Search results for: physiological signals

Authors: Vanessa Bennemann, Gabriela Laste, Márcia Inês Goettert

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The gestational period is a phase in which the pregnant woman undergoes constant physiological and hormonal changes, which are part of the woman’s biological cycle, the development of the fetus, childbirth, and lactation. These are factors of response to the immunological adaptation of the human reproductive process that is directly related to the pregnancy’s well-being and development. Although most pregnancies occur without complications, about 15% of pregnant women will develop potentially fatal complications, implying maternal and fetal risk. Therefore, requiring specialized care for high-risk pregnant women (HRPW) with obstetric interventions for the survival of the mother and/or fetus. Among the risk factors that characterize HRPW are the women's age, gestational diabetes mellitus (GDM), autoimmune diseases, infectious diseases such as syphilis and HIV, hypertension (SAH), preeclampsia, eclampsia, HELLP syndrome, uterine contraction abnormalities, and premature placental detachment (PPD), thyroid disorders, among others. Thus, pregnancy has an impact on the thyroid gland causing changes in the functioning of the mother's thyroid gland, altering the thyroid hormone (TH) profiles and production as pregnancy progresses. Considering, throughout the gestational period, the interpretation of the results of the tests to evaluate the thyroid functioning depends on the stage in which the pregnancy is. Thyroid disorders are directly related to adverse obstetric outcomes and in child development. Therefore, the adequate release of TH is important for a pregnancy without complications and optimal fetal growth and development. Objective: Investigate the physiological effects caused by thyroid disorders in the gestational period. Methods: A search for articles indexed in PubMed, Scielo, and MDPI databases, was performed using the term “AND”, with the descriptors: Pregnancy, Thyroid. With several combinations that included: Melatonin, Thyroidopathy, Inflammatory processes, Cytokines, Anti-inflammatory, Antioxidant, High-risk pregnancy. Subsequently, the screening was performed through the analysis of titles and/or abstracts. The criteria were: including clinical studies in general, randomized or not, in the period of 10 years prior to the research, in the English literature; excluded: experimental studies, case reports, research in the development phase. Results: In the preliminary results, a total of studies (n=183) were found, (n=57) excluded, such as studies of cancer, diabetes, obesity, and skin diseases. Conclusion: To date, it has been identified that thyroid diseases can impair the fetus’s brain development. Further research is suggested on this matter to identify new substances that may have a potential therapeutic effect to aid the gestational period with thyroid diseases.

Keywords: pregnancy, thyroid, melatonin, high-risk pregnancy

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Authors: Navdeep Goel, Salvador Gabarda

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Digital images are widely used in computer applications. To store or transmit the uncompressed images requires considerable storage capacity and transmission bandwidth. Image compression is a means to perform transmission or storage of visual data in the most economical way. This paper explains about how images can be encoded to be transmitted in a multiplexing time-frequency domain channel. Multiplexing involves packing signals together whose representations are compact in the working domain. In order to optimize transmission resources each 4x4 pixel block of the image is transformed by a suitable polynomial approximation, into a minimal number of coefficients. Less than 4*4 coefficients in one block spares a significant amount of transmitted information, but some information is lost. Different approximations for image transformation have been evaluated as polynomial representation (Vandermonde matrix), least squares + gradient descent, 1-D Chebyshev polynomials, 2-D Chebyshev polynomials or singular value decomposition (SVD). Results have been compared in terms of nominal compression rate (NCR), compression ratio (CR) and peak signal-to-noise ratio (PSNR) in order to minimize the error function defined as the difference between the original pixel gray levels and the approximated polynomial output. Polynomial coefficients have been later encoded and handled for generating chirps in a target rate of about two chirps per 4*4 pixel block and then submitted to a transmission multiplexing operation in the time-frequency domain.

Keywords: chirp signals, image multiplexing, image transformation, linear canonical transform, polynomial approximation

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Authors: Ami Fadhillah Amir Abdul Nasir, Amanda C. Niehaus, Skye F. Cameron, Frank A. Von Hippel, John Postlethwait​, Robbie S. Wilson

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For suicidal breeders, the physiological stresses and energetic costs of breeding are fatal. Environmental stressors such as pollution should compound these costs, yet suicidal breeding is so rare among mammals that this is unknown. Here, we explored the consequences of metal contamination to the health, aging and performance of endangered, suicidally-breeding northern quolls (Dasyurus hallucatus) living near an active manganese mine on Groote Eylandt, Northern Territory, Australia. We found respirable manganese dust at levels exceeding international recommendations even 20km from mining sites and substantial accumulation of manganese within quolls’ hair, testes, and in two brain regions—the neocortex and cerebellum, responsible for sensory perception and motor function, respectively. Though quolls did not differ in sprint speeds, motor skill, or manoeuvrability, those with higher accumulation of manganese crashed at lower speeds during manoeuvrability tests, indicating a potential effect on sight or cognition. Immune function and telomere length declined over the breeding season, as expected with ageing, but manganese contamination exacerbated immune declines and suppressed cortisol. Unexpectedly, male quolls with higher levels of manganese had longer telomeres, supporting evidence of unusual telomere dynamics among Dasyurids—though whether this affects their lifespan is unknown. We posit that sublethal contamination via pollution, mining, or urbanisation imposes physiological costs on wildlife that may diminish reproductive success or survival.

Keywords: ecotoxicology, heavy metal, manganese, telomere length, cortisol, locomotor

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Authors: Ionel Zagan, Vasile Gheorghita Gaitan, Adrian Brezulianu

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This paper presents the contributions in designing a mobile system named Tele-ECG implemented for remote monitoring of cardiac patients. For a better flexibility of this application, the authors chose to implement a local memory and multiple communication interfaces. The project described in this presentation is based on the ARM Cortex M0+ microcontroller and the ADAS1000 dedicated chip necessary for the collection and transmission of Electrocardiogram signals (ECG) from the patient to the microcontroller, without altering the performances and the stability of the system. The novelty brought by this paper is the implementation of a remote monitoring system for cardiac patients, having a real-time behavior and multiple interfaces. The microcontroller is responsible for processing digital signals corresponding to ECG and also for the implementation of communication interface with the main server, using GSM/Bluetooth SIMCOM SIM800C module. This paper translates all the characteristics of the Tele-ECG project representing a feasible implementation in the biomedical field. Acknowledgment: This paper was supported by the project 'Development and integration of a mobile tele-electrocardiograph in the GreenCARDIO© system for patients monitoring and diagnosis - m-GreenCARDIO', Contract no. BG58/30.09.2016, PNCDI III, Bridge Grant 2016, using the infrastructure from the project 'Integrated Center for research, development and innovation in Advanced Materials, Nanotechnologies, and Distributed Systems for fabrication and control', Contract No. 671/09.04.2015, Sectoral Operational Program for Increase of the Economic Competitiveness co-funded from the European Regional Development Fund.

Keywords: Tele-ECG, real-time cardiac monitoring, electrocardiogram, microcontroller

Procedia PDF Downloads 248

Authors: Jasbinder Singh, Harjit Pal Singh, S. A. Khan

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The work, in this paper, presents the comparison of encoded speech signals by different VoIP narrow-band and wide-band codecs for different modulation schemes. The simulation results indicate that codec has an impact on the speech quality and also effected by modulation schemes.

Keywords: VoIP, coders, modulations, BER, MOS

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Authors: Andreas Aceranti, Riccardo Dossena, Marco Colorato, Simonetta Vernocchi

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By the term “limbic resonance,” we usually refer to a state of deep connection, both emotional and physiological, between people who, when in resonance, find their limbic systems in tune with one another. Limbic resonance is not only about sharing emotions but also physiological states. In fact, people in such resonance can influence each other’s heart rate, blood pressure, and breathing. Limbic resonance is fundamental for human beings to connect and create deep bonds among a certain group. It is fundamental for our social skills. A relationship between gifted and resonant subjects is perceived as feeling safe, living the relation like an isle of serenity where it is possible to recharge, to communicate without words, to understand each others without giving explanations, to strengthen the balance of each member of the group. Within the circle, self-esteem is consolidated and makes it stronger to face what is outside, others, and reality. The idea that gifted people who are together may be unfit for the world does not correspond to the truth. The circle made up of people with high cognitive potential characterized by a limbic resonance is, in general, experienced as a solid platform from which you can safely move away and where you can return to recover strength. We studied 8 adults (between 21 and 47 years old). All of them with IQ higher than 130. We monitored their brain waves frequency (alpha, beta, theta, gamma, delta) by means of biosensing tracker along with their physiological states (heart beat frequency, blood pressure, breathing frequency, pO2, pCO2) and some blood works only (5-HT, dopamine, catecholamines, cortisol). The subjects of the study were asked to adhere to a protocol involving bonding activities (such as team building activities), role plays, meditation sessions, and group therapy. All these activities were carried out together. We observed that after about 4 months of activities, their brain waves frequencies tended to tune quicker and quicker. After 9 months, the bond among them was so important that they could “sense” each other inner states and sometimes also guess each others’ thoughts. According to our findings, it may be hypothesized that large synchronized outbursts of cortex neurons produces not only brain waves but also electromagnetic fields that may be able to influence the cortical neurons’ activity of other people’s brain by inducing action potentials in large groups of neurons and this is reasonably conceivable to be able to transmit information such as different emotions and cognition cues to the other’s brain. We also believe that upcoming research should focus on clarifying the role of brain magnetic particles in brain-to-brain communication. We also believe that further investigations should be carried out on the presence and role of cryptochromes to evaluate their potential roles in direct brain-to-brain communication.

Keywords: limbic resonance, psychotherapy, brain waves, emotion regulation, giftedness

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Authors: Guanhua Zhou, Zhongqi Ma

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Submerged aquatic vegetation (SAV) in wetlands can absorb nitrogen and phosphorus effectively to prevent the eutrophication of water. It is feasible to monitor the distribution of SAV through remote sensing, but for the reason of weak vegetation signals affected by water body, traditional terrestrial vegetation indices are not applicable. This paper aims at constructing SAV index to enhance the vegetation signals and distinguish SAV from water body. The methodology is as follows: (1) select the bands sensitive to the vegetation parameters based on global sensitivity analysis of SAV canopy radiative transfer model; (2) take the soil line concept as reference, analyze the distribution of SAV and water reflectance simulated by SAV canopy model and semi-analytical water model in the two-dimensional space built by different sensitive bands; (3)select the band combinations which have better separation performance between SAV and water, and use them to build the SAVI indices in the form of normalized difference vegetation index(NDVI); (4)analyze the sensitivity of indices to the water and vegetation parameters, choose the one more sensitive to vegetation parameters. It is proved that index formed of the bands with central wavelengths in 705nm and 842nm has high sensitivity to chlorophyll content in leaves while it is less affected by water constituents. The model simulation shows a general negative, little correlation of SAV index with increasing water depth. Moreover, the index enhances capabilities in separating SAV from water compared to NDVI. The SAV index is expected to have potential in parameter inversion of wetland remote sensing.

Keywords: global sensitivity analysis, radiative transfer model, submerged aquatic vegetation, vegetation indices

Procedia PDF Downloads 236

Authors: Salman Ahmad, Muhammad Aown Sammar Raza, Muhammad Farrukh Saleem, Rashid Iqbal, Muhammad Saqlain Zaheer, Muhammad Usman Aslam, Imran Haider, Muhammad Adnan Nazar, Muhammad Ali

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Among the various abiotic stresses, drought stress is one of the most challenging for field crops. Wheat is one of the major staple food of the world, which is highly affected by water deficit stress in the current scenario of climate change. In order to ensure food security by depleting water resources, there is an urgent need to adopt technologies which result in sufficient crop yield with less water consumption. Mulching and partial rootzone drying (PRD) are two important management techniques used for water conservation and to mitigate the negative impacts of drought. The experiment was conducted to screen out the best-suited mulch for wheat under PRD system. Two water application techniques (I1= full irrigation I2= PRD irrigation) and four mulch treatments (M0= un-mulched, M1= black plastic mulch, M2= wheat straw mulch and M4= cotton sticks mulch) were conducted in completely randomized design with four replications. The treatment, black plastic mulch was performed the best than other mulch treatments. For irrigation levels, higher values of growth, physiological and water-related parameters were recorded in control treatment while, quality traits and enzymatic activities were higher under partial root zone drying. The current study concluded that adverse effects of drought on wheat can be significantly mitigated by using mulches but black plastic mulch was best suited for partial rootzone drying irrigation system in wheat.

Keywords: antioxidants, leaf water relations, Mulches, osmolytes, partial root zone drying, photosynthesis

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Authors: Yasir Arafat, Asma Shah, Hua Shao

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Background and Aims: Legume/cereal intercropping is used worldwide for enhancement in biomass and yield of cereal crops. However, because of intercropping, the belowground biological and chemical interactions and their effect on physiological parameters and yield of crops are limited. Methods: Wheat faba bean (WF) intercropping was designed to understand the underlying changes in the soil's chemical environment, soil microbial communities, and effect on growth and yield parameters. Experimental plots were established as having no root partition (NRP), semi-root partition (SRP), complete root partition (CRP), and their sole cropping (CK). Low molecular weight organic acids (LMWOAs) were determined by GC-MS, and high throughput sequencing of the 16S rRNA gene was carried out to screen microbial structure and composition in different root partitions of the WF intercropping system. Results: We show that intercropping induced a shift in the relative abundance of some genera of plant growth promoting rhizobacteria (PGPR) such as Allorhizobium, Neorhizobium, Pararhizobium, and Rhizobium species and resulted in better growth and yield performance of wheat. Moreover, as the plant's distance of wheat from faba beans decreased, the diversity of microbes increased, and a positive effect was observed on physiological traits and crop yield. Furthermore, an abundance and positive correlations of palmitic acid, arachidic acid, stearic acid, and 9-Octadecenoic with PGPR were recorded in the root zone of WF intercropping, which can play an important role in this facilitative mechanism of enhancing growth and yield of cereals. Conclusion: The two treatments clearly affected soil microbial and chemical composition, which can be reflected in growth and yield enhancement.

Keywords: intercropping, microbial community, LMWOAs, PGPR, soil chemical environment

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Authors: Cristian Pauna

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Trading the financial markets is a widespread activity today. A large number of investors, companies, public of private funds are buying and selling every day in order to make profit. Algorithmic trading is the prevalent method to make the trade decisions after the electronic trading release. The orders are sent almost instantly by computers using mathematical models. This paper will present a price prediction methodology based on a multi-dimensional neural network. Using the Fisher transform, the neural network will be instructed for a low-latency auto-adaptive process in order to predict the price evolution for the next period of time. The model is designed especially for algorithmic trading and uses the real-time price series. It was found that the characteristics of the Fisher function applied at the nodes scale level can generate reliable trading signals using the neural network methodology. After real time tests it was found that this method can be applied in any timeframe to trade the financial markets. The paper will also include the steps to implement the presented methodology into an automated trading system. Real trading results will be displayed and analyzed in order to qualify the model. As conclusion, the compared results will reveal that the neural network methodology applied together with the Fisher transform at the nodes level can generate a good price prediction and can build reliable trading signals for algorithmic trading.

Keywords: algorithmic trading, automated trading systems, financial markets, high-frequency trading, neural network

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Authors: Mohammad Arabi

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The development of advanced technologies in the field of signal processing and vibration analysis has enabled more accurate analysis and fault detection in electrical systems. This research investigates the application of temporal and frequency features in detecting faults in electric motor bearings, aiming to enhance fault detection accuracy and prevent unexpected failures. The use of methods such as deep learning algorithms and neural networks in this process can yield better results. The main objective of this research is to evaluate the efficiency and accuracy of methods based on temporal and frequency features in identifying faults in electric motor bearings to prevent sudden breakdowns and operational issues. Additionally, the feasibility of using techniques such as machine learning and optimization algorithms to improve the fault detection process is also considered. This research employed an experimental method and random sampling. Vibration signals were collected from electric motors under normal and faulty conditions. After standardizing the data, temporal and frequency features were extracted. These features were then analyzed using statistical methods such as analysis of variance (ANOVA) and t-tests, as well as machine learning algorithms like artificial neural networks and support vector machines (SVM). The results showed that using temporal and frequency features significantly improves the accuracy of fault detection in electric motor bearings. ANOVA indicated significant differences between normal and faulty signals. Additionally, t-tests confirmed statistically significant differences between the features extracted from normal and faulty signals. Machine learning algorithms such as neural networks and SVM also significantly increased detection accuracy, demonstrating high effectiveness in timely and accurate fault detection. This study demonstrates that using temporal and frequency features combined with machine learning algorithms can serve as an effective tool for detecting faults in electric motor bearings. This approach not only enhances fault detection accuracy but also simplifies and streamlines the detection process. However, challenges such as data standardization and the cost of implementing advanced monitoring systems must also be considered. Utilizing temporal and frequency features in fault detection of electric motor bearings, along with advanced machine learning methods, offers an effective solution for preventing failures and ensuring the operational health of electric motors. Given the promising results of this research, it is recommended that this technology be more widely adopted in industrial maintenance processes.

Keywords: electric motor, fault detection, frequency features, temporal features

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Authors: Sadegh Lotfieblisofla, Arash Khodabakhshi

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Tissue plasminogen activator (tPA) as a serine protease plays an important role in the fibrinolytic system and the dissolution of fibrin clots in human body. The production of this drug in plants such as tobacco could reduce its production costs. In this study, expression of tPA gene and protein targeting to different plant cell compartments, using various signal peptides has been investigated. For high level of expression, Kozak sequence was used after CaMV35S in the beginning of the gene. In order to design the final construction, Extensin, KDEL (amino acid sequence including Lys-Asp-Glu-Leu) and SP (γ-zein signal peptide coding sequence) were used as leader signals to conduct this protein into apoplast, endoplasmic reticulum and cytosol spaces, respectively. Cloned human tPA gene under the CaMV (Cauliflower mosaic virus) 35S promoter and NOS (Nopaline Synthase) terminator into pBI121 plasmid was transferred into tobacco explants by Agrobacterium tumefaciens strain LBA₄₄₀₄. The presence and copy number of genes in transgenic tobacco was proved by Southern blotting. Enzymatic activity of the rt-PA protein in transgenic plants compared to non-transgenic plants was confirmed by Zymography assay. The presence and amount of rt-PA recombinant protein in plants was estimated by ELISA analysis on crude protein extract of transgenic tobacco using a specific antibody. The yield of recombinant tPA in transgenic tobacco for SP, KDEL, Extensin signals were counted 0.50, 0.68, 0.69 microgram per milligram of total soluble proteins.

Keywords: tPA, recombinant, transgenic, tobacco

Procedia PDF Downloads 121

Authors: M. D. Haneef, R. B. Randall, Z. Peng

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Journal bearings used in IC engines are prone to premature failures and are likely to fail earlier than the rated life due to highly impulsive and unstable operating conditions and frequent starts/stops. Vibration signature extraction and wear debris analysis techniques are prevalent in the industry for condition monitoring of rotary machinery. However, both techniques involve a great deal of technical expertise, time and cost. Limited literature is available on the application of these techniques for fault detection in reciprocating machinery, due to the complex nature of impact forces that confounds the extraction of fault signals for vibration based analysis and wear prediction. This work is an extension of a previous study, in which an engine simulation model was developed using a MATLAB/SIMULINK program, whereby the engine parameters used in the simulation were obtained experimentally from a Toyota 3SFE 2.0 litre petrol engines. Simulated hydrodynamic bearing forces were used to estimate vibrations signals and envelope analysis was carried out to analyze the effect of speed, load and clearance on the vibration response. Three different loads 50/80/110 N-m, three different speeds 1500/2000/3000 rpm, and three different clearances, i.e., normal, 2 times and 4 times the normal clearance were simulated to examine the effect of wear on bearing forces. The magnitude of the squared envelope of the generated vibration signals though not affected by load, but was observed to rise significantly with increasing speed and clearance indicating the likelihood of augmented wear. In the present study, the simulation model was extended further to investigate the bearing wear behavior, resulting as a consequence of different operating conditions, to complement the vibration analysis. In the current simulation, the dynamics of the engine was established first, based on which the hydrodynamic journal bearing forces were evaluated by numerical solution of the Reynold’s equation. Also, the essential outputs of interest in this study, critical to determine wear rates are the tangential velocity and oil film thickness between the journal and bearing sleeve, which if not maintained appropriately, have a detrimental effect on the bearing performance. Archard’s wear prediction model was used in the simulation to calculate the wear rate of bearings with specific location information as all determinative parameters were obtained with reference to crank rotation. Oil film thickness obtained from the model was used as a criterion to determine if the lubrication is sufficient to prevent contact between the journal and bearing thus causing accelerated wear. A limiting value of 1 µm was used as the minimum oil film thickness needed to prevent contact. The increased wear rate with growing severity of operating conditions is analogous and comparable to the rise in amplitude of the squared envelope of the referenced vibration signals. Thus on one hand, the developed model demonstrated its capability to explain wear behavior and on the other hand it also helps to establish a correlation between wear based and vibration based analysis. Therefore, the model provides a cost-effective and quick approach to predict the impending wear in IC engine bearings under various operating conditions.

Keywords: condition monitoring, IC engine, journal bearings, vibration analysis, wear prediction

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Authors: Ning Li, Jiacheng Zhang, Zheng Yang, Sylvia Kang

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Introduction: Polycystic ovary syndrome (PCOS) is a common physiological symptom in women of reproductive age. Women with PCOS may have infrequent or prolonged menstrual periods and excess male hormone (androgen) levels. Mira analyzes the cycle profiles and the luteinizing hormone (LH) changes in urine, closely related to the fertility level of healthy women and PCOS women. From the difference between the two groups, Mira helps to understand the physiological state of PCOS women and their hormonal changes in the menstrual cycle. Methods: In this study, data from 1496 cycles and information from 342 women belonging to two groups (181 PCOS and 161 Healthy) were collected and analyzed. Women test their luteinizing hormone (LH) in urine daily with Mira fertility test wand and Mira analyzer, from the day after the menstruation to the starting day of the next menstruation. All the collected data meets Mira’s user agreement and users’ identification was removed. The cycle length, LH peak, and other cycle information of the PCOS group were compared with the Healthy group. Results: The average cycle length of PCOS women is 41 days and of the Healthy women is 33 days. 91.4% of cycle length is within 40 days for the Healthy group, while it decreases to 71.9% for the PCOS group. This means PCOS women have a longer menstrual cycle and more variation during the cycle. With more variation, the ovulation prediction becomes more difficult for the PCOS group. The deviation between the LH surge day and the predicted ovulation day, calculated by the starting day of the next menstruation minus 14 days, is greater in the PCOS group compared with the Healthy group. Also, 46.96% of PCOS women have an irregular cycle, and only 19.25% of healthy women show an irregular cycle. Conclusion: PCOS women have longer menstrual cycles and more variation during the menstrual cycles. The traditional ovulation prediction is not suitable for PCOS women.

Keywords: menstrual cycle, PCOS, urinary luteinizing hormone, Mira

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Authors: Vidhya Venugopal, Rekha S.

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Introduction: Climate change and the growing frequency of higher average temperatures and heat waves have detrimental health effects, especially for certain vulnerable groups with limited socioeconomic status (SES) or physiological capacity to adapt to or endure high temperatures. Little research has been conducted on the effects of heat stress on pregnant women and fetuses in tropical regions such as India. Very high ambient temperatures may worsen Adverse Pregnancy Outcomes (APOs) and are a major worry in the scenario of climate change. The relationship between rising temperatures and APO must be better understood in order to design more effective interventions. Methodology: We conducted an observational cohort study involving 865 pregnant women in various districts of Tamil Nadu districts between 2014 and 2021. Physiological Heat Strain Indicators (HSI) such as morning and evening Core Body Temperature (CBT) and Urine Specific Gravity (USG) were monitored using an infrared thermometer and refractometer, respectively. A validated, modified version of the HOTHAPS questionnaire was utilised to collect self-reported health symptoms. A follow-up was undertaken with the mothers to collect information regarding birth outcomes and APOs, such as spontaneous abortions, stillbirths, Preterm Birth (PTB), birth abnormalities, and Low Birth Weight (LBW). Major findings of the study: According to the findings of our study, ambient temperatures (mean WBGT°C) were substantially higher (>28°C) for approximately 46% of women performing moderate daily life activities. 82% versus 43% of these women experienced dehydration and heat-related complaints. 34% of women had USG >1.020, which is symptomatic of dehydration. APOs, which include spontaneous abortions, were prevalent at 2.2%, stillbirth/preterm birth/birth abnormalities were prevalent at 2.2%, and low birth weight was prevalent at 16.3%. With exposures to WBGT>28°C, the incidence of miscarriage or unexpected abortion rose by approximately 2.7 times (95% CI: 1.1-6.9). In addition, higher WBGT exposures were associated with a 1.4-fold increased risk of unfavorable birth outcomes (95% Confidence Interval [CI]: 1.02-1.09). The risk of spontaneous abortions was 2.8 times higher among women who conceived during the hotter months (February – September) compared to those women who conceived in the cooler months (October – January) (95% CI: 1.04-7.4). Positive relationships between ambient heat and APOs found in this study necessitate further exploration into the underlying factors for extensive cohort studies to generate information to enable the formulation of policies that can effectively protect these women against excessive heat stress for enhanced maternal and fetal health.

Keywords: heat exposures, community, pregnant women, physiological strain, adverse outcome, interventions

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Authors: O.F. Akinmoladun, F.N. Fon, C.T. Mpendulo, O. Okoh

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The sustainability of livestock production is under threat as a result of water scarcity, fluctuating precipitation, and high environmental temperature. These combined stressors have impacted negatively on general animal production and welfare, necessitating a very reliable and cost-effective management practices, especially in arid and water-limited regions of the world. Instead of the above, this study was designed to investigate the growth performance and physiological response of water-restricted Xhosa ear-lobe goats fed diets supplemented with single or multiple vitamin C (VC) during summer. The total forty-eight goats used for the experiment were balanced for body weight and randomly assigned to the seven treatment groups (seven goats/treatment): GI (W100%); GII (W70%); GIII (W50%); GIV (W70%+3g/day VC); GV ((W50% +3g/day VC); GVI (W70%+3g/d VC+extra 5g on every eight-day); GVII (W50%+3g/d VC+extra 5g on every eight-day). The design was a complete randomized design and VC was administered per os. At the end of the 75-day feeding trial, GIII (W50%) animals were the most affected (P<0.05) and the effect was more pronounced in their body condition scores (BCs). Weight loss and depression in feed intake due to water restriction (P<0.05) were attenuated by VC treated groups (GIV-GVII). Changes in body thermal gradient (BTG) and rectal temperature (RcT) were similar (P>0.05) across the various experimental groups. The attenuation effect of VC was significant in responses to respiratory rate (RR) and cortisol. Supplementation of VC (either single or multiple) did not significantly (P>0.05) improve water restriction effect on body condition scores (BCs) and FAMACHA©. The current study found out that Xhosa ear lobe goats can adapt to the prevailing bioclimatic changes and limited water intake. However, supplementation of vitamin C can be beneficial at modulating these stressful stimuli. Continuous consistencies in the outcome of vitamin C on water-stressed animals can help validate recommendations especially to farmers in the arid and water-limited regions across the globe.

Keywords: vitamin C, Xhosa ear-lobe, thermotolerance, water stress

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Authors: Caren Hilger, Silke Burkert, Friederike Kendel

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Men with localized prostate cancer (PCa) have to choose among different treatment options, such as active surveillance (AS) and radical prostatectomy (RP). All available treatment options may be accompanied by specific psychological or physiological side effects. Depending on the nature and extent of these side effects, patients are more or less likely to be satisfied or to struggle with their treatment decision in the long term. Therefore, the aim of this study was to assess and explain decisional regret in men with localized PCa. The role of erectile functioning as one of the main physiological side effects of invasive PCa treatment, depressive symptoms as a common psychological side effect, and the association of erectile functioning and depressive symptoms with decisional regret were investigated. Men with localized PCa initially managed with AS or RP (N=292) were matched according to length of therapy (mean 47.9±15.4 months). Subjects completed mailed questionnaires assessing decisional regret, changes in erectile functioning, depressive symptoms, and sociodemographic variables. Clinical data were obtained from case report forms. Differences among the two treatment groups (AS and RP) were calculated using t-tests and χ²-tests, relationships of decisional regret with erectile functioning and depressive symptoms were computed using multiple regression. Men were on average 70±7.2 years old. The two treatment groups differed markedly regarding decisional regret (p<.001, d=.50), changes in erectile functioning (p<.001, d=1.2), and depressive symptoms (p=.01, d=.30), with men after RP reporting higher values, respectively. Regression analyses showed that after adjustment for age, tumor risk category, and changes in erectile functioning, depressive symptoms were still significantly associated with decisional regret (B=0.52, p<.001). Additionally, when predicting decisional regret, the interaction of changes in erectile functioning and depressive symptoms reached significance for men after RP (B=0.52, p<.001), but not for men under AS (B=-0.16, p=.14). With increased changes in erectile functioning, the association of depressive symptoms with decisional regret became stronger in men after RP. Decisional regret is a phenomenon more prominent in men after RP than in men under AS. Erectile functioning and depressive symptoms interact in their prediction of decisional regret. Screening and treating depressive symptoms might constitute a starting point for interventions aiming to reduce decisional regret in this target group.

Keywords: active surveillance, decisional regret, depressive symptoms, erectile functioning, prostate cancer, radical prostatectomy

Procedia PDF Downloads 197

Authors: S. M. Ishtiaque, V. K. Yadav, S. D. Joshi, J. K. Chatterjee

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The DIAMETRIC FAULTS system has been developed that captures a bi-directional image of yarn continuously in sequentially manner and provides the detailed classification of faults. A novel mathematical framework developed on the acquired bi-directional images forms the basis of fault classification in four broad categories, namely, Thick1, Thick2, Thin and Normal Yarn. A discretised version of Radon transformation has been used to convert the bi-directional images into one-dimensional signals. Images were divided into training and test sample sets. Karhunen–Loève Transformation (KLT) basis is computed for the signals from the images in training set for each fault class taking top six highest energy eigen vectors. The fault class of the test image is identified by taking the Euclidean distance of its signal from its projection on the KLT basis for each sample realization and fault class in the training set. Euclidean distance applied using various techniques is used for classifying an unknown fault class. An accuracy of about 90% is achieved in detecting the correct fault class using the various techniques. The four broad fault classes were further sub classified in four sub groups based on the user set boundary limits for fault length and fault volume. The fault cross-sectional area and the fault length defines the total volume of fault. A distinct distribution of faults is found in terms of their volume and physical dimensions which can be used for monitoring the yarn faults. It has been shown from the configurational based characterization and classification that the spun yarn faults arising out of mass variation, exhibit distinct characteristics in terms of their contours, sizes and shapes apart from their frequency of occurrences.

Keywords: Euclidean distance, fault classification, KLT, Radon Transform

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Authors: Anup Anand Deshmukh, Catherine Soladie, Renaud Seguier

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Emotion plays a key role in many applications like healthcare, to gather patients’ emotional behavior. Unlike typical ASR (Automated Speech Recognition) problems which focus on 'what was said', it is equally important to understand 'how it was said.' There are certain emotions which are given more importance due to their effectiveness in understanding human feelings. In this paper, we propose an approach that models human stress from audio signals. The research challenge in speech emotion detection is finding the appropriate set of acoustic features corresponding to an emotion. Another difficulty lies in defining the very meaning of emotion and being able to categorize it in a precise manner. Supervised Machine Learning models, including state of the art Deep Learning classification methods, rely on the availability of clean and labelled data. One of the problems in affective computation is the limited amount of annotated data. The existing labelled emotions datasets are highly subjective to the perception of the annotator. We address the first issue of feature selection by exploiting the use of traditional MFCC (Mel-Frequency Cepstral Coefficients) features in Convolutional Neural Network. Our proposed Emo-CNN (Emotion-CNN) architecture treats speech representations in a manner similar to how CNN’s treat images in a vision problem. Our experiments show that Emo-CNN consistently and significantly outperforms the popular existing methods over multiple datasets. It achieves 90.2% categorical accuracy on the Emo-DB dataset. We claim that Emo-CNN is robust to speaker variations and environmental distortions. The proposed approach achieves 85.5% speaker-dependant categorical accuracy for SAVEE (Surrey Audio-Visual Expressed Emotion) dataset, beating the existing CNN based approach by 10.2%. To tackle the second problem of subjectivity in stress labels, we use Lovheim’s cube, which is a 3-dimensional projection of emotions. Monoamine neurotransmitters are a type of chemical messengers in the brain that transmits signals on perceiving emotions. The cube aims at explaining the relationship between these neurotransmitters and the positions of emotions in 3D space. The learnt emotion representations from the Emo-CNN are mapped to the cube using three component PCA (Principal Component Analysis) which is then used to model human stress. This proposed approach not only circumvents the need for labelled stress data but also complies with the psychological theory of emotions given by Lovheim’s cube. We believe that this work is the first step towards creating a connection between Artificial Intelligence and the chemistry of human emotions.

Keywords: deep learning, brain chemistry, emotion perception, Lovheim's cube

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Authors: Mariam G. Eshak, Ahmed Abbas, M. I. El-Sabry, M. M. Mashaly

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This investigation was conducted to determine the physiological response and evaluate the expression of inflammatory and cell death genes and DNA damage induced by endotoxic shock in laying hens. Endotoxic shock was induced by a single intravenous injection of 107 Escherichia coli (E. coli,) colony/hen. In the present study, 240 forty-week-old laying hens (H&N) were randomly assigned into 2 groups with 3 replicates of 40 birds each. Hens were reared in battery cages with wire floors in an open-sided housing system under natural conditions. Housing and general management practices were similar for all groups. At 42-wk of age, 45 hens from the first group (15 replicate) were infected with E. coli, while the same number of hens from the second group was injected with saline and served as a control. Heat shock protein-70 (HSP-70) expression, plasma corticosterone concentration, body temperature, and the gene expression of bax, caspase-3 activity, P38, Interlukin-1β (Il-1β), and tumor necrosis factor alpha (TNF-α) genes and DNA damage in the brain and liver were measured. Hens treated with E. coli showed significant (P≤0.05) increase of body temperature by 1.2 ᴼC and plasma corticosterone by 3 folds compared to the controls. Further, hens injected with E.Coli showed markedly over-expression of HSP-70 and increase DNA damage in brain and liver. These results were synchronized with activating cell death program since our data showed significant (P≤0.05) high expression of bax and caspase-3 activity genes in the brain and liver. These results were related to remarkable over-inflammation gene expression of P38, IL-1β, and TNF-α in brain and liver. In conclusion, our results indicate that endotoxic shock induces inflammatory physiological response and triggers cell death program by promoting P38, IL-1β, and TNF-α gene expression in the brain and liver.

Keywords: chicken, DNA damage, Escherichia coli, gene expression, inflammation

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Authors: Jinsiang Shaw, Sheng-Xiang Xu

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This paper presents the development of an autonomous automated guided vehicle (AGV) with a robot arm attached on top of it within the framework of robot operation system (ROS). ROS can provide libraries and tools, including hardware abstraction, device drivers, libraries, visualizers, message-passing, package management, etc. For this reason, this AGV can provide automatic navigation and parts transportation and pick-and-place task using robot arm for typical industrial production line use. More specifically, this AGV will be controlled by an on-board host computer running ROS software. Command signals for vehicle and robot arm control and measurement signals from various sensors are transferred to respective microcontrollers. Users can operate the AGV remotely through the TCP / IP protocol and perform SLAM (Simultaneous Localization and Mapping). An RGBD camera and LIDAR sensors are installed on the AGV, using these data to perceive the environment. For SLAM, Gmapping is used to construct the environment map by Rao-Blackwellized particle filter; and AMCL method (Adaptive Monte Carlo localization) is employed for mobile robot localization. In addition, current AGV position and orientation can be visualized by ROS toolkit. As for robot navigation and obstacle avoidance, A* for global path planning and dynamic window approach for local planning are implemented. The developed ROS AGV with a robot arm on it has been experimented in the university factory. A 2-D and 3-D map of the factory were successfully constructed by the SLAM method. Base on this map, robot navigation through the factory with and without dynamic obstacles are shown to perform well. Finally, pick-and-place of parts using robot arm and ensuing delivery in the factory by the mobile robot are also accomplished.

Keywords: automated guided vehicle, navigation, robot operation system, Simultaneous Localization and Mapping

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Authors: Indika Fernando, Jiangang Fei, Roger Stanely, Hossein Enshaei

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Ever increasing demand for quality fresh produce by the consumers, had increased the gravity on the post-harvest supply chains in multi-fold in the recent years. Mechanical injury to fresh produce was a critical factor for produce wastage, especially with the expansion of supply chains, physically extending to thousands of miles. The impact of vibration damages in transit was identified as a specific area of focus which results in wastage of significant portion of the fresh produce, at times ranging from 10% to 40% in some countries. Several studies were concentrated on quantifying the impact of vibration to fresh produce, and it was a challenge to collect vibration impact data continuously due to the limitations in battery life or the memory capacity in the devices. Therefore, the study samples were limited to a stretch of the transit passage or a limited time of the journey. This may or may not give an accurate understanding of the vibration impacts encountered throughout the transit passage, which limits the accuracy of the results. Consequently, an approach which can extend the capacity and ability of determining vibration signals in the transit passage would contribute to accurately analyze the vibration damage along the post-harvest supply chain. A mechanism was developed to address this challenge, which is capable of measuring the in transit vibration continuously through the transit passage subject to a minimum acceleration threshold (0.1g). A system, consisting six tri-axel vibration transducers installed in different locations inside the cargo (produce) pallets in the truck, transmits vibration signals through LORA (Long Range Radio) technology to a central device installed inside the container. The central device processes and records the vibration signals transmitted by the portable transducers, along with the GPS location. This method enables to utilize power consumption for the portable transducers to maximize the capability of measuring the vibration impacts in the transit passage extending to days in the distribution process. The trial tests conducted using the approach reveals that it is a reliable method to measure and quantify the in transit vibrations along the supply chain. The GPS capability enables to identify the locations in the supply chain where the significant vibration impacts were encountered. This method contributes to determining the causes, susceptibility and intensity of vibration impact damages to fresh produce in the post-harvest supply chain. Extensively, the approach could be used to determine the vibration impacts not limiting to fresh produce, but for products in supply chains, which may extend from few hours to several days in transit.

Keywords: post-harvest, supply chain, wireless transducers, LORA, fresh produce

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Authors: Margarida Porfírio Tomás, Paula Pereira, José Manuel Palma Oliveira

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The decline in employment rates across sectors like industry and construction is exacerbated by an aging workforce. This has far-reaching implications for the economy, including skills gaps, labour shortages, productivity challenges due to physical limitations, and workplace safety concerns. To sustain the workforce and pension systems, technology plays a pivotal role. Robots provide valuable support to human workers, and effective human-robot interaction is essential. FORTIS, a Horizon project, aims to address these challenges by creating a comprehensive Human-Robot Interaction (HRI) solution. This solution focuses on multi-modal communication and multi-aspect interaction, with a primary goal of maintaining a human-centric approach. By meeting the needs of both human workers and robots, FORTIS aims to facilitate efficient and safe collaboration. The project encompasses three key activities: 1) A Human-Centric Approach involving data collection, annotation, understanding human behavioural cognition, and contextual human-robot information exchange. 2) A Robotic-Centric Focus addressing the unique requirements of robots during the perception and evaluation of human behaviour. 3) Ensuring Human-Robot Trustworthiness through measures such as human-robot digital twins, safety protocols, and resource allocation. Factor Social, a project partner, will analyse psycho-physiological signals that influence human factors, particularly in hazardous working conditions. The analysis will be conducted using a combination of case studies, structured interviews, questionnaires, and a comprehensive literature review. However, the adoption of novel technologies, particularly those involving human-robot interaction, often faces hurdles related to acceptance. To address this challenge, FORTIS will draw upon insights from Social Sciences and Humanities (SSH), including risk perception and technology acceptance models. Throughout its lifecycle, FORTIS will uphold a human-centric approach, leveraging SSH methodologies to inform the design and development of solutions. This project received funding from European Union’s Horizon 2020/Horizon Europe research and innovation program under grant agreement No 101135707 (FORTIS).

Keywords: skills gaps, productivity challenges, workplace safety, human-robot interaction, human-centric approach, social sciences and humanities, risk perception

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Authors: E. M. Condori-Peñaloza, S. S. Costa

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Eleusine indica L, known as goose-grass, is considered a troublesome weed that can cause important economic losses in the agriculture worldwide. However, this grass is used as a medicinal plant in some regions of Brazil to treat influenza and pneumonia. In Africa and Asia, it is used to treat malaria and as diuretic, anti-helminthic, among other uses. Despite its therapeutic potential, little is known about the chemical composition and bioactive compounds of E. indica. Hitherto, two major flavonoids, schaftoside and vitexin, were isolated from aerial part of the species and showed inhibitory activity on lung neutrophil influxes in mice, suggesting a beneficial effect on airway inflammation. Therefore, the aim of this study was to analyze the chemical profile of aqueous extracts from aerial parts of Eleusine indica specimens using high performance liquid chromatography (HPLC-DAD) and 1H nuclear magnetic resonance spectroscopy (NMR), with emphasis on phenolic compounds. Specimens of E. indica were collected in Minas Gerais state, Brazil. Aerial parts of fresh plants were extracted by decoction (10% p/v). After spontaneous precipitation of the aqueous extract at 10-12°C for 24 hours, the supernatant obtained was frozen and lyophilized. After that, 1 g of the extract was dissolved into 25 mL of water and fractionated on a reverse phase chromatography column (RP-2), eluted with a gradient of H2O/EtOH. Five fractions were obtained. The extract and fractions had their chemical profile analyzed by using HPLC-DAD (C-18 column: 20 μL, 256 -365 nm; gradient water 0.01% phosphoric acid/ acetonitrile. The extract was also analyzed by NMR (1H, 500 MHz, D2O) in order to access its global chemical composition. HPLC-DAD analyses of crude extract allowed the identification of ten phenolic compounds. Fraction 1, eluted with 100% water, was poor in phenolic compounds and no major peak was detected. In fraction 2, eluted with 100% water, it was possible to observe one major peak at retention time (RT) of 23.75 minutes compatible with flavonoid; fraction 3, also eluted with 100% water, showed four peaks at RT= 21.47, 23.52, 24.33 and 25.84 minutes, all of them compatible with flavonoid. In fraction 4, eluted with 50%/ethanol/50% water, it was possible to observe 3 peaks compatible with flavonoids at RT=24.65, 26.81, 27.49 minutes, and one peak (28.83 min) compatible with a phenolic acid derivative. Finally, in fraction 5, eluted with 100% ethanol, no phenolic substance was detected. The UV spectra of all flavonoids detected were compatible with the flavone subclass (λ= 320-345 nm). The 1H NMR spectra of aerial parts extract showed signals in three regions: δ 0.8-3.0 ppm (aliphatic compounds), δ 3.0-5.5 ppm corresponding to carbohydrates (signals most abundant and overlapped), and δ 6.0-8.5 ppm (aromatic compounds). Signals compatible with flavonoids (rings A and B) could also be detected in the crude extract spectra. These results suggest the presence of several flavonoids in E. indica, which reinforces their therapeutic potential. The pharmacological activities of Eleusine indica extracts and fractions will be further evaluated.

Keywords: flavonoids, HPLC, NMR, phenolic compounds

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Authors: Svetlana Cojocaru, Mircea Petic, Inga Titchiev

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Humanity faces more and more often with different social disasters, which in turn can generate new accidents and catastrophes. To mitigate their consequences, it is important to obtain early possible signals about the events which are or can occur and to prepare the corresponding scenarios that could be applied. Our research is focused on solving two problems in this domain: identifying signals related that an accident occurred or may occur and mitigation of some consequences of disasters. To solve the first problem, methods of selecting and processing texts from global network Internet are developed. Information in Romanian is of special interest for us. In order to obtain the mentioned tools, we should follow several steps, divided into preparatory stage and processing stage. Throughout the first stage, we manually collected over 724 news articles and classified them into 10 categories of social disasters. It constitutes more than 150 thousand words. Using this information, a controlled vocabulary of more than 300 keywords was elaborated, that will help in the process of classification and identification of the texts related to the field of social disasters. To solve the second problem, the formalism of Petri net has been used. We deal with the problem of inhabitants’ evacuation in useful time. The analysis methods such as reachability or coverability tree and invariants technique to determine dynamic properties of the modeled systems will be used. To perform a case study of properties of extended evacuation system by adding time, the analysis modules of PIPE such as Generalized Stochastic Petri Nets (GSPN) Analysis, Simulation, State Space Analysis, and Invariant Analysis have been used. These modules helped us to obtain the average number of persons situated in the rooms and the other quantitative properties and characteristics related to its dynamics.

Keywords: lexicon of disasters, modelling, Petri nets, text annotation, social disasters

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Authors: Mokhtar Arazpour

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Objectives: Recently a new kind of stance control knee joint has been developed called the 'sensor lock.' This study aimed to develop and evaluate 'sensor lock', which could potentially solve the problems of walking parameters and gait symmetry in subjects with quadriceps weakness. Methods: Nine subjects with quadriceps weakness were enrolled in this study. A custom-made knee ankle foot orthosis (KAFO) with the same set of components was constructed for each participant. Testing began after orthotic gait training was completed with each of the KAFOs and subjects demonstrated that they could safely walk with crutches. Subjects rested 30 minutes between each trial. The 10 meters walking test is used to assess walking speed in meters/second (m/s). The total time taken to ambulate 6 meters (m) is recorded to the nearest hundredth of a second. 6 m is then divided by the total time (in seconds) taken to ambulate and recorded in m/s. The 6 Minutes Walking Test was used to assess walking endurance in this study. Participants walked around the perimeter of a set circuit for a total of six minutes. To evaluate Physiological cost index (PCI), the subjects were asked to walk using each type of KAFOs along a pre-determined 40 m rectangular walkway at their comfortable self-selected speed. A stopwatch was used to calculate the speed of walking by measuring the time between starting and stopping time and the distance walked. Results: The use of a KAFO fitted with the “sensor lock” knee joint resulted in improvements to walking speed, distance walked and physiological cost index when compared with the knee joint in lock mode. Conclusions: This study demonstrated that the use of a KAFO with the “sensor lock” knee joint could provide significant benefits for subjects with a quadriceps weakness when compared to a KAFO with the knee joint in lock mode.

Keywords: stance control knee joint, knee ankle foot orthosis, quadriceps weakness, walking, energy consumption

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Authors: Yi Yang, Jiasong Sun

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Almost every aspect of our daily lives is now intertwined with some degree of human-computer interaction (HCI). HCI courses draw on knowledge from disciplines as diverse as computer science, psychology, design principles, anthropology, and more. Our HCI courses, named the Media and Cognition course, are constantly updated to reflect state-of-the-art technological advancements such as virtual reality, augmented reality, and artificial intelligence-based interactions. For more than a decade, our course has used an interest-based approach to teaching, in which students proactively propose some research-based questions and collaborate with teachers, using course knowledge to explore potential solutions. Semantic communication plays a key role in facilitating understanding and interaction between users and computer systems, ultimately enhancing system usability and user experience. The advancements in AI-generated technology, which have gained significant attention from both academia and industry in recent years, are exemplified by language models like GPT-3 that generate human-like dialogues from given prompts. Our latest version of the Human-Computer Interaction course practices a semantic communication platform based on AI-generated techniques. The purpose of this semantic communication is twofold: to extract and transmit task-specific information while ensuring efficient end-to-end communication with minimal latency. An AI-generated semantic communication platform evaluates the retention of signal sources and converts low-retain ability visual signals into textual prompts. These data are transmitted through AI-generated techniques and reconstructed at the receiving end; on the other hand, visual signals with a high retain ability rate are compressed and transmitted according to their respective regions. The platform and associated research are a testament to our students' growing ability to independently investigate state-of-the-art technologies.

Keywords: human-computer interaction, media and cognition course, semantic communication, retainability, prompts

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Authors: Hadj Abd El Kader Benghenia, Fethi Bereksi Reguig

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In clinical medicine, blood pressure, raised blood hemodynamic monitoring is rich pathophysiological information of cardiovascular system, of course described through factors such as: blood volume, arterial compliance and peripheral resistance. In this work, we are interested in analyzing these signals to propose a detection algorithm to delineate the different sequences and especially systolic blood pressure (SBP), diastolic blood pressure (DBP), and the wave and dicrotic to do their analysis in order to extract the cardiovascular parameters.

Keywords: blood pressure, SBP, DBP, detection algorithm

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Authors: Laura Helena Caicedo Lopez, Luis Miguel Contreras Medina, Ramon Gerardo Guevara Gonzales, Juan E. Andrade

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In this study, we evaluated the effect of three different hydric stress conditions: Low (LHS), medium (MHS), and high (HHS) on capsaicinoid content and enzyme regulation of C. annuum plants. Five main peaks were detected using a 2 Hz resolution vibrometer laser (Polytec-B&K). These peaks or “characteristic frequencies” were used as acoustic emissions (AEs) treatment, transforming these signals into audible sound with the frequency (Hz) content of each hydric stress. Capsaicinoids (CAPs) are the main, secondary metabolites of chili pepper plants and are known to increase during hydric stress conditions or short drought-periods. The AEs treatments were applied in two plant stages: the first one was in the pre-anthesis stage to evaluate the genes that encode the transcription of enzymes responsible for diverse metabolic activities of C. annuum plants. For example, the antioxidant responses such as peroxidase (POD), superoxide dismutase (Mn-SOD). Also, phenyl-alanine ammonia-lyase (PAL) involved in the biosynthesis of the phenylpropanoid compounds. The chalcone synthase (CHS) related to the natural defense mechanisms and species-specific aquaporin (CAPIP-1) that regulate the flow of water into and out of cells. The second stage was at 40 days after flowering (DAF) to evaluate the biochemical effect of AEs related to hydric stress on capsaicinoids production. These two experiments were conducted to identify the molecular responses of C. annuum plants to AE. Moreover, to define AEs could elicit any increase in the capsaicinoids content after a one-week exposition to AEs treatments. The results show that all AEs treatment signals (LHS, MHS, and HHS) were significantly different compared to the non-acoustic emission control (NAE). Also, the AEs induced the up-regulation of POD (~2.8, 2.9, and 3.6, respectively). The gene expression of another antioxidant response was particularly treatment-dependent. The HHS induced and overexpression of Mn-SOD (~0.23) and PAL (~0.33). As well, the MHS only induced an up-regulation of the CHs gene (~0.63). On the other hand, CAPIP-1 gene gas down-regulated by all AEs treatments LHS, MHS, and HHS ~ (-2.4, -0.43 and -6.4, respectively). Likewise, the down-regulation showed particularities depending on the treatment. LHS and MHS induced downregulation of the SOD gene ~ (-1.26 and -1.20 respectively) and PAL (-4.36 and 2.05, respectively). Correspondingly, the LHS and HHS showed the same tendency in the CHs gene, respectively ~ (-1.12 and -1.02, respectively). Regarding the elicitation effect of AE on the capsaicinoids content, additional treatment controls were included. A white noise treatment (WN) to prove the frequency-selectiveness of signals and a hydric stressed group (HS) to compare the CAPs content. Our findings suggest that WN and NAE did not present differences statically. Conversely, HS and all AEs treatments induced a significant increase of capsaicin (Cap) and dihydrocapsaicin (Dcap) after one-week of a treatment. Specifically, the HS plants showed an increase of 8.33 times compared to the NAE and WN treatments and 1.4 times higher than the MHS, which was the AEs treatment with a larger induction of Capsaicinoids among treatments (5.88) and compared to the controls.

Keywords: acoustic emission, capsaicinoids, elicitors, hydric stress, plant signaling

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Authors: Qianhui Li, Christoph H. Bruecker

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Atherosclerotic plaques are typically found where flow separation and variations of shear stress occur. Although helical flow patterns and flow separations have been recorded in the aorta, their relation has not been clearly clarified and especially in the condition of artificial heart valve prostheses. Therefore, an experimental study is performed to investigate the hemodynamic performance of different mechanical heart valves (MHVs), i.e. the SJM Regent bileaflet mechanical heart valve (BMHV) and the Lapeyre-Triflo FURTIVA trileaflet mechanical heart valve (TMHV), in a transparent model of the human aorta under a physiological pulsatile right-hand helical flow condition. A typical systolic flow profile is applied in the pulse-duplicator to generate a physiological pulsatile flow which thereafter flows past an axial turbine blade structure to imitate the right-hand helical flow induced in the left ventricle. High-speed particle image velocimetry (PIV) measurements are used to map the flow evolution. A circular open orifice nozzle inserted in the valve plane as the reference configuration initially replaces the valve under investigation to understand the hemodynamic effects of the entered helical flow structure on the flow evolution in the aortic arch. Flow field analysis of the open orifice nozzle configuration illuminates the helical flow effectively delays the flow separation at the inner radius wall of the aortic arch. The comparison of the flow evolution for different MHVs shows that the BMHV works like a flow straightener which re-configures the helical flow pattern into three parallel jets (two side-orifice jets and the central orifice jet) while the TMHV preserves the helical flow structure and therefore prevent the flow separation at the inner radius wall of the aortic arch. Therefore the TMHV is of better hemodynamic performance and reduces the pressure loss.

Keywords: flow separation, helical aortic flow, mechanical heart valve, particle image velocimetry

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