Samantha Sudhoff, Pranav Perumal, Zhaoqing Wu
et al.
Climate discourse online plays a crucial role in shaping public understanding of climate change and influencing political and policy outcomes. However, climate communication unfolds across structurally distinct platforms with fundamentally different incentive structures: paid advertising ecosystems incentivize targeted, strategic persuasion, while public social media platforms host largely organic, user-driven discourse. Existing computational studies typically analyze these environments in isolation, limiting our ability to distinguish institutional messaging from public expression. In this work, we present a comparative analysis of climate discourse across paid advertisements on Meta (previously known as Facebook) and public posts on Bluesky from July 2024 to September 2025. We introduce an interpretable, end-to-end thematic discovery and assignment framework that clusters texts by semantic similarity and leverages large language models (LLMs) to generate concise, human-interpretable theme labels. We evaluate the quality of the induced themes against traditional topic modeling baselines using both human judgments and an LLM-based evaluator, and further validate their semantic coherence through downstream stance prediction and theme-guided retrieval tasks. Applying the resulting themes, we characterize systematic differences between paid climate messaging and public climate discourse and examine how thematic prevalence shifts around major political events. Our findings show that platform-level incentives are reflected in the thematic structure, stance alignment, and temporal responsiveness of climate narratives. While our empirical analysis focuses on climate communication, the proposed framework is designed to support comparative narrative analysis across heterogeneous communication environments.
Complex salt geometries and strong velocity contrasts pose significant challenges for velocity model building and subsalt imaging. Although full waveform inversion (FWI) provides high-resolution velocity models, its performance strongly depends on the accuracy of initial model. On the other hand, gravity focusing inversion (GFI) can recover compact density distributions and provide reliable long-wavelength structural information for seismic exploration, but it suffers from poor depth resolution and inherent non-uniqueness. To better invert salt structure by leveraging the complementary advantages of full waveform and gravity data, we propose a multi-physics alternating coupled inversion strategy for salt dome model. The proposed strategy mainly includes three parts. First, we perform FWI using a simple layered velocity model to obtain preliminary velocity updates and extract the salt top boundary. Second, this structural information is used as a constraint in GFI to recover a compact salt density distribution beneath the salt top. Third, the resulting salt geometry is used to construct an improved velocity model for the next stage of FWI. Through iterative alternation, FWI provides reliable structural constraints for GFI, while GFI supplies a more reasonable macroscopic salt model for FWI, effectively mitigating the strong dependence on the initial model. In addition, a depth-varying density contrast is introduced in GFI to better represent sediment compaction effects. Compared with unconstrained GFI and conventional FWI using a horizontally layered initial model, the proposed method effectively improves both velocity and density reconstruction in the modified BP salt model and SEG/EAGE salt model.
Nisrina Anggi Syahputri, Lilis Siti Badriah, Arintoko
et al.
This study aims to examine the effect of the Covid-19 pandemic, inflation, the BI 7-Day Repo Rate (BI7DRR), and Credit Interest Rates on Non-Performing Loans (NPL) at Commercial Banks in Indonesia, both partially and simultaneously. This quantitative research, which explores rare phenomena such as the ongoing Covid-19 pandemic and empirical findings that partially reject the hypothesis and the loanable funds theory, offers novelty compared to previous studies. Using secondary data from March 2020 to March 2022 obtained from Bank Indonesia, the Financial Services Authority, and the Central Statistics Agency, this study applies multiple regression analysis with SPSS for Windows, employing t-tests, F-tests, and adjusted R² to measure the impact on NPL. The results show that partially, the Covid-19 pandemic and inflation do not affect NPL, while BI7DRR has a negative effect of 0.513% and Credit Interest Rates have a positive effect of 0.367% on NPL. Simultaneously, these four variables influence NPL by 52.2%, suggesting that Ho₅ is accepted and Ha₅ is rejected, which can be attributed to government and central bank fiscal policies as well as commercial bank credit relief programs for debtors. These findings imply the need for synergy among commercial banks, the central bank, and the government to navigate macroeconomic uncertainties through careful BI7DRR adjustments, competitive lending rates, credit restructuring, and stringent debtor evaluation, while encouraging debtors to enhance productivity and make well-informed credit decisions to prevent future NPL surges.
In the corporate world, it is the obligation of every employee to meet the targets set by the company, in practice there are many factors that support the good or bad performance of an employee in completing the goals set by the company. In Bank Syariah Indonesia, especially the frontliner, which is the vanguard in banking services, is also the vanguard in the company's business, it is certainly a challenge in running services and selling the company's business. Especially in the world of Islamic banking in carrying out business and service aspects, it is supported by many factors, including the existence of an organizational culture that serves as a guideline for employees to harmonize the same in culture and organization. Another factor in improving or decreasing employee performance in the company is inseparable from the factors of superiors or leaders of each supervision. To create achievement motivation that can encourage every employee to complete the targets given by the company. The method applied in this research is quantitative, which indicates that this research is causal in nature, where the researcher aims to analyze and describe the cause-and-effect relationship or mutual influence relationship between the variables studied. The number of samples used from the overall population was 100 respondents using a questionnaire with a linkert scale of 1-5 Statistical tests were used to assess the significance of regression results and to measure the strength of the relationship between each variable studied. This data management focuses on the security of the data of the respondents. In this study, it is known that the overall variables studied, namely organizational culture, leadership function and employee performance mediated by achievement motivation in Islamic banking in the Bandung region have a significant impact on each other. Employee performance in each employee of the company has the influence of the variables that have been studied.
A remarkable project to record the Complete Songs of Robert Tannahill, the Paisley weaver-poet, has concluded with the 2024 release of a fifth and final disc, a fitting tribute marking the 250th anniversary of Tannahill’s birth. This review article discusses why Tannahill is an important and distinctive voice in the Scottish traditional song repertoire, and assesses the achievements of the recording project.
Mirajul Islam, Michael J. Daniels, Donald Lloyd-Jones
et al.
An important issue in joint modelling for outcomes and longitudinal risk factors in cohort studies is to have an accurate assessment of events. Events determined based on ICD-9 codes can be very inaccurate, in particular for cardiovascular disease (CVD) where ICD-9 codes may overestimate the frequency of CVD. Motivated by the lack of adjudicated events in the Established Populations for Epidemiologic Studies of the Elderly (EPESE) cohort, we develop methods that use a related cohort Atherosclerosis Risk in Communities (ARIC), with both ICD-9 code events and adjudicated events, to create a posterior predictive distribution of adjudicated events. The methods are based on the construction of flexible Bayesian joint models combined with a Bayesian additive regression trees to directly address the ICD-9 misclassification. We assessed the performance of our approach by simulation study and applied to ARIC data.
Citation faithfulness detection is critical for enhancing retrieval-augmented generation (RAG) systems, yet large-scale Chinese datasets for this task are scarce. Existing methods face prohibitive costs due to the need for manually annotated negative samples. To address this, we introduce the first large-scale Chinese dataset CiteCheck for citation faithfulness detection, constructed via a cost-effective approach using two-stage manual annotation. This method balances positive and negative samples while significantly reducing annotation expenses. CiteCheck comprises training and test splits. Experiments demonstrate that: (1) the test samples are highly challenging, with even state-of-the-art LLMs failing to achieve high accuracy; and (2) training data augmented with LLM-generated negative samples enables smaller models to attain strong performance using parameter-efficient fine-tuning. CiteCheck provides a robust foundation for advancing citation faithfulness detection in Chinese RAG systems. The dataset is publicly available to facilitate research.
Tubagus Chaeru Nugraha, El-Sawy El-Sawy Ahmed Abdel Rahim, Fahmy Lukman
Islamic religious education at universities has not yet become a foundational aspect of scientific discipline thinking. This study aims to explore the role of Islamic religious education in achieving Sustainable Development Goals (SDGs). A descriptive analysis method was employed, incorporating data collection through selected questionnaires and interviews, content analysis of the gathered data, and presentation of the results in tables with descriptive and explanatory explanations. The findings indicate that Islamic religious education, when implemented through a well-designed Problem-Based Learning (PBL) method, effectively trains students to provide paradigmatic solutions to issues related to population, the planet, and the economy. This approach fosters an academic atmosphere that encourages learning and enthusiasm among students. The PBL design equips students with the skills to apply Islamic concepts and methods as comprehensive solutions to various environmentally friendly challenges concerning population, planet, and economic issues. In conclusion, integrating PBL in Islamic religious education at universities enhances students' ability to address SDGs, promoting sustainable development through the application of Islamic principles.
In this work, we investigate an $α$-$T_3$ lattice in the form of a Corbino disk, characterized by inner and outer radii $R_1$ and $R_2$, threaded by a tunable magnetic flux. Through exact (analytic) solution of the stationary Dirac-Weyl equation, we compute the transmission probability of the carriers and hence obtain the conductance features for $0<α\leq 1$ ($α$ denotes the strength of the hopping between the central atom and one of the other two) which allows ascertaining the role of the flat band, alongwith scrutinizing the transport features from graphene to a dice lattice. Our results reveal periodic Aharonov-Bohm (AB) oscillations in the conductance, reminiscent of the utility of the Corbino disk as an electron pump. Further, these results are strongly influenced by parameters, such as, doping level, ratio of the inner and outer radii, magnetic flux, and $α$. Additionally, complex quantum interference effect resulting in the possible emergence of higher harmonic modes and split-peak structures in the conductance, become prominent for smaller $α$ values and larger ratios of the radii. We also find that, away from the charge-neutrality point (zero doping), the conductance oscillations are more pronounced and sensitive to the various parameters, with the corresponding behaviour largely governed via the evanescent wave transport. The Fano factor reveals distinct transport regimes, transitioning from Poissonian to pseudo-diffusive for $α< 1$, and from ballistic to pseudo-diffusive for $α= 1$. This setup, thus serves as a fertile ground for studying the generation of quantum Hall current and Aharonov-Bohm (AB) oscillations in a flat band system, alongwith demonstrating intricate appearance of higher harmonics in electron transport.
This research examines the integration between Islam and science in the context of contemporary Islamic education. The primary focus of this research is to comprehend the harmony that can be achieved between scholarly pursuits and Islamic beliefs. The research method involves literature analysis and case studies on Islamic educational approaches that combine scientific principles with religious values. This study highlights the crucial role of Islamic education in providing a solid scholarly foundation while preserving moral and spiritual values. The discussion encompasses the integration of Islamic concepts into the curriculum, the implementation of teaching methods that combine critical thinking with Islamic ethical values, and how this approach can stimulate innovative thinking without compromising religious principles.The research findings indicate that an approach that creates harmony between Islam and science can strengthen the Islamic identity of learners while equipping them with knowledge relevant to the modern era. The practical implications of this research include guidelines for the development of Islamic education curricula that align religious values with the demands of the modern world, thus shaping a generation that is not only intellectually smart but also possesses a strong moral character.
This project concerns developing and validating an image guidance framework for application to a robotic-assisted fibular reduction in ankle fracture surgery. The aim is to produce and demonstrate proper functioning of software for automatic determination of directions for fibular repositioning with the ultimate goal of application to a robotic reduction procedure that can reduce the time and complexity of the procedure as well as provide the benefits of reduced error in ideal final fibular position, improved syndesmosis restoration and reduced incidence of post-traumatic osteoarthritis. The focus of this product will be developing and testing the image guidance software, from the input of preoperative images through the steps of automated segmentation and registration until the output of a final transformation that can be used as instructions to a robot on how to reposition the fibula, but will not involve developing or implementing the hardware of the robot itself.
Large language models (LLMs) can explain their predictions through post-hoc or Chain-of-Thought (CoT) explanations. But an LLM could make up reasonably sounding explanations that are unfaithful to its underlying reasoning. Recent work has designed tests that aim to judge the faithfulness of post-hoc or CoT explanations. In this work we argue that these faithfulness tests do not measure faithfulness to the models' inner workings -- but rather their self-consistency at output level. Our contributions are three-fold: i) We clarify the status of faithfulness tests in view of model explainability, characterising them as self-consistency tests instead. This assessment we underline by ii) constructing a Comparative Consistency Bank for self-consistency tests that for the first time compares existing tests on a common suite of 11 open LLMs and 5 tasks -- including iii) our new self-consistency measure CC-SHAP. CC-SHAP is a fine-grained measure (not a test) of LLM self-consistency. It compares how a model's input contributes to the predicted answer and to generating the explanation. Our fine-grained CC-SHAP metric allows us iii) to compare LLM behaviour when making predictions and to analyse the effect of other consistency tests at a deeper level, which takes us one step further towards measuring faithfulness by bringing us closer to the internals of the model than strictly surface output-oriented tests. Our code is available at \url{https://github.com/Heidelberg-NLP/CC-SHAP}
M.Syukri Azwar Lubis, Ahmat Nurullah, Eka Selvi Handayani
et al.
Penelitian ini bertujuan untuk mengetahui untuk mengetahui pengaruh sikap kepala sekolah terhadap kinerja guru SMA di wilayah Tangerang Selatan, untuk mengetahui seberapa besar pengaruh sikap kepala sekolah terhadap kinerja guru SMA di wilayah Tangerang Selatan, untuk mengetahui sikap kepala sekolah yang dapat mempengaruhi kinerja guru. Metode penelitian ini menggunakan pendekatan kuantitatif dengan metode korelasional dan ex post facto. Populasi dalam penelitian adalah guru SMA di wilayah Tangerang Selatan. Sedangkan sampel penelitian sebanyak 32 guru atau dengan kata lain subjek penelitian ini adalah 32 orang guru SMA di wilayah Tangerang Selatan. Variabel bebas (X) dalam penelitian ini yaitu sikap kepala sekolah dan Variabel terikat (Y) dalam penelitian ini yaitu kinerja guru. Teknik pengumpulan data dengan menggunakan angket dan metode analisis menggunakan Regresi Sederhana. Teknik pengujian hipotesis menggunakan analisis korelasi dan analisis regresi linier sederhana. Sebelum dilakukan uji analisis, terlebih dahulu dilakukan uji prasyarat yaitu uji normalitas dan uji liniearitas. Pengujian hipotesis dengan taraf signifikansi 5% diperoleh bahwa nilai p korelasi antara variabel sikap kepala sekolah dengan kinerja guru sebesar 0,079. Nilai signifikansi p > 0,05 (0,079 > 0,05), karena nilai Fhitung lebih kecil dari Ftabel maka dapat disimpulkan bahwa terdapat pengaruh secara signifikan antara variabel sikap kepala sekolah terhadap Kinerja Guru.
Internet of Things (IoT)-based applications must be integrated with wireless communication technologies for this make application data easily accessible. The wireless communication system is a crucial component of IoT infrastructure, serving as a bridge for bidirectional connection for data gathering and control message delivery. In this article, a modified meander form microstrip patch antenna for IoT applications in 2.4 GHz ISM (Industrial, Scientific, and Medical) band is suggested.The suggested antenna has a gain of up to 4.01 dBi and an efficiency of up to 90% directivity up to 7.14. Theperformance after simulation of this antenna that is combined with a 2.4GHz radio frequency module and IoT sensors. Having small size and high fractional bandwidth which gives a good performance in IoT application. The patch's length width is 30.2 mm, and its length 47mm at a resonance frequency of 2.4 GHz is 38 mm, with a feeding offset position of 6 mm. The substrate has a height of 1.5 mm that appropriate for short-range IoT applications.
The goal of information-seeking dialogue is to respond to seeker queries with natural language utterances that are grounded on knowledge sources. However, dialogue systems often produce unsupported utterances, a phenomenon known as hallucination. To mitigate this behavior, we adopt a data-centric solution and create FaithDial, a new benchmark for hallucination-free dialogues, by editing hallucinated responses in the Wizard of Wikipedia (WoW) benchmark. We observe that FaithDial is more faithful than WoW while also maintaining engaging conversations. We show that FaithDial can serve as training signal for: i) a hallucination critic, which discriminates whether an utterance is faithful or not, and boosts the performance by 12.8 F1 score on the BEGIN benchmark compared to existing datasets for dialogue coherence; ii) high-quality dialogue generation. We benchmark a series of state-of-the-art models and propose an auxiliary contrastive objective that achieves the highest level of faithfulness and abstractiveness based on several automated metrics. Further, we find that the benefits of FaithDial generalize to zero-shot transfer on other datasets, such as CMU-Dog and TopicalChat. Finally, human evaluation reveals that responses generated by models trained on FaithDial are perceived as more interpretable, cooperative, and engaging.
الملخص: یعتبر الدجاجلة أخطر مرض یدخل جسد الأمة الإسلامية ویفت في عضدها، ویضعف قوتها؛ لأنه تقضي على المنهج القويم الذي تسلكه لتحقيق السعادة الدنيوية والأخروية. فالصِّدق علامة الحقِّ وأهله، والكذب علامة الباطل وأهله، وأهل الباطل لهم مناهج في الدَّجل والكذب، خاصة في البيئة الدينية، فمنها: وصف المقابل لهم بالكذب في الدين لصرف الناس عن عقيدته وهديه، ومنها الكذب في الدين على لسان أهل الحق لإضلال الناس عن الحق الذي جاؤوا به، ومنها استعمال الكذب في الدين للحصول على مآرب شخصية نفعيَّة. ويُعدُّ الكذب عند أهل الحديث من المصطلحات الخطيرة التي تهوي بصاحبها في النار بما تواتر عن النبي صلى الله عليه وسلم من أخبار؛ لأنه تحريف للوقائع وتغيير للحقائق، ومن وصف به في ميزان الجرح والتعديل فلا يجوز قبول خبره، ولا الاحتجاج به، ويجب بيان أمره للناس ليحذروه. ولكن بالمقابل استعمل مصطلح "دجال من الدجاجلة" من قبل قوم من الرواة الثقات في حق رواة ثقات آخرين، ليسوا بكاذبين ولا دجَّالين، دفعهم إلى ذلك التعصب أو العداوة أو المنافرة، فجاءت هذه الدراسة لتبين المعنى المقصود من لفظـ دجال أو دجال من الدجاجلة عند إطلاقه. وهل المراد به المعنى اللغوي أو المعنى الاصطلاحي عند أهل الحديث، والتدقيق في مقصد قائله، وماذا يترتب على ذلك من آثار في نطاق علم الجرح والتعديل؛ لأنه مقصود دراستنا، وبيان الأئمة المحدثين الذين استخدموا مصطلح الدجاجلة، والدفاع عن الأئمة الذين وُصِفوا به وليسوا من أهله، وكشف الرواة الذين وصفوا به وهم من أهله ليحذرهم الناس.أما إشكالية البحث فهي إطلاق لفظ "الدجال" على من هو داخل فيه على مراد المحدثين من استعمال هذا المصطلح، واستعماله أحيانًا بمعناه اللغوي للنيل من عالم ما وإهانته بما لا يمت لعلم الجرح والتعديل بصلة، وهذان الاستعمالان استخدما من قبل علماء الحديث ورواته في حق علماء الحديث ورواته. لذا جاء البحث ليزيل هذا الإشكال ويبين مصير المتهم من البريء. أما المنهج المتبع في البحث فهو المنهج الوصفي التحليلي؛ لأنه الأقرب إلى مضمون البحث. وقد وصلت الدراسة إلى النتائج الآتية: إن لفظ "دجال، أو دجال من الدجاجلة" يراد به الكذب في الحديث النبوي على الحقيقية الاصطلاحية، وهو متناسب مع الدجال الأكبر الذي يظهر قبل قيام الساعة، ويدعى ما ليس عنده كذباً وزورًا.إن لفظ دجال يختلف عن لفظ دجال من الدجاجلة في المرتبة الوصفية، ففي قوله دجال من الدجاجلة تحقير على وجه المبالغة، وهو يشبه كذاب، وركن في الكذب. فهما مرتبتان، الثانية أشد جرحًا من الأولى. وهذا لم ينبه إليه في كتب الجرح والتعديل.قد يطلق لفظ دجال ويراد به التحقير والتصغير والشتم، وهو لا يدخل في ميزان الجرح والتعديل لأنه خارج عن موضوع الحديث النبوي.اتهام الإمام ابن اسحاق بالدجل هو من مناكفة الأقران، وما يحدث بينهم من حساسيات تصدر معها ألفاظ لا يراد منها الحقيقية، ويشهد لذلك رجوع الأمام مالك عن مخاصمة ابن اسحاق وإكرامه.اتهام الإمام أبو حنيفة بالدجل لا قيمة له في ميزان الجرح والتعديل؛ لأن تعليل الحكم بأن مذهبه لم يدخل المدينة، ليس معتبرًا عند علماء الحديث لأنه جرح مبهم لا يستند إلى دليل، ونسبة هذا الكلام إلى أحد أئمة السلف فيها نظر، أو لعله يتكلم في نقد مذهب الرأي الذي عليه الإمام وهذا أيضًا غير معتبر في الجرح، أو هو من باب التعصب والتجني، والله أعلم. إن الإمام ابن حبان كان له النصيب الأوفى والحظ الأوفر في كشف النقاب عن هؤلاء الدجاجلة، فكان لمن بعده مصدرًا كاشفًا وموضحاً، فكتابه المجروحين يعد مصدرًا مهماً لمتابعة هؤلاء.هذا، ويجب على الأئمة في كل زمان إخضاع الأحكام الصادرة في حق أئمة الدين إلى النقد، كي لا يجرح إمام بغير حق، وربما كان هذا الإمام قدوة ومرجعًا للمسلمين في علم من العلوم.
The study aims to innovate the teaching and learning process of mathematics with a group of elementary school students from a rural population of Colombia, where the use of information and communications technology resources, as well as internet access in limited. The teachers implement microlearning so that children learn to solve arithmetic problems. The experience is descriptive with a non-probabilistic convenience sampling, developed from the creation and application of a virtual learning object whose pedagogical strategy was the use of microlearning. The study shows that the use of information and communications technology resources assist the students to learn mathematics. It also develops the office content, skill to interpret, know and solve mathematical problems from everyday situation to students
Social media platforms provide convenient means for users to participate in multiple online activities on various contents and create fast widespread interactions. However, this rapidly growing access has also increased the diverse information, and characterizing user types to understand people's lifestyle decisions shared in social media is challenging. In this paper, we propose a weakly supervised graph embedding based framework for understanding user types. We evaluate the user embedding learned using weak supervision over well-being related tweets from Twitter, focusing on 'Yoga', 'Keto diet'. Experiments on real-world datasets demonstrate that the proposed framework outperforms the baselines for detecting user types. Finally, we illustrate data analysis on different types of users (e.g., practitioner vs. promotional) from our dataset. While we focus on lifestyle-related tweets (i.e., yoga, keto), our method for constructing user representation readily generalizes to other domains.