bluuebunny/crossref_metadata_2025_split huggingface dataset:
Weekly Somapacitan in GH Deficiency: 4-Year Efficacy, Safety, and Treatment/Disease Burden Results From REAL 3
Authors: Sävendahl Lars , Battelino Tadej , Højby Rasmussen Michael , Brod Meryl , Röhrich Sebastian , Saenger Paul , Horikawa Reiko 
Published: March 2023

Abstract

Context
Growth hormone deficiency (GHD) in children is currently treated with daily injections of GH, which can be burdensome for patients and their parents/guardians. Somapacitan is a GH derivative in development for once-weekly treatment of GHD.

Objective
This work aimed to assess the efficacy and safety of somapacitan, and associated disease/treatment burden, after 4 years of treatment and 1 year after switching to somapacitan from daily GH.

Methods
This long-term safety extension of a multicenter, controlled phase 2 trial (NCT02616562) took place at 29 sites in 11 countries. Patients were prepubertal, GH-naive children with GHD. Fifty patients completed 4 years of treatment. Patients in the pooled group received somapacitan (0.04, 0.08, 0.16 mg/kg/week) for 1 year, followed by the highest dose (0.16 mg/kg/week) for 3 years. Patients in the switched group received daily GH 0.034 mg/kg/day for 3 years, then somapacitan 0.16 mg/kg/week for 1 year. Main outcome measures were height velocity (HV), change from baseline in HV SD score (SDS), change from baseline in height SDS, disease burden, and treatment burden for patients and parents/guardians.

Results
Changes from baseline in HV and HV SDS were similar and as expected in both groups. Observer-reported outcomes showed that patients and parents/guardians seem to have experienced a reduced treatment burden when switching from daily GH to somapacitan. Most parents/guardians (81.8%) strongly/very strongly preferred somapacitan over daily GH.

Conclusions
Somapacitan showed similar efficacy and safety in patients who continued somapacitan treatment and those who switched from daily GH to somapacitan. Once-weekly injections may lead to a reduced treatment burden relative to once-daily injections. A plain-language summary of this work is available.
Inter-rater agreement between radiologists using the novel CT-TDV (T3c+; tumour deposits; EMVI) system in patients with potentially curable right colon cancer
Authors: Hodges Nicola , Duxbury Oliver , Corr Alison , Cho Seung Hyon , Miskovic Danilo , Brown Gina 
Published: March 2023

Objectives: The novel CT-TDV scoring system, identifying T3c + disease; the presence/absence of tumour deposits and EMVI has been shown to be superior in predicting prognosis when compared to the CT-TNM staging system in the evaluation of colon cancer. Reproducibility of this scoring system between specialist GI radiologists has not been assessed previously. The aim of this study was to assess the inter-rater agreement of gastrointestinal radiologists in assessing the novel pre-operative CT-TDV scoring of patients with potentially curable right-sided colon cancer. Methods: Ninety-three right colon cancer pre-operative CT scans were graded as CT TDV “good” versus TDV “poor” by four radiologists. Inter-rater agreement was assessed using the intraclass correlation coefficient (ICC) between all four readers and individual readers against the central radiologist using Cohen’s κ statistic. Results: The ICC comparing those graded as TDV “good” versus TDV “poor” for all 93 cases was 0.61 (0.51–0.70) indicating moderate reliability. Individual κ scores across the 93 cases were 0.76, 0.59 and 0.59 (p < 0.001) indicating moderate to substantial agreement. Conclusion: The CT TDV scoring system is reproducible amongst trained gastrointestinal radiologists in the assessment of newly diagnosed right colon cancer. Advances in knowledge: This further validates the clinical utility of the CT TDV scoring system as a prognostic tool to guide the management of patients with potentially curable right colon cancer.
An Ensemble Learning Approach with Gradient Resampling for Class-Imbalance Problems
Authors: Zhao Hongke , Zhao Chuang , Zhang Xi , Liu Nanlin , Zhu Hengshu , Liu Qi , Xiong Hui 
Published: March 2023

Imbalanced classification is widely referred in many real-world applications and has been extensively studied. Most existing algorithms consider alleviating the imbalance by sampling or guiding ensemble learners with punishments. The combination of ensemble learning and sampling strategy at class level has achieved great progress. Actually, specific hard examples have little benefit for model learning and even degrade the performance. From the view of identifying classification difficulty of samples, one important motivation is to design algorithms to finely equip different samples with progressive learning. Unfortunately, how to perfectly configure the sampling and learning strategies under ensemble principles at the sample level remains a research gap. In this paper, we propose a new view from the sample level rather than class level in existing studies. We design an ensemble approach in pipe with sample-level gradient resampling, that is, balanced cascade with filters (BCWF). Before that, as a preliminary exploration, we first design a hard examples mining algorithm to explore the gradient distribution of classification difficulty of samples and identify the hard examples. Specifically, BCWF uses an under-sampling strategy and a boosting manner to train T predictive classifiers and reidentify hard examples. In BCWF, moreover, we design two types of filters: the first is assembled with a hard filter (BCWF_h), whereas the second is assembled with a soft filter (BCWF_s). In each round of boosting, BCWF_h strictly removes a gradient/set of the hardest examples from both classes, whereas BCWF_s removes a larger number of harder and easy examples simultaneously for final balanced-class retention. Consequently, the well-trained T predictive classifiers can be used with two ensemble voting strategies: average probability and majority vote. To evaluate the proposed approach, we conduct intensive experiments on 10 benchmark data sets and apply our algorithms to perform default user detection on a real-world peer to peer lending data set. The experimental results fully demonstrate the effectiveness and the managerial implications of our approach when compared with 11 competitive algorithms.History: Accepted by Ram Ramesh, Area Editor for Data Science & Machine Learning.Funding: This work was supported by the National Natural Science Foundation of China [Grants 72101176, 71722005, and 72241432], the National Key R&D program of China [Grant 2020YFA0908600] and the Natural Science Foundation of Tianjin City [Grant 18JCJQJC45900].Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2023.1274 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2021.0104 ) at ( http://dx.doi.org/10.5281/zenodo.6360996 ).
Distributionally Robust Batch Contextual Bandits
Authors: Si Nian , Zhang Fan , Zhou Zhengyuan , Blanchet Jose 
Published: March 2023

Policy learning using historical observational data are an important problem that has widespread applications. Examples include selecting offers, prices, or advertisements for consumers; choosing bids in contextual first-price auctions; and selecting medication based on patients’ characteristics. However, existing literature rests on the crucial assumption that the future environment where the learned policy will be deployed is the same as the past environment that has generated the data: an assumption that is often false or too coarse an approximation. In this paper, we lift this assumption and aim to learn a distributionally robust policy with incomplete observational data. We first present a policy evaluation procedure that allows us to assess how well the policy does under worst-case environment shift. We then establish a central limit theorem type guarantee for this proposed policy evaluation scheme. Leveraging this evaluation scheme, we further propose a novel learning algorithm that is able to learn a policy that is robust to adversarial perturbations and unknown covariate shifts with a performance guarantee based on the theory of uniform convergence. Finally, we empirically test the effectiveness of our proposed algorithm in synthetic datasets and demonstrate that it provides the robustness that is missing using standard policy learning algorithms. We conclude the paper by providing a comprehensive application of our methods in the context of a real-world voting data set.This paper was accepted by Hamid Nazerzadeh, data science.Funding: This work was supported by the National Science Foundation [Grant CCF-2106508] and the Air Force Office of Scientific Research [Award FA9550-20-1-0397]. Z. Zhou also gratefully acknowledges the JP Morgan AI Research Grant and the New York University’s Center for Global Economy and Business faculty research grant for support on this work. Additional support is gratefully acknowledged from the National Science Foundation [Grants 1915967 and 2118199].Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4678 .
Human and Machine: The Impact of Machine Input on Decision Making Under Cognitive Limitations
Authors: Boyacı Tamer , Canyakmaz Caner , de Véricourt Francis 
Published: March 2023

The rapid adoption of artificial intelligence (AI) technologies by many organizations has recently raised concerns that AI may eventually replace humans in certain tasks. In fact, when used in collaboration, machines can significantly enhance the complementary strengths of humans. Indeed, because of their immense computing power, machines can perform specific tasks with incredible accuracy. In contrast, human decision makers (DMs) are flexible and adaptive but constrained by their limited cognitive capacity. This paper investigates how machine-based predictions may affect the decision process and outcomes of a human DM. We study the impact of these predictions on decision accuracy, the propensity and nature of decision errors, and the DM’s cognitive efforts. To account for both flexibility and limited cognitive capacity, we model the human decision-making process in a rational inattention framework. In this setup, the machine provides the DM with accurate but sometimes incomplete information at no cognitive cost. We fully characterize the impact of machine input on the human decision process in this framework. We show that machine input always improves the overall accuracy of human decisions but may nonetheless increase the propensity of certain types of errors (such as false positives). The machine can also induce the human to exert more cognitive efforts, although its input is highly accurate. Interestingly, this happens when the DM is most cognitively constrained, for instance, because of time pressure or multitasking. Synthesizing these results, we pinpoint the decision environments in which human-machine collaboration is likely to be most beneficial. This paper was accepted by Jeannette Song, operations management. Supplemental Material: The data files and online appendices are available at https://doi.org/10.1287/mnsc.2023.4744 .
Spectral studies of Nd3+ doped different fluorophosphate glasses for their aptness in laser applications at 1060 nm
Authors:   Sri Venkateswara University, Narayana Devara B. Surya , Ratnakaram Y.C. , Kumar M. 
Published: March 2023

Neodymium doped fluorophosphate (FP:Nd3+) glasses with different chemical compositions (59NH4H2PO4+15ZnO +15BaF2+10X+1·0NdF3 (X=LiF, NaF, CaF2, SrF2, AlF3)) were prepared by melt quenching. Their structures and spectroscopic properties were studied using x-ray diffraction, FTIR, FT-Raman and 31P, 27Al MAS NMR techniques. Various structural groups were identified using FTIR and FT-Raman spectra. The depolymerisation of metaphosphate chains are described by the decrease of Q2 tetrahedral sites allowing the formation of pyrophosphate groups revealed by 31P MAS NMR spectroscopic studies. Optical properties were studied using absorption and photoluminescence spectroscopy. Judd–Ofelt intensity parameters Ωλ (λ=2, 4 and 6) were estimated from absorption spectra. Radiative parameters such as transition probabilities (A), radiative lifetimes (τR), integrated absorption cross-sections (Σ) and branching ratios (βR) were calculated. Two emission lines at 1060 and 1330 nm were observed for Nd3+ in all the fluorophosphate glasses. From the emission spectra, emission characteristics were studied via optical band gains (σe×τR) and gain bandwidths (σe×Δλeff). Fairly large numerical values for peak emission cross-sections (σe) and branching ratios (β) for 4F3/2Æ4I11/2 transition of Nd3+ ion doped calcium fluorophosphate glass were observed. These results are rosy for NIR laser application at 1060 nm.
Rethinking mental health care provided to migrants and refugees; a randomized controlled trial on the effectiveness of Value Based Counseling, a culturally sensitive, strength-based psychological intervention
Authors: Orang Tahereh Mina , Missmahl Inge , Gardisi Maryam , Kluge Ulrike 
Published: March 2023

BackgroundDespite traumatic experiences and persistent psychosocial stressors, many refugees and migrants display resilience and strength in the midst and aftermath of hardships. ‘Value Based Counseling’ (VBC), a low-threshold, short-term and culturally sensitive psychological intervention avoids the stigmatization and pathologization of mental health problems, and, in line with latest research calling for a rethink of mental health care for migrants and refugees, focusses on the resilience and resources of clients.MethodThis pragmatic, assessor-blinded randomized controlled trial employed a pre-post control group design to assess the effectiveness of VBC in the development of psychological assets. Refugees and migrants aged 18 or above were randomly assigned to either VBC sessions delivered by counselors matched with their clients according to gender and native language, or to a waiting list.ResultsPer protocol and intention-to-treat (ITT) analyses revealed that compared with participants in the waiting-list group (n = 50), the VBC group (n = 53) experienced a greater improvement in resilience (adjusted difference 11.59, 95% CI 8.35 to 14.84, effect size .49,p <.001) and perspective taking (adjusted difference 3.98, 95% CI 2.12 to 5.84, effect size .39,p <.001) after four sessions on average. These positive results remained consistent until a 3-month follow-up assessment within the VBC group.ConclusionVBC with a focus on personal resources in the Here and Now, and with a culturally sensitive approach, helps clients exposed to persistent psychosocial stressors to develop strength and to increase agency over their lives.
What’s in, and what’s out? A study of student choice of learning activities in a flipped EFL classroom
Authors: Shen Yan 
Published: March 2023

Abstract
Flipping pedagogy has gained popularity in higher education. Learning activities are decisive to the effectiveness of a flipped classroom. However, research dedicated to learning activities in flipped classrooms is limited in quantity and even scarcer from learners’ perspectives. This paper explores students’ choice of learning activities in and out of a flipped EFL classroom to find more targeted measures to enhance teaching and learning practices in flipped classrooms. Student proposals (n = 30) for learning activities from 30 sophomores in an integrated English course (IEC) were used as media for data collection. The technology acceptance model (TAM) was used as the analytical framework. The findings showed that the participants proposed a conventional learning method emphasising lectures and revisions, which can result from students’ understanding of effective learning and their perceived usefulness of technology. This study concluded that successful flipped teaching entails considering student needs in the e-learning environment, quality learning activities and sufficient support for students to develop their autonomy.
On the Bivariate Generalized Gamma-Lindley Distribution
Authors: Ghorbel Mohamed Ali , Mecene Rahmouna 
Published: March 2023

ABSTRACT
In this research paper, we propose a new class of bivariate distributions called Bivariate Generalized Gamma-Lindley (BGGL) distribution with four parameters. This model is a mixture of independent Gamma random variables and bivariate generalized Lindley distribution. We investigate various properties of the new bivariate distribution such as graphical representation, joint moments and correlation. Furthermore, we derive a measure of entropy of this bivariate distribution. We also derive the distributions of the random variables X
1 + X
2, X
1/(X
1 + X
2), X
1/X
2 and X
1
X
2 as well as the corresponding moment properties when X
1 and X
2 follow the BGGL distribution. Additionally, we address two approximations of the product of the proposed model and assess their goodness of fit. Next, we elaborate the expectation maximization (E.M) algorithm in order to estimate the BGGL model parameters. Finally, we provide two concrete examples to demonstrate the applicability of the results.
General overview of biopolymers: structure and properties
Authors: Sasikanth Vasuki , Meganathan Bhuvaneswari , Rathinavel Thirumalaisamy , Seshachalam Sindhu , Nallappa Harini , Gopi Brindha 
Published: March 2023

Abstract
Biopolymers are synthesized from a biological origin under natural phenomenon especially during their growth cycle, in the form of polymeric substances that portrays excellent properties such as flexibility, tensile strength, steadiness, reusability, and so on. The amalgamated form of two or more biopolymers leads to the formation of “biocomposites” with novel applications. Several mechanisms were identified for the effective production of biopolymers from diverse life forms such as microbial origin plant and animal origin. Based on their origin, biopolymer differs in their structure and functions. Biopolymers are preferred over chemically synthesized polymers due to their biodegradability and their impact on the environment. Biopolymers play a pivotal role in pharmaceutical industries. The biopolymers could be employed for, the administration of medicine as well as regenerative medicine to reach minimal immunogenicity and maximum pharmacological expressivity in a treated individual. Based on their properties biopolymers were exclusively used in medical devices, cosmaceuticals, and confectionaries, it is also used as additives in food industries, bio-sensors, textile industries, and wastewater treatment plants. Ecological support is of utmost concern nowadays due to the ever-expanding ramification over the planet by usage of plastic as packaging material, turning up scientists and researchers to focus on biodegradable biopolymer utilization. The miscibility-structural-property relation between every biopolymer must be focused on to improve the better environment. Specific biopolymers are designed for the betterment of agrarian and commoners of society. Advanced structural modifications, properties of biopolymers, and applications of biopolymers to achieve a greener environment were discussed in this chapter.
FSH promotes immature porcine Sertoli cell proliferation by activating the CCR7/Ras-ERK signaling axis
Authors: Yin Yanfei , Ma Jiajia , Lu Xiaofang , Yan Saina , Jiang Qianqian , Wu Dazhi , Chen Bin , Weng Bo , Ran MaoLiang 
Published: March 2023

In brief
The appropriate growth and functions of Sertoli cells are crucial to testis development and spermatogenesis in mammals. This study reveals a novel mechanism of follicle-stimulating hormone in immature porcine Sertoli cell proliferation.

Abstract
Follicle-stimulating hormone (FSH) is a major Sertoli cell mitogen that binds to the FSH receptor. Sertoli cells are indispensable for testis development and spermatogenesis. However, the regulatory mechanisms of FSH in immature Sertoli cell proliferation have not been determined, particularly in domestic animals. In the present study, we identified the regulatory mechanisms of FSH during immature porcine Sertoli cell proliferation. Transcriptome analysis revealed 114 differentially expressed genes that were induced by FSH treatment, which contains 68 upregulated and 46 downregulated genes. These differentially expressed genes were enriched in multiple pathways, including the Ras signaling pathway. Knockdown of the CC-chemokine receptor 7 (CCR7) gene, which was upregulated by FSH, inhibited cell cycle progression by arresting cells in the G1 phase and reduced the cell proliferation and ERK1/2 phosphorylation. In addition, Kobe0065 inhibited Ras signaling in a similar manner as CCR7 knockdown. Furthermore, FSH abolished the effects of Ras signaling pathway inhibition and CCR7 knockdown. Collectively, FSH promotes immature porcine Sertoli cell proliferation by activating the CCR7/Ras-ERK signaling axis. Our results provide novel insights into the regulatory mechanism of FSH in porcine testis development and spermatogenesis by deciding the fate of immature porcine Sertoli cells.
Knowledge of pharmacovigilance among healthcare professionals and the impact of an educational intervention
Authors: Shenoy Ashok K , Kamath Ashwin , Chowta Mukta N , Boloor Archith , Aravind Ajith , Thakur Priyamedha Bose , Kumar Sachin 
Published: March 2023

Aim. To determine the knowledge regarding various aspects of pharmacovigilance among doctors and nurses of a tertiary care teaching hospital and to evaluate the effect of an educational intervention.
Methods. A cross-sectional study was conducted among doctors and nurses of a tertiary care teaching hospital. The participants attended a one-hour educational session during which the concept of pharmacovigilance, the Pharmacovigilance Program of India, the need for reporting ADRs, and the method of reporting were explained by a subject expert. A 20-item questionnaire was used to assess their knowledge regarding pharmacovigilance before and after an educational session. The pre-post comparisons were done using Wilcoxon’s signed-rank test. A p-value less than 0.05 was considered statistically significant.
Results. Forty-two doctors and 115 nurses participated in the study. A significant improvement in the participant scores was seen following the educational intervention in both doctors (Z = −5.344, p < 0.001) and nurses (Z = −8.808, p < 0.001). Lack of knowledge/awareness was perceived as the major barrier for ADR reporting among nurses as well as doctors.
Conclusion. There is need for education and training among doctors and nurses to enhance their knowledge about drug safety and reporting practices. Educational intervention is likely to improve the knowledge regarding pharmacovigilance, and thereby enhance reporting by healthcare professionals.