bluuebunny/crossref_metadata_2025 huggingface dataset:
Divide and focus: generating novel focal polarization modalities by symmetry-based phase tailoring in one dimension
Authors: Bauer Thomas , Golub Ilya
Published: April 2023

Symmetry-based tailoring of photonic systems recently heralded the advent of novel concepts, such as photonic topological insulators and bound states in the continuum. In optical microscopy systems, similar tailoring was shown to result in tighter focusing, spawning the field of phase- and polarization-tailored light. Here, we show that even in the fundamental case of 1D focusing using a cylindrical lens, symmetry-based phase tailoring of the input field can result in novel features. Dividing the beam or utilizing a π phase shift for half the input light along the non-invariant focusing direction, these features include a transverse dark focal line and a longitudinally polarized on-axis sheet. While the former can be used in dark-field light-sheet microscopy, the latter, similar to the case of a radially polarized beam focused by a spherical lens, results in a z polarized sheet with reduced lateral size when compared with the thickness of a transversely polarized sheet produced by focusing a non-tailored beam. Moreover, the switching between these two modalities is achieved by a direct 90° rotation of the incoming linear polarization. We interpret these findings in terms of the requirement to adapt the symmetry of the incoming polarization state to match the symmetry of the focusing element. The proposed scheme may find application in microscopy, probing anisotropic media, laser machining, particle manipulation, and novel sensor concepts.
Independent transmitted and reflected colors enabled by Fano resonant optical coatings
Authors: Teng Xinyue , Song Maowen , Ren Yongze , Lin Peicheng , Zhang Yanzeng , Xu Ting
Published: April 2023

Conventionally, optical coatings transmit and reflect the complementary colors due to the limitations of the resonant modes in multilayered structures. Here, we experimentally demonstrate a type of semi-transparent optical coating that can produce the same color in transmission and reflection based on Fano resonance. The results verify that when the metallic spacer is extremely thin, almost the same reflectance and transmittance spectra can be simultaneously achieved with the efficiency about 40%. Furthermore, we comprehensively explore the change of the colors by varying the thickness of the metal and the refractive index of the dielectric cap. Benefiting from the flexible tuning of the coupled resonator, a broad palette of colors and chromatic information display are presented. Our semi-transparent optical coatings exhibit viewing angle tolerance up to 40°, which may lead to novel display and optical anti-counterfeiting techniques.
Polarization control investigation based on integrated graphene-assisted microring cavity
Authors: fan huibo , Chen Yulu , Pang Hanyue
Published: April 2023

In this paper, we propose and analyze an integrated polarization-selective structure of graphene-assisted silica microring cavity to realize polarization control due to different optical distributions of whispering-gallery modes (WGMs) in microring and polarization-dependent absorption of graphene. A graphene stripe is partially side-coupled with silica microring to distinctly influence the propagations of TE mode and TM mode in the microring. Especially, the appearance of plasmonic mode in the groove between graphene and microring enhances light-matter interaction between graphene and TM polarized mode, while without that for the case of TE mode propagation. By applying voltage on graphene stripe, along with its electro-optic modulation effect, the difference in the polarization extinction ratio of 20.6 dB is obtained between the cases of polarized TM mode and TE mode in the microring. Furthermore, second silica microring is added in this hybrid structure to couple the original microring, along with graphene stripe embedded in between, finally realizing electromagnetically induced transparency (EIT) lineshape because of the plasmonic coupling in both cavities with the condition of TM mode propagation, while without any lineshape change for the case of TE mode propagation. This compact hybrid structure offers a good integrated photonic platform to realize excellent polarization-selective device.
Recurrent predictive coding models for associative memory employing covariance learning
Authors: Tang Mufeng , Salvatori Tommaso , Millidge Beren , Song Yuhang , Lukasiewicz Thomas , Bogacz Rafal
Published: April 2023

The computational principles adopted by the hippocampus in associative memory (AM) tasks have been one of the most studied topics in computational and theoretical neuroscience. Recent theories suggested that AM and the predictive activities of the hippocampus could be described within a unitary account, and that predictive coding underlies the computations supporting AM in the hippocampus. Following this theory, a computational model based on classical hierarchical predictive networks was proposed and was shown to perform well in various AM tasks. However, this fully hierarchical model did not incorporate recurrent connections, an architectural component of the CA3 region of the hippocampus that is crucial for AM. This makes the structure of the model inconsistent with the known connectivity of CA3 and classical recurrent models such as Hopfield Networks, which learn the covariance of inputs through their recurrent connections to perform AM. Earlier PC models that learn the covariance information of inputs explicitly via recurrent connections seem to be a solution to these issues. Here, we show that although these models can perform AM, they do it in an implausible and numerically unstable way. Instead, we propose alternatives to these earlier covariance-learning predictive coding networks, which learn the covariance information implicitly and plausibly, and can use dendritic structures to encode prediction errors. We show analytically that our proposed models are perfectly equivalent to the earlier predictive coding model learning covariance explicitly, and encounter no numerical issues when performing AM tasks in practice. We further show that our models can be combined with hierarchical predictive coding networks to model the hippocampo-neocortical interactions. Our models provide a biologically plausible approach to modelling the hippocampal network, pointing to a potential computational mechanism during hippocampal memory formation and recall, which employs both predictive coding and covariance learning based on the recurrent network structure of the hippocampus.
Structural connectivity-based predictors of cognitive impairment in stroke patients attributable to aging
Authors: Bučková Barbora Rehák , Kala David , Kořenek Jakub , Matušková Veronika , Kumpošt Vojtěch , Svobodová Lenka , Otáhal Jakub , Škoch Antonín , Šulc Vlastimil , Olšerová Anna , Vyhnálek Martin , Janský Petr , Tomek Aleš , Marusič Petr , Jiruška Přemysl , Hlinka Jaroslav
Published: April 2023

Despite the rising global burden of stroke and its socio-economic implications, the neuroimaging predictors of subsequent cognitive impairment are still poorly understood. We address this issue by studying the relationship of white matter integrity assessed within ten days after stroke and patients’ cognitive status one year after the attack. Using diffusion-weighted imaging, we apply the Tract-Based Spatial Statistics analysis and construct individual structural connectivity matrices by employing deterministic tractography. We further quantify the graph-theoretical properties of individual networks. The Tract-Based Spatial Statistic did identify lower fractional anisotropy as a predictor of cognitive status, although this effect was mostly attributable to the age-related white matter integrity decline. We further observed the effect of age propagating into other levels of analysis. Specifically, in the structural connectivity approach we identified pairs of regions significantly correlated with clinical scales, namely memory, attention, and visuospatial functions. However, none of them persisted after the age correction. Finally, the graph-theoretical measures appeared to be more robust towards the effect of age, but still were not sensitive enough to capture a relationship with clinical scales. In conclusion, the effect of age is a dominant confounder especially in older cohorts, and unless appropriately addressed, may falsely drive the results of the predictive modelling.
Use of machine learning to identify risk factors for coronary artery disease
Authors: Huang Alexander A. , Huang Samuel Y.
Published: April 2023

Coronary artery disease (CAD) is the leading cause of death in both developed and developing nations. The objective of this study was to identify risk factors for coronary artery disease through machine-learning and assess this methodology. A retrospective, cross-sectional cohort study using the publicly available National Health and Nutrition Examination Survey (NHANES) was conducted in patients who completed the demographic, dietary, exercise, and mental health questionnaire and had laboratory and physical exam data. Univariate logistic models, with CAD as the outcome, were used to identify covariates that were associated with CAD. Covariates that had a p<0.0001 on univariate analysis were included within the final machine-learning model. The machine learning model XGBoost was used due to its prevalence within the literature as well as its increased predictive accuracy in healthcare prediction. Model covariates were ranked according to the Cover statistic to identify risk factors for CAD. Shapely Additive Explanations (SHAP) explanations were utilized to visualize the relationship between these potential risk factors and CAD. Of the 7,929 patients that met the inclusion criteria in this study, 4,055 (51%) were female, 2,874 (49%) were male. The mean age was 49.2 (SD = 18.4), with 2,885 (36%) White patients, 2,144 (27%) Black patients, 1,639 (21%) Hispanic patients, and 1,261 (16%) patients of other race. A total of 338 (4.5%) of patients had coronary artery disease. These were fitted into the XGBoost model and an AUROC = 0.89, Sensitivity = 0.85, Specificity = 0.87 were observed (Fig 1). The top four highest ranked features by cover, a measure of the percentage contribution of the covariate to the overall model prediction, were age (Cover = 21.1%), Platelet count (Cover = 5.1%), family history of heart disease (Cover = 4.8%), and Total Cholesterol (Cover = 4.1%). Machine learning models can effectively predict coronary artery disease using demographic, laboratory, physical exam, and lifestyle covariates and identify key risk factors.
“Acute kidney injury in critically ill patients with COVID–19: The AKICOV multicenter study in Catalonia”
Authors: Sánchez Arsenio De La Vega , Pérez Ana Navas , Pérez-Carrasco Marcos , Sonet María Torrens , Buendia Yolanda Diaz , Ballujera Patricia Ortiz , López Miguel Rodríguez , Riera Joan Sabater , Olmo-Isasmendi Aitor , Torra Ester Vendrell , García-Pumarino María Álvarez , Villamayor Mercedes Ibarz , Catalán Ibars Rosa María , Zelaya Iban Oliva , Chica Javier Pardos , Anglès Conxita Rovira , Tomasa-Irriguible Teresa M. , Serra Anna Baró , Casanova Edward J. , De Molina Francisco J. González ,   on behalf of The AKICOV Group
Published: April 2023

This study describes the incidence, evolution and prognosis of acute kidney injury (AKI) in critical COVID-19 during the first pandemic wave. We performed a prospective, observational, multicenter study of confirmed COVID-19 patients admitted to 19 intensive care units (ICUs) in Catalonia (Spain). Data regarding demographics, comorbidities, drug and medical treatment, physiological and laboratory results, AKI development, need for renal replacement therapy (RRT) and clinical outcomes were collected. Descriptive statistics and logistic regression analysis for AKI development and mortality were used. A total of 1,642 patients were enrolled (mean age 63 (15.95) years, 67.5% male). Mechanical ventilation (MV) was required for 80.8% and 64.4% of these patients, who were in prone position, while 67.7% received vasopressors. AKI at ICU admission was 28.4% and increased to 40.1% during ICU stay. A total of 172 (10.9%) patients required RRT, which represents 27.8% of the patients who developed AKI. AKI was more frequent in severe acute respiratory distress syndrome (ARDS) ARDS patients (68% vs 53.6%, p<0.001) and in MV patients (91.9% vs 77.7%, p<0.001), who required the prone position more frequently (74.8 vs 61%, p<0.001) and developed more infections. ICU and hospital mortality were increased in AKI patients (48.2% vs 17.7% and 51.1% vs 19%, p <0.001) respectively). AKI was an independent factor associated with mortality (IC 1.587–3.190). Mortality was higher in AKI patients who required RRT (55.8% vs 48.2%, p <0.04). Conclusions There is a high incidence of AKI in critically ill patients with COVID-19 disease and it is associated with higher mortality, increased organ failure, nosocomial infections and prolonged ICU stay.
DagSim: Combining DAG-based model structure with unconstrained data types and relations for flexible, transparent, and modularized data simulation
Authors: Al Hajj Ghadi S. , Pensar Johan , Sandve Geir K.
Published: April 2023

Data simulation is fundamental for machine learning and causal inference, as it allows exploration of scenarios and assessment of methods in settings with full control of ground truth. Directed acyclic graphs (DAGs) are well established for encoding the dependence structure over a collection of variables in both inference and simulation settings. However, while modern machine learning is applied to data of an increasingly complex nature, DAG-based simulation frameworks are still confined to settings with relatively simple variable types and functional forms. We here present DagSim, a Python-based framework for DAG-based data simulation without any constraints on variable types or functional relations. A succinct YAML format for defining the simulation model structure promotes transparency, while separate user-provided functions for generating each variable based on its parents ensure simulation code modularization. We illustrate the capabilities of DagSim through use cases where metadata variables control shapes in an image and patterns in bio-sequences. DagSim is available as a Python package at PyPI. Source code and documentation are available at: https://github.com/uio-bmi/dagsim
Development and validation of the nomogram to predict the risk of hospital drug shortages: A prediction model
Authors: Dong Jie , Gao Yang , Liu Yi , Yang Xiuling
Published: April 2023

Introduction

Reasons for drug shortages are multi-factorial, and patients are greatly injured. So we needed to reduce the frequency and risk of drug shortages in hospitals. At present, the risk of drug shortages in medical institutions rarely used prediction models. To this end, we attempted to proactively predict the risk of drug shortages in hospital drug procurement to make further decisions or implement interventions.

Objectives

The aim of this study is to establish a nomogram to show the risk of drug shortages.

Methods

We collated data obtained using the centralized procurement platform of Hebei Province and defined independent and dependent variables to be included in the model. The data were divided into a training set and a validation set according to 7:3. Univariate and multivariate logistic regression were used to determine independent risk factors, and discrimination (using the receiver operating characteristic curve), calibration (Hosmer-Lemeshow test), and decision curve analysis were validated.

Results

As a result, volume-based procurement, therapeutic class, dosage form, distribution firm, take orders, order date, and unit price were regarded as independent risk factors for drug shortages. In the training (AUC = 0.707) and validation (AUC = 0.688) sets, the nomogram exhibited a sufficient level of discrimination.

Conclusions

The model can predict the risk of drug shortages in the hospital drug purchase process. The application of this model will help optimize the management of drug shortages in hospitals.
Projektmenedzsment-érettség vizsgálata közszférában tevékenykedő szolgáltatásfókuszú vállalatok példája alapján
Authors: Blaskovics Bálint , Szabó Lajos , Kádár Zsombor , Molnár Máté , Tóth Nikolett , Tóth János
Published: April 2023

A projektmenedzsment szempontjából érett szervezetek nagyobb mértékben képesek biztosítani a projektek sikeres teljesítését, így képesek lehetnek komoly versenyelőnyre szert tenni versenytársaikkal szemben. Ebből fakadóan számos olyan modell létezik a szakirodalomban, amely hatékonyan és hatásosan tudja értékelni a projektmenedzsment-érettség mértékét. Azonban a közszférára szakosodott modellek száma kevesebb, különösen, ha olyan szervezeteket veszünk figyelembe, amelyek jelentős mennyiségű szolgáltatási vagy termékfejlesztési projektet indítanak, azaz fontos számukra a megfelelő technológiamenedzsment. A szerzők megállapítják, hogy Cooke-Davies és Arzymanow modellje a projektmenedzsment támogatásának mértékével, valamint a projektvezető képzésével kiegészítve jól illeszkedik ilyen szervezetekre is, és így megfelelő módon képes értékelni azok projektmenedzsment-érettségét is. A szerzők továbbá olyan fejlesztési javaslatokat is megfogalmaznak a modellek alapján, amelyek javíthatják az adott szervezet projektmenedzsment gyakorlatát.
Egy virtuális közösségi pénzen alapuló fenntartható sharing economy modell kialakításának lépései
Authors: Szemerédi Eszter , Tatay Tibor
Published: April 2023

A 2008-as gazdasági válságot követően megnőtt az érdeklődés az olyan üzleti modellek iránt, amelyek a szereplők közötti együttműködés alternatív formáit biztosítják. Ezzel egyidejűleg a környezetszennyezéssel kapcsolatos aggodalmak is felerősödtek és a környezeti szempontok gazdasági tevékenységekbe történő integrálása egyre fontosabbá vált. Erre válaszul jelentek meg többek között a közösségi gazdasági és a peer-to-peer fizetési rendszerek. A COVID-19 világjárvány hatásai a korábbi gazdasági válságokhoz képest is új kihívások elé állítják a gazdasági szereplőket, ami az alternatív útkeresési folyamatok ismételt előtérbe kerüléséhez vezethet. Az előttünk álló ökológiai problémák miatt azonban a járványt követően a korábbi gazdasági mechanizmusok helyreállításán túl a célnak egy az ökológiai lábnyom csökkentését elősegítő gazdasági modell kiépítésének kell lennie. Ebben a tanulmányban a szerzők célja egy újszerű megoldási koncepció elemeinek bemutatása, amely azon a hipotézisen alapul, hogy az intelligens szerződések révén létrehozott digitális közösségi valuta elősegítheti a megosztás valódi gyakorlatát, szemben a jelenleg működő sharing economy platformok profitorientált megközelítésével.
A munkahelyi mozgásprogramok szervezeti és egyéni oldala : Előnyök, értékteremtő tényezők, motivációk
Authors: Szabó Ágnes , Kajos Attila
Published: April 2023

A fizikai aktivitás előnyei mind egyéni, mind társadalmi szinten jól ismertek és széles körben kutatottak. Kevesebb kutatás foglalkozik azonban a vállalati szinttel, különösen arra vonatkozóan, hogy a szervezetek hogyan tudják a leghatékonyabban ösztönözni alkalmazottaikat a fizikai aktivitásra és a munkahelyi mozgásprogramokban való részvételre. Jelen cikk a magyarországi mozgásprogramok előnyeit interjúkra épülő kvalitatív (n=13), míg a munkahelyi sportolással kapcsolatos előnyöket, motivációkat kérdőíves kvantitatív kutatással (n=728) mutatja be, utóbbit az önmeghatározás elméletének felhasználásával. A kutatás eredményei nyomán megállapítható, hogy míg a mozgásprogramok elindításának fő vezetői motivációi az elkötelezettség növelése, a fluktuáció és a hiányzások csökkentése voltak, addig a munkavállalókat leginkább az introjektált és az identifikált szabályozók motiválják, vagyis a munkahelyi sport nem teljesen belső indíttatású, és lazán kapcsolódik a vezetői célokhoz. A motivációval kapcsolatos további kutatások elengedhetetlenek ahhoz, hogy a vállalatok segítséget kapjanak abban, hogyan kommunikálhatják, népszerűsíthetik a leghatékonyabban a munkahelyi mozgásprogramjaikat a munkavállalóik számára.
Perfil de egreso del Nutricionista en Chile: similitudes y particularidades entre las distintas instituciones de Educación Superior.
Authors: Cáceres Rodríguez Paola , Torrealba Silva Francisca , Chavarría Tapia Christopher , Bugueño Araya Claudia Alejandra
Published: April 2023

Introducción: El Perfil de Egreso es un elemento curricular que define las competencias específicas y genéricas, que particularizan a un profesional. Se elabora a partir de los ámbitos de desempeño de la profesión, la disciplina y las demandas del medio. En Chile, 35 instituciones dictan el programa de Nutrición y Dietética y, dada su heterogeneidad y la falta de un consenso de estándares mínimos nacionales, el objetivo de este estudio fue analizar los perfiles de egreso declarados por las instituciones, con el fin de determinar puntos de consenso y/o particularidades que permitan evaluar su pertinencia.
Metodología: Estudio descriptivo mixto de tipo transversal. Se analizaron 35 universidades que corresponden al universo a julio de 2022. Se utilizaron como material empírico, los textos titulados como “Perfil de egreso” publicados en las páginas webs oficiales de las instituciones. Se utilizó el programa Atlas.ti versión 22 para el análisis temático de tipo descriptivo de los textos, siguiendo una lógica inductiva.
Resultados: Se analizaron 33 perfiles (2 no estaban publicados). El ámbito clínico es el que estaba mayormente presente en los perfiles (94%), seguido por el de salud pública (85%) y gestión de servicios de alimentación (82%), con 25 instituciones (76%) declarando los tres ámbitos tradicionales de la disciplina. Dentro del ámbito de desempeños no tradicionales, el más presente fue investigación (64%), seguido por manejo de herramientas tecnológicas (18%) y deporte (15%). Del 73% que declaran el ámbito genérico, ética es la subcategoría que se presenta con mayor frecuencia (23%), seguido por trabajo en equipo (19%) y responsabilidad social (18%).
Conclusiones: Existe una amplia diversidad tanto en la forma como en el fondo de los textos publicados. Si bien la gran mayoría declara al menos los 3 ámbitos tradicionales, el 48% no declara desempeños para todos los ámbitos identificados.
Scrambling and Binding in Korean: An Experimental Investigation
Authors:   The Society Of Modern Grammar, Jegal Min
Published: April 2023

This article provides an experiment-based study on scrambling involved in binding. There have been a large number of attempts to analyze scrambling in terms of A/A’-distinctions. These analyses are dependent upon the canonical Binding Theory(BT). Binding relations, however, do not always determine which copy of a scrambled phrase is interpreted. Besides, different acceptability judgments on the same sentence among researchers have been one of the impediments to proposing a far-reaching theory regarding scrambling. For this reason, this paper conducted an acceptability judgment testing to scrutinize the mixed nature of scrambling and binding. In the experiment, ‘scrambling effects’ are observed in all but one of the conditions; it suggests that scrambling-involved data can be analyzed by means of the inactiveness of the base copy. The parallels of the pronoun ku and the anaphor caki observed in scrambled contexts support the idea that the dependence on the BT for understanding the nature of scrambling is problematic.
Problems on Tagging of Parts of Speech of Chinese Two- Syllable Body Compound-Focused on Verb and Adjective
Authors:   The Society Of Modern Grammar, Lee Sunhee
Published: April 2023

This paper analyzed the partiality of 42 two-syllable body compound words with different parts of speech as verbs and adjectives in various dictionaries through the modification of adverbs of degree. Type A body compound words consist of a subject predicate structure except for three predicate object structures. It is difficult to say that this type of compound word is lexicalized as a typical adjective because it is found that it receives little modification of adverbs of degree. Type B body compound words consist of predicate object structures, and it is a general view that as the internal closeness increases, they have been lexically converted from predicate object phrases into heterologous verbs. Many of these compound words can be seen as verb adjectives and concurrent verbs because they are relatively actively modified by adverbs of degree. The internal closeness of Chinese compound words is generally higher in the predicate object structure than the subject predicate structure. As the lexical progress of the predicate object structure with high internal closeness is more active, it is thought that type B compound words are more formulated by adverbs of degree.
Study of Focus on Form and Focus on Forms on L2 Pronunciation Development of English Consonant
Authors:   The Society Of Modern Grammar, Lee Youn-Kyoung
Published: April 2023

The study aimed at examining the effectiveness of Focus on Form (FonF) and Focus on Forms (FonFs) on L2 Pronunciation development of English consonant. For data, 34 pre-intermediate English major college learners participated in the study. For 3 weeks, experimental group 1 (n=11) received the FonF instruction with corrective feedback (CF). Experimental group 2 (n=11) received the FonF instruction without CF. The control group (n=12) received FonFs instruction. The findings of the study revealed that the 2 FonF groups showed statistically significant differences in the post-test regardless of CF (p=.035, p=.023, p<.05). However, the FonFs group did not show any statistical difference between the pre-and post-test (p=.993, p>.05). Even though the types of CF: recast and clarification requests, did not provide direct assistance in the study, the results of the study had an academic contribution, proving the effectiveness of the FonF instruction on L2 pronunciation development. Finally, suggestions for future studies are discussed.
Null Arguments in Korean Sign Language
Authors:   The Society Of Modern Grammar, Park Hyunjun
Published: April 2023

The purpose of this paper is to analyze the distribution and characteristics of null arguments in Korean Sign Language (KSL). Languages such as Spanish and Italian, which have a rich system of overt morphological agreement, allow subject-drop but not object-drop. For this reason, it has been said that the null arguments are licensed by rich verbal morphology. On the other hand, languages such as Korean and Chinese do not have a rich agreement system like Spanish and Italian. Thus, the verbs are used with the same ending regardless of person, number, and gender features. In this paper, we show that KSL is different from those languages like Korean and Chinese in that arguments can be dropped with both agreeing and non-agreeing verbs. In some contexts, in addition, null arguments of non-agreeing verbs are not allowed, whereas null arguments of agreeing verbs are totally acceptable. Therefore, to solve these problems, in this paper, we suggest hybrid analysis in licensing null arguments in KSL.
A Contrastive Study on the Lexicalization of Korean and Greek Motion Events
Authors:   The Society Of Modern Grammar, Kim Hyejin
Published: April 2023

The following research investigates the lexicalization patterns of motion events in Korean and Greek. Cross-linguistic differences in the encoding of motion events are typically attributed to differences in encoding strategies offered by languages and the limited possibilities for organizing semantic components of movement (i.e., Manner and Course). According to Talmy (1985, 2000), Korean and Modern Greek have been classified as “verb-framed languages,” although there is some disagreement among researchers regarding this classification. Korean language, while debatably not clearly belonging to the verb-framed language or some third category, generally exhibits the characteristics of a V-language. Modern Greek, on the other hand, is a language that demonstrates the coexistence of verb and satellite-framed language, sharing certain properties with satellite language systems, and is situated in an intermediate position on the typological continuum between V and S-languages. Through the research, it is confirmed that the two languages, while initially categorized as V-languages, display unique features in the lexicalization patterns of motion events. Based on the results of this study, further cross-linguistic research can be conducted to explore the individual characteristics of each language in relation to language acquisition.
The Meaning and Realization of Intonation for Korean Sentence-final Ending ‘-ney’
Authors:   The Society Of Modern Grammar, Kim Ki-Yu
Published: April 2023

The purpose of this paper is to confirm the realization of meaning and intonation for Korean sentence-final ending ‘-ney’. For this, based on the speech act, cognition and assumption of hearer, we looked into the realization of intonation for sentence-closing ending, ‘-ney’ in Seoul/Gyeonggi regions and Daegu/North Gyeongsang regions. In this paper, after extracting the physical properties(speech rate, start-point/end-point pitch, minimum/maximum pitch, slope) of each region’s intonation through production test, an objective analysis was attempted using a statistical program. This thesis is significant in that it attempted to analyze the meaning of the sentence-final ending ‘-ney’ in Korean, focusing on various physical attributes of intonation.
Sensory Characteristics and Acceptability of air potato Dioscorea bulbifera L. bulbils products
Authors: Gutierrez Ruby Lyn V
Published: April 2023

Air potato, Dioscorea bulbifera L., bulbils are known to contain primary metabolites such as ash, carbohydrates, crude fiber, lipid, moisture and protein. It also exhibited secondary metabolites: anthrones, anthraquinones, coumarins, essential oils, fatty acids, flavonoids, phenols, steroids, tannins and triterpenes. Cytotoxicity analyses also revealed its non-toxic nature and thus, safe to be consumed. These scientific data were the bases for developing products for maximum utilization of the crop for household consumption and additional income generation through cultivation. This study focused on the sensory characteristics and acceptability of the identified products of air potato (AP) bulbils for consumption and adoption by farmers. It used the descriptive research design. A researcher-made questionnaire was used as the instrument for gathering the data needed. The data were analyzed using the Hedonic scale, frequency count and mean. The findings showed that air potato halaya (jam) and ice cream were liked and accepted extremely; air potato polvoron and maja (white pudding) were liked and accepted very much; air potato chips and flour were liked and accepted moderately. Air potato flour, mainly the ingredient for polvoron and maja, was slightly liked and accepted due to its bitterness. These evaluations revealed that air potato bulbils when adequately nurtured and prepared can be a vital aid for family consumption, additional livelihood and a cheap rich nutritious source of raw materials. Thus, these significant results strongly recommend air potatoes for cultivation and promotion of the diversity and conservation of their species.
Screening of Sunflower Genotypes for Reaction to Alternaria Leaf Blight Disease across Multi-environments using Pooled Analysis
Authors: Asish K Binodh , Thankappan Sugitha , Paramasivam M
Published: April 2023

Sunflower (Helianthus annuus L.) is an oilseed crop with potential health benefits as a source of oil and dietary fiber. The productivity of sunflower is hampered by both biotic and abiotic stresses caused due to climate changes. So far, the available gene pool is having moderately resistant lines. In the present study, we evaluated two screening methods by artificially challenging the plants with the causative agent A. helianthi. Significant changes in disease severity have been observed across 160 pre-breeding lines of sunflower, including the susceptible check, Morden in three different seasons. Among the160 pre-breeding lines derived from a mutant population of sunflower cv. Morden, 6.25 and 5.63 % of lines showed less leaf blight disease incidence under in vivo and in vitro environments respectively. Moreover, 44.38 % of the sunflower pre breeding lines demonstrated field tolerance with disease severity in the scale of 5. The promising accessions evaluated in our studies by whole plant assay method and detached leaf technique includes KSFI 19, KSFI 24, KSFI 147, KSFI 56, KSFI 120, KSFI 88, KSFI 152, KSFI 51 and KSFI 115. Therefore, these sunflower lines, could be employed for introgression of resistance genes against leaf blight disease in sunflower cultivars through marker assisted breeding strategies.
Application trends of the systemic paradigm in pharmaceutical research
Authors: Mahanova T. V. , Tkachenko N. О.
Published: April 2023

Pharmacists use systematic knowledge to study the regularities of complex, multilevel systems with a considerable number of variable, feedback connections between them in order to find or make rational management decisions. However, the level and direction of application of the system paradigm of knowledge in pharmacy remain to the end do not determine.
The aim of our research is to identify trends in the application of a systemic paradigm in modern pharmaceutical research to outline promising directions in pharmaceutical science for raising the level of pharmaceutical assistance to the population.
Materials and methods. The research material was publications of fundamental and applied research of domestic and foreign scientists on the raised issue, scientific and methodical publications, dissertations on the repositions of medical and pharmaceutical universities of Ukraine, and database PubMed for the last 20 years.
Results. The research, analysis, and systematization of 59 scientific works of domestic scientists on the application of system paradigms in pharmaceutical research by different applied values were carried out. Namely this pharmaceutical provision for diseases of different nosology, management of pharmaceutical organizations (including regulation, logistics), assessment of medical technologies, social pharmacy (including patient-centered model), pharmaceutical marketing (including pricing, information support), and systems architecture.
Conclusions. The developed array of information sources showed the significant spread of system methodology, approach, and system method. However, the issue of a coordinated and integral definition of the pharmaceutical system remains open. Perspective has seen the application of system analysis and modeling of pharmaceutical systems with modern computer technologies with the further realization of results in the patient’s health care system to increase the level of pharmaceutical care.
Monitorowanie jakości powietrza w Polsce w świetle koncepcji smart city
Authors: Tomala Magdalena
Published: April 2023

Do skutecznego zarządzania inteligentnym miastem władze regionów potrzebują danych, pozwalających na monitorowanie np. stanu gleby, powietrza, i in. czynników. Dlatego w takim mieście instaluje się wiele czujników, kamer i mierników. Pozwalają one na analizowanie i reagowanie w czasie rzeczywistym na problemy, występujące w mieście, takie jak np. analiza płynności ruchu samochodowego, dostępność miejsc parkingowych i in., pozwalające władzom regionów prowadzenie właściwej polityki miejskiej. Wśród wielu czynników, które można monitorować w przestrzeni miejskiej na uwagę zasługuje kwestia zanieczyszczenia powietrza. To jeden z najważniejszych problemów, z którymi borykają się władze miast. Skutki zanieczyszczenia powietrza są szeroko omawiane w literaturze zarówno przez badaczy nauk społecznych, jak i medycznych. W tym kontekście można postawić pytanie badawcze: w jakim stopniu prowadzone działania przez polskie miasta przyczyniają się do zmniejszenia pyłu PM10 w powietrzu? Czy działania w ramach polityki ochrony środowiska są skuteczne i czy następuje poprawa sytuacji w badanym obszarze w okresie od 2010 r. do 2020 r. Celem pracy jest zbadanie polityki monitorowania stanu zanieczyszczenia powietrza pyłem PM10 w polskich miastach. Stan monitorowania powietrza zbadano za pomocą statystyki opisowej. Do zbadania zróżnicowania między przestrzenią miejską i wiejską wykorzystano analizę wariancji. Wybrano próbę metodą losową po 24 stacji pomiarowych reprezentujących przestrzeń miejską i podmiejską i pozamiejską. Następnie uwzględniając zmienne towarzyszące jak: PKB na osobę, liczba ludności zastosowano analizę kowariancji do zbadania ich wpływu na jakość powietrza. Artykuł składa się z trzech części. W pierwszej części dokonano analizy literatury przedmiotu, w drugiej części przedstawiono podejście metodologiczne i w ostatniej przedstawiono wyniki analizy.
Application of machine learning tools for feature selection in the identification of prognostic markers in COVID-19
Authors: Johm Jaime Sprockel Diaz , Restrepo Guerrero Hector Fabio , Fernandez Juan Jose Diaztagle
Published: April 2023

Objective

To identify prognostic markers by applying machine learning strategies to the feature selection.

Methods

An observational, retrospective, multi-center study that included hospitalized patients with a confirmed diagnosis of COVID-19 in three hospitals in Colombia. Eight strategies were applied to select prognostic-related characteristics. Eight logistic regression models were built from each set of variables and the predictive ability of the outcome was evaluated. The primary endpoint was transfer to intensive care or in-hospital death.

Results

The database consisted of 969 patients of which 486 had complete data. The main outcome occurred in 169 cases. The development database included 220 patients, 137 (62.3%) were men with a median age of 58.2, 39 (17.7%) were diabetic, 62 (28.2%) had high blood pressure, and 32 (14.5%) had chronic lung disease. Thirty-three variables were identified as prognostic markers, and those selected most frequently were: LDH, PaO2/FIO2 ratio, CRP, age, neutrophil and lymphocyte counts, respiratory rate, oxygen saturation, ferritin, and HCO3. The eight logistic regressions developed were validated on 266 patients in whom similar results were reached (accuracy: 65.8–72.9%).

Conclusions

The combined use of strategies for selecting characteristics through machine learning techniques makes it possible to identify a broad set of prognostic markers in patients hospitalized for COVID-19 for death or hospitalization in intensive care.
Developing easy-to-use, cost-effective wound dressing material by coating commercial cotton bandages with nanomaterials
Authors: Parkale Rohit , Pulugu Priyanka , Kumar Prasoon
Published: April 2023

Commercial cotton gauze bandages are applied on wounds to prevent contact with dust and/or pathogens, while ensuring enough aeration for accelerated wound healing. More often than not, these bandages are used in conjunction with antiseptic (topical) agents to avoid any post-dressing infections. Additionally, healing medications need to be orally administered to accelerate the healing process and manage the pain. Mechanical debridement remains a problem upon removal of the wound dressing material which leads to delayed healing. In the present work, commercial bandages have been modified to have anti-microbial properties and the capability of localised drug delivery to minimise the local pain and post-dressing infections at a wound site. To achieve this diclofenac sodium (an anti-inflammatory drug) loaded biodegradable, polycaprolactone-based nanofibrous mat has been layered on top of a commercial cotton bandage whose surface has been modified with the coating of chitosan and zinc oxide nanoparticles. The chitosan coating over the cotton gauze bandage brings in the antibacterial properties, while the zinc oxide nanoparticles provide ultra-violet protection. The drug loaded nanofibrous mat releases diclofenac sodium under a simulated wound microenvironment. The article delineates the nanomaterials on cotton gauze bandages as an effective alternative to commonly used cotton gauze bandages for wound dressing applications.
Digitizing Carroll D. Wright’s “Hand and Machine Labor” Study
Authors: Atack Jeremy , A. Margo Robert , W. Rhode Paul
Published: April 2023

We describe our digitization of a uniquely detailed study of 19th century production methods assembled by the United States Department of Labor (1899). The staff spent five years collecting and assembling data on the production of hundreds of highly specific products (as well as some services) at the production operations level using traditional artisanal (“hand”) methods and by the (then) most modern “machine” methods, measuring productivity in terms of the time taken to complete a specific task or set of tasks. The data proved too complex and voluminous to use, except as a source of anecdotes, until now. We describe how we have made these invaluable data from the first industrial revolution tractable to modern analysis and how they might be used to provide insight and perspective into the effects of robotics and artificial intelligence on labor during the third industrial revolution.
Ordering ORDO: Capturing the Freiburg School’s Post-war Development through a Text Mining Analysis of its Yearbook (1948–2014)
Authors: Küsters Anselm
Published: April 2023

Current research on the long-term influence of ordoliberal and neoliberal ideas is hampered by an overly static and generalised picture of the Freiburg School. To address this gap, the paper analyses all articles published in ORDO, the flagship journal of the Freiburg School, between 1948 and 2014. This makes it possible to distinguish three phases of post-war ordoliberalism, to identify personal continuities and breaks, and to summarise thematic, methodological, and conceptual developments. Since the analysis utilises text mining methods, such as keyword identification and Topic Modeling, and validates the results of distant reading with close reading and external data, the paper also highlights some general methodological insights for using Digital Humanities in the historical sciences.
High-speed all-optical digital-to-analog converter based on photonic crystal ring resonators
Authors: Behbahani Pirooz Nezhadmazare , Soroosh Mohammad , Farshidi Ebrahim
Published: April 2023

In this paper, a 2-bit all-optical digital-to-analog converter, including two ring resonators has been presented. Some nonlinear rods have been placed at the center of the rings which their refractive indices depend on the incoming optical intensity. Concerning the states of two input bits, each ring does the switching operation and guides the optical waves toward the output port. The finite difference time domain method has been used to calculate the electric and magnetic components of optical waves. The maximum absolute error of the digital-to-analog converter is equal to 2.43 %, less than the previous works. Also, the insertion loss varies from −11.13 dB to −8.57 dB for the different states. Besides, the maximum propagation time of the structure is just 1.8 ps suitable for high-speed applications.
Light-driven bioprocesses
Authors: Runda Michael E. , Schmidt Sandy
Published: April 2023

Enzyme catalysis and photocatalysis are two research areas that have become of major interest in organic synthesis. This is mainly because both represent attractive strategies for making chemical synthesis more efficient and sustainable. Because enzyme catalysis offers several inherent advantages, such as high substrate specificity, regio-, and stereoselectivity, and activity under environmentally benign reaction conditions, biocatalysts are increasingly being adopted by the pharmaceutical and chemical industries. In addition, photocatalysis has proven to be a powerful approach for accessing unique reactivities upon light irradiation and performing reactions with an extended substrate range under milder conditions compared to light-independent alternatives. It is therefore not surprising that bio- and photocatalytic approaches are now often combined to exploit the exquisite selectivity of enzymes and the unique chemical transformations accessible to photocatalysis. In this chapter, we provide an overview of the wide variety of light-driven bioprocesses, ranging from photochemical delivery of reducing equivalents to redox enzymes, photochemical cofactor regeneration, to direct photoactivation of enzymes. We also highlight the possibility of catalyzing non-natural reactions via photoinduced enzyme promiscuity and the combination of photo- and biocatalytic reactions used to create new synthetic methodologies.
Biopolymer based membrane technology for environmental applications
Authors: Janakiraman Vardhana , Sowmya Srinivasarao , Thenmozhi Mani
Published: April 2023

The visible deterioration of environmental health, as witnessed for a few decades now, has been the subject of debate and research for a long time. In the desperation to remove the pollutants from the available natural resources, countless physical, chemical, and biological methods have been introduced. However, they hold a few drawbacks and tend to alter the nature of the resources. To avoid intentional alteration, physical and biological methods are put-together to develop biopolymer-based membranes that would help the crisis and sort out the preferences. The technique includes trapping industrial carbon dioxide and other gases, drinking water treatment, wastewater treatment, desalination, reclamation, and reuse. Membrane technology is still a hot topic for new openings. Biocompatibility, biodegradability, and cost-effectivity of biopolymers are the greatest assets for developing technology. The efficacy of biopolymer-based membranes is covered in this chapter and their techniques in helping the environment.
Synthesis, characterization and in vitro activity study of some organotin(IV) carboxylates against leukemia cancer cell, L-1210
Authors: Hadi Sutopo , Winarno Ermin Katrin , Winarno Hendig , Berawi Khairun Nisa , Suhartati Tati , Yandri Yandri , Simanjuntak Wasinton
Published: April 2023

This paper presents successful resynthesizing of several dibutyl-, diphenyl-, and triphenyltin(IV) carboxylate compounds, and their activity against leukemia cancer cell, L-1210. The compounds were synthesized by reacting the dibutyltin(IV) oxide (DBTO) (1), diphenyltin(IV) oxide (DPTO) (3), and triphenyltin(IV) hydroxide (TPTOH) (5) with 3-hydroxybenzoic acid (3-HHBz). Prior to cancer activity tests, the compounds were characterized by UV–Vis, FT-IR, NMR (both 1H NMR and 13C NMR), and microanalysis to determine elemental composition of the samples. The anticancer tests revealed that triphenyltin(IV) 3-hydroxybenzoate (TPTHBz) (6) displayed significantly higher activity than those exhibited by dibutyltin(IV) di(3-hydroxybenzoate) (DBTHBz) (2) and diphenyltin(IV) di(3-hydroxybenzoate) (DPTHBz) (4).
Irradiation effects on phenolic content in Bulgarian honey bee products and correlation to the antioxidant activity
Authors: Mladenova Ralitsa B. , Solakov Nikolay Y. , Loginovska Kamelia K.
Published: April 2023

Bee pollen and bee bread are considered for a good source of nourishing and polyphenol substances which may act as powerful antioxidants. Some main phenolic compounds of studied non-irradiated and irradiated samples were identified and compared by high performance liquid chromatography (HPLC). The effects of irradiation treatment of bee pollen and bee bread on their phenolic content were studied. For this purpose, the samples were γ-irradiated with 2, 5, 10 and 20 kGy. The results show that the ionizing radiation affect phenolic content of analyzed samples depends on the dose and the chemical composition of honey bee product. The identified phenolic substances and changes in their amount after irradiation were related to free radical scavenging activity (FRSA) of studied samples. FRSA of bee pollen and bee bread were determined by electron paramagnetic resonance (EPR). Gamma treatment with 5 kGy has a positive effect on antioxidant potential at both honey bee products.