bluuebunny/crossref_metadata_2025 huggingface dataset:
Bridging the Gap: Assessing the Integration of Artificial Intelligence in Healthcare for Improved Efficiency and Doctor Adaptability.
Authors: Alrabie Mohammad
Published: November 2023

The premise behind implementing artificial intelligence in healthcare comes from the initiative that aims towards improving the healthcare standards, services, and accessibilities in a time and cost-efficient manner. The conceptual framework is based on the null hypothesis which states that there is no relationship between implementing artificial intelligence in healthcare and doctor’s redundancy. Having used the 2-tailed One-Sample T-Test to test that hypothesis on IBM SPSS, in order to successfully reject the hypothesis, and present an alternatively more accurate hypothesis that is more accurately representative. Additionally, DICE framework has also been presented in order to calculate the success/failure likelihoods of implementing artificial intelligence in healthcare. We conclude that artificial intelligence significantly impacts cost reduction in the long term, as well as only ever displacing behind-the-curve doctors who are unwilling to broaden their knowledge and develop their skills. Finally, we conclude that people’s resistance to change significantly affects the efficient and effective implementation of artificial intelligence in healthcare.
RETRACTED: The Well-Being of Migrant Hispanic American Indians in New York City: From the Rural South to the Industrial North
Authors: DelaCruz Juan J. , Kakolyris Andreas , Suen Tin Shan
Published: November 2023

The authors have requested that this preprint be removed from Research Square.
Advancing Named Entity Recognition with Syntax-Aware Attention Mechanisms
Authors: Jason Tomasz , Neumann Muly , Adam Ammar
Published: November 2023

Named entity recognition (NER) stands as a pivotal task in natural language processing (NLP). Recent advancements have considerably enhanced its effectiveness. However, a gap remains in these systems' ability to fully leverage the recursive dynamics of linguistic structures. This study introduces a novel approach, intertwining the recognition of entities with a deeper understanding of linguistic syntax and tree-like structures. Utilizing a Tree-LSTM that operates under the guidance of dependency trees, we capture the intricate syntactic relationships between words. This process is further refined through the dual application of relative and global attention mechanisms. The relative attention zone is on critical words in the context of each evaluated word, whereas global attention identifies keywords throughout the entire sentence. By projecting these attention-modulated features into a tagging space, our model employs a conditional random field classifier to determine entity labels. We discover that our model adeptly highlights verbs that reveal the types of entities, influenced by their syntactic roles within sentences. Our model sets a new benchmark for performance on two prominent datasets, substantiating our approach.
Generalized Analysis of Methods for Solving Systems of Nonlinear Equations With Point and Interval Coefficients
Authors: Ibragimov Alimzhan
Published: November 2023

In this article we consider interval methods for solvingpoint (with real coefficients) and interval (with intervalcoefficients on the right side) systems of nonlinear algebraicequations. These methods are used to demonstrably solve pointsystems of nonlinear equations, as well as to find outer estimatesof the so-called united set of solutions to systems of nonlinearequations with interval coefficients. First, we will analyze theinterval methods of Newton and Krawczyk to show the advantages anddisadvantages of these and similar iterative methods. Next, wepropose a vertex method for outer estimation of solution sets ofinterval nonlinear systems, which also uses these iterativemethods. Here we limited ourselves only partially to intervalsystems. The proposed vertex method is more efficient where theconvergence of the iterative process is not guaranteed for theinterval iterative methods of Newton, Krawczyk or Hansen-Sengupta.The conducted numerical experiments show that the proposed vertexmethod gives more accurate estimates than the direct applicationof interval iterative methods.
Polynomial stability of Timoshenko system with strong damping and strong distributed delay terms
Authors: Laribi Imene , Krelifa Ali , Zitouni Salah , Ouchenane Djamel
Published: November 2023

In this research work, we study the linear Timoshenko problem with a strong damping and a strong distributed delay when it acts on the first equation. We first prove the existence and uniqueness solution of the system by using the semi-group theory. Then, we illustrate the lack of exponential stability even in the condition of equal wave propagation is satisfied. Furthermore, we show the polynomial decay of solution with rate t−½. From this perspective, we demonstrate the optimality of the rate.
Rapid entomological assessment in eight high malaria endemic regencies in Papua Province revealed the presence of indoor and outdoor malaria transmissions
Authors: Rozi Ismail E , Permana Dendi H , Syahrani Lepa , Asih Puji BS , Zubaidah Siti , Risandi Rifqi , Wangsamuda Suradi , Dewayanti Farahana K , Demetouw Michael R. Demetouw , Mabui Silas , Robaha Marthen M F , Sumiwi Maria E , Bangs Michael J , Lobo Neil F , Hawley William A , Syafruddin Din
Published: November 2023

Background
Malaria in eastern Indonesia remains high despite significant reduction and elimination in other parts of the country. A rapid entomological assessment was conducted in eight high malaria endemic regencies of Papua Province, Indonesia, to expedite malaria elimination efforts in this region. This study aims to characterize specific, actionable endpoints toward understanding where and when malaria transmission is happening, where interventions may function best, and identify gaps in protection that result in continued transmission.
Methods
The entomological assessment included identifying potential vectors through human landing catch (HLC), indoor morning and night resting collections, identification of larval sites through surveillance of water bodies, and vector incrimination toward understanding exposure to malaria transmission.
Results
Human landing catches (HLCs) and larval collections identified 10 Anopheles species, namely Anopheles koliensis, An. punctulatus, An. farauti, An. hinesorum, An. longirostris, An. peditaeniatus, An. tesselatus, An. vagus, An. subpictus and An. kochi. The most common and abundant species found overall were An. koliensis and An. punctulatus, while An. farauti was found in large numbers in the coastal areas of Mimika and Sarmi Regencies. Vector incrimination on Anopheles collected from HLCs and night indoor resting demonstrated that An. koliensis and An. punctulatus carried Plasmodium in Keerom, Jayapura, and Sarmi Regencies. Analysis of HLCs for the most common species revealed the An. koliensis, An. punctulatus and An. farauti, bite indoors and outdoors at equal rates. Larval surveillance demonstrated that most water bodies in and surrounding residential areas contained Anopheles larvae.
Conclusions
This study demonstrated indoor and outdoor exposure to mosquito bites and gaps in protection, enabling exposure to infectious bites in all regencies. This may explain why current malaria control efforts focusing on indoor protection have failed to reduce malaria incidence in the region substantially. Optimization of insecticide-treated bed nets (ITNs), as well as installment of mosquito screens in houses, may further reduce indoor transmission. For outdoor transmission, the use of community-centric approaches to reduce or eliminate larval sources within and surrounding the village through the guidance of locally stationed entomologists, along with Social and Behavior Change Communication (SBCC) mediated health education towards the local adoption of mosquito protection tools during outdoor activities, may reduce malaria transmission.
In Silico, Evolutionary Analysis and Designing guide RNA constructs for the Precise Modification of the Thermosensitive Genic Male Sterile (OsTMS5) Gene using the CRISPR/Cas9 System in Rice (Oryza sativaL.): A Comprehensive Study and Construct Development for Crop Improvement
Authors: Behera Laxmipreeya , Samal Kailash Ch. , Parmeswaran C , Agrawal Pawan Kumar , Achary V. Mohan Murali , Dash Manasi , Dwibedi Sanat Kumar , Bhol Raj Kumari , Kherawat Bhagwat Singh , Chung Sang-Min , Kesawat Mahipal Singh , Samantaray Sanghamitra
Published: November 2023

The CRISPR/Cas9 system represents a state-of-the-art technology for precise genome editing in plants. In this study, we performed in silico and evolutionary analyses, as well as designed guide RNA constructs for the precise modification of the thermosensitive genic male sterile (OsTMS5) gene using the CRISPR/Cas9 system in rice (Oryza sativa L.). The OsTMS5 promoter harbors a diverse array of cis-elements, which are linked to light responsiveness, hormonal regulation, and stress-related signalling. Further, expression pattern of OsTMS5 revealed that OsTMS5 exhibited responsiveness to hormones and were activated across diverse tissues and developmental stages in rice. In addition, we meticulously designed guide RNAs (gRNAs) with a length of 20 base pairs. This design process was conducted using the CRISPR-P v2.0 online platform. The target of these gRNAs was the rice thermosensitive genic male sterile gene OsTMS5. The selection of the top two gRNAs was made after conducting a thorough evaluation, which included assessing factors such as on-score value, minimum off-target score, GC content, potential off-target sites, and genomic location. In this study, two types of entry vectors were utilized, and the pMDC99 vector served as the destination vector for plant transformation. Following the annealing and ligation of the gRNAs through LR recombination, the resulting plasmid was named as "pMDC99-eSPCas9+OsU6-OsTMS5-target1-gRNA+OsU6-OsTMS5-target2-gRNA." Subsequently, this plasmid obtained from the third LR recombination was introduced into Agrobacterium EHA105 for the purpose of conducting rice transformation. Therefore, these constructs have the potential for use not only in molecular genetic analyses and molecular breeding in rice but also in a wide range of other crop species.
Stiffness estimation of Rubber plantation timber by using the Smart Thumper Application
Authors: Phonetip Khamtan , Faircloth Adam , Soukphaxay Khonethong , Syvongsouk Khonexay
Published: November 2023

The objective of this study was to investigate the results of estimating modulus of elasticity of rubber plantation timber based on the SMART THUMPER™ application and the universal testing machine. The results showed that there was a no significant difference between the responses of the MOE between two testing methods at the P-value of 2.06 (P > 0.05). The average MOE for Universal testing machine is 10048 ± 2610 MPa while the Smart Thumper App is 10155 ± 2415 MPa. It is suggested to conduct further experiments i.e. Group of specimens with defects and a group of clear specimens.
Low-dose Esketamine promotes brain protection via the ERK/Nrf2 pathway in vascular dementia rats
Authors: Shi jinlin , Guo minxuan , Yu Xinran , Zhang Huan , Li xuze , Gan Jianhui
Published: November 2023

Backdround
: By establishing the rat model of vascular dementia and observing the effects of low-dose Esketamine on cognitive function and related mechanisms in rats with vascular dementia, providing a new idea for clinical drug treatment of Vascular dementia (VD).
Methods
100 rats were randomly divided into five groups: sham operation group, vascular dementia group, Esketamine group, Esketamine + PD98059 group, and Esketamine + DMSO group. Except for the sham operation group, the other groups were established vascular dementia rat models by intraperitoneal injection of sodium nitroprusside to reduce blood pressure and bilateral common carotid artery occlusion/reperfusion. The Morris water maze test assessed rats' learning and memory ability. ELISA detected changes in SOD and IL-1β levels in rat serum; the levels of ERK, Nrf2, and p-ERK in the hippocampus were detected by western blotting; and the pathological changes in the hippocampus of rats in each group were detected by HE staining.
Results
The results showed that the escape latency of VD rats was significantly higher than that of Group Sham and Group VK. In contrast, the times of crossing the platform and the staying time distance of the target quadrant of VD rats were significantly lower than that of Group Sham and Group VK. Compared with the Group VD, the expression of ERK, p-ERK and Nrf2 in the hippocampus of Group VK increased, which improved brain injury, increased the level of serum antioxidant SOD and decreased the level of inflammatory factor IL-1β.
Conclusion
Low-dose ketamine can improve cognitive impairment and reduce the damage to the hippocampus in VD rats. Its protective effect is related to increasing BDNF levels, activating the ERK/Nrf2 pathway, increasing antioxidant substances in the body and inhibiting inflammatory factors.
Identification and validation of pyroptosis patterns in AML via comprehensive bioinformatics analysis
Authors: Zhang Huifang , Deng Zeyu , Huang Zineng , Wang Peilong , Cheng Zhao , Peng Hongling
Published: November 2023

Background
Pyroptosis, a new type of programmed cell death, was associated with inflammation, immunity, and the development of tumor. However, the prognostic roles of pyroptosis-related genes and the correlation between pyroptosis and immunity in acute myeloid leukemia (AML) remains to be unrevealed.
Methods
This study analyzed the expression level and prognostic roles of 40 pyroptosis-related genes in AML patients. Clinical subtypes of AML were identified by nonnegative matrix factorization method (NMF) according to the expression level of pyroptosis-related genes. We also comprehensively explore the enrichment score (ES) of immunologic gene sets in different subtypes of AML by gene set variation analysis (GSVA). Least absolute shrinkage and selection operator method (LASSO) were used to seek prognostic immunologic gene sets and protein-protein interaction network was constructed to identify hub gens.
Results
32 pyroptosis-related genes were differently expressed between AML and the healthy, and 9 pyroptosis-related genes were significantly associated with the prognosis of AML patients. We identified two clinically relevant subtypes of AML and patients with subtype 1 had a better overall survival. The ES of immunologic gene sets were significantly different in two subtypes of AML and four were associated with the prognosis of AML patients. Notably, MF enrichment and Reactome pathway indicated that four prognostic immunologic gene sets were mainly associated with terms of cell adhesion molecule binding, ubiquitin protein ligase binding, cytokine activity in MF, and interferon signaling, class I MHC mediated antigen processing & presentation. Finally, 9 hub genes were found from the four prognostic immunologic gene sets.
Conclusions
We demonstrated the important role of pyroptosis in AML and identified two AML subtypes. This provides additional useful data for the development of clinical therapy for AML.
Wave-particle duality in the asymmetrical double-slit interference experiments
Authors: Van Thuan Vo , Duc Vinh Vu , Thanh Hung Nguyen , Quang Thieu Dang
Published: November 2023

We perform spectral analysis based on a suitable theoretical correlation between V-wave visibility and D-particle distinguishability following the complemen-tarity principle to verify wave-particle duality in the asymmetrical double-slit experiments. The selective interference spectra obtained in the experiments ensure the single-photon approximation in the Fraunhofer far-field condition. The results show that the theoretical interpretation following wave-particle complementarity may not be consistent with the experimental data, especially at the first main minima of the optical diffraction distributions. A dilemma would arise when one tries to revise the theoretical explanations for preserving the complementarity principle.
Sample Size Determination For Multidimensional Parameters And The A-Optimal Subsampling In A Big Data Linear Regression Model
Authors: Zhang Sheng , Tan Fei , Peng Hanxiang
Published: November 2023

To fast approximate the least squares estimator (LSE) efficiently in a Big Data linear regression by a subsampling LSE, numerous optimal sampling distributions are derived based on the criterion of minimizing the sum of the component variances of the subsampling LSE. We discuss truncation of the distributions, and construct the Scoring Algorithm with far less running time for implementing the subsampling LSE than for the full-sample LSE. The subsampling LSE is proved to be almost surely asymptotically normal for an arbitrary sampling distribution under suitable conditions. Motivated by subsampling and data-splitting in machine learning, sample size determination for multidimensional parameters is investigated. We conduct a comprehensive evaluation of our proposed approach through various numerical studies and compare it with the uniform sampling. Our results in both simulated and real data indicate that our approach substantially outperforms the uniform and the Algorithm significantly reduces the computational time required for implementing the full-sample LSE.
Modeling of Amplified Spontaneous Emission Noise for Quantum Communication Applications
Authors: Udvary Eszter
Published: November 2023

There is an increasing need for quantum communication applications, including true random numbers and quantum key distribution. The Amplified Spontaneous Emission (ASE) is a quantum physics process, which can play a significant role in both cases. A physical model for detecting and acquiring the ASE noise is developed. The photon probability is calculated, and the relationship with system parameters is presented. Experimental results quantitatively validate the physical model; the simulation results all significantly fit the corresponding experimental data well.
Modular geodesics and wedge domains in non-compactly causal symmetric spaces
Authors: Morinelli Vincenzo , Neeb Karl-Hermann , Gestur´Olafsson Gestur´OlafssonGestur´
Published: November 2023

We continue our investigation of the interplay between causal structures on symmetric spaces and geometric aspects of Algebraic Quantum Field Theory. We adopt the perspective that the geometric implementation of the modular group is given by the flow generated by an Euler element of the Lie algebra (an element defining a 3-grading). Since any Euler element of a semisimple Lie algebra specifies a canonical non-compactly causal symmetric space M = G/H, we turn in this paper to the geometry of this flow. Our main results concern the positivity region W of the flow (the corresponding wedge region): If G has trivial center, then W is connected, it coincides with the so-called observer domain, specified by a trajectory of the modular flow which at the same time is a causal geodesic. It can also be characterized in terms of a geometric KMS condition, and it has a natural structure of an equivariant fiber bundle over a Riemannian symmetric space that exhibits it as a real form of the crown domain of G/K. Among the tools that we need for these results are two observations of independent interest: a polar decomposition of the positivity domain and a convexity theorem for G-translates of open H-orbits in the minimal flag manifold specified by the 3-grading.
MSC 2010: Primary 22E45; Secondary 81R05, 81T05
Three South African silcrete sources can be identified regardless of heat treatment using solution ICP-MS and LA-ICP-MS
Authors: Hirniak Jayde N. , Murray John K. , Zipkin Andrew M.
Published: November 2023

Silcrete is widely used for stone tool manufacture throughout various parts of the world and is sometimes heat-treated to improve flaking quality. Properly sourcing this raw material can provide insight into exchange networks and mobility patterns of early human populations, however, we only have a minor understanding of how heat treatment impacts the geochemistry of silcrete and how this varies between and within sources. This is particularly important in South Africa where heat-treated silcrete artifacts are common during the later Middle Stone Age. Here, we examine how heat treatment affects the geochemical composition of silcrete from three sources near the Pinnacle Point site complex in South Africa. We selected five unheated and five experimentally heat-treated silcrete samples from each source (n = 30) for solution ICP-MS analysis. We also test whether laser ablation ICP-MS is a viable method for sourcing silcrete since sample preparation for solution analyses can be challenging (i.e., use of harsh chemicals, issues digesting the sample). Our results suggest that all sources can be distinguished regardless of the treatment state and for both analytical approaches. The results of this study will help inform future provenience studies of silcrete artifacts to better understand how early humans living near Pinnacle Point interacted with the landscape.
Revisiting Named Entity Recognition in Food Computing: Enhancing Performance and Robustness
Authors: Akujuobi Uchenna , Liu Shuhong , Besold Tarek R.
Published: November 2023

In the ever-evolving domain of food computing, Named Entity Recognition (NER) presents transformative potential that extends far beyond mere word tagging in recipes. Its implications encompass intelligent recipe recommendations, health analysis, and personalization. Nevertheless, existing NER models in food computing encounter challenges stemming from variations in recipe input standards, limited annotations, and dataset quality. This article addresses the specific problem of ingredient NER and introduces two innovative models: SINERA, an efficient and robust model, and SINERAS, a semi-supervised variant that leverages a Gaussian Mixture Model (GMM) to learn from untagged ingredient list entries.
To mitigate issues associated with data quality and availability in food computing, we introduce the SINERA dataset, a diverse and comprehensive repository of ingredient lines. Additionally, we identify and tackle a pervasive challenge---spurious correlations between entity positions and predictions. To address this, we propose a set of data augmentation rules tailored for food NER. Extensive evaluations conducted on the SINERA dataset and a revised TASTEset dataset underscore the performance of our models. They outperform several state-of-the-art benchmarks and rival the BERT model while maintaining smaller parameter sizes and reduced training times.
Multiparametric magnetic resonance imaging in preoperative assessment of follicular thyroid neoplasm
Authors: Song Bin , Zheng Tingting , Wang Hao , Tang Lang , Xie Xiaoli , Fu Qingyin , Liu Weiyan , Wu Pu-Yeh , Zeng Mengsu
Published: November 2023

Objectives
To examine multiparametric magnetic resonance imaging for differentiating follicular thyroid neoplasm (FTN) from non-FTN and malignant FTN (MFTN) from benign FTN (BFTN).
Methods
Seven hundred two thyroid nodules, postoperatively confirmed by pathology, were retrospectively investigated and divided into two cohorts: training (n = 482) and validation (n = 220). The 133 FTNs were split into two groups: BFTN (n = 116) and MFTN (n = 17). Univariate and multivariate logistic regression analysis were used to identify independent predictors of FTN and MFTN. An nomogram for FTN and a risk score system for MFTN were constructed based on the results of multivariable analysis. Nomogram’ performance was evaluated based on discrimination, calibration, and clinical utility. The diagnostic performance of the risk score system for MFTN was compared with the performance of the Thyroid Imaging Reporting and Data System (TIRADS).
Results
The nomogram, which incorporated independent predictors, demonstrated good discrimination and calibration for differentiating FTN and non-FTN both in the training cohort (AUC = 0.947, Hosmer-Lemeshow P = 0.698) and the validation cohort (AUC = 0.927, Hosmer-Lemeshow P = 0.088). Tumor size, restricted diffusion, and cystic degeneration were risk factors for differentiating MFTN from BFTN. The AUC of the risk score system for MFTN prediction was 0.902 (95% CI 0.811–0.993), and the sensitivity, specificity, accuracy, and positive and negative predictive values of the risk score system at the optimal cutoff value were 76.5%, 94%, 91.8%, 65%, and 96.5%, respectively, which was better performance than five TIRADS.
Conclusions
The models based on MRI features had favorable diagnostic performance for preoperative prediction of FTN and MFTN. These models may aid in reducing unnecessary invasive biopsy or surgery.
Flexural behavior of reinforced concrete beams with steel and GFRP reinforcement
Authors: Kinjawadekar Trupti Amit , Patil Shantharam , Nayak Gopinatha , Kumar Saish
Published: November 2023

The use of alternative reinforcement in concrete structures in the form of glass fiber-reinforced polymer (GFRP) is a favorable option to the traditional reinforcement of steel. These bars possess unique features, including resistance to corrosion, an impressive tensile strength by weight ratio, and electromagnetic transparency, making them particularly appealing to the construction sector and structural engineers. The brittleness of GFRP bars significantly lowers the concrete beams’ ductility. Moreover, the significant deformations observed during the post-cracking phase is the effect of lower elastic modulus of these bars. The aim of this research study is to gain a deeper insight into the behaviour of structural members in flexure that are reinforced with GFRP bars. The failure modes were observed. The outcomes of load‒deflection performance are discussed. The fracture patterns observed in beams subjected to two point loading conditions have been documented for beams made of reinforced concrete that use both steel and GFRP as reinforcement. A finite element nonlinear analysis is performed using ABAQUS, to explore the exact response of specimens observed in experimental studies. A comparative study was performed between the experimental and numerical results.
Evaluation of the effect of Drimia Maritima and curcumin extracts in changes in the expression of Bax, Bcl-2, and P53 genes in lung cancer non-small cell
Authors: Sepehr Negin Noori , Soleimanifar Fatemeh , Dehaghi Nafiseh Khosravi , Mahboudi Hossein , zare Fereshteh , Tavasoli Afsaneh , Sameni Fatemeh , Kashani Hamed Haddad
Published: November 2023

Introduction:
Lung cancer is one of the most common malignancies in the world, with a very high mortality rate. Surgery and chemotherapy are among the first approaches to cancer treatment, which are associated with severe side effects, so more research has been done in the field of using medicinal plants with less toxicity. In the present study, we investigated the simultaneous effect of Drimia maritima plant extract (proscillaridin A), a cardiac glycoside, and turmeric plant extract (curcumin) in inducing apoptosis of non-small cell lung cancer cells.
Methods and Materials
Treatment of cancerous and non-cancerous cells with plant extracts was done by the MTT method, and the RNA of the samples was extracted using an extraction kit, and then cDNAs were synthesized using a special kit. Specific primers were designed for the sequence of P53, Bax, Bcl-2, and Gapdh genes, and the expression levels of the desired genes were checked and analyzed using the real-time PCR method. Cell cycle changes and apoptosis rates were also checked using the flow cytometry method.
Results
The results of investigating the simultaneous effect of proscillaridin and curcumin extracts on non-small cell lung cancer cells showed that we did not witness the synergistic power of the extracts together with each other, but we saw an increase in the survival of cancerous and non-cancerous cells, which, of course, in the case of non-cancerous cells were more impressive, and the two extracts seem to have neutralized each other's effect. The results indicate that the effect of each extract alone on cell lines (especially Calu-3 compared to A549) was greater.
Conclusions
Therefore, according to the research, it is possible that the use of extracts along with a suitable chemotherapy drug has a more significant effect on the life of normal or non-cancerous cells, which reduces the side effects of the drug and can increase the penetration rate of the chemotherapy drug, so in this field, more studies are needed.
Visualization Literacy
Authors: Pohl Margit
Published: November 2023

Visualisierung von abstrakten Daten (z. B. Daten zu COVID-19) spielt in den Massenmedien eine immer grössere Rolle. Allerdings sind komplexe Visualisierungen für viele Personen nicht leicht zu interpretieren. Die Fähigkeit, solche Darstellungen zu verstehen, wird als Visualization Literacy bezeichnet. Diese neue Forschungsrichtung beruht auf Untersuchungen in anderen Bereichen, wie etwa Visual Literacy, Graph Comprehension oder Studien zu Cognitive Biases oder Onboarding für Visualisierungen. Im folgenden Artikel werden diese Forschungsbereiche dargestellt und ihre Bedeutung für Visualization Literacy diskutiert. Es gibt zwei wesentliche Aspekte bei Visualization Literacy, einerseits die Frage, wie man Wissen über Visualisierungen am besten vermitteln kann, andererseits auch, wie Visualisierungen gestaltet sein müssen, dass sie von Menschen ohne Vorwissen über dieses Gebiet angemessen verstanden werden können. Visualization Literacy ist eng mit Data Literacy verwandt, da grosse, komplexe Datensätze durch Visualisierungen oft leichter interpretiert werden können. Zusammenhänge in den Daten oder Extremwerte können wesentlich problemloser erkannt werden. Daher ist es wichtig, dass Kenntnisse über Visualisierungen im schulischen Unterricht vermittelt werden, damit Betrachtende keine fehlerhaften Schlüsse aus Visualisierungen ziehen.
Regulatory Science: The Maturation of an Evolving Scientific Discipline
Authors: Moghissi A. Alan , Steen Tomoko , Calderone Richard , Auffret Jean Pierre , Jaeger Lisa , Xu Liwei Sarah , Wixson McBride Carolyn , McBride Dennis
Published: November 2023

Regulatory science encompasses the participation of a large array of scientific disciplines involved in the regulatory process. Although each discipline addresses different phenomenology and exploits different methodologies, the common scientific core is the same:  objective pursuit of verifiable and useful knowledge.  This paper updates the definition and scope of the practice of regulatory science, starting with a concise historical overview. It then examines the different phases of regulatory science applications: initial, exploratory, and standard operating. The paper also reviews the definitions of regulatory science used by various agencies and provides abbreviated scientific definitions. The paper summarizes Best Available Regulatory Science (BARS) and Metrics for Evaluation of Scientific Claims (MERSC), along with key elements and tools of regulatory science: peer review; regulatory science ethics, including the so-called Jeffersonian principle; mathematical models; cost benefit analysis; and stakeholder participation. The paper concludes with a brief description of these key tools and elements, highlighting their importance in the field of regulatory science.
Critical success factors of the financial performance of commercial private banks: A study in a developing nation
Authors: M. Anwarul Islam K. , Bin Amin Mohammad , Alamgir Hossain Sk , Islam Roushanara , Popp Jozsef
Published: November 2023

This study’s objective is to examine the impact of employee innovativeness, readiness to change, employee creativity, and learning capability on the financial performance of private banks in Bangladesh. The study involved 334 bank employees from three prominent private banks in Bangladesh. Those banks were selected with better ratings by the central bank and have several branches across the country. First, branch managers were contacted about this study and collected employee emails from each branch information desk. Then, email invitations were sent to each employee of the selected bank branches. This study involved branch managers, senior officers, officers, and junior bank executives. Past studies also considered senior and junior bank officers as they directly contribute to a bank’s performance. The study utilized a methodical questionnaire to assess the three independent variables: employee innovativeness, readiness to change, and learning capability. The dependent variable in this study was financial performance, which was assessed through key financial indicators such as profitability and sales growth over three years. SPSS was utilized to conduct hypothesis testing by considering 95% confidence interval. Correlation results show that all three independent variables were significantly correlated with the bank’s financial performance. The study’s regression results suggest that bank employees’ readiness to change (β value = 0.393) significantly impacts the bank’s financial performance, followed by employee innovativeness (β value = 0.338). On the other hand, employees’ learning capability (β value = 0.202) has the least significant impact on financial performance. Moreover, three independent variables explain 42.9% variance in bank financial performance.
Protein Species of Origin Determination By NMR Relaxometry
Authors: Webster Gregory K.
Published: November 2023

Aims:

The aim of this project was to develop a QC friendly and efficient method of protein
species of origin identification to replace more costly mass spectrometric based methods currently
being used for this testing.

Background:

NMR relaxation measurements with proteins in aqueous solutions exploit the fast
chemical exchange between water and exposed NH and OH protons of amino acid side chains in
the folded protein structure unique to each biologic drug. Implementation of this technique has led
to routine testing for authentication and forensics of biopharmaceuticals, determination of moisture
content in lyophilized protein formulations and aggregation of proteins in solution. For small
molecule applications, TD-NMR can detect if solvents are received neat or tainted with moisture,
impurities, or denaturants.

Objective:

The objective of this study was to evaluate the ability of NMR Relaxation measurements
to differentiate between sources of Albumin proteins as a rapid QC test. Evaluation of differences
in molecular mobility between components in a solution as reflected in the longitudinal
(T1) and transverse (T2) relaxation times of protons demonstrate that NMR relaxation techniques
can distinguish between different albumin sources of origin.

Methods:

Representative albumin proteins from differing sources of origin were studied. Using
bovine serum albumin (BSA) as the target species of origin, NMR relaxation techniques as well as
chemometric modeling were used to evaluate the use of this technique for protein source of origin
identification.

Results:

NMR Relaxation using benchtop instrumentation showed that the bovine albumin species
of origin can be distinguished from porcine, chicken egg white and sheep sources of origin. Goat
albumin selectivity remained questionable and BSA cannot be distinguished from human or rabbit
sources of origin within the representative variability.

:

T2 transverse relaxation results were significantly more discriminating for protein source identification
than the T1 longitudinal relaxation result by itself. The T1 longitudinal relaxation result did
not contribute significantly to this investigation. However, fusing the T1 data with the T2 transverse
relaxation results and using larger data sets merit further evaluation in the hope of achieving
additional selectivity.

Conclusion:

While additional lots are needed for more definitive results, this preliminary evaluation
of using NMR Relaxation demonstrated the capability for the source of origin species discrimination
and identification using benchtop NMR instrumentation.
The Relationship Between Sarcopenia And Proteinuria, What Do We
Know?
Authors: Gungor Ozkan , Ulu Sena , Inci Ayca , Topal Kenan , Kalantar-Zadeh Kamyar
Published: November 2023

Sarcopenia is one of the most common geriatric syndromes in the elderly. It is defined
as a decrease in muscle mass and function, and it can lead to physical disability, falls, poor
quality of life, impaired immune system, and death. It is known that, the frequency of sarcopenia
increases in the kidney patient population compared to healthy individuals. Although it is known
that kidney disease can lead to sarcopenia; our knowledge of whether sarcopenia causes kidney
disease is limited. Prior studies have suggested that protein energy wasting may be a risk of de
novo CKD. Proteinuria is an important manifestation of kidney disease and there is a relationship
between sarcopenia and proteinuria in diabetes, geriatric population, kidney transplant, and
nephrotic syndrome. Does proteinuria cause sarcopenia or vice versa? Are they both the results
of common mechanisms? This issue is not clearly known. In this review, we examined the relationship
between sarcopenia and proteinuria in the light of other studies.
Machine Learning Algorithms for Health Care Data Analytics Handling Imbalanced Datasets
Authors: Sajana T. , Rama Rao K.V.S.N.
Published: November 2023

In Machine Learning, classification is considered a supervised learning
technique to predict class samples based on labeled data. Classification techniques have
been applied to various domains such as intrusion detection, credit card fraud detection,
etc. However, classification techniques on all these domains have been applied to
balanced datasets. Balanced datasets are those which contain equal proportion of
majority and minority examples. However, in real-time, obtaining balanced datasets is
difficult because majority of the datasets tend to be imbalanced. Developing a model
for classifying imbalanced datasets is a challenge, particularly in the medical domain.
Accurate identification of a disease-affected patient within time is critical as any
misclassification leads to severe consequences. However the imbalanced nature of most
of the real-time datasets presents a challenge for most of the conventional machine
learning algorithms. For the past few years, researchers have developed models using
Conventional machine learning algorithms (linear and nonlinear) are stating
unsatisfactory performance in classifying imbalanced datasets. To address this problem
of skewed datasets several statistics techniques & robust machine Learning techniques
have been developed by the researchers. The discussion on handling imbalanced
datasets in the healthcare domain using machine learning techniques is a primary focus
of this chapter.
Smart Water Bottle with Smart Technology
Authors: Shanthi Dumpala
Published: November 2023

Working people have forgotten the importance of water intake. Smart Water
Bottle will blow an alarm if it is being used by homemakers or people at home. This
device can also be configured to their smartphones, which would send a message or
alarm to their smartphones, making the user remember the intake of water by keeping
some time interval. If configured to their mobiles, it would send a record of the amount
of water taken by the user. The latest emerging technology like IoT, Android and many
others will definitely be useful to the user.
Electromagnetic Fields and Radiation
Authors: Kamal Hossain Md. , Haider Mohammad R.
Published: November 2023

Electromagnetic radiation is a form of energy that comprises electric and
magnetic waves. It propagates in free space and contains neither mass nor charge but
carries energy as a photon packet. The energy associated with electromagnetic
radiation is directly proportional to the frequency from extremely low frequencies to
visible light and above. The highly low-frequency electromagnetic field is generated by
the electrical devices and power systems, while the radio and microwave signal radiates
by the mobile tower, microwave oven, heater, radar, etc. The extremely high-frequency
radiation emitted from medical devices, radioactive decay, nuclear weapons, etc.
Therefore, environmental exposure to electromagnetic radiation increases gradually
due to increasing electricity demands, advanced technologies, mobile communications,
etc. However, exposure to electromagnetic radiation has an adverse biological effect
depending on the current intensity, strength of the magnetic field, and duration of
exposure. This book chapter introduces electrostatics and magneto-statics, the
formation of electromagnetic fields and waves, frequency spectrum, source of
radiations, and their exposure limits.
Ultraviolet Radiation: Benefits, Harms, and Protection
Authors: Robinson Jabari , Begum Rahima , Maqbool Muhammad
Published: November 2023

Ultraviolet (UV) radiation is used in several devices for various applications.
These applications include medical, research and industrial uses. Some of these
applications are fundamental tools for our modern era. These applications range from
visualization of DNA to eradication of dangerous diseases and microorganisms in the
air and water. While UV radiation is not energetic enough to be considered ionizing
radiation and is treated as less hazardous, it is the form of non-ionizing radiation that is
closest to the ionization region. UV radiation does have the ability to break chemical
bonds and can pose significant hazards to humans. These hazards may include
discomfort, temporary loss of sight or impairment, permanent loss of sight, or cancer.
To mitigate the hazards from UV exposures, the hazards must be assessed, and
administrative controls and engineering controls should be utilized. Federal regulations
and guidance regarding UV hazard assessment and mitigation for the end-users of UV
devices are not currently robust, but the American Conference of Governmental
Industrial Hygienists (ACGIH) has provided some useful information for assessment.
Infrared Radiation: Benefits, Hazards, and Protections
Authors: Maqbool Muhammad
Published: November 2023

 Infrared radiation falls on the electromagnetic spectrum between
microwaves and red visible light with a wavelength of ~750 nm-1 mm. Infrared
radiation is emitted from materials as heat and can be used for medical, industrial, and
military purposes. Infrared can be used to reduce swelling, increase tissue repair in
sports injuries and help treat patients with cardiovascular disease. The industrial sector
uses infrared tomography to image inside buildings, electrical equipment, and fuel
processing plants. There are few known harms when it comes to infrared radiation
effects. Infrared radiation can cause skin damage, eye damage, and greenhouse effects.
Not much research is known on the appropriate dosage or the body's response to doses
of infrared radiation. There are a few preventative ways to reduce the harm caused by
infrared radiation. People can follow the three cardinal rules of radiation and the
ALARA principle. They can also wear personal protection equipment when working or
around infrared radiation sources. People can also learn and try to help the planet by
reducing their carbon footprint to stop global warming from getting worse.
Nonionizing Radiation Risk Management and Safety
Authors: Nadeem Abbasi Ahmed , Jangda Abdul Qadir , Yousuf Asad
Published: November 2023

The applications of Nonionizing radiation (NIR) has increased in recent
years. Safety authorities and the public were concerned about the use of devices that
emit NIR. Questions about acute or chronic effects have subsequently become more
important. According to many studies and experiments carried out, EMF does not
affect the functioning of a living organism, provided that those certain established
acceptable standards are not exceeded. It comprises lower quantum energies and,
therefore, has different biological effects and interactions with matter. It displays its
unique personality, although it shares the same wave characteristics as ionizing
radiation. We can describe this in terms of its frequency, energy, and wavelength. It is
longer, less frequent, and lazier compared to ‘IR’, but it can still inflict a good deal of
damage. This Chapter will cover the effect of NIR interaction with matter, risk
management, and safety associated with its application.
Architecture in the Novel 'Austerlitz' by W. G. Sebald
Authors: Erdoğan Nevnihal , Gündoğdu Nihan Sümeyye
Published: November 2023

Austerlitz is the final novel of W. G. Sebald, one of the leading writers of
German literature, published before his death. In this novel, Sebald deals with the life
of the protagonist, Jacques Austerlitz, a Jewish scientist born in Wertach in 1934, in
exile after being separated from his homeland. Austerlitz is an architectural historian.
After choosing the academic path in his career, he learns about his past and begins to
search for his real family following the death of his adoptive parents. Austerlitz was
kidnapped from Czechoslovakia during the Nazi era of Germany and brought to Britain
as a refugee and adopted by a family in Wales. The work begins with the scene where
Austerlitz, while drawing at the Antwerp Railway Station in 1967, encountered the
novel's unnamed narrator and began to talk. Later on, Austerlitz continues to meet with
this anonymous narrator in various cities during his travels in Europe. While
researching his family, Austerlitz also provides the reader with an analysis of the
architectural structures in the city he is in. These cities are not randomly chosen places.
While Sebald searches for his authentic self, it is not accidental that the architecture
integrated into the story consists of structures from the post-war era. In this work, we
analyze the information the author presents about the architecture of the buildings to
the reader; European architecture is conveyed not through a single style but by
considering different structures built in different periods. While making these analyses,
establishing a connection with the European Jews during the Holocaust (the genocide
of European Jews) was tried. While examining the story of Austerlitz, European
architecture is treated in an integrated way into the storyline. The buildings and cities
discussed in the novel, Austerlitz, are examined considering their periods and
architectural styles. Of the buildings examined in parallel with the flow of the novel,
some have undergone changes today, as well as those that we do not have information
about. In the book, in which various buildings from different eras are discussed, the
architectural analysis has been handled under three different headings in line with the
flow of the story, and it is seen that the architectural styles and ideologies of the periods
are effective in the buildings. While searching for his authentic self throughout the
work, the protagonist, Austerlitz, has shed light on the dusty shelves of architectural
history.