bluuebunny/crossref_metadata_2025 huggingface dataset:
Impact of Impurities on the Economic Assessment of Carbon Dioxide Capture, Transport, and Storage
Authors: Seo Kwangduk , Choi Yoojin , Lee Kun Sang
Published: March 2024

The study proposes a techno-economic evaluation of geological storage of CO2 coupled with enhanced oil recovery based on the composition and price of the CO2 stream. A compositional reservoir model was developed to analyze the effect of CO2 and impurities on oil recovery and storage efficiency. The results indicate that most impurities increase the minimum miscibility pressure between the injected gas and the reservoir fluid. The higher the impurity content of the CO2, the lower the sweep and displacement efficiencies, which decreased oil recovery, while the amount of stored CO2 compared to the injected carbon increased. According to an economic analysis that includes capture, transportation, and storage, the net present values (NPVs) from CO2 composition scenarios ranging from 77.4% to 99.9% are almost identical. However, a sensitivity analysis of the economic parameters indicated that NPV is sensitive to the price of oil, discount rates, and tax policy.
Pore-Scale Investigation of Caprock Integrity in Underground Hydrogen Storage
Authors: Wang Hai , Chen Shengnan , Deng Peng , Wang Muming , Xu Zhengxiao
Published: March 2024

This study investigates the sealing capacity of shale caprocks for underground storage of hydrogen (H2) utilizing mercury intrusion capillary pressure (MICP) data of caprock samples. The research explores the influence of capillary forces on gas leakage through caprocks and evaluates the effectiveness of caprocks in confining H2 and CO2. Results indicate that the interfacial tension between H2 and water/brine is significantly higher than that between CO2 and water/brine, leading to greater column heights for H2 (ranging from 59 to 667 meters) compared to CO2 (ranging from 20 to 500 meters). Additionally, the study reveals that thicker caprock layers significantly reduce the rate of gas leakage, with CO2 exhibiting higher mass leakage rates due to its larger molar mass and lower interfacial tension compared to H2. Furthermore, while the capillary bundle model estimates higher leakage rates, the pore network model, accounting for the shielding effect of small channels, predicts lower leakage rates, demonstrating its potential for more accurate estimations. The findings highlight the potential of shale caprocks as effective barriers for H2 and CO2 storage, emphasizing the importance of capillary forces and caprock thickness in mitigating gas leakage.
Investigating the Effect of Carbon Dioxide Concentration on Hydrate Formation Risk from Water Alternating Gas (WAG) Changeover Operations
Authors: Moghaddam F. Sahari , Abdi M. Abedinzadegan , James L. A.
Published: March 2024

Hydrate formation is a flow assurance challenge for offshore oil and gas operations with subsea pipelines, wells, and tiebacks. In Water-Alternating-Gas (WAG) operations, hydrates can form within the injection wells when switching from water-to-gas and vice versa. This study investigates hydrate formation in a WAG injection well under water-to-gas and gas-to-water changeover operations. Compositional changes, temperature, and required thermodynamic inhibitor are evaluated within the injector well where hydrate formation is likely.

The simulation study is conducted on a representative offshore field at a seabed depth of 124 m and temperature of 3ºC. The dynamic multiphase flow simulator was used for the WAG simulation and fluid modeling. The subcooling is evaluated to detect potential hydrate formation. After determining the hydrate risk zones for water-to-gas and gas-to-water operations through detecting the regions with positive values of subcooling where the fluids can be exposed to hydrate formation, the effects of gas composition (CO2 content) change, and methanol injection on the subcooling profile are evaluated.

Simulation results indicated a higher risk of hydrate formation after the start of water injection in gas-to-water during an offshore injection well changeover operation due to slower fluid displacement. In both cases, after starting the injection operation the subcooling is reduced significantly for the entire well. However, in the water-to-gas changeover, the sections of the well that had water and gas were outside the hydrate formation region after 1 hour of gas injection. For a water injection rate of 2,300 m3/day, 1 MSm3/d of gas was adequate to displace the entire water column in the well into the reservoir in the water-to-gas changeover operation. For gas-to-water changeover operation, full displacement of the gas occurred after 11 hours and 9 hours for the base natural gas case and the natural water with NG (CO2 44 wt%) case, respectively. Methanol slug injection (5 m3) at the end of the water injection inhibited hydrate formation for the entire length of the well. Fluid model simulations indicate that changing the CO2 composition (5-44 wt%) has a noticeable effect on the phase envelope and shifts the hydrate curve up to 2ºC.

Few previous studies have investigated WAG changeover operations with the effect of CO2 and methanol concentrations on hydrate formation. One study found hydrate formation risk in water-to-gas operations based on onshore well with no attention to the impact of thermodynamic inhibitors and gas composition. This study investigates the hydrate formation risk, the impact of natural gas (NG) composition (CO2, 5-44 wt%), and the applicability of methanol in WAG changeover operations in an offshore well.
Introducing a New Hybrid Data-Physics Architecture for Production Forecasting in Unconventional Wells
Authors: Matoorian R. , Malaieri M. , Shor R. , Aguilera R.
Published: March 2024

This research presents a new architecture and implementation to overcome inherent challenges in leveraging machine learning (ML) for evaluating production performance in unconventional wells. By implementing a hybrid data-physics architecture (HDP), our goal is to effectively address several persistent hurdles, including generalizability limitations across diverse samples, the necessity for extensive training datasets, and the discrepancies between model predictions and fundamental physical principles. These fundamental constraints form the focal points of our comprehensive investigation.

This new HDP architecture seamlessly integrates a physics-based equation into the framework of a deep neural network model. The training dataset encompasses a wide array of influencing factors on production rates, encompassing information that may not readily conform to conventional physical equations. This sophisticated approach enables the inclusion of supplementary data, thereby significantly enhancing the precision of production forecasts. As a result, these data points are adeptly employed to derive the model's underlying physical parameters, leading to highly accurate production rate calculations. Once these parameters are estimated with minimal error, the trained model exhibits exceptional proficiency in forecasting both short-term and long-term production rates consistently.

To thoroughly evaluate the efficacy of the developed architecture, an extensive assessment was conducted using unconventional wells situated in the Duvernay resource within the western Canadian sedimentary basin (WCSB). This evaluation spanned three different methodologies to compute future production rates: with physical decline curve equations including Arps, Power Law, and Duong, with data-driven modeling where production rate forecasted with different powerful ML techniques including Random Forest, Ada-Boost, and K-Nearest Neighbors, and finally with HDP modeling. The results compared with different statistical metrics across all evaluated scenarios, the hybrid model consistently exhibited superior precision in production forecasting.

A noteworthy advantage intrinsic to the new hybrid architecture is its remarkable capacity to generate more accurate predictions without requiring extensive sample points for training. This characteristic proves especially advantageous for newly established wells with limited production histories. Moreover, the predictive outcomes yielded by the hybrid model demonstrate a strong alignment with fundamental physical models, thereby validating its applicability across both short-term and long-term production forecasting contexts.
Synergizing Hybrid Agile-Scrum and CRISP-DM Approaches in Data Science Project Management
Authors: Amirian E. , Abdollahzadeh A. , Sulaiman N.
Published: March 2024

Delivering a data science project encompasses several hurdles that need to be addressed. As the project matures, the business requirements may change over time. In addition, uncertainties associated with data integrity, quantity, and quality can have an impact on the success of the project. The effectiveness of advanced analytics and algorithms that is changing depending on the complexity of the project and ambiguities in project values potentially will lead to adverse effects on deliverables and task prioritization.

Agile-scrum framework enables projects with time-boxed iterations (sprints). It also introduces delivery through increments (MVPs) that assist in reaching the overall aim or vision of the product. However, backlog prioritization and sequence of tasks is not bounded by any criteria and depends fully on product owner’s understanding of product goal and value. On the other hand, CRISP-DM is a solid place to start for advising developers on the steps and tasks needed to build a data science product. It enables exploratory and discovery work through iterations to satisfy the requirements of the data science project. However, the lack of time element within the process might cause infinite iterative cycles and delay delivery to customers.

At Petronas, we have integrated a hybrid strategy that envelops the CRISP-DM process within defined time-limited sprints. The process flow from CRISP-DM can help to plan which tasks to be assigned in which sprint. Properly assigned scrum team roles will ensure proper establishment of scrum. Furthermore, conducting scrum events will enable effective and productive customers engagement. Periodic inspection of scrum artifacts will also ensure alignment with product goals.

This hybrid approach demonstrates how the change in requirements can be strategically addressed by utilizing the Agile-Scrum CRISP-DM methodology while ensuring that the product goal is achieved. It also highlights how Agile-Scrum ensures successful delivery of product, maximizing product value, and customer satisfaction, while CRISP-DM can guide us in planning for data science project sprints.
Tight Gas Production Prediction in the Southern Montney Play Using Machine Learning Approaches
Authors: Hui Gang , Yao Fuyu , Pi Zhiyang , Bao Penghu , Wang Wei , Wang Muming , Wang Hai , Gu Fei
Published: March 2024

Recently, the machine learning approach has been used to forecast tight gas production from unconventional resources. However, the performance of machine learning-based predictive models has not been successful with respect to actual field production. The poor performance has been ascribed to several factors, including the relatively few field data and few input data from geological, geomechanical, and operational information. This study uses big data analytics to develop a prediction model for Southern Montney Play in the province of British Columbia, Canada. First, a complete dataset is built, including ten geological, geomechanical, and operational characteristics for 3146 horizontal wells in Southern Montney Play. Then, the relationships between the first-year production and input parameters are evaluated, and controlling factors are identified. Finally, a comparative study of prediction models with distinctive training algorithms is conducted to find the best algorithm for predicting first-year production. The results reveal that the top features that contribute most to tight gas productivity are total injection volume, porosity, and formation pressure. Features with secondary effects are net thickness, fracturing depth, and number of stages. The other features, including permeability, gas saturation, horizontal length, and cumulative proppant injection, are the least related. The Random Forest algorithm with the highest correlation coefficient (R2=0.82) and lowest mean absolute error (MSE=0.15) is picked. The Random Forest-based production prediction matches the observed field production, indicating that the northeastern portion of the study area has the highest estimated tight gas productivity. This procedure can be applied to additional scenarios involving tight gas production and used to guide the future site selection and fracturing job size, thereby achieving effective tight gas development.
Creating a Multiphase Production Model Tailored to Deviated Oil-Producing Wells for Integration as Input into a Machine Learning Model for ESP Survival Analysis
Authors: Sindi Wisam , Fruhwirth Rudolf , Gamsjäger Ernst , Hofstätter Herbert
Published: March 2024

A comprehensive model estimates wellbore production variables, including flow velocities, phase fractions/holdups, fluid properties, pressure/temperature profiles, and Electrical Submersible Pump (ESP) performance metrics. Coupled with instrument data, these inputs support productivity surveillance and ESP status prediction driven by machine learning (ML). The wellbore production model's effectiveness is evaluated by comparing it with industry-sourced field data encompassing muti-probe production logging tool (PLT) measurements from multiphase producing wells.

This work is based on Nodal Analysis, which involves dividing the wellbore into numerous sections and applying the conservation of mass, momentum, and energy principles to model pressure, temperature, and other essential profiles. Three multiphase flow methods are employed: homogeneous flow, separated flow with slip (Hagedorn-Brown method), and separated flow with slip and flow pattern (Mukherjee-Brill method). Affinity Laws are used to describe the ESP performance. A machine learning model is trained using manually labelled historical data subsets comprising model results and actual field measurements. Its purpose is to recognize ESP operational statuses such as pump off, normal operation, electrical wear, and mechanical wear. Supervised feature selection methods are utilized to identify the most relevant parameters.

The along the wellbore measurements from PLT e.g. the phase holdup (also referred to as in-situ volume fraction) is in agreement with the modelling results. For a wide range of liquid rates and gas-liquid ratios, flow rates can be determined with an average deviation of less than 10%. Machine learning feature selection methods, such as sequential backward elimination, reveal that production modelling results are crucial for identifying ESP statuses, including mass rate, viscosity, and pump parameters like efficiency. This study demonstrates that hydrodynamic modelling results provide additional information for ML training that electro-mechanical raw data may lack. Thanks to the integration of hydrodynamic modelling and raw data supplied to the ML algorithm, it can classify operational statuses with 99% accuracy and predict ESP failure months in advance.

When the model is connected to standard wellbore instrumentation, it enables near real-time production monitoring and provides essential hydrodynamic input to ML-based algorithms for continuous monitoring ESP equipment. It can be used as a virtual flowmeter (VFM) or a validation tool for multiphase flowmeters (MPFM), enhancing allocation split accuracy and enabling operators to concentrate on true contributors. The methodology can be integrated into a digital oilfield (DOF) system, employed as a digital twin, or, as demonstrated in this study, integrated into asset modelling with ESP survival analysis and failure prediction using ML.
Successful Implementation of A Solids-Free Fluid Loss System Used in Coiled Tubing Operations in Argentina
Authors: Gimenez Leonardo D. , Betti Enzo J.
Published: March 2024

This paper highlights the successful implementation of a solids-free fluid loss system during Coiled Tubing (CT) interventions executed in the Austral Basin. This treatment contains a low-viscosity, solids-free, Relative Permeability Modifier (RPM) for lost circulation control during sand cleanout operations performed in these low-pressure reservoir wells where the Bottom Hole Pressure (BHP) exceeds the reservoir pressure. Avoiding fluid losses reduces the likelihood of getting stuck CT from settling sand or differential sticking.

Significant experience has been acquired in Argentina using this system to avoid fluid loss during interventions, and the correct system formulation has been defined based on field information, lab testing, and experience. This system was applied mainly during CT sand cleanout operations in cased gas wells with sandstone formations and severe fluid losses. Pills of RPM are pumped and forced into the fractured zone without any damage to the formation before carrying out the CT sand cleanout intervention.

RPMs are being formulated and used within the oil industry to help mitigate fluid losses during intervention. The objective is to decrease the relative permeability to water without any (or minimum) modification to the relative permeability to oil. This methodology can be applied in water-wet formations without oil permeability modification, and in the Austral Basin in Argentina, this implementation has demonstrated its benefits during workover interventions. Following RPM treatments, wells were cleaned out without any circulation fluid losses or stuck pipe issues, leading to the successful execution of planned well programs.

The findings of this study can benefit the oil and gas industry by offering a viable and alternative solution for the intervention of depleted gas wells where it is necessary to avoid any fluid losses to the formation during any workover or CT intervention.
Validity and reliability of the Arabic versions of the General Risk Propensity Scale (GRiPS) and the Risk Proneness Short Scale (R-1)
Authors: Fekih-Romdhane Feten , Malaeb Diana , Sakr Fouad , Dabbous Mariam , Obeid Sahar , Hallit Souheil
Published: March 2024

Background
Until today, only a few studies have been conducted in Arab countries and settings to understand the prevalence and correlates of engaging in domain-specific risky behaviors. However, no or very little research attention has been paid to risk-taking propensity as a predictor of such behaviors. In this study, we propose to validate two short self‐report measures of general risk propensity in Arabic, the General Risk Propensity Scale (GRiPS) and the Risk Proneness Short Scale (R-1)
Methods
An online survey was carried-out in a sample of native Arabic-speaking adults from Lebanon (n = 748, mean age of 34.48 ± 13.25 years, 66.5% females). The forward-backward translation method was adopted.
Results
The original one-factor structure of the GRiPS was replicated in this study, except for two items that were removed (item 4 “I would take a risk even if it meant I might get hurt”, and item 5 “Taking risks is an important part of my life”). Analyses showed that the R-1 loaded on the same factor as the GRiPS, and that its scores correlated positively with GRiPS scores. McDonald’s ω and Cronbach’s α values were very good for both the GRiPS (ω and α values of .89) and the R-1 (ω and α values of .87), indicating internal consistency of the scales. The GRiPS exhibited measurement invariance with respect to gender at the configural, metric, and scalar levels. The R-1 was also found to be gender invariant. Finally, medium-sized positive correlations were found between GRiPS/R-1 scores and the impulsiveness dimensions “sensation seeking” and “urgency”.
Conclusion
The Arabic GRiPS and the R-1 seem to be suitable and applicable as simple, time-efficient and low-cost self-report measures in a wide range of research areas where an individual's general disposition toward risks plays an important role. If conducting the research under no time constraints or limitations, we would recommend using the GRiPS.
Enhancing diagnostic yield of monogenic diabetes through phenotypic and molecular reanalysis of 128 individuals with young onset hyperglycemia: highlighting the significance of accurate case characterization
Authors: Teles Milena , Junior Augusto Santomauro , Costa-Riquetto Aline , Gomes Larissa , De Santana Lucas , Jorge Alexander , Franco Pedro
Published: March 2024

Aim: Our objective is to enhance the molecular diagnostic precision in a cohort of unresolved monogenic diabetes cases, previously investigated by next-generation sequencing target panel (tNGS), through comprehensive bidirectional phenotypic and genotypic reanalysis.
Methods: We analyzed molecular and clinical data from 128 unresolved cases referred between 2011 and 2019. These included 92 cases suspected of maturity-onset diabetes of the young (MODY), 12 of neonatal diabetes, 16 of familial partial lipodystrophy (FPLD), 7 of mitochondrial diabetes, and 1 of Wolfram syndrome. All cases were initially investigated using a tNGS panel comprising 51 nuclear genes and the complete mitochondrial genome.
Results: Our extensive reanalysis process enhanced molecular diagnostic yields from 9 to 26%. Phenotypic reevaluation, entailing in-depth phenotyping, was instrumental in excluding 62 (48.4%) atypical cases. Genotypic reanalysis identified 5 previously overlooked molecular defects: two mutations in regulatory regions (one in the HNF1A promoter and another in the PTF1A enhancer); one in the MTTK mitochondrial gene; one in the MFN2 gene; and one in the GCK gene. Conclusions: Our findings indicate that a combined approach of genotypic and phenotypic reanalysis is an effective strategy for improving molecular diagnostic accuracy in individuals with suspected monogenic diabetes.
Stereotactic radiosurgery (SRS) for patients with brainstem cerebral cavernous malformations (CCMs): An International, Multicentric Study
Authors: Dayawansa Sam , Dumot Chloe , Mantziaris Georgios , Xu Zhiyuan , Pikis Stylianos , Peker Selcuk , Samanci Yavuz , Ardor Gokce D , Nabeel Ahmed M. , Reda Wael A. , Tawadros Sameh R. , Abdelkarim Khaled , El-Shehaby Amr M. N. , Eldin Reem M Emad , Elazzazi Ahmed H , Moreno Nuria Martínez , Álvarez Roberto Martínez , Liscak Roman , May Jaromir , Mathieu David , Tourigny Jean-Nicolas , Tripathi Manjul , Rajput Akshay , Kumar Narendra , Kaur Rupinder , Picozzi Piero , Franzini Andrea , Speckter Herwin , Hernandez Wenceslao , Brito Anderson , Warnick Ronald E. , Alzate Juan , Kondziolka Douglas , Bowden Greg N. , Patel Samir , sheehan jason
Published: March 2024

Introduction: Brainstem cerebral cavernous malformations (CCM) are clinically more aggressive compared to superficial CCMs. Due to their location, resection can be challenging, making stereotactic radiosurgery (SRS) an attractive alternative for symptomatic patient.
Method: Brainstem CCM patients (n=170) were treated with Gamma Knife SRS at 11 radiosurgical centers. Hemorrhagic risk reduction, risk factors of post-SRS hemorrhage, and clinical outcomes were retrospectively analyzed.
Results: Most patients had a single (165/170 patients) brainstem CCMs treated; the majority of CCMs (165/181) presented with bleeding. Single-session SRS decreased the risk of repeat hemorrhage in patients with hemorrhagic brainstem CCM (HR: 0.17, p<0.001) using recurrent multivariate analysis. The annual hemorrhage rate decreased from 14.8 per 100 CCM-years before SRS to 2.3 after treatment. Using univariate Cox-analysis, the probability of a new hemorrhages after SRS was reduced for patient older than 35 years (HR= 0.21, p=0.002) and increased with a margin dose >13Gy (HR= 2.57, p=0.044). Adverse radiation effect (ARE) occurred in 9 patients (5.3%) and was symptomatic in four (2.4%). At a median follow-up of 3.4 years (Inter-quartile range: 5.4), 13 patients (8.0%) had a worsened clinical status, with the treated CCM being the cause in 5.6% (10) of the patients.
Conclusion: Single-session SRS decreased the risk of repeat hemorrhage in patients with hemorrhagic brainstem CCM and conveyed this benefit with a low risk of advrse radiation effects (ARE) and worsening clinical status.
Clinical significance of metastasectomy and pathological response to pembrolizumab in mismatch repair-deficient metastatic colorectal cancer: A retrospective multi-institutional study
Authors: Shimada Yoshifumi , Nakano Mae , Matsumoto Akio , Ozeki Hikaru , Abe Kaoru , Tajima Yosuke , Yamai Daisuke , Nogami Hitoshi , Nakano Masato , Tani Tatsuo , Kawahara Mikako , Nishimura Atsushi , Kobayashi Yuka , Bamba Yuta , Suzuki Susumu , Oyanagi Hidehito , Ohashi Taku , Kameyama Hitoshi , Iwaya Akira , Ichikawa Hiroshi , Sakata Jun , Wakai Toshifumi
Published: March 2024

Background: Metastasectomy is an important treatment to improve survival outcomes in metastatic colorectal cancer (mCRC). However, the evidence regarding the significance of metastasectomy in selected patients with tumors deficient in mismatch repair (dMMR) has been lacking. We aimed to describe the significance of metastasectomy in patients with dMMR mCRC, and the pathological complete response (pCR) rate of patients who underwent metastasectomy after pembrolizumab treatment.
Methods: This retrospective analysis included 42 patients with dMMR mCRC treated at Niigata University Medical and Dental Hospitaland its affiliated hospitals. Clinicopathological characteristics, including metastasectomy, were analyzed to evaluate overall survival (OS). Moreover, pCR rate after pembrolizumab treatment was evaluated in patients who underwent metastasectomy.
Results: The sites of metastases were lymph node in 17, peritoneum in 16, and liver in seven patients. Metastasectomy was performed in 18 (43%) of the 42 patients. The five-year OS for patients who underwent metastasectomy was 100%, and metastasectomy was an independent prognostic factor for OS (P = 0.009). Three patients underwent metastasectomy with curative intent after pembrolizumab treatment, and pCR was achieved in all three patients (100%).
Conclusions: For this small retrospective study, the data suggest that metastasectomy is an important treatment for patients with dMMR mCRC, and patients treated with pembrolizumab show an excellent pCR rate.
GCC2 promotes non-small cell lung cancer growth by maintaining Golgi apparatus integrity and stimulating EGFR signaling pathways
Authors: Hong Sunghoi , Kim Min Sang , Jeong Hyesun , Choi Byeong Hyeon , Park Jiho , Shin Gun Seop , Jung Jik-Han , Shin Hyunku , Kang Ka-Won , Jeon Ok Hwa , Yu Jewon , Park Ji-Ho , Park Yong , Choi Yeonho , Kim Hyun Koo
Published: March 2024

Fundamental changes in intracellular processes, such as overactive growth signaling pathways, are common in carcinomas and are targets of many cancer therapeutics. GRIP and coiled-coil containing 2 (GCC2) is a trans-Golgi network (TGN) golgin maintaining Golgi apparatus structure and regulating vesicle transport. Here, we found an aberrant overexpression of GCC2 in non-small cell lung cancer (NSCLC) and conducted shRNA-mediated gene knockdown to investigate the role of GCC2 in NSCLC progression. shRNA-mediated GCC2 knockdown suppressed NSCLC cell growth, migration, stemness, and epithelial-mesenchymal transition (EMT) in vitro and tumor growth in vivo. In addition, GCC2 knockdown suppressed cancer cell exosome secretion and the oncogenic capacity of cancer cell-derived exosomes. Mechanistically, GCC2 inhibition decreased epidermal growth factor receptor (EGFR) expression and downstream growth and proliferation signaling. Furthermore, GCC2 inhibition compromised Golgi structural integrity in cancer cells, indicating a functional role of GCC2 in regulating intracellular trafficking and signaling to promote lung cancer progression. Together, these findings suggest GCC2 as a potential therapeutic target for the treatment of NSCLC.
Plug-and-Play Engineering of Modular Polyketide Synthases
Authors: Zhang Lihan , Huang Zilei , Xie Shengling , Liu Runzhou , Xiang Changjun , Yao Shunyu
Published: March 2024

Modular polyketide synthases (PKSs) are multidomain, assembly line enzymes that biosynthesize complex antibiotics such as erythromycin and rapamycin. The modular characteristic of PKSs has made them an ideal platform for custom production of designer polyketides by combinatorial biosynthesis. However, engineered hybrid PKS pathways often exhibit significant loss of enzyme activity, and a general principle for PKS reprogramming has not been established. Here we present a strategy for designing hybrid PKSs that is applicable to diverse PKSs. We reveal that two conserved motifs, located at the post-acyltransferase linker and near the acyl carrier protein, are robust cut sites for constructing functional hybrid PKS pathways. Through mixing various PKS pathways at these cut sites, we demonstrate custom production of polyketides with different starter units, extender units, and variable reducing states. Furthermore, we expand the applicability of these cut sites to construct hybrid pathways involving cis-AT PKS, trans-AT PKS, and even nonribosomal peptide synthetase, illustrating the generality of our strategy for the engineering of assembly line enzymes. Collectively, our findings enable plug-and-play reprogramming of modular PKSs and facilitate the synthetic biology application of assembly line enzymes towards bioproduction of designer molecules.
Preparation, Inspection, and Optimization of Rotary Friction Welding Parameters for 2017aa Aluminum Alloy Specimens.
Authors: Nateche Tahar , Chakroune Nabil , Amara Mouna , Boudaa Habib , Ayad Ibrahim , Mekhfi Souad , Suleiman Rami K. , Lamsafda Sidammar , meliani mohammed hadj , Pluvinage Guy
Published: March 2024

The qualification of the FSW process in aerospace requires the production of high-quality joints with long tool lifespan. This necessitates fine-tuning process parameters such as tool geometry (shoulder and pin dimensions, threading) and feed and rotation speeds. The experimental part involves characterizing the FSW weld joint through the study of mechanical properties and microstructural changes. The analyses and control observations performed on the obtained weld beads have, on one hand, enabled the correlation of joint quality with operational parameters. To achieve this, a local fabrication procedure aimed at producing defect-free joints was devised. Microstructural analysis revealed that the tool's rotation speed influences recrystallization conditions; the higher the rotation speed, the greater the welding energy and the more pronounced the softening of the material in the Heat Affected Zone (HAZ).
Factors influencing perceptions of processed baby foods and feeding practices among Indian mothers: A qualitative investigation
Authors: Singh Suruchi
Published: March 2024

Objective: To explore how professionally qualified, working Indian mothers conceptualize healthy foods in general, perceive processed infant and baby foods available commercially and what feeding practices they actually follow with their children at home.
Design: Five focus groups with 8-12 participants were conducted around the participants’ conceptualization of healthy food, their perceptions about commercially available processed baby and infant foods and their actual feeding practices that they routinely follow with their children. Discussion transcripts were analyzed using an inductive coding approach.
Setting: India.
Participants: Fifty-one professionally qualified, working women with at least one child under 5 years of age.
Results: Participants agreed that fresh food is healthiest. They also had favorable opinions about processed infant and baby foods with regards to healthfulness, hygiene and safety. Healthy foods were largely conceptualized in relation to nutrient claims, ingredients and discernible outcomes. They use cues, such as health claims, brand, price, package design and others to determine healthfulness of the product. Perception was heavily influenced by these extrinsic cues rather than by participants’ own nutrition knowledge. Despite having the knowledge, most participants admitted to using these foods on account of factors such as their own inability to lactate, social pressure, lack of time, convenience and others.
Conclusions: Most educated and well off people continue to use these products. While they rue the lack of stringent regulatory measures in India, they feel there is an urgent need to address this huge policy gap by way of legislation and regulation.
Comparative Study of 99mTc-3PRGD2 SPECT/CT and 18F-FDG PET/CT in the Diagnosis of Metastatic Lymph Nodes from Esophageal Squamous Cell Carcinoma
Authors: Wang Xiaojin , Liu Guichao , li Zhanyu , Shi Jiyun , Liang Mingzhu , Fu Guining , Lv Liangzhan , Ju Shaolong , Wang Yin , Xu Wenhua , Wang Fan , Cao Qingdong , Shan Hong
Published: March 2024

Objectives
Lymph node (LN) metastasis represents a significant prognostic factor for esophageal squamous cell carcinoma (ESCC), and there is a lack of effective methods to accurately predict metastatic LNs. The present study aimed to compare the performance of 99mTc-3PRGD2 SPECT/CT and 18F-FDG PET/CT for diagnosing metastatic LNs in ESCC.
Methods
Fifteen patients with suspected ESCC were enrolled and underwent 99mTc-3PRGD2 SPECT/CT and 18F-FDG PET/CT examinations preoperatively. High-definition bone carving reconstruction technology (HD-xSPECT Bone) was applied to quantitatively assess the SUVmax of LN in SPECT/CT. A comparison of 99mTc-3PRGD2 SPECT/CT and 18F-FDG PET/CT was performed for the diagnosis of LN metastasis with pathology as the gold standard.
Results
Among the 15 patients, 23 metastatic LNs were predicted by SPECT/CT with SUVmax of 2.71 ± 1.34, of which 15 were pathologically confirmed. Among the 32 metastatic LNs predicted by PET/CT with SUVmax of 4.41 ± 4.02, 17 were pathologically confirmed. The sensitivity, specificity, accuracy, PPV and NPV of SPECT/CT in diagnosing metastatic LNs were 62.50%, 91.21%, 85.22%, 65.22% and 90.22%, and those of PET/CT were 70.83%, 83.52%, 80.87%, 53.13% and 91.57%, respectively. There was no significant difference in sensitivity (p = 0.061) or specificity (p = 0.058) between the two methods. The AUCSPECT/CT was 0.816 and the SUVmax threshold was 2.5.
Conclusion
99mTc-3PRGD2 SPECT/CT is an effective method for quantitatively diagnosing metastatic LNs by HD-xSPECT Bone technology in ESCC, and its diagnostic sensitivity and specificity were not inferior to those of 18F-FDG PET/CT. The SUVmax cut-off value of 2.5 showed the highest agreement with pathology.
LapEfficientDepth: lightweight model for monocular depth estimation based on small samples
Authors: Zhang Guangyuan , Guan Hongliang , Li Kefeng , Wang Zhenfei , Wang Peng , Fu Chen , Zhu Zhenfang
Published: March 2024

This study proposes an improved LapDepth model, named LapEfficientDepth, for the monocular depth estimation field. The objective is to reduce the error in model-predicted relative depths and enhance depth estimation accuracy, addressing the issues of substantial resource consumption and large parameter count inherent in the original model. By incorporating lightweight modules, the LapEfficientDepth model significantly reduces model the complexity and resource requirements of the model while maintaining high accuracy estimation. Specifically, the parameter count of the LapEfficientDepth model has been reduced to 6M, constituting only 8.2% of the parameter volume found in the original LapDepth model, while achieving an approximate 1% improvement in accuracy compared to the Lite-Mono-8M model, which has a similar number of parameters. In addition, the LapEfficientDepth model exhibits exceptional transfer learning capabilities. After pre-training on the KITTI dataset and further training on the ETH3D-S dataset, the model achieved a1, a2, and a3 metrics of 0.706, 0.997, and 0.999, respectively, proving its rapid adaptability and learning ability on small sample datasets. This offers an effective solution for high-performance, lightweight monocular depth estimation network models.
Telehealth-facilitated palliative care enables more people to die at home: An analysis of clinical outcomes and service activity data
Authors: Haydon Helen M , Lotfaliany Mojtaba , Broadbent Andrew , Snoswell Centaine L , Smith Anthony C , Brydon Julie-Ann , Caffery Liam J , Thomas Emma E
Published: March 2024

Background
Telehealth-facilitated models of palliative care are a patient-focused way to deliver specialist care in or closer to home for people with a life-limiting illness. Telehealth can increase access to palliative care and support people experiencing symptoms of advanced disease in their own home, reducing the discomfort of travel. This retrospective cohort study examines the activity and outcomes of a regional telehealth-facilitated palliative care service to i) describe which patients are most likely to use telehealth; and ii) determine the impact of telehealth on patient outcomes including place of death, timely access to care, responsiveness to urgent needs and pain management.
Methods
Analysis of service activity data (patient demographics, care modality, consultation frequency) and Palliative Care Outcomes Collaborative data registry (place of death, timely access to palliative care, responsiveness to urgent needs as measured by time in unstable phase, pain management) were undertaken. Outcomes were compared between patients who had no videoconsultations (n = 683) and those who had one or more videoconsultations (n = 524).
Results
Compared to people who had no videoconsultations, those who had at least one appointment via video were: more than twice as likely to die at home and spent a shorter amount of time in the unstable phase of palliation. Mixed results were found regarding timely access to palliative care. There was no significant difference in pain management between consultation modes.
Conclusion
Telehealth-facilitated palliative care has multiple benefits, including the increased likelihood of fulfilling someone’s wish to die at home, often their preferred place of death.
Exploring the Impact of the JEEViKA Swasthya Mitra Helpdesk Intervention on Improving Healthcare Access in Tertiary Healthcare Facilities in Bihar: A Qualitative Descriptive Evaluation.
Authors: Kumar Pragya , Ahmad Shamshad , Pradhan Narottam , Chaudhary Neha , H Haripriya , Kumari Sarita , G Naveen K , Yadav Akanksha , Jha Rakesh , Pa Ashraf Md. , Swati Swati , Purty Apolenarius , Somya Somya
Published: March 2024

Background: Rural populations in Bihar, India, face significant healthcare access challenges due to geographical, infrastructural, and financial barriers. The Swasthya Mitra program, initiated by the Bihar Rural Livelihood Promotion Society in collaboration with local and international partners, aims to mitigate these challenges by employing trained community members to navigate patients through the healthcare system.
Methods: This qualitative study employed semistructured int erviews and thematic analysis to evaluate the Swasthya Mitra program in the Bhagalpur and Jamui districts in Bihar, India. The participants included Swasthya Mitras, healthcare professionals, and beneficiaries. This study focused on understanding the program's impact on healthcare access, out-of-pocket expenditures, and the role of Swasthya Mitras in facilitating healthcare services.
Findings: The program significantly improved healthcare access for rural populations, with beneficiaries reporting reduced navigational confusion, decreased out-of-pocket expenditures, and enhanced patient care. Swasthya Mitras effectively bridged the gap between the community and healthcare facilities, ensuring timely and efficient medical attention. The program also empowered women, both Swasthya Mitras and beneficiaries, by improving their access to healthcare and increasing their involvement in health-related decision-making.
Interpretation: The Swasthya Mitra program offers a viable model for improving healthcare access in rural settings, demonstrating the importance of community involvement in healthcare delivery. The findings suggest that such programs can be instrumental in overcoming barriers to healthcare access and reducing financial burdens on vulnerable populations.
Screening of PDSS1 as a potential biomarker for hepatocellular carcinoma based on a copper-related prognostic signature through bulk and single-cell RNA-sequencing analysis
Authors: Lin Kainan , Cai Jingwei , Pan Siyuan , Yu Xuefei , Qiu Yiwu , Ying Zhangguo , Feng He , Zhang Lizhuo , Liu Yanyang , Shen Huize , Hong Yangjian , Li Qinglin , Jin Renan
Published: March 2024

Background: Currently, there is few literature comprehensively analyzing landscape of cuproptosis-related genes (CRGs) in liver hepatocellular carcinoma (LIHC) with multiple omics approaches.
Aims: Using comprehensive analysis, we aim to find out how CRGs works on LIHC.
Method: With data from The Cancer Genome Atlas (TCGA) database, we constructed a prognostic prediction model for CGRs using LASSO regression analysis and performed immune infiltration analysis using the same dataset. To validate findings, we utilized RNA expression data from the International Cancer Genome Consortium (ICGC). Furthermore, we analyzed the enrichment and features of CRGs in epithelial cells using single-cell RNA sequencing (scRNA-seq) data. To validate the reliability of findings, we performed several experiments including RT-PCR, cloning formation assay, scratch assay, and Transwell assay.
Result: We have constructed a high-precision risk scoring model composed of CRGs for predicting prognosis in TCGA-LIHC. Reliability of the risk prognosis model was confirmed through Kaplan-Meier curve analysis, time-dependent ROC analysis, and multivariate regression analysis. Furthermore, we found knocking down PDSS1 increased sensitivity of LIHC cells to copper ions, and both proliferation and migration abilities were significantly reduced. Finally, we comprehensively characterized the features of CRGs in LIHC through scRNA-seq.
Conclusion: Current research predicts cuproptosis may be involved in the pathogenesis of LIHC and associated with patient prognosis. Tumor cells with high cuproptosis features are closely related to tumor-associated macrophages (TAMs), which leads to the activation of tumor-related transcription factors (TFs) and a high metabolic microenvironment. Identified CRGs can serve as candidate biomarkers or therapeutic targets for LIHC.
The improvement in electrochemical properties with the addition of SiO2 into PMMA/PLA-LiBOB Gel Polymer Electrolytes Based Lithium Ions Battery
Authors: Khan N. M. , Kufian M. Z. , SAMSUDIN AHMAD SALIHIN
Published: March 2024

The present work investigates the impact of SiO2 nanofiller on the electrochemical properties of gel polymer electrolytes (GPEs) composed of PMMA/PLA-LiBOB. The study encompasses two distinct systems: PMMA/PLA-LiBOB (System I) and PMMA/PLA-LiBOB-SiO2 (System II). Nyquist plots were generated to analyze the samples' bulk resistance (Rb), and it was found that Rb value shows a decreasing trend with the incorporation of SiO2. The ionic conductivity increases from 1.69×10-6 S cm-1 to 1.37×10-3 S cm-1 at room temperature, with the highest composition achieved at 6 wt.% of SiO2. Dielectric properties revealed that the addition of SiO2 nanofiller led to the enhancement of dielectric constant (ε′) and dielectric loss (ε″), attributed to SiO2 nanofiller with high orientation polarizability and space charge polarization effects. Linear Sweep Voltammetry (LSV) measurements from both GPE samples are 4.1 V (System I) and 4.7 V (System II). Comparative electrochemical performances of the batteries assembled in System I and System II were conducted, demonstrating the superiority of System II in terms of stability and cycling performance. The differential capacity analysis further supported the enhanced electrochemical activity upon SiO2 nanofiller incorporation.
Engineering the performance of bifunctional oxygen electrocatalysts by modulating the atomically dispersed Co,Ni on N-doped cotton biomass aerogel of carbon fiber catalysts for rechargeable zinc-air battery
Authors: Yang Zhengyu , Jin Wan , Yang Zhengyu
Published: March 2024

Rational construction of advanced bifunctional catalysts with dual-active-sites is still challenging for both oxygen reduction (ORR) and oxygen evolution reactions (OER).The design of metal single atom catalysts prepared through high-temperature gas transport is an emerging method. The CoNi-N-C catalyst was prepared by using Co powder and Nickel foam to volatilize atomic dispersed Co,Ni element embedded in nitrogen doped cotton biomass biomass aerogel of carbon fibers in a high temperature tubular furnace in ammonia atmosphere. In this work, CoNi-N-C-1000 monoatomic catalyst was successfully synthesized by using the above method The resulting CoNi-N-C-1000 exhibited excellent bifunctional catalytic performance for ORR (E1/2=0.85V) and OER (Ej=10=1.54V) in alkaline electrolytes, which can compete with previously reported bifunctional electrocatalysts. In addition, compared to the Pt/C+RuO2 mixed catalyst, this bifunctional catalyst can endow the self-made zinc-air battery with better power density (128.5 mW/cm2) and cycle stability (142.3 hours), demonstrating its potential feasibility in practical applications of rechargeable zinc-air batteries.
Perceived abusive supervision and suicidal risk in Chinese graduate students: the chain mediating roles of autonomy need and professional identity
Authors: Yao Yingying , Chen Jianqiao , Chi Haoyang , Hang Yaming , Qiao Zhihong
Published: March 2024

Background: The suicide issue of graduate students related to the strained relationships with their academic supervisors has triggered wide concern and heated discussion recently. The study aimed to explore the relationship between abusive supervision graduate students perceived and the suicidal risk of them, and the mediating roles of autonomy need and professional identity.
Method: An online survey was conducted among 233 graduate students and the perceived abusive supervision, autonomy need, professional identity, suicidal ideation, depressive symptoms and psychache (psychological pain) were measured.
Results: It was found that the perceived abusive supervision positively correlated to the latent variable suicidal risk (suicidal ideation, depressive symptoms and paychache as three indicators), and worked through the respective mediating effects of autonomy need, professional identity and the chain mediating effect of them. The total indirect effect size was 0.130, accounting for 27.78% of overall effect size. These findings deepen the understanding of the influence of abusive supervision under high education setting and provided practical insights into psychosocial intervention from the perspective of the self-determination theory and the model of professional identity formation.