bluuebunny/crossref_metadata_2025 huggingface dataset:
IDENTIFICACIÓN AUTOMÁTICA DE CÁNCER DE PIEL APLICANDO MACHINE LEARNING
Authors: Florez Fuentes Anderson Smith , Guzmán Cabrera Rafael , Vargas Rodriguez Everardo
Published: July 2023

En la actualidad la implementación del machine learning en la medicina, especial en la oncología, se ha convertido en una herramienta clave para la detección de malformaciones, infecciones, problemas cardiacos, cáncer, entre otros, anomalías del cuerpo humano qué al aplicar aprendizaje automático, estos procesos se convierten en herramientas que fortalecen el diagnóstico médico. En este trabajo se presenta una revisión de la literatura y los resultados obtenidos de una implementación en Python para llevar a cabo la clasificación de imágenes médicas con presencia de cáncer de piel. Se utilizaron cuatro métodos de aprendizaje distintos: máquinas de vectores de soporte, vecinos más cercanos, redes neuronales y árboles de decisión. Se utilizó la base de datos HAM10000, la cual contiene imágenes médicas manualmente etiquetadas, lo que asegura que el proceso de entrenamiento sea efectivo. En la implementación de una muestra balanceada, la que permite demostrar la eficiencia de la implementación realizada en la identificación del cáncer de piel, esta implementación tiene una gran variabilidad en los resultados, alcanzando valores cercanos al 100% de precisión en algunos casos.
On Unguided Automatic Colorization of Monochrome Images
Authors:   Warsaw University of Life Sciences - SGGW, Institute of Information Technology, ul. Nowoursynowska 159, Warsaw, Poland, Śluzek Andrzej
Published: July 2023

Image colorization is a challenging problem due to the infinite RGB solutions for a grayscale picture. Therefore, human assistance, either directly or indirectly, is essential for achieving visually plausible colorization. This paper aims to perform colorization using only a grayscale image as the data source, without any reliance on metadata or human hints. The method assumes an (arbitrary) rgb2gray model and utilizes a few simple heuristics. Despite probabilistic elements, the results are visually acceptable and repeatable, making this approach feasible (e.g. for aesthetic purposes) in domains where only monochrome visual representations exist. The paper explains the method, presents exemplary results, and discusses a few supplementary issues.
Semi-Supervised Learning Approach for Fine Grained Human Hand Action Recognition in Industrial Assembly
Authors:   Bosch Rexroth AG, Lise-Meitner-Strasse 4, 89081 Ulm, Germany, Sturm Fabian , Sathiyababu Rahul ,   Bosch Rexroth AG, Lise-Meitner-Strasse 4, 89081 Ulm, Germany, Hergenroether Elke ,   University of Applied Sciences Darmstadt, Schoefferstrasse 3, 64295 Darmstadt, Germany, Siegel Melanie ,   University of Applied Sciences Darmstadt, Schoefferstrasse 3, 64295 Darmstadt, Germany
Published: July 2023

Until now, it has been impossible to imagine industrial manual assembly without humans due to their flexibility and adaptability. But the assembly process does not always benefit from human intervention. The error-proneness of the assembler due to disturbance, distraction or inattention requires intelligent support of the employee and is ideally suited for deep learning approaches because of the permanently occurring and repetitive data patterns. However, there is the problem that the labels of the data are not always sufficiently available. In this work, a spatio-temporal transformer model approach is used to address the circumstances of few labels in an industrial setting. A pseudo-labeling method from the field of semi-supervised transfer learning is applied for model training, and the entire architecture is adapted to the fine-grained recognition of human hand actions in assembly. This implementation significantly improves the generalization of the model during the training process over different variations of strong and weak classes from the ground truth and proves that it is possible to work with deep learning technologies in an industrial setting, even with few labels. In addition to the main goal of improving the generalization capabilities of the model by using less data during training and exploring different variations of appropriate ground truth and new classes, the recognition capabilities of the model are improved by adding convolution to the temporal embedding layer, which increases the test accuracy by over 5% compared to a similar predecessor model.
On Importance of Scene Structure for Hardware-Accelerated Ray Tracing
Authors:   Czech Technical University in Prague, Karlovo namesti 13, 121 35, Prague, Czech Republic, Kacerik Martin , Bittner Jiri ,   Czech Technical University in Prague, Karlovo namesti 13, 121 35, Prague, Czech Republic
Published: July 2023

Ray tracing is typically accelerated by organizing the scene geometry into an acceleration data structure. Hardware-accelerated ray tracing, available through modern graphics APIs, exposes an interface to the acceleration structure (AS) builder that constructs it given the input scene geometry. However, this process is opaque, with limited knowledge and control over the internal algorithm. Additional control is available through the layout of the AS builder input data, the geometry of the scene structured in a user-defined way. In this work, we evaluate the impact of a different scene structuring on the run time performance of the ray-triangle intersections in the context of hardware-accelerated ray tracing. We discuss the possible causes of significantly different outcomes (up to 1.4 times) for the same scene and identify a potential to reduce the cost by automatic input structure optimization.
Effects of forearm rotation towards cross-user classification accuracy of forearm gestures
Authors:   Politeknik Kota Kinabalu, Sabah, FU ZINVI , BANI HASHIM AHMAD YUSAIRI ,   Universiti Teknikal Malaysia, Melaka, JAMALUDIN ZAMBERI ,   Universiti Teknikal Malaysia, Melaka, SYAKIR MOHAMAD IMRAN ,   Universiti Teknikal Malaysia, Melaka
Published: July 2023

Electromyography (EMG) is a random biological signal that depends on the electrode placement and the physiology of the individual. Currently, EMG control is practically limited by this individualistic nature and requires per session training. This study investigates the EMG signals based on six locations on the lower forearm during contraction. Gesture classification was performed en-bloc across 20 subjects without retraining with the objective of determining the most classifiable gestures based on the similarity of their resultant EMG signals. Principle component analysis (PCA) and linear discriminant analysis (LDA) were the principal tools for analysis. The results showed that many gesture pairs could be accurately classified per channel with accuracies of over 85%. However, classification rates dropped to unreliable levels when up to nine gestures were classified over the single channels. The classification results show universal classification based on a common EMG database is possible without retraining for limited gestures.
IMPLEMENTASI MANAJEMEN BERBASIS SEKOLAH DALAM MENINGKATKAN PRESTASI BELAJAR PESERTA DIDIK DI SMA MUHAMMADIYAH SUNGGUMINASA KEC. SOMBA OPU KAB. GOWA
Authors: . Surga , . Armiana
Published: July 2023

The purpose of this study was to determine the implementation of school-based management, the inhibiting and supporting factors as well as the solution in improving the learning achievement of students at SMA Muhammadiyah Sungguminasa Kec. Somba Opu Kab. Gowa. This type of research uses descriptive qualitative research with a phenomenological approach. Methods of data collection using interviews and documentation. The data analysis technique uses data analysis, data presentation and drawing conclusions. The results of the study show that the implementation of school-based management has not been fully implemented properly, caused by the inhibiting factor, namely the financial situation so that it is difficult to procure facilities and infrastructure and their maintenance is also quite apprehensive because they often procure but do not last long for use, student admissions have not met the quota for class capacity. However, it is still supported by educators, the majority of whom have reached a master's education level of around 20%, supported by infrastructure, namely sufficient classes and supported by good teacher cooperation. So that the solution given is holding meetings with parents of students in procuring facilities to support the teaching and learning process, as well as conducting socialization to the school community inviting togetherness in using and maintaining facilities so that they are well controlled, so that they can be used when needed. And continue to socialize to the junior high school level, install student admission announcements openly and introduce the achievements and advantages of the school.
An Overview of the Impact of the Food Sector “Intelligent Packaging” and “Smart Packaging”
Authors: POLI Maria , MALAGAS Konstantinos , NOMIKOS Spyridon , PAPAPOSTOLOU Apostolos , VLASSAS Grigoris
Published: July 2023

The contribution of traditional packaging was significant to the initial development of food distribution systems; however, it can no longer meet the growing demands of modern consumers, businesses, and the rapidly evolving supply chain. New advances in various sciences, particularly in information and communication technologies (ICT), contribute to the emergence of new forms of packaging. The transition to “innovative packaging” with additional functions is beneficial for all participants in the food chain. “Intelligent packaging” and “smart packaging” both provide helpful information and continuous monitoring of the food / product safety and quality during the whole chain. Packaging should be seen as an entire system and offers many benefits to many sectors of our society, such as economic rewards, reduction of food waste, increased food safety, contribution to the circular economy, and in general, responds better to the growing demands of users in their daily lives. The current research reviewed a large number of relevant studies, discussed the main issues, and finally, functional outcomes were generated. Practitioners and academicians will benefit from the current study and acquire helpful knowledge on an exciting topic.
Análisis y prevención del peligro por inundaciones en quebradas de alto riesgo en la ciudad de Arequipa – Perú
Authors:   Universidad Católica de Santa María (UCSM), Escuela Profesional de Ingeniería Civil, Arequipa, Perú, Ccanccapa Puma Joel , Hidalgo Valdivia Alejandro Víctor ,   Universidad Católica de Santa María (UCSM), Escuela Profesional de Ingeniería Civil, Arequipa, Perú, Noriega Aquise Guillermo Yorel ,   Iniversidad Católica de Santa María (UCSM), Escuela Profesional de Ingeniería Civil, Arequipa, Perú, Aguilar Chavez Alex Eduardo ,   Universidad Católica de Santa María (UCSM), Escuela Profesional de Ingeniería Civil, Arequipa, Perú, Marques Marcelo ,   Universidad Estadual de Maringá (UEM), Umuarama, Brasil
Published: July 2023

La ciudad de Arequipa, la segunda ciudad más importante del Perú, se ve enfrentada a eventos extremos como lluvias de alta intensidad, pero de corta duración que generan inundaciones y crecidas del rio Chili (avenidas de lodo y huaycos). Esta situación agrava la vulnerabilidad de la población asentada en las márgenes de las quebradas posteriormente torrenteras, debido a la poca o nula planificación territorial por parte de las entidades gubernamentales reflejadas cada año en pérdidas humanas y de infraestructuras presentes. La frecuencia de estos eventos va en aumento con el tiempo y es por esta razón que se generan umbrales de precipitaciones extremas para su correspondiente caracterización con un registro de 41 años (1981-2021) con el objetivo de informar sobre la peligrosidad de un fenómeno meteorológico adverso, previsto o en desarrollo. Se utilizó datos de precipitación máxima de 24 horas de las estaciones meteorológicas del SENAMHI (Servicio Nacional de Meteorología e Hidrología del Perú) para obtener el hidrograma líquido para diferentes periodos de retorno con el modelo hidrológico HEC - HMS. También se realizaron estudios de mecánica de suelos para determinar los parámetros reológicos del flujo no newtoniano y luego calibrar a través de eventos históricos con el modelo hidráulico HEC - RAS. Finalmente se elaboraron mapas cartográficos en QGIS para evaluar las zonas de peligro por inundaciones en las torrenteras Del Pato, San Lázaro, Venezuela y Los Incas.
Double Structure Synergy and The Empowering of Poetic Experience in Chairil Anwar’s Poem ‘Senja Di Pelabuhan Kecil’
Authors: Baharuddin Baharuddin
Published: July 2023

The paper studies Chairil Anwar’s poem Senja di Pelabuhan Kecil. It focuses on analyzing the strategies Chairil Anwar applies in manipulating text double structure (the linguistic and literary ones). The data analyzed derives from the poem and in order to illuminate some key terms in the poem, comparison with other poems by the same poet is taken. The analysis of the poem is conducted by elaborating both linguistic and literary approaches. That is conducted by analytically discuss the linguistic devices and their interaction with the structure of literary tropes. It is found that the poet relies much on intensifying the synergy between the two structures. The intensive correlate manifests in the harmonious collaboration between Serial Verb construction and the event seriality; the correlation of morpho-syntactically priming of agent’s role (voice system) and the foregrounding of agent initiation of event (deviation from ordinary use of language). Phonologically considered, the poem shows parallelism between the prosody of line (sound) and the synesthetic (Winter, 2019), the co-perception through vision and hearing sensing. Another essential correlation found constitutes syntactic-phonological pattern which facilitates the representation of encyclopedic experience, which is the rhythm of the speaker’s heartbeat.
Methodological recommendations for the elaboration of the discussion of the clinical case report
Authors:   Instituto de Investigaciones en Ciencias Biomédicas (INICIB). Universidad Ricardo Palma, Lima-Peru., Pichardo Rodriguez Rafael , Saavedra Velazco Marcos ,   Instituto de Investigaciones en Ciencias Biomédicas (INICIB). Universidad Ricardo Palma, Lima-Peru., Bracamonte Hernández Juan Jesús ,   Instituto de Investigaciones en Ciencias Biomédicas (INICIB). Universidad Ricardo Palma, Lima-Peru., Peña Oscuvilca Willy ,   Instituto de Investigaciones en Ciencias Biomédicas (INICIB). Universidad Ricardo Palma, Lima-Peru., Ruiz Franco Oscar ,   Facultad de Medicina Humana. Universidad Nacional Mayor de San Marcos, Lima-Peru.
Published: July 2023

Introduction: Case reports are a type of biomedical publication that allow us to share experiences regarding the etiology, diagnosis, therapeutics, and prognosis of anecdotal events that occur both in one and in several patients during clinical practice. Objective: to elaborate methodological recommendations for the elaboration of the discussion of a clinical case report. Methods: A narrative review of international guidelines and available evidence was carried out. Results: A total of 411,227 articles were located, finally selecting 10 narrative review articles. Discussion: The discussion is the most relevant section of the case report despite being considered by some journals as an optional contribution. We recommend for the elaboration of the discussion, to follow the following four steps: a) finding and comparison with the current evidence, b) justification of the causality of the findings, c) limitations and strengths in the management of the exposed case and d) clinical implications and prospects for the future. Conclusion: It is recommended to follow the four sequential steps for the elaboration of the discussion and to evaluate its impact on the scientific production in undergraduate and postgraduate students.
A simple but effective solution for proximal mark absence on some microcatheters in intracranial aneurysm embolization: Technical note
Authors: Figueroa-Sanchez Jose A. , Martinez Hector R. , Avalos-Montes Pablo J. , Arreola-Aldape Carlos A. , Guerrero Jose Alberto Moran , Caro-Osorio Enrique
Published: July 2023

Background:

Endovascular coil embolization is increasingly being used for the treatment of intracranial aneurysms and other pathologies such as arteriovenous (AV) malformations and AV fistulas. Appropriate embolization technique requires a microcatheter with two radiopaque marks, one proximal and one distal. We present an alternative coils deployment technique for intracranial aneurysms, using a microcatheter without a proximal radiopaque mark.

Methods:

We describe the technique for embolization that was used in a 36-year-old female patient, in which we used a microcatheter without a proximal radiopaque mark for coil embolization of an intracranial aneurysm.

Results:

We used a Headway Duo flow directed microcatheter for a coiling embolization of an intracranial aneurysm, solving the absence of the proximal radiopaque mark by cannulating the microcatheter with a Traxcess 0.014 microguidewire, and placing an external mark on the screen in the proximal portion of the microguidewire 30 mm radiopaque tip to indirectly mark the proximal mark of the microcatheter.

Conclusion:

There is scarce evidence supporting the use of microcatheters with no proximal radiopaque mark for coil embolization. This report attempts to disclose how an easy and simple technique can be used as a rescue method to solve the proximal radiopaque mark absence during endovascular coil release procedures. To the best of our knowledge, this technique has not been previously described; therefore, its use is not widespread among neurointerventionists.
THE EFFICTIVENESS OF THE INFLUENCE OF DRONE HOMOGENATE ON THE LIVE WEIGHT OF ROMANOV YOUNG RAM SHEEP
Authors:   Timirâzevskaâ selʹskohozâjstvennaâ akademiâ, GALIEVA Z.A.
Published: July 2023

In the article consider the impact on the productive indicators of Romanov breed rams of the use of beekeeping products - drone homogenate in the diet. It was found that the live weight of the animals of the experimental groups was higher in all age groups in comparison with their peers in the control group, which proves the economic effi ciency of the use of drone homogenates in the diet of sheep
Síndrome de Wolff-Parkinson-White neonatal: reporte de un caso
Authors: Pérez-Parra Jesús Elmer , Castañeda-Delgado María Luisa
Published: July 2023

El síndrome de Wolff-Parkinson-White es un problema relevante en Neonatología dado que la aparente falta de signos o síntomas al ojo no entrenado, puede retrasar el diagnóstico y llevar a complicaciones e incluso choque y muerte súbita por taquicardia supraventricular. Palabras clave: síndrome, Wolff-Parkinson-White, taquicardia, supraventricular
Enhancing Human-Machine Interaction: Real-Time Emotion Recognition through Speech Analysis
Authors: Andrade Dominik Esteves de , Buchkremer Rüdiger
Published: July 2023

Humans, as intricate beings driven by a multitude of emotions, possess a remarkable ability to decipher and respond to socio-affective cues. However, many individuals and machines struggle to interpret such nuanced signals, including variations in tone of voice. This paper explores the potential of intelligent technologies to bridge this gap and improve the quality of conversations. In particular, the authors propose a real-time processing method that captures and evaluates emotions in speech, utilizing a terminal device like the Raspberry Pi computer. Furthermore, the authors provide an overview of the current research landscape surrounding speech emotional recognition and delve into our methodology, which involves analyzing audio files from renowned emotional speech databases. To aid incomprehension, the authors present visualizations of these audio files in situ, employing dB-scaled Mel spectrograms generated through TensorFlow and Matplotlib. The authors use a support vector machine kernel and a Convolutional Neural Network with transfer learning to classify emotions. Notably, the classification accuracies achieved are 70% and 77%, respectively, demonstrating the efficacy of our approach when executed on an edge device rather than relying on a server. The system can evaluate pure emotion in speech and provide corresponding visualizations to depict the speaker's emotional state in less than one second on a Raspberry Pi. These findings pave the way for more effective and emotionally intelligent human-machine interactions in various domains.
Decoding the Dynamics of Cultural Change: A Cultural Evolution Approach to the Psychology of Acculturation
Authors: Kunst Jonas R. , Mesoudi Alex
Published: July 2023

Although acculturation psychology is extensively studied in the social sciences, research progress has slowed due to overused methodologies and theories, and emerging challenges to core conceptual tenets. Here, we seek to stimulate scientific inquiry into acculturation by integrating underutilized cultural evolutionary perspectives. We propose that cultural evolutionary mechanisms, such as (anti)conformity, prestige bias, payoff bias, and vertical transmission are instrumental in understanding when, why, and how minority- and majority-group members acculturate. The direction and potency of these mechanisms is proposed to be modulated by a combination of contextual and individual factors, resulting in acculturation strategies that at the population level form “cultural evolutionary equilibria.” These equilibria in turn have consequences for the long-term, population-level dynamics of cultural evolution. We outline how our integration of perspectives can allow researchers to model the dynamics of large-scale cultural change, increasing our understanding of the complex challenges faced by today’s diverse societies.
An Outside-in Approach to Human Resource Management
Authors: Adhikari Dev Raj
Published: July 2023

This article discusses the outside-in approach to understanding human resource management (HRM) in relation to sustainable development goals (SDGs). The author presents four propositions, based on the literature review, that connect long-term business challenges to sustainable HRM goals. The article emphasizes the need for a wider scholarly and professional perspective in order to effectively conceptualize and implement sustainable HRM practices and address long-term business challenges. Due to the lack of sustainable HRM knowledge in countries like Nepal, the article aims to provide a detailed explanation of the concepts. As a conceptual paper, further expansion and testing of the propositions will be necessary in the future.
Growth and meat productivity of bulls depending on the similarity of their blood group B antigens with mothers
Authors: Ugnivenko Anatolii , Natalych Oleksandr
Published: July 2023

Various molecular genetic markers are used to comprehensively assess the breeding value of animals based on genetic information. Therefore, an important place in the qualitative improvement of beef cattle breeds is occupied by the improvement of methods of animal selection using the immunogenetic characteristics of their blood. The purpose of the study is to determine the dependence of weight growth and meat productivity of animals of the Ukrainian beef breed on the number of similar antigenic factors of the B blood group system in them and their mothers. After weaning, the first group contained bulls (n = 12) who had similar antigens from 2 to 6 inclusive. The second group (n = 15) – from 7 to 13. When studying the features of weight gain and meat productivity of bulls, it was proved that the similarity in the B system of cattle blood groups between mother and offspring is informative regarding the homo- or heterozygosity of the latter. It was found that animals with a lower amount of antigens similar to the mother outperformed (by 9.3%) homozygous peers in the test from 8 to 18 months of age in terms of average daily weight gain and had a higher live weight (by 8.0%) at 18 months, indicating their better early maturity. With lower antigenic similarity between mother and offspring, the expression of meat forms is 7.8% and 6.0% higher, respectively, at 15 and 18 months of age.After slaughter, there is no significant difference between homozygous and heterozygous bulls in terms of meat productivity, including pre-slaughter live and slaughter weight. When selecting offsprings with fewer antigens similar to their mother, they tend to reduce the slaughter yield (by 0.5 points) and the muscle content in carcasses (by 3.2%). The selection of bulls of Ukrainian beef breed with a smaller number of antigens of the B blood group system, similar to mothers, will help to improve their weight growth and the expression of meat forms, and will allow predicting future meat productivity
Excessive Use of Social Networking Sites and Intention to Invest in Stock Market among Gen Z: A Parallel Mediation Model
Authors: Ahuja Sonal , Grover Karan
Published: July 2023

The use of social media sites is inevitable. It is one of the most influential means of communication nowadays, particularly among Generation Z, who are often referred to as digital natives. The objective of this study is to examine the influence of excessive use of social networking sites (SNS) on investment intention in the stock market among Generation Z. The study further investigates the parallel mediating roles of financial attitude and perceived behavioral control (PBC). A cross-sectional self-administered questionnaire was conducted among Gen Z in India and responses were analyzed using variance-based structural equation modeling in SmartPLS 4 software. Additionally, the predictive relevance of investment intention was found using PLSPredict. The results revealed that the excessive usage of social media positively influences the intention of this young generation to participate in the securities market. Further, the parallel mediation results establish the role of financial attitude and PBC between excessive use of SNS and investment intention. The predictive power of investment intention was reported to be high. These findings have significant practical implications for financial service providers, finance content creators on various social media platforms (influencers), and financial advisers.
Study and Analysis of Concentric Shell and Double Tube Heat Exchanger Using Tio2 Nanofluid
Authors: Abdulmajeed Bassma Abbas , Majeed Noor Sabih
Published: July 2023

In this paper, nanofluid of TiO2/water of concentrations of 0.002% and 0.004% volume was used. This nanofluid was flowing through heat exchanger of shell and concentric double tubes with counter current flow to the hot oil. The thermal conductivity of nanofluid is enhanced with increasing concentrations of the TiO2, this increment was by 19% and 16.5% for 0.004% and 0.002% volume respectively relative to the base fluid (water). Also the heat transfer coefficient of the nanofluid is increased as Reynold's number and nanofluid concentrations increased too. The heat transfer coefficient is increased by 66% and 49% for 0.004% and 0.002% volume respectively relative to the base fluid. This study showed that the friction factor of nanofluid was decreased as Reynold's number increased.
Ethical and moral decision-making for self-driving cars based on deep reinforcement learning
Authors: Qian Zhuoyi , Guo Peng , Wang Yifan , Xiao Fangcheng
Published: July 2023

Self-driving cars are expected to replace human drivers shortly, bringing significant benefits to society. However, they have faced opposition from various organizations that argue it is challenging to respond to instances involving unavoidable personal injury. In situations involving deadly collisions, self-driving cars must make decisions that balance life and death. This paper investigates the ethical and moral decision-making challenges for self-driving cars from an algorithmic perspective. To address this issue, we introduce the accident-prioritized replay mechanism to the Deep Q-Networks (DQN) algorithm based on early humanities research. The mechanism quantifies a reward function that takes priority into account. RGB (red, green, blue) images obtained by the camera installed in front of the self-driving cars are fed into the Xception network for training. To evaluate our approach, we compare it to the conventional DQN algorithm. The simulation results indicate that the Rawlsian DQN algorithm has superior stability and interpretability in decision-making. Furthermore, the majority of respondents to our survey accept the final decision made by our algorithm. Our experiment demonstrates that it is possible to incorporate ethical considerations into self-driving car decision-making, providing a solution for rational decision-making in emergency and dilemma circumstances.
A dense layer model for cognitive emotion recognition with feature representation
Authors: Yuvaraj S. , Vijay Franklin J.
Published: July 2023

The predictions of cognitive emotions are complex due to various cognitive emotion modalities. Deep network model has recently been used with huge cognitive emotion determination. The visual and auditory modalities of cognitive emotion recognition system are proposed. The extraction of powerful features helps obtain the content related to cognitive emotions for different speaking styles. Convolutional neural network (CNN) is utilized for feature extraction from the speech. On the other hand, the visual modality uses the 50 layers of a deep residual network for prediction purpose. Also, extracting features is important as the datasets are sensitive to outliers when trying to model the content. Here, a long short-term memory network (LSTM) is considered to manage the issue. Then, the proposed Dense Layer Model (DLM) is trained in an E2E manner based on feature correlation that provides better performance than the conventional techniques. The proposed model gives 99% prediction accuracy which is higher to other approaches.
Pandemi Yoğun Bakımda Çalışan Hemşirelerin Koronafobi Düzeyi ve Etkileyen Faktörler
Authors: COŞAR ERTEM Aytül , ERTEM Uğur
Published: July 2023

2019'da Çin'in Wuhan kentinde başlayan ve hızla tüm dünyaya yayılan koronavirüs hastalığı 2019 (COVİD-19), Dünya Sağlık Örgütü tarafından 11 Mart 2020 tarihinde küresel bir pandemi ilan edilmiştir. Koronafobi, COVİD-19 salgını sırasında yeni koronavirüsün neden olduğu spesifik bir fobidir. Bu çalışma, pandemi yoğun bakım ünitesinde çalışan hemşirelerde COVİD-19 pandemisinin neden olduğu koronafobi düzeyini değerlendirmek ve sonuçları pandemi dışı yoğun bakım ünitesinde çalışan hemşireler ile karşılaştırmayı amaçlamaktadır. Ayrıca pandemi yoğun bakım ünitesinde çalışan hemşirelerin koronafobi düzeyine etki eden faktörlerinde belirlenmesi amaçlanmıştır. Haziran 2021-Ekim 2021 tarihleri arasında pandemi yoğun bakım ünitesinde çalışan toplam 34 hemşire çalışmaya dahil edildi. Kontrol grubu olarak pandemi dışı yoğun bakım ünitesinde çalışan toplam 20 hemşire çalışmaya dahil edildi. Hastaların sosyodemografik verileri kaydedildi. Her iki gruptaki tüm katılımcılar COVİD-19 Fobi Ölçeğini (C19P-S) doldurdu. Pandemi yoğun bakımda çalışan hemşire grubunda C19P-S psikolojik alt ölçek puanı kontrol grubuna göre istatistiksel olarak anlamlı yüksekti (p0,05). Ayrıca pandemi yoğun bakımda çalışan hemşirelerde C19P-S toplam puanı ile sosyodemografik özellikler ve COVİD-19 geçirme durumu arasında anlamlı ilişki bulunmadı (p>0,05). Çalışma sonuçlarımız, pandemi yoğun bakım ünitesinde çalışan hemşirelerin bu olağanüstü pandemi durumunda psikolojik olarak daha fazla etkilendiklerini göstermektedir. Koronafobinin erken tespiti ve zamanında psikolojik destek çok önemlidir.
Geomembranes to Prevent Swallowing
Authors: Abdullah Deden Disa , Aminush Arham , Sukma Dedy , Pratami Allisa , Suprapto  , Udarwis Robi , Triwibowo Anton , Ramadhan Taufik
Published: July 2023

The high intensity of rain increases the runoff of the mine area so that the water flowing through the drainage channel carries erosion so that the sediment pond very quickly silts up. The impact is that the water flowing from the sediment pond to the river will be cloudy, disturbing biodiversity in the river. This study aimed to evaluate the effectiveness of using geomembranes in preventing siltation in sediment ponds. This research was conducted in the monkey area of PT Antareja Mahada Makmur Site Multi Harapan Utama. This study used qualitative research methods. Data were collected through field surveys by directly observing the waters where geomembranes have been installed. The collected data were analyzed through three stages: data reduction, presentation, and conclusion drawing. The results showed that using geomembrane in drainage can reduce erosion and siltation in wastewater settling ponds. The innovative use of geomembranes in settling ponds positively impacts the environment, cost efficiency, and team understanding within the company.
FREQUENCY OF VARIOUS TYPES OF DENTOALVEOLAR INJURIES IN TRAUMA PATIENTS VISITING TO TERIARY CARE HOSPITAL
Authors: Uddin Fahim , Ahmad Sajjad , Qayum Zahid
Published: July 2023

Objectives: To determine the frequency of various types of dento alveolar injuries in traumapatients.Materials and Methods: A Descriptive, Cross Sectional study was conducted at the departmentof Oral and maxillofacial surgery, Hayatabad Medical Complex, Peshawar from 30th July 2021to 30th January 2022. A total of 198 patients were observed in the study. Non probability, consecutive sampling technique was applied.Results: Mean age was 45.6 Years ± 1.92. fourth decade had been the commonest one. Genderwise distribution among 198 patients were analyzed as n= male was 64 (32.3%) and female was134 (67.7%). Distribution of Enamel Infarction among 198 patients were analyzed as n=Yes was47 (23,7%) and No was 151(76.3%). Distribution of enamel fracture among 198 patients wereanalyzed as n= Yes was 45 (22.7%) and No was 153 (77.3%). Distribution of Enamel and Dentinfracture among 198 patients were analyzed as n= Yes was 50(25.3%) and No was 148 (74.7%).Intrusion of tooth into alveolar socket wall among 198 patients were analyzed as n=Yes was 69(34.8%) and No was 129(65.2%)
Cyclometalated iridium(III) complexes combined with fluconazole: antifungal activity against resistant C. albicans
Authors: Lu Jun-Jian , Xu Zhi-Chang , Zhu Hou , Zhu Lin-Yuan , Ma Xiu-Rong , Wang Rui-Rui , Li Rong-Tao , Ye Rui-Rong
Published: July 2023

Candida albicans (C. albicans) is a ubiquitous clinical fungal pathogen. In recent years, combination therapy, a potential treatment method to overcome C. albicans resistance, has gained traction. In this study, we synthesized a series of cyclometalated iridium(III) complexes with the formula [Ir(C-N)2(tpphz)](PF6) (C-N = 2-phenylpyridine (ppy, in Ir1), 2-(2-thienyl)pyridine (thpy, in Ir2), 2-(2,4-difluorophenyl) pyridine (dfppy, in Ir3), tpphz = tetrapyrido[3,2-a:2',3'-c:3'',2''-h:2''',3'''-j]phenazine) and polypyridyl ruthenium(II) complexes with the formula [Ru(N-N)2(tpphz)](PF6)2 (N-N = 2,2'-bipyridine (bpy, in Ru1), 1,10-phenanthroline (phen, in Ru2), 4,7-diphenyl-1,10-phenanthroline (DIP, in Ru3)), and investigated their antifungal activities against drug-resistant C. albicans and their combination with fluconazole (FLC). Of which, the combination of the lead iridium(III) complex Ir2 and FLC showed strong antifungal activity against drug-resistant C. albicans. Mechanism studies have shown that they can inhibit the formation of hyphae and biofilm, damage mitochondrial function and accumulate intracellular ROS. Therefore, iridium(III) complexes combined with FLC can be used as a promising treatment to exert anti-drug-resistant C. albicans activity, in order to improve the treatment efficiency of fungal infection.
Investigation of the shared molecular mechanisms and hub genes between myocardial infarction and depression
Authors: Wang Mengxi , Cheng Liying , Gao Ziwei , Li Jianghong , Ding Yuhan , Shi Ruijie , Xiang Qian , Chen Xiaohu
Published: July 2023

Background

The pathogenesis of myocardial infarction complicating depression is still not fully understood. Bioinformatics is an effective method to study the shared pathogenesis of multiple diseases and has important application value in myocardial infarction complicating depression.

Methods

The differentially expressed genes (DEGs) between control group and myocardial infarction group (M-DEGs), control group and depression group (D-DEGs) were identified in the training set. M-DEGs and D-DEGs were intersected to obtain DEGs shared by the two diseases (S-DEGs). The GO, KEGG, GSEA and correlation analysis were conducted to analyze the function of DEGs. The biological function differences of myocardial infarction and depression were analyzed by GSVA and immune cell infiltration analysis. Four machine learning methods, nomogram, ROC analysis, calibration curve and decision curve were conducted to identify hub S-DEGs and predict depression risk. The unsupervised cluster analysis was constructed to identify myocardial infarction molecular subtype clusters based on hub S-DEGs. Finally, the value of these genes was verified in the validation set, and blood samples were collected for RT-qPCR experiments to further verify the changes in expression levels of these genes in myocardial infarction and depression.

Results

A total of 803 M-DEGs, 214 D-DEGs, 13 S-DEGs and 6 hub S-DEGs (CD24, CSTA, EXTL3, RPS7, SLC25A5 and ZMAT3) were obtained in the training set and they were all involved in immune inflammatory response. The GSVA and immune cell infiltration analysis results also suggested that immune inflammation may be the shared pathogenesis of myocardial infarction and depression. The diagnostic models based on 6 hub S-DEGs found that these genes showed satisfactory combined diagnostic performance for depression. Then, two molecular subtypes clusters of myocardial infarction were identified, many differences in immune inflammation related-biological functions were found between them, and the hub S-DEGs had satisfactory molecular subtypes identification performance. Finally, the analysis results of the validation set further confirmed the value of these hub genes, and the RT-qPCR results of blood samples further confirmed the expression levels of these hub genes in myocardial infarction and depression.

Conclusion

Immune inflammation may be the shared pathogenesis of myocardial infarction and depression. Meanwhile, hub S-DEGs may be potential biomarkers for the diagnosis and molecular subtype identification of myocardial infarction and depression.
Ocean color atmospheric correction methods in view of usability for different optical water types
Authors: Hieronymi Martin , Bi Shun , Müller Dagmar , Schütt Eike M. , Behr Daniel , Brockmann Carsten , Lebreton Carole , Steinmetz François , Stelzer Kerstin , Vanhellemont Quinten
Published: July 2023

Satellite remote sensing allows large-scale global observations of aquatic ecosystems and matter fluxes from the source through rivers and lakes to coasts, marginal seas into the open ocean. Fuzzy logic classification of optical water types (OWT) is increasingly used to optimally determine water properties and enable seamless transitions between water types. However, effective exploitation of this method requires a successful atmospheric correction (AC) over the entire spectral range, i.e., the upstream AC is suitable for each water type and always delivers classifiable remote-sensing reflectances. In this study, we compare five different AC methods for Sentinel-3/OLCI ocean color imagery, namely IPF, C2RCC, A4O, POLYMER, and ACOLITE-DSF (all in the 2022 current version). We evaluate their results, i.e., remote-sensing reflectance, in terms of spatial exploitability, individual flagging, spectral plausibility compared to in situ data, and OWT classifiability with four different classification schemes. Especially the results of A4O show that it is beneficial if the performance spectrum of the atmospheric correction is tailored to an OWT system and vice versa. The study gives hints on how to improve AC performance, e.g., with respect to homogeneity and flagging, but also how an OWT classification system should be designed for global deployment.
Cancer risk algorithms in primary care: can they impact risk estimates and referral decisions?
Authors: Arora Kavleen , Kostopoulou Olga , Palfi Bence
Published: July 2023

Background

Cancer risk algorithms were introduced to clinical practice in the last decade, but they remain underused.

Aim

In two randomised controlled experiments, we tested the impact of an unnamed cancer risk algorithm (QCancer) on GPs’ risk assessment and 2-week-wait referral decisions. We also tested the impact of algorithm information, ‘social proof’, and a visual explanation.

Method

We presented two different samples of GPs (totaln=372) with vignettes depicting patients with possible colorectal (Experiment 1) or upper GI (Experiment 2) cancers and measured their risk estimates and inclination to refer both before and after seeing the algorithmic estimate. In Experiment 1, half of the participants read information about the algorithm. In Experiment 2, half of the participants read how Experiment 1 participants had found the algorithm useful (‘social proof’). Half of the participants also saw an explanatory bar graph representing the relative contribution of symptoms to the risk estimate.

Results

Both experiments provided consistent results: after seeing the algorithm, GPs’ inclination to refer changed on 26% of instances. ‘Social proof’ enhanced the algorithm’s impact on both risk estimates and referrals. Neither information about the algorithm nor the explanatory graph impacted behaviour. In both experiments, learning took place, as GPs’ initial risk estimates moved closer to QCancer over time.

Conclusion

Cancer risk algorithms have the potential to impact risk assessment and decision making and may have a role as learning tools. Informing clinicians about their proven usefulness to colleagues may maximise impact.
Exploring the value of in-practice point-of-care testing (POCT) for high-risk groups
Authors: Leston Meredith , Hoang Uy , de Lusignan Simon
Published: July 2023

Background

Mounting evidence for poorer seroconversion and accelerating vaccine waning in clinical risk groups (CRGs) suggests that, even if vaccinated, monoclonals and antivirals may still be required. However, the efficacy of said alternatives are highly time sensitive. As such, a clinical workflow that unlocks access to these treatments in both a timely and antimicrobially-responsible manner is essential. In-practice point-of-care testing (POCT) may offer a solution to this dual challenge.

Aim

The present study investigated the uptake and prescription outcomes of POCT in a past patient cohort that attended primary care with symptoms of influenza-like illness (ILI). This work extracted CRG patient data from the overall cohort with a special emphasis on the immunosuppressed.

Method

Researchers utilised data gathered between October 2019 and March 2020 where POCT was instituted in 12 practices within the Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) network. Researchers subdivided full cohort data (n= 648) by CRG and, specifically, immunosuppressed status.

Results

Patients in CRGs constituted 24.8% of swabbed patients; the immunosuppressed constituted 1.9%. Key predictors for POCT positivity in CRG patients were similar to those of the underlying cohort. Evidence was found for increased — and sometimes inappropriate — antibiotic prescription in CRGs via inflated odds ratios (ORs) between POCT positivity and antibiotic prescribing in these patients versus the full cohort (OR 0.75, 95% confidence interval [CI] = 0.31 to 1.80,P= 0.52 versus OR 0.61, 95% CI = 0.38 to 0.99,P= 0.03). Antivirals were consistently underutilised.

Conclusion

This work highlights the value of POCT for vulnerable patients.
Destructive and self-destructive tendencies in the deep psychological sphere of urban and rural young people as a reflection of difficulties in separation and social adaptation
Authors: Smirnov Aleksander , Maksimova Lyudmila
Published: July 2023

The relevance of the research lies in the high social significance of research in the field of revealing mechanisms of destructive behavior formation in adolescence. The study of depth-psychological sphere of personality makes it possible to identify unconscious tendencies reflecting tendencies to destructive behavior, as well as to predict the risks of such manifestations in human behavior.

Purpose of the research is the study and presentation of destructive and selfdestructive tendencies in the in-depth psychological sphere of young people living in urban and rural areas.

Theoretical research methods are the comparative-analytical method as well as the inductive and deductive methods. Empirical research methods: methods of directed conversation, observation, as well as psychodiagnostic method (method of experimental diagnostics of motives «Szondi-Test»). Statistical processing of the data is carried out both manually and with the help of the software package «Statistica».

The analysis of empirically received data indicates that the in-depth psychological sphere and its separate areas reflect the natural course of the crisis period of personal and social development for adolescence. Five conditional personality types of young people are identified: «Normally socialized», «Aggressive», «Destructive and self-destructive», «Passive and dependent», «Regressive and addictive». In analyzing it was found that the probability of destructive and selfdestructive tendencies in rural youth is higher than in urban youth.

From the scientific point of view, the research confirms and completes the existing scientific information about the processes and regularities of personality development in adolescence. Scientific novelty of the research is given by the revealed and described in-depth psychological processes and peculiarities of personal and age development of young people.
Climate Data collection and its challenges
Authors: Sun Weirong
Published: July 2023

How to collect methane is very important.
Pengaruh Pemberian Probiotik pada Infeksi Clostridium Difficile
Authors: Dharmawan Ade , Agista Dhimas Garin Dewa , Sinsanta Sinsanta , Layanto Nicolas , Deby Deby
Published: July 2023

Clostridium difficile (C.difficile) merupakan bakteri gram positif, bersifat anaerob, membentuk spora, dan merupakan patogen penting pada penyakit diare akibat antibiotik. Bakteri ini merupakan flora normal dalam saluran pencernaan manusia namun dapat menjadi patogen serta membentuk toksin yang terdiri dari 2, yaitu toksin A dan toksin B. Dikarenakan antibiotik termasuk faktor risiko terjadinya infeksi C. difficile (CDI), tatalaksana yang dapat diberikan yaitu probiotik. Probiotik mungkin efektif dalam pencegahan dan pengobatan CDI dalam beberapa cara: perubahan flora usus, peningkatan aktivitas antimikroba, dan sebagai imunomodulasi. Pengaruh probiotik, cara pemberian, serta lama pemberian yang masih bervariasi membuat probiotik belum bisa dijadikan sebagai terapi infeksi C. difficile. Namun, probiotik masih dapat menjadi salah satu pilihan terapi adjuvant pada penanganan infeksi CDI.
Analysis of a Tall Structure Considering Three Different Filler System using ETABS
Authors: - Simran Chhabra
Published: July 2023

A reinforced concrete building with masonry infill is most common type of construction in India. Traditionally, conventional clay bricks or concrete blocks which are heavy rigid materials have been used as Infill wall. Though, AAC (aerated light weight concrete) blocks which are lightweight, flexible building materials that provides insulation and fire resistance and have lower impact on environment, can be used as masonry infill (MI) material in buildings. AAC blocks are now also available in India. A number of researchers have studied the behavior of AAC in-filled reinforced concrete (R/C) frames experimentally. Interlocking Bricks are even introduced further which adds an advantage over AAC bricks.
IN THIS PAPER presenting review of literatures
Index Terms: Interlocking Blocks, AAC block, Infill frame, Equivalent strut model.