bluuebunny/crossref_metadata_2025 huggingface dataset:
Analytic Solution for the Strongly Nonlinear Multi‐Order Fractional Version of a BVP Occurring in Chemical Reactor Theory
Authors: Erturk Vedat Suat , Alomari A.K. , Kumar Pushpendra , Murillo-Arcila Marina
Published: June 2022

This study is devoted to constructing an approximate analytic solution of the fractional form of a strongly nonlinear boundary value problem with multi‐fractional derivatives that comes in chemical reactor theory. We construct the solution algorithm based on the generalized differential transform technique in four simple steps. The fractional derivative is defined in the sense of Caputo. We also mathematically prove the convergence of the algorithm. The applicability and effectiveness of the given scheme are justified by simulating the equation for given parameter values presented in the system and compared with existing published results in the case of standard derivatives. In addition, residual error computation is used to check the algorithm’s correctness. The results are presented in several tables and figures. The goal of this study is to justify the effects and importance of the proposed fractional derivative on the given nonlinear problem. The generalization of the adopted integer‐order problem into a fractional‐order sense which includes the memory in the system is the main novelty of this research.
miR‐338‐3p Plays a Significant Role in Casticin‐Induced Suppression of Acute Myeloid Leukemia via Targeting PI3K/Akt Pathway
Authors: Yu Kewei , Wang Juan , Hou Junhui , Zhang Lei , Liang Hui
Published: June 2022

Objective. Casticin is generally used in traditional herbal medicine for its anti‐inflammatory and anticarcinogenic pharmacological properties. Also, microRNAs are indispensable oncogenes or cancer suppressors being dysregulated in various diseases. In this study, we aimed to elucidate the mechanisms underlying effects of casticin on the progression of acute myeloid leukemia (AML). Methods. CCK‐8 and flow cytometry were utilized to measure the proliferation and apoptosis of AML cell lines, respectively, after treatment with different concentrations of casticin. The alteration of several microRNA expressions in response to casticin treatment was detected by performing qRT‐PCR, and the activity of PI3K/Akt pathways was evaluated through immunoblotting. Afterwards, the potential target gene of miR‐338‐3p was investigated by dual‐luciferase reporter assay. In order to evaluate the role of miR‐338‐3p in the casticin‐induced cellular phenotype changes, AML cells were transfected with miR‐338‐3p mimics or inhibitor and then subjected to proliferation and apoptosis analysis. Finally, a mouse xenograft model system was employed to investigate the role of casticin in AML progression in vivo. Results. Suppressed cellular proliferation and enhanced apoptosis were observed in HL‐60 and THP‐1 cells after exposure to casticin, accompanied by remarkable upregulation of the miR‐338‐3p expression as well as a decline in the phosphorylation of PI3K and Akt proteins. RUNX2 was identified as a direct target molecular of miR‐338‐3p, which might account for the findings that miR‐338‐3p knockdown enhanced the PI3K/Akt pathway activity, whereas the miR‐338‐3p overexpression inactivated this signaling pathway. In addition, the inhibition of the miR‐338‐3p expression attenuated severe cell apoptosis and suppressions of PI3K/Akt pathway induced by casticin. Furthermore, casticin treatment retarded tumor growth rate in mouse models, whilst elevating miR‐338 expression and repressing the activity of PI3K/Akt pathway in vivo. However, miR‐338‐3p depletion could also abolish the phenotypic alterations caused by casticin treatment. Conclusion. Casticin promotes AML cell apoptosis but inhibits AML cell proliferation in vitro and tumor growth in vivo by upregulating miR‐338‐3p, which targets RUNX2 and thereafter inactivates PI3K‐Akt signaling pathway. Our results provide insights into the mechanisms underlying the action of casticin in the control of AML progression.
Interactive Landscape Design and Application Effect Evaluation of Community Sports Park by Wireless Communication Technology
Authors: Luo Rongrong , Wang Jing
Published: June 2022

To improve the comprehensive quality of urban community sports parks and enhance the modern life quality of residents, first, wireless communication technology is discussed. Second, the construction of community sports parks and the concept of interaction design (IxD) are explored. Finally, a comprehensive assessment of the construction of sports facilities in the park is carried out. In the research method, a field investigation is carried out on the sports park built in Chongqing first, and the research content is designed according to the investigation results. Then, the current sports park construction results are investigated and evaluated by means of a questionnaire survey. The research results show that the five community sports parks in Chongqing still need to be improved in terms of their comprehensive construction. The most obvious in terms of their essential functions is the Yangtianwo community sports park, which has the lowest comprehensive score of 29 (total score is 60). Subsequently, in the comprehensive evaluation of community sports parks, Yangtianwo has the lowest satisfaction evaluation. Finally, in the evaluation of wireless communication technology, residents have the lowest satisfaction with Dashuijing community sports park, and the evaluation score is 20 (total score is 30). It denotes that the comprehensive evaluation of Yangtianwo is the worst among the five community sports parks. The research not only provides a reference for the construction of community sports parks in Chongqing but also contributes to the comprehensive development of community sports parks.
Research on Segmenting E-Commerce Customer through an Improved K-Medoids Clustering Algorithm
Authors: Wu Zengyuan , Jin Lingmin , Zhao Jiali , Jing Lizheng , Chen Liang
Published: June 2022

In view of the shortcomings of traditional clustering algorithms in feature selection and clustering effect, an improved Recency, Frequency, and Money (RFM) model is introduced, and an improved K-medoids algorithm is proposed. Above model and algorithm are employed to segment customers of e-commerce. First, traditional RFM model is improved by adding two features of customer consumption behavior. Second, in order to overcome the defect of setting K value artificially in traditional K-medoids algorithm, the Calinski–Harabasz (CH) index is introduced to determine the optimal number of clustering. Meanwhile, K-medoids algorithm is optimized by changing the selection of centroids to avoid the influence of noise and isolated points. Finally, empirical research is done using a dataset from an e-commerce platform. The results show that our improved K-medoids algorithm can improve the efficiency and accuracy of e-commerce customer segmentation.
Research on Enterprise Strategy Based on Block Chain Security Sharing Mechanism
Authors: Li Ziyan
Published: June 2022

As an emerging electronic information technology, block chain is gradually entering the public’s field of vision. The two major advantages of this emerging technology are security and efficient sharing of information. It is known for its data immutability, traceability, distributed ledger, joint maintenance of each node, and cost reduction. At present, most enterprises still use the traditional data ledger recording mode and the way of sharing the data of the alliance enterprises. Therefore, some enterprises still face problems such as large data errors and artificial tampering with the contents of the ledger, which damages the interests of the company and slows down the company development. In terms of information sharing, enterprises adopt traditional methods to transmit and share data, but also face data distortion and slow data sharing efficiency, which is not conducive to the company’s strategic deployment. Therefore, the use of block chain technology is introduced. Under the security sharing mechanism of the block chain, we use data screening algorithms such as genetic algorithms and sorting calculation algorithms such as entropy algorithms to process the information on the block chain to get the desired part. In the experimental part of this paper, the traditional method and the method using block chain technology in this paper are used to compare the relevant factors affecting the enterprise strategy. Finally, the strategic tendency of the two enterprises is analyzed according to the intuitive graph obtained by calculation, and the method of this paper is highlighted.
Abstract A11: How to adjust comorbidity in mortality outcome in Korean cancer patients using claim-based health care big data
Authors: Lee Sanghee , Cho Hyunsoon
Published: June 2022

Background and Objective: Cancer prognosis is frequently complicated by the presence of comorbid conditions. Prognostic prediction model with less-precise comorbidity risk adjustment would result in biased estimates. This study aimed to illustrate the impact of comorbidity measurements and algorithms for cancer patients using claim-based health care big data.

Method: Data from population-based health claims data, national health insurance database in Korea were used to capture comorbidities in cancer patients. Quan’s ICD-10 was used to identify Charlson and Elixhauser comorbidity. The prevalence of comorbid condition and its impact on mortality were compared according to different claim types (inpatient and outpatient) and ascertainment periods (look-back and window). To improve diagnostic accuracy, Klabunde rule-out algorithm and drug prescriptions were considered, and we assessed how they affect our results. Impact of comorbidity on mortality was assessed by using Cox proportional hazards model adjusting for sex. Prognostic performance to predict short- and long- erm morality was compared using Harrel’s c-statistic.

Result: The most common comorbid conditions were “peptic ulcer disease (PUD),” “chronic pulmonary disease (COPD),” and “mild liver disease (MLD)” in Korean cancer patients. Elixhauser additionally captured 30% of patients with “hypertension” and 3.6% with “depression”; these conditions are not included in Charlson. 90-day versus no window period decreased prevalence of PUD from 27.4 to 19.1 (COPD, 20.2 to 16.3; MLD, 16.4 to 9.5). By shortening the look-back from 3 years to 1 year, prevalence of PUD decreased from 22.9 to 12.9 (COPD, 19.7 to 10.3; MLD, 12.0 to 6.6). In the absence of rule-out algorithm, the prevalence was at most 1.8 times greater in COPD. Within inpatient claim, use of window period had increased HR of MLD (1.9 to 3.7), whereas HR of “myocardial infarction” turned out to be statistically nonsignificant. The C-statistic was 0.71 in 1-year mortality prediction with only inpatient claim. However, better performance was shown with both in- and outpatient claim in predicting 5-year mortality.

Conclusion: Prevalence of comorbidity and its impact on the prognosis prediction vary considerably by comorbidity measurement and algorithm. The higher estimated risk of death in inpatient claim would reflect disease severity. Researchers need to check how patients’ comorbidities are captured by various factors associated with claim-based data, then choose the most adequate algorithm according to patients’ characteristics and study purpose.

Citation Format: Sanghee Lee, Hyunsoon Cho. How to adjust comorbidity in mortality outcome in Korean cancer patients using claim-based health care big data [abstract]. In: Proceedings of the AACR Special Conference on Modernizing Population Sciences in the Digital Age; 2019 Feb 19-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(9 Suppl):Abstract nr A11.
Abstract A30: Comparing mail-based and Internet population health assessment data: Survey implementation protocol
Authors: Fuemmler Bernard F. , Miller Carrie A. , Wheeler David , Dahman Bassam , Gal Tamas , Kim Sunny , Morris Bonnie , Sheng Yaou , Ginder Gordon
Published: June 2022

Purpose of the Study: Traditionally, population-based health assessments have been conducted through resource intensive approaches such as in-person interviews and mail-based surveys. Newer information technologies have been developed for collecting survey data electronically (i.e., e-cohort approaches), which can be leveraged to recruit participants and collect survey data more efficiently than traditional studies. Funded by a National Cancer Institute P30 Supplement, the purpose of this study overall is to assess health practices and improve cancer prevention and control outreach within our cancer center’s catchment area. The purpose of this report is to describe procedures of this ongoing project collecting survey data through traditional and electronic methods.

Methods: This study will administer a survey using two approaches to population health assessment. The first survey cohort will be obtained via a mail-based survey using traditional probability-based sampling methods. A second cohort will be recruited and assessed through technology-enabled methods. This e-cohort will be contacted using an Internet and mobile phone application adapted from the platform developed by Vibrent Health for the National Institutes of Health All of Us study. In addition to the survey responses, data from wearable devices and health service records data will be collected from participants of the e-cohort.

Results: This protocol report will describe implementation procedures of an epidemiologic research study employing both conventional and novel approaches to survey administration. Upon completion of this study, results will provide metrics for comparing the methodologies, such as response rates and respondent characteristics (e.g., socio-demographics, medical history, and lifestyle behaviors) within and between each approach.

Conclusions: Ultimately, results of this study will aid the development of future epidemiologic research studies by providing practical guidance for public health and survey researchers regarding traditional and electronic survey applications, and perhaps, novel insights from the complementary approach of using both survey research methodologies in tandem.

Citation Format: Bernard F. Fuemmler, Carrie A. Miller, David Wheeler, Bassam Dahman, Tamas Gal, Sunny Kim, Bonnie Morris, Yaou Sheng, Gordon Ginder. Comparing mail-based and Internet population health assessment data: Survey implementation protocol [abstract]. In: Proceedings of the AACR Special Conference on Modernizing Population Sciences in the Digital Age; 2019 Feb 19-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(9 Suppl):Abstract nr A30.
Abstract A40: Characterization of quantitative gene-expression dimensions in myeloma tumors
Authors: Waller Rosalie G. , Madsen Michael J. , Gardner John , Sborov Douglas , Camp Nicola J.
Published: June 2022

Background: Clinical management and research of multiple myeloma (MM), a cancer of plasma cells, is limited by tumor heterogeneity. A standard approach to deconstruct tumor heterogeneity is to use hierarchical clustering techniques to determine mutually exclusive categorical subtypes. However, categorical subtypes may fail to capture potential important variations that cross tumor subtypes. An alternate approach is to determine orthogonal, quantitative tumor dimensions where each dimension is an independent tumor characteristic. We hypothesize that using a quantitative framework for tumor heterogeneity in MM will uncover biologically relevant components to tumors and may reflect specific molecular liabilities and therapeutic vulnerabilities. Further, these quantitative characteristics may be more homogeneous genetically and useful for germline gene mapping.

Objective: Identify orthogonal, quantitative dimensions in MM tumors using gene expression.

Data: RNA sequencing on treatment-naïve, CD138 sorted tumor cells from 768 individuals. Publicly available from the MM Research Foundation’s Clinical Outcomes on MM Genetic Profiles Assessment (CoMMpass) Interim Analysis 12a. SALMON transcripts per million adjusted expression estimates on 16,870 protein coding genes.

Analyses: Multistage singular value decomposition (SVD) to 1) select representative genes, and 2) characterize the orthogonal, quantitative tumor dimensions. Stage 1: Genes that contribute most to the initial SVD will be selected as representative genes. Stage 2: SVD on selected genes to identify quantitative gene expression tumor dimensions. Each dimension is a linear combination of the representative genes. Future work will associate the quantitative dimensions with demographic, clinical, and genetic (germline and somatic) characteristics, in addition to response to treatment using penalized linear regression modeling.

Conclusions: We present a new approach for the characterization of MM tumors using a more sophisticated quantitative framework that will facilitate more flexibility for subsequent statistical modeling. Improved measures for tumors have the potential to provide increased power for identification of association between tumor characteristics and genetic (germline or somatic) characteristics with ultimate potential for genetic counseling, insights into mechanism, risk stratification, response to treatment, and new candidates for precision therapeutics.

Citation Format: Rosalie G. Waller, Michael J. Madsen, John Gardner, Douglas Sborov, Nicola J. Camp. Characterization of quantitative gene-expression dimensions in myeloma tumors [abstract]. In: Proceedings of the AACR Special Conference on Modernizing Population Sciences in the Digital Age; 2019 Feb 19-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(9 Suppl):Abstract nr A40.
Abstract IA01: Opportunities in technology and connected health for population science
Authors: Kibbe Warren A.
Published: June 2022

The revolution in consumer-based wearables, smart homes, and ubiquitous computing provides a new foundation for understanding with data the patient experience, and just as importantly understanding the health trajectories of people as they go through their lives outside of the health system. Likewise, coupling these data with patient-reported outcomes data for cancer patients provides new avenues for understanding the experience and outcomes of cancer patients as they go through various therapeutic regimes. Providing flexible, well-described mechanisms for storing and analyzing these many data sources is critical for enabling the use of these data for the generation of novel insights and improving patient surveillance, screening, care and survivorship.

Citation Format: Warren A. Kibbe. Opportunities in technology and connected health for population science [abstract]. In: Proceedings of the AACR Special Conference on Modernizing Population Sciences in the Digital Age; 2019 Feb 19-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(9 Suppl):Abstract nr IA01.
Abstract IA06: Wearable sweat sensor for personalized health monitoring
Authors: Gao Wei
Published: June 2022

The rising research interest in personalized and precision medicine promises to revolutionize traditional medical practices. This presents a tremendous opportunity for developing wearable devices toward predictive analytics and treatment. In this talk, I will introduce fully integrated flexible biosensors for multiplexed in situ perspiration analysis, which can selectively and accurately measure a wide spectrum of sweat analytes (e.g., metabolites, electrolytes, heavy metals, drugs, and other small molecules). This platform allows us to gain real-time insight into the sweat secretion and gland physiology. I will also demonstrate an integrated wearable sweat extraction and sensing system that can be programmed to induce sweat on demand with various secretion profiles. To demonstrate the clinical value of our wearable sweat-sensing platform, human subject studies were performed toward fitness monitoring, physiologic monitoring, disease diagnosis, and drug monitoring. These wearable and flexible devices open the door to a wide range of personalized monitoring and diagnostic applications.

Citation Format: Wei Gao. Wearable sweat sensor for personalized health monitoring [abstract]. In: Proceedings of the AACR Special Conference on Modernizing Population Sciences in the Digital Age; 2019 Feb 19-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(9 Suppl):Abstract nr IA06.
Abstract IA13: Use of administrative and electronic health records to identify cancer recurrences
Authors: Li Christopher I.
Published: June 2022

There are approximately 16 million cancer survivors in the United States, and outcomes of major concern for these survivors are their risks of developing a cancer recurrence, a second primary cancer, and dying of cancer. While cancer registries routinely collect data on second cancers and mortality, they do not ascertain data on recurrences. Gold-standard data on recurrences currently relies on review of medical records, which is costly, time consuming, and does not include events that occur after the review takes place. Extracting data from administrative and electronic health records provides an opportunity to ascertain information on recurrences in real time. We are using two approaches to address this issue that leverage gold-standard data on recurrences we have ascertained through one of our large population-based studies of breast cancer. The first involves the development and implementation of an algorithm for breast cancer recurrences using medical claims data, and the second applies machine learning and artificial intelligence to text in electronic health records. Methods and progress related to these two approaches will be presented.

Citation Format: Christopher I. Li. Use of administrative and electronic health records to identify cancer recurrences [abstract]. In: Proceedings of the AACR Special Conference on Modernizing Population Sciences in the Digital Age; 2019 Feb 19-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(9 Suppl):Abstract nr IA13.
Abstract IA25: Early progress on the All of Us Research Program
Authors: Denny Joshua C.
Published: June 2022

The US Precision Medicine Initiative All of Us Research Program seeks to engage at least 1 million diverse individuals across the US. To achieve this goal, the All of Us Research Program will recruit participants via health care provider organizations (including regional medical centers, federally qualified health centers, and Veterans Affairs Medical Centers) as well as through “direct volunteer” enrollment sites at fast-access convenience provider networks. All of Us will collect EHR records, participant-provided information, biospecimens, mobile and sensor data, and other data sources to provide a robust data sets for individuals. They will also be recontactable, based on user preferences, for possible subsequent studies and trials. Importantly, participants will have access to their information in All of Us. All of Us was launched May 6, 2018 and has now accrued over 95,000 individuals, with more than 160,000 having initially signed up. The ultimate goals for All of Us include enabling research that can lead to accurate diagnoses and redefinition of disease, more rational disease-prevention strategies, better treatment selection, and the discovery of novel therapies.

Citation Format: Joshua C. Denny. Early progress on the All of Us Research Program [abstract]. In: Proceedings of the AACR Special Conference on Modernizing Population Sciences in the Digital Age; 2019 Feb 19-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(9 Suppl):Abstract nr IA25.
The Central Inflammatory Network: A Hypothalamic fMRI Study of Experimental Endotoxemia in Humans
Authors: Färber Natalia , Manuel Jorge , May Marcus , Foadi Nilufar , Beissner Florian
Published: June 2022

Introduction: Inflammation is a mechanism of the immune system that is part of the reaction to pathogens or injury. The central nervous system closely regulates inflammation via neuroendocrine or direct neuroimmune mechanisms, but our current knowledge of the underlying circuitry is limited. Therefore, we aimed to identify hypothalamic centres involved in sensing or modulating inflammation and to study their association with known large-scale brain networks. Methods: Using high-resolution functional magnetic resonance imaging (fMRI), we recorded brain activity in healthy male subjects undergoing experimental inflammation from intravenous endotoxin. Four fMRI runs covered key phases of the developing inflammation: pre-inflammatory baseline, onset of endotoxemia, onset of pro-inflammatory cytokinemia, and peak of pro-inflammatory cytokinemia. Using masked independent component analysis, we identified functionally homogeneous subregions of the hypothalamus, which were further tested for changes in functional connectivity during inflammation and for temporal correlation with tumour necrosis factor and adrenocorticotropic hormone serum levels. We then studied the connection of these inflammation-associated hypothalamic subregions with known large-scale brain networks. Results: Our results show that there are at least 6 hypothalamic subregions associated with inflammation in humans including the paraventricular nucleus, supraoptic nucleus, dorsomedial hypothalamus, bed nucleus of the stria terminalis, lateral hypothalamic area, and supramammillary nucleus. They are functionally embedded in at least 3 different large-scale brain networks, namely a medial frontoparietal network, an occipital-pericentral network, and a midcingulo-insular network. Conclusion: Measuring how the hypothalamus detects or modulates systemic inflammation is a first step to understand central nervous immunomodulation.
Automatic generation of user-defined test algorithm description file for memory BIST implementation
Authors: Jidin Aiman Zakwan , Hussin Razaidi , Fook Lee Weng , Mispan Mohd Syafiq , Ying Loh Wan
Published: June 2022

Memory built-in self-test (BIST) is a widely used technique to allow the self-test and self-checking of the embedded memories on chips after the fabrication process. It can be used by implementing a standard testing algorithm available in the EDA tool library or a user-defined algorithm (UDA). This paper presents the development of software that automatically generates a description file of a UDA to be deployed for memory BIST circuit implementation using Tessent memory BIST software. It comprises the test setup and also the microprogram coding for each instruction to be executed when performing tests on embedded memories. The proposed automation software was tested by using March SR as the input algorithm and the results obtained from the simulations show that the output test patterns generated by the implemented memory BIST match the expected patterns and passed all the tests, which validated the correct functionality of the UDA description file generation. The proposed automation software also fast generation the UDA description file, which was completed in less than 500 ms.
Design and performance analysis of efficient hybrid mode multi-ported memory modules on FPGA platform
Authors: Siddaraju Druva Kumar , Munibyrappa Roopa
Published: June 2022

The multi-ported memories (MPMs) are essential and are part of the parallel computing system for high-performance features. The MPMs are commonly used in most processors and advanced system-on-chip (SoC) for faster computation and high-speed processing. In this manuscript, efficient MPMs are designed using the integration of hierarchical bank division with xor (HBDX) and bank division with remap table (BDRT) approaches. The BDRT approach is configured using remap table with a hash write controlling mechanism to avoid write conflicts. The different multiple read ports are designed using BDX, and HBDX approaches are discussed in detail. The results of 2W4R and 3W4R memory modules are analyzed in detail concerning chip area, operating frequency (MHz), block random access memories (BRAMs), and throughput (Gbps) for different memory depths on virtex-7 field programmable gate array (FPGA). The 2W4R utilizes 2.27% slices, operates at 268 MHz frequency by consuming 64 BRAMs for 16K memory depth. Similarly, the 3W4R uses 2.28% slices, operates at 250 MHz frequency by consuming 96 BRAMs for 16K Memory depth. The proposed designs are compared with existing MPM approaches with better chip utilization (Slices), frequency, and BRAMs on the same FPGA device.
Machine to machine communication enabled internet of things: a review
Authors: Sudarmani Rajagopal , Venusamy Kanagaraj , Sivaraman Sathish , Jayaraman Poongodi , Suriyan Kannadhasan , Alagarsamy Manjunathan
Published: June 2022

Internet of things (IoT) will be the main part in upcoming generation devices that would not simply sense and report, also will have the controlling capability. It may be a connected vehicle, connected devices, robot, a building automation system, a door lock or a thermostat, these connected machines or devices will provide greater impact on our daily lives. Control data and the operating instructions could be protected to ensure control and autonomy for our safety and security, this could be a critical task. Privacy and security are important consideration in designing the system. With the intense growth of devices or devices with facilities such as computing and communication are carried out using a profound technology known as machine to machine (M2M) communication, which is specially designed for cross‐platform integration. In many industries, smart homes, smart cities, smart agriculture, government, connected devices, security, healthcare, education, public safety, and supply chain management. Internet of things (IoT) and machine to machine communication have to be implemented in near future. Also, this paper gives an in depth view about the different M2M techniques with interconnected IoT for truly connected, smart, and sustainable world.
Comparison of breast cancer classification models on Wisconsin dataset
Authors: Kadhim Rania R. , Kamil Mohammed Y.
Published: June 2022

Breast cancer is the leading cause of death for women worldwide. Cancer can be discovered early, lowering the rate of death. Machine learning techniques are a hot field of research, and they have been shown to be helpful in cancer prediction and early detection. The primary purpose of this research is to identify which machine learning algorithms are the most successful in predicting and diagnosing breast cancer, according to five criteria: specificity, sensitivity, precision, accuracy, and F1 score. The project is finished in the Anaconda environment, which uses Python's NumPy and SciPy numerical and scientific libraries as well as matplotlib and Pandas. In this study, the Wisconsin diagnostic breast cancer dataset was used to evaluate eleven machine learning classifiers: decision tree, quadratic discriminant analysis, AdaBoost, Bagging meta estimator, Extra randomized trees, Gaussian process classifier, Ridge, Gaussian nave Bayes, k-Nearest neighbors, multilayer perceptron, and support vector classifier. During performance analysis, extremely randomized trees outperformed all other classifiers with an F1-score of 96.77% after data collection and data analysis.
Pre-current amplifier based transimpedance amplifier for biosensors
Authors: Roogi Jyoti M. , Devi Manju
Published: June 2022

In this paper, we present current amplifier based transimpedance amplifier (TIA) for biosensor applications. Proposed design has low-noise, high Transimpedance gain that can be used for low current measurement applications. The current amplifier based TIA is implemented in order to resolve the fabrication issues related to high value feedback resistor. In this design, the input block to TIA is a low amplitude current amplifier. The designed amplifier is implemented in 90 nm complementary metal-oxide semiconductor (CMOS) technology. The design achieves transimpedance gain of 800 kΩ with a bandwidth of 5 kHz and input referred current noise is of 0.152 pA/√𝐻𝑍 for an input of 41 nA bypassed from current amplifier with input of 200 pA.
A generalization of the concept of differentiability
Authors: Miranda José Carlos Simon de , Fichmann Luiz
Published: June 2022

In this work we unify and generalize the existing definitions of derivatives of functions by presenting a new concept on differentiability.
Exploring Health Care Providers' Experiences of Providing Collaborative Palliative Care for Patients With Advanced Heart Failure At Home: A Qualitative Study
Authors: Graham Cassandra , Schonnop Rebecca , Killackey Tieghan , Kavalieratos Dio , Bush Shirley H. , Steinberg Leah , Mak Susanna , Quinn Kieran , Isenberg Sarina R.
Published: June 2022

Background

The HeartFull Collaborative is a regionally organized model of care which involves specialist palliative care and cardiology health care providers (HCPs) in a collaborative, home‐based palliative care approach for patients with advanced heart failure (AHF). We evaluated HCP perspectives of barriers and facilitators to providing coordinated palliative care for patients with AHF at home.

Methods and Results

We conducted a qualitative study with 17 HCPs (11 palliative care and 6 cardiology) who were involved in the HeartFull Collaborative from April 2013 to March 2020. Individual, semi‐structured interviews were held with each practitioner from November 2019 to March 2020. We used an interpretivist and inductive thematic analysis approach. We identified facilitators at 2 levels: (1) individual HCP level (on‐going professional education to expand competency) and (2) interpersonal level (shared care between specialties, effective communication within the care team). Ongoing barriers were identified at 2 levels: (1) individual HCP level (e.g. apprehension of cardiology practitioners to introduce palliative care) and (2) system level (e.g. lack of availability of personal support worker hours).

Conclusions

Our results suggest that a collaborative shared model of care delivery between palliative care and cardiology improves knowledge exchange, collaboration and communication between specialties, and leads to more comprehensive patient care. Addressing ongoing barriers will help improve care delivery. Findings emphasize the acceptability of the program from a provider perspective, which is encouraging for future implementation. Further research is needed to improve prognostication, assess patient and caregiver perspectives regarding this model of care, and assess the economic feasibility and impact of this model of care.
The Physical Astronomy of Levi ben Gerson
Authors: Goldstein Bernard R.
Published: June 2022

Levi ben Gerson (1288–1344) was a medieval astronomer who responded in an unusual way to the Ptolemaic tradition. He significantly modified Ptolemy’s lunar and planetary theories, in part by appealing to physical reasoning. Moreover, he depended on his own observations, with instruments he invented, rather than on observations he found in literary sources. As a result of his close attention to the variation in apparent planetary sizes, a subject entirely absent from the Almagest, he discovered a new phenomenon of Mars and noticed a serious flaw in Ptolemy’s treatment of the Moon.
A Twentieth-Century Phlogiston: Constructing Error and Differentiating Domains
Authors: Allchin Douglas
Published: June 2022

In the 1950s–60s biochemists searched intensively for a series of high-energy molecules in the cell. Although we now believe that these molecules do not exist, biochemists claimed to have isolated or identified them on at least sixteen occasions. The episode parallels the familiar eighteenth-century case of phlogiston, in illustrating how error is not simply the loss of facts but, instead, must be actively constructed. In addition, the debates surrounding each case demonstrate how revolutionary-scale disagreement is sometimes resolved by differentiating or partitioning empirical domains, rather than by replacement of one theory by another.
Accelerated Neutral Atom Beam (ANAB) Modified Polypropylene for Reducing Bacteria Colonization Without Antibiotics
Authors: Liu Luting , Khoury Joseph , Webster Thomas J.
Published: June 2022

For this first time, this study utilized Accelerated Neutral Atom Beam (ANAB) technology to modify polypropylene to inhibit bacteria colonization in vitro after 24 hours without the use of drugs or antibiotics. Specifically, ANAB was designed and used to increase the surface
energy of polypropylene to be closer to that of two critical proteins (mucin and casein) contained in bodily fluids that if adsorbed to a material surface can decreased bacteria colonization. Materials were characterized using atomic force microscopy demonstrating an expected greater surface
roughness and surface area for the ANAB-treated samples compared to controls. A wide range of gram-positive, gram-negative, and antibiotic resistant bacteria were tested here (including Staph. epidermidis, Staph. aureus, MRSA, multi-drug resistant E. coli, and Pseudomonas
aeruginosa) and demonstrated on average an over a 3-log reduction in bacteria after 24 hours. Further, this study confirmed a greater adsorption of mucin and casein on ANAB-treated polypropylene as the mechanism to decrease bacteria colonization. Lastly, this study utilized an aggressive
cleaning procedure and showed strong durability of the ABAN-treated surfaces. This study is important as it demonstrates a way to potentially decrease polypropylene based implant infections using ANAB modification without using antibiotics.
Photothermolysis Mediated by Gold Nanorods Conjugated with Epidermal Growth Factor Receptor (EGFR) Monoclonal Antibody Induces Apoptosis via the Mitochondrial Apoptosis Pathway in Laryngeal Squamous Cell Cancer
Authors: Zhang Shi-Wen , Wang Hao , Qiu You-Yu , Huang Ren-Chao , Dong Zi-Chen , Zhang Lu , Zhao Liu-Fang , Xu Hong-Yang , Sun Wei-Di
Published: June 2022

Gold nanorods (AuNRs) have unique optical properties and biological affinity and can be used to treat tumors when conjugated with other protein molecules. Our previous studies have shown that EGFR monoclonal antibody (EGFRmAb)-modified AuNRs exert strong antitumor activity in vitro
by inducing apoptosis. In this study, we tested the effects of EGFRmAb-modified AuNRs on laryngeal squamous cell cancer (LSCC) in vitro and in vivo. The in vitro results showed that EGFRmAb-modified AuNRs inhibited NP-69, BEAS-2B and Hep-2 cell growth and induced mitochondria-dependent
apoptosis. The mitochondrial membrane potential was reduced, leading to the release of cytochrome C (Cyt C) and consequent activation of the intrinsic mitochondrial apoptosis pathway. Moreover, we observed that the occurrence of mitochondrial apoptosis is related to the destruction of the
lysosome-mitochondria axis. To verify the effects in vivo, we also established a laryngeal tumor model in nude mice by subcutaneous transplantation. In model mice treated with EGFRmAb-modified AuNRs and irradiated with an NIR laser, tumor cell apoptosis and tumor growth were inhibited.
These results suggest that EGFRmAb-modified AuNRs induced apoptosis through the intrinsic mitochondrial apoptotic pathway and are a potential candidate for cancer therapy.
Double Nutri (Liposomal Encapsulation) Enhances Bioavailability of Vitamin C and Extends Its Half-Life in Plasma
Authors: Wen Chiung-Jung , Chiang Chi-Fu , Lee Chung-Sheng , Lin Yung-Hsiang , Tsai Jaw-Shiun
Published: June 2022

Vitamin C is an important antioxidant in the human body that plays a role in many body functions. Liposomal encapsulation is a technology commonly used in food processing and medicine. This study determines whether Double Nutri (liposomal encapsulation) increases the absorption rate
for vitamin C supplementation. Subjects enrolled in this study took vitamin C without liposome; then, 14 d washout was given with liposomal process A vitamin C. After 14 d washout, the subjects took liposomal process B vitamin C (Double Nutri) was given. After taking the test sample, the vitamin
C concentration in venous blood was measured from the baseline (0 h), 0.5, 1, 2, 3, 4, and 8 h. Eleven healthy subjects were recruited for three tests. The vitamin C concentration for liposomal process B vitamin C (Double Nutri) group is higher (7.26±3.52, p<0.01) than that
for the liposomal process A vitamin C group (6.41±3.80, p<0.05) and for vitamin C without liposome (2.21±4.07). This shows that Double Nutri has better bioavailability and can last up in the body to 8 hours. In addition, this study shows that Double Nutri increases
the half-life of vitamin C in plasma and has higher bioavailability.
Two-Photon Nanoprobe for NIR-II Imaging of Tumour and Biosafety Evaluation
Authors: Zha Yiqian , Cui Xinyuan , Liu Yanlei , Fan Shanshan , Lu Yi , Cui Shengsheng , Cui Daxiang
Published: June 2022

How to develop near-infrared second window (NIR-II, 1000–1700 nm) fluorescent nanoprobes with a uniform size, strong fluorescence signal and good biosafety owns great clinical requirement. Herein we reported that a two photon fluorescent nanoprobe was developed via encapsulating
NIR-II-fluorescent molecules into DSPE-PEG, which was effectively endocytosized by cancer cells, and achieved strong NIR-II fluorescence imaging in cancer cells and cancer cell-beard mice models. Prepared NIR-II-fluorescent nanoprobe exhibited rapid metabolism and excellent biocompatibility.
In conclusion, the prepared two photon nanoprobe owns good biosafety, and clinical translational prospect in NIR-II fluorescent imaging of tumour in vivo in near future.
X-Linked Inhibitor of Apoptosis Protein (XIAP)-Loaded Magnetic Mesoporous Silica Nanoparticles Incorporated with miR-233 to Improve Radio Sensitization of Cervical Cancer Cells and Promote Apoptosis
Authors: Li Wen , Li Fang , Zhang Yang , Ren Hongtao , Bao Xing , Wang Zhongwei , Wang Yali
Published: June 2022

This study investigated the impact of magnetic mesoporous silica nanoparticles (MMSN)-encapsulated X-linked inhibitor of apoptosis protein (XIAP) and miR-233 on tumor microenvironment in cervical cancer, to provide targeted treatment and strategy, to improve radio sensitization of cancer
cells. Cervical cancer cells were treated with normal saline (control group), XIAP-loaded metallic mesoporous silica nanoparticles (MMSNs), and miR-233-targeted material (XIAP group, XIAP+miR-233 group). Proliferation, apoptosis and colony forming ability of cancer cells were assessed by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl
tetrazolium bromide (MTT) method, flow cytometry and colony formation experiments. In vivo experiments were established to observe the impact of XIAP-loaded MMSNs and miR-233 on tumor growth. Administration of XIAP-loaded MMSNs suppressed tumor growth of cervical cancer, and presence
of miR-233 targeted material further decreased tumor volume, increasing radio sensitization of cancer cells. In vitro experiments confirmed that, combined treatment of XIAP and miR-233 suppressed cancer cell proliferation and invasion when inducing apoptosis. XIAP MMSNs characterized
by large unit surface area, high dispersion and adhesion, and prolonged circulation time, improving drug delivery and treatment selectivity of chemotherapeutic drugs. This study suggests that XIAP MMSNs with miR-233 material suppress cervical cancer cell progression and tumor growth when augmenting
radiosensitization of cancer cells, providing evidence for targeted therapy for the disease.
Poly d,l-(lactic-co-glycolic) Acid PEGylated Isoliquiritigenin Alleviates Traumatic Brain Injury by Reversing Cyclooxygenase 2 Level
Authors: Li Zhengyang , Xu Chao , Wang Yan
Published: June 2022

As a severe neurological disease of trauma, traumatic brain injury (TBI) leads to other disorders, such as depression, dementia and epilepsy. This study investigated whether poly d,l-(lactic-co-glycolic) acid (PLGA) PEGylated isoliquiritigenin could alleviate TBI. One hundred and eighty-three patients with clinical brain trauma were divided into two groups with or without intracranial injury in magnetic resonance imaging. The clinical results showed that serum cyclooxygenase 2 (COX-2) levels were obviously increased in the TBI patients compared to the patients with head trauma only or healthy individuals. Intracranial injection of isoliquiritigenin in TBI rats reversed TBI induced increase of COX-2 level, significantly reduced water content and contusion volume. Our findings suggest that PLGA PEG nanoparticles loaded with isoliquiritigenin can achieve the same effects as intracranial administration of isoliquiritigenin in reducing serum COX-2 level.
A Nucleus-Targeted Nanosystem Integrated with Photodynamic Therapy and Chemotherapy
Authors: Xin Jing , Wang Sijia , Wang Jing , Fu Lei , Zhang Zhenxi , Yao Cuiping
Published: June 2022

Minimally invasive photodynamic therapy, destroying lesions with a light-activated photosensitizer, has been increasingly performed since it is highly efficiency, safe, synergistically compatible, repeatable, and minimally-invasive, with few adverse reactions. However, the most present
photosensitizer or nanodrug delivery system containing a photosensitizer can target tumor cells but rarely cell nuclei. In this regard, the nucleus-targeting drug delivery system has been developed aiming impair tumor cells in an efficient and direct manner. In this study, the cationic liposome
(Clip) drug delivery system integrated with low dose nucleus-targeting chemotherapeutic drug Doxorubicin (DOX) and photosensitizer AlPcS4 (Clip-AlPcS4@DOX) was synthesized. Among them, Clip was used to efficiently load drugs into cells almost at the same time, low dose DOX was used to open
the channel for the materials to enter the nucleus on the premise of ensuring low cytotoxicity and then introduced photosensitizer into the nucleus, AlPcS4 photosensitizer was used to damage directly and efficiently through the photodynamic therapy (PDT) effect after entering the nucleus.
In summary, a nucleus-targeting nanodrug delivery system (Clip-AlPcS4@DOX) was designed and synthesized and could be induced cell apoptosis more quickly and efficiently. Therefore, it could be a promising nucleus-targeting nanosized reagent integrating the PDT and chemotherapy for gastric
therapy.
Dual pH and Temperature-Sensitive Nanogels Loaded with Eugenol for Regulating Central Nervous System
Authors: Li Yan , Wang Jing-Wen , Dong Qiu-Shi , Zhao Bao-Chang , Zhang Ji-Mei , Li Yan-Ling , Lu Zhi-Guo , Zhang Xin
Published: June 2022

Fragrances have many biological activities such as anti-anxiety, anti-depression, and improving cognitive memory. However, most fragrances are so volatile that the useful lifespan of the fragrances is very short and excessive fragrance concentration makes us uncomfortable. In this study,
dual pH and temperature-sensitive nanogels named EG@CPMONGs were prepared to encapsulate eugenol. This nano-fragrance was then applied to silk. In the following, the effects of EG@CPMO-NGs on the regulation of central nervous systems were evaluated. Open-field tests showed that EG@CPMONGs
had an obvious effect on stress relief. Elevated plus-maze tests proved the significant effect of EG@CPMO-NGs on anti-anxiety. Morris water maze tests demonstrated the positive impact of nano-fragrance on spatial learning and memory. Therefore, these dual pH and temperature-sensitive nanogels
loaded with eugenol had significant and positive effects on the central nervous system.