Miracle-dz/UniFAR-FTUs huggingface dataset:
A Robust Embedded Discrete Fracture Modeling Workflow for Simulating Complex Processes in Field-Scale Fractured Reservoirs

Traditionally, fractured reservoir simulations use Dual-Porosity, Dual-Permeability (DPDK) models that can idealize fractures and misrepresent connectivity. The Embedded Discrete Fracture Modeling (EDFM) approach improves flow predictions by integrating a realistic fracture network grid within a structured matrix grid. However, small fracture cells with high conductivity that pose a challenge for simulators can arise and ad hoc strategies to remove them can alter connectivity or fail for field-scale cases. We present a new gridding algorithm that controls the geometry and topology of the fracture network while enforcing a lower bound on the fracture cell sizes. It honors connectivity and systematically removes cells below a chosen fidelity factor. Furthermore, we implemented a flexible grid coarsening framework based on aggregation and flow-based transmissibility upscaling to convert EDFMs to various coarse representations for simulation speedup. Here, we consider pseudo-DPDK (pDPDK) models to evaluate potential DPDK inaccuracies and the impact of strictly honoring EDFM connectivity via Connected Component within Matrix (CCM) models. We combine these components into a practical workflow that can efficiently generate upscaled EDFMs from stochastic realizations of thousands of geologically realistic natural fractures for ensemble applications. We first consider a simple waterflood example to illustrate our fracture upscaling to obtain coarse (pDPDK and CCM) models. The coarse simulation results show biases consistent with the underlying assumptions (e.g., pDPDK can over-connect fractures). The preservation of fracture connectivity via the CCM aggregation strategy provides better accuracy relative to the fine EDFM forecast while maintaining computational speedup. We then demonstrate the robustness of the proposed EDFM workflow for practical studies through application to an improved oil recovery (IOR) study for a fractured carbonate reservoir. Our automatable workflow enables quick screening of many possibilities since the generation of full-field grids (comprising almost a million cells) and their preprocessing for simulation completes in a few minutes per model. The EDFM simulations, which account for complicated multiphase physics, can be generally performed within hours while coarse simulations are about a few times faster. The comparison of ensemble fine and coarse simulation results shows that on average, a DPDK representation can lead to high upscaling errors in well oil and water production as well as breakthrough time while the use of a more advanced strategy like CCM provides greater accuracy. Finally, we illustrate the use of the Ensemble Smoother with Multiple Data Assimilation (ESMDA) approach to account for field measured data and provide an ensemble of history-matched models with calibrated properties.
Embedding Compression in Recommender Systems: A Survey

To alleviate the problem of information explosion, recommender systems are widely deployed to provide personalized information filtering services. Usually, embedding tables are employed in recommender systems to transform high-dimensional sparse one-hot vectors into dense real-valued embeddings. However, the embedding tables are huge and account for most of the parameters in industrial-scale recommender systems. In order to reduce memory costs and improve efficiency, various approaches are proposed to compress the embedding tables. In this survey, we provide a comprehensive review of embedding compression approaches in recommender systems. We first introduce deep learning recommendation models and the basic concept of embedding compression in recommender systems. Subsequently, we systematically organize existing approaches into three categories, namely low-precision, mixed-dimension, and weight-sharing, respectively. Lastly, we summarize the survey with some general suggestions and provide future prospects for this field.
Generalized additive model (GAM) based corrosion growth prediction model using mass in-line inspection (ILI) data

In the pipeline integrity management, corrosion growth plays an important role since it is critical to the determination of the re-inspection interval and development of appropriate maintenance plans. This paper describes the use of the Generalized Additive Model (GAM) to predict the growth rate of the depth of internal corrosion on oil and gas pipeline using mass in-line inspection (ILI) data. The model considers the obtained information from ILI data, including distance from elbow, distance from upstream girth weld, initial defect depth, pressure, elevation, as independent variables. The proposed model does not require corrosion data in different corrosion stages and prior knowledge about corrosion mechanism, which the present processes-based models need. Besides, GAM is a parametric free method so that less time is spent on parameters selection than other data-driven methods now used in industry. Thus, it is ideal for industrial application where obtaining growth path through multiple ILIs matching can be time intensive and prone to errors. The case of real ILI data with 1107 internal corrosion, collected from an in-service pipeline segment is applied to illustrate and validate the growth model. Through comparison with Back Propagation Neural Networks (BPNN) and General Regression Neural Network (GRNN), the results show that the proposed model is more accurate for the internal corrosion growth prediction, with the accuracy rate up to 98.4%, which is better than that of BPNN and GRNN based models, with the values of 94.8% and 95.7% respectively. It also has a faster computation speed, taking 0.497 s, while BPNN and GRNN spent 0.955 s and 2.991 s respectively.
Phase 2 trial of a DNA vaccine (pTVG-HP) and nivolumab in patients with castration-sensitive non-metastatic (M0) prostate cancer

Purpose We have previously reported that a plasmid DNA vaccine encoding prostatic acid phosphatase (pTVG-HP) had greater clinical activity when given in combination with pembrolizumab to patients with metastatic, castration-resistant prostate cancer. The current trial was conducted to evaluate vaccination with PD-1 blockade, using nivolumab, in patients with early, recurrent (M0) prostate cancer. Methods Patients with M0 prostate cancer were treated with pTVG-HP (100 µg administered intradermally) and nivolumab (240 mg intravenous infusion) every 2 weeks for 3 months, and then every 4 weeks for 1 year of total treatment. Patients were then followed for an additional year off treatment. The primary objectives were safety and complete prostate-specific antigen (PSA) response (PSA<0.2 ng/mL). Results 19 patients were enrolled. No patients met the primary endpoint of complete PSA response; however, 4/19 (21%) patients had a PSA decline >50%. Median PSA doubling times were 5.9 months pretreatment, 25.6 months on-treatment (p=0.001), and 9.0 months in the subsequent year off-treatment. The overall median radiographic progression-free survival was not reached. Grade 3 or 4 events included adrenal insufficiency, fatigue, lymphopenia, and increased amylase/lipase. 9/19 (47%) patients developed immune-related adverse effects (irAE). The development of irAE and increased CXCL9 were associated with increased PSA doubling time. Quantitative NaF PET/CT imaging showed the resolution of subclinical lesions along with the development of new lesions at each time point. Conclusions In this population, combining nivolumab with pTVG-HP vaccination was safe, and immunologically active, prolonged the time to disease progression, but did not eradicate disease. Quantitative imaging suggested that additional treatments targeting mechanisms of resistance may be required to eliminate tumors. Trial registration number NCT03600350.
Klinische Relevanz von Kontextfaktoren als Auslöser von Placebo- und Nocebo-Effekten bei muskuloskelettalen Schmerzen

Welche Rolle spielen Kontextfaktoren bei der Therapie? Und wie können sich Therapeut*innen diese zunutze machen? Das Autorenteam gibt in diesem Artikel umfassend Antwort auf diese Fragen. Sicher ist: Über die Modulation der Kontextfaktoren kann der spezifische Therapieeffekt positiv unterstützt werden. Therapeut*innen sollten dies bewusst nutzen.
Systemisches Denken, subjektive Befunde und das diagnostische „Schubladendenken“ bei ME/CFS – Eine vorwiegend qualitative Public-Health-Studie aus Patientensicht

Zusammenfassung Hintergrund ME/CFS (Myalgische Enzephalomyelitis/Chronisches Fatigue-Syndrom) ist eine vorwiegend als neuroimmunologische Multisystem-Erkrankung betrachtete Krankheit, die vielen Ärzt*innen in Deutschland noch immer unbekannt ist oder die von ihnen als psychosomatische Erkrankung eingeordnet wird. ME/CFS-Patient*innen berichten von den aus ihrer Sicht erheblichen Defiziten hinsichtlich der ärztlichen Behandlung und einer als problematisch empfundenen Arzt-Patienten-Beziehung (AP-Beziehung). Ziel der vorliegenden Studie ist es, aus Sicht der Betroffenen den Ablauf der Diagnosefindung als einen wichtigen Einflussfaktor auf die AP-Beziehung bei ME/CFS genauer zu analysieren. Methode Im Rahmen eines explorativen qualitativen Surveys wurden 544 ME/CFS-Erkrankte (> 20 J.; 455 ♀, 89 ♂) mit ärztlicher ME/CFS-Diagnose schriftlich nach ihren Erfahrungen hinsichtlich des Ablaufs der Diagnosefindung befragt. Das Sampling erfolgte zuvor durch Selbstaktivierung und über das Schneeballprinzip. Der zu beantwortende Fragebogen war analog zu einem fokussierten, standardisierten Leitfadeninterview aufgebaut. Die Auswertung erfolgte im Rahmen einer qualitativen Inhaltsanalyse nach Mayring. Einige der Ergebnisse wurden anschließend quantifiziert. Ergebnisse Die Proband*innen beschrieben den aus ihrer Sicht mangelhaften Ablauf der Diagnosefindung als zentralen Faktor einer problematischen AP-Beziehung bei ME/CFS. Sie berichteten von unzulänglichem Fachwissen, mangelnder Erfahrung im Umgang mit den Erkrankten und fehlender Fortbildungsbereitschaft der konsultierten Ärzt*innen. Viele Ärzt*innen stritten aus ihrer Sicht die Existenz von ME/CFS ab oder ordneten sie als rein psychosomatische Krankheit ein, beharrten auf ihrem Wissensstand, ignorierten das Patientenwissen und missachteten mitgebrachtes wissenschaftliches Informationsmaterial. Sie gingen nach „Standardprogramm“ vor, dachten in „Schubladen“ und seien unfähig zu systemischem Denken. Dies hätte erhebliche Auswirkungen auf die AP-Beziehung. Diskussion Aus Sicht der ME/CFS-Erkrankten sind der Ablauf der Diagnosefindung und die Anerkennung von ME/CFS als neuroimmunologische Multisystem-Erkrankung die zentralen Aspekte einer von ihnen als problematisch erlebten AP-Beziehung. Bereits in der Vergangenheit wurden als „subjektiv“ klassifizierte und damit ignorierte Befunde, das für die biomedizinisch orientierte Medizin charakteristische diagnostische „Schubladendenken“ und ein Gesundheitssystem, das dem systemischen Denken bei der Diagnosefindung entgegensteht, als Faktoren identifiziert, die erheblichen Einfluss auf das AP-Verhältnis haben können.
Subspecies divergence, hybridisation and the spatial environment shape phylosymbiosis in the microbiome of house mice

Closely related host species share similar symbionts, yet how host genetics and the environment affect symbiont communities at different stages of host genetic divergence remains largely unknown. Similarly, it is unclear whether host-symbiont associations result from or contribute to host divergence. We examined the intestinal community of 619 wild-caught mice from Germany’s European house mouse hybrid zone. Here, hybridisation upon secondary contact reflects divergence and could be traced gradually. Temporal and spatial factors were strong predictors of microbiome composition. Subspecies divergence predicted the composition similarity of the overall microbiome, specifically in the bacteria, parasite and fungal components. The effect of hybridisation was generally weak but significant for the fungal component. We confirmed our results in experiments with wild-derived inbred mice: subspecies’ genetic distances and hybridisation predicted the overall microbiome composition, and hybridisation further predicted fungal similarities among individuals. Fungi seemed more stable to the community perturbation of infection than other components of the microbiome. Differences between subspecies were more substantial across different microbiome components than those associated with hybridisation. Diverged microbiomes are a product of host divergence and are maintained by host genetics upon large environmental effects. These results provide a unique perspective into the ecoevolutionary processes shaping phylosymbiosis.
Dielectric analysis of surface modified nano-graphite: effects of frequency and thickness

Abstract The nano-graphite (NG) and acid modified nano-graphite (ANG) have been synthesized from graphite powder via mixture of strong acid (sulphuric acid and nitric acid) respectively by a soft chemistry route involving microwave, ultrasonic method and characterized by high-resolution electron microscopy (HR-TEM), scanning electron microscopy (SEM), fourier-transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD), clearly demonstrated the successful synthesis of acid modified NG. SEM images confirmed the surface morphology of NG, and ANG and HR-TEM study shows the nanoparticles size of NG and ANG. FTIR data confirmed the presence of acid functional groups on the surface of synthesized NG powder. XRD data of NG and ANG shows that 2θ is at 26.43° and 0.336 nm is an interlayer distance (d). NG and ANG pellets have been prepared for their dielectric analysis with frequency for different thickness. The dielectric loss tangent (tanδ) spectra show relaxation peak with frequency and peak shifts due to presence of polar groups in the ANG. The capacitance values of NG and ANG decrease with frequency and increase with thicknesses due to the capacitive nature of nanoparticles. The dielectric permittivity decreases with frequency and increases with thickness due to the charge orientation and dipole moment change of functional groups of synthesized NG, and ANG. The electrical conductivity of NG and ANG nanoparticles increases with frequency and thickness of NG and ANG pellets due to the conductive nature. Electrical conductivity and dielectric permittivity of NG and ANG are found to highly rely on thickness, according to the dielectric evaluation.
A real-time generation method for light field 3D image source based on instancing camera rendering

Light field 3D display is a glasses-free 3D display that samples and reconstructs the light field guided by ray optics. To increase the density of the discrete viewpoints, parallax images in more than tens or even hundreds of directions should be sampled, which adds up to computation and slowdowns the generation speed of the 3D image source. In this paper, a fast generation method for 3D image source based on instancing camera rendering is proposed, which greatly optimizes the speed of the parallax image rendering process in light field 3D display. Experimental results reveal that the proposed method can generate the 4K and 8K light field 3D image sources at over 60 frames per second (fps) with viewpoints less than 160 and 80, respectively, performing at least 106% and 94% faster than the conventional non-instancing method.
Towards a bottom-up approach for collaboration in cultural heritage: the case of the Council for British Research in the Levant (CBRL) Amman Institute and the JEA's Urban Heritage Preservation Committee

Since the 19th century, Jordan, with its diverse and rich heritage, has been a thriving hub for international scholars and researchers. To further this pursuit, several international research institutes have been established in the country. This article showcases the partnership between the Council for British Research in the Levant (CBRL) Amman Institute, an international institute whose research topics include archaeology and heritage, and the Jordan Engineers Association’s Urban Heritage Preservation Committee. Their collaboration aimed to attract architects and increase their interest and knowledge of Jordan’s heritage, in theory and practice, by designing a comprehensive programme of activities. These activities included a training course, webinars, a heritage award, heritage walks and heritage days. By considering the specific interests of the audience, and leveraging the knowledge and experience of both partners, they were able to collaborate with over 18 organizations in 9 events. The success and expansion of this partnership can be attributed to several factors, such as a wide range of activities, inclusive topics, bilingualism and efficient communication tools.
Uveitis Associated with Juvenile Idiopathic Arthritis

ABSTRACT Juvenile idiopathic arthritis (JIA) is the most common cause of uveitis in children. While symptoms are usually mild, persistent eye inflammation could lead to severe complications and impaired vision. It is essential that JIA patients at risk are diagnosed with uveitis early, receive adequate treatment, and avoid developing complications, such as cataract, glaucoma, and amblyopia. The purpose of this mini-review is to summarize the screening strategies and clinical management for JIA-associated uveitis (JIA-U) as well as the current state of molecular markers linked to this condition. Because glaucoma is one of the most common causes of visual loss in JIA-U, special focus will be put on this serious complication. We conclude by describing the current evidence regarding the long-standing question of whether chronic anterior uveitis without arthritis may be the same disease entity as JIA-U.
Challenge of vegetation greening on water resources sustainability: Insights from a modeling‐based analysis in Northwest China

Forest restoration policies are often implemented without the assessment of their full environmental impact. In this study, we investigated the challenges of vegetation greening resulted from forest restoration on water resource sustainability, using a model‐based simulation in northwestern China. Four different vegetation scenarios and 25 future climate scenarios were employed using the Soil and Water Assessment Tool model. Results suggest that (a) the mean annual evapotranspiration changes from only 7.2% in the barren case to 100% in the forest case; however, it produced a 35.2% reduction in average annual streamflow and a 157% increase in soil water storage. The upstream vegetation greening caused the enhancement of water retention, while also creating great challenges for future downstream water resource sustainability; (b) seasonal effect was significant in that 100% forest case increased evapotranspiration (+40%) but it also reduced the streamflow (−73%) compared to the barren case in growing season, which may exacerbate spring and summer drought; (c) changes of evapotranspiration and streamflow were only 0.3% and −0.9% at T + 3.9 °C when compared to the historic scenario in barren cases, while for all forest cases, variations were 3% and −21.8%, respectively; (d) vegetation greening induced more remarkable changes in hydrological components than those resulting from climate change. Our “what if” research provides new insights for promoting sustainable management of water resources and ecosystems in mountainous water source areas.
Strong and graded associations between level of asthma severity and all-cause hospital care use and costs in the UK

Background Hospital admissions account for a large share of the healthcare costs incurred by people with asthma. We assessed the hospital care use and costs associated with asthma severity using the UK Biobank cohort and linked healthcare data. Methods Adult participants with asthma at recruitment were classified using their prescription data into mild and moderate-to-severe asthma and matched separately to asthma-free controls by age, sex, ethnicity and location. The associations of asthma, by severity, with the annual number of all-cause hospital admissions, days spent in hospital and hospital costs were estimated over a 10-year follow-up period using three specifications of negative binomial regression models that differed according to the sociodemographic and clinical characteristics adjusted for. Results Of the 25 031 participants with active asthma, 80% had mild asthma and 20% had moderate-to-severe asthma. Compared with participants with mild asthma, those with moderate-to-severe asthma were on average 2.7 years older, more likely to be current (13.7% vs 10.4%) or previous (40.2% vs 35.2%) smokers, to have a higher body mass index (BMI), and to be suffering from a variety of comorbid diseases. Following adjustments for age, sex, ethnicity and location, people with mild asthma experienced on average 36% more admissions (95% CI 28% to 40%), 43% more days in hospital (95% CI 35% to 51%) and 36% higher hospital costs (95% CI 31% to 41%) annually than asthma-free individuals, while people with moderate-to-severe asthma experienced excesses of 93% (95% CI 81% to 107%), 142% (95% CI 124% to 162%) and 98% (95% CI 88% to 108%), respectively. Further adjustments for socioeconomic deprivation, smoking status, BMI and comorbidities resulted in smaller though still highly significant positive associations, graded by severity, between asthma and hospital use and costs. Conclusions Strong graded associations are reported between asthma severity and the extent of hospital use and costs in the UK. These findings could inform future assessments of the value of asthma management interventions.
Effect of adverse perinatal outcomes on postpartum maternal mental health in low-income and middle-income countries: a protocol for systematic review

Introduction More than three-fourths of adverse perinatal outcomes (preterm, small for gestational age, low birth weight, congenital anomalies, stillbirth and neonatal death) occur in low-income and middle-income countries. These adverse perinatal outcomes can have both short-term and long-term consequences on maternal mental health. Even though there are few empirical studies on the effect of perinatal loss on maternal mental illness, comprehensive information on the impact of adverse perinatal outcomes in resource-limited settings is scarce. Therefore, we aim to systematically review and synthesise evidence on the effect of adverse perinatal outcomes on maternal mental health. Methods and analysis The primary outcome of our review will be postpartum maternal mental illness (anxiety, depression, post-traumatic stress disorder and postpartum psychosis) following adverse perinatal outcomes. All peer-reviewed primary studies published in English will be retrieved from databases: PubMed, MEDLINE, CINAHL Ultimate (EBSCO), PsycINFO, Embase, Scopus and Global Health through the three main searching terms—adverse perinatal outcomes, maternal mental illness and settings, with a variant of subject headings and keywords. We will follow the Joanna Briggs Institute critical appraisal checklist to assess the quality of the studies we are including. The review findings will be reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 statement. Estimate-based meta-analysis will be performed. We will assess heterogeneity between studies using the I2 statistics and publication bias will be checked using funnel plots and Egger’s test. A subgroup analysis will be conducted to explore potential sources of heterogeneity (if available). Finally, the certainty of the evidence will be evaluated using the Grading of Recommendations, Assessment, Development and Evaluation approach. Ethics and dissemination Since this systematic review does not involve human participants, ethical approval is not required. The review will be submitted for publication in a peer-reviewed journal. PROSPERO registration number CRD42023405980.