bluuebunny/crossref_metadata_2025 huggingface dataset:
RELATIONSHIP BETWEEN STRESS LEVEL AND INCREASED BLOOD SUGAR LEVELS IN PATIENTS WITH DIABETES MELLITUS
Authors: Susanti Susanti , Bistara Difran Nobel
Published: March 2023

Diabetes Mellitus is a chronic disease that requires a long treatment time, funding very expensive treatment, besides the prevalence of diabetes mellitus is also increasing. The necessity of people with diabetes mellitus in changing their lifestyle so that blood sugar in the body remains balanced can make them vulnerable to stress. Stress and Diabetes Mellitus have a very close relationship, especially in urban residents. Stress in people with diabetes mellitus can cause problems in controlling blood sugar levels. The purpose of the study was to determine the relationship between stress levels and blood sugar levels in people with Diabetes Mellitus. This study used an observational analytic method with a cross sectional approach with a sample of 45 respondents with diabetes mellitus in the RW 7 Simokerto Village, Simkerto District, Surabaya, which was taken using simple random sampling technique. Measurement of stress levels using a questionnaire. Blood sugar levels were obtained from observations using a glucometer at random. Data were analyzed using Spearman Rho correlation test. Spearman rank correlation test results obtained p = 0.00 and r = 0.909. This means that there is a relationship between stress levels and blood sugar levels in people with diabetes mellitus (H0 rejected, H1 accepted) and shows a very strong positive correlation between stress levels and blood sugar levels. The majority of respondents with stress levels in the non-stress category (score 0–3) had blood sugar levels in the normal category (80-140mg/dL). The higher the level of stress experienced, the higher the value of blood sugar levels. Suggestions for further researchers are to investigate other factors that can affect blood sugar levels, as well as to observe stress behavior so that the results are more valid.
THE DESCRIPTION OF STRESS LEVELS OF PARENTS ACCOMPANYING CHILDREN STUDY FROM HOME (SFH) DURING THE COVID-19 PANDEMIC
Authors: Yuliani Feri Catur , Hermawati Erlina , Nurinnafi’a Ahda Maulida Ulufan
Published: March 2023

The current case of the spread of Covid-19 in Indonesia is still very massive, the Ministry of Education and Culture issued a policy for learning activities to be carried out from home. During the implementation of learning from home, it turns out that there are many obstacles that are felt by educators and parents so that it triggers stress on parents. The purpose of this study was to determine the results of parents' stress levels which could be a consideration for educators to choose the right method when carrying out learning from home according to the abilities of their parents. This type of research is descriptive with a quantitative approach. Descriptive analysis is data analysis by describing or describing the data that has been collected. The sampling technique used was consecutive sampling with a sample of 717 respondents and data collection by questionnaires containing identity, informed consent, and Perceived Stress Scale (PSS) questionnaires. The results of The Description of Stress Levels of Parents Accompanying Children Study From Home (SFH) during the Covid-19 Pandemic showed that 8% of respondents experienced severe stress, 75% experienced moderate stress, and 16% experienced mild stress.
Pengaruh penambahan tepung kedelai (Glycine max) dan kopi bubuk robusta terhadap sifat kimia dan organoleptik brownies
Authors: Utomo Deny , Muslimah Devi Putri
Published: March 2023

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Pengaruh Perbedaan Konsentrasi Maltodekstrin dan Na-CMC terhadap Sifat Fisikokimia Bubuk Buah Semangka Merah
Authors: Jati Ignasius Radix A.P. , Birgitta Artadila Kusuma  , Erni Setijawaty  , Rachel Meiliawati Yoshari
Published: March 2023

Red watermelon is commonly served as fresh cut fruit or juice. In order to broaden the use of watermelon, it can also be processed into powder. The purpose of this research was to determine the effect of different types of encapsulation and concentrations of Maltodextrin and Na-CMC on the physicochemical properties of watermelon powder. In this research, the red watermelon juice that mixed with maltodextrin and Na-CMC as encapsulants was dried using a cabinet dryer at a temperature of 60-65°C for 6 hours. The treatment levels of maltodextrin were 6%, 12% and 18%, while the Na-CMC levels was 2.5%, 5% and 7.5%. All of the treatments were repeated three times. The tests carried out included moisture content, hygroscopic level, total phenol, antioxidant activity, color and pH. The results showed that the red watermelon powder with the addition of maltodextrin has a water content of 1.68-3.65%; hygroscopic level between 9.27-11.56%; total phenol content of 437.9543-887.9543 mg GAE/g, antioxidant activity of 34.15-75.79% , color of L=49,.0-61,; C=25.4-28.2; H=33.6°-35.7° and pH value of 6.14-6.34. Meanwhile, red watermelon powder with the addition of Na-CMC has a water content of 2.85-3.67%; hygroscopic level 16.87-23.65%; total phenol 224.3183-673.1820 mg GAE/g, antioxidant activity 23.51-72.71% RSA, color with L=42.8-46.0;C=27.8-30.1; H=26.4°-28.7°, and pH 7.10-7.51.Therefore, maltodextrin and Na-CMC can potentially  be used for encapsulation of red watermelon powder.
The Effectiveness of Underwater LED as a Fish Aggregating Device on a Fixed-Liftnet in Pangkep Waters
Authors: U Fatma , Kurnia Muhammad , Musbir Musbir , Sahil M. Sahil Rizky Bin , Putera Dion Pratama , Al Haq Suci Insyirah
Published: March 2023

The rapid development of electrical technology in the field of fishing, especially utilizing the light to collect fish into the catchable area. Generally, Light emitting diode (LED) lamps for fishing are placed above the water surface. The success of this technology has become the basis for conducting experiments with the position of the lamp in the water to see its effectiveness as a fish collection device. The aim is to develop the application of light fishing technology by; (1) testing the effectiveness of using LED lights in collecting fish in the fixed lift-net catchable area to increase the number of catches; (2) assessing the quality of the catch, namely main and by-catch. The research was carried out in May-October 2022 in the Pangkajene and Islands Regency waters. The case method is one unit of fixed lift-net using 4 units of LED underwater lights with a power of 60 W. Data collecting with experimental fishing, namely following fishing operations for 40 trips. The parameters analyzed were the number and types of catches and the effectiveness of fishing gear based on fishing trips. The results showed that the catches types obtained were 15 species with 101.72 kg total catch. The number of catches is not significant, but the results of this study provide one hope, especially for Mitra fishermen. The innovation of LED underwater lights is new information that has good prospects as a more effective and environmentally friendly light capture device.
Kata kunci: Lampu Celup LED, bagan tancap, Perairan Pangkep
Length-Weight Relationship and Condition Factor of Yellowfin Tuna (Thunnus albacares) from Demta Coast, Jayapura Regency, Papua
Authors: Kalor John Dominggus , Paiki Kalvin , Rumahorbo Basa T.
Published: March 2023

The population of Thunnus albacares yellowfin tuna from the Scombridae family is very abundant in North Papua Waters (WPP 717). This study aims to analyze the parameters of population dynamics based on the long-weight relationship and condition factors on Thunnus albacares in Demta Coastal Waters, Jayapura Regency. Fish data collection uses passive and active fishing methods using gill nets, handlines, and long line fishing through fishing activities by traditional fishermen during April - June 2022. Data analysis uses analysis length-weight relationship and condition factor. The results of this study found that the population structure of yellowfin tuna (T. albaceras) was very diverse in the waters of North Papua, with a negative allometric growth pattern (b < 3), i.e. the growth of body length was faster than weight. The condition factor averaged 1.1302 with a maximum of 1.4718 and a minimum of 0.7028. Where in the gonadal maturity period morphometric adaptation occurs, weight growth becomes faster and body length becomes slower.
METASTATIC RENAL CELL CARCINOMA MASQUERADING AS A BREAST LUMPA CLINICAL INSIGHT INTO A SYNCHRONOUS CASE OF OLIGOMETASTATIC RENAL CELL CARCINOMA
Authors: Irshad Bhat Fibah , Faisal Masood Pirzada , Mushtaq Humaira
Published: March 2023

Introduction: Renal Cell Carcinoma (RCC), a highly vascular tumor may present with rare metastasis at initial presentation. Synchronous breast
metastasis from clear cell renal cell carcinoma is very rare and correlates with poor prognosis. In absence of any renal complaints, a breast lump can
mimic a primary breast carcinoma or benign breast disease. A 55-year-old fema Case History: le, presented with a swelling in the right breast.
Physical examination was suggestive of a benign swelling in view of well-dened margins, no lymphadenopathy, no skin changes. Fine needle
aspiration cytology was done twice and was inconclusive. Tru-Cut biopsy revealed metastatic RCC. Mammography showed BIRADS-IV lesion
and PET-CT revealed oligometastatic disease with breast and a small solitary lung metastasis. The patient underwent simultaneous right
cytoreductive nephrectomy and lumpectomy. Early detection and surgical resecti Conclusion: on of limited metastatic disease is important, as the
treatment instituted at an earlier stage when it is amenable to surgical resection improves the survival considerably
STATISTICAL LITERACY AMONG UNDERGRADUATE STUDENTS IN CHENNAI: A SURVEY STUDY
Authors: Roshan Marlecha Rhithik , Raguraman S
Published: March 2023

Background: Statistical literacy has been recognized as an essential knowledge for the undergraduate students to possess basic concept of
statistical knowledge. Aim: The aim of this study was to evaluate the level of statistical literacy among undergraduate students in Chennai.
Materials & Methods: The two-element model of statistical literacy by Gal (2004), knowledge component (comprised of ve cognitive elements:
literacy skills, statistical knowledge, mathematical knowledge, context knowledge, and critical questions) and a dispositional component
(comprised of two elements: critical stance, and beliefs and attitudes), was used. Asurvey was conducted on 283 undergraduate students of various
colleges of Chennai. Results: The results revealed that the undergraduate students had moderate level of overall statistical literacy, knowledge
component and a dispositional component. In the knowledge component, the students had high level of literacy skills and mathematical
knowledge, moderate level of statistical knowledge and low level of context knowledge. Additionally, in the dispositional component, the students
had moderate level of critical stance, and beliefs and attitudes. Conclusion:The practical implications for educators to improve students' statistical
literacy were discussed.
ORAL HYGIENE AWARENESS AND PRACTICE AMONGST PATIENTS VISITING THE DEPARTMENT OF PERIODONTOLOGY AT GOVERNMENT DENTAL COLLEGE AND HOSPITAL, JAMNAGAR
Authors: Panwar Sandhya , Patel Hetavi , Patel Nayana , Changela Radha , Verlianey Nisha , Sheth Malav
Published: March 2023

Background: Oral diseases are a major public health concern owing to their high prevalence and their effects on the individual's quality of life.
Although many studies have been carried out from time to time to assess the knowledge and behaviour of people about oral health, there is still a
lack of awareness and practice regarding the same. Aim: To assess oral hygiene awareness among patients visiting the Department of
Periodontology at Government Dental College and Hospital, Jamnagar Materials & Methods:Across-sectional study was carried out among 500
patients visiting the Department of Periodontology at Government Dental College and Hospital, Jamnagar. Subjects were selected using a
convenient sampling technique and were asked to ll a self-constructed questionnaire consisting questions regarding awareness and practices
related to oral hygiene. Responses from the patients were evaluated in terms of numbers and percentages. Results: The results of the study showed
an acute lack of oral hygiene awareness and limited knowledge of oral hygiene practices as well as effect of poor oral hygiene on systemic health.
Conclusion: There is an urgent need for comprehensive educational programs to promote good oral hygiene and impart education about correct
oral hygiene practices
CLINICAL PRESENTATION OF DENGUE IN COVID ERA
Authors: Padmanabhan K.
Published: March 2023

Dengue incidence been increasing in this decade but in the last year the care for dengue is changed because of COVID pandemic. Aim of this study
to analyze the presentation of dengue in this pandemic. Design of this study is Cross sectional, we retrospectively collected data of dengue positive
patients in a single UPHC and analyzed. This study involved 42 patients. The diagnosis was done mainly based on NS 1 Ag positivity. 65% had
thrombocytopenia but only 19% needed platelet transfusion. There is an elevation of SGPT & SGOT. As per prognosis 39 patients improved and 3
of the patients were shifted to tertiary centre
AWARENESS OF THE RELATIONSHIP BETWEEN SYSTEMIC AND PERIODONTAL DISEASES AMONG PHYSICIANS AND DENTISTS IN GUJARAT: A CROSSSECTIONAL STUDY.
Authors: Pate Hetavi , Panwar Sandhya , Patel Nayana , Changela Radha , Verlianey Nisha , Sheth Malav
Published: March 2023

Background & Objective: An association between oral conditions such as periodontal diseases and systemic conditions is noted. As such,
periodontal disease is associated with an increased risk of systemic illnesses such as cardiovascular disease, diabetes, adverse pregnancy outcome
and stroke. Keeping this in view, the present survey was designed to evaluate the acquaintance, orientation and behaviour of general medical
practitioners; concerning the effects of periodontal disease on systemic health. Materials and Methods: A typed questionnaire carrying sets of
questions was distributed among general dental practitioners and non-dental practitioners of Gujarat government and private set ups.
Questionnaire was developed to assess the acquaintance, orientation and behaviour of doctors towards periodontal disease. Results: Dental
practitioners have knowledge regarding the inter-relationship of periodontal disease and systemic conditions. And most of the non-dental
practitioners have knowledge regarding the inter-relationship of periodontal disease and diabetes mellitus. However, majority of them do not know
about the potential effect of periodontal disease on other organ systems. Conclusion: General medical practitioners have inadequate knowledge
regarding inter-relationship. Hence, oral health related training should be an integral part of the medical curriculum
Next-generation power substation communication networks: IEC 61850 meets programmable networks
Authors: Gutierrez Sergio , Botero Juan Felipe , Gaviria Natalia , Fletscher Luis Alejandro , Leal Erwin Alexander
Published: March 2023

The electrical grid undergoes a fundamental change with the introduction of the Smart Grid; in particular, power substations have been evolving towards automated systems. Power substation communication networks evolved from legacy infrastructures mostly formed by serial devices to Ethernet-based digital communications networks, thanks to the introduction of the IEC 61850 standard. However, this evolution inherited the shortcomings of the traditional decentralized network management. This paper explores the upcoming evolution of IEC 61850 when it meets the ground-breaking programmable network technologies: Software Defined Networks (SDN) and Programmable Data Planes (PDP). Here, we describe how recent proposals leverage SDN to improve network management tasks such as topology discovery, multicast traffic management, QoS provisioning, among others in IEC 61850 based systems. We also outline potential improvements to critical network management tasks in power substations using PDP features such as in-band network telemetry. Finally, we discuss different challenges in the management of the communication network of Smart Power Substations and how they can be addressed with the implementation of programmable networks
LPV Modeling and Robust Sampled-Data H∞ Control of a Tailless Flapping Wing Micro Aerial Vehicle With Parameter Uncertainties
Authors: Guo Qingcheng , Zhang Weiping , Deng Zhicheng , Mou Jiawang , Wu Chaofeng
Published: March 2023

In order to achieve improved tracking performance, this paper considers the distinct features of tailless flapping wing micro air vehicles (FWMAVs), and proposes a robust $\bm{H_{\infty}}$ controller.

A linear parameter Varying (LPV) model is established for a tailless FWMAV with parameter uncertainty, based on the complete dynamic and kinetic model with quasi-steady and linear damping.

Sampled data is used as feedback signals in controller design to overcome the influence of the control period not being much larger than the flapping period.

An input delay technique is employed to convert the sampled-data system into a continuous-time system with a state delay. The controller is restricted to a designed multivariable proportional-integral (PI) structure for practical engineering implementation.

A Lyapunov-Krasovskii function is employed to establish the stability and $\bm{H_{\infty}}$  performance of the closed-loop,  and an optimization problem involving linear matrix inequalities (LMIs) is obtained using diagonal Lyapunov matrix hypotheses.

Numerical simulations demonstrate the strong robustness of the proposed controller, and flight experiments verify its effectiveness and superior performance compared to a state-of-the-art benchmark controller.
Structure of the space of GL4 (Z2)-coinvariants Z2 ⊗ GL4 (Z2) P H∗ (Z42,Z2) in some generic degrees and its application
Authors: Võ Phúc Đặng
Published: March 2023

 Let $A$ denote the Steenrod algebra at the prime 2 and let $k = \mathbb Z_2.$ A very difficult problem in algebraic topology is to determine a minimal set of $A$-generators for the polynomial ring $P_q = k[x_1, \ldots, x_q] = H^{*}(k^{q}, k)$ on $q$ generators $x_1, \ldots, x_q$ with $|x_1|= |x_2| = \cdots = |x_q| =  1.$ Equivalently, one can write down explicitly a basis for the cohit space $\pmb{Q}^{q} := k\otimes_{A} P_q$ in each non-negative degree $n.$ This subject, which has now a long history, is the content of the classical "hit problem" proposed in [Abstracts Papers Presented Am. Math. Soc.  \textbf{833} (1987), 55-89]. Furthermore, it is closely related to the $q$-th transfer homomorphism $Tr_q^{A}$ constructed by William Singer in [Math. Z. \textbf{202} (1989), 493-523]. This $Tr_q^{A}$ passes from the space of $G(q)$-coinvariant $k\otimes _{G(q)} P_A((P_q)_n^{*})$ of $\pmb{Q}^{q}$ to the $k$-cohomology group of the Steenrod algebra, ${\rm Ext}_{A}^{q, q+n}(k, k),$ where $G(q)$ denotes the general linear group of degree $q$ over the field $k,$ whereas $P_A((P_q)_n^{*})$ is the primitive part of $(P_q)^{*}_n$ under the action of $A.$ Particularly, Singer conjectured that $Tr_q^{A}$ is a monomorphism, but this remains unanswered for all $q\geq 4.$ Accordingly, the aim of the present study is to deal with the Singer conjecture for rank 4 in certain internal degrees. Specifically, by the usage of the techniques of the hit problem in four variables, we explicitly determine the structure of $k\otimes _{G(4)} P_A((P_4)_{n}^{*})$ in some generic degrees $n.$ Then, applying these results and a representation of $Tr_4^{A}$ via the lambda algebra, we state that Singer's conjecture is true for rank $q = 4$ in respective degrees $n.$ This has contributed to the final proof of Singer's conjecture in the rank 4 case.
Targetless Extrinsic Calibration of Camera and Low-resolution 3D LiDAR
Authors: Ou Ni , Cai Yuhang , Yang Jiawen , Wang Junzheng
Published: March 2023

This article provides a targetless extrinsic calibration method between camera and low-resolution 3D LiDAR. We carried out real-world experiments on a multi-sensor platform containing a Velodyne VLP-16 LiDAR and a camera. Ground-truth extrinsic matrix is generated by a state-of-the-art target-based method. Regarding the calibration error, the rotation and translation RMSE of our method are 0.59° and 3cm respectively. Codes are avaible at https://github.com/gitouni/Targetless-LiDAR-camera-calibration.

NB: This article has been accepted for publication in IEEE Sensors Journal.  Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Citation Information: 10.1109/JSEN.2023.3263833
Targetless Extrinsic Calibration of Camera and Low-resolution 3D LiDAR
Authors: Ou Ni , Cai Yuhang , Yang Jiawen , Wang Junzheng
Published: March 2023

This article provides a targetless extrinsic calibration method between camera and low-resolution 3D LiDAR. We carried out real-world experiments on a multi-sensor platform containing a Velodyne VLP-16 LiDAR and a camera. Ground-truth extrinsic matrix is generated by a state-of-the-art target-based method. Regarding the calibration error, the rotation and translation RMSE of our method are 0.59 degree and 3cm respectively. We also open source our codes at github (See Section III-D).
Use of Federated Learning and Blockchain towards Securing Financial Services
Authors: Chatterjee Pushpita , Das Debashis , Rawat Danda
Published: March 2023

This paper presents a survey of FL and blockchain for financial security. 
Design of Variation-Tolerant 1F-1T Memory Array for Neuromorphic Computing
Authors: Rana Masud S K , Thunder Sunanda , Müller Franz , Laleni Nellie , Raffel Yannick , Lederer Maximilian , Pirro Luca , Chohan Talha , Hsuen Jing-Hua , Wu Tian-Li , Seidel Konrad , Kaempfe Thomas , De Sourav , Chakrabarti Bhaswar
Published: March 2023

This letter proposes a memory cell, denoted by 1F-1T, consisting of a ferroelectric field-effect transistor (Fe-FET) cascoded with another current-limiting transistor (T). The transistor reduces the impact of drain current (Id) variations by limiting the on-state current in FeFET, denoted by 1F. We have fabricated 28nm high-k-meta-gate (HKMG) based FeFETs, and the experimental data is used to model and simulate single-cell and memory arrays. The simulation shows significant improvement in bit-line (BL) current (IBL ) variation for 1F-1T memory array. Finally, the system-level neuromorphic simulation with 1F-1T synapses shows an inference accuracy of 97.6% for MNIST hand-written digits with multi-layer perceptron (MLP) neural networks.
A modular LoRa sensor network for research and industrial application
Authors: Neitzke Klaus-Peter
Published: March 2023

The paper describes the structure of a wireless sensor network. This is able to measure, transmit and store field sensor data from a rural environment. The data are stored at a web server and they are available on a web page. LoRa transceivers are responsible for the transfer of the data from the sensor to the gateway. This allows long distances but with a limited data rate. A data acquisition system reads the sensor and transmits the data via LoRa protocol at the 868 MHz frequency. A gateway receives the data and send them to the internet. If there is no direct link between the sensor and the gateway, one or more repeater will forward the data. The gateway between the LoRa and the internet will transfer the data to a web server. All data are available on this server for further analysis. Arduino Uno and Mega Boards and RTF95W LoRa modules are the basis hardware for the sensors, repeater and gateways. An important request to this sensor network was the modular set up of the complete system. Additional no commercial cloud provider is used. All components of this sensor network are self-designed and manufactured. 
Energy Management in Microgrid and Multi-microgrid
Authors: Xing Xueliang , Jia Limin
Published: March 2023

Considered as basic structures of next-generation energy system, environment-friendly and flexible microgrid (MG) systems are potential solutions to deal with stochastic renewable energy sources (RESs). The essence of management is to maximize the benefits of available resources through coordination and optimization, which also applies to energy systems. Adaptable energy management approaches provide the possibility to construct effective and various energy interaction. The purpose of this paper is to present a systematic review of energy management in MG systems, and further to propose an energy management model. Therefore, this paper first comprehensively reviews recent research studies on MG, particularly in the interconnected mode (called as multi-microgrid, MMG). Based on the analysis of relative literatures, a STEER (stability, touch, efficiency, evenness, and resilience) strategy is proposed and formulated from the perspective of energy utilization for energy management. Then, critical technologies in energy management are reviewed and summarized from the aspects of control, communication, optimization, prediction, and evaluation. Furthermore, energy management system is illustrated from the perspectives of system function, management framework and operation logic, based on a four-layer hierarchical architecture. Eight main prospects on the future trend of energy management in MG and MMG are also presented.
Beam-Reconfigurable Antenna with Inductive Partially Reflective Surface and Parasitic Elements
Authors: LIANG QIUYAN , Kiong Lau Buon , Zhou Gaonan
Published: March 2023

 A reconfigurable partially reflective surface (PRS) antenna can offer low-cost and low-complexity beam steering, traditionally implemented using a phased array with a bulky feeding network. This paper utilizes ray-tracing to prove analytically that an inductive nonuniform PRS facilitates larger beam deflection and lower sidelobe level (SLL) than a capacitive one, given the same reflection phase difference. With a suitable tradeoff in the beam deflection angle and gain variation between the reconfigurable states, an inductive reconfigurable PRS is designed for a ±13° steering range. To enhance the steering range with minimal complexity, two parasitic elements loaded with PIN diodes are added to the feeding source, resulting in the overall steering range of ±30°. The fabricated prototype verified that the pencil-shape beam can be steered towards 0º and ±30º with SLLs of less than -19dB at 5.5GHz. The antenna achieved peak realized gains of 9.5-10.4dBi for the three states with gain variation of less than 0.9dBi. The measured overlapped impedance band covers 5.41-5.63 GHz for all states. 
Tunable Bandpass FSS With Wideband Tuning and Low Insertion Loss Based on Waveguide Array
Authors: Zhong Shuomin , Lai Peining , Chen Yi , Liu Taijun , Huang Jifu
Published: March 2023

In this paper, we present a tunable bandpass frequency-selective surface (FSS) with wide tuning range. The FSS is composed of a metallic rectangular waveguide array implanted in the double-sided printed circuit board (DSPCB) and an array of embedded varactors with bias network in the backside of the DSPCB. The waveguide array has a frequency-selective transmission peak due to tunneling effect and the transmission frequency is tuned by changing the capacitance of varactors through different bias voltages. One advantage of this configuration is that the varactors together with the bias network are designed on the same layer, which can effectively reduce the overall thickness into only 0.006λc (λc is the free-space wavelength at the highest transmission frequency). On the other hand, the insertion loss associated with the parasitic resistance of varactors is greatly decreased, owing to the novel integrated design of biasing lines with varactors and the nearly-full-metal waveguide array. A prototype is fabricated and measured, showing that by changing the varactor capacitance from 0.12 pF to 1 pF, the passband exhibits a 2.32:1 frequency tuning range from 5.8 GHz to 2.5 GHz with an insertion loss of 0.2 dB-2.6 dB. A polarization-insensitive FSS is also studied in simulations.
Quantum-Resistant Highly Accurate Wind Speed Prediction Model
Authors: Phan Quoc Bao , Nguyen Tuy
Published: March 2023

This study aims to address the increasing complexity of cyber attacks and the sensitivity of wind speed data by exploring the combination of Artificial Intelligence (AI) and cyber security measures for improved wind speed prediction accuracy and security. The collected wind speed dataset is pre-processed and encrypted using the ring learning with errors (ring-LWE) encryption algorithm, which is known for its high level of security. The encrypted data is then input to the Ensemble Empirical Mode Decomposition (EEMD) to split the encrypted signal and reduce the impact of encryption noise. The combination of Convolutional Neural Networks and Long Short-Term Memory (CNN-LSTM) models are also applied to each intrinsic mode function (IMFs) of the decomposition result. Furthermore, the parallel programming framework is also employed during the training phase, significantly improving the processing speed and efficiency. The results of the predictions are decrypted and compared with the testing set, and other works to evaluate the proposed model. The Mean Absolute Percent Error (MAPE) ranges from 7% to 10%, indicating a high level of accuracy. The findings of the study have practical implications for wind energy production and the development of smart grid systems. The study highlights the importance of considering both accuracy and security when using AI and suggests future directions for research in this area, including the development of more advanced encryption algorithms and the integration of AI and cyber security into real-world wind energy systems.
Identification and Severity Assessment of COVID-19 Using Lung CT Scans
Authors: Thyagachandran Anand , Balachandran Aathira , Murthy Hema A
Published: March 2023

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, continues to have a significant impact on the global population. To effectively triage patients and understand the progression of the disease, a metric-based analysis of diagnostic techniques is necessary. The objective of the present study is to identify COVID-19 from chest CT scans and determine the extent of severity, defined by a severity score that indicates the volume of infection. An unsupervised preprocessing pipeline is proposed to extract relevant clinical features and utilize this information to employ a pretrained ImageNet EfficientNetB5 model to extract discriminative features. Subsequently, a shallow feed-forward neural network is trained to classify the CT scans into three classes, namely COVID-19, Community-Acquired Pneumonia, and Normal. Through various ablation studies, we find that a domain-specific preprocessing pipeline has a significant positive impact on classification accuracy. The infection segmentation mask generated from the preprocessed pipeline performs better than state-of-the-art supervised semantic segmentation models. Further, the estimated infection severity score is observed to be well correlated with radiologists' assessments. The results confirm the importance of domain-specific preprocessing for training machine learning algorithms.
RFID landslide monitoring : long-term outdoor signal processing and phase unwrapping
Authors: Charléty Arthur , Le Breton Mathieu , Baillet Laurent , Larose Eric
Published: March 2023

Localization of passive Radio-Frequency Identification (RFID) tags has been used to monitor landslide surface displacement since 5 years. This method, applied on slow displacements lower than 1cm per day, allows a high spatiotemporal resolution at a relatively low cost. With the feedback of the previous years, this paper proposes to summarize the various challenges encountered with the long-term outdoor RFID localization method, and presents data-processing solutions that were implemented to overcome these challenges. We propose a complex-smoothing unwrapping algorithm, a multi-frequency merging operation, as well as multi-tag and multi-antenna phase combining method. The concept of an unwrapping reference guide is presented and applied with groups of tags showing coherent displacements, or with absolute reference measurements. These approaches allow a higher data availability up to 38% for one site over multiple years, and a better phase unwrapping. Earth surface displacement monitoring with RFID proves to be a robust and accurate solution, with four equipped sites across France and Switzerland.
Transmission Investment Coordination using MILP Lagrange Dual Decomposition and Auxiliary Problem Principle
Authors: Chakrabarti Sambuddha , Khajeh Hosna , Nudell Thomas R , hesamzadeh Mohammad Reza , Baldick
Published: March 2023

This paper considers the investment coordination problem for the long term transmission capacity expansion in a situation where there are multiple regional Transmission Planners (TPs), each acting in order to maximize the utility in only its own region. In such a setting, any particular TP does not normally have any incentive to cooperate with the neighboring TP(s), although the optimal investment decision of each TP is contingent upon those of the neighboring TPs. A game-theoretic interaction among the TPs does not necessarily lead to this overall social optimum. We, therefore, introduce a social planner and call it the Transmission Planning Coordinator (TPC) whose goal is to attain the optimal possible social welfare for the bigger geographical region. In order to achieve this goal, this paper introduces a new incentive mechanism, based on distributed optimization theory. This incentive mechanism can be viewed as a set of rules of the transmission expansion investment coordination game, set by the social planner TPC, such that, even if the individual TPs act selfishly, it will still lead to the TPC's goal of attaining overall social optimum. Finally, the effectiveness of our approach is demonstrated through several simulation studies.
Optimizing representations of multiple simultaneous attributes for gait generation using deep learning
Authors: Sharma Abhishek , Rombokas Eric
Published: March 2023

Rich variations in gait are generated according to several attributes of the individual and environment, such as age, athleticism, terrain, speed, personal ”style”, mood, etc. The effects of these attributes can be hard to quantify explicitly, but relatively straightforward to sample. We seek to generate gait that expresses these attributes, creating synthetic gait samples that exemplify a custom mix of attributes. This is difficult to perform manually, and generally restricted to simple, human-interpretable and handcrafted rules. In this manuscript, we present neural network architectures to learn representations of hard to quantify attributes from data, and generate gait trajectories by composing multiple desirable attributes. We demonstrate this method for the two most commonly desired attribute classes: individual style and walking speed. We show that two methods, cost function design and latent space regularization, can be used individually or combined. We also show two uses of machine learning classifiers that recognize individuals and speeds. Firstly, they can be used as quantitative measures of success; if a synthetic gait fools a classifier, then it is considered to be a good example of that class. Secondly, we show that classifiers can be used in the latent space regularizations and cost functions to improve training beyond a typical squared-error cost. 
Laplacian salience-gated feature pyramid network for accurate liver vessel segmentation
Authors: Gao Zhan , Zong Qiuhao , Wang Yiqi , Yan Yan , Wang Yuqing , Zhu Ning , Zhang Jin , Wang Yunfu , Zhao Liang
Published: March 2023

Liver vessels generated from computed tomography are usually pretty small, which poses big challenges for satisfactory vessel segmentation, including 1) the scarcity of high-quality and large-volume vessel masks, 2) the difficulty in capturing vessel-specific features, and 3) the heavily imbalanced distribution of vessels and liver tissues. To advance, a sophisticated model and an elaborated dataset have been built. The model has a newly conceived Laplacian salience filter, highlighting vessel-like regions and suppressing other liver regions, to shape the vessel-specific feature learning and to balance vessels against others. It is further coupled with a pyramid deep learning architecture to capture various levels of features, hence the enhancement of feature formulation. Experiments show that this model markedly outperforms the state-of-the-art approaches, achieving a relative improvement of Dice score by at least 1.63% compared to the existing best model on available datasets. More promisingly, the averaged Dice score produced by existing models on the newly con- structed dataset is as high as 0.728 ± 0.067, which is at least 19.1% higher than that obtained from the existing best dataset under the same settings. These observations suggest that the proposed Laplacian salience, along with the elaborated dataset, can be helpful for liver vessel seg- mentation. 
Physiological and kinematic effects of a parallel rehabilitation robot (PWRR) on wrist movements
Authors: Zhang Leiyu , Yu Zhendong , Su Peng , Li Jianfeng , Ge Ruidong
Published: March 2023

The procedures were approved by the Ethics Committee at Beijing University of Technology.  
Modeling the Brain as Shannon Information Source Using fMRI Signals
Authors: Gunal Degirmendereli Gonul , Yarman Vural Fatoş T.
Published: March 2023

In this study, we suggest an information-theoretic brain model, assuming that the fMRI recordings of a subject, who performs a cognitive task, are the observable signals, generated by the anatomical regions, each of which can be represented as an information source. Based upon this assumption, we define two versions of Shannon entropy, namely, dynamic and static entropy to analyze the information content of anatomical regions during a cognitive state. We also propose two network models by estimating dynamic and static Kullback-Leibler (K-L) divergences to investigate the interactions across the anatomical regions. 
Channel and hardware impairment data augmentation for robust modulation classification
Authors: Perenda Erma , Bovet Gerome , Zheleva Mariya , Pollin Sofie
Published: March 2023

Deep learning has achieved remarkable results in modulation classification under two assumptions: a large amount of labeled class-balanced data is available, and test data shares the same distribution as data used for training. However, due to dynamic wireless fading channels and hardware imperfections, it is implausible that these assumptions hold in practice. This paper proposes Model-based Data Augmentation for Deep learning-based Modulation Classification (MDA-DMC) to build a high-quality dataset from a small amount of labeled seed data.

We develop two novel augmentation methods to combat channel and hardware impairments, along with two widely

used augmentation methods, adding Gaussian noise and rotation. We are the first to investigate the relationship

between augmentation methods and impairments due to channel and hardware imperfections. We show that MDA-

DMC can successfully combat the hardware imperfections for the same channel model as the channel model of

seed data. Furthermore, with a few AWGN seed data, MDA-DMC achieves an accuracy gain of up to 17.20% in fading channels. By adding a few fading seed data, MDA-DMC improves accuracy by an additional 10.78% in fading channels. 
Improper Gaussian Signaling for IRS Assisted Multiuser SWIPT Systems With Hardware Impairments
Authors: Fang Junjie , Zhang Chao , Wu QingQing , Li Ang
Published: March 2023

In this paper, we focus on intelligent reflecting surface (IRS) assisted multiuser simultaneous wireless information and power transfer (SWIPT)  systems with hardware impairments (HWIs), which result from the aggregate effect of in-phase and quadrature-phase imbalance (IQI), power amplifier non-linearity, quantization distortion, phase noise, etc. Improper Gaussian signaling (IGS) is employed to combat the signal distortion incurred by HWIs and the interference from other users. We aim to maximize the minimum achievable information rate among all users by jointly optimizing the active beamforming vectors, passive reflecting coefficients, and power splitting coefficients, subject to the minimum harvested energy requirements of these users and the total power budget at the transmitter. Due to the intricate coupling between the reflecting coefficients and beamforming vectors, we propose a two-level iterative optimization algorithm to solve this non-convex problem. Based on the above, we also study the weighted rate-energy region maximization problem. Numerical results show that the use of IGS significantly outperforms traditional proper Gaussian signaling (PGS) in the considered systems and also affirm the effectiveness of the proposed optimization algorithm.
A Comparison of PCA and HOG for Feature Extraction and Classification of Human Faces
Authors: Ipe Navin
Published: March 2023

This paper presents a simple analysis and comparison of the efficacy of feature extraction and generalization achieved using Histogram of Oriented Gradients (HOG) and Principal Component Analysis (PCA). A Naı̈ve Bayes classifier was trained with a dataset of pre-classified human male and female face images. The classifier was then presented with a fresh set of faces and was given the task of classifying the images as male or female. Also attempted, was an experiment of testing using the same images used for training. It was observed that PCA was more adaptive than HOG, in identifying new faces. HOG was more accurate in identifying the same faces, provided there were sufficient training samples. In all, PCA was found to be a better feature extractor, since it did not require many training examples. It only mattered that a sufficient number of principal components were used to obtain good classification accuracy.
A case report on pulmonary fibro-emphysema: an incorrectly framed case
Authors: Scaramozzino Marco Umberto , Sapone Giovanni , Sheenam  , Fulgido Attilio
Published: March 2023

This case report describes the combination of pulmonary fibrosis and emphysema (CPFE) as a possible new addition to the growing list of smoking-related lung diseases, which are characterised by the coexistence of usual interstitial pneumonia (UIP) or non-specific interstitial pneumonia (NSIP) with emphysema in tobacco smokers.
Intraosseous access: a simulation analysis
Authors: Antov Miki  , Rinaldi Bartolomeo , Bergesio Giorgio  , Vallana Vittoria  , Roasio Agostino
Published: March 2023

Introduction: The priority in critical patients is to find a vascular access. The most used access is the peripheral venous access, but when its placement goes wrong or is difficult, the literature recommends implementing intraosseous (IO) access as a valid alternative. The IO access is a rapid, reliable and a relatively safe method. Despite the recommendations, IO access is rarely used when indicated. The objective of this study was to evaluate the critical points of the IO procedure, positioning time, percentage of success at first attempt in simulation and, in according to obtained outcomes, checking of the procedure inclusion within university programs. 
Material and methods: A sample of 84 people was recruited; among them 44 were students attending the third year of the Degree Course in Nursing of the University of Turin (site of Asti) and 40 nurses from intensive care unit and emergency ward of Cardinal Massaia Hospital of Asti. A short lesson about IO access took place, followed by a practical demonstration. Subsequently, the IO access insertion performance and difficulty perceived were evaluated. Statistical analysis was performed by means of inferential and descriptive bivariate analysis. 
Results: The average value of the performance “IO access insertion” was 12.2±1.22 (average of the assigned points by the sample). The average difficulty perceived was 1.65±0.42, and mainly found in “selection of the correct point of insertion” with a value of 2.64±0.87, “needle placement” with a medium value of 2.35±1.02 and “medication” with a value of 2.0±0.94. Average execution time of IO access and needle placement were 73.3 and 36.1 seconds, respectively. Finally, the success rate at the first attempt was 72.6%. 
Discussion: The IO access execution time, for the complete procedure and for the needle placement only, was below the 3 minutes. Among nurses and students, data of the success of the procedure show significant results, but the difference between subgroups is still lower than expected considering 
the results of the statistical analysis about procedure success, execution time and error percentage. Most critical issues were found in the retrieval of area of insertion, whereas the most difficulty perceived was on reference point selection, correct needle placement and medication. The procedure may become subject of teaching in the University. 
Conclusion: The study evaluates the possibility of the IO access use, by underlining how is necessary a training about it. The principal reason of ‘non-use’ of this device is the disinformation of healthcare professionals. The results seem to underline the importance of a possible integration of IO access technique in the programs of Degree Nursing Course and post-base course. This may improve nursing in emergency situations and therefore, patient outcomes. When healthcare staff training is possible, periodical refresh is particularly recommended in order to maintain the acquired skills.
Earth observation method for an operational assessment of crop phenology metric “start of the season”
Authors: Bohovic Roman , Hlavinka Petr , Možný Martin , Semerádová Daniela , Bálek Jan , Trnka Miroslav
Published: March 2023

Vegetation phenology is one of the key indicators for assessing inter annual changes of ecosystems while crop phenology has crucial and practical importance for precise timing of farming practices of today’s smart agriculture. The aim of this study is to develop and implement a procedure for filtering and processing daily satellite signals from Moderate Resolution Imaging Spectroradiometer (MODIS) satellites for the operational derivation of vegetation indices and land surface phenology (LSP) metrics. Second, this work investigates and selects precisely adjusted parameters for the calculation of a specific LSP metric – the SOS (start of the season). The SOS obtained from the satellite data was compared with available in situ ground measurements at 80 sites with records from 2000-2012 across the Czech Republic. The coefficients of determination, R2, for the land surface phenology based on Earth observation and traditional ground phenology indicated differences between the two methods. However, the average R2 at all sites for agricultural land was 0.31 for winter wheat onset of leaf sheath elongation; the R2 exceeded 0.5 at 21 sites and was approximately 0.7 at some sites. The developed procedure proved suitable for operational monitoring of actual crop conditions and other influence factors that are important for drought monitoring.
Paolo Grossi e un'eredità che non passa
Authors: Comitato editoriale
Published: March 2023

Un pensiero per Paolo Grossi