Search results for: battery diagnosis

Authors: Nuray Ucar, Pelin Altay, Ilkay Ozsev Yuksek

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Graphene oxide fibers have recently received increasing attention due to their excellent properties such as high specific surface area, high mechanical strength, good thermal properties and high electrical conductivity. They have shown notable potential in various applications including batteries, sensors, filtration and separation and wearable electronics. Carbon nanotubes (CNTs) have unique structural, mechanical, and electrical properties and can be used together with graphene oxide fibers for several application areas such as lithium ion batteries, wearable electronics, etc. Metals salts that can be converted into metal ions and metal oxide can be also used for several application areas such as battery, purification natural gas, filtration, absorption. This study investigates the effects of CNT and metal complex compounds (MnCl₂, metal salts) on the morphological structure of graphene oxide fibers. The graphene oxide dispersion was manufactured by modified Hummers method, and continuous graphene oxide fibers were produced with wet spinning. The CNT and MnCl₂ were incorporated into the coagulation baths during wet spinning process. Produced composite continuous fibers were analyzed with SEM, SEM-EDS and AFM microscopies and as spun fiber counts were measured.

Keywords: continuous graphene oxide fiber, Hummers' method, CNT, MnCl₂

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Authors: Ali Shareef, Aliha Shareef, Yifeng Zhu

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Energy minimization is of great importance in wireless sensor networks in extending the battery lifetime. One of the key activities of nodes in a WSN is communication and the routing of their data to a centralized base-station or sink. Routing using the shortest path to the sink is not the best solution since it will cause nodes along this path to fail prematurely. We propose a cross-layer energy efficient routing protocol Optrix that utilizes a convex formulation to maximize the lifetime of the network as a whole. We further propose, Optrix-BW, a novel convex formulation with bandwidth constraint that allows the channel conditions to be accounted for in routing. By considering this key channel parameter we demonstrate that Optrix-BW is capable of congestion control. Optrix is implemented in TinyOS, and we demonstrate that a relatively large topology of 40 nodes can converge to within 91% of the optimal routing solution. We describe the pitfalls and issues related with utilizing a continuous form technique such as convex optimization with discrete packet based communication systems as found in WSNs. We propose a routing controller mechanism that allows for this transformation. We compare Optrix against the Collection Tree Protocol (CTP) and we found that Optrix performs better in terms of convergence to an optimal routing solution, for load balancing and network lifetime maximization than CTP.

Keywords: wireless sensor network, Energy Efficient Routing

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Authors: Min Kyung An

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In Wireless Sensor Networks which consist of tiny wireless sensor nodes with limited battery power, one of the most fundamental applications is data aggregation which collects nearby environmental conditions and aggregates the data to a designated destination, called a sink node. Important issues concerning the data aggregation are time efficiency and energy consumption due to its limited energy, and therefore, the related problem, named Minimum Latency Aggregation Scheduling (MLAS), has been the focus of many researchers. Its objective is to compute the minimum latency schedule, that is, to compute a schedule with the minimum number of timeslots, such that the sink node can receive the aggregated data from all the other nodes without any collision or interference. For the problem, the two interference models, the graph model and the more realistic physical interference model known as Signal-to-Interference-Noise-Ratio (SINR), have been adopted with different power models, uniform-power and non-uniform power (with power control or without power control), and different antenna models, omni-directional antenna and directional antenna models. In this survey article, as the problem has proven to be NP-hard, we present and compare several state-of-the-art approximation algorithms in various models on the basis of latency as its performance measure.

Keywords: data aggregation, convergecast, gathering, approximation, interference, omni-directional, directional

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Authors: Jessica A. Hellings, Piyushkumar Jani

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Background: Systemic autoimmune disorders are increasingly implicated in neuropsychiatric illness, especially in the setting of treatment resistance in individuals of all ages. Gluten allergy in fullest extent results in celiac disease, affecting multiple organs including central nervous system (CNS). Clinicians often lack awareness of the association between neuropsychiatric illness and gluten allergy, partly since many such research studies are published in immunology and gastroenterology journals. Methods: Following a Pubmed literature search and online searches on celiac disease websites, 40 articles are critically reviewed in detail. This work reviews celiac disease, gluten intolerance and current evidence of their relationship to neuropsychiatric and systemic illnesses. The review also covers current work-up and diagnosis, as well as dietary interventions, gluten restriction outcomes, and future research directions. Results: Gluten allergy in susceptible individuals damages the small intestine, producing a leaky gut and malabsorption state, as well as allowing antibodies into the bloodstream, which attack major organs. Lack of amino acid precursors for neurotransmitter synthesis together with antibody-associated brain changes and hypoperfusion may result in neuropsychiatric illness. This is well documented; however, studies in neuropsychiatry are often small. In the large CATIE trial, subjects with schizophrenia had significantly increased antibodies to tissue transglutaminase (TTG), and antigliadin antibodies, both significantly greater gluten antibodies than in control subjects. On later follow up, TTG-6 antibodies were identified in these subjects’ brains but not in their intestines. Significant evidence mostly from small studies also exists for gluten allergy and celiac-related depression, anxiety disorders, attention-deficit/hyperactivity disorder, autism spectrum disorders, ataxia, and epilepsy. Dietary restriction of gluten resulted in remission in several published cases, including for treatment-resistant schizophrenia. Conclusions: Ongoing and larger studies are needed of the diagnosis and treatment efficacy of the gluten-free diet in neuropsychiatric illness. Clinicians should ask about the patient history of anemia, hypothyroidism, irritable bowel syndrome and family history of benefit from the gluten-free diet, not limited to but especially in cases of treatment resistance. Obtaining gluten antibodies by a simple blood test, and referral for gastrointestinal work-up in positive cases should be considered.

Keywords: celiac, gluten, neuropsychiatric, translational

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Authors: Heri Suryoatmojo, Adi Kurniawan, Feby A. Pamuji, Nursalim, Syaffaruddin, Herbert Innah

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Photovoltaic (PV) system hybrid with diesel system is utilized widely for electrification in remote area. PV output power fluctuates due to uncertainty condition of temperature and sun irradiance. When the penetration of PV power is large, the reliability of the power utility will be disturbed and seriously impact the unstable frequency of system. Therefore, designing a robust frequency controller in PV-diesel hybrid power system is very important. This paper proposes new method of frequency control application in hybrid PV-diesel system based on artificial neural network (ANN). This method can minimize the frequency deviation without smoothing PV output power that controlled by maximum power point tracking (MPPT) method. The neural network algorithm controller considers average irradiance, change of irradiance and frequency deviation. In order the show the effectiveness of proposed algorithm, the addition of battery as energy storage system is also presented. To validate the proposed method, the results of proposed system are compared with the results of similar system using MPPT only. The simulation results show that the proposed method able to suppress frequency deviation smaller compared to the results of system using MPPT only.

Keywords: energy storage system, frequency deviation, hybrid power generation, neural network algorithm

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Authors: Liang Zhao, Jili Zhang, Chongquan Zhong

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Energy consumption data, in particular those involving public buildings, are impacted by many factors: the building structure, climate/environmental parameters, construction, system operating condition, and user behavior patterns. Traditional methods for data analysis are insufficient. This paper delves into the data mining technology to determine its application in the analysis of building energy consumption data including energy consumption prediction, fault diagnosis, and optimal operation. Recent literature are reviewed and summarized, the problems faced by data mining technology in the area of energy consumption data analysis are enumerated, and research points for future studies are given.

Keywords: data mining, data analysis, prediction, optimization, building operational performance

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Authors: Danna Jia, Bin Li

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Background: Atopic dermatitis (AD) is a chronic and refractory inflammatory skin disease characterized by relapsing eczematous and pruritic skin lesions. The global prevalence of AD ranges from 1~ 20%, and its incidence rates are increasing. It affects individuals from infancy to adulthood, significantly impacting their daily lives and social activities. Despite its major health burden, the precise mechanisms underlying AD remain unknown. Understanding the genetic differences associated with AD is crucial for advancing diagnosis and targeted treatment development. This study aims to identify candidate genes of AD by using bioinformatics analysis. Methods: We conducted a comprehensive analysis of four pooled transcriptomic datasets (GSE16161, GSE32924, GSE130588, and GSE120721) obtained from the Gene Expression Omnibus (GEO) database. Differential gene expression analysis was performed using the R statistical language. The differentially expressed genes (DEGs) between AD patients and normal individuals were functionally analyzed using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Furthermore, a protein-protein interaction (PPI) network was constructed to identify candidate genes. Results: Among the patient-level gene expression datasets, we identified 114 shared DEGs, consisting of 53 upregulated genes and 61 downregulated genes. Functional analysis using GO and KEGG revealed that the DEGs were mainly associated with the negative regulation of transcription from RNA polymerase II promoter, membrane-related functions, protein binding, and the Human papillomavirus infection pathway. Through the PPI network analysis, we identified eight core genes: CD44, STAT1, HMMR, AURKA, MKI67, and SMARCA4. Conclusion: This study elucidates key genes associated with AD, providing potential targets for diagnosis and treatment. The identified genes have the potential to contribute to the understanding and management of AD. The bioinformatics analysis conducted in this study offers new insights and directions for further research on AD. Future studies can focus on validating the functional roles of these genes and exploring their therapeutic potential in AD. While these findings will require further verification as achieved with experiments involving in vivo and in vitro models, these results provided some initial insights into dysfunctional inflammatory and immune responses associated with AD. Such information offers the potential to develop novel therapeutic targets for use in preventing and treating AD.

Keywords: atopic dermatitis, bioinformatics, biomarkers, genes

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Authors: Sirus Mohammadi, Rohala Moghimi

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The main advantages of microgrids are high energy efficiency through the application of Combined Heat and Power (CHP), high quality and reliability of the delivered electric energy and environmental and economic advantages. This study presents an energy management system (EMS) to optimize the operation of the microgrid (MG). In this paper an Adaptive Modified Firefly Algorithm (AMFA) is presented for optimal operation of a typical MG with renewable energy sources (RESs) accompanied by a back-up Micro-Turbine/Fuel Cell/Battery hybrid power source to level the power mismatch or to store the energy surplus when it’s needed. The problem is formulated as a nonlinear constraint problem to minimize the total operating cost. The management of Energy storage system (ESS), economic load dispatch and operation optimization of distributed generation (DG) are simplified into a single-object optimization problem in the EMS. The proposed algorithm is tested on a typical grid-connected MG including WT/PV/Micro Turbine/Fuel Cell and Energy Storage Devices (ESDs) then its superior performance is compared with those from other evolutionary algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Fuzzy Self Adaptive PSO (FSAPSO), Chaotic Particle PSO (CPSO), Adaptive Modified PSO (AMPSO), and Firefly Algorithm (FA).

Keywords: microgrid, operation management, optimization, firefly algorithm (AMFA)

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Authors: Anusit Punsirichaiyakul, Tosaphol Ratniyomchai, Thanatchai Kulworawanichpong

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The paper aims to study the energy storage system in the form of gravity energy by the weight of concrete stacks. This technology has the potential to replace expensive battery storage. This paper is a trial plan in abandoned mines in Thailand. This is to start with construct concrete boxes to be stacked vertically or obliquely to form appropriate shapes and, therefore, to store the potential energy. The stored energy can be released or discharged back to the system by deploying the concrete stacks to the ground. This is to convert the potential energy stored in the concrete stacks to the kinetic energy of the concrete box movement. This design is incorporating mechanical transmission to reduce the height of the concrete stacks. This study also makes a comparison between the energy used to construct concrete stacks in various shapes and the energy to deploy all the concrete boxes to ground. This paper consists of 2 test systems. The first test is to stack the concrete in vertical shape. The concrete stack has a maximum height of 50 m with a gear ratio of 1:200. The concrete box weight is 115 tons/piece with a total stored energy of 1800 kWh. The oblique system has a height of 50 m with a similar gear ratio of 1:200. The weight of the concrete box is 90 tons/piece and has a total stored energy of 1440 kWh. Also, it has an overall efficiency of 65% and a lifetime of 50 years. This storage has higher storage densities compared to other systems.

Keywords: gravity, concrete stacks, vertical, oblique

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Authors: Keiko Yamauchi, Motoyuki Nakao, Yoko Ishihara

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The increase in the number of women with breast cancer in Japan has required hospitals to provide a higher quality of medicine so that patients are satisfied with the treatment they receive. However, patients’ satisfaction following breast cancer treatment has not been sufficiently studied. Hence, we investigated the factors influencing patient satisfaction following breast cancer treatment among Japanese women. These women underwent either breast-conserving surgery (BCS) (n = 380) or total mastectomy (TM) (n = 247). In March 2016, we conducted a cross-sectional internet survey of Japanese women with breast cancer in Japan. We assessed the following factors: socioeconomic status, cancer-related information, the role of medical decision-making, the degree of satisfaction regarding the treatments received, and the regret arising from the medical decision-making processes. We performed logistic regression analyses with the following dependent variables: extreme satisfaction with the treatments received, and regret regarding the medical decision-making process. For both types of surgery, the odds ratio (OR) of being extremely satisfied with the cancer treatment was significantly higher among patients who did not have any regrets compared to patients who had. Also, the OR tended to be higher among patients who chose to play a wanted role in the medical decision-making process, compared with patients who did not. In the BCS group, the OR of being extremely satisfied with the treatment was higher if, at diagnosis, the patient’s youngest child was older than 19 years, compared with patients with no children. The OR was also higher if patient considered the stage and characteristics of their cancer significant. The OR of being extremely satisfied with the treatments was lower among patients who were not employed on full-time basis, and among patients who considered the second medical opinions and medical expenses to be significant. These associations were not observed in the TM group. The OR of having regrets regarding the medical decision-making process was higher among patients who chose to play a role in the decision-making process as they preferred, and was also higher in patients who were employed on either a part-time or contractual basis. For both types of surgery, the OR was higher among patients who considered a second medical opinion to be significant. Regardless of surgical type, regret regarding the medical decision-making process decreases treatment satisfaction. Patients who received breast-conserving surgery were more likely to have regrets concerning the medical decision-making process if they could not play a role in the process as they preferred. In addition, factors associated with the satisfaction with treatment in BCS group but not TM group included the second medical opinion, medical expenses, employment status, and age of the youngest child at diagnosis.

Keywords: medical decision making, breast-conserving surgery, total mastectomy, Japanese

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Authors: Vinai K. Singh

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In Neural Network-based Learning techniques, there are several models of Convolutional Networks. Whenever the methods are deployed with large datasets, only then can their applicability and appropriateness be determined. Clinical and pathological pictures of lobular carcinoma are thought to exhibit a large number of random formations and textures. Working with such pictures is a difficult problem in machine learning. Focusing on wet laboratories and following the outcomes, numerous studies have been published with fresh commentaries in the investigation. In this research, we provide a framework that can operate effectively on raw photos of various resolutions while easing the issues caused by the existence of patterns and texturing. The suggested approach produces very good findings that may be used to make decisions in the diagnosis of cancer.

Keywords: lobular carcinoma, convolutional neural networks (CNN), deep learning, histopathological imagery scans

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Authors: Jacob Wahl, Jane Zhang

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This paper describes the development and characterization of a prototype IoT network for use with agricultural imaging and monitoring applications. The sensor and gateway nodes are designed using the ESP32 SoC with integrated Bluetooth Low Energy 4.2 and Wi-Fi. A development board, the Arducam IoTai ESP32, is used for prototyping, testing, and power measurements. Google’s Firebase is used as the cloud storage site for image data collected by the sensor. The sensor node captures images using the OV2640 2MP camera module and transmits the image data to the gateway via Bluetooth Low Energy. The gateway then uploads the collected images to Firebase via a known nearby Wi-Fi network connection. This image data can then be processed and analyzed by computer vision and machine learning pipelines to assess crop growth or other needs. The sensor node achieves a wireless transmission data throughput of 220kbps while consuming 150mA of current; the sensor sleeps at 162µA. The sensor node device lifetime is estimated to be 682 days on a 6600mAh LiPo battery while acquiring five images per day based on the development board power measurements. This network can be utilized by any application that requires high data rates, low power consumption, short-range communication, and large amounts of data to be transmitted at low-frequency intervals.

Keywords: Bluetooth low energy, ESP32, firebase cloud, IoT, smart farming

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Authors: Alamgir Naushad, Ghulam Abbas, Shehzad Ali Shah, Ziaul Haq Abbas

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Unlike conventional networks, it is particularly challenging to manage resources efficiently in Wireless Sensor Networks (WSNs) due to their inherent characteristics, such as dynamic network topology and limited bandwidth and battery power. To ensure energy efficiency, this paper presents a routing protocol for WSNs, namely, Enhanced Hybrid Multipath Routing (EHMR), which employs hierarchical clustering and proposes a next hop selection mechanism between nodes according to a maximum residual energy metric together with a minimum hop count. Load-balancing of data traffic over multiple paths is achieved for a better packet delivery ratio and low latency rate. Reliability is ensured in terms of higher data rate and lower end-to-end delay. EHMR also enhances the fast-failure recovery mechanism to recover a failed path. Simulation results demonstrate that EHMR achieves a higher packet delivery ratio, reduced energy consumption per-packet delivery, lower end-to-end latency, and reduced effect of data rate on packet delivery ratio when compared with eminent WSN routing protocols.

Keywords: energy efficiency, load-balancing, hierarchical clustering, multipath routing, wireless sensor networks

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Authors: Yasar Samet Gokceoglu, Ayse Nur Incesu, Furkan Okatar, Berk Nimetoglu, Serkan Bayram, Turgut Akgul

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Ankle syndesmosis injuries pose a significant challenge in orthopedic practice due to their potential for prolonged recovery and chronic ankle dysfunction. Accurate diagnosis and management of these injuries are essential for achieving optimal patient outcomes. The use of radiological methods, such as X-ray, computed tomography (CT), and magnetic resonance imaging (MRI), plays a vital role in the accurate diagnosis of syndesmosis injuries in the context of ankle fractures. Treatment options for ankle syndesmosis injuries vary, with surgical interventions such as screw fixation and suture-button implantation being commonly employed. The choice of treatment is influenced by the severity of the injury and the presence of associated fractures. Additionally, the mechanism of injury, such as pure syndesmosis injury or specific fracture types, can impact the stability and management of syndesmosis injuries. Ankle fractures with syndesmosis injury present a complex clinical scenario, requiring accurate diagnosis, appropriate reduction, and tailored management strategies. The interplay between the mechanism of injury, associated fractures, and treatment modalities significantly influences the outcomes of these challenging injuries. The long-term outcomes and patient satisfaction following ankle fractures with syndesmosis injury are crucial considerations in the field of orthopedics. Patient-reported outcome measures, such as the Foot and Ankle Outcome Score (FAOS), provide essential information about functional recovery and quality of life after these injuries. When diagnosing syndesmosis injuries, standard measurements, such as the medial clear space, tibiofibular overlap, tibiofibular clear space, anterior tibiofibular ratio (ATFR), and the anterior-posterior tibiofibular ratio (APTF), are assessed through radiographs and computed tomography (CT) scans. These parameters are critical in evaluating the presence and severity of syndesmosis injuries, enabling clinicians to choose the most appropriate treatment approach. Despite advancements in diagnostic imaging, challenges remain in accurately diagnosing and treating ankle syndesmosis injuries. Traditional diagnostic parameters, while beneficial, may not capture the full extent of the injury or provide sufficient information to guide therapeutic decisions. This gap highlights the need for exploring additional diagnostic parameters that could enhance the accuracy of syndesmosis injury diagnoses and inform treatment strategies more effectively. The primary goal of this research is to evaluate the usefulness of traditional radiographic measurements in comparison to new CT-based measurements for diagnosing ankle syndesmosis injuries. Specifically, this study aims to assess the accuracy of conventional parameters, including medial clear space, tibiofibular overlap, tibiofibular clear space, ATFR, and APTF, in contrast with the recently proposed CT-based measurements such as the delta and gamma angles. Moreover, the study intends to explore the relationship between these diagnostic parameters and functional outcomes, as measured by the Foot and Ankle Outcome Score (FAOS). Establishing a correlation between specific diagnostic measurements and FAOS scores will enable us to identify the most reliable predictors of functional recovery following syndesmosis injuries. This comparative analysis will provide valuable insights into the accuracy and dependability of CT-based measurements in diagnosing ankle syndesmosis injuries and their potential impact on predicting patient outcomes. The results of this study could greatly influence clinical practices by refining diagnostic criteria and optimizing treatment planning for patients with ankle syndesmosis injuries.

Keywords: ankle syndesmosis injury, diagnostic accuracy, computed tomography, radiographic measurements, Tibiofibular syndesmosis distance

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Authors: Aneesha Fonseca, Arij Daas, Muhammed Abdulkader

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Transient intraocular pressure (IOP) rise is a common occurrence after glaucoma laser procedures. However, this pressure spike usually lasts only a few days. We describe a case of a 60-year-old Caucasian gentleman who underwent selective laser trabeculoplasty (SLT) in both eyes for ocular hypertension previously treated with Bimatoprost and Timolol and developed a sustained raised IOP. His IOP rose from 34 and 33 mmHg pre-laser to 48 and 42 mmHg after SLT in the right and left eye, respectively. Even after maximum medical therapy (Bimatoprost, Timolol, Brinzolamide Apraclonidine, and oral Acetozolamide), his IOP remained at 32 and 28mmHg. A provisional diagnosis of trabeculitis was made, and topical Ketorolac was commenced in addition to the IOP-lowering medications. Within a week, his IOP came down to 21 and 18mmHg in the right and left eye, respectively.

Keywords: complications, selective laser trabeculoplasty, sustained pressure rise, trabeculitis

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Authors: Z. Mmango, U. Nwodo, L. V. Mabinya, A. I. Okoh

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Cellulose and hemicellulose account for a large portion of the world‘s plant biomass. In nature, these polysaccharides are intertwined forming complex materials that requires multiple and expensive treatment processes to free up the raw materials trapped in the matrix. Enzymatic degradation remains as the preferred technique as it is inexpensive and eco-friendly. However, the insufficiencies of enzyme battery systems in the degradation of lignocellulosic complex motivate the search for effective degrading enzymes from bacterial isolates from uncommon environment. The study aimed at the evaluation of actinomycetes isolated from saw dust samples collected from wood factory under bed. Cellulase and xylanase production was screened through organism culture on carboxyl methyl cellulose agar and Birchwood xylan. Halo zone indicating lignocellose utilization was shown by an isolate identified through 16S rRNA gene as Micrococcus luteus. The optimum condition for the production of cellulase and xylanase were incubation temperature of 25 °C, fermentation medium pH 5 and 10, agitation speed of 50 and 200 (rpm) and fermentation incubation time of 96 and 84 (h) respectively. The high cellulose and xylanase activity obtained from this isolate portends industrial relevance.

Keywords: carboxyl methyl cellulose, birchwood xylan, optimization, cellulase, xylanase, micrococcus, DNS method

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Authors: Mekha Mathew, Varun P Gopi

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Wireless Capsule Endoscopy (WCE) has become a great device in Gastrointestinal (GI) tract diagnosis, which can examine the entire GI tract, especially the small intestine without invasiveness and sedation. Bleeding in the digestive tract is a symptom of a disease rather than a disease itself. Hence the detection of bleeding is important in diagnosing many diseases. In this paper we proposes a novel method for distinguishing bleeding regions from normal regions based on Contourlet transform and Local Binary Pattern (LBP). Experiments show that this method provides a high accuracy rate of 96.38% in CIE XYZ colour space for k-Nearest Neighbour (k-NN) classifier.

Keywords: Wireless Capsule Endoscopy, local binary pattern, k-NN classifier, contourlet transform

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Authors: M. D. Levi, Netanel Shpigel, Sergey Sigalov, Gregory Salitra, Leonid Daikhin, Doron Aurbach

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We have developed an in-situ method for tracking ions adsorption into composite nanoporous carbon electrodes based on quartz-crystal microbalance (QCM). In these first papers QCM was used as a simple gravimetric probe of compositional changes in carbon porous composite electrodes during their charging since variation of the electrode potential did not change significantly width of the resonance. In contrast, when we passed from nanoporous carbons to a composite Li-ion battery material such as LiFePO4 olivine, the change in the resonance width was comparable with change of the resonance frequency (polymeric binder PVdF was shown to be completely rigid when used in aqueous solutions). We have provided a quantitative hydrodynamic admittance model of ion-insertion processes into electrode host accompanied by intercalation-induced dimensional changes of electrode particles, and hence the entire electrode coating. The change in electrode deformation and the related porosity modify hydrodynamic solid-liquid interactions tracked by QCM with dissipation monitoring. Using admittance modeling, we are able to evaluate the changes of effective thickness and permeability/porosity of composite electrode caused by applied potential and as a function of cycle number. This unique non-destructive technique may have great advantage in early diagnostics of cycling life durability of batteries and supercapacitors.

Keywords: Li-ion batteries, particles deformations, QCM-D, viscoelasticity

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Authors: Tania Chalton

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In June 2013, an independent review of the Liverpool Care Pathway (LCP) identified a number of problems with the implementation of the LCP in the UK and recommended that it be replaced by individual care plans for each patient. As a result of the UK findings, in November 2013 the Ministry of Health (MOH) commissioned the Palliative Care Council to initiate a programme of work to investigate an appropriate approach for the care of people in their last days of life in New Zealand (NZ). The Last Days of Life Working Group commenced a process to develop national consensus on the care of people in their last days of life in April 2014. In order to develop its advice for the future provision of care to people in their last days of life, the Working Group (WG) established a comprehensive work programme and as a result has developed a series of working papers. Specific areas of focus included: An analysis of the UK Independent Review findings and an assessment of these findings to the NZ context. A stocktake of services providing care to people in their last days of life, including aged residential care (ARC); hospices; hospitals; and primary care. International and NZ literature reviews of evidence and best practice. Survey of family to understand the consumer perspective on the care of people in their last days of life. Key aspects of care that required further considerations for NZ were: Terminology: clarify terminology used in the last days of life and in relation to death and dying. Evidenced based: including specific review of evidence regarding, spiritual, culturally appropriate care as well as dementia care. Diagnosis of dying: need for both guidance around the diagnosis of dying and communication with family. Workforce issues: access to an appropriate workforce after hours. Nutrition and hydration: guidance around appropriate approaches to nutrition and hydration. Symptom and pain management: guidance around symptom management. Documentation: documentation of the person’s care which is robust enough for data collection and auditing requirements, not ‘tick box’ approach to care. Education and training: improved consistency and access to appropriate education and training. Leadership: A dedicated team or person to support and coordinate the introduction and implementation of any last days of life model of care. Quality indicators and data collection: model of care to enable auditing and regular reviews to ensure on-going quality improvement. Cultural and spiritual: address and incorporate any cultural and spiritual aspects. A final document was developed incorporating all the evidence which provides guidance to the health sector on best practice for people at end of life: “Principles and guidance for the last days of life: Te Ara Whakapiri”.

Keywords: end of life, guidelines, New Zealand, palliative care

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Authors: Leonard Tiong, Sonit Singh, Kevin Ho Shon, Sarah Lewis

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Investigation into the use of artificial intelligence in radiology continues to develop at a rapid rate. During the coronavirus pandemic, the combination of an exponential increase in chest x-rays and unpredictable staff shortages resulted in a huge strain on the department's workload. There is a World Health Organisation estimate that two-thirds of the global population does not have access to diagnostic radiology. Therefore, there could be demand for a program that could detect acute changes in imaging compatible with infection to assist with screening. We generated a conventional neural network and tested its efficacy in recognizing changes compatible with coronavirus infection. Following ethics approval, a deidentified set of 77 normal and 77 abnormal chest x-rays in patients with confirmed coronavirus infection were used to generate an algorithm that could train, validate and then test itself. DICOM and PNG image formats were selected due to their lossless file format. The model was trained with 100 images (50 positive, 50 negative), validated against 28 samples (14 positive, 14 negative), and tested against 26 samples (13 positive, 13 negative). The initial training of the model involved training a conventional neural network in what constituted a normal study and changes on the x-rays compatible with coronavirus infection. The weightings were then modified, and the model was executed again. The training samples were in batch sizes of 8 and underwent 25 epochs of training. The results trended towards an 85.71% true positive/true negative detection rate and an area under the curve trending towards 0.95, indicating approximately 95% accuracy in detecting changes on chest X-rays compatible with coronavirus infection. Study limitations include access to only a small dataset and no specificity in the diagnosis. Following a discussion with our programmer, there are areas where modifications in the weighting of the algorithm can be made in order to improve the detection rates. Given the high detection rate of the program, and the potential ease of implementation, this would be effective in assisting staff that is not trained in radiology in detecting otherwise subtle changes that might not be appreciated on imaging. Limitations include the lack of a differential diagnosis and application of the appropriate clinical history, although this may be less of a problem in day-to-day clinical practice. It is nonetheless our belief that implementing this program and widening its scope to detecting multiple pathologies such as lung masses will greatly assist both the radiology department and our colleagues in increasing workflow and detection rate.

Keywords: artificial intelligence, COVID, neural network, machine learning

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Authors: Wei Hu, Wenguang Chen, Chong Dong

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In order to improve the efficiency and safety of photovoltaic power generation devices, this photovoltaic power generation system combines Artificial Intelligence (AI) and the Internet of Things (IoT) to control the chasing photovoltaic power generation device to track the sun to improve power generation efficiency and then convert energy management. The system uses artificial intelligence as the control terminal, the power generation device executive end uses the Linux system, and Exynos4412 is the CPU. The power generating device collects the sun image information through Sony CCD. After several power generating devices feedback the data to the CPU for processing, several CPUs send the data to the artificial intelligence control terminal through the Internet. The control terminal integrates the executive terminal information, time information, and environmental information to decide whether to generate electricity normally and then whether to convert the converted electrical energy into the grid or store it in the battery pack. When the power generation environment is abnormal, the control terminal authorizes the protection strategy, the power generation device executive terminal stops power generation and enters a self-protection posture, and at the same time, the control terminal synchronizes the data with the cloud. At the same time, the system is more intelligent, more adaptive, and longer life.

Keywords: photo-voltaic power generation, the pursuit of light, artificial intelligence, internet of things, photovoltaic array, power management

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Authors: Samarjeet Singh, Shubhank Arya, Shubham Chauhan

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In recent years, the rise in carbon emissions and the widespread effects of global warming have brought new energy vehicles into the spotlight. Electric vehicles (EVs) and hydrogen fuel cell vehicles (HFCVs), both producing zero tailpipe emissions, are seen as promising alternatives. This paper examines the working, structural characteristics, and safety designs of EVs and HFCVs, comparing their carbon emissions, charging infrastructure, energy efficiency, and safety features. The analysis reveals that both EVs and HFCVs significantly reduce carbon emissions and enhance safety compared to traditional vehicles, with EVs showing greater emission reductions. Moreover, EVs are advancing more rapidly in terms of charging infrastructure compared to hydrogen energy vehicles. However, HFCVs exhibit lower energy efficiency than EVs. In terms of safety, both types surpass conventional vehicles, though EVs are more prone to overheating and fire hazards due to battery design issues. Current research suggests that EV technology and its supporting infrastructure are more comprehensive, cost-effective, and efficient in reducing carbon emissions. With continued investment in the development of new energy vehicles and potential advancements in hydrogen energy production, the future for HFCVs appears promising. The paper also expresses optimism for innovative solutions that could accelerate the growth of hydrogen energy vehicles.

Keywords: electric vehicles, fuel cell electric vehicles, automotive engineering, energy transition

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Authors: Fakhrosadat Sajjadian

Abstract:

The majority of deaths in cancer patients are caused by distant metastasis. Breast cancer shows a unique spread pattern, often affecting bone, liver, lung, and brain. Breast cancer can be categorized into various subtypes according to gene expression patterns, and these subtypes exhibit specific preferences for organs where metastasis occurs. Breast tumors with luminal characteristics have a preference for spreading to the bone, whereas basal-like breast cancer (BLBC) shows a tendency to metastasize to the lungs. Still, the mechanisms behind this particular pattern of metastasis in organs have yet to be fully understood. In this evaluation, we will outline the latest progress in molecular signaling pathways and treatment methods for breast cancer lung metastasis.

Keywords: lung cancer, liver cancer, diagnosis, BLBC, metastasis

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Authors: Saeedeh Shahbazkhany

Abstract:

Cancer is a terrible disease that, if not diagnosed early, therapy can be difficult while it is easily medicable if it is diagnosed in early stages. So it is very important for cancer diagnosis that medical procedures are performed. In this paper we introduce a new method. In this method, we only need pictures of healthy cells and cancer cells. In fact, where we suspect cancer, we take a picture of cells or tissue in that area, and then take some pictures of the surrounding tissues. Then, fractal dimension of images are calculated and compared. Cancer can be easily detected by comparing the fractal dimension of images. In this method, we use Matlab software.

Keywords: Matlab software, fractal dimension, cancer, surrounding tissues, cells or tissue, new method

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Authors: Nasim Hashemi, Abbas Sheikhtaheri

Abstract:

Telemedicine is the use of telecommunication and information technologies to provide health care services that would often not be consistently available in distant rural communities to people at these remote areas. Teleophthalmology is a branch of telemedicine that delivers eye care through digital medical equipment and telecommunications technology. Thus, teleophthalmology can overcome geographical barriers and improve quality, access, and affordability of eye health care services. Since teleophthalmology has been widespread applied in recent years, the aim of this study was to determine the different applications of teleophthalmology in the world. To this end, three bibliographic databases (Medline, ScienceDirect, Scopus) were comprehensively searched with these keywords: eye care, eye health care, primary eye care, diagnosis, detection, and screening of different eye diseases in conjunction with telemedicine, telehealth, teleophthalmology, e-services, and information technology. All types of papers were included in the study with no time restriction. We conducted the search strategies until 2015. Finally 70 articles were surveyed. We classified the results based on the’type of eye problems covered’ and ‘the type of telemedicine services’. Based on the review, from the ‘perspective of health care levels’, there are three level for eye health care as primary, secondary and tertiary eye care. From the ‘perspective of eye care services’, the main application of teleophthalmology in primary eye care was related to the diagnosis of different eye diseases such as diabetic retinopathy, macular edema, strabismus and aged related macular degeneration. The main application of teleophthalmology in secondary and tertiary eye care was related to the screening of eye problems i.e. diabetic retinopathy, astigmatism, glaucoma screening. Teleconsultation between health care providers and ophthalmologists and also education and training sessions for patients were other types of teleophthalmology in world. Real time, store–forward and hybrid methods were the main forms of the communication from the perspective of ‘teleophthalmology mode’ which is used based on IT infrastructure between sending and receiving centers. In aspect of specialists, early detection of serious aged-related ophthalmic disease in population, screening of eye disease processes, consultation in an emergency cases and comprehensive eye examination were the most important benefits of teleophthalmology. Cost-effectiveness of teleophthalmology projects resulted from reducing transportation and accommodation cost, access to affordable eye care services and receiving specialist opinions were also the main advantages of teleophthalmology for patients. Teleophthalmology brings valuable secondary and tertiary care to remote areas. So, applying teleophthalmology for detection, treatment and screening purposes and expanding its use in new applications such as eye surgery will be a key tool to promote public health and integrating eye care to primary health care.

Keywords: applications, telehealth, telemedicine, teleophthalmology

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Authors: Ji Su Kim, Bo Ram Choi, Ju Yeon Cho, Hyukjin Lee

Abstract:

Epidermal growth factor receptor (EGFR) 19 deletion mutation gene is over-expressed in carcinoma patient. EGFR 19 deletion mutation is known as typical biomarker of non-small cell lung cancer (NSCLC), which one section in the coding exon 19 of EGFR is deleted. Therefore, there have been many attempts over the years to detect EGFR 19 deletion mutation for replacing conventional diagnostic method such as PCR and tissue biopsy. We developed a simple and facile detection platform based on Rolling Circle Amplification (RCA), which provides highly amplified products in isothermal amplification of the ligated DNA template. Limit of detection (~50 nM) and a faster detection time (~30 min) could be achieved by introducing RCA.

Keywords: EGFR19, cancer, diagnosis, rolling circle amplification (RCA), hydrogel

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Authors: Tarek Aly

Abstract:

The shoulder is the most mobile joint whose stability requires the interaction of both dynamic and static stabilizers. Its wide range of movement predisposes to a high susceptibility to dislocation, accounting for nearly 50% of all dislocations. This trauma typically results in ligament injury (e.g., labral tear, capsular strain) or bony fracture (e.g., loss of glenoid or humeral head bone), which frequently causes recurrent instability. Patients with significant glenoid defects may require Latarjet procedure, which involves transferring the coracoid to the antero-inferior glenoid rim. In spite of outstanding results, 15 to 30% of cases suffer complications. In this article, we discuss the diagnosis of recurrent shoulder instability, the surgical technique and various complications of Latarjet procedure.

Keywords: recurrent, anterior gleno-humeral instability, latarjet, unstable shoulder

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Authors: Judith Partouche-Sebban, Saeedeh Rezaee Vessal

Abstract:

Because of the rising number of new cases of cancer, especially among women, it is more than essential to better understand how women experience cancer in order to bring them adapted to support and care and enhance their well-being and patient experience. Cancer stands for a traumatic experience in which the diagnosis, its medical treatments, and the related side effects lead to deep physical and psychological changes that may arouse considerable stress and anxiety. In order to reduce these negative emotions, women tend to use various defense mechanisms, among which denial has been defined as the most frequent mechanism used by breast cancer patients. This study aims to better understand the consequences of the experience of cancer and their link with the adoption of a denial strategy. The empirical research was done among female cancer survivors in France. Since the topic of this study is relatively unexplored, a qualitative methodology and open-ended interviews were employed. In total, 25 semi-directive interviews were conducted with a female with different cancers, different stages of treatment, and different ages. A systematic inductive method was performed to analyze data. The content analysis enabled to highlight three different denial-related behaviors among women with cancer, which serve a self-protective function. First, women who expressed high levels of anxiety confessed they tended to completely deny the existence of their cancer immediately after the diagnosis of their illness. These women mainly exhibit many fears and a deep distrust toward the medical context and professionals. This coping mechanism is defined by the patient as being unconscious. Second, other women deliberately decided to deny partial information about their cancer, whether this information is related to the stages of the illness, the emotional consequences, or the behavioral consequences of the illness. These women use this strategy as a way to avoid the reality of the illness and its impact on the different aspects of their life as if cancer does not exist. Third, some women tend to reinterpret and give meaning to their cancer as a way to reduce its impact on their life. To this end, they may use magical thinking or positive reframing, or reinterpretation. Because denial may lead to delays in medical treatments, this topic deserves a deep investigation, especially in the context of oncology. As denial is defined as a specific defense mechanism, this study contributes to the existing literature in service marketing which focuses on emotions and emotional regulation in healthcare services which is a crucial issue. Moreover, this study has several managerial implications for healthcare professionals who interact with patients in order to implement better care and support for the patients.

Keywords: cancer, coping mechanisms, denial, healthcare services

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Authors: Brenda Thean I. Lim, Safurah Jaafar

Abstract:

Augmented reality (AR) in the healthcare industry has been gaining popularity in recent years, principally in areas of medical education, patient care and digital health solutions. One of the drivers in deciding to invest in AR technology is the potential economic benefits it could bring for patients and healthcare providers, including the pharmaceutical and medical technology sectors. Works of literature have shown that the benefits and impact of AR technologies have left trails of achievements in improving medical education and patient health outcomes. However, little has been published on the economic impact of AR in healthcare, a very resource-intensive industry. This systematic review was performed on studies focused on the benefits and impact of AR in healthcare to appraise if they meet the founded quality criteria so as to identify relevant publications for an in-depth analysis of the economic impact assessment. The literature search was conducted using multiple databases such as PubMed, Cochrane, Science Direct and Nature. Inclusion criteria include research papers on AR implementation in healthcare, from education to diagnosis and treatment. Only papers written in English language were selected. Studies on AR prototypes were excluded. Although there were many articles that have addressed the benefits of AR in the healthcare industry in the area of medical education, treatment and diagnosis and dental medicine, there were very few publications that identified the specific economic impact of technology within the healthcare industry. There were 13 publications included in the analysis based on the inclusion criteria. Out of the 13 studies, none comprised a systematically comprehensive cost impact evaluation. An outline of the cost-effectiveness and cost-benefit framework was made based on an AR article from another industry as a reference. This systematic review found that while the advancements of AR technology is growing rapidly and industries are starting to adopt them into respective sectors, the technology and its advancements in healthcare were still in their early stages. There are still plenty of room for further advancements and integration of AR into different sectors within the healthcare industry. Future studies will require more comprehensive economic analyses and costing evaluations to enable economic decisions for or against implementing AR technology in healthcare. This systematic review concluded that the current literature lacked detailed examination and conduct of economic impact and benefit analyses. Recommendations for future research would be to include details of the initial investment and operational costs for the AR infrastructure in healthcare settings while comparing the intervention to its conventional counterparts or alternatives so as to provide a comprehensive comparison on impact, benefit and cost differences.

Keywords: augmented reality, benefit, economic impact, healthcare, patient care

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Authors: Ons Sassi, Wahiba Ramdane Cherif-Khettaf, Ammar Oulamara

Abstract:

In this paper, we consider a new real-life Heterogenous Electric Vehicle Routing Problem with Time Dependant Charging Costs and a Mixed Fleet (HEVRP-TDMF), in which a set of geographically scattered customers have to be served by a mixed fleet of vehicles composed of a heterogenous fleet of Electric Vehicles (EVs), having different battery capacities and operating costs, and Conventional Vehicles (CVs). We include the possibility of charging EVs in the available charging stations during the routes in order to serve all customers. Each charging station offers charging service with a known technology of chargers and time-dependent charging costs. Charging stations are also subject to operating time windows constraints. EVs are not necessarily compatible with all available charging technologies and a partial charging is allowed. Intermittent charging at the depot is also allowed provided that constraints related to the electricity grid are satisfied. The objective is to minimize the number of employed vehicles and then minimize the total travel and charging costs. In this study, we present a Mixed Integer Programming Model and develop a Charging Routing Heuristic and a Local Search Heuristic based on the Inject-Eject routine with three different insertion strategies. All heuristics are tested on real data instances.

Keywords: charging problem, electric vehicle, heuristics, local search, optimization, routing problem

Procedia PDF Downloads 460