bluuebunny/crossref_metadata_2025 huggingface dataset:
Self‐assembly of heterochiral, aliphatic dipeptides with Leu
Authors: Scarel Erica , De Corti Marco , Polentarutti Maurizio , Pierri Giovanni , Tedesco Consiglia , Marchesan Silvia
Published: December 2023

This work describes the self‐assembly behavior of heterochiral, aliphatic dipeptides, l‐Leu‐d‐Xaa (Xaa = Ala, Val, Ile, Leu), in green solvents such as acetonitrile (MeCN) and buffered water at neutral pH. Interestingly, water plays a structuring role because at 1% v/v, it enables dipeptide self‐assembly in MeCN to yield organogels, which then undergo transition towards crystals. Other organic solvents and oils were tested for gelation, and metastable gels were formed in tetrahydrofuran, although at high peptide concentration (80 mM). Single‐crystal X‐ray diffraction revealed the dipeptides' supramolecular packing modes in amphipathic layers, as opposed to water channels reported for the homochiral Leu–Leu, or hydrophobic columns reported for homochiral Leu–Val and Leu–Ile.
Tumor growth inhibition‐overall survival modeling in non‐small cell lung cancer: A case study from GEMSTONE‐302
Authors: Sheng Yucheng , Teng Shu‐wen , Wang Jingru , Wang Hao , Tse Archie N.
Published: December 2023

Overall survival is vital for approving new anticancer drugs but is often impractical for early‐phase studies. The tumor growth inhibition‐overall survival (TGI‐OS) model could bridge the gap between early‐ and late‐stage development. This study aimed to identify an appropriate TGI‐OS model for patients with non‐small cell lung cancer from the GEMSTONE‐302 study of sugemalimab. We used three TGI models to delineate tumor trajectories and investigated three OS model for linking TGI metric to OS. All three TGI models accurately captured tumor profiles at the individual level. The published atezolizumab‐based TGI‐OS model predicted survival time satisfactorily through simulation‐based evaluation, whereas the other published model built from multi‐treatment underestimated OS. Our study‐specific TGI‐OS model identified time‐to‐growth as the most significant metric with the number of metastatic sites and neutrophil‐to‐lymphocyte ratio at baseline as covariates and exhibited robust OS predictability. Our findings demonstrated the effectiveness of the TGI‐OS models in predicting phase III outcomes, which underpins their value as a powerful tool for antitumor drug development.
Multistep estimators of the between‐study covariance matrix under the multivariate random‐effects model for meta‐analysis
Authors: Jackson Dan , Viechtbauer Wolfgang , van Aert Robbie C. M.
Published: December 2023

A wide variety of methods are available to estimate the between‐study variance under the univariate random‐effects model for meta‐analysis. Some, but not all, of these estimators have been extended so that they can be used in the multivariate setting. We begin by extending the univariate generalised method of moments, which immediately provides a wider class of multivariate methods than was previously available. However, our main proposal is to use this new type of estimator to derive multivariate multistep estimators of the between‐study covariance matrix. We then use the connection between the univariate multistep and Paule–Mandel estimators to motivate taking the limit, where the number of steps tends toward infinity. We illustrate our methodology using two contrasting examples and investigate its properties in a simulation study. We conclude that the proposed methodology is a fully viable alternative to existing estimation methods, is well suited to sensitivity analyses that explore the use of alternative estimators, and should be used instead of the existing DerSimonian and Laird‐type moments based estimator in application areas where data are expected to be heterogeneous. However, multistep estimators do not seem to outperform the existing estimators when the data are more homogeneous. Advantages of the new multivariate multistep estimator include its semi‐parametric nature and that it is computationally feasible in high dimensions. Our proposed estimation methods are also applicable for multivariate random‐effects meta‐regression, where study‐level covariates are included in the model.
Evaluating a shrinkage estimator for the treatment effect in clinical trials
Authors: van Zwet Erik W. , Tian Lu , Tibshirani Robert
Published: December 2023

The main objective of most clinical trials is to estimate the effect of some treatment compared to a control condition. We define the signal‐to‐noise ratio (SNR) as the ratio of the true treatment effect to the SE of its estimate. In a previous publication in this journal, we estimated the distribution of the SNR among the clinical trials in the Cochrane Database of Systematic Reviews (CDSR). We found that the SNR is often low, which implies that the power against the true effect is also low in many trials. Here we use the fact that the CDSR is a collection of meta‐analyses to quantitatively assess the consequences. Among trials that have reached statistical significance we find considerable overoptimism of the usual unbiased estimator and under‐coverage of the associated confidence interval. Previously, we have proposed a novel shrinkage estimator to address this “winner's curse.” We compare the performance of our shrinkage estimator to the usual unbiased estimator in terms of the root mean squared error, the coverage and the bias of the magnitude. We find superior performance of the shrinkage estimator both conditionally and unconditionally on statistical significance.
Advances in Atomically Dispersed Metal and Nitrogen Co‐Doped Carbon Catalysts for Advanced Oxidation Technologies and Water Remediation: From Microenvironment Modulation to Non‐Radical Mechanisms
Authors: Ma Wenjie , Ren Xiaohui , Li Jiahao , Wang Shuai , Wei Xinyu , Wang Na , Du Yunchen
Published: December 2023

Atomically dispersed metal and nitrogen co‐doped carbon catalysts (M‐N‐C) have been attracting tremendous attentions thanks to their unique MNx active sites and fantastic catalytic activities in advanced oxidation technologies (AOTs) for water remediation. However, precisely tailoring the microenvironment of active sites at atomic level is still an intricate challenge so far, and understanding of the non‐radical mechanisms in persulfate activation exists many uncertainties. In this review, latest developments on the microenvironment modulation strategies of atomically dispersed M‐N‐C catalysts including regulation of central metal atoms, regulation of coordination numbers, regulation of coordination heteroatoms, and synergy between single‐atom catalysts (SACs) with metal species are systematically highlighted and discussed. Afterwards, progress and underlying limitations about the typical non‐radical pathways from production of singlet oxygen, electron transfer mechanism to generation of high‐valent metal species are well demonstrated to inspire intrinsic insights about the mechanisms of M‐N‐C/persulfate systems. Lastly, perspectives for the remaining challenges and opportunities about the further development of carbon‐based SACs in environment remediation are also pointed out. It is believed that this review will be much valuable for the further design of active sites in M‐N‐C/persulfate catalytic systems and promote the wide application of SACs in various fields.
Nested Biofabrication: Matryoshka‐Inspired Intra‐Embedded Bioprinting
Authors: Alioglu Mecit Altan , Yilmaz Yasar Ozer , Singh Yogendra Pratap , Nagamine Momoka , Celik Nazmiye , Kim Myoung Hwan , Pal Vaibhav , Gupta Deepak , Ozbolat Ibrahim T.
Published: December 2023

Engineering functional tissues and organs remains a fundamental pursuit in bio‐fabrication. However, the accurate constitution of complex shapes and internal anatomical features of specific organs, including their intricate blood vessels and nerves, remains a significant challenge. Inspired by the Matryoshka doll, here a new method called “Intra‐Embedded Bioprinting (IEB)” is introduced building upon existing embedded bioprinting methods. a xanthan gum‐based material is used which served a dual role as both a bioprintable ink and a support bath, due to its unique shear‐thinning and self‐healing properties. IEB's capabilities in organ modeling, creating a miniaturized replica of a pancreas using a photocrosslinkable silicone composite is demonstrated. Further, a head phantom and a Matryoshka doll are 3D printed, exemplifying IEB's capability to manufacture intricate, nested structures. Toward the use case of IEB and employing an innovative coupling strategy between extrusion‐based and aspiration‐assisted bioprinting, a breast tumor model that included a central channel mimicking a blood vessel, with tumor spheroids bioprinted in proximity is developed. Validation using a clinically‐available chemotherapeutic drug illustrated its efficacy in reducing the tumor volume via perfusion over time. This method opens a new way of bioprinting enabling the creation of complex‐shaped organs with internal anatomical features.
Development of a second‐screen system for sharing virtual reality information
Authors: Nakano Bunta , Matsumoto Takaki , Hoshikawa Naoto , Ito Tomoyoshi , Shiraki Atsushi
Published: December 2023

Since virtual reality technology can easily realize a particular environment, it has been applied to various training. This technology is also expected in education such as those dealing with three‐dimensional figures because they can represent phenomena in three dimensions. One of the standard virtual reality technologies is wearing a head‐mounted display to experience a virtual reality project. However, the virtual reality experience is limited to the person wearing the head‐mounted display (in most cases) when considering the use of head‐mounted display‐based virtual reality in education, making its usage unsuitable for mass education. Therefore, in this study, we develop a second‐screen system that can share virtual reality information using an Android device. Healthy first‐ and second‐year high school students between the ages of 15 and 17 were asked to use the virtual reality educational materials that implemented the developed system, and a questionnaire survey was conducted. There were no negative comments in the survey on whether proposing second‐screen system was necessary, demonstrating the usefulness of the proposed system. Therefore, the second‐screen system may adapt VR technology to mass education. In addition, we developed a package to integrate our second‐screen system into the pre‐existing virtual reality projects. This package simplifies the procedure for implementing a second‐screen system, thus helping to reuse the virtual reality projects that have been developed so far.
The role of geriatric nutritional risk index as a predictor for postoperative outcomes in gastrointestinal emergencies
Authors: Takano Yasuhiro , Kobayashi Yasunobu , Kudo Tomohiro , Takahashi Sumika , Kanno Hironori , Hanyu Nobuyoshi
Published: December 2023

Background

The geriatric nutritional risk index (GNRI) is a simple nutritional and inflammatory marker for older adults. The aim of the present study was to investigate the usefulness of the GNRI in older adults who underwent emergency gastrointestinal surgery.

Methods

This study included 206 older adults who had undergone emergency gastrointestinal surgery. We retrospectively investigated the relationship between the GNRI and postoperative complications. Univariate and multivariate analyses were performed to evaluate risk factors for postoperative complications. We then evaluated the association between GNRI and clinical variables among older adults undergoing emergency gastrointestinal surgery.

Results

Postoperatively, all complications occurred in 89 (43%) older adults, infectious in 53 (26%), and non‐infectious in 36 (17%). In the multivariate analysis, age (p = 0.016), GNRI (p = 0.012), operative severity (p = 0.003), and operation time (p = 0.003) were independent risk factors for all postoperative complications. While the GNRI (p = 0.049) was an independent risk factor for infectious complications, age (p = 0.035) and bleeding volume (p = 0.035) were independent risk factors for postoperative non‐infectious complications. In the low GNRI group, age (p = 0.029), serum C‐reactive protein levels (p < 0.001), and proportion of sarcopenia (p < 0.001) were significantly higher, and the length of hospital stay (p < 0.001) was significantly longer than that in the high GNRI group. In Spearman's rank correlation coefficient, the skeletal mass index and the GNRI had a positive correlation (r = 0.415 and p < 0.001).

Conclusion

The GNRI may be a predictor of postoperative infectious complications in older adults after emergency gastrointestinal surgery, suggesting the usefulness of the GNRI as a nutritional marker and sarcopenia‐related parameter.

Trial registration number

No. 22‐16.
The risk analysis index demonstrates exceptional discrimination in predicting frailty's impact on neurosurgical length of stay quality metrics
Authors: Gagliardi Thomas A. , Conti Joseph T. , Courville Jordyn T. , Owodunni Oluwafemi P. , Courville Evan N. , Kazim Syed F. , Schmidt Meic H. , Bowers Christian A.
Published: December 2023

Background

Quality measures determine reimbursement rates and penalties in value‐based payment models. Frailty impacts these quality metrics across surgical specialties. We compared the discriminatory thresholds for the risk analysis index (RAI), modified frailty index‐5 (mFI‐5) and increasing patient age for the outcomes of extended length of stay (LOS [eLOS]), prolonged LOS within 30 days (pLOS), and protracted LOS (LOS > 30).

Methods

Patients ≥18 years old who underwent neurosurgical procedures between 2012 and 2020 were queried from the ACS‐NSQIP. We performed receiver operating characteristic analysis, and multivariable analyses to examine discriminatory thresholds and identify independent associations.

Results

There were 411,605 patients included, with a median age of 59 years (IQR, 48–69), 52.2% male patients, and a white majority 75.2%. For eLOS: RAI C‐statistic 0.653 (95% CI: 0.652–0.655), versus mFI‐5 C‐statistic 0.552 (95% CI: 0.550–0.554) and increasing patient age C‐statistic 0.573 (95% CI: 0.571–0.575). Similar trends were observed for pLOS‐ RAI: 0.718, mFI‐5: 0.568, increasing patient age: 0.559, and for LOS>30‐ RAI: 0.714, mFI‐5: 0.548, and increasing patient age: 0.506. Patients with major complications had eLOS 10.1%, pLOS 26.5%, and LOS >30 45.5%. RAI showed a larger effect for all three outcomes, and major complications in multivariable analyses.

Conclusion

Increasing frailty was associated with three key quality metrics that is, eLOS, pLOS, LOS > 30 after neurosurgical procedures. The RAI demonstrated a higher discriminating threshold compared to both mFI‐5 and increasing patient age. Preoperative frailty screening may improve quality metrics through risk mitigation strategies and better preoperative communication with patients and their families.
Clinical impact of skeletal muscle mass change during the neoadjuvant chemotherapy period in patients with gastric cancer: An ancillary study of JCOG1002
Authors: Sato Reo , Tokunaga Masanori , Mizusawa Junki , Sato Yuya , Ito Seiji , Takahari Daisuke , Sano Takeshi , Onaya Hiroaki , Yoshikawa Takaki , Boku Narikazu , Terashima Masanori
Published: December 2023

Background

Recent studies have revealed that sarcopenia is associated with postoperative complications and poor prognosis. Although neoadjuvant chemotherapy is a promising treatment for gastric cancer, its toxicity may lead to the loss of skeletal muscle mass. This study investigates the changes in skeletal muscle mass during neoadjuvant chemotherapy and its clinical impact on patients with locally advanced gastric cancer.

Methods

Fifty patients who completed two courses of neoadjuvant chemotherapy followed by surgery were included. Skeletal muscle mass was measured using computed tomography images before and after chemotherapy. The proportion of skeletal muscle mass change (%SMC) during neoadjuvant chemotherapy and its cutoff value was explored using the receiver operating characteristic for the overall survival of patients undergoing R0 resection. Risk factors of skeletal muscle mass loss were also evaluated.

Results

Overall, 64% of patients had skeletal muscle mass loss during neoadjuvant chemotherapy (median %SMC −3.4%; range: −18.9% to 10.3%). Multivariable analysis identified older age (≥70 years) as an independent predictor of skeletal muscle mass loss (mean [95% confidence interval]: −4.70% [−8.83 to −0.58], p = 0.026). Among 43 patients undergoing R0 resection, %SMC <−6.9% was an independent poor prognostic factor for overall survival (hazard ratio, 11.53; 95% confidence interval, 2.78–47.80) and relapse‐free survival (hazard ratio 4.54, 95% confidence interval 1.50–13.81).

Conclusions

Skeletal muscle mass loss occurs frequently during neoadjuvant chemotherapy for locally advanced gastric cancer and could adversely affect survival outcomes.
Cameras, Pencils, Traumas: Drawn Images in and as Documentary Practice
Authors: Mousavi Nafiseh
Published: December 2023

Night and Fog in Kurdistan, a documentary film in its last stages of post-production at the time this chapter is being written, documents six years in the life of seven teenage girls who survived the ISIS genocide of Yazidis in 2014. Night and Fog in Kurdistan is a hybrid documentary in its way of combining different types of images, various perspectives, and different approaches to documentary filmmaking. In this film, the photographic image is once in a while interrupted and joined by drawings that serve different functions: They illustrate what is being narrated, portray what has not been captured by any media, or reproduce the archival photographic images. Analysing these functions as situated in the broader frame of different media relations, the article aims to investigate the affordances of drawing for documentation, especially in the case of traumatic experiences and in interaction with other modes of representation. The article is based on an analysis of the final cut of the film plus different versions of the drawings as well as two in-depth conversations with the director and her team.
Parental Impressions and Perspectives of Efficacy in Prenatal Counseling for Single Ventricle Congenital Heart Disease
Authors: Houlihan Taylor Hartzel , Combs Jill , Smith Elizabeth , Coulter Elizabeth , Figueroa Lucia , Falkensammer Christine , Savla Jill , Goldmuntz Elizabeth , Degenhardt Karl , Szwast Anita , Shillingford Amanda , Rychik Jack
Published: December 2023

Although commonly performed, optimal techniques, strategies, and content to achieve the most effective prenatal counseling have not been explored. We investigate the efficacy of prenatal counseling via survey feedback of parents of children with prenatally diagnosed single ventricle. Grades of counseling using a Likert scale (1–5) were solicited to assess: (1) overall impression of quantity of counseling, (2) explanation of the heart defect, (3) preparation for heart surgery, (4) preparation for hospital course and care, (5) preparation for complications and outcomes of a Fontan circulation, and (6) preparation for neurological, school-related, or behavioral problems. Impressions were solicited concerning specific providers. A comprehensive fetal counseling score was calculated for each participant. Burden of care including length of hospitalization was explored as impacting prenatal counseling grades. There were 59 survey respondents. Average age of the children at the time of survey was 4.6 ± 3.3 years (range 1–10 years). Highest grades were for explanation of the heart condition, with lowest grades for preparation for neurological, school-related, or behavioral problems. Cardiac surgeon received the highest with social worker lowest grade for provider. Negative correlation was found between the composite fetal counseling score and parental recollection of length of hospitalization (Pearson r = − 0.357, p < 0.01). Prenatal counseling for neurological, school-related, and behavioral problems in single ventricle is deficient. Further studies analyzing prenatal counseling techniques and content can help improve upon the delivery of this important aspect of prenatal care.
Preoperative evaluation of MRI features and inflammatory biomarkers in predicting microvascular invasion of combined hepatocellular cholangiocarcinoma
Authors: Zhang Juan , Dong Wei , Liu Wanmin , Fu Jiazhao , Liao Tian , Li Yinqiao , Huo Lei , Jia Ningyang
Published: December 2023

Purpose

Microvascular invasion (MVI) is a significant prognostic factor in combined hepatocellular cholangiocarcinoma (cHCC-CCA). However, its diagnosis relies on postoperative histopathologic analysis. This study aims to identify preoperative inflammatory biomarkers and MR-imaging features that can predict MVI in cHCC-CCA.

Methods

This retrospective study enrolled 119 patients with histopathologically confirmed cHCC-CCA between January 2016 and December 2021. Two radiologists, unaware of the clinical data, independently reviewed all MR image features. Univariable and multivariable analyses were performed to determine the independent predictors for MVI among inflammatory biomarkers and MRI characteristics. The area under the receiver operating characteristic (ROC) curve (AUC) was used to evaluate the diagnostic performance.

Results

Multivariable logistic regression analysis identified four variables significantly associated with MVI (p < 0.05), including two inflammatory biomarkers [albumin-to-alkaline phosphatase ratio (AAPR) and aspartate aminotransferase-to-neutrophil ratio index (ANRI)] and two MRI features (non-smooth tumor margin and arterial phase peritumoral enhancement). A combined model for predicting MVI was constructed based on these four variables, with an AUC of 0.802 (95% CI 0.719–0.870). The diagnostic efficiency of the combined model was higher than that of the imaging model.

Conclusion

Inflammatory biomarkers and MRI features could be potential predictors for MVI in cHCC-CCA. The combined model, derived from inflammatory biomarkers and MRI features, showed good performance in preoperatively predicting MVI in cHCC-CCA patients.

Graphical abstract
An improved protocol for bacteria identification by MALDI-TOF MS directly from positive blood cultures
Authors: Cruz Sara , Abreu David , Gomes Rosário , Martins-Oliveira Inês , Silva-Dias Ana , Perez-Viso Blanca , Cantón Rafael , Pina-Vaz Cidália
Published: December 2023

FASTinov® developed a rapid antimicrobial susceptibility test that includes the purification of a bacterial suspension directly from positive blood cultures (BC). In order to streamline laboratory workflow, the use of the bacterial suspension obtained through FASTinov® sample prep was tested for identification (ID) by matrix absorption laser deionization–time of flight mass spectrometry (MALDI-TOF MS) (Bruker) in 364 positive BC, and its accuracy assessed comparing with the MALDI-TOF MS ID of the next-day subcultured colonies. FASTinov sample prep was highly reliable for rapid ID directly from BC with proportion of agreement of 94.9% for Gram-positive and 96.3% for Gram-negative bacteria.
C-reactive protein levels, the prognostic nutritional index, and the lactate dehydrogenase-to-lymphocyte ratio are important prognostic factors in primary central nervous system lymphoma: a single-center study of 223 patients
Authors: Zuo Jinyi , Lei Ting , Zhong Shuai , Zhou Jiajun , Liu Rui , Wu Chenxing , Li Shouwei
Published: December 2023

Primary central nervous system lymphoma (PCNSL) is a rare and highly aggressive type of extranodal non-Hodgkin lymphoma (NHL), and the prognosis is poor. Currently, the most used prognostic models are the Memorial Sloan-Kettering Cancer Center (MSKCC) and International Extranodal Lymphoma Study Group (IELSG) scores; however, their predictive effects are changing with increasing incidence and changing treatment regimens. A growing body of evidence has demonstrated that inflammatory and nutritional markers are factors that can determine tumor prognosis. Therefore, the aim of this study was to identify and validate novel prognostic factors for PCNSL. Clinical information was collected from 223 patients with PCNSL. Patients younger than 18 years of age were excluded. Progression-free survival (PFS) and overall survival (OS) were used as endpoints, and receiver operating characteristic (ROC) curve analyses were conducted to determine the cutoff values for the inflammatory indicators. Correlations between variables and PFS or OS were assessed using univariate and multivariate analyses, and positive indicators were selected for survival analysis. A prognostic nutritional index (PNI) < 49.38 was associated with worse PFS (p = 0.003), and outcomes significantly differed between patients with a PNI ≥ 49.38 and < 49.38 (p < 0.001). Age < 60 years (p < 0.001) and C-reactive protein (CRP) levels < 3.14 (p = 0.001) were associated with better OS. In elderly patients (≥ 60 years), a lactate dehydrogenase-to-lymphocyte ratio (LLR) < 95.69 (p = 0.021) was associated with better OS, and the outcome significantly differed between patients with an LLR ≥ 95.69 and LLR < 95.69 (p = 0.015). The PNI and CRP levels are prognostic factors for PCNSL, and CRP was the first time shown to be a prognosis factor of PCNSL. In elderly patients with PCNSL, the LLR can predict prognosis.
What We Have Learned About Social Integration: Conclusion
Authors: Grunow Daniela , Sachweh Patrick , Schimank Uwe , Traunmüller Richard
Published: December 2023

This chapter concludes the special issue on social integration and makes three additional contributions. First, we discuss how the featured articles employ the concept of social integration that we have proposed in the introduction. We find clear references to the four ingredients of social integration that we have suggested: consensus, trust, conformity and cooperation. Many articles also agree with the multi-level nature of social integration. Second, we synthesise the answers that the featured articles provide for the open questions we have posed: how social integration is generated and how it is linked to societal outcomes, both normatively desirable and undesirable. Although most authors in this special issue start from the premise that social integration is inherently desirable, our conceptual lens also brings in the “dark side” of social integration. Third, we identify two further aspects that deserve more attention in future research: a rigorous analysis of how the mechanisms of social integration operate on the micro-, meso- and macro-levels of society; and more attention to the transnational interdependencies in which national modes of social integration are embedded.
Endosulfan residues and farmers’ replacement behaviors of endosulfan in the north-west inland cotton region
Authors: Zhou Shuyan , Zhang Yang , Wang Jingjing , Cheng Shikun , Zhuo Fuyan , Hong Yun
Published: December 2023

We assessed the situation of endosulfan residues in cotton fields after the endosulfan ban came into effect and the current knowledge, attitude, and practice (KAP) of cotton farmers on the phase-out of endosulfan and the application of alternative technologies. Topsoil samples (n = 91) of cotton fields were collected from the major cotton-producing areas in China, namely the north-west inland cotton region, and the endosulfan residues were analyzed. A KAP survey was carried out for cotton farmers, and 291 questionnaires were distributed. The influences of gender, age, education background, cotton planting years, publicity and training, income sources, and other factors on cotton farmers’ KAP were analyzed. The results showed that endosulfan sulfate was the main endosulfan residue in the soil, followed by β-endosulfan and α-endosulfan, the average residual contents were 0.569, 0.139, and 0.060 µg/kg, respectively. The results of the KAP study showed that cotton farmers scored low on knowledge about the phase-out of endosulfan and the application of alternative technologies but high on attitude and practice. The number of family members, years of cotton planting, age, and the cotton-planting area had different degrees of influence on KAP scores. The training could significantly improve the KAP scores of cotton farmers; training should be more targeted and designed reasonably for key groups, such as men and the population under 30, followed by training them to use pesticides safely. For large-scale cotton growers, training should focus on green prevention and control technologies.
Factors Influencing Medication Adherence Among Adults Living with Diabetes and Comorbidities: a Qualitative Systematic Review
Authors: Gow Kendall , Rashidi Amineh , Whithead Lisa
Published: December 2023

Purpose of review

Medication adherence plays an important role in improving health outcomes related to diabetes and comorbidity. The potential factors influencing medication adherence and how they contribute to health behaviors have not been synthesized to date. This review synthesized qualitative studies that identified factors influencing medication adherence among adults living with diabetes and comorbidity.

Recent findings

Twenty-eight findings were extracted and synthesized into four themes: perceived support, lack of knowledge, medication issues, and the importance of routine. The findings highlight the factors that support medication adherence and areas that can be targeted to support and promote medication adherence. The findings also support the potential role of healthcare providers in supporting people living with diabetes and comorbidity to adhere to and maintain medication regimes.

Several factors were identified that are amenable to intervention within the clinical practice setting and have the potential to enhance medication adherence and improve health outcomes for people living with diabetes and comorbidities. The development of acceptable and effective interventions could have a positive effect on medication adherence and health outcomes.
Enhancing Strength-Ductility Synergy of CoCrNi-Based Medium-Entropy Alloy Through Coherent L12 Nanoprecipitates and Grain Boundary Precipitates
Authors: Li Leilei , Song Kaikai , Gao Qingwei , Zhou Changshan , Liu Xiaoming , Wang Yaocen , Bai Xiaojun , Cao Chongde
Published: December 2023

The L12-strengthened Co34Cr32Ni27Al4Ti3 medium-entropy alloy (MEA) with precipitations of grain boundaries has been developed through selective laser melting (SLM) followed by cold rolling and annealing, exhibiting excellent strength-ductility synergy. The as-printed alloy exhibits low yield strength (YS) of ~ 384 MPa, ultimate tensile strength (UTS) of ~ 453 MPa, and uniform elongation (UE) of 1.5% due to the existence of the SLM-induced defects. After cold rolling and annealing, the YS, UTS, and UE are significantly increased to ~ 739 MPa, ~ 1230 MPa, and ~ 47%, respectively. This enhancement primarily originates from the refined grain structure induced by cold rolling and annealing. The presence of coherent spherical γ' precipitates (L12 phases) and Al/Ti-rich precipitates at the grain boundaries, coupled with increased lattice defects such as dislocations, stacking faults, and ultrafine deformation twins, further contribute to the property’s improvement. Our study highlights the potential of SLM in producing high-strength and ductile MEA with coherent L12 nanoprecipitates, which can be further optimized through subsequent rolling and annealing processes. These findings offer valuable insights for the development of high-performance alloys for future engineering applications.
A Semantic Enhanced Course Recommender System via Knowledge Graphs for Limited User Information Scenarios
Authors: Sanguino Juan , Manrique Ruben , Mariño Olga
Published: December 2023

The Universal Declaration of Human Rights states that “everyone has the right to education” and it must be “equally accessible to all”. Aligned with these principles are online learning platforms that offer free online courses that require no or minimal information from their students to democratize learning. Despite the benefits, the lack of user information challenges traditional recommendation systems and, when applied to education, impacts student experiences. This paper addresses the problem of limited student information in course recommendation systems. We tackle the problem by generating a semantically enriched vector-based representation of course content using an Open Knowledge Graph (DBpedia) and Topic Modeling methods, such as LDA and LSA and by collecting tracking events from log systems (Google Analytics) to create a hybrid recommendation system using content-based and collaborative filtering strategies for low-information scenarios. Our experiments use GCFGlobal.org, an online learning platform offering free self-paced online courses to 100 million people, to validate our approach. Results indicate that the proposed approach outperforms the previous works in the field contributing to the creation of fairer recommendation systems.
Neural nonnegative matrix factorization for hierarchical multilayer topic modeling
Authors: Haddock Jamie , Will Tyler , Vendrow Joshua , Zhang Runyu , Molitor Denali , Needell Deanna , Gao Mengdi , Sadovnik Eli
Published: December 2023

We introduce a new method based on nonnegative matrix factorization, Neural NMF, for detecting latent hierarchical structure in data. Datasets with hierarchical structure arise in a wide variety of fields, such as document classification, image processing, and bioinformatics. Neural NMF recursively applies NMF in layers to discover overarching topics encompassing the lower-level features. We derive a backpropagation optimization scheme that allows us to frame hierarchical NMF as a neural network. We test Neural NMF on a synthetic hierarchical dataset, the 20 Newsgroups dataset, and the MyLymeData symptoms dataset. Numerical results demonstrate that Neural NMF outperforms other hierarchical NMF methods on these data sets and offers better learned hierarchical structure and interpretability of topics.
Combined gas effect on the oil reservoir in a dual-well system
Authors: Ali Imran , Gubanov Sergey Igorevich , Alexandrovna Olkhovskaya Valeria , Moiseevich Shterenberg Alexander , Silantieva Anastasia Mikhailovna , Siddiqui Mohammad Nahid
Published: December 2023

Nowadays, high-viscosity oil reservoirs are located in a sphere of extra attention with the demands of special technologies. To maximize high-viscosity oil production advanced action technologies are used involving thermal and many other chemical methods. The article describes the results of a laboratory experiment to determine the rheological properties of high-viscosity oil, which determine the optimal temperature of the reservoir heating. A new method of thermobaric layer treatment; including heat transfer agent injection by a dual-well system; is suggested (injection to a vertical shaft and a heated oil production from a side shaft). A new steam injection steam-gas injection is proposed. The optimal layer warming temperature was 50 °C. The results of the calculations of the radius of the reservoir heating to the target temperature, which allowed for optimizing oil production are also discussed. Efficiency and warming area dependence on a heat-transfer agent to a layer injection time are also identified and presented. It was observed that thermo-physical calculations using the data of a laboratory experiment are useful in the well-design, as it allowed to determine the parameters of the technology and the position of the bottom hole about the source of heating. The optimal bottom hole spacing between the production side shaft and the vertical shaft was found to be 76.0 m. The optimal temperature of 50 °C was reached 10 days after the warning started.
Convolution Neural Network Bidirectional Long Short-Term Memory for Heartbeat Arrhythmia Classification
Authors: Alkhawaldeh Rami S. , Al-Ahmad Bilal , Ksibi Amel , Ghatasheh Nazeeh , Abu-Taieh Evon M. , Aldehim Ghadah , Ayadi Manel , Alkhawaldeh Samar M.
Published: December 2023

Arrhythmia is a heart condition that poses a severe threat to life and requires prompt medical attention. One of the challenges in detecting arrhythmias accurately is that incorrect diagnoses can have severe consequences. In light of this, it is critical to develop a solution that is both effective and reliable. In this study, we propose a residual Convolution Neural Network Bidirectional Long Short-Term Memory (DeepResidualBiLSTM) model for classifying Arrhythmia types, which addresses the vanishing gradient problem and captures the relevant features in the signals’ long dependencies. The model is characterized by its simplicity, stability, and ability to extract meaningful features effectively. Using two well-known datasets, the experimental results demonstrate exceptional accuracy, precision, and recall values of approximately 99.4% at the early stage of 20 epoch training. Furthermore, the model demonstrates a remarkable ability to discriminate between Arrhythmia classes under varying thresholds using the ROC curve metric, with a high value, in most cases, of 100% for accurately detecting positive cases.
Carbon taxation in Singapore's semiconductor sector: a mini-review on GHG emission metrics and reporting
Authors: Li Yuanzhe , Wang Yan , Chong Daphne , Xu Zhongqi , Li Luzi , Hu Yuchun
Published: December 2023

The threat of climate change has catalyzed global endeavors to curb greenhouse gas emissions, with carbon taxation emerging as a pivotal policy instrument. Singapore, akin to Taiwan, has embraced this tool, and its ramifications on their semiconductor industry are both profound and multifaceted. At the outset, the imposition of carbon taxes inevitably escalates production costs for semiconductor firms, compelling them to offset their carbon footprint financially. This escalation, in turn, poses a risk of eroding the industry's competitive edge, nudging firms to contemplate the prospect of migrating to locales with more lenient carbon taxation regimes. However, in juxtaposition to these challenges, carbon taxation unveils a silver lining. It instigates semiconductor entities to recalibrate their operations, infusing energy-efficient technologies and pivoting towards renewable energy avenues. Such transitions not only attenuate their carbon emissions but also curtail their financial burden arising from carbon taxation. This manuscript elucidates a panoramic landscape of both policy innovations and technological strides specific to Singapore's semiconductor arena. It aims to be an instrumental compass for stakeholders, delineating pathways for achieving optimal eco-financial equilibrium in the sector.

Graphical Abstract
Effects of niacin on apo A1 and B levels: a systematic review and meta-analysis of randomised controlled trials
Authors: Saboori Somayeh , Yousefi Rad Esmaeil , Tammam Jonathan , Thondre Pariyarath Sangeetha , Coe Shelly
Published: December 2023

Niacin has been investigated for its potential impact on lipid metabolism and cardiovascular health. This meta-analysis aims to systematically evaluate the effects of niacin interventions on apo A1 and apo B levels, key regulators of lipoprotein metabolism and markers of cardiovascular risk. A comprehensive search of the literature was performed on five databases of PubMed, Scopus, Web of Science, Embase and Cochrane library, from inception up to 15 July 2023. This search identified 1452 publications, from which twelve randomised controlled trials met the inclusion criteria. The intervention dosages ranged from 500 to 3000 mg/d, and the study durations spanned from 6 to 102·8 weeks. The niacin intervention demonstrated a significant reduction in apo B levels (weighted mean differences (WMD): −24·37 mg/dl, P = 0·01). Subgroup analyses indicated that intervention duration played a role, with trials of ≤ 16 weeks showing a greater reduction in apo B. Regarding apo A1, niacin significantly increased its levels (WMD: 8·23 mg/dl, P < 0·001). Subgroup analyses revealed that the beneficial effects of niacin on apo A1 were observed at a dosage of > 1500 mg/d (P < 0·001), and extended-release niacin was more effective compared with other forms (P < 0·001). According to the Begg’s regression test, no publication bias was observed in this systematic review and meta-analysis. This meta-analysis highlights niacin’s potential role in improving lipid profiles and cardiovascular health. Further well-designed clinical trials are needed to elucidate and confirm optimal dosages and durations of niacin interventions for influencing apo A1 and B.
Visibility and exploitation in social networks
Authors: Galimullin Rustam , Pedersen Mina Young
Published: December 2023

Social media is not a neutral channel. How visible information posted online is depends on many factors such as the network structure, the emotional volatility of the content, and the design of the social media platform. In this paper, we use formal methods to study the visibility of agents and information in a social network, as well as how vulnerable the network is to exploitation. We introduce a modal logic to reason about a social network of agents that can follow each other, post, and share information. We show that by imposing some simple rules on the system, a potentially malicious agent can take advantage of the network construction to post an unpopular opinion that may reach many agents. The network is presented both in static and dynamic forms. We prove completeness, expressivity, and model checking problem complexity results for the corresponding logical systems.
Evaluation der deutschsprachigen Version des Regulatory Emotional Self-Efficacy Fragebogens für Jugendliche
Authors: Gutzweiler Raphael , Schug Sira , Lohoff Judith , In-Albon Tina
Published: December 2023

Zusammenfassung: Theoretischer Hintergrund: Die Überzeugung, dass die eigenen Emotionen reguliert werden können, zählt als Voraussetzung für eine erfolgreiche Emotionsregulation und damit für die psychische Gesundheit. Methode: In drei Stichproben (Jugend, Schüler_innen, klinische Stichprobe) wurde bei 509 Jugendlichen und jungen Erwachsenen ( M = 16.55 Jahren, SD = 2.72, Range = 13 – 23 Jahre, 66.6 % weiblich) eine angepasste Fragebogenversion des Regulatory Emotional Self-Efficacy (RESE-D; Caprara et al., 2008 ) zur Erfassung der Selbstwirksamkeit im Umgang mit Emotionen evaluiert. Mittels Multigruppenfaktorenanalyse wurde die Faktorenstruktur des RESE-D, Messinvarianz, Reliabilität und Validität in Bezug zu weiteren Fragebögen überprüft. Ergebnisse: Jugendliche der klinischen Stichprobe zeigten eine signifikant geringere Selbstwirksamkeit in der Emotionsregulation als die Schulstichprobe (differenzielle Validität). Die Reliabilität (interne Konsistenz Cronbachs α zwischen .71 und .82 für die Subskalen) und konvergente Validität des RESE-D konnte mittels signifikanter Korrelationen zu Konstrukten wie Emotionsregulation, allgemeiner Selbstwirksamkeit, Lebensqualität und erhöhter Ängstlichkeit aufgezeigt werden. Schlussfolgerungen: Mit dem RESE-D liegt ein reliabler, valider und mit zehn Items ökonomischer Fragebogen für das Jugendalter vor.
Model of Storm Surge Maximum Water Level Increase in a Coastal Area Using Ensemble Machine Learning and Explicable Algorithm
Authors: Sun Kun , Pan Jiayi
Published: December 2023

This study proposes a novel, new ensemble model (NEM) designed to simulate the maximum water level increases caused by storm surges in a frequently cyclone‐affected coastal water of Hong Kong, China. The model relies on storm and water level data spanning 1978–2022. The NEM amalgamates three machine learning algorithms: Random Forest (RF), Gradient Boosting Decision Tree (GBDT), and XGBoost (XGB), employing a stacking technique for integration. Six parameters, determined using the Random Forest and Recursive Feature Elimination algorithms (RF‐RFE), are used as input features for the NEM. These parameters are the nearest wind speed, gale distance, nearest air pressure, minimum distance, maximum pressure drop within 24 hr, and large wind radius. Model assessment results suggest that the NEM exhibits superior performance over RF, GBDT, and XGB, delivering high stability and precision. It reaches a coefficient of determination (R2) up to 0.95 and a mean absolute error (MAE) that fluctuates between 0.08 and 0.20 m for the test data set. An interpretability analysis conducted using the SHapley Additive exPlanations (SHAP) method shows that gale distance and nearest wind speed are the most significant features for predicting peak water level increases during storm surges. The results of this study could provide practical implications for predictive models concerning storm surges. These findings present essential tools for the mitigation of coastal disasters and the improvement of marine disaster warning systems.
How the Hunga Tonga—Hunga Ha'apai Water Vapor Cloud Impacts Its Transport Through the Stratosphere: Dynamical and Radiative Effects
Authors: Niemeier Ulrike , Wallis Sandra , Timmreck Claudia , van Pham Trang , von Savigny Christian
Published: December 2023

The eruption of the Hunga Tonga—Hunga Ha'apai (HTHH) volcano on 15 January 2022 injected about 150 Tg of water vapor (H2O), roughly 10% of the background stratospheric H2O content, to altitudes above 50 km. Simulations of the spatial evolution of the H2O cloud with the ICON‐Seamless model are very close to observations from the Aura Microwave Limb Sounder. The vertical transport of the H2O cloud had three phases: an initial subsidence phase, a stable phase, and a rising phase. Radiative cooling of H2O clearly affects the transport of the H2O cloud, as demonstrated with passive tracers, and is the main driver within the subsidence phase. It also counteracts the large‐scale rising motion in the tropics, leading to the stable phase, and modulates the large‐scale transport of the H2O cloud for about 9 months. This holds for different QBO phases, where the H2O cloud differs mainly in its vertical extent.
Reduced Deep Convection and Bottom Water Formation Due To Antarctic Meltwater in a Multi‐Model Ensemble
Authors: Chen Jia‐Jia , Swart Neil C. , Beadling Rebecca , Cheng Xuhua , Hattermann Tore , Jüling André , Li Qian , Marshall John , Martin Torge , Muilwijk Morven , Pauling Andrew G. , Purich Ariaan , Smith Inga J. , Thomas Max
Published: December 2023

The additional water from the Antarctic ice sheet and ice shelves due to climate‐induced melt can impact ocean circulation and global climate. However, the major processes driving melt are not adequately represented in Coupled Model Intercomparison Project phase 6 (CMIP6) models. Here, we analyze a novel multi‐model ensemble of CMIP6 models with consistent meltwater addition to examine the robustness of the modeled response to meltwater, which has not been possible in previous single‐model studies. Antarctic meltwater addition induces a substantial weakening of open‐ocean deep convection. Additionally, Antarctic Bottom Water warms, its volume contracts, and the sea surface cools. However, the magnitude of the reduction varies greatly across models, with differing anomalies correlated with their respective mean‐state climatology, indicating the state‐dependency of the climate response to meltwater. A better representation of the Southern Ocean mean state is necessary for narrowing the inter‐model spread of response to Antarctic meltwater.