bluuebunny/crossref_metadata_2025 huggingface dataset:
An Open-Source Wireless Sensor Node Platform with Active Node-Level Reliability for Monitoring Applications
Authors: Widhalm Dominik , Goeschka Karl M. , Kastner Wolfgang
Published: November 2021

In wireless sensor networks, the quality of the provided data is influenced by the properties of the sensor nodes. Often deployed in large numbers, they usually consist of low-cost components where failures are the norm, even more so in harsh outdoor environments. Current fault detection techniques, however, consider the sensor data alone and neglect vital information from the nodes’ hard- and software. As a consequence, they can not distinguish between rare data anomalies caused by proper events in the sensed data on one side and fault-induced data distortion on the other side. In this paper, we contribute with a novel, open-source sensor node platform for monitoring applications such as environmental monitoring. For long battery life, it comprises mainly low-power components. In contrast to other sensor nodes, our platform provides self-diagnostic measures to enable active node-level reliability. The entire sensor node platform including the hardware and software components has been implemented and is publicly available and free to use for everyone. Based on an extensive and long-running practical experiment setup, we show that the detectability of node faults is improved and the distinction between rare but proper events and fault-induced data distortion is indeed possible. We also show that these measures have a negligible overhead on the node’s energy efficiency and hardware costs. This improves the overall reliability of wireless sensor networks with both, long battery life and high-quality data.
A Simple Phase-Sensitive Surface Plasmon Resonance Sensor Based on Simultaneous Polarization Measurement Strategy
Authors: Li Meng-Chi , Chen Kai-Ren , Kuo Chien-Cheng , Lin Yu-Xen , Su Li-Chen
Published: November 2021

The SPR phenomenon results in an abrupt change in the optical phase such that one can measure the phase shift of the reflected light as a sensing parameter. Moreover, many studies have demonstrated that the phase changes more acutely than the intensity, leading to a higher sensitivity to the refractive index change. However, currently, the optical phase cannot be measured directly because of its high frequency; therefore, investigators usually have to use complicated techniques for the extraction of phase information. In this study, we propose a simple and effective strategy for measuring the SPR phase shift based on phase-shift interferometry. In this system, the polarization-dependent interference signals are recorded simultaneously by a pixelated polarization camera in a single snapshot. Subsequently, the phase information can be effortlessly acquired by a phase extraction algorithm. Experimentally, the proposed phase-sensitive SPR sensor was successfully applied for the detection of small molecules of glyphosate, which is the most frequently used herbicide worldwide. Additionally, the sensor exhibited a detection limit of 15 ng/mL (0.015 ppm). Regarding its simplicity and effectiveness, we believe that our phase-sensitive SPR system presents a prospective method for acquiring phase signals.
Semi-Automatic Spectral Image Stitching for a Compact Hybrid Linescan Hyperspectral Camera towards Near Field Remote Monitoring of Potato Crop Leaves
Authors: Chatelain Pierre , Delmaire Gilles , Alboody Ahed , Puigt Matthieu , Roussel Gilles
Published: November 2021

The miniaturization of hyperspectral cameras has opened a new path to capture spectral information. One such camera, called the hybrid linescan camera, requires accurate control of its movement. Contrary to classical linescan cameras, where one line is available for every band in one shot, the latter asks for multiple shots to fill a line with multiple bands. Unfortunately, the reconstruction is corrupted by a parallax effect, which affects each band differently. In this article, we propose a two-step procedure, which first reconstructs an approximate datacube in two different ways, and second, performs a corrective warping on each band based on a multiple homography framework. The second step combines different stitching methods to perform this reconstruction. A complete synthetic and experimental comparison is performed by using geometric indicators of reference points. It appears throughout the course of our experimentation that misalignment is significantly reduced but remains non-negligible at the potato leaf scale.
Free Space Detection Using Camera-LiDAR Fusion in a Bird’s Eye View Plane
Authors: Yu Byeongjun , Lee Dongkyu , Lee Jae-Seol , Kee Seok-Cheol
Published: November 2021

Although numerous road segmentation studies have utilized vision data, obtaining robust classification is still challenging due to vision sensor noise and target object deformation. Long-distance images are still problematic because of blur and low resolution, and these features make distinguishing roads from objects difficult. This study utilizes light detection and ranging (LiDAR), which generates information that camera images lack, such as distance, height, and intensity, as a reliable supplement to address this problem. In contrast to conventional approaches, additional domain transformation to a bird’s eye view space is executed to obtain long-range data with resolutions comparable to those of short-range data. This study proposes a convolutional neural network architecture that processes data transformed to a bird’s eye view plane. The network’s pathways are split into two parts to resolve calibration errors in the transformed image and point cloud. The network, which has modules that operate sequentially at various scaled dilated convolution rates, is designed to quickly and accurately handle a wide range of data. Comprehensive empirical studies using the Karlsruhe Institute of Technology and Toyota Technological Institute’s (KITTI’s) road detection benchmarks demonstrate that this study’s approach takes advantage of camera and LiDAR information, achieving robust road detection with short runtimes. Our result ranks 22nd in the KITTI’s leaderboard and shows real-time performance.
An Augmented Reality Periscope for Submarines with Extended Visual Classification
Authors: Breitinger André , Clua Esteban , Fernandes Leandro A. F.
Published: November 2021

Submarines are considered extremely strategic for any naval army due to their stealth capability. Periscopes are crucial sensors for these vessels, and emerging to the surface or periscope depth is required to identify visual contacts through this device. This maneuver has many procedures and usually has to be fast and agile to avoid exposure. This paper presents and implements a novel architecture for real submarine periscopes developed for future Brazilian naval fleet operations. Our system consists of a probe that is connected to the craft and carries a 360 camera. We project and take the images inside the vessel using traditional VR/XR devices. We also propose and implement an efficient computer vision-based MR technique to estimate and display detected vessels effectively and precisely. The vessel detection model is trained using synthetic images. So, we built and made available a dataset composed of 99,000 images. Finally, we also estimate distances of the classified elements, showing all the information in an AR-based interface. Although the probe is wired-connected, it allows for the vessel to stand in deep positions, reducing its exposure and introducing a new way for submarine maneuvers and operations. We validate our proposal through a user experience experiment using 19 experts in periscope operations.
Fish Segmentation in Sonar Images by Mask R-CNN on Feature Maps of Conditional Random Fields
Authors: Chang Chin-Chun , Wang Yen-Po , Cheng Shyi-Chyi
Published: November 2021

Imaging sonar systems are widely used for monitoring fish behavior in turbid or low ambient light waters. For analyzing fish behavior in sonar images, fish segmentation is often required. In this paper, Mask R-CNN is adopted for segmenting fish in sonar images. Sonar images acquired from different shallow waters can be quite different in the contrast between fish and the background. That difference can make Mask R-CNN trained on examples collected from one fish farm ineffective to fish segmentation for the other fish farms. In this paper, a preprocessing convolutional neural network (PreCNN) is proposed to provide “standardized” feature maps for Mask R-CNN and to ease applying Mask R-CNN trained for one fish farm to the others. PreCNN aims at decoupling learning of fish instances from learning of fish-cultured environments. PreCNN is a semantic segmentation network and integrated with conditional random fields. PreCNN can utilize successive sonar images and can be trained by semi-supervised learning to make use of unlabeled information. Experimental results have shown that Mask R-CNN on the output of PreCNN is more accurate than Mask R-CNN directly on sonar images. Applying Mask R-CNN plus PreCNN trained for one fish farm to new fish farms is also more effective.
Signal Enhancement of Pressure-Sensitive Film Based on Localized Surface Plasmon Resonance
Authors: Zhou Bei , Gu Feng , Liu Yingzheng , Peng Di
Published: November 2021

Pressure-sensitive films have been used for measurement in micro flow, but thin films have very limited intensity, resulting in poor signal-noise ratio (SNR). This paper presents a pressure-sensitive film whose emission signal is enhanced by silver nanoparticles (AgNPs) based on localized surface plasmon resonance (LSPR). Electronic beam evaporator and annealing furnace are used to fabricate silver nanotexture surface. PtTFPP and polystyrene are dissolved in toluene and then spin-coated on the silver nanotexture surface to prepare the pressure-sensitive films. Signal enhancement of film with AgNPs due to LSPR is analyzed and enhancement effect of samples with different particle sizes and spacer thickness are compared. Pressure and temperature calibrations are performed to assess the sensing performance of pressure-sensitive films. Pressure-sensitive films with AgNPs demonstrate signal enhancement due to LSPR and show promise for measurement in micro flow.
Ionizing Radiation Monitoring Technology at the Verge of Internet of Things
Authors: Ahmad Muhammad Ikmal , Ab. Rahim Mohd Hafizi , Nordin Rosdiadee , Mohamed Faizal , Abu-Samah Asma’ , Abdullah Nor Fadzilah
Published: November 2021

As nuclear technology evolves, and continues to be used in various fields since its discovery less than a century ago, radiation safety has become a major concern to humans and the environment. Radiation monitoring plays a significant role in preventive radiological nuclear detection in nuclear facilities, hospitals, or in any activities associated with radioactive materials by acting as a tool to measure the risk of being exposed to radiation while reaping its benefit. Apart from in occupational settings, radiation monitoring is required in emergency responses to radiation incidents as well as outdoor radiation zones. Several radiation sensors have been developed, ranging from as simple as a Geiger-Muller counter to bulkier radiation systems such as the High Purity Germanium detector, with different functionality for use in different settings, but the inability to provide real-time data makes radiation monitoring activities less effective. The deployment of manned vehicles equipped with these radiation sensors reduces the scope of radiation monitoring operations significantly, but the safety of radiation monitoring operators is still compromised. Recently, the Internet of Things (IoT) technology has been introduced to the world and offered solutions to these limitations. This review elucidates a systematic understanding of the fundamental usage of the Internet of Drones for radiation monitoring purposes. The extension of essential functional blocks in IoT can be expanded across radiation monitoring industries, presenting several emerging research opportunities and challenges. This article offers a comprehensive review of the evolutionary application of IoT technology in nuclear and radiation monitoring. Finally, the security of the nuclear industry is discussed.
Detection of Lung Cancer Cells in Solutions Using a Terahertz Chemical Microscope
Authors: Yoshida Yuichi , Ding Xue , Iwatsuki Kohei , Taniizumi Katsuya , Inoue Hirofumi , Wang Jin , Sakai Kenji , Kiwa Toshihiko
Published: November 2021

Cancer genome analysis has recently attracted attention for personalized cancer treatment. In this treatment, evaluation of the ratio of cancer cells in a specimen tissue is essential for the precise analysis of the genome. Conventionally, the evaluation takes at least two days and depends on the skill of the pathologist. In our group, a terahertz chemical microscope (TCM) was developed to easily and quickly measure the number of cancer cells in a solution. In this study, an antibody was immobilized on a sensing plate using an avidin-biotin reaction to immobilize it for high density and to improve antibody alignment. In addition, as the detected terahertz signals vary depending on the sensitivity of the sensing plate, the sensitivity was evaluated using pH measurement. The result of the cancer cell detection was corrected using the result of pH measurement. These results indicate that a TCM is expected to be an excellent candidate for liquid biopsies in cancer diagnosis.
Study on Multi-Model Soft Sensor Modeling Method and Its Model Optimization for the Fermentation Process of Pichia pastoris
Authors: Wang Bo , Wang Xingyu , He Mengyi , Zhu Xianglin
Published: November 2021

The problems that the key biomass variables in Pichia pastoris fermentation process are difficult measure in real time; this paper mainly proposes a multi-model soft sensor modeling method based on the piecewise affine (PWA) modeling method, which is optimized by particle swarm optimization (PSO) with an improved compression factor (ICF). Firstly, the false nearest neighbor method was used to determine the order of the PWA model. Secondly, the ICF-PSO algorithm was proposed to cooperatively optimize the number of PWA models and the parameters of each local model. Finally, a least squares support vector machine was adopted to determine the scope of action of each local model. Simulation results show that the proposed ICF-PSO-PWA multi-model soft sensor modeling method accurately approximated the nonlinear features of Pichia pastoris fermentation, and the model prediction accuracy is improved by 4.4884% compared with the weighted least squares vector regression model optimized by PSO.
Development of a Low-Cost Optical Sensor to Detect Eutrophication in Irrigation Reservoirs
Authors: Rocher Javier , Parra Lorena , Jimenez Jose M. , Lloret Jaime , Basterrechea Daniel A.
Published: November 2021

In irrigation ponds, the excess of nutrients can cause eutrophication, a massive growth of microscopic algae. It might cause different problems in the irrigation infrastructure and should be monitored. In this paper, we present a low-cost sensor based on optical absorption in order to determine the concentration of algae in irrigation ponds. The sensor is composed of 5 LEDs with different wavelengths and light-dependent resistances as photoreceptors. Data are gathered for the calibration of the prototype, including two turbidity sources, sediment and algae, including pure samples and mixed samples. Samples were measured at a different concentration from 15 mg/L to 4000 mg/L. Multiple regression models and artificial neural networks, with a training and validation phase, are compared as two alternative methods to classify the tested samples. Our results indicate that using multiple regression models, it is possible to estimate the concentration of alga with an average absolute error of 32.0 mg/L and an average relative error of 11.0%. On the other hand, it is possible to classify up to 100% of the samples in the validation phase with the artificial neural network. Thus, a novel prototype capable of distinguishing turbidity sources and two classification methodologies, which can be adapted to different node features, are proposed for the operation of the developed prototype.
A Wearable Soft Fabric Sleeve for Upper Limb Augmentation
Authors: Hoang Trung Thien , Sy Luke , Bussu Mattia , Thai Mai Thanh , Low Harrison , Phan Phuoc Thien , Davies James , Nguyen Chi Cong , Lovell Nigel H. , Do Thanh Nho
Published: November 2021

Soft actuators (SAs) have been used in many compliant robotic structure and wearable devices, due to their safe interaction with the wearers. Despite advances, the capability of current SAs is limited by scalability, high hysteresis, and slow responses. In this paper, a new class of soft, scalable, and high-aspect ratio fiber-reinforced hydraulic SAs is introduced. The new SA uses a simple fabrication process of insertion where a hollow elastic rubber tube is directly inserted into a constrained hollow coil, eliminating the need for the manual wrapping of an inextensible fiber around a long elastic structure. To provide high adaptation to the user skin for wearable applications, the new SAs are integrated into flexible fabrics to form a wearable fabric sleeve. To monitor the SA elongation, a soft liquid metal-based fabric piezoresistive sensor is also developed. To capture the nonlinear hysteresis of the SA, a novel asymmetric hysteresis model which only requires five model parameters in its structure is developed and experimentally validated. The new SAs-driven wearable robotic sleeve is scalable, highly flexible, and lightweight. It can also produce a large amount of force of around 23 N per muscle at around 30% elongation, to provide useful assistance to the human upper limbs. Experimental results show that the soft fabric sleeve can augment a user’s performance when working against a load, evidenced by a significant reduction on the muscular effort, as monitored by electromyogram (EMG) signals. The performance of the developed SAs, soft fabric sleeve, soft liquid metal fabric sensor, and nonlinear hysteresis model reveal that they can effectively modulate the level of assistance for the wearer. The new technologies obtained from this work can be potentially implemented in emerging assistive applications, such as rehabilitation, defense, and industry.
Cerium(IV) and Iron(III) Oxides Nanoparticles Based Voltammetric Sensor for the Sensitive and Selective Determination of Lipoic Acid
Authors: Ziyatdinova Guzel , Gimadutdinova Liliya
Published: November 2021

A novel voltammetric sensor based on CeO2·Fe2O3 nanoparticles (NPs) has been developed for the determination of lipoic acid, playing an essential role in aerobic metabolism in the living organism. Sensor surface modification provides a 5.6-fold increase of the lipoic acid oxidation currents and a 20 mV anodic shift of the oxidation potential. The best voltammetric parameters have been obtained for the 0.5 mg mL−1 dispersion of CeO2·Fe2O3 NPs. Scanning electron microscopy (SEM) confirms the presence of spherical NPs of 25–60 nm, and their aggregates evenly distributed on the electrode surface and formed porous coverage. This leads to the 4.4-fold increase of the effective surface area vs. bare glassy carbon electrode (GCE). The sensor shows a significantly higher electron transfer rate. Electrooxidation of lipoic acid on CeO2·Fe2O3 NPs modified GCE is an irreversible diffusion-controlled pH-independent process occurring with the participation of two electrons. The sensor gives a linear response to lipoic acid in the ranges of 0.075–7.5 and 7.5–100 μM with the detection limit of 0.053 μM. The sensor is selective towards lipoic acid in the presence of inorganic ions, ascorbic acid, saccharides, and other S-containing compounds. The sensor developed has been tested on the pharmaceutical dosage forms of lipoic acid.
An Efficient Approach Using Knowledge Distillation Methods to Stabilize Performance in a Lightweight Top-Down Posture Estimation Network
Authors: Park Changhyun , Lee Hean Sung , Kim Woo Jin , Bae Han Byeol , Lee Jaeho , Lee Sangyoun
Published: November 2021

Multi-person pose estimation has been gaining considerable interest due to its use in several real-world applications, such as activity recognition, motion capture, and augmented reality. Although the improvement of the accuracy and speed of multi-person pose estimation techniques has been recently studied, limitations still exist in balancing these two aspects. In this paper, a novel knowledge distilled lightweight top-down pose network (KDLPN) is proposed that balances computational complexity and accuracy. For the first time in multi-person pose estimation, a network that reduces computational complexity by applying a “Pelee” structure and shuffles pixels in the dense upsampling convolution layer to reduce the number of channels is presented. Furthermore, to prevent performance degradation because of the reduced computational complexity, knowledge distillation is applied to establish the pose estimation network as a teacher network. The method performance is evaluated on the MSCOCO dataset. Experimental results demonstrate that our KDLPN network significantly reduces 95% of the parameters required by state-of-the-art methods with minimal performance degradation. Moreover, our method is compared with other pose estimation methods to substantiate the importance of computational complexity reduction and its effectiveness.
Fundamental Studies on the Use of Distributed Fibre Optical Sensing on Concrete and Reinforcing Bars
Authors: Galkovski  Tena , Lemcherreq Yasmin , Mata-Falcón Jaime , Kaufmann Walter
Published: November 2021

Distributed fibre optical sensing (DFOS) allows for quasi-continuous strain measurement in a broad range of gauge lengths and measurement frequencies. In particular, Rayleigh backscatter-based coherent optical frequency domain reflectometry has recently registered a significant application increase in structural concrete research and monitoring thanks to its numerous merits, such as high resolution and low invasiveness. However, it is not a plug-and-play technique. The quality of the acquired data depends highly on the choice of the fibre optical sensor and the methods of instrumentation and post-processing. Furthermore, its unprecedented resolution and sensitivity allow capturing local effects not well documented so far. This paper analyses the suitability of DFOS based on Rayleigh backscatter for reliably measuring strains and discusses the origin and structural relevance of local variations in the results. A series of experimental investigations are presented, comprising tensile tests on bare reinforcing bars and concrete compression tests. A critical analysis of the results leads to a best practice for applying DFOS to reinforcing bars and concrete, which establishes a basis for reliable, accurate measurements in structural concrete applications with bonded reinforcement.
Advances in Biosensors Technology for Detection and Characterization of Extracellular Vesicles
Authors: Bari Saif Mohammad Ishraq , Hossain Faria Binte , Nestorova Gergana G.
Published: November 2021

Exosomes are extracellular vehicles (EVs) that encapsulate genomic and proteomic material from the cell of origin that can be used as biomarkers for non-invasive disease diagnostics in point of care settings. The efficient and accurate detection, quantification, and molecular profiling of exosomes are crucial for the accurate identification of disease biomarkers. Conventional isolation methods, while well-established, provide the co-purification of proteins and other types of EVs. Exosome purification, characterization, and OMICS analysis are performed separately, which increases the complexity, duration, and cost of the process. Due to these constraints, the point-of-care and personalized analysis of exosomes are limited in clinical settings. Lab-on-a-chip biosensing has enabled the integration of isolation and characterization processes in a single platform. The presented review discusses recent advancements in biosensing technology for the separation and detection of exosomes. Fluorescent, colorimetric, electrochemical, magnetic, and surface plasmon resonance technologies have been developed for the quantification of exosomes in biological fluids. Size-exclusion filtration, immunoaffinity, electroactive, and acoustic-fluid-based technologies were successfully applied for the on-chip isolation of exosomes. The advancement of biosensing technology for the detection of exosomes provides better sensitivity and a reduced signal-to-noise ratio. The key challenge for the integration of clinical settings remains the lack of capabilities for on-chip genomic and proteomic analysis.
Confeccionando Territorios
Authors: Valdivieso Diego
Published: November 2021

Este artículo explora cómo el trabajo técnico y las decisiones burocráticas de funcionarios públicos en la primera línea de implementación de programas de desarrollo estatales intervienen en la generación y reformulación de categorías identitarias y territoriales. La ejecución de una metodología participativa en base a la generación de ‘mapas parlantes’ llevada a cabo por los funcionarios a cargo del Programa de Desarrollo Territorial Indígena (PDTI) en la isla Quehui, en el archipiélago de Chiloé, gatilló que uno de los grupos de usuarios que participaba en la actividad reforzara su deseo de formar una junta de vecinos que representara sus propios intereses. Este ejemplo etnográfico permite ilustrar cómo el Estado descentralizado interfiere en la arena política local al utilizar categorías identitarias y un enfoque topográfico, en desmedro de uno topológico, que no presta atención a la porosidad y permeabilidad de las fronteras territoriales.
PEMANFAATAN SUPERVISI EDUKATIF KOLABORATIF SECARA PERIODIK SEBAGAI UPAYA PENINGKATAN KINERJA GURU DALAM PEMBELAJARAN DI KELAS SMP NEGERI 3 IBUN
Authors:   SMPN 3 Ibun, Kab. Bandung, Juariyah Ida
Published: November 2021

The Purpose of the study is describing the steps of collaborative educative supervision periodically in preparing learning plans, implementing, assessing learning achievement, carrying out follow-up on student learning achievements that can improve teacher performance. This research was carried out at SMP Negeri 3 Ibun, Bandung Regency, starting from supervision on March 7th. until September 2018 This performance improvement is carried out through periodic collaborative educational supervision. The data collection method in this study consisted of four main activities, namely initial data collection, data analysis results at the end of each cycle, as well as other responses from teachers to the implementation of collaborative educational supervision. Based on the results of these studies, it can be concluded that teacher performance increases in preparing lesson plans, implementing learning, assessing learning achievement, carrying out follow-up assessments of student achievement.
How do Key Populations Cope their Behaviour Related Stigma? A Qualitative Study in a Province in Sri Lanka
Authors: Fernando T.S.M. , Vidanapathirana H.M.J.P.
Published: November 2021

Key populations are at the highest risk of acquiring and transmitting the Human Immuno-deficiency Virus (HIV). Due to the stigma vested upon them, they have become least accessible for preventive and curative services for HIV. Therefore, coping strategies are essential to minimize stigma to end AIDS by 2025, five years ahead of the global target of ending AIDS in 2030.
The objective was to describe the coping strategies adopted by key-populations to overcome behavior-related stigma.
Data from thirty-two in-depth interviews were analyzed using the thematic analysis method.
Pengungkapan Kuantitatif dan Kualitatif Segmen Operasi Berdasarkan PSAK 5 Revisi 2009 (Penyesuaian 2015) di Indonesia
Authors: Fakhriyyah Dewi Diah , Hidayati Irma
Published: November 2021

Reporting of operating segments has become an important concern, therefore there is a PSAK 5 regulation which is continuously updated based on IFRS 8 to improve operating segment reporting. This study aims to examine the application of operating segment disclosure and its determinants in public companies in Indonesia.This research method is quantitative method. The operating segment in the financial statements of the LQ 45 Index’s Company in 2016 is analyzed by scoring to the items required by PSAK 5 Revised 2009 (Amandement 2015). The results showed that the majority cozmpany's compliance level of quantitative information is medium level of compliance,. Quantitative disclosure shows the most reported items are profit loss and total assets, meanwhile the least reported item is other non current assets and main customer information . Meanwhile, the most reported item of qualitative disclosure is the main products and services which generate revenues for the operating segments. This study shows that companies disclose more quantitative information than qualitative. In addition, the good corporate governance mechanism that determines the extent of disclosure of operating segments is institutional ownership and the board of directors. This research has implications for operating segment regulators to do better and contribute to the agency theory and signaling theory.
La difusión del patrimonio arqueológico a través de las nuevas tecnologías
Authors: Raies Alejandra
Published: November 2021

Este trabajo versa sobre la utilidad de la implementación de nuevas tecnologías, tales como drones, fotogrametría, entornos virtuales e impresiones 3D, para la generación de conocimiento y soporte de los procesos de registro, análisis, conservación, difusión y divulgación del patrimonio arqueológico. Específicamente expondremos la aplicación de estas técnicas para la reconstrucción y recreación tridimensional de las baterías costeras y el devenir de la batalla acontecida el 20 de noviembre de 1845 en Vuelta de Obligado (Buenos Aires, Argentina). El fin último perseguido fue facilitar la trasmisión del conocimiento generado tras las investigaciones arqueológicas en el sitio, buscando lograr una representación lo más completa y fidedigna posible del proceso histórico. Asimismo, estas recreaciones no solo proporcionaron otros modos de percepción, sino que permitieron una explicación más clara y precisa del sitio, el registro arqueológico y su interpretación, favoreciendo la comprensión de la complejidad del campo bélico de la batalla. Los modelados de creación propia logrados (no procedentes de la realidad o de paralelismos) admiten no solo su uso como recurso didáctico y de divulgación patrimonial para colegas, científicos y la sociedad en general, sino que además nos permitieron generar, a modo de herramienta, nuevas preguntas o expectativas arqueológicas respecto al sitio.
Validez del diámetro de la vaina del nervio óptico por ultrasonografía para el diagnóstico de hipertensión intracraneana en traumatismo craneoencefálico severo
Authors: Zamora-Cueva Rodrigo , Vásquez-Tirado Gustavo
Published: November 2021

Objetivo: Determinar la validez del diámetro de la vaina del nervio óptico por ultrasonografía para el diagnóstico de hipertensión intracraneana en pacientes con traumatismo craneoencefálico severo. Material y métodos: Se Realizó un estudio de prueba diagnosticas que evaluó a 43 pacientes con sospecha de hipertensión intracraneana secundario a un traumatismo craneoencefálico severo, que cumplieron los criterios diagnósticos según la “Regla de Decisión Clínica” basado en hallazgos clínicos y tomográficos, luego se realizaron mediciones de la vaina del nervio óptico por ultrasonografía en el Hospital Regional Docente de Trujillo entre Mayo del 2019 -Enero del 2020. Resultados: De un total de 43 pacientes, al procesar los datos mediante la curva ROC, se obtuvo un punto de corte del diámetro de la vaina del nervio óptico de 6,05 mm equivalente a hipertensión intracraneana, con un área bajo la curva (AUC) de 0,776 (P=0,004); sensibilidad, especificidad, valor de predicción positiva y negativa de 82,76%, 57,14%, 80% y 61,54% respectivamente. No se encontraron diferencias significativas entre los 2 grupos en cuanto a sexo, edad, anisocoria e hipotensión arterial diastólica. Conclusiones: El diámetro de la vaina del nervio óptico medido por ultrasonografía tiene validez para el diagnóstico de hipertensión intracraneana secundario a un traumatismo craneoencefálico severo.
Nivel de conocimientos sobre certificados de defunción en médicos recién egresados
Authors: Soto-Cáceres Víctor Alberto
Published: November 2021

Objetivo: Precisar el nivel de conocimientos sobre el llenado correcto de certificados de defunción en médicos que inician servicio rural urbano marginal de salud (SERUMS). El estudio: Diseño descriptivo transversal. Población: asistentes al curso de inducción SERUMS: 86 recién egresados. Instrumento: cuestionario con preguntas basadas en la “Guía Técnica para el correcto llenado de certificados de defunción 2018” Ministerio de Salud. Hallazgos: 23% del total tiene nivel pésimo, 41% malo, 34% regular y 2% bueno; la mayoría no sabe precisar la causa básica de muerte y 98% no considera como causa básica la circunstancia del accidente y 85% desconocen sobre SINADEF. Conclusiones: El nivel de conocimientos sobre el llenado correcto de certificado de defunción es muy bajo con gran desconocimiento para ubicar causa básica de muerte.
Factores asociados a inadecuadas prácticas de distanciamiento social durante la pandemia por COVID-19 en Perú
Authors: Diaz-Lazo Aníbal V. , Ruiz-Aquino Mely , Beraún-Barrantes José Antonio , Arroyo-Hernández Hugo
Published: November 2021

Objetivo: Determinar los factores asociados a inadecuadas prácticas de distanciamiento social durante la pandemia por COVID-19 en Perú. Material y métodos. Se administró una encuesta en línea dirigida para adultos de diversas regiones del Perú seleccionados mediante un muestreo por bola de nieve, la encuesta incluía una escala para la medición de prácticas de distanciamiento social, el uso de la información, el afrontamiento emocional frente al coronavirus y características sociodemográficas. Se realizó un análisis bivariado y multivariado utilizando razones de prevalencia cruda (RP) y ajustadas (RPa) con intervalos de confianza al 95 % por medio de modelos lineales generalizados. Resultados. Se incluyeron 377 personas de los cuales el 55,4 % fueron hombres y 77,5 % residían fuera de Lima, el 35 % de los encuestados tuvo inadecuadas prácticas de distanciamiento social lo que estuvo asociado con tener primaria o secundaria incompleta (RPa 1,41, IC 95 %: 1,11 a 1,81), inadecuado uso de la información (RPa 2,82, IC 95 %: 1,98 a 4,05) e inadecuado afrontamiento emocional frente al coronavirus (RPa 1,76, IC 95 %: 1,27 a 2,42). Conclusión. Personas con menor grado de instrucción, inadecuado uso de la información y con un negativo afrontamiento emocional frente al coronavirus tienen mayor probabilidad de inadecuadas prácticas de distanciamiento social.
Nivel de resiliencia del personal de salud frente a la pandemia por Covid-19
Authors: Gamboa-Moreno Linda Noheli , Becerra-Rodríguez Kira Galina , López-Vergara Yara Irene , Goicochea-Ríos Evelyn
Published: November 2021

Introducción: La resiliencia es un factor determinante para ayudar a afrontar alguna situación de estrés, por ello el objetivo de nuestro estudio, fue medir el nivel de resiliencia en el personal de salud en dos hospitales de la ciudad de Trujillo frente a la pandemia por Covid-19. El estudio: Se realizó un estudio descriptivo transversal con 106 trabajadores de salud, a quienes mediante una entrevista se les administró un cuestionario compuesto de 25 ítems. Hallazgos: Se encontró que la mayor parte de participantes fueron del sexo femenino (67,9% vs 32,1%) y 40,6%, personal médico. En ambos hospitales se halló un nivel alto de resiliencia, 95% en el Hospital La Noria y 98% en EsSalud-La Esperanza. Conclusiones: El personal de salud presentó nivel alto de resiliencia frente a la pandemia del Covid-19.
Dosis de refuerzo con la vacuna BNT162b2 en población que recibió el esquema de vacunación completa para COVID-19 en Perú: Un análisis crítico de la evidencia actual*
Authors: Toro-Huamanchumo Carlos J. , Zavala-Loayza José A. , Martinez-Rivera Raisa N. , Peralta Verónica , Peña-Sánchez Eric R.
Published: November 2021

Introducción: En el Perú, el programa actual de inmunización para COVID-19 comprende las vacunas BBIBP-CorV, BNT162B2 y ChAdOx1 nCoV-19. Si bien el esquema de inmunización es de dos dosis, algunos países han incluido recientemente una dosis de refuerzo a su esquema. Métodos: Se realizó una búsqueda de evidencia científica sobre la eficacia y seguridad de la vacunación de refuerzo con la vacuna BNT162b2 en población con esquema de vacunación completa para COVID-19 en Perú. Evidencia incluida: Se consideraron cuatro documentos de recomendación basados en evidencia, un estudio observacional y tres ensayos clínicos fase III en curso. Conclusión: A la fecha, no existe evidencia suficiente sobre la eficacia de agregar una dosis de refuerzo al esquema de inmunización para COVID-19. La evidencia disponible no permite justificar el uso de una dosis de refuerzo con la vacuna BNT162B2 en población que recibió previamente dos dosis de las vacunas anteriormente mencionadas.
Programa interdisciplinario de Medicina Física y Rehabilitación en las unidades de cuidados intensivos de un hospital de referencia en Lima, Perú
Authors: De la Cerna-Luna Roger , Calderón-Berrio Alan , Tang-Candiotti Romina , Ramírez-Chipana Mabel , Taype-Rondan Alvaro
Published: November 2021

Carta al editor ( Sin resumen )
Uso de la morfina en el manejo sintomático de la disnea en pacientes con COVID-19
Authors: Azañero-Haro Johan , Soto Alonso
Published: November 2021

Carta al editor ( Sin resumen )
Riesgo de aerolización como limitante para el uso de cánulas de alto flujo en pacientes con insuficiencia respiratoria por Covid-19 de hospitales de recursos limitados
Authors: Vergara-Tam Rodrigo , Ruesta-Berdejo Ramón , Ccami-Bernal Fabricio , Castillo-Peña Luis , Arredondo-Nontol Miriam
Published: November 2021

Carta al Editor ( Sin resúmen )
Development of ESG Banking in Russia
Authors: Bezgacheva O. L. , Rumyantseva A. Yu.
Published: November 2021

Aim. The presented study aims to assess the current state of the banking sector of the economy and its potential for the development of ESG banking and implementation of ESG standards.

Tasks. The authors analyze the current level of ESG standards implementation and the banks’ readiness to further implement ESG standards.

Methods. This study uses general scientific methods of cognition to analyze the problems and obstacles that arise during ESG standards implementation in banking practice.

Results. The banking community’s participation in the funding of sustainable development projects is selective rather than overarching, with banks choosing individual banking products. Reports marginally trace their participation in lending to business projects related to the circular economy of various industries.

Conclusions. The special place of the banking sector in the national economy and its interaction with the real sector of the economy offer great potential for the development of ESG standards, making it possible to introduce ESG technologies both in banking activities and in their active promotion to other sectors of the economy through customers, thereby accelerating the transition towards a circular economy in Russia. The strength of the Russian banking system has been tested in recent years, and it embraces the formation of new rules of economic behavior. By overcoming existing obstacles, banks will be able to switch to ESG standards in the coming years, thus becoming pioneers in doing business based on the principles of environmental, social, and managerial responsibility.
Foundations of Hungarian Defence Policy
Authors: Bak Pál , Németh Gergely , Szőke Diána
Published: November 2021

This article aims to outline the foundations of contemporary Hungarian defence policy thinking, highlighting the factors which have shaped it during the last years. Hungary lies in a unique geostrategic position, at the crossroads of ‘eastern’ and ‘southern’ challenges. The study therefore begins by presenting an overview of Hungary’s place in the global security environment, especially in light of the instability currently characterising certain regions on Europe’s periphery. It then goes on to discuss the institutional framework of Hungarian security and defence policy, primarily concentrating on NATO and the EU CSDP. The newly adopted National Security Strategy, together with the National Military Strategy (currently under review) serve as the starting point for the analysis.Our study also pays particular attention to Hungary’s large-scale military modernisation programme, the Zrínyi Programme. Based on this, the authors identify three major challenges shaping the medium-term outlook for Hungarian defence policy. These are (i) the pressures of illegal mass migration; (ii) the challenges of transnational terrorism; along with (iii) the activity and potential for conflict among regional and global powers. In addition, the article briefly highlights the future challenges that Hungary must reckon with, including the security-related implications of global climate change, energy dependency, cyber defence, together with the proliferation of nuclear and conventional weapons.
Underwater Ad-Hoc Networks: A Review
Authors: Wengle Emil , Potter John , Dong Hefeng
Published: November 2021

Underwater sensor networks have become increasingly interesting in the past four decades. They can be used in a multitude of scenarios, commercial and military alike. Underwater networks can communicate in several ways, but when nodes are far apart, underwater acoustic communication is the only feasible way. The complex underwater acoustic channel puts high demands on the network protocols. The physical layer needs to contend with short coherence times, high intersymbol interference and significant Doppler spread. The routing protocol needs to handle intermittent connectivity and mobile network topologies, such as autonomous underwater vehicle networks. The medium access control protocol needs to manage medium access with high latency and potentially high packet loss ratios without congesting the network. The available acoustic modems are still rather expensive, which limits the size of a sensor network. Voices have also been raised from the academia for a paradigm shift, from hardware-defined, proprietary modems to software-defined, open-architecture modems, in order to accelerate research in the field and enable interoperability. This paper reviews the recent advancements in designing and implementing underwater networks on several levels and discusses some interesting approaches to underwater ad-hoc networking. The focus lies on acoustic communication.
Why We Should Be Skeptical of Quantum Computing
Authors: Kadin Alan
Published: November 2021

It is widely believed that quantum computing is on the threshold of practicality, with performance that will soon greatly surpass that of classical computing. On the contrary, I argue that quantum computing does not currently exist, and probably never will. First, although quantum annealing systems have been demonstrated to solve practical optimization problems, they are actually performing classical analog annealing, with no quantum enhancement. In contrast, while systems of quantum gate arrays, which are expected to perform digital quantum computing, have been fabricated with up to ~ 100 qubits in several technologies, they have not performed any practical computations. This is not merely a question of excess noise; the theory of massive quantum entanglement, necessary for the desired performance, has never been actually been verified. The well-established quantum results such as electronic energy bands do not incorporate quantum entanglement. I suggest that the experimental observations in multi-qubit systems may be explained as the result of delocalized coupled oscillator modes, similar to that in electronic energy bands. Such coupled modes would not yield the exponential increase in degrees of freedom needed for quantum speedup, and hence would not be useful for computing. Tests on these multi-qubit systems should be able to distinguish these two models. The quantum computing research community really needs to address this issue.
TFW: Annotated Thermal Faces in the Wild Dataset
Authors: Kuzdeuov Askat , Aubakirova Dana , Koishigarina Darina , Varol Hüseyin Atakan
Published: November 2021

Face detection and localization of facial landmarks are the primary steps in building many face applications in computer vision. Numerous algorithms and benchmark datasets have been proposed to develop accurate face and facial landmark detection models in the visual domain. However, varying illumination conditions still pose challenging problems. Thermal cameras can address this problem because of their operation in longer wavelengths. However, thermal face detection and localization of facial landmarks in the wild condition are overlooked. The main reason is that most of the existing thermal face datasets have been collected in controlled environments. In addition, many of them contain no annotations of face bounding boxes and facial landmarks. In this work, we present a thermal face dataset with manually labeled bounding boxes and facial landmarks to address these problems. The dataset contains 9,202 images of 145 subjects, collected in both controlled and wild conditions. As a baseline, we trained the YOLOv5 object detection model and its adaptation for face detection, YOLO5Face, on our dataset. To show the efficacy of our dataset, we evaluated these models on the RWTH-Aachen thermal face dataset in addition to our test set. We have made the dataset, source code, and pretrained models publicly available at https://github.com/IS2AI/TFW to bolster research in thermal face analysis.
Practical Compact Routing on Sparse Graphs
Authors: Hormann Kai , Gotsman Craig
Published: November 2021

We describe a simple and practical algorithm for compact routing on graphs which admit compact and balanced vertex separators. Using a recursive nested dissection of then-vertex graph based on these separators, we construct routing tables with as few as O(log n) entries per vertex in a preprocessing step. They support handshaking-based routing on the graph with moderate stretch, where the handshaking can be implemented similarly to a DNS lookup. We describe a basic version of the algorithm that requires modifiable headers and a more advanced version which eliminates this need and provides better stretch. A number of algorithmic parameters control a graceful tradeoff between the size of the routing tables and the stretch. Our routing algorithm is most effective on planar graphs and unit disk graphs of moderate edge/vertex density.
UNPark, Milan. A social innovation experiment beneath the Serra Monte Ceneri Flyover
Authors: Carli Paolo , Scrugli Patrizia
Published: November 2021

Urban infrastructure in high-density metropolitan contexts constitutes an experimental frontier for improving the citizens’ quality of life and also represents a still undervalued resource in producing economic, energy, environmental and social value. Infrastructure such as the Serra Monte Ceneri Flyover in Milan, a source of distress and degradation associable with the idea of “wasted architecture”, can only be transformed into resource through a process of enhancement and a circular, multi-layer and multi-functional design vision. UNPark research is configured as an urban innovation hub by which to trigger reflection on the transition potential towards infrastructure multifunctionality.