bluuebunny/crossref_metadata_2025_split huggingface dataset:
Psychological interventions to promote self-forgiveness: a systematic review
Authors: Vismaya A. , Gopi Aswathy , Romate John , Rajkumar Eslavath 
Published: May 2024

Abstract
Background
Being able to forgive one’s own wrongdoings improves the health and well-being of a person. People find it difficult to forgive themselves due to different reasons. It is essential to enhance the ability to accept one’s deeds and thereby enhance self-forgiveness. The current systematic review’s objective is to comprehend the application and efficiency of numerous interventions that improve self-forgiveness.

Methods
The search was done on electronic databases such as PubMed, ERIC, Web of Science, PsycNet, Science Direct, and Google Scholar. The initial search yielded 399 articles. After the duplicate removal, 19 articles met the eligibility criteria. Two studies were identified through related references. Thus, 21 articles were finalized for review. The study adhered to the PRISMA recommendations for systematic reviews.

Results
The 21 finalized articles varied in method, participants, research design, duration, measurement tools used, and observed outcomes. Thirteen of the 21 finalized articles followed interventions specifically designed to promote self-forgiveness. Interventions are seen to be applied at both individual and group levels.

Conclusion
The review categorizes the interventions into self-directed and group. The self-directed interventions, notably those based on Enright’s process model, demonstrate its efficiency in nurturing self-forgiveness. Self-forgiveness interventions are also found to be effective in promoting other positive psychological and clinical variables. Further implications and future research avenues are outlined.
A proposed hybrid framework to improve the accuracy of customer churn prediction in telecom industry
Authors: Ouf Shimaa , Mahmoud Kholoud T. , Abdel-Fattah Manal A. 
Published: May 2024

AbstractIn the telecom sector, predicting customer churn has increased in importance in recent years. Developing a robust and accurate churn prediction model takes time, but it is crucial. Early churn prediction avoids revenue loss and improves customer retention. Telecom companies must identify these customers before they leave to solve this issue. Researchers have used a variety of applied machine-learning approaches to reveal the hidden relationships between different features. A key aspect of churn prediction is the accuracy level that affects the learning model's performance. This study aims to clarify several aspects of customer churn prediction accuracy and investigate state-of-the-art techniques' performance. However, no previous research has investigated performance using a hybrid framework combining the advantages of selecting suitable data preprocessing, ensemble learning, and resampling techniques. The study introduces a proposed hybrid framework that improves the accuracy of customer churn prediction in the telecom industry. The framework is built by integrating the XGBOOST classifier with the hybrid resampling method SMOTE-ENN, which concerns applying effective techniques for data preprocessing. The proposed framework is used for two experiments with three datasets in the telecom industry. This study determines which features are most crucial and influence customer churn, introduces the impact of data balancing, compares the classifiers' pre- and post-data balancing performances, and examines a speed-accuracy trade-off in hybrid classifiers. Many metrics, including accuracy, precision, recall, F1-score, and ROC curve, are used to analyze the results. All evaluation criteria are used to identify the most effective experiment. The results of the accuracy of the hybrid framework that respects balanced data outperformed applying the classifier only to imbalanced data. In addition, the results of the proposed hybrid framework are compared to previous studies on the same datasets, and the result of this comparison is offered. Compared with the review of the latest works, our proposed hybrid framework with the three datasets outperformed these works.
Hybrid topic modeling method based on dirichlet multinomial mixture and fuzzy match algorithm for short text clustering
Authors: Alsmadi Mutasem K. , Alzaqebah Malek , Jawarneh Sana , ALmarashdeh Ibrahim , Al-Betar Mohammed Azmi , Alwohaibi Maram , Al-Mulla Noha A. , Ahmed Eman AE , AL Smadi Ahmad 
Published: May 2024

AbstractTopic modeling methods proved to be effective for inferring latent topics from short texts. Dealing with short texts is challenging yet helpful for many real-world applications, due to the sparse terms in the text and the high dimensionality representation. Most of the topic modeling methods require the number of topics to be defined earlier. Similarly, methods based on Dirichlet Multinomial Mixture (DMM) involve the maximum possible number of topics before execution which is hard to determine due to topic uncertainty, and many noises exist in the dataset. Hence, a new approach called the Topic Clustering algorithm based on Levenshtein Distance (TCLD) is introduced in this paper, TCLD combines DMM models and the Fuzzy matching algorithm to address two key challenges in topic modeling: (a) The outlier problem in topic modeling methods. (b) The problem of determining the optimal number of topics. TCLD uses the initial clustered topics generated by DMM models and then evaluates the semantic relationships between documents using Levenshtein Distance. Subsequently, it determines whether to keep the document in the same cluster, relocate it to another cluster, or mark it as an outlier. The results demonstrate the efficiency of the proposed approach across six English benchmark datasets, in comparison to seven topic modeling approaches, with 83% improvement in purity and 67% enhancement in Normalized Mutual Information (NMI) across all datasets. The proposed method was also applied to a collected Arabic tweet and the results showed that only 12% of the Arabic short texts were incorrectly clustered, according to human inspection.
Downscaling Taiwan precipitation with a residual deep learning approach
Authors: Hsu Li-Huan , Chiang Chou-Chun , Lin Kuan-Ling , Lin Hsin-Hung , Chu Jung-Lien , Yu Yi-Chiang , Fahn Chin-Shyurng 
Published: May 2024

AbstractIn response to the growing demand for high-resolution rainfall data to support disaster prevention in Taiwan, this study presents an innovative approach for downscaling precipitation data. We employed a hierarchical architecture of Multi-Scale Residual Networks (MSRN) to downscale rainfall from a coarse 0.25-degree resolution to a fine 0.0125-degree resolution, representing a substantial challenge due to a resolution increase of over 20 times. Our results demonstrate that the hierarchical MSRN outperforms both the one-step MSRN and linear interpolation methods when reconstructing high-resolution daily rainfall. It surpasses the linear interpolation method by 15.1 and 9.1% in terms of mean absolute error and root mean square error, respectively. Furthermore, the hierarchical MSRN excels in accurately reproducing high-resolution rainfall for various rainfall thresholds, displaying minimal biases. The threat score (TS) highlights the hierarchical MSRN's capability to replicate extreme rainfall events, achieving TS scores exceeding 0.54 and 0.46 at rainfall thresholds of 350 and 500 mm per day, outperforming alternative methods. This method is also applied to an operational global model, the ECMWF’s daily rainfall forecasts over Taiwan. The evaluation results indicate that our approach is effective at improving rainfall forecasts for thresholds greater than 100 mm per day, with more significant improvement for the 1- to 3-day lead forecast. This approach also offers a realistic visual representation of fine-grained rainfall distribution, showing promise for making significant contributions to disaster preparedness and weather forecasting in Taiwan.
Quantum annealing-aided design of an ultrathin-metamaterial optical diode
Authors: Kim Seongmin , Park Su-Jin , Moon Seunghyun , Zhang Qiushi , Hwang Sanghyo , Kim Sun-Kyung , Luo Tengfei , Lee Eungkyu 
Published: May 2024

AbstractThin-film optical diodes are important elements for miniaturizing photonic systems. However, the design of optical diodes relies on empirical and heuristic approaches. This poses a significant challenge for identifying optimal structural models of optical diodes at given wavelengths. Here, we leverage a quantum annealing-enhanced active learning scheme to automatically identify optimal designs of 130 nm-thick optical diodes. An optical diode is a stratified volume diffractive film discretized into rectangular pixels, where each pixel is assigned to either a metal or dielectric. The proposed scheme identifies the optimal material states of each pixel, maximizing the quality of optical isolation at given wavelengths. Consequently, we successfully identify optimal structures at three specific wavelengths (600, 800, and 1000 nm). In the best-case scenario, when the forward transmissivity is 85%, the backward transmissivity is 0.1%. Electromagnetic field profiles reveal that the designed diode strongly supports surface plasmons coupled across counterintuitive metal–dielectric pixel arrays. Thereby, it yields the transmission of first-order diffracted light with a high amplitude. In contrast, backward transmission has decoupled surface plasmons that redirect Poynting vectors back to the incident medium, resulting in near attenuation of its transmission. In addition, we experimentally verify the optical isolation function of the optical diode.
Co-production of 1,3-propanediol and phage phiKpS2 from the glycerol fermentation by Klebsiella pneumoniae
Authors: Duan Suyang , Zhang Zhirong , Wang Xiaoli , Sun Yaqin , Dong Yuesheng , Ren Lina , Geng Lili , Xiu Zhilong 
Published: May 2024

AbstractAs an alternative to antibiotics in response to antimicrobial-resistant infections, bacteriophages (phages) are garnering renewed interest in recent years. However, the massive preparation of phage is restricted using traditional pathogens as host cells, which incurs additional costs and contamination. In this study, an opportunistic pathogen, Klebsiella pneumoniae used to convert glycerol to 1,3-propanediol (1,3-PDO), was reused to prepare phage after fermentation. The phage infection showed that the fed-batch fermentation broth containing 71.6 g/L 1,3-PDO can be directly used for preparation of phage with a titer of 1 × 108 pfu/mL. Then, the two-step salting-out extraction was adopted to remove most impurities, e.g. acetic acid (93.5%), ethanol (91.5%) and cells (99.4%) at the first step, and obtain 1,3-PDO (56.6%) in the top phase as well as phage (97.4%) in the middle phase at the second step. This integrated process provides a cheap and environment-friendly manner for coproduction of 1,3-PDO and phage.
Graphical abstract
Evaluation of lesion contrast in the walk-through long axial FOV PET scanner simulated with XCAT anthropomorphic phantoms
Authors: Dadgar Meysam , Maebe Jens , Vandenberghe Stefaan 
Published: May 2024

Abstract
Background
This study evaluates the lesion contrast in a cost-effective long axial field of view (FOV) PET scanner, called the walk-through PET (WT-PET). The scanner consists of two flat detector panels covering the entire torso and head, scanning patients in an upright position for increased throughput. High-resolution, depth-of-interaction capable, monolithic detector technology is used to provide good spatial resolution and enable detection of smaller lesions.

Methods
Monte Carlo GATE simulations are used in conjunction with XCAT anthropomorphic phantoms to evaluate lesion contrast in lung, liver and breast for various lesion diameters (10, 7 and 5 mm), activity concentration ratios (8:1, 4:1 and 2:1) and patient BMIs (18–37). Images were reconstructed iteratively with listmode maximum likelihood expectation maximization, and contrast recovery coefficients (CRCs) were obtained for the reconstructed lesions.

Results
Results shows notable variations in contrast recovery coefficients (CRC) across different lesion sizes and organ locations within the XCAT phantoms. Specifically, our findings reveal that 10 mm lesions consistently exhibit higher CRC compared to 7 mm and 5 mm lesions, with increases of approximately 54% and 330%, respectively, across all investigated organs. Moreover, high contrast recovery is observed in most liver lesions regardless of diameter or activity ratio (average CRC = 42%), as well as in the 10 mm lesions in the lung. Notably, for the 10 mm lesions, the liver demonstrates 42% and 62% higher CRC compared to the lung and breast, respectively. This trend remains consistent across lesion sizes, with the liver consistently exhibiting higher CRC values compared to the lung and breast: 7 mm lesions show an increase of 96% and 41%, while 5 mm lesions exhibit approximately 294% and 302% higher CRC compared to the lung and breast, respectively.

Conclusion
A comparison with a conventional pixelated LSO long axial FOV PET shows similar performance, achieved at a reduced cost for the WT-PET due to a reduction in required number of detectors.
Power equalization and optimization of photovoltaic module based on forward-flyback converter
Authors: Tang DaiBin , Siaw Fei Lu , Thio Tzer Hwai Gilbert 
Published: May 2024

AbstractThis paper focuses on enhancing the energy extraction efficiency of photovoltaic (PV) modules through the use of a straightforward power converter and control algorithm. This research delves into the electrical characteristics of PV modules, explaining the concepts of global maximum power point, and local maximum power points. By integrating maximum power point tracking algorithms and differential power processing technology, an innovative scheme for power equalization and optimization of PV modules is introduced. The scheme is based on a single-switch multi-winding forward-flyback converter. Using the STP-340-72-Vfh-type PV module as a case study, a simulation model is developed with PLECS simulation software. The simulations cover 30 different irradiance scenarios. The findings illustrate the effectiveness of the proposed PV module power optimization system in achieving maximum power output under different irradiance conditions, achieving an average efficiency of 94.61%. This efficiency rate is 13.95% greater than that of existing global maximum power tracking schemes.
Eye-movement desensitisation and reprocessing therapy (EMDR) to prevent transition to psychosis in people with an at-risk mental state (ARMS): mixed method feasibility study
Authors: Strelchuk Daniela , Wiles Nicola , Turner Katrina , Derrick Catherine , Martin David , Davies Jonathan , Zammit Stan 
Published: May 2024

BackgroundTrauma plays an important role in the development of psychosis, but no studies have investigated whether a trauma-focused therapy could prevent psychosis.AimsThis study aimed to establish whether it would be feasible to conduct a multicentre randomised controlled trial (RCT) to prevent psychosis in people with an at-risk mental state (ARMS), using eye-movement desensitisation and reprocessing therapy (EMDR).MethodThis started as a mixed-method randomised study comparing EMDR to treatment as usual but, as a result of low participant recruitment, was changed to a single-arm feasibility study. The proposed primary outcome for an RCT was transition to psychosis at 12-month follow-up. Data on secondary outcomes were also collected. Qualitative interviews were conducted with patients and therapists.ResultsFourteen participants were recruited from the Early Intervention teams. Most people who expressed an interest in taking part attended an assessment to determine eligibility. All those eligible consented to take part. A total of 64% (7 of 11) of participants who were offered EMDR were followed up at 12 months. Of the 11 participants offered EMDR, one (11%, 95% CI: 0.2%, 48%) transitioned to psychosis. Nine patients and three therapists were interviewed. Participants who completed therapy (n = 4; mean 10.5 sessions) found EMDR helpful, but those who discontinued (n = 6; mean 5.2 sessions) said it had not benefitted them overall. Therapists said EMDR could be effective, although not for all patients.ConclusionsFuture studies recruiting people with an ARMS to an RCT may need to extend recruitment beyond Early Intervention teams. Although some individuals found EMDR helpful, reasons for discontinuing need to be addressed in future studies.
Personalized Timing for Allogeneic Stem-Cell Transplantation in Hematologic Neoplasms: A Target Trial Emulation Approach Using Multistate Modeling and Microsimulation
Authors: Gregorio Caterina , Spreafico Marta , D'Amico Saverio , Sauta Elisabetta , Asti Gianluca , Lanino Luca , Tentori Cristina Astrid , Platzbecker Uwe , Haferlach Torsten , Diez-Campelo Maria , Fenaux Pierre , Komrokji Rami , Della Porta Matteo Giovanni , Ieva Francesca 
Published: May 2024

PURPOSE Decision about the optimal timing of a treatment procedure in patients with hematologic neoplasms is critical, especially for cellular therapies (most including allogeneic hematopoietic stem-cell transplantation [HSCT]). In the absence of evidence from randomized trials, real-world observational data become beneficial to study the effect of the treatment timing. In this study, a framework to estimate the expected outcome after an intervention in a time-to-event scenario is developed, with the aim of optimizing the timing in a personalized manner. METHODS Retrospective real-world data are leveraged to emulate a target trial for treatment timing using multistate modeling and microsimulation. This case study focuses on myelodysplastic syndromes, serving as a prototype for rare cancers characterized by a heterogeneous clinical course and complex genomic background. A cohort of 7,118 patients treated according to conventional available treatments/evidence across Europe and United States is analyzed. The primary clinical objective is to determine the ideal timing for HSCT, the only curative option for these patients. RESULTS This analysis enabled us to identify the most appropriate time frames for HSCT on the basis of each patient's unique profile, defined by a combination relevant patients' characteristics. CONCLUSION The developed methodology offers a structured framework to address a relevant clinical issue in the field of hematology. It makes several valuable contributions: (1) novel insights into how to develop decision models to identify the most favorable HSCT timing, (2) evidence to inform clinical decisions in a real-world context, and (3) the incorporation of complex information into decision making. This framework can be applied to provide medical insights for clinical issues that cannot be adequately addressed through randomized clinical trials.
A new dawn for the study of cell type evolution
Authors: Pomaville Matthew B. , Sattler Sydney M. , Abitua Philip B. 
Published: May 2024

ABSTRACT
Animal evolution is influenced by the emergence of new cell types, yet our understanding of this process remains elusive. This prompts the need for a broader exploration across diverse research organisms, facilitated by recent breakthroughs, such as gene editing tools and single-cell genomics. Essential to our understanding of cell type evolution is the accurate identification of homologous cells. We delve into the significance of considering developmental ontogeny and potential pitfalls when drawing conclusions about cell type homology. Additionally, we highlight recent discoveries in the study of cell type evolution through the application of single-cell transcriptomics and pinpoint areas ripe for further exploration.
Multiple cis-regulatory elements control prox1a expression in distinct lymphatic vascular beds
Authors: Panara Virginia , Yu Hujun , Peng Di , Staxäng Karin , Hodik Monika , Filipek-Gorniok Beata , Kazenwadel Jan , Skoczylas Renae , Mason Elizabeth , Allalou Amin , Harvey Natasha L. , Haitina Tatjana , Hogan Benjamin M. , Koltowska Katarzyna 
Published: May 2024

ABSTRACT
During embryonic development, lymphatic endothelial cell (LEC) precursors are distinguished from blood endothelial cells by the expression of Prospero-related homeobox 1 (Prox1), which is essential for lymphatic vasculature formation in mouse and zebrafish. Prox1 expression initiation precedes LEC sprouting and migration, serving as the marker of specified LECs. Despite its crucial role in lymphatic development, Prox1 upstream regulation in LECs remains to be uncovered. SOX18 and COUP-TFII are thought to regulate Prox1 in mice by binding its promoter region. However, the specific regulation of Prox1 expression in LECs remains to be studied in detail. Here, we used evolutionary conservation and chromatin accessibility to identify enhancers located in the proximity of zebrafish prox1a active in developing LECs. We confirmed the functional role of the identified sequences through CRISPR/Cas9 mutagenesis of a lymphatic valve enhancer. The deletion of this region results in impaired valve morphology and function. Overall, our results reveal an intricate control of prox1a expression through a collection of enhancers. Ray-finned fish-specific distal enhancers drive pan-lymphatic expression, whereas vertebrate-conserved proximal enhancers refine expression in functionally distinct subsets of lymphatic endothelium.
Spectral programmable mid-infrared optical parametric oscillator
Authors: Liang Junrui , Xu Jiangming , Ke Yanzhao , Li Sicheng , He Junhong , Guo Yidong , Zhang Yang , Ma Xiaoya , Ye Jun , Li Xiao , Leng Jinyong , Zhou Pu 
Published: May 2024

A spectral programmable, continuous-wave mid-infrared (MIR) optical parametric oscillator (OPO), enabled by a self-developed high-power spectral tailorable fiber laser, was proposed and realized. While operating at a single-wavelength, the maximum idler power reached 5.53 W at 3028 nm, with a corresponding pump-to-idler conversion efficiency of 14.7%. The wavelength number switchable output was available from one to three. The single idler was tunable in a range of 528 nm (2852–3380 nm). In a dual-wavelength operation, the interval between two idlers could be flexibly tuned for 470 nm (53–523 nm), and the intensity of each channel was controllable. Triple-wavelength idler emission was realized, meanwhile exhibiting spectral custom-tailored characteristics. Furthermore, we balanced the parametric gain through the pre-modulating broadband multi-peak pump spectra, enabling a 10 dB bandwidth adjustment of the idler emission from 20 to 125 nm. This versatile mid-infrared laser, simultaneously featuring wide tuning, multi-wavelength operation, and broad bandwidth manipulation, has great application potential in composition detection, terahertz generation, and speckle-free imaging.
Encuentros con el estado. Transferencias monetarias condicionadas en la sierra norte de puebla, México
Authors: Rivermar Pérez María Leticia , D'Aubeterre Buznego María Eugenia 
Published: May 2024

añeja vocación agrícola en la Sierra Norte de Puebla, en el centro del país que, reducida a la condición de “lugar remanente”, fue especializándose desde el último tercio del pasado siglo en la provisión de trabajadores baratos a la economía estadounidense. Identificamos dos momentos clave de esa regulación operando bajo dos distinguibles formas de hegemonía. Focalizamos especialmente el encuentro de mujeres retornadas con la operación del Programa gubernamental condicionadas Oportunidades, un modelo de intervención que privilegia la asistencia focalizada sobre el bienestar general. El análisis se fundamenta en información etnográfica compilada en ambos lados de la frontera entre 2007 y 2014, en la coyuntura de la Gran Recesión en Estados Unidos