addressing nonlinear prediction issues, the GRNN model performed remarkably well in creating NCU.
Lung operation training in low-cost virtual reality simulation environments
Authors: Piazzolla Pietro , Gribaudo Marco , Buttiglione Marco Domenico , Guerrera Francesco , Colombo Giorgio
Published: July 2024

Surgical operations must be preformed by skilled and qualified personnel. Training is therefore of paramount importance to master enough skill to succeeds in the tasks without endangering the health of the patients. Combining different types of training activities, can help reaching the goal in a quicker and more effective way. In this scenario, Virtual Reality represents an interesting step, particularly thanks to the reduction in the cost of the equipment that have made their adoption affordable and their availability widespread. In this work, we present our advances in training lung operations with low-cost virtual reality simulation environments.
3d weather radar network cartesian products generation framework
Authors: Szuster Piotr , Kolodziej Joanna
Published: July 2024

This paper presents a new framework for process?ing 3D-volumetric radar data that generates Cartesian products for operational and numerical weather predic?tion purposes. Transformation of a typical polar-radial coordinate system into 3D Cartesian coordinates facil?itates weather radar composition, visualisation, and as?similation. Moreover, using 3D Cartesian coordinates significantly improves the flexibility of the product generation process. Implementation of the framework generated 72 composite products in a reasonable run time.
Effective protocol for continuous pericapsular nerve group block in femur fracture patients undergoing hip surgery: two case reports
Authors: Jung Younghoon , Choi Sangmin , Lee Siyoung , Kim Nara , Kim Eunsoo
Published: July 2024

Pericapsular nerve group (PENG) block was introduced as an effective way to control postoperative pain in patients who have undergone hip surgery. Therefore, we would like to discuss how to perform PENG block accurately on the basis of two cases, both of which involved hip fracture patients. Ultrasound-guided continuous PENG block was performed, and postoperative pain was adequately controlled in both cases. To mount the catheter in the correct position, it should be inserted after the needle enters at the lowest angle possible. If it is confirmed that the psoas tendon is pushed upward without an increase in injection pressure during drug injection, an accurate continuous PENG block has been achieved. We also analyzed fluoroscopic images to determine how the drug spread, and we observed that the drug spread around the hip capsule along the iliacus and psoas muscle.
QSAR modeling of isoquinoline derivatives having AKR1C3 inhibitory activity: Lead optimization
Authors: Gopinath Papichettypalle , ranjan Dwivedi Ashish , Durgaprasad Beda , Bidhuhusan Karkara , Raghuveer Pathuri , RamReddy Godela , Rao Kasula Ramalingeswara , Ravisankara Reddy Dontireddy , Subramanyam Sibala
Published: July 2024

Aldo-keto reductase 1C3 is a promising drug target for castration-resistant prostate cancer. In the present study, quantitative structure-activity relationship studies were carried out by QSARINS software on 3-(3, 4-dihydroisoquinolin-2(1H)-yl sulfonyl) benzoic acid derivatives having AKR1C3 inhibitory activity. The developed Quantitative Structure-activity relationship (QSAR) model suggests that the descriptors play key roles and are extremely helpful in predicting bioactivity. The best model shows validated statistical values, and residual information predicts the obtained model is robust, stable, and can be utilized to the extent of a novel series of isoquinoline derivatives.
YAP/TAZ enhances P-body formation to promote tumorigenesis
Authors: Shen Xia , Peng Xiang , Guo YueGui , Dai Zhujiang , Cui Long , Yu Wei , Liu Yun , Liu Chen-Ying
Published: July 2024

The role of processing bodies (P-bodies) in tumorigenesis and tumor progression is not well understood. Here, we showed that the oncogenes YAP/TAZ promote P-body formation in a series of cancer cell lines. Mechanistically, both transcriptional activation of the P-body-related genes SAMD4A, AJUBA, and WTIP and transcriptional suppression of the tumor suppressor gene PNRC1 are involved in enhancing the effects of YAP/TAZ on P-body formation in colorectal cancer (CRC) cells. By reexpression of PNRC1 or knockdown of P-body core genes (DDX6, DCP1A, and LSM14A), we determined that disruption of P-bodies attenuates cell proliferation, cell migration, and tumor growth induced by overexpression of YAP5SA in CRC. Analysis of a pancancer CRISPR screen database (DepMap) revealed co-dependencies between YAP/TEAD and the P-body core genes and correlations between the mRNA levels of SAMD4A, AJUBA, WTIP, PNRC1, and YAP target genes. Our study suggests that the P-body is a new downstream effector of YAP/TAZ, which implies that reexpression of PNRC1 or disruption of P-bodies is a potential therapeutic strategy for tumors with active YAP.
Glycan-shielded homodimer structure and dynamical features of the canine distemper virus hemagglutinin relevant for viral entry and efficient vaccination
Authors: Fukuhara Hideo , Yumoto Kohei , Sako Miyuki , Kajikawa Mizuho , Ose Toyoyuki , Kawamura Mihiro , Yoda Mei , Chen Surui , Ito Yuri , Takeda Shin , Mwaba Mwila , Wang Jiaqi , Hashiguchi Takao , Kamishikiryo Jun , Maita Nobuo , Kitatsuji Chihiro , Takeda Makoto , Kuroki Kimiko , Maenaka Katsumi
Published: July 2024

Canine distemper virus (CDV) belongs to morbillivirus, including measles virus (MeV) and rinderpest virus, which causes serious immunological and neurological disorders in carnivores, including dogs and rhesus monkeys, as recently reported, but their vaccines are highly effective. The attachment glycoprotein hemagglutinin (CDV-H) at the CDV surface utilizes signaling lymphocyte activation molecule (SLAM) and Nectin-4 (also called poliovirus-receptor-like-4; PVRL4) as entry receptors. Although fusion models have been proposed, the molecular mechanism of morbillivirus fusion entry is poorly understood. Here, we determined the crystal structure of the globular head domain of CDV-H vaccine strain at 3.2 Å resolution, revealing that CDV-H exhibits a highly tilted homodimeric form with a six-bladed β-propeller fold. While the predicted Nectin-4-binding site is well conserved with that of MeV-H, that of SLAM is similar but partially different, which is expected to contribute to host specificity. Five N-linked sugars covered a broad area of the CDV-H surface to expose receptor-binding sites only, supporting the effective production of neutralizing antibodies. These features are common to MeV-H, although the glycosylation sites are completely different. Furthermore, real-time observation using high-speed atomic force microscopy revealed highly mobile features of the CDV-H dimeric head via the connector region. These results suggest that sugar-shielded tilted homodimeric structure and dynamic conformational changes are common characteristics of morbilliviruses and ensure effective fusion entry and vaccination.
A single-cell atlas of the miracidium larva of the human blood fluke Schistosoma mansoni: cell types, developmental pathways and tissue architecture
Authors: Attenborough Teresa , Rawlinson Kate A , Soria Carmen L Diaz , Ambridge Kirsty , Sankaranarayanan Geetha , Graham Jennie , Cotton James A , Doyle Stephen R , Rinaldi Gabriel , Berriman Matthew
Published: July 2024

Schistosomes are parasitic flatworms that cause the water-borne disease schistosomiasis, affecting millions of people worldwide. The miracidium larva of schistosomes represents the first post-embryonic stage of development and is critical to transmission. After hatching, a miracidium infects a freshwater snail and transforms into a mother sporocyst, where its stem cells generate daughter sporocysts that give rise to many human-infective cercariae larvae. To understand this important life cycle stage at the cellular and molecular levels, we have used single-cell RNA sequencing,
in situ
hybridisation and image analysis to create a whole-body cell atlas of the miracidium larva of
Schistosoma mansoni
. Our atlas shows that each miracidium is composed of ∼365 cells and 19 transcriptionally distinct cell types. We show that 93% of miracidium cells are somatic (57% neural, 19% muscle, 13% epidermal (tegument), 2% parenchyma, 2% protonephridia), and the remaining 7% are stem cells. Cellular diversity within tissue types is revealed, and is highest in neurons. There are two stem cell populations, and they show different activation and potency states. Trajectory analysis indicates that one stem cell population is the origin of the tegument lineage and the other likely contains pluripotent cells. Furthermore, each of these stem populations is transcriptionally distinct based on sex-linked gene expression in male and female larvae. Through single cell transcriptomics and
in-situ
hybridisation we identified every cell in the whole organism revealing the organisation of the miracidium. This single cell atlas provides the foundation to understand the development and interaction of cell types and tissues as they change over a life cycle that is characterised by complex morphological changes.
Presynaptic Rac1 in the hippocampus selectively regulates working memory
Authors: Kim Jaebin , Bustamante Edwin , Sotonyi Peter , Maxwell Nicholas , Parameswaran Pooja , Kent Julie K , Wetsel William C , Soderblom Erik J , Rácz Bence , Soderling Scott H
Published: July 2024

One of the most extensively studied members of the Ras superfamily of small GTPases, Rac1 is an intracellular signal transducer that remodels actin and phosphorylation signaling networks. Previous studies have shown that Rac1-mediated signaling is associated with hippocampal-dependent working memory and longer-term forms of learning and memory and that Rac1 can modulate forms of both pre- and postsynaptic plasticity. How these different cognitive functions and forms of plasticity mediated by Rac1 are linked, however, is unclear. Here, we show that spatial working memory in mice is selectively impaired following the expression of a genetically encoded Rac1 inhibitor at presynaptic terminals, while longer-term cognitive processes are affected by Rac1 inhibition at postsynaptic sites. To investigate the regulatory mechanisms of this presynaptic process, we leveraged new advances in mass spectrometry to identify the proteomic and post-translational landscape of presynaptic Rac1 signaling. We identified serine/threonine kinases and phosphorylated cytoskeletal signaling and synaptic vesicle proteins enriched with active Rac1. The phosphorylated sites in these proteins are at positions likely to have regulatory effects on synaptic vesicles. Consistent with this, we also report changes in the distribution and morphology of synaptic vesicles and in postsynaptic ultrastructure following presynaptic Rac1 inhibition. Overall, this study reveals a previously unrecognized presynaptic role of Rac1 signaling in cognitive processes and provides insights into its potential regulatory mechanisms.
Electrophysiological dynamics of salience, default mode, and frontoparietal networks during episodic memory formation and recall revealed through multi-experiment iEEG replication
Authors: Das Anup , Menon Vinod
Published: July 2024

Dynamic interactions between large-scale brain networks underpin human cognitive processes, but their electrophysiological mechanisms remain elusive. The triple network model, encompassing the salience network (SN), default mode network (DMN), and frontoparietal network (FPN), provides a framework for understanding these interactions. We analyzed intracranial electroencephalography (EEG) recordings from 177 participants across four diverse episodic memory experiments, each involving encoding as well as recall phases. Phase transfer entropy analysis revealed consistently higher directed information flow from the anterior insula (AI), a key SN node, to both DMN and FPN nodes. This directed influence was significantly stronger during memory tasks compared to resting state, highlighting the AI’s task-specific role in coordinating large-scale network interactions. This pattern persisted across externally driven memory encoding and internally governed free recall. Control analyses using the inferior frontal gyrus (IFG) showed an inverse pattern, with DMN and FPN exerting higher influence on IFG, underscoring the AI’s unique role. We observed task-specific suppression of high-gamma power in the posterior cingulate cortex/precuneus node of the DMN during memory encoding, but not recall. Crucially, these results were replicated across all four experiments spanning verbal and spatial memory domains with high Bayes replication factors. Our findings advance understanding of how coordinated neural network interactions support memory processes, highlighting the AI’s critical role in orchestrating large-scale brain network dynamics during both memory encoding and retrieval. By elucidating the electrophysiological basis of triple network interactions in episodic memory, our study provides insights into neural circuit dynamics underlying memory function and offer a framework for investigating network disruptions in memory-related disorders.
Electrophysiological dynamics of a triple network model of cognitive control: A multi-experiment replication
Authors: Das Anup , Menon Vinod
Published: July 2024

Dynamic interactions between large-scale brain networks are thought to underpin human cognitive processes, but their underlying electrophysiological dynamics remain unknown. The triple network model, which highlights the salience, default mode, and frontoparietal networks, provides a fundamental framework for understanding these interactions. To unravel the electrophysiological mechanisms underlying these network dynamics, we utilized intracranial EEG recordings from 177 participants across four distinct memory experiments. Our findings revealed a consistent pattern of directed information flow from the anterior insula, a key node of the salience network, to both the default mode and frontoparietal networks. Notably, this pattern of information transmission was observed regardless of the nature of the tasks, whether they involved externally driven stimuli during encoding or internally governed processes during free recall. Moreover, the directed information flow from the anterior insula to the other networks was present irrespective of the activation or suppression states of individual network nodes. Furthermore, we observed a specific suppression of high-gamma power in the posterior cingulate cortex/precuneus node of the default mode network during memory encoding, but not recall, suggesting a task-specific functional down-regulation of this region. Crucially, these results were reliably replicated across all four experiments, underscoring the robustness and generalizability of our findings. Our study significantly advances the understanding of how coordinated neural network interactions underpin cognitive operations and highlights the critical role of the anterior insula in orchestrating the dynamics of large-scale brain networks. These findings have important implications for elucidating the neural basis of cognitive control and its potential disruptions in various neurological and psychiatric disorders.
Radiation Pattern Correction of Faulty Planar Phased Array using Genetic Algorithm
Authors: B. Saleem R. A. , Shah A. A. , Munsif H. , Najam A. I. , Khattak S. , Ullah I.
Published: July 2024

The probability of antenna array failure or malfunctioning cannot be ruled out, and hardware replacement of faulty elements is not always a viable solution. Therefore, academic and industrial interest in self-healing phased arrays are on the rise. In this work, the phase-only genetic algorithm (GA) optimization flow for the radiation pattern correction of a 4 × 4 phase faulty planar antenna array is proposed. Initially, a reference array pattern at the desired scan angle is generated. Then random phase faults are introduced across the 1 × 4 antenna elements in any one of 4 sub-arrays to produce maximum distortion in the reference radiation pattern of 4 × 4 planar array. The proposed GA re-computes the new excitation weights for the remaining non-faulty 3 sub-arrays to correct the overall radiation pattern of 4 × 4 array. This is achieved by calculating the array output power for reference and GA computed weights. The GA corrected patterns fairly follow the desired array patterns in terms of peak gain and reducing sidelobe levels for the desired scan angle. The efficiency of the optimized radiation patterns was evaluated in full-wave HFSS model and measurements validation. In this way, maintenance cost can be reduced with recovery of acceptable level of radiation pattern using software instead of physically replacing faulty antenna elements in the array.
Meniscus injury prediction model based on metric learning
Authors: Wang Yu , Liang Yiwei , Wang Guangjun , Wang Tao , Xu Shu , Yang Xianjun , Sun Yining , Ding Zenghui
Published: July 2024

A meniscus injury is a prevalent condition affecting the knee joint. The construction of a subjective prediction model for meniscus injury represents a potentially invaluable diagnostic tool for physicians. Nevertheless, given the variability of pathological manifestations among individual patients, machine learning-based models may produce errors when attempting to predict specific medical records. In order to mitigate this issue, the present study suggests the incorporation of metric learning within the machine learning (ML) modelling process, with the aim of reducing the intra-class spacing of comparable samples and thereby enhancing the classification accuracy of individual medical records. This work has not yet been attempted in the field of knee joint prediction. The findings demonstrate that the adoption of metric learning produces better optimal outcomes. Compared to machine learning baseline models, F1 was increased by 2%.
Evaluation of in-house dengue real-time PCR assays in West Java, Indonesia
Authors: Kinanti Denti R. , Ahmad Intan , Putra Ramadhani , Yusmalinar Sri , Wibowo Indra , Anggraeni Tjandra , Dwiartama Angga , Tjia Tommy Octavianus Soetrisno , Destiani Putri Cahya , Khoirunnisa Karimatu , Tu Wu-Chun , Neoh Kok-Boon , Apip Rosye Arosdiani , Raksanagara Ahyani , Dewi Jani Ira , Tisnawati Yeppi , Warisman Aan , Rostiana Tita , Fibriani Azzania
Published: July 2024

Dengue is an infectious disease caused by infection of dengue virus (DENV) transmitted by Aedes aegypti and Aedes albopictus. In Indonesia, dengue commonly occurs with an increasing incidence rate annually. It is known that early detection of dengue infection is one of the keys to controlling this disease outbreak. Rapid and accurate early detection to diagnose dengue can be achieved by molecular tests, one of which is through a real-time PCR method. However, real-time PCR assay for dengue developed based on Indonesian DENV sequences has not been available. Therefore, we developed in-house dengue real-time PCR (SYBR- and TaqMan-based) assays and evaluated those assays in routine clinical testing in the community. These assays target the 3′ UTR region of the four DENV serotypes and was found to be specific for DENV. The most sensitive assay was the TaqMan assay with the LOD95% of 482 copy/ml, followed by the SYBR assay with the LOD95% of 14,398 copy/ml. We recruited dengue suspected patients from three primary health care services in West Java, Indonesia to represent the community testing setting. Dengue infection was examined using the two in-house real-time PCR assays along with NS1, IgM, and IgG rapid diagnostic tests (RDT). In total, as many as 74 clinical specimens of dengue suspected patients were included in this study. Among those patients, 21 were positive for TaqMan assay, 17 were positive for SYBR assay, nine were positive for NS1 test, six were positive for both IgG and IgM tests, and 22 were positive for IgG test only. Compared with our in-house TaqMan assay, the sensitivity of NS1 test, IgM test, and IgG test were 42.86%, 14.29%, and 28.57% respectively. Among these three RDT tests, NS1 showed 100% specificity. Thus, our study confirmed that NS1 test showed high specificity, indicating that a positive result of NS1 can be confidently considered a dengue case. However, NS1, IgM, and IgG tests with RDT are not enough to diagnose a dengue case. We suggest applying the high sensitivity and specificity rRT-PCR test as the gold standard for early detection and antibody test as a follow-up test for rRT-PCR negative cases.
Compelling Classroom Accumulation and Harmonious Teaching of Public Elementary School Teachers
Authors: Nugas Marilou M. , Baguio Josephine B.
Published: July 2024

This study investigated the relationship between compelling classroom accumulation and harmonious teaching practices among public elementary school teachers in Manay District, Davao Oriental. The research employed a non-experimental quantitative design with a correlational approach. A total of 132 teachers from public elementary schools participated through universal sampling. Data analysis involved calculating means, Pearson's r correlation coefficient, and regression analysis. The findings revealed that both compelling classroom accumulation (encompassing vision, sensitivity, needs awareness, and risk-taking) and harmonious teaching (characterized by supportive, instructive, preventive, and responsive practices) were frequently observed among the teachers. Additionally, a statistically significant positive relationship was identified between these two factors. The study further suggests that the various aspects of compelling classroom accumulation significantly influence the development of harmonious teaching practices among the educators in Manay District. Based on these results, public elementary school teachers are encouraged to participate in conferences and training programs offered by DepEd. These professional development opportunities can equip teachers with the necessary skills to enhance their abilities, improve student learning opportunities, and implement more effective teaching practices.
Project-based Learning Model for Freestyle Swimming Education at the Faculty of Teacher Training and Education, Universitas Megarezky
Authors: Rusli Kurnia , Talib Syamsul Bachri , Ikhsan Andi
Published: July 2024

This study aimed to develop a project-based learning (PBL) model for freestyle swimming in the Physical Education Department of Megarezky University's Faculty of Teacher Training and Education, which was developed through a series of stages, including analysis, design, development, implementation, and evaluation. In this study, 30 students and 5 lecturers were selected as samples using purposive sampling techniques. Data were collected through surveys, interviews, and observations, and analyzed using descriptive analysis and content analysis. The results show that the PBL model can enhance students' skills and abilities in freestyle swimming, improve their learning outcomes, and promote active and independent learning. Additionally, the model can assist lecturers in teaching more effectively and improving the quality of freestyle swimming education. In conclusion, the PBL model for freestyle swimming can be an alternative to improve student's learning outcomes in freestyle swimming education, with significant advantages, such as enhancing students' critical thinking and problem-solving skills and improving the quality of freestyle swimming education. The research findings indicate that the PBL model has high validity, practicality, and effectiveness in improving students' learning outcomes in freestyle swimming. Therefore, efforts should be made to optimize the use of this model in freestyle swimming education and conduct further research to develop the model further and apply it to various contexts.
Interdisciplinary Applications of AI: Dermatology and Psychology
Authors: Shek Nova , Lee Eunseo , Lee Grace , Ko Hayden , Lee Eugene
Published: July 2024

Artificial Intelligence (AI) is profoundly transforming interdisciplinary domains like dermatology and psychology, providing revolutionary possibilities in the areas of diagnosis, treatment, and patient care. AI-driven solutions in dermatology are improving diagnostic accuracy by analyzing medical photos to identify skin disorders such as melanoma with a level of precision comparable to that of professional dermatologists. These technologies utilize machine learning algorithms that have been trained on extensive datasets to detect minor patterns and anomalies in skin lesions. This enables the early detection of skin conditions and the creation of personalized treatment strategies. Moreover, artificial intelligence (AI) assists in optimizing the efficiency of workflows, minimizing diagnostic inaccuracies, and enhancing the availability of dermatological treatment, particularly in places with limited access to healthcare services. Within the field of psychology, artificial intelligence (AI) has a significant influence. It is utilized to assess individuals' mental well-being by analyzing their text and speech patterns, employing techniques such as natural language processing and sentiment analysis. Artificial intelligence algorithms have the capability to observe and analyze patient interactions, offering immediate and accurate observations regarding emotional states and possible psychological illnesses. The incorporation of AI enables more precise evaluations and prompt actions, enhancing conventional therapeutic methods. In addition, chatbots and virtual therapists that utilise artificial intelligence provide instant assistance and ongoing supervision, thereby extending the accessibility of mental health care. The integration of AI with dermatology and psychology not only improves diagnostic skills and treatment results but also highlights the significance of interdisciplinary collaboration in advancing healthcare. By using artificial intelligence (AI), these industries can utilize data-driven analysis to provide more accurate, tailored, and easily accessible healthcare, thereby enhancing patient results and quality of life.
Everything smells like poo, landfill, and rotten food”: A retrospective case report using Clinical Emotional Freedom Techniques (EFT) for parosmia following COVID-19
Authors: Boath Elizabeth ,   Staffordshire University: Stoke-on-Trent, Staffordshire, GB, Philpott Carl ,   University of East Anglia: Norwich, Norfolk, GB
Published: July 2024

Abstract: Parosmia is a disorder of scent that has affected millions of people worldwide following their recovery from COVID-19. Parosmia post COVID-19 can be long-term and has a negative impact on quality of life. Despite this there is limited evidence for effective treatment strategies. This retrospective case report details the use of Clinical Emotional Freedom Techniques (EFT) to address parosmia following COVID-19 with a single client over three sessions. The sessions addressed specific food, drink, and odors that were having a major negative impact on the client’s quality of life, psychological well-being, physical health, weight, and relationships. By the end of the three sessions, the client was able to tolerate certain scents and eat foods that the client selected to tap on. The client’s quality of life improved to the point where she was able to eat, go out to restaurants, socialize, and ultimately return to work. Whether EFT can be successfully applied to other people experiencing parosmia following COVID-19 or parosmia caused by other conditions is not clear and requires further research. Keywords: parosmia, sense of smell, COVID-19, Clinical Emotional Freedom Techniques, EFT
Energy psychology for social anxiety and erythrophobia: A case study
Authors: Pujo Annick
Published: July 2024

Background: The intense fear of blushing in public (erythrophobia) is part of the spectrum of social anxiety that affects between 3% and 13% of the population. This phobia can be very debilitating for those who suffer from it. It may stem from a difficult childhood marked by educational attitudes based on shame and humiliation as well as repeated traumatic experiences. Object: The aim here is to explain in detail how the energy psychology techniques Clinical EFT (the manualized form of Emotional Freedom Techniques) and Energetic Memory Reconsolidation Therapy function in practice, as applied to “Jeanne,” a young woman suffering from social anxiety and erythrophobia following a chaotic start in life. Method and setting: The therapeutic plan was drawn up on the theoretical basis of the scientific literature on energy psychology, which has produced convincing results in the treatment of trauma and anxiety. The therapy was threefold: (a) learning to manage anxiety autonomously using Clinical EFT, (b) trauma treatment using Energetic Memory Reconsolidation Therapy, and (c) psycho-education. Jeanne had a total of 15 sessions, two of which are detailed here to illustrate the work. At the start of each session, the SUD (Subjective Units of Distress) scale was used to rate the level of blushing anxiety (the scale ranges from 0 to 10, with 0 being no distress and 10 being the most imaginable). Results: The level of anxiety decreased from 9/10 to 3/10 between the first and last sessions. In addition, the number of problem situations encountered (blushing having generated negative emotions) dropped from 5 per week to 0 per week between the beginning and end of therapy. Jeanne’s goal of not blushing at her wedding was achieved. She was able to experience the event without worrying about or even thinking about the anxiety. Conclusion: Psychotherapy based on energy techniques enabled me to treat Jeanne’s social anxiety and erythrophobia in depth by targeting the sources while giving her access to an emotional regulation tool to use independently: Clinical EFT. Keywords: erythrophobia, fear of blushing, social anxiety, Emotional Freedom Techniques, Clinical EFT, Memory Reconsolidation, Matrix Reimprinting
Anomaly patterns about strong convective events in the tropics and midlatitudes: Observations from radiosondes and surface weather stations
Authors: Mitovski Toni , Folkins Ian
Published: December 2013

We use 13 years (1998–2010) of rainfall estimates from the Tropical Rainfall Measuring Mission to identify high rain events located close to radiosondes. This is done in four regions: the Western Tropical Pacific, Tropical Brazil, Southeast China, and Southeast U.S. We then construct composite anomaly patterns of temperature, relative humidity, surface pressure, convective available potential energy (CAPE), geopotential height, mass divergence, relative vorticity, and potential vorticity about these high rain events. One motivation of this analysis is to identify regional differences in the interaction between strong convective events and the background atmosphere. We find, overall, that the changes in meteorological variables which occur during the evolution of strong convective events in midlatitudes are similar to the changes that occur in the tropics. In midlatitudes, however, strong convective events are associated with stronger anomalies in surface pressure and geopotential height and exhibit a warm anomaly in the lower troposphere prior to peak rainfall. In the Southeast U.S., the near‐surface layer of positive CAPE that occurs prior to high rain events is thicker than in the Western Tropical Pacific. In the two midlatitude regions, the midlevel potential vorticity maximum that develops during the growth stage of high rain events acquires a downward tilt toward the surface during the decay stage, suggesting downward transport toward the surface. A conceptual model previously used to interpret the anomaly patterns of the 2 day equatorial wave is used to interpret the anomaly patterns associated with more general types of high rain events in the tropics.
Selbstorganisation und Bildung von (Hydro‐)Gelen durch kooperative π‐π‐Wechselwirkungen und unkonventionelle C‐H⋅⋅⋅X‐Wasserstoffbrücken
Authors: Rest Christina , Mayoral María José , Fucke Katharina , Schellheimer Jennifer , Stepanenko Vladimir , Fernández Gustavo
Published: December 2013

Schwache C‐H⋅⋅⋅X‐Wasserstoffbrücken stellen bedeutende stabilisierende Kräfte im Bereich des Kristall‐Engineerings und der Anionenerkennung in Lösung dar, doch ihr quantitativer Einfluss auf die Stabilisierung von supramolekularen Polymeren oder Gelen blieb bislang unerforscht. Hier berichten wir von einem Oligophenylenethinylen(OPE)‐basierten, amphiphilen PtII‐Komplex, der in der Lage ist, in wässrigem sowie polarem Medium supramolekulare, polymere Strukturen zu bilden. Dieser Selbstorganisationsprozess wird durch π‐π‐ und verschiedene schwache C‐H⋅⋅⋅X‐Wechselwirkungen induziert, unter Einbeziehung von am PtII‐Zentrum gebundenen Chloratomen, sowie von Sauerstoffatomen und polarisierten Methylengruppen der peripheren Glykolketten. Mithilfe verschiedener experimenteller Verfahren (UV/Vis‐, 1D‐ und 2D‐NMR‐Spektroskopie, DLS, AFM, SEM und Röntgenbeugung) kann gezeigt werden, dass das Zusammenspiel von verschiedenen schwachen, nichtkovalenten Wechselwirkungen zu einer kooperativen Bildung von eindimensionalen, selbstorganisierten Strukturen und Gelen führt, wobei die molekulare Anordnung auch im kristallinen Zustand erhalten bleibt.
Rhodium(III)‐Catalyzed ortho Alkenylation of N‐Phenoxyacetamides with N‐Tosylhydrazones or Diazoesters through CH Activation
Authors: Hu Fangdong , Xia Ying , Ye Fei , Liu Zhenxing , Ma Chen , Zhang Yan , Wang Jianbo
Published: December 2013

A coupling reaction of N‐phenoxyacetamides with N‐tosylhydrazones or diazoesters through RhIII‐catalyzed CH activation is reported. In this reaction, ortho‐alkenyl phenols were obtained in good yields and with excellent regio‐ and stereoselectivity. Rh–carbene migratory insertion is proposed as the key step in the reaction mechanism.