bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quantum Machine Learning Techniques Integrated in Quantum Software Testing
Authors: Gutam Bala Gangadhara , Malchi Sunil Kumar 
Published: July 2024

Abstract

Quantum computing (QC) is the era of the mechanisms that quantum solves complex problems faster than classical computers (CCs). Today, there are more opportunities for the public and private sectors to use high-value quantum solutions. QC relies on quantum phenomena to calculate incredible speeds and set for significant expansion. Quantum computers, QC-based Internet of Things (IoT), and communication devices to create, process, and transmit quantum states and entanglement are anticipated to enhance society’s quantum software. In this context, this paper introduces the Quantum Software Testing (QST) approach with Machine Learning (ML) techniques integrated into the Quantum Software Testing Life Cycle (QSTLC). The proposed Quantum Machine Learning Testing (QMLT) exploits ML techniques at critical stages of the QST to enhance testing efficiency, accuracy, and adaptability. Finally, the proposed automated test report generation, summarizing, and knowledge extraction technique facilitates comprehensive documentation and knowledge transfer.
Solvothermal Synthesis of Quaternary Cu-Fe-Bi-S Nanostructure as a Promising Electrode Material for OER and Supercapacitor Performance
Authors: Umer Muhammad , Awais Muhammad , Aslam Sidra , Bilal Anas , . Javaria , Abbas Waseem , Mirza Misbah , Safdar Muhammad 
Published: July 2024

Abstract

The rational development and synthesis of renewable nanostructured materials hold significant importance within the realm of energy storage applications. In this study, the quaternary chalcogenide of Cu2FeBiS4 was fabricated using a facile solvothermal method and evaluated for its performance in Oxygen Evolution Reaction (OER) and Supercapacitor applications. The material underwent characterization employing various analytical techniques, including X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDX), X-ray photoelectron spectroscopy (XPS), and Raman analysis. Cu2FeBiS4 demonstrates an improved super-capacitive performance, exhibiting an outstanding specific capacity (Cs) of 1530 F g–1 at 2 A g–1. The admirable electrochemical activity is mainly due to the synergistic effect of mixed metal sulfide nanostructure that can escalate the rapid diffusion of ions and electrons, which is beneficial to the electrode/electrolyte contact area, thereby boosting the rate of charge transfer. Additionally, Cu2FeBiS4 exhibits a commendable energy density of 43.17 Wh kg− 1 at a power density of 327.87 W kg− 1, accompanied by a retention rate of 96.2% after 1000 cycles. As a result, the Cu2FeBiS4 electrode developed in this study is evinced to be a promising electrode material for high-performance energy storage devices. Moreover, Cu2FeBiS4 demonstrates proficient electrocatalytic properties for the oxygen evolution reaction, displaying a minimal overpotential of 202 mV versus the reversible hydrogen electrode (RHE) at 10 mA cm− 2 and exhibiting operational stability for up to 10 hours.
Is severe maternal morbidity a risk factor for postpartum hospitalization with mental health or substance use disorder diagnoses? Findings from a retrospective cohort study in Maryland: 2016-2019
Authors: WOLFSON Carrie L , ANGELSON Jessica Tsipe , CREANGA Andreea A 
Published: July 2024

Abstract

BACKGROUND
Perinatal mental health conditions and substance use are leading causes, often co-occurring, of pregnancy-related and pregnancy-associated deaths in the United States. This study compares odds of hospitalization with a mental health condition or substance use disorder or both during the first year postpartum between patients with and without severe maternal morbidity (SMM) during delivery hospitalization.
Methods
Data are from the Maryland’s State Inpatient Database and include patients with a delivery hospitalization during 2016–2018 (n = 197,749). We compare rate of hospitalization with a mental health condition or substance use disorder or both at 42 days and 42 days to 1 year postpartum by occurrence of SMM during the delivery hospitalization. We use multivariable logistic regression to derive the odds of hospitalization with each outcome for patients by SMM status, adjusted for patient sociodemographic characteristics, presence of mental health condition or substance use disorder diagnoses during the delivery hospitalization, and delivery outcome. SMM, mental health conditions, and substance use disorders are identified using ICD-10 diagnosis and procedure codes.
RESULTS
Overall, 5,793 patients (2.9%) who delivered during 2016–2018 experienced hospitalization in the year following delivery. Among these patients, 24.3% (n = 1,410) had a mental health condition diagnosis, 10.6% (n = 619) had a substance use disorder diagnosis, and 9.8% (n = 570) had co-occurring mental health condition and substance use disorder diagnoses. Patients with SMM had 3.7 times the odds (95% CI 2.7, 5.2) of hospitalization with a mental health condition diagnosis, 2.7 times the odds (95% CI 1.6, 4.4) of a hospitalization with substance use disorder diagnosis, and 3.0 times the odds (95% CI 1.8, 4.8) of hospitalization with co-occurring mental health condition and substance use disorder diagnoses during the first-year postpartum adjusting for covariates.
CONCLUSION
Patients who experience SMM during their delivery hospitalization had higher odds of hospitalization with a mental health condition, substance use disorder, and co-occurring mental health condition and substance use disorder in the one-year postpartum period. Treatment and support resources for mental health and substance use providers --including enhanced screening and warm handoffs -- should be made available to patients with SMM upon discharge after delivery, and evidence-based interventions to improve mental health and reduce substance use should be prioritized in these patients.
Electrocatalytic radical degradation of 2-aminoethanol by nickel, palladium and platinum complexes bearing non-innocent diarylamido/bis(phosphine) pincer ligand
Authors: Mikhailov Ilya K. , Gafurov Zufar N. , Kagilev Alexey A. , Sakhapov Il’yas F. , Morozov Vladimir I. , Ganeev Gumar R. , Khayarov Khasan R. , Kulikova Vasilisa A. , Kirkina Vladislava A. , Gutsul Evgenii I. , Shubina Elena S. , Belkova Natalia V. , Sinyashin Oleg G. , Yakhvarov Dmitry G. 
Published: July 2024

Abstract

The electrocatalytic activity of PNP pincer complexes with general formula (PNP)MCl (PNP is bis(2-diisopropylphosphino-4-methylphenyl)amide; M = nickel, palladium and platinum) in the oxidative 2-aminoethanol (MEA, a recalcitrant pollutant) degradation process was studied using cyclic voltammetry method. Complexes fulfil the requirements typically expected of a redox mediator or catalyst. Their electrochemical oxidation yields the aminyl radical species which unpaired electron is localized on the ligand. The mechanism of interaction of these aminyl radical complexes with MEA was studied using ESR- and NMR-spectroscopy methods. The addition of MEA to the solution of model platinum derivative leads to the disappearance of ESR signal responsible for the aminyl radical complex, whereas the 31P{1H} NMR spectrum revealed the regeneration of neutral (PNP)MCl. Palladium derivative was found to be the most effective catalyst of the series with an Icat/Ip value of 6.7. Controlled potential electrolysis has allowed us to identify the main products of the catalytic process and to propose the mechanism of the overall process.
A single-plasmid-based, easily curable CRISPR/Cas9 system for rapid, iterative genome editing in Pseudomonas putida KT2440
Authors: Wen Qifeng , Chen Jinjin , Li Jin , Dharmasiddhi Ida Putu Wiweka , Yang Maohua , Xing Jianmin , Liu Yilan 
Published: July 2024

Abstract

Background
Pseudomonas putida KT2440, a non-pathogenic soil bacterium, is a key platform strain in synthetic biology and industrial applications due to its robustness and metabolic versatility. Various systems have been developed for genome editing in P. putida, including transposon modules, integrative plasmids, recombineering systems, and CRISPR/Cas systems. However, rapid iterative genome editing is limited by the complex and lengthy processes.
Results
We discovered that the pBBR1MCS2 plasmid carrying the CRISPR/Cas9 module could be easily cured in P. putida KT2440 at 30 oC. We then developed an all-in-one CRISPR/Cas9 system for yqhD and ech-vdh-fcs deletions, respectively, and further optimized the editing efficiency by varying homology arm lengths and target sites. Sequential gene deletions of vdh and vanAB was carried out rapidly using single-round processing and easy plasmid curing. This system's user-friendliness was validated by novice users in two labs for various gene deletions, substitutions, and insertion. Finally, iterative genome editing was used to engineering P. putida for valencene biosynthesis, achieving a 10-fold increase in yield.
Conclusions
We developed and applied a rapid all-in-one plasmid CRISPR/Cas9 system for genome editing in P. putida. This system requires lest than 1.5 days for one edit due to simplified plasmid construction, electroporation and curing processes, thus accelerating the cycle of genome editing. To our knowledge, this is the fastest iterative genome editing system for P. putida. Using this system, we rapidly engineered P. putida for valencene biosynthesis for the first time, showcasing the system's potential for expanding biotechnological applications.
Diffraction imaging method using the pattern operator in migrated dip-angle gathers
Authors: Sheng Tongjie , Zhao Jingtao , Chen Zongnan 
Published: July 2024

Abstract

Diffracted wavefield carries high-resolution information about subwavelength geological structural elements crucial for imaging small-scale subsurface discontinuities. However, the presence of strong reflection often obscures weak diffraction, limiting the effective use of diffraction in depicting detailed small-scale structures. To obtain a high-resolution diffraction image, we present a novel two-phase diffraction separation method that combines pattern-based method and energy attenuation function of stationary reflection in migrated dip angle gathers. In the first phase, the pattern-based method utilizes pattern operator to characterize non-stationary features of reflection in dip angle gathers and effectively eliminates the reflection outside the stationary point. In the second phase, the energy attenuation function based on dip angle is used to further attenuate residual reflection near the stationary point. The conflicting dip angles often reduces the performance of dip-based energy attenuation methods. We introduce the covariance rate criterion to adaptively adjust the conflicting dip angle, so that the energy attenuation function can more accurately attenuate the residual reflection. The numerical experiment conducted on classic Sigsbee2B model validates the efficacy of the proposed method in suppressing strong high-slope reflection while preserving details of small-scale faults and scatterers. The real data application demonstrates the performance of the method to highlight deep fractures, presenting additional potential reservoir-related structural insights.
Advanced Brain Tumor Classification Utilizing MaskR-CNN with Fuzzy C-Means Clustering
Authors: K Muthulakshmi , M Jayalakshmi 
Published: July 2024

Abstract

Brain tumors are a major concern in medical diagnostics, necessitating precise and prompt detectionfor optimal treatment. While radiologists may diagnose them using medical imaging, automating theprocess has several advantages, including increased efficiency and accessibility. Magnetic resonanceimaging (MRI) is the most effective way to detect these tumors. An automated system that accuratelyidentifies and localizes them in MRI scans can greatly benefit patients lacking immediate access toa radiologist. Our study proposes a method combining Mask R-CNN and Fuzzy C-Means (FCM)clustering to boost the accuracy of brain tumor detection in MRI images. This approach identifiestumors and segments abnormal brain tissues but also gauges the likelihood of tumor presence, offering acomprehensive diagnostic tool. While Mask R-CNN excels in segmentation accuracy, integrating FCMclustering further refines the detection process. FCM, which allows data to belong to multiple clusters,is proven in medical images where tumor boundaries can be ambiguous. Our experiment utilizes theBraTS 2018 and 2020 datasets, employing five-fold cross-validation to demonstrate the effectiveness andvalidate the clinical application of our proposed method.
Perturbing the Gradient for alleviating Meta Overfitting
Authors: Gogoi Manas , Tiwari Sambhavi , Verma Shekhar 
Published: July 2024

Abstract

The reason for Meta Overfitting can be attributed to two factors: Mutual Non-exclusivity and the Lack of diversity, consequent to which a single global function can fit the support set data of all the meta-training tasks and fail to generalize to new unseen tasks. This issue is evidenced by low error rates on the meta-training tasks, but high error rates on new tasks. However, there can be a number of novel solutions to this problem keeping in mind any of the two objectives to be attained, i.e. to increase diversity in the tasks and to reduce the confidence of the model for some of the tasks. Inlight of the above, this paper proposes a number of solutions to tackle meta-overfitting on few-shot learning settings, such as few-shot sinusoid regression and few shot classification. Our proposed approaches demonstrate improved generalization performance compared to state-of-the-art baselines for learning in a non-mutually exclusive task setting. Overall, this paper aims to provide insights into tackling overfitting in meta-learning and to advance the field towards more robust and generalizable models.
Comparison of Models Predicting Efficacy of Radioiodine Therapy in Patients with Differentiated Thyroid Cancer
Authors: Borowczyk Martyna , Jodłowska-Siewert Elżbieta , Filipowicz Dorota , Verburg Frederik A. , Ziemnicka Katarzyna , Szczepanek-Parulska Ewelina , Ruchała Marek 
Published: July 2024

Abstract

Purpose
Differentiated thyroid cancer (DTC) is the most common type of endocrine malignancy, with its incidence on the rise over recent decades. Despite a favorable prognosis, DTC management remains complex, often involving thyroidectomy followed by radioactive iodine (RAI) therapy. While RAI is crucial for patient outcomes, its efficacy varies, necessitating the identification of predictors for treatment response. New guidelines underscore the need for personalized follow-up plans, prompting research into predictive models to refine prognostic accuracy.
Methods
We conducted a retrospective analysis of 744 DTC patients treated at a single center, focusing on clinicopathological factors and thyroid biomarkers. Multivariate logistic regression models were constructed to evaluate the predictive value of different DTC biomarkers, adjusting for covariates such as age, sex, and disease stage. Cut-off values for these biomarkers were determined to predict RAI efficacy.
Results
Analysis revealed no significant difference in predictive performance among models incorporating various DTC biomarkers. Stimulated thyroglobulin (sTg) emerged as a reliable predictor, with a mean cut-off value of 7.22 ng/mL. Additionally, chronic lymphocytic thyroiditis (CLT) status tended to enhance predictive accuracy, although not significantly.
Conclusions
Our study underscores the utility of sTg as a single parameter for predicting RAI efficacy in DTC patients, with a defined cut-off value facilitating clinical decision-making. The inclusion of CLT status may further enhance predictive models, warranting consideration in future analyses. Overall, our findings contribute to the advancement of personalized management approaches for DTC patients undergoing RAI therapy.
Crocin effects on the anticancer properties of Lactobacillus lactis probiotics against colorectal adenocarcinoma cells
Authors: Gholipour Faranak , Entezar Mehdi , Amini Mohammad , Vandghanooni Somayeh , Baradaran Behzad , Eskandani Morteza , Mokhtarzadeh Amir Ali 
Published: July 2024

Abstract

There are numerous potential mechanisms that can account for the propensity of probiotics to prevent the onset of colorectal cancer. These effects include but are not limited to deactivation of cancer-causing agents, competition with harmful bacteria, boosting the immune system, and reducing cell proliferation by controlling apoptosis and cell differentiation. Other benefits include fermenting undigested food and limiting the activity of certain signaling pathways. Research has shown that the gut microbiota is impacted by nutrition, which subsequently affects the metabolomics, thereby establishing a connection between diet, microbiota, and overall health. The objective of this study was to assess the resistance of Lactobacillus lactis to Crocin. The study involved extracting cell-free supernatants from untreated bacteria and bacteria treated with crocin, and then examining their ability to prevent the growth of HCT-116 colon cancer cells. It was proven that L. lactic, when treated with crocin, can effectively fight against various types of harmful bacteria and can survive in acidic conditions. After 48 hours, both CFS and cro-CFS showed a dose-dependent inhibition of HCT-116 cell growth. The half-maximal inhibitory concentration was 97.41 µL/mL for CFS and 72.07 µL/mL for cro-CFS. The results of flow cytometry tests confirmed the MTT assay findings, showing that cro-CFS-treated cells had a higher rate of apoptosis at 46.8% compared to CFS-treated cells at 25.42%. The results were confirmed by qPCR, which showed that the Caspase 9 and BAX genes were upregulated and the BCL-2 expression level was reduced in cells treated with cro-CFS and CFS. Crocin could alter the metabolomics of probiotics present in the gut, potentially impacting their ability to fight cancer.
Microenvironment engineering by targeted delivery of activated Ag NPs for boosting electrocatalytic CO2 reduction reaction
Authors: Wang Shun , Xu Ting , Yang Hao , Lu Tianrui , Zhong Rui , Lv Jing-Jing , Zhu Shaojun , Zhang Mingming , Wang Zheng-Jun , Yuan Yifei , Li Jun , Wang Jichang , Jin Huile , Pan Shuang , Wang Xin , Cheng Tao 
Published: July 2024

Abstract

To boost the performance of electrocatalytic CO2 reduction reaction (eCO2RR), a unique synthetic method that deploys the in situ reduction of precoated precursors was developed to produce activated Ag nanoparticles (NPs) within the gas diffusion layer (GDL), where the thus-obtained Ag NPs-Skeleton could block direct contact between the active Ag sites and electrolyte. Specifically, compared to the conventional surface loading mode in the acidic media, our freestanding and binder free electrode could achieve obvious higher CO selectivity of 94%, CO production rate of 23.3 mol g-1 h-1, single-pass CO2 conversion of 58.6%, and enhanced long-term stability of 8 hours. Our study shows that delivering catalysts within the GDL does not only gain the desired physical protection from GDL skeleton to achieve a superior local microenvironment for more efficient pH-universal eCO2RR, but also manifests the pore structures to effectively address gas accumulation and flood issues, thereby stabilizing the catalysts.
Calibrating global behaviour of equation of state by combining nuclear and astrophysics inputs in a machine learning approach
Authors: I Sk Md Adil , Saxena Prafulla , Malik Tuhin , Patra N.K. , Agrawal B. K. 
Published: July 2024

Abstract

We implemented symbolic regression techniques to identify suitable analytical functions that map various properties of neutron stars (NSs), obtained by solving the Tolman-Oppenheimer-Volkoff (TOV) equations, to a few key parameters of the equation of state (EoS). These symbolic regression models (SRMs) are then employed to perform Bayesian inference with a comprehensive dataset from nuclear physics experiments and astrophysical observations. The posterior distributions of EoS parameters obtained from Bayesian inference using SRMs closely match those obtained directly from the solutions of TOV equations. Our SRM-based approach is approximately 100 times faster, enabling efficient Bayesian analyses across different combinations of data to explore their sensitivity to various EoS parameters within a reasonably short time.
Structural re-evaluation of the human gluteus maximus muscle
Authors: Anetai Hidaka , Kato Kota , Kudoh Hiroyuki , Sakai Tatsuo , Ichimura Koichiro 
Published: July 2024

Abstract

The gluteus maximus (GM) is a powerful hip joint extensor acting strongly on the femur. However, most anatomical studies report that the larger superior portion of the GM inserts into the iliotibial tract rather than the femur, creating an apparent discrepancy between its structure and function. To address this, we re-evaluated the GM structure in 25 formalin-fixed Japanese cadavers. We found that the superior three-fourths of the GM formed a strong plate-like tendon inserted into the gluteal tuberosity of the femur, with partial adhesions to the iliotibial tract. The remaining inferior portion terminates at a complex involving the lateral femoral intermuscular septum, strong plate-like tendon of the superior portion, and proximal tendon of the vastus lateralis. These findings resolve the functional anatomy discrepancy of the GM: the larger superior portion primarily inserts into the femur, contributing hip joint movement, while the smaller inferior portion supports this function. Kinesiological data on the GM should be reinterpreted based on this precise anatomy. This will significantly improve our understanding of human GM function.
First report of natural infection with infectious spleen and kidney necrosis virus (ISKNV) associated with disease outbreaks in two gourami species (Trichopodus spp.)
Authors: Dinh-Hung Nguyen , Dong Ha Thanh , Phiwsaiya Kornsunee , Taengphu Suwimon , Linh Nguyen Vu , Chatchaiphan Satid , Rodkhum Channarong , Mai Hung N. , Dhar Arun K. , Senapin Saengchan 
Published: July 2024

Abstract

Infectious spleen and kidney necrosis virus (ISKNV) has broad host range and pose significant threat to aquaculture species. Herein, we report two disease outbreaks in snakeskin gourami (Trichopodus pectoralis) in Thailand, marked by skin hemorrhage, scale loss, internal organ necrosis, and a mortality rate exceeding 60%. Additionally, three spot gourami (Trichopodus trichopterus) cultured in the same ponds along with snakeskin gourami were found to be affected and tested positive for the virus. Histopathological examination revealed extensive necrosis of hematopoietic tissues in the kidneys and spleen, accompanied by the presence of numerous megalocytic cells in both fish species. Real-time PCR assays, using protocolstargeting major capsid protein (MCP) gene in a broad range of Megalocytivirus genotypes, confirmed the presence of ISKNV in the infected fish. Furthermore, molecular and phylogenetic analyses based on the MCP gene (1,362 bp) and the adenosine triphosphatase (ATPase) gene (720 bp) revealed that the ISKNV strains in gourami and other fish hosts were closely related, suggesting possible cross-species transmission. This report extends the host range of ISKNV and highlights the need to prevent the spread of this virus across species boundaries. Further research is needed to understand the pathogenicity and transmission routes of the virus, gain insights into its epidemiology, and develop strategies to mitigate disease outbreaks.