bluuebunny/crossref_metadata_2025 huggingface dataset:
Nutrient Recovery from Wastewater by a Consortium of Algae Species for Biofuel Production
Authors: Ayala Edgardo
Published: March 2023

Current energy sources are predominantly petroleum-based and their use increases greenhouse gas (GHG) emissions. As the global population grows,
and along with it the demand for energy, there is a need to further develop renewable energy sources to avoid the effects of increasing
atmospheric CO2 concentrations on the climate. Biofuels, a renewable energy source, have gained significant interest as a replacement
for petroleum-based fuels due to their environmental benefits and carbon neutrality. Biofuels are expected to make up 9.0% of the total fuel
consumption in the U.S. by 2040, up from 7.3% in 2019 [1]. Currently, terrestrial crop-based biofuels are the most widely used. However, their
production competes for land, fertilizer, and water resources with food production. Cultivation of microalgae-based biofuels can avoid this competition
through higher productivity that leads to lower land requirements and their ability to use wastewater as a water and nutrient source for cultivation.
We designed and tested a large-scale and semi-continuous operating algal polyculture cultivation system to determine the utility of using undiluted
agricultural wastewater as the sole nutrient and water source for algal production. Algal biomass was evaluated for both biofuel production and water
treatment (i.e., nutrient sequestration). Algal biomass was converted to a bio-oil by hydrothermal liquefaction (HTL). We also asked if algal
production could be maximized by recycling nutrients recovered from HTL processing into a secondary bench-scale algal cultivation system (i.e., in a
closed nutrient-loop system). Semi-continuous operations resulted in increased biomass yields, with projections estimated at 4,000 kg biomass/year in
polyhydroxyalkanoate effluent (PHAE). Recycling HTL(aq) did not present additional benefits in sustaining or increasing algal productivity.
Based on our estimations, the highest economic return will result from coupling nitrogen (N) water quality trading (WQT) with biomass conversion to
bio-crude.
Investigations on the interactions of Streptolysin O and Lysenin with Natural and Artificial Lipid Membranes
Authors: Ayllon Marcelo
Published: March 2023

The investigations described in this work are focused on better understanding the interactions between pore-forming toxins (PFTs) and lipid membranes.
The necessity of these investigations is justified by the important role of PFTs in infectivity and their potential impact on the development of
alternative strategies for mitigating the global burden presented by infectious diseases and the onset of antimicrobial resistance. To achieve our
scientific goals, we employed Red Blood Cells (RBCs) as a model for assessing the lytic action of two PFTs, Streptolysin O (SLO), and lysenin. To address
the interactions between PFTs and specific membrane moieties as mediators of binding, oligomerization, and lysis, we employed spectrophotometrical
assessments of hemolysis in conjunction with affinity measurements by the Kinetics Exclusion Assay (KinExA). The observation that SLO-induced hemolysis
was gradually diminished upon cholesterol depletion even when the affinity of SLO for target membranes increased led to the conclusion that a slight
reduction in the cholesterol content promotes binding but affects oligomerization into functional pores. Sphingomyelin depletion also led to a reduced
hemolytic activity of lysenin but significantly diminished the barrier function of RBC membranes. Prompted by these results, we investigated the use
of liposomes as target decoys for SLO and lysenin, capable of diminishing hemolysis in a concentration-dependent manner, which may constitute a
complementary or alternative therapeutic approach for infectious diseases in which PFTs act as virulence factors. A direct comparison between the
inhibitory effectiveness of monoclonal antibodies and liposomes for SLO clearance indicates the tremendous potential therapeutic applications
presented by custom-designed liposomes for aiding in the world-wide fight against bacterial infections.
Improved Computational Prediction of Function and Structural Representation of Self-Cleaving Ribozymes with Enhanced
Parameter Selection and Library Design
Authors: Beck James D.
Published: March 2023

Biomolecules could be engineered to solve many societal challenges, including disease diagnosis and treatment, environmental sustainability, and
food security. However, our limited understanding of how mutational variants alter molecular structures and functional performance has constrained
the potential of important technological advances, such as high-throughput sequencing and gene editing. Ribonuleic Acid (RNA) sequences are thought
to play a central role within many of these challenges. Their continual discovery throughout all domains of life is evidence of their significant
biological importance (Weinreb et al., 2016). The self-cleaving ribozyme is a class of noncoding Ribonuleic Acid (ncRNA) that has been
useful for relating sequence variants to structural features and their associated catalytic activities. Self-cleaving ribozymes possess tractable
sequence spaces, perform easily identifiable catalytic functions, and have well documented structures. The determination of a self-cleaving ribozyme’s
structure and catalytic activity within the laboratory is typically a slow and expensive process. Most current explorations of structure and function
come from these empirical processes. Computational approaches to the prediction of catalytic activity and structure are fast and inexpensive, but
have failed both to achieve atomic accuracy or to correctly identify all base-pair interactions (Watkins et al., 2018). One prominent
impediment to computational approaches is the lack of existing structural and functional data typically required by predictive models
(Jumper et al., 2021). Using data from deep-mutational scanning experiments and high-throughput sequencing technology, it is
possible to computationally map mutational variants to their observed catalytic activity for a range of self-cleaving ribozymes. The resulting
map reveals important base-pairing relationships that, in turn, facilitate accurate predictions of higher-order variants. Using sequence data
from three experimental replicates of five model self-cleaving ribozymes, I will identify and map all single and double mutation variants to
their observed cleavage activity. These mappings will be used to identify structural features within each ribozyme. Next, I will show within a
training tool how observed cleavage for multiple reaction times can be used to identify the catalytic rates of our model ribozymes. Finally,
I will predict the functional activity for model ribozyme variants of various mutational orders using machine learning models trained only on
functionally labeled sequence variants. Together, these three dissertation chapters represent the kind of analysis needed to further the
implementation of more accurate structural and functional prediction algorithms.
Associations Between the School Physical Environment and Climate in Rural Schools
Authors: Castleton Tate
Published: March 2023

According to the National Center for Education Statistics (2021), more than half of all public-school districts and nearly
one-third of all public-school students attend rural schools in the U.S. This study identifies characteristics of the physical
environment of rural schools, considers how the physical environment of rural schools compares to urban and suburban schools, and
describes the associations of a school’s physical environment with perceptions of school climate among students, staff, and parents.

Using the School Assessment for Environmental Typology (SAfETy; Bradshaw et al., 2015), this study objectively assessed the
physical environment of 40 rural schools in Idaho. Those characteristics were compared with data collected in prior research
(Bottiani et al., 2020). This study found rural and non-rural schools, and the make-up of their physical environments, are not
that different. The physical environment of rural schools had low frequencies of instances of disorder, such as trash, graffiti,
drugs, paraphernalia, and evidence of building decline, such as broken windows and neglected landscaping. Rural schools also produced
moderate scores related to appearance, with characteristics including illumination, visibility, and ownership. Most schools in this
study were found to have interior and exterior surveillance cameras in place and employed school resource officers.

Rural secondary schools in this study had a higher presence of surveillance measures than non-rural high schools, whereas non-rural
high schools had higher frequencies of disorder. And, although a comparison to non-rural elementary schools is not available, the rural
elementary schools score in the current study show similar physical environmental characteristics as did urban secondary schools in
all three factors of the SAfETy.

In addition, the current work also examined aspects of the social environment, through evaluating school climate. The Maryland Safe
and Supportive (MDS3) School Climate Survey Suite was administered to students, parents, and staff in all 40 schools participating
in this study. Multi-variable regression analysis was used to examine the associations between the SAfETy and school climate. Several
associations were found among students, with fewer associations among staff and parents.

This research study concludes that a variety of important, urgent, and malleable associations exist between a rural school’s physical
environment and perceptions of school climate among students, staff, and parents. This research, and future research that builds upon
this work, will assist schools as they strive to transform, strengthen, and sustain positive school environments for all stakeholders.
Understanding and Mitigating the Effects of Artificial Light on Bats and Nocturnal Arthropods in Grand Teton National Park
Authors: Cole Hunter
Published: March 2023

Bat and insect populations are at risk globally, and identifying factors that may influence bat and insect populations alongside
mitigation techniques for anthropogenic factors that may negatively influence these taxa will be crucial for their conservation. To
identify landscape characteristics that influence bats throughout Grand Teton National Park, we placed passive acoustic monitors
throughout the park in areas with different microhabitat characteristics to identify factors that influence activity. Additionally,
we developed a R package, `EcoCountHelper`, to assist wildlife managers in analyzing ecological count data similar to our bat
monitoring data. As a demonstration of the package, we conducted a GLMM-based analysis of this landscape-scale bat monitoring data.
Following our broad-scale assessment of bat activity in Grand Teton National Park, we also installed experimental street lights capable
of emitting both red and white light throughout Grand Teton National Park’s Colter Bay area, and monitored bat and insect activity while
altering the color of light illuminating a focal parking lot to assess red light’s ability to mitigate the impacts of artificial light on
bats and insects.

Through our park-wide acoustic monitoring, we found that bat habitat use varied for the seven species we fit candidate models for, with
distance to water, the number of buildings suitable for roosting, and forest cover all influencing activity levels for different species
of bats throughout the park. As a result of our fine-spatial-scale research surrounding light pollution mitigation, we also found that
red light does not seem to be an effective method of promoting bat activity in artificially illuminated areas that is similar to that
of unlit areas, but insects did exhibit more similar sample counts to unlit areas during red light treatment periods than white light
treatment periods. Our findings both provide valuable information for land and wildlife managers in Grand Teton National Park to conserve
bat and insect populations, and highlight the need for additional research surrounding bat-human interactions. Additionally, we hope our
development of a streamlined R package for GLMM analysis using count data will facilitate and promote robust and reproducible analyses
for wildlife managers and researchers alike.
The Influence of Visitors, Habitat, and Methodology on Mexican Spotted
Owl (Strik occidentalis lucida) Occupancy and Detection in a Remote Canyon Environment
Authors: Fuller Kirsten
Published: March 2023

National Parks across America play an important role in protecting natural resources and providing access to recreation for visitors.
However, these goals may come into conflict as visitation rates rise. Grand Canyon National Park in Northern Arizona is one of the most
highly visited parks in the United States, with over 6 million visitors a year. Backcountry hiking and camping are popular activities in
the park, and many highly visited hiking trails and campgrounds overlap with known breeding areas of a threatened species, Mexican
Spotted Owl. In this thesis, I explore the intersection of recreation and wildlife conservation at this popular park through the lens of
long-term occupancy of a threatened species. My aims are to (1) assess the potential impact of visitor use on long-term occupancy (2001
to 2021) of Mexican Spotted Owls at the Grand Canyon, and (2) evaluate the potential for autonomous recording units (ARUs) to complement
current survey protocols. To assess long-term occupancy, I ran a multi-season occupancy model using 20-years of call-back survey data
conducted in protected activity centers (PACs), along with measures of visitor use and habitat characteristics. To assess the use of
ARUs, I ran a single-season occupancy model using three years of data, which was collected using autonomous recording units in PACs
from 2019 to 2021. I found that visitor use in the Grand Canyon had no effect on owl occupancy, which remained stable across PACs
over the 20-year study period. Owl occupancy remained high across the 20-year survey period and was strongly informed by habitat
characteristics. Specifically, Mexican Spotted Owls occupied PACs with higher proportions of mixed shrubland habitat and Supai
formation. Conversely, owl occupancy decreased in PACs with more pinyon-juniper woodland habitat and Redwall Limestone. Assessing
the use of ARUs as a complement to current protocol, ARUs were found to be a useful tool for supplementing traditional call-back
surveys, particularly at PACs with extremely limited access. In particular, ARUs detected Mexican Spotted Owls with high probability
early in the breeding season prior to the official call-back survey period, which allows managers to extend their monitoring period.
In highly remote PACs, ARUs were more suitable than call-backs because they could collect more data with less effort. Incorporating
this method into Spotted Owl survey protocol may be essential for improving monitoring of under-sampled locations, which is a critical
component for assessing long-term trends for this species across its range.
Sexually Selected Preferences for Human Altruism Across Sexual Orientation, Gender, Age, and Reproductive Status
Authors: Kappelman Katherine Valinske
Published: March 2023

Prior studies have attempted to establish how human altruism has evolved, including theories of kin selection, reciprocal altruism, and costly
signaling. Recent investigations have explored the evolution of altruism as the result of sexual selection, where individuals may exhibit
altruistic behavior because it is preferred by potential mates. In this study, I examine how altruistic behavior toward different people
(family, friends, strangers, or general altruistic acts) is preferred when considering potential short-term and long-term mates. While previous
research has examined this question using college-aged heterosexual participants, this study uses a more diverse sample, including individuals
who identify as LGBTQ, those of varying ages, and those who identify as childfree. Seven hypotheses were tested to understand how preferences
for altruistic behavior vary based on individual characteristics. An on-line survey was conducted and over 500 participants responded. Results
show that women prefer potential mates who behave altruistically toward strangers more so than men; when examining long-term relationships,
people prefer potential mates who behave altruistically toward family; and that an individual’s self-reported altruistic behavior is positively
correlated with an individual’s preference for altruistic behavior in a mate. Surprisingly, some hypotheses were not confirmed. For instance,
there is no difference between preferences for altruistic behavior in potential mates based on sexual orientation. When examining women’s
preferences for altruistic behavior in potential mates based on reproductive status, I found that post-reproductive women have a greater
preference for altruistic behavior that is directed toward strangers or general altruistic behavior as compared to reproductive aged women.
The results of this thesis provide insights into the evolution of human altruism.
A Phenomenological Study of Digital Business Simulation Games and Implementation for Corporate Learning
Authors: Manjorin Jeremy Morgan
Published: March 2023

This qualitative phenomenological study investigated the experiences of a purposive sample of eight Learning and Development executives to
understand the circumstances leading to, as well as the experiences implementing Digital Business Simulation Games (DBSG) in a corporate
learning environment, specifically related to the financial service industry. Their perception of the organizational needs, decision-making
process of those involved, as well as the experience in design, development, and implementation may contribute to a better understanding of
the circumstances within an organization where a DBSG would be an effective solution to achieve the development goals of learners within
that organization. This study will also investigate the impact the implementation of the DBSG had on the organization, as well as provide
further insight into best practices and critical success factors for future implementations. The research technique employed was a modified
van Kaam method as described by Moustakas (1994) based upon transcribed interviews using semi-structured questions to capture the organizational
needs, decision-making, and implementation experiences as well as perceptions of the participants. Five significant themes with two subthemes
that emerged are prevalent from within the collected data from the participants: 1) needs intake and leadership support, 2) safe space to
practice, 3) innovation on current curricula, 4) higher degrees of engagement, and 5) positive measurement results. The resulting analysis
also led to considerable collection of best practices and critical success factors in deciding to undertake a DBSG program, and the design,
development and implementation of a DBSG
Structure, Function, and Immunogenic Applications of AB5-type ADP-Ribosylating Bacterial Toxins
Authors: Overgaard Elise Marie
Published: March 2023

Bacterial mono-ADP-ribosyltransferases (ARTs) catalyze the singular transfer of an ADP-ribose moiety from an NAD+ molecule onto a target
molecule. ARTs contain an ancient and highly conserved tertiary structure and have a wide variety of intracellular targets and effects.
Some, but not all, bacterial ARTs have an AB5-type multimeric structure consisting of an enzymatically active subunit non-covalently
situated atop of a non-toxic pentamer. The active, or A, subunit of AB5-type toxins has a catalytic action that contributes to
bacterial pathogenicity, and it is sometimes, but not always, an ART. ArtAB is an ART with AB5-type structure from the virulent
and highly antibiotic resistant Salmonella Typhimurium DT104. In the studies described here, we tested the hypothesis that the active
subunit of ArtAB is structurally and enzymatically homologous to that of the well-characterized AB5-type ART pertussis toxin.
ArtAB was purified from E. coli and was used to characterize ArtAB’s cellular effects, predicted structure, and biophysical
properties. In addition, a set of single-residue mutants was constructed and purified to probe ArtAB’s active site. AB5-type toxins
have long been studied for their immunogenic properties, and some of these bacterial munitions have been harnessed and repurposed as vaccines
or vaccine adjuvants to prevent infectious disease. Their receptor-binding pentamer, abbreviated as B5, binds to, and facilitates
entry into, host cells. In additional work presented here, we tested the hypothesis that the B5 subunit of cholera toxin (CTB)
from Vibrio cholerae could be used to construct a safe and effective mucosal vaccine
against Staphylococcus aureus-caused mastitis. We constructed a bovine vaccine by
conjugating Staphylococcus aureus antigens to the CTB-based adjuvant platform, and the immunogenicity of the vaccine was
characterized in a bovine clinical trial. Finally, clinical isolates of caprine S. aureus were screened for the presence of
surface antigens that could be use in a caprine version of the vaccine against mastitis. The work on bacterial AB5-type ARTs
presented here contributes to a growing global understanding of the bacterial ART family, lays a foundation for the potential incorporation of
ArtAB in a vaccine against Salmonella, and advances the development of bovine and caprine vaccines
against S. aureus-caused mastitis.
Hate Speech Detection Using Textual and User Features
Authors: Raut Rohan
Published: March 2023

Social media platforms provide users with a powerful platform to share their ideas. Using one’s right to expression to incite
hatred toward a particular group of people is inappropriate. However, hate speech is pervasive in our society. Spreading hate
through online social networks like Facebook, Twitter, Tiktok, and Instagram is commonplace in today’s milieu. One such case is
the unprecedented COVID-19 pandemic, which engendered anti-Asian hate.

In current literature, there is limited study on using user features in conjunction with textual features to detect hate. This
thesis aims to combine textual features with user features to improve the state-of-the-art hate speech detection technique. To test
our approach, we used four different datasets available in the public domain. We have used various tools to access Twitter APIs to
extract required user information, either to use directly or further compute other features using that information.

We have represented the textual features in the form of BERT embeddings and linguistic features. The 97 linguistic measures computed
with a Linguistic Inquiry and Word Count (LIWC) tool quantify the text’s cognitive, affective, and grammatical processes. The user
feature consisted of demographic, behavioral-based, emotion-based, personality, readability, and writing style features. Our experimental
evaluation over three datasets shows that the top twenty linguistic features and the top twenty user features are the best combinations
for hate speech detection.

Hate speech is mostly emotionally charged. We further analyzed these user and linguistic features. Among the most intuitive and prominent
results was that features like anger, negative emotion, swearing, fear, and annoyance were high in hate speech, while the happiness feature was low.

We compared multiple approaches along with the existing state-of-the-art. We found that the best approach with textual features was
combining LIWC features with BERT embeddings. This combination gave us the F1 of 0.82 and 0.79 on Crowd-sourced (DS1) and
Kaggle (DS3), respectively. Followed by this, we identified the top LIWC and user features for hate speech detection. We found that
features representing negative emotions like anger, fear, sadness, and annoyance were prominently high in hate speech. Happiness is
lower in hate speech. After this, we analyzed the F1 scores with standalone LIWC and user features. We also used their
combinations. We found that the combination of the top twenty LIWC and top twenty user features gives the best F1 scores
of 0.74, 0.90, and 0.64 on DS1, NAACL (DS2), and anti-Asian Covid hate (DS4) dataset.

Finally, we used traditional machine learning algorithms combining BERT embeddings with the top twenty linguistic features and the
top twenty user features. We obtained the F1 scores of 0.78, 0.92, and 0.84 on DS1, DS2, and DS4 respectively. We also
compared our approach with other studies using user and textual features.
Modulation of Alpha-Crystallin-Membrane Association by Phospholipid Acyl Chain Length and Degree of Unsaturation
Authors: Trossi-Torres Geraline
Published: March 2023

Cataract is the leading cause of blindness worldwide. The only treatment for cataracts is the surgical removal of the cataractous
lens and the replacement of an intraocular lens. With less availability of treatment and low income, the visual damage caused by
cataracts can go untreated. The cataract may develop again after surgery, such as posterior capsule opacification. With age and cataracts,
α-crystallin, a significant protein of the mammalian eye lens, is progressively associated with the eye lens membrane. The primary
association sites of α-crystallin with the membranes are phospholipids. However, it is unclear if phospholipids’ acyl chain length and
degree of unsaturation influence the α-crystallin association. We used the electron paramagnetic resonance (EPR) approach to investigate
the association of α-crystallin with phosphatidylcholine (PC) membranes of different acyl chain lengths and degrees of unsaturation,
with and without cholesterol (Chol). The association constant (Ka) of α-crystallin follows the trends, i.e., Ka
(14:0–14:0 PC) > Ka (18:0–18:1 PC) > Ka (18:1– 18:1 PC) ≈ Ka (16:0–20:4 PC) where the presence of Chol
decreases Ka for all membranes. With an increase in α-crystallin concentration, the saturated and monounsaturated membranes
rapidly become more immobilized near the headgroup regions than the polyunsaturated membranes. Our results directly correlate the mobility
and order near the headgroup regions of the membrane with the Ka, with the less mobile and more ordered membrane having
substantially higher Ka. Furthermore, our results show that the hydrophobicity near the headgroup regions of the membrane
increases with the α-crystallin association, indicating that the α-crystallin-membrane association forms the hydrophobic barrier to the
transport of polar and ionic molecules, supporting the barrier hypothesis in cataract development. Taken together, our findings clearly
show how the changes in phospholipids’ acyl chain length and degree of unsaturation influence α-crystallin association with model
membranes and provide insight for further investigations to examine how such changes in lipids in the eye lens membranes with age and
cataracts modulate α-crystallin association with native membranes.
Diabetes mellitus: los orígenes de un no tan dulce término
Authors: Villalba Leonardo Miguel
Published: March 2023

Muy frecuentemente en la práctica médica se suele hacer referencia al término diabetes mellitus, pero escasamente nos preguntamos su origen etimológico e histórico, ya que no se corresponde a palabras propias del idioma inglés o español. Lo cierto es que este concepto ha sido construido a lo largo de los años, desde épocas ancestrales, para describir un fenómeno patológico del cual aún no se tenía mucho conocimiento. A partir de ello, resulta curioso y útil comprender las connotaciones que le han dado al término los distintos pensadores y científicos a través de una somera investigación sobre lo ya publicado en distintos textos científicos, con el fin de comprender a la diabetes mellitus no solo como una enfermedad con sus consecuentes subclasificaciones, sino como un fenómeno histórico que ha cambiado el curso de la humanidad y de la práctica médica hasta la actualidad. Hay registros de la existencia de la diabetes mellitus desde alrededor del 1500 a.C. que provienen de distintas culturas como la hindú, la egipcia, la griega, la china, entre otras. Con el paso de los años se logró reconocer y describir la signo-sintomatología que la caracteriza, pero hubo dificultades para identificar las causas responsables de este cuadro. El amplio estudio de este padecimiento por diversos personajes históricos ha logrado establecer distintas entidades y formas de manifestación, como la diabetes tipo 1 y tipo 2, diabetes insípida, etc., que hasta la fecha sufre modificaciones de acuerdo con los nuevos hallazgos científicos.
Information System Assessment of the Creditworthiness of an Individual
Authors: Nahirna Alla , Chumachenko Oleksandra , Pyechkurova Olena
Published: March 2023

Nowadays enterprise information systems of banks provide modules for calculating creditworthiness of the business. Such systems are complex and it is difficult to maintain and develop them. Moreover, it requires the involvement of large teams. In addition, systems are complicated to change and update in accordance with changes in current legislation. From another point of view, demand for consumer loans is high, and creating a separate module for calculating the creditworthiness of an individual is appropriate in case of increasing the adaptability to changes and updates of the system. Calculating the creditworthiness of an individual is relevant not only for the banking system, but also for other spheres such as logistics and marketing.The work describes the created information system for calculating the creditworthiness of an individual, which calculates the class of the borrower based on data from credit history, credit rating, quality characteristics, financial indicators of the person and characteristics of the credit transaction.The use of the Asp.Net Core platform and the Vue.js framework to build a software module that can be used both independently and easily integrated into other corporate systems is demonstrated.In this work the major steps of designing and developing the system are described.
Analysis and Synthesis of Technology for Textual Information Classification
Authors: Kuznetsov Vladyslav , Krak Iurii , Lіashko Volodymyr , Kasianiuk Veda
Published: March 2023

The task of developing effective text information classification systems requires the thoughtful analysis and synthesis of variable components of technology. These components strongly affect the practical efficiency and the requirements to the data. For this purpose, a typical technology was discussed, comparing the regular “learning from features” approach versus the more advanced “deep learning” approach, that studies from data. In order to implement the technology, the first approach was tested, which included the means (methods, algorithms) for analysis of the features of the source text, by applying the dimensionality transformation, and building model solutions that allow the correct classification of data by a set of features. As a result, all the steps of the technology are described, which allowed to determine the way of presenting data in terms of hidden features in data, their presentation in a standard visual form and evaluate the solution, as well as its practical efficiency, based on this set of features. In a depth study, the informational core of the document was studied, using the regression and T-stochastic grouping of features for dimensionality reduction.The separate results contain estimation of practical efficiency of the algorithms in terms of time and relative performance for each step of the proposed technology. This estimation gives a possibility to obtain the best algorithm of intelligent data processing that is useful for a given dataset and application. In order to estimate the best suited algorithm for separation in reduced dimension an experiment was carried out which allowed the selection of the best range of data classification algorithms, in particular boosting methods. As a result of the analysis of the technology, the necessary steps of this technology were discussed and the classification on real text data was conducted, which allowed to identify the most important stages of the technology for text classification.
Usage of the Speech Disfluency Detection Method for the Machine Translation of the Transcriptions of Spoken Language
Authors: Kramov Artem , Pogorilyy Sergiy
Published: March 2023

Neural machine translation falls into the category of natural language processing tasks. Despite the availability of a big number of research papers that are devoted to the improvement of the quality of the machine translation of documents, the problem of the translation of the spoken language that contains the elements of the disfluency speech is still an actual task, especially for low-resource languages like the Ukrainian language. In this paper, the problem of the neural machine translation of the transcription results of the spoken language that incorporate different elements of the disfluency speech has been considered in the case of the translation from the English language to the Ukrainian language. Different methods and software libraries for the detection of the elements of disfluency speech in English texts have been analyzed. Due to the lack of open-access corpora of the speech disfluency samples, a new synthetic labeled corpus has been created. The created corpus contains both the original version of a document and its modified version according to the different types of speech disfluency: filler words (uh, ah, etc.) and phrases (you know, I mean), reparandum-repair pairs (cases when a speaker corrects himself during the speech). The experimental verification of the effectiveness of the usage of the method of disfluency speech detection for the improvement of the machine translation of the spoken language has been performed for the pair of English and Ukrainian languages. It has been shown that the current state-of-the-art neural translation models cannot produce the appropriate translation of the elements of speech disfluency, especially, in the reparandum-repair cases. The results obtained may indicate that the mentioned method of disfluency speech detection can be used for the previous processing of the transcriptions of spoken dialogues for the creation of coherent translations by the usage of the different models of neural machine translation.
Algorithm for Extraction of Keyframes of Images in Video Retrieval Systems
Authors: Afonin Andrii , Oksiuta Iryna
Published: March 2023

As a part of this work, there was a study of image processing algorithms used in video search systems.With the development of search engines and an increase in the types of queries possible for searching, the need for indexing an increasing amount of diverse information is growing. New data in the form of images and videos require new processing techniques to extract key content descriptions. In video search engines, according to this description, users can find the video files most relevant to the search query. The search query, in turn, can be of various types: text, search by image, search by video file to find a similar one, etc. Therefore, it is necessary to accurately describe the objects in the video in order to assign appropriate labels to the video file in the search engine database.In this article, we focused on the algorithm for extracting key frames of faces from a video sequence, since one of the important objects in the video are people themselves. This algorithm allows you to perform the initial processing of the file and save the identified frames with faces in order to later process this data with the help of the face recognition algorithm and assign the appropriate labels. An alternative application for this algorithm is the current processing of video files to form datasets of faces for the development and training of new computer vision models. The main criteria for such an algorithm were: the accuracy of face detection, the ability to distinguish keyframes of all people from each other, comprehensive evaluation of candidate frames and sorting by the relevance of the entire set for each face.After an analysis of existing solutions for specific stages of the algorithm, the article proposes a sequence of steps for the algorithm for extracting key frames of faces from a video file. An important step is to assess the quality of all candidates and sort them by quality. For this, the work defines various metrics for assessing the quality of the frame, which affect the overall assessment and, accordingly, the sorting order. The article also describes the basic version of the interface for using the proposed algorithm.
Parking Spot Occupancy Classification Using Deep Learning
Authors: Kreshchenko Taras , Yushchenko Yury
Published: March 2023

In today’s world, where a car is present in almost every family, the parking problem plays an extremely important role. Parking is one of the most important factors in modern transport infrastructure, because it allows to save the time of both drivers and passengers, to increase the level of comfort and safety of road trips. In Ukraine, this problem is especially relevant, since nowadays it is going through the process of improving its parking infrastructure.The paper examines the problem of parking in large cities, proposes a system for recognizing occupancy of parking spots using computer vision. Such system would use camera feed to track the occupancy of each parking space within a slot. Its benefits would include ease of scalability, saving time of drivers and passengers, automation of parking payment and detection of unpaid parkings. In addition, it makes it possible to easily collect statistics about the busyness of various areas throughout the day or week.The paper also describes the algorithm of classifying the parking spot, as well as a possible architecture that the system may have.Possible problems in training a computer vision model for building the proposed system are considered. Firstly, the available parking datasets are lacking images collected in snow conditions or during nighttime. The hypothesized solution is to use vehicle detection datasets, the number of which that are publicly available is considerably bigger. Another problem is that classification accuracy drops drastically when using different images in train and test dataset. The hypothesized solution here is to apply incremental learning to improve the model as it is being used in a real-life scenario.
INTEGRATION OF STANDARDISED INDUSTRIAL ENTERPRISE MANAGEMENT SYSTEMS
Authors: Gorlova O. P.
Published: March 2023

The article addresses issues in the field of standards-based management systems. It is devoted to the methodology for the creation of integrated management systems (ISU) in industrial enterprises. A constant growth in the number and complexity of ISUs, as well as the number of industrial enterprises that implement them, sparked interest in research on the mode and prerequisites of integration, different input factors, and the results of the use of ISUs, their efficiency and efficacy, and antecedents of manageability of an enterprise during ISU formation or expansion. This forms the relevance of the presented study. The purpose of this article is to determine the ways to implement ISU in industrial enterprises, its key aspects, and possible implementation scenarios of it. Based on the application of project management and organisational change management methodologies, the universal stages of integration of standardised management systems of an industrial enterprise are highlighted. These stages are found in the traditional approach to standardisation process cycle, namely PDCA (plan-direct-control-act). Defining factors have been identified that contribute to the development of ISU. Cotter's Eight Stage Organisational Change Model methodology was applied to the task of ISU integration and development that results in attributing specified tasks for each stage; which enables more efficient ISU implementation and application. From this position, success in the integration of standardised management systems is decisively determined by the quality of management and the capabilities of managers, which is confirmed by the results of modern research in knowledge management in the context of the management of complex systems. This approach also means that any project of integration should provide for a mandatory phase of institutionalisation, which is necessary for the assimilation of new practise and the formation of a «new norm» of work within the ISU. In addition, considering the unique nature of the complexity of ISU formation, the need for a distinct stage of ISU formation — modelling of various configurations -– is identified, since it seems almost impossible to predict and plan all important aspects of both the implementation project and the functioning of the ISU in an analytical way. Through a combination of the most common elements of the ISU, integration scenarios that fit the different needs of the companies and a variety of strategies are identified. The process of implementing the ISU has been improved by shaping two additional phases: modelling at the beginning of the process and institutionalisation and institutionalisation at the end to consolidate new approaches to management in the practice of managers and employees. Some directions for future research are shaped.
CRM-SYSTEMS IN MARKETING RISKS MANAGEMENT OF BANK`S RISK PROTECTION PROJECTS
Authors: Сhaikovskа M. P. , Stoyanov V. M.
Published: March 2023

The article examines the theoretical, methodological and practical aspects of the formation of information and analytical support for marketing risk management of risk protection projects of a commercial bank in the conditions of modern challenges of the uncertainty of the marketing environment and global digital transformations. Requirements for an effective bank risk management system based on modern technological tools and innovative methodological approaches are formulated. The directions of the transformation of risk management paradigms were analyzed, the expediency of a systemic multidimensional approach to the implementation of integrated risk management based on modern international regulatory standards was clarified. The need for the convergence of project management methods in risk management for better prioritization of risks, consistency with the strategic goal of activity, and planning of steps to optimally achieve the goal is substantiated. The marketing orientation of bank risk protection projects is revealed. It is  proposed to expand the list of banks' risks and to transform the weighting coefficients of the existing ones in the conditions of innovative technological transformations in order to strengthen socio-ecological responsibility to society. Particular attention is paid to determining the place of marketing risks in the management system of banks, as a critical element of an effective risk management model. The direction of improving the information and analytical support of the bank's risk protection projects through the implementation of CRM systems as an information communication tool and an information source on marketing risk management is proposed.
ECONOMIC, LEGAL AND ORGANIZATIONAL PRINCIPLES OF PRESERVING STATE SOVEREIGNTY ON THE TERRITORY OF AN ISOLATED COMMUNITY DURING THE HYBRID PERIOD
Authors: Shmulevych P. V. , Maksymenko O. P.
Published: March 2023

The hybridity of the actions of the aggressor country (Russia), disregard for the rules and customs of war, systematic violation of the norms of international humanitarian law require urgent and non-standard solutions on the part of our state in order to preserve the lives of citizens who find themselves in areas of hostilities, in isolated or occupied territorial communities. The state is obliged to direct all available own resources to the effective provision of the rights and freedoms of citizens and the protection of the most vulnerable sections of the population, and not to rely on the self-organization of the population and local self-government. Such labour resources of the State are, in particular, civil servants who work in territorial administrations of state bodies and are physically located in an isolated city. The article carries out an economic and legal analysis of the actual situation in the city of Kherson, which took place in the period between the beginning of the war and the establishment of their own quasi-government by the occupiers. Closed information regarding the approaches, standards and realities of the work of the Home Front Command of the State of Israel was analyzed. Based on the experience of this country, urgent organizational mechanisms for long-term support of the life activity of the city, isolated and controlled by the invaders, through the involvement of local civil servants, who are currently not involved in work, in the system of the Home Front Service, are proposed.
Does Socioeconomic Status Influence Achievement? An analysis of the Performance of Kosovar Students on the 2015 and 2018 PISA Assessment
Authors: Shala Arif , Grajcevci Albulene , Latifi Fadil
Published: March 2023

Socioeconomic status has long been considered an influential factor in student achievement. Similar to existing literature, results of this analysis reveal that socioeconomic status influenced student achievement in the 2015 and 2018 PISA assessments. However, the achievement gap between categories widened between 2015 and 2018. Results reveal that home possessions, school location, parental education
played a role in achievement. Furthermore, students who attended private schools outperformed students in public schools, a gap that widened considerably between assessments. Results of the current analysis reveal the importance of socioeconomic factors in achievement and, the need for policy builders to mitigate this impact.
Student-Centred Instruction in Science and Technology: a Model of Factors at Organizational and Individual Levels
Authors: Pejić Papak Petra , Valenčič Zuljan Milena , Zuljan Darjo
Published: March 2023

To achieve the goals of modern science and technology teaching, it is vital to organize student-centred instruction (SCI). The organization of SCI requires the teacher’s ability to organize cognitively challenging teaching in a stimulating environment. The fundamental purpose of the study was to determine whether the teacher’s organization of SCI was
related to factors at the school level (organizational context) and factors at the
individual level (individual context). We designed a model comprising four sets of factors. The results show a statistically significant correlation between SCI and all four sets of factors.
Methodological Particularities in Research on Contemporary Childhood in Croatia: A Pedagogical – Psychological Perspective
Authors: Dubovicki Snježana , Velki Tena
Published: March 2023

The study aimed to determine the methodological particularities present in research on contemporary childhood. The study methodology involves an analysis of Croatian journals in which the subject of contemporary childhood has been published in the last two years. The inclusion criteria for article analysis were as follows: Social Science discipline, field of Pedagogy and Psychology, participants’ age (from 6 to 14 years) and the visibility of the journal citation. The analysis of the contemporary approach included methodological particularities. The results show that these studies of contemporary childhood do not apply “contemporary” approaches to the examination of childhood.