bluuebunny/crossref_metadata_2025 huggingface dataset:
Rancang Bangun Robot Pemotong Rumput Secara Otomatis dengan Kontrol Smartphone Android Berbasis Arduino Uno
Authors: Yusman Yusman , Mellyssa Widdha , Salahuddin Salahuddin , Mukhlisin Kharazzi , Mualla Said
Published: November 2024

Kegiatan merawat rumput halaman rumah, taman rekreasi atau lapangan sepakbolaperlu dilakukan secara rutin untuk menjaga agar tampak rapi dan asri. Penggunaan alat pemotong rumput yang lazim digunakan adalah dengan cara digendong atau alat pemotong dengan cara didorong yang membutuhkan tenaga manusia lebih ekstra. Tujuan dari penelitian ini adalah merancang bangun robot pemotong rumput yang dapat bekerja secara otomatis yang dikontrol dengan Smartphone Android berbasis arduino. Robot pemotong rumput ini dapat bekerja dalam dua mode yaitu mode manual dan mode otomatis. Pada mode manual robot akan bekerja memotong rumput dengan cara dikendalikan oleh user menggunakan joystick android, dan pada mode otomatis robot akan memotong rumput secara autonomous dengan bantuan frame untuk memotong rumput halaman hingga batas jarak sensor dengan dinding frame yang telah ditentukan. Robot ini menggunakan mikrokontroler ATMEGA 2560 dan software aplikasi yang digunakan adalah arduino robot ini juga berbasis android yang dan dirancang dengan menggunakan joystick android sebagai pengendalinya. Hasil pengujian menunjukkan bahwa robot mampu memotong rumput dengan mode manual dengan luas maksimum 2100 m2 selama 118,77 detik dan kecepatan rata-rata 0,4942 m/s. Untuk mode otomatis robot dengan bantuan frame sepanjang 7,35mmampu memotong rumput dengan luas maksimum 102,9 m2 selama 70,94 detik.
Expert information processing system for traffic light system decision-making with adaptive conditional tram priority
Authors: Rebezyuk Leonid M. , Lytvynenko Mykhailo
Published: November 2024

The expert information processing system was proposed for a traffic signal system at a multimodal intersection with three types of traffic users: public transport (tram), pedestrians, and general traffic. The system considers the dynamics characteristics of the tram after it is detected by the entry detector of the intersection and is based on a set of fuzzy decision-making rules for decision-making on the time parameters adjustment of the traffic signal plan based on the compatibility of traffic direction signals and the importance of traffic requests. For general traffic signals, the solution is to extend or terminate the permissive signal for a certain group of traffic directions controlled by this signal. Decisions for tram signals, depending on the proximity of the planned permissive signal and the importance of the associated request, can affect both the time parameters of the immediate traffic signal plan and change the overall signal sequence and/or their duration. The conditional priority involves taking into account possible conflicts be-tween the decisions from the public transport signals or from public transport and general traffic signals, which are handled by the corresponding production rules proposed in the paper. The traffic light plan is changed iteratively in an acyclic manner, considering the degree of confidence of the decision obtained by a two-level fuzzy inference model based on the Mamdani algorithm, the second level of which is responsible for determining the signal sequence and the first level for their time parameters. The information processing model is implemented and validated using SUMO urban mobility simulation tool for moderate and saturated transport demands for a non-trivial intersection with synthetic traffic demand. The experimental results demonstrate the applicability of the system in conditions of a saturated transport demand, allowing to reduce the negative impact on the general traffic flows without a significant increase in the time losses of tram passengers compared to the adaptive unconditional way of implementing tram traffic light priority.
Modernization blood service’s specialized information systems
Authors: Mikhnova Alina V. , Mikhnov Dmytro K. , Chyrkova Kateryna S.
Published: November 2024

The object of the research is a mathematical apparatus for searching for the optimal variant of the project solution for the modernization blood service’s specialized medical information systems, which allows determining ways to increase the efficiency of blood services attached to limits of defined expendable resources by reducing the number of manual data entry operations during business processes with the help of appropriate organizational and technical components of specialized medical information systems.
The purpose of the development of a mathematical apparatus for searching for a variant of a project solution for the modernization blood service’s specialized medical information systems is a formalized presentation of the problem finding an optimal variant of a project solution for the modernization blood service’s specialized medical information systems, taking into account the components of business processes, components of specialized medical information systems, performance indicators of blood services, partial and generalized indicators of the functioning of specialized medical information systems, expendable resources for the implementation of a variant of the project solution for the modernization specialized medical information systems or a separate organizational and technical component.
To solve the problem, a process-oriented approach to the organization of a specialized medical information system with a decomposition into organizational and technical components was used, on the basis of which a formalized presentation of the optimal version of the project solution for the modernization a specialized medical information system by increasing the degree of automation of the relevant organizational and technical components was proposed, that provides the maximum integrated indicator of the functioning of the specialized medical information system, which correlates with the actual key socially significant indicators of the activity of the blood service. The ER model of the modernization of the specialized medical information system was designed, which allows to graphically present the structure of the search for the optimal variant of the project solution for the modernization of the specialized medical information system.
The results of the study were used to find the optimal project solution for the modernization of the specialized medical information system of the CNE KHRC "Regional Blood Service Center", which made it possible to improve the key socially significant indicators of the blood service 's activity by determining the optimal data entry’s degree of automation on each organizational and technical component of the specialized medical information system considering the existing expendable resources for modernization.
Study of the ensemble of machine learning models in medical diagnostics
Authors: Panforova Iryna Yu. , Butska Anastasiya S.
Published: November 2024

The research discusses the use of machine learning models for medical diagnosis, which is of great significance in modern medicine. The focus of the article is on the use of ensemble models in which convolutional neural networks (CNN), models for classification and regression tasks (SVM), and long short-term memory recurrent networks (LSTM) are involved. The effectiveness of these methods is compared both individually and in an ensemble approach in the context of improving the accuracy of medical diagnosis.
Despite numerous studies discussed in the article combining multiple models simultaneously to enhance prediction accuracy, the topic of ensemble modeling in machine learning for medical diagnosis remains relevant. Previous research has proposed a wide range of ML models for analyzing electronic medical records, with most studies using k-means, KNN, and SVM.
Research results indicate that the use of an ensemble model that combines the mentioned ML methods leads to an increase in diagnostic accuracy. Even though individual ML methods may be effective in specific areas, their combination into an integrated structure allows overcoming limitations that may arise when using only one method.
The advantages and disadvantages of the chosen ensemble model are discussed. The main advantage lies in the increased accuracy of medical diagnosis, which can lead to early detection of diseases and, consequently, improve treatment outcomes. On the other hand, drawbacks may include the complexity of developing and tuning the ensemble approach, as well as computational resource requirements.
It is important to note that the obtained results suggest that combining different models can significantly improve the quality of disease diagnosis. This is a significant contribution to the development of the medical field, as it can contribute to the early detection and effective treatment of various pathologies.
Fuzzy decision-making model for automatic mail sorting line
Authors: Grebennik Igor , Kovalenko Oleksii
Published: November 2024

The object of this research is the implementation of fuzzy control in an automated mail sorting line.
To decrease the processing time of postal items, automated sorting lines with conveyor belts are used, which carry out transportation to predefined loading points. The principal limitation of such systems is the decision-making model's inherent ambiguity when implementing the designated sorting logic.
To overcome these shortcomings, a fuzzy decision-making model for automated sorting lines has been developed. This model allows implementing the sorting logic of postal items to specified loading points under predefined conditions. For this, the fuzzy classification of objects based on their parameters has been formalized, with loading points determined for each class. The fuzzy inference process stages have been formalized based on the Takagi-Sugeno-Kanga algorithm. The input and output fuzzy linguistic variables have been identified, and a rulebase for fuzzy inference has been formalized for fuzzification. For defuzzification, the center of gravity calculation for singletons has been chosen.
Three criteria have been defined to implement the sorting logic, facilitated by the fuzzy inference rulebase. The first criterion sorts items to loading points considering cost evaluation, irrespective of weight and dimensions. The second criterion considers weight evaluation independent of dimensions. The third one takes into account the combined evaluation of weight and dimensions.
The developed model was tested using the Matlab environment. The simulation confirmed the model's functionality and the sorting management criteria for postal items to loading points.
The case-base reasoning to support decision-making in humanitarian response
Authors: Bilova Tetiana , Dyomina Victoriya , Pobizhenko Iryna , Ostapenko Olena
Published: November 2024

The object of the study is decision-making processes in humanitarian response. It is noted that certain experience of humanitarian response can be used in similar situations in the future. It is determined that humanitarian response processes have the following features: complexity and dynamism; decision-making takes place in conditions of uncertainty; emerging situations require a prompt response.
There is a lack of an integrated approach to the creation of decision support systems in humanitarian response. Current research is related to decision-making in the framework of predicting and eliminating the consequences of natural disasters, man-made disasters and armed conflicts, and humanitarian issues are considered as related.
Case-base reasoning was chosen as a representation of knowledge about humanitarian response processes. This method allows using previous decision-making experience without performing a detailed analysis of the subject area and adapting the accumulated knowledge to new situations.
The functions and structure of an decision-making support system in humanitarian response are defined. The system uses the case-base reasoning module to represent knowledge, which simulates human reasoning and is based on the effective use of existing experience.
The module implements a modified case-base reasoning. The parametric representation of a case is extended by the indicator of the use of precedents. The structured representation of the case solution in the form of a sequence of steps, each of which has its own characteristics, allows for the adaptation of several cases that are close to the current situation.
The results of the study were experimentally verified by training the module on the initial data set. Fifty cases were generated for the experiment, describing decision-making in the provision of drinking and industrial water to the population. The training results show that when the cases database is filled with fifty cases, the classification quality is 89%. The results obtained allow us to conclude that it is expedient to structure knowledge about humanitarian response in the form of cases with the possibility of further adaptation to new situations and training.
Development of a business model to improve the efficiency of hiring new employees to IT companies
Authors: Jarmak Valeriy
Published: November 2024

The object of the research is the process of increasing the efficiency of hiring new employees to IT companies, which is considered as one of the measures of continuous improvement of IT project management processes.
Hiring talented and motivated IT specialists is seriously complicated nowadays due to the oversaturation of the labor market in the IT industry with candidates who are either exclusively financially motivated or have a low level of qualifications. The consequence of this problem is an increase in time and money spent on identifying and selecting for further processing a subset of resumes of specialists who will be relevant to the needs of the IT company. Therefore, the study of models of active strategies for conducting career guidance activities among future candidates for work in the IT industry is relevant.
The purpose of the study is to create a business model for professional orientation of candidates for positions in IT companies. This business model should combine the advantages of basic business planning models and flexible business development methods, taking into account the peculiarities of the process of professional orientation in the IT industry of Ukraine.
As a basis for this business model, it is proposed to use the Business Model Canvas. Within this model, to increase the flexibility of activities related to the presentations of IT professions, it is proposed to use the Walt Disney method. During the research, Walt Disney's derivative method was modified by abandoning his first stage use of the role of the Dreamer and instead using the role of the Optimist. A person in the role of an Optimist should determine the advantages, positive aspects, favorable opportunities of the presentation object, etc.
The results of the modification of Walt Disney's method were used during the development of the Business Model Canvas for the process of increasing the efficiency of hiring new employees to IT companies. The key activities of the Business Model Canvas were determined, the sequence of their implementation was established, which allows eliminating the shortcomings of individual activities.
Development of a method of forecasting the results of the performances of athletes and teams in sports competitions
Authors: Yevlanov Maksym , Vasyltcova Nataliia , Uvarova Victoriya
Published: November 2024

The object of the research is the task of forecasting the results of the performances of athletes and/or teams in competitions. The expediency of solving the problems of long-term forecasting in sports activities has been determined. A comparative analysis of the mathematical methods used to predict the results of sports competitions was conducted. The groups of mathematical methods that, according to the results of the comparative analysis, are determined to be the most suitable for solving the problems of long-term forecasting of the performance results of athletes and/or teams are highlighted. The theoretical and applied relevance of solving similar problems is substantiated.
Machine learning methods and methods based on Bayesian models were chosen as the main research methods. The peculiarities of the use of these methods when solving the problem of long-term prediction of performance results are determined. Bayesian estimates of the probability of success and failure of an athlete's performance at a competition are proposed. A method for solving the problem of long-term prediction of performance results has been developed, which combines the advantages of machine learning methods and methods based on Bayesian models. In contrast to the practices of solving the forecasting problem existing in Ukraine, the developed method allows taking into account not only historical information about competitions that took place before, but also information about future types of competitions.
The experimental verification of the obtained scientific results was carried out while solving the problem of forecasting the results of athletes' performances in World Cup competitions for the Federation of Underwater Sports and Underwater Activities of Ukraine. The purpose of solving this problem is to increase the efficiency and determine the priority of athletes in the next competitions of this type. The course and results of solving the problem for the leading athletes of the Federation of Underwater Sports and Underwater Activities of Ukraine were considered.
Особенности формирования сухого вещества у видов и сортотипов люцерны в зависимости от длительности использования травостоев и распространенности вирусно-фитоплазменных болезней
Authors: Сайфутдинова Л.
Published: November 2024

В 2019-2023 гг. в коллекционном питомнике в Центрально-Черноземном регионе изучали 52 сортообразца люцерны, относящиеся к видам Medicago falcata, M. sativa и 3 сортотипам M. varia: желтогибридному, пестрогибридному и синегибридному. Исследованы особенности распространения комплекса фитоплазменных болезней и формирования урожайности сухого вещества у видов и сортообразцов люцерны различного эколого-географического происхождения. Установлено достоверное влияние генотипа сортообразцов на формирование урожайности сухого вещества как по укосам, так и в целом за 5 лет жизни --- достоверно на 68,8 % показатель определяется фактором «генотип», на 22,3 % --- фактором «год жизни травостоя», на 0,4 % --- взаимодействием факторов. По степени распространенности вирусно-фитоплазменной инфекции в среднем за 5 лет жизни травостоев сортообразцы люцерны можно расположить следующим образом: M. falcata (4,9 %) > M. varia -желтогибридный (9,0 %) > M. varia -пестрогибридный (9,8%) > M. varia-синегибридный (16,9 %) > M. sativa (28,5 %) при варьировании признака 9,1-23,2%. Распространенность вирусно-фитоплазменной инфекции в посевах люцерны достоверно на 21,0 % определяется фактором «генотип», на 54,4 % --- «год жизни травостоев», на 17,0 % --- генотип-средовыми отношениями. Полученные данные необходимо учитывать в селекционной работе для оптимального подбора пар для гибридизации, при формировании питомников поликросса, а также при поиске источников ценных селекционных признаков для создания новых высокопродуктивных сортов люцерны.
Фенотипическое проявление элементов продуктивности у клевера ползучего из различных местообитаний юга Среднерусской возвышенности
Authors: Сопина Н. , Печегин А. , Осипян Б. , Печегина Ю. , Усольцева Е. , Биюшкина А.
Published: November 2024

Оценены и классифицированы 36 дикорастущих образцов клевера ползучего (Trifolium repens L.), отобранных в местах интенсивного выпаса скота, приуроченных к поймам рек, днищам балок и меловым обнажениям юга Среднерусской возвышенности, как исходного материала для селекции сортов газонного и лугопастбищного направлений. Образцы оценивали в культуре в 2021-2023 гг. в 3 закладках опыта стандартным методом без повторностей. Стандарт – сорт Нанук. Проявление 16 основных селекционно-ценных признаков и свойств изучали у растений 2-го года жизни. Популяции клевера ползучего из различных по почвенным условиям местообитаний обладают значительной изменчивостью и могут быть объединены в 4 кластера. По комплексу признаков и свойств наибольшей близостью к селекционному сорту Нанук обладают образцы, объединенные в кластер II. Наиболее сильно отличаются от стандарта образцы, входящие в кластеры III и IV, которые уступают сорту Нанук по длине столонов на 11,8-12,6 см, ширине центрального листочка – на 0,86-0,97 см, массе 1000 семян – на 0,25-0,27 г, урожайности семян – на 17,2-18,9 г/м2. При этом выявлена сильная положительная корреляционная связь между толщиной столона и количеством цветков в соцветии (rS = 0,945); количеством цветков в соцветии и семян на 1 головку (rS = 0,949); количеством семян на 1 головку и урожайностью семян (rS = 0,966) при p<0,05.
Разработка технологической линии комбикормов для ценных пород рыб с применением мультиэнзимных комплексов
Authors: Василенко В. , Фролова Л. , Дорохин Р. , Кочарьян А. , Еремин И.
Published: November 2024

Выращивание осетровых рыб в искусственных водоемах является единственной реальной возможностью сохранения их численности для использования в питании человека. При искусственном кормлении рыб особое внимание необходимо уделять качественному составу комбикорма для обеспечения его максимальной конверсии и снижения экологической нагрузки на окружающую среду. В настоящее время ограничен ввоз импортных компонентов комбикормов, таких как рыбная и мясная мука и премиксы, что накладывает ограничения на разработку высокоэффективных рецептур и производство качественного рыбного сырья для рыбоперерабатывающей промышленности. В Российской Федерации существует значительный резерв источников нетрадиционного для кормопроизводства сырья, которое при соответствующей обработке, например методами экструдирования и экспандирования, может служить альтернативной заменой дорогостоящего импортного сырья. Доказано, что экструзионная обработка исходных компонентов эффективно повышает питательную ценность получаемого аквакорма. Однако внесение подобных компонентов требует изменения технологического процесса производства комбикормов и соответственно создания новых технологических линий. Предложена линия комбикормов для ценных пород рыб с применением мультиэнзимных комплексов, в которой используется перьевая мука как источник высококачественного белка, содержащего комплекс незаменимых для рыб аминокислот., Полученные корма для осетровых рыб полностью соответствуют предъявляемым требованиям и минимизируют стоимость комбикорма на 6-9 %. Установлены близкие результаты по скорости роста осетра, развитию, конверсии корма и выживаемости в сравнении с лучшими на российском рынке аналогами комбикормами.
Presentación inusual de trauma por arma de fuego. Embolización venosa mixta. A propósito de un caso
Authors: Cortés-Portilla Oskar Francisco , Cristancho-Torres Laura , Palacios-Rodríguez Helmer Emilio , De Paz-Cobo David Andrés
Published: November 2024

Introducción. El trauma es una de las principales causas de muerte a nivel mundial. Dentro de los mecanismos de trauma se encuentran las heridas penetrantes por arma de fuego. Entre las heridas que pueden ocasionar mayor morbilidad y mortalidad están las heridas vasculares, en las que el equipo de emergencias debe actuar oportunamente para lograr la supervivencia del paciente. Una de las formas de presentación menos frecuente es la embolización de los proyectiles por los vasos sanguíneos.
Caso clínico. Se presenta el caso clínico de un paciente quien desarrolló una embolización venosa del proyectil desde la vena subclavia izquierda hacia la vena ilíaca interna izquierda, sin confirmación de defectos de las cámaras cardíacas, lo que constituye una embolización retrógrada.
Resultados. A consecuencia de la migración venosa mixta del proyectil, la única complicación que tuvo este paciente fue un hemoneumotórax.
Conclusión. El trauma por heridas de arma de fuego es una de las primeras causas de lesiones de causa externa en nuestro país. Una complicación inusual es la embolización vascular del proyectil. No existe un consenso de manejo, pero dado el riesgo de embolización anterógrada con complicaciones adicionales, se prefiere la extracción del proyectil. Es un tema infrecuente, pero de conocimiento necesario para el médico de emergencias y el cirujano.
Resiko Adiksi Gadget Berdsarkan Citra MRI Brain di Kelurahan Genuk Kecamatan Ungaran Barat Kota Ungaran
Authors: Tsania Novia Putri , Andriani Intan
Published: November 2024

Gadget pada remaja tidak hanya kebutuhan untuk akademis, namun juga sebagai sarana untuk berekreasi.  Masyarakat Indonesia masih belum menganggap adiksi gadget sebagai patologikal dan belum menyadari dampak negatif dari adiksi gadget pada karang taruna. Pencegahan dini dan menurunkan resiko remaja dengan adiksi gadget diperlukan instrumen yang dapat memperlihatkan kelainan pada brain dengan melihat hasil citra MRI Brain dan tingkat konsentrasi metabolit tubuh untuk menegakkan diagnosa yang tepat dan akurat dengan menggunakan MRS.  Pemeriksaan MRS merupakan salah satu pemeriksaan yang mampu memperlihatkan tingkat metabolit tubuh pada remaja dengan adiksi gadget dan bersifat non invasif karena tidak menggunakan radiasi sehingga sangat aman bagi tubuh manusia. Penyuluhan resiko Adiksi Gadget ini diharapkan dapat menurunkan angka remaja dengan adiksi gadget. Remaja dengan adiksi gadget kemungkinan mengalami perubahan pada hasil citra MRI dan perubahan pada nilai konsentrasi metabolit. Metabolit tubuh ini bisa dilihat atau dideteksi menggunakan software penunjang MRS pada modalitas MRI.
Sosialisasi Komunikasi Kebencanaan dalam Meningkatkan Kesadaran Mitigasi Bencana Alam pada Siswa Sekolah Dasar 09 Cibadak Sukabumi
Authors: Muhamad Pagi , Sentosa Angela Jani , Panggabean Sahara Uli , Ramadhan Alfajri , Dharmawicaesa Narindra , Otami ⁠Dika
Published: November 2024

This community service aims to raise disaster mitigation awareness among students at SDN 09 Cibadak, Sukabumi, an area prone to natural disasters such as earthquakes and landslides. Using a participatory approach, the program was conducted through interactive lectures and disaster simulations. Evaluation was carried out using pre-tests and post-tests to measure the improvement in students' knowledge. The results showed a significant increase in students' understanding of disaster mitigation steps. The disaster simulation effectively trained students to respond to emergency situations. This activity is crucial for building student preparedness and fostering a disaster-aware culture at school and in the surrounding community, potentially minimizing the risk of casualties in future disasters.
Pengenalan Fauna Penghuni Ekosistem Mangrove Bagi Anak-Anak Usia Sekolah di Kampung Kondo, Distrik Naukenjerai
Authors: Merly Sendy Lely , Untari Untari , Tuhumena Jeremias , Redu Silas Tanggu , Ismanto Heru
Published: November 2024

The mangrove forest ecosystem is an important ecosystem in coastal areas. It functions as a greenbelt and is able to provide a source of food for people living in coastal areas. Even the mangrove ecosystem is a habitat for various fauna that inhabit the ground floor, trees, and also the waters in this ecosystem. The role of early childhood is very important, by providing a proper understanding of both the types of fauna that inhabit the mangrove ecosystem on the coast of Kampung Kondo and what are the benefits of each fauna, children will be able to recognize the potential they have, utilize and manage the resources they have based on local wisdom they have. The method used is the exploring method where together with the children enter the mangrove forest area and the samples found are immediately identified and, together they pay attention to the habitat of the fauna found. The results of this activity are that children are able to identify 5 gastropods species, 1 shellfish species, 2 crab species, and 1 fish species, and ultimately, understand the habitat of each fauna.
Tube array for the multiplex detection of sweetpotato viruses
Authors: Wanjala Bramwel Waswa , Ateka Elijah M. , Miano Douglas W. , Low Jan W. , Fuentes Segundo , Adams Ian P. , Kreuze Jan F.
Published: November 2024

Sweetpotato is an important staple food crop affected by viruses causing significant yield losses. Sweetpotato virus diagnosis is hindered by low titers, uneven plant distribution, inhibitors, mixed infections, and diverse viral strains. Current serological tests are not sensitive enough to reliably detect viruses directly from sweetpotato and prior grafting onto Ipomoea setosa is a prerequisite before testing by nitrocellulose membrane enzyme-linked immunosorbent assay (NCM-ELISA). The study evaluated the effectiveness of STAR (Sweetpotato virus Tube-Array) microarrays for simultaneous detection of sweetpotato viruses. The operational performance of STAR assay was compared with that of the conventional method (NCM-ELISA). Twenty-five samples previously indexed by I. setosa and tested with NCM-ELISA were selected and tested in parallel in Lima and Nairobi. The agreement between STAR and NCM-ELISA was measured using Cohen’s kappa index. Reliability of the assay between Labs was accessed by Bland-Altman plot. Furthermore, we estimated the turnaround time and cost between STAR and NCM-ELISA. Cohen’s kappa index revealed a disagreement between NCM-ELISA and the STAR assays. Bias was occasionally detected by STAR which is more sensitive and detects more viruses not detected by NCM-ELISA. Concordance analysis displayed by the Bland-Altman plot and regression analysis results from the two Labs agreed closely. STAR costs approximately USD 70 per sample and detects up to 15 viruses while grafting indexing/NCM-ELISA costs USD 130 to test 10 viruses per sample. STAR testing is performed directly from sweetpotato tissues and does not necessitate grafting onto Ipomoea setosa prior to testing as is the case with NCM-ELISA. STAR based testing holds promise for the simultaneous detection of sweetpotato viruses given its satisfactory sensitivity, specificity, accuracy, and short time to results. STAR could be suitable for routine diagnosis of sweetpotato viruses and can be utilized in epidemiological studies, quarantine, and certification of the sweetpotato seed system.Key wordsSTAR, microarray, multiplex, concordance, accuracy, NCM-ELISA, Sweetpotato viruses, virus detection.
Lanes, Clusters, Lines of Sight: Modelling diagnostic eyecare clinics to improve patient flow
Authors: Sailer Kerstin , Utley Martin , Pachilova Rosica , Fouad Ahmed Tarek Zaky , Li Xiaoming , Jayaram Hari , Foster Paul J.
Published: November 2024

Lengthy waiting times for ophthalmology appointments in the UK National Health Service (NHS) increased further in the immediate aftermath of the Covid-19 pandemic, necessitating a different approach to triaging patients safely and at speed. Moorfields Eye Hospital NHS Trust therefore opened an additional diagnostic hub designed with a linear spatial layout and patient flow system, which is analyzed in this paper in comparison to an existing clinic. We integrate direct observations of patient flows, and an architectural layout analysis based on space syntax methods with queuing simulations from operations research and show that the two clinics operate differently and that both clinics have their advantages and disadvantages. The newly opened clinic with a lane system supports flows and coordination by line of sight between stations, which contrasts with a lack of sightlines in the existing clinic. The latter layout with clusters of stations compensates by enabling a more organic flow especially in conjunction with experienced technicians, which is beneficial when the clinic gets busy. When high patient load is simulated in the queuing models, the lane system results in slightly bigger bottlenecks and longer clinic durations. An ideal allocation of the number of stations to diagnostic activities based on clusters is suggested. This work stands in the tradition of combining architectural and operations research. By reflecting on the variability of diagnostic processes found in our observations, we contribute to the understanding of routines as performative. We also add insight to the growing field of evidence-based design, particularly by highlighting the importance of line-of-sight relationships in ophthalmology.
From Offer to Close: A Machine Learning Approach to Forecast Real Estate Transaction Outcomes
Authors: Zhao Yu
Published: November 2024

Accurately forecasting whether a real estate transaction will close is crucial for agents, lenders, and investors, impacting resource allocation, risk management, and client satisfaction. This task, however, is complex due to a combination of economic, procedural, and behavioral factors that influence transaction outcomes. Traditional machine learning approaches, particularly gradient boosting models like Gradient Boost Decision Tree, have proven effective for tabular data, outperforming deep learning models on structured datasets. However, recent advances in attention-based deep learning models present new opportunities to capture temporal dependencies and complex interactions within transaction data, potentially enhancing prediction accuracy. This article explores the challenges of forecasting real estate transaction closures, compares the performance of machine learning models, and examines how attention-based models can improve predictive insights in this critical area of real estate analytics.
Tu Designing Smart Roads with Climate-Responsive Materials for Enhanced Durability and Maintenance
Authors: Hatami Dezdarani Vahid , Pour Mohammadi Mohammad Hossein
Published: November 2024

With the increasing severity of climate change and the rising traffic volume, the need for designing smart roads that can withstand environmental conditions has gained significant importance. This research focuses on the utilization of climate-responsive materials in road construction that can autonomously react to climatic variations, thereby enhancing the durability and efficiency of roadways. A comprehensive examination of various smart materials, including nanocomposites, self-healing materials, and temperature-sensitive coatings, is conducted to ascertain their efficacy in modern infrastructure.
A key aspect of this research is the evaluation of the performance of these materials under diverse climatic conditions and their impact on reducing maintenance costs. Specifically, this study emphasizes how the application of these materials can improve road performance against environmental factors such as extreme temperatures, humidity, and heavy precipitation. The anticipated results indicate a substantial reduction in damage caused by harsh environmental [1]conditions, directly leading to increased road longevity and decreased maintenance expenses.
Moreover, this study will explore the social and economic implications of employing these materials in infrastructure projects. For instance, the diminished need for frequent repairs and maintenance can free up financial resources for other projects,
ultimately contributing to more sustainable development. Furthermore, as smart roads are expected to enhance safety and comfort for drivers, this will positively affect the quality of life for road users.
The methodology of the research includes numerical simulations and field tests to assess material performance under real-world conditions. Data obtained from these experiments will be used to optimize road design and propose innovative solutions aimed at improving infrastructure performance [2]. Overall, this research represents a significant step towards the development of sustainable and resilient road infrastructure capable of adapting to climatic changes, and it can provide guidance for road designers and managers to implement more effective transport solutions.
Ultimately, the findings of this study can serve as a model for other infrastructure projects across various geographical regions and facilitate the transfer of innovative technologies in this field. Given the impending environmental challenges, the development of smart roads and the use of advanced materials will be justified not only economically but also socially.
Desirability biases perceptual decisions in the aversive domain
Authors: Kim Haena , Liu Alicia , Leong Yuan Chang
Published: November 2024

Perceptual judgments are often influenced by goals and preferences, resulting in biased judgements that deviate from objective reality. When presented with ambiguous images, observers are biased to report seeing images associated with rewards. However, it remains unclear whether this is driven by a bias toward stimuli that people are motivated to see (i.e., desirability) or stimuli that are motivationally significant (i.e., relevance). As rewards are both desirable and motivationally relevant, these effects are not easily dissociated in a reward context. This study investigates the effects of desirability and relevance on perceptual judgments in an aversive context involving financial losses. Across two experiments conducted between 2023-2024, participants completed a visual categorization task where ambiguous stimuli were associated with a large financial loss. Participants’ perceptual judgments were biased away from stimuli associated with the loss, indicating a desirability bias. Drift diffusion model analyses revealed that this bias was due to a shift in the starting point of evidence accumulation, such that participants required more evidence to commit to a response associated with an undesirable outcome. The bias in starting point correlated with individual differences in punishment sensitivity but not reward sensitivity, highlighting how individual traits shape motivational effects on perceptual decisions. Results replicated across an in-lab sample and a larger online sample. Altogether, our study provides robust evidence of a desirability bias in perceptual decisions involving financial losses, identifying both the computational mechanisms and trait-level differences that influence how people decide what they see when faced with the prospect of undesirable outcomes.
A Qualitative Analysis of Lived Experiences, Mental Health Treatment Needs, and Psychotherapeutic Applications Among Veterans with Long COVID
Authors: Boucher Caroline , Glatt Sofie , Silver Chana , Chennapragada Lakshmi , Sullivan Sarah , Dichiara Ariana , Sokol Yosef , Patel Sapana , Goodman Marianne
Published: November 2024

Long COVID remains a pressing health concern among Americans, with current data suggesting that 45% of those infected by COVID-19 experience at least one symptom of Long COVID. Veterans are a particularly at-risk population due to their unique demographic characteristics and lived experiences. Despite this, there has been a lack of treatment development for Long COVID that targets mental health symptoms and is veteran-specific. There is a need for effective treatments to help veterans cope with a Long COVID diagnosis and recovery. This quality improvement project aims to gain insight into the lived experiences and mental health needs of veterans with Long COVID to help inform future treatment development. A sample of 21 veterans (57% Male, 67% Black, 43% Hispanic) participated in qualitative interviews where they were asked 23 questions about their experiences living with Long COVID and seeking medical treatment, as well as their ongoing mental health needs. Qualitative data was extracted from these interviews and analyzed. Four main themes were identified: interpersonal concerns and challenges with social interaction; difficulties with day-to-day living; barriers and facilitators to accessing medical treatment; and mental health effects and attitudes towards psychotherapy. Veterans described significant impairments in functioning, as well as feelings of isolation and loneliness. These findings demonstrate the need for a psychotherapeutic intervention that can facilitate interpersonal connection, improve functioning, and decrease psychiatric symptoms.
Mitigating AI Bias in School Psychology: Toward Equitable and Ethical Implementation
Authors: Lockwood Adam
Published: November 2024

The integration of Artificial Intelligence (AI) into school psychology is evolving rapidly, presenting both opportunities and challenges. AI has the potential to enhance educational and mental health services by facilitating data-driven decision-making, streamlining administrative tasks, and offering personalized interventions for students. However, biases inherent in AI systems—reflecting the prejudices of developers and historical data—pose significant risks of exacerbating systemic inequalities. This paper examines AI’s historical context, current applications in education, and specific uses within school psychology. It also discusses the socio-political factors contributing to algorithmic biases, data privacy concerns, and language/cultural inequities in AI systems. Recommendations are offered to mitigate AI biases, emphasizing the importance of diverse representation in AI development, comprehensive policy formation, transparency, and community involvement. Addressing these concerns is crucial for ensuring that AI contributes equitably to student success.
Not to Worry? The Relation between Parental Worry, Self-Efficacy, and Parenting Behaviors in the Context of Adolescent Depression
Authors: Veenman Myrthe , Janssen Loes H. C. , van Houtum Lisanne Antonetta Elisabeth Maria , Wentholt Wilma , Wever Mirjam , Tollenaar Marieke , Verkuil Bart , Fried Eiko I , Elzinga Bernet M.
Published: November 2024

Adolescent depression is impactful for adolescents and for their parents. High worry and low self-efficacy may be rather prominent among parents with adolescents with depression, but how this may in turn have an effect on parenting behaviors, such as warmth and criticism, is not well known. In a healthy control (i.e, 80 adolescents, M_age = 15.90, SD_age = 1.35; 151 parents, M_age = 49.04, SD_age = 5.87) and depression sample (i.e., 34 adolescents with depression, M_age = 15.65, SD_age = 1.54; 58 parents, M_age = 50.10, SD_age = 5.30), we estimated Gaussian graphical network models on adolescent-reported affect states (i.e., happy, relaxed, sad, & irritated), adolescent- and parent-reported parenting behaviors (i.e., warmth, understanding, listening, criticism, dominance), and parent-reported parental worry and self-efficacy. Parents of adolescents with depression reported higher levels of worry, but not less self-efficacy. In both samples, parent-reported worry was positively related to adolescent-reported sadness and parent-reported parental criticism. Moreover, parent-reported self-efficacy was positively related to adolescent- and parent-reported parental warmth. Only in the depression sample, parent-reported worry was positively related to adolescent-reported parental warmth. Parental worry, self-efficacy, parenting behaviors and adolescent affect were interrelated with considerable differences between the control and depression sample. As a next step, studies with more intensive daily assessments may yield individual family analyses, while also accounting for contextual factors, to further increase our understanding of the relation between parental worry, self-efficacy and parenting behaviors in the context of adolescent depression.
Workplace Training Unpacked: Labor Market Competition and Investment in General Skills
Authors: Albanese Mattia , Aliberti Manfredi
Published: November 2024

Skills acquired on the job, whether general or industry-specific, significantly influence workers' labor market outcomes. Workers with general skills tend to have higher re-employment prospects and greater resilience to economic shocks. Using novel data from a recent policy intervention in the Italian labor market, we develop a new measure that captures the tasks taught in firm-provided training for individual workers. This measure enables us to examine the relationship between labor market competition and firms' decisions to invest in general versus industry-specific skills. Our findings indicate that, as theory predicts, workers in more competitive labor markets receive less general training.
Ethnic Movement in Nepal: Interactions Between State and Non-State Actors
Authors: Kaini Tika Raj , Rai Menu
Published: November 2024

This paper aims to explore the nature and role of ethnic movements taken place in Nepal. It basically highlights the pattern of interactions between state and non-state actors participated in ethnic movements. In the backdrop of the essence of rise and extent of influence, authors have explored the result experienced by the participants in this movement. It has further depicted the realms of change induced in the causation of ethnic movement. Trajectories of movements, forms of these movement, focus of movements and the collectivity generated in movement have also been investigated here in this paper.
Societal Transformations Aftermath COVID-19: An Overdue Exploration of Positive and Negative Impacts
Authors: Joshi Yashoda Bhatta
Published: November 2024

COVID-19 pandemic has showcased profound changes across human society, altering various facets of social life. Beyond its immediate health implications, the pandemic has brought about powerful social transformations reshaping interpersonal dynamics, work patterns, and community adaptability. This research article examines multifaceted impact of COVID-19 on societies globally, considering its both positive and negative implications. Through a comprehensive review of literature and analysis of real-life scenarios, the study explores how the pandemic has reshaped social structures, behaviors, and attitudes. The paper concludes suggesting that the pandemic has deeply and diversely impacted the lives of people in general across the geographical boundaries by a complex interplay of consequences, highlighting the need to continuously navigate the post-pandemic social landscape.
A Study Of Association Of Intra-Abdominal Pressure With Severity And Outcome In Patients Of Emergency Laparotomy
Authors: Kurra Amit , Sukhadia Mukta , Thomas Nimil Mary , Sethi Deepak , Sharma Navaratna
Published: November 2024

Introduction: The present study is done to study the association of intra-abdominal pressure with intra-operative findings and postoperative surgical complications in patients of emergency laparotomies so that timely and appropriate interventions can be planned and administered.
Methods: The study was done on 84 patients. The intra-abdominal pressure was measured indirectly by measuring the pressure within the urinary bladder via Foley's catheter.
Results: There was positive association between the higher grades of IAP and intra-abdominal contamination and gangrenous bowel, the mean value of IAP being 20.4 mmHg. A statistically positive association was also observed between preoperative IAP and post-operative complications, the mean IAP ≥19mmHg.
Conclusion: There is a significant positive association of raised pre-operative intra-abdominal pressure with intra-operative finding of gangrenous and edematous bowel and postoperative surgical complications.