bluuebunny/crossref_metadata_2025 huggingface dataset:
Analisis Dinamik Model Penyebaran Rumor Ignorances-Discussant-Spreader-Remover (IDSR) pada Jejaring Sosial
Authors: Darajat Pangestuti Prima , Robby Rizka Rizqi , Rasikhun Hady , Ikawati Deasy Sandhya Elya
Published: July 2023

Penyebaran rumor memberikan banyak dampak negatif pada kehidupan sosial masyarakat. Karakteristik penyebaran rumor perlu dipelajari untuk mendapatkan informasi ilmiah sekaligus menentukan strategi pengendalian yang tepat. Pada penelitian ini dikontruksi model penyebaran rumor Ignorances-Discussant-Spreader-Remover  (IDSR) dengan memperhatikan faktor pemberian pernyataan balasan. Pada model dilakukan analisis dinamik dengan menentukan titik kesetimbangan, eksistensi, serta kestabilan lokal titik kesetimbangan tersebut. Diperoleh bahwa, titik kesetimbangan bebas rumor eksis dengan kriteria kestabilan tertentu. Sementara itu dua titik kesetimbangan lain memiliki syarat eksistensi dan ditentukan syarat kestabilannya menggunakan kriteria kestabilan Routh-Hurwitz. Simulasi numerik dilakukan menggunakan metode rungge-kutta orde 4 dan software MATLAB untuk menggambarkan karakteristik masing-masing titik kesetimbangan tersebut serta membuktikan analisa teoritis yang dilakukan.
Pozzolanic properties of marble industrial waste and its used in concrete
Authors: Handayani Agil Fitri , Muhammad Dzul Fikri , Hidayatullah Muhammad Arif , Sari Ninda Lufita
Published: July 2023

Concrete needs to use alternative materials to reduce cement content to limit the effect of carbon emissions. Marble dust as a waste of the marble industry has very fine grains. X-Ray Fluorescence (X-RF) method was conducted to determine the mineral properties of marble dust. Marble dust was found to contain 98.62% Calcium Oxide (CaO), 0.17% Sulfur Trioxide (SO3) and some elements in small levels. To determine the impact of marble dust on the mechanical characteristics of concrete, an experimental study was conducted. Test specimens were made with four different levels of marble dust, namely 0%, 5%, 10%, and 15%. The experimental results showed that the optimum usage was 6.62% by weight of cement which gave the advantage of increasing the compressive strength of concrete by 11.77%.
Analisis Sentiment di Twitter terhadap Anies Baswedan sebagai Bakal Calon Presiden 2024 Menggunakan Metode K-Nearest Neighbor
Authors: Febriansyah Indra , Fikry Muhammad , Yusra
Published: July 2023

Anies Baswedan menjadi tokoh politik yang paling banyak diperbincangkan di Twitter. Banyaknya opini masyarakat di Twitter dapat dimanfaatkan untuk memperoleh gambaran positif dan negatif dengan melakukan analisis sentimen. Penelitian ini bertujuan untuk menerapkan metode K-Nearest Neighbor dalam melakukan analisis sentimen di Twitter terhadap Anies Baswedan sebagai bakal calon presiden 2024. Data tweet yang digunakan berjumlah 3.400 tweets dengan 2.130 label positif dan 1.270 label negatif. Pengujian model K-Nearest Neighbor menggunakan metode 10-fold cross validation dilakukan dengan dua eksperimen, yaitu pengujian tanpa seleksi fitur dan pengujian menggunakan seleksi fitur threshold pada nilai Document Frequency (DF). Metode K-Nearest Neighbor menghasilkan model dengan performa terbaik pada pengujian menggunakan seleksi fitur DF threshold, dengan kombinasi parameter nilai k = 14 dan DF threshold bernilai 12 memperoleh nilai akurasi sebesar 87,35%, presisi sebesar 87,39%, recall sebesar 85,3%, dan f1 score sebesar 86,13%.
ANALISIS WACANA ASPEK KOHESI GRAMATIKAL REFEREN TERJEMAHAN ALQURAN SURAT AT-THALAQ: TEKNIK DAN KUALITAS PENERJEMAHAN
Authors: Mufida Aghnia
Published: July 2023

Terjemahan Alquran, khususnya dalam bahasa Indonesia, sangat berguna untuk membantu masyarakat muslim di Indonesia dalam memahami kitab sucinya. Penelitian ini akan membahas tentang terjemahan Alquran versi penerbit Kementerian Agama Republik Indonesia (KEMENAG RI) tahun 2014, lebih khususnya variasi unsur kohesi gramatikal referen yang terdapat dalam surat At-Thalaq, teknik penerjemahan yang digunakan, serta kualitas terjemahannya, dengan menggunakan metode kualitiatif deskriptif. Hasil penelitian menyatakan bahwa terdapat tiga jenis referen, yaitu personal, demonstratif dan komparatif dengan tujuh macam teknik penelitian; teknik penerjemahan harfiah, padanan lazim, generalisasi, amplifikasi, kalke, amplifikasi linguistik dan kompensasi. Pada tingkat keakuratan dan keterbacaan terjemah, hasil terjemahan pada penelitian ini tergolong akurat dan tingkat terbaca sedang.
Efektivitas penggunaan permainan domino dalam meningkatkan kemampuan menghafal mufrodat bagi siswa kelas 8 Mts Miftahul Ulum mojokerto
Authors: Irfan Chudlori
Published: July 2023

Mufrodat yang memadai dapat mendukung kemampuan seseorang untuk berkomunikasi dalam bahasa Arab. Salah satu faktor yang menyebabkan kurangnya kemampuan Mufrodat adalah guru cenderung monoton dalam mentransfer materi kepada siswa. maka siswa akan mudah bosan dan siswa dengan cepat melupakan kosakata yang baru diterima. Ada pengembangan strategi pendidikan kosa kata pendidikan yang bertujuan untuk memperoleh pendidikan bahasa Arab yang efektif yaitu Permainan Domino dalam pengajaran bahasa Arab. Penenilitian ini bertujuan untuk mengungkap kemampuan siswa dalam pemerolehan pembelajaran kosakata dengan menggunakan strategi domino dan mengungkap perbedaan yang signifikan antara kemampuan siswa yang mempelajari kosakata menggunakan strategi Domino dan kekampuan siswa mempelajari kosakata tanpa menggunakan strategi Domino. Penelitian ini menggunakan pendekatan kuantitatif dengan jenis penelitian eskperimen semu. Adapun sampel data dari penelitian ini berjumlah 54 siswa dari kelas 8 (B) dan (D) di Madrasah Miftahul Ulum Mojokerto. Peneliti menggunakan Uji Mann Whitney dan Wilcoxon untuk mengetahui perbedaan dan pengaruhnya dalam penggunaan strategi Domino pada pembelajaran kosakata untuk siswa di Madrasah Miftahul Ulum Mojokerto. Setelah menganalisis data, peneliti memperoleh Nilai Asymp.Sig 0,001. Setelah perhitungan, hasil 0,001 < 0,05. Hal ini menerangkan bahwa hipotesis alternatif (Ha) diterima dan hipotesis nol (Ho) ditolak. Artinya penggunaan permainan domino lebih efektif dari pada pembelajaran menggunakan metode konvensional.
TEACHING VOCABULARY IN UNIVERSITY CONTEXT : A CASE STUDY
Authors: Lestari Asti Ramadhani Endah
Published: July 2023

This study aimed at investigating the classroom activities in vocabulary learning. The researcher tries to analysed the factors affecting the successfulness of vocabulary learning. This study used a case study method by adapting a model proposed by Miles and Huberman. The subject of this study is students and lecturer in vocabulary classroom. The students take the vocabulary classroom in the 3rd semester. There were 38 students and one lecturer involved in this study. The result of this study proved that there are several factors affecting the effectiveness of vocabulary learning, such as syllabus, learning methods and techniques, materials and media of learning, the role of teachers and students, and also motivation.
Geosciences and the Energy Transition
Authors: Gardiner Nicholas J. , Roberts Jennifer J. , Johnson Gareth , Smith Daniel J. , Bond Clare E. , Knipe Rob , Haszeldine Stuart , Gordon Sarah , O’Donnell Megan
Published: July 2023

A substantial and rapid decarbonisation of the global economy is required to limit anthropogenic climate change to well below 2°C average global heating by 2050. Yet, emissions from fossil fuel energy generation—which dominate global greenhouse gas emissions—are at an all-time high. Progress and action for an energy transition to net zero carbon is critical, and one in which geoscience sectors and geoscientists will play multiple roles. Here, we outline the landscape of the geosciences and the energy transition in the context of the climate crisis, and intergovernmental policies on climate and social justice. We show how geoscience sectors, skills, knowledge, data, and infrastructure, both directly and indirectly, will play a key role in the energy transition. This may be in the responsible sourcing of raw materials for low carbon energy technologies; in the decarbonisation of heating; and in the near-permanent geological capture and storage of carbon through novel technology development. A new and unprecedented challenge is to reach Geological Net Zero, where zero carbon emissions from geological resource production and consumption are achieved via permanent geological storage. We identify overarching and cross-cutting issues for a sustainable and fair net zero carbon energy transition, and the associated geoscience challenges and opportunities. Finally, we call for geoscience professionals to recognise and take responsibility for their role in ensuring a fair and sustainable energy transition at the pace and scale required.
Stability and machine learning applications of persistent homology using the Delaunay-Rips complex
Authors: Mishra Amish , Motta Francis C.
Published: July 2023

Persistent homology (PH) is a robust method to compute multi-dimensional geometric and topological features of a dataset. Because these features are often stable under certain perturbations of the underlying data, are often discriminating, and can be used for visualization of structure in high-dimensional data and in statistical and machine learning modeling, PH has attracted the interest of researchers across scientific disciplines and in many industry applications. However, computational costs may present challenges to effectively using PH in certain data contexts, and theoretical stability results may not hold in practice. In this paper, we define, implement, and investigate a simplicial complex construction for computing persistent homology of Euclidean point cloud data, which we call the Delaunay-Rips complex (DR). By only considering simplices that appear in the Delaunay triangulation of the point cloud and assigning the Vietoris-Rips weights to simplices, DR avoids potentially costly computations in the persistence calculations. We document and compare a Python implementation of DR with other simplicial complex constructions for generating persistence diagrams. By imposing sufficient conditions on point cloud data, we are able to theoretically justify the stability of the persistence diagrams produced using DR. When the Delaunay triangulation of the point cloud changes under perturbations of the points, we prove that DR-produced persistence diagrams exhibit instability. Since we cannot guarantee that real-world data will satisfy our stability conditions, we demonstrate the practical robustness of DR for persistent homology in comparison with other simplicial complexes in machine learning applications. We find in our experiments that using DR in an ML-TDA pipeline performs comparatively well as using other simplicial complex constructions.
Finite element analysis of biomechanical effects of mineralized collagen modified bone cement on adjacent vertebral body after vertebroplasty
Authors: Yang Cunheng , Wang Fumin , Huang Xingxing , Zhang Hao , Zhang Meng , Gao Junxiao , Shi Shengbo , Wang Fuyang , Yang Fangjun , Yu Xiaobing
Published: July 2023

Objective: To investigate whether mineralized collagen modified polymethyl methacrylate (MC-PMMA) bone cement impacts the implanted vertebral body and adjacent segments and the feasibility of biomechanical properties compared with common bone cement in the treatment of osteoporotic vertebral compression fractures (OVCF).

Methods: A healthy volunteer was selected to perform a three-dimensional reconstruction of the T11-L1 vertebral body to establish the corresponding finite element model of the spine, and the changes in the stress distribution of different types of cement were biomechanically analyzed in groups by applying quantitative loads.

Results: The stress distribution of the T11-L1 vertebral body was similar between the two bone types of cement under various stress conditions.

Conclusion: Mineralized collagen modified bone cement had the advantages of promoting bone regeneration, good biocompatibility, good transformability, and coupling, and had support strength not inferior to common PMMA bone cement, indicating it has good development prospects and potential.
Polymer-based nanosystems and their applications in bone anticancer therapy
Authors: Nafo Wanis
Published: July 2023

The mortality rate of bone cancer has witnessed a substantial reduction in recent years, all thanks to the advent of advanced cancer treatment modalities such as surgical intervention, radiation, and chemotherapy. Nevertheless, these popular modalities come with a set of clinical challenges, including non-specificity, side effects, and drug intolerance. In recent years, polymer-based nanosystems have emerged as a promising solution in bone anti-cancer therapy by virtue of their unique physical and chemical properties. These nanosystems can be tailored for use in different drug release mechanisms for therapeutic implementations. This review delves into the efficacy of these therapy applications in bone cancer (with a focus on one of the most common types of cancers, Osteosarcoma) treatment and their correlation with the properties of polymer-based nanosystems, in addition to their interaction with the tumor microenvironment and the biological milieu.
Describing complex interactions of social-ecological systems for tipping point assessments: an analytical framework
Authors: Froese Rebecca , Andrino Alberto , Giudice Renzo , Stuch Benjamin , Kilian Salas Simone , Böhner Jürgen , Boy Diana , Boy Jens , Brown Foster , Díaz García Elisa , Figueroa Diana , Frör Oliver , Guggenberger Georg , Horn Marcus A. , Hasson Shabeh ul , Jung Christopher , Lagneaux Elisabeth G. , Meurer Katharina H. E. , Pinzón Cuellar Claudia , Schaldach Rüdiger , Ribeiro Sabina Cerruto , Schilling Janpeter , Schmidt Fernando A. , Schönenberg Regine , Selaya Galia , Vega Claudia M. , Vetter Vanessa M. S. , Villavicenio Miguel , Callo-Concha Daniel , Jansen Merel , Jungkunst Hermann F.
Published: July 2023

Humans play an interconnecting role in social-ecological systems (SES), they are part of these systems and act as agents of their destruction and regulation. This study aims to provide an analytical framework, which combines the concept of SES with the concept of tipping dynamics. As a result, we propose an analytical framework describing relevant dynamics and feedbacks within SES based on two matrixes: the “tipping matrix” and the “cross-impact matrix.” We take the Southwestern Amazon as an example for tropical regions at large and apply the proposed analytical framework to identify key underlying sub-systems within the study region: the soil ecosystem, the household livelihood system, the regional social system, and the regional climate system, which are interconnected through a network of feedbacks. We consider these sub-systems as tipping elements (TE), which when put under stress, can cross a tipping point (TP), resulting in a qualitative and potentially irreversible change of the respective TE. By systematically assessing linkages and feedbacks within and between TEs, our proposed analytical framework can provide an entry point for empirically assessing tipping point dynamics such as “tipping cascades,” which means that the crossing of a TP in one TE may force the tipping of another TE. Policy implications: The proposed joint description of the structure and dynamics within and across SES in respect to characteristics of tipping point dynamics promotes a better understanding of human-nature interactions and critical linkages within regional SES that may be used for effectively informing and directing empirical tipping point assessments, monitoring or intervention purposes. Thereby, the framework can inform policy-making for enhancing the resilience of regional SES.
Strength is relevant: experimental evidence of strength as a marker of commitment
Authors: Boulat Kira , Maillat Didier
Published: July 2023

When relevance theory tried to express the underlying processes involved during interpretation, Sperber and Wilson posited a process of context elaboration in which interpretation is seen as a path of least effort leading to the selection of a set of most salient contextual assumptions and implications. In this view, contextual assumptions are not randomly scattered in the hearer's cognitive environment during this context elaboration process. Instead, Relevance Theory claims that there are some organizing principles ordering contextual assumptions and determining which assumptions will be more likely to be accessed first in the process. The focus of this paper is on one such organizing principle captured by the notion of strength. Sperber and Wilson define it as the degree of confidence with which an assumption is held. While this notion has been posited right from the early days of Relevance theory, it has been left relatively untouched in relevance-theoretic accounts. In this paper, we will assess the explanatory potential of the notion of strength by linking it to the much-debated range of phenomena understood as related to commitment, i.e., the degree of speaker involvement in the truth of their utterance. Our goal will be to argue for a theoretical account of strength, in which strength is regarded as a cognitive marker of commitment, and more generally of the epistemic value of an utterance. In order to support this claim, we will present a series of original experimental designs in which we manipulated the level of speaker commitment in the information conveyed by their utterance. We predicted, on the basis of the theoretical model put forward, that such a manipulation would impact the level of strength. This cognitive effect, it is claimed, can in turn be measured through a recall task. We present results which support this model and discuss its implications.
Webcam-use in the NICU-setting from the perspective of Health Care Professionals and its implication for communication with parents
Authors: Stümpel Johanne , Dörrhöfer Annika , Mantell Pauline , Jannes Christiane , Reimer Alinda , Woopen Christiane
Published: July 2023

Background

In Germany, a growing number of neonatal intensive care units (NICUs) are equipped with webcams. The utilization of webcams in the NICU is gaining greater attention and the impact of this technology can be manifold. However, there has been no definite understanding of its impact. We will highlight the webcam's implications on the communication between parents and Health Care Professionals (HCPs) in German NICUs.

Methods

20 interviews were conducted with HCPs from three German NICUs between December 2019 and August 2020 according to a qualitative research design. Seven out of them had no webcam experience, whereas for 13 of them, webcam-use is part of their working routine. Interviews were analyzed following Kuckartz's thematic analysis. Findings were assessed in accordance with the NICU Communication Framework.

Results

HCPs consider the webcams as a beneficial addition to the interaction of parents with their infants, as well as the HCP-parent interaction. At the same time, HCPs created new pathways of communication with parents via the webcam. Any negative effects feared by HCPs without webcam experience regarding the communication with parents, including a lasting shift of conversation away from the infant and toward more technical aspects of the webcams, but also an increase in phone calls from parents and an associated increase in workload, could not be confirmed by HCPs with webcam experience.

Conclusion

The findings indicate that the implementation of webcams in German NICUs not only has an influence on the communication between parents and HCPs, but it expands communicative pathways. It can be stated that they support tailored communication but are not necessarily sufficient to account for all aspects themselves. The results of this study help to assess the impact of webcams on communication between parents and HCPs and should be applied to strengthen it within NICUs equipped with webcams.

Clinical trial registration

The Neo-CamCare Study is registered at the German Clinical Trial Register. DRKS-ID: DRKS0001775; Date of registration: 05/09/2019.
Automatized localization of induced geothermal seismicity using robust time-domain array processing
Authors: Hering Philip , Lindenfeld Michael , Rümpker Georg
Published: July 2023

The surveillance of geothermal seismicity is typically conducted using seismic networks, deployed around the power plants and subject to noise conditions in often highly urbanized areas. In contrast, seismic arrays can be situated at greater distances and allow monitoring of different power plants from one central location, less affected by noise interference. However, the effectiveness of arrays to monitor geothermal reservoirs is not well investigated and the increased distance to the source coincides with a decreased accuracy of the earthquake localizations. It is therefore essential to establish robust data processing and to obtain precise estimates of the location uncertainties. Here, we use time-domain array data processing and solve for the full 3-D slowness vector using robust linear regression. The approach implements a Biweight M-estimator, which yields stable parameter estimates and is well suited for real-time applications. We compare its performance to conventional least squares regression and frequency wavenumber analysis. Additionally, we implement a statistical approach based on changepoint analysis to automatically identify P- and S-wave arrivals within the recorded waveforms. The method can be seen as a simplification of autoregressive prediction. The estimated onsets facilitate reliable calculations of epicentral distances. We assess the performance of our methodology by comparison to network localizations for 77 induced earthquakes from the Landau and Insheim deep-geothermal reservoirs, situated in Rhineland-Palatinate, Germany. Our results demonstrate that we can differentiate earthquakes originating from both reservoirs and successfully localize the majority of events within the magnitude range of ML -0.2 to ML 1.3. The discrepancy between the two localization methods is mostly less than 1 km, which falls within the statistical errors. However, a few localizations deviate significantly, which can be attributed to poor observations during the winter of 2021/2022.
Controlling factors of organic matter accumulation and lacustrine shale distribution in Lianggaoshan Formation, Sichuan Basin, SW China
Authors: Fang Rui , Jiang Yuqiang , Sun Shasha , Luo Yao , Qi Lin , Dong Dazhong , Lai Qiang , Luo Yuzhuo , Jiang Zengzheng
Published: July 2023

The lacustrine shale, represented by the Lianggaoshan Formation, is widely distributed in oil and gas basins of China and will be a key target for unconventional hydrocarbon exploration in the future. Due to the complexity of geological conditions, the distribution of lacustrine shale and the mechanism of organic matter (OM) enrichment show significant differences between different basins. In this study, seismic interpretation, core observation, high-frequency geochemical analysis and other methods are integrated to reveal factors controlling lacustrine shale distribution and OM accumulation in lacustrine shale. The results suggest that six bottom-to-top organic-rich shale intervals are identified within the Lianggaoshan Formation due to lake-basin migration. The migration process of depocenters controls the planar distribution of lacustrine organic-rich shale. The organic-rich lacustrine shale within 1st Member and 2nd Member is characterized by relatively high paleoproductivity and dysoxic condition. The lacustrine organic-rich shale of the upper to the top of 3rd Member is characterized by relatively low paleoproductivity, relatively high terrestrial input, and dysoxic condition. Paleoproductivity and preservation condition caused by lake-level rise are generally the major influencing factor of organic matter accumulation in 1st Member and 2nd Member organic-rich shale. The input of terrestrial OM, and the condition of preservation caused by rapid deposition are the major factors controlling OM accumulation in 3rd Member of Lianggaoshan Formation.
Bariatric surgery and its impact on depressive symptoms, cognition, brain and inflammation
Authors: Kotackova Lenka , Marecek Radek , Mouraviev Andrei , Tang Ariana , Brazdil Milan , Cierny Michal , Paus Tomas , Pausova Zdenka , Mareckova Klara
Published: July 2023

Background

Obesity has been associated with depressive symptoms and impaired cognition, but the mechanisms underlying these relationships are not well understood. It is also not clear whether reducing adiposity reverses these behavioral outcomes. The current study tested the impact of bariatric surgery on depressive symptoms, cognition, and the brain; using a mediation model, we also examined whether the relationship between changes in adiposity after the surgery and those in regional thickness of the cerebral cortex are mediated by changes in low-grade inflammation (as indexed by C-reactive protein; CRP).

Methods

A total of 18 bariatric patients completed 3 visits, including one baseline before the surgery and two post-surgery measurements acquired at 6- and 12-months post-surgery. Each visit consisted of a collection of fasting blood sample, magnetic resonance imaging of the brain and abdomen, and assessment of depressive symptoms and cognition.

Results

After surgery, we observed reductions of both visceral fat (p< 0.001) and subcutaneous fat (p< 0.001), less depressive symptoms (p< 0.001), improved verbal reasoning (p< 0.001), and reduced CRP (p< 0.001). Mediation analyses revealed that the relationships between the surgery-related changes in visceral fat and cortical thickness in depression-related regions are mediated by changes in CRP (ab=-.027, SE=.012, 95% CI [-.054, -,006]).

Conclusion

These findings suggest that some of the beneficial effects of bariatric surgery on brain function and structure are due to a reduction of adiposity-related low-grade systemic inflammation.
Clinical evaluation of autologous platelet-rich plasma therapy for intrauterine adhesions: a systematic review and meta-analysis
Authors: Tang Ruonan , Xiao Xifeng , He Yunan , Qiu Daner , Zhang Wanlin , Wang Xiaohong
Published: July 2023

Objective

This meta-analysis aims to evaluate the efficacy and safety of autologous platelet-rich plasma (PRP) administration in reducing adhesion recurrence and improving pregnancy outcomes in patients with intrauterine adhesion (IUA).

Methods

We conducted a comprehensive search of Pubmed, Embase, the Cochrane Library, Web of Science, Scopus, and China National Knowledge Internet (CNKI) from inception to February 10, 2023, without any language or regional restrictions. We used random-effects models to assess odds ratios (OR) and weight mean differences (WMD) with 95% confidence intervals (CI).

Results

Our meta-analysis included a total of 730 patients from 10 clinical studies (6 RCTs and 4 non-RCTs). The results showed that PRP administration significantly increased endometrial thickness (WMD = 0.79, 95% CI: 0.40–1.19; P < 0.001; I2 = 0.0%), menstrual volume (WMD = 2.96, 95% CI = 2.30–3.61; P < 0.001; I2 = 0.0%), and days of menstruation (WMD = 1.13, 95% CI = 0.86–1.41; P < 0.001; I2 = 0.0%). Additionally, the clinical pregnancy rate was also improved (OR = 1.82, 95% CI: 1.19-2.78; P = 0.006; I2 = 0.0%). However, there was insufficient evidence to reach a conclusion regarding the effects of PRP on the recurrence rate of moderate to severe IUA, changes in AFS scores, miscarriage rate, and live birth rate.

Conclusions

Our analysis confirms that autologous PRP is an effective treatment for IUA. However, the limited sample size suggests that the results should be interpreted with caution. Therefore, larger and well-designed studies are necessary in the future to confirm these findings and explore the optimal PRP dosing regimens further.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO, identifier CRD42023391115.
Regional electricity market price forecasting based on an adaptive spatial–temporal convolutional network
Authors: Xu Jian , Hu Bo , Zhang Pengfei , Zhou Xiaoming , Xing Zuoxia , Hu Zhanshuo
Published: July 2023

The accurate prediction of electricity prices has great significance for the power system and the electricity market, regional electricity prices are difficult to predict due to congestion issues in regional transmission lines. A regional electricity price prediction framework is proposed based on an adaptive spatial–temporal convolutional network. The proposed framework is expected to better explore regional electricity prices’ spatial–temporal dynamic characteristics in the electricity spot market and improve the predictive accuracy of regional electricity prices. First, different areas of the electricity market are regarded as nodes. Then, each area’s historical electricity price data are used as the corresponding node’s characteristic information and constructed into a graph. Finally, a graph containing the spatial–temporal information on electricity prices is input to the adaptive spatial–temporal prediction framework to predict the regional electricity price. Operational data from the Australian electricity market are adopted, and the prediction results from the proposed adaptive spatial–temporal prediction framework are compared with those of existing methods. The numerical example results show that the predictive accuracy of the proposed framework is better than the existing baseline and similar methods. In the twelve-step forecast example in this paper, considering the spatial dependence of the spot electricity price can improve the forecast accuracy by at least 10.3% and up to 19.8%.
A novel few-sample wind power prediction model based on generative adversarial network and quadratic mode decomposition
Authors: He Hang , Yuan Manman
Published: July 2023

With the emergence of various new power systems, accurate wind power prediction plays a critical role in their safety and stability. However, due to the historical wind power data with few samples, it is difficult to ensure the accuracy of power system prediction for new wind farms. At the same time, wind power data show significant uncertainty and fluctuation. To address this issue, it is proposed in this research to build a novel few-sample wind power prediction model based on the least-square generative adversarial network (LSGAN) and quadratic mode decomposition (QMD). Firstly, a small amount of original wind power data are generated to improve the data by least-square generative adversarial network, which solves the error in prediction with limited sample data. Secondly, a quadratic mode decomposition method based on ensemble empirical mode decomposition (EEMD) and variational mode decomposition (VMD) is developed to address the instability of wind power data and extract hidden temporal characteristics. Specifically, ensemble empirical mode decomposition decomposes the data once to obtain a set of intrinsic mode functions (IMFs), and then variational mode decomposition is used to decompose the fuzzy irregular IMF1 function twice. Finally, a bidirectional long short-term memory network (BiLSTM) based on particle swarm optimization (PSO) is applied to predict wind power data. The LSGAN-QMD-PSO-BiLSTM model proposed in this research is verified on a wind farm located in Spain, which indicates that the proposed model achieves the lowest root mean square error (RMSE) and mean absolute error (MAE) errors of 100.6577 and 66.5175 kW, along with the highest R2 of 0.9639.
Public health implications of severe floods in Pakistan: assessing the devastating impact on health and the economy
Authors: Raza Mahnoor , Fatima Alina , Habiba Ume , Shah Hussain Haider
Published: July 2023

Natural disasters, including droughts, earthquakes, landslides, and floods, cause human mortality, property destruction, and social and economic turmoil. More than 33 million people in Pakistan have been impacted by floods due to the recent heavy rains. Many public hospitals, water treatment plants, and educational institutions have also been damaged or destroyed. Water and vector-borne diseases may have spread more widely due to the floods. A rapid health emergency response must be initiated to treat the injured, stocking healthcare facilities with vital supplies and back up mobile health teams in the impacted areas.
Biochar aggravates the negative effect of drought duration on the growth and physiological dynamics of Pinus massoniana
Authors: Wang Xue , Zheng Wei-Long , Ma Xiuzhi , Yu Fei-Hai , Li Mai-He
Published: July 2023

Biochar has been considered as a cost-effective amendment to improve the soil water content and thus to mitigate the effects of drought on plants. However, less is known about the mitigating effects of biochar application on the negative effect of longer drought duration on trees. We investigated the effects of drought duration in combination with biochar application on the growth, tissue non-structural carbohydrate (NSC) concentrations, needle photosynthesis, and δ13C content of 1-year-old Pinus massoniana saplings in a greenhouse experiment. We found that the height and total biomass of P. massoniana saplings were significantly decreased with increasing drought duration, which was likely attributed to the suppressed photosynthetic capacity. The longer drought duration (e.g., 1 month) significantly decreased needle photosynthesis and increased the value of needle δ13C but did not deplete tissue NSC concentrations at the expense of growth, suggesting that plants prioritize carbon storage over growth in response to a long duration of drought. Surprisingly, the application of biochar significantly decreased the survival of P. massoniana saplings and aggravated the negative effect of drought duration on the growth of P. massoniana, which is probably attributed to the increased soil pH value of >7.5, as P. massoniana is adapted to mildly acid to neutral soils. Our results suggest that the effect of biochar application might be species specific, and it can aggravate the negative effect of drought duration on plants that are less tolerant to alkaline soils.
Vitamin D supplementation reduced blood inflammatory cytokines expression and improved graft function in kidney transplant recipients
Authors: Bai Yang-Juan , Li Ya-Mei , Hu Shu-Meng , Zou Yuan-Gao , An Yun-Fei , Wang Lan-Lan , Shi Yun-Ying
Published: July 2023

Background

Chronic allograft dysfunction(CAD) is the leading cause of graft loss in kidney transplant recipients (KTRs). Inflammatory process is believed to be one of the major contributors to CAD. The aim of this study is to explore the anti-inflammatory effect of vitamin D (VD) supplementation in KTRs and its role in the graft function improvement(protection).

Methods

A retrospective cohort of 39 KTRs with chronic antibody mediated rejection(CAMR)or stable renal function and a prospective cohort of 42 KTRs treated or untreated with VD were enrolled. Serum levels of vitamin D metabolism and serum inflammatory cytokines, renal graft function, and routine blood biomarkers were tested and dynamically tracked within 12 months post-transplant.

Results

Compared with the stable group, the CAMR group exhibited significantly elevated serum levels of inflammatory cytokines IL-1β, IFN-γ, IL-2, IL-10, IP-10, and HMGB1 (P <0.05). The supplementation of vitamin D effectively increased the serum concentration of vitamin D in kidney transplant recipients (KTRs) in the treated group. During the course of treatment, the treated group exhibited a gradual increase in eGFR levels, which were significantly higher than those observed in the untreated group at 12 months post-transplant (p<0.05). Notably, as eGFR improved, there was a significant decrease in levels of IL-1β, IFN-γ, IL-2, IL-10, IP-10 and HMGB1 in the treated group compared to the untreated group (P<0.05).

Conclusion

This study confirmed that immune-inflammation is a crucial factor in the development of CAD in KTRs.VD deficiency impairs its anti-inflammatory activity. By assisting in the regulation of excessive immune inflammation and restoration of immune homeostasis, effective VD supplementation contributes to protection and maintenance of graft function in KTRs.
β-catenin attenuation leads to up-regulation of activating NKG2D ligands and tumor regression in BrafV600E-driven thyroid cancer cells
Authors: Zou Minjing , Al-Yahya Suhad , Al-Alwan Monther , BinEssa Huda A. , Khabar Khalid S. A. , Almohanna Falah , Assiri Abdullah M. , Altaweel Abdulmohsen , Qattan Amal , Meyer Brian F. , Alzahrani Ali S. , Shi Yufei
Published: July 2023

Introduction

BRAFV600E mutations frequently occur in papillary thyroid cancer (PTC). β-catenin, encoded by CTNNB1, is a key downstream component of the canonical Wnt signaling pathway and is often overexpressed in PTC. BRAFV600E-driven PTC tumors rely on Wnt/β-catenin signaling to sustain growth and progression.

Methods

In the present study, we investigated the tumorigenicity of thyroid cancer cells derived from BRAFV600E PTC mice following Ctnnb1 ablation (BVE-Ctnnb1null).

Results

Remarkably, the tumorigenic potential of BVE-Ctnnb1null tumor cells was lost in nude mice. Global gene expression analysis of BVE-Ctnnb1null tumor cells showed up-regulation of NKG2D receptor activating ligands (H60a, H60b, H60c, Raet1a, Raet1b, Raet1c, Raet1d, Raet1e, and Ulbp1) and down-regulation of inhibitory MHC class I molecules H-2L and H-2K2 in BVE-Ctnnb1null tumor cells. In vitro cytotoxicity assay demonstrated that BVE-Ctnnb1wt tumor cells were resistant to NK cell-mediated cytotoxicity, whereas BVE-Ctnnb1null tumor cells were sensitive to NK cell-mediated killing. Furthermore, the overexpression of any one of these NKG2D ligands in the BVE-Ctnnb1wt cell line resulted in a significant reduction of tumor growth in nude mice.

Conclusions

Our results indicate that active β-catenin signaling inhibits NK cell-mediated immune responses against thyroid cancer cells. Targeting the β-catenin signaling pathway may have significant therapeutic benefits for BRAF-mutant thyroid cancer by not only inhibiting tumor growth but also enhancing host immune surveillance.
Assessment of BoHV-4-based vector vaccine intranasally administered in a hamster challenge model of lung disease
Authors: Park Seok-Chan , Conti Laura , Franceschi Valentina , Oh Byungkwan , Yang Myeon-Sik , Ham Gaeul , Di Lorenzo Antonino , Bolli Elisabetta , Cavallo Federica , Kim Bumseok , Donofrio Gaetano
Published: July 2023

Introduction

Bovine herpesvirus 4 (BoHV-4) is a bovine Rhadinovirus not associated with a specific pathological lesion or disease and experimentally employed as a viral vector vaccine. BoHV-4-based vector (BoHV-4-BV) has been shown to be effective in immunizing and protecting several animal species when systemically administrated through intramuscular, subcutaneous, intravenous, or intraperitoneal routes. However, whether BoHV-4-BV affords respiratory disease protection when administered intranasally has never been tested.

Methods

In the present study, recombinant BoHV-4, BoHV-4-A-S-ΔRS-HA-ΔTK, was constructed to deliver an expression cassette for the SARS-CoV-2 spike glycoprotein, and its immunogenicity, as well as its capability to transduce cells of the respiratory tract, were tested in mice. The well-established COVID-19/Syrian hamster model was adopted to test the efficacy of intranasally administered BoHV-4-A-S-ΔRS-HA-ΔTK in protecting against a SARS-CoV-2 challenge.

Results

The intranasal administration of BoHV-4-A-S-ΔRS-HA-ΔTK elicited protection against SARS-CoV-2, with improved clinical signs, including significant reductions in body weight loss, significant reductions in viral load in the trachea and lungs, and significant reductions in histopathologic lung lesions compared to BoHV-4-A-S-ΔRS-HA-ΔTK administered intramuscularly.

Discussion

These results suggested that intranasal immunization with BoHV-4-BV induced protective immunity and that BoHV-4-BV could be a potential vaccine platform for the protection of other animal species against respiratory diseases.
Advances in attractive therapeutic approach for macrophage activation syndrome in COVID-19
Authors: Chen Shunyao , Zhang Cong , Chen Deng , Dong Liming , Chang Teding , Tang Zhao-Hui
Published: July 2023

Nowadays, people have relaxed their vigilance against COVID-19 due to its declining infection numbers and attenuated virulence. However, COVID-19 still needs to be concern due to its emerging variants, the relaxation of restrictions as well as breakthrough infections. During the period of the COVID-19 infection, the imbalanced and hyper-responsive immune system plays a critical role in its pathogenesis. Macrophage Activation Syndrome (MAS) is a fatal complication of immune system disease, which is caused by the excessive activation and proliferation of macrophages and cytotoxic T cells (CTL). COVID-19-related hyperinflammation shares common clinical features with the above MAS symptoms, such as hypercytokinemia, hyperferritinemia, and coagulopathy. In MAS, immune exhaustion or defective anti-viral responses leads to the inadequate cytolytic capacity of CTL which contributes to prolonged interaction between CTL, APCs and macrophages. It is possible that the same process also occurred in COVID-19 patients, and further led to a cytokine storm confined to the lungs. It is associated with the poor prognosis of severe patients such as multiple organ failure and even death. The main difference of cytokine storm is that in COVID-19 pneumonia is mainly the specific damage of the lung, while in MAS is easy to develop into a systemic. The attractive therapeutic approach to prevent MAS in COVID-19 mainly includes antiviral, antibiotics, convalescent plasma (CP) therapy and hemadsorption, extensive immunosuppressive agents, and cytokine-targeted therapies. Here, we discuss the role of the therapeutic approaches mentioned above in the two diseases. And we found that the treatment effect of the same therapeutic approach is different.
Insight of a lipid metabolism prognostic model to identify immune landscape and potential target for retroperitoneal liposarcoma
Authors: Wang Zhenyu , Tao Ping , Fan Peidang , Wang Jiongyuan , Rong Tao , Hou Yingyong , Zhou Yuhong , Lu Weiqi , Hong Liang , Ma Lijie , Zhang Yong , Tong Hanxing
Published: July 2023

Introduction

The exploration of lipid metabolism dysregulation may provide novel perspectives for retroperitoneal liposarcoma (RPLS). In our study, we aimed to investigate potential targets and facilitate further understanding of immune landscape in RPLS, through lipid metabolism-associated genes (LMAGs) based prognostic model.

Methods

Gene expression profiles and corresponding clinical information of 234 cases were enrolled from two public databases and the largest retroperitoneal tumor research center of East China, including cohort-TCGA (n=58), cohort-GSE30929 (n=92), cohort-FD (n=50), cohort-scRNA-seq (n=4) and cohort-validation (n=30). Consensus clustering analysis was performed to identify lipid metabolism-associated molecular subtypes (LMSs). A prognostic risk model containing 13 LMAGs was established using LASSO algorithm and multivariate Cox analysis in cohort-TCGA. ESTIMATE, CIBERSORT, XCELL and MCP analyses were performed to visualize the immune landscape. WGCNA was used to identify three hub genes among the 13 model LMAGs, and preliminarily validated in both cohort-GSE30929 and cohort-FD. Moreover, TIMER was used to visualize the correlation between antigen-presenting cells and potential targets. Finally, single-cell RNA-sequencing (scRNA-seq) analysis of four RPLS and multiplexed immunohistochemistry (mIHC) were performed in cohort-validation to validate the discoveries of bioinformatics analysis.

Results

LMS1 and LMS2 were characterized as immune-infiltrated and -excluded tumors, with significant differences in molecular features and clinical prognosis, respectively. Elongation of very long chain fatty acids protein 2 (ELOVL2), the enzyme that catalyzed the elongation of long chain fatty acids, involved in the maintenance of lipid metabolism and cellular homeostasis in normal cells, was identified and negatively correlated with antigen-presenting cells and identified as a potential target in RPLS. Furthermore, ELOVL2 was enriched in LMS2 with significantly lower immunoscore and unfavorable prognosis. Finally, a high-resolution dissection through scRNA-seq was performed in four RPLS, revealing the entire tumor ecosystem and validated previous findings.

Discussion

The LMS subgroups and risk model based on LMAGs proposed in our study were both promising prognostic classifications for RPLS. ELOVL2 is a potential target linking lipid metabolism to immune regulations against RPLS, specifically for patients with LMS2 tumors.
Identification and characterisation of anti-IL-13 inhibitory single domain antibodies provides new insights into receptor selectivity and attractive opportunities for drug discovery
Authors: Walker Kayleigh , Baravalle Roberta , Holyfield Rachel , Kalms Jacqueline , Wright Helena , Seewooruthun Chitra , Muskett Frederick W. , Scott-Tucker Anthony , Merritt Andy , Henry Alistair , Lawson Alastair D. G. , Hall Gareth , Prosser Christine , Carr Mark D.
Published: July 2023

Interleukin-13 (IL-13) is a cytokine involved in T-cell immune responses and is a well validated therapeutic target for the treatment of asthma, along with other allergic and inflammatory diseases. IL-13 signals through a ternary signalling complex formed with the receptors IL-13Rα1 and IL-4Rα. This complex is assembled by IL-13 initially binding IL-13Rα1, followed by association of the binary IL-13:IL-13Rα1 complex with IL-4Rα. The receptors are shared with IL-4, but IL-4 initially binds IL-4Rα. Here we report the identification and characterisation of a diverse panel of single-domain antibodies (VHHs) that bind to IL-13 (KD 40 nM-5.5 μM) and inhibit downstream IL-13 signalling (IC50 0.2-53.8 μM). NMR mapping showed that the VHHs recognise a number of epitopes on IL-13, including previously unknown allosteric sites. Further NMR investigation of VHH204 bound to IL-13 revealed a novel allosteric mechanism of inhibition, with the antibody stabilising IL-13 in a conformation incompatible with receptor binding. This also led to the identification of a conformational equilibrium for free IL-13, providing insights into differing receptor signalling complex assembly seen for IL-13 compared to IL-4, with formation of the IL-13:IL-13Rα1 complex required to stabilise IL-13 in a conformation with high affinity for IL-4Rα. These findings highlight new opportunities for therapeutic targeting of IL-13 and we report a successful 19F fragment screen of the IL-13:VHH204 complex, including binding sites identified for several hits. To our knowledge, these 19F containing fragments represent the first small-molecules shown to bind to IL-13 and could provide starting points for a small-molecule drug discovery programme.
Modulation of innate lymphoid cells by enteric bacterial pathogens
Authors: Sah Prakash , Zenewicz Lauren A.
Published: July 2023

Innate lymphoid cells (ILCs) are key regulators of tissue homeostasis, inflammation, and immunity to infections. ILCs rapidly respond to environmental cues such as cytokines, microbiota and invading pathogens which regulate their function and phenotype. Even though ILCs are rare cells, they are enriched at barrier surfaces such as the gastrointestinal (GI) tract, and they are often critical to the host’s immune response to eliminate pathogens. On the other side of host-pathogen interactions, pathogenic bacteria also have the means to modulate these immune responses. Manipulation or evasion of the immune cells is often to the pathogen’s benefit and/or to the detriment of competing microbiota. In some instances, specific bacterial virulence factors or toxins have been implicated in how the pathogen modulates immunity. In this review, we discuss the recent progress made towards understanding the role of non-cytotoxic ILCs during enteric bacterial infections, how these pathogens can modulate the immune response, and the implications these have on developing new therapies to combat infection.