bluuebunny/crossref_metadata_2025_split huggingface dataset:
Toward a smart forecasting model in supply chain management: A case study of coffee in Vietnam
Authors: Nguyen Thi Thuy Hanh , Bekrar Abdelghani , Le Thi Muoi , Abed Mourad , Kantasa‐ard Anirut 
Published: August 2024

AbstractForecasting is a crucial part of supply chain management. Accurate forecasts have a strong influence on supply chain performance. Many forecasting methods have been developed and adapted in various domains and industries. However, none are perfect in all contexts due to the data's characteristics and the methods' strength. Hence, we propose a new ARIMAX‐LSTM hybrid forecasting model that integrates ARIMAX and LSTM models to improve the ability to capture different combinations of linear and nonlinear patterns in time series. Our proposed model is validated in a case study of coffee demand in Vietnam. The case study results show that our proposed model outperforms the well‐known single and current hybrid models regarding performance measures and degree of association. Moreover, to prove the model's robustness, we test and compare our proposed model to the previous study for Thailand's agricultural products (pineapple, corn, and cassava). Computational results demonstrate that our hybrid model is superior in the majority of experiments. It has a strong capability of predicting complex time series data. Furthermore, our proposed method increases forecasting accuracy and enhances supply chain performance (measured by the bullwhip effect; net‐stock amplification, and transportation cost.
Forecasting USD/RMB exchange rate using the ICEEMDAN‐CNN‐LSTM model
Authors: Zhou Yun , Zhu Xuxu 
Published: August 2024

AbstractBecause the exchange rate is essentially a dynamic and nonlinear system, exchange rate forecasting has been one of the most challenging topics in the financial field. This paper proposes a novel idea of “decomposition‐reconstruction‐integration” to predict exchange rate. First, based on ICEEMDAN, the original sequences are decomposed into multifrequency IMFs. Second, we use t‐test to determine the high‐frequency IMFs, low‐frequency IMFs, and trend sequence and reconstruct the high‐frequency IMFs into a new component sequence. Third, we use CNN‐LSTM model to predict these components separately and finally get the final prediction result by integration. This paper takes the USD/RMB exchange rate as research object, and the experimental results show that (1) the fluctuations of USD/RMB exchange rate are mainly affected by the trend sequence and low‐frequency IMFs and are less affected by high‐frequency IMFs. (2) The evaluation criterions RMSE, MAE, and MAPE of the ICEEMDAN‐CNN‐LSTM model are relatively small, with values of 0.0156, 0.0112, and 0.1679, respectively, indicating that the predictive performance of the model is optimal. (3) This paper has conducted various robust tests, all of which indicate that the proposed model has high prediction accuracy and stability. In summary, this paper has certain theoretical significance and application value.
Representation of women in clinical trials supporting FDA‐approval of contemporary cancer therapies
Authors: Kalathoor Sujay , Ghazi Sanam , Otieno Beryl , Babcook Melissa A. , Chen Sunnia , Nidhi Neha , Bae Junu , Pierre‐Charles Jovan , Breathett Khadijah , Mazimba Sula , Johnson Amber , Brewer LaPrincess , Mohammed Selma , Carter Rebecca R. , Bonsu Janice M. , Ferdousi Mussammat , Kola‐Kehinde Onaopepo , McLaughlin Eric , Brammer Jonathan , Ruz Patrick , Khan Sarah , Odei Bismarck , Mitchell Darrion , Wei Lai , Patel Prem , Paskett Electra D. , Addison Daniel 
Published: August 2024

AbstractContemporary anticancer therapies frequently have different efficacy and side effects in men and women. Yet, whether women are well‐represented in pivotal trials supporting contemporary anticancer drugs is unknown. Leveraging the Drugs@FDA database, clinicaltrials.gov, MEDLINE, and publicly available FDA‐drug‐reviews, we identified all pivotal (phase II and III) non‐sex specific trials supporting FDA‐approval of anticancer drugs (1998–2018). Observed‐enrollment‐rates were compared to expected‐population‐rates derived from concurrent US‐National‐Cancer‐Institute's Surveillance‐Epidemiology‐and‐End‐Results (SEER) reported rates and US‐Census databases. Primary outcome was the proportional representation of women across trials, evaluated by a participation‐to‐prevalence ratio (PPR), according to cancer type. Secondary outcome was the report of any sex‐specific analysis of efficacy and/or safety, irrespective of treatment‐arm. Overall, there were 148 trials, enrolling 60,216 participants (60.5 ± 4.0 years, 40.7% female, 79.1% biologic, targeted, or immune‐based therapies) evaluating 99 drugs. Sex was reported in 146 (98.6%) trials, wherein 40.7% (24,538) were women, compared to 59.3% (35,678) men (p < .01). Altogether, women were under‐represented in 66.9% trials compared to the proportional incidence of cancers by respective disease type; weight‐average PPR of 0.91 (relative difference: ‐9.1%, p < .01). Women were most under‐represented in gastric (PPR = 0.63), liver (PPR = 0.71), and lung (PPR = .81) cancer trials. Sex‐based safety data was reported in 4.0% trials. There was no association between adequate female enrollment and drug efficacy (HR: 0.616 vs. 0.613, p = .96). Over time, there was no difference in the percentage of women recruited into clinical trials. Among pivotal clinical trials supporting contemporary FDA‐approved cancer drugs, women were frequently under‐represented and sex‐specific‐efficacy and safety‐outcomes were commonly not reported.
Long‐term patient‐reported values following cancer surgery: A global survey study
Authors: Joseph Edward A. , Abdullah Abiha , Maxwell Conor M. , Yellin Samuel , Chalikonda Sricharan , Bartlett David L. , Allen Casey J. 
Published: August 2024

AbstractBackground and ObjectivesWe evaluated the long‐term quality of life (QOL) and priorities of an international cohort of cancer surgery survivors.MethodsPatients were surveyed through online support groups. We utilized the Short Form‐12 questionnaire to evaluate QOL and a novel survey to assess the relative importance of longevity, experience, and costs.ResultsA total of 592 patients from six continents responded. They were 58 ± 12 years old, 70% female, and 92% White. Patients averaged 37 months from their initial cancer diagnosis, with a maximum survivorship of 46 years. Across 17 disease sites, respondents generally ranked longevity, functional independence, and emotional well‐being most important, while treatment experience and costs were ranked least important (W = 33.6%, p < 0.001). However, a subset of respondents ranked costs as significantly important. There were no differences in QOL based on demographics, except patients with higher education and income reported better QOL scores. Despite improvements in QOL throughout survivorship, both physical‐QOL (41.1 ± 11.1 at 1 year vs. 42.3 ± 12.6 at 5 years, p = 0.511) and mental‐QOL (41.3 ± 13.4 at 1 year vs. 44.6 ± 13.9 at 5 years, p = 0.039) remained below that of the general population (50 ± 10; both p < 0.001).ConclusionsCancer survivors experience enduring physical and mental impairment throughout survivorship. Future efforts should aim to provide sustained support across varied socioeconomic groups, ensuring equitable care and enhancement of QOL postcancer treatment.
More than meets the eye: Augmented reality in surgical oncology
Authors: Prasad Kavita , Fassler Carly , Miller Alexis , Aweeda Marina , Pruthi Sumit , Fusco Joseph C. , Daniel Bruce , Miga Michael , Wu Jie Ying , Topf Michael C. 
Published: August 2024

AbstractBackground and ObjectivesIn the field of surgical oncology, there has been a desire for innovative techniques to improve tumor visualization, resection, and patient outcomes. Augmented reality (AR) technology superimposes digital content onto the real‐world environment, enhancing the user's experience by blending digital and physical elements. A thorough examination of AR technology in surgical oncology has yet to be performed.MethodsA scoping review of intraoperative AR in surgical oncology was conducted according to the guidelines and recommendations of The Preferred Reporting Items for Systematic Review and Meta‐analyzes Extension for Scoping Reviews (PRISMA‐ScR) framework. All original articles examining the use of intraoperative AR during surgical management of cancer were included. Exclusion criteria included virtual reality applications only, preoperative use only, fluorescence, AR not specific to surgical oncology, and study design (reviews, commentaries, abstracts).ResultsA total of 2735 articles were identified of which 83 were included. Most studies (52) were performed on animals or phantom models, while the remaining included patients. A total of 1112 intraoperative AR surgical cases were performed across the studies. The most common anatomic site was brain (20 articles), followed by liver (16), renal (9), and head and neck (8). AR was most often used for intraoperative navigation or anatomic visualization of tumors or critical structures but was also used to identify osteotomy or craniotomy planes.ConclusionsAR technology has been applied across the field of surgical oncology to aid in localization and resection of tumors.
Accuracy and consistency of publicly available Large Language Models as clinical decision support tools for the management of colon cancer
Authors: Kaiser Kristen N. , Hughes Alexa J. , Yang Anthony D. , Turk Anita A. , Mohanty Sanjay , Gonzalez Andrew A. , Patzer Rachel E. , Bilimoria Karl Y. , Ellis Ryan J. 
Published: August 2024

AbstractBackgroundLarge Language Models (LLM; e.g., ChatGPT) may be used to assist clinicians and form the basis of future clinical decision support (CDS) for colon cancer. The objectives of this study were to (1) evaluate the response accuracy of two LLM‐powered interfaces in identifying guideline‐based care in simulated clinical scenarios and (2) define response variation between and within LLMs.MethodsClinical scenarios with “next steps in management” queries were developed based on National Comprehensive Cancer Network guidelines. Prompts were entered into OpenAI ChatGPT and Microsoft Copilot in independent sessions, yielding four responses per scenario. Responses were compared to clinician‐developed responses and assessed for accuracy, consistency, and verbosity.ResultsAcross 108 responses to 27 prompts, both platforms yielded completely correct responses to 36% of scenarios (n = 39). For ChatGPT, 39% (n = 21) were missing information and 24% (n = 14) contained inaccurate/misleading information. Copilot performed similarly, with 37% (n = 20) having missing information and 28% (n = 15) containing inaccurate/misleading information (p = 0.96). Clinician responses were significantly shorter (34 ± 15.5 words) than both ChatGPT (251 ± 86 words) and Copilot (271 ± 67 words; both p < 0.01).ConclusionsPublicly available LLM applications often provide verbose responses with vague or inaccurate information regarding colon cancer management. Significant optimization is required before use in formal CDS.
Prognostic utility of circulating tumor DNA methylation analysis in stage IV colorectal cancer
Authors: Momose Hirotaka , Sugimoto Kiichi , Irie Takahiro , Nomura Sachio , Ro Hisashi , Ishiyama Shun , Takahashi Makoto , Pisanic Thomas , Sakamoto Kazuhiro 
Published: August 2024

AbstractBackground and ObjectivesOur aim in this study was to investigate the usefulness of circulating tumor (ct) DNA methylation analysis for predicting long‐term outcomes after resection in Stage IV colorectal cancer (CRC).MethodsMethylation analyses were performed on 95 plasma samples from patients with CRC who underwent surgery. The methylation status (relative methylation value: RMV) of CpG within the promoter region of three genes (CHFR, SOX11, and CDO1) was assessed to quantitative methylation‐specific PCR (qMSP) analysis.ResultsIn the patients who had undergone resection of the primary tumor and metastatic organs with curative intent, the CHFR‐RMV high group had significantly worse recurrence‐free survival (RFS) compared with the CHFR‐RMV low group (p = 0.001). Multivariate analysis revealed that CHFR‐RMV was a significant independent prognostic factor (hazard ratio = 2.63 (1.29–5.36); p = 0.008). In the patients who had undergone resection of the primary tumor with metastatic organs with curative intent after neoadjuvant systemic chemotherapy, the SOX11‐RMV high group had significantly worse RFS compared with the SOX11‐RMV low group (p = 0.004).ConclusionsThe current study showed the usefulness of ctDNA methylation analysis for predicting the possibility of curative resection and long‐term outcomes after resection in Stage IV CRC. A future prospective study is needed to obtain more conclusive results.
Oncogenic pathway signatures predict the risk of progression and recurrence in well‐differentiated pancreatic neuroendocrine tumors
Authors: Mederos Michael A. , Court Colin M. , Dipardo Benjamin J. , Pisegna Joseph R. , Dawson David W. , Joe Hines O. , Donahue Timothy R. , Graeber Thomas G. , Girgis Mark D. , Tomlinson James S. 
Published: August 2024

AbstractBackgroundPancreatic neuroendocrine tumors (pNETs) are genomically diverse tumors. The management of newly diagnosed well‐differentiated pNETs is limited by a lack of sensitivity of existing biomarkers for prognostication. Our goal was to investigate the potential utility of genetic markers as a predictor of progression‐free survival (PFS) and recurrence‐free survival (RFS).MethodsWhole‐exome sequencing of resected well‐differentiated, low and intermediate‐grade (G1 and G2) pNETs and normal adjacent tissue from patients who underwent resection from 2005 to 2015 was performed. Genetic alterations were classified using pan‐genomic and oncogenic pathway classifications. Additional samples with genetic and clinicopathologic data available were obtained from the publicly available International Cancer Genome Consortium (ICGC) database and included in the analysis. The prognostic relevance of these genomic signatures on PFS and RFS was analyzed.ResultsThirty‐one patients who underwent resection for pNET were identified. Genomic analysis of mutational, copy number, cytogenetic, and complex phenomena revealed similar patterns to prior studies of pNETs with relatively few somatic gene mutations but numerous instances of copy number changes. Analysis of genomic and clinicopathologic outcomes using the combined data from our study as well as the ICGC pNET cohort (n = 124 patients) revealed that the recurrent pattern of whole chromosome loss (RPCL) and metastatic disease were independently associated with disease progression. When evaluating patients with local disease at the time of resection, RPCL and alterations in the TGFβ oncogenic pathway were independently associated with the risk of recurrence.ConclusionsWell‐differentiated pNETs are genomically diverse tumors. Pathway signatures may be prognostic for predicting disease progression and recurrence.
Assessment of Fetal Ventricular Size and Shape in Women With Intrahepatic Cholestasis of Pregnancy Using Speckle Tracking
Authors: Li Rui , Wang Wan , Qiu Xia , He Ting , Tang Xiaoqin 
Published: August 2024

ObjectiveTo examine the effect of intrahepatic cholestasis of pregnancy (ICP) on fetal heart morphology.MethodsThis case–control study was conducted with 40 women with ICP and 54 pregnant controls. Fetal heart quantification based on speckle tracking technology was used to assess the morphology of the fetal right and left ventricles. Routine ventricular size parameters, global and 24‐segment spherical indices (SIs) were measured and compared between groups.ResultsThe routine fetal cardiac parameters, global and right‐ventricular SIs did not differ between the ICP and control groups. The left‐ventricular apical (segments 16‐24) SIs were lower in the ICP group than in the control group (P < .05), with no significant difference in the other left‐ventricular segments.ConclusionsSubclinical morphological changes were observed in the left ventricular apical segments of the fetal hearts in women with ICP, which indicates an intrauterine environment with high bile acid concentrations. Twenty‐four‐segment SIs can be used to effectively evaluate these changes.
Mindsets and mirrors: How growth mindsets shape anthropomorphism in AI‐enabled technologies
Authors: Chen Qian Qian , Yi Youjae 
Published: August 2024

AbstractAcross multiple studies, we found that people with a growth mindset (whose abilities are believed to be developable) are more likely to see artificial intelligence (AI) devices as human‐like. This effect holds for intelligent personal assistants, where growth‐mindset users attributed more human qualities to these AI helpers. Furthermore, people with a growth mindset were more open to new experiences and felt less threatened by AI, which in turn made them see AI as more human‐like. Interestingly, the more human‐like the AI features became, the less a growth mindset influenced how human‐like people perceived the AI. Our findings highlight the importance of designing AI that can be personalized and adapt to user needs. They also suggest a connection between how human‐like AI appears and how threatening people perceive it. This knowledge can be used to create AI technology that is user‐centered and fosters positive interactions.
Cross‐licensing or not: The optimal choices of competing ICT firms in a duopoly market
Authors: Liu Yifan , Li Minqiang , Feng Haiyang , Feng Nan 
Published: August 2024

AbstractCross‐licensing, which grants each party the right to produce products using the other's patents, is a prevalent strategy for information and communications technology (ICT) firms to improve product quality and respond to intense competition. This study focuses on the cross‐licensing choices of two competing ICT firms that engage in price competition with substitutable products of different quality levels. Using a game‐theoretical model, we find that each firm will have a higher (lower) profit as its competitor's product quality improves in a price‐sensitive (quality‐sensitive) market. Signing a cross‐licensing agreement is profitable for the two firms when their quality improvements are roughly symmetric or when customers are sensitive to the price difference but less sensitive to the quality difference. Furthermore, we examine the quality‐to‐price ratio, which reflects customer perceived value, and find that cross‐licensing may achieve a win–win–win situation for both firms and customers when there is no significant difference in quality improvements between the two firms or when the competition intensity is moderate. The rationale behind these results hinges on the integration of the quality improvement effect and the quality differentiation effect. The results explain the observations of ICT firms' cross‐licensing practices and provide managerial implications for ICT firms and policymakers.
A frequency reconfigurable microstrip antenna with radiation and scattering state switching
Authors: Zhang Lin‐Man , Ding Xiao , Bozzi Maurizio 
Published: August 2024

AbstractThis letter presents the theoretical investigation by a transmission line model and the physical implementation of a novel frequency reconfigurable microstrip antenna with switchable states. More specifically, by using voltage‐controlled PIN diodes, the antenna can be switched between a radiation state and a low‐scattering state. In the radiation state, the operation frequency of the antenna can be electrically modified between 1.5 and 2.3 GHz by acting on the voltage applied to the varactors. In the low‐scattering state, the antenna achieves a significant in‐band radar cross section reduction, with a maximum value of 26.7 dB. The proposed antenna is fabricated and measured. The validity of the proposed strategy is verified by the good agreement between simulated and measurement results. The antenna designed by the proposed approach has great advantages in the radiation performance, aperture size, profile height and design freedom. This work indicates the feasibility of employing the reconfiguration technique to mnipulate the scattering features of an antenna without deteriorating its radiation characteristics.
Effect of berberine combined with metformin on autophagy in polycystic ovary syndrome by regulating AMPK/AKT/mTOR pathway
Authors: Jin Ruiying , Chen Aixue , Ye Yongju , Ren Yuefang , Lu Jiali , Xuan Feilan , Zhou Weimei 
Published: August 2024

AbstractThe pathologic mechanism of polycystic ovary syndrome (PCOS) is related to increased autophagy of granulosa cells. Both berberine and metformin have been shown to improve PCOS, but whether the combination of berberine and metformin can better improve PCOS by inhibiting autophagy remains unclear. PCOS models were constructed by injecting dehydroepiandrosterone into rats, and berberine, metformin or berberine combined with metformin was administered to rats after modeling. Rats' body weight and ovarian weight were measured before and after modeling. Histopathological examination of ovarian tissue and estrous cycle analysis of rats were performed. Insulin resistance, hormone levels, oxidative stress, and lipid metabolism in PCOS rats were assessed. Expression of the AMPK/AKT/mTOR pathway and autophagy‐related proteins was analyzed by Western blot assays. Granulosa cells were isolated from rat ovarian tissue and identified by immunofluorescence staining followed by transmission electron microscopy analysis. Berberine combined with metformin reduced the body weight and ovarian weight of PCOS rats, increased the number of primordial and primary follicles, decreased the number of secondary and atretic follicles, normalized the estrous cycle, and improved insulin resistance, androgen biosynthesis, oxidative stress and lipid metabolism disorders, and increased estrogen production. In addition, berberine combined with metformin reduced the number of autophagosomes in granulosa cells, which may be related to AMPK/AKT/mTOR pathway activation, decreased Beclin1 and LC3II/LC3I levels, and increased p62 expression. Berberine combined with metformin could inhibit autophagy by activating the AMPK/AKT/mTOR pathway in PCOS, indicating that berberine combined with metformin is a potential treatment strategy for PCOS.
Improved visualization of intracranial distal arteries with multiple 2D slice dynamic ASL‐MRA and super‐resolution convolutional neural network
Authors: Suzuki Yuriko , Koktzoglou Ioannis , Li Ziyu , Jezzard Peter , Okell Thomas 
Published: August 2024

AbstractPurposeTo develop a novel framework to improve the visualization of distal arteries in arterial spin labeling (ASL) dynamic MRA.MethodsThe attenuation of ASL blood signal due to the repetitive application of excitation RF pulses was minimized by splitting the acquisition volume into multiple thin 2D (M2D) slices, thereby reducing the exposure of the arterial blood magnetization to RF pulses while it flows within the brain. To improve the degraded vessel visualization in the slice direction due to the limited minimum achievable 2D slice thickness, a super‐resolution (SR) convolutional neural network (CNN) was trained by using 3D time‐of‐flight (TOF)‐MRA images from a large public dataset. And then, we applied domain transfer from 3D TOF‐MRA to M2D ASL‐MRA, while avoiding acquiring a large number of ASL‐MRA data required for CNN training.ResultsCompared to the conventional 3D ASL‐MRA, far more distal arteries were visualized with higher signal intensity by using M2D ASL‐MRA. In general, however, the vessel visualization with a conventional interpolation was prone to be blurry and unclear due to the limited spatial resolution in the slice direction, particularly in small vessels. Application of CNN‐based SR transferred from 3D TOF‐MRA to M2D ASL‐MRA successfully addressed such a limitation and achieved clearer visualization of small vessels than conventional interpolation.ConclusionThis study demonstrated that the proposed framework provides improved visualization of distal arteries in later dynamic phases, which will particularly benefit the application of this approach in patients with cerebrovascular disease who have slow blood flow.